本文整理汇总了Python中scipy.integrate.nquad方法的典型用法代码示例。如果您正苦于以下问题:Python integrate.nquad方法的具体用法?Python integrate.nquad怎么用?Python integrate.nquad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scipy.integrate
的用法示例。
在下文中一共展示了integrate.nquad方法的15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: getThresholdMoments
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def getThresholdMoments(x,myP,whichModel):
if whichModel==0: # Gaussian
M1,err = nInt.quad(integrateGaussianMoment,-5,5,args=(x[0],myP,1))
M2,err = nInt.quad(integrateGaussianMoment,-5,5,args=(x[0],myP,2))
elif whichModel==1: # t
lowerBound = np.maximum(x[1]-40,2)
support = [[-7,7],[lowerBound,x[1]+40]]
M1,err=nInt.nquad(thresholdMoment,support,args=(x[0],x[1],myP,whichModel,1))
M2,err=nInt.nquad(thresholdMoment,support,args=(x[0],x[1],myP,whichModel,2))
elif whichModel==2: # Variance-gamma
invCdf = th.nvmPpf(myP,x[1],0)
support = [[-7,7],[0,100]]
M1,err=nInt.nquad(thresholdMoment,support,args=(x[0],x[1],myP,whichModel,1,invCdf))
M2,err=nInt.nquad(thresholdMoment,support,args=(x[0],x[1],myP,whichModel,2,invCdf))
elif whichModel==3: # Generalized hyperbolic
invCdf = th.nvmPpf(myP,x[1],1)
support = [[-7,7],[0,100]]
M1,err=nInt.nquad(thresholdMoment,support,args=(x[0],x[1],myP,whichModel,1,invCdf))
M2,err=nInt.nquad(thresholdMoment,support,args=(x[0],x[1],myP,whichModel,2,invCdf))
return M1,M2
示例2: compute_expectation
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def compute_expectation(model, fun):
# Computes the expectation of fun(th) wrt the posterior distribution,
# given by exp(model.log_p_marg(th))
th_shape = model.th_shape
L = np.prod(th_shape)
lims = [[-np.inf, np.inf]] * L
def integrand(*args):
th = np.array(args).reshape(th_shape)
return np.exp(model.log_p_marg(th)) * fun(th)
return integrate.nquad(integrand, lims)[0]
示例3: test_fixed_limits
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_fixed_limits(self):
def func1(x0, x1, x2, x3):
return x0**2 + x1*x2 - x3**3 + np.sin(x0) + (1 if
(x0 - 0.2*x3 - 0.5 - 0.25*x1 > 0) else 0)
def opts_basic(*args):
return {'points' : [0.2*args[2] + 0.5 + 0.25*args[0]]}
res = nquad(func1, [[0,1], [-1,1], [.13,.8], [-.15,1]],
opts=[opts_basic, {}, {}, {}])
assert_quad(res, 1.5267454070738635)
示例4: test_variable_limits
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_variable_limits(self):
scale = .1
def func2(x0, x1, x2, x3, t0, t1):
return x0*x1*x3**2 + np.sin(x2) + 1 + (1 if x0 + t1*x1 - t0 > 0 else 0)
def lim0(x1, x2, x3, t0, t1):
return [scale * (x1**2 + x2 + np.cos(x3)*t0*t1 + 1) - 1,
scale * (x1**2 + x2 + np.cos(x3)*t0*t1 + 1) + 1]
def lim1(x2, x3, t0, t1):
return [scale * (t0*x2 + t1*x3) - 1,
scale * (t0*x2 + t1*x3) + 1]
def lim2(x3, t0, t1):
return [scale * (x3 + t0**2*t1**3) - 1,
scale * (x3 + t0**2*t1**3) + 1]
def lim3(t0, t1):
return [scale * (t0 + t1) - 1, scale * (t0 + t1) + 1]
def opts0(x1, x2, x3, t0, t1):
return {'points':[t0 - t1*x1]}
def opts1(x2, x3, t0, t1):
return {}
def opts2(x3, t0, t1):
return {}
def opts3(t0, t1):
return {}
res = nquad(func2, [lim0, lim1, lim2, lim3], args=(0,0),
opts=[opts0, opts1, opts2, opts3])
assert_quad(res, 25.066666666666663)
示例5: test_square_separate_ranges_and_opts
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_square_separate_ranges_and_opts(self):
def f(y, x):
return 1.0
assert_quad(nquad(f, [[-1, 1], [-1, 1]], opts=[{}, {}]), 4.0)
示例6: test_square_aliased_ranges_and_opts
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_square_aliased_ranges_and_opts(self):
def f(y, x):
return 1.0
r = [-1, 1]
opt = {}
assert_quad(nquad(f, [r, r], opts=[opt, opt]), 4.0)
示例7: test_square_separate_fn_ranges_and_opts
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_square_separate_fn_ranges_and_opts(self):
def f(y, x):
return 1.0
def fn_range0(*args):
return (-1, 1)
def fn_range1(*args):
return (-1, 1)
def fn_opt0(*args):
return {}
def fn_opt1(*args):
return {}
ranges = [fn_range0, fn_range1]
opts = [fn_opt0, fn_opt1]
assert_quad(nquad(f, ranges, opts=opts), 4.0)
示例8: test_matching_quad
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_matching_quad(self):
def func(x):
return x**2 + 1
res, reserr = quad(func, 0, 4)
res2, reserr2 = nquad(func, ranges=[[0, 4]])
assert_almost_equal(res, res2)
assert_almost_equal(reserr, reserr2)
示例9: test_matching_dblquad
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_matching_dblquad(self):
def func2d(x0, x1):
return x0**2 + x1**3 - x0 * x1 + 1
res, reserr = dblquad(func2d, -2, 2, lambda x:-3, lambda x:3)
res2, reserr2 = nquad(func2d, [[-3, 3], (-2, 2)])
assert_almost_equal(res, res2)
assert_almost_equal(reserr, reserr2)
示例10: test_matching_tplquad
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_matching_tplquad(self):
def func3d(x0, x1, x2, c0, c1):
return x0**2 + c0 * x1**3 - x0 * x1 + 1 + c1 * np.sin(x2)
res = tplquad(func3d, -1, 2, lambda x:-2, lambda x:2,
lambda x, y : -np.pi, lambda x, y : np.pi,
args=(2, 3))
res2 = nquad(func3d, [[-np.pi, np.pi], [-2, 2], (-1, 2)], args=(2, 3))
assert_almost_equal(res, res2)
示例11: ise
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def ise(estimateddensity, theoreticaldensity):
def integrand(*x):
value = np.array(x)
return (estimateddensity(value) - theoreticaldensity(value))**2
return integrate.nquad(integrand, [[-5., 5.], [-5., 5.]])
