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zgEv4ub7AQ}?Rv-td}`f~jCgIP+X1clDW<_`6SiAYS7|pdh|~Fh-f*HRr}UiWMCA>1dT)qp2Y{L;X)2Ffki0b`~jXa?LH zP+=VaiXkz!?nG7QFQs_Yyr7VPRepb~F;3(7AdL(nA0Hp1{n?tw?Fs(FE&PFXvQ(GF z6}i9`jK2a*5MscT+S`{%zlWQZqaJD!?K(Rmz##Z;2*=Q27v0+nzlRG8wdK6~M}!I% zr#%|vf`3KB#EqvaR{iNbXj?Z=f6#h!F#4eHzKm{|T5!2=(aP{h7mwB8u#*Pf0_J;1 zrpBKSNUp~!a`=ANV_ARC_vg9*clrzXIIGPZF+iadQOxP%^KOf5z`S|udVpY>EYs%z zTDHrvOuYn_6=e-3UA%KGa3SaLaRv8Cy`X~oxX~5FpIzam2agrIG?M$oyKurR0@=Bt% z9q3UctPdnb{QSv$v=*ljo+0EGzIeOAM@JkH*7k7I#zC1o>wKC)f;N|PD$)Z<zAgecK8>^&VVFmxATj{z)#%Lz#6ZkE&z7ikcM6>6=!iY zti3z}3L3_^e(%ov?rr}97dO1^rm2na`-k`LEqX@*c;2EE{0;`w$e9}Jr26~o-7h_> z1QnXH-pknf_zgM-6jNq4g6HXZvnPX(b@z;Bt1bWRyG8&Y9^rR4C@Vwis2dM%?e7ykdi3MH*4jo~ zUwa-UlzE$K3NlR; pl.DataFrame:\n", + " cf_cols = [SOURCE_TYPE, CAPACITY, CAPACITY_FACTOR, ACTIVITY, CO2_EMISSIONS_FACTOR,\n", + " CH4_EMISSIONS_FACTOR, N2O_EMISSIONS_FACTOR, CO2_EMISSIONS, CH4_EMISSIONS, \n", + " N2O_EMISSIONS, TOTAL_CO2E_20YRGWP, TOTAL_CO2E_100YRGWP]\n", + " return (df.with_columns(\n", + " c_iso3_country.cast(ct.iso3_enum).alias(ISO3_COUNTRY),\n", + " c_gas.cast(ct.gas_enum, strict=False).alias(GAS),\n", + " # TODO: change eventually to enum\n", + " c_original_inventory_sector.cast(pl.String).alias(ORIGINAL_INVENTORY_SECTOR),\n", + " c_temporal_granularity.cast(ct.temporal_granularity_enum).alias(TEMPORAL_GRANULARITY),\n", + " ).with_columns(\n", + " *[C(\"conf_\" + col_name).cast(pl.Categorical, strict=False).alias(\"conf_\" + col_name) for col_name in cf_cols]\n", + " ))\n", + "\n", + "def _load_sources(fp) -> pl.DataFrame:\n", + " dates = [\n", + " START_TIME, END_TIME, CREATED_DATE, MODIFIED_DATE\n", + " ]\n", + " uint64s = [SOURCE_ID]\n", + " floats = [EMISSIONS_QUANTITY, EMISSIONS_FACTOR, CAPACITY, CAPACITY_FACTOR, ACTIVITY, LAT, LON]\n", + " enums = {\n", + " ISO3_COUNTRY:ct.iso3_enum, \n", + " GAS:ct.gas_enum, \n", + " TEMPORAL_GRANULARITY:ct.temporal_granularity_enum,\n", + " # TODO: activate once the whole list is gathered\n", + " # ORIGINAL_INVENTORY_SECTOR:ct.inventory_sector_enum\n", + " }\n", + " # TODO: make it lazy\n", + " df = pl.read_csv(fp.read(), infer_schema_length=0) #.lazy()\n", + " num_other = 12\n", + " check_cols = [ACTIVITY, ACTIVITY_UNITS, EMISSIONS_FACTOR, EMISSIONS_FACTOR_UNITS, \n", + " CAPACITY_UNITS, CAPACITY, CAPACITY_FACTOR, GEOMETRY_REF, LAT, LON, ORIGINAL_INVENTORY_SECTOR] + [f\"other{i}\" for i in range(1,num_other+1)] + [f\"other{i}_def\" for i in range(1,num_other+1)]\n", + " for col_name in check_cols:\n", + " if col_name not in df.columns:\n", + " df = df.with_columns(pl.lit(None).cast(pl.String, strict=False).alias(col_name))\n", + " # Check that the columns match exactly\n", + " s1 = set(df.columns)\n", + " s2 = set(all_columns)\n", + " assert s1 == s2, (s1-s2, s2-s1, list(zip(sorted(df.columns), sorted(all_columns))))\n", + " df = df.select(*all_columns)\n", + " return (df.with_columns(\n", + " # Only start_time and end_time are required\n", + " *[C(col_name).str.to_datetime(strict=(col_name in {START_TIME, END_TIME})).alias(col_name) for col_name in dates])\n", + " .with_columns(\n", + " c_iso3_country.cast(ct.iso3_enum).alias(ISO3_COUNTRY),\n", + " c_gas.cast(ct.gas_enum).alias(GAS),\n", + " c_temporal_granularity.cast(ct.temporal_granularity_enum).alias(\"temporal_granularity\"),\n", + " # TODO: change eventually to enum\n", + " # c_original_inventory_sector.cast(pl.Categorical).alias(ORIGINAL_INVENTORY_SECTOR)\n", + " ).with_columns(*[C(col_name).cast(pl.Float64, strict=False).alias(col_name) for col_name in floats])\n", + " .with_columns(*[C(col_name).cast(pl.UInt64).alias(col_name) for col_name in uint64s])\n", + " # This is for debugging the memory consumption, remove eventually\n", + " .limit(1_000_000_000)\n", + " )\n", + "\n", + "def _load_source_confidence(fp) -> pl.DataFrame:\n", + " dates = [\n", + " START_TIME, END_TIME, CREATED_DATE, MODIFIED_DATE\n", + " ]\n", + " cf_cols = [SOURCE_TYPE, CAPACITY, CAPACITY_FACTOR, ACTIVITY, CO2_EMISSIONS_FACTOR,\n", + " CH4_EMISSIONS_FACTOR, N2O_EMISSIONS_FACTOR, CO2_EMISSIONS, CH4_EMISSIONS, \n", + " N2O_EMISSIONS, TOTAL_CO2E_20YRGWP, TOTAL_CO2E_100YRGWP]\n", + " uint64s = [SOURCE_ID]\n", + " # TODO: make it lazy\n", + " df = pl.read_csv(fp.read(), infer_schema_length=0) #.lazy()\n", + " sels = ([C(col_name).str.to_datetime(strict=(col_name in {START_TIME, END_TIME})).alias(col_name) for col_name in dates]\n", + " + [c_iso3_country.cast(ct.iso3_enum).alias(ISO3_COUNTRY), c_source_id.cast(pl.UInt64).alias(SOURCE_ID)]\n", + " + [C(col_name).cast(pl.Categorical, strict=False).alias(\"conf_\"+col_name) for col_name in cf_cols]\n", + " )\n", + " df = df.select(*sels)\n", + " # For debugging\n", + " return df #.limit(1_000)\n", + "\n", + "def _load_source_conf(s_fp, c_fp) -> pl.DataFrame:\n", + " s_df = _load_sources(s_fp)\n", + " c_df = _load_source_confidence(c_fp)\n", + " return (s_df.join(c_df.drop([\"created_date\", \"modified_date\"]),\n", + " on=[\"start_time\", \"end_time\", \"iso3_country\", \"source_id\"], \n", + " how=\"left\")\n", + " )\n", + "\n", + "def read_all_sources(p: Path) -> pl.DataFrame:\n", + " res_df = None\n", + " # dfs = []\n", + " # TODO: replace by a proper temp directory\n", + " tmp_dir = Path(tempfile.gettempdir())\n", + " data_files = []\n", + " for fname in _files:\n", + " _logger.debug(f\"open {fname}\")\n", + " zf = ZipFile(Path(ct_data_source) / fname)\n", + " source_names = [n for n in zf.namelist() if n.endswith(\"-sources.csv\")]\n", + " _logger.debug(f\"sources: {source_names}\")\n", + " for sname in source_names:\n", + " _logger.debug(f\"opening {fname} / {sname}\")\n", + " c_name = sname.replace(\"_emissions-sources.csv\", \"_emissions-sources_confidence.csv\")\n", + " _logger.debug(f\"opening {fname} / {c_name}\")\n", + " df = _load_source_conf(zf.open(sname), zf.open(c_name))\n", + " df = (df.with_columns(\n", + " pl.lit(fname.replace(\".zip\", \"\")).cast(pl.Categorical).alias(\"ct_package\"),\n", + " pl.lit(sname.replace(\"_emissions-sources.csv\", \"\")).cast(pl.Categorical).alias(\"ct_file\")))\n", + " tmp_name = tmp_dir / sname.replace(\".csv\",\".parquet\")\n", + " df.write_parquet(tmp_name)\n", + " data_files.append(tmp_name)\n", + " _logger.debug(f\"wrote {tmp_name}\")\n", + " dfs = []\n", + " for tmp_name in data_files:\n", + " _logger.debug(f\"scan {tmp_name}\")\n", + " df = pl.scan_parquet(tmp_name)\n", + " df = df.pipe(_recast_parquet)\n", + " dfs.append(df)\n", + " res_df = pl.concat(dfs)\n", + " return res_df\n", + "\n", + "def _load_country_emissions(fp) -> pl.DataFrame:\n", + " dates = [\n", + " START_TIME, END_TIME, CREATED_DATE, MODIFIED_DATE\n", + " ]\n", + " floats = [EMISSIONS_QUANTITY]\n", + " enums = {\n", + " ISO3_COUNTRY:ct.iso3_enum, \n", + " GAS:ct.gas_enum, \n", + " TEMPORAL_GRANULARITY:ct.temporal_granularity_enum,\n", + " # TODO: activate once the whole list is gathered\n", + " # ORIGINAL_INVENTORY_SECTOR:ct.inventory_sector_enum\n", + " }\n", + " df = pl.read_csv(fp.read(), infer_schema_length=0)\n", + " all_columns = ['iso3_country',\n", + " 'start_time',\n", + " 'end_time',\n", + " 'original_inventory_sector',\n", + " 'gas',\n", + " 'emissions_quantity',\n", + " 'emissions_quantity_units',\n", + " 'temporal_granularity',\n", + " 'created_date',\n", + " 'modified_date']\n", + " # Check that the columns match exactly\n", + " s1 = set(df.columns)\n", + " s2 = set(all_columns)\n", + " assert s1 == s2, (s1-s2, s2-s1, list(zip(sorted(df.columns), sorted(all_columns))))\n", + " df = df.select(*all_columns)\n", + " return (df.with_columns(\n", + " # Only start_time and end_time are required\n", + " *[C(col_name).str.to_datetime(format=\"%Y-%m-%d %H:%M:%S%.f\",\n", + " strict=(col_name in {START_TIME, END_TIME})).alias(col_name) for col_name in dates])\n", + " .with_columns(\n", + " c_iso3_country.cast(ct.iso3_enum).alias(ISO3_COUNTRY),\n", + " c_gas.cast(ct.gas_enum, strict=False).alias(GAS),\n", + " # TODO: causing issues\n", + " # c_original_inventory_sector.cast(pl.Categorical).alias(ORIGINAL_INVENTORY_SECTOR),\n", + " c_temporal_granularity.cast(ct.temporal_granularity_enum).alias(TEMPORAL_GRANULARITY)\n", + " ).with_columns(*[C(col_name).cast(pl.Float64, strict=False).alias(col_name) for col_name in floats])\n", + " )\n", + "\n", + "\n", + "def read_country_emissions(p: Path) -> pl.DataFrame:\n", + " # TODO: add meta info about the provenance: ct_package and ct_file\n", + " # So fast there is no need to store a materialized version.\n", + " dfs = []\n", + " for fname in _files:\n", + " _logger.debug(f\"open {fname}\")\n", + " zf = ZipFile(Path(ct_data_source) / fname)\n", + " source_names = [n for n in zf.namelist() if n.endswith(\"_country_emissions.csv\")]\n", + " _logger.debug(f\"sources: {source_names}\")\n", + " for sname in source_names:\n", + " _logger.debug(f\"opening {fname} / {sname}\")\n", + " df = _load_country_emissions(zf.open(sname))\n", + " df = (df.with_columns(\n", + " pl.lit(fname.replace(\".zip\", \"\")).cast(pl.Categorical).alias(CT_PACKAGE),\n", + " pl.lit(sname.replace(\"_country_emissions.csv\", \"\")).cast(pl.Categorical).alias(CT_FILE)))\n", + " dfs.append(df)\n", + " res_df = pl.concat(dfs)\n", + " return res_df\n", + " \n", + "\n", + "ct_data_source = \"/home/tjhunter/Downloads/\"\n", + "cedf = read_country_emissions(Path(ct_data_source))\n", + "\n", + "if False:\n", + " df = read_all_sources(Path(ct_data_source))\n", + " # Using snappy because it is more broadly compatible with parquet readers\n", + " # Polars 0.20 does not support statistics\n", + " for year in range(2015, 2023):\n", + " df.filter(c_start_time.dt.year()==year).sink_parquet(\n", + " f\"/home/tjhunter/Downloads/ct_data_{year}.parquet\",\n", + " compression=\"snappy\",\n", + " statistics=False\n", + " )\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": 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iso3_countrystart_timeend_timeoriginal_inventory_sectorgasemissions_quantityemissions_quantity_unitstemporal_granularitycreated_datemodified_datect_packagect_file
enumdatetime[ns]datetime[ns]strenumf64strenumdatetime[ns]datetime[ns]catcat
"AUT"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"n2o"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"AZE"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"co2"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"ABW"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"co2"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"ABW"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"n2o"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"ABW"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"ch4"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"ABW"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"co2e_20yr"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"ABW"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"co2e_100yr"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"AFG"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"co2"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"AFG"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"n2o"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"AGO"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"co2"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"AGO"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"n2o"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
"AIA"2022-01-01 00:00:002022-12-31 00:00:00"enteric-fermen…"co2"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""enteric-fermen…
………………………………
"URY"2018-01-01 00:00:002018-12-31 00:00:00"wastewater-tre…"co2e_100yr"5.1538e6"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:14.435384"waste""wastewater-tre…
"XKX"2018-01-01 00:00:002018-12-31 00:00:00"wastewater-tre…"co2e_20yr"0.0"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:14.748780"waste""wastewater-tre…
"TUV"2017-01-01 00:00:002017-12-31 00:00:00"wastewater-tre…"co2e_20yr"7437.522372"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:21.046751"waste""wastewater-tre…
"TUV"2017-01-01 00:00:002017-12-31 00:00:00"wastewater-tre…"co2e_100yr"2543.390255"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:21.046751"waste""wastewater-tre…
"UGA"2017-01-01 00:00:002017-12-31 00:00:00"wastewater-tre…"co2e_20yr"1.7555e7"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:21.046751"waste""wastewater-tre…
"URY"2017-01-01 00:00:002017-12-31 00:00:00"wastewater-tre…"co2e_20yr"1.5896e7"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:21.360708"waste""wastewater-tre…
"TUV"2016-01-01 00:00:002016-12-31 00:00:00"wastewater-tre…"co2e_20yr"7356.396048"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:27.777139"waste""wastewater-tre…
"TUV"2016-01-01 00:00:002016-12-31 00:00:00"wastewater-tre…"co2e_100yr"2516.497358"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:27.777139"waste""wastewater-tre…
"UGA"2016-01-01 00:00:002016-12-31 00:00:00"wastewater-tre…"co2e_20yr"1.6999e7"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:28.159334"waste""wastewater-tre…
"UGA"2015-01-01 00:00:002015-12-31 00:00:00"wastewater-tre…"co2e_20yr"1.6456e7"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:34.328448"waste""wastewater-tre…
"ZWE"2015-01-01 00:00:002015-12-31 00:00:00"wastewater-tre…"co2e_20yr"6.1586e6"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:34.624499"waste""wastewater-tre…
"ZWE"2015-01-01 00:00:002015-12-31 00:00:00"wastewater-tre…"co2e_100yr"2.1487e6"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:34.624499"waste""wastewater-tre…
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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "px.bar(cedf_gy\n", + " .filter(c_emissions_quantity > 0)\n", + " .group_by(c_iso3_country)\n", + " .agg(c_emissions_quantity.sum())\n", + " .sort([c_emissions_quantity], descending=True)\n", + " .head(20)\n", + ",x=ISO3_COUNTRY, y=EMISSIONS_QUANTITY,log_y=True)\n", + "\n", + "# Mozambique emits more than Germany??" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "95b7897e-a998-424e-b4f1-ba182166c323", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=electricity-generation
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "electricity-generation", + "marker": { + "color": "#636efa", + "pattern": { + "shape": "" + } + }, + "name": "electricity-generation", + "offsetgroup": "electricity-generation", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "USA", + "IND", + "RUS", + "FRA", + "NLD" + ], + "xaxis": "x", + "y": [ + 4677936000, + 1495505000, + 1248621000, + 559267000, + 34645000, + 32668000 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=other-manufacturing
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "other-manufacturing", + "marker": { + "color": "#EF553B", + "pattern": { + "shape": "" + } + }, + "name": "other-manufacturing", + "offsetgroup": "other-manufacturing", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "USA", + "IND", + "RUS", + "FRA", + "NLD" + ], + "xaxis": "x", + "y": [ + 1490127951.9888403, + 424128723.606085, + 221799277.27273008, + 215670149.28375, + 19073449.246585, + 12193871.512025 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=road-transportation
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "road-transportation", + "marker": { + "color": "#00cc96", + "pattern": { + "shape": "" + } + }, + "name": "road-transportation", + "offsetgroup": "road-transportation", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "USA", + "CHN", + "IND", + "RUS", + "FRA", + "NLD" + ], + "xaxis": "x", + "y": [ + 1450640857.8154, + 745990158.70195, + 285635833.36465997, + 160241992.09235498, + 111643269.31693998, + 26668255.568942 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=oil-and-gas-production-and-transport
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "oil-and-gas-production-and-transport", + "marker": { + "color": "#ab63fa", + "pattern": { + "shape": "" + } + }, + "name": "oil-and-gas-production-and-transport", + "offsetgroup": "oil-and-gas-production-and-transport", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "RUS", + "USA", + "CHN", + "IND", + "NLD", + "FRA" + ], + "xaxis": "x", + "y": [ + 1361334668.3591173, + 1102325980.735412, + 230845790.5803214, + 35193116.42119852, + 7929394.684596755, + 319728.97873531544 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=steel
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "steel", + "marker": { + "color": "#FFA15A", + "pattern": { + "shape": "" + } + }, + "name": "steel", + "offsetgroup": "steel", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "IND", + "RUS", + "USA", + "FRA", + "NLD" + ], + "xaxis": "x", + "y": [ + 1287028706, + 237189869, + 74936012, + 43316553, + 16827194, + 10432281 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=other-energy-use
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "other-energy-use", + "marker": { + "color": "#19d3f3", + "pattern": { + "shape": "" + } + }, + "name": "other-energy-use", + "offsetgroup": "other-energy-use", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "RUS", + "USA", + "FRA", + "IND", + "NLD" + ], + "xaxis": "x", + "y": [ + 1255404004.0149999, + 306808312.84871, + 130664512.07946001, + 15406295.133308996, + 13901667.78145, + 9406471.065440003 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=cement
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "cement", + "marker": { + "color": "#FF6692", + "pattern": { + "shape": "" + } + }, + "name": "cement", + "offsetgroup": "cement", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "IND", + "USA", + "RUS", + "FRA", + "NLD" + ], + "xaxis": "x", + "y": [ + 1167218721, + 258232689, + 59129760, + 23338140, + 9263124, + 0 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=coal-mining
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "coal-mining", + "marker": { + "color": "#B6E880", + "pattern": { + "shape": "" + } + }, + "name": "coal-mining", + "offsetgroup": "coal-mining", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "USA", + "RUS", + "IND", + "NLD", + "FRA" + ], + "xaxis": "x", + "y": [ + 1012289909.122534, + 84713033.68341155, + 66960795.259558454, + 31741952.15149903, + 0, + 0 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=residential-and-commercial-onsite-fuel-usage
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "residential-and-commercial-onsite-fuel-usage", + "marker": { + "color": "#FF97FF", + "pattern": { + "shape": "" + } + }, + "name": "residential-and-commercial-onsite-fuel-usage", + "offsetgroup": "residential-and-commercial-onsite-fuel-usage", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "USA", + "RUS", + "IND", + "FRA", + "NLD" + ], + "xaxis": "x", + "y": [ + 628529048.57945, + 589216241.15025, + 225186460.52688, + 178479101.17412, + 70222126.36766699, + 22293411.702589 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=fluorinated-gases
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "fluorinated-gases", + "marker": { + "color": "#FECB52", + "pattern": { + "shape": "" + } + }, + "name": "fluorinated-gases", + "offsetgroup": "fluorinated-gases", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "USA", + "IND", + "RUS", + "NLD", + "FRA" + ], + "xaxis": "x", + "y": [ + 441347044.25357795, + 187861829.38009, + 62042966.16935601, + 44208771.49510093, + 18462256.959119, + 12006695.469621003 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=forest-land-clearing
iso3_country=%{x}
emissions_quantity=%{y}", + "legendgroup": "forest-land-clearing", + "marker": { + "color": "#636efa", + "pattern": { + "shape": "" + } + }, + "name": "forest-land-clearing", + "offsetgroup": "forest-land-clearing", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "USA", + "RUS", + "CHN", + "IND", + "FRA", + "NLD" + ], + "xaxis": "x", + "y": [ + 395253295.8984375, + 369410552.9785156, + 226329803.4667969, + 41901696.767657995, + 15439952.8503418, + 312207.2219848633 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "original_inventory_sector=solid-fuel-transformation
iso3_country=%{x}
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", 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i32catcatu32
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2022"forestry_and_l…"wetland-fires"32730
2022"forestry_and_l…"net-shrubgrass…248045
2022"forestry_and_l…"removals"250620
2022"forestry_and_l…"shrubgrass-fir…93935
2022"forestry_and_l…"forest-land-cl…211315
2022"forestry_and_l…"net-wetland"213760
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b13dRobyeGI4/H4+gYWP02y1cyE31aiSiROFhdPWfSBo2zuOsqVMQ5aZrB6J0j3tI6epNEbTiC/2227Vw04s5PGP+/tAtdZjQH3PNai5lluUZ8x9nI2jQsDBHTrGd24ZTsqThdEvN1bTZEbTvgH7bPTq7KctTnn5v23WL5izQl23a0EUFXvb0+8dfImjEOH28XivqplpVPHN18YpLzbNLj9CrJlKq6DhdO4ZT2jSevp79K5LUK6JdHkoeRo+k9MhevBJJ/6mISLolSaIwSpNaHyPd50o9QUAQEAQEgZhHIHGi+LN/x8XzVUgJfZ6yLWjVpwMpg7JPjwvFl9B/PHoupU/76B0N/bkLVKF+d9q3YSpZ/QYNPZJmIQQnIt1ULV8kangS5UZvpiXKjbpNiYdRbnBzNHlqIj1Cr5YCNPStW7ooxUMek5udu8Jp41f6m3SzhpGUUeUcQDlx0llY1YrlIinXix5ZhEa9cEE/7EtSpRh69HaYT8hHOMhVgPqJEkmYT72dQGoJAoKAIOAfATG54a2MkBL69j1HKW1mHqpWoSivV2ZpxjHIl9DPXbJRadlPUv/uzYwWtqlQm8MnLaQl0/qT1W8g9D8f/4Oa1alILboNoUWT+0UdWoTQ6021EPqESei37wyndRv0CX2r5ncI/a/Hw2jmbH1ToTer3SH0l5QD84jRibSzKGd72k2N6t+JR7puYzidUCFOdUvNGpFRcf91ZaSeICAICAKCwB0EhNDzVkNICf0Xm76hASM+peKvvkzZsmSkZA8kjdY7RJO5l8WX0J+/cJmqNu1NU4d1oyfTP06d3h9D+XPnoFYNXyer38xOseNnLqPd+47SDBUpBzbGQuj1ZlQIvRB6nZUSVwg9Eq4h8Zpu6dwhQgi9LlhSTxAQBAQBPwgIoecti5AS+urKwdSqQBN+L4svoUfbqzbspGGTFtA/1/+lkkXyUP9uzaKSYQX6zUzoIyIjqV7b/lSxZEFqUru8EHrNCRVCL4ReZ6ncD4Te7dY/CHgwgQOyDjpSRxAQBASB+xcBIfS8uQ0poed1JX5Ki4Zeb96E0Mc0oY8ecztUmWK5NvTx1eSGo6H/9TjRV1v0TYVeK+IimPyg/Pev8h34Xe+dQi1kEk7zqKm+04OBRBfVB/ue1dT3/bhnXZKGBIF7gIAQeh7IQuh5+ImGXhM/IfQxTegxEXdIvRB6ng09h9AfOhxGCxfrE3rY7nsJ/ZkzpMKEeiIb6ZRSJVz0WlFPGKEbN8JorfJXuHZNj9WnUBGJypdxEXIHSBEEBAFBILYREELPm4GQEvrcZd6y7A2iydxvRTT0ejMqhP5eEPo7cyGEPmES+klTw+nCRT1C/2hqN7V66w6hRxjZ02f0ZLHSMv3PbdwQeEoYuR2EJ3WHuUlFRZUiCAgCgkAUAkLoeYshpIR+5x6VqchU/rt5i3774yzNU9Fl2jerRm+ULczrbRyUFkKvNylC6IXQ66yU+8GGPjY19BxC//XWcNrkIMRomxYRlD69Z1b/OEW0dr3+rUTB/C56IafnZsCl/nPzlgN2rzLqPaDCjHolHEga7cl9hM6bKHUEgXuPgBB6HuYhJfSBunL85BnqPXgazR3Xm9fbOCgthF5vUoTQC6HXWSlC6HkmN7FF6I/9EkafztUn9LVUmE8vob98RcnO0ZfNksWlsk7fuQ74+ecwwjN0Csj8c9ldKpO5p3ZkBDJu68kaAupmIbG+RZROl6SOICAI3EZACD1vKdwTQo8uFqnSgbYtH8PrbRyUFkKvNylC6IXQ66wUIfQJj9BfvEg0Yow+S87xnJvq1rqTMwAHCRwodAqiCb3dQeUMeMSjp//pWBht/FL/MFG+TCRlzeKRDSYykbpciCpO5c2yOmOVOoJAfENACD1vxu4Jod+8Yx99NHoObZg/lNfbOCgthF5vUoTQC6HXWSlC6GOa0N+JoOJrQ88xueFo6GOT0B84GEaLluoT+iYqk7GX0CN5GTIh6xbcDGTJ5GH015UD8+5vw+jGv3oHkRQPuim/MlPypna5rNq+fEXfeAiRkB56SLenUk8QiB0EhNDzcA8poS9fr/tdvbmh4t5duHSF3n+nMdWsXJzX21iSNseh9+2CEHq9SRFCL4ReZ6UIoY9pQn9nFoTQE3EI/alTYTRpmv5hoJyKKFS4kMdU6No/YTRxcjhduapH6B9L46aWKotysmSe+duwKZy2btc/TLRtGUHp0um8gVJHEIg9BITQ87APKaFftOrru3rz0IPJ6PlnM1OmJ5/g9TSE0pPnrKTR05bQvo1TKXGiOxvysrXb1L8vpqvXblD5Evmpb5fGxu9C6D3g168TSdmf9WiFzp0jGjtR/5pcCL0Qep1XWAi9EHq7dRJKkxsh9HZoy++CwL1DQAg9D+uQEnpeV2Je+qaKuvPux1MoUaIwWr1pF+3fNC2K0J889SfVaf0hTR/RgzKme4w69RlDpYrmpfrVSwuhvz01QujDaNTYRBRxx3zXctEirF/TRpEUrhRpOAYtWRpO+w/qa9U6tYuICgt45EgYzV+krw2UsJUSttJuRxUNfcLU0F+/TnRGhSjVLXAgTptWt7bUEwSCR0AIffDYQTLkhP7Pvy7S4tVb6Odff6ckKhzA05kzUu03StAjqW6HFeD1lyXtUvHRlq/bRpXLvEq5SzePRuhnzF9Dv5w4TQN6NDfa2LrrII2dvoQWTOobjdD/fvocNe08mIb1bUsvPf+0JJbSnBHR0Auh11kqoqEXDb3dOhENPc/k5mflCDx7nr5yoM6bkfT8856b2Vu3iE6d1jMTQv0Uym7/scf0bf3t5l5+v78REELPm9+QEvojP/1mkN30adPQC89lMXp28OivBJI/ZWg3evH2v/G6zJeOiIykl0pFJ/R9h86gzE+mo6Z1KhgNnPnzb6rWvA99s2p8FKFv27gqNWg/gDq+VYPKFMtn1BMber35EEIvhF5npQihF0Jvt06E0Mceof/7b6JR4/RNLV960UU1qjnIOGY3+fL7fY2AEHre9IaU0Dfq+DHlzpmN3mlVK1qvRk5ZRHsP/Eizx/Ti9TZE0v4IfY+PJlGeF56h2lVKGq1cuXadClVuSwc2Tacpc1cpx96rdPTYCSqtzHAa1SwX1ZOr12/R0Z9dNGm6vilF9aouKlrAU//cBReNGB1OyndYq2TM4Kb2LYmSPRBGuHH4bAnRnr36GpN32rvoqYyetvfsc9HcBfr9bljXRXlyeeqf+MNFI8fpy75a0E013iCVHTJMRXhw0RjlEIbMlDolhbrcebuti9Kk9rT35VYXrVyt33br5i7Kns1T/8iPLpoyU1/2TfUxKpz/9lydd9GQkeGOTG7atSB1UxVGkUpJNWe+i/Yd0G+7ayeXMv/y1P/2exfNW6gv27iBS72LnvrHT7po9AR92WJF3FSlkmeurl5zK1mi83/rrbGUD7upUzuiRx9RmUPVmNd/5VIJh/TbbtvSRc9k9dQ/9IOLps0KLAuaYP61Vg0XFXrF8y9n/3LRJ8PDjT7olGxPu6m1upxLpNKXRqr3atqnRD8c1Rsznt/tbRdluD1Xu/a4lHmU/pibNnRRrttz9etv6t2YqC9buqSLKpYJN0IoXr6q5mo8OcoU27ENUaqUnrlavcGlQjjqt92htYuyZvbUP3DYRTNm68vWedNFBfJ56p8+63mvdAsIffNGd+Zq4jRyFLayW2eXUjp52tv5rYsWLtZvu3ljlRArh6f+z7+6aLzax3RL+bIuKlvCM1cXLrkVMVbfGQdOsZirh1OofV9N1vIviLZs01+fHdsgwo6nr/sOuWjWHP1+16vlolfyeOqfOuOioaP0ZXPnclHDOuGG2eGtCLfS7rvp5k09xIBTOuV69/BD+u3pPVlqxVUEHn4wSVztWrzoV4gIvefTmqdsC1o24yP6X8boBnenzp6nSg3fpX0bpsYJUPwR+o9Hz1Wb/KN3NPTnLlCF+t2NPsMp9tPP16kPvYve61CfqpYvEjWOK4rQ/xgEoS9iIvQjgyD0D9wm9PMdEvrOJkK/NwhC//JtQn8yCEJf3UToxzok9J1MhP6rIAj9syZCP9UhoX/VROiHOiT0bX0I/X6HhN5LEvcEQehfuk0SfwuC0L+hLqoMQn/dTWOcEvq2RKlTeUjihs2K0G9QH2Rf9h1gJ2jbwkXZsng+4IfV4cuK0Ps+AoS+YN7bhB6HrxHOCH2rph6SiIPytDnOCb2XJO7+zjmhf/E2Sfz1hIvGTtInMKVLuKhCaQ9JvAJCP9EhoW9NlPJhz1yt2agIvYNMse1bKUJ/myQeVIcvp4Q+/22SeOZcEIS+gVqftw9fk2Y4JPTq8JXucQ/G3+x1TuhzZvfIHjuuCP0U/bkqr6LclCnumauLlxWhV4cvJ4S+Awj9gx5Cv2KNc0Kf+SlPX/erw9esufr9BqHPl/vO4Wuo+l7plpdA6GsrQq/GDEI/XlGAEyf1DiKJlVVQVzVXaR/Tb0+3X1IvbiKQUgg9a2JCROg9fUDyqFH9O1DeXM9G69R3B3+mzn3H0tdLRrE6Gyphf4R+7pKNSgN/kvp3b2Y0s233QRo+aSEtmdbfIPQ/H/+DmtWpSC26DaFFk/spbdxjRj0xudGbFTG5EZMbnZUiJjdicmO3TsTkJn6a3Ch9GM34NJEjQt+pfSSlSuW5Zrt6zRNdTbc8mlopFtSflPiDgJjc8OYqpIR+4Ji5ypn0AHVvW5dyZs9s9OzQj8dpyPj5VK54fuqkbM/jQvFH6M9fuExVm/amqcO60ZPpH6dO74+h/LlzUKuGr0dzih0/cxnt3neUZqhoOGFK1SKEXm9GhdALoddZKULohdDbrRMh9AmT0O/bH0ZLlvtz5vV//YcIY1kya9rc2S06+f2eICCEngdzSAk9wkKOUPbyny3dqK7XPLH9kqnUdnWUXXrnVjWjxXzndZsn7Y/Q44mrNuykYZMW0D/X/6WSRfJQ/27NKEmSxNEIPWTrte1PFUsWpCa1ywuh15wKIfRC6HWWihB6IfR260QIvRB6uzWC34XQ66AUt+oIoefNR0gJvbcr/yli//upc8p5MFLZ0z9BDyZ/gNfLOCwtGnq9yRFCL4ReZ6UIoRdCb7dOhNALobdbI84JPez6RZuvg2tM1hFCz0M3pIQesdufy/YUPZ7mkWi9+vGX35X923XK91J2Xm/joLQQer1JEUIvhF5npQihF0Jvt06E0Auht1sjzgm9zhOlTkwjIISeh3BICX3p2l2oz9uN6LVCL0Xr1Td7jxDivK/7bAivt3FQWgi93qQIoRdCr7NShNALobdbJ0LohdDbrREh9DoIxb06Quh5cxJSQo/sq4tVVJinM2WI1qsTf/xJVZr2ijNhK3mQRZcWQq+HphB6IfQ6K0UIvRB6u3UihD4AobcIDdu2ZQSlS+dBlpMplpNYihvlJrBTrP8VE82GXi9SZvQHiQWO3asY8t+F0PMgDSmhr9ighxHHvWbl4tF6tXTNVpo8ZyWtmfsJr7dxUFoIvd6kCKEXQq+zUoTQC6G3WydC6EVDb7dGfDX011TIy0NH9OPZZ8nkoidUUiuU/1TSx7N/EkVE6LRKhBwx6dO5KZG/gDx6j0iwtYTQ86Y+pIR+4YqvaNDYeVTrjRL0wnNZjLCOh48epwXq399RUW7qVy/D620clBZCrzcpQuiF0OusFCH0Qujt1okQeiH0dmvEl9D//nsYTZmhz7ArV3BR/ldw5eGJfz9hcmLCoUCn4CbkrSYRlDSpp/a1f1RePZf+FUHSB9yU7LZsGOnLoS13PHfsFUKvs8IC1wkpoUczK9fvoLkqbOXxk2dU9kE3ZXoynRG2skalYryexlFpIfR6EyOEXgi9zkoRQi+E3m6dCKEXQm+3RuISod+4KYx279U/TOAwkDatZ4Rn/gyjXbv0Sf3zOdz07DPx11ZICL3Oyr6HhJ7XnfgnLYReb86E0Auh11kpQuiF0Nutk5ARemWBcUAlK1q0VJ9sNbHeiroAACAASURBVGkYSVmzeAjTqVNhNGmavmy5Mi4qXMij9b32TxhNnBxOV67qkbXH0ripZfNISpbMg86GTeG0dbu+CUlCt6GPTQ39mvXhtPMb/blq3/oOof/xpzCaO19/jdWtFUl4P+JrEULPm7mQa+h53Yl/0kLo9eZMCL0Qep2VIoReCL3dOgkZoVcNHTgohN4O7zpvRtLzz3tIYnx1ik2IhP7WLaI/le2/bnnooTBKnTp2DwNC6HVny3+9+5LQX7/xL7338RT6++IVmjO2V9TIYQI0eNxntHztNkqcOBG1blRF2fWXNn6/dPkavfvxJNp74Ccjjv6HKkusN26+1W9C6PUWoBB6IfQ6K0UIvRB6u3UihF409HZrBL+bo9wkREL/119hNGaCvnY/bx43VakcqQNtjNURQs+D9r4j9Gf+/Jva9RxJWVXozLPnLkQj9Ii2M2/pJpo8pAtduXKdGnX6mKYM7UbPZn3SOAAkeyAJ9Whfj3bsOUwfDp9FGxcOo8TKVd3qNyH0egtQCL0Qep2VIoReCL3dOhFCL4Tebo0IoScKHaG3iIeqMxEO6gihdwCWn6r3HaG/cOkq7Tt8jJI/kJTGzVwWjdC3eXcEVSiZn94oW9iAYvikheRSWvsurWpR/optaMWsjyl92keN3+q0+ZDaNq5CRQvkCvhbsYIvkRB6vQUohF4Ivc5KEUIvhN5unQihF0Jvt0aE0IeS0OugHZo6Quh5ON53hN4Lx06lZfcl9BXq96Ah77emF7JnMaotX7edNm7da2S3rdigO+1ZOzkKzd6Dp1H2p5+icsXzB/yt4ZtlhdBrrr/4SehdVL2Km3K/5LErvHw5jEaNTUQRmreSmf7nNq59w5U/FJ6wZGk47T8Y2DnKVw/SqV0EpUnjAfjIoTCav0T/+rRhvUh6Jpun32fPEo1XYdd0S9HCLipdymUETPtXxWCePDURnf9bz3kv5cNuat3SRSke8rS9fWc4rdug7xAmhF4Ivd06FUKf0Ag9Ntxw4iSWEpMbu7eKSExu7DGK6zUSFKEvWbMzTR3WnbL+L70xL5u2fkczF66lj959ixq0H0Bblo6Omq+BY+YqUpKcqpQrEvC3Ds2qU6TLrW4EbtGEqXqEBw28Wc1NZYolMdo69WcEfTLCQ5x0SsYM6kahfSJ6KHm4IpZumvFZBO3Zq992t05uypbZ0/a23bdo9mf6so3ru+nVfB7Zn4/foqGj9WULF3JT/TcTU6LwMBXXN5KGjnMbRFOnpEhB1LUjUfrHPaR09cZbtPwL/bbbtXRTrhyefn938BZNmq4vW7O6IrdFPUGBfz8TQYOGqQQjDgj9O+0SqZjC4XRLzdXUT2/RvgP65Pbdzm7K8j9Pv7d+c4vmLNDvd7OGbiqQxyN79JdbNGKsvuxrRd1Uu6pnri5eUXM12uWI0HfrFE5p0yRSYWuJVqy7RavX6bfdobVbHbg9/d574BZNnqEvW+dNF5Uo7JmrE6cjaOBQdZDS9PHK9rSbOrVOREkTq7mKcNG4aZH0w1H9tt/r4qbMT3r6vXnnTfpsof48N2/spvy5PbI//HyLRo7Xb7dMSTdVr5yE1FQpnyE1V2NcdOGinvyjygGua4dwSpM6kbqpVAfOVbdow5d6sujr223dlOMZT79377tF02bpy9at5aLihTxz9dsft2jgMH1ZEPp2zRNREjVXN9VcjZoYScd+0ZNXqVHova5EmTJ49pKvtt+k+Yv056plUzflzeUZ86Efb9GYiXrton7Fcm56o1wSlZ+F6NzfkTRklMtRlJuuHcMpdcpExjdnwbII+nqrftud27vpuac9/d713S2aPltftkFtNxUt6JE9fvIWDRqhL5s7l4taNEqiTFfD6N+bLho+LpJOnNSTV25u9G4XoqfSe+Zq49ab9PkS/blq1cxNeV709PvAD7do3GS9dlG/SiU3VSztkT3zV4TaA1VkIgdx6Lu2C6OHU3jmau6iCKXY0G+7a0c3PZPF0/aOPbdo1lx92YZ13VQkv0f22G+31BrTl82XVymg6iY25iq2Cr45UoJHIEER+mrNelP/Hs2jNPQr1m+nVRt2Kq19GyqlyL6vhj7Tk08YSbIC/daifmX689K/dPw40dSZ+trTalVclE85oKBcuuymMeMSOyL0LZq5KIl6Z0FWlq4Ip73f6b8EHdtGRmXAO3yYaN5C/X7Xr6OiHeTwLDaQcScON9DQV67gGfPN/9yKVCd2ROjbtoqkVCk9be9UcXlXrdbf2Fs0i6TMmTyyv/xKNH2W/phrVI2kPC97ZC9dJBoxxpmGvnkTl5ExECP/fFGYpYbe9zV+u30kPf64518PHiKa/7l+v6Ghfy67R/b0aaJxk/RloaFHiD0khrtxg2jilHBHhL5tKzc9rDT1KFu2hTnS0Ld+K5KeesrT72PHiGbM1u93zeqR6jbFI3tBzdXwUZ5DhU4BoW/SEGNWtZXQHBUqzgmhf6djZNRtyv4DRAsX6/e7cYNIFTva08tTp3Cboi9bqoQ6xBR3G7cp11UCmwlqrpwQ+jYtXPTgQ571+dXmMNr0lf571bZlJGXM6On3Tz8TzZqj3+9aNSLppVweWUROGT5aXxaEHnsR1ifmd+bscEeEvnMnNVepPW3v26/eSwc3X01V2Mps2Tyyv/+u3g11e6Vb8E4VK6w6rCbr6rUwGq8OA07CVrZWc5U8uWffX7chzFHYynZq/8yQwdPToz8SzZ6n3+86NSPpxRc8sn/9RTRS3VLqlpdedFGtNz0vYaRShEybGe6I0L/dIVJFXvG09t33RIuX6bfdrHEkPZ3VI/vbCaIp0/VlK1d0UaECt29mr6h3Uu2fdxN6/7blSCzVslmEkTEWZdWaMEdhKzu0iSQ8A+XID+QobGU9FbYyZ06PLCLcjB6vP2Zo6Ku94dkDI9XQLlxwU4SKlKNTwhQRR4ScB5LqcxF/z33ikdtxWXUalTp3IZCgCP3b74+lUkXy0OtlXzWAGDH5c0Wkb9J7HepT4SrtafHUDynd4x4b+rpt+9NbdStRqaJ5LH8TG3q9typ+mtyQMrkBSbw3Jje+SEYzuTmiTG4W6W/OYnITRiMUSXRC6BvVv3P18pk66Doh9J07REQRj0OHwxwRerSLAwXKmTNicmO3o4jJTUIzufG8G2JyY/dmKN5iikPPcYqNiMDhKxGdOq1H0JM9QNS+TQSlvK10s++p/xpiQx8sch65BEXo13+9h6bOW0WTP+lKV1Q+5kYdB9LwD9qqa7ln6aNRs43rsR7t6hLs73sOnGJEuXkweTLL34TQ6y1AIfT2NvRC6InEhl4Ivd2OIoReCL3dGsHvErYy+LCVQuh1Vljcq5OgCD3i0A8ZP58Wr95CSZMkpuZKA9+kdnljVi5f/Yfe/Wiysi88QulUpJvebzdU9uKee0ar34TQ6y1qIfRC6HVWihB6IfR260QIfUIm9NAY65mFCaGPPUJ/XWVC1vU1w/ueOIlbKU+JRENvt/tZ/37fEnoeLPrSQuj1sBJCfx8QesO+3Hq+JcqNcpYUkxvbTQE29C/k9Cymi4Zvin4UJiH0CZnQ65sdCqGPPUK/X2VgXvmF/lzBRBRR4YTQ226dlhWE0PPwk7CVmvgJob8PCL3GXAuhF0KvsUxICH0YTZwc7sgptmXzSEp222dww6ZwR06xbVtGRDla/nwszJlT7JsqGMLznsMXHJhHqSAOugVOsTWqwXmUyKX+M+PTRI6cYjupwACpUokNvS7eccWG/vt9YSpghz6hb95ECL3uHFvVE0LPRFE09HoACqEXQq+zUsTkRkxu7NaJaOhFQ2+3RvC7aOhjT0MvhF5nhYa+jhD60GMqTxQEBAFBQBAQBAQBQUAQEATuGQLxjNDj6k0vjNI9Q1AaEgQEAUFAEBAEBAFBQBAQBGIRgXhG6GMRKWlaEBAEBAFBQBAQBAQBQUAQiIMICKGPg5MiXRIEBAFBQBAQBAQBQUAQEAR0ERBCr4uU1BMEBAFBQBAQBAQBQUAQEATiIAJC6OPgpEiXBAFBQBAQBAQBQUAQEAQEAV0EhNDrIiX1BAFBQBAQBAQBQUAQEAQEgTiIgBD6EE3Kfzdv0ZGffqMLF6/SY2lSUY5s/6OkSZOE5Okul5vCw62j+9xU7R/44Vfave8o7f7+B5o58t2QtB0XH3JL5ZQ+cOQXunj5KqVJnZJezJGVEifST2IREQn5X+nCpSv0eJpH6IXsWShRIr104sHi8d3Bn4y2nsqQ1njEseOn6MQff1KxQi9RksT6fQ+2fX9yQybMp25t6tg+kou3bwO67cY1zHT6ze0zV952Mi0qxMZ74dsdzj4WjGyo17bveKz2bs43gztXwY77n+v/0rrNu9W+m4peU3uX0wI8Dh79lc7/fZmeSJuanlPfSd29myOLfnLkObLBYq2LrQ4/0H2W1IvfCAihD8H84SPcue84g8A//mgq+vOvi+RW/zeyX3vK9fzTli28WLJpwN8PfjmDNm7dS4PGzqONC4bdVQ/t7v7eQ+AP/PCLQRbz5squ/p6lCiULOG43PCycUqRITtuXj7VFJVC/UzyYnHauGu+4bQjoyB7+8Tdq13Ok+giE0+OPpVZYX1CHnXAaP7AzPZv1Sdt+/3ryDLXpMdwg8KfOnKc0j6akpEmS0JiPOtIzWazlOWOuUL87zVCHrHSPP0r7Dh+jTn3G0P8yPkFZM6Wnfl0DrwEMiNMu5Dv0GuUXl517D1OR/LlUP9JSwzfLGgcO38LBm9Mu+hFqzHTXN6ffnD7H5pg57wV3jXL2MY4sZ21bjRm/6ezdwX4zuHPFGfdbXYdQpFKInD77NzWpXZ7qVi1FB5Ui6dhvp6hahaKW+y/63e69kfTfzZv0hNoH/zp/UWW+fYDGDOhIWf6XPsZk8eDYapuDdTBrzIpPeAF+MHky2vXFBEu8y9bpSmfOqbTANgXr3K6fTtq1a09+t0ZACH0IVkiVpr2oRb3KVLlMoainLVm9heYs3kBLpvW3bAFa5kAldaqHDa3C5avXCP/bt+Qs3oSezpyR6lUrRZVKFaSHUzyoPRpzu24V3v/EH2dp9LTF1KFZdcrz4rO2zzHLo49//X2JZsxfQwXy5KDqFYtpj9mpbO1W/ahK+SLGmL1l1ufraMPXe2jO2F62/W7aeRCVfe0V40NUrFpH2rJ0NC1ds5UWLP+S5k/s66jf5y9cpnlLN1JOpeGv9XpxS9kiVTrQtuVjjDrNOg+mOqr9EoVfptK13qGvl/gn3N4HcrDGM1au3+G3b4PGzTM09LjZOfrzCZo3vs9d9Th4c9pFR0KFmdP1zek3p8+xOWbOe4F++65RJ+8GZx/jyHLWtu+YfV8cu72b883gzhVn3BXq96A1cwcb+/07H4yj2WN60VmlVGnRZQit/HSg5R7YsMPHVLl0QapdpWRUvYUrvqI1X+2iGSOsb5Q5smiMI8+R5WAdzBozv4dfbPyGDv14nBrXLGcoa/Db7EXrje97VfUNtSrgL3v2/0iNlCxuwS9cukqfqu/s889mNrgGFJYoXl4SqnZtP+BSwRIBIfQhWCD5K7Y2TrxhYXfMYkBUC1ZuQ7tXTwxBC/4fgRfu65376etv9lNERAQVLZCLihV8iV55KXtQ5j6nzp6nRmrT3fT58KD6/O9/N6lSg3eDkteVfblsCwPTRMpMxWskA9lXX29H362fYtvvVyq0Mm4QcM3rJfQQKli5LX1jc7Pg7+G3bkVQ6dpdbEl5ubrd1IHhffr1xBnqOXAKrZ4z2NgUi1XtSDtWjrPtt28FXbysHly+XndaO+8To0ohNX5/NytevM1mQU7w9te+TruQCzVm3PWt029un7nyvnjrjjnU7wX6oftucPYxjmxMrG3dF5nzzeDOFWfcDdp/RLNGvWfccNZp3S9KCYL9124fw5i/WTUhmvkovpOF32hne6vLkcWccOQ5shysdddSoHqvVe9E6+cPpQdMpr+67yRkNyhZs9kwTNrKKM29nQKK0y53zAldXgh9CFbAOx+MVxrfkvRK7ueinrZ110FatnYrDevb1rIFrjmF9+GnFRnfrMj9/GWb6PSf52nP2smORwaihmvgCYM6O5aFAE7pFZUGx87kxt/DdWWh0Z47ro+6sk0d9ZiTp/6kZu984tcsybetV9XHY/OikcZGBUK/aeFwWqC0RKs3feNXQ20HBK6bW3UfZvsxm7tkI02Ytdy4bh7UsxWVKpqHfvzldxoxeSFNHNzFrpm7ftfFyyyIj+e16zcopc9NDjbq2eo2qXndine1w8UbDwymXciFGjOn6zuYfnP7zJH3l0dbd8yhfi8wf7rvhnnRcfYxp7Lctc3ZuznfDO5cccaN28xvvjtC5Yrnp+GTFlKPdnVp+7eHCKZPCyd9YLmPvdGkF3383luGz5K3HDx6nLr3n2ho/a0KRxbP5chzZIPC2qU6fFtb5W+N6ZoOglhjTszfSrwjddp8aNxMWxV8Gz+f3C+aLG5icOOgQ+iDbdfxh1AEoiEghD4EC6Lf8Fm0+Iuv6cXnslKqlA+p68jLhoMstOVQ2uPKH8UfUeaaU5w8dY627T6o/g4Yjp7PP5tJ2UW/aFyV2RXYFcJU5e+LcA5NRWWK5aPMT6WzEzN+7zdsZrR6cPz5VjnkwuTmw27NLJ/BkYUz6WPKT+GRVCmi2gAhPf77Wcr+9FO2fe81aCrVVeY6+KhA03Xj35uUU10jftKnNWV68glL+RJvvh3t98hIF126co26tK5tXGv6FmyAsJn3lnPnL1FidbPw6CN3zKcuXlLmVI/cGYu/DnDwwvPgyDZwzFxa8+UuAsFLniyp8rEoaHyMUzyU3HLMHLw57VphpusEhoPeus3fEsw/MA+li+WNckq2GjS33/7mGesMuOsUf/K6Y7Z7fqDncN4LtOn03fDtJ2cfC1aWs7bRf87ezflmcOeKM25o6M0Ft9IZ0qWhVg3foKw2dvC4TX5v4GQq8erLlC7to4av2ZfbvqO+XRobBwSrwpHFcznyHFkO1r5rzKnp4HilQPpMmYTWqPQaZXgijWEmhQNZ1fJFqX2zapZ4Q3b52m2GeSu4AfbQZWs8/3/bxlVsZYNt127/kt+tERBCH4IVEsjm1vfRr5d91b41Rf7/VVpcHdMVOOBhQ32tUG4q/MoLxg2B+XrNqrGvdnxP+DCULfYKrdq4Q2mM89IWteF+oBw0yxV/xbafsKczl8SJExvOleiH2fQo+oM8qofgZD1PgiYoUNGx/TfLIsoM/A7MBNtq4DgAmctFZVc4f/kmKvDy8/Rm5dfuEi1cpb1fB2NEqNhm3OBsoa27DtHedda3KRy80KkeH00y5qRt46qK2CpHYuWMNn7mcuOw+fF7LWznOtiDH7ddq7k2d9rfvH+5/XvqrdZ30YK5DDKPMWN9D+zZ0jY6B7ffl6/+Q5ev/KO6ePskr/5Xl34TaPrw7lp+LsEeRDgO9pz3ArJO3w1ze5x9jCPLWV+BXhpdU7hQfTOc7mHefge7xmw3C5sKOHwhSg7IPPZdfGvgB6ZTOLJ4PkeeJxucYiEQJrpmdJDfvGMf4Vt/QSntUiu8iyuuULJIHh24DVn8/X3xMj2q7OiLv5rbOIzpFE67Os+XOv4REEIfB1eGrjkFrioRphKav5dfeIbyKdt5/CF6il3BNeIHXZooB5lnomzJfz7+B7XvOYrWfTbETjzWfke/o4pSWZw5d4GSJElEeV/ITmM+7mjbr1AeCNAYbgfgKObP7wB9bVCjDNVUZB+E+qdf/1Bajq30hTLvyZDuMeUgVsiIRqR7oLAdXIAK8A/ANan5sIeQebgO3rrM46gbqHAOfpx20R/zXLtdLkNLdOXadSPUHW6EvGXFzOhaQ/x7pYbv0kB1WDFHmYIJSO9PptHyGXfXN4+f0+9hExcqx7N1lPLhh6JBCqcyaCU7t6xpOJUFKpyDCMfBPibIrdW7YR4/Zx/jyHLWV6D50927g32XIcfdwzhrLCbWCbTGdhFyOHjFpiwH60D91jWji81xS9uxg4AQ+hDhvmL9dlq1YadBOhCSq6Iiaoh6E1hb7WmYa06BZxxXmmOErtylQlh+u+8HI4yjnZ1bvvIt6ds1Hs2t1zkUmuOiKhqLrg08POFBTnH6hxc9yCm85+3GjD5zZM1TdvO/W9RXmf+88FwWql+9tO1sBvqIFy3wYlC27NCQ1VU2if4cwmAjDwfYG//+RwgV5lYHkPIl8ht/3nj0th2+XYGDF5x250943zBV8has02rNetsSes7Bj9OuP1yA33wVjQjrvWfHBpbQgZTvWDHuLgc8HUd1Tr9xK7Nkav9otqfoKJ7pL/Ss7yA4BxE8K9iY19EOyhbI+js8Bapu9W74kwlmH/M+hyPrfYaT9RWKvTvYbwZ3D+OsMc46wS0OoonBTNF0eUVfbv/OiDoG05BAZo/NlY9UoDJN3XztPfCTiiq3nkaoUNH+CkeeI8vB2juOYG9TcKBetXGnke8kwqQAwXO7tbXOP4Lv+nClnEBY56HvtzGUhDAxvaoUKmZz10BzYv+9MjkK6H4EpZ4tAkLobSGyrzBp9krDPhmxvOGAck5d7yM8VEWliWtRv7LlA7jmFP4eDk27XUx12LyumPmxYQKAUHtDlA3556s2G9ELhvRpYzvoKXNX0dqvdlMz5Ug5YMSn1FWFP0QIR1zLIfSlVeHI+nsuTBxK1+qiDijOIwo5+YjXbPlBtOYRj/k3ZbsPZ9J2TQPbJO5XSbBWbdhB65W/AjbGMsqWu6y6ajbb18ckXl68sT69tqtYdzpzxTn4cdoNhAc+KkWrdrB1QkZov0qlCkUzhVq06mvjIOkvPKe5PU6/W3YbahwMfRPBde47NiDZMLfNOYhwY157+uHPtdZ2O6Bg3w2rJ+vsY4Hkg5XVXV9ol7N3c74ZvmN2sodBlrPG7FdC4Bo4DOAGObtPvpBRUxdTp7dqUE6llDE7zJqfBF+YQAVmO/ADO6QcbAMlu+LIc2S5WHM0/G+/P9ZInojbeyj5zAV4WxUoIAYp80Tcah49dpIG925FW1Q0PQSQGPdxdF8y3+eE+vvOWXMJTVYIfQhmHBruxVM/jJaYBxpQeJPraOX8deEHFRc8xzOZLHvHOUXPW7pJ2dxnN4g/wvElTZLYyFoKO+sHkz9giwoOBHPH9jZMR7wafhDrysrUwc6MgyPrr2PQRCA6SNM6FWz77a+C7kccSbzMJXHicGP8usQcNyA79xw2tCZfbvveSISFWw2Y5VgVLl744K9UBwrcIJ29bbuKw6bXFMiu7WAPfpx2A/UJUTGQ+Gnz4pGWmEFj217Vu6nCiho29MpB2aVw0ElAxu03J4sn5yDCjXkdrK8EJoL7bthr9PxPN2cP9PdE3fVltfh09u5QfzN09zD0m7PGIA97cmiNfbW+UBBYFUTnwa2Zb9G9vQpqc49lIS7WHA1/xQY9aOWsgUFlQcdesmBSX+NWGTfQyNGC2z+dvCnc71UsT1m8bl4IfQimD5vzBpXJ1ddGGWGj7GKbwx5u++5DxjUkXh5vGT9rmcog2owK5n2ezDHAzd3lnKK5w0aEGJjsoHgJPexH32jc05bQc2TRXrBX1VYksb3KPmtnpgT530+fM+yjU/nYSDvFE1FPvlKOm3BIBsm0Kly8nPbNXJ978OO0jY+ZuYBA4KD8bod66jBS3PbRINbQWp9VfhbwU8itNFWB3iXbh2lW4Gbx5BxEODGvOb4SXmiCfTc4Gj3OHshdX5y9m/PN8LcUcRDR3cM4a2zipyto5sK1RmbXRD5aX7vEft/sPUL5X85x1+3Vdwd/Nny5rIqV2YtZDuY3/gpHniPLwRrj4Gj467btT/PG9dYygfXF7IOhM41ocIgcB8UkTDYRta1mi74x/n3X3Gqlmh8EhNCHYFnAThpXWgjnBPt5mNyMm7nMsJ22i0OPK3qEk8qaKUO0nsBLHBoPhPMq+1o+v73knKKxMQcqrRu9YYvK643eoynDuhnaTyQVQfY/mODAhr5Vw9ct5Tmy3Ktqfx9x4I8QjuYMhv4G8Mm4zwyzJGjDcO1YKF9OlQL9vEEyzc6X/mQ5jmwcvNAX7lzbLoYAFbjt4qrXXJAMLL0Kv/bQg8lsu4TQk4imkSZ1KtuoNr4P4/Sbm8UTfQn2IBJUzOvbg+f4SuARnHeDo9Hj7IGc9YUxc/ZuzjeDs4d513qwa8yb+Mxf5nK7l9LqvTLL+vv+WJm9mGUDRWjjyHNkOe8zZDkafmTh/f7QMeWbUMyIcGP2bbMLMdql33japEKKPq14CW5j8N9fVFJEhGe2C3nJ/V7ZrSP5PTACQuhDsDqu/XODBo2dZyQnQvQQaAHLKBLep3Pju5L4+DYHMvy1SvLgqznUuYbknKIHjJwd1RWYIpy/cEmZgxxRpLYEdVVx1e0KCGr6tGkMgoXwl8keSGoQJ8TetyscWe5VNecjDsK08tNBKiHUSSNJ1KRPuhj5BoClnV02x5GNgxfmwjzXuAU6oTbooz+fpBYNKvuNn2+ePw655bRrt4bsfn+r6xB18IpUB66/qUnt8obTHexBj/12yjaiBqff3CyeduOy+p0T85rjK4E+cd4Nzg0UZw/0YokDOhKuPfzQg3dpj63w5uzdnG8GZw/DeDiHXXN2WKdr1feb85dSfO3ce1j5FL0S7ZDe++2Glo/GYQSH+2ALR54jG0x/ORr+kjU7R7v1N7f/lUquaFVgGmouYeEq34D61utE0ON+r4LBSWQ8CAihD+FKAFmC6UwK9WHQvdqf8OlyatXgjbs+JDMXrDWIiFXhnKL9PRdhFQeOmUMzRkQ3dXACEScEmY5sqK+qvWPTabserjDH9zFEzJrBIspJc/vysU5gMjZa3YgtgR6s0+dAsvA5gBPZwJ7Wcei5Bz/f9nXbhZxddAkrwBFKFNkncfvyzgfjaPaYXsaVcYsuQ9ShbKCjuUJl3X5zs3haxZI3d/rglzP8ZMjvGgAAIABJREFUjsHXDr60ShaXRSNZHNdJnvNucDR6nD0QpHrAqNnGzeIt5WsBpQQ0vO91qK+VL4Czd3snL5hvBnc/4Bx2kR0205PpjJtYBFDglgMqYMCY6UtpytCu2o/KWbwJHd48U7u+b0WOvI6szjuMqGe7vpigNYZgb1O0Hm5TCQpKKEbMBX0PpnC+V8G0lxBlhNCHYNY55hRoPlhnNM4p2t+wsXEUUuH+vLbxVtBwQpBxZDlX1V6sgw2dNktFhkme7AEjJOlbXT6hmaPeox0q7flAdTuzYf7Q23DpRwnRdWTj4BVoDq/f+Ncwldq3cZrjN4Bz8HPSbvSrbnWzoMKvLf5ii5FZ8tV8L1j2GxktZ6n5AekwaxUxZn8hRu1A0O13r0FTlO1p6aAyEaMPVrHkzX30Z/LAsYPn+krovRv+UeZo9Dh7IG4WkTn3nVY1qcZb79Mc5eQ/ec5KpcG+oRWRiLN3c74Z3P2Ac9it3ryPuqH83dCQp3z4wWhmHFvUTbPTggNNgUptaPdq/QhlOqTaqh8ceR1Z8zv8xcZv6NCPx42bUIR2xm+IgIdkeDgUxWTh5AxAdtwPh88ylCC+xe4wxV2fIcEkgUbFFEIfgtXja07xtwoVhUyROrHNOR9htJFYmfd4bYrxcbr6z3Uth02E8DMXnMK37T5Ifyl7cDjA2BVOCDKOLOeqGmPitF2mTlfDZt5cEKa0V8eGKtOuXvY9s6yuIxunz972fCOv5MiWiX789Xd6UYWKc1qcHPxC2S76uWf/jzR0wnwj6oJVgTbom++OGD4o0CrCR2K7OnzhI7dw0ge2Qw5Fv4PN4mnXObznvmExvWs7tpLFhfrdwHg4Gj0dWTgcblo43Ng/vY79OGQXUbkEdHJxcPZuzjeDux9wDruwpw5U7Mwx4GtkLoiasv7rb41DupP8BrhNsjMZsXqHOPJOZREYY71S9pgDZuA2CCa1OkEYAmn7UzyY3HaNcnIGwE+jV6cGlC9Xdgr3uYmxM3firk+7/U9+D4yAEPoYWB3QOixft532Hz6mtIlNLFvgOKPB7OODrk2M8JY4SddvO8DIpPl2ixoqyZJ1KERcVZvLRZXJ8sAPvximCXbhMiHHCUHGkfX2Odirak7bIHnmEh4Wrm1zy3Fk4/QZ/eVEXuEc/DjtBnpprt/4j4rX6GSr0QNpMRc4hGVIl0Y5bL9Bdg5h3H4He+OG/lpd18PMZuPWvYa/jr9wuFw7eNy8bNq2ly5euqaSkKVUh9S8hjOcTuG8GxyNHkcWmuGdK8cb77CX0CMqEvbGtfMCJzLy4sHZu30xdfLN4O4H3MOuznrwVwd4mwuUUTgE4LCdO2c228cGG0XJ+2COfLCyIPRQIEDx4y1QCiFyjM6Nhlnbj4M8TAhnzF9DBfLkoOoVi9liFmyFN1U0m0VT+gUlzl2fQTUqQgYCQuhjaCFgg4YGyM5OjvMRxosD222QFVwfZ1a2sm9Wfs1I8hJM/Hs4DY6etkTLntEcgszsKKQTgsypLOfq0Hd6OaHTOEuF48jmFC/ffnIir3AOfpx2zWMIpR2nzhxy+s3R2qJvViY3MLPBR/3y1Wvkz+SGYwe/cv0O6j/yUypZJA898VhqI9Tn5p376MNuTY1bjpgsHI0eR7Z+uwGGwgX5IEA2kZMDCakG92plRBizK5y929+zdb8Z3D2Mc9jl+LXY4Wn1OyeKEp7LkefIjlfBEz5TCReRBRdOpSDkOFBVLV/UNlpMIDwQLrVSg3dp0+fDOZBaysLvqF2TqvR05oyO2+CuT8cNikAUAkLoQ7AYfK8hI9S17dcq7OS8ZZtMttX+G+J8hCG7fv4wI2wi4sOunz9EJYVKZthGB2MnHIw9I0alY1cYCGYdWfPVYWJ1/QcbTmS4TZM6peGEfOnyNSqS/0Uj6oxOCTaJDef6M1C/dEwDzLI6ePm2FerIK7oHP267HDtOYIBDFLIbIovkY4+mMkiaXQZlyHH6HSqtLd7Fq8pp8+GHkmvHkebYwSMc4aBeLY2skt6y6/sfqN+wmbR6zmDb14rzbnA0ehxZmCwmUQn1kEgPewJMb17JncPIWaBTOHs355uBvgW7h+mMC3UCmSCb/VqwRvHtWbZ2m4ocVcT2VhjPDTbpGieKEtrlyHNk0TZCUOOgf0HtQwgfWbxQbuPgHGzBob+icvr3ZxYWKodc+Kohat/LKj9A6lQp1R50p7d2obg9kdHgMI1VFL3ohMQOFheREw19SNYArmvN5YrKmIocUSCYSAxlVTgf4b5DZ9ApdX13TmX/rFS6kBH/Hdfm73082chca1WwyZgLbEe37NpvJOJxetUWDMn0tu1U9iMVlSKb0hrUfL1ElLkLSDGyM/bs2MB2PjlJbDjXnxzTAPOgnOIFWW7kFV9QdQ9+3HY5dpyIIDRyyiIqpT6ccEY7c+5vI5FXj3b1jLjMVoXTb67W9k/1Ln80erY6iBwwIq8kTZqESqiDCNY2DiW6xWl4PSSl2rt2cjQTMmRgLqBuGb9fP8W2Wc67wdHocWRtB2VTgbN3c74ZnD0MQwrljSeeh4NR/fYDaJVN9CiOKRsnihL6yJHnyHLXGA7U5gK/g2/3HTVMbj7s1uyux4fKIdfX1NLcEKwArAon7C8Xr4QuLxr6GFgBIMefKe38b7+fJbuYupzm8XIjeU7SJElULN+8hiYPbZ/+8zw9lSGt5aMbd4oeug+OLhnTP0bN61ZSYcmecNQtp45C5oc7lQ2UOa/Q6/bmTWiXk8TGHyi6158c0wAOXpCFORay/r2QPYuhfUaW2pzPZqZP+rS2nWvOwY/TLvrNseNEDGYcqM0aeWjskU1zo3KEtCqcfnO0tugTQgri3W1Rr9Ltg8gFI/IK8kRMHKx3A4XnOD34IcrLwJ4tDfMTbwEB695/ouMDvlde993gJBxCW8Fqqzm3Co42SI3KTr4Z3D2M4yzpbyi4IS1Tp4ttdDSOKRsnihL6zJF3Kstdz2aMP1WR1cwlceLEyu8gLRV+5QXbmzuOQ+5V5YuHW3DfAs6hG5LbLKsb9lfjVZEqFgjoE3r9aHwCuEIAtq6IlmBn+sJJ3BMIaJzq7ZxxY2qSYA6DdNExVSrU764OSY2MDc1boKX7QI1Zx5GNk8TG35isrj/N9TmmAf7ahfZ0v4rh/Eru5xxB7TTySqgOfk7bxaA4dpyF1bu3ZcnoaLGy8TF6rXpH2rFinDZmTvvN0dqiU7Dl3qb8YswfTfQbe4mdP455UE4JfSBAYF71Yo6s2niZK+q+G2aNnlVD/pQjHG21760CzEfmKXvnnOrgW+v14rZjDvXerfvNCPUeZjtQU4UeAyZFq46bIAR/yKuioQzu3cryURxTNm4UJY68U1nzekYSL0TyKZQ3pzqgp1I+MteMaFv1lIKlc8uaTqA3zJXsIsyYH8hxyIVCpE/nRup28OWoR2Iv6P3JNFo+I3rAAZ1B6Ib91XmW1AmMgD6hFxQDIoDFai5eG3pc+ds5rnCup2DPOGn2CsOOHGYQ3oIP0wvPZaUOzapZxuuGHSeegfrpHn+USistv51m39uGr5On999h7gPNL7LIplD2v/5Kj48mUZ0qJQ17XTg89hk8zcjg2aN9PSrwcg7LlfalMpvo3n+C0iQ+paKWPGY4GSFb66CerbRCR3KS2Di9/jQPhGsaAPOLA2pD3b3vB9qtbJv3H/7FGL/dNTf6gCt2mJ145xYZRUFUi6nMvsFoW3S3Am67HDtOED0UxH+G2Qo+rNPnrzaSB7WoX9lyCNx+6+Ljrx5uJcYM6GhkYPaWk6fOGZFXPp/8gfajnd58QZu+ffehu/aS8bOWUb+uzQzTQau1wnk3tAflpyJXW+37SCchBTl7N+ebwdnDfMcLB9k5Y3tpTwFyeJjLBWXPve6rb+n9dxqr2Op3/C/8PZBjysaJooS+cOQ5snAi7qzyHOB21PztHDJ+Pk0b3l0bd1R0ekjnOOQiuEXfIdMpe7b/0Tvq4DFn8QZa/eUu6ta2DlUqVVCr3zigIgNzSqXpxw3UEWUWG0yYZK3GpJKBgBD6ECwEvGjmgjBoT6Z/XC3+ulSy8J0Trm5TutdT+JjBJvhZH414s86DafqIHsqZJYXfaBjoB4hxb2WKUbRgLoPM/6nScG9RySRw7f6aInp2pXw9/5sRzH2eUM+7qGLxv92iJjWocXf4TGzsCNkFbcO4GUvpuDJNQpKNoRMW0LIZA+yaNpwckTIcTkaPPpLSIBu69sWcJDac60/ONSw+CvARwFUrEpLkyfWs0og9G3BufQHErcaMke8a87xPadM69RljhIvLmim9ImtNbfEONgwjt12OHSdMSLyHTjg9ItwlCqLD/HfzZtQBeI+yGw8lXpx5Rj+QdAbvf/kS+emRlCmMA+uar3ZRhRIFjEOZ9+DetE4F23lzUqFlt6FGW1l9wlTC5ArOxIh0U/a1fAEfyXk3cKs3Y8Eaw8m9fdPqKnlbUu2uh1pbDS1kq+7DbG9WA3VQd+/mfDM4e5hvv52SRH/jhkKomdqj7GLJc0zZtBdEHKuYv2Lru0LsgtzCRNRJMi0MK5i54jjk4nALPz2E4M73UnYa81Eng5zbFShPBo6ZS2vUAQCKArzPFUoWNMKTBlLy2T1TftdDQAi9Hk73tJbu9RSu1DYvHnmXLR2SVtiFrYTD4cD3WlCu55+OGhvnSs37EG/biItfS4XP9BdrF/1GUg3YcpdVtpcLJ/dTGv1HA8a2v6fgx1BjZm2eS92m/KUOUDiUlCn2SlRiMDTtz6wAtqfn/75smD68qkyNirzyIj2iDmu6pUiVDsqMY4xRHYe9OlVLUQl10ET0BrvkJpwwjJx2dccWqJ6/DIf+6uKQ41s4/eaYj6AffT6ZrjX0/t3vdoiDRmzBii9pw9d7jPCXaZQTbXlFxOEEDP8aq4LIWF+rQ7avFl5nL9HqsEWlKk17GQeGnxSxz6hunaAF3LHnkIoOsl85A9e3fDxHWw2FiLmAaOG2s0vr2sbNTjBFd+8O5tkxIRMMSfTtB8Zc4s3OjkzCnJqycf0dOPIcWTjUFsjzvBGwAreDMJWcpm4K4fT+2fg+jqbU6a2b+eHIqFwoX07t9tBP3HIuVtGf6qnM10j+lf/l51RW5Vq2iStxA4/9pm3jqkqJlNpQFo6fudyIlPOx4hxSYg4BIfQhwjZYLaa/5nWvp7CRIkwl6uNq6+GHHjSiVOD/R8p7qxLIubRgZWdpuH3bgIaqfvXSxsZVrl43vxn94PiXR5nb/HLitBE2bpC6FUB0jwYdPrIN82kVB9ncl0DXmZw4yjBRwjUmPkYRyq7ZXJyYQ3jlDigb+DHTl2rF/UeGXNheIgwjDgIgosUKvkQ6YcAQknD+xPfp1xNnyDBjUWEI3er/ilVV9uQrre3JOWEYOe0CI66224vzqKmLqdNbNbTfdG6/tRuyqejUZnbYxIW0ddcBalSzLKW9HUsemvMySrPeoVl1y9YmfLqcWjV4465EaTMXrKUmtcvbDonzblRr1puWTh9gHPBxeEWmauxtbzTuaevAzNFWY882FyTXm798kzL7e97I5xFM0d278exgvxmcPcx3TJg3uwyvZhmYipgL1iiiruAgBg2uVbGKroObR6vCiaKE53LkObKYY/gd4IYVN1CXVQQ8JGuDWapu0rZg1qGvjNODGxR+zz+byYiuhVtNaNrHqBw1qzbutFUCgVtAUWTOjgvTWiiQti7zKJakxAwCQuhDgCtHi8lxrALJG6DCOK79arcR4g4agHLFX6H3OtT366FuHio+nJVKFYr24YKJAyJGzNPUHKxYv51Wbdhp2ODDzKZiyQJUuUyhKG0gNgH0ybdAezpBEeOkisx3bF7D6CueAYJrF5/XHAfZauqAg78SXd5tkHNoH/p2aWzpb4Bn1WndT5n35DSuHxOFRz8wOdF+ePulG/7RXP/ITycM7SUSAQEzO0IOWRyygDdMTby+BjBzGDF5oW3kFE4YRk676PfUeV8oUr/ccChLkzoVXbh8hXaoQw20uTCj8bqN2EWScvox4/Y7BFuK8Qin/YYj8KIpHxq3Xd4C+/sGKqSgXVZKDtnivhutewynIYrgYB/AOzZ/Yl/DtwYaSScOzKHAHYqICirGt53vE9ri7N2cbwZnD0O/OXMNE0lzSaTMJmFeCnMs+KpYlWjRddTLe0YlL0uSJJHhUAu/EadFN4pSoOdy5J3Knjt/iS4oM1SQY3PWWLsxh+rw5nQv8Zra+fbv0I/Ho/kD+Os/bvVwKDebweJbhYO7EHq7Gef9LoSeh58hzdFi+jPF2KGux3DN1aV1LcvewSYR1+zvKKcb2AzPGdvbCHH3j9LWj+jX3lL2uNIctO81im6qg4BhQ69INkxBxg/sHC10XaCHTJq90rCRa/hmWWODOqeu1WD/W1E5zNg5HXIhDzYNd6B29+z/UdnvzzeIhFWp2rS3lo2/v2dgQzMXRC5B9AMcJuxsT3Fo2rr7AMGxFo6wRWB2UyCXcjDKepdGNVD/8UFBqnVz0hxoRO3slblhGINtF+PAxwxXvDmzZ44aFhygh01aSNOG6TuUOf2YoTFOv7nr2yvvtN84fO1cOd649fIW+A4gss+3a6JHJ/HtI5dscd4N3HohiU1Rtaaxp7xe5lXac+BHekxpNO20vqEiPF48cMCv2+ZDrYMyZ+/mfDP8rS/dPcz7vfI+w+1y0d+KaCKWfNECL9oe8EO1tvEcHJ76Dp2pAjhkMW51nRbdKEqBnsuRdyIb7E0M+s1N5OUdO24J7KIQOcUf3AMWAb7FG3kK3CCdUi7g9h03hfDFsbspdNoHqR8dASH0IVgRHC2mv+ahqR43c5lt5lNcbW1SMbWR4RCJSqCFw5UvQtz5yyLn2xauS5FICmneQfRyKzMYJMXC1aBdQXtIXgVHPW8Baa2jPoZ29vscsxlOGu5AYwLpKV6jk62TUpO3B9FYda0cjGMPwhGaC8g1rrrhKJQ7ZzZLuEHsMj+VzjjkYVPE9bbTgqtefLRJmdp4S5d+E2i6irTgL96wtw43DGOw7aJ9OJR9s2pCtI8GPiJOzcJw8+TUhILTb6dzE6i+U5tZEEzkGzBf5f9x5i+apm46nIaxdUq2OO8GTKLMBSQhwxOPqWR5Bf3e8JnrcrTVNZWPj7lEqv0QuUOa161I7ZpWC2oadffuUH8zdPcwf4PCTSEcHxF+0m6d2N1K4EZoq0pQWL/63cEQ/LWN96x0LcSwn2iJNzeKEkeeI8u5iQkEiG4iL8gHq/yyyjh78MsZtHHrXho0dp7fbz3W08oNO4zb+7OKzINbQNFXU5mx2fnyBPXSiVAUAiEn9IFSRt/PmHO1mL7Y6JpigCRCI4cPoJfQg6AjxJ1OTHZvu0gigRd09aZdtFdpxr7TyAyJ9jYsGHaXnRwcXr9ZNd5yun21DtDuL1m91Qg7iXCU3uLPbIabhpuzDmFnvObL3UYEEmxSZt1EbRWGM6YKtIa7VKhKhKuEvSqiA8HsJ6/604mXDdvq2YvWUcqHH4rWxQvKZhgaFMRD1g1F5mSM3HbrtxtgmGA1UpoeaJ1xqwFNz5fbvqO543o76UpUXZ0cDdx+B9UxC6Fgcw5w+6FLttBObL0b/saoq63e/f3RaOKJE4cbN2D+HKV1sdTdu0P9zdDtX6B66DcURHa5Dvw5fXtT1MD0DZGlvtj4je3tsrcfWNswcbOL2sSJooS2OPIc2VDfxGAsuom8OMovs9+A75qB2RAUK5evXtOOtMZdnyKvh0DICb1es/dXLY4WM5ApxqKVm2mlTSptEB5oVJDdEeQeWTF/Pv4HDe7VytDkWhXYAH69cx99oa66d+45ouwYnzFsk0sVzasVmgrOleHKjrxt4yqG/TxIOW4Vbvz7Hw3r29bxBOuGPuOm4ba7ot974CcVc3e9X5Ml36Qq5kHqXGfiRuTAkV8NW0rcbCA2sZ3zsj8g4UwMcr/rux9o5IfWplWQh231kqn977Ld1IlgYqeRs5poTrt4rtehDGsaIRxBMLNlzkifqAQ2Wf6X3nKNcXI0cPvtePH7CASbc4DjmOqvz7pkC7Kcd8PunXSKJ0db7aQtzt7N+WbY4WW1h2F8WCfm4s2bMk9lN98wf6gTCIKu6zT+fdANxbIg9yaGk8grJpRfOgoRTrStWJ6ueN+8EPpYnsJAphjd2tSxTdSBqzdoLuEgCGdWmN68kjsHpVD/tXNQQvxmJHaqVLqQEcJQJ76sGSo45OLKDbavcGBDuDtE0+jTubHjZ+G5utkwnabh9p1eK6da3Aggxv2ho8e1YvE7WTogp22U8x8I/Kkz51VIwZTKKTiJshHuaBzE7ArHDhMxxicO7nKXvWPnvmNtfS04dsKcds14ID465gU5B9I+dsfEywozTo6GUPXbbk79/c7JOcBx2rZzlETUGZijPP9s5mCGZXv48laAphjKAYTLQ/K5uirEqm5xGpqPS4w5e7fumPzV4+5huF01F5hZwsF80iddjJweVoVzwDc/16l/CA65C1Z8RZuVEgr5R+Bwie/Wm5WLayXH48hzZLk3MZxEXhzlF0chwom2xXkvRFYSS4VkDcxdssFI+JPjmUzG8z5ftZmQjRPXiJzrW93OeTV6MMv4VmUS3aeyiH5vYzbz8ei5tGHLt8oe+3EjQyy08+boGLpt4wOM2M0pVMhM3ayjMO0xl4jICGVG8T3B9Mcue57TNNyBxuEb6lNnvHakx+oZiCpU9rVXDILiNY9aumYrYcO2c8YNpR2m0xCO/sakaydslg22Xaztw8oR1vsRf145yOqkP+fkaAhFv3XWk786nJwDHMfUaE6xPh2D0/a23QeNqC6Bsopy3g1/OOAQh/C2TtLMOyWJXGIc7BxDLhTfjGD2MH99xnM+U9p5HNjsIkZxDvgcQt9v+Czl73Xc8CPC7Sb8voAhTA8RWtGucOQ5spybmEBj0r3N5ii/OAoRTrQtu3mU360RCImG3mtDl1DBBnlAbG9oyBHKcdbCdVQk/4uERE3I2GpVkFVt3ebdRlg+nQyt5mfhAwub6gM//EKZnkxnHCqQQRR/OplTsZHv+v6IYTsPG3qYMUBL3aSWfdxpzge8g4quYy5eB1F4xdv1m5OGG23CNrD/iE8NO2zcCuCGo5wi2j07NbBNmMGJBIIbETgqg4x6CT36A7tVO5+DUNphOiU9/taurp1wMB/wD9XclFa+FK/me4H2K+fwt98fow6KiY11Ac0tspPAzMicSt1fH705Gnx/08nREEy/g9v7/HscBZtzgOOYGlz/70hx3g1/bePdLKwySkfPpmntoRXs2g6WGHP2bs43g7OHBZpnmEkgmIJOGFzfZwRzwHca/x7ZxdfM/STaHg1b8kqN3qXty8faLl+OPEfWtmNBVNBN5MVRfnEUIpxoW0HAISImBEJC6BM6ot7MpyA6SMgwuHdrFVIwCxWt2sE27iq0UIiucPrs30YCF2hwcRA49tspqlahqCW0ecu1pIwqBnDtN4orEpTPUXxb3wfDXvZrlbQIDk06dtmh/oDfqzXUqc8YSqZSUbdXUSyeQPIdFa4T2mM4Fg/pEz0SjV2fnEQCwUdh86KRhikUCD2iE+EKGSZLdnH/uXaYHILKsRMOpl28M2vnDTEOx9A4t2zwuoqQUCDqUbjVQHjUJdP6W06PnTmF3dx6fw+WJOo+P1A97CVOcw5wHVN/+vUP2rRtL128dE0doFIa/jTBJr9x8m4EurGD092MEe9qQ+k0NB+XGHP2bs43g7uHgRCai9eGfuSURVrx930nRPeAzzHXgb/PipkfG+al3oIDFbIM20VVQ32OPEeWM2b0m5PIi6P84iStDGW0Le2XXyoaCAihD8FCqN68D73bvj79cOwEbdyyl2aP6WlkOixfr7ttQhckMVkzdzDhivmdD8Yp2V4GyWzRZYitUyxs1+Ec+fXO/UYGUYRTRPbQYgVzGdp6q4LEQjMWrDFCVLZvWt02HrkdTE4+4JxNjpOGG2OAphxZ7JBh11uuKFOfUjU728bq9oeBbiQQ5AxASEFoltEHxIDPqeyRkTEw05NPWMLLtcM0P9xpCEc7O2Hd2znddhGq0quVLaRuL3zDr4I8FFUZbrctt844yAlnyMHL7j2x+52Tc4DjmIpEZf1HfmpEFTIOusqkAfbKH3ZrapjjBVN03w3OjV0w/fLKcIkxZ+/mfDO4exgOqeYCZQaSQ3VrW5dKKrt0q8I54Pua65y/cMkIyFC7Sgnq2rq2ZbvIT7Ba/dWtWlJp6VMY30tExymscnK8kvs5I/M1SqCbO448R9Y8ZuxdJ5RD8tGfT1KLBpWpcc1ytsuXk8jL9uEWFThJKzntiiwPASH0PPwMadiuf6ASZCRNmpiGvd+WsmXJaGQgxUeyfTPreMbw9p816j3DWdKbJRHPfPX1do6uP3FtjNiv0z9bTYiCcnjzTMuRQbOBD/VPitgjrnm3tnWMDKSbd+xXNon1g0JF9wPO2eQ4abgxKJDEjbdj93sHCYfL1xu/F1RWSieRQLztYW0g9jtCX+JQZk6R7Q94rh2mlXmUuT27Q6DTRRFMu5UbvUd932lsfKRB9N6qX5leev7pqKa37jpIS9dsoeEftHPaHdINZxhMvx13JoBAKHIOBNOXcnW70aBeLQ1HeW/BvoaoFjAnDKYE8244bcffAT88LJxSpEhua4rBJcacvZvzzQj1HuYEc7sDvpNnoS5uhQaOmWN7E1OhfveozNBWbQQK18yR58j66ysOIgi8MLBnC6dwOarPUX5xklZy8sw4GqBUvgsBIfQxuCh++PlElKNsoGZgQvDNd0cMcj1cZcBEoqHtKr09SMXCSR9Y9g6a/O27DymHtQMGWcmaKYNhu4+Mi89l+5+lLNIwL50+wNAUwxEPqZpxq/BG454G4Q2mcD7gnE3OSRpu+DiAuEIj5S3QOm3ddcDWxAn1EU0IoT7hpAnnrAolC1Bk3p+4AAAgAElEQVTV8kW0EmaEOlmRzvpCn60cHs3zbJex1lw3WviyAGr6YNpd//UewscE2WFx0Nml3o2XVOItxNCHVg4fQiQosUuA42/96oYzDKbfwbwv/mQ4OQc4B5GXy7agvWsnR4uEhPe5gDoA2znYe8fBeTcQvxy3jDhcw18CYXd1oj+ZD/iI1HLij7M0etpiIyOl3QGVS4w5e3eg9aLzTnP3MJ21GigLqI6skzowC8E82GUydvLMuF4X31ko7PZtnGbbVbvbbKtEXhzlFydpJSfPjC0gUsESASH0IVggIJQg1oj2gms1bxk/axn169rMCAUWKAIMtDzmgkxqGdKloVYN36CsNrG2vdq8BjXK0BtlCxt2x7qltQqhOESZe0BT7L0ZgLYY5h07VozTegznA+7bgJNNzlfWSRpuQ/a2b53TyCvelNbNVCbJAcp5s6sKLTpv6UatlNacZEWc9aU1kRaVOOHLgm0bxB324winF6i8XvZVy8dzHBaD7XdMyDnJOcA5iNR4632lMWxp5LTwFoRK7d5/Ii2a0s92aJx3Y76K9AT77VLK3AeH5DPn/qavtn+vlBv1qEalYrZt+1Y4dfY8Nerwsa09OJcYc/buUL3TTvcwYMXJAurFGt8K+H6Zi9mM0d+kwezOXCCP6El/KYUKFEq6hRvDniPPkcXhBUERcJt+RCn74GdnV/wl8vLKBJPIS1f5Faqkld6+6kbmscNDfrdGgEfodQ1o7/NZQNxqkBBoyM1l87Z9VLxIbkP7XlbFaHdSdEwxEB4TNvTIeIhoLQjhlS+X+lP/zfxUOsvmxs9abjhkQpsPG8HXy7xKe1SW2MeUTf2YjzrZdpXzAff3cN1NjpOG27ddpw6POOzMHdvbyCbpjVQDrXtl5Qi9dZm1TTcnWVHA9bVDrS+lybRbXxxyywlfxmnXdgHaVOA4LMZmv2OibZ29JBCcRiQolWPCrnDejZLKfwUx0M0aeWjs2/ccGdRtIUhL577jaMKgzpbdjgms0aAO3tx32jswp3sY5DhZQOGv9aEKIYnbYd9iZ+aJDObmclFlqkaENviNeUM+260z/B7MmM3P5cjHlqwOLjp1dJVfnKSV/vqhm2dGZwy6daxjYuk+JX7V4xH6+DXWGOstrs++Xjr6rg+fTiZOdCoUphjQpnnIvYfg2zkNQrNjLnCMyvDEYyrRVEFK9kBSW6w4H3Bc5a/auNPwM4hQhMFcYMtvVThpuH2f63Rzhs2t92rYS+ixQcJMyY7Qc5IVcdcXh9xywpdx2sVccSLVcBwWuf22fXksKnDbDnYv4VztYzicdwOH3S1LRkfLmgwC8Fr1jlq3hcEmXeNizdm7ue+0dwk53cM4axOyiOLWS4X4heIoXPl9mYtOfgjf9hHRbfS0JTRlaFftrnHHzJG/17Kc8NAc5VegpJXw+7IrnDwzds+W360REEIfghWCcHGtGrxxVybOmQvWGqEorQrHFAPP/f30OcO+OJX68xaY/cB0JyYL5wP+9vtj6cKlK4YDXnh49I9Cp7dqxGS3oz1bN/KKV+h15bA5ZVg3I1kYPsi1VSbLtV/tNmzoWzV8Pcb6zVlf6BSH3HLiuXPaRb85kWo4DovcfnMWAqdtzl7CvdrnvBu47UNB1A+EdYXmfPr81YZioYVyirYqnKRrHKzRJw7e3Hfai4nTPQxyHGfJN1v01TLB0n0HdENemp/nNIa9b1848hxZKMG+UqGLnRSzGZ3b5SKYriAqW9ECLxrZv61KqJRfTs26YitqlRNc79e69wehj2XTH7tTtFXadI4pxifjPjOy0sJcZdzHb1OhfDlVPPvzxkufyxQZxN/itdLImeu3bvSG37XP+YBXbNCDVs4aGE0jp/uCcdJwW7UxZMJ86qZs4q0K5jl92jSU/ok0huMmCAeSgSFUqF2x0zbvPfATzVm8nkb0a2/3KMe/c8it48ZMAjHRrm6kGo7DYkz0WxdHTtucvSRQ/yzNR0x32px3A/b7MLFBQZxxOC+jpE6FKFA3o/yS9iinXd/CSbrGwRr94ODN+WYEmiudPQyyHGdJhFZu16QqPZ05o+6Sjqq3WZkImgu+W1t27VcZYH/ze0jAwQ6KKW/s+Z+P/6GisO2LcpyGzwWSIQYqHHmOrGNgHAjgAASfk+PqRl4nQy4eDZmr/9ygh1VY62AUfZxbCQdDk6ohQOD+IPQhAILzCE7adI4pRula76hY9YPox19O0gRlEw871CM//UbQttklK7LSyJmxCJQKnPMBr9u2P80b1zuozYWThhvj8tUeeMe6c+9hFSEoF/0vY1pCxlo451mVnXsOGwco3cJJM2/lxGZu/+CXM/x2h0Nudcfnr15MtKsbqYbjsBgT/dbFkdM2Zy9B/4I11/Edm9N3w589tj+8cDPmWzhJ1zhYox8cvDnfjFDtYWYsdZ0lew6cYvhevfziM+rAlRKJm6PKsL5tLZd5404Do/0OE52M6R+j5nUr+c3Fgfpt1eGhwMs5DMXV8IkLjWRniIKENQPH6Xfb1wsYnYwjz5E1D9LOlE13XzDXw0EICfjssvr++ddF+mj0bBU96gBBEYbbrxLK5woHAbuM7Ob2giH0wZrBBYOHyNxBQAh9PFgNgUKI1QMxHt/HGEHtVv1owaS+xmm8iHrZddJhc4YOG7vEylnOG1kHfbz6z/Vopj+Bnr9QZUj9/tAxI4JFamWTZ9Ya2EX24abhRm4Af2XQuHmGhv6Asuk8qiIQ2B2Igtnk0G4waeatnNjMY4FG01/hkFvOGuG2G1NOi3Zj4vbb7vlWv8d024H2Eo75iO94gn038BynhwFO0rWYxhrjiYnwj6Haw8zzpuss6RupxvyMN1U42VAWhE7cCt80FfAByqtJQ7pGy1xs5zjNkefImjHgJNMKhOVBFboXDuNIkGhV4CPyVIa01KJepdvRoy7Q5Dkr1Q3+JVtzHfNznZp1cczgQrl+EuKzhNCHaNaDTZvOCSE26/N1KsPrA1RRxUJ/q8snNFMlqNqhYtgPHDuPNswfajmyuUs2GHGavdEFoAE5dvwUNa1TwbARtys4QHzQtYkhD21J/bYDDNu+t1vUoPrVywQWV9f0JWt3jhbe01zZzsaQk4bbakzI6utNSuIvQymXtHDSzMcWsbVbAzH9O8dp0c6kIab7HhvP5+wlHPMR7rthlnd6GOAmXePMEwdvtBvsNyNQn3X3MI6zJAcvp9nJsQ9vVyGUEbABGuktityblT8IA1muTreA4Uk58hxZO4x0k2nhOXBCNhcEkUBEPeSrgQ+XVUHoyW3Lx0YL1nEvos1wzODssJPfrREQQh+CFcJJm84JIVamTlfDZt5cnng8NfXq2FBdTeaxHBmilyADJDTsiMc8a+E6IykVog5MH9HDFhVoynELgA0W9uQIkwkNTc2WH9DGBcNs5YOtwEnD7W0TH4IDR341HHNhWoN04cjUi4IIPLMXb1DXwBUtu9hjwCQa3LuV9jA4aeY5xBYdjC1yy22X47TIcSbj9lt7UfipyDloc/YSjvmI7zCcvhtmeaeEnoM1JxEX2uXgzflmoG3OHsZxluSYkDjNTt6ww0eGfxKUTONmLFMmPimoXvXSRix3JEScOs/jTI0kYv4KR54ja7cmnSTT8vqWeJ+JscOHSyfnDByYxwzoaNT3FiSiQvjQzyd/YNlNjuM0xwzODjv53RoBIfQhWCGhSJuOq9lr129QSpXoSbdgYzAXpDyHNkOngNDjyg4mOtACDO7d2kh0AU2IXQhGPB9X3evnDzMccGuqjWP9/CHKeSmZEf3FzrZPp3+B6nDTcMO2r41KqgUCf+rMeUrzaEpKmiSJir3fUSszZbB956SZ5xBb9JdDboMdbyja5TotmvvuxJkstvBCf7kHbd8x7z/yi2Hz7M+Bzmum52+OL12+ZmREXr5um23Gas4a8ZV1ehjo8dEkqqM0lYiYBQfePoOn0bHfTlEPZVsN22urwknEZX5uMHs355sR9B4WguARHBMSp9nJodF/7+PJ9Mtvp+mhh5IRzDyxb+M7c1XdBqM8/2zmgOSUI8+RNa+NUCXTslrHgcy6Zi9aT8jAXr5EfnokZQpDs7/mq11UoUQBQ5HlTYKJA5Nv8XWcxnceSRRzKuVXrdeLW75XHDO4UO4lCfFZQuhDMOuctOkwpxg4Zq6R3AmOScmTJaUKJQsaV2oplFd6MAVXqn27NLEUrd68j3Ioqk8/HDtBG7fsVck9eqroEv8Srm1xtWlX+g6dQcjIeE453lQqXcgI24irRGzAi6d+aCleVt0sIBukXQnk5GknZ/V7086DVJKvV6hu1VJRyaHgHLdARQ6YP7Gv5aOtItWYBacN737Xczhp5i2J7XKV1Td65E9beJyQW9uHOajgtF2u06Jv13SdyXzlnPbbASR3VeUetPFAkBGQ+NVqT0FBUjt/EZzQ1pSh3aKyw0JBsHXXAVq+djvt2HOIXs33gpGXokwx+6R4dlGcgsFEJ2oLbgqxX0FzOW7GUjr++1kjjOzQCQto2YwBwTSrLcPZuznfDM4ehsHZadmhxf0/e9cBJkWxhEtEkkhOYsaAiKigSJAMkjOi5HCSc8455yDhCEoGAQkSJGckI0pUUUGMqIgkUXmGV3/jnnN7u5N6Zmd3r+t97/M9b7q7unq2p7q66v/3MvqMbuqkxkpmU0jsspOjEP7ajeCs0f+liAY+sZhvn3DpZdqiN1kyLZm0rv5j5ph6l4f2iDH1HAprkfJqlLvvZRqcqYlE8UPKoXdgcWVo0xFhQtpKm8bVOXc9Pf1w6ReaPm+NQA8Y0bu5rnZATpm5cC1duXYjXk46TtNPP5mDryJriI9yIDnEBFSDxs3jyvekNH5AG3rskfsE0ROugttxOyNBLt7mXYdFdPvlYs+LOcBh+u6HS6IQR09WbdhDgB9sxLjTGZmZ9jIzBuIaGNGWSqUL0j/8H0iwIk9f33ZouBEpP7B+unAAfORQ6A9FUAf53+uJHlKNtl25EvkTdCNDM++0Ywvl7Dq3Ru+F0d+tjOt00aLZYrJAc7Cit5EN9P4uc9CGowZHHpHqMvybLM8M1Xly5Qg6HAhgBk+Yx0zD+Sl1qpS0ZfcRwXaNiB6c+Hss3BZqfxs4AGEPenfT+4xAUsTQMZRBbfEdgJCCUbZOV1o+azBDyzJPBDv6+zn/Wk9k0pvQr8zeLfPNkNnDoLcs54C/Tc2mkMiwk8vWEcm0l2kb6P2zQqYlk9Ylsw8F07tlj/Gu3sAH1zkx8r5aX0Hl0Fu3mW4LbG4+xjwztOlwJHHiTc6QUj4RH2Su6jdKfcHVVs+29eiJRx+Ip1NM59EiDx45h0ZOscPTJzO3A/gIo2gXMFo+Qe46agKMTv9afe3k2+JDv4vJPTA2HPrtyyfQMkbdgSNkhGzjG9sOUo1Wb6tEHU47ttBFxrmVeWdCNa5MMVnAj5lJZAkZ26CtzEH7mdIx4gAPgqb8eZ+M24f0dILjjQMjmJvv4P+g9gbO/JOPPSg7FZEiUb/dMFq/ID5coX/HMqgtqC/Jx+k2X1z4TqChjOrTggDX14Dzr42AAWTTm2T2bq0NrH4znNjDTC1uAB9KJoVEhp1cto5Ipr1M20B2tkOmZWq9dB6yGvyCb6EVfPMQOOza6jWxv+iJ0Q2Q7FxU++AWUA69w2+HVScTV1hLYwfEw4XFRxb5hkYOPT5Iu1ZOSoDnjj7dLEyFyWRuB+BIv8ORNBTw+gRIOcjpdduhRwFv3RqlRSEsIl2I7OXmm4Ex/VsFxELWvh43mJxj2OSFgh0W148glkJ0s3f7+paimVbfEdlX1Gnn1qw+suPKRFBlislk9TZrHyvPfcxQqj5EqmDtcNOFd/M9ds7Pf/09lS7yvHg/Cz7/lCnnHqk667ce4PS/g+wc3yXaVmAErZx+AQOzeiMP/2WOmh/ZONNsk3jPaVFbXqzYig5vmJGgH+wb4OBIxs58h9drid8h9s8TXDtQiomH9EQ2vUlm79bqZXU/kNnDMK6MwyWbQmLrReBGsnVEMu1l2lol0/K3j1OpbFbfMdRpaOUX3luWrtnOdSlPCfALPZGps7D7fqh2ty2gHHqH3wSrPxzQnuMjDDKjbHxVjOgS0k9KMAFEsOp9n8rIeUeBkH/EGP/fh9ri8PTiupO5HcDV6xq+jq/Gua6ZM6a9fT2/8fb/b9O4mmmVtTTcuoyWQXpEihEcgAyMhW9G8CFFAVKXlrUJV+aLpvYTuL6/cjGzFYZXq++ILOqKjHNrxi7BnpEdVyaCKsOTIKu3jM1QR7Pv8KkEaXTT579Lg7vFCOf8LuZ/MBKgX6Go9b1tB+lHTuOzUqiOCCKYi3EwwMHdTFsUs2oFUefjpz+n55/JaQkNKti83nhrpXDYg4mdWzOZ9CboIbN3a+dhdT/QtrW6h6Gtv8P1E94PJsqrV6MMR2BfNXq1EvzdbAqJzEFCtkBepr1MW6tkWv7G9U9lw295JaesohAcdWBmReYd842BW3Qcbra/M8HssHHPma2zsNyxahDPAsqhd/iFgKNrhKWuHRIfz3Vb94vI2EV25uFcVuQ88tp8CjaiaXYqYmzHBLK3A4hc3KbxvkoZOI8eB5iShfPaUUW0ad5tHBf4dTNsL+Mc44odKTqADPPl38ORKFKtncjLNytaog4zBxEnUFcwDliEL/9ynTLxISoXp1RoU57M6m71OZlxZSKotnkS/p2gjN5WbaR9HvCRQKNALrtW8FvBb6Qc58WjyDWYfP3dj5TmnrvjEbyBXwI1MmZFmxJmJm0Q/aKoXCuXr16nzTuP0IAujZnv4nHdoRGJDybghth76CRNm7da3GT6i8weKJPeBD1k9m7tPKx+M2T2sGB2xo3GtHnvCrZxq2I2hcT8QSJhcatsHZFMe5m2Vm1p5nnsD0gDWjN3uJnHxTPa4JfpRn4P4vBYt/UQUwd8/zHM1lnY1U21u20B5dBH8JvgVMTYjgl8twNoq2V3tHI7gA8BPshWiu9AlhFI0E86rhlAQW43zvN74dmcAZ+LB1XH43//42VOL7hTRBKB2asnGPvAuukCGtTn0J/+9EuBZOAjpbJqS7MHEW2/VlFX4AB0HjhNOPCZmTYdt0AoPJ40uB0989SjVlU2/bzsuDIRVBmeBFm9TRsowIOAfd0Ndky/KLyZNLox094mEMThNzhtRCcq9EJuwVOBGzAr6+xENA9Tw7gxXcbQ2nn6jsepT88HNRlS44A0AockUF6/l3ugzDrLtJXZw4KNa9Ypl00h8R/f7EFCto5Ipr1MW6NbCauIQrAfDtkvcS1YoBQ0vfG0tm/VqKruKwg+Ga38xTduXzKCFPhZ2jbVB82QqbOQ+V2otsqhd+QdkMFCNvrB6ynoVMRY1ghmHAD8yB/PcT89yw4kPvQj3lhEO/Z9KHLR4Wi+XPR56sW56EbpL8iZDST12gylRVP60gkmxpo46x3a/PZYU9PCNeJARvt5mjH46zNpiZ7UbztMwIE+wfOAc//4I/fTZ+e/odF9W4roqdFhINDfzR5E/NtaQV0BoUvzepWp8suF4roB0tAiJtBa9dZQU3ay85DsuDIRVBmeBFm97djK1yZ2wRpq2aBqAj6Jecs2UZPXyut2jUL6dQtGMWzlVyKvHNFW3MogMmq24BsDmPk9m5kjDv0lX+lMh96LNfO4rWe83ANl9m6kQ02YsVzwYIwb0JoevC8rH8T+Ynz124EJK2JlD0O/2H+1AgcRCEcr1u3i90e/gFk2hcR/XmYPElbsEU7PyiIKAYlKK3/+9SfteP9Dunr9Bs2dGJ9FFs9pxwM6D9a10PO5RWrrL1zTso+Z5OtxDVnnFrV1zXT4w0/i/T1p0iSUPVsmUyzyXtVZhNO6e6WLitA7YHkZLGTz15AJFXUjYmzHHGYcACDYLOac8yyZ0hHSChBJb1avkigGhpM+a9F6kWowY3QXOyqQlpAGTHVHN80y3c/V678yqhCK9xIW3Wk7QV42kDRSpUxOcIiRepP/uVyGhxD04fRBxApaDAoK4VRpU7hQC1CwcuuAUR7ThjN40KtxoZYMT4KXekN3FKRt3X2U09HAZJxWoM6AidlIcKj1Oe4+0ig4TEWYLA6szmZFmxJmts3Y6Uv9HI+/6MhHn9B97ARMGd5RtxuZwj8v90CZvRs3LkDkQf45ajbAOr3n4HGBuIXbFatidg9Dv/63nEn5NggHCnAVGKVHWdVL+7zMQUKmQB46yLSXaStjL7T1h3T1rRVq7vDt1BP8rjpzvRduuXyCdw2/1UBcKbK66rU3rLNQqJSOmF859A6YUQYLOdDwZq8hZSLGDkw7rgsz7I75K7SKc5iRVgAEH23hLqJExWt2MMSODuYYQxkQjCByDZIubTTaaK6IcIFRLxBjnlFb/N0MAU6wfny204u4y6KudBk0nQuoSvHh48k4NZCX/O6mvTR+YBszU7T1jOy4MjdfMjwJsnrbMta/jXbu/5CQRlK2WH6GktzPMJLP054Dx2lQt6YCdUZP5nMxfcoUyakiI9M06zqG5k3uTfs5Ijdy6hJDCEf0i9uy06LO4ppwFp7K+bApdBy0BamTVu5knof7780s8v2NajXi8zv8I/gwVr63h2/DGgfl0fCNFS57oE8fs3u39sCFvGSQ2uGdxS2LFaQv37iye5jMO2u2rcxBQqZAHvrJtJdp60a9g1l7B0KGwnemUJU2hoEco0M2iuYXrdxiGgwi2m9izK6J288ph94BC8tgIQca3uzLf/XaTZH/bSdi7MC0LXVRqnZnEaG/N2tGgRCDSDzop32CHNneI2bT4mn9dPtF9D2YICq/fe8xGj1tCW1hnPtAIrPByhDgQBcUBp04c46JtBB5TSciJ75Dze2/fcERsicSqC2LujJ4wnx2kHZTHiYbS5vmbr4JuSpSMYoVfFYQmHEQV0jsqM6W1tToYdlxZW6+jHTT+7us3jJjIz96EKd1IVLqq9NAWle7PpMN08hwC4acea0AGrZvh4YCX95fhkxcQGX43wO7/ji/e50GTOHc/aTCmQeaBl6OSUPaxYvw6c0tUEGuXVuAeG5c7FJD9maZWzO7uum1M7t3g9QP8LmABK0Dh54LfhGsqN18oCFcscwe5tNd5vDmht2M+pQpkEffMu1l2toBNEA0G/s0bk1wyFvBdTFIs8F3A79NkMbVrFDMEMkON3YF8j0lWNwBsYxD31tLN/BN0Al6e3p/XZPrkSgisIDbw1PMzVG80LMJ+nG6zsLo3YjOvwdmPTaaq3LojSxk4u8yWMgy15AmVHPtEb0TvHZQ39XelDmrBIRe1bKFxWZw8NgZEUkEIgdSbfC3+rXKUEyditI646MaDCHIf4P9mTdJOAVFC+ThQ4Y+woMMAQ7SKFr3nCA24W+/vyRyZ8GyO2V4B5GLb0Ywr+soIr47pSECkra/YHr7j1mF18ZJkR3X6s2XHk26b16AeTXK6ZbVW8aGOLACtx3vr8+hx2GvaLX2hkhKeE4rSe5IkiAXX/v3opyKs2nJWJE6Vr1pP2rRoAojbBWIewToHgtXbDFVZ+FUQa5vcBTClqjV0TCSKGNr2bYyezfyjLe/f4weZTQjBDPwzy8ufC9Ie4yYuu3sYU4f3mRsBwQp1AtoBb9LPZEpkEe/Mu1l2vrPyQygAThoxvZvLZCpkNZ16pNzfPgrI5z5H/jQh9tkgD6A/0RP8M3BDTA4LMDIjrQsvGfgXME/3RKn6yzc0jMa+1UOvcerKnMNGciBwUc8deqUlnJm7ZhA7wSv7U+bJoDo+bFTZ+na9ZtBhxzaI0ZXHSeiU9oBsMGu2bxPYGaj4NWOaAlwCjG0ZSAIy6adR3H6QX6BHexz1OAwAe4P1+16AlSa4W8sFJEVXxFxSS7C7dOhgWEepX+/WlZKO3O128bOuFZvvrQ06TggAj0FDhJuQ/A3OKe4AanOfAdmxY7eZvsO9ByKedfOGyGQn4qwEz+WP75ArsFBEB95OxKMvVl7JR/ovcVvo2j1DvT+mimGw8oW5OrdXukN7uUeKLN3AxlMK3cwclZ2vr1EVNaqmNnDnDy8WdXP9/xuTh0bwreFgdImT++ap9utTIE8OpZpL9M20KSMAA3wuzy4PlYcxrEHbFw8Oh4SHAJQlRv1MrzJ8Y3946UrIroP1ngtmaOewY1Sbuy+A6qduxZQDr0D9rUarXZgSNGF1oFB2sSFby4SCFhASBUodcOpcX39OHnFblY3tyDbgJZhFLkNpiMc8xoVioorzYWMHANoL38BKy0c/aScW+xz6PEMxj1ogGEPxxZFxM25iBjOKaA2QWh16TKKiK3hRpspYDa7FmShkMnOuDI3X4juI+0qOSMo+QSHIRQjWslRtqO3afsFeHDJ6u1c65BT3NrgoAgG1GJ8rd2mcXWRWqcnVtmbKzfqTQMZJx61FUgna1a/skCh8gnqLFZv3EMTBrU1nJJMQa7M7ZXXe6ChYUw+AKccaU8bGP0GB3WrgvZ6e5iThzdTugXYG1AL1LdjA3qBIYKT8AFVK9gXzYrsIVumvUxb3/yMAA1w+NqydDzXwyRjpuVutJ6Rh7T7GJDRUHdhhEgElJvNuw5zdD5twNQYo73E93e8W1YIrYyCbkC/AgTmU8zQ7i/2Ek3MvjnR/5xy6B1Y40Bsbqs27BV5q0/keCBuhEBFbaBbn7tso7gSa9e0pvgRy8i3nEPbqP0IW2xuVsaVuWI3+sFb0cMqZBuut7XyJxcJ7WbSniXvbjcsHITjgYj6lWs3OPH8v1527DsmIu+1KhWnh+4PHGFDPviuFZNEgSAcehBUAdECH3AjSEFEAt9nlBItNjlyK0FoZfUQEmoH1Wcl2XG1XAdm3g849MtnDooXkUJ+OfKV9zDOu1mR1dvsOIGes+o8WGVv3sJIOijAzc3Fr3AYDnEa3LO5H4tLg0OOLAjuzNxcyRTkytxeBbJbqPZAJ/Zu9IE9YAMX8kNQRAy0GT2xs5tmdv8AACAASURBVIc5eXiz+06/wvUBK2YPtts8rp3sb1KmvdW2dgANug2JJaQlNWIkmyNcSwJiODDDprknlah/WrhiM1UqU4iqlXtJ15YIBCG16buLPwvIW3yjkJ//+ZffigCUVTFLaBUv6OY3CDgp3j98kgD5umhqX6sqqOcNLKAcepdeEbOkKsC8BvvjWd7YAfHWvU0dpuE+xSyqxzlSo58jF0h1UMeDRMjpAkf/sWSu2J2OsluBbIMzrZVrnFeI2w1gdhd8/indtwF6I3cxJ+PQa8XHrJmbsey1EGHaZ+A4oQgOf0e0/rffb1FujlAgnzHYIcDXHh9CkF6hoNgnICRBHu47swZZeoOtslJa6lznYdlxrX5IpzMO+9urt4lDFlIZ8DHCTUr18kXj5SgbXTLI6i1jP6tztsPeDLucOXuB0+B+DaqqmdoKqwW52sFkbq+83ANl9m44NHDk4bihyLE8fwPy5Mph6nWxs4c5eXgzpWSAh7oMmkZtm1SnRx82z1ocaCyrvwv/PmTaW21rB9AA37PpzNr74anPgqanAsxg4+IxuktRoX5Pka6D3zhsv5B5WnDr2bzrWMPofqCO9Qit7L4Tqp2zFlAOvbP2jOvNbAQVBTCr5wwTDh4iVUA7wJVU1cZ9aBtHcc2Klq7dbBuZ52Su2P3HtRplD9TeLuwk8hnf5ug8rgD7dWqoaxJE2fevnZbgGTMsntpGgOVDjrQRiZavDXK/Mb/yJV+kdGlSiw16485DVKFkAZGCgytRSELYzfjuKuZ64yaKalPpFkvKvBeB2tot5tX2ZfVDirZAWwAMJGAY06e7h0oUeo5KFUmI9mJ2vuu3HaDKHBkLlVids5a9WaujFfZmu++I1YJcrX4yt1f+a/HN9z8J2FrUULw7d5irSyWzdz9TOkagC6HGI3/eJ03DgwaakNk9zKnDm12j9hk5Wxxi8jKCU/q0aQTClk+swOeaPWQHS98w2z7QPGXaBrMbOEGQL++0gOF2PkPXov6mTqvBcbVagI3evy7hd0w7vlVCK3/dz577hou+P6BfrtzgOq80An7XzUJcp20Xqf0ph96BlQv28l+/cdOQwKEVI5+g8A0Onu9Hh6gNNo5AzmMwda1+/GWnLXPFHmhsK1F2kDqBaRGOGhzaCoyWg0LHYMg2RnPFhor0FaNN7uAHZ+jFvLnE5qtNhzh28jNDQhaZNKP+Y+YYTUH8PVhBMfKMhzJE4Q5G1cBBE+RY5bhAtw/ns6ZllCG3xMliXjNcB4HmgbXFISYN/77MygLGcw8kc5ZupOacZ47CxZfyP+3KR1g7rlXnwaiQTQ87Gnm5wyYvpE07D4vCa8DcIUUQSBrYm9wUmdsr6IXbUOiNPeFLTosr+VJecesZCFLPyXnI7N2Xr1y/rTMfEs9//T2VLvK8sDduCa3kk/vmY3YPc3L+VvsCYVkweYVTu6JR9JC3Tu6YS9v2fkCjmCdi27Lxjk8fN5JAk8NvYcLM5dSzbV3BFItvEdIR9USG0AooYUMnLRDBk6yZ0tNFrvnadeAjGtIdXBovOj5P1eF/FlAOvQNvg8zLj9QARC2KFnhGRJaqvFyYjp74lDJxTr0Rw6JW9VA79DJX7IFMbpYYZfbi9eJDGMOFp8PYSe3G+aZLOLWiBKO+oBjYSBDF1Iovh37S7BWW6g6s2tvpNCOjeWr/3rH/FErBtRntmta4vcHytStudHAwsYucYmZ8J4t5teOZIfJCQdjIKYvFbwppaKhNqVCqoPiopWbYTz0JdoDaxLciQCoChj9qY8Du6ZbYudWQwY6GUw2nsAszS4InYhFzRqDw+lc+DE0c3M5wmsEcl9SpUhrCbWo7t3p7hUMMbtcKvZBbMOoW5n/iwBoKcWrvRm0HDiO4VUDxoVFgwak9LBQ2MjMG6giAx+8vSEsyI60aVTV8TK+vQO2dGltbtO2vJFBn8Ju7ev2GQKBxWhCh1woCXtmzZWRc+qqU48F7nR4urr9ydbvTqL4tKO/Tj8f9OyAFAW1rw6LRro2rOmbqEP5waMr7lElCbQE4VlqBk5U9ayYueikoomRmRUvXjgi/tirebB9WnpO5YsfHa8KM5QKLfdyA1iLiiWtj3GikS5taVw1ELUFQlZ3rDXxoMYjuV2YEBbDPGgkccX97g9Gye5u6VIoje2bFqkPv369smpFZPfEccpSB7KLFer7Gti7NZF/APE8gRonlJgeXLeaVIfICyyw+YECHycbkSj+wozR93hpxzT+id3OTM4j/mC+1SrAacy2GkeNlZxAnbzWsjA+EFBRqA5Pe97vCbxI3V4FgWP371joucFKQ3jGXbzQK5MtFNSsW01Vl8aqtApUr1+MPiecA04lCQKSQgf1ZT5D2kiRJEkGS9jLnogdCzrBiByvPOrV3a8fEvIE/ridO7WFW5urEs/755L4+e4+YJWqJ7s2SMd5hGxjsPsEBfcvuI1To+dx8K5uWEd5uiGhzPa5L6tyitqF62r7g8lxgcIRPPvuKmjeoLNKe/MXJsQ2VC8MHjG6U9ZBq8pZtTh8wyaM2jQjfuwK8x3y4ZXYYzjZ6VFIOvQNraXT6RwHj3kPHqX7Nlx0YLX4XcGaBS6uFXek6OJbmTOjh+lW53cnAMRrVp4WouMcmj0jnnoPHBerLtBGddLuFc+pzQn2OB5wJ1ByYcejt6uzfzmo6RKBxraQZyegNjHHUY8BZ8wnIvao07m0prcuqDrLFvDJEXnBQcYjRHmxFAeKrXWy/J8C19xU9N+owgha80ceqSQyfl73VWLtlH63fekCkoWRlZxjkbZVfLmSYjobD14F108VH2Pe7Ov3pl6LwetMS/eK7YJPCzUilBr0Mb75QzIvIHd5P6D9/+WYq8mIesT/MmdjT0GZfMGrHOp4zbmNwiEPqCv4bSufeUEm/B2TSo6yOFS7PA4Y1kHz3wyXxrv7CWOmdmtemBrUSfidhr858e6QFHcC3Y+z0pYZprcHmj7okIDmN7KN/wJcZ22idnV4bPUdcO5YRrLUMUg1u+Eby9/0JDXgEEOJ6DJ3hCMqR0zaLpv6UQ+/AampP8/7dodASGw+uU7u2epX8sbtlrvbGc5QbEFZgW9UK8jOzZckgIheVShd0YIYJu5C5Yn+t5WBaNnOgKOYEni6IlRD1hLNlhBFehbGzZ4/vLiJ3KO55jeG8kIKDHHpQXJsRuyQ2vr7t5GUH0gtRCzgviBK5KXCSsIHjJsIncPj2HjphC77MrK72i3n1R9ASeWnxtbWtcGhEgTnYFbVzRkTX6OCnV7OAOgUwL+Kw0YPTd5wWmVuNmQvXCae2IcPdgUAG6RtYg4q8ByD3X0/qtx0m4CnxEYYOwMH/7Pw3NLpvS5HOZkdw0K7ISBtGEX4fIzD2A8D8je7XivIwYhTwuI3Wyl8vYLkjLx17ghV4Ujvzk9m7ZdKjoKvsHmZnvm618d18IRXw1RaDAq5boN85bpAKVWljm00YUWZ8Qz7a9pbu1GTGDgRpvZJrwABDCRhJp0XriCflYlikM6EGBrDYgFu+wjcbOCwD1S3UIuq3kprnGwi1ftEwnnLoPV5FvcOAVrVACCwv8XX4qjeHJmB/s4q6YscEMlfsg8bNExCOyJsELjgcL2zmtRme0egDjggErmYB4Yi8X6QlofgNV+5mRIbERiYvG7pF4m2KGZsGe0a2mNfM2CBS6/B6rQSP+mot4NzicItUFhS7mqm1QKpIMEEaCAjVgKXsxgdZ5lYDkfWVbw4RheI+wcENvzGjojvc8iH3HORVKDpHtDz/c7lMIzEhP1Yr+Hgf+egTkXIzpLs++3PN1/tTr3b16ePPL9C2PR8wvF4fgfSFg5tZp9z/kG0F2SfYWhtlnsns3Wbe7WDPyOxhMuO61RaR8vo1ywhivnL1utNO5uvwF6CqFcj3lAjaYM/Hs28t3SDYs9+e3t+0aloUJxwgz/DhHIdHPXFqbN8YZvHcTU8qyIPDucj9MYYIrV2lZFz6CwplEZAwIi8zSrnR000mpVZ2zom9vXLobb4BTl1t2RxeNGvRfZxgCvWHvOo8cKqpQjaZsQO1NXvF3pmv8Xcy4gpgrECSgn9+ceF7kcvYLqaGrlpwPJLyKd+XPoIP+fVfb5pGa5EhsZHJyw7H2xR/QwN1IZwk2BU9dEQaCJhMp81bLQ6E/oKP9bqt+0X6yUV25gERikg1iJLsoiGFwjYytxpw6LcyWoZ/mhEi4EZsxLJz80cGSpo0KdfGZBFoQEb2RsEcDvnJkiWl8QPaiBxyFMfiFsRoP5A9ZMvO2257GadHZg+zq68T7czMGd+QQLVjOMQA6QrOKKLNCI7gu4HcezNwiDIoTrJj+9suVHjuSDsEUp7WP8D3ErcaRoSE2kj/P3//LVL4UHdVtEAeQ3ZymZRaJ96zxNyHcuhtrr4bV1uoSo9k9jSzV+xg/dTKHaIQOKMojjUSpOsM6tZEFNAhql+/zTCx0XRqXstUjYIMiY1MXna43Kbo2dcNpAV8DLcyIyly9lHMBiSShx/IZrTM4u/IWQ8myKW9+dsf4kD45GMPmurP7ENGNTFm+7HznMytBnC+USDapnE1kZOMlJtpTFDz2+9/kBHOt0wKnZ15OtVG5pBtV4dA+OZW924Zp0dmD7M7ZyfayczZN/6Pl67QZc61x16FtDKzIovihHHsjC2L5252foGeq1C/B3OrNBKHap8AenkQ36ZZrYtBgGQps6Sf5/3cKLovk1IrM1/VVqHcOPIOyFxtaRWwipwS6oIbra4yV+wyUXaQ0OxbM1VE/bBJwzkEhnFtzr00SiuA/jIkNjJ52eFwm2KXNMjujwSkTlijssXy0/pt+wW5yJ4Dx/lABjzi/Ha7NdVOxim3iohhSqEQPIQoJDCtfQykyFd9ufgL1L9z4yA4/P+5pjIpdJiameirGyaQOWQ7qY/VvVvG6ZHZw5ycs9W+ZOYskwICPWVQnGTGloG0tmpf/+d37PuQC1FjBcQuUOFuE4t9yYAULXkvtk6wh+8H6lqM0L1kUmpl5+xue6MkvGCjB6M4c15bFaF3wKYyV1syDn38wiqG4uJr6pXv7eHitsaChdBNkblil4myA11my9Lx4goQOfdblo4VcIxm2O9gDxkSG5m8bDNr4RZjoMx1sxm9gz2DW6xBXGiZj5khfcgpKLRs12cybX57rGHXMgdWp51ys4gYhpMyeMDIedCDi/N1jWgaCuBSMyOwTBGa2RQ6jOtE9NWO7WQO2XbGC9bGqkMv4/TI7GFOztlqXzJzluXxkEFxkh3bqp2cfB43owc+OC1IGDOkSyOIy7RAAVbGOsmIQO36TDIErgAy1nabKbVW9FHPJrSAcugdeCucutpC+oCZtBM9lY8e/5TGxS6No3l2YHqOdyETZR84bi59y0QsP3JedKUyhUSRFGimgWWMgkArYpXERiYv20vGQCeum63Y1ffsC+VbCIhR3Kb4HHqgcxSt1t4Q+QR9OH1glXHKzSJi2LGTto0MXJzRYcCqbmZT6NCvTPTVql7a590+ZJvVzere7ZTTY3UPMzsfN55zas7QzSqPh5MoTkZjo64Dex4KzCEIYuza/5FIO4QzXZoZVB9xkdhJu3Z20ZCANhWvHy5yR4QfxHxAltMTmZRaN967xNSncugdWG2Zqy3kgALCCqxqwMnuP/ot+pxxlXu2q0cF8uayrB3yikvU6qgL5WX34kirDOjhgRsPSmec/rFRgXL9lcolDKOCMlF2FBRt3nWYkt11lyCSwcaJq0BgGT+QPUs8ewW66HLa6TG7QF4yBspcN5udX6DnsM5r540QsGlF2IkfywVsIA26k+HU7DLUyhxYrTrl8REx7mBEjPOGiBgy9pJtK1PIJpNCB71loq8y85Y5ZMuMi7YyaUYyTo9Xe5isvWTmHGhsKzwesihO/uPrjd2440hq06S6+H5jvwOJItIN8Y1E3ddOToXpxd/3GhWKyppUt70MGpI/CVjSO+8UyHJaLhNXlVed27KAcuhtmS1hI7tXW4hWA5oNP5hpc1fTeaYxB6b6uNhl9O7cYYba2T2BG3Zs8MDgCfPpNBct1qtRRsDkXfzxMoHx8YVncxoWzTgZZbc6DxmnRyYv26qeTj4vc90so8eS1dsZ+jCnwDQHYk0yhkUsxhCjYG/1Ra+s9m/mwBqsTzjocMKqli2sO6xXKUpQSoY11X9SVgrZZFLoMK6T0Ver74RXz7uRZoSDFfgA9ERmD/PKVtpxnarlQaQct26AkrUrY/k2u3vrOpab642NAMpe/qYDBhbcKjPHdouHxANnGakrIPtzU5xAQ8Iegv0QQRmzopcqqe3jLSa/9ESciGh6orjxoMqhN7aRq0/4SFV++/0Wla3TlZbPGsw460yaxI4+IKf0ROYELjsp6Ldx8Zh4cJEgrajUqJcoWtUTK1F2WT2N2ltxerR52X/zRvcTo4jsZ8QeHGoEaZiOeLnJOXndbGRPp/9u98CK/O99h0+JXHKssU+mz3+XBneLEbmkwfLLvUpRgo6yrKn+9jdbyCa7bk5HX83qY3TIdpOlWybNCOlkMxeuTfB+ojbo6SdzUHuG7zVbB2VlDzNrVzeewy3l0IkLaAfnVwuSIXZ4yxXPT306NjAFO2yXBRlz8S9O9c0P+eVFXnxGQKyCs0LL4aC1gZWxwcy971+4SBSRImCnhW7FnlauTndDBmXZNbCKhrRi/W56nInlnn3qUVGjNuKNRYTsA9zGJ0vGN+J8y9CrfX1Dbgo90jTtnNwGRpC1XyS2Vw69zVXTy4n2dYliTSO8V1C95+N0my8ufCc2uFFMmQwSnAbth9PWpeN0tXPiBG5z+qIIDukU2kgrcgerNe1riDaDK2NsnL4Umc/PfysKehG9lSniszsXGafnBDNTAhrQiHnPy03O6etmPTuf/PgcpU1zt6gFwUd7BV8573j/QwE1hyvnMpwmVbNCMZF2YyQyB1agCiHnMwdjVWsFuawglypX4kUqywgwgcSrFCWfQw+2ZCdYU9Gf2UI2PAtCKdxgIIUOv88KpQqI20IjHHmtDe1E9IzeA72/W2LplhkoQFuZNCOko/VsW4+eYHI9rcR0Hk1zJvZkWMbUAprRrMjsYWbHkH2uY/8plCJFMmrXtAZlzZRepJ9MfnOlwEk3SsGTYUGG3uA0CCSjpi0REfoTvG99whj3SwKQVFkduyF/u0F0iJuDaXPfFWtZj4mzcAuPwN2bS9YLVdrH1JQ1qW57q2hIL9fpRoun9qMsmdIJjht8n5vVqxSXKjRr0Xqxp84Y3UV3XBkUO1cNkgg6Vw69zUXW5kS/t+2gwMwGMRI+hPgbCGLy5XlCfBD1BJta7Pw1Ih0BjJe42sLpGI5iKS6e0ROrJ3CbUw3YDBTzG/i/dauX4uhKavFDx/UnMG/zP/ck/cP/gQAv3F9QRDx3Ui/KxljZH53+nLDRwwHM8dC9HD1t6qSapvqy4vT4dwgHBikthzfMMDWWFw/hoIW6g4zp0wpWXTelRkw/8XEGORCcrVOfnGNW4DLio/ADv+t4R5CW1ZsjPUYic2AF6tFuXHv7UY2bYVH2KkUJ9pBhTZUpZPMVl8bUrUjDOIrajZ2cJau36TLrOhXRM3oPwvXvMmlGuInZtXJSgsOSmfczkD1k9rBQ2RffKxxWEejyCThEStfuLIrn9USGBVmvX6QC+jDZX6zYKuA+bnXsT7/4WoA0fPHld3T33SkIDi4CGJj3dZ4v5KknHqZ3Zg1y1fRW0ZDyV2jF63D7O4b9E6zt2sALAjTFa3YwzByQQbFz1SCJoHPl0DuwyNict3A0XcvQiGsqbM7YwNwSqydwJ/WAU67JZAjadSACCxRIvr9mCrf5h2I6j6E61UuLglrkG7ppLygp4/TgoKUVbHBbdh+hFet20boFI3XNawTB+MGJs7Ro5RZXGH5xC/QXX/N+d/FnavJaeT6ElSZE0lF87XRhFj6KB9fHiqgb1nnj4tHx8i/xcavMaVn4WBiJzIE1dsEaatmgagIW5XnLNgkb6ImXKUoyrKkyhWyIGCM6B7xqHyIRCv8qM9pFsLVyKqJn9B7o/d0o5Uamb6O2MmlGKNDWOra+sRBpN7q9ktnDjObk5t+RioK8cW1hJWrPqjTubegkhoIF+Y23Voqgmr/YHRv1Ptdu/BrUpAhohUrMoCGV4oMV9gAUv9ZqNkBE4rUpSEBy6j1iNi2e1k9XbRkUu1DZI1rHUQ69AysLh375zEHxmOu+Y2jFOq2HiPw5PZHJrbZ6Andgqo50Ua5ud4bVHEDnLjDrHLNbblg0WkT0i1Xn0/86/boBWQVknB5EbrWSlKO/uFnAlS2w1vVEL+UGuYT4sJ1inF83IugV6vcUjjVuUboMmkYLp/QV193Nu441PIhYtTdyRsETkJKv1uHwreeDjvagiwKruvy7MDoAYVyZAyuiZHOXbRQ08e2a1hT6mJVQpiiZ1cnt53B48kVJfQ49bhqrNu4T1KF3KqInMzen+QZkdMFt3XG+WQWxlxGbptFBRC/3X2YPk5mfbFvkoePW+v57M8d1hSDJ3kMnDAMLMizIGAyR+GCCoNPeQyc5dXI1LY0dkOAx2bFl7Wa3vVU0pClzVhGyDQAagO/RwWNnqCKn3aW5527x7cDf6tcqQzF1KuqqJINiZ3euqt1tCyiH3oE3YTqnzLzN19O1KhWn7Hy6xcu/euNeTrcpSu24uMmso4cPAujaV23YK5jcwPDmE6MCEjMncJmpOsl1hrQLpBn9cetWHGsdHLCJs5ZzVKCrjJq222K9nI5Wa5XB5vjic7kSRIwRBU3LG6abAlr6+ZN7i8hfnVaD4zgKzJJxWdGt25BYAb/aiAvMjjAnAuojAMua5p5U/Lu4yqlomwV/QLVyLxl2K3NgRS0H8uTP8nt1H0edu7epwwXMpxgP+jg7W/rpPqGu8dBz7rRGatWoqqHN7D5QpVFvmj2+u0iDw3sBrOlNOw+LlEFwPQQSpyJ6dnUO1k6Gb8COLti74MQjBRGC2gwj5BQ3cv/d3sPs2MZMGzPIPtZZkOOPjJTYYIK0UETTEYF+8rEHEzwmO7YZG7jxjB1CrO17j9GxU2fp2vXbqUGBZGiPGF11vUSxc8OOkdSncugdWi0U24HqHgVl6dPdQyUKPWeYAx9saEQtYrqM4aLT4brayUQhHZq27W5+vHSFEOHOwLbyiVtMqVolUWi5bM0OgS7xb5q/+POOfcdEKgoOZQ/dn9VwXijm6tgs4fVssIZgkszz5CM0pMfrfFC7P+4xuzmzhgpqHsCHHgcKOLgTZi4X5CD7jpwiOK64WXJScECZzkXCH576LOhHgakDBEKSFbF6YEUu/+o5w0QRGnLxEXlDmgMizkZwcaGu8dA6d6h3QBpXoedz83V3Wq7HuSHWql6N0tS5RW0rJrP0LN6Fe7NkFNftOEilSJ5M3BahuC+YOBXRs6SoiYet8g2Y6DLgIziIwZHHARbF3uX595UnVw797hyAzHNqD7M7b7vtnED2cYoF2c4cvBzbjr7+bYwIsZwYA32EE4qdU3OKlH6UQx+GK4UfRJFq7QwRcmSikGE47ZCohKgFijJzapxqDOxz0HOz0x2okNdfOatU73Dcu7Z8lcZMf1vcBLRqWFVAgYXCoUeEXitALcmeLSNHXqtSjhAxFtpZXBlM9lY9JwgiKxSZ+24l4HjhOtgIDva/Gg/iGo/RIa3xQApe55a1472DSLEYO30peYbbrLN4TkT07Lwbem2Qh36GEUtwgHZTnikdI6AlAYaQP++TAsXEiliBQtT269QeZkVXJ56VRfbB72DPweNxjKtAqwLHhRkxqmEy6kNmbKO+Q/l3K2RcodRLjeWMBZRD74AdZfIhN2y/fU3rkz//+lPA/KEa3ugDLhOFdGDaEdlFMHx/q461HYd+27LxAvFg1NQlDCd4joZ0b0o9hs00hPmMSEOz0lZzOP3nKYPJjjQ4RE+LFniGgMhU5eXCdPTEp5SJc+qnDO+oa1IvazwCIW3AQS1UpY2rSEqyDo9X76jTTNtW5nH5ynWRlvTetgNMCPg9lS7yPN+C5RccB0bOvVUoRK1eTu1hVubqxLMyyD5L+VZ10uwVbON8olDz+x9/FoyrgP6sVamYoXraGiZfautKhmlFOiBuZvVEdmxD5UL4gBNkXCFUVw1l0QLKobdosECPy+RD+hNe+AotQXIBqD89kYlCOjDtiOzi4Aecy86U3EBh0cqxk58ZFrZqnwdk3yuVi5u2gf+B4f3DJ2kIs+2iOPXE9jmm+7HzoKxjbWdMtLGTw6kdy0e6ZgeTHTcuWsF6Z8+aifP3C4p0Ej3xssajXpuhVCDfUyJvHXriA/zW0g0cmTxBbwfAyLa7Nv7t4hdt/yN4IVa+t4dZSxubJjhyAsfe6nxkmbatjhfseYAgAMMfhYOogzIq7rcKhagd16k9zKm5m+1HBtkH9Rrg+tBG5GUZV1HrBgSwNXP1U1vdGNuszdRzygJWLKAceivWCrNnZaKQYTaVkKmDj+6EGcspY4Y0NG5Aa4FSgwgobkTSMQGIW7Jm874EhaAoxMIVcvmSL7o1rOhX1rF2SjmrOZwymOzBdP6YUzFyPf6Q4ZS8rPHoybc20BMIPbgif5TJscZw+hD+GUo5ykXN42KXxhVR641tB8feibnIMG07MX6gPlAIDh4GPbELhYg+vdrDZO2FolN8s3BY/JPTSrVihMn+Eqeg7ln1hi1c9GB6I7X1JWY8N+IQcWNsWVuq9soCgSygHHoH3gujlBu9IYyip4hqfPn1RUFE4S8yUUgHph2RXSBSDjZe4LAjwjO6X0vhVC9bu5OmjeiUYE5OMQKjY1B+nzhzTrCm4toYufpGmNNuGNmqY+2kDlZyOGUw2X//4xbtO3xKFD8jwu+T6fPfZfKyGJEW4QUrsVlb4kCB9wRsoVkzpzfbzNHncOAsUaujocODQe3g2DuhrFWmbSfRYbT+WgAAIABJREFUuozSlPS4JWSgEK3uYU7Y2Yk+UMtSkIu9UcN0Z5L4TNGFXsitOwQOjBDUK6D2CMXjc/jmCrdYzetXNlQvWGrr1es3aO7EXq6ObaicekBZwCELKIfeAUNqU27+ZufhJ1y5Hj3NyBRlqGurV3VHiBc99XsSKDdIzcCBYdHUvqY1NRuFNN1hFD0IFrtlMwcKJw946EtnDBRV+cFIrZxiBAYyRWsu1IQD/+33l8QNQbK77uJ87g6mC7ucXAYrjrWT44YqhxPU5bhSz+EX1QYaFYrpgPgDeMFwFKA9ocbiEsN8Zs2SXkDpGeVky85Dlk3YDo69rM5oL8O0LTu+DLeEDBSi1T1Mdp5Ota/etB+9O3eYre5AdOTD30+VMrmAmYTgwAv4Y9+h/eimWQH7l0ltlR3b1oRVI48t4OTRP3RTUQ69S7Y+wQQj0xi+D3l/bkmkRyHdsotev4PGzaO6DAGY89EHBPEX4AzhFNRuPtCQvVSGERjQiWWL5xcFWD7iHsBJAkITh4pQSygcay9TA4ClvptJ3fyj8FaLn0O9Ljj4te09STgpWRkTHsGBFCmS05RhHegRFxGJZNmE7eDYh9q24TieHShEmT3MSxs06TSKpnJBeuq7U1pWA3u0GXGDfdXLsc3MWT2jLOCzgHLoXXoXsFGDWTRQfp5emo1WHbDq6UkkRyFdMrtht10HT6ft7x8T+cjI6cQ/v2DGWlzlGpGAyTACI4J5YP10EWn1OfRQtiDToR/kf++myKR1yejlZWpA7II11LJB1QTFz/OWbaImr5WXmZarbRu2H0GVuXAXxE4+Wc7pYBt3HjJMDZBRTJZN2A6OvYy+4dBW5sBq9JvUm5/MHual3fCb3LjjsKgZAv+IFpZA+767oaNRWqweM68b+qg+lQXcsIBy6B2wKoigtIIUDpDDrFi3KyDFvTbNJimnYIAgCnjZKIJDzu8VJpMp8mIew+h+pEYhHTC57S4OcCqUVu4Q6CcZRXGskcgwAgONY9eKSSL/Ew799uUTRN4+oBWXuIhegjm5kdZlZCv8PdxTA0JBZGbGTtpnAFt5cH1svIMI9ETxHg6Ebkko2YTdmkOo+5U5sGp/k//8/TfhG3KNC/OLFshjyJYts4eF2kba8VDsHUxQy6QnMgW16FcGiU52bC9trsZOXBZQDr0D641IvFZ80JOg/86X53HdEYZPXkiPPXwf1a5SMu4jjlQM5MH36dBAt22kRiEdMLnjXZilTbfLCAz2TaT6oBAW0XowmObmQmegl5hhpnV8wiHo0MvUAL1i5pM75tK2vR8IPgBwA4STwNEb0btZPGKpk5+cpx5DZzC77mjXVJVlEzaKgLqmuIcdO3lgxY0u8M7Pc8qV0b4fbMpm9zAPTWZ7aJmCWtuD/tvQy7FldVftE5cFlEPv8Xoj5QLMlVpcdETkQCRz6L1YXe1krm09nrZnw8vSpn/93Y+U5p67KS3/164Atg03Mrh2DoV49Z54mRqgLWb2tzEK6fAbA8IF/nc4ye4Dx6n3yFlUsnBeypYlA/3w0y9MNHdM4MGjkNctkWUT9gcGuHT5Ch04eoZTh0pSt1avuaW2p/06fWAFfG7R6u0NMexl9zCvjCazD8kU1GK+Xo7tlb3VuInPAsqhd2jN//e/P+n02S/p8i/XBCHUUzkfNoVMUaF+D+rXqRG9lP/pOE1AHDJo/DzatGSMrnb+17Y/M8wdmEjNXNs6NO2I60aGNn3MtLfpnfW7BG49IC4BtQZCGVyXP/PUo2F7+JK53pdZYK9TA7xAi5Gxl68t8nk37zosnHkc+sA++ijf4nkhfzCxVXJOE7MjZ899QyOnLHI199+OXk61kTqwBgDRwE1Muz6TaPeqyYb7PqAfc+a4P95zgDHu2KwW5X7ykXg3PE7NV7YfGT4MmYJa6C2zB8qOLWs31V5ZwKwFlENv1lJ+zw2ZuIDKFM0nWBSPM6JNpwFTGFEjqXDmwRRId9xBk4a0M9xYdzB9dY+hsfREjgcoe7ZMAmrvDB8MRvVpSaW5fyuCa1sQGB0//TlH9JpYaZponpWhTQe05boFo7jm4SuKZYIUIBhhrRCdNMqDl/mYOb04TlzvW9EJ413/9Te6h9Et7uDfRSjEK7QY2bnhQI6UvbtTpRBd4VBy/debUjdCZnUClCnGJ/oPt7/r4FiaM6GHuFGyKuBdKMQ3kEc2Bs+dttpnOD0vc2Ct1DA+9jmIlrD392xbN15BdKD5yuxh4WQ/K3wYThfUWtkDnR47nNZA6RJdFlAOvc31xNXopiVjxYcX14EtGlShiqULxPWGfMaFK7bQqreGGo7wM0f1D3xwWkT3M6RLI0hvcDCwI9iokMZjlK5jvu+/+dH4JCDm24bfkzK06fXaDI1z3LX5s0X4Xdi3ZqqlyVr5mFnq2OTDZq/3TXYX8DFEmIe/sZCJu04QbrBQEFySMeCRI2z3/Tarj1doMWb1C/Yc3qtB3ZoINlvA5dVvM0wUS3ZqXovq13xZtvug7ccze/LCFZtFOplWLl+5LlJ/OreoTZVKFwzafsX63fH+9hc78+DQ+IlvrwANm5jETC67D1PdZxegX93Lxfm+g5yevWT2sHBbB7N8GDIFtcHmbHYPdGPscFsHpU90WEA59DbXEWgUPkhKRKH8ESjgWBet3oHeXzPF5gjGzVB9r5U/ORVkNxPnLHl3O21dOs64g0T4hFHxnh582fx3NlNKxgSvWKoANes6huZN7k37j5yikVxcacfeZj9mbiyT2et9mbGBbf5A9izUvF4lwYz7/Y+XadaidZyidMUQyUNmXLT1Ci1GVm9EX3E4xE0GCqkffiAbvVK5ONVuMcjVAl7Q2696c2gCVlqzuP1IP9HKL3wQOPHxF7RwSl9xOIlG8SqXXWYPC7d1CAUfRrA5h2IPDDd7K32i2wLKobe5vpUb9aaBXRpT/ueeJLDQNWP66Wc1edR7D52k1Rv30IRBbROMoEcZrn34Lb7q1hPAH2rlGl+Zg+UeqSCI8itJaAEZ+LKX63QTOfNayZo5PfXt0NByehT6CNXHTOZ6X+YdAvrT++ycasmdAOlahJ1H526QAmvoFVqMjL3QtuQrnWjL0vGiLgNkZ1uWjqVUKVMQIGr3r5tmu3sj3kNwWswY3TUBbn/ngVNp4uB2tsY9+fE5euOtVTR7XDdb7cO9kUw9jszcZPYwmXFl2xoVpt787Xf68uuL9BSjfwUS1GRsf/8D+uXKDb7hS8N77vOCR8SMyO6BMmOb0U89oyzghAWUQ2/Tilt2HxURtNxc/IqisUPHztCzuR8TV9bIhTzFBU61ObIWKJddSxn+GW9SW/cepZoVi1HmDOkI6By4sn21Sgl6tWpJS9rhCvFtjs5jU+zXqaGltuphYwsgJ1grSe5IksABMu6FCIgii6b2NfOoI8/IXO/LKPAKO6RgOEUqgU9wA4Jo7juzBsl0bdjWK7QYQ8UMHhg4bi59y4fGHzldqVKZQtSyYRWCM9F7xCxa+eYQ2e6l2lvF7dcj15NSJEwaR0sue6jMKcOHsW7Lfho6aQGVKpKPsmZKTxf5tm/XgY9oSPemptCfZPZA2bFDZV81jrKAcugl3oHbBawXCJHxYFKlbGHdERA5mM+pG9qcYjj19dsOow2LrONO46OLCKhMNE/CJBHRFKlKOFQhCgqq8DLFnhepIUaCCBNSR3zPfn7+WwIEZbFCz8aLQhv1k7tEEzq9a57RYw78PX5cFg7WDRSn2ihwtKMMakgWr9ommCHTpUktDrpgPK1QsoCwI/SBNK1TwU73hm3CCS3GUNl/H8ANBhBukt11F73M7yVSb3BQ/+6HS6beUbPj+D8ni9sPfgatQOc9h47T6U+/pBWzB9tVK6zbeZnLbncPC2uD6ihXrm53GtW3BeV9+j9el0MffkyDGQ3O7HfSLhKdE2NHqt2V3pFlAeXQe7xeuErfuXJSPGg4kA6V4qt3I2ZIXFFqxZdDP2n2Ctr+zgSPZxaewwNVqB/frBQt+Ixw5n9gRKI9jP09sk8LKs6OuZ4AYnTupF6i3UeMJNSx/xTBMJvjoXtpcLempiccCoceRYqPM6wd0sBwcBnxxiLC3H3FqS/zdXWv9vVdxcLvP2aOKZsM7RFj6rnE8NCvN38XDn3G9GkN30cn7SGL29+448h46qDI8757M9HrdStFLXGaV7nsMnuYk++M1b6MUm70+stbtjl9sGlWvBtRpCwW4Pq1D7fMDtjUKSQ6O2NbtY16PvFYwCj9UcYSyqGXsZ4DbbsNiRXoNq9z4WB2Tk346eerNGfpe4x2kJLGD2yjOwIcQ62AnOr+ezNT9zZ1qdRLeR3QLvq6wI3IyN7N4+HGI9e335i3aM3c4boTLlKtfVyRc0zn0VSnemkqyXYGnKURdrS2Y0TXcBBwU5Dvv3hqP8qSKR0hPxq3Cs34HcNNENBTZi1aLyLmM0Z3cVMNz/rWq1Mxqk3xTGkeGIXEQIj57uLP1OS18lSX3zG8n59/+S3VqFDUddVww3fj5m+UJkS3OK5PyMUBvMpll9nDXDSHYdcyWPC1mg0QQZcnNNj7KEoGg3KwGyCnkOjsjG1oDPWAsoALFlAOvQtGtdIlUiCAaY6oy2UmhgKRTPFCz1HbJtVDlhoRT183j49WDOPSs8GYeQtWbh2HWhRsaFy9Lp0xgM5dYHr2kbPFVe8//J9ijGZklOL03vaDNIGhATNyMde4Aa2FQ4+0hOsMSZgubWrHZ5u/QivG/54h+sUt0N53p9Cdd/4HP4rUjuI1WW9mKXZLPv3ia5q7bCNHm9NQu6Y1GSEomVtDJehXW6eC1B5wQ6zcsIfqVCslnORwlQr1e9LGxaPFYavLoGkCJQYHsOZdxzIHQvwouJNzwM3AyCmLaeOOQ/T7H7fEWlUoVVDgoqdm/gAzsorti/ccAQqkVFVgNKjq5YuEjHvAjI7R8IzMHhZO87eCBR9Mbxx28+TKEfDPbiPR6Y0dTnZWuiQeCyiHPsLXGoWaJ86cE4cBfESfzvlIPMctwqfnuPpNO49iPO1CAgrQJ0hPgTOyZHo//lfBiY+QD47D1x+3bsURf8FpnThruSEMI+D/RnGECR8BFGiN7teS8dmP07K1OwXrrNNSqnZnEaFHQSoiTIjE4/3wCW4Jeo+YTYunYc7uSLWmfUXB2lm20X1Mmta9TR3af/QU7dp/nLHo67szqE6vcJIRATe6iQm5YpoBUTCNmhocvuq0GswHyIHir7IoN0Zz6jl8pnC82zSuzill6UUq2vR5a8CPRyP4RstIZi9eT5t2HqaYuhVpGJPudWtdh5as3kYlmHegfUxNo+YR+3cvctn197D+EWVLs1jwOGTuO3yKrly7EVd7g4lOn/8upzvGCFQ3LZoW/iaDRKc1op2xI2oRlLJRYwHl0Hu8lDJ5mLhybN1zgvj4f/v9JRH9RTHdlOEd6PFH4tOCezzNsBn+PNusHcOM3mKiI5FDz9HPvzmCO31k53jXucEU/vHSFcHkiZsUn6DmwSj6rCWiqtt6iHDUECW3mq5j1pBT5qyi97YdpKpclA3isoOMwgT8fB8KE/5Wv1YZiqlT0WyXlp+rEdOPVs8ZRrAPnBAQDKHuo2rjPrRteehrPGDvlxjn3ccfYXlCIWgAhCusFQ5CE2YuFxHyfcx1gPzj5TMHuaYBor5IGwNil0/+4BxlvJ+43TESwG3iAAm2a8Dp7ln9BoFnoTKnuJlpb9R/OP7dq1x22T0snGxpFgseaYM4kOfwg6lEMTYOjfi9lC3+QrypySDRaTuyM3Y42VjpkngsoBx6j9daJg8TTlLZ4vlFCoHvIwqHYNmaHXGRPY+nF5bD41YD6BuAPoNj/hwjJ/hHd4IpDifl6jWgGt1GaIF0HRxLc5gzQA89ZtC4eVS3RmnK+egDVAcOPTu3SKUA1rhbDs/2vcfo2KmzjMJ0M+g6uFmQ2ooPm2P7txJ28UWb4STC+XMz1QeT3bD9ULw5//nXn7Tj/Q/ZybxBcyf2Csv3EkohQq8VRM2zZ8vI8JVVKceD97qmN26Q8E5q0bZQTI1DmZn3M3+FlpziNVPo59uLUGiLw5uZ9q5NzMWOvcxll9nDXDSJbtcyWPC4odrNh0T/fdqI+MwJJDq7Y3tlZzVu4rWAcugjeO3xEQUSDhAlfB9RTAfRtoP875U4a4HxnAO/cMVmEeXWymVmxcyWJQN1blGb03kKBhwU2Ovb3z8miFBwTY9/fsG5+I1rl6N2MTWcVTRMepvO6UkbOKe6aIFnRG52lZcL09ETn1ImzqmfMryjq1qC7E0ruFVB3ULDV8rGc1pdVSKCOvelzMA+eJd/YBz8BcyMbDZlpgoT7c0e313cesEBeo1rFZCCgxx6YOlHo0RLLnuo1kYGCz52wRpq2aBqAt6Pecs2ieLxoOJATZjtsUNlWDWOssC/FlAOvcevggyUF4hNdq2YRMn4mhwO/XZOY0BONpyoJdMjK5cyVMsQDG87NaMKGcGEvsT4/qveHEpgh9WKUZQIzx44ejpemzsYkQioRm6j3YTKroHGmfzmynj/GihM2bNmYsKkgpQieegKZL20gdWx9fYDbV/58jxhtWvd51GguG7rflq/9QDfHP0ibq4q8uEU5Hi4JTAS6H1vloyiZgOEe1hfwMAWK6gPBWvUbzj/3atcdit72N9swP9K4cPDmnb4MIy+k0YsszIz93JsGb1V28RnAeXQe7zmMlBe+HAijQOFsIjWI1c5N9Nmj+E0h4fudxcW0WOz2R5ei7cNiD5cyc5dupEK5Msl2Hr1BLmUM0Z3TRAl6