本文整理汇总了Python中scipy.special.expm1方法的典型用法代码示例。如果您正苦于以下问题：Python special.expm1方法的具体用法？Python special.expm1怎么用？Python special.expm1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scipy.special的用法示例。
在下文中一共展示了special.expm1方法的14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_expm1_complex
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def test_expm1_complex(self):
expm1 = cephes.expm1
assert_equal(expm1(0 + 0j), 0 + 0j)
assert_equal(expm1(complex(np.inf, 0)), complex(np.inf, 0))
assert_equal(expm1(complex(np.inf, 1)), complex(np.inf, np.inf))
assert_equal(expm1(complex(np.inf, 2)), complex(-np.inf, np.inf))
assert_equal(expm1(complex(np.inf, 4)), complex(-np.inf, -np.inf))
assert_equal(expm1(complex(np.inf, 5)), complex(np.inf, -np.inf))
assert_equal(expm1(complex(1, np.inf)), complex(np.nan, np.nan))
assert_equal(expm1(complex(0, np.inf)), complex(np.nan, np.nan))
assert_equal(expm1(complex(np.inf, np.inf)), complex(np.inf, np.nan))
assert_equal(expm1(complex(-np.inf, np.inf)), complex(-1, 0))
assert_equal(expm1(complex(-np.inf, np.nan)), complex(-1, 0))
assert_equal(expm1(complex(np.inf, np.nan)), complex(np.inf, np.nan))
assert_equal(expm1(complex(0, np.nan)), complex(np.nan, np.nan))
assert_equal(expm1(complex(1, np.nan)), complex(np.nan, np.nan))
assert_equal(expm1(complex(np.nan, 1)), complex(np.nan, np.nan))
assert_equal(expm1(complex(np.nan, np.nan)), complex(np.nan, np.nan)) 示例2: test_expm1_complex_hard
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def test_expm1_complex_hard(self):
# The real part of this function is difficult to evaluate when
# z.real = -log(cos(z.imag)).
y = np.array([0.1, 0.2, 0.3, 5, 11, 20])
x = -np.log(np.cos(y))
z = x + 1j*y
# evaluate using mpmath.expm1 with dps=1000
expected = np.array([-5.5507901846769623e-17+0.10033467208545054j,
2.4289354732893695e-18+0.20271003550867248j,
4.5235500262585768e-17+0.30933624960962319j,
7.8234305217489006e-17-3.3805150062465863j,
-1.3685191953697676e-16-225.95084645419513j,
8.7175620481291045e-17+2.2371609442247422j])
found = cephes.expm1(z)
# this passes.
assert_array_almost_equal_nulp(found.imag, expected.imag, 3)
# this fails.
assert_array_almost_equal_nulp(found.real, expected.real, 20) 示例3: _stats
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _stats(self, c):
g = lambda n: sc.gamma(n*c + 1)
g1 = g(1)
g2 = g(2)
g3 = g(3)
g4 = g(4)
g2mg12 = np.where(abs(c) < 1e-7, (c*np.pi)**2.0/6.0, g2-g1**2.0)
gam2k = np.where(abs(c) < 1e-7, np.pi**2.0/6.0,
sc.expm1(sc.gammaln(2.0*c+1.0)-2*sc.gammaln(c + 1.0))/c**2.0)
eps = 1e-14
gamk = np.where(abs(c) < eps, -_EULER, sc.expm1(sc.gammaln(c + 1))/c)
m = np.where(c < -1.0, np.nan, -gamk)
v = np.where(c < -0.5, np.nan, g1**2.0*gam2k)
# skewness
sk1 = np.where(c < -1./3, np.nan,
np.sign(c)*(-g3+(g2+2*g2mg12)*g1)/((g2mg12)**(3./2.)))
