Remove experimental LCh support from master branch

constants.py

@@ -17,4 +17,4 @@
 
 # list of color spaces that colorspacious can correctly perform a deltaE calculation in
 CSPACE_LIST = ['CAM02-UCS', 'CAM02-LCD', 'CAM02-SCD',
-               'CIELab', 'sRGB1', 'sRGB1-linear', 'XYZ1', 'CIELCh']
+               'CIELab', 'sRGB1', 'sRGB1-linear', 'XYZ1']

palettizer.py

@@ -11,7 +11,6 @@
 import sg_extensions
 
 
-
 def index2rgb(arr, pal):
     channels = [pal[arr, i] for i in range(3)]
     return np.stack(channels, axis=-1)
@@ -26,27 +25,14 @@ def counter(iterable, message='', id='single', end=None):
             break
 
 
-def arc_dist(arr1, arr2):
-    return np.radians(np.abs(180 - ((180 + arr2[..., 2] - arr1[..., 2]) % 360))) * ((arr2[..., 1] + arr1[..., 1]) / 2)
-
-
-# special distance function for cylindrical coordinates
-def cylinder_deltaE(color1, color2, input_space="sRGB1", uniform_space="CIELCh"):
-    uniform1 = cspace_convert(color1, input_space, uniform_space)
-    uniform2 = cspace_convert(color2, input_space, uniform_space)
-    return np.sqrt(np.sum((uniform1[..., :2] - uniform2[..., :2]) ** 2, axis=-1)) + arc_dist(uniform1, uniform2)
-
-
 def split_deltaE(image, color2, input_space="sRGB1", uniform_space="CAM02-UCS"):
     split_val = 25000 * np.ceil(virtual_memory()[1] / 1024**3)
     splits = math.ceil((len(color2)**0.5555) * image.shape[0] * image.shape[1] / split_val)
     # splits = math.ceil((sys.getsizeof(image) * sys.getsizeof(color2)) / virtual_memory()[1])
     image_sliced = np.array_split(image, splits)
     pool = multi.Pool(processes=min([multi.cpu_count(), splits, ]))
-    if uniform_space == 'CIELCh':
-        image_output_sliced = pool.imap(lambda x: cylinder_deltaE(x, color2, input_space, uniform_space), image_sliced)
-    else:
-        image_output_sliced = pool.imap(lambda x: deltaE(x, color2, input_space, uniform_space), image_sliced)
+
+    image_output_sliced = pool.imap(lambda x: deltaE(x, color2, input_space, uniform_space), image_sliced)
 
     image_output_sliced = [a for a in counter(image_output_sliced, 'Quantizing...', end=splits)]
     pool.close()