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from numpy import (pi, r_, minimum, maximum, atleast_1d, atleast_2d, mod, ones,
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from numpy import (r_, minimum, maximum, atleast_1d, atleast_2d, mod, ones,
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floor, random, eye, nonzero, where, repeat, sqrt, exp, inf,
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floor, random, eye, nonzero, where, repeat, sqrt, exp, inf,
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diag, zeros, sin, arcsin, nan) # @UnresolvedImport
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diag, zeros, sin, arcsin, nan)
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from numpy import triu # @UnresolvedImport
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from numpy import triu
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from scipy.special import ndtr as cdfnorm, ndtri as invnorm
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from scipy.special import ndtr as cdfnorm, ndtri as invnorm
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from scipy.special import erfc
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from scipy.special import erfc
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from wafo import mvn
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from wafo import mvn
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@ -95,8 +95,9 @@ class Rind(object):
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>>> Bup, Blo = np.atleast_2d(Bup,Blo)
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>>> Bup, Blo = np.atleast_2d(Bup,Blo)
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>>> Bup[0,ind] = np.minimum(Bup[0,ind] , infinity*dev[indI[ind+1]])
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>>> Bup[0,ind] = np.minimum(Bup[0,ind] , infinity*dev[indI[ind+1]])
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>>> Blo[0,ind] = np.maximum(Blo[0,ind] ,-infinity*dev[indI[ind+1]])
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>>> Blo[0,ind] = np.maximum(Blo[0,ind] ,-infinity*dev[indI[ind+1]])
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>>> rind(Sc,m,Blo,Bup,indI, xc, nt=0)
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>>> np.allclose(rind(Sc,m,Blo,Bup,indI, xc, nt=0),
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(array([ 0.05494076]), array([ 0.00083066]), array([ 1.00000000e-10]))
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... ([0.05494076], [ 0.00083066], [ 1.00000000e-10]), rtol=1e-3)
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True
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Compute expectation E( X1^{+}*X2^{+} ) with random
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Compute expectation E( X1^{+}*X2^{+} ) with random
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correlation coefficient,Cov(X1,X2) = rho2.
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correlation coefficient,Cov(X1,X2) = rho2.
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@ -104,7 +105,8 @@ class Rind(object):
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>>> Sc2 = [[1, rho2], [rho2 ,1]]
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>>> Sc2 = [[1, rho2], [rho2 ,1]]
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>>> Blo2 = 0; Bup2 = np.inf; indI2 = [-1, 1]
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>>> Blo2 = 0; Bup2 = np.inf; indI2 = [-1, 1]
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>>> rind2 = wg.Rind(method=1)
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>>> rind2 = wg.Rind(method=1)
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>>> g2 = lambda x : (x*(np.pi/2+np.arcsin(x))+np.sqrt(1-x**2))/(2*np.pi)
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>>> def g2(x):
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... return (x*(np.pi/2+np.arcsin(x))+np.sqrt(1-x**2))/(2*np.pi)
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>>> E2 = g2(rho2) # exact value
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>>> E2 = g2(rho2) # exact value
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>>> E3 = rind(Sc2,m2,Blo2,Bup2,indI2,nt=0)
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>>> E3 = rind(Sc2,m2,Blo2,Bup2,indI2,nt=0)
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>>> E4 = rind2(Sc2,m2,Blo2,Bup2,indI2,nt=0)
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>>> E4 = rind2(Sc2,m2,Blo2,Bup2,indI2,nt=0)
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@ -482,7 +484,8 @@ def prbnormtndpc(rho, a, b, D=None, df=0, abseps=1e-4, IERC=0, HNC=0.24):
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>>> a2 = np.zeros(2)
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>>> a2 = np.zeros(2)
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>>> b2 = np.repeat(np.inf,2)
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>>> b2 = np.repeat(np.inf,2)
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>>> [val2,err2, ift2] = wg.prbnormtndpc(rho2,a2,b2)
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>>> [val2,err2, ift2] = wg.prbnormtndpc(rho2,a2,b2)
