fix some type errors; add more comments
This commit is contained in:
Haiming Zhang
parent
43b665ba48
commit
0097d39873
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@ -237,15 +237,16 @@ def Tresca(eqStress, paras, sigmas, mFix, criteria, Jac = False):
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'''
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Tresca yield criterion
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the fitted parameters is: paras(sigma0)
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eqStress, mFix, criteria are invalid input
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'''
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lambdas = principalStresses(sigmas)
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r = np.amax(np.array([abs(lambdas[2,:]-lambdas[1,:]),\
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abs(lambdas[1,:]-lambdas[0,:]),\
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abs(lambdas[0,:]-lambdas[2,:])]),0) - paras
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if not Jac:
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lambdas = principalStresses(sigmas)
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r = np.amax(np.array([abs(lambdas[2,:]-lambdas[1,:]),\
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abs(lambdas[1,:]-lambdas[0,:]),\
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abs(lambdas[0,:]-lambdas[2,:])]),0) - paras
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return r.ravel()
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else:
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return -np.ones(len(r))
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return -np.ones(len(sigmas))
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def Cazacu_Barlat(eqStress, paras, sigmas, mFix, criteria, Jac = False):
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'''
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@ -334,7 +335,7 @@ def Hill1948(eqStress, paras, sigmas, mFix, criteria, Jac = False):
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'''
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Hill 1948 yield criterion
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the fitted parameters are F, G, H, L, M, N
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eqStress, criteria are invalid input
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eqStress, mFix, criteria are invalid input
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'''
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s11,s22,s33,s12,s23,s31 = sigmas
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jac = np.array([(s22-s33)**2,(s33-s11)**2,(s11-s22)**2, 2.0*s23**2,2.0*s31**2,2.0*s12**2])
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@ -347,6 +348,7 @@ def Hill1979(eqStress,paras, sigmas, mFix, criteria, Jac = False):
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'''
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Hill 1979 yield criterion
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the fitted parameters are: f,g,h,a,b,c,m
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criteria are invalid input
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'''
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if mFix[0]: m = mFix[1]
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else: m = paras[-1]
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@ -379,16 +381,16 @@ def Hosford(eqStress, paras, sigmas, mFix, criteria, Jac = False):
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if criteria == 'vonmises':
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coeff = np.ones(3)
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a = 2.0
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sigma0 = paras
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a = 2.0
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elif criteria == 'hershey':
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coeff = np.ones(3)
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sigma0 = paras[0]
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if mFix[0]: a = mFix[1]
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else: a = paras[1]
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coeff = np.ones(3)
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else:
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print '11'
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coeff = paras[0:3]
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coeff = paras[0:3]
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sigma0 = eqStress
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if mFix[0]: a = mFix[1]
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else: a = paras[3]
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@ -421,6 +423,7 @@ def Barlat1991(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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the fitted parameters are:
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Isotropic: sigma0, m
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Anisotropic: a, b, c, f, g, h, m
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m is optional
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'''
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if criteria == 'barlat1991iso':
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sigma0 = paras[0]
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@ -451,7 +454,7 @@ def Barlat1991(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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jm = r*math_ln(left)/(-m**2) + dfdl*0.5*(
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absc1**m*math_ln(absc1) + absc2**m*math_ln(absc2) + absc3**m*math_ln(absc3) )
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if criteria == 'barlat1991iso':
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js = -(r + 1.0)/sigma0
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js = -r/sigma0
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if mFix[0]: return js
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else: return np.vstack((js,jm)).T
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else:
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@ -471,7 +474,10 @@ def Barlat1991(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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def BBC2003(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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'''
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residuum of the BBC2003 yield criterion for plain stress
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BBC2003 yield criterion
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the fitted parameters are
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a, b, c, d, e, f, g, k; k is optional
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criteria are invalid input
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'''
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a,b,c, d,e,f,g= paras[0:7]
