Merge branch '309-reduce-warnings' into 'develop'

Resolve "Reduce warnings" Closes #309 See merge request iek-3/shared-code/fine!323
FZJ-IEK3-VSA · Feb 8, 2024 · 9ba5d4b · 9ba5d4b
2 parents f1d98fe + 087ac0a
commit 9ba5d4b
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Showing 7 changed files with 31 additions and 29 deletions.
diff --git a/fine/IOManagement/standardIO.py b/fine/IOManagement/standardIO.py
@@ -809,7 +809,7 @@ def plotLocations(
     locationsShapeFileName,
     indexColumn,
     plotLocNames=False,
-    crs="epsg:3035",
+    crs="EPSG:3035",
     faceColor="none",
     edgeColor="black",
     fig=None,
@@ -840,7 +840,7 @@ def plotLocations(
     :type plotLocNames: boolean
 
     :param crs: coordinate reference system
-        |br| * the default value is 'epsg:3035'
+        |br| * the default value is 'EPSG:3035'
     :type crs: string
 
     :param faceColor: face color of the plot
@@ -884,7 +884,7 @@ def plotLocations(
     :type dpi: scalar > 0
     """
 
-    gdf = gpd.read_file(locationsShapeFileName).to_crs({"init": crs})
+    gdf = gpd.read_file(locationsShapeFileName).to_crs(crs)
 
     if ax is None:
         fig, ax = plt.subplots(1, 1, figsize=figsize, **kwargs)
@@ -919,7 +919,7 @@ def plotTransmission(
     loc0,
     loc1,
     ip=0,
-    crs="epsg:3035",
+    crs="EPSG:3035",
     variableName="capacityVariablesOptimum",
     color="k",
     loc=7,
@@ -961,7 +961,7 @@ def plotTransmission(
     :type ip: int
 
     :param crs: coordinate reference system
-        |br| * the default value is 'epsg:3035'
+        |br| * the default value is 'EPSG:3035'
     :type crs: string
 
     :param variableName: parameter for plotting installed capacity ('_capacityVariablesOptimum') or operation
@@ -1024,7 +1024,7 @@ def plotTransmission(
     if capMax == 0:
         return fig, ax
     cap = cap / capMax
-    gdf = gpd.read_file(transmissionShapeFileName).to_crs({"init": crs})
+    gdf = gpd.read_file(transmissionShapeFileName).to_crs(crs)
 
     if ax is None:
         fig, ax = plt.subplots(1, 1, figsize=figsize, **kwargs)
@@ -1082,7 +1082,7 @@ def plotLocationalColorMap(
     ip=0,
     perArea=True,
     areaFactor=1e3,
-    crs="epsg:3035",
+    crs="EPSG:3035",
     variableName="capacityVariablesOptimum",
     doSum=False,
     cmap="viridis",
@@ -1128,7 +1128,7 @@ def plotLocationalColorMap(
     :type areaFactor: scalar > 0
 
     :param crs: coordinate reference system
-        |br| * the default value is 'epsg:3035'
+        |br| * the default value is 'EPSG:3035'
     :type crs: string
 
     :param variableName: parameter for plotting installed capacity ('_capacityVariablesOptimum') or operation
@@ -1184,7 +1184,7 @@ def plotLocationalColorMap(
 
     if doSum:
         data = data.sum(axis=1)
-    gdf = gpd.read_file(locationsShapeFileName).to_crs({"init": crs})
+    gdf = gpd.read_file(locationsShapeFileName).to_crs(crs)
 
     # Make sure the data and gdf indices match
     ## 1. Sort the indices to obtain same order

diff --git a/fine/aggregations/spatialAggregation/aggregation.py b/fine/aggregations/spatialAggregation/aggregation.py
@@ -6,12 +6,11 @@
 import logging
 import warnings
 from copy import deepcopy
+
 import numpy as np
-import xarray as xr
-from shapely.ops import cascaded_union
-from shapely.geometry.multipolygon import MultiPolygon
-from shapely.geometry.polygon import Polygon
 import pandas as pd
+import xarray as xr
+from shapely.ops import unary_union
 
 logger_representation = logging.getLogger("spatial_representation")
 
@@ -46,7 +45,7 @@ def aggregate_geometries(xr_data_array_in, sub_to_sup_region_id_dict):
     for sub_region_id_list in sub_to_sup_region_id_dict.values():
         temp_shape_list = list(xr_data_array_in.sel(space=sub_region_id_list).values)
 
-        shape_union = cascaded_union(temp_shape_list)
+        shape_union = unary_union(temp_shape_list)
 
         shape_list.append(shape_union)
 

diff --git a/fine/aggregations/spatialAggregation/managerUtils.py b/fine/aggregations/spatialAggregation/managerUtils.py
@@ -45,7 +45,7 @@ def create_gdf(df, geometries, crs=3035, file_path=None, files_name="xr_regions"
     :rtype: gpd.GeoDataFrame
     """
 
-    gdf = gpd.GeoDataFrame(df, geometry=geometries, crs=f"epsg:{crs}")
+    gdf = gpd.GeoDataFrame(df, geometry=geometries, crs=f"EPSG:{crs}")
 
     if file_path is not None:
         gdf.reset_index(drop=True, inplace=True)

diff --git a/fine/aggregations/technologyAggregation/techAggregationUtils.py b/fine/aggregations/technologyAggregation/techAggregationUtils.py
@@ -148,7 +148,7 @@ def rasterize_xr_ds(
         )
 
     # STEP 2. Match the CRS of shapefile to that of the dataset
-    shp_file = shp_file.to_crs({"init": gridded_RE_ds.attrs[CRS_attr]})
+    shp_file = shp_file.to_crs(gridded_RE_ds.attrs[CRS_attr])
 