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>>> g2 = lambda x : 0.25+np.arcsin(x[0]*x[1])/(2*pi)
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>>> def g2(x):
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... return 0.25+np.arcsin(x[0]*x[1])/(2*np.pi)
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>>> E2 = g2(rho2) # exact value
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>>> E2 = g2(rho2) # exact value
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>>> np.abs(E2-val2)<err2
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>>> np.abs(E2-val2)<err2
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True
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True
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@ -490,10 +493,12 @@ def prbnormtndpc(rho, a, b, D=None, df=0, abseps=1e-4, IERC=0, HNC=0.24):
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>>> rho3 = np.random.rand(3)
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>>> rho3 = np.random.rand(3)
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>>> a3 = np.zeros(3)
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>>> a3 = np.zeros(3)
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>>> b3 = np.repeat(inf,3)
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>>> b3 = np.repeat(inf,3)
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>>> [val3,err3, ift3] = wg.prbnormtndpc(rho3,a3,b3)
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>>> [val3, err3, ift3] = wg.prbnormtndpc(rho3,a3,b3)
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>>> g3 = lambda x : 0.5-sum(np.sort(np.arccos([x[0]*x[1],x[0]*x[2],x[1]*x[2]])))/(4*pi)
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>>> def g3(x):
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... return 0.5-sum(np.sort(np.arccos([x[0]*x[1],
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... x[0]*x[2],x[1]*x[2]])))/(4*np.pi)
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>>> E3 = g3(rho3) # Exact value
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>>> E3 = g3(rho3) # Exact value
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>>> np.abs(E3-val3)<err2
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>>> np.abs(E3-val3) < 5 * err2
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True
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True
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@ -547,7 +552,7 @@ def prbnormndpc(rho, a, b, abserr=1e-4, relerr=1e-4, usesimpson=True,
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>>> a2 = np.zeros(2)
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>>> a2 = np.zeros(2)
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>>> b2 = np.repeat(np.inf,2)
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>>> b2 = np.repeat(np.inf,2)
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>>> [val2,err2, ift2] = wg.prbnormndpc(rho2,a2,b2)
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>>> [val2,err2, ift2] = wg.prbnormndpc(rho2,a2,b2)
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>>> g2 = lambda x : 0.25+np.arcsin(x[0]*x[1])/(2*pi)
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>>> g2 = lambda x : 0.25+np.arcsin(x[0]*x[1])/(2*np.pi)
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>>> E2 = g2(rho2) #% exact value
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>>> E2 = g2(rho2) #% exact value
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>>> np.abs(E2-val2)<err2
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>>> np.abs(E2-val2)<err2
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True
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True
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@ -556,7 +561,9 @@ def prbnormndpc(rho, a, b, abserr=1e-4, relerr=1e-4, usesimpson=True,
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>>> a3 = np.zeros(3)
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>>> a3 = np.zeros(3)
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>>> b3 = np.repeat(inf,3)
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>>> b3 = np.repeat(inf,3)
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>>> [val3,err3, ift3] = wg.prbnormndpc(rho3,a3,b3)
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>>> [val3,err3, ift3] = wg.prbnormndpc(rho3,a3,b3)
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>>> g3 = lambda x : 0.5-sum(np.sort(np.arccos([x[0]*x[1],x[0]*x[2],x[1]*x[2]])))/(4*pi)
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>>> def g3(x):
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... return 0.5-sum(np.sort(np.arccos([x[0]*x[1],
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... x[0]*x[2],x[1]*x[2]])))/(4*np.pi)
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>>> E3 = g3(rho3) # Exact value
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>>> E3 = g3(rho3) # Exact value
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>>> np.abs(E3-val3)<err2
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>>> np.abs(E3-val3)<err2
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True
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True
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