test: additional multi model parameter test

python/ngen_cal/tests/conftest.py

@@ -231,3 +231,12 @@ def multi_model_shared_params() -> Mapping[str, list[Parameter]]:
     params = {'A':[p1], 'B':[p2], 'C':[p3]}
 
     return params
+
+@pytest.fixture
+def multi_model_shared_params2() -> Mapping[str, list[Parameter]]:
+    p1 = Parameter(name='a', min=0, max=1, init=0)
+    p2 = Parameter(name='a', min=0, max=1, init=0)
+    p3 = Parameter(name='c', min=0, max=1, init=0)
+    params = {'A':[p1, p3], 'B':[p2]}
+
+    return params

python/ngen_cal/tests/test_params.py

@@ -24,3 +24,16 @@ def test_multi_params(multi_model_shared_params: Mapping[str, list[Parameter]]):
     assert pa.drop('model', axis=1).equals( pb.drop('model', axis=1) )
     # ensure unique params/alias are not modifed by selection
     assert pa.loc['a', '1'] != pc.loc['c', '1']
+
+def test_multi_params2(multi_model_shared_params2: Mapping[str, list[Parameter]]):
+    # This is essentially the path the params go through from
+    # creation in model.py to update in search.py
+    params = _params_as_df(multi_model_shared_params2)
+    params = pd.DataFrame(params).rename(columns={'init':'0'})
+    # create new iteration from old
+    params['1'] = params['0']
+    #update the parameters by index
+    params.loc['a', '1'] = 0.5
+    pa = params[ params['model'] == 'A' ].drop('model', axis=1).loc['a']
+    pb = params[ params['model'] == 'B' ].drop('model', axis=1).loc['a']
+    assert pa.equals( pb )