Feature/init measures base

climada/entity/measures/base.py

@@ -24,6 +24,8 @@
 import copy
 import logging
 from pathlib import Path
+from typing import Optional, Tuple
+
 import numpy as np
 import pandas as pd
 from geopandas import GeoDataFrame
@@ -81,33 +83,87 @@ class Measure():
         cost of risk transfer
     """
 
-    def __init__(self):
-        """Empty initialization."""
-        self.name = ''
-        self.haz_type = ''
-        self.color_rgb = np.array([0, 0, 0])
-        self.cost = 0
+    def __init__(
+        self,
+        name: str = "",
+        haz_type: str = "",
+        cost: float = 0,
+        hazard_set: str = NULL_STR,
+        hazard_freq_cutoff: float = 0,
+        exposures_set: str = NULL_STR,
+        imp_fun_map: str = NULL_STR,
+        hazard_inten_imp: Tuple[float, float] = (1, 0),
+        mdd_impact: Tuple[float, float] = (1, 0),
+        paa_impact: Tuple[float, float] = (1, 0),
+        exp_region_id: Optional[list] = None,
+        risk_transf_attach: float = 0,
+        risk_transf_cover: float = 0,
+        risk_transf_cost_factor: float = 1,
+        color_rgb: Optional[np.ndarray] = None
+    ):
+        """Initialize a Measure object with given values.
+
+        Parameters
+        ----------
+        name : str, optional
+            name of the measure
+        haz_type : str, optional
+            related hazard type (peril), e.g. TC
+        cost : float, optional
+            discounted cost (in same units as assets)
+        hazard_set : str, optional
+            file name of hazard to use (in h5 format)
+        hazard_freq_cutoff : float, optional
+            hazard frequency cutoff
+        exposures_set : str  or climada.entity.Exposure, optional
+            file name of exposure to use (in h5 format) or Exposure instance
+        imp_fun_map : str, optional
+            change of impact function id of exposures, e.g. '1to3'
+        hazard_inten_imp : tuple(float, float), optional
+            parameter a and b of hazard intensity change
+        mdd_impact : tuple(float, float), optional
+            parameter a and b of the impact over the mean damage degree
+        paa_impact : tuple(float, float), optional
+            parameter a and b of the impact over the percentage of affected assets
+        exp_region_id : int, optional
+            region id of the selected exposures to consider ALL the previous
+            parameters
+        risk_transf_attach : float, optional
+            risk transfer attachment
+        risk_transf_cover : float, optional
+            risk transfer cover
+        risk_transf_cost_factor : float, optional
+            factor to multiply to resulting insurance layer to get the total
+            cost of risk transfer
+        color_rgb : np.array, optional
+            integer array of size 3. Color code of this measure in RGB.
+            Default is None (corresponds to black).
+        """
+        self.name = name
+        self.haz_type = haz_type
+        self.color_rgb = np.array([0, 0, 0]) if color_rgb is None else color_rgb
+        self.cost = cost
 
         # related to change in hazard
-        self.hazard_set = NULL_STR
-        self.hazard_freq_cutoff = 0
+        self.hazard_set = hazard_set
+        self.hazard_freq_cutoff = hazard_freq_cutoff
 
         # related to change in exposures
-        self.exposures_set = NULL_STR
-        self.imp_fun_map = NULL_STR  # ids of impact functions to change e.g. 1to10
+        self.exposures_set = exposures_set
+        self.imp_fun_map = imp_fun_map
 
         # related to change in impact functions
-        self.hazard_inten_imp = (1, 0)  # parameter a and b
-        self.mdd_impact = (1, 0)  # parameter a and b
-        self.paa_impact = (1, 0)  # parameter a and b
+        self.hazard_inten_imp = hazard_inten_imp
+        self.mdd_impact = mdd_impact
+        self.paa_impact = paa_impact
 
         # related to change in region
-        self.exp_region_id = []
+        self.exp_region_id = [] if exp_region_id is None else exp_region_id
 
