raise ModelError in predictions and residuals

egsim/smtk/residuals.py

@@ -22,7 +22,7 @@
 from .flatfile import (FlatfileError, MissingColumnError, FlatfileMetadata,
                        ColumnDataError, IncompatibleColumnError, EVENT_ID_COLUMN_NAME)
 from .validators import (validate_inputs, harmonize_input_gsims, sa_period,
-                         harmonize_input_imts, validate_imt_sa_limits)
+                         harmonize_input_imts, validate_imt_sa_limits, ModelError)
 from .registry import (get_ground_motion_values, Clabel,
                        ground_motion_properties_required_by)
 from .converters import vs30_to_z1pt0_cy14, vs30_to_z2pt5_cb14
@@ -226,29 +226,32 @@ def get_expected_motions(
     columns = []
     # Period range for GSIM
     for gsim_name, gsim in gsims.items():
-        # validate SA periods:
-        imts_ok = validate_imt_sa_limits(gsim, imts)
-        if not imts_ok:
-            continue
-        imt_names, imt_vals = list(imts_ok.keys()), list(imts_ok.values())
-        cmaker = ContextMaker('*', [gsim], {'imtls': {i: [0] for i in imt_names}})
-        # TODO above is imtls relevant, or should we use PGA: [0] as in trellis?
-        #  maybe harmonize and document why we do the line above?
-        mean, total, inter, intra = get_ground_motion_values(
-            gsim, imt_vals, cmaker.recarray([ctx]))
-        # assign data to our tmp lists:
-        columns.extend(product(imt_names, [Clabel.mean], [gsim_name]))
-        data.append(mean)
-        stddev_types = gsim.DEFINED_FOR_STANDARD_DEVIATION_TYPES
-        if const.StdDev.TOTAL in stddev_types:
-            columns.extend((i, Clabel.total_std, gsim_name) for i in imt_names)
-            data.append(total)
-        if const.StdDev.INTER_EVENT in stddev_types:
-            columns.extend((i, Clabel.inter_ev_std, gsim_name) for i in imt_names)
-            data.append(inter)
-        if const.StdDev.INTRA_EVENT in stddev_types:
-            columns.extend((i, Clabel.intra_ev_std, gsim_name) for i in imt_names)
-            data.append(intra)
+        try:
+            # validate SA periods:
+            imts_ok = validate_imt_sa_limits(gsim, imts)
+            if not imts_ok:
+                continue
+            imt_names, imt_vals = list(imts_ok.keys()), list(imts_ok.values())
+            cmaker = ContextMaker('*', [gsim], {'imtls': {i: [0] for i in imt_names}})
+            # TODO above is imtls relevant, or should we use PGA: [0] as in trellis?
+            #  maybe harmonize and document why we do the line above?
+            mean, total, inter, intra = get_ground_motion_values(
+                gsim, imt_vals, cmaker.recarray([ctx]))
+            # assign data to our tmp lists:
+            columns.extend(product(imt_names, [Clabel.mean], [gsim_name]))
+            data.append(mean)
+            stddev_types = gsim.DEFINED_FOR_STANDARD_DEVIATION_TYPES
+            if const.StdDev.TOTAL in stddev_types:
+                columns.extend((i, Clabel.total_std, gsim_name) for i in imt_names)
+                data.append(total)
+            if const.StdDev.INTER_EVENT in stddev_types:
+                columns.extend((i, Clabel.inter_ev_std, gsim_name) for i in imt_names)
+                data.append(inter)
+            if const.StdDev.INTRA_EVENT in stddev_types:
+                columns.extend((i, Clabel.intra_ev_std, gsim_name) for i in imt_names)
+                data.append(intra)
+        except Exception as exc:
+            raise ModelError(f'{gsim_name}: ({exc.__class__.__name__}) {str(exc)}')
 
     return pd.DataFrame(columns=pd.MultiIndex.from_tuples(columns),
                         data=np.hstack(data), index=ctx.sids)

egsim/smtk/scenarios.py

@@ -21,7 +21,7 @@
 from .flatfile import FlatfileMetadata
 from .converters import vs30_to_z1pt0_cy14, vs30_to_z2pt5_cb14
 from .validators import (validate_inputs, harmonize_input_gsims,
-                         harmonize_input_imts, validate_imt_sa_limits)
+                         harmonize_input_imts, validate_imt_sa_limits, ModelError)
 
 
 @dataclass
@@ -103,19 +103,19 @@ class RuptureProperties)
     # Get the ground motion values
     data = []
     columns = []
-    for gsim_label, gsim in gsims.items():
+    for gsim_name, gsim in gsims.items():
         imts_ok = validate_imt_sa_limits(gsim, imts)
         if not imts_ok:
             continue
         imt_names, imt_vals = list(imts_ok.keys()), list(imts_ok.values())
         try:
             median, sigma, tau, phi = get_ground_motion_values(gsim, imt_vals, ctxts)
             data.append(median)
-            columns.extend((i, Clabel.median, gsim_label) for i in imt_names)
+            columns.extend((i, Clabel.median, gsim_name) for i in imt_names)
             data.append(sigma)
-            columns.extend((i, Clabel.std, gsim_label) for i in imt_names)
+            columns.extend((i, Clabel.std, gsim_name) for i in imt_names)
         except Exception as exc:
-            raise ValueError(f'Error in {gsim_label}: {str(exc)}')
+            raise ModelError(f'{gsim_name}: ({exc.__class__.__name__}) {str(exc)}')
 
