Merge remote-tracking branch 'origin/develop' into feature/check_meas_tuto

Author: Chahan Kropf

.github/CODEOWNERS

@@ -0,0 +1,7 @@
+# This is a comment.
+# Each line is a file pattern followed by one or more owners.
+
+# These owners will be the default owners for everything in
+# the repo. Unless a later match takes precedence, they will
+# be requested for review when someone opens a pull request.
+*       @emanuel-schmid @chahank @peanutfun

.github/workflows/ci.yml

@@ -22,7 +22,7 @@ jobs:
       # Do not abort other tests if only a single one fails
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.11"]
+        python-version: ["3.10", "3.11", "3.12"]
 
     steps:
       -

.github/workflows/pull-request.yml

@@ -16,7 +16,7 @@ jobs:
           ref: ${{ github.event.pull_request.head.sha }}
       -
         name: Checkout target commit
-        run: git -c protocol.version=2 fetch --no-tags --prune --no-recurse-submodules --depth=1 origin ${{ github.event.pull_request.base.ref }}
+        run: git -c protocol.version=2 fetch --no-tags --prune --no-recurse-submodules --depth=50 origin ${{ github.event.pull_request.base.ref }}
       -
         name: Set up Python 3.11
         uses: actions/setup-python@v5

.gitignore

@@ -183,3 +183,5 @@ results/
 !.pylintrc
 !.readthedocs.yml
 !.github
+climada_petals/
+climada_python/

AUTHORS.md

@@ -1,4 +1,3 @@
-(authors)=
 # CLIMADA List of Authors
 
 * Gabriela Aznar-Siguan

CHANGELOG.md

@@ -10,15 +10,33 @@ Code freeze date: YYYY-MM-DD
 
 ### Dependency Changes
 
+Removed:
+
+- `pandas-datareader`
+
 ### Added
+- Added optional parameter to `geo_im_from_array`, `plot_from_gdf`, `plot_rp_imp`, `plot_rp_intensity`,
+`plot_intensity`, `plot_fraction`, `_event_plot` to mask plotting when regions are too far from data points [#1047](https://github.com/CLIMADA-project/climada_python/pull/1047). To recreate previous plots (no masking), the parameter can be set to None.
+- Added instructions to install Climada petals on Euler cluster in `doc.guide.Guide_Euler.ipynb` [#1029](https://github.com/CLIMADA-project/climada_python/pull/1029)
+
+- `ImpactFunc` and `ImpactFuncSet` now support equality comparisons via `==` [#1027](https://github.com/CLIMADA-project/climada_python/pull/1027)
 
 ### Changed
+
 - `Hazard.local_exceedance_intensity`, `Hazard.local_return_period` and `Impact.local_exceedance_impact`, `Impact.local_return_period`, using the `climada.util.interpolation` module: New default (no binning), binning on decimals, and faster implementation [#1012](https://github.com/CLIMADA-project/climada_python/pull/1012)
+- 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)
+
 ### Fixed
 
+- NaN plotting issues in `geo_im_from_array`[#1038](https://github.com/CLIMADA-project/climada_python/pull/1038)
+- Broken ECMWF links in pydoc of `climada.hazard.storm_europe` relocated. [#944](https://github.com/CLIMADA-project/climada_python/pull/944)
+
 ### Deprecated
 
 ### Removed
+
 - `climada.util.interpolation.round_to_sig_digits` [#1012](https://github.com/CLIMADA-project/climada_python/pull/1012)
 
 ## 6.0.1
@@ -42,27 +60,27 @@ Added:
 
 Updated:
 
