Merge branch 'development' of magit1.mpie.de:damask/DAMASK into miscImprovements
This commit is contained in:
Martin Diehl
commit
03bb0b8a98
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@ -1160,9 +1160,9 @@ function plastic_phenopowerlaw_postResults(Tstar_v,ipc,ip,el)
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enddo
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plastic_phenopowerlaw_postResults(c+j) = plastic_phenopowerlaw_gdot0_slip(instance)*0.5_pReal* &
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((abs(tau_slip_pos)/plasticState(ph)%state(j,of))**plastic_phenopowerlaw_n_slip(instance) &
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+(abs(tau_slip_neg)/plasticState(ph)%state(j,of))**plastic_phenopowerlaw_n_slip(instance))&
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*sign(1.0_pReal,tau_slip_pos)
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*sign(1.0_pReal,tau_slip_pos) &
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+(abs(tau_slip_neg)/(plasticState(ph)%state(j,of)))**plastic_phenopowerlaw_n_slip(instance) &
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*sign(1.0_pReal,tau_slip_neg))
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enddo slipSystems1
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enddo slipFamilies1
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c = c + nSlip
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@ -18,7 +18,7 @@ fileExtensions = { \
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# -----------------------------
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class vector: # mimic py_post node object
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x,y,z = [None,None,None]
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def __init__(self,coords):
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self.x = coords[0]
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self.y = coords[1]
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@ -102,7 +102,7 @@ class MPIEspectral_result: # mimic py_post result object
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self._frequencies = self._keyedPackedArray('frequencies:',count=self.N_loadcases,type='i')
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if all ( i is None for i in self._frequencies):
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self._frequencies = self._keyedPackedArray('frequencies',count=self.N_loadcases,type='i')
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self._increments = self._keyedPackedArray('increments:',count=self.N_loadcases,type='i')
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if all (i is None for i in self._increments):
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self._increments = self._keyedPackedArray('increments',count=self.N_loadcases,type='i')
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@ -111,7 +111,7 @@ class MPIEspectral_result: # mimic py_post result object
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if self.startingIncrement is None:
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self.startingIncrement = self._keyedPackedArray('startingIncrement',count=1,type='i')[0]
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self._times = self._keyedPackedArray('times:',count=self.N_loadcases,type='d')
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if all (i is None for i in self._times):
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self._times = self._keyedPackedArray('times',count=self.N_loadcases,type='d')
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@ -119,15 +119,15 @@ class MPIEspectral_result: # mimic py_post result object
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self._logscales = self._keyedPackedArray('logscales:',count=self.N_loadcases,type='i')
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if all (i is None for i in self._logscales):
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self._logscales = self._keyedPackedArray('logscales',count=self.N_loadcases,type='i')
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self.size = self._keyedPackedArray('size:',count=3,type='d')
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if self.size == [None,None,None]: # no 'size' found, try legacy alias 'dimension'
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self.size = self._keyedPackedArray('dimension',count=3,type='d')
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self.grid = self._keyedPackedArray('grid:',count=3,type='i')
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if self.grid == [None,None,None]: # no 'grid' found, try legacy alias 'resolution'
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self.grid = self._keyedPackedArray('resolution',count=3,type='i')
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self.N_nodes = (self.grid[0]+1)*(self.grid[1]+1)*(self.grid[2]+1)
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self.N_elements = self.grid[0] * self.grid[1] * self.grid[2]
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@ -139,7 +139,7 @@ class MPIEspectral_result: # mimic py_post result object
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self.N_increments = 1 # add zero'th entry
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for i in range(self.N_loadcases):
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self.N_increments += self._increments[i]//self._frequencies[i]
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# parameters for file handling depending on output format
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if options.legacy:
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@ -176,17 +176,17 @@ class MPIEspectral_result: # mimic py_post result object
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name = ''
