def test_solo_w_flatten(self):
# Test merge_arrays on a single array w & w/o flattening
w = self.data[0]
test = merge_arrays(w, flatten=False)
assert_equal(test, w)
test = merge_arrays(w, flatten=True)
control = np.array([(1, 2, 3.0), (4, 5, 6.0)],
dtype=[('a', int), ('ba', float), ('bb', int)])
assert_equal(test, control)
def test_wmasked_arrays(self):
# Test merge_arrays masked arrays
(_, x, _, _) = self.data
mx = ma.array([1, 2, 3], mask=[1, 0, 0])
test = merge_arrays((x, mx), usemask=True)
control = ma.array([(1, 1), (2, 2), (-1, 3)],
mask=[(0, 1), (0, 0), (1, 0)],
dtype=[('f0', int), ('f1', int)])
assert_equal(test, control)
test = merge_arrays((x, mx), usemask=True, asrecarray=True)
assert_equal(test, control)
assert_(isinstance(test, MaskedRecords))
def test_flatten(self):
# Test standard & flexible
(_, x, _, z) = self.data
test = merge_arrays((x, z), flatten=True)
control = np.array([(1, 'A', 1.), (2, 'B', 2.)],
dtype=[('f0', int), ('A', '|S3'), ('B', float)])
assert_equal(test, control)
test = merge_arrays((x, z), flatten=False)
control = np.array([(1, ('A', 1.)), (2, ('B', 2.))],
dtype=[('f0', int),
('f1', [('A', '|S3'), ('B', float)])])
assert_equal(test, control)
def test_w_shorter_flex(self):
# Test merge_arrays w/ a shorter flexndarray.
z = self.data[-1]
# Fixme, this test looks incomplete and broken
#test = merge_arrays((z, np.array([10, 20, 30]).view([('C', int)])))
#control = np.array([('A', 1., 10), ('B', 2., 20), ('-1', -1, 20)],
# dtype=[('A', '|S3'), ('B', float), ('C', int)])
#assert_equal(test, control)
# Hack to avoid pyflakes warnings about unused variables
merge_arrays((z, np.array([10, 20, 30]).view([('C', int)])))
np.array([('A', 1., 10), ('B', 2., 20), ('-1', -1, 20)],
dtype=[('A', '|S3'), ('B', float), ('C', int)])
def test_solo(self):
# Test merge_arrays on a single array.
(_, x, _, z) = self.data
test = merge_arrays(x)
control = np.array([(1, ), (2, )], dtype=[('f0', int)])
assert_equal(test, control)
test = merge_arrays((x, ))
assert_equal(test, control)
test = merge_arrays(z, flatten=False)
assert_equal(test, z)
test = merge_arrays(z, flatten=True)
assert_equal(test, z)
def test_standard(self):
# Test standard & standard
# Test merge arrays
(_, x, y, _) = self.data
test = merge_arrays((x, y), usemask=False)
control = np.array([(1, 10), (2, 20), (-1, 30)],
dtype=[('f0', int), ('f1', int)])
assert_equal(test, control)
test = merge_arrays((x, y), usemask=True)
control = ma.array([(1, 10), (2, 20), (-1, 30)],
mask=[(0, 0), (0, 0), (1, 0)],
dtype=[('f0', int), ('f1', int)])
assert_equal(test, control)
assert_equal(test.mask, control.mask)
def test_singlerecord(self):
(_, x, y, z) = self.data
test = merge_arrays((x[0], y[0], z[0]), usemask=False)
control = np.array([(1, 10, ('A', 1))],
dtype=[('f0', int), ('f1', int),
('f2', [('A', '|S3'), ('B', float)])])
assert_equal(test, control)
def test_flatten_wflexible(self):
# Test flatten standard & nested
(w, x, _, _) = self.data
test = merge_arrays((x, w), flatten=True)
control = np.array([(1, 1, 2, 3.0), (2, 4, 5, 6.0)],
dtype=[('f0', int), ('a', int), ('ba', float),
('bb', int)])
assert_equal(test, control)
test = merge_arrays((x, w), flatten=False)
controldtype = [('f0', int),
('f1', [('a', int), ('b', [('ba', float),
('bb', int)])])]
control = np.array([(1., (1, (2, 3.0))), (2, (4, (5, 6.0)))],
dtype=controldtype)
assert_equal(test, control)
def test_w_singlefield(self):
# Test single field
test = merge_arrays(
(np.array([1, 2]).view([('a', int)]), np.array([10., 20., 30.])), )
control = ma.array([(1, 10.), (2, 20.), (-1, 30.)],
mask=[(0, 0), (0, 0), (1, 0)],
dtype=[('a', int), ('f1', float)])
assert_equal(test, control)