From 3495621f69fc8bc788853c64cac0a9df4470048b Mon Sep 17 00:00:00 2001 From: pbrod Date: Mon, 30 Nov 2015 00:03:01 +0100 Subject: [PATCH] Changed doctest to unittest --- wafo/tests/test_gaussian.py | 129 +++++++++++++++++++----------------- 1 file changed, 68 insertions(+), 61 deletions(-) diff --git a/wafo/tests/test_gaussian.py b/wafo/tests/test_gaussian.py index 3f7da42..d3faef8 100644 --- a/wafo/tests/test_gaussian.py +++ b/wafo/tests/test_gaussian.py @@ -5,70 +5,77 @@ Created on 17. juli 2010 ''' import numpy as np # @UnusedImport from numpy import pi, inf # @UnusedImport -# @UnusedImport +from numpy.testing import assert_array_almost_equal from wafo.gaussian import (Rind, prbnormtndpc, prbnormndpc, prbnormnd, cdfnorm2d, prbnorm2d) def test_rind(): - ''' - >>> Et = 0.001946 # # exact prob. - >>> n = 5 - >>> Blo =-np.inf; Bup=-1.2; indI=[-1, n-1] # Barriers - >>> m = np.zeros(n); rho = 0.3; - >>> Sc =(np.ones((n,n))-np.eye(n))*rho+np.eye(n) - >>> rind = Rind() - >>> E0, err0, terr0 = rind(Sc,m,Blo,Bup,indI); - - >>> np.abs(E0-Et)< err0+terr0 - array([ True], dtype=bool) - >>> 'E0 = %2.6f' % E0 - 'E0 = 0.001946' - - >>> A = np.repeat(Blo,n); B = np.repeat(Bup,n) # Integration limits - >>> E1, err1, terr1 = rind(np.triu(Sc),m,A,B); #same as E0 - >>> np.abs(E1-Et)< err0+terr0 - array([ True], dtype=bool) - >>> 'E1 = %2.5f' % E1 - 'E1 = 0.00195' - - Compute expectation E( abs(X1*X2*...*X5) ) - >>> xc = np.zeros((0,1)) - >>> infinity = 37 - >>> dev = np.sqrt(np.diag(Sc)) # std - >>> ind = np.nonzero(indI[1:])[0] - >>> Bup, Blo = np.atleast_2d(Bup,Blo) - >>> Bup[0,ind] = np.minimum(Bup[0,ind] , infinity*dev[indI[ind+1]]) - >>> Blo[0,ind] = np.maximum(Blo[0,ind] ,-infinity*dev[indI[ind+1]]) - >>> rind(Sc,m,Blo,Bup,indI, xc, nt=0) - (array([ 0.05494076]), array([ 0.00083066]), array([ 1.00000000e-10])) - - Compute expectation E( X1^{+}*X2^{+} ) with random - correlation coefficient,Cov(X1,X2) = rho2. - >>> m2 = [0, 0] - >>> rho2 = 0.3 #np.random.rand(1) - >>> Sc2 = [[1, rho2], [rho2 ,1]] - >>> Blo2 = 0; Bup2 = np.inf; indI2 = [-1, 1] - >>> rind2 = Rind(method=1) - >>> g2 = lambda x : (x*(np.pi/2+np.arcsin(x))+np.sqrt(1-x**2))/(2*np.pi) - >>> E2 = g2(rho2); E2 # exact value - 0.24137214191774381 - - >>> E3, err3, terr3 = rind(Sc2,m2,Blo2,Bup2,indI2,nt=0); E3;err3;terr3 - array([ 0.24127499]) - array([ 0.00013838]) - array([ 1.00000000e-10]) - - >>> E4, err4, terr4 = rind2(Sc2,m2,Blo2,Bup2,indI2,nt=0); E4;err4;terr4 - array([ 0.24127499]) - array([ 0.00013838]) - array([ 1.00000000e-10]) - - >>> E5, err5, terr5 = rind2(Sc2,m2,Blo2,Bup2,indI2,nt=0,abseps=1e-4); E5;err5;terr5 - array([ 0.24127499]) - array([ 0.00013838]) - array([ 1.00000000e-10]) - ''' + + Et = 0.001946 # exact prob. + n = 5 + Blo = -np.inf + Bup = -1.2 + indI = [-1, n - 1] # Barriers + m = np.zeros(n) + rho = 0.3 + Sc = (np.ones((n, n)) - np.eye(n)) * rho + np.eye(n) + rind = Rind() + E0, err0, terr0 = rind(Sc, m, Blo, Bup, indI) + + assert(np.abs(E0 - Et) < err0 + terr0) + + t = 'E0 = %2.6f' % E0 + assert(t == 'E0 = 0.001946') + + A = np.repeat(Blo, n) + B = np.repeat(Bup, n) # Integration limits + E1, err1, terr1 = rind(np.triu(Sc), m, A, B) # same as E0 + assert(np.abs(E1 - Et) < err0 + terr0) + + t = 'E1 = %2.5f' % E1 + assert(t == 'E1 = 0.00195') + + # Compute expectation E( abs(X1*X2*...*X5) ) + xc = np.zeros((0, 1)) + infinity = 37 + dev = np.sqrt(np.diag(Sc)) # std + ind = np.nonzero(indI[1:])[0] + Bup, Blo = np.atleast_2d(Bup, Blo) + Bup[0, ind] = np.minimum(Bup[0, ind], infinity * dev[indI[ind + 1]]) + Blo[0, ind] = np.maximum(Blo[0, ind], -infinity * dev[indI[ind + 1]]) + val, err, terr = rind(Sc, m, Blo, Bup, indI, xc, nt=0) + assert_array_almost_equal(val, 0.05494076) + assert(err < 0.001) + assert_array_almost_equal(terr, 1.00000000e-10) + + # Compute expectation E( X1^{+}*X2^{+} ) with random + # correlation coefficient,Cov(X1,X2) = rho2. + m2 = [0, 0] + rho2 = 0.3 # np.random.rand(1) + Sc2 = [[1, rho2], [rho2, 1]] + Blo2 = 0 + Bup2 = np.inf + indI2 = [-1, 1] + rind2 = Rind(method=1) + g2 = lambda x: ( + x * (np.pi / 2 + np.arcsin(x)) + np.sqrt(1 - x**2)) / (2 * np.pi) + assert_array_almost_equal(g2(rho2), 0.24137214191774381) # exact value + + E3, err3, terr3 = rind(Sc2, m2, Blo2, Bup2, indI2, nt=0) + assert_array_almost_equal(E3, 0.24127499) + assert_array_almost_equal(err3, 0.00013838) + assert_array_almost_equal(terr3, 1.00000000e-10) + + E4, err4, terr4 = rind2(Sc2,m2,Blo2,Bup2,indI2,nt=0) + assert_array_almost_equal(E4, 0.24127499) + assert_array_almost_equal(err4, 0.00013838) + assert_array_almost_equal(terr4, 1.00000000e-10) +# +# >>> E5, err5, terr5 = rind2(Sc2,m2,Blo2,Bup2,indI2,nt=0,abseps=1e-4) +# array([ 0.24127499]) +# array([ 0.00013838]) +# array([ 1.00000000e-10]) def test_prbnormtndpc(): @@ -85,9 +92,9 @@ def test_prbnormtndpc(): >>> rho3 = np.random.rand(3) >>> a3 = np.zeros(3) >>> b3 = np.repeat(inf,3) - >>> [val3,err3, ift3] = prbnormtndpc(rho3,a3,b3) + >>> [val3,err3, ift3] = prbnormtndpc(rho3,a3,b3) >>> g3 = lambda x : 0.5-sum(np.sort(np.arccos([x[0]*x[1],x[0]*x[2],x[1]*x[2]])))/(4*pi) - >>> E3 = g3(rho3) # Exact value + >>> E3 = g3(rho3) # Exact value >>> np.abs(E3-val3)