def test_set_fill_value(self):
arr = SparseArray([1., np.nan, 2.], fill_value=np.nan)
arr.fill_value = 2
assert arr.fill_value == 2
arr = SparseArray([1, 0, 2], fill_value=0, dtype=np.int64)
arr.fill_value = 2
assert arr.fill_value == 2
# coerces to int
msg = "unable to set fill_value 3\\.1 to int64 dtype"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = 3.1
msg = "unable to set fill_value nan to int64 dtype"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = np.nan
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
arr.fill_value = True
assert arr.fill_value
# coerces to bool
msg = "unable to set fill_value 0 to bool dtype"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = 0
msg = "unable to set fill_value nan to bool dtype"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = np.nan
def test_setting_fill_value_updates():
arr = SparseArray([0.0, np.nan], fill_value=0)
arr.fill_value = np.nan
# use private constructor to get the index right
# otherwise both nans would be un-stored.
expected = SparseArray._simple_new(
sparse_array=np.array([np.nan]),
sparse_index=IntIndex(2, [1]),
dtype=SparseDtype(float, np.nan),
)
tm.assert_sp_array_equal(arr, expected)
def test_setting_fill_value_updates():
arr = SparseArray([0.0, np.nan], fill_value=0)
arr.fill_value = np.nan
# use private constructor to get the index right
# otherwise both nans would be un-stored.
expected = SparseArray._simple_new(
sparse_array=np.array([np.nan]),
sparse_index=IntIndex(2, [1]),
dtype=SparseDtype(float, np.nan),
)
tm.assert_sp_array_equal(arr, expected)
def test_setting_fill_value_fillna_still_works():
# This is why letting users update fill_value / dtype is bad
# astype has the same problem.
arr = SparseArray([1., np.nan, 1.0], fill_value=0.0)
arr.fill_value = np.nan
result = arr.isna()
# Can't do direct comparison, since the sp_index will be different
# So let's convert to ndarray and check there.
result = np.asarray(result)
expected = np.array([False, True, False])
tm.assert_numpy_array_equal(result, expected)
def test_setting_fill_value_fillna_still_works():
# This is why letting users update fill_value / dtype is bad
# astype has the same problem.
arr = SparseArray([1., np.nan, 1.0], fill_value=0.0)
arr.fill_value = np.nan
result = arr.isna()
# Can't do direct comparison, since the sp_index will be different
# So let's convert to ndarray and check there.
result = np.asarray(result)
expected = np.array([False, True, False])
tm.assert_numpy_array_equal(result, expected)
def test_set_fill_value(self):
arr = SparseArray([1., np.nan, 2.], fill_value=np.nan)
arr.fill_value = 2
self.assertEqual(arr.fill_value, 2)
arr = SparseArray([1, 0, 2], fill_value=0, dtype=np.int64)
arr.fill_value = 2
self.assertEqual(arr.fill_value, 2)
# coerces to int
msg = "unable to set fill_value 3\\.1 to int64 dtype"
with tm.assertRaisesRegexp(ValueError, msg):
arr.fill_value = 3.1
msg = "unable to set fill_value nan to int64 dtype"
with tm.assertRaisesRegexp(ValueError, msg):
arr.fill_value = np.nan
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
arr.fill_value = True
self.assertTrue(arr.fill_value)
# coerces to bool
msg = "unable to set fill_value 0 to bool dtype"
with tm.assertRaisesRegexp(ValueError, msg):
arr.fill_value = 0
msg = "unable to set fill_value nan to bool dtype"
with tm.assertRaisesRegexp(ValueError, msg):
arr.fill_value = np.nan
# invalid
msg = "fill_value must be a scalar"
for val in [[1, 2, 3], np.array([1, 2]), (1, 2, 3)]:
with tm.assertRaisesRegexp(ValueError, msg):
arr.fill_value = val
def test_set_fill_value(self):
arr = SparseArray([1., np.nan, 2.], fill_value=np.nan)
arr.fill_value = 2
self.assertEqual(arr.fill_value, 2)
arr = SparseArray([1, 0, 2], fill_value=0, dtype=np.int64)
arr.fill_value = 2
self.assertEqual(arr.fill_value, 2)
# coerces to int
msg = "unable to set fill_value 3\\.1 to int64 dtype"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = 3.1
msg = "unable to set fill_value nan to int64 dtype"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = np.nan
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
arr.fill_value = True
assert arr.fill_value
# coerces to bool
msg = "unable to set fill_value 0 to bool dtype"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = 0
msg = "unable to set fill_value nan to bool dtype"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = np.nan
# invalid
msg = "fill_value must be a scalar"
for val in [[1, 2, 3], np.array([1, 2]), (1, 2, 3)]:
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = val
def test_set_fill_value(self):
arr = SparseArray([1., np.nan, 2.], fill_value=np.nan)
arr.fill_value = 2
assert arr.fill_value == 2
arr = SparseArray([1, 0, 2], fill_value=0, dtype=np.int64)
arr.fill_value = 2
assert arr.fill_value == 2
# XXX: this seems fine? You can construct an integer
# sparsearray with NaN fill value, why not update one?
# coerces to int
# msg = "unable to set fill_value 3\\.1 to int64 dtype"
# with pytest.raises(ValueError, match=msg):
arr.fill_value = 3.1
assert arr.fill_value == 3.1
# msg = "unable to set fill_value nan to int64 dtype"
# with pytest.raises(ValueError, match=msg):
arr.fill_value = np.nan
assert np.isnan(arr.fill_value)
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
arr.fill_value = True
assert arr.fill_value
# coerces to bool
# msg = "unable to set fill_value 0 to bool dtype"
# with pytest.raises(ValueError, match=msg):
arr.fill_value = 0
assert arr.fill_value == 0
# msg = "unable to set fill_value nan to bool dtype"
# with pytest.raises(ValueError, match=msg):
arr.fill_value = np.nan
assert np.isnan(arr.fill_value)
def test_set_fill_value(self):
arr = SparseArray([1., np.nan, 2.], fill_value=np.nan)
arr.fill_value = 2
assert arr.fill_value == 2
arr = SparseArray([1, 0, 2], fill_value=0, dtype=np.int64)
arr.fill_value = 2
assert arr.fill_value == 2
# XXX: this seems fine? You can construct an integer
# sparsearray with NaN fill value, why not update one?
# coerces to int
# msg = "unable to set fill_value 3\\.1 to int64 dtype"
# with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = 3.1
assert arr.fill_value == 3.1
# msg = "unable to set fill_value nan to int64 dtype"
# with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = np.nan
assert np.isnan(arr.fill_value)
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
arr.fill_value = True
assert arr.fill_value
# coerces to bool
# msg = "unable to set fill_value 0 to bool dtype"
# with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = 0
assert arr.fill_value == 0
# msg = "unable to set fill_value nan to bool dtype"
# with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = np.nan
assert np.isnan(arr.fill_value)
def test_set_fill_invalid_non_scalar(self, val):
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
msg = "fill_value must be a scalar"
with pytest.raises(ValueError, match=msg):
arr.fill_value = val
def test_set_fill_invalid_non_scalar(self, val):
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
msg = "fill_value must be a scalar"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = val
def test_set_fill_invalid_non_scalar(self, val):
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
msg = "fill_value must be a scalar"
with pytest.raises(ValueError, match=msg):
arr.fill_value = val
def test_set_fill_invalid_non_scalar(self, val):
arr = SparseArray([True, False, True], fill_value=False, dtype=np.bool)
msg = "fill_value must be a scalar"
with tm.assert_raises_regex(ValueError, msg):
arr.fill_value = val
