Merge branch 'develop' of github.com:CLIMADA-project/climada_python into develop

Author: emanuel-schmid

.github/workflows/ci.yml

@@ -47,7 +47,7 @@ jobs:
       -
         name: Install CLIMADA
         run: |
-          python -m pip install ".[test]"
+          python -m pip install "./[dev]"
       -
         name: Run Unit Tests
         run: |

.zenodo.json

@@ -119,6 +119,9 @@
     },
     {
       "name": "Valentin Gebhart"
+    },
+    {
+      "name": "Dahyann Araya"
     }
   ]
 }

AUTHORS.md

@@ -36,3 +36,4 @@
 * Luca Severino
 * Samuel Juhel
 * Valentin Gebhart
+* Dahyann Araya

CHANGELOG.md

@@ -39,6 +39,7 @@ Removed:
 - World Bank indicator data is now downloaded directly from their API via the function `download_world_bank_indicator`, instead of relying on the `pandas-datareader` package [#1033](https://github.com/CLIMADA-project/climada_python/pull/1033)
 - `Exposures.write_hdf5` pickles geometry data in WKB format, which is faster and more sustainable. [#1051](https://github.com/CLIMADA-project/climada_python/pull/1051)
 - The online documentation has been completely overhauled, now uses PyData theme: [#977](https://github.com/CLIMADA-project/climada_python/pull/977)
+- Add `climada.hazard.xarray` module with helper structures for reading Hazard objects from `xarray` data [#1063](https://github.com/CLIMADA-project/climada_python/pull/1063)
 
 ### Fixed
 
@@ -47,6 +48,8 @@ Removed:
 
 ### Deprecated
 
+- `Hazard.from_xarray_raster_file`. Use `Hazard.from_xarray_raster` and pass the file path as `data` argument [#1063](https://github.com/CLIMADA-project/climada_python/pull/1063)
+
 ### Removed
 
 - `climada.util.interpolation.round_to_sig_digits` [#1012](https://github.com/CLIMADA-project/climada_python/pull/1012)
@@ -102,6 +105,7 @@ Removed:
 
 ### Added
 
+- `climada.entity.impact_funcs.trop_cyclone.ImpfSetTropCyclone.get_impf_id_regions_per_countries` function [#1034](https://github.com/CLIMADA-project/climada_python/pull/1034)
 - `climada.hazard.tc_tracks.TCTracks.subset_years` function [#1023](https://github.com/CLIMADA-project/climada_python/pull/1023)
 - `climada.hazard.tc_tracks.TCTracks.from_FAST` function, add Australia basin (AU) [#993](https://github.com/CLIMADA-project/climada_python/pull/993)
 - Add `osm-flex` package to CLIMADA core [#981](https://github.com/CLIMADA-project/climada_python/pull/981)
@@ -221,6 +225,7 @@ CLIMADA tutorials. [#872](https://github.com/CLIMADA-project/climada_python/pull
 - `Impact.write_hdf5` now throws an error if `event_name` is does not contain strings exclusively [#894](https://github.com/CLIMADA-project/climada_python/pull/894)
 - Split `climada.hazard.trop_cyclone` module into smaller submodules without affecting module usage [#911](https://github.com/CLIMADA-project/climada_python/pull/911)
 - `yearly_steps` parameter of `TropCyclone.apply_climate_scenario_knu` has been made explicit [#991](https://github.com/CLIMADA-project/climada_python/pull/991)
+- `Hazard.write_hdf5` writes centroids as x,y columns (or as wkb in case of polygons) at a compression level of 9, not as pickled `Shapely` objects anymore, which reduces the size of the files significantly.
 
 ### Fixed
 

climada/engine/unsequa/calc_cost_benefit.py

@@ -398,7 +398,7 @@ def _map_costben_calc(
             ent_future=ent_fut,
             save_imp=False,
             assign_centroids=False,
-            **cost_benefit_kwargs
+            **cost_benefit_kwargs,
         )
         # Extract from climada.impact the chosen metrics
         uncertainty_values.append(

climada/entity/exposures/litpop/litpop.py

@@ -19,6 +19,7 @@
 """
 
 import logging
+import numbers
 from pathlib import Path
 
 import geopandas
@@ -820,12 +821,12 @@ def _from_country(
             total_value = _get_total_value_per_country(iso3a, fin_mode, reference_year)
 
