Avoid signed vs. unsigned comparison warning for loop variables in memoryview tutorial.

docs/examples/userguide/memoryviews/quickstart.pyx

-from cython.view cimport array as cvarray
-import numpy as np
-
-# Memoryview on a NumPy array
-narr = np.arange(27, dtype=np.dtype("i")).reshape((3, 3, 3))
-cdef int [:, :, :] narr_view = narr
-
-# Memoryview on a C array
-cdef int carr[3][3][3]
-cdef int [:, :, :] carr_view = carr
-
-# Memoryview on a Cython array
-cyarr = cvarray(shape=(3, 3, 3), itemsize=sizeof(int), format="i")
-cdef int [:, :, :] cyarr_view = cyarr
-
-# Show the sum of all the arrays before altering it
-print("NumPy sum of the NumPy array before assignments: %s" % narr.sum())
-
-# We can copy the values from one memoryview into another using a single
-# statement, by either indexing with ... or (NumPy-style) with a colon.
-carr_view[...] = narr_view
-cyarr_view[:] = narr_view
-# NumPy-style syntax for assigning a single value to all elements.
-narr_view[:, :, :] = 3
-
-# Just to distinguish the arrays
-carr_view[0, 0, 0] = 100
-cyarr_view[0, 0, 0] = 1000
-
-# Assigning into the memoryview on the NumPy array alters the latter
-print("NumPy sum of NumPy array after assignments: %s" % narr.sum())
-
-# A function using a memoryview does not usually need the GIL
-cpdef int sum3d(int[:, :, :] arr) nogil:
-    cdef size_t i, j, k
-    cdef int total = 0
-    I = arr.shape[0]
-    J = arr.shape[1]
-    K = arr.shape[2]
-    for i in range(I):
-        for j in range(J):
-            for k in range(K):
-                total += arr[i, j, k]
-    return total
-
-# A function accepting a memoryview knows how to use a NumPy array,
-# a C array, a Cython array...
-print("Memoryview sum of NumPy array is %s" % sum3d(narr))
-print("Memoryview sum of C array is %s" % sum3d(carr))
-print("Memoryview sum of Cython array is %s" % sum3d(cyarr))
-# ... and of course, a memoryview.
-print("Memoryview sum of C memoryview is %s" % sum3d(carr_view))
+from cython.view cimport array as cvarray
+import numpy as np
+
+# Memoryview on a NumPy array
+narr = np.arange(27, dtype=np.dtype("i")).reshape((3, 3, 3))
+cdef int [:, :, :] narr_view = narr
+
+# Memoryview on a C array
+cdef int carr[3][3][3]
+cdef int [:, :, :] carr_view = carr
+
+# Memoryview on a Cython array
+cyarr = cvarray(shape=(3, 3, 3), itemsize=sizeof(int), format="i")
+cdef int [:, :, :] cyarr_view = cyarr
+
+# Show the sum of all the arrays before altering it
+print("NumPy sum of the NumPy array before assignments: %s" % narr.sum())
+
+# We can copy the values from one memoryview into another using a single
+# statement, by either indexing with ... or (NumPy-style) with a colon.
+carr_view[...] = narr_view
+cyarr_view[:] = narr_view
+# NumPy-style syntax for assigning a single value to all elements.
+narr_view[:, :, :] = 3
+
+# Just to distinguish the arrays
+carr_view[0, 0, 0] = 100
+cyarr_view[0, 0, 0] = 1000
+
+# Assigning into the memoryview on the NumPy array alters the latter
+print("NumPy sum of NumPy array after assignments: %s" % narr.sum())
+
+# A function using a memoryview does not usually need the GIL
+cpdef int sum3d(int[:, :, :] arr) nogil:
+    cdef size_t i, j, k, I, J, K
+    cdef int total = 0
+    I = arr.shape[0]
+    J = arr.shape[1]
+    K = arr.shape[2]
+    for i in range(I):
+        for j in range(J):
+            for k in range(K):
+                total += arr[i, j, k]
+    return total
+
+# A function accepting a memoryview knows how to use a NumPy array,
+# a C array, a Cython array...
+print("Memoryview sum of NumPy array is %s" % sum3d(narr))
+print("Memoryview sum of C array is %s" % sum3d(carr))
+print("Memoryview sum of Cython array is %s" % sum3d(cyarr))
+# ... and of course, a memoryview.
+print("Memoryview sum of C memoryview is %s" % sum3d(carr_view))