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filepos=0 # start at the beginning
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while name != identifier and filepos < self.dataOffset: # stop searching when found or when reached end of header
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self.file.seek(filepos)
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self.file.seek(filepos)
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# read the starting tag in front of the keyword (Fortran indicates start and end of writing by a 4 byte tag indicating the length of the following data)
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dataLen=struct.unpack('i',self.file.read(4))[0]
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name = self.file.read(len(identifier)) # anticipate identifier
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start=filepos+(4+len(identifier)) # position of the values for the found key
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start=filepos+(4+len(identifier)) # position of the values for the found key
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filepos=filepos+(4+dataLen+4) # forward to next keyword
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if name==identifier: # found the correct name
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key['pos'] = start # save position
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key['name'] = name
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return key
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return key
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def _keyedPackedArray(self,identifier,count = 3,type = 'd',default = None):
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bytecount = {'d': 8,'i': 4}
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@ -251,10 +251,10 @@ class MPIEspectral_result: # mimic py_post result object
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def element_sequence(self,e):
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return e-1
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def element_id(self,e):
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return e+1
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def element(self,e):
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a = self.grid[0]+1
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b = self.grid[1]+1
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@ -291,7 +291,7 @@ class MPIEspectral_result: # mimic py_post result object
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print 'seeking',incStart+where
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print 'e',e,'idx',idx
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sys.exit(1)
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else:
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self.fourByteLimit = 2**31 -1 -8
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# header & footer + extra header and footer for 4 byte int range (Fortran)
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@ -309,7 +309,7 @@ class MPIEspectral_result: # mimic py_post result object
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data += self.file.read(1)
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where += 1
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value = struct.unpack('d',data)[0]
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else:
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else:
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self.file.seek(incStart+where+(where//self.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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@ -328,39 +328,39 @@ class MPIEspectral_result: # mimic py_post result object
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# -----------------------------
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def ipCoords(elemType, nodalCoordinates):
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"""returns IP coordinates for a given element"""
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nodeWeightsPerNode = {
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7: [ [27.0, 9.0, 3.0, 9.0, 9.0, 3.0, 1.0, 3.0],
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[ 9.0, 27.0, 9.0, 3.0, 3.0, 9.0, 3.0, 1.0],
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[ 3.0, 9.0, 27.0, 9.0, 1.0, 3.0, 9.0, 3.0],
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[ 9.0, 3.0, 9.0, 27.0, 3.0, 1.0, 3.0, 9.0],
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[ 9.0, 3.0, 1.0, 3.0, 27.0, 9.0, 3.0, 9.0],
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[ 3.0, 9.0, 3.0, 1.0, 9.0, 27.0, 9.0, 3.0],
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[ 1.0, 3.0, 9.0, 3.0, 3.0, 9.0, 27.0, 9.0],
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[ 3.0, 1.0, 3.0, 9.0, 9.0, 3.0, 9.0, 27.0] ],
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57: [ [27.0, 9.0, 3.0, 9.0, 9.0, 3.0, 1.0, 3.0],
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[ 9.0, 27.0, 9.0, 3.0, 3.0, 9.0, 3.0, 1.0],
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[ 3.0, 9.0, 27.0, 9.0, 1.0, 3.0, 9.0, 3.0],
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[ 9.0, 3.0, 9.0, 27.0, 3.0, 1.0, 3.0, 9.0],
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[ 9.0, 3.0, 1.0, 3.0, 27.0, 9.0, 3.0, 9.0],
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[ 3.0, 9.0, 3.0, 1.0, 9.0, 27.0, 9.0, 3.0],
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[ 1.0, 3.0, 9.0, 3.0, 3.0, 9.0, 27.0, 9.0],
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[ 3.0, 1.0, 3.0, 9.0, 9.0, 3.0, 9.0, 27.0] ],
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117: [ [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] ],
