Coerce numpy.generic instances to dtypes in SparseNdarray constructor.

This protects against callers using the former instead of the latter, as
is done in various numpy functions that accept dtype=.

Author: LTLA

src/delayedarray/SparseNdarray.py

@@ -132,6 +132,13 @@ def __init__(
             if is_masked is None:
                 is_masked = False 
 
+        # Sometimes people put the numpy data class instead of the dtype.
+        # It's a common enough mistake that we ought to catch it here.
+        if not isinstance(dtype, numpy.dtype): 
+            dtype = numpy.dtype(dtype)
+        if not isinstance(index_dtype, numpy.dtype): 
+            index_dtype = numpy.dtype(index_dtype)
+
         self._dtype = dtype
         self._index_dtype = index_dtype
         self._is_masked = is_masked

tests/test_SparseNdarray.py

@@ -117,7 +117,7 @@ def test_SparseNdarray_check(mask_rate):
     contents = mock_SparseNdarray_contents(test_shape, mask_rate=mask_rate)
     y = delayedarray.SparseNdarray(test_shape, contents)
     assert y.shape == test_shape
-    assert y.dtype == numpy.float64
+    assert y.dtype is numpy.dtype("float64")
     assert repr(y).find("SparseNdarray") > 0
     assert delayedarray.is_sparse(y)
     assert delayedarray.is_masked(y) == (mask_rate > 0)
@@ -172,9 +172,13 @@ def shorten(con, depth):
 
     empty = delayedarray.SparseNdarray(test_shape, None, dtype=numpy.dtype("int32"), index_dtype=numpy.dtype("int32"))
     assert empty.shape == test_shape
-    assert empty.dtype == numpy.int32
+    assert empty.dtype is numpy.dtype("int32")
     assert not empty.is_masked
 
+    empty = delayedarray.SparseNdarray(test_shape, None, dtype=numpy.float32, index_dtype=numpy.int32) # generics converted to dtypes
+    assert empty.dtype is numpy.dtype("float32")
+    assert empty.index_dtype is numpy.dtype("int32")
+
 
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