fix missing module in .travis.yml, README.md, setup.py. split tests. …

…improved filenames

.travis.yml

@@ -46,13 +46,13 @@ install:
         conda create --yes -n test python="3.6";
       fi
     - source activate test
-    - pip install numpy scipy matplotlib pip nose sphinx==1.4 gpy torch
+    - pip install numpy scipy matplotlib pip nose sphinx==1.4 gpy torch sklearn
     - pip install setuptools
     - pip install coveralls
     - pip install coverage
     - python setup.py install
 
-script: 
+script:
     - coverage run test.py
 
 after_success:

README.md

@@ -47,7 +47,7 @@
 See the [**Examples**](#examples) section below and the [**Tutorials**](tutorials/README.md) to have an idea of the potential of this package.
 
 ## Dependencies and installation
-**EZyRB** requires `numpy`, `scipy`, `matplotlib`, `vtk`, `nose` (for local
+**EZyRB** requires `numpy`, `scipy`, `sklearn`, `matplotlib`, `vtk`, `nose` (for local
 test) and `sphinx` (to generate the documentation).The coe has been tested with
 Python3.5 version, but it should be compatible with Python3. It can be
 installed using `pip` or directly from the source code.

ezyrb/__init__.py

@@ -14,5 +14,5 @@
 from .gpr import GPR
 from .reducedordermodel import ReducedOrderModel
 from .ann import ANN
-from .kneighborsregressor import KNeighborsRegressor
-from .radius_neighborsregressor import RadiusNeighborsRegressor
+from .kneighbors_regressor import KNeighborsRegressor
+from .radius_neighbors_regressor import RadiusNeighborsRegressor

ezyrb/neighborsregressor.py → ezyrb/neighbors_regressor.py

@@ -11,7 +11,7 @@ class NeighborsRegressor(Approximation):
     """
 
     def __init__(self, **kwargs):
-        raise ValueError("This class must be extended, not used.")
+        raise NotImplementedError("This class must be extended, not used.")
 
     def fit(self, points, values):
         """

setup.py

@@ -17,7 +17,7 @@
 KEYWORDS='pod interpolation reduced-basis model-order-reduction'
 
 REQUIRED = [
-    'future', 'numpy', 'scipy',	'matplotlib', 'GPy'
+    'future', 'numpy', 'scipy',	'matplotlib', 'GPy', 'sklearn'
 ]
 
 EXTRAS = {

tests/test_k_neighbors_regressor.py

@@ -56,12 +56,13 @@ def test_with_db_predict(self):
         assert rom.predict([2]) == 5
         assert rom.predict([3]) == 3
 
-    def test_wrong(self):
+    def test_wrong1(self):
         # wrong number of params
         with self.assertRaises(Exception):
             reg = KNeighborsRegressor()
             reg.fit([[1, 2], [6,], [8, 9]], [[1, 0], [20, 5], [8, 6]])
 
+    def test_wrong2(self):
         # wrong number of values
         with self.assertRaises(Exception):
             reg = KNeighborsRegressor()

tests/test_radius_neighbors_regressor.py

@@ -56,12 +56,13 @@ def test_with_db_predict(self):
         assert rom.predict([2]) == 5
         assert rom.predict([3]) == 3
 
-    def test_wrong(self):
+    def test_wrong1(self):
         # wrong number of params
         with self.assertRaises(Exception):
             reg = RadiusNeighborsRegressor()
             reg.fit([[1, 2], [6,], [8, 9]], [[1, 0], [20, 5], [8, 6]])
 
+    def test_wrong2(self):
         # wrong number of values
         with self.assertRaises(Exception):
             reg = RadiusNeighborsRegressor()