BUG: sparse/_csparsetools: work around dtype equality bugs in earlier…

… numpy versions

scipy/sparse/_csparsetools.pyx

@@ -33,24 +33,34 @@ ctypedef fused value_t:
     long double complex
 
 
+# Use .char to work around dtype comparison bugs in earlier Numpy
+# versions
+
 DTYPE_NAME_MAP = {
-    np.dtype(np.bool_): "npy_bool",
-    np.dtype(np.int8): "npy_int8",
-    np.dtype(np.uint8): "npy_uint8",
-    np.dtype(np.int16): "npy_int16",
-    np.dtype(np.uint16): "npy_uint16",
-    np.dtype(np.int32): "npy_int32",
-    np.dtype(np.uint32): "npy_uint32",
-    np.dtype(np.int64): "npy_int64",
-    np.dtype(np.uint64): "npy_uint64",
-    np.dtype(np.float32): "npy_float32",
-    np.dtype(np.float64): "npy_float64",
-    np.dtype(np.longdouble): "long double",
-    np.dtype(np.complex64): "float complex",
-    np.dtype(np.complex128): "double complex",
-    np.dtype(np.clongdouble): "long double complex"
+    np.dtype(np.bool_).char: "npy_bool",
+    np.dtype(np.int8).char: "npy_int8",
+    np.dtype(np.uint8).char: "npy_uint8",
+    np.dtype(np.int16).char: "npy_int16",
+    np.dtype(np.uint16).char: "npy_uint16",
+    np.dtype(np.int32).char: "npy_int32",
+    np.dtype(np.uint32).char: "npy_uint32",
+    np.dtype(np.int64).char: "npy_int64",
+    np.dtype(np.uint64).char: "npy_uint64",
+    np.dtype(np.float32).char: "npy_float32",
+    np.dtype(np.float64).char: "npy_float64",
+    np.dtype(np.longdouble).char: "long double",
+    np.dtype(np.complex64).char: "float complex",
+    np.dtype(np.complex128).char: "double complex",
+    np.dtype(np.clongdouble).char: "long double complex"
 }
 
+if np.dtype('q').itemsize == 4:
+    DTYPE_NAME_MAP['q'] = "npy_int32"
+    DTYPE_NAME_MAP['Q'] = "npy_uint32"
+elif np.dtype('q').itemsize == 8:
+    DTYPE_NAME_MAP['q'] = "npy_int64"
+    DTYPE_NAME_MAP['Q'] = "npy_uint64"
+
 
 def prepare_index_for_memoryview(cnp.ndarray i, cnp.ndarray j, cnp.ndarray x=None):
     """
@@ -135,10 +145,11 @@ def lil_insert(cnp.npy_intp M, cnp.npy_intp N, object[:] rows, object[:] datas,
     """
     Work around broken Cython fused type dispatch
     """
+    dtype = np.dtype(dtype)
     try:
-        key = DTYPE_NAME_MAP[dtype]
+        key = DTYPE_NAME_MAP[dtype.char]
     except KeyError:
-        raise ValueError("Unsupported data type: %r" % (dtype,))
+        raise ValueError("Unsupported data type: %r" % (dtype.char,))
 
     _lil_insert[key](M, N, rows, datas, i, j, x)
 
@@ -239,10 +250,13 @@ def lil_fancy_set(cnp.npy_intp M, cnp.npy_intp N,
     Work around broken Cython fused type dispatch
     """
     try:
-        key = DTYPE_NAME_MAP[values.dtype]
-        ikey = DTYPE_NAME_MAP[i_idx.dtype]
+        key = DTYPE_NAME_MAP[values.dtype.char]
+    except KeyError:
+        raise ValueError("Unsupported data type: %r" % (values.dtype.char,))
+    try:
+        ikey = DTYPE_NAME_MAP[i_idx.dtype.char]
     except KeyError:
-        raise ValueError("Unsupported data type")
+        raise ValueError("Unsupported data type: %r" % (i_idx.dtype.char,))
 
     if key != "npy_bool":
         _lil_fancy_set[ikey, key](M, N, rows, data, i_idx, j_idx, values)