Merge branch 'develop'

# Conflicts:
#	climada/_version.py
#	setup.py

Author: emanuel-schmid

.gitignore

@@ -60,6 +60,7 @@ climada/hazard/test/data/tc_tracks_nc/*
 climada/hazard/test/data/tc_tracks.h5
 climada/hazard/test/data/test_centr.h5
 climada/hazard/test/data/test_haz.h5
+climada/hazard/test/data/test_unsupported.h5
 climada/test/data/1988234N13299.nc
 climada/test/data/exposure_buildings_default_47_7.h5
 climada/test/data/exposure_high_47_8.h5

README.md

@@ -26,13 +26,26 @@ Follow the [tutorial](https://climada-python.readthedocs.io/en/latest/tutorial/1
 
 Documentation is available on Read the Docs:
 
+Note that all the documentations has two versions,'latest' and 'stable', and explicit version numbers, such as 'v3.1.1', in the url path. 'latest' is created from the 'develop' branch and has the latest changes by developers, 'stable' from the latest release. For more details about documentation versions, please have a look at [here](https://readthedocs.org/projects/climada-python/versions/).
+
+CLIMADA python:
 * [online (recommended)](https://climada-python.readthedocs.io/en/latest/)
 * [PDF file](https://climada-python.readthedocs.io/_/downloads/en/stable/pdf/)
 
+CLIMADA petals:
+* [online (recommended)](https://climada-petals.readthedocs.io/en/latest/)
+* [PDF file](https://climada-petals.readthedocs.io/_/downloads/en/stable/pdf/)
+* [petals Tutorials on GitHub](https://github.com/CLIMADA-project/climada_petals/tree/main/doc/tutorial)
+
+
 ## Citing CLIMADA
 
 If you use CLIMADA please cite (in general, in particular for academic work) :
 
+The [used version](https://zenodo.org/search?page=1&size=20&q=climada)
+
+and/or the following published articles:
+
 Aznar-Siguan, G. and Bresch, D. N., 2019: CLIMADA v1: a global weather and climate risk assessment platform, Geosci. Model Dev., 12, 3085–3097, https://doi.org/10.5194/gmd-12-3085-2019
 
 Bresch, D. N. and Aznar-Siguan, G., 2021: CLIMADA v1.4.1: towards a globally consistent adaptation options appraisal tool, Geosci. Model Dev., 14, 351-363, https://doi.org/10.5194/gmd-14-351-2021

climada.conf

@@ -23,5 +23,8 @@
     "util": {
         "test_data": "{test_directory}/util/test/data"
     },
+    "data_api": {
+        "supported_exposures_types": ["litpop", "crop_production", "base"]
+    },
     "log_level": "INFO"
 }

climada/__init__.py

@@ -58,6 +58,7 @@
         HAZ_DEMO_H5,
         TC_ANDREW_FL,
         DEMO_DIR.joinpath('demo_emdat_impact_data_2020.csv'),
+        DEMO_DIR.joinpath('nl_rails.gpkg'),
     ] + WS_DEMO_NC
 }
 
@@ -68,9 +69,9 @@ def test_installation():
     """
     from unittest import TestLoader, TextTestRunner
     suite = TestLoader().discover(start_dir='climada.engine.test',
-                                           pattern='test_cost_benefit.py')
+                                  pattern='test_cost_benefit.py')
     suite.addTest(TestLoader().discover(start_dir='climada.engine.test',
-                                                 pattern='test_impact.py'))
+                                        pattern='test_impact.py'))
     TextTestRunner(verbosity=2).run(suite)
 
 

climada/_version.py

@@ -1 +1 @@
-__version__ = '3.1.3'
+__version__ = '3.2.0'

climada/conf/climada.conf

@@ -43,7 +43,7 @@
     },
     "hazard": {
         "relative_cropyield": {
-            "local_data": "{exposures.crop_production.local_data}",
+            "local_data": "{local_data.system}/ISIMIP_crop",
             "filename_wheat_mask": "mask_winter_and_spring_wheat_areas_phase3.nc4"
         },
         "trop_cyclone": {
@@ -65,6 +65,8 @@
         "url": "https://climada.ethz.ch/data-api/v1/",
         "chunk_size": 8192,
         "cache_db": "{local_data.system}/.downloads.db",
+        "cache_enabled": true,
+        "cache_dir": "{local_data.system}/.apicache",
         "supported_hazard_types": ["river_flood", "tropical_cyclone", "storm_europe", "relative_cropyield"],
         "supported_exposures_types": ["litpop", "crop_production"]
     }

climada/engine/calibration_opt.py

@@ -20,19 +20,19 @@
     Optimization and manual calibration
 """
 