jxwKk0c3M62Tomt4cefXaBcjz+U2KZtar56bJraDtbO04dYNTWYekjKAl7lssvsYVITDtDY6MDgFB+GDMus7Jy9HFtWd9U+cVlAOfRhtt52obzAWIpcZW2xZphNLWzVAYpBpQa9TJNxIQ8cWOFaSZUyRYL56WGhax8OZ1x0mUVLFOgQRh6NjAFdaRs4B8GoON9IlUjF/Teal9HfwyWX3eoeZjQvp/6e2PkwnLKj6kdZwIwFlENvxkohfsYslJfRVWCI1Y7Y4RDxqsj430YpN7uZUXbIhPmimNVfTu+al+DfabHQPzv3DW3de1TcAmTOkI4wJgqYX61Sgl6tWjJibaenuEKHiJxl1RbnA/XpJ4at3M9pYvVqlKGurV41nEik4v4bTixCHjC7h4V6Ok7yYXgBEeqzl5djh3rN1HiRawHl0Ifh2pmF8pJJ1wnDaYdEpcHj4zvegDI88tEnIuVmSPcYXR2A0tC3YwN64ZmclERD0oRGKEzWE7QFvrgWRQQf4fpthwmCqmgUhQ4R2at64swXNG3euzRzTFdbE4kE3H9bE/u3kZVcdplx/NvK7GFO6mGmL6f4MLyCCMUcvRzbjI3VM8oCPgsoh97jd0EGystfdbvpOh6bIKTDA7lDK0mTJuXC1Cz0Uv6nDYv/XmGIyWA040aTgHO7c+WkeDjfqHkoxRCORjcDRn2H698VOkS4row5vbCfFKhkzKAcrLdIwP03Z4nAT3mVyy6zh8nM105bp/gwvIQI9XJsOzaPnjYOQBRFjzFMzUQ59KbM5N5DMlBegbQym67j3owip2fkvxpF1rWz6TJoGrVtUp0effg+y5PsNiSWLjPB0+v1Kgl0m59+vkpzlr5HdzO6zviBbSz3FwkNjFLC3ESmiAT7hJOOwJzXCpzxLbuP0Ip1u2jdgpGGqkYq7r/hxCw+EOpcdqt7mMXpOPK4E3wYXkKEejm2IwugOkk0FlAOfRgs9f+YtfT02S+Fw4eUjKdyPmzJ0dROwWy6ThhM23MVcpdoQoFy34Mp1mfkbAEJmjfP45Q+bRqO6P/3pJFTfuPX3yiWcdlxfXv5yjVRvFy80HPigKBHSOW5kSQUUOgQEsYLcVNE4rXiw+3v3roO5eP33UjCAvc/DAqUQ53LbnUPM1rHcP27VxChsIeXY4freii9wtMCyqH3YF2GTFxAZYrmo8IvPE3HOU+104ApzICXVDjzP3IxGjzFSUPaCThKPXEyXccDM3g+pNWPISDYgskrjNetRFlAWSC+BYAIlZx5MqJRwiGX3eoeFqnr4BVEKOzl5diRul5Kb28soBx6D+xetHp72rRkLKdbpKDqTftRiwZVmMSlQJwmQD9ZuGILrXprqK52TqfreGAKT4csyfnrO5mYyy3xiiTIrfnY6VehQ9ixWmS2uXr9V7p67VdWHrmvt6Xr4FiaM6FHVN5ChUMuu9t7WDi9iV5ChHo5djitgdIlvC2gHHoP1ufFiq3o8IYZYuRCldskKIpEMVrR6h3o/TVTbGmHA0GNCkVttU0sjVBrcOPmb3TP3akSEEUFs4FVrG5tyklSRsX59IuvhWOTMX0aunLtBl25eoOKvJjHNopIuK+VQocI9xVyTr/xM5ZzEGIzpbnn7nidXr5ynbJlyUCdW9SmSsw8q8Q5C9jZw5wbXfWkLKAsEG4WUA69BytSuVFvGtilMeV/7klC7mmz+pXp2acejdNk76GTjFG+hyYMaqur3bmvvqdla3YI51ATFOM87WNUt3ppqlWpuGKM9bMgclyHcsrTjvePEQr/7rorKZUrnp/6MBxlWj9nxN/4WqxuHLoufPsDffLZV9S8QWVqXLuc7loNn7yQHuNi2tpVSsYdIHDwAmtqnw4NPHgL3R9SoUO4b+NwGeGlau1o1ZtDKWvm9PFUKvNaV9q2bHy4qBkVesjsYZFqAK8gQmEvL8eO1PVSentjAeXQe2D3LbuPUt9Rb1JuLn5FfumhY2fo2dyPiegWsJtPfXKeanNO9sCuTXS1QwT4hWdzUs4c98d7bvKbK6ljs1qU+8lHDPPwPZi+p0N27D+FUqRIRu2a1qCsmdILkijYK0mSO2hs//iFgWYUXbxqm1ivkX2a6z4eDCmhUJU2dOi9WDNDhfEzgeHFwgMdIgwqJcN45ZxSDSRiM0Z3TXDb1XngVJo4uJ1Tw6h+2AJO72GRYFSvIEJhGy/HjoS1UTqGjwWUQ+/RWsBxP3P2Al3jvNNgUqVsYV3tCldtS/vXTkvwjIqKBTdb/gotafeqyZQqZYq4h67duEmla3emIxtnWn4bAL0IjPmPtr2l27ZC/R7Ur1MjgXfvk4MfnKFBTHS1ackYy+NGQgOFDhEJq+S8jr6AgvM9qx5hAaf3sEi1aqghQrV28nLsSF0vpbf7FlAOvfs2dm0EOIQv5s0lomJaPOJjJz8zBTXnmmK2O3afSAI1C9uWTxAFyT75meFCqzTuHfBwFGgq2txVpN6c4bSZPHwboifIJ+8xNJaeyPEAZc+WSdzEnGGo0lF9WlJpRjyKRlHoENG4qsZzSizIK8aWcOcJJ/YwdzQLba+hhgjVzs7LsUNr5TAcTV26Bl0U5dCH4ftqRyX1ETVntbVb9vFh5wm6/97McQ1AqrP30AnDQmJgyQ/jXPhNOw8TuANSJE9G5Urkp97t65tC8cDB4cAHpwXfQIZ0aajg808JqNJoFoUOEc2rG3huai9yd81l9jB3NXOvdy8hQr0c2z2Lqp6j0QJh6tC7H6mNtsVUH1FzK/rrzd9p867DjDSTlomdnjXX6N+nUPfw99//UJeWtalWswG0aGo/mrVoHf3KaDnhniesflGWllo9LGEB8DVENS+Dxz8mmT1MYlk9beolRKiXY3tqdDV4xFkgTB36iLOj5wonJjxiGWM36zaW/vrrL/ru4s/U5LXyAg3o5Mfn6PMvvzWM0KPIc/u/6TrFanSgPavf4L7+piKM8HFg/XRdtYIhJfg3Orljrsz0wqrt612C1wa8xdjkSqLLAkCNOsFEeUhHADRrnlw5bDNeR5dlnJ2NzB7mrCbe9KZNLw21Bl6OHeq5qvEizwLKoY+8NYun8dff/SjQcYwgFyN8mo6pX6F+T9q4eLTIYe8yaBotnNJXIN007zqW1i0YqTtOgUqt6cC66aJm4bZDP5lOf3qByXOmGxa2apES9AZJn/Yex+bqdUebdx2JUwG1BmBBXrlhD9WpVkocpCJXPA7RhqHhTn/6JbXtM4kd+CSUmdGjfuDfVJIkSWj6yM5cNxIfhSsM1Y8olWT2sIiaaBBlvbyN9nLsaFg7NQd3LaAcenft62rvY6a9Te+s3yWixNNGdKJCL+TmyPMlQk74Mxpce1eViLDOG7QbTvMn96Y72fGo02owLZ0xUMwASDX71yVEDNJOr37bYQJKFA4KnPvHH7mfPjv/DY3u25JKFH4uwizhjbo4SCHCuGbucG8UUKO6YoHXWg6mauWLUL0a/x3U5r+zmbYyRO+iqX1dGTOxdiqzh7lns9BVKnrpVHs5tntrp3qOFgsohz6CV7LMq104qjyKGUi/otj5awTjKJBTQIC0ZHr/CJ6Ze6qDzOkg4/6XK/EiTZi5nHq2rUv7jpyiYyfP0vKZg3QHBq09iKhSpUxOqzjSDKSc/M/l4gJX46i6UfrJByfO0qKVW8I+F192ZZCW8RLDrfqYkmX7U+3DwwJ5yzYXa3pX0jvjFAK0Hw7Kx7bMDg8lo0QLmT0sGkzgZXqpl2NHw9qpObhrAeXQu2tfV3uv12ZonOOOCNmymQMJqQ1FqrenfWumujp2pHaO6JZW7rjjDoaRzEgtG1alHA/ea3paVrG2tekn/oMAKQcIOCCoslqoa1phDx7csP1QvFH//OtPZuj9kK5ev0FzJ/byQCM1pFsWQHBh8bT+8Zhiv2Im5Riuo1BMsc5a3ak9zFmtVG/KAsoCXltAOfRer4DE+LjSTpkiOVUsVYCadR1D8ziVZD9Hm0dOXUJbl46T6DnxNf3j1v8Ea69ZsXv1qsWwRy5+NEv7vpPjTS8pR28fvC8rNXylbNTDdUbzugaa2+fnvxVrmi5t6rg/3+Lf1PmvL1LORx9IbObwZL5W9zBPlLQ56HvbD9KEGcspY4Y0NG5Aa7GPYC+9zqSA2nfOZve6zbwc243NyNXZAAAgAElEQVT5qD6j1wLKoY/gtX25TjeRM6+VrJnTU98ODaOWrMiJ5brK7LxInyFCceNt6To4luYw8so9qVOZGsKqQ4+i2KETF3CE+hgh7QSpO+WK56c+HRuogmZTFlcPhbMFPv3ia5q7bKNAt2nXtCYHGpKFs7oRr5sTe1gkGQHs56P6tBCIZJ98/hWN7teS9hw8TsvW7hT1Y26Kl2O7OS/Vd/RZQDn0EbymgNDSSpI7kggEFiXBLTCeozwLV2wWyEBauXzlOmXLkoE6t6hNlUoXNDShVaztjv2nUAp2cto1rUFZGQUEyDpI28F6je3f2nA89YCyQDhboFrTvqIu5Sw79vcxE3L3NnVo/9FTtGv/cerToX44qx5xujm1h0XSxLUppXVbDxFgBgiMINVr96r4N4FOz8vLsZ2ei+ovui2gHProXl81Oz8LvMSY8aveHBov1xePIApjJtf37LlvaPv7H9AvV25wikEavgl5nh59KLuhnfNXaCk+PKlSpoh79hpfF5eu3ZmObJxp2D7YA6HDlrCtomqYCCxQI6YfrZ4zjH77/RY17TyKlsYOoJu//U5VG/ehbczdoMQ5C8juYc5pErqeBo2bR3UZQQnpW3Xg0PP7haBI7eYDae+7U1xVxMuxg09MQee6uugR2rly6CN04aB2MLKi1KlSGhIdRfC0pVRv0X0czRjdNcFNRueBUw0RZtZt2U9DJy2gUkXy3Y6y/3iZdh34iIZ0byqik3pSiEmp4NgAGccnKISt0pjrHtbqw2VKTVg1TuQWCM2Hv1XPCXzT1EqkrPngYJHTDVQQ9X47+wrK7GHOamKzNxtRCHB9bOd0RQRPUGyNf35x4XtqXLsctYupYVMRc830x67GnSQx15F6SlnAZQsoh95lA7vZvZas6O+//xFkSXOXbqQC+XJRzYrF3Bw66voePH6ewJjXk3J1u9Oovi0o79OPxz126MOPCW03LBqt23btln2UL88TdP+9meOeA1/A3kMnDBlqo87YakJRZ4HpDJu7gQsXixZ4hjbuOERVXi5MR098Spk4p37K8I5RN99wnJCZPSwc9Taj04Gjp+M9dgenKmbPmlEUx7otXo7t9txU/9FlAeXQR9d6ErCfKzXoRdvfUdfcgZYW8JEzF66lK9duCIhPn8C5fvrJHNSeoz2FX3g64FsBrO0PNs2KF90HkkcBjr5/aIC1/evN32nzrsNcNJg2qqApo+zno6Zj0wKoB9EKakOyZ81ElcoUpBTJVYGsTbMGbCazhzmph+pLWUBZILwsoBz68FoPaW0Qta9Yv6dKuQliSaQA9Gxbj57wg9KL6Tya5kzsSekZdi992sBEUbWaDaCRjLSgpbI/99X31GPoDFoxe7Du2oEd9S8uYv7u4s/U5LXyVLd6aYHY8PmX36oIvfRbrzoIVwt8/NkFyvX4Q+GqXkTqJbOHReSEWWkv00u9HDtS10vp7Y0FlEPvjd0dGRVXrFpB1f+Rjz4RKTdDusc4Mka0dVK8ZkfatXISgVBKK2aLYgPZQ8BQahgyAz1TgQ9ZGxePFmlRXQZNo4VT+oqiruZdxzLb78hoM3No5hOa9PDQzCXCR8HN4L7DpxLcfE2f/y4N7hZDBZ9/yvA3EuEmCJn6buxhIVPe5kBeppd6ObZNc6lmUWEB6x845dBH8MIvYGIprSRNmpRzCrPQS/mfTuCwRvA0HVUdyBtapBlf5yApufNO/eImGYIRsDvOZ+IvjOErGsTYhau0pf3rVFGso4usOgu5BVCoicNqDj/Ep137P6IShZ8TReNli78Qcr2icUCZPSya7OFleqlbY9uoF46mJQ2PuUTwIiiHPjxeIaVFiCwwY8FaUyO1alQ1wXMyBCOrN+6lg8fOCMdmwszlnPZTl/Yxq++xk2dp+cxBpnRSD4WDBaxHTcJBa7d1wMF09+o3EkThZW6+3NY5UvuX2cMidc6B9LaUXuqwk2Zp7GgyuppLWFtAOfRhvTz6yv3vf38KpjxAJ15mCERQr5d8KS+9UrmEut4OYrphkxaaWvF+nRomeE6GYAQReq0g5Sd7tozUsmFVyvHgvaZ0Ug8pC4SrBWIXrKGWDaomgIN9c/F71Kx+pXBVOyL1ktnDInLCrLSX6aVejh2p66X09sYCyqH3xu6OjDp4wnw6/el5qlejDGXOmE7goi9etZVeeDYnszM2cGQM1cl/FnCDYARY3cmT3aXMrCwQ8Ra4ev1XunrtV57Hf+hRXQfH0pwJPQQ+vRJlAbsW8DK91Mux7dpLtUucFlAOfQSve+GqbbnQcgylvefuuFlcuXqDKjXqRfvWTI3gmbmr+qoNewj58LjVwEGoQqkCVL18EcO6A1lyE+XwuLuuqnfvLDB+xnJauGIzpdHsRdDm8pXrlC1LBurcojZVKl3QOwWjbGS7e1iUmUFNR1lAWUBjAeXQR/DrgPzUtfNGcJFn8rhZAO+8WtO+tG3Z+NDOLEJSi2cvXk+bdh6mmLoVadjEBdStdR1asnqbKNxrH1NT12YyBCMR5/BEyHqG9iVXowWzwEvV2tGqN4dS1szp4z2icuidf2dk9jDntHE4Kd1AMS/TS70c27n1Uj0lBgskUoc+mLcSWV4MGBk38H/rVi/FUfrUAmVi8aptAuUm/3NP8sX37avvp3M+khjeZVNzBIbz4qn9OH89ExWr0YH2cCEfIueVG/aive9OMdWH/0MoeK1Roahu20hyeEL7qbZlctUozCwAlJsZo7smyKHvPHAqTRzcLsy0jWx13NjDwt0iXqaXejl2uK+L0i+8LJBIHfrwWgS72lSo34PZTo1bb1oyxvihRPJE/got6cjGmWK2PoceiAVVG/cxdOhBIrVszQ6Bta1JE6Yd+44JoqhalYrTQ/cHpiJXDk8iecHUNJUFXLaAzB7msmqude9leqmXY7tmUCc6Dhr5USEhJ8xrpw/l0NuxmmoTsRao0qg3zR7fnbJlziAw4F+rVkqk4CCHvmXDKrrzqtqkryg4zpnj/njPgfa+Y7NalPvJR6RuQ/7++58EEc6INbRSPFFZ4PUu5oIGb3GBrBI5C8jsYXIje9fay/RSL8f2zuJq5Ei0gHLoI3HVAujscyqjZDquTQO47/dmyUj3Zs1IfUe9SSmSJ6PihZ6lYgWfNRwTkZr9axOSQJnJEw5GH45BT+6YS9v2fkCjpi4Jfe2D4azVA8oCxhbYvOuI8UP8RLkS+U09px4KbgGZPSxS7epleqmXY0fqeim9vbGAcui9sbvjo+Yu0YRO75rneL/R3CGKXAu9kNv0FA9+cIZezJsrQRT94LGPqWC+XLr9aOnD/R9Mn/YeQnT+6vUbhP+tRFkgIiwQ4GYdjMs3bv5G99ydSt02hWARre5hIVDJlSG8TC/1cmxXjKk6jVoLKIc+SpZWOfTWF9KOzWShJ+G4w+FJo3C5rS+YahG2Frjx6280bPJCkb4GVBDcfCEa37t9fYVB7+Kq2dnDXFRHda0soCzgoQWUQ++h8Z0cesX63cwQW9zJLqO+L6sfQxnoScCJjpyymHB9+/sftyhlimSMf1+QeratS6nvThn1tlYTjG4LIH0Nh9UuLWtTrWYDaBEjSc1atI5+5cOrQrlxb+2t7mHuaeJsz3p4c16ml3o5trMWVr1FowWUQx/hq/rJ51/RnoPH6WcmScqUIa3AU3/8kfhFmxE+RdfU7zlsJo3u19J0/zLQkz2HzxTEVW0aV+eC3PT0w6VfaPq8NfzviEb0bm5aB/WgskA4WqBg5Ta0ffkEujtVijj0KKTfFGF8+gPrp4ejylGhk9U9LBom7eUhxsuxo2Ht1BzctYBy6N21r6u9L2UIxUmzV1DpIvkE4+n3P/5MO/d9yFHfegyhWMzVsRNj5zLQk3B4dq+aTMmT3RVnuj9u/Y/KvNrFEC4zMdpazTmyLFCgUms6sG66yJv3wcGe/vRLArtyoofNDRG9yfptB6hymUKR9eLY0NZLp9rLsW2YSjUJcws4DfCpHPowX3A99UrV7kwzx3SNF5FHxL5dn0m0jaNlSm5bIBwg9YCEszR2gLhF8cmly1epRkw/5dCrFzXiLVC/7TAa2LUJPcGQrnDucUv42flvaHTfluLWUIlzFljwzuaAnc1ZupGa169MD96XVZAL4nAVjaJNL0VQRBsk0c7XaWcJfZsdOxrtruYU/hZQDn34r1FQDZECsmfVG3TnnUninvnfn39R8ZodAsIrRvBUpVTXQup9du4b2rr3KNWsWIwyZ0hHQJ8B0+urVUrQq1VL6o6jBz2pbQgYSoj2g+Kja2/4SlnKliUD/fDTL4QPM5yd9jE1pebna+zGB8wRxVQnUW+Bq9d+pbvuSkqpUianVRv2iNSb/M/logzpFGqT04vff8ycgF1u2nmIyhbPT2fOfskHqwcspRM6raMb/ckCEsjo5OXYMnqrtonLAsqhj+D1hpMIaVy7HCXjVA4UXs5ZukEgTCBSoyShBSo17EXzJ/eOFymHU48I44ZFo3VNpgc9qW0YCHryH6b0Xbd1P63feoAusjMPR6di6YJUmwuZkVuvRFkAFghRdoarxlaFg66aN2jnPj6MaAzqyAASyK6Gl2PL6q7aJy4LKIc+gtcbaBJIsYEgMnbztz/E/4ZD+cetWwQnEnJ006wInqWzqoMddufKSfGuaX/7/RaVeqWTqeK9P//6i06cOUeXr1wTdQtP53wk3g2Js9qq3pQFIs8CKs84NGvmj/l/6tPzYj+6xWkonQdNo2kjOoVGkRCMIgNIIKuel2PL6q7aJy4LKIc+gtf74k+XTWmfLXMGU88lhoe6DYmly4wI9Hq9SpSd2WJ/+vkq32q8xykCKWn8wDa6Jjj31ffUuucE4cB/+/0lypghDSW76y6aMryDIbLQjAVrg/bdqlHVxGB6NcdEYgHl0Lu70IkR818GkEB2NbwcW1Z31T5xWSCiHPpouI5OXK9X+M0WH8PY+WtoB6MBIcqO1JfihZ6jtk2qGxLgNO08SuSo1q1eOg7JA/n3yxhtaOmMgbqTHTZpYdzf/+abk58YtnI/M9XWq1GGurZ6NfwMpTRSFrBpAcWJYdNwJpspzH+ThlKPKQskMgtElEOfyNbGcLp66C1vTehBH5w4S4tWblHELoaWNPdA/gotRVpO0jvvjHPo0RKQlAdtYG2fOPMFTZv3rkAqUqIsEI0WGBu7lLq3rhONU/NsTokR8z8QIEGSO5JQ6tQpad+aqa6uhZdjuzox1XnUWUA59BG8pFr0Fv9pgHYdZFOnPjnPEehnI3iWzqr+3vaDNGHGcpEuM25AawHxhlzU6zduUrq0qXUHK1y1Le1aMUkUIANrG0Q6y9bupA3c55Lp/S0rihoHQPwd3jDDclvVQFkgnCzQvu/kgOoc+OA0FXnxGf6dZSEgPKHuRImcBRIj5r8WkAClYRe+uUhvvLVSIITly/OEnEENWns5tqsTU51HnQUix6FX+TYJXj5AxSVNeqeAiIOAev36rzcp7T13R92L6tSEgAQxqk8LOvnxOVFQDKZYMO3CMTcqIsNVd90apUXhGaL1KKbN/cTDNKZ/K3ro/qy6KgJzXitAotiy+witWLeL1i0Y6dT0VD/KAp5YYN2W/QHHHTVtiYjQn8Dv7bMLtg6+nkwojAdVmP+3F+fbi5eoUfsRtP2d0HOueDl2GL+aUalaJMFBR45DH5WvitykXms5mAZ1a0K5Hn+IoRAvU/02w+gaR5o7Na9F9Wu+LNd5lLaGzZbNHCgQgOq2HiJy3+Fcg7EVTK5m5cI3P4ice7M424iqaQUHMdwOwNnJl+dxs8Oq55QFHLaAu5GS8vV6xDHFFuLUNKSsKZGzgML8v22/3/+4RZ0HTqPYUZ3lDGqjtZdj21BXNUkkFlAOvesL7d75DikgyB8Ejjmixw8/kI1eYVzz2i0G0bZl412fWSQOMGjcPBFlz/noA1QHDj2zt+IwVLv5QMXYGokLqnQOGwvoQboCSnHhyq30et2KYaNvJCuS2OBzP/3ia5q7bCNlTJ+G2jWtSSlTJAvZ8nk5dsgmqQayYQH3fDsbyogmyqG3a7kwaFeSsdO3LB1PSOeAQ7pl6VjGo09BwFrfv25aGGgYfip0HTydtr9/jB59KDt99e0P4p9fXPhekHO1i6kRfgorjZQFIsACMpCuETC9sFIxMdq6WtO+VK7Ei3SWHfv7smWi7m3qMErYKdq1/zj16VDf1fXxcmxXJ6Y6N22B8HPdA6uuHHrTSxp+Dw4cN1fkEf7IzKOVyhSilg2r0Nlz31DvEbNo5ZtDwk/hMNDoAENFauWOJHcIPHqkvyhRFlAWsGcBGUhXeyOilbvpQvb1crelN7Z2d05GvdeI6Uer5wwTdUuYP25Wb/72O1Vt3Ie2MTiBm+Ll2G7OS/UdfRZQDn0ErylyvzfvOizIjV4u9rxIvQFiy3c/XKIHsmeJ4Jm5p7oqJHbPtqrnxGsBpyFdE68ljWeeGG3dign9xjL4AOqW6rQaLGqf/uA0LtxS71/r7m20l2Mbvw3qCWWB/yygHPoIfxvg1APPHNBayC/MkyuHwElXEtgCqpBYvRnKAs5bwGlIV+c1jJ4eE6OtpzMZIOCBixZ4hjbuOERVXi5MR098Spn4mzdleEdXF9fLsV2dmOo86iygHPoIXtLTn35JbftMYgc+CWXOlJ5+4OLOJEmS0PSRnemJHPdH8MzcU10VErtnW9Vz4rWADKRr4rWavZknRltPfnNlPGMlEamSmTjVtCClSO5ugayXY9t7Q1SrxGoB5dBH8Moj2lytfBGqx6gtPpn/zmbauvsoLZraN4JnFlx12axZVUgcla+FmlQYWcAqpGsYqR5xqihbR9ySKYUTae1LKKatHPoI/nnlLdtcsIzexZjmPgE+LlBujm2ZHcEzc091VUjsnm1Vz4nbAkBfQTABDNWZM6blup4XBJSuEuctAFI8EOLB1pkypKUShZ+jxx+J3lvZGQvWBjViq0ZVnTewpkcvx3Z1YqrzqLOAcugjeElBhrR4Wn/Kmjl93CwAxRjTZYw8Dn2k4DRZXD9VSGzRYOpxZQETFti5/0PBhVG2WH5av20/lS76PO05cJyJ75oy3GB+Ez2oR8xaYOmaHTRp9goqXSQfH5zS0fc//kw7931IPdvWo1qVipntJqKeGzZpYZy+fzMp4E+XfmHYytN8O12GurZ61dW5eDm2qxNTnUedBZRDH8FL+vn5b0V0Jl3a1HGzAIHL+a8vCuIkJeYtMHj8PBrYtYn5BupJZQFlgTgLVG3Slwbx7wesx8VqdKA9q9+gz85/Q+36TKbNb49VlnLQAqVqd6aZY7rGi8gjYt+O66nchnB0cBrSXQEMYtq8d4UtQi1ejh3quUbHeLLJupFhBeXQR8Y6BdTy2MmzprTPl+cJU88lhoc27zpCMxeupSvXbtA/HOnxCci5nn4yB7VncqnCLzydGEyh5qgs4JgFXijfgo5snCmgc30OPdhMi1ZrTwfWT3dsHNUR0UvV2tGeVW/QnQyG4BPcPBav2cF1CMdwsj/27wKVWou001CLl2OHeq5qvMixgHLoI2etEmiKqJhP/vn7b8EYe+3GTXrysQcJG7xP1s4bHsGzdFZ1FMXiavoJvxuMmM6jac7EnpSebzvSp73H2UFVb8oCUW4B/K7WzhshcMKLsBMPzPB31u8STufY/q2jfPahnd7sxevFgGC3TpbsLvr15u80Z+kGgfbSvH7l0CoTotHwbdMKvm9bdh+hFet20boFI13VwsuxXZ2Y6jzqLKAc+ghYUrOXRYgaIL/yPBen9enQIAJmFnoVi9fsSLtWThKRRK2Uea2rfN1B6KejRlQWCAsLLFm9nfI/l1OkgZSv14PJ7pJSsULPUpvG1SlVyuRhoWO0KFGr2QBCig0Etr352x/ifyMQ8cetW3E3j0c3zYqWKYtIvFaSMhAE2L27t64j0rzcFC/HdnNequ/os4By6KNsTcEUW7R6e9q/zl32vEg1G+jCU6VMkUB92E17hR2p81N6KwsoC0S3BS4y34gZyZY5g5nH1DPKAsoCUWIB5dBHyUL6pnHyk/PUvu9kEYVWktACQAEC8x/wm//UpCXhyXdmDVImUxZQFrBhgf/9709atnYn7TrwEV3+F0qx5Et56ZXKJeLB6troWjVRFiDUiwHR54HsWYQ1AAiBPRy3QFrYZjdM5eXYbsxH9Rm9FlAOfQSvbaWGveJpDwcV+X692tej2vwhVZLQAnVaDaaCz+emF57NSXcyq65WCr2QW5lMWUBZwIYFBk+YT6c/PS9gBOF4XfzxMi1etVX8zlT6nw2D6jR5nWGJzchbE3qYeSwinqlQvwfNndSLcOvw0enPqWP/KSLlJsdD99JghkZ1U7wc2815edd3lGJie2fQuJGVQx8Gi2BXBV8epa990jvvpHuzZqS7UyVMKbE7RrS1q960H707d1i0TUvNR1nAUwsUrtqWNi4eQ2nvuTtOjytXb1ClRr1o35qpnuoWbYMDqcuMRBP+Pwqt318zRUwbAAZ1qpcm3ACBi2X3qslmzGH7GS/Htq20apgoLaAc+ghf9q+/+5HS8EdU+yGN8Cm5qn6TTqNo6vCOlPrulK6OozqPVguo6FKglUVROVBuUiXnAth/L76AvlKtaV9VbO7ST+Hvv/+hGzd/ozSMLBTtUq5ud1o6YwCdu8CADyNn04ZFo+kf/k+x6gzV6XK9mJdje7KuZlE4PFFODapnAeXQR/D7MWba2wIaDgWd00Z0IqSMfHfxkki7eeapR8NiZuHm/sQuWEMbdxym8iVfpAzp7iEt1s1r1UqFhc2UEsoCkWaBjTsO0Qb+b93qpTi4kJp++vkKp9xso5fyP83oN08K5wvydM5HIm1qYacvDkojpyzmfewQ/f7HLUqZIhlVKFWQ4XjrRm2gAu9SLNc+AcVnVJ+WzEScjz794muaOGs5zRjtLrGUl2OH3cunFAprCyiHPqyXR185XDeuWzCKN7avxGYHxrwzZ78kUFUvmd4/gmfmnuo9h80M2vnofi3dG1j1rCwQxRZAnrGGpy3oTDctMZf/HcWmkp5az+G3CbwACZotc3r64dIvNH3eGv53RCN6N5fuP1w7+PHSFQJcJQIxPsEtRZIk8SGI3dDfy7HdmI/qMzotoBz6CF7Xem2Gxjnur7UcTMtmDhQYxEUYtlLlrUbwwirVlQWUBZQFgligYOU2Im88OZNK+eSPW/8T+eR7372dZx4N4iUTupdjR8PaqTl4YwHl0Htjd0dGnf/OZr5uTU4VSxWgZl3H0LzJvWn/kVM0cuoS2rp0nCNjRFsneht1vjxPRNt01XyUBZQFoswCqFdYGjuAMmVIGzczpFnWiOkXVQ69lgk9KTMOI8UGTMQZ06ehK9duEIqui7yYR9xMOy1eju30XMIt7dXp+an+/rOAcugj+G14uU43kTOvlax8Bdu3Q0ORY+i1hONGot2okSPwPcPr3XXXnfT8MzlpyrAOXptMja8sEJEWyFPKHHTgyR1zI3J+4aT07MXradPOw9TwlbKULUsG+uGnX2gBB3dKFH6O2sfUDCdVHdNl+OSF9NjD91HtKiXjUmxWb9xLH392wXVYVC/HdsyAqqNEYQHl0EfwMv/511/xtE9yR5KQ5BNGsMkSqH6Lr6oHjptHTz/5CNWvWSaapqbmoiwQMgv8cvW6qbHSp/0v/9lUA/VQAgsgrXLd1v20fusBusjOPHLKK5YuyNwjxUVufTQK0oz2r50W7/uG/PlCVdrQofdiXZ2yl2O7OjHVedRZQDn0UbekakJWLXD1+q+cf9qVjmycYbWpel5ZQFngXwvAwTr5yTm69PNVypolPT352IMEbgwlobEAotW5Hn8oNIOFeBQUXffr1EigJvnk4AdnaND4eeR2obWXY4fYzGq4CLeAcugjeAEDXXMjSp86dUpVFGthXRGlBzRZ0zoVLLQiAcTnVjwsHNOVLBlHPZyoLHDuq++pbe9JAlYwK7N5/sTIKym4vgdpbI88eG+isoXbkwVU5b7Dp0QeOaL1Ppk+/11mTY1hJuyn6C5Gg4km2bHvQ+oxNJaeyPEAZc+WScCiAtHNB2Hp5ly9HNvNeam+o88CyqGP4DXVXnNjX7/wzUV6462VIo9SFXgGX9hVG/bQe9sP0uVfrgma+gpcVFy9fJGova6O4FdcqR4hFmjYfgRVLlOQtFwOy9fupI07D9Hcib0iZBaRoWaL7uOEQ5vjoezxFN61/yORR1+uxItUtvgLkTEZC1r+zPv1gQ9Oi307Q7o04uCiLQy20JXlR70c27KyqkGitYBy6L1eeofDvN9ykWwj/rhuf2eC1zMLy/F9BWUxdSvSsIkLqFvrOrRk9baoLigLy4VQSkWVBV6s2IoOro9NkOP8UtW2dGD99Kiaq9eTKVylLe1e/UaCKDzQb7YtG++1eq6N72VKl5dju2ZQ1XHUWUA59FG2pLiO7TxwGsWO6hxlM3NmOiVf6USLp/YT17bFanSgPfxhRA595Ya9ogryzRlrqV6UBcxZAOhRI3o3i8cEe/KT85wmMYM2Lh5trhP1lCkLgO26ZYOqCQAQ5i3bRE1eK2+qj0h7yMuULi/HjrR1ig59IzfhVTn0EfYGgvYbSAapUiYXmn92/hvCVSuuBHH9WLpIPpWzqrOm+Su05OLX22yxPoceqUtVG/dRDn2E/RaUuuFjgd0HjlPvkbOoZOG8cVCKO94/RgO7NhYpIEqUBWQs4GVKl5djy9hMtU18FlAOfYSteeOOI6lNk+pUIG8uemf9LpowYzljzj8vnPmLP12mnVw81KtdPapRoWiEzSw06lZp1Jtmj+/OlOkZCFfXyPkFpjNy6Fs2rBIaJdQoygJRaIGvvv2RNu86LHDRAaVYrkR+epSxw5UoC8hawMuULi/HlrWbap+4LKAc+ghb7/+3d/dRPpZ5HMc/RiO7HmbMFOmBympaUwkVSjtSUbES5ugAAAsqSURBVIctGw4qql1TnDDsqskwJpmRos4YzCDWUzpUhEbZDU1ZGe2yu4qVZ0o1Jyny/DR73/dQppnJzJj78fe+/+mczu93fb/X63t3+s79u+7rMvfEXWGunwy/wDrqe9LoQWpw1stRG7fsUt+kdC193Y419BW84N8Fe/Ok2Lq1o1W3TrSGjJqiqhdWUVzLxvpdi8YuZEPIwAj4/z8NW0phHv7DwwVbaENg0J+WPri5pMvN2CFQZKZYgQI09BWI6cRQLY2GfuXpAzZu79jPWgN+9mEi5mFT7bo9xUuxThSDGAggYAmY64znLlxubaVo7ed6+lq+cq26d7xTndrHqf7lddBCoFwCbi7pcjN2ubD4UsgK0ND7rPQ9+qVZT5PNPdMnTFugWhHV9aBxwql5gMvhI8c05bVsa0ZBPQLcZ+UiXQRCQsB8inlT4xjFXH15ofmOnTJPCb06KdY4ifm6mKtCwoJJ2iPg5pIuN2Pbo8moQRSgofdZVT/b+rkGj5ysrTu+VLVqVbVv/0FVrhxmvCRbVT8cOGTNptE1V+qNyc/6bGakiwACfhW41die8iPjl8OfX0HfStGv9SJvBBAIngANvU9reujwUe0/cLDE7M2XPrkQQAABJwRy12zQLcaL+mFhhc9OXvvJZuOQu4ZOpECMAAtMnLmoxNn17nmfrTN3M7atE2PwwAnQ0Pu8pOaa+XUbtmnv9wWnnpo/a5tP7LkQQAABBBAIgkBq+qwfp5FvHIu+c3eeNm7epfiHO+iRLu1snaKbsW2dGIMHToCG3sclNV9E65P4stXA7/5qj6KjaqpKeLjGpfVXw6sKr2X18TRJHQEEEEAAgUICs+cv1afG4WXPJ8U7LuNmbMcnS0DfCNDQ+6ZURRN9bOAotY272dpF4swhSeY2ceZuE3Mmpvh4ZqSOAAIIIIBAyQKHDh+xzhL5z9KpjjO5GdvxyRLQNwI09L4pVdFEzVNPV2VnWjvcnGnozU+Ze9XnGv+eCwEEEEAAgSAKnDx5SpkzFriyo5ubsYNYS+ZUMQI09BXj6Moo5s4SOW+mq0qVcKuhX2YcJjV30ft6Z1muXstMdiUngiKAQAkCHD7FrYFAuQTcPOfAzdjlwuJLIStAQ+/j0psnnXb/w53Wi7Dm03pzH/pYY8vKF5N7c4iLV+tKU+fVypAXAgh4VMDNcw7cjO3RcpCWRwVo6D1amLKmtfOLPNWo/mtFRdYo61f5PAIIIIAAAp4VcPOcAzdje7YgJOZJARp6T5aFpBBAAAEEEEDAFHDznAM3Y1N9vwm4+xM8Db3f7hfyRQABBBBAIEQFHu6bplfHDwnR2ds07VPGuBxfYxOuc8PS0DtnTSQEEEAAAQQQOA+B2NaPan3O9PMYga8iEEwBGnrP1dXdn2w8x0FCCCCAAAIInBagoedWQKB4ARp67gwEEEAAAQQQ8IXArt15qndZHV/kSpIIOClAQ++kNrFsEOAXDRtQGRIBBBDwjEBi2iR1u7+NmlzXUEePHVfyC1O1ZcduJfZ9UM2b/NYzeZIIAm4K0NC7qU9sBFwV4E0oV/kJjgACpRIwt4788K0M61T0CdPe0vbPv1bHe1ppTNZcLZiWWqox+BACQRegoQ96hZnfWQI8zed2QAABBPwmEPdAgj6YP9Y6PLFtt7/o9cnDVbd2lEraI95v8yNfBCpCgIa+IhQZ49wCPAw+txGfQAABBBAoItBr0Gg1NZbbbN35pcLDL9CopMeV9813erhfmt6bMwYxBBAwBGjouQ0QQAABBBBAwLMCX3+zV1kzFqqK0cz3/1Mn61T0PXv3ad2GrWrTqqln8yYxBJwUoKF3UptYCCCAAAIIIIAAAghUsAANfQWDMhwCCCAQEgIso/NWmQNcD3OrykzjCf3OL/J04sTJQu5vTH7WW3UgGwRcEgjBhp4XI1261wiLAAIIIIBAmQW69R6uFs1idVPjGFUOCyv0/ZY3xZZ5PL6AQBAFQrChD2IZmZMbAvxp6IY6MRFwUCDAT70dVDzvUB0fG+rx7Sn5v8F5F5kBzluAhv68CRkAAQQQQAABBOwSeHTAKI1PS1D1ar+yKwTjIuB7ARp635eQCSCAAALnFhiZMVtv/32l9h84pHFGczQy41WlP9dX18VcpWUr1ip59FR9tGjCuQfiE/YK8LC3iG/WzIV6d/nHuueOWxQVWUOVzvpEV+MEWS4EQlug4KdEGvrQvguYPQII+FRg+EvT1TbuZpVmDfGK1es0MGW8ZmYkKapWTUVH1rReMnzogbt0UVSEBxp6ulif3oaOpJ2YOqnEOC8MfcKRHAiCgNcFaOi9XiHyQwABBH4mcPz4CbXv8YyGD3qsVA399LlLtCTnY83JGlasJU/oucUQQAABfwvQ0Pu7fmSPAAIBFjh27Lgy/jpf2e+t0r4fDqr+ZXU04fmBeiRhpL7K+/bHmSc+2V09u7QrVmL4yzP01jsf6vjp7f463NVS5lPN2NaPata4JDW9/poiT+jNz6a/8oYWLlmpo8eO6fbmjZU8sIdqRdQIsDZT86rA2k82lSo18142L37vKRUXHwqYAA19wArKdBDwnAA7hZS7JCljpmnVv9ZrSEIPXXpJtDZt+0Lt72xhjXfj3b2UZTT3pVly88rsbH2w6r96dfyQH3P5pYY+NX2W1m/aodSn/6iqVS/Uc8YfBfn5+Zo8elC558IXESivwNMjJmrxslzVNE6IrWWsof9+3wHrD9xrf1NPJ06eNO7NgpEXTU8rbwi+h4DvBWjofV9CJoAAAkEUOHjoiG6770m9/OyTxR5vb1dDf+jwUd1qxJ0xdrAaN2pg0X762XZ1fWK4ViwYZ72UyIWAkwJpY2ep4dVXqEuHOFWqVMn643Le4g+tP3CT+j/kZCrEQsCzAjT0HigNDzA9UARSQMBjAhu37FKnXsP0/pvpqn1RZJHs7Groz8SNqFFNZ7YTyT+Vb+2OM3/qCMU0uMJjUqRji4CH1q00b99Hq97OVFjYT/vbnDLuSfMPz9zsTFumz6AI+E2Aht5vFSNfBBD4BYHg/Hn8v8071Tk+RTnz0nVxtHMN/Zm4cyamGHEjCllH14pQ+AWVuQMRcFTg3oeeVmpiLzW7oWCNvHmtWbdJQ1+Yondnv+hoLgRDwKsCNPRerYzX8wpO3+R1afILUQHziXir+/sqY0R/tb71xiIKTdvGKyO1v1rdcv05hcqyht5a6mPEfX5wvO5t0/ycY/MBBOwWWL7y33ombZJiY67UxVGR2rN3n7UMbNSQJ9TmtiZ2h2d8BHwhQEPvizKRJAIIhKJAotHErNuwTSl/fkSX1I6y1gy3aNbIejnw9z0HG08sYzQgvrO1rjiiprFEpoSrLA29OYT5UuzSFWuUPKCnrm1Yr6CB2rj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stru32f64
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"road-transport…169223.1400e9
"steel"109201.7520e9
"solid-waste-di…103141.0297e9
………
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"oil-and-gas-re…6849.7051e8
"oil-and-gas-pr…6603.4766e9
"copper-mining"5558.3548502e7
"iron-mining"5367.1405542e7
"pulp-and-paper…3878.3640643e7
"bauxite-mining…1758.114666e6
"petrochemicals…1161.4665e8
" + ], + "text/plain": [ + "shape: (31, 3)\n", + "┌───────────────────────────────────┬────────┬────────────────────┐\n", + "│ original_inventory_sector ┆ c ┆ emissions_quantity │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ str ┆ u32 ┆ f64 │\n", + "╞═══════════════════════════════════╪════════╪════════════════════╡\n", + "│ null ┆ 294849 ┆ -3.8651e9 │\n", + "│ domestic-shipping ┆ 213983 ┆ 1.9471e8 │\n", + "│ international-shipping ┆ 139957 ┆ 5.1798e8 │\n", + "│ wastewater-treatment-and-dischar… ┆ 53466 ┆ 1.3067e8 │\n", + "│ … ┆ … ┆ … │\n", + "│ iron-mining ┆ 536 ┆ 7.1405542e7 │\n", + "│ pulp-and-paper ┆ 387 ┆ 8.3640643e7 │\n", + "│ bauxite-mining ┆ 175 ┆ 8.114666e6 │\n", + "│ petrochemicals ┆ 116 ┆ 1.4665e8 │\n", + "└───────────────────────────────────┴────────┴────────────────────┘" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(sdf_gy\n", + " .group_by(c_original_inventory_sector)\n", + " .agg(c_source_id.count().alias(\"c\"), c_emissions_quantity.sum())\n", + " .collect()\n", + " .sort(\"c\", descending=True))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "2c34bbc9-db33-4fcb-8eba-da5afacff476", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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iso3_countryoriginal_inventory_sectoremissions_quantity
enumstrf64
"CHN""electricity-ge…4.5421e9
"USA""electricity-ge…1.4893e9
"CHN""coal-mining"1.0123e9
"CHN""steel"9.22971074e8
"USA""oil-and-gas-pr…8.5006e8
"USA""oil-and-gas-pr…8.4849e8
"USA""road-transport…8.2750e8
"CHN""cement"7.046727e8
"CHN""road-transport…4.0347e8
"CHN""rice-cultivati…3.9366e8
"CHN""synthetic-fert…2.9521e8
"CHN""chemicals"2.6414734e8
………
"CHN""enteric-fermen…2.6370e6
"FRA""aluminum"2.626109e6
"FRA""solid-waste-di…2.569196e6
"FRA""domestic-shipp…2.1999e6
"FRA""domestic-aviat…1.8067e6
"FRA""pulp-and-paper…938314.0
"CHN""bauxite-mining…830360.0
"FRA""water-reservoi…106100.867704
"FRA""oil-and-gas-pr…86660.769884
"FRA""rice-cultivati…0.0
"FRA"null-4.5304e7
"CHN"null-6.4086e8
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+ "text/html": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "px.bar(\n", + "(sdf_gy\n", + ".group_by(c_original_inventory_sector)\n", + " .agg(c_emissions_quantity.sum())\n", + " .sort([c_emissions_quantity], descending=True)\n", + " .collect()\n", + "),\n", + " \n", + " x=ORIGINAL_INVENTORY_SECTOR,y=\"emissions_quantity\",log_y=True)" + ] + }, + { + "cell_type": "markdown", + "id": "c0181b04-a9bd-4d6e-bb40-0c71979c9f5e", + "metadata": {}, + "source": [ + "# Joint analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "4d231c95-3f12-4a3e-905b-aa2588ba3b90", + "metadata": {}, + "outputs": [], + "source": [ + "cedf_gy_agg = (cedf_gy\n", + " .group_by(c_iso3_country, c_ct_package, c_ct_file)\n", + " .agg(c_emissions_quantity.sum())\n", + " )\n", + "\n", + "sdf_gy_agg = (sdf_gy\n", + " .group_by(c_iso3_country, c_ct_package, c_ct_file)\n", + " .agg(c_emissions_quantity.sum())\n", + " .collect()\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "22369338-e91b-405e-a016-4169546a566e", + "metadata": {}, + "source": [ + "Total emissions from country inventory" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "9cebc3d2-6895-4553-8d99-c15a6a0a4ff5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (2, 2)
is_emissionemissions_quantity
boolf64
false-2.1259e10
true7.6431e10
" + ], + "text/plain": [ + "shape: (2, 2)\n", + "┌─────────────┬────────────────────┐\n", + "│ is_emission ┆ emissions_quantity │\n", + "│ --- ┆ --- │\n", + "│ bool ┆ f64 │\n", + "╞═════════════╪════════════════════╡\n", + "│ false ┆ -2.1259e10 │\n", + "│ true ┆ 7.6431e10 │\n", + "└─────────────┴────────────────────┘" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(cedf_gy_agg\n", + " .with_columns((c_emissions_quantity > 0).alias(\"is_emission\"))\n", + " .group_by(\"is_emission\")\n", + " .agg(c_emissions_quantity.sum())\n", + " .sort(\"is_emission\")\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "9dea47b0-3a73-482c-aed8-3d6ef8ddb473", + "metadata": {}, + "source": [ + "Total emissions from source inventory" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "f57444c7-da3d-4236-b6c0-8194082c9979", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (2, 2)
is_emissionemissions_quantity
boolf64
false-5.7529e10
true9.5150e10
" + ], + "text/plain": [ + "shape: (2, 2)\n", + "┌─────────────┬────────────────────┐\n", + "│ is_emission ┆ emissions_quantity │\n", + "│ --- ┆ --- │\n", + "│ bool ┆ f64 │\n", + "╞═════════════╪════════════════════╡\n", + "│ false ┆ -5.7529e10 │\n", + "│ true ┆ 9.5150e10 │\n", + "└─────────────┴────────────────────┘" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(sdf_gy_agg\n", + " .with_columns((c_emissions_quantity > 0).alias(\"is_emission\"))\n", + " .group_by(\"is_emission\")\n", + " .agg(c_emissions_quantity.sum())\n", + " .sort(\"is_emission\")\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "a7699bf7-8e94-414a-836d-84aa0b60adb1", + "metadata": {}, + "source": [ + "TODO: there is a significant discrepancy between the total reported for each report." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "0f93bfef-5cf8-4183-a27c-f32db0a606f9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (12_916, 5)
iso3_countryct_packagect_fileemissions_quantity_semissions_quantity_ce
enumcatcatf64f64
"ABW""agriculture""enteric-fermen…null0.0
"CUW""agriculture""enteric-fermen…null0.0
"SWZ""agriculture""enteric-fermen…null47815.6
"VAT""agriculture""enteric-fermen…null0.0
"VGB""agriculture""enteric-fermen…null0.0
"IOT""agriculture""enteric-fermen…null0.0
"MAR""agriculture""enteric-fermen…null4.4698e6
"MNP""agriculture""enteric-fermen…null0.0
"ALB""agriculture""enteric-fermen…null517546.4
"BEL""agriculture""enteric-fermen…null308582.4
"COD""agriculture""enteric-fermen…null731715.6
"CYP""agriculture""enteric-fermen…null88902.8
……………
"GIN""agriculture""synthetic-fert…4917.187885null
"HKG""agriculture""enteric-fermen…0.0null
"LIE""agriculture""enteric-fermen…0.0null
"SUR""agriculture""synthetic-fert…494.277044null
"BRN""agriculture""synthetic-fert…8130.169221null
"BFA""agriculture""synthetic-fert…3200.893827null
"BWA""agriculture""synthetic-fert…3075.866695null
"ZNC""forestry_and_l…"net-shrubgrass…-82226.761935null
"ZNC""forestry_and_l…"forest-land-cl…2417.281475null
"TLS""agriculture""synthetic-fert…8746.57223null
"TKM""agriculture""synthetic-fert…46194.154235null
"MOZ""agriculture""synthetic-fert…6825.984899null
" + ], + "text/plain": [ + "shape: (12_916, 5)\n", + "┌──────────────┬────────────────────┬────────────────────┬────────────────────┬────────────────────┐\n", + "│ iso3_country ┆ ct_package ┆ ct_file ┆ emissions_quantity ┆ emissions_quantity │\n", + "│ --- ┆ --- ┆ --- ┆ _s ┆ _ce │\n", + "│ enum ┆ cat ┆ cat ┆ --- ┆ --- │\n", + "│ ┆ ┆ ┆ f64 ┆ f64 │\n", + "╞══════════════╪════════════════════╪════════════════════╪════════════════════╪════════════════════╡\n", + "│ ABW ┆ agriculture ┆ enteric-fermentati ┆ null ┆ 0.0 │\n", + "│ ┆ ┆ on-other ┆ ┆ │\n", + "│ CUW ┆ agriculture ┆ enteric-fermentati ┆ null ┆ 0.0 │\n", + "│ ┆ ┆ on-other ┆ ┆ │\n", + "│ SWZ ┆ agriculture ┆ enteric-fermentati ┆ null ┆ 47815.6 │\n", + "│ ┆ ┆ on-other ┆ ┆ │\n", + "│ VAT ┆ agriculture ┆ enteric-fermentati ┆ null ┆ 0.0 │\n", + "│ ┆ ┆ on-other ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ ZNC ┆ forestry_and_land_ ┆ forest-land-cleari ┆ 2417.281475 ┆ null │\n", + "│ ┆ use ┆ ng ┆ ┆ │\n", + "│ TLS ┆ agriculture ┆ synthetic-fertiliz ┆ 8746.57223 ┆ null │\n", + "│ ┆ ┆ er-application ┆ ┆ │\n", + "│ TKM ┆ agriculture ┆ synthetic-fertiliz ┆ 46194.154235 ┆ null │\n", + "│ ┆ ┆ er-application ┆ ┆ │\n", + "│ MOZ ┆ agriculture ┆ synthetic-fertiliz ┆ 6825.984899 ┆ null │\n", + "│ ┆ ┆ er-application ┆ ┆ │\n", + "└──────────────┴────────────────────┴────────────────────┴────────────────────┴────────────────────┘" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "EMISSIONS_QUANTITY_S = EMISSIONS_QUANTITY + \"_s\"\n", + "EMISSIONS_QUANTITY_CE = EMISSIONS_QUANTITY + \"_ce\"\n", + "jdf = (cedf_gy_agg\n", + " .join(sdf_gy_agg, on=[ISO3_COUNTRY, CT_PACKAGE, CT_FILE], suffix=\"_s\", how=\"outer\")\n", + ".with_columns(\n", + " c_iso3_country.fill_null(C(ISO3_COUNTRY+\"_s\")),\n", + " c_ct_package.fill_null(C(CT_PACKAGE+\"_s\")),\n", + " c_ct_file.fill_null(C(CT_FILE+\"_s\")),\n", + " c_emissions_quantity.alias(EMISSIONS_QUANTITY_CE),\n", + ").select(\n", + " c_iso3_country,\n", + " c_ct_package,\n", + " c_ct_file,\n", + " EMISSIONS_QUANTITY_S,\n", + " EMISSIONS_QUANTITY_CE\n", + "))\n", + "jdf" + ] + }, + { + "cell_type": "markdown", + "id": "93cdf3a5-bce1-49ee-8f03-374b08a717ca", + "metadata": {}, + "source": [ + "Sanity check to ensure that no emission was lost along the way" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "6c4d5a3e-50d2-4c30-801a-12836d8ac987", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (1, 5)
iso3_countryct_packagect_fileemissions_quantity_semissions_quantity_ce
enumcatcatf64f64
"GRC""power""electricity-ge…1.7217e71.8314e7
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" + ], + "text/plain": [ + "shape: (3, 3)\n", + "┌─────────────┬──────────────────────┬───────────────────────┐\n", + "│ is_emission ┆ emissions_quantity_s ┆ emissions_quantity_ce │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ bool ┆ f64 ┆ f64 │\n", + "╞═════════════╪══════════════════════╪═══════════════════════╡\n", + "│ true ┆ 9.4461e10 ┆ 7.6428e10 │\n", + "│ false ┆ -5.6840e10 ┆ -2.1257e10 │\n", + "│ null ┆ -461722.074512 ┆ 0.0 │\n", + "└─────────────┴──────────────────────┴───────────────────────┘" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(jdf\n", + " .with_columns(((C(EMISSIONS_QUANTITY_S) > 0) | (C(EMISSIONS_QUANTITY_CE) > 0)).alias(\"is_emission\"))\n", + " .group_by(\"is_emission\")\n", + " .agg(C(EMISSIONS_QUANTITY_S).sum(), C(EMISSIONS_QUANTITY_CE).sum()))" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "d7d95d2a-fc24-4939-acb2-a199e90287d4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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", + "text/html": [ + "
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\n", + "shape: (163, 6)
ct_packagect_fileiso3_countryemissions_quantity_semissions_quantity_cefound
catcatenumf64f64f64
"power""electricity-ge…"SLE"5000.016000.00.3125
"power""electricity-ge…"UGA"15000.081000.00.185185
"power""electricity-ge…"GNB"27000.067000.00.402985
"power""electricity-ge…"TCD"33000.0249000.00.13253
"power""electricity-ge…"DJI"38000.049000.00.77551
"power""electricity-ge…"NER"65000.0311000.00.209003
"power""electricity-ge…"BEN"76000.0166000.00.457831
"power""electricity-ge…"NAM"81000.089000.00.910112
"power""electricity-ge…"COD"83000.0321000.00.258567
"power""electricity-ge…"GIN"86000.0640000.00.134375
"power""electricity-ge…"GMB"108000.0255000.00.423529
"power""electricity-ge…"RWA"112000.0287000.00.390244
………………
"power""electricity-ge…"TWN"1.59274e81.6489e80.965941
"power""electricity-ge…"ZAF"1.99288e81.99571e80.998582
"power""electricity-ge…"IRN"2.07061e82.17963e80.949982
"power""electricity-ge…"IDN"2.32013e82.46401e80.941607
"power""electricity-ge…"DEU"2.35282e82.56218e80.918288
"power""electricity-ge…"SAU"2.53227e82.6305e80.962657
"power""electricity-ge…"KOR"2.55641e82.62354e80.974412
"power""electricity-ge…"JPN"4.14062e84.39829e80.941416
"power""electricity-ge…"RUS"5.33325e85.59267e80.953614
"power""electricity-ge…"IND"1.2134e91.2486e90.971774
"power""electricity-ge…"USA"1.4893e91.4955e90.995854
"power""electricity-ge…"CHN"4.5421e94.6779e90.970958
" + ], + "text/plain": [ + "shape: (163, 6)\n", + "┌────────────┬───────────────────┬──────────────┬───────────────────┬───────────────────┬──────────┐\n", + "│ ct_package ┆ ct_file ┆ iso3_country ┆ emissions_quantit ┆ emissions_quantit ┆ found │\n", + "│ --- ┆ --- ┆ --- ┆ y_s ┆ y_ce ┆ --- │\n", + "│ cat ┆ cat ┆ enum ┆ --- ┆ --- ┆ f64 │\n", + "│ ┆ ┆ ┆ f64 ┆ f64 ┆ │\n", + "╞════════════╪═══════════════════╪══════════════╪═══════════════════╪═══════════════════╪══════════╡\n", + "│ power ┆ electricity-gener ┆ SLE ┆ 5000.0 ┆ 16000.0 ┆ 0.3125 │\n", + "│ ┆ ation ┆ ┆ ┆ ┆ │\n", + "│ power ┆ electricity-gener ┆ UGA ┆ 15000.0 ┆ 81000.0 ┆ 0.185185 │\n", + "│ ┆ ation ┆ ┆ ┆ ┆ │\n", + "│ power ┆ electricity-gener ┆ GNB ┆ 27000.0 ┆ 67000.0 ┆ 0.402985 │\n", + "│ ┆ ation ┆ ┆ ┆ ┆ │\n", + "│ power ┆ electricity-gener ┆ TCD ┆ 33000.0 ┆ 249000.0 ┆ 0.13253 │\n", + "│ ┆ ation ┆ ┆ ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ power ┆ electricity-gener ┆ RUS ┆ 5.33325e8 ┆ 5.59267e8 ┆ 0.953614 │\n", + "│ ┆ ation ┆ ┆ ┆ ┆ │\n", + "│ power ┆ electricity-gener ┆ IND ┆ 1.2134e9 ┆ 1.2486e9 ┆ 0.971774 │\n", + "│ ┆ ation ┆ ┆ ┆ ┆ │\n", + "│ power ┆ electricity-gener ┆ USA ┆ 1.4893e9 ┆ 1.4955e9 ┆ 0.995854 │\n", + "│ ┆ ation ┆ ┆ ┆ ┆ │\n", + "│ power ┆ electricity-gener ┆ CHN ┆ 4.5421e9 ┆ 4.6779e9 ┆ 0.970958 │\n", + "│ ┆ ation ┆ ┆ ┆ ┆ │\n", + "└────────────┴───────────────────┴──────────────┴───────────────────┴───────────────────┴──────────┘" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "subs_df" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "98a79e9f-43cb-45e7-8549-cc2aa2f029ad", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "DEBUG:matplotlib:matplotlib data path: /home/tjhunter/work/carbonmap/science/climate_trace/.venv/lib/python3.10/site-packages/matplotlib/mpl-data\n", + "DEBUG:matplotlib:CONFIGDIR=/home/tjhunter/.config/matplotlib\n", + "DEBUG:matplotlib:interactive is False\n", + "DEBUG:matplotlib:platform is linux\n", + "DEBUG:matplotlib:CACHEDIR=/home/tjhunter/.cache/matplotlib\n", + "DEBUG:matplotlib.font_manager:Using fontManager instance from /home/tjhunter/.cache/matplotlib/fontlist-v330.json\n", + "WARNING:pytensor.tensor.blas:Using NumPy C-API based implementation for BLAS functions.\n" + ] + } + ], + "source": [ + "import arviz as az\n", + "import pymc as pm\n", + "import numpy as np\n", + "logging.getLogger(\"matplotlib\").setLevel(\"WARNING\")\n", + "logging.getLogger(\"filelock\").setLevel(\"WARNING\")" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "7bc3035f-5d44-4ae4-ae4b-a70fbfd0b04c", + "metadata": {}, + "outputs": [], + "source": [ + "basic_model = pm.Model()\n", + "\n", + "em_s = np.array([1.4893, 2.5, 5.0])\n", + "em_ce = np.array([1.4955, 1.0, 1.0])\n", + "\n", + "def shiftedGamma(mean, size):\n", + " alpha = 8.5\n", + " beta = 2.0\n", + " # Putting the observed value on the mode of the distribution\n", + " mode = (alpha-1) / beta\n", + " # Mapping 10.m -> 0, m -> 1.0\n", + " return mean * (4/3. - (1.0/3) * (1.0 / mode) * pm.Gamma.dist(alpha=alpha, beta = beta, size=size))\n", + "\n", + "with basic_model:\n", + " init_est = em_ce\n", + " epsi = pm.TruncatedNormal(\"epsi\", mu = init_est, sigma=0.5 * init_est, lower=init_est * 0.5, upper=init_est * 10.0)\n", + " cp = pm.CustomDist(\"cp\", epsi, dist=shiftedGamma, observed=em_ce)\n", + " ip = pm.CustomDist(\"ip\", epsi, dist=shiftedGamma, observed=em_s)\n", + "\n", + "# with basic_model:\n", + "# mean = 1.0\n", + "# alpha = 8.5\n", + "# beta = 2.5\n", + "# # Putting the observed value on the mode of the distribution\n", + "# mode = (alpha-1) / beta\n", + "# # Mapping 4.m -> 0, m -> 1.0\n", + "# res = pm.Deterministic(\"pc\", mean * (4/3. - (1.0/3) * (1.0 / mode) * pm.Gamma(\"gam\", alpha=alpha, beta = beta)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "259e0352-2c14-4c10-834f-62bfdf7488e7", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:pymc.sampling.mcmc:Auto-assigning NUTS sampler...\n", + "INFO:pymc.sampling.mcmc:Initializing NUTS using jitter+adapt_diag...\n", + "INFO:pymc.sampling.mcmc:Multiprocess sampling (4 chains in 4 jobs)\n", + "INFO:pymc.sampling.mcmc:NUTS: [epsi]\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "
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step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1531.2619304730674.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 2106.1051656863983.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 3722.466882441551.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1305.9654349923946.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1038.5129616417235.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 17536.169913009326.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 5647.055561227237.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1689.8615656169666.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1460.0419096957983.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1055.972918046751.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 5147.260470310525.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 10529.38165208882.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 4228.661923273439.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1271.6685896430693.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 3118.8017076741685.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1309.8491936496227.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 35154.4731015717.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 3604.2682822398997.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1842.0076232103413.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1817.1840971448275.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1102.8433734595544.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1027.8079879592774.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 2330.0343520601264.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 2760.5998211858036.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 2679.2401135116706.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: 1478.1124079931085.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "DEBUG:pymc.stats.convergence:Energy change in leapfrog step is too large: inf.\n", + "INFO:pymc.sampling.mcmc:Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 1 seconds.\n", + "ERROR:pymc.stats.convergence:There were 26 divergences after tuning. Increase `target_accept` or reparameterize.\n" + ] + } + ], + "source": [ + "with basic_model:\n", + " # draw 1000 posterior samples\n", + " idata = pm.sample()" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "87252c9d-412b-4228-b982-5855204742b6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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meansdhdi_3%hdi_97%mcse_meanmcse_sdess_bulkess_tailr_hat
epsi[0]1.530.141.281.790.00.02814.462120.881.0
epsi[1]2.250.142.022.500.00.02449.411774.921.0
epsi[2]4.130.133.914.380.00.03219.412628.101.0
\n", + "
" + ], + "text/plain": [ + " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk ess_tail \\\n", + "epsi[0] 1.53 0.14 1.28 1.79 0.0 0.0 2814.46 2120.88 \n", + "epsi[1] 2.25 0.14 2.02 2.50 0.0 0.0 2449.41 1774.92 \n", + "epsi[2] 4.13 0.13 3.91 4.38 0.0 0.0 3219.41 2628.10 \n", + "\n", + " r_hat \n", + "epsi[0] 1.0 \n", + "epsi[1] 1.0 \n", + "epsi[2] 1.0 " + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "az.summary(idata, round_to=2)" + ] + }, + { + "cell_type": "markdown", + "id": "9ce15719-083c-44b1-ab67-c2dab8ca985d", + "metadata": {}, + "source": [ + "# Analyzing error bounds" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "3af461c5-e692-43c9-9260-a8b681601138", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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iso3_countryct_fileconf_total_co2e_100yrgwpct_packagecountemissions_quantity
enumcatcatcatu32f64
"BRA""removals""medium""forestry_and_l…5597-4.8601e9
"COD""removals""medium""forestry_and_l…267-4.6924e9
"AGO""removals""medium""forestry_and_l…177-3.4949e9
"MOZ""removals""medium""forestry_and_l…141-3.0537e9
"ZMB""removals""medium""forestry_and_l…126-2.7422e9
"RUS""net-forest-lan…"medium""forestry_and_l…2479-2.2479e9
"AUS""removals""medium""forestry_and_l…551-2.2324e9
"BRA""net-forest-lan…"medium""forestry_and_l…5597-1.9387e9
"RUS""removals""medium""forestry_and_l…2479-1.9316e9
"USA""removals""medium""forestry_and_l…3195-1.7630e9
"CAF""removals""medium""forestry_and_l…69-1.5976e9
"BRA""net-shrubgrass…"medium""forestry_and_l…5597-1.2465e9
………………
"BRA""forest-land-fi…"low""forestry_and_l…23381.1465e9
"USA""forest-land-cl…"low""forestry_and_l…30041.1858e9
"IND""electricity-ge…"medium""power"4711.2134e9
"USA""electricity-ge…"medium""power"21601.4784e9
"CAF""forest-land-fi…"low""forestry_and_l…692.0777e9
"AUS""forest-land-fi…"low""forestry_and_l…2772.4736e9
"ZMB""forest-land-fi…"low""forestry_and_l…1263.1439e9
"BRA""forest-land-cl…"low""forestry_and_l…55713.1661e9
"AGO""forest-land-fi…"low""forestry_and_l…1703.3166e9
"COD""forest-land-fi…"low""forestry_and_l…2193.6139e9
"MOZ""forest-land-fi…"low""forestry_and_l…1413.7217e9
"CHN""electricity-ge…"medium""power"12254.5421e9
" + ], + "text/plain": [ + "shape: (5_585, 6)\n", + "┌──────────────┬──────────────────┬──────────────────┬──────────────────┬───────┬──────────────────┐\n", + "│ iso3_country ┆ ct_file ┆ conf_total_co2e_ ┆ ct_package ┆ count ┆ emissions_quanti │\n", + "│ --- ┆ --- ┆ 100yrgwp ┆ --- ┆ --- ┆ ty │\n", + "│ enum ┆ cat ┆ --- ┆ cat ┆ u32 ┆ --- │\n", + "│ ┆ ┆ cat ┆ ┆ ┆ f64 │\n", + "╞══════════════╪══════════════════╪══════════════════╪══════════════════╪═══════╪══════════════════╡\n", + "│ BRA ┆ removals ┆ medium ┆ forestry_and_lan ┆ 5597 ┆ -4.8601e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ COD ┆ removals ┆ medium ┆ forestry_and_lan ┆ 267 ┆ -4.6924e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ AGO ┆ removals ┆ medium ┆ forestry_and_lan ┆ 177 ┆ -3.4949e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ MOZ ┆ removals ┆ medium ┆ forestry_and_lan ┆ 141 ┆ -3.0537e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ AGO ┆ forest-land-fire ┆ low ┆ forestry_and_lan ┆ 170 ┆ 3.3166e9 │\n", + "│ ┆ s ┆ ┆ d_use ┆ ┆ │\n", + "│ COD ┆ forest-land-fire ┆ low ┆ forestry_and_lan ┆ 219 ┆ 3.6139e9 │\n", + "│ ┆ s ┆ ┆ d_use ┆ ┆ │\n", + "│ MOZ ┆ forest-land-fire ┆ low ┆ forestry_and_lan ┆ 141 ┆ 3.7217e9 │\n", + "│ ┆ s ┆ ┆ d_use ┆ ┆ │\n", + "│ CHN ┆ electricity-gene ┆ medium ┆ power ┆ 1225 ┆ 4.5421e9 │\n", + "│ ┆ ration ┆ ┆ ┆ ┆ │\n", + "└──────────────┴──────────────────┴──────────────────┴──────────────────┴───────┴──────────────────┘" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df= (sdf_gy\n", + " .group_by([c_iso3_country, c_ct_file, c_conf_total_co2e_100yrgwp, c_ct_package])\n", + " .agg(pl.count().alias(\"count\"), c_emissions_quantity.sum())\n", + " .collect()\n", + " # .sort(by=[ORIGINAL_INVENTORY_SECTOR, \"conf_total_co2e_100yrgwp\"])\n", + " .sort(by=c_emissions_quantity)\n", + ")\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "id": "77e2e956-e701-4659-8f45-1eda8cd57d33", + "metadata": {}, + "outputs": [], + "source": [ + "import scipy as sp\n", + "margins = {\"very high\": 0.01, \"high\": 0.05,\"medium\":0.25, \"low\": 0.5, \"very low\": 1.}\n", + "# margins = {\"very high\": 0.01, \"high\": 0.05,\"medium\":0.1, \"low\": 0.15, \"very low\": 0.2}\n", + "\n", + "ERR_MARGIN = \"err_margin\"\n", + "rankings = (df.with_columns(\n", + " (c_conf_total_co2e_100yrgwp.replace(margins, return_dtype=pl.Float32, default=margins[\"very low\"])\n", + " * c_emissions_quantity).alias(ERR_MARGIN)\n", + ").group_by(c_iso3_country, c_ct_file, c_ct_package)\n", + " .agg(c_emissions_quantity.sum(), C(ERR_MARGIN).sum())\n", + " .sort(by=ERR_MARGIN, descending=True)\n", + " .with_row_index()\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "id": "006fe01b-3d84-4adc-9e3c-d3d211dc661a", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=power
iso3_country=%{x}
err_margin=%{y}", + "hovertext": [ + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation" + ], + "legendgroup": "power", + "marker": { + "color": "#636efa", + "pattern": { + "shape": "" + } + }, + "name": "power", + "offsetgroup": "power", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "USA", + "IND", + "RUS", + "JPN", + "SAU", + "IDN", + "MEX", + "AUS", + "BRA" + ], + "xaxis": "x", + "y": [ + 1135520250, + 380505500, + 303344500, + 133331250, + 110116250, + 63306750, + 58003250, + 40048750, + 35435750, + 11386500 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=fossil_fuel_operations
iso3_country=%{x}
err_margin=%{y}", + "hovertext": [ + "coal-mining", + "oil-and-gas-production-and-transport-sub-field", + "oil-and-gas-production-and-transport", + "oil-and-gas-production-and-transport", + "oil-and-gas-production-and-transport", + "oil-and-gas-refining", + "oil-and-gas-refining", + "coal-mining", + "oil-and-gas-refining", + "coal-mining", + "oil-and-gas-production-and-transport", + "coal-mining", + "oil-and-gas-production-and-transport", + "oil-and-gas-production-and-transport", + "oil-and-gas-production-and-transport", + "coal-mining", + "oil-and-gas-refining", + "coal-mining", + "oil-and-gas-refining", + "oil-and-gas-refining", + "oil-and-gas-refining", + "oil-and-gas-refining", + "oil-and-gas-production-and-transport", + "oil-and-gas-production-and-transport", + "oil-and-gas-refining", + "coal-mining", + "oil-and-gas-production-and-transport", + "oil-and-gas-refining", + "coal-mining", + "coal-mining" + ], + "legendgroup": "fossil_fuel_operations", + "marker": { + "color": "#EF553B", + "pattern": { + "shape": "" + } + }, + "name": "fossil_fuel_operations", + "offsetgroup": "fossil_fuel_operations", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "USA", + "RUS", + "USA", + "SAU", + "CHN", + "RUS", + "USA", + "IND", + "AUS", + "CHN", + "RUS", + "BRA", + "AUS", + "IDN", + "IND", + "SAU", + "IDN", + "BRA", + "USA", + "JPN", + "IDN", + "IND", + "MEX", + "MEX", + "MEX", + "JPN", + "AUS", + "BRA", + "JPN" + ], + "xaxis": "x", + "y": [ + 506144954.56126684, + 482893133.77916634, + 423472782.07985336, + 215573856.9080299, + 112742448.54645227, + 95264030.97744998, + 49339484.871300004, + 44362801.253050275, + 38195346.21710001, + 36943786.29317708, + 35861735.582544066, + 35483740.927065484, + 34153786.872586966, + 28843816.01394186, + 18616093.85234346, + 16686102.939899668, + 16567250.22425, + 12958929.672789441, + 11927786.089000002, + 9268430.392289868, + 9237034.914725002, + 9142905.82427, + 7464836.714518398, + 6609319.16636112, + 4071533.34295, + 498379.0042848399, + 212450.44258987345, + 127217.39689568692, + 88798.66614617534, + 62922.87288308509 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=manufacturing
iso3_country=%{x}
err_margin=%{y}", + "hovertext": [ + "steel", + "cement", + "chemicals", + "steel", + "steel", + "cement", + "aluminum", + "other-manufacturing", + "chemicals", + "steel", + "chemicals", + "petrochemicals", + "chemicals", + "steel", + "steel", + "cement", + "pulp-and-paper", + "petrochemicals", + "cement", + "aluminum", + "cement", + "cement", + "cement", + "steel", + "cement", + "pulp-and-paper", + "pulp-and-paper", + "cement", + "steel", + "aluminum", + "steel", + "pulp-and-paper", + "aluminum", + "chemicals", + "chemicals", + "pulp-and-paper", + "aluminum", + "steel", + "chemicals", + "chemicals", + "cement", + "aluminum", + "aluminum", + "aluminum", + "pulp-and-paper", + "chemicals", + "chemicals", + "pulp-and-paper", + "aluminum" + ], + "legendgroup": "manufacturing", + "marker": { + "color": "#00cc96", + "pattern": { + "shape": "" + } + }, + "name": "manufacturing", + "offsetgroup": "manufacturing", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "CHN", + "CHN", + "IND", + "JPN", + "IND", + "CHN", + "USA", + "RUS", + "RUS", + "USA", + "CHN", + "IND", + "USA", + "BRA", + "USA", + "USA", + "USA", + "IDN", + "AUS", + "SAU", + "BRA", + "MEX", + "IDN", + "JPN", + "BRA", + "CHN", + "RUS", + "MEX", + "IND", + "AUS", + "IDN", + "RUS", + "JPN", + "BRA", + "RUS", + "IDN", + "SAU", + "MEX", + "SAU", + "AUS", + "SAU", + "BRA", + "USA", + "IND", + "AUS", + "IDN", + "AUS", + "JPN" + ], + "xaxis": "x", + "y": [ + 461485537, + 176168175, + 157800280.5, + 79812926.5, + 63937060, + 63149232, + 53374476.75, + 48837304.13777141, + 41043270, + 33528742, + 30781873.5, + 30507126.101149995, + 29325777.5, + 21658276.5, + 20553223, + 14782440, + 12783757.5, + 11438266.256524997, + 10423100.75, + 9903495.5, + 9093598.25, + 8813814.5, + 8122178, + 8060880, + 7108621.5, + 6354978.5, + 5978548.5, + 5834535, + 5630312.5, + 4473887.5, + 3175633.5, + 2497598, + 2159160.75, + 2099352.5, + 1883040.5, + 1746940, + 1737501, + 1685675, + 1419672.5, + 1332954, + 1145647.25, + 1069544, + 914600, + 777753.75, + 701355.5, + 300720, + 211335, + 147864.5, + 85744.75 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=transportation
iso3_country=%{x}
err_margin=%{y}", + "hovertext": [ + "road-transportation", + "road-transportation", + "road-transportation", + "road-transportation", + "road-transportation", + "road-transportation", + "international-shipping", + "international-shipping", + "domestic-shipping", + "road-transportation", + "road-transportation", + "road-transportation", + "international-shipping", + "international-shipping", + "international-shipping", + "road-transportation", + "domestic-shipping", + "domestic-shipping", + "international-shipping", + "domestic-shipping", + "international-shipping", + "international-shipping", + "international-shipping", + "international-shipping", + "domestic-aviation", + "domestic-shipping", + "domestic-shipping", + "domestic-shipping", + "domestic-shipping", + "domestic-aviation", + "international-aviation", + "domestic-shipping", + "domestic-shipping", + "domestic-aviation", + "domestic-aviation", + "international-aviation", + "domestic-aviation", + "international-aviation", + "international-aviation", + "domestic-aviation", + "international-aviation", + "domestic-aviation", + "international-aviation", + "domestic-aviation", + "international-aviation", + "domestic-aviation", + "international-aviation", + "international-aviation", + "international-aviation", + "domestic-aviation" + ], + "legendgroup": "transportation", + "marker": { + "color": "#ab63fa", + "pattern": { + "shape": "" + } + }, + "name": "transportation", + "offsetgroup": "transportation", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "USA", + "CHN", + "JPN", + "BRA", + "MEX", + "IND", + "CHN", + "USA", + "CHN", + "RUS", + "AUS", + "IDN", + "AUS", + "BRA", + "JPN", + "SAU", + "USA", + "JPN", + "IND", + "IDN", + "SAU", + "MEX", + "IDN", + "RUS", + "USA", + "BRA", + "RUS", + "IND", + "AUS", + "CHN", + "USA", + "MEX", + "SAU", + "IND", + "RUS", + "CHN", + "JPN", + "IND", + "JPN", + "BRA", + "AUS", + "IDN", + "MEX", + "AUS", + "SAU", + "MEX", + "BRA", + "RUS", + "IDN", + "SAU" + ], + "xaxis": "x", + "y": [ + 413749221.7772734, + 201733184.59332314, + 98788273.77491634, + 59023436.50045672, + 53863222.39684388, + 52572033.71043159, + 49197209.74029004, + 36217471.469945885, + 30918717.359692086, + 25979589.141394563, + 25366995.96810233, + 22076489.47267748, + 21126393.192253686, + 19278252.0696365, + 18202883.63029748, + 15800549.122138472, + 15127006.260504434, + 14890549.853085926, + 12085489.94578321, + 11002308.331899347, + 7502284.767246966, + 7067323.766661348, + 7015835.088696944, + 6460621.856054698, + 6421649.53160419, + 6382934.936150068, + 5507173.0724411635, + 4892648.271249217, + 4193195.678601363, + 3707797.642957098, + 3364776.402962669, + 2361648.7568414756, + 1577698.1910965182, + 672687.2522111502, + 652503.8514037399, + 581944.6854049711, + 562562.8529846122, + 520879.5235957431, + 511047.1147755999, + 491635.357759684, + 417722.17675946787, + 401755.0653654636, + 392626.71235693345, + 363028.63504188275, + 343103.6985836236, + 321879.05824690463, + 296492.64700319193, + 205539.79598889616, + 147037.731687514, + 135674.1451439288 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=agriculture
iso3_country=%{x}
err_margin=%{y}", + "hovertext": [ + "cropland-fires", + "cropland-fires", + "enteric-fermentation-cattle-pasture", + "synthetic-fertilizer-application", + "cropland-fires", + "synthetic-fertilizer-application", + "enteric-fermentation-cattle-pasture", + "manure-left-on-pasture-cattle", + "enteric-fermentation-cattle-pasture", + "synthetic-fertilizer-application", + "cropland-fires", + "cropland-fires", + "cropland-fires", + "enteric-fermentation-cattle-pasture", + "cropland-fires", + "synthetic-fertilizer-application", + "synthetic-fertilizer-application", + "synthetic-fertilizer-application", + "rice-cultivation", + "cropland-fires", + "manure-left-on-pasture-cattle", + "enteric-fermentation-cattle-pasture", + "rice-cultivation", + "enteric-fermentation-cattle-pasture", + "synthetic-fertilizer-application", + "manure-left-on-pasture-cattle", + "rice-cultivation", + "manure-left-on-pasture-cattle", + "enteric-fermentation-cattle-feedlot", + "manure-left-on-pasture-cattle", + "synthetic-fertilizer-application", + "manure-left-on-pasture-cattle", + "enteric-fermentation-cattle-pasture", + "rice-cultivation", + "synthetic-fertilizer-application", + "rice-cultivation", + "enteric-fermentation-cattle-pasture", + "manure-management-cattle-feedlot", + "enteric-fermentation-cattle-pasture", + "manure-left-on-pasture-cattle", + "rice-cultivation", + "manure-management-cattle-feedlot", + "enteric-fermentation-cattle-feedlot", + "manure-left-on-pasture-cattle", + "enteric-fermentation-cattle-feedlot", + "cropland-fires", + "cropland-fires", + "manure-left-on-pasture-cattle", + "enteric-fermentation-cattle-feedlot", + "enteric-fermentation-cattle-feedlot", + "enteric-fermentation-cattle-feedlot", + "enteric-fermentation-cattle-pasture", + "manure-management-cattle-feedlot", + "manure-left-on-pasture-cattle", + "manure-management-cattle-feedlot", + "manure-management-cattle-feedlot", + "manure-management-cattle-feedlot", + "synthetic-fertilizer-application", + "rice-cultivation" + ], + "legendgroup": "agriculture", + "marker": { + "color": "#FFA15A", + "pattern": { + "shape": "" + } + }, + "name": "agriculture", + "offsetgroup": "agriculture", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "BRA", + "IND", + "BRA", + "CHN", + "IDN", + "IND", + "IND", + "BRA", + "USA", + "IDN", + "USA", + "RUS", + "MEX", + "MEX", + "AUS", + "RUS", + "BRA", + "AUS", + "CHN", + "CHN", + "USA", + "AUS", + "IND", + "IDN", + "MEX", + "IND", + "IDN", + "MEX", + "USA", + "AUS", + "USA", + "IDN", + "RUS", + "JPN", + "JPN", + "BRA", + "CHN", + "USA", + "JPN", + "RUS", + "USA", + "CHN", + "RUS", + "CHN", + "CHN", + "SAU", + "JPN", + "JPN", + "BRA", + "AUS", + "MEX", + "SAU", + "RUS", + "SAU", + "AUS", + "BRA", + "MEX", + "SAU", + "RUS" + ], + "xaxis": "x", + "y": [ + 353528152.2541918, + 269702650.7642192, + 196912125.9965854, + 147610335.58049294, + 142818726.71389616, + 60508489.17211499, + 57390596.55462504, + 56676830.67001902, + 54965720.325897306, + 40306632.64341372, + 38363574.56434143, + 37795592.815871626, + 32442420.872552447, + 27947234.995951585, + 24485728.533020396, + 24257412.46624784, + 21438345.98639603, + 19794466.581479173, + 19682851.681072235, + 18354373.930343766, + 18256963.50989676, + 18066829.690600406, + 17425174.462506283, + 15126704.917518653, + 13668849.192898426, + 13071470.057324901, + 11919166.215627173, + 8043997.714304318, + 7974766.675000021, + 7142076.895188778, + 7122929.544205212, + 5097908.176847357, + 4367259.182262428, + 4079540.7667016494, + 3484739.0220892397, + 3351645.137626039, + 2532968.386646312, + 2114763.724999989, + 1907057.2770603881, + 1494120.8888299353, + 1158736.3679252586, + 911534.525000046, + 857743.8, + 853676.9653023914, + 659246.1749999998, + 659244.4521116232, + 651544.8682908715, + 642664.3677862096, + 581064.6750000048, + 396634.35000000015, + 232078.1999999996, + 216884.39483946504, + 90058.52499999998, + 73095.74533926492, + 15054.974999999997, + 11270.649999999958, + 4243.449999999999, + 2660.04052429235, + 1382.2139296973419 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=waste
iso3_country=%{x}
err_margin=%{y}", + "hovertext": [ + "solid-waste-disposal", + "solid-waste-disposal", + "solid-waste-disposal", + "solid-waste-disposal", + "solid-waste-disposal", + "solid-waste-disposal", + "solid-waste-disposal", + "wastewater-treatment-and-discharge", + "wastewater-treatment-and-discharge", + "wastewater-treatment-and-discharge", + "wastewater-treatment-and-discharge", + "wastewater-treatment-and-discharge", + "solid-waste-disposal", + "solid-waste-disposal", + "wastewater-treatment-and-discharge", + "wastewater-treatment-and-discharge", + "solid-waste-disposal", + "wastewater-treatment-and-discharge", + "wastewater-treatment-and-discharge", + "wastewater-treatment-and-discharge" + ], + "legendgroup": "waste", + "marker": { + "color": "#19d3f3", + "pattern": { + "shape": "" + } + }, + "name": "waste", + "offsetgroup": "waste", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "RUS", + "MEX", + "USA", + "CHN", + "BRA", + "AUS", + "IND", + "USA", + "CHN", + "IND", + "BRA", + "JPN", + "IDN", + "JPN", + "RUS", + "MEX", + "SAU", + "IDN", + "AUS", + "SAU" + ], + "xaxis": "x", + "y": [ + 87461311.1, + 66571155.66499998, + 43497704.03131298, + 28371735.58000001, + 25174932.789999995, + 15908959.705, + 13357649.234999998, + 11725764.961388389, + 3725099.0129526956, + 2893120.5238977554, + 2669451.5835356005, + 2415625.347790851, + 2392995.690000002, + 2369213.3850000002, + 2367513.534312601, + 1954224.8544013884, + 1062399.295, + 815343.7062741695, + 568870.2164680543, + 112192.62744626896 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=mineral_extraction
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", 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emissions_quantityerr_margin
f64f64
3.7621e102.5173e10
" + ], + "text/plain": [ + "shape: (1, 2)\n", + "┌────────────────────┬────────────┐\n", + "│ emissions_quantity ┆ err_margin │\n", + "│ --- ┆ --- │\n", + "│ f64 ┆ f64 │\n", + "╞════════════════════╪════════════╡\n", + "│ 3.7621e10 ┆ 2.5173e10 │\n", + "└────────────────────┴────────────┘" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rankings.select(c_emissions_quantity.sum(), C(ERR_MARGIN).sum())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5bb687c7-a8d0-400f-8c26-527c0208548c", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/_sources/ingestion.ipynb b/_sources/ingestion.ipynb new file mode 100644 index 0000000..0a0389f --- /dev/null +++ b/_sources/ingestion.ipynb @@ -0,0 +1,69 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data ingestion and formatting\n", + "\n", + "This notebook explains how to convert the Climate TRACE dataset to a format that is more appropriate for data science. \n", + "\n", + "```{note}\n", + "This section is relevant for data engineers, or data scientists who want to understand how the data \n", + "has been prepared. Skip if you just want to access the final, prepared data.\n", + "```\n", + "\n", + "The original data from Climate TRACE is offered as a series of CSV files bundled in ZIP archives. That format is universally understood, but it is not the most effective for effective analysis.\n", + "\n", + "Instead, we are going to use the Parquet format. This format has a number of advantages:\n", + "- it is _column-based_ : data systems can process big chunks of data at once, rather than line by line. Also, depending on the information requested, systems will read only the relevant columns and skip the rest very effectively\n", + "- it is _structured_ : basic information about numbers, categories, ... are preserved. This provides a large speed boost\n", + "- it is _universal_ : most modern data systems will be able to read it\n", + "\n", + "```{admonition} TODO\n", + "complete this notebook\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/_sources/initial_analysis.ipynb b/_sources/initial_analysis.ipynb new file mode 100644 index 0000000..f22679f --- /dev/null +++ b/_sources/initial_analysis.ipynb @@ -0,0 +1,8265 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "5b280157-80eb-498c-9b37-2d60257eb3f7", + "metadata": {}, + "source": [ + "# Data exploration of the Climate TRACE dataset\n", + "\n", + "In this chapter, we look at the dataset and we answer a few questions:\n", + "- which countries are the biggest emitters?\n", + "- what sectors are the most responsible for emissions?\n", + "\n", + "In a second part, we compare two different views on emissions:\n", + "\n", + "- the _source_ view, which looks from a bottom up view at all the sources (factories, mines, farms, ...)\n", + "- the _country_ view, which is a top down approach, and derives many values from aggregate economic activity, for example how many tons of coal were burned to produced annually. This is the official reporting method followed by countries to report their emissions to the United Nations as part of the Paris agreements.\n", + "\n", + "The data has already been prepared from the original Climate TRACE dataset. If you want to understand the preprocessing, read the chapter Ingestion.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "098161b5-cbdc-4974-b579-3159cfb107d1", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "markdown", + "id": "50e077ce-d044-4840-80a8-f38f232d39d8", + "metadata": {}, + "source": [ + "We import all the libraries that we will use in this notebook:\n", + "- the [Polars](https://pola.rs/) library, a very fast package with a clear interface.\n", + "- the [Plotly Express](https://plotly.com/python/plotly-express/) visualization library\n", + "- the `ctrace` package (included in this repository), that contains tools to read and understand the Climate TRACE data." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "14b5ed9f-45f7-471f-b654-627501391f32", + "metadata": {}, + "outputs": [], + "source": [ + "import polars as pl\n", + "import plotly.express as px\n", + "\n", + "from ctrace.constants import *\n", + "import ctrace as ct" + ] + }, + { + "cell_type": "markdown", + "id": "6a5363f2-ed1b-4c04-92c6-0b096520967a", + "metadata": {}, + "source": [ + "The country emissions are available through the `read_country_emissions()` function. This function will download by default the latest set of reports (currently the V2, publised in November 2023). If the data has already been downloaded, it will use this copy.\n", + "\n", + "The format being returned is a Polars `DataFrame`. This format will be very familiar to people used to working with Pandas, Spark or R dataframes." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c9eea6a9-0f47-45bf-aa06-e156a03250fc", + "metadata": {}, + "outputs": [], + "source": [ + "cedf = ct.read_country_emissions()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "35f7d301-eb09-412d-94a7-696fbd5cb439", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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"ABW"2022-01-01 00:00:002022-12-31 00:00:00"other-agricult…"co2"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""other-agricult…
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"ABW"2022-01-01 00:00:002022-12-31 00:00:00"other-agricult…"ch4"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""other-agricult…
"ABW"2022-01-01 00:00:002022-12-31 00:00:00"other-agricult…"co2e_20yr"0.0"tonnes"null2023-10-23 11:43:08.395355null"agriculture""other-agricult…
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"TUV"2016-01-01 00:00:002016-12-31 00:00:00"wastewater-tre…"co2e_100yr"2516.497358"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:27.777139"waste""wastewater-tre…
"UGA"2016-01-01 00:00:002016-12-31 00:00:00"wastewater-tre…"co2e_20yr"1.6999e7"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:28.159334"waste""wastewater-tre…
"UGA"2015-01-01 00:00:002015-12-31 00:00:00"wastewater-tre…"co2e_20yr"1.6456e7"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:34.328448"waste""wastewater-tre…
"ZWE"2015-01-01 00:00:002015-12-31 00:00:00"wastewater-tre…"co2e_20yr"6.1586e6"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:34.624499"waste""wastewater-tre…
"ZWE"2015-01-01 00:00:002015-12-31 00:00:00"wastewater-tre…"co2e_100yr"2.1487e6"tonnes""annual"2023-10-06 14:56:33.4283282023-11-03 15:13:34.624499"waste""wastewater-tre…
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Here is how the emissions data is structured.\n", + "\n", + "This data is highly structured, which is reflected in the schema itself. This schema has a lot of enumerations (`iso3_country`, `gas`, ...), where only a few values are expected. For example, all the country names are represented by their official [ISO 3166 3-letter country codes](https://en.wikipedia.org/wiki/List_of_ISO_3166_country_codes). Internally, Polars can assign small integers to represent them all, which consumes less memory and speeds up manipulations. This has a further advantage: since we know the values to expect, we can give them names in the code such as `CH4`, `CO2`, .... We can use all the software tools to find and update references to various gas as we work with it. \n", + "\n", + "```{admonition} TODO\n", + "move all this part in its own notebook, this is about technical details\n", + "```\n", + "\n", + "```{admonition} TODO\n", + "finish all the enumerations in the code, there are still categories\n", + "```\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "37a1e1c6-a92c-4093-bc2e-2a70475adf0d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "OrderedDict([('iso3_country',\n", + " Enum(categories=['ABW', 'AFG', 'AGO', 'AIA', 'ALA', 'ALB', 'AND', 'ARE', 'ARG', 'ARM', 'ASM', 'ATA', 'ATF', 'ATG', 'AUS', 'AUT', 'AZE', 'BDI', 'BEL', 'BEN', 'BES', 'BFA', 'BGD', 'BGR', 'BHR', 'BHS', 'BIH', 'BLM', 'BLR', 'BLZ', 'BMU', 'BOL', 'BRA', 'BRB', 'BRN', 'BTN', 'BVT', 'BWA', 'CAF', 'CAN', 'CCK', 'CHE', 'CHL', 'CHN', 'CIV', 'CMR', 'COD', 'COG', 'COK', 'COL', 'COM', 'CPV', 'CRI', 'CUB', 'CUW', 'CXR', 'CYM', 'CYP', 'CZE', 'DEU', 'DJI', 'DMA', 'DNK', 'DOM', 'DZA', 'ECU', 'EGY', 'ERI', 'ESH', 'ESP', 'EST', 'ETH', 'FIN', 'FJI', 'FLK', 'FRA', 'FRO', 'FSM', 'GAB', 'GBR', 'GEO', 'GGY', 'GHA', 'GIB', 'GIN', 'GLP', 'GMB', 'GNB', 'GNQ', 'GRC', 'GRD', 'GRL', 'GTM', 'GUF', 'GUM', 'GUY', 'HKG', 'HMD', 'HND', 'HRV', 'HTI', 'HUN', 'IDN', 'IMN', 'IND', 'IOT', 'IRL', 'IRN', 'IRQ', 'ISL', 'ISR', 'ITA', 'JAM', 'JEY', 'JOR', 'JPN', 'KAZ', 'KEN', 'KGZ', 'KHM', 'KIR', 'KNA', 'KOR', 'KWT', 'LAO', 'LBN', 'LBR', 'LBY', 'LCA', 'LIE', 'LKA', 'LSO', 'LTU', 'LUX', 'LVA', 'MAC', 'MAF', 'MAR', 'MCO', 'MDA', 'MDG', 'MDV', 'MEX', 'MHL', 'MKD', 'MLI', 'MLT', 'MMR', 'MNE', 'MNG', 'MNP', 'MOZ', 'MRT', 'MSR', 'MTQ', 'MUS', 'MWI', 'MYS', 'MYT', 'NAM', 'NCL', 'NER', 'NFK', 'NGA', 'NIC', 'NIU', 'NLD', 'NOR', 'NPL', 'NRU', 'NZL', 'OMN', 'PAK', 'PAN', 'PCN', 'PER', 'PHL', 'PLW', 'PNG', 'POL', 'PRI', 'PRK', 'PRT', 'PRY', 'PSE', 'PYF', 'QAT', 'REU', 'ROU', 'RUS', 'RWA', 'SAU', 'SDN', 'SEN', 'SGP', 'SGS', 'SHN', 'SJM', 'SLB', 'SLE', 'SLV', 'SMR', 'SOM', 'SPM', 'SRB', 'SSD', 'STP', 'SUR', 'SVK', 'SVN', 'SWE', 'SWZ', 'SXM', 'SYC', 'SYR', 'TCA', 'TCD', 'TGO', 'THA', 'TJK', 'TKL', 'TKM', 'TLS', 'TON', 'TTO', 'TUN', 'TUR', 'TUV', 'TWN', 'TZA', 'UGA', 'UKR', 'UMI', 'URY', 'USA', 'UZB', 'VAT', 'VCT', 'VEN', 'VGB', 'VIR', 'VNM', 'VUT', 'WLF', 'WSM', 'XKX', 'YEM', 'ZAF', 'ZMB', 'ZWE', 'ZNC', 'UNK', 'SCG'])),\n", + " ('start_time', Datetime(time_unit='ns', time_zone=None)),\n", + " ('end_time', Datetime(time_unit='ns', time_zone=None)),\n", + " ('original_inventory_sector', String),\n", + " ('gas',\n", + " Enum(categories=['ch4', 'co2', 'co2e_20yr', 'co2e_100yr', 'n2o'])),\n", + " ('emissions_quantity', Float64),\n", + " ('emissions_quantity_units', String),\n", + " ('temporal_granularity',\n", + " Enum(categories=['annual', 'other', 'month', 'week', 'day', 'hour'])),\n", + " ('created_date', Datetime(time_unit='ns', time_zone=None)),\n", + " ('modified_date', Datetime(time_unit='ns', time_zone=None)),\n", + " ('ct_package', Categorical(ordering='physical')),\n", + " ('ct_file', Categorical(ordering='physical'))])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cedf.schema" + ] + }, + { + "cell_type": "markdown", + "id": "4aef5438-e8b1-41d5-bfa0-62307d4f9403", + "metadata": {}, + "source": [ + "Another trick is to define all the Dataframe _columns_ that we are going to manipulate.\n", + "For example, there is a column called `gas` that refers to all the gas being tabulated.\n", + "Coming from the Pandas world, it would be normal to refer to this column:\n", + "\n", + "```py\n", + "cedf_pdf[cedf_pdf[\"gas\"]==\"ch4\"]\n", + "```\n", + "\n", + "Polars offers a more succint syntax by considering an _abstract column_, for example for the gas:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "db31255d-3854-49b9-8490-2ea461423fef", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "col(\"gas\")" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pl.col(\"gas\")" + ] + }, + { + "cell_type": "markdown", + "id": "8d585d85-0c0b-45f1-b66e-6abc4a30be5d", + "metadata": {}, + "source": [ + "That `col(\"gas\")` refers to any dataframe column called `gas`. The `select` method operates on a polars dataframe takes such columns as instructions to select specific columns." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "6812f202-9759-42e2-b99a-9c7e43468ae6", + "metadata": {}, + "outputs": [], + "source": [ + "cedf.select(pl.col(\"gas\"));" + ] + }, + { + "cell_type": "markdown", + "id": "30478d30-6104-48ec-a8fd-41318eb7a2bd", + "metadata": {}, + "source": [ + "The `ctrace` library predefines all the columns defined in the Climate TRACE datasets, all prefixed by the `c_` prefix:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "78e09c07-6703-49d5-9dd2-d81e0662e6d4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "col(\"gas\")" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ct.constants.c_gas" + ] + }, + { + "cell_type": "markdown", + "id": "86de4661-d05a-4a26-9eb8-d875498f45e4", + "metadata": {}, + "source": [ + "This reduces the chance of making a typo, allows us to use the autocompletion features of editors, and it will catch any mistake before executing the code. Selecting all the data related to methane is simply:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "074dcb9e-af56-4afa-92f1-5c93b9c95c76", + "metadata": {}, + "outputs": [], + "source": [ + "cedf.filter(c_gas == CH4);" + ] + }, + { + "cell_type": "markdown", + "id": "4e061de9-2bea-4d69-9c49-3cf55f0997fd", + "metadata": {}, + "source": [ + "# Country checks\n", + "\n", + "In this section, we identify the biggest emitters and sort out a few unexpected insights.\n", + "\n", + "We focus this analysis on the year *2022* and on the aggregated emissions. You can look at how the results change when you focus on a specific gas (`co2`, `nh4`, ...) or on a shorter time horizon (`co2e_20yr`)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "b4d4b73d-59cb-43f4-ad37-f68c8746be4b", + "metadata": {}, + "outputs": [], + "source": [ + "gas = \"co2e_100yr\"\n", + "year = 2022\n", + "\n", + "cedf_gy = cedf.filter(c_gas == gas).filter(c_start_time.dt.year()==year)" + ] + }, + { + "cell_type": "markdown", + "id": "abca0337-d101-4f4e-bea0-e1b8d316411c", + "metadata": {}, + "source": [ + "First question: how much do we emit? 55GT of CO2e (gigatonnes of CO2 equivalent). Note the first wrinkle already: this takes into account the absorption by the vegetation. If we did not take into action the beneficial actions of our friends the trees, our emissions would be already higher. Trees will come back as a complicated topic.\n", + "\n", + "Here are the net emissions, taking into account all the contribution of the forestry and land use sector: 55GT of CO2 equivalent" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "fd631d03-f831-4e3e-96b9-9f46104d09e0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "px.bar(cedf_gy\n", + " .filter(c_emissions_quantity > 0)\n", + " .group_by(c_iso3_country)\n", + " .agg(c_emissions_quantity.sum())\n", + " .sort([c_emissions_quantity], descending=True)\n", + " .head(20)\n", + ",x=ISO3_COUNTRY, y=EMISSIONS_QUANTITY,log_y=False)\n" + ] + }, + { + "cell_type": "markdown", + "id": "d7b1770b-047a-42de-9047-920d0234af40", + "metadata": {}, + "source": [ + "Looking at each sector gives quickly a nuanced sector and shows the difference\n", + "between the various countries.\n", + "\n", + "- the Chinese electricity sector emits more than Western Europe combined. This is not to say that Europeans should not make efforts - they should!. But these efforts can come from many ways, such as incentivizing China to reduce the role of coal in its domestic supply of electricity.\n", + "\n", + "- the emissions from the oil and gas sector in Russia is bigger than all the emissions of Germany. These emissions are typically quick wins (fixing leaks on old pipes).\n", + "\n", + "- Angola and Mozambique have more gross emissions than Japan! Clearing forested areas are very bad for the climate and have only short-term economic benefits. Finding fairer ways to preserve natural resources would also go a long way towards helping developing countries achieve their goals.\n", + "\n", + "- France is about twice as big as Russia looking at the economy (GDP), yet it contributes much less\n", + "\n", + "```{admonition} CTODO\n", + "Check these conclusions with experts\n", + "```\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "5bb687c7-a8d0-400f-8c26-527c0208548c", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "ct_file=electricity-generation
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", + "text/html": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "px.bar(cedf_gy\n", + " .group_by(c_iso3_country, c_ct_file)\n", + " .agg(c_emissions_quantity.sum())\n", + " .sort([c_emissions_quantity], descending=True)\n", + " .filter(c_iso3_country.is_in([\n", + " \"CHN\", \"USA\", \"IND\", \"RUS\",\"MOZ\",\"FRA\", \"NLD\"]))\n", + ",x=ISO3_COUNTRY, y=EMISSIONS_QUANTITY,color=CT_FILE,log_y=False)" + ] + }, + { + "cell_type": "markdown", + "id": "67ecf794-d2c4-4fc2-bce4-52e0fc4f0d3a", + "metadata": {}, + "source": [ + "## Source checks\n", + "\n", + "Let's look now at all the sources tracked by Climate TRACE.\n", + "\n", + "We load the data first.\n", + "\n", + "```{admonition} TODO\n", + "complete this section\n", + "```\n", + "\n", + "```{note} Technical\n", + "- We load the data using `scan_parquet`. This instructs Polars to delay the actual loading in memory until requested. The amount of memory necessary will then be minimal, even if the dataset itself is 4GB.\n", + "\n", + "- We reset the schema, in particular we add all the information about enumerations. This provides better type checks and helps Polars with optimizing its queries.\n", + "\n", + "```\n", + "\n", + "You can see that Polars has not done any processing if you attempt to display the data:" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "71fcae25-e772-4089-b8bf-f2a16eee3819", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

NAIVE QUERY PLAN

run LazyFrame.show_graph() to see the optimized version

\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "polars_query\n", + "\n", + "\n", + "\n", + "FILTER BY (col("gas")) == (String(c... [(0, 0)]\n", + "\n", + "FILTER BY (col("gas")) == (String(c...\n", + "\n", + "\n", + "\n", + "WITH COLUMNS ["conf_source_type","conf_capacity","conf_capacity_factor","conf_activity","conf_co2_emissions_factor","conf_ch4_emissions_factor","conf_n2o_emissions_factor","conf_co2_emissions","conf_ch4_emissions","conf_n2o_emissions","conf_total_co2e_20yrgwp","conf_total_co2e_100yrgwp"] [(0, 1)]\n", + "\n", + "WITH COLUMNS ["conf_source_type","conf_capacity","conf_capacity_factor","conf_activity","conf_co2_emissions_factor","conf_ch4_emissions_factor","conf_n2o_emissions_factor","conf_co2_emissions","conf_ch4_emissions","conf_n2o_emissions","conf_total_co2e_20yrgwp","conf_total_co2e_100yrgwp"]\n", + "\n", + "\n", + "\n", + "FILTER BY (col("gas")) == (String(c... [(0, 0)]--WITH COLUMNS ["conf_source_type","conf_capacity","conf_capacity_factor","conf_activity","conf_co2_emissions_factor","conf_ch4_emissions_factor","conf_n2o_emissions_factor","conf_co2_emissions","conf_ch4_emissions","conf_n2o_emissions","conf_total_co2e_20yrgwp","conf_total_co2e_100yrgwp"] [(0, 1)]\n", + "\n", + "\n", + "\n", + "\n", + "WITH COLUMNS ["iso3_country","gas","original_inventory_sector","temporal_granularity"] [(0, 2)]\n", + "\n", + "WITH COLUMNS ["iso3_country","gas","original_inventory_sector","temporal_granularity"]\n", + "\n", + "\n", + "\n", + "WITH COLUMNS ["conf_source_type","conf_capacity","conf_capacity_factor","conf_activity","conf_co2_emissions_factor","conf_ch4_emissions_factor","conf_n2o_emissions_factor","conf_co2_emissions","conf_ch4_emissions","conf_n2o_emissions","conf_total_co2e_20yrgwp","conf_total_co2e_100yrgwp"] [(0, 1)]--WITH COLUMNS ["iso3_country","gas","original_inventory_sector","temporal_granularity"] [(0, 2)]\n", + "\n", + "\n", + "\n", + "\n", + "Parquet SCAN /home/tjhunter/.cache/pooch/climate_trace_2022.parquet;\n", + "π */60;\n", + "σ - [(0, 3)]\n", + "\n", + "Parquet SCAN /home/tjhunter/.cache/pooch/climate_trace_2022.parquet;\n", + "π */60;\n", + "σ -\n", + "\n", + "\n", + "\n", + "WITH COLUMNS ["iso3_country","gas","original_inventory_sector","temporal_granularity"] [(0, 2)]--Parquet SCAN /home/tjhunter/.cache/pooch/climate_trace_2022.parquet;\n", + "π */60;\n", + "σ - [(0, 3)]\n", + "\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sdf = ct.read_source_emissions(year=year)\n", + "sdf_gy = sdf.filter(c_gas == gas)\n", + "sdf_gy" + ] + }, + { + "cell_type": "markdown", + "id": "8a39c5b9-f9e3-4a05-bad2-2b4b8b505775", + "metadata": {}, + "source": [ + "How much emissions are released according to the source tracking? This number is significantly lower compared to what was estimated per country (41GT CO2e instead of 58GT CO2e). As explained, the source tracking explicitly lists all the known sources while country emissions complete this number with indirect inferences from economic statistics. We will explore later where the gap is coming from, but it is good to keep in mind that about 30% of all emissions are not assigned to known sources yet. This is a large number!\n", + "\n", + "The forestry and land use category is notoriously hard to estimate, so we are going for now to leave it aside" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "403e7a0b-beed-41bd-aa08-2d3a684855e6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (1, 1)
