hoisted ax to Visualizer base class and model name to ScoreVisualizer…

… base class, closes #62

yellowbrick/base.py

@@ -38,6 +38,7 @@ class Visualizer(BaseEstimator):
     """
 
     def __init__(self, **kwargs):
+        self.ax = None
         self.size  = kwargs.pop('size', None)
         self.color = kwargs.pop('color', None)
 
@@ -89,6 +90,8 @@ def __init__(self, model, **kwargs):
         self.estimator = model
         super(ScoreVisualizer, self).__init__(**kwargs)
 
+        self.name = get_model_name(self.estimator)
+
     def fit(self, X, y=None, **kwargs):
         self.estimator.fit(X, y, **kwargs)
         return self

yellowbrick/classifier.py

@@ -49,6 +49,7 @@ def __init__(self, model, **kwargs):
 
         super(ClassificationScoreVisualizer, self).__init__(model, **kwargs)
 
+
 ##########################################################################
 ## Classification Report
 ##########################################################################
@@ -86,11 +87,13 @@ def __init__(self, model, classes=None, **kwargs):
         """
         super(ClassificationReport, self).__init__(model, **kwargs)
 
-        # TODO: hoist
-        self.estimator = model
-        self.ax = None
+        ## hoisted to Visualizer base class
+        # self.ax = None
+
+        ## hoisted to ScoreVisualizer base class
+        # self.estimator = model
+        # self.name = get_model_name(self.estimator)
 
-        self.name = get_model_name(self.estimator)
         self.cmap = kwargs.pop('cmap', ddlheatmap)
         self.classes_ = classes
 
@@ -220,9 +223,11 @@ def __init__(self, model, **kwargs):
         """
         super(ROCAUC, self).__init__(model, **kwargs)
 
-        # TODO hoist to main
-        self.name = get_model_name(self.estimator)
-        self.ax = None
+        ## hoisted to Visualizer base class
+        # self.ax = None
+
+        ## hoisted to ScoreVisualizer base class
+        # self.name = get_model_name(self.estimator)
 
         # TODO refactor to use new Yellowbrick color utils
         self.colors = {
@@ -343,11 +348,13 @@ def __init__(self, model, classes=None, **kwargs):
         """
         super(ClassBalance, self).__init__(model, **kwargs)
 
-        # TODO: hoist
-        self.estimator = model
-        self.ax = None
+        ## hoisted to Visualizer base class
+        # self.ax = None
+
+        ## hoisted to ScoreVisualizer base class
+        # self.estimator = model
+        # self.name      = get_model_name(self.estimator)
 
-        self.name      = get_model_name(self.estimator)
         self.colors    = kwargs.pop('colors', YELLOWBRICK_PALETTES['paired'])
         self.classes_  = classes
 
@@ -387,7 +394,7 @@ def score(self, X, y=None, **kwargs):
 
         y : ndarray or Series of length n
             An array or series of target or class values
-            
+
         Returns
         ------
 

yellowbrick/features/base.py

@@ -42,8 +42,9 @@ def __init__(self, ax=None, **kwargs):
         super(FeatureVisualizer, self).__init__(**kwargs)
 
         # The figure params
-        # TODO: hoist to a higher level base class
-        self.ax = ax
+
+        ## hoisted to Visualizer base class
+        # self.ax = ax
 
     def fit(self, X, y=None, **fit_params):
         """

yellowbrick/regressor.py

@@ -77,8 +77,12 @@ def __init__(self, model, **kwargs):
 
         super(PredictionError, self).__init__(model, **kwargs)
 
-        self.ax = None
-        self.name = get_model_name(self.estimator)
+        ## hoisted to Visualizer base class
+        # self.ax = None
+
+        ## hoisted to ScoreVisualizer
+        # self.name = get_model_name(self.estimator)
+
         self.colors = {
             'point': kwargs.pop('point_color', '#F2BE2C'),
             'line': kwargs.pop('line_color', '#2B94E9'),
@@ -193,8 +197,11 @@ def __init__(self, model, **kwargs):
 
         super(ResidualsPlot, self).__init__(model, **kwargs)
 
-        self.ax = None
-        self.name = get_model_name(self.estimator)
+        ## hoisted to Visualizer base class
+        # self.ax = None
+
+        ## hoisted to ScoreVisualizer
+        # self.name = get_model_name(self.estimator)
 
         # TODO Is there a better way to differentiate between train and test points?
         # We'd like to color them differently in draw...
@@ -284,7 +291,7 @@ def draw(self, y_pred, residuals, train=False, **kwargs):
 
     def poof(self):
         """
-        
+
         Returns
         ------