sk = np.where(abs(c) <= eps**0.29, 12*np.sqrt(6)*_ZETA3/np.pi**3, sk1)
# kurtosis
ku1 = np.where(c < -1./4, np.nan,
(g4+(-4*g3+3*(g2+g2mg12)*g1)*g1)/((g2mg12)**2))
ku = np.where(abs(c) <= (eps)**0.23, 12.0/5.0, ku1-3.0)
return m, v, sk, ku 示例4: _ppf
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _ppf(self, q, c):
return sc.expm1(q * sc.log1p(c)) / c 示例5: _cdf
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _cdf(self, x, c, d):
return -sc.expm1(self._logsf(x, c, d)) 示例6: _logpdf
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _logpdf(self, x, a, c):
negxc = -x**c
exm1c = -sc.expm1(negxc)
logp = (np.log(a) + np.log(c) + sc.xlogy(a - 1.0, exm1c) +
negxc + sc.xlogy(c - 1.0, x))
return logp 示例7: _sf
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _sf(self, x, b):
return np.exp(-sc.expm1(x**b)) 示例8: _pdf
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _pdf(self, x, a, b, c):
# genexpon.pdf(x, a, b, c) = (a + b * (1 - exp(-c*x))) * \
# exp(-a*x - b*x + b/c * (1-exp(-c*x)))
return (a + b*(-sc.expm1(-c*x)))*np.exp((-a-b)*x +
b*(-sc.expm1(-c*x))/c) 示例9: _isf
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _isf(self, q, c):
x = -np.log(-sc.log1p(-q))
return _lazywhere((x == x) & (c != 0), (x, c),
lambda x, c: -sc.expm1(-c * x) / c, x) 示例10: _stats
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _stats(self, c):
g = lambda n: sc.gamma(n*c + 1)
g1 = g(1)
g2 = g(2)
g3 = g(3)
g4 = g(4)
g2mg12 = np.where(abs(c) < 1e-7, (c*np.pi)**2.0/6.0, g2-g1**2.0)
gam2k = np.where(abs(c) < 1e-7, np.pi**2.0/6.0,
sc.expm1(sc.gammaln(2.0*c+1.0)-2*sc.gammaln(c + 1.0))/c**2.0)
eps = 1e-14
gamk = np.where(abs(c) < eps, -_EULER, sc.expm1(sc.gammaln(c + 1))/c)
m = np.where(c < -1.0, np.nan, -gamk)
v = np.where(c < -0.5, np.nan, g1**2.0*gam2k)
# skewness
sk1 = _lazywhere(c >= -1./3,
(c, g1, g2, g3, g2mg12),
lambda c, g1, g2, g3, g2gm12:
np.sign(c)*(-g3 + (g2 + 2*g2mg12)*g1)/g2mg12**1.5,
fillvalue=np.nan)
sk = np.where(abs(c) <= eps**0.29, 12*np.sqrt(6)*_ZETA3/np.pi**3, sk1)
# kurtosis
ku1 = _lazywhere(c >= -1./4,
(g1, g2, g3, g4, g2mg12),
lambda g1, g2, g3, g4, g2mg12:
(g4 + (-4*g3 + 3*(g2 + g2mg12)*g1)*g1)/g2mg12**2,
fillvalue=np.nan)
ku = np.where(abs(c) <= (eps)**0.23, 12.0/5.0, ku1-3.0)
return m, v, sk, ku 示例11: _munp
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def _munp(self, n, b):
# wrong answer with formula, same as in continuous.pdf
# return sc.gamman+1)-sc.gammainc1+n, b)
if n == 1:
return (1-(b+1)*np.exp(-b))/(-sc.expm1(-b))
elif n == 2:
return 2*(1-0.5*(b*b+2*b+2)*np.exp(-b))/(-sc.expm1(-b))
else:
# return generic for higher moments
# return rv_continuous._mom1_sc(self, n, b)
return self._mom1_sc(n, b) 示例12: copula_bv_frank
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def copula_bv_frank(u, v, theta):
'''Cook, Johnson bivariate copula
'''
if not theta > 0:
raise ValueError('theta needs to be strictly positive')
cdfv = -np.log(1 + expm1(-theta*u) * expm1(-theta*v) / expm1(-theta))/theta
cdfv = np.minimum(cdfv, 1) #necessary for example if theta=100
return cdfv 示例13: evaluate
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def evaluate(self, t, theta):
return - (np.log(-expm1(-theta*t)) - np.log(-expm1(-theta)))
#return - np.log(expm1(-theta*t) / expm1(-theta)) 示例14: inverse
# 需要导入模块: from scipy import special [as 别名]
# 或者: from scipy.special import expm1 [as 别名]
def inverse(self, phi, theta):
return -np.log1p(np.exp(-phi) * expm1(-theta)) / theta