def test_ndbincount():
def check(expected):
npt.assert_equal(bc[0, 0], expected[0])
npt.assert_equal(bc[0, 1], expected[1])
npt.assert_equal(bc[1, 0], expected[2])
npt.assert_equal(bc[2, 2], expected[3])
x = np.array([[0, 0], [0, 0], [0, 1], [0, 1], [1, 0], [2, 2]]).T
expected = [2, 2, 1, 1]
# count occurrences in x
bc = ndbincount(x)
npt.assert_equal(bc.shape, (3, 3))
check(expected)
# pass in shape
bc = ndbincount(x, shape=(4, 5))
npt.assert_equal(bc.shape, (4, 5))
check(expected)
# pass in weights
weights = np.arange(6.)
weights[-1] = 1.23
expeceted = [1., 5., 4., 1.23]
bc = ndbincount(x, weights=weights)
check(expeceted)
# raises an error if shape is too small
npt.assert_raises(ValueError, ndbincount, x, None, (2, 2))
def test_ndbincount():
def check(expected):
assert_equal(bc[0, 0], expected[0])
assert_equal(bc[0, 1], expected[1])
assert_equal(bc[1, 0], expected[2])
assert_equal(bc[2, 2], expected[3])
x = np.array([[0, 0], [0, 0], [0, 1], [0, 1], [1, 0], [2, 2]]).T
expected = [2, 2, 1, 1]
# count occurrences in x
bc = ndbincount(x)
assert_equal(bc.shape, (3, 3))
check(expected)
# pass in shape
bc = ndbincount(x, shape=(4, 5))
assert_equal(bc.shape, (4, 5))
check(expected)
# pass in weights
weights = np.arange(6.)
weights[-1] = 1.23
expeceted = [1., 5., 4., 1.23]
bc = ndbincount(x, weights=weights)
check(expeceted)
# raises an error if shape is too small
assert_raises(ValueError, ndbincount, x, None, (2, 2))