本文整理汇总了Python中numpy.core._umath_tests.innerwt方法的典型用法代码示例。如果您正苦于以下问题：Python _umath_tests.innerwt方法的具体用法？Python _umath_tests.innerwt怎么用？Python _umath_tests.innerwt使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类numpy.core._umath_tests的用法示例。
在下文中一共展示了_umath_tests.innerwt方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_innerwt
# 需要导入模块: from numpy.core import _umath_tests [as 别名]
# 或者: from numpy.core._umath_tests import innerwt [as 别名]
def test_innerwt(self):
a = np.arange(6).reshape((2, 3))
b = np.arange(10, 16).reshape((2, 3))
w = np.arange(20, 26).reshape((2, 3))
assert_array_equal(umt.innerwt(a, b, w), np.sum(a*b*w, axis=-1))
a = np.arange(100, 124).reshape((2, 3, 4))
b = np.arange(200, 224).reshape((2, 3, 4))
w = np.arange(300, 324).reshape((2, 3, 4))
assert_array_equal(umt.innerwt(a, b, w), np.sum(a*b*w, axis=-1)) 示例2: test_innerwt_empty
# 需要导入模块: from numpy.core import _umath_tests [as 别名]
# 或者: from numpy.core._umath_tests import innerwt [as 别名]
def test_innerwt_empty(self):
"""Test generalized ufunc with zero-sized operands"""
a = np.array([], dtype='f8')
b = np.array([], dtype='f8')
w = np.array([], dtype='f8')
assert_array_equal(umt.innerwt(a, b, w), np.sum(a*b*w, axis=-1)) 示例3: test_axis_argument
# 需要导入模块: from numpy.core import _umath_tests [as 别名]
# 或者: from numpy.core._umath_tests import innerwt [as 别名]
def test_axis_argument(self):
# inner1d signature: '(i),(i)->()'
inner1d = umt.inner1d
a = np.arange(27.).reshape((3, 3, 3))
b = np.arange(10., 19.).reshape((3, 1, 3))
c = inner1d(a, b)
assert_array_equal(c, (a * b).sum(-1))
c = inner1d(a, b, axis=-1)
assert_array_equal(c, (a * b).sum(-1))
out = np.zeros_like(c)
d = inner1d(a, b, axis=-1, out=out)
assert_(d is out)
assert_array_equal(d, c)
c = inner1d(a, b, axis=0)
assert_array_equal(c, (a * b).sum(0))
# Sanity checks on innerwt and cumsum.
a = np.arange(6).reshape((2, 3))
b = np.arange(10, 16).reshape((2, 3))
w = np.arange(20, 26).reshape((2, 3))
assert_array_equal(umt.innerwt(a, b, w, axis=0),
np.sum(a * b * w, axis=0))
assert_array_equal(umt.cumsum(a, axis=0), np.cumsum(a, axis=0))
assert_array_equal(umt.cumsum(a, axis=-1), np.cumsum(a, axis=-1))
out = np.empty_like(a)
b = umt.cumsum(a, out=out, axis=0)
assert_(out is b)
assert_array_equal(b, np.cumsum(a, axis=0))
b = umt.cumsum(a, out=out, axis=1)
assert_(out is b)
assert_array_equal(b, np.cumsum(a, axis=-1))
# Check errors.
# Cannot pass in both axis and axes.
assert_raises(TypeError, inner1d, a, b, axis=0, axes=[0, 0])
# Not an integer.
assert_raises(TypeError, inner1d, a, b, axis=[0])
# more than 1 core dimensions.
mm = umt.matrix_multiply
assert_raises(TypeError, mm, a, b, axis=1)
# Output wrong size in axis.
out = np.empty((1, 2, 3), dtype=a.dtype)
assert_raises(ValueError, umt.cumsum, a, out=out, axis=0)
# Regular ufuncs should not accept axis.
assert_raises(TypeError, np.add, 1., 1., axis=0)