def test_dtype_from_char(self):
mat = np.eye(3)
codes = 'efdgFDG'
for c in codes:
tgt = np.sum(mat, dtype=c, axis=1).dtype.type
res = nansum(mat, dtype=c, axis=1).dtype.type
assert_(res is tgt)
# scalar case
tgt = np.sum(mat, dtype=c, axis=None).dtype.type
res = nansum(mat, dtype=c, axis=None).dtype.type
assert_(res is tgt)
def test_dtype_from_input(self):
codes = 'efdgFDG'
for c in codes:
mat = np.eye(3, dtype=c)
tgt = np.sum(mat, axis=1).dtype.type
res = nansum(mat, axis=1).dtype.type
assert_(res is tgt)
# scalar case
tgt = np.sum(mat, axis=None).dtype.type
res = nansum(mat, axis=None).dtype.type
assert_(res is tgt)
def test_dtype_from_char(self):
mat = np.eye(3)
codes = 'efdgFDG'
for c in codes:
tgt = np.sum(mat, dtype=c, axis=1).dtype.type
res = nansum(mat, dtype=c, axis=1).dtype.type
assert_(res is tgt)
# scalar case
tgt = np.sum(mat, dtype=c, axis=None).dtype.type
res = nansum(mat, dtype=c, axis=None).dtype.type
assert_(res is tgt)
def test_dtype_from_input(self):
codes = 'efdgFDG'
for c in codes:
mat = np.eye(3, dtype=c)
tgt = np.sum(mat, axis=1).dtype.type
res = nansum(mat, axis=1).dtype.type
assert_(res is tgt)
# scalar case
tgt = np.sum(mat, axis=None).dtype.type
res = nansum(mat, axis=None).dtype.type
assert_(res is tgt)
def test_empty(self):
mat = np.zeros((0, 3))
tgt = [0] * 3
res = nansum(mat, axis=0)
assert_equal(res, tgt)
tgt = []
res = nansum(mat, axis=1)
assert_equal(res, tgt)
tgt = 0
res = nansum(mat, axis=None)
assert_equal(res, tgt)
def test_empty(self):
mat = np.zeros((0, 3))
tgt = [0]*3
res = nansum(mat, axis=0)
assert_equal(res, tgt)
tgt = []
res = nansum(mat, axis=1)
assert_equal(res, tgt)
tgt = 0
res = nansum(mat, axis=None)
assert_equal(res, tgt)
def test_out(self):
mat = np.eye(3)
resout = np.zeros(3)
tgt = np.sum(mat, axis=1)
res = nansum(mat, axis=1, out=resout)
assert_almost_equal(res, resout)
assert_almost_equal(res, tgt)
def test_allnans(self):
# Check for FutureWarning and later change of return from
# NaN to zero.
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
res = nansum([np.nan]*3, axis=None)
if np.__version__[:3] < '1.9':
assert_(np.isnan(res), 'result is not NaN')
assert_(len(w) == 1, 'no warning raised')
assert_(issubclass(w[0].category, FutureWarning))
# Check there is no warning for not all-nan
nansum([0]*3, axis=None)
assert_(len(w) == 1, 'unwanted warning raised')
else:
assert_(res == 0, 'result is not 0')
assert_(len(w) == 0, 'warning raised')
def test_allnans(self):
# Check for FutureWarning and later change of return from
# NaN to zero.
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
res = nansum([np.nan] * 3, axis=None)
if np.__version__[:3] < '1.9':
assert_(np.isnan(res), 'result is not NaN')
assert_(len(w) == 1, 'no warning raised')
assert_(issubclass(w[0].category, FutureWarning))
# Check there is no warning for not all-nan
nansum([0] * 3, axis=None)
assert_(len(w) == 1, 'unwanted warning raised')
else:
assert_(res == 0, 'result is not 0')
assert_(len(w) == 0, 'warning raised')
def test_out(self):
mat = np.eye(3)
resout = np.zeros(3)
tgt = np.sum(mat, axis=1)
res = nansum(mat, axis=1, out=resout)
assert_almost_equal(res, resout)
assert_almost_equal(res, tgt)
def test_allnans(self):
# Check for FutureWarning and later change of return from
# NaN to zero.
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
res = nansum([np.nan]*3, axis=None)
assert_(res == 0, 'result is not 0')
assert_(len(w) == 0, 'warning raised')
def test_allnans(self):
# Check for FutureWarning and later change of return from
# NaN to zero.
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
res = nansum([np.nan] * 3, axis=None)
assert_(res == 0, 'result is not 0')
assert_(len(w) == 0, 'warning raised')
def test_empty(self):
mat = np.zeros((0, 3))
if np.__version__[:3] < '1.9':
tgt = [np.nan]*3
res = nansum(mat, axis=0)
assert_equal(res, tgt)
tgt = []
res = nansum(mat, axis=1)
assert_equal(res, tgt)
tgt = np.nan
res = nansum(mat, axis=None)
assert_equal(res, tgt)
else:
tgt = [0]*3
res = nansum(mat, axis=0)
assert_equal(res, tgt)
tgt = []
res = nansum(mat, axis=1)
assert_equal(res, tgt)
tgt = 0
res = nansum(mat, axis=None)
assert_equal(res, tgt)
def test_empty(self):
mat = np.zeros((0, 3))
if np.__version__[:3] < '1.9':
tgt = [np.nan] * 3
res = nansum(mat, axis=0)
assert_equal(res, tgt)
tgt = []
res = nansum(mat, axis=1)
assert_equal(res, tgt)
tgt = np.nan
res = nansum(mat, axis=None)
assert_equal(res, tgt)
else:
tgt = [0] * 3
res = nansum(mat, axis=0)
assert_equal(res, tgt)
tgt = []
res = nansum(mat, axis=1)
assert_equal(res, tgt)
tgt = 0
res = nansum(mat, axis=None)
assert_equal(res, tgt)
def test_result_values(self):
tgt = [np.sum(d) for d in _rdat]
res = nansum(_ndat, axis=1)
assert_almost_equal(res, tgt)
def test_mutation(self):
# Check that passed array is not modified.
ndat = _ndat.copy()
nansum(ndat)
assert_equal(ndat, _ndat)
def test_keepdims(self):
mat = np.eye(3)
for axis in [None, 0, 1]:
tgt = np.sum(mat, axis=axis, keepdims=True)
res = nansum(mat, axis=axis, keepdims=True)
assert_(res.ndim == tgt.ndim)
def test_keepdims(self):
mat = np.eye(3)
for axis in [None, 0, 1]:
tgt = np.sum(mat, axis=axis, keepdims=True)
res = nansum(mat, axis=axis, keepdims=True)
assert_(res.ndim == tgt.ndim)
def test_mutation(self):
# Check that passed array is not modified.
ndat = _ndat.copy()
nansum(ndat)
assert_equal(ndat, _ndat)
def test_result_values(self):
tgt = [np.sum(d) for d in _rdat]
res = nansum(_ndat, axis=1)
assert_almost_equal(res, tgt)
