Clean up PR for merge

README.md

@@ -1,10 +1,15 @@
-[![Build Status](https://travis-ci.org/rhiever/tpot.svg?branch=master)](https://travis-ci.org/rhiever/tpot)
-[![Code Health](https://landscape.io/github/rhiever/tpot/master/landscape.svg?style=flat)](https://landscape.io/github/rhiever/tpot/master)
-[![Coverage Status](https://coveralls.io/repos/rhiever/tpot/badge.svg?branch=master&service=github)](https://coveralls.io/github/rhiever/tpot?branch=master)
-![Python 2.7](https://img.shields.io/badge/python-2.7-blue.svg)
-![Python 3.5](https://img.shields.io/badge/python-3.5-blue.svg)
+Master status: [![Master Build Status](https://travis-ci.org/rhiever/tpot.svg?branch=master)](https://travis-ci.org/rhiever/tpot)
+[![Master Code Health](https://landscape.io/github/rhiever/tpot/master/landscape.svg?style=flat)](https://landscape.io/github/rhiever/tpot/master)
+[![Master Coverage Status](https://coveralls.io/repos/rhiever/tpot/badge.svg?branch=master&service=github)](https://coveralls.io/github/rhiever/tpot?branch=master)
+
+Development status: [![Development Build Status](https://travis-ci.org/rhiever/tpot.svg?branch=development)](https://travis-ci.org/rhiever/tpot)
+[![Development Code Health](https://landscape.io/github/rhiever/tpot/development/landscape.svg?style=flat)](https://landscape.io/github/rhiever/tpot/development)
+[![Development Coverage Status](https://coveralls.io/repos/rhiever/tpot/badge.svg?branch=development&service=github)](https://coveralls.io/github/rhiever/tpot?branch=development)
+
+Package information: ![Python 2.7](https://img.shields.io/badge/python-2.7-blue.svg)
+![Python 3.5](https://img.shields.io/badge/python-3.6-blue.svg)
 ![License](https://img.shields.io/badge/license-GPLv3-blue.svg)
-[![PyPI version](https://badge.fury.io/py/tpot.svg)](https://badge.fury.io/py/tpot)
+[![PyPI version](https://badge.fury.io/py/TPOT.svg)](https://badge.fury.io/py/TPOT)
 
 [![Join the chat at https://gitter.im/rhiever/tpot](https://badges.gitter.im/rhiever/tpot.svg)](https://gitter.im/rhiever/tpot?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
 

docs/sitemap.xml

@@ -31,7 +31,6 @@
      <lastmod>2017-03-22</lastmod>
      <changefreq>daily</changefreq>
     </url>
-
 
 
     <url>
@@ -65,4 +64,4 @@
     </url>
 
 
-</urlset>
+</urlset>

tests.py

@@ -314,7 +314,6 @@ def isclose(a, b, rel_tol=1e-09, abs_tol=0.0):
     assert not np.allclose(cv_score1, cv_score_weight)
     assert isclose(known_score, score)
 
-
 def test_predict():
     """Assert that the TPOT predict function raises a RuntimeError when no optimized pipeline exists"""
 
@@ -342,7 +341,6 @@ def test_predict_2():
 
     assert result.shape == (testing_features.shape[0],)
 
-
 def test_predict_proba():
     """Assert that the TPOT predict_proba function returns a numpy matrix of shape (num_testing_rows, num_testing_classes)"""
 
@@ -400,7 +398,6 @@ def test_warm_start():
 
     assert tpot_obj._pop == first_pop
 
-
 def test_fit():
     """Assert that the TPOT fit function provides an optimized pipeline"""
     tpot_obj = TPOTClassifier(random_state=42, population_size=1, offspring_size=2, generations=1, verbosity=0)
@@ -519,8 +516,7 @@ def test_generate_pipeline_code():
 def test_generate_import_code():
     """Assert that generate_import_code() returns the correct set of dependancies for a given pipeline"""
     tpot_obj = TPOTClassifier()
-    pipeline = creator.Individual.\
-        from_string('GaussianNB(RobustScaler(input_matrix))', tpot_obj._pset)
+    pipeline = creator.Individual.from_string('GaussianNB(RobustScaler(input_matrix))', tpot_obj._pset)
 
     expected_code = """import numpy as np
 
@@ -562,7 +558,7 @@ def test_mutNodeReplacement():
 
 
 def test_export_pipeline():
-    """Assert that exported_pipeline() generated a compile source file as expected given a fixed complex pipeline"""
+    """Assert that exported_pipeline() generated a compile source file as expected given a fixed pipeline"""
     tpot_obj = TPOTClassifier()
     pipeline_string= ('KNeighborsClassifier(CombineDFs('
     'DecisionTreeClassifier(input_matrix, DecisionTreeClassifier__criterion=gini'
@@ -603,7 +599,6 @@ def test_export_pipeline():
 """
     assert expected_code == export_pipeline(pipeline, tpot_obj.operators, tpot_obj._pset)
 