emissions_quantity
f64
4.1399e10
" + ], + "text/plain": [ + "shape: (1, 1)\n", + "┌────────────────────┐\n", + "│ emissions_quantity │\n", + "│ --- │\n", + "│ f64 │\n", + "╞════════════════════╡\n", + "│ 4.1399e10 │\n", + "└────────────────────┘" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(sdf_gy\n", + " .filter(c_ct_package != (\"forestry_and_land_use\"))\n", + " .select(c_emissions_quantity.sum())\n", + " .collect()\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "52eb65aa-ad87-4bf9-b262-76d9156bf829", + "metadata": {}, + "source": [ + "### Emissions over multiple years\n", + "\n", + "Small note: some data (boat voyages) cross over the years. This is a small value of all the emissions (<1%), so we are not going to account for that." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "bd8c4a46-1c94-4aad-89a9-90dbd6157c40", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (2, 2)
end_timeemissions_quantity
i32f64
20223.7515e10
20231.0609e8
" + ], + "text/plain": [ + "shape: (2, 2)\n", + "┌──────────┬────────────────────┐\n", + "│ end_time ┆ emissions_quantity │\n", + "│ --- ┆ --- │\n", + "│ i32 ┆ f64 │\n", + "╞══════════╪════════════════════╡\n", + "│ 2022 ┆ 3.7515e10 │\n", + "│ 2023 ┆ 1.0609e8 │\n", + "└──────────┴────────────────────┘" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(sdf_gy.group_by(c_end_time.dt.year())\n", + " .agg(c_emissions_quantity.sum())\n", + " .collect())" + ] + }, + { + "cell_type": "markdown", + "id": "87e168bb-5c5f-42bc-802b-5adb334b47c8", + "metadata": {}, + "source": [ + "### Number of tracked sources\n", + "\n", + "How many sources were tracked last year?\n", + "\n", + "We get more than 600k if the forestry and land use changes are included.\n", + "\n", + "Technical:\n", + "\n", + "Notice that we did not need to ingest the data in a database, and yet this query takes less than a second. Pretty good for a decently large dataset! Try to reproduce this analysis in Pandas and see what happens." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "fe845e74-a0b9-4892-9428-ba7fd9a926c0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "627582" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(sdf_gy.select(c_source_id.unique_counts())\n", + " .count()\n", + " .collect()\n", + " .item() # Using .item() to have a single number\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "f6e7bcd3-ba5f-49b0-bd0c-565657338f11", + "metadata": {}, + "source": [ + "Excluding them, we get the number reported officially by Climate TRACE (328k)." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "471254a9-8566-4c8f-8068-637dd52d961d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "326516" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(sdf_gy.filter(c_ct_package != \"forestry_and_land_use\")\n", + ".select(c_source_id.unique_counts())\n", + " .count()\n", + " .collect()\n", + " .item()\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "8475bf1f-34b3-4bab-967a-a06b72af91d1", + "metadata": {}, + "source": [ + "```{admonition} CTODO\n", + "Some records seem to be duplicated? Some source ids are present many time despite being defined on an annual basis. Here is an example. Confirm with CTrace.\n", + "```\n", + "\n", + "Here are the list of records defined multiple times:" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "968db8b8-0917-4636-8a23-24aab2cfb705", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (10, 3)
source_idtemporal_granularityc
u64enumu32
13169068"annual"4
13173388"annual"4
13175447"annual"4
5012955"annual"4
5012944"annual"5
5035013"annual"6
13168862"annual"6
5035200"annual"7
5012995"annual"8
25743740"annual"2751
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5012995"AND"null2022-01-01 00:00:002022-12-31 00:00:00"annual""co2e_100yr"274.54295nullnullnull"T CO2"nullnull"T CO2"2023-09-29 00:00:00null"Sant Julià de …""42.4658681.493838"AND.7_1"null"1"nullnullnullnullnullnullnullnullnull"level 1 GADM i…null"GADM admin lev…nullnullnullnullnullnullnullnullnull"gadm_AND.7_1"null"high"null"low""low"nullnull"low"nullnull"low""low""forestry_and_l…"forest-land-cl…
5012995"AND"null2022-01-01 00:00:002022-12-31 00:00:00"annual""co2e_100yr"274.54295nullnullnull"T CO2"nullnull"T CO2"2023-09-29 00:00:00null"Sant Julià de …""42.4658681.493838"AND.7_1"null"1"nullnullnullnullnullnullnullnullnull"level 1 GADM i…null"GADM admin lev…nullnullnullnullnullnullnullnullnull"gadm_AND.7_1"null"high"null"low""low"nullnull"low"nullnull"low""low""forestry_and_l…"forest-land-cl…
5012995"AND"null2022-01-01 00:00:002022-12-31 00:00:00"annual""co2e_100yr"274.54295nullnullnull"T CO2"nullnull"T CO2"2023-09-29 00:00:00null"Sant Julià de …""42.4658681.493838"AND.7_1"null"1"nullnullnullnullnullnullnullnullnull"level 1 GADM i…null"GADM admin lev…nullnullnullnullnullnullnullnullnull"gadm_AND.7_1"null"high"null"low""low"nullnull"low"nullnull"low""low""forestry_and_l…"forest-land-cl…
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" + ], + "text/plain": [ + "shape: (3, 60)\n", + "┌───────────┬───────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬──────────┐\n", + "│ source_id ┆ iso3_coun ┆ original_ ┆ start_tim ┆ … ┆ conf_tota ┆ conf_tota ┆ ct_packag ┆ ct_file │\n", + "│ --- ┆ try ┆ inventory ┆ e ┆ ┆ l_co2e_20 ┆ l_co2e_10 ┆ e ┆ --- │\n", + "│ u64 ┆ --- ┆ _sector ┆ --- ┆ ┆ yrgwp ┆ 0yrgwp ┆ --- ┆ cat │\n", + "│ ┆ enum ┆ --- ┆ datetime[ ┆ ┆ --- ┆ --- ┆ cat ┆ │\n", + "│ ┆ ┆ str ┆ μs] ┆ ┆ cat ┆ cat ┆ ┆ │\n", + "╞═══════════╪═══════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪══════════╡\n", + "│ 3240495 ┆ LTU ┆ wastewate ┆ 2022-01-0 ┆ … ┆ low ┆ low ┆ waste ┆ wastewat │\n", + "│ ┆ ┆ r-treatme ┆ 1 ┆ ┆ ┆ ┆ ┆ er-treat │\n", + "│ ┆ ┆ nt-and-di ┆ 00:00:00 ┆ ┆ ┆ ┆ ┆ ment-and │\n", + "│ ┆ ┆ schar… ┆ ┆ ┆ ┆ ┆ ┆ -dischar │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ … │\n", + "│ 3240496 ┆ LTU ┆ wastewate ┆ 2022-01-0 ┆ … ┆ low ┆ low ┆ waste ┆ wastewat │\n", + "│ ┆ ┆ r-treatme ┆ 1 ┆ ┆ ┆ ┆ ┆ er-treat │\n", + "│ ┆ ┆ nt-and-di ┆ 00:00:00 ┆ ┆ ┆ ┆ ┆ ment-and │\n", + "│ ┆ ┆ schar… ┆ ┆ ┆ ┆ ┆ ┆ -dischar │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ … │\n", + "│ 3240497 ┆ LTU ┆ wastewate ┆ 2022-01-0 ┆ … ┆ low ┆ low ┆ waste ┆ wastewat │\n", + "│ ┆ ┆ r-treatme ┆ 1 ┆ ┆ ┆ ┆ ┆ er-treat │\n", + "│ ┆ ┆ nt-and-di ┆ 00:00:00 ┆ ┆ ┆ ┆ ┆ ment-and │\n", + "│ ┆ ┆ schar… ┆ ┆ ┆ ┆ ┆ ┆ -dischar │\n", + "│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ … │\n", + "└───────────┴───────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴──────────┘" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sdf_gy.filter(c_ct_file == \"wastewater-treatment-and-discharge\").head(3).collect()" + ] + }, + { + "cell_type": "markdown", + "id": "5fd911fa-4fbc-48b3-97dd-0a194c44a81f", + "metadata": {}, + "source": [ + "Looking now at emissions and gathering by country, we get a plot relatively similar to what we saw in the section above.\n", + "\n", + "However, we see already that values can be quite off between the source methodology and the country methodology: China's gross sources sum to 10 BTCO2e, but the gross country emissions sum to 15.8 BTCO2e.\n", + "\n", + "```{admonition} CTODO\n", + "Is this accurate? This seems still very off. Confirm with CT.\n", + "```\n", + "\n", + "Again, France and the Netherlands barely appear in this graph, and Mozambique's forest management practices have an enormous impact." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "d3e6791b-dde4-4b6d-afa4-ba97d66f9158", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "ct_file=electricity-generation
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", + "text/html": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "px.bar(\n", + "(sdf_gy\n", + ".group_by(c_iso3_country, c_ct_file)\n", + " .agg(c_emissions_quantity.sum())\n", + " .sort([c_emissions_quantity], descending=True)\n", + " .filter(c_iso3_country.is_in([\"CHN\", \"USA\", \"IND\", \"RUS\",\"MOZ\",\"FRA\", \"NLD\"]))\n", + " .collect()\n", + ")\n", + " ,x=ISO3_COUNTRY, y=EMISSIONS_QUANTITY,color=CT_FILE,log_y=False)" + ] + }, + { + "cell_type": "markdown", + "id": "5d43da77-d964-4e3d-8a69-2950c3acc309", + "metadata": {}, + "source": [ + "## Conclusion\n", + "\n", + "In this section, we saw:\n", + "- how to access the Climate TRACE dataset in a modern data processing tool (Polars)\n", + "- how to produce high-level statistics per country and per sector\n", + "\n", + "From the data, it should be clear that tackling emissions is a global issue, in which a few countries dominate.\n", + "Some countries with large economic outputs (France, The Netherlands) can have minimal emissions, in part because they have low-emission means of producing electricity and they have outsourced their industries. Some others with comparably small economic outputs or populations (ex: Mozambique) have a disproportionate impact because of how they treat their ecosystems and land.\n", + "\n", + "```{seealso} Exercise\n", + "Take your country look at the sources of emissions\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6aef1b12-4dc1-4152-85c3-9425adcc5789", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/_sources/intro.md b/_sources/intro.md new file mode 100644 index 0000000..857d875 --- /dev/null +++ b/_sources/intro.md @@ -0,0 +1,26 @@ +# Saving the planet with data: deriving insights from the Climate Trace project. + +Our human activities are responsible for most of the greenhouse gases (GHG) +released in the atmosphere. These gas stay in the atmosphere for long periods of time and they drive profound changes in the physical systems and the ecosystems around us. Where do they come from? What can we do about it? + +You cannot control what you cannot measure. Identifying the source of these emissions is a key step for eventually reducing them. The [Climate TRACE](https://climatetrace.org/) project is a consortium of research labs, non-profit organizations and companies that aims at providing a comprehensive, global understanding of all the emissions around the planet. It makes high level datasets available for anyone to browse and share. + +This handbook is a series of tutorials aimed at data scientists and technical people who may be wondering how to explore the dataset offered by Climate TRACE. I hope that this series of notebooks inspires scientists and engineers to understand better the source of emissions around them, and to give them the curiosity to engage and improve this information. + +Even if we are going to analyze hundreds of millions of sources of GHG gases on a planetary scale, any reasonably modern laptop should be enough to run these. Along the way, I will use and point out the modern data science techniques that makes this analysis so fast and streamlined. +The technical sections that also explain the how the code is running will be clearly marked with a `Technical` label. You can skip them if you are just interested in the results. + +After reading this handbook, you should be able to do the following: +- access and manipulate the Climate Trace dataset with Python and Jupyter +- derive basic insights about emissions from this dataset: which countries emit the most, the least, which sorts of gas, etc. +- where our knowledge is the most uncertain +- where independent measurements of the same sources gives inconsistent values + +```{warning} + +This handbook is still a draft. Numbers are still being checked with experts. + +``` + +```{tableofcontents} +``` diff --git a/_sources/markdown-notebooks.md b/_sources/markdown-notebooks.md new file mode 100644 index 0000000..a057a32 --- /dev/null +++ b/_sources/markdown-notebooks.md @@ -0,0 +1,53 @@ +--- +jupytext: + formats: md:myst + text_representation: + extension: .md + format_name: myst + format_version: 0.13 + jupytext_version: 1.11.5 +kernelspec: + display_name: Python 3 + language: python + name: python3 +--- + +# Notebooks with MyST Markdown + +Jupyter Book also lets you write text-based notebooks using MyST Markdown. +See [the Notebooks with MyST Markdown documentation](https://jupyterbook.org/file-types/myst-notebooks.html) for more detailed instructions. +This page shows off a notebook written in MyST Markdown. + +## An example cell + +With MyST Markdown, you can define code cells with a directive like so: + +```{code-cell} +print(2 + 2) +``` + +When your book is built, the contents of any `{code-cell}` blocks will be +executed with your default Jupyter kernel, and their outputs will be displayed +in-line with the rest of your content. + +```{seealso} +Jupyter Book uses [Jupytext](https://jupytext.readthedocs.io/en/latest/) to convert text-based files to notebooks, and can support [many other text-based notebook files](https://jupyterbook.org/file-types/jupytext.html). +``` + +## Create a notebook with MyST Markdown + +MyST Markdown notebooks are defined by two things: + +1. YAML metadata that is needed to understand if / how it should convert text files to notebooks (including information about the kernel needed). + See the YAML at the top of this page for example. +2. The presence of `{code-cell}` directives, which will be executed with your book. + +That's all that is needed to get started! + +## Quickly add YAML metadata for MyST Notebooks + +If you have a markdown file and you'd like to quickly add YAML metadata to it, so that Jupyter Book will treat it as a MyST Markdown Notebook, run the following command: + +``` +jupyter-book myst init path/to/markdownfile.md +``` diff --git a/_sources/markdown.md b/_sources/markdown.md new file mode 100644 index 0000000..faeea60 --- /dev/null +++ b/_sources/markdown.md @@ -0,0 +1,55 @@ +# Markdown Files + +Whether you write your book's content in Jupyter Notebooks (`.ipynb`) or +in regular markdown files (`.md`), you'll write in the same flavor of markdown +called **MyST Markdown**. +This is a simple file to help you get started and show off some syntax. + +## What is MyST? + +MyST stands for "Markedly Structured Text". It +is a slight variation on a flavor of markdown called "CommonMark" markdown, +with small syntax extensions to allow you to write **roles** and **directives** +in the Sphinx ecosystem. + +For more about MyST, see [the MyST Markdown Overview](https://jupyterbook.org/content/myst.html). + +## Sample Roles and Directives + +Roles and directives are two of the most powerful tools in Jupyter Book. They +are like functions, but written in a markup language. They both +serve a similar purpose, but **roles are written in one line**, whereas +**directives span many lines**. They both accept different kinds of inputs, +and what they do with those inputs depends on the specific role or directive +that is being called. + +Here is a "note" directive: + +```{note} +Here is a note +``` + +It will be rendered in a special box when you build your book. + +Here is an inline directive to refer to a document: {doc}`markdown-notebooks`. + + +## Citations + +You can also cite references that are stored in a `bibtex` file. For example, +the following syntax: `` {cite}`holdgraf_evidence_2014` `` will render like +this: {cite}`holdgraf_evidence_2014`. + +Moreover, you can insert a bibliography into your page with this syntax: +The `{bibliography}` directive must be used for all the `{cite}` roles to +render properly. +For example, if the references for your book are stored in `references.bib`, +then the bibliography is inserted with: + +```{bibliography} +``` + +## Learn more + +This is just a simple starter to get you started. +You can learn a lot more at [jupyterbook.org](https://jupyterbook.org). diff --git a/_sources/notebooks.ipynb b/_sources/notebooks.ipynb new file mode 100644 index 0000000..35b46ad --- /dev/null +++ b/_sources/notebooks.ipynb @@ -0,0 +1,122 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Content with notebooks\n", + "\n", + "You can also create content with Jupyter Notebooks. This means that you can include\n", + "code blocks and their outputs in your book.\n", + "\n", + "## Markdown + notebooks\n", + "\n", + "As it is markdown, you can embed images, HTML, etc into your posts!\n", + "\n", + "![](https://myst-parser.readthedocs.io/en/latest/_static/logo-wide.svg)\n", + "\n", + "You can also $add_{math}$ and\n", + "\n", + "$$\n", + "math^{blocks}\n", + "$$\n", + "\n", + "or\n", + "\n", + "$$\n", + "\\begin{aligned}\n", + "\\mbox{mean} la_{tex} \\\\ \\\\\n", + "math blocks\n", + "\\end{aligned}\n", + "$$\n", + "\n", + "But make sure you \\$Escape \\$your \\$dollar signs \\$you want to keep!\n", + "\n", + "## MyST markdown\n", + "\n", + "MyST markdown works in Jupyter Notebooks as well. For more information about MyST markdown, check\n", + "out [the MyST guide in Jupyter Book](https://jupyterbook.org/content/myst.html),\n", + "or see [the MyST markdown documentation](https://myst-parser.readthedocs.io/en/latest/).\n", + "\n", + "## Code blocks and outputs\n", + "\n", + "Jupyter Book will also embed your code blocks and output in your book.\n", + "For example, here's some sample Matplotlib code:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from matplotlib import rcParams, cycler\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "plt.ion()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Fixing random state for reproducibility\n", + "np.random.seed(19680801)\n", + "\n", + "N = 10\n", + "data = [np.logspace(0, 1, 100) + np.random.randn(100) + ii for ii in range(N)]\n", + "data = np.array(data).T\n", + "cmap = plt.cm.coolwarm\n", + "rcParams['axes.prop_cycle'] = cycler(color=cmap(np.linspace(0, 1, N)))\n", + "\n", + "\n", + "from matplotlib.lines import Line2D\n", + "custom_lines = [Line2D([0], [0], color=cmap(0.), lw=4),\n", + " Line2D([0], [0], color=cmap(.5), lw=4),\n", + " Line2D([0], [0], color=cmap(1.), lw=4)]\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 5))\n", + "lines = ax.plot(data)\n", + "ax.legend(custom_lines, ['Cold', 'Medium', 'Hot']);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "There is a lot more that you can do with outputs (such as including interactive outputs)\n", + "with your book. For more information about this, see [the Jupyter Book documentation](https://jupyterbook.org)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/_sources/sce_diffs.ipynb b/_sources/sce_diffs.ipynb new file mode 100644 index 0000000..c5eed14 --- /dev/null +++ b/_sources/sce_diffs.ipynb @@ -0,0 +1,143250 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "62e9d308-51f1-41cb-8d47-1b90ca9a988f", + "metadata": {}, + "source": [ + "# Comparing source and country inventories\n", + "\n", + "The Climate TRACE dataset provides two sets of inventories:\n", + "- tracking every source of emissions\n", + "- using econonomic output statistics to derive country-level emissions\n", + "\n", + "The second approach is described in more details in (TODO: ref to the implicit doc).\n", + "\n", + "This chapter compares the two approaches and identifies gaps between the two results.\n", + "We conclude with a statistical approach to combine the two estimates into a single,\n", + "more precise estimate, using Bayesian statistics.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "14bca6ff-90a9-4b86-941e-c15ae282292d", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "55939329-eb86-47ad-9086-21fc31b85682", + "metadata": {}, + "outputs": [], + "source": [ + "import polars as pl\n", + "pl.enable_string_cache() # TODO: remove\n", + "import plotly.express as px\n", + "import plotly.graph_objects as go # Will use more advanced visualization functions\n", + "\n", + "from ctrace.constants import *\n", + "import ctrace as ct" + ] + }, + { + "cell_type": "markdown", + "id": "8fe4e493-6bae-4acb-b99c-1b99751ddb18", + "metadata": {}, + "source": [ + "We first load the data for the year 2022, only focusing on CO2-equivalent emissions.\n", + "`sdf_gy` is the dataframe of the source emissions for this gas and this year." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "c4e1b5f2-1737-4d60-b92b-c6a7812fd48e", + "metadata": {}, + "outputs": [], + "source": [ + "year = 2022\n", + "gas = \"co2e_100yr\"\n", + "\n", + "cedf = ct.read_country_emissions()\n", + "sdf = ct.read_source_emissions(year=year)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "2d147e40-b941-4240-8d3f-03722f2a9a7c", + "metadata": {}, + "outputs": [], + "source": [ + "sdf_gy = sdf.filter(c_gas == gas)\n", + "cedf_gy = cedf.filter(c_gas == gas).filter(c_start_time.dt.year()==year)" + ] + }, + { + "cell_type": "markdown", + "id": "0d155e12-3007-4ecb-8860-f67aada18a1c", + "metadata": {}, + "source": [ + "## Comparing visually the two datasets\n", + "\n", + "Let us check first if the numbers roughly match for each country and for each sector. Are we in the same ballpark estimate between the tracking of the sources and country-level aggregations?\n", + "\n", + "First aggregate the emissions by country, sector and sub-sector:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3c612f27-da89-4222-b6c0-b214f28131d0", + "metadata": {}, + "outputs": [], + "source": [ + "cedf_gy_agg = (cedf_gy\n", + " .group_by(c_iso3_country, c_ct_package, c_ct_file)\n", + " .agg(c_emissions_quantity.sum())\n", + ")\n", + "\n", + "sdf_gy_agg = (sdf_gy\n", + " .group_by(c_iso3_country, c_ct_package, c_ct_file)\n", + " .agg(c_emissions_quantity.sum())\n", + " .collect()\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e0965506-22be-4b10-bbea-7e9ebfce280e", + "metadata": {}, + "source": [ + "The `jdf` dataframe is the joint dataframe holding estimates for each sector, country, sub-sector.\n", + "Some sectors and subsectors will be missing in one or the other dataframe, depending\n", + "on what countries have reported.\n", + "\n", + "Technical: we are using an `outer` join to capture both sides of the data, even if one is\n", + "missing.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "06edd0f0-398e-4955-8867-0addc693fb43", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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……………
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" + ], + "text/plain": [ + "shape: (12_916, 5)\n", + "┌──────────────┬────────────────────┬────────────────────┬────────────────────┬────────────────────┐\n", + "│ iso3_country ┆ ct_package ┆ ct_file ┆ emissions_quantity ┆ emissions_quantity │\n", + "│ --- ┆ --- ┆ --- ┆ _s ┆ _ce │\n", + "│ enum ┆ cat ┆ cat ┆ --- ┆ --- │\n", + "│ ┆ ┆ ┆ f64 ┆ f64 │\n", + "╞══════════════╪════════════════════╪════════════════════╪════════════════════╪════════════════════╡\n", + "│ ABW ┆ agriculture ┆ other-agricultural ┆ null ┆ 0.0 │\n", + "│ ┆ ┆ -soil-emission… ┆ ┆ │\n", + "│ GGY ┆ agriculture ┆ other-agricultural ┆ null ┆ 0.0 │\n", + "│ ┆ ┆ -soil-emission… ┆ ┆ │\n", + "│ IMN ┆ agriculture ┆ other-agricultural ┆ null ┆ 24305.1 │\n", + "│ ┆ ┆ -soil-emission… ┆ ┆ │\n", + "│ UZB ┆ agriculture ┆ other-agricultural ┆ null ┆ 2.4475e6 │\n", + "│ ┆ ┆ -soil-emission… ┆ ┆ │\n", + "│ ARE ┆ agriculture ┆ other-agricultural ┆ null ┆ 552339.5 │\n", + "│ ┆ ┆ -soil-emission… ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ COD ┆ agriculture ┆ synthetic-fertiliz ┆ 5302.583184 ┆ null │\n", + "│ ┆ ┆ er-application ┆ ┆ │\n", + "│ ZNC ┆ forestry_and_land_ ┆ net-shrubgrass ┆ -82226.761935 ┆ null │\n", + "│ ┆ use ┆ ┆ ┆ │\n", + "│ HTI ┆ agriculture ┆ synthetic-fertiliz ┆ 8151.493148 ┆ null │\n", + "│ ┆ ┆ er-application ┆ ┆ │\n", + "│ GNQ ┆ agriculture ┆ synthetic-fertiliz ┆ 46.693207 ┆ null │\n", + "│ ┆ ┆ er-application ┆ ┆ │\n", + "│ MCO ┆ agriculture ┆ manure-left-on-pas ┆ 0.0 ┆ null │\n", + "│ ┆ ┆ ture-cattle ┆ ┆ │\n", + "└──────────────┴────────────────────┴────────────────────┴────────────────────┴────────────────────┘" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "EMISSIONS_QUANTITY_S = EMISSIONS_QUANTITY + \"_s\"\n", + "EMISSIONS_QUANTITY_CE = EMISSIONS_QUANTITY + \"_ce\"\n", + "\n", + "jdf = (cedf_gy_agg\n", + " .join(sdf_gy_agg, on=[ISO3_COUNTRY, CT_PACKAGE, CT_FILE], suffix=\"_s\", how=\"outer\")\n", + ".with_columns(\n", + " c_iso3_country.fill_null(C(ISO3_COUNTRY+\"_s\")),\n", + " c_ct_package.fill_null(C(CT_PACKAGE+\"_s\")),\n", + " c_ct_file.fill_null(C(CT_FILE+\"_s\")),\n", + " c_emissions_quantity.alias(EMISSIONS_QUANTITY_CE),\n", + ").select(\n", + " c_iso3_country,\n", + " c_ct_package,\n", + " c_ct_file,\n", + " EMISSIONS_QUANTITY_S,\n", + " EMISSIONS_QUANTITY_CE\n", + "))\n", + "jdf" + ] + }, + { + "cell_type": "markdown", + "id": "655bdeab-678e-4313-8ed5-8ff34c0afb0a", + "metadata": {}, + "source": [ + "Quick check where we have differences in missing data:\n", + "\n", + "```{admonition} CTODO\n", + "Shouldn't the sources be a subset of all the data reported by the countries? I would assume\n", + "that the countries and EDGAR / FAOSTATS are more comprehensive at country level than CTrace.\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "f2c194e9-5211-447c-b317-71894cf94f9a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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truefalse84
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" + ], + "text/plain": [ + "shape: (3, 3)\n", + "┌───────────┬────────────┬──────────────┐\n", + "│ present_s ┆ present_ce ┆ iso3_country │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ bool ┆ bool ┆ u32 │\n", + "╞═══════════╪════════════╪══════════════╡\n", + "│ false ┆ true ┆ 7997 │\n", + "│ true ┆ false ┆ 84 │\n", + "│ true ┆ true ┆ 4835 │\n", + "└───────────┴────────────┴──────────────┘" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(jdf.group_by(\n", + " C(EMISSIONS_QUANTITY_S).is_not_null().alias(\"present_s\"),\n", + " C(EMISSIONS_QUANTITY_CE).is_not_null().alias(\"present_ce\"))\n", + " .agg(c_iso3_country.count())\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b1be804b-c71a-4c04-8ee9-48791abd580a", + "metadata": {}, + "outputs": [], + "source": [ + "# jdf.filter(C(EMISSIONS_QUANTITY_S).is_not_null() & C(EMISSIONS_QUANTITY_CE).is_null())" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "79cf428b-ef40-4335-83c3-764bae7f1d50", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "shape: (3, 3)\n", + "┌─────────────┬──────────────────────┬───────────────────────┐\n", + "│ is_emission ┆ emissions_quantity_s ┆ emissions_quantity_ce │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ bool ┆ f64 ┆ f64 │\n", + "╞═════════════╪══════════════════════╪═══════════════════════╡\n", + "│ null ┆ -461722.074512 ┆ 0.0 │\n", + "│ false ┆ -5.6840e10 ┆ -2.1257e10 │\n", + "│ true ┆ 9.4461e10 ┆ 7.6428e10 │\n", + "└─────────────┴──────────────────────┴───────────────────────┘" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(jdf\n", + " .with_columns(((C(EMISSIONS_QUANTITY_S) > 0) | (C(EMISSIONS_QUANTITY_CE) > 0)).alias(\"is_emission\"))\n", + " .group_by(\"is_emission\")\n", + " .agg(C(EMISSIONS_QUANTITY_S).sum(), C(EMISSIONS_QUANTITY_CE).sum()))" + ] + }, + { + "cell_type": "markdown", + "id": "bde1583b-e09f-4179-8241-a0e21a628a38", + "metadata": {}, + "source": [ + "To better compare, we also add a ratio between the source-defined emissions\n", + "and the country-defined emissions. If we knew perfectly the emissions, this number would be one. However:\n", + "- the sources should be just an observed fraction of all the emissions, so this fraction should generally be expected to be less than one\n", + "- the emissions are known only to some degree of accuracy. There is noise in the measurement. As a result, the fraction should be wiggling around one.\n", + "- Some sectors are just not observed at all in some countries, so having infinite values is expected." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "29030237-f490-46b4-97b2-ac76f569815d", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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The source-based emissions are exactly triple the values reported in the country-based emissions.\n", + "\n", + "```{admonition} CTODO\n", + "Verify with CT about the values there. Maybe they know about it already?\n", + "```\n", + "\n", + "The US Virgin Islands seem to undereport a manufacturing activity.\n", + "\n", + "```{admonition} CTODO\n", + "Verify with CT about the values there. Maybe they know about it already?\n", + "```\n", + "\n", + "The Feroe islands seem to be have big discrepancies in their forest management\n", + "\n", + "```{admonition} CTODO\n", + "Verify with CT about the values there. Maybe they know about it already?\n", + "```\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "f277f7c1-9a95-4a4a-9ed8-2c40d91614ea", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + " \n", + " " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "customdata": [ + [ + "agriculture", + "other-agricultural-soil-emissions" + ], + [ + "agriculture", + "other-agricultural-soil-emissions" + ], + [ + "agriculture", + "other-agricultural-soil-emissions" + ], + [ + "agriculture", + "other-agricultural-soil-emissions" + ], + [ + "agriculture", + "other-agricultural-soil-emissions" + ], + [ + "agriculture", + "other-agricultural-soil-emissions" + ], + [ + "agriculture", + "other-agricultural-soil-emissions" + ], + [ + "agriculture", + "other-agricultural-soil-emissions" + ], + [ + "agriculture", + 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y3UwkEL8EGAHVyJsCqhEgs5MACZCAnRIwlYA6935hFNEZExMb9bwpHn716jVqtnTH0lBvdbvTx6ROfUerG51qVv7mY7IzTzwToIBqBE4B1QiQ2UmABEjATglQQN/t+M27DqFaxZJIIK7o/JgUWUBfvHiJ7ft+RY3vSn1MUcwTDwQooBohU0A1AmR2EiABErBTAhRQfTs+soDu3n9C3Bm/G4HDu+v7EpamGwEKqEaUZhdQcV7CtXzzNLaC2UmABEiABOKbgC0I6Ir1uzFzwTrcufsAuXJkQcCQLvg0VzaFUn42efYK9edGtSqJiORRTPZ3EzcdZUClRj0x3ssVHiOno2D+XJji3wdFqnbArhWTkD5tasiD6b3Hz8WuX44hSZLE6N+thYpmflO7K45tnWk4nL6f1xSUK/mVuN/+O0QIaO6cWdBj0ARVRvp0qdFG3KQk6zRj/k+YFzzY0M3fNu6lvs6dM6vK26lVHUwMXYbzl67hwLppOHv+MoYGzMSFyzfwWe7s8B/UGXk+yRrfw8Rm30cB1di1ZhdQUf9reSmgGruR2UmABGIiIC+/kocDMulKwBYE9MTv55A5UzollX6TwvHg0WOMEqJ27uI1tOrug7kTByLfpzkwZc5KTP9xDbYuGaeeLVatE0oVKwifAR2RIX0aJEua5B0BlWLp4OCAYX3bQU6nv3nzBimSJ42TgMo1oEvX7sTPh08ZIqA7xHR8bAJ65fo/8BvojC/y50FSIb112nigq1MDNK5dCfOWbcZPW3/BgilDdR0D9lwYBVRj71NANQJkdhIgARKwUwK2IKCRu273/uMImbcWPwYNQmj4WpwXEuo30EU98vTZvyhVq7NBQGW0c0bgAJQp/qWhiIgIaJpUKVGypgtWz/UX0ckshs+fPH1mUgEtXrgAXDs2Vu/79dSf6DtiMrYtGa++lhJcvIYLdq98G6Fl0k6AAqqRIQVUI0BmJwESIAE7JWALAhq+fAs2bN+vBO3Rk2dIlyaVmtb2DwpH8mRJ4ebS1NC7Zep2w6o5vioCKmVzx7KJyCiinxEpQkATOCRA+QY98OvmGUicOFGMAtp3xBSUL/XuFHxcI6ByGUD45CGGKXjH+pVRq0pp9T65IcrdayrSpklpeP/TZ8/VLn1Ow+vzA2tzArrnwAkEizUnf4q1G6lSpkCLhlVVCF0mGcIPmLwAqzbsQaJECcX3G6J1k+/VZ/fuP4Kn33QcPn4GmTOmg3f/jmp6ILbPKKD6DESWQgIkQAL2RsDaBVROa48Knq+EM1OGtNi25whmLVyvvg6ZtwYXr9zESI9OqltfvnqF4tWdsXlRoEFAI9Z7vi+gqVOlQMkanbEuPAA5s2UyDIvn/75ACRGFPLopVK0Llaldb3/Ur17+nTWgUkCX/bQL+w6dNEzBy01JU+auNEyhy/rIstaGySjr2zWgkY9wOnLiDIaI9Z/r5gXY27CMt/banIAuXr0decVi4a+/yo9bt++hVY+RGDO0K775+gu1IHr+iq0IGdMPDx4+gVMvP4SO7Y/PP/sEA/1CxRqUxPBwbSUG7Sl4j5uLLYsD1ULnmD6jgMbbWOWLSIAESMCmCJhEQMUZ9M5u8XMO6PJ1u7B288+YNd4D8hzPgX4huHrjthJQuYGnXS9//Cj+LDfwzF28EWOmLnxnCj46AZVT3L2GTkLK5MkxtI+TCh7dvf8Qn2TPjCpN3eDn6YJyIuop39HUebh6JvImJCmgW3YfVutOF00fgYQJEuDytZto1sUL64XUyvIXr9kBr8A56uuoBFQKap3WHujQojZkZPS1aN8Z8b7CBfPa1Bg0Z2NsTkDfh9nVI1CE1MuIHXgV0c1zPGpXLY0GNSqox8ZNX4zXYmD369IMpet0E+tN/JA9Swb1WYtu3ujeriEqlSka7Wffli0GCqg5hy/fTQIkQALWS8AkAipwxNdB9I/FlHvvYUG4KjbvyKn0JnW+VZHHiJ3mS9buwPSw1ZCRSylxC1dtw/KZPrFGQKUg3rn3EMPHzsYvYiORCgT1aq3+7ZY76cdOXaSm96U4ysBRiSKffyCgcs1pryGTcPL0OTg1q4luYsZzytxVagY0vTjovkyJQpBrVid4u0YpoHJUyY1UPmIn/snT59VSgKoVShgiutY76iyn5jYroC9evsKeA8fF4AnDomnD1bR6bfHbzJhhXQ2/wazauFf9ljTUzUnsdhuAQxtCDD0jQ+8F8+USNyqUjvaztk1rUEAtZyzrUBO5zVdu92UiARIgAdMTsHYBNYaQjCjKafWf105Ru9mZSMAmBVTK45pN+5AsWRIM6tUGDWu+jXhWdeyjdt3J6QCZtu4+gjmLN8DX0xltXEeq88ciklxAnSplcpG3YrSf9ezYxCIE9E2JpRzJJEACJEACVkbgY2/8ia2Zk0JexvbIO5/36vzfRh+jMsbw8JOnz3FCRB9LiJ3lCUUEc+aCn7B+234VAWUiAUnAJgVUNuz16zc49/dVDBg5DS0aVUMzEf5v3HEIfMSC6Ig1HKs37VXrV8YM64ZqQk7fj4DKnW5yUXJ0n7m0rmcRAnojXzhHMwmQAAmQgJURyJY+mZXVOO7VldPz3QeOxx9/XYK8WDN/3pxirWY7teeCiQRsWkAjuleeRXbm3CWxEakb3IYFi3tmS6B+jfLq4/EhS/Ds+b8Y2LM1KjR0xbIZ3mptikwtxQG6zi3rolqlEjF+xjWg/EEiARKwdAI8R94ye8hUU/CW2VrWigTeJWBzEVC5prO0ONg2jTjG4dLVm2oRslwYLddrbtp5SNyEsBYho93VbQ1OYofeuBHd1QJm34k/4pWImnr0aImfxS74Qf6hahd8iuTJYvyMAsofKRIgARIggY8hQAH9GGrMYysEbE5APXyni81HJ/BUrD+RO+lktFOu1UyYMIE6ymHMlIVYJo6OSCJ2tHUSEc72zWupvrz/8DE8fUOw/8hvyCZ2wg9xaysOty0c62cUUFv5UWA7SIAESCB+CVBA45c332ZZBGxOQOMbLwU0vonzfSRAAiRgGwQooLbRj2zFxxGggH4cN0MuCqhGgMxOAiRAAnZKgAJqpx3PZisCFFCNA4ECqhEgs5MACZCAnRIwlYC+OLTHKKKJS1U06nk+TAJ6EKCAaqU4TWsB2vNfdXyqvRCWQAIkQAIkEK8ETCWg95oZJ5TpFhsnrJEhFanaQZ2hLfdcGJNO/nEeo4Le3iMvU0zlyFsM61Qto/Z0/Lh0E27+cw/9ujYz5nV8NjYCZriHxQ4EVFyMq04hM1GigJoILIslARIgAdsmYM8CKs8JPXryLCqWLmKUgF68cgPykPsv8ue27cFhB62zAwE1cS9SQE0MmMWTAAmQgG0SsBUB3b0iCOnE/epaUlwjoFrewbyWRYACqrU/KKBaCTI/CZAACdglAVsRUE/XVgiZt1b1YUtx82BXpwbqz/LYwyRJEqO38w/q63MXr6FT3wBsXzoBR06cwYjAuVg9x/eDCOivp/6EV+AcXLn+DyqVKaoinhFT8NPCVuOfO/fVUYnyz0+ePlO3LR05cRbZxRGK3gM64uuv8qsy5TT/sNGz1JR9xPngJYt+bpjKn7tkI56ISGz2rBkxwdsVuXJksctxaK5GU0C1kqeAaiXI/CRAAiRglwRsRUAb1aqEYX2ccPveA7QTF7wM7t0G35Yt9lECmlJc/lKjZX+4uTRFgxoVsPfgSXT1CMSoQZ2VOL4voPK2w9njPVDky88QJtaHbtx+APOnDMXLV69QS5TTs9MPopzy4nzwk+jmOQ7+A11U3b5v3g+bF45F2jQpxW2Jl5H/05zqvHCm+CNAAdXKmgKqlaD95re3+xHlUmy5JJuJBEhAEbAVAV02w8dwx/uUuatw65+7GN6v/UcJ6IVL19Hfe6q4iXCcYZQ0dRmOdo41oxTQU2cuIGhkL/XstZt30NRlGPauCsax3/5CP68p2LIo0FBOi65eaN2kOupUK4tqzfqKP3+v/pM3HjLFPwEKqFbmFFCtBJmfBOyHACXcfvo6Di21FQGVU+qZMqRVLV68Zgd2/3IMQb69PxDQv/6+Cud+o2Ocgj9y/CxmLvhJRTEjUuRd8O9HQG/evqeirzLJqfm6bT2x/6ep2Lr7yAfl9Bw8ETW++0aJ7LUbtxE0azl2/XIc7ZrVhHOrunBwMOGG5TiMB3t7hAKqtccpoFoJMj8JkAAJ2CUBWxHQJSFehl3pU+asxC0hhTICOm76YiV1fTo7qv49cPQ0PHynxSig5y9eF9diT8cmMT0ekVp290ErsbY0qin4iPWg7wuo3GHvMfLdcpx6+cGxXmVVTkSSUVMX9zHo4+KIapVK2OU4NFejKaBayVNAtRJkfhIgARKwSwK2IqD1q5fHCCGcd+8/gpS8Qb3a4LtyxbB07U6s2bwPs8Z5IEECByGWITjw6+8xCqicDq/Rwh0DerRUG48O/HpaCaKvh7NRAvrixUuxltQd/buJcqqVUUc+te89CiM9OqFqxRK4dPWmkuYXL1+ptaGNa1dCXTE1z6SVQNyPvqSAamVNAdVKkPlJgARIwC4J2IKA1hQbfVxa11PT2W/evEELEans3q6h6s/n/77AAJ9pOHv+stjsk0pJ3rSwVdi2ZHyMu+DlDnmvcXPVNLncMJQ6VQqUKFzAKAGV75frQIePmY0bt+6g1Ndf4F9Rn3rfl1Nldu4/Fpeu3URSsUu/crmvMVjsqk+UMKFdjkNzNZoCqpU8BVQrQeYnARIgAbskYAsCak0d195tFDo0r62is0zmJ0AB1doHFFCtBJmfBEiABOySgKkE9PGoAUbxTOk52qjnreXhfYdOolih/EiZIhkOiqn87gMnYH14gGHDlLW0w1brSQHV2rMUUK0EmZ8ESIAE7JKAqQTULmFG0Wjv8WHYvPOgWgqQJVN69BJngtb4rhTxWAgBCqjWjqCAaiXI/CRAAiRglwQooHbZ7Wz0/wlQQLUOBQqoVoLWm59nOpq27+ztoH7T0mTpFkiAAmqBncIqGUfgtXj8Iy+QooAah/rDpymgWgkyv0UQ0PC3iEXUn5UgAesjQAG1vj5jjfUjQAHVyHL9DS+NJWjPXiyRcQvOtb+RJZAACZAACWglQAHVSpD5rZkABVRj71FAJUBGzzQOI2YnARKwQwIUUDvsdDbZQIACqnEwUEA1AmR2EiABErBTAqYS0DX3LxhFtH7aT416ng+TgB4EKKAaKVJANQJkdhIgARKwUwKmElCHw1ONIvqmZDejno/88M1/7sFtWBDOX7wGlzb1sHj1Dowd3g2FC+b96DKjynjyj/MYFTQf84IH61quMYXNXrge50Q7fQZ0NCYbn42GAAVU49CggGoEyOwkQAIkYKcEbEFAx01fjCdPn2OIuMpSXnXZoP1gkwjo4yfP1H3uFUsX0TRa5OH0XxbIg/RpUxtdDgXUaGQxZqCAauRJAdUIkNlJwEwEeMqTmcDztQYCtiCgbsOCUaVCcTSsWUG1q1arASYRUL2GTcvuPvD1dMZnubMbXaRlCegbUX95FqD1Jgqoxr6jgGoEaKHZrf9H20LBslokQAI2I6Bjpi7EolXbkDRpEqROmQIb5o9+R0AdO49A386OKFfqK9Vm+eyRE2cRMKSL+nr7vqMYH7IU12/eRoG8n2CEe3v1f5kqNeqJ8V6u8Bg5HQXz54Jzq7oYETgXq+f4qs/L1euO/t1bYPLslSIC+ww1K5fG8H7t4ODggOO//QX/4Pm4eOUGUiZPBs+erVFVSPKIsXOwbN1OZEyfFokSJcTG+WOQIIEDgmevwJI1O/DmzRu0+aEGurStr95x6/Y9DAmYiV9P/YncObOi9Ndf4MGjJzFOwculAsNGz4JcmlC6+JdIkyoFShb9HPVrlI+2Xi9evIS8tWnXL8cg/1y0UD5M8e+j6rZxx0HIKPODh49RsUwReLl3RIrkSfHL4d8wSrTx5u27SJUiuaGN1vTjRQHV2FsUUI0AmZ0ESIAE7JSA7hHQ/yLudJcAACAASURBVB9IEp9rQHsOniiut/xGCZZMkSOgMQmolMMW3bwxfbQ7vvr8UyxftwvT563BunkBSCzksFi1TihVrKCSvQzp0+C3MxfeEdAiVTugTrWy8O7fUQloi67eGNa3HSp8UxhXr/+Dew8eqan2rXuOwH9SOLYuGafqV6WpG2aO8zBEQFes3415yzZj1ngPvH79Gq26j8Tg3m3UVL+M7qZNk1IsL3DCtRu30a63n/h+0WgF9OWrV6jVsj96iis/Gwgeew6cRDfPcfAf6KL4RFevLbsPI2zJRlUv4c/468JVFMyXCxcuXUdLwSgsaBDyiojtAJ9pyJUjC/oIqW/ccQjcu7VQ7b1+6w4SJUxodXfcU0A1/sVHAdUIkNlJwNoJcC7f2nvQbPXXXUD/3xJrENCZC9YJ0boCPyFnEalGC3f1tRRPKZgzAgegjIgiynTkxJkPBHRJiBe+yJ9bfS4jlYWEyLZqXO2d/nz2/F+UrNkZJ7bNVhHF9wXUxX0salUpjR/qfqvyTQhdikePnyoJLV7DBWvD/PFJ9szqs9GTF+Ch+Cy6TUjHROS1n9cUbFkUaKhDi65eaN2kukHQIz6IXK+z5y/DxX2MEt1qFUsgYcK3VwuFhq/Fn4JRwOC3EWO5fnVU8AIVBe47Yop4zgF9uzRH9iwZzDaGtbyYAqqFnshLAdUIkNlJgARIwE4J2JuALhRT8Ef/PwXvJ6KScirZzaWpoffb9vRVU+A1K3+jBHTHsoliujxNtAIa+XOvwDkqSujkWBN7D55UEcX7Igoq04nT53Fs60wVJXxfQBt1GIIbIoKYOHEi9ezLl6/UmlYP11Zqmv/XzTMMn8W2BnTr7iOYueAnzJ8y1NCmyBHimOollyYEz1qOqyLS6uHaElXKF4ffpHkqMpxCLCOQ6fXrN0iVMrla6iAFdkb4T1i0ehsqlSkqhLktUqZ4+5y1JAqoxp6igGoEyOwkQAIkYKcEbF1A5RS7a4fGhp3rk8Vay4tXbqo1oCFiuv2vv68aontyCFQXEdDAYd3UGkgpoLtWTDLsVo8qAhr58wgBbVizopLM2RM8UUyU81Cs2SwrRDJCQKs69lGR1YhNSJ36jkYTEf2sK6bzIye5HrR4dWesDx+N7Fkzqo/GhyzBnXsPo42Ayl36cs3qpoVjDUU59fKDY73K+LZssRjrFZHh0LE/1LT95oWBkMJ+/eYdtTY2uvT02b8YPCoUmTOmw0Cx1tWaEgVUY29RQDUCZHYSIAESsFMCti6gUsZyZMuE3s4/KBFs2d1XrPfMrQRUrm9sJXakTwvoi8JffKYifbMXrccqMb0sI5UfK6Ayetmk01Ahr0FIniyJkjgfscEnQkDl2skubRuoKKvcsCTfG758C4JG9lJ1lesp34hIo5TOnkMmIWum9Coaeuufu2jvNgplShSKVkDlBqIaLd3Rv1tLsT61jDo2qn3vURjp0QlfF84fbb3k+tIkiRMja+b0uHv/Ieo7DcLymT549OQp2riORLCvG4qL/HJpgKyf3KglN0YV/iKvYjVlzkq16SkmUbXEHzEKqMZeoYBqBMjsJEACJGCnBGxdQKVkevpOF9PFL5A+XSqxnrOQOrA+Yhf8tr1HEThtEW7ffSA2DOXGsD7t1DS6TB8roHIKXq7V3LTzILIIeaxdtQzClm4SkcwAJWvrt+1HgPhcRjjl95InS4oZ88W0+YotSvCyZc4Ar/4dUKLI52Jq/i4GB8zAid/PIc8nWcXGogr4469LMe6Cl+tAh4+Zrab1S4ld8/Js1Hrfl1NrQKOrl9y1P3jUDCHpT9U0evvmtdCy0du1rBEnBVy9fgtpUqeES+t66jMPwXX3/uNiw1YiFPjsE/h6OCuBtaZEAdXYWxRQjQCZnQRIgATslIAtCKiddl2cmy2jph2a18Z35YrFOY+9PEgB1djTFFCNAJmdBEiABOyUgKkEtP6f64wiuiZ/HaOet/eH5bFNcuo+cpJT9pP93NRO9WKF8qtI5sFfT6P7wAkq0popQ1p7x/ZB+ymgGocEBVQjQGYnARIgATslYCoBtVOcFtFseaD8ZjH9/1xMvcslAL3EmaA1vitlEXWztEpQQLX2SJcgrSVozn/Vz1lzGSyABEiABEggfglQQOOXN99mWQQooFr7gwKqlSDzkwAJkIBdEqCA2mW3s9H/J0AB1ToUKKBaCTI/CZAACdglAQqoXXY7G00B1WkMUEB1AsliSMBKCfAqTivtOPNXmwJq/j5gDcxH4N0I6BtREQfzVcYq30wBtcpuY6VJgARIwNwEKKDm7gG+35wEOAWvlT4FVCtB5icBEiABuyRgKgG9dkxGk+Keshdj5CnutPikXgQooFpJUkC1EmR+EiABErBLAqYS0KXOL4zi2XRGYqOej/ywvALSbViQuuHIpU09dGxhv2eKnvzjPNy9pmLD/NHR8pR3zzdrUEVdBapXist79XqXnuVQQLXSpIBqJcj8JEACJGCXBGxBQMdNX4wnT59jiFtbde1kkiQfL7NxHQQ/bf0FdauVjevj8fZcXESQAvpfd1BAtQ5NCqhWgsxPAiYk8FqULXcJMZGA5RGwBQF1GxaMKhWKo2HNCvEC+OGjJ2jcaSi2LAqMl/cZ8xIKqDG0xJajNyIZl8XSn47nf3AooJY+IFg/EiABErBIAtYuoGOmLsSiVduQNGkSpE6ZQk09S0H0mxSOPQeOw8HBAc3FdHP39o3Un6eFrUaK5Elx6swFbNxxEPOCByOpiJgODZiJC5dv4LPc2eE/qDPyfJIVL168hLxVaNcvx9SfixbKh/FernDq5Yffz/6NbFkyoMgXedX3KjXqqf7vMXI6CubPBbksoJtTQ1SrVEL1++k/L6Jj3wDsXD4JiRMl/GAsHP/tL/gHz8fFKzeQMnkyePZsjapCqmUqV687+ndvgcmzV4pI7zMxdV4aw/u1U+158fIVRk+ej3Xb9iN5sqRo06Q6FgoecZ2Cj8/3OnYegb6dHVGu1FeqXbLfjpw4i4AhXfDL4d8wSrT/5u27SJUiuaH9si+HjZmlPk+bJhU8XVuhcvmvdftZskEB1Y1N3AqyWAGVi8pt7HeLuPUIn4qGAE8L4tAgAcsiYO0CKmn2HDxRXDX5DerXKK/gDh41Q/1/WN92Ska7DAhEi0ZV4VivshJQeY+6a8fGaCCeT5QwEeq3G4iuTg3QuHYl9ZmcXl8wRUQ4dx9G2JKNmDnOQ8ge8NeFqyiYL5eSxDauvti1YpKhM4tV64RSxQrCZ0BHZEifBst+2olDx/5QUirThNCluP/wMYaLOkWVrl7/B/cePMKXBfJg654j8BcCvXXJOPVokaodUEdM93v376gEtEVXb9W2Ct8URvjyLVixfjdmBg5AIiG2vcVa2MtXb8VZQOPzvTEJaOOOQ+DerYVq0/Vbd0S/JFR31w/0C0XChAng5d5BSXynfqOxIXw00qVNpcsPEgVUK0aLFVCtDWN+EiABErBtAub+pcwWBbRkzc5YPdcPObNlUoNn1ca9WLlhN2aP91QCuu/QSYRNGqQ++/XUn+g7YjK2LRmvvpaRzuI1XLB75SQVxXRxHyPWljqhWsUSSoRkikpApSTOEBJYpviX6pl79x+hRkt3VW6qlMlRu/UAjPRwRsmin8c6oJ89/xeyDSe2zUaCBA5KQJeEeOGL/LlV3iEiWlvo80/RqnE1OIv6ybWoUp5l2r7vKAKCF8RZQCNXxtTvjUlA+46YIvg6oG+X5sguIssyvXr1Gt/U7oKVs32RO2cW9b3WPUbCybGmbhuoKKCxDsdYHqCAaiXI/CRAAtZEwNzWZk2sYqmrrQmojDKWr98Dv26egcSJE6nWy+lbv6BwrJ7jqwT05u17GNbHSX22edchtWs8bZqUBlJPnz3H0lBvNQ0vp4iDZy3H1Ru34eHaElXKF49WQHcsm4iMIvoZkXoPDVLTxVIcZZR2s1gzKqfNo0p7DwopFtHW+yIKKtOJ0+dxbOtMFQmUAhq5bK/AOcgrlgpIEWsi1qL269pcRQ5lMnYNaHy+930BlUsFjv5/Cl7K74zwn7Bo9TZUKlMUg3u3xUuxvKB8gx7vMH0uNpl59GiJJnW+1eWnUFcBlR0oO+X9JH8bkWsk5G8MNpcooDbXpWwQCZAACcQHAVsTUBk1KyWiZqsiRc1WbtiD9eLf/+mj+ykB/efOfbVjXqYjJ86oiOK6eQEx4pbT6d08x2HzwkA8ENP6bVxHvjMFLyVRTsmnT5vaUM62vUexcOVWFPnyMxVZ7dulWZTvuP/gMao0dcPsCZ4oJtaZymUDZcW6z8gCGrnsyAIqp6Qb1Khg2IC158AJjJzwY5wioGVLFIrX97bo5g3XDo1RsXQRxWHy7BVC5m+qNaAR6emzf8USilBkzpgOA7q3RMlanQXzseprUyRdBfSryu1xasecD+p5595DVGvWF0c3hZqiDeYtkwJqXv58OwmQAAlYKQFbE1DZDYP8Q/Fa7G2W6wYj1oC2b1ZLrRF9X0BfvnqFOq090KFFbTjWr4zXQmDPnL+MwgXz4tLVm0iSODGyZk6Pu/cfor7TICyf6aM2LX3XpBc2LngrRhHT5O8LqCy7Vsv+SCmm4McM7YbPP/skylEi3yMjmbtWBImNREnUJiIfsfkpLgL649JNas1qyBh3FS3t7zNVrVWNyyakQp/nidf3yg1aOcSyiN7OP6h+adndB1+JpQRSQOVSiMJiQ5dsw5Q5K9XyhxHu7eHpFyIux3RQvzDITVZ/XriCT7JnVhvJ9Ei6COjPh06pusj1EDPG9n+nXq9ev8aWXYdx8Nhp/PTjKD3qbFFl5Dj5NmRvznQo+4e7+sxZH76bBEiABEggdgK2KKCPHj+Fz4Qw7Pz5mFp/KXfBO7eqa9gFHzkCKgmdEwfY+4yfi5Ni2ltO21etUEKs1+ykoqNyQ9PDR0+RMkUytG9eCy0bvZ1FHTNlIVZu3KMESspfVBFQ+VzA5AWQfrJy9sgYO2O0eG7TzoPIkik9alctgzAhluvDAwxT8NFFQGVkVS4v2LjjgJCyZOjfrbna8LRebNSJLkU+BzQ+33vh0nV4+k7Hs+cvkD5dKrFetpC6PEAKqIf4/u79x8UJAYlQQIi6r1gvK8Vf9qW/aJ/cmCUPTCqQ9xNM9nN7Z8lE7KM8+id0EVCvcXOxV4Ser4idZBHrPiJemUCsuZCLkeWxBhHrJLRUOLa8f/19VRyLsEDtgEuTOoUYtLXR7v/LAiRAOSBXiSkBuWOtqzimoXWT71WRcpmAp990HD5+Rv1WJXe8yV11sX1GAY2tR/g5CZAACZBAVASME9C4HzEYnzchWXLPyiOEcufMqgSYyfII6CKgslnyN4HabTzMfjisXIeaURwfIBcry+ME5FqR0DH98VXBT9VxCfNXbBW/MfXDg4dP1HlioSJiK0Pz8riBZEkTi4XOrcQuvVPwFlK9ZXGg+g0ops8ooJY3qFkjEiABErAGAsYJaNxbtHfSy7g/LJ6s0OvthiFbSmfOXUbbnr5q5lUeKSQdpXlXrw+a6ObSFN+WLaZr0+PzXZErfvTkWbV84P0kPSfyBi1dG6uhMN0EVEmo2DUV1SGvGuqnOasMd8sjEupVLycWMY8X4fXSatGwTPIKMblWpZ9YnFy6Tjd1dETEEQRywW73dg3VjrDoPpODlgKquYustIC4RyOstIGsNgmQgIkJmEpATVxtiy++eRcvFYAaKGZea1UpbfH1tdcK6iqgEqI8ckHeciDXDryf5OLX+EzyaIHqzfthrjhzTN6wUFssdh4zrKta4CyTPJ9MHnY7VJwzVqfNABzaEGKontyZJw+9lbceRPdZ26Y1KKDx2aF8FwmQAAnYEAEKqA11JptiNAFdBTR41gpMn7daHGWQH6lTpfigMlNH9TG6gloyyOMQZIo48qGqYx91WK2UUZm27j6COYs3wNfT+YNjHeTCW7mAumHNitF+1rNjE4sQ0NOf6bMjzTjWjAAax4tPkwAJkMC7BNKkSEwkJGC3BHQV0O+a9MagXq1V1NDcKTR8rbpxYXpAPyQRxzbIJK+b8hG76yIioKs37cXazT+LqGg3VBNy+n4EVB6E20zs4IvuM5fW9SxCQM/kS2Zu3Hw/CZAACZCAkQRSJbe9tZdGIuDjdkxAVwEtIa7QWhvmr86aMmeS97Ou3fKzOhJKHt8QkdyGBasrvSLurB0fskQcSfCvWidSoaErls3wRrbMb6+hkmdkObesi2qVSsT4GdeAmrOn+W4SIAESsF4CnIK33r5jzbUT0FVAXQdNVMIWcS+q9uoZX8Lydbswb9lmTB3VVywDSK4KSCh2ssvDazftPIQZ89ciZLS7uE3hsdgF749xI7qjRJHP4TvxR7x6/UZdMyXPDZOH6cpd8PJsr5g+o4Aa30fMQQIkQAIkAFBAOQrsmYCuAipvBBgpjgCoLI5Ayp83pzjWKMk7bCPO3DQlcBnJlGd6Rk7yyquZ4waog1TlAbbLhKQmEQfedhIRTnm4rUzyDltP3xDsP/IbsmXJoNaNli/19n7XmD6jgJqyN1k2CZAACdguAZMJ6OUjxkH7pIRxz/NpEtCBgK4CKq+ziinJa7RsLVFAba1H2R4SIAESiB8CJhPQsNbGNcAp3LjnIz0tr210GxakbtVxaVMPHVvU+eiyImeU98rXbOmOpaHeSJc2VbS3HUXOI2c/Q+atURfNyPvl3w+CxaVi8gamEYFzsXqOb1wet5hn5LWgsi/6dY36znuLqWikiugqoJbYQFPXiQJqasIsnwRIgARsk4AtCKg8T/vJ0+dq1vDff18YNv3q0WObdx0S+zZKRnvfe+R3yKMfqzR1E/tQRiG9ENaIzcfG1sNaBFRusv6yQB7R1tSqiRev3FD98EX+3MY22WzPU0A1oqeAagTI7CRAAiRgBwQSiDbKw+siJ1sQULm5t0qF4uLIwrcXvJgqRXffe8T7zp6/jB4DJ2DTwrGaqmAtAio3SssjJCOOldTUaDNl1lVAv67uHGMzft08w0zNNN1rKaCmY8uSSYAESMCWCVi7gI6ZuhCLVm1DUrHfI3XKFNgwfzQePnoCv0nh2HPgOBwcHNBcHGXYvX0j9Wd5Uc2o4Pm4efsuUqVIDk9xAk1VIa9y+niuuEb7yZNnyJ41IyZ4uyJXjizvTLvHJKB//HVJ7OGYjr/+voosmdKjQ/PauHr9HxUFjbgA55xYItCpbwC2L52ghpQU1qHiwpkLl28oifMf1Bny6MW4CGhMbZwWtlqdrnPi93M4cfoc8n+aU4li3v+fP75xx0F1C+MDse+kYpki8HLvKDY7J4XMJ/8vL/KRz8wLHozXYhmCv+Alo5spxYboCF4jxs4Re1l2ius106rlBhvnj4E8evKfO/dVJFrud5FfL16zQ10KVLF0EQzr2w5pxPnssn2h4T8JvpnVMZSJxX4Y146N4VivsuISXV+Y4udQVwGVu8cjp+ciHH/h8nXMF8ciyQZGXIFpioaYrUxj19qYoKJX69qe2JsAE4skARIgAYsiEP8C6iDa/+ZDBhrWgPYcPBE1vvvGcLzh4FFv/z2SwiNFrcuAQLRoVFUJjjyL271bC1T4prC6KjOROKEmcaJE+F7cWLhZRC7TpkkJeYe7lLaECRPEWUDl+07/eVGsRQ1WEiyT3HAcnYDK9aV12nigq1MDdWqPXDsqN1EvmDI0TgIaUxulSM5csA4/Bg1CgbyfICR8DbbtOYolISNw4dJ1tBTXfIeJz6SQDvCZpkS7T2dHJaCyHm9dqbw4uScJbghG9x48UlPtW/ccgb8Q+61Lxqn2yeUGM8d5GCKgMn+EgK7csEeJ5PTR/dSlQN7j5kLeTz96aFfVvrY9/ZSoNqtfBb+d/Rvte/tj98pJ4plX0faFKX5wdBXQ6CooFyfLqy3DJw8xRRvMWyYF1Lz8+XYSIAESsFIC8S+g0YDSUUBL1uyM1XP9kPP/54HLK69XbtiN2eM90XfEFCGWDujbpTmyi9NmZJIyWK1ZX8hTcuR/8ujDiBQ56hnbFLwxAvrrqT9FXSZj25Lx6lVSzoqLc8ylhElfiW0TUkxtlCL4x18XMd7LVZUt18WWrtMVmxcFCg578OeFKwgY3EV9JtdxjgpeoDY8yXzy6zBxdXhUSUZV5XtPbJut1sTGJKBdPQLVhUARR2Jeu3FbXEU+AAfFdeMnfv9LLVXYt2ayikrLVLNlf0z2c1NSHF1fmOJHLF4EVFa8YsOe2LMqyBRtMG+ZFFDz8ufbSYAESMBKCdiagMojC8vX7wG53E5O7cokp939xNXWUrKkRM0Q07+LVm9DpTJFMbh3W3VZjBSkoFnLseuX42jXrCacW9VVcqSngMrpeed+o9UUvNzc5O41VUVcI9LTZ8/Vjvvbd+/HKKCxtVGK5I1/7mK4iABHpG8b90LIGHfIc8rlfxGS/VqcPS6v/JZRW5nv5u17GNbHyZBv70EhpGJpwn0RBZXpxOnzOLZ1poocxySgkSPNMp+U/KLVOioHk4I9fMxsrBGXBkWkum09ETi8u9rAFF1fmOJHLF4EdMe+X+E7aZ4KsdtcooBaVJdmP9/GoupjzspcyzvPnK/nu62ZQDQztdbcJEusu60JqBSdUrW7YNVsX+TOmUUhl1G/9dv2q+ng/2TvXwweFYrMGdOpmwgj0rWbd+DiPgZ9XBzVpTZaBFSus5QSK6e3ZTpw9DQ8fKcpAZXT0HJWVh7V9H6KbQ1obG2UInnqj/MI8u2tipbSXapWF+xYNgFL1+7EddHGEe7tP3hv5Cl0+eH9B4+VZM6e4IlihfKp5Qxl63U3CGhVcX34jMABUU7BOwuGtauUwQ91v1Xvketh6zkNxOGNITh68uwHgh1ZQKPrC1P8/OgqoLVaDfigjvK3ijv3Hqj1IBGLXE3RELOVSQE1G/qoXkwB/Y8KBdSihiYrQwIfELA1AZUNlLcIvhabYLzcOxjWgLZvVkutEZVT34W/yKsieFPmrFTnVvZ3bYFLl2+q6NuLl6/QzXOcmjquW62sJgGVsrdm8z7MEusk5ZS1vGjmwK+/KwF9+eoV6rT2QIcWteFYv7La7HNGbEoqXDBvnNaAxtRGKZJyA9DcSQNVeRNCl4oo8CksnDYcciNUG9eRCPZ1Q/HC+dUGIbkWVq4VfV9AL129CXm2+q4VQUieLAkWis1ePuKin4gIqIxydmnbQEy1f6NEO3L+Fet3Y+7ijQgd6460qVPCW+STz/gM6Bhl+yIEVK5Hle+Nqi9M8eOrq4DKDn8/yfB6oc8/VbvLbDJRQC2qWymgViqgUZ1RY1Eji5UhAf0J2KKASqnymRCGnT8fU9PLchd8xJS6h9ipvnv/cbXxqMBnn8DXw1kdFt+5/1hcunZTXZldudzXGCw2yEhJ1RIBlZug5SYfuds9bZpUSmqnha0yrPuUMugzfi5OimntRGK5QLUKJTDSo1OcBDSmNkoRvHztlprKPikioRG74D/NlU0NoO37jmJ8yFIRlbyFNEIOXVrXQ8tG1T4QUPns6MkLxBXiB9XO/tpVyyBMbCxaHx6g2MiocoD4XO54l98LW7LJsAlJ5p3+4xqEL9+s3il3wQ/q1Ub1R1QR3ggBzZ4lY7R9of/oB3QVUFNU0OLLpIBaVBdRQK1UQC1qFLEyJBA/BGxBQOOHlPW8RQqoXEcq17dabJIHIbzdf2TWpLuA3rh1V921fvbcJfVbTj5xnIL8DUhepWWTiQJqUd1KAaWAWtSAZGVIIAYCJhPQbUbut6jqbhX9JHerN+/q9UFd3Vya4tuyxXRtg1wrKae830+hY/uL8zfTRPuu96fSda2UjRWmq4D+Jg5Q7dAnQByvkFGt85BJHsQqpVR2WpH/f8+mGFJALao7cyxJblH1MWdlrjo+Nefr+W4SIIFYCJhMQG2EvLw5Sq7OsaZEAY17b+kqoE69/PD1V/nFGV/N3qmBXIR7+Pgf4mDWwXGvmbU8SQG1qJ6igP7XHRRQixqarAwJfECAAspBYc8EdBXQEuIg15WRjl+IAHtFHAEgF7na4lWcoIBa1M8PBZQCalEDkpUhgRgIUEA5POyZgK4CKg+bn+jTEyWLfv4O0yMnzqLP8GDsXD7R9lhTQN8uZo7idjdzdDYFlAJqjnHHd5LAxxCggH4MNeaxFQK6Cqi/uO1AHrEwoHtLfFXwU8VIHkMg72SV10L1dv7BVrj91w4KqEX1KQWUAmpRA5KVIQFGQDkGSCBKAroKqLzzdLxY77lgxRZ1oKxM8oyvFg2rok8XR3V2lc0lexBQKzqjkQJKAbW5v2PYIJslwAiozXYtGxYHAroKaMT75AGwl67cVLcN5M6ZVdx7mjQOVbHSR+xBQK2oayigFFArGq6sqhkJ7PN4e1e5OVPTGYlN8vpND98GgOKaaqS2weBQXBvP58xGQFcB3b3/hLjCKZe63zVy+uOvS+pKrlLFCpqtoSZ7MQXUZGg/pmAKKAX0Y8YN89gfAVsW0BwnHxnVoVcLW/c53YeO/SHulp+Bh4+fqGsuSxQpYFT7tT4s74ev2dIdS0O9bffMc62Qosivq4B+37wfhro54bty7x4I+8vh3zB87GxsXDDGBE0wb5FLnV+YtwLi7eUDXpq9DpZSAQooBdRSxiLrYdkEKKCR/q6wcgFt0c0bHZrXxveVSor9sG+MXu4nD7jfvu9X1Piu1EcP2s27DqFaxZLq3nmmuBHQVUC//r4Tls30Qb48Od55+9+Xb6Bhh8E2eQwTBTRuAy2+nqKAUkDja6zxPdZNgAJqOwJavkEPLBPRx+xZM37UoJSztys37Ebg8O4flZ+ZPo6ArgJap40HOrSoDcd6ld+pzYr1uxEybw3Wh4/+uFpacC4KqGV1DgWUAmpZI5K1sVQCFFB9BLRcve6QV2FOmbsKMpLYxamB2vcxVXz97Nm/aOtYA92cGqqXHf/tL/gHz8fFKzeQMnkyePZsjaoVJyWKVAAAIABJREFUiqvPZDn9u7fA5Nkr8eTpM3VyzvB+7eDg4ADHziPQt7MjypX6Sj27aNU2yOMdvQd0hOugidh36CSyZk6Pb4p9gYAhXSCdY+aCdbhz9wFy5ciivvdprmwq7/pt+xE0azmu3byD/OKq8GF9nNB7WBDuP3iM9OlSo02T6urZGfN/wrzg/y7P+bZxL/W13NfSqe9odGpVBxNDl+H8pWs4sG4ailTtgF0rJiF92tTq8+oimrpg5VZcF+8pXDAvRg/tarjCU9Zv8uwVqj6NalUS0dejmOzvhmyZM1jqj4tJ6qWrgC5evR2jxOBqJu5+l1dxyoFz6vR5LBLf7yt2wbcWHWtryeHwVLM36cqn7c1eB0upAAWUAmopY5H1sGwCFFB9BFSKV1MRdBrUqw1On/0brV1HonbVMvDp31FJXpNOQ7FuXoASxKviUpp7Dx7hywJ5sHXPEfhPCsfWJeNURWQ5daqVhbfIJwW0RVdvDOvbDhW+KRytgEqxlKlM3W5YNcfXIHAnfj+HzJnSqa/9xDsePHqMUYM64+z5y2jdYySCfHujuLi18bKoz2e5s2Pp2p34+fApQwR0h5iOj01A5QU7fgOdxb6XPEq43xfQf+7exwxxBXk6IaT9vacqqZWifu7iNbTq7oO5Ewci36c5MGXOSkz/cY3iQAHV+HfGmk37EC6OYTovIL958wZ5PsmmjmH6oe63Gku2zOwUUMvqFwooBdSyRiRrY6kEKKD6CehysfSuQN5PVIEyUjjBu6dhI5AU0CFib8j7G4OePf8XJWt2xolts9W6SSlwS0K8hNDlVuUMDpiJrz7/FK0aVzNaQCOPOXk2eci8teIq8EGQ97TLiGXA4LfiGpE+RkCLFy4A146NDWW8L6CVy3+Ntk1rqM9Xb9qL7XuPYryXK0LD1yo/8hvooj57KqLEpWp1poBa6l8UllwvCqhl9Q4FlAJqWSOStbFUAhRQ/QR05/JJyCCmr2Wq0tQNM8d5qMiiTHL6vH+3Fihd/AvsPXgSYUs2iunut7v0T4gZ0mNbZ6pNQ1LgdiybaJim9gqcg7yiDCfHmh8I6EIxBX9UTMFHFwENX74FG7bvV0sCHj15hnRpUqnpc79J80S0MpmKRBoroJUa9UT45CGGKXjH+pVRq0rpaAU08ufrtu4XU/+/qMirvLAnebKk79Th/Qiupf7M6F0vXafg9a6cNZRHAbWsXqKAUkAta0SyNpZKgAKqn4BGrH2MSUAL5sul5HT2BE8UK5RPHc1YVqz7jCygkcuJLKByl7trh8aoWLqIqrRcP3lRnDUelYDK6XO5FFAKZ6YMabFNTPXPWrhefS3XqV6+etMQfYwgsOynXWodacQmJLkpacrclVgwZah6RJ5pXqKGC9aG+RsEVC41rFn5m2gFNPLnkQVU7oeRdR/p0clQdvHqzti8KNCIKXh597X177angGr825ECqhGgztkpoBRQnYcUi7NRAhTQ+BXQ7FkzqPWgu1YEiQhgEsgops/4sDgJqMfI6ciRLZO6zluKa0uxhlJOz0cloMvX7cLazT9j1ngPyPM5B/qF4OqN20pAT/95Ee16+2P66H4o+mU+/PX3FbV0YMvuw2ot5qLpI5AwQQJcvnYTzbp4iY3TAWpT0eI1OyCFWH4dsQnpYwVUrkNt18sfP4r6yCjx3MUbMWbqQk7B2+jfMyZtFgXUpHiNLpwCSgE1etAwg10SoIDGr4DKKfjRkxdg086DyJIpvdqoFLZ0k5K6iCn46CKgFy5dh6fvdDx7/kLsVE+FMsULqXWUUQnoYzHlLne1yw1PGdOnQZM630JGOCN2tK/auFdFUG/duY+8YmOQXL8q12H2GjIJJ0+fg1OzmmrXvoyWrtqwRwioeF+JQpBrSSd4u2oWUEl9ydodmC7Wo8pbI+VUvZRxWQ9uQrLLv4o+vtEU0I9nZ4qcFFAKqCnGFcu0PQIUUH0E1PZGRvy2SE7vl6zRGT+vnWLb15ZHgZVT8BrHGgVUI0Cds1NAKaA6Dykji3stnk9gZB4+bg4CtiygTn8/NQppWJ7kRj3Phz+ewJOnz8Xmq3MoIXbRJxSbr2Yu+EmdTSojoPaWKKAae5wCqhGgztkpoBRQnYcUi7NRArYsoDbaZTbRLLlEoPvA8fjjr0tqG1H+vDkxtE87fP7Z22Os7ClRQDX29r1mFTWWoD37k6mbtRdiIyVQQCmgNjKU2QwTE6CAmhgwiyeBWAhoEFBONUm2FFDL+hmjgFJALWtEsjaWSoACaqk9w3rZCwENAmoviGJuJwVU73EgJyXkGWcflyigFNCPGznMZW8EKKD21uNsr6URoIBq7BEKqEaAWrJH4aoUUAqoliHFvPZDgAJqP33NlsYvgbjOj1NANfYLBVQjQJ2zU0ApoDoPKRZnowQooDbasWyW1RCggGrsKgqoRoA6Z7dqAdX5drWrjsYdxaJzV7A4ErBoAjYtoMfPG8e+aF7jnufTJKADAQqoRogUUI0Adc5u1QKqMwsKqM5AWZxVE5Cns8qpwYhk0wLaJci4vpre07jnP/Lp3kOD1M1E35Ur9pElGJ+tSNUO4vrPSepKTWtL5uAVn4wooBppU0A1AtQ5OwX0P6AUUJ0HF4uzKQIU0EjdGU8CeujYH/gsTw5kSBd/MmgKAf378g08fPwEhQvqGzn+aesvqFutrKFjzMErPn/IKaAaaVNANQLUOTsFlAKq85BicTZKgAIa/wJqjqFkCgEdN30xcmbLhOYNq+rWpIePnqBxp6HYsihQtzItvSAKqMYeooBqBKhzdgooBVTnIcXibJQABVQfAS1XrzvcXJpiytxVePHiJbo4NVB3mk8VXz979i/aOtZAN6eG6mWd+o5GswZVULPyN+rP1b8rhQUrt+L6zTsqmjh6aFdkTJ9GPbtxx0FI0Xvw8DEqlikCL/eOqtxpYavV/0+duaCemRc8GK9fvYZ/8HxcvHIDKZMng2fP1qhaobgqJzYBffPmDYJnr8CSNTsg/9zmhxro0rY+1m75GTPCf8KSUC8kTpRQvffk6fOoVqkE/CbNE99LhBQpkmH0kK44cPR3o+p0+s+L8Bkfht/O/o1MGdJivFcPeAXOxe/i62xZMqDIF3nF91zf4SUF1W9SOPYcOA4HBwc0Fxy7t2+k/izr9uTpM3W70pETZ5FdlOE9oCO+/iq/Rf/0UkA1dg8FVCNAnbNTQCmgOg8pFmejBCig+gioFLym9SpjUK82OC0EqrXrSNSuWgY+/TvimhDLJiKqt25eALJmTv+BgP5z9z5mjO2PdGJ9Zn/vqfg0VzYlsxcuXUfLbt4ICxqEvLmzY4DPNOTKkQV9Ojsq2Zq3bDNcOzZGgxrlkTRJEty4dQf3HjzClwXyYOueI/AXorZ1ybg4CeiK9btVebPGe+D169do1X0kBvdug4qli6grM4uLO9trVi6Ntj19sSTEC1kypYPHyOkoUaSAIQJqTJ1evHyFWi37o12zmkrGb9y6q4TxumhDG1dftV41IkUW9sGjZqhvD+vbDlJGuwwIRItGVeEo2Mv3h4avxWzRhiJffoawpZuwcfsBzJ8y1KJ/eimgGruHAqoRoM7ZLVFA43omms4owDWgehNleZZAQK/DIiig+gno8pk+KJD37V3m3zbuhQnePZWgySQFdIibk/r6/Qho5fJfo23TGuq51Zv2YvveoyryJ2XqzwtXEDC4i/ps36GTGBW8AKvn+CrZkl+HTRoU5XB89vxflKzZGSe2zUaCBA6xRkBd3MeiVpXS+KHut6q8CaFL8ejxU1HntkoKm3UegRxiul1+LmVPpqgENK51+vXUWSHb0wyCHNEIGb2NSUBlm1bP9VNT/zKt2rgXKzfsFtLpqZjIiHDQyF7qMyn+TV2GYe+qYEv4kY22DhRQjd1DAdUIUOfsFieg5rJPwZUCqvPgYnE2RYACGqk7NWxCkhHQncsnGTYWVWnqhpnjPPCZiFzK5CgErn+3Fihd/IsPBNSxfmUlfzKt27of67f9giDf3mqKe/m6XWJaO5n67PXrN0iVMjk2zB+tZOvm7XsY1sfJ0IC9B4WQLtmI+yIKKtMJMVV+bOtMJEqYMFYBbdRhiIqgJk6cSOV9KSKUVcT0va+ns/paRh5lVHW3iExGPBOVgMa1TlKyZy9c/0F0MiYBLVuyEMrX74FfN88w1OGXw7/BLyjcIOWR3//Pnfuo29YT+3+aatE/sxRQjd1DAdUIUOfsFiegOrfPmOIooMbQ4rP2RoACqp+ARj7myBgBjVgP+r6ASsmU60JHuLf/YFjKz6RgyQilTPcfPIZ85+wJnihWKJ+ani4r1qXGVUBlVLaJiG5G3n0e8dIz5y6jc/+xKFroM3yRL7dacymTh6+YghdT8xGbkIyp068n/4SnX8gHm40uXrkpIqAjo5yC/75SSZSq3QWrZvsid84sqg4rN+wRwr4f00f3U1IemQkF1E7+NqOAWlZHU0D/6w8KqGWNTeuuTRT33lp3g0ABtVwBPXfxmpKxYF83sQYzv5oSl9Phcpr/fdm6dPWmmubftSIIyZMlwcJV29QGn7gKqIy0hi/foqav5VS7fM8bEXHNkim9WA/qIzYlVVeboGSkdGbgAOTPm1NtBnr56pWKwsrobMi8Ne8IYEx1khumqrdwR/d2DYX4foc7dx+IdayJ1Wai75r0wsYFY5E5Yzq1fCDykoVB/qF4LTZJebl3MKwBbd+sFuqLdbAUUCv/y+hjq08BNZKcif8do4BSQI0ckXzcTglQQC1XQGXNtu8T60FDluLq9VtIkzolXFrXQ8tG1T6QLfns6MkLsGnnQSWNcgOU3ISzPjwgTlPwcuf7jPk/Yf6KLUp0s2XOAK/+HfDrqT/x86HfEDrWXYGSm5UWCbkNnzxUbJK6hj7DJ0Nuoho3vKd49sw7AhpbnU7+cR4+48Jw5vxlZBRnok4L6KfEdsyUhVi5cQ+++vxThIxxf0dAZd18JoRh58/H1HIEuQveuVVdwy54RkDt8C8yCqhldToFlAJqWSOStbFUAhRQfQTUUvuX9bJ8AmZcA2rG3Rk69gsFVEeYOhRFAaWA6jCMWIQdELBpAQ1eY1wPutY37nkre1qeT9q8q9cHtZZHPn1bNv6uBbUybCavrhkF1ORti5cXUEDjBXOcX0IBpYDGebAY+6CJl48YWx0+r42ATQuoNjTMTQLxQsC6BVSvA+E0oKaAaoBngqwUUAqoCYYVi7RBAhRQG+xUNsmqCFi3gEaDWl5JNdAvFLfF7jJ5TVdEkouNA8Ri5VXi+IJE4mqtruJ6sNZNvlcf37v/SByNMB2Hj59RO9C8xS0OpYoVjP2zZhXN3uFPpm42ex0spQIUUAqonmPRAn7H1bM5LCsSAQoohwMJmJeAzQnotRu30WPQBHyWJ4c6RyyygMpdbPNXbBW7y/qJ+2WfwKmXn9jh1h+ff/aJEtZkSRPDw7WVuGXhFLzHzcWWxYFqF11Mnzn3fmHeHhRv9x720ux1sJQKUEApoJYyFlkPyyZAAbXs/mHtbJ+AzQnonXsP1fEJyZMmweQ5K98R0G6e48URDaXF/bEVVM+Om75YnavVr0szlK7TTV1zJe9klamFuIdWntNVqUzRaD+Ti5cpoJb1Q0IBpYBa1ohkbSyVAAXUUnuG9bIXAjYnoBEd97OIYr4voLVbe2DMsK4oXDCvekzepbpl92EMFffU1mkzAIc2hBj6fUjATBTMlws1K5eO9jN5hy0F1LJ+VCigFFDLGpGsjaUSoIBaas+wXvZCwK4EtKpjH8wQNxlE3FG7dfcRzFm8Qd35+v4VWP7ijlV52GvDmhWj/axnxyYWIaAzJia2l/Eaezunxf6I3TzR1W5ayoaSgNEEljqbf/lU0xmm+bv75vMzRvHIkvRzo57nwySgBwGzCqgpF/hHFQFt3HEIfDw6GSKgqzftxdrNP4uoaDdUE3L6fgQ0zydZIe+qje4zeTMDI6B6DEP9ymAElBFQ/UYTS7JlArYcAV1/48MzL2Pqy9pZh9tyV7NtFkrArAJqSiZRCajbsGBUq1hC3Z0q0/iQJXj2/F8M7NkaFRq6YtkMb3UNl0wtxR2wzi3rolqlEjF+RgE1ZS8aXzYFlAJq/KhhDnskQAH9r9cpoPb4E2D+NtuVgG7aeUjc+boWIaPd8eDRY7EL3h/jRnRHiSKfw3fij3j1+g08erQU97+ewiD/ULULPkXyZDF+RgE1/yCOXAMKKAXUskYka2OpBCigFFBLHZv2Ui+7ElB5DuiYKQuxbN0uJEmcCJ1EhLN981qqr+8/fAxP3xDsP/Ibsomd8EPc2qJ8qcKxfkYBtawfFQooBdSyRiRrY6kEKKD6CGiZut3gKY4vnBC6FPLf2BYNq6J7+0aqcPl1aPhaLF6zA48eP0XF0kUwrG87nD57ET7j52JNmL96bmrYKvy4dBP2rAxGggQOWLx6O34R/xaPG9EDG3ccVCfWPBD/RlcsUwRe7h1FYCgppoWtVv8/deaCekYeuRixwdhSxxzr9S4BmxXQ+OpoCmh8kY7beyigtiagvP8ybiOfTxlLgAKqj4AWqdoBjWtXUqfJ3Lp9T52vPVgEcKqUL46V4tIXKZbTR/dD6lQp1Pna8l72kWIvRtl63bF1yTikT5taLXl7LARVfr9ooXwY4DMNJYp+jrIlCqGlOBIxLGgQ8ubOrr6fK0cW9OnsqAR03rLNcO3YWBytWB5JkyRBwoQJjB0GFvG8KffDWEQDo6mEhQmo9XUDBdSyhvexl6Mtq0JmrE2xRAPM+Ha+mgQsmwAFVD8BXTFzJPLnzakKDJ61Av/cuY8R7u3R1SNQHWUoBVUmeVFM7dYDcFAceejiPgZtf6iBkkI0m7oMUxt+X758paKn1Rz7IjSwP7aKYxL/vHAFAYO7qPz7Dp3EqOAFWD3HVwmo/Dps0iDLHmisXbQELExAra+n4iqgr0XTTPW7GW9C+m/cUED/Y0EBtb6/T1jj+CNAAdVPQLcvnYBMGdKqAhet2oY9B04gyLc35Mkz7t1aoMI3b5ezvXr1GkWrdcSeVUFYsHIbHj16gkIFP8Uvh39Dy0bVMFLsxRgrTqVpJSKiO5dPhN+keVgulszJvRgyvRb7NOTxiBvmj1YCelNEXIf1cYq/QcM36UqAAqoRZ1wFVONrYsxOAaWARjVAKKCm/Klj2dZOgAKqn4AuCfHCF/lzqwLl6TJyvebwfu3hLKKctauUwQ91v1WfXb3+D+o5DcThjSE4fPyMWtuZ55NsqFKhOKp/WxKVf3BD5zb11G2GY4Z2U5Ipr9SW0dT3k/xMRlrlfg0m6yRAAdXYbxRQjQB1zs4I6H9AKaA6Dy4WZ1MEKKD6CWjd78uJzUEdcO/+I/zgPAz+g1zUNdYr1u/G3MUbETrWHWlSpxQbj8Lg4OAAnwEd1VrQ737ordaALpo2XEU2PUZOx8k/zqvNwY71KuPcxWvqIphgXzcUL5xfbWS6fusOCuT9RMkpBdS6fyQpoBr7jwKqEaDO2SmgFFCdhxSLs1ECFFD9BNTTtTVC5q1RBbZoVBXdnBoaCp/+4xqEL9+svpa74Af1aqNkU6ZOfUernfKzxnuor9ds2gdPvxCsDw9A7pxZ1fe27zsqoqpLRfT0lpJYeQGMnK6Pm4Ba374SG/1xi7JZFFCNvU0B1QhQ5+wUUAqozkOKxdkoAQqofgK6e0UQ0qVNZaMjhc0yFQEKqEayFFCNAHXOTgGlgOo8pFicjRKwZQE9dG+BUb1WKl1Lo56P/LA8hmnXiklqKp2JBIwhQAE1hlYUz1JANQLUOXuOQTN0LtF6i7vq52y9lWfNScDEBGxZQE2M7p3iKaDxSdu23kUB1difFFCNAHXOTgH9DygFVOfBxeJsigAF1Ka6k42xQgIUUI2dRgHVCFDn7BRQCqjOQ4rF2SgBCqiNdiybZTUEKKAau4oCqhGgztkpoBRQnYcUi7NRAhRQG+1YkzSLu+lNgZUCqpEqBVQjQJ2zU0CtUEB53bvOPwUsLi4EKKBxocRnLJWAKW9XjK82U0A1kqaAagRoTHZ5l6n8qYshlbr2ypgSbfrZQ9kT2nT72DgS0EKAAqqFHvOSgHYCFFCNDCmgGgHqnD3+BNTyp2RMLaBx+H1A595lcSSgHwGbFtC/jeSUx8jn+TgJ6ECAAqoRIgVUI0Cds8efgOpccRMUZ2oBNUGVWSQJxBsBmxbQaUZi7Grk83xcEXj16jVqtnTH0lBvHsT/EWOCAvoR0CJnoYBqBKhzdgrof0ApoDoPrv8Xx8ivabjGd6kU0EjENQjovkMn8WWBPFZ7EL28k377vl9R47tSsQ7BqJ7dvOsQqlUsiQQJ5GJ2JmMIUECNoRXFsxRQjQB1zk4BpYDqPKRYnI0SoIDqI6Atu/vA19MZn+XObpUjZff+E1i5YTcCh3ePtf7GPBtrYRb1gHmWlFFANQ4CCqhGgDpnp4BSQHUeUiwuGgLWHgmmgGoX0BFj52DZup3ImD4tEiVKiI3zx6Bz/7Ho1KoOJoYuw/lL13Bg3TSsWL8bMxesw527D5ArRxYEDOmCT3Nlw5ETZxAa/pP4Xmas3fwzEidOBNeOjeFYr7Kq3I9LN2Huko148uQZsmfNiAnerip/mbrd4OnaChNCl+LNmzdo0bAqurdvpPI8fPQEfpPCsefAcTg4OKB5gyrqM/nnaWGrkSJ5Upw6cwEbdxyEz4COGB+yBPcfPEb6dKnRpkl1tG9eK8r6Pn32HD0GTfjg2cg3QZ27eA0+4+fi9NmLYko+Nfp0djREVjv1HY3qIsq6YOVWXL95B4UL5sXooV0FuzR2+3cMBVRj11NANQLUOTsFlAKq85BicTZKgAKqXUBlCVWaumHmOA9DBFSK1pXr/8BvoDO+yJ9HCd+J388hc6Z0yJY5g5LDB48eY9SgzkpA2/b0wxC3tmhWvwp+O/s32vf2x+6Vk/DixSt837wfNi8ci7RpUuLMucvI/2lOJEyYAFL6GteuhKFuTrh1+x6cevlhsCijSvniGDzq7XXMw/q2UzLaZUAgWjSqqqRWCui8ZZuV5DaoUR5JkyRRsvnz4VPvRECjq+/StTs/eDZCQFOnSoH6ToPQqWUdNKnzrZLcLkLGfwwejHx5ckBy+efufcwY21/JaX/vqUrC3Vya2uhPWOzNooDGzijGJyigGgHqnJ0CSgHVeUixOBslQAE1nYAWL1xASV5Uaff+4wiZtxY/Bg1SAtpj4ATsWzNZRShlqtmyPyb7uSGvmNKv1qwvWjf5Xv2XInkyQ3FS+lbMHIn8eXOI7zkgeNYK/HPnPka4t0fJmp2xeq4fcmbLpJ5ftXGvmmKfPd5TCahcsxo2aZChrKikMnK9I9c3JgG9fPUW+oyYjC2LAg3ZhwTMRA5Rj+7tGioBrVz+a7RtWkN9vnrTXmzfexTjvVxt9Ccs9mZRQGNnRAHVyCg+s1NAKaDxOd74LuslMMw7kdkrP2NiYtPUIR53wUcVAXWsXxm1qpQ2tC18+RZs2L5fRDVf4pGYTk+XJhXmicigFNDhY2ZjTZi/4dm6bT1VNPKL/Llx7cZtBM1ajl2/HEe7ZjXh3KquElUpoNuXTkCmDGlVvkWrtokp9xMYKdailq/fA79unqGm82X65fBv8AsKx+o5vkpAb4qI6bA+TjEKaHT1jUlADx8/g1limcH8KUMNZU+auQwPHj5REV4poJG5rNu6H+u3/YIg396mGQNWUCoFVGMnMQKqEaDO2SmgFFCdhxSLs1ECFNBIHathF3xVxz6YETjgnSn4ZmLdZc3K36gX7BA7zEcFz1fCKYVx254jmLVwvUFARwTOVXIYkSILaMT3rok1ky7uY9DHxRHVKpVQArokxEtJqkxyHeeDh4+F6DmhVO0uWDXbF7lzZlGfrdywR4jefkwf3U8JqIyUSiGMSMt+2qWiohGbkGKq7/vPyjIipuAvXLoOd6+p2LpknKFsuRxARnKlOEsBjcyFAipi12IBr9z+xPSRBCigHwnORNkooBRQEw0tFmtjBCig+gho445D0KVtAyWcMjr5vmgtX7dLbTCaNd5DnZs50C8EV0VkMyICGp2Ays1Gl67eVJL54uUrdPMcp9Z91q1WVklf3e/Lwcu9A+7df4QfnIfBf5ALKpUpikH+oXgttEZ+FrEGtH2zWqgv1nxGJaBbdh/GlDkrsWj6CCRMkEBN10dX3/eflUcvRV4DWq/tQHQQm5gc1XrWC2pD1sKpw5UMU0A//AuEAqrxL1UKqEaAOmengFJAdR5SLM5GCVBA9RFQGV0MmLxA7UZfHx6AnoMnqUhfdSGk8qSEx2LKvfewIFwVG5Pkjm+5QUdGEmMT0OxZMiqBu3TtptgslBiVy32tNholSphQSZ+na2uxlnSNaoTcZNTNqaH686PHT+EzIQw7fz6GVCmTq13wEVP3UQno02f/oteQSTh5+hycxDS/U9Oa0db3/WflO9/fBS+XFPzx10VkE/Xv16UZvitXTNWLAkoB1f2vUgqo7kg1FUgBpYBqGkDmziz3YXBOKl56gQKqj4DGS2e99xIpfbtXBPH2IXPA1/GdjIBqhEkB1QhQ5+wUUAqozkOKxdkoAZsW0PVGdlptI5838+ORo45mrgpfr4EABVQDPJmVAqoRoM7ZKaAUUJ2HFIuzUQI2LaD/a+/O43Ss9z+Ov20lLUREi9OiVBQVyVLRlCzZJiOMEbKMfTe2LIORbexLliZJqQgd2aKjbCWpwzkt6ieFHFoOCVmGc12XGjX8cs99XTP3tbzux+P8cXJ9v/f3+/x85573fK/l9mnNfp8WAdQfBSaA2qwjAdQmoMPNCaAEUIeXFN35VIAA6tPCMi3PCBBAbZaKAGoT0OHmBFACqMNLiu58KkAA9WlhmZZnBAigNktFALUJ6HBzAigB1OElRXc+FSCA+rSwTMszAgRQm6UigNoEdLg5AZQA6vCSojufChBAfVrerOm1AAAUG0lEQVRYpuUZAQKozVIRQG0COtycAEoAdXhJ0Z1PBQigPi0s0/KMAAHUZqkIoDYBHW5OACWAOryk6M6nAr4OoAc+zFjV8p352kxeCGSlAAHUpjYB1Cagw82veaulwz16t7vvas707uAZOQKZLODnAHp68xMZ0stWZkGGjudgBJwQIIDaVHRDAJ0R19DmLPzTPNunuf0zGZszIYDaBKS5rwUIoGfL68YAumHzv3T7LX/TlXkv9/U6DPLkCKA2q08AtQnocHMC6FlQAqjDi8vH3Znf/ml+C2iQXgRQdwfQRu2GaFjvlrqpaJEgLctAzZUAarPcBFCbgA43J4ASQB1eUnTnUwECqP0A+lTn4WpUN0rVqtyn48dPqHyt9urSqr7i6le1On8ourOeT+6l/FdeoX7PztS/v9ipU6dOWW3aNatrHTNn/krNfn2Fjhz5VUWuLqBxiR006+WlWrD0XRW4Mq9y5syhFS+P0pGjv2rAqOf1/kefKu8Vl6l3h8aqXKG0T1dnMKZFALVZZwKoTUCHmxNACaDpl9SGhJwOrzLvdldhxEnvDt7hkRNA7QfQKS8s0n8PHlK/znFat2mbRk5+xQqRz43srm9271OTDkO1dtFEpaae0voPt6l8mZL64ccDqt2sr96YNURXXHapHnmyu96eN9oIlZdq+47dKnbDtcqRI7uq1O+iWckJaTugfZJmWP99cI/m+vyrb/V095FaPnek8uW9zOGVQXdZJUAAtSnthgA68/ZcNmfho+Z5Yn00GXtT4RT8GT8C6Nl1RAA9a0EAtR9AP/zkcw2fONcKk0kT5urGooU1OWWRVr+erCVvb5R5HeeYge3O+SBrGD9YXVrHqGyp2xTVoJtiox+x/pfnkrPX8P8xgJoBtmz1NlqUMkxFry1k9RfbfqiaxjymxypzB7+93xSRa00AtWlPALUJ6HRzAmiaKAGUAJr+x4sASgA930duuDchmafdK9Rur3/MH6cGbQZr1pieGjp+jhrXe0RLV7+v0iWKqUHtKtZu6OSUhfp2zz7jYuNs+r+dezRhSCdjR7SE9u77UROff0Pvvb9VTzV4TC0b1zQOyfanHdCDPx+23qeAcSr/99cx470T2jdSdI0Hnf4tQn9ZJEAAtQlNALUJ6HRzAigBNN2aYgeUHdDzfcywA2p/B9TsoXnXZ1W9SjnNXbhKi40dyrlvrNLuvd9rzYaPNfXZbrrh+sKKaT1INaPutwKmGS6faDlAPeKftALo76+9+39Sqx6j1LVVjKIeuEcPx3TVzDG9rFPw5g7ovdVaW6fqCxbI5/RvDfqLkAAB1CY8AdQmoNPNCaD+D6Dm7drmbdshvgigBFAC6F//sIS7A2r2OvXFxVr2ziZVLl9K3do0sHY52/Yea900ZO6Mmq+omG4a0b+NypQqbl2/2bBtoqYO76q77rhZu77br9uKFdWJk6lGu2TVq/6AFVbrteivNnG1rVPsZmjtnTTdeFJDNvXvEqdLcl+sr4xd1OuKFDRO218c4icBh7lNgABqsyIEUJuATjcngPo/gGZwzRBACaAE0MwLoFu2bVdcxyS9OKGv7r3rVuuNqjXupVJGuDRDp/lasmqjxs2YrwL5rtAdxW/Qz4cOq37Nh3THrTeodc/R2rV3vy6+KJcRYkurnxEwc+bIYYTaDzTCuKnp9OnTWjZ3hHH3/GnretPV67ZY/+2WG6/T5KQu1s1LvLwpQAC1WTcCqE1Ap5uHEkCzG296yuk3dl9/XAN6piYEUAIoATTzAqj7PvkYkVcECKA2K0UAtQnocPP5m0843KN3u+OGEwJo+tXLmjgr4utrQL9MytAHV7Zb+mboeA5GwAkBAqhNRTcE0Cf6ZuzDxuaUXd38cD8+SH8vUJaFDZfvKLMDyg5o0HZAXf0hzeAQ+E2AAGpzKRBAbQI63JwASthIv6QIoKwJAqjDH7R0h4ADAgRQm4huCKBLWx2zOQv/NJ8wjjsis3wH1OXLhwBKACWAuvyHlOEFUoAAarPsBFCbgA43J4ASNrJ+B9S8o828DsH9ryy7LMP9FPLzNaAe4GeICIgAanMRuCGAzry3mc1Z+Kf5/Pde8M9kbM6EsHEGkB1Q/ihhB9TmhwnNEcgEAQJoCKgHDv5iPAT3OX20dbv1LQyJPVtYD9Q1XwTQEACz8BACKGEj/XJzw05XFv4I/OVbJQ446ZahRHwcblgXM8fnirgDA0AgUgIE0BDk+yTNUO6LcymhQ2Nt2PxvJSbP1qrXxlgPyyWAhgCYhYcQQAmgBND//wcuuAH03K/PIoBm4Qczb4XAeQQIoBdYFuY3LtxXo63enJ2kIoXyW0ebXyPW7qk6evD+UgRQl/1YEUAJoG4JoOa3hZqxx02v4AbQc6tAAHXTymQsQRQggF6g6vt/OKAaTXpp8/LpaUf2HzFLxW++XnH1q7oigFY7HMSly5wvJFD/wWYXOiQQ/97yoxcCMc9QJslnxVml5S74BkdOwYeyajnGrwIE0AtU9ts9+9Wkw1C9t3BC2pHm99Fedukl6tgimgDq158M5uUbATcEDbdgEkAJoG5Zi4wDAQLoBdbAwUOHFRXT9Zwd0L9dd7VaxT7OCkIAAQQQQAABBBDIoAABNASwinU6aMHMRBUueOYa0Ebthqhlo5qKeuCeEFpzCAIIIIAAAggggMAfBQigIayHYePnKPXUaSW0b6SNxl3wfYfPsO6Cz3NJ7hBacwgCCARVwI03IgW1FswbAQTcJUAADaEe5mn43sOm64Mtn6qwcSd8/y5xqlCmZAgtOQQBBBBAAAEEEEAgvQABNIw1YT6aacTkV7R4+TrlzJlD8U3rKDb6kYz15J1v78vYvAJ+9NoPtqpH4lSNG9xB5cuUCLiGx6afCduVazZ8ogmzFmjnrv/oumsKqY/xLGHWhcfWhcPDXbdpmyalLNRXX+82bmbNo4Z1HjZ+h9R2+F3oDgH3CxBAw6jRwmVr9fLC1Zo+qrt+PnRETTslacbonrr1puvC6I0mfhFImbdMS1ZtVGrqKetyDYKG/cp6+e808w/VpAkvqfrD5XTn7TfrnXVbNHB0itYtnmh9iQWvYAq89uY/dGPRIipdopi+//GAGrcfqlHPxKts6duCCcKsAytAAA2j9G17jzV+qdyn2lUrWq2Tn3tNp4xfNj3inwyjN5r4RWDFmk3WpRnm+mjfrC4B1C+FdWoexnXkpR5tqZXzRuvqglc61Sv9eFwgPmGMqlUpp7rVKnl8JgwfgYwJEEAz5mUdXT02QaMGxKtk8Rut/794xXqtWvuRJg7tFEZvNMkMgUjunDXpMIwAmhlFtdtnJBeFMfZtn3+tzs9M0KpXk5U9u9u+I8kuLu0zKnDiZKrWbdqqIWNf1KvTBqpggXwZ7YLjEfC0AAE0jPI9bDwXdOaYXrrJOI1ivlav3aIXXluuORP7htEbTfwmQAB1tqKZcGmmswMMobdjx08oruMwPW08vu2xymVDaMEhfhYwv03v7ys3KHfui9S3UxPVeezM2TReCARJgAAaRrXrteivIQlPp+2AvrlyvZa8vdG4JrRHGL3RxG8CBFC/VdTefE6mpqpT/wnGNeLXq0ur+vY6o7VvBE4Zl2Ts+OY79Ro6TQ3rRqlBrcq+mRsTQSAUAQJoKErpjukyYJKiKt2jWlUrWP8ydvrr+vXYcfXpGBtGbzTxmwAB1G8VDX8+5g1pPYdMU/58l1uPb+OFQHqBGXOXaPuOXcaNSG3BQSBQAgTQMMq98t3NmvnyEk0f2UM//3LYuAt+uJIHtdM9d94aRm808ZsAAdRvFQ1vPuZd8OapVnMHdEDXp5Ttt8s+c+XKpVzG49t4BVPAvF/gvrtv1xWX5dGu7/Zbu+PRNR5UXP2qwQRh1oEVIICGUXrzF8uoKfO0YOl7uihXTuu6rmZPVgujJ5r4UYAA6seqZnxOX329R3Wa9zunYccW0Tz3MeOcvmmRMOw54+ajbTp69JiuzHu5dSbNXBM5cmT3zRyZCAKhCBBAQ1HiGAQQQAABBBBAAAHHBAigjlHSEQIIIIAAAggggEAoAgTQUJR8ckyEH4PoE0WmgQACTgn44RFbTlnQDwJBEyCABq3izBcBBBBAAAEEEIiwAAE0wgXg7RFAAAEEEEAAgaAJEECDVnHmiwACCCCAAAIIRFiAABrhAvD2CCCAAAIIIIBA0AQIoEGrOPNFAAEEEEAAAQQiLEAAjXABeHsEEHCpAI+NcGlhGBYCCIQn4K7nThBAw6sirRDwpQCZy5dlZVIIIICA6wQIoK4rCQNC4K8EiIisDwQQQAAB7ws4H0DdtcPr/Qp5ZQbkIq9UinEigAACCCAQcQHnA2jEp8QAEEAAAQQQQAABBNwsQAB1c3UYGwIIIIAAAggg4EMBAqgPi8qUEEAAAQQQQAABNwsQQN1cHcaGAAIIIIAAAgj4UODcAMpNRD4sM1NCAAEEEEAAAQTcI8AOqHtqwUgQcI3Av774WgNHpWjHt3tVsUxJTUrqHLGxRT/9jJ6o+ZBiox+J2BiC9cY80iJY9Wa2CERGgAAaGXfeFQFXCzSMH6zixYqqY4tonTiZqiKF8kdsvATQTKLnbFcmwdItAgiEIkAADUWJYxAImEDZ6vFKHtReD5S7M+IzJ4BGvAQMAAEEEHBcgADqOCkdIuBdgc++/EZdB07Wru/2p01i2dwRKnrt1Zq/5F3NeuUt7d3/k4peU0jxTeuoRlQ567hv9+xT9dgErX49WYULntktPZmaqlJRT+vlKc+o1B03a/jEucpzSW4d/fWY3ly5XqdPnVYlI+AO6t5cl+bJbbU5eOiwBo+ZrXc3fmIce7FaxT6upavfV62qFTkF791lxcgRQACBcwQIoCwKBBA4R6D0oy01dXhXlS9Twvq3NRs+UY/EKRrUo7lKlyimzf/8QonJszUusYMevL9UyAH09b+vUWPjWs6YxyvrwM+/qJsRdutWr2Sd6jdfvZOm69MvdurZfq2tsDp19mKtWLNJPds1IoCyThFAAAEfCRBAfVRMpoKAUwLpA2hcxyTddftNRhBsmPYWw8bP0Vc79yhlbO+QA+jqdVv09rzRypYtm9XP+JkL9NmXOzVtRHcdOfqrytVsq0nDuuih8qWsf//l8FE9UK+TesQ/SQB1qrj0gwACCLhAgADqgiIwBATcJpA+gFaq01F9OsWqZtT9aUNdvGK9Rk55ResXTwo5gH6z+z9W2Pz9lTJvmcxQ+tKkfvry692q27y/1iwYp4IF8qUdU6NJghE+HyWAum2RMB4EEEDAhgAB1AYeTd0jwA29ztYifQA1dyYHdHvqTwF00fJ1GjdjvhUYz3cNqLmjad7M9MdrQPd9/1/rtP35Auj2HbtVr0V/vfvGeF2VP2/aMXWa91ODWlUIoM6WmN4QQACBiAoQQCPKz5sj4E6B852Cv/O2G9WrfaO0AZun4M3nhM4a00s//HRQD0V31ltzntUN1xe2jvl0+07FtB4UcgA9fOTMKfjnRnZXxbIlrT6OHz+hisbua5dW9Qmg7lwqjAoBBBAIS4AAGhYbjRDwt0D6APrO+o+VMHSaEnu20N133qIPP/5cA0enWA+or2A8qN58PRzT1dghLa9ubWJ0yLh2s9eQaVr7wdaQA6jZh9nGvK40qU8r6874lFeXa+GytVwD6u/lxuwQQCCAAgTQABadKSNwIYH0AdQ8fsnbGzVtzpvabTyiqcjVV6lNXC3VrVYprauPtm5X0oSXtHffj7rKuIazaf2qmjJ7kcYO7pD2GKa/OgVvdnTolyMaZvTx3sZ/KkeO7NZjmLZ+tkN3l7yFHdALFY1/RwABBDwkQAD1ULEYKgIIIIAAAggg4AcBAqgfqsgcMkWAb8TOFFZfd8qa8XV5mRwCCDgoQAB1EJOuEEAAAQQQQAABBC4sQAC9sFFIR7DzERITByGAAAIIIIAAAiKAsggQQOBPAvwxxYJAAAEEEMhsAQJoZgvTPwIIIIAAAggggMCfBAigLAgEvCrA1z95tXKMGwEEEAi8AAE08Esg6wDIS1lnzTshgAACCCAgufc3LwGU9YkAAggggAACCCCQpQIEUMe5uYXDcVI6RAABBBBAAAFfCRBAfVVOJoMAAggggEAABdj78VzRCaCeKxkDjpwAn3CRs+edEUAAAQTcKhDOb0cCqFurybgQQAABBBBAAAGfChBAfVpYpoUAAggggAACCLhVgADq1sowLgSCIBDOeZsguDBHBBBAIIMCXvs4JYBmsMAcHqqA134UQp0XxyGAAAIIIICAXQECqF1B2iOAAAIIIIAAAghkSIAAmiEuLx7MTqQXq8aYEUAAAQQQyFqBrP3WJAJo1laXd0MAAQQQQAABBAIvQAAN/BIAAAEEEEAAAQQQyFoBAmjWevNuCCDgCQEuXfFEmRgkAgh4VoAA6tnSMfDIC2Tt9TKRny8jQAABBBBAwBkBAqgzjvTiVgE2stxaGcaFAAIIIBBgAQJogIvP1BFAAAEEEEAAgUgIEEAjoc57IoAAAggggAACARYggAa4+EwdAQQQQAABBBCIhAABNBLqvCcCCCCAAAIIIBBgAQKob4rPHdm+KSUTQQABBBBAwOcCBFCfF5jpIYAAAggggAACbhMggLqtIowHAQQQQAABBBDwuQAB1OcFZnoIIIAAAggggIDbBAigbqsI40EAAQQQcLkA33Dh8gIxPA8IEEA9UCSGiAACbhAgdLihCowBAQT8IUAA9UcdmQUCCCCAAAIIIOAZAQKoZ0rFQBFAAIHfBHjqGksBAQQ8LkAA9XgBGT4CCCCAAAIIIOA1AQKo1yrGeBFAAAEEEEAAAY8LEEA9XkA/DJ9bO/xQReaAAAIIIIBA6AIE0NCtOBIBBBBAAAHxRzOLAAH7Av8D0l0q1SWcG0cAAAAASUVORK5CYII=", + "text/html": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "px.histogram(jdf_cmp, x=\"found\",\n", + " color=CT_PACKAGE,\n", + " range_x=[0,3],\n", + " nbins=5000)" + ] + }, + { + "cell_type": "markdown", + "id": "215a0974-8a84-4de7-8b92-fd184ea3b062", + "metadata": {}, + "source": [ + "## Combining both estimates with Bayesian analysis\n", + "\n", + "So far, we have been taking the figures for granted. Can we have a more precise estimate for each sector? Can we put some uncertainty margins around these numbers?\n", + "\n", + "I am going to show in this section how Bayesian analysis can help. Our goal is: for a given sector, given the reports from the sources and the report from country inventories, can we have a better guess at the true value of emissions? \n", + "\n", + "We will take some values from the manufacturing sector, but other sectors can also be considered." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "b1e05456-b9fe-45b8-8f7e-73c4d12bb052", + "metadata": {}, + "outputs": [], + "source": [ + "import arviz as az\n", + "import pymc as pm\n", + "import numpy as np\n", + "import scipy\n", + "import logging\n", + "logging.getLogger(\"matplotlib\").setLevel(\"WARNING\")\n", + "logging.getLogger(\"filelock\").setLevel(\"WARNING\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "2c94dbd7-ee43-4d06-8bb3-f0f5df47a290", + "metadata": {}, + "outputs": [], + "source": [ + "subs_df = (jdf_cmp\n", + " .filter(c_ct_package == \"manufacturing\")\n", + " .filter((C(\"found\") > 0.1) & (C(\"found\") < 10))\n", + " .drop_nulls()\n", + " .sort(by=EMISSIONS_QUANTITY_S))\n", + "# px.histogram(subs_df, x=EMISSIONS_QUANTITY_CE,\n", + "# hover_name=ISO3_COUNTRY,\n", + "# # log_x=True,\n", + "# # range_x=[0,3],\n", + "# nbins=500)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "fb0730df-0d30-4377-acf7-ec1c0ee2655b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (386, 6)
iso3_countryct_packagect_fileemissions_quantity_semissions_quantity_cefound
enumcatcatf64f64f64
"CHL""manufacturing""chemicals"2885.02885.01.0
"SYR""manufacturing""steel"3744.03744.01.0
"VEN""manufacturing""chemicals"6396.06396.01.0
"VEN""manufacturing""steel"6564.06564.01.0
"TCD""manufacturing""chemicals"13428.013428.01.0
………………
"CHN""manufacturing""aluminum"2.13497907e82.13497907e81.0
"IND""manufacturing""cement"2.52596928e82.58232689e80.978176
"CHN""manufacturing""chemicals"2.6414734e82.8985344e80.911313
"CHN""manufacturing""cement"7.046727e81.1672e90.603719
"CHN""manufacturing""steel"9.22971074e81.2870e90.717133
" + ], + "text/plain": [ + "shape: (386, 6)\n", + "┌──────────────┬───────────────┬───────────┬──────────────────────┬─────────────────────┬──────────┐\n", + "│ iso3_country ┆ ct_package ┆ ct_file ┆ emissions_quantity_s ┆ emissions_quantity_ ┆ found │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ ce ┆ --- │\n", + "│ enum ┆ cat ┆ cat ┆ f64 ┆ --- ┆ f64 │\n", + "│ ┆ ┆ ┆ ┆ f64 ┆ │\n", + "╞══════════════╪═══════════════╪═══════════╪══════════════════════╪═════════════════════╪══════════╡\n", + "│ CHL ┆ manufacturing ┆ chemicals ┆ 2885.0 ┆ 2885.0 ┆ 1.0 │\n", + "│ SYR ┆ manufacturing ┆ steel ┆ 3744.0 ┆ 3744.0 ┆ 1.0 │\n", + "│ VEN ┆ manufacturing ┆ chemicals ┆ 6396.0 ┆ 6396.0 ┆ 1.0 │\n", + "│ VEN ┆ manufacturing ┆ steel ┆ 6564.0 ┆ 6564.0 ┆ 1.0 │\n", + "│ TCD ┆ manufacturing ┆ chemicals ┆ 13428.0 ┆ 13428.0 ┆ 1.0 │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ CHN ┆ manufacturing ┆ aluminum ┆ 2.13497907e8 ┆ 2.13497907e8 ┆ 1.0 │\n", + "│ IND ┆ manufacturing ┆ cement ┆ 2.52596928e8 ┆ 2.58232689e8 ┆ 0.978176 │\n", + "│ CHN ┆ manufacturing ┆ chemicals ┆ 2.6414734e8 ┆ 2.8985344e8 ┆ 0.911313 │\n", + "│ CHN ┆ manufacturing ┆ cement ┆ 7.046727e8 ┆ 1.1672e9 ┆ 0.603719 │\n", + "│ CHN ┆ manufacturing ┆ steel ┆ 9.22971074e8 ┆ 1.2870e9 ┆ 0.717133 │\n", + "└──────────────┴───────────────┴───────────┴──────────────────────┴─────────────────────┴──────────┘" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "subs_df" + ] + }, + { + "cell_type": "markdown", + "id": "5080aae9-ae65-4339-bce3-0ef9cf2e9eb6", + "metadata": {}, + "source": [ + "Here is the model that we will assume. Suppose that the true emission of a given sector has a normalized value of 1GT CO2e. Countries have an incentive to under-report the true value, because they may have more commitments to reduce their emissions in the future. Emissions are hard to measure in general, so _undereporting_ is more likeley than _overreporting_. It makes more sense to use a statistical distribution that is more skewed towards lower values, that is, an _asymetrical distribution_.\n", + "Also, emissions should be positive for the industry. Negative values are not likely.\n", + "\n", + "This is why a first example of a model is this shifted-flipped Gamma distribution. We may argue about the exact parameters and the margins of errors, but this should give reasonable results as a start.\n", + "\n", + "Let's assume that this is also the expected shape for the _source emissions_, for similar reasons:\n", + "- we do not know precisely how much we missed\n", + "- for what we are accounting, there is also a margin of error\n", + "\n", + "This model can be refined based on expert knowledge (we may have further information about how much was missed for a sector). " + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "5efc3426-3fbc-4075-ad0b-f8b55ffe42df", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "hovertemplate": "x=%{x}
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def shiftedGamma(mean, size):\n", + " # Picking some sensible parameters\n", + " alpha = 3.0\n", + " beta = 2.0\n", + " # mode = (alpha-1) / beta # Putting the observed value on the mode of the distribution\n", + " mean_ = (alpha) / beta\n", + " # Mapping 10.m -> 0, m -> 1.0\n", + " return mean * (4/3. - (1.0/3) * (1.0 / mean_) * pm.Gamma.dist(alpha=alpha, beta = beta, size=size))\n", + "\n", + "x = shiftedGamma(mean=1.0, size=1)\n", + "xs = np.linspace(0,2,100)\n", + "ys = pm.logp(x, xs).eval()\n", + "px.line(x=xs,y=np.exp(ys))" + ] + }, + { + "cell_type": "markdown", + "id": "02e7cf6f-7dd3-4e76-a7e4-a738d36cb64b", + "metadata": {}, + "source": [ + "Armed with this first model, we define our statistical inference problem: given two observations of the emissions (per country and per source), what is the likely distribution of true emission values?\n", + "\n", + "Here is an implementation of this model in [PyMC](https://www.pymc.io/welcome.html), a popular library for Bayesian analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "0cafae47-3db3-4307-8a15-3510136a4d97", + "metadata": {}, + "outputs": [], + "source": [ + "basic_model = pm.Model()\n", + "\n", + "# The values of the emissions per source and per country\n", + "em_s = np.array(subs_df[EMISSIONS_QUANTITY_S])\n", + "em_ce = np.array(subs_df[EMISSIONS_QUANTITY_CE])\n", + "# start_pt = scipy.stats.gmean([em_s, em_ce], axis=0)\n", + "\n", + "# Given the wide range of scales, normalizing them around the source emissions\n", + "norm_factor = em_s\n", + "em_s_normed = em_s / norm_factor\n", + "em_ce_normed = em_ce / norm_factor\n", + "start_pt_normed = scipy.stats.gmean([em_s_normed, em_ce_normed], axis=0)\n", + "\n", + "\n", + "with basic_model:\n", + " # The initial value: the geometric mean of both estimate\n", + " init_est = start_pt_normed\n", + " # The Gamma distribution is only defined over positive values, so we need to clamp the values of emissions to prevent \n", + " # PyMC from sampling values with zero probability.\n", + " max_bound = np.maximum(em_s_normed, em_ce_normed)\n", + " epsi = pm.TruncatedNormal(\"epsi\", mu = init_est, sigma=1.5 * init_est, lower=max_bound * 0.75, upper=max_bound * 5.0)\n", + " # TODO: maybe just use gamma distributions directly?\n", + " cp = pm.CustomDist(\"cp\", epsi, dist=shiftedGamma, observed=em_ce_normed)\n", + " ip = pm.CustomDist(\"ip\", epsi, dist=shiftedGamma, observed=em_s_normed)\n" + ] + }, + { + "cell_type": "markdown", + "id": "7fec1684-caa8-4609-bef9-9783870a843b", + "metadata": {}, + "source": [ + "We run the sampler with 4 chains. The default parameters should work out of the box for such a simple model." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "37769cf0-166e-4fc1-a800-512741914db3", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Auto-assigning NUTS sampler...\n", + "Initializing NUTS using jitter+adapt_diag...\n", + "Multiprocess sampling (4 chains in 4 jobs)\n", + "NUTS: [epsi]\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " 100.00% [8000/8000 00:04<00:00 Sampling 4 chains, 0 divergences]\n", + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 4 seconds.\n" + ] + } + ], + "source": [ + "num_chains = 4\n", + "with basic_model:\n", + " idata = pm.sample(chains=num_chains)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "5a8acebe-95f8-4073-8d6a-92f17dc8f413", + "metadata": {}, + "outputs": [], + "source": [ + "# Not plotting, too many variables to plot\n", + "# az.plot_trace(idata, combined=True);" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "0ae56fa0-50f6-47c4-99b2-9fded22e9737", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meansdhdi_3%hdi_97%mcse_meanmcse_sdess_bulkess_tailr_hatmedian
epsi[0]0.960.130.791.200.00.09215.212807.001.000.93
epsi[1]0.960.130.791.190.00.09870.832632.551.000.93
epsi[2]0.960.150.791.200.00.09176.202474.241.010.93
epsi[3]0.960.140.781.200.00.09872.172365.211.000.93
epsi[4]0.960.130.781.190.00.07466.172712.101.000.93
.................................
epsi[381]0.970.140.781.210.00.010382.082563.771.000.93
epsi[382]0.970.130.791.200.00.09592.342553.111.000.94
epsi[383]1.030.140.841.290.00.09779.912293.651.000.99
epsi[384]1.530.231.251.910.00.08799.632413.621.001.47
epsi[385]1.280.181.051.570.00.09783.892564.911.001.24
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386 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk \\\n", + "epsi[0] 0.96 0.13 0.79 1.20 0.0 0.0 9215.21 \n", + "epsi[1] 0.96 0.13 0.79 1.19 0.0 0.0 9870.83 \n", + "epsi[2] 0.96 0.15 0.79 1.20 0.0 0.0 9176.20 \n", + "epsi[3] 0.96 0.14 0.78 1.20 0.0 0.0 9872.17 \n", + "epsi[4] 0.96 0.13 0.78 1.19 0.0 0.0 7466.17 \n", + "... ... ... ... ... ... ... ... \n", + "epsi[381] 0.97 0.14 0.78 1.21 0.0 0.0 10382.08 \n", + "epsi[382] 0.97 0.13 0.79 1.20 0.0 0.0 9592.34 \n", + "epsi[383] 1.03 0.14 0.84 1.29 0.0 0.0 9779.91 \n", + "epsi[384] 1.53 0.23 1.25 1.91 0.0 0.0 8799.63 \n", + "epsi[385] 1.28 0.18 1.05 1.57 0.0 0.0 9783.89 \n", + "\n", + " ess_tail r_hat median \n", + "epsi[0] 2807.00 1.00 0.93 \n", + "epsi[1] 2632.55 1.00 0.93 \n", + "epsi[2] 2474.24 1.01 0.93 \n", + "epsi[3] 2365.21 1.00 0.93 \n", + "epsi[4] 2712.10 1.00 0.93 \n", + "... ... ... ... \n", + "epsi[381] 2563.77 1.00 0.93 \n", + "epsi[382] 2553.11 1.00 0.94 \n", + "epsi[383] 2293.65 1.00 0.99 \n", + "epsi[384] 2413.62 1.00 1.47 \n", + "epsi[385] 2564.91 1.00 1.24 \n", + "\n", + "[386 rows x 10 columns]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "summ = az.summary(idata, round_to=2,stat_funcs={\"median\":lambda z:np.percentile(z,50)})\n", + "summ" + ] + }, + { + "cell_type": "markdown", + "id": "e10d87d9-6ed3-44b8-b1ec-8ccd8c5a50ae", + "metadata": {}, + "source": [ + "All the inferred values are now aggregated back. The Bayesian analysis also can tell us if the observations are _likely_ to be\n", + "close to the true value, or if they are _inconsistent_ with the inferred range of possible emissions values. If an observed value for the source or the country emissions is marked as invalid, we can conclude that this combination is not consistent and that we should refine these values by better analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "9579e623-a7fa-43fe-8d66-d795b59d1383", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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indexmeansdhdi_3%hdi_97%mcse_meanmcse_sdess_bulkess_tailr_hat...s_validce_validvalidsceiso3_countryct_packagect_fileemissions_quantity_semissions_quantity_ce
0epsi[0]2.769600e+033.750500e+022.279150e+033.462000e+030.00.09215.212807.001.00...TrueTrueTrue2885.02.885000e+03CHLmanufacturingchemicals2885.02.885000e+03
1epsi[1]3.594240e+034.867200e+022.957760e+034.455360e+030.00.09870.832632.551.00...TrueTrueTrue3744.03.744000e+03SYRmanufacturingsteel3744.03.744000e+03
2epsi[2]6.140160e+039.594000e+025.052840e+037.675200e+030.00.09176.202474.241.01...TrueTrueTrue6396.06.396000e+03VENmanufacturingchemicals6396.06.396000e+03
3epsi[3]6.301440e+039.189600e+025.119920e+037.876800e+030.00.09872.172365.211.00...TrueTrueTrue6564.06.564000e+03VENmanufacturingsteel6564.06.564000e+03
4epsi[4]1.289088e+041.745640e+031.047384e+041.597932e+040.00.07466.172712.101.00...TrueTrueTrue13428.01.342800e+04TCDmanufacturingchemicals13428.01.342800e+04
..................................................................
381epsi[381]2.070930e+082.988971e+071.665284e+082.583325e+080.00.010382.082563.771.00...TrueTrueTrue213497907.02.134979e+08CHNmanufacturingaluminum213497907.02.134979e+08
