%PDF-
%PDF-
Mini Shell
Mini Shell
from __future__ import division, absolute_import, print_function
import warnings
import numpy as np
from numpy.core import (array, arange, atleast_1d, atleast_2d, atleast_3d,
block, vstack, hstack, newaxis, concatenate, stack)
from numpy.testing import (TestCase, assert_, assert_raises,
assert_array_equal, assert_equal, run_module_suite,
assert_raises_regex, assert_almost_equal)
from numpy.compat import long
class TestAtleast1d(TestCase):
def test_0D_array(self):
a = array(1)
b = array(2)
res = [atleast_1d(a), atleast_1d(b)]
desired = [array([1]), array([2])]
assert_array_equal(res, desired)
def test_1D_array(self):
a = array([1, 2])
b = array([2, 3])
res = [atleast_1d(a), atleast_1d(b)]
desired = [array([1, 2]), array([2, 3])]
assert_array_equal(res, desired)
def test_2D_array(self):
a = array([[1, 2], [1, 2]])
b = array([[2, 3], [2, 3]])
res = [atleast_1d(a), atleast_1d(b)]
desired = [a, b]
assert_array_equal(res, desired)
def test_3D_array(self):
a = array([[1, 2], [1, 2]])
b = array([[2, 3], [2, 3]])
a = array([a, a])
b = array([b, b])
res = [atleast_1d(a), atleast_1d(b)]
desired = [a, b]
assert_array_equal(res, desired)
def test_r1array(self):
""" Test to make sure equivalent Travis O's r1array function
"""
assert_(atleast_1d(3).shape == (1,))
assert_(atleast_1d(3j).shape == (1,))
assert_(atleast_1d(long(3)).shape == (1,))
assert_(atleast_1d(3.0).shape == (1,))
assert_(atleast_1d([[2, 3], [4, 5]]).shape == (2, 2))
class TestAtleast2d(TestCase):
def test_0D_array(self):
a = array(1)
b = array(2)
res = [atleast_2d(a), atleast_2d(b)]
desired = [array([[1]]), array([[2]])]
assert_array_equal(res, desired)
def test_1D_array(self):
a = array([1, 2])
b = array([2, 3])
res = [atleast_2d(a), atleast_2d(b)]
desired = [array([[1, 2]]), array([[2, 3]])]
assert_array_equal(res, desired)
def test_2D_array(self):
a = array([[1, 2], [1, 2]])
b = array([[2, 3], [2, 3]])
res = [atleast_2d(a), atleast_2d(b)]
desired = [a, b]
assert_array_equal(res, desired)
def test_3D_array(self):
a = array([[1, 2], [1, 2]])
b = array([[2, 3], [2, 3]])
a = array([a, a])
b = array([b, b])
res = [atleast_2d(a), atleast_2d(b)]
desired = [a, b]
assert_array_equal(res, desired)
def test_r2array(self):
""" Test to make sure equivalent Travis O's r2array function
"""
assert_(atleast_2d(3).shape == (1, 1))
assert_(atleast_2d([3j, 1]).shape == (1, 2))
assert_(atleast_2d([[[3, 1], [4, 5]], [[3, 5], [1, 2]]]).shape == (2, 2, 2))
class TestAtleast3d(TestCase):
def test_0D_array(self):
a = array(1)
b = array(2)
res = [atleast_3d(a), atleast_3d(b)]
desired = [array([[[1]]]), array([[[2]]])]
assert_array_equal(res, desired)
def test_1D_array(self):
a = array([1, 2])
b = array([2, 3])
res = [atleast_3d(a), atleast_3d(b)]
desired = [array([[[1], [2]]]), array([[[2], [3]]])]
assert_array_equal(res, desired)
def test_2D_array(self):
a = array([[1, 2], [1, 2]])
b = array([[2, 3], [2, 3]])
res = [atleast_3d(a), atleast_3d(b)]
desired = [a[:,:, newaxis], b[:,:, newaxis]]
assert_array_equal(res, desired)
def test_3D_array(self):
a = array([[1, 2], [1, 2]])
b = array([[2, 3], [2, 3]])
a = array([a, a])
b = array([b, b])
res = [atleast_3d(a), atleast_3d(b)]
desired = [a, b]
assert_array_equal(res, desired)
class TestHstack(TestCase):
def test_non_iterable(self):
assert_raises(TypeError, hstack, 1)
def test_empty_input(self):
assert_raises(ValueError, hstack, ())
def test_0D_array(self):
a = array(1)
b = array(2)
res = hstack([a, b])
desired = array([1, 2])
assert_array_equal(res, desired)