-- `cartopy` >=0.23 → >=0.24
-- `cfgrib` >=0.9.9,<0.9.10 &rarr; >=0.9
-- `dask` >=2024.2,<2024.3 &rarr; >=2025.2
-- `eccodes` >=2.27,<2.28 &rarr; >=2.40
-- `gdal` >=3.6 &rarr; >=3.10
-- `geopandas` >=0.14 &rarr; >=0.14,<1.0
-- `h5py` >=3.8 &rarr; >=3.12
-- `haversine` >=2.8 &rarr; >=2.9
-- `matplotlib-base` >=3.9 &rarr; >=3.10
-- `netcdf4` >=1.6 &rarr; >=1.7
-- `numba` >=0.60 &rarr; >=0.61
-- `pillow` =9.4 &rarr; =11.1
-- `pyproj` >=3.5 &rarr; >=3.7
-- `pytables` >=3.7 &rarr; >=3.10
-- `python` =3.9 &rarr; =3.11
-- `rasterio` >=1.3 &rarr; >=1.4
-- `scikit-learn` >=1.5 &rarr; >=1.6
-- `scipy` >=1.13 &rarr; >=1.14,<1.15
-- `tqdm` >=4.66 &rarr; >=4.67
-- `xarray` >=2024.6 &rarr; >=2025.1
-- `xlsxwriter` >=3.1 &rarr; >=3.2
+- `cartopy` >=0.23 → >=0.24
+- `cfgrib` >=0.9.9,<0.9.10 → >=0.9
+- `dask` >=2024.2,<2024.3 → >=2025.2
+- `eccodes` >=2.27,<2.28 → >=2.40
+- `gdal` >=3.6 → >=3.10
+- `geopandas` >=0.14 → >=0.14,<1.0
+- `h5py` >=3.8 → >=3.12
+- `haversine` >=2.8 → >=2.9
+- `matplotlib-base` >=3.9 → >=3.10
+- `netcdf4` >=1.6 → >=1.7
+- `numba` >=0.60 → >=0.61
+- `pillow` =9.4 → =11.1
+- `pyproj` >=3.5 → >=3.7
+- `pytables` >=3.7 → >=3.10
+- `python` =3.9 → =3.11
+- `rasterio` >=1.3 → >=1.4
+- `scikit-learn` >=1.5 → >=1.6
+- `scipy` >=1.13 → >=1.14,<1.15
+- `tqdm` >=4.66 → >=4.67
+- `xarray` >=2024.6 → >=2025.1
+- `xlsxwriter` >=3.1 → >=3.2
 
 Removed:
 
@@ -73,7 +91,7 @@ Removed:
 - `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)
-- `doc.tutorial.climada_entity_Exposures_osm.ipynb` tutorial explaining how to use `osm-flex`with CLIMADA
+- `doc.tutorial.climada_entity_Exposures_osm.ipynb` tutorial explaining how to use `osm-flex` with CLIMADA
 - `climada.util.coordinates.bounding_box_global` function [#980](https://github.com/CLIMADA-project/climada_python/pull/980)
 - `climada.util.coordinates.bounding_box_from_countries` function [#980](https://github.com/CLIMADA-project/climada_python/pull/980)
 - `climada.util.coordinates.bounding_box_from_cardinal_bounds` function [#980](https://github.com/CLIMADA-project/climada_python/pull/980)
@@ -105,8 +123,8 @@ Removed:
 - the _geometry_ column of the inherent `GeoDataFrame` is set up at initialization
 - latitude and longitude column are no longer present there (the according arrays can be retrieved as properties of the Exposures object: `exp.latitude` instead of `exp.gdf.latitude.values`).
 - `Exposures.gdf` has been renamed to `Exposures.data` (it still works though, as it is a property now pointing to the latter)
-- the `check` method does not add a default "IMPF_" column to the GeoDataFrame anymore
-- Updated IBTrACS version from v4.0 to v4.1 ([#976](https://github.com/CLIMADA-project/climada_python/pull/976)
+- the `check` method does not add a default `'IMPF_'` column to the GeoDataFrame anymore
+- Updated IBTrACS version from v4.0 to v4.1 [#976](https://github.com/CLIMADA-project/climada_python/pull/976)
 - Fix xarray future warning in TCTracks for .dims to .sizes
 - Fix hazard.concatenate type test for pathos pools
 
@@ -140,20 +158,20 @@ Added:
 
 Updated:
 
-- `bottleneck` >=1.3 &rarr; >=1.4
-- `cartopy` >=0.22 &rarr; >=0.23
-- `contextily` >=1.5 &rarr; >=1.6
-- `dask` >=2024.1,<2024.3 &rarr; >=2024.2,<2024.3
-- `matplotlib-base` >=3.8 &rarr; >=3.9
-- `numba` >=0.59 &rarr; >=0.60
-- `numexpr` >=2.9 &rarr; >=2.10
-- `pint` >=0.23 &rarr; >=0.24
-- `pycountry` >=22.3 &rarr; >=24.6
-- `requests` >=2.31 &rarr; >=2.32
-- `salib` >=1.4 &rarr; >=1.5
-- `scikit-learn` >=1.4 &rarr; >=1.5
-- `scipy` >=1.12 &rarr; >=1.13
-- `xarray` >=2024.2 &rarr; >=2024.6
+- `bottleneck` >=1.3 → >=1.4
+- `cartopy` >=0.22 → >=0.23
+- `contextily` >=1.5 → >=1.6
+- `dask` >=2024.1,<2024.3 → >=2024.2,<2024.3
+- `matplotlib-base` >=3.8 → >=3.9
+- `numba` >=0.59 → >=0.60
+- `numexpr` >=2.9 → >=2.10
+- `pint` >=0.23 → >=0.24
+- `pycountry` >=22.3 → >=24.6
+- `requests` >=2.31 → >=2.32
+- `salib` >=1.4 → >=1.5
+- `scikit-learn` >=1.4 → >=1.5
+- `scipy` >=1.12 → >=1.13
+- `xarray` >=2024.2 → >=2024.6
 
