Merge pull request scikit-learn-contrib#153 from scikit-learn-contrib…

…/versioneering

Store pyearth version information in the Earth object.

pyearth/earth.py

@@ -7,7 +7,8 @@
                                       check_X_y)
 import numpy as np
 from scipy import sparse
-
+from ._version import get_versions
+__version__ = get_versions()['version']
 
 class Earth(BaseEstimator, RegressorMixin, TransformerMixin):
 
@@ -254,6 +255,11 @@ class Earth(BaseEstimator, RegressorMixin, TransformerMixin):
         array of shape m. If several feature importance types are
         specified, then it is dict where each key is a feature importance type
         name and its corresponding value is an array of shape m.
+    
+    `_version`: string
+        The version of py-earth in which the Earth object was originally 
+        created.  This information may be useful when dealing with 
+        serialized Earth objects.
 
 
     References
@@ -317,6 +323,7 @@ def __init__(self, max_terms=None, max_degree=None, allow_missing=False,
         self.enable_pruning = enable_pruning
         self.feature_importance_type = feature_importance_type
         self.verbose = verbose
+        self._version = __version__
 
     def __eq__(self, other):
         if self.__class__ is not other.__class__:

pyearth/test/test_earth.py

@@ -18,6 +18,7 @@
 from pyearth._basis import (Basis, ConstantBasisFunction,
                             HingeBasisFunction, LinearBasisFunction)
 from pyearth import Earth
+import pyearth
 
 numpy.random.seed(0)
 
@@ -306,6 +307,16 @@ def test_pickle_compatibility():
     assert_true(model_copy.basis_[0] is model_copy.basis_[1]._get_root())
 
 
+def test_pickle_version_storage():
+    earth = Earth(**default_params)
+    model = earth.fit(X, y)
+    assert_equal(model._version, pyearth.__version__)
+    model._version = 'hello'
+    assert_equal(model._version,'hello')
+    model_copy = pickle.loads(pickle.dumps(model))
+    assert_equal(model_copy._version, model._version)
+
+
 def test_copy_compatibility():
     model = Earth(**default_params).fit(X, y)
     model_copy = copy.copy(model)