382epsi[382]2.450190e+083.283760e+071.995516e+083.031163e+080.00.09592.342553.111.00...TrueTrueTrue252596928.02.582327e+08INDmanufacturingcement252596928.02.582327e+08
383epsi[383]2.720718e+083.698063e+072.218838e+083.407501e+080.00.09779.912293.651.00...TrueTrueTrue264147340.02.898534e+08CHNmanufacturingchemicals264147340.02.898534e+08
384epsi[384]1.078149e+091.620747e+088.808409e+081.345925e+090.00.08799.632413.621.00...FalseTrueFalse704672700.01.167219e+09CHNmanufacturingcement704672700.01.167219e+09
385epsi[385]1.181403e+091.661348e+089.691196e+081.449065e+090.00.09783.892564.911.00...FalseTrueFalse922971074.01.287029e+09CHNmanufacturingsteel922971074.01.287029e+09
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386 rows × 21 columns

\n", + "
" + ], + "text/plain": [ + " index mean sd hdi_3% hdi_97% \\\n", + "0 epsi[0] 2.769600e+03 3.750500e+02 2.279150e+03 3.462000e+03 \n", + "1 epsi[1] 3.594240e+03 4.867200e+02 2.957760e+03 4.455360e+03 \n", + "2 epsi[2] 6.140160e+03 9.594000e+02 5.052840e+03 7.675200e+03 \n", + "3 epsi[3] 6.301440e+03 9.189600e+02 5.119920e+03 7.876800e+03 \n", + "4 epsi[4] 1.289088e+04 1.745640e+03 1.047384e+04 1.597932e+04 \n", + ".. ... ... ... ... ... \n", + "381 epsi[381] 2.070930e+08 2.988971e+07 1.665284e+08 2.583325e+08 \n", + "382 epsi[382] 2.450190e+08 3.283760e+07 1.995516e+08 3.031163e+08 \n", + "383 epsi[383] 2.720718e+08 3.698063e+07 2.218838e+08 3.407501e+08 \n", + "384 epsi[384] 1.078149e+09 1.620747e+08 8.808409e+08 1.345925e+09 \n", + "385 epsi[385] 1.181403e+09 1.661348e+08 9.691196e+08 1.449065e+09 \n", + "\n", + " mcse_mean mcse_sd ess_bulk ess_tail r_hat ... s_valid ce_valid \\\n", + "0 0.0 0.0 9215.21 2807.00 1.00 ... True True \n", + "1 0.0 0.0 9870.83 2632.55 1.00 ... True True \n", + "2 0.0 0.0 9176.20 2474.24 1.01 ... True True \n", + "3 0.0 0.0 9872.17 2365.21 1.00 ... True True \n", + "4 0.0 0.0 7466.17 2712.10 1.00 ... True True \n", + ".. ... ... ... ... ... ... ... ... \n", + "381 0.0 0.0 10382.08 2563.77 1.00 ... True True \n", + "382 0.0 0.0 9592.34 2553.11 1.00 ... True True \n", + "383 0.0 0.0 9779.91 2293.65 1.00 ... True True \n", + "384 0.0 0.0 8799.63 2413.62 1.00 ... False True \n", + "385 0.0 0.0 9783.89 2564.91 1.00 ... False True \n", + "\n", + " valid s ce iso3_country ct_package ct_file \\\n", + "0 True 2885.0 2.885000e+03 CHL manufacturing chemicals \n", + "1 True 3744.0 3.744000e+03 SYR manufacturing steel \n", + "2 True 6396.0 6.396000e+03 VEN manufacturing chemicals \n", + "3 True 6564.0 6.564000e+03 VEN manufacturing steel \n", + "4 True 13428.0 1.342800e+04 TCD manufacturing chemicals \n", + ".. ... ... ... ... ... ... \n", + "381 True 213497907.0 2.134979e+08 CHN manufacturing aluminum \n", + "382 True 252596928.0 2.582327e+08 IND manufacturing cement \n", + "383 True 264147340.0 2.898534e+08 CHN manufacturing chemicals \n", + "384 False 704672700.0 1.167219e+09 CHN manufacturing cement \n", + "385 False 922971074.0 1.287029e+09 CHN manufacturing steel \n", + "\n", + " emissions_quantity_s emissions_quantity_ce \n", + "0 2885.0 2.885000e+03 \n", + "1 3744.0 3.744000e+03 \n", + "2 6396.0 6.396000e+03 \n", + "3 6564.0 6.564000e+03 \n", + "4 13428.0 1.342800e+04 \n", + ".. ... ... \n", + "381 213497907.0 2.134979e+08 \n", + "382 252596928.0 2.582327e+08 \n", + "383 264147340.0 2.898534e+08 \n", + "384 704672700.0 1.167219e+09 \n", + "385 922971074.0 1.287029e+09 \n", + "\n", + "[386 rows x 21 columns]" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "summ = summ.reset_index()\n", + "HDI_LOW = \"hdi_3%\"\n", + "HDI_HIGH = \"hdi_97%\"\n", + "summ[\"mean\"] *= norm_factor\n", + "summ[\"median\"] *= norm_factor\n", + "summ[\"sd\"] *= norm_factor\n", + "summ[HDI_LOW] *= norm_factor\n", + "summ[HDI_HIGH] *= norm_factor\n", + "summ[\"s_valid\"] = (summ[HDI_LOW] < em_s) & (em_s < summ[HDI_HIGH])\n", + "summ[\"ce_valid\"] = (summ[HDI_LOW] < em_ce) & (em_ce < summ[HDI_HIGH])\n", + "summ[\"valid\"] = summ[\"s_valid\"] & summ[\"ce_valid\"]\n", + "summ[\"s\"] = em_s\n", + "summ[\"ce\"] = em_ce\n", + "summ[ISO3_COUNTRY] = subs_df[ISO3_COUNTRY]\n", + "summ[CT_PACKAGE] = subs_df[CT_PACKAGE]\n", + "summ[CT_FILE] = subs_df[CT_FILE]\n", + "summ[EMISSIONS_QUANTITY_S]=subs_df[EMISSIONS_QUANTITY_S]\n", + "summ[EMISSIONS_QUANTITY_CE]=subs_df[EMISSIONS_QUANTITY_CE]\n", + "summ" + ] + }, + { + "cell_type": "markdown", + "id": "25474f6c-86c7-4427-a5d0-ccf596cf3c0c", + "metadata": {}, + "source": [ + "Here are all the estimated ranges of emission values for the considered sectors.\n", + "\n", + "Looking at the top sector (Chinese manufacturing), our Bayesian analysis inferred an _median emission_ of 1.14BT CO2e, and the true value being very likely between 0.96BT and 1.4BT (94% confidence interval). However, the value of the source emission is 0.9BT. That value is likely to be inaccurate and we should explore further if we can refine it.\n", + "\n", + "You should zoom and hover over the data points to see how much the values diverge.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "3d290e31-b9da-4fa7-9175-daae67cf00d2", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "customdata": [ + [ + "manufacturing", + "CHL", + "chemicals", + 2885, + 2885 + ], + [ + "manufacturing", + "SYR", + "steel", + 3744, + 3744 + ], + [ + "manufacturing", + "VEN", + "chemicals", + 6396, + 6396 + ], + [ + "manufacturing", + "VEN", + "steel", + 6564, + 6564 + ], + [ + "manufacturing", + "TCD", + "chemicals", + 13428, + 13428 + ], + [ + "manufacturing", + "EST", + "pulp-and-paper", + 16614, + 16614 + ], + [ + "manufacturing", + "ETH", + "chemicals", + 21000, + 21000 + ], + [ + "manufacturing", + "AFG", + "cement", + 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "px.scatter(\n", + " summ,y=\"median\",\n", + " color=\"valid\",\n", + " log_y=True,\n", + " error_y = summ[HDI_HIGH]-summ[\"median\"],\n", + " error_y_minus=summ[\"median\"]-summ[HDI_LOW],\n", + " hover_data=[CT_PACKAGE,ISO3_COUNTRY,CT_FILE,EMISSIONS_QUANTITY_S,EMISSIONS_QUANTITY_CE]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "ac5aeca8-947e-456e-9bb6-afd0b8408fdc", + "metadata": {}, + "source": [ + "This is another visualization that puts all the data in the same plot. You can see how this simple model shines for estimating conservative figures: between two wildly different values, it will lean towards the higher one, and when they are close, it will average them out." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "28643385-f266-4951-9f6b-b0398092860c", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "error_y": { + "array": [ + 778.9499999999998, + 973.4399999999996, + 1726.9199999999992, + 1772.2799999999988, + 3491.279999999999, + 4153.5, + 5670, + 6000, + 6535.079999999998, + 6135.359999999997, + 8329.499999999996, + 8533.359372499996, + 11765.25, + 13014.399999999994, + 12649.769999999997, + 12508.079999999994, + 12099, + 15604.159999999989, + 16852.049999999996, + 17055.219999999987, + 18379.65999999999, + 19607.039999999994, + 22131.899999999994, + 23060.749999999985, + 23244.499999999985, + 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JKV6UUWkLpHjRhl45McWLMiptgRQv2tCHZGKKF5PDSvFiEiCbKxGgeFHCpDWI4kUrfqXkFC9KmLQGUbxoxa+cnOJFGZW2QIoXbeiVE1O8KKPSFkjxog19SCameDE5rBQvJgGyuRIBihclTFqDKF604ldKTvGihElrEMWLVvzKySlelFFpC6R40YZeOTHFizIqbYEUL9rQh2RiiheTw0rxYhIgmysRoHhRwqQ1iOJFK36l5BQvSpi0BlG8aMWvnJziRRmVtkCKF23olRNTvCij0hZI8aINfUgmpngxOawULyYBsrkSAYoXJUxagyhetOJXSk7xooRJaxDFi1b8yskpXpRRaQukeNGGXjkxxYsaqi2VuYi3RiA9LFatgR+jKF78CNOHU9XUODDpstvw/ksPITEh8OPuQ1d9CqV48QmXdzDFi0mAbK5EoN2IF4vA4VRCEnRBFC9BNyReHaJ4Cf4xongJ/jGSPaR4Cf5xongJ/jGieGl4jLJzgIWLbMiOzcXsQUuRH1lkBA480gMzt0xEaqoTUyY5AjLAFC8BwWwk+XTpKpwzYWRtwsXL12DCGcNhtcqHA/8c36zZjIH9eiApIc4/J/TxLBQvPgKrH07xYhIgmysRaDfiRYlGcAZRvATnuNTtFcVL8I8RxUvwjxHFS9sYI4qX4B8nneLFKvAERl2oj4NbuGSG52LuCcuRl5wrGns+dI/4fiTOLR2Ea66uUT+xichQFi+lZcD6TQ7IP4cOtqJDsglQJpsWFZdi2q/vw5L/PWXyTE03v+zGv+KRO3+D3t3TWjVPYyeneDGJneLFJEA2VyJA8aKESWsQxYtW/ErJKV6UMGkNonjRil85OWe8KKPSFkjxog29cmKd4kW5kwEM3JNpwatv2PC/6e+iOFbOcvGe6TCoMg2vx09CWmpgOhaq4kXKlr/8vQq5ecc5zrrchtEjpJIzf0iRcv8Tr2DVD1uREB+LO2++HGedPhRVVdV46Jk3sHzVBuPzk0/sg2f+cjOuuuVRbNuxF6mdkjH4hF7Ga4PHz8Lyec8Zs1N+fevfMf6MYZg9bwkOH8nH+NHDcOkF4/Hgk6/ikPj7aRkD8fQDNyI8PAwbt+7CYy/MRtaBQ4iJisSdv5sp4jNE7Gv44LOvkJKUgLAwGxbNfsKYTfPCq/Mw55NlcDqduOKis3H9leeZB9DIGSheTKKleDEJkM2VCFC8KGHSGkTxohW/UnKKFyVMWoMoXrTiV05O8aKMSlsgxYs29MqJKV48UZWVAwtyDuF3WCC+INede4uXU37uh49OHa3M2GxgqIqXV96uwTffec55iooCnv9buFlkRvu7Hn0JNpsVf7ltFn7cmYVf/+nvWPj237Fm4094Y84i/PfpO2ARw7sr8yAG9Ek3JMkVNz9iiBb3UV+8FJWU4qUnb4fT4cTF196P+LgY/OeJ2xAdFWG0/fXl5xhLlQ7mHEFBYbGxpGjpyrV47Lm3sXTO08Zpx138ByO3e8bLvAUr8NYHi/HKM3fA4XDg8hsfxj2/vwJnnDbYLxzqn4TixSRWiheTANlciQDFixImrUEUL1rxKyWneFHCpDWI4kUrfuXkFC/KqLQFUrxoQ6+cmOLFG9W3YgrGxUUfH/uCt3z5/Xe/wJ8v6arM2GxgqIqXvz9Xje27vIsq/u2BcNNLjmRh3FOnXI8PX30E3bt2MoZg5k0P46oZk9AzPRXX3vYE7v3DVaJ+yzBDzshDRbzIGS8zp0804v/0l3+gf+/02tkpjz3/NpIT471mq5RXVGL4pOuw6YtXjdkt9cXLtbc9icnjTsNF55xpnPfZl95HcUmZ6N+VZm+dBttTvJjESvFiEiCbKxGgeFHCpDWI4kUrfqXkFC9KmLQGUbxoxa+cnOJFGZW2QIoXbeiVE1O8eKOSy40uzlmInNTsY190yYHJOw/g7pUbkF18AbYPvpo1XpTvsoYDG5zxEilmvDxufsbL0cISnH7+TWJJT3xt8orKKtxx02WYPvVMrN20Ay+8MhcHD+Xijpsvw7jTM5TEyyXnn4VJZ51mnPOOh/+NYYP7GcuN5PHEP941Zr7cNGsavv5+szGr5qiY9SKPTT/uwYal/0WYzeYlXi6cdS8O/ZxnLFGSR3V1DcaJZUmyDkxrHBQvJqlSvJgEyOZKBChelDBpDaJ40YpfKTnFixImrUEUL1rxKyeneFFGpS2Q4kUbeuXEFC+eqGRx3U8X2LDzcCU2DFsMR/w2JIgZC3eu3IQz9h0ygnfZh2DBsGcoXpTvsoYDjRovj4saL/nHv+6vGi9yxsvwyddh8btPomNKYqM9XbPhJ9xw59Mi7ikUipowV9z8cJNLjS45f5wQL6ca52tMvMgaLXJWy6vP3okhon6MrDUz8twba8XL+Bl/xMtP/bl2qZGsHTNdzHapu5uSSbRNNqd4MUmX4sUkQDZXIkDxooRJaxDFi1b8SskpXpQwaQ2ieNGKXzk5xYsyKm2BFC/a0CsnpnjxROUurptWuROzCu5Dco0wMfWO6pFno/Lq25UZmw0M1aVGkouUL+s2unY1yjjZv7sa3fnof0SFHouxZCcqMgI7Mw+gW1pHIXqOwh4ejs4dk5B/tAjnXXU35v73r4iwh2Ps9Fuw6B2XrJHLgurXeFERL+dPGo3pYnek5fOeF3ntePejL/BXUczXPeNl2jX3iuVI5xsCxyKKzMz9bDnenrsEzz98C7qkdkCOmP0ia8ikdU4xe+s02J7ixSRWiheTANlciQDFixImrUEUL1rxKyWneFHCpDWI4kUrfuXkFC/KqLQFUrxoQ6+cmOLFE5UsrpuTY0H/f16O8MLDor6uWGYkK7AeO2oiY1B5z7/g7BCgLY1E3lAWL8o3agsCZZ0UWXdFFreVuwX169UNLz76B+zaewD3/O1lMROlDDHRkfjVpZNx2YUTjAxyudCHi1ZiUP+eRtHclogXudTo7y++g8+/+h6dOiRhyvgReOP9z7Hg7ceNpUYLvliNx8XXZZ/ka1IKvTz7U2O3JNnn1I7J+Mvts8Qypv4tuOrmm1C8NM+oyQiKF5MA2VyJAMWLEiatQRQvWvErJad4UcKkNYjiRSt+5eQUL8qotAVSvGhDr5yY4sUblXX7ekQ+U2dGi5QvYuaEo1tvVPz2LwGVLrJ3FC/KtzMDFQhQvChAaiqE4sUkQDZXIkDxooRJaxDFi1b8SskpXpQwaQ2ieNGKXzk5xYsyKm2BFC/a0CsnpnhpQLzs24nIR2/w+kL1+GmonHGjMlt/BVK8+IskzyMJULyYvA8oXkwCZHMlAhQvSpi0BlG8aMWvlJziRQmT1iCKF634lZNTvCij0hZI8aINvXJiipeGUUU+8ydYt2/0+GL53f+EI72vMlt/BVK8+Iskz0Px4od7oHXFi0P00LW/eWsdHRMiIH/Q/bmgHFU13vu5t1Zentc3AhQvvvHSEU3xooO6bzkpXnzjpSOa4kUHdd9zUrz4zizQLSheAk3c93wUL40wKy2C/dM3Yd2/C05R16Xq3Ku0SBfZO4oX3+9rtmicAGe8mLw7Wle8mOycQnOKFwVIQRBC8RIEg9BMFyhegn+MKF6Cf4woXoJ/jGQPKV6Cf5woXoJ/jPwpXlyVUIL7eOV1GzL3WrB2yFqsEx/ySM5LxpnfjEVKXgpmXVWDXj1b4ZfAEkwLT0vxEtz3VFvrHcWLyRGjeDEJkM2VCFC8KGHSGkTxohW/UnKKFyVMWoMoXrTiV05O8aKMSlsgxYs29MqJ/SlelJNqDJTi5SvHXiwZt8SjF7HFcbh07qWtJ15MXDPFiwl4bOpFgOLF5E1B8WISIJsrEaB4UcKkNYjiRSt+peQUL0qYtAZRvGjFr5yc4kUZlbZAihdt6JUTtzfxIsFcvm8pvqrZ58Xo8y7nYZA9RZldoAIpXgJFun3koXgxOc4ULyYBsrkSAYoXJUxagyhetOJXSk7xooRJaxDFi1b8yskpXpRRaQukeNGGXjlxexQv09d+jdXJO7wYLYqfgZOSY5TZBSqQ4iVQpNtHHooXk+NM8WISIJsrEaB4UcKkNYjiRSt+peQUL0qYtAZRvGjFr5yc4kUZlbZAihdt6JUTB694ab3NPZ6Yn49nT/rIg1FqThoeyJ2CuFhgeewOZIXnoUN1LMaU9EWMIwI9ezhbp/aLwkhRvChAYogyAYoXZVQNB1K8mATI5koEKF6UMGkNonjRil8pOcWLEiatQRQvWvErJ6d4UUalLZDiRRt65cTBK16UL8GnQKO4bqYF2anZRoFdeaTkJyNj/TCjMvCXY77Ega77a88pC+9O/fwcTBoVjvFjpQwK/EHxEnjmoZyR4sXk6FK8mATI5koEKF6UMGkNonjRil8pOcWLEiatQRQvWvErJ6d4UUalLZDiRRt65cTtUbxsyi1GUUwxuhxKMzg5xW5DOf0X4bNR3nVf5Ndn5o/ADUkncsaL8l3FwGAmQPFicnQoXkwCZHMlAhQvSpi0BlG8aMWvlJziRQmT1iCKF634lZNTvCij0hZI8aINvXLi9iJeFiyyYs+RSswdsALbOuw1+CSUxeHcVRMQUXIEr5y7slFm1+6Pw4NnXKTM1N+BoTzjxVlShKrvV8JZWoTwU8bA2sklw3i0HgGKF5NsKV5MAmRzJQIUL0qYtAZRvGjFr5Sc4kUJk9Ygihet+JWTU7woo9IWSPGiDb1y4vYiXuQSo7mJ67Du2PIiN6DYMhuslnIURoY3yuzva6yYefFVykz9HRiq4kVKl6I/z4Lj55xaZNE33g37WVP9gvDN9z/H63MWobS0HGmdU/DsQzcjvUsn7M7Kxl+feR0/7shCYkIc/njdDJw99hQj54zrHsSt4u+jThlk/P1/H32BtZt24PF7r8e/3vgY0VER2LI9E4uWfY+3XrgH6Wmd8JA41/JVG2C3h+P2G36JCyefgR179uO+x/+LzP2H0Lt7Gh67+zr06NbZL9dl9iRtV7yIqWlyPaDug+JF9wi0j/wUL8E/zhQvwT9GFC/BP0YUL8E/RrKHFC/BP04UL8E/Ru1FvGSLZ/srCxZhW2R2nUFxP8jVfaDzfLj77ZptmHxgIjpccDaXGvn5di598RFUfrXA46yW6FgkvLbQdKajhSWYeOmfsPjdJ5EQH4Ptu/ejb8+ucIr/zrvqbvz6sqmYPvVMQ6Jcf/uTeFNIlD49ujQrXt76YDFuvmYazj/7dETY7fjzw/+CxWLB/bdejaqqarFszYkkIXOmXnEHfnvV+Zg2ZQxkm0+XrsI7/7jP9HX54wRtV7z44+r9cA6KFz9A5CmaJUDx0iwi7QEUL9qHoNkOULw0i0h7AMWL9iFQ6gDFixImrUEUL1rxKyVvL+JFwpjwwxf4MSVLiUuvvCK8/vFyWAoG4bXkh3GWKKzL4rpK6JSDih+8GdVb13vFx78wx/SSo5oaByZccitmTp9ofERHRRp5Nm3bjT8++CKW/O+p2rz3ipkpXVI74MarL2hWvHyzZjPeeO5uo63MMXzStfj49cfQvWun2vOt37ITt4ocX8x5xnhNCpmMs6/Fig+fM6SM7oPixeQIULyYBMjmSgQoXpQwaQ2ieNGKXyk5xYsSJq1BFC9a8Ssnp3hRRqUtkOJFG3rlxO1JvDzyQQH+MfzDRtgcn+ly2bocTP0+BVkYiZoBQ42ZLr24nbTyPaUa2NCMF0THIPG1RaqnaDIu+1Aunn9lrlgGtBFXXzIJv7n8HCxduRavvPMZZteZffLcfz9AYVEp7v3DlV7i5V2x1GhdnaVGh3MLcP8fXcvO5Kya08+/CesXv4zw8LDavixevga3/eWfxkwb91FWXoH3X3ooKJYbUbyYvL0oXkwCZHMlAhQvSpi0BlG8aMWvlJziRQmT1iCKF634lZNTvCij0hZI8dJK6GWZA+kJ/HC0F/Eia7wU7MzBJNttmDsoFVmJsRgiHswfO2OoB8WuR8sw48vLRe2PZNisQMYQBzKG+gl2C8crpGu83P4rOI4cqk/3jIQAACAASURBVCXjzxov7pNmH87Dtbc9gT9eOwPJSXGGFFk65+nanPf87WX0EnVYpJj55Q0P4eZZ03DGaYONr7/46jxkHThcW+PlSN5RQ9DIo7qmBsPPvg6fvf04uooZM+5j7abtkLNoPnvr8RaOeOs2o3gxyZfixSRANlciQPGihElrEMWLVvxKySlelDBpDaJ40YpfOTnFizIqbYEUL9rQKycOdfHyxVdWoxznnJwsHOnwGSzhebh8425ctmWPwWhleif87YyTsalzEk7eX4UT1pwLZ0UfrUuL6g9eqIoXeZ2uXY1WiD+LEX6q/3Y1KhEFdfcdPIwT+nZHVXUNbrjzaaPeyqSzTsW5V96FWZdOxozzxmHrjkxcJ2q8vPvPB4zlQnc8/G9j2dHvf3MRiopLcdmNf8Wg/j0bFC+y/7fc9xxioqJwn5gFI+u75B8tQmqnZEydeQdm/XKKyHEWHGJJ0nZRbPekAb2U35etGUjxYpIuxYtJgGyuRIDiRQmT1iCKF634lZJTvChh0hpE8aIVv3JyihdlVNoCKV60oVdOHOri5f6HwrA3PRNLxi3xYHLHyo24U3yIyqjYbh+O9+L/hPxw11bGUtTorOnSnsSL8o3aYKBDvCqmJTVwyGVAUqjsyz4siuCG46xRQ3GPmKkSZrMZuxo98MSr+GlXlpAkKfjT9Zdg7Kghxlky9+Xgzkf+jfKKKiSJWVEjMk7EHhHv3tWo7owXGZ9XUIQHnnwVq37YYpz7rltmisK7o2t3Ttr84x5jGdL40cPw8B2/Nne5fmodEuKltKwcdz36EnLzC43tpdyHtF+Pv/gOPlq4EmFhNlHh+AKjyI88Co4W485H/40fNm5Hx5REPHT7NThlyADja+dceScKCoux7IP/Q7ho5z6OFpVg7LRbcFrGQPzniduMlyle/HQn8jRNEqB4Cf4bhOIl+MeI4iX4x4jiJfjHSPaQ4iX4x4niJfjHKNTFi5zx8mDCK9iV6DkWCaLmRub/vQ9nVAzKnm6s7ktwjF8oz3gJDsLtqxdtXrzI4j033f0seottqHLEOrK64mXeghWYPW+pkCR/Mgr3XHXLo3jpydvRv3c3Q9RERoTjjpsvxzdrtuChp1/HkveeMoyZFC9WYWFv/e0lGHd6Ru0dIfcTl9tSyf3IKV7a1xtF99VSvOgegebzU7w0z0h3BMWL7hFoPj/FS/OMgiGC4iUYRqHpPlC8BP8Yhbp4kSNw2sZ/4UC8a1ebukfecx+i8qrbUTN0dFAPFMVLUA9Pm+tcmxcvcpqR3DoqKsKOF1/70EO83HDnM5gy/jRj2pE8nv73e3CIWTByWtNpU28QW1A9ijSxFkwesqCP3MrqzJFDDPEyedxpxpSnpx64sXZQZ970MEYNH4SN23ZRvLS5W71td5jiJfjHj+Il+MeI4iX4x4jiJfjHSPaQ4iX4x4niJfjHqD2Il7vmPYY3MlzLiNzH1B378HLGtXB2SA36QaJ4CfohalMdbPPixU37WzFrpb54mSKK6zxx/29rC+p8tOhrLFnxA+77w1WYesWfsWbhf2oHS1ZAHtAnHVdefLYhXv52z/W4TlRhXvLe04iJjjSqKt9y73O4/srzIGfScMZLm7rP23xnKV6CfwgpXoJ/jChegn+MKF6Cf4woXtrGGFG8BP84hap42ZMpK7UA7ywvQUHEHKzrnYetHZOM10ZnHcItixOwo+9NmHV1TdAPEsVL0A9Rm+pgSIuX8TP+iJef+jN6i22q5LF0xVq89t5CPHLnb3DFzQ9j+bznagfrseffRmxMFH53zXRDvDz/yO/xvNhbXM6AkZWY5ZZWUVERSO2Ygg8XHhcvJeXVbWrA63c2KsJmLKsqq6gWs4Ha9KWEdOdjIsPQ1u+1kB4gcXGR4TZUiurpDr6Rgnaow23ih0Hx/a6qWhaF49FaBGrEe0D+sNqSQ/57ZA+3orwy+H8gb8n1hUqb6IgwlIqfG3gEL4EI8T6qrnFCvh95BCeBMPFvklV8r6ysCq1/k35/hxPZnbNFUd3FqLRXGvDjyyvxwvw1SMgehkVxV6PCGof/e7xl/04EcjRlDyPFs1JZhfl/k+TP8jzaN4GQFi/TrrkXfxVVjN1bSH38+deYv/hbMQvmBkwQUqb+jJce3Trj2pnn1oqXTFFJ+e15S/BfIW/k7JnXnr3TKMZbV7wUFLu+obTVIy463PgBuai0iv84B/EgJsba0dbvtSDG65euydkU8mFR/qDLIzgJRNhtxo4JfKhv3fGRhe0tQqC05LCJB5FoMU5FZXyobwm/QLVJiLGjsKQS/G4XKOK+55EPeZVCMlM0+84uUC3sYVZRW9IaEhKzrExsOJLjIvf4d3sx/8SvUGav8kDZP7srLtk4BRee6/rO0ad3oEi3PI8UY7HivVQonpPMHoni+6bxQwiPdksgpMXLH+5/ARPOGIbzzj7dGOBn/jNHbFFVibt+NxOjL7gZH7z8kJjB4qrxIvcK/81l52DCmGG14iU9rSPOuvgPuF/sD/7eJ8sMAfPZ0tUe4oW7GrXb905AL5xLjQKKu0XJuNSoRdgC2ohLjQKKu0XJuNSoRdgC3og1XgKO3OeEXGrkM7KANwiFpUZiY1nk5FiMj/e+KcG6k9eKZUQ7GmV5oOevAs7ZTEIuNTJDj23rEwhp8fL5V2vw8uz5+M/fb0NhcYnY1egxPP3gjRg2uD8e+b83jRked9x0GWR9mLsfe8nY1Sg6KrJWvMglSg8++RoWLfsOdwpZc8Gk0RQvfA9pIUDxogW7T0kpXnzCpSWY4kULdp+SUrz4hEtbMMWLNvTKiSlelFFpC2zL4qWucFnwuRXbh3yC7wYeQYW98SU5k3dk47+/uEsb75YkpnhpCTW2aYxASIsXOd35iX+8iw8+Wy7WjIfh12JGy68unWywOFpUgjsf+Q9Wr92KVLGz0b1/uBKnn3KS8TV3jRcpXtZs+AnX//kprPjwOUPKcMYL30w6CFC86KDuW06KF9946YimeNFB3becFC++8dIVTfGii7x6XooXdVa6ItuSeJEFczP3WpAtZrbsLluAg8lZ2J9UgcIoYE9yFKqtVoFRLiFqeC1NvFhx8Pr7P6LjzGfQq2fbWaRI8aLr3RGaeUNGvOgaHi410kW+feWleAn+8aZ4Cf4xongJ/jGieAn+MZI9pHgJ/nFqb+LlldddNbz2JGRjW4e9xgANPNIDvY66NtgIxh102pJ4+eIrK5aJj59G/x9W9omuI1jqyxbvv4/LzMarH67EvMj7sDl6DB66v+3U8KJ4Cf7vdao9/P19z2P61DMxdtQQ1SZ+j6N4MYmU4sUkQDZXIkDxooRJaxDFi1b8SskpXpQwaQ2ieNGKXzk5xYsyKm2B7U283P9QGPamZ4qddJZ4MJ/45UT02NczKB/225J4kTNePto6D0+cWNDAPV1XtniKF7l99D8+3IJlKaLsQ7cMo+01bWAbafdFUrxo+xbmU+Jv1mzGwH49kJQQ12g7uYqld48uSE5sPManpC0IpnhpAbS6TSheTAJkcyUCFC9KmLQGUbxoxa+UnOJFCZPWIIoXrfiVk1O8KKPSFtjexIsUA1dWf4Q9YXkezHtVJ+PNsAuCcnlLS8TLvupipIfF+u2+ktzksfHnEnwXsRc1FgeKrBVwVNgwIrcf8n+MR36+WETUaRGWnfoTdqfI2S6NLylydcyJaLHL4/tzvsDQA6X4R8qziOjbp00Jl/YgXgpqKvBRQSbknxck9kJPuz4hYfaGlpvkPHLnbyDLhATzQfFicnQoXkwCZHMlAhQvSpi0BlG8aMWvlJziRQmT1iCKF634lZNTvCij0hbY3sSLBN0187UGeQfrTjoq4iVbbNG8cJEN2bG5mD1oKfIji4xrHL93GMZnZiA11YkpkxzN3mdS2OwqLYY9Lw62vEoc2NcBVY5cbNtxFDtO+B7fDixGRbhLmhyv0+JEp+IKHI6NPPa6/HrT+yFHVNfgjq834qp1e7BeCK9NHc9D35GpYiaCExlD205tl1AXL1K2ZGydg8xK1/0kj1d7jsOvUk5o9l5SCThaWIKHnnkdy1dtgN0ejttv+CUunHwGdmdl46/i9R93ZCFRzE7543UzcPbYU4xTzrjuQdwq/j7qlEHG3//30RdYu2kHHr/3evHndrz09qdI79IR8xd/i3BRu/Xma6ZhxrlnGRvhfPDZV0hJSkBYmA2LZj8hYueL2qwR2LI9U2yS8z3eeuEePPPvObjk/HGYdNapkHVgX3h1HuaIXYvl51dcdDauv/I8I++b73+O1+csQmlpOdI6p+DZh24WeTupXHazMRQvzSJqOoDixSRANlciQPGihElrEMWLVvxKySlelDBpDaJ40YpfOTnFizIqbYFtXbzIUq3N6wRPvKNWfImsdFd9F/fRfV8PfDtmnLZxaCqxFC+lVlHvpKxxmSFnpLz6hg3/m/4uimOLPU435uszcXZ1v0ZnkrjrsmweuBmrT10l2rqlihMW8anTIvM2NXuloa95vyZlS3pBBYbuq8bZG+2wl6RifcIkpHSLRZqiGArKARKdCtWlRr/K/AKv5/7kgT3RZkf+0F/7ZSj+9Jd/wCLur/tvvRpVVdWG3EhMiMV5V90tNruZatRakVLk+tufxJtCivQRS4CaEy9X/u5RYzOcS84bh6079uJXv3+sdvObcRf/Af99+o7aGS//euNjvPXBYkPOnH/26Yiw23GdyOUWL/MWrDC+/sozd8DhcODyGx/GPb+/AoNP6I2Jl/4Ji999EgnxMdi+ez/69uwKm01+RzJ/ULyYZEjxYhIgmysRoHhRwqQ1iOJFK36l5BQvSpi0BlG8aMWvnJziRRmVtsC2Ll58BSclw1fbSzB3+GLkJbuWGyXnJeOSDRNxRu9YjBvrq8bxtQdq8bIIcHlYBeYOWFFbBLhXQRou3zIBUdURXkWA5bbNK3LyMAsfeyXIKOmOBysmYHXyDizATuPrZ6I7un8/GHkCQWnNbqztvQRfnWA71va4eGlu5orK1VyxLB4RWZeIh+rj0endnejb29lmZ7jUv+5QFS9n/fQRvio+6DXMewZfYXrJUU2NA8MnXYuPX38M3bsenymyadtu/PHBF7Hkf0/V5r338f+iS2oH3Hj1Bc2Kl5vuehbffPKiIXTkMemy2/Hio39A315d0ZB4kXVf3nju7tpcv77177Xi5drbnsTkcafhonPONL7+7Evvo7ikDHf9biYmXHIrZk6faHzIHY39eVC8mKRJ8WISIJsrEaB4UcKkNYjiRSt+peQUL0qYtAZRvGjFr5yc4kUZVcAC8wssWL/B9UDyc1gxViXsQmR1OE4v6oMYR4T4bXPbXOqhClAW1zW0gvhfdmq20SwtJ03M6nAphmDZSUf2c9Wp32LLwC0elyb7OvXzcxrs5+a8EkwqnOOFot+ufkIupRybzSK/7BIrfQ/XILG8DOu6RaPG2Oa5oUNtNktj/OMrqvDCwd+idy+X0EpMBJIS295Soubur1AVLw3NeEkQM14K/DDjRS4zOv38m7B+8cvGkiD3sWTFD3jlnc8w+x/31b723H8/QGFRqTGTpf6Ml3fFUqN1dZYaPfDEq/jkjcdq255z5Z146oEbcULf7g2Kl8O5Bbj/j1fVxtcVLxfOuheHfs6r7V+1mLU1bnSGUScm+1Aunn9lrlgmtRFXXzIJv7n8nFrZ09z90tzXKV6aI9TM1yleTAJkcyUCFC9KmLQGUbxoxa+UnOJFCZPWIIoXrfiVk1O8KKMKWKB7Scr2PtuxYvTy2rz2SjsunD8Ng1Ni22RxU1WAcsaLPMSqBhw54hJQHTo44X7uGx8kM17kOF1e+RGy7J5FgGV/R+T1Q2F0EYaX9sDkIledi6FDnCgQGwldvu8Lr2VUl3x+IZaNXI7D8e5zucVH3aVLzW33XJdwXXHS+DKkrkfLMOWLM+AsysCsq2qCsnCx6n3TXFyoihdZ42Xo1vewt/L48jV/1XiprqnB8LOvw2dvP46uYjaL+1i3eQdu+8s/sXTO07Wv3fO3l9FLFMSVcuOXNzyEm2dNwxmnDTa+/qKowZJ14HBtjZcHn3odH7/2SG3buuJl/Iw/4uWn/uyx1OhI3lFD6LiPuuJFfj5dzHY5Z8LIRm+B7MN5uPa2J/DHa2dgwphhzd0qSl+neFHC1HgQxYtJgGyuRIDiRQmT1iCKF634lZJTvChh0hpE8aIVv3JyihdlVAELlDNe1okZL9elv4Uya6VH3tFF/XBXzRltsrhpwAAGMNHo9YuQmeialXP88BQkXQ92Q2xVOcpiDsMhVgrFV5TBYRUiSYiltJJSXPv9Drw3uDvmDO4mTlFXkjS341DjORPLK3DrN5tErir8+5SB2NZRTGMRs2jixN/TC6owdGcHRO+dDEd1inESmZXiRf3GkT/LB9Mh5cuHBXvErkaVuNDPuxrdct9ziImKwn1ixoms75J/tAipnZJx7pV3YdalkzHDqNOSadRdefefDxhLku54+N/GsqPf/+YiFBWXQu5UNKh/TyXxMu2ae0Vx3PONwrlyKZKs8dKUeJn72XK8PXcJnn/4FiNnjpj94nQ4ER8Xg30HDxuzaKrELJgb7nwa06aMaVLQ+DKmFC++0GogluLFJEA2VyJA8aKESWsQxYtW/ErJKV6UMGkNonjRil85OcWLMqqABh51VODErHe8cvYtTsNXJ00KaF+YzJNAQ7VdGmfUuDxJEHJk+WsL8LfRJ+Odwb0NMeJZr6XxJURhYibCgNxCxFRWIyc2BgllTthrxM5F+XZ0KojA6T9GIKYCKLB1QpU1CjsTk1ARUQXH0QxXV8Wpe/VyzYqZMqlGFM4N/VEO1RkvrT1yeQVFeODJV7Hqhy0Is9lw1y0zRZHb0cauRnLJ0E+7soSIScGfrr8EY0cNMbqTuS8Hdz7yb5QL0ZeUGIsRGSdij4h372rU1IyXBV+sxuMvvmNIngVips0bcz5vUrzIuJdnf4rZ85YYtV1SOybjL7fPEkV+uxoyaF/2YVGQNxxnjRqKe8SsGXkN/jgoXkxSpHgxCZDNlQhQvChh0hpE8aIVv1JyihclTFqDKF604ldO3hriZUtlLgbZXb9J59EyArIQ64lZs1Fp95zxkpHTD/NHjm7ZSdnKZwJyHHJyXMt9lmMvViIL2RvikZ+Yh8wemR7niy63wmqpQrHY4ch1ND9j5Y6VG/H4GSfXiZefupcXNdw+vqISjyzchaF7ovBh/E3It6XBIlZnyVYRdogiok5DpHQXxXHtdieSkxu+7F49Q6+OS1MDTPHi8+3PBk0QoHgxeXtQvJgEyOZKBChelDBpDaJ40YpfKTnFixImrUEUL1rxKyf3h3hxb3W7Nz0Ty0VNErcsyNgwDMPEx1miJkew1OVQBqMx0F1c943MLCwbdZyn3NnnyjVT8YvTwrnUKEDj4663s3bIWqwTH74fTcuX367ZhtmD+6BQGpPaw4nIqhqUG0VtjrdPKyzFxLWpsO8Vuw8dKzQc6suDfOfdeAuKF3/S5LkoXkzeAxQvJgGyuRIBihclTFqDKF604ldKTvGihElrEMWLVvzKyf0lXj75oQQfnjvPa4bGxC8n4ure3SlelEcEcD/sy619i+OKkN05GxGisG6PrJ7GA3evHs6QLq7rA6pWD83OARYssuG+sf89lquxbZzrChb1XYaeWbga8/t3w9LeXT2u5dGlP2DwoTysiRuJA6XnwRJRhJpjy4TkzJYpkxxITXUaH37eJbfVmepKQPGii3xo5qV4MTmuFC8mAbK5EoGAiRd3fTalXjGoLgGKl+C/Hyhegn+MKF6Cf4xkD/0hXuR5lhXmYGbeQq+Lvi5sKB7oNrRtwAiSXrqL68ruFORbUFxsQY2wMF26uHb2SQrx7aR1DoNkL3ceksuLFnzu2l3p4MlvYsFQUTDFp6Ohei3yBMd3KZq2LRPzBvasPWt4jQMDD5Vi6k8/45z1FnwfNQkJE0YjIe544uRkuXwIFC4+jYUrmOKlBdDYpFECFC8mbw6KF5MA2VyJQMDEi1JvGNQQAYqX4L8vKF6Cf4woXoJ/jGQP/SVe5mYewu+wwOuipxVk4IWhroKLPFpGIDnOjtIKsfSksqZlJ2CrWgJyBkt5uQU7kCvu1l04WFiBgbk9IWu5LO66FofEds7dD0Wie1ERfkxz4EiMXAJUd0tnb5iywO3knfvwwYm9PL7YK68IMWJP7M2dk3DqvqO4aqUNVUeHY1tqrFHk9s3L3vCaIdZ3Vz9MXD0WXbu66q9cczXH3F+3L8WLv0jyPJIAxYvJ+4DixSRANlciQPGihElrEMWLVvxKySlelDBpDaJ40YpfObm/xItcHnNxzkLkpB7fWtculsc8d2gGzhsTrtwfBnoToHhp+V0h6w9JbbI8dgdWxOwwZg912dNd1GtZV0d61F8mVDdffenivYzosk278Y/PvhW7Ew2uLZR76r5CXLisF/KqRhrFb927RMuznXSSKHjbrRxXd37b68IykIqXIie3i12GWj6qLWtJ8dIybmzVMAGKF5N3BsWLSYBsrkSA4kUJk9Ygihet+JWSU7woYdIaRPGiFb9ycn+IF/lw+6X4qAyvwJYTtxg1SeJKYiGL68YWx2Eci+sqj0dDgRQvTeNrahet+x8Kg3dh3OZ3G2o4o2sWSpjDiWqraxnSSYfyMX/253BWJyM7rBdWRZ2DLVFjDNHiztJYAdyBYteqQofnrlUzYvvi2Q5nmLpf2LhhAhQvvDP8SYDixSRNiheTANlciQDFixImrUEUL1rxKyVvj+JlX3WxwSY9LFaJke4gihfdI6CW31/iZZkQL+7NaS3ik9pHW/EAyl2N1MaisSiKF08y60T9k/UbrFibuh2f9VmN8rBKRFbbMf3HM3Fibg/07OlAZqZLjBxwLsBLZx4QoqTpLZobZt+woHli0WqkFZdhbdh0lOf9wpAsFdY4PPd3KwqKPUVKUyO/sDQLvz78RW1It7AYvJ86pc18jzd3Vwe+NcVL4JmHckaKF5OjS/FiEiCbKxGgeFHCpDWI4kUrfqXk7UW8vPK6TTxUVGDugBXY1mGvwSatKBmXb52IpPI4zArA+n/31rYy98L4Lfghai86VsdiUtEg9KhMQWIjhT4pXpRuZe1B/hAv2i8ixDvQ3sWLuy7L1oJiLAnbiZ0lxbAcrsYPg/fUGXlReLjagnPXxMIZVojMtFJs6xyFijBbA3dHQ4Vv6y4pqlWIXm2v+SETV38Xix97XoTuY/ogLtYVGxluxcABNp/Ei2wnhboUMAnWcEyK7i7+jAjxu1nf5VG86GMfipkpXkyOKsWLSYBsrkSA4kUJk9Ygihet+JWStxfxIqfJrzr1W2wZuMWDS1pOGqZ+fg4eur9aiZeZIPfWtovHLUZWukv+uI8L50/D8LjkBgtAUryYoR64thQvgWPd0kyhJF7cuwYViVorO3dZkFu5HlX5GSiLWI6ygjg4I4tF7ZU8VIk/o8sdGJEldhmKKsKX/S1YOFgUp7W5t2xsqOBtc0uIGtsKurGRcSKhvAqDD1Sh1740RByYAEd1Ciwidc96W3pHR9hgD/ddvLT0nmA73wlQvPjOjC0aJ0DxYvLuoHgxCZDNlQhQvChh0hpE8aIVv1Ly9iJepPS4oGoOcsNdy4zqHisxC716un8zq4StRUHyQWnlpkr8Nt27EOToon64q+YMZAz17gfFS4twB7wRxUvAkfucUIqXTdtqUFntwHLsxRxsNc4xFf0wBX2NzwPxvaChjsvvUfKQ2y/L7wLZJRX4JnILKosq0DkvEWFluaiuAkqjs5GTcgQHk6uMuDK7BVmJkUKkyBkp9YXIcYHSSSzpORwbVSd1Y7NVmpIqjQmZhl//7O1FWNSzH0oOz4CjMMPIHRMNxMc50a+vE33FR2Sk06MALsWLz7d1wBtQvAQceUgnpHgxObwULyYBsrkSAYoXJUxagyhetOJXSt5exIuEMWrtImQlH98pRr4md4vZ0/9yJVb+CPqhOBfnH/nE61RDi7vj05PGN5iC4sUf5Fv/HBQv/mfc0BLBgUd6YPpPYxBVHeHzEkEpXm6+3YG96ZlYMm6JR4dlAeNh4qM1Z7/JrZalWHHPUjlalIs9uzvAGr8OR9K/R1anMhxItIplkTYcjQyH03AxdWem1BWzdWutuC+l6e2aGx4hFZnS/JKiiBoHKgz54zrkUqKLt/RB1gkXIbpjHLp1dcAudpROTASSEhsX3RQv/n8f+fuMFC/+Jtq+z0fxYnL8KV5MAmRzJQIUL0qYtAZRvGjFr5RcRby4HxbkCbNRjJ3IRSwiILfrlEf931gqJdYQdMu8/fggw/tha/4FJwesN/K32pOL56A41nPmzTTxIPnCpD4N9oPiJWDDYyoRxYspfA02lksEl4/+Cjv67PD4+qBtgzDy+1E+SxIpXp5+0YHnMubiUFyexzkjq+y455srG1zuV79zbiH0ZY91omZUFiKrwpFxqD9OPzDICK1fM0q+7zP3iqU++RasPbQA2V0z8X0vJ47E2GEUUG5QsDQlURqbldLcEqGWjpFnrZbRWYcwYU82PhjYEzUIw5m7SjF+YyQ+HWJDmSiOG58v/m3ImWosJWpsJ6LGekLx0tIxClw7ipfAsW4PmSheTI4yxYtJgGyuRIDiRQmT1iCKF634lZKriBd3bZLtfbZjxejlteftkdUTE5dN9Fqjr5Q4wEHyAU4+OuSI7Xk3n7jZyN5/Zz/02NfT+Lw1f8vtvlRZ2HLhIhvWFufh87GLa+WLfIicunMUBvR3YMokhxeZYBAv7mUQjQ2bruUZAb6NmkwXyuLFLQ5+DivGW0mrUWqtQLQjAlfkjzAKRMs6HXIbbKkKvuixFutSdzYrI1TGTub9heNt8TDvucNNtMOOz60zG1wWJLdE/rb8EIocFeI9b0G81Y4ZsX2MYqvuGi99N/0P+RHeyw4P9PwVAtqcJQAAIABJREFU3LVTZP/kcqSdyMcYpIvFSClGl+WMjWees9WrGeUSE8N/7IATMxOFcLDgSNJRFCXmIKtjJfYmRSGqqhpl4WEiqvGCsypMGo7xRbg0vpSoa2EJDsTH1Evhiu96tAynb4tBYk4GOh+JQxliUBiZBluYKMYr6sWE252oqrQgrYsTHToAUWIJkTwyhjibnOFS/3ooXlp+FwSqJcVLoEi3jzwULybHmeLFJEA2VyJA8aKESWsQxYtW/ErJVcSLFAazvyrF0yPe8zrnlF0jcVH1iQ0KA6UOBChIihd5GI8QdZ5R3J8GQry4BZZTJJW/Cc5NFjOHimNhrxC7b4i/96pXZNKNJhjEi5ufXKLhLlDcb1d/9NvVz+hmIPgF6FZpcZpQFi9fCKmy6NsqfHjuh0IYFtUykkv1Lpl7KSaNCofcBruhAtYjvh+Jk7ad1OA9Inei2S8+uomt3Rvb3n3g1vdRGO0pSRLKYrF14MW1/ZD9k/mXny5mx/T1nB0j31vJuclGEe1B3SJx3TUOjJu/Chv7exbaTixIxMTMU9AlMxYlhR2w5BdzsDftaG2OHkcsGJbpQJjThrz4YiwdIIqV1H5XqXvbNFa0VmVJj/s8jddqafwGbVq+xFVUoktRGX7qkGCconNxKa5f8xOyEmKxJ74zBh0Axm5MxoaeJdjeSdaCccJeFYno/HQ4cs+sTdtQQdwWv2kaaEjx4k+arXMuipfW4dpez0rxYnLkKV5MAmRzJQIUL0qYtAZRvGjFr5RcRbzIEy0rzMHMvIVe55wupMvzfU9TytXeg+ou2ZI1HnKE0IqLBVJTXb8ZbmzJVjCIF7m0YlvKXsw+yXOp1rjMDIzfO0xpeUaoj38oixcpDV/P3YmXUlZ4DePMfWNwYXg/ZIbn4q7k+ai21HjE9KpOxpthF9TOTnFLkvqSRgqaQULQpPYtx8qTV2F57E5jNk3EoUTs77rf45ynrx2JG1NOxE/Iw0eJ61BQU4mwgmjs7r3LEAauuiiex6l7K3D7okpkpdTgy36R2NDdgv2JouiIcajURvF1eY8vs1DcfW1MuDR0ruOxEaJYcHpBBSKqnbCKl+PLhGwqlNspOxFVFoWYsggM3R0Be3U0Nna1odISgbScLoh0FuFAWF+Ex4tvRLKdcDIVFeJ7kcASJbySpBIuPu/Z3Wl8nwrEslKKl+D/TknxEvxj1JZ6SPFicrQoXkwCZHMlAhQvSpi0BlG8aMWvlFxVvHyemSf2/vnY65yXHh6Bp08bqJSLQS0jEAziRfb83MyFWAdhi+ocMU47tvcKXHHilhEMTKtQFi+S4FMHtuLpqu+8YEphIme+1F2GWDeoS0kyvh90fu1LUrx8sClfzJ6ZVyfMJRGGrR+Og6kHkZPqWQS7/67uqIguRE1YCeyWEojNkMXWyDYciY4Q9VFUaqG4UkVVVYnlPuFeeRuTNd6v1xUgzYmV5grSym40JFpE0W9RqDaiugan7SvEgMPlyBJipCTMLl63Ia4kCvG5XWAVEsWRdyZsUbtQU3asPpQ8ndV1eVaBxSo+l6uboqKchuRNTgbEaXHCAPl395InfTs5NfTOpHgJzPcrM1koXszQY9v6BCheTN4TFC8mAbK5EgGKFyVMWoMoXrTiV0quIl7kTI316614IH917TITefLkvGTccXAKJpwS7rEdqFJiBikTCBbxMujH91EQ2XBdDOWLCeHAYBcvR0XNE1nnpKXH/74uxZ0dP0Sl3bPeyq8XX4K3xn2IijDP1915Rv2YgfcnD/FI+/iR9XiueH0DXWlcVgw/eAQ/dBHFQ2qPxmuVuEKamiVSP7XqMqCmxEtzIqZuTldsR7FldGJZNcKFDOmWZ0OPH0ej5ti2y+5lkYYeERIlTK6WFCWgbOLPMFFXpXs3KVRgbMscKySKnJESFdnS0Q2edhQvwTMWjfWE4iX4x6gt9ZDixeRoUbyYBMjmSgQoXpQwaQ3SKl7kb/2865Rq5RGMyVXES93aJFndM0VtkjzjN9z9RHFae1VEo7VJgvF622KfgkW8nLf0O6zts9UDYWpOGn4YOUkbVnfRX7nb1kpRCFUek9EXcWLXLXkEsuhvsIkXd0Hc1RF78XLHFSizVYj6JGFIqRTFcEs64qqaYRjSMUZp+Yg816YtFnxwOEvsMrTckC/ye8CZX5+JUR2S8dfB7vpPx+WDRWzVc+JPvXDG+pNhi9sHW2QRKhxlqIjJxYb0IqxPl1sP+yIr3LdZU22akzH1b9XmznXMeng0824TKaaRlIfJf3S867tYHaL4rMOB6KoaVIkitAMOV6DLkUh03jMCjqIM498pi0BhE82lSOmQ4hQi2xn0dbNa601P8dJaZP13XooX/7HkmWTdPXEQRMsJULy0nB1bqhOgeFFnpStSq3jRddFtLK+KeJHFdReI3XjE7HcUFgLl5WIHC/Fb14RE8UAh/mzPDwmBGO5gEC9yecj6nVWY0385stJdgkNKl4vWTsSoQeEYN1aP5ZRFf7PFTlVLxi2unYkhhYAspJqSlxLQor+tLV7ckkku91qBLLGlu91jt536kkmO2Sc/lBhLeurPUpHjJzldOH8aBqfENlujx12XpaH7Xf7A/NYv36iXQ8iDwkpkx8saKm4ZUbe1e3mQr6JE/R03a912/O+k3ig1dhJq7HCiU3EFDsdKUddwUdz48kqxe4+8jrp9ledzXcPkHQdx67IcvDu4J/IiosSrTtQIk9L5qAVh1ZGI+flE5FaMNApqy1MYW0cfO5UsqC3Hzf2n+tWFbiTFS/CPLcVL8I9RW+ohxYvJ0aJ4MQmQzZUIULwoYdIaRPHS+vjXrbdg/QbXov61qdvFUpAS9MpPRa+jacZrQ4c4kDG08d8lqIiX1r8KZmiKQEvFiyyIm7nX4rHTTJqQJRPEFuARlRGYdVWN8owQ93bc8oGxMkJU3xRHhNiNST5EyudIXbsayWt8cfg85MTmeSA84Uh3zNzyi2aFgj/vvNYWL3IM6m/pLvs/ddE5SDuU5jUGngVxG57ZMWZnBi7Mz0CPdJcLOCo2LKquArIP56GkRIy1bZ+oiZKNsuh8MTHDiWqxnOikzGiccKQcX/crwY5Ookh0UhXyo63YlxSJallYRBwppWXIjXbtjNN44Vr396X6NVpUl/00PnrpR4ux4tXP8Gn/brhrwikojHAV0R2Sk4u8qAjsEzv5yOOkQ/mYP3sxvk9Lx+aO8fiqV2fkivU6lWJmSlSVE6dkVeDKtQfxQ8oJWNstGvaiNFSLmTvhxR1hrYmDs6Q7HDUpxlWGi1krdpHGIWa4yO2kLaLKraxZGykwuKWYr1sr+/P+bCvnongJ/pGieAn+MWpLPaR4MTlaFC8mAbK5EgGKFyVMWoNaS7zIhy35o/pWscvKt91cW4KO2j8IJ+b2MD6fdbXnrhpaIbRycvdvouedOxd5YgmQ+5DLgM78ZizOEjMRxjcxG4HipZUHyMfTy9lFckaRWJSB9WJmQ45YQnOWrSf6RSWioLjKpzoO8n0yV+z4sm7IWo9eSPkiZ4T4Il7kfeY+CvJdD8qJSceFXlP3mI8IGg2XbBaKmVdlYRWYO2AFtnXYi6TyOOSLB+GGjgM9f9Vs6ro7TS0XS5XW45Axk2SKWK6UJj7zZRcXs+JlYWkWtlbmYVJ0OgbZU7z6Lsfz4dFvetVS6XYkDZd+O1V8T7SgoCgXmX02YvWJOSiKK0FSYSTy40WRpgYPUWC1vAaR1dVihoYFJRFW1FhtQp7Isa4ra72L1w44UiC2JU5s4KxOPPLFD/jX8BNq5YZnkBmp4oSrzktH45RWMTndIfo9aWc2rly3Ay+MOAlbO8fhFFGQ9uoVVsSLrdorLVHYLbbq2ZWcIpb7VKDbIVEjRnRhTxfXPSOL08q5WlbxP7l7j1gRVHvlYUKcWAQKWUtFzvaLEbv82IRcqRTe0S4myCSJy5dFa+12p1G01pd7pdkbsx0HULwE/+BTvAT/GLWlHlK8+Dha9f8ZpXjxESDDW0SA4qVF2ALaqLXEi/zN7+aBm7H61FUe1yN31zhJbEeq67fvAYV7LFl+gQX/KdiC5+C928irOB+nJqaIB4T2MeOl7oP5gj6rsVU8mEdVRxhS7vQDgwxpMWWSniUxqveGfLj+KbtSLA/5EMWxx4XCGFFLo/+u/j7JEpmzoZ2I5OsqUkK1z4GKc9ca+vTsT712vanfh14HemDl6HFNdm1LZS7ePbgfWV+mGHWL6goq93Kl4XHJyrNmGhIv7uVBjXVkj5iRtExIrSXjP8Xebu6dfJw4cU8Szl6bggGl4TgS58DubvtE1Zow/OuUBiSTEBBxldVCyFjFTA13nRGZsbFCsPWX9zS33Kf+T3lN12X57ZptWJmeis2dk+r0ofEc8RWVeOmTlZjfPx3zTuiJYrtr16EZm/dh2P5SzB2UhphKBy5ZW4y+ByOxOu50ZMV0RU25aycfeWZZIEBOtpGriiIixUyTePGa8O+y8Gxf8ZGTY4HY0AgJMWGorKlBWYVYYtTJiWMTYYzzBLIeUKDeM20xD8VL8I8axUvwj1Fb6iHFi8nRongxCZDNlQhQvChh0hrUWuJFPsxMq5mDn22eO6x0rI7FvLAZ7e4H6Nt/XI/Zkd47hPxfzHhc3LF7k/dAKM14aerBfOKXEzHW2kP5IVrXG2fBIiteTFiBdak7PLoQWWXHTQuuQtIJhZjXbTVKrRWIdkTgivwRkPd9z2O1Iur3e/T6RchM9NyaV8a0RfEiZ6esyynBDMypd5liZoLDBqectiAOKU1+ueocXHdmotf3AvcMsVWnfuuxQ1dD431CbnfcdmRik7JOypufy6tgz4tDOlKwZkOVIQJ27N2NmqiDOBy3A7mJRcgWDmJfkt2YWSEFSUWYTexkI4utNl1gduqOffisn1gHVKsYGts6ubklPa52NkeNMaulNQ/Z5zOyDuPuCcNFmobqohzva3xFFW76qgA9dw5GiS0BuRHRONShBJbqONQcFYVnRWiY8DBy155YsWzHXa7lmhbOakyOs6O0QhTCrWw/syJbc6xb49wUL61B1b/npHjxL8/2fjaKF5N3AMWLSYBsrkSA4kUJk9agpsSLrE1SIIoPyuPnsGIcCSvCwHJXXRJ5DB3ibHKmRu+ds72m3EdU27G77+Var1lH8gd/2IWXUlZ4pf5X5QU4r7/8rXPjRyiJl8YfzIERVd3xYtz4NrHt9S+2L8JWu7csufCTafhs0qceRUylZLhk7qWYNCq8wSVlt8/fj9knLfG4AQZtG4TPp5yq41Y1nXNHiVh69fP7Xufpkt0VfXa7ZkD02NcDdlF/RhYzdc9+kzPDCgqArzdX4i3LRmwatKmJvrjEQFJFHB4unILKrDix/AsoE5LlcNRy5IcXiLoeTqzr7sTO1OOn6Xe4CkVR1ciJq1/bRHXGiEpcY0uAmp6F4u7lzd9twQunDWpmHFT64T6Fd963PliGc3YewKd9u+Ifpw5CUXgUEkpFQe4qC2IqwhEpxiY+t5uokSL2Pj46CDWiRopY1WMILjkrrajYgjghWtyHP5fwULyYfgu2+gkoXlodsekEFC+mEfIEdQhQvJi8HbSLl4YK6PtwTR0TIsRvVaz4uaAcVeKHKx7BSYDiJTjHpW6vmhIv7sKfy0d/hR19XL/dlw+RE7/8hVEosrn6E2ct/bq2nTtnv139sGzC6OAH48ceygfKr7+x4JG4pbW7zcjTZ2wYhokpqcjulI0e9lijZoU8EkVdgrpLj/wtXtxCbVtEDhbGbzFmZpxZ3A9jSvoZ+ZsTambRNPZgPriwOxaePN7s6QPS/txVX3vNeJHvjcvzRuC1VG/Bdm3uGFyd0tdrdoecPbNlq9gGOHGvWJq3RQibCiElemLE1mHo1sWJyZNq/Cai3EWe9yRkY+4JK4y6K7L+yvQfxxiFnpsr8qwKVs5qujhnoddSo7O/moi+OT3hFDNKZP0Ne4So/yE+P/kkIUzKnDhw0GIUjJ177mfIi3cVBz5+uP+d955NYhOFUjuWVIi6Mlaxs024a0ca42ho5oma/PC+1pa0a65WSsNf/2T2Etx4zshj9Vd8OYdn7LjMg/iyZxdxKZ6v37FyI37/zW5six6NTUmT8JMtQ4gVUX3G4qyN7CxKtMhZLB1EGZtOHWV9FFknReySJaSLqGvbqgfFS6vi9cvJKV78grFVT0Lx0qp4293JKV5MDrl28WKy/xQvJgEGqDnFS4BAm0jT3IyXj2p2es3UiKqx4z/7r0BTuz9IabOvoAIfj1ha+wAmt7Y9f/UEdE8Uu7W0cBq6iUvV1lQunfhSFj4Vzz85qdmiVkWuIa62iBo4bqElO5ecl4xp86d7Fdv1t3iRY/NteY4xM6PuIWdZjPx+VLNCzSxIWefl3MxFXg/mV2+fgEfPdi/ZMJul9drL/r+/uBovZMgaL8eX0skaL+knVGB2ymqv5DdUj8C9fQd6ve6Wmx6VPo79RWqD5uSmL1fZ2NbF7i2LzxseY2yZ29CRK2pCV1ZajCKl8s+8PPGRDxRV7Mb3nQoQbjmEmmqg29FysYtMLAqTDmNLVwv2di5HfIkV/XNsGHDAilMyge8GHcCiE6NRHCG2PxdTXooiwsSSHsexJT3u7B5ExIt1txFuTkb4QqWx2MbrnXi2UBEyTZxLFj4x9jB2HaOzDuGTdxYbtVdmThsr5EvMsWsXdVGqaxAhlj6FVztFsV0nEkTRXTkLJULURelQaENcSbSYsWJHVXgleu9Lw/DsQ1if3BuHRS0VuSwIpd3hrDpWEFiklEvfWrocyB+EGzsHxUtr0vXPuSle/MOxNc9C8dKadNvfuSleTI45xYtJgGyuRIDiRQmT1qDmarzM2P0FvrFmefVxTupknB5ZZw5/vQj31rbil6ioCKKtbXXAljMN1ontpOWuG8Viin55uRPZYmvdD6bM8+rOlF0jcVPKQI/tpf0tXmR/7gtfinUx3uP65t5rmhRqZvm5i+vuPFSJr4evwt70vYgVO5v0E0Vpzzo8yCi02RaK62aKWR3yvpb9l/JFzuSKK45DoSi2+9G587yWGv3t5wtx6Wix5Uq9w71DknxZ1C81pEbdJRz+mGHgXsIjl4f80/odPo7eXKcXLtHSI68KyWWVOBppFcWOncafFaIIbI3whaV2UZtFiA9Z86T5w1NEDPw5HwfjosX5xBQXcSSWVaBAbBWsdjQkNUyKDiOxL+f1jpUCpC6L1KJSsXRJjq1nrCxIe/nGXWK75O44HBMpis9WozzcirTCKrFTkQMTdhThwvUVeC8jHtlRHSBrqUzaEIEjti4oCOuIPGsqClNy4BDbITurhTA5dvr6Gse9wVGEnEEkepEiVi7K2SnxwrXI8jTRMU4M6HdcqNWfUac2FoGLongJHOuWZqJ4aSm5wLWjeAkc6/aQieLF5ChTvJgEyOZKBChelDBpDWpOvMz8/jss67jVq48fR1yM4WmikmIjh3unEPkwmS9+Oy6PJDFd3b1DRXvfneL9n7Pw+5IvvOhdVZ2Bx/oO8Xjd3+JFnnzs5kXYGetdo2RVt4uRHtb4uKrerHL8M8VuMLI20FtJrkKzssDsuXtG4qd1ka5nyAaef4P1t/B1r1suD8oWO7CUl4nyF2LCi0Ms04gSJUMixNKMvKPAzs6ZWD56uSFf5GySM8VMmFHVPTDiVIeHUFNlWTfOvbWyfF/JWSdinxjxp1wi4nqwDhd9KCy0ID5/J8rzi7E1oQilthpUhudg9cB87Owod6OpvwSn/qO8ityQ2VRnhfhypfVzN9UXX/vZUD88Z/hEVDuOzSxxSQy5bMkmZqVEVTmQUlKDUXuP4tL1+fj0xERkRndFh/JijN2YjAMdyrCqlw3W6khURJYjqjwGUZmT4RAzTIwJLfWkidET8VpyilxuJWqrhLuW8yQLaVJeZhHLy5zGsp76hz9rqfgyKoGMpXgJJO2W5aJ4aRm3QLaieAkk7dDPRfFicowpXkwCZHMlAhQvSpi0BjUnXl5aUIpH+3zo8Rt8+dv9ecPPaLKwrtaLagPJP9mej9/aP/LqqawF8uBwVwFS99Ea4uWKZRtE/Yd1HnnkUqflvS/wy7jKZS2Lvq3Ce9P/53HvGMupPplu1JHJGOqAXMIid0JxC7m2+mApa46tXGnDp5+Lh+X6PsCWC4eYsRDVZTmslXGwRhcb2+Y6wotRFp2Lssgy8WBfiZG75EyIKswfbBW764SJZThitomYxeA+XW6MDVViP94am1jmI2aNuGZeWMUuOE4xM0U+3R8XKmfv3G/UO1nVrVOdMW5quY7KLJBAiBbvN2+kuM5yj9k2QoSI18qM1+pKpMZFTL/co9iRkuCyHaJNcmmF+KhGr8M2JBRHIz6vK6xlneAodO3SI3yWGCDXn8ZqIPFpWJiY9yM+6Sjqn7gzxQjhFik+isQO0vZwC6KjnZC7RUsBlprqEDJFfF1snZzW+OTANvDdKrBdpHgJLO+WZKN4aQm1wLaheAks71DPRvFicoQpXkwCZHMlAhQvSpj8GuR+XlA9abPFdcXMhaK4IqMeSZFYUtEjqwf67exvPID4s/6Ean9DIU4u/fjxR1Fs99B6rBuytvaSuoudXu4pmoDRp3vuFuVv8SJnbGzabMW80xbXFvuVQuSsb8diWGyyXwq6yhkv/8zfirfFbJf6xx8OT8DFnbq3mS3FpUSSD97LvhZFTeK3okQUwj3cIQ81YdU4Z2sBOpQV41+nd8HupChRpwTGUpopOw5i8s4s3D9umFhmI9Z9HJuR4snCu/hrtDAype79eD2C3bGqszyaeqe4Z1I0tu2xu61qLtW4hvrUmMxx4qRDBZgv6p1s6iTqnVw0FoXH7Nxlm3bhsaVrsKh3F7wybABWH5NLUkTZxXq+AWIZW+8DCYguTkKlkFzdspOFWElFiVgG9rOod4KqOEOwyMxSktjlVshiOU66KC8kl3n1Fcvd5NHeZ+Xp+l5L8aKLvHpeihd1VroiKV50kQ/NvBQvJseV4sUkQDZXIkDxooRJa1Cz4kUsF5FPKLWPVq6/Gg+iFC8tGzr5IL9MfMjfpOel5CK7czZS8lIgiw9LsOPGOjy2Hfa3eJEFXfeIcXXX35FLYmR9EnedT3+N6+0/rsfsyPVekB4IH43rurp2UArU4a6l4i4Su/+ABfsP7xYzKQ6IuhtHhFQsQFi5KEwaUYnyiHIx2SECaSVHMH3zAczJSMJnJ3QwZplUySd1j6PxWSDiBxWxVKWhGRlmREXd5MF2Htk3zz51LyhCvuBWdEyapIu1Weds3yfqnqSLuidRRt0TOXMltqpGzNxxiL87xKwfJ8bsrMTVaw+i0JqCfFsn5EZEi12kUlFd1hudi5zIs3WudVkV1jhY5KwiseVxbQ9EN8QKHnTp7BSzUEQNGyFVoqKEVOluR0llRa0GC/Z6J4F6fwRTHoqXYBqNhvtC8RL8Y0TxEvxj1JZ6SPFicrQoXkwCZHMlAhQvSpi0BjW31Ehr50I0ubvYrry8o6Ieh1hlgnAxKSJW/LZdPtdnDPGsBWJWvOyrLsai0iwkWO04OzodpYcjRIFfUSxV5M3KsoiCrkD37q7f9hehAnnJeTgrXqyNcK9MaeE4vPptPu5N81xOJWue/LP8Akw+We7W0vRRt/DsDuRCLNARG24nIU5IEXm4C8+6657UPdu6Da6lN/tydiOrw1cosVWKJToO5MVVYVeHMPwcK2eh1F1603BfwsUuMlWyQmmjh7/kR90E9c+pkqO5GO+vj9h/SMwWEQKjVkN4z6qRs0jChRCJEDVO5E46Uo7UiGquchcih7hXk0sc6J1biWEHirAzKQmlllhUhYmZJDVh6CCW34zaVYkjkfFY17sK4WLsM3ZHIKwqGpsjR0MKE2Pr52Ndc2cPFzsnyVVEA/pL43u83oksDly38HBLlvCkJUchJ6+swflHzd2P/HpgCFC8BIazmSwUL2boBaYtxUtgOLeXLBQvJkea4sUkQDZXIkDxooRJaxDFi1b8Ssnrihe3jFiHHLwC+f9iZCAVv8NphpBwywi51OfVN2xi151MLBm3pDZPrJjZMvXzqRicElu7lay7EO7chHWYm+iq+xLtsOO6I2NwSlkPY9tZX5ddyHN+u9qKj6t3YPWpqzwKzV4klhn17AHk5rq6JWPLwsTMGFFTo0wUgYXYGjf1SBRslSXYmn4Uy04qxm4xc0E+odvFlsWjdthgs5QguTAGh1KKEVVhRbWQKjUWB/Z1sGK3eLgOE3VPqt3bvdRefX2xUH+2SnPyQp5IJaa5YW18loxnS5W4xvvjqo0iZ+h4XvcZmUdwzo+5mLS1HJuSuuPbDkNRXdNBbKkUD2eZq76QezGS10464lRGUeRjh5zQI/8aZhOze8QnsshwmFi6IwsNyzo2KWISSqSYaVJV4SpAnJh0vPF4MbMr0AfFS6CJ+56P4sV3ZoFuQfESaOK+56N48Z0ZWzROgOLF5N1B8WISIJsrEaB4UcKkNai9ihd33Q4pG1bE7jDGYExJP0wvEMU1xSGX+wTLUVe8yGVCPxTl4UOxZXHdwyhaO3967fIvt3h585dveBS3lW1kLZlrd0+sFS+Sxeu7szwEjYyTs1MunD8N5w2P8Vj61BAXtxDasdOC4hKL2PUH+LlsPRxiV6POudGiRqkT+/psQH5MNYqjKxAtHsS7F+firMx9uG3qychKdG+17JIE3cSSFId4qj8Y754Z435gb6guSXMypCWCpf5VquY43u74bJnm2rrayGU4PcTHyu6yEqt3n6XwkEuXoqqrheRwIrG82iiqaxczUSQVq/i6/DyxrAZjdxXj1F1OfDoowag5E1YltomuiEHy/iEoKT/JiO/Xx2kUNm5r2w2beV9SvJihF5i2FC+B4WwmC8WLGXqBaUvxEhjO7SULxYvJkaZ4MQmQzZUIULwoYdIa1F7Fy/0PhWGtKGxbt7gTH6GWAAAgAElEQVStHIiMDcMwTHw8dL+YWqHhqCuEfojea/RgXFl/TC0ZjEpRB6O8HHg5ehVWpXtv8X3N+qm4cWQnjx1Uuma+5nUV/UvS8FjYUGOZUdTRWFQXFOOdHtn4ul/dXY5cD/6jdzhgtZaL5TZO48G+RvyvzG6BVcwosYkiGvnRovhyhM3YXcf1YRPLUDyX5yT8f3vnAedGdb3tV9rem73FvRtsHFzAmGaawTa9Q4BQQ0JIAuGfUBIS4KOFQEgCpNAJhBKaAUNsTHehu1IMbthet7XZXW/vkr5zR6tdbR9pikard/LbYFtzz73znNFKenTvuQ2NyK9tlF1lVGXTjoe9S3l6EiD6xIh/5B3P3W/3XsyVHYQeOmC8Vvw1VWqW1CXG47gNJbj6szV4fP9J2JqVgcoUN3JqfcLGhXj5yaz1b+ucJHIrvTIP8Y05yC9Nk/ZubM3OhDdlB1xVE6WY79fwls+EO2UTvA0yGyXYxwSjDMxEUf+VH7U6KlF2RGqRWScD8kTOyJ/V5Be1A8++45Vw8W9XnJIcgZs8gl1SvEQQvs6uKV50gorgaRQvEYSvs2uKF52geJouAjEtXop37MYvfncfjjl8Gq7+8RltwE740Q2oqKrBBy/fh4SgrRcrq2txxGlXYfqUffHwPb/Rzqd40XWf8SSDBChejAFUswbeXOSvL7GycD1K0sqR7EnCwdsnyLfe/mUlc2cbm5kRq+JFCY6ri15AeWJNhySleBLx8PYL+pzhYSyzPbdWQuiTAz+WXaS+7nDSQZ/PwKTvUjB47E68OHgj1hZ4Wh9vX7oxoURmkjS3YPyeOpy/skQrCvvU1CGtWw23f2JXAkXNJlHHpN3l+IH8PPODMb1ckp4lL8HNzRAcgXh6pUh35+kZR+dzOv79jLXfyU45wHOTRiFN1s7sU9KEkbsykPn9EMQ1D0TCXqk607IbuxJb+QXVxYmTWidelaagOiZqOU6cJEDhT4x3ISvbX9snU3Y6ThAxEpcgW0M3y3bHuUHreSSE+nuilKWJRVli5nON4sVMmtbEonixhquZUSlezKRpTSyKF2u4xmrUmBUvn6xci5vufhyjhg/CvmOHdxEvbnk3939XnI2jDvFPl1fH86+9h6dffhtFBXkUL1HyjFHFNysqXVieshWL5BvPOncTpkmthcAyiMn7d9xu1qmXpUe8qA+a6lA7u6gPm02JjRi7aZz8+Hc9idTMAycwDSwXWXLoYmwY7V8Oow61BOTseedgfFFi23KRcMfrVPGitlxeLQVSa92N2pbEy1OLkSZ1R2bLLIA51RORneXDlMkdP5yGymDCNy/JTISO4iWpJRHfjTkv1FAdzg9edvN91WZsSt2EdVk12BNXi0mb03DaWi++yU/DhsG7MGJrEabs2o1lY2qxRYq+lmc0YOnozoVnZbaCVrPEXzC2/eh5+Y0qiqpmn3Q8t7tisqFKleBL7Ula6JUlvcXqnIKexhncV3fndGWkZusky3KdoRVNUhxWZn6Up2rFYNOq81CbUdY2A8XVkoGMskJUxBdpokShj1M/8T5kSIrU9sPqmDLZKzVO3Ji6nxTtrWw0dO+wsbUEKF6s5WtGdIoXMyhaG4PixVq+ZkSneDGDImMECMSseFn11QZkpqfijXc+0Vh0nvEy56jp2LKtBPfefGXb3XL+z2/HwdMm4otvNlG8RMlzSNVxWOzd2qXmwsRvJmLG5wdHzTa+esVL5wKg2oeZCC/5cMKtonZrWVVSi7PwYpfhXIrJuDJ5codlJeGM2aniJSCd3j7qbRQP9S+5CRxq9seJdRMNS6fjFn7eZWaJeo69NffAtr4ChWfrZRegHbvLUOVaizqpYVKdWYzE+nQ0JdegLqlWdsyRJThJLWhKaEFZhuxWJEs4ylNl69pEtaSko4gYUlWL7W21S2T3ltK9WDcgp5f06RMK+vLf2wyPnkVO97F7ny3S3iZ0EZMhWy6liDxSWw4H+A2oa0BpavDamO76l5olstwnTXbhSWrxIq/Gg3HbMkWmFEpRWCWiPHCVHwRfs3/rYSVTlFOJk/ypNKWJUFE7TKlCsANyIc8v/5KcvnbQSZB1PNlpCRQv+m7CiJ1F8RIx9Lo7pnjRjSpiJ1K8RAy97o4pXnSj4ok6CMSseAmwue/Rl7U/dhYvd934U/zkN/fgnRf+gjR5g1q8Yw+u+v39+OmPTsIrC5e2iZdo/1YuR7YCjZevHvfWNMluDMa+9e79flM7QhhbyqHjfu5yyopVLlztXoD1abu6PPbstsswVSY05WZbed3hjLprm4FZSbo+iMzZuBAr0fVa94y51JyBRHGU9ypLcO73C7pcwfSmYXhjwizDV5adJnKgsRnNUpTTSUe5zHhZuqYRlw9+usuwVI2S+7zHY9qU8Mf88ONuFO9twIfjVrXNJhq7IxWTtso2yxnlaExoRmVaM6qk5uuGgbL9ssweCRQ39Q/IOukQ+s45esfSXYZ7lyIdfwPqFShdz5u6qwwri5Ts6PjYD7/8DsdsKMNzPxiFBneyVvskq86Fo7/xILkpHh+PThSJlYRxm/NQIJOT1g2Uv6c1wN2YCZfbC5/a01h2NHI1iu1Kkv2LmzPgrZJfkNKNSx5SM1XU5kZpkkc1YWjSfj5kSamZoiI/i6Ki9joneq+uO4rq9SgjJUF7TeLhXAJKNJdVNXI7aeemCFmpCaiXelZNIk95OJNAsqyLVCUNquuliBQPRxJQKyByMhLk953x1yT1Xp5HbBOgeOlBvDxwx9V44LGXMXPG/jht7uH4xxOvyDd3UgtiYB5efbNdvDTLN4HRfKhp3eoNdYtcR/gfvZxNYMKy+diY0Y2M2O9iZMdFxy9B9S2wnntt+EcvYVda696yQWlp2v+nzk6SDaNbvqEBR1Y812VnmvO3zsQTJ+9reATqA6NHfh2oXVJCPUrLgU+W+2QJTTWeyPgYXyXuRL4szzi7dhoOahyBPKlfcfD07nah0d9T4pqHupw8qrII8wefhD2lPjTKyo7aOv9PRYXMNJHP3o0JK2UXl+FoTlmLVF+RbFW8CwN2p2KfBln2kxCHT0fsRXN1PBqTGzCi+nucsH4zrjllLL4skCkOHX6jhDL2nj626/04392SGf2c+j6z5/ElyQ3QqKqxth4FAnO3MhXdyiV1UsflTmoZVJz8pMlME9VLkibDRXDUezFkLzCtuBmHfpuMbZmpWJ07RpMlLiVL5F7xVPoliVtWHKrJQdoO0HKopTyjRrhQVQUMHybFYVu3J66Uv0utXu1xdf+p1VRKvg/IdWl958uuyBniYJRcUbNWhg7Wn0OPug5tOVfoh0tekORlyeIvAkIfF1t0JKD3NYncIkcgTl6TfPKa5A3jNSlyo46tnt3ye1K9B/dY+sVnbDE1+2q1Iuvygtqi3uAZPNTvTR6xTYDipRfxsqV4F5555R08du91mHv+9fj3327Aii/WdxAvLK7r/CfQBR+swfsjgncZkcKKJUVYNnl21OxEoWepkcrEqYs/x+fDOxYTVde6YsZs5yfKwhGqOicff+rGU6Ub8OmBn7TJF1X/5tKSmZg00Wu4zomRpUaB5UCvnDgP5bnyKTjoOPbdYzGwwIfTZ8VjQmIO6vbIrBFZrlMmp31ftQW7qnagthao98oynRa3LADxytbB2+TDs0/bbji5MR7VMuPkm4IklKb76wAFjmEyUyVVvhHdKzvF1CfEoypZLefp7ui4dOaozTvx/shBXU4Mddvf9gC9SZXulgf1NMbAh/2+JE3Xx9uvqf2xTFmm8/PP1+J1qQP2VYF/CdPVn3yl1Xx5dtIYtMg7ssKaRowob8QpX5eiSL4Re3pqEXbIbIAp2xtx0oo0kVMurM9PQVpltuy4IzajUnbYyfoartrBYlbEftQOgyuhQoSdfEAK7LYj783U37V6KH73Ist2pD6NpG9IK/YsKSKbP9CnCTLZ7EfbzlgVl+1rKY+FTzNTQnOpkSkYLQ/CpUaWIzbcAZcaGUZoeQAuNbIcseEOuNTIMEIGCCJA8dKLeBlaNBBHnvkr3HTNhXjh9Q80AbPg3U8pXqLoKbRwkRtffuXGkjHt290qETFnySyMKUjEnNkew7U97MChR7yo3WVWb2zGi+OWtNXyyC3PxcmfHotZE9Jw1BHGbb0d12pFHwGxoWI3StHh8pxyJDYnIrdMlmzIh9uRw32G65wYES9KDD377W7cWdh5KZRsPeyJg1dmNagjpzoR5y9Nw7ai3fh8tEcEi6rb0dcRLC4C53YuLNvd7IS+5IWKpeec7sbXnUzpSbB0P4NlaGUNhsvPsmGFbR0ctH03vhmYI9sRBwSS/7qO3bQdCTILY8FYfxXXgbIl85g9zcirTELu3nwM3jUA6TWZKEuXZVGZDXC1yhFf2Uxkt+xCRYKsp5FhaPqpdThKiqglOGpihzbLyedCmgiQJplFoia9xEutE7V7TpPMTi7IF8cik+tkl2RNnqgZJPX1/v+mpKjzfLLbTkdOI0eEPnOqrzshGh6neImGLMnSstwUlJTX99uZstGRhd5HSfHi/CxSvDg/RxQvzs9RNI2Q4qUX8TJqWBFu+fO/seiDz3DDL8/HKbMPpXiJprtbxqqK626WWhNanYKgL8PlM5I2yf+SCz2Ihg84esSL2tUo8MGwKalRm9WRUZ2hPg9q1xrLuxopsbFKdvZRR8VeqWlU6f8ArIp9ykQP5Jiws0934iWwK0/gabNjzW7kLZ8Hn2c7npiWjS8HJbepi52ZsoY4LbD0LfhDt54lG50FSG+zREKVJT3F7k2oBB7TM5Olt3Pbr2N0WR0Kqrw4eH0i8itSRZxIXSp3Ej4dCRQP8GJQWRIO2dSMzbKf8MbcPLikRgkSquGqG4zEunyNc1NCk38CSYu/IKzyJUq6JYinGSwTUBpEhiSLCEkN8lmBmSTZstwrJwrqQUXZr+guw6V4iY4MUrw4P08UL87PEcWL83NE8eL8HEXTCCle+hAvy9esw0+vuxdLX71f3ownU7xE090tYw3+4FtS4v8Am5Pr0755Vof64C1pdfzRk3jZ1lKDofGyxkAONeMlcCi5oI7snPYP8EfH8IwXMxKs5I2qfbKnvBw7tg1ATfN38DWOQplvKer3ZsAlu/LUx5WjSbZVbvF64XV7UJlRg115HtmVx43tWf5P8zNkVsbatlkZgbUkeuSKGVcRHKMvoaJH0HSN0XW75nZ5oh7Ll6U5aU1eJEstwcK9cUivT5QtiFVdFKk/0pCEpLoBiKvP10SptvxGCrx26EX+ki0CRDbqwZDBakGVSDSZdqL+rmaYaPJEntOFsjxLHUqqBGaU5GTHYegg2UmpjoUMzb6bzIpH8WIWSWvjULxYy9eM6BQvZlC0NgbFi7V8zYhO8WIGRcYIEIh58WL0VmCNF6ME2V4PgYB4CSyZKcstw5JDFrfVA5m4dj/MWD4DI0xYMqNnPP3pHMVUHWpZmjqqasuwt3ARyjIrZXvjZpRmyvbGsvOA+oi/PSsZzaryp3YES5PeJEZPAiPUf++Nem8zXDq366vfvoSLiEuxHI1qylCnQy3/+fsby7Fw1HiUxxUgvikVKXulhonMPvElSjESWboTUIFut1+aJMRLcUH5c1JrOLUFsapfooTo8GEdl+EYnZ2WnhIvQofixcnPX4oXJ2enfWwUL87PE8WL83NE8eL8HFG8OD9H0TRCiheD2aJ4MQiQzXUR6CxeuivCeviHM3FcixSLvUi++uehEVBSZYtaatZ61DaUoakhD2l1JdhYVYSk9O+wfYfIlqFL8MWoKilAq3agCRx9zUbpS1CEm4Se4yZ6ZGtQbdccPaKl+zhHbtmJUiku4i8W235OhmyFrYrFpkux3YHVzbKjkRupjV6ZneJCg8wayZCCvhsGxKMkq3W6mJImLcBpH6chQcIk1WfBVXqQ7M6QB/EoGCxFYFWxV3WopTsTJni1mWaRnGVG8RLuPWlfO4oX+1gb6YnixQg9e9pSvNjD2UgvFC9G6NnTluLFHs6x0gvFi8FMU7wYBMjmuggELzVSy4tmbH+pS7spKMQbI+boihetJwVmp6hlY+oj/Tffyja5MkNFFTRtTl0rM1RK0ZhUg4bEBlSnN6Ikx4Nm2QawLDUOlSkJUhPEjSzZQ/fK5d/gjbHDOm173J1o0StXujvPSNvgDPnjnP7NFlzz0Ze44djp+HBYgXZCuuy6M7q0EXk18citTEOD1PZJbkySLaDjkV4+At54KRTrSe5Q7yS/2ocGVxqqcktkqVSmtpOOS7pQtYDaRtyKIrDcxy2FYqtkCdULZzzf5dY54MspOPjbqciUGijZMjuosLXWrROXtlG8OP+ZT/Hi/BypEVK8OD9PFC/OzxHFi/NzRPHi/BxF0wgpXgxmi+LFIEA210UgWLzsrmvE1D3Pdf0A/P1YvHbgobri9XSSKkbcEN+IhaM/xcrCDdpph2yfiOM3zdD+rHaBUlsZV6MRb2Kj/LcZRUjHXIzRHjcymyFQQ0VcAsrLXdo2uZ8V18ATt1xmWRSjZEAlPGoqhRx7pWbK1hxVMyUgS3q77L5mrhhB1ptc6fmxsWWV2JAn62mCZq745YcLagvjexZ9ivdGDsPCcYMwpLIep329G+esrEBZ3CBUx+dhWdFolCWlQe26o/Ui/6eW6PjkD2nJLtlBx4f0NKl1IrV6PbIhUo5IEYUqV2r+qHonTTKLpbuddAIkulvS81FDCc4qebMLrNmpQ/F4/jFGINrWluLFNtRhd0TxEjY6WxtSvNiKO6zOKF7CwmZrI4oXW3GH1RnFS1jY2KgHAhQvBm8NiheDANlcF4Fg8aIExfFfvte2ZXTgw/uZmw/FfUeN1RWvp5PUzkhLDl2MDaP90iVwTPxmImZ8frBWQ2bdriYsOO5/bfVl1DljN47FzI+O0LVLVKDg8aefu0WwQAqdlmHn4PnYUlSF2kQX9qTHt85OUcKkN2mid0aJHiR9Ld0JflzF62075u7PzWxoRkFNEyZud2Pqqv1RnDgRyPwa3vKZcKdsap95osK3hlBlVNSP2nVJHXmy5fD06f6tpZWgChSJVn83Wv+kL0qV3kaZafUyqrzScdBxS+50XJ45oa/mjnic4sURaeh1EBQvzs+RGiHFi/PzRPHi/BxRvDg/RxQvzs9RNI2Q4sVgtiheDAJkc10EOtd4Ubu9rJq8EsVDilGRVQFPvBTbkCO3PBfHv3UCkpqSwto+Wi3lOQxPdBnTwJZ0vBJ/Fr5d58LL8WtlRswnXc750eLTMC0jFxU1ZahLWIuqSv8+1mU56/FdUY3MUnHJjBXIY25UJSdIcdY4pDY1oy5RVVXtrVBtT4jCFS99tesqYeQXpTYbJauhCUWVTWiWgrAZDbK8ScqtJEhJnTRZ6pRbpbaCll2y6lNkqU+CXJFbdutJROKe/WX74py2LYyDJclcmUFU1Lo0R9eNEOGTXqjZgJvLP2+TL9E020Who3iJ8A2ko3uKFx2QHHAKxYsDktDHEChenJ8jihfn54jixfk5iqYRUrwYzBbFi0GA/aS5qruyXX4OTrbmU3QX8aK4iR944Yz/oia9pgPFsZtk9smHR/QoXupFGAS21u4O/zHNz0hh1eBZDT6RCsk4bU0a6pMq8cnIZnw3sH3ran8MHybsqcbafNlWuXXJTHDhVv1p7kmKhLekp6d+24vUdjwjTrY7Hr+7FkPLE1CwpxCJ5aNkxx1ZriNbGrcdrY5IysVo2x2r+ieqQIqamaIeipO/J4mDSZC/Z2bKN8OyZfmYMf4ZK1bPStHPOfwz1cyXr5v2IsudgImJeeEHikBLipcIQA+xS4qXEIFF6HSKlwiBD6FbipcQYEXoVIqXCIEPoVuKlxBg8dQ+CVC89Imo9xMoXgwCtKi5qlWiPgTvSi/DqgL/spl9S4djZGWR9udLwtj5Ry3DUcf60euxUZbiNCY0Yvj2EWhKlA+i+36tPZbYlIhZ7x+Lot1Fupbd6L384KVGwW0Gb/l3lxAjmnPx4diT2/591WoXVq9xo6EeqHGvRn18Cerc1VJ8tgLf59SjNlkVTnUjpckrs1LiUJqWGLRzTiBM51oqnZfaBA8j+LHAv3cWJ3pnnaj2fZ3bXR/tbfyzVWRnnSYPhlU0YnBVPX79QQkWTMjAJ0Nz4fa6MLAyCXll+UjYeaQ2M0UJlQG5qh4KMHeOf2lPX9JkQGYSquqb0dTsP5+H8whQvDgvJ51HRPHi/BypEVK8OD9PFC/OzxHFi/NzRPHi/BxF0wgpXgxmK5bEi96PvwaRmtJcSZJdBbuwYPb/OsSb9f4sDN82IqxlOCqmki5LD10SFLMrFSVfzp53Dq44N77XD+tfN5VpcfTMGuhJvIxc/6yIn8DsFP9YBu/14ca3amXL5Ba8s28iNg/0YneWCxUp8fg+TS2H6Xz0Vd8kcL7eO0DPeT316Z8Z0rWGSmAM7VJHbX9cUN0kksiNnDqP7OwTp+3sk9CcKBRcSC2ZAF9SNXxSQ0WbhRMIK38I7MisZrOoGSrq724JnSM7LAdmp4S6Kw/FiylPXUuDULxYiteU4BQvpmC0PAjFi+WIDXdA8WIYoeUBKF4sR2y4A4oXwwijM4D6DrXz5H4TroTixSDEWBIvBlHZ2lzVKvmZ5018GberQ7/5nnTMizsLFRXQZoHUt+7gsze5BjkNsjvPpoOQ0pKEyft7MWVyQAK0hzi5+E2s8Jb0eS0vFs7BId0sO1Lypjq9Gu8c+XZbcVo9dVk6i5dKqaNSXjoAdy/5CPNnrutmPLK7TVOLFKvVWz9FjyzpSdj0iUNO0Bc/UEslpaUFo0ob4JVdjKZur0dybQ4S9o5Bc/VUuNOK4asdBq9HZqa0/l5Uy35U27R0/z/kywoYtcvPfhNkd590tcWx1F5J1jPO8M+heAmfnV0tKV7sIh1+P9EnXvTsrBY+D6e2pHhxambax0Xx4vwcUbw4P0cUL87PUTSNkOLFYLYoXgwCtLD56E3PoiGu4w4sqrsdIy7Ge4vdWPRxM1498VWpkSL7Frce6TUZOPWNUzH74AR0N+PhwK/nY2eabMXTxzE/6UxMK1IWoOOhxMv/ZEegksKOQqivuizV5cm45+8tcGeuwsKjlmF7ltpKGbhh2Rc4tHgPLj71MJSldmcW+hIeeme79HbB3c1S6Xy+/5x4qaGi6qgoKRTouVlmrEwtbsaoTePhLj8Avub2uiHqHFU7JVkkyrBhXhEo/h1+upNifeXE6scpXqwmbDw+xYtxhlZHiD7xYjURZ8aneHFmXoJHRfHi/BxRvDg/RxQvzs9RNI2Q4sVgtiheDAK0sPlhH76PzYO3duihsKQIK2bMhtqS+dmKDbgTy7qM4E4cjZOzhyMnu+uMl3Pf+QJLx6zs0MbldcPnbq/rMWzbcDw79Ogelxl1V5clzZuI9aPO6zIWNXNny1YXGuvj8ckXG/DqCQtluVBHwfL0vMW44PQjdJLsTrTokS9dBU5Si0fbmaj98J+TXd8kBWqbkdqoFvy4tOU/WSXjZN/off07+7ROU1F1VGSjoNY1QP4o6q9zZyvBYs8sFZ3QdJ1G8aILU0RPoniJKH5dnVO86MIU8ZMoXiKegj4HQPHSJ6KIn0DxEvEU9DkAipc+EfGEEAhQvIQAq7tTKV4MArSouZrRsnxdE/5zwIK2JT3pNek4/qNjcfL4HBx1hBe/3bgGT8Wv6jKC/0uYjl8PntDl31XB3j3fA+9N/KStmK6SLFNXT8WGMetlCVENikTsTFy7nyYULrnQ06182efrl1Cd1nEnomHlRfh46mwsXOTWdhwqrypDccF8bCuo1rZhbpE6JN/lpnVL64dffodK2Z55wdihIdLsLFz8f0/yeDCwpgGXrtiGcXvq8b9xQ1CSKvKkNhmpDWlIrEtHfGMOyhMzMe+45V36PPn105BX7hcsaraK+klKlFkuqUBeLjB9ur5itSFeTMRPp3iJeAr6HADFS5+IIn4CxUvEU6BrABQvujBF9CSKl4ji19U5xYsuTBE9ieIlovj7XecULwZTSvFiEKBFzdWSHk0jyP/tal3Wo3YaCqxvufWmFjz/YR3+b/ALXUbwlx1n45xDxRJ0OoJjalMz1NFatFX7q/xf8KKbnsTLuc98F1Sg1y87jlmVKzVN0uDxelGfWop5B9fJbJJAVaegzto6bh/c9bLc6LwvN+HE847Ftiz/8qahlTUYU16F90cO6nAVBSJUpm52I61eFdl1IWvPGKBqojYTJS55Ezz1o9vOV8Vm3TKhRY1QFaBVo1FCSf3kDQCam4Glkz/G0oK1bW1Oq5iC0yunYORwX5+7AFmU+oiFpXiJGHrdHVO86EYVsRMpXiKGPqSO7RcvFlU6DOmqo+tkihfn54vixfk5onhxfo6iaYQULwazRfFiEKBFzdWMF3XUN7hkBolsoywTTJKlLEppdhneH7YKLclNKJDZKZ6yJKyYskLbGUjtRjTzw5k4I38YJk3sKg7Ush91NErZGDUrRR1qSUyS1B9RR2C74foG/+PVNS5s3OTCzsalqPk+A3WZm+FpjIMnaS9ysQnrC91YNqwQ1Un+barbj87bMfdcpyVTBrP08QUYVlWLSimk+9bgaViVcgyKSpMQ15yBHQPq0ZTQAq/a2Uc6UJECP8MG+YvRjh7pX9aTnS31U7pZXtVXitTuTJXeZmS5E3Tt0NRXvGh9nOLF+ZmjeHF+jihenJ8jNUL7xUt0cHHSKClenJSN7sdC8eL8HFG8OD9H0TRCiheD2aJ4MQjQpuZqmdCK6nIppvtKhx6HF4/ArA9maTsNZUhh3cBxpCxF6mk74V0ichpE6ASOVWtEsny2RmaF7MbasTuwpaAW64pE+GQkwy2FTLxaIZPOMgVIaW5BfUJn6dIXkPY5NeNLq3H7m1uRVVaI4sIjMOGUfVHZkin1awBtM6PWQ8mVDNnZJ3DYscNPX1fRHx+neHF+Vg/FNIcAACAASURBVClenJ8jihfn54jiJTpyRPHi/DxRvDg/RxQvzs9RNI2Q4sVgtiheDAK0qfmq1S78MW4ZPszY0KXHny87G3mNGdqsj4zWjYh6Wyqz4q5XMWrnm3hhchaemDZclvek4riN27E9Mw1r83MkfnDtlEB3XcWLkUsfv6cWR71/AXIyc5Eqq6KKZOyqKC2PyBGgeIkce709U7zoJRW58yheIsc+lJ454yUUWpE5l+IlMtxD6ZXiJRRakTmX4iUy3PtrrxQvBjNL8WIQoI3NT133Hj5PKu7S491lp6CgagB27pSZIrJsqK6xDLUJa9FUPhielB2or3NptU5qs7aiOmM7Ur2VGLm3GnfMnNzN6Pvavrm7C+6uTfe7CE3a2YBx2wYgZcscwJOH3mbm2IiWXQkBihfn3wYUL87PUVSLl067tDmfdvgjpHgJn51dLSle7CIdfj8UL+Gzs6slxYtdpGOjH4oXg3mmeDEI0KbmrtIS3Pv2W7j34MCsEL/YiPd4ceraXThxbQWemzoAi8bmBy0PCh6c3rornYVJ7yImQfpvjgsU0e167glrmlH41dlaQVtvcx58qritnDZihL8GTSwWsbXplgm5G4qXkJHZ3oDixXbkIXcY1eIl5KuN3gYUL87PHcWL83NE8eL8HFG8OD9H0TRCiheD2aJ4MQjQ5OaBAri1DbIdc9U3yFy/DLM++xDupnrpyYe7DvsB/iQ/7cuB1ABkx562Wizq74GvLYP/23mgPQmV3kRLx8eGVtbi9oVb8N6IoaiMlx2N4qVQrxT4dXldSPAkIm3PBHhkhyAlXc49LQ4pmU3acqiUZJOhMZwpBCheTMFoaRCKF0vxmhKc4sUUjJYHoXixHLHhDiheDCO0PADFi+WIDXdA8WIYIQMEEaB4MXg7ULwYBBhG870VLqyWgrZqx6INZUuxI20jql1NSBZpsamgGrVJPmzOTZHtmGV9kByTdpfj6VeWYJhssaykyl2HTmqVLz11Hs5yIamzUl2LXRlprVLHL3DGltaKRAEGVrmQWyXFdr1xiGuJQ3JDBhJ2HgmPbOOclKCWOPngU9NZVH0Y+U+m1JpJkB2fh8jOQ8kiWuYcmYQmn5JHPJxKgOLFqZlpHxfFi/NzRPHi/BypEVK8OD9PFC/OzxHFi/NzRPHi/BxF0wgpXgxmi+LFIMAQmivhUiE79qitmhe+5caeHzyI1yer7XuCi9l2X8T2+A3b8MzLi0VquPDbY6biwQP27abn3uJ0lTFTd5aK3EnQiuseubEKZ36YhS3ZWdiaOhjuWqkP0zBa6yPgU5JFrqRIIVwlWjIz/QVxx4xRYsUnf+4dxKC8FET7vRZCqqPyVIoX56eN4sX5OaJ4cX6OKF6iI0cUL87PE8WL83NE8eL8HEXTCCleDGYr2j8MD8xKgnqj+31FA5o97VsOG8RiavP3Frvxgfx4CxZg3hFbUJksFXBlaZC2BqdNuvTeZVZDI7b87SVtNsmyofk46bxjgxoES5XO8qX72S9qV6Ej3r0APilwGy/uJyFBdkRSk13kGL+PF6NGtIfPzgZyso2xpXgx9ZayJBjFiyVYTQ1K8WIqTkuCUbxYgtX0oJzxYjpS0wNSvJiO1PSAFC+mIzU9IMWL6UhjOiDFi8H0U7wYBNhLc7UFdEWlC6puyzrfi3j6yKrWs/vaBajr44cW78Ybz73TJmyenTRSZr4cgKqkRAyVJUi3LF6Jl/YdjYVjB6OgpgFFlS1Il6VMiS1ueNxSe6XZjcyaVGTKTkdxDfnwVE3RxqLUz603tVgHoTUyxYvliA13QPFiGKHlASheLEdsuAOKF8MIbQlA8WILZkOdULwYwmdLY4oXWzAb6oTixRA+Nu5EoJ+Jl/Bqcxi5KyhejNDrvm1AuKz8Yi9K0xbj3Wk7sSOrc0XZ0HL94vOfYh+MxOcpc7BpTybSvNXYmCSFa2UIaimQ2utI/ErbEfijNqlGPSb/DcxqGTrU/29TJvt3SFK7C1l9ULxYTdh4fIoX4wytjkDxYjVh4/EpXowztCMCxYsdlI31QfFijJ8drWNbvGjvvO3AbKgPihdD+Ni4E4F+Jl7szy/Fi3HmaimR8hsffLgXTYWLsbtgFzYWNKM4JzVoq+VAP73Ndun42D57arDflkzk7JgCT7VfstgxO8U4ka4RKF6soGpuTIoXc3laEY3ixQqq5sakeDGXp1XRKF6sImteXIqX7lmqj/r+r80if8S2eIk8fz0joHjRQ4nn6CVA8aKXVA/nUbwYBCjNb7o1Hu7MVXhhzsf++i0djs6ipW0uSutZsgyoxYuzluQiqa5AkyuonAiv7BYUODKzfJg2xd/u6COc8nIbGjeKl9B4ReJsipdIUA+tT4qX0HhF4myKl0hQD71PipfQmdndguLFbuKh90fxEjozu1tQvNhNvH/3R/FiML8ULwYBSnM14+WBhAfw2aDW6rQ9hmyXLvlSh2VQpUfqsAD7LD8R3vrRGDrMh33G+pCW5kNuLnTtFmR89PZEoHixh7ORXihejNCzpy3Fiz2cjfRC8WKEnn1tKV7sYx1uTxQv4ZKzrx3Fi32sw+2J4iVccmzXHQGKF4P3BcVL7wBVvZbVa9xobALKmlajKmct4urTUZtRht25NahL8mFvqgvf5ck+yx2O4N2F1APt20SftLoFA7+4QlsZ6o4DsjJ92vbMU/b3St0V6+utGLxlwmpO8RIWNlsbUbzYijuszihewsJmayOKF3NwW72cguLFnDxZGYXixUq65sSmeDGHo5VRKF6spBt7sSleDOac4qV7gAHhUl5VhpLcRVg5thTf5gfPaOm8bXPnOMFLivznHrapFuM2jgVKjtd2kr7kQo8thW0N3iKmNKd4MQWjpUEoXizFa0pwihdTMFoahOLFUrymBad4MQ2lZYEoXixDa1pgihfTUFoWiOLFMrQxGZjixWDaKV66B6iWD30gP8vm3Id1+Wo2S/uMFdlHqNPfu5Mu2n5DOKC4DqN2ZCGr+HB4GkZrOxBNlZkt2dlqhosPOdn9c4ZLZyIULwafqDY0p3ixAbLBLiheDAK0oTnFiw2QTeiC4sUEiBaHoHixGLAJ4SleTIBocQiKF4sBx1h4iheDCad46R7g3goX5q15BTcNr9AESijipUDqt5z0v7nwKdEiTZVcSZSauycc7y+MW1joQ0rn3aUN5tHpzSlenJ4hgOLF+TmieHF+jihenJ8jNUKKF+fnieLF+TmieHF+jihenJ+jaBohxYvBbFG8+AGqpUUVlS6s21iO0rjPUZ65E8uH12BTnlpe1NcMl45JOGeFG7OzL0ZCvP/fo3UnIoO3VofmFC9m0rQmFsWLNVzNjErxYiZNa2JRvFjD1eyoFC9mEzU/HsWL+UzNjkjxYjZR8+NRvJjPNJYjUrwYzD7Fix/g40/GYeuOciyb9R+p5ZLeKlvUI8FLjIJhd18896Q1Ujh39RVaDZdbb2oxmJ3+05zixfm5pHhxfo4oXpyfI4oX5+dIjZDixfl5onhxfo4oXpyfI4oX5+comkZI8WIwWxQvfoBqxsvT3z+M/45N6JXojC21GLInHYnNyUiuyYG7cjx8shW0OtrK6ba6GoqXdpQULwafqDY0p3gxC7JaUqj2ZDH/oHgxn6nZESlezCZqTTyKF2u4mhmV4sVMmtbEonixhquZUSlezKTJWBQvBu+BWBcvu0qAhga/Kbn8+3/gm4GqkG73S4suensg4naeAq+cnpnqQ0aW1GvJ92mFcnOyfP12K2iDt5jWnOLFDIrWxqB4sZavGdEpXsygaG0Mihdr+ZoVneLFLJLWxaF4sY6tWZEpXswiaV0cihfr2MZiZIoXg1mPNfGiditSmuWDL5ehIn8jKtPrUZ3SjG8LE1CRktQjzczGZvxrz5kYPjRXO0eTLTGyI5HBW4zixQyANsSgeLEBssEuKF4MArShOcWLDZBN6ILixQSIFoegeLEYsAnhKV5MgGhxCIoXiwHHWHiKF4MJjwXxUt8AlJT4Z7U88VQcfAUL8Pjsnd2Q636mi5Iu574zEYNTD8cJcz0oKjQIPQabc8aL85NO8eL8HFG8OD9HFC/Oz5EaIcWL8/NE8eL8HFG8OD9HFC/Oz1E0jZDixWC2YkG8bN7i0oSLK74MxZOfw1sT1MyWnormtgP98cvT4IoDPJVTtNNVi0su9GDkiEA1F4PwY6g5xYvzk03x4vwcUbw4P0cUL87PEcVLdOSI4sX5eaJ4cX6OKF5UjkLbndb5WY3cCCleDLKPBfGi6rgsXBSH18bcj+WD1fbQnY+uT0g1y+WmNVcgKdF/7tgxPqSn+1BY6ENKskHoMdic4sX5Sad4cX6OKF6cnyOKF+fniOIlOnJE8eL8PFG8OD9HFC/Oz1E0jZDixWC2+rN4CV5iVNtQhtnJ83ug1VW8XPxBDmaNPA2T9/exlovBe0w1p3gxAaLFISheLAZsQniKFxMgWhyif4kXNc+zf87w5FIji58IJoSneDEBosUhKF4sBmxCeCeIF+v2ejQBEEOERIDiJSRcXU/uz+KlbYlR7hK8MOsrVCW3Tl/p8EayfcnRwNpGzNgQh4JtE+Arn6mtLeLSIoM3WGtzihdzOFoZheLFSrrmxKZ4MYejlVH6l3ixklRkY1O8RJa/nt4pXvRQiuw5FC+R5a+ndyeIFz3j5DnRQYDixWCe+rN4CSwxumfGg6hKSmj95i4gWvyzXM76xI3skimaivFKLRftuz055egjlJ8FpnDGi8E7zN+c4sUUjJYGoXixFK8pwSleTMFoaRCKF0vxmhbckHhxqzcMpg2FgXogQPHi/FuD4sX5OaJ4cX6OommEFC8Gs9Ufxcuq1S6sXuOGB2VYPfBFvDJBSRd1tE+ZzmhswZkfDIdr1/GyS5EPc+f430WxcK7BG6qH5hQv1nA1MyrFi5k0rYlF8WINVzOjUryYSdO6WIbEi3XDYuQgAhQvzr8dKF6cnyOKF+fnKJpGSPGiI1sPPjUfeyur8dtfnt/l7P4oXt5b7MYH8rP6qPuwYmh3xXSBk9a0IH/1FdrslhHDfbj0Io8OkjwlXAIUL+GSs68dxYt9rMPtieIlXHL2taN4sY+1kZ4oXozQs6ctxYs9nI30QvFihJ49bSle7OEcK73EpHh5+OnXcf9j87D6nUcRHyf7Hbcer765TP79ZVTX1GPOUdNx868v0h6PNfGyt8KFj9ctw+UFG1rJdCyeq3Ys+v3Xx+HoQ4bLbJdYeapE9jopXiLLX0/vFC96KEX2HIqXyPLX0zvFix5KkT+H4iXyOehrBBQvfRGK/OMUL5HPQV8joHjpixAfD4VATImXpqZm3HDnI4iLc2HBu59izbuPtYmX4h27ce4Vt+Lxv16PwYUDcPUfHsAxh0/D+afPijnxom6gBZ9+GCRe1L/4lxlN2lWLGUtOgqdxNEZypksozzVD51K8GMJnS2OKF1swG+qE4sUQPlsaU7zYgtlwJxQvhhFaHoDixXLEhjugeDGM0PIAFC+WI46pDmJKvHi9Pry2aBlOPPYQTJ51WQfx8sR/F2LT1p24/frLtBtg6adf4u+Pz8PzD93cQbxs27kHl1zzJ9x785XYf8Jo9MelRur6P/tiCy5Keru1qG77c+LydwdhsHsu4qQ4nlbbZTYr5NnxG4PixQ7KxvqgeDHGz47WFC92UDbWB8WLMX52taZ4sYt0+P1QvITPzq6WFC92kQ6/H4qX8NmxZVcCMSVeApff4vFg/2M6ipeb//wERgwpxCXnztVO27W7DKdd9gd88sY/28TLlRedigt+cTuu+vEZOHbmAdp5/VG8qOK6K1a5Udy8EC8esbVNvpz5mRv7lF+CGTO8mDK5vdAun1jWE6B4sZ6x0R4oXowStL49xYv1jI32QPFilKA97Sle7OFspBeKFyP07GlL8WIPZyO9ULwYoce2nQlQvLTWeLn+jocwdb+xOOeUozVGVTV1OPjEK/HFu4/jkWfeQHlFNb7duBWzZPnRhWfNbuPY1BLdMz4SZOqKSwrkNst1BFTKG4u8WPCWT/u7S/7PlbcEqJwIX0ueVkz3+ONcOHG22g+Sh10EEuPdiPZ7zS5WdvYT2Fxd9amWMKpZdT46STtTEFJfbrc/YypPPKwjoF5PlEAJ51CvR+qNbouHOQqHn11t4uW9Q4snut//2MUqUv2o55FXXpDsfk3iM1d/xtVLklt+6bXwNUk/NJvPVO8a4uX9XbMJr0nqvTyP2CZA8dIqXu68/xkU5ee2z3jZU46551+H1W8/qs14eerFRfB4vdrORqfOOaztrvm+oiGq76CcjCTtF8re6sa2N7rlUly3Ym/Pl5WdA+Rm86XVzsQPzE5GtN9rdvKyq6/gZ0FOWiJqZJt19aGThzMJqG8XXfImt7ahxZkD7C+jUp/0lEEJ41Af6DNS4rG3pimM1mxiF4GBWckorWxo+8LGrn7Zj34CWWkJaGjyorHZ3l0nw3vm67+u/nRmcmIc4uXDeE1dc3+6rH51LeoLm+z0RJRXNRq+LvVenkdsE6B4aRUvz8x7R2a0FOO26y7V7ohln32Jvzz0AuY9dpsmXjZs3o5Lzz0el197D156+P9hkBTgVUd/WGpUWeXGpuJGbN+hllj5XzLrPd+h1rUDab7ByEkbhZRkn7Zt9MgRFC6R+JXBpUaRoB5an1xqFBqvSJzNpUaRoB5an1xqFBqvSJ3NpUaRIq+/36hdaqQmBcTI9xdcaqT/fo7UmVxqFCny/bNfipdW8VJaXolTL/k9Hr33WgwpGoirb3oA0yfvi5/+6KQOxXX/+e9X8dnqb/GE7H6kvjntD+Jlwds+vP6mvMrlLsGH01fi2/z0Dnf7eR+mIGXT+TjyCC+Olh8e9hOgeLGfeag9UryESsz+8yle7Gceao8UL6ESi8z5FC+R4R5Kr1ErXkK5yCg/l+LF+QmkeHF+jqJphBQvreJFJe2Ntz/GvQ89j9q6Bhx92FTcdu2lSEiI7yBeVGHe8668DccfPQMXnzOnX4iXz1YAb320HrfOfF8oaJVdutzDf103FQeO358zXiL07KZ4iRD4ELqleAkBVoROpXiJEPgQuqV4CQFWBE+leIkgfJ1dU7zoBBXB0yheIghfZ9cULzpB8TRdBGJSvOgio/Ok/jDjRb3RvfqVB3H/sJ6XEf2y2IUbZl6kkwpPM5sAxYvZRM2PR/FiPlOzI1K8mE3U/HgUL+YztSIixYsVVM2NSfFiLk8rolG8WEHV3JgUL+byjPVoFC8G74D+Il5+8tyDeGRcz+Lllm8G4fK5xxmkxebhEqB4CZecfe0oXuxjHW5PFC/hkrOvHcWLfayN9NT/xYua+RvdNe0oXozc4fa0pXixh7ORXihejNBj284EKF4M3hP9Qbyo4rpPzvsWt054C1VJCV2IjN9TiyuKr8KBB3i51Mjg/RJuc4qXcMnZ147ixT7W4fZE8RIuOfvaUbzYx9pIT/1fvBih44y2FC/OyENvo6B4cX6OKF6cn6NoGiHFi8Fs9Qfxoorrzpfiuu6cJVh60Cqsy0/D2NJa5Fe5MHxXHlK2zgFa8lhc1+C9YqQ5xYsReva0pXixh7ORXihejNCzpy3Fiz2cjfZC8WKUoPXtKV6sZ2y0B4oXowStb0/xYj3jWOqB4sVgtqNZvCxc5EZZaRwqakqxKe81lOTUYMTWIUjYfrpGJSHBh4R4F4YN86KwEBjJ7aQN3i3hN6d4CZ+dXS0pXuwiHX4/FC/hs7OrJcWLXaSN9UPxYoyfHa0pXuygbKwPihdj/OxoTfFiB+XY6YPixWCuo1m8PP5kHLbuKMeLpz+PyuTENhLHrW3A0OW/wCUXeri0yOD9YVZzihezSFoXh+LFOrZmRaZ4MYukdXEoXqxja2ZkihczaVoTi+LFGq5mRqV4MZOmNbEoXqzhGqtRKV4MZj6axcuuEuDJdU/hgeHeLhReqToSk8aNQEqyQUBsbgoBihdTMFoahOLFUrymBKd4MQWjpUEoXizFa1pwihfTUFoWiOLFMrSmBaZ4MQ2lZYEoXixDG5OBKV4Mpj0axYtaYlRS4oIHZXhy0rP4Lje1C4UnysfguKmHGaTD5mYRoHgxi6R1cSherGNrVmSKF7NIWheH4sU6tmZGpngxk6Y1sSherOFqZlSKFzNpWhOL4sUarrEaleLFYOajUbyoJUbFu7/DCycvkiVGahcjtW1i+5HZ2IwXfWdgv31yDdJhc7MIULyYRdK6OBQv1rE1KzLFi1kkrYtD8WIdWzMjU7yYSdOaWBQv1nA1MyrFi5k0rYlF8WIN11iNSvFiMPPRKF7UEqM71j2IV4Z3XUekpMupH+UjYdsZrPFi8N4wsznFi5k0rYlF8WINVzOjUryYSdOaWBQv1nA1OyrFi9lEzY9H8WI+U7MjUryYTdT8eBQv5jON5YgULwazH43iRV3yqR/9A58PSuty9T+ePx7eisO1OTAsrmvw5jCxOcWLiTAtCkXxYhFYE8NSvJgI06JQFC8WgTU5LMWLyUAtCEfxYgFUk0NSvJgM1IJwFC8WQI3hkBQvBpMfreLl+vlP4ukf+DpcvZrt8lHBT5CT3fHfDSJicxMIULyYANHiEBQvFgM2ITzFiwkQLQ5B8WIxYJPCU7yYBNLCMBQvFsI1KTTFi0kgLQxD8WIh3BgMTfFiMOnRKF5Ucd2168vxv4Oewbp8/6wXJV3OWjwcI5PmYs5sD4oKDYJhc1MJULyYitOSYBQvlmA1NSjFi6k4LQlG8WIJVtODUryYjtT0gBQvpiM1PSDFi+lITQ9I8WI60pgOSPFiMP3RKF5Ucd0tW11Q81rcuUvgTahBXMV4eBpHc4mRwfvBquYUL1aRNS8uxYt5LK2KRPFiFVnz4lK8mMfSykgUL1bSNSc2xYs5HK2MQvFiJV1zYlO8mMORUfwEKF4M3gnRKF5Ucd2GBv9ORi5vAlpaXEhKbkaL17/EqLDQh5SudXcNkmJzIwQoXozQs6ctxYs9nI30QvFihJ49bSMlXtxyeV57LrFf9ELx4vw0Urw4P0cUL87PEcWL83MUTSOkeDGYrWgUL8GXPDArCeqN7vcVDWj2sLaLwdvBsuYUL5ahNS0wxYtpKC0LRPFiGVrTAkdKvJh2ATESiOLF+YmmeHF+jihenJ8jihfn5yiaRkjxYjBbFC8GAbK5LgIUL7owRfQkipeI4tfVOcWLLkwRPYniJaL4dXdO8aIbVcROpHiJGHrdHVO86EYVsRMpXiKGvl92TPFiMK0ULwYBsnkfBNSSMB8oXpx/o1C8OD9HFC/OzxHFi/NzpEaoxMvO8nqtLhwPZxKgeHFmXoJHRfHi/BxRvDg/R9E0QooXg9mieDEIkM11EaB40YUpoidRvEQUv67OKV50YYroSRQvEcWvu3NbZryw8I7ufHR3IsWLIXy2NKZ4sQWzoU4oXgzhY+NOBEwVL6ownXqdjKWD4iWWsh25a6V4iRx7vT1TvOglFbnzKF4ix15vzxQveklF9jxbxEtkLzHqe6d4cX4KKV6cnyOKF+fnKJpGaKp4iaYLN2usFC9mkWSc3ghQvDj//qB4cX6OKF6cnyOKF+fnSI2Q4sX5eaJ4cX6OKF6cnyOKF+fnKJpGSPFiMFsULwYBsrkuAhQvujBF9CSKl4ji19U5xYsuTBE9ieIlovh1d07xohtVxE6keIkYet0dU7zoRhWxEyleIoa+X3ZM8WIwrRQvBgGyuS4CFC+6MEX0JIqXiOLX1TnFiy5MET2J4iWi+HV3TvGiG1XETqR4iRh63R1TvOhGFbETKV4ihr5fdkzxYjCt/Ua8VDaiuUVV6eHhRAIUL07MSscxUbw4P0cUL87PEcWL83OkRkjx4vw8Ubw4P0cUL87PEcWL83MUTSOkeImmbHGsJEACJEACJEACJEACJBAmAZ+04zbgYcJjMxIgARIwQIDixQA8NiUBEiABEiABEiABEiABEuhPBGJxn9b+lD9eCwk4kwDFizPzwlGRAAnEAAG+tYuBJPMSSYAESIAESIAESIAEYp4AxUvM3wIEQAIkQAIkQAIkQAIkQAIkQAIkQAIkYBUBiheryEZB3FffXIb7H3sZ1TX1mHPUdNz864sQHxcXBSPvv0P8ePnX+PFv7ulwgcteewA5WRnw+Xz40z+ew2uSt/j4OFxx4Sk4//RZ/ReGw66srr4Bv73zEZTtrcLTf7+xbXQVlTW44c6HsOKL9RiYl41br70UB+w/Xnu8t8ccdnn9ZjgPP/26/F6bh9XvPNr2+4zPK2ek1+Px4qkXF+GZeW+jsroWk/YZhVuvuxRDigZqA+ztNYmvV/bl8IOPVmvvDbZsK8GQQfn47S/Ow8EHTNQGcN+jL0M9xwLH6BGDMf/fd2h//WrdZtx09+PYun03Ju07Cn+68acoGJhj38BjqKdln32Jvz/xCjZu3o70tFSce8rR8p7gZI1Ab+8V+Jpk302yuXgX/vrIi/hkxVrtPduhB+6H//ebS5CakowWjwf7H3NZh8H85ZafY/aRB/K9nn0p6tDT7u/34uSLf4cb5PfdaXMP7/N3Gl+TIpSoKO+W4iXKExju8It37Ma5V9yKx/96PQYXDsDVf3gAxxw+jR/kwwVqUrs33vkYSz5egzt/d3lbxIAMe2XhUjz7yrt4+J5fo6q6DhdedSce+fO1GDdqiEm9M0xPBHbtLsPPf/c3jBo+CCV7yjuIFyVjkpMScL28WH8k4uzWvzyJd164V/vQ39tjpG0ugaamZhFgjyAuzoUF736KNe8+1iZe+Lwyl3W40UrLK/GPf7+Ki86arb3u3PvQC1CvRf/84zXaf3t6TeLrVbjEQ2+nPrTfef/TmHv0QSJPRuO9ZStx85+fgPoCQP1OU3+eOH4kTj/e/8HEJf+Li3PD6/VhznnX4sqLT9Xa/uvJ1zRx87dbfxH6INiiTwIvzH8fI4cVYfLEMfi+rALn/fx23POHT9aJ5QAAETZJREFUK3Dg5H3Q23sFvib1ida0E5RwUb/zjjxkMtxuF35109+1fKnnyJ7SCpxzxS14+/l72/qLc7vhcrl6zV/byayQbFqeAoF+dsNfsXN3KS4+e44mXnr7ncbXJNPxx0xAipeYSXXHC33ivwuxaetO3H6937gv/VS+PXl8Hp5/6OYYJeKMy1bfBivrfu2V53YZkHpRmHv0dJx83KHaY3+RDy1eeZP8myvOccbg+/EoyiuqsfrrjUhJStQ+OAZmvKgPKdOP/xnmP3knivJzNQLn/uxWXHnRKTj8oB/0+NjMGfv3Y1qRuTT1Jum1Rctw4rGHYPKsyzqIFz6vIpOTvnpd+eV63HjXo1j4zN3o7TWJr1d9kbTucfW8mnLsj/HWf/+szV755Y334YwTjtA+TAYfarbLr2/5JxY955+xWVvXgCNOvwrvv/Q3ZKSnWjdARtYIXHH9vTJz+SCcOucw9PRe4dc/PZuvSRG8Xx57bgG+k/fdd9zwY3y7sRh/kNlhLz58C9/rRTAnga7nv/UhFsuXnokJCZg+ZR9NvPT2O+2lNxbzM5QD8haNQ6B4icasmTBm9a3ViCGFuOTcuVo09Y3+aZf9AZ+88U8TojNEuAT+9dRreOqFRVrz7Kx0+VZxJi4//0Tt73PPvx733HQF9pNvG9Xx2qIP8c7SFXjg9qvC7Y7tQiSglqwEixf1rdXxF1yH5W8+3Bbp9396DONHD5Upw9N7fOxHZx4XYs88XS+BwBTu4BkvfF7ppWfveY//dwG+2bBVvqn/mTaToqfXJL5e2ZuX4N6+/HazzIi9H+88/xftW/tLr/kTNm7ZgebmFgySWUu/vPR0TcKoWWX/e+cT/Ouua9qaH3fub3C/vD7tM2ZY5C6gn/fc3OLBss++wG1/fQrPP3iztty1p/cKf/jVhXxNisD9oL6g2bB5h4jJf+C6n/9Q+1JGLU3+ybV/lmVHSTJjLA6HTZ+E6+UxJSn5Xs/eJKlZSRdd/Uf854Eb8ae/P4sZ0yZo4qW332nPvfouP0PZm6Z+0xvFS79JZWgXcv0dD2HqfmNxjqwLVkdVTR0OPvFKfPHu49q0YR6RIaDezFbX1iM7Mx3rv9uGX8i3i1dfdgZOOu4QHH3WNXj03uswSqYXq+PdpSvx7xfelBeL30VmsDHYa2fxUrxjDy74xe1Y8sr9bTT++MAzsuY+BafMPqzHx9SHFR7WEOhOvPB5ZQ1rI1HVc0ctl3zmH7/Xlh319pr0u7se4euVEdhhtm2U5Xs/+uUduOyHJ2i1J9RRLe8V1HuEBPlmWC2Lvf6OBzHvsdvx+epvZanlV7j35ivbejtdvsxRHzRnTJ0Q5gjYrDcCSvK//tZHSE5OxO+uukBec/yzYXt6r6BmWvT0esXXJGvuNbXsS0mxJnlvp5ZY/uonZyFB6r2oQy0Ry8vJ0pYj/eHux5A/IAe3Sc0rvtezJhc9RVVLwFSdS/Vz/e0PtYmXl/+3pMffaSqv/Axlb576S28UL/0lkyFex533P6MtjWib8SJ1K+aefx1Wv/1oiJF4upUEVBFDtU7+zt9ejtMu/T1uk6VhgRkvamrkG29/LDVffmPlEBg7iEBn8aIKhB4jQqzzjJfhQwpw9slH9fhYYBYT4ZpPoDvx0rkXPq/M5x5KRDVT7OJf/VErYhhYdtfbaxJfr0Kha8656nl01e/vlxpiQ/Gry8/sMagqBn/CMTO0b+rVB5XgGS+zf3gt7pa6I/tPGG3OoBilCwG1FEwtX7nu9gdx7qnH4OyTjuzxvcI9N/2Mr0kRuofU77x7H3pe6oZ4tRl+nY9VX23Atbc9KDPL7uV7PRtztOiDz7Dwvc/aalEFixc1o7yn32lqdh8/Q9mYqH7UFcVLP0pmKJfyzLx3tDWmyq6rQ1XIVzVD5j12WyhheK7FBP4p9URUfZHf/+pHWmG2Yw6bqs1+UcdfH34RDY1N+O0vz7d4FAwfINBZvKh/P/SUX+DlR29F4UB/jZcfXnkbfizfEB9z+NReHyNVawjoES98XlnDXk9U9fvskmvuwk8uOEn7wB44entN4uuVHrLmnaN2n1IfAnOzM7TXnt6Oi391F34oH/hHDS+S+i/3481n79ZOV7vAHXLSz7FYZgNmZaSZNzhG6pbAI8+8oc2SVR/qe3uv0NvrFdFaS0DViVMbWSyed1+XjtSMsdv+9h9thzC+17M2D8HR1WvRNxuKpbZLvPbPasa5mpF06pzDcdZJR/T4O0196Wn3ZyivjI/rEey7N6zqieLFKrIOj6umNp56ye9l6cq12laeV9/0AKZP3hc//dFJDh95/x6eMuxqi9X8Adla7YMrf/u3tp0K3lq8HI8++wYevvs3sjSsVqbp/xF/ueVKTJ00rn9DcdDVdSde7rjvP/DIt45qfbZ6/Hd/fETb1UhtGdnbYw66rH41lO7EC59XzkixmiGmaoSob+UDAlmNLDkpSQRzVY+vSXy9si9/qh6FWsKinkc3XXOR7LLi71stLVIfSFRtsaMPnaL9fntr8edQSyvn//tOrSbZKZfcKMuSjsccqW/1r6fm44tvNuExWR7Lw1wC6gPYe/JeYfqUfZEpM4227dyjzU5SNeFU/bDe3ivwNcncXPQWTe1qNGJYofaljFrOr9jX1TdqdflUjRc1S2y07JRYtrdKW7J3oLwHV4X5+V7PvhxVVtWiuaWlrcPbRX5N+8E4rUi1yk9Pv9P4mmRfjvpbTxQv/S2jIVyPMrZq6qPafeBomUlx27WXypsrv/XlERkCD/3ndaiiXbV19SgqGCDfCp+IE2cdrA1GvSG+55//xcsLlmh2Xq27v/icOZEZaIz22p14UR8mb7jjYXy6ci0KZfme+ob4kAP20wj19liMIrT8srsTL3xeWY5dVwfPvvKu9uGj86HqVCmB3NtrEl+vdCE2fNJGKQKqPmx0PlQNkCsuPFnb1Uh9aFQ76o0bNUSE83myvfQI7XT1ZYESz6p+z4RxI3DXjT/R6vfwMJ+AqomkZirXywf5nKwMTWSqHKn6O729V+Brkvm56Cmi2k1P/eytrEFSUgIOO3ASbpAZymom2QcfrcY9//qv7GJZLtJS8ie78altppXc5Hs9+3LUuafgpUZ9/U7ja1Lk8hTNPVO8RHP2OHYSIAESIAESIAESIAESIAESIAESIAFHE6B4cXR6ODgSIAESIAESIAESIAESIAFLCLB4hiVYGZQESKArAYoX3hUkQAIkQAIkQAIkQAIkQAIkQAIkQAIkYBEBiheLwDIsCZAACZAACZAACZAACZAACZAACZAACVC88B4gARIgARIgARIgARIgARIgARIgARIgAYsIULxYBJZhSYAESIAESIAESIAESIAESIAESIAESIDihfcACZAACZAACZAACZAACZAACZAACZAACVhEgOLFIrAMSwIkQAIkQAIkQAIkQAIkQAIkQAIkQAIUL7wHSIAESIAESIAE+iDAPVe7AvLJP7l455AACZAACZAACZBAnwQoXvpExBNIgARIgARIgARIgARIgARIgARIgARIIDwCFC/hcWMrEiABEiABEiABEogRApzxFCOJ5mWSAAmQAAlYRIDixSKwDEsCJEACJEACJEACJEACJEACJEACJEACFC+8B0iABEiABEiABEiABEiABEiABEiABEjAIgIULxaBZVgSIAESIAESIAESIAESIAESIAESIAESoHjhPUACJEACJEACJEACJEACJEACJEACJEACFhGgeLEILMOSAAmQAAmQAAmQQP8hwAK7/SeX4V4J74FwybEdCZAACVC88B4gARIgARIgARIgARIgARIgARIgARIgAYsIULxYBJZhSYAE7CDAb9/soMw+SIAESIAESIAESIAESIAEwidA8RI+O7YkARIgARIgARIgARIgARIgARIgARKIEQLhfu1L8RIjNwgvkwRIgARIgARIgARIgARIgARIgARIwH4CFC/2M2ePJEACJEACJEACJEACJEACJEACJEACMUKA4iVGEs3LJAESIAESIAESIAESIAESIAESIAESsJ8AxYv9zPvuMdyFY31H5hkkQAIkQAIkQAIkQAIkQAIkQAIkYBGB/vdh1iekXAZpUbwYBMjmJEACJEACJEACJEACJEACJEACJEACJNATAYoX3hskQAIkQAIkQAIkQAIkQAIkQAIkQAIkYBEBiheLwDIsCZAACZAACZAACZAACZAACZAACZAACVC88B4gARIgARIgARIgARIgARIgARIgARIgAYsIULxYBJZhSYAESIAESIAESIAESIAESIAESIAESIDihfcACZAACZAACZAACZAACZAACZAACZAACVhEgOLFIrAMSwIkQAIkQAIkQAIkQAIkQAIkQAIkQAIUL7wHSIAESIAESIAESIAESIAESIAESIAESMAiAhQvFoFlWBIgARIgARIgARIgARIgARIgARIgARKgeOE9QAIkQAIkQAIkQAIkQAIkQAIkQAIkQAIWEaB4sQgsw5IACZAACZAACZAACZAACZAACZAACZAAxQvvARIgARIgARIgARIgARIgARIgARIgARKwiADFi0VgGZYESIAESIAESIAESIAESIAESIAESIAEKF54D5AACZAACZAACZAACZAACZAACZAACZCARQQoXiwCy7AkQAIkQAIkQAIkQAIkQAIkQAIkQAIkQPHCe4AESIAESIAESIAESIAESIAESIAESIAELCJA8WIRWIYlARIgARIgARIgARIgARIgARIgARIgAYoX3gMkQAIkQAIkQAIkQAIkQAIkQAIkQAIkYBEBiheLwDIsCZAACZAACZAACZAACZAACZAACZAACVC88B4gARIgARIgARIgARIgARIgARIgARIgAYsIULxYBJZhSYAESIAESIAESIAESIAESIAEYo+ATy7ZFXuXzSvuhQDFC28PEiABEiABEiABEiABEiABEiABEiABErCIAMWLRWAZlgRIgARIgARIgARIwAkE+N2zE7LAMZAACZBALBOgeInl7PPaSYAESIAESIAESIAESIAESIAESIAELCVA8WIpXgYnARIgARIgARIgARIgARIgARIgARKIZQIUL7GcfV47CZAACZAACZAACZAACZAACZAACZCApQQoXizFy+AkQAIkQAIkQAIkQAIkQAIkQAIkQAKxTIDiJZazz2snARIgARIgARIgARIgARIgARIgARKwlADFi6V4GZwESIAESIAESIAESIAESIAESIAESCCWCVC8xHL2ee0kQAIkQAIkQAIkQAIkQAIkQAIkQAKWEqB4sRRv7AX3ySW7Yu+yecUkQAIkQAIkQAIkQAIkQAIkQAIk0C0BihfeGCRAAiRAAiRAAiRAAiRAAiRAAiRAAiRgEQGKF4vAMiwJkAAJkAAJkAAJkAAJkAAJkAAJkAAJULzwHiABEiABEiABEiABEiABEiABEiABUwh4JYrblEgM0n8IULz0n1zySkiABEiABEiABEiABEiABEiABEiABBxGgOLFYQnhcEiABEiABEiABEiABEiABEjAVgKcpGErbnYWewQoXmIv57xiEiABEiABowT4BtUoQbYnARIgARIgARIggZghQPESM6nmhZIACZAACZAACZAACZAACZAACZAACdhNgOLFbuLsjwRIgARIgARIgARIgARIgARIgARIIGYIULzETKp5oSRAAiRAAiRAAiRAAiRAAiRAAiRAAnYToHixmzj7IwESIAESIAESIAESIAESIAESIAESiBkCFC8xk2peqKkEWFjTVJwMRgIkQAIkQAIkQAIkQAIkQAL9lQDFS3/NLK+LBEiABEiABEiABEiABEiABEiABEgg4gQoXiKeAg6ABEiABEiABEiABEiABEiABEiABEigvxL4/0I+5FsfKefYAAAAAElFTkSuQmCC", + "text/html": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = go.Figure()\n", + "xs = list(range(len(summ)))\n", + "fig.add_trace(\n", + "go.Scatter(\n", + " x=xs,\n", + " y=summ[\"median\"],\n", + " name=\"estimate\",\n", + " mode='markers',\n", + " error_y=dict(\n", + " type='data',\n", + " symmetric=False,\n", + " array=summ[HDI_HIGH]-summ[\"median\"],\n", + " arrayminus=summ[\"median\"]-summ[HDI_LOW])\n", + " )\n", + " \n", + ")\n", + "fig.add_trace(\n", + " go.Scatter(\n", + " x=xs,\n", + " y=summ[\"s\"],\n", + " name=\"source\",\n", + " mode='markers',\n", + " )\n", + ")\n", + "fig.add_trace(go.Scatter(\n", + " x=xs,\n", + " y=summ[\"ce\"],\n", + " name=\"countries\",\n", + " mode='markers',\n", + " ))\n", + "fig.update_yaxes(type=\"log\")\n", + "\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "f101a2b6-f784-4864-a1e1-2bba1681cb35", + "metadata": {}, + "source": [ + "## Conclusion\n", + "\n", + "In this section, we first saw how to visually inspect the differences between emissions of different countries, both from a source level and country report level. We identified a couple of sectors in which emissions diverge between both methods of reporting.\n", + "\n", + "Finally, we saw how to use Bayesian analysis to start combining multiple data sources together. This example only considers two estimates. See as an exercise what happens with different distributions, such as Gaussian distributions for example." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e01c4e2d-3bb9-40dd-ae69-1136cb558137", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/_sources/uncertainty_drilldown.ipynb b/_sources/uncertainty_drilldown.ipynb new file mode 100644 index 0000000..e29adb3 --- /dev/null +++ b/_sources/uncertainty_drilldown.ipynb @@ -0,0 +1,3700 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "2dfde7f4-f6d7-4377-9959-e00573f0f636", + "metadata": {}, + "source": [ + "# Uncertainty drilldown\n", + "\n", + "We have explored various ways to reduce the uncertainty in the emissions data. Now we look at the question: **if we want to obtain more precise estimates, which sector should we focus on?**\n", + "\n", + "This section presents a simple framework to get started. You will see that the initial suspects are not what you think.\n", + "\n", + "For now, let's assume that picking each sector in any country is just as easy. In practice of course, the choice of analysis is driven by the data available. Nevertheless, it is a good baseline to understand how hard it would be to reduce this uncertainty.\n", + "\n", + "The source emissions dataset contains _qualitative confidence_ for each source, based on expert assessment of the data. The values are very low confidence, low confidence, medium, high and very high. In our simple baseline, we are going to assume that each of these confidence assessment correspond to a numerical value of uncertainty." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "488a4f87-502c-466e-a32d-a47d1c87dbdb", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "51a0a8ec-b228-4079-9ba5-316f9b2e3bfb", + "metadata": {}, + "outputs": [], + "source": [ + "import polars as pl\n", + "import plotly.express as px\n", + "import scipy as sp\n", + "\n", + "from ctrace.constants import *\n", + "import ctrace as ct\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "f4936172-3741-4ae4-9b8f-3ef7b3a3c016", + "metadata": {}, + "outputs": [], + "source": [ + "year = 2022\n", + "gas = \"co2e_100yr\"\n", + "gas_conf = CONF_TOTAL_CO2E_100YRGWP\n", + "c_gas_conf = C(gas_conf)\n", + "sdf_gy = ct.read_source_emissions(year=year).filter(c_gas == gas)" + ] + }, + { + "cell_type": "markdown", + "id": "30f5bf57-ab6a-49ab-afce-90456e2ef49e", + "metadata": {}, + "source": [ + "The confidence intervals are provided for each source. To reduce the workload, we are aggregating first by confidence interval, country, sector and subsector. This is all we need to consider for this analysis and it makes the analysis significantly faster.\n", + "\n", + "```{note} Technical\n", + "All the aggregation keys are enumerations or categories. This makes operations very fast because Polars knows exactly how many key to expect.\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "5052b095-fd7b-45df-819a-7c1b13ead32a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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"COD""removals""medium""forestry_and_l…267-4.6924e9
"AGO""removals""medium""forestry_and_l…177-3.4949e9
"MOZ""removals""medium""forestry_and_l…141-3.0537e9
"ZMB""removals""medium""forestry_and_l…126-2.7422e9
………………
"BRA""forest-land-cl…"low""forestry_and_l…55713.1661e9
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"COD""forest-land-fi…"low""forestry_and_l…2193.6139e9
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"CHN""electricity-ge…"medium""power"12254.5421e9
" + ], + "text/plain": [ + "shape: (5_585, 6)\n", + "┌──────────────┬──────────────────┬──────────────────┬──────────────────┬───────┬──────────────────┐\n", + "│ iso3_country ┆ ct_file ┆ conf_total_co2e_ ┆ ct_package ┆ count ┆ emissions_quanti │\n", + "│ --- ┆ --- ┆ 100yrgwp ┆ --- ┆ --- ┆ ty │\n", + "│ enum ┆ cat ┆ --- ┆ cat ┆ u32 ┆ --- │\n", + "│ ┆ ┆ cat ┆ ┆ ┆ f64 │\n", + "╞══════════════╪══════════════════╪══════════════════╪══════════════════╪═══════╪══════════════════╡\n", + "│ BRA ┆ removals ┆ medium ┆ forestry_and_lan ┆ 5597 ┆ -4.8601e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ COD ┆ removals ┆ medium ┆ forestry_and_lan ┆ 267 ┆ -4.6924e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ AGO ┆ removals ┆ medium ┆ forestry_and_lan ┆ 177 ┆ -3.4949e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ MOZ ┆ removals ┆ medium ┆ forestry_and_lan ┆ 141 ┆ -3.0537e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ ZMB ┆ removals ┆ medium ┆ forestry_and_lan ┆ 126 ┆ -2.7422e9 │\n", + "│ ┆ ┆ ┆ d_use ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ BRA ┆ forest-land-clea ┆ low ┆ forestry_and_lan ┆ 5571 ┆ 3.1661e9 │\n", + "│ ┆ ring ┆ ┆ d_use ┆ ┆ │\n", + "│ AGO ┆ forest-land-fire ┆ low ┆ forestry_and_lan ┆ 170 ┆ 3.3166e9 │\n", + "│ ┆ s ┆ ┆ d_use ┆ ┆ │\n", + "│ COD ┆ forest-land-fire ┆ low ┆ forestry_and_lan ┆ 219 ┆ 3.6139e9 │\n", + "│ ┆ s ┆ ┆ d_use ┆ ┆ │\n", + "│ MOZ ┆ forest-land-fire ┆ low ┆ forestry_and_lan ┆ 141 ┆ 3.7217e9 │\n", + "│ ┆ s ┆ ┆ d_use ┆ ┆ │\n", + "│ CHN ┆ electricity-gene ┆ medium ┆ power ┆ 1225 ┆ 4.5421e9 │\n", + "│ ┆ ration ┆ ┆ ┆ ┆ │\n", + "└──────────────┴──────────────────┴──────────────────┴──────────────────┴───────┴──────────────────┘" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df= (sdf_gy\n", + " .group_by([c_iso3_country, c_ct_file, c_gas_conf, c_ct_package])\n", + " .agg(pl.len().alias(\"count\"), c_emissions_quantity.sum())\n", + " .sort(by=c_emissions_quantity)\n", + " .collect()\n", + ")\n", + "df" + ] + }, + { + "cell_type": "markdown", + "id": "d4195754-d956-43f0-99fb-ea19bf87835c", + "metadata": {}, + "source": [ + "We are going to use a very simple mapping from qualitative confidence assessments to quantitative error bounds. We are going to assume that a very high confidence is around 1% standard deviation and that a very low confidence is around 30-50% standard deviation, with a geometric progression in between.\n", + "\n", + "By default, if no confidence is provided, we will assume it is very low. We will err on the side of caution.\n", + "\n", + "```{note}\n", + "Try different numbers. The results of this ananlysis are rather stable to different choices.\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c7f7bca7-e8fb-4eca-8e1c-2e5e8fd6140a", + "metadata": {}, + "outputs": [], + "source": [ + "margins = {\"very high\": 0.01, \"high\": 0.03,\"medium\":0.07, \"low\": 0.15, \"very low\": 0.3}" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a2e28a4f-ede7-4ee1-8ed1-9c9e0ac4fd48", + "metadata": {}, + "outputs": [], + "source": [ + "ERR_MARGIN = \"err_margin\"\n", + "\n", + "df = (df.with_columns(\n", + " (c_gas_conf.replace(margins, return_dtype=pl.Float32, default=margins[\"very low\"])\n", + " * c_emissions_quantity).alias(ERR_MARGIN)\n", + ")\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "2142c5b9-0534-4ecc-bed8-4cbfe3de14d4", + "metadata": {}, + "source": [ + "What is the total error? It is around 18%, which is reasonable (the IPCC reports provide a 10% standard deviation).\n", + "\n", + "TODO cite WGI\n", + "\n", + "```{admonition} TODO\n", + "The count does not match the number of sources?\n", + "```\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "7c350c61-0550-44fa-8396-1528db3ab538", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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emissions_quantityerr_margincount
f64f64u32
3.7621e107.7654e91015480
" + ], + "text/plain": [ + "shape: (1, 3)\n", + "┌────────────────────┬────────────┬─────────┐\n", + "│ emissions_quantity ┆ err_margin ┆ count │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ f64 ┆ f64 ┆ u32 │\n", + "╞════════════════════╪════════════╪═════════╡\n", + "│ 3.7621e10 ┆ 7.7654e9 ┆ 1015480 │\n", + "└────────────────────┴────────────┴─────────┘" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.select(c_emissions_quantity.sum(), C(ERR_MARGIN).sum(), C(\"count\").sum())" + ] + }, + { + "cell_type": "markdown", + "id": "3de3fc99-8cdc-42ad-81f3-8fe6a8d84e07", + "metadata": {}, + "source": [ + "Let us look at the error margins based on this scheme. As you could expect,\n", + "the forestry and land use sector has huge errors.\n", + "\n", + "However, I was not expecting coal mining and oil&gas transport to have such uncertainties. This is mostly related to fugitive (but significant) emissions of methane from coal mines and oil installations. This should be partially addressed in the coming 2 years with a number of satellites that will explicitly track methane (TODO cite).\n", + "\n", + "The agriculture sector is also a big candidate, but interestingly rice cultivation is not so much of an issue. Fires to croplands and enteric fermentation (cow burps) are much more uncertain.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "31444db2-d5c9-4881-9e48-364cf1151c8c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + " \n", + " " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

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indexiso3_countryct_filect_packageemissions_quantityerr_margin
u32enumcatcatf64f64
0"MOZ""forest-land-fi…"forestry_and_l…3.7217e95.5825e8
1"COD""forest-land-fi…"forestry_and_l…3.6139e95.4209e8
2"AGO""forest-land-fi…"forestry_and_l…3.3166e94.9750e8
3"BRA""forest-land-cl…"forestry_and_l…3.1661e94.7491e8
4"ZMB""forest-land-fi…"forestry_and_l…3.1439e94.7159e8
5"AUS""forest-land-fi…"forestry_and_l…2.4736e93.7104e8
6"CHN""electricity-ge…"power"4.5421e93.1795e8
7"CAF""forest-land-fi…"forestry_and_l…2.0777e93.1165e8
8"USA""forest-land-cl…"forestry_and_l…1.1858e91.7787e8
9"BRA""forest-land-fi…"forestry_and_l…1.1465e91.7198e8
" + ], + "text/plain": [ + "shape: (10, 6)\n", + "┌───────┬──────────────┬────────────────────┬────────────────────┬────────────────────┬────────────┐\n", + "│ index ┆ iso3_country ┆ ct_file ┆ ct_package ┆ emissions_quantity ┆ err_margin │\n", + "│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ u32 ┆ enum ┆ cat ┆ cat ┆ f64 ┆ f64 │\n", + "╞═══════╪══════════════╪════════════════════╪════════════════════╪════════════════════╪════════════╡\n", + "│ 0 ┆ MOZ ┆ forest-land-fires ┆ forestry_and_land_ ┆ 3.7217e9 ┆ 5.5825e8 │\n", + "│ ┆ ┆ ┆ use ┆ ┆ │\n", + "│ 1 ┆ COD ┆ forest-land-fires ┆ forestry_and_land_ ┆ 3.6139e9 ┆ 5.4209e8 │\n", + "│ ┆ ┆ ┆ use ┆ ┆ │\n", + "│ 2 ┆ AGO ┆ forest-land-fires ┆ forestry_and_land_ ┆ 3.3166e9 ┆ 4.9750e8 │\n", + "│ ┆ ┆ ┆ use ┆ ┆ │\n", + "│ 3 ┆ BRA ┆ forest-land-cleari ┆ forestry_and_land_ ┆ 3.1661e9 ┆ 4.7491e8 │\n", + "│ ┆ ┆ ng ┆ use ┆ ┆ │\n", + "│ 4 ┆ ZMB ┆ forest-land-fires ┆ forestry_and_land_ ┆ 3.1439e9 ┆ 4.7159e8 │\n", + "│ ┆ ┆ ┆ use ┆ ┆ │\n", + "│ 5 ┆ AUS ┆ forest-land-fires ┆ forestry_and_land_ ┆ 2.4736e9 ┆ 3.7104e8 │\n", + "│ ┆ ┆ ┆ use ┆ ┆ │\n", + "│ 6 ┆ CHN ┆ electricity-genera ┆ power ┆ 4.5421e9 ┆ 3.1795e8 │\n", + "│ ┆ ┆ tion ┆ ┆ ┆ │\n", + "│ 7 ┆ CAF ┆ forest-land-fires ┆ forestry_and_land_ ┆ 2.0777e9 ┆ 3.1165e8 │\n", + "│ ┆ ┆ ┆ use ┆ ┆ │\n", + "│ 8 ┆ USA ┆ forest-land-cleari ┆ forestry_and_land_ ┆ 1.1858e9 ┆ 1.7787e8 │\n", + "│ ┆ ┆ ng ┆ use ┆ ┆ │\n", + "│ 9 ┆ BRA ┆ forest-land-fires ┆ forestry_and_land_ ┆ 1.1465e9 ┆ 1.7198e8 │\n", + "│ ┆ ┆ ┆ use ┆ ┆ │\n", + "└───────┴──────────────┴────────────────────┴────────────────────┴────────────────────┴────────────┘" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rankings = (df.group_by(c_iso3_country, c_ct_file, c_ct_package)\n", + " .agg(c_emissions_quantity.sum(), C(ERR_MARGIN).sum())\n", + " .sort(by=ERR_MARGIN, descending=True)\n", + " .with_row_index()\n", + ")\n", + "rankings.head(10)" + ] + }, + { + "cell_type": "markdown", + "id": "e51509ea-1614-4a2a-a8ad-cc02635395cf", + "metadata": {}, + "source": [ + "Grouping by country, we have have a discussion about which sectors are the most uncertain.\n", + "\n", + "In the US, road transportation is a surprising source of uncertainty that should be relatively easy to address." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "4f8d9208-d60e-4dc7-bc3e-2445289790a0", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=power
iso3_country=%{x}
err_margin=%{y}", + "hovertext": [ + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation", + "electricity-generation" + ], + "legendgroup": "power", + "marker": { + "color": "#636efa", + "pattern": { + "shape": "" + } + }, + "name": "power", + "offsetgroup": "power", + "orientation": "v", + "showlegend": true, + "textposition": "auto", + "type": "bar", + "x": [ + "CHN", + "USA", + "IND", + "RUS", + "JPN", + "SAU", + "IDN", + "MEX", + "AUS", + "BRA" + ], + "xaxis": "x", + "y": [ + 317945671.3536456, + 106759660.57060659, + 84936460.36161482, + 37332750.158943236, + 31008570.225693285, + 17725890.075467527, + 16240910.069145262, + 11348930.120311677, + 9922010.042242706, + 3188480.0137132406 + ], + "yaxis": "y" + }, + { + "alignmentgroup": "True", + "hovertemplate": "%{hovertext}

ct_package=fossil_fuel_operations
