von Mises fitting seems to work, still needs polishing (adding options etc)
This commit is contained in:
Martin Diehl
parent
5f638a059a
commit
fd2164b391
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@ -4,10 +4,13 @@
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import numpy as np
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from scipy.optimize import curve_fit
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from scipy.linalg import svd
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import threading,time,os,subprocess,shlex
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import threading,time,os,subprocess,shlex,string
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import damask
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from optparse import OptionParser
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scriptID='aa'
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geomName='20grains16x16x16'
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popt1=np.ones(6,'d')
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popt1=[np.ones(1,'d'),np.ones(6,'d')]
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def execute(cmd,dir='./'):
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@ -28,16 +31,16 @@ def asFullTensor(voigt):
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def Hill48(x, F,G,H,L,M,N):
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a = F*(x[1]-x[2])**2 + G*(x[2]-x[0])**2 + H*(x[0]-x[1])** + \
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2*L*x[4]**2 + 2*M*x[5]**2 + 2*N*x[3]**2 -1.
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return a.ravel() * 1000.0
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return a.ravel()
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def vonMises(x, S_y):
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sv=np.zeros(0,'d')
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for i in xrange(np.shape(x)[0]):
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U, l, Vh = svd(np.array(x[i,:]).reshape(3,3))
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for i in xrange(np.shape(x)[1]):
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U, l, Vh = svd(np.array(x[:,i]).reshape(3,3))
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sv = np.append(sv,l)
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sv = sv.reshape(np.shape(x)[0],3)
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ooo= (sv[:,2]-sv[:,1])**2+(sv[:,1]-sv[:,0])**2+(sv[:,0]-sv[:,2])**2-2*S_y**2
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return ooo
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sv = sv.reshape(np.shape(x)[1],3)
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ooo = (sv[:,2]-sv[:,1])**2+(sv[:,1]-sv[:,0])**2+(sv[:,0]-sv[:,2])**2-2*S_y**2
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return ooo.ravel()
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#---------------------------------------------------------------------------------------------------
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class Loadcase():
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@ -47,13 +50,16 @@ class Loadcase():
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'''
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# ------------------------------------------------------------------
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def __init__(self):
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def __init__(self,finalStrain,incs,time):
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print('using the random load case generator')
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self.finalStrain = finalStrain
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self.incs = incs
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self.time = time
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def getNext(self,N=0):
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def getLoadcase(self,N=0):
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defgrad=['*']*9
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stress =[0]*9
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values=(np.random.random_sample(9)-.5)*scale*2
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values=(np.random.random_sample(9)-.5)*self.finalStrain*2
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main=np.array([0,4,8])
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np.random.shuffle(main)
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@ -70,8 +76,8 @@ class Loadcase():
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return 'f '+' '.join(str(c) for c in defgrad)+\
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' p '+' '.join(str(c) for c in stress)+\
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' incs %s'%incs+\
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' time %s'%duration
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' incs %s'%self.incs+\
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' time %s'%self.time
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#---------------------------------------------------------------------------------------------------
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class Criterion(object):
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@ -83,19 +89,21 @@ class Criterion(object):
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self.name = name.lower()
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if self.name not in ['hill48','vonmises']: print('Mist')
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print('using the %s criterion'%self.name)
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self.popt = 0.0
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def fit(self,stress):
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global popt1
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try:
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spopt1, pcov = curve_fit(Hill48, stress, np.zeros(np.shape(stress)[1]),p0=popt1,xtol=1e-30)
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popt = popt1
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print 'Hill 48', popt
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print Hill48(stress,popt[0],popt[1],popt[2],popt[3],popt[4],popt[5])
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popt1[0], pcov = curve_fit(vonMises, stress, np.zeros(np.shape(stress)[1]),p0=popt1[0])
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print 'Mises', popt1[0], pcov
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except Exception as detail:
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print detail
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pass
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try:
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popt1[1], pcov = curve_fit(Hill48, stress, np.zeros(np.shape(stress)[1]),p0=popt1[1])
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print 'Hill48', popt1[1], pcov
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except Exception as detail:
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print detail
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pass
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#popt, pcov = curve_fit(vonMises, stress, np.zeros(np.shape(stress)[0]))
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#print 'von Mises', popt
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#---------------------------------------------------------------------------------------------------
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@ -159,14 +167,12 @@ def doSim(delay,thread):
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if l not in table.labels: print '%s not found'%l
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while table.data_read():
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if float(table.data[table.labels.index('Mises(ln(V))')]) > 0.002:
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yieldStress = np.array(table.data[table.labels.index('1_Cauchy'):table.labels.index('9_Cauchy')+1],'d')
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yieldStress = np.array(table.data[table.labels.index('1_Cauchy'):table.labels.index('9_Cauchy')+1],'d')/10.e8
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s.acquire()
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print('starting fitting for sim %i from %s'%(me,thread))
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global stressAll
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stressAll=np.append(yieldStress,stressAll)
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for i in range(np.shape(stressAll.reshape(len(stressAll)//9,9).transpose())[1]):
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print i, stressAll.reshape(len(stressAll)//9,9).transpose()[:,i]
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myFit.fit(stressAll.reshape(len(stressAll)//9,9).transpose())
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s.release()
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@ -183,19 +189,41 @@ def converged():
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else:
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return True
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# main
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
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Add column(s) with derived values according to user defined arithmetic operation between column(s).
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Columns can be specified either by label or index. Use ';' for ',' in functions.
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Example: distance to IP coordinates -- "math.sqrt( #ip.x#**2 + #ip.y#**2 + round(#ip.z#;3)**2 )"
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""", version=string.replace(scriptID,'\n','\\n')
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)
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parser.add_option('--labelnodalcoords', dest='nodalcoords', type='string', nargs=3, \
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help='labels of nodal coords in ASCII table')
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parser.add_option('-l','--load' , dest='load', type='float', nargs=3, \
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help='load: final strain; increments; time', metavar='float int float')
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parser.add_option('-g','--geometry', dest='formulas', action='extend', type='string', \
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help='(list of) formulas corresponding to labels', metavar='<LIST>')
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parser.add_option('-c','--criterion',dest='formulas', action='extend', type='string', \
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help='(list of) formulas corresponding to labels', metavar='<LIST>')
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parser.set_defaults(load = [0.005,20,20.0])
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parser.set_defaults(formulas= [])
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options = parser.parse_args()[0]
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minN_simulations=20
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maxN_simulations=14
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maxN_simulations=40
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N_simulations=0
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s=threading.Semaphore(1)
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scale = 0.02
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incs = 10
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duration = 10
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stressAll=np.zeros(0,'d').reshape(0,0)
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myLoad = Loadcase()
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myFit = Criterion('Hill48')
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myLoad = Loadcase(options.load[0],options.load[1],options.load[2])
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myFit = Criterion('vonmises')
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N_threads=3
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t=[]
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