         # risk transfer
-        self.risk_transf_attach = 0
-        self.risk_transf_cover = 0
-        self.risk_transf_cost_factor = 1
+        self.risk_transf_attach = risk_transf_attach
+        self.risk_transf_cover = risk_transf_cover
+        self.risk_transf_cost_factor = risk_transf_cost_factor
 
     def check(self):
         """

climada/entity/measures/measure_set.py

@@ -101,12 +101,13 @@ def __init__(self):
         --------
         Fill MeasureSet with values and check consistency data:
 
-        >>> act_1 = Measure()
-        >>> act_1.name = 'Seawall'
-        >>> act_1.color_rgb = np.array([0.1529, 0.2510, 0.5451])
-        >>> act_1.hazard_intensity = (1, 0)
-        >>> act_1.mdd_impact = (1, 0)
-        >>> act_1.paa_impact = (1, 0)
+        >>> act_1 = Measure(
+        ...     name='Seawall',
+        ...     color_rgb=np.array([0.1529, 0.2510, 0.5451]),
+        ...     hazard_intensity=(1, 0),
+        ...     mdd_impact=(1, 0),
+        ...     paa_impact=(1, 0),
+        ... )
         >>> meas = MeasureSet()
         >>> meas.append(act_1)
         >>> meas.tag.description = "my dummy MeasureSet."
@@ -357,45 +358,46 @@ def read_att_mat(measures, data, file_name, var_names):
             """Read MATLAB measures attributes"""
             num_mes = len(data[var_names['var_name']['name']])
             for idx in range(0, num_mes):
-                meas = Measure()
-
-                meas.name = u_hdf5.get_str_from_ref(
-                    file_name, data[var_names['var_name']['name']][idx][0])
-
                 color_str = u_hdf5.get_str_from_ref(
                     file_name, data[var_names['var_name']['color']][idx][0])
-                meas.color_rgb = np.fromstring(color_str, dtype=float, sep=' ')
-                meas.cost = data[var_names['var_name']['cost']][idx][0]
-                meas.haz_type = u_hdf5.get_str_from_ref(
-                    file_name, data[var_names['var_name']['haz']][idx][0])
-                meas.hazard_freq_cutoff = data[var_names['var_name']['haz_frq']][idx][0]
-                meas.hazard_set = u_hdf5.get_str_from_ref(
-                    file_name, data[var_names['var_name']['haz_set']][idx][0])
+
                 try:
-                    meas.hazard_inten_imp = (
+                    hazard_inten_imp = (
                         data[var_names['var_name']['haz_int_a']][idx][0],
                         data[var_names['var_name']['haz_int_b']][0][idx])
                 except KeyError:
-                    meas.hazard_inten_imp = (
+                    hazard_inten_imp = (
                         data[var_names['var_name']['haz_int_a'][:-2]][idx][0], 0)
 
-                # different convention of signes followed in MATLAB!
-                meas.mdd_impact = (data[var_names['var_name']['mdd_a']][idx][0],
-                                   data[var_names['var_name']['mdd_b']][idx][0])
-                meas.paa_impact = (data[var_names['var_name']['paa_a']][idx][0],
-                                   data[var_names['var_name']['paa_b']][idx][0])
-                meas.imp_fun_map = u_hdf5.get_str_from_ref(
-                    file_name, data[var_names['var_name']['fun_map']][idx][0])
+                meas_kwargs = dict(
+                    name=u_hdf5.get_str_from_ref(
+                        file_name, data[var_names['var_name']['name']][idx][0]),
+                    color_rgb=np.fromstring(color_str, dtype=float, sep=' '),
+                    cost=data[var_names['var_name']['cost']][idx][0],
+                    haz_type=u_hdf5.get_str_from_ref(
+                        file_name, data[var_names['var_name']['haz']][idx][0]),
+                    hazard_freq_cutoff=data[var_names['var_name']['haz_frq']][idx][0],
+                    hazard_set=u_hdf5.get_str_from_ref(
+                        file_name, data[var_names['var_name']['haz_set']][idx][0]),
+                    hazard_inten_imp=hazard_inten_imp,
+                    # different convention of signs followed in MATLAB!
+                    mdd_impact=(data[var_names['var_name']['mdd_a']][idx][0],
+                                data[var_names['var_name']['mdd_b']][idx][0]),
+                    paa_impact=(data[var_names['var_name']['paa_a']][idx][0],
+                                data[var_names['var_name']['paa_b']][idx][0]),
+                    imp_fun_map=u_hdf5.get_str_from_ref(
+                        file_name, data[var_names['var_name']['fun_map']][idx][0]),
+                    exposures_set=u_hdf5.get_str_from_ref(
+                        file_name, data[var_names['var_name']['exp_set']][idx][0]),
+                    risk_transf_attach=data[var_names['var_name']['risk_att']][idx][0],
+                    risk_transf_cover=data[var_names['var_name']['risk_cov']][idx][0],
+                )
 
