DAMASK_EICMD/processing/misc/yieldSurface.py

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#!/usr/bin/python
# -*- coding: UTF-8 no BOM -*-
import threading,time,os,subprocess,shlex,string
import numpy as np
from scipy.optimize import curve_fit
from scipy.linalg import svd
from optparse import OptionParser
import damask
scriptID = '$Id$'
scriptName = scriptID.split()[1]
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def execute(cmd,dir='./'):
initialPath=os.getcwd()
os.chdir(dir)
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out = ''
line = True
process = subprocess.Popen(shlex.split(cmd),stdout=subprocess.PIPE,stderr = subprocess.STDOUT)
while line:
line = process.stdout.readline()
out += line
os.chdir(initialPath)
def asFullTensor(voigt):
return np.array([[voigt[0],voigt[3],voigt[5]],\
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[voigt[3],voigt[1],voigt[4]],\
[voigt[5],voigt[4],voigt[2]]])
#---------------------------------------------------------------------------------------------------
class Loadcase():
#---------------------------------------------------------------------------------------------------
'''
Class for generating load cases for the spectral solver
'''
# ------------------------------------------------------------------
def __init__(self,finalStrain,incs,time):
print('using the random load case generator')
self.finalStrain = finalStrain
self.incs = incs
self.time = time
def getLoadcase(self,N=0):
defgrad=['*']*9
stress =[0]*9
values=(np.random.random_sample(9)-.5)*self.finalStrain*2
main=np.array([0,4,8])
np.random.shuffle(main)
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for i in main[:2]: # fill 2 out of 3 main entries
defgrad[i]=1.+values[i]
stress[i]='*'
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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)
off=np.array(off)
np.random.shuffle(off)
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for i in off[0:2]:
if i != 0:
defgrad[i]=values[i]
stress[i]='*'
return 'f '+' '.join(str(c) for c in defgrad)+\
' p '+' '.join(str(c) for c in stress)+\
' incs %s'%self.incs+\
' time %s'%self.time
#---------------------------------------------------------------------------------------------------
class Criterion(object):
#---------------------------------------------------------------------------------------------------
'''
Fitting to certain criterion
'''
def __init__(self,name='worst'):
self.name = name
self.results = {
'vonmises':{'fit':np.ones(1,'d'),'err':np.inf},
'hill48' :{'fit':np.ones(6,'d'),'err':np.inf},
'worst' :{'err':np.inf},
'best' :{'err':np.inf}
}
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if self.name.lower() not in self.results.keys():
raise Exception('no suitable fitting criterion selected')
else:
print('fitting to the %s criterion'%name)
def Hill48(x, F,G,H,L,M,N):
a = F*(x[1]-x[2])**2 + G*(x[2]-x[0])**2 + H*(x[0]-x[1])** + \
2*L*x[4]**2 + 2*M*x[5]**2 + 2*N*x[3]**2 -1.
return a.ravel()
def vonMises(x, S_y):
sv=np.zeros(0,'d')
for i in xrange(np.shape(x)[1]):
U, l, Vh = svd(np.array(x[:,i]).reshape(3,3))
sv = np.append(sv,l)
sv = sv.reshape(np.shape(x)[1],3)
ooo = (sv[:,2]-sv[:,1])**2+(sv[:,1]-sv[:,0])**2+(sv[:,0]-sv[:,2])**2-2*S_y**2
return ooo.ravel()
def fit(self,stress):
try:
popt1[0], pcov = curve_fit(vonMises, stress, np.zeros(np.shape(stress)[1]),p0=popt1[0])
print 'Mises', popt1[0], pcov
except Exception as detail:
print detail
pass
try:
popt1[1], pcov = curve_fit(Hill48, stress, np.zeros(np.shape(stress)[1]),p0=popt1[1])
print 'Hill48', popt1[1], pcov
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except Exception as detail:
print detail
pass
#---------------------------------------------------------------------------------------------------
class myThread (threading.Thread):
#---------------------------------------------------------------------------------------------------
'''
Runner class
'''
def __init__(self, threadID):
threading.Thread.__init__(self)
self.threadID = threadID
def run(self):
s.acquire()
conv=converged()
s.release()
while not conv:
doSim(4.,self.name)
s.acquire()
conv=converged()
s.release()
def doSim(delay,thread):
global options.geometry
s.acquire()
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me=getLoadcase()
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if not os.path.isfile('%s.load'%me):
print('generating loadcase for sim %s from %s'%(me,thread))
f=open('%s.load'%me,'w')
f.write(myLoad.getLoadcase(me))
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f.close()
s.release()
else: s.release()
s.acquire()
if not os.path.isfile('%s_%i.spectralOut'%(options.geometry,me)):
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print('starting simulation %s from %s'%(me,thread))
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s.release()
execute('DAMASK_spectral -g %s -l %i'%(options.geometry,me))
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else: s.release()
s.acquire()
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))
s.release()
execute('postResults --cr f,p %s_%i.spectralOut'%(options.geometry,me))
execute('addCauchy ./postProc/%s_%i.txt'%(options.geometry,me))
execute('addStrainTensors -l -v ./postProc/%s_%i.txt'%(options.geometry,me))
execute('addMises -s Cauchy -e ln(V) ./postProc/%s_%i.txt'%(options.geometry,me))
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else: s.release()
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s.acquire()
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print('reading values for sim %i from %s'%(me,thread))
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s.release()
refFile = open('./postProc/%s_%i.txt'%(options.geometry,me))
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table = damask.ASCIItable(refFile)
table.head_read()
for l in ['Mises(ln(V))','1_Cauchy']:
if l not in table.labels: print '%s not found'%l
while table.data_read():
if float(table.data[table.labels.index('Mises(ln(V))')]) > 0.002:
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))
global stressAll
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stressAll=np.append(yieldStress,stressAll)
myFit.fit(stressAll.reshape(len(stressAll)//9,9).transpose())
s.release()
def getLoadcase():
global N_simulations
N_simulations+=1
return N_simulations
def converged():
global N_simulations
global maxN_simulations
if N_simulations < maxN_simulations:
return False
else:
return True
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Performs calculations with various loads on given geometry file and fits yield surface.
""", version=string.replace(scriptID,'\n','\\n')
)
parser.add_option('-l','--load' , dest='load', type='float', nargs=3,
help='load: final strain; increments; time', metavar='float int float')
parser.add_option('-g','--geometry', dest='geometry', type='string',
help='name of the geometry file', metavar='string')
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>')
parser.add_option('-c','--criterion',dest='fittin', action='extend', type='string', # this should be a choice
help='(list of) formulas corresponding to labels', metavar='<LIST>')
parser.add_option('--min', dest='min', type='int',
help='minimum number of simulations', metavar='int')
parser.add_option('--max', dest='max', type='int',
help='maximum number of iterations', metavar='int')
parser.add_option('--threads', dest='threads', type='int',
help='number of parallel executions', metavar='int')
parser.set_defaults(min = 12)
parser.set_defaults(max = 30)
parser.set_defaults(threads = 4)
parser.set_defaults(load = [0.008,80,80.0])
parser.set_defaults(geometry ='20grains16x16x16')
options = parser.parse_args()[0]
N_simulations=0
s=threading.Semaphore(1)
stressAll=np.zeros(0,'d').reshape(0,0)
myLoad = Loadcase(options.load[0],options.load[1],options.load[2])
myFit = Criterion('vonmises')
for i in range(options.threads):
t.append(myThread(i))
t[i].start()
for i in range(options.threads):
t[i].join()
print 'finished fitting to yield criteria'