fused types

skimage/feature/_texture.pyx

@@ -13,23 +13,17 @@ cdef extern from "numpy/npy_math.h":
     double NAN "NPY_NAN"
 
 
-#ctypedef fused uint_8_16:
-#    cython.uint8_t
-#    cython.uint16_t
-
-
-#cpdef char_or_float plus_one(char_or_float var):
-#    return var + 1
-
-
-#def show_me():
-#    cdef:
-#        cython.char a = 127
-#        cython.float b = 127
-#    print 'char', plus_one(a)
-#    print 'float', plus_one(b)
-    
-def _glcm_loop(cnp.uint16_t[:, ::1] image, double[:] distances,
+ctypedef fused uint_8_16:
+    cnp.uint8_t
+    cnp.uint16_t
+    cnp.uint32_t
+    cnp.uint64_t
+    cnp.int8_t
+    cnp.int16_t
+    cnp.int32_t
+    cnp.int64_t
+        
+def _glcm_loop(uint_8_16[:, ::1] image, double[:] distances,
                double[:] angles, Py_ssize_t levels,
                cnp.uint32_t[:, :, :, ::1] out):
     """Perform co-occurrence matrix accumulation.
@@ -59,7 +53,7 @@ def _glcm_loop(cnp.uint16_t[:, ::1] image, double[:] distances,
 
     cdef:
         Py_ssize_t a_idx, d_idx, r, c, rows, cols, row, col
-        cnp.uint16_t i, j
+        uint_8_16 i, j
         cnp.float64_t angle, distance
 
     with nogil:

skimage/feature/texture.py

@@ -112,7 +112,7 @@ def greycomatrix(image, distances, angles, levels=None, symmetric=False,
         raise ValueError("Float images are not supported by greycomatrix. "
                          "The image needs to be cast to an unsigned integer type.")
     
-    # for 16 bit images, levels must be set.
+    # for 16 bit images (or larger), levels must be set.
     if image.dtype != np.uint8:
         if levels is None:
             raise ValueError("The levels argument is required for data types other than uint8. "
@@ -125,7 +125,7 @@ def greycomatrix(image, distances, angles, levels=None, symmetric=False,
     assert image_max < levels, "The image maximum needs to be smaller than `levels`."
 
     # image is cast to uint16 (because of fixed typing in cython) 
-    image = image.astype(np.uint16)
+    #image = image.astype(np.uint16)
 
     distances = np.ascontiguousarray(distances, dtype=np.float64)
     angles = np.ascontiguousarray(angles, dtype=np.float64)