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Copy file name to clipboardExpand all lines: CHANGELOG.md
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- Added optional parameter to `geo_im_from_array`, `plot_from_gdf`, `plot_rp_imp`, `plot_rp_intensity`,
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`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.
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- 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)
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- Added util methods to handle crs coordinates consistently: `is_geo_coords`, `check_if_geo_coords`, `get_crs_unit`, `estimate_matching_threshold`, `degree_to_km`, and `km_to_degree`[#1080](https://github.com/CLIMADA-project/climada_python/pull/1080)
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-`ImpactFunc` and `ImpactFuncSet` now support equality comparisons via `==`[#1027](https://github.com/CLIMADA-project/climada_python/pull/1027)
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### Changed
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- Changed the default mask_distance in `util.plot.geo_im_from_array` to 0.03 to avoid white gaps in gridded hazard data with comparably low resolution (>80 centroids per axis) [#1073](https://github.com/CLIMADA-project/climada_python/pull/1073)
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- Increased speed of `util.plot.add_shapes` by avoiding for loops, substantially speeding up `Hazard.plot_intensity` and other functions. [#1073](https://github.com/CLIMADA-project/climada_python/pull/1073)
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- Update `util.coordinates.match_centroids` and `util.coordinates.match_coordinates` so that they also
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accept coordinates that are not defined in degree.
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accept coordinates that are not defined in degree.[#1080](https://github.com/CLIMADA-project/climada_python/pull/1080)
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- Implement cheap test to check that input coordinates at least seem geographic for functions that require
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geographic coordinates as input (e.g. `util.coordinates.dist_to_coast`, `util.coordinates.coord_on_land`).
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geographic coordinates as input (e.g. `util.coordinates.dist_to_coast`, `util.coordinates.coord_on_land`).[#1080](https://github.com/CLIMADA-project/climada_python/pull/1080)
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-`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)
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- 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)
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-`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)
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