def test_1D_array(self):
a = array([1])
b = array([2])
res = hstack([a, b])
desired = array([1, 2])
assert_array_equal(res, desired)
def test_2D_array(self):
a = array([[1], [2]])
b = array([[1], [2]])
res = hstack([a, b])
desired = array([[1, 1], [2, 2]])
assert_array_equal(res, desired)
class TestVstack(TestCase):
def test_non_iterable(self):
assert_raises(TypeError, vstack, 1)
def test_empty_input(self):
assert_raises(ValueError, vstack, ())
def test_0D_array(self):
a = array(1)
b = array(2)
res = vstack([a, b])
desired = array([[1], [2]])
assert_array_equal(res, desired)
def test_1D_array(self):
a = array([1])
b = array([2])
res = vstack([a, b])
desired = array([[1], [2]])
assert_array_equal(res, desired)
def test_2D_array(self):
a = array([[1], [2]])
b = array([[1], [2]])
res = vstack([a, b])
desired = array([[1], [2], [1], [2]])
assert_array_equal(res, desired)
def test_2D_array2(self):
a = array([1, 2])
b = array([1, 2])
res = vstack([a, b])
desired = array([[1, 2], [1, 2]])
assert_array_equal(res, desired)
class TestConcatenate(TestCase):
def test_exceptions(self):
# test axis must be in bounds
for ndim in [1, 2, 3]:
a = np.ones((1,)*ndim)
np.concatenate((a, a), axis=0) # OK
assert_raises(np.AxisError, np.concatenate, (a, a), axis=ndim)
assert_raises(np.AxisError, np.concatenate, (a, a), axis=-(ndim + 1))
# Scalars cannot be concatenated
assert_raises(ValueError, concatenate, (0,))
assert_raises(ValueError, concatenate, (np.array(0),))
# test shapes must match except for concatenation axis
a = np.ones((1, 2, 3))
b = np.ones((2, 2, 3))
axis = list(range(3))
for i in range(3):
np.concatenate((a, b), axis=axis[0]) # OK
assert_raises(ValueError, np.concatenate, (a, b), axis=axis[1])
assert_raises(ValueError, np.concatenate, (a, b), axis=axis[2])
a = np.rollaxis(a, -1)
b = np.rollaxis(b, -1)
axis.append(axis.pop(0))
# No arrays to concatenate raises ValueError
assert_raises(ValueError, concatenate, ())
def test_concatenate_axis_None(self):
a = np.arange(4, dtype=np.float64).reshape((2, 2))
b = list(range(3))
c = ['x']
r = np.concatenate((a, a), axis=None)
assert_equal(r.dtype, a.dtype)
assert_equal(r.ndim, 1)
r = np.concatenate((a, b), axis=None)
assert_equal(r.size, a.size + len(b))
assert_equal(r.dtype, a.dtype)
r = np.concatenate((a, b, c), axis=None)
d = array(['0.0', '1.0', '2.0', '3.0',
'0', '1', '2', 'x'])
assert_array_equal(r, d)
def test_large_concatenate_axis_None(self):
# When no axis is given, concatenate uses flattened versions.
# This also had a bug with many arrays (see gh-5979).
x = np.arange(1, 100)
r = np.concatenate(x, None)
assert_array_equal(x, r)
# This should probably be deprecated:
r = np.concatenate(x, 100) # axis is >= MAXDIMS
assert_array_equal(x, r)
def test_concatenate(self):
# Test concatenate function
# One sequence returns unmodified (but as array)
r4 = list(range(4))
assert_array_equal(concatenate((r4,)), r4)
# Any sequence
assert_array_equal(concatenate((tuple(r4),)), r4)
assert_array_equal(concatenate((array(r4),)), r4)
# 1D default concatenation
r3 = list(range(3))
assert_array_equal(concatenate((r4, r3)), r4 + r3)
# Mixed sequence types
assert_array_equal(concatenate((tuple(r4), r3)), r4 + r3)
assert_array_equal(concatenate((array(r4), r3)), r4 + r3)
# Explicit axis specification
assert_array_equal(concatenate((r4, r3), 0), r4 + r3)
# Including negative
assert_array_equal(concatenate((r4, r3), -1), r4 + r3)
# 2D
a23 = array([[10, 11, 12], [13, 14, 15]])
a13 = array([[0, 1, 2]])
