new script for reconstruction of elements from F/IP(spectral_buildElements.py), corrected spectral_randomSeeding.py, made post/postResults.py aware of additional header/footer for file positions larger than 2**31-1
This commit is contained in:
Martin Diehl
parent
f74b16051b
commit
99f2b8603a
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@ -231,11 +231,29 @@ class MPIEspectral_result: # mimic py_post result object
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return self.N_element_scalars
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def element_scalar(self,e,idx):
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self.file.seek(self.dataOffset+(self.position*(4+self.N_elements*self.N_element_scalars*8+4) + 4+(e*self.N_element_scalars + idx)*8))
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fourByteLimit = 2**31 -1 -8
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incStart = self.dataOffset\
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+ self.position*(( 1\
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+ self.N_elements*self.N_element_scalars\
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+(self.N_elements*self.N_element_scalars*8)//fourByteLimit\
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)*8)
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# header and footer
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# values
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# extra header and footer for 4 byte int range (Fortran)
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where = (e*self.N_element_scalars + idx)*8
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try:
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value = struct.unpack('d',self.file.read(8))[0]
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if where%fourByteLimit + 8 >= fourByteLimit: # danger of reading into fortran record footer at 4 byte limit
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data=''
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for i in xrange(8):
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where+= 1
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self.file.seek(incStart+where+(where//fourByteLimit)*8+4)
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data+=self.file.read(1)
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value = struct.unpack('d',data)[0]
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else:
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self.file.seek(incStart+where+(where//fourByteLimit)*8+4)
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value = struct.unpack('d',self.file.read(8))[0]
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except:
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print 'seeking',self.dataOffset+(self.position*(4+self.N_elements*self.N_element_scalars*8+4) + 4+(e*self.N_element_scalars + idx)*8)
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print 'seeking',incStart+where+(where//fourByteLimit)*8+4
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print 'e',e,'idx',idx
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sys.exit(1)
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return [elemental_scalar(node,value) for node in self.element(e).items]
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@ -0,0 +1,167 @@
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#!/usr/bin/env python
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import os,re,sys,math,string,numpy,damask
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from optparse import OptionParser, Option
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# -----------------------------
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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def location(idx,res):
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return ( idx % res[0], \
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( idx // res[0]) % res[1], \
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( idx // res[0] // res[1]) % res[2] )
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def index(location,res):
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return ( location[0] % res[0] + \
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( location[1] % res[1]) * res[0] + \
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( location[2] % res[2]) * res[1] * res[0] )
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
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Calculates current coordinates and nodal displacement from IP/FP based deformation gradient.
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""" + string.replace('$Id$','\n','\\n')
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)
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parser.add_option('-c','--coordinates', dest='coords', type='string',\
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help='column heading for coordinates [%default]')
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parser.add_option('-d','--defgrad', dest='defgrad', type='string', \
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help='heading of columns containing tensor field values')
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parser.set_defaults(coords = 'ip')
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parser.set_defaults(defgrad = 'f' )
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(options,filenames) = parser.parse_args()
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# ------------------------------------------ setup file handles ---------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name, 'input':open(name), \
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'output':open(os.path.splitext(name)[0]+'_nodal'+os.path.splitext(name)[1],'w')})
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# ------------------------------------------ loop over input files ---------------------------------------
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for file in files:
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if file['name'] != 'STDIN': print file['name'],
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table = damask.ASCIItable(file['input']) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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table.info_append(string.replace('$Id$','\n','\\n') + \
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'\t' + ' '.join(sys.argv[1:]))
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# --------------- figure out dimension and resolution
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try:
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locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data
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except ValueError:
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print 'no coordinate data found...'
