# Licensed under an MIT open source license - see LICENSE


'''
Test functions for Cramer
'''

import numpy.testing as npt

from ..statistics import Cramer_Distance
from ._testing_data import \
    dataset1, dataset2, computed_data, computed_distances


def test_cramer():
    tester = \
        Cramer_Distance(dataset1["cube"],
                        dataset2["cube"],
                        noise_value1=0.1,
                        noise_value2=0.1).distance_metric(normalize=False)

    npt.assert_allclose(tester.data_matrix1,
                        computed_data["cramer_val"])
    npt.assert_almost_equal(tester.distance,
                            computed_distances['cramer_distance'])


def test_cramer_spatial_diff():

    small_data = dataset1["cube"][0][:, :26, :26]

    tester2 = Cramer_Distance(small_data, dataset2["cube"])
    tester2.distance_metric(normalize=False)
    tester3 = Cramer_Distance(dataset2["cube"], small_data)
    tester3.distance_metric(normalize=False)

    npt.assert_almost_equal(tester2.distance, tester3.distance)

# Licensed under an MIT open source license - see LICENSE


'''
Test functions for Cramer
'''

from unittest import TestCase

import numpy as np
import numpy.testing as npt

from ..statistics import Cramer_Distance
from ._testing_data import \
    dataset1, dataset2, computed_data, computed_distances


class testCramer(TestCase):

    def test_cramer(self):
        self.tester = \
            Cramer_Distance(dataset1["cube"],
                            dataset2["cube"],
                            noise_value1=0.1,
                            noise_value2=0.1).distance_metric(normalize=False)

        npt.assert_allclose(self.tester.data_matrix1,
                            computed_data["cramer_val"])
        npt.assert_almost_equal(self.tester.distance,
                                computed_distances['cramer_distance'])

    def test_cramer_spatial_diff(self):

        small_data = dataset1["cube"][0][:, :26, :26]

        self.tester2 = Cramer_Distance(small_data, dataset2["cube"])
        self.tester2.distance_metric(normalize=False)
        self.tester3 = Cramer_Distance(dataset2["cube"], small_data)
        self.tester3.distance_metric(normalize=False)

        npt.assert_almost_equal(self.tester2.distance, self.tester3.distance)

--- 
+++ 
@@ -5,9 +5,6 @@
 Test functions for Cramer
 '''
 
-from unittest import TestCase
-
-import numpy as np
 import numpy.testing as npt
 
 from ..statistics import Cramer_Distance
@@ -15,27 +12,26 @@
     dataset1, dataset2, computed_data, computed_distances
 
 
-class testCramer(TestCase):
+def test_cramer():
+    tester = \
+        Cramer_Distance(dataset1["cube"],
+                        dataset2["cube"],
+                        noise_value1=0.1,
+                        noise_value2=0.1).distance_metric(normalize=False)
 
-    def test_cramer(self):
-        self.tester = \
-            Cramer_Distance(dataset1["cube"],
-                            dataset2["cube"],
-                            noise_value1=0.1,
-                            noise_value2=0.1).distance_metric(normalize=False)
+    npt.assert_allclose(tester.data_matrix1,
+                        computed_data["cramer_val"])
+    npt.assert_almost_equal(tester.distance,
+                            computed_distances['cramer_distance'])
 
-        npt.assert_allclose(self.tester.data_matrix1,
-                            computed_data["cramer_val"])
-        npt.assert_almost_equal(self.tester.distance,
-                                computed_distances['cramer_distance'])
 
-    def test_cramer_spatial_diff(self):
+def test_cramer_spatial_diff():
 
-        small_data = dataset1["cube"][0][:, :26, :26]
+    small_data = dataset1["cube"][0][:, :26, :26]
 
-        self.tester2 = Cramer_Distance(small_data, dataset2["cube"])
-        self.tester2.distance_metric(normalize=False)
-        self.tester3 = Cramer_Distance(dataset2["cube"], small_data)
-        self.tester3.distance_metric(normalize=False)
+    tester2 = Cramer_Distance(small_data, dataset2["cube"])
+    tester2.distance_metric(normalize=False)
+    tester3 = Cramer_Distance(dataset2["cube"], small_data)
+    tester3.distance_metric(normalize=False)
 
-        npt.assert_almost_equal(self.tester2.distance, self.tester3.distance)
+    npt.assert_almost_equal(tester2.distance, tester3.distance)
Remove importing UnitCase from Cramer tests
