本文整理汇总了Python中numpy.core.umath.sqrt方法的典型用法代码示例。如果您正苦于以下问题：Python umath.sqrt方法的具体用法？Python umath.sqrt怎么用？Python umath.sqrt使用的例子？那么, 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的用法示例。
在下文中一共展示了umath.sqrt方法的8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_branch_cuts
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import sqrt [as 别名]
def test_branch_cuts(self):
# check branch cuts and continuity on them
_check_branch_cut(np.log, -0.5, 1j, 1, -1, True)
_check_branch_cut(np.log2, -0.5, 1j, 1, -1, True)
_check_branch_cut(np.log10, -0.5, 1j, 1, -1, True)
_check_branch_cut(np.log1p, -1.5, 1j, 1, -1, True)
_check_branch_cut(np.sqrt, -0.5, 1j, 1, -1, True)
_check_branch_cut(np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True)
_check_branch_cut(np.arccos, [ -2, 2], [1j, 1j], 1, -1, True)
_check_branch_cut(np.arctan, [0-2j, 2j], [1, 1], -1, 1, True)
_check_branch_cut(np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True)
_check_branch_cut(np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True)
_check_branch_cut(np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True)
# check against bogus branch cuts: assert continuity between quadrants
_check_branch_cut(np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1)
_check_branch_cut(np.arccos, [0-2j, 2j], [ 1, 1], 1, 1)
_check_branch_cut(np.arctan, [ -2, 2], [1j, 1j], 1, 1)
_check_branch_cut(np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1)
_check_branch_cut(np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1)
_check_branch_cut(np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1) 示例2: test_branch_cuts_complex64
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import sqrt [as 别名]
def test_branch_cuts_complex64(self):
# check branch cuts and continuity on them
_check_branch_cut(np.log, -0.5, 1j, 1, -1, True, np.complex64)
_check_branch_cut(np.log2, -0.5, 1j, 1, -1, True, np.complex64)
_check_branch_cut(np.log10, -0.5, 1j, 1, -1, True, np.complex64)
_check_branch_cut(np.log1p, -1.5, 1j, 1, -1, True, np.complex64)
_check_branch_cut(np.sqrt, -0.5, 1j, 1, -1, True, np.complex64)
_check_branch_cut(np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64)
_check_branch_cut(np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64)
_check_branch_cut(np.arctan, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64)
_check_branch_cut(np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64)
_check_branch_cut(np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64)
_check_branch_cut(np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64)
# check against bogus branch cuts: assert continuity between quadrants
_check_branch_cut(np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64)
_check_branch_cut(np.arccos, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64)
_check_branch_cut(np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64)
_check_branch_cut(np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64)
_check_branch_cut(np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64)
_check_branch_cut(np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64) 示例3: test_branch_cuts
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import sqrt [as 别名]
def test_branch_cuts(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1 示例4: test_branch_cuts_complex64
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import sqrt [as 别名]
def test_branch_cuts_complex64(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1, True, np.complex64
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctan, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arcsinh, [0-2j, 2j], [1, 1], -1, 1, True, np.complex64
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccos, [0-2j, 2j], [ 1, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64
yield _check_branch_cut, np.arccosh, [0-2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64
yield _check_branch_cut, np.arctanh, [0-2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64 示例5: test_power_float
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import sqrt [as 别名]
def test_power_float(self):
x = np.array([1., 2., 3.])
assert_equal(x**0, [1., 1., 1.])
assert_equal(x**1, x)
assert_equal(x**2, [1., 4., 9.])
y = x.copy()
y **= 2
assert_equal(y, [1., 4., 9.])