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if mFix[0]: k = mFix[1]
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@ -524,7 +530,10 @@ def BBC2003(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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def BBC2005(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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'''
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residuum of the BBC2005 yield criterion for plain stress
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BBC2005 yield criterion
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the fitted parameters are
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a, b, L ,M, N, P, Q, R, k; k is optional
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criteria are invalid input
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'''
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a,b,L, M, N, P, Q, R = paras[0:8]
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if mFix[0]: k = mFix[1]
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@ -571,8 +580,11 @@ def BBC2005(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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def Yld200418p(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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'''
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C: c12,c21,c23,c32,c13,c31,c44,c55,c66
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D: d12,d21,d23,d32,d31,d13,d44,d55,d66
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Yld2004-18p yield criterion
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the fitted parameters are
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C: c12,c21,c23,c32,c13,c31,c44,c55,c66; D: d12,d21,d23,d32,d31,d13,d44,d55,d66
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and m, m is optional
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criteria are invalid input
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'''
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C,D = paras[0:9], paras[9:18]
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if mFix[0]: m = mFix[1]
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@ -610,14 +622,21 @@ def Yld200418p(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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else: return np.vstack((jc,jd,jm)).T
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def KarafillisBoyce(eqStress, paras, sigmas, mFix, criteria, Jac=False):
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'''
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Karafillis-Boyce yield criterion
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the fitted parameters are
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c11,c12,c13,c14,c15,c16,c21,c22,c23,c24,c25,c26,alpha,b1,b2,a
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0<alpha<1, b1,b2,a are optional
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criteria are invalid input
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'''
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ks = lambda (s1,s2,s3,s4,s5,s6),(c1,c2,c3,c4,c5,c6): np.array( [
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((c2+c3)*s1-c3*s2-c2*s3)/3.0, ((c3+c1)*s2-c3*s1-c1*s3)/3.0,
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((c1+c2)*s3-c2*s1-c1*s2)/3.0, c4*s4, c5*s5, c6*s6 ])
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C1,C2,alpha = paras[0:6], paras[6:12], paras[12]
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if mFix[0]: b1=b2=a = mFix[1]
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else: b1,b2,a = paras[12:15]
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print b1,b2,a
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else: b1,b2,a = paras[13:16]
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p,q = ks(sigmas, C1), ks(sigmas, C2)
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plambdas,qlambdas = principalStress(p), principalStress(q)
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b1i,b2i,ai,rb2 = 1.0/b1, 1.0/b2, 1.0/a, 3.0**b2/(2.0**b2+2.0)
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@ -1109,11 +1128,11 @@ parser.add_option('-t','--threads', dest='threads', type='int',
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parser.add_option('-d','--dimension', dest='dimension', type='int',
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help='dimension of the virtual test [%default]', metavar='int')
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parser.add_option('-v', '--vegter', dest='vegter', action='store_true',
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help='Vegter criteria [%default]')
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help='Vegter criteria [%default]', metavar='float')
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parser.add_option('-e', '--exponent',dest='exponent', type='float',
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help='exponent of non-quadratic criteria')
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parser.add_option('-u', '--uniaxial',dest='eqStress', type='float',
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help='Equivalent stress')
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help='Equivalent stress', metavar='float')
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parser.set_defaults(min = 12)
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parser.set_defaults(max = 30)
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parser.set_defaults(threads = 4)
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@ -1145,9 +1164,6 @@ if options.yieldValue[2] != int(options.yieldValue[2]):
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if not os.path.isfile('numerics.config'):
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print('numerics.config file not found')
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if not os.path.isfile('material.config'):
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print('material.config file not found')
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numParas = len(fitCriteria[options.criterion]['bound'])
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nExpo = fitCriteria[options.criterion]['nExpo']
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Guess = []
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@ -1161,8 +1177,7 @@ for i in xrange(numParas):
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g = (temp[0]+temp[1])/2.0
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if g == 0: g = temp[1]*0.5
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Guess.append(g)
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print Guess
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print fitCriteria[options.criterion]['bound']
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if options.vegter is True:
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options.dimension = 2
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unitGPa = 10.e8
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