Remove all uses of Tag from climada/engine

CHANGELOG.md

@@ -68,8 +68,8 @@ Removed:
 ### Removed
 
 - `Centroids.set_raster_from_pix_bounds` [#721](https://github.com/CLIMADA-project/climada_python/pull/721)
-
 - `requirements/env_developer.yml` environment specs. Use 'extra' requirements when installing the Python package instead [#712](https://github.com/CLIMADA-project/climada_python/pull/712)
+- `Impact.tag` attribute. This change is not backwards-compatible with respect to the files written and read by the `Impact` class [#743](https://github.com/CLIMADA-project/climada_python/pull/743)
 
 ## v3.3.2
 

climada/engine/impact.py

@@ -21,7 +21,7 @@
 
 __all__ = ['ImpactFreqCurve', 'Impact']
 
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 import logging
 import copy
 import csv
@@ -51,7 +51,6 @@
 import climada.util.dates_times as u_dt
 import climada.util.plot as u_plot
 from climada.util.select import get_attributes_with_matching_dimension
-from climada.util.tag import Tag
 
 LOGGER = logging.getLogger(__name__)
 
@@ -88,9 +87,6 @@ class Impact():
     imp_mat : sparse.csr_matrix
         matrix num_events x num_exp with impacts.
         only filled if save_mat is True in calc()
-    tag : dict
-        dictionary of tags of exposures, impact functions set and
-        hazard: {'exp': Tag(), 'impf_set': Tag(), 'haz': Tag()}
     haz_type : str
         the hazard type of the hazard
     """
@@ -109,7 +105,6 @@ def __init__(self,
                  aai_agg=0,
                  unit='',
                  imp_mat=None,
-                 tag=None,
                  haz_type=''):
         """
         Init Impact object
@@ -145,15 +140,11 @@ def __init__(self,
             value unit used (given by exposures unit)
         imp_mat : sparse.csr_matrix, optional
             matrix num_events x num_exp with impacts.
-        tag : dict, optional
-            dictionary of tags of exposures, impact functions set and
-            hazard: {'exp': Tag(), 'impf_set': Tag(), 'haz': Tag()}
         haz_type : str, optional
             the hazard type
         """
 
         self.haz_type = haz_type
-        self.tag = tag or {}
         self.event_id = np.array([], int) if event_id is None else event_id
         self.event_name = [] if event_name is None else event_name
         self.date = np.array([], int) if date is None else date
@@ -216,11 +207,13 @@ def calc(self, exposures, impact_funcs, hazard, save_mat=False, assign_centroids
 
 #TODO: new name
     @classmethod
-    def from_eih(cls, exposures, impfset, hazard,
-                 at_event, eai_exp, aai_agg, imp_mat=None):
+    def from_eih(cls, exposures, hazard, at_event, eai_exp, aai_agg, imp_mat=None):
         """
         Set Impact attributes from precalculated impact metrics.
 
+        .. versionchanged:: 3.3
+           The ``impfset`` argument was removed.
+
         Parameters
         ----------
         exposures : climada.entity.Exposures
@@ -260,10 +253,6 @@ def from_eih(cls, exposures, impfset, hazard,
             at_event = at_event,
             aai_agg = aai_agg,
             imp_mat = imp_mat if imp_mat is not None else sparse.csr_matrix((0, 0)),
-            tag = {'exp': exposures.tag,
-                   'impf_set': impfset.tag,
-                   'haz': hazard.tag
-                   },
             haz_type = hazard.haz_type,
             )
 
@@ -543,7 +532,6 @@ def calc_freq_curve(self, return_per=None):
             ifc_impact = interp_imp
 
