2014-07-02 16:12:51 +05:30
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#!/usr/bin/python
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# -*- coding: UTF-8 no BOM -*-
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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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2014-07-07 19:47:44 +05:30
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import threading,time,os,subprocess,shlex
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import damask
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2014-07-08 21:39:02 +05:30
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geomName='20grains16x16x16'
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popt1=np.ones(6,'d')
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2014-07-07 19:47:44 +05:30
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def execute(cmd,dir='./'):
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initialPath=os.getcwd()
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out = ''
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line = True
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process = subprocess.Popen(shlex.split(cmd),stdout=subprocess.PIPE,stderr = subprocess.STDOUT)
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while line:
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line = process.stdout.readline()
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out += line
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os.chdir(initialPath)
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2014-07-02 16:12:51 +05:30
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def asFullTensor(voigt):
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return np.array([[voigt[0],voigt[3],voigt[5]],\
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2014-07-07 19:47:44 +05:30
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[voigt[3],voigt[1],voigt[4]],\
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[voigt[5],voigt[4],voigt[2]]])
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2014-07-02 16:12:51 +05:30
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def Hill48(x, F,G,H,L,M,N):
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2014-07-04 19:10:15 +05:30
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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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2014-07-02 16:12:51 +05:30
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2*L*x[4]**2 + 2*M*x[5]**2 + 2*N*x[3]**2 -1.
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2014-07-04 19:10:15 +05:30
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return a.ravel()
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2014-07-02 16:12:51 +05:30
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def vonMises(x, S_y):
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2014-07-07 19:47:44 +05:30
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sv=np.zeros(0,'d')
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2014-07-08 21:39:02 +05:30
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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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2014-07-07 19:47:44 +05:30
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sv = np.append(sv,l)
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2014-07-08 21:39:02 +05:30
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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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2014-07-07 19:47:44 +05:30
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return ooo
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2014-07-02 16:12:51 +05:30
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#---------------------------------------------------------------------------------------------------
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class Loadcase():
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#---------------------------------------------------------------------------------------------------
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'''
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Class for generating load cases for the spectral solver
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'''
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# ------------------------------------------------------------------
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def __init__(self):
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print('using the random load case generator')
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def getNext(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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main=np.array([0,4,8])
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np.random.shuffle(main)
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2014-07-07 19:47:44 +05:30
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for i in main[:2]: # fill 2 out of 3 main entries
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2014-07-02 16:12:51 +05:30
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defgrad[i]=1.+values[i]
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stress[i]='*'
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2014-07-07 19:47:44 +05:30
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for off in [[1,3,0],[2,6,0],[5,7,0]]: # fill 3 off-diagonal pairs of defgrad (1 or 2 entries)
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2014-07-02 16:12:51 +05:30
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off=np.array(off)
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np.random.shuffle(off)
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2014-07-07 19:47:44 +05:30
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for i in off[0:2]:
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if i != 0:
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defgrad[i]=values[i]
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stress[i]='*'
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2014-07-02 16:12:51 +05:30
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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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#---------------------------------------------------------------------------------------------------
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class Criterion(object):
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#---------------------------------------------------------------------------------------------------
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'''
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Fitting to certain criterion
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'''
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def __init__(self,name):
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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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2014-07-07 19:47:44 +05:30
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try:
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2014-07-08 21:39:02 +05:30
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spopt1, pcov = curve_fit(Hill48, stress, np.zeros(np.shape(stress)[1]),p0=popt1)
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popt = popt1
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2014-07-07 19:47:44 +05:30
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print 'Hill 48', popt
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2014-07-08 21:39:02 +05:30
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print Hill48(stress,popt[0],popt[1],popt[2],popt[3],popt[4],popt[5])
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2014-07-07 19:47:44 +05:30
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except Exception as detail:
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print detail
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pass
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2014-07-08 21:39:02 +05:30
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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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2014-07-02 16:12:51 +05:30
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#---------------------------------------------------------------------------------------------------
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#---------------------------------------------------------------------------------------------------
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'''
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Runner class
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'''
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class myThread (threading.Thread):
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def __init__(self, threadID):
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threading.Thread.__init__(self)
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self.threadID = threadID
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def run(self):
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s.acquire()
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conv=converged()
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s.release()
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while not conv:
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doSim(4.,self.name)
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s.acquire()
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conv=converged()
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s.release()
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def doSim(delay,thread):
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2014-07-07 19:47:44 +05:30
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2014-07-02 16:12:51 +05:30
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s.acquire()
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2014-07-04 19:10:15 +05:30
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me=getLoadcase()
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2014-07-08 21:39:02 +05:30
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if not os.path.isfile('%s.load'%me):
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print('generating loadcase for sim %s from %s'%(me,thread))
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f=open('%s.load'%me,'w')
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f.write(myLoad.getNext(me))
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f.close()
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s.release()
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else: s.release()
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s.acquire()
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if not os.path.isfile('%s_%s.spectralOut'%(geomName,me)):
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print('starting simulation %i from %s'%(me,thread))
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s.release()
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execute('DAMASK_spectral -l %i -g %i'%(me,geomName))
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else: s.release()
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2014-07-07 19:47:44 +05:30
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2014-07-08 21:39:02 +05:30
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s.acquire()
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if not os.path.isfile('./postProc/%s_%s.txt'%(geomName,me)):
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print('starting post processing for sim %i from %s'%(me,thread))
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s.release()
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execute('postResults --cr f,p %i_%i.spectralOut'%(geomName,me))
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execute('addCauchy ./postProc/%i_%i.txt'%(geomName,me))
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execute('addStrainTensors -l -v ./postProc/%i_%i.txt'%(geomName,me))
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execute('addMises -s Cauchy -e ln(V) ./postProc/%i_%i.txt'%(geomName,me))
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else: s.release()
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2014-07-07 19:47:44 +05:30
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s.acquire()
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2014-07-08 21:39:02 +05:30
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print('reading values for sim %i from %s'%(me,thread))
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2014-07-07 19:47:44 +05:30
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s.release()
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refFile = open('./postProc/20grains16x16x16_%i.txt'%me)
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2014-07-08 21:39:02 +05:30
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refFile = open('./postProc/20grains16x16x16_1.txt')
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2014-07-07 19:47:44 +05:30
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table = damask.ASCIItable(refFile)
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table.head_read()
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for l in ['Mises(ln(V))','1_Cauchy']:
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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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2014-07-08 21:39:02 +05:30
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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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2014-07-07 19:47:44 +05:30
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s.acquire()
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2014-07-08 21:39:02 +05:30
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print('starting fitting for sim %i from %s'%(me,thread))
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2014-07-02 16:12:51 +05:30
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global stressAll
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2014-07-08 21:39:02 +05:30
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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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2014-07-02 16:12:51 +05:30
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s.release()
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def getLoadcase():
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global N_simulations
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N_simulations+=1
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return N_simulations
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def converged():
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global N_simulations
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global maxN_simulations
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if N_simulations < maxN_simulations:
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return False
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else:
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return True
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# main
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minN_simulations=20
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maxN_simulations=14
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2014-07-02 16:12:51 +05:30
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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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2014-07-08 21:39:02 +05:30
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stressAll=np.zeros(0,'d').reshape(0,0)
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2014-07-02 16:12:51 +05:30
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myLoad = Loadcase()
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myFit = Criterion('Hill48')
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N_threads=3
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t=[]
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for i in range(N_threads):
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t.append(myThread(i))
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t[i].start()
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for i in range(N_threads):
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t[i].join()
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print "Exiting Main Thread"
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