-                meas.exposures_set = u_hdf5.get_str_from_ref(
-                    file_name, data[var_names['var_name']['exp_set']][idx][0])
                 exp_region_id = data[var_names['var_name']['exp_reg']][idx][0]
                 if exp_region_id:
-                    meas.exp_region_id = [exp_region_id]
-                meas.risk_transf_attach = data[var_names['var_name']['risk_att']][idx][0]
-                meas.risk_transf_cover = data[var_names['var_name']['risk_cov']][idx][0]
+                    meas_kwargs["exp_region_id"] = [exp_region_id]
 
-                measures.append(meas)
+                measures.append(Measure(**meas_kwargs))
 
         data = u_hdf5.read(file_name)
         meas_set = cls()
@@ -444,47 +446,56 @@ def read_att_excel(measures, dfr, var_names):
             """Read Excel measures attributes"""
             num_mes = len(dfr.index)
             for idx in range(0, num_mes):
-                meas = Measure()
+                # Search for (a, b) values, put a=1 otherwise
+                try:
+                    hazard_inten_imp = (dfr[var_names['col_name']['haz_int_a']][idx],
+                                        dfr[var_names['col_name']['haz_int_b']][idx])
+                except KeyError:
+                    hazard_inten_imp = (1, dfr['hazard intensity impact'][idx])
+
+                meas_kwargs = dict(
+                    name=dfr[var_names['col_name']['name']][idx],
+                    cost=dfr[var_names['col_name']['cost']][idx],
+                    hazard_freq_cutoff=dfr[var_names['col_name']['haz_frq']][idx],
+                    hazard_set=dfr[var_names['col_name']['haz_set']][idx],
+                    hazard_inten_imp=hazard_inten_imp,
+                    mdd_impact=(dfr[var_names['col_name']['mdd_a']][idx],
+                                dfr[var_names['col_name']['mdd_b']][idx]),
+                    paa_impact=(dfr[var_names['col_name']['paa_a']][idx],
+                                dfr[var_names['col_name']['paa_b']][idx]),
+                    imp_fun_map=dfr[var_names['col_name']['fun_map']][idx],
+                    risk_transf_attach=dfr[var_names['col_name']['risk_att']][idx],
+                    risk_transf_cover=dfr[var_names['col_name']['risk_cov']][idx],
+                    color_rgb=np.fromstring(
+                        dfr[var_names['col_name']['color']][idx], dtype=float, sep=' '),
+                )
 
-                meas.name = dfr[var_names['col_name']['name']][idx]
                 try:
-                    meas.haz_type = dfr[var_names['col_name']['haz']][idx]
+                    meas_kwargs["haz_type"] = dfr[var_names['col_name']['haz']][idx]
                 except KeyError:
                     pass
-                meas.color_rgb = np.fromstring(
-                    dfr[var_names['col_name']['color']][idx], dtype=float, sep=' ')
-                meas.cost = dfr[var_names['col_name']['cost']][idx]
 