res = array([[10, 11, 12], [13, 14, 15], [0, 1, 2]])
assert_array_equal(concatenate((a23, a13)), res)
assert_array_equal(concatenate((a23, a13), 0), res)
assert_array_equal(concatenate((a23.T, a13.T), 1), res.T)
assert_array_equal(concatenate((a23.T, a13.T), -1), res.T)
# Arrays much match shape
assert_raises(ValueError, concatenate, (a23.T, a13.T), 0)
# 3D
res = arange(2 * 3 * 7).reshape((2, 3, 7))
a0 = res[..., :4]
a1 = res[..., 4:6]
a2 = res[..., 6:]
assert_array_equal(concatenate((a0, a1, a2), 2), res)
assert_array_equal(concatenate((a0, a1, a2), -1), res)
assert_array_equal(concatenate((a0.T, a1.T, a2.T), 0), res.T)
def test_stack():
# non-iterable input
assert_raises(TypeError, stack, 1)
# 0d input
for input_ in [(1, 2, 3),
[np.int32(1), np.int32(2), np.int32(3)],
[np.array(1), np.array(2), np.array(3)]]:
assert_array_equal(stack(input_), [1, 2, 3])
# 1d input examples
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
r1 = array([[1, 2, 3], [4, 5, 6]])
assert_array_equal(np.stack((a, b)), r1)
assert_array_equal(np.stack((a, b), axis=1), r1.T)
# all input types
assert_array_equal(np.stack(list([a, b])), r1)
assert_array_equal(np.stack(array([a, b])), r1)
# all shapes for 1d input
arrays = [np.random.randn(3) for _ in range(10)]
axes = [0, 1, -1, -2]
expected_shapes = [(10, 3), (3, 10), (3, 10), (10, 3)]
for axis, expected_shape in zip(axes, expected_shapes):
assert_equal(np.stack(arrays, axis).shape, expected_shape)
assert_raises_regex(np.AxisError, 'out of bounds', stack, arrays, axis=2)
assert_raises_regex(np.AxisError, 'out of bounds', stack, arrays, axis=-3)
# all shapes for 2d input
arrays = [np.random.randn(3, 4) for _ in range(10)]
axes = [0, 1, 2, -1, -2, -3]
expected_shapes = [(10, 3, 4), (3, 10, 4), (3, 4, 10),
(3, 4, 10), (3, 10, 4), (10, 3, 4)]
for axis, expected_shape in zip(axes, expected_shapes):
assert_equal(np.stack(arrays, axis).shape, expected_shape)
# empty arrays
assert_(stack([[], [], []]).shape == (3, 0))
assert_(stack([[], [], []], axis=1).shape == (0, 3))
# edge cases
assert_raises_regex(ValueError, 'need at least one array', stack, [])
assert_raises_regex(ValueError, 'must have the same shape',
stack, [1, np.arange(3)])
assert_raises_regex(ValueError, 'must have the same shape',
stack, [np.arange(3), 1])
assert_raises_regex(ValueError, 'must have the same shape',
stack, [np.arange(3), 1], axis=1)
assert_raises_regex(ValueError, 'must have the same shape',
stack, [np.zeros((3, 3)), np.zeros(3)], axis=1)
assert_raises_regex(ValueError, 'must have the same shape',
stack, [np.arange(2), np.arange(3)])
# np.matrix
m = np.matrix([[1, 2], [3, 4]])
assert_raises_regex(ValueError, 'shape too large to be a matrix',
stack, [m, m])
class TestBlock(TestCase):
def test_block_simple_row_wise(self):
a_2d = np.ones((2, 2))
b_2d = 2 * a_2d
desired = np.array([[1, 1, 2, 2],
[1, 1, 2, 2]])
result = block([a_2d, b_2d])
assert_equal(desired, result)
def test_block_simple_column_wise(self):
a_2d = np.ones((2, 2))
b_2d = 2 * a_2d
expected = np.array([[1, 1],
[1, 1],
[2, 2],
[2, 2]])
result = block([[a_2d], [b_2d]])
assert_equal(expected, result)
def test_block_with_1d_arrays_row_wise(self):
# # # 1-D vectors are treated as row arrays
a = np.array([1, 2, 3])
b = np.array([2, 3, 4])
expected = np.array([1, 2, 3, 2, 3, 4])
result = block([a, b])
assert_equal(expected, result)
def test_block_with_1d_arrays_multiple_rows(self):
a = np.array([1, 2, 3])
b = np.array([2, 3, 4])
expected = np.array([[1, 2, 3, 2, 3, 4],
[1, 2, 3, 2, 3, 4]])
result = block([[a, b], [a, b]])