     # distances:
     columns.append((

tests/django/test_api_views.py

@@ -36,7 +36,8 @@ def test_model_info():
                            content_type="application/json")
     assert response.status_code == 200
     assert sorted(response.json().keys()) == ['CauzziEtAl2014']
-    assert all(isinstance(v, dict) and sorted(v.keys()) == ['doc', 'imts', 'props']
+    assert all(isinstance(v, dict) and
+               sorted(v.keys()) == ['doc', 'imts', 'props', 'sa_limits']
                for v in response.json().values())
 
     data = {'model': ['BindiEtAl2014Rjb', 'CauzziEtAl2014']}
@@ -45,7 +46,8 @@ def test_model_info():
                            content_type="application/json")
     assert response.status_code == 200
     assert sorted(response.json().keys()) == ['BindiEtAl2014Rjb', 'CauzziEtAl2014']
-    assert all(isinstance(v, dict) and sorted(v.keys()) == ['doc', 'imts', 'props']
+    assert all(isinstance(v, dict) and
+               sorted(v.keys()) == ['doc', 'imts', 'props', 'sa_limits']
                for v in response.json().values())
 
     data = {'model': ['x', 'CauzziEtAl2014']}

tests/smtk/residuals/test_residuals.py

@@ -2,6 +2,8 @@
 test residuals computations (standard and likelihood)
 """
 import json
+from unittest.mock import patch
+
 import numpy as np
 import os
 import pandas as pd
@@ -12,7 +14,7 @@
 from egsim.smtk.flatfile import read_flatfile, ColumnType
 from scipy.constants import g
 from egsim.smtk.registry import Clabel
-
+from egsim.smtk.validators import ModelError
 
 # load flatfile once:
 BASE_DATA_PATH = os.path.join(os.path.dirname(__file__), "data")
@@ -212,3 +214,14 @@ def test_assign_series():
                 raise AssertionError('series are identical, they should not be')
             except AssertionError:
                 pass
+
+
+@patch('egsim.smtk.residuals.get_ground_motion_values', side_effect=ValueError('a'))
+def test_model_error(mock_get_gmv):
+    with pytest.raises(ModelError) as err:
+        gsims, imts, flatfile = get_gsims_imts_flatfile()
+        res_df = get_residuals(gsims, imts, flatfile, likelihood=True)
+    assert mock_get_gmv.called
+    # the expected model is the first among the gsims (sorted), so:
+    expected_model = sorted(gsims)[0]
+    assert f'{expected_model}: (ValueError) a' in str(err.value)

tests/smtk/scenarios/test_scenarios_predictions.py

@@ -2,8 +2,11 @@
 Tests for generation of data for trellis plots
 """
 import os
+from unittest.mock import patch
+
 import numpy as np
 import pandas as pd
+import pytest
 
 from openquake.hazardlib.gsim.akkar_2014 import AkkarEtAlRjb2014
 from openquake.hazardlib.gsim.bindi_2014 import BindiEtAl2014Rjb
@@ -13,6 +16,7 @@
 from egsim.smtk.registry import Clabel
 from egsim.smtk.flatfile import ColumnType, FlatfileMetadata
 from egsim.smtk import scenarios
+from egsim.smtk.validators import ModelError
 
 BASE_DATA_PATH = os.path.join(os.path.dirname(__file__), "data")
 
@@ -297,3 +301,23 @@ def open_ref_hdf(file_name) -> pd.DataFrame:
     new_ref = pd.DataFrame({v: ref[c] for c, v in c_mapping.items()})
     new_ref.columns = pd.MultiIndex.from_tuples(new_ref.columns)
     return new_ref
+
+
+@patch('egsim.smtk.scenarios.get_ground_motion_values', side_effect=ValueError('a'))
+def test_model_error(mock_get_gmv):
+    magnitudes = np.arange(4., 8.1, 0.1)
+    distance = 20.
+
+    with pytest.raises(ModelError) as err:
+        dfr = get_scenarios_predictions(
+            gsims,
+            imts,
+            magnitudes,
+            distance,
+            scenarios.RuptureProperties(dip=60.0, aspect=1.5, rake=-90),
+            scenarios.SiteProperties(vs30=800, z1pt0=50., z2pt5=1.)
+        )
+    assert mock_get_gmv.called
+    # the expected model is the first among the gsims (sorted), so:
+    expected_model = sorted(gsims)[0]
+    assert f'{expected_model}: (ValueError) a' in str(err.value)