     # STEP 3. rasterize each geometry and add it to new data_var "rasters"
 

diff --git a/test/aggregations/conftest.py b/test/aggregations/conftest.py
@@ -406,7 +406,7 @@ def gridded_RE_data(scope="session"):
 
     test_xr_ds = xr.Dataset({"capacity": capacity_xr_da, "capfac": capfac_xr_da})
 
-    test_xr_ds.attrs["SRS"] = "epsg:3035"
+    test_xr_ds.attrs["SRS"] = "EPSG:3035"
 
     return test_xr_ds
 
@@ -458,6 +458,6 @@ def sample_shapefile(scope="session"):
 
     df = pd.DataFrame({"region_ids": ["reg_01", "reg_02"]})
 
-    gdf = gpd.GeoDataFrame(df, geometry=test_geometries, crs={"init": "epsg:3035"})
+    gdf = gpd.GeoDataFrame(df, geometry=test_geometries, crs="EPSG:3035")
 
     return gdf
diff --git a/test/aggregations/spatialAggregation/test_groupingUtils.py b/test/aggregations/spatialAggregation/test_groupingUtils.py
@@ -177,9 +177,20 @@ def test_get_custom_distance_matrix(
 
     # FUNCTION CALL
     n_regions = 3
-    output_dist_matrix = gprUtils.get_custom_distance_matrix(
-        test_ts_dict, test_1d_dict, test_2d_dict, n_regions, weights
-    )
+    if isinstance(weights, dict):
+        if not "variables" in weights:
+            with pytest.warns(UserWarning):
+                output_dist_matrix = gprUtils.get_custom_distance_matrix(
+                    test_ts_dict, test_1d_dict, test_2d_dict, n_regions, weights
+                )
+        else:
+            output_dist_matrix = gprUtils.get_custom_distance_matrix(
+                test_ts_dict, test_1d_dict, test_2d_dict, n_regions, weights
+            )
+    else:
+        output_dist_matrix = gprUtils.get_custom_distance_matrix(
+            test_ts_dict, test_1d_dict, test_2d_dict, n_regions, weights
+        )
 
     # ASSERTION
     assert np.isclose(expected_dist_matrix, output_dist_matrix).all()

diff --git a/test/conftest.py b/test/conftest.py
@@ -723,7 +723,6 @@ def multi_node_test_esM_init(esM_init):
             distances=data["Pipelines, distances"],
             hasCapacityVariable=True,
             hasIsBuiltBinaryVariable=False,
-            bigM=300,
             locationalEligibility=data["Pipelines, eligibility"],
             capacityMax=data["Pipelines, eligibility"] * 15,
             sharedPotentialID="pipelines",
@@ -745,7 +744,6 @@ def multi_node_test_esM_init(esM_init):
             distances=data["Pipelines, distances"],
             hasCapacityVariable=True,
             hasIsBuiltBinaryVariable=False,
-            bigM=300,
             locationalEligibility=data["Pipelines, eligibility"],
             capacityMax=data["Pipelines, eligibility"] * 15,
             sharedPotentialID="pipelines",
@@ -1262,7 +1260,6 @@ def multi_node_test_esM_optimized(esM_init):
             distances=data["Pipelines, distances"],
             hasCapacityVariable=True,
             hasIsBuiltBinaryVariable=False,
-            bigM=300,
             locationalEligibility=data["Pipelines, eligibility"],
             capacityMax=data["Pipelines, eligibility"] * 15,
             sharedPotentialID="pipelines",
@@ -1284,7 +1281,6 @@ def multi_node_test_esM_optimized(esM_init):
             distances=data["Pipelines, distances"],
             hasCapacityVariable=True,
             hasIsBuiltBinaryVariable=False,
-            bigM=300,
             locationalEligibility=data["Pipelines, eligibility"],
             capacityMax=data["Pipelines, eligibility"] * 15,
             sharedPotentialID="pipelines",
@@ -1757,7 +1753,6 @@ def multi_node_test_esM_init(scope="session"):
             distances=data["Pipelines, distances"],
             hasCapacityVariable=True,
             hasIsBuiltBinaryVariable=False,
-            bigM=300,
             locationalEligibility=data["Pipelines, eligibility"],
             capacityMax=data["Pipelines, eligibility"] * 15,
             sharedPotentialID="pipelines",
@@ -1780,7 +1775,6 @@ def multi_node_test_esM_init(scope="session"):
             distances=data["Pipelines, distances"],
             hasCapacityVariable=True,
             hasIsBuiltBinaryVariable=False,
-            bigM=300,
             locationalEligibility=data["Pipelines, eligibility"],
             capacityMax=data["Pipelines, eligibility"] * 15,
             sharedPotentialID="pipelines",
@@ -2228,7 +2222,6 @@ def multi_node_test_esM_optimized(scope="session"):
             distances=data["Pipelines, distances"],
             hasCapacityVariable=True,
             hasIsBuiltBinaryVariable=False,
-            bigM=300,
             locationalEligibility=data["Pipelines, eligibility"],
             capacityMax=data["Pipelines, eligibility"] * 15,
             sharedPotentialID="pipelines",
@@ -2250,7 +2243,6 @@ def multi_node_test_esM_optimized(scope="session"):
             distances=data["Pipelines, distances"],
             hasCapacityVariable=True,
             hasIsBuiltBinaryVariable=False,
-            bigM=300,
             locationalEligibility=data["Pipelines, eligibility"],
             capacityMax=data["Pipelines, eligibility"] * 15,
             sharedPotentialID="pipelines",