-                meas.hazard_freq_cutoff = dfr[var_names['col_name']['haz_frq']][idx]
-                meas.hazard_set = dfr[var_names['col_name']['haz_set']][idx]
-                # Search for (a, b) values, put a = 1 otherwise
                 try:
-                    meas.hazard_inten_imp = (dfr[var_names['col_name']['haz_int_a']][idx],
-                                             dfr[var_names['col_name']['haz_int_b']][idx])
+                    meas_kwargs["exposures_set"] = dfr[var_names['col_name']['exp_set']][idx]
                 except KeyError:
-                    meas.hazard_inten_imp = (1, dfr['hazard intensity impact'][idx])
+                    pass
 
                 try:
-                    meas.exposures_set = dfr[var_names['col_name']['exp_set']][idx]
-                    meas.exp_region_id = ast.literal_eval(dfr[var_names['col_name']['exp_reg']][idx])
+                    meas_kwargs["exp_region_id"] = ast.literal_eval(
+                        dfr[var_names['col_name']['exp_reg']][idx])
                 except KeyError:
                     pass
                 except ValueError:
-                    meas.exp_region_id = dfr[var_names['col_name']['exp_reg']][idx]
-
-                meas.mdd_impact = (dfr[var_names['col_name']['mdd_a']][idx],
-                                   dfr[var_names['col_name']['mdd_b']][idx])
-                meas.paa_impact = (dfr[var_names['col_name']['paa_a']][idx],
-                                   dfr[var_names['col_name']['paa_b']][idx])
-                meas.imp_fun_map = dfr[var_names['col_name']['fun_map']][idx]
-                meas.risk_transf_attach = dfr[var_names['col_name']['risk_att']][idx]
-                meas.risk_transf_cover = dfr[var_names['col_name']['risk_cov']][idx]
+                    meas_kwargs["exp_region_id"] = dfr[var_names['col_name']['exp_reg']][idx]
+
                 try:
-                    meas.risk_transf_cost_factor = dfr[var_names['col_name']['risk_fact']][idx]
+                    meas_kwargs["risk_transf_cost_factor"] = (
+                        dfr[var_names['col_name']['risk_fact']][idx]
+                    )
                 except KeyError:
                     pass
 
-                measures.append(meas)
+                measures.append(Measure(**meas_kwargs))
 
         dfr = pd.read_excel(file_name, var_names['sheet_name'])
         dfr = dfr.fillna('')

climada/entity/measures/test/test_base.py

@@ -144,9 +144,10 @@ def test_cutoff_hazard_region_pass(self):
 
     def test_change_exposures_impf_pass(self):
         """Test _change_exposures_impf"""
-        meas = Measure()
-        meas.imp_fun_map = '1to3'
-        meas.haz_type = 'TC'
+        meas = Measure(
+            imp_fun_map='1to3',
+            haz_type='TC',
+        )
 
         imp_set = ImpactFuncSet()
         imp_tc = ImpactFunc()
@@ -179,8 +180,7 @@ def test_change_exposures_impf_pass(self):
 
     def test_change_all_hazard_pass(self):
         """Test _change_all_hazard method"""
-        meas = Measure()
-        meas.hazard_set = HAZ_DEMO_H5
+        meas = Measure(hazard_set=HAZ_DEMO_H5)
 
         ref_haz = Hazard.from_hdf5(HAZ_DEMO_H5)
 
@@ -198,8 +198,7 @@ def test_change_all_hazard_pass(self):
 
     def test_change_all_exposures_pass(self):
         """Test _change_all_exposures method"""
-        meas = Measure()
-        meas.exposures_set = EXP_DEMO_H5
+        meas = Measure(exposures_set=EXP_DEMO_H5)
 
         ref_exp = Exposures.from_hdf5(EXP_DEMO_H5)
 
@@ -218,8 +217,7 @@ def test_change_all_exposures_pass(self):
 
     def test_not_filter_exposures_pass(self):
         """Test _filter_exposures method with []"""
-        meas = Measure()
-        meas.exp_region_id = []
+        meas = Measure(exp_region_id=[])
 
         exp = Exposures()
         imp_set = ImpactFuncSet()
@@ -242,9 +240,10 @@ def test_not_filter_exposures_pass(self):
 
     def test_filter_exposures_pass(self):
         """Test _filter_exposures method with two values"""
-        meas = Measure()
-        meas.exp_region_id = [3, 4]
-        meas.haz_type = 'TC'
+        meas = Measure(
+            exp_region_id=[3, 4],
+            haz_type='TC',
+        )
 
         exp = Exposures.from_mat(ENT_TEST_MAT)
         exp.gdf.rename(columns={'impf_': 'impf_TC', 'centr_': 'centr_TC'}, inplace=True)