示例12: test_integrate_2d
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_integrate_2d(self):
np.random.seed(1234)
c = np.random.rand(4, 5, 16, 17)
x = np.linspace(0, 1, 16+1)**1
y = np.linspace(0, 1, 17+1)**2
# make continuously differentiable so that nquad() has an
# easier time
c = c.transpose(0, 2, 1, 3)
cx = c.reshape(c.shape[0], c.shape[1], -1).copy()
_ppoly.fix_continuity(cx, x, 2)
c = cx.reshape(c.shape)
c = c.transpose(0, 2, 1, 3)
c = c.transpose(1, 3, 0, 2)
cx = c.reshape(c.shape[0], c.shape[1], -1).copy()
_ppoly.fix_continuity(cx, y, 2)
c = cx.reshape(c.shape)
c = c.transpose(2, 0, 3, 1).copy()
# Check integration
p = NdPPoly(c, (x, y))
for ranges in [[(0, 1), (0, 1)],
[(0, 0.5), (0, 1)],
[(0, 1), (0, 0.5)],
[(0.3, 0.7), (0.6, 0.2)]]:
ig = p.integrate(ranges)
ig2, err2 = nquad(lambda x, y: p((x, y)), ranges,
opts=[dict(epsrel=1e-5, epsabs=1e-5)]*2)
assert_allclose(ig, ig2, rtol=1e-5, atol=1e-5,
err_msg=repr(ranges))
示例13: test_fixed_limits
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_fixed_limits(self):
def func1(x0, x1, x2, x3):
val = (x0**2 + x1*x2 - x3**3 + np.sin(x0) +
(1 if (x0 - 0.2*x3 - 0.5 - 0.25*x1 > 0) else 0))
return val
def opts_basic(*args):
return {'points': [0.2*args[2] + 0.5 + 0.25*args[0]]}
res = nquad(func1, [[0, 1], [-1, 1], [.13, .8], [-.15, 1]],
opts=[opts_basic, {}, {}, {}], full_output=True)
assert_quad(res[:-1], 1.5267454070738635)
assert_(res[-1]['neval'] > 0 and res[-1]['neval'] < 4e5)
示例14: test_variable_limits
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_variable_limits(self):
scale = .1
def func2(x0, x1, x2, x3, t0, t1):
val = (x0*x1*x3**2 + np.sin(x2) + 1 +
(1 if x0 + t1*x1 - t0 > 0 else 0))
return val
def lim0(x1, x2, x3, t0, t1):
return [scale * (x1**2 + x2 + np.cos(x3)*t0*t1 + 1) - 1,
scale * (x1**2 + x2 + np.cos(x3)*t0*t1 + 1) + 1]
def lim1(x2, x3, t0, t1):
return [scale * (t0*x2 + t1*x3) - 1,
scale * (t0*x2 + t1*x3) + 1]
def lim2(x3, t0, t1):
return [scale * (x3 + t0**2*t1**3) - 1,
scale * (x3 + t0**2*t1**3) + 1]
def lim3(t0, t1):
return [scale * (t0 + t1) - 1, scale * (t0 + t1) + 1]
def opts0(x1, x2, x3, t0, t1):
return {'points': [t0 - t1*x1]}
def opts1(x2, x3, t0, t1):
return {}
def opts2(x3, t0, t1):
return {}
def opts3(t0, t1):
return {}
res = nquad(func2, [lim0, lim1, lim2, lim3], args=(0, 0),
opts=[opts0, opts1, opts2, opts3])
assert_quad(res, 25.066666666666663)
示例15: test_square_aliased_fn_ranges_and_opts
# 需要导入模块: from scipy import integrate [as 别名]
# 或者: from scipy.integrate import nquad [as 别名]
def test_square_aliased_fn_ranges_and_opts(self):
def f(y, x):
return 1.0
def fn_range(*args):
return (-1, 1)
def fn_opt(*args):
return {}
ranges = [fn_range, fn_range]
opts = [fn_opt, fn_opt]
assert_quad(nquad(f, ranges, opts=opts), 4.0)