Added extract/aggrisk_keys and disabled avg_losses in Aristotle mode

openquake/calculators/extract.py

@@ -815,12 +815,7 @@ def extract_agg_curves(dstore, what):
     return ArrayWrapper(arr, dict(json=hdf5.dumps(attrs)))
 
 
-@extract.add('agg_keys')
-def extract_agg_keys(dstore, what):
-    """
-    Aggregate the exposure values (one for each loss type) by tag. Use it as
-    /extract/agg_keys?
-    """
+def _agg_keys(dstore):
     aggby = dstore['oqparam'].aggregate_by[0]
     keys = numpy.array([line.decode('utf8').split('\t')
                         for line in dstore['agg_keys'][:]])
@@ -832,7 +827,36 @@ def extract_agg_keys(dstore, what):
         dic[tag] = keys[ok, i]
     for name in values.dtype.names:
         dic[name] = okvalues[name]
-    return pandas.DataFrame(dic)
+    df = pandas.DataFrame(dic)
+    return df, ok
+
+
+@extract.add('agg_keys')
+def extract_agg_keys(dstore, what):
+    """
+    Aggregate the exposure values (one for each loss type) by tag. Use it as
+    /extract/agg_keys?
+    """
+    return _agg_keys(dstore)[0]
+
+
+@extract.add('aggrisk_keys')
+def extract_aggrisk_keys(dstore, what):
+    """
+    Aggregates risk by tag. Use it as /extract/aggrisk_keys?
+    """
+    df, ok = _agg_keys(dstore)
+    K = len(ok)
+    ws = dstore['weights'][:]
+    adf = dstore.read_df('aggrisk')
+    acc = {lt: numpy.zeros(K) for lt in LOSSTYPE[adf.loss_id.unique()]}
+    for agg_id, rlz_id, loss, loss_id in zip(
+            adf.agg_id, adf.rlz_id, adf.loss, adf.loss_id):
+        if agg_id < K:
+            acc[LOSSTYPE[loss_id]][agg_id] += loss * ws[rlz_id]
+    for name in acc:
+        df[name + '_risk'] = acc[name][ok]
+    return df
 
 
 @extract.add('agg_losses')

openquake/calculators/tests/event_based_risk_test.py

@@ -22,6 +22,7 @@
 
 from openquake.baselib.general import gettemp
 from openquake.baselib.hdf5 import read_csv
+from openquake.baselib.writers import CsvWriter, FIVEDIGITS
 from openquake.hazardlib import InvalidFile
 from openquake.hazardlib.source.rupture import get_ruptures
 from openquake.commonlib import logs, readinput
@@ -99,8 +100,13 @@ def test_case_1_ins(self):
         # this is a case with insured losses and tags
         self.run_calc(case_1.__file__, 'job_ins.ini', concurrent_tasks='4')
 
-        # testing agg_keys
+        # testing agg_keys and aggrisk_keys
         [fname] = export(('agg_keys', 'csv'), self.calc.datastore)
+        self.assertEqualFiles('expected/%s' % strip_calc_id(fname), fname,
+                              delta=1E-5)
+        df = extract(self.calc.datastore, 'aggrisk_keys')
+        fname = self.calc.datastore.export_path('aggrisk_keys.csv')
+        CsvWriter(fmt=FIVEDIGITS).save(df, fname)
         self.assertEqualFiles('expected/%s' % strip_calc_id(fname), fname,
                               delta=1E-5)
 

openquake/commonlib/oqvalidation.py

@@ -1896,7 +1896,10 @@ def aristotle(self):
         exposure with a known structure
         """
         exposures = self.inputs.get('exposure', [])
-        return exposures and exposures[0].endswith('.hdf5')
+        yes = exposures and exposures[0].endswith('.hdf5')
+        if yes:
+            self.avg_losses = False
+        return yes
 
     @property
     def aelo(self):

openquake/qa_tests_data/event_based_risk/case_1/expected/aggrisk_keys.csv

@@ -0,0 +1,6 @@
+#,,,,,,,,"generated_by='OpenQuake engine 3.22.0-git8859f48b4b', start_date='2025-01-17T07:05:09', checksum=1040388326"
+policy,taxonomy,number,nonstructural,structural,area,nonstructural_risk,structural_risk,structural+nonstructural_ins_risk
+A,RC,5.00000E+02,1.00000E+03,2.00000E+03,1.00000E+01,2.73602E+01,6.16284E+01,1.58074E+01
+A,RM,3.00000E+00,1.50000E+03,3.00000E+03,1.00000E+01,2.12580E+01,1.43613E+02,6.94350E+01
+B,RM,1.00000E+01,2.50000E+03,5.00000E+03,1.00000E+00,9.44013E+01,3.55602E+02,2.75387E+02
+B,W,1.00000E+03,5.00000E+02,1.00000E+03,1.00000E+01,2.60544E+01,2.52457E+02,2.42886E+02