Merge e613f1b into eb8521f

brian2modelfitting/metric.py

@@ -244,6 +244,22 @@ def calc(self, model_results, data_results, dt):
         """
         pass
 
+    def revert_normalization(self, error):
+        """
+        Revert the normalization to recover the error before normalization.
+
+        Parameters
+        ----------
+        error : Quantity or float
+            The normalized error.
+
+        Returns
+        -------
+        raw_error : Quantity or float
+            The error before normalization
+        """
+        return error / self.normalization
+
 
 class TraceMetric(Metric):
     """
@@ -457,13 +473,13 @@ def get_dimensions(self, output_dim):
     def get_normalized_dimensions(self, output_dim):
         return output_dim**2 * get_dimensions(self.normalization)**2
 
+    def revert_normalization(self, error):
+        return error / self.normalization**2
+
 
 class FeatureMetric(TraceMetric):
     def __init__(self, stim_times, feat_list, weights=None, combine=None,
                  t_start=0*second, normalization=1.):
-        if normalization != 1:
-            raise ValueError('Do not set the normalization factor when using '
-                             'the FeatureMetric, use weights instead.')
         super(FeatureMetric, self).__init__(t_start=t_start,
                                             normalization=normalization)
         self.stim_times = stim_times

brian2modelfitting/tests/test_metric.py

@@ -246,10 +246,6 @@ def test_get_features_feature_metric():
     inp_times = [[99 * ms, 150 * ms], [49 * ms, 150 * ms]]
 
     # Default comparison: absolute difference
-    # Check that FeatureMetric rejects the normalization argument
-    with pytest.raises(ValueError):
-        feature_metric = FeatureMetric(inp_times, ['voltage_base'],
-                                       normalization=2)
     feature_metric = FeatureMetric(inp_times, ['voltage_base'])
     results = feature_metric.get_features(voltage_model, voltage_target, dt=dt)
     assert len(results) == 3

brian2modelfitting/tests/test_modelfitting_spikefitter.py

@@ -131,7 +131,7 @@ def test_spikefitter_fit(setup):
     for attr in attr_fit:
         assert hasattr(sf, attr)
 
-    assert isinstance(sf.metric, Metric)
+    assert len(sf.metric) == 1 and isinstance(sf.metric[0], Metric)
     assert isinstance(sf.optimizer, Optimizer)
 
     assert isinstance(results, dict)