-import numpy as np
-import pandas as pd
 import datetime as dt
 import copy
+import itertools
+import logging
+import numpy as np
+import pandas as pd
 from scipy import interpolate
 from scipy.optimize import minimize
-import itertools
 
 from climada.engine import Impact
 from climada.entity import ImpactFuncSet, ImpfTropCyclone, impact_funcs
 from climada.engine.impact_data import emdat_impact_yearlysum, emdat_impact_event
 
-import logging
 LOGGER = logging.getLogger(__name__)
 
 
@@ -111,7 +111,7 @@ def calib_instance(hazard, exposure, impact_func, df_out=pd.DataFrame(),
             raise ValueError('adding simulated impacts to reported impacts not'
                              ' yet implemented. use yearly_impact=True or run'
                              ' without init_impact_data.')
-    if not return_cost == 'False':
+    if return_cost != 'False':
         df_out = calib_cost_calc(df_out, return_cost)
     return df_out
 

climada/engine/cost_benefit.py

@@ -265,6 +265,7 @@ def combine_measures(self, in_meas_names, new_name, new_color, disc_rates,
         -------
         climada.CostBenefit
         """
+        # pylint: disable=protected-access
         new_cb = CostBenefit()
         new_cb.present_year = self.present_year
         new_cb.future_year = self.future_year

climada/engine/forecast.py

@@ -24,7 +24,6 @@
 
 import logging
 import datetime as dt
-from pathlib import Path
 import numpy as np
 import matplotlib.pyplot as plt
 from matplotlib.patches import Patch
@@ -340,8 +339,8 @@ def plot_imp_map(
             figure size for plt.subplots, width, height in inches
             The default is (9, 13)
         adapt_fontsize : bool, optional
-            If set to true, the size of the fonts will be adapted to the size of the figure. Otherwise
-            the default matplotlib font size is used. Default is True.
+            If set to true, the size of the fonts will be adapted to the size of the figure.
+            Otherwise the default matplotlib font size is used. Default is True.
 
         Returns
         -------
@@ -397,6 +396,7 @@ def _plot_imp_map(
         adapt_fontsize=True,
     ):
         # select hazard with run_datetime
+        # pylint: disable=protected-access
         if run_datetime is None:
             run_datetime = self.run_datetime[0]
         haz_ind = np.argwhere(np.isin(self.run_datetime, run_datetime))[0][0]
@@ -729,8 +729,8 @@ def plot_exceedence_prob(
             figure size for plt.subplots, width, height in inches
             The default is (9, 13)
         adapt_fontsize : bool, optional
-            If set to true, the size of the fonts will be adapted to the size of the figure. Otherwise
-            the default matplotlib font size is used. Default is True.
+            If set to true, the size of the fonts will be adapted to the size of the figure.
+            Otherwise the default matplotlib font size is used. Default is True.
 
         Returns
         -------
@@ -794,6 +794,7 @@ def _plot_exc_prob(
     ):
         """plot the probability of reaching a threshold"""
         # select hazard with run_datetime
+        # pylint: disable=protected-access
         if run_datetime is None:
             run_datetime = self.run_datetime[0]
         haz_ind = np.argwhere(np.isin(self.run_datetime, run_datetime))[0][0]
@@ -962,8 +963,8 @@ def plot_warn_map(
         close_fig : bool, optional
             Figure is not drawn if True. The default is False.
         adapt_fontsize : bool, optional
-            If set to true, the size of the fonts will be adapted to the size of the figure. Otherwise
-            the default matplotlib font size is used. Default is True.
+            If set to true, the size of the fonts will be adapted to the size of the figure.
+            Otherwise the default matplotlib font size is used. Default is True.
 
