From 8d2d98c6b5aaade704f1b072174cb1609872f585 Mon Sep 17 00:00:00 2001 From: Samuel Jackson Date: Thu, 15 Aug 2024 13:13:36 +0100 Subject: [PATCH 1/8] Remove segfault handling and add jobscripts --- README.md | 24 +++++++++++++++++++++--- jobs/ingest.csd3.slurm.sh | 23 +++++++++++++++++++++++ jobs/metadata.csd3.slurm.sh | 22 ++++++++++++++++++++++ src/main.py | 2 +- src/mast.py | 21 --------------------- src/task.py | 7 +++++++ 6 files changed, 74 insertions(+), 25 deletions(-) create mode 100644 jobs/ingest.csd3.slurm.sh create mode 100644 jobs/metadata.csd3.slurm.sh diff --git a/README.md b/README.md index d8cfb50..ec6f3a9 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,7 @@ ### FAIR MAST Data Ingestion -## Installation on CSD3 +## Running on CSD3 +### Installation on CSD3 After logging into your CSD3 account (on Icelake node), first load the correct Python module: @@ -45,7 +46,23 @@ source ~/rds/rds-ukaea-mast-sPGbyCAPsJI/uda-ssl.sh You should now be able to run the following commands. -## Local Ingestion +### Submitting runs on CSD3 + +1. First submit a job to collect all the metadata: + +```sh +qsub ./jobs/metadata.csd3.slurm.sh +``` + +2. Then submit an ingestion job + +```sh +qsub ./jobs/ingest.csd3.slurm.sh campaign_shots/tiny_campaign.csv s3://mast/test/shots/ amc +``` + +## Manually Running Ingestor + +### Local Ingestion The following section details how to ingest data into a local folder on freia with UDA. @@ -61,7 +78,7 @@ mpirun -np 16 python3 -m src.main data/local campaign_shots/tiny_campaign.csv -- Files will be output in the NetCDF format to `data/local`. -## Ingestion to S3 +### Ingestion to S3 The following section details how to ingest data into the s3 storage on freia with UDA. @@ -80,3 +97,4 @@ mpirun -np 16 python3 -m src.main data/local campaign_shots/tiny_campaign.csv -- ``` This will submit a job to the freia job queue that will ingest all of the shots in the tiny campaign and push them to the s3 bucket. + diff --git a/jobs/ingest.csd3.slurm.sh b/jobs/ingest.csd3.slurm.sh new file mode 100644 index 0000000..b5747eb --- /dev/null +++ b/jobs/ingest.csd3.slurm.sh @@ -0,0 +1,23 @@ +#!/bin/bash +#SBATCH -A UKAEA-AP002-CPU +#SBATCH -p icelake +#SBATCH --job-name=fair-mast-ingest +#SBATCH --output=fair-mast-ingest_%A.out +#SBATCH --time=5:00:00 +#SBATCH --mem=256G +#SBATCH --ntasks=128 +#SBATCH -N 2 + + +summary_file=$1 +bucket_path=$2 +num_workers=$SLURM_NTASKS + +random_string=$(head /dev/urandom | tr -dc A-Za-z0-9 | head -c 16) +temp_dir="/rds/project/rds-sPGbyCAPsJI/local_cache/$random_string" +metadata_dir="/rds/project/rds-sPGbyCAPsJI/data/uda" + +source /rds/project/rds-sPGbyCAPsJI/uda-ssl.sh + +mpirun -np $num_workers \ + python3 -m src.main $temp_dir $summary_file --metadata_dir $metadata_dir --bucket_path $bucket_path --upload --force --source_names ${@:3} diff --git a/jobs/metadata.csd3.slurm.sh b/jobs/metadata.csd3.slurm.sh new file mode 100644 index 0000000..a67556b --- /dev/null +++ b/jobs/metadata.csd3.slurm.sh @@ -0,0 +1,22 @@ +#!/bin/bash +#SBATCH -A UKAEA-AP002-CPU +#SBATCH -p icelake +#SBATCH --job-name=fair-mast-ingest +#SBATCH --output=%A_%a.out +#SBATCH --time=0:20:00 +#SBATCH --mem=60G +#SBATCH --ntasks=128 +#SBATCH -N 2 + +num_workers=$SLURM_NTASKS + +uda_path="/rds/project/rds-sPGbyCAPsJI/data/uda" +source /rds/project/rds-sPGbyCAPsJI/uda-ssl.sh + +# Parse Signal and Source metadata from UDA +mpirun -n $num_workers python3 -m src.create_uda_metadata $uda_path campaign_shots/M9.csv +mpirun -n $num_workers python3 -m src.create_uda_metadata $uda_path campaign_shots/M8.csv +mpirun -n $num_workers python3 -m src.create_uda_metadata $uda_path campaign_shots/M7.csv +mpirun -n $num_workers python3 -m src.create_uda_metadata $uda_path campaign_shots/M6.csv +mpirun -n $num_workers python3 -m src.create_uda_metadata $uda_path campaign_shots/M5.csv + diff --git a/src/main.py b/src/main.py index 5e907a3..a390782 100644 --- a/src/main.py +++ b/src/main.py @@ -27,7 +27,7 @@ def main(): parser.add_argument("--force", action="store_true") parser.add_argument("--signal_names", nargs="*", default=[]) parser.add_argument("--source_names", nargs="*", default=[]) - parser.add_argument("--file_format", choices=['zarr', 'nc', 'h5']) + parser.add_argument("--file_format", choices=['zarr', 'nc', 'h5'], default='zarr') parser.add_argument("--facility", choices=['MAST', 'MASTU'], default='MAST') args = parser.parse_args() diff --git a/src/mast.py b/src/mast.py index d91790d..af67459 100644 --- a/src/mast.py +++ b/src/mast.py @@ -156,27 +156,6 @@ def get_signal(self, shot_num: int, name: str, format: str) -> xr.Dataset: else: signal_name = name - # Pull the signal on a seperate process first. - # Sometimes this segfaults, so first we need to check that we can pull it safely - # To do this we pull the signal on a serperate process and check the error code. - def _get_signal(signal_name, shot_num): - client = self._get_client() - try: - client.get(signal_name, shot_num) - except pyuda.ServerException: - pass - - p = Process(target=_get_signal, args=(signal_name, shot_num)) - p.start() - p.join() - code = p.exitcode - - if code < 0: - raise RuntimeError( - f"Failed to get data for {signal_name}/{shot_num}. Possible segfault with exitcode: {code}" - ) - - # Now we know it is safe to access the signal and we will not get a segfault signal = client.get(signal_name, shot_num) dataset = self._convert_signal_to_dataset(name, signal) dataset.attrs["shot_id"] = shot_num diff --git a/src/task.py b/src/task.py index 2cafde5..bb234bd 100644 --- a/src/task.py +++ b/src/task.py @@ -35,7 +35,12 @@ def __init__(self, local_file: Path, config: UploadConfig): def __call__(self): logging.info(f"Uploading {self.local_file} to {self.config.url}") + + if not Path(self.config.credentials_file).exists(): + raise RuntimeError(f"Credentials file {self.config.credentials_file} does not exist!") + env = os.environ.copy() + args = [ "s5cmd", "--credentials-file", @@ -48,7 +53,9 @@ def __call__(self): str(self.local_file), self.config.url, ] + logging.debug(' ' .join(args)) + subprocess.run( args, stdout=subprocess.DEVNULL, From bf334b7cbe0d949f7a40fea82d68984cf6cb1409 Mon Sep 17 00:00:00 2001 From: Samuel Jackson Date: Thu, 15 Aug 2024 13:20:54 +0100 Subject: [PATCH 2/8] Fix for ruff --- src/mast.py | 1 - src/workflow.py | 6 ++---- 2 files changed, 2 insertions(+), 5 deletions(-) diff --git a/src/mast.py b/src/mast.py index af67459..99e8a74 100644 --- a/src/mast.py +++ b/src/mast.py @@ -1,5 +1,4 @@ import re -from multiprocessing import Process import typing as t import numpy as np import xarray as xr diff --git a/src/workflow.py b/src/workflow.py index a41737d..0836718 100644 --- a/src/workflow.py +++ b/src/workflow.py @@ -107,8 +107,6 @@ def __init__( def __call__(self, shot: int): self.data_dir.mkdir(exist_ok=True, parents=True) - local_path = self.data_dir / f"{shot}.{self.file_format}" - create = CreateDatasetTask( self.metadata_dir, @@ -123,7 +121,7 @@ def __call__(self, shot: int): try: create() except Exception as e: - import traceback; traceback.print_exc(); + import traceback print(traceback.format_exc()) logging.error(f"Failed to run workflow with error {type(e)}: {e}") @@ -145,7 +143,7 @@ def run_workflows(self, shot_list: list[int], parallel=True): def _run_workflows_serial(self, shot_list: list[int]): n = len(shot_list) for i, shot in enumerate(shot_list): - result = self.workflow(shot) + self.workflow(shot) logging.info(f"Done shot {i+1}/{n} = {(i+1)/n*100:.2f}%") def _run_workflows_parallel(self, shot_list: list[int]): From 168814393eaf8c3431ab59217c1e5b28f63f5867 Mon Sep 17 00:00:00 2001 From: Samuel Jackson Date: Thu, 15 Aug 2024 13:37:51 +0100 Subject: [PATCH 3/8] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 17c48fc..919055e 100644 --- a/README.md +++ b/README.md @@ -51,13 +51,13 @@ You should now be able to run the following commands. 1. First submit a job to collect all the metadata: ```sh -qsub ./jobs/metadata.csd3.slurm.sh +sbatch ./jobs/metadata.csd3.slurm.sh ``` 2. Then submit an ingestion job ```sh -qsub ./jobs/ingest.csd3.slurm.sh campaign_shots/tiny_campaign.csv s3://mast/test/shots/ amc +sbatch ./jobs/ingest.csd3.slurm.sh campaign_shots/tiny_campaign.csv s3://mast/test/shots/ amc ``` ## Manually Running Ingestor From c1b4e77ef6cbe526afea2e58c0113f6cd4e90adc Mon Sep 17 00:00:00 2001 From: Samuel Jackson Date: Thu, 15 Aug 2024 13:59:41 +0100 Subject: [PATCH 4/8] remove notebook --- notebooks/signal_summary.ipynb | 733 --------------------------------- 1 file changed, 733 deletions(-) delete mode 100644 notebooks/signal_summary.ipynb diff --git a/notebooks/signal_summary.ipynb b/notebooks/signal_summary.ipynb deleted file mode 100644 index 03ae0cc..0000000 --- a/notebooks/signal_summary.ipynb +++ /dev/null @@ -1,733 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 221, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": "/*! jQuery v3.6.0 | (c) OpenJS Foundation and other contributors | 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shot_numsnameurishaperanksignal_statussource_aliasunitsdescriptionlabeldimensions
Loading... (need help?)
\n", - "\n", - "
\n" - ], - "text/plain": [ - " shot_nums name \\\n", - "0 28617 ABM_CALIB_SHOT \n", - "1 28618 ABM_CALIB_SHOT \n", - "2 28619 ABM_CALIB_SHOT \n", - "3 28620 ABM_CALIB_SHOT \n", - "4 28621 ABM_CALIB_SHOT \n", - "... ... ... \n", - "1290907 30467 ESX_UPPER_INV_RADIUS \n", - "1290908 30468 ESX_UPPER_INV_RADIUS \n", - "1290909 30469 ESX_UPPER_INV_RADIUS \n", - "1290910 30470 ESX_UPPER_INV_RADIUS \n", - "1290911 30471 ESX_UPPER_INV_RADIUS \n", - "\n", - " uri shape rank \\\n", - "0 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [1] 1 \n", - "1 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [1] 1 \n", - "2 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [1] 1 \n", - "3 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [1] 1 \n", - "4 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [1] 1 \n", - "... ... ... ... \n", - "1290907 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [2] 1 \n", - "1290908 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [2] 1 \n", - "1290909 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [2] 1 \n", - "1290910 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [2] 1 \n", - "1290911 /home/ir-jack5/rds/rds-ukaea-mast-sPGbyCAPsJI/... [2] 1 \n", - "\n", - " signal_status source_alias units \\\n", - "0 1 abm \n", - "1 1 abm \n", - "2 1 abm \n", - "3 1 abm \n", - "4 1 abm \n", - "... ... ... ... \n", - "1290907 1 esx cm \n", - "1290908 1 esx cm \n", - "1290909 1 esx cm \n", - "1290910 1 esx cm \n", - "1290911 1 esx cm \n", - "\n", - " description label dimensions \n", - "0 Shot used for calibration (obsolete) Calibration Shot [time] \n", - "1 Shot used for calibration (obsolete) Calibration Shot [time] \n", - "2 Shot used for calibration (obsolete) Calibration Shot [time] \n", - "3 Shot used for calibration (obsolete) Calibration Shot [time] \n", - "4 Shot used for calibration (obsolete) Calibration Shot [time] \n", - "... ... ... ... \n", - "1290907 cm [time] \n", - "1290908 cm [time] \n", - "1290909 cm [time] \n", - "1290910 cm [time] \n", - "1290911 cm [time] \n", - "\n", - "[1290912 rows x 11 columns]" - ] - }, - "execution_count": 212, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df = pd.read_parquet('~/mast-data/raw/sample_summary_metadata.parquet')\n", - "df" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Overview of shapes & ranks" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 84, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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"ALP_OUTER_UP_R 2\n", - "ALP_OUTER_UP_RAW_VFLOAT 12\n", - "ALP_OUTER_UP_TE 12\n", - "ALP_OUTER_UP_TIME 10\n", - "ALP_OUTER_UP_TIMEMID 12\n", - "ALP_OUTER_UP_VFLOAT 12\n", - "ALP_OUTER_UP_Z 2\n", - "AMS_ACOEFF 7\n", - "AMS_CH 7\n", - "AMS_COSBEAM 7\n", - "AMS_CPF 7\n", - "AMS_CPFNOISE 7\n", - "AMS_CWL 7\n", - "AMS_FILTERPN 7\n", - "AMS_FWHM 7\n", - "AMS_GAMMA 7\n", - "AMS_GAMMANOISE 7\n", - "AMS_LPF 7\n", - "AMS_LPFNOISE 7\n", - "AMS_MD 7\n", - "AMS_OFFSET 7\n", - "AMS_PHASE1 7\n", - "AMS_PHASE2 7\n", - "AMS_PITCHA 7\n", - "AMS_PITCHANOISE 7\n", - "AMS_RETAR1 7\n", - "AMS_RETAR2 7\n", - "AMS_RPOS 7\n", - "AMS_S0 7\n", - "AMS_S0NOISE 7\n", - "AMS_S1 7\n", - "AMS_S1NOISE 7\n", - "AMS_S2 7\n", - "AMS_S2NOISE 7\n", - "AMS_S3 7\n", - "AMS_S3NOISE 7\n", - "AMS_TRANS 7\n", - "AMS_VX0 7\n", - "AMS_VY0 7\n", - "ESM_R_LARMOR_MULTI 2\n", - "ESM_V_ION_MULTI 2\n", - "Name: size, dtype: int64" - ] - }, - "execution_count": 215, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "shapes = df[['name', 'shape']]\n", - "shapes.loc[:, 'shape'] = shapes['shape'].map(lambda x: tuple(x)[1:])\n", - "shapes = shapes.drop_duplicates()\n", - "\n", - "shapes = shapes.groupby('name').size()\n", - "shapes.name = 'size'\n", - "# shapes.name = 'num'\n", - "sns.histplot(shapes)\n", - "shapes.loc[shapes > 1]" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Overview of signal status" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Get a list of the units" - ] - }, - { - "cell_type": "code", - "execution_count": 225, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
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namelabeldescriptionold_unitsnew_unitslong_name
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\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ureg = UnitRegistry()\n", - "ureg.define('@alias tesla = Tesla')\n", - "ureg.define('@alias watt = Watts')\n", - "\n", - "unit_map = json.load(Path('~/mast-data/mappings/units.json').expanduser().open('r'))\n", - "\n", - "def parse_unit(name, mode='compact'):\n", - " name = unit_map[name] if name in unit_map else name\n", - " try:\n", - " quantity = ureg.parse_expression(name)\n", - " if mode == 'compact':\n", - " return \"{:~C}\".format(quantity.u)\n", - " else:\n", - " return \"{}\".format(quantity.u)\n", - " except:\n", - " return ''\n", - "\n", - "units_summary = df[['name', 'label', 'description', 'units']].drop_duplicates().reset_index(drop=True)\n", - "units_summary['description'] = units_summary.description.astype(str)\n", - "units_summary = units_summary.rename(dict(units='old_units'), axis=1)\n", - "units_summary['new_units'] = units_summary['old_units'].map(parse_unit)\n", - "units_summary['long_name'] = units_summary['old_units'].map(partial(parse_unit, mode='verbose'))\n", - "units_summary.to_parquet('~/mast-data/mappings/units.parquet')\n", - "units_summary\n", - "show(units_summary, style=\"table-layout:auto;width:50%;float:left\")" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Look at the unique dimension names, see what we can combine:" - ] - }, - { - "cell_type": "code", - "execution_count": 190, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
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nameold_dimensionnew_dimensions
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\n" - ], - "text/plain": [ - " name old_dimension new_dimensions\n", - "0 ABM_CALIB_SHOT time time\n", - "1 ABM_CHANNEL_STATUS time time\n", - "2 ABM_CHANNEL_STATUS dim_0 dim_0\n", - "3 ABM_CHANNEL_TYPE time time\n", - "4 ABM_CHANNEL_TYPE dim_0 dim_0\n", - "... ... ... ...\n", - "1675 ESX_LOWER_INV_RADIUS time time\n", - "1676 ESX_PASSNUMBER time time\n", - "1677 ESX_STATUS time time\n", - "1678 ESX_UPPER_INV_PSI time time\n", - "1679 ESX_UPPER_INV_RADIUS time time\n", - "\n", - "[1680 rows x 3 columns]" - ] - }, - "execution_count": 190, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dims = df[['name', 'dimensions']]\n", - "dims.loc[:, 'dimensions'] = dims.dimensions.map(lambda x: tuple(x))\n", - "dims = dims.drop_duplicates()\n", - "dim_names = []\n", - "for key, item in dims.iterrows():\n", - " for dim in item.dimensions:\n", - " dim_names.append((item['name'], dim, dim))\n", - "\n", - "dim_map = json.load(Path('~/mast-data/mappings/dimensions.json').expanduser().open('r'))\n", - "\n", - "def parse_dimensions(dim_name):\n", - " return dim_map.get(dim_name, dim_name)\n", - "\n", - "dims = pd.DataFrame(dim_names, columns=['name', 'old_dimension', 'new_dimensions'])\n", - "dims['new_dimensions'] = dims['new_dimensions'].map(parse_dimensions)\n", - "dims.to_parquet('~/mast-data/mappings/dimensions.parquet')\n", - "dims" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mast", - "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": "3.9.16" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} From 942ed46ae56a0c1f4f60f757c91204f244d03c25 Mon Sep 17 00:00:00 2001 From: Samuel Jackson Date: Thu, 15 Aug 2024 14:06:03 +0100 Subject: [PATCH 5/8] Remove notebooks --- notebooks/data-structure-report.ipynb | 5510 - notebooks/images/schema.png | Bin 43392 -> 0 bytes notebooks/images/website1.PNG | Bin 221282 -> 0 bytes notebooks/images/website2.PNG | Bin 88454 -> 0 bytes notebooks/map_signals.ipynb | 124338 ----------------------- notebooks/sample_hdf.ipynb | 2634 - 6 files changed, 132482 deletions(-) delete mode 100644 notebooks/data-structure-report.ipynb delete mode 100644 notebooks/images/schema.png delete mode 100644 notebooks/images/website1.PNG delete mode 100644 notebooks/images/website2.PNG delete mode 100644 notebooks/map_signals.ipynb delete mode 100644 notebooks/sample_hdf.ipynb diff --git a/notebooks/data-structure-report.ipynb b/notebooks/data-structure-report.ipynb deleted file mode 100644 index 26706e6..0000000 --- a/notebooks/data-structure-report.ipynb +++ /dev/null @@ -1,5510 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "41361f6c", - "metadata": { - "toc": true - }, - "source": [ - "

Table of Contents

\n", - "" - ] - }, - { - "cell_type": "markdown", - "id": "7e7d5c7f-d8ef-400b-9162-b90965ed864c", - "metadata": {}, - "source": [ - "# Introduction" - ] - }, - { - "cell_type": "markdown", - "id": "694f8456-f8cc-45a7-b4d0-3ca03b06a9b5", - "metadata": {}, - "source": [ - "This document will describe a general overview of the MAST dataset, particularly its data structure. We will access or retrieve the data structure using the Python [UDA](https://users.mastu.ukaea.uk/data-access-and-tools) and [CPF](https://users.mastu.ukaea.uk/sites/default/files/uploads/CPF.pdf) APIs provided by the UKAEA. The Python packages can only be accessed from the UKAEA's internal Linux cluster called Freia. The scope of this document is limited to the data structure we retrieve via these APIs. We shall discuss the MAST data in a separate document.\n", - "\n", - "Each MAST experiment is around 5 GB. Therefore the whole MAST dataset could weigh more than 150 TB. The last experiment was performed on the 27th of September, 2013, with shot number 30473." - ] - }, - { - "cell_type": "markdown", - "id": "e68158df", - "metadata": {}, - "source": [ - "## Conventions used in this report" - ] - }, - { - "cell_type": "markdown", - "id": "c117b452", - "metadata": {}, - "source": [ - "`Code type` " - ] - }, - { - "cell_type": "markdown", - "id": "9f230ab0", - "metadata": {}, - "source": [ - "denotion is used to emphasize variables, objects or classes (eg. `Signal` would refer to a signal class)" - ] - }, - { - "cell_type": "markdown", - "id": "fce82927", - "metadata": {}, - "source": [ - "`CODE_TYPE` with capital letters" - ] - }, - { - "cell_type": "markdown", - "id": "64341eaf", - "metadata": {}, - "source": [ - " is used for ListType values: `SOURCE`/`SOURCES`, `SIGNAL`/`SIGNALS`, `SHOT`/`SHOTS`" - ] - }, - { - "cell_type": "markdown", - "id": "39ee1706", - "metadata": {}, - "source": [ - "**Shots** or **Shot**" - ] - }, - { - "cell_type": "markdown", - "id": "f1f4c2e7", - "metadata": {}, - "source": [ - "is used to refer to a single experiment" - ] - }, - { - "cell_type": "markdown", - "id": "5cfcc0c8", - "metadata": {}, - "source": [ - "**_Bold italics_**" - ] - }, - { - "cell_type": "markdown", - "id": "623fd87d", - "metadata": {}, - "source": [ - "is used for `SOURCE` types : **_Raw_**, **_Analysed_**, **_Image_**" - ] - }, - { - "cell_type": "markdown", - "id": "659e7450", - "metadata": {}, - "source": [ - "*Italics*" - ] - }, - { - "cell_type": "markdown", - "id": "e74a2922", - "metadata": {}, - "source": [ - "is used for `SOURCE` formats, such as *TIF*, *IPX*, *IDA3* etc." - ] - }, - { - "cell_type": "markdown", - "id": "644e70fd", - "metadata": {}, - "source": [ - "# Overview of Dataset" - ] - }, - { - "cell_type": "markdown", - "id": "96282397-ed50-42b9-8e5a-25a509e55d85", - "metadata": {}, - "source": [ - "## Web UI" - ] - }, - { - "cell_type": "markdown", - "id": "544bdc4e", - "metadata": {}, - "source": [ - "The UKAEA has developed a [Web UI](https://users.mastu.ukaea.uk/internal/shot/27933) to browse the MAST dataset. Fig. 1 and 2 are screenshots of an example shot and its data from the web link.\n", - " \n", - "

\n", - " \"schema\"\n", - "

\n", - "

\n", - "

Figure 1. Example screenshot showing the source information of the shot number 27933.
\n", - "

\n", - "\n", - "

\n", - " \"schema\"

\n", - "

\n", - "

\n", - "

Figure 2. Example screenshot showing the metadata information of the shot number 27933.
\n", - "

\n" - ] - }, - { - "cell_type": "markdown", - "id": "864655a8", - "metadata": {}, - "source": [ - "
\n", - "Note: We can retrieve more information using the UDA and CPF APIs. We noticed minor inconsistencies with the CPF information displayed in the Web UI.\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "ddc7d2d9", - "metadata": {}, - "source": [ - "

\n", - " \"schema\"\n", - "

\n", - "

\n", - "

Figure 3. A high-level schema.
\n", - " \n", - "

\n", - "\n", - "Each experiment in the dataset is called a **shot**. Fig. 1 illustrates a high-level schema. Each shot (in UDA API defined using enumerator symbol `SHOTS`) consists of sources (`SOURCES`). There are three types of sources:\n", - "1. **_Raw_** - unprocessed data,\n", - "2. **_Analysed_** - processed data, and\n", - "3. **_Image_** - video or image.\n", - "\n", - "The **_Raw_** and **_Analysed_** types of `SOURCES` are also defined additionally as `SIGNALS`. \n", - "\n", - "In the following section, we will use the UDA API and retrieve and discuss an example shot's `SOURCES` and `SIGNALS` information. The metadata information of shots is stored in *CPF* (central physics file) files; we will discuss this in the final section of this document. " - ] - }, - { - "cell_type": "markdown", - "id": "e0bd94ac", - "metadata": {}, - "source": [ - "## Import Python Packages" - ] - }, - { - "cell_type": "markdown", - "id": "3d530c27", - "metadata": {}, - "source": [ - "In this section, we import the required Python, UDA and CPF packages." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "c83d3fb8", - "metadata": {}, - "outputs": [], - "source": [ - "import pyuda\n", - "from mast.mast_client import ListType\n", - "from pycpf import pycpf" - ] - }, - { - "cell_type": "markdown", - "id": "2aee7813", - "metadata": {}, - "source": [ - "Import other relavant Python packages used in this document." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "a554274e", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "from rich import inspect, print" - ] - }, - { - "cell_type": "markdown", - "id": "857fde37", - "metadata": {}, - "source": [ - "Create the `pyuda` client for fetching the data. Please see the UDA document for more details." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "656b22c3", - "metadata": {}, - "outputs": [], - "source": [ - "client = pyuda.Client()\n", - "client.set_property(\"get_meta\", True)" - ] - }, - { - "cell_type": "markdown", - "id": "b27c1bfe", - "metadata": {}, - "source": [ - "# **Shot**" - ] - }, - { - "cell_type": "markdown", - "id": "0e5b2755", - "metadata": {}, - "source": [ - "\n", - "As mentioned earlier, `SHOT` is a single experiment from the MAST dataset. Each shot is assigned a unique number. The numbers are assigned chronologically as the experiments are performed. \n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "e7c488f5", - "metadata": {}, - "source": [ - "
\n", - "Note: Although there are officially more than 30000 shots, there is no information about the shots with a value <11700, which is accessible on the MAST website. Currently, no data from shots <8000 is accessible through UDA API\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "72f7a7f5-a039-411e-b54b-d7923d74bbe0", - "metadata": {}, - "source": [ - "To access a shot and its data, the shot number is required. For example," - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "26f38ec9", - "metadata": {}, - "outputs": [], - "source": [ - "shot_1 = 27933" - ] - }, - { - "cell_type": "markdown", - "id": "20267059", - "metadata": {}, - "source": [ - "The `ListType` defines two enumerator values `SOURCES` and `SIGNALS`. The UDA client takes an enumerator as an argument to fetch the relavant data." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "4b312efb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭────────────────────────────────── <enum 'ListType'> ──────────────────────────────────╮\n",
-       " class ListType(value, names=None, *, module=None, qualname=None, type=None, start=1): \n",
-       "                                                                                       \n",
-       "   SHOTS = <ListType.SHOTS: 3>                                                         \n",
-       " SIGNALS = <ListType.SIGNALS: 1>                                                       \n",
-       " SOURCES = <ListType.SOURCES: 2>                                                       \n",
-       "╰───────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "
\n" - ], - "text/plain": [ - "\u001b[34m╭─\u001b[0m\u001b[34m───────────────────────────────── \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95menum\u001b[0m\u001b[39m \u001b[0m\u001b[32m'ListType'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m ─────────────────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;96mclass \u001b[0m\u001b[1;31mListType\u001b[0m\u001b[1m(\u001b[0mvalue, \u001b[33mnames\u001b[0m=\u001b[3;35mNone\u001b[0m, *, \u001b[33mmodule\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mqualname\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mstart\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m: \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mSHOTS\u001b[0m = \u001b[1m<\u001b[0m\u001b[1;95mListType.SHOTS:\u001b[0m\u001b[39m \u001b[0m\u001b[1;36m3\u001b[0m\u001b[1m>\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mSIGNALS\u001b[0m = \u001b[1m<\u001b[0m\u001b[1;95mListType.SIGNALS:\u001b[0m\u001b[39m \u001b[0m\u001b[1;36m1\u001b[0m\u001b[1m>\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mSOURCES\u001b[0m = \u001b[1m<\u001b[0m\u001b[1;95mListType.SOURCES:\u001b[0m\u001b[39m \u001b[0m\u001b[1;36m2\u001b[0m\u001b[1m>\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m╰───────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "inspect(ListType, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "e36c5e16", - "metadata": {}, - "source": [ - "
\n", - "Note: SHOT is shown as a ListType but it might be an incorrect representation.\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "92d48ac7", - "metadata": {}, - "source": [ - "## Retrieve `SOURCES` of a Shot" - ] - }, - { - "cell_type": "markdown", - "id": "72074f89", - "metadata": {}, - "source": [ - "A shot contains a list of sources (`SOURCES`) as a list or array of `ListData`. For example fetch the list of sources of a shot:" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "d934bc39", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "sources_1 = client.list(ListType.SOURCES, shot_1)" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "b828d7f3-b6fb-4800-a811-cbcfcf64e30a", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Number of sources in shot 27933 = 81\n",
-       "
\n" - ], - "text/plain": [ - "Number of sources in shot \u001b[1;36m27933\u001b[0m = \u001b[1;36m81\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "print(f\"Number of sources in shot {shot_1} = {len(sources_1)}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "eab46f29", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭───── <class 'mast.mast_client.ListData'> ─────╮\n",
-       " ╭───────────────────────────────────────────╮ \n",
-       "  ListData(                                  \n",
-       "  shot=27933,                            \n",
-       "  pass_=0,                               \n",
-       "  status=1,                              \n",
-       "  source_alias='abm',                    \n",
-       "  format='IDA3',                         \n",
-       "  filename='abm0279.33',                 \n",
-       "  type='Analysed',                       \n",
-       "  description='multi-chord bolometers',  \n",
-       "  run_id=-1                              \n",
-       "  )                                          \n",
-       " ╰───────────────────────────────────────────╯ \n",
-       "                                               \n",
-       "  description = 'multi-chord bolometers'       \n",
-       "     filename = 'abm0279.33'                   \n",
-       "       format = 'IDA3'                         \n",
-       "        pass_ = 0                              \n",
-       "       run_id = -1                             \n",
-       "         shot = 27933                          \n",
-       " source_alias = 'abm'                          \n",
-       "       status = 1                              \n",
-       "         type = 'Analysed'                     \n",
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shotpass_statussource_aliasformatfilenametypedescriptionrun_id
02793301abmIDA3abm0279.33Analysedmulti-chord bolometers-1
12793301adaIDA3ada0279.33AnalysedLinear D-Alpha Camera-1
22793301adgIDA3adg0279.33AnalysedPlasma Edge Density gradient from the linear D...-1
32793311agaIDA3aga0279.33Analysedmolecular deuterium pressure, neutral gas pres...-1
42793301agaIDA3aga0279.33Analysedmolecular deuterium pressure, neutral gas pres...-1
..............................
7627933-11xtbIDA3xtb0279.33RawThomson scattering background data-1
7727933-11xtmIDA3xtm0279.33RawEdge Thomson scattering data-1
7827933-11xtpIDA3xtp0279.33RawLangmuir Probes - top-1
7927933-11xycCDFxyc027933.ncRawCore Thomson scattering data-1
8027933-11xyrCDFxyr027933.ncRawReal time Thomson scattering data-1
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81 rows × 9 columns

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" - ], - "text/plain": [ - " shot pass_ status source_alias format filename type \\\n", - "0 27933 0 1 abm IDA3 abm0279.33 Analysed \n", - "1 27933 0 1 ada IDA3 ada0279.33 Analysed \n", - "2 27933 0 1 adg IDA3 adg0279.33 Analysed \n", - "3 27933 1 1 aga IDA3 aga0279.33 Analysed \n", - "4 27933 0 1 aga IDA3 aga0279.33 Analysed \n", - ".. ... ... ... ... ... ... ... \n", - "76 27933 -1 1 xtb IDA3 xtb0279.33 Raw \n", - "77 27933 -1 1 xtm IDA3 xtm0279.33 Raw \n", - "78 27933 -1 1 xtp IDA3 xtp0279.33 Raw \n", - "79 27933 -1 1 xyc CDF xyc027933.nc Raw \n", - "80 27933 -1 1 xyr CDF xyr027933.nc Raw \n", - "\n", - " description run_id \n", - "0 multi-chord bolometers -1 \n", - "1 Linear D-Alpha Camera -1 \n", - "2 Plasma Edge Density gradient from the linear D... -1 \n", - "3 molecular deuterium pressure, neutral gas pres... -1 \n", - "4 molecular deuterium pressure, neutral gas pres... -1 \n", - ".. ... ... \n", - "76 Thomson scattering background data -1 \n", - "77 Edge Thomson scattering data -1 \n", - "78 Langmuir Probes - top -1 \n", - "79 Core Thomson scattering data -1 \n", - "80 Real time Thomson scattering data -1 \n", - "\n", - "[81 rows x 9 columns]" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_1 = pd.DataFrame(sources_1)\n", - "df_1" - ] - }, - { - "cell_type": "markdown", - "id": "9670dc54", - "metadata": { - "tags": [] - }, - "source": [ - "A `SOURCE` attributes are:\n", - "\n", - "* `shot` - the unique number of a `SHOT`\n", - "* `pass_` - for **_Analysed_** type it would mean how many processing iterations it went through, the first - number 0, for **_Raw_** we would see -1\n", - "* `status` - internal data status set by responsible officer:\n", - " * -1 Poor Data: do not use\n", - " * 0 Something is wrong in the Data\n", - " * 1 either **_Raw_** data not checked or **_Analysed_** data quality is Unknown\n", - " * 2 Data has been checked - no known problems\n", - " * 3 Data was validated\n", - "* `source_alias` - three letter alias name, which can be used for a separate source inspection\n", - "* `format` - file format: *IDA3*, *CBF*, *JPG*, *TIF* etc. \n", - "* `filename` - name in the internal data system we don't have access to\n", - "* `type` - e.g., **_Analysed_**, **_Raw_** or **_Image_**\n", - "* `description` - text description of the source\n", - "* `run_id` - [TODO: For Nathan]\n" - ] - }, - { - "cell_type": "markdown", - "id": "c2c8eb71", - "metadata": {}, - "source": [ - "### Source type, format, & alias\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "936d25ed", - "metadata": {}, - "source": [ - "There are three different types of source, e.g., **_Image_**, **_Raw_**, and **_Analysed_**. " - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "95277df0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Source types are {'Raw', 'Analysed', 'Image'}\n",
-       "
\n" - ], - "text/plain": [ - "Source types are \u001b[1m{\u001b[0m\u001b[32m'Raw'\u001b[0m, \u001b[32m'Analysed'\u001b[0m, \u001b[32m'Image'\u001b[0m\u001b[1m}\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "types = set([source.type for source in sources_1 if source.type is not None])\n", - "print(f\"Source types are {types}\")" - ] - }, - { - "cell_type": "markdown", - "id": "888e2518", - "metadata": {}, - "source": [ - "`SOURCES` are saved as numerous formats. For example, the sources of the `shot_1` use the following formats:" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "ee49e967", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
The formats of the sources of shot 27933 are {'CDF', 'IDA3', 'NIDA', 'ASCII', 'IPX', 'TIF'}\n",
-       "
\n" - ], - "text/plain": [ - "The formats of the sources of shot \u001b[1;36m27933\u001b[0m are \u001b[1m{\u001b[0m\u001b[32m'CDF'\u001b[0m, \u001b[32m'IDA3'\u001b[0m, \u001b[32m'NIDA'\u001b[0m, \u001b[32m'ASCII'\u001b[0m, \u001b[32m'IPX'\u001b[0m, \u001b[32m'TIF'\u001b[0m\u001b[1m}\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "formats = set([source.format for source in sources_1 if source.format is not None])\n", - "print(f\"The formats of the sources of shot {shot_1} are {formats}\")" - ] - }, - { - "cell_type": "markdown", - "id": "211ecc4d", - "metadata": {}, - "source": [ - "There are other formats available in different shots. \n", - "\n", - "Some formats are more likely to be used in a certain source types. For example, *JPG*, *IPX* and *TIF* are more likely to be an **_Image_** type, while *IDA3* is **_Analysed_** type." - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "b9a58656-6b59-40c7-82d0-74846db2fec5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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typeformats
0Analysed{IDA3}
1Image{TIF, IPX}
2Raw{CDF, NIDA, ASCII, IDA3}
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" - ], - "text/plain": [ - " type formats\n", - "0 Analysed {IDA3}\n", - "1 Image {TIF, IPX}\n", - "2 Raw {CDF, NIDA, ASCII, IDA3}" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_1.groupby(\"type\", as_index=False).agg(formats=(\"format\", lambda x: set(x)))" - ] - }, - { - "cell_type": "markdown", - "id": "672771c6", - "metadata": {}, - "source": [ - "Aliases use three letter names. Usually, the **_Raw_** types use aliases with first letter `x`, **_Analysed_** use `a`, and **_Image_** use `r`. However, it is not always true. There might be some exceptions, which will be discussed later." - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "edacd996-4c7d-4ab2-812e-96b01d7c3a53", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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typealiases
0Analysed{air, amc, amb, lim, asm, ait, ahx, anu, aga, ...
1Image{rda, rdb, rir, rit, rgb, rba, rbc, rzz, rbb, ...
2Raw{xmp, xim, xlp, xcm, xfi, xpc, xsx, pcs, xmw, ...
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" - ], - "text/plain": [ - " type aliases\n", - "0 Analysed {air, amc, amb, lim, asm, ait, ahx, anu, aga, ...\n", - "1 Image {rda, rdb, rir, rit, rgb, rba, rbc, rzz, rbb, ...\n", - "2 Raw {xmp, xim, xlp, xcm, xfi, xpc, xsx, pcs, xmw, ..." - ] - }, - "execution_count": 46, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_1.groupby(\"type\", as_index=False).agg(aliases=(\"source_alias\", lambda x: set(x)))" - ] - }, - { - "cell_type": "markdown", - "id": "f27ec8c0", - "metadata": {}, - "source": [ - "Below we discuss **_Raw_** and **_Analysed_** sources together, while **_Image_** sources separately. This is due to the former sharing similarities in data access." - ] - }, - { - "cell_type": "markdown", - "id": "b0acec38", - "metadata": {}, - "source": [ - "### **_Raw_** & **_Analysed_** types" - ] - }, - { - "cell_type": "markdown", - "id": "199e85cc", - "metadata": {}, - "source": [ - "The **_Raw_** and **_Analysed_** types have `SOURCE` names and additionally they also have `SIGNAL` names. These are used to access the source `SIGNAL`. UDA uses a class named `Signal` for **_Raw_** and **_Analysed_** type data.\n", - "\n", - "The unanalysed or unprocessed data are categorised as **_Raw_** types. **_Raw_** type data are mostly saved in *CDF* or *IDA3* format. In some cases it is also saved in *NIDA* format (which is an image or video file) and *ASCII* format. These formats are commonly used throughout the whole dataset." - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "c48f7e98-4478-46bc-bb18-2530c4b51a0a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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typeformataliases
0RawASCII{msf}
1RawCDF{xmp, xfi, xsx, rcb, xsm, xyc, xmc, xyr, xms, ...
2RawIDA3{xim, xlp, xcm, xpc, pcs, xtm, xdc, xmd, xax, ...
3RawNIDA{xmw}
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" - ], - "text/plain": [ - " type format aliases\n", - "0 Raw ASCII {msf}\n", - "1 Raw CDF {xmp, xfi, xsx, rcb, xsm, xyc, xmc, xyr, xms, ...\n", - "2 Raw IDA3 {xim, xlp, xcm, xpc, pcs, xtm, xdc, xmd, xax, ...\n", - "3 Raw NIDA {xmw}" - ] - }, - "execution_count": 47, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_1.loc[df_1[\"type\"] == \"Raw\"].groupby([\"type\", \"format\"], as_index=False).agg(\n", - " aliases=(\"source_alias\", lambda x: set(x))\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "078e5472", - "metadata": {}, - "source": [ - "The processed or analysed data are categorised as **_Analysed_** types and they usually use *IDA3* format." - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "b457b371-5520-4933-b88e-f718e7283ad6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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typeformataliases
0AnalysedIDA3{air, amc, amb, lim, asm, ait, ahx, anu, aga, ...
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" - ], - "text/plain": [ - " type format aliases\n", - "0 Analysed IDA3 {air, amc, amb, lim, asm, ait, ahx, anu, aga, ..." - ] - }, - "execution_count": 48, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_1.loc[df_1[\"type\"] == \"Analysed\"].groupby([\"type\", \"format\"], as_index=False).agg(\n", - " aliases=(\"source_alias\", lambda x: set(x))\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "0a7bdd62", - "metadata": {}, - "source": [ - "We also noticed that some shots use *BINARY* format, as demonstrated below." - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "d861c2a6", - "metadata": {}, - "outputs": [], - "source": [ - "shot_2 = 12000\n", - "sources_2 = client.list(ListType.SOURCES, shot_2)\n", - "df_2 = pd.DataFrame(sources_2)" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "e52e45c8-177b-4550-a1b9-966a4a2c1cbe", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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typeformataliases
0RawBINARY{rcb, rts, rcc, rbm, pcs}
1RawIDA3{xim, xlp, xcm, xpc, xsx, xmw, xvs, xtm, xmc, ...
2RawNIDA{rir, xpx}
\n", - "
" - ], - "text/plain": [ - " type format aliases\n", - "0 Raw BINARY {rcb, rts, rcc, rbm, pcs}\n", - "1 Raw IDA3 {xim, xlp, xcm, xpc, xsx, xmw, xvs, xtm, xmc, ...\n", - "2 Raw NIDA {rir, xpx}" - ] - }, - "execution_count": 50, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_2.loc[df_2[\"type\"] == \"Raw\"].groupby([\"type\", \"format\"], as_index=False).agg(\n", - " aliases=(\"source_alias\", lambda x: set(x))\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "19148948", - "metadata": {}, - "source": [ - "Here we can see, there might be exceptions to more commonly used *IDA3*, like *ASCII*. " - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "dc39d538-d89b-4743-ac8f-08089942798d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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typeformataliases
0AnalysedASCII{lim}
1AnalysedIDA3{amc, amb, asm, anu, atm, asj, aga, abm, ane, ...
\n", - "
" - ], - "text/plain": [ - " type format aliases\n", - "0 Analysed ASCII {lim}\n", - "1 Analysed IDA3 {amc, amb, asm, anu, atm, asj, aga, abm, ane, ..." - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_2.loc[df_2[\"type\"] == \"Analysed\"].groupby([\"type\", \"format\"], as_index=False).agg(\n", - " aliases=(\"source_alias\", lambda x: set(x))\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "f8907548", - "metadata": {}, - "source": [ - "It is demonstrated above, using the client, that **_Analysed_** and **_Raw_** types have source names and what they look like. It is also shown that there are particular file formats associated with these types. Data access description using `SIGNAL` names can be found in 3.2 and 3.3." - ] - }, - { - "cell_type": "markdown", - "id": "1fb15ba2-0a85-4ea9-b6af-0e2b187b0168", - "metadata": {}, - "source": [ - "#### Retrieve data (as `SIGNALS` or `Signal`)" - ] - }, - { - "cell_type": "markdown", - "id": "a00e7f1f", - "metadata": {}, - "source": [ - "We can specify the UDA client to fetch the `SIGNALS` of a shot, which will return a list\n", - "A shot contains a list of sources (`SOURCES`) as a list or array of `ListData`. For example fetch the list of sources of a shot:\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "e9e7cf83", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "signals_1 = client.list(ListType.SIGNALS, shot_1)\n", - "# aliases = set([signal.source_alias for signal in signals])" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "e0784f10-0814-49d3-a3e0-cbdff5eaa717", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Number of signals in shot 27933 = 10594\n",
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\n" - ], - "text/plain": [ - "Number of signals in shot \u001b[1;36m27933\u001b[0m = \u001b[1;36m10594\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "print(f\"Number of signals in shot {shot_1} = {len(signals_1)}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "4d87f59e-eb7d-4025-95d9-bb05e6ba7492", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭──────────── <class 'mast.mast_client.ListData'> ────────────╮\n",
-       " ╭─────────────────────────────────────────────────────────╮ \n",
-       "  ListData(                                                \n",
-       "  shot=27933,                                          \n",
-       "  pass_=0,                                             \n",
-       "  signal_name='ABM_CALIB_SHOT',                        \n",
-       "  generic_name='',                                     \n",
-       "  source_alias='abm',                                  \n",
-       "  type='Analysed',                                     \n",
-       "  description='Shot used for calibration (obsolete)',  \n",
-       "  signal_status=1,                                     \n",
-       "  mds_name='\\\\TOP.ANALYSED.ABM:CALIB_SHOT'             \n",
-       "  )                                                        \n",
-       " ╰─────────────────────────────────────────────────────────╯ \n",
-       "                                                             \n",
-       "   description = 'Shot used for calibration (obsolete)'      \n",
-       "  generic_name = ''                                          \n",
-       "      mds_name = '\\\\TOP.ANALYSED.ABM:CALIB_SHOT'             \n",
-       "         pass_ = 0                                           \n",
-       "          shot = 27933                                       \n",
-       "   signal_name = 'ABM_CALIB_SHOT'                            \n",
-       " signal_status = 1                                           \n",
-       "  source_alias = 'abm'                                       \n",
-       "          type = 'Analysed'                                  \n",
-       "╰─────────────────────────────────────────────────────────────╯\n",
-       "
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shotpass_signal_namegeneric_namesource_aliastypedescriptionsignal_statusmds_name
0279330ABM_CALIB_SHOTabmAnalysedShot used for calibration (obsolete)1\\TOP.ANALYSED.ABM:CALIB_SHOT
1279330ABM_CHANNEL_STATUSabmAnalysedFailed = 0, OK = 11\\TOP.ANALYSED.ABM.CHANNEL:STATUS
2279330ABM_CHANNEL_TYPEabmAnalysedChannel type (0 = poloidal, 1 = co-tangential,...1\\TOP.ANALYSED.ABM:CHANNEL_TYPE
3279330ABM_GAINabmAnalysedGain of pre-amplifiers1\\TOP.ANALYSED.ABM:GAIN
4279330ABM_I-BOLabmAnalysedIncident powers (x - channel)1\\TOP.ANALYSED.ABM:I_BOL
..............................
1058927933-1/XYR/RTTExyrRaw1\\TOP.RAW.XYR:RTTE
1059027933-1/XYR/SEGMENT1xyrRaw1\\TOP.RAW.XYR:SEGMENT1
1059127933-1/XYR/SEGMENTTIMExyrRaw1\\TOP.RAW.XYR:SEGMENTTIME
1059227933-1/XYR/SENTTIMExyrRaw1\\TOP.RAW.XYR:SENTTIME
1059327933-1/XYR/TIME1xyrRaw1\\TOP.RAW.XYR:TIME1
\n", - "