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_plot_data = (rankings\n", + " .filter(~(c_ct_package == \"forestry_and_land_use\")))\n", + "_country_order = (_plot_data\n", + " .group_by(c_iso3_country)\n", + " .agg(C(ERR_MARGIN).sum())\n", + " .sort(by=ERR_MARGIN, descending=True)[ISO3_COUNTRY].to_list())\n", + "px.bar(_plot_data.filter(c_iso3_country.is_in(_country_order[:10])), x=ISO3_COUNTRY,\n", + " y=ERR_MARGIN, \n", + " color=CT_PACKAGE,\n", + " hover_name=CT_FILE, \n", + " category_orders = {ISO3_COUNTRY: _country_order},\n", + " log_y=False)" + ] + }, + { + "cell_type": "markdown", + "id": "9a87f1d3-05c8-43f0-a871-4d1f77c04666", + "metadata": {}, + "source": [ + "## Conclusion\n", + "\n", + "We saw in this notebook how to define levels of uncertainty from qualitative assessments. This gives us areas of focus: electrical generation in China, transportation in the US, ...\n", + "\n", + "It also underlines - again - the complexity around forestry and land uses. Vegetation is both the largest sink of carbon at scale and the least understood. There is much to understand in that area." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "55893d8a-0d99-44d1-a8e4-115a8b061d1e", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css b/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css new file mode 100644 index 0000000..eb19f69 --- /dev/null +++ b/_sphinx_design_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css @@ -0,0 +1 @@ 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0em; +} +aside.footnote > p:last-of-type:after, +div.citation > p:last-of-type:after { + content: ""; + clear: both; +} + +dl.field-list { + display: grid; + grid-template-columns: fit-content(30%) auto; +} + +dl.field-list > dt { + font-weight: bold; + word-break: break-word; + padding-left: 0.5em; + padding-right: 5px; +} + +dl.field-list > dd { + padding-left: 0.5em; + margin-top: 0em; + margin-left: 0em; + margin-bottom: 0em; +} + +dl { + margin-bottom: 15px; +} + +dd > :first-child { + margin-top: 0px; +} + +dd ul, dd table { + margin-bottom: 10px; +} + +dd { + margin-top: 3px; + margin-bottom: 10px; + margin-left: 30px; +} + +.sig dd { + margin-top: 0px; + margin-bottom: 0px; +} + +.sig dl { + margin-top: 0px; + margin-bottom: 0px; +} + +dl > dd:last-child, +dl > dd:last-child > :last-child { + margin-bottom: 0; +} + +dt:target, span.highlighted { + background-color: #fbe54e; +} + +rect.highlighted { + fill: #fbe54e; +} + +dl.glossary dt { + font-weight: bold; + font-size: 1.1em; 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exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return o}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),c=n.n(e);function a(t){try{return document.execCommand(t)}catch(t){return}}var f=function(t){t=c()(t);return a("cut"),t};var l=function(t){var e,n,o,r=1 + + + + diff --git a/_static/copybutton.css b/_static/copybutton.css new file mode 100644 index 0000000..f1916ec --- /dev/null +++ b/_static/copybutton.css @@ -0,0 +1,94 @@ +/* Copy buttons */ +button.copybtn { + position: absolute; + display: flex; + top: .3em; + right: .3em; + width: 1.7em; + height: 1.7em; + opacity: 0; + transition: opacity 0.3s, border .3s, background-color .3s; + user-select: none; + padding: 0; + border: none; + outline: none; + border-radius: 0.4em; + /* The colors that GitHub uses */ + border: #1b1f2426 1px solid; + background-color: #f6f8fa; + color: #57606a; +} + +button.copybtn.success { + border-color: #22863a; + color: #22863a; +} + +button.copybtn svg { + stroke: currentColor; + width: 1.5em; + height: 1.5em; + padding: 0.1em; +} + +div.highlight { + position: relative; +} + +/* Show the copybutton */ +.highlight:hover button.copybtn, button.copybtn.success { + opacity: 1; +} + +.highlight button.copybtn:hover { + background-color: rgb(235, 235, 235); +} + +.highlight button.copybtn:active { + background-color: rgb(187, 187, 187); +} + +/** + * A minimal CSS-only tooltip copied from: + * https://codepen.io/mildrenben/pen/rVBrpK + * + * To use, write HTML like the following: + * + *

Short

+ */ + .o-tooltip--left { + position: relative; + } + + .o-tooltip--left:after { + opacity: 0; + visibility: hidden; + position: absolute; + content: attr(data-tooltip); + padding: .2em; + font-size: .8em; + left: -.2em; + background: grey; + color: white; + white-space: nowrap; + z-index: 2; + border-radius: 2px; + transform: translateX(-102%) translateY(0); + transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); +} + +.o-tooltip--left:hover:after { + display: block; + opacity: 1; + visibility: visible; + transform: translateX(-100%) translateY(0); + transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); + transition-delay: .5s; +} + +/* By default the copy button shouldn't show up when printing a page */ +@media print { + button.copybtn { + display: none; + } +} diff --git a/_static/copybutton.js b/_static/copybutton.js new file mode 100644 index 0000000..2ea7ff3 --- /dev/null +++ b/_static/copybutton.js @@ -0,0 +1,248 @@ +// Localization support +const messages = { + 'en': { + 'copy': 'Copy', + 'copy_to_clipboard': 'Copy to clipboard', + 'copy_success': 'Copied!', + 'copy_failure': 'Failed to copy', + }, + 'es' : { + 'copy': 'Copiar', + 'copy_to_clipboard': 'Copiar al portapapeles', + 'copy_success': '¡Copiado!', + 'copy_failure': 'Error al copiar', + }, + 'de' : { + 'copy': 'Kopieren', + 'copy_to_clipboard': 'In die Zwischenablage kopieren', + 'copy_success': 'Kopiert!', + 'copy_failure': 'Fehler beim Kopieren', + }, + 'fr' : { + 'copy': 'Copier', + 'copy_to_clipboard': 'Copier dans le presse-papier', + 'copy_success': 'Copié !', + 'copy_failure': 'Échec de la copie', + }, + 'ru': { + 'copy': 'Скопировать', + 'copy_to_clipboard': 'Скопировать в буфер', + 'copy_success': 'Скопировано!', + 'copy_failure': 'Не удалось скопировать', + }, + 'zh-CN': { + 'copy': '复制', + 'copy_to_clipboard': '复制到剪贴板', + 'copy_success': '复制成功!', + 'copy_failure': '复制失败', + }, + 'it' : { + 'copy': 'Copiare', + 'copy_to_clipboard': 'Copiato negli appunti', + 'copy_success': 'Copiato!', + 'copy_failure': 'Errore durante la copia', + } +} + +let locale = 'en' +if( document.documentElement.lang !== undefined + && messages[document.documentElement.lang] !== undefined ) { + locale = document.documentElement.lang +} + +let doc_url_root = DOCUMENTATION_OPTIONS.URL_ROOT; +if (doc_url_root == '#') { + doc_url_root = ''; +} + +/** + * SVG files for our copy buttons + */ +let iconCheck = ` + ${messages[locale]['copy_success']} + + +` + +// If the user specified their own SVG use that, otherwise use the default +let iconCopy = ``; +if (!iconCopy) { + iconCopy = ` + ${messages[locale]['copy_to_clipboard']} + + + +` +} + +/** + * Set up copy/paste for code blocks + */ + +const runWhenDOMLoaded = cb => { + if (document.readyState != 'loading') { + cb() + } else if (document.addEventListener) { + document.addEventListener('DOMContentLoaded', cb) + } else { + document.attachEvent('onreadystatechange', function() { + if (document.readyState == 'complete') cb() + }) + } +} + +const codeCellId = index => `codecell${index}` + +// Clears selected text since ClipboardJS will select the text when copying +const clearSelection = () => { + if (window.getSelection) { + window.getSelection().removeAllRanges() + } else if (document.selection) { + document.selection.empty() + } +} + +// Changes tooltip text for a moment, then changes it back +// We want the timeout of our `success` class to be a bit shorter than the +// tooltip and icon change, so that we can hide the icon before changing back. +var timeoutIcon = 2000; +var timeoutSuccessClass = 1500; + +const temporarilyChangeTooltip = (el, oldText, newText) => { + el.setAttribute('data-tooltip', newText) + el.classList.add('success') + // Remove success a little bit sooner than we change the tooltip + // So that we can use CSS to hide the copybutton first + setTimeout(() => el.classList.remove('success'), timeoutSuccessClass) + setTimeout(() => el.setAttribute('data-tooltip', oldText), timeoutIcon) +} + +// Changes the copy button icon for two seconds, then changes it back +const temporarilyChangeIcon = (el) => { + el.innerHTML = iconCheck; + setTimeout(() => {el.innerHTML = iconCopy}, timeoutIcon) +} + +const addCopyButtonToCodeCells = () => { + // If ClipboardJS hasn't loaded, wait a bit and try again. This + // happens because we load ClipboardJS asynchronously. + if (window.ClipboardJS === undefined) { + setTimeout(addCopyButtonToCodeCells, 250) + return + } + + // Add copybuttons to all of our code cells + const COPYBUTTON_SELECTOR = 'div.highlight pre'; + const codeCells = document.querySelectorAll(COPYBUTTON_SELECTOR) + codeCells.forEach((codeCell, index) => { + const id = codeCellId(index) + codeCell.setAttribute('id', id) + + const clipboardButton = id => + `` + codeCell.insertAdjacentHTML('afterend', clipboardButton(id)) + }) + +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string +} + +/** + * Removes excluded text from a Node. + * + * @param {Node} target Node to filter. + * @param {string} exclude CSS selector of nodes to exclude. + * @returns {DOMString} Text from `target` with text removed. + */ +function filterText(target, exclude) { + const clone = target.cloneNode(true); // clone as to not modify the live DOM + if (exclude) { + // remove excluded nodes + clone.querySelectorAll(exclude).forEach(node => node.remove()); + } + return clone.innerText; +} + +// Callback when a copy button is clicked. Will be passed the node that was clicked +// should then grab the text and replace pieces of text that shouldn't be used in output +function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { + var regexp; + var match; + + // Do we check for line continuation characters and "HERE-documents"? + var useLineCont = !!lineContinuationChar + var useHereDoc = !!hereDocDelim + + // create regexp to capture prompt and remaining line + if (isRegexp) { + regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') + } else { + regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') + } + + const outputLines = []; + var promptFound = false; + var gotLineCont = false; + var gotHereDoc = false; + const lineGotPrompt = []; + for (const line of textContent.split('\n')) { + match = line.match(regexp) + if (match || gotLineCont || gotHereDoc) { + promptFound = regexp.test(line) + lineGotPrompt.push(promptFound) + if (removePrompts && promptFound) { + outputLines.push(match[2]) + } else { + outputLines.push(line) + } + gotLineCont = line.endsWith(lineContinuationChar) & useLineCont + if (line.includes(hereDocDelim) & useHereDoc) + gotHereDoc = !gotHereDoc + } else if (!onlyCopyPromptLines) { + outputLines.push(line) + } else if (copyEmptyLines && line.trim() === '') { + outputLines.push(line) + } + } + + // If no lines with the prompt were found then just use original lines + if (lineGotPrompt.some(v => v === true)) { + textContent = outputLines.join('\n'); + } + + // Remove a trailing newline to avoid auto-running when pasting + if (textContent.endsWith("\n")) { + textContent = textContent.slice(0, -1) + } + return textContent +} + + +var copyTargetText = (trigger) => { + var target = document.querySelector(trigger.attributes['data-clipboard-target'].value); + + // get filtered text + let exclude = '.linenos'; + + let text = filterText(target, exclude); + return formatCopyText(text, '', false, true, true, true, '', '') +} + + // Initialize with a callback so we can modify the text before copy + const clipboard = new ClipboardJS('.copybtn', {text: copyTargetText}) + + // Update UI with error/success messages + clipboard.on('success', event => { + clearSelection() + temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_success']) + temporarilyChangeIcon(event.trigger) + }) + + clipboard.on('error', event => { + temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_failure']) + }) +} + +runWhenDOMLoaded(addCopyButtonToCodeCells) \ No newline at end of file diff --git a/_static/copybutton_funcs.js b/_static/copybutton_funcs.js new file mode 100644 index 0000000..dbe1aaa --- /dev/null +++ b/_static/copybutton_funcs.js @@ -0,0 +1,73 @@ +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string +} + +/** + * Removes excluded text from a Node. + * + * @param {Node} target Node to filter. + * @param {string} exclude CSS selector of nodes to exclude. + * @returns {DOMString} Text from `target` with text removed. + */ +export function filterText(target, exclude) { + const clone = target.cloneNode(true); // clone as to not modify the live DOM + if (exclude) { + // remove excluded nodes + clone.querySelectorAll(exclude).forEach(node => node.remove()); + } + return clone.innerText; +} + +// Callback when a copy button is clicked. Will be passed the node that was clicked +// should then grab the text and replace pieces of text that shouldn't be used in output +export function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { + var regexp; + var match; + + // Do we check for line continuation characters and "HERE-documents"? + var useLineCont = !!lineContinuationChar + var useHereDoc = !!hereDocDelim + + // create regexp to capture prompt and remaining line + if (isRegexp) { + regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') + } else { + regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') + } + + const outputLines = []; + var promptFound = false; + var gotLineCont = false; + var gotHereDoc = false; + const lineGotPrompt = []; + for (const line of textContent.split('\n')) { + match = line.match(regexp) + if (match || gotLineCont || gotHereDoc) { + promptFound = regexp.test(line) + lineGotPrompt.push(promptFound) + if (removePrompts && promptFound) { + outputLines.push(match[2]) + } else { + outputLines.push(line) + } + gotLineCont = line.endsWith(lineContinuationChar) & useLineCont + if (line.includes(hereDocDelim) & useHereDoc) + gotHereDoc = !gotHereDoc + } else if (!onlyCopyPromptLines) { + outputLines.push(line) + } else if (copyEmptyLines && line.trim() === '') { + outputLines.push(line) + } + } + + // If no lines with the prompt were found then just use original lines + if (lineGotPrompt.some(v => v === true)) { + textContent = outputLines.join('\n'); + } + + // Remove a trailing newline to avoid auto-running when pasting + if (textContent.endsWith("\n")) { + textContent = textContent.slice(0, -1) + } + return textContent +} diff --git a/_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css b/_static/design-style.1e8bd061cd6da7fc9cf755528e8ffc24.min.css new file mode 100644 index 0000000..eb19f69 --- /dev/null +++ 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zB(Y#$oL!o_oI|#`LeD5m>ezV6;nKHq@ZYvUufb~M33Qw%6`GhEa}S@P!}T;dH@bLx zG_yiKDTq6zQz}25>oeWOXpL<9!kJrP)LQASx)Dh$MiaKmk}q7TZJjtiA`M6zv_)Sn zoW-S@(c2ebP+DQqvD-S;#gt=zlveyhax!aybe(eZtlKEO1+bZSM diff --git a/_static/images/logo_jupyterhub.svg b/_static/images/logo_jupyterhub.svg new file mode 100644 index 0000000..60cfe9f --- /dev/null +++ b/_static/images/logo_jupyterhub.svg @@ -0,0 +1 @@ +logo_jupyterhubHub diff --git a/_static/language_data.js b/_static/language_data.js new file mode 100644 index 0000000..250f566 --- /dev/null +++ b/_static/language_data.js @@ -0,0 +1,199 @@ +/* + * language_data.js + * ~~~~~~~~~~~~~~~~ + * + * This script contains the language-specific data used by searchtools.js, + * namely the list of stopwords, stemmer, scorer and splitter. + * + * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]; + + +/* Non-minified version is copied as a separate JS file, is available */ + +/** + * Porter Stemmer + */ +var Stemmer = function() { + + var step2list = { + ational: 'ate', + tional: 'tion', + enci: 'ence', + anci: 'ance', + izer: 'ize', + bli: 'ble', + alli: 'al', + entli: 'ent', + eli: 'e', + ousli: 'ous', + ization: 'ize', + ation: 'ate', + ator: 'ate', + alism: 'al', + iveness: 'ive', + fulness: 'ful', + ousness: 'ous', + aliti: 'al', + iviti: 'ive', + biliti: 'ble', + logi: 'log' + }; + + var step3list = { + icate: 'ic', + ative: '', + alize: 'al', + iciti: 'ic', + ical: 'ic', + ful: '', + ness: '' + }; + + var c = "[^aeiou]"; // consonant + var v = "[aeiouy]"; // vowel + var C = c + "[^aeiouy]*"; // consonant sequence + var V = v + "[aeiou]*"; // vowel sequence + + var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 + var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 + var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 + var s_v = "^(" + C + ")?" + v; // vowel in stem + + this.stemWord = function (w) { + var stem; + var suffix; + var firstch; + var origword = w; + + if (w.length < 3) + return w; + + var re; + var re2; + var re3; + var re4; + + firstch = w.substr(0,1); + if (firstch == "y") + w = firstch.toUpperCase() + w.substr(1); + + // Step 1a + re = /^(.+?)(ss|i)es$/; + re2 = /^(.+?)([^s])s$/; + + if (re.test(w)) + w = w.replace(re,"$1$2"); + else if (re2.test(w)) + w = w.replace(re2,"$1$2"); + + // Step 1b + re = /^(.+?)eed$/; + re2 = /^(.+?)(ed|ing)$/; + if (re.test(w)) { + var fp = re.exec(w); + re = new RegExp(mgr0); + if (re.test(fp[1])) { + re = /.$/; + w = w.replace(re,""); + } + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1]; + re2 = new RegExp(s_v); + if (re2.test(stem)) { + w = stem; + re2 = /(at|bl|iz)$/; + re3 = new RegExp("([^aeiouylsz])\\1$"); + re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re2.test(w)) + w = w + "e"; + else if (re3.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + else if (re4.test(w)) + w = w + "e"; + } + } + + // Step 1c + re = /^(.+?)y$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(s_v); + if (re.test(stem)) + w = stem + "i"; + } + + // Step 2 + re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step2list[suffix]; + } + + // Step 3 + re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step3list[suffix]; + } + + // Step 4 + re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; + re2 = /^(.+?)(s|t)(ion)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + if (re.test(stem)) + w = stem; + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1] + fp[2]; + re2 = new RegExp(mgr1); + if (re2.test(stem)) + w = stem; + } + + // Step 5 + re = /^(.+?)e$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + re2 = new RegExp(meq1); + re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) + w = stem; + } + re = /ll$/; + re2 = new RegExp(mgr1); + if (re.test(w) && re2.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + + // and turn initial Y back to y + if (firstch == "y") + w = firstch.toLowerCase() + w.substr(1); + return w; + } +} + diff --git a/_static/locales/ar/LC_MESSAGES/booktheme.mo b/_static/locales/ar/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..15541a6a375f93efed3f410c2f892174ba91aaa0 GIT binary patch literal 1541 zcmZvaJ!}+56vrn40$lhsA5n;v39lh z&UUPnK|(?lfROD&7suGxxK0yMQ@o*|gesy+5vu&(?mBh?qn-WTn|=G<|NZw~b#1&Y zus*}?#(shQ752{`;fA&4V5qyTPS`e-!60i}(%5{r(0^;D!zP`#V66yFspV7<>kvF5*86z5`j$ z=8ez}?gu^a8}Li;DtHLIQScsk0P*i2&-V)CK7WC%Q*07qAJ7GU4juvd{a%p0tQWim zeu4N7$oY#!{2XK-Ul-?ZLAIP{VE@?5Oee^5uV0WLc46~8yjT}6*2P}4uiOhI#i!V; zXZ>RTx%Xyl*phu;(K~`m+PV^FjkZeL1V5sYI1K7moHI9c!}v9+ja5U&{2;G|4YhWh zm^7}c{~g+Tn8?Tvl<2F47Nu9i{l>4L9=6uy?FAD0FiY3w(=eiIKTWvQbqOe&{(Wd5^qM9YH}dGcsaNzja& zq-k29Wt#nO;9At7wwrWQc-|J&abpO^Bu%@f8>dB@7kE5QPu!GiO4q{asH8bJN^P3Y zvv7uYJM=8C@P0OzYSB}gLot+ZNt#(-bAo@Zj6?Yfp?anYnoPQR?;I# z{we#%LHPn31obOfkF`-+I9KUX>gUj zW@~ literal 0 HcmV?d00001 diff --git a/_static/locales/ar/LC_MESSAGES/booktheme.po b/_static/locales/ar/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..edae2ec --- /dev/null +++ b/_static/locales/ar/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ar\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "موضوع بواسطة" + +msgid "Open an issue" +msgstr "افتح قضية" + +msgid "Contents" +msgstr "محتويات" + +msgid "Download notebook file" +msgstr "تنزيل ملف دفتر الملاحظات" + +msgid "Sphinx Book Theme" +msgstr "موضوع كتاب أبو الهول" + +msgid "Fullscreen mode" +msgstr "وضع ملء الشاشة" + +msgid "Edit this page" +msgstr "قم بتحرير هذه الصفحة" + +msgid "By" +msgstr "بواسطة" + +msgid "Copyright" +msgstr "حقوق النشر" + +msgid "Source repository" +msgstr "مستودع المصدر" + +msgid "previous page" +msgstr "الصفحة السابقة" + +msgid "next page" +msgstr "الصفحة التالية" + +msgid "Toggle navigation" +msgstr "تبديل التنقل" + +msgid "repository" +msgstr "مخزن" + +msgid "suggest edit" +msgstr "أقترح تحرير" + +msgid "open issue" +msgstr "قضية مفتوحة" + +msgid "Launch" +msgstr "إطلاق" + +msgid "Print to PDF" +msgstr "طباعة إلى PDF" + +msgid "By the" +msgstr "بواسطة" + +msgid "Last updated on" +msgstr "آخر تحديث في" + +msgid "Download source file" +msgstr "تنزيل ملف المصدر" + +msgid "Download this page" +msgstr "قم بتنزيل هذه الصفحة" diff --git a/_static/locales/bg/LC_MESSAGES/booktheme.mo b/_static/locales/bg/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..da95120037f8d7c52ad1f166a7682ea55ca47a01 GIT binary patch literal 1708 zcmaKqOKcQJ5QaOv0vkhkhC?jT2nh&cNkBwFYxY90B_t3AOpcMpyUpy7b@wpSL+}lZ zc_s=RKte*|C2`<_7URcy7jLdPR->G9h;qvTamgjhjlX8bj}R-P?fIs=y6dm{dw*ZQ z?5@DG8KWEHSBxzfKYoB0o|Q|4z)!5gYX#T^t^_xLtH5sX6L34Y5iEo2!IR(`P=OzV zHs>hFdG3I#!TVqr_zYYJPUie2U;izi{|U0*KVSh|x->h#2IP4+$a!{vO>jTB41AmO zFOci|8~haPLhws)C%7B@Hs=rEKFpioR`3nD2VA{8JAV*le@=j0?>TT6cp2OVJ_ot4 z*WiBe50LY0LeuQ=S0K-igY45ea0fUFvgOv1JgO3NWrRpO`@TbYDa&#J04 z8uLU~YT|f^4W5=k94AWjM}bBXBl{2ciBp+gq(T!1)p!vCDOMX z%z7FyzF${Td*=h+vjIf3x?r>F4C`bfVWiFnCdtcQkUma)U!h8cPEd+Dt17m5q+0w& zMKQ9KWTsza{bH(IICkV%?|gjko-YcyvBiPmP?e-b0iTC;FVH=*QuCr%+4AXuzT$!T zeUYc*Gb$?f>WZlb+AqligMlp^^|YVB*ODCc3;p#Z^6JGt6Ai^Bsl#*{m-qF^?6bU6 z%dKU(_p_dYpa*V5&_n77dhBk}xVz~t(j+x#hMF`X=r)bH5$d>$?h>`ABk5bs2r;-dTfq#Q2#?t@q|9teP3*uNPWy^ACfqd~8<8}Y{+a1%CJzCK zxEruG6KALRIVJ-U$3Yy!~NpG7AK|w8QyPuG1485SvTmo%i zrHNb3JL61fEcXDLQBPwL`;mLLOPayeL#0F0B5ju4Yr5-c6aTq5cjf(V=MS}!0~aLI KlK*|VZ0$SA#iddJ literal 0 HcmV?d00001 diff --git a/_static/locales/bg/LC_MESSAGES/booktheme.po b/_static/locales/bg/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..1f363b9 --- /dev/null +++ b/_static/locales/bg/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: bg\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Тема от" + +msgid "Open an issue" +msgstr "Отворете проблем" + +msgid "Contents" +msgstr "Съдържание" + +msgid "Download notebook file" +msgstr "Изтеглете файла на бележника" + +msgid "Sphinx Book Theme" +msgstr "Тема на книгата Sphinx" + +msgid "Fullscreen mode" +msgstr "Режим на цял екран" + +msgid "Edit this page" +msgstr "Редактирайте тази страница" + +msgid "By" +msgstr "От" + +msgid "Copyright" +msgstr "Авторско право" + +msgid "Source repository" +msgstr "Хранилище на източника" + +msgid "previous page" +msgstr "предишна страница" + +msgid "next page" +msgstr "Следваща страница" + +msgid "Toggle navigation" +msgstr "Превключване на навигацията" + +msgid "repository" +msgstr "хранилище" + +msgid "suggest edit" +msgstr "предложи редактиране" + +msgid "open issue" +msgstr "отворен брой" + +msgid "Launch" +msgstr "Стартиране" + +msgid "Print to PDF" +msgstr "Печат в PDF" + +msgid "By the" +msgstr "По" + +msgid "Last updated on" +msgstr "Последна актуализация на" + +msgid "Download source file" +msgstr "Изтеглете изходния файл" + +msgid "Download this page" +msgstr "Изтеглете тази страница" diff --git a/_static/locales/bn/LC_MESSAGES/booktheme.mo b/_static/locales/bn/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..6b96639b726a2fa959a6419b6f8b7e0dfcce33ae GIT binary patch literal 1646 zcmbV~&5IOA7>8S2xE{WN>)mqrjbP_+ zD|`%n|9`+8@Gtlc{Cs5;eF=|2zkdOGUHYZ{3U0$*$xxrd?Ipj1NbvXay{#>+)sQwK zLc@BGr=Q8s@3s2pVyti%e$UVEm)Gmv@K$Kxb@iIkGQ)QH3Dc6%KAm>6q}ejje*L3r z>$oA5HgZzyAH?ybE$6p$-O1{5(WYr7xk%%tj7A!XA>+Uti*qA7X(KkWA+(Cd;*P4f zqC=@vB32^F^Nx(hvqTZ3#rXcw=x~uglc~-VqqA;wIBg~Bl-TQgnP|xqG73*IS+qW( zo6WWqDn6MsW0O!s$y282M*BKNku;Mh6WuA>9MAOkvTmve8r7pR%ZaLqqE6Ml~R{3$6RYz1^ zHxkvXiQSWlsf@*{*+H+Gm{gVVb|;J5)lr?D$ZJBS!OVxh8WP3p@HQnr8y3617^+0h zTGzYm>~GFKb#|8L(pyu`-gfp`;o|IhXQy$z<$9NR^WnYI&Q1wu?}S90&tc32?JEMg4wtZV(;LB0u<-^*y2)npB|JLL@f}SDrcO%Hi&xc%8I{oPgE$%7j?Kgl1>Fz ze@F9IjWZ|r@GsvuUE*t^AN05zoTs2{kFZmI~m25V-8`&>S^dPTx 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obrazovky" + +msgid "Edit this page" +msgstr "Upravit tuto stránku" + +msgid "By" +msgstr "Podle" + +msgid "Copyright" +msgstr "autorská práva" + +msgid "Source repository" +msgstr "Zdrojové úložiště" + +msgid "previous page" +msgstr "předchozí stránka" + +msgid "next page" +msgstr "další strana" + +msgid "Toggle navigation" +msgstr "Přepnout navigaci" + +msgid "repository" +msgstr "úložiště" + +msgid "suggest edit" +msgstr "navrhnout úpravy" + +msgid "open issue" +msgstr "otevřené číslo" + +msgid "Launch" +msgstr "Zahájení" + +msgid "Print to PDF" +msgstr "Tisk do PDF" + +msgid "By the" +msgstr "Podle" + +msgid "Last updated on" +msgstr "Naposledy aktualizováno" + +msgid "Download source file" +msgstr "Stáhněte si zdrojový soubor" + +msgid "Download this page" +msgstr "Stáhněte si tuto stránku" diff --git a/_static/locales/da/LC_MESSAGES/booktheme.mo b/_static/locales/da/LC_MESSAGES/booktheme.mo new file mode 100644 index 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"Sphinx Book Theme" +msgstr "Sphinx-Buch-Thema" + +msgid "Fullscreen mode" +msgstr "Vollbildmodus" + +msgid "Edit this page" +msgstr "Bearbeite diese Seite" + +msgid "By" +msgstr "Durch" + +msgid "Copyright" +msgstr "Urheberrechte ©" + +msgid "Source repository" +msgstr "Quell-Repository" + +msgid "previous page" +msgstr "vorherige Seite" + +msgid "next page" +msgstr "Nächste Seite" + +msgid "Toggle navigation" +msgstr "Navigation umschalten" + +msgid "repository" +msgstr "Repository" + +msgid "suggest edit" +msgstr "vorschlagen zu bearbeiten" + +msgid "open issue" +msgstr "offenes Thema" + +msgid "Launch" +msgstr "Starten" + +msgid "Print to PDF" +msgstr "In PDF drucken" + +msgid "By the" +msgstr "Bis zum" + +msgid "Last updated on" +msgstr "Zuletzt aktualisiert am" + +msgid "Download source file" +msgstr "Quelldatei herunterladen" + +msgid "Download this page" +msgstr "Laden Sie diese Seite herunter" diff --git a/_static/locales/el/LC_MESSAGES/booktheme.mo 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!= 1);\n" + +msgid "Theme by the" +msgstr "Temo de la" + +msgid "Open an issue" +msgstr "Malfermu numeron" + +msgid "Contents" +msgstr "Enhavo" + +msgid "Download notebook file" +msgstr "Elŝutu kajeran dosieron" + +msgid "Sphinx Book Theme" +msgstr "Sfinksa Libro-Temo" + +msgid "Fullscreen mode" +msgstr "Plenekrana reĝimo" + +msgid "Edit this page" +msgstr "Redaktu ĉi tiun paĝon" + +msgid "By" +msgstr "De" + +msgid "Copyright" +msgstr "Kopirajto" + +msgid "Source repository" +msgstr "Fonto-deponejo" + +msgid "previous page" +msgstr "antaŭa paĝo" + +msgid "next page" +msgstr "sekva paĝo" + +msgid "Toggle navigation" +msgstr "Ŝalti navigadon" + +msgid "repository" +msgstr "deponejo" + +msgid "suggest edit" +msgstr "sugesti redaktadon" + +msgid "open issue" +msgstr "malferma numero" + +msgid "Launch" +msgstr "Lanĉo" + +msgid "Print to PDF" +msgstr "Presi al PDF" + +msgid "By the" +msgstr "Per la" + +msgid "Last updated on" +msgstr "Laste ĝisdatigita la" + +msgid "Download source file" +msgstr "Elŝutu fontodosieron" + +msgid "Download this page" +msgstr "Elŝutu ĉi tiun paĝon" diff --git a/_static/locales/es/LC_MESSAGES/booktheme.mo b/_static/locales/es/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..ba2ee4dc22148ed53f2aeba32c5965654d4a5a2f GIT binary patch literal 1396 zcmZ9Kzi$;s5XU#z;m3pU!zKwxjKJWQQZ~wEO{|$=X8*l*5%yj3EgEC(L#m|@E3-CIKPyLHQ^!@|o{A*Bj z4$La`8F(5z16~6q{%=5u|2}vYjQ#o}@F?a_K{@|BDEE2^ehj_>C4c{bvhUD`U0&uv z*?$p~_`U+=+!`qRz6aYpfs%6BBl;4{Ji6po;@;mNp-!U9Icai#X`&;(C9e__T(%nW zw)>mpL*DQZy5tBcRcdJ)pH3yKo8BdMDdMNz4yGuRTJ{f|^^|Mp6HmSWQEwW{d*1tzb%mTC1mCsq-qL_43=ae|t-eKOjtW>vaY#^sij18-e zU>uxyy|KKi?sj^CYadPWVO!m;OXD8uC5dfPa>c40^|ZUw#21BS?P$vslng{1KTKV8 zUUWKW55MCO;ccWl{h{a&Tjjy}+WN}g`qfKU z27O|OlkJ*EIw63|wI$;gbyiY{oW}PitHT?6`vSSR$zizSGM^h)jP#AENrPMDiUxTd zX^w*p+XS-1RUfK2(ynf&aeQr2cfaHFPM;g=s}~jrYQqQVnr;8cCiiNY181d=I%iD{ zk_k)9C=?Vlg{(ANUY4?kat==RzrVWKpj=Q5{Q{y&B&juy+NY=9viqbpt^2(7Sd&X+ 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pantalla completa" + +msgid "Edit this page" +msgstr "Edita esta página" + +msgid "By" +msgstr "Por" + +msgid "Copyright" +msgstr "Derechos de autor" + +msgid "Source repository" +msgstr "Repositorio de origen" + +msgid "previous page" +msgstr "pagina anterior" + +msgid "next page" +msgstr "siguiente página" + +msgid "Toggle navigation" +msgstr "Navegación de palanca" + +msgid "repository" +msgstr "repositorio" + +msgid "suggest edit" +msgstr "sugerir editar" + +msgid "open issue" +msgstr "Tema abierto" + +msgid "Launch" +msgstr "Lanzamiento" + +msgid "Print to PDF" +msgstr "Imprimir en PDF" + +msgid "By the" +msgstr "Por el" + +msgid "Last updated on" +msgstr "Ultima actualización en" + +msgid "Download source file" +msgstr "Descargar archivo fuente" + +msgid "Download this page" +msgstr "Descarga esta pagina" diff --git a/_static/locales/et/LC_MESSAGES/booktheme.mo b/_static/locales/et/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..983b82391f499b67a9046c15d0dd8744650ad925 GIT binary patch literal 1341 zcmZ9Kzi%8x6vqb=^5gOYNC*@$VrY^ev%C-5~0q6cNoSQvQHcDIz*5N(ux8-*>yj7Nec{?37 zm@hCt!hG}w7K~$WDuqWK$8rQb2_6H_g2%xn@O|(C_#QX{&wyWnr$GYW22;<6py+%D zo&tXWPl7*z?}ESdeBSTB?Csw{@%I-v01qANzCR6$y#$KRMeqsu1$Y$v1AGho6Fdz5 z4az++J_JsIlKZFNIq(K3aoh#Zg45o90E(Y)LCNb!P;`Fo`2>{wpMm1IA0b zcW{Vb>7mpIdO`vjME%rCbb#Z zLB#9Ln`>&T^B1V~k&_R*YOAf;-PhM8wsB1jsl}?dyPU?psw`<|W?Y%XaN_8G>Z0@F zr*qN&8_XbscI- zgH4-*vBjDXO&n_1F3dRkd|7v|qf1VIJknP`Sstj{^T%OktXj#ancCu*yH}n+<|;=N z-jrOCj`OFMOqk`wddINU##;0GR19tBdvzi?e7zruw52+Aw>NT5Q%F&X%h*Lj=6f7z z8jNuq=-IE#jk<#c{m?m+L;rJ$825O_Nq(D^8CKl}zio+{#UD_z^uJ)WVl7Wi?YTr` zTRZHgk)aH+jLK4D)OfM3BNeE1ohJ(1utQX6H>rE`y-+P|2~e4t1fZw$r;!^}gUIe5 P_MW2m5}a<3ol*Y+f5$~k literal 0 HcmV?d00001 diff --git a/_static/locales/et/LC_MESSAGES/booktheme.po b/_static/locales/et/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..345088f --- /dev/null +++ b/_static/locales/et/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: et\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Teema" + +msgid "Open an issue" +msgstr "Avage probleem" + +msgid "Contents" +msgstr "Sisu" + +msgid "Download notebook file" +msgstr "Laadige sülearvuti fail alla" + +msgid "Sphinx Book Theme" +msgstr "Sfinksiraamatu teema" + +msgid "Fullscreen mode" +msgstr "Täisekraanirežiim" + +msgid "Edit this page" +msgstr "Muutke seda lehte" + +msgid "By" +msgstr "Kõrval" + +msgid "Copyright" +msgstr "Autoriõigus" + +msgid "Source repository" +msgstr "Allikahoidla" + +msgid "previous page" +msgstr "eelmine leht" + +msgid "next page" +msgstr "järgmine leht" + +msgid "Toggle navigation" +msgstr "Lülita navigeerimine sisse" + +msgid "repository" +msgstr "hoidla" + +msgid "suggest edit" +msgstr "soovita muuta" + +msgid "open issue" +msgstr "avatud küsimus" + +msgid "Launch" +msgstr "Käivitage" + +msgid "Print to PDF" +msgstr "Prindi PDF-i" + +msgid "By the" +msgstr "Autor" + +msgid "Last updated on" +msgstr "Viimati uuendatud" + +msgid "Download source file" +msgstr "Laadige alla lähtefail" + +msgid "Download this page" +msgstr "Laadige see leht alla" diff --git a/_static/locales/fi/LC_MESSAGES/booktheme.mo b/_static/locales/fi/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..d8ac054597c924e3010f629caeac1c748b7211cd GIT binary patch literal 1368 zcmZ9KJ#5r46vquMU&lA4Af!r|g^wXX5kqz52B58kprWEjclYv|xbfLh>>S*}#K;Cr ztS2O9B*cCTVrBw~l?gF1AR)y6B`K}2;{5K}=lB1=7k@o5`BGq<#+lRCrOA1CaQ!^kKlhsTrZJIH9K_^ryK`_q_#3i5+EIO9achW2 zhLpr@X9L;b@gpA=I!S|AaF48UDwfs-T6Zp!8`{wJvUg?CqyH8|s=drrLSix20jamb zrP3JRD~PP@yO_j1<%2BqSOtouvxrOEOU3;he^6Fx?@JOZg|3?XUWo3*(Ha#V+1j$!k61sdlv~SpmKV48XD?rEHI0qB!<^bOz`&KTmRqe+kV}^cf!#bT&>G1)AQnFuaA9SXR 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"Edit this page" +msgstr "Muokkaa tätä sivua" + +msgid "By" +msgstr "Tekijä" + +msgid "Copyright" +msgstr "Tekijänoikeus" + +msgid "Source repository" +msgstr "Lähteen arkisto" + +msgid "previous page" +msgstr "Edellinen sivu" + +msgid "next page" +msgstr "seuraava sivu" + +msgid "Toggle navigation" +msgstr "Vaihda navigointia" + +msgid "repository" +msgstr "arkisto" + +msgid "suggest edit" +msgstr "ehdottaa muokkausta" + +msgid "open issue" +msgstr "avoin ongelma" + +msgid "Launch" +msgstr "Tuoda markkinoille" + +msgid "Print to PDF" +msgstr "Tulosta PDF-tiedostoon" + +msgid "By the" +msgstr "Mukaan" + +msgid "Last updated on" +msgstr "Viimeksi päivitetty" + +msgid "Download source file" +msgstr "Lataa lähdetiedosto" + +msgid "Download this page" +msgstr "Lataa tämä sivu" diff --git a/_static/locales/fr/LC_MESSAGES/booktheme.mo b/_static/locales/fr/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..f663d39f0faa76c5b9bd504c51252eef74cca5de GIT 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TA2+cw{Vw>h7Yg+MtLz81? literal 0 HcmV?d00001 diff --git a/_static/locales/fr/LC_MESSAGES/booktheme.po b/_static/locales/fr/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..88f3517 --- /dev/null +++ b/_static/locales/fr/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: fr\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Thème par le" + +msgid "Open an issue" +msgstr "Ouvrez un problème" + +msgid "Contents" +msgstr "Contenu" + +msgid "Download notebook file" +msgstr "Télécharger le fichier notebook" + +msgid "Sphinx Book Theme" +msgstr "Thème du livre Sphinx" + +msgid "Fullscreen mode" +msgstr "Mode plein écran" + +msgid "Edit this page" +msgstr "Modifier cette page" + +msgid "By" +msgstr "Par" + +msgid "Copyright" +msgstr "droits d'auteur" + +msgid "Source repository" +msgstr "Dépôt source" + +msgid "previous page" +msgstr "page précédente" + +msgid "next page" +msgstr "page suivante" + +msgid "Toggle navigation" +msgstr "Basculer la navigation" + +msgid "repository" +msgstr "dépôt" + +msgid "suggest edit" +msgstr "suggestion de modification" + +msgid "open issue" +msgstr "signaler un problème" + +msgid "Launch" +msgstr "lancement" + +msgid "Print to PDF" +msgstr "Imprimer au format PDF" + +msgid "By the" +msgstr "Par le" + +msgid "Last updated on" +msgstr "Dernière mise à jour le" + +msgid "Download source file" +msgstr "Télécharger le fichier source" + +msgid "Download this page" +msgstr "Téléchargez cette page" diff --git a/_static/locales/hr/LC_MESSAGES/booktheme.mo b/_static/locales/hr/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..eca4a1a2842830f06bd5f6235bf01d07bdd313d2 GIT binary patch literal 1402 zcmZ9KJ!~9B6vu}+kmLvh)-Bbu!YZ&sL*)#Wq0oOW>)iY z#I7UJKoJQlD$3MIh{}~uqNJdrprN2bqC$d-|Jz;1r;K*?xAU?8_kVBZ_tmrCDzsP8 z*U*1Oe;xg+XYfKhe?}=h>H=QRffvE^;1%!!xCXugz6HJv4#8FMQ}7bV;EQ1F_z)DG zZ@?G8@4$=TWAG*L$BsXD^S^cDKS7E2FW3WDR@(nBfihkLMdxksC-6Fmt?DmO{`(sg z-~WN)YvpX4?<)8j#_OQu@i8cQeBP}`P-^oC6rIQ5W$*{^dGHvNe1GZqM>qcuD0MvZ zY`gv@DF5B)#v@RCe+FI!b5KeyIf$NkxPmU8B<^y9bfYDCNE01tQa`D+)KxSg*?1KH z%T4MpwK#{4ax`^Pw+`@7ELnZzY-Ae)KI#K+iZZI(?h9Kvos)Hu_nn*4eN*x2ba2UM z{M2MDO`uvAtTuBKA$>9&rK$>r--+ODxdTQVUeRy*EU zh&bB0JyN@EJkPZYCOUthcI(pE2XsrkjZ2=fYTmTp<}`LiQ88IPH-(M{K`cLrtve@i z+90*(xpAqpy(Aw}Q7~LGGJzF0;VkyI^8P*c0crzk0e zJ5}W`eCg#p>R8HV8p8`ORd-?8+@kgmPE(NjB4ZRZpsbXo1{+%JywM17c0!7$ZS zdp+04j?>}H5RL>u+?)6`B(!QC;nQ(E%YYHwOi5)9EgF2Tundr{ymsm2Z;f2mKh k(#nYgw(f}olqHrfw@Z7L48TfWxy6y8Q4`jSBkXa^hFIaGO(a}_Drr&ngPIpyPhwkKtCW1zS zxtWoenhB;xBBn-yn24D8zwTalu&Ao9Uv<5s{`Yli#|wdR9BT&a6V_?0r`xb$Ol}tf zQ|!UE3)}}zg45t0a0WaEo&}G9U2qD#3myOoJP3w{Pe6|I9NZ7S1owfj!NcI&h98>q z&yD>JoIl_+xD%H+@5zQ2!9%dS z4R3=dU_S)+f*T;`dD8G1$o{WD_Im?z{P&Ih5#&5yK-S?0$ohz#wGPuD`<((=a*oaa zSxfd~Z8_ffK#0nR_2t3u=fQPw4%YQ37D84vb8p87>(4#hjm4TkQX%F>m@;G}=B){2 zg2zWWayrd|Sg?;xZdD?U4b-=GDA#mOTgTo;H=zFxL#DkfRZ3zp(E*`1&83*aj(wjsI*=O>qg>UnQ5~j z=eV|BMg@s#m;L%pJ)5RENuwU=R0WMBhBiW7o#i}rlG4#5ZDUjRSa=`Plu#w%B`C$N z(;&2$llB909??3o&fn(z?J9F?WqD;KhDS6Yp*?cS)QjtnT^a+xb_X5}DL&Qs{# z?=7`&Y~6Fp_%(9vMKiF8HfcxR=o0auv z_q>s3y7KCU*_ODI6J+IW*=v!hp&aNkC~@B;F{`@wufgMIJ{Em)%}J(mRd82~uKPNE zu!45VT#b~I5H)6^M@|hh?PQ`$a((5ZmR_kKRwzf4qZ=wC=HgJvLU}~a#5@JmHKeM~ zcQ+dhueyjH6-vS(Hi{zy4lKXvX09`YYnog=urAe8uFQH2W~4-u2I{*$(n5sIJAG7C T@Rc+s5Lgrh10CRyRonjp5+F85 literal 0 HcmV?d00001 diff --git a/_static/locales/id/LC_MESSAGES/booktheme.po b/_static/locales/id/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..9ffb56f --- /dev/null +++ b/_static/locales/id/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: id\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Tema oleh" + +msgid "Open an issue" +msgstr "Buka masalah" + +msgid "Contents" +msgstr "Isi" + +msgid "Download notebook file" +msgstr "Unduh file notebook" + +msgid "Sphinx Book Theme" +msgstr "Tema Buku Sphinx" + +msgid "Fullscreen mode" +msgstr "Mode layar penuh" + +msgid "Edit this page" +msgstr "Edit halaman ini" + +msgid "By" +msgstr "Oleh" + +msgid "Copyright" +msgstr "hak cipta" + +msgid "Source repository" +msgstr "Repositori sumber" + +msgid "previous page" +msgstr "halaman sebelumnya" + +msgid "next page" +msgstr "halaman selanjutnya" + +msgid "Toggle navigation" +msgstr "Alihkan navigasi" + +msgid "repository" +msgstr "gudang" + +msgid "suggest edit" +msgstr "menyarankan edit" + +msgid "open issue" +msgstr "masalah terbuka" + +msgid "Launch" +msgstr "Meluncurkan" + +msgid "Print to PDF" +msgstr "Cetak ke PDF" + +msgid "By the" +msgstr "Oleh" + +msgid "Last updated on" +msgstr "Terakhir diperbarui saat" + +msgid "Download source file" +msgstr "Unduh file sumber" + +msgid "Download this page" +msgstr "Unduh halaman ini" diff --git a/_static/locales/it/LC_MESSAGES/booktheme.mo b/_static/locales/it/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..53ba476edd2df2a802917e9df402257ceca1a130 GIT binary patch literal 1403 zcmZXSJ&aXF6vsyafhY1QYQiQS8W$5EU!j1vc?Gb$351Os-eM!oynD~ycVOPkWoGWm zTH9#}m5qrNiM6q@vN55xvLLatGO@6+(D*<1-gP%Hxii0e=Htvc|2Z#C?tf~~-bG(P z{{{Vh^sipSfOhD0WAK^77~TMnfQP_S;9+n9db5tC&9bmQINr7VD9+^sD7S+ zZ-HNfN5E&`3Gn-#Klk&$_V(|f-uE{+0Qc?d&L0KUUI5k4BKQM%1;keK2Z+!7i9yf* z1s(_g1vTGe`;B=I{0KY^u7H})r~P~cRhutC&HGzW&wmGM{6B(v?m2h{{0%$^{sW!` z4;<+7S_JjnwcfrBYTWn1Q(y(ER@tjRN(zMHIBUF`R@^(uqn+2D6ew@4L zg5J|zQb*pB(DY&Nai5y1VnoTv1fhfnT;$=ca`*|y1aBki?jP#?!}jLE+O4&f-Stc7 zFAjQPha1~9k0>L63$?T2m#CQ8m^hE`ZLAKj?(U1$r%jH-6<>r>d^Mu0Q^|un)>jR5 z9TALm*F@`vt0B(QhBFUgSr)TwUH`yMh9yxlG%Xix0~y&& z3LB-cB(8l-D%nxCMbU^4uPmkzD-_D^sYeYovZ|_hYt|6+raF6N+B(TUeM703ahwOj z!*UGfp34HuR+WV4?HsPL=1>m45R2fh*HNhPRL3xNJhx_&?Yu^?zAcKo|5pQ*LIIU4 z9%X=yZ5mFd5t*`cmL{7}b7xJ=^_*qP(gmDLw)@AXu2??D^RnquqSO=xr-aR>O-k3u a)*Q3l*@6-(xNK#4xqhOgLbT*tS;gN$Zm<*V0gr*F!6RT6JPeM4`#}XB0Byp@Am^!p`@mOV z7q|)@0zW4Fn)rVt_HU5uZGb6o$Bx$f{UF;tAm=#)eg-dtd%-^-*V_PDx7aDf37`|? zeoukD;5CqS=MqLB_wxkgxVgmt1?-0X4dj{qO1J@X+@W2qe$Rs(cQvs`6FUcTpOYZ# zd6M|6Adj4TU>#hW-}7v_@AidK;vhE9mlyZXi}UiVd9FvXkushE>ug^<53aoj8)J$8 zzT$crKWU3f+%VcIZ9^RVa^Sf|D{h)8T{2EVYGYN-m<~=w|xXST6$p^DKQdw8cB>C zxj87tTJ-|uo6xf+D2p+_=;?>@I%^v*stG0HugtZ28aJ+6Qc^pUp6gf-MYMWoTj~tg zX%+DUHR+isk=>R)j9gbir9vl=V(zQFO%D~)cU2G~TSm6(r@4MQuACYk8XnlX?>m1n zl?*mLUiMW+S_rt{mmE*`%Y4xZLS?ge#s||^w&DUuhxb&F9?*GH@U)weS8|?B-Ey=W zVXhhJO{GRkQQ(x)gC>{=GgAAp8D=l_%hoY_R?FV3>^s+=67+^$;pPAU literal 0 HcmV?d00001 diff --git a/_static/locales/iw/LC_MESSAGES/booktheme.po b/_static/locales/iw/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..4ea190d --- /dev/null +++ b/_static/locales/iw/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: iw\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "נושא מאת" + +msgid "Open an issue" +msgstr "פתח גיליון" + +msgid "Contents" +msgstr "תוכן" + +msgid "Download notebook file" +msgstr "הורד קובץ מחברת" + +msgid "Sphinx Book Theme" +msgstr "נושא ספר ספינקס" + +msgid "Fullscreen mode" +msgstr "מצב מסך מלא" + +msgid "Edit this page" +msgstr "ערוך דף זה" + +msgid "By" +msgstr "על ידי" + +msgid "Copyright" +msgstr "זכויות יוצרים" + +msgid "Source repository" +msgstr "מאגר המקורות" + +msgid "previous page" +msgstr "עמוד קודם" + +msgid "next page" +msgstr "עמוד הבא" + +msgid "Toggle navigation" +msgstr "החלף ניווט" + +msgid "repository" +msgstr "מאגר" + +msgid "suggest edit" +msgstr "מציע לערוך" + +msgid "open issue" +msgstr "בעיה פתוחה" + +msgid "Launch" +msgstr "לְהַשִׁיק" + +msgid "Print to PDF" +msgstr "הדפס לקובץ PDF" + +msgid "By the" +msgstr "דרך" + +msgid "Last updated on" +msgstr "עודכן לאחרונה ב" + +msgid "Download source file" +msgstr "הורד את קובץ המקור" + +msgid "Download this page" +msgstr "הורד דף זה" diff --git a/_static/locales/ja/LC_MESSAGES/booktheme.mo b/_static/locales/ja/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..1cefd29ce3cc08792667a82dc7ff47e9843107be GIT binary patch literal 1471 zcma))U2GIp6vr=uT2=%temyktnh+I|RZ$+uHv1sbO-LX%QhlH9-p&qe?;Yo((zoth z!EFJNkCxzqu~zx0SU`c+ubA-Uv++eAe7Tv~_Q5w};+y|7GulOC;?11-%{lkn^L6K! z-gVOq>v2dQu6IDn_Xk)2*RIXZZv;v211Zik;1ak4q&&ao z_TO@S&AKd35BL)Hd%6F@2|fYNfYiq|km|n!QoJ8>{U?y}t$^hJJGcehbZ=(g z0h0bQNasgDiZ_<)lR3|UkHUThq>)oh@}pU9hR|%O@9u?E>>&uvmlpL;i{?kUXs#3! zA=v{Ey4&tWeb61=55ZW{`(?Yv@$jH7*egl~LIyrQ+;Pvb>jB%X-jWSv)wooF7*^^a zA8{ID)$FU#tBQXZgSz8$*Rlm0s5t>b|D{&KM#HaqLP$QUYJ%;x{D6mU%?d<~D+xW6 z)jE6Cg@Yxz75=BO|)yDPjO+O|NI0-c}~bwE^u;+|UZ4dMBS zR^nOyBIPfpnG5^&>>F6!-~QYSg?zBZp>bD~cz^<)cN>-?`+2o)dAX*25Q`IlO*w3@i^0SgZ zRp#5b_7~Xl$+OE7hnZ=9YND2D&Y9*#)@d&!S7*EK+UR$U{>JE*(KAMC6J0ZU+C;M^ z`q*e3JZ1ERi7p!bh0&j-o|DW(-_lp~<^OPPo;J+|qu);tEd58ke>rs)FR!$Zu=w!h z&Y7=QE_`G(9#lEWlJgUtTT#-!nao^I&VIs{Z!N}0r&&CGVrBLi!p9%ph)+&2{5I%2 zK7KuJEq2#CZ}bHdEv5a=V6`%k-R^d(Xw}Jf>8QN5e!h zBbA`3bkQ)WS=dVKSy@;~B<{I88!P_b+$$|{a=-hV^ZNe(@4NG5)%+^MSdZvHd_rtS zROaA?v3M?Hcvu@=3&Ew}VsJIs26lk!z^&jKFbl2%PlD~B0GES0VHu=655Q&M6L2Xw z0j>n66Mjh6KPU5VAnE-CQ{cRL@%?s?<{cpA*#_Ef2kG3A zWc>t4Ehi1?A9+}fAZZd{dqh6EFS_D$EB?$Vqvj_EszTqMS+R^&H z>|hBG*9E~2DXE3jK7P0*&#?=d9aa}*QCWE|l@|R-n>7qsZZHEJ ziA7vbTyRv7*q)W%4{Te&r9dUHqRxq&PWR-~XN2b?TZYH_Y0^)(lvBrgj&;rK@7cLK zl{7ZpS8_#$YZ%z&7A;41@?634e4(?a`?}KyX3lw*^v?<}-6eA>??^kt5A-`ab<~n} zfWBto^Y9)w_0g!> zVBythE}X>$!Q{z_su`ZeFjL;phL~syBFa zXVlaiX8iI$xBl9S?ljH#2qeqqHLg5*5Kc5=W8s^|_vRD}$A^$29KXrU!@=^_j5Dv6%;4cA#sHtggl>eA))${_687xQDk?6`Kc@OWFO}WOS!3uO( zjPOmFMc3|`Ymgi(M~_AsRb8*l6oj5N!k1G#oNSsg^a1i?<=NZRz?N8C9`e*ob%^~2 D6Q!<* literal 0 HcmV?d00001 diff --git a/_static/locales/ko/LC_MESSAGES/booktheme.po b/_static/locales/ko/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..6ee3d78 --- /dev/null +++ b/_static/locales/ko/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ko\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "테마별" + +msgid "Open an issue" +msgstr "이슈 열기" + +msgid "Contents" +msgstr "내용" + +msgid "Download notebook file" +msgstr "노트북 파일 다운로드" + +msgid "Sphinx Book Theme" +msgstr "스핑크스 도서 테마" + +msgid "Fullscreen mode" +msgstr "전체 화면으로보기" + +msgid "Edit this page" +msgstr "이 페이지 편집" + +msgid "By" +msgstr "으로" + +msgid "Copyright" +msgstr "저작권" + +msgid "Source repository" +msgstr "소스 저장소" + +msgid "previous page" +msgstr "이전 페이지" + +msgid "next page" +msgstr "다음 페이지" + +msgid "Toggle navigation" +msgstr "탐색 전환" + +msgid "repository" +msgstr "저장소" + +msgid "suggest edit" +msgstr "편집 제안" + +msgid "open issue" +msgstr "열린 문제" + +msgid "Launch" +msgstr "시작하다" + +msgid "Print to PDF" +msgstr "PDF로 인쇄" + +msgid "By the" +msgstr "에 의해" + +msgid "Last updated on" +msgstr "마지막 업데이트" + +msgid "Download source file" +msgstr "소스 파일 다운로드" + +msgid "Download this page" +msgstr "이 페이지 다운로드" diff --git a/_static/locales/lt/LC_MESSAGES/booktheme.mo b/_static/locales/lt/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..4468ba04bc134a84fea5e3c973461cf02c9c2da3 GIT binary patch literal 1413 zcmZvaJ*-qk6vsyag_RElKVp1=p+SgQ1!6(=Ws8Trm%IpJ!!Cq&-rn=>&feLX$$UJx zy>yfs3mYDtv7j(9R@&?)#@fol&{Y(AbXL(_rUwj`9qL(er@8vgIw=pko$cKo&XOVSm=ES z^8O^qK3oL({z?6$1#4Nz2(054oJ;=;JiGzE*_kpy=GszcBB+< zVRAov2m8<3><4U^|G(mLjYp;ti7%W@WK+ZsUk6=|lDOjTSmRV7txL4wTqQTPq1|wF zISlEQU>fNty(&qp7CIsI&UP&u6NiDw%84sTTvaj2>KHSL zUeFdvoa|j$6a9r=An&41F4Us$N7~+%m$|mVh$bZFtK3-hG;n2UNLsa}OO-T4EZt3u z>KyAVM0}tv?Q&E0p7b%7C80_}Cn&{@X_(sUMf(ENwtj7O_x!@A z=Ua`j?LqCSBNGbv%p0ZcvK)?7h?KfF2W#z1yZ3^!ag#!O)ec>uZP}5RHgsxTRkqCV zwIfYx^-K=RwAWmi#E!InzKz|B%X0Cvd)CU+U3uZ$a!agNntg;f8E)25tYny{XFsAC z9jD(SkfM$V#H6LA*|v6LHF0AnD>v~vCkoohO{LBB-b;69+sY(u|L3sMiR5g1`bhd5 zjq=k+;szC}%nlMS$9vjXC#gc)P6nF&q9-bfo{CjQZe*xbNYi^#C9ConpM%1oLFKH0 za&)0WJ=gQWZ5W!M$i7!O!aIl|0e?HQ2Ro%kmCL#^O7u6its3{(8W!QLNCjg(=>2Jsvw ClWZvf literal 0 HcmV?d00001 diff --git a/_static/locales/lt/LC_MESSAGES/booktheme.po b/_static/locales/lt/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..01be267 --- /dev/null +++ b/_static/locales/lt/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: lt\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Tema" + +msgid "Open an issue" +msgstr "Atidarykite problemą" + +msgid "Contents" +msgstr "Turinys" + +msgid "Download notebook file" +msgstr "Atsisiųsti nešiojamojo kompiuterio failą" + +msgid "Sphinx Book Theme" +msgstr "Sfinkso knygos tema" + +msgid "Fullscreen mode" +msgstr "Pilno ekrano režimas" + +msgid "Edit this page" +msgstr "Redaguoti šį puslapį" + +msgid "By" +msgstr "Iki" + +msgid "Copyright" +msgstr "Autorių teisės" + +msgid "Source repository" +msgstr "Šaltinio saugykla" + +msgid "previous page" +msgstr "Ankstesnis puslapis" + +msgid "next page" +msgstr "Kitas puslapis" + +msgid "Toggle navigation" +msgstr "Perjungti naršymą" + +msgid "repository" +msgstr "saugykla" + +msgid "suggest edit" +msgstr "pasiūlyti redaguoti" + +msgid "open issue" +msgstr "atviras klausimas" + +msgid "Launch" +msgstr "Paleiskite" + +msgid "Print to PDF" +msgstr "Spausdinti į PDF" + +msgid "By the" +msgstr "Prie" + +msgid "Last updated on" +msgstr "Paskutinį kartą atnaujinta" + +msgid "Download source file" +msgstr "Atsisiųsti šaltinio failą" + +msgid "Download this page" +msgstr "Atsisiųskite šį puslapį" diff --git a/_static/locales/lv/LC_MESSAGES/booktheme.mo b/_static/locales/lv/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..74aa4d8985d96a07c4c9be96f006f3b58d884342 GIT binary patch literal 1404 zcmZ9K&5ImG7{*_dsL7ZQP5eMvump*E7&XB|oMjFhcNYS?IAk~8Yi8c*sqUVtras2( zdKwT<9)#7Cr{GC*^B|r)^?-kXCk3y9;7t%O;`2^-vdb1-{p+f(exK)k=-;oN`-(7L z!d%1r1@l$R&!4~zPs;uHG2 zUH=1$um8Z;!As|eUIA~m+y%w|6qJ5G0bd5c0G|fGYu|qlzJT=-lzP8`lHs4A_&D=q zlgkxQ>Rkt~f$z861tmufO5Zssk;}JoUbN-BWGj829FU-AF-2E~^e;o|NY;|8ctc5g z22*^U9FmJ@OFxKVl@HxMz@_4p=>umY+Zgar9e9&XBW=2mZRzw_Sr>WeT%jhWmHkCxl1EW^k%TQzfIrX3xkO4V3L9xG?DPIfe<4=WtdR+$hI z)4&^xB2Eo9w`s4@^IW-LqVor|S51w*uWpOC{VC6wR(CaQdfIncRMGG) zBv*eURUdB+Oli45Wvi9v9Ia6vne84ZIht?0o$f< A2mk;8 literal 0 HcmV?d00001 diff --git a/_static/locales/lv/LC_MESSAGES/booktheme.po b/_static/locales/lv/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..993a1e4 --- /dev/null +++ b/_static/locales/lv/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: lv\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Autora tēma" + +msgid "Open an issue" +msgstr "Atveriet problēmu" + +msgid "Contents" +msgstr "Saturs" + +msgid "Download notebook file" +msgstr "Lejupielādēt piezīmju grāmatiņu" + +msgid "Sphinx Book Theme" +msgstr "Sfinksa grāmatas tēma" + +msgid "Fullscreen mode" +msgstr "Pilnekrāna režīms" + +msgid "Edit this page" +msgstr "Rediģēt šo lapu" + +msgid "By" +msgstr "Autors" + +msgid "Copyright" +msgstr "Autortiesības" + +msgid "Source repository" +msgstr "Avota krātuve" + +msgid "previous page" +msgstr "iepriekšējā lapa" + +msgid "next page" +msgstr "nākamā lapaspuse" + +msgid "Toggle navigation" +msgstr "Pārslēgt navigāciju" + +msgid "repository" +msgstr "krātuve" + +msgid "suggest edit" +msgstr "ieteikt rediģēt" + +msgid "open issue" +msgstr "atklāts jautājums" + +msgid "Launch" +msgstr "Uzsākt" + +msgid "Print to PDF" +msgstr "Drukāt PDF formātā" + +msgid "By the" +msgstr "Ar" + +msgid "Last updated on" +msgstr "Pēdējoreiz atjaunināts" + +msgid "Download source file" +msgstr "Lejupielādēt avota failu" + +msgid "Download this page" +msgstr "Lejupielādējiet šo lapu" diff --git a/_static/locales/ml/LC_MESSAGES/booktheme.mo b/_static/locales/ml/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..2736e8fcf6f9e923c2403307f0b366086d37b335 GIT binary patch literal 1883 zcmbW0%ZnUE9LGydG>*^22ObnFl0!U=*`!Gj=35eWDu@Vn6%SYIC#v~L=<+PV8oUUd{}t%`e}*gYclZSS_^!ZZxSjb`_!_(p zTd=uFh;ewl;wqeG{x{qKTbqR#gE5?hpTno&U(oq&;Si6(7JLc50p0#-xD$R4pMlrl zez^G_At=eHx!OEj&F+K95`^|`3%xs|tB0$dYp$lQaXj&eABB3jp*ug}eRDN&btbLg zC_?O6*AzH~{-A|&9)JdV{ljJRVAnvQRl4{_?&D7b7KD1k z&HJ`jzT)e&M4gbqlB?mhqaXMpAZg<;-hlh5ZiX1=e36nUswzgb&SN${bnp4Gv=IQ6$P05hgaiFop^2w W+5FkQ^s?wV7=JSkIl3Km4aE({iDO&< literal 0 HcmV?d00001 diff --git a/_static/locales/ml/LC_MESSAGES/booktheme.po b/_static/locales/ml/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..81daf7c --- /dev/null +++ b/_static/locales/ml/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ml\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "പ്രമേയം" + +msgid "Open an issue" +msgstr "ഒരു പ്രശ്നം തുറക്കുക" + +msgid "Download notebook file" +msgstr "നോട്ട്ബുക്ക് ഫയൽ ഡൺലോഡ് ചെയ്യുക" + +msgid "Sphinx Book Theme" +msgstr "സ്ഫിങ്ക്സ് പുസ്തക തീം" + +msgid "Edit this page" +msgstr "ഈ പേജ് എഡിറ്റുചെയ്യുക" + +msgid "By" +msgstr "എഴുതിയത്" + +msgid "Copyright" +msgstr "പകർപ്പവകാശം" + +msgid "Source repository" +msgstr "ഉറവിട ശേഖരം" + +msgid "previous page" +msgstr "മുൻപത്തെ താൾ" + +msgid "next page" +msgstr "അടുത്ത പേജ്" + +msgid "Toggle navigation" +msgstr "നാവിഗേഷൻ ടോഗിൾ ചെയ്യുക" + +msgid "suggest edit" +msgstr "എഡിറ്റുചെയ്യാൻ നിർദ്ദേശിക്കുക" + +msgid "open issue" +msgstr "തുറന്ന പ്രശ്നം" + +msgid "Launch" +msgstr "സമാരംഭിക്കുക" + +msgid "Print to PDF" +msgstr "PDF- ലേക്ക് പ്രിന്റുചെയ്യുക" + +msgid "By the" +msgstr "എഴുതിയത്" + +msgid "Last updated on" +msgstr "അവസാനം അപ്‌ഡേറ്റുചെയ്‌തത്" + +msgid "Download source file" +msgstr "ഉറവിട ഫയൽ ഡൗൺലോഡുചെയ്യുക" + +msgid "Download this page" +msgstr "ഈ പേജ് ഡൗൺലോഡുചെയ്യുക" diff --git a/_static/locales/mr/LC_MESSAGES/booktheme.mo b/_static/locales/mr/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..fe530100d7715cdc19a6f9db33a971665835f3c4 GIT binary patch literal 1674 zcma))-D_M$7>7rVU#qnriYO?KB2uYGt)hetL1>ylCBZ;a@uD{;yVJ8rH#3KG&bG~6 zRisua;ze5NO^wW!;71IF+EldSwKo+61wrPsjrLTQ<5nO9X$iPPmDi?R5_3f- z*T>{OU(0+)Eh-V7av_#JZ?debq)w0ISz70aXmzZP)flf6MT$}#$xUxiX4T6wMQMt1 z(Km0ZR-GJZC$ForB1Kb1(Zq`;L9Q`#U}kc-zxUba8xuy?O4rH!QlXl%M)kR(o922< zwmNB9se1h2{8TbJJXfZ=I;_fMQnySy*I84JF64D%I@MVZ^O|z8Y|M6hW!g=qOu1M! zr7ps>8h>F-#@F%PT0TB5_dY$=5YC=={Zr0fboPp~>pX9~wCwsPo&DVPkH=Hao^bXY zXIEYSL*AVI()HhVc3C?6MacEOvlp1GgbA^$%){9gR+l%mHiEnj&-JixH&Y;SGbt{+ z{t03z?p+g;%KlU0jXnJ;6hm+E zO4d<`2T4o{Hn?Oyg$)#jm)Q^UYaHJCp>S-t$!CBi7ej)}A>Wy>@(p%y@Lc$O&cyp1 zdP#?v^I4GaH+|g|B8k!Ldl%Wfwrg(}`)i>kl#a*D@zz$^*>a1%2AcIZ5x;fu4@Sqm A6951J literal 0 HcmV?d00001 diff --git a/_static/locales/mr/LC_MESSAGES/booktheme.po b/_static/locales/mr/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..fd857bf --- /dev/null +++ b/_static/locales/mr/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: mr\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "द्वारा थीम" + +msgid "Open an issue" +msgstr "एक मुद्दा उघडा" + +msgid "Download notebook file" +msgstr "नोटबुक फाईल डाउनलोड करा" + +msgid "Sphinx Book Theme" +msgstr "स्फिंक्स बुक थीम" + +msgid "Edit this page" +msgstr "हे पृष्ठ संपादित करा" + +msgid "By" +msgstr "द्वारा" + +msgid "Copyright" +msgstr "कॉपीराइट" + +msgid "Source repository" +msgstr "स्त्रोत भांडार" + +msgid "previous page" +msgstr "मागील पान" + +msgid "next page" +msgstr "पुढील पृष्ठ" + +msgid "Toggle navigation" +msgstr "नेव्हिगेशन टॉगल करा" + +msgid "suggest edit" +msgstr "संपादन सुचवा" + +msgid "open issue" +msgstr "खुला मुद्दा" + +msgid "Launch" +msgstr "लाँच करा" + +msgid "Print to PDF" +msgstr "पीडीएफवर मुद्रित करा" + +msgid "By the" +msgstr "द्वारा" + +msgid "Last updated on" +msgstr "अखेरचे अद्यतनित" + +msgid "Download source file" +msgstr "स्त्रोत फाइल डाउनलोड करा" + +msgid "Download this page" +msgstr "हे पृष्ठ डाउनलोड करा" diff --git a/_static/locales/ms/LC_MESSAGES/booktheme.mo b/_static/locales/ms/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..f02603fa2522a40060bd3f1b5d65052c77530de6 GIT binary patch literal 1213 zcmZXRJ8Km|6vs!6uj@1M0TG1}Eworov@58TBL2_ajS)TU%x`DrywA6>k!K8Y7V9F`8>~xM5BFh% zd;s@@AHhT5C-5lv6+91q2g&v)I0lYF`6PH1JO$nc$*v2Y0Pldu!3W?dC>w4z_m7+N zHb`+^fGzM9NcL|*vVRZ02ETwK;L`&&w?VSo0ms4TAm#b4;b-tP&Og8l;4hH$$Kizh zUTHW1Qhptf^p`=>djwK_>)<(X03HLMfK>lZ^ZpV{}g%EROCaZxzWLzM_G6K*tH6hX%sTdt($LUZL@kZi>& z4I{%>X6M;z?cd7EIOUBUu+=J4dW+9cF1<{ak_~s>uT$@tG%Y08Vne0ED+JMU%h%Z$ zic<%vtlUs0G-K1wUB*6INTU1FI=E=_I%q^eqhYw#(!$c*-uvW@iB{KW zFSU<)gG#o!N7S2DA(WoxaVD&jzH_fPA5HD)S)tvUw9%Z7O`>$#=2Ly;TZ=-c0nKak z(zRBKU_}wl8(X?I*VXXoI=7~I{oA>w`Q;9uyguDx%Y{TQY0E^;V^w*;2yki7=)(TYV{?8_pQ^c*8Iog%4v$iD&q$RjNP literal 0 HcmV?d00001 diff --git a/_static/locales/ms/LC_MESSAGES/booktheme.po b/_static/locales/ms/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..b616d70 --- /dev/null +++ b/_static/locales/ms/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ms\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Tema oleh" + +msgid "Open an issue" +msgstr "Buka masalah" + +msgid "Download notebook file" +msgstr "Muat turun fail buku nota" + +msgid "Sphinx Book Theme" +msgstr "Tema Buku Sphinx" + +msgid "Edit this page" +msgstr "Edit halaman ini" + +msgid "By" +msgstr "Oleh" + +msgid "Copyright" +msgstr "hak cipta" + +msgid "Source repository" +msgstr "Repositori sumber" + +msgid "previous page" +msgstr "halaman sebelumnya" + +msgid "next page" +msgstr "muka surat seterusnya" + +msgid "Toggle navigation" +msgstr "Togol navigasi" + +msgid "suggest edit" +msgstr "cadangkan edit" + +msgid "open issue" +msgstr "isu terbuka" + +msgid "Launch" +msgstr "Lancarkan" + +msgid "Print to PDF" +msgstr "Cetak ke PDF" + +msgid "By the" +msgstr "Oleh" + +msgid "Last updated on" +msgstr "Terakhir dikemas kini pada" + +msgid "Download source file" +msgstr "Muat turun fail sumber" + +msgid "Download this page" +msgstr "Muat turun halaman ini" diff --git a/_static/locales/nl/LC_MESSAGES/booktheme.mo b/_static/locales/nl/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..e59e7ecb308a7648cd23aa6342a9ad98a61d0009 GIT binary patch literal 1356 zcmZXTJ5Los6vqcag)1TtUj+$cqf)Gju^^CJh(JODkqBZvyL;~La`(<`W@dTSmfC47 z`~-XfW8nv|v9q$Ewb8~-3*-OXUAP1%JNw%?Gxz+@WA4%Tz*~WF19KAdE9MmDt3JFi z2G0qBM-1V00UQPg!3l5(oCL3fx52Am6C4Mhfg>P+S3qC$CCGl>fS1Ad;4pXyj)5O) zey;7`>h*V!^?rj5u)n|h{RqhGNs#^A0Y8F|zya_lcoF;svhE*{ng4G|2HU zfE@n|kmKI2*9Rc$zXmzZceVWx9L4%m%`YJ5bp-OcA0YetTieIZSNl^S#~pwZ;4H`` z=N$Mv$HI25E$f~haMji1Jb17l9<0YPv;H+qxD=N#xwoeW*MWP;bwN40{S^!Qc%)BB zJTcmn_6{G#zRi--xzS!`5#mI~uCZ|uI< zDAG*t$pwyWGo=oR?puacPMao4a*|r@WQp<_L^SRBDmueDl}KS}Co^Ro_9^$SOcFwr zgiH{M*`~+`D{-(z*1_AHtn>rc54y^YwUxD{-u}$J2aUS0!RCHJbJ8P#`$euYJujnF zSx3J4d~-RN?VYnqyB67CNk=BmbTTJr!^}5Ul}<|3bx!KMv7VP!<-xMC9S1|vUApGO zd0Bln?`nCgDQBkV8|as@-IqkwS9EI1Sg6udX`Q7gMb~>RJ??afw3Uu~8!34iTBHBl zi0Od1qM24Aq+POY$n;EGCeKm6M7k&?+d-F=M@18=IxkHDla2^|PO9GX1u3ivbE1xT z+=^}4Zo{ONva*On--8-OUjI=r94V1Y}`N=IHv19Ut jbWAeLReX?b<52fDoT%;?`~gm~I(s23S;SN2irW1H>^?=m literal 0 HcmV?d00001 diff --git a/_static/locales/nl/LC_MESSAGES/booktheme.po b/_static/locales/nl/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..f16f4bc --- /dev/null +++ b/_static/locales/nl/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: nl\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Thema door de" + +msgid "Open an issue" +msgstr "Open een probleem" + +msgid "Contents" +msgstr "Inhoud" + +msgid "Download notebook file" +msgstr "Download notebookbestand" + +msgid "Sphinx Book Theme" +msgstr "Sphinx-boekthema" + +msgid "Fullscreen mode" +msgstr "Volledig scherm" + +msgid "Edit this page" +msgstr "bewerk deze pagina" + +msgid "By" +msgstr "Door" + +msgid "Copyright" +msgstr "auteursrechten" + +msgid "Source repository" +msgstr "Bronopslagplaats" + +msgid "previous page" +msgstr "vorige pagina" + +msgid "next page" +msgstr "volgende bladzijde" + +msgid "Toggle navigation" +msgstr "Schakel navigatie" + +msgid "repository" +msgstr "repository" + +msgid "suggest edit" +msgstr "suggereren bewerken" + +msgid "open issue" +msgstr "open probleem" + +msgid "Launch" +msgstr "Lancering" + +msgid "Print to PDF" +msgstr "Afdrukken naar pdf" + +msgid "By the" +msgstr "Door de" + +msgid "Last updated on" +msgstr "Laatst geupdate op" + +msgid "Download source file" +msgstr "Download het bronbestand" + +msgid "Download this page" +msgstr "Download deze pagina" diff --git a/_static/locales/no/LC_MESSAGES/booktheme.mo b/_static/locales/no/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..6cd15c88de675226c00ca4d0430171075e5559ff GIT binary patch literal 1317 zcmZ9KJ#5r46vxeXdz6pzxm3a|d<+2!3{|TeDD*@{E2`eX#NxZWChjG6WIIQ@F#r=I zh=CaiW+cQ+7sSlefekSsA;E&g!2exRwZe-1i=UnMe;@gJZ0`$!aT;?1^9$w~%xAl> zV2tb*0*@HQvL74+N5JFYC^!M00?&abz$SPMTm}z=1ReoH&Bq}7c@7=|Ux8!bTW}nF zU-MIK->moFLDu^NHo!f5s_zejyq^Hs&w20zcpb!5@dLyoequQQ{ss?%e?g9WWG`|7 z&ww2NwR(RWJc|7Tkn_pGec+?o{vnrOx2I^Ydmn%A>ZL_zf>(PJ4kZLarm5`W=b%5)w zZL7>O-*ZGp<~Am=pnQ;J5vxG4v+R9LTr zb?c&Cq}r^>S&prfQchyH%5IfY$0kWe(x`z>RL~GHv=*x9EbCMvg`Y>jh2AfB-HRnbKxP z_EP0Mh336ZE1KHA=alg)i!%*zV<7HREar_#Z59h#6sa0`M0_gBf~5&B$u(bn(=RqnJ4d{?xCazSi7Dd36F5NEp? z<)YnpdLTAmS7{(1PP{Mcl94asi9}+1PF;uA{A!sWqQCgLP1e#J@rEvuCjIeG)u_ z_zHL&oC3+mBarlB@FchjQl1we?OzAU{{~3=--1+!&*l7gkoNrokAjC_hW4EWNq-dF z2i^p!UUxt$Ipw67YDs=blg_=fL9(w&^`%C>sF5z^AYYUllKnH&-R^8uf4W1;k81~m7!h)9ylfZ~^CgwY?O|s!8_53#eN#D}ib%4l zPdl`G0* zrR^Q^E{h@wml7v|6|*b@U!4i752bZbtMMX#mGW2nnJcq1vs2siW24t9Wnrs}c`9q% z!@$)v5lT<+ped}AzW!iwx;nnS&I;|8q^(Zrz=TRiH9p=@zH(RSC_`OqJWVR|NoGY- zoi?`RYFwxN(ABR`V3KC)moz_L=VO;ADlp!Wow9!{+QNF%d)$vmWXUlwR2&%HTrgJW19E;7l zzACcDJ`;)Rh+tW;2Q~|urlsI%&bL2qk_T%ViEOb+o5j!ziwCfPoA2cCtFji~wj$ZA z@p+raPIaI5KE$fLmvXo`p>N|Ts6=nA`!wj_O|+>xW d^Crc{P^+yKEfI-Mu31OGXlgVp$}sP%{Q=l!SrY&N literal 0 HcmV?d00001 diff --git a/_static/locales/pl/LC_MESSAGES/booktheme.po b/_static/locales/pl/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..80d2c89 --- /dev/null +++ b/_static/locales/pl/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: pl\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Motyw autorstwa" + +msgid "Open an issue" +msgstr "Otwórz problem" + +msgid "Contents" +msgstr "Zawartość" + +msgid "Download notebook file" +msgstr "Pobierz plik notatnika" + +msgid "Sphinx Book Theme" +msgstr "Motyw książki Sphinx" + +msgid "Fullscreen mode" +msgstr "Pełny ekran" + +msgid "Edit this page" +msgstr "Edytuj tę strone" + +msgid "By" +msgstr "Przez" + +msgid "Copyright" +msgstr "prawa autorskie" + +msgid "Source repository" +msgstr "Repozytorium źródłowe" + +msgid "previous page" +msgstr "Poprzednia strona" + +msgid "next page" +msgstr "Następna strona" + +msgid "Toggle navigation" +msgstr "Przełącz nawigację" + +msgid "repository" +msgstr "magazyn" + +msgid "suggest edit" +msgstr "zaproponuj edycję" + +msgid "open issue" +msgstr "otwarty problem" + +msgid "Launch" +msgstr "Uruchomić" + +msgid "Print to PDF" +msgstr "Drukuj do PDF" + +msgid "By the" +msgstr "Przez" + +msgid "Last updated on" +msgstr "Ostatnia aktualizacja" + +msgid "Download source file" +msgstr "Pobierz plik źródłowy" + +msgid "Download this page" +msgstr "Pobierz tę stronę" diff --git a/_static/locales/pt/LC_MESSAGES/booktheme.mo b/_static/locales/pt/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..d0ddb8728e1d5ef72dddc1537f66aa32251a83c8 GIT binary patch literal 1364 zcmZ9KJ!lj`6vsyszs~RYi3A)AKVkhsL@peXm>dKW4Dqy|yM5Uk-JMxyXV09qrC4bb zE3pu<6hyS##>&dd!p6cz!N$T$|8I9gLWZ0D-MpQB@BjWY-^NCt35+9{h16S(zZ$SR;BglC^gY3_DkUjkg^8V2+RlY+YuTO%k z_iDYq0kY*B<9wX!0496Oy4Me+EOW5GJh*=z>>q1pUk_m-WvQ8UtRL(@Yuttj8%m$V z)DS=E`y_5yrAF9A~6$c zkJPKnb{@xB&k-4!*pS4W%Dl|ePxSZ1+Sg`TPO-L5pAr(~Q+BJKIyQ=8l12@5q`XEEL(9HWXSq&QBy}{>iJ+c4DOK2kgX}J`T^Gu%F2!T+4-5Z_m|FJY}CdEoncB%=^@}k z8Y^ukWUsGWM!t2s(+;k!?Q_axOXPwX)3c#AQBz*)YTuYsCd%P!Q>MPL5a&+CLEE|{ zYf6)r%dB;ILRNoUXN)}2l9$d-G{iJ)q}Wy`Tzm+v2(=>^C{+#@RV=2IURF*jcR$wy zD??aTpZLaCOMFYpAW1l*WLmt4v{B_@b0}L2&D+qT-&mnh(n=I7vDb-`%I7N94^{E1 zcxfdiIC)dNQVDLK6_Z`3WS+>>*=|gU60=F_bfO(LmX~0$I{o6U(^gh;I@l*sE7k*N z>oXB$Fttuh#-5x(d)$^9P*fEbsVm+tv!2x!?&s);C8;hsuS6ZkWkdpvO!dtuOAFi$ LL?J8GWh3H0!r)O_ literal 0 HcmV?d00001 diff --git a/_static/locales/pt/LC_MESSAGES/booktheme.po b/_static/locales/pt/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..45ac847 --- /dev/null +++ b/_static/locales/pt/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: pt\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Tema por" + +msgid "Open an issue" +msgstr "Abra um problema" + +msgid "Contents" +msgstr "Conteúdo" + +msgid "Download notebook file" +msgstr "Baixar arquivo de notebook" + +msgid "Sphinx Book Theme" +msgstr "Tema do livro Sphinx" + +msgid "Fullscreen mode" +msgstr "Modo tela cheia" + +msgid "Edit this page" +msgstr "Edite essa página" + +msgid "By" +msgstr "De" + +msgid "Copyright" +msgstr "direito autoral" + +msgid "Source repository" +msgstr "Repositório fonte" + +msgid "previous page" +msgstr "página anterior" + +msgid "next page" +msgstr "próxima página" + +msgid "Toggle navigation" +msgstr "Alternar de navegação" + +msgid "repository" +msgstr "repositório" + +msgid "suggest edit" +msgstr "sugerir edição" + +msgid "open issue" +msgstr "questão aberta" + +msgid "Launch" +msgstr "Lançamento" + +msgid "Print to PDF" +msgstr "Imprimir em PDF" + +msgid "By the" +msgstr "Pelo" + +msgid "Last updated on" +msgstr "Última atualização em" + +msgid "Download source file" +msgstr "Baixar arquivo fonte" + +msgid "Download this page" +msgstr "Baixe esta página" diff --git a/_static/locales/ro/LC_MESSAGES/booktheme.mo b/_static/locales/ro/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..3c36ab1df7c589ad82614599b8c91f072a25d4a6 GIT binary patch literal 1390 zcmZ{jxo;Ce6vhX_5zG}5ZUr$kT#~s&fgHI>97~Z1L||yB#=9@;f%VL44!~(cNeM!T zzkmW7Bt%b&NVHTGv{Xn`NHmD=truc}813$F=kWX9`}X8CsJNO-Bou44rIk82E zW8ekwD0mG#0%~vyTm=t+&p?jz3S_U|fL!MXkn8*mPJmxQ*7*st&Nlprc^KsLXDc>A z&U>kv-vQZju7S_7m#oj;a^0f?p-U~+<-u`yunv38zH-h8DR$!Kd`AcS&)<;qgbk%n zVs?N_h8~GIYXX_z@lp(&&U!(#>;scql}cj+b*;T8mvv4X%iczp&|iz8r@bsxMq)nI z0il0S+cD35;)smw+mysr<%5hxssg3b8qA|fdg6M41IkG4eI&8uv_TLnms)LcbExO2 zuwDo22I6MX)8?U^<=i?w>XRs+vOBD)W3wzLY1Dn4sh}ZZ=wTRUXIW<`QaHM=ZLHEB z3GZW;5wavyf>i8XN#8^5U79nrN}tCR1WA7O>Nc7D^1!X_=B#5k}&OPu5mlqSjw% ze9!ggnq18PeE0wD`{?}IYPqW%0!Wn*zA9eO0NP-Sd!P*Z&(5Mvp+E_$mG57h;3yNf z@}T<)Q9@L?UQv!@t~hzGN|ByUi8HjaaJHLM9|{Y76xA;^5T@*t78+y)y;r5zA;cW% z6j3gq1Ltf%1{N7Mh$B&^tz>kF94xj(C8Xe$PteOytPUysU!2AvEWuE6Fj7Z>o*_qS K1txIYaExD}s9q8P literal 0 HcmV?d00001 diff --git a/_static/locales/ro/LC_MESSAGES/booktheme.po b/_static/locales/ro/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..532b3b8 --- /dev/null +++ b/_static/locales/ro/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ro\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Tema de" + +msgid "Open an issue" +msgstr "Deschideți o problemă" + +msgid "Contents" +msgstr "Cuprins" + +msgid "Download notebook file" +msgstr "Descărcați fișierul notebook" + +msgid "Sphinx Book Theme" +msgstr "Tema Sphinx Book" + +msgid "Fullscreen mode" +msgstr "Modul ecran întreg" + +msgid "Edit this page" +msgstr "Editați această pagină" + +msgid "By" +msgstr "De" + +msgid "Copyright" +msgstr "Drepturi de autor" + +msgid "Source repository" +msgstr "Depozit sursă" + +msgid "previous page" +msgstr "pagina anterioară" + +msgid "next page" +msgstr "pagina următoare" + +msgid "Toggle navigation" +msgstr "Comutare navigare" + +msgid "repository" +msgstr "repertoriu" + +msgid "suggest edit" +msgstr "sugerează editare" + +msgid "open issue" +msgstr "problema deschisă" + +msgid "Launch" +msgstr "Lansa" + +msgid "Print to PDF" +msgstr "Imprimați în PDF" + +msgid "By the" +msgstr "Langa" + +msgid "Last updated on" +msgstr "Ultima actualizare la" + +msgid "Download source file" +msgstr "Descărcați fișierul sursă" + +msgid "Download this page" +msgstr "Descarcă această pagină" diff --git a/_static/locales/ru/LC_MESSAGES/booktheme.mo b/_static/locales/ru/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..6b8ca41f36ebf869818399a9584cdb15619bea78 GIT binary patch literal 1722 zcmZ{iPiz!b9LJx6N>>C0{~WCHj6uL;MNkv6buUP3NFY{Oy-#-^yQABg$;>R!8?=By zpk6eZkcjo>ZEd^jw#)9`jK?>LiHQeq#*-Is-2D7zrnWZnvTr^!zxmDY_x*j}{=RSL zmx}cqdz}3X`vCjaLtI$99#)E<8sqXP+zofZ{csG9!)M_u@M&0v```y~4>WKujB{Rv zQs)c!1iS-x!|&l!u$%MeJpNn${3n!t_hA9<*pYp|2g>s}lsboC555U^!oQ&C`x}bB zF@i6^7vWp*ZFm@l@KtyR9)~}{gYZ5)1P?rt)qfX0&vOMzodC-FMW|sH%3Qy~Bk&LS zGTh71lK%!g2;Ya|(?xg`eg?&InL*;Bbw69Q%iLQRlGKxI@mH42FH8IruciMpY+9?w z*>bj97p>AWd<Owguyc8|lEQ8#P&TV@hv4PPLlNs2UpM=~=&K)EOs=bt|Yjv8id_3$EYFWp61Twd!?)O2Z^b@jo`zxOlo&{K$k6 z)k-?+UzGmEv~%I?>9doY?~lFqdLcKqSeXk!s4V?^=qzIFXM1NyDcB~ z^h;%Z?8rnx*}Ha_UXm-xW!tfr6}wJC zN81q@gr(9Fv3Bw)dp^0PldHtnY+u_Sxf$6W-wgO>O_L_|y0EwXD@jYPrM(BqO_Ddt zDEk#lk9`p%b*uDr%Zu6PU zG_bh>@urJlTp^1w`f2$AR}2{1AJVy&({OH-XdNXBVw1Appn{Ug&D59FU~!E~qO?uY z2%}Tqa+P*D{a@R!x0@kSMzqWv;2@B-rtEiw@7eZ-vn#fz?Gn!QP_`~@{!JJr^D>2; zYX|@P$s&z$lLI4H4zg!gP;s5$q8v^-E0ZiHHwb^e&1~CN%&|G1oY;Q{yqk7fcCfJk literal 0 HcmV?d00001 diff --git a/_static/locales/ru/LC_MESSAGES/booktheme.po b/_static/locales/ru/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..b718b48 --- /dev/null +++ b/_static/locales/ru/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ru\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Тема от" + +msgid "Open an issue" +msgstr "Открыть вопрос" + +msgid "Contents" +msgstr "Содержание" + +msgid "Download notebook file" +msgstr "Скачать файл записной книжки" + +msgid "Sphinx Book Theme" +msgstr "Тема книги Сфинкс" + +msgid "Fullscreen mode" +msgstr "Полноэкранный режим" + +msgid "Edit this page" +msgstr "Редактировать эту страницу" + +msgid "By" +msgstr "По" + +msgid "Copyright" +msgstr "авторское право" + +msgid "Source repository" +msgstr "Исходный репозиторий" + +msgid "previous page" +msgstr "Предыдущая страница" + +msgid "next page" +msgstr "Следующая страница" + +msgid "Toggle navigation" +msgstr "Переключить навигацию" + +msgid "repository" +msgstr "хранилище" + +msgid "suggest edit" +msgstr "предложить редактировать" + +msgid "open issue" +msgstr "открытый вопрос" + +msgid "Launch" +msgstr "Запуск" + +msgid "Print to PDF" +msgstr "Распечатать в PDF" + +msgid "By the" +msgstr "Посредством" + +msgid "Last updated on" +msgstr "Последнее обновление" + +msgid "Download source file" +msgstr "Скачать исходный файл" + +msgid "Download this page" +msgstr "Загрузите эту страницу" diff --git a/_static/locales/sk/LC_MESSAGES/booktheme.mo b/_static/locales/sk/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..59bd0ddfa341477cf5ccfdc88f4c3e6127046f7a GIT binary patch literal 1393 zcmZ9KKWrRD6vijSKyrit=ARHoJeoj?1A-``v#uc6mLesxmAg<-Am(Iw==v>7a08THd<;rm`=IpY4k&eh2g>u`gW~ryD0Tk|O5J~fa_(Nc zzXDUK|0PiBy9|o{Iw-jZpgi{xC@mLFS&OFRlMGV#=>h3w2I;R1(UBqg;w6239ut!4 z2~6=jJ)|#^@o`MFWBGp7wHbaCb5`#=8`;KyKjqAuERSl#ePRozQ?f4d$hk4?nu1TZ zgR6YP4{gTW1S)mLYBMzv(*G~Fs-g&qXSOtPDXSYgM5@YEM^4FEtSg)3YP-Y%ZOMdC zvD)#*Ld4O|#+Dj1ex6GgOmu#x24!ySK3$V+!<;9qmRA}zH4R;s6--u7O{SxPiRJy+ zq;ulan3SHU##L?XQ}Ut8GDb>9C5YnoIEmfsY4-#60ct&J{JY}cT{?GeUcb3{a{tPk zZ+F_pc89Z)dlV7it+LR@u2Yh0A2{}J54XBkPtJL5!!G;orcGRGY}TWzBNIC}w9P8? zwMSvx*(oZoi|&^5lh7kuE|;PI&N?-J`)^o!txs1juXogY6?)ZEJ1#xCtJU@>=)Bnr zU1l0t--9arjh>CyA! zZ|R}^TYP-iOeo=k_sEUBK5*0V4ADZtsjcUv$Fb6dIjHA}(Ucy4hGb%cXdqT-thpkjw8w z94mEnM;EAFODWoF<;0UM`ZS%T+8S2)Skfe~=jnmos~5@rll9m4U7_dmM!H@|Co1(H Di}h+h literal 0 HcmV?d00001 diff --git a/_static/locales/sk/LC_MESSAGES/booktheme.po b/_static/locales/sk/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..f6c423b --- /dev/null +++ b/_static/locales/sk/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: sk\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Téma od" + +msgid "Open an issue" +msgstr "Otvorte problém" + +msgid "Contents" +msgstr "Obsah" + +msgid "Download notebook file" +msgstr "Stiahnite si zošit" + +msgid "Sphinx Book Theme" +msgstr "Téma knihy Sfinga" + +msgid "Fullscreen mode" +msgstr "Režim celej obrazovky" + +msgid "Edit this page" +msgstr "Upraviť túto stránku" + +msgid "By" +msgstr "Autor:" + +msgid "Copyright" +msgstr "Autorské práva" + +msgid "Source repository" +msgstr "Zdrojové úložisko" + +msgid "previous page" +msgstr "predchádzajúca strana" + +msgid "next page" +msgstr "ďalšia strana" + +msgid "Toggle navigation" +msgstr "Prepnúť navigáciu" + +msgid "repository" +msgstr "Úložisko" + +msgid "suggest edit" +msgstr "navrhnúť úpravu" + +msgid "open issue" +msgstr "otvorené vydanie" + +msgid "Launch" +msgstr "Spustiť" + +msgid "Print to PDF" +msgstr "Tlač do PDF" + +msgid "By the" +msgstr "Podľa" + +msgid "Last updated on" +msgstr "Posledná aktualizácia dňa" + +msgid "Download source file" +msgstr "Stiahnite si zdrojový súbor" + +msgid "Download this page" +msgstr "Stiahnite si túto stránku" diff --git a/_static/locales/sl/LC_MESSAGES/booktheme.mo b/_static/locales/sl/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..87bf26de683cb18c73bd23c2b4c57ef6a02545ec GIT binary patch literal 1374 zcmZ9KyKfXR5XQ}$9PjWFC=#aOAvj*5h%UN@MVlwf1j4YtMW$vtK7Sz7QA(F{dy;VIIMJx(*A* z*7ZW*5ffN8gWJKa;9hV7oB|Jk$H0AH8=M61fIC3~cY(3y6OjEp2X}z4!0q5`a1Z#l z=EvIprQUx7Io@xu0dCk(-QNlFehOqi$H8~tMQ{`NqvlU=3--Uk-Qc>7LL34o!NcHb zkab@J`TGNq^T|Ly_ZVc|FG1Eh0$KkXa4+~CYpSj^k88a!&*8idy!V z`%t7QK_wv*NO67Y#^!v|yiY#BTT52)n;gGcMsD1kzd5`1{rs78jk>VS#g&{|GD5)F z+$e2lWVfe$pxC~*IM2jgT5~@lP4MDpz zCx-(XW@_w<9uAzh?%#>APv}sH5H9X{E*5diD#H~rZm5EBHe?#D`0z|yaZ3$VV*3d1 zf=gV-^ojji64%jMWljW5^x#&@4 literal 0 HcmV?d00001 diff --git a/_static/locales/sl/LC_MESSAGES/booktheme.po b/_static/locales/sl/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..9822dc5 --- /dev/null +++ b/_static/locales/sl/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: sl\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Tema avtorja" + +msgid "Open an issue" +msgstr "Odprite številko" + +msgid "Contents" +msgstr "Vsebina" + +msgid "Download notebook file" +msgstr "Prenesite datoteko zvezka" + +msgid "Sphinx Book Theme" +msgstr "Tema knjige Sphinx" + +msgid "Fullscreen mode" +msgstr "Celozaslonski način" + +msgid "Edit this page" +msgstr "Uredite to stran" + +msgid "By" +msgstr "Avtor" + +msgid "Copyright" +msgstr "avtorske pravice" + +msgid "Source repository" +msgstr "Izvorno skladišče" + +msgid "previous page" +msgstr "Prejšnja stran" + +msgid "next page" +msgstr "Naslednja stran" + +msgid "Toggle navigation" +msgstr "Preklopi navigacijo" + +msgid "repository" +msgstr "odlagališče" + +msgid "suggest edit" +msgstr "predlagajte urejanje" + +msgid "open issue" +msgstr "odprto vprašanje" + +msgid "Launch" +msgstr "Kosilo" + +msgid "Print to PDF" +msgstr "Natisni v PDF" + +msgid "By the" +msgstr "Avtor" + +msgid "Last updated on" +msgstr "Nazadnje posodobljeno dne" + +msgid "Download source file" +msgstr "Prenesite izvorno datoteko" + +msgid "Download this page" +msgstr "Prenesite to stran" diff --git a/_static/locales/sr/LC_MESSAGES/booktheme.mo b/_static/locales/sr/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..ec740f4852f3973fa72ed0c7f7cf59273b8dba41 GIT binary patch literal 1679 zcmZ{i&2Jk;7>5TMpf#n12FigTrXZCM$qB70R5|j2(nPA%iiifpt=iZVd#SU#+K*9wix4UV%CCk|YD;tzleJn!xzyAg~$`^-$R zf|BP7d;(sF`{57pDcCFcOL6{NvA++c-k-1p_w32;FeHVeLgQ7^hJ zGdzy`B&?ZThjG)5bl^0MnyI@nssG*1CaqRf3ytygl3zFKtP{mL3F=O4>e~0%Ctj_o z-VO+GJncqNV$@vddL;4n-04|$KCc&=z>nP650};Xpy_&-^(oOd-!w}`WnaCJdz$wf zjh4}#bIENuu}cxpT#j>fzSPN!1fjX)`bi;sBz=@L8U~dHCrI%>FtxaRre1!}gb~>) zID-xfGsC|hn|!@gG`2jy9GHrZ5ik|B9M_xHwWbqBCa%6aKU+RIj0+tv zS~OvK#;f^t*K1Vt$ptqqoproMLSHL73QKdXBy?KkSwCEgD%uOOZB#uzt@CB|6;B_j z>SM1?mz2F>J33uW*U}Z+wmY_)ohZA>uESZ+w$lw|zev~9H9JUG(p9@{2io4t;AJmR@7g|5U2Qwul5jS5J6+fI7K$b?*B^Gym(vvm#N%kCu@EWomq3c>6awm HD*E*gL}ZXP literal 0 HcmV?d00001 diff --git a/_static/locales/sr/LC_MESSAGES/booktheme.po b/_static/locales/sr/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..e809230 --- /dev/null +++ b/_static/locales/sr/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: sr\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Тхеме би" + +msgid "Open an issue" +msgstr "Отворите издање" + +msgid "Contents" +msgstr "Садржај" + +msgid "Download notebook file" +msgstr "Преузмите датотеку бележнице" + +msgid "Sphinx Book Theme" +msgstr "Тема књиге Спхинк" + +msgid "Fullscreen mode" +msgstr "Режим целог екрана" + +msgid "Edit this page" +msgstr "Уредите ову страницу" + +msgid "By" +msgstr "Од стране" + +msgid "Copyright" +msgstr "Ауторско право" + +msgid "Source repository" +msgstr "Изворно спремиште" + +msgid "previous page" +msgstr "Претходна страница" + +msgid "next page" +msgstr "Следећа страна" + +msgid "Toggle navigation" +msgstr "Укључи / искључи навигацију" + +msgid "repository" +msgstr "спремиште" + +msgid "suggest edit" +msgstr "предложи уређивање" + +msgid "open issue" +msgstr "отворено издање" + +msgid "Launch" +msgstr "Лансирање" + +msgid "Print to PDF" +msgstr "Испис у ПДФ" + +msgid "By the" +msgstr "Од" + +msgid "Last updated on" +msgstr "Последње ажурирање" + +msgid "Download source file" +msgstr "Преузми изворну датотеку" + +msgid "Download this page" +msgstr "Преузмите ову страницу" diff --git a/_static/locales/sv/LC_MESSAGES/booktheme.mo b/_static/locales/sv/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..b07dc76ff21128244172d2e415cc899555d8b49d GIT binary patch literal 1365 zcmZ9Ky>App7{XZ}|d=zQVMY>d0>TJUwK!GS|siLHd(&c$~H~3(*Gryg$_j%@>d3o;WBZ2ZE>JsWR z)Jv%M7to-bct;3);v|}P!BgM~@H}`DTmmnGm%$If0eB9)11^FDo&i(GpFxiE5Ihb3 z0-geY1>Xk`IzH{jUv&LfAnW}L_P`@Y+Wm_l_m@D9a|Qez{0hWU@h8Z7e}laLACT8A z9Bq9sg6#KG@FQ>;^|ue&MB7Xc{&_$WV4fmrpPUX_NMBC1d<&HLVI2>ISM)cNT zDs_}z6(rVjoe=u}?s{cR90ejPCoU&(OT{EBpQ}W+2Kkatlh7xu)KFSXs3tL$x9(u73Q%I)?{Lst}rq*YU0sH7ocX*ad*9P6|q zKG0OVs2vT8zb&|U%F`w^(-Z1 zKF^i36kcC+hKrsX9@jHt-W)0~UWJ0RHRwJIJFG|WNq7Z50sn;0!@U&o7(5PV;9F4M{{RobKj41& z@a;;?!xtbeX@>OX{(5y6M3y47A9wJS8l@l7I~meb8I-3U@UzelnM(bH_d|LjeI~u4 zB&Ck5^3z4%s2P{8W=Y&H)T}#g2QKPq>k6~t+?)DDGB7*axf^C(bKPdqPja0`u~Boq zq#)vWxe(=r9;UshFg@+8T8M_W+gC58#_GuGB+rLNEoOcl%M6n_~Kv<@xsE9lI>D`3aM?=WN&Y5*v5);gzIlEkrgR(mY~Bt;NAGiw5m^ zmz~Tz+NOS)Pd_uI!*qJT)%&LPp{J%=sw%gu@~f)+wA%QnDo0iMT~%)Q%}sWAT~-@s zt8&XvWPPzJFLmFFj3kCLZVZKXbJg6qObpgpYXhKc{dPQvXD4*l1`&-oR|ZVWnD5S zLMPGk+4yL_MW)wWJ7GI+sWh)Cq}dE7ao%TGqX8uPK%$P%oUIVNaozG6uhIA~XTs-( z77E8j3VKIkNhd=@QrBItuMs9x^kr3kK4HautE;{2cexG}GQN=#P4;o6q{&7}8xZ++ zl w$ZZQ&WaeX;?9mtGBq&}escqTfGyJc(*W8(47(T)#0?{xcP9tpFr||Or2L57y?*IS* literal 0 HcmV?d00001 diff --git a/_static/locales/ta/LC_MESSAGES/booktheme.po b/_static/locales/ta/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..500042f --- /dev/null +++ b/_static/locales/ta/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ta\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "வழங்கிய தீம்" + +msgid "Open an issue" +msgstr "சிக்கலைத் திறக்கவும்" + +msgid "Download notebook file" +msgstr "நோட்புக் கோப்பைப் பதிவிறக்கவும்" + +msgid "Sphinx Book Theme" +msgstr "ஸ்பிங்க்ஸ் புத்தக தீம்" + +msgid "Edit this page" +msgstr "இந்தப் பக்கத்தைத் திருத்தவும்" + +msgid "By" +msgstr "வழங்கியவர்" + +msgid "Copyright" +msgstr "பதிப்புரிமை" + +msgid "Source repository" +msgstr "மூல களஞ்சியம்" + +msgid "previous page" +msgstr "முந்தைய பக்கம்" + +msgid "next page" +msgstr "அடுத்த பக்கம்" + +msgid "Toggle navigation" +msgstr "வழிசெலுத்தலை நிலைமாற்று" + +msgid "suggest edit" +msgstr "திருத்த பரிந்துரைக்கவும்" + +msgid "open issue" +msgstr "திறந்த பிரச்சினை" + +msgid "Launch" +msgstr "தொடங்க" + +msgid "Print to PDF" +msgstr "PDF இல் அச்சிடுக" + +msgid "By the" +msgstr "மூலம்" + +msgid "Last updated on" +msgstr "கடைசியாக புதுப்பிக்கப்பட்டது" + +msgid "Download source file" +msgstr "மூல கோப்பைப் பதிவிறக்குக" + +msgid "Download this page" +msgstr "இந்தப் பக்கத்தைப் பதிவிறக்கவும்" diff --git a/_static/locales/te/LC_MESSAGES/booktheme.mo b/_static/locales/te/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..0a5f4b46adfda1551ae6791c3c3782525b61be04 GIT binary patch literal 1806 zcmbu8?`s@I7{^DgzpiR+74e1QD2kPOYU&G1LO_}((2{DPsaEjK=5D&TdYxHz_mbva zT2L$M3z1kXg(AcfwAS4~Neb5f0lujqQV?VieD5FN3qLcn=UrpK7cRH^*?DH3U*CQ1 zw_V$o1=qvek8yv`{W$mAxAEY*0dI#t!Motk@Lu>Ud<6aho$p_87u?C=2jJ6i2YeYi zzX^ChJOuB9$KXz=YA)3F59{^k(B)Z$4Y&rK|263Re}o(GCUki}y(4f1KFWF>z6o!@ z*Wm7LLQKL1xEEf7ufjj!vvA~2A@;zx;Pdc3_zYZw?)**o1l&$Dhu|Lg6r6|7{snaU zU4^f}Um%kFbGaHHtXJD1WeGz1>mHu2N2iC=&RtGZchR1B$iD?W+^g&V?%L)waXOPu z(25ZI7x~Geqr`+s7qcYp6yktc&|MR?r8b3{Gv-}+Jn5=|IXAtmr8XIhPLj(sij|mb zCj}Av%jqaDWG`(;g=$Nq#dOrut&Vs-Ra!<`CVAddVkS#8PDaigm=Z@q{7j`LPYRPQ ziX&+!(I@48SIcZiolwF*xU=VM^?@zFv*l@L zDz6jwvaMLG-4f{crQm*REN}ghN#a8coKPu>p z%YTFt$m|qAXTDh&g5gT~hljsJ*ry=A+<9Nb1sA(o5-xGw{Z;?6OlS@gI#jemLQG%z zrpf6>XY=H3-bW;Qrf>v2>%ZN4n4aM|U<|2-ZBn^mBghuhM0)Dv2+@ei()B(V2&(za uuMrF7ToguSy%w`N&3+IHSt#2LVBfiP)B5iT;9Jx)h5&elIS4O(ZT|-CPABOA literal 0 HcmV?d00001 diff --git a/_static/locales/te/LC_MESSAGES/booktheme.po b/_static/locales/te/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..b1afebb --- /dev/null +++ b/_static/locales/te/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: te\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "ద్వారా థీమ్" + +msgid "Open an issue" +msgstr "సమస్యను తెరవండి" + +msgid "Download notebook file" +msgstr "నోట్బుక్ ఫైల్ను డౌన్లోడ్ చేయండి" + +msgid "Sphinx Book Theme" +msgstr "సింహిక పుస్తక థీమ్" + +msgid "Edit this page" +msgstr "ఈ పేజీని సవరించండి" + +msgid "By" +msgstr "ద్వారా" + +msgid "Copyright" +msgstr "కాపీరైట్" + +msgid "Source repository" +msgstr "మూల రిపోజిటరీ" + +msgid "previous page" +msgstr "ముందు పేజి" + +msgid "next page" +msgstr "తరువాతి పేజీ" + +msgid "Toggle navigation" +msgstr "నావిగేషన్‌ను టోగుల్ చేయండి" + +msgid "suggest edit" +msgstr "సవరించమని సూచించండి" + +msgid "open issue" +msgstr "ఓపెన్ ఇష్యూ" + +msgid "Launch" +msgstr "ప్రారంభించండి" + +msgid "Print to PDF" +msgstr "PDF కి ముద్రించండి" + +msgid "By the" +msgstr "ద్వారా" + +msgid "Last updated on" +msgstr "చివరిగా నవీకరించబడింది" + +msgid "Download source file" +msgstr "మూల ఫైల్‌ను డౌన్‌లోడ్ చేయండి" + +msgid "Download this page" +msgstr "ఈ పేజీని డౌన్‌లోడ్ చేయండి" diff --git a/_static/locales/tg/LC_MESSAGES/booktheme.mo b/_static/locales/tg/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..b21c6c6340194fdf35f7e5660deb42479c8dbff9 GIT binary patch literal 1628 zcmaiyO^6gn6vxZY=tNE8S5Q|hA#9RE$8XSGCI@vF1jR*HLCB?drtIlBTh(+|t9#pZ z_b^Dr#19Y@K@`-J?Yg?