 ### Added
 
@@ -188,6 +206,7 @@ CLIMADA tutorials. [#872](https://github.com/CLIMADA-project/climada_python/pull
 - `Impact.from_hdf5` now calls `str` on `event_name` data that is not strings, and issue a warning then [#894](https://github.com/CLIMADA-project/climada_python/pull/894)
 - `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)
 
 ### Fixed
 
@@ -258,17 +277,17 @@ Added:
 
 Updated:
 
-- `contextily` >=1.3 &rarr; >=1.5
-- `dask` >=2023 &rarr; >=2024
-- `numba` >=0.57 &rarr; >=0.59
-- `pandas` >=2.1 &rarr; >=2.1,<2.2
-- `pint` >=0.22 &rarr; >=0.23
-- `scikit-learn` >=1.3 &rarr; >=1.4
-- `scipy` >=1.11 &rarr; >=1.12
-- `sparse` >=0.14 &rarr; >=0.15
-- `xarray` >=2023.8 &rarr; >=2024.1
-- `overpy` =0.6 &rarr; =0.7
-- `peewee` =3.16.3 &rarr; =3.17.1
+- `contextily` >=1.3 → >=1.5
+- `dask` >=2023 → >=2024
+- `numba` >=0.57 → >=0.59
+- `pandas` >=2.1 → >=2.1,<2.2
+- `pint` >=0.22 → >=0.23
+- `scikit-learn` >=1.3 → >=1.4
+- `scipy` >=1.11 → >=1.12
+- `sparse` >=0.14 → >=0.15
+- `xarray` >=2023.8 → >=2024.1
+- `overpy` =0.6 → =0.7
+- `peewee` =3.16.3 → =3.17.1
 
 Removed:
 
@@ -311,13 +330,13 @@ Release date: 2023-09-27
 
 Added:
 
-- `matplotlib-base` None &rarr; >=3.8
+- `matplotlib-base` None → >=3.8
 
 Changed:
 
-- `geopandas` >=0.13 &rarr; >=0.14
-- `pandas` >=1.5,<2.0 &rarr; >=2.1
-- `salib` >=1.3.0 &rarr; >=1.4.7
+- `geopandas` >=0.13 → >=0.14
+- `pandas` >=1.5,<2.0 → >=2.1
+- `salib` >=1.3.0 → >=1.4.7
 
 Removed:
 
@@ -346,37 +365,37 @@ Added:
 
 Changed:
 
-- `cartopy` >=0.20.0,<0.20.3 &rarr; >=0.21
-- `cfgrib` >=0.9.7,<0.9.10 &rarr; =0.9.9
-- `contextily` >=1.0 &rarr; >=1.3
-- `dask` >=2.25 &rarr; >=2023
-- `eccodes` [auto] &rarr; =2.27
-- `gdal` !=3.4.1 &rarr; >=3.6
-- `geopandas` >=0.8 &rarr; >=0.13
-- `h5py` >=2.10 &rarr; >=3.8
-- `haversine` >=2.3 &rarr; >=2.8
-- `matplotlib` >=3.2,< 3.6 &rarr; >=3.7
-- `netcdf4` >=1.5 &rarr; >=1.6
-- `numba` >=0.51,!=0.55.0 &rarr; >=0.57
-- `openpyxl` >=3.0 &rarr; >=3.1
-- `pandas-datareader` >=0.9 &rarr; >=0.10
-- `pathos` >=0.2 &rarr; >=0.3
-- `pint` >=0.15 &rarr; >=0.22
-- `proj` !=9.0.0 &rarr; >=9.1
-- `pycountry` >=20.7 &rarr; >=22.3
-- `pytables` >=3.6 &rarr; >=3.7
-- `rasterio` >=1.2.7,<1.3 &rarr; >=1.3
-- `requests` >=2.24 &rarr; >=2.31
-- `salib` >=1.3.0 &rarr; >=1.4
-- `scikit-learn` >=1.0 &rarr; >=1.2
-- `scipy` >=1.6 &rarr; >=1.10
-- `sparse` >=0.13 &rarr; >=0.14
-- `statsmodels` >=0.11 &rarr; >=0.14
-- `tabulate` >=0.8 &rarr; >=0.9
-- `tqdm` >=4.48 &rarr; >=4.65
-- `xarray` >=0.13 &rarr; >=2023.5
-- `xlrd` >=1.2 &rarr; >=2.0
-- `xlsxwriter` >=1.3 &rarr; >=3.1
+- `cartopy` >=0.20.0,<0.20.3 → >=0.21
+- `cfgrib` >=0.9.7,<0.9.10 → =0.9.9
+- `contextily` >=1.0 → >=1.3
+- `dask` >=2.25 → >=2023
+- `eccodes` [auto] → =2.27
+- `gdal` !=3.4.1 → >=3.6
+- `geopandas` >=0.8 → >=0.13
+- `h5py` >=2.10 → >=3.8
+- `haversine` >=2.3 → >=2.8
+- `matplotlib` >=3.2,< 3.6 → >=3.7
+- `netcdf4` >=1.5 → >=1.6
+- `numba` >=0.51,!=0.55.0 → >=0.57
+- `openpyxl` >=3.0 → >=3.1
+- `pandas-datareader` >=0.9 → >=0.10
+- `pathos` >=0.2 → >=0.3
+- `pint` >=0.15 → >=0.22
+- `proj` !=9.0.0 → >=9.1
+- `pycountry` >=20.7 → >=22.3
+- `pytables` >=3.6 → >=3.7
+- `rasterio` >=1.2.7,<1.3 → >=1.3
+- `requests` >=2.24 → >=2.31
+- `salib` >=1.3.0 → >=1.4
+- `scikit-learn` >=1.0 → >=1.2
+- `scipy` >=1.6 → >=1.10
+- `sparse` >=0.13 → >=0.14
+- `statsmodels` >=0.11 → >=0.14
+- `tabulate` >=0.8 → >=0.9
+- `tqdm` >=4.48 → >=4.65
+- `xarray` >=0.13 → >=2023.5
+- `xlrd` >=1.2 → >=2.0
+- `xlsxwriter` >=1.3 → >=3.1
 