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continue
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grid = [{},{},{}]
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while table.data_read(): # read next data line of ASCII table
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if str(table.data[locationCol+1]) in grid[1] and len(grid[1])>1: # geomdim[1] and res[1] already figured out, skip layers
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table.data_skipLines(len(grid[1])*len(grid[0])-1)
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else:
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if str(table.data[locationCol]) in grid[0]: # geomdim[0] and res[0] already figured out, skip lines
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table.data_skipLines(len(grid[0])-1)
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for j in xrange(3):
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grid[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z
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res = numpy.array([len(grid[0]),\
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len(grid[1]),\
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len(grid[2]),],'i') # resolution is number of distinct coordinates found
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geomdim = res/numpy.maximum(numpy.ones(3,'d'),res-1.0)* \
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numpy.array([max(map(float,grid[0].keys()))-min(map(float,grid[0].keys())),\
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max(map(float,grid[1].keys()))-min(map(float,grid[1].keys())),\
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max(map(float,grid[2].keys()))-min(map(float,grid[2].keys())),\
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],'d') # dimension from bounding box, corrected for cell-centeredness
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if res[2] == 1:
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geomdim[2] = min(geomdim[:2]/res[:2])
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N = res.prod()
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print '\t%s @ %s'%(geomdim,res)
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# --------------- figure out columns to process
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key = '1_%s' %options.defgrad
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if key not in table.labels:
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sys.stderr.write('column %s not found...\n'%key)
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else:
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column = table.labels.index(key)
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# ------------------------------------------ read value field ---------------------------------------
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defgrad = numpy.array([0.0 for i in xrange(N*9)]).reshape(list(res)+[3,3])
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table.data_rewind()
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table.data_read()
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inc = table.data[table.labels.index('inc')]
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table.data_rewind()
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idx = 0
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while table.data_read(): # read next data line of ASCII table
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(x,y,z) = location(idx,res) # figure out (x,y,z) position from line count
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idx += 1
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defgrad[x,y,z] = numpy.array(map(float,table.data[column:column+9]),'d').reshape(3,3)
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file['input'].close() # close input ASCII table
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# ------------------------------------------ process value field ----------------------------
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defgrad_av = damask.core.math.tensor_avg(res,defgrad)
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centroids = damask.core.math.deformed_fft(res,geomdim,defgrad_av,1.0,defgrad)
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nodes = damask.core.math.mesh_regular_grid(res,geomdim,defgrad_av,centroids)
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# ------------------------------------------ process data ---------------------------------------
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table = damask.ASCIItable(fileOut=file['output'],buffered= False) # make unbuffered ASCII_table
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table.info_append(string.replace('$Id$','\n','\\n') + \
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'\t' + ' '.join(sys.argv[1:]))
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table.labels_append('inc elem node ip grain ') # extend ASCII header with new labels
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table.labels_append(['node.%s'%(coord) for coord in 'x','y','z']) # extend ASCII header with new labels
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table.labels_append(['Displacement %s'%(coord) for coord in 'X','Y','Z']) # extend ASCII header with new labels
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table.head_write()
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ielem = 0
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for z in xrange(res[2]+1):
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for y in xrange(res[1]+1):
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for x in xrange(res[0]+1):
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ielem +=1
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entry = [inc,0,ielem,0,0,'\t'.join([str(a) for a in(nodes[x][y][z])]),'\t'.join([str(a) for a in (nodes[x][y][z] - (x,y,z)*(geomdim/res))])]
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table.data_append(entry)
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table.data_write() # output processed line
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table.data_clear()
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# ------------------------------------------ assemble header ---------------------------------------
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table.output_flush() # just in case of buffered ASCII table
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if file['name'] != 'STDIN': file['output'].close # close output ASCII table
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@ -71,12 +71,9 @@ grainEuler[1,:] = numpy.arccos(2*grainEuler[1,:]-1)*180/math.pi
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grainEuler[2,:] = 360*grainEuler[2,:]
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seedpoint = numpy.random.permutation(options.res[0]*options.res[1]*options.res[2])[:options.N_Seeds]
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seeds[0,:]=numpy.mod(seedpoint,options.res[0])/options.res[0]+1
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seeds[1,:]=numpy.mod((seedpoint-seeds[0,:])/options.res[0],options.res[1])+1
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seeds[2,:]=(seedpoint-seeds[0,:]-options.res[1]*seeds[1,:])/(options.res[0]*options.res[1])+1
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seeds[0,:]=(seeds[0,:]+numpy.random.rand(1,options.N_Seeds)-0.5)/options.res[0]
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seeds[1,:]=(seeds[1,:]+numpy.random.rand(1,options.N_Seeds)-0.5)/options.res[1]
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seeds[2,:]=(seeds[2,:]+numpy.random.rand(1,options.N_Seeds)-0.5)/options.res[2]
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seeds[0,:]=(numpy.mod(seedpoint ,options.res[0])+numpy.random.random())/options.res[0]
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seeds[1,:]=(numpy.mod(seedpoint// options.res[0] ,options.res[1])+numpy.random.random())/options.res[1]
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seeds[2,:]=(numpy.mod(seedpoint//(options.res[1]*options.res[0]),options.res[2])+numpy.random.random())/options.res[2]
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f = open(options.filename+'.seeds', 'w')
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@ -112,6 +112,7 @@ bin_link = { \
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'postResults.py',
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'spectral_iterationCount.py',
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'spectral_parseLog.py',
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'spectral_buildElements.py',
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'tagLabel.py',
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],
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}
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