assert_equal(expected, result)
def test_block_with_1d_arrays_column_wise(self):
# # # 1-D vectors are treated as row arrays
a_1d = np.array([1, 2, 3])
b_1d = np.array([2, 3, 4])
expected = np.array([[1, 2, 3],
[2, 3, 4]])
result = block([[a_1d], [b_1d]])
assert_equal(expected, result)
def test_block_mixed_1d_and_2d(self):
a_2d = np.ones((2, 2))
b_1d = np.array([2, 2])
result = block([[a_2d], [b_1d]])
expected = np.array([[1, 1],
[1, 1],
[2, 2]])
assert_equal(expected, result)
def test_block_complicated(self):
# a bit more complicated
one_2d = np.array([[1, 1, 1]])
two_2d = np.array([[2, 2, 2]])
three_2d = np.array([[3, 3, 3, 3, 3, 3]])
four_1d = np.array([4, 4, 4, 4, 4, 4])
five_0d = np.array(5)
six_1d = np.array([6, 6, 6, 6, 6])
zero_2d = np.zeros((2, 6))
expected = np.array([[1, 1, 1, 2, 2, 2],
[3, 3, 3, 3, 3, 3],
[4, 4, 4, 4, 4, 4],
[5, 6, 6, 6, 6, 6],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]])
result = block([[one_2d, two_2d],
[three_2d],
[four_1d],
[five_0d, six_1d],
[zero_2d]])
assert_equal(result, expected)
def test_nested(self):
one = np.array([1, 1, 1])
two = np.array([[2, 2, 2], [2, 2, 2], [2, 2, 2]])
three = np.array([3, 3, 3])
four = np.array([4, 4, 4])
five = np.array(5)
six = np.array([6, 6, 6, 6, 6])
zero = np.zeros((2, 6))
result = np.block([
[
np.block([
[one],
[three],
[four]
]),
two
],
[five, six],
[zero]
])
expected = np.array([[1, 1, 1, 2, 2, 2],
[3, 3, 3, 2, 2, 2],
[4, 4, 4, 2, 2, 2],
[5, 6, 6, 6, 6, 6],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]])
assert_equal(result, expected)
def test_3d(self):
a000 = np.ones((2, 2, 2), int) * 1
a100 = np.ones((3, 2, 2), int) * 2
a010 = np.ones((2, 3, 2), int) * 3
a001 = np.ones((2, 2, 3), int) * 4
a011 = np.ones((2, 3, 3), int) * 5
a101 = np.ones((3, 2, 3), int) * 6
a110 = np.ones((3, 3, 2), int) * 7
a111 = np.ones((3, 3, 3), int) * 8
result = np.block([
[
[a000, a001],
[a010, a011],
],
[
[a100, a101],
[a110, a111],
]
])
expected = array([[[1, 1, 4, 4, 4],
[1, 1, 4, 4, 4],
[3, 3, 5, 5, 5],
[3, 3, 5, 5, 5],
[3, 3, 5, 5, 5]],
[[1, 1, 4, 4, 4],
[1, 1, 4, 4, 4],
[3, 3, 5, 5, 5],
[3, 3, 5, 5, 5],
[3, 3, 5, 5, 5]],
[[2, 2, 6, 6, 6],
[2, 2, 6, 6, 6],
[7, 7, 8, 8, 8],
[7, 7, 8, 8, 8],
[7, 7, 8, 8, 8]],
[[2, 2, 6, 6, 6],
[2, 2, 6, 6, 6],
[7, 7, 8, 8, 8],
[7, 7, 8, 8, 8],
[7, 7, 8, 8, 8]],
[[2, 2, 6, 6, 6],
[2, 2, 6, 6, 6],
[7, 7, 8, 8, 8],
[7, 7, 8, 8, 8],
[7, 7, 8, 8, 8]]])
assert_array_equal(result, expected)
def test_block_with_mismatched_shape(self):
a = np.array([0, 0])
b = np.eye(2)
assert_raises(ValueError, np.block, [a, b])
assert_raises(ValueError, np.block, [b, a])
def test_no_lists(self):
assert_equal(np.block(1), np.array(1))
assert_equal(np.block(np.eye(3)), np.eye(3))
def test_invalid_nesting(self):
msg = 'depths are mismatched'
assert_raises_regex(ValueError, msg, np.block, [1, [2]])
assert_raises_regex(ValueError, msg, np.block, [1, []])
assert_raises_regex(ValueError, msg, np.block, [[1], 2])
assert_raises_regex(ValueError, msg, np.block, [[], 2])
assert_raises_regex(ValueError, msg, np.block, [
[[1], [2]],
[[3, 4]],
[5] # missing brackets
])
def test_empty_lists(self):
assert_raises_regex(ValueError, 'empty', np.block, [])
assert_raises_regex(ValueError, 'empty', np.block, [[]])
assert_raises_regex(ValueError, 'empty', np.block, [[1], []])
def test_tuple(self):
assert_raises_regex(TypeError, 'tuple', np.block, ([1, 2], [3, 4]))
assert_raises_regex(TypeError, 'tuple', np.block, [(1, 2), (3, 4)])
if __name__ == "__main__":
run_module_suite()
Zerion Mini Shell 1.0