10594 rows × 9 columns

\n", - "
" - ], - "text/plain": [ - " shot pass_ signal_name generic_name source_alias type \\\n", - "0 27933 0 ABM_CALIB_SHOT abm Analysed \n", - "1 27933 0 ABM_CHANNEL_STATUS abm Analysed \n", - "2 27933 0 ABM_CHANNEL_TYPE abm Analysed \n", - "3 27933 0 ABM_GAIN abm Analysed \n", - "4 27933 0 ABM_I-BOL abm Analysed \n", - "... ... ... ... ... ... ... \n", - "10589 27933 -1 /XYR/RTTE xyr Raw \n", - "10590 27933 -1 /XYR/SEGMENT1 xyr Raw \n", - "10591 27933 -1 /XYR/SEGMENTTIME xyr Raw \n", - "10592 27933 -1 /XYR/SENTTIME xyr Raw \n", - "10593 27933 -1 /XYR/TIME1 xyr Raw \n", - "\n", - " description signal_status \\\n", - "0 Shot used for calibration (obsolete) 1 \n", - "1 Failed = 0, OK = 1 1 \n", - "2 Channel type (0 = poloidal, 1 = co-tangential,... 1 \n", - "3 Gain of pre-amplifiers 1 \n", - "4 Incident powers (x - channel) 1 \n", - "... ... ... \n", - "10589 1 \n", - "10590 1 \n", - "10591 1 \n", - "10592 1 \n", - "10593 1 \n", - "\n", - " mds_name \n", - "0 \\TOP.ANALYSED.ABM:CALIB_SHOT \n", - "1 \\TOP.ANALYSED.ABM.CHANNEL:STATUS \n", - "2 \\TOP.ANALYSED.ABM:CHANNEL_TYPE \n", - "3 \\TOP.ANALYSED.ABM:GAIN \n", - "4 \\TOP.ANALYSED.ABM:I_BOL \n", - "... ... \n", - "10589 \\TOP.RAW.XYR:RTTE \n", - "10590 \\TOP.RAW.XYR:SEGMENT1 \n", - "10591 \\TOP.RAW.XYR:SEGMENTTIME \n", - "10592 \\TOP.RAW.XYR:SENTTIME \n", - "10593 \\TOP.RAW.XYR:TIME1 \n", - "\n", - "[10594 rows x 9 columns]" - ] - }, - "execution_count": 56, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dfs_1 = pd.DataFrame(signals_1)\n", - "dfs_1" - ] - }, - { - "cell_type": "markdown", - "id": "a4bfdd7a", - "metadata": {}, - "source": [ - "A `SIGNAL` attributes are:\n", - "\n", - "* `shot` - the unique number of a `SHOT`\n", - "* `pass_` - for **_Analysed_** type it would mean how many processing iterations it went through, the first - number 0, for **_Raw_** we would see -1\n", - "* `signal_name` - the name of a signal \n", - "* `generic_signal` - usually left blank, but can contain a shorter type of alias for common signals for easy access. Example: 'AMC_PLASMA CURRENT' has the alias 'ip'.\n", - "* `source_alias` - three letter alias name, which can be used for a separate source inspection\n", - "* `type` - e.g., **_Analysed_**, **_Raw_** or **_Image_**\n", - "* `description` - text description of the signal\n", - "* `signal_status` - internal data status set by responsible officer:\n", - " * -1 Poor Data: do not use\n", - " * 0 Something is wrong in the Data\n", - " * 1 either **_Raw_** data not checked or **_Analysed_** data quality is Unknown\n", - " * 2 Data has been checked - no known problems\n", - " * 3 Data was validated\n", - "* `mds_name` - MDS refers to an older technology called MDSPLUS that attempted to provide a universal data model and access mechanism.\n" - ] - }, - { - "cell_type": "markdown", - "id": "50dd4eea", - "metadata": {}, - "source": [ - "#### `SIGNAL` Name as Alias Dictionary\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "14ae0a98", - "metadata": {}, - "source": [ - "We can build a `SOURCE` dictionary, where an alias (three letter name) and `SIGNAL` name are organised as a set. This is done for convenience - grouping aliases with corresponding signals makes data exploration easier. To *inspect* each `SOURCE` we can use an alias and it will provide us with meta information, but to access the `SIGNAL` itself, one needs a separate `SIGNAL` name contained in such a set.\n", - "\n", - "**_Image_** `SOURCES` don't belong to `SIGNALS` and their access is different from **_Raw_** and **_Analysed_**, therefore, they cannot be found in `alias_signal_dict` below." - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "090158cc", - "metadata": {}, - "outputs": [], - "source": [ - "aliases_1 = set([signal.source_alias for signal in signals_1])\n", - "\n", - "alias_signal_dict = {\n", - " source: set(\n", - " [signal.signal_name for signal in signals_1 if signal.source_alias == source]\n", - " )\n", - " for source in aliases_1\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "4e2c26e8", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
╭─────────────────────── <class 'dict'> ───────────────────────╮\n",
-       " ╭──────────────────────────────────────────────────────────╮ \n",
-       "  {                                                         \n",
-       "  'air': {                                              \n",
-       "  │   │   'AIR_PTOT_OSP_ELM',                               \n",
-       "  │   │   'AIR_PHI_START_OSP',                              \n",
-       "  │   │   'AIR_PKPOWER_DENSITY_ISP',                        \n",
-       "  │   │   'AIR_PASSNUMBER',                                 \n",
-       "  │   │   'AIR_TEMPERATURE_OSP',                            \n",
-       "  │   │   'AIR_Z_EXTENT_ISP',                               \n",
-       "  │   │   'AIR_QPROFILE_ISP',                               \n",
-       "  │   │   'AIR_ETOTSUM_ISP_ELM',                            \n",
-       "  │   │   'AIR_QPROFILE_ISP_ELM',                           \n",
-       "  │   │   'AIR_PTOT_ISP_ELM',                               \n",
-       "  │   │   ... +49                                           \n",
-       "  },                                                    \n",
-       "  'xmp': {                                              \n",
-       "  │   │   '/XMP/DEVICES/D2_ADC103/RANGE',                   \n",
-       "  │   │   '/XMP/REF20',                                     \n",
-       "  │   │   '/XMP/REF23',                                     \n",
-       "  │   │   '/XMP/DEVICES/LIMIT',                             \n",
-       "  │   │   '/XMP/DEVICES/D2_ADC103/CHANNEL',                 \n",
-       "  │   │   '/XMP/TIME1'                                      \n",
-       "  },                                                    \n",
-       "  'amc': {                                              \n",
-       "  │   │   'AMC_P2IU FEED CURRENT',                          \n",
-       "  │   │   'AMC_P4L CURRENT',                                \n",
-       "  │   │   'AMC_P5U CASE CURRENT',                           \n",
-       "  │   │   'AMC_P4L COIL CURRENT',                           \n",
-       "  │   │   'AMC_P5L CURRENT',                                \n",
-       "  │   │   'AMC_P3U FEED CURRENT',                           \n",
-       "  │   │   'AMC_P4L CASE CURRENT',                           \n",
-       "  │   │   'AMC_P3L CASE CURRENT',                           \n",
-       "  │   │   'AMC_P5U CURRENT',                                \n",
-       "  │   │   'AMC_VERSION',                                    \n",
-       "  │   │   ... +36                                           \n",
-       "  },                                                    \n",
-       "  'xim': {                                              \n",
-       "  │   │   'XIM_DA/BO10',                                    \n",
-       "  │   │   'XIM_MASS_END',                                   \n",
-       "  │   │   'XIM_DA/HU10/R1',                                 \n",
-       "  │   │   'XIM_PELLET_HALPHA/2',                            \n",
-       "  │   │   'XIM_PREION_TRIG',                                \n",
-       "  │   │   'XIM_DA/HL11/L1',                                 \n",
-       "  │   │   'XIM_CII/HU10/U',                                 \n",
-       "  │   │   'XIM_DA/HU10/U1',                                 \n",
-       "  │   │   'XIM_DA/HL11/R1',                                 \n",
-       "  │   │   'XIM_TRIGGER',                                    \n",
-       "  │   │   ... +14                                           \n",
-       "  },                                                    \n",
-       "  'xlp': {                                              \n",
-       "  │   │   'XLP_V8',                                         \n",
-       "  │   │   'XLP_I10',                                        \n",
-       "  │   │   'XLP_V1',                                         \n",
-       "  │   │   'XLP_M8',                                         \n",
-       "  │   │   'XLP_V9',                                         \n",
-       "  │   │   'XLP_I4',                                         \n",
-       "  │   │   'XLP_V7',                                         \n",
-       "  │   │   'XLP_I12',                                        \n",
-       "  │   │   'XLP_V2',                                         \n",
-       "  │   │   'XLP_M1',                                         \n",
-       "  │   │   ... +30                                           \n",
-       "  },                                                    \n",
-       "  'xcm': {                                              \n",
-       "  │   │   'XCM_MFPS RELEASE',                               \n",
-       "  │   │   'XCM_TC_TH3',                                     \n",
-       "  │   │   'XCM_P1PS I',                                     \n",
-       "  │   │   'XCM_L8212A#4',                                   \n",
-       "  │   │   'XCM_S4 POSITION',                                \n",
-       "  │   │   'XCM_TEST_CH16',                                  \n",
-       "  │   │   'XCM_MFPS VOLTS',                                 \n",
-       "  │   │   'XCM_TC_REFBOT',                                  \n",
-       "  │   │   'XCM_TC_BH3',                                     \n",
-       "  │   │   'XCM_33KV SUPPLY',                                \n",
-       "  │   │   ... +60                                           \n",
-       "  },                                                    \n",
-       "  'xfi': {                                              \n",
-       "  │   │   '/XFI/DEVICES/D2_FIDA/SERSIZE',                   \n",
-       "  │   │   '/XFI/DEVICES/D2_FIDA/CHIPNAME',                  \n",
-       "  │   │   '/XFI/DEVICES/D2_FIDA/CLEARCYCLES',               \n",
-       "  │   │   '/XFI/BIN/8',                                     \n",
-       "  │   │   '/XFI/PIXEL1',                                    \n",
-       "  │   │   '/XFI/BIN/1',                                     \n",
-       "  │   │   '/XFI/BIN/2',                                     \n",
-       "  │   │   '/XFI/DEVICES/D2_FIDA/READOUT',                   \n",
-       "  │   │   '/XFI/BIN/6',                                     \n",
-       "  │   │   '/XFI/BIN/3',                                     \n",
-       "  │   │   ... +20                                           \n",
-       "  },                                                    \n",
-       "  'amb': {                                              \n",
-       "  │   │   'AMB_OBR14',                                      \n",
-       "  │   │   'AMB_CCBV19',                                     \n",
-       "  │   │   'AMB_CCBV11',                                     \n",
-       "  │   │   'AMB_CCBV20',                                     \n",
-       "  │   │   'AMB_OBR18',                                      \n",
-       "  │   │   'AMB_CCBV05',                                     \n",
-       "  │   │   'AMB_OBR15',                                      \n",
-       "  │   │   'AMB_CCBV21',                                     \n",
-       "  │   │   'AMB_OBR12',                                      \n",
-       "  │   │   'AMB_FL/P5U/1',                                   \n",
-       "  │   │   ... +74                                           \n",
-       "  },                                                    \n",
-       "  'xpc': {                                              \n",
-       "  │   │   'XPC_TRCF_0104_11',                               \n",
-       "  │   │   'XPC_GAS IBFUA DRIVE',                            \n",
-       "  │   │   'XPC_GAS HM12B REF',                              \n",
-       "  │   │   'XPC_LINCAM2',                                    \n",
-       "  │   │   'XPC_GAS TC5B REF',                               \n",
-       "  │   │   'XPC_GAS BC5 REF',                                \n",
-       "  │   │   'XPC_NBI SS CURRENT',                             \n",
-       "  │   │   'XPC_TRCF_0104_6',                                \n",
-       "  │   │   'XPC_GAS TC5B DRIVE',                             \n",
-       "  │   │   'XPC_GAS IBFUB REF',                              \n",
-       "  │   │   ... +60                                           \n",
-       "  },                                                    \n",
-       "  'xsx': {                                              \n",
-       "  │   │   '/XSX/HCAM/U/17',                                 \n",
-       "  │   │   '/XSX/HCAM/U/14',                                 \n",
-       "  │   │   '/XSX/TCAM/17',                                   \n",
-       "  │   │   '/XSX/TCAM/9',                                    \n",
-       "  │   │   '/XSX/TCAM/2',                                    \n",
-       "  │   │   '/XSX/HCAM/L/14',                                 \n",
-       "  │   │   '/XSX/HCAM/L/3',                                  \n",
-       "  │   │   '/XSX/HCAM/L/16',                                 \n",
-       "  │   │   '/XSX/HCAM/U/10',                                 \n",
-       "  │   │   '/XSX/HCAM/U/18',                                 \n",
-       "  │   │   ... +49                                           \n",
-       "  },                                                    \n",
-       "  ... +54                                               \n",
-       "  }                                                         \n",
-       " ╰──────────────────────────────────────────────────────────╯ \n",
-       "                                                              \n",
-       " 29 attribute(s) not shown. Run inspect(inspect) for options. \n",
-       "╰──────────────────────────────────────────────────────────────╯\n",
-       "
\n" - ], - "text/plain": [ - "\u001b[34m╭─\u001b[0m\u001b[34m────────────────────── \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'dict'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m ──────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m╭──────────────────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'air'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_PTOT_OSP_ELM'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_PHI_START_OSP'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_PKPOWER_DENSITY_ISP'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_PASSNUMBER'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_TEMPERATURE_OSP'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_Z_EXTENT_ISP'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_QPROFILE_ISP'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_ETOTSUM_ISP_ELM'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_QPROFILE_ISP_ELM'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AIR_PTOT_ISP_ELM'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33m...\u001b[0m +\u001b[1;36m49\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'xmp'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XMP/DEVICES/D2_ADC103/RANGE'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XMP/REF20'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XMP/REF23'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XMP/DEVICES/LIMIT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XMP/DEVICES/D2_ADC103/CHANNEL'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XMP/TIME1'\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'amc'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P2IU FEED CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P4L CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P5U CASE CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P4L COIL CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P5L CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P3U FEED CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P4L CASE CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P3L CASE CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_P5U CURRENT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMC_VERSION'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33m...\u001b[0m +\u001b[1;36m36\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'xim'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_DA/BO10'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_MASS_END'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_DA/HU10/R1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_PELLET_HALPHA/2'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_PREION_TRIG'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_DA/HL11/L1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_CII/HU10/U'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_DA/HU10/U1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_DA/HL11/R1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XIM_TRIGGER'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33m...\u001b[0m +\u001b[1;36m14\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'xlp'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_V8'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_I10'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_V1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_M8'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_V9'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_I4'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_V7'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_I12'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_V2'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XLP_M1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33m...\u001b[0m +\u001b[1;36m30\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'xcm'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_MFPS RELEASE'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_TC_TH3'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_P1PS I'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_L8212A#4'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_S4 POSITION'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_TEST_CH16'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_MFPS VOLTS'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_TC_REFBOT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_TC_BH3'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XCM_33KV SUPPLY'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33m...\u001b[0m +\u001b[1;36m60\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'xfi'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/DEVICES/D2_FIDA/SERSIZE'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/DEVICES/D2_FIDA/CHIPNAME'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/DEVICES/D2_FIDA/CLEARCYCLES'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/BIN/8'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/PIXEL1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/BIN/1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/BIN/2'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/DEVICES/D2_FIDA/READOUT'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/BIN/6'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'/XFI/BIN/3'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33m...\u001b[0m +\u001b[1;36m20\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'amb'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_OBR14'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_CCBV19'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_CCBV11'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_CCBV20'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_OBR18'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_CCBV05'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_OBR15'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_CCBV21'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_OBR12'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'AMB_FL/P5U/1'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33m...\u001b[0m +\u001b[1;36m74\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m}\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[32m'xpc'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XPC_TRCF_0104_11'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'XPC_GAS IBFUA DRIVE'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - 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] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "inspect(alias_signal_dict, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "4d1ca948", - "metadata": {}, - "source": [ - "For example, 'xss' will give us meta information" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "e1b027b5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭─────────────────────── <class 'list'> ───────────────────────╮\n",
-       " ╭──────────────────────────────────────────────────────────╮ \n",
-       "  [                                                         \n",
-       "  ListData(                                             \n",
-       "  │   │   shot=27933,                                       \n",
-       "  │   │   pass_=-1,                                         \n",
-       "  │   │   status=1,                                         \n",
-       "  │   │   source_alias='xss',                               \n",
-       "  │   │   format='CDF',                                     \n",
-       "  │   │   filename='xss027933.nc',                          \n",
-       "  │   │   type='Raw',                                       \n",
-       "  │   │   description='Ocean Optics system',                \n",
-       "  │   │   run_id=-1                                         \n",
-       "  )                                                     \n",
-       "  ]                                                         \n",
-       " ╰──────────────────────────────────────────────────────────╯ \n",
-       "                                                              \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options. \n",
-       "╰──────────────────────────────────────────────────────────────╯\n",
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'/XSS/WAVELENGTH2', '/XSS/TIME1', '/XSS/SPEC2', '/XSS/SPEC6', '/XSS/TIME2', '/XSS/TIME3', '/XSS/WAVELENGTH1', \n",
-       "'/XSS/SPEC1', '/XSS/SPEC4', '/XSS/WAVELENGTH4', '/XSS/SPEC3', '/XSS/TIME5', '/XSS/WAVELENGTH3', '/XSS/TIME4', \n",
-       "'/XSS/WAVELENGTH5'\n",
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typeformataliases
0ImageIPX{rir, rda, rgb, rbb, rba, rdb, rit, rbc}
1ImageTIF{rzz, rbe}
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" - ], - "text/plain": [ - " type format aliases\n", - "0 Image IPX {rir, rda, rgb, rbb, rba, rdb, rit, rbc}\n", - "1 Image TIF {rzz, rbe}" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_1.loc[df_1[\"type\"] == \"Image\"].groupby([\"type\", \"format\"], as_index=False).agg(\n", - " aliases=(\"source_alias\", lambda x: set(x))\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "20cca233", - "metadata": {}, - "source": [ - "There are consistencies in different experiments or `SHOTS`, for example, the other `SHOT` has *JPG* format." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b7af8652", - "metadata": {}, - "outputs": [], - "source": [ - "df_2.loc[df_2[\"type\"] == \"Image\"].groupby([\"type\", \"format\"], as_index=False).agg(\n", - " aliases=(\"source_alias\", lambda x: set(x))\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "491ea786", - "metadata": { - "tags": [] - }, - "source": [ - "## **_Raw_**" - ] - }, - { - "cell_type": "markdown", - "id": "6ae6eeb1", - "metadata": {}, - "source": [ - "**_Raw_** sources can be of several formats: *CDF*, *IDA3*, *ASCII*, *BINARY* and *NIDA*. However,we suspectt that *NIDA* format belongs to the **_Raw_** `SOURCES`incorrectly, because it should be in the **_Image_** `SOURCES`. There might be other irregularities with formats, such as **_Raw_** `SHOTS` with numbers between 27000 and 27500 names xyc,xbt can also be of *NCDF* format. " - ] - }, - { - "cell_type": "markdown", - "id": "ff4b81f2", - "metadata": {}, - "source": [ - "### *CDF* format" - ] - }, - { - "cell_type": "markdown", - "id": "01c8a53c", - "metadata": {}, - "source": [ - " *CDF* format is commonly used for **_Raw_** images. *NCDF* format can be inspected and accessed the same way as *CDF* . In the cell below is shown what one of the *CDF* `SOURCES` looks like. It follows the same structure as any other **_Raw_**, **_Analysed_** or **_Image_** format. This is what is referred as the `SOURCE` meta information in this document. " - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "4baf39c5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭─────────────────────── <class 'list'> ───────────────────────╮\n",
-       " ╭──────────────────────────────────────────────────────────╮ \n",
-       "  [                                                         \n",
-       "  ListData(                                             \n",
-       "  │   │   shot=27933,                                       \n",
-       "  │   │   pass_=-1,                                         \n",
-       "  │   │   status=1,                                         \n",
-       "  │   │   source_alias='xms',                               \n",
-       "  │   │   format='CDF',                                     \n",
-       "  │   │   filename='xms027933.nc',                          \n",
-       "  │   │   type='Raw',                                       \n",
-       "  │   │   description='Multi-channel MSE',                  \n",
-       "  │   │   run_id=-1                                         \n",
-       "  )                                                     \n",
-       "  ]                                                         \n",
-       " ╰──────────────────────────────────────────────────────────╯ \n",
-       "                                                              \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options. \n",
-       "╰──────────────────────────────────────────────────────────────╯\n",
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╭─ <class 'pyuda._structured.StructuredData'> ─╮\n",
-       " ╭──────────────────────────────────────────╮ \n",
-       "  <Structured Data: data>                   \n",
-       " ╰──────────────────────────────────────────╯ \n",
-       "                                              \n",
-       " children = [                                 \n",
-       "                <Structured Data: ch00>,      \n",
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-       "                <Structured Data: ch03>,      \n",
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-       "                <Structured Data: ch17>,      \n",
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-       "                <Structured Data: ch39>,      \n",
-       "                <Structured Data: ch40>,      \n",
-       "                <Structured Data: ch41>,      \n",
-       "                <Structured Data: test>       \n",
-       "            ]                                 \n",
-       "     name = 'data'                            \n",
-       "╰──────────────────────────────────────────────╯\n",
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"\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mStructured\u001b[0m\u001b[39m Data: ch37\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mStructured\u001b[0m\u001b[39m Data: ch38\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mStructured\u001b[0m\u001b[39m Data: ch39\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mStructured\u001b[0m\u001b[39m Data: ch40\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mStructured\u001b[0m\u001b[39m Data: ch41\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mStructured\u001b[0m\u001b[39m Data: test\u001b[0m\u001b[1m>\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m]\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mname\u001b[0m = \u001b[32m'data'\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m╰──────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "data = client.get(\"xms\", shot_1)\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "f4cab185", - "metadata": {}, - "source": [ - "In this case data can be accesses as data.children[i], while in some cases data.children[i].children[j] might be required. \n", - "Data in this `children` also belongs to a class `StructuredData`." - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "39e50338", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭───────────── <class 'pyuda._structured.StructuredData'> ─────────────╮\n",
-       " ╭──────────────────────────────────────────────────────────────────╮ \n",
-       "  <Structured Data: ch11>                                           \n",
-       " ╰──────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                      \n",
-       "    channel = array([4], dtype=int32)                                 \n",
-       "   children = []                                                      \n",
-       "       data = array([-60,   8, -36, ..., -36, -52,   4], dtype=int16) \n",
-       "     device = '/devices/d3_pxi6133'                                   \n",
-       " dimensions = 'time1=650000'                                          \n",
-       "       name = 'ch11'                                                  \n",
-       "     offset = array([0.], dtype=float32)                              \n",
-       "      scale = array([3.8147555e-05], dtype=float32)                   \n",
-       "      title = 'Volt'                                                  \n",
-       "      units = 'V'                                                     \n",
-       "╰──────────────────────────────────────────────────────────────────────╯\n",
-       "
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\n", - "Note: In this case data is accessed unscaled, with scale available as an array within `data.children`. Another curios thing is the data being an array of int16, while scale is a float32. When data accessed as a Signal, it is available scaled and having a type float32.\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "e837310e", - "metadata": {}, - "source": [ - "Below is demonstrated the second and the recommended method for data access which uses the `SIGNAL` name.\n", - "Data in this case belongs to the class `Signal`. In this example we are retrieving exactly the same data array as above. One can observe that array of the data is different from the previous, because it is automatically scaled." - ] - }, - { - "cell_type": "markdown", - "id": "3cb3f7ea", - "metadata": {}, - "source": [ - "Previously, we accessed xms alias with `data.children[11]` which is the channel 11(ch11) of the `SOURCE`. To be able to retrieve the exact same signal, `alias_signal_dict` in Sec. [3.1.2.2] can be useful. We can see which `SIGNALS` belong to xms `SOURCE`. " - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "da0f8d6f-09e9-4ee2-96af-4754566c99fe", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
'/XMS/CH22', '/XMS/CH06', '/XMS/CH29', '/XMS/DEVICES/D3_PXI6133/RANGE', '/XMS/DEVICES/D4_PXI6133/RANGE', \n",
-       "'/XMS/CH16', '/XMS/DEVICES/D3_PXI6133/CHANNEL', '/XMS/CH26', '/XMS/DEVICES/D6_PXI6133/CHANNEL', '/XMS/CH04', \n",
-       "'/XMS/CH05', '/XMS/CH01', '/XMS/CH09', '/XMS/CH23', '/XMS/CH33', '/XMS/CH40', '/XMS/DEVICES/D5_PXI6133/RANGE', \n",
-       "'/XMS/DEVICES/D4_PXI6133/CHANNEL', '/XMS/CH18', '/XMS/CH12', '/XMS/DEVICES/D7_PXI6133/CHANNEL', \n",
-       "'/XMS/DEVICES/D6_PXI6133/RANGE', '/XMS/CH11', '/XMS/CH13', '/XMS/CH39', '/XMS/CH03', '/XMS/CH35', \n",
-       "'/XMS/DEVICES/D5_PXI6133/CHANNEL', '/XMS/DEVICES/D2_PXI6133/CHANNEL', '/XMS/CH00', '/XMS/CH31', '/XMS/CH10', \n",
-       "'/XMS/CH37', '/XMS/CH27', '/XMS/CH20', '/XMS/CH24', '/XMS/CH28', '/XMS/CH30', '/XMS/CH07', '/XMS/TEST', \n",
-       "'/XMS/CH34', '/XMS/CH25', '/XMS/CH08', '/XMS/CH17', '/XMS/CH41', '/XMS/CH36', '/XMS/DEVICES/LIMIT', '/XMS/CH02', \n",
-       "'/XMS/CH21', '/XMS/DEVICES/D2_PXI6133/RANGE', '/XMS/CH14', '/XMS/CH15', '/XMS/CH32', '/XMS/TIME1', \n",
-       "'/XMS/DEVICES/D7_PXI6133/RANGE', '/XMS/CH38', '/XMS/CH19'\n",
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╭─────────────────────────────────── <class 'pyuda._signal.Signal'> ───────────────────────────────────╮\n",
-       " ╭──────────────────────────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  <Signal: Volt>                                                                                    \n",
-       " ╰──────────────────────────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                                      \n",
-       "        data = array([-0.00228885,  0.00030518, -0.00137331, ..., -0.00137331,                        \n",
-       "                      -0.00198367,  0.00015259], dtype=float32)                                       \n",
-       " description = ''                                                                                     \n",
-       "        dims = [<Dim: Time>]                                                                          \n",
-       "      errors = array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)                                    \n",
-       "       label = 'Volt'                                                                                 \n",
-       "        meta = {                                                                                      \n",
-       "                   'signal_name': b'/xms/ch11',                                                       \n",
-       "                   'signal_alias': b'/XMS/CH11',                                                      \n",
-       "                   'path': b'/net/mustrgsrvr1/export/mastu/data/MAST_Data/27933/LATEST/xms027933.nc', \n",
-       "                   'filename': b'xms027933.nc',                                                       \n",
-       "                   'format': b'CDF',                                                                  \n",
-       "                   'exp_number': 27933,                                                               \n",
-       "                   'pass': -1,                                                                        \n",
-       "                   'pass_date': b'2011-12-15'                                                         \n",
-       "               }                                                                                      \n",
-       "        rank = 1                                                                                      \n",
-       "       shape = (650000,)                                                                              \n",
-       "        time = <Dim: Time>                                                                            \n",
-       "  time_index = 0                                                                                      \n",
-       "       units = 'V'                                                                                    \n",
-       "╰──────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "
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╭─────────────────────────── <class 'numpy.ndarray'> ───────────────────────────╮\n",
-       " ╭───────────────────────────────────────────────────────────────────────────╮ \n",
-       "  array([-0.05    , -0.049999, -0.049998, ...,  0.599997,  0.599998,         \n",
-       "  │   │   0.599999])                                                         \n",
-       " ╰───────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                               \n",
-       "     base = 1                                                                  \n",
-       "   ctypes = <numpy.core._internal._ctypes object at 0x7f8eb51d4198>            \n",
-       "     data = <memory at 0x7f8eb520d1c8>                                         \n",
-       "    dtype = dtype('float64')                                                   \n",
-       "    flags =   C_CONTIGUOUS : True                                              \n",
-       "              F_CONTIGUOUS : True                                              \n",
-       "              OWNDATA : False                                                  \n",
-       "              WRITEABLE : True                                                 \n",
-       "              ALIGNED : True                                                   \n",
-       "              WRITEBACKIFCOPY : False                                          \n",
-       "              UPDATEIFCOPY : False                                             \n",
-       "                                                                               \n",
-       "     flat = <numpy.flatiter object at 0x560d0b963e50>                          \n",
-       "     imag = array([0., 0., 0., ..., 0., 0., 0.])                               \n",
-       " itemsize = 8                                                                  \n",
-       "   nbytes = 5200000                                                            \n",
-       "     ndim = 1                                                                  \n",
-       "     real = array([-0.05    , -0.049999, -0.049998, ...,  0.599997,  0.599998, \n",
-       "                    0.599999])                                                 \n",
-       "    shape = (650000,)                                                          \n",
-       "     size = 650000                                                             \n",
-       "  strides = (8,)                                                               \n",
-       "        T = array([-0.05    , -0.049999, -0.049998, ...,  0.599997,  0.599998, \n",
-       "                    0.599999])                                                 \n",
-       "╰───────────────────────────────────────────────────────────────────────────────╯\n",
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"\u001b[34m│\u001b[0m \u001b[3;33mnbytes\u001b[0m = \u001b[1;36m5200000\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mndim\u001b[0m = \u001b[1;36m1\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mreal\u001b[0m = \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m-0.05\u001b[0m , \u001b[1;36m-0.049999\u001b[0m, \u001b[1;36m-0.049998\u001b[0m, \u001b[33m...\u001b[0m, \u001b[1;36m0.599997\u001b[0m, \u001b[1;36m0.599998\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0.599999\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mshape\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m650000\u001b[0m,\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33msize\u001b[0m = \u001b[1;36m650000\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mstrides\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m8\u001b[0m,\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mT\u001b[0m = \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m-0.05\u001b[0m , \u001b[1;36m-0.049999\u001b[0m, \u001b[1;36m-0.049998\u001b[0m, \u001b[33m...\u001b[0m, \u001b[1;36m0.599997\u001b[0m, \u001b[1;36m0.599998\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0.599999\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m╰───────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "time_axis = data.time.data\n", - "inspect(time_axis, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "3efc5eab", - "metadata": {}, - "source": [ - "### Sources & Data in *IDA3* format" - ] - }, - { - "cell_type": "markdown", - "id": "85d2a3f9", - "metadata": {}, - "source": [ - "*IDA3* is the second most commonly used format in **_Raw_** and it is used as the main `SIGNAL` format in **_Analysed_**. Unlike *CBF*, it cannot be accessed via `SOURCE` name/alias. Here we demonstrate it for 'xmd' `SOURCE`, but all the other are structured the same way." - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "80cf024e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭────────────────────────────────────── <class 'list'> ──────────────────────────────────────╮\n",
-       " ╭────────────────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  [                                                                                       \n",
-       "  ListData(                                                                           \n",
-       "  │   │   shot=27933,                                                                     \n",
-       "  │   │   pass_=-1,                                                                       \n",
-       "  │   │   status=1,                                                                       \n",
-       "  │   │   source_alias='xmd',                                                             \n",
-       "  │   │   format='IDA3',                                                                  \n",
-       "  │   │   filename='xmd0279.33',                                                          \n",
-       "  │   │   type='Raw',                                                                     \n",
-       "  │   │   description='Magnetic Field Measurements: Centre Column Toroidal Array of'+35,  \n",
-       "  │   │   run_id=-1                                                                       \n",
-       "  )                                                                                   \n",
-       "  ]                                                                                       \n",
-       " ╰────────────────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                            \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options.                               \n",
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╭─────────────────────── <class 'pyuda._signal.Signal'> ────────────────────────╮\n",
-       " ╭───────────────────────────────────────────────────────────────────────────╮ \n",
-       "  <Signal: V>                                                                \n",
-       " ╰───────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                               \n",
-       "        data = array([ 0.        , -0.0390625 , -0.04150391, ..., -0.29785156, \n",
-       "                      -0.00732422, -0.12451172], dtype=float32)                \n",
-       " description = ''                                                              \n",
-       "        dims = [<Dim: Time>]                                                   \n",
-       "      errors = array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)             \n",
-       "       label = 'V'                                                             \n",
-       "        meta = {                                                               \n",
-       "                   'signal_name': b'XMD_NTM/FPGA/01',                          \n",
-       "                   'signal_alias': b'XMD_NTM/FPGA/01',                         \n",
-       "                   'path': b'',                                                \n",
-       "                   'filename': b'xmd0279.33',                                  \n",
-       "                   'format': b'IDA3',                                          \n",
-       "                   'exp_number': 27933,                                        \n",
-       "                   'pass': -1,                                                 \n",
-       "                   'pass_date': b'2011-12-15'                                  \n",
-       "               }                                                               \n",
-       "        rank = 1                                                               \n",
-       "       shape = (132096,)                                                       \n",
-       "        time = <Dim: Time>                                                     \n",
-       "  time_index = 0                                                               \n",
-       "       units = 'V'                                                             \n",
-       "╰───────────────────────────────────────────────────────────────────────────────╯\n",
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Could not translate logical name IDA3_ERR_MESS_FILE", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mServerException\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m/tmp/ipykernel_22687/2461860100.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"xmd\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshot_1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0minspect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/depot/uda-2.5.3/python/pyuda/_client.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, signal, source, time_first, time_last, **kwargs)\u001b[0m\n\u001b[1;32m 168\u001b[0m \"\"\"\n\u001b[1;32m 169\u001b[0m \u001b[0;31m# Standard signal\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 170\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcpyuda\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msignal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 171\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_unpack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtime_first\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtime_last\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 172\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32mpyuda/cpyuda/cpyuda.pyx\u001b[0m in \u001b[0;36mcpyuda.get_data\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mServerException\u001b[0m: No IDA Signal in IDA Source File. Could not translate logical name IDA3_ERR_MESS_FILE" - ] - } - ], - "source": [ - "data = client.get(\"xmd\", shot_1)\n", - "inspect(data)" - ] - }, - { - "cell_type": "markdown", - "id": "8e0c9c5a", - "metadata": {}, - "source": [ - "#### Errors & Exceptions" - ] - }, - { - "cell_type": "markdown", - "id": "27599f3c", - "metadata": {}, - "source": [ - "An exception where data in **_Raw_** can be accessed only as a `Video` rather than a `Signal` is demonstrated below." - ] - }, - { - "cell_type": "markdown", - "id": "c886de8e", - "metadata": {}, - "source": [ - "One cannot fund this `SOURCE` 'rcc' in source dictionary, see below. " - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "3c24dd9b", - "metadata": {}, - "outputs": [], - "source": [ - "shot_3 = 30420\n", - "\n", - "sources_3 = client.list(ListType.SOURCES, shot_3)\n", - "signals_3 = client.list(ListType.SIGNALS, shot_3)\n", - "\n", - "aliases_3 = set([signal.source_alias for signal in signals_3])\n", - "\n", - "alias_signal_dict_3 = {\n", - " source: set(\n", - " [signal.signal_name for signal in signals_3 if signal.source_alias == source]\n", - " )\n", - " for source in aliases_3\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "29d6ba48", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "# commented as this will print a very big dictionary\n", - "# print(alias_signal_dict_3)" - ] - }, - { - "cell_type": "markdown", - "id": "a0414fba", - "metadata": {}, - "source": [ - "At the same time we can see that the `SOURCE` is *IDA3* and belongs to type **_Raw_**." - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "a078d137", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭──────────────────────────────── <class 'list'> ────────────────────────────────╮\n",
-       " ╭────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  [                                                                           \n",
-       "  ListData(                                                               \n",
-       "  │   │   shot=30420,                                                         \n",
-       "  │   │   pass_=-1,                                                           \n",
-       "  │   │   status=1,                                                           \n",
-       "  │   │   source_alias='rcc',                                                 \n",
-       "  │   │   format='IDA3',                                                      \n",
-       "  │   │   filename='rcc0304.20',                                              \n",
-       "  │   │   type='Raw',                                                         \n",
-       "  │   │   description='CELESTE-3: core charge exchange (CXRS) spectrometer',  \n",
-       "  │   │   run_id=-1                                                           \n",
-       "  )                                                                       \n",
-       "  ]                                                                           \n",
-       " ╰────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options.                   \n",
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╭─────────────────────────────── <class 'pyuda._video.Video'> ───────────────────────────────╮\n",
-       " ╭────────────────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  <pyuda._video.Video object at 0x7f8eb41afa90>                                           \n",
-       " ╰────────────────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                            \n",
-       "          camera = 'Pluto PS482, PixCam 1.6'                                                \n",
-       "      ccd_height = 270                                                                      \n",
-       "       ccd_width = 342                                                                      \n",
-       "       close_flc = 0                                                                        \n",
-       " close_flc_delay = 0                                                                        \n",
-       "       date_time = '25/09/2013 12:32'                                                       \n",
-       "           depth = 14                                                                       \n",
-       "        exp_mode = 3.0                                                                      \n",
-       "     file_format = 'RCC'                                                                    \n",
-       "     frame_times = array([-50000, -45008, -40008, -35006, -30008, -25008, -20008, -15008,   \n",
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-       "                          589992, 595138], dtype=int32)                                     \n",
-       "          frames = [                                                                        \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadcdc860>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadcdc8d0>,                       \n",
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-       "                       <pyuda._video.Frame object at 0x7f8eadc901d0>,                       \n",
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-       "                       <pyuda._video.Frame object at 0x7f8eadc90cf8>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90d30>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90d68>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90da0>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90dd8>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90e10>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90e48>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90e80>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90eb8>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90ef0>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90f28>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90f60>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90f98>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc90fd0>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc95048>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc95080>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc950b8>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc950f0>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc95128>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc95160>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc95198>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc951d0>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc95208>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc95240>,                       \n",
-       "                       <pyuda._video.Frame object at 0x7f8eadc95278>                        \n",
-       "                   ]                                                                        \n",
-       "          height = 36                                                                       \n",
-       "              id = 'CXR 01'                                                                 \n",
-       "        is_color = 0                                                                        \n",
-       "      n_channels = 4                                                                        \n",
-       "        n_frames = 130                                                                      \n",
-       "      n_i2m_rows = 250                                                                      \n",
-       "  n_notch_pulses = 0                                                                        \n",
-       "           n_roi = 5                                                                        \n",
-       "        open_flc = 0                                                                        \n",
-       "  open_flc_delay = 0                                                                        \n",
-       "     orientation = 2231306                                                                  \n",
-       "        prom_set = array([254,   1,   1,   0], dtype=int32)                                 \n",
-       "        read_out = 3.3844000000000003                                                       \n",
-       "            shot = 30420                                                                    \n",
-       "        temp_set = 96                                                                       \n",
-       "        time_out = 10000                                                                    \n",
-       "      trig_pulse = 999983.0                                                                 \n",
-       "           width = 684                                                                      \n",
-       "           x_roi = array([  0, 342,   1], dtype=int32)                                      \n",
-       "           y_roi = array([[  0,   0,   1,   1,   0,  11,  11,   1,  11, 105,  15,   1, 116, \n",
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-       "                             0,   0,   0,   0,   0,   0],                                   \n",
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-       "                             0,   0,   0,   0,   0,   0]], dtype=int32)                     \n",
-       "╰────────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "
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"\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90d68\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90da0\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90dd8\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90e10\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90e48\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90e80\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90eb8\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90ef0\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90f28\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90f60\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90f98\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc90fd0\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc95048\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc95080\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc950b8\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc950f0\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc95128\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc95160\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc95198\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc951d0\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc95208\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc95240\u001b[0m\u001b[1m>\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mpyuda._video.Frame\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7f8eadc95278\u001b[0m\u001b[1m>\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m]\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mheight\u001b[0m = \u001b[1;36m36\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mid\u001b[0m = \u001b[32m'CXR 01'\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mis_color\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mn_channels\u001b[0m = \u001b[1;36m4\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mn_frames\u001b[0m = \u001b[1;36m130\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mn_i2m_rows\u001b[0m = \u001b[1;36m250\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mn_notch_pulses\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mn_roi\u001b[0m = \u001b[1;36m5\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mopen_flc\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mopen_flc_delay\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33morientation\u001b[0m = \u001b[1;36m2231306\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mprom_set\u001b[0m = \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m254\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mdtype\u001b[0m=\u001b[35mint32\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mread_out\u001b[0m = \u001b[1;36m3.3844000000000003\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mshot\u001b[0m = \u001b[1;36m30420\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtemp_set\u001b[0m = \u001b[1;36m96\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtime_out\u001b[0m = \u001b[1;36m10000\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtrig_pulse\u001b[0m = \u001b[1;36m999983.0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mwidth\u001b[0m = \u001b[1;36m684\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mx_roi\u001b[0m = \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m342\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mdtype\u001b[0m=\u001b[35mint32\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33my_roi\u001b[0m = \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1m[\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m11\u001b[0m, \u001b[1;36m11\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m11\u001b[0m, \u001b[1;36m105\u001b[0m, \u001b[1;36m15\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m116\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m32\u001b[0m, \u001b[1;36m16\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m148\u001b[0m, \u001b[1;36m120\u001b[0m, \u001b[1;36m15\u001b[0m, \u001b[1;36m2\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m]\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m[\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m]\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m[\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m]\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m[\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m, \u001b[1;36m0\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mdtype\u001b[0m=\u001b[35mint32\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m╰────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "data = client.get_images(\"rcc\", shot_3)\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "d1bb76f9", - "metadata": {}, - "source": [ - "### Sources & Data in *NIDA* format" - ] - }, - { - "cell_type": "markdown", - "id": "11ed7c76", - "metadata": {}, - "source": [ - "*NIDA* should not be in **_Raw_** `SOURCE` types. Following the same approach as for other formats, one can see that some of such `SOURCES` don't have meaningful description, when we inspect it. UDA API is also not able to access the data, although can get some mets file information, which involves path to the data. Unfortunately, currently, we cannot access this either." - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "45bb3a9a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭──────────────────────────────────── <class 'list'> ─────────────────────────────────────╮\n",
-       " ╭─────────────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  [                                                                                    \n",
-       "  ListData(                                                                        \n",
-       "  │   │   shot=27933,                                                                  \n",
-       "  │   │   pass_=-1,                                                                    \n",
-       "  │   │   status=1,                                                                    \n",
-       "  │   │   source_alias='xmw',                                                          \n",
-       "  │   │   format='NIDA',                                                               \n",
-       "  │   │   filename='xmw0279.33',                                                       \n",
-       "  │   │   type='Raw',                                                                  \n",
-       "  │   │   description='Share the knowledge - If you know what this is, let me know!',  \n",
-       "  │   │   run_id=-1                                                                    \n",
-       "  )                                                                                \n",
-       "  ]                                                                                    \n",
-       " ╰─────────────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                         \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options.                            \n",
-       "╰─────────────────────────────────────────────────────────────────────────────────────────╯\n",
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╭─────── <class 'pyuda._signal.Signal'> ───────╮\n",
-       " ╭──────────────────────────────────────────╮ \n",
-       "  <Signal>                                  \n",
-       " ╰──────────────────────────────────────────╯ \n",
-       "                                              \n",
-       "        data = None                           \n",
-       " description = ''                             \n",
-       "        dims = []                             \n",
-       "      errors = None                           \n",
-       "       label = ''                             \n",
-       "        meta = {                              \n",
-       "                   'signal_name': b'xmw',     \n",
-       "                   'signal_alias': b'xmw',    \n",
-       "                   'path': b'/xmw0279.33',    \n",
-       "                   'filename': b'xmw0279.33', \n",
-       "                   'format': b'NIDA',         \n",
-       "                   'exp_number': 27933,       \n",
-       "                   'pass': -1,                \n",
-       "                   'pass_date': b'2011-12-15' \n",
-       "               }                              \n",
-       "        rank = 0                              \n",
-       "       shape = ()                             \n",
-       "        time = None                           \n",
-       "  time_index = None                           \n",
-       "       units = ''                             \n",
-       "╰──────────────────────────────────────────────╯\n",
-       "
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╭────────────────────────────────────── <class 'list'> ──────────────────────────────────────╮\n",
-       " ╭────────────────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  [                                                                                       \n",
-       "  ListData(                                                                           \n",
-       "  │   │   shot=27933,                                                                     \n",
-       "  │   │   pass_=-1,                                                                       \n",
-       "  │   │   status=1,                                                                       \n",
-       "  │   │   source_alias='msf',                                                             \n",
-       "  │   │   format='ASCII',                                                                 \n",
-       "  │   │   filename='msf027933.csv',                                                       \n",
-       "  │   │   type='Raw',                                                                     \n",
-       "  │   │   description='MAST shot file, a .csv file containing OPC parameters from t'+59,  \n",
-       "  │   │   run_id=-1                                                                       \n",
-       "  )                                                                                   \n",
-       "  ]                                                                                       \n",
-       " ╰────────────────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                            \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options.                               \n",
-       "╰────────────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "
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╭──────── <class 'pyuda._signal.Signal'> ─────────╮\n",
-       " ╭─────────────────────────────────────────────╮ \n",
-       "  <Signal>                                     \n",
-       " ╰─────────────────────────────────────────────╯ \n",
-       "                                                 \n",
-       "        data = None                              \n",
-       " description = ''                                \n",
-       "        dims = []                                \n",
-       "      errors = None                              \n",
-       "       label = ''                                \n",
-       "        meta = {                                 \n",
-       "                   'signal_name': b'msf',        \n",
-       "                   'signal_alias': b'msf',       \n",
-       "                   'path': b'/msf027933.csv',    \n",
-       "                   'filename': b'msf027933.csv', \n",
-       "                   'format': b'ASCII',           \n",
-       "                   'exp_number': 27933,          \n",
-       "                   'pass': -1,                   \n",
-       "                   'pass_date': b'2011-12-15'    \n",
-       "               }                                 \n",
-       "        rank = 0                                 \n",
-       "       shape = ()                                \n",
-       "        time = None                              \n",
-       "  time_index = None                              \n",
-       "       units = ''                                \n",
-       "╰─────────────────────────────────────────────────╯\n",
-       "
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╭────────────────────────────────────── <class 'list'> ──────────────────────────────────────╮\n",
-       " ╭────────────────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  [                                                                                       \n",
-       "  ListData(                                                                           \n",
-       "  │   │   shot=12000,                                                                     \n",
-       "  │   │   pass_=0,                                                                        \n",
-       "  │   │   status=0,                                                                       \n",
-       "  │   │   source_alias='pcs',                                                             \n",
-       "  │   │   format='BINARY',                                                                \n",
-       "  │   │   filename='pcs0120.00',                                                          \n",
-       "  │   │   type='Raw',                                                                     \n",
-       "  │   │   description='Plasma control system shot file, and is in the same format a'+83,  \n",
-       "  │   │   run_id=-1                                                                       \n",
-       "  ),                                                                                  \n",
-       "  ListData(                                                                           \n",
-       "  │   │   shot=12000,                                                                     \n",
-       "  │   │   pass_=-1,                                                                       \n",
-       "  │   │   status=1,                                                                       \n",
-       "  │   │   source_alias='pcs',                                                             \n",
-       "  │   │   format='BINARY',                                                                \n",
-       "  │   │   filename='pcs0120.00',                                                          \n",
-       "  │   │   type='Raw',                                                                     \n",
-       "  │   │   description='Plasma control system shot file, and is in the same format a'+83,  \n",
-       "  │   │   run_id=-1                                                                       \n",
-       "  )                                                                                   \n",
-       "  ]                                                                                       \n",
-       " ╰────────────────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                            \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options.                               \n",
-       "╰────────────────────────────────────────────────────────────────────────────────────────────╯\n",
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"\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mstatus\u001b[0m=\u001b[1;36m0\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33msource_alias\u001b[0m=\u001b[32m'pcs'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mformat\u001b[0m=\u001b[32m'BINARY'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mfilename\u001b[0m=\u001b[32m'pcs0120.00'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Raw'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Plasma control system shot file, and is in the same format a'\u001b[0m+\u001b[1;36m83\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mrun_id\u001b[0m=\u001b[1;36m-1\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1;35mListData\u001b[0m\u001b[1m(\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mshot\u001b[0m=\u001b[1;36m12000\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mpass_\u001b[0m=\u001b[1;36m-1\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mstatus\u001b[0m=\u001b[1;36m1\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33msource_alias\u001b[0m=\u001b[32m'pcs'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mformat\u001b[0m=\u001b[32m'BINARY'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mfilename\u001b[0m=\u001b[32m'pcs0120.00'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Raw'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Plasma control system shot file, and is in the same format a'\u001b[0m+\u001b[1;36m83\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mrun_id\u001b[0m=\u001b[1;36m-1\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m)\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m]\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m╰────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m35\u001b[0m\u001b[3m attribute(s) not shown.\u001b[0m Run \u001b[1;35minspect\u001b[0m\u001b[1m(\u001b[0minspect\u001b[1m)\u001b[0m for options. \u001b[34m│\u001b[0m\n", - "\u001b[34m╰────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "data = [source for source in sources_2 if source.source_alias == \"pcs\"]\n", - "# rts,pcs,rcb,rbm,rcc\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "1b2d66c4", - "metadata": {}, - "source": [ - "This alias ('pcs') contains two `SOURCES` associated with it, which seems to be an error." - ] - }, - { - "cell_type": "markdown", - "id": "11dc0a92", - "metadata": {}, - "source": [ - "### Data in *ASCII* format." - ] - }, - { - "cell_type": "markdown", - "id": "aa9202b9", - "metadata": {}, - "source": [ - "Above was demonstrated that currently only meta data can be retrieved using UDA API for *BINARY* and *NIDA* types, the same holds for *ASCII*." - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "cec7819e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭─────── <class 'pyuda._signal.Signal'> ───────╮\n",
-       " ╭──────────────────────────────────────────╮ \n",
-       "  <Signal>                                  \n",
-       " ╰──────────────────────────────────────────╯ \n",
-       "                                              \n",
-       "        data = None                           \n",
-       " description = ''                             \n",
-       "        dims = []                             \n",
-       "      errors = None                           \n",
-       "       label = ''                             \n",
-       "        meta = {                              \n",
-       "                   'signal_name': b'pcs',     \n",
-       "                   'signal_alias': b'pcs',    \n",
-       "                   'path': b'/pcs0120.00',    \n",
-       "                   'filename': b'pcs0120.00', \n",
-       "                   'format': b'BINARY',       \n",
-       "                   'exp_number': 12000,       \n",
-       "                   'pass': 0,                 \n",
-       "                   'pass_date': b'1980-02-10' \n",
-       "               }                              \n",
-       "        rank = 0                              \n",
-       "       shape = ()                             \n",
-       "        time = None                           \n",
-       "  time_index = None                           \n",
-       "       units = ''                             \n",
-       "╰──────────────────────────────────────────────╯\n",
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╭─────────────────────── <class 'list'> ───────────────────────╮\n",
-       " ╭──────────────────────────────────────────────────────────╮ \n",
-       "  [                                                         \n",
-       "  ListData(                                             \n",
-       "  │   │   shot=27933,                                       \n",
-       "  │   │   pass_=0,                                          \n",
-       "  │   │   status=1,                                         \n",
-       "  │   │   source_alias='ams',                               \n",
-       "  │   │   format='IDA3',                                    \n",
-       "  │   │   filename='ams0279.33',                            \n",
-       "  │   │   type='Analysed',                                  \n",
-       "  │   │   description='Multi-channel MSE',                  \n",
-       "  │   │   run_id=-1                                         \n",
-       "  )                                                     \n",
-       "  ]                                                         \n",
-       " ╰──────────────────────────────────────────────────────────╯ \n",
-       "                                                              \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options. \n",
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╭──────────────────────────── <class 'pyuda._signal.Signal'> ────────────────────────────╮\n",
-       " ╭────────────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  <Signal:  >                                                                         \n",
-       " ╰────────────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                        \n",
-       "        data = array([[ 0.,  2.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14., 15., \n",
-       "                       23., 16., 17., 18., 20., 21., 22., 24., 25., 27., 30., 28., 29., \n",
-       "                       31., 32., 33., 35., 38., 37., 39., 40., 41.]], dtype=float32)    \n",
-       " description = ''                                                                       \n",
-       "        dims = [<Dim: Time>, <Dim:  >]                                                  \n",
-       "      errors = array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,  \n",
-       "                       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,  \n",
-       "                       0., 0., 0.]], dtype=float32)                                     \n",
-       "       label = ' '                                                                      \n",
-       "        meta = {                                                                        \n",
-       "                   'signal_name': b'AMS_CH',                                            \n",
-       "                   'signal_alias': b'AMS_CH',                                           \n",
-       "                   'path': b'',                                                         \n",
-       "                   'filename': b'ams0279.33',                                           \n",
-       "                   'format': b'IDA3',                                                   \n",
-       "                   'exp_number': 27933,                                                 \n",
-       "                   'pass': 0,                                                           \n",
-       "                   'pass_date': b'2011-12-15'                                           \n",
-       "               }                                                                        \n",
-       "        rank = 2                                                                        \n",
-       "       shape = (1, 35)                                                                  \n",
-       "        time = <Dim: Time>                                                              \n",
-       "  time_index = 0                                                                        \n",
-       "       units = ' '                                                                      \n",
-       "╰────────────────────────────────────────────────────────────────────────────────────────╯\n",
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"\u001b[34m│\u001b[0m \u001b[3;33merrors\u001b[0m = \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m.\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mdtype\u001b[0m=\u001b[35mfloat32\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mlabel\u001b[0m = \u001b[32m' '\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mmeta\u001b[0m = \u001b[1m{\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'signal_name'\u001b[0m: \u001b[32mb'AMS_CH'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'signal_alias'\u001b[0m: \u001b[32mb'AMS_CH'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'path'\u001b[0m: \u001b[32mb''\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'filename'\u001b[0m: \u001b[32mb'ams0279.33'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'format'\u001b[0m: \u001b[32mb'IDA3'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'exp_number'\u001b[0m: \u001b[1;36m27933\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'pass'\u001b[0m: \u001b[1;36m0\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'pass_date'\u001b[0m: \u001b[32mb'2011-12-15'\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m}\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mrank\u001b[0m = \u001b[1;36m2\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mshape\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m35\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtime\u001b[0m = \u001b[1m<\u001b[0m\u001b[1;95mDim:\u001b[0m\u001b[39m Time\u001b[0m\u001b[1m>\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtime_index\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33munits\u001b[0m = \u001b[32m' '\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m╰────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "data = client.get(\"AMS_CH\", shot_1)\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "d69fa368", - "metadata": {}, - "source": [ - "## **_Image_**" - ] - }, - { - "cell_type": "markdown", - "id": "1addfebb", - "metadata": {}, - "source": [ - "**_Image_**(s) use *IPX*, *NIDA*, *JPG*, *TIF* format. *JPG* and *TIF* were used in earlier shots (until 12000). After that, *IPX* and *NIDA* were used. *JPG* stopped being used around 17000, while *TIF* can be seen throughout the experiments. \n", - "\n", - "The *IPX* format **_Image_** type sources are stored in the `Video` object. The other formats are not currently accessible by UDA. The UDA API for reading image or video data can be found in [this doc](https://users.mastu.ukaea.uk/data-access-and-tools/uda/ipx)." - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "36d0d773-42b4-48fe-9943-412e68be04e0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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typeformataliases
0ImageIPX{rir, rda, rgb, rbb, rba, rdb, rit, rbc}
1ImageTIF{rzz, rbe}
\n", - "
" - ], - "text/plain": [ - " type format aliases\n", - "0 Image IPX {rir, rda, rgb, rbb, rba, rdb, rit, rbc}\n", - "1 Image TIF {rzz, rbe}" - ] - }, - "execution_count": 65, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_1.loc[df_1[\"type\"] == \"Image\"].groupby([\"type\", \"format\"], as_index=False).agg(\n", - " aliases=(\"source_alias\", lambda x: set(x))\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "87877088", - "metadata": {}, - "source": [ - "### **_Image_** `SOURCE` & Data" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "id": "c7e71257", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭─────────────────────── <class 'list'> ───────────────────────╮\n",
-       " ╭──────────────────────────────────────────────────────────╮ \n",
-       "  [                                                         \n",
-       "  ListData(                                             \n",
-       "  │   │   shot=27933,                                       \n",
-       "  │   │   pass_=-1,                                         \n",
-       "  │   │   status=1,                                         \n",
-       "  │   │   source_alias='rba',                               \n",
-       "  │   │   format='IPX',                                     \n",
-       "  │   │   filename='rba027933.ipx',                         \n",
-       "  │   │   type='Image',                                     \n",
-       "  │   │   description='Photron bullet camera A',            \n",
-       "  │   │   run_id=-1                                         \n",
-       "  )                                                     \n",
-       "  ]                                                         \n",
-       " ╰──────────────────────────────────────────────────────────╯ \n",
-       "                                                              \n",
-       " 35 attribute(s) not shown. Run inspect(inspect) for options. \n",
-       "╰──────────────────────────────────────────────────────────────╯\n",
-       "
\n" - ], - "text/plain": [ - "\u001b[34m╭─\u001b[0m\u001b[34m────────────────────── \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'list'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m ──────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m╭──────────────────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m[\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1;35mListData\u001b[0m\u001b[1m(\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mshot\u001b[0m=\u001b[1;36m27933\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mpass_\u001b[0m=\u001b[1;36m-1\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mstatus\u001b[0m=\u001b[1;36m1\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33msource_alias\u001b[0m=\u001b[32m'rba'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mformat\u001b[0m=\u001b[32m'IPX'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mfilename\u001b[0m=\u001b[32m'rba027933.ipx'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Image'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Photron bullet camera A'\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mrun_id\u001b[0m=\u001b[1;36m-1\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m)\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m]\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m╰──────────────────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1;36m35\u001b[0m\u001b[3m attribute(s) not shown.\u001b[0m Run \u001b[1;35minspect\u001b[0m\u001b[1m(\u001b[0minspect\u001b[1m)\u001b[0m for options. \u001b[34m│\u001b[0m\n", - "\u001b[34m╰──────────────────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "data = [source for source in sources_1 if source.source_alias == \"rba\"]\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "60ded376", - "metadata": {}, - "source": [ - "**_Image_** type `SOURCES` don't have `SIGNAL` names and can only be accessed using `SOURCE` alias as an argument. In order to read the *IPX* format we use the `get_images` function, and the `get` function for reading the other image formats. " - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "id": "ee509775", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
╭────────────────────────── <class 'pyuda._video.Video'> ───────────────────────────╮\n",
-       " ╭───────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  <pyuda._video.Video object at 0x7f8eb57cd860>                                  \n",
-       " ╰───────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                   \n",
-       "  board_temp = 0.0                                                                 \n",
-       "      bottom = 952                                                                 \n",
-       "      camera = ''                                                                  \n",
-       "    ccd_temp = 0.0                                                                 \n",
-       "       codex = 'JP2'                                                               \n",
-       "   date_time = '2011-12-15T16:00:12Z'                                              \n",
-       "       depth = 8                                                                   \n",
-       "    exposure = 1667.0                                                              \n",
-       " file_format = 'IPX-1'                                                             \n",
-       "      filter = ''                                                                  \n",
-       " frame_times = array([0.001673, 0.021673, 0.041673, 0.061673, 0.081673, 0.101673,  \n",
-       "                      0.103673, 0.105673, 0.107673, 0.109673, 0.111673, 0.113673,  \n",
-       "                      0.115673, 0.117673, 0.119673, 0.121673, 0.123673, 0.125673,  \n",
-       "                      0.127673, 0.129673, 0.131673, 0.133673, 0.135673, 0.137673,  \n",
-       "                      0.139673, 0.141673, 0.143673, 0.145673, 0.147673, 0.149673,  \n",
-       "                      0.151673, 0.153673, 0.155673, 0.157673, 0.159673, 0.161673,  \n",
-       "                      0.163673, 0.165673, 0.167673, 0.169673, 0.171673, 0.173673,  \n",
-       "                      0.175673, 0.177673, 0.179673, 0.181673, 0.183673, 0.185673,  \n",
-       "                      0.187673, 0.189673, 0.191673, 0.193673, 0.195673, 0.197673,  \n",
-       "                      0.199673, 0.201673, 0.203673, 0.205673, 0.207673, 0.209673,  \n",
-       "                      0.211673, 0.213673, 0.215673, 0.217673, 0.219673, 0.221673,  \n",
-       "                      0.223673, 0.225673, 0.227673, 0.229673, 0.231673, 0.233673,  \n",
-       "                      0.235673, 0.237673, 0.239673, 0.241673, 0.243673, 0.245673,  \n",
-       "                      0.247673, 0.249673, 0.251673, 0.253673, 0.255673, 0.257673,  \n",
-       "                      0.259673, 0.261673, 0.263673, 0.265673, 0.267673, 0.269673,  \n",
-       "                      0.271673, 0.273673, 0.275673, 0.277673, 0.279673, 0.281673,  \n",
-       "                      0.283673, 0.285673, 0.287673, 0.289673, 0.291673, 0.293673,  \n",
-       "                      0.295673, 0.297673, 0.299673, 0.301673, 0.303673, 0.305673,  \n",
-       "                      0.307673, 0.309673, 0.311673, 0.313673, 0.315673, 0.317673,  \n",
-       "                      0.319673, 0.321673, 0.323673, 0.325673, 0.327673, 0.329673,  \n",
-       "                      0.331673, 0.333673, 0.335673, 0.337673, 0.339673, 0.341673,  \n",
-       "                      0.343673, 0.345673, 0.347673, 0.349673, 0.351673, 0.353673,  \n",
-       "                      0.355673, 0.357673, 0.359673, 0.361673, 0.363673, 0.365673,  \n",
-       "                      0.367673, 0.369673, 0.371673, 0.373673, 0.375673, 0.377673,  \n",
-       "                      0.379673, 0.381673, 0.383673, 0.385673, 0.387673, 0.389673]) \n",
-       "      frames = [                                                                   \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadce9710>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadce96a0>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc54400>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc54438>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc54470>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc544a8>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc544e0>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc54518>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc54550>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc54588>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc545c0>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc545f8>,                  \n",
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-       "                   <pyuda._video.Frame object at 0x7f8eadc67208>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc67240>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc67278>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc672b0>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc672e8>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc67320>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc67358>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc67390>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc673c8>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc67400>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc67438>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc67470>,                  \n",
-       "                   <pyuda._video.Frame object at 0x7f8eadc674a8>                   \n",
-       "               ]                                                                   \n",
-       "        gain = array([2., 0.])                                                     \n",
-       "        hbin = 0                                                                   \n",
-       "      height = 704                                                                 \n",
-       "    is_color = 0                                                                   \n",
-       "        left = 1                                                                   \n",
-       "        lens = ''                                                                  \n",
-       "    n_frames = 150                                                                 \n",
-       "      offset = array([0., 0.])                                                     \n",
-       " orientation = 0                                                                   \n",
-       "     pre_exp = 0.0                                                                 \n",
-       "       right = 768                                                                 \n",
-       "        shot = 27933                                                               \n",
-       "      strobe = 0                                                                   \n",
-       "        taps = 0                                                                   \n",
-       "         top = 249                                                                 \n",
-       "     trigger = -0.10000000149011612                                                \n",
-       "        vbin = 0                                                                   \n",
-       "        view = 'HL07 + 25mm lens + HeII 468nm filter'                              \n",
-       "       width = 768                                                                 \n",
-       "╰───────────────────────────────────────────────────────────────────────────────────╯\n",
-       "
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\u001b[3;33mn_frames\u001b[0m = \u001b[1;36m150\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33moffset\u001b[0m = \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m0\u001b[0m., \u001b[1;36m0\u001b[0m.\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33morientation\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mpre_exp\u001b[0m = \u001b[1;36m0.0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mright\u001b[0m = \u001b[1;36m768\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mshot\u001b[0m = \u001b[1;36m27933\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mstrobe\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtaps\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtop\u001b[0m = \u001b[1;36m249\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtrigger\u001b[0m = \u001b[1;36m-0.10000000149011612\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mvbin\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mview\u001b[0m = \u001b[32m'HL07 + 25mm lens + HeII 468nm filter'\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mwidth\u001b[0m = \u001b[1;36m768\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m╰───────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "data = client.get_images(\"rba\", shot_1)\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "5f0346f0", - "metadata": {}, - "source": [ - "**_Image_** data is encoded in the `Frame` object of the `Video`." - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "id": "3ccd1066", - "metadata": {}, - "outputs": [], - "source": [ - "frame_im = data.frames[11].k" - ] - }, - { - "cell_type": "markdown", - "id": "23c4609f", - "metadata": {}, - "source": [ - "Then we can see an image it is a grey image with shape 704x768." - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "id": "409f69f3", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(704, 768)" - ] - }, - "execution_count": 69, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "frame_im.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "id": "56d66cb7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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qWzt41jG147XWlmscca3P9vA6SfhF+Fj7iOtgHvGL+62treUv7nltJfx0EVf11UGQAbcDYTd7hXuUm9cbHBDwrhefDN7a2sLOzs7KT8us9Rp14HbQ9Kf6qn4ujutTvHjPfto/MgBXXTX9rI9Vfc8Buh5nyNLM1vJ6k22XqUzT9P+01u4V5wcA/Pji+n0APgHgVxfu75+OavWTrbU7Wmt3TdP0N718qllL/bOZLFuLobIs/6tKcWHcLDaiW5afNjg3YPjrQIiBloFD3G9vby9BZGdnZ+l2eHiIM2fOYG9vbzmb8YfR+fCbEzeY1J/1d7O2Mgie9QMMXJ1W0lvo1jK5hc/KTMjyVHBVd9cHdLsZyFlptkAb6bCuvfGjDDzYi1u45s0D18dfqDWVOwkovgrgzsX13QAepXCPLdyOgUpr7UEcsZkVRXuAkA1aoKabGaVVs8ul6xoGOP5SaUZ+bvDoSO4gGXfCWIzlGY/jx3d/OB03gwRLiRl+e3t7eXr26tWryx0f1ScGdJyeVbCuTFRlOu4eqA/5hVRmS9ah3btjep1f10UYWEbEzfCcbtWndZFXJywVXl+LMFtbW0tgcH3L6doDaNYtA7WeaX7DC7XTNE2ttTGDbTXewwAeBoCI72Y+5+7EgY3699Jx7MPFycJkoMTbzAoIvAbSWls+4JdtBe/v768M0EiPB+i1a9dW0tOHCnUdhRdsgVWWkZmOMdtVdcp+JwEQdcvaN2OgESfLI3bYevr0mIuyMG1Tl7ZjGVn/74ky1kwfLY/rt27iqNZ8nJwUVJ5oC7OmtXYXgCcX7o8DuIfCvWbh1pWqAt2s6OI5uhnuWeP2aKPG1YZTluDiugZnXTgumwJZmZQFMaMBrr9LNraiY0HWMRqu32zhj3UdXXx05dT0tO57ZmnVVlq+bNZXcIrZPtwzHdzs7MyHaZqwtbW1Av5a9oinbE5NQ8c+svKwH4Mp970MJDS9kbJX7XRSUPkIgLcDeM/i/8Pk/suttQ8AeCOAZ0fWU1gyRjHHLVvw1Q6naWR5ZzsRGZhkabmFM/XXPBlsohNyh9S1F12ojLWVMG9iTYVnKl5bYVbFYMVmmgNlTiurRyc6s59U5szyPEiUKSjoKGvrTX7RBpEHt7nqN9o/glVl5tzIgbgAGTWXovzO1NG64EmtkpEt5X+Bo0XZV7bWHgPwP+AITD7UWnsXgC8DeNsi+O/jaDv5ERxtKb+zl76KzhZVZ3HmRmX3axzXsBng6EKXa2BlEpEGH25znSybvTNW4Gam6HjRoRlsYnfkzJkzS9ayubm53EWJBwv5SWW3zcyglc3Cqn/P1h9dv5gjDAR6zWXJBmnFiKp7Z9YyKLP0WCHfaz8fXUx2wDIHmDhepOXMYpWR3Z9fTLzeYsJOAH6pl+aIaKOPLGZlg1MBgd2ztEbjKANys11PsrDKGlQPPiCnTIEBJRZgY+FWF735mneAeAaLWY7TVnGDlt0ctWdGxGEcEHA5uR7YPe55ZuedDp00lAFoOrxInunGccIvTKDeJKLxsz4c9zqY3e5PVh5On5lUlKkC/2qsqKzFiVpXkZWJEv8ZW3DxTnLvJGM/rBNTzBiE7rOjymq4s+o3gDivrBNF3mH6xNpKLP7ygbdIN0AnTtkqM+FvMLPu4V+xQgdaWv4QHXz8raKqXUZYXzZBOD3ZjfuallknubhnkFJAjXqMXTwe6LzeofWq+ke6ziTi/terK45brZWprj1ZC1BRRgLkCJuheoiGcw3PeWkHqWbCnp5xP8pU1FyKa6WaLNlswrsY8ZY4juN2ACLPK1euLJ9cjoGhA94xhpEOVs3KVVoZKziJuTQKThlQsPDgD704fPgpw4nwfMKZmQ3roXmpjmpeu7K4+K4cLCN1q+PLyVqACotT2gFBXId/VsgMkFxeo/+V3j0dMgDLytjLy82ovKYS51WAI6ayvb29LP+VK1fwzDPP4MqVKyumgktbyzOn/MBxYIsZN2OcHK+6d2aSGxx8jL5H891kE36VvhVAqCmr/tlk5Cay7D7SiTJwuKrPqZnI5cgm4krWClQqYMj8R2bLk8SpOk822LjhMsAY1W+E5VTxdWcIuP5i7M3NTTzzzDN44oknVhhKgA+LgoHreBEOuD6w9GHI0IkHrWMxPdtdB7bbicqAZ+6htko/Nm/DXRemOZweXmN/5666aP5x71ithqsWqDNWo2s1o8wUWDNQCckoc1YhgN8ydjNLNvPqzNQzryrEdmssHE8HBIeL9RR3sExpdsTJqGx0Cn2z/rPPPouvfvWry7UWBp5qZmQ37ajZgA4w0W1jLhs/ldvruBWYc9lZl2ynxLEn11e4fRQ0XL6cpstb+2U2gWWMxS0u80E+7ZtuW9xNetqGme7VhAasGai4ylZ3R0td5Tuzx+Wl8Ti8y9+lowOMZzC3Os/hdIaPePz2/JjpdNbgTuxmmmm6/mRydLoLFy7gySefTE1HNzMy+I2YOSpRDyo6QJ1U4K5trCxCwYXXsDLRdub+5LaJtS2qcrAe2l5ZXYysi7Burr6if0Q/cJOu24LX9CKNXputFahU6BnXirRa6ZXZEuIqPgOek0jop/pqAwGr5gKDCYAVxnJwcICtra1jn+oIwImOwexFWcXBwQGeeuqpJcjFaVIts87erm54NyQbvFonKo6W6xmMHogpe8jMMk1LBw/Hr/qhLpKyf3ZAjbeXM9ZcsR/HaLO6cGUAVheIOW8HbuGuk+7ou3fWClRYslkoq4xwy+x1TbdnuzvgymbMESCLhna2t6PCboBmZeOO5kA2OvzFixdx5coVAPVuirP/K9ang0VPrGai5mZPKnNWqfucdZTezKt5sT4ujANHp5M7p+MkW1B2+lQL16wX70plZn9lXlfttVagkgGHGyj8r9e9dJ0fp9OrxGpQaxpuxmYazlvJfA0cP8Ku9P3w8HD57hVXlojHW8eRrpNslg5xIMj3XAaOowOsB+gZ/WbTkgdCtRCZiRuo1dqHsgctg1t/0IcV43xKlR//c5kynbjtHYC5NPll5+qfgZvmV8lagQpQMwcVN4uPMJEem+FwlU5OD6dXFpYBwl2rjuHGNn00Ng9c7Swx6Pb29gDkVD87+zDSJgFearZoZ1V7PsJmQODq0bVflDP83BPImSiIqZ/6O0bgZvgeaOgZF8du5orqr0+f98DDpRHhGcxuGaYC5APZAQgLd9Aeg6nMiWwGrPRlMJsrmS3N9243I15p4NiEW1uZpgl7e3srdn9r17/hM1JWB4asX/hxnbjOm7Ut13l25iNjSVxfmm/Vp/R6jhmi+fQAQf0ciFRA2NNf66bSrarDDPAzJqWydqBSgUB1zfcZU8jWSLIwo0wlC1NVvgOjsHVj1g8JVpKtf3CcmFn1GZ6gvLHYqwvEc/XPmJi2gdu2jX8Gda4HPYVa1WEGXFqGaZpW0p3DCCKu6ze8G8ID0plNrA+XNfNn9uL8QkbAg5liBkaOFWv93lLmT2W2aGVm4DEKAq7BeWApRVfdMnMnM4H0vlrT4J2cCO86vx4k4wEW4fXlS/z6BGUs2lG5Mzr2EAPKibP5s3BcN9lAcfXvTBLN3zGDzEzUPJ3oTB1pzDFXAoS0fjNmxeln40B1YjcNw+tBHEb7UeQTYVwbZbI2oDJqOowwlV5armJ0lmF3bcSeeaVxVUfXQBXLCnPD2cTZrKhl3N3dxe7u7vJbyqoT55ltK6pUB7u4fNkpXM7fpVOZJ+yXfYbV3Tug0TDZ4Ml01HrqTUC9BVt2d2zOmZsKeFoe1VfL4ZinpjtNx5/0drI2oBLiBmzWsTMmkaVXpZGxiswsUFaVgYSmxwzE2ci6C8Sf8+BZjfOMQRUsRN+Jsr+/j3PnzuFlL3sZ9vb2luaQ1pMbIJFGdKhw086lC7RRhozNZKDAHVnBrWJHLl6WJw/q0XiufylQqpmS7eIxWPTKUoGFsgvXnxSENKxjX44BhTiGp7J2oJKxCKC/ttKjZwogGYV0qO3is3sGRK5DVulGJ4hrpsvhp50/gIdPzu7t7WFnZwfXrl3DlStX8E3f9E248847ceXKFVy5cmVlW1pBj38qAVy6XsOSDS6uq1E3vmedelufLJn5mC1cZjO8MwUdsGo6/KqDCOf6kF5rORgglA3phKasRPNjHbj/ZmAT167/q6wdqIRkAFKxEmUu6ucWvNg/y7fHZjSfTC9Nk/XSDsCnaXX3R9kZMxUGof39fezt7eHatWu4evUqXvGKV+D555/HU089tWQz7syCM9kcQ2Ag5IGng1XBgHXm9Q3AL1xm4OSus4HN9cZ6qJ49cQueWb9zkweno2d6MmBQf5dP5efcM6ZWjS0Nn8nagEo2SNXMcKIN6hhDxSIqIHI69tA7a0BOMwvP1/xNZGD1SD+zEmYqrbXlDk985vTKlSu4dOkSXvayl+G+++4DAFy8eHH50iY+fr23t3fs+Q5dTGSdeBZ2A44XMxl4wl+/35yBiPr3dnwcW3FrQHOePXLMwYXP0ql0rAAo65vcF5nNZjpm+Wn5enn1ZG1ApcdM1K83I2glONsz6yyaRo/uOV25geawGmB1FstmNKW/PMvEcyYBLgEszz//PF75ylfi/vvvx6OPPornn38eV65cWS7c6pvhVFc9NKezlw54d6/gwuEi7cytqrcKiLheKzcuD4AVMHfAX/WbTJRVRD7aT7I8qt0dTZ/T1fAubfVTfW45UKkGofOLQqpJw+HiusdEMmR2aVUdWg+yqb6aZujGwKGdSc0ftel54TZYQ1yH6ROAcubMGZw/fx6vetWrcP78eXzlK1/B1772teXH2qdpOvYUq3uGBMDKlw3jFQqRRvZ2s/BTMFT7/iRmjhNH57M2Zz8H2pU5ogPPsQC+53qJh0PdBJfl12MxnIf6c50oy+EwqvstyVRUssbngamDEzj+8hxOy6WneTpTphc+0s0amPV1ZQSuN7bbstNOEfkcHl7/oiGbQTF4A1iuXr2KK1eu4OLFizh79izOnTuHV73qVfie7/kefPGLX8RTTz21fPtbdCg+IMffD+I37sc/gwWv0VSsREFBd4D4v7ebU7lnM2zGBNxAdHkpI8j00d0+bT+Or6JglZnulY4Kji6cLhxngDrK2NcKVCpkrBrZDU6XdlUpFRjMkZGGrXTJOqoylgAgAMsPhzFTaa1hb29vedDt8uXL2NzcxO7uLs6cOYPd3V28+tWvxvd+7/fir/7qr5bvWHGmBm8rq3uwFAUWAMfiZUATYeO/tzNT9QU3yFzdV2CjujnTJMvfiRuYDCzZuk4vnwwAWe9M/yhjvFKDw1d6jIDLyHd/7gHwfhx9L3kC8PA0TQ+11l4O4IMA7gXwJQBvm6bp6XaU40M4+v7PJQDvmKbpM718WPlsBhG9nK4pcrvBnHWSEao32rE5b007yyc6m7ItNpfCTSl0DHLg+jNC165dW741/8KFC9jd3cXOzg7Onz+Pu+++G69//evx+c9/Hl/60pdW9In4/KExZizxzWU+F6MsRXdzKoDiMNmsGmEzFuriVUynMmmdWZOBWg9wsryUyWSTpUsz4lRlyuok/KI/6btgsnocmWRHmMo+gH8wTdNnWmsvA/Dp1tofAXgHgI9O0/Se1tq7AbwbwK8C+GkA9y9+bwTwG4v/rmRgkpkOPZsvszW10lXYL6OgChRON+38WV48ewLHHyDU8ukMx1vKATD8zZlwD2B57rnnll8rvO222/Ct3/qteMMb3oCtrS184QtfWObDOzMKKlEfbAqpCaPMhf0USHoUXevQtUcvvGMGFWPR62gD/VoBA33cs2QTXaSX9ZMMZBzzcsxey+b6dfaZD/2v2kVl5GNifwPgbxbXF1prnwdwN4AHcPTlQgB4H4BP4AhUHgDw/uko90+21u5oi+8uD+RVDlTnzuJYiGvQanA79xG9Od+qUzldMr1iAGTA6hZ49VMd4R9PKMfaSphCZ8+exdmzZ/Ft3/ZtePOb34zWGj73uc9hY2MDly9fXppQkZ+CCF8rgPD5FO6U2RZyr4511uW4SvFd+hqH69wNSr6OeLoTF8JnjVSPXvkqIGHhMjo24oDElUfde8zcjatKZq2ptNbuBfCDAD4F4E4Ciq/iyDwCjgDnUYr22MJtBVRaaw8CeFDzyJhENlAz8Kgqlhs+Yx9xX+mQSTY7ZP7cGRg89OyB6/Qxy7G5FAOXj6PHzhEzl/jO8pkzZ/Cyl70M99xzD37sx34MGxsb+NznPrd8037kE+mqSaTmjzN5+F/LktUZX1ezcEXxezOs88+YaqUn76qM9pPIg4E3i9tjcBy/x7w0rPbRuB81d1SGQaW1dhuAfwng70/T9JwMkqm11p9uSKZpehjAw4u0J/E7NtDdgGf3rAKytKowC51K5M/00PQUMMJN02D3mBF5duS0QiK8+/qhW0fg/ANk4lOo586dw5kzZ3DXXXfhR3/0R7GxsYHPfvazuHz58rG6iYXUYCi8tsL1lS266sDsDQp3rxODK6cORNZLw1WgX4ljT1lcNzlEHH0cIwOGCkAzc6nKV9OfMyFmMgQqrbVtHAHKb0/T9K8Wzk+EWdNauwvAkwv3xwHcQ9Ffs3A7sWTsRXQccstmA+fu8pt7zW4KMBUzcteaHrMTvtY38fOnOCIu7yAFWzlz5gw2Nzfxqle9Cm9+85uxv7+PT37yk7hy5crKC6F0wdYt0kZ5HKC4WbLHBEbcHICzu2OzzEZOIm4yqdJzQMDHCEYno4qluX7ME4JOWtV4cOZRr75Gdn8agN8C8Plpmv4ReX0EwNsBvGfx/2Fy/+XW2gdwtED77DSwniJ5lvc6KHuDP+6rRh+tvAwQ1N+Fd/cuvurcCxedJGY7ftlTmCaxkxPpBqiwGbS9vb2shzvuuAM/8iM/gv39ffzxH/8xLl26tMyLwYP/9dCb05fjZ2Vx9aBu7O7avQc+jplmbefS6Q2srJ9ULKQ3kbhyZf01K1cG3o6VZ3r32MoIU3kzgP8KwL9rrf2bhdt/iyMw+VBr7V0AvgzgbQu/38fRdvIjONpSfudAHkvJKFdmOmhcF49ncs4jRCvU3bsG023fTD/V3zWyi+s6UIThB/K4fLxzFCCyubm5spOjM2uwle3t7eUnUw8ODnDbbbfhh3/4h3H16lV84hOfwOXLl5fx+OCbMg52512SaqBnwOI6dtWpKyDg69FB6+L2BpgD0Ky9R9LWMZGNkSzdqmzsp+DC+WVlcDKy+/PHALKR/BYTfgLwS710TbxjM8joAI1r9u81iIuT6ZJJr/NyOAdaFQNjHVyH0boKtgKsrhnwdWur51jCLQ7IhVsAUhznf9Ob3oQrV67gYx/7GC5fvpweYFNwYbDrsRE36KN8brvWDSy97/UVV/faDk4qtpBJb5DrxDfKkDIWUgFfBmZVf9R0qjKv1YnaTLLBrZ2kxxiyNF3Hc3mN6OHCVB3bAZuCCcdRxqWLuJmebPq4FzQFQ4n//f19XL16FXfccQduu+02vOENb8DVq1fx8Y9/fGVXKPTQrWPAv8wpE60HB8QufE/mzNg6uDJQ13R6DLPSTftBr84cQAA4ti7j0o74WRosumhcpamyVqDiGMPIW96ztEJGKkLjZGk4fUdpoUvbdYQKHDIdKsbGuzCxU6O6aj3HIuyVK1dw++23Y3d3F9/3fd+HK1eu4BOf+MTKGos70q66OJ2dH4fRusnKmMVnUb0ynUbrntvPgUtPtwycKh1dfNXbld3poiy3Kl8VzslagQqQV3hIZg5k8V1DjyKuiz+ic+VW5TkyGFU3HgQMcjrLxvNBnBabRvGhsXBnULl06RLOnz+P7e1tfNd3fdfSFHrmmWdW9NHDbtnA0g7a66zuFGxWR3NZg6tjZYaZeVCl5/RzjFWPQkT+vX7vrnVi0nyzcmZAlqXXA5i1AxUgR9aqonq2qEujl6dzH53BHJj1ZkI3A2dldvlkujFTCdCINRReY4mwnMe1a9eWL3g6c+YMAOCee+7BG97wBvzJn/wJnn32WVvGrEyjD+pxPbnOXbUji5v93eSS1aGaQz0Q6/Ux/leg4rKq+eHKr/U9UjeuPquxo348YWWylqAyMiMA9eDrDbYKLHoA5cKOMCz3qPtoR+1RaTdweL2FmYp+vY9nSwWVeCDx2rVry3Ms0zThW77lW/C6170On/70p/Hss88e+y5ONsO5/6wueibCyL3WSdW3enFHpAKsSC8Dnmiz7OSxYzVZOZz/KAPmcjj3Km9gTUGlorcuTIhjB5xGBgZZ3Kri3KyR+Y+wqJMcidZZRvXlNPkjWvwqyhD9bEekr6Cys7OzZDC33347Xvva1+LP//zP8dxzzx0bUCNlGh2sDHqcpjsqMMpMs4lA21bbuTdYXVyXf9Z/p+n4R8ocK+n1d5cn55XVVzZROl2drCWoqGQztSt0BSbuadA5AzmbJVx+mndGX53unLZ7gG0uEEbnZqakR/uB6w8Mchr8sqdYVwGAa9eu4fDwEOfPn8d3fud34i//8i/x3HPPpfXFemQg71iN+jmgztq8NwPrC8dPKqODuNKFxZV3NP2sX3G6DjSziS9jeLccUwGOg0MFAtWMNGLWzGlwF07Trjr5SN68PViBl8Z3gzXc+b0r+hVEfvDw8PBwhbVEuDjstru7u3zaOfx2d3dx33334Ytf/CIuXLhgt5cdSFQDR+urmpWrTl+1Y1VfvbpWXV2+2mezga8ML1ie053fbFgxcKdfVhfuEKfG1TF2yzGVqnCZW4W0lX+EmWt6cL4jppDqw/eOMWi8jNpmoObyZ/MH8B985/wjfd7VCYbDrz6Ypgnb29u455578JWvfAUXLlxY0UXZycjsmF3zoKvKrGWv6syBiAKCAy8Gg95sXvURLoeyqKrvZH2i56f++voMFu0LVV2HrA2oVLTV0TZ2Uzu7N6irWWJET42fdZ6qPK7s4ZcNBO7oOthcOSKMzkQ6MJmxhPBrIjmvYDoMKvxowKtf/WocHBwsz7G4cjgmk9VV5e/6BPtpOE5Hw+hT3VwvGXNhcQ/oOcZZTXoa300urr+5Mjpw1LhxrXpqXbmxWbXT2oCKkx6tA44vVmbxNU74V4Dj3LSTjbCqHli5BnL5utk0K4fT1aXLL8yO+4jLgMF5x4uwmcXE9cbGBu6880488cQTuHjxop3dRoDA6coSaTj9nCjzcOk53XhAVmyjxwhcv1KGymGzF6D3+h6HcwCSTaC9ccDhqnoE1ghUXCFdR3AdlCVjPCMspKdXj/Zx+GoWHgUiVxZlGapbNoC5E+uukH6LOa751ZQ6wPjFS/yLuK985SsxTVMKLE7vXpgsnvvP2r43cWTA5gZyxiiz8lTtrm0UbeFYpgKby4PZjvuMjergnq/KwipgqawNqGgn4YrL/FgyBHZSpZOZGCNxXZysE2YznUuDOw/XC78bo4qb+Wna3LnY/NG02CyYptX31HLYO+64AwcHB7h8+XI3b+c3Wi+hU2/waNohGRPNBmxmAmh7KlhxnWna4a7hXDountYRu/NCfNSV6u2AKgPoXv2uDahUUlG1EG2obDaqKsQ1dI9quriOLjtxulYzmyuf5uUGgqsLDRvAoG/m109/XLt2bRmXB7F761trDbfffjsAHHu6uapTF6Z6k50DIE1PB7dLS0Gb42f6qb/O+hyG3Z3Zpjs+CvQ68F0eThxYjYAU69gDEpa1AZWRWTyzQUfT5dmnF7diEpyeG8Aat0eZex1+RM9s9otOqeDC98F23JOp+uqE+OmXDONfn/0BgNtuuw3AdWDhU6NVfahbNnO6cFmYLA0HBBqX+0A20VVsiu/dIHX9u5ooe+ImRNc3K8bFekT8nqwNqFSs4GYMOr3PBn41y2Xh51Q4h3MNOtLA1UlVNxtx2m4mjDj6Hhb+n6ZpxSQKcGCAYEDht8ABwPnz5wEcAYvS8bkzYdU/dObN4o5MNsoGK9G6dAyDdRwpX9SzA7asX6tO/O/SyfLWdOaMvbUBFaC/TpENeGf6ZJWcNURFi3v6OZo4MnM5VqGiM6rrVBkVd53SlY3DxcJtmD2xfdxaW+76OB3dJzqU8p87dw7TNOHSpUvHTI3Rmd+VU+PMmd0zk6fKm/PI9HTP7zgW5fLK2lzzd/F6bC4r49y+VclagUrICCXOqDwwBjYOTKp4Wd6VqcP3VeeuZpm58VRvR9Wr8qnJFACjABGSmQ3MGrgznj17FtM04cqVK3YNwdWBu1em2Gszpx9L1oc0fKZr1v+cvxMHUtUkM5qe07WKo3HdfU/WBlS0sapKdUxkTgPqoNN4GRCojpV+7lrjzAEnFQeM1QyYddqss/DrEYKBRJ4MJPGWfQUPBSE2BXZ2drCxsYHnn3++O6PqJNBjc1zWqi6ywZvFqyYWl0cGgD3dK785rGG0TnqM0KXb65trAypzaFw2K3HnrjqNPv3pdGCpOukoqvc6IV87cOHOOqqL6pOxtiwuP3QYAMOf/2DRlyjFv66tRP3v7Ozg8PBwud3M5WIgyZiWK3uIe3K5iu9E28C1cTa5VExF4znGnbVxr30576wsmX4qc5iJytqACkvFHkIqk0HFdbpIs2qEjDlkjVvpkZkarmy9ODzoeh0qY0v67AzXCT8ZzUfw9dmhWGPhtZaKMYZfhN3Z2QGAlXMsDPpc3qx8nM8omDvTIGMFrq3dZMb6xXt++auQWh4968N58EJ2j51k7e/6htZJNnG78s4BmbUClRFKWlGvzM+l26NwnG/VkePapZ25a/mycKyHY2ZzGtrl6crjAAhYNV/CLR5CrJ5y5VOhTuednR201nD58uXlR+WdXk7nrGzOP+LPMSFUsn7Ahw/jPl4iHvexfsSnl3tpZ/ln48P1O9eu2YSoLKoCqUq6b5VurZ1prf3r1tr/21r7i9ba/7hwv6+19qnW2iOttQ+21nYW7ruL+0cW/vcOabKQUeagcUapHM8Upqw2jxFQq2a0SlR3nbkynbLwTi8Xlg+iqbv68bM9/BBh3OvBt6x+QxQ4tra2cPbs2ZUFYZe30zcrg6sXZSVzwTmr54q1VuF6elSMoWrzkbpwon1NmdQI8AEDoALgKoCfmKbp+wH8AICfaq29CcCvA3jvNE3fAeBpAO9ahH8XgKcX7u9dhBsSrbCsUrOK5QHhpKqwKl/1yzqyK4vG1cNhI2aT0zP7rwZZT7cqTIAJsPq8zzQdnV9hcHGi7aSyubm5/J7z1taWrZeejoBflxgBH00v7jVMiJv42E1NSG17zUcBmcOMsDCVETMoA+u5eal0QWU6kouL2+3FbwLwEwB+Z+H+PgA/t7h+YHGPhf9b2ijEifTMGeeefdKDGzVjQjpzZG4ubtXJHA2tRDtUBTwjM0iPgYW/1oMDbc0/6HwACj9YqDrwv/OLBdyzZ88uXwbFumU6cnlYx4rxunrk66jX3k/XTUaZpauDLA1tJ1cmJ2rCuHoI3bV+nV6jMvRRndbaZjv65OmTAP4IwBcBPDNNU7yK/TEAdy+u7wbwKAAs/J8F8AqT5oOttT9rrf0ZF2BAlxtG02zm6VWou2f3asA4yfJT92qWdOwri5elWbEz/q/OpAAomQqLA36d5Xd2drC7u2uZC4evBjyHndu2XC72VwDJ0swmAg6j9dBjQy6t3qSn4vpIxVZ77MXJ0ELtNE0HAH6gtXYHgN8F8N2zcvFpPgzgYQBorU0Lt6U/z0jaQK7xFZV7CK1heHbSiuW0e4O2YjlV/GxWqQZ8xlI4X1c3WXgWPaYfgMLbzJFesBN+k1w8R1StrfR04I/Hh/kVppYCHpdPB1sFmHofg56ZSmYeRXhdqK3K5waw5lENZA0b9yNmUMUgVc8bkVm7P9M0PdNa+ziAHwJwR2tta8FGXgPg8UWwxwHcA+Cx1toWgNsBPDVXMTcwRuP1wo7Q4xD3Wr8sTsaAHEg5P9bNpa26a6d3elVpu06dxWPwde7AcSCKAee28PndLiODPrZpY/ua13D0M66qV8Ygs1lb41RtH2mwGRHX2ftkXV1yPhnLcTLHXyfTrN+chJ2wjOz+vGrBUNBaOwvgJwF8HsDHAfz8ItjbAXx4cf2RxT0W/h+bbkBDN5hEv24aFdW9kcrrUVw3gzkb1unGjTtqxmT+GdiNlKuXThWOz7ho2ll7hMR6CvtzmM3NzRUTaXd3F9vb29ja2krPuei9Ajy3jerIayd8BkXPo+i5lOqzvRlQ88/1EwWvqj+5szKaP4vL0/XRSlqvk7TWvg9HC6+bOAKhD03T9D+11r4dwAcAvBzAZwH8l9M0XW2tnQHwzwH8IICvAfiFaZr+upPH5MDCoezI/egsk4UdBa457o518MwNeDNOhRt9NN+qPrJOq/9uMAGrIMksRJ9gduWIf91hyR5a5P4wstum2+N64K/Sq+oL7scnj3nAsx76NLeWJfTU9wNnrKLS37mPMJUsHe2zFy5cwP7+vq3ELqh8PcSBShJulls2+DReNpjiumdejOjV06MyP9if42kn6emX6ayMKmNOPFh08GjeDDxVeRhU1K+3/a7vZnHpc3zHoqr+n9VhxhgADyq8M8b6ZPrt7+8fK3NldjrJzB6On9VrleYIqKzViVpgdSbuVV42i9xo3nzdY0tzzIosT6eDzgxVPGVBcwDPAU7FhjR9XqBlHWJmZjOmWl+pBjm3iQIJA4q+g5d11ee9eIDptQ6+qp8xoOj6GwMJ65n1q9b8G/w5DIv7GFrVdi6/kf7aY28qawUqo7N7iBY2Q+eqcZyfNswIpazEDdgqzEh8Bl72438HTq7D9oAxq+dpmpYPGgKrABNhY7dIGUVWpwxKTnjtgvPlfwYXLU/FStVkYV0VaDK9MiCuTEEnvb7Heo1Mdpm7jpmsT2VpOlkbUKkKGzI662pFjSJtZUe6+zlhRvPOBrTLQ1/A1NOLAUXpr/vndGOgxYCO96yE8MDmz0vw7DvK4nrt3Ovc+hDkHAk9K9NtJF09fewGalw7pjQ6mHtAweGqdai4zybjUUAB1ghUKnEDzQ3iakDPZRQj95qv6shxemDjBrPLW0FktFO5MjCwuPL0AJDXD65duwbAmxmZjq5MEc4NXAYo1tWxlrhW1sJpO+DQwaRhw48Blcutps80rb4UXFlVr+0yMNL7EVat5XOTR2+CqfIIWRtQqQZ9j2mMMJiTmB1Ojwrg5uafsYwKXEZmkB6oxhO0AJbf9Il4VV2pfsyYOI6yFXbLOqk+zRx6ctyM8fCAcnF00ZgHNptvrBeDRHWKNjN7Ip57QpvP1fCu0DRNK9+xVsnafZStqmg7O5Cp3DNZG1BhmVuIOVRtNN05+fdklIVw+BGTSdNweWiHrxhTbyZkIOHncji8zupcFscOIr4eYOP4LrwL4wCJ8wugc8fjuSy6NpOxy54wM2GmkOkYrIbzzFhkTy8FdA3v7kfllmEqzqRRv6pBRyg8u/UqVMNUs8QcGjoqnI7rMFofrtPqoM7KNWICuYF39erVpRnAx/fV7GDW4nZrKkCJGX+krrR+uD4y06liesFkMhO6p5frx2qecbjQp2fCzHUbGVecf09uGaYyOhuPxsuYQQ+cnDtTXGfnZ/lWM0PWGVx8R0Mdda3ydP4xYPWTGT29QuJZnCqeO017UuF1lt5iaVbezC/LL5uAes/79Nhy1pd7E17F3DLQyKQaC9Ukf8uAykllBDjcTONosIZn2h7+OuizGV2vna49AFC3no2s+XAZ5rK8UQDI1jkyMyhkzs4M1yevy/AHzTjPXrpu8TYrW+TvGFMFABmoZAvQyuRGGEOPkVQTXk9Xx2ar8Cy3DKiMDA5Hg8PdDRxHh93g4LR7ZhXryn5OvypsJa4zOd0zhsED3IEt6xPhssf0OW7UVay3uAVbl8+IO5eTzaWeCeJEB3UGMpq22wXqrWU4dpe1edZeIVk/dnk73UbSPAmYqdwyoDJCWTOEzho+Q3LNy5kcOih7po3Txa2DzJWMyWQgE/+6aFoB45zZmMO6nRj2q9ory0/NH33lguab3btBreZVJXPYHOej9eAGtTLMrJ+E39xJNnPL+vDc/nnLgEplh1aFzuJk/r3w2WBTd+c3Skc57ZGZO5ttMuBznVTLNNfsch2yGqDsF4u8Lk9On81PZ47wLoozjyJMVe9ux6cqJwOZvuZA68NJFZZNSwf6lZ4nkQxgsn6WyS0BKtUA61VuRU/V/ySzjw7WzJQZtWWruCO6uQ7oys+7Nc5M7Jknrl7jXs9/VOKO2FcMpurcvbZ2i8Y6iKuwLs3IU02dbL3mJEf1NT/OV/XoDfpeH1d2pHFvKVCpCuvoIV87JB0xR7iSKtqvNNMNQs1rZHap2FemryuXDugM2DSdbGYF6jUUpeZuAbM3wLROWf/q4T+3Xa2is7uWLz6I5nTMTtmyjs4/8nPPDGVpa7/mI/29wdtjkFXfzOql5zcqawMqPdNgxIzRzlTFde7ZoO2ZS1kDV/GyPCsZKUdmzrmBlpk84c9p9OolK4+G0VOmLg0HFpnJE+FDgiHpZMPpcJgoSwZOVbkUGLl8TnSRtmK4vYlB9VMZAYWsTXuMr9df1wZUVHqA4sJrg40M2GzwcKfUGYXDj9DwrDw3AiajplCmQ9xnHXoURDRd3e3RunCLtj2Q4mue9d2pWU4nm3Wz/KrdH2VSjkVpGqqvPoZQDfzMzFK/ipGNSFY3LNrPe/msDaiMmD9z/F1F68ygjZylm+nIHSszabKB6tJnPbNOxP7q5vQCPO1WM6Y3MynDyXTguuW85wKjrm/0AIDDavld2rxAzG5ZutyOulWugOLMl+r8CaeTmT4jzMWlqW4j6ShrUbeerA2oVMpmVFOlRxWzGVTpdjYQKvNgRI+5HWKkIR2Y9YBOdanAYSS/TEe3EAwcB4QKACL86HmUkS1h3bGpDsM500rd3dZ8lh7Xn4at+k1WR4799MzkkwCTY+2ZrA2oALXdGveV9GZw586zTNjsrmEqXSo2Uuk3R18WN5Nk5XM6qVul9yiwONaTDfDsVKnzVxNk9CRuDyxGRNMYMad7MtdU6YU7qT7ZJDsCbLfUmorOtOwGzLPtXRylsJkNn4GKhgn3zNYNNzfwevpyOiMN6WYrx05Ul4p9VR0sYwJOTz2J2jvRygNYzRJlBaMmlAqnqeE03Wr9Z5r8k8jZjhf/Z/4scxjCnH6lfdGNPY2nZlomawUqIaOV79YFKpahbi4Mb7NW6xTs7sK6PIDj7yrV9FXfTI+sTlx5M1OoApVKtL65bMEmtHzuNKuanwwukY6WVc0Exx4rUy8zwbLy61PFYQJlABDbwppmVl8MblGWXjtoe/bM22jnrN6yeCPuTtYSVDKpqHj8Z8+asPQaQUHNrR1UftVaw4iZUek/ao4488YNLsCf3MykxxbnMCrA79xkx+wrfVh0DcYxSY6vdVXVQcUk3YTj7hWo1L/HEjXtOSa3MtRqsq2Yd5Xn8NNY7eh7yp9trf3e4v6+1tqnWmuPtNY+2FrbWbjvLu4fWfjfO5qHFoDvR0yejHZWaffCZrNfpoubDUZnIM6Tf71wnHaPula6uQ42py1GRHXVmZ1BJWR0TcQBnpZN7+eWpQIg7X8nraeeWVdNiOpeTZaj8VzYqi/PecTzV3D0ZcKQXwfw3mmavgPA0wDetXB/F4CnF+7vXYQbkqxzZx3fDQLdcXB5KHV0HS46SA8U1H2UiWRUNBvsLo4OSK2XOZ06A8NMd62f0EV/WmfV1ioDpAMXVz8uv147uTK4dREFP+D6C6UODw+X33fWtuD7aZqW4ar2Yl24npxkQOH6SjUOqni9OJUMgUpr7TUA/nMAv7m4bwB+AsDvLIK8D8DPLa4fWNxj4f+WNtC7MyDJwmaDIBrD2fNZfF1jcCyBB5gymGzQucZyx7izOlAZYWsjknUiBwIZUMe3jTmcM7FGAdkBeK/dnLizIlrHGdtybRbgwf4KQAooWqdVHuwedcb/o5OM5uHy7LllabmxVsnomso/BvAPAbxscf8KAM9MRx9nB4DHANy9uL4bwKMLBfZba88uwv9HTrC19iCAB8XNXmdu0UF64ihrZlNmFdZbl8jiqI6VLj2ZEzbTp5JsO13jt3b0hUL+PGdrDVtbWysDMNth44Gmb6VXwHYDtOrUurjrwvKht0yyszG9PurAUONng3SEYWi/ze6duAkj8+ulf0NrKq21nwHw5DRNn+6FnSPTND08TdPrp2l6/SKfSocUUEYRN9LJZi8OE269iu3l6/JyDdmbeUYacmQmytiA5u86ffYWtwyEqnWNTG81KVT3Kj93apgHOJsfHFbNn8xEcXWXMZtMqnp2986vYg4jerk+3Mt3LssZYSpvBvCzrbW3AjgD4JsAPATgjtba1oKtvAbA44vwjwO4B8BjrbUtALcDeKqXyRwUde5V/CxMhu6u4lWfDNAqE2UUHKqFuGpGGgFHV5e9cuo2cFyHO7+jxJmOVfn4XSrh7liCe3aG3Z3Zy/4s2X0VrjqXMwoSXPbwy7aTewDM99qv3KQ3MqE6GZ2wWbpMZZqmX5um6TXTNN0L4BcAfGyapr8D4OMAfn4R7O0APry4/sjiHgv/j02DmvU6pFvz4F+cdRg1ETKTpsdEOD/VYaRcqq87u1Hp3CuPhqncMjqfzU4884UZpGXRn0o2YJS1KFBofYdwXg7oK516x/k5fAXkPZZSlZ1F+0jVtzL3jEm4Ppj9NM5IPw+5kXMqvwrgA621/xnAZwH81sL9twD889baIwC+hiMg6sroYGKWoPF6lLyXdtZw0UhuRs/ycmH4PIh+xIpn6VE2oeBX6ajlqxgRpz9Nq9+i4U4Vb+FXlsLXVfohGTNxunB9uLbRvDgPTV/TzCRbX3FlmSPKHBzr1fJVZXZx9drdqz7OfbSuAKCdhN7cbGmtTXSd0viK3mVhWbSzu/gjDEQHZ5Vuxoa2t7dXBiB3LF0ArcQBLKfrwru4boeHwY8BUdNi96i7YDCuLTUO569paVxlBNngcGsnLHOeCxoFFH4hd2Z2ZhMAAFy9ejXdRdK6dKYqSzXpOpljBrXWcPHiRRwcHNjOuXYnal1lA8ffP6riKj3cNX3NR9OppOef2fYOaJSOqn6VnhzH5TUyg2p9ZWzDDbwMtJWVsT4OfMPdnZ5lYHB9QR+p4HKzSTlN+edYWHovWFL9RkwZNhnZTdPQcG6yUXFAovUxByx67qOMZe1ABTjOKMINyAeQQ/WMYejAcWaDdoIeY3I6O9CI8BWljs490iGysrKfzvgZ6GQvJcoYoZZze3vbPvDHQMP1qnWTvdWNmaNSfwYC174RJhskCiT68KIDqax8qsvIIKz6bta+IxMNX2cTdU+vk/gBawQqrgKcZKYR3+t1lYbq4AAjS0vz1c7do5v6ZcA5M4wCX6Vf5ZbR6KwMCqARbnNzE1tbW8d2cjje1atXy3wVaBmM+J2ykX6YZtn7ZrP+4IDESa9eMyblwmq7ZpMYh+2xQU2/p4ebDNyE0QOeW4apjCBoRfNdg83Jt2JCnL8DtUz/jKVkujuGpOllrIQl88/c51DkjEHyeQ/HeJwebovYMbjW2sqBNa3X7AE9l2/1LhcuJx8EzPqmnt3JDue5PsT9le81L9Uta7Nq8GdpOLkZO1hrAyqjQJDN0BmqO7+MklYDgMM4t4jTC6+dhmf9kJh53baq6yDVzOaArRcm69js5/KMQav5ZYPF1SVw/G1rPTbFbMF966d3OlbLpKZOZcK4+s2YB+cV7gqwPUaR9bUeK3Y69/zmhGFZG1DJGEAVzs0knEZvIGUDcVSHrAE47YyRVHmE7hW15fJlHVbdXNosjjloGbJ6df58YK1ifFlduKeVq3MlWXswSPAOjQvbSzsr+8jAreqew1X9UsOPmDUZU650yOJW+oesDaiwjJo/PXMga5zKVOnpwGEdQLhZeeSBRmf29HTpsa3MTTuHY0tOh6qzAqsgENfxv7+/XwKuE16kZbcQ/tRG5OV2neK6Mo1ceTR+xdiyNnPurv+xbq5tMqlYsJajBwaatyvHSBprCSpOKnBwAzKr4MpU6eVXuWte2UBQHVz8g4OD4Q7g8hxhQ9y5K7DIOrgD+DkvRtI0svYIYMmArwI2XePI3tNSAXr4ZyxppJ0ib07fsUKuZwW0SrhuHMBp2plf1VfmyFqBSs/kcJ3dde6RdKtV+xHqmeXDAyA7YKXl0OuRWaWaYV06OiCrOJlbBSjsplu4zjTSAeMGrHu1gvOL+tZdImYuOuBGdn9YT10r4vJFeTc3N1dOH6t+WVtwXnMGcNXXR4BCx5CC08g4cLI2oNIrgA4UnT1HKmEU/XsNMhqmiqszlc5ivfTd4Kzou+rcM7EqhuJ0YzDlcx56QrQyJ+awQHeWRMvRWltZ9Gb9swcUXZ7MVFy/yR5I7KWZ6R16VpL14zn3ldlWXfdkbUAlYwwKGs4+7Jk64T5q+mjciBOdserEDHqZLZuZadksnoFAlo7Lx5XJSY/9VXUX3yiOcKwbD7zskQCViKMfe1cdIt8eqFZS1WN1ylYPyOlhQTV3tF6y60rHym/E7Mz65Wg6PVkbUBmZkbNZkoVnk95s6AZdRk1Vl0jP6aKsQ8Nw58r065krTrdRM6hKw+miaanwKxCcLhl4cH3PBfkQ94yP6hE/Nk2YrbCbm3jYjHXXnLfT1QFHVhcVg8n63cgEo2XMADgDmzmyNqAyIr1KCz83ANx1hdgazumR5RuiD771QMKdj8h04NO4GetRd9dpXRkqpsL3HNbV+eiWcgV41SBm/+ye86ye7VFd9FrTPskzQHqdgU0vXceGNe2euD7jJuNM90rWBlQqE0HdM6koWzWQMreMCmYzyai4svK1zlpZeN2G1DyyzjZi4rB7r1Np2swCbrR+3bYyS/Y0spolGifTqar3LI0MyLKnqbP6zBh2JSPmTpWX00nvGcRGZG1AhaWi6yMzbebn0uM8R+5HB2OlQ6aHMz9aa2nnHAHREdaWzVCjUplN4RYA49q2Mj2A+kSsAxz3IGA2WCJ9V5fspjowg6r00/wy5qb1mEnFmrN0M2GwyJj8SSbNtQKVrFOFG4dxcbWCKpCpgKsKy24906liJCNhshlixGbmsFWnrTq3A0zX+Q4PD1dOqupCrFu3UNDIQC976xrnXb2Zjd31WZ0wIXmHyOWjoMTXnKaaV659dddJ29iZJVoOxyJ6krFBl0Zv3PRkbUAl63DsX0mPUrrw2lHmsI5M/yp+NeBDqsU+N5tmnbACZtU565iVuaedkv10QTPCZadde+Dl9HJMRtPk10HqJBIPKLKJNvripqweIw1nlrrJwfX5rE0y1pD1udGJKNMpM8VGxsXagEqF0CxuNnbpcHh273VWDuMAQMHL6T2C5pqvdkzXGfm/qicXPqO32rGV7bn/GLDsHm+rcztAnGZVt+oO5E8tOwm9skHArITd1SSpFnSzsyqOvVQPCWq7hhnl6qyaUEaYcpamq6Meux6RtQEVlQo8nIlQzezqnqWjbpyOY1AV/XTuGdV0UnWWqhwj96qfqwenjwKQYyuqo243V+U4qTCQqB6Z+/b2Ng4ODrC/v78EEWZVrF9mnrnBHqATZc+O42s/cHXYm0C1XKMmk6sPDpOxfpenk7UFFWDewpUbZNUM6OihUmhNi91OMhgqoHCdimci1wl1oGdsSsvCumjYrL6qwVqBC6ef1SvP7iPC6WTvWHFAowww/vkzIQwiUR9ud0nTVfeI71iPe1eLA5qs7CcZ6BmIjzDeuTLnW8pfd4kON1q4iglUdmLEddTSzeaOVmb6ZPeZjiqhgx53dybOiA494fT5x2sP7tQoh8teVqT5AP41jRqmt8bBg7tKh8Pzj592DhDZ2NhY+fxISPixVPplZRthk+zuwJt/Ok6yvnQj0utrIWsFKlxpoxWgA6xnClXMxjEcDevcsrRdQzuQysrD6WcmjN73BrIDpCxfzjtjeo4VVXFcPgparnxZ22bhQ6rDcJubm0vgiG9DZ3XNfgw0DmQ4D07bhXUTIUs2Kbq6HEnnJDJnYgcGzZ/W2pcAXABwAGB/mqbXt9ZeDuCDAO4F8CUAb5um6el21CIPAXgrgEsA3jFN02dGlXf0vbIttVGyGaA3mOeKa0AFp1FTIv6rd4c46TW01tkcfeaEY7eqvk+Sjy78cpl4oPPzQWrK8MIph4t4rbUVhsXmT7bd7JiDtod7a5+bjDS9kB6IZnXm9OH7akw5v2yyzWQOU/lPp2n6gWnx7WMA7wbw0Wma7gfw0cU9APw0gPsXvwcB/MZoBlyY3sBkqezEDGWz2dpdZw2mHaGaJTKdKnbFonUSsyz/grLzrMhuqq+r56oOnM49vefWr0sjxIGs6/DKeviezS6O7/pZxrg4nYpZRr2HW+g4wm4076rtVCcnVX27MNlhvhG5kYXaBwD8+OL6fQA+gaOvFj4A4P3TkYafbK3d0Vq7a5qmv+kl2LPZMhbDUj3OrmBQNQKHceaT07dqLIf+PWCqOmxvpu8xt6z+XJqaltPbDc7eIHDpZwxI/d1ajAKLLswGI4n/kHgPSiyq6usSIj93sK3Xfr3DcKFr1a9cPTmpBj3Xg+al+vfGRk9GQWUC8H+1oy8J/pNpmh4GcCcBxVcB3Lm4vhvAoxT3sYXbCqi01h7EEZNht+MZJxQe8C8DqiqkN0BHGisbPNVMkJ1tGBEHAr1ZRDtfBSyubBVoTNP1N9NVrDKLH4PTvTIg27FR3bUPuH9XbhUGimAVBwcHxz7nys8ThWSnb10eEV7D8MnjCkwdqLv8HFi4JQVtZ86vN3ZG2MooqPzINE2Pt9a+BcAftdb+UjKcGn26dEQWwPTwQtFp4YbF/VAhKqod4ipq1DasQC4Du2wmcmXSATNCX3mm4TQdg2M/7UyurCcFY81X47Fbdphta+uoKzozTd+Vkp1LccwkSyeuOXysqwRzGe2HWhYnbAbp60JPMuG49uqxvBthH6PlBwZBZZqmxxf/T7bWfhfA3wbwRFuYNa21uwA8uQj+OIB7KPprFm6zxA0AR9NcPFd5WYfP8gKu01LtnFV+mocObM6HO6zOfKP2seablaViLSMsx5llrmxZOpyfvnwpA51eR1Z/XoittoHdVnEMdjaBeOE2+kI847S1tWVNY2fucN1Vb/N3UgF91dc5TFzfCKjMAdfuQm1r7Xxr7WVxDeA/A/DnAD4C4O2LYG8H8OHF9UcA/N12JG8C8Ow0sJ7ihAe06/jcueOXnZGYM9O4n+qVNab79eK5crHOmS5uFnIDvtItBszBwcFy4IQ7/zvdebBlabEbpwdgxc1tKbu2zLZ9q8XPbM1C65HT0QXu+HeL4tw28aVGXUCPX/hxmq48GUhn/i6cTgjadzhfd6/5VUyXZYSp3AngdxcJbgH436dp+oPW2p8C+FBr7V0AvgzgbYvwv4+j7eRHcLSl/M6BPFbEzeohFWtg0VmoMlsyBpTF4XjhrjsTWSfJzKYsLq/HuDSquqiYRJW/dsxgUQpeHF6fTI483enRKm+nA4uaT1z/7K5l5lOzuljrPp8azIXzyE7Hctn0iWy3oKyv3cxels1uvf6TMYms72bsuteveswdANqNUKKbJU3WY3oVNZhm2jEVKPTsQhZH72MW0g7Fuo8MaB6AFeBU9VKVtXLTa+1sGagqY8g6rq5/ZDNjpKlsQ00VjuPMJ9VP/fXJZRdfmRf/FFRdm0fZs8lR2d3+/j4uXbpkwVfbNetXLlw1BliXHityaV28eBEHBwe2Y6/lsz9ZRc4BF1eZXDGuQ2kj6cyn6XDHmyM9FsMzZtbBtCyOBVR14AAkm71YN9XXuffqNhMNowu0VedXP2YuXE+8GMtxe1vUHNYBiurEJl4WJoTDVI84zKlP157uBVE93TivEZAC1hRUgLFF2bniUD7rSDpoXYOyWcDpu7KMmiDZ+kVWlh6zKWlqQXWzWbNHlbO0gPr7Oi6PXhnVfFHJWFj1jFAPrFnc2RXVW7eUnS4RjtvdTSaVLjpZVAzV1WdlYjvwrvrVWj37w8IVPAoovcE4F5h0RubG5WtdzFQdsocBR3Ws2Aq7OR1GQYrTyUDUmSxVJ8vMCifuCXEWrmONx7qz8Hka/qkZE26aDg/4WJiNcqkflzkz41xYLns1Kel/1TfdfyZZvszGVY9eumvLVEIyqu6kR1+dWeVm4h49dOieDfYsvaohK1oNHH+nao+t8LVjgNpZlclN02TXNFwnd2Wq4ujahuZT7faMigM+PtCm5oxuRyvQjLz+gP1cP2FdYkdo5HO3rj0rAHETj8rIhKPhqgl67UElJKu8zPToUf/erOzyV12ysBmzcGkGsPXS1Hg66CtddFbj8jig7c1ICjqVfqNlcwDDfiy9beWRzp8tzmvaobc+WKjg7wCL64LLrwC0ubmJnZ0dXL58+ZgZo1L5uUlV/XqTpsbPwt6STKUHIi78iFsvjBswvYHXS9N1lGrwjDS800nz07xdGs6fga6qVzfrZrpl+Wdpu3vHBthvJE8O22tH9ywQA0r2+AW7O38HTDs7O9jb28P+/n4XhEf6iWOw0a7VYyPaj7K2vmWZypzZm8OHOPZSAVQ2OKoB4Sp+xGRTBuEG9YieGftQwKhob6Vrlk4PcLIzI9GpuXP2Bn+IPh/kRPXTunVrGhynAosIM2JCZGCdycbGxvIVl1rX2QTS00PLVYVhvdmPJxe+r2RtQSUreG/m5X9F9GqAuXguf/V3g9rFcQ+UufwrRtELx35OF51lNJxeZ6BRAYQr48jsxouY2bqKSyNYRA/kON0qjHNzoJutrQDebFCGFf6czs7ODq5du4b9/X0Ljj2p+mkFUi4NV588jipZW1AB8hl0ZMCwVMjs8nR5Z2lXAyVjIr00eqwicxsZWFq+EfCo7rNBz/4hbrF3a2vr2DqGC1cdZst0VHHpVmH5tKy+xEnPfDgzCVgFjxBlQxFvY2MDZ86cWR6Ey0xarQPHVHtl03DKSEbyzWStQWUOzYxKyd6n4qhuxQp6gKJmQZafi1sBYDYrjTCcLJ7T0XUo7lgZ+2D/7BfhYhZ2OzwRlk/MRmfPnkp2YKIPCkYejhk64ALyJ6d1kEU/49O1CjQMPgwMylT0ocXIR9mKsoO5E9sIi+b8nYwypZC1BpVKssrOKrhn8lR5uIE5hy05u1T9Qnrbkk7vOaDmZjUeoL0OrHpXADgKKBzHAQrrl62rqBuzEufG7vxKyQx4uO4CTBhkGGzix4uurH+UnfMI962tLezu7i5fvaB1mrEI1z8yIOm1W9XXRmTtQcXN8hU1HKFngF97cHn2DmVpwzm6qI1fAd+o/iMsxwFvr6NmabNuDESOofCg1CPxLv1eHTML1TTcOom2XwARA1L1AGQmWkY2dfiBRV1v2d/fX3l/SxzLV2YYuuzu7uLq1asrDDwD8YpdxL/rEy6trD+o3y29pgLke+0qGfjodS+dLA3HRlyjZzppnk6HrCNkgOnKV+nsdOvpwWXjQceDQUEFWD2NyiwkhN2d+dFjGiGODbEwc+CBwfdVu0W+ejDOHZRjsIjy8jtaIm1mLJxnAOfGxgZ2d3eXTCf8XR8b2R7mtKu0tPxZmN7Bw7UElYx5zGEjblBmfm5AuXgcPjvV6hC9YjO9/Jxezq3SRXWqZqsQd/Sc46u+mr8+0Kd58oN93OE5fbeWouYRh8vqicsTA7XqQ5mZxHqy+RPsg4//MzNivcKsceDE12fPnsW1a9ewt7d3rK5ZsvbQ8HMeeuV+wQvSyqgyWUtQqSpH3SoaV4kbcBmjUdGKzhgR6+uAZQTAMipa6al+2eJ1xXRcp9TO61iR00kZC4NGiHtxUYh7liZLrzf76jWnVz0e4do2wFHFPUcU8SMf9lMmE+GCrWR9U003147KdLLyZWHcOOnJWoKKSg8kRkAkk4r9OBbD6wkj+VcAUJlkFYPK8tZOxWk6iu/SD/fsPjtLkrEJXWh1YWMXJNtaVlBxoKOLrA7EOU+ur4g358zNNE32RUuhT7QDv+vWgbsukvMLm86cOWPPrXCZHNDH/cgjCy49ZaRzZW2fUnYSha2ooPPPOkZ2n7nzzNBD/cxtRL9wy+L2zEAFiwyclBHqz7nHLBt0373AKPyA1Vc5uq1Wds+eRNZwLA6wMral5c4YMcdVnTRdHoDV+ZqNjaNXSca5HMe+QiLu1tYWzp49e8xdy+IAwE0krk6y+4rZ3pLmj8ock2I0fo8xOHeXR2+AV/qO6K5hMnqb6Z9RYE4vm5U1XY6rgzgzV/g9rXHP+So7yLaUdW3CMRoGFC0LMxkd0HzILauTXh+M4/UMtpw+AyenW52XOTw8xJkzZ3DlyhXs7e2lZpC20UibjrS9m9iqNENuCVAB8pk7/Nx9Jtkgrio2M0cykOnp7zq/S3M0XFY+BzrOv1cfTI8dkLi03PkPrUterK2EFzGVsutgdCdG3ba1PqnMZdLyZRMKgwMPemZ1wHXQ2d/fX95z3q7vhn5nzpxZLthqGNZBTSKna49lZOOM268ntwyozKH8HCcbLBW94/SyNDKAcKwg028E/Nw13zv20yuzrk9kcar0GCiycvDZjbjWNHkwZgOf11tioGqezvxxuocebh2G09F6ykxWPa7PC7EchneDHHuM8jsT7+zZs7h69eqSrbAOGQDo9ehEW7HfYKg9WXtQyQrKUpkGWVy3aOYGqNNnxD3bIcriqu49GWEiGcBVJtSIvhXQapoKCApo7KaDTsEoA5KIG25aH8ry1BTJwlWA7dqMzcPsuH6Ezz78zuWKOFtbWytspRoPWgY1d7U8Gk/jOOn1z7UHlV4BNZxKj2XEvRtIjNAuPfV39FjTH9GH082AMiurgkfVATntHtXP9AP8KwkysHIH3fjUrfN3+nI8dnfg4swCXfOIumI2peZM5MEztobhA3BsBmk5nHvowvUZ+cbaSuwEVQzF1RW7VXXr6qtizE6GQKW1dgeA3wTwtwBMAP5rAF8A8EEA9wL4EoC3TdP0dDvS5CEcffvnEoB3TNP0mZF8RmXUbMiooIbTaw1TDUptNLddGfejLKQHkGo6ZOVx5c30Yp0rvZypwD9NU+9125gXbkfCs2SH1Fy5NF4PNLm93ESS3asJ48A2gEcXZSPPbPv8/PnzuHDhwgq70fMtkYeb8HoTksZlvzlMenRL+SEAfzBN03cD+H4AnwfwbgAfnabpfgAfXdwDwE8DuH/xexDAbwzmMSw8C7Bb/GsnB/pApKIdUmcevuYfv2zZ6ezyiOu5OiqLcyxF68p1iJ5eqmM2iFV4l2V0llSptpGdbGxsrJwf4fbiNLO6cX0rK5/68/ax+7oh/6JuHJC4tDc3N3H27NnllnQWzuXH+mf9bGSyG+2fI589vR3AfwLgtxaZX5um6RkADwB43yLY+wD83OL6AQDvn47kkwDuaEffWr7potQ0c1vofSx+1YmyDqkdUMWF76Vd6VHpy2mo/d7rOD0dnH+vPMDx2XdEKkB1A8iZSFmdO9Mu003D9dht3FcsTcP2mAKwuo3OzHdrawvnzp1bCe+YUDWZcL1o/iOAMwI+I+bPfQD+A4B/1lr7fgCfBvArAO6crn8j+as4+jwqANwN4FGK/9jCbeV7yq21B3HEZIbEUeQecLiOFZ0gG3gu37niOmTWqL2Om4Vzabs6yehqNthcOBfP/XiGrLaJswGhbg5Q2OTRttT0nAnDrID9XP+aY/Zw+q6N9QFG/dTpNK0++c3/vKgbL3HiLeasv1T3qquTrA/3ZARUtgC8DsDfm6bpU621h3Dd1InMpiafLu3JNE0PA3gYAEbiZgPDVWgl3GFHK6lK5yThM51HZkUOpzNfxVI4nqPF6u/CK1V3dB6owYLrvzp+79ZSdNBlg7ACgAx4KpDIdp8cYLmByPf8PhVmTRXDUR3PnTuHCxcupAya9e/po/G1vnRCrtIIGQGVxwA8Nk3Tpxb3v4MjUHmitXbXNE1/047MmycX/o8DuIfiv2bhdlMlA4RRoBhhKo4duIrV2UkHe2vN7gCwP7tV7OIkZaoG2wiouDUBBhcFFD49q2nrOoIDDscqnL4Rnv0yf03DTSoV2DjA0Dh8rwwo8uOF3Ko9eUcKuA48GxtHr5y8fPmyPRDn+s3IxOv6MpejZxWwdEFlmqavttYeba191zRNXwDwFgCfW/zeDuA9i/8PL6J8BMAvt9Y+AOCNAJ4lM+kFETeQ2W9RjpX7kIwmapiRinUzRwYQqks28DNdK1bSYyEVY6n8w6RhsNB3pOg169B70JDDZ25ZGRmksvrgcC4NrU/NL2tTXoxWEIhrTqe1duxEbcQPUfbCh/XimSB+xsqVNVsuqPq4HubT8DdrTQUA/h6A326t7QD4awDvxNEi74daa+8C8GUAb1uE/X0cbSc/gqMt5XcO5mElq6TwU1DQytMZw4XP8svc3KzVYxGqW+ins2sFVJmuboZmfx3smi/PysrAIo6rr8yUyLaNWRfnp7pmYOLWylzZXX1lcdz6jdvudhKmDPc7ZkJ6ypafXGZ/J5wun2E5d+7cyrmVCMv/XO4eM+f2UGDROqjqHQDajawr3Cxpg+sx1eAbjXczpddIPCtm1NkN5pG8Ru8dcGT37A4cN3t6YNEzhzTNEX/OpwITjcf1qvWjbRNumn4FtFnagN8h5N05fqrbAYFOjPp+loh/4cIFPPvss8cO3KkOTtcKiHgydpNcaw1PP/009vb2bIdd+xO1LCNAklVE+Kn7yEyUDXZlQlna2kFVtNNkzKjSL9Mj/KtZmsNk91wmoP9KQadPBiCcHv/rm9MckLC+TgctY/w7EygDZlfW0UlN244ZS/hlZjOvozB7iHq77bbb8Pzzzx/7BnOlWwUmDnyq8ZTJLQUqI1KtZVSdrMcUMqkGqqaZ2bJOJ3c/xy9zUz8Xxg1kZioufV0f0fDV9jCHY9s+O03r9IjBxveOiamOvbrRfpTFYRPGmRBhDsV7a6OsnOaISc1pbm1t4fz587h27doKCDmwUoYyWi6WUeB6SYFKRlWB+jxI1cF6eWXpu5l/JM3RsFmeWZpVPrpmotcVsCjzUMbB6XN+DmQUgBy7crtBupahabBkgJSVmcNoOsDqMfkAjDmH/jJ2GuUJP86Pw54/fx4XL17E3t7eEFA4cOH7TAdNr+qjLylQUZNDzRtXcT3gqfLK0gl/7uQnSaOi5s49W7fh/5EyahyXvwOYkOr8iUrvkFwPKN0Coiuj08eF7Q30EH2+h3dzVDeuR34NQtUvOV6sq2Rs7+zZsyvby5p/6Ov6SjYmov9mY+gbhqkA3mbsIXi1HjEnzyxtp08vHU4vfm727QEld6bszEZINvCU0VQgoPmHjo6lZIPEdX41kTJTJwOL7Oll1pcHkebf6xujOziat95XE6GuvUU9nDt3DhcvXrTAFlIxocrtJGPilgMVnUlG6GNv5jkpmJw07pxFvgivZogLV/07mp+ZiqODiMPx2/BD+LkVjqMgwMKvQeC4umir5ee0FBiyBd2sHjOzmNPla2URWb2qvirVGgiHcabY1tbWsbUaJ1z/Lj9mKRp+VG45UMkWi0YG6kkXY0f0qQCuWs9R0U4cM7vrDFnHy/LNgEQHoM76DkAingKHxuF0WY/MLHQmVbZTkwGh5puZDloXzkTgcBkQRFx158GpgBT/PXbD/pymukcZesw4M2MqM6fHslRuOVCppDfIQkaQ3KU7mmY2o7G/62Quz+ztZBmI6cDT6+rsiTOPVDRMBtQMYL3tZ013ZG0oy0tl9PGIasLh2dv1D5e+C8NPlGcMRAEn7nk3SQEle92Gpj13fJx0An9JgYp2mFGbsQcCWV7a0XsVr7SSdXDxQ7c4gVnNzI7haNpZfK2HDISCNbktZ3aLOJm54oTXPLSO3HmVim31xDGdqKNKlBG4V0Fm6VWTC19Xb4njBd5Ij9/in5XB9ctR4JhrDQC3GKhkdiBQL5aOxmO3Xid1A7k30/XSzGb0LJ42POvEn9eMfzZVlK3MOT3rys96unAV++CyB6hkW9VZPiOir5905RgxJd3EkMVVBuHMisqk4bgV69IDcizMtKoyuYmyqodMbhlQcZVVdYCR+2pgVHpEGiONwPnNMbt6M3E287GfMqO9vb3l4OTv8Wxubq585ErT1QGu4g68uWPzWRq8MOvKymXLGGhV/wxYBwcHS2AZNWt67Ve1Q/XfEzZ94t656a6PA7IMDObuWPXMP+AWApXRhhgRN+Nwhc2hxVmDceU78ybLYzTv1q4vDlYzreYZs1kwmXAPINja2lqCDF8zU+kBb8y6ChaqP7D6gKNLW80tjq+MJhM3w3P9hVtWFo3nrjV8lmf4Rb9hhsImVVwrELmFW04zRPufMqOsnA5M1L8ntwyojCDkSNwehXWdpgcYPbNH0+b8NbwCRaZv1tl19nVujtFE3go2MagDWLa3t5eAE26qLzMVwJ9/Aa6bVBkzUjNNy1vF1cNpLn+tAyducIboC6xHZn0GEwcovHbC8R2YVKCmYV1/dn0zSysbL05uGVA5CaDozJb5ZfdZZ8sq3lV41oAVEGleanJV4Vxny6ivxnPCL/Rm3VtrS/Npa2sL29vby9/W1hZ2dnawvb1tzbhsodc971PVqQMUTS/KoFvLCixZO2vdOOCoGE9mRjATUYDRRVcHKOzmdn9cf1O2kenGouV/STGVEXGDaSRcJq6CR8PPZSmaj+sEmpeCRQYQPQDrAZeCc/yiY1+9evWYX5hNOzs72NnZwe7u7grLCYYTQBADiXeBnN6VblW9BgMbfS4nhFlIBg4RxpkYzvTIQEIHuQMrBhxOu/pCgNZNBaAaZ47ZE/KSApWq4I7268xepTtC+1xeo+E1n5H43Jk1HdXFAQ0zAq4TTkvTd+zH5XtwcIC9vT1cvnx5Jb9YIA52E6ATzGZ7e9tuK7tyc7o8uFlvbmOns4bTOuIXKmUDU4/Ps7s7vq8mD7tVW8p8z/EVTEZBwZUpC1fdq6w1qPQGZ9bxWbKO5NIYyYf10v9eupVu7N8DFgdCmk4GhAoMjia79OYyA2D1lYg807q0Yxdqc3NzCTDBbnZ3d1cWi/V8SFzHJ1Ijb8A/k8MnlCNs9tR0xhy4/K5OOG0HNhEmCzdSt+46A4ZMtK85AJ07Sa41qFQzsLsfdRtlKD29erMAN0Y2GLTxsvRc/hlzqOKP6KySmT8MNFldRgfNAJUHVawNKLvhbe9gOAE0YVLpwbwQBjHVgwePbss6fUPPUVGQiPI6ZsPu6qdp6q5QZvpwOm4sZX0hm3TYv+pjaw0qIXNQcjS9jF1UjEfDVulrPlkDjppe1aw4et/LbyQfBS8HLAoy7l7L5sLzgI/3hXB8Nal4sXhnZ2cJQnrwr3qad+5Epiyn2gHivpAddJuzzc0mkwMbDl8BhQur4+MlwVR6JkZlcvRAw5kZlYlUuWs6qpum7RrU2feadg98RkzBLN5I+dkv62A6oBwIsB//MuBydRf+fOYGAC5durQMy09N86Ix706FX4RjccxC3V25M3YS9z0w4fgj4BdxXbp85iXr9yoa/iQT+tqCSlYYZ/NlcRSQ3ECPcFlelS5Z3gp+7t/lHXqNsChlDFV99Mo3agZWs7h2XPZXEND84zqrK1dnFRAD17dZs7gBJLElzqYV71BFfD7er4CigNQzkbi9srUR3Q3ifLIzLI4RV2yjMmNGx5iTLqi01r4LwAfJ6dsB/PcA3r9wvxfAlwC8bZqmp9tRKzyEo890XALwjmmaPtPVJJGskjIUrUAnS3skDUfTq3Sq2TdLZwToOD9XF47RVfk4yeowY1qZfi6e6+QVC2UQqPTVezWRMiDO4vLjBnrgjw8DMjhpnWW7P66O3FF7deuZN67NMlDphRtp50xmfaKjtbaJo68NvhHALwH42jRN72mtvRvAN0/T9Kuttbfi6DtBb12Ee2iapjd20u0qcVIq1ktTpZrdKzCodDvJwB4Jlw1Wp+tIflp2BZcKFEdAMGNgel2Bvctr9N6BUy8vly+DDm+R6yMOEZ7P3GidVmso7tMbLHxO6OrVq3YHaRRkNF03KbJcunQJBwcHttHnmj9vAfDFaZq+3Fp7AMCPL9zfB+ATAH4VwAMA3j8dafHJ1todbfF51Jl5rchM8DsW70YGcS+NjKlU93MGZo8haaefptWPWVV1x2lnDK1XNk7npIBQ5ZmZVdl9xiq1nJVOymriP9z39/ePxVXwCgbDQBMsh3erOD8GG9d+GevJwGSUXVd9Ze5kPhdUfgHAv1hc30lA8VUAdy6u7wbwKMV5bOF2Q6Ayh6mctGJ6la8NPzo7ZzpoGPeAoObt9K1MiwjXAxYVN9h7YOP85nTuk+hYtbUDo4rdZaZQBVpz+lWAPZtk/KQ4//REsbJE/o+FWi0X/+t6VsZsW2vH3tmi4XtlHgaVdvTJ058F8GvqN03TNGLCSHoPAnhwNPwLYfqMzHgVDXSV3qPXbnCNDtYMKLK6GaH2lbszFyJdVy430LSOKkDusckKRJ2OmXsGcJUuynI4jwy4dLLI9NJ2VabDoBPXfCbH6cOLt71+zPWifgrQI+NwDlP5aQCfmabpicX9E2HWtNbuAvDkwv1xAPdQvNcs3LQQDwN4GABaaxcAfGGGLjcsI5VzkjAjA5yuXwngP3YzeenJablvffm2zGMOqPwirps+APARAG8H8J7F/4fJ/Zdbax/A0ULts1N/PeUL0zS9foYuLwlprf3Zabm/ceQbpdxDoNJaOw/gJwH8N+T8HgAfaq29C8CXAbxt4f77ONr5eQRHW8rvvGnansqpnMrayxCoTNP0PIBXiNtTONoN0rATjrabT+VUTuUbUPrv4vv6yMMvtgIvkpyW+xtLviHKPevw26mcyqmcSk/WhamcyqmcyktEXnRQaa39VGvtC621R9rRcf+XhLTW7mmtfby19rnW2l+01n5l4f7y1toftdb+avH/zQv31lr7Xxb18G9ba697cUtwY9Ja22ytfba19nuL+/taa59alO+Di3NPaK3tLu4fWfjf+6IqfgPSjk6P/05r7S9ba59vrf3QN0p7s7yooNKOniX6X3F0Bua1AH6xtfbaF1Onmyj7AP7BNE2vBfAmAL+0KNu7AXx0mqb7AXx0cQ8c1cH9i9+DAH7j66/yTZVfAfB5uv91AO+dpuk7ADwN4F0L93cBeHrh/t5FuFtVHgLwB9M0fTeA78dR+b9R2vu6xEm6F+MH4IcA/CHd/xqAX3sxdXoBy/phHG3LfwHAXQu3u3B0RgcA/gmAX6Twy3C32g9HBx4/CuAnAPwegIajQ19b2u4A/hDADy2utxbh2otdhhOU+XYA/5/q/o3Q3vp7sc2f7Dmhl5QsKP0PAvgU5j8zdSvKPwbwDwHE+fRXAHhmmqb9xT2XbVnuhf+zkOMLt4jcB+A/APhnC7PvNxfnu74R2ntFXmxQeclLa+02AP8SwN+fpuk59puOpqiX1PZba+1nADw5TdOnX2xdvs6yBeB1AH5jmqYfBPA8rps6AF6a7e3kxQaVoeeEblVprW3jCFB+e5qmf7VwfmLxrBRO8szULSBvBvCzrbUvAfgAjkyghwDc0VqLw5ZctmW5F/63A3jq66nwTZLHADw2TdOnFve/gyOQeam39zF5sUHlTwHcv9gZ2MHRqxU+8iLrdFOkHT2i+lsAPj9N0z8ir3hmCjj+zNTfXewKvAljz0ytnUzT9GvTNL1mmqZ7cdSeH5um6e8A+DiAn18E03JHffz8IvwtN5tP0/RVAI+2ozclAkenzT+Hl3h7W3mxF3Vw9JzQvwfwRQD/3Yutz00s14/giOr+WwD/ZvF7K47WCz4K4K8A/N8AXr4I33C0E/ZFAP8OwOtf7DLchDr4cQC/t7j+dgD/GkfPhP0fAHYX7mcW948s/L/9xdb7Bsr7AwD+bNHm/yeAb/5Gau/4nZ6oPZVTOZWbKi+2+XMqp3IqLzE5BZVTOZVTualyCiqnciqnclPlFFRO5VRO5abKKaicyqmcyk2VU1A5lVM5lZsqp6ByKqdyKjdVTkHlVE7lVG6q/P9XriMsYNMiKAAAAABJRU5ErkJggg==", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.imshow(frame_im, cmap=\"gray\")" - ] - }, - { - "cell_type": "markdown", - "id": "c49fbcc4", - "metadata": {}, - "source": [ - "If we use the `get` function to fetch *IPX* (of alias `rba`) format, it may not throw any error or exception, however, the data would be empty. For example," - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "79419ec3", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭──────── <class 'pyuda._signal.Signal'> ─────────╮\n",
-       " ╭─────────────────────────────────────────────╮ \n",
-       "  <Signal>                                     \n",
-       " ╰─────────────────────────────────────────────╯ \n",
-       "                                                 \n",
-       "        data = None                              \n",
-       " description = ''                                \n",
-       "        dims = []                                \n",
-       "      errors = None                              \n",
-       "       label = ''                                \n",
-       "        meta = {                                 \n",
-       "                   'signal_name': b'rba',        \n",
-       "                   'signal_alias': b'rba',       \n",
-       "                   'path': b'/rba027933.ipx',    \n",
-       "                   'filename': b'rba027933.ipx', \n",
-       "                   'format': b'IPX',             \n",
-       "                   'exp_number': 27933,          \n",
-       "                   'pass': -1,                   \n",
-       "                   'pass_date': b'2011-12-15'    \n",
-       "               }                                 \n",
-       "        rank = 0                                 \n",
-       "       shape = ()                                \n",
-       "        time = None                              \n",
-       "  time_index = None                              \n",
-       "       units = ''                                \n",
-       "╰─────────────────────────────────────────────────╯\n",
-       "
\n" - ], - "text/plain": [ - "\u001b[34m╭─\u001b[0m\u001b[34m─────── \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'pyuda._signal.Signal'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m ────────\u001b[0m\u001b[34m─╮\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m╭─────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mSignal\u001b[0m\u001b[1m>\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m╰─────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mdata\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mdescription\u001b[0m = \u001b[32m''\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mdims\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33merrors\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mlabel\u001b[0m = \u001b[32m''\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mmeta\u001b[0m = \u001b[1m{\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'signal_name'\u001b[0m: \u001b[32mb'rba'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'signal_alias'\u001b[0m: \u001b[32mb'rba'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'path'\u001b[0m: \u001b[32mb'/rba027933.ipx'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'filename'\u001b[0m: \u001b[32mb'rba027933.ipx'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'format'\u001b[0m: \u001b[32mb'IPX'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'exp_number'\u001b[0m: \u001b[1;36m27933\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'pass'\u001b[0m: \u001b[1;36m-1\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'pass_date'\u001b[0m: \u001b[32mb'2011-12-15'\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m}\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mrank\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mshape\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtime\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtime_index\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33munits\u001b[0m = \u001b[32m''\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m╰─────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "data = client.get(\"rba\", shot_1)\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "00aa4ce6", - "metadata": {}, - "source": [ - "### Erros & Exceptions" - ] - }, - { - "cell_type": "markdown", - "id": "2ea83100", - "metadata": {}, - "source": [ - "In some cases, meta data can be fetched if using `get`, but without any data." - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "id": "b9e2506d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭──────── <class 'pyuda._signal.Signal'> ─────────╮\n",
-       " ╭─────────────────────────────────────────────╮ \n",
-       "  <Signal>                                     \n",
-       " ╰─────────────────────────────────────────────╯ \n",
-       "                                                 \n",
-       "        data = None                              \n",
-       " description = ''                                \n",
-       "        dims = []                                \n",
-       "      errors = None                              \n",
-       "       label = ''                                \n",
-       "        meta = {                                 \n",
-       "                   'signal_name': b'rzz',        \n",
-       "                   'signal_alias': b'rzz',       \n",
-       "                   'path': b'/rzz027933.tif',    \n",
-       "                   'filename': b'rzz027933.tif', \n",
-       "                   'format': b'TIF',             \n",
-       "                   'exp_number': 27933,          \n",
-       "                   'pass': -1,                   \n",
-       "                   'pass_date': b'2011-12-15'    \n",
-       "               }                                 \n",
-       "        rank = 0                                 \n",
-       "       shape = ()                                \n",
-       "        time = None                              \n",
-       "  time_index = None                              \n",
-       "       units = ''                                \n",
-       "╰─────────────────────────────────────────────────╯\n",
-       "
\n" - ], - "text/plain": [ - "\u001b[34m╭─\u001b[0m\u001b[34m─────── \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'pyuda._signal.Signal'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m ────────\u001b[0m\u001b[34m─╮\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m╭─────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m<\u001b[0m\u001b[1;95mSignal\u001b[0m\u001b[1m>\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m╰─────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mdata\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mdescription\u001b[0m = \u001b[32m''\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mdims\u001b[0m = \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33merrors\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mlabel\u001b[0m = \u001b[32m''\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mmeta\u001b[0m = \u001b[1m{\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'signal_name'\u001b[0m: \u001b[32mb'rzz'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'signal_alias'\u001b[0m: \u001b[32mb'rzz'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'path'\u001b[0m: \u001b[32mb'/rzz027933.tif'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'filename'\u001b[0m: \u001b[32mb'rzz027933.tif'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'format'\u001b[0m: \u001b[32mb'TIF'\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'exp_number'\u001b[0m: \u001b[1;36m27933\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'pass'\u001b[0m: \u001b[1;36m-1\u001b[0m, \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[32m'pass_date'\u001b[0m: \u001b[32mb'2011-12-15'\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[1m}\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mrank\u001b[0m = \u001b[1;36m0\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mshape\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtime\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33mtime_index\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m│\u001b[0m \u001b[3;33munits\u001b[0m = \u001b[32m''\u001b[0m \u001b[34m│\u001b[0m\n", - "\u001b[34m╰─────────────────────────────────────────────────╯\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# it is a TIF image, but only meta data is accessible.\n", - "data = client.get(\"rzz\", shot_1)\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "id": "58e687d9", - "metadata": {}, - "outputs": [ - { - "ename": "ServerException", - "evalue": "Can't open file /net/mustrgsrvr1/export/mastu/data/MAST_Data/27933/LATEST/rzz027933.ipx", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mServerException\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m/tmp/ipykernel_25138/3110243593.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# error output with get_images\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_images\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'rzz'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshot_1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0minspect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdocs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/depot/uda-mast-1.3.6/python/mast/mast_client.py\u001b[0m in \u001b[0;36mget_images\u001b[0;34m(self, signal, source, first_frame, last_frame, stride, frame_number, header_only, rcc_calib_path)\u001b[0m\n\u001b[1;32m 94\u001b[0m \u001b[0mcomm\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m')'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 96\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcpyuda\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomm\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 97\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror_code\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 98\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror_message\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32mpyuda/cpyuda/cpyuda.pyx\u001b[0m in \u001b[0;36mcpyuda.get_data\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mServerException\u001b[0m: Can't open file /net/mustrgsrvr1/export/mastu/data/MAST_Data/27933/LATEST/rzz027933.ipx" - ] - } - ], - "source": [ - "# error output with get_images\n", - "data = client.get_images(\"rzz\", shot_1)\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "35cb5ea8", - "metadata": {}, - "source": [ - "For the other shot, which has *JPG* format image." - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "id": "2611bfb9", - "metadata": {}, - "outputs": [ - { - "ename": "ServerException", - "evalue": "Can't open file /net/mustrgsrvr1/export/mastu/data/MAST_Data/12000/LATEST/mhd012000.ipx", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mServerException\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m/tmp/ipykernel_25138/2073778830.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# error output with get_images\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_images\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'mhd'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshot_2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0minspect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdocs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/depot/uda-mast-1.3.6/python/mast/mast_client.py\u001b[0m in \u001b[0;36mget_images\u001b[0;34m(self, signal, source, first_frame, last_frame, stride, frame_number, header_only, rcc_calib_path)\u001b[0m\n\u001b[1;32m 94\u001b[0m \u001b[0mcomm\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m')'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 95\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 96\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcpyuda\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomm\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 97\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror_code\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 98\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror_message\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32mpyuda/cpyuda/cpyuda.pyx\u001b[0m in \u001b[0;36mcpyuda.get_data\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mServerException\u001b[0m: Can't open file /net/mustrgsrvr1/export/mastu/data/MAST_Data/12000/LATEST/mhd012000.ipx" - ] - } - ], - "source": [ - "# error output with get_images\n", - "data = client.get_images(\"mhd\", shot_2)\n", - "inspect(data, docs=False)" - ] - }, - { - "cell_type": "markdown", - "id": "8769061c", - "metadata": {}, - "source": [ - "In this situation use `get` to fetch metadata information and path." - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "c3ea9047", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
╭────────────────────────── <class 'pyuda._signal.Signal'> ───────────────────────────╮\n",
-       " ╭─────────────────────────────────────────────────────────────────────────────────╮ \n",
-       "  <Signal>                                                                         \n",
-       " ╰─────────────────────────────────────────────────────────────────────────────────╯ \n",
-       "                                                                                     \n",
-       "        data = None                                                                  \n",
-       " description = ''                                                                    \n",
-       "        dims = []                                                                    \n",
-       "      errors = None                                                                  \n",
-       "       label = ''                                                                    \n",
-       "        meta = {                                                                     \n",
-       "                   'signal_name': b'mhd',                                            \n",
-       "                   'signal_alias': b'mhd',                                           \n",
-       "                   'path': b'/net/fuslsa/data/MAST_Data/12000/Pass0/mhd0120.00_jpg', \n",
-       "                   'filename': b'mhd0120.00_jpg',                                    \n",
-       "                   'format': b'JPG',                                                 \n",
-       "                   'exp_number': 12000,                                              \n",
-       "                   'pass': 0,                                                        \n",
-       "                   'pass_date': b'1980-02-10'                                        \n",
-       "               }                                                                     \n",
-       "        rank = 0                                                                     \n",
-       "       shape = ()                                                                    \n",
-       "        time = None                                                                  \n",
-       "  time_index = None                                                                  \n",
-       "       units = ''                                                                    \n",
-       "╰─────────────────────────────────────────────────────────────────────────────────────╯\n",
-       "
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\n", - "Note: There is a mismatch with the data on the website, especially in the values of CPF Data Summary table: https://users.mastu.ukaea.uk/internal/shot/27933 . Current information: cpf values available via pycpf are the correct ones. Information about data contained can be found in the https://users.mastu.ukaea.uk/sites/default/files/uploads/CPF.pdf\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "id": "68bb0dc2", - "metadata": { - "code_folding": [] - }, - "outputs": [], - "source": [ - "def retrieve_cpf(shot):\n", - " cpf = {}\n", - " for field in pycpf.columns():\n", - " name = field[0]\n", - " entry = pycpf.query(name, f\"shot = {shot}\")\n", - " if entry:\n", - " cpf[name] = {\n", - " \"data\": entry[name][0],\n", - " \"description\": field[1],\n", - " }\n", - " else:\n", - " cpf[name] = {\n", - " \"data\": None,\n", - " \"description\": field[1],\n", - " }\n", - " return cpf" - ] - }, - { - "cell_type": "markdown", - "id": "e27e5534", - "metadata": {}, - "source": [ - "CPF files can be presented as a table, where it has a name of a row (Name-first column in the table below), data and description of the data available for each of the rows. " - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "id": "a0d3fccc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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datadescription
P12450NoneCP3c Set Volts
P15202NoneAdditive Gas Plenum
q95_truby0.0q-95 at time of Ruby TS
area_max1.610378Maximum Poloidal Cross-Sectional Area
tipmax0.2679Time of Maximum Plasma Current
creation'2011-12-15'Data Dictionary Entry Creation Date
P21083NoneFA1 enable Duration
P21087NoneFA3 enable Duration
wmhd_truby0.0Stored Energy at time of Ruby TS
P21078NoneP1PS Positive I Limit (Max. +ve Current from P...
P21052NoneMFPS set enable Start Time (Offset by 5s)
P05016NoneSelect FA3
li_3_max1.074974li(3) Maximum value
tzeff_maxNoneTime of Maximum Plasma Z-Effective
P21084NoneFA2 enable Start Time (Offset by 5s) (Normally...
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" - ], - "text/plain": [ - " data description\n", - "P12450 None CP3c Set Volts\n", - "P15202 None Additive Gas Plenum\n", - "q95_truby 0.0 q-95 at time of Ruby TS\n", - "area_max 1.610378 Maximum Poloidal Cross-Sectional Area\n", - "tipmax 0.2679 Time of Maximum Plasma Current\n", - "creation '2011-12-15' Data Dictionary Entry Creation Date\n", - "P21083 None FA1 enable Duration\n", - "P21087 None FA3 enable Duration\n", - "wmhd_truby 0.0 Stored Energy at time of Ruby TS\n", - "P21078 None P1PS Positive I Limit (Max. +ve Current from P...\n", - "P21052 None MFPS set enable Start Time (Offset by 5s)\n", - "P05016 None Select FA3\n", - "li_3_max 1.074974 li(3) Maximum value\n", - "tzeff_max None Time of Maximum Plasma Z-Effective\n", - "P21084 None FA2 enable Start Time (Offset by 5s) (Normally..." - ] - }, - "execution_count": 76, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df = pd.DataFrame(retrieve_cpf(shot_1)).transpose()\n", - "df.head(15)" - ] - }, - { - "cell_type": "markdown", - "id": "9d57618e", - "metadata": {}, - "source": [ - "In this table there are 265 rows, some of them have data value equal to None, such rows typically have Names starting with P and followed by 5 numbers. Other Names are typically having physics nomenclature. CPF file contains the most important experiment values, both experimental conditions as well as results of the analysis. It has information in string format (descriptions,scientist names, summary, postshot, time and date), float and int." - ] - } - ], - "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": "3.7.1" - }, - "toc": { - "base_numbering": 1, - "nav_menu": {}, - "number_sections": true, - "sideBar": true, - "skip_h1_title": false, - "title_cell": "Table of Contents", - "title_sidebar": "Contents", - "toc_cell": true, - "toc_position": { - "height": "calc(100% - 180px)", - "left": "10px", - "top": "150px", - "width": "254px" - }, - "toc_section_display": true, - "toc_window_display": true - }, - "toc-autonumbering": true, - "toc-showcode": false, - "toc-showmarkdowntxt": false, - 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"The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2\n", - "from skimage import filters\n", - "from IPython.display import Image, display\n", - "import imageio\n", - "import matplotlib.pyplot as plt\n", - "import xarray as xr\n", - "import zarr\n", - "import os\n", - "import pandas as pd\n", - "import numpy as np\n", - "from src.archive.transforms import PipelineRegistry\n", - "\n", - "def load_source(path):# -> dict[Any, Dataset]:\n", - " store = zarr.open(path)\n", - " keys = list(store.keys())\n", - " dt = {key: xr.open_zarr(path + '/'+ key) for key in keys}\n", - " return dt\n", - " \n", - "\n", - "def make_channel_df(dataset):\n", - " items = []\n", - " for key, ds in dataset.data_vars.items():\n", - " item = dict(name=ds.attrs['uda_name'], description=ds.attrs['description'])\n", - " items.append(item)\n", - "\n", - " df = pd.DataFrame(items)\n", - " return df\n", - "\n", - "def make_gif(dataset, file_name: str):\n", - " frames = dataset.data.values\n", - " duration = (dataset.time.values.max() - dataset.time.values.min()) / len(frames)\n", - " imageio.mimsave(file_name, frames, duration=duration, loop=0)\n", - "\n", - "def plot_gif(file_name: str):\n", - " with open(file_name, 'rb') as file:\n", - " display(Image(data=file.read(), format='png'))\n", - "\n", - "def print_datasets(dt):\n", - " for key, ds in dt.items():\n", - " print(ds.sizes, key, ds.attrs['description'])\n", - "\n", - "pipelines = PipelineRegistry()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ABM - Needs Review" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "

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-       "  * time            (time) float32 30kB -0.1 -0.0996 -0.0992 ... 2.899 2.899 2.9\n",
-       "Data variables: (12/21)\n",
-       "    calib_shot      int16 2B ...\n",
-       "    channel_status  (dim_0) float32 128B dask.array<chunksize=(32,), meta=np.ndarray>\n",
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-       "    gain            (dim_0) float32 128B dask.array<chunksize=(32,), meta=np.ndarray>\n",
-       "    i-bol           (time, dim_0) float32 960kB dask.array<chunksize=(7500, 32), meta=np.ndarray>\n",
-       "    km              (dim_0) float32 128B dask.array<chunksize=(32,), meta=np.ndarray>\n",
-       "    ...              ...\n",
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-       "    tco_emis        (time, chord) float32 330kB dask.array<chunksize=(7500, 11), meta=np.ndarray>\n",
-       "    v-bol           (time, dim_0) float32 960kB dask.array<chunksize=(7500, 32), meta=np.ndarray>\n",
-       "    version         float32 4B ...\n",
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-       "    z-slits         (dim_0) float32 128B dask.array<chunksize=(32,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  multi-chord bolometers\n",
-       "    file_name:    abm0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         abm\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       abm\n",
-       "    uda_name:     ABM\n",
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-       "    description:  Linear D-Alpha Camera\n",
-       "    file_name:    ada0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         ada\n",
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-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       ada\n",
-       "    uda_name:     ADA\n",
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-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
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-       "    tc5b            (time) float32 531kB dask.array<chunksize=(132812,), meta=np.ndarray>\n",
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-       "    description:  molecular deuterium pressure, neutral gas pressure, Gas Inj...\n",
-       "    file_name:    aga0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         aga\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       aga\n",
-       "    uda_name:     AGA\n",
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-       "  * time        (time) float32 60kB -0.1 -0.0999 -0.0998 -0.0997 ... 1.4 1.4 1.4\n",
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-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         ahx\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       ahx\n",
-       "    uda_name:     AHX\n",
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-       "    version:      0
" - ], - "text/plain": [ - " Size: 240kB\n", - "Dimensions: (time: 15000)\n", - "Coordinates:\n", - " * time (time) float32 60kB -0.1 -0.0999 -0.0998 -0.0997 ... 1.4 1.4 1.4\n", - "Data variables:\n", - " hxr_mezzw (time) float32 60kB dask.array\n", - " hxr_s (time) float32 60kB dask.array\n", - " hxr_w (time) float32 60kB dask.array\n", - " passnumber float32 4B ...\n", - " status float32 4B ...\n", - " version float32 4B ...\n", - "Attributes:\n", - " description: Hard X-rays\n", - " file_name: ahx0304.20\n", - " format: IDA3\n", - " mds_name: None\n", - " name: ahx\n", - " quality: Not Checked\n", - " shot_id: 30420\n", - " signal_type: Analysed\n", - " source: ahx\n", - " uda_name: AHX\n", - " uuid: 36843196-5cf2-5b70-a053-51cb1fc838ec\n", - " version: 0" - ] - }, - "execution_count": 78, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'ahx'\n", - "path = f'/common/tmp/sjackson/local_cache2/30420.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AIM" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 1MB\n",
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-       "Data variables:\n",
-       "    da_hm10_t        (time) float32 200kB dask.array<chunksize=(50000,), meta=np.ndarray>\n",
-       "    da_hm10_t_error  (time) float32 200kB dask.array<chunksize=(50000,), meta=np.ndarray>\n",
-       "    da_to10          (time) float32 200kB dask.array<chunksize=(50000,), meta=np.ndarray>\n",
-       "    da_to10_error    (time) float32 200kB dask.array<chunksize=(50000,), meta=np.ndarray>\n",
-       "    passnumber       int32 4B dask.array<chunksize=(), meta=np.ndarray>\n",
-       "    status           int32 4B dask.array<chunksize=(), meta=np.ndarray>
" - ], - "text/plain": [ - " Size: 1MB\n", - "Dimensions: (time: 50000)\n", - "Coordinates:\n", - " * time (time) float32 200kB -0.01 -0.00998 -0.00996 ... 0.99 0.99\n", - "Data variables:\n", - " da_hm10_t (time) float32 200kB dask.array\n", - " da_hm10_t_error (time) float32 200kB dask.array\n", - " da_to10 (time) float32 200kB dask.array\n", - " da_to10_error (time) float32 200kB dask.array\n", - " passnumber int32 4B dask.array\n", - " status int32 4B dask.array" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'aim'\n", - "path = f'/common/tmp/sjackson/local_cache2/30420.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AIR" - ] - }, - { - "cell_type": "code", - "execution_count": 81, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/4011811044.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 11MB\n",
-       "Dimensions:              (dim_0: 299, time: 3120)\n",
-       "Coordinates:\n",
-       "  * dim_0                (dim_0) float32 1kB 0.8 0.8016 0.8032 ... 1.269 1.271\n",
-       "  * time                 (time) float32 12kB -0.04998 -0.04978 ... 0.4086 0.4088\n",
-       "Data variables: (12/30)\n",
-       "    alphaconst_osp       float32 4B ...\n",
-       "    alphaconst_osp_elm   float32 4B ...\n",
-       "    camera_view_osp      float32 4B ...\n",
-       "    etot_osp             (time) float32 12kB dask.array<chunksize=(3120,), meta=np.ndarray>\n",
-       "    etot_osp_elm         (time) float32 12kB dask.array<chunksize=(3120,), meta=np.ndarray>\n",
-       "    etotsum_osp          (time) float32 12kB dask.array<chunksize=(3120,), meta=np.ndarray>\n",
-       "    ...                   ...\n",
-       "    status               float32 4B ...\n",
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-       "    temperature_osp      (time) float32 12kB dask.array<chunksize=(3120,), meta=np.ndarray>\n",
-       "    tprofile_osp         (time, dim_0) float32 4MB dask.array<chunksize=(3120, 299), meta=np.ndarray>\n",
-       "    z_extent_osp         float32 4B ...\n",
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-       "Attributes:\n",
-       "    description:  IR Camera, IR Temperature Reference thermocouples\n",
-       "    file_name:    air0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         air\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       air\n",
-       "    uda_name:     AIR\n",
-       "    uuid:         25edd92e-1378-54ad-8ce1-cf09df251ab8\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 11MB\n", - "Dimensions: (dim_0: 299, time: 3120)\n", - "Coordinates:\n", - " * dim_0 (dim_0) float32 1kB 0.8 0.8016 0.8032 ... 1.269 1.271\n", - " * time (time) float32 12kB -0.04998 -0.04978 ... 0.4086 0.4088\n", - "Data variables: (12/30)\n", - " alphaconst_osp float32 4B ...\n", - " alphaconst_osp_elm float32 4B ...\n", - " camera_view_osp float32 4B ...\n", - " etot_osp (time) float32 12kB dask.array\n", - " etot_osp_elm (time) float32 12kB dask.array\n", - " etotsum_osp (time) float32 12kB dask.array\n", - " ... ...\n", - " status float32 4B ...\n", - " svn_revision float32 4B ...\n", - " temperature_osp (time) float32 12kB dask.array\n", - " tprofile_osp (time, dim_0) float32 4MB dask.array\n", - " z_extent_osp float32 4B ...\n", - " z_start_osp float32 4B ...\n", - "Attributes:\n", - " description: IR Camera, IR Temperature Reference thermocouples\n", - " file_name: air0304.20\n", - " format: IDA3\n", - " mds_name: None\n", - " name: air\n", - " quality: Not Checked\n", - " shot_id: 30420\n", - " signal_type: Analysed\n", - " source: air\n", - " uda_name: AIR\n", - " uuid: 25edd92e-1378-54ad-8ce1-cf09df251ab8\n", - " version: 0" - ] - }, - "execution_count": 81, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'air'\n", - "path = f'/common/tmp/sjackson/local_cache2/30420.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AIT" - ] - }, - { - "cell_type": "code", - "execution_count": 82, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/4060667584.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 17MB\n",
-       "Dimensions:              (dim_0: 214, time: 3161)\n",
-       "Coordinates:\n",
-       "  * dim_0                (dim_0) float32 856B 0.8 0.8063 0.8126 ... 1.815 1.82\n",
-       "  * time                 (time) float32 13kB -0.04995 -0.04975 ... 0.4087 0.4089\n",
-       "Data variables: (12/57)\n",
-       "    alphaconst_isp       float32 4B ...\n",
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-       "    alphaconst_osp_elm   float32 4B ...\n",
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-       "    ...                   ...\n",
-       "    tprofile_isp         (time, dim_0) float32 3MB dask.array<chunksize=(3161, 214), meta=np.ndarray>\n",
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-       "    z_extent_isp         float32 4B ...\n",
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-       "    z_start_isp          float32 4B ...\n",
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-       "Attributes:\n",
-       "    description:  IR Camera\n",
-       "    file_name:    ait0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         ait\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       ait\n",
-       "    uda_name:     AIT\n",
-       "    uuid:         cd0e985b-a11f-59ec-b625-28a370fc6d49\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 17MB\n", - "Dimensions: (dim_0: 214, time: 3161)\n", - "Coordinates:\n", - " * dim_0 (dim_0) float32 856B 0.8 0.8063 0.8126 ... 1.815 1.82\n", - " * time (time) float32 13kB -0.04995 -0.04975 ... 0.4087 0.4089\n", - "Data variables: (12/57)\n", - " alphaconst_isp float32 4B ...\n", - " alphaconst_isp_elm float32 4B ...\n", - " alphaconst_osp float32 4B ...\n", - " alphaconst_osp_elm float32 4B ...\n", - " camera_view_isp float32 4B ...\n", - " camera_view_osp float32 4B ...\n", - " ... ...\n", - " tprofile_isp (time, dim_0) float32 3MB dask.array\n", - " tprofile_osp (time, dim_0) float32 3MB dask.array\n", - " z_extent_isp float32 4B ...\n", - " z_extent_osp float32 4B ...\n", - " z_start_isp float32 4B ...\n", - " z_start_osp float32 4B ...\n", - "Attributes:\n", - " description: IR Camera\n", - " file_name: ait0304.20\n", - " format: IDA3\n", - " mds_name: None\n", - " name: ait\n", - " quality: Not Checked\n", - " shot_id: 30420\n", - " signal_type: Analysed\n", - " source: ait\n", - " uda_name: AIT\n", - " uuid: cd0e985b-a11f-59ec-b625-28a370fc6d49\n", - " version: 0" - ] - }, - "execution_count": 82, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'ait'\n", - "path = f'/common/tmp/sjackson/local_cache2/30420.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ALP - needs review" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/2521670961.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 3MB\n",
-       "Dimensions:                    (time: 288, npts_inner: 32, npts_outer: 64)\n",
-       "Coordinates:\n",
-       "  * time                       (time) float32 1kB 0.1504 0.1514 ... 0.4489\n",
-       "Dimensions without coordinates: npts_inner, npts_outer\n",
-       "Data variables: (12/105)\n",
-       "    badamps                    float32 4B ...\n",
-       "    inner_lo_chisq             (time, npts_inner) float32 37kB dask.array<chunksize=(288, 32), meta=np.ndarray>\n",
-       "    inner_lo_denpeakval        (time) float32 1kB dask.array<chunksize=(288,), meta=np.ndarray>\n",
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-       "    inner_lo_jsapeakpos        (time) float32 1kB dask.array<chunksize=(288,), meta=np.ndarray>\n",
-       "    ...                         ...\n",
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-       "Attributes:\n",
-       "    description:  Langmuir Probe\n",
-       "    file_name:    alp0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         alp\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       alp\n",
-       "    uda_name:     ALP\n",
-       "    uuid:         6e90b3e9-7ec8-594c-8789-2bbf14a556b5\n",
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<xarray.Dataset> Size: 18MB\n",
-       "Dimensions:          (time: 650000)\n",
-       "Coordinates:\n",
-       "  * time             (time) float32 3MB -0.1 -0.1 -0.1 -0.09999 ... 1.2 1.2 1.2\n",
-       "Data variables:\n",
-       "    n=2_amplitude    (time) float32 3MB dask.array<chunksize=(650000,), meta=np.ndarray>\n",
-       "    n=2_frequency    (time) float32 3MB dask.array<chunksize=(650000,), meta=np.ndarray>\n",
-       "    n=2_signal       (time) float32 3MB dask.array<chunksize=(650000,), meta=np.ndarray>\n",
-       "    n=odd_amplitude  (time) float32 3MB dask.array<chunksize=(650000,), meta=np.ndarray>\n",
-       "    n=odd_frequency  (time) float32 3MB dask.array<chunksize=(650000,), meta=np.ndarray>\n",
-       "    n=odd_signal     (time) float32 3MB dask.array<chunksize=(650000,), meta=np.ndarray>\n",
-       "    passnumber       float32 4B ...\n",
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-       "Attributes:\n",
-       "    description:  Magnetic Field Measurements: Analysis of Centre Column Toro...\n",
-       "    file_name:    ama0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         ama\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       ama\n",
-       "    uda_name:     AMA\n",
-       "    uuid:         5e447e91-a1c5-5597-b0c5-03af65abe4e9\n",
-       "    version:      0
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Also requires including mapping r and z coordinates" - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/681441263.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 85, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "source = 'amb'\n", - "path = f'/common/tmp/sjackson/local_cache2/30420.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset\n", - "\n", - "ds = dataset['ccbv'].dropna(dim='time')\n", - "plt.plot(ds.time, ds.values[0])\n", - "\n", - "ds = dataset['obv'].dropna(dim='time')\n", - "plt.plot(ds.time, ds.values[0])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AMC - Needs Review" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/2795289470.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 5MB\n",
-       "Dimensions:            (time: 30000)\n",
-       "Coordinates:\n",
-       "  * time               (time) float32 120kB -2.0 -2.0 -2.0 ... 3.999 4.0 4.0\n",
-       "Data variables: (12/46)\n",
-       "    efps_current       (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    error_field_02     (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    error_field_05     (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    p2il_coil_current  (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    p2il_feed_current  (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    p2iu_coil_current  (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    ...                 ...\n",
-       "    p6u_current        (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    plasma_current     (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    sol_current        (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    status             float32 4B ...\n",
-       "    tf_current         (time) float32 120kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    version            float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  Plasma Current and PF/TF Coil Currents\n",
-       "    file_name:    amc0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         amc\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       amc\n",
-       "    uda_name:     AMC\n",
-       "    uuid:         01aad0c4-2a84-59e2-8b1b-168b4bd66aa3\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 5MB\n", - "Dimensions: (time: 30000)\n", - "Coordinates:\n", - " * time (time) float32 120kB -2.0 -2.0 -2.0 ... 3.999 4.0 4.0\n", - "Data variables: (12/46)\n", - " efps_current (time) float32 120kB dask.array\n", - " error_field_02 (time) float32 120kB dask.array\n", - " error_field_05 (time) float32 120kB dask.array\n", - " p2il_coil_current (time) float32 120kB dask.array\n", - " p2il_feed_current (time) float32 120kB dask.array\n", - " p2iu_coil_current (time) float32 120kB dask.array\n", - " ... ...\n", - " p6u_current (time) float32 120kB dask.array\n", - " plasma_current (time) float32 120kB dask.array\n", - " sol_current (time) float32 120kB dask.array\n", - " status float32 4B ...\n", - " tf_current (time) float32 120kB dask.array\n", - " version float32 4B ...\n", - "Attributes:\n", - " description: Plasma Current and PF/TF Coil Currents\n", - " file_name: amc0304.20\n", - " format: IDA3\n", - " mds_name: None\n", - " name: amc\n", - " quality: Not Checked\n", - " shot_id: 30420\n", - " signal_type: Analysed\n", - " source: amc\n", - " uda_name: AMC\n", - " uuid: 01aad0c4-2a84-59e2-8b1b-168b4bd66aa3\n", - " version: 0" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'amc'\n", - "path = f'/common/tmp/sjackson/local_cache2/30420.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset\n", - "\n", - "# df = make_channel_df(dataset)\n", - "# df.to_csv('amc.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Plasma Current for shot 30420')" - ] - }, - "execution_count": 87, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "current = dataset['plasma_current']\n", - "current = current.isel(time=current.time < .5)\n", - "current = current.isel(time=current.time > -.1)\n", - "\n", - "plt.plot(current.time, current)\n", - "plt.xlabel(f\"Time [{current.time.attrs['units']}]\")\n", - "plt.ylabel(f\"Current [{current.attrs['units']}]\")\n", - "plt.title(f\"Plasma Current for shot {current.attrs['shot_id']}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AMH - Needs Review\n", - "\n", - "AMH also needs further tensorising, but we should check with Lucy about groups." - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/1472096944.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 537kB\n",
-       "Dimensions:              (time: 2200)\n",
-       "Coordinates:\n",
-       "  * time                 (time) float32 9kB 0.289 0.289 0.289 ... 0.329 0.329\n",
-       "Data variables: (12/63)\n",
-       "    halo_ccu_2           (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    halo_p2l_1           (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    halo_p2l_2           (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    halo_p2l_3           (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    halo_p2l_4           (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    halo_p2l_5           (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    ...                   ...\n",
-       "    phalo_sum_p2l_inner  (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    phalo_sum_p2l_outer  (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    phalo_sum_p2u_inner  (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    phalo_sum_p2u_outer  (time) float32 9kB dask.array<chunksize=(2200,), meta=np.ndarray>\n",
-       "    status               float32 4B ...\n",
-       "    version              float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  Halo current Measurements (HAL), P2/P3 Halo Current Measure...\n",
-       "    file_name:    amh0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         amh\n",
-       "    quality:      Bad\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       amh\n",
-       "    uda_name:     AMH\n",
-       "    uuid:         b183d6f1-befe-5843-84da-67e4bf82acbc\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 537kB\n", - "Dimensions: (time: 2200)\n", - "Coordinates:\n", - " * time (time) float32 9kB 0.289 0.289 0.289 ... 0.329 0.329\n", - "Data variables: (12/63)\n", - " halo_ccu_2 (time) float32 9kB dask.array\n", - " halo_p2l_1 (time) float32 9kB dask.array\n", - " halo_p2l_2 (time) float32 9kB dask.array\n", - " halo_p2l_3 (time) float32 9kB dask.array\n", - " halo_p2l_4 (time) float32 9kB dask.array\n", - " halo_p2l_5 (time) float32 9kB dask.array\n", - " ... ...\n", - " phalo_sum_p2l_inner (time) float32 9kB dask.array\n", - " phalo_sum_p2l_outer (time) float32 9kB dask.array\n", - " phalo_sum_p2u_inner (time) float32 9kB dask.array\n", - " phalo_sum_p2u_outer (time) float32 9kB dask.array\n", - " status float32 4B ...\n", - " version float32 4B ...\n", - "Attributes:\n", - " description: Halo current Measurements (HAL), P2/P3 Halo Current Measure...\n", - " file_name: amh0304.20\n", - " format: IDA3\n", - " mds_name: None\n", - " name: amh\n", - " quality: Bad\n", - " shot_id: 30420\n", - " signal_type: Analysed\n", - " source: amh\n", - " uda_name: AMH\n", - " uuid: b183d6f1-befe-5843-84da-67e4bf82acbc\n", - " version: 0" - ] - }, - "execution_count": 88, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'amh'\n", - "path = f'/common/tmp/sjackson/local_cache2/30420.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset\n", - "\n", - "# df = make_channel_df(dataset)\n", - "# df.to_csv('amh.csv')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AMM - Needs Review\n", - "\n", - "Another source that can be hevily tensorized" - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/305250279.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 19MB\n",
-       "Dimensions:        (time: 30000, incon_channel: 10, lhorw_channel: 6,\n",
-       "                    mid_channel: 12, ring_channel: 10, rodgr_channel: 12,\n",
-       "                    uhorw_channel: 6, vertw_channel: 8)\n",
-       "Coordinates:\n",
-       "  * incon_channel  (incon_channel) <U7 280B 'incon1' 'incon2' ... 'incon10'\n",
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-       "  * ring_channel   (ring_channel) <U6 240B 'ring1' 'ring2' ... 'ring9' 'ring10'\n",
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-       "  * time           (time) float32 120kB -2.0 -2.0 -2.0 ... 4.0 4.001 4.001\n",
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-       "  * vertw_channel  (vertw_channel) <U6 192B 'vertw1' 'vertw2' ... 'vertw8'\n",
-       "Data variables: (12/25)\n",
-       "    botcol         (time) float64 240kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    endcrown_l     (time) float64 240kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    endcrown_u     (time) float64 240kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    incon          (incon_channel, time) float64 2MB dask.array<chunksize=(10, 30000), meta=np.ndarray>\n",
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-       "    mid            (mid_channel, time) float64 3MB dask.array<chunksize=(12, 30000), meta=np.ndarray>\n",
-       "    ...             ...\n",
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-       "    tcutoff        float64 8B ...\n",
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-       "    topcol         (time) float64 240kB dask.array<chunksize=(30000,), meta=np.ndarray>\n",
-       "    uhorw          (uhorw_channel, time) float64 1MB dask.array<chunksize=(6, 30000), meta=np.ndarray>\n",
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-       "Attributes:\n",
-       "    description:  Output from EFIT's wall model: calculated induced currents ...\n",
-       "    file_name:    amm0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         amm\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       amm\n",
-       "    uda_name:     AMM\n",
-       "    uuid:         d0b7e413-69f1-5e78-97b4-39ad11f1a9bf\n",
-       "    version:      0
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<xarray.Dataset> Size: 505MB\n",
-       "Dimensions:                 (dim_0: 2219, dim_1: 30, time: 2366)\n",
-       "Coordinates:\n",
-       "  * dim_0                   (dim_0) float32 9kB 0.0 1.0 ... 2.217e+03 2.218e+03\n",
-       "  * dim_1                   (dim_1) float32 120B 0.0 1.0 2.0 ... 27.0 28.0 29.0\n",
-       "  * time                    (time) float32 9kB -0.047 -0.0465 ... 0.597 0.5975\n",
-       "Data variables: (12/57)\n",
-       "    acoeff                  (dim_0, dim_1) float32 266kB dask.array<chunksize=(2219, 30), meta=np.ndarray>\n",
-       "    beam_ok                 float32 4B ...\n",
-       "    ch                      (dim_0) float32 9kB dask.array<chunksize=(2219,), meta=np.ndarray>\n",
-       "    cosbeam                 (dim_0) float32 9kB dask.array<chunksize=(2219,), meta=np.ndarray>\n",
-       "    cpf                     (time, dim_0) float32 21MB dask.array<chunksize=(2366, 2219), meta=np.ndarray>\n",
-       "    cpf_error               (time, dim_0) float32 21MB dask.array<chunksize=(2366, 2219), meta=np.ndarray>\n",
-       "    ...                      ...\n",
-       "    status                  int32 4B ...\n",
-       "    trans                   (dim_0) float32 9kB dask.array<chunksize=(2219,), meta=np.ndarray>\n",
-       "    version                 float32 4B ...\n",
-       "    viewstr                 (dim_0) float32 9kB dask.array<chunksize=(2219,), meta=np.ndarray>\n",
-       "    vx0                     (dim_0, dim_1) float32 266kB dask.array<chunksize=(2219, 30), meta=np.ndarray>\n",
-       "    vy0                     (dim_0, dim_1) float32 266kB dask.array<chunksize=(2219, 30), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  Multi-channel MSE\n",
-       "    file_name:    ams0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         ams\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       ams\n",
-       "    uda_name:     AMS\n",
-       "    uuid:         93f00af6-646d-5dbf-bc4b-f4082969b0da\n",
-       "    version:      0
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<xarray.Dataset> Size: 8MB\n",
-       "Dimensions:               (time: 99921)\n",
-       "Coordinates:\n",
-       "  * time                  (time) float64 799kB -0.5 -0.5 -0.4999 ... 2.0 2.0 2.0\n",
-       "Data variables: (12/20)\n",
-       "    passnumber            int32 4B ...\n",
-       "    ss_full_power         (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    ss_full_power_error   (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    ss_half_power         (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    ss_half_power_error   (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    ss_sum_power          (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    ...                    ...\n",
-       "    sw_sum_power          (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    sw_sum_power_error    (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    sw_third_power        (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    sw_third_power_error  (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    tot_sum_power         (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "    tot_sum_power_error   (time) float32 400kB dask.array<chunksize=(99921,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  Neutral Beam Injection data\n",
-       "    file_name:    anb0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         anb\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       anb\n",
-       "    uda_name:     ANB\n",
-       "    uuid:         1014bccb-b858-5c7b-aee5-d7f7b89aeb81\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 8MB\n", - "Dimensions: (time: 99921)\n", - "Coordinates:\n", - " * time (time) float64 799kB -0.5 -0.5 -0.4999 ... 2.0 2.0 2.0\n", - "Data variables: (12/20)\n", - " passnumber int32 4B ...\n", - " ss_full_power (time) float32 400kB dask.array\n", - " ss_full_power_error (time) float32 400kB dask.array\n", - " ss_half_power (time) float32 400kB dask.array\n", - " ss_half_power_error (time) float32 400kB dask.array\n", - " ss_sum_power (time) float32 400kB dask.array\n", - " ... ...\n", - " sw_sum_power (time) float32 400kB dask.array\n", - " sw_sum_power_error (time) float32 400kB dask.array\n", - " sw_third_power (time) float32 400kB dask.array\n", - " sw_third_power_error (time) float32 400kB dask.array\n", - " tot_sum_power (time) float32 400kB dask.array\n", - " tot_sum_power_error (time) float32 400kB dask.array\n", - "Attributes:\n", - " description: Neutral Beam Injection data\n", - " file_name: anb0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: anb\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: anb\n", - " uda_name: ANB\n", - " uuid: 1014bccb-b858-5c7b-aee5-d7f7b89aeb81\n", - " version: 0" - ] - }, - "execution_count": 92, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'anb'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ANE" - ] - }, - { - "cell_type": "code", - "execution_count": 132, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/4087638451.py:3: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 524kB\n",
-       "Dimensions:        (time: 32768)\n",
-       "Coordinates:\n",
-       "  * time           (time) float32 131kB -0.01 -0.00996 -0.00992 ... 1.301 1.301\n",
-       "Data variables:\n",
-       "    co2            (time) float32 131kB dask.array<chunksize=(32768,), meta=np.ndarray>\n",
-       "    density        (time) float32 131kB dask.array<chunksize=(32768,), meta=np.ndarray>\n",
-       "    hene           (time) float32 131kB dask.array<chunksize=(32768,), meta=np.ndarray>\n",
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-       "Attributes:\n",
-       "    description:  CO2 Interferometry\n",
-       "    file_name:    ane0304.20\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         ane\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30420\n",
-       "    signal_type:  Analysed\n",
-       "    source:       ane\n",
-       "    uda_name:     ANE\n",
-       "    uuid:         5f814dd8-7336-56d7-a1ea-bac62e5cdcd3\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 524kB\n", - "Dimensions: (time: 32768)\n", - "Coordinates:\n", - " * time (time) float32 131kB -0.01 -0.00996 -0.00992 ... 1.301 1.301\n", - "Data variables:\n", - " co2 (time) float32 131kB dask.array\n", - " density (time) float32 131kB dask.array\n", - " hene (time) float32 131kB dask.array\n", - " passnumber float32 4B ...\n", - " status float32 4B ...\n", - " status_detail float32 4B ...\n", - " version float32 4B ...\n", - "Attributes:\n", - " description: CO2 Interferometry\n", - " file_name: ane0304.20\n", - " format: IDA3\n", - " mds_name: None\n", - " name: ane\n", - " quality: Not Checked\n", - " shot_id: 30420\n", - " signal_type: Analysed\n", - " source: ane\n", - " uda_name: ANE\n", - " uuid: 5f814dd8-7336-56d7-a1ea-bac62e5cdcd3\n", - " version: 0" - ] - }, - "execution_count": 132, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'ane'\n", - "path = f'/common/tmp/sjackson/local_cache2/30420.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ANT" - ] - }, - { - "cell_type": "code", - "execution_count": 98, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/1934396220.py:3: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 16B\n",
-       "Dimensions:       ()\n",
-       "Data variables:\n",
-       "    neutron_dose  float32 4B ...\n",
-       "    passnumber    float32 4B ...\n",
-       "    status        float32 4B ...\n",
-       "    version       float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  Neutron Dose\n",
-       "    file_name:    ant0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         ant\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       ant\n",
-       "    uda_name:     ANT\n",
-       "    uuid:         c02ae64b-dfe9-52f7-9f1a-888b7ee99b53\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 16B\n", - "Dimensions: ()\n", - "Data variables:\n", - " neutron_dose float32 4B ...\n", - " passnumber float32 4B ...\n", - " status float32 4B ...\n", - " version float32 4B ...\n", - "Attributes:\n", - " description: Neutron Dose\n", - " file_name: ant0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: ant\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: ant\n", - " uda_name: ANT\n", - " uuid: c02ae64b-dfe9-52f7-9f1a-888b7ee99b53\n", - " version: 0" - ] - }, - "execution_count": 98, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'ant'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ANU" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/1251111175.py:3: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 5MB\n",
-       "Dimensions:         (time: 194512)\n",
-       "Coordinates:\n",
-       "  * time            (time) float32 778kB -0.1025 -0.1 -0.09999 ... 1.388 1.393\n",
-       "Data variables:\n",
-       "    errors          (time) float32 778kB dask.array<chunksize=(194512,), meta=np.ndarray>\n",
-       "    neutrons        (time) float32 778kB dask.array<chunksize=(194512,), meta=np.ndarray>\n",
-       "    neutrons_cb     (time) float32 778kB dask.array<chunksize=(194512,), meta=np.ndarray>\n",
-       "    neutrons_count  (time) float32 778kB dask.array<chunksize=(194512,), meta=np.ndarray>\n",
-       "    neutrons_dc     (time) float32 778kB dask.array<chunksize=(194512,), meta=np.ndarray>\n",
-       "    passnumber      float32 4B ...\n",
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-       "    version         float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  Neutrons\n",
-       "    file_name:    anu0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         anu\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       anu\n",
-       "    uda_name:     ANU\n",
-       "    uuid:         9b710b29-1ef8-55bc-971f-3ed9c5cf811d\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 5MB\n", - "Dimensions: (time: 194512)\n", - "Coordinates:\n", - " * time (time) float32 778kB -0.1025 -0.1 -0.09999 ... 1.388 1.393\n", - "Data variables:\n", - " errors (time) float32 778kB dask.array\n", - " neutrons (time) float32 778kB dask.array\n", - " neutrons_cb (time) float32 778kB dask.array\n", - " neutrons_count (time) float32 778kB dask.array\n", - " neutrons_dc (time) float32 778kB dask.array\n", - " passnumber float32 4B ...\n", - " status float32 4B ...\n", - " version float32 4B ...\n", - "Attributes:\n", - " description: Neutrons\n", - " file_name: anu0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: anu\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: anu\n", - " uda_name: ANU\n", - " uuid: 9b710b29-1ef8-55bc-971f-3ed9c5cf811d\n", - " version: 0" - ] - }, - "execution_count": 99, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'anu'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AOE - Needs Review\n", - "\n", - "Requires further work! Time ranges are different!" - ] - }, - { - "cell_type": "code", - "execution_count": 101, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/1224662746.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 30MB\n",
-       "Dimensions:     (time: 757862)\n",
-       "Coordinates:\n",
-       "  * time        (time) float32 3MB 2.384e-07 2.238e-06 ... 0.5243 0.5243\n",
-       "Data variables:\n",
-       "    co2_frac    (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    fast_k      (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    fast_ka     (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    fast_sync   (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    fast_u      (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    k_band      (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    ka_band     (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    passnumber  float32 4B ...\n",
-       "    ramping     (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    status      float32 4B ...\n",
-       "    u_band      (time) float32 3MB dask.array<chunksize=(757862,), meta=np.ndarray>\n",
-       "    version     float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  IST Reflectometer\n",
-       "    file_name:    aoe0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         aoe\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       aoe\n",
-       "    uda_name:     AOE\n",
-       "    uuid:         d2acfca7-96b2-558d-bd44-063ca22b47c6\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 30MB\n", - "Dimensions: (time: 757862)\n", - "Coordinates:\n", - " * time (time) float32 3MB 2.384e-07 2.238e-06 ... 0.5243 0.5243\n", - "Data variables:\n", - " co2_frac (time) float32 3MB dask.array\n", - " fast_k (time) float32 3MB dask.array\n", - " fast_ka (time) float32 3MB dask.array\n", - " fast_sync (time) float32 3MB dask.array\n", - " fast_u (time) float32 3MB dask.array\n", - " k_band (time) float32 3MB dask.array\n", - " ka_band (time) float32 3MB dask.array\n", - " passnumber float32 4B ...\n", - " ramping (time) float32 3MB dask.array\n", - " status float32 4B ...\n", - " u_band (time) float32 3MB dask.array\n", - " version float32 4B ...\n", - "Attributes:\n", - " description: IST Reflectometer\n", - " file_name: aoe0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: aoe\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: aoe\n", - " uda_name: AOE\n", - " uuid: d2acfca7-96b2-558d-bd44-063ca22b47c6\n", - " version: 0" - ] - }, - "execution_count": 101, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'aoe'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ARP" - ] - }, - { - "cell_type": "code", - "execution_count": 102, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/378457931.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 2MB\n",
-       "Dimensions:      (time: 177304)\n",
-       "Coordinates:\n",
-       "  * time         (time) float32 709kB 0.15 0.15 0.15 ... 0.2914 0.2914 0.2914\n",
-       "Data variables:\n",
-       "    passnumber   float32 4B ...\n",
-       "    rp_gap_efit  (time) float32 709kB dask.array<chunksize=(177304,), meta=np.ndarray>\n",
-       "    rp_radius    (time) float32 709kB dask.array<chunksize=(177304,), meta=np.ndarray>\n",
-       "    status       float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  Reciprocating Probe\n",
-       "    file_name:    arp0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         arp\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       arp\n",
-       "    uda_name:     ARP\n",
-       "    uuid:         9a6d57e8-4d84-5db9-b484-b7734cbfba4c\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 2MB\n", - "Dimensions: (time: 177304)\n", - "Coordinates:\n", - " * time (time) float32 709kB 0.15 0.15 0.15 ... 0.2914 0.2914 0.2914\n", - "Data variables:\n", - " passnumber float32 4B ...\n", - " rp_gap_efit (time) float32 709kB dask.array\n", - " rp_radius (time) float32 709kB dask.array\n", - " status float32 4B ...\n", - "Attributes:\n", - " description: Reciprocating Probe\n", - " file_name: arp0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: arp\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: arp\n", - " uda_name: ARP\n", - " uuid: 9a6d57e8-4d84-5db9-b484-b7734cbfba4c\n", - " version: 0" - ] - }, - "execution_count": 102, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'arp'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ASB" - ] - }, - { - "cell_type": "code", - "execution_count": 103, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/531739116.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 636B\n",
-       "Dimensions:       (time: 52)\n",
-       "Coordinates:\n",
-       "  * time          (time) float32 208B -0.015 0.002204 0.01941 ... 0.8452 0.8624\n",
-       "Data variables:\n",
-       "    cii_dga       (time) float32 208B dask.array<chunksize=(52,), meta=np.ndarray>\n",
-       "    oii_dga       (time) float32 208B dask.array<chunksize=(52,), meta=np.ndarray>\n",
-       "    passnumber    int32 4B ...\n",
-       "    status        int32 4B ...\n",
-       "    svn_revision  float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  D-alpha emission and other spectral lines\n",
-       "    file_name:    asb0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         asb\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       asb\n",
-       "    uda_name:     ASB\n",
-       "    uuid:         79357e85-023f-591a-b0fb-8796dc642ad3\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 636B\n", - "Dimensions: (time: 52)\n", - "Coordinates:\n", - " * time (time) float32 208B -0.015 0.002204 0.01941 ... 0.8452 0.8624\n", - "Data variables:\n", - " cii_dga (time) float32 208B dask.array\n", - " oii_dga (time) float32 208B dask.array\n", - " passnumber int32 4B ...\n", - " status int32 4B ...\n", - " svn_revision float32 4B ...\n", - "Attributes:\n", - " description: D-alpha emission and other spectral lines\n", - " file_name: asb0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: asb\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: asb\n", - " uda_name: ASB\n", - " uuid: 79357e85-023f-591a-b0fb-8796dc642ad3\n", - " version: 0" - ] - }, - "execution_count": 103, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'asb'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ASM - Needs Review\n", - "Another one which needs to be tensorized" - ] - }, - { - "cell_type": "code", - "execution_count": 104, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/3841051880.py:3: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 3MB\n",
-       "Dimensions:              (time: 32163, sad_m_channel: 11)\n",
-       "Coordinates:\n",
-       "  * sad_m_channel        (sad_m_channel) <U8 352B 'sad_m01' ... 'sad_m012'\n",
-       "  * time                 (time) float32 129kB -2.0 -2.0 -2.0 ... 4.0 4.001 4.001\n",
-       "Data variables: (12/16)\n",
-       "    hm_periods           (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    hm_rating            (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    out_nn_pattern       (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    out_nn_rating        (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    out_rating           (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    out_signal           (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    ...                   ...\n",
-       "    sad_d02_2-8          (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    sad_d03_4-10         (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    sad_d04_5-11         (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    sad_d05_6-12         (time) float32 129kB dask.array<chunksize=(32163,), meta=np.ndarray>\n",
-       "    sad_m                (sad_m_channel, time) float32 1MB dask.array<chunksize=(11, 32163), meta=np.ndarray>\n",
-       "    status               float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  H-mode and locked mode detector, Outer Saddle Magnetic Coil...\n",
-       "    file_name:    asm0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         asm\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       asm\n",
-       "    uda_name:     ASM\n",
-       "    uuid:         bd50e5ec-1be0-523b-9f15-7bec0626d027\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 3MB\n", - "Dimensions: (time: 32163, sad_m_channel: 11)\n", - "Coordinates:\n", - " * sad_m_channel (sad_m_channel) \n", - " hm_rating (time) float32 129kB dask.array\n", - " out_nn_pattern (time) float32 129kB dask.array\n", - " out_nn_rating (time) float32 129kB dask.array\n", - " out_rating (time) float32 129kB dask.array\n", - " out_signal (time) float32 129kB dask.array\n", - " ... ...\n", - " sad_d02_2-8 (time) float32 129kB dask.array\n", - " sad_d03_4-10 (time) float32 129kB dask.array\n", - " sad_d04_5-11 (time) float32 129kB dask.array\n", - " sad_d05_6-12 (time) float32 129kB dask.array\n", - " sad_m (sad_m_channel, time) float32 1MB dask.array\n", - " status float32 4B ...\n", - "Attributes:\n", - " description: H-mode and locked mode detector, Outer Saddle Magnetic Coil...\n", - " file_name: asm0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: asm\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: asm\n", - " uda_name: ASM\n", - " uuid: bd50e5ec-1be0-523b-9f15-7bec0626d027\n", - " version: 0" - ] - }, - "execution_count": 104, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'asm'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset\n", - "# df = make_channel_df(dataset)\n", - "# df.to_csv('asm.csv')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ASX - Needs Review\n", - "\n", - "Time has two values, but these differ between variables." - ] - }, - { - "cell_type": "code", - "execution_count": 106, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/2167650289.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 80B\n",
-       "Dimensions:              (npts: 2)\n",
-       "Dimensions without coordinates: npts\n",
-       "Data variables:\n",
-       "    elm_freqs            (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    elmy                 (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    large_scale          (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    lower_false_inv_rad  (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    modes                (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    passnumber           int32 4B ...\n",
-       "    sawteeth             (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    sawtooth_periods     (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    status               int32 4B ...\n",
-       "    up_cam_nos_sawt_inv  (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    upper_false_inv_rad  (npts) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  Automatic analysis of soft X-rays, sawtooth\n",
-       "    file_name:    asx0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         asx\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       asx\n",
-       "    uda_name:     ASX\n",
-       "    uuid:         a1ff2e5f-3902-58d2-82fd-67fac3f402af\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 80B\n", - "Dimensions: (npts: 2)\n", - "Dimensions without coordinates: npts\n", - "Data variables:\n", - " elm_freqs (npts) float32 8B dask.array\n", - " elmy (npts) float32 8B dask.array\n", - " large_scale (npts) float32 8B dask.array\n", - " lower_false_inv_rad (npts) float32 8B dask.array\n", - " modes (npts) float32 8B dask.array\n", - " passnumber int32 4B ...\n", - " sawteeth (npts) float32 8B dask.array\n", - " sawtooth_periods (npts) float32 8B dask.array\n", - " status int32 4B ...\n", - " up_cam_nos_sawt_inv (npts) float32 8B dask.array\n", - " upper_false_inv_rad (npts) float32 8B dask.array\n", - "Attributes:\n", - " description: Automatic analysis of soft X-rays, sawtooth\n", - " file_name: asx0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: asx\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: asx\n", - " uda_name: ASX\n", - " uuid: a1ff2e5f-3902-58d2-82fd-67fac3f402af\n", - " version: 0" - ] - }, - "execution_count": 106, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'asx'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AYC" - ] - }, - { - "cell_type": "code", - "execution_count": 107, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/251954800.py:4: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 3MB\n",
-       "Dimensions:              (time: 174, arb: 130, radial_index: 130,\n",
-       "                          spectral_index: 4)\n",
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-       "  * arb                  (arb) float32 520B 0.0 1.0 2.0 ... 127.0 128.0 129.0\n",
-       "  * radial_index         (radial_index) float32 520B 1.0 2.0 3.0 ... 129.0 130.0\n",
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-       "  * time                 (time) float32 696B 0.0 1.02e-05 0.00417 ... 85.0 86.0\n",
-       "Data variables: (12/37)\n",
-       "    acqiris_time         (time) float32 696B dask.array<chunksize=(174,), meta=np.ndarray>\n",
-       "    angle                (arb) float32 520B dask.array<chunksize=(130,), meta=np.ndarray>\n",
-       "    aspectra             (time, radial_index, spectral_index) float32 362kB dask.array<chunksize=(174, 130, 4), meta=np.ndarray>\n",
-       "    chi2                 (time, radial_index) float32 90kB dask.array<chunksize=(174, 130), meta=np.ndarray>\n",
-       "    covariance_ne_te     (time, radial_index) float32 90kB dask.array<chunksize=(174, 130), meta=np.ndarray>\n",
-       "    instrument_dr        (time, radial_index) float32 90kB dask.array<chunksize=(174, 130), meta=np.ndarray>\n",
-       "    ...                   ...\n",
-       "    time_                (time) float32 696B dask.array<chunksize=(174,), meta=np.ndarray>\n",
-       "    version_fibre        float32 4B ...\n",
-       "    version_poly         float32 4B ...\n",
-       "    version_raman        float32 4B ...\n",
-       "    xyc_time             (time) float32 696B dask.array<chunksize=(174,), meta=np.ndarray>\n",
-       "    yag_nelint           (time) float32 696B dask.array<chunksize=(174,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  Core Thomson scattering data\n",
-       "    file_name:    ayc0297.90\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         ayc\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      29790\n",
-       "    signal_type:  Analysed\n",
-       "    source:       ayc\n",
-       "    uda_name:     AYC\n",
-       "    uuid:         a991f3ce-bc05-5366-b55b-3c072a3ca904\n",
-       "    version:      0
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...\n", - " xyc_time (time) float32 696B dask.array\n", - " yag_nelint (time) float32 696B dask.array\n", - "Attributes:\n", - " description: Core Thomson scattering data\n", - " file_name: ayc0297.90\n", - " format: IDA3\n", - " mds_name: None\n", - " name: ayc\n", - " quality: Not Checked\n", - " shot_id: 29790\n", - " signal_type: Analysed\n", - " source: ayc\n", - " uda_name: AYC\n", - " uuid: a991f3ce-bc05-5366-b55b-3c072a3ca904\n", - " version: 0" - ] - }, - "execution_count": 107, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'ayc'\n", - "path = f'/common/tmp/sjackson/local_cache2/29790.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "code", - "execution_count": 108, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 108, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from skimage.morphology import disk\n", - "te = dataset['te'].T\n", - "te.values = te.values / 1000\n", - "te = te.fillna(0)\n", - "te.values = filters.median(te.values, footprint=disk(1))\n", - "\n", - "ne = dataset['ne'].T\n", - "ne = ne.fillna(0)\n", - "ne.values = ne.values / 1e19\n", - "ne.values = filters.median(ne.values, footprint=disk(1))\n", - "\n", - "r = dataset.r.dropna(dim='time')\n", - "te = te.sel(time=r.time)\n", - "ne = ne.sel(time=r.time)\n", - "time = te.time\n", - "angle = r.values[0]#dataset['angle']\n", - "\n", - "time, angle = np.meshgrid(time, angle)\n", - "\n", - "fig, ax = plt.subplots()\n", - "plt.pcolormesh(time, angle, te, cmap='jet')\n", - "ax.set_xlabel('Time [sec]')\n", - "ax.set_ylabel('Radius [m]')\n", - "ax.set_title(f\"Thompson Scattering $T_e$ [keV] Profile for shot {te.attrs['shot_id']}\")\n", - "plt.colorbar()\n", - "\n", - "fig, ax = plt.subplots()\n", - "plt.pcolormesh(time, angle, ne, cmap='jet')\n", - "ax.set_xlabel('Time [sec]')\n", - "ax.set_ylabel('Radius [m]')\n", - "ax.set_title(\"Thompson Scattering $n_e$ [$10^{19} m^{-3}$]\" + f\" Profile for shot {ne.attrs['shot_id']}\")\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### AYE" - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/2895452325.py:3: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 348kB\n",
-       "Dimensions:              (arb: 16, time: 138, radial_index: 16,\n",
-       "                          spectral_index: 4)\n",
-       "Coordinates:\n",
-       "  * arb                  (arb) float32 64B 0.0 1.0 2.0 3.0 ... 13.0 14.0 15.0\n",
-       "  * radial_index         (radial_index) float32 64B 1.0 2.0 3.0 ... 15.0 16.0\n",
-       "  * spectral_index       (spectral_index) float32 16B 1.0 2.0 3.0 4.0\n",
-       "  * time                 (time) float32 552B 0.0 0.00416 0.00832 ... 67.0 68.0\n",
-       "Data variables: (12/32)\n",
-       "    angle                (arb) float32 64B dask.array<chunksize=(16,), meta=np.ndarray>\n",
-       "    aspectra             (time, radial_index, spectral_index) float32 35kB dask.array<chunksize=(138, 16, 4), meta=np.ndarray>\n",
-       "    chi2                 (time, radial_index) float32 9kB dask.array<chunksize=(138, 16), meta=np.ndarray>\n",
-       "    covariance_ne_te     (time, radial_index) float32 9kB dask.array<chunksize=(138, 16), meta=np.ndarray>\n",
-       "    gauss_amplitude      (time, radial_index, spectral_index) float32 35kB dask.array<chunksize=(138, 16, 4), meta=np.ndarray>\n",
-       "    gauss_dclevel        (time, radial_index, spectral_index) float32 35kB dask.array<chunksize=(138, 16, 4), meta=np.ndarray>\n",
-       "    ...                   ...\n",
-       "    te                   (time, radial_index) float32 9kB dask.array<chunksize=(138, 16), meta=np.ndarray>\n",
-       "    te_error             (time, radial_index) float32 9kB dask.array<chunksize=(138, 16), meta=np.ndarray>\n",
-       "    time_                (time) float32 552B dask.array<chunksize=(138,), meta=np.ndarray>\n",
-       "    version_fibre        float32 4B ...\n",
-       "    version_poly         float32 4B ...\n",
-       "    version_raman        float32 4B ...\n",
-       "Attributes:\n",
-       "    description:  Edge Thomson scattering data\n",
-       "    file_name:    aye0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         aye\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       aye\n",
-       "    uda_name:     AYE\n",
-       "    uuid:         0bc63d4d-ca79-5f29-b490-b28f7dd28e67\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 348kB\n", - "Dimensions: (arb: 16, time: 138, radial_index: 16,\n", - " spectral_index: 4)\n", - "Coordinates:\n", - " * arb (arb) float32 64B 0.0 1.0 2.0 3.0 ... 13.0 14.0 15.0\n", - " * radial_index (radial_index) float32 64B 1.0 2.0 3.0 ... 15.0 16.0\n", - " * spectral_index (spectral_index) float32 16B 1.0 2.0 3.0 4.0\n", - " * time (time) float32 552B 0.0 0.00416 0.00832 ... 67.0 68.0\n", - "Data variables: (12/32)\n", - " angle (arb) float32 64B dask.array\n", - " aspectra (time, radial_index, spectral_index) float32 35kB dask.array\n", - " chi2 (time, radial_index) float32 9kB dask.array\n", - " covariance_ne_te (time, radial_index) float32 9kB dask.array\n", - " gauss_amplitude (time, radial_index, spectral_index) float32 35kB dask.array\n", - " gauss_dclevel (time, radial_index, spectral_index) float32 35kB dask.array\n", - " ... ...\n", - " te (time, radial_index) float32 9kB dask.array\n", - " te_error (time, radial_index) float32 9kB dask.array\n", - " time_ (time) float32 552B dask.array\n", - " version_fibre float32 4B ...\n", - " version_poly float32 4B ...\n", - " version_raman float32 4B ...\n", - "Attributes:\n", - " description: Edge Thomson scattering data\n", - " file_name: aye0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: aye\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: aye\n", - " uda_name: AYE\n", - " uuid: 0bc63d4d-ca79-5f29-b490-b28f7dd28e67\n", - " version: 0" - ] - }, - "execution_count": 110, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'aye'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### EFM - Needs Review\n", - "Needs more work\n", - "\n", - "0 -1 is normalised psi\n", - "\n", - "psi - psi_norm - areap_c\n", - "dim_0 - num_iterations - chisq_magnetic\n", - "psi - psi_norm - elongpsi_c\n", - "dim_0 - fcoil_segs_n - fcoil_ang1\n", - "dim_0 - fcoil_segs_n - fcoil_ang2\n", - "dim_0 - fcoil_n - fcoil_c\n", - "dim_0 - fcoil_n - fcoil_chisq\n", - "dim_0 - ffprime_coefs_n - ffprime_coefs\n", - "dim_0 - magpr_n - fwtmp\n", - "dim_0 - silop_n - fwtsi\n", - "dim_0 - nr - gridr\n", - "dim_0 - nz - gridz\n", - "r - nr_prof - jr\n", - "dim_0 - limiter_n - limiterr\n", - "dim_0 - limiter_n - limiterz\n", - "dim_0 - magpr_n - magpr_ang\n", - "z/r - nz/nr - plasma_currrz\n", - "\n", - "pprime_coefs - as ffprime\n", - "r - nr_prof - pr_c\n", - "r - nr_prof - psir\n", - "height/radius - nz/nr - psirz\n", - "psi - psi_norm - pwpsi_c\n", - "r - nr_prof - qr\n", - "r - nr_prof - rvals - rvals for the radial profiles\n", - "\n", - "dim_0 - silop_n - silop_c\n", - "dim_0 - silop_n - silop_chisq" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 4MB\n",
-       "Dimensions:            (time: 66, psi_norm: 65, n_iterations: 10,\n",
-       "                        fcoil_seg_n: 938, fcoil_n: 101, ffprime_coefs_n: 2,\n",
-       "                        mag_probe_n: 78, psi_loop_n: 46, r: 65, z: 65,\n",
-       "                        profile_r: 129, lcfs_coords: 139, limiter_n: 37,\n",
-       "                        pprime_coefs_n: 2, profile_z: 65)\n",
-       "Coordinates: (12/13)\n",
-       "  * fcoil_n            (fcoil_n) float32 404B 0.0 1.0 2.0 ... 98.0 99.0 100.0\n",
-       "  * ffprime_coefs_n    (ffprime_coefs_n) float32 8B 0.0 1.0\n",
-       "  * lcfs_coords        (lcfs_coords) float32 556B 0.0 1.0 2.0 ... 137.0 138.0\n",
-       "  * mag_probe_n        (mag_probe_n) float32 312B 0.0 1.0 2.0 ... 75.0 76.0 77.0\n",
-       "  * n_iterations       (n_iterations) float32 40B 0.0 1.0 2.0 ... 7.0 8.0 9.0\n",
-       "  * pprime_coefs_n     (pprime_coefs_n) float32 8B 0.0 1.0\n",
-       "    ...                 ...\n",
-       "  * profile_z          (profile_z) float32 260B -2.0 -1.938 -1.875 ... 1.938 2.0\n",
-       "  * psi_loop_n         (psi_loop_n) float32 184B 0.0 1.0 2.0 ... 43.0 44.0 45.0\n",
-       "  * psi_norm           (psi_norm) float32 260B 0.0 0.01562 ... 0.9844 1.0\n",
-       "  * r                  (r) float32 260B 0.06 0.09031 0.1206 ... 1.939 1.97 2.0\n",
-       "  * time               (time) float32 264B -0.05 -0.045 -0.04 ... 0.3 0.305\n",
-       "  * z                  (z) float32 260B -2.0 -1.938 -1.875 ... 1.875 1.938 2.0\n",
-       "Dimensions without coordinates: fcoil_seg_n, limiter_n\n",
-       "Data variables: (12/151)\n",
-       "    all_times          (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    areap_c            (time, psi_norm) float32 17kB dask.array<chunksize=(66, 65), meta=np.ndarray>\n",
-       "    betan              (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    betap              (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    betapd             (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    betat              (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    ...                 ...\n",
-       "    wpol               (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    xpoint1_rc         (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    xpoint1_zc         (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    xpoint2_rc         (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    xpoint2_zc         (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "    zbdry              (time) float32 264B dask.array<chunksize=(66,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  Basic EFIT\n",
-       "    file_name:    efm0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         efm\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       efm\n",
-       "    uda_name:     EFM\n",
-       "    uuid:         5504040f-07a7-5c7a-88a7-a157b47a2090\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 4MB\n", - "Dimensions: (time: 66, psi_norm: 65, n_iterations: 10,\n", - " fcoil_seg_n: 938, fcoil_n: 101, ffprime_coefs_n: 2,\n", - " mag_probe_n: 78, psi_loop_n: 46, r: 65, z: 65,\n", - " profile_r: 129, lcfs_coords: 139, limiter_n: 37,\n", - " pprime_coefs_n: 2, profile_z: 65)\n", - "Coordinates: (12/13)\n", - " * fcoil_n (fcoil_n) float32 404B 0.0 1.0 2.0 ... 98.0 99.0 100.0\n", - " * ffprime_coefs_n (ffprime_coefs_n) float32 8B 0.0 1.0\n", - " * lcfs_coords (lcfs_coords) float32 556B 0.0 1.0 2.0 ... 137.0 138.0\n", - " * mag_probe_n (mag_probe_n) float32 312B 0.0 1.0 2.0 ... 75.0 76.0 77.0\n", - " * n_iterations (n_iterations) float32 40B 0.0 1.0 2.0 ... 7.0 8.0 9.0\n", - " * pprime_coefs_n (pprime_coefs_n) float32 8B 0.0 1.0\n", - " ... ...\n", - " * profile_z (profile_z) float32 260B -2.0 -1.938 -1.875 ... 1.938 2.0\n", - " * psi_loop_n (psi_loop_n) float32 184B 0.0 1.0 2.0 ... 43.0 44.0 45.0\n", - " * psi_norm (psi_norm) float32 260B 0.0 0.01562 ... 0.9844 1.0\n", - " * r (r) float32 260B 0.06 0.09031 0.1206 ... 1.939 1.97 2.0\n", - " * time (time) float32 264B -0.05 -0.045 -0.04 ... 0.3 0.305\n", - " * z (z) float32 260B -2.0 -1.938 -1.875 ... 1.875 1.938 2.0\n", - "Dimensions without coordinates: fcoil_seg_n, limiter_n\n", - "Data variables: (12/151)\n", - " all_times (time) float32 264B dask.array\n", - " areap_c (time, psi_norm) float32 17kB dask.array\n", - " betan (time) float32 264B dask.array\n", - " betap (time) float32 264B dask.array\n", - " betapd (time) float32 264B dask.array\n", - " betat (time) float32 264B dask.array\n", - " ... ...\n", - " wpol (time) float32 264B dask.array\n", - " xpoint1_rc (time) float32 264B dask.array\n", - " xpoint1_zc (time) float32 264B dask.array\n", - " xpoint2_rc (time) float32 264B dask.array\n", - " xpoint2_zc (time) float32 264B dask.array\n", - " zbdry (time) float32 264B dask.array\n", - "Attributes:\n", - " description: Basic EFIT\n", - " file_name: efm0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: efm\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: efm\n", - " uda_name: EFM\n", - " uuid: 5504040f-07a7-5c7a-88a7-a157b47a2090\n", - " version: 0" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'efm'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "dataset\n", - "\n", - "# # df = pd.DataFrame(items)\n", - "# # df.to_csv('efm.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": 113, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/3102430359.py:19: UserWarning: The following kwargs were not used by contour: 'label'\n", - " ax.contourf(R, Z, d[index], cmap='magma', levels=20, label='Plasma Current')\n", - "/tmp/ipykernel_6672/3102430359.py:18: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.\n", - " fig, ax = plt.subplots()\n", - "/tmp/ipykernel_6672/3102430359.py:38: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.\n", - " image = imageio.imread(file_name)\n" - ] - }, - { - "data": { - "image/png": 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", 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", 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", 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", 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", 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", 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Qa665hvbt23vsr+h05uISExNp2rRpqR++xMREDh065L7vcrl4+umnef7559myZYt7jBD4756EwtAIcOTIEb/l7PJ2tqavdb/99hvw5xi1korqWsTbc1a3bl2P5yZYU6ZMweFw8OCDDxITE8PLL7/M8OHDqVOnDk8//TRQOF6lW7duth+jiN3nvqzPU+PGjZkxYwbPP/88v/32G5988gmPPvoo9957L40bNw76bLxt27YBhSG+pFNPPZVPPvmEzMxMatWq5V7u73Uv6ZRTTmHu3Lk4nU5+/fVXFi1axGOPPcaYMWNo2bKlx3dC8TFHRUq+5tu2bfP6+px66qnu9eUJUm3atKFNmzYAXHvttZx33nlceOGFfPPNN1iWVao7rricnBygdBdd8+bN3ePErrrqKsaMGUP//v3ZuHGju+wLL7xAdnY2t99+O7fffjsAf/vb3zjxxBN59913fZ6NOW/ePJKTkxk0aJDtY5byU5CSGu3kk08OOsDdfPPNzJo1i3HjxtGjRw8SExOxLIthw4Z5jFXo3bs3mzdv5r333mPJkiX85z//Ydq0acycOdPjB81bC52/5cWD28MPP8y//vUv/u///o8HHniA5ORkHA4H48aN8ztuAnD/IPz8888BnQLuqzWjeHgrztf0Fd7WFdV17ty5HvOHFYmM9Pwq8vXclMfKlSvp2LGjO0hfc8017NmzhzvuuIM6deowbNgwVq1axTvvvFPuxwr2uQ+WZVmccsopnHLKKQwePJiTTz6ZefPmVcq0Bv5ed18iIiJo164d7dq1o0ePHvTr14958+Z5fDYD+TxUtssvv5zrr7+e//3vf7Ru3ZrGjRsDhS15Je3evds9V1hZ+/z3v//NF198wYABA4DCP6Dee+89tm/fztatW93hq2fPnjRo0ICkpKRS+9m+fTtffvklY8aMISoqqvwHK7YpSImU8PbbbzN8+HCeeOIJ97KcnJxSZ+8AJCcnM3LkSEaOHMnRo0fp3bs39913X8h+0N5++2369evHSy+95LH88OHD1K9f3++2gwYNIiIigldffTWgQc9169b1eoxFrRblceKJJwKFZ2uFqmUy2G4sy7JKddndfvvt7Nmzh4ceeoh58+bRqVMnLr744nLXLdjnvjxatWpF3bp1vf64l6WopWTjxo2l1m3YsIH69et7tEaFQlGLm936+qpr0XoI/r3hS1GXWlFL9AknnECDBg28TmT77bffBhSaS+6zuGbNmrlb5g4fPszq1au57LLLvO7n9ddfxxijbr1qQGftiZQQERFR6q/gZ599tlTLTMmzE2vXrs1JJ50U0rMRvdXlrbfeYufOnWVum5qayujRo1myZAnPPvtsqfUul4snnniCP/74AygMO+np6fz000/uMrt373afDVUeAwYMICEhgYcffpj8/PxS60vOCh2I+Ph4AK/hz5v+/fvz22+/lRpn9cgjj3DaaaexdetWLrroIvcUCeUR7HMfiG+++YbMzMxSy7/99lsOHDjgtXuuLI0bN6Zjx47MmTPH43lct24dS5Ys4fzzzw96n0W+/PJLr6910bgrO/U9//zz+fbbb1m1apV7WWZmJi+++CItWrRwj9krCn+Bvjf27t1ball+fj6vvPIKcXFxHmMBL7vsMhYtWuQRypctW8b//vc/hg4d6l7m6z1dNCbvjDPO8FuniRMnUlBQwK233up1/WuvvUazZs38TkEhlUMtUlIuH330kfuvweJ69uxJq1atqqBG5XfBBRcwd+5cEhMTOe2001i1ahWffvppqTFJp512Gn379qVz584kJyfz/fff8/bbb5caVF/eutx///2MHDmSnj178vPPPzNv3ryAn9snnniCzZs3849//IN3332XCy64gLp167J9+3beeustNmzYwLBhwwAYNmwYd911F5dccgn/+Mc/yMrKYsaMGZxyyillDmwvS0JCAjNmzOCaa67hjDPOYNiwYTRo0IDt27fz4Ycf0qtXL5577rmg9ln0A/fGG29wyimnkJyczOmnn+5zjMzEiRNZuHAhw4cPZ+nSpfTs2ZOjR4/y+uuvs2XLFs4880wefPBBevTowXnnnVfm4y9btsw9Lqa4IUOGcPrppwf13Adi7ty5zJs3j0suuYTOnTsTHR3N+vXrefnll4mNjXVPbxCsxx9/nEGDBtGjRw9GjRpFdnY2zz77LImJieW6BuWjjz7K6tWrufTSS93jBn/44QdeeeUVkpOTvc6vVZYJEybw+uuvM2jQIP7xj3+QnJzMnDlz2LJlC++88447BJ944okkJSUxc+ZM6tSpQ61atejWrZvP8V3XX389GRkZ9O7dmxNOOIG0tDTmzZvHhg0beOKJJzzGKN1999289dZb9OvXj1tuuYWjR4/y+OOP065dO0aOHOku99BDD/HVV18xcOBAmjVrxsGDB3nnnXf47rvvuPnmmz2u/vDII4+4x+dFRkaycOFClixZwoMPPuieE6u4devW8dNPPzFhwoSQtb5JOVTlKYMSvvydrk2J046pRjObe0OJU+gPHTpkRo4caerXr29q165tBgwYYDZs2GCaN29uhg8f7i734IMPmq5du5qkpCQTFxdn2rRpYx566CGTl5fnLjN8+HBTq1atUo/Zp08f07Zt21LLS87wnJOTY2677TbTuHFjExcXZ3r16mVWrVpl+vTpE/DzUVBQYP7zn/+Ys88+2yQmJpqoqCjTvHlzM3LkyFKn5y9ZssScfvrpJjo62rRu3dq8+uqrPqc/8PaaljVD9/Lly82AAQNMYmKiiY2NNSeeeKIZMWKE+f77791lfD1n3uqxcuVK07lzZxMdHR3QVAj79+83Y8eONampqSYyMtI0atTIXHvttWbDhg0mIyPDtGnTxiQkJJiff/7Z5z6K3lu+bnPnznWXDfS5D2Rm859++snccccd5owzzjDJyckmMjLSNG7c2AwdOtT88MMPfo/bGN/THxhjzKeffmp69epl4uLiTEJCgrnwwgvNr7/+6lGmrM9oSV999ZW56aabzOmnn+4+9mbNmpkRI0aYzZs3e5T1NbO5t/f55s2bzeWXX26SkpJMbGys6dq1q1m0aFGpbd977z1z2mmnmcjIyDKnQnj99ddN//79TUpKiomMjDR169Y1/fv3N++9957X8uvWrTPnnXeeiY+PN0lJSeavf/2rSUtL8yizZMkSc8EFF5gmTZqYqKgoU6dOHdOrVy8za9YsjxnMjTFm0aJFpmvXrqZOnTomPj7edO/e3bz55ps+6zthwgQDmJ9++slnGak8ljFVOJJPREREJIxpjJSIiIiITQpSIiIiIjYpSImIiIjYFDZBasqUKZx55pnUqVOHhg0bMmTIEK/ziZT01ltv0aZNG2JjY2nXrp3XSx6IiIiI2BE2Qerzzz/npptu4uuvv2bp0qXk5+dz3nnneZ1XpcjKlSu56qqrGDVqFGvWrGHIkCEMGTKEdevWVWLNRUREpKYK27P29u3bR8OGDfn888/p3bu31zJXXnklmZmZLFq0yL2se/fudOzYkZkzZ1ZWVUVERKSGCtsJOYum1y9+xfKSVq1axfjx4z2WDRgwgIULF/rcJjc312NmapfLxcGDB6lXr54mPhMREQkTxhiOHDlCkyZNQnLFAl/CMki5XC7GjRtHr169/F7pOy0tjZSUFI9lKSkppKWl+dxmypQpTJ48OWR1FRERkaqzY8cOmjZtWmH7D8sgddNNN7Fu3Tr++9//hnzfEydO9GjFSk9PP3YRyVpqkRIREQkThSOXMqlTp06FPk7YBamxY8eyaNEivvjiizITZqNGjdizZ4/Hsj179tCoUSOf28TExBATE1NquWVZClIiIiJhxBgq/Lc7bM7aM8YwduxYFixYwGeffebz4pPF9ejRg2XLlnksW7p0KT169KioaoqIiMhxJGxapG666SZee+013nvvPerUqeMe55SYmEhcXBwA1157LSeccAJTpkwB4JZbbqFPnz488cQTDB48mPnz5/P999/z4osvVtlxiIiISM0RNi1SM2bMID09nb59+9K4cWP37Y033nCX2b59O7t373bf79mzJ6+99hovvvgiHTp04O2332bhwoV+B6iLiIiIBCps55GqLBkZGSQmJmJZtTVGSkREQiY+Po769TW1jh3GGPbvP0BWVrbfMsYcJT09nYSEhAqrS9h07YmIiNQElmUxYsRfueiiQURFRSlI2WCMIT8/n/ff/4jZs+dRlW1CClIiIiKVaMSIvzJs2OUkJSVWdVXC3rBhlwMwa9arVVaHsBkjJSIiEu5q1YrnoosGHQtRlm7lvCUlJXLRRYOIj48L+rUIFQUpERGRSlKvXjJRUVFVXY0aJSoqivr161XZ4ytIiYiIVBJN7hx6Vf2cKkiJiIiI2KQgJSIiImKTztoTERGRMt133ySOHj3C1KlPel2/ceMGZs16mTVr1nD06FFSUlI444zOXHPNtTRv3pxdu3Zx8cUXltpu4MBBPPDAgzidTubOfYVFiz4gLS2NmJgYUlNTGTLkEoYMuaSiD882BSkREREply+//IK77rqT7t17cP/9D9K0aVMOHTrIp59+ysyZM5gy5RF32enTZ9CqVSv3/djYGAD+/e8XWbDgXe64405OPfU0MjMzWb/+VzIyMir9eIKhICUiIiK25eRkc//9k+nVqxePP/6Ee/kJJ5zA6ae348iRIx7lExMTqV+/fqn9fPHFF1x++VD69z/XveyUU06puIqHiIKUiIhINeDI9nO5E4cDExMTWFnLwsTG+i3rigvdvEurVq3i8OHDXHPNcK/r69SpE9B+6tWrx3fffcfllw+lbt26IatfRVOQEhERqQbO6H2Wz3WHe/Vi01PPuO93OK8/ETk5XsseOaMzG1940X2/3UUXEHX4sEeZ779bXb7KFrNjxw4AWrRoEVD5UaNG4nD8ea7bv//9H1q3bsOtt45nwoQ7GTjwPFq1akX79h3o3bsPvXr1ClldK4KClIiIiNgW7HXuHn74EVq2bOm+n5KSAkCrVq2YP/9N1q9fz48//siaNT9w2223csEFF3DPPfeGtM6hpCAlIiJSDfzwxX99rjMOz9mKflzyqe+yJSan/Pn9ReWrWBmaNWsGwNatW2nfvn2Z5VNSUkhNTfW6zuFw0LZtW9q2bcvVV1/N4sWLmTTpX4wcOYoTTjghpPUOFc0jJSIiUg244uJ83oqPjyqzbLHxUb7KhlL37j1ISkpi7tw5XteXHGwejFatCluusv2MCatqapESERGRgBw9epSNGzd6LEtMTOSee/7FhAl3MX78rVx55TBSU1M5fPgwn366lLS0NB5+eEqZ+77rrjvp0KED7du3p169+uzatZPp05+jWbPmAY+/qgoKUiIiIhKQ1atX87e/Xe2x7OKLL+aee+7lpZdmMXv2LP71r3+SmZlJSkoKXbqcyQ033BjQvrt3786SJZ8we/Ysjh49Sr169ejS5UzGjLmeyMjqG1csE+woseNMRkYGiYmJWFZtXWhSRETKpXnzVJ5//slj8yjpN6X8DPv37+fGG8ezbdsOzzXGYMxR0tPTSUhIqLAaaIyUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiEglKRwArXO8Qqmqn1MFKRERkUpy4MBB8vPzq7oaNUp+fj779x+ossdXkBIREakkmZlZvP/+Rxw+nA4Y3cp5O3w4nfff/4isrKqb+bz6znAlIiJSA82ePQ+Aiy4aRFRUlOYotMEYQ35+Pu+//5H7+awqmpCzDJqQU0REKkJ8fBz169fTb4sNxhj27z/gtyWqsibkVIuUiIhIFcjKymb79j+quhpSThojJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNoVVkPriiy+48MILadKkCZZlsXDhQr/lV6xYgWVZpW5paWmVU2ERERGp0cIqSGVmZtKhQwemT58e1HYbN25k9+7d7lvDhg0rqIYiIiJyPAmrmc0HDRrEoEGDgt6uYcOGJCUlhb5CIiIiclwLqxYpuzp27Ejjxo0599xz+eqrr/yWzc3NJSMjw+MmIiIi4k2NDlKNGzdm5syZvPPOO7zzzjukpqbSt29ffvjhB5/bTJkyhcTERPctNTW1EmssIiIi4cQyxpiqroQdlmWxYMEChgwZEtR2ffr0oVmzZsydO9fr+tzcXHJzc933MzIySE1NxbJq6wrdIiIiYcIYgzFHSU9PJyEhocIeJ6zGSIVC165d+e9//+tzfUxMDDExMZVYIxEREQlXNbprz5u1a9fSuHHjqq6GiIiI1ABh1SJ19OhRNm3a5L6/ZcsW1q5dS3JyMs2aNWPixIns3LmTV155BYCnnnqKli1b0rZtW3JycvjPf/7DZ599xpIlS6rqEERERKQGCasg9f3339OvXz/3/fHjxwMwfPhwZs+eze7du9m+fbt7fV5eHrfddhs7d+4kPj6e9u3b8+mnn3rsQ0RERMSusB1sXlkyMjJITEzUYHMREZEwUlmDzY+7MVIiIiIioaIgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE1hFaS++OILLrzwQpo0aYJlWSxcuLDMbVasWMEZZ5xBTEwMJ510ErNnz67weoqIiMjxIayCVGZmJh06dGD69OkBld+yZQuDBw+mX79+rF27lnHjxnHdddfxySefVHBNRURE5HhgGWNMVVfCDsuyWLBgAUOGDPFZ5q677uLDDz9k3bp17mXDhg3j8OHDfPzxxwE9TkZGBomJiVhWbSzLKm+1RUREpBIYYzDmKOnp6SQkJFTY44RVi1SwVq1aRf/+/T2WDRgwgFWrVlVRjURERKQmiazqClSktLQ0UlJSPJalpKSQkZFBdnY2cXFxpbbJzc0lNzfXfT8jI6PC6ykiIiLhqUa3SNkxZcoUEhMT3bfU1NSqrpKIiIhUUzU6SDVq1Ig9e/Z4LNuzZw8JCQleW6MAJk6cSHp6uvu2Y8eOyqiqiIiIhKEa3bXXo0cPFi9e7LFs6dKl9OjRw+c2MTExxMTEVHTVREREpAYIqxapo0ePsnbtWtauXQsUTm+wdu1atm/fDhS2Jl177bXu8n//+9/5/fffufPOO9mwYQPPP/88b775JrfeemtVVF9ERERqmLAKUt9//z2dOnWiU6dOAIwfP55OnTpx7733ArB79253qAJo2bIlH374IUuXLqVDhw488cQT/Oc//2HAgAFVUn8RERGpWcJ2HqnKonmkREREwo/mkRIRERGp5hSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsSnsgtT06dNp0aIFsbGxdOvWjW+//dZn2dmzZ2NZlsctNja2EmsrIiIiNVlkVVcgGG+88Qbjx49n5syZdOvWjaeeeooBAwawceNGGjZs6HWbhIQENm7c6L5vWVZlVVcqmGUMyRhSMDQsdqtvDM9Y0Rw89lpfa/L5q8knHkMtIAZwYLAo/EviUiuOdVYEAH83edxu8sjFIgfIBXKwyDv2/3usGH4+VradcdIbJ+lYHMbiMHAIiz1YHMDC6L0mIlLjhVWQevLJJxk9ejQjR44EYObMmXz44Ye8/PLLTJgwwes2lmXRqFGjyqymhIoxNMZwEi5OwvAakeQeCycPuHK5kzyfb+A3ieQghYGnOS764/T5MMXbKOtgaIkBjNeyjxdb3hsnz5hcr+XygUuI4yOrsIZdjJMLTQG7LYutONhC4b+5ClsiImEtbIJUXl4eq1evZuLEie5lDoeD/v37s2rVKp/bHT16lObNm+NyuTjjjDN4+OGHadu2bWVUWYLUyTgZQAEdjYtTcHESLmoVW/+NFc+vx8JRlgWRxzLNQWAPDvZgse/YLYM/A8p7RPK75SATyDzW0uQCXFgYYH2xHu5XiOJzK5JYDDEUtl4V/T8Ww/+Kld2CgzeJJAlDIoYkDPWA+hiiKGydKtIDJ/eQVyqf7TIWW7C4w4rlm2MtXYnGEI1hHxYoaImIVGthE6T279+P0+kkJSXFY3lKSgobNmzwuk3r1q15+eWXad++Penp6UydOpWePXvyyy+/0LRpU6/b5Obmkpv7ZytDRkZG6A5CwBhOwtAdJ+2Nk6etaHZaheFkEAU8YPI8ijuBrVhsxnEsQhV6gWjmWFHswyK/jLDxkxXBTx5b+7bHcrAnwENZbEWy2Cr9EYo0hd2N+4sFqXU4eJ4ommJogYuWuKgDNMHQBIOr2PbXkM/TJpcM4Hfj4HccbMZis+VgAw5WE0GWApaISLUQNkHKjh49etCjRw/3/Z49e3Lqqafywgsv8MADD3jdZsqUKUyePLmyqnhcSDUu+uGknymgH05SizXLrCSCncdaef5LBK8RyVorgvU4+A0HW30EpcLxT9UzTBRYFjtL1G25Fcny4qHLGOod60ZsgcujVayBKXx+EoCOuOhYFLOOPW1nW3GsPPbR7W6cnI6TdUTwCw6OKGCJiFSqsAlS9evXJyIigj17PNsL9uzZE/AYqKioKDp16sSmTZt8lpk4cSLjx49338/IyCA1NdVepYWhJp/5JsdjWS7wHRGsxcH2YgHiCyuSL7y08AQrPqZxufdRkbJyd4NVOCD9APB9idaySY4YHjbRtMRFKwytcHGicXEyLk7FxS/Fyl9h8rmFfPf9jcbieyL41orgOyJYjYMChSsRkQoTNkEqOjqazp07s2zZMoYMGQKAy+Vi2bJljB07NqB9OJ1Ofv75Z84//3yfZWJiYoiJiQlFlY8rEcZwHk6uMfkstiJ51YoC4BsiKAC+w8FyIlluRbCSCHLK8eNe3YNSWQKt/4bc3bg7rX08XRssB0tMBKfhoimG1hhaU8BfTQEATa1a7D628WnGSRYWW62wm/VERKTaCpsgBTB+/HiGDx9Oly5d6Nq1K0899RSZmZnus/iuvfZaTjjhBKZMmQLA/fffT/fu3TnppJM4fPgwjz/+ONu2beO6666rysOoOYyhIy6uMflcRQEpx/qeGhnjDlLbLQf1qM1RG8Ep3ANTeZV1/Fm5u3nRiuZFKxqAesZFF1x0wUlX4+QEDLuLhaaHTS4X4mSrsficCFZYkSwngh0KViIitoVVkLryyivZt28f9957L2lpaXTs2JGPP/7YPQB9+/btOBx//igcOnSI0aNHk5aWRt26dencuTMrV67ktNNOq6pDqBEcxjCOfK41+bQrNkx6Lxav82drVJFAQ1RlBqeEGO8nG1S0jNw/Qravks9XNvBJ7m4+IdJrC1YEhdMytMDQggKGH2u12mwsFhPJOIcmqxURCZZljPE+YY4AhWOkEhMTsazamsyzmGWuLPriJAf4gEjmWlF8QkRQ43EqIjhVVUCqCKEIXVm5uz3u1zKGXjjpY5z0pYAuuIgEVhDBOY54d7m7TC4bcbCCSA7rfS8iYcgYgzFHSU9PJyEhocIeR0GqDApS0Mq4uNXkMdmKZv+xbqBepoC2uHiTqIB/aEMVnGpSWCoPu0GreLiqbQxn4cQAnxwb6J9sDHvMURwUTj/xAw4+I5LFx8a3uY7Tz4GIhBcFqWrieA5S7Y2Tu0weQykgAniAaO5zBDcQv7zhqaJCU7JVfc7EPGh2hHR/dgJW8XDV2LiYaPL4C05O9ZjhCvZgcb8Vzcxj47JERKqrygpSYTVGSirHycbFVJPDBcUuq/IREe4Wi7KUJzyFIjhVp5AUiEDrG2jg8vYclhWuir9m6cA/jgWrJsbFOTg51xRw/rETCrKLDcA6wbg4CyeLidQcViJyXFKLVBmOqxYpY3jA5HE7eURT2K3zFpE8ZkXzo1X2zOB2AlR5g1NlhKb6rgbl3sd+x74Q1MQ3O61awbZc5eXsoi9OvifC3Z17q8ljqsklF1h0bKzcR0GOlRMRqQhqkZLKZ1mkGEM0hS1Qt1qx/FbGqfGVGZ5CFZpCEYwq4zGDCV/enpuywlXJ16GsYBUd24SVeHYDHgE2YtEaw2UUcJkpYB8Wb5hIXrei+BqHrhcoIjWaWqTKUNNbpGKNIQ44dOzY6hsXPXDxARF+fwCDDVB2wpPd4FQVQakq2GnlCqblKpAWq6JQ1d4UTsZ6NQU0OjafWA7QyKqtLj8RqRIabF5N1OQg1d44mWty2I7FhVZcQC0HwQSoYMOTneAUitDUMCqu3PsItb352eXaPpiQFWi4KitYZeXuJsIYzsXJVSafAmCU48/n9klXDqusCBYSWeaFpkVEyktBqpqokUHKGMaSz2MmlxggDYseVjzbQ9SNF0yACiY82Q1N1TEolZedoBVouAokWAXTWgXQzjhZa7IA2I3Ff4ji31YUOzWruohUEAWpaqKmBaloY5hhchhB4azWHxDBaCuWfX5+0EIdoCoyPJU3NCXHVv2wwYM5BeXaPtCQFapgFUioqp2zkxtMPqPJp/Gxrj8nhZO5zrCiWEYEpgZ8vkSk+lCQqiZqUpBKMS7eNtn0xIUTuMOK4WmifHbpVUWACiY42QlN1SEolZedoBWqcFXeUJWXs4shFPB3k0+/YtNrXGXF8maJSwuJiJSHglQ1UVOClGUMP5gs2uPiEHCVFcdSH/NChTJABdr6FEiACjY4lTc01Yup/Nf7QG75Po6BhqxAglVFhqqs3N2capz83eTTFyddrHj3uKk2xsnvOMgL48+biFQ9BalqoqYEKYAOxslTJpfRViybfHTlBRKiQhWgQhmegg1NVRGSQiXYsBVIuCpvsPIXqsoKVJYx7m69SGNYbzKJBh63ovkPUeSE+edORKqGglQ1EfZBypiA5/EJRYgKRYAKJDwFGpzKE5jqxVTNR+NArr06BxqwQhGsQh2qigamn2JcLDFZpB4bR5WGxVQrmplEkR2Onz8RqTIKUtVEOAepRGN422QzyYpmZRmXdykrRJU3QFVWeAomOFVVUCqvYIJWIOGqrGBlN1TZDVTRxjCCfO4yebQ4Fqj+wOIeK4ZXidSgdBEJiIJUNRGuQSreGD42WfTCxe9YnGrV8nrZjopuhSpvgCorPAUanOyEpnrRzrILVZADeWVfkqfUNgEGrLLClb9g5S9U2Wml8heoIo3hGgr4p8ml5bFA1ceK478BXvNRRI5vClLVRDgGqUhjeM9kMxAnh4C/WPH85OVaeRXZClWeAFXe8BRMaKrKsFQegQatQMKVv2AV6lBlJ1DFGMPN5NHJuPhrsQk+440hK0w+kyJS+RSkqolwDFJPuHIYRz6ZwLlWPN+EOESVpxvPboAKRXgKNjQ1jMkPqnyo7c0NbjqAQMJVWcEq1KEqlIGquIbGxY8mi6etKKYSrYski0gpClLVRLgFqf6mgE9M4Y/aJVYs73uZm6eiQlSoA1R5w1MgwSmUYaleTK7PdQdyY0L2OBB4yCorXPkLVnZCVWUFqltMHk+awuf7JxyMtGJZ6+UPBhE5filIVRPhFKSSjWGtyeQEDNOJ4h+O2FJlKjtE+QpQdluf/IWnsoJTsKHJXzCqLMEEsEDClb9gZSdUVUWgysrdDcbwVwp40uRSH0MecLcVw1NEaTC6iAAKUtVGOAWpRGOYbnLoiIszrXivp4v7C1J2QlSwAQqCb4Gq6PBUnsCUHG/v4sIHs8p3KZtAAlZZwcpOqApVK1WoAlV94+JFk8vFxy559CkRjLRi2aVr+Ikc9xSkqolwClJFkozhcDUMUaEKUP7CU1nBKdDQZDcghVowgauscOUvWIUyVFVUoPLZ3Zezi9Hk86TJJR54lijGeWmNFZHji4JUNREOQaqOMRwBvxNv2glR4RKg/IWnQIKTndCUmBiaoJWebq9lKpCAZTdY+QpVlR2ogm2dam2cTDZ5jLJiyaymn1URqTxhE6Ryc3OJiQntQNrqJByC1FuubCKAMVYM+710aVS3EFXRAcpfeAo0NIUqKIVCoGGrrHDlK1jZaanyFqqCCVTBjKEKqnWq+Nl9xnAnefyHaA5W08+uiFScahukPvroI+bPn8+XX37Jjh07cLlc1KpVi06dOnHeeecxcuRImjRpUlH1rXTVPUi1MU5+MVm4gPZWPOtLnLkUziGqMgNUsMEpvn5gFwcORNb+4CeYLCtchTpUVWagClWYusfkMtnksR4HA6w4dmrclMhxpdoFqQULFnDXXXdx5MgRzj//fLp27UqTJk2Ii4vj4MGDrFu3ji+//JJVq1YxYsQIHnjgARo0KPuitNVddQ9SL7myGUEBC4jkckfpH09fQSrYMVHBhKhguvIqMkD5C0+BBKdQhiW7Ag1ZdoNVKAJVMF1+5QlTEHigysrdzWnGyWKTTSqG37Hob8WzTWFK5LhR7YJUjx49uOeeexg0aBAOh+8vo507d/Lss8+SkpLCrbfeGrKKVpXqHKRSjYvfTCZRQHcrnu8quTWqskKUtwAV6vBkJzRFNQzNvEX5e4OfXb2sgOUvWAUTqsobqKqydSordzfNjIulJouTMOw4FqY2KUyJHBeqXZA6XlXnIPWkK4dbyGcZEZzniC+1PtjWqIoIUVUdoMobnkIVluwKJGTZDVVVHagqK0w1Ni6WmmxOxcVuLM614kp1gYtIzaMgVU1U1yBVz7jYYjKpBZxnxbGsxIVcj5cQ5S1A+QpPZQWnYENTRONaQZX3xrk7M+htygpX/oKVt1AVroEqmDDVwLj4xGTTARe7sGht1dJ1+kRquGodpIwxvP322yxfvpy9e/ficrk81r/77rshq2BVq65B6laTx1STy2ocdLXiPaY+CLZLrzqFqMoOUIGEp1AEJjsCCVn+QlVlB6rqHqbqGsMik8UzVjRveLl0kojULJUVpII/XQgYN24cL7zwAv369SMlJaVaBYzjxRyiyLFgF5bf+aOK8zfAvCR/180rrjqHKF8BqqzwZDc4WQ0D+6CavRkBlStZD2/BqvixlAxVxY+/ZKhKTMwuFaaKnteSgapeTG6pMNUwJr9UmKoX7SwVpurFmFJhql6MVSpMJcdGlgpTDaPifE6T4N7OSi0VphJimpYKU/ExjTmUu5uzicel7ysRCSFbLVLJycm8+uqrnH/++RVRp2qlurZI+RNMt15ltEaFKkRVZIAKNDwFGpbsCjRk+WutCraVqjytU1XRMmV3zJTHHFNAQ+OiOabUSRoiUjNUVouUrdNXEhMTadWqVajrIiFgZ7qDkmpaiIpqGOEzREU0ruU3RFkNEzxuFS3Qxyuqt7e6+zteb89PYmJ2qecyOT7b63Ne8nVpGJNf6vXzNubN6/vAS8ult/dUyfeet/envwtqFyn+2WhvnPxoslhgsqlnXH62EhHxz1aL1Jw5c/j44495+eWXiYsr38VXq7vq1iIVaQzvmGw+tCKZQxS5JepUWa1RFRWiAunKK28rVFnBKSgNk4MrX9Leg0EV99di5auVylcLVXlap+yOm7LbMmX3bD5f46VijeE7k8VpuHiXSIZasQF3kYtIeKjWg82zs7O55JJL+Oqrr2jRogVRUZ5foD/88EPIKljVqluQOt8U8IHJZi8WqVYtCgIYZB7MmXp2W6MCGRdVmSEq5AGqvIEpWAEErGBDVagDVXUMU8F08XU0TlaZLKKBq61YDUAXqWGq9WDz4cOHs3r1av72t79psHklG2gKf1zeJtIjRAUrkK4QCG7SzeLKClGBqIwQVe0CVMnH9ROorIYJPsNURONapcJU0fPibVB6oIPRi4epQAehlxToAPSS7A4+Lyk+pjFZubtZa0UwxUQziTxuMXkKUiJii60g9eGHH/LJJ59w1llnhbo+UoazKPwRXFEBA2QDPVOvJF/Xz/OnrNaoQC4uXKEhykaAMg3rB1TO2rs/8J2WEaiKjsFboPIWpnzxFqYC4S1MlSoT4Nl8JXk7k6+k+q4GPi8nU8TbWXxFZlpR/NPk0Q0XrY2TjRp4LiJBsjXYPDU1tUKbyfyZPn06LVq0IDY2lm7duvHtt9/6Lf/WW2/Rpk0bYmNjadeuHYsXL66kmoZeXWNoR+HA2C8J7As/mEHmgais1qiSSrZGlSdE+R3I3TA54BBlGtb3uAXK1nZl1MvX8fgajB4Iby2AgQRcrycPBPAeCCSQ+7pAdnHBDDzfazn4+Nhn6RpT9ddWFJHwYytIPfHEE9x5551s3bo1xNXx74033mD8+PFMmjSJH374gQ4dOjBgwAD27t3rtfzKlSu56qqrGDVqFGvWrGHIkCEMGTKEdevWVWq9Q6UXThzABhzsLXG9MH+TcJZUnm69kiqjNSqQCwwHE6J8V8x/gLIbnMoS1H79BKryhilfZ/SVVPL18Ta2zdcFpj23K3t4ZiDBPZCWVH9/UMy1osgCYtBFHkQkeLYGm9etW5esrCwKCgqIj48vNdj84MHgzkQKVLdu3TjzzDN57rnnAHC5XKSmpnLzzTczYcKEUuWvvPJKMjMzWbRokXtZ9+7d6dixIzNnzgzoMavTYPNHXTncTj7/Joq/O2I91pX3bL1QDTIPpDWqvEGq5A9+uUNUAAGqKpTZBehn/JS3rr5AB6AHMvg8kDP5QjXwPFRzS/kadB5lDLHAEY31FKlRqvVg86eeeirE1ShbXl4eq1evZuLEie5lDoeD/v37s2rVKq/brFq1ivHjx3ssGzBgAAsXLvT5OLm5ueTm/vnDnpER2ASJleG0om69KhrHEUjrQFlCHaK8CVWIqqoAVfLxfQaqhsl+x06VDFO+BqAHMvi8pJIDz71Wz+bA81KPFaKxUiUVDTrPtyzKbj8TEfHO9ll7lW3//v04nU5SUlI8lqekpLBhwwav26SlpXktn5aW5vNxpkyZwuTJk8tf4Qpw5rEg9b8Ae2RDPT5KqiE/YUo8+Rt0LiJiV8BjpDIzg7tKfbDlq4uJEyeSnp7uvu3Y4f9U6soSZQwNjo3h+B11QRQJdOC0lE8g49S8jZUKF+eZAg64jrDClVXVVRGRMBNwkDrppJN45JFH2L17t88yxhiWLl3KoEGDeOaZZ0JSwSL169cnIiKCPXv2eCzfs2cPjRo18rpNo0aNgioPEBMTQ0JCgsetOkg5FqLygAPVJEjZGWguUh05gSQgUQPORSRIAXftrVixgrvvvpv77ruPDh060KVLF5o0aUJsbCyHDh3i119/ZdWqVURGRjJx4kSuv/76kFY0Ojqazp07s2zZMoYMGQIUDjZftmwZY8eO9bpNjx49WLZsGePGjXMvW7p0KT169Ahp3SpDk2Nf8LuxSl3KIpgz9qSYCphs0zRs6HW55ePM0uONtzmlqoOsY3+cxCtIiUiQAg5SrVu35p133mH79u289dZbfPnll6xcuZLs7Gzq169Pp06d+Pe//82gQYOIiKiYL8rx48czfPhwunTpQteuXXnqqafIzMxk5MiRAFx77bWccMIJTJkyBYBbbrmFPn368MQTTzB48GDmz5/P999/z4svvlgh9atI3+KgnlWbpHJ+0Ydy6oOazM5Ac18hquS6YEOVaVg/uEk8JWhFHXrxVVoLEQlHQQ82b9asGbfddhu33XZbRdTHryuvvJJ9+/Zx7733kpaWRseOHfn444/dA8q3b9+Ow/Fnb2XPnj157bXXuOeee7j77rs5+eSTWbhwIaeffnql173cLIvDwOFq0q3nTSDzAknVCma286oSyOViQs117N9YtUiJSJDKfz57JRs7dqzPrrwVK1aUWjZ06FCGDh1awbUSKJwTKKzC1N6Dvie33Ls/6Fapiuq+C2VrVFWHqEC69So7REHhZLcAPwd4xQARkSK2ZjaXyneicfGUK4cHXeU7M6qsC7oWKevisFA1P3gl5zfyNqGkt7Dg6+K+fi8KXMXdadbe/bYn5fR5vCXYnZDTm7Kuued9m7JbWMuaQwq8T8hZkr+pD84/dnmYj3WtPREJkoJUmKiH4WbyudrL1IFFMzSHg5ITNJb88S05yWMgP+DewkBwlfIfpqoiUAUUoIIMUXZbo7y9BmVNxgneZzavTop/bj6zIvkvEXwUfo30IlLFFKTCxP5jY6PqBzGGI9STDwbSMlCyhaEiztAqa9ZtCLJVCsqc1LKyAlV5WqEguBAVaGtUSYFcHsabUHXrBdJaGmjLa5GnrGj6OOL5WS1SIhIkBakwURSkagGxwV8eMayEqlUq1GEK/gw6oQxVQe2zkkOU3S69QFqjqku3nohIeQQVpM455xzeffddn+v3799Pq1atyl0pKS0DyDn2/2YVcGaRtx+jihonVVb3XiACaTmBiglTRcoTqoLe1k9XHoS+O8+XQLr0vKnM1qhAFHXr1TWGf5lc4mv4HyciUnGCClLLly/niiuuYNKkSV7XO51Otm3bFpKKSQmWxffHzigqOsPIrmC7PTy2raTuvUBapQIZeA6+w5TfAehlBJeSigejQG4BCyBABdsSZbc1KtAuvVJB2cvrX5GtUcG8vx80udxn8njThCagicjxJ+iuvRkzZvDUU09xySWXhO319MLVf48FqbNM2T8wlSmQloSSP6aBtErZDVOBdvNBGYEKbIWqcin+eOUIUMF055V8DtPT4yo9RJV8D3kLUXbHRpXs1itqjepinIw5dvLGo1Z0mfsWEfEm6CB18cUX8/XXX/PLL7/QvXt3fv/994qol3jx32MDYb117fk6cy+YsSGBdu/ZaZXypqLCFHgPVL4CBgQQqKB0yClPyLKxn6I62glQ5RkTVdkhyhtv78PyjI2KMIYZJgcHMI9IvrR0tp6I2GMZE/jgAIfDQVpaGg0bNiQ9PZ2rrrqKb775hjfeeIP+/fuzZ88emjRpgtNZztPRq5GMjAwSExOxrNpYVtXOKh5rDPUw7LS8519f19xLiGnqdbm3y8XUdzUotczb5WKSY0v/8Hi7iHHJCTrrRZd+bzSM8ZzSoV5M6bmykuNL/5AmJpZeFl+/dMiLaui7azGicS2f6wCshlV30epA5oLyNwbKV1enr/Fl1SVElQzqgYaokq1R3kJU0R8cY00eT5tcDgGnWbXY6+MzJSLhyxiDMUdJT08nIaHivsttf3skJiby4YcfMnr0aM4//3ymTZsWynqJFzmW5TNEhUp5WqXsdPGBvZYpKF/rVBF/rVTg2QoU6CSX5RHoY/mrt78WKF+tUN668ko+5wdyY0q9Nntzoyo0RHlT3nFRLYyLB0xhWP+nFaMQJSLlElSLVEREBLt376ZhiYuzzp8/n+uuu45+/fqxePFitUhVggRjyPBSn8pslYLSLVOBtEpBxbdMgffWKShfC5U/gbZe2Q1kZZ2B529i0mCmNrDbCgWhD1GBtEYFMi4K/myNet+VxWCcfI2Ds6x4TDX6XItI6FRWi5Ttrr2S1q5dy5AhQ9ixY4eCVAWKMoZXTA4XUkBrq1apFqpQBCmo+C4+CCxMFW5bMYEK/IeqIuUJV3YFOm1BsOEJyh+gIHxDFEAD42KmyeVmK4Zdao0SqbGqZZD6/PPP6dWrF5GR3r+gDxw4wIcffsi1114bsgpWteoWpAA+c2XRBycPEM19Ds8fOl9BCmpemILQBSoILFR5Yydo2Z3fqazL4fibX6smBSgILkRZxqjlSeQ4Uy2D1PGoOgapK0w+r5scdmPR0qpFfol6hSpMeQtSEHiYgqoNVOA7VEHZwQrsh6tQCPQagnbCE/ieXLM83XiF21evEBVnDB+YbOZZUcyyqvf1/0QkdBSkqonqGKSijGGLyaQxhmFWLG+V+HGo6FYpqNowVbh96AIVBBaqSgpFyLJzweWyZnUPVXgC35d6Ke/UBpUVoqKNYaHJZgBODgGtrVocUHeeyHFBQaqaqI5BCmCSK5d7yeNLIuhrxUEFtUpB5YYpqNhABWWHqiJ2wlWoBXopnLKuiVeRAapwP+U7K68iQlSSMbxqshmEk0xgoBXHSs0XJXLcUJCqJqprkDrBuPjNZBIDDLLiWOLlByLYgedQvcMUBB+owH+ogsCDVZFQB6xAw1JxgVxM2N918So7QEH5WqEguBDVyTh502TTCkMOcLEVx6cKUSLHFQWpaqK6BimAx105jCefpUQw0BFfar2dVikITZiCwAehFy6v+EAFZYeqIsGGq4oUSGiCsi8oHGx4gsoNUFD+ViiAkSaf50wOscDvWFxhxbHGqrqxbiJSNRSkqonqHKTqGsPfyeMZosn0UbfqGKYgdIEKfIeqwv2FJliVFKqgFWhIKqms0AS+gxOELjwVLg88QEHFtUIVudHk8azJ5X0iGWnFcriafW5FpHIoSFUT1TlIBaqywhRU30BVuE//oaqI3XBVEQIJTEX8BSewF54K91t9AxR4md7AGC6igA+I1JQHIscxBalqIlyClGUMrXGxwUsXhr8gBZUXpiB0gQr8hyooO1gV7j+wcOVNeQNXMCGppLJCE/gPTmAvPBWuK3+AguAu9eKvFeoSk89Ek0d/K97rbP8icnxSkKomwiFIpRgX75ls2uCimxXPxkoKUxB8Vx/4DlPgO1AVrqvYUPXn49gPV6EWSGAqrrLDE4QmQEHwrVCNjIvHTC5/pfDxvU1QKyLHLwWpaiIcgpRlDMtMNn1wsgEHPXz8ZV7ZYQoqP1BB2aGqSDDhynddgg9dwYYjb8oKTO7H8hOcCusS2vAEoQlQ4LsVKtIYbiKf+0wuCYALeJIo/mnFUFBNP6MiUvkUpKqJcAhSAA2Ni29NFqkYPiSCIVYcrkoMU1AxgQrKF6og8GBVJBQBKxQCDUvFlRWcwH54guBbnyA0AQoKQ9TZpoBnTS7tcAHwDQ5utmJZrbPyRKQEBalqIlyCFMAZxskXJos4YArR3OOjm6M8YQrst06B/0AF9lup/iwT2Ns52HBVlrLCl51Q5E8ggcld1k9wKlxvLzxB8K1PYC9AFfmPK5uRFLAfi7utaF4mSgPKRcQrBalqIpyCFMDVJp+5JgfA6+VjilRkmIKKDVQQWKgqLBfc2zvUAas8gglL7m3KCE2FZewHJ7DX+gT2AlSUMdQBDh777DUwLiaaPB6wYjgUBp9HEak6ClLVRLgFKYDHXDncRj67sDjZqkWOjTmmilR1oIKyQxUEHqwKy4b/Wz6QwPRn2bKPt7LDE/gPUBHG8DcK+JfJ5RccXOxlwlkREX8UpKqJcAxSEcbwtMnlGSua/5VxgdZQhCkof6CC0IUqCC5YeW5XPT4OwQQlz+0Cq39ZwQnshyewH6AijwWou00uJ1J4LLuw6GrFs1sXGxaRIChIVRPhGKS8STbG3T1SUiBhCkITqCB0oQoCD1ZgP1xVR4EGpiLlDU5FQt36BH8GqGspnA+q1bEAtReLqVY0zxNFdhh/9kSkaihIVRM1IUj1MwUsMNmMsWJ508eYKQhd6xSELlBB4KEKggtWxVXHkBVsWCoSSGiC8gcn8B+eoOwAVWSEyeelY2P79hwLUDOJIitMP3MiUvUUpKqJmhCkXnDlcB35uICbrRhmWtE+y4aydQoCC1RQMaHKXQeb4SpYxcOY3RAUjEADU5FAghNUTnhqZVw0xcUXVuFrE20MX5gs5ltRvKAWKBEJAQWpaqImBCnHsTFTN1J4iv4kK5oHiQY/x1NVgQoCD1VF7ISrIpUVsuwKNiwVCTQ0QdnBCcoXnuDP6+ENwMlNJo+BOPkdizZWLY9r5Pl7T4qIBKOyglT1/hWRkHBZFjcTwz5jMYk8Jps8UjCMJ4Z8Hz9cWbm7AwpTRT+gZQWq4j/EZYWqkj/sZQUrb6Eh0HAVbFCxE7zshqFABBOYigQSnCA04Qkg0RhuIZ8bTR4n8effbZtwkIzhAMfegwpRIhKG1CJVhprQIlXcjSaPZ03hZU2+xUFfK57cMo4r0NYpCLyFqkgwLVVFgm2xKq48rVdVxU5YKhJoaIKygxOUHZ7Ac+zTaJPHNJNL0bN+GJhFFDOtaDbpLDwRqUBqkZIK8bwVzQ4cvGyy+QVHmSEK/vxhDKaFCgILVcG0VBUJtsWquGBCSUWGrvKEI2+CCUxFAglOEFh4gsL3yYnGRR6w41hI2oCDOOBnHDxvRfGqBpCLSA0TNi1SBw8e5Oabb+aDDz7A4XBw2WWX8fTTT1O7dm2f2/Tt25fPP//cY9n111/PzJkzA37cmtYiVaSxcZGL5Z4SoblxcQZOFhBZZhdLMC1UEHwrVRE7rVXFlaflqrqyE5gg8NAEwQUngCRjuIQChpt8zsbJc0RxiyO2sJAxdMLFGhzquhORSqUWqRL++te/snv3bpYuXUp+fj4jR45kzJgxvPbaa363Gz16NPfff7/7fny8ZkgGPCc3NIZnTQ6DcfIhEfyDWLb66XYJpoUKgm+lKlLyxz/YYFVW6KhuQctuSCopmNBUJNjwdIJxMZwChpgC+uCkaFINJ1C32DgoLIs16ILCIlJzhUWQWr9+PR9//DHfffcdXbp0AeDZZ5/l/PPPZ+rUqTRp0sTntvHx8TRq1KiyqhqWHMAPRHAuTgbjpJ/J5EGieZJon4PRIfhABaV/sMsTrKB8rVahCi5VxU5ggsBDE3iOd3IzhuUmyz3zOMA6HMyzInmVKHZp7JOIHEfComvv5Zdf5rbbbuPQoUPuZQUFBcTGxvLWW29xySWXeN2ub9++/PLLLxhjaNSoERdeeCH/+te//LZK5ebmkpub676fkZFBampqjeva86a1cfKcyeUvFF64dxMWT1jRvEKUz+v1lRRst19xdrsAfSlv12BVsxuUigsmNBUpCk+RxtALJ4NNAWfj5GwrnoJj74PHXDl0w8V7ViTvE6mB4yJS7ahrr5i0tDQaNmzosSwyMpLk5GTS0tJ8bnf11VfTvHlzmjRpwk8//cRdd93Fxo0beffdd31uM2XKFCZPnhyyuoeTjVYE5xLH1RQw1eRyEoYZJhenBS/hexLP4uy0UhXx9qNfnnAVbBCp6OAVimDkT3lCU5HkY+OdBpsCBlBAUrF1vXHy2bGvjDutGI15EhGhioPUhAkTePTRR/2WWb9+ve39jxkzxv3/du3a0bhxY8455xw2b97MiSee6HWbiRMnMn78ePf9ohap44Zl8RpRvEckI8nnapPPPP68rEwP42QXFtvKaIEo+QNtt6Uq1OHKn4oOOqFiJzAV57W7Dhhp8nnB5HiMaNqHxWIiWGxF8k3xNQpRIiJAFQep2267jREjRvgt06pVKxo1asTevXs9lhcUFHDw4MGgxj9169YNgE2bNvkMUjExMcTExAS8z5oq07J4jmieK3Y5GcsYXjLZnIjhbRPJf6woviACZxBTKED5uv/Ad5CoqIBVFcobloor/txHG8PZOOmNk97GyUtWlPv6i2twEAH8iIMPieRDK5JvceBSaBIR8alKg1SDBg1o0KDsM6d69OjB4cOHWb16NZ07dwbgs88+w+VyucNRINauXQtA48bl+yE/XiVj2IaD1jgZRgHDTAH7sHjPRPKuFclnRPgdnF4kVK1VJQUaPqoqcIUyHHnjraUp1hiGUMAZxkVPnHTHSfHZsXYYyx2k1uKghVXLPQeUiIiULSwGmwMMGjSIPXv2MHPmTPf0B126dHFPf7Bz507OOeccXnnlFbp27crmzZt57bXXOP/886lXrx4//fQTt956K02bNi01t5Q/NXUeqfLoYJzcZPIZQj71ii1/lijGFc0fVA6hClY1la+uuRTj4kxc5ACfHrsYcJIxHDBHPcrtweILIvjcimAZkfxPwUlEaiANNi9h3rx5jB07lnPOOcc9IeczzzzjXp+fn8/GjRvJysoCIDo6mk8//ZSnnnqKzMxMUlNTueyyy7jnnnuq6hBqjB+tCMZYEdxoYuiDk0tNAUMoYJH159uptyngLpPHsmMtVT/i+PPitGXwFRTg+AlZ/p4DgAbGRWcKJ1HtfGwy1WbHpiNYRoQ7SB22LBaZCPbg4HvLwedEsFGTY4qIhEzYtEhVFbVIBcZx7G1UNJ7mIVcuE8hzrz8ArCCSz6wIPiOS/2FVyI95dQ9aZQWkkqKM4WRc1MPwZVFQNYY9JpP6eH50XcCvOFhOREhaBkVEwplapCSslByQPMeKYi8W55gCeuOkHnAZBVxmCoBcOljxrDt2Flhb48RB4XXZAhlj5U+wQaWkQIJYeR/Dlw7GSXtctDEuTsVFG5yciCES2IFFC+vY5ZAsi9XGQTMMa3Cw2orgBxysIYIjCvsiIpVKLVJlUItU+UUaQxdc/IUC+hknJ+GilVXL3dX3uiubKyggH1iPg59wsNFysAMH27D4koiAuwWro1rGkIKhES5OwNACFy2MIQHDNY4/h35/6sqi37HJUIvLoLClqU+xCTEdxuhsOhERP9QiJTVGgWXxNRF8TQQPW4UhoHgwygUOA0lAe1y0x0VRr1U2UNv688LUD7hyaYWLvccuuHwAi0NYHKTw/99bxeY6MqZCug+bGhcpGJKK3RIpHNgdi+HOYt1q77uyGOwlHBUZZQx5x+q4GgcWhWFyveVgAw7W42CXl25QhSgRkepBQUoqXckQMMIRB8bQDEN7XLTDyYnGRSoGF3iEiAEU0LlwKSWGCJEOJFt13PeXmmx6GSfZQA4WOcf+zQcygV6OWu6yM1w59MKJBURhiAVigTgMFpDg+HO/M00Og/yEo3+aGHcX5SEK/80E0rDYdayVbSsOtlkWxc+Xu0vjmkREwo6ClFQPlsV2LLbjYBGR4KPBZbIVwym4qGcMyRjqYahL4f+zSpSNxRADFE6vWpS6Cv89UqJsc1y0LQpo3qpXrBVtFw524OLwsdawdOAwlvsWBeQf2+5WK5YbKZzgVEREah6NkSqDxkiFr7rGUAtDHIWhKvbYv9FAAfB5seka2hsndY+FrHwKW66Kt2TtrqCzDEVEpGJojJRIOR2yLHfXWll+Kj62SkREJECa0lhERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsSlsgtRDDz1Ez549iY+PJykpKaBtjDHce++9NG7cmLi4OPr3789vv/1WsRUVERGR40bYBKm8vDyGDh3KDTfcEPA2jz32GM888wwzZ87km2++oVatWgwYMICcnJwKrKmIiIgcLyxjjKnqSgRj9uzZjBs3jsOHD/stZ4yhSZMm3Hbbbdx+++0ApKenk5KSwuzZsxk2bFhAj5eRkUFiYiKWVRvLsspbfREREakExhiMOUp6ejoJCQkV9jhh0yIVrC1btpCWlkb//v3dyxITE+nWrRurVq3yuV1ubi4ZGRkeNxERERFvamyQSktLAyAlJcVjeUpKinudN1OmTCExMdF9S01NrdB6ioiISPiq0iA1YcIELMvye9uwYUOl1mnixImkp6e7bzt27KjUxxcREZHwEVmVD37bbbcxYsQIv2VatWpla9+NGjUCYM+ePTRu3Ni9fM+ePXTs2NHndjExMcTExNh6TBERETm+VGmQatCgAQ0aNKiQfbds2ZJGjRqxbNkyd3DKyMjgm2++CerMPxERERFfwmaM1Pbt21m7di3bt2/H6XSydu1a1q5dy9GjR91l2rRpw4IFCwCwLItx48bx4IMP8v777/Pzzz9z7bXX0qRJE4YMGVJFRyEiIiI1SZW2SAXj3nvvZc6cOe77nTp1AmD58uX07dsXgI0bN5Kenu4uc+edd5KZmcmYMWM4fPgwZ511Fh9//DGxsbGVWncRERGpmcJuHqnKpnmkREREwo/mkRIRERGp5hSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsSlsgtRDDz1Ez549iY+PJykpKaBtRowYgWVZHreBAwdWbEVFRETkuBFZ1RUIVF5eHkOHDqVHjx689NJLAW83cOBAZs2a5b4fExNTEdUTERGR41DYBKnJkycDMHv27KC2i4mJoVGjRhVQIxERETnehU3Xnl0rVqygYcOGtG7dmhtuuIEDBw5UdZVERESkhgibFik7Bg4cyKWXXkrLli3ZvHkzd999N4MGDWLVqlVERER43SY3N5fc3Fz3/YyMjMqqroiIiISZKm2RmjBhQqnB4CVvGzZssL3/YcOGcdFFF9GuXTuGDBnCokWL+O6771ixYoXPbaZMmUJiYqL7lpqaavvxRUREpGazjDGmqh583759ZXa1tWrViujoaPf92bNnM27cOA4fPmzrMRs0aMCDDz7I9ddf73W9txap1NRULKs2lmXZekwRERGpXMYYjDlKeno6CQkJFfY4Vdq116BBAxo0aFBpj/fHH39w4MABGjdu7LNMTEyMzuwTERGRgITNYPPt27ezdu1atm/fjtPpZO3ataxdu5ajR4+6y7Rp04YFCxYAcPToUe644w6+/vprtm7dyrJly7j44os56aSTGDBgQFUdhoiIiNQgYTPY/N5772XOnDnu+506dQJg+fLl9O3bF4CNGzeSnp4OQEREBD/99BNz5szh8OHDNGnShPPOO48HHnhALU4iIiISElU6RiocZGRkkJiYqDFSIiIiYaSyxkiFTdeeiIiISHWjICUiIiJik4KUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNYRGktm7dyqhRo2jZsiVxcXGceOKJTJo0iby8PL/b5eTkcNNNN1GvXj1q167NZZddxp49eyqp1iIiIlLThUWQ2rBhAy6XixdeeIFffvmFadOmMXPmTO6++26/291666188MEHvPXWW3z++efs2rWLSy+9tJJqLSIiIjWdZYwxVV0JOx5//HFmzJjB77//7nV9eno6DRo04LXXXuPyyy8HCgPZqaeeyqpVq+jevXtAj5ORkUFiYiKWVRvLskJWfxEREak4xhiMOUp6ejoJCQkV9jhh0SLlTXp6OsnJyT7Xr169mvz8fPr37+9e1qZNG5o1a8aqVasqo4oiIiJSw0VWdQXs2LRpE88++yxTp071WSYtLY3o6GiSkpI8lqekpJCWluZzu9zcXHJzc93309PTgcJkKyIiIuGh6He7on+/qzRITZgwgUcffdRvmfXr19OmTRv3/Z07dzJw4ECGDh3K6NGjQ16nKVOmMHnyZC9rMlGWEhERCS8HDhwgMTGxwvZfpWOk9u3bx4EDB/yWadWqFdHR0QDs2rWLvn370r17d2bPno3D4btn8rPPPuOcc87h0KFDHq1SzZs3Z9y4cdx6661etyvZIuVyuTh48CD16tULyzFSGRkZpKamsmPHjgrtI66udPw6fh2/jl/Hf3wef3p6Os2aNSuVA0KtSlukGjRoQIMGDQIqu3PnTvr160fnzp2ZNWuW3xAF0LlzZ6Kioli2bBmXXXYZABs3bmT79u306NHD53YxMTHExMR4LKvIF6CyJCQkHJcfpCI6fh2/jl/Hf7w63o+/rLxQ7v1X6N5DZOfOnfTt25dmzZoxdepU9u3bR1pamsdYp507d9KmTRu+/fZbABITExk1ahTjx49n+fLlrF69mpEjR9KjR4+Az9gTERER8ScsBpsvXbqUTZs2sWnTJpo2beqxrqhnMj8/n40bN5KVleVeN23aNBwOB5dddhm5ubkMGDCA559/vlLrLiIiIjVXWASpESNGMGLECL9lWrRoUWpkfmxsLNOnT2f69OkVWLvqLSYmhkmTJpXqrjxe6Ph1/Dp+Hb+OX8dfkcJ2Qk4RERGRqhYWY6REREREqiMFKRERERGbFKREREREbFKQEhEREbFJQSoMTZ8+nRYtWhAbG0u3bt3cc2d58+9//5uzzz6bunXrUrduXfr371+q/IgRI7Asy+M2cODAij4M24I5/tmzZ5c6ttjYWI8yxhjuvfdeGjduTFxcHP379+e3336r6MOwLZjj79u3b6njtyyLwYMHu8uEy+v/xRdfcOGFF9KkSRMsy2LhwoVlbrNixQrOOOMMYmJiOOmkk5g9e3apMsE8n1Up2ON/9913Offcc2nQoAEJCQn06NGDTz75xKPMfffdV+q1L35Jruok2ONfsWKF1/d+yWut1tTX39vn2rIs2rZt6y4TTq//lClTOPPMM6lTpw4NGzZkyJAhbNy4sczt3nrrLdq0aUNsbCzt2rVj8eLFHutD8f2vIBVm3njjDcaPH8+kSZP44Ycf6NChAwMGDGDv3r1ey69YsYKrrrqK5cuXs2rVKlJTUznvvPPYuXOnR7mBAweye/du9+3111+vjMMJWrDHD4Wz+hY/tm3btnmsf+yxx3jmmWeYOXMm33zzDbVq1WLAgAHk5ORU9OEELdjjf/fddz2Ofd26dURERDB06FCPcuHw+mdmZtKhQ4eApzPZsmULgwcPpl+/fqxdu5Zx48Zx3XXXeYQJO++nqhLs8X/xxRece+65LF68mNWrV9OvXz8uvPBC1qxZ41Gubdu2Hq/9f//734qofrkFe/xFNm7c6HF8DRs2dK+rya//008/7XHcO3bsIDk5udRnP1xe/88//5ybbrqJr7/+mqVLl5Kfn895551HZmamz21WrlzJVVddxahRo1izZg1DhgxhyJAhrFu3zl0mJN//RsJK165dzU033eS+73Q6TZMmTcyUKVMC2r6goMDUqVPHzJkzx71s+PDh5uKLLw51VStEsMc/a9Ysk5iY6HN/LpfLNGrUyDz++OPuZYcPHzYxMTHm9ddfD1m9Q6W8r/+0adNMnTp1zNGjR93Lwun1LwKYBQsW+C1z5513mrZt23osu/LKK82AAQPc98v7fFaVQI7fm9NOO81MnjzZfX/SpEmmQ4cOoatYJQnk+JcvX24Ac+jQIZ9ljqfXf8GCBcayLLN161b3snB9/Y0xZu/evQYwn3/+uc8yV1xxhRk8eLDHsm7dupnrr7/eGBO673+1SIWRvLw8Vq9eTf/+/d3LHA4H/fv3Z9WqVQHtIysri/z8fJKTkz2Wr1ixgoYNG9K6dWtuuOGGMi8mXRXsHv/Ro0dp3rw5qampXHzxxfzyyy/udVu2bCEtLc1jn4mJiXTr1i3g57SyhOL1f+mllxg2bBi1atXyWB4Or3+wVq1a5fFcAQwYMMD9XIXi+QwnLpeLI0eOlPrs//bbbzRp0oRWrVrx17/+le3bt1dRDStGx44dady4Meeeey5fffWVe/nx9vq/9NJL9O/fn+bNm3ssD9fXPz09HaDU+7m4sr4DQvX9ryAVRvbv34/T6SQlJcVjeUpKSql+f1/uuusumjRp4vHGGThwIK+88grLli3j0Ucf5fPPP2fQoEE4nc6Q1r+87Bx/69atefnll3nvvfd49dVXcblc9OzZkz/++APAvV15ntPKUt7X/9tvv2XdunVcd911HsvD5fUPVlpamtfnKiMjg+zs7JB8nsLJ1KlTOXr0KFdccYV7Wbdu3Zg9ezYff/wxM2bMYMuWLZx99tkcOXKkCmsaGo0bN2bmzJm88847vPPOO6SmptK3b19++OEHIDTfp+Fi165dfPTRR6U+++H6+rtcLsaNG0evXr04/fTTfZbz9R1Q9PqG6vs/LC4RI6HxyCOPMH/+fFasWOEx4HrYsGHu/7dr14727dtz4oknsmLFCs4555yqqGrI9OjRgx49erjv9+zZk1NPPZUXXniBBx54oAprVvleeukl2rVrR9euXT2W1+TXXwq99tprTJ48mffee89jjNCgQYPc/2/fvj3dunWjefPmvPnmm4waNaoqqhoyrVu3pnXr1u77PXv2ZPPmzUybNo25c+dWYc0q35w5c0hKSmLIkCEey8P19b/ppptYt25dtRnPpRapMFK/fn0iIiLYs2ePx/I9e/bQqFEjv9tOnTqVRx55hCVLltC+fXu/ZVu1akX9+vXZtGlTuescSuU5/iJRUVF06tTJfWxF25Vnn5WlPMefmZnJ/PnzA/pyrK6vf7AaNWrk9blKSEggLi4uJO+ncDB//nyuu+463nzzzVLdHCUlJSVxyimnhP1r70vXrl3dx3a8vP7GGF5++WWuueYaoqOj/ZYNh9d/7NixLFq0iOXLl9O0aVO/ZX19BxS9vqH6/leQCiPR0dF07tyZZcuWuZe5XC6WLVvm0epS0mOPPcYDDzzAxx9/TJcuXcp8nD/++IMDBw7QuHHjkNQ7VOwef3FOp5Off/7ZfWwtW7akUaNGHvvMyMjgm2++CXiflaU8x//WW2+Rm5vL3/72tzIfp7q+/sHq0aOHx3MFsHTpUvdzFYr3U3X3+uuvM3LkSF5//XWPKS98OXr0KJs3bw77196XtWvXuo/teHj9ofBst02bNgX0R1R1fv2NMYwdO5YFCxbw2Wef0bJlyzK3Kes7IGTf/0ENk5cqN3/+fBMTE2Nmz55tfv31VzNmzBiTlJRk0tLSjDHGXHPNNWbChAnu8o888oiJjo42b7/9ttm9e7f7duTIEWOMMUeOHDG33367WbVqldmyZYv59NNPzRlnnGFOPvlkk5OTUyXH6E+wxz958mTzySefmM2bN5vVq1ebYcOGmdjYWPPLL7+4yzzyyCMmKSnJvPfee+ann34yF198sWnZsqXJzs6u9OMrS7DHX+Sss84yV155Zanl4fT6HzlyxKxZs8asWbPGAObJJ580a9asMdu2bTPGGDNhwgRzzTXXuMv//vvvJj4+3txxxx1m/fr1Zvr06SYiIsJ8/PHH7jJlPZ/VSbDHP2/ePBMZGWmmT5/u8dk/fPiwu8xtt91mVqxYYbZs2WK++uor079/f1O/fn2zd+/eSj++sgR7/NOmTTMLFy40v/32m/n555/NLbfcYhwOh/n000/dZWry61/kb3/7m+nWrZvXfYbT63/DDTeYxMREs2LFCo/3c1ZWlrtMye+/r776ykRGRpqpU6ea9evXm0mTJpmoqCjz888/u8uE4vtfQSoMPfvss6ZZs2YmOjradO3a1Xz99dfudX369DHDhw9332/evLkBSt0mTZpkjDEmKyvLnHfeeaZBgwYmKirKNG/e3IwePbpafpEUCeb4x40b5y6bkpJizj//fPPDDz947M/lcpl//etfJiUlxcTExJhzzjnHbNy4sbIOJ2jBHL8xxmzYsMEAZsmSJaX2FU6vf9Hp7CVvRcc7fPhw06dPn1LbdOzY0URHR5tWrVqZWbNmldqvv+ezOgn2+Pv06eO3vDGF00E0btzYREdHmxNOOMFceeWVZtOmTZV7YAEK9vgfffRRc+KJJ5rY2FiTnJxs+vbtaz777LNS+62pr78xhafyx8XFmRdffNHrPsPp9fd27IDHZ9rb99+bb75pTjnlFBMdHW3atm1rPvzwQ4/1ofj+t45VUERERESCpDFSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE0KUiJy3Dlw4AANGzZk69at5drPsGHDeOKJJ0JTKREJSwpSIhKWRowYgWVZWJZFVFQULVu25M477yQnJ6fMbR966CEuvvhiWrRoUa463HPPPTz00EOkp6eXaz8iEr4UpEQkbA0cOJDdu3fz+++/M23aNF544QUmTZrkd5usrCxeeuklRo0aVe7HP/300znxxBN59dVXy70vEQlPClIiErZiYmJo1KgRqampDBkyhP79+7N06VK/2yxevJiYmBi6d+/uXrZixQosy+KTTz6hU6dOxMXF8Ze//IW9e/fy0Ucfceqpp5KQkMDVV19NVlaWx/4uvPBC5s+fXyHHJyLVn4KUiNQI69atY+XKlURHR/st9+WXX9K5c2ev6+677z6ee+45Vq5cyY4dO7jiiit46qmneO211/jwww9ZsmQJzz77rMc2Xbt25dtvvyU3NzdkxyIi4SOyqisgImLXokWLqF27NgUFBeTm5uJwOHjuuef8brNt2zaaNGnidd2DDz5Ir169ABg1ahQTJ05k8+bNtGrVCoDLL7+c5cuXc9ddd7m3adKkCXl5eaSlpdG8efMQHZmIhAsFKREJW/369WPGjBlkZmYybdo0IiMjueyyy/xuk52dTWxsrNd17du3d/8/JSWF+Ph4d4gqWvbtt996bBMXFwdQqstPRI4P6toTkbBVq1YtTjrpJDp06MDLL7/MN998w0svveR3m/r163Po0CGv66Kiotz/LzobsDjLsnC5XB7LDh48CECDBg3sHIKIhDkFKRGpERwOB3fffTf33HMP2dnZPst16tSJX3/9NWSPu27dOpo2bUr9+vVDtk8RCR8KUiJSYwwdOpSIiAimT5/us8yAAQP45ZdffLZKBevLL7/kvPPOC8m+RCT8KEiJSI0RGRnJ2LFjeeyxx8jMzPRapl27dpxxxhm8+eab5X68nJwcFi5cyOjRo8u9LxEJT5YxxlR1JUREKtOHH37IHXfcwbp163A47P89OWPGDBYsWMCSJUtCWDsRCSc6a09EjjuDBw/mt99+Y+fOnaSmptreT1RUVKl5pUTk+KIWKRERERGbNEZKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMSm/wfa7XHZ62bxVwAAAABJRU5ErkJggg==", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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KyvL+/9577+Xcc8/liCOO4Oijj2bw4MFceumlHHPMMT7bKz+duaK0tDTatm1b6YsvLS2N33//3Xvbtm2efPJJ/vWvf7Fp0ybvGCGouXsSSkMjwP79+2ss51RVZ2tWd99PP/0E/DFG7UDldS1X1WPWpEkTn8cmUJMmTcLlcnH//feTmJjIiy++yMiRI2nUqBFPPvkkUDpepU+fPo73Uc7pY1/b+6l169ZMnTqVf/3rX/z00098+OGHPPzww9x99920bt064LPxtmzZApSG+AMdeeSRfPjhh+Tm5tKgQQPv8pqe9wMdccQRzJo1C4/Hww8//MD8+fN55JFHuOqqq+jYsaPPZ0LFMUflDnzOt2zZUuXzc+SRR3rvDyZIdenShS5dugBw2WWXceaZZ3LOOefw1VdfYVlWpe64igoKCoDKXXTt27f3jhO75JJLuOqqqxg4cCDr16/3ln322WfJz8/nlltu4ZZbbgHgr3/9K4ceeihvv/12tWdjzp49m6ZNmzJkyBDHxyzBU5CSeu3www8POMDdcMMNTJ8+nTFjxtC3b1/S0tKwLIsRI0b4jFU45ZRT2LhxI++88w4LFy7k3//+N5MnT2batGk+X2hVtdDVtLxicHvwwQe56667+Nvf/sZ9991H06ZNcblcjBkzpsZxE4D3C2H16tV+nQJeXWtGxfBWUXXTV1R1X3ldZ82a5TN/WLm4ON+Pouoem2AsW7aMHj16eIP0pZdeys6dO7n11ltp1KgRI0aMYPny5bz11ltB7yvQxz5QlmVxxBFHcMQRRzB06FAOP/xwZs+eHZFpDWp63qvjdrvp1q0b3bp1o2/fvpx66qnMnj3b573pz/sh0i688EKuvvpq/ve//9G5c2dat24NlLbkHWjHjh3eucJq2+bzzz/Pp59+yqBBg4DSH1DvvPMOW7duZfPmzd7w1a9fP1q0aEHjxo0rbWfr1q189tlnXHXVVcTHxwd/sOKYgpTIAd58801GjhzJ448/7l1WUFBQ6ewdgKZNmzJ69GhGjx5NTk4Op5xyCvfcc0/IvtDefPNNTj31VF544QWf5fv27aN58+Y1rjtkyBDcbjcvv/yyX4OemzRpUuUxlrdaBOPQQw8FSs/WClXLZKDdWJZlVeqyu+WWW9i5cycPPPAAs2fPpmfPnpx77rlB1y3Qxz4YnTp1okmTJlV+udemvKVk/fr1le5bt24dzZs392mNCoXyFjen9a2uruX3Q+CvjeqUd6mVt0QfcsghtGjRosqJbL/++mu/QvOB26yoXbt23pa5ffv2sWLFCi644IIqt/PKK69gjFG3XhTQWXsiB3C73ZV+BT/99NOVWmYOPDuxYcOGHHbYYSE9G7Gqurzxxhts37691nUzMjK48sorWbhwIU8//XSl+23b5vHHH2fbtm1AadjJysri+++/95bZsWOH92yoYAwaNIjU1FQefPBBiouLK91/4KzQ/khJSQGoMvxVZeDAgfz000+Vxlk99NBDHHXUUWzevJk//elP3ikSghHoY++Pr776itzc3ErLv/76a/bs2VNl91xtWrduTY8ePZg5c6bP47hmzRoWLlzIWWedFfA2y3322WdVPtfl466c1Pess87i66+/Zvny5d5lubm5PPfcc3To0ME7Zq88/Pn72vjtt98qLSsuLuall14iOTnZZyzgBRdcwPz5831C+eLFi/nf//7H8OHDvcuqe02Xj8k79thja6zT+PHjKSkp4aabbqry/jlz5tCuXbsap6CQyFCLlATlgw8+8P4arKhfv3506tSpDmoUvLPPPptZs2aRlpbGUUcdxfLly/noo48qjUk66qijGDBgAL169aJp06Z8++23vPnmm5UG1Qdbl3vvvZfRo0fTr18/Vq9ezezZs/1+bB9//HE2btzIP/7xD95++23OPvtsmjRpwtatW3njjTdYt24dI0aMAGDEiBHcfvvtnHfeefzjH/8gLy+PqVOncsQRR9Q6sL02qampTJ06lUsvvZRjjz2WESNG0KJFC7Zu3cp7773HiSeeyDPPPBPQNsu/4F577TWOOOIImjZtytFHH13tGJnx48czb948Ro4cyaJFi+jXrx85OTm88sorbNq0ieOPP57777+fvn37cuaZZ9a6/8WLF3vHxVQ0bNgwjj766IAee3/MmjWL2bNnc95559GrVy8SEhL48ccfefHFF0lKSvJObxCoRx99lCFDhtC3b18uv/xy8vPzefrpp0lLSwvqGpQPP/wwK1as4Pzzz/eOG1y5ciUvvfQSTZs2rXJ+rdqMGzeOV155hSFDhvCPf/yDpk2bMnPmTDZt2sRbb73lDcGHHnoojRs3Ztq0aTRq1IgGDRrQp0+fasd3XX311WRnZ3PKKadwyCGHkJmZyezZs1m3bh2PP/64zxilO+64gzfeeINTTz2VG2+8kZycHB599FG6devG6NGjveUeeOABvvjiCwYPHky7du3Yu3cvb731Ft988w033HCDz9UfHnroIe/4vLi4OObNm8fChQu5//77vXNiVbRmzRq+//57xo0bF7LWNwlCXZ4yKLGrptO1OeC0Y6JoZvOqcMAp9L///rsZPXq0ad68uWnYsKEZNGiQWbdunWnfvr0ZOXKkt9z9999vevfubRo3bmySk5NNly5dzAMPPGCKioq8ZUaOHGkaNGhQaZ/9+/c3Xbt2rbT8wBmeCwoKzM0332xat25tkpOTzYknnmiWL19u+vfv7/fjUVJSYv7973+bk08+2aSlpZn4+HjTvn17M3r06Eqn5y9cuNAcffTRJiEhwXTu3Nm8/PLL1U5/UNVzWtsM3UuWLDGDBg0yaWlpJikpyRx66KFm1KhR5ttvv/WWqe4xq6oey5YtM7169TIJCQl+TYWwe/duc/3115uMjAwTFxdnWrVqZS677DKzbt06k52dbbp06WJSU1PN6tWrq91G+Wurur9Zs2Z5y/r72Pszs/n3339vbr31VnPssceapk2bmri4ONO6dWszfPhws3LlyhqP25jqpz8wxpiPPvrInHjiiSY5Odmkpqaac845x/zwww8+ZWp7jx7oiy++MNddd505+uijvcferl07M2rUKLNx40afstXNbF7V63zjxo3mwgsvNI0bNzZJSUmmd+/eZv78+ZXWfeedd8xRRx1l4uLiap0K4ZVXXjEDBw406enpJi4uzjRp0sQMHDjQvPPOO1WWX7NmjTnzzDNNSkqKady4sfnLX/5iMjMzfcosXLjQnH322aZNmzYmPj7eNGrUyJx44olm+vTpPjOYG2PM/PnzTe/evU2jRo1MSkqKOeGEE8zrr79ebX3HjRtnAPP9999XW0YixzKmDkfyiYiIiMQwjZESERERcUhBSkRERMQhBSkRERERh2ImSE2aNInjjz+eRo0a0bJlS4YNG1blfCIHeuONN+jSpQtJSUl069atykseiIiIiDgRM0Hqk08+4brrruPLL79k0aJFFBcXc+aZZ1Y5r0q5ZcuWcckll3D55Zfz3XffMWzYMIYNG8aaNWsiWHMRERGpr2L2rL1du3bRsmVLPvnkE0455ZQqy1x88cXk5uYyf/5877ITTjiBHj16MG3atEhVVUREROqpmJ2Qs3x6/YpXLD/Q8uXLGTt2rM+yQYMGMW/evGrXKSws9JmZ2rZt9u7dS7NmzTTxmYiISIwwxrB//37atGkTkisWVCcmg5Rt24wZM4YTTzyxxit9Z2Zmkp6e7rMsPT2dzMzMateZNGkSEydODFldRUREpO788ssvtG3bNmzbj8kgdd1117FmzRo+//zzkG97/PjxPq1YWVlZtGvXDstqpBYpERGRGGGMwZj9NGrUKKz7ibkgdf311zN//nw+/fTTWhNmq1at2Llzp8+ynTt30qpVq2rXSUxMJDExsdJyy7IUpERERGKIMYT9uztmztozxnD99dczd+5cPv7442ovPllR3759Wbx4sc+yRYsW0bdv33BVU0RERA4iMdMidd111zFnzhzeeecdGjVq5B3nlJaWRnJyMgCXXXYZhxxyCJMmTQLgxhtvpH///jz++OMMHTqUV199lW+//Zbnnnuuzo5DRERE6o+YaZGaOnUqWVlZDBgwgNatW3v/XnvtNW+ZrVu3smPHDu/tfv36MWfOHJ577jm6d+/Om2++ybx582ocoC4iIiLir5idRypSsrOzSUtLw+VK1RgpEREJmZSUZJo1a4bLpe+WQNm2Yc+ePeTl5VdbxhiDbWeTlZVFampq2OoSM117IiIi9YFlWYwa9WfOOWcw8fEJ6Dd64IyB4uIi3n13ATNmzKEu24QUpERERCJo1Kg/M2LEBaSlNa7rqsS8ESMuAGD69Nl1VoeYGSMlIiIS6xo0SOGccwaXhShLf0H+paU15pxzBpOSkhzoUxEyClIiIiIR0rRpU+LjE+q6GvVKfHwCzZo1q7P9K0iJiIhEiMtlaUxUiFkWdTpgX0FKRERExCEFKRERERGHdNaeiIiI1OqeeyaQk7Ofxx77Z5X3r1+/junTX+S771aSk5NDeno6xx57HJdeehnt27fn119/5dxzz6603uDBQ7jvvgfweDzMmvUS8+e/S2bmDhITE8nIaMewYecxbNh54T48xxSkREREJCifffYpt99+Kyec0Jd7732Atm3b8vvve/noo4+YNu1fTJr0sLfslClT6dTpUO/tpKREAJ5//jnmzn2LW2+9nSOPPIrc3Fx+/PEHsrOzI348gVCQEhEREccKCvK59957OPHEk3j00ce9yw855BCOProb+/fv9ymfltaY5s2bV9rOp59+woUXDmfgwDO8y4444ohwVTtkFKRERESigCu/hsuduFyYxET/yloWJimpxrJ2cujmXVq+fDn79u3j0ksvq/L+Ro0a+bWdZs2a8c0333DhhRfRpEmTkNUv3BSkREREosCxp5xY7X37TjyJDU885b3d/czTcRcUVFl2/7G9WP/s897b3f40lPh9+3zKfPvNyuAqW8Evv2wFoEOHjn6Vv/zy0T7TFTz//At07tyFm266mXHjbmXw4DPo1KkTxxzTnVNOGcCJJ1b/uEQDBSkRERFxLNDL3D344CQ6dvwjdKWntwKgU6dOvPrqG/z444/897+r+O67ldx88xjOPvsc7rzz7lBWOaQUpERERKLAyk+/qPY+4/Kdrei/CxdXX/aAGT9X/+e94CpWi3bt2gGwefMmjjmme63l09NbkZHRrsr7XC4XXbt2pWvXrvz5z3/h/fffY8KEuxg9+nIOOeSQkNY7VDSPlIiISBSwk5Or/as4PqrWshXGR1VXNpROOKEvjRs3Ztasl6q8/8DB5oHo1KkTAPk1jAmra2qREhEREb/k5OSwfv16n2VpaWnceefdjBt3G2PHjuHiiy8hIyODffv28dFHC8nMzOTBBx+qddu3334r3bt355hjutOsWTN+/fVXpkx5mnbt2tOhQ4cwHVHwFKRERETELytWfMtf/3qJz7Jzzx3GnXfezQsvzGDGjBe56647yM3NJT09neOOO55rrrnWr22fcEJfFi5cwIwZ08nJyaFZs2Ycd9zxXHXV1cTFRW9csYwJdJjYwSU7O5u0tDRcrlQsXWlSRESC0L59BlOmPEbz5i0AfacEz7B79y6uu+4Wtmz5xfceY7DtbLKyskhNTQ1bDTRGSkRERMQhBSkRERERhxSkRERERBxSkBIRERFxSEFKREQkQmzbBDwTuNTMmNLHta4oSImIiETI3r17KS4uqutq1CvFxUXs2bOnzvavICUiIhIhubl5vPvuArKy9gFGf0H+ZWXt4913F5CXV3czn0fvDFciIiL10IwZcwA455zBxMcnoCkKA2dMaUvUu+8u8D6edUUTctZCE3KKiEg4pKQk06xZM1wufbcEyrYNe/bsqbElKlITcqpFSkREpA7k5eWTl7etrqshQdIYKRERERGHFKREREREHFKQEhEREXFIQUpERETEIQUpEREREYcUpEREREQcUpASERERcSimgtSnn37KOeecQ5s2bbAsi3nz5tVYfunSpViWVekvMzMzMhUWERGRei2mglRubi7du3dnypQpAa23fv16duzY4f1r2bJlmGooIiIiB5OYmtl8yJAhDBkyJOD1WrZsSePGjUNfIRERETmoxVSLlFM9evSgdevWnHHGGXzxxRc1li0sLCQ7O9vnT0RERKQq9TpItW7dmmnTpvHWW2/x1ltvkZGRwYABA1i5cmW160yaNIm0tDTvX0ZGRgRrLCIiIrHEMsaYuq6EE5ZlMXfuXIYNGxbQev3796ddu3bMmjWryvsLCwspLCz03s7OziYjIwOXKxXL0hW6RUREYoExBtvOJisri9TU1LDtJ6bGSIVC7969+fzzz6u9PzExkcTExAjWSERERGJVve7aq8qqVato3bp1XVdDRERE6oGYapHKyclhw4YN3tubNm1i1apVNG3alHbt2jF+/Hi2b9/OSy+9BMATTzxBx44d6dq1KwUFBfz73//m448/ZuHChXV1CCIiIlKPxFSQ+vbbbzn11FO9t8eOHQvAyJEjmTFjBjt27GDr1q3e+4uKirj55pvZvn07KSkpHHPMMXz00Uc+2xARERFxKmYHm0dKdnY2aWlpGmwuIiISQyI12PygGyMlIiIiEioKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIiIiIQwpSIiIiIg4pSImIiIg4pCAlIiIi4pCClIiIiIhDClIiIiIiDilIiYiIiDikICUiIiLikIKUiIiIiEMKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIiIiIQwpSIiIiIg4pSImIiIg4pCAlIiIi4pCClIiIiIhDClIiIiIiDilIiYiIiDikICUiIiLikIKUiIiIiEMKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIiIiIQwpSIiIiIg4pSImIiIg4pCAlIiIi4pCClIiIiIhDClIiIiIiDilIiYiIiDgUU0Hq008/5ZxzzqFNmzZYlsW8efNqXWfp0qUce+yxJCYmcthhhzFjxoyw11NEREQODjEVpHJzc+nevTtTpkzxq/ymTZsYOnQop556KqtWrWLMmDFcccUVfPjhh2GuqYiIiBwMLGOMqetKOGFZFnPnzmXYsGHVlrn99tt57733WLNmjXfZiBEj2LdvHwsWLPBrP9nZ2aSlpeFypWJZVrDVFhERkQgwxmDb2WRlZZGamhq2/cRUi1Sgli9fzsCBA32WDRo0iOXLl9dRjURERKQ+iavrCoRTZmYm6enpPsvS09PJzs4mPz+f5OTkSusUFhZSWFjovZ2dnR32eoqIiEhsqtctUk5MmjSJtLQ0719GRkZdV0lERESiVL0OUq1atWLnzp0+y3bu3ElqamqVrVEA48ePJysry/v3yy+/RKKqIiIiEoPqddde3759ef/9932WLVq0iL59+1a7TmJiIomJieGumoiIiNQDMdUilZOTw6pVq1i1ahVQOr3BqlWr2Lp1K1DamnTZZZd5y//973/n559/5rbbbmPdunX861//4vXXX+emm26qi+qLiIhIPRNTQerbb7+lZ8+e9OzZE4CxY8fSs2dP7r77bgB27NjhDVUAHTt25L333mPRokV0796dxx9/nH//+98MGjSoTuovIiIi9UvMziMVKZpHSkREJPZoHikRERGRKKcgJSIiIuKQgpSIiIiIQwpSIiIiIg4pSImIiIg4pCAlIiIi4pCClIiIiIhDClIiIiIiDilIiYiIiDikICUiIiLikIKUiIiIiEMKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIiIiIQwpSIiIiIg4pSImIiIg4pCAlIiIi4pCClIiIiIhDClIiIiIiDilIiYiIiDikICUiIiLikIKUiIiIiEMKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIiIiIQ3F1XQGRiDOGRkAxUGBZAHQwNkNMMU0xNMKQBKRgSAZSjOE5VwIfWvEA9DIlTLPzsSj9JWKV/ZX/KplsJTLdlQDAYcbDk3YBxUBR2f72Y5EL7MdiqRXHZ1bp2zDZGHrhYQ8We7DYi0VJWf1ERCQ6KUhJvdW+LBy1w5CBTTtjk4FNKwwJwEgrmdlWaeDpioenTUG12/rYxPFhWaZpCPTErrZsY4z3/00xDKLkjztN5fLlQaoDNkvtXJ/7sqAsWLmYacUzzZUIQJIxnEUJmVjswMUOLG8oFBGRyFGQkpiVagxd8XCUsemKh6ONh0ddiSwqazk6Gg/P1BCOmlZINZtw8TZx7ClrMcrHIg/IxyIfWGb98Vb5HhdnuVIwlOYiG8v7f4CNFXrMf8bFKCuZeCChrIWrYVmrV0PgW8vtLWsBP+GiKYYmGFxAGpCGoRMe3q/wdu2Azet2ns/x/A5swcUWXLxmxfN6WauYyxhSgX0AClsiIiGlICUxpYfxcK9dwNF4aFdF884S4/EGqf/hYi5xbLVcbMPFVsvFL1j8ios9WORXCBU/WG4ucjfwqw6/Wy4W+jm8cLfl4uWyVq/a/GC5OdLdCCgNP40xNKvwt6HCPt3A57hpjaE1NilAE6AJNj2wWckfAe1wbNbaOfwO/ISb/1ku/kfZn+XmJ1w+j4WIiPjPMsZU0dkg5bKzs0lLS8PlSsXSl03ENDSGfpRwkvHwteVmflk4Osp4+N7O8ZbbhsVa3PxguViDmy8sNxsqtPIcFIwhDTgEm/ZlXZjfWHGsLHscTjMlLDygy7Ci+6xEJrqSAGhibIaaElZbbn7ERZFe8yISo4wx2HY2WVlZpKamhm0/apGS6GAMPbEZaoo5y5TQC4+3TWUO8d4g9SMubrCS+N5ysxY3+/RFD5ZFFpCFmx9wl/YRVvCxFUcjVyqdsDkcm87GU/Zv6e31FVq6euNhhskHAyXAelysttyswcUKy81XxJGtx1xExEtBSupcsjH8YO8n44Cuup+x+NyK472yEAVgLIupVmKkqxjz8q3Slru1uKHC4wlgVWiULsbiE9x0w6Yphq7YdDVlA+sNjLaSmVXWVdnJeOhnPKwpa70qVMASkYOQgpREVJIxnG+KOQKbe8q6k/Kt0jPPmuDhI0qD0yIrjm2WpjmLBFMhAH1sxfGxuyEYwyEYuuGhm7HpjodeZaGp3GBTwlOmwNt6tRYX31puVuBmheXme9wUK1yJSD0Xc2OkpkyZwqOPPkpmZibdu3fn6aefpnfv3lWWnTFjBqNHj/ZZlpiYSEFB9WdyHUhjpEKjm/FwuSniL6aIJpTO4ZTuSvV2E3U0Nr9ixVSrRmpyh7quQpWy8zdHZD8X2UX83RRxdFnr1YFOdTXwTu3Q3tgkYPgJl84cFJGI0BipKrz22muMHTuWadOm0adPH5544gkGDRrE+vXradmyZZXrpKamsn79eu9thaHIaWgMF5tirjBFHI/Hu3wzFi9ZCbgxlA/o2RRFrU/RGpD8FUj9gwldr7sSeJ0EMIa2GI7Fw3Gm9K8nHr6rcObgDaaQMaaI37D4AjefW3F8YblZhVuTjopITIupFqk+ffpw/PHH88wzzwBg2zYZGRnccMMNjBs3rlL5GTNmMGbMGPbt2+d4n2qRcu4Gu5DJZfM4FQH/IY4XXAl8RJxPd1JdiPWwFCmOg5YxPi1PU+x8Rpoikg4olgt8hZuLXA104oCIhJRapA5QVFTEihUrGD9+vHeZy+Vi4MCBLF++vNr1cnJyaN++PbZtc+yxx/Lggw/StWvXSFT5oHOCKcEClpd158y24hlliphtJTDLimdXHbU6KTQ5V9NjV2PIOiAUXedK5iaTRC88nGQ8nGhK6IeHphg6Y5dOFlpmrF1IIbDUiuMHXHUeukVEahIzQWr37t14PB7S09N9lqenp7Nu3boq1+ncuTMvvvgixxxzDFlZWTz22GP069ePtWvX0rZt2yrXKSwspLCw0Hs7Ozs7dAdRT/UyJUy0CxlMCd/gpq+rAVgWey0XvcommIwkBafIqO5xri5gFVkWy4ljuRXHoyRiGcOR2KTzR+uVZQy3mUKaY8CUzta+jDiWWnEstuJYrWAlIlEmZoKUE3379qVv377e2/369ePII4/k2Wef5b777qtynUmTJjFx4sRIVTGmHW083GMXMKzsWnLFwPeWiyTA/+H8wYuV4NQs4bA62e+eog0R3Z+/ActYFj/g5ocKyxKBf1oJnG5KOAEPTYChlDDUlICBD4ljqJ8z0IuIRELMBKnmzZvjdrvZuXOnz/KdO3fSqlUrv7YRHx9Pz5492bCh+i+W8ePHM3bsWO/t7OxsMjIynFW6nsowNpNMAReZYlyAh9JuvPutRH6OwKzi0RSc6iocBcJJHcMRvqp63g4MVwWWxSNWEo8AccbQAw8nGw+nmRJOocQ7WzuUnszwuZ3DJ1Yc71txLCFOM7GLSMTFTJBKSEigV69eLF68mGHDhgGlg80XL17M9ddf79c2PB4Pq1ev5qyzzqq2TGJiIomJmvCxJqeaEkaYYgBet+K510pkXZgDVF2Gp1gIS6HmzzGHImzVFK5KLItvieNbK47JJBJvSi/6XG4AJRyNzdGmiOtMEfuBhcTxrhXPB1Yce6LoTFARqb9iJkgBjB07lpEjR3LcccfRu3dvnnjiCXJzc71zRV122WUccsghTJo0CYB7772XE044gcMOO4x9+/bx6KOPsmXLFq644oq6PIyYlGIMeWW/9l+y4umGh5etBP4bxgAV6fB0MAamYFT3eAUbsA583suDVbFlUVxh+SfEcZ4rhcGmhLNNMYdguIASLjAleAxcaiXzusu/C0aLiDgVU0Hq4osvZteuXdx9991kZmbSo0cPFixY4B2AvnXrVlyuP36F/v7771x55ZVkZmbSpEkTevXqxbJlyzjqqKPq6hBiTrIxPGAKGGaK6e5qxH7LAsviViu59pUdiFR4isXQ1NrTrtYyO9xbI1CTmoU6YFUXrPZbFu8Sz7tWPNebJI7FwzlloaoHpRduLjfIFNPDeJhnxbP+YLuotYiEVUzNI1UXDuZ5pHoYDy/beXSh9Fpro61kZoXpF364A1RdByd/QlC0iVQoC7YFq6qzBNsYm18rdO3N8+RydtlJEetw8R8rnnesOL7GrbMAReqpSM0jpSBVi4MySBnDTaaIB0wBCcB2LK50JbPwgIvdBiuc4SmSwSkWQ1KohCtsOQ1X1U29cJldxEWmmNMooeJPgR1YvGXFM9ZKwj5Y3t8iBwkFqShxsAWpFGP4t8nnorLB5HOJ42pXMntDOHA3XAEq3OHpYA5MToUqaIUqWDUyhsGmmHMp4SxTTCrwBW76uxt6y7Q1ti6YLVIPKEhFiYMtSD1p53OdKaIIuMlK4lkrIWQXmQ1HgApXeIqm0NQ6vmHthQK0ozgn5NsMaP8hCFiBhqsDQ1WCMZxGCUVYfFw2nqqZsdlm7+cHXLxiJfCqFa9QJRKjFKSixMEWpJoam3fsPMa5kvjCCs25CKEOUOEIT5EKTuEIRZEUzgAWbLgKNlgBDDHFvGXn+XT/LcbNv60E3rHiNU+VSAxRkIoSB0OQ6mY8rK54JtMBF5x1KpQBKtThKZzBKdbDUrBCGbachqtgQlUTY3OBKeESU0R/PN7lu7G4yJXCpyH6gSEi4aUgFSXqe5C63i7kCVPAGCuJZ1yhmYg0GgNUOILTwR6YnAhFyHISrgIJVhVDVXtjM9oUMcoUkY4hw9WI3WVdfUcaDzuxQjp+UERCR0EqStTnIDXWLuQRU3pVvEetBMa7gp8bKhQhKhrDU6RCU3pydLV27MwvCfs+gg1XgQYrf0NVxUDlLrtczYoKrVFLPTkcj4c3rXj+ZSXwFe6QjScUkeApSEWJ+hqkbrcLeMAUAnC/lcg9VmJQXwKhaoUKNkSFIjyFKzRFW0gKtVCHLqcBK5Bg5SRUQelEtUvtHHqVzbEG8A1u/mUl8LoVT2E9+qwQiVUKUlGiPgapG+1CHi9riZpgJfKAKymo7dV1K1S0haf6HpicCEXIchKswh2qepkSrjVFXGyKKX8X7cbiDiuJF3V5GpE6pSAVJepbkLrCLmKayQfgHiuR+4MIUbEcoEIVnCIZmtLDc1WeSnbmR2Y/pfsKLmAFGq78DVaBhqrmxuZvpoi/myLaYfhzhev8WcZo9nSROqAgFSXqW5C6wy7gXlNYOibKSnLcnRdsiKqLABVseApHaIpUOAqnUAcvp+GqLkNVeaByG8NQSviAOIrL3ltj7EKGmWIecyXyHnEKVSIRoiAVJepbkAI4zZTwcRADY4MJUU4DVF2Ep1AFp/oQloIRiqDlJFwFEqxCFaoqzU1lDOvsHA4rG0u1BhePW4m8asV7g5aIhIeCVJSoD0EqyRg8EJIP7kiHqEgHqGDDUyRDU6sku/ZCAcosiNyp/MEErHAGK39CVSCtVK2NzT9MIVeZItLK7vsFiyetRP5tJZATo58rItFOQSpKxHyQMoYXTT6HG5sRrhS2O5zzJhYCVKTDU6hDUziCUbiFOng5DVeBBqtIhqryQJVqDFebIv5hCmlN6cfubCueka4Uv+oiIoFRkIoSsR6kygeXe4AzXA0czcoc7SHKSYByEp5CEZxiMSwFIxRBy0m4CiRYhSpU+RuoEo3hr6aYsaaQS1wpfF92VYHGxlAAFMTg54xINFKQihKxHKSONR4+s3NIBMZbSTzqYOZypyEqGgNUpMNTJEPTIclFQW9je37kTtcPJmAFGqxCHaqCbaUqD1QHns33jJ3POaaYSVYiL1gJGkMlEiQFqSgRq0EqyRhWlQ1y/Q9xXOBKCfhsoUiFqGgLUE7CUyhDUyhCUSSEOng5DVfhClahCFX+BCqAeGP43s7h8LJB6T9jcbeVxGtWvM7yE3FIQSpKxGqQut8uYJwpZBsWPVyN2FcPQlQgASoWwlOsBCanQhG0Ag1XgYSqaAtUCcbwN1PEHaaQNmVjqL7BzT9cSXyjCyWLBExBKkrEYpDqZjx8becQD5zvSuE/VnxA6zsJUdHSChVIgAo0PDkNTpEITK2Sg5tjIDM/cqcbBhOwwhWsQhWqQhGoUozhRlPIbaaQRmX3jbKSeVkzpYsEREEqSsRikDraeHjBzmMLLi5yNwho3WgLUXUdoJyEp1AFp2DDUbiFMnw5CVd1GaoiEahaGZsHTQFDTQlHuRqyx+EZtyIHKwWpKBGLQQpKZ1huAGQHUOdoClHh6MbzN0AFGp6CCU7RHpacCjZkhTtYRUuo8idQNTU2e8tDlDFMNgW8a8Xzsbr7RGqkIBUlYipIGRPR2coDCVF12QoVjgDlJDyFOzS1SAv8or7ldmWF7qLNNXEasAINVqEOVdEQqACGmmLesfMAeJs4bnIlO54bTqS+i5kgVVhYSGJi4KfVx4pYClLT7Dx24uJBK5HCMA8uD0eIqosAFc7wFIrgFEw4CqdQBi8n4SqQYOVvqIrmQFUeptKMYYIp4FpTRBzwO3CNlcybGj8lUknUBqkPPviAV199lc8++4xffvkF27Zp0KABPXv25Mwzz2T06NG0adMmXPWNuFgJUh2NzY/2fuKA3q6GrCyb5M8f9S1EhTJABRKegglO0RqYnAgmZEVDqIpEoAq2daqr8fBvO5/j8QDwkhXPjVYy+6P4M0ok0qIuSM2dO5fbb7+d/fv3c9ZZZ9G7d2/atGlDcnIye/fuZc2aNXz22WcsX76cUaNGcd9999GiRYuwVTxSYiVITbXzuNIUs4A4zg5ggHmshKhoDVBOwlMkQlNay4Jay2T9lhT2epRzGq4CDVb+hqpItlKFOlCVh6k4Y7jLFDLOFOIGPsXNae7IdNGKxIKoC1J9+/blzjvvZMiQIbhc1X8Ibd++naeffpr09HRuuummkFW0rsRCkMowNuvt/SQAp7gasCyAQaiBBKlYDlH+BKhwhadgg5M/oShSQhW+nASrQEJVpFupgglTEFygOtGU8KKdz9WuZJZqALqIV9QFqYNVLASpJ+x8rjdFLMHNGQH8Ig1Xa5Q/ISpUXXmhaIUKdYByGpyiKTA5EWzICiRchSNU1XWgCiZMxRvjc0mZs00xP+JiYwBd/CL1jYJUlIj2INXK2Gyw95NE6UWJl/j5izTaQ1QkWqH8CVDhCk+RDk2JbUu/UAu3eSK6X6fhqi5DVSwHKoDDjIdv7dLtX+5K4a0AJ+QVqS+iOkgZY3jzzTdZsmQJv/32G7bt+4X19ttvh6yCdS3ag9R4u4D7TCFf4uYkVwO/pz8IR5depEJUJLrxwhGggg1P5WGoLoQqgDkJVuEIVdEeqIIJU22NzUw7j/54sIF/WElMc3DBcpFYF9VB6sYbb+TZZ5/l1FNPJT09vVLAmD59esgqWNeiPUgdYzz8zRTxqRXH237+8jyYQ1QoAlS4w1NdBqZABRuwAg1W/oaqSAaqumidqi1Mucom7rzOlL7e77ESud9KdDzPnEgsiuog1bRpU15++WXOOuuscNQpqkR7kHIiWoNUtIcofwNUoOEploKTP5yGq0BCVX0LVOEIUxjD3aaQu00hAE9bCYy1kjD15HNMpDZRHaQ6duzIBx98QJcuXcJRp6hS34LUwRiiIhGgAglPoQpOcW0b1V7IoZJt+0O2LSfBKtShKlSBKtjuvrro6rvWLuQpU/r6vMpK5kVN3ikHiagOUjNnzmTBggW8+OKLJCdH7qrxdSFag1SCMTxmCnjTiucz3H79yqyPISqYVqhIBiin4SmcYcmpYENWoMHK31AVqkBVH1unRthFDDPF/MWVgieKPsdEwimqg1R+fj7nnXceX3zxBR06dCA+3ndszsqVK0NWwboWrUFqmCnmTTuP7Vh0dDXCroMgFc0hKphWqFAFqEDDUzSGJn85DVeBhKr6FqjqoqvPZ4xUENfmFIkFkQpSjmZvGzlyJCtWrOCvf/1rlYPNJfwuNsUAvGLF+xWiAhHIxJs1icYQFWwrVKgDVETCU9tmf/x/256w7OLA4/A3WFV8rGoLVeWPfW2Bqvw5rClQlb8OagpU5a+jmgJVqyS7xjCVnlx9mEpPjqs2TLWOb1htmGrtaVdlmGqWcFiVYSo1uUNpmCr7nIg3hkfKuvpusup3j4JIJDhqkWrQoAEffvghJ510UjjqFFWisUUq2Rgy7WwaAH1cDVjhx9xRsdYaFW0hKpQBKujwVDEYhVOIQlegrVX+tlL500IVqdapWGqZ6m9KWGznAjDclcJczTMl9VSkWqT8u+DUATIyMsJaqZpMmTKFDh06kJSURJ8+ffj6669rLP/GG2/QpUsXkpKS6NatG++//36Eaho+gyihAbAZixWE9oyvaGiNinSIapGWE1SISmzr9itExbVtFHiIatus8l+kVLVvB/sP9Lj9fTzTWhbU+tzU9txC6WujtpBda1dxLWP1anpN1/ReqOl9VN2Pmdrew59YcTxqlQbD5+08Ohr/rj8pIlVzFKQef/xxbrvtNjZv3hzi6tTstddeY+zYsUyYMIGVK1fSvXt3Bg0axG+//VZl+WXLlnHJJZdw+eWX89133zFs2DCGDRvGmjVrIlrvULugrFvvbSverzEOgc5iXpvaWqNiLURVp7Yvan++8MtDhN9Boq5CUyAc1i/QxyKQQFUbf8a9xWKYCkTFz4G7rCSW4aYxMMfOI0EXuBBxzFHXXpMmTcjLy6OkpISUlJRKg8337t0bsgpW1KdPH44//nieeeYZAGzbJiMjgxtuuIFx48ZVKn/xxReTm5vL/PnzvctOOOEEevTowbRp0/zaZ7R17SUaww47m1TgRFcDvgpht14kuvTCMS4qXCGqJv4EKL9Fa2ByIsDuwEC6/fzp8gtFd1+4u/pC3c3ntIsvw9issHNoiuFJK4GbXRovJfVLVA82f+KJJ0JcjdoVFRWxYsUKxo8f713mcrkYOHAgy5cvr3Kd5cuXM3bsWJ9lgwYNYt68edXup7CwkMLCQu/t7Ozs4CoeYh2x2YNFFvB1iLv1QiGYX8+xEKJCFqCCDU9tWwW3fk22ZTpfN8CB7eWPlz+BKrGt268B6f4MRg/FQHSng9BDPQDd6eDzXywXf3MlM8/O40ZTxH9MPJ/4ea1OEfmD47P2Im337t14PB7S09N9lqenp7Nu3boq18nMzKyyfGZm9V8UkyZNYuLEicFXOEzWWW4OdzWiNSakc0eFqjWqJuHo0qt2nWgNUU4DVDiDU237chqsyo81hIEqUmEq3JyGqepUF6ZqM9+K53krnvNNCe2MDXXf6C4Sc/weI5WbmxvQhgMtHy3Gjx9PVlaW9++XX36p6yr5eMLOZ6IpjMrPu1CN5fBXbWNWqhJTIaptqz/+6lLFejipSwDjqfx5HCM1bircY6acCPQ95s8PpDusJNq5GjFLM56LOOJ3kDrssMN46KGH2LFjR7VljDEsWrSIIUOG8NRTT4WkguWaN2+O2+1m586dPst37txJq1ZVf7i3atUqoPIAiYmJpKam+vxFiyRjuMoU8X+mkFi7lns0tEaFI0T5NXg6kIHZ0RKeahJMoPKDv2GqtkAV7WEq1IPPA2kxrthS/bvlojAKxn+KxCq/g9TSpUv55ptv6NixI3369OG6667jgQce4PHHH+fOO+/k/PPPp02bNvztb3/jnHPO4bbbbgtpRRMSEujVqxeLFy/2LrNtm8WLF9O3b98q1+nbt69PeYBFixZVWz7aHYeHBGAHFpv8aJOKZLdeOFqjnJylV9sXX1WCCVG1CjRAxRInoc/PUOnv2X2xEKZq4jRMBcLfKU0sYxhgSnDrDD6RgPj9Tu3cuTNvvfUWW7du5Y033uCzzz5j2bJl5Ofn07x5c3r27Mnzzz/PkCFDcLvDMwh67NixjBw5kuOOO47evXvzxBNPkJuby+jRowG47LLLOOSQQ5g0aRIAN954I/379+fxxx9n6NChvPrqq3z77bc899xzYalfuPUzpeMmluGOqUs7OG2Nqk4ou/TCFqICCVAhYB9ySMDruLZvD8m+gT+Ow9/xVG2b+T12KthxU/6MmapNq+R8vy98XGndWmY/dyLQgedV8c54DmAMn9q59MXDMFcK89EknSL+CvgnT7t27bj55pu5+eabw1GfGl188cXs2rWLu+++m8zMTHr06MGCBQu8A8q3bt2Ky/XHB1a/fv2YM2cOd955J3fccQeHH3448+bN4+ijj4543UOhtyn9slh+EJxZE4kuvToNUUEGKCfByd9tBBWw2raKyTAV7ODzujiLLxDVncHnZVkst9z0NR5GmGLma7ZzEb85mkfqYBJN80it8OynOzZDXSl86McHXai69upiAs5QTncQyiBVlyEqFOEpEEEFqkDO9PMjTPkzPUJtZ/OFe46pSM8tFYp5pbwtUsD5ppjX7Ty+wE1/d92d0SgSKlF9iRipG+0oDRdbQvi0heqSME446darjpMB5tUJ5KLDPupRiCrfp+P9BjpuqhaRGi8VjGDGSjkRinGJFX9s7S0bd9kU/bYWCYSCVIxIMYby39O/xNDTFqoBs6Hm5Es1+IsNBx6iggozIeK4DrE2eL4OhfJHhdP53vaUBalmClIiAYmdb+SDXJ5l0ciVSmtXI3Lr4Pp6keSkWy9UwtoaFaC6DlAHCmuYClGrVG38uchxTZycFepd1+G8UpH6MbKnYouURnyI+E1BKpZYFrssPWUHCuXYqOpEsjUqGlqhqhPtYcpxEA6RSHfvhVJ5kIoD0uq2KiIxJaBv5dNPP52333672vt3795Np06dgq6UxA6n4zRC2ZURKmFrjQowREW7WKijBK7QsrjSSuZFK54Ede+J+C2gILVkyRIuuugiJkyYUOX9Ho+HLVu2hKRi4muoKeY1Ty7X2oW1FxYRcWC6K4GrXClq+RYJQMDvlqlTp/LEE09w3nnnxez19GJRF2NzASUcR82neIdasBcqFjmY1DYFgojUPwEHqXPPPZcvv/yStWvXcsIJJ/Dzzz+Ho15ygMSypna1R4kcXAKdkNPfmc3Bdx6ps0wxxxqPLhEjEiBH7bdHHnkk33zzDRkZGRx//PF89NFHoa6XHKD8IsWFflxjL1pE69QHIvVBdRNyOmIMz9n5fG3ncEKEW71FYp3jjvC0tDTee+89rrzySs466ywmT54cynrJAcpbpGL3nCCRg5vTmc1DocbLwwCdsGmFoRD4lro981Ek1gTUZHDgJVIsy+Khhx6iR48eXHHFFXz88cchrZz8IXbaoUTqL6cXLo5GFbv1rjSlP9G+xE1hDF0QXSQaBNQiVd1l+UaMGMHnn3/O6tWrQ1IpqSy7LErF0hWwQnGx1XohgOvOBXV9uwgJuI7+Hn8IrrkX7PX2grlwcTQIZHxUuRbG5tqyIPVPV2ItpUXkQAFPf9C0adMq7+vRowcrVqxg+vTpIamY+CoPUqkRnt/FyQezP8LdleFEbV/C1fIjAAQimsNU2EKUH/y5cHFdqumMvUhdsLgqtV2s+BZTSAPgG9y8F1gnhYgQYJDq378/cXHVv9GaNWvGZZddFnSlpLLnrQTSXKn81YquroWQDnh1qLrulupaF2prlahK0F/iAQYK1/btURWoHNUnkGMOQRgNd2tUtHfrOfnR09LYXFPWGjXRlQjq1hMJmGZdixEFllV6jb2D+IMuqufo8ScIOGidqeswFZFAF4IuvXCrLUTFamtUB2x2YvEVbhaoNUrEEQUpiTo1ffGEW02tGiH5Mo+RMBV0gIrguCjQ2CinXfBfW3Ec6WrExa6Ug/pHmkgwFKRiRFNj84ydz5sezSYfCk6692oV4rFSFUWyqy/o/YQwRPnD8dg2P9XX1qhyJZbFNl0SRsQxy1R3Kp4AkJ2dTVpaGi5XaqXpHyIpxRiy7WwAmrtS2edHXVKTO/i17WYJh9V4f22XiantwsU1TcxZ3cWLWyXZ1a5zSHLVs2m1Sq76m6lFWvVfPmktC6pcXtMFjOPaNqr2PqD2ixh7y/l/MeOaOL2IcMiDWRjGRAV7lh6Ed2xUbd3NToJUoCGqutaomoLU/XYBv2PxTysBo5YoqaeMMdh2NllZWaSmpoZtP+oUjxF5lsWvWLTBcCgeVkTwqdvh3lpjmNpRnFNrmApUZoGrxjAViF1ZDWsMU1Up3OapNkyVbNtfc5gqDwm1Bary4BFkoKrrcVR1EaDg4ApR1XESooaYYsaZ0otNfWW5+VxfAyJBUXtuDPm57Ok61IQmYERKTV8OTqZBqO4LzMlZVTV90QY9XsrfrqttmSGdJiAiyuscpSEq67ekmAtRNQlVl15rY/OiXVqBZ6wEPrcUokSCpSAVQzaUjWM4jNgKUk45GXQe6FQIEFyYqvVLP5BxQE7CSaQ5qd+2PREPUbWJxhAVii69mi4F4zKGl+w8WmD4Dhe3W2EYJyhyEFKQiiEby56uw+sgSNV2VlCk55NyMhVCOMIU+PHlH0CQ+GOdKApUTgNegAEqFkJUbeoyRFUnO38zGMOjpoBT8ZAD/MWVokvBiISIglQM+d4qHbNzvPHvLKWqztCpSm0XNA0Fp917oWyVAuenuQcdpiC4QBXJYBXsPgM8Tn8DVDSEqGg4Q8/JuKi7TCE3lk28ebWVzP8sXZhYJFTUQR5DlpVdlT0RQ7Ix5EfZL8pgBp3vzK/+DL7qbM9PqPYMvsz85GrP4qtu8Hn5F3F1Z/LVNAAd/ggEtZ7V5+9g9CrXdRimyge0hzOMhTg8gf9TG4R71vJo7s6D2qc62IiLEuBmK4nXXFE8sa1IDNL0B7WIlukPyrU0Nr8FMOeLv1MgQO3TIEDdTIUAzqZDgOqnRABn0yKUqylQlas1UFXkJFTVNQfzQAUyqWkozsoDhahyhxkPG9QSJQeRSE1/oCBVi2gLUk6Eaj4pqD1IgcLUgQIKVOWiNVg5nEQzGgMUhK8rD+o+RA0yxfwXN5mabFMOUgpSUSJqg5Qxfl/SIZRBCsLbKlV6f/X3RTpMQR0HqnJ1EayCnHk80EvqhCpAQd22QkHdh6gzTDHz7Dy24eIUVwN2KkzJQUgTckqVGhnDbDuPnng40tWInBCGuz1FG/wOUzWpbazUzvySWsOUE6EeM1Uu67ekGsNUeQCoLVD5PYaqKjWFGqchKwyXtAlHeCoXDa1QEPquPAhtiLrQLmKmyScR+A4Xu4iiH4Ai9ZBapGoRdS1SxvCDncMR2PzFSvZ74OjB0ioF4WuZgtpbp8D/FqpyQbVURQEnF3OubwEKoiNE3WAX8rgpwAXMJY6/uFIoiobPLZE6oK69KBF1QQq4zy5gvClkLnEMdzfwa51IDzqH8IYpCE83H4QuUEHgoQqiO1g5CU3lQh2eIDQBCmI/RFnG8JAp4OayKQ6mWAncZCVhR8lnlkhdUJCKEtEYpLobDyvsHPKBVq5UckN4AWMIXasURG+YgugPVAeKZMAKJjBVFEh4AgWoQAIU/NESdaddwD1l188bbyXxqJXg9xhKkfpKQSpKRGOQwhh+tHM4HJtLrGTeCHH3HtSfMAXBtU5BaANVuVAEq2gUaHAC/8MTxEaAKr0/ciEKoIWxWWzn8rCVyGzNEyUCaLC51MSyeMuKZ5wp5AJTzBvE9gdnbYPPa5usM7PAVWOYqm0QOtQcqMq/vGsbkA7+B6oDA0csBisnoalcqMMThCZAQeRbocDZeKjGxrCv7MfdLsvFsa6GlETLjz2Rg4hapGoRlS1SwLHGw9d2DnlAW1cq2SGeCgEi2yoFddsy5d1GiFqoIPBWqgNFU7gKJjSVCyQ8QWwFqNL7IxeiBpgS5th5/J+VxHS1QIlUSV17USJagxTG8JqdxxdWHC9aCX5PgxBIkIL6F6Yg8oGqXLDB6kChClqhCElVCTQ4QWjDE9SfAAWlIcplDP9nCrnTFOIGvsTNya4GmGj6bBKJEgpSB9i7dy833HAD7777Li6XiwsuuIAnn3yShg2r/+AdMGAAn3zyic+yq6++mmnTpvm936gNUkEIR6sURC5MlZap+f5IBioIPFRB6INVXXISmiDwi0jHSoCCwMdCQc0hKt3YzLLzOI3S4DvdiucfVnLUXXNTJFooSB1gyJAh7Nixg2effZbi4mJGjx7N8ccfz5w5c6pdZ8CAARxxxBHce++93mUpKSkBPaAHe5CC2A1TEPlABc5CVbloD1dOA1NFdRmeoO4CFDgfUH6aKeElO49WGHKA66xkDSoXqYWCVAU//vgjRx11FN988w3HHXccAAsWLOCss85i27ZttGnTpsr1BgwYQI8ePXjiiScc7zvag1SKMVxoiknF8Iwr0e/1YiFMQfBdfeBfmILQB6pywQSriiIRskIRlA4UaHAC/8MThKb1CWoPUKVlQtuNB7WHqHbGZr29n3jge1xc4kphvS4+LFIrBakKXnzxRW6++WZ+//1377KSkhKSkpJ44403OO+886pcb8CAAaxduxZjDK1ateKcc87hrrvuIiUlpdp9FRYWUlhY6L2dnZ1NRkZG1AapgaaYBXYe+4B2rlTyAqhjXY6XgtCFqdIytW8nlIEK6jZURSsnoQkCC04QutYnCD5AQXhaoSq62y6gNTY3WckUROHnkEg00vQHFWRmZtKyZUufZXFxcTRt2pTMzMxq1/vzn/9M+/btadOmDd9//z23334769ev5+233652nUmTJjFx4sSQ1T3cFhPHBlwchs31ppBHrNC3KARqh3urX2GqtmvylfPn2ny1TZEAf3yp1haoyr+kawtUFb/8/Q1V1QWNWAtYTgNTRXUZnqDuAhTUHKIsY7jSFPGlFcf3ZS1P91qJmmBTJErVaYvUuHHjePjhh2ss8+OPP/L2228zc+ZM1q9f73Nfy5YtmThxItdcc41f+/v44485/fTT2bBhA4ceemiVZWKtRQrgr3YRM0w+e7E43NWIrCholSoXra1T4H8LFfjfSuXdtoPWqurURcgKRVA6UKDBCfwPTxC6AFVbeILwdeMdaTxMs/M5EQ/f4OZEVwNd5kXEoYOiRermm29m1KhRNZbp1KkTrVq14rfffvNZXlJSwt69e2nVqpXf++vTpw9AjUEqMTGRxET/xxpFgzlWPLeZQo7C5iZTyD0BtEpl528OKEztKdoQUJiqq9YpCF0LFfjfSuXd9gGhIZhgFY5QE05OAlO5QIITRLb1CUIfoKD0PZhgDONNIbebQhKA/cDLVnyt9RGRulenQapFixa0aNGi1nJ9+/Zl3759rFixgl69egGlrUu2bXvDkT9WrVoFQOvWrR3VN1rZlsU9riRet/O40RTyjElgt+XfF4wT4QxTUHvrVPkXXqgDFfjf7VfOabDy7i+ELVeRFkxgKhdocILQhqfScs677yC4AAVwsilhqp1PF0pfe/OJ43pXMtvC+B4WkdCJicHmUDr9wc6dO5k2bZp3+oPjjjvOO/3B9u3bOf3003nppZfo3bs3GzduZM6cOZx11lk0a9aM77//nptuuom2bdtWmluqJtF+1l45yxi+snM4Fpt/Wgnc5grsSy7QLj4IXzcf+N/VB/5195WW83uTAXX7lQu0+6/WOkRByApFWKoonMEJQheeILgABf4NJj/NlLDQzgUgE4sbXcm8RZzGQ4mEwEHRtReI2bNnc/3113P66ad7J+R86qmnvPcXFxezfv168vLyAEhISOCjjz7iiSeeIDc3l4yMDC644ALuvPPOujqEsDKWxQRXEjfbhcx10CUQaBcfhK9lCvzv6gP/uvtKy5X+60+gCqSVqlxVISGYcBXqEBNpTkJTuUDCE8RGgILKZ+Qtxc1XuPnecjHeSvZeO09EYkfMtEjVlVhpkQKg/KkMop6RaJmCum+d+qN8QMUBZ61VFYW65aquBROYyoUrOJWWrT08QWQC1BmmmDF2EcNdKd6pShKMoSjaP1tEYpDmkYoSMRWkDpBqjN8XM/ZZz0GYgvB29UFggQpiI1QdKBpDViiCUkWBhqZydRGeIDQB6ijj4RG7gMGU1utOK5GHXHU/VYlIfaYgFSViMUjFG8M9ppArTBG9XA0dDVqNVJiC+hGoyoU6WAWiYggLdfhxymlogsCCU2n5yIUn8C9AtTQ2E8rei26gCPiXlcADViK/azC5SFgpSEWJWAxSLmP41M7lBDx8QBznuFIcdfdFc5iC8AeqP9ZztJqPugxYkRBMYCoXaHAqXce/8AThb32CCmOgjOH2sukMyj++3yaO8a4kNuryLiIRoSAVJWIxSAF0MR6+tXNIAkZbycxyeIHTSIYpiEyggroNVQeKlZAVirBUUbiDE/gXniCEAaqCl+08RphivsHNra4kPrdi5twekXpBQSpKxGqQArjNLuBBU0g20M/VkHUOfwk7DVMQudYpcBaowHmo+mP9oFYPSKhCV6hDUW2chKY/1q2b8AT+B6gUY7jWFDHXivO2OB1hPPQ0Hl634jEx9tkhUh8oSEWJWA5SbmP4yM7lZDz8Dxd9XQ0DunxMRZEOUxD5QAXBh6o/thOSzcScYALTH9sILDhBZMMT/BGgko3hGlPELaaQlhhmWvFc7qr+ougiEjkKUlEiloMUQAtj85WdQztMUOOlILgwBZEPVBAdocp3myHfZMSFIiz9sa3AQxP4H5zAv/AEgQWoxsZwlSnkRlNEOqUfoRtwca+VyByH3egiEloKUlEi1oMUQE/jYYGdy41WEq8G+SFfV2EKggtUEFyogvAEq6r3E5HdVBLKgFT9PpwFJ6j78FTu/+wCbjWFlL+afsbiASuJ2VY8JTH6GSFSH2lmcwmZ7yw3h7oakROCD3knM6BXVP7F5SRQlX85Og1U/l7LrzpVhYBwhKtIBJpwCyYwlQskOIH/4QkcBChjvC25FtAQ+B4XT1iJzFGAEjmoqUWqFvWhRepA6camJYbVQZ6GHWzrFATXQgXBt1JB8C1VVYlU61VdC0VggsBDk3e9MIYnyxiGUsKtdiGPuRJ5t+zSS82MzbF4WKRr4olENXXtRYn6FqSONB4+sHNJBE5zNeDHKAhTEHyggugNVQeKlZAVqpBUlUgEJ/AvPIFvgEo1hlGmiGtMEYdTepbkEtyc4Q7/a0NEQkdBKkrUtyDVyBgW2rkcj4dfsTjD1YD19ShMQWgClc/2IhCu/BFoAAtnEAqE09DkXT8C4Qmgs/FwrSlipCnyjn/aBzxvJfCUlcgOzUQuElMUpKJEfQtSAE2NzUd2Lsdgk4nFIFcD1oZgtuVoC1QQ+lAF0ROsok2wgcm7nQCDE/gfnqDqyTMBvvDk0AcPAGtx8YyVwGwrwXtxYRGJLQpSUaI+BikoHeexwM6lJza7y8LUf6MoTJWL9lDls/2DIGCFKiz5bNNBcILgwlOGsbnMFPGslcDuspami+0iLjLFPONKZAlujX8SiXEKUlGivgYpgCbG5n07j+Px8Dsw0NUwJGEKojtQlQt3sKq0vxgIWuEISj7bdxiaILDgBJXDU7IxDDPFjDJFnIoHFzDWSuIpV6LjOolI9NL0BxJ2v1suBrka8J6dSwqGrYQuKJZ/iYUqUFX8Eg1VqDrwSz3cwSrcISXaBBOaygUbngC6Gg9XmyL+YopIq7B8CW5+0rgnEQmSWqRqUZ9bpMo1NIYkjLeLo+KcOaES6haqcuFoqaoo0q1WsSgUgalcoMEJqh/zBKWtrtvt/ZRPQ7sJi5esBGZZCWxWiBKp19QiJRGTY1nkVGiNusUU0drY3GolYYcoUIW6hapcOFqqKqouJByMASuUgamck+AEVYcntzGcQQl9jYcJriSgtNX1DSueZGOYVjb2SRcQFpFQUotULQ6GFqmKDjUefrBzcAMLiWOkK5ldIf7lHq7WqYrC3VJVnVgOWOEISgdyGpyg+panrsbDZaaIP5tiWpdd9+5IV0N+KhvvZxmj8CRyEFKLlNSJjZabS1wpzLDzOJMSVto5jHSl8LEVupeKz+SHYQpV4W6pqo6TMBKO8BWJUFSbYEJTuerCU4eys+7OM8V0K5s0E2A3Fq9Y8RRWaGFViBKRcFKLVC0Othapcl2Nhzl2Hl2xsYGHrUTusRLxhOkxiEQrVbm6aq2qz0IRmqCG8U7GkAgUlr3+hpli3rTzACgG3iOOl1wJfEAcxQfR+1REqqfpD6LEwRqkoPR08X+afK40xQB8RByDXSlhn18nkqGqnMKVf0IVmMrVNFAc4HDj4SJTzF9NMa9a8UwsG/uUbAwz7Tz+Y8Uz34pn30H23hSR2ilIRYmDOUiVu9AuYprJZ7yVxPMRnHOnLgLVgQ7GgBXqsFRRbcEJoIvxcIEp5nxTTPcK3Xbf4KavrncnIn5SkIoSClKl0o3NTixva1QfU8J+LH4I0QSetYmGUFWVWAxa4QxKB/InOHkZwyd2LieWXaYFSrvtPiaOV6x45lrx5B7E70ERCYwGm0tU2VnhzL1GxjDHzqMthhesBCZaiT73h0MkBqg7EUgoCXXoimQg8pe/wSnRGE6hhFOMh7usxNKAbllstFwcbzx8RBxvWfH8x4rjd833JCJRTC1StVCLVGUtjc2/7HyGUQJADvCYlcg/rcSIX+A1mkLVwSiQFqeOxmawKWawKWEAJTQoW96rwqWJ2hqb/Vhk6b0mIkFS116UUJCq3kmmhEfsAnqXdcX8isU9VhIzrPiQTeQZKAWr8Aioi+4AZ5liHrUL6FxhvBPAdiwWWHFMthJZF6EuYhE5eKhrT6Le51Yc/VwNGG6KecAU0AnDcyaftZaLr+ropVXVF77Clf+CCUwYQxdshpoSPrHcfFs291gBFp2xKQGW4eYDK54FVhyrcYX9DFARkXBTkJLgWBZvWAm8Y+K51hRxDB6+qjB5Z39Twte4ya/DL0yFK19BhaUDNDKGkynhdFPC2aaEQ8tanZ4iwRukluPmQlcKHxNHtoKTiNQzClISEkWWxROW79QILY3N+3Yu+7F43kpgqpXAr1EycLi6MFFfAlYow1JVUo3hAzuXXnh8PkQKgaXE8RV/dNXlWxbziA9rfURE6oqClIRNJ2x+xaIjhvGmkFtMIa9b8TxpJbIySsfE+BtA6ipwhTsgHaipsemDhxNM6Ti48osBZwNtsIkDNuBiiVXaZbeYOE1RICIHFQ02r4UGmwfHbQznUMKNdiEnV5gfaDlurnAlsz5KA9XBqofx0M+U0AcPvY2HwysMEN+DRStXI++16040JWzBxbYoaWUUEalIg82lXvCUdevMc8dzrPHwD1PIxaaYXnjI5I8v4G7Gww4sdutLOSIsY+iKTQ/j4WVXgnf543Y+/SsEXoB1uPjacvMZccRROkkmwBchvJC1iEis0iehRMxKy80oK4XxxqY3Hp+5gp618zkWD4uI41UrnneteA1MDqFGxnA8HvqaEvoZD30ooXHZfe+aeO9zsciKI89YfGW5+dpy8zVxuo6diEgNFKQk4nZYLt6p0BqVYgwWpS/GIZQwxJRQYvL5BjeLrTjet+L4Wq0f/jGGNhh+w6KkLADdZxcw3hRWKpoDfIWbNAxZlJZ9qGwMlIiI+Cdm+lEeeOAB+vXrR0pKCo0bN/ZrHWMMd999N61btyY5OZmBAwfy008/hbeiErA8y6KvuyFHuhoy0UrkR1zEAX3xcKcp5DpT9EdhYzjGeHAd7EP7jKGNsTnVlPB3u5B/2vks8OSyw97PVns/3St0z20tC0lbsHjFiucfVhLHuRrSzJXKIHdDtqo7VUTEsZj5mV9UVMTw4cPp27cvL7zwgl/rPPLIIzz11FPMnDmTjh07ctdddzFo0CB++OEHkpL0yzva/GS5uc9ycx9JtDM2p5kSTqOEd6w/Tp0/GpuVdg75wFrcrLZcrMHNasvN97jq1RireGPIwKYdhnbGZqkV5w0915oinjIFVa5XQunlWFaU9ci9ZiXwthXPnnr02IiIRIuYO2tvxowZjBkzhn379tVYzhhDmzZtuPnmm7nlllsAyMrKIj09nRkzZjBixAi/9qez9qLLuaaYmXYeDau5f4yVxDOu0vms2hmbgaaEbZbFNlz8gov9UfAcxhlDCwzpGH7B8gacXqaEsaaIdsamHTatMT5NxpdaybxSNjD8TFPMf+w8fsbF/3Cx3nKxDjffWy7W4qYgCo5TRKQu6ay9IG3atInMzEwGDhzoXZaWlkafPn1Yvnx5tUGqsLCQwsI/xpNkZ2eHva7iv3eseJq6UumEzdHYHGM8HG08dMPmUGz+V6HV5QRTwnMmHyr8VMgGduBiHxZ3u5JYXDb26jDjYZApYQ8WuZZFCaVnpxVjUQysx+UNPE2NzRHYJAKJGBKAJGNIBJKBpZabDWXTOvQ3JUywC2iIIRVogqFZhQqNspJ52SoNRy0xXGyKqSgf2IqLrbh8Bn1/TByNXKkUKzCJiNSpehukMjMzAUhPT/dZnp6e7r2vKpMmTWLixIlhrZsEx7YsNuBmA27mVej2SzGGkgrlfrcs3jdxtMUmA5smQCqQWjY3UnKFQHO88fBkeVdZFW20f7GSea0s8JxmSnjV5Fdbv7+R7A1SyRhOOWA6ASjtftuF5dPitBo3t1hJbLFc/ILFFlzswqryenQlClAiIlGhToPUuHHjePjhh2ss8+OPP9KlS5cI1QjGjx/P2LFjvbezs7PJyMiI2P7FubwDwsUiK55F7j+CVgNjaItNOoZUDN9UuIzJDsvFG8TTzNikUPrGiMcQD8SDz1QMWZbFRuOiEMr+LO+/+cDOCmVX4uYSK5lsy2I/Fvuw2InFXizvxJbltlmuSpfZERGR6FanQermm29m1KhRNZbp1KmTo223atUKgJ07d9K6dWvv8p07d9KjR49q10tMTCQxUV9m9VGuZbEeN+uruG+pFcdSP6dYWGTF09nt37XjfrNcvGEl1F5QRERiUp0GqRYtWtCiRYuwbLtjx460atWKxYsXe4NTdnY2X331Fddcc01Y9ikiIiIHl5g5H3rr1q2sWrWKrVu34vF4WLVqFatWrSInJ8dbpkuXLsydOxcAy7IYM2YM999/P//5z39YvXo1l112GW3atGHYsGF1dBQiIiJSn8TMYPO7776bmTNnem/37NkTgCVLljBgwAAA1q9fT1ZWlrfMbbfdRm5uLldddRX79u3jpJNOYsGCBZpDSkREREIi5uaRijTNIyUiIhJ7IjWPVMx07YmIiIhEGwUpEREREYcUpEREREQcUpASERERcUhBSkRERMQhBSkRERERhxSkRERERBxSkBIRERFxSEFKRERExCEFKRERERGHFKREREREHFKQEhEREXFIQUpERETEIQUpEREREYcUpEREREQcUpASERERcUhBSkRERMQhBSkRERERhxSkRERERBxSkBIRERFxSEFKRERExCEFKRERERGHFKREREREHFKQEhEREXFIQUpERETEIQUpEREREYcUpEREREQcUpASERERcUhBSkRERMQhBSkRERERhxSkRERERBxSkBIRERFxSEFKRERExCEFKRERERGHFKREREREHIqZIPXAAw/Qr18/UlJSaNy4sV/rjBo1CsuyfP4GDx4c3oqKiIjIQSOurivgr6KiIoYPH07fvn154YUX/F5v8ODBTJ8+3Xs7MTExHNUTERGRg1DMBKmJEycCMGPGjIDWS0xMpFWrVmGokYiIiBzsYqZrz6mlS5fSsmVLOnfuzDXXXMOePXvqukoiIiJST8RMi5QTgwcP5vzzz6djx45s3LiRO+64gyFDhrB8+XLcbneV6xQWFlJYWOi9nZ2dHanqioiISIyp0xapcePGVRoMfuDfunXrHG9/xIgR/OlPf6Jbt24MGzaM+fPn880337B06dJq15k0aRJpaWnev4yMDMf7FxERkfrNMsaYutr5rl27au1q69SpEwkJCd7bM2bMYMyYMezbt8/RPlu0aMH999/P1VdfXeX9VbVIZWRk4HKlYlmWo32KiIhIZBljsO1ssrKySE1NDdt+6rRrr0WLFrRo0SJi+9u2bRt79uyhdevW1ZZJTEzUmX0iIiLil5gZbL5161ZWrVrF1q1b8Xg8rFq1ilWrVpGTk+Mt06VLF+bOnQtATk4Ot956K19++SWbN29m8eLFnHvuuRx22GEMGjSorg5DRERE6pGYGWx+9913M3PmTO/tnj17ArBkyRIGDBgAwPr168nKygLA7Xbz/fffM3PmTPbt20ebNm0488wzue+++9TiJCIiIiFRp2OkYkF2djZpaWkaIyUiIhJDIjVGKma69kRERESijYKUiIiIiEMKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIiIiIQwpSIiIiIg4pSImIiIg4pCAlIiIi4pCClIiIiIhDClIiIiIiDilIiYiIiDikICUiIiLikIKUiIiIiEMKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIiIiIQwpSIiIiIg4pSImIiIg4pCAlIiIi4pCClIiIiIhDClIiIiIiDilIiYiIiDikICUiIiLikIKUiIiIiEMKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIiIiIQwpSIiIiIg4pSImIiIg4pCAlIiIi4pCClIiIiIhDClIiIiIiDsVEkNq8eTOXX345HTt2JDk5mUMPPZQJEyZQVFRU43oFBQVcd911NGvWjIYNG3LBBRewc+fOCNVaRERE6ruYCFLr1q3Dtm2effZZ1q5dy+TJk5k2bRp33HFHjevddNNNvPvuu7zxxht88skn/Prrr5x//vkRqrWIiIjUd5YxxtR1JZx49NFHmTp1Kj///HOV92dlZdGiRQvmzJnDhRdeCJQGsiOPPJLly5dzwgkn+LWf7Oxs0tLScLlSsSwrZPUXERGR8DHGYNvZZGVlkZqaGrb9xESLVFWysrJo2rRptfevWLGC4uJiBg4c6F3WpUsX2rVrx/LlyyNRRREREann4uq6Ak5s2LCBp59+mscee6zaMpmZmSQkJNC4cWOf5enp6WRmZla7XmFhIYWFhd7bWVlZQGmyFRERkdhQ/r0d7u/vOg1S48aN4+GHH66xzI8//kiXLl28t7dv387gwYMZPnw4V155ZcjrNGnSJCZOnFhpuTH7UZYSERGJLXv27CEtLS1s26/TMVK7du1iz549NZbp1KkTCQkJAPz6668MGDCAE044gRkzZuByVd8z+fHHH3P66afz+++/+7RKtW/fnjFjxnDTTTdVud6BLVK2bbN3716aNWsWk2OksrOzycjI4JdffglrH3G00vHr+HX8On4d/8F5/FlZWbRr165SDgi1Om2RatGiBS1atPCr7Pbt2zn11FPp1asX06dPrzFEAfTq1Yv4+HgWL17MBRdcAMD69evZunUrffv2rXa9xMREEhMTfZaF8wmIlNTU1IPyjVROx6/j1/Hr+A9WB/vx15YXgt5+WLceItu3b2fAgAG0a9eOxx57jF27dpGZmekz1mn79u106dKFr7/+GoC0tDQuv/xyxo4dy5IlS1ixYgWjR4+mb9++fp+xJyIiIlKTmBhsvmjRIjZs2MCGDRto27atz33lPZPFxcWsX7+evLw8732TJ0/G5XJxwQUXUFhYyKBBg/jXv/4V0bqLiIhI/RUTQWrUqFGMGjWqxjIdOnSoNDI/KSmJKVOmMGXKlDDWLrolJiYyYcKESt2VBwsdv45fx6/j1/Hr+MMpZifkFBEREalrMTFGSkRERCQaKUiJiIiIOKQgJSIiIuKQgpSIiIiIQwpSMWjKlCl06NCBpKQk+vTp4507qyrPP/88J598Mk2aNKFJkyYMHDiwUvlRo0ZhWZbP3+DBg8N9GI4FcvwzZsyodGxJSUk+ZYwx3H333bRu3Zrk5GQGDhzITz/9FO7DcCyQ4x8wYECl47csi6FDh3rLxMrz/+mnn3LOOefQpk0bLMti3rx5ta6zdOlSjj32WBITEznssMOYMWNGpTKBPJ51KdDjf/vttznjjDNo0aIFqamp9O3blw8//NCnzD333FPpua94Sa5oEujxL126tMrX/oHXWq2vz39V72vLsujatau3TCw9/5MmTeL444+nUaNGtGzZkmHDhrF+/fpa13vjjTfo0qULSUlJdOvWjffff9/n/lB8/itIxZjXXnuNsWPHMmHCBFauXEn37t0ZNGgQv/32W5Xlly5dyiWXXMKSJUtYvnw5GRkZnHnmmWzfvt2n3ODBg9mxY4f375VXXonE4QQs0OOH0ll9Kx7bli1bfO5/5JFHeOqpp5g2bRpfffUVDRo0YNCgQRQUFIT7cAIW6PG//fbbPse+Zs0a3G43w4cP9ykXC89/bm4u3bt393s6k02bNjF06FBOPfVUVq1axZgxY7jiiit8woST11NdCfT4P/30U8444wzef/99VqxYwamnnso555zDd99951Oua9euPs/9559/Ho7qBy3Q4y+3fv16n+Nr2bKl9776/Pw/+eSTPsf9yy+/0LRp00rv/Vh5/j/55BOuu+46vvzySxYtWkRxcTFnnnkmubm51a6zbNkyLrnkEi6//HK+++47hg0bxrBhw1izZo23TEg+/43ElN69e5vrrrvOe9vj8Zg2bdqYSZMm+bV+SUmJadSokZk5c6Z32ciRI825554b6qqGRaDHP336dJOWllbt9mzbNq1atTKPPvqod9m+fftMYmKieeWVV0JW71AJ9vmfPHmyadSokcnJyfEui6Xnvxxg5s6dW2OZ2267zXTt2tVn2cUXX2wGDRrkvR3s41lX/Dn+qhx11FFm4sSJ3tsTJkww3bt3D13FIsSf41+yZIkBzO+//15tmYPp+Z87d66xLMts3rzZuyxWn39jjPntt98MYD755JNqy1x00UVm6NChPsv69Oljrr76amNM6D7/1SIVQ4qKilixYgUDBw70LnO5XAwcOJDly5f7tY28vDyKi4tp2rSpz/KlS5fSsmVLOnfuzDXXXFPrxaTrgtPjz8nJoX379mRkZHDuueeydu1a732bNm0iMzPTZ5tpaWn06dPH78c0UkLx/L/wwguMGDGCBg0a+CyPhec/UMuXL/d5rAAGDRrkfaxC8XjGEtu22b9/f6X3/k8//USbNm3o1KkTf/nLX9i6dWsd1TA8evToQevWrTnjjDP44osvvMsPtuf/hRdeYODAgbRv395neaw+/1lZWQCVXs8V1fYZEKrPfwWpGLJ79248Hg/p6ek+y9PT0yv1+1fn9ttvp02bNj4vnMGDB/PSSy+xePFiHn74YT755BOGDBmCx+MJaf2D5eT4O3fuzIsvvsg777zDyy+/jG3b9OvXj23btgF41wvmMY2UYJ//r7/+mjVr1nDFFVf4LI+V5z9QmZmZVT5W2dnZ5Ofnh+T9FEsee+wxcnJyuOiii7zL+vTpw4wZM1iwYAFTp05l06ZNnHzyyezfv78OaxoarVu3Ztq0abz11lu89dZbZGRkMGDAAFauXAmE5vM0Vvz666988MEHld77sfr827bNmDFjOPHEEzn66KOrLVfdZ0D58xuqz/+YuESMhMZDDz3Eq6++ytKlS30GXI8YMcL7/27dunHMMcdw6KGHsnTpUk4//fS6qGrI9O3bl759+3pv9+vXjyOPPJJnn32W++67rw5rFnkvvPAC3bp1o3fv3j7L6/PzL6XmzJnDxIkTeeedd3zGCA0ZMsT7/2OOOYY+ffrQvn17Xn/9dS6//PK6qGrIdO7cmc6dO3tv9+vXj40bNzJ58mRmzZpVhzWLvJkzZ9K4cWOGDRvmszxWn//rrruONWvWRM14LrVIxZDmzZvjdrvZuXOnz/KdO3fSqlWrGtd97LHHeOihh1i4cCHHHHNMjWU7depE8+bN2bBhQ9B1DqVgjr9cfHw8PXv29B5b+XrBbDNSgjn+3NxcXn31Vb8+HKP1+Q9Uq1atqnysUlNTSU5ODsnrKRa8+uqrXHHFFbz++uuVujkO1LhxY4444oiYf+6r07t3b++xHSzPvzGGF198kUsvvZSEhIQay8bC83/99dczf/58lixZQtu2bWssW91nQPnzG6rPfwWpGJKQkECvXr1YvHixd5lt2yxevNin1eVAjzzyCPfddx8LFizguOOOq3U/27ZtY8+ePbRu3Tok9Q4Vp8dfkcfjYfXq1d5j69ixI61atfLZZnZ2Nl999ZXf24yUYI7/jTfeoLCwkL/+9a+17idan/9A9e3b1+exAli0aJH3sQrF6ynavfLKK4wePZpXXnnFZ8qL6uTk5LBx48aYf+6rs2rVKu+xHQzPP5Se7bZhwwa/fkRF8/NvjOH6669n7ty5fPzxx3Ts2LHWdWr7DAjZ539Aw+Slzr366qsmMTHRzJgxw/zwww/mqquuMo0bNzaZmZnGGGMuvfRSM27cOG/5hx56yCQkJJg333zT7Nixw/u3f/9+Y4wx+/fvN7fccotZvny52bRpk/noo4/Mscceaw4//HBTUFBQJ8dYk0CPf+LEiebDDz80GzduNCtWrDAjRowwSUlJZu3atd4yDz30kGncuLF55513zPfff2/OPfdc07FjR5Ofnx/x46tNoMdf7qSTTjIXX3xxpeWx9Pzv37/ffPfdd+a7774zgPnnP/9pvvvuO7NlyxZjjDHjxo0zl156qbf8zz//bFJSUsytt95qfvzxRzNlyhTjdrvNggULvGVqezyjSaDHP3v2bBMXF2emTJni897ft2+ft8zNN99sli5dajZt2mS++OILM3DgQNO8eXPz22+/Rfz4ahPo8U+ePNnMmzfP/PTTT2b16tXmxhtvNC6Xy3z00UfeMvX5+S/317/+1fTp06fKbcbS83/NNdeYtLQ0s3TpUp/Xc15enrfMgZ9/X3zxhYmLizOPPfaY+fHHH82ECRNMfHy8Wb16tbdMKD7/FaRi0NNPP23atWtnEhISTO/evc2XX37pva9///5m5MiR3tvt27c3QKW/CRMmGGOMycvLM2eeeaZp0aKFiY+PN+3btzdXXnllVH6QlAvk+MeMGeMtm56ebs466yyzcuVKn+3Ztm3uuusuk56ebhITE83pp59u1q9fH6nDCVggx2+MMevWrTOAWbhwYaVtxdLzX346+4F/5cc7cuRI079//0rr9OjRwyQkJJhOnTqZ6dOnV9puTY9nNAn0+Pv3719jeWNKp4No3bq1SUhIMIcccoi5+OKLzYYNGyJ7YH4K9Pgffvhhc+ihh5qkpCTTtGlTM2DAAPPxxx9X2m59ff6NKT2VPzk52Tz33HNVbjOWnv+qjh3weU9X9fn3+uuvmyOOOMIkJCSYrl27mvfee8/n/lB8/ltlFRQRERGRAGmMlIiIiIhDClIiIiIiDilIiYiIiDikICUiIiLikIKUiIiIiEMKUiIiIiIOKUiJiIiIOKQgJSIiIuKQgpSIHHT27NlDy5Yt2bx5c1DbGTFiBI8//nhoKiUiMUlBSkRi0qhRo7AsC8uyiI+Pp2PHjtx2220UFBTUuu4DDzzAueeeS4cOHYKqw5133skDDzxAVlZWUNsRkdilICUiMWvw4MHs2LGDn3/+mcmTJ/Pss88yYcKEGtfJy8vjhRde4PLLLw96/0cffTSHHnooL7/8ctDbEpHYpCAlIjErMTGRVq1akZGRwbBhwxg4cCCLFi2qcZ3333+fxMRETjjhBO+ypUuXYlkWH374IT179iQ5OZnTTjuN3377jQ8++IAjjzyS1NRU/vznP5OXl+ezvXPOOYdXX301LMcnItFPQUpE6oU1a9awbNkyEhISaiz32Wef0atXryrvu+eee3jmmWdYtmwZv/zyCxdddBFPPPEEc+bM4b333mPhwoU8/fTTPuv07t2br7/+msLCwpAdi4jEjri6roCIiFPz58+nYcOGlJSUUFhYiMvl4plnnqlxnS1bttCmTZsq77v//vs58cQTAbj88ssZP348GzdupFOnTgBceOGFLFmyhNtvv927Tps2bSgqKiIzM5P27duH6MhEJFYoSIlIzDr11FOZOnUqubm5TJ48mbi4OC644IIa18nPzycpKanK+4455hjv/9PT00lJSfGGqPJlX3/9tc86ycnJAJW6/ETk4KCuPRGJWQ0aNOCwww6je/fuvPjii3z11Ve88MILNa7TvHlzfv/99yrvi4+P9/6//GzAiizLwrZtn2V79+4FoEWLFk4OQURinIKUiNQLLpeLO+64gzvvvJP8/Pxqy/Xs2ZMffvghZPtds2YNbdu2pXnz5iHbpojEDgUpEak3hg8fjtvtZsqUKdWWGTRoEGvXrq22VSpQn33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", 