         # disaggregate total value proportional to LitPop values:
-        if isinstance(total_value, (float, int)):
+        if isinstance(total_value, numbers.Number):
             litpop_gdf["value"] = (
                 np.divide(litpop_gdf["value"], litpop_gdf["value"].sum()) * total_value
             )
         elif total_value is not None:
-            raise TypeError("total_value must be int or float.")
+            raise TypeError(f"total_value ({total_value}) must be a number.")
 
         exp = LitPop()
         exp.set_gdf(litpop_gdf)

climada/entity/impact_funcs/test/test_tc.py

@@ -115,7 +115,7 @@ def test_default_values_pass(self):
         self.assertEqual(impfs.size(), 10)
         self.assertEqual(impfs.get_ids()["TC"], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
         self.assertEqual(impf_wp4.intensity_unit, "m/s")
-        self.assertEqual(impf_wp4.name, "North West Pacific (WP4)")
+        self.assertEqual(impf_wp4.name, "North West Pacific")
         self.assertAlmostEqual(v_halfs["WP2"], 188.4, places=7)
         self.assertAlmostEqual(v_halfs["ROW"], 110.1, places=7)
         self.assertListEqual(list(impf_wp4.intensity), list(np.arange(0, 121, 5)))
@@ -135,7 +135,7 @@ def test_RMSF_pass(self):
         self.assertEqual(impfs.size(), 10)
         self.assertEqual(impfs.get_ids()["TC"], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
         self.assertEqual(impf_na1.intensity_unit, "m/s")
-        self.assertEqual(impf_na1.name, "Caribbean and Mexico (NA1)")
+        self.assertEqual(impf_na1.name, "Caribbean and Mexico")
         self.assertAlmostEqual(v_halfs["NA1"], 59.6, places=7)
         self.assertAlmostEqual(v_halfs["ROW"], 73.4, places=7)
         self.assertListEqual(list(impf_na1.intensity), list(np.arange(0, 121, 5)))
@@ -153,7 +153,7 @@ def test_quantile_pass(self):
         self.assertEqual(impfs.size(), 10)
         self.assertEqual(impfs_p10.size(), 10)
         self.assertEqual(impf_si.intensity_unit, "m/s")
-        self.assertEqual(impf_si_p10.name, "South Indian (SI)")
+        self.assertEqual(impf_si_p10.name, "South Indian")
         self.assertAlmostEqual(impf_si_p10.mdd.max(), 0.99999999880, places=5)
         self.assertAlmostEqual(impf_si.calc_mdr(30), 0.01620503041, places=5)
         intensity = np.random.randint(26, impf_si.intensity.max())
@@ -168,6 +168,35 @@ def test_get_countries_per_region(self):
         self.assertListEqual(out[2], [124, 840])
         self.assertListEqual(out[3], ["CAN", "USA"])
 
+    def test_get_imf_id_regions_per_countries(self):
+        """Test get_impf_id_regions_per_countries()"""
+        ifs = ImpfSetTropCyclone()
+        impf_id_reg_id_reg_name = ifs.get_impf_id_regions_per_countries(
+            countries=["CHE"]
+        )
+
+        # the first element of impf_id_reg_id_reg_name [0] is the impact function id,
+        # the second [1] is the region id, the third [2] is the region name.
+        self.assertEqual(impf_id_reg_id_reg_name[0][0], 10)
+        self.assertEqual(impf_id_reg_id_reg_name[1][0], "ROW")
+        self.assertEqual(impf_id_reg_id_reg_name[2][0], "Rest of The World")
+        impf_id_reg_id_reg_name = ifs.get_impf_id_regions_per_countries(countries=[756])
+        self.assertEqual(impf_id_reg_id_reg_name[0][0], 10)
+        self.assertEqual(impf_id_reg_id_reg_name[1][0], "ROW")
+        self.assertEqual(impf_id_reg_id_reg_name[2][0], "Rest of The World")
+
+        impf_id_reg_id_reg_name = ifs.get_impf_id_regions_per_countries(
+            countries=["CHE", 268]
+        )
+        # CHE
+        self.assertEqual(impf_id_reg_id_reg_name[0][0], 10)
+        self.assertEqual(impf_id_reg_id_reg_name[1][0], "ROW")
+        self.assertEqual(impf_id_reg_id_reg_name[2][0], "Rest of The World")
+        # GEO (georgia, 268)
+        self.assertEqual(impf_id_reg_id_reg_name[0][1], 3)
+        self.assertEqual(impf_id_reg_id_reg_name[1][1], "NI")
+        self.assertEqual(impf_id_reg_id_reg_name[2][1], "North Indian")
+
 
 # Execute Tests
 if __name__ == "__main__":