         Returns
         -------
@@ -1027,6 +1028,7 @@ def _plot_warn(
     ):
         """plotting the warning level of each warning region based on thresholds"""
         # select hazard with run_datetime
+        # pylint: disable=protected-access
         if run_datetime is None:
             run_datetime = self.run_datetime[0]
         haz_ind = np.argwhere(np.isin(self.run_datetime, run_datetime))[0][0]

climada/engine/impact.py

@@ -111,7 +111,7 @@ def calc_freq_curve(self, return_per=None):
 
         Returns
         -------
-            ImpactFreqCurve
+            climada.engine.impact.ImpactFreqCurve
         """
         ifc = ImpactFreqCurve()
         ifc.tag = self.tag
@@ -251,7 +251,7 @@ def calc_risk_transfer(self, attachment, cover):
 
         Returns
         -------
-        climada.engine.Impact
+        climada.engine.impact.Impact
         """
         new_imp = copy.deepcopy(self)
         if attachment or cover:
@@ -270,7 +270,7 @@ def calc_risk_transfer(self, attachment, cover):
 
         return new_imp, Impact()
 
-    def plot_hexbin_eai_exposure(self, mask=None, ignore_zero=True,
+    def plot_hexbin_eai_exposure(self, mask=None, ignore_zero=False,
                                  pop_name=True, buffer=0.0, extend='neither',
                                  axis=None, adapt_fontsize=True, **kwargs):
         """Plot hexbin expected annual impact of each exposure.
@@ -308,7 +308,7 @@ def plot_hexbin_eai_exposure(self, mask=None, ignore_zero=True,
         axis.set_title('Expected annual impact')
         return axis
 
-    def plot_scatter_eai_exposure(self, mask=None, ignore_zero=True,
+    def plot_scatter_eai_exposure(self, mask=None, ignore_zero=False,
                                   pop_name=True, buffer=0.0, extend='neither',
                                   axis=None, adapt_fontsize=True, **kwargs):
         """Plot scatter expected annual impact of each exposure.
@@ -331,8 +331,8 @@ def plot_scatter_eai_exposure(self, mask=None, ignore_zero=True,
         axis  : matplotlib.axes._subplots.AxesSubplot, optional
             axis to use
         adapt_fontsize : bool, optional
-                If set to true, the size of the fonts will be adapted to the size of the figure. Otherwise
-                the default matplotlib font size is used. Default is True.
+                If set to true, the size of the fonts will be adapted to the size of the figure.
+                Otherwise the default matplotlib font size is used. Default is True.
         kwargs : optional
             arguments for hexbin matplotlib function
 
@@ -371,8 +371,8 @@ def plot_raster_eai_exposure(self, res=None, raster_res=None, save_tiff=None,
         axis : matplotlib.axes._subplots.AxesSubplot, optional
             axis to use
         adapt_fontsize : bool, optional
-                If set to true, the size of the fonts will be adapted to the size of the figure. Otherwise
-                the default matplotlib font size is used. Default is True.
+                If set to true, the size of the fonts will be adapted to the size of the figure.
+                Otherwise the default matplotlib font size is used. Default is True.
         kwargs : optional
             arguments for imshow matplotlib function
 
@@ -428,7 +428,7 @@ def plot_basemap_eai_exposure(self, mask=None, ignore_zero=False, pop_name=True,
         axis.set_title('Expected annual impact')
         return axis
 
-    def plot_hexbin_impact_exposure(self, event_id=1, mask=None, ignore_zero=True,
+    def plot_hexbin_impact_exposure(self, event_id=1, mask=None, ignore_zero=False,
                                     pop_name=True, buffer=0.0, extend='neither',
                                     axis=None, adapt_fontsize=True, **kwargs):
         """Plot hexbin impact of an event at each exposure.
@@ -457,8 +457,8 @@ def plot_hexbin_impact_exposure(self, event_id=1, mask=None, ignore_zero=True,
         axis : matplotlib.axes._subplots.AxesSubplot
             optional axis to use
         adapt_fontsize : bool, optional
-            If set to true, the size of the fonts will be adapted to the size of the figure. Otherwise
-            the default matplotlib font size is used. Default is True.
+            If set to true, the size of the fonts will be adapted to the size of the figure.
+            Otherwise the default matplotlib font size is used. Default is True.
 