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", 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", 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", 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", 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feJq8vDzfv++8805OP/10unXrxqGHHsrw4cO54IILOOyww/z2V3U6c3XZ2dnsv//+Nb74srOz+e2333y/e71eHn30Uf7xj3/w66+/+sYIQfDuSagIjQB79uwJup5dgc7WrO22n376Cfh9jNq+qtpaJdBj1rx5c7/HJlxTpkzB5XJx991343a7eeaZZxgzZgxNmjTh0UcfBSrGq/Tv39/2fVSx+9jX9X5q374906dP5x//+Ac//fQT7733Hvfffz+333477du3D/tsvHXr1gEVIX5fBx98MO+99x4FBQU0atTItzzY876vbt26MXv2bDweDz/88APz5s3jgQce4NJLL6VLly5+nwnVxxxV2fc5X7duXcDn5+CDD/bdHkmQ6tGjBz169ADgwgsv5MQTT+TUU0/lyy+/xLKsGt1x1RUXFwM1u+g6derkGyd23nnncemllzJ06FBWr17tW/fJJ5+kqKiIG264gRtuuAGAP//5zxxwwAG8/vrrtZ6NOWfOHFq0aMGIESNsH7NETkFK6rWDDjoo7AB39dVXM3PmTMaPH8+AAQPIzs7GsixGjx7tN1Zh0KBBrFmzhjfffJP58+fzr3/9i6lTpzJjxgy/L7RAFbpgy6sHt3vvvZfbbruNv/zlL9x11120aNECl8vF+PHjg46bAHxfCCtWrAjpFPDaqhnVw1t1tU1fEei2qrbOnj3bb/6wKqmp/h9FtT02kfj888/p06ePL0hfcMEFbN26lRtvvJEmTZowevRoFi9ezGuvvRbxfYX72IfLsiy6detGt27dOPnkkznooIOYM2dOTKY1CPa81yYlJYVevXrRq1cvBgwYwHHHHcecOXP83puhvB9i7eyzz+ayyy7jf//7H927d6d9+/ZARSVvX1u2bPHNFVbXPv/5z3/y8ccfM2zYMKDiD6g333yT9evXs3btWl/4GjhwIK1bt6ZZs2Y19rN+/Xo++eQTLr30UtLS0iI/WLFNQUpkH6+++ipjxozh4Ycf9i0rLi6ucfYOQIsWLRg3bhzjxo1j7969DBo0iDvuuMOxL7RXX32V4447jqefftpv+e7du2nVqlXQbUeMGEFKSgr//ve/Qxr03Lx584DHWFW1iMQBBxwAVJyt5VRlMtxuLMuyanTZ3XDDDWzdupV77rmHOXPm0LdvX04//fSI2xbuYx+Jrl270rx584Bf7nWpqpSsXr26xm2rVq2iVatWftUoJ1RV3Oy2t7a2Vt0O4b82alPVpVZVid5vv/1o3bp1wIlsv/rqq5BC8777rK5jx46+ytzu3btZsmQJZ511VsD9vPDCCxhj1K2XAHTWnsg+UlJSavwV/Pjjj9eozOx7dmLjxo058MADHT0bMVBbXnnlFTZt2lTntjk5OVxyySXMnz+fxx9/vMbtXq+Xhx9+mI0bNwIVYScvL4/vvvvOt86WLVt8Z0NFYtiwYTRt2pR7772XsrKyGrfvOyt0KLKysgAChr9Ahg4dyk8//VRjnNV9993HIYccwtq1aznttNN8UyREItzHPhRffvklBQUFNZZ/9dVX7Ny5M2D3XF3at29Pnz59ePbZZ/0ex5UrVzJ//nxOOumksPdZ5ZNPPgn4XFeNu7LT3pNOOomvvvqKxYsX+5YVFBTw1FNP0blzZ9+YvarwF+prY9u2bTWWlZWV8dxzz5GZmek3FvCss85i3rx5fqF84cKF/O9//2PUqFG+ZbW9pqvG5B1++OFB2zRx4kTKy8u59tprA97+/PPP07Fjx6BTUEhsqCIlEXnnnXd8fw1WN3DgQLp27RqHFkXulFNOYfbs2WRnZ3PIIYewePFi3n///Rpjkg455BCGDBnCEUccQYsWLfjmm2949dVXawyqj7Qtd955J+PGjWPgwIGsWLGCOXPmhPzYPvzww6xZs4a//e1vvP7665xyyik0b96c9evX88orr7Bq1SpGjx4NwOjRo7n55ps544wz+Nvf/kZhYSHTp0+nW7dudQ5sr0vTpk2ZPn06F1xwAYcffjijR4+mdevWrF+/nrfeeotjjjmGJ554Iqx9Vn3BvfTSS3Tr1o0WLVpw6KGH1jpGZuLEibzxxhuMGTOGBQsWMHDgQPbu3csLL7zAr7/+ylFHHcXdd9/NgAEDOPHEE+u8/4ULF/rGxVQ3cuRIDj300LAe+1DMnj2bOXPmcMYZZ3DEEUeQnp7Ojz/+yDPPPENGRoZveoNwPfjgg4wYMYIBAwZw0UUXUVRUxOOPP052dnZE16C8//77WbJkCWeeeaZv3ODSpUt57rnnaNGiRcD5teoyYcIEXnjhBUaMGMHf/vY3WrRowbPPPsuvv/7Ka6+95gvBBxxwAM2aNWPGjBk0adKERo0a0b9//1rHd1122WXk5+czaNAg9ttvP3Jzc5kzZw6rVq3i4Ycf9hujdMstt/DKK69w3HHHcc0117B3714efPBBevXqxbhx43zr3XPPPXz22WcMHz6cjh07smvXLl577TW+/vprrr76ar+rP9x3332+8Xmpqam88cYbzJ8/n7vvvts3J1Z1K1eu5LvvvmPChAmOVd8kAvE8ZVCSV7DTtdnntGMSaGbzQNjnFPrffvvNjBs3zrRq1co0btzYDBs2zKxatcp06tTJjBkzxrfe3Xffbfr162eaNWtmMjMzTY8ePcw999xjSktLfeuMGTPGNGrUqMZ9Dh482PTs2bPG8n1neC4uLjbXX3+9ad++vcnMzDTHHHOMWbx4sRk8eHDIj0d5ebn517/+Zf7whz+Y7Oxsk5aWZjp16mTGjRtX4/T8+fPnm0MPPdSkp6eb7t27m3//+9+1Tn8Q6Dmta4buDz/80AwbNsxkZ2ebjIwMc8ABB5ixY8eab775xrdObY9ZoHZ8/vnn5ogjjjDp6ekhTYWwY8cOc9VVV5mcnByTmppq2rVrZy688EKzatUqk5+fb3r06GGaNm1qVqxYUes+ql5btf3Mnj3bt26oj30oM5t/99135sYbbzSHH364adGihUlNTTXt27c3o0aNMkuXLg163MbUPv2BMca8//775phjjjGZmZmmadOm5tRTTzU//PCD3zp1vUf39dlnn5krr7zSHHroob5j79ixoxk7dqxZs2aN37q1zWwe6HW+Zs0ac/bZZ5tmzZqZjIwM069fPzNv3rwa27755pvmkEMOMampqXVOhfDCCy+YoUOHmrZt25rU1FTTvHlzM3ToUPPmm28GXH/lypXmxBNPNFlZWaZZs2bm/PPPN7m5uX7rzJ8/35xyyimmQ4cOJi0tzTRp0sQcc8wxZubMmX4zmBtjzLx580y/fv1MkyZNTFZWljn66KPNyy+/XGt7J0yYYADz3Xff1bqOxI5lTBxH8omIiIgkMY2REhEREbFJQUpERETEJgUpEREREZuSJkhNmTKFo446iiZNmtCmTRtGjhwZcD6Rfb3yyiv06NGDjIwMevXqFfCSByIiIiJ2JE2Q+uijj7jyyiv54osvWLBgAWVlZZx44okB51Wp8vnnn3Peeedx0UUXsWzZMkaOHMnIkSNZuXJlDFsuIiIi9VXSnrW3fft22rRpw0cffcSgQYMCrnPuuedSUFDAvHnzfMuOPvpo+vTpw4wZM2LVVBEREamnknZCzqrp9atfsXxfixcv5rrrrvNbNmzYMN54441atykpKfGbmdrr9bJr1y5atmypic9ERESShDGGPXv20KFDB0euWFCbpAxSXq+X8ePHc8wxxwS90ndubi5t27b1W9a2bVtyc3Nr3WbKlClMnjzZsbaKiIhI/GzYsIH9998/avtPyiB15ZVXsnLlSj799FPH9z1x4kS/KlZeXl7lRSQbqSIlIiKSJCpGLhXQpEmTqN5P0gWpq666innz5vHxxx/XmTDbtWvH1q1b/ZZt3bqVdu3a1bqN2+3G7XbXWG5ZloKUiIhIEjGGqH93J81Ze8YYrrrqKubOncsHH3xQ68UnqxswYAALFy70W7ZgwQIGDBgQrWaKiIhIA5I0Fakrr7yS559/njfffJMmTZr4xjllZ2eTmZkJwIUXXsh+++3HlClTALjmmmsYPHgwDz/8MCeffDIvvvgi33zzDU899VTcjkNERETqj6SpSE2fPp28vDyGDBlC+/btfT8vvfSSb53169ezZcsW3+8DBw7k+eef56mnnqJ37968+uqrvPHGG0EHqIuIiIiEKmnnkYqV/Px8srOzsazGGiMlIiKOycrKpFUrTa1jhzGGHTt2UlhYFHQdY/aSl5dH06ZNo9aWpOnaExERqQ8sy2Ls2PM57bQRpKWlKUjZYIyhrKyM//znHWbNmkM8a0IKUiIiIjE0duz5jB59Ns2aZce7KUlv9OizAZg5899xa0PSjJESERFJdo0aZXHaaSMqQ5Slnwh/mjXL5rTTRpCVlRn2c+EUBSkREZEYadmyBWlpafFuRr2SlpZGq1Yt43b/ClIiIiIxosmdnRfvx1RBSkRERMQmBSkRERERm3TWnoiIiNTpjjsmsXfvHh566O8Bb1+9ehUzZz7DsmXL2Lt3L23btuXww4/gggsupFOnTmzevJnTTz+1xnbDh4/grrvuxuPxMHv2c8yb919yc3Nxu93k5OQwcuQZjBx5RrQPzzYFKREREYnIJ598zM0338TRRw/gzjvvZv/99+e333bx/vvvM2PGdKZMuc+37rRp0+natavv94wMNwD//OdTzJ37OjfeeBMHH3wIBQUF/PjjD+Tn58f8eMKhICUiIiK2FRcXceedkznmmGN48MGHfcv3228/Dj20F3v27PFbPzs7m1atWtXYz8cff8zZZ49i6NATfMu6desWvYY7REFKREQkAbiKglzuxOXCuN2hrWtZmIyMoOt6M52bd2nx4sXs3r2bCy4YE/D2Jk2ahLSfli1b8vXXX3P22aNo3ry5Y+2LNgUpERGRBHD4oGNrvW33Mcfw8yOP+X7vfeJQUoqLA6675/AjWP3kU77fe512Cmm7d/ut883XSyJrbDUbNmwAoHPnziGtf9FF43C5fj/X7Z///Bfdu/fg2muvY8KEmxg+/ES6du3KYYf1ZtCgwRxzzDGOtTUaFKRERETEtnCvc3fvvffRpUsX3+9t27YFoGvXrrz44sv8+OOPfPvttyxbtpTrr7+WU045hVtvvd3RNjtJQUpERCQBLP3401pvMy7/2Yq+nf9+7evuMznliv/Mi6xhdejYsSMAa9eu5bDDDqtz/bZt25KTkxPwNpfLRc+ePenZsyd/+tOfePvtt5k06TbGjbuI/fbbz9F2O0XzSImIiCQAb2ZmrT/Vx0fVuW618VG1reuko48eQLNmzZg9+9mAt+872DwcXbtWVK6KgowJizdVpERERCQke/fuZfXq1X7LsrOzufXW25gw4Wauu+5azj13NDk5OezevZv3319Abm4u9947pc5933zzTfTu3ZvDDjuMli1bsXnzJqZNe4KOHTuFPP4qHhSkREREJCRLlizhz3/+k9+y008/nVtvvZ2nn57JrFkzue22/6OgoIC2bdty5JFHcfnlV4S076OPPpr5899j1qyZ7N27l5YtW3LkkUdx6aWXkZqauHHFMuGOEmtg8vPzyc7OxrIa60KTIiISkU6dcvjHP/5eOY+SvlMiZ9ixYwdXXHEd69Zt8L/FGIzZS15eHk2bNo1aCzRGSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKREQkRioGQOscLyfF+zFVkBIREYmRnTt3UVZWFu9m1CtlZWXs2LEzbvevICUiIhIjBQWF/Oc/77B7dx5g9BPhz+7defznP+9QWBi/mc8Td4YrERGRemjWrDkAnHbaCNLS0jRHoQ3GGMrKyvjPf97xPZ7xogk566AJOUVEJBqysjJp1aqlvltsMMawY8fOoJWoWE3IqYqUiIhIHBQWFrF+/cZ4N0MipDFSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJiU1IFqY8//phTTz2VDh06YFkWb7zxRtD1Fy1ahGVZNX5yc3Nj02ARERGp15IqSBUUFNC7d2+mTZsW1narV69my5Ytvp82bdpEqYUiIiLSkCTVzOYjRoxgxIgRYW/Xpk0bmjVr5nyDREREpEFLqoqUXX369KF9+/accMIJfPbZZ0HXLSkpIT8/3+9HREREJJB6HaTat2/PjBkzeO2113jttdfIyclhyJAhLF26tNZtpkyZQnZ2tu8nJycnhi0WERGRZGIZY0y8G2GHZVnMnTuXkSNHhrXd4MGD6dixI7Nnzw54e0lJCSUlJb7f8/PzycnJwbIa6wrdIiIiScIYgzF7ycvLo2nTplG7n6QaI+WEfv368emnn9Z6u9vtxu12x7BFIiIikqzqdddeIMuXL6d9+/bxboaIiIjUA0lVkdq7dy8///yz7/dff/2V5cuX06JFCzp27MjEiRPZtGkTzz33HACPPPIIXbp0oWfPnhQXF/Ovf/2LDz74gPnz58frEERERKQeSaog9c0333Dcccf5fr/uuusAGDNmDLNmzWLLli2sX7/ed3tpaSnXX389mzZtIisri8MOO4z333/fbx8iIiIidiXtYPNYyc/PJzs7W4PNRUREkkisBps3uDFSIiIiIk5RkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMSmpApSH3/8MaeeeiodOnTAsizeeOONOrdZtGgRhx9+OG63mwMPPJBZs2ZFvZ0iIiLSMCRVkCooKKB3795MmzYtpPV//fVXTj75ZI477jiWL1/O+PHjufjii3nvvfei3FIRERFpCCxjjIl3I+ywLIu5c+cycuTIWte5+eabeeutt1i5cqVv2ejRo9m9ezfvvvtuSPeTn59PdnY2ltUYy7IibbaIiIjEgDEGY/aSl5dH06ZNo3Y/SVWRCtfixYsZOnSo37Jhw4axePHiOLVIRERE6pPUeDcgmnJzc2nbtq3fsrZt25Kfn09RURGZmZk1tikpKaGkpMT3e35+ftTbKSIiIsmpXlek7JgyZQrZ2dm+n5ycnHg3SURERBJUvQ5S7dq1Y+vWrX7Ltm7dStOmTQNWowAmTpxIXl6e72fDhg2xaKqIiIgkoXrdtTdgwADefvttv2ULFixgwIABtW7jdrtxu93RbpqIiIjUA0lVkdq7dy/Lly9n+fLlQMX0BsuXL2f9+vVARTXpwgsv9K3/17/+lV9++YWbbrqJVatW8Y9//IOXX36Za6+9Nh7NFxERkXomqYLUN998Q9++fenbty8A1113HX379uX2228HYMuWLb5QBdClSxfeeustFixYQO/evXn44Yf517/+xbBhw+LSfhEREalfknYeqVjRPFIiIiLJR/NIiYiIiCQ4BSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERm1Lj3QCRZJBuDM0xNMOQAXxrpfhuG2jK6VS53I0BqPxvxf+fJg2PZfnW7YihCCjCorjy/1W/r8XyrSsiIolPQUoapFRjaIehPYYOeGkKzLbSfLc/5i1mMB6aUxGgsqptWwpkWk18v99gyjid8lrva5aVhqfy35eaMi4Ism4HqxFbqQhSt3tLOINyfsNiNxa/Ab9h8Ztl8RsWs0ljT2XoamEMLgw7sTAKYiIiMaMgJfVWmjGUVQsVd3pLGEo5nTG0xvj1axcBs0mFyvVzMByK129/XiAPKMDCMsYXWJbjohEpFAOl/H5/VrXtqvxguVhoUsjEkAlkgO/fmRh+q7b9AXg5bJ82AL5y12tWKnuqQpcp4WrKKANyjcUWLHJxsQWLLZbFNNLZVdlelzF4FbZERBxhGWNM3as1XPn5+WRnZ2NZjbH05ZOYjGE/DP3w0M946YuHbngrqklWY184esVbxJnVqkFlwBYsNleGjj9ZGZRUrnuk8ZBdGWx+w2IXFvkQ02rPgcZL56rjqPoxhuZAcwx/tjIorWzPDG8xl1BW6746WI3YalVExwe9xYyjjHW4WI+LdViss1z8isX/cLEal7oXRSTpGWMwZi95eXk0bdo0avejIFUHBanENslbwsWU0YHAL+P9rUZsqQwQg005LTH8gotNWOyoZ91gqcbQtrK7suLHS3tT8e8rLLevCvWyt4izgnQv5liN2Fz5mJ1uyuiK4Sdc/EhF2FI1S0SSQayClLr2JOFZxtAXLyMoZ6jxcKqVyd7KL/N0oAOGcmAFLr4mhW+sii/91bjYaf3egfeRVb9f7uWWxSYsNlVfGCDz/MXKYDJeOmHoiJdOxtAJL13x0gHD5mobnW/K/UJXEfCDcfEDLr63XDxOOsUKViLSgKkiVQdVpOKjuTGcSDnDTTnD8NC2WsXpTCuDNysHhh9ovLTByzJSKNLz47i/mlIGGw8H4aUHXjKr3VYENLUa+ypUt5gS9jOG7ywX35LCClwU6DkRkThRRUoarHNMGbNNsd+Lcw/wPqm8a6WwmN+nHvjZcvGzpkOLmhlWOjMqs5DLGLpi6ImHnnhpbPDr5htlyisGx1dmXi+wxlisIIUllov7SPeNVxMRqS9UkaqDKlLR1cgYTqOcTVh8XNn11tl4WWMKWImLd0jhXSuVz0jxOwMvmWW528flfgtLtkR1/2ebMg43Xnrj4bDKbsIqP+Cil6uR7/eHvcWUAcutFJbh4idcGnslIo5SRaoW06ZN48EHHyQ3N5fevXvz+OOP069fv4Drzpo1i3Hjxvktc7vdFBcXx6KpUosMYziZcs4x5ZxEOVnAf0nxBam1losuNGK9lTyVpniFo3DYaWM44etVK41Xq2WhVsZL78opHIqqrecyhospozGAqTjTMB/4yqTwFSl8ZKXwfj0fzyYi9UdSfVq99NJLXHfddcyYMYP+/fvzyCOPMGzYMFavXk2bNm0CbtO0aVNWr17t+11VpfhpbbxcYcq4gjJaVatW/A+Lr6vNFA4kXIhKhqAUDaEcd21ha4flYiEuFu6zPBW4wXLTx3jpU1m9agoMxcNQPPQ2/kHqElPKN6TwrapWIpKAkqprr3///hx11FE88cQTAHi9XnJycrj66quZMGFCjfVnzZrF+PHj2b17t+37VNeecz73FtC/coLJ9Vi8SBovWaksx5VQY2caamiKlrqqWinGcAhejsZDf+PhCyuFf1npAHQwXjaYAgB2A5+RwkdWKh+TwlLNdyUiQahrbx+lpaUsWbKEiRMn+pa5XC6GDh3K4sWLa91u7969dOrUCa/Xy+GHH869995Lz549Y9HkBu9o4/E7c2u6lY5lSnnYSmcuqQnxJajQFH21PcZVActjVQxIX0EK/9znJdEYeJsUjsFDM+BkPJxsKi64swe4FTdPVIYuEZF4SJogtWPHDjweD23btvVb3rZtW1atWhVwm+7du/PMM89w2GGHkZeXx0MPPcTAgQP5/vvv2X///QNuU1JSQklJie/3/Px85w6igehvPNxtSvgjHq6x3DxBxRfdv0lltpUa1+pTMgWnpu7Ar9FYyC/ZGPX7CPRc7Fu9+p/l4lQrC5cx9MbLYDwMNh6OpZwWwI5qc14dZTzcY0r42ErhY1L4khTfTPUiItGSNEHKjgEDBjBgwADf7wMHDuTggw/mySef5K677gq4zZQpU5g8eXKsmlivtDNeppgSLqycwLEUaGWMb1LIeMwinkjBKZ7BKFx22upE+ApWvVpGCstI4RGrYpLWXnhZV23qiz9SzvF4OL6yYlUMfGlSWEQKC6xUvlJXoIhEQdIEqVatWpGSksLWrVv9lm/dupV27dqFtI+0tDT69u3Lzz//XOs6EydO5LrrrvP9np+fT05Ojr1GNxDpxvA3SrnVlNKkctksUrnDcrMhDoPG4xmekiksOS2UY7cbtgI9p9/tU716iTTyLItBxsMgPLTHVFSw8DDJlDLYyuTTyo+8fS9oLSJiV9IEqfT0dI444ggWLlzIyJEjgYrB5gsXLuSqq64KaR8ej4cVK1Zw0kkn1bqO2+3G7XY70eQG4x+mmHGVVagvcDHeyqhxFl60xTo8NeTAFIlgj1u4IWvf53wbMKNkS8UEosZwEIbBlHO88XAUHr6oNpHr300JQ005C0jlPSuVhaToUjciYkvSBCmA6667jjFjxnDkkUfSr18/HnnkEQoKCnxzRV144YXst99+TJkyBYA777yTo48+mgMPPJDdu3fz4IMPsm7dOi6++OJ4Hka984iVzlDj4XbLzWxSY9aFF8vwlCjBqYWVGNXRXWaD4/us7TEOJ2BVf01sAp4H/lWyBYzxG5t3HB66YehGGVeaMgqA+SaV/1ipzCOVXQpVIhKipApS5557Ltu3b+f2228nNzeXPn368O677/oGoK9fvx6X6/eupN9++41LLrmE3NxcmjdvzhFHHMHnn3/OIYccEq9DSH7GcDVl5BgvN7kyAFhppXAgjSiPwZdPrMJTrINTogSkUIXT3khDV6Dnwm64qhrMPsDK4jjKOdF4OIVycjCcQTlnmHJ+weIgGiXUlBwikriSah6peNA8Ur9ragxPm2LOpJxy4GCrEb/EaAxUtANULIJTsoWlWHKiwhVu16DvDEFjOBwvp5lyTqOcT0jhmso/ElKM4QNTxMek8B8rlW9wxeWkCREJX6zmkVKQqoOCVIU+xsNLpogDMZQC11tu/kFa1P9qj1aAimZwSsTA1MrbOuxtdri2R6El4YskZIUTrqqCVYoxvrP7BptyPjC/X+BmMxb/paIL8ENNryCS0BSkEkSDD1LGcAllPGJKyADWYjHayozqYPJkCk+xCk12glCiiFYgsxOwwg1WTY3hFMo5zZQznHLfWalQMSHoX60MXrTSwm6HiESfglSCaOhBaoa3mEuouLDsPFIYa2XyWxQfB6dDlNPhKVrBKZmDklOcCFzhhqtwglV58WaG4OE0U86plLM/hn5WFksq/6joaTy0wPApKer+E0kAClIJoqEHqb+YUqabEv7PSudh0qP2BZGoAcrp4KTAZE8kISuccBVqsCos3szheFla7TqRz3iLGEM5a7F4njTmWKmsivE0ICLyOwWpBNEQg5RlzO+ByRi6YfhflAaVOxmgEi08xSo0tUnLjMn9RGJbWVHdK9lgJ2A5HayqxlZN9RYzljKqf1wvwcUcK42XSCU3DpPTijRkClIJoqEFqT+acu41JZxmZbItih/8iRagnAhP0QhOyRCSnORE4IpWuAolVHmLN3Mq5ZxvyhiOh6rRUz/goperUdjtEhH7FKQSREMKUieacl43RWQCj5HGtZWngDvNqRAVaYCKNDw5FZwaWliyK5KQFU64CrViVVewyizexKjKUPWulco9VsUVE9zGMM0U84qVxvuk6Pp/IlGiIJUgGkqQOsmU86opwg38lxTOsTIpdfh4EyFARRKeIg1O0QxMLTKSZ27dXcXlju/TTsgKNVw5Ua0qKt7s6y4/y5TxsikGYBMWT5PGv6w0NqnrT8RRClIJoiEEqdNMGS+ZYtKBuaRynpXh+AVdnQhR8QhQkYQnJ4NTMgUlJzgRtsINV04Fq7pCVafijfzVlHEu5bSm4uO3HJhHKk9aaSzQWX8ijlCQShD1PUidZcqYY4pJA14mlQusDEcv9ZKMAcpueIo0OMUjLLV0O/dc7yyJzUdJJCErnHAVSrCKJFSlGcPwkg1casoYgse3/FArix91tp9IxBSkEkR9DlKNjWGFKaAjhudJZayV4eh4jUhDlN0AFcvqUyThycng5GQgiiUnw5edgOVksIokVHUq3shlpozOeBnpyvIt/4spZSkpLFewEgmbglSCqM9BCqC98fIXyphCOl6Hji+ZAlSswlOkoSlZg5ITIg1b4QSsUINVtEKV7/p/QBvjZa0pwA18RAqPWWn8h1TH3qci9Z2CVIKo70HKackSosINUOGGp0iCU7RCU0t3fN7qO0ui976xE7KcDlaRhKpgVapWxZu415RwNuW+aRR+xeJxK52ZpJGvzyORoBSkEkR9C1IuY3jBFPOalcrLDl8jLB4hKpwAlYjhyYnQFK+AFA1OhK5ohqu6glU0QlWz4k1cbsq4jFJaVi7bA5xjZTLfalgnIYiEQ0EqQdS3IHWPt4QJlFIIHGQ1cmy25UhCVCIFqGiHJ7vBqT6FJbsiCVnhhqtQglWk1araQlVtgcoUb+Z8yvibKaMrXjpbjdhR+f5NMUbzUYnsQ0EqQdSnIHWOKeOFyvlrznfwqvWxDFGJEKDCCU92gpOToalluqfuleJgZ6mzg6fthKxwwlWkwcpupSpgqDKGjiWb/K7j9563kO1YTLHS+V4D00UABamEUV+CVFfjZbkpoBHwIGlMcGDW8oYUoKIZniIJTokalJwQadgKN1yFGqyiGarCrVIVlmzhYONhpSn0LZtLKvda6SxVoJIGTkEqQdSLIGUM75oiTsDDh6RwopUZ8Zk/yR6inA5Q4YQnO8EpWoGpjbssKvvdVuLs+Lt92QlZ0QhW0QpV4QaqbsUbmWhKOZNyqjrr3yaFWy033ypQSQOlIJUg6kOQOt+U8ZwppgjobTVijQPjouwGqWiFKCcDlNPhKdzgFGloilY4iiYnglc0w5UToSoWVaru3hLGl2ziPMqpejSGWZm8r0Hp0gApSCWI+hCk7vaWMJFSbrHSub/ywqmRiEWIcroK5VSAikZ4shOckjEs2RVJyAonXCV6qAonUHX1ljKhZCOH4+Ewq5HvagWWMbr8jDQYClIJoj4EKYB+xsNSXBFf/iWRQlSiBahQw1O4wcmJ0NTSXRLxPpywsyTyIF/FTsCKR7AKFqqiHaiyjJcdpVuBikvSLDaFvGmlMpV09ibx55lIKBSkEkR9CVJOsBOi4tmVV1eIimWACic82QlOiRKUnBBJ2Ao3XDkdrKIRqpwIVIUlWzjPlPHvyrN2t2Fxl5XOk6Rp2gSpt5ImSJWUlOB2O/dXZqJJ1iDlMob7TQlPWun8HKcxUYlahXIiQDkZnsINTtEITS2yQr/mXDC7CiO7cHMwdgNWOOEq1GBVV6iKZZUq5EBlDCeVbOBuU8JBVLTvG1xcZmXoWn5SLyVskHrnnXd48cUX+eSTT9iwYQNer5dGjRrRt29fTjzxRMaNG0eHDh2i1d6YS9YgdaEpY6YpZisWnaxGlEXQ9oYUoiINUE6Hp0hCk1PhKFqcCF3hhiunQ1WkVapoV6gCVadKizdzMWXcbUpoDpQDj5DG/1nuiLv+RRJJwgWpuXPncvPNN7Nnzx5OOukk+vXrR4cOHcjMzGTXrl2sXLmSTz75hMWLFzN27FjuuusuWrcO/4KwiSYZg1S6MawyBXTCcJPl5mEr3fa+oj0myqkQlQwBKpTwZCc4JXpgsiOSkBVOuAo1WDkRquxWqaIVqJoUb2KqKeFcynmfFIZZmZAkn3EioUi4IDVgwABuvfVWRowYgctVe1fRpk2bePzxx2nbti3XXnutYw2Nl2QMUleZUh41JWzCopvViOIErUYlQ4iKNEA5HZ6cCE3Z2bENXnl5znX32QlYoQarRAlVsQ5UQ4o3sAoXv1QOAWhqDG4M2x26fJRIvCRckGqoki1INTKGn00BbTD81XLzzxhXo5wMUZF25SVygAo1PNkJTrEOSpGKJGiFG6xiHaqSJVAVlmzx/Xuat5hRlHGjlcGzpKpKJUlLQSpBJFuQusWUcJcp5ScsDq02f0y4Ej1ERVKFilaAciI8hRucYhGaslr9/oVeuCN2EzvaDVjhhKtQglUooSrSKlW0A1Wo1SlP8WY+NYUcjheA90lhrJXBFlWnJAkldJAyxvDqq6/y4Ycfsm3bNrxer9/tr7/+umMNjLdkClIZxrDe7KUlkV+UONwgVd9DVDQDVKjhKZLQVD0MxYsTISzccBVqqHKyUhVJlSoRAlVp8WbGU8odppRMYDMWZ1mZfKUz+yTJJHSQuuaaa3jyySc57rjjaNu2bY2AMXPmTMcaGG/JFKQaG8O1lDLMlDPIyrJ9Pb1ohSioO0glWoiKd4AKNzwlQmCyw27ICidYORmq4hWowj3LL5LqVIfiTbxmijgUL8XAX60MZkfwx5lIrCV0kGrRogX//ve/Oemkk6LRpoSSTEHKCfHs0oskRMWyChUsQEUansIJTk6GprQ29qsNZduic0HlcMOV06EqGQNVJNWpQGHKVbyZ50wxp1POLqC71ZhdDeBzUOqHhA5SXbp04Z133qFHjx7RaFNCUZAKrj6GKLtVqGAhyokAZTc4RRKSnBRp4AonWCViqAoWqGLR3We3OlVUvJlJppRPrRRd/FiSSkIHqWeffZZ3332XZ555hszM6M1knAiSJUjdZEpYjYv/kppwXXqRjotyOkTFsgoVLEA5HZ4SJTCFy07AikaoStZAFYswVf2sPoAhppxcLFZp3JQksIQOUkVFRZxxxhl89tlndO7cmbQ0/w+OpUuXOtbAeEuGINXOeFlrCkgD+lpZfGfzwy0aQSpZQpSdKlS0AlSo4cmJ4JTSvlHE+6ji2VLg2L7CDVehBiunQlVDCFS1hakDjZcvTQEu4GQrk89VpZIEFasgZesdMGbMGJYsWcKf//zngIPNJbbOoZw0YDGuhApRoUjkEBXLABVKeLIbnJwMS5HcTzhBq/qxhhKqqh6/ugJV1XNQV6BqkVUUNExVvQaCBao27rKgYapluqfWMNXSbWoNUy3dVsAw1SIjNWCYapOWWSNMtfK2rhGmWlg5fmGqqXt/vzCV5W5PYckWdgPfksJgPMw1xQwkizWaHkEaMFsVqUaNGvHee+9x7LHHRqNNCSUZKlIfews4Bi/XWG6esDkBZzyqUXbHRSViiEqUABWr0OQEOxWscCpVoVSpQqlQOdHlFyxQ2R2MHs/KVKYxfGAK6YeX1VgcYzXitwT9fJSGK1YVKVt/RuTk5ES1UcFMmzaNzp07k5GRQf/+/fnqq6+Crv/KK6/Qo0cPMjIy6NWrF2+//XaMWhob+xkvx+DFC7xur8AYty69YOqa5iCQRAtR2dlFtYaorFblQUNUWpsU308wKe0b+f1EwmrTNOQfJ9hpe6iPC9T9GEPw56hKi6yiOk8WqOtszaBj7NI9QbuWa3391vJ6r+0PjUDvqUB/zOz73t33/Z7lbk+RZTHSymQdFt0xvGqKSNPcztJA2QpSDz/8MDfddBNr1651uDnBvfTSS1x33XVMmjSJpUuX0rt3b4YNG8a2bdsCrv/5559z3nnncdFFF7Fs2TJGjhzJyJEjWblyZUzbHU1nUfFF8RkpbE6i8rrTXXqJGKICCTVABWMnODkdjqIRtqIVqmIVqFq6S4IGqjbusjoDVe37rj1MBXrtxyJMbbVcnGplkg8MwcNTphgUpqQBstW117x5cwoLCykvLycrK6vGYPNdu3Y51sDq+vfvz1FHHcUTTzwBgNfrJScnh6uvvpoJEybUWP/cc8+loKCAefPm+ZYdffTR9OnThxkzZoR0n4netRdpt16ideklWohyKkBB8G68UMJTqJyqGEWD2ZZva7tQuwFD6fpzossv0sHodrv6nBqE7mQ334mmnP+aIj4khZFWZkQXSRdxUkIPNn/kkUccbkbdSktLWbJkCRMnTvQtc7lcDB06lMWLFwfcZvHixVx33XV+y4YNG8Ybb7xR6/2UlJRQUvL7l2d+vr0P/lhoa7y+a2LZ7dYLh1MDzO1I5hBlN0CFGp4SOTjta9+2hhqsqh6LugJV1eMZLFCFMjC9rkHpVa+B2gJVXYPRq15vgQJV1Ws0UKCqel0HClThDEIPdQD6vgINQP8UOKF4A5+TYvvaniLJzPZZe7G2Y8cOPB4Pbdu29Vvetm1bVq1aFXCb3NzcgOvn5ubWej9Tpkxh8uTJkTc4Bk7AQybwPa6E6daLVjXKCYkUopyoQEUUoNq0sL9tINvsVaGrH0MoocrpQBXKWX7BqlOhnN0X6nX8amwb5Ky+2u8vcJgKJFCY2te+Z/LV5mNNgSANWMjfvgUF4Z1hE+76iWLixInk5eX5fjZsqPtDJF7+YCq+JN4mNlMexItT1ahAohWigo3LqasKFSxE2RqD1KZFzR+nOXAf4RxXqGOpnBo/FUwkA9Hrul5j7fsMb0RGsDNdq7MzXqq6tsbLFG8J/U10LhskkohCDlIHHngg9913H1u2bKl1HWMMCxYsYMSIETz22GOONLBKq1atSElJYevWrX7Lt27dSrt27QJu065du7DWB3C73TRt2tTvJ1ENqhxo/kkM/hqM59iocITTpRfOl1i4ISqQYAOjQw1QIYl2aAqVzXY4HahCPcMvmHiFqWifzRfq4PO6VP1Rdocp5SZKmWiCn8UoUp+EHKQWLVrE119/TZcuXejfvz9XXnkl99xzDw8//DC33norZ555Jh06dOAvf/kLp556KjfddJOjDU1PT+eII45g4cKFvmVer5eFCxcyYMCAgNsMGDDAb32ABQsW1Lp+MmllvByIwQt8arMilQzCrUYFXDeMEBXoC8+pEFUbRwJUIgSnuoTZxnCqb6GEqVCqU8HUhzBlV6hVqb9b6XiBU/HQU1UpaSDCPmtv/fr1vPLKK3zyySesW7eOoqIiWrVqRd++fRk2bBgjRowgJSU6X+wvvfQSY8aM4cknn6Rfv3488sgjvPzyy6xatYq2bdty4YUXst9++zFlyhSgYvqDwYMHc99993HyySfz4osvcu+997J06VIOPfTQkO4zkc/aa24MffDwoY2KVKzP1rNTjXKiSy/ScVHRDFF1ffmHHKAiYNq0srWdtW1HRPfrE8bYqlAHptc1fqquM/vqGjcVzTP67JzN58SEnaGcxRfqJWRe9BYxinLmkMqFrvp9LVZJbAl9rb14euKJJ3jwwQfJzc2lT58+PPbYY/Tv3x+AIUOG0LlzZ2bNmuVb/5VXXuHWW29l7dq1HHTQQTzwwAOcdNJJId9fIgepSIQTpOLVrRdOkIq0Sy+RQlSdAcpGeLIbmMIVUcAKMVSFEqgSOUxFY2qEaIQpu9Mh9DUevjGFlANtrMbk1aPPTUkuClIJQkEqukEq3Hmj4l2NSrYQFasAtS/bgaqehKmGXpXa4t1LGwx9rCxW2Lz+p0ikEvoSMRJ///YWca+3hOZJkIPtDF4N9SyjcDkdomoT7xBl2rSKW4iqfv9htyGM8VORsnsR6FDUNV4qGDtn8sVqrFSoNlNxvx1I/M8nkUgpSCWh1sbLeZRzI6WU2tg+1tWoaAv3VHAnhXLR4SqxCFHxDlCBhN0mh8JUpNcejHTweTB1XZuv1u2CDDxPJBuw2ICFW0FKGgAFqSR0WOVs5muwKEji7sZwpzyIxpl6saxG1SZoIAjxLLdEDFD7SsQwFemZfMFEUpWKtmhVfKuMtDLp7GrMf6zauylF6gsFqSRUFaS+S4JpD6LdrZdo1ahwu/TqDFF1cCpAmTZtavxEQ1jtDTFERjtMBROtqpST3XuhCuUPm5An50ziP/BEwhVWkDr++ON5/fXXa719x44ddO3aNeJGSXAHm4ogtSJBLguTaGJRjXKqSy8SkQaoukJToHDlVMBK9OpZdYlWlQq3ey8e46SsJBi7KeKUsL6JP/zwQ8455xwmTZoU8HaPx8O6descaZjUrnXluIOt6K++ROJ4l14URRKIolmxCiiRJxmVgF4xxXzhLWCwsR9CRZJF2CWN6dOn88gjj3DGGWck7fX0kl3Lyq69HQkQpGI10DxeZx8lKrsVHWerSpHtJ5mqUsks1IsYh6Ku6Q8AXMZwHOUchZe9CfAZJRJtYQep008/nS+++ILvv/+eo48+ml9++SUa7ZIgmlf+f6c+pOqnKFVgolFFimllKohon8GXSGqbSypSgeaRsqMPXpoBecByDcOVBsDWq/zggw/m66+/Jicnh6OOOor333/f6XZJEIdZWbS0GrPYxmBzp6c+sMupixQnOluDzOtgp5ITzcCTKGFKEsMQKsZwfUIKHg06lwbA9p8L2dnZvPXWW1xyySWcdNJJTJ061cl2SRDGsthtWZTWww+peJ6xF42B5okgFkHH7n2EdQafBFXb7OaBBJrZPFJVs5oPqRwXtcjGNUBFklFYr/R9L5FiWRb33Xcfffr04eKLL+aDDz5wtHEi0WJ3QsTaODZLtgKDJLGOxsvQyorUB0kwPYuIE8KqSNV2Wb7Ro0fz6aefsmLFCkcaJbVLM4aZ3iJmeYvI0CnGttV14dhw1XXdtpCFeK25cFjbtjm+T6fuI+Rr8kXhcYmFuq65V5tg19uLlXCvswdwuynBDbxPCt/qGnvSQIQ9/UGLFoH/Yu7Tpw9Llixh5syZjjRMArOACynnAspJj3dj6plAX3qBLkxb18VsG5pYBLW61HUR47ouYBxMtJ5vO2E+3IHmgc7YC/WCxeGo6tZ7wkrnHVK4zXL2DxWRRBZWkBo8eDCpqbV/qLRs2ZILL7ww4kZJ7bzV/l3/RkiFN3YjnDEh8VLbF3hdX/zBhFzF8dtmm+OBJ9J9Jko1KpJqYqCgHQ9OvxfsVKMAllspnOLK4itVo6QB0bmpSab635d68uqpKAYHpwJVpPuwEwZrk6jVqGDdesGqUU5168WqGgWayVwaNn0XJ5nqFamUJL6yulNz1jRUkQYRu4EqGpWtoBJ4bFSsq1G1devFuxpVXLyZt0wRj3mLaW28iDQ0ClJJxgDFlf+O9hSDtZXvJQZCCBBOVHXqCkZVtzsZoBKpGuXYSQL7aEjVqP+jlGF4GEcZTSLem0jyUZBKNpbF9srRUa1tVKSqBoUmGycvc/H7PkMbEBvqgPPavpRtj5OKUZiq2M+2gD9OsrbtCG9cVB3HH+0QFaxbL1g1Khpn6iVqNerY4g3cbkoBuMLK4BddSF0aIL3qk1BVkGqTAF17+37QJoJAXzqh/qVv90uwSrzClJNVHqeF3b4QjjlRQ1RdnDxTr7YQZbcaFW6Ialm8idmmGBfwJGnMtuI/ZYNIPChIJaFTrUyyrca8XU8nvEvEM/eiOQ2CE2EKEi9Q2QpQSR6inO7Si1eI2te+IaqseDMvmiJaYfgGF9dqugNpwBSkklCu5WKvZUESXCKmrg/ocETavRfoyyrQl1usq1LgXJiC+AcqW/cf4vHFM0TVJRHHRQW8vxDGRQWrNBeWbOFBU8LReNkFnGNlUpIEn0Ui0aIgJXETzTP3wp24MBThVKXiHabg90ATi1Bl+75CrEJB/EOU3XFRdkOUE+Oi9q1GBXrPhdOlVzXGcoGVyk5gjJXJOo2LkgZOUzQnod7Gw+WmjG1Y3O5SSX1niRXRBYx3lrhrXHtvV2FmwIsYB1K4IzXghYzLtnkCXoPPs6WAlPaBz7k02/Kx2jSt/c6qQkeY1+QLFHBCvmBwCPsKWxihMJTJSxt6iAq1S29fdifefMtK5UAak69KlAiWqe0CegJAfn4+2dnZWFbjGhdtjpehppz3TBE/4uJQl71JELLc7UNet6l7/zrXaWHl1HpbK2/rWm9rk1b7l1CLjMBfbi3dNZ+H2oJUy/SaX6Bt3GUBtg98EeNAYSo7O3DAChSmoPYLGtcWpqoEDVTVJdOFjmMcoEAhynefEQ4uP7R4I3uAHzVruSQJYwzG7CUvL4+mTUP8PLVBNdkktKryaTsQL6lJkIODjZNyqnsvnO6OUMdKQejX3wN73Xx1dfWFdCmZMLrH4qKqfWF04TlVhQoWogp3pNY5sFwhqkLn4o28ZQr5yBRyqInO3FsiyUpBKgltxGIvkAYcQP2dSbi2rolwBp2HM1YqnFPTnQpTUHcgCPm6fNUDSzyDlc12hBOg4t2V15BCVKviTbxjimgB/ISLX/S1IeJHXXt1SMSuPYAvvQUciZczrQzetDF/SzhdexB59x7Y6+ILp3uvYnlkXXwV+6jZzVfbeCmnuvmq1NXdB2F0+QXiZDegA2EtnIs3x7sbD+o+o9PJKQ4q9lfzdV7bHxLRCFFZxZv42BTSHcMPuBhsZbErgT4HRYKJVdeeBpsnqdW4OBIvh+DlzXg3Jop2FZcHDFM7S0zAMBXOwPNtJWm1hqka7ahl8HleXmbAMBVsADrUHqiCDUSvUhU+bAWqBOgCDCc8gTMBCqIbouqqZiZjiMou3sR8U0R3DOuwGG5lKkSJBKAabZJaVjng80ibFwlNtEvFRPsixrV9YUU6XgrC7+aDurv6Qum+quoKCzeYxEO4bQ31MahrHBTUPRYKotuVZ2eyzXiHqObFm/jIFHIIXjZiMczKYpOmORAJSBWpJPVNZQZuEaPLxOSXbKyze2+X2RC0e2+Ha3vQ7r1a9+tQVWpnaUrALr5AlalAUyKAvcoUBO7qq6s6Bb9XY0KtUlUXURdgBOwGu1AqT1WcqEBBclShKpbbvwhxuCGqsGQLBouNuAAvJ1pZrFWIEqmVxkjVIVHHSKUZQ2PgtwjaFI9xUhCb6RAqloc+XgrCGzMF4Y+bgtrHTkHd46eqhDKOKhR2g5aTFTCnwxNEP0BBbCfZjHWIqtLEGBpj2KIQJUkqVmOkFKTqkKhByilOzycF0Rl0DrUHKUiuMAXBAxWEHqrAuWAVC+EEpyr1OUBV7DP0KhREL0T1Kt7IcZRzn66bJ/WEglSCUJDyl2xVqYrb4hOmILaBqkqiBCs7oamKk+EJohugIDYhqrbpQEK5AHFdIWpg8QZeM0U0BsZYGfzbxpnAIolGQSpBJHKQ6mc83G1K2IPFWS57F9qNRpCCyKpSEJsuPnAuTEF0AxXYC1XVRStgRRKYqoQanKo4UX2C5AhQYL8KBXWHqAuL1/GoKSEVWEAKZ1qZFCbYZ52IHQpSCSKRg9QBxsv/TAGlQGurMXttti/ZwpSTXXwQfpiq2F/41SlwJlBViTRYxVO4wQmcqz5BdAMUODcWCqLXlZdiDPcUr+VKKl7ns0nlUiuD0gT7nBOxS5eI2ceuXbs4//zzadq0Kc2aNeOiiy5i7969QbcZMmQIlmX5/fz1r3+NUYujb43l4ics0oHjCf0LOFEEu3RMMMEuxlrbl1Ftp5RD8KkRaj3zKsgUCcG+pOu67EjVqfqhhIaqU/+r/yQiu+2s/liEMn1BKJd0CWUqA7vTGUDFa8nODOW1deXt+1rfVlYUsCsv3BDVzHh4tfgXrqQMLzDBSmesQpSILUlTkRoxYgRbtmzhySefpKysjHHjxnHUUUfx/PPP17rNkCFD6NatG3feeadvWVZWVljJNJErUgCPeIu5mjKeIo3LXRm295NsVSmwV5mquC28MVNgrzoFdVeooO4qFYRXqapNtCpYTgW4UCtOVUKpPEHd1SeIXgWqYt+Rd+OBc115hSVbGGbKmWeKKAQusDL4j8ZEST2krr1qfvzxRw455BC+/vprjjzySADeffddTjrpJDZu3EiHDh0CbjdkyBD69OnDI488Yvu+Ez1Ijaj8QFyPRRerEcSoew/qZ5iCxA5U1TkRruIp3OAEsQ1PEJ0AVXFbZN14UHdXHgSf3uBSU8oXpPCdlbxdxCLBKEhV88wzz3D99dfz22+/+ZaVl5eTkZHBK6+8whlnnBFwuyFDhvD9999jjKFdu3aceuqp3HbbbWRlZdV6XyUlJZSU/P6FmJ+fT05OTsIGqUxj2GH2kgEcZmXxfQQfivGqSkH9CVMV+609UEF0QlWVRAxXdgJTlVCDE4QWniB5AhQ4V4XCGMaWrGceqazXvFDSQOhae9Xk5ubSpk0bv2Wpqam0aNGC3NzcWrf705/+RKdOnejQoQPfffcdN998M6tXr+b111+vdZspU6YwefJkx9oebUWWxUKTwsl4OM+Uc2sM/7oMZbZzqHvGc6h71vNtZUW1hqnaZj6H2mc/r7itYnlts6BD4EBV9SVbW6Cq+qKuLVBVfeEHC1T7BohQg1Ww0BKtkBVJUNpXOMEJEic8VdxH+AEKol+FamE8TCteyyl4uJgyjiGLogT8o1AkWcU1SE2YMIH7778/6Do//vij7f1feumlvn/36tWL9u3bc/zxx7NmzRoOOOCAgNtMnDiR6667zvd7VUUqkc200sg08FWEf2kWlmyx1cUXiniHKai9OhXsQse1XVYGnAtUUHeVym6wqs7JwOOEcEMThB6cILTwBMkZoCCEKhTQt3gDc0wxORiKgaesNKJ7VUuRhieun6zXX389Y8eODbpO165dadeuHdu2bfNbXl5ezq5du2jXrl3I99e/f38Afv7551qDlNvtxu1Orpl951ppzI3TYNFQq1IQmzAFtXf1RaM6BaEHqor91x2qIPxgVcVul2C02AlL1YUTnCB24anivpwLUGC/Gw9qhijLGK4uWcdkU0oqsBqL86xMvtV4KBHHxTVItW7dmtat676I7YABA9i9ezdLlizhiCOOAOCDDz7A6/X6wlEoli9fDkD79tGputQHdqpS4YSpUEQSpiC61SmwH6gq9l93qILwg1WVcIKL3dAVaTgKJlrBCeoOTxBZ9ani9ugFKAitCuUu3syLpoihVLxO55DKFVaG7XnmRCS4pBhsDhXTH2zdupUZM2b4pj848sgjfdMfbNq0ieOPP57nnnuOfv36sWbNGp5//nlOOukkWrZsyXfffce1117L/vvvz0cffRTy/Sb6WXvVtTFeLqSM2aSxNYJuPrvde04OPofIBqBD8EHoEHwgesXtwd8awQakV6lrYPrv9xV8gHogoYarRBRuYKridHCCyKtPFbc7E6DAfhUKKv4QSjGGj00hh+HlaiuDWaTaPptXJJlpsPk+5syZw1VXXcXxxx+Py+XirLPO4rHHHvPdXlZWxurVqyksLAQgPT2d999/n0ceeYSCggJycnI466yzuPXWW+N1CFH3kilmEB7SLJiC/e7JaI6VgtC6+MCZyhQE7+qD4NWpitvtVajA/8vciUpVdcHCSLxDlt2gtK9wghMkfniC6ASoFsWb2IkFloXHsriQTFzATzpDTyTqkqYiFS/JVJE635TxnClmJ3CA1Zg9EbY3mnNLgXOVKYh+dapinbrfKqFUqSD0StXv9x1+xSrZhBuaIPTgBM6Ep4p1oh+gIPSxUBeUrGeKKWEG6Ux0Jdf4TpFo0jxSCSKZglSKMXxnCumBl9usdO61IvtQjXYXH8Q2TEHiBSoIP1T93o7kDFd2AlOVcIIThBaeILLqE8Q+QAHkFG/kSVPCHyrHQn1MCkOtTDwJ/jklEisKUgkimYIUwGhTxhxTzG9UVKXy4lCVguQOU+BcoILwQhXYD1Y17jcOQSuSkLSvcEMTOBecKtaxH54gegEq03i5qng9N1OKG9gD3GK5mU4aJgk+o0RiRUEqQSRbkHIZwzJTyKF4uZN0JjtQ6k+kMAWJF6gq1otOqKriVLhKVHZCE4QenMCZ8AT2qk8QeYACOKx4Iy+aInKoaOc7pHC5lcEGjYUSqUFBKkEkW5ACOMuU8bIpJp+KqtQuB9odizAFzlanwLlABc6HKrAfrKokU8CyG5aqCyc4QWjhqWK96FSfwJkAVXWNvHbGyypTwE4sbrLcvKYz8kRqpSCVIJIxSFnG8KUpZAkp3GK5+S2OQQqSI0yB84GqYt3w3l6RBqtAoh22nAhIgYQbmsC54ATRCU8QOEBB4BDVuHgTZ1LODCvdt2ygKWcpKRQnyeeRSLwoSCWIZAxSAG5jKHG4vYkYpiA5AlXF+vbeatEIV4nETmDybRticKpYN/LwBLEJUOXFm7mSMm4zJWQDJ1iZfGAlzWw1IglB80hJRJwOURDZ/FLhzn4e6lxTUPd8U1WqvgDrClR1zT9VpfoXcyihat8v/VCDVbCgkQwhK5Kg5LefMEJTxfqhPb6RhicIr/uuSqAAVVq8mbGU8X+mlI6V46C+xkUeyfNHnEhDo4pUHZK1IlWlm/HysCnmCSud9xz6izaWlSmITnUKQq9QQehVKgi/UvX7dtF7KzoZuJwKRkHvI8zQVLFN6I9fNMMThFd9Aigu3syfKOd2U8IBlQFqIxZ3WG5mkaqz8URsUNdegkj2IPWAt5jrKeNHXPSxsih36BgSOUxBYgSqKnaDVcW29fvtaScw/b5teI9NtMMThB+gqgaRpxrDD6aAAzBsxWKKlc5TpEWlsizSUChIJYhkD1LZxrDaFNAaw3jLzePVBq1GKtZhChInUEHsQ1Xg/SX22zeSoOS/n/CPM5TgBHWHJ7BXfYIgAap4M8Pw8AEplFV+rpxlyjgAL0+QTmESftaIJBoFqQSR7EEK4BJTygxTwl7gKKsR/3NwzplIr8mXaNUpCD9Qgb1QVcXpcBXafYb+tncqDIV+f/Y+kkINThB5eAJ7AaqoeDNnUM5EU8rheLnccvOUg3/ciMjvFKQSRH0IUpYxvGuKGIqH5bgYaGU52mUQjzAF0Q9UYC9UQWTBqko8AlYs2Q1MVZwOThCd8ARQUryZ0ZQzwZRyCF4A9gKTLTd/V5ASiQoFqQRRH4IUQHvjZakppA2GJ0jjGleGo/uPV5iC2AQqiG+oqi5ZAlakQam6cEJTFafCE9gPUBjDeSXrudmU+gaR7wYeJ53HrHRHJssVkcAUpBJEfQlSAMNNOW+ZIpbgYpCV5fiEfpGGKYhddapKrENVFafDVV0iDV9OhqK62AlNEHpwgiiHJ34fRA7wlreQ4XjYjsVUK43ppJOf5J8lIslAQSpB1KcgBXCqKec9UiiN0rHEM0xB7AMVRB6qqsQ6XMWb3cBUxengBMHDEwQPUIUlWzjAeLnKlDLVSmd95VjEfsbD0Xj4F2kaRC4SQwpSCaK+BakajHH8Wl1OhCmIT6CCyEIVOBesqkvGkBVpUKounNBUJRbhCSrOwPsjHv5mSjkZDy7gQdKY4HD3uYiERzObS1RZxnCXKaUlhstxOxqmIpkBvbpwZ0OvrurL0U6gqv4FbCdU7ful70SwCieURCt0ORmMgrETmsC54AShdd1lGMOfKONvpoxelQPIAd4mhXd1OReRBkMVqTrU14rUUcbD56YQF3CN5eaJKJ05lAjVKYisQlUl0kpVddGoWiUbu4GpSqjBCUILTxD62CeXMayqnEATKs7Ae5Y0nrDSHZ1eRETsU9degqivQQrgOlPKg6YED3CKlcn8KP0V7VSYgsgDFSReqKpSH8NVpGGpunCCEzgXnqAiQB1mPHyHy1e9/bu3mNMp5wkrnWdII6+efT6IJDsFqQRRn4MUxvAvU8w4ytkNDLSyWG1F5zpqiRamwJlAVSUawWpfiRa0nAxJ+wo3NEHowQlCD0+pxnAm5fzNlDIAL4OtTD6t/IOjsTEUAZ769rkgUk8oSCWIeh2kgHRjmG+K+AMefsJigNWI36J4nE4GKkjMUAWxCVb1hZ3QVCUa4Qmgq/EyxpQxljL2r+y+KwGut9xM1wSaIklBQSpB1PcgBdDaePnCFNIZwwekcIKV6fiZfNU5HabAuUAFzoeqKg09XEUSmKqEE5wgvPAE0NJ4mWOKOQGPb9lWLKZbaTxJGts0/kkkaeisPYmZ7ZaLkWSy0BTyTystqiEKnDurr7qqL0wnAlX1L2snQ1WwIFEfQpYTQam6cEMThBacwD88pRjj657bhUVnvHiBBaQwy0rjDVKjNu+aiCQ/VaTq0BAqUlWaGMOeGB9jNKpT4GyFqrpoVavqEs+g5XRAqo2d4AShhyeoFqCM4Ui8XGTKOIFyelqNfNefPNaUsxEXa1V9Eklq6tpLEA0pSFW3v/FysSnjTisdbwyOO1qBCqIXqiB+wSrZ2Q1NEF5wAv/qUyvj5XzKGbfP3E/nWBm8ZqXZbpOIJB517UncuI1hoSnkQAzdjJcxZFCWhN19VZzs9tvXvoFAwcpfJIGpukjCE0AP4+FOU8qplFM1VLwIeJ1U/mWl8THROVtVROo/VaTq0FArUmebMmabYtKpmKn5HCuTohgdfzSrU1WiWaUKpL4HLKcCU5VwgxPUDE+pxlBe+ZrtZrz8aAoA+BoXs6w0XtDcTyL1mrr2EkRDDVIAw0w5r5oisoCPSOF0KzOmY6hiEagg9qEqkEQOWk6HpEDsBCeoGZ4yjeFsyhlrytiOxWjX73NvXWNK+YAUVkRprjQRSSwKUgmiIQcpgGNMOf81RWQD3+DiJCuTnTEehBurQAWJEarqO7uhCWoGJwCM4Si8/MWUcS5lZFcuLgLaWY3Z2wDftyKiIJUwGnqQAuhrPLxjimiN4SVS+ZMrPjNsxzJQVVGwikwkoam6gAEKOM+UcbMp9Rs4/gsWM600niONjTrzTqTB0mBzSRjLrBQGk8njpoTxljtu7aj6Mo1loNo3CChY1c6p0AS1B6c2xksBFgWVf9S0xtALL0XAa6Qy00rjI1IwDfSPHhGJPQUpCclqK4UTrSy/Zc2NierlZGoTj0BVJVBYaGjhysnAVKW24ATQzBjOoJzRpozj8PBXy80zlefevUQqRRa8rIHjIhInClJiy1hTxt9NMReSyTwrPi+j6l++8QhVVWoLFskasKIRlAIJFp6yjOFUyhltyhlGOdXroL2NFyoz01bLxT/Rte9EJH4UpCRsLmM4z1QM6p1ririVdO4nPeqXlgkmnlWq2oQTSKIdumIVjoIJFpyqa2QMG8xe36BxgBW4eNFK5WXS+EXjnkQkgWiweR002DywVGOYakq4gjIAXiCVi60MihPoMUqkUNXQhBqaUoxhCB764OVh6/fK0nveQrrg5SXSeNFK5XtNWSAiYYrVYPOk+dPunnvuYeDAgWRlZdGsWbOQtjHGcPvtt9O+fXsyMzMZOnQoP/30U3Qb2kCUWxZXuzK4wnJTBpxHOR+ZQvYz3jq3jZXCki2+H4mu6o91nY+3MQwwHh71FrPBFDDfFHGfKaFdtdfOaCuTblYjbnO5FaJEJKElTZAqLS1l1KhRXH755SFv88ADD/DYY48xY8YMvvzySxo1asSwYcMoLi6OYksblietdE60MtmBxZF4+cIU0jQBi5wKVc4KKzhV6ma8TPGWsMYU8Kkp5CrKaIthBxb/JI3qV7r7zbLi2lUsIhKqpOvamzVrFuPHj2f37t1B1zPG0KFDB66//npuuOEGAPLy8mjbti2zZs1i9OjRId2fuvZC09l4mWuKeN1K5a44TpFgh7oAg7MbPlOMwQ0UVr5vxpoynjYVf8TsAd4glZesNBaQ4ruUi4iIUzSPVIR+/fVXcnNzGTp0qG9ZdnY2/fv3Z/HixbUGqZKSEkpKSny/5+fnR72t9cFay8UxZFFUbVl742UXFiUJ/iW5b1BoqMHKiWpdmjGMoJzzTDknUs59VjoPVp5zN5dUhpPKK1Yqb5GaUOPpRETsqrdBKjc3F4C2bdv6LW/btq3vtkCmTJnC5MmTo9q2+qqw2hej2xj+Y4owwGgyk+pMq9oCRX0IWFHp2jSG/nj5synjHMppxe9F7mONhwcrXxZ5lsVoKz6z4ouIREtcv90mTJiAZVlBf1atWhXTNk2cOJG8vDzfz4YN0b9ga33UDS8dMRyBl29MAWeZsng3KWL7jgtKxHFXwdoYjXZaxrDSFPK5KeQKymiFYQsWfyeNgVYWZyg4iUg9F9eK1PXXX8/YsWODrtO1a1db+27Xrh0AW7dupX373ysJW7dupU+fPrVu53a7cbuTa4xPIlphpXA4WTxvijkWDy+bYp4wHm603JTWwy6dRApT0dLEGIZTzpHGw82uDACMZbHauMjByxuk8m8rjQ9IwVMPn2MRkUDiGqRat25N69ato7LvLl260K5dOxYuXOgLTvn5+Xz55Zdhnfkn9m2yXBxPJpNNKRMo5SrK6G88nEcmvyZRV1+DZQzdMAyjnOGmnOPw+GYYf8qks6byObzacrOLxJpDTEQkVpLm22z9+vUsX76c9evX4/F4WL58OcuXL2fv3r2+dXr06MHcuXMBsCyL8ePHc/fdd/Of//yHFStWcOGFF9KhQwdGjhwZp6NoeMoti/9zuTnFymQncBRe/mE0/USiO8+UscYU8KMp4BFTwvDKELUaiwdJo6Taupstl0KUiDRYSTPY/Pbbb+fZZ5/1/d63b18APvzwQ4YMGQLA6tWrycvL861z0003UVBQwKWXXsru3bs59thjeffdd8nIyIhp2wXesVI5nEb8wxRztaXHP2EYw6F4OYVy3iKVFZWTXxYCnTGUAJ+QwnwrlXmksFqTY4qI+Em6eaRiTfNIRde1ppRFpLBMX9Axk2YMg/FwiinnFMrpUnmW3V2kc4erovOusTH8AQ8fkeJ3NqaISLLQPFJS7x1vynnIlFAK3EY6D5OO0Zd21LQ0XqaZEoZRTvWPlCJgISksqzZuba9l8Y4+HkRE6pQ0Y6Sk/llGCq+TSjpwvyllvilKqGv1JbNsYzjNlPGnatNO7Mbij5UhagsW/yKNkVYmra3GnO7K4k0rrfYdiohIQOraq4O69qLMGP5CGY+YEhoBu4DLrAxe15d6WJoawwA8HGfKGYKHw/GSAqzHoovVyHfdurNMGetwsQSXqn8iUq+pa08aBsviGdL5hFRmmyKOwssrpph7jZfbXJrPKyBj/C7o+7y3iHMpr7HaKlx8SApu8J1l95oCqoiIoxSkJCH8ZLk4lizuMKXcTCk/aJ4pPxnGMAgPp5tyjqOcPjTyTWy6nYr/r8HiI1JZZKXwISls1mMoIhJ16tqrg7r2Yq+P8fAdLryVj/fRxsOvWGxtQMEg1RiOxMsfKeePxsPAapNhApxqZfK2VfF3UHvjpQzY0YAeHxGRuqhrTxqs5dWmQmhnvMytvPjxGDJYYNXPl2yKMaQCJZXh8QrKmGpK/NbZhMVbpPKGlcoH/P4YbVGAEhGJm/r5rST1RmNgKxa98PKuKeJBk8ZtlpuyJK8OtjNe+uOhf+X/j8LDtZabp0kHYBEp7AQWkcoHVgofkMr/sPzGRomISPypa68O6tqLvwxjeMiUcDkVp/J/iYtrrAy+xpVUwaK98fKwKaE/HjpT8203gzSurLwYMMZggc6sExGxKVZdewpSdVCQShxnmDL+aYppXvn7J6QwxMpMqDCVY7yMoJzDjJdD8fIhKUyuPPuwmTHsNBXXhvQCK3HxJSl8aaXwBS5WaUoCERHHaIyUyD7mWml8Qwr3mhLOoJzvEqAilWIMZ1HOIONhEB564j+haPVRTrsti/G4WYmLr0lhr0KTiEjSU0WqDqpIJaYmxpCJYVvlQOuuxktzDEuifM2+DsZLJwyLq+7HGHJNAa0ru+q8wKek8AUprLRcLMPFD7qOoIhIzKkiJRLEHstiT+X8Sc2N4b+miBy8nE8m/3XizD5j6IThcDz0NV764qEvXtpj2IhFJypnC7csZpmKy9x8bKXwCSns1Fl0IiINhoKUJL1yYB0WPYDXTRHX4uYJKz3k7a3K0LS2WgCaZ4oYgafGuh4gF4tsIK9y2YSqAeIiItLgKEhJ0ttjWZxGJo+bEi6ljEdNCQcaL9dZbt+knlVSjOFgvByOlz6mosrUFw+NgOY09o1b+gkXx+NhJS6WkcJSq+L/3+GiSF28IiJSSWOk6qAxUknEGG6glPtNKQDvksK5VqYvHN1qSphgSskMsGkhcKyVxbeV45maGUMh+C7DIiIiyUVjpETCZVk8hJu1uHjWFDMcD73wsrhyFvDfsMgE8oFlpLAMF8usFJbiYjUuPNVC024FKBERCYGClNQ7r1ppbMTFTFPEgdWC1Euk8p6VyhoszdckIiKOUJCSeukLK4WDrcZQred6h+ViRxzbJCIi9Y/O05b6TZUnERGJIgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsSlpgtQ999zDwIEDycrKolmzZiFtM3bsWCzL8vsZPnx4dBsqIiIiDUZqvBsQqtLSUkaNGsWAAQN4+umnQ95u+PDhzJw50/e72+2ORvNERESkAUqaIDV58mQAZs2aFdZ2brebdu3aRaFFIiIi0tAlTdeeXYsWLaJNmzZ0796dyy+/nJ07d8a7SSIiIlJPJE1Fyo7hw4dz5pln0qVLF9asWcMtt9zCiBEjWLx4MSkpKQG3KSkpoaSkxPd7fn5+rJorIiIiSSauFakJEybUGAy+78+qVats73/06NGcdtpp9OrVi5EjRzJv3jy+/vprFi1aVOs2U6ZMITs72/eTk5Nj+/5FRESkfrOMMSZed759+/Y6u9q6du1Kenq67/dZs2Yxfvx4du/ebes+W7duzd13381ll10W8PZAFamcnBwsqzGWZdm6TxEREYktYwzG7CUvL4+mTZtG7X7i2rXXunVrWrduHbP727hxIzt37qR9+/a1ruN2u3Vmn4iIiIQkaQabr1+/nuXLl7N+/Xo8Hg/Lly9n+fLl7N2717dOjx49mDt3LgB79+7lxhtv5IsvvmDt2rUsXLiQ008/nQMPPJBhw4bF6zBERESkHkmawea33347zz77rO/3vn37AvDhhx8yZMgQAFavXk1eXh4AKSkpfPfddzz77LPs3r2bDh06cOKJJ3LXXXep4iQiIiKOiOsYqWSQn59Pdna2xkiJiIgkkViNkUqarj0RERGRRKMgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJik4KUiIiIiE1JEaTWrl3LRRddRJcuXcjMzOSAAw5g0qRJlJaWBt2uuLiYK6+8kpYtW9K4cWPOOusstm7dGqNWi4iISH2XFEFq1apVeL1ennzySb7//numTp3KjBkzuOWWW4Jud+211/Lf//6XV155hY8++ojNmzdz5plnxqjVIiIiUt9ZxhgT70bY8eCDDzJ9+nR++eWXgLfn5eXRunVrnn/+ec4++2ygIpAdfPDBLF68mKOPPjqk+8nPzyc7OxvLaoxlWY61X0RERKLHGIMxe8nLy6Np06ZRu5+kqEgFkpeXR4sWLWq9fcmSJZSVlTF06FDfsh49etCxY0cWL14ciyaKiIhIPZca7wbY8fPPP/P444/z0EMP1bpObm4u6enpNGvWzG9527Ztyc3NrXW7kpISSkpKfL/n5eUBFclWREREkkPV93a0v7/jGqQmTJjA/fffH3SdH3/8kR49evh+37RpE8OHD2fUqFFccskljrdpypQpTJ48OcAtBShLiYiIJJedO3eSnZ0dtf3HdYzU9u3b2blzZ9B1unbtSnp6OgCbN29myJAhHH300cyaNQuXq/aeyQ8++IDjjz+e3377za8q1alTJ8aPH8+1114bcLt9K1Jer5ddu3bRsmXLpBwjlZ+fT05ODhs2bIhqH3Gi0vHr+HX8On4df8M8/ry8PDp27FgjBzgtrhWp1q1b07p165DW3bRpE8cddxxHHHEEM2fODBqiAI444gjS0tJYuHAhZ511FgCrV69m/fr1DBgwoNbt3G43brfbb1k0n4BYadq0aYN8I1XR8ev4dfw6/oaqoR9/XXkh4v1Hde8O2bRpE0OGDKFjx4489NBDbN++ndzcXL+xTps2baJHjx589dVXAGRnZ3PRRRdx3XXX8eGHH7JkyRLGjRvHgAEDQj5jT0RERCSYpBhsvmDBAn7++Wd+/vln9t9/f7/bqnomy8rKWL16NYWFhb7bpk6disvl4qyzzqKkpIRhw4bxj3/8I6ZtFxERkforKYLU2LFjGTt2bNB1OnfuXGNkfkZGBtOmTWPatGlRbF1ic7vdTJo0qUZ3ZUOh49fx6/h1/Dp+HX80Je2EnCIiIiLxlhRjpEREREQSkYKUiIiIiE0KUiIiIiI2KUiJiIiI2KQglYSmTZtG586dycjIoH///r65swL55z//yR/+8AeaN29O8+bNGTp0aI31x44di2VZfj/Dhw+P9mHYFs7xz5o1q8axZWRk+K1jjOH222+nffv2ZGZmMnToUH766adoH4Zt4Rz/kCFDahy/ZVmcfPLJvnWS5fn/+OOPOfXUU+nQoQOWZfHGG2/Uuc2iRYs4/PDDcbvdHHjggcyaNavGOuE8nvEU7vG//vrrnHDCCbRu3ZqmTZsyYMAA3nvvPb917rjjjhrPffVLciWScI9/0aJFAV/7+15rtb4+/4He15Zl0bNnT986yfT8T5kyhaOOOoomTZrQpk0bRo4cyerVq+vc7pVXXqFHjx5kZGTQq1cv3n77bb/bnfj8V5BKMi+99BLXXXcdkyZNYunSpfTu3Zthw4axbdu2gOsvWrSI8847jw8//JDFixeTk5PDiSeeyKZNm/zWGz58OFu2bPH9vPDCC7E4nLCFe/xQMatv9WNbt26d3+0PPPAAjz32GDNmzODLL7+kUaNGDBs2jOLi4mgfTtjCPf7XX3/d79hXrlxJSkoKo0aN8lsvGZ7/goICevfuHfJ0Jr/++isnn3wyxx13HMuXL2f8+PFcfPHFfmHCzuspXsI9/o8//pgTTjiBt99+myVLlnDcccdx6qmnsmzZMr/1evbs6ffcf/rpp9FofsTCPf4qq1ev9ju+Nm3a+G6rz8//o48+6nfcGzZsoEWLFjXe+8ny/H/00UdceeWVfPHFFyxYsICysjJOPPFECgoKat3m888/57zzzuOiiy5i2bJljBw5kpEjR7Jy5UrfOo58/htJKv369TNXXnml73ePx2M6dOhgpkyZEtL25eXlpkmTJubZZ5/1LRszZow5/fTTnW5qVIR7/DNnzjTZ2dm17s/r9Zp27dqZBx980Lds9+7dxu12mxdeeMGxdjsl0ud/6tSppkmTJmbv3r2+Zcn0/FcBzNy5c4Ouc9NNN5mePXv6LTv33HPNsGHDfL9H+njGSyjHH8ghhxxiJk+e7Pt90qRJpnfv3s41LEZCOf4PP/zQAOa3336rdZ2G9PzPnTvXWJZl1q5d61uWrM+/McZs27bNAOajjz6qdZ1zzjnHnHzyyX7L+vfvby677DJjjHOf/6pIJZHS0lKWLFnC0KFDfctcLhdDhw5l8eLFIe2jsLCQsrIyWrRo4bd80aJFtGnThu7du3P55ZfXeTHpeLB7/Hv37qVTp07k5ORw+umn8/333/tu+/XXX8nNzfXbZ3Z2Nv379w/5MY0VJ57/p59+mtGjR9OoUSO/5cnw/Idr8eLFfo8VwLBhw3yPlROPZzLxer3s2bOnxnv/p59+okOHDnTt2pXzzz+f9evXx6mF0dGnTx/at2/PCSecwGeffeZb3tCe/6effpqhQ4fSqVMnv+XJ+vzn5eUB1Hg9V1fXZ4BTn/8KUklkx44deDwe2rZt67e8bdu2Nfr9a3PzzTfToUMHvxfO8OHDee6551i4cCH3338/H330ESNGjMDj8Tja/kjZOf7u3bvzzDPP8Oabb/Lvf/8br9fLwIED2bhxI4Bvu0ge01iJ9Pn/6quvWLlyJRdffLHf8mR5/sOVm5sb8LHKz8+nqKjIkfdTMnnooYfYu3cv55xzjm9Z//79mTVrFu+++y7Tp0/n119/5Q9/+AN79uyJY0ud0b59e2bMmMFrr73Ga6+9Rk5ODkOGDGHp0qWAM5+nyWLz5s288847Nd77yfr8e71exo8fzzHHHMOhhx5a63q1fQZUPb9Off4nxSVixBn33XcfL774IosWLfIbcD169Gjfv3v16sVhhx3GAQccwKJFizj++OPj0VTHDBgwgAEDBvh+HzhwIAcffDBPPvkkd911VxxbFntPP/00vXr1ol+/fn7L6/PzLxWef/55Jk+ezJtvvuk3RmjEiBG+fx922GH079+fTp068fLLL3PRRRfFo6mO6d69O927d/f9PnDgQNasWcPUqVOZPXt2HFsWe88++yzNmjVj5MiRfsuT9fm/8sorWblyZcKM51JFKom0atWKlJQUtm7d6rd869attGvXLui2Dz30EPfddx/z58/nsMMOC7pu165dadWqFT///HPEbXZSJMdfJS0tjb59+/qOrWq7SPYZK5Ecf0FBAS+++GJIH46J+vyHq127dgEfq6ZNm5KZmenI6ykZvPjii1x88cW8/PLLNbo59tWsWTO6deuW9M99bfr16+c7toby/BtjeOaZZ7jgggtIT08Pum4yPP9XXXUV8+bN48MPP2T//fcPum5tnwFVz69Tn/8KUkkkPT2dI444goULF/qWeb1eFi5c6Fd12dcDDzzAXXfdxbvvvsuRRx5Z5/1s3LiRnTt30r59e0fa7RS7x1+dx+NhxYoVvmPr0qUL7dq189tnfn4+X375Zcj7jJVIjv+VV16hpKSEP//5z3XeT6I+/+EaMGCA32MFsGDBAt9j5cTrKdG98MILjBs3jhdeeMFvyova7N27lzVr1iT9c1+b5cuX+46tITz/UHG2288//xzSH1GJ/PwbY7jqqquYO3cuH3zwAV26dKlzm7o+Axz7/A9rmLzE3YsvvmjcbreZNWuW+eGHH8yll15qmjVrZnJzc40xxlxwwQVmwoQJvvXvu+8+k56ebl599VWzZcsW38+ePXuMMcbs2bPH3HDDDWbx4sXm119/Ne+//745/PDDzUEHHWSKi4vjcozBhHv8kydPNu+9955Zs2aNWbJkiRk9erTJyMgw33//vW+d++67zzRr1sy8+eab5rvvvjOnn3666dKliykqKor58dUl3OOvcuyxx5pzzz23xvJkev737Nljli1bZpYtW2YA8/e//90sW7bMrFu3zhhjzIQJE8wFF1zgW/+XX34xWVlZ5sYbbzQ//vijmTZtmklJSTHvvvuub526Hs9EEu7xz5kzx6Smpppp06b5vfd3797tW+f66683ixYtMr/++qv57LPPzNChQ02rVq3Mtm3bYn58dQn3+KdOnWreeOMN89NPP5kVK1aYa665xrhcLvP+++/71qnPz3+VP//5z6Z///4B95lMz//ll19usrOzzaJFi/xez4WFhb519v38++yzz0xqaqp56KGHzI8//mgmTZpk0tLSzIoVK3zrOPH5ryCVhB5//HHTsWNHk56ebvr162e++OIL322DBw82Y8aM8f3eqVMnA9T4mTRpkjHGmMLCQnPiiSea1q1bm7S0NNOpUydzySWXJOQHSZVwjn/8+PG+ddu2bWtOOukks3TpUr/9eb1ec9ttt5m2bdsat9ttjj/+eLN69epYHU7Ywjl+Y4xZtWqVAcz8+fNr7CuZnv+q09n3/ak63jFjxpjBgwfX2KZPnz4mPT3ddO3a1cycObPGfoM9nokk3OMfPHhw0PWNqZgOon379iY9Pd3st99+5txzzzU///xzbA8sROEe//33328OOOAAk5GRYVq0aGGGDBliPvjggxr7ra/PvzEVp/JnZmaap556KuA+k+n5D3TsgN97OtDn38svv2y6detm0tPTTc+ePc1bb73ld7sTn/9WZQNFREREJEwaIyUiIiJik4KUiIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIg3Ozp07adOmDWvXro1oP6NHj+bhhx92plEikpQUpEQkKY0dOxbLsrAsi7S0NLp06cJNN91EcXFxndvec889nH766XTu3DmiNtx6663cc8895OXlRbQfEUleClIikrSGDx/Oli1b+OWXX5g6dSpPPvkkkyZNCrpNYWEhTz/9NBdddFHE93/ooYdywAEH8O9//zvifYlIclKQEpGk5Xa7adeuHTk5OYwcOZKhQ4eyYMGCoNu8/fbbuN1ujj76aN+yRYsWYVkW7733Hn379iUzM5M//vGPbNu2jXfeeYeDDz6Ypk2b8qc//YnCwkK//Z166qm8+OKLUTk+EUl8ClIiUi+sXLmSzz//nPT09KDrffLJJxxxxBEBb7vjjjt44okn+Pzzz9mwYQPnnHMOjzzyCM8//zxvvfUW8+fP5/HHH/fbpl+/fnz11VeUlJQ4diwikjxS490AERG75s2bR+PGjSkvL6ekpASXy8UTTzwRdJt169bRoUOHgLfdfffdHHPMMQBcdNFFTJw4kTVr1tC1a1cAzj77bD788ENuvvlm3zYdOnSgtLSU3NxcOnXq5NCRiUiyUJASkaR13HHHMX36dAoKCpg6dSqpqamcddZZQbcpKioiIyMj4G2HHXaY799t27YlKyvLF6Kqln311Vd+22RmZgLU6PITkYZBXXsikrQaNWrEgQceSO/evXnmmWf48ssvefrpp4Nu06pVK3777beAt6Wlpfn+XXU2YHWWZeH1ev2W7dq1C4DWrVvbOQQRSXIKUiJSL7hcLm655RZuvfVWioqKal2vb9++/PDDD47d78qVK9l///1p1aqVY/sUkeShICUi9caoUaNISUlh2rRpta4zbNgwvv/++1qrUuH65JNPOPHEEx3Zl4gkHwUpEak3UlNTueqqq3jggQcoKCgIuE6vXr04/PDDefnllyO+v+LiYt544w0uueSSiPclIsnJMsaYeDdCRCSW3nrrLW688UZWrlyJy2X/78np06czd+5c5s+f72DrRCSZ6Kw9EWlwTj75ZH766Sc2bdpETk6O7f2kpaXVmFdKRBoWVaREREREbNIYKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERm/4fOYkpMWSiUYYAAAAASUVORK5CYII=", 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", 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", 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", 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", 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", 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", 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", 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222/n9NNPp3v37hx++OGMGjWKCy64gCOOOMJjf1WnM1eXkZFBx44da/3wZWRk8Pvvv7v/drlcPPzwwzz22GNs2LDBPUYI6u6ehIrQCLB///4617PL29mavu775ZdfgD/GqNVU1dYq3p6zFi1aeDw3gZo+fToOh4M777yTlJQUnnrqKcaPH0+zZs14+OGHgYrxKgMGDLD9GFXsPvf1fZ7at2/PrFmzeOyxx/jll1947733uPfee7n11ltp3759wGfjbdq0CagI8TUdcsghvPfeexQUFNCkSRP38rpe95q6d+/O/PnzcTqd/PTTTyxatIj77ruPSZMm0bVrV4/vhOpjjqrUfM03bdrk9fU55JBD3PcHE6R69uxJz549AbjwwgsZMWIEp556Kl9++SWWZdXqjquuuLgYqN1F17lzZ/c4sfPOO49JkyYxfPhw1q5d61738ccfp6ioiOuuu47rrrsOgPPPP58DDzyQV1991efZmAsWLKBly5aMHj3a9jFL8BSkpEE7+OCDAw5wf/vb35gzZw6TJ09m0KBBZGRkYFkW48aN8xirMGTIENavX8/rr7/O+++/z3//+19mzJjB7NmzPX7QvFXo6lpePbjdfffd/POf/+Svf/0rd9xxBy1btsThcDB58uQ6x00A7h+EH374wa9TwH1VM6qHt+p8TV/h7b6qts6fP99j/rAqiYmeX0W+nptgfP755/Tp08cdpC+44AJ27NjB9ddfT7NmzRg3bhzLly/nlVdeCfqxAn3uA2VZFt27d6d79+6cfPLJHHzwwSxYsCAi0xrU9br7kpCQQK9evejVqxeDBg3i+OOPZ8GCBR6fTX8+D5F29tlnc+mll/K///2PHj160L59e6CiklfT9u3b3XOF1bfP//znP3z88ceMHDkSqPgH1Ouvv87mzZvZuHGjO3wNHjyYNm3akJmZWWs/mzdv5pNPPmHSpEkkJSUFf7Bim4KUSA0vv/wy48eP58EHH3QvKy4urnX2DkDLli2ZOHEiEydOJD8/nyFDhnDbbbeF7Aft5Zdf5vjjj+fJJ5/0WL5v3z5at25d57ajR48mISGBZ555xq9Bzy1atPB6jFVVi2AceOCBQMXZWqGqTAbajWVZVq0uu+uuu44dO3Zw1113sWDBAvr27cvpp58edNsCfe6D0a1bN1q0aOH1x70+VZWStWvX1rpvzZo1tG7d2qMaFQpVFTe77fXV1qr7IfD3hi9VXWpVlegDDjiANm3aeJ3I9quvvvIrNNfcZ3WdOnVyV+b27dvHihUrOOuss7zu57nnnsMYo269GKCz9kRqSEhIqPWv4EcffbRWZabm2YlNmzbloIMOCunZiN7a8tJLL7Ft27Z6t83OzuaSSy7h/fff59FHH611v8vl4sEHH2Tr1q1ARdjJzc3l+++/d6+zfft299lQwRg5ciTNmzfn7rvvpqysrNb9NWeF9kd6ejqA1/DnzfDhw/nll19qjbO65557OPTQQ9m4cSOnnXaae4qEYAT63Pvjyy+/pKCgoNbyr776ij179njtnqtP+/bt6dOnD/PmzfN4HlevXs3777/PSSedFPA+q3zyySdeX+uqcVd22nvSSSfx1VdfsXz5cveygoICnnjiCbp06eIes1cV/vx9b+zcubPWsrKyMp5++mnS0tI8xgKeddZZLFq0yCOUL1myhP/973+MHTvWvczXe7pqTN6RRx5ZZ5umTJlCeXk5V199tdf7n332WTp16lTnFBQSGapISVDeeecd978Gqxs8eDDdunWLQouCd8oppzB//nwyMjI49NBDWb58OR988EGtMUmHHnoow4YNo1+/frRs2ZJvvvmGl19+udag+mDbcvvttzNx4kQGDx7MDz/8wIIFC/x+bh988EHWr1/P3//+d1599VVOOeUUWrRowebNm3nppZdYs2YN48aNA2DcuHHceOONnHHGGfz973+nsLCQWbNm0b1793oHttenefPmzJo1iwsuuIAjjzyScePG0aZNGzZv3sxbb73FMcccw7///e+A9ln1A/fCCy/QvXt3WrZsyeGHH+5zjMyUKVNYuHAh48ePZ/HixQwePJj8/Hyee+45NmzYwNFHH82dd97JoEGDGDFiRL2Pv2TJEve4mOrGjBnD4YcfHtBz74/58+ezYMECzjjjDPr160dycjI///wzTz31FKmpqe7pDQJ1//33M3r0aAYNGsRFF11EUVERjz76KBkZGUFdg/Lee+9lxYoVnHnmme5xgytXruTpp5+mZcuWXufXqs9NN93Ec889x+jRo/n73/9Oy5YtmTdvHhs2bOCVV15xh+ADDzyQzMxMZs+eTbNmzWjSpAkDBgzwOb7r0ksvJS8vjyFDhnDAAQeQk5PDggULWLNmDQ8++KDHGKWbb76Zl156ieOPP55//OMf5Ofnc//999OrVy8mTpzoXu+uu+7is88+Y9SoUXTq1Im9e/fyyiuv8PXXX/O3v/3N4+oP99xzj3t8XmJiIgsXLuT999/nzjvvdM+JVd3q1av5/vvvuemmm0JWfZMgRPOUQYlfdZ2uTY3Tjomhmc29ocYp9L///ruZOHGiad26tWnatKkZOXKkWbNmjencubMZP368e70777zT9O/f32RmZpq0tDTTs2dPc9ddd5nS0lL3OuPHjzdNmjSp9ZhDhw41hx12WK3lNWd4Li4uNtdee61p3769SUtLM8ccc4xZvny5GTp0qN/PR3l5ufnvf/9rjjvuOJORkWGSkpJM586dzcSJE2udnv/++++bww8/3CQnJ5sePXqYZ555xuf0B95e0/pm6F66dKkZOXKkycjIMKmpqebAAw80EyZMMN988417HV/Pmbd2fP7556Zfv34mOTnZr6kQdu/eba666iqTnZ1tEhMTTbt27cyFF15o1qxZY/Ly8kzPnj1N8+bNzQ8//OBzH1XvLV+3+fPnu9f197n3Z2bz77//3lx//fXmyCOPNC1btjSJiYmmffv2ZuzYsWblypV1Hrcxvqc/MMaYDz74wBxzzDEmLS3NNG/e3Jx66qnmp59+8linvs9oTZ999pm58sorzeGHH+4+9k6dOpkJEyaY9evXe6zra2Zzb+/z9evXm7PPPttkZmaa1NRU079/f7No0aJa277++uvm0EMPNYmJifVOhfDcc8+Z4cOHm6ysLJOYmGhatGhhhg8fbl5//XWv669evdqMGDHCpKenm8zMTPOXv/zF5OTkeKzz/vvvm1NOOcV06NDBJCUlmWbNmpljjjnGzJkzx2MGc2OMWbRokenfv79p1qyZSU9PNwMHDjQvvviiz/bedNNNBjDff/+9z3UkcixjojiST0RERCSOaYyUiIiIiE0KUiIiIiI2KUiJiIiI2BQ3QWr69OkcffTRNGvWjLZt2zJmzBiv84nU9NJLL9GzZ09SU1Pp1auX10seiIiIiNgRN0Hqo48+4sorr+SLL75g8eLFlJWVMWLECK/zqlT5/PPPOe+887jooov49ttvGTNmDGPGjGH16tURbLmIiIg0VHF71t6uXbto27YtH330EUOGDPG6zrnnnktBQQGLFi1yLxs4cCB9+vRh9uzZkWqqiIiINFBxOyFn1fT61a9YXtPy5cu55pprPJaNHDmShQsX+tympKTEY2Zql8vF3r17adWqlSY+ExERiRPGGPbv30+HDh1CcsUCX+IySLlcLiZPnswxxxxT55W+c3JyyMrK8liWlZVFTk6Oz22mT5/OtGnTQtZWERERiZ4tW7bQsWPHsO0/LoPUlVdeyerVq/n0009Dvu8pU6Z4VLFyc3MrLyLZRBUpERGROFExcqmAZs2ahfVx4i5IXXXVVSxatIiPP/643oTZrl07duzY4bFsx44dtGvXzuc2KSkppKSk1FpuWZaClIiISBwxhrD/dsfNWXvGGK666ipee+01PvzwQ58Xn6xu0KBBLFmyxGPZ4sWLGTRoULiaKSIiIo1I3FSkrrzySp599llef/11mjVr5h7nlJGRQVpaGgAXXnghBxxwANOnTwfgH//4B0OHDuXBBx/k5JNP5vnnn+ebb77hiSeeiNpxiIiISMMRNxWpWbNmkZuby7Bhw2jfvr379sILL7jX2bx5M9u3b3f/PXjwYJ599lmeeOIJevfuzcsvv8zChQvrHKAuIiIi4q+4nUcqUvLy8sjIyMCymmqMlIiIhEx6ehqtW2tqHTuMMezevYfCwqI61zEmn9zcXJo3bx62tsRN156IiEhDYFkWEyb8hdNOG01SUpKClA3GGMrKynjjjXeYO3cB0awJKUiJiIhE0IQJf2HcuLPJzMyIdlPi3rhxZwMwZ84zUWtD3IyREhERiXdNmqRz2mmjK0OUpVuQt8zMDE47bTTp6WkBvxahoiAlIiISIa1atSQpKSnazWhQkpKSaN26VdQeX0FKREQkQjS5c+hF+zlVkBIRERGxSUFKRERExCadtSciIiL1uu22qeTn7+eBB/7l9f61a9cwZ85TfPvtt+Tn55OVlcWRR/bjggsupHPnzvz222+cfvqptbYbNWo0d9xxJ06nk/nzn2bRojfJyckhJSWF7Oxsxow5gzFjzgj34dmmICUiIiJB+eSTj7nxxhsYOHAQt99+Jx07duT33/fywQcfMHv2LKZPv8e97syZs+jWrZv779TUFAD+858neO21V7n++hs45JBDKSgo4OeffyIvLy/ixxMIBSkRERGxrbi4iNtvn8YxxxzD/fc/6F5+wAEHcPjhvdi/f7/H+hkZGbRu3brWfj7++GPOPnssw4ef6F7WvXv38DU8RBSkREREYoCjqI7LnTgcmJQU/9a1LExqap3rutJCN+/S8uXL2bdvHxdcMN7r/c2aNfNrP61ateLrr7/m7LPH0qJFi5C1L9wUpERERGLAkUOO9XnfvmOOYd1Dj7j/7j1iOAnFxV7X3X9kP9Y+/oT7716nnULSvn0e63zz9YrgGlvNli1bAOjSpYtf61900UQcjj/OdfvPf/5Ljx49ufrqa7jpphsYNWoE3bp144gjejNkyFCOOeaYkLU1HBSkRERExLZAr3N399330LVrV/ffWVlZAHTr1o3nn3+Rn3/+me+++45vv13JtddezSmnnMItt9wa0jaHkoKUiIhIDFj58ac+7zMOz9mKvnv/A9/r1pic8oc3FgXXsHp06tQJgI0bN3LEEUfUu35WVhbZ2dle73M4HBx22GEcdthh/PnPf+btt99m6tR/MnHiRRxwwAEhbXeoaB4pERGRGOBKS/N5qz4+qt51q42P8rVuKA0cOIjMzEzmz5/n9f6ag80D0a1bReWqqI4xYdGmipSIiIj4JT8/n7Vr13osy8jI4JZb/slNN93INddczbnnjiM7O5t9+/bxwQeLycnJ4e67p9e77xtvvIHevXtzxBFH0KpVa377bRszZ/6bTp06+z3+KhoUpERERMQvK1as4Pzz/+yx7PTTT+eWW27lySfnMHfuHP75z/+joKCArKwsjjrqaC6//Aq/9j1w4EDef/895s6dQ35+Pq1ateKoo45m0qRLSUyM3bhimUBHiTUyeXl5ZGRkYFlNdaFJEREJSufO2Tz22L8q51HSb0rwDLt37+aKK65h06YtnvcYgzH55Obm0rx587C1QGOkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREQipGIAtM7xCqVoP6cKUiIiIhGyZ89eysrKot2MBqWsrIzdu/dE7fEVpERERCKkoKCQN954h337cgGjW5C3fftyeeONdygsjN7M57E7w5WIiEgDNHfuAgBOO200SUlJmqPQBmMMZWVlvPHGO+7nM1o0IWc9NCGniIiEQ3p6Gq1bt9Jviw3GGHbv3lNnJSpSE3KqIiUiIhIFhYVFbN68NdrNkCBpjJSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNgUV0Hq448/5tRTT6VDhw5YlsXChQvrXH/ZsmVYllXrlpOTE5kGi4iISIMWV0GqoKCA3r17M3PmzIC2W7t2Ldu3b3ff2rZtG6YWioiISGMSVzObjx49mtGjRwe8Xdu2bcnMzAx9g0RERKRRi6uKlF19+vShffv2nHjiiXz22Wd1rltSUkJeXp7HTURERMSbBh2k2rdvz+zZs3nllVd45ZVXyM7OZtiwYaxcudLnNtOnTycjI8N9y87OjmCLRUREJJ5YxhgT7UbYYVkWr732GmPGjAlou6FDh9KpUyfmz5/v9f6SkhJKSkrcf+fl5ZGdnY1lNdUVukVEROKEMQZj8snNzaV58+Zhe5y4GiMVCv379+fTTz/1eX9KSgopKSkRbJGIiIjEqwbdtefNqlWraN++fbSbISIiIg1AXFWk8vPzWbdunfvvDRs2sGrVKlq2bEmnTp2YMmUK27Zt4+mnnwbgoYceomvXrhx22GEUFxfz3//+lw8//JD3338/WocgIiIiDUhcBalvvvmG448/3v33NddcA8D48eOZO3cu27dvZ/Pmze77S0tLufbaa9m2bRvp6ekcccQRfPDBBx77EBEREbErbgebR0peXh4ZGRkabC4iIhJHIjXYvNGNkRIREREJFQUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbIqrIPXxxx9z6qmn0qFDByzLYuHChfVus2zZMo488khSUlI46KCDmDt3btjbKSIiIo1DXAWpgoICevfuzcyZM/1af8OGDZx88skcf/zxrFq1ismTJ3PxxRfz3nvvhbmlIiIi0hhYxhgT7UbYYVkWr732GmPGjPG5zo033shbb73F6tWr3cvGjRvHvn37ePfdd/16nLy8PDIyMrCspliWFWyzRUREJAKMMRiTT25uLs2bNw/b48RVRSpQy5cvZ/jw4R7LRo4cyfLly6PUIhEREWlIEqPdgHDKyckhKyvLY1lWVhZ5eXkUFRWRlpZWa5uSkhJKSkrcf+fl5YW9nSIiIhKfGnRFyo7p06eTkZHhvmVnZ0e7SSIiIhKjGnSQateuHTt27PBYtmPHDpo3b+61GgUwZcoUcnNz3bctW7ZEoqkiIiIShxp0196gQYN4++23PZYtXryYQYMG+dwmJSWFlJSUcDdNREREGoC4qkjl5+ezatUqVq1aBVRMb7Bq1So2b94MVFSTLrzwQvf6l112Gb/++is33HADa9as4bHHHuPFF1/k6quvjkbzRUREpIGJqyD1zTff0LdvX/r27QvANddcQ9++fbn11lsB2L59uztUAXTt2pW33nqLxYsX07t3bx588EH++9//MnLkyKi0X0RERBqWuJ1HKlI0j5SIiEj80TxSIiIiIjFOQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGb4i5IzZw5ky5dupCamsqAAQP46quvfK47d+5cLMvyuKWmpkawtSIiItKQJUa7AYF44YUXuOaaa5g9ezYDBgzgoYceYuTIkaxdu5a2bdt63aZ58+asXbvW/bdlWZFqrohtbY2Lg3DRDGiGoTmGJkAKhiTgBZL41ar4d9BA4+TPpoxEwAU4a/z3GSuJ760EAA4yLkZRTjFQiEURUIRFIbAfiw042KfPiIiI3+IqSP3rX//ikksuYeLEiQDMnj2bt956i6eeeoqbbrrJ6zaWZdGuXbtINlPEq0OMk4G4aIuLLGPIwtCWiv9mYTjZSuObysBzLuU8ZEp87muVlcCvlQXlQ3BxJWU+1/2SBL6nYr9H4uThOvZ7iZXCUyQDMMyU85Qp5ncs9mGxG4udWOywKv67jET+VxnmMAYUwESkEYqbIFVaWsqKFSuYMmWKe5nD4WD48OEsX77c53b5+fl07twZl8vFkUceyd13381hhx0WiSZLI5JmDD1w0QMXXXHRzRi64uLvVgo/V4aj0Ti5v44Q0w7j/v+dWKzDIg+L/VjkU1ExKgHKsNjKH6HlWxzcQTJOCxymor8+gar/Gv5XrQd/KxYvkEg6hjQgFUjHkA40x7C72n7bYOhcefNQ+eckC/5XGbqG4uQVVxGbcbAViy042GJV/heL1SSwV0FLRBqguAlSu3fvxul0kpWV5bE8KyuLNWvWeN2mR48ePPXUUxxxxBHk5ubywAMPMHjwYH788Uc6duzodZuSkhJKSv74scvLywvdQUjcyzSGYqC4MhSca8q4y5TQGeN1wGEPXPxcWQ1ahYN3SGAHFjtwuCs7OypvG6rt4QUriResJL/atMpKYFVlWKOerPK5lcjnln8f+8UkMtBKJxNDSwytMWSZP6poa6u1NxtDC6AFLnoD4KR6/rrMSuE/laGrr3EyxZSyBYstVkXw2oCDdTjIVdgSkTgTN0HKjkGDBjFo0CD334MHD+aQQw7h8ccf54477vC6zfTp05k2bVqkmigxLNkY+uCiP04GGCf9cXIQhjOsVN6gIuSUAl0rE8NuLNbgYD0WGywHG3DwdWWIAvjQSuRDP0NMLNhnWR7tB3wGtVdIZKWVTjaGbFxkm4r/dqz8u3pIPBwXZ1Fe8UeNYtcuY3GllcIrlSGytXHRDcMaHOQpZIlIDIqbb/XWrVuTkJDAjh07PJbv2LHD7zFQSUlJ9O3bl3Xr1vlcZ8qUKVxzzTXuv/Py8sjOzrbXaIlL/Y2TGaaYvrhI8XJ/x2q//h+RyDArjZ9xsNsK70mw6Sntw7r/YG2svAEUlmz3ud6XJPB3K4Vs46JTZdDqiqE9hjYY8qqltZE4edoUA7DVWPyEo+JmOfiJBL7DQaEClohEUdwEqeTkZPr168eSJUsYM2YMAC6XiyVLlnDVVVf5tQ+n08kPP/zASSed5HOdlJQUUlK8/XxKQ2MZQz8qzmJbQQLvVFaL8oGBuADYhcVXOPjSSuArEviaBI+z2vZaFp+E4GMU6yEpUHUdz1ZgjpflTYyLbqaUDVYylFb8gykZ+A2LDhg6YuiIkxHVug1PtdJ4u/L5725cHIyLFTjICXOoFRGpEjdBCuCaa65h/PjxHHXUUfTv35+HHnqIgoIC91l8F154IQcccADTp08H4Pbbb2fgwIEcdNBB7Nu3j/vvv59NmzZx8cUXR/MwJIpaGMNoyhllyhmBkzaVv8gvkugOUmtw8BcrlS9JYANWyM5Ga2hhKdQKLAc/WBXzvFU9Vy9U3jKMk56uUnqaUg4q28uhuDgUFz9W6zI8lzJuM6UA/GYsVuJgBQmstBJYgYPtClciEgZxFaTOPfdcdu3axa233kpOTg59+vTh3XffdQ9A37x5Mw7HH1+Wv//+O5dccgk5OTm0aNGCfv368fnnn3PooYdG6xAkSpKN4WVTxAicVB/CnQd8QCJvVBu75LIsnse/gd6+RDM0NU/xfiJFtOWVbLW9ba6VwJcJaXxJGiRmeN5Z2Y2Yi8WPOOiJiw4YOuDklGrVq8NJd59B2cW4KAGFKxEJmmWMMfWv1njl5eWRkZGBZTXVZJ5xJM0Y+uHk02oB6XNXAQNw8T0O3iGRd60EPieB8iBf10iFplgNSOEQTOhKNy66l2zjSFz0M06OxEUnXLSymuKqfK3nuYo4n3J+w+IbEvjCcvBlZddtgT7nIg2CMQZj8snNzaV58+ZhexwFqXooSMURYzgeJxeZMk6lnGSgvdXUPaZpoHHyO7DWSqhzN/UJV3BqTEEpFAIJW8nGRanlcA+Cf9VVxCmU1zwnESfwHQ4GWelBB2wRia5IBam46toT8SbFGP5MOX83pRxROUgcYAMW3XCxsvLn8gubASocwSkSoamlFX9nm+41W/xet67nsGbIKq3swqt6Lc+nonJ1hKuEfqaY/q4ijnYVk23KSQKPEPWCqwiAZVYCH5HATzg0i7uIuKkiVQ9VpGLbMFPO86bYPWi8AHiaJOZZSXwdxA9eKMNTOEJTPIakUAokcFVXXxWrvSmjrXHynaNi0HuKcbG1eD2pNWad/4gEllkJLCUh6AqniISHuvZihIJU7Ek3xj13UJZxscEUsB2LmVYyT5Fk+6K7oQpPoQxOkQpMrV1tIvI43ux27Ar5PgMNWr4CVoIx9HcVc6yrkONcRQxwFZJe7f53SOAUxx9LmhnDfn1PiMQEBakYoSAVOw43Tu4yJaQBI6r9eB1lnHyLA6eN1yeWwlM4QlM0A1K4BBO8AglY3sJVsnHRz1XCsa5CBpfv4xUrkSesikvfdDQufjUFfImD96xE3iORFTjcA9xFJLIUpGKEglT0dTYuppkS/kI5DqAM6GY14bcgTl0PNkAFG5xCFZpiISi1TUrza72dZUVhbskfAg1b/gSs+roFTynezHOVs7BX2UPFNQvftxJ5i4Swz34vIn9QkIoRClLR08a4uNmUchlllZe7rZg4859WCuts/CBFMzwFG5zCEZj8DUCxJthA5m/Iqi9ceQtWHV1lDHcVcIKzkONdhWRUO/lhnJXKS5XXEGxqDCVAmb5TRMJGQSpGKEhFx9HGyWJTSLPKvxeTwM1WCittDOwNJkBFIzyFKjTFa1AKBTthy5+AFUi4SjSGo13FnOAq4ARnAWemdOR3K4HCku1MMSXcaEr5gERetRJZRKIuyiwSYgpSMUJBKjqSjOFnU8BuLG62UvjQCnymjkgHqGgEp3CFpZapsTkzyt7i8pDsJ5CgVV/AslO5eqFkGye5Ctx/lwAfkMCrVhKvk8jv+q4RCZqCVIxQkIqMrsbF300p11kp7kHjHY2LrTaudWc3QEUqPNkNTqEITbEakELNbuDyJ2AFE6yqQpVlDEeYEk515jPGmU+PymsEAuwDsqymmhBUJEgKUjFCQSrMjOEyyrjflJAOXGul8JCVXO9m3sRygLITnoIJTuEMTK1SovM52FMSuq+qQINWfQGrrnDlK1hVr1T1cJVwujOf08p/5384GOf447X/j6uYbywHr5LILg1WF/GbglSMUJAKn9bGxX9NMafiBOBDErjCSuWXAH8sIhWgwh2e7ASnUASmaAWjcAomdPkTskIdrKqHqhTjoqTycjaHGic/mEKg4vI1S0ngZSuR10jUGYAi9VCQihEKUuFxoilnjimmPRVnL91kpfAoSZgIdOOFM0AFEp4CDU7BhKZIhKVWKaH7KtlTEt72Bhq0gg1XvoJVfaGqtSnnL+V5nOHcTz9T4l5eTkWomm4l85GN8YMijYGCVIxQkAq9yaaUByt/FH7EwflWKt8HeDZeuANULIQnO8EpVIEplKEo0oINYf6GrPrCVaiDVRdXKWc48znDuZ++lZ+fc5M78HL5fqDimpMloOsAilRSkIoRClKh18s4+cwUMo8krrdSKA7geY3HABWu8BRMaIrnoBQKdsKWPwGrrnDlK1jZCVXdXKWMcebzSGILyi2LwpLtTHOVcA5lzLOSeIYktqrrTxo5BakYoSAVGpnGeFwDr71xsT3MY6HCEaBCHZ7CHZxCFZhaJTtDsp9w21Ma/AWEAwlZ9YWrUAWregesG8PXJZvoWXn2n4uK6RTmWUm8RiIl+u6SRkhBKkYoSAVvtCnnGVPEyVY6X0RgQs1YD1DhCk/BhKZ4CUqhYDds+Ruw6gpXgQYrf0NVXslWmhgXY5z7Od+Zx7GuP/a1B3iMZG5zpNTTcpGGRUEqRihIBWesKWO+KSYJeIokLnGkBrR9uEJUKANUKKtP4QxOoQ5LbVPKQro/O3aWJIV0f4GGLH/ClZ1gZTdUVVWourpK+bMzj78488g25fyHJC6r+uwZQxK6PI00fApSMUJByr6/mlJmmxISgGdJZKKVGtAkg+EIUZEOUKEMT4EEp2BCUywEpHAIJnT5G7DqC1aRDlUOYzjRVcAGK5n/OSrmZzuseCtvmCKeJInHrKSgLv4tEssUpGKEgpQ9fzelzKg8s+gJkrjSSsHl5/MXzSpUKAJUNMKTneAUzsDUKqWk/pUCsKckvN1SdkJWKMJVoMHKn1BV35QK95Tu5ErnPgDKgJdI5CErmRU2ut1FYpmCVIxQkArcFFPCnZWDXu8niZusFL9PyY5WFSoSAcqf8BSO4BRsYAp1KIqUUISvQAOWP+HKTrAKVajKK9lKgjGc5MrnivJ9HmOpPiGBhyuv9efvP3pEYpmCVIxQkAqMwxheNsWcTjn/tJK5m+SwhKhIVqHCHaD8CU/hDk7xGpaCZTds+RuwgglWkQhVvV3FXFn+O2c795MEbMHiIKuJrvMnDULcBKmSkhJSUhru2SAKUoFLMoZTKedVy/9/zYc6RDWEAOVveAokOIUqMLVMr//ivpG2tzD4izpXsROw/AlX9QWrcIQqfwJVO1POpPJ9bHQWMLvyWpcOY5hEGfNJokDffRKHYjZIvfPOOzz//PN88sknbNmyBZfLRZMmTejbty8jRoxg4sSJdOjQIVztjTgFKf8cYFxsw7I1q3KkQ1Q0A1Qoqk+RCE6xGJSCFWzQCjRcBRusAglVoQpU1Z1WvJkFppidWNxvJTOLJIr0HShxJOaC1GuvvcaNN97I/v37Oemkk+jfvz8dOnQgLS2NvXv3snr1aj755BOWL1/OhAkTuOOOO2jTJvAr3scaBan6dTMulptCXiORv1kpAZ1WHU8hKpwBKlThKdDgFK7AlJERmv3m5oauylQXuyHL33AVT6GqKlCNduYzvWwXB5qK914OFvdZyTxOUkBXIxCJlpgLUoMGDeKWW25h9OjROBy+T5fdtm0bjz76KFlZWVx99dUha2i0KEjVrbkxfGYKORQXX+HgeCvd7y9Zf0NUJLrygqlCRTNABRKcgglNoQpGkRCq8GUnXIUqWAUaqsIVqBKM4TxnHjeW76GLqdjfb1jcU1mh0qB0iWUxF6QaKwUp3xKM4U1TxEicbMVioJXu92VfIhmiwlWFshugIhWeAg1O8RSWghFM0Ao0XIUiWIUjVAUaqBKN4S/OPG4o30MnU87nODjOStcFkiWmKUjFCAUp3x50FTOZMgqBIVY63/o5D02shKhYClChCE+BBKdQhab01r4veRIuhbv9v8ROIOwGrEDClT/Byk6o8rfrr74qVX2BKskYLnDmstZKZnF5LgAZlSeXPEOigpXElJgOUsYYXn75ZZYuXcrOnTtxuVwe97/66qsha2C0KUh5N9KU87ap+AIea6X6fYZeQw1R0QpQ/oYnu8EpGkEpFEIVtuyEK3+DVSRDVagDVXXXF23kVkpZSgJXWims1cSeEiMiFaRsfdtMnjyZxx9/nOOPP56srCwFjEYmxRgeN8UAPEJSowhRdqpQdgNUKMJToMEpXgOTL76OJ9CAVfN59CdYVX996gpV1V9nX6Gq6n3iLVBVvb9qBqqq92P1QFX1/q0KVFXv8+qBqm1SmjtMVX1+qgJV1edtr9ni/nxWBaq8pAwKy3ZzPE6+NYXcZ5KZbiVTot8FaSRsVaRatmzJM888w0knnRSONsUUVaS8G2nKuc6UcpqV5tcp0ZEKUXbHQ4WyChWOABXK8BSq0JTUNrKVh7Kdob3ocpVgqleBVKxCVanyVaUKZYWqrjFU3qpTnV1lPFi2k5GuAgD+h8UkK5VPrPB0w4r4I6a79rp27co777xDz549w9GmmKIgFRqhClJ2Q1S0q1DhClD+hCe7wSnSQSlYoQpadoNVpENVoN1+YQ9UxnC6K5/7S3fSnorX4nIrhScqJ/gUibSYDlLz5s3j3Xff5amnniItLTLzvESLgtQfWhhDEwxbA7xafEMKUbEQoEIdnuItMAUq2IBlJ1iFOlSFskoVbKCqb/xUc+PkzrLdnOncT28rjS0Bfl+IhEpMB6mioiLOOOMMPvvsM7p06UJSkueHeOXKlSFrYLQpSP1hrquI0yhnopXK6xEeFxXqEBWJrjxfIcpXgAq2+uRveApFcEpo3yToffjDub0gLPsNJlyFM1gFG6qiFai8dfe1MeXsshIpLNkOwJ9MOR+RgLORf49K5MT0YPPx48ezYsUKzj//fA02byT6GicXUI4L2E5k54qKdogKd4AC3yEqFOHJbnCKVFiy24ZgQlbN5ySQYFX9Ofc3VFW9jvUFqqr3gT+D1L0FKl+D070NTPc1KL16mGqZmljngPS6BqPvqgxU6SntOaN8P3PLtvMWCZyHf+MqReKFrYpUkyZNeO+99zj22GPD0aaYoopUhbddhYzEyQISudDh37+u/QlSwYQo8B2kAg1RsViFqitE1RegAg1PsRCaQiEUFSw71apAq1Sh7PoLtEIViupUoIPRT3Xu58nSHNIwfIGD0600dqvLT8IsUhUpW+/k7OzssDaqLjNnzqRLly6kpqYyYMAAvvrqqzrXf+mll+jZsyepqan06tWLt99+O0ItbTiGmnJG4qQMmGr5N1NzINfQsyuWQlTblDKvIapVSonXENUyvajOKpS3EJXeutx98yapbYL7Vp+E9k08bsGy2jYP6BYuoTguf5/D6up7bWqqeo39Ge9W13sFfL/HwHuwb5XsrPUebpViar3fa34uqn9+2ialeXzOqn8Wq//jp+ofSm8mNOO05I7sxcFAXHxqCulmPOcfFIlXtipSb731Fo8++iizZ8+mS5cuYWiWdy+88AIXXnghs2fPZsCAATz00EO89NJLrF27lrZt29Za//PPP2fIkCFMnz6dU045hWeffZZ7772XlStXcvjhh/v1mI2+ImUMn5pCBuHiMZL4myPVr83CXY0KNESB9yAVqhDlfR+BVaF8/aiGovoUTFgKZ/Cpj9mZF9L92a1YxVKVqq4KVSjGT9VXnQpm3FR3VymvlG6liylnJxanWml8owk8JUxierB5ixYtKCwspLy8nPT09FqDzffu3RuyBlY3YMAAjj76aP79738D4HK5yM7O5m9/+xs33XRTrfXPPfdcCgoKWLRokXvZwIED6dOnD7Nnz/brMRt7kDrNlPGaKaYA6G41IcePcny0QhQEVo0KJEQF0pUXqgAFdYeo+gJUoOEpmoEpUKEIWLEaqqIRqPzp7rPT1ectTLU15bxSso0+poQCoJfVhE3q5pMwiOnB5g899FCIm1G/0tJSVqxYwZQpU9zLHA4Hw4cPZ/ny5V63Wb58Oddcc43HspEjR7Jw4UKfj1NSUkJJyR8/hHl5of0XcVwxhqtNRVB4mOSQhahgNKQQZSdAhTI8xVNwqqlm2+0Eq+rPVSChquo1sDNA3Z9AFcjAdF9hqr4B6f4ORvd3IHr1Qejwx0D0moPQ80q2stNKZHRKNvNLf+M7V5lClMQ922ftRdru3btxOp1kZWV5LM/KymLNmjVet8nJyfG6fk5Ojs/HmT59OtOmTQu+wQ3AYJwMqZxYb0YIJ9ULdoC5N3bO0KspHCEqlN14dYUofwNUyMJT25bBbb8ztFXr6scVTKiKt0BV31l+rVJK/A5TUPF+D3WYqq4qTOVbDsYmH1Dx7VLq+/tYJB74/U+BgoLAyuCBrh8rpkyZQm5urvu2ZcuW+jdqoC6qrEbNIZG9IbwMTF1COS4qkMHlsRyi6hr87M+gatuDvNu29H0LVhj3HcyAdjtjyewOTveXvwPSfQlkIDrUft8HOgjda/u8DEAvtyxM5fdKmjGcaeq+gLdIrPI7SB100EHcc889bN++3ec6xhgWL17M6NGjeeSRR0LSwCqtW7cmISGBHTt2eCzfsWMH7dq187pNu3btAlofICUlhebNm3vcGqPmxjCWii/7JyNYjQq3QOaJ8iYcIaq+M/F88TdA+SUcYcmuELXDboC0e8af3TP9/BGKMOXtferzbNMQhan6zuYDaJ2cxTemkJdMMcebhnXxbGkc/O73WLZsGTfffDO33XYbvXv35qijjqJDhw6kpqby+++/89NPP7F8+XISExOZMmUKl156aUgbmpycTL9+/ViyZAljxowBKgabL1myhKuuusrrNoMGDWLJkiVMnjzZvWzx4sUMGjQopG1riM6jjCbATzhY7kfejodqVF3Xzqu1rp9n5/kbouxUoXzxJ0D5JZphKRA122mjW7DqOQmk2y+S3X2x2NUXaDefx/7qmLiz+gB0gELLwVIS6ImL/5pietOE/EZ4Yo/Er4DP2tu8eTMvvfQSn3zyCZs2baKoqIjWrVvTt29fRo4cyejRo0lICM/prC+88ALjx4/n8ccfp3///jz00EO8+OKLrFmzhqysLC688EIOOOAApk+fDlRMfzB06FDuueceTj75ZJ5//nnuvvtuTX/gh9NNGVNMKc9ZSTzsR0UqnGfqxUKXXiyEqLoCVLTDk2nbGmvn7rDsu042x1rZGUcV6Fl+4Ty7z58z++yc1efPGX11nc3nz9QI3s7ka2JcLC9eT1cMs0niSj+nWRGpS0xPfxBN//73v7n//vvJycmhT58+PPLIIwwYMACAYcOG0aVLF+bOnete/6WXXuKWW25h48aNHHzwwdx3332cdNJJfj9eYw1SVRzG4ArR+Ki6glQ0qlGxFqLsBCjwI0QFGZ5M29ZBbe9LSINXhAKVnSkTAg1U0QxToZgawde0CPXNMdW/eAtLTMX6Pa0m/KKz+SRIClIxorEHKX/EejWqoYYov6pQNkJUuIJTfYIOVgpTXoUjTIWjKgXwRtF6jsfJ5VYKT4RwbKY0TjF9iRhp2E425bSIYL62M91BvIpYiApgoLZp29rjFi1BP77Nwel2BqMHyu6Fo+vjzyD0QPk6m6+6uk7Q8GfKEV+f+Y+peJ6OM4F3i4pEi4KUeGhvXLxhivjN5IcsTNk9U6+hVaMiEqJsBKhYE3Soi9EwFYhQTo9gZ2qEWuv5mArkj/3Yr9ZX/3741EogH1CMkniiICUeTq2c8mAlDn6PwNxRsVqNisUQVe+p/HEeoLyx3VYb1alwh6lwzjUVaqGsSvmaDsGbj0igldWUCQ7/LpMjEgsUpMTDaZXzuLxp2Zr0PmpCXY3y6zEjHKJ88iM0hKvrzrRt63ELl6ACVQDiNUzFY1XK2z+iUlI7UK6xqBJnAgpSJ5xwAq+++qrP+3fv3k23bt2CbpRER6IxDKssqr9p7+pBtUSqWy+UArmGXijZDlH1CCY81QxK9QWnQNa1157GF6ZCpa4w5Y0/ValwsHT+k8SZgILU0qVLOeecc5g6darX+51OJ5s2bQpJwyTyeuAiDcijYiLO+oT7AsX+aijVqICFMUSFo8IUqn3GS7dkqIRy9vN48Kop5n+ufE7SLOcSJwLu2ps1axYPPfQQZ5xxRtxeT0+864sLgFUkuK+BFU6xOj6qppitRtUj0MARiS66qscJfh8BhqkwV6UkNApLtnM4Tg7EkB/txoj4KeAgdfrpp/PFF1/w448/MnDgQH799ddwtEuioE/lKcffxejQuWh169UU6mpUOLr0AgkakQhPsfCY4bwkTrx078WSmpeKAUg3hm5UVI5/jNHvIZGabL1TDznkEL7++muys7M5+uij+eCDD0LdLomCmVYyF1ipLLBqT8gXSfWd2VOdP3PWgP1uvVBWoyLVpRdoiIqmYAJVY+riC/cZfJGouvrjkMqq+A4s9mhmc4kTtt+pGRkZvPXWW1xyySWcdNJJzJgxI5TtkijYYDl41kriays0P/h2B5oHy+6cNnYH1/pbjfIm4GpUiEJUVCpCdYhYmAqgKhWP3XvxPk7qsMogpWqUxJOATs2qeYkUy7K455576NOnDxdffDEffvhhSBsnDVe8jI+qKdAzn+yw+wMe7xUa07Yt1s6d0W6GbQntmwR0+Ziktgm2Lmzc0FS/RMx5puIfM98qSEkcCejd6uuyfOPGjePTTz/lhx9+CEmjJPLaGheXmVK/z5SJ9Bl7oR4fZfdsPbtC0q0XojE+sVSJCoV4DZDhCFH+XHvPG2/X3At8H95/H3xduLimo11FjMBJOfCYrrMncSSgitTSpUtp2dL7l3mfPn1YsWIFb731VkgaJpF1OC5mmhJ+xMHbcTYZZ6wJtlvPjngNEw2JnYsZxzJvFy/2V80LF9e638tA89Wle5lOMk0wbNT4KIkjAf1iDh06tM77W7VqxYUXXhhUgyQ62laeKbOT6M4qHMhAc3/VdSmLureLjQG4odTQqlESOXtKPauqe0oC+67wVo2q3q23x3JwixV8ZUwk0hT7BYidIBUIf8/YC6d4H9wbaxT0vCvcHfx7fW9h+KYPqd6tV70aVb1bz32/l2qUSDxTkBIA2pr4C1LeBHMV+lhg92w9fyikiDfexkcF063nTV1jowY4i1hUsoVhmslc4pSClACQXlmRyo/zICXSWNkdaO6Purr1/BlkXqV6NSqvZCstjZM5ZdsZ6iriQhOda/uJBEtBSgCo+ipUjIouszPP+x079wa973iYWsBOG62du8PQkvAK5Iy9cHbrhboa5W2Qua+xUZYxPFG6nWxTzv+w+IeVavtxRaJJQUqAhhOkfP3rWCrEcpiKSNsCCKQ+Q60X0T5jLxaqUf6OjaoaYH5t+V5GugopAs6x0tgfget7ioRD9EfrSkyYayXxCQn8omwdkNzctJgYcG7t3N0op0BQNap+wVSj7Jyp523eqJoDzI9zFnJL+R4ArrJS+SFEV1MQiQb9agoAq60EXreS+CmOvtDqm6sm1kWrihGLVSlVo+wLVTUq0C49X9WoKr669NqZcuaUbiMBmEMic6N8bU+RYClISYMX6Hw3f2xnb06bUFQRvArBOKkqsRSm7LZF1aj6Q1Qg1aha64SpSy+/ZAc/4uB7HPxN46KkAVCQEgA6GxfnmTJG6BTksAjkBzSQakh1gQaLWAhTEWtDmKpRsSyUA8x9/WPEV4iq2aVXfeLNnZaDUVYao6w0ijQuShoABSkB4HicPGOK+YcpjWo76ppvJpRq/mvbX6Ge1DDgbqF6AkG8hClr586gKlEBHWcYQ1Qgr18kq1HBhqjqn4+aIcrbCR3+jIvq7yyisGQ7AE7LYocuAyMNhN7JAkBO5fl6WcTmWW/eugxC/hg2T/v29oPm7YcwZFWpMISpYIKNnceyv32A3Xkh7A6tqbGHqLrGRdWcL2pi+T6WlG7hQVcxmNj8jhGxS0FKgD+CVHs/g1TVvyztCudlIkI5BYLdcVKB8PWDHMkw9cd2oQ1V1fcX7D7DHaLCNcA8XkNU7X3UPS7K1+DyUc58ZpRVvPZ5WKDuPGlgNP2BALC9Mki1weAwBlecfNntLS7365p7e0qsWhcv3lOaQKtk/3/k3I9ZmEbLdM8KmbdpEAp3J5Le2vNf7WU7nSS1DdGZkTv31nnpmKrgYXdahLqCj7fLzYSzoqUQVSGSISqQweXVQ1T1cVFHuoqZW7qdBGAuiUyzkn22XyReqSIlAOzCohxIADqEqHuv+gDTeBHqa4z5y1ZVyk/hOLutZqUpXCEq4PFQoBBlQzhC1KGuEl4r2UoTDO+TwKVWqqpR0iApSAkALstibeXboReuqLbF14DzSIyT8sbbv+i9/XAFO1bKdhefH8HBViCJItvtVYjyUPO9u7MkKaBJN+2GqB6uEhaVbKUlLr7EwVgrjXKFKGmgFKTE7bvKt0NvAu/uijXexkl5O4Xb25iQSFSlQhqmwO8AEeuBKqgAFeDZedEOUYW7E+sNUbm5aba787yFqFrrhWmuqD6uElrhZCUOTrLSyVeIkgbMMkanUNQlLy+PjIwMLKspVgP/MhhgnLTC8DUOdvlxanJ6Svt612me0rHO+1ta2V6Xt3a18bq8bZL3Hw5v46RapdR+vWqOkwK8jpNqm1L7SvStUkpqP2567R8Vb5eMqTlWqoqv8VIJ7Zt4XW61be51uYc6xk15E81LywQd6myclRfOWcsDCVH1CeVkm+EIUXXNFVVYsp3TTRmfksAeTXMgUWKMwZh8cnNzad7cj+9OmxSk6tGYgpQd9YUpu0EKAgtTvgacN8QwBeEJVFXCGaxCVg0Lc4CChtGVB6Gb4qC+uaKaFm+gFIvNpZGZC06kPpEKUjprT8Iqr2RrvWEqFPw9ey+avJ3FB77P5HNuL/AZpszOvPrDVFXYCDBQeQs7gYarsHUf2pwXqqFXoSA0FyG2MyYKIL14I4tKtlKOxXCSyFEVShqR2P7lkYgbYJyMMeUstBL5MgIXMN5rttRZlQoHf6dC2FmSVKsqtackpVZVyt/pECD0YQr8qE7VM02CP6I+rioCAQpitwoFgV83L1IhKqNoA2+WbuVAU8ZGLJJ0EWJpZBSkxMMlppSJlJNoTESCVF12O3Z57d7bWVbktXvPW1VqT4nx2r3nr1gPUxBgdapKkMEqIoKYlTycAQriqwoF4QtRbYp+5c3SrWSbcn7F4kQrnS2qRkkjEzfv+L179/KXv/yF5s2bk5mZyUUXXUR+fn6d2wwbNgzLsjxul112WYRaHJ/etSq++Ef7eeaePzOcR3s+qWDO4PO9T/tTIoDvH9i6zuar68e+6iw0vwNE1VluYbyESsCqt8nmGCg7Z+MFWoXyJ0T5c0YeBFeFCtWgcrtTHBxQtJ73SraQbcr5GQdDrXQ2KkRJIxQ3g81Hjx7N9u3befzxxykrK2PixIkcffTRPPvssz63GTZsGN27d+f22293L0tPTw9o0FljG2yeYQw7TT6JwIFWE7++GMN59h6E7wy+iuWhHXgO/g8+B98D0MH3IHSoeyB6Fb8GpNclXFWrEIY3uxOWRrMCBfFRhQLfIeoIVzFvVs4TtQoHo6w0v870FYkkDTav5ueff+bdd9/l66+/5qijjgLg0Ucf5aSTTuKBBx6gQ4cOPrdNT0+nXbt2kWpq3Mu1LD4zCQzFySjKmU1oLukQqUHnvgTSxRfMeCkIvJsPvAequi4nUxUE6uvyq2IrVMVStaqaYGZ7D1eAguh040HkQxTALiuBfRj+h4OTrXT2NYJ/ZIr4Ehf/hFi+fDmZmZnuEAUwfPhwHA4HX375ZZ3bLliwgNatW3P44YczZcoUCgsL61y/pKSEvLw8j1tj807l2KiTje9qSXXBXsAY6r6IcaAznXu7Kj3438Xni9cfLB8/br66+ex09dX1Y+5v15Sdbq9YEkz7q56jcHThQWgm1gR7VShvA8qD7coDz+kNvM0Ttb50NydY6YxUiBKJj4pUTk4ObWtcJDUxMZGWLVuSk5Pjc7s///nPdO7cmQ4dOvD9999z4403snbtWl599VWf20yfPp1p06aFrO3x6C0SuYdShuOkpTHsjeEvykAGnvsSyAWNg61MQeCD0KH+ix37U6GqUjOMBN0FGAahCHzhrD5B9LrxIPgqFAQ2R1Re8RaucO5jd/l+5laelbdZXXkiQJSD1E033cS9995b5zo///yz7f1PmjTJ/f+9evWiffv2nHDCCaxfv54DDzzQ6zZTpkzhmmuucf+dl5dHdnZkT8+Ptp+sBFYZB20wdMfFF4Tm7L36uvfqmgrB1xl8gfLVxRdLYQp8d/VVqa/LD/wLVeA7tEQiYIWyQhZocKoS6u47qD88QfgCVMX2oenKAygs3sJDZTu5yJlLGbAcB2ujfEavSCyJapC69tprmTBhQp3rdOvWjXbt2rGzxtXly8vL2bt3b0DjnwYMGADAunXrfAaplJQUUlK8f4k1JqdZaWzHwuVnNaqwZLtfg86DEYrpECC8YQpqD0Kv+sH0Nm4KvA9ErytQwR8//v5UqcD/UFVdrHcD2g1OEL3qE4QuQEHoq1DgOR4qwzh5pXQ7f3IV4gKmWCnui5uLSIWoBqk2bdrQpk39VYZBgwaxb98+VqxYQb9+/QD48MMPcblc7nDkj1WrVgHQvn14f/Abgm1hKtsHU5WqS6yEqYp9BF6dgvAFKvAeOuyEq2gKJjhB+MITRD9AVezDvyoU+NGVV7KVbq5SXiz9jR6mlHzgfCuNN624GA0iElFxNf3Bjh07mD17tnv6g6OOOso9/cG2bds44YQTePrpp+nfvz/r16/n2Wef5aSTTqJVq1Z8//33XH311XTs2JGPPvrI78dtbNMf1JRgDJ0wbPAzWPlblQrHdAgQ2JQIEPy0COB9aoSKfXifHgG8T5EAvqdJqFLXdAlV6gtVvsRKsAo2MFUJNDhBZMMT+A5QEJpuPAi8Ky+vZCvHOAtZULqVVsAWLE6z0vhe3XkSZzT9QQ0LFizgqquu4oQTTsDhcHDWWWfxyCOPuO8vKytj7dq17rPykpOT+eCDD3jooYcoKCggOzubs846i1tuuSVahxB3jjRO3jBFFAI9aeJ3N1+42RkvFe7KFNQOVL66+sBedQrqr1BB7QDhb7CqL8CEKmiFKih5E+7wBPEZoMD/qQ0Aji7bSSvgKxycYaXp2nkidYibilS0NOaKVLoxbDL5tATGWam85Oc1tOKtKgWBVaYgMtUpqL9CBf5VqarYrVbFIjuhqUo4whOEPkBB/eOgKpYFXoWCGiHKGLCsiulMjOEyyphLEsWN7HtPGo5IVaQUpOrRmIMUwK2uEqZSyioc9LPSwY/nIFRBChpWmKrYl71ABaEPVVXiIVwFE5og8OAEsRWeKvYTWIAC/7vyTnbm87fSHEZb6RQ0wu85aZgUpGJEYw9SLYxhg8mnGXCqlcbbfg42jURVCmI3TEF0A1UVO8GqpnAHrWBDkjfhDE5Qf3iC+AhQ6cbF9LJd/NWZC8BUK5k7LZ21LA2DglSMaOxBCuAeVzHXU8bnODjOz6oUNJ4wBdEJVBBYqILQBKtYYyc0VYlkeILIBiioO0T1cRXz35It9MDgAh4gmVutZMoa6fecNDwKUjFCQQraGRfrTQGpwJ+sND6KcFUKwhOmIPCz+SruC211qmKfvgMVhCdUVYmXcBVMYKoSSHCC8IYnsB+gwH4VKsEY/l7+O/8s300SsA2L8VYqSzW1gTQwClIxQkGqwqOuYq6gjP+zkrkngNJ/YwtTEJ7qVBV/AlUVu8GqukiHrFCEperCEZyg/vAEgVWfKvYZ2gAFtUMUwK1lu7m+vOKC1K+SyKVWakxfBkrELgWpGKEgVeEA4+IgXH5Xo6oEMtt5OAefg70wBZEPVBX7DW2ogtAEq1gWaGiqEonwBNEPUFBxBYJ2xsVnppA7rRTmkOh3V71IvFGQihEKUsELZZgKpioFsRWmoP5AVbH/0Ieq6uIpYNkNS1X8DU1VIhmeKpYHFqDAdzceVFwn77LyfRxuSriw2ld9gjE49X0mDZyCVIxQkKot27gYjpM5fs4rBZHt4oPQd/NVifVAVSWYYFVTpIJWsCHJm3AEJ7AXnir2b6/6BIEFqLySrQx1FvJA2U56mlIAhlppfKpxUNKIKEjFCAUpTx2MizWVA88HWOl8G8BlI+IlTIH96lTF/fYDFfgXqioex/9gBaENV7Em0MBUJRTBCQIPTxXLwxOgDnCVcXf5Ls505ldsj8XNVgpzScToO0waEQWpGKEgVdszriLOo5yVOBhspft9unQkx0tVCVdXHwQXqCC6oaq6eApYdgNTFX+DEwQXnioeK3Tdd1B/gEoxLv5e/jvXlu+lCQYn8BhJ3GalsE/fXdIIKUjFCAWp2rKMi+9NIa0x3EEytzlCfxYfxEaYgvB197nXCWGg+uNx7QermiIRtIINSN4EEpqg/uAEoQ1PEJoAVSXJGL4pXkc3DJ+QwN+tFF1oWBo1BakYoSDl3dmmjBdMMeXAsVY6X4ehiw8aRpj6Y53gK1RVAg1WFY8funAVSwINTFX8CU4Q/vAEdXffgfcAZRnDqa583nY0pbzyGnmnmnKaYnhOZ+OJKEjFCgUp3+a7ivgz5azBwVFWOkUBPD+hDlMQ/Bl9EBuBCsIfqjweKw4Clt2wVMXf0AT1BycITXgCewEKYxjtKuD/yvbQ25RwmZXCf6zketss0tgoSMUIBSnfMo3he1PAAZiAJ+qE6IQpCL46BZELVBBYqKoSbLjyJRShK9hQVJ9AQhMEF5wq7vP9OvpTfQL/K1CnufK5oWwvR5iK1yEX+D8rhVkKUiK1KEjFCAWpuo0w5fzJlDPVSqEkwOcnkCAFkQ1TEJpABaENVWAvWEH4wlW0BBqYqvgTnCDy4Ql8V6DGOvdzffleDqmcymA/MItkHrCS2GM5fLZFpDFTkIoRClLhFc0wBbEXqCrWC+wjaTdYVReLIctuUKrO39AEdQenivsDC09gv/pU08tF6xmJk33AoyTziJWsy7qI1ENBKkYoSPkv0RgmUcbjJAU0a3JDCVMQ2kBVsW7gH89QBKt4FEhogvqDU8U64QlP4DtANTUuznfm8mJ5IVsrq00DjJMTKGcmyeTqe0jELwpSMUJByk/GsNAUcSpOHiaJaxypAW0erjAFsRuoILBQVbG+/Y9rQwhYgYYl93Z+hKaK9ep+fgMJTxBYgOpgyri8fB8Tyn8nE3iAJG4M8HMkIn+IVJDS9QIkNCyLeSRxqnHyD8r4wSQEdAmZwpLtAYWpqh8ffwLVXrPFrzC127Gr3jBV9YNZX6Cq+sGtL1BV/+H2J1TVDASBBKv6Qki0g5bdkFRrP36Gpop17QUnCC48wR/v4T6uYq4q/50znfup+sSsxeJHzQElEhdUkaqHKlKB+acp4TZTSikw3ErjswCv7RVoZQqiV50C/ytU4H+VCgKvVP2xXeP5OAcSmP7Ypv7nJ5zhCaqNgTKGl0p/Y5SrwH3fUhJ4yErmLRJ0OReRIKlrL0YoSAXGMoYXTDFnUc5uLAZb6awP8KyiWAlTEP1AVcVusPpj+/j8mNsJS39s698x1xWcILDwBHVXn1KNi2Is92SZdxZt4ArKeIFEHrKSA7p2pYjUTUEqRihIBS7NGD40hfTHxf+wGGqlszPGwhSEJ1BBYKEKohOsfO83Ml8HwQQk7/vzv931BScIbXgCaGPKubR8H5eU72OMleKu1LY1LpKAbZrCQCTkFKRihIKUPVnGxeemkJYYRlnpfGnzX9qxVJ2C8AYqsBeqqoQrXMWSQAJTlWCCEwQWnsAzQPVwlXBV+e+c58yjahrSx0niCg0iFwk7BakYoSBl34HGRSaGFUF2V8RadQoCC1QQ+VBVXbwFLDthqYo/oQnqDk4QXHiyjGGEq4BLyvcx0lXoXr4cB/+ykllIIi59l4iEnYJUjFCQCp0exslmHAFdk6+KnTAFsReowF6ogtAFK1/CHbiCCUje+BuaqtgNT+BfgKpiGcM3xevojsEFvE4iD1rJLNf4J5GIUpCKEQpSoXG0cfK2KeRLEjjDSqMshsMUBB6oILKhqrpwB6xoCzQwQf2hCeoOTuBneDKGo0wx55fn8TeX032ZpItMKT2Ni9lWcsAnW4hIaChIxQgFqdA4xpTzrikiHXiZRP5spQY0+3kVu2EKYjtQQWhCVXXxFLDshKXq/AlOYK/qBLUrT2nGxVjnfv5atot+uACYYKUyP4C500QkvDQhpzQon1mJnEkar5sizqYclynmQlIDrkwVlmwH7AWqvJKtAYepqh/XQAJV9R/rQEKVtzAQTLjyN5yEI3AFG4zq4m9oAvtVJ/DebXegq5TxJduYQBktKpcVAy+QyCpUeRJpjFSRqocqUqF1minjBVNMMvA2CYy10ii2+bxGujoF9ipUVexWqmoKdeUqVgUSmKrUF5wg8PBUpUXxNjaaAndcWo/FbCuZuSTpAsIiMUhdezFCQSr0RphyXqns5ltGAqdbaeRHIUyB/UAFsRGqqsRruLITlqr4E5qq2AlP7U0ZR7uKeb48373sXVchpcBjVjLvafZxkZimIBUjFKTC41hTzhumiK9J4DQrzT1I1654DVRVQh2svIlk2AomIPkSquAEvsNTsnFxsrOAP5ft5EScuIAuVhNyKgeMJxpDub4HROKCxkhJg/aplcgQ0vkVR9AhCgK/6HFNgVwEuabqP9p2Q1XNkBCOYBWOcBMOgQSmKvUFJ6ij284YepZsY4Ip4zzKaFntrs9JoC2GnMq/FaJEpCZVpOqhilSEGMN1lPISSWwK8nTxYKtTEFyFqkooKlU1RaJyFSl2AlMVf4IT1D3mqerEhT+bMuabYvfyrVg8TRLzrCTWaeoCkbilrr0YoSAVGVeZUh42JWzBYoSVzv9iIExBaAJVlXAEq+piKWQFE5Jq8jc0Qd3BCaCw+DcG4SIRwyeV17vLNIb1Jp/3SGSulcQHJGjmcZEGQEEqRihIRUYH4+I9U8ShuNiJxSgrje9CMBN0qAIVxFeoileBhKYq9YUngMTi3/gLZVxqyuiFiy9wcIyjifv+VGNsnz0qIrEpUkEqburWd911F4MHDyY9PZ3MzEy/tjHGcOutt9K+fXvS0tIYPnw4v/zyS3gbKrb8Zjk43kpjJQ7aYvjIFHKaKQt6v4Ul291dOMHKK9nq14+2P/aaLR63xqjmcxBId131my+Fxb9xRPFWHi7awFaTz79NCb1wUQj8jIPkav+GVIgSEbvipiI1depUMjMz2bp1K08++ST79u2rd5t7772X6dOnM2/ePLp27co///lPfvjhB3766SdSU/27+roqUpHV3BheMUX8CScAU61k7iI5JKeZh7I6VSWUVSpvGkLlKtigGEh4rR6aZ7uKuYQ/wvhqHDxhJfEMSeTqsyzS4Klrz4e5c+cyefLkeoOUMYYOHTpw7bXXct111wGQm5tLVlYWc+fOZdy4cX49noJU5CUawwOmhL9RRjnQ30oPSTdflXAEKgh/qKopVkJWqCtqdoJTZ+PiXMp4kSQ2Vo6vG2vK+K8p5jUS+Y+VxGckgD7DIo2Gpj8I0oYNG8jJyWH48OHuZRkZGQwYMIDly5f7DFIlJSWUlJS4/87Lywt7W8VTuWUx2UrlO5NAGiakIQqCu8xMXaoHgEiEqobSJRhod2nV69fcGCZRxl9MOcdWVjATLbibFAAWksgiqylFCk8iEkYNNkjl5FTM/JKVleWxPCsry32fN9OnT2fatGlhbZv4Z06NC8B2NS5aYFgZomAVrkAFtcNBpKtVsSiY8WVVr5VlDH/CyURTxhmUUzXFqAtYSgI/VRv2WWZZBD/KTkSkblEdbH7TTTdhWVadtzVr1kS0TVOmTCE3N9d927KlYfyrP961NIa3TCHLTCEnmdBeEDeUA9J98XeAdENR83jtVJ2q36qkA6+ZIv5cGaJW4+B6K4VOVhNGONJZWCN8i4iEW1QrUtdeey0TJkyoc51u3brZ2ne7du0A2LFjB+3b/1Fx2LFjB3369PG5XUpKCikpKbYeU8KnDNiMgx44WWiKuJ4UHiEppNc68/jBDtM4qiregkW8Va1CHQhrhtkDjIvTKOdI4+ISKwUsiwLL4j8miVRgrpXENzg07klEoiqqQapNmza0aROeSQS7du1Ku3btWLJkiTs45eXl8eWXX3L55ZeH5TElfPZbFqeQxmxTzETK+ZcpYSTl/JVU93XQQimc3X6+1BdMIh20wl0581YF7GGcjKGcMaac/rjcy2eRxEoqunSvc/h3xq2ISCTEzRipzZs3s3fvXjZv3ozT6WTVqlUAHHTQQTRt2hSAnj17Mn36dM444wwsy2Ly5MnceeedHHzwwe7pDzp06MCYMWOidyBiW7llcTGpfEMZD5gSRuJklSnkElJ50wrPWzmSVar6xHuXYF3dp6eZMqabUnpWC08uKq5197qVyFZUdRKR2BQ3QerWW29l3rx57r/79u0LwNKlSxk2bBgAa9euJTc3173ODTfcQEFBAZMmTWLfvn0ce+yxvPvuu37PISUxyLKYTTIfkcAzppg+uLjclPJmBE5tj6VQFevqG3PWyzjZh8WWympiERY9cVECfFgZnt4gkR261p2IxLi4m0cq0jSPVOxKNob/M6XMspLC0r3nr8YeqvwdqN/RuBhXOV3BEbh4gCRurOymSzKGMyjnHRLZr8+ZiISA5pESqUepZTHV8jwx4G+mlIUkuisdkVAzSDTkYBXo2Y0HGBenUM7ZppxhON2nCZdQcQZelTLL4kV0xp2IxB8FKWkwxpsyHjIl3EQpfyWV98I0bqo+DSVYBT0lhDF8ZgrJ5o+i9zISeNZK5BWS2KfKk4g0AApS0mB8SALf4aA3Lt42RbxgErnaSon6OBtfgSTaAStUc2c1M4ZhODnFlNMfJ/2sdFyWBZbFmyaRPjh5w0rkBZLYrDFPItLAaIxUPTRGKr6kG8M0U8I/KCMB2AdMsVL4T4jnnIqG6sEr3BOI1qWpMQzFyVBTzhCcHImL6nPNH2el8XllNdAyJu6fdxGJT7pocYxQkIpPfY2T2aaYoypPp19AIhc60urZSvxxj6uY62tcfGUdFu+QyCIrkY9JoFSfFRGJMg02FwnCt1YCg0jnSsq4w5QwX5cOCViWcTEKJ6NMOU9bSbxTWWV63kriTFPOUhL5yErgIxLYpi47EWmkFKSkwXJZFo+SzAKS2FutQpJkDGWqmNTiMIYBuBhtyhlFOf2qTY6ZZyx3kFqFg+5WE12aRUQEBSlpBKqHqIOMi8WmkKdNEg9YyZqzqFJLY1hr8mlZY/nXOHiXRF6vfgaknjMRETcFKWlUrjWldMJwC6VcZsq4m2RmkdQoxvSkGsPRODkGJ8cZJ/uxGFc5bmyvZbHDOAAXi0nkHSuR90hgp7rsRETqpMHm9dBg8wbGGMZQzp2mlEMqu642YfFPK4UFJDa4asskU8pRxsURODkCF9WnL90PtLKa4qw85k7GxTYs998iIvEsUoPN9c9NaVwsi4VWEr2tdCZZKWzFojOGp00x000pxPG/KxKNob9xeiw7y5RzEWUcXRmitmPxEon8w0phmJVebRQUbLYcClEiIgFS1540Sk7L4snKgeg3mFKmUkoRxFVFKskY+uHiWMo51jg5DieZQAeauCchfcxK4guTwPeWg5UksAErro5RRCTWqWuvHuraaxwGGCdf4nCHjIONi19iNHScYsq52pQyACc1Z8bagcW5ViqfROnyOCIisULzSIlE0JfWH3NzNzOGlaaArVjMIYn5JLE9koOujaEjhj5UjG3qbVzMsJL5orKNzai4JAvALiw+JYFPrQQ+JYEVODSTuIhIBClIidTQFycuoDuG6aaUOynlXZPAHCuJRSSGbA6q6pdPOci4+Jsp5TBc9MZZaxqCL0jgi8oLsSwhgUlWCp+SwNpqVTQREYk8de3VQ117jVMTYxhLORNMGcfxxwDunVhcZqXwegAzpScYw9G4OIFy+hoXnXHRFRd3WCk8bCUDcKRx8rUpdG9TBqzBwXc4+M5K4H0SWG0l+HgEERGpSV17IlFUYFnMJYm5VhLdjYsJpox/UMpmLDrh3789OhsXD5tihuAkw8v9XY0LKrP5OhzcSzJrrYrw9BOORjG3lYhIvFNFqh6qSEmVBGNIAK8Bp6NxMRwn+4FXKqtVzY1hl8knEdgDLCWRT60EfsXBBiw24qBQ7ykRkbBQRUokxjgty93Jl2kMx1POCcbJnyinR2WVajkOd5DKsywuJpXVOFilQeAiIg2SgpRIgIaYcpaaIo9lTiquS7eYxIpJPStD0/wAxlKJiEj8UZASCcDJppxXKkPUTzj4kASWWAl8RCK5qjiJiDQ6ClIiAXibBIZZ6WzG4jdd0FdEpNFTkBIJgLEs93xOIiIi+ie1iIiIiE0KUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIiIiIiNilIiYiIiNikICUiIiJiU9wEqbvuuovBgweTnp5OZmamX9tMmDABy7I8bqNGjQpvQ0VERKTRSIx2A/xVWlrK2LFjGTRoEE8++aTf240aNYo5c+a4/05JSQlH80RERKQRipsgNW3aNADmzp0b0HYpKSm0a9cuDC0SERGRxi5uuvbsWrZsGW3btqVHjx5cfvnl7NmzJ9pNEhERkQYibipSdowaNYozzzyTrl27sn79em6++WZGjx7N8uXLSUhI8LpNSUkJJSUl7r/z8vIi1VwRERGJM1GtSN100021BoPXvK1Zs8b2/seNG8dpp51Gr169GDNmDIsWLeLrr79m2bJlPreZPn06GRkZ7lt2drbtxxcREZGGzTLGmGg9+K5du+rtauvWrRvJycnuv+fOncvkyZPZt2+frcds06YNd955J5deeqnX+71VpLKzs7GspliWZesxRUREJLKMMRiTT25uLs2bNw/b40S1a69Nmza0adMmYo+3detW9uzZQ/v27X2uk5KSojP7RERExC9xM9h88+bNrFq1is2bN+N0Olm1ahWrVq0iPz/fvU7Pnj157bXXAMjPz+f666/niy++YOPGjSxZsoTTTz+dgw46iJEjR0brMERERKQBiZvB5rfeeivz5s1z/923b18Ali5dyrBhwwBYu3Ytubm5ACQkJPD9998zb9489u3bR4cOHRgxYgR33HGHKk4iIiISElEdIxUP8vLyyMjI0BgpERGROBKpMVJx07UnIiIiEmsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbFJQUpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExCYFKRERERGbFKREREREbFKQEhEREbEpLoLUxo0bueiii+jatStpaWkceOCBTJ06ldLS0jq3Ky4u5sorr6RVq1Y0bdqUs846ix07dkSo1SIiItLQxUWQWrNmDS6Xi8cff5wff/yRGTNmMHv2bG6++eY6t7v66qt58803eemll/joo4/47bffOPPMMyPUahEREWnoLGOMiXYj7Lj//vuZNWsWv/76q9f7c3NzadOmDc8++yxnn302UBHIDjnkEJYvX87AgQP9epy8vDwyMjKwrKZYlhWy9ouIiEj4GGMwJp/c3FyaN28etseJi4qUN7m5ubRs2dLn/StWrKCsrIzhw4e7l/Xs2ZNOnTqxfPnySDRRREREGrjEaDfAjnXr1vHoo4/ywAMP+FwnJyeH5ORkMjMzPZZnZWWRk5Pjc7uSkhJKSkrcf+fm5gIVyVZERETiQ9Xvdrh/v6MapG666SbuvffeOtf5+eef6dmzp/vvbdu2MWrUKMaOHcsll1wS8jZNnz6dadOmebmnAGUpERGR+LJnzx4yMjLCtv+ojpHatWsXe/bsqXOdbt26kZycDMBvv/3GsGHDGDhwIHPnzsXh8N0z+eGHH3LCCSfw+++/e1SlOnfuzOTJk7n66qu9blezIuVyudi7dy+tWrWKyzFSeXl5ZGdns2XLlrD2EccqHb+OX8ev49fxN87jz83NpVOnTrVyQKhFtSLVpk0b2rRp49e627Zt4/jjj6dfv37MmTOnzhAF0K9fP5KSkliyZAlnnXUWAGvXrmXz5s0MGjTI53YpKSmkpKR4LAvnCxApzZs3b5QfpCo6fh2/jl/H31g19uOvLy8Evf+w7j1Etm3bxrBhw+jUqRMPPPAAu3btIicnx2Os07Zt2+jZsydfffUVABkZGVx00UVcc801LF26lBUrVjBx4kQGDRrk9xl7IiIiInWJi8HmixcvZt26daxbt46OHTt63FfVM1lWVsbatWspLCx03zdjxgwcDgdnnXUWJSUljBw5ksceeyyibRcREZGGKy6C1IQJE5gwYUKd63Tp0qXWyPzU1FRmzpzJzJkzw9i62JaSksLUqVNrdVc2Fjp+Hb+OX8ev49fxh1PcTsgpIiIiEm1xMUZKREREJBYpSImIiIjYpCAlIiIiYpOClIiIiIhNClJxaObMmXTp0oXU1FQGDBjgnjvLm//85z8cd9xxtGjRghYtWjB8+PBa60+YMAHLsjxuo0aNCvdh2BbI8c+dO7fWsaWmpnqsY4zh1ltvpX379qSlpTF8+HB++eWXcB+GbYEc/7Bhw2odv2VZnHzyye514uX1//jjjzn11FPp0KEDlmWxcOHCerdZtmwZRx55JCkpKRx00EHMnTu31jqBPJ/RFOjxv/rqq5x44om0adOG5s2bM2jQIN577z2PdW677bZar331S3LFkkCPf9myZV7f+zWvtdpQX39vn2vLsjjssMPc68TT6z99+nSOPvpomjVrRtu2bRkzZgxr166td7uXXnqJnj17kpqaSq9evXj77bc97g/F97+CVJx54YUXuOaaa5g6dSorV66kd+/ejBw5kp07d3pdf9myZZx33nksXbqU5cuXk52dzYgRI9i2bZvHeqNGjWL79u3u23PPPReJwwlYoMcPFbP6Vj+2TZs2edx/33338cgjjzB79my+/PJLmjRpwsiRIykuLg734QQs0ON/9dVXPY599erVJCQkMHbsWI/14uH1LygooHfv3n5PZ7JhwwZOPvlkjj/+eFatWsXkyZO5+OKLPcKEnfdTtAR6/B9//DEnnngib7/9NitWrOD444/n1FNP5dtvv/VY77DDDvN47T/99NNwND9ogR5/lbVr13ocX9u2bd33NeTX/+GHH/Y47i1bttCyZctan/14ef0/+ugjrrzySr744gsWL15MWVkZI0aMoKCgwOc2n3/+Oeeddx4XXXQR3377LWPGjGHMmDGsXr3avU5Ivv+NxJX+/fubK6+80v230+k0HTp0MNOnT/dr+/LyctOsWTMzb94897Lx48eb008/PdRNDYtAj3/OnDkmIyPD5/5cLpdp166duf/++93L9u3bZ1JSUsxzzz0XsnaHSrCv/4wZM0yzZs1Mfn6+e1k8vf5VAPPaa6/Vuc4NN9xgDjvsMI9l5557rhk5cqT772Cfz2jx5/i9OfTQQ820adPcf0+dOtX07t07dA2LEH+Of+nSpQYwv//+u891GtPr/9prrxnLsszGjRvdy+L19TfGmJ07dxrAfPTRRz7XOeecc8zJJ5/ssWzAgAHm0ksvNcaE7vtfFak4UlpayooVKxg+fLh7mcPhYPjw4SxfvtyvfRQWFlJWVkbLli09li9btoy2bdvSo0cPLr/88novJh0Ndo8/Pz+fzp07k52dzemnn86PP/7ovm/Dhg3k5OR47DMjI4MBAwb4/ZxGSihe/yeffJJx48bRpEkTj+Xx8PoHavny5R7PFcDIkSPdz1Uons944nK52L9/f63P/i+//EKHDh3o1q0bf/nLX9i8eXOUWhgeffr0oX379px44ol89tln7uWN7fV/8sknGT58OJ07d/ZYHq+vf25uLkCt93N19X0HhOr7X0EqjuzevRun00lWVpbH8qysrFr9/r7ceOONdOjQweONM2rUKJ5++mmWLFnCvffey0cffcTo0aNxOp0hbX+w7Bx/jx49eOqpp3j99dd55plncLlcDB48mK1btwK4twvmOY2UYF//r776itWrV3PxxRd7LI+X1z9QOTk5Xp+rvLw8ioqKQvJ5iicPPPAA+fn5nHPOOe5lAwYMYO7cubz77rvMmjWLDRs2cNxxx7F///4otjQ02rdvz+zZs3nllVd45ZVXyM7OZtiwYaxcuRIIzfdpvPjtt9945513an324/X1d7lcTJ48mWOOOYbDDz/c53q+vgOqXt9Qff/HxSViJDTuuecenn/+eZYtW+Yx4HrcuHHu/+/VqxdHHHEEBx54IMuWLeOEE06IRlNDZtCgQQwaNMj99+DBgznkkEN4/PHHueOOO6LYssh78skn6dWrF/379/dY3pBff6nw7LPPMm3aNF5//XWPMUKjR492//8RRxzBgAED6Ny5My+++CIXXXRRNJoaMj169KBHjx7uvwcPHsz69euZMWMG8+fPj2LLIm/evHlkZmYyZswYj+Xx+vpfeeWVrF69OmbGc6kiFUdat25NQkICO3bs8Fi+Y8cO2rVrV+e2DzzwAPfccw/vv/8+RxxxRJ3rduvWjdatW7Nu3bqg2xxKwRx/laSkJPr27es+tqrtgtlnpARz/AUFBTz//PN+fTnG6usfqHbt2nl9rpo3b05aWlpI3k/x4Pnnn+fiiy/mxRdfrNXNUVNmZibdu3eP+9fel/79+7uPrbG8/sYYnnrqKS644AKSk5PrXDceXv+rrrqKRYsWsXTpUjp27Fjnur6+A6pe31B9/ytIxZHk5GT69evHkiVL3MtcLhdLlizxqLrUdN9993HHHXfw7rvvctRRR9X7OFu3bmXPnj20b98+JO0OFbvHX53T6eSHH35wH1vXrl1p166dxz7z8vL48ssv/d5npARz/C+99BIlJSWcf/759T5OrL7+gRo0aJDHcwWwePFi93MVivdTrHvuueeYOHEizz33nMeUF77k5+ezfv36uH/tfVm1apX72BrD6w8VZ7utW7fOr39ExfLrb4zhqquu4rXXXuPDDz+ka9eu9W5T33dAyL7/AxomL1H3/PPPm5SUFDN37lzz008/mUmTJpnMzEyTk5NjjDHmggsuMDfddJN7/XvuucckJyebl19+2Wzfvt19279/vzHGmP3795vrrrvOLF++3GzYsMF88MEH5sgjjzQHH3ywKS4ujsox1iXQ4582bZp57733zPr1682KFSvMuHHjTGpqqvnxxx/d69xzzz0mMzPTvP766+b77783p59+uunataspKiqK+PHVJ9Djr3Lssceac889t9byeHr99+/fb7799lvz7bffGsD861//Mt9++63ZtGmTMcaYm266yVxwwQXu9X/99VeTnp5urr/+evPzzz+bmTNnmoSEBPPuu++616nv+YwlgR7/ggULTGJiopk5c6bHZ3/fvn3uda699lqzbNkys2HDBvPZZ5+Z4cOHm9atW5udO3dG/PjqE+jxz5gxwyxcuND88ssv5ocffjD/+Mc/jMPhMB988IF7nYb8+lc5//zzzYABA7zuM55e/8svv9xkZGSYZcuWebyfCwsL3evU/P777LPPTGJionnggQfMzz//bKZOnWqSkpLMDz/84F4nFN//ClJx6NFHHzWdOnUyycnJpn///uaLL75w3zd06FAzfvx499+dO3c2QK3b1KlTjTHGFBYWmhEjRpg2bdqYpKQk07lzZ3PJJZfE5BdJlUCOf/Lkye51s7KyzEknnWRWrlzpsT+Xy2X++c9/mqysLJOSkmJOOOEEs3bt2kgdTsACOX5jjFmzZo0BzPvvv19rX/H0+ledzl7zVnW848ePN0OHDq21TZ8+fUxycrLp1q2bmTNnTq391vV8xpJAj3/o0KF1rm9MxXQQ7du3N8nJyeaAAw4w5557rlm3bl1kD8xPgR7/vffeaw488ECTmppqWrZsaYYNG2Y+/PDDWvttqK+/MRWn8qelpZknnnjC6z7j6fX3duyAx2fa2/ffiy++aLp3726Sk5PNYYcdZt566y2P+0Px/W9VNlBEREREAqQxUiIiIiI2KUiJiIiI2KQgJSIiImKTgpSIiIiITQpSIiIiIjYpSImIiIjYpCAlIiIiYpOClIiIiIhNClIi0ujs2bOHtm3bsnHjxqD2M27cOB588MHQNEpE4pKClIjEpQkTJmBZFpZlkZSURNeuXbnhhhsoLi6ud9u77rqL008/nS5dugTVhltuuYW77rqL3NzcoPYjIvFLQUpE4taoUaPYvn07v/76KzNmzODxxx9n6tSpdW5TWFjIk08+yUUXXRT04x9++OEceOCBPPPMM0HvS0Tik4KUiMStlJQU2rVrR3Z2NmPGjGH48OEsXry4zm3efvttUlJSGDhwoHvZsmXLsCyL9957j759+5KWlsaf/vQndu7cyTvvvMMhhxxC8+bN+fOf/0xhYaHH/k499VSef/75sByfiMQ+BSkRaRBWr17N559/TnJycp3rffLJJ/Tr18/rfbfddhv//ve/+fzzz9myZQvnnHMODz30EM8++yxvvfUW77//Po8++qjHNv379+err76ipKQkZMciIvEjMdoNEBGxa9GiRTRt2pTy8nJKSkpwOBz8+9//rnObTZs20aFDB6/33XnnnRxzzDEAXHTRRUyZMoX169fTrVs3AM4++2yWLl3KjTfe6N6mQ4cOlJaWkpOTQ+fOnUN0ZCISLxSkRCRuHX/88cyaNYuCggJmzJhBYmIiZ511Vp3bFBUVkZqa6vW+I444wv3/WVlZpKenu0NU1bKvvvrKY5u0tDSAWl1+ItI4qGtPROJWkyZNOOigg+jduzdPPfUUX375JU8++WSd27Ru3Zrff//d631JSUnu/686G7A6y7JwuVwey/bu3QtAmzZt7ByCiMQ5BSkRaRAcDgc333wzt9xyC0VFRT7X69u3Lz/99FPIHnf16tV07NiR1q1bh2yfIhI/FKREpMEYO3YsCQkJzJw50+c6I0eO5Mcff/RZlQrUJ598wogRI0KyLxGJPwpSItJgJCYmctVVV3HfffdRUFDgdZ1evXpx5JFH8uKLLwb9eMXFxSxcuJBLLrkk6H2JSHyyjDEm2o0QEYmkt956i+uvv57Vq1fjcNj/9+SsWbN47bXXeP/990PYOhGJJzprT0QanZNPPplffvmFbdu2kZ2dbXs/SUlJteaVEpHGRRUpEREREZs0RkpERETEJgUpEREREZsUpERERERsUpASERERsUlBSkRERMQmBSkRERERmxSkRERERGxSkBIRERGxSUFKRERExKb/B6JG8Xwsr+KUAAAAAElFTkSuQmCC", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from matplotlib.colors import LogNorm\n", - "\n", - "d = dataset['plasma_current_rz'].dropna(dim='time')\n", - "r = dataset['r']\n", - "z = dataset['z']\n", - "\n", - "lcfs_R = dataset['lcfs_r'].sel(time=d.time)\n", - "lcfs_Z = dataset['lcfs_z'].sel(time=d.time)\n", - "\n", - "R, Z = np.meshgrid(r, z)\n", - "\n", - "def plot_frame(index):\n", - " lcfs_r = lcfs_R[index].values\n", - " lcfs_r = lcfs_r[~np.isnan(lcfs_r)]\n", - " lcfs_z = lcfs_Z[index].values\n", - " lcfs_z = lcfs_z[~np.isnan(lcfs_z)]\n", - "\n", - " fig, ax = plt.subplots()\n", - " ax.contourf(R, Z, d[index], cmap='magma', levels=20, label='Plasma Current')\n", - " ax.plot(lcfs_r, lcfs_z, c='red', linestyle='--', label='LCFS')\n", - "\n", - " plt.title(f'EFIT Plasma Current & LCFS for Shot {d.attrs[\"shot_id\"]}')\n", - " plt.ylabel('Z (m)')\n", - " plt.xlabel('R (m)')\n", - " plt.legend()\n", - "\n", - "num_frames = len(d)\n", - "file_names = []\n", - "for i in range(num_frames):\n", - " plot_frame(i)\n", - " file_name = f'frame_{i}.png'\n", - " plt.savefig(file_name)\n", - " file_names.append(file_name)\n", - "\n", - "gif_filename = 'efit_plasma_current.gif'\n", - "with imageio.get_writer(gif_filename, mode='I', duration=0.1, loop=0) as writer:\n", - " for file_name in file_names:\n", - " image = imageio.imread(file_name)\n", - " writer.append_data(image)\n", - "\n", - "for file_name in file_names:\n", - " os.remove(file_name)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ESM - Needs Review\n", - "\n", - "ibmp1_r_larmor and similar can be dropped if unity." - ] - }, - { - "cell_type": "code", - "execution_count": 210, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 44MB\n",
-       "Dimensions:               (time: 33827, fit_quality_n: 2, radius: 130)\n",
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-       "  * time                  (time) float32 135kB -0.01 -0.00996 ... 1.517 1.517\n",
-       "  * fit_quality_n         (fit_quality_n) float32 8B -999.0 -1e+03\n",
-       "  * radius                (radius) float32 520B 0.0 1.0 2.0 ... 128.0 129.0\n",
-       "Data variables: (12/79)\n",
-       "    area_outin_ratio      (time) float32 135kB dask.array<chunksize=(33827,), meta=np.ndarray>\n",
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-       "    dr_sep_out            (time) float32 135kB dask.array<chunksize=(33827,), meta=np.ndarray>\n",
-       "    efm_comb_ratingav     (fit_quality_n) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    efm_comb_ratingmin    (fit_quality_n) float32 8B dask.array<chunksize=(2,), meta=np.ndarray>\n",
-       "    ...                    ...\n",
-       "    v_ion                 float32 4B dask.array<chunksize=(), meta=np.ndarray>\n",
-       "    v_ion_multi           (time, radius) float32 18MB dask.array<chunksize=(33827, 130), meta=np.ndarray>\n",
-       "    v_loop_dynamic        (time) float32 135kB dask.array<chunksize=(33827,), meta=np.ndarray>\n",
-       "    v_loop_static         (time) float32 135kB dask.array<chunksize=(33827,), meta=np.ndarray>\n",
-       "    w_dot                 (time) float32 135kB dask.array<chunksize=(33827,), meta=np.ndarray>\n",
-       "    x                     (time) float32 135kB dask.array<chunksize=(33827,), meta=np.ndarray>
" - ], - "text/plain": [ - " Size: 44MB\n", - "Dimensions: (time: 33827, fit_quality_n: 2, radius: 130)\n", - "Coordinates:\n", - " * time (time) float32 135kB -0.01 -0.00996 ... 1.517 1.517\n", - " * fit_quality_n (fit_quality_n) float32 8B -999.0 -1e+03\n", - " * radius (radius) float32 520B 0.0 1.0 2.0 ... 128.0 129.0\n", - "Data variables: (12/79)\n", - " area_outin_ratio (time) float32 135kB dask.array\n", - " av_t float32 4B dask.array\n", - " dr_sep_in (time) float32 135kB dask.array\n", - " dr_sep_out (time) float32 135kB dask.array\n", - " efm_comb_ratingav (fit_quality_n) float32 8B dask.array\n", - " efm_comb_ratingmin (fit_quality_n) float32 8B dask.array\n", - " ... ...\n", - " v_ion float32 4B dask.array\n", - " v_ion_multi (time, radius) float32 18MB dask.array\n", - " v_loop_dynamic (time) float32 135kB dask.array\n", - " v_loop_static (time) float32 135kB dask.array\n", - " w_dot (time) float32 135kB dask.array\n", - " x (time) float32 135kB dask.array" - ] - }, - "execution_count": 210, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'esm'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "\n", - "dt = load_source(path)\n", - "pipelines = PipelineRegistry()\n", - "dataset = pipelines.get(source)(dt)\n", - "dataset\n", - "# for key, ds in dataset.items():\n", - "# print(key, ds.squeeze().coords)\n", - "\n", - "# df = pd.DataFrame(items)\n", - "# df.to_csv('esm.csv')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ESX" - ] - }, - { - "cell_type": "code", - "execution_count": 114, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_6672/3576158116.py:3: RuntimeWarning: Failed to open Zarr store with consolidated metadata, but successfully read with non-consolidated metadata. This is typically much slower for opening a dataset. To silence this warning, consider:\n", - "1. Consolidating metadata in this existing store with zarr.consolidate_metadata().\n", - "2. Explicitly setting consolidated=False, to avoid trying to read consolidate metadata, or\n", - "3. Explicitly setting consolidated=True, to raise an error in this case instead of falling back to try reading non-consolidated metadata.\n", - " dataset = xr.open_zarr(path)\n" - ] - }, - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 28B\n",
-       "Dimensions:           (time: 1)\n",
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-       "  * time              (time) float32 4B 0.0\n",
-       "Data variables:\n",
-       "    lower_inv_psi     (time) float32 4B dask.array<chunksize=(1,), meta=np.ndarray>\n",
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-       "Attributes:\n",
-       "    description:  EFIT, D. Taylors work\n",
-       "    file_name:    esx0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         esx\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Analysed\n",
-       "    source:       esx\n",
-       "    uda_name:     ESX\n",
-       "    uuid:         53c68369-8879-56c9-8282-440ad7d79101\n",
-       "    version:      0
" - ], - "text/plain": [ - " Size: 28B\n", - "Dimensions: (time: 1)\n", - "Coordinates:\n", - " * time (time) float32 4B 0.0\n", - "Data variables:\n", - " lower_inv_psi (time) float32 4B dask.array\n", - " lower_inv_radius (time) float32 4B dask.array\n", - " passnumber float32 4B ...\n", - " status float32 4B ...\n", - " upper_inv_psi (time) float32 4B dask.array\n", - " upper_inv_radius (time) float32 4B dask.array\n", - "Attributes:\n", - " description: EFIT, D. Taylors work\n", - " file_name: esx0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: esx\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Analysed\n", - " source: esx\n", - " uda_name: ESX\n", - " uuid: 53c68369-8879-56c9-8282-440ad7d79101\n", - " version: 0" - ] - }, - "execution_count": 114, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'esx'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### RBA" - ] - }, - { - "cell_type": "code", - "execution_count": 115, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 43MB\n",
-       "Dimensions:  (time: 3490, height: 96, width: 128)\n",
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-       "  * time     (time) float64 28kB 1e-05 0.001343 0.002677 ... 0.294 0.294 0.294\n",
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-       "    data     (time, height, width) uint8 43MB dask.array<chunksize=(873, 24, 32), meta=np.ndarray>\n",
-       "Attributes: (12/45)\n",
-       "    CLASS:           IMAGE\n",
-       "    IMAGE_SUBCLASS:  IMAGE_INDEXED\n",
-       "    IMAGE_VERSION:   1.2\n",
-       "    board_temp:      0.0\n",
-       "    bottom:          616\n",
-       "    camera:          \n",
-       "    ...              ...\n",
-       "    uda_name:        RBA\n",
-       "    uuid:            85b7639d-08e7-5ac8-8b4f-3e6fa7717e4c\n",
-       "    vbin:            0\n",
-       "    version:         -1\n",
-       "    view:            Hl07 floor mount + FFC2 + 25mm lens + CII filter\n",
-       "    width:           128
" - ], - "text/plain": [ - " Size: 43MB\n", - "Dimensions: (time: 3490, height: 96, width: 128)\n", - "Coordinates:\n", - " * time (time) float64 28kB 1e-05 0.001343 0.002677 ... 0.294 0.294 0.294\n", - "Dimensions without coordinates: height, width\n", - "Data variables:\n", - " data (time, height, width) uint8 43MB dask.array\n", - "Attributes: (12/45)\n", - " CLASS: IMAGE\n", - " IMAGE_SUBCLASS: IMAGE_INDEXED\n", - " IMAGE_VERSION: 1.2\n", - " board_temp: 0.0\n", - " bottom: 616\n", - " camera: \n", - " ... ...\n", - " uda_name: RBA\n", - " uuid: 85b7639d-08e7-5ac8-8b4f-3e6fa7717e4c\n", - " vbin: 0\n", - " version: -1\n", - " view: Hl07 floor mount + FFC2 + 25mm lens + CII filter\n", - " width: 128" - ] - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'rba'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "\n", - "dataset = xr.open_zarr(path)\n", - "make_gif(dataset, file_name)\n", - "# plot_gif(file_name)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### RBB" - ] - }, - { - "cell_type": "code", - "execution_count": 116, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 78MB\n",
-       "Dimensions:  (time: 271, height: 448, width: 640)\n",
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-       "  * time     (time) float64 2kB 1.6e-05 0.002016 0.004016 ... 0.293 0.294 0.295\n",
-       "Dimensions without coordinates: height, width\n",
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-       "    data     (time, height, width) uint8 78MB dask.array<chunksize=(68, 112, 160), meta=np.ndarray>\n",
-       "Attributes: (12/45)\n",
-       "    CLASS:           IMAGE\n",
-       "    IMAGE_SUBCLASS:  IMAGE_INDEXED\n",
-       "    IMAGE_VERSION:   1.2\n",
-       "    board_temp:      0.0\n",
-       "    bottom:          680\n",
-       "    camera:          \n",
-       "    ...              ...\n",
-       "    uda_name:        RBB\n",
-       "    uuid:            92011c56-53de-5389-a1ea-2ed0efbb3d61\n",
-       "    vbin:            0\n",
-       "    version:         -1\n",
-       "    view:            photron HM10 + Dalpha filter\n",
-       "    width:           640
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<xarray.Dataset> Size: 40MB\n",
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-       "    data     (time, height, width) uint16 40MB dask.array<chunksize=(5, 256, 256), meta=np.ndarray>\n",
-       "Attributes: (12/45)\n",
-       "    CLASS:           IMAGE\n",
-       "    IMAGE_SUBCLASS:  IMAGE_INDEXED\n",
-       "    IMAGE_VERSION:   1.2\n",
-       "    board_temp:      0.0\n",
-       "    bottom:          1024\n",
-       "    camera:          \n",
-       "    ...              ...\n",
-       "    uda_name:        RBC\n",
-       "    uuid:            602ed774-2abd-57fb-a3fb-c7b3c3b59fb0\n",
-       "    vbin:            0\n",
-       "    version:         -1\n",
-       "    view:            HM02; 14mm; CIII 465nm; 6.5mm;\n",
-       "    width:           1024
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<xarray.Dataset> Size: 0B\n",
-       "Dimensions:  ()\n",
-       "Data variables:\n",
-       "    *empty*
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<xarray.Dataset> Size: 171MB\n",
-       "Dimensions:  (time: 306, height: 364, width: 512, channel: 3)\n",
-       "Coordinates:\n",
-       "  * time     (time) float64 2kB -0.009999 -0.008999 -0.007999 ... 0.294 0.295\n",
-       "Dimensions without coordinates: height, width, channel\n",
-       "Data variables:\n",
-       "    data     (time, height, width, channel) uint8 171MB dask.array<chunksize=(77, 91, 128, 2), meta=np.ndarray>\n",
-       "Attributes: (12/46)\n",
-       "    CLASS:           IMAGE\n",
-       "    IMAGE_SUBCLASS:  IMAGE_TRUECOLOR\n",
-       "    IMAGE_VERSION:   1.2\n",
-       "    INTERLACE_MODE:  INTERLACE_PIXEL\n",
-       "    board_temp:      0.0\n",
-       "    bottom:          512\n",
-       "    ...              ...\n",
-       "    uda_name:        RCO\n",
-       "    uuid:            c9ba8074-5a7d-5738-bb26-9a7f6d9ae2b4\n",
-       "    vbin:            0\n",
-       "    version:         -1\n",
-       "    view:            HM11 - normal \n",
-       "    width:           512
" - ], - "text/plain": [ - " Size: 171MB\n", - "Dimensions: (time: 306, height: 364, width: 512, channel: 3)\n", - "Coordinates:\n", - " * time (time) float64 2kB -0.009999 -0.008999 -0.007999 ... 0.294 0.295\n", - "Dimensions without coordinates: height, width, channel\n", - "Data variables:\n", - " data (time, height, width, channel) uint8 171MB dask.array\n", - "Attributes: (12/46)\n", - " CLASS: IMAGE\n", - " IMAGE_SUBCLASS: IMAGE_TRUECOLOR\n", - " IMAGE_VERSION: 1.2\n", - " INTERLACE_MODE: INTERLACE_PIXEL\n", - " board_temp: 0.0\n", - " bottom: 512\n", - " ... ...\n", - " uda_name: RCO\n", - " uuid: c9ba8074-5a7d-5738-bb26-9a7f6d9ae2b4\n", - " vbin: 0\n", - " version: -1\n", - " view: HM11 - normal \n", - " width: 512" - ] - }, - "execution_count": 119, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'rco'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "\n", - "file_name =f'{source}_animated.gif' \n", - "\n", - "make_gif(dataset, file_name)\n", - "# plot_gif(file_name)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### RGB" - ] - }, - { - "cell_type": "code", - "execution_count": 120, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 61MB\n",
-       "Dimensions:  (time: 99, height: 480, width: 640)\n",
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-       "  * time     (time) float64 792B -0.008983 0.00012 0.009223 ... 0.874 0.8831\n",
-       "Dimensions without coordinates: height, width\n",
-       "Data variables:\n",
-       "    data     (time, height, width) uint16 61MB dask.array<chunksize=(25, 120, 160), meta=np.ndarray>\n",
-       "Attributes: (12/45)\n",
-       "    CLASS:           IMAGE\n",
-       "    IMAGE_SUBCLASS:  IMAGE_INDEXED\n",
-       "    IMAGE_VERSION:   1.2\n",
-       "    board_temp:      38.5\n",
-       "    bottom:          480\n",
-       "    camera:          IPX-VGA210LCFN      ASSY-0074-0002-RE04 SW v1.63 BL v1.3...\n",
-       "    ...              ...\n",
-       "    uda_name:        RGB\n",
-       "    uuid:            da822845-6b50-5cda-8152-93579dca8c34\n",
-       "    vbin:            0\n",
-       "    version:         -1\n",
-       "    view:            Sector9U\n",
-       "    width:           640
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<xarray.Dataset> Size: 114MB\n",
-       "Dimensions:  (time: 186, height: 480, width: 640)\n",
-       "Coordinates:\n",
-       "  * time     (time) float64 1kB -0.01329 -0.008451 -0.003617 ... 0.8763 0.8812\n",
-       "Dimensions without coordinates: height, width\n",
-       "Data variables:\n",
-       "    data     (time, height, width) uint16 114MB dask.array<chunksize=(24, 120, 160), meta=np.ndarray>\n",
-       "Attributes: (12/45)\n",
-       "    CLASS:           IMAGE\n",
-       "    IMAGE_SUBCLASS:  IMAGE_INDEXED\n",
-       "    IMAGE_VERSION:   1.2\n",
-       "    board_temp:      38.25\n",
-       "    bottom:          480\n",
-       "    camera:          IPX-VGA210LCCN      ASSY-0074-0002-RE04 SW v1.63 BL v1.3...\n",
-       "    ...              ...\n",
-       "    uda_name:        RGC\n",
-       "    uuid:            afba7f61-2408-5bce-b20a-cac704bb9a91\n",
-       "    vbin:            0\n",
-       "    version:         -1\n",
-       "    view:            Sector9U\n",
-       "    width:           640
" - ], - "text/plain": [ - " Size: 114MB\n", - "Dimensions: (time: 186, height: 480, width: 640)\n", - "Coordinates:\n", - " * time (time) float64 1kB -0.01329 -0.008451 -0.003617 ... 0.8763 0.8812\n", - "Dimensions without coordinates: height, width\n", - "Data variables:\n", - " data (time, height, width) uint16 114MB dask.array\n", - "Attributes: (12/45)\n", - " CLASS: IMAGE\n", - " IMAGE_SUBCLASS: IMAGE_INDEXED\n", - " IMAGE_VERSION: 1.2\n", - " board_temp: 38.25\n", - " bottom: 480\n", - " camera: IPX-VGA210LCCN ASSY-0074-0002-RE04 SW v1.63 BL v1.3...\n", - " ... ...\n", - " uda_name: RGC\n", - " uuid: afba7f61-2408-5bce-b20a-cac704bb9a91\n", - " vbin: 0\n", - " version: -1\n", - " view: Sector9U\n", - " width: 640" - ] - }, - "execution_count": 121, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'rgc'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "\n", - "file_name =f'{source}_animated.gif' \n", - "\n", - "make_gif(dataset, file_name)\n", - "# plot_gif(file_name)\n", - "dataset\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### RIR" - ] - }, - { - "cell_type": "code", - "execution_count": 122, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 11MB\n",
-       "Dimensions:  (time: 2221, height: 8, width: 320)\n",
-       "Coordinates:\n",
-       "  * time     (time) float64 18kB -0.04998 -0.04978 -0.04958 ... 0.3938 0.394\n",
-       "Dimensions without coordinates: height, width\n",
-       "Data variables:\n",
-       "    data     (time, height, width) uint16 11MB dask.array<chunksize=(556, 4, 160), meta=np.ndarray>\n",
-       "Attributes: (12/45)\n",
-       "    CLASS:           IMAGE\n",
-       "    IMAGE_SUBCLASS:  IMAGE_INDEXED\n",
-       "    IMAGE_VERSION:   1.2\n",
-       "    board_temp:      49.5\n",
-       "    bottom:          192\n",
-       "    camera:          SBF125 InSb FPA 320x256 format with SBF1134 4Chan Rev6 (...\n",
-       "    ...              ...\n",
-       "    uda_name:        RIR\n",
-       "    uuid:            0ab1432e-d5be-5989-9eb4-c62fe4446d1b\n",
-       "    vbin:            0\n",
-       "    version:         -1\n",
-       "    view:            Lower divertor view#6\n",
-       "    width:           320
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<xarray.Dataset> Size: 6MB\n",
-       "Dimensions:  (time: 371, height: 32, width: 256)\n",
-       "Coordinates:\n",
-       "  * time     (time) float64 3kB -0.04995 -0.04875 -0.04755 ... 0.3928 0.3941\n",
-       "Dimensions without coordinates: height, width\n",
-       "Data variables:\n",
-       "    data     (time, height, width) uint16 6MB dask.array<chunksize=(93, 16, 128), meta=np.ndarray>\n",
-       "Attributes: (12/45)\n",
-       "    CLASS:           IMAGE\n",
-       "    IMAGE_SUBCLASS:  IMAGE_INDEXED\n",
-       "    IMAGE_VERSION:   1.2\n",
-       "    board_temp:      0.0\n",
-       "    bottom:          0\n",
-       "    camera:          Thermosensorik CMT 256 SM HS\n",
-       "    ...              ...\n",
-       "    uda_name:        RIT\n",
-       "    uuid:            39ff8f30-f0a3-5a08-a01a-ad2c06d75cd1\n",
-       "    vbin:            0\n",
-       "    version:         -1\n",
-       "    view:            HL01 Upper divertor view#1\n",
-       "    width:           256
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<xarray.Dataset> Size: 332MB\n",
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-       "                               ai_obr_channel: 19, ai_obv_channel: 19,\n",
-       "                               ai_ring_channel: 10, ai_rodgr_channel: 12,\n",
-       "                               ai_uhorw_channel: 6, ai_vertw_channel: 8,\n",
-       "                               ...\n",
-       "                               isoflux_t_seg_td_channel: 13,\n",
-       "                               isoflux_t_seg_ti_channel: 13,\n",
-       "                               isoflux_t_seg_tp_channel: 13,\n",
-       "                               isoflux_t_seg_u_channel: 18,\n",
-       "                               isoflux_t_zpsh_n_channel: 18,\n",
-       "                               isoflux_t_zpsh_p_channel: 18)\n",
-       "Coordinates: (12/14)\n",
-       "  * isoflux_e_seg_channel     (isoflux_e_seg_channel) <U15 780B 'isoflux_e_se...\n",
-       "  * isoflux_t_rpsh_n_channel  (isoflux_t_rpsh_n_channel) <U17 1kB 'isoflux_t_...\n",
-       "  * isoflux_t_rpsh_p_channel  (isoflux_t_rpsh_p_channel) <U17 1kB 'isoflux_t_...\n",
-       "  * isoflux_t_seg_channel     (isoflux_t_seg_channel) <U15 1kB 'isoflux_t_seg...\n",
-       "  * isoflux_t_seg_gd_channel  (isoflux_t_seg_gd_channel) <U17 884B 'isoflux_t...\n",
-       "  * isoflux_t_seg_gi_channel  (isoflux_t_seg_gi_channel) <U17 884B 'isoflux_t...\n",
-       "    ...                        ...\n",
-       "  * isoflux_t_seg_ti_channel  (isoflux_t_seg_ti_channel) <U17 884B 'isoflux_t...\n",
-       "  * isoflux_t_seg_tp_channel  (isoflux_t_seg_tp_channel) <U17 884B 'isoflux_t...\n",
-       "  * isoflux_t_seg_u_channel   (isoflux_t_seg_u_channel) <U16 1kB 'isoflux_t_s...\n",
-       "  * isoflux_t_zpsh_n_channel  (isoflux_t_zpsh_n_channel) <U17 1kB 'isoflux_t_...\n",
-       "  * isoflux_t_zpsh_p_channel  (isoflux_t_zpsh_p_channel) <U17 1kB 'isoflux_t_...\n",
-       "  * time                      (time) float64 320kB -2.0 -2.0 -2.0 ... 2.0 2.0\n",
-       "Dimensions without coordinates: ai_ccbv_channel, ai_flcc_channel,\n",
-       "                                ai_incon_channel, ai_lhorw_channel,\n",
-       "                                ai_mid_channel, ai_obr_channel, ai_obv_channel,\n",
-       "                                ai_ring_channel, ai_rodgr_channel,\n",
-       "                                ai_uhorw_channel, ai_vertw_channel, ai_ccbv,\n",
-       "                                equil_seg_channel\n",
-       "Data variables: (12/996)\n",
-       "    ai_cpu1_botcol            (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    ai_cpu1_camera_ok         (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    ai_cpu1_ccbv              (ai_ccbv_channel, time) float32 6MB dask.array<chunksize=(40, 40000), meta=np.ndarray>\n",
-       "    ai_cpu1_co2               (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    ai_cpu1_endcrown_l        (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    ai_cpu1_endcrown_u        (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    ...                        ...\n",
-       "    z_s_zip                   (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    z_s_zipref                (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    z_t_zdgain                (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    z_t_zpgain                (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    z_t_zref                  (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "    z_t_ztest                 (time) float32 160kB dask.array<chunksize=(40000,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  Digital Plasma Control\n",
-       "    file_name:    xdc030397.nc\n",
-       "    format:       CDF\n",
-       "    mds_name:     None\n",
-       "    name:         xdc\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Raw\n",
-       "    source:       xdc\n",
-       "    uda_name:     XDC\n",
-       "    uuid:         a5357c0f-bf9b-5739-bda0-9c61b94fd4c7\n",
-       "    version:      -1
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<xarray.Dataset> Size: 101MB\n",
-       "Dimensions:                        (dim_0: 16, dim_1: 2, time: 1400000)\n",
-       "Coordinates:\n",
-       "  * dim_0                          (dim_0) int32 64B 0 1 2 3 4 ... 12 13 14 15\n",
-       "  * dim_1                          (dim_1) int32 8B 0 1\n",
-       "  * time                           (time) float64 11MB -0.1 -0.1 ... 0.6 0.6\n",
-       "Data variables: (12/18)\n",
-       "    devices_d3_acq216_025_channel  (dim_0) int32 64B dask.array<chunksize=(16,), meta=np.ndarray>\n",
-       "    devices_d3_acq216_025_range    (dim_0, dim_1) float32 128B dask.array<chunksize=(16, 2), meta=np.ndarray>\n",
-       "    devices_limit                  (dim_0) float64 128B dask.array<chunksize=(16,), meta=np.ndarray>\n",
-       "    omaha_1lz                      (time) float32 6MB dask.array<chunksize=(1400000,), meta=np.ndarray>\n",
-       "    omaha_2lt                      (time) float32 6MB dask.array<chunksize=(1400000,), meta=np.ndarray>\n",
-       "    omaha_2lz                      (time) float32 6MB dask.array<chunksize=(1400000,), meta=np.ndarray>\n",
-       "    ...                             ...\n",
-       "    omaha_5lz                      (time) float32 6MB dask.array<chunksize=(1400000,), meta=np.ndarray>\n",
-       "    omaha_5ur                      (time) float32 6MB dask.array<chunksize=(1400000,), meta=np.ndarray>\n",
-       "    omaha_5ut                      (time) float32 6MB dask.array<chunksize=(1400000,), meta=np.ndarray>\n",
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-       "    time1                          (time) float64 11MB dask.array<chunksize=(1400000,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  Magnetic Field Measurements: OMAHA high frequency Mirnov co...\n",
-       "    file_name:    xmo029790.nc\n",
-       "    format:       CDF\n",
-       "    mds_name:     None\n",
-       "    name:         xmo\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      29790\n",
-       "    signal_type:  Raw\n",
-       "    source:       xmo\n",
-       "    uda_name:     XMO\n",
-       "    uuid:         ff541ac3-6b1c-5373-8d33-b85fd46bc75b\n",
-       "    version:      -1
" - ], - "text/plain": [ - " Size: 101MB\n", - "Dimensions: (dim_0: 16, dim_1: 2, time: 1400000)\n", - "Coordinates:\n", - " * dim_0 (dim_0) int32 64B 0 1 2 3 4 ... 12 13 14 15\n", - " * dim_1 (dim_1) int32 8B 0 1\n", - " * time (time) float64 11MB -0.1 -0.1 ... 0.6 0.6\n", - "Data variables: (12/18)\n", - " devices_d3_acq216_025_channel (dim_0) int32 64B dask.array\n", - " devices_d3_acq216_025_range (dim_0, dim_1) float32 128B dask.array\n", - " devices_limit (dim_0) float64 128B dask.array\n", - " omaha_1lz (time) float32 6MB dask.array\n", - " omaha_2lt (time) float32 6MB dask.array\n", - " omaha_2lz (time) float32 6MB dask.array\n", - " ... ...\n", - " omaha_5lz (time) float32 6MB dask.array\n", - " omaha_5ur (time) float32 6MB dask.array\n", - " omaha_5ut (time) float32 6MB dask.array\n", - " omaha_5uz (time) float32 6MB dask.array\n", - " omaha_6lz (time) float32 6MB dask.array\n", - " time1 (time) float64 11MB dask.array\n", - "Attributes:\n", - " description: Magnetic Field Measurements: OMAHA high frequency Mirnov co...\n", - " file_name: xmo029790.nc\n", - " format: CDF\n", - " mds_name: None\n", - " name: xmo\n", - " quality: Not Checked\n", - " shot_id: 29790\n", - " signal_type: Raw\n", - " source: xmo\n", - " uda_name: XMO\n", - " uuid: ff541ac3-6b1c-5373-8d33-b85fd46bc75b\n", - " version: -1" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'xmo'\n", - "path = f'/common/tmp/sjackson/local_cache2/29790.zarr/{source}'\n", - "# path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ds = dataset['omaha_3lz']\n", - "ds = ds.isel(time=(ds.time > 0) & (ds.time < .37))\n", - "plt.plot(ds.time, ds)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "from scipy.signal import stft\n", - "from matplotlib.colors import LogNorm\n", - "\n", - "# Parameters to limit the number of frequencies\n", - "nperseg = 2000 # Number of points per segment\n", - "nfft = 2000 # Number of FFT points\n", - "\n", - "# Compute the Short-Time Fourier Transform (STFT)\n", - "sample_rate = 1/(ds.time[1] - ds.time[0])\n", - "f, t, Zxx = stft(ds, fs=int(sample_rate), nperseg=nperseg, nfft=nfft)\n", - "\n", - "fig, ax = plt.subplots(figsize=(15, 5))\n", - "cax = ax.pcolormesh(t, f/1000, np.abs(Zxx), shading='nearest', cmap='jet', norm=LogNorm(vmin=1e-5))\n", - "ax.set_ylim(0, 50)\n", - "ax.set_title(f'XMO/OMAHA/3LZ - Shot {ds.attrs[\"shot_id\"]}')\n", - "ax.set_ylabel('Frequency [Hz]')\n", - "ax.set_xlabel('Time [sec]')\n", - "plt.colorbar(cax, ax=ax)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### XPC" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 40MB\n",
-       "Dimensions:           (time: 134750)\n",
-       "Coordinates:\n",
-       "  * time              (time) float32 539kB -0.1 -0.1 -0.09999 ... 1.499 1.5 1.5\n",
-       "Data variables: (12/74)\n",
-       "    a14_0116#06       (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    a14_0118#03       (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    a14_0118#06       (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    chfs_drive        (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    clamp_p1_drive    (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    clamp_p2_drive    (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    ...                ...\n",
-       "    trcf_0104_16      (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    trcf_0104_5       (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    trcf_0104_6       (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    trcf_0104_9       (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    z_d_f_b           (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "    zip_velocity      (time) float32 539kB dask.array<chunksize=(134750,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  Datac system. Monitoring what goes in/out PCS\n",
-       "    file_name:    xpc0303.97\n",
-       "    format:       IDA3\n",
-       "    mds_name:     None\n",
-       "    name:         xpc\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Raw\n",
-       "    source:       xpc\n",
-       "    uda_name:     XPC\n",
-       "    uuid:         0f5f284a-39b5-526e-8205-7862aac45ecf\n",
-       "    version:      -1
" - ], - "text/plain": [ - " Size: 40MB\n", - "Dimensions: (time: 134750)\n", - "Coordinates:\n", - " * time (time) float32 539kB -0.1 -0.1 -0.09999 ... 1.499 1.5 1.5\n", - "Data variables: (12/74)\n", - " a14_0116#06 (time) float32 539kB dask.array\n", - " a14_0118#03 (time) float32 539kB dask.array\n", - " a14_0118#06 (time) float32 539kB dask.array\n", - " chfs_drive (time) float32 539kB dask.array\n", - " clamp_p1_drive (time) float32 539kB dask.array\n", - " clamp_p2_drive (time) float32 539kB dask.array\n", - " ... ...\n", - " trcf_0104_16 (time) float32 539kB dask.array\n", - " trcf_0104_5 (time) float32 539kB dask.array\n", - " trcf_0104_6 (time) float32 539kB dask.array\n", - " trcf_0104_9 (time) float32 539kB dask.array\n", - " z_d_f_b (time) float32 539kB dask.array\n", - " zip_velocity (time) float32 539kB dask.array\n", - "Attributes:\n", - " description: Datac system. Monitoring what goes in/out PCS\n", - " file_name: xpc0303.97\n", - " format: IDA3\n", - " mds_name: None\n", - " name: xpc\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Raw\n", - " source: xpc\n", - " uda_name: XPC\n", - " uuid: 0f5f284a-39b5-526e-8205-7862aac45ecf\n", - " version: -1" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'xpc'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### XSX" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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<xarray.Dataset> Size: 138MB\n",
-       "Dimensions:                          (time: 300000, dim_0: 96, dim_1: 2,\n",
-       "                                      hcam_l_channel: 36, hcam_u_channel: 36,\n",
-       "                                      tcam_channel: 36)\n",
-       "Coordinates:\n",
-       "  * dim_0                            (dim_0) int32 384B 0 1 2 3 ... 92 93 94 95\n",
-       "  * dim_1                            (dim_1) int32 8B 0 1\n",
-       "  * hcam_l_channel                   (hcam_l_channel) <U21 3kB '0' ... 'hcam_...\n",
-       "  * hcam_u_channel                   (hcam_u_channel) <U21 3kB '0' ... 'hcam_...\n",
-       "  * tcam_channel                     (tcam_channel) <U21 3kB '0' ... 'tcam_9'\n",
-       "  * time                             (time) float64 2MB -0.009999 ... 0.59\n",
-       "Data variables: (12/30)\n",
-       "    acq196_061_ch01                  (time) float32 1MB dask.array<chunksize=(300000,), meta=np.ndarray>\n",
-       "    acq196_147_96                    (time) float32 1MB dask.array<chunksize=(300000,), meta=np.ndarray>\n",
-       "    devices_d112_acq196_061_channel  (dim_0) float64 768B dask.array<chunksize=(96,), meta=np.ndarray>\n",
-       "    devices_d112_acq196_061_range    (dim_0, dim_1) float32 768B dask.array<chunksize=(96, 2), meta=np.ndarray>\n",
-       "    devices_d2_acq196_147_channel    (dim_0) int32 384B dask.array<chunksize=(96,), meta=np.ndarray>\n",
-       "    devices_d2_acq196_147_range      (dim_0, dim_1) float32 768B dask.array<chunksize=(96, 2), meta=np.ndarray>\n",
-       "    ...                               ...\n",
-       "    tcam_r1                          (tcam_channel) float64 288B dask.array<chunksize=(36,), meta=np.ndarray>\n",
-       "    tcam_r2                          (tcam_channel) float64 288B dask.array<chunksize=(36,), meta=np.ndarray>\n",
-       "    tcam_theta_rad                   (tcam_channel) float64 288B dask.array<chunksize=(36,), meta=np.ndarray>\n",
-       "    tcam_z1                          (tcam_channel) float64 288B dask.array<chunksize=(36,), meta=np.ndarray>\n",
-       "    tcam_z2                          (tcam_channel) float64 288B dask.array<chunksize=(36,), meta=np.ndarray>\n",
-       "    time1                            (time) float64 2MB dask.array<chunksize=(300000,), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    description:  SRX Camera\n",
-       "    file_name:    xsx030397.nc\n",
-       "    format:       CDF\n",
-       "    mds_name:     None\n",
-       "    name:         xsx\n",
-       "    quality:      Not Checked\n",
-       "    shot_id:      30397\n",
-       "    signal_type:  Raw\n",
-       "    source:       xsx\n",
-       "    uda_name:     XSX\n",
-       "    uuid:         3b231f73-f0b9-564c-84cf-937d28d42d46\n",
-       "    version:      -1
" - ], - "text/plain": [ - " Size: 138MB\n", - "Dimensions: (time: 300000, dim_0: 96, dim_1: 2,\n", - " hcam_l_channel: 36, hcam_u_channel: 36,\n", - " tcam_channel: 36)\n", - "Coordinates:\n", - " * dim_0 (dim_0) int32 384B 0 1 2 3 ... 92 93 94 95\n", - " * dim_1 (dim_1) int32 8B 0 1\n", - " * hcam_l_channel (hcam_l_channel) \n", - " acq196_147_96 (time) float32 1MB dask.array\n", - " devices_d112_acq196_061_channel (dim_0) float64 768B dask.array\n", - " devices_d112_acq196_061_range (dim_0, dim_1) float32 768B dask.array\n", - " devices_d2_acq196_147_channel (dim_0) int32 384B dask.array\n", - " devices_d2_acq196_147_range (dim_0, dim_1) float32 768B dask.array\n", - " ... ...\n", - " tcam_r1 (tcam_channel) float64 288B dask.array\n", - " tcam_r2 (tcam_channel) float64 288B dask.array\n", - " tcam_theta_rad (tcam_channel) float64 288B dask.array\n", - " tcam_z1 (tcam_channel) float64 288B dask.array\n", - " tcam_z2 (tcam_channel) float64 288B dask.array\n", - " time1 (time) float64 2MB dask.array\n", - "Attributes:\n", - " description: SRX Camera\n", - " file_name: xsx030397.nc\n", - " format: CDF\n", - " mds_name: None\n", - " name: xsx\n", - " quality: Not Checked\n", - " shot_id: 30397\n", - " signal_type: Raw\n", - " source: xsx\n", - " uda_name: XSX\n", - " uuid: 3b231f73-f0b9-564c-84cf-937d28d42d46\n", - " version: -1" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "source = 'xsx'\n", - "path = f'/common/tmp/sjackson/local_cache2/30397.zarr/{source}'\n", - "dataset = xr.open_zarr(path)\n", - "dataset" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "fmast", - "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": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/sample_hdf.ipynb b/notebooks/sample_hdf.ipynb deleted file mode 100644 index 6846a41..0000000 --- a/notebooks/sample_hdf.ipynb +++ /dev/null @@ -1,2634 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import h5py\n", - "import pandas as pd\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib as mpl\n", - "from pathlib import Path\n", - "\n", - "plt.style.use('ggplot')\n", - "mpl.rcParams['scatter.edgecolors'] = 'black'\n", - "mpl.rcParams['lines.markeredgecolor'] = 'black'\n", - "\n", - "\n", - "data_dir = Path('../data/hdf')\n", - "data_file = data_dir / '30449.h5'" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "Pull out all of the signal names, shapes, dimensions, and data types from the sample HDF5 file." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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nameshapen_dimsdtypeunitslabeldescriptionshot_id
0abm/CALIB_SHOT/data()0int16Calibration Shot30449
1abm/CALIB_SHOT/errors()0int16Calibration Shot30449
2abm/CALIB_SHOT/time()0float32SCalibration Shot30449
3abm/CHANNEL_STATUS/data(32,)1float32channel_status30449
4abm/CHANNEL_STATUS/errors(32,)1float32channel_status30449
...........................
995amc/STATUS/time()0float32S30449
996amc/TF CURRENT/data(30000,)1float32kATF Current30449
997amc/TF CURRENT/errors(30000,)1float32TF Current30449
998amc/TF CURRENT/time(30000,)1float32sTF Current30449
999amc/VERSION/data()0float3230449
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1000 rows × 8 columns