         return ImpactFreqCurve(
-            tag=self.tag,
             return_per=ifc_return_per,
             impact=ifc_impact,
             unit=self.unit,
@@ -885,14 +873,10 @@ def write_csv(self, file_name):
         LOGGER.info('Writing %s', file_name)
         with open(file_name, "w", encoding='utf-8') as imp_file:
             imp_wr = csv.writer(imp_file)
-            imp_wr.writerow(["tag_hazard", "tag_exposure", "tag_impact_func",
-                             "unit", "tot_value", "aai_agg", "event_id",
+            imp_wr.writerow(["haz_type", "unit", "tot_value", "aai_agg", "event_id",
                              "event_name", "event_date", "event_frequency", "frequency_unit",
                              "at_event", "eai_exp", "exp_lat", "exp_lon", "exp_crs"])
-            csv_data = [[[self.haz_type], [self.tag['haz'].file_name],
-                         [self.tag['haz'].description]],
-                        [[self.tag['exp'].file_name], [self.tag['exp'].description]],
-                        [[self.tag['impf_set'].file_name], [self.tag['impf_set'].description]],
+            csv_data = [[self.haz_type],
                         [self.unit], [self._tot_value], [self.aai_agg],
                         self.event_id, self.event_name, self.date,
                         self.frequency, [self.frequency_unit], self.at_event,
@@ -920,32 +904,26 @@ def write_col(i_col, imp_ws, xls_data):
         imp_wb = xlsxwriter.Workbook(file_name)
         imp_ws = imp_wb.add_worksheet()
 
-        header = ["tag_hazard", "tag_exposure", "tag_impact_func",
-                  "unit", "tot_value", "aai_agg", "event_id",
+        header = ["haz_type", "unit", "tot_value", "aai_agg", "event_id",
                   "event_name", "event_date", "event_frequency", "frequency_unit",
                   "at_event", "eai_exp", "exp_lat", "exp_lon", "exp_crs"]
         for icol, head_dat in enumerate(header):
             imp_ws.write(0, icol, head_dat)
-        data = [str(self.haz_type), str(self.tag['haz'].file_name),
-                str(self.tag['haz'].description)]
+        data = [str(self.haz_type)]
         write_col(0, imp_ws, data)
-        data = [str(self.tag['exp'].file_name), str(self.tag['exp'].description)]
-        write_col(1, imp_ws, data)
-        data = [str(self.tag['impf_set'].file_name), str(self.tag['impf_set'].description)]
-        write_col(2, imp_ws, data)
-        write_col(3, imp_ws, [self.unit])
-        write_col(4, imp_ws, [self._tot_value])
-        write_col(5, imp_ws, [self.aai_agg])
-        write_col(6, imp_ws, self.event_id)
-        write_col(7, imp_ws, self.event_name)
-        write_col(8, imp_ws, self.date)
-        write_col(9, imp_ws, self.frequency)
-        write_col(10, imp_ws, [self.frequency_unit])
-        write_col(11, imp_ws, self.at_event)
-        write_col(12, imp_ws, self.eai_exp)
-        write_col(13, imp_ws, self.coord_exp[:, 0])
-        write_col(14, imp_ws, self.coord_exp[:, 1])
-        write_col(15, imp_ws, [str(self.crs)])
+        write_col(1, imp_ws, [self.unit])
+        write_col(2, imp_ws, [self._tot_value])
+        write_col(3, imp_ws, [self.aai_agg])
+        write_col(4, imp_ws, self.event_id)
+        write_col(5, imp_ws, self.event_name)
+        write_col(6, imp_ws, self.date)
+        write_col(7, imp_ws, self.frequency)
+        write_col(8, imp_ws, [self.frequency_unit])
+        write_col(9, imp_ws, self.at_event)
+        write_col(10, imp_ws, self.eai_exp)
+        write_col(11, imp_ws, self.coord_exp[:, 0])
+        write_col(12, imp_ws, self.coord_exp[:, 1])
+        write_col(13, imp_ws, [str(self.crs)])
 
         imp_wb.close()
 
@@ -1023,11 +1001,6 @@ def write_dict(group, name, value):
             for key, val in value.items():
                 write(group, key, val)
 
