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BUG: sparse: Propagate dtype through CSR/CSC constructors #13403

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merged 4 commits into from
Jan 30, 2021
Merged

BUG: sparse: Propagate dtype through CSR/CSC constructors #13403

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52f53df
Fix gh-13329
perimosocordiae Jan 19, 2021
7185d00
Add a regression test
perimosocordiae Jan 19, 2021
4066b56
Fix the regression tests, and the underlying bug
perimosocordiae Jan 27, 2021
817f564
Update scipy/sparse/compressed.py
perimosocordiae Jan 29, 2021
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3 changes: 2 additions & 1 deletion scipy/sparse/compressed.py
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Expand Up @@ -51,7 +51,8 @@ def __init__(self, arg1, shape=None, dtype=None, copy=False):
if len(arg1) == 2:
# (data, ij) format
from .coo import coo_matrix
other = self.__class__(coo_matrix(arg1, shape=shape))
other = self.__class__(coo_matrix(arg1, shape=shape,
dtype=dtype))
self._set_self(other)
elif len(arg1) == 3:
# (data, indices, indptr) format
Expand Down
7 changes: 4 additions & 3 deletions scipy/sparse/coo.py
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Expand Up @@ -131,9 +131,10 @@ def __init__(self, arg1, shape=None, dtype=None, copy=False):
M, N = arg1
self._shape = check_shape((M, N))
idx_dtype = get_index_dtype(maxval=max(M, N))
data_dtype = getdtype(dtype, default=float)
self.row = np.array([], dtype=idx_dtype)
self.col = np.array([], dtype=idx_dtype)
self.data = np.array([], getdtype(dtype, default=float))
self.data = np.array([], dtype=data_dtype)
self.has_canonical_format = True
else:
try:
Expand All @@ -154,11 +155,11 @@ def __init__(self, arg1, shape=None, dtype=None, copy=False):
self._shape = check_shape((M, N))

idx_dtype = get_index_dtype(maxval=max(self.shape))
data_dtype = getdtype(dtype, obj, default=float)
self.row = np.array(row, copy=copy, dtype=idx_dtype)
self.col = np.array(col, copy=copy, dtype=idx_dtype)
self.data = np.array(obj, copy=copy)
self.data = np.array(obj, copy=copy, dtype=data_dtype)
self.has_canonical_format = False

else:
if isspmatrix(arg1):
if isspmatrix_coo(arg1) and copy:
Expand Down
14 changes: 11 additions & 3 deletions scipy/sparse/tests/test_base.py
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Expand Up @@ -3523,6 +3523,11 @@ def test_constructor4(self):
ij = vstack((row,col))
csr = csr_matrix((data,ij),(4,3))
assert_array_equal(arange(12).reshape(4,3),csr.todense())

# using Python lists and a specified dtype
csr = csr_matrix(([2**63 + 1, 1], ([0, 1], [0, 1])), dtype=np.uint64)
dense = array([[2**63 + 1, 0], [0, 1]], dtype=np.uint64)
assert_array_equal(dense, csr.toarray())

def test_constructor5(self):
# infer dimensions from arrays
Expand Down Expand Up @@ -4086,13 +4091,16 @@ def test_constructor1(self):
# unsorted triplet format
row = array([2, 3, 1, 3, 0, 1, 3, 0, 2, 1, 2])
col = array([0, 1, 0, 0, 1, 1, 2, 2, 2, 2, 1])
data = array([6., 10., 3., 9., 1., 4.,
11., 2., 8., 5., 7.])
data = array([6., 10., 3., 9., 1., 4., 11., 2., 8., 5., 7.])

coo = coo_matrix((data,(row,col)),(4,3))

assert_array_equal(arange(12).reshape(4,3),coo.todense())

# using Python lists and a specified dtype
coo = coo_matrix(([2**63 + 1, 1], ([0, 1], [0, 1])), dtype=np.uint64)
dense = array([[2**63 + 1, 0], [0, 1]], dtype=np.uint64)
assert_array_equal(dense, coo.toarray())

def test_constructor2(self):
# unsorted triplet format with duplicates (which are summed)
row = array([0,1,2,2,2,2,0,0,2,2])
Expand Down