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" - ], - "text/plain": [ - " name shape n_dims dtype units \\\n", - "0 abm/CALIB_SHOT/data () 0 int16 \n", - "1 abm/CALIB_SHOT/errors () 0 int16 \n", - "2 abm/CALIB_SHOT/time () 0 float32 S \n", - "3 abm/CHANNEL_STATUS/data (32,) 1 float32 \n", - "4 abm/CHANNEL_STATUS/errors (32,) 1 float32 \n", - ".. ... ... ... ... ... \n", - "995 amc/STATUS/time () 0 float32 S \n", - "996 amc/TF CURRENT/data (30000,) 1 float32 kA \n", - "997 amc/TF CURRENT/errors (30000,) 1 float32 \n", - "998 amc/TF CURRENT/time (30000,) 1 float32 s \n", - "999 amc/VERSION/data () 0 float32 \n", - "\n", - " label description shot_id \n", - "0 Calibration Shot 30449 \n", - "1 Calibration Shot 30449 \n", - "2 Calibration Shot 30449 \n", - "3 channel_status 30449 \n", - "4 channel_status 30449 \n", - ".. ... ... ... \n", - "995 30449 \n", - "996 TF Current 30449 \n", - "997 TF Current 30449 \n", - "998 TF Current 30449 \n", - "999 30449 \n", - "\n", - "[1000 rows x 8 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def load_hdf(path):\n", - " results = []\n", - "\n", - " def _visitor(name, node):\n", - " if isinstance(node, h5py.Dataset):\n", - " shape = node.shape\n", - " shape = tuple(v for v in shape if v != 1)\n", - " n_dims = len(shape) if len(node.shape) >= 1 else 1 \n", - " units = node.attrs.get('units', '')\n", - " label = node.parent.attrs.get('label', '')\n", - " description = node.parent.attrs.get('description', '')\n", - " result = dict(name=name, shape=shape, n_dims=n_dims, dtype=node.dtype, units=units, label=label, description=description)\n", - " results.append(result)\n", - " \n", - " with h5py.File(path) as handle:\n", - " handle.visititems(_visitor)\n", - " meta_df = pd.DataFrame(results)\n", - " meta_df['shot_id'] = int(data_file.stem)\n", - " return meta_df\n", - "\n", - "meta_df = load_hdf(data_file)\n", - "meta_df.head(1000)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "There are approximately ~2 billion data points for a given shot" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1944466520.0" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sep = '/'\n", - "meta_df['n_elements'] = meta_df['shape'].apply(np.prod)\n", - "meta_df['signal_name'] = meta_df.name.map(lambda x: sep.join(x.split(sep)[:-1]))\n", - "meta_df['source_name'] = meta_df.name.map(lambda x: x.split(sep)[0])\n", - "meta_df['signal_type'] = meta_df.name.map(lambda x: x.split(sep)[-1])\n", - "meta_df.n_elements.sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "There are approximately 17795 different signals for a given shot" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Signals 17795\n", - "Sources 64\n" - ] - } - ], - "source": [ - "print('Signals', len(meta_df.signal_name.unique()))\n", - "print('Sources', len(meta_df.source_name.unique()))" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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nameshapen_dimsdtypeunitslabeldescriptionshot_idn_elementssignal_namesource_namesignal_type
0abm/CALIB_SHOT/data()0int16Calibration Shot304491.0abm/CALIB_SHOTabmdata
3abm/CHANNEL_STATUS/data(32,)1float32channel_status3044932.0abm/CHANNEL_STATUSabmdata
6abm/CHANNEL_TYPE/data(32,)1float32channel_type3044932.0abm/CHANNEL_TYPEabmdata
9abm/GAIN/data(32,)1float32GAIN3044932.0abm/GAINabmdata
12abm/I-BOL/data(7500, 32)2float32W/m^2i-bol30449240000.0abm/I-BOLabmdata
.......................................
54498xyr/RTTE/data(240, 130)2uint16eV/xyr/rtTe3044931200.0xyr/RTTExyrdata
54500xyr/SEGMENT1/data(240,)1int3230449240.0xyr/SEGMENT1xyrdata
54502xyr/SEGMENTTIME/data(240,)1float64/segmentTime30449240.0xyr/SEGMENTTIMExyrdata
54504xyr/SENTTIME/data(240,)1float64/sentTime30449240.0xyr/SENTTIMExyrdata
54506xyr/TIME1/data(240,)1float64sTime30449240.0xyr/TIME1xyrdata
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11153 rows × 12 columns

