本文整理匯總了Python中numpy.arctanh方法的典型用法代碼示例。如果您正苦於以下問題：Python numpy.arctanh方法的具體用法？Python numpy.arctanh怎麽用？Python numpy.arctanh使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類numpy的用法示例。
在下文中一共展示了numpy.arctanh方法的12個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_branch_cuts
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
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
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
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_against_cmath
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
def test_against_cmath(self):
import cmath
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s" % (fname, p, a, b)) 示例4: invert_bfgs
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
def invert_bfgs(gen_model, invert_model, ftr_model, im, z_predict=None, npx=64):
_f, z = invert_model
nz = gen_model.nz
if z_predict is None:
z_predict = np_rng.uniform(-1., 1., size=(1, nz))
else:
z_predict = floatX(z_predict)
z_predict = np.arctanh(z_predict)
im_t = gen_model.transform(im)
ftr = ftr_model(im_t)
prob = optimize.minimize(f_bfgs, z_predict, args=(_f, im_t, ftr),
tol=1e-6, jac=True, method='L-BFGS-B', options={'maxiter': 200})
print('n_iters = %3d, f = %.3f' % (prob.nit, prob.fun))
z_opt = prob.x
z_opt_n = floatX(z_opt[np.newaxis, :])
[f_opt, g, gx] = _f(z_opt_n, im_t, ftr)
gx = gen_model.inverse_transform(gx, npx=npx)
z_opt = np.tanh(z_opt)
return gx, z_opt, f_opt 示例5: test_branch_cuts
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
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6: test_branch_cuts_complex64
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
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7: test_against_cmath
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
def test_against_cmath(self):
import cmath
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(np.complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s" % (fname, p, a, b)) 示例8: test_branch_cuts
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
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9: test_against_cmath
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
def test_against_cmath(self):
import cmath, sys
points = [-1-1j, -1+1j, +1-1j, +1+1j]
name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan',
'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'}
atol = 4*np.finfo(np.complex).eps
for func in self.funcs:
fname = func.__name__.split('.')[-1]
cname = name_map.get(fname, fname)
try:
cfunc = getattr(cmath, cname)
except AttributeError:
continue
for p in points:
a = complex(func(np.complex_(p)))
b = cfunc(p)
assert_(abs(a - b) < atol, "%s %s: %s; cmath: %s"%(fname, p, a, b)) 示例10: shwgrad
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
def shwgrad(imtuple, flux, pol_prim="amp_phase",pol_solve=(0,1,1),
norm_reg=NORM_REGULARIZER):
"""Gradient of the Holdaway-Wardle polarimetric entropy
"""
if norm_reg: norm = flux
else: norm = 1
iimage = imtuple[0]
zeros = np.zeros(len(iimage))
mimage = make_m_image(imtuple, pol_prim)
if pol_prim=="amp_phase":
gradi = zeros
gradchi = zeros
if pol_solve[1]!=0:
gradm = -iimage * np.arctanh(mimage)
else:
gradm = zeros
out = (gradi, gradm, gradchi)
else:
raise Exception("polarimetric representation %s not added to pol gradient yet!" % pol_prim)
return np.array(out)/norm 示例11: rc2lar
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
def rc2lar(k):
"""Convert reflection coefficients to log area ratios.
:param k: reflection coefficients
:return: inverse sine parameters
The log area ratio is defined by G = log((1+k)/(1-k)) , where the K
parameter is the reflection coefficient.
.. seealso:: :func:`lar2rc`, :func:`rc2poly`, :func:`rc2ac`, :func:`rc2ic`.
:References:
[1] J. Makhoul, "Linear Prediction: A Tutorial Review," Proc. IEEE, Vol.63, No.4, pp.561-580, Apr 1975.
"""
assert numpy.isrealobj(k), 'Log area ratios not defined for complex reflection coefficients.'
if max(numpy.abs(k)) >= 1:
raise ValueError('All reflection coefficients should have magnitude less than unity.')
# Use the relation, atanh(x) = (1/2)*log((1+k)/(1-k))
return -2 * numpy.arctanh(-numpy.array(k)) 示例12: total_photon_num_dist_pure_state
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import arctanh [as 別名]
def total_photon_num_dist_pure_state(cov, cutoff=50, hbar=2, padding_factor=2):
r""" Calculates the total photon number distribution of a pure state
with zero mean.
Args:
cov (array): :math:`2N\times 2N` covariance matrix in xp-ordering
cutoff (int): Fock cutoff
tol (float): tolerance for determining if displacement is negligible
hbar (float): the value of :math:`\hbar` in the commutation
padding_factor (int): expanded size of the photon distribution to avoid accumulation of errors
Returns:
(array): Total photon number distribution
"""
if is_pure_cov(cov):
A = Amat(cov, hbar=hbar)
(n, _) = A.shape
N = n // 2
B = A[0:N, 0:N]
rs = np.arctanh(np.linalg.svd(B, compute_uv=False))
return gen_multi_mode_dist(rs, cutoff=cutoff, padding_factor=padding_factor)[0:cutoff]
raise ValueError("The Gaussian state is not pure")