{x;qOwd8{6D@{o&%oP^*d#K?f}Wpw_pnH1Q&v@ z3%&tK*FWF}u!PNBU}wRfz%8&Zfe!dP_zn0sxE@@yD9?KJ9kAteKMU^WF zJC>CiI~?GEE4d#GJ20M-!R?)~ z>>S<1-6l7a<}oHySZKVs&CQhc{Mbyqb88w7X3RqzI{&F#*USvhMoiLrM6s>Hk4E|6 zc@o%qM9F2t?V4KSrinZf?58}t0JXzb84{b#Mr}$-{y{=+V#Xn)X(lNzTPtR6wl32O zGdJL5Bs-5oxB+T`zIGRrAt`^lPLZT?M?g!0angPB{%GR5vxHp0oR8Arqi zbZiRp&%w__8!lf*NbDpe;WA2%r?Xi$atSF8VXr;q_FB@_W_A(5kPfr&0p+;^8?eY= pg1vVOUqyoB&tBYSn9xh&7BjPW`v%MukJU629MMs5Ow+8v{s(GpYQg{j literal 0 HcmV?d00001 diff --git a/_static/locales/tg/LC_MESSAGES/booktheme.po b/_static/locales/tg/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..29b8237 --- /dev/null +++ b/_static/locales/tg/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: tg\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Мавзӯъи аз" + +msgid "Open an issue" +msgstr "Масъаларо кушоед" + +msgid "Contents" +msgstr "Мундариҷа" + +msgid "Download notebook file" +msgstr "Файли дафтарро зеркашӣ кунед" + +msgid "Sphinx Book Theme" +msgstr "Сфинкс Мавзӯи китоб" + +msgid "Fullscreen mode" +msgstr "Ҳолати экрани пурра" + +msgid "Edit this page" +msgstr "Ин саҳифаро таҳрир кунед" + +msgid "By" +msgstr "Бо" + +msgid "Copyright" +msgstr "Ҳуқуқи муаллиф" + +msgid "Source repository" +msgstr "Анбори манбаъ" + +msgid "previous page" +msgstr "саҳифаи қаблӣ" + +msgid "next page" +msgstr "саҳифаи оянда" + +msgid "Toggle navigation" +msgstr "Гузаришро иваз кунед" + +msgid "repository" +msgstr "анбор" + +msgid "suggest edit" +msgstr "пешниҳод вироиш" + +msgid "open issue" +msgstr "барориши кушод" + +msgid "Launch" +msgstr "Оғоз" + +msgid "Print to PDF" +msgstr "Чоп ба PDF" + +msgid "By the" +msgstr "Бо" + +msgid "Last updated on" +msgstr "Last навсозӣ дар" + +msgid "Download source file" +msgstr "Файли манбаъро зеркашӣ кунед" + +msgid "Download this page" +msgstr "Ин саҳифаро зеркашӣ кунед" diff --git a/_static/locales/th/LC_MESSAGES/booktheme.mo b/_static/locales/th/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..abede98aa11b163e580a26b545980ace31e61ccf GIT binary patch literal 1766 zcma)*-)|K~6vqcarB^@&)CU_K663GrYB9uM>wQ7mgal$EMW46#4trN`XEwWgD~&H; 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cLPeiV0|6qlnFzL#U0qn`*`iT?nxl@xb2Mx-{rpyeF$L|PmGL73Xj zjT&US*r9DL+Oc6=XyNi4J`IP)4~3RpiSp}N5WkMWZ=`O(hjnrBo?i;ppCMASYj{fI qV*6MBqwc03(drtRAFXAoSBd=B?a4S*sk|OB^ZqtY{YJQZ;_45RC*i9A literal 0 HcmV?d00001 diff --git a/_static/locales/th/LC_MESSAGES/booktheme.po b/_static/locales/th/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..ac65ee0 --- /dev/null +++ b/_static/locales/th/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: th\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "ธีมโดย" + +msgid "Open an issue" +msgstr "เปิดปัญหา" + +msgid "Contents" +msgstr "สารบัญ" + +msgid "Download notebook file" +msgstr "ดาวน์โหลดไฟล์สมุดบันทึก" + +msgid "Sphinx Book Theme" +msgstr "ธีมหนังสือสฟิงซ์" + +msgid "Fullscreen mode" +msgstr "โหมดเต็มหน้าจอ" + +msgid "Edit this page" +msgstr "แก้ไขหน้านี้" + +msgid "By" +msgstr "โดย" + +msgid "Copyright" +msgstr "ลิขสิทธิ์" + +msgid "Source repository" +msgstr "ที่เก็บซอร์ส" + +msgid "previous page" +msgstr "หน้าที่แล้ว" + +msgid "next page" +msgstr "หน้าต่อไป" + +msgid "Toggle navigation" +msgstr "ไม่ต้องสลับช่องทาง" + +msgid "repository" +msgstr "ที่เก็บ" + +msgid "suggest edit" +msgstr "แนะนำแก้ไข" + +msgid "open issue" +msgstr "เปิดปัญหา" + +msgid "Launch" +msgstr "เปิด" + +msgid "Print to PDF" +msgstr "พิมพ์เป็น PDF" + +msgid "By the" +msgstr "โดย" + +msgid "Last updated on" +msgstr "ปรับปรุงล่าสุดเมื่อ" + +msgid "Download source file" +msgstr "ดาวน์โหลดไฟล์ต้นฉบับ" + +msgid "Download this page" +msgstr "ดาวน์โหลดหน้านี้" diff --git a/_static/locales/tl/LC_MESSAGES/booktheme.mo b/_static/locales/tl/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..8df1b73310e0c606251d1abff7e6033d1f6b273f GIT binary patch literal 1273 zcmZ{iJ#P~+7{?8ixA4}MHz7bWh@lJz6qYJggw!_(YD=U9)PcpxxsJ)jKAr8h8TbH< zl>mt^fEW=h3@|dWP{DwN#01}fk%9knmnKyup2YV%`|Ricw;%r;A9>CYr_e5-eL%a2 z_Gk|th%ew?a0@&DeghAKKfp8KZ;;mh1;@cLOg;`?0Z)LpKw38o9s}=zN5K_v43vGY z_s5_1`!7J!c@37pw;-+m2-5n`;Ct{ph(FuhSLAyJ(z;h52j75~!7cDS_y;@-j*b-m zC%}W~-v&p)J0SUA0Z)SpJPAGlY2GGy4txoc|92qy`UKMYuOOYrFAzsE2s#`3PH_Yc zHrRgZAP%9?9w{GbQ&0{H+8gOp(7q^W|Kx>&wCSAbj3LR`Ob>tV+mg-Nw3lhs_H53s zo5YHk8|!7$+74gUi5w0)8?u(%HR#*g@l+_u=40)Val5-HoaZ5pg_kk6hAoOEtD7`fpKHxt1^q`P0PmGs4|~w zYF}CuMg<%mawMf%5;BoQ3pVSzGB;`7b(Ndbym+ll7=Ee3C$CPI*s^AIft_~oQ`+M| zjoMMlC845tP)?QC3^N9mW&fLyY9mxPB*L)jFaumd3$>sZlm_4E_)y1P<99=X&7mSu zQF#bj7^^11I1!U-GjxO_E86t}@}&6i_@% literal 0 HcmV?d00001 diff --git a/_static/locales/tl/LC_MESSAGES/booktheme.po b/_static/locales/tl/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..662d66c --- /dev/null +++ b/_static/locales/tl/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: tl\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "Tema ng" + +msgid "Open an issue" +msgstr "Magbukas ng isyu" + +msgid "Download notebook file" +msgstr "Mag-download ng file ng notebook" + +msgid "Sphinx Book Theme" +msgstr "Tema ng Sphinx Book" + +msgid "Edit this page" +msgstr "I-edit ang pahinang ito" + +msgid "By" +msgstr "Ni" + +msgid "Copyright" +msgstr "Copyright" + +msgid "Source repository" +msgstr "Pinagmulan ng imbakan" + +msgid "previous page" +msgstr "Nakaraang pahina" + +msgid "next page" +msgstr "Susunod na pahina" + +msgid "Toggle navigation" +msgstr "I-toggle ang pag-navigate" + +msgid "suggest edit" +msgstr "iminumungkahi i-edit" + +msgid "open issue" +msgstr "bukas na isyu" + +msgid "Launch" +msgstr "Ilunsad" + +msgid "Print to PDF" +msgstr "I-print sa PDF" + +msgid "By the" +msgstr "Sa pamamagitan ng" + +msgid "Last updated on" +msgstr "Huling na-update noong" + +msgid "Download source file" +msgstr "Mag-download ng file ng pinagmulan" + +msgid "Download this page" +msgstr "I-download ang pahinang ito" diff --git a/_static/locales/tr/LC_MESSAGES/booktheme.mo b/_static/locales/tr/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..029ae18afb5360a8c238a052e8d3971761759d3d GIT binary patch literal 1373 zcmZ{izi%8x6vqdWKynFz!~~?sQXUOIiX{o62)3@sVLOWA2n!$dC&=i7J19yL{j6T0W2%?d)gY?96-L@67yl{`g~s z_CESD`XA_*&>y~r7uw0!mBOP=;q?Z120RHafv3P_@ICND@LjMEo(I1M&w>oT4aSc5 zLCNz7d<%R6o&kRZ&w(7D`FN2cjBk&jSbMQ3yvf}|L z^-dgb=PiL35fdohSHUH48x$WIDEhw##oq%^>ihtT&YwW>`D+*d4$8W}!FRxeF7BOZ z>s|syPtwI-fS96gfHHp*lr0wzl2>wx9;q$97n`h;HKI?N=#nP7WUs~N1$3mG*A#z? 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z$~?F1e_~CYdU3r0$=I6uq5ePVO_Bn=P}riFSZ}qf6oE57w5w3K+FoX+hEW?y<4|&p zx|p)Aw=sGx%}Vw#el49X^(ARiaRizwH+vA!fH?=_BQ=JATO9Uo!rm6_g(Z9Fvrf~J ziFzY}!KTjO`w9hS|3mkKY2Z8hBsWpwH*$FgF5fip{lMp#&N|*Vkp4MHrJJsNw1%8D c^9?3>eEmE8GP@z_uy-`khW>?G>aA{%rxd0lq5uE@ literal 0 HcmV?d00001 diff --git a/_static/locales/ur/LC_MESSAGES/booktheme.po b/_static/locales/ur/LC_MESSAGES/booktheme.po new file mode 100644 index 0000000..94bcab3 --- /dev/null +++ b/_static/locales/ur/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ur\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "Theme by the" +msgstr "کے ذریعہ تھیم" + +msgid "Open an issue" +msgstr "ایک مسئلہ کھولیں" + +msgid "Download notebook file" +msgstr "نوٹ بک فائل ڈاؤن لوڈ کریں" + +msgid "Sphinx Book Theme" +msgstr "سپنکس بک تھیم" + +msgid "Edit this page" +msgstr "اس صفحے میں ترمیم کریں" + +msgid "By" +msgstr "بذریعہ" + +msgid "Copyright" +msgstr "کاپی رائٹ" + +msgid "Source repository" +msgstr "ماخذ ذخیرہ" + +msgid "previous page" +msgstr "سابقہ ​​صفحہ" + +msgid "next page" +msgstr "اگلا صفحہ" + +msgid "Toggle navigation" +msgstr "نیویگیشن ٹوگل کریں" + +msgid "suggest edit" +msgstr "ترمیم کی تجویز کریں" + +msgid "open issue" +msgstr "کھلا مسئلہ" + +msgid "Launch" +msgstr "لانچ کریں" + +msgid "Print to PDF" +msgstr "پی ڈی ایف پرنٹ کریں" + +msgid "By the" +msgstr "کی طرف" + +msgid "Last updated on" +msgstr "آخری بار تازہ کاری ہوئی" + +msgid "Download source file" +msgstr "سورس فائل ڈاؤن لوڈ کریں" + +msgid "Download this page" +msgstr "اس صفحے کو ڈاؤن لوڈ کریں" diff --git a/_static/locales/vi/LC_MESSAGES/booktheme.mo b/_static/locales/vi/LC_MESSAGES/booktheme.mo new file mode 100644 index 0000000000000000000000000000000000000000..2bb32555c3ea0dab08ed37b71cb863fbe75698c6 GIT binary patch literal 1431 zcmZvb&x;&I6vr#s{2bR9catc(#OK8%htWiG2(!#(H#@MntBVvV&v#)!JFr^_{KP>F`@nJV05}OA1gF4b;9KAkunA6pAA*NK z3BCmSiq}An^CkEqxCxGf--9oMKUe&tTK}_}KL%Ov30MQi#>)GLK%P&59Onf13wRdX z3;qSN-ajCp`xj*0y?e@hC&AY-KMlSLE>x7&{%7EEtZ#xGrw?+zzkx4+4=O$aInLi8 z=P?fP6X0=>=PmFs_%X6t9{djXqq7H;REU`#e&m%Dv(|WNyu(A%OLe5YIB!2Su?;$8te4By zUZxct%bjIsvow_dS@cRfN`gp=xsLV-{cPIG;@E|$l!jJqM~a2OdCHPb;AMxb!8|je z5+5Wu5E#l0;esOMR|IFK`YgJ+E?Oq}qlDRK7TFmDND~hLNUKno*_5*I#duC ze1pUH?uya95XS7fK6vqb$6da&5d>$e(Tqr%5FL8(*`2r*YiH`^Z>aE(?ll6i#v)Y{nLNAmS zVZLM|@+Cqff{+L(H9>+X*h#n|&YXJarQWrDsNf1G{?EIRgwekJ?VFu>|Np%Cx20*2 zVQfXTBHkmmBW^Fl3uEes3ZOb zQk?;C9XJZE1)qXHfzuJ+M)Utfc@-qRPhbpOu_D~R9;Cb#q&h!?W$*w<>pw>P43chB zQ^;m;Gx8RY{OyX^7V!v3^?n6uod9Y7@6r5Kko@OC(isEk+)qHNR|2Y~glBh97KqDQIoyw}Q#g=trLPD*?? 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"next page" +msgstr "下一頁" + +msgid "Toggle navigation" +msgstr "顯示或隱藏導覽列" + +msgid "repository" +msgstr "儲存庫" + +msgid "suggest edit" +msgstr "提出修改建議" + +msgid "open issue" +msgstr "公開的問題" + +msgid "Launch" +msgstr "啟動" + +msgid "Print to PDF" +msgstr "列印成 PDF" + +msgid "By the" +msgstr "作者：" + +msgid "Last updated on" +msgstr "最後更新時間：" + +msgid "Download source file" +msgstr "下載原始檔" + +msgid "Download this page" +msgstr "下載此頁面" diff --git a/_static/logo.png b/_static/logo.png new file mode 100644 index 0000000000000000000000000000000000000000..06d56f40c838b64eb048a63e036125964a069a3a GIT binary patch literal 9854 zcmcJ#_ghoX7cGn*K?4W`P^xr9dX-2=s)7_L0g)Pd2}GoYu8}Goq=uqY=^(vJ3q7D9 zgx&ncihTY58>yQhyHVAq6+lGO~MVagOauq5m9v<`6Yyea8LU7g^33d5#6JIpIaLG z-1|gCJhU3BN``QY-K@=)`@JW9M^t~b7uLWQYei|mDOJQ5UUg0~vIqbGt~C8wn@$P% z5pl~zRjG%ihlB(HjNnDEe-dDz2JixSk(`6?==a`q;3sz5kB=vYkB^Usv)VI9k21rD zJiTz9qguh+nKE8m#+pE4C16PIb7Iqf7uN3q_3Quydk+ycREf|Kaf=g!AT$7Pt5%T^ 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border-left-color: var(--mystnb-source-margin-color); + border-left-width: medium; +} + +div.cell details.hide>summary>span { + opacity: var(--mystnb-hide-prompt-opacity); +} + +div.cell details.hide[open]>summary>span.collapsed { + display: none; +} + +div.cell details.hide:not([open])>summary>span.expanded { + display: none; +} + +@keyframes collapsed-fade-in { + 0% { + opacity: 0; + } + + 100% { + opacity: 1; + } +} +div.cell details.hide[open]>summary~* { + -moz-animation: collapsed-fade-in 0.3s ease-in-out; + -webkit-animation: collapsed-fade-in 0.3s ease-in-out; + animation: collapsed-fade-in 0.3s ease-in-out; +} + +/* Math align to the left */ +.cell_output .MathJax_Display { + text-align: left !important; +} + +/* Pandas tables. Pulled from the Jupyter / nbsphinx CSS */ +div.cell_output table { + border: none; + border-collapse: collapse; + border-spacing: 0; + color: black; + font-size: 1em; + table-layout: fixed; +} + +div.cell_output thead { + border-bottom: 1px solid black; + vertical-align: bottom; +} + +div.cell_output tr, +div.cell_output th, +div.cell_output td { + text-align: right; + vertical-align: middle; + padding: 0.5em 0.5em; + line-height: normal; + white-space: normal; + max-width: none; + border: none; +} + +div.cell_output th { + font-weight: bold; +} + +div.cell_output tbody tr:nth-child(odd) { + background: #f5f5f5; +} + +div.cell_output tbody tr:hover { + background: rgba(66, 165, 245, 0.2); +} + +/** source code line numbers **/ +span.linenos { + opacity: 0.5; +} + +/* Inline text from `paste` operation */ + +span.pasted-text { + font-weight: bold; +} + +span.pasted-inline img { + max-height: 2em; +} + +tbody span.pasted-inline img { + max-height: none; +} + +/* Font colors for 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.-Color[class*=-C11] { + color: #FFFF00 +} + +div.highlight .-Color[class*=-BGC11] { + background-color: #FFFF00 +} + +div.highlight .-Color[class*=-C12] { + color: #0000FF +} + +div.highlight .-Color[class*=-BGC12] { + background-color: #0000FF +} + +div.highlight .-Color[class*=-C13] { + color: #FF00FF +} + +div.highlight .-Color[class*=-BGC13] { + background-color: #FF00FF +} + +div.highlight .-Color[class*=-C14] { + color: #00FFFF +} + +div.highlight .-Color[class*=-BGC14] { + background-color: #00FFFF +} + +div.highlight .-Color[class*=-C15] { + color: #FFFFFF +} + +div.highlight .-Color[class*=-BGC15] { + background-color: #FFFFFF +} + +div.highlight .-Color[class*=-C16] { + color: #000000 +} + +div.highlight .-Color[class*=-BGC16] { + background-color: #000000 +} + +div.highlight .-Color[class*=-C17] { + color: #00005F +} + +div.highlight .-Color[class*=-BGC17] { + background-color: #00005F +} + +div.highlight .-Color[class*=-C18] { + color: #000087 +} + +div.highlight .-Color[class*=-BGC18] { + background-color: #000087 +} + +div.highlight .-Color[class*=-C19] { + color: #0000AF +} + +div.highlight .-Color[class*=-BGC19] { + background-color: #0000AF +} + +div.highlight .-Color[class*=-C20] { + color: #0000D7 +} + +div.highlight .-Color[class*=-BGC20] { + background-color: #0000D7 +} + +div.highlight .-Color[class*=-C21] { + color: #0000FF +} + +div.highlight .-Color[class*=-BGC21] { + background-color: #0000FF +} + +div.highlight .-Color[class*=-C22] { + color: #005F00 +} + +div.highlight .-Color[class*=-BGC22] { + background-color: #005F00 +} + +div.highlight .-Color[class*=-C23] { + color: #005F5F +} + +div.highlight .-Color[class*=-BGC23] { + background-color: #005F5F +} + +div.highlight .-Color[class*=-C24] { + color: #005F87 +} + +div.highlight .-Color[class*=-BGC24] { + background-color: #005F87 +} + +div.highlight .-Color[class*=-C25] { + color: #005FAF +} + +div.highlight .-Color[class*=-BGC25] { + background-color: #005FAF +} + +div.highlight .-Color[class*=-C26] { + color: #005FD7 +} + +div.highlight .-Color[class*=-BGC26] { + background-color: #005FD7 +} + +div.highlight .-Color[class*=-C27] { + color: #005FFF +} + +div.highlight .-Color[class*=-BGC27] { + background-color: #005FFF +} + +div.highlight .-Color[class*=-C28] { + color: #008700 +} + +div.highlight .-Color[class*=-BGC28] { + background-color: #008700 +} + +div.highlight .-Color[class*=-C29] { + color: #00875F +} + +div.highlight .-Color[class*=-BGC29] { + background-color: #00875F +} + +div.highlight .-Color[class*=-C30] { + color: #008787 +} + +div.highlight .-Color[class*=-BGC30] { + background-color: #008787 +} + +div.highlight .-Color[class*=-C31] { + color: #0087AF +} + +div.highlight .-Color[class*=-BGC31] { + background-color: #0087AF +} + +div.highlight .-Color[class*=-C32] { + color: #0087D7 +} + +div.highlight .-Color[class*=-BGC32] { + background-color: #0087D7 +} + +div.highlight .-Color[class*=-C33] { + color: #0087FF +} + +div.highlight .-Color[class*=-BGC33] { + background-color: #0087FF +} + +div.highlight .-Color[class*=-C34] { + color: #00AF00 +} + +div.highlight .-Color[class*=-BGC34] { + background-color: #00AF00 +} + +div.highlight .-Color[class*=-C35] { + color: #00AF5F +} + +div.highlight .-Color[class*=-BGC35] { + background-color: #00AF5F +} + +div.highlight .-Color[class*=-C36] { + color: #00AF87 +} + +div.highlight .-Color[class*=-BGC36] { + background-color: #00AF87 +} + +div.highlight .-Color[class*=-C37] { + color: #00AFAF +} + +div.highlight .-Color[class*=-BGC37] { + background-color: #00AFAF +} + +div.highlight .-Color[class*=-C38] { + color: #00AFD7 +} + +div.highlight .-Color[class*=-BGC38] { + background-color: #00AFD7 +} + +div.highlight .-Color[class*=-C39] { + color: #00AFFF +} + +div.highlight .-Color[class*=-BGC39] { + background-color: #00AFFF +} + +div.highlight .-Color[class*=-C40] { + color: #00D700 +} + +div.highlight .-Color[class*=-BGC40] { + background-color: #00D700 +} + +div.highlight .-Color[class*=-C41] { + color: #00D75F +} + +div.highlight .-Color[class*=-BGC41] { + background-color: #00D75F +} + +div.highlight .-Color[class*=-C42] { + color: #00D787 +} + +div.highlight .-Color[class*=-BGC42] { + background-color: #00D787 +} + +div.highlight .-Color[class*=-C43] { + color: #00D7AF +} + +div.highlight .-Color[class*=-BGC43] { + background-color: #00D7AF +} + +div.highlight .-Color[class*=-C44] { + color: #00D7D7 +} + +div.highlight .-Color[class*=-BGC44] { + background-color: #00D7D7 +} + +div.highlight .-Color[class*=-C45] { + color: #00D7FF +} + +div.highlight .-Color[class*=-BGC45] { + background-color: #00D7FF +} + +div.highlight .-Color[class*=-C46] { + color: #00FF00 +} + +div.highlight .-Color[class*=-BGC46] { + background-color: #00FF00 +} + +div.highlight .-Color[class*=-C47] { + color: #00FF5F +} + +div.highlight .-Color[class*=-BGC47] { + background-color: #00FF5F +} + +div.highlight .-Color[class*=-C48] { + color: #00FF87 +} + +div.highlight .-Color[class*=-BGC48] { + background-color: #00FF87 +} + +div.highlight .-Color[class*=-C49] { + color: #00FFAF +} + +div.highlight .-Color[class*=-BGC49] { + background-color: #00FFAF +} + +div.highlight .-Color[class*=-C50] { + color: #00FFD7 +} + +div.highlight .-Color[class*=-BGC50] { + background-color: #00FFD7 +} + +div.highlight .-Color[class*=-C51] { + color: #00FFFF +} + +div.highlight .-Color[class*=-BGC51] { + background-color: #00FFFF +} + +div.highlight .-Color[class*=-C52] { + color: #5F0000 +} + +div.highlight .-Color[class*=-BGC52] { + background-color: #5F0000 +} + +div.highlight .-Color[class*=-C53] { + color: #5F005F +} + +div.highlight .-Color[class*=-BGC53] { + background-color: #5F005F +} + +div.highlight .-Color[class*=-C54] { + color: #5F0087 +} + +div.highlight .-Color[class*=-BGC54] { + background-color: #5F0087 +} + +div.highlight .-Color[class*=-C55] { + color: #5F00AF +} + +div.highlight .-Color[class*=-BGC55] { + background-color: #5F00AF +} + +div.highlight .-Color[class*=-C56] { + color: #5F00D7 +} + +div.highlight .-Color[class*=-BGC56] { + background-color: #5F00D7 +} + +div.highlight .-Color[class*=-C57] { + color: #5F00FF +} + +div.highlight .-Color[class*=-BGC57] { + background-color: #5F00FF +} + +div.highlight .-Color[class*=-C58] { + color: #5F5F00 +} + +div.highlight .-Color[class*=-BGC58] { + background-color: #5F5F00 +} + +div.highlight .-Color[class*=-C59] { + color: #5F5F5F +} + +div.highlight .-Color[class*=-BGC59] { + background-color: #5F5F5F +} + +div.highlight .-Color[class*=-C60] { + color: #5F5F87 +} + +div.highlight .-Color[class*=-BGC60] { + background-color: #5F5F87 +} + +div.highlight .-Color[class*=-C61] { + color: #5F5FAF +} + +div.highlight .-Color[class*=-BGC61] { + background-color: #5F5FAF +} + +div.highlight .-Color[class*=-C62] { + color: #5F5FD7 +} + +div.highlight .-Color[class*=-BGC62] { + background-color: #5F5FD7 +} + +div.highlight .-Color[class*=-C63] { + color: #5F5FFF +} + +div.highlight .-Color[class*=-BGC63] { + background-color: #5F5FFF +} + +div.highlight .-Color[class*=-C64] { + color: #5F8700 +} + +div.highlight .-Color[class*=-BGC64] { + background-color: #5F8700 +} + +div.highlight .-Color[class*=-C65] { + color: #5F875F +} + +div.highlight .-Color[class*=-BGC65] { + background-color: #5F875F +} + +div.highlight .-Color[class*=-C66] { + color: #5F8787 +} + +div.highlight .-Color[class*=-BGC66] { + background-color: #5F8787 +} + +div.highlight .-Color[class*=-C67] { + color: #5F87AF +} + +div.highlight .-Color[class*=-BGC67] { + background-color: #5F87AF +} + +div.highlight .-Color[class*=-C68] { + color: #5F87D7 +} + +div.highlight .-Color[class*=-BGC68] { + background-color: #5F87D7 +} + +div.highlight .-Color[class*=-C69] { + color: #5F87FF +} + +div.highlight .-Color[class*=-BGC69] { + background-color: #5F87FF +} + +div.highlight .-Color[class*=-C70] { + color: #5FAF00 +} + +div.highlight .-Color[class*=-BGC70] { + background-color: #5FAF00 +} + +div.highlight .-Color[class*=-C71] { + color: #5FAF5F +} + +div.highlight .-Color[class*=-BGC71] { + background-color: #5FAF5F +} + +div.highlight .-Color[class*=-C72] { + color: #5FAF87 +} + +div.highlight .-Color[class*=-BGC72] { + background-color: #5FAF87 +} + +div.highlight .-Color[class*=-C73] { + color: #5FAFAF +} + +div.highlight .-Color[class*=-BGC73] { + background-color: #5FAFAF +} + +div.highlight .-Color[class*=-C74] { + color: #5FAFD7 +} + +div.highlight .-Color[class*=-BGC74] { + background-color: #5FAFD7 +} + +div.highlight .-Color[class*=-C75] { + color: #5FAFFF +} + +div.highlight .-Color[class*=-BGC75] { + background-color: #5FAFFF +} + +div.highlight .-Color[class*=-C76] { + color: #5FD700 +} + +div.highlight .-Color[class*=-BGC76] { + background-color: #5FD700 +} + +div.highlight .-Color[class*=-C77] { + color: #5FD75F +} + +div.highlight .-Color[class*=-BGC77] { + background-color: #5FD75F +} + +div.highlight .-Color[class*=-C78] { + color: #5FD787 +} + +div.highlight .-Color[class*=-BGC78] { + background-color: #5FD787 +} + +div.highlight .-Color[class*=-C79] { + color: #5FD7AF +} + +div.highlight .-Color[class*=-BGC79] { + background-color: #5FD7AF +} + +div.highlight .-Color[class*=-C80] { + color: #5FD7D7 +} + +div.highlight .-Color[class*=-BGC80] { + background-color: #5FD7D7 +} + +div.highlight .-Color[class*=-C81] { + color: #5FD7FF +} + +div.highlight .-Color[class*=-BGC81] { + background-color: #5FD7FF +} + +div.highlight .-Color[class*=-C82] { + color: #5FFF00 +} + +div.highlight .-Color[class*=-BGC82] { + background-color: #5FFF00 +} + +div.highlight .-Color[class*=-C83] { + color: #5FFF5F +} + +div.highlight .-Color[class*=-BGC83] { + background-color: #5FFF5F +} + +div.highlight .-Color[class*=-C84] { + color: #5FFF87 +} + +div.highlight .-Color[class*=-BGC84] { + background-color: #5FFF87 +} + +div.highlight .-Color[class*=-C85] { + color: #5FFFAF +} + +div.highlight .-Color[class*=-BGC85] { + background-color: #5FFFAF +} + +div.highlight .-Color[class*=-C86] { + color: #5FFFD7 +} + +div.highlight .-Color[class*=-BGC86] { + background-color: #5FFFD7 +} + +div.highlight .-Color[class*=-C87] { + color: #5FFFFF +} + +div.highlight .-Color[class*=-BGC87] { + background-color: #5FFFFF +} + +div.highlight .-Color[class*=-C88] { + color: #870000 +} + +div.highlight .-Color[class*=-BGC88] { + background-color: #870000 +} + +div.highlight .-Color[class*=-C89] { + color: #87005F +} + +div.highlight .-Color[class*=-BGC89] { + background-color: #87005F +} + +div.highlight .-Color[class*=-C90] { + color: #870087 +} + +div.highlight .-Color[class*=-BGC90] { + background-color: #870087 +} + +div.highlight .-Color[class*=-C91] { + color: #8700AF +} + +div.highlight .-Color[class*=-BGC91] { + background-color: #8700AF +} + +div.highlight .-Color[class*=-C92] { + color: #8700D7 +} + +div.highlight .-Color[class*=-BGC92] { + background-color: #8700D7 +} + +div.highlight .-Color[class*=-C93] { + color: #8700FF +} + +div.highlight .-Color[class*=-BGC93] { + background-color: #8700FF +} + +div.highlight .-Color[class*=-C94] { + color: #875F00 +} + +div.highlight .-Color[class*=-BGC94] { + background-color: #875F00 +} + +div.highlight .-Color[class*=-C95] { + color: #875F5F +} + +div.highlight .-Color[class*=-BGC95] { + background-color: #875F5F +} + +div.highlight .-Color[class*=-C96] { + color: #875F87 +} + +div.highlight .-Color[class*=-BGC96] { + background-color: #875F87 +} + +div.highlight .-Color[class*=-C97] { + color: #875FAF +} + +div.highlight .-Color[class*=-BGC97] { + background-color: #875FAF +} + +div.highlight .-Color[class*=-C98] { + color: #875FD7 +} + +div.highlight .-Color[class*=-BGC98] { + background-color: #875FD7 +} + +div.highlight .-Color[class*=-C99] { + color: #875FFF +} + +div.highlight .-Color[class*=-BGC99] { + background-color: #875FFF +} + +div.highlight .-Color[class*=-C100] { + color: #878700 +} + +div.highlight .-Color[class*=-BGC100] { + background-color: #878700 +} + +div.highlight .-Color[class*=-C101] { + color: #87875F +} + +div.highlight .-Color[class*=-BGC101] { + background-color: #87875F +} + +div.highlight .-Color[class*=-C102] { + color: #878787 +} + +div.highlight .-Color[class*=-BGC102] { + background-color: #878787 +} + +div.highlight .-Color[class*=-C103] { + color: #8787AF +} + +div.highlight .-Color[class*=-BGC103] { + background-color: #8787AF +} + +div.highlight .-Color[class*=-C104] { + color: #8787D7 +} + +div.highlight .-Color[class*=-BGC104] { + background-color: #8787D7 +} + +div.highlight .-Color[class*=-C105] { + color: #8787FF +} + +div.highlight .-Color[class*=-BGC105] { + background-color: #8787FF +} + +div.highlight .-Color[class*=-C106] { + color: #87AF00 +} + +div.highlight .-Color[class*=-BGC106] { + background-color: #87AF00 +} + +div.highlight .-Color[class*=-C107] { + color: #87AF5F +} + +div.highlight .-Color[class*=-BGC107] { + background-color: #87AF5F +} + +div.highlight .-Color[class*=-C108] { + color: #87AF87 +} + +div.highlight .-Color[class*=-BGC108] { + background-color: #87AF87 +} + +div.highlight .-Color[class*=-C109] { + color: #87AFAF +} + +div.highlight .-Color[class*=-BGC109] { + background-color: #87AFAF +} + +div.highlight .-Color[class*=-C110] { + color: #87AFD7 +} + +div.highlight .-Color[class*=-BGC110] { + background-color: #87AFD7 +} + +div.highlight .-Color[class*=-C111] { + color: #87AFFF +} + +div.highlight .-Color[class*=-BGC111] { + background-color: #87AFFF +} + +div.highlight .-Color[class*=-C112] { + color: #87D700 +} + +div.highlight .-Color[class*=-BGC112] { + background-color: #87D700 +} + +div.highlight .-Color[class*=-C113] { + color: #87D75F +} + +div.highlight .-Color[class*=-BGC113] { + background-color: #87D75F +} + +div.highlight .-Color[class*=-C114] { + color: #87D787 +} + +div.highlight .-Color[class*=-BGC114] { + background-color: #87D787 +} + +div.highlight .-Color[class*=-C115] { + color: #87D7AF +} + +div.highlight .-Color[class*=-BGC115] { + background-color: #87D7AF +} + +div.highlight .-Color[class*=-C116] { + color: #87D7D7 +} + +div.highlight .-Color[class*=-BGC116] { + background-color: #87D7D7 +} + +div.highlight .-Color[class*=-C117] { + color: #87D7FF +} + +div.highlight .-Color[class*=-BGC117] { + background-color: #87D7FF +} + +div.highlight .-Color[class*=-C118] { + color: #87FF00 +} + +div.highlight .-Color[class*=-BGC118] { + background-color: #87FF00 +} + +div.highlight .-Color[class*=-C119] { + color: #87FF5F +} + +div.highlight .-Color[class*=-BGC119] { + background-color: #87FF5F +} + +div.highlight .-Color[class*=-C120] { + color: #87FF87 +} + +div.highlight .-Color[class*=-BGC120] { + background-color: #87FF87 +} + +div.highlight .-Color[class*=-C121] { + color: #87FFAF +} + +div.highlight .-Color[class*=-BGC121] { + background-color: #87FFAF +} + +div.highlight .-Color[class*=-C122] { + color: #87FFD7 +} + +div.highlight .-Color[class*=-BGC122] { + background-color: #87FFD7 +} + +div.highlight .-Color[class*=-C123] { + color: #87FFFF +} + +div.highlight .-Color[class*=-BGC123] { + background-color: #87FFFF +} + +div.highlight .-Color[class*=-C124] { + color: #AF0000 +} + +div.highlight .-Color[class*=-BGC124] { + background-color: #AF0000 +} + +div.highlight .-Color[class*=-C125] { + color: #AF005F +} + +div.highlight .-Color[class*=-BGC125] { + background-color: #AF005F +} + +div.highlight .-Color[class*=-C126] { + color: #AF0087 +} + +div.highlight .-Color[class*=-BGC126] { + background-color: #AF0087 +} + +div.highlight .-Color[class*=-C127] { + color: #AF00AF +} + +div.highlight .-Color[class*=-BGC127] { + background-color: #AF00AF +} + +div.highlight .-Color[class*=-C128] { + color: #AF00D7 +} + +div.highlight .-Color[class*=-BGC128] { + background-color: #AF00D7 +} + +div.highlight .-Color[class*=-C129] { + color: #AF00FF +} + +div.highlight .-Color[class*=-BGC129] { + background-color: #AF00FF +} + +div.highlight .-Color[class*=-C130] { + color: #AF5F00 +} + +div.highlight .-Color[class*=-BGC130] { + background-color: #AF5F00 +} + +div.highlight .-Color[class*=-C131] { + color: #AF5F5F +} + +div.highlight .-Color[class*=-BGC131] { + background-color: #AF5F5F +} + +div.highlight .-Color[class*=-C132] { + color: #AF5F87 +} + +div.highlight .-Color[class*=-BGC132] { + background-color: #AF5F87 +} + +div.highlight .-Color[class*=-C133] { + color: #AF5FAF +} + +div.highlight .-Color[class*=-BGC133] { + background-color: #AF5FAF +} + +div.highlight .-Color[class*=-C134] { + color: #AF5FD7 +} + +div.highlight .-Color[class*=-BGC134] { + background-color: #AF5FD7 +} + +div.highlight .-Color[class*=-C135] { + color: #AF5FFF +} + +div.highlight .-Color[class*=-BGC135] { + background-color: #AF5FFF +} + +div.highlight .-Color[class*=-C136] { + color: #AF8700 +} + +div.highlight .-Color[class*=-BGC136] { + background-color: #AF8700 +} + +div.highlight .-Color[class*=-C137] { + color: #AF875F +} + +div.highlight .-Color[class*=-BGC137] { + background-color: #AF875F +} + +div.highlight .-Color[class*=-C138] { + color: #AF8787 +} + +div.highlight .-Color[class*=-BGC138] { + background-color: #AF8787 +} + +div.highlight .-Color[class*=-C139] { + color: #AF87AF +} + +div.highlight .-Color[class*=-BGC139] { + background-color: #AF87AF +} + +div.highlight .-Color[class*=-C140] { + color: #AF87D7 +} + +div.highlight .-Color[class*=-BGC140] { + background-color: #AF87D7 +} + +div.highlight .-Color[class*=-C141] { + color: #AF87FF +} + +div.highlight .-Color[class*=-BGC141] { + background-color: #AF87FF +} + +div.highlight .-Color[class*=-C142] { + color: #AFAF00 +} + +div.highlight .-Color[class*=-BGC142] { + background-color: #AFAF00 +} + +div.highlight .-Color[class*=-C143] { + color: #AFAF5F +} + +div.highlight .-Color[class*=-BGC143] { + background-color: #AFAF5F +} + +div.highlight .-Color[class*=-C144] { + color: #AFAF87 +} + +div.highlight .-Color[class*=-BGC144] { + background-color: #AFAF87 +} + +div.highlight 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Object.getOwnPropertyNames(this))this[t]=null}_queueCallback(t,e,i=!0){Ut(t,e,i)}_getConfig(t){return t=this._mergeConfigObj(t,this._element),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}static getInstance(t){return Nt.get(Ht(t),this.DATA_KEY)}static getOrCreateInstance(t,e={}){return this.getInstance(t)||new this(t,"object"==typeof e?e:null)}static get VERSION(){return"5.3.2"}static get DATA_KEY(){return`bs.${this.NAME}`}static get EVENT_KEY(){return`.${this.DATA_KEY}`}static eventName(t){return`${t}${this.EVENT_KEY}`}}const ye=t=>{let e=t.getAttribute("data-bs-target");if(!e||"#"===e){let i=t.getAttribute("href");if(!i||!i.includes("#")&&!i.startsWith("."))return null;i.includes("#")&&!i.startsWith("#")&&(i=`#${i.split("#")[1]}`),e=i&&"#"!==i?Mt(i.trim()):null}return e},we={find:(t,e=document.documentElement)=>[].concat(...Element.prototype.querySelectorAll.call(e,t)),findOne:(t,e=document.documentElement)=>Element.prototype.querySelector.call(e,t),children:(t,e)=>[].concat(...t.children).filter((t=>t.matches(e))),parents(t,e){const i=[];let n=t.parentNode.closest(e);for(;n;)i.push(n),n=n.parentNode.closest(e);return i},prev(t,e){let i=t.previousElementSibling;for(;i;){if(i.matches(e))return[i];i=i.previousElementSibling}return[]},next(t,e){let i=t.nextElementSibling;for(;i;){if(i.matches(e))return[i];i=i.nextElementSibling}return[]},focusableChildren(t){const e=["a","button","input","textarea","select","details","[tabindex]",'[contenteditable="true"]'].map((t=>`${t}:not([tabindex^="-"])`)).join(",");return this.find(e,t).filter((t=>!Wt(t)&&Bt(t)))},getSelectorFromElement(t){const e=ye(t);return e&&we.findOne(e)?e:null},getElementFromSelector(t){const e=ye(t);return e?we.findOne(e):null},getMultipleElementsFromSelector(t){const e=ye(t);return e?we.find(e):[]}},Ee=(t,e="hide")=>{const i=`click.dismiss${t.EVENT_KEY}`,n=t.NAME;fe.on(document,i,`[data-bs-dismiss="${n}"]`,(function(i){if(["A","AREA"].includes(this.tagName)&&i.preventDefault(),Wt(this))return;const s=we.getElementFromSelector(this)||this.closest(`.${n}`);t.getOrCreateInstance(s)[e]()}))},Ae=".bs.alert",Te=`close${Ae}`,Ce=`closed${Ae}`;class Oe extends ve{static get NAME(){return"alert"}close(){if(fe.trigger(this._element,Te).defaultPrevented)return;this._element.classList.remove("show");const t=this._element.classList.contains("fade");this._queueCallback((()=>this._destroyElement()),this._element,t)}_destroyElement(){this._element.remove(),fe.trigger(this._element,Ce),this.dispose()}static jQueryInterface(t){return this.each((function(){const e=Oe.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}Ee(Oe,"close"),Qt(Oe);const xe='[data-bs-toggle="button"]';class ke extends ve{static get NAME(){return"button"}toggle(){this._element.setAttribute("aria-pressed",this._element.classList.toggle("active"))}static jQueryInterface(t){return this.each((function(){const e=ke.getOrCreateInstance(this);"toggle"===t&&e[t]()}))}}fe.on(document,"click.bs.button.data-api",xe,(t=>{t.preventDefault();const e=t.target.closest(xe);ke.getOrCreateInstance(e).toggle()})),Qt(ke);const Le=".bs.swipe",Se=`touchstart${Le}`,De=`touchmove${Le}`,$e=`touchend${Le}`,Ie=`pointerdown${Le}`,Ne=`pointerup${Le}`,Pe={endCallback:null,leftCallback:null,rightCallback:null},Me={endCallback:"(function|null)",leftCallback:"(function|null)",rightCallback:"(function|null)"};class je extends be{constructor(t,e){super(),this._element=t,t&&je.isSupported()&&(this._config=this._getConfig(e),this._deltaX=0,this._supportPointerEvents=Boolean(window.PointerEvent),this._initEvents())}static get Default(){return Pe}static get DefaultType(){return Me}static get NAME(){return"swipe"}dispose(){fe.off(this._element,Le)}_start(t){this._supportPointerEvents?this._eventIsPointerPenTouch(t)&&(this._deltaX=t.clientX):this._deltaX=t.touches[0].clientX}_end(t){this._eventIsPointerPenTouch(t)&&(this._deltaX=t.clientX-this._deltaX),this._handleSwipe(),Xt(this._config.endCallback)}_move(t){this._deltaX=t.touches&&t.touches.length>1?0:t.touches[0].clientX-this._deltaX}_handleSwipe(){const t=Math.abs(this._deltaX);if(t<=40)return;const e=t/this._deltaX;this._deltaX=0,e&&Xt(e>0?this._config.rightCallback:this._config.leftCallback)}_initEvents(){this._supportPointerEvents?(fe.on(this._element,Ie,(t=>this._start(t))),fe.on(this._element,Ne,(t=>this._end(t))),this._element.classList.add("pointer-event")):(fe.on(this._element,Se,(t=>this._start(t))),fe.on(this._element,De,(t=>this._move(t))),fe.on(this._element,$e,(t=>this._end(t))))}_eventIsPointerPenTouch(t){return this._supportPointerEvents&&("pen"===t.pointerType||"touch"===t.pointerType)}static isSupported(){return"ontouchstart"in document.documentElement||navigator.maxTouchPoints>0}}const Fe=".bs.carousel",He=".data-api",Be="next",We="prev",ze="left",Re="right",qe=`slide${Fe}`,Ve=`slid${Fe}`,Ye=`keydown${Fe}`,Ke=`mouseenter${Fe}`,Qe=`mouseleave${Fe}`,Xe=`dragstart${Fe}`,Ue=`load${Fe}${He}`,Ge=`click${Fe}${He}`,Je="carousel",Ze="active",ti=".active",ei=".carousel-item",ii=ti+ei,ni={ArrowLeft:Re,ArrowRight:ze},si={interval:5e3,keyboard:!0,pause:"hover",ride:!1,touch:!0,wrap:!0},oi={interval:"(number|boolean)",keyboard:"boolean",pause:"(string|boolean)",ride:"(boolean|string)",touch:"boolean",wrap:"boolean"};class ri extends ve{constructor(t,e){super(t,e),this._interval=null,this._activeElement=null,this._isSliding=!1,this.touchTimeout=null,this._swipeHelper=null,this._indicatorsElement=we.findOne(".carousel-indicators",this._element),this._addEventListeners(),this._config.ride===Je&&this.cycle()}static get Default(){return si}static get DefaultType(){return oi}static get NAME(){return"carousel"}next(){this._slide(Be)}nextWhenVisible(){!document.hidden&&Bt(this._element)&&this.next()}prev(){this._slide(We)}pause(){this._isSliding&&jt(this._element),this._clearInterval()}cycle(){this._clearInterval(),this._updateInterval(),this._interval=setInterval((()=>this.nextWhenVisible()),this._config.interval)}_maybeEnableCycle(){this._config.ride&&(this._isSliding?fe.one(this._element,Ve,(()=>this.cycle())):this.cycle())}to(t){const e=this._getItems();if(t>e.length-1||t<0)return;if(this._isSliding)return void fe.one(this._element,Ve,(()=>this.to(t)));const i=this._getItemIndex(this._getActive());if(i===t)return;const n=t>i?Be:We;this._slide(n,e[t])}dispose(){this._swipeHelper&&this._swipeHelper.dispose(),super.dispose()}_configAfterMerge(t){return t.defaultInterval=t.interval,t}_addEventListeners(){this._config.keyboard&&fe.on(this._element,Ye,(t=>this._keydown(t))),"hover"===this._config.pause&&(fe.on(this._element,Ke,(()=>this.pause())),fe.on(this._element,Qe,(()=>this._maybeEnableCycle()))),this._config.touch&&je.isSupported()&&this._addTouchEventListeners()}_addTouchEventListeners(){for(const t of we.find(".carousel-item img",this._element))fe.on(t,Xe,(t=>t.preventDefault()));const t={leftCallback:()=>this._slide(this._directionToOrder(ze)),rightCallback:()=>this._slide(this._directionToOrder(Re)),endCallback:()=>{"hover"===this._config.pause&&(this.pause(),this.touchTimeout&&clearTimeout(this.touchTimeout),this.touchTimeout=setTimeout((()=>this._maybeEnableCycle()),500+this._config.interval))}};this._swipeHelper=new je(this._element,t)}_keydown(t){if(/input|textarea/i.test(t.target.tagName))return;const e=ni[t.key];e&&(t.preventDefault(),this._slide(this._directionToOrder(e)))}_getItemIndex(t){return this._getItems().indexOf(t)}_setActiveIndicatorElement(t){if(!this._indicatorsElement)return;const e=we.findOne(ti,this._indicatorsElement);e.classList.remove(Ze),e.removeAttribute("aria-current");const i=we.findOne(`[data-bs-slide-to="${t}"]`,this._indicatorsElement);i&&(i.classList.add(Ze),i.setAttribute("aria-current","true"))}_updateInterval(){const t=this._activeElement||this._getActive();if(!t)return;const e=Number.parseInt(t.getAttribute("data-bs-interval"),10);this._config.interval=e||this._config.defaultInterval}_slide(t,e=null){if(this._isSliding)return;const i=this._getActive(),n=t===Be,s=e||Gt(this._getItems(),i,n,this._config.wrap);if(s===i)return;const o=this._getItemIndex(s),r=e=>fe.trigger(this._element,e,{relatedTarget:s,direction:this._orderToDirection(t),from:this._getItemIndex(i),to:o});if(r(qe).defaultPrevented)return;if(!i||!s)return;const a=Boolean(this._interval);this.pause(),this._isSliding=!0,this._setActiveIndicatorElement(o),this._activeElement=s;const l=n?"carousel-item-start":"carousel-item-end",c=n?"carousel-item-next":"carousel-item-prev";s.classList.add(c),qt(s),i.classList.add(l),s.classList.add(l),this._queueCallback((()=>{s.classList.remove(l,c),s.classList.add(Ze),i.classList.remove(Ze,c,l),this._isSliding=!1,r(Ve)}),i,this._isAnimated()),a&&this.cycle()}_isAnimated(){return this._element.classList.contains("slide")}_getActive(){return we.findOne(ii,this._element)}_getItems(){return we.find(ei,this._element)}_clearInterval(){this._interval&&(clearInterval(this._interval),this._interval=null)}_directionToOrder(t){return Kt()?t===ze?We:Be:t===ze?Be:We}_orderToDirection(t){return Kt()?t===We?ze:Re:t===We?Re:ze}static jQueryInterface(t){return this.each((function(){const e=ri.getOrCreateInstance(this,t);if("number"!=typeof t){if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}else e.to(t)}))}}fe.on(document,Ge,"[data-bs-slide], [data-bs-slide-to]",(function(t){const e=we.getElementFromSelector(this);if(!e||!e.classList.contains(Je))return;t.preventDefault();const i=ri.getOrCreateInstance(e),n=this.getAttribute("data-bs-slide-to");return n?(i.to(n),void i._maybeEnableCycle()):"next"===_e.getDataAttribute(this,"slide")?(i.next(),void i._maybeEnableCycle()):(i.prev(),void i._maybeEnableCycle())})),fe.on(window,Ue,(()=>{const t=we.find('[data-bs-ride="carousel"]');for(const e of t)ri.getOrCreateInstance(e)})),Qt(ri);const ai=".bs.collapse",li=`show${ai}`,ci=`shown${ai}`,hi=`hide${ai}`,di=`hidden${ai}`,ui=`click${ai}.data-api`,fi="show",pi="collapse",mi="collapsing",gi=`:scope .${pi} .${pi}`,_i='[data-bs-toggle="collapse"]',bi={parent:null,toggle:!0},vi={parent:"(null|element)",toggle:"boolean"};class yi extends ve{constructor(t,e){super(t,e),this._isTransitioning=!1,this._triggerArray=[];const i=we.find(_i);for(const t of i){const e=we.getSelectorFromElement(t),i=we.find(e).filter((t=>t===this._element));null!==e&&i.length&&this._triggerArray.push(t)}this._initializeChildren(),this._config.parent||this._addAriaAndCollapsedClass(this._triggerArray,this._isShown()),this._config.toggle&&this.toggle()}static get Default(){return bi}static get DefaultType(){return vi}static get NAME(){return"collapse"}toggle(){this._isShown()?this.hide():this.show()}show(){if(this._isTransitioning||this._isShown())return;let t=[];if(this._config.parent&&(t=this._getFirstLevelChildren(".collapse.show, .collapse.collapsing").filter((t=>t!==this._element)).map((t=>yi.getOrCreateInstance(t,{toggle:!1})))),t.length&&t[0]._isTransitioning)return;if(fe.trigger(this._element,li).defaultPrevented)return;for(const e of t)e.hide();const e=this._getDimension();this._element.classList.remove(pi),this._element.classList.add(mi),this._element.style[e]=0,this._addAriaAndCollapsedClass(this._triggerArray,!0),this._isTransitioning=!0;const i=`scroll${e[0].toUpperCase()+e.slice(1)}`;this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(mi),this._element.classList.add(pi,fi),this._element.style[e]="",fe.trigger(this._element,ci)}),this._element,!0),this._element.style[e]=`${this._element[i]}px`}hide(){if(this._isTransitioning||!this._isShown())return;if(fe.trigger(this._element,hi).defaultPrevented)return;const t=this._getDimension();this._element.style[t]=`${this._element.getBoundingClientRect()[t]}px`,qt(this._element),this._element.classList.add(mi),this._element.classList.remove(pi,fi);for(const t of this._triggerArray){const e=we.getElementFromSelector(t);e&&!this._isShown(e)&&this._addAriaAndCollapsedClass([t],!1)}this._isTransitioning=!0,this._element.style[t]="",this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(mi),this._element.classList.add(pi),fe.trigger(this._element,di)}),this._element,!0)}_isShown(t=this._element){return t.classList.contains(fi)}_configAfterMerge(t){return t.toggle=Boolean(t.toggle),t.parent=Ht(t.parent),t}_getDimension(){return this._element.classList.contains("collapse-horizontal")?"width":"height"}_initializeChildren(){if(!this._config.parent)return;const t=this._getFirstLevelChildren(_i);for(const e of t){const t=we.getElementFromSelector(e);t&&this._addAriaAndCollapsedClass([e],this._isShown(t))}}_getFirstLevelChildren(t){const e=we.find(gi,this._config.parent);return we.find(t,this._config.parent).filter((t=>!e.includes(t)))}_addAriaAndCollapsedClass(t,e){if(t.length)for(const i of t)i.classList.toggle("collapsed",!e),i.setAttribute("aria-expanded",e)}static jQueryInterface(t){const e={};return"string"==typeof t&&/show|hide/.test(t)&&(e.toggle=!1),this.each((function(){const i=yi.getOrCreateInstance(this,e);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t]()}}))}}fe.on(document,ui,_i,(function(t){("A"===t.target.tagName||t.delegateTarget&&"A"===t.delegateTarget.tagName)&&t.preventDefault();for(const t of we.getMultipleElementsFromSelector(this))yi.getOrCreateInstance(t,{toggle:!1}).toggle()})),Qt(yi);const wi="dropdown",Ei=".bs.dropdown",Ai=".data-api",Ti="ArrowUp",Ci="ArrowDown",Oi=`hide${Ei}`,xi=`hidden${Ei}`,ki=`show${Ei}`,Li=`shown${Ei}`,Si=`click${Ei}${Ai}`,Di=`keydown${Ei}${Ai}`,$i=`keyup${Ei}${Ai}`,Ii="show",Ni='[data-bs-toggle="dropdown"]:not(.disabled):not(:disabled)',Pi=`${Ni}.${Ii}`,Mi=".dropdown-menu",ji=Kt()?"top-end":"top-start",Fi=Kt()?"top-start":"top-end",Hi=Kt()?"bottom-end":"bottom-start",Bi=Kt()?"bottom-start":"bottom-end",Wi=Kt()?"left-start":"right-start",zi=Kt()?"right-start":"left-start",Ri={autoClose:!0,boundary:"clippingParents",display:"dynamic",offset:[0,2],popperConfig:null,reference:"toggle"},qi={autoClose:"(boolean|string)",boundary:"(string|element)",display:"string",offset:"(array|string|function)",popperConfig:"(null|object|function)",reference:"(string|element|object)"};class Vi extends ve{constructor(t,e){super(t,e),this._popper=null,this._parent=this._element.parentNode,this._menu=we.next(this._element,Mi)[0]||we.prev(this._element,Mi)[0]||we.findOne(Mi,this._parent),this._inNavbar=this._detectNavbar()}static get Default(){return Ri}static get DefaultType(){return qi}static get NAME(){return wi}toggle(){return this._isShown()?this.hide():this.show()}show(){if(Wt(this._element)||this._isShown())return;const t={relatedTarget:this._element};if(!fe.trigger(this._element,ki,t).defaultPrevented){if(this._createPopper(),"ontouchstart"in document.documentElement&&!this._parent.closest(".navbar-nav"))for(const t of[].concat(...document.body.children))fe.on(t,"mouseover",Rt);this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Ii),this._element.classList.add(Ii),fe.trigger(this._element,Li,t)}}hide(){if(Wt(this._element)||!this._isShown())return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){if(!fe.trigger(this._element,Oi,t).defaultPrevented){if("ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.off(t,"mouseover",Rt);this._popper&&this._popper.destroy(),this._menu.classList.remove(Ii),this._element.classList.remove(Ii),this._element.setAttribute("aria-expanded","false"),_e.removeDataAttribute(this._menu,"popper"),fe.trigger(this._element,xi,t)}}_getConfig(t){if("object"==typeof(t=super._getConfig(t)).reference&&!Ft(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${wi.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(){if(void 0===e)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let t=this._element;"parent"===this._config.reference?t=this._parent:Ft(this._config.reference)?t=Ht(this._config.reference):"object"==typeof this._config.reference&&(t=this._config.reference);const i=this._getPopperConfig();this._popper=Dt(t,this._menu,i)}_isShown(){return this._menu.classList.contains(Ii)}_getPlacement(){const t=this._parent;if(t.classList.contains("dropend"))return Wi;if(t.classList.contains("dropstart"))return zi;if(t.classList.contains("dropup-center"))return"top";if(t.classList.contains("dropdown-center"))return"bottom";const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?Fi:ji:e?Bi:Hi}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(_e.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...Xt(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=we.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter((t=>Bt(t)));i.length&&Gt(i,e,t===Ci,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=Vi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(2===t.button||"keyup"===t.type&&"Tab"!==t.key)return;const e=we.find(Pi);for(const i of e){const e=Vi.getInstance(i);if(!e||!1===e._config.autoClose)continue;const n=t.composedPath(),s=n.includes(e._menu);if(n.includes(e._element)||"inside"===e._config.autoClose&&!s||"outside"===e._config.autoClose&&s)continue;if(e._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;const o={relatedTarget:e._element};"click"===t.type&&(o.clickEvent=t),e._completeHide(o)}}static dataApiKeydownHandler(t){const e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ti,Ci].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ni)?this:we.prev(this,Ni)[0]||we.next(this,Ni)[0]||we.findOne(Ni,t.delegateTarget.parentNode),o=Vi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}fe.on(document,Di,Ni,Vi.dataApiKeydownHandler),fe.on(document,Di,Mi,Vi.dataApiKeydownHandler),fe.on(document,Si,Vi.clearMenus),fe.on(document,$i,Vi.clearMenus),fe.on(document,Si,Ni,(function(t){t.preventDefault(),Vi.getOrCreateInstance(this).toggle()})),Qt(Vi);const Yi="backdrop",Ki="show",Qi=`mousedown.bs.${Yi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Ui={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Gi extends be{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Ui}static get NAME(){return Yi}show(t){if(!this._config.isVisible)return void Xt(t);this._append();const e=this._getElement();this._config.isAnimated&&qt(e),e.classList.add(Ki),this._emulateAnimation((()=>{Xt(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),Xt(t)}))):Xt(t)}dispose(){this._isAppended&&(fe.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=Ht(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),fe.on(t,Qi,(()=>{Xt(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){Ut(t,this._getElement(),this._config.isAnimated)}}const Ji=".bs.focustrap",Zi=`focusin${Ji}`,tn=`keydown.tab${Ji}`,en="backward",nn={autofocus:!0,trapElement:null},sn={autofocus:"boolean",trapElement:"element"};class on extends be{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return nn}static get DefaultType(){return sn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),fe.off(document,Ji),fe.on(document,Zi,(t=>this._handleFocusin(t))),fe.on(document,tn,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,fe.off(document,Ji))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=we.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===en?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?en:"forward")}}const rn=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",an=".sticky-top",ln="padding-right",cn="margin-right";class hn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,ln,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e+t)),this._setElementAttributes(an,cn,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,ln),this._resetElementAttributes(rn,ln),this._resetElementAttributes(an,cn)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&_e.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=_e.getDataAttribute(t,e);null!==i?(_e.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(Ft(t))e(t);else for(const i of we.find(t,this._element))e(i)}}const dn=".bs.modal",un=`hide${dn}`,fn=`hidePrevented${dn}`,pn=`hidden${dn}`,mn=`show${dn}`,gn=`shown${dn}`,_n=`resize${dn}`,bn=`click.dismiss${dn}`,vn=`mousedown.dismiss${dn}`,yn=`keydown.dismiss${dn}`,wn=`click${dn}.data-api`,En="modal-open",An="show",Tn="modal-static",Cn={backdrop:!0,focus:!0,keyboard:!0},On={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class xn extends ve{constructor(t,e){super(t,e),this._dialog=we.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new hn,this._addEventListeners()}static get Default(){return Cn}static get DefaultType(){return On}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||fe.trigger(this._element,mn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(En),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(fe.trigger(this._element,un).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){fe.off(window,dn),fe.off(this._dialog,dn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Gi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new on({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=we.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),qt(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,fe.trigger(this._element,gn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){fe.on(this._element,yn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),fe.on(window,_n,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),fe.on(this._element,vn,(t=>{fe.one(this._element,bn,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(En),this._resetAdjustments(),this._scrollBar.reset(),fe.trigger(this._element,pn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(fe.trigger(this._element,fn).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(Tn)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(Tn),this._queueCallback((()=>{this._element.classList.remove(Tn),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=Kt()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=Kt()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=xn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}fe.on(document,wn,'[data-bs-toggle="modal"]',(function(t){const e=we.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),fe.one(e,mn,(t=>{t.defaultPrevented||fe.one(e,pn,(()=>{Bt(this)&&this.focus()}))}));const i=we.findOne(".modal.show");i&&xn.getInstance(i).hide(),xn.getOrCreateInstance(e).toggle(this)})),Ee(xn),Qt(xn);const kn=".bs.offcanvas",Ln=".data-api",Sn=`load${kn}${Ln}`,Dn="show",$n="showing",In="hiding",Nn=".offcanvas.show",Pn=`show${kn}`,Mn=`shown${kn}`,jn=`hide${kn}`,Fn=`hidePrevented${kn}`,Hn=`hidden${kn}`,Bn=`resize${kn}`,Wn=`click${kn}${Ln}`,zn=`keydown.dismiss${kn}`,Rn={backdrop:!0,keyboard:!0,scroll:!1},qn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class Vn extends ve{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return Rn}static get DefaultType(){return qn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||fe.trigger(this._element,Pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new hn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($n),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Dn),this._element.classList.remove($n),fe.trigger(this._element,Mn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(fe.trigger(this._element,jn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add(In),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Dn,In),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new hn).reset(),fe.trigger(this._element,Hn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Gi({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():fe.trigger(this._element,Fn)}:null})}_initializeFocusTrap(){return new on({trapElement:this._element})}_addEventListeners(){fe.on(this._element,zn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():fe.trigger(this._element,Fn))}))}static jQueryInterface(t){return this.each((function(){const e=Vn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}fe.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=we.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),Wt(this))return;fe.one(e,Hn,(()=>{Bt(this)&&this.focus()}));const i=we.findOne(Nn);i&&i!==e&&Vn.getInstance(i).hide(),Vn.getOrCreateInstance(e).toggle(this)})),fe.on(window,Sn,(()=>{for(const t of we.find(Nn))Vn.getOrCreateInstance(t).show()})),fe.on(window,Bn,(()=>{for(const t of we.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&Vn.getOrCreateInstance(t).hide()})),Ee(Vn),Qt(Vn);const Yn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Un={allowList:Yn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"

"},Gn={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},Jn={entry:"(string|element|function|null)",selector:"(string|element)"};class Zn extends be{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Un}static get DefaultType(){return Gn}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Jn)}_setContent(t,e,i){const n=we.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?Ft(e)?this._putElementInTemplate(Ht(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return Xt(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const ts=new Set(["sanitize","allowList","sanitizeFn"]),es="fade",is="show",ns=".modal",ss="hide.bs.modal",os="hover",rs="focus",as={AUTO:"auto",TOP:"top",RIGHT:Kt()?"left":"right",BOTTOM:"bottom",LEFT:Kt()?"right":"left"},ls={allowList:Yn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},cs={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class hs extends ve{constructor(t,i){if(void 0===e)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,i),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return ls}static get DefaultType(){return cs}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),fe.off(this._element.closest(ns),ss,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=fe.trigger(this._element,this.constructor.eventName("show")),e=(zt(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),fe.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(is),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.on(t,"mouseover",Rt);this._queueCallback((()=>{fe.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!fe.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(is),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.off(t,"mouseover",Rt);this._activeTrigger.click=!1,this._activeTrigger[rs]=!1,this._activeTrigger[os]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),fe.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(es,is),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(es),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Zn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(es)}_isShown(){return this.tip&&this.tip.classList.contains(is)}_createPopper(t){const e=Xt(this._config.placement,[this,t,this._element]),i=as[e.toUpperCase()];return Dt(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return Xt(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...Xt(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)fe.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===os?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===os?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");fe.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?rs:os]=!0,e._enter()})),fe.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?rs:os]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},fe.on(this._element.closest(ns),ss,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=_e.getDataAttributes(this._element);for(const t of Object.keys(e))ts.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:Ht(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=hs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}Qt(hs);const ds={...hs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},us={...hs.DefaultType,content:"(null|string|element|function)"};class fs extends hs{static get Default(){return ds}static get DefaultType(){return us}static get 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e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=we.find(vs,this._config.target);for(const e of t){if(!e.hash||Wt(e))continue;const t=we.findOne(decodeURI(e.hash),this._element);Bt(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(bs),this._activateParents(t),fe.trigger(this._element,ms,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))we.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(bs);else for(const e of we.parents(t,".nav, .list-group"))for(const t of we.prev(e,ws))t.classList.add(bs)}_clearActiveClass(t){t.classList.remove(bs);const e=we.find(`${vs}.${bs}`,t);for(const t of e)t.classList.remove(bs)}static jQueryInterface(t){return this.each((function(){const e=Ts.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}fe.on(window,_s,(()=>{for(const t of we.find('[data-bs-spy="scroll"]'))Ts.getOrCreateInstance(t)})),Qt(Ts);const Cs=".bs.tab",Os=`hide${Cs}`,xs=`hidden${Cs}`,ks=`show${Cs}`,Ls=`shown${Cs}`,Ss=`click${Cs}`,Ds=`keydown${Cs}`,$s=`load${Cs}`,Is="ArrowLeft",Ns="ArrowRight",Ps="ArrowUp",Ms="ArrowDown",js="Home",Fs="End",Hs="active",Bs="fade",Ws="show",zs=".dropdown-toggle",Rs=`:not(${zs})`,qs='[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',Vs=`.nav-link${Rs}, .list-group-item${Rs}, [role="tab"]${Rs}, ${qs}`,Ys=`.${Hs}[data-bs-toggle="tab"], .${Hs}[data-bs-toggle="pill"], .${Hs}[data-bs-toggle="list"]`;class Ks extends ve{constructor(t){super(t),this._parent=this._element.closest('.list-group, .nav, [role="tablist"]'),this._parent&&(this._setInitialAttributes(this._parent,this._getChildren()),fe.on(this._element,Ds,(t=>this._keydown(t))))}static get NAME(){return"tab"}show(){const t=this._element;if(this._elemIsActive(t))return;const e=this._getActiveElem(),i=e?fe.trigger(e,Os,{relatedTarget:t}):null;fe.trigger(t,ks,{relatedTarget:e}).defaultPrevented||i&&i.defaultPrevented||(this._deactivate(e,t),this._activate(t,e))}_activate(t,e){t&&(t.classList.add(Hs),this._activate(we.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.removeAttribute("tabindex"),t.setAttribute("aria-selected",!0),this._toggleDropDown(t,!0),fe.trigger(t,Ls,{relatedTarget:e})):t.classList.add(Ws)}),t,t.classList.contains(Bs)))}_deactivate(t,e){t&&(t.classList.remove(Hs),t.blur(),this._deactivate(we.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.setAttribute("aria-selected",!1),t.setAttribute("tabindex","-1"),this._toggleDropDown(t,!1),fe.trigger(t,xs,{relatedTarget:e})):t.classList.remove(Ws)}),t,t.classList.contains(Bs)))}_keydown(t){if(![Is,Ns,Ps,Ms,js,Fs].includes(t.key))return;t.stopPropagation(),t.preventDefault();const e=this._getChildren().filter((t=>!Wt(t)));let i;if([js,Fs].includes(t.key))i=e[t.key===js?0:e.length-1];else{const n=[Ns,Ms].includes(t.key);i=Gt(e,t.target,n,!0)}i&&(i.focus({preventScroll:!0}),Ks.getOrCreateInstance(i).show())}_getChildren(){return we.find(Vs,this._parent)}_getActiveElem(){return this._getChildren().find((t=>this._elemIsActive(t)))||null}_setInitialAttributes(t,e){this._setAttributeIfNotExists(t,"role","tablist");for(const t of e)this._setInitialAttributesOnChild(t)}_setInitialAttributesOnChild(t){t=this._getInnerElement(t);const e=this._elemIsActive(t),i=this._getOuterElement(t);t.setAttribute("aria-selected",e),i!==t&&this._setAttributeIfNotExists(i,"role","presentation"),e||t.setAttribute("tabindex","-1"),this._setAttributeIfNotExists(t,"role","tab"),this._setInitialAttributesOnTargetPanel(t)}_setInitialAttributesOnTargetPanel(t){const e=we.getElementFromSelector(t);e&&(this._setAttributeIfNotExists(e,"role","tabpanel"),t.id&&this._setAttributeIfNotExists(e,"aria-labelledby",`${t.id}`))}_toggleDropDown(t,e){const i=this._getOuterElement(t);if(!i.classList.contains("dropdown"))return;const n=(t,n)=>{const s=we.findOne(t,i);s&&s.classList.toggle(n,e)};n(zs,Hs),n(".dropdown-menu",Ws),i.setAttribute("aria-expanded",e)}_setAttributeIfNotExists(t,e,i){t.hasAttribute(e)||t.setAttribute(e,i)}_elemIsActive(t){return t.classList.contains(Hs)}_getInnerElement(t){return t.matches(Vs)?t:we.findOne(Vs,t)}_getOuterElement(t){return t.closest(".nav-item, .list-group-item")||t}static jQueryInterface(t){return this.each((function(){const e=Ks.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}fe.on(document,Ss,qs,(function(t){["A","AREA"].includes(this.tagName)&&t.preventDefault(),Wt(this)||Ks.getOrCreateInstance(this).show()})),fe.on(window,$s,(()=>{for(const t of we.find(Ys))Ks.getOrCreateInstance(t)})),Qt(Ks);const Qs=".bs.toast",Xs=`mouseover${Qs}`,Us=`mouseout${Qs}`,Gs=`focusin${Qs}`,Js=`focusout${Qs}`,Zs=`hide${Qs}`,to=`hidden${Qs}`,eo=`show${Qs}`,io=`shown${Qs}`,no="hide",so="show",oo="showing",ro={animation:"boolean",autohide:"boolean",delay:"number"},ao={animation:!0,autohide:!0,delay:5e3};class lo extends ve{constructor(t,e){super(t,e),this._timeout=null,this._hasMouseInteraction=!1,this._hasKeyboardInteraction=!1,this._setListeners()}static get Default(){return ao}static get DefaultType(){return ro}static get NAME(){return"toast"}show(){fe.trigger(this._element,eo).defaultPrevented||(this._clearTimeout(),this._config.animation&&this._element.classList.add("fade"),this._element.classList.remove(no),qt(this._element),this._element.classList.add(so,oo),this._queueCallback((()=>{this._element.classList.remove(oo),fe.trigger(this._element,io),this._maybeScheduleHide()}),this._element,this._config.animation))}hide(){this.isShown()&&(fe.trigger(this._element,Zs).defaultPrevented||(this._element.classList.add(oo),this._queueCallback((()=>{this._element.classList.add(no),this._element.classList.remove(oo,so),fe.trigger(this._element,to)}),this._element,this._config.animation)))}dispose(){this._clearTimeout(),this.isShown()&&this._element.classList.remove(so),super.dispose()}isShown(){return this._element.classList.contains(so)}_maybeScheduleHide(){this._config.autohide&&(this._hasMouseInteraction||this._hasKeyboardInteraction||(this._timeout=setTimeout((()=>{this.hide()}),this._config.delay)))}_onInteraction(t,e){switch(t.type){case"mouseover":case"mouseout":this._hasMouseInteraction=e;break;case"focusin":case"focusout":this._hasKeyboardInteraction=e}if(e)return void this._clearTimeout();const i=t.relatedTarget;this._element===i||this._element.contains(i)||this._maybeScheduleHide()}_setListeners(){fe.on(this._element,Xs,(t=>this._onInteraction(t,!0))),fe.on(this._element,Us,(t=>this._onInteraction(t,!1))),fe.on(this._element,Gs,(t=>this._onInteraction(t,!0))),fe.on(this._element,Js,(t=>this._onInteraction(t,!1)))}_clearTimeout(){clearTimeout(this._timeout),this._timeout=null}static jQueryInterface(t){return this.each((function(){const e=lo.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named 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(element.nodeName || '').toLowerCase() : null;\n}","export default function getWindow(node) {\n if (node == null) {\n return window;\n }\n\n if (node.toString() !== '[object Window]') {\n var ownerDocument = node.ownerDocument;\n return ownerDocument ? ownerDocument.defaultView || window : window;\n }\n\n return node;\n}","import getWindow from \"./getWindow.js\";\n\nfunction isElement(node) {\n var OwnElement = getWindow(node).Element;\n return node instanceof OwnElement || node instanceof Element;\n}\n\nfunction isHTMLElement(node) {\n var OwnElement = getWindow(node).HTMLElement;\n return node instanceof OwnElement || node instanceof HTMLElement;\n}\n\nfunction isShadowRoot(node) {\n // IE 11 has no ShadowRoot\n if (typeof ShadowRoot === 'undefined') {\n return false;\n }\n\n var OwnElement = getWindow(node).ShadowRoot;\n return node instanceof OwnElement || node instanceof ShadowRoot;\n}\n\nexport { isElement, isHTMLElement, isShadowRoot };","import getNodeName from \"../dom-utils/getNodeName.js\";\nimport { isHTMLElement } from \"../dom-utils/instanceOf.js\"; // This modifier takes the styles prepared by the `computeStyles` modifier\n// and applies them to the HTMLElements such as popper and arrow\n\nfunction applyStyles(_ref) {\n var state = _ref.state;\n Object.keys(state.elements).forEach(function (name) {\n var style = state.styles[name] || {};\n var attributes = state.attributes[name] || {};\n var element = state.elements[name]; // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n } // Flow doesn't support to extend this property, but it's the most\n // effective way to apply styles to an HTMLElement\n // $FlowFixMe[cannot-write]\n\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (name) {\n var value = attributes[name];\n\n if (value === false) {\n element.removeAttribute(name);\n } else {\n element.setAttribute(name, value === true ? '' : value);\n }\n });\n });\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state;\n var initialStyles = {\n popper: {\n position: state.options.strategy,\n left: '0',\n top: '0',\n margin: '0'\n },\n arrow: {\n position: 'absolute'\n },\n reference: {}\n };\n Object.assign(state.elements.popper.style, initialStyles.popper);\n state.styles = initialStyles;\n\n if (state.elements.arrow) {\n Object.assign(state.elements.arrow.style, initialStyles.arrow);\n }\n\n return function () {\n Object.keys(state.elements).forEach(function (name) {\n var element = state.elements[name];\n var attributes = state.attributes[name] || {};\n var styleProperties = Object.keys(state.styles.hasOwnProperty(name) ? state.styles[name] : initialStyles[name]); // Set all values to an empty string to unset them\n\n var style = styleProperties.reduce(function (style, property) {\n style[property] = '';\n return style;\n }, {}); // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n }\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (attribute) {\n element.removeAttribute(attribute);\n });\n });\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'applyStyles',\n enabled: true,\n phase: 'write',\n fn: applyStyles,\n effect: effect,\n requires: ['computeStyles']\n};","import { auto } from \"../enums.js\";\nexport default function getBasePlacement(placement) {\n return placement.split('-')[0];\n}","export var max = Math.max;\nexport var min = Math.min;\nexport var round = Math.round;","export default function getUAString() {\n var uaData = navigator.userAgentData;\n\n if (uaData != null && uaData.brands && Array.isArray(uaData.brands)) {\n return uaData.brands.map(function (item) {\n return item.brand + \"/\" + item.version;\n }).join(' ');\n }\n\n return navigator.userAgent;\n}","import getUAString from \"../utils/userAgent.js\";\nexport default function isLayoutViewport() {\n return !/^((?!chrome|android).)*safari/i.test(getUAString());\n}","import { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport { round } from \"../utils/math.js\";\nimport getWindow from \"./getWindow.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getBoundingClientRect(element, includeScale, isFixedStrategy) {\n if (includeScale === void 0) {\n includeScale = false;\n }\n\n if (isFixedStrategy === void 0) {\n isFixedStrategy = false;\n }\n\n var clientRect = element.getBoundingClientRect();\n var scaleX = 1;\n var scaleY = 1;\n\n if (includeScale && isHTMLElement(element)) {\n scaleX = element.offsetWidth > 0 ? round(clientRect.width) / element.offsetWidth || 1 : 1;\n scaleY = element.offsetHeight > 0 ? round(clientRect.height) / element.offsetHeight || 1 : 1;\n }\n\n var _ref = isElement(element) ? getWindow(element) : window,\n visualViewport = _ref.visualViewport;\n\n var addVisualOffsets = !isLayoutViewport() && isFixedStrategy;\n var x = (clientRect.left + (addVisualOffsets && visualViewport ? visualViewport.offsetLeft : 0)) / scaleX;\n var y = (clientRect.top + (addVisualOffsets && visualViewport ? visualViewport.offsetTop : 0)) / scaleY;\n var width = clientRect.width / scaleX;\n var height = clientRect.height / scaleY;\n return {\n width: width,\n height: height,\n top: y,\n right: x + width,\n bottom: y + height,\n left: x,\n x: x,\n y: y\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\"; // Returns the layout rect of an element relative to its offsetParent. Layout\n// means it doesn't take into account transforms.\n\nexport default function getLayoutRect(element) {\n var clientRect = getBoundingClientRect(element); // Use the clientRect sizes if it's not been transformed.\n // Fixes https://github.com/popperjs/popper-core/issues/1223\n\n var width = element.offsetWidth;\n var height = element.offsetHeight;\n\n if (Math.abs(clientRect.width - width) <= 1) {\n width = clientRect.width;\n }\n\n if (Math.abs(clientRect.height - height) <= 1) {\n height = clientRect.height;\n }\n\n return {\n x: element.offsetLeft,\n y: element.offsetTop,\n width: width,\n height: height\n };\n}","import { isShadowRoot } from \"./instanceOf.js\";\nexport default function contains(parent, child) {\n var rootNode = child.getRootNode && child.getRootNode(); // First, attempt with faster native method\n\n if (parent.contains(child)) {\n return true;\n } // then fallback to custom implementation with Shadow DOM support\n else if (rootNode && isShadowRoot(rootNode)) {\n var next = child;\n\n do {\n if (next && parent.isSameNode(next)) {\n return true;\n } // $FlowFixMe[prop-missing]: need a better way to handle this...\n\n\n next = next.parentNode || next.host;\n } while (next);\n } // Give up, the result is false\n\n\n return false;\n}","import getWindow from \"./getWindow.js\";\nexport default function getComputedStyle(element) {\n return getWindow(element).getComputedStyle(element);\n}","import getNodeName from \"./getNodeName.js\";\nexport default function isTableElement(element) {\n return ['table', 'td', 'th'].indexOf(getNodeName(element)) >= 0;\n}","import { isElement } from \"./instanceOf.js\";\nexport default function getDocumentElement(element) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return ((isElement(element) ? element.ownerDocument : // $FlowFixMe[prop-missing]\n element.document) || window.document).documentElement;\n}","import getNodeName from \"./getNodeName.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport { isShadowRoot } from \"./instanceOf.js\";\nexport default function getParentNode(element) {\n if (getNodeName(element) === 'html') {\n return element;\n }\n\n return (// this is a quicker (but less type safe) way to save quite some bytes from the bundle\n // $FlowFixMe[incompatible-return]\n // $FlowFixMe[prop-missing]\n element.assignedSlot || // step into the shadow DOM of the parent of a slotted node\n element.parentNode || ( // DOM Element detected\n isShadowRoot(element) ? element.host : null) || // ShadowRoot detected\n // $FlowFixMe[incompatible-call]: HTMLElement is a Node\n getDocumentElement(element) // fallback\n\n );\n}","import getWindow from \"./getWindow.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isHTMLElement, isShadowRoot } from \"./instanceOf.js\";\nimport isTableElement from \"./isTableElement.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getUAString from \"../utils/userAgent.js\";\n\nfunction getTrueOffsetParent(element) {\n if (!isHTMLElement(element) || // https://github.com/popperjs/popper-core/issues/837\n getComputedStyle(element).position === 'fixed') {\n return null;\n }\n\n return element.offsetParent;\n} // `.offsetParent` reports `null` for fixed elements, while absolute elements\n// return the containing block\n\n\nfunction getContainingBlock(element) {\n var isFirefox = /firefox/i.test(getUAString());\n var isIE = /Trident/i.test(getUAString());\n\n if (isIE && isHTMLElement(element)) {\n // In IE 9, 10 and 11 fixed elements containing block is always established by the viewport\n var elementCss = getComputedStyle(element);\n\n if (elementCss.position === 'fixed') {\n return null;\n }\n }\n\n var currentNode = getParentNode(element);\n\n if (isShadowRoot(currentNode)) {\n currentNode = currentNode.host;\n }\n\n while (isHTMLElement(currentNode) && ['html', 'body'].indexOf(getNodeName(currentNode)) < 0) {\n var css = getComputedStyle(currentNode); // This is non-exhaustive but covers the most common CSS properties that\n // create a containing block.\n // https://developer.mozilla.org/en-US/docs/Web/CSS/Containing_block#identifying_the_containing_block\n\n if (css.transform !== 'none' || css.perspective !== 'none' || css.contain === 'paint' || ['transform', 'perspective'].indexOf(css.willChange) !== -1 || isFirefox && css.willChange === 'filter' || isFirefox && css.filter && css.filter !== 'none') {\n return currentNode;\n } else {\n currentNode = currentNode.parentNode;\n }\n }\n\n return null;\n} // Gets the closest ancestor positioned element. Handles some edge cases,\n// such as table ancestors and cross browser bugs.\n\n\nexport default function getOffsetParent(element) {\n var window = getWindow(element);\n var offsetParent = getTrueOffsetParent(element);\n\n while (offsetParent && isTableElement(offsetParent) && getComputedStyle(offsetParent).position === 'static') {\n offsetParent = getTrueOffsetParent(offsetParent);\n }\n\n if (offsetParent && (getNodeName(offsetParent) === 'html' || getNodeName(offsetParent) === 'body' && getComputedStyle(offsetParent).position === 'static')) {\n return window;\n }\n\n return offsetParent || getContainingBlock(element) || window;\n}","export default function getMainAxisFromPlacement(placement) {\n return ['top', 'bottom'].indexOf(placement) >= 0 ? 'x' : 'y';\n}","import { max as mathMax, min as mathMin } from \"./math.js\";\nexport function within(min, value, max) {\n return mathMax(min, mathMin(value, max));\n}\nexport function withinMaxClamp(min, value, max) {\n var v = within(min, value, max);\n return v > max ? max : v;\n}","import getFreshSideObject from \"./getFreshSideObject.js\";\nexport default function mergePaddingObject(paddingObject) {\n return Object.assign({}, getFreshSideObject(), paddingObject);\n}","export default function getFreshSideObject() {\n return {\n top: 0,\n right: 0,\n bottom: 0,\n left: 0\n };\n}","export default function expandToHashMap(value, keys) {\n return keys.reduce(function (hashMap, key) {\n hashMap[key] = value;\n return hashMap;\n }, {});\n}","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport contains from \"../dom-utils/contains.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport { within } from \"../utils/within.js\";\nimport mergePaddingObject from \"../utils/mergePaddingObject.js\";\nimport expandToHashMap from \"../utils/expandToHashMap.js\";\nimport { left, right, basePlacements, top, bottom } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar toPaddingObject = function toPaddingObject(padding, state) {\n padding = typeof padding === 'function' ? padding(Object.assign({}, state.rects, {\n placement: state.placement\n })) : padding;\n return mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n};\n\nfunction arrow(_ref) {\n var _state$modifiersData$;\n\n var state = _ref.state,\n name = _ref.name,\n options = _ref.options;\n var arrowElement = state.elements.arrow;\n var popperOffsets = state.modifiersData.popperOffsets;\n var basePlacement = getBasePlacement(state.placement);\n var axis = getMainAxisFromPlacement(basePlacement);\n var isVertical = [left, right].indexOf(basePlacement) >= 0;\n var len = isVertical ? 