-
 def test_export_pipeline_2():
     """Assert that exported_pipeline() generated a compile source file as expected given a fixed simple pipeline (only one classifier)"""
     tpot_obj = TPOTClassifier()
@@ -659,7 +654,6 @@ def test_export_pipeline_3():
 """
     assert expected_code == export_pipeline(pipeline, tpot_obj.operators, tpot_obj._pset)
 
-
 def test_operator_export():
     """Assert that a TPOT operator can export properly with a function as a parameter to a classifier"""
     export_string = TPOTSelectKBest.export(5)

tpot/_version.py

@@ -18,4 +18,4 @@
 
 """
 
-__version__ = '0.7'
+__version__ = '0.7.0'

tpot/base.py

@@ -47,7 +47,6 @@
 from ._version import __version__
 from .operator_utils import TPOTOperatorClassFactory, Operator, ARGType, set_sample_weight
 from .export_utils import export_pipeline, expr_to_tree, generate_pipeline_code
-
 from .decorators import _timeout, _pre_test, TimedOutExc
 from .built_in_operators import CombineDFs
 
@@ -69,6 +68,7 @@ def handler(dwCtrlType, hook_sigint=_thread.interrupt_main):
         return 0
     win32api.SetConsoleCtrlHandler(handler, 1)
 
+
 class TPOTBase(BaseEstimator):
     """TPOT automatically creates and optimizes machine learning pipelines using genetic programming"""
 
@@ -612,6 +612,7 @@ def _set_param_recursive(self, pipeline_steps, parameter, value):
         """
         for (_, obj) in pipeline_steps:
             recursive_attrs = ['steps', 'transformer_list', 'estimators']
+
             for attr in recursive_attrs:
                 if hasattr(obj, attr):
                     self._set_param_recursive(getattr(obj, attr), parameter, value)
@@ -620,7 +621,6 @@ def _set_param_recursive(self, pipeline_steps, parameter, value):
                 if hasattr(obj, parameter):
                     setattr(obj, parameter, value)
 
-
     def _evaluate_individuals(self, individuals, features, classes, sample_weight = None):
         """Determines the `individual`'s fitness
 
@@ -660,7 +660,7 @@ def _evaluate_individuals(self, individuals, features, classes, sample_weight =
             # This is a fairly hacky way to prevent TPOT from getting stuck on bad pipelines and should be improved in a future release
             individual = individuals[indidx]
             individual_str = str(individual)
-            if (individual_str.count('PolynomialFeatures') > 1):
+            if individual_str.count('PolynomialFeatures') > 1:
                 if self.verbosity > 2:
                     self._pbar.write('Invalid pipeline encountered. Skipping its evaluation.')
                 fitnesses_dict[indidx] = (5000., -float('inf'))
@@ -745,6 +745,7 @@ def _wrapped_cross_val_score(sklearn_pipeline, features=features, classes=classe
                 else:
                     time.sleep(0.2)
             resulting_score_list = [-float('inf') if x == 'Timeout' else x for x in list(res_imap)]
+
         else:
             resulting_score_list = []
             for sklearn_pipeline in sklearn_pipeline_list:
@@ -775,7 +776,6 @@ def _wrapped_cross_val_score(sklearn_pipeline, features=features, classes=classe
     def _mate_operator(self, ind1, ind2):
         return gp.cxOnePoint(ind1, ind2)
 
-
     @_pre_test
     def _random_mutation_operator(self, individual):
         """Perform a replacement, insertion, or shrink mutation on an individual
@@ -801,7 +801,6 @@ def _random_mutation_operator(self, individual):
         ]
         return np.random.choice(mutation_techniques)(individual)
 
-
     def _gen_grow_safe(self, pset, min_, max_, type_=None):
         """Generate an expression where each leaf might have a different depth
         between min_ and max_.

tpot/export_utils.py

@@ -141,8 +141,6 @@ def generate_import_code(pipeline, operators):
     # number of operators
     num_op = len(operators_used)
 
-
-
     # Build dict of import requirments from list of operators
     import_relations = {}
     for op in operators:
@@ -270,7 +268,6 @@ def generate_export_pipeline_code(pipeline_tree, operators):
 
     return pipeline_text
 
-
 def process_operator(operator, operators, depth=0):
     steps = []
     op_name = operator[0]