-        def write_tag(group, name, value):
-            """Write a tag object using the dict writer"""
-            group = group.create_group(name)  # name is 'exp', 'haz', 'impf_set'
-            value.to_hdf5(group)              # value is a Tag
-
         def _write_csr_dense(group, name, value):
             """Write a CSR Matrix in dense format"""
             group.create_dataset(name, data=value.toarray())
@@ -1052,7 +1025,6 @@ def write_csr(group, name, value):
         #       2) Anything is 'object', so this serves as fallback/default.
         type_writers = {
             str: write_attribute,
-            Tag: write_tag,
             dict: write_dict,
             sparse.csr_matrix: write_csr,
             Collection: write_dataset,
@@ -1107,7 +1079,7 @@ def from_csv(cls, file_name):
         # pylint: disable=no-member
         LOGGER.info('Reading %s', file_name)
         imp_df = pd.read_csv(file_name)
-        imp = cls(haz_type=str(imp_df.tag_hazard[0]))
+        imp = cls(haz_type=imp_df.haz_type[0])
         imp.unit = imp_df.unit[0]
         imp.tot_value = imp_df.tot_value[0]
         imp.aai_agg = imp_df.aai_agg[0]
@@ -1128,12 +1100,7 @@ def from_csv(cls, file_name):
             imp.crs = u_coord.to_crs_user_input(imp_df.exp_crs.values[0])
         except AttributeError:
             imp.crs = DEF_CRS
-        imp.tag['haz'] = Tag(str(imp_df.tag_hazard[1]),
-                             str(imp_df.tag_hazard[2]))
-        imp.tag['exp'] = Tag(str(imp_df.tag_exposure[0]),
-                             str(imp_df.tag_exposure[1]))
-        imp.tag['impf_set'] = Tag(str(imp_df.tag_impact_func[0]),
-                                  str(imp_df.tag_impact_func[1]))
+
         return imp
 
     def read_csv(self, *args, **kwargs):
@@ -1158,16 +1125,7 @@ def from_excel(cls, file_name):
         """
         LOGGER.info('Reading %s', file_name)
         dfr = pd.read_excel(file_name)
-        imp = cls(haz_type=str(dfr['tag_hazard'][0]))
-        imp.tag['haz'] = Tag(
-            file_name = dfr['tag_hazard'][1],
-            description = dfr['tag_hazard'][2])
-        imp.tag['exp'] = Tag()
-        imp.tag['exp'].file_name = dfr['tag_exposure'][0]
-        imp.tag['exp'].description = dfr['tag_exposure'][1]
-        imp.tag['impf_set'] = Tag()
-        imp.tag['impf_set'].file_name = dfr['tag_impact_func'][0]
-        imp.tag['impf_set'].description = dfr['tag_impact_func'][1]
+        imp = cls(haz_type=str(dfr['haz_type'][0]))
 
         imp.unit = dfr.unit[0]
         imp.tot_value = dfr.tot_value[0]
@@ -1215,24 +1173,11 @@ def from_hdf5(cls, file_path: Union[str, Path]):
             ├─ event_name
             ├─ frequency
             ├─ imp_mat
-            ├─ tag/
-            │  ├─ exp/
-            │  │  ├─ .attrs/
-            │  │  │  ├─ file_name
-            │  │  │  ├─ description
-            │  ├─ haz/
-            │  │  ├─ .attrs/
-            │  │  │  ├─ haz_type
-            │  │  │  ├─ file_name
-            │  │  │  ├─ description
-            │  ├─ impf_set/
-            │  │  ├─ .attrs/
-            │  │  │  ├─ file_name
-            │  │  │  ├─ description
             ├─ .attrs/
             │  ├─ aai_agg
             │  ├─ crs
             │  ├─ frequency_unit
+            │  ├─ haz_type
             │  ├─ tot_value
             │  ├─ unit
 
@@ -1300,13 +1245,6 @@ def from_hdf5(cls, file_path: Union[str, Path]):
                 # pylint: disable=no-member
                 kwargs["event_name"] = list(file["event_name"].asstr()[:])
 
-            # Tags
-            if "tag" in file:
-                tag_group = file["tag"]
-                # the tag group has tags for 'exp', 'haz' and 'impf_set'
-                tag_kwargs = {tag: Tag.from_hdf5(tag_group[tag]) for tag in tag_group.keys()}
-
-                kwargs["tag"] = tag_kwargs
         # Create the impact object
         return cls(**kwargs)
 
@@ -1476,7 +1414,6 @@ def _build_exp(self):
             crs=self.crs,
             value_unit=self.unit,
             ref_year=0,
-            tag=Tag(),
             meta=None
         )
 