'height' : 'width';\n\n if (!arrowElement || !popperOffsets) {\n return;\n }\n\n var paddingObject = toPaddingObject(options.padding, state);\n var arrowRect = getLayoutRect(arrowElement);\n var minProp = axis === 'y' ? top : left;\n var maxProp = axis === 'y' ? bottom : right;\n var endDiff = state.rects.reference[len] + state.rects.reference[axis] - popperOffsets[axis] - state.rects.popper[len];\n var startDiff = popperOffsets[axis] - state.rects.reference[axis];\n var arrowOffsetParent = getOffsetParent(arrowElement);\n var clientSize = arrowOffsetParent ? axis === 'y' ? arrowOffsetParent.clientHeight || 0 : arrowOffsetParent.clientWidth || 0 : 0;\n var centerToReference = endDiff / 2 - startDiff / 2; // Make sure the arrow doesn't overflow the popper if the center point is\n // outside of the popper bounds\n\n var min = paddingObject[minProp];\n var max = clientSize - arrowRect[len] - paddingObject[maxProp];\n var center = clientSize / 2 - arrowRect[len] / 2 + centerToReference;\n var offset = within(min, center, max); // Prevents breaking syntax highlighting...\n\n var axisProp = axis;\n state.modifiersData[name] = (_state$modifiersData$ = {}, _state$modifiersData$[axisProp] = offset, _state$modifiersData$.centerOffset = offset - center, _state$modifiersData$);\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state,\n options = _ref2.options;\n var _options$element = options.element,\n arrowElement = _options$element === void 0 ? '[data-popper-arrow]' : _options$element;\n\n if (arrowElement == null) {\n return;\n } // CSS selector\n\n\n if (typeof arrowElement === 'string') {\n arrowElement = state.elements.popper.querySelector(arrowElement);\n\n if (!arrowElement) {\n return;\n }\n }\n\n if (!contains(state.elements.popper, arrowElement)) {\n return;\n }\n\n state.elements.arrow = arrowElement;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'arrow',\n enabled: true,\n phase: 'main',\n fn: arrow,\n effect: effect,\n requires: ['popperOffsets'],\n requiresIfExists: ['preventOverflow']\n};","export default function getVariation(placement) {\n return placement.split('-')[1];\n}","import { top, left, right, bottom, end } from \"../enums.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getWindow from \"../dom-utils/getWindow.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getComputedStyle from \"../dom-utils/getComputedStyle.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport { round } from \"../utils/math.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar unsetSides = {\n top: 'auto',\n right: 'auto',\n bottom: 'auto',\n left: 'auto'\n}; // Round the offsets to the nearest suitable subpixel based on the DPR.\n// Zooming can change the DPR, but it seems to report a value that will\n// cleanly divide the values into the appropriate subpixels.\n\nfunction roundOffsetsByDPR(_ref, win) {\n var x = _ref.x,\n y = _ref.y;\n var dpr = win.devicePixelRatio || 1;\n return {\n x: round(x * dpr) / dpr || 0,\n y: round(y * dpr) / dpr || 0\n };\n}\n\nexport function mapToStyles(_ref2) {\n var _Object$assign2;\n\n var popper = _ref2.popper,\n popperRect = _ref2.popperRect,\n placement = _ref2.placement,\n variation = _ref2.variation,\n offsets = _ref2.offsets,\n position = _ref2.position,\n gpuAcceleration = _ref2.gpuAcceleration,\n adaptive = _ref2.adaptive,\n roundOffsets = _ref2.roundOffsets,\n isFixed = _ref2.isFixed;\n var _offsets$x = offsets.x,\n x = _offsets$x === void 0 ? 0 : _offsets$x,\n _offsets$y = offsets.y,\n y = _offsets$y === void 0 ? 0 : _offsets$y;\n\n var _ref3 = typeof roundOffsets === 'function' ? roundOffsets({\n x: x,\n y: y\n }) : {\n x: x,\n y: y\n };\n\n x = _ref3.x;\n y = _ref3.y;\n var hasX = offsets.hasOwnProperty('x');\n var hasY = offsets.hasOwnProperty('y');\n var sideX = left;\n var sideY = top;\n var win = window;\n\n if (adaptive) {\n var offsetParent = getOffsetParent(popper);\n var heightProp = 'clientHeight';\n var widthProp = 'clientWidth';\n\n if (offsetParent === getWindow(popper)) {\n offsetParent = getDocumentElement(popper);\n\n if (getComputedStyle(offsetParent).position !== 'static' && position === 'absolute') {\n heightProp = 'scrollHeight';\n widthProp = 'scrollWidth';\n }\n } // $FlowFixMe[incompatible-cast]: force type refinement, we compare offsetParent with window above, but Flow doesn't detect it\n\n\n offsetParent = offsetParent;\n\n if (placement === top || (placement === left || placement === right) && variation === end) {\n sideY = bottom;\n var offsetY = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.height : // $FlowFixMe[prop-missing]\n offsetParent[heightProp];\n y -= offsetY - popperRect.height;\n y *= gpuAcceleration ? 1 : -1;\n }\n\n if (placement === left || (placement === top || placement === bottom) && variation === end) {\n sideX = right;\n var offsetX = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.width : // $FlowFixMe[prop-missing]\n offsetParent[widthProp];\n x -= offsetX - popperRect.width;\n x *= gpuAcceleration ? 1 : -1;\n }\n }\n\n var commonStyles = Object.assign({\n position: position\n }, adaptive && unsetSides);\n\n var _ref4 = roundOffsets === true ? roundOffsetsByDPR({\n x: x,\n y: y\n }, getWindow(popper)) : {\n x: x,\n y: y\n };\n\n x = _ref4.x;\n y = _ref4.y;\n\n if (gpuAcceleration) {\n var _Object$assign;\n\n return Object.assign({}, commonStyles, (_Object$assign = {}, _Object$assign[sideY] = hasY ? '0' : '', _Object$assign[sideX] = hasX ? '0' : '', _Object$assign.transform = (win.devicePixelRatio || 1) <= 1 ? \"translate(\" + x + \"px, \" + y + \"px)\" : \"translate3d(\" + x + \"px, \" + y + \"px, 0)\", _Object$assign));\n }\n\n return Object.assign({}, commonStyles, (_Object$assign2 = {}, _Object$assign2[sideY] = hasY ? y + \"px\" : '', _Object$assign2[sideX] = hasX ? x + \"px\" : '', _Object$assign2.transform = '', _Object$assign2));\n}\n\nfunction computeStyles(_ref5) {\n var state = _ref5.state,\n options = _ref5.options;\n var _options$gpuAccelerat = options.gpuAcceleration,\n gpuAcceleration = _options$gpuAccelerat === void 0 ? true : _options$gpuAccelerat,\n _options$adaptive = options.adaptive,\n adaptive = _options$adaptive === void 0 ? true : _options$adaptive,\n _options$roundOffsets = options.roundOffsets,\n roundOffsets = _options$roundOffsets === void 0 ? true : _options$roundOffsets;\n var commonStyles = {\n placement: getBasePlacement(state.placement),\n variation: getVariation(state.placement),\n popper: state.elements.popper,\n popperRect: state.rects.popper,\n gpuAcceleration: gpuAcceleration,\n isFixed: state.options.strategy === 'fixed'\n };\n\n if (state.modifiersData.popperOffsets != null) {\n state.styles.popper = Object.assign({}, state.styles.popper, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.popperOffsets,\n position: state.options.strategy,\n adaptive: adaptive,\n roundOffsets: roundOffsets\n })));\n }\n\n if (state.modifiersData.arrow != null) {\n state.styles.arrow = Object.assign({}, state.styles.arrow, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.arrow,\n position: 'absolute',\n adaptive: false,\n roundOffsets: roundOffsets\n })));\n }\n\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-placement': state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'computeStyles',\n enabled: true,\n phase: 'beforeWrite',\n fn: computeStyles,\n data: {}\n};","import getWindow from \"../dom-utils/getWindow.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar passive = {\n passive: true\n};\n\nfunction effect(_ref) {\n var state = _ref.state,\n instance = _ref.instance,\n options = _ref.options;\n var _options$scroll = options.scroll,\n scroll = _options$scroll === void 0 ? true : _options$scroll,\n _options$resize = options.resize,\n resize = _options$resize === void 0 ? true : _options$resize;\n var window = getWindow(state.elements.popper);\n var scrollParents = [].concat(state.scrollParents.reference, state.scrollParents.popper);\n\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.addEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.addEventListener('resize', instance.update, passive);\n }\n\n return function () {\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.removeEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.removeEventListener('resize', instance.update, passive);\n }\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'eventListeners',\n enabled: true,\n phase: 'write',\n fn: function fn() {},\n effect: effect,\n data: {}\n};","var hash = {\n left: 'right',\n right: 'left',\n bottom: 'top',\n top: 'bottom'\n};\nexport default function getOppositePlacement(placement) {\n return placement.replace(/left|right|bottom|top/g, function (matched) {\n return hash[matched];\n });\n}","var hash = {\n start: 'end',\n end: 'start'\n};\nexport default function getOppositeVariationPlacement(placement) {\n return placement.replace(/start|end/g, function (matched) {\n return hash[matched];\n });\n}","import getWindow from \"./getWindow.js\";\nexport default function getWindowScroll(node) {\n var win = getWindow(node);\n var scrollLeft = win.pageXOffset;\n var scrollTop = win.pageYOffset;\n return {\n scrollLeft: scrollLeft,\n scrollTop: scrollTop\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nexport default function getWindowScrollBarX(element) {\n // If has a CSS width greater than the viewport, then this will be\n // incorrect for RTL.\n // Popper 1 is broken in this case and never had a bug report so let's assume\n // it's not an issue. I don't think anyone ever specifies width on \n // anyway.\n // Browsers where the left scrollbar doesn't cause an issue report `0` for\n // this (e.g. Edge 2019, IE11, Safari)\n return getBoundingClientRect(getDocumentElement(element)).left + getWindowScroll(element).scrollLeft;\n}","import getComputedStyle from \"./getComputedStyle.js\";\nexport default function isScrollParent(element) {\n // Firefox wants us to check `-x` and `-y` variations as well\n var _getComputedStyle = getComputedStyle(element),\n overflow = _getComputedStyle.overflow,\n overflowX = _getComputedStyle.overflowX,\n overflowY = _getComputedStyle.overflowY;\n\n return /auto|scroll|overlay|hidden/.test(overflow + overflowY + overflowX);\n}","import getParentNode from \"./getParentNode.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nexport default function getScrollParent(node) {\n if (['html', 'body', '#document'].indexOf(getNodeName(node)) >= 0) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return node.ownerDocument.body;\n }\n\n if (isHTMLElement(node) && isScrollParent(node)) {\n return node;\n }\n\n return getScrollParent(getParentNode(node));\n}","import getScrollParent from \"./getScrollParent.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getWindow from \"./getWindow.js\";\nimport isScrollParent from \"./isScrollParent.js\";\n/*\ngiven a DOM element, return the list of all scroll parents, up the list of ancesors\nuntil we get to the top window object. This list is what we attach scroll listeners\nto, because if any of these parent elements scroll, we'll need to re-calculate the\nreference element's position.\n*/\n\nexport default function listScrollParents(element, list) {\n var _element$ownerDocumen;\n\n if (list === void 0) {\n list = [];\n }\n\n var scrollParent = getScrollParent(element);\n var isBody = scrollParent === ((_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body);\n var win = getWindow(scrollParent);\n var target = isBody ? [win].concat(win.visualViewport || [], isScrollParent(scrollParent) ? scrollParent : []) : scrollParent;\n var updatedList = list.concat(target);\n return isBody ? updatedList : // $FlowFixMe[incompatible-call]: isBody tells us target will be an HTMLElement here\n updatedList.concat(listScrollParents(getParentNode(target)));\n}","export default function rectToClientRect(rect) {\n return Object.assign({}, rect, {\n left: rect.x,\n top: rect.y,\n right: rect.x + rect.width,\n bottom: rect.y + rect.height\n });\n}","import { viewport } from \"../enums.js\";\nimport getViewportRect from \"./getViewportRect.js\";\nimport getDocumentRect from \"./getDocumentRect.js\";\nimport listScrollParents from \"./listScrollParents.js\";\nimport getOffsetParent from \"./getOffsetParent.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport contains from \"./contains.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport rectToClientRect from \"../utils/rectToClientRect.js\";\nimport { max, min } from \"../utils/math.js\";\n\nfunction getInnerBoundingClientRect(element, strategy) {\n var rect = getBoundingClientRect(element, false, strategy === 'fixed');\n rect.top = rect.top + element.clientTop;\n rect.left = rect.left + element.clientLeft;\n rect.bottom = rect.top + element.clientHeight;\n rect.right = rect.left + element.clientWidth;\n rect.width = element.clientWidth;\n rect.height = element.clientHeight;\n rect.x = rect.left;\n rect.y = rect.top;\n return rect;\n}\n\nfunction getClientRectFromMixedType(element, clippingParent, strategy) {\n return clippingParent === viewport ? rectToClientRect(getViewportRect(element, strategy)) : isElement(clippingParent) ? getInnerBoundingClientRect(clippingParent, strategy) : rectToClientRect(getDocumentRect(getDocumentElement(element)));\n} // A \"clipping parent\" is an overflowable container with the characteristic of\n// clipping (or hiding) overflowing elements with a position different from\n// `initial`\n\n\nfunction getClippingParents(element) {\n var clippingParents = listScrollParents(getParentNode(element));\n var canEscapeClipping = ['absolute', 'fixed'].indexOf(getComputedStyle(element).position) >= 0;\n var clipperElement = canEscapeClipping && isHTMLElement(element) ? getOffsetParent(element) : element;\n\n if (!isElement(clipperElement)) {\n return [];\n } // $FlowFixMe[incompatible-return]: https://github.com/facebook/flow/issues/1414\n\n\n return clippingParents.filter(function (clippingParent) {\n return isElement(clippingParent) && contains(clippingParent, clipperElement) && getNodeName(clippingParent) !== 'body';\n });\n} // Gets the maximum area that the element is visible in due to any number of\n// clipping parents\n\n\nexport default function getClippingRect(element, boundary, rootBoundary, strategy) {\n var mainClippingParents = boundary === 'clippingParents' ? getClippingParents(element) : [].concat(boundary);\n var clippingParents = [].concat(mainClippingParents, [rootBoundary]);\n var firstClippingParent = clippingParents[0];\n var clippingRect = clippingParents.reduce(function (accRect, clippingParent) {\n var rect = getClientRectFromMixedType(element, clippingParent, strategy);\n accRect.top = max(rect.top, accRect.top);\n accRect.right = min(rect.right, accRect.right);\n accRect.bottom = min(rect.bottom, accRect.bottom);\n accRect.left = max(rect.left, accRect.left);\n return accRect;\n }, getClientRectFromMixedType(element, firstClippingParent, strategy));\n clippingRect.width = clippingRect.right - clippingRect.left;\n clippingRect.height = clippingRect.bottom - clippingRect.top;\n clippingRect.x = clippingRect.left;\n clippingRect.y = clippingRect.top;\n return clippingRect;\n}","import getWindow from \"./getWindow.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getViewportRect(element, strategy) {\n var win = getWindow(element);\n var html = getDocumentElement(element);\n var visualViewport = win.visualViewport;\n var width = html.clientWidth;\n var height = html.clientHeight;\n var x = 0;\n var y = 0;\n\n if (visualViewport) {\n width = visualViewport.width;\n height = visualViewport.height;\n var layoutViewport = isLayoutViewport();\n\n if (layoutViewport || !layoutViewport && strategy === 'fixed') {\n x = visualViewport.offsetLeft;\n y = visualViewport.offsetTop;\n }\n }\n\n return {\n width: width,\n height: height,\n x: x + getWindowScrollBarX(element),\n y: y\n };\n}","import getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nimport { max } from \"../utils/math.js\"; // Gets the entire size of the scrollable document area, even extending outside\n// of the `` and `` rect bounds if horizontally scrollable\n\nexport default function getDocumentRect(element) {\n var _element$ownerDocumen;\n\n var html = getDocumentElement(element);\n var winScroll = getWindowScroll(element);\n var body = (_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body;\n var width = max(html.scrollWidth, html.clientWidth, body ? body.scrollWidth : 0, body ? body.clientWidth : 0);\n var height = max(html.scrollHeight, html.clientHeight, body ? body.scrollHeight : 0, body ? body.clientHeight : 0);\n var x = -winScroll.scrollLeft + getWindowScrollBarX(element);\n var y = -winScroll.scrollTop;\n\n if (getComputedStyle(body || html).direction === 'rtl') {\n x += max(html.clientWidth, body ? body.clientWidth : 0) - width;\n }\n\n return {\n width: width,\n height: height,\n x: x,\n y: y\n };\n}","import getBasePlacement from \"./getBasePlacement.js\";\nimport getVariation from \"./getVariation.js\";\nimport getMainAxisFromPlacement from \"./getMainAxisFromPlacement.js\";\nimport { top, right, bottom, left, start, end } from \"../enums.js\";\nexport default function computeOffsets(_ref) {\n var reference = _ref.reference,\n element = _ref.element,\n placement = _ref.placement;\n var basePlacement = placement ? getBasePlacement(placement) : null;\n var variation = placement ? getVariation(placement) : null;\n var commonX = reference.x + reference.width / 2 - element.width / 2;\n var commonY = reference.y + reference.height / 2 - element.height / 2;\n var offsets;\n\n switch (basePlacement) {\n case top:\n offsets = {\n x: commonX,\n y: reference.y - element.height\n };\n break;\n\n case bottom:\n offsets = {\n x: commonX,\n y: reference.y + reference.height\n };\n break;\n\n case right:\n offsets = {\n x: reference.x + reference.width,\n y: commonY\n };\n break;\n\n case left:\n offsets = {\n x: reference.x - element.width,\n y: commonY\n };\n break;\n\n default:\n offsets = {\n x: reference.x,\n y: reference.y\n };\n }\n\n var mainAxis = basePlacement ? getMainAxisFromPlacement(basePlacement) : null;\n\n if (mainAxis != null) {\n var len = mainAxis === 'y' ? 'height' : 'width';\n\n switch (variation) {\n case start:\n offsets[mainAxis] = offsets[mainAxis] - (reference[len] / 2 - element[len] / 2);\n break;\n\n case end:\n offsets[mainAxis] = offsets[mainAxis] + (reference[len] / 2 - element[len] / 2);\n break;\n\n default:\n }\n }\n\n return offsets;\n}","import getClippingRect from \"../dom-utils/getClippingRect.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getBoundingClientRect from \"../dom-utils/getBoundingClientRect.js\";\nimport computeOffsets from \"./computeOffsets.js\";\nimport rectToClientRect from \"./rectToClientRect.js\";\nimport { clippingParents, reference, popper, bottom, top, right, basePlacements, viewport } from \"../enums.js\";\nimport { isElement } from \"../dom-utils/instanceOf.js\";\nimport mergePaddingObject from \"./mergePaddingObject.js\";\nimport expandToHashMap from \"./expandToHashMap.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport default function detectOverflow(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n _options$placement = _options.placement,\n placement = _options$placement === void 0 ? state.placement : _options$placement,\n _options$strategy = _options.strategy,\n strategy = _options$strategy === void 0 ? state.strategy : _options$strategy,\n _options$boundary = _options.boundary,\n boundary = _options$boundary === void 0 ? clippingParents : _options$boundary,\n _options$rootBoundary = _options.rootBoundary,\n rootBoundary = _options$rootBoundary === void 0 ? viewport : _options$rootBoundary,\n _options$elementConte = _options.elementContext,\n elementContext = _options$elementConte === void 0 ? popper : _options$elementConte,\n _options$altBoundary = _options.altBoundary,\n altBoundary = _options$altBoundary === void 0 ? false : _options$altBoundary,\n _options$padding = _options.padding,\n padding = _options$padding === void 0 ? 0 : _options$padding;\n var paddingObject = mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n var altContext = elementContext === popper ? reference : popper;\n var popperRect = state.rects.popper;\n var element = state.elements[altBoundary ? altContext : elementContext];\n var clippingClientRect = getClippingRect(isElement(element) ? element : element.contextElement || getDocumentElement(state.elements.popper), boundary, rootBoundary, strategy);\n var referenceClientRect = getBoundingClientRect(state.elements.reference);\n var popperOffsets = computeOffsets({\n reference: referenceClientRect,\n element: popperRect,\n strategy: 'absolute',\n placement: placement\n });\n var popperClientRect = rectToClientRect(Object.assign({}, popperRect, popperOffsets));\n var elementClientRect = elementContext === popper ? popperClientRect : referenceClientRect; // positive = overflowing the clipping rect\n // 0 or negative = within the clipping rect\n\n var overflowOffsets = {\n top: clippingClientRect.top - elementClientRect.top + paddingObject.top,\n bottom: elementClientRect.bottom - clippingClientRect.bottom + paddingObject.bottom,\n left: clippingClientRect.left - elementClientRect.left + paddingObject.left,\n right: elementClientRect.right - clippingClientRect.right + paddingObject.right\n };\n var offsetData = state.modifiersData.offset; // Offsets can be applied only to the popper element\n\n if (elementContext === popper && offsetData) {\n var offset = offsetData[placement];\n Object.keys(overflowOffsets).forEach(function (key) {\n var multiply = [right, bottom].indexOf(key) >= 0 ? 1 : -1;\n var axis = [top, bottom].indexOf(key) >= 0 ? 'y' : 'x';\n overflowOffsets[key] += offset[axis] * multiply;\n });\n }\n\n return overflowOffsets;\n}","import getOppositePlacement from \"../utils/getOppositePlacement.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getOppositeVariationPlacement from \"../utils/getOppositeVariationPlacement.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport computeAutoPlacement from \"../utils/computeAutoPlacement.js\";\nimport { bottom, top, start, right, left, auto } from \"../enums.js\";\nimport getVariation from \"../utils/getVariation.js\"; // eslint-disable-next-line import/no-unused-modules\n\nfunction getExpandedFallbackPlacements(placement) {\n if (getBasePlacement(placement) === auto) {\n return [];\n }\n\n var oppositePlacement = getOppositePlacement(placement);\n return [getOppositeVariationPlacement(placement), oppositePlacement, getOppositeVariationPlacement(oppositePlacement)];\n}\n\nfunction flip(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n\n if (state.modifiersData[name]._skip) {\n return;\n }\n\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? true : _options$altAxis,\n specifiedFallbackPlacements = options.fallbackPlacements,\n padding = options.padding,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n _options$flipVariatio = options.flipVariations,\n flipVariations = _options$flipVariatio === void 0 ? true : _options$flipVariatio,\n allowedAutoPlacements = options.allowedAutoPlacements;\n var preferredPlacement = state.options.placement;\n var basePlacement = getBasePlacement(preferredPlacement);\n var isBasePlacement = basePlacement === preferredPlacement;\n var fallbackPlacements = specifiedFallbackPlacements || (isBasePlacement || !flipVariations ? [getOppositePlacement(preferredPlacement)] : getExpandedFallbackPlacements(preferredPlacement));\n var placements = [preferredPlacement].concat(fallbackPlacements).reduce(function (acc, placement) {\n return acc.concat(getBasePlacement(placement) === auto ? computeAutoPlacement(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n flipVariations: flipVariations,\n allowedAutoPlacements: allowedAutoPlacements\n }) : placement);\n }, []);\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var checksMap = new Map();\n var makeFallbackChecks = true;\n var firstFittingPlacement = placements[0];\n\n for (var i = 0; i < placements.length; i++) {\n var placement = placements[i];\n\n var _basePlacement = getBasePlacement(placement);\n\n var isStartVariation = getVariation(placement) === start;\n var isVertical = [top, bottom].indexOf(_basePlacement) >= 0;\n var len = isVertical ? 'width' : 'height';\n var overflow = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n altBoundary: altBoundary,\n padding: padding\n });\n var mainVariationSide = isVertical ? isStartVariation ? right : left : isStartVariation ? bottom : top;\n\n if (referenceRect[len] > popperRect[len]) {\n mainVariationSide = getOppositePlacement(mainVariationSide);\n }\n\n var altVariationSide = getOppositePlacement(mainVariationSide);\n var checks = [];\n\n if (checkMainAxis) {\n checks.push(overflow[_basePlacement] <= 0);\n }\n\n if (checkAltAxis) {\n checks.push(overflow[mainVariationSide] <= 0, overflow[altVariationSide] <= 0);\n }\n\n if (checks.every(function (check) {\n return check;\n })) {\n firstFittingPlacement = placement;\n makeFallbackChecks = false;\n break;\n }\n\n checksMap.set(placement, checks);\n }\n\n if (makeFallbackChecks) {\n // `2` may be desired in some cases – research later\n var numberOfChecks = flipVariations ? 3 : 1;\n\n var _loop = function _loop(_i) {\n var fittingPlacement = placements.find(function (placement) {\n var checks = checksMap.get(placement);\n\n if (checks) {\n return checks.slice(0, _i).every(function (check) {\n return check;\n });\n }\n });\n\n if (fittingPlacement) {\n firstFittingPlacement = fittingPlacement;\n return \"break\";\n }\n };\n\n for (var _i = numberOfChecks; _i > 0; _i--) {\n var _ret = _loop(_i);\n\n if (_ret === \"break\") break;\n }\n }\n\n if (state.placement !== firstFittingPlacement) {\n state.modifiersData[name]._skip = true;\n state.placement = firstFittingPlacement;\n state.reset = true;\n }\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'flip',\n enabled: true,\n phase: 'main',\n fn: flip,\n requiresIfExists: ['offset'],\n data: {\n _skip: false\n }\n};","import getVariation from \"./getVariation.js\";\nimport { variationPlacements, basePlacements, placements as allPlacements } from \"../enums.js\";\nimport detectOverflow from \"./detectOverflow.js\";\nimport getBasePlacement from \"./getBasePlacement.js\";\nexport default function computeAutoPlacement(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n placement = _options.placement,\n boundary = _options.boundary,\n rootBoundary = _options.rootBoundary,\n padding = _options.padding,\n flipVariations = _options.flipVariations,\n _options$allowedAutoP = _options.allowedAutoPlacements,\n allowedAutoPlacements = _options$allowedAutoP === void 0 ? allPlacements : _options$allowedAutoP;\n var variation = getVariation(placement);\n var placements = variation ? flipVariations ? variationPlacements : variationPlacements.filter(function (placement) {\n return getVariation(placement) === variation;\n }) : basePlacements;\n var allowedPlacements = placements.filter(function (placement) {\n return allowedAutoPlacements.indexOf(placement) >= 0;\n });\n\n if (allowedPlacements.length === 0) {\n allowedPlacements = placements;\n } // $FlowFixMe[incompatible-type]: Flow seems to have problems with two array unions...\n\n\n var overflows = allowedPlacements.reduce(function (acc, placement) {\n acc[placement] = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding\n })[getBasePlacement(placement)];\n return acc;\n }, {});\n return Object.keys(overflows).sort(function (a, b) {\n return overflows[a] - overflows[b];\n });\n}","import { top, bottom, left, right } from \"../enums.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\n\nfunction getSideOffsets(overflow, rect, preventedOffsets) {\n if (preventedOffsets === void 0) {\n preventedOffsets = {\n x: 0,\n y: 0\n };\n }\n\n return {\n top: overflow.top - rect.height - preventedOffsets.y,\n right: overflow.right - rect.width + preventedOffsets.x,\n bottom: overflow.bottom - rect.height + preventedOffsets.y,\n left: overflow.left - rect.width - preventedOffsets.x\n };\n}\n\nfunction isAnySideFullyClipped(overflow) {\n return [top, right, bottom, left].some(function (side) {\n return overflow[side] >= 0;\n });\n}\n\nfunction hide(_ref) {\n var state = _ref.state,\n name = _ref.name;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var preventedOffsets = state.modifiersData.preventOverflow;\n var referenceOverflow = detectOverflow(state, {\n elementContext: 'reference'\n });\n var popperAltOverflow = detectOverflow(state, {\n altBoundary: true\n });\n var referenceClippingOffsets = getSideOffsets(referenceOverflow, referenceRect);\n var popperEscapeOffsets = getSideOffsets(popperAltOverflow, popperRect, preventedOffsets);\n var isReferenceHidden = isAnySideFullyClipped(referenceClippingOffsets);\n var hasPopperEscaped = isAnySideFullyClipped(popperEscapeOffsets);\n state.modifiersData[name] = {\n referenceClippingOffsets: referenceClippingOffsets,\n popperEscapeOffsets: popperEscapeOffsets,\n isReferenceHidden: isReferenceHidden,\n hasPopperEscaped: hasPopperEscaped\n };\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-reference-hidden': isReferenceHidden,\n 'data-popper-escaped': hasPopperEscaped\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'hide',\n enabled: true,\n phase: 'main',\n requiresIfExists: ['preventOverflow'],\n fn: hide\n};","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport { top, left, right, placements } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport function distanceAndSkiddingToXY(placement, rects, offset) {\n var basePlacement = getBasePlacement(placement);\n var invertDistance = [left, top].indexOf(basePlacement) >= 0 ? -1 : 1;\n\n var _ref = typeof offset === 'function' ? offset(Object.assign({}, rects, {\n placement: placement\n })) : offset,\n skidding = _ref[0],\n distance = _ref[1];\n\n skidding = skidding || 0;\n distance = (distance || 0) * invertDistance;\n return [left, right].indexOf(basePlacement) >= 0 ? {\n x: distance,\n y: skidding\n } : {\n x: skidding,\n y: distance\n };\n}\n\nfunction offset(_ref2) {\n var state = _ref2.state,\n options = _ref2.options,\n name = _ref2.name;\n var _options$offset = options.offset,\n offset = _options$offset === void 0 ? [0, 0] : _options$offset;\n var data = placements.reduce(function (acc, placement) {\n acc[placement] = distanceAndSkiddingToXY(placement, state.rects, offset);\n return acc;\n }, {});\n var _data$state$placement = data[state.placement],\n x = _data$state$placement.x,\n y = _data$state$placement.y;\n\n if (state.modifiersData.popperOffsets != null) {\n state.modifiersData.popperOffsets.x += x;\n state.modifiersData.popperOffsets.y += y;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'offset',\n enabled: true,\n phase: 'main',\n requires: ['popperOffsets'],\n fn: offset\n};","import computeOffsets from \"../utils/computeOffsets.js\";\n\nfunction popperOffsets(_ref) {\n var state = _ref.state,\n name = _ref.name;\n // Offsets are the actual position the popper needs to have to be\n // properly positioned near its reference element\n // This is the most basic placement, and will be adjusted by\n // the modifiers in the next step\n state.modifiersData[name] = computeOffsets({\n reference: state.rects.reference,\n element: state.rects.popper,\n strategy: 'absolute',\n placement: state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'popperOffsets',\n enabled: true,\n phase: 'read',\n fn: popperOffsets,\n data: {}\n};","import { top, left, right, bottom, start } from \"../enums.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport getAltAxis from \"../utils/getAltAxis.js\";\nimport { within, withinMaxClamp } from \"../utils/within.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport getFreshSideObject from \"../utils/getFreshSideObject.js\";\nimport { min as mathMin, max as mathMax } from \"../utils/math.js\";\n\nfunction preventOverflow(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? false : _options$altAxis,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n padding = options.padding,\n _options$tether = options.tether,\n tether = _options$tether === void 0 ? true : _options$tether,\n _options$tetherOffset = options.tetherOffset,\n tetherOffset = _options$tetherOffset === void 0 ? 0 : _options$tetherOffset;\n var overflow = detectOverflow(state, {\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n altBoundary: altBoundary\n });\n var basePlacement = getBasePlacement(state.placement);\n var variation = getVariation(state.placement);\n var isBasePlacement = !variation;\n var mainAxis = getMainAxisFromPlacement(basePlacement);\n var altAxis = getAltAxis(mainAxis);\n var popperOffsets = state.modifiersData.popperOffsets;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var tetherOffsetValue = typeof tetherOffset === 'function' ? tetherOffset(Object.assign({}, state.rects, {\n placement: state.placement\n })) : tetherOffset;\n var normalizedTetherOffsetValue = typeof tetherOffsetValue === 'number' ? {\n mainAxis: tetherOffsetValue,\n altAxis: tetherOffsetValue\n } : Object.assign({\n mainAxis: 0,\n altAxis: 0\n }, tetherOffsetValue);\n var offsetModifierState = state.modifiersData.offset ? state.modifiersData.offset[state.placement] : null;\n var data = {\n x: 0,\n y: 0\n };\n\n if (!popperOffsets) {\n return;\n }\n\n if (checkMainAxis) {\n var _offsetModifierState$;\n\n var mainSide = mainAxis === 'y' ? top : left;\n var altSide = mainAxis === 'y' ? bottom : right;\n var len = mainAxis === 'y' ? 'height' : 'width';\n var offset = popperOffsets[mainAxis];\n var min = offset + overflow[mainSide];\n var max = offset - overflow[altSide];\n var additive = tether ? -popperRect[len] / 2 : 0;\n var minLen = variation === start ? referenceRect[len] : popperRect[len];\n var maxLen = variation === start ? -popperRect[len] : -referenceRect[len]; // We need to include the arrow in the calculation so the arrow doesn't go\n // outside the reference bounds\n\n var arrowElement = state.elements.arrow;\n var arrowRect = tether && arrowElement ? getLayoutRect(arrowElement) : {\n width: 0,\n height: 0\n };\n var arrowPaddingObject = state.modifiersData['arrow#persistent'] ? state.modifiersData['arrow#persistent'].padding : getFreshSideObject();\n var arrowPaddingMin = arrowPaddingObject[mainSide];\n var arrowPaddingMax = arrowPaddingObject[altSide]; // If the reference length is smaller than the arrow length, we don't want\n // to include its full size in the calculation. If the reference is small\n // and near the edge of a boundary, the popper can overflow even if the\n // reference is not overflowing as well (e.g. virtual elements with no\n // width or height)\n\n var arrowLen = within(0, referenceRect[len], arrowRect[len]);\n var minOffset = isBasePlacement ? referenceRect[len] / 2 - additive - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis : minLen - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis;\n var maxOffset = isBasePlacement ? -referenceRect[len] / 2 + additive + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis : maxLen + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis;\n var arrowOffsetParent = state.elements.arrow && getOffsetParent(state.elements.arrow);\n var clientOffset = arrowOffsetParent ? mainAxis === 'y' ? arrowOffsetParent.clientTop || 0 : arrowOffsetParent.clientLeft || 0 : 0;\n var offsetModifierValue = (_offsetModifierState$ = offsetModifierState == null ? void 0 : offsetModifierState[mainAxis]) != null ? _offsetModifierState$ : 0;\n var tetherMin = offset + minOffset - offsetModifierValue - clientOffset;\n var tetherMax = offset + maxOffset - offsetModifierValue;\n var preventedOffset = within(tether ? mathMin(min, tetherMin) : min, offset, tether ? mathMax(max, tetherMax) : max);\n popperOffsets[mainAxis] = preventedOffset;\n data[mainAxis] = preventedOffset - offset;\n }\n\n if (checkAltAxis) {\n var _offsetModifierState$2;\n\n var _mainSide = mainAxis === 'x' ? top : left;\n\n var _altSide = mainAxis === 'x' ? bottom : right;\n\n var _offset = popperOffsets[altAxis];\n\n var _len = altAxis === 'y' ? 'height' : 'width';\n\n var _min = _offset + overflow[_mainSide];\n\n var _max = _offset - overflow[_altSide];\n\n var isOriginSide = [top, left].indexOf(basePlacement) !== -1;\n\n var _offsetModifierValue = (_offsetModifierState$2 = offsetModifierState == null ? void 0 : offsetModifierState[altAxis]) != null ? _offsetModifierState$2 : 0;\n\n var _tetherMin = isOriginSide ? _min : _offset - referenceRect[_len] - popperRect[_len] - _offsetModifierValue + normalizedTetherOffsetValue.altAxis;\n\n var _tetherMax = isOriginSide ? _offset + referenceRect[_len] + popperRect[_len] - _offsetModifierValue - normalizedTetherOffsetValue.altAxis : _max;\n\n var _preventedOffset = tether && isOriginSide ? withinMaxClamp(_tetherMin, _offset, _tetherMax) : within(tether ? _tetherMin : _min, _offset, tether ? _tetherMax : _max);\n\n popperOffsets[altAxis] = _preventedOffset;\n data[altAxis] = _preventedOffset - _offset;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'preventOverflow',\n enabled: true,\n phase: 'main',\n fn: preventOverflow,\n requiresIfExists: ['offset']\n};","export default function getAltAxis(axis) {\n return axis === 'x' ? 'y' : 'x';\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getNodeScroll from \"./getNodeScroll.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport { round } from \"../utils/math.js\";\n\nfunction isElementScaled(element) {\n var rect = element.getBoundingClientRect();\n var scaleX = round(rect.width) / element.offsetWidth || 1;\n var scaleY = round(rect.height) / element.offsetHeight || 1;\n return scaleX !== 1 || scaleY !== 1;\n} // Returns the composite rect of an element relative to its offsetParent.\n// Composite means it takes into account transforms as well as layout.\n\n\nexport default function getCompositeRect(elementOrVirtualElement, offsetParent, isFixed) {\n if (isFixed === void 0) {\n isFixed = false;\n }\n\n var isOffsetParentAnElement = isHTMLElement(offsetParent);\n var offsetParentIsScaled = isHTMLElement(offsetParent) && isElementScaled(offsetParent);\n var documentElement = getDocumentElement(offsetParent);\n var rect = getBoundingClientRect(elementOrVirtualElement, offsetParentIsScaled, isFixed);\n var scroll = {\n scrollLeft: 0,\n scrollTop: 0\n };\n var offsets = {\n x: 0,\n y: 0\n };\n\n if (isOffsetParentAnElement || !isOffsetParentAnElement && !isFixed) {\n if (getNodeName(offsetParent) !== 'body' || // https://github.com/popperjs/popper-core/issues/1078\n isScrollParent(documentElement)) {\n scroll = getNodeScroll(offsetParent);\n }\n\n if (isHTMLElement(offsetParent)) {\n offsets = getBoundingClientRect(offsetParent, true);\n offsets.x += offsetParent.clientLeft;\n offsets.y += offsetParent.clientTop;\n } else if (documentElement) {\n offsets.x = getWindowScrollBarX(documentElement);\n }\n }\n\n return {\n x: rect.left + scroll.scrollLeft - offsets.x,\n y: rect.top + scroll.scrollTop - offsets.y,\n width: rect.width,\n height: rect.height\n };\n}","import getWindowScroll from \"./getWindowScroll.js\";\nimport getWindow from \"./getWindow.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getHTMLElementScroll from \"./getHTMLElementScroll.js\";\nexport default function getNodeScroll(node) {\n if (node === getWindow(node) || !isHTMLElement(node)) {\n return getWindowScroll(node);\n } else {\n return getHTMLElementScroll(node);\n }\n}","export default function getHTMLElementScroll(element) {\n return {\n scrollLeft: element.scrollLeft,\n scrollTop: element.scrollTop\n };\n}","import { modifierPhases } from \"../enums.js\"; // source: https://stackoverflow.com/questions/49875255\n\nfunction order(modifiers) {\n var map = new Map();\n var visited = new Set();\n var result = [];\n modifiers.forEach(function (modifier) {\n map.set(modifier.name, modifier);\n }); // On visiting object, check for its dependencies and visit them recursively\n\n function sort(modifier) {\n visited.add(modifier.name);\n var requires = [].concat(modifier.requires || [], modifier.requiresIfExists || []);\n requires.forEach(function (dep) {\n if (!visited.has(dep)) {\n var depModifier = map.get(dep);\n\n if (depModifier) {\n sort(depModifier);\n }\n }\n });\n result.push(modifier);\n }\n\n modifiers.forEach(function (modifier) {\n if (!visited.has(modifier.name)) {\n // check for visited object\n sort(modifier);\n }\n });\n return result;\n}\n\nexport default function orderModifiers(modifiers) {\n // order based on dependencies\n var orderedModifiers = order(modifiers); // order based on phase\n\n return modifierPhases.reduce(function (acc, phase) {\n return acc.concat(orderedModifiers.filter(function (modifier) {\n return modifier.phase === phase;\n }));\n }, []);\n}","import getCompositeRect from \"./dom-utils/getCompositeRect.js\";\nimport getLayoutRect from \"./dom-utils/getLayoutRect.js\";\nimport listScrollParents from \"./dom-utils/listScrollParents.js\";\nimport getOffsetParent from \"./dom-utils/getOffsetParent.js\";\nimport orderModifiers from \"./utils/orderModifiers.js\";\nimport debounce from \"./utils/debounce.js\";\nimport mergeByName from \"./utils/mergeByName.js\";\nimport detectOverflow from \"./utils/detectOverflow.js\";\nimport { isElement } from \"./dom-utils/instanceOf.js\";\nvar DEFAULT_OPTIONS = {\n placement: 'bottom',\n modifiers: [],\n strategy: 'absolute'\n};\n\nfunction areValidElements() {\n for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {\n args[_key] = arguments[_key];\n }\n\n return !args.some(function (element) {\n return !(element && typeof element.getBoundingClientRect === 'function');\n });\n}\n\nexport function popperGenerator(generatorOptions) {\n if (generatorOptions === void 0) {\n generatorOptions = {};\n }\n\n var _generatorOptions = generatorOptions,\n _generatorOptions$def = _generatorOptions.defaultModifiers,\n defaultModifiers = _generatorOptions$def === void 0 ? [] : _generatorOptions$def,\n _generatorOptions$def2 = _generatorOptions.defaultOptions,\n defaultOptions = _generatorOptions$def2 === void 0 ? DEFAULT_OPTIONS : _generatorOptions$def2;\n return function createPopper(reference, popper, options) {\n if (options === void 0) {\n options = defaultOptions;\n }\n\n var state = {\n placement: 'bottom',\n orderedModifiers: [],\n options: Object.assign({}, DEFAULT_OPTIONS, defaultOptions),\n modifiersData: {},\n elements: {\n reference: reference,\n popper: popper\n },\n attributes: {},\n styles: {}\n };\n var effectCleanupFns = [];\n var isDestroyed = false;\n var instance = {\n state: state,\n setOptions: function setOptions(setOptionsAction) {\n var options = typeof setOptionsAction === 'function' ? setOptionsAction(state.options) : setOptionsAction;\n cleanupModifierEffects();\n state.options = Object.assign({}, defaultOptions, state.options, options);\n state.scrollParents = {\n reference: isElement(reference) ? listScrollParents(reference) : reference.contextElement ? listScrollParents(reference.contextElement) : [],\n popper: listScrollParents(popper)\n }; // Orders the modifiers based on their dependencies and `phase`\n // properties\n\n var orderedModifiers = orderModifiers(mergeByName([].concat(defaultModifiers, state.options.modifiers))); // Strip out disabled modifiers\n\n state.orderedModifiers = orderedModifiers.filter(function (m) {\n return m.enabled;\n });\n runModifierEffects();\n return instance.update();\n },\n // Sync update – it will always be executed, even if not necessary. This\n // is useful for low frequency updates where sync behavior simplifies the\n // logic.\n // For high frequency updates (e.g. `resize` and `scroll` events), always\n // prefer the async Popper#update method\n forceUpdate: function forceUpdate() {\n if (isDestroyed) {\n return;\n }\n\n var _state$elements = state.elements,\n reference = _state$elements.reference,\n popper = _state$elements.popper; // Don't proceed if `reference` or `popper` are not valid elements\n // anymore\n\n if (!areValidElements(reference, popper)) {\n return;\n } // Store the reference and popper rects to be read by modifiers\n\n\n state.rects = {\n reference: getCompositeRect(reference, getOffsetParent(popper), state.options.strategy === 'fixed'),\n popper: getLayoutRect(popper)\n }; // Modifiers have the ability to reset the current update cycle. The\n // most common use case for this is the `flip` modifier changing the\n // placement, which then needs to re-run all the modifiers, because the\n // logic was previously ran for the previous placement and is therefore\n // stale/incorrect\n\n state.reset = false;\n state.placement = state.options.placement; // On each update cycle, the `modifiersData` property for each modifier\n // is filled with the initial data specified by the modifier. This means\n // it doesn't persist and is fresh on each update.\n // To ensure persistent data, use `${name}#persistent`\n\n state.orderedModifiers.forEach(function (modifier) {\n return state.modifiersData[modifier.name] = Object.assign({}, modifier.data);\n });\n\n for (var index = 0; index < state.orderedModifiers.length; index++) {\n if (state.reset === true) {\n state.reset = false;\n index = -1;\n continue;\n }\n\n var _state$orderedModifie = state.orderedModifiers[index],\n fn = _state$orderedModifie.fn,\n _state$orderedModifie2 = _state$orderedModifie.options,\n _options = _state$orderedModifie2 === void 0 ? {} : _state$orderedModifie2,\n name = _state$orderedModifie.name;\n\n if (typeof fn === 'function') {\n state = fn({\n state: state,\n options: _options,\n name: name,\n instance: instance\n }) || state;\n }\n }\n },\n // Async and optimistically optimized update – it will not be executed if\n // not necessary (debounced to run at most once-per-tick)\n update: debounce(function () {\n return new Promise(function (resolve) {\n instance.forceUpdate();\n resolve(state);\n });\n }),\n destroy: function destroy() {\n cleanupModifierEffects();\n isDestroyed = true;\n }\n };\n\n if (!areValidElements(reference, popper)) {\n return instance;\n }\n\n instance.setOptions(options).then(function (state) {\n if (!isDestroyed && options.onFirstUpdate) {\n options.onFirstUpdate(state);\n }\n }); // Modifiers have the ability to execute arbitrary code before the first\n // update cycle runs. They will be executed in the same order as the update\n // cycle. This is useful when a modifier adds some persistent data that\n // other modifiers need to use, but the modifier is run after the dependent\n // one.\n\n function runModifierEffects() {\n state.orderedModifiers.forEach(function (_ref) {\n var name = _ref.name,\n _ref$options = _ref.options,\n options = _ref$options === void 0 ? {} : _ref$options,\n effect = _ref.effect;\n\n if (typeof effect === 'function') {\n var cleanupFn = effect({\n state: state,\n name: name,\n instance: instance,\n options: options\n });\n\n var noopFn = function noopFn() {};\n\n effectCleanupFns.push(cleanupFn || noopFn);\n }\n });\n }\n\n function cleanupModifierEffects() {\n effectCleanupFns.forEach(function (fn) {\n return fn();\n });\n effectCleanupFns = [];\n }\n\n return instance;\n };\n}\nexport var createPopper = /*#__PURE__*/popperGenerator(); // eslint-disable-next-line import/no-unused-modules\n\nexport { detectOverflow };","export default function debounce(fn) {\n var pending;\n return function () {\n if (!pending) {\n pending = new Promise(function (resolve) {\n Promise.resolve().then(function () {\n pending = undefined;\n resolve(fn());\n });\n });\n }\n\n return pending;\n };\n}","export default function mergeByName(modifiers) {\n var merged = modifiers.reduce(function (merged, current) {\n var existing = merged[current.name];\n merged[current.name] = existing ? Object.assign({}, existing, current, {\n options: Object.assign({}, existing.options, current.options),\n data: Object.assign({}, existing.data, current.data)\n }) : current;\n return merged;\n }, {}); // IE11 does not support Object.values\n\n return Object.keys(merged).map(function (key) {\n return merged[key];\n });\n}","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nimport offset from \"./modifiers/offset.js\";\nimport flip from \"./modifiers/flip.js\";\nimport preventOverflow from \"./modifiers/preventOverflow.js\";\nimport arrow from \"./modifiers/arrow.js\";\nimport hide from \"./modifiers/hide.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles, offset, flip, preventOverflow, arrow, hide];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow }; // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper as createPopperLite } from \"./popper-lite.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport * from \"./modifiers/index.js\";","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow };","/*!\n * Bootstrap v5.3.2 (https://getbootstrap.com/)\n * Copyright 2011-2023 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n */\nimport * as Popper from '@popperjs/core';\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/data.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n/**\n * Constants\n */\n\nconst elementMap = new Map();\nconst Data = {\n set(element, key, instance) {\n if (!elementMap.has(element)) {\n elementMap.set(element, new Map());\n }\n const instanceMap = elementMap.get(element);\n\n // make it clear we only want one instance per element\n // can be removed later when multiple key/instances are fine to be used\n if (!instanceMap.has(key) && instanceMap.size !== 0) {\n // eslint-disable-next-line no-console\n console.error(`Bootstrap doesn't allow more than one instance per element. Bound instance: ${Array.from(instanceMap.keys())[0]}.`);\n return;\n }\n instanceMap.set(key, instance);\n },\n get(element, key) {\n if (elementMap.has(element)) {\n return elementMap.get(element).get(key) || null;\n }\n return null;\n },\n remove(element, key) {\n if (!elementMap.has(element)) {\n return;\n }\n const instanceMap = elementMap.get(element);\n instanceMap.delete(key);\n\n // free up element references if there are no instances left for an element\n if (instanceMap.size === 0) {\n elementMap.delete(element);\n }\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/index.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst MAX_UID = 1000000;\nconst MILLISECONDS_MULTIPLIER = 1000;\nconst TRANSITION_END = 'transitionend';\n\n/**\n * Properly escape IDs selectors to handle weird IDs\n * @param {string} selector\n * @returns {string}\n */\nconst parseSelector = selector => {\n if (selector && window.CSS && window.CSS.escape) {\n // document.querySelector needs escaping to handle IDs (html5+) containing for instance /\n selector = selector.replace(/#([^\\s\"#']+)/g, (match, id) => `#${CSS.escape(id)}`);\n }\n return selector;\n};\n\n// Shout-out Angus Croll (https://goo.gl/pxwQGp)\nconst toType = object => {\n if (object === null || object === undefined) {\n return `${object}`;\n }\n return Object.prototype.toString.call(object).match(/\\s([a-z]+)/i)[1].toLowerCase();\n};\n\n/**\n * Public Util API\n */\n\nconst getUID = prefix => {\n do {\n prefix += Math.floor(Math.random() * MAX_UID);\n } while (document.getElementById(prefix));\n return prefix;\n};\nconst getTransitionDurationFromElement = element => {\n if (!element) {\n return 0;\n }\n\n // Get transition-duration of the element\n let {\n transitionDuration,\n transitionDelay\n } = window.getComputedStyle(element);\n const floatTransitionDuration = Number.parseFloat(transitionDuration);\n const floatTransitionDelay = Number.parseFloat(transitionDelay);\n\n // Return 0 if element or transition duration is not found\n if (!floatTransitionDuration && !floatTransitionDelay) {\n return 0;\n }\n\n // If multiple durations are defined, take the first\n transitionDuration = transitionDuration.split(',')[0];\n transitionDelay = transitionDelay.split(',')[0];\n return (Number.parseFloat(transitionDuration) + Number.parseFloat(transitionDelay)) * MILLISECONDS_MULTIPLIER;\n};\nconst triggerTransitionEnd = element => {\n element.dispatchEvent(new Event(TRANSITION_END));\n};\nconst isElement = object => {\n if (!object || typeof object !== 'object') {\n return false;\n }\n if (typeof object.jquery !== 'undefined') {\n object = object[0];\n }\n return typeof object.nodeType !== 'undefined';\n};\nconst getElement = object => {\n // it's a jQuery object or a node element\n if (isElement(object)) {\n return object.jquery ? object[0] : object;\n }\n if (typeof object === 'string' && object.length > 0) {\n return document.querySelector(parseSelector(object));\n }\n return null;\n};\nconst isVisible = element => {\n if (!isElement(element) || element.getClientRects().length === 0) {\n return false;\n }\n const elementIsVisible = getComputedStyle(element).getPropertyValue('visibility') === 'visible';\n // Handle `details` element as its content may falsie appear visible when it is closed\n const closedDetails = element.closest('details:not([open])');\n if (!closedDetails) {\n return elementIsVisible;\n }\n if (closedDetails !== element) {\n const summary = element.closest('summary');\n if (summary && summary.parentNode !== closedDetails) {\n return false;\n }\n if (summary === null) {\n return false;\n }\n }\n return elementIsVisible;\n};\nconst isDisabled = element => {\n if (!element || element.nodeType !== Node.ELEMENT_NODE) {\n return true;\n }\n if (element.classList.contains('disabled')) {\n return true;\n }\n if (typeof element.disabled !== 'undefined') {\n return element.disabled;\n }\n return element.hasAttribute('disabled') && element.getAttribute('disabled') !== 'false';\n};\nconst findShadowRoot = element => {\n if (!document.documentElement.attachShadow) {\n return null;\n }\n\n // Can find the shadow root otherwise it'll return the document\n if (typeof element.getRootNode === 'function') {\n const root = element.getRootNode();\n return root instanceof ShadowRoot ? root : null;\n }\n if (element instanceof ShadowRoot) {\n return element;\n }\n\n // when we don't find a shadow root\n if (!element.parentNode) {\n return null;\n }\n return findShadowRoot(element.parentNode);\n};\nconst noop = () => {};\n\n/**\n * Trick to restart an element's animation\n *\n * @param {HTMLElement} element\n * @return void\n *\n * @see https://www.charistheo.io/blog/2021/02/restart-a-css-animation-with-javascript/#restarting-a-css-animation\n */\nconst reflow = element => {\n element.offsetHeight; // eslint-disable-line no-unused-expressions\n};\n\nconst getjQuery = () => {\n if (window.jQuery && !document.body.hasAttribute('data-bs-no-jquery')) {\n return window.jQuery;\n }\n return null;\n};\nconst DOMContentLoadedCallbacks = [];\nconst onDOMContentLoaded = callback => {\n if (document.readyState === 'loading') {\n // add listener on the first call when the document is in loading state\n if (!DOMContentLoadedCallbacks.length) {\n document.addEventListener('DOMContentLoaded', () => {\n for (const callback of DOMContentLoadedCallbacks) {\n callback();\n }\n });\n }\n DOMContentLoadedCallbacks.push(callback);\n } else {\n callback();\n }\n};\nconst isRTL = () => document.documentElement.dir === 'rtl';\nconst defineJQueryPlugin = plugin => {\n onDOMContentLoaded(() => {\n const $ = getjQuery();\n /* istanbul ignore if */\n if ($) {\n const name = plugin.NAME;\n const JQUERY_NO_CONFLICT = $.fn[name];\n $.fn[name] = plugin.jQueryInterface;\n $.fn[name].Constructor = plugin;\n $.fn[name].noConflict = () => {\n $.fn[name] = JQUERY_NO_CONFLICT;\n return plugin.jQueryInterface;\n };\n }\n });\n};\nconst execute = (possibleCallback, args = [], defaultValue = possibleCallback) => {\n return typeof possibleCallback === 'function' ? possibleCallback(...args) : defaultValue;\n};\nconst executeAfterTransition = (callback, transitionElement, waitForTransition = true) => {\n if (!waitForTransition) {\n execute(callback);\n return;\n }\n const durationPadding = 5;\n const emulatedDuration = getTransitionDurationFromElement(transitionElement) + durationPadding;\n let called = false;\n const handler = ({\n target\n }) => {\n if (target !== transitionElement) {\n return;\n }\n called = true;\n transitionElement.removeEventListener(TRANSITION_END, handler);\n execute(callback);\n };\n transitionElement.addEventListener(TRANSITION_END, handler);\n setTimeout(() => {\n if (!called) {\n triggerTransitionEnd(transitionElement);\n }\n }, emulatedDuration);\n};\n\n/**\n * Return the previous/next element of a list.\n *\n * @param {array} list The list of elements\n * @param activeElement The active element\n * @param shouldGetNext Choose to get next or previous element\n * @param isCycleAllowed\n * @return {Element|elem} The proper element\n */\nconst getNextActiveElement = (list, activeElement, shouldGetNext, isCycleAllowed) => {\n const listLength = list.length;\n let index = list.indexOf(activeElement);\n\n // if the element does not exist in the list return an element\n // depending on the direction and if cycle is allowed\n if (index === -1) {\n return !shouldGetNext && isCycleAllowed ? list[listLength - 1] : list[0];\n }\n index += shouldGetNext ? 1 : -1;\n if (isCycleAllowed) {\n index = (index + listLength) % listLength;\n }\n return list[Math.max(0, Math.min(index, listLength - 1))];\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/event-handler.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst namespaceRegex = /[^.]*(?=\\..*)\\.|.*/;\nconst stripNameRegex = /\\..*/;\nconst stripUidRegex = /::\\d+$/;\nconst eventRegistry = {}; // Events storage\nlet uidEvent = 1;\nconst customEvents = {\n mouseenter: 'mouseover',\n mouseleave: 'mouseout'\n};\nconst nativeEvents = new Set(['click', 'dblclick', 'mouseup', 'mousedown', 'contextmenu', 'mousewheel', 'DOMMouseScroll', 'mouseover', 'mouseout', 'mousemove', 'selectstart', 'selectend', 'keydown', 'keypress', 'keyup', 'orientationchange', 'touchstart', 'touchmove', 'touchend', 'touchcancel', 'pointerdown', 'pointermove', 'pointerup', 'pointerleave', 'pointercancel', 'gesturestart', 'gesturechange', 'gestureend', 'focus', 'blur', 'change', 'reset', 'select', 'submit', 'focusin', 'focusout', 'load', 'unload', 'beforeunload', 'resize', 'move', 'DOMContentLoaded', 'readystatechange', 'error', 'abort', 'scroll']);\n\n/**\n * Private methods\n */\n\nfunction makeEventUid(element, uid) {\n return uid && `${uid}::${uidEvent++}` || element.uidEvent || uidEvent++;\n}\nfunction getElementEvents(element) {\n const uid = makeEventUid(element);\n element.uidEvent = uid;\n eventRegistry[uid] = eventRegistry[uid] || {};\n return eventRegistry[uid];\n}\nfunction bootstrapHandler(element, fn) {\n return function handler(event) {\n hydrateObj(event, {\n delegateTarget: element\n });\n if (handler.oneOff) {\n EventHandler.off(element, event.type, fn);\n }\n return fn.apply(element, [event]);\n };\n}\nfunction bootstrapDelegationHandler(element, selector, fn) {\n return function handler(event) {\n const domElements = element.querySelectorAll(selector);\n for (let {\n target\n } = event; target && target !== this; target = target.parentNode) {\n for (const domElement of domElements) {\n if (domElement !== target) {\n continue;\n }\n hydrateObj(event, {\n delegateTarget: target\n });\n if (handler.oneOff) {\n EventHandler.off(element, event.type, selector, fn);\n }\n return fn.apply(target, [event]);\n }\n }\n };\n}\nfunction findHandler(events, callable, delegationSelector = null) {\n return Object.values(events).find(event => event.callable === callable && event.delegationSelector === delegationSelector);\n}\nfunction normalizeParameters(originalTypeEvent, handler, delegationFunction) {\n const isDelegated = typeof handler === 'string';\n // TODO: tooltip passes `false` instead of selector, so we need to check\n const callable = isDelegated ? delegationFunction : handler || delegationFunction;\n let typeEvent = getTypeEvent(originalTypeEvent);\n if (!nativeEvents.has(typeEvent)) {\n typeEvent = originalTypeEvent;\n }\n return [isDelegated, callable, typeEvent];\n}\nfunction addHandler(element, originalTypeEvent, handler, delegationFunction, oneOff) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return;\n }\n let [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n\n // in case of mouseenter or mouseleave wrap the handler within a function that checks for its DOM position\n // this prevents the handler from being dispatched the same way as mouseover or mouseout does\n if (originalTypeEvent in customEvents) {\n const wrapFunction = fn => {\n return function (event) {\n if (!event.relatedTarget || event.relatedTarget !== event.delegateTarget && !event.delegateTarget.contains(event.relatedTarget)) {\n return fn.call(this, event);\n }\n };\n };\n callable = wrapFunction(callable);\n }\n const events = getElementEvents(element);\n const handlers = events[typeEvent] || (events[typeEvent] = {});\n const previousFunction = findHandler(handlers, callable, isDelegated ? handler : null);\n if (previousFunction) {\n previousFunction.oneOff = previousFunction.oneOff && oneOff;\n return;\n }\n const uid = makeEventUid(callable, originalTypeEvent.replace(namespaceRegex, ''));\n const fn = isDelegated ? bootstrapDelegationHandler(element, handler, callable) : bootstrapHandler(element, callable);\n fn.delegationSelector = isDelegated ? handler : null;\n fn.callable = callable;\n fn.oneOff = oneOff;\n fn.uidEvent = uid;\n handlers[uid] = fn;\n element.addEventListener(typeEvent, fn, isDelegated);\n}\nfunction removeHandler(element, events, typeEvent, handler, delegationSelector) {\n const fn = findHandler(events[typeEvent], handler, delegationSelector);\n if (!fn) {\n return;\n }\n element.removeEventListener(typeEvent, fn, Boolean(delegationSelector));\n delete events[typeEvent][fn.uidEvent];\n}\nfunction removeNamespacedHandlers(element, events, typeEvent, namespace) {\n const storeElementEvent = events[typeEvent] || {};\n for (const [handlerKey, event] of Object.entries(storeElementEvent)) {\n if (handlerKey.includes(namespace)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n }\n }\n}\nfunction getTypeEvent(event) {\n // allow to get the native events from namespaced events ('click.bs.button' --> 'click')\n event = event.replace(stripNameRegex, '');\n return customEvents[event] || event;\n}\nconst EventHandler = {\n on(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, false);\n },\n one(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, true);\n },\n off(element, originalTypeEvent, handler, delegationFunction) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return;\n }\n const [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n const inNamespace = typeEvent !== originalTypeEvent;\n const events = getElementEvents(element);\n const storeElementEvent = events[typeEvent] || {};\n const isNamespace = originalTypeEvent.startsWith('.');\n if (typeof callable !== 'undefined') {\n // Simplest case: handler is passed, remove that listener ONLY.\n if (!Object.keys(storeElementEvent).length) {\n return;\n }\n removeHandler(element, events, typeEvent, callable, isDelegated ? handler : null);\n return;\n }\n if (isNamespace) {\n for (const elementEvent of Object.keys(events)) {\n removeNamespacedHandlers(element, events, elementEvent, originalTypeEvent.slice(1));\n }\n }\n for (const [keyHandlers, event] of Object.entries(storeElementEvent)) {\n const handlerKey = keyHandlers.replace(stripUidRegex, '');\n if (!inNamespace || originalTypeEvent.includes(handlerKey)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n }\n }\n },\n trigger(element, event, args) {\n if (typeof event !== 'string' || !element) {\n return null;\n }\n const $ = getjQuery();\n const typeEvent = getTypeEvent(event);\n const inNamespace = event !== typeEvent;\n let jQueryEvent = null;\n let bubbles = true;\n let nativeDispatch = true;\n let defaultPrevented = false;\n if (inNamespace && $) {\n jQueryEvent = $.Event(event, args);\n $(element).trigger(jQueryEvent);\n bubbles = !jQueryEvent.isPropagationStopped();\n nativeDispatch = !jQueryEvent.isImmediatePropagationStopped();\n defaultPrevented = jQueryEvent.isDefaultPrevented();\n }\n const evt = hydrateObj(new Event(event, {\n bubbles,\n cancelable: true\n }), args);\n if (defaultPrevented) {\n evt.preventDefault();\n }\n if (nativeDispatch) {\n element.dispatchEvent(evt);\n }\n if (evt.defaultPrevented && jQueryEvent) {\n jQueryEvent.preventDefault();\n }\n return evt;\n }\n};\nfunction hydrateObj(obj, meta = {}) {\n for (const [key, value] of Object.entries(meta)) {\n try {\n obj[key] = value;\n } catch (_unused) {\n Object.defineProperty(obj, key, {\n configurable: true,\n get() {\n return value;\n }\n });\n }\n }\n return obj;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/manipulator.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nfunction normalizeData(value) {\n if (value === 'true') {\n return true;\n }\n if (value === 'false') {\n return false;\n }\n if (value === Number(value).toString()) {\n return Number(value);\n }\n if (value === '' || value === 'null') {\n return null;\n }\n if (typeof value !== 'string') {\n return value;\n }\n try {\n return JSON.parse(decodeURIComponent(value));\n } catch (_unused) {\n return value;\n }\n}\nfunction normalizeDataKey(key) {\n return key.replace(/[A-Z]/g, chr => `-${chr.toLowerCase()}`);\n}\nconst Manipulator = {\n setDataAttribute(element, key, value) {\n element.setAttribute(`data-bs-${normalizeDataKey(key)}`, value);\n },\n removeDataAttribute(element, key) {\n element.removeAttribute(`data-bs-${normalizeDataKey(key)}`);\n },\n getDataAttributes(element) {\n if (!element) {\n return {};\n }\n const attributes = {};\n const bsKeys = Object.keys(element.dataset).filter(key => key.startsWith('bs') && !key.startsWith('bsConfig'));\n for (const key of bsKeys) {\n let pureKey = key.replace(/^bs/, '');\n pureKey = pureKey.charAt(0).toLowerCase() + pureKey.slice(1, pureKey.length);\n attributes[pureKey] = normalizeData(element.dataset[key]);\n }\n return attributes;\n },\n getDataAttribute(element, key) {\n return normalizeData(element.getAttribute(`data-bs-${normalizeDataKey(key)}`));\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/config.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Class definition\n */\n\nclass Config {\n // Getters\n static get Default() {\n return {};\n }\n static get DefaultType() {\n return {};\n }\n static get NAME() {\n throw new Error('You have to implement the static method \"NAME\", for each component!');\n }\n _getConfig(config) {\n config = this._mergeConfigObj(config);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n _configAfterMerge(config) {\n return config;\n }\n _mergeConfigObj(config, element) {\n const jsonConfig = isElement(element) ? Manipulator.getDataAttribute(element, 'config') : {}; // try to parse\n\n return {\n ...this.constructor.Default,\n ...(typeof jsonConfig === 'object' ? jsonConfig : {}),\n ...(isElement(element) ? Manipulator.getDataAttributes(element) : {}),\n ...(typeof config === 'object' ? config : {})\n };\n }\n _typeCheckConfig(config, configTypes = this.constructor.DefaultType) {\n for (const [property, expectedTypes] of Object.entries(configTypes)) {\n const value = config[property];\n const valueType = isElement(value) ? 'element' : toType(value);\n if (!new RegExp(expectedTypes).test(valueType)) {\n throw new TypeError(`${this.constructor.NAME.toUpperCase()}: Option \"${property}\" provided type \"${valueType}\" but expected type \"${expectedTypes}\".`);\n }\n }\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap base-component.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst VERSION = '5.3.2';\n\n/**\n * Class definition\n */\n\nclass BaseComponent extends Config {\n constructor(element, config) {\n super();\n element = getElement(element);\n if (!element) {\n return;\n }\n this._element = element;\n this._config = this._getConfig(config);\n Data.set(this._element, this.constructor.DATA_KEY, this);\n }\n\n // Public\n dispose() {\n Data.remove(this._element, this.constructor.DATA_KEY);\n EventHandler.off(this._element, this.constructor.EVENT_KEY);\n for (const propertyName of Object.getOwnPropertyNames(this)) {\n this[propertyName] = null;\n }\n }\n _queueCallback(callback, element, isAnimated = true) {\n executeAfterTransition(callback, element, isAnimated);\n }\n _getConfig(config) {\n config = this._mergeConfigObj(config, this._element);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n\n // Static\n static getInstance(element) {\n return Data.get(getElement(element), this.DATA_KEY);\n }\n static getOrCreateInstance(element, config = {}) {\n return this.getInstance(element) || new this(element, typeof config === 'object' ? config : null);\n }\n static get VERSION() {\n return VERSION;\n }\n static get DATA_KEY() {\n return `bs.${this.NAME}`;\n }\n static get EVENT_KEY() {\n return `.${this.DATA_KEY}`;\n }\n static eventName(name) {\n return `${name}${this.EVENT_KEY}`;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/selector-engine.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst getSelector = element => {\n let selector = element.getAttribute('data-bs-target');\n if (!selector || selector === '#') {\n let hrefAttribute = element.getAttribute('href');\n\n // The only valid content that could double as a selector are IDs or classes,\n // so everything starting with `#` or `.`. If a \"real\" URL is used as the selector,\n // `document.querySelector` will rightfully complain it is invalid.\n // See https://github.com/twbs/bootstrap/issues/32273\n if (!hrefAttribute || !hrefAttribute.includes('#') && !hrefAttribute.startsWith('.')) {\n return null;\n }\n\n // Just in case some CMS puts out a full URL with the anchor appended\n if (hrefAttribute.includes('#') && !hrefAttribute.startsWith('#')) {\n hrefAttribute = `#${hrefAttribute.split('#')[1]}`;\n }\n selector = hrefAttribute && hrefAttribute !== '#' ? parseSelector(hrefAttribute.trim()) : null;\n }\n return selector;\n};\nconst SelectorEngine = {\n find(selector, element = document.documentElement) {\n return [].concat(...Element.prototype.querySelectorAll.call(element, selector));\n },\n findOne(selector, element = document.documentElement) {\n return Element.prototype.querySelector.call(element, selector);\n },\n children(element, selector) {\n return [].concat(...element.children).filter(child => child.matches(selector));\n },\n parents(element, selector) {\n const parents = [];\n let ancestor = element.parentNode.closest(selector);\n while (ancestor) {\n parents.push(ancestor);\n ancestor = ancestor.parentNode.closest(selector);\n }\n return parents;\n },\n prev(element, selector) {\n let previous = element.previousElementSibling;\n while (previous) {\n if (previous.matches(selector)) {\n return [previous];\n }\n previous = previous.previousElementSibling;\n }\n return [];\n },\n // TODO: this is now unused; remove later along with prev()\n next(element, selector) {\n let next = element.nextElementSibling;\n while (next) {\n if (next.matches(selector)) {\n return [next];\n }\n next = next.nextElementSibling;\n }\n return [];\n },\n focusableChildren(element) {\n const focusables = ['a', 'button', 'input', 'textarea', 'select', 'details', '[tabindex]', '[contenteditable=\"true\"]'].map(selector => `${selector}:not([tabindex^=\"-\"])`).join(',');\n return this.find(focusables, element).filter(el => !isDisabled(el) && isVisible(el));\n },\n getSelectorFromElement(element) {\n const selector = getSelector(element);\n if (selector) {\n return SelectorEngine.findOne(selector) ? selector : null;\n }\n return null;\n },\n getElementFromSelector(element) {\n const selector = getSelector(element);\n return selector ? SelectorEngine.findOne(selector) : null;\n },\n getMultipleElementsFromSelector(element) {\n const selector = getSelector(element);\n return selector ? SelectorEngine.find(selector) : [];\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/component-functions.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst enableDismissTrigger = (component, method = 'hide') => {\n const clickEvent = `click.dismiss${component.EVENT_KEY}`;\n const name = component.NAME;\n EventHandler.on(document, clickEvent, `[data-bs-dismiss=\"${name}\"]`, function (event) {\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n if (isDisabled(this)) {\n return;\n }\n const target = SelectorEngine.getElementFromSelector(this) || this.closest(`.${name}`);\n const instance = component.getOrCreateInstance(target);\n\n // Method argument is left, for Alert and only, as it doesn't implement the 'hide' method\n instance[method]();\n });\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap alert.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$f = 'alert';\nconst DATA_KEY$a = 'bs.alert';\nconst EVENT_KEY$b = `.${DATA_KEY$a}`;\nconst EVENT_CLOSE = `close${EVENT_KEY$b}`;\nconst EVENT_CLOSED = `closed${EVENT_KEY$b}`;\nconst CLASS_NAME_FADE$5 = 'fade';\nconst CLASS_NAME_SHOW$8 = 'show';\n\n/**\n * Class definition\n */\n\nclass Alert extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME$f;\n }\n\n // Public\n close() {\n const closeEvent = EventHandler.trigger(this._element, EVENT_CLOSE);\n if (closeEvent.defaultPrevented) {\n return;\n }\n this._element.classList.remove(CLASS_NAME_SHOW$8);\n const isAnimated = this._element.classList.contains(CLASS_NAME_FADE$5);\n this._queueCallback(() => this._destroyElement(), this._element, isAnimated);\n }\n\n // Private\n _destroyElement() {\n this._element.remove();\n EventHandler.trigger(this._element, EVENT_CLOSED);\n this.dispose();\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Alert.getOrCreateInstance(this);\n if (typeof config !== 'string') {\n return;\n }\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](this);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nenableDismissTrigger(Alert, 'close');\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Alert);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap button.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$e = 'button';\nconst DATA_KEY$9 = 'bs.button';\nconst EVENT_KEY$a = `.${DATA_KEY$9}`;\nconst DATA_API_KEY$6 = '.data-api';\nconst CLASS_NAME_ACTIVE$3 = 'active';\nconst SELECTOR_DATA_TOGGLE$5 = '[data-bs-toggle=\"button\"]';\nconst EVENT_CLICK_DATA_API$6 = `click${EVENT_KEY$a}${DATA_API_KEY$6}`;\n\n/**\n * Class definition\n */\n\nclass Button extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME$e;\n }\n\n // Public\n toggle() {\n // Toggle class and sync the `aria-pressed` attribute with the return value of the `.toggle()` method\n this._element.setAttribute('aria-pressed', this._element.classList.toggle(CLASS_NAME_ACTIVE$3));\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Button.getOrCreateInstance(this);\n if (config === 'toggle') {\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$6, SELECTOR_DATA_TOGGLE$5, event => {\n event.preventDefault();\n const button = event.target.closest(SELECTOR_DATA_TOGGLE$5);\n const data = Button.getOrCreateInstance(button);\n data.toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Button);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/swipe.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$d = 'swipe';\nconst EVENT_KEY$9 = '.bs.swipe';\nconst EVENT_TOUCHSTART = `touchstart${EVENT_KEY$9}`;\nconst EVENT_TOUCHMOVE = `touchmove${EVENT_KEY$9}`;\nconst EVENT_TOUCHEND = `touchend${EVENT_KEY$9}`;\nconst EVENT_POINTERDOWN = `pointerdown${EVENT_KEY$9}`;\nconst EVENT_POINTERUP = `pointerup${EVENT_KEY$9}`;\nconst POINTER_TYPE_TOUCH = 'touch';\nconst POINTER_TYPE_PEN = 'pen';\nconst CLASS_NAME_POINTER_EVENT = 'pointer-event';\nconst SWIPE_THRESHOLD = 40;\nconst Default$c = {\n endCallback: null,\n leftCallback: null,\n rightCallback: null\n};\nconst DefaultType$c = {\n endCallback: '(function|null)',\n leftCallback: '(function|null)',\n rightCallback: '(function|null)'\n};\n\n/**\n * Class definition\n */\n\nclass Swipe extends Config {\n constructor(element, config) {\n super();\n this._element = element;\n if (!element || !Swipe.isSupported()) {\n return;\n }\n this._config = this._getConfig(config);\n this._deltaX = 0;\n this._supportPointerEvents = Boolean(window.PointerEvent);\n this._initEvents();\n }\n\n // Getters\n static get Default() {\n return Default$c;\n }\n static get DefaultType() {\n return DefaultType$c;\n }\n static get NAME() {\n return NAME$d;\n }\n\n // Public\n dispose() {\n EventHandler.off(this._element, EVENT_KEY$9);\n }\n\n // Private\n _start(event) {\n if (!this._supportPointerEvents) {\n this._deltaX = event.touches[0].clientX;\n return;\n }\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX;\n }\n }\n _end(event) {\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX - this._deltaX;\n }\n this._handleSwipe();\n execute(this._config.endCallback);\n }\n _move(event) {\n this._deltaX = event.touches && event.touches.length > 1 ? 