assert_almost_equal(x**(-1), [1., 0.5, 1./3])
assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)])
for out, inp, msg in _gen_alignment_data(dtype=np.float32,
type='unary'):
exp = [ncu.sqrt(i) for i in inp]
assert_almost_equal(inp**(0.5), exp, err_msg=msg)
np.sqrt(inp, out=out)
assert_equal(out, exp, err_msg=msg)
for out, inp, msg in _gen_alignment_data(dtype=np.float64,
type='unary'):
exp = [ncu.sqrt(i) for i in inp]
assert_almost_equal(inp**(0.5), exp, err_msg=msg)
np.sqrt(inp, out=out)
assert_equal(out, exp, err_msg=msg) 示例6: test_branch_cuts
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import sqrt [as 别名]
def test_branch_cuts(self):
# check branch cuts and continuity on them
yield _check_branch_cut, np.log, -0.5, 1j, 1, -1
yield _check_branch_cut, np.log2, -0.5, 1j, 1, -1
yield _check_branch_cut, np.log10, -0.5, 1j, 1, -1
yield _check_branch_cut, np.log1p, -1.5, 1j, 1, -1
yield _check_branch_cut, np.sqrt, -0.5, 1j, 1, -1
yield _check_branch_cut, np.arcsin, [ -2, 2], [1j, -1j], 1, -1
yield _check_branch_cut, np.arccos, [ -2, 2], [1j, -1j], 1, -1
yield _check_branch_cut, np.arctan, [-2j, 2j], [1, -1 ], -1, 1
yield _check_branch_cut, np.arcsinh, [-2j, 2j], [-1, 1], -1, 1
yield _check_branch_cut, np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1
yield _check_branch_cut, np.arctanh, [ -2, 2], [1j, -1j], 1, -1
# check against bogus branch cuts: assert continuity between quadrants
yield _check_branch_cut, np.arcsin, [-2j, 2j], [ 1, 1], 1, 1
yield _check_branch_cut, np.arccos, [-2j, 2j], [ 1, 1], 1, 1
yield _check_branch_cut, np.arctan, [ -2, 2], [1j, 1j], 1, 1
yield _check_branch_cut, np.arcsinh, [ -2, 2, 0], [1j, 1j, 1 ], 1, 1
yield _check_branch_cut, np.arccosh, [-2j, 2j, 2], [1, 1, 1j], 1, 1
yield _check_branch_cut, np.arctanh, [-2j, 2j, 0], [1, 1, 1j], 1, 1 示例7: _std
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import sqrt [as 别名]
def _std(array, epsilon=1.0, bounds=None, axis=None, dtype=None, keepdims=np._NoValue, accountant=None, nan=False):
ret = _var(array, epsilon=epsilon, bounds=bounds, axis=axis, dtype=dtype, keepdims=keepdims, accountant=accountant,
nan=nan)
if isinstance(ret, mu.ndarray):
ret = um.sqrt(ret)
elif hasattr(ret, 'dtype'):
ret = ret.dtype.type(um.sqrt(ret))
else:
ret = um.sqrt(ret)
return ret 示例8: test_power_float
# 需要导入模块: from numpy.core import umath [as 别名]
# 或者: from numpy.core.umath import sqrt [as 别名]
def test_power_float(self):
x = np.array([1., 2., 3.])
assert_equal(x**0, [1., 1., 1.])
assert_equal(x**1, x)
assert_equal(x**2, [1., 4., 9.])
y = x.copy()
y **= 2
assert_equal(y, [1., 4., 9.])
assert_almost_equal(x**(-1), [1., 0.5, 1./3])
assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)])
for out, inp, msg in _gen_alignment_data(dtype=np.float32,
type='unary',
max_size=11):
exp = [ncu.sqrt(i) for i in inp]
assert_almost_equal(inp**(0.5), exp, err_msg=msg)
np.sqrt(inp, out=out)
assert_equal(out, exp, err_msg=msg)
for out, inp, msg in _gen_alignment_data(dtype=np.float64,
type='unary',
max_size=7):
exp = [ncu.sqrt(i) for i in inp]
assert_almost_equal(inp**(0.5), exp, err_msg=msg)
np.sqrt(inp, out=out)
assert_equal(out, exp, err_msg=msg)