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54496xyr/RTNE/data(240, 130)2float32m^-3/rtne3044931200.0xyr/RTNExyrdata
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nameshapen_dimsdtypeunitslabeldescriptionshot_idn_elementssignal_namesource_namesignal_type
117act/C_PLA_RAW_SPECTRUM/data(3, 32, 60)3float32Photo electrRaw spectrum304495760.0act/C_PLA_RAW_SPECTRUMactdata
135act/C_SS_RAW_SPECTRUM/data(3, 64, 60)3float32Photo electrRaw spectrum3044911520.0act/C_SS_RAW_SPECTRUMactdata
153act/SS_BGSPEC/data(130, 64, 60)3float32Photo electrBackground spectrum30449499200.0act/SS_BGSPECactdata
159act/SS_COVARIANCE/data(130, 64, 16)3float32N/AInt, Pos, Wid, Alpha cov30449133120.0act/SS_COVARIANCEactdata
165act/SS_CXSPEC/data(130, 64, 60)3float32Photo electrActive spectrum30449499200.0act/SS_CXSPECactdata
174act/SS_FITS/data(130, 64, 60)3float32Photo electrFitted spectrum30449499200.0act/SS_FITSactdata
177act/SS_SPECTRA/data(130, 64, 60)3float32Photo electrSpectrum30449499200.0act/SS_SPECTRAactdata
198act/_C_PLB_RAW_SPECTRUM/data(3, 32, 60)3float32Photo electrRaw spectrum304495760.0act/_C_PLB_RAW_SPECTRUMactdata
1821ayc/ASPECTRA/data(104, 130, 4)3float32VsFitted spectra3044954080.0ayc/ASPECTRAaycdata
1854ayc/PLASMALIGHT_ERROR/data(104, 130, 4)3float32VsPlasma light noise on sc3044954080.0ayc/PLASMALIGHT_ERRORaycdata
1857ayc/POISSON_ERROR/data(104, 130, 4)3float32VsPoisson error on scatter3044954080.0ayc/POISSON_ERRORaycdata
1878ayc/SPECTRA/data(104, 130, 4)3float32VsRaw spectra3044954080.0ayc/SPECTRAaycdata
1881ayc/SPECTRA_STRAY_LIGHT/data(104, 130, 4)3float32VsRaw spectra3044954080.0ayc/SPECTRA_STRAY_LIGHTaycdata
1914aye/ASPECTRA/data(104, 16, 4)3float32VsFitted spectra304496656.0aye/ASPECTRAayedata
1923aye/GAUSS_AMPLITUDE/data(104, 16, 4)3float32Vsgaussian amplitude spect304496656.0aye/GAUSS_AMPLITUDEayedata
1926aye/GAUSS_DCLEVEL/data(104, 16, 4)3float32Vsgaussian DC level spectr304496656.0aye/GAUSS_DCLEVELayedata
1929aye/GAUSS_POSITION/data(104, 16, 4)3float32Vsgaussian position spectr304496656.0aye/GAUSS_POSITIONayedata
1932aye/GAUSS_SIGMA/data(104, 16, 4)3float32Vsgaussian sigma spectra304496656.0aye/GAUSS_SIGMAayedata
1971aye/SPECTRA/data(104, 16, 4)3float32VsRaw spectra304496656.0aye/SPECTRAayedata
2440efm/PLASMA_CURR(R,Z)/data(82, 65, 65)3float32A/m^2J(r,z)30449346450.0efm/PLASMA_CURR(R,Z)efmdata
2467efm/PSI(R,Z)/data(95, 65, 65)3float32Wb/radpsi(r,z)30449401375.0efm/PSI(R,Z)efmdata
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" - ], - "text/plain": [ - " name shape n_dims dtype \\\n", - "117 act/C_PLA_RAW_SPECTRUM/data (3, 32, 60) 3 float32 \n", - "135 act/C_SS_RAW_SPECTRUM/data (3, 64, 60) 3 float32 \n", - "153 act/SS_BGSPEC/data (130, 64, 60) 3 float32 \n", - "159 act/SS_COVARIANCE/data (130, 64, 16) 3 float32 \n", - "165 act/SS_CXSPEC/data (130, 64, 60) 3 float32 \n", - "174 act/SS_FITS/data (130, 64, 60) 3 float32 \n", - "177 act/SS_SPECTRA/data (130, 64, 60) 3 float32 \n", - "198 act/_C_PLB_RAW_SPECTRUM/data (3, 32, 60) 3 float32 \n", - "1821 ayc/ASPECTRA/data (104, 130, 4) 3 float32 \n", - "1854 ayc/PLASMALIGHT_ERROR/data (104, 130, 4) 3 float32 \n", - "1857 ayc/POISSON_ERROR/data (104, 130, 4) 3 float32 \n", - "1878 ayc/SPECTRA/data (104, 130, 4) 3 float32 \n", - "1881 ayc/SPECTRA_STRAY_LIGHT/data (104, 130, 4) 3 float32 \n", - "1914 aye/ASPECTRA/data (104, 16, 4) 3 float32 \n", - "1923 aye/GAUSS_AMPLITUDE/data (104, 16, 4) 3 float32 \n", - "1926 aye/GAUSS_DCLEVEL/data (104, 16, 4) 3 float32 \n", - "1929 aye/GAUSS_POSITION/data (104, 16, 4) 3 float32 \n", - "1932 aye/GAUSS_SIGMA/data (104, 16, 4) 3 float32 \n", - "1971 aye/SPECTRA/data (104, 16, 4) 3 float32 \n", - "2440 efm/PLASMA_CURR(R,Z)/data (82, 65, 65) 3 float32 \n", - "2467 efm/PSI(R,Z)/data (95, 65, 65) 3 float32 \n", - "\n", - " units label description shot_id n_elements \\\n", - "117 Photo electr Raw spectrum 30449 5760.0 \n", - "135 Photo electr Raw spectrum 30449 11520.0 \n", - "153 Photo electr Background spectrum 30449 499200.0 \n", - "159 N/A Int, Pos, Wid, Alpha cov 30449 133120.0 \n", - "165 Photo electr Active spectrum 30449 499200.0 \n", - "174 Photo electr Fitted spectrum 30449 499200.0 \n", - "177 Photo electr Spectrum 30449 499200.0 \n", - "198 Photo electr Raw spectrum 30449 5760.0 \n", - "1821 Vs Fitted spectra 30449 54080.0 \n", - "1854 Vs Plasma light noise on sc 30449 54080.0 \n", - "1857 Vs Poisson error on scatter 30449 54080.0 \n", - "1878 Vs Raw spectra 30449 54080.0 \n", - "1881 Vs Raw spectra 30449 54080.0 \n", - "1914 Vs Fitted spectra 30449 6656.0 \n", - "1923 Vs gaussian amplitude spect 30449 6656.0 \n", - "1926 Vs gaussian DC level spectr 30449 6656.0 \n", - "1929 Vs gaussian position spectr 30449 6656.0 \n", - "1932 Vs gaussian sigma spectra 30449 6656.0 \n", - "1971 Vs Raw spectra 30449 6656.0 \n", - "2440 A/m^2 J(r,z) 30449 346450.0 \n", - "2467 Wb/rad psi(r,z) 30449 401375.0 \n", - "\n", - " signal_name source_name signal_type \n", - "117 act/C_PLA_RAW_SPECTRUM act data \n", - "135 act/C_SS_RAW_SPECTRUM act data \n", - "153 act/SS_BGSPEC act data \n", - "159 act/SS_COVARIANCE act data \n", - "165 act/SS_CXSPEC act data \n", - "174 act/SS_FITS act data \n", - "177 act/SS_SPECTRA act data \n", - "198 act/_C_PLB_RAW_SPECTRUM act data \n", - "1821 ayc/ASPECTRA ayc data \n", - "1854 ayc/PLASMALIGHT_ERROR ayc data \n", - "1857 ayc/POISSON_ERROR ayc data \n", - "1878 ayc/SPECTRA ayc data \n", - "1881 ayc/SPECTRA_STRAY_LIGHT ayc data \n", - "1914 aye/ASPECTRA aye data \n", - "1923 aye/GAUSS_AMPLITUDE aye data \n", - "1926 aye/GAUSS_DCLEVEL aye data \n", - "1929 aye/GAUSS_POSITION aye data \n", - "1932 aye/GAUSS_SIGMA aye data \n", - "1971 aye/SPECTRA aye data \n", - "2440 efm/PLASMA_CURR(R,Z) efm data \n", - "2467 efm/PSI(R,Z) efm data " - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data_signals.loc[meta_df.n_dims == 3]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Some notes on this:\n", - "\n", - " - Objects are actually just binary strings. So are not large or complicated\n", - " - Mix of (1, ) dimensional values and () zero dimensional values. Is there a difference?\n" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 15.722222222222216, 'Number of Elements')" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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dnz59/N2FTst1ZGBDKioqVFFRIanuYcHrrruuLbrVrm3cuFGbNm1SdHS00tLS/N0dAADQgTUrkf3Xv/5Vf/3rX73eu3DhgubNm9dgTG1trdeEbuTIkVfRzdZhNpv1m9/8Rn//+9+1fft2FRQUyGazqVevXoqPj1dKSooGDRrkMzY8PFwvvPCCNmzYoOzsbBUXF8tkMikmJkbjxo1TSkqKTKaGhzMuLk7Lly/X+vXrtXfvXpWUlMhsNismJkaJiYmaMGGC1yrwy9122216/vnntX79eh04cEBlZWUKDg5WbGyskpKSNHbs2BaPDwAAQGvqqHNH14pjqe5H4cuPpJEko9Goe++9V7///e918eJF5eXlacCAAe6V0ZLkcDT8o7pnmWeMZ9sOh6PekTIulZWVPmNc14217VnuGevLtGnT3KvNpW9Xe3luv97VGAwGRUREqKioyOuhB3Qt3Adw4V5oLxo+jqOrOH36tF/bN5lMnfZBt1dfffWKdU6fPq2//OUv2r17tx5++GElJCS0Qc/ar+TkZCUnJ/u7GwAAoBNoViL70qVLslqtXu85nc567zXklltu0YwZM5rTZKszGo2aOHGiJk6c2OxYi8Wi1NRUpaamXlXboaGhmjlzZoMrr68kIiJCs2fPvqpYAACAttZR546eZ1M3tiI8OjrafW21WjVgwIB6Z1/fdNNNPmMbOks7LCzMq05DiWxXvMVi8UqEu+IvXbqkysrKBrdmd8V7tudL9+7d1b17d59lXT1hU1tb2+XHANwH+Bb3AvyN+8+/+vTpo3nz5slkMunVV19VZGSkbr75Zn93CwAAoMNrViJ71KhRXk9Xvv766woKCmo0MWs0GmWxWBQTE8NWWwAAAF1IR507hoSEqFevXl7J5itxrVSOioqSwWBQbW2tCgoKGlxRXlBQIKnuQceQkBD3+3379vWq45ks9xV/eXlMTIz7Oj8/X/37929WPAAAAK7e97//ff3973/XunXrNH/+fH93BwAAoMNrViL75ptv9nqa8PXXX1dAQEC9M6UBAACAjjx3HD58uLZu3arCwsIG65w8edJ9HR4eLqnuXMT4+HgdOXJE+/fv19SpU+vF1dbWKicnx92Opz59+uiGG25QSUmJ9u/frzvuuKNevN1u15EjRyRJt956q1dZfHy8AgICVFlZqf379/tMZFutVvf3ujweAAAAV+/6669XUFCQDh8+7O+uAAAAdAoNH8rcBGvWrNHKlStbqy8AAADoxDrS3HHChAmSpKKiIu3Zs6deudPp1IYNGyTVbQ0eGxvrLktMTJQkHTp0SEePHq0Xu2vXLp05c8arrovBYNBdd90lSdq5c6eKi4vrxW/atEl2u11Go1F33nmnV5nZbNaYMWMkSVu2bHGfNe5p/fr1kuq2JR81apSvrw8AAICrUFlZKZvN5nMOBgAAgOZrUSIbAAAA6IwGDx6ssWPHSpJWrlyp3bt3q6amRpJUUlKil156SSdOnJAkPfTQQzIav51WJyYmqm/fvqqtrdXy5ct18OBBSXXJ7127drmT+SNHjtSwYcPqtT116lSFhobK4XBo2bJlysvLkyRVV1dr8+bNWrNmjSQpKSnJ5xneDz74oAIDA3Xu3Dmlp6fr9OnTkupWcmdkZGjLli2SpOnTp3ttaw4AAICW2bp1q2pra9WrVy9/dwUAAKBTaNbW4o1xOp0qKipSeXm5qqurG607ZMiQ1moWAAAAHVBHmDv+5Cc/0fnz53XkyBG9+OKL6t69uwICAnTp0iV3nRkzZtTbKr1bt25asGCBlixZIqvVqmeffVaBgYFyOp2qqqqSJMXGxuqJJ57w2W5QUJAWLVqkpUuX6uTJk1q0aJEsFosqKyvdyfRbb721wbPGw8PDNX/+fK1YsUJHjhzRk08+qaCgINntdjmdTknS+PHjfW57DgAAAG8lJSWNlldWVurs2bPKzs7W3//+d0nS6NGj26JrAAAAnV6LE9nnzp3TO++8o927d6uysvKK9Q0Gg/785z+3tFkAAAB0QB1p7mg2m/Wb3/xGf//737V9+3YVFBTIZrOpV69eio+PV0pKigYNGuQzNjw8XC+88II2bNig7OxsFRcXy2QyKSYmRuPGjVNKSopMpoan4nFxcVq+fLnWr1+vvXv3qqSkRGazWTExMUpMTNSECRO8VoFf7rbbbtPzzz+v9evX68CBAyorK1NwcLBiY2OVlJTkXm0OAACAxs2dO7dZ9aOjo/XAAw9co94AAAB0LS1KZJeWlupXv/qVSktLmxxTW1vbkiYBAADQQXXEuaPRaNTEiRM1ceLEZsdaLBalpqYqNTX1qtoODQ3VzJkzG1x5fSURERGaPXv2VcUCAACgeW688UaNGzdO9913n8xms7+70yJ5eXn65JNP9MUXX7gfyIyOjtaUKVNYbQ4AANpUixLZ77//vkpLS2U2m/WDH/xAt99+u3r16tXo6hAAAAB0TcwdAQAA0NH8/ve/b7S8W7duCg4OVmBgYBv16NrLzMzUgQMHNHr0aE2aNEmVlZX6xz/+oRdeeEEPPPCAHnzwQX93EQAAdBEtSmTv379fkjRnzhy2JwQAAECjmDsCAACgo+ndu7e/u9DmkpOT9ZOf/EQBAQHu91JSUvT000/rgw8+0JQpUxQSEuLHHgIAgK6iRctfLly4oG7dumnUqFGt1R8AAAB0UswdAQAAgPYvPj7eK4kt1R25M2bMGNXU1OjUqVN+6hkAAOhqWrQiu0ePHrLZbOrWrVtr9QcAAACdFHNHAAAAdHQ2m03Hjx/X+fPnJUk9e/ZUbGysLBaLn3t27ZWWlkqqm9cDAAC0hRYlsocNG6Zt27bp9OnT6tOnT2v1CQAAAJ0Qc0cAAAB0VPn5+Xr33Xe1f/9+OZ1OrzKj0aiRI0fqoYceUt++fVulPYfDocOHDysvL0/Hjx9XXl6eSkpKJEkzZsxQamrqFT/DZrNpw4YNys7OVnFxsYxGoyIjI5WQkKCUlBSZTE3/abi0tFRbt27VgAEDFBERcdXfCwAAoDlatLX49OnTZTab9fbbb7dWfwAAANBJMXcEAABAR5Sdna1f/vKX2rt3b70ktiQ5nU59/vnn+uUvf6k9e/a0Sptff/21nnvuOa1Zs0Z79uxxJ7Gbymq16uc//7kyMjJUUFAgSaqurtaxY8f01ltv6Ve/+pXKy8ub9FkOh0PPP/+8qqqq9Pjjjzf7uwAAAFytFiWyIyIitGDBAh0+fFjPPvusvvjiC9nt9tbqGwAAADoR5o4AAADoaIqLi/Xyyy+rqqpKvXv31o9+9CO99NJLWr16tVavXq2XXnpJP/rRjxQeHq6qqiq9/PLLKi4ubpW2g4ODNWzYME2dOlVPPvmkQkNDmxRXU1Oj9PR0Wa1WhYWF6d/+7d/01ltv6a233tLPfvYzWSwWHT9+XK+88soVP6u6ulovvPCCjh8/rp/+9Ke66aabWvitAAAAmq5FW4s/+OCD7usvvvhCX3zxxRVjDAaD/vznP7ekWQAAAHRAzB0BAADQ0WRmZqq6uloDBw7Ur371K5nNZq/yiIgIRURE6K677tLSpUv11VdfacOGDfrRj37UonYHDx6sP/3pT17vvfPOO02K3bZtm/Lz8yVJaWlpGjhwoKS6LdATEhLkdDr18ssva9++fTp48KCGDRvm83Oqq6v14osv6sCBA5ozZ47GjBnTgm8EAADQfC1akX01amtr27pJAAAAdFDMHQEAAOBPBw8elCTNmjWrXhLbk9ls1qxZsyRJBw4caHG7RuPV/2y7bds2SdLQoUPdSWxP48aNU3h4uFfdy7mS3Z999pl+9KMfafz48VfdHwAAgKvVohXZv/nNb1qrHwAAAOjkmDsCAACgozl79qwsFov69u17xbp9+/aVxWLR2bNn26BnvjkcDuXm5kqSRo4c6bOOwWDQiBEjtHnzZp9Jd6fTqd///vfavXu3Zs6cqUmTJl3TPgMAADSkRYnsIUOGtFY/AAAA0MkxdwQAAEBH061bN9XU1DSpbm1traqrq9WtW7dr3KuGFRYWunc1iomJabCeq6ysrEzl5eUKCQlxl61evVo7duzQwIEDdd1112n79u1esYMGDdKNN954DXoPAADgrUWJbAAAAAAAAADorCIiIvTNN99o//79GjFiRKN1c3JyVFVVpaioqLbpnA+lpaXu6169ejVYz7OstLTUK5Gdl5cnSfrqq6/01Vdf1Yv9yU9+QiIbAAC0CRLZAAAAAAAAAODDqFGj9M0332jlypX61a9+pejoaJ/1Tp48qZUrV7pj/MVut7uvAwMDG6znWeYZI0nPPPPMVbVdVVWlqqoq92uDwSCLxeK+bk3N+bzWbru1tNd+dQausWWMcTnuDTSG+6N9alEi+/Dhw1cVx7aSAAAAXQ9zRwAAAHQ0kydP1kcffaTS0lItXLhQY8eO1bBhw9wrms+ePauDBw8qOztb1dXV6tWrl6ZMmeLnXvvHunXrlJGR4X4dGxur9PR09e7d+xq16GhSrT59+lyj9pujfl/bR786t4iICH93Ae0U9wYaw/3RvrQokb1kyZJmxxgMBv35z39uSbMAAADogJg7AgAAoKMJCgrSL3/5S6Wnp8tqtWrHjh3asWOHz7rh4eFasGCBexWyP5jNZve1w9FwotezzDOmJaZNm6Z77rnH/dq1os1qtaq6urpV2vD+7LAm1T19+nSrtn116m/z3j761TkZDAZFRESoqKjIfWY8IHFvoHHcH23HZDI1+UG3Nt9anP/4AAAAaCrmjgAAAPC3mJgYvfDCC9q4caN27dql/Px8OZ1OSZLRaFTfvn01btw4TZo0qdWSwlfr8rOvb7rpJp/1mnqWdnN0795d3bt391nmz3l9e/3/FO21X51JbW0t4wyfuDfQGO6P9qVFiew1a9Y0Wl5RUaGvv/5a69atU35+vn7+859r8ODBLWkSAAAAHRRzRwAAAHRUZrNZ999/v+6//35VV1ervLxckhQSEiKTqc3XCjUoKipKBoNBtbW1Kigo0MiRI33WKygokCSFhoYqJCSkVfuwceNGbdq0SdHR0UpLS2vVzwYAAF2L8Vp+eFBQkIYPH65f//rXGjRokP7jP/5DxcXF17JJAAAAdFDMHQEAANARmEwmhYaGKjQ0tF0lsSUpMDBQ8fHxkqT9+/f7rFNbW6ucnBxJ0vDhw1u9D8nJyVqxYgVJbAAA0GLXNJHtYjAY9Mgjj6iiokIZGRlt0SQAAAA6KOaOAAAA8Kfy8nKdOHFC+fn5TapfW1ur/Px8nThxwr1S258SExMlSYcOHdLRo0frle/atUtnzpzxqgsAANAetUkiW5IiIyNlsVh08ODBtmoSAAAAHRRzRwAAAPjLiy++qAULFmjTpk1Nqm8wGLR582YtWLBAr7zySqv1o7y8XBcuXHD/uc7lrqys9Hrfbrd7xSUmJqpv376qra3V8uXL3XNqp9OpXbt2aeXKlZKkkSNHatiwYa3WXwAAgNbWZnvfVFdXq7KyUlVVVW3VJAAAADoo5o4AAADwh6+//lqHDh1SaGioZs6c2eS4Rx99VJ9++qn279+vb775RjfffHOL+7Jw4UJZrdZ672dmZiozM9P9OjExUXPnznW/7tatmxYsWKAlS5bIarXq2WefVWBgoJxOp3t+HRsbqyeeeKLFffSFM7IBAEBrabNE9qeffqqamhr16tWrrZoEAABAB8XcEQAAAP6wY8cOSVJKSooCAgKaHBcQEKDJkyfrnXfe0SeffNIqieyWCA8P1wsvvKANGzYoOztbxcXFMplMiomJ0bhx45SSknLNzvdOTk5WcnLyNfnsa+WORdfXe2/XsrN+6AkAAPB0TRPZ1dXVKikpUXZ2ttatWyepbssaAAAA4HLMHQEAAOBvX331lSRp1KhRzY4dNWqU3nnnHeXm5rZKX1599dUWxVssFqWmpio1NbVV+gMAANDWWpTIfvDBB5tVv1evXpoxY0ZLmgQAAEAHxdwRAAAA7d2ZM2dkNBoVFRXV7NjIyEgZjUYVFRVdg54BAAB0PW2ytXhAQIDGjBmjf/7nf2Z7SAAAADSKuSMAAAD8paKiQkFBQVcdHxQUJJvN1oo9AgAA6LpalMj+zW9+02i50WhUSEiI+vTpo27durWkKQAAAHRwzB0BAADQ3lksFlVUVFx1fEVFhSwWSyv2qOPZuHGjNm3apOjoaKWlpfm7OwAAoANrUSJ7yJAhrdUPAAAAdHLMHQEAANDehYWF6dKlS8rPz1ffvn2bFVtQUCCn06nQ0NBr07kOIjk5WcnJyf7uBgAA6ASM/u4AAAAAAAAAALQHgwYNkiTt3Lmz2bE7duzw+gwAAAC0TKsnsq1Wq77++mt9/fXXslqtrf3xAAAA6ESYOwIAAKA9GT16tCTpb3/7mwoLC5scd/LkSf3tb3/z+gwAAAC0TIu2Fnc5d+6c1q1bp507d+rixYteZdddd53uvPNO3XfffQoLC2uN5gAAANCBMXcEAABAezVixAjFxcUpLy9P//7v/64nn3xS8fHxjcbk5ubqpZdeksPhUFxcnEaOHNlGvQUAAOjcWpzIzs3N1fPPP6/y8nKf5RcvXtTf/vY37dixQ7/4xS/YWgcAAKALY+4IAACA9u6JJ57Qr371K5WWluo3v/mNhg0bptGjR+vmm29WSEiIJKm8vFzffPON9uzZo4MHD0qSgoKC9MQTT/iz6+3Cxo0btWnTJkVHRystLc3f3QEAAB1YixLZ58+f13/8x3/o0qVLslgs+u53v6vhw4fr+uuvlySdPXtWBw8e1JYtW3Tx4kX9x3/8h1588UX17NmzVToPAACAjoO5IwAAADqCyMhI/epXv9Ly5ctVWlqqgwcPupPVDQkLC1NaWpoiIyPbqJftV3JyspKTk/3dDQAA0Am0KJG9YcMGXbp0SZGRkXr66afVq1cvr/LIyEgNGzZMycnJevbZZ3Xq1Cl9+OGHevjhh1vUaQAAAHQ8zB0BAADQUfTv31/PP/+8PvjgA3300UeqqKjwWS8oKEgTJ07Ufffdp+uuu66NewkAANC5tSiRvW/fPknS7Nmz6/0Q6alXr16aPXu2fvOb32jv3r38GAkAANAFMXcEAABARxISEqJHHnlE//zP/6xjx46poKDAfUROSEiIYmJi1K9fPxmNRj/3FAAAoHNqUSK7uLhYZrNZ8fHxV6wbHx+vwMBAWa3WljQJAACADoq5IwAAADoio9GoAQMGaMCAAf7uCgAAQJfS5o8L1tbWtnWTAAAA6KCYOwIAAAAAAABdU4sS2eHh4bLb7frqq6+uWPerr76Sw+FQeHh4S5oEAABAB8XcEQAAAOj8Nm7cqPnz52v58uX+7goAAOjgWpTIHjFihCTpv/7rv3ThwoUG650/f14rV66UJI0cObIlTQIAAKCDYu4IAAAAdH7JyclasWKF0tLS/N0VAADQwbXojOx7771XH3/8sQoKCjR//nx997vf1bBhw9SrVy9J0tmzZ/XFF19oy5YtKi8vV1BQkO65555W6TgAAAA6FuaOAAAAAAAAAJqqRYns0NBQ/eIXv9Dzzz+v8vJyrVu3TuvWrfNZNygoSL/4xS8UGhrakiZb3QcffKB33nnH/fq9995rsK7NZtOGDRuUnZ2t4uJiGY1GRUZGKiEhQSkpKTKZGh/OsrIyZWZm6vPPP1dJSYkCAgIUExOjxMRE3X333TIYDI3GFxUVKTMzUzk5OSorK5PZbFZcXJwmTpyosWPHNu+LAwAAtLHOMHcEAAAAAAAA0DZalMiWpCFDhuiFF17Q2rVrtXv3bpWXl3uVh4SE6I477tD06dPdq23ai1OnTun9999vUl2r1apnnnlGVqtVkhQYGKjq6modO3ZMx44d044dO/T0008rJCTEZ3xeXp6WLl2qixcvSpLMZrPsdrtyc3OVm5ur3bt3a+HChQ0mw/fu3asVK1bI4XBIkiwWi8rLy5WTk6OcnByNHz9ec+bMuWIyHAAAwJ868twRAAAAAAAAQNtpcSJbkq6//nrNmjVLs2bNUnFxsc6fPy9J6tmzp8LDw1ujiVbndDr1+uuvq6qqSgMHDtRXX33VYN2amhqlp6fLarUqLCxMc+fO1fDhw+V0OrV7926tXLlSx48f1yuvvKLFixfXi6+oqNCyZct08eJFRUVFad68eerXr5+qq6uVlZWlVatWKScnR2+++aYee+yxevHFxcXuJPagQYM0Z84cRUZGym63KzMzUxkZGdq6dauioqJ03333teo4AQAAtLaOOHcEAAAAAAAA0LaMzQ2oqalRRUWFKioqfJaHh4drwIABGjBggPuHSFd9p9PZst62oo0bN+rLL7/UnXfeqeHDhzdad9u2bcrPz5ckpaWluesbjUYlJCRo1qxZkqR9+/bp4MGD9eIzMzNVVlamgIAALV68WP369ZMkmUwmJScnKzU1VZKUlZWlU6dO1Ytfs2aNHA6HQkNDtWjRIkVGRkqqW9WdmpqqpKQkSdLatWvrrWoCAADwp84ydwQAAAAAAADQtpqdyP7d736nf/mXf9Frr73W5JjXX39d//Iv/6JXX321uc1dE8XFxXr33Xd13XXX6Yc//OEV62/btk2SNHToUA0cOLBe+bhx49w/vLrqetq+fbskKSEhwecqo5SUFJnNZjmdTu3YscOrzG63Kzs7W5I0adIkBQcH14u///77JdWd4f3pp59e8fsAAAC0lc4wdwQAAADQdBs3btT8+fO1fPlyf3cFAAB0cM1KZBcUFGjPnj0KCgrSnDlzmhw3e/ZsBQUF6R//+IdOnz7d7E62tpUrV8rhcOjRRx9Vjx49Gq3rcDiUm5srSRo5cqTPOgaDQSNGjJAkHThwwKvs1KlTKikpaTTebDZr8ODBkqScnByvstzcXFVWVkqSu43LhYeHKyoqymc8AACAv3SWuSMAAACApktOTtaKFSuUlpbm764AAIAOrllnZH/yySeSGl4Z3JCQkBAlJydr7dq1+uSTT9xbaftDVlaWDh48qGHDhikxMfGK9QsLC1VbWytJiomJabCeq6ysrEzl5eUKCQmRJPeW5E2J37dvn06ePOn1fkFBgfu6b9++jcYXFhbWiwcAAPCXzjB3vNwHH3ygd955x/36vffea7CuzWbThg0blJ2dreLiYhmNRkVGRiohIUEpKSkymRqfipeVlSkzM1Off/65SkpKFBAQoJiYGCUmJuruu++WwWBoNL6oqEiZmZnKyclRWVmZzGaz4uLiNHHiRI0dO7Z5XxwAAKCLmjdvXrPqd+/eXcHBwYqOjtaIESM0evRoGY3N3hQTAAAAamYi27UyecyYMc1uaMyYMVq7dq0OHTrU7NjWUlpaqtWrVysgIECPP/54k2NcevXq1WA9z7LS0lJ3IvvcuXPNirfZbLLb7TKbzV7xwcHBCggIuGK8Z3sAAAD+1NHnjpc7deqU3n///SbVtVqteuaZZ2S1WiVJgYGBqq6u1rFjx3Ts2DHt2LFDTz/9tHvOeLm8vDwtXbpUFy9elFS3g4/dbldubq5yc3O1e/duLVy4sMFk+N69e7VixQo5HA5JksViUXl5uXJycpSTk6Px48drzpw5V0yGAwAAdHWu+VxzHT16VH//+98VHR2t+fPnKzo6upV7BgAA0Pk1K5F9+vRpGY1GxcbGNruhvn37ymAw6NSpU82ObS3/9V//pYqKCj388MO68cYbmxRjt9vd14GBgQ3W8yzzjLHZbE2K90xS22w2dyLbFd9YrGe5Z3u+VFVVqaqqyv3aYDDIYrG4r9sDVz/aS3/aK8ap6RirpmGcmo6xahrGyT/a03h39LmjJ6fTqddff11VVVUaOHCgvvrqqwbr1tTUKD09XVarVWFhYZo7d66GDx8up9Op3bt3a+XKlTp+/LheeeUVLV68uF58RUWFli1bposXLyoqKkrz5s1Tv379VF1draysLK1atUo5OTl688039dhjj9WLLy4udiexBw0apDlz5igyMlJ2u12ZmZnKyMjQ1q1bFRUVpfvuu69Vxwk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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "labelsize = 18\n", - "mpl.rc('xtick', labelsize=labelsize) \n", - "mpl.rc('ytick', labelsize=labelsize) \n", - "mpl.rc('axes', labelsize=labelsize) \n", - "color = '#1e5df8'\n", - "\n", - "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(20, 5))\n", - "dtype_counts = data_signals.groupby('dtype').name.count()\n", - "dtype_counts = dtype_counts.sort_values()\n", - "dtype_counts.plot.bar(ax=ax1, linewidth=1.2, color=color)\n", - "ax1.set_ylabel('Counts')\n", - "ax1.set_xlabel('Data Type')\n", - "\n", - "n_dims_counts = data_signals.groupby('n_dims').name.count()\n", - "n_dims_counts = n_dims_counts.sort_values()\n", - "n_dims_counts.plot.bar(ax=ax2, linewidth=1.2, color=color)\n", - "ax2.set_ylabel('Counts')\n", - "ax2.set_xlabel('No. of Dimensions')\n", - "plt.tight_layout()\n", - "\n", - "n_elements_counts = data_signals.n_elements\n", - "n_elements_counts.plot.hist(ax=ax3, bins=100, linewidth=1.2, color=color)\n", - "plt.yscale('log')\n", - "plt.ylabel('log Counts')\n", - "plt.xlabel('Number of Elements')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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name_datashape_datan_dims_datadtype_dataunits_datalabel_datadescription_datashot_id_datan_elements_datasignal_name...shape_timen_dims_timedtype_timeunits_timelabel_timedescription_timeshot_id_timen_elements_timesource_name_timesignal_type_time
1abm/CHANNEL_STATUS/data(32,)1float32channel_status3044932.0abm/CHANNEL_STATUS...()0float32Schannel_status304491.0abmtime
2abm/CHANNEL_TYPE/data(32,)1float32channel_type3044932.0abm/CHANNEL_TYPE...()0float32Schannel_type304491.0abmtime
3abm/GAIN/data(32,)1float32GAIN3044932.0abm/GAIN...()0float32SGAIN304491.0abmtime
4abm/I-BOL/data(7500, 32)2float32W/m^2i-bol30449240000.0abm/I-BOL...(7500,)1float32si-bol304497500.0abmtime
5abm/KM/data(32,)1float32WattsKM3044932.0abm/KM...()0float32SKM304491.0abmtime
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10474xyc/430/4/DATA/data(240, 300)2float32/xyc/430/4/data3044972000.0xyc/430/4/DATA...(300,)1float64s/xyc/430/4/data30449300.0xyctime
10487xyc/LASER_AREA_ENERGY/DATA/data(240, 300)2float32/xyc/laser_area_energy/data3044972000.0xyc/LASER_AREA_ENERGY/DATA...(300,)1float64s/xyc/laser_area_energy/data30449300.0xyctime
10496xyc/LASER_AREA_ENERGY2/DATA/data(240, 300)2float32/xyc/laser_area_energy2/data3044972000.0xyc/LASER_AREA_ENERGY2/DATA...(300,)1float64s/xyc/laser_area_energy2/data30449300.0xyctime
10504xyc/LASER_TRACKER_GS/DATA/data(240, 300)2float32/xyc/laser_tracker_gs/data3044972000.0xyc/LASER_TRACKER_GS/DATA...(300,)1float64s/xyc/laser_tracker_gs/data30449300.0xyctime
10508xyc/YAG_LIGHT/DATA/data(240, 300)2float32/xyc/yag_light/data3044972000.0xyc/YAG_LIGHT/DATA...(300,)1float64s/xyc/yag_light/data30449300.0xyctime
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838 rows × 23 columns