0 : event.touches[0].clientX - this._deltaX;\n }\n _handleSwipe() {\n const absDeltaX = Math.abs(this._deltaX);\n if (absDeltaX <= SWIPE_THRESHOLD) {\n return;\n }\n const direction = absDeltaX / this._deltaX;\n this._deltaX = 0;\n if (!direction) {\n return;\n }\n execute(direction > 0 ? this._config.rightCallback : this._config.leftCallback);\n }\n _initEvents() {\n if (this._supportPointerEvents) {\n EventHandler.on(this._element, EVENT_POINTERDOWN, event => this._start(event));\n EventHandler.on(this._element, EVENT_POINTERUP, event => this._end(event));\n this._element.classList.add(CLASS_NAME_POINTER_EVENT);\n } else {\n EventHandler.on(this._element, EVENT_TOUCHSTART, event => this._start(event));\n EventHandler.on(this._element, EVENT_TOUCHMOVE, event => this._move(event));\n EventHandler.on(this._element, EVENT_TOUCHEND, event => this._end(event));\n }\n }\n _eventIsPointerPenTouch(event) {\n return this._supportPointerEvents && (event.pointerType === POINTER_TYPE_PEN || event.pointerType === POINTER_TYPE_TOUCH);\n }\n\n // Static\n static isSupported() {\n return 'ontouchstart' in document.documentElement || navigator.maxTouchPoints > 0;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap carousel.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$c = 'carousel';\nconst DATA_KEY$8 = 'bs.carousel';\nconst EVENT_KEY$8 = `.${DATA_KEY$8}`;\nconst DATA_API_KEY$5 = '.data-api';\nconst ARROW_LEFT_KEY$1 = 'ArrowLeft';\nconst ARROW_RIGHT_KEY$1 = 'ArrowRight';\nconst TOUCHEVENT_COMPAT_WAIT = 500; // Time for mouse compat events to fire after touch\n\nconst ORDER_NEXT = 'next';\nconst ORDER_PREV = 'prev';\nconst DIRECTION_LEFT = 'left';\nconst DIRECTION_RIGHT = 'right';\nconst EVENT_SLIDE = `slide${EVENT_KEY$8}`;\nconst EVENT_SLID = `slid${EVENT_KEY$8}`;\nconst EVENT_KEYDOWN$1 = `keydown${EVENT_KEY$8}`;\nconst EVENT_MOUSEENTER$1 = `mouseenter${EVENT_KEY$8}`;\nconst EVENT_MOUSELEAVE$1 = `mouseleave${EVENT_KEY$8}`;\nconst EVENT_DRAG_START = `dragstart${EVENT_KEY$8}`;\nconst EVENT_LOAD_DATA_API$3 = `load${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst EVENT_CLICK_DATA_API$5 = `click${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst CLASS_NAME_CAROUSEL = 'carousel';\nconst CLASS_NAME_ACTIVE$2 = 'active';\nconst CLASS_NAME_SLIDE = 'slide';\nconst CLASS_NAME_END = 'carousel-item-end';\nconst CLASS_NAME_START = 'carousel-item-start';\nconst CLASS_NAME_NEXT = 'carousel-item-next';\nconst CLASS_NAME_PREV = 'carousel-item-prev';\nconst SELECTOR_ACTIVE = '.active';\nconst SELECTOR_ITEM = '.carousel-item';\nconst SELECTOR_ACTIVE_ITEM = SELECTOR_ACTIVE + SELECTOR_ITEM;\nconst SELECTOR_ITEM_IMG = '.carousel-item img';\nconst SELECTOR_INDICATORS = '.carousel-indicators';\nconst SELECTOR_DATA_SLIDE = '[data-bs-slide], [data-bs-slide-to]';\nconst SELECTOR_DATA_RIDE = '[data-bs-ride=\"carousel\"]';\nconst KEY_TO_DIRECTION = {\n [ARROW_LEFT_KEY$1]: DIRECTION_RIGHT,\n [ARROW_RIGHT_KEY$1]: DIRECTION_LEFT\n};\nconst Default$b = {\n interval: 5000,\n keyboard: true,\n pause: 'hover',\n ride: false,\n touch: true,\n wrap: true\n};\nconst DefaultType$b = {\n interval: '(number|boolean)',\n // TODO:v6 remove boolean support\n keyboard: 'boolean',\n pause: '(string|boolean)',\n ride: '(boolean|string)',\n touch: 'boolean',\n wrap: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Carousel extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._interval = null;\n this._activeElement = null;\n this._isSliding = false;\n this.touchTimeout = null;\n this._swipeHelper = null;\n this._indicatorsElement = SelectorEngine.findOne(SELECTOR_INDICATORS, this._element);\n this._addEventListeners();\n if (this._config.ride === CLASS_NAME_CAROUSEL) {\n this.cycle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$b;\n }\n static get DefaultType() {\n return DefaultType$b;\n }\n static get NAME() {\n return NAME$c;\n }\n\n // Public\n next() {\n this._slide(ORDER_NEXT);\n }\n nextWhenVisible() {\n // FIXME TODO use `document.visibilityState`\n // Don't call next when the page isn't visible\n // or the carousel or its parent isn't visible\n if (!document.hidden && isVisible(this._element)) {\n this.next();\n }\n }\n prev() {\n this._slide(ORDER_PREV);\n }\n pause() {\n if (this._isSliding) {\n triggerTransitionEnd(this._element);\n }\n this._clearInterval();\n }\n cycle() {\n this._clearInterval();\n this._updateInterval();\n this._interval = setInterval(() => this.nextWhenVisible(), this._config.interval);\n }\n _maybeEnableCycle() {\n if (!this._config.ride) {\n return;\n }\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.cycle());\n return;\n }\n this.cycle();\n }\n to(index) {\n const items = this._getItems();\n if (index > items.length - 1 || index < 0) {\n return;\n }\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.to(index));\n return;\n }\n const activeIndex = this._getItemIndex(this._getActive());\n if (activeIndex === index) {\n return;\n }\n const order = index > activeIndex ? ORDER_NEXT : ORDER_PREV;\n this._slide(order, items[index]);\n }\n dispose() {\n if (this._swipeHelper) {\n this._swipeHelper.dispose();\n }\n super.dispose();\n }\n\n // Private\n _configAfterMerge(config) {\n config.defaultInterval = config.interval;\n return config;\n }\n _addEventListeners() {\n if (this._config.keyboard) {\n EventHandler.on(this._element, EVENT_KEYDOWN$1, event => this._keydown(event));\n }\n if (this._config.pause === 'hover') {\n EventHandler.on(this._element, EVENT_MOUSEENTER$1, () => this.pause());\n EventHandler.on(this._element, EVENT_MOUSELEAVE$1, () => this._maybeEnableCycle());\n }\n if (this._config.touch && Swipe.isSupported()) {\n this._addTouchEventListeners();\n }\n }\n _addTouchEventListeners() {\n for (const img of SelectorEngine.find(SELECTOR_ITEM_IMG, this._element)) {\n EventHandler.on(img, EVENT_DRAG_START, event => event.preventDefault());\n }\n const endCallBack = () => {\n if (this._config.pause !== 'hover') {\n return;\n }\n\n // If it's a touch-enabled device, mouseenter/leave are fired as\n // part of the mouse compatibility events on first tap - the carousel\n // would stop cycling until user tapped out of it;\n // here, we listen for touchend, explicitly pause the carousel\n // (as if it's the second time we tap on it, mouseenter compat event\n // is NOT fired) and after a timeout (to allow for mouse compatibility\n // events to fire) we explicitly restart cycling\n\n this.pause();\n if (this.touchTimeout) {\n clearTimeout(this.touchTimeout);\n }\n this.touchTimeout = setTimeout(() => this._maybeEnableCycle(), TOUCHEVENT_COMPAT_WAIT + this._config.interval);\n };\n const swipeConfig = {\n leftCallback: () => this._slide(this._directionToOrder(DIRECTION_LEFT)),\n rightCallback: () => this._slide(this._directionToOrder(DIRECTION_RIGHT)),\n endCallback: endCallBack\n };\n this._swipeHelper = new Swipe(this._element, swipeConfig);\n }\n _keydown(event) {\n if (/input|textarea/i.test(event.target.tagName)) {\n return;\n }\n const direction = KEY_TO_DIRECTION[event.key];\n if (direction) {\n event.preventDefault();\n this._slide(this._directionToOrder(direction));\n }\n }\n _getItemIndex(element) {\n return this._getItems().indexOf(element);\n }\n _setActiveIndicatorElement(index) {\n if (!this._indicatorsElement) {\n return;\n }\n const activeIndicator = SelectorEngine.findOne(SELECTOR_ACTIVE, this._indicatorsElement);\n activeIndicator.classList.remove(CLASS_NAME_ACTIVE$2);\n activeIndicator.removeAttribute('aria-current');\n const newActiveIndicator = SelectorEngine.findOne(`[data-bs-slide-to=\"${index}\"]`, this._indicatorsElement);\n if (newActiveIndicator) {\n newActiveIndicator.classList.add(CLASS_NAME_ACTIVE$2);\n newActiveIndicator.setAttribute('aria-current', 'true');\n }\n }\n _updateInterval() {\n const element = this._activeElement || this._getActive();\n if (!element) {\n return;\n }\n const elementInterval = Number.parseInt(element.getAttribute('data-bs-interval'), 10);\n this._config.interval = elementInterval || this._config.defaultInterval;\n }\n _slide(order, element = null) {\n if (this._isSliding) {\n return;\n }\n const activeElement = this._getActive();\n const isNext = order === ORDER_NEXT;\n const nextElement = element || getNextActiveElement(this._getItems(), activeElement, isNext, this._config.wrap);\n if (nextElement === activeElement) {\n return;\n }\n const nextElementIndex = this._getItemIndex(nextElement);\n const triggerEvent = eventName => {\n return EventHandler.trigger(this._element, eventName, {\n relatedTarget: nextElement,\n direction: this._orderToDirection(order),\n from: this._getItemIndex(activeElement),\n to: nextElementIndex\n });\n };\n const slideEvent = triggerEvent(EVENT_SLIDE);\n if (slideEvent.defaultPrevented) {\n return;\n }\n if (!activeElement || !nextElement) {\n // Some weirdness is happening, so we bail\n // TODO: change tests that use empty divs to avoid this check\n return;\n }\n const isCycling = Boolean(this._interval);\n this.pause();\n this._isSliding = true;\n this._setActiveIndicatorElement(nextElementIndex);\n this._activeElement = nextElement;\n const directionalClassName = isNext ? CLASS_NAME_START : CLASS_NAME_END;\n const orderClassName = isNext ? CLASS_NAME_NEXT : CLASS_NAME_PREV;\n nextElement.classList.add(orderClassName);\n reflow(nextElement);\n activeElement.classList.add(directionalClassName);\n nextElement.classList.add(directionalClassName);\n const completeCallBack = () => {\n nextElement.classList.remove(directionalClassName, orderClassName);\n nextElement.classList.add(CLASS_NAME_ACTIVE$2);\n activeElement.classList.remove(CLASS_NAME_ACTIVE$2, orderClassName, directionalClassName);\n this._isSliding = false;\n triggerEvent(EVENT_SLID);\n };\n this._queueCallback(completeCallBack, activeElement, this._isAnimated());\n if (isCycling) {\n this.cycle();\n }\n }\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_SLIDE);\n }\n _getActive() {\n return SelectorEngine.findOne(SELECTOR_ACTIVE_ITEM, this._element);\n }\n _getItems() {\n return SelectorEngine.find(SELECTOR_ITEM, this._element);\n }\n _clearInterval() {\n if (this._interval) {\n clearInterval(this._interval);\n this._interval = null;\n }\n }\n _directionToOrder(direction) {\n if (isRTL()) {\n return direction === DIRECTION_LEFT ? ORDER_PREV : ORDER_NEXT;\n }\n return direction === DIRECTION_LEFT ? ORDER_NEXT : ORDER_PREV;\n }\n _orderToDirection(order) {\n if (isRTL()) {\n return order === ORDER_PREV ? DIRECTION_LEFT : DIRECTION_RIGHT;\n }\n return order === ORDER_PREV ? DIRECTION_RIGHT : DIRECTION_LEFT;\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Carousel.getOrCreateInstance(this, config);\n if (typeof config === 'number') {\n data.to(config);\n return;\n }\n if (typeof config === 'string') {\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$5, SELECTOR_DATA_SLIDE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (!target || !target.classList.contains(CLASS_NAME_CAROUSEL)) {\n return;\n }\n event.preventDefault();\n const carousel = Carousel.getOrCreateInstance(target);\n const slideIndex = this.getAttribute('data-bs-slide-to');\n if (slideIndex) {\n carousel.to(slideIndex);\n carousel._maybeEnableCycle();\n return;\n }\n if (Manipulator.getDataAttribute(this, 'slide') === 'next') {\n carousel.next();\n carousel._maybeEnableCycle();\n return;\n }\n carousel.prev();\n carousel._maybeEnableCycle();\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$3, () => {\n const carousels = SelectorEngine.find(SELECTOR_DATA_RIDE);\n for (const carousel of carousels) {\n Carousel.getOrCreateInstance(carousel);\n }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Carousel);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap collapse.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$b = 'collapse';\nconst DATA_KEY$7 = 'bs.collapse';\nconst EVENT_KEY$7 = `.${DATA_KEY$7}`;\nconst DATA_API_KEY$4 = '.data-api';\nconst EVENT_SHOW$6 = `show${EVENT_KEY$7}`;\nconst EVENT_SHOWN$6 = `shown${EVENT_KEY$7}`;\nconst EVENT_HIDE$6 = `hide${EVENT_KEY$7}`;\nconst EVENT_HIDDEN$6 = `hidden${EVENT_KEY$7}`;\nconst EVENT_CLICK_DATA_API$4 = `click${EVENT_KEY$7}${DATA_API_KEY$4}`;\nconst CLASS_NAME_SHOW$7 = 'show';\nconst CLASS_NAME_COLLAPSE = 'collapse';\nconst CLASS_NAME_COLLAPSING = 'collapsing';\nconst CLASS_NAME_COLLAPSED = 'collapsed';\nconst CLASS_NAME_DEEPER_CHILDREN = `:scope .${CLASS_NAME_COLLAPSE} .${CLASS_NAME_COLLAPSE}`;\nconst CLASS_NAME_HORIZONTAL = 'collapse-horizontal';\nconst WIDTH = 'width';\nconst HEIGHT = 'height';\nconst SELECTOR_ACTIVES = '.collapse.show, .collapse.collapsing';\nconst SELECTOR_DATA_TOGGLE$4 = '[data-bs-toggle=\"collapse\"]';\nconst Default$a = {\n parent: null,\n toggle: true\n};\nconst DefaultType$a = {\n parent: '(null|element)',\n toggle: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Collapse extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._isTransitioning = false;\n this._triggerArray = [];\n const toggleList = SelectorEngine.find(SELECTOR_DATA_TOGGLE$4);\n for (const elem of toggleList) {\n const selector = SelectorEngine.getSelectorFromElement(elem);\n const filterElement = SelectorEngine.find(selector).filter(foundElement => foundElement === this._element);\n if (selector !== null && filterElement.length) {\n this._triggerArray.push(elem);\n }\n }\n this._initializeChildren();\n if (!this._config.parent) {\n this._addAriaAndCollapsedClass(this._triggerArray, this._isShown());\n }\n if (this._config.toggle) {\n this.toggle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$a;\n }\n static get DefaultType() {\n return DefaultType$a;\n }\n static get NAME() {\n return NAME$b;\n }\n\n // Public\n toggle() {\n if (this._isShown()) {\n this.hide();\n } else {\n this.show();\n }\n }\n show() {\n if (this._isTransitioning || this._isShown()) {\n return;\n }\n let activeChildren = [];\n\n // find active children\n if (this._config.parent) {\n activeChildren = this._getFirstLevelChildren(SELECTOR_ACTIVES).filter(element => element !== this._element).map(element => Collapse.getOrCreateInstance(element, {\n toggle: false\n }));\n }\n if (activeChildren.length && activeChildren[0]._isTransitioning) {\n return;\n }\n const startEvent = EventHandler.trigger(this._element, EVENT_SHOW$6);\n if (startEvent.defaultPrevented) {\n return;\n }\n for (const activeInstance of activeChildren) {\n activeInstance.hide();\n }\n const dimension = this._getDimension();\n this._element.classList.remove(CLASS_NAME_COLLAPSE);\n this._element.classList.add(CLASS_NAME_COLLAPSING);\n this._element.style[dimension] = 0;\n this._addAriaAndCollapsedClass(this._triggerArray, true);\n this._isTransitioning = true;\n const complete = () => {\n this._isTransitioning = false;\n this._element.classList.remove(CLASS_NAME_COLLAPSING);\n this._element.classList.add(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n this._element.style[dimension] = '';\n EventHandler.trigger(this._element, EVENT_SHOWN$6);\n };\n const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1);\n const scrollSize = `scroll${capitalizedDimension}`;\n this._queueCallback(complete, this._element, true);\n this._element.style[dimension] = `${this._element[scrollSize]}px`;\n }\n hide() {\n if (this._isTransitioning || !this._isShown()) {\n return;\n }\n const startEvent = EventHandler.trigger(this._element, EVENT_HIDE$6);\n if (startEvent.defaultPrevented) {\n return;\n }\n const dimension = this._getDimension();\n this._element.style[dimension] = `${this._element.getBoundingClientRect()[dimension]}px`;\n reflow(this._element);\n this._element.classList.add(CLASS_NAME_COLLAPSING);\n this._element.classList.remove(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n for (const trigger of this._triggerArray) {\n const element = SelectorEngine.getElementFromSelector(trigger);\n if (element && !this._isShown(element)) {\n this._addAriaAndCollapsedClass([trigger], false);\n }\n }\n this._isTransitioning = true;\n const complete = () => {\n this._isTransitioning = false;\n this._element.classList.remove(CLASS_NAME_COLLAPSING);\n this._element.classList.add(CLASS_NAME_COLLAPSE);\n EventHandler.trigger(this._element, EVENT_HIDDEN$6);\n };\n this._element.style[dimension] = '';\n this._queueCallback(complete, this._element, true);\n }\n _isShown(element = this._element) {\n return element.classList.contains(CLASS_NAME_SHOW$7);\n }\n\n // Private\n _configAfterMerge(config) {\n config.toggle = Boolean(config.toggle); // Coerce string values\n config.parent = getElement(config.parent);\n return config;\n }\n _getDimension() {\n return this._element.classList.contains(CLASS_NAME_HORIZONTAL) ? WIDTH : HEIGHT;\n }\n _initializeChildren() {\n if (!this._config.parent) {\n return;\n }\n const children = this._getFirstLevelChildren(SELECTOR_DATA_TOGGLE$4);\n for (const element of children) {\n const selected = SelectorEngine.getElementFromSelector(element);\n if (selected) {\n this._addAriaAndCollapsedClass([element], this._isShown(selected));\n }\n }\n }\n _getFirstLevelChildren(selector) {\n const children = SelectorEngine.find(CLASS_NAME_DEEPER_CHILDREN, this._config.parent);\n // remove children if greater depth\n return SelectorEngine.find(selector, this._config.parent).filter(element => !children.includes(element));\n }\n _addAriaAndCollapsedClass(triggerArray, isOpen) {\n if (!triggerArray.length) {\n return;\n }\n for (const element of triggerArray) {\n element.classList.toggle(CLASS_NAME_COLLAPSED, !isOpen);\n element.setAttribute('aria-expanded', isOpen);\n }\n }\n\n // Static\n static jQueryInterface(config) {\n const _config = {};\n if (typeof config === 'string' && /show|hide/.test(config)) {\n _config.toggle = false;\n }\n return this.each(function () {\n const data = Collapse.getOrCreateInstance(this, _config);\n if (typeof config === 'string') {\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$4, SELECTOR_DATA_TOGGLE$4, function (event) {\n // preventDefault only for elements (which change the URL) not inside the collapsible element\n if (event.target.tagName === 'A' || event.delegateTarget && event.delegateTarget.tagName === 'A') {\n event.preventDefault();\n }\n for (const element of SelectorEngine.getMultipleElementsFromSelector(this)) {\n Collapse.getOrCreateInstance(element, {\n toggle: false\n }).toggle();\n }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Collapse);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dropdown.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$a = 'dropdown';\nconst DATA_KEY$6 = 'bs.dropdown';\nconst EVENT_KEY$6 = `.${DATA_KEY$6}`;\nconst DATA_API_KEY$3 = '.data-api';\nconst ESCAPE_KEY$2 = 'Escape';\nconst TAB_KEY$1 = 'Tab';\nconst ARROW_UP_KEY$1 = 'ArrowUp';\nconst ARROW_DOWN_KEY$1 = 'ArrowDown';\nconst RIGHT_MOUSE_BUTTON = 2; // MouseEvent.button value for the secondary button, usually the right button\n\nconst EVENT_HIDE$5 = `hide${EVENT_KEY$6}`;\nconst EVENT_HIDDEN$5 = `hidden${EVENT_KEY$6}`;\nconst EVENT_SHOW$5 = `show${EVENT_KEY$6}`;\nconst EVENT_SHOWN$5 = `shown${EVENT_KEY$6}`;\nconst EVENT_CLICK_DATA_API$3 = `click${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYDOWN_DATA_API = `keydown${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYUP_DATA_API = `keyup${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst CLASS_NAME_SHOW$6 = 'show';\nconst CLASS_NAME_DROPUP = 'dropup';\nconst CLASS_NAME_DROPEND = 'dropend';\nconst CLASS_NAME_DROPSTART = 'dropstart';\nconst CLASS_NAME_DROPUP_CENTER = 'dropup-center';\nconst CLASS_NAME_DROPDOWN_CENTER = 'dropdown-center';\nconst SELECTOR_DATA_TOGGLE$3 = '[data-bs-toggle=\"dropdown\"]:not(.disabled):not(:disabled)';\nconst SELECTOR_DATA_TOGGLE_SHOWN = `${SELECTOR_DATA_TOGGLE$3}.${CLASS_NAME_SHOW$6}`;\nconst SELECTOR_MENU = '.dropdown-menu';\nconst SELECTOR_NAVBAR = '.navbar';\nconst SELECTOR_NAVBAR_NAV = '.navbar-nav';\nconst SELECTOR_VISIBLE_ITEMS = '.dropdown-menu .dropdown-item:not(.disabled):not(:disabled)';\nconst PLACEMENT_TOP = isRTL() ? 'top-end' : 'top-start';\nconst PLACEMENT_TOPEND = isRTL() ? 'top-start' : 'top-end';\nconst PLACEMENT_BOTTOM = isRTL() ? 'bottom-end' : 'bottom-start';\nconst PLACEMENT_BOTTOMEND = isRTL() ? 'bottom-start' : 'bottom-end';\nconst PLACEMENT_RIGHT = isRTL() ? 'left-start' : 'right-start';\nconst PLACEMENT_LEFT = isRTL() ? 'right-start' : 'left-start';\nconst PLACEMENT_TOPCENTER = 'top';\nconst PLACEMENT_BOTTOMCENTER = 'bottom';\nconst Default$9 = {\n autoClose: true,\n boundary: 'clippingParents',\n display: 'dynamic',\n offset: [0, 2],\n popperConfig: null,\n reference: 'toggle'\n};\nconst DefaultType$9 = {\n autoClose: '(boolean|string)',\n boundary: '(string|element)',\n display: 'string',\n offset: '(array|string|function)',\n popperConfig: '(null|object|function)',\n reference: '(string|element|object)'\n};\n\n/**\n * Class definition\n */\n\nclass Dropdown extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._popper = null;\n this._parent = this._element.parentNode; // dropdown wrapper\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n this._menu = SelectorEngine.next(this._element, SELECTOR_MENU)[0] || SelectorEngine.prev(this._element, SELECTOR_MENU)[0] || SelectorEngine.findOne(SELECTOR_MENU, this._parent);\n this._inNavbar = this._detectNavbar();\n }\n\n // Getters\n static get Default() {\n return Default$9;\n }\n static get DefaultType() {\n return DefaultType$9;\n }\n static get NAME() {\n return NAME$a;\n }\n\n // Public\n toggle() {\n return this._isShown() ? this.hide() : this.show();\n }\n show() {\n if (isDisabled(this._element) || this._isShown()) {\n return;\n }\n const relatedTarget = {\n relatedTarget: this._element\n };\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$5, relatedTarget);\n if (showEvent.defaultPrevented) {\n return;\n }\n this._createPopper();\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement && !this._parent.closest(SELECTOR_NAVBAR_NAV)) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop);\n }\n }\n this._element.focus();\n this._element.setAttribute('aria-expanded', true);\n this._menu.classList.add(CLASS_NAME_SHOW$6);\n this._element.classList.add(CLASS_NAME_SHOW$6);\n EventHandler.trigger(this._element, EVENT_SHOWN$5, relatedTarget);\n }\n hide() {\n if (isDisabled(this._element) || !this._isShown()) {\n return;\n }\n const relatedTarget = {\n relatedTarget: this._element\n };\n this._completeHide(relatedTarget);\n }\n dispose() {\n if (this._popper) {\n this._popper.destroy();\n }\n super.dispose();\n }\n update() {\n this._inNavbar = this._detectNavbar();\n if (this._popper) {\n this._popper.update();\n }\n }\n\n // Private\n _completeHide(relatedTarget) {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$5, relatedTarget);\n if (hideEvent.defaultPrevented) {\n return;\n }\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop);\n }\n }\n if (this._popper) {\n this._popper.destroy();\n }\n this._menu.classList.remove(CLASS_NAME_SHOW$6);\n this._element.classList.remove(CLASS_NAME_SHOW$6);\n this._element.setAttribute('aria-expanded', 'false');\n Manipulator.removeDataAttribute(this._menu, 'popper');\n EventHandler.trigger(this._element, EVENT_HIDDEN$5, relatedTarget);\n }\n _getConfig(config) {\n config = super._getConfig(config);\n if (typeof config.reference === 'object' && !isElement(config.reference) && typeof config.reference.getBoundingClientRect !== 'function') {\n // Popper virtual elements require a getBoundingClientRect method\n throw new TypeError(`${NAME$a.toUpperCase()}: Option \"reference\" provided type \"object\" without a required \"getBoundingClientRect\" method.`);\n }\n return config;\n }\n _createPopper() {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s dropdowns require Popper (https://popper.js.org)');\n }\n let referenceElement = this._element;\n if (this._config.reference === 'parent') {\n referenceElement = this._parent;\n } else if (isElement(this._config.reference)) {\n referenceElement = getElement(this._config.reference);\n } else if (typeof this._config.reference === 'object') {\n referenceElement = this._config.reference;\n }\n const popperConfig = this._getPopperConfig();\n this._popper = Popper.createPopper(referenceElement, this._menu, popperConfig);\n }\n _isShown() {\n return this._menu.classList.contains(CLASS_NAME_SHOW$6);\n }\n _getPlacement() {\n const parentDropdown = this._parent;\n if (parentDropdown.classList.contains(CLASS_NAME_DROPEND)) {\n return PLACEMENT_RIGHT;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPSTART)) {\n return PLACEMENT_LEFT;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP_CENTER)) {\n return PLACEMENT_TOPCENTER;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPDOWN_CENTER)) {\n return PLACEMENT_BOTTOMCENTER;\n }\n\n // We need to trim the value because custom properties can also include spaces\n const isEnd = getComputedStyle(this._menu).getPropertyValue('--bs-position').trim() === 'end';\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP)) {\n return isEnd ? PLACEMENT_TOPEND : PLACEMENT_TOP;\n }\n return isEnd ? PLACEMENT_BOTTOMEND : PLACEMENT_BOTTOM;\n }\n _detectNavbar() {\n return this._element.closest(SELECTOR_NAVBAR) !== null;\n }\n _getOffset() {\n const {\n offset\n } = this._config;\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10));\n }\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element);\n }\n return offset;\n }\n _getPopperConfig() {\n const defaultBsPopperConfig = {\n placement: this._getPlacement(),\n modifiers: [{\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n }, {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }]\n };\n\n // Disable Popper if we have a static display or Dropdown is in Navbar\n if (this._inNavbar || this._config.display === 'static') {\n Manipulator.setDataAttribute(this._menu, 'popper', 'static'); // TODO: v6 remove\n defaultBsPopperConfig.modifiers = [{\n name: 'applyStyles',\n enabled: false\n }];\n }\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n };\n }\n _selectMenuItem({\n key,\n target\n }) {\n const items = SelectorEngine.find(SELECTOR_VISIBLE_ITEMS, this._menu).filter(element => isVisible(element));\n if (!items.length) {\n return;\n }\n\n // if target isn't included in items (e.g. when expanding the dropdown)\n // allow cycling to get the last item in case key equals ARROW_UP_KEY\n getNextActiveElement(items, target, key === ARROW_DOWN_KEY$1, !items.includes(target)).focus();\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Dropdown.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n static clearMenus(event) {\n if (event.button === RIGHT_MOUSE_BUTTON || event.type === 'keyup' && event.key !== TAB_KEY$1) {\n return;\n }\n const openToggles = SelectorEngine.find(SELECTOR_DATA_TOGGLE_SHOWN);\n for (const toggle of openToggles) {\n const context = Dropdown.getInstance(toggle);\n if (!context || context._config.autoClose === false) {\n continue;\n }\n const composedPath = event.composedPath();\n const isMenuTarget = composedPath.includes(context._menu);\n if (composedPath.includes(context._element) || context._config.autoClose === 'inside' && !isMenuTarget || context._config.autoClose === 'outside' && isMenuTarget) {\n continue;\n }\n\n // Tab navigation through the dropdown menu or events from contained inputs shouldn't close the menu\n if (context._menu.contains(event.target) && (event.type === 'keyup' && event.key === TAB_KEY$1 || /input|select|option|textarea|form/i.test(event.target.tagName))) {\n continue;\n }\n const relatedTarget = {\n relatedTarget: context._element\n };\n if (event.type === 'click') {\n relatedTarget.clickEvent = event;\n }\n context._completeHide(relatedTarget);\n }\n }\n static dataApiKeydownHandler(event) {\n // If not an UP | DOWN | ESCAPE key => not a dropdown command\n // If input/textarea && if key is other than ESCAPE => not a dropdown command\n\n const isInput = /input|textarea/i.test(event.target.tagName);\n const isEscapeEvent = event.key === ESCAPE_KEY$2;\n const isUpOrDownEvent = [ARROW_UP_KEY$1, ARROW_DOWN_KEY$1].includes(event.key);\n if (!isUpOrDownEvent && !isEscapeEvent) {\n return;\n }\n if (isInput && !isEscapeEvent) {\n return;\n }\n event.preventDefault();\n\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n const getToggleButton = this.matches(SELECTOR_DATA_TOGGLE$3) ? this : SelectorEngine.prev(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.next(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.findOne(SELECTOR_DATA_TOGGLE$3, event.delegateTarget.parentNode);\n const instance = Dropdown.getOrCreateInstance(getToggleButton);\n if (isUpOrDownEvent) {\n event.stopPropagation();\n instance.show();\n instance._selectMenuItem(event);\n return;\n }\n if (instance._isShown()) {\n // else is escape and we check if it is shown\n event.stopPropagation();\n instance.hide();\n getToggleButton.focus();\n }\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_DATA_TOGGLE$3, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_MENU, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_KEYUP_DATA_API, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, SELECTOR_DATA_TOGGLE$3, function (event) {\n event.preventDefault();\n Dropdown.getOrCreateInstance(this).toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Dropdown);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/backdrop.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$9 = 'backdrop';\nconst CLASS_NAME_FADE$4 = 'fade';\nconst CLASS_NAME_SHOW$5 = 'show';\nconst EVENT_MOUSEDOWN = `mousedown.bs.${NAME$9}`;\nconst Default$8 = {\n className: 'modal-backdrop',\n clickCallback: null,\n isAnimated: false,\n isVisible: true,\n // if false, we use the backdrop helper without adding any element to the dom\n rootElement: 'body' // give the choice to place backdrop under different elements\n};\n\nconst DefaultType$8 = {\n className: 'string',\n clickCallback: '(function|null)',\n isAnimated: 'boolean',\n isVisible: 'boolean',\n rootElement: '(element|string)'\n};\n\n/**\n * Class definition\n */\n\nclass Backdrop extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n this._isAppended = false;\n this._element = null;\n }\n\n // Getters\n static get Default() {\n return Default$8;\n }\n static get DefaultType() {\n return DefaultType$8;\n }\n static get NAME() {\n return NAME$9;\n }\n\n // Public\n show(callback) {\n if (!this._config.isVisible) {\n execute(callback);\n return;\n }\n this._append();\n const element = this._getElement();\n if (this._config.isAnimated) {\n reflow(element);\n }\n element.classList.add(CLASS_NAME_SHOW$5);\n this._emulateAnimation(() => {\n execute(callback);\n });\n }\n hide(callback) {\n if (!this._config.isVisible) {\n execute(callback);\n return;\n }\n this._getElement().classList.remove(CLASS_NAME_SHOW$5);\n this._emulateAnimation(() => {\n this.dispose();\n execute(callback);\n });\n }\n dispose() {\n if (!this._isAppended) {\n return;\n }\n EventHandler.off(this._element, EVENT_MOUSEDOWN);\n this._element.remove();\n this._isAppended = false;\n }\n\n // Private\n _getElement() {\n if (!this._element) {\n const backdrop = document.createElement('div');\n backdrop.className = this._config.className;\n if (this._config.isAnimated) {\n backdrop.classList.add(CLASS_NAME_FADE$4);\n }\n this._element = backdrop;\n }\n return this._element;\n }\n _configAfterMerge(config) {\n // use getElement() with the default \"body\" to get a fresh Element on each instantiation\n config.rootElement = getElement(config.rootElement);\n return config;\n }\n _append() {\n if (this._isAppended) {\n return;\n }\n const element = this._getElement();\n this._config.rootElement.append(element);\n EventHandler.on(element, EVENT_MOUSEDOWN, () => {\n execute(this._config.clickCallback);\n });\n this._isAppended = true;\n }\n _emulateAnimation(callback) {\n executeAfterTransition(callback, this._getElement(), this._config.isAnimated);\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/focustrap.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$8 = 'focustrap';\nconst DATA_KEY$5 = 'bs.focustrap';\nconst EVENT_KEY$5 = `.${DATA_KEY$5}`;\nconst EVENT_FOCUSIN$2 = `focusin${EVENT_KEY$5}`;\nconst EVENT_KEYDOWN_TAB = `keydown.tab${EVENT_KEY$5}`;\nconst TAB_KEY = 'Tab';\nconst TAB_NAV_FORWARD = 'forward';\nconst TAB_NAV_BACKWARD = 'backward';\nconst Default$7 = {\n autofocus: true,\n trapElement: null // The element to trap focus inside of\n};\n\nconst DefaultType$7 = {\n autofocus: 'boolean',\n trapElement: 'element'\n};\n\n/**\n * Class definition\n */\n\nclass FocusTrap extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n this._isActive = false;\n this._lastTabNavDirection = null;\n }\n\n // Getters\n static get Default() {\n return Default$7;\n }\n static get DefaultType() {\n return DefaultType$7;\n }\n static get NAME() {\n return NAME$8;\n }\n\n // Public\n activate() {\n if (this._isActive) {\n return;\n }\n if (this._config.autofocus) {\n this._config.trapElement.focus();\n }\n EventHandler.off(document, EVENT_KEY$5); // guard against infinite focus loop\n EventHandler.on(document, EVENT_FOCUSIN$2, event => this._handleFocusin(event));\n EventHandler.on(document, EVENT_KEYDOWN_TAB, event => this._handleKeydown(event));\n this._isActive = true;\n }\n deactivate() {\n if (!this._isActive) {\n return;\n }\n this._isActive = false;\n EventHandler.off(document, EVENT_KEY$5);\n }\n\n // Private\n _handleFocusin(event) {\n const {\n trapElement\n } = this._config;\n if (event.target === document || event.target === trapElement || trapElement.contains(event.target)) {\n return;\n }\n const elements = SelectorEngine.focusableChildren(trapElement);\n if (elements.length === 0) {\n trapElement.focus();\n } else if (this._lastTabNavDirection === TAB_NAV_BACKWARD) {\n elements[elements.length - 1].focus();\n } else {\n elements[0].focus();\n }\n }\n _handleKeydown(event) {\n if (event.key !== TAB_KEY) {\n return;\n }\n this._lastTabNavDirection = event.shiftKey ? TAB_NAV_BACKWARD : TAB_NAV_FORWARD;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/scrollBar.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst SELECTOR_FIXED_CONTENT = '.fixed-top, .fixed-bottom, .is-fixed, .sticky-top';\nconst SELECTOR_STICKY_CONTENT = '.sticky-top';\nconst PROPERTY_PADDING = 'padding-right';\nconst PROPERTY_MARGIN = 'margin-right';\n\n/**\n * Class definition\n */\n\nclass ScrollBarHelper {\n constructor() {\n this._element = document.body;\n }\n\n // Public\n getWidth() {\n // https://developer.mozilla.org/en-US/docs/Web/API/Window/innerWidth#usage_notes\n const documentWidth = document.documentElement.clientWidth;\n return Math.abs(window.innerWidth - documentWidth);\n }\n hide() {\n const width = this.getWidth();\n this._disableOverFlow();\n // give padding to element to balance the hidden scrollbar width\n this._setElementAttributes(this._element, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n // trick: We adjust positive paddingRight and negative marginRight to sticky-top elements to keep showing fullwidth\n this._setElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n this._setElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN, calculatedValue => calculatedValue - width);\n }\n reset() {\n this._resetElementAttributes(this._element, 'overflow');\n this._resetElementAttributes(this._element, PROPERTY_PADDING);\n this._resetElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING);\n this._resetElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN);\n }\n isOverflowing() {\n return this.getWidth() > 0;\n }\n\n // Private\n _disableOverFlow() {\n this._saveInitialAttribute(this._element, 'overflow');\n this._element.style.overflow = 'hidden';\n }\n _setElementAttributes(selector, styleProperty, callback) {\n const scrollbarWidth = this.getWidth();\n const manipulationCallBack = element => {\n if (element !== this._element && window.innerWidth > element.clientWidth + scrollbarWidth) {\n return;\n }\n this._saveInitialAttribute(element, styleProperty);\n const calculatedValue = window.getComputedStyle(element).getPropertyValue(styleProperty);\n element.style.setProperty(styleProperty, `${callback(Number.parseFloat(calculatedValue))}px`);\n };\n this._applyManipulationCallback(selector, manipulationCallBack);\n }\n _saveInitialAttribute(element, styleProperty) {\n const actualValue = element.style.getPropertyValue(styleProperty);\n if (actualValue) {\n Manipulator.setDataAttribute(element, styleProperty, actualValue);\n }\n }\n _resetElementAttributes(selector, styleProperty) {\n const manipulationCallBack = element => {\n const value = Manipulator.getDataAttribute(element, styleProperty);\n // We only want to remove the property if the value is `null`; the value can also be zero\n if (value === null) {\n element.style.removeProperty(styleProperty);\n return;\n }\n Manipulator.removeDataAttribute(element, styleProperty);\n element.style.setProperty(styleProperty, value);\n };\n this._applyManipulationCallback(selector, manipulationCallBack);\n }\n _applyManipulationCallback(selector, callBack) {\n if (isElement(selector)) {\n callBack(selector);\n return;\n }\n for (const sel of SelectorEngine.find(selector, this._element)) {\n callBack(sel);\n }\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap modal.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$7 = 'modal';\nconst DATA_KEY$4 = 'bs.modal';\nconst EVENT_KEY$4 = `.${DATA_KEY$4}`;\nconst DATA_API_KEY$2 = '.data-api';\nconst ESCAPE_KEY$1 = 'Escape';\nconst EVENT_HIDE$4 = `hide${EVENT_KEY$4}`;\nconst EVENT_HIDE_PREVENTED$1 = `hidePrevented${EVENT_KEY$4}`;\nconst EVENT_HIDDEN$4 = `hidden${EVENT_KEY$4}`;\nconst EVENT_SHOW$4 = `show${EVENT_KEY$4}`;\nconst EVENT_SHOWN$4 = `shown${EVENT_KEY$4}`;\nconst EVENT_RESIZE$1 = `resize${EVENT_KEY$4}`;\nconst EVENT_CLICK_DISMISS = `click.dismiss${EVENT_KEY$4}`;\nconst EVENT_MOUSEDOWN_DISMISS = `mousedown.dismiss${EVENT_KEY$4}`;\nconst EVENT_KEYDOWN_DISMISS$1 = `keydown.dismiss${EVENT_KEY$4}`;\nconst EVENT_CLICK_DATA_API$2 = `click${EVENT_KEY$4}${DATA_API_KEY$2}`;\nconst CLASS_NAME_OPEN = 'modal-open';\nconst CLASS_NAME_FADE$3 = 'fade';\nconst CLASS_NAME_SHOW$4 = 'show';\nconst CLASS_NAME_STATIC = 'modal-static';\nconst OPEN_SELECTOR$1 = '.modal.show';\nconst SELECTOR_DIALOG = '.modal-dialog';\nconst SELECTOR_MODAL_BODY = '.modal-body';\nconst SELECTOR_DATA_TOGGLE$2 = '[data-bs-toggle=\"modal\"]';\nconst Default$6 = {\n backdrop: true,\n focus: true,\n keyboard: true\n};\nconst DefaultType$6 = {\n backdrop: '(boolean|string)',\n focus: 'boolean',\n keyboard: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Modal extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._dialog = SelectorEngine.findOne(SELECTOR_DIALOG, this._element);\n this._backdrop = this._initializeBackDrop();\n this._focustrap = this._initializeFocusTrap();\n this._isShown = false;\n this._isTransitioning = false;\n this._scrollBar = new ScrollBarHelper();\n this._addEventListeners();\n }\n\n // Getters\n static get Default() {\n return Default$6;\n }\n static get DefaultType() {\n return DefaultType$6;\n }\n static get NAME() {\n return NAME$7;\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget);\n }\n show(relatedTarget) {\n if (this._isShown || this._isTransitioning) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$4, {\n relatedTarget\n });\n if (showEvent.defaultPrevented) {\n return;\n }\n this._isShown = true;\n this._isTransitioning = true;\n this._scrollBar.hide();\n document.body.classList.add(CLASS_NAME_OPEN);\n this._adjustDialog();\n this._backdrop.show(() => this._showElement(relatedTarget));\n }\n hide() {\n if (!this._isShown || this._isTransitioning) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$4);\n if (hideEvent.defaultPrevented) {\n return;\n }\n this._isShown = false;\n this._isTransitioning = true;\n this._focustrap.deactivate();\n this._element.classList.remove(CLASS_NAME_SHOW$4);\n this._queueCallback(() => this._hideModal(), this._element, this._isAnimated());\n }\n dispose() {\n EventHandler.off(window, EVENT_KEY$4);\n EventHandler.off(this._dialog, EVENT_KEY$4);\n this._backdrop.dispose();\n this._focustrap.deactivate();\n super.dispose();\n }\n handleUpdate() {\n this._adjustDialog();\n }\n\n // Private\n _initializeBackDrop() {\n return new Backdrop({\n isVisible: Boolean(this._config.backdrop),\n // 'static' option will be translated to true, and booleans will keep their value,\n isAnimated: this._isAnimated()\n });\n }\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n });\n }\n _showElement(relatedTarget) {\n // try to append dynamic modal\n if (!document.body.contains(this._element)) {\n document.body.append(this._element);\n }\n this._element.style.display = 'block';\n this._element.removeAttribute('aria-hidden');\n this._element.setAttribute('aria-modal', true);\n this._element.setAttribute('role', 'dialog');\n this._element.scrollTop = 0;\n const modalBody = SelectorEngine.findOne(SELECTOR_MODAL_BODY, this._dialog);\n if (modalBody) {\n modalBody.scrollTop = 0;\n }\n reflow(this._element);\n this._element.classList.add(CLASS_NAME_SHOW$4);\n const transitionComplete = () => {\n if (this._config.focus) {\n this._focustrap.activate();\n }\n this._isTransitioning = false;\n EventHandler.trigger(this._element, EVENT_SHOWN$4, {\n relatedTarget\n });\n };\n this._queueCallback(transitionComplete, this._dialog, this._isAnimated());\n }\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS$1, event => {\n if (event.key !== ESCAPE_KEY$1) {\n return;\n }\n if (this._config.keyboard) {\n this.hide();\n return;\n }\n this._triggerBackdropTransition();\n });\n EventHandler.on(window, EVENT_RESIZE$1, () => {\n if (this._isShown && !this._isTransitioning) {\n this._adjustDialog();\n }\n });\n EventHandler.on(this._element, EVENT_MOUSEDOWN_DISMISS, event => {\n // a bad trick to segregate clicks that may start inside dialog but end outside, and avoid listen to scrollbar clicks\n EventHandler.one(this._element, EVENT_CLICK_DISMISS, event2 => {\n if (this._element !== event.target || this._element !== event2.target) {\n return;\n }\n if (this._config.backdrop === 'static') {\n this._triggerBackdropTransition();\n return;\n }\n if (this._config.backdrop) {\n this.hide();\n }\n });\n });\n }\n _hideModal() {\n this._element.style.display = 'none';\n this._element.setAttribute('aria-hidden', true);\n this._element.removeAttribute('aria-modal');\n this._element.removeAttribute('role');\n this._isTransitioning = false;\n this._backdrop.hide(() => {\n document.body.classList.remove(CLASS_NAME_OPEN);\n this._resetAdjustments();\n this._scrollBar.reset();\n EventHandler.trigger(this._element, EVENT_HIDDEN$4);\n });\n }\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_FADE$3);\n }\n _triggerBackdropTransition() {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED$1);\n if (hideEvent.defaultPrevented) {\n return;\n }\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n const initialOverflowY = this._element.style.overflowY;\n // return if the following background transition hasn't yet completed\n if (initialOverflowY === 'hidden' || this._element.classList.contains(CLASS_NAME_STATIC)) {\n return;\n }\n if (!isModalOverflowing) {\n this._element.style.overflowY = 'hidden';\n }\n this._element.classList.add(CLASS_NAME_STATIC);\n this._queueCallback(() => {\n this._element.classList.remove(CLASS_NAME_STATIC);\n this._queueCallback(() => {\n this._element.style.overflowY = initialOverflowY;\n }, this._dialog);\n }, this._dialog);\n this._element.focus();\n }\n\n /**\n * The following methods are used to handle overflowing modals\n */\n\n _adjustDialog() {\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n const scrollbarWidth = this._scrollBar.getWidth();\n const isBodyOverflowing = scrollbarWidth > 0;\n if (isBodyOverflowing && !isModalOverflowing) {\n const property = isRTL() ? 'paddingLeft' : 'paddingRight';\n this._element.style[property] = `${scrollbarWidth}px`;\n }\n if (!isBodyOverflowing && isModalOverflowing) {\n const property = isRTL() ? 'paddingRight' : 'paddingLeft';\n this._element.style[property] = `${scrollbarWidth}px`;\n }\n }\n _resetAdjustments() {\n this._element.style.paddingLeft = '';\n this._element.style.paddingRight = '';\n }\n\n // Static\n static jQueryInterface(config, relatedTarget) {\n return this.each(function () {\n const data = Modal.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](relatedTarget);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$2, SELECTOR_DATA_TOGGLE$2, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n EventHandler.one(target, EVENT_SHOW$4, showEvent => {\n if (showEvent.defaultPrevented) {\n // only register focus restorer if modal will actually get shown\n return;\n }\n EventHandler.one(target, EVENT_HIDDEN$4, () => {\n if (isVisible(this)) {\n this.focus();\n }\n });\n });\n\n // avoid conflict when clicking modal toggler while another one is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR$1);\n if (alreadyOpen) {\n Modal.getInstance(alreadyOpen).hide();\n }\n const data = Modal.getOrCreateInstance(target);\n data.toggle(this);\n});\nenableDismissTrigger(Modal);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Modal);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap offcanvas.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$6 = 'offcanvas';\nconst DATA_KEY$3 = 'bs.offcanvas';\nconst EVENT_KEY$3 = `.${DATA_KEY$3}`;\nconst DATA_API_KEY$1 = '.data-api';\nconst EVENT_LOAD_DATA_API$2 = `load${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst ESCAPE_KEY = 'Escape';\nconst CLASS_NAME_SHOW$3 = 'show';\nconst CLASS_NAME_SHOWING$1 = 'showing';\nconst CLASS_NAME_HIDING = 'hiding';\nconst CLASS_NAME_BACKDROP = 'offcanvas-backdrop';\nconst OPEN_SELECTOR = '.offcanvas.show';\nconst EVENT_SHOW$3 = `show${EVENT_KEY$3}`;\nconst EVENT_SHOWN$3 = `shown${EVENT_KEY$3}`;\nconst EVENT_HIDE$3 = `hide${EVENT_KEY$3}`;\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY$3}`;\nconst EVENT_HIDDEN$3 = `hidden${EVENT_KEY$3}`;\nconst EVENT_RESIZE = `resize${EVENT_KEY$3}`;\nconst EVENT_CLICK_DATA_API$1 = `click${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY$3}`;\nconst SELECTOR_DATA_TOGGLE$1 = '[data-bs-toggle=\"offcanvas\"]';\nconst Default$5 = {\n backdrop: true,\n keyboard: true,\n scroll: false\n};\nconst DefaultType$5 = {\n backdrop: '(boolean|string)',\n keyboard: 'boolean',\n scroll: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Offcanvas extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._isShown = false;\n this._backdrop = this._initializeBackDrop();\n this._focustrap = this._initializeFocusTrap();\n this._addEventListeners();\n }\n\n // Getters\n static get Default() {\n return Default$5;\n }\n static get DefaultType() {\n return DefaultType$5;\n }\n static get NAME() {\n return NAME$6;\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget);\n }\n show(relatedTarget) {\n if (this._isShown) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$3, {\n relatedTarget\n });\n if (showEvent.defaultPrevented) {\n return;\n }\n this._isShown = true;\n this._backdrop.show();\n if (!this._config.scroll) {\n new ScrollBarHelper().hide();\n }\n this._element.setAttribute('aria-modal', true);\n this._element.setAttribute('role', 'dialog');\n this._element.classList.add(CLASS_NAME_SHOWING$1);\n const completeCallBack = () => {\n if (!this._config.scroll || this._config.backdrop) {\n this._focustrap.activate();\n }\n this._element.classList.add(CLASS_NAME_SHOW$3);\n this._element.classList.remove(CLASS_NAME_SHOWING$1);\n EventHandler.trigger(this._element, EVENT_SHOWN$3, {\n relatedTarget\n });\n };\n this._queueCallback(completeCallBack, this._element, true);\n }\n hide() {\n if (!this._isShown) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$3);\n if (hideEvent.defaultPrevented) {\n return;\n }\n this._focustrap.deactivate();\n this._element.blur();\n this._isShown = false;\n this._element.classList.add(CLASS_NAME_HIDING);\n this._backdrop.hide();\n const completeCallback = () => {\n this._element.classList.remove(CLASS_NAME_SHOW$3, CLASS_NAME_HIDING);\n this._element.removeAttribute('aria-modal');\n this._element.removeAttribute('role');\n if (!this._config.scroll) {\n new ScrollBarHelper().reset();\n }\n EventHandler.trigger(this._element, EVENT_HIDDEN$3);\n };\n this._queueCallback(completeCallback, this._element, true);\n }\n dispose() {\n this._backdrop.dispose();\n this._focustrap.deactivate();\n super.dispose();\n }\n\n // Private\n _initializeBackDrop() {\n const clickCallback = () => {\n if (this._config.backdrop === 'static') {\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n return;\n }\n this.hide();\n };\n\n // 'static' option will be translated to true, and booleans will keep their value\n const isVisible = Boolean(this._config.backdrop);\n return new Backdrop({\n className: CLASS_NAME_BACKDROP,\n isVisible,\n isAnimated: true,\n rootElement: this._element.parentNode,\n clickCallback: isVisible ? clickCallback : null\n });\n }\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n });\n }\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n if (event.key !== ESCAPE_KEY) {\n return;\n }\n if (this._config.keyboard) {\n this.hide();\n return;\n }\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n });\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Offcanvas.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](this);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$1, SELECTOR_DATA_TOGGLE$1, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n if (isDisabled(this)) {\n return;\n }\n EventHandler.one(target, EVENT_HIDDEN$3, () => {\n // focus on trigger when it is closed\n if (isVisible(this)) {\n this.focus();\n }\n });\n\n // avoid conflict when clicking a toggler of an offcanvas, while another is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR);\n if (alreadyOpen && alreadyOpen !== target) {\n Offcanvas.getInstance(alreadyOpen).hide();\n }\n const data = Offcanvas.getOrCreateInstance(target);\n data.toggle(this);\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$2, () => {\n for (const selector of SelectorEngine.find(OPEN_SELECTOR)) {\n Offcanvas.getOrCreateInstance(selector).show();\n }\n});\nEventHandler.on(window, EVENT_RESIZE, () => {\n for (const element of SelectorEngine.find('[aria-modal][class*=show][class*=offcanvas-]')) {\n if (getComputedStyle(element).position !== 'fixed') {\n Offcanvas.getOrCreateInstance(element).hide();\n }\n }\n});\nenableDismissTrigger(Offcanvas);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Offcanvas);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/sanitizer.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n// js-docs-start allow-list\nconst ARIA_ATTRIBUTE_PATTERN = /^aria-[\\w-]*$/i;\nconst DefaultAllowlist = {\n // Global attributes allowed on any supplied element below.\n '*': ['class', 'dir', 'id', 'lang', 'role', ARIA_ATTRIBUTE_PATTERN],\n a: ['target', 'href', 'title', 'rel'],\n area: [],\n b: [],\n br: [],\n col: [],\n code: [],\n div: [],\n em: [],\n hr: [],\n h1: [],\n h2: [],\n h3: [],\n h4: [],\n h5: [],\n h6: [],\n i: [],\n img: ['src', 'srcset', 'alt', 'title', 'width', 'height'],\n li: [],\n ol: [],\n p: [],\n pre: [],\n s: [],\n small: [],\n span: [],\n sub: [],\n sup: [],\n strong: [],\n u: [],\n ul: []\n};\n// js-docs-end allow-list\n\nconst uriAttributes = new Set(['background', 'cite', 'href', 'itemtype', 'longdesc', 'poster', 'src', 'xlink:href']);\n\n/**\n * A pattern that recognizes URLs that are safe wrt. XSS in URL navigation\n * contexts.\n *\n * Shout-out to Angular https://github.com/angular/angular/blob/15.2.8/packages/core/src/sanitization/url_sanitizer.ts#L38\n */\n// eslint-disable-next-line unicorn/better-regex\nconst SAFE_URL_PATTERN = /^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i;\nconst allowedAttribute = (attribute, allowedAttributeList) => {\n const attributeName = attribute.nodeName.toLowerCase();\n if (allowedAttributeList.includes(attributeName)) {\n if (uriAttributes.has(attributeName)) {\n return Boolean(SAFE_URL_PATTERN.test(attribute.nodeValue));\n }\n return true;\n }\n\n // Check if a regular expression validates the attribute.\n return allowedAttributeList.filter(attributeRegex => attributeRegex instanceof RegExp).some(regex => regex.test(attributeName));\n};\nfunction sanitizeHtml(unsafeHtml, allowList, sanitizeFunction) {\n if (!unsafeHtml.length) {\n return unsafeHtml;\n }\n if (sanitizeFunction && typeof sanitizeFunction === 'function') {\n return sanitizeFunction(unsafeHtml);\n }\n const domParser = new window.DOMParser();\n const createdDocument = domParser.parseFromString(unsafeHtml, 'text/html');\n const elements = [].concat(...createdDocument.body.querySelectorAll('*'));\n for (const element of elements) {\n const elementName = element.nodeName.toLowerCase();\n if (!Object.keys(allowList).includes(elementName)) {\n element.remove();\n continue;\n }\n const attributeList = [].concat(...element.attributes);\n const allowedAttributes = [].concat(allowList['*'] || [], allowList[elementName] || []);\n for (const attribute of attributeList) {\n if (!allowedAttribute(attribute, allowedAttributes)) {\n element.removeAttribute(attribute.nodeName);\n }\n }\n }\n return createdDocument.body.innerHTML;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/template-factory.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$5 = 'TemplateFactory';\nconst Default$4 = {\n allowList: DefaultAllowlist,\n content: {},\n // { selector : text , selector2 : text2 , }\n extraClass: '',\n html: false,\n sanitize: true,\n sanitizeFn: null,\n template: '
'\n};\nconst DefaultType$4 = {\n allowList: 'object',\n content: 'object',\n extraClass: '(string|function)',\n html: 'boolean',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n template: 'string'\n};\nconst DefaultContentType = {\n entry: '(string|element|function|null)',\n selector: '(string|element)'\n};\n\n/**\n * Class definition\n */\n\nclass TemplateFactory extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n }\n\n // Getters\n static get Default() {\n return Default$4;\n }\n static get DefaultType() {\n return DefaultType$4;\n }\n static get NAME() {\n return NAME$5;\n }\n\n // Public\n getContent() {\n return Object.values(this._config.content).map(config => this._resolvePossibleFunction(config)).filter(Boolean);\n }\n hasContent() {\n return this.getContent().length > 0;\n }\n changeContent(content) {\n this._checkContent(content);\n this._config.content = {\n ...this._config.content,\n ...content\n };\n return this;\n }\n toHtml() {\n const templateWrapper = document.createElement('div');\n templateWrapper.innerHTML = this._maybeSanitize(this._config.template);\n for (const [selector, text] of Object.entries(this._config.content)) {\n this._setContent(templateWrapper, text, selector);\n }\n const template = templateWrapper.children[0];\n const extraClass = this._resolvePossibleFunction(this._config.extraClass);\n if (extraClass) {\n template.classList.add(...extraClass.split(' '));\n }\n return template;\n }\n\n // Private\n _typeCheckConfig(config) {\n super._typeCheckConfig(config);\n this._checkContent(config.content);\n }\n _checkContent(arg) {\n for (const [selector, content] of Object.entries(arg)) {\n super._typeCheckConfig({\n selector,\n entry: content\n }, DefaultContentType);\n }\n }\n _setContent(template, content, selector) {\n const templateElement = SelectorEngine.findOne(selector, template);\n if (!templateElement) {\n return;\n }\n content = this._resolvePossibleFunction(content);\n if (!content) {\n templateElement.remove();\n return;\n }\n if (isElement(content)) {\n this._putElementInTemplate(getElement(content), templateElement);\n return;\n }\n if (this._config.html) {\n templateElement.innerHTML = this._maybeSanitize(content);\n return;\n }\n templateElement.textContent = content;\n }\n _maybeSanitize(arg) {\n return this._config.sanitize ? sanitizeHtml(arg, this._config.allowList, this._config.sanitizeFn) : arg;\n }\n _resolvePossibleFunction(arg) {\n return execute(arg, [this]);\n }\n _putElementInTemplate(element, templateElement) {\n if (this._config.html) {\n templateElement.innerHTML = '';\n templateElement.append(element);\n return;\n }\n templateElement.textContent = element.textContent;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap tooltip.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$4 = 'tooltip';\nconst DISALLOWED_ATTRIBUTES = new Set(['sanitize', 'allowList', 'sanitizeFn']);\nconst CLASS_NAME_FADE$2 = 'fade';\nconst CLASS_NAME_MODAL = 'modal';\nconst CLASS_NAME_SHOW$2 = 'show';\nconst SELECTOR_TOOLTIP_INNER = '.tooltip-inner';\nconst SELECTOR_MODAL = `.${CLASS_NAME_MODAL}`;\nconst EVENT_MODAL_HIDE = 'hide.bs.modal';\nconst TRIGGER_HOVER = 'hover';\nconst TRIGGER_FOCUS = 'focus';\nconst TRIGGER_CLICK = 'click';\nconst TRIGGER_MANUAL = 'manual';\nconst EVENT_HIDE$2 = 'hide';\nconst EVENT_HIDDEN$2 = 'hidden';\nconst EVENT_SHOW$2 = 'show';\nconst EVENT_SHOWN$2 = 'shown';\nconst EVENT_INSERTED = 'inserted';\nconst EVENT_CLICK$1 = 'click';\nconst EVENT_FOCUSIN$1 = 'focusin';\nconst EVENT_FOCUSOUT$1 = 'focusout';\nconst EVENT_MOUSEENTER = 'mouseenter';\nconst EVENT_MOUSELEAVE = 'mouseleave';\nconst AttachmentMap = {\n AUTO: 'auto',\n TOP: 'top',\n RIGHT: isRTL() ? 'left' : 'right',\n BOTTOM: 'bottom',\n LEFT: isRTL() ? 'right' : 'left'\n};\nconst Default$3 = {\n allowList: DefaultAllowlist,\n animation: true,\n boundary: 'clippingParents',\n container: false,\n customClass: '',\n delay: 0,\n fallbackPlacements: ['top', 'right', 'bottom', 'left'],\n html: false,\n offset: [0, 6],\n placement: 'top',\n popperConfig: null,\n sanitize: true,\n sanitizeFn: null,\n selector: false,\n template: '
' + '
' + '
' + '
',\n title: '',\n trigger: 'hover focus'\n};\nconst DefaultType$3 = {\n allowList: 'object',\n animation: 'boolean',\n boundary: '(string|element)',\n container: '(string|element|boolean)',\n customClass: '(string|function)',\n delay: '(number|object)',\n fallbackPlacements: 'array',\n html: 'boolean',\n offset: '(array|string|function)',\n placement: '(string|function)',\n popperConfig: '(null|object|function)',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n selector: '(string|boolean)',\n template: 'string',\n title: '(string|element|function)',\n trigger: 'string'\n};\n\n/**\n * Class definition\n */\n\nclass Tooltip extends BaseComponent {\n constructor(element, config) {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s tooltips require Popper (https://popper.js.org)');\n }\n super(element, config);\n\n // Private\n this._isEnabled = true;\n this._timeout = 0;\n this._isHovered = null;\n this._activeTrigger = {};\n this._popper = null;\n this._templateFactory = null;\n this._newContent = null;\n\n // Protected\n this.tip = null;\n this._setListeners();\n if (!this._config.selector) {\n this._fixTitle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$3;\n }\n static get DefaultType() {\n return DefaultType$3;\n }\n static get NAME() {\n return NAME$4;\n }\n\n // Public\n enable() {\n this._isEnabled = true;\n }\n disable() {\n this._isEnabled = false;\n }\n toggleEnabled() {\n this._isEnabled = !this._isEnabled;\n }\n toggle() {\n if (!this._isEnabled) {\n return;\n }\n this._activeTrigger.click = !this._activeTrigger.click;\n if (this._isShown()) {\n this._leave();\n return;\n }\n this._enter();\n }\n dispose() {\n clearTimeout(this._timeout);\n EventHandler.off(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n if (this._element.getAttribute('data-bs-original-title')) {\n this._element.setAttribute('title', this._element.getAttribute('data-bs-original-title'));\n }\n this._disposePopper();\n super.dispose();\n }\n show() {\n if (this._element.style.display === 'none') {\n throw new Error('Please use show on visible elements');\n }\n if (!(this._isWithContent() && this._isEnabled)) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOW$2));\n const shadowRoot = findShadowRoot(this._element);\n const isInTheDom = (shadowRoot || this._element.ownerDocument.documentElement).contains(this._element);\n if (showEvent.defaultPrevented || !isInTheDom) {\n return;\n }\n\n // TODO: v6 remove this or make it optional\n this._disposePopper();\n const tip = this._getTipElement();\n this._element.setAttribute('aria-describedby', tip.getAttribute('id'));\n const {\n container\n } = this._config;\n if (!this._element.ownerDocument.documentElement.contains(this.tip)) {\n container.append(tip);\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_INSERTED));\n }\n this._popper = this._createPopper(tip);\n tip.classList.add(CLASS_NAME_SHOW$2);\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop);\n }\n }\n const complete = () => {\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOWN$2));\n if (this._isHovered === false) {\n this._leave();\n }\n this._isHovered = false;\n };\n this._queueCallback(complete, this.tip, this._isAnimated());\n }\n hide() {\n if (!this._isShown()) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDE$2));\n if (hideEvent.defaultPrevented) {\n return;\n }\n const tip = this._getTipElement();\n tip.classList.remove(CLASS_NAME_SHOW$2);\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop);\n }\n }\n this._activeTrigger[TRIGGER_CLICK] = false;\n this._activeTrigger[TRIGGER_FOCUS] = false;\n this._activeTrigger[TRIGGER_HOVER] = false;\n this._isHovered = null; // it is a trick to support manual triggering\n\n const complete = () => {\n if (this._isWithActiveTrigger()) {\n return;\n }\n if (!this._isHovered) {\n this._disposePopper();\n }\n this._element.removeAttribute('aria-describedby');\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDDEN$2));\n };\n this._queueCallback(complete, this.tip, this._isAnimated());\n }\n update() {\n if (this._popper) {\n this._popper.update();\n }\n }\n\n // Protected\n _isWithContent() {\n return Boolean(this._getTitle());\n }\n _getTipElement() {\n if (!this.tip) {\n this.tip = this._createTipElement(this._newContent || this._getContentForTemplate());\n }\n return this.tip;\n }\n _createTipElement(content) {\n const tip = this._getTemplateFactory(content).toHtml();\n\n // TODO: remove this check in v6\n if (!tip) {\n return null;\n }\n tip.classList.remove(CLASS_NAME_FADE$2, CLASS_NAME_SHOW$2);\n // TODO: v6 the following can be achieved with CSS only\n tip.classList.add(`bs-${this.constructor.NAME}-auto`);\n const tipId = getUID(this.constructor.NAME).toString();\n tip.setAttribute('id', tipId);\n if (this._isAnimated()) {\n tip.classList.add(CLASS_NAME_FADE$2);\n }\n return tip;\n }\n setContent(content) {\n this._newContent = content;\n if (this._isShown()) {\n this._disposePopper();\n this.show();\n }\n }\n _getTemplateFactory(content) {\n if (this._templateFactory) {\n this._templateFactory.changeContent(content);\n } else {\n this._templateFactory = new TemplateFactory({\n ...this._config,\n // the `content` var has to be after `this._config`\n // to override config.content in case of popover\n content,\n extraClass: this._resolvePossibleFunction(this._config.customClass)\n });\n }\n return this._templateFactory;\n }\n _getContentForTemplate() {\n return {\n [SELECTOR_TOOLTIP_INNER]: this._getTitle()\n };\n }\n _getTitle() {\n return this._resolvePossibleFunction(this._config.title) || this._element.getAttribute('data-bs-original-title');\n }\n\n // Private\n _initializeOnDelegatedTarget(event) {\n return this.constructor.getOrCreateInstance(event.delegateTarget, this._getDelegateConfig());\n }\n _isAnimated() {\n return this._config.animation || this.tip && this.tip.classList.contains(CLASS_NAME_FADE$2);\n }\n _isShown() {\n return this.tip && this.tip.classList.contains(CLASS_NAME_SHOW$2);\n }\n _createPopper(tip) {\n const placement = execute(this._config.placement, [this, tip, this._element]);\n const attachment = AttachmentMap[placement.toUpperCase()];\n return Popper.createPopper(this._element, tip, this._getPopperConfig(attachment));\n }\n _getOffset() {\n const {\n offset\n } = this._config;\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10));\n }\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element);\n }\n return offset;\n }\n _resolvePossibleFunction(arg) {\n return execute(arg, [this._element]);\n }\n _getPopperConfig(attachment) {\n const defaultBsPopperConfig = {\n placement: attachment,\n modifiers: [{\n name: 'flip',\n options: {\n fallbackPlacements: this._config.fallbackPlacements\n }\n }, {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }, {\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n }, {\n name: 'arrow',\n options: {\n element: `.${this.constructor.NAME}-arrow`\n }\n }, {\n name: 'preSetPlacement',\n enabled: true,\n phase: 'beforeMain',\n fn: data => {\n // Pre-set Popper's placement attribute in order to read the arrow sizes properly.\n // Otherwise, Popper mixes up the width and height dimensions since the initial arrow style is for top placement\n this._getTipElement().setAttribute('data-popper-placement', data.state.placement);\n }\n }]\n };\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n };\n }\n _setListeners() {\n const triggers = this._config.trigger.split(' ');\n for (const trigger of triggers) {\n if (trigger === 'click') {\n EventHandler.on(this._element, this.constructor.eventName(EVENT_CLICK$1), this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context.toggle();\n });\n } else if (trigger !== TRIGGER_MANUAL) {\n const eventIn = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSEENTER) : this.constructor.eventName(EVENT_FOCUSIN$1);\n const eventOut = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSELEAVE) : this.constructor.eventName(EVENT_FOCUSOUT$1);\n EventHandler.on(this._element, eventIn, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context._activeTrigger[event.type === 'focusin' ? TRIGGER_FOCUS : TRIGGER_HOVER] = true;\n context._enter();\n });\n EventHandler.on(this._element, eventOut, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context._activeTrigger[event.type === 'focusout' ? TRIGGER_FOCUS : TRIGGER_HOVER] = context._element.contains(event.relatedTarget);\n context._leave();\n });\n }\n }\n this._hideModalHandler = () => {\n if (this._element) {\n this.hide();\n }\n };\n EventHandler.on(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n }\n _fixTitle() {\n const title = this._element.getAttribute('title');\n if (!title) {\n return;\n }\n if (!this._element.getAttribute('aria-label') && !this._element.textContent.trim()) {\n this._element.setAttribute('aria-label', title);\n }\n this._element.setAttribute('data-bs-original-title', title); // DO NOT USE IT. Is only for backwards compatibility\n this._element.removeAttribute('title');\n }\n _enter() {\n if (this._isShown() || this._isHovered) {\n this._isHovered = true;\n return;\n }\n this._isHovered = true;\n this._setTimeout(() => {\n if (this._isHovered) {\n this.show();\n }\n }, this._config.delay.show);\n }\n _leave() {\n if (this._isWithActiveTrigger()) {\n return;\n }\n this._isHovered = false;\n this._setTimeout(() => {\n if (!this._isHovered) {\n this.hide();\n }\n }, this._config.delay.hide);\n }\n _setTimeout(handler, timeout) {\n clearTimeout(this._timeout);\n this._timeout = setTimeout(handler, timeout);\n }\n _isWithActiveTrigger() {\n return Object.values(this._activeTrigger).includes(true);\n }\n _getConfig(config) {\n const dataAttributes = Manipulator.getDataAttributes(this._element);\n for (const dataAttribute of Object.keys(dataAttributes)) {\n if (DISALLOWED_ATTRIBUTES.has(dataAttribute)) {\n delete dataAttributes[dataAttribute];\n }\n }\n config = {\n ...dataAttributes,\n ...(typeof config === 'object' && config ? config : {})\n };\n config = this._mergeConfigObj(config);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n _configAfterMerge(config) {\n config.container = config.container === false ? document.body : getElement(config.container);\n if (typeof config.delay === 'number') {\n config.delay = {\n show: config.delay,\n hide: config.delay\n };\n }\n if (typeof config.title === 'number') {\n config.title = config.title.toString();\n }\n if (typeof config.content === 'number') {\n config.content = config.content.toString();\n }\n return config;\n }\n _getDelegateConfig() {\n const config = {};\n for (const [key, value] of Object.entries(this._config)) {\n if (this.constructor.Default[key] !== value) {\n config[key] = value;\n }\n }\n config.selector = false;\n config.trigger = 'manual';\n\n // In the future can be replaced with:\n // const keysWithDifferentValues = Object.entries(this._config).filter(entry => this.constructor.Default[entry[0]] !== this._config[entry[0]])\n // `Object.fromEntries(keysWithDifferentValues)`\n return config;\n }\n _disposePopper() {\n if (this._popper) {\n this._popper.destroy();\n this._popper = null;\n }\n if (this.tip) {\n this.tip.remove();\n this.tip = null;\n }\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Tooltip.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Tooltip);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap popover.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$3 = 'popover';\nconst SELECTOR_TITLE = '.popover-header';\nconst SELECTOR_CONTENT = '.popover-body';\nconst Default$2 = {\n ...Tooltip.Default,\n content: '',\n offset: [0, 8],\n placement: 'right',\n template: '
' + '
' + '

' + '
' + '
',\n trigger: 'click'\n};\nconst DefaultType$2 = {\n ...Tooltip.DefaultType,\n content: '(null|string|element|function)'\n};\n\n/**\n * Class definition\n */\n\nclass Popover extends Tooltip {\n // Getters\n static get Default() {\n return Default$2;\n }\n static get DefaultType() {\n return DefaultType$2;\n }\n static get NAME() {\n return NAME$3;\n }\n\n // Overrides\n _isWithContent() {\n return this._getTitle() || this._getContent();\n }\n\n // Private\n _getContentForTemplate() {\n return {\n [SELECTOR_TITLE]: this._getTitle(),\n [SELECTOR_CONTENT]: this._getContent()\n };\n }\n _getContent() {\n return this._resolvePossibleFunction(this._config.content);\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Popover.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Popover);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap scrollspy.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$2 = 'scrollspy';\nconst DATA_KEY$2 = 'bs.scrollspy';\nconst EVENT_KEY$2 = `.${DATA_KEY$2}`;\nconst DATA_API_KEY = '.data-api';\nconst EVENT_ACTIVATE = `activate${EVENT_KEY$2}`;\nconst EVENT_CLICK = `click${EVENT_KEY$2}`;\nconst EVENT_LOAD_DATA_API$1 = `load${EVENT_KEY$2}${DATA_API_KEY}`;\nconst CLASS_NAME_DROPDOWN_ITEM = 'dropdown-item';\nconst CLASS_NAME_ACTIVE$1 = 'active';\nconst SELECTOR_DATA_SPY = '[data-bs-spy=\"scroll\"]';\nconst SELECTOR_TARGET_LINKS = '[href]';\nconst SELECTOR_NAV_LIST_GROUP = '.nav, .list-group';\nconst SELECTOR_NAV_LINKS = '.nav-link';\nconst SELECTOR_NAV_ITEMS = '.nav-item';\nconst SELECTOR_LIST_ITEMS = '.list-group-item';\nconst SELECTOR_LINK_ITEMS = `${SELECTOR_NAV_LINKS}, ${SELECTOR_NAV_ITEMS} > ${SELECTOR_NAV_LINKS}, ${SELECTOR_LIST_ITEMS}`;\nconst SELECTOR_DROPDOWN = '.dropdown';\nconst SELECTOR_DROPDOWN_TOGGLE$1 = '.dropdown-toggle';\nconst Default$1 = {\n offset: null,\n // TODO: v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: '0px 0px -25%',\n smoothScroll: false,\n target: null,\n threshold: [0.1, 0.5, 1]\n};\nconst DefaultType$1 = {\n offset: '(number|null)',\n // TODO v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: 'string',\n smoothScroll: 'boolean',\n target: 'element',\n threshold: 'array'\n};\n\n/**\n * Class definition\n */\n\nclass ScrollSpy extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n\n // this._element is the observablesContainer and config.target the menu links wrapper\n this._targetLinks = new Map();\n this._observableSections = new Map();\n this._rootElement = getComputedStyle(this._element).overflowY === 'visible' ? null : this._element;\n this._activeTarget = null;\n this._observer = null;\n this._previousScrollData = {\n visibleEntryTop: 0,\n parentScrollTop: 0\n };\n this.refresh(); // initialize\n }\n\n // Getters\n static get Default() {\n return Default$1;\n }\n static get DefaultType() {\n return DefaultType$1;\n }\n static get NAME() {\n return NAME$2;\n }\n\n // Public\n refresh() {\n this._initializeTargetsAndObservables();\n this._maybeEnableSmoothScroll();\n if (this._observer) {\n this._observer.disconnect();\n } else {\n this._observer = this._getNewObserver();\n }\n for (const section of this._observableSections.values()) {\n this._observer.observe(section);\n }\n }\n dispose() {\n this._observer.disconnect();\n super.dispose();\n }\n\n // Private\n _configAfterMerge(config) {\n // TODO: on v6 target should be given explicitly & remove the {target: 'ss-target'} case\n config.target = getElement(config.target) || document.body;\n\n // TODO: v6 Only for backwards compatibility reasons. Use rootMargin only\n config.rootMargin = config.offset ? `${config.offset}px 0px -30%` : config.rootMargin;\n if (typeof config.threshold === 'string') {\n config.threshold = config.threshold.split(',').map(value => Number.parseFloat(value));\n }\n return config;\n }\n _maybeEnableSmoothScroll() {\n if (!this._config.smoothScroll) {\n return;\n }\n\n // unregister any previous listeners\n EventHandler.off(this._config.target, EVENT_CLICK);\n EventHandler.on(this._config.target, EVENT_CLICK, SELECTOR_TARGET_LINKS, event => {\n const observableSection = this._observableSections.get(event.target.hash);\n if (observableSection) {\n event.preventDefault();\n const root = this._rootElement || window;\n const height = observableSection.offsetTop - this._element.offsetTop;\n if (root.scrollTo) {\n root.scrollTo({\n top: height,\n behavior: 'smooth'\n });\n return;\n }\n\n // Chrome 60 doesn't support `scrollTo`\n root.scrollTop = height;\n }\n });\n }\n _getNewObserver() {\n const options = {\n root: this._rootElement,\n threshold: this._config.threshold,\n rootMargin: this._config.rootMargin\n };\n return new IntersectionObserver(entries => this._observerCallback(entries), options);\n }\n\n // The logic of selection\n _observerCallback(entries) {\n const targetElement = entry => this._targetLinks.get(`#${entry.target.id}`);\n const activate = entry => {\n this._previousScrollData.visibleEntryTop = entry.target.offsetTop;\n this._process(targetElement(entry));\n };\n const parentScrollTop = (this._rootElement || document.documentElement).scrollTop;\n const userScrollsDown = parentScrollTop >= this._previousScrollData.parentScrollTop;\n this._previousScrollData.parentScrollTop = parentScrollTop;\n for (const entry of entries) {\n if (!entry.isIntersecting) {\n this._activeTarget = null;\n this._clearActiveClass(targetElement(entry));\n continue;\n }\n const entryIsLowerThanPrevious = entry.target.offsetTop >= this._previousScrollData.visibleEntryTop;\n // if we are scrolling down, pick the bigger offsetTop\n if (userScrollsDown && entryIsLowerThanPrevious) {\n activate(entry);\n // if parent isn't scrolled, let's keep the first visible item, breaking the iteration\n if (!parentScrollTop) {\n return;\n }\n continue;\n }\n\n // if we are scrolling up, pick the smallest offsetTop\n if (!userScrollsDown && !entryIsLowerThanPrevious) {\n activate(entry);\n }\n }\n }\n _initializeTargetsAndObservables() {\n this._targetLinks = new Map();\n this._observableSections = new Map();\n const targetLinks = SelectorEngine.find(SELECTOR_TARGET_LINKS, this._config.target);\n for (const anchor of targetLinks) {\n // ensure that the anchor has an id and is not disabled\n if (!anchor.hash || isDisabled(anchor)) {\n continue;\n }\n const observableSection = SelectorEngine.findOne(decodeURI(anchor.hash), this._element);\n\n // ensure that the observableSection exists & is visible\n if (isVisible(observableSection)) {\n this._targetLinks.set(decodeURI(anchor.hash), anchor);\n this._observableSections.set(anchor.hash, observableSection);\n }\n }\n }\n _process(target) {\n if (this._activeTarget === target) {\n return;\n }\n this._clearActiveClass(this._config.target);\n this._activeTarget = target;\n target.classList.add(CLASS_NAME_ACTIVE$1);\n this._activateParents(target);\n EventHandler.trigger(this._element, EVENT_ACTIVATE, {\n relatedTarget: target\n });\n }\n _activateParents(target) {\n // Activate dropdown parents\n if (target.classList.contains(CLASS_NAME_DROPDOWN_ITEM)) {\n SelectorEngine.findOne(SELECTOR_DROPDOWN_TOGGLE$1, target.closest(SELECTOR_DROPDOWN)).classList.add(CLASS_NAME_ACTIVE$1);\n return;\n }\n for (const listGroup of SelectorEngine.parents(target, SELECTOR_NAV_LIST_GROUP)) {\n // Set triggered links parents as active\n // With both
    and