run black on code. Final changes for #7

lib/catnip/tests/test_preparation.py

@@ -72,26 +72,26 @@ def tearDown(self):
         pass
 
     def test_get_xy_noborder(self):
-        '''
+        """
         Test basic version of _get_xy_noborder
-        '''
+        """
 
         indices_expected = (2, 4, 1, 4)
 
         # set up test data
         d = np.full((5, 5), True)
         # fill some values
-        d[3,2]=False
-        d[3,3,]=False
-        d[1,3]=False
+        d[3, 2] = False
+        d[3, 3,] = False
+        d[1, 3] = False
 
         indices_actual = _get_xy_noborder(d)
         self.assertEqual(indices_expected, indices_actual)
 
     def test_get_xy_noborder_false(self):
-        '''
+        """
         Test get_xy_noborder when mask all False
-        '''
+        """
 
         indices_expected = (0, 5, 0, 5)
 
@@ -102,9 +102,9 @@ def test_get_xy_noborder_false(self):
         self.assertEqual(indices_expected, indices_actual)
 
     def test_get_xy_noborder_true(self):
-        '''
+        """
         Test _get_xy_noborder when all True - error
-        '''
+        """
 
         # set up test data
         d = np.full((5, 5), True)
@@ -161,29 +161,32 @@ def test_add_coord_system(self):
         self.assertRaises(TypeError, add_coord_system, self.mslp_daily_cube)
 
     def test_extract_rot_cube(self):
-        '''
+        """
         Test the shape of the extracted cube and min/max
         lat and lon
-        '''
+        """
 
         # define box to extract
         min_lat = 50
         min_lon = -10
         max_lat = 60
         max_lon = 0
 
-        tcube = self.rcm_monthly_cube.extract_strict('air_temperature')
-        extracted_cube = extract_rot_cube(tcube, min_lat, min_lon,
-                                   max_lat, max_lon)
+        tcube = self.rcm_monthly_cube.extract_strict("air_temperature")
+        extracted_cube = extract_rot_cube(tcube, min_lat, min_lon, max_lat, max_lon)
         self.assertEqual(np.shape(extracted_cube.data), (2, 102, 78))
-        self.assertEqual(np.max(extracted_cube.coord('latitude').points),
-                         61.365291870327816)
-        self.assertEqual(np.min(extracted_cube.coord('latitude').points),
-                         48.213032844268646)
-        self.assertEqual(np.max(extracted_cube.coord('longitude').points),
-                         3.642576550089792)
-        self.assertEqual(np.min(extracted_cube.coord('longitude').points),
-                         -16.29169201066359)
+        self.assertEqual(
+            np.max(extracted_cube.coord("latitude").points), 61.365291870327816
+        )
+        self.assertEqual(
+            np.min(extracted_cube.coord("latitude").points), 48.213032844268646
+        )
+        self.assertEqual(
+            np.max(extracted_cube.coord("longitude").points), 3.642576550089792
+        )
+        self.assertEqual(
+            np.min(extracted_cube.coord("longitude").points), -16.29169201066359
+        )
 
     def test_add_time_coord_cats(self):
         cube = self.mslp_daily_cube.copy()

lib/catnip/tests/test_visualisation.py

@@ -38,6 +38,7 @@
 import imagehash
 from PIL import Image
 from catnip.visualisation import vector_plot, plot_regress
+
 # import matplotlob after catnip vector plot as that sets the Agg
 # backend
 import matplotlib.pyplot as plt
@@ -48,23 +49,23 @@
 #: Default maximum perceptual hash hamming distance.
 _HAMMING_DISTANCE = 0
 
+
 def _compare_images(figure, expected_filename):
-    '''
+    """
     Use imagehash to compare images fast and reliably.
 
     Returns True if they match within tolerance, false
     otherwise
-    '''
+    """
     img_buffer = io.BytesIO()
     figure.savefig(img_buffer, format="png")
     img_buffer.seek(0)
     gen_phash = imagehash.phash(Image.open(img_buffer), hash_size=_HASH_SIZE)
-    exp_phash = imagehash.phash(
-        Image.open(expected_filename), hash_size=_HASH_SIZE
-    )
+    exp_phash = imagehash.phash(Image.open(expected_filename), hash_size=_HASH_SIZE)
     distance = abs(gen_phash - exp_phash)
     return distance <= _HAMMING_DISTANCE
 
+
 class TestVisualisation(unittest.TestCase):
     """Unittest class for visualisation module"""
 
@@ -74,10 +75,10 @@ def setUpClass(self):
         file2 = os.path.join(conf.DATA_DIR, "gcm_monthly.pp")
         self.rcm_monthly_cube = iris.load(file1)
         self.gcm_monthly_cube = iris.load(file2)
-        self.gcm_u = self.gcm_monthly_cube.extract_strict('x_wind')
-        self.gcm_v = self.gcm_monthly_cube.extract_strict('y_wind')
-        self.rcm_u = self.rcm_monthly_cube.extract_strict('x_wind')[0,...]
-        self.rcm_v = self.rcm_monthly_cube.extract_strict('y_wind')[0,...]
+        self.gcm_u = self.gcm_monthly_cube.extract_strict("x_wind")
+        self.gcm_v = self.gcm_monthly_cube.extract_strict("y_wind")
+        self.rcm_u = self.rcm_monthly_cube.extract_strict("x_wind")[0, ...]
+        self.rcm_v = self.rcm_monthly_cube.extract_strict("y_wind")[0, ...]
 
     @classmethod
     def tearDownClass(cls):
@@ -109,7 +110,7 @@ def test_vector_plot_gcm_title(self):
 
         expected_png = os.path.join(conf.KGO_DIR, "gcm_ws_title.png")
 
-        vector_plot(self.gcm_u, self.gcm_v, title='GCM W/S')
+        vector_plot(self.gcm_u, self.gcm_v, title="GCM W/S")
 
         actual_fig = plt.gcf()
         self.assertTrue(_compare_images(actual_fig, expected_png))
@@ -136,13 +137,13 @@ def test_vector_plot_gcm_n10(self):
         vector_plot(self.gcm_u, self.gcm_v, npts=10)
 
         actual_fig = plt.gcf()
-        plt.savefig('/scratch/fris/gcm_ws_n10.png')
+        plt.savefig("/scratch/fris/gcm_ws_n10.png")
         self.assertTrue(_compare_images(actual_fig, expected_png))
 
     def test_vector_rot_error(self):
-        '''
+        """
         Test that passing a global field gives an Exception
-        '''
+        """
 
         self.assertRaises(Exception, vector_plot, self.gcm_u, self.gcm_v, unrotate=True)