@@ -1498,7 +1435,6 @@ def _build_exp_event(self, event_id):
             crs=self.crs,
             value_unit=self.unit,
             ref_year=0,
-            tag=Tag(),
             meta=None
         )
 
@@ -1719,8 +1655,8 @@ def concat(cls, imp_list: Iterable, reset_event_ids: bool = False):
           ``frequency``, ``imp_mat``, ``at_event``,
         - sums up the values of attributes ``eai_exp``, ``aai_exp``
         - and takes the following attributes from the first impact object in the passed
-          impact list: ``coord_exp``, ``crs``, ``unit``, ``tot_value``, ``tag``,
-          ``frequency_unit``
+          impact list: ``coord_exp``, ``crs``, ``unit``, ``tot_value``,
+          ``frequency_unit``, ``haz_type``
 
         If event ids are not unique among the passed impact objects an error is raised.
         In this case, the user can set ``reset_event_ids=True`` to create unique event ids
@@ -1806,7 +1742,6 @@ def stack_attribute(attr_name: str) -> np.ndarray:
             eai_exp=np.nansum([imp.eai_exp for imp in imp_list], axis=0),
             aai_agg=np.nansum([imp.aai_agg for imp in imp_list]),
             imp_mat=imp_mat,
-            tag=first_imp.tag,
             haz_type=first_imp.haz_type,
             frequency_unit=first_imp.frequency_unit,
             **kwargs,
@@ -1850,10 +1785,6 @@ class ImpactFreqCurve():
     """Impact exceedence frequency curve.
     """
 
-    tag : dict = field(default_factory=dict)
-    """dictionary of tags of exposures, impact functions set and
-        hazard: {'exp': Tag(), 'impf_set': Tag(), 'haz': Tag()}"""
-
     return_per : np.array = np.array([])
     """return period"""
 

climada/engine/impact_calc.py

@@ -175,9 +175,8 @@ def _return_impact(self, imp_mat_gen, save_mat):
             imp_mat = None
             at_event, eai_exp, aai_agg = self.stitch_risk_metrics(imp_mat_gen)
         return Impact.from_eih(
-            self.exposures, self.impfset, self.hazard,
-            at_event, eai_exp, aai_agg, imp_mat
-            )
+            self.exposures, self.hazard, at_event, eai_exp, aai_agg, imp_mat
+        )
 
     def _return_empty(self, save_mat):
         """
@@ -202,8 +201,9 @@ def _return_empty(self, save_mat):
                 )
         else:
             imp_mat = None
-        return Impact.from_eih(self.exposures, self.impfset, self.hazard,
-                        at_event, eai_exp, aai_agg, imp_mat)
+        return Impact.from_eih(
+            self.exposures, self.hazard, at_event, eai_exp, aai_agg, imp_mat
+        )
 
     def minimal_exp_gdf(self, impf_col, assign_centroids, ignore_cover, ignore_deductible):
         """Get minimal exposures geodataframe for impact computation

climada/engine/impact_data.py

@@ -30,7 +30,6 @@
 from climada.util.constants import DEF_CRS
 import climada.util.coordinates as u_coord
 from climada.engine import Impact
-from climada.util.tag import Tag
 
 LOGGER = logging.getLogger(__name__)
 
@@ -956,14 +955,6 @@ def emdat_to_impact(emdat_file_csv, hazard_type_climada, year_range=None, countr
     # Inititate Impact-instance:
     impact_instance = Impact(haz_type=hazard_type_climada)
 
-    impact_instance.tag = dict()
-    impact_instance.tag['haz'] = Tag(file_name=emdat_file_csv,
-                                     description='EM-DAT impact, direct import')
-    impact_instance.tag['exp'] = Tag(file_name=emdat_file_csv,
-                                     description='EM-DAT impact, direct import')
-    impact_instance.tag['impf_set'] = Tag(file_name=None, description=None)
-
-
     # Load EM-DAT impact data by event:
     em_data = emdat_impact_event(emdat_file_csv, countries=countries, hazard=hazard_type_emdat,
                                  year_range=year_range, reference_year=reference_year,