         Returns
         --------
@@ -471,12 +471,13 @@ def plot_hexbin_impact_exposure(self, event_id=1, mask=None, ignore_zero=True,
             kwargs['cmap'] = CMAP_IMPACT
         impact_at_events_exp = self._build_exp_event(event_id)
         axis = impact_at_events_exp.plot_hexbin(mask, ignore_zero, pop_name,
-                                                buffer, extend, axis=axis, adapt_fontsize=adapt_fontsize,
+                                                buffer, extend, axis=axis,
+                                                adapt_fontsize=adapt_fontsize,
                                                 **kwargs)
 
         return axis
 
-    def plot_basemap_impact_exposure(self, event_id=1, mask=None, ignore_zero=True,
+    def plot_basemap_impact_exposure(self, event_id=1, mask=None, ignore_zero=False,
                                      pop_name=True, buffer=0.0, extend='neither', zoom=10,
                                      url='http://tile.stamen.com/terrain/tileZ/tileX/tileY.png',
                                      axis=None, **kwargs):
@@ -619,7 +620,8 @@ def calc_impact_year_set(self, all_years=True, year_range=None):
 
         Returns
         -------
-        Impact year set of type numpy.ndarray with summed impact per year.
+        yearset : numpy.ndarray
+            Impact year set of type numpy.ndarray with summed impact per year.
         """
         if year_range is None:
             year_range = []
@@ -851,16 +853,17 @@ def read_excel(self, *args, **kwargs):
     @staticmethod
     def video_direct_impact(exp, impf_set, haz_list, file_name='',
                             writer=animation.PillowWriter(bitrate=500),
-                            imp_thresh=0, args_exp=None, args_imp=None):
+                            imp_thresh=0, args_exp=None, args_imp=None,
+                            ignore_zero=False, pop_name=False):
         """
         Computes and generates video of accumulated impact per input events
         over exposure.
 
         Parameters
         ----------
-        exp : Exposures
+        exp : climada.entity.Exposures
             exposures instance, constant during all video
-        impf_set : ImpactFuncSet
+        impf_set : climada.entity.ImpactFuncSet
             impact functions
         haz_list : (list(Hazard))
             every Hazard contains an event; all hazards
@@ -877,6 +880,12 @@ def video_direct_impact(exp, impf_set, haz_list, file_name='',
         args_imp : optional
             arguments for scatter (points) or hexbin (raster)
             matplotlib function used in impact
+        ignore_zero : bool, optional
+            flag to indicate if zero and negative
+            values are ignored in plot. Default: False
+        pop_name : bool, optional
+            add names of the populated places
+            The default is False.
 
         Returns
         -------
@@ -932,17 +941,17 @@ def run(i_time):
             haz_list[i_time].plot_intensity(1, axis=axis, cmap='Greys', vmin=v_lim[0],
                                             vmax=v_lim[1], alpha=0.8)
             if plot_raster:
-                exp.plot_hexbin(axis=axis, mask=exp_list[i_time], ignore_zero=True,
-                                pop_name=False, **args_exp)
+                exp.plot_hexbin(axis=axis, mask=exp_list[i_time], ignore_zero=ignore_zero,
+                                pop_name=pop_name, **args_exp)
                 if imp_list[i_time].coord_exp.size:
-                    imp_list[i_time].plot_hexbin_eai_exposure(axis=axis, pop_name=False,
+                    imp_list[i_time].plot_hexbin_eai_exposure(axis=axis, pop_name=pop_name,
                                                               **args_imp)
                     fig.delaxes(fig.axes[1])
             else:
-                exp.plot_scatter(axis=axis, mask=exp_list[i_time], ignore_zero=True,
-                                 pop_name=False, **args_exp)
+                exp.plot_scatter(axis=axis, mask=exp_list[i_time], ignore_zero=ignore_zero,
+                                 pop_name=pop_name, **args_exp)
                 if imp_list[i_time].coord_exp.size:
-                    imp_list[i_time].plot_scatter_eai_exposure(axis=axis, pop_name=False,
+                    imp_list[i_time].plot_scatter_eai_exposure(axis=axis, pop_name=pop_name,
                                                                **args_imp)
                     fig.delaxes(fig.axes[1])
             fig.delaxes(fig.axes[1])
@@ -1155,7 +1164,7 @@ def select(self,
 
         Returns
         -------
-        imp : climada.engine.Impact
+        imp : climada.engine.impact.Impact
             A new impact object with a selection of events and/or exposures
 
         """