 Removed:
 

README.md

@@ -16,9 +16,9 @@ CLIMADA is divided into two parts (two repositories):
 1. the core [climada_python](https://github.com/CLIMADA-project/climada_python) contains all the modules necessary for the probabilistic impact, the averted damage, uncertainty and forecast calculations. Data for hazard, exposures and impact functions can be obtained from the [data API](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_util_api_client.ipynb). [Litpop](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_entity_LitPop.ipynb) is included as demo Exposures module, and [Tropical cyclones](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_hazard_TropCyclone.ipynb) is included as a demo Hazard module.
 2. the petals [climada_petals](https://github.com/CLIMADA-project/climada_petals) contains all the modules for generating data (e.g., TC_Surge, WildFire, OpenStreeMap, ...). Most development is done here. The petals builds-upon the core and does not work as a stand-alone.
 
-It is recommend for new users to begin with the core (1) and the [tutorials](https://github.com/CLIMADA-project/climada_python/tree/main/doc/tutorial) therein.
+For new users, we recommend to begin with the core (1) and the [tutorials](https://github.com/CLIMADA-project/climada_python/tree/main/doc/tutorial) therein.
 
-This is the Python (3.9+) version of CLIMADA - please see [here](https://github.com/davidnbresch/climada) for backward compatibility with the MATLAB version.
+This is the Python version of CLIMADA - please see [here](https://github.com/davidnbresch/climada) for backward compatibility with the MATLAB version.
 
 ## Getting started
 

climada/engine/cost_benefit.py

@@ -1079,9 +1079,7 @@ def _calc_impact_measures(
         # compute impact for each measure
         for measure in meas_set.get_measure(hazard.haz_type):
             LOGGER.debug("%s impact of measure %s.", when, measure.name)
-            imp_tmp, risk_transf = measure.calc_impact(
-                exposures, imp_fun_set, hazard, assign_centroids=False
-            )
+            imp_tmp, risk_transf = measure.calc_impact(exposures, imp_fun_set, hazard)
             impact_meas[measure.name] = dict()
             impact_meas[measure.name]["cost"] = (
                 measure.cost,

climada/engine/impact.py

@@ -1178,6 +1178,7 @@ def plot_rp_imp(
         return_periods=(25, 50, 100, 250),
         log10_scale=True,
         axis=None,
+        mask_distance=0.01,
         kwargs_local_exceedance_impact=None,
         **kwargs,
     ):
@@ -1194,6 +1195,11 @@ def plot_rp_imp(
             plot impact as log10(impact). Default: True
         smooth : bool, optional
             smooth plot to plot.RESOLUTIONxplot.RESOLUTION. Default: True
+        mask_distance: float, optional
+            Only regions are plotted that are closer to any of the data points than this distance,
+            relative to overall plot size. For instance, to only plot values
+            at the centroids, use mask_distance=0.01. If None, the plot is not masked.
+            Default is 0.01.
         kwargs_local_exceedance_impact: dict
             Dictionary of keyword arguments for the method impact.local_exceedance_impact.
         kwargs : dict, optional
@@ -1242,7 +1248,12 @@ def plot_rp_imp(
             )
 
         axis = u_plot.plot_from_gdf(
-            impacts_stats, title, column_labels, axis=axis, **kwargs
+            impacts_stats,
+            title,
+            column_labels,
+            axis=axis,
+            mask_distance=mask_distance,
+            **kwargs,
         )
         return axis, impacts_stats_vals