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nameshapen_dimsdtypeunitslabeldescriptionshot_idn_elementssignal_namesource_namesignal_type
0abm/CALIB_SHOT/data()0int16Calibration Shot304491.0abm/CALIB_SHOTabmdata
1abm/CALIB_SHOT/errors()0int16Calibration Shot304491.0abm/CALIB_SHOTabmerrors
2abm/CALIB_SHOT/time()0float32SCalibration Shot304491.0abm/CALIB_SHOTabmtime
3abm/CHANNEL_STATUS/data(32,)1float32channel_status3044932.0abm/CHANNEL_STATUSabmdata
4abm/CHANNEL_STATUS/errors(32,)1float32channel_status3044932.0abm/CHANNEL_STATUSabmerrors
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40396xyr/430/TE/errors(240,)1float32/xyr/430/Te30449240.0xyr/430/TExyrerrors
40397xyr/430/TE/time(240,)1float64s/xyr/430/Te30449240.0xyr/430/TExyrtime
40398xyr/TIME1/data(240,)1float64sTime30449240.0xyr/TIME1xyrdata
40399xyr/TIME1/errors(240,)1float64Time30449240.0xyr/TIME1xyrerrors
40400xyr/TIME1/time(240,)1float64sTime30449240.0xyr/TIME1xyrtime
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94910 rows × 12 columns

