Use RegressionModel.fit for consistency with LCM class.

urbansim/models/regression.py

@@ -3,7 +3,7 @@
 import statsmodels.formula.api as smf
 
 from . import util
-from .. exceptions import ModelEvaluationError
+from ..exceptions import ModelEvaluationError
 
 
 def fit_model(df, filters, model_expression):
@@ -106,7 +106,7 @@ def __init__(self, fit_filters, predict_filters, model_expression,
         self.name = name or 'RegressionModel'
         self.model_fit = None
 
-    def fit_model(self, data):
+    def fit(self, data):
         """
         Fit the model to data and store/return the results.
 
@@ -127,6 +127,22 @@ class instance for use during prediction.
         self.model_fit = fit
         return fit
 
+    @property
+    def fitted(self):
+        """
+        True if the model is ready for prediction.
+
+        """
+        return bool(self.model_fit)
+
+    def assert_fitted(self):
+        """
+        Raises a RuntimeError if the model is not ready for prediction.
+
+        """
+        if not self.fitted:
+            raise RuntimeError('Model has not been fit.')
+
     def predict(self, data):
         """
         Predict a new data set based on an estimated model.
@@ -144,8 +160,7 @@ def predict(self, data):
             after applying filters.
 
         """
-        if not self.model_fit:
-            raise RuntimeError('Model has not been fit.')
+        self.assert_fitted()
         return predict(
             data, self.predict_filters, self.model_fit, self.ytransform)
 
@@ -229,7 +244,7 @@ def _iter_groups(self, data):
         for name in self.models:
             yield name, groups.get_group(name)
 
-    def fit_models(self, data):
+    def fit(self, data):
         """
         Fit each of the models in the group.
 
@@ -244,7 +259,7 @@ def fit_models(self, data):
             Keys are the segment names.
 
         """
-        return {name: self.models[name].fit_model(df)
+        return {name: self.models[name].fit(df)
                 for name, df in self._iter_groups(data)}
 
     def predict(self, data):

urbansim/models/tests/test_regression.py

@@ -82,7 +82,7 @@ def test_RegressionModel(test_df):
     with pytest.raises(RuntimeError):
         model.predict(test_df)
 
-    fit = model.fit_model(test_df)
+    fit = model.fit(test_df)
     assert isinstance(fit, RegressionResultsWrapper)
     assert isinstance(model.model_fit, RegressionResultsWrapper)
 
@@ -104,7 +104,7 @@ def test_RegressionModelGroup(groupby_df):
     assert isinstance(hmg.models['y'], regression.RegressionModel)
     assert hmg.models['y'].name == 'y'
 
-    fits = hmg.fit_models(groupby_df)
+    fits = hmg.fit(groupby_df)
     assert isinstance(fits['x'], RegressionResultsWrapper)
     assert isinstance(fits['y'], RegressionResultsWrapper)