Merge branch 'dev' into prt_support

.readthedocs.yml

@@ -7,7 +7,7 @@ version: 2
 
 # Set the version of Python and other tools you might need
 build:
-  os: ubuntu-22.04
+  os: ubuntu-lts-latest
   tools:
     python: "3.11"
 

nlmod/cache.py

@@ -447,13 +447,13 @@ def _same_function_arguments(func_args_dic, func_args_dic_cache):
     for key, item in func_args_dic.items():
         # check if cache and function call have same argument names
         if key not in func_args_dic_cache:
-            msg = f"cache was created using different function argument {key}, do not use cached data"
+            msg = f"cache was created using different function argument '{key}' not in cached arguments, do not use cached data"
             logger.info(msg)
             return False
 
         # check if cache and function call have same argument types
         if not isinstance(item, type(func_args_dic_cache[key])):
-            msg = f"cache was created using different function argument type: {key}: {type(func_args_dic_cache[key])}, do not use cached data"
+            msg = f"cache was created using different function argument types for {key}: current '{type(item)}' cache: '{type(func_args_dic_cache[key])}', do not use cached data"
             logger.info(msg)
             return False
 
@@ -469,11 +469,16 @@ def _same_function_arguments(func_args_dic, func_args_dic_cache):
                 else:
                     msg = f"cache was created using different function argument: {key}, do not use cached data"
                     logger.info(msg)
+                logger.debug(f"{key}: {item} != {func_args_dic_cache[key]}")
                 return False
         elif isinstance(item, np.ndarray):
             if not np.allclose(item, func_args_dic_cache[key]):
                 msg = f"cache was created using different numpy array for: {key}, do not use cached data"
                 logger.info(msg)
+                logger.debug(
+                    f"array '{key}' max difference with stored copy is "
+                    f"{np.max(np.abs(item - func_args_dic_cache[key]))}"
+                )
                 return False
         elif isinstance(item, (pd.DataFrame, pd.Series, xr.DataArray)):
             if not item.equals(func_args_dic_cache[key]):

nlmod/gwf/surface_water.py

@@ -869,6 +869,8 @@ def add_min_ahn_to_gdf(
         The default is 'ahn_min'.
     statistic : string, optional
         The statistic to calculate at each surface water feature. The default is 'min'.
+    progressbar : bool, optional
+        Show a progressbar when True. The default is False.
 
     Returns
     -------

nlmod/sim/sim.py

@@ -170,7 +170,7 @@ def sim(ds, exe_name=None, version_tag=None, **kwargs):
         sim_name=ds.model_name,
         exe_name=exe_name,
         version=ds.mfversion,
-        sim_ws=ds.model_ws,
+        sim_ws=kwargs.pop("sim_ws", ds.model_ws),
         **kwargs,
     )
 

nlmod/util.py

@@ -878,7 +878,7 @@ def format(self, record) -> str:
         return super().format(record)
 
 
-def get_color_logger(level="INFO"):
+def get_color_logger(level="INFO", logger_name=None):
     """Get a logger with colored output.
 
     Parameters
@@ -911,7 +911,7 @@ def get_color_logger(level="INFO"):
     handler = logging.StreamHandler(sys.stdout)
     handler.setFormatter(formatter)
 
-    logger = logging.getLogger()
+    logger = logging.getLogger(logger_name)
     logger.handlers[:] = []
     logger.addHandler(handler)
     logger.setLevel(getattr(logging, level))
@@ -1137,7 +1137,13 @@ def gdf_intersection_join(
         if np.any(measure.sum() > min_total_overlap * measure_org):
             # take the largest
             ind = measure.idxmax()
-            gdf_to.loc[index, columns] = gdf_from.loc[ind, columns]
+            idf_from = gdf_from.loc[ind, columns]
+            if idf_from.index.size > 1:
+                logger.warning(
+                    f"Warning, multiple entries found for '{ind}'. Using the first one."
+                )
+                idf_from = idf_from.iloc[0]
+            gdf_to.loc[index, columns] = idf_from
             if add_index_from_column:
                 gdf_to.loc[index, add_index_from_column] = ind
     return gdf_to
@@ -1152,8 +1158,9 @@ def zonal_statistics(
     all_touched=True,
     statistics="mean",
     add_to_gdf=True,
+    progressbar=False,
 ):
-    """Calculate raster statistics in the features of a GeoDataFrame
+    """Calculate raster statistics in the features of a GeoDataFrame.
 
     Parameters
     ----------
@@ -1186,7 +1193,8 @@ def zonal_statistics(
     add_to_gdf : bool, optional
         Add the result to the orignal GeoDataFrame if True. Otherwise return a
         GeoDataFrame with only the statistics. The default is True.
-
+    progressbar : bool, optional
+        show progressbar when using rasterstats. The default is False.
 
     Returns
     -------
@@ -1259,6 +1267,7 @@ def zonal_statistics(
                 all_touched=all_touched,
                 affine=da.rio.transform(),
                 nodata=da.rio.nodata,
+                progress=progressbar,
             )
         else:
             # we assume da is a filename
@@ -1267,6 +1276,7 @@ def zonal_statistics(
                 da,
                 stats=stat,
                 all_touched=all_touched,
+                progress=progressbar,
             )
         for stat, column in zip(statistics, columns):
             geometry[column] = [x[stat] for x in stats]