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" - ], - "text/plain": [ - " name shape n_dims dtype units \\\n", - "0 abm/CALIB_SHOT/data () 0 int16 \n", - "1 abm/CALIB_SHOT/errors () 0 int16 \n", - "2 abm/CALIB_SHOT/time () 0 float32 S \n", - "3 abm/CHANNEL_STATUS/data (32,) 1 float32 \n", - "4 abm/CHANNEL_STATUS/errors (32,) 1 float32 \n", - "... ... ... ... ... ... \n", - "40396 xyr/430/TE/errors (240,) 1 float32 \n", - "40397 xyr/430/TE/time (240,) 1 float64 s \n", - "40398 xyr/TIME1/data (240,) 1 float64 s \n", - "40399 xyr/TIME1/errors (240,) 1 float64 \n", - "40400 xyr/TIME1/time (240,) 1 float64 s \n", - "\n", - " label description shot_id n_elements signal_name \\\n", - "0 Calibration Shot 30449 1.0 abm/CALIB_SHOT \n", - "1 Calibration Shot 30449 1.0 abm/CALIB_SHOT \n", - "2 Calibration Shot 30449 1.0 abm/CALIB_SHOT \n", - "3 channel_status 30449 32.0 abm/CHANNEL_STATUS \n", - "4 channel_status 30449 32.0 abm/CHANNEL_STATUS \n", - "... ... ... ... ... ... \n", - "40396 /xyr/430/Te 30449 240.0 xyr/430/TE \n", - "40397 /xyr/430/Te 30449 240.0 xyr/430/TE \n", - "40398 Time 30449 240.0 xyr/TIME1 \n", - "40399 Time 30449 240.0 xyr/TIME1 \n", - "40400 Time 30449 240.0 xyr/TIME1 \n", - "\n", - " source_name signal_type \n", - "0 abm data \n", - "1 abm errors \n", - "2 abm time \n", - "3 abm data \n", - "4 abm errors \n", - "... ... ... \n", - "40396 xyr errors \n", - "40397 xyr time \n", - "40398 xyr data \n", - "40399 xyr errors \n", - "40400 xyr time \n", - "\n", - "[94910 rows x 12 columns]" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "meta_df = pd.concat([load_hdf(data_file) for data_file in data_dir.glob('*.h5')])\n", - "\n", - "sep = '/'\n", - "meta_df['n_elements'] = meta_df['shape'].apply(np.prod)\n", - "meta_df['signal_name'] = meta_df.name.map(lambda x: sep.join(x.split(sep)[:-1]))\n", - "meta_df['source_name'] = meta_df.name.map(lambda x: x.split(sep)[0])\n", - "meta_df['signal_type'] = meta_df.name.map(lambda x: x.split(sep)[-1])\n", - "meta_df" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([30449])" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "time_signals = meta_df.loc[meta_df.signal_type == 'time']\n", - "time_signals.shot_id.unique()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3.7.15 ('mast')", - "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": "3.7.15" - }, - "orig_nbformat": 4, - "vscode": { - "interpreter": { - "hash": "32e2b93e115fa525e7525c12e1993da1e1ac7bb7d8640820198c0399f26c9e57" - } - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} From 8adcd04f177c4e31177a5765b298beb44fcba05d Mon Sep 17 00:00:00 2001 From: Samuel Jackson Date: Thu, 15 Aug 2024 14:17:25 +0100 Subject: [PATCH 6/8] Update memory request --- jobs/ingest.csd3.slurm.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/jobs/ingest.csd3.slurm.sh b/jobs/ingest.csd3.slurm.sh index b5747eb..dd05075 100644 --- a/jobs/ingest.csd3.slurm.sh +++ b/jobs/ingest.csd3.slurm.sh @@ -4,7 +4,7 @@ #SBATCH --job-name=fair-mast-ingest #SBATCH --output=fair-mast-ingest_%A.out #SBATCH --time=5:00:00 -#SBATCH --mem=256G +#SBATCH --mem=250G #SBATCH --ntasks=128 #SBATCH -N 2 From 74343ce7c70559ac3409261e39aac271b86655ac Mon Sep 17 00:00:00 2001 From: Samuel Jackson Date: Mon, 19 Aug 2024 08:18:01 +0100 Subject: [PATCH 7/8] Update README --- README.md | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/README.md b/README.md index 919055e..a60b633 100644 --- a/README.md +++ b/README.md @@ -41,9 +41,28 @@ Edit `uda/python/setup.py` and change the "version" to 1.3.9. ```sh python -m pip install uda/python +cd .. source ~/rds/rds-ukaea-mast-sPGbyCAPsJI/uda-ssl.sh ``` +#### S3 Support (Optional) + +Finally, for uploading to S3 we need to install `s5cmd` and make sure it is on the path: + +```sh +wget https://github.com/peak/s5cmd/releases/download/v2.2.2/s5cmd_2.2.2_Linux-64bit.tar.gz +tar -xvzf s5cmd_2.2.2_Linux-64bit.tar.gz +PATH=$PWD:$PATH +``` + +And add a config file for the bucket keys, by creating a file called `.s5cfg.stfc`: + +``` +[default] +aws_access_key_id= +aws_secret_access_key= +``` + You should now be able to run the following commands. ### Submitting runs on CSD3 From b55d40ba26cd43adab2bbee46be2c9c41191b355 Mon Sep 17 00:00:00 2001 From: Samuel Jackson Date: Mon, 19 Aug 2024 08:51:44 +0100 Subject: [PATCH 8/8] Fix README --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index a60b633..456c559 100644 --- a/README.md +++ b/README.md @@ -26,7 +26,7 @@ source fair-mast-ingestion/bin/activate Update pip and install required packages: ```sh -python -m pip install --U pip +python -m pip install -U pip python -m pip install -e . ```