added more options to command line
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@ -28,6 +28,31 @@ def asFullTensor(voigt):
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[voigt[3],voigt[1],voigt[4]],\
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[voigt[5],voigt[4],voigt[2]]])
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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()
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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)[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)[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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fittingCriteria = {
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'vonMises':{'fit':np.ones(1,'d'),'err':np.inf},
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'hill48' :{'fit':np.ones(6,'d'),'err':np.inf},
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'worst' :{'err':np.inf},
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'best' :{'err':np.inf}
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}
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thresholdParameter = ['totalshear','equivalentStrain']
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#---------------------------------------------------------------------------------------------------
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class Loadcase():
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#---------------------------------------------------------------------------------------------------
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@ -73,41 +98,27 @@ class Criterion(object):
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'''
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def __init__(self,name='worst'):
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self.name = name
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self.results = {
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'vonmises':{'fit':np.ones(1,'d'),'err':np.inf},
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'hill48' :{'fit':np.ones(6,'d'),'err':np.inf},
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'worst' :{'err':np.inf},
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'best' :{'err':np.inf}
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}
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if self.name.lower() not in self.results.keys():
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self.results = fittingCriteria
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if self.name.lower() not in map(str.lower, self.results.keys()):
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raise Exception('no suitable fitting criterion selected')
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else:
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print('fitting to the %s criterion'%name)
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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()
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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)[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)[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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def fit(self,stress):
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try:
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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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#popt1[0], pcov = curve_fit(self.vonMises, stress, np.zeros(np.shape(stress)[1]),p0=popt1[0])
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popt, pcov = curve_fit(vonMises, stress, np.zeros(np.shape(stress)[1]))
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perr = np.sqrt(np.diag(pcov))
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print 'Mises', popt, perr
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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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popt, pcov = curve_fit(Hill48, stress, np.zeros(np.shape(stress)[1]))
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#popt1[1], pcov = curve_fit(self.Hill48, stress, np.zeros(np.shape(stress)[1]),p0=popt1[1])
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perr = np.sqrt(np.diag(pcov))
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print 'Hill48', popt, perr
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except Exception as detail:
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print detail
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pass
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@ -134,7 +145,6 @@ class myThread (threading.Thread):
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def doSim(delay,thread):
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global options.geometry
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s.acquire()
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me=getLoadcase()
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if not os.path.isfile('%s.load'%me):
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@ -156,6 +166,9 @@ def doSim(delay,thread):
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if not os.path.isfile('./postProc/%s_%i.txt'%(options.geometry,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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try:
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execute('postResults --cr f,p --co totalshear %s_%i.spectralOut'%(options.geometry,me))
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except:
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execute('postResults --cr f,p %s_%i.spectralOut'%(options.geometry,me))
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execute('addCauchy ./postProc/%s_%i.txt'%(options.geometry,me))
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execute('addStrainTensors -l -v ./postProc/%s_%i.txt'%(options.geometry,me))
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@ -169,16 +182,25 @@ def doSim(delay,thread):
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refFile = open('./postProc/%s_%i.txt'%(options.geometry,me))
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table = damask.ASCIItable(refFile)
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table.head_read()
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if options.fitting =='equivalentStrain' :
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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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if float(table.data[table.labels.index('Mises(ln(V))')]) > options.yieldValue:
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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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elif options.fitting =='totalshear' :
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for l in ['totalshear','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('totalshear')]) > options.yieldValue:
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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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print np.shape(stressAll)
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print('starting fitting for sim %i from %s'%(me,thread))
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myFit.fit(stressAll.reshape(len(stressAll)//9,9).transpose())
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s.release()
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@ -189,8 +211,7 @@ def getLoadcase():
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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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if N_simulations < options.max:
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return False
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else:
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return True
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@ -206,40 +227,60 @@ Performs calculations with various loads on given geometry file and fits yield s
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)
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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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help='load: final strain; increments; time %default', metavar='float int float')
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parser.add_option('-g','--geometry', dest='geometry', type='string',
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help='name of the geometry file', metavar='string')
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parser.add_option('-c','--criterion',dest='criterion', action='extend', type='string', # this should be a choice
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help='(list of) formulas corresponding to labels', metavar='<LIST>')
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parser.add_option('-c','--criterion',dest='fittin', action='extend', type='string', # this should be a choice
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help='(list of) formulas corresponding to labels', metavar='<LIST>')
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help='name of the geometry file [%default]', metavar='string')
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parser.add_option('--criterion', dest='criterion', action='store', choices=fittingCriteria.keys(),
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help='criterion for stopping simulations [%default]', metavar='string')
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parser.add_option('--fitting', dest='fitting', action='store', choices=thresholdParameter,
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help='yield criterion [%default]', metavar='string')
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parser.add_option('--yieldvalue', dest='yieldValue', action='store', type='float',
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help='yield criterion [%default]', metavar='float')
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parser.add_option('--min', dest='min', type='int',
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help='minimum number of simulations', metavar='int')
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help='minimum number of simulations [%default]', metavar='int')
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parser.add_option('--max', dest='max', type='int',
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help='maximum number of iterations', metavar='int')
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help='maximum number of iterations [%default]', metavar='int')
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parser.add_option('--threads', dest='threads', type='int',
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help='number of parallel executions', metavar='int')
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help='number of parallel executions [%default]', metavar='int')
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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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parser.set_defaults(yieldValue = 0.002)
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parser.set_defaults(load = [0.008,80,80.0])
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parser.set_defaults(geometry ='20grains16x16x16')
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parser.set_defaults(criterion = 'worst')
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parser.set_defaults(fitting = 'totalshear')
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parser.set_defaults(geometry = '20grains16x16x16')
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options = parser.parse_args()[0]
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if not os.path.isfile(options.geometry+'.geom'):
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parser.error('geometry file %s.geom not found'%options.geometry)
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if not os.path.isfile('material.config'):
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parser.error('material.config file not found')
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if options.threads<1:
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parser.error('invalid number of threads %i'%options.threads)
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if options.min<0:
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parser.error('invalid minimum number of simulations %i'%options.min)
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if options.max<options.min:
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parser.error('invalid maximumb number of simulations (below minimum)')
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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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N_simulations=0
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s=threading.Semaphore(1)
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stressAll=np.zeros(0,'d').reshape(0,0)
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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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myFit = Criterion(options.criterion)
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threads=[]
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for i in range(options.threads):
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t.append(myThread(i))
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t[i].start()
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threads.append(myThread(i))
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threads[i].start()
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for i in range(options.threads):
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t[i].join()
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threads[i].join()
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print 'finished fitting to yield criteria'
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