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nodeWeightsPerNode = {
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7: [ [27.0, 9.0, 3.0, 9.0, 9.0, 3.0, 1.0, 3.0],
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[ 9.0, 27.0, 9.0, 3.0, 3.0, 9.0, 3.0, 1.0],
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[ 3.0, 9.0, 27.0, 9.0, 1.0, 3.0, 9.0, 3.0],
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[ 9.0, 3.0, 9.0, 27.0, 3.0, 1.0, 3.0, 9.0],
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[ 9.0, 3.0, 1.0, 3.0, 27.0, 9.0, 3.0, 9.0],
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[ 3.0, 9.0, 3.0, 1.0, 9.0, 27.0, 9.0, 3.0],
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[ 1.0, 3.0, 9.0, 3.0, 3.0, 9.0, 27.0, 9.0],
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[ 3.0, 1.0, 3.0, 9.0, 9.0, 3.0, 9.0, 27.0] ],
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57: [ [27.0, 9.0, 3.0, 9.0, 9.0, 3.0, 1.0, 3.0],
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[ 9.0, 27.0, 9.0, 3.0, 3.0, 9.0, 3.0, 1.0],
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[ 3.0, 9.0, 27.0, 9.0, 1.0, 3.0, 9.0, 3.0],
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[ 9.0, 3.0, 9.0, 27.0, 3.0, 1.0, 3.0, 9.0],
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[ 9.0, 3.0, 1.0, 3.0, 27.0, 9.0, 3.0, 9.0],
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[ 3.0, 9.0, 3.0, 1.0, 9.0, 27.0, 9.0, 3.0],
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[ 1.0, 3.0, 9.0, 3.0, 3.0, 9.0, 27.0, 9.0],
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[ 3.0, 1.0, 3.0, 9.0, 9.0, 3.0, 9.0, 27.0] ],
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117: [ [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] ],
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125: [ [ 3.0, 0.0, 0.0, 4.0, 1.0, 4.0],
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[ 0.0, 3.0, 0.0, 4.0, 4.0, 1.0],
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[ 0.0, 0.0, 3.0, 1.0, 4.0, 4.0],],
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[ 0.0, 0.0, 3.0, 1.0, 4.0, 4.0],],
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127: [ [ 45.0, 17.0, 17.0, 17.0],
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[ 17.0, 45.0, 17.0, 17.0],
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[ 17.0, 17.0, 45.0, 17.0],
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[ 17.0, 17.0, 17.0, 45.0],],
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136: [ [42.0, 15.0, 15.0, 14.0, 5.0, 5.0],
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[15.0, 42.0, 15.0, 5.0, 14.0, 5.0],
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[15.0, 15.0, 42.0, 5.0, 5.0, 14.0],
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[14.0, 5.0, 5.0, 42.0, 15.0, 15.0],
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[ 5.0, 14.0, 5.0, 15.0, 42.0, 15.0],
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[ 5.0, 5.0, 14.0, 15.0, 15.0, 42.0] ],
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[ 17.0, 17.0, 17.0, 45.0],],
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136: [ [42.0, 15.0, 15.0, 14.0, 5.0, 5.0],
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[15.0, 42.0, 15.0, 5.0, 14.0, 5.0],
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[15.0, 15.0, 42.0, 5.0, 5.0, 14.0],
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[14.0, 5.0, 5.0, 42.0, 15.0, 15.0],
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[ 5.0, 14.0, 5.0, 15.0, 42.0, 15.0],
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[ 5.0, 5.0, 14.0, 15.0, 15.0, 42.0] ],
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}
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Nips = len(nodeWeightsPerNode[elemType])
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ipCoordinates = [[0.0,0.0,0.0] for i in range(Nips)]
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for ip in range(Nips):
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@ -369,7 +369,7 @@ def ipCoords(elemType, nodalCoordinates):
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ipCoordinates[ip][i] += nodeWeightsPerNode[elemType][ip][node] * nodalCoordinates[node][i]
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for i in range(3):
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ipCoordinates[ip][i] /= sum(nodeWeightsPerNode[elemType][ip])
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return ipCoordinates
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@ -377,15 +377,15 @@ def ipCoords(elemType, nodalCoordinates):
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# -----------------------------
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def ipIDs(elemType):
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"""returns IP numbers for given element type"""
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ipPerNode = {
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7: [ 1, 2, 4, 3, 5, 6, 8, 7 ],
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57: [ 1, 2, 4, 3, 5, 6, 8, 7 ],
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ipPerNode = {
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7: [ 1, 2, 4, 3, 5, 6, 8, 7 ],
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57: [ 1, 2, 4, 3, 5, 6, 8, 7 ],
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117: [ 1 ],
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125: [ 1, 2, 3 ],
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127: [ 1, 2, 3, 4 ],
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136: [ 1, 2, 3, 4, 5, 6 ],
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125: [ 1, 2, 3 ],
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127: [ 1, 2, 3, 4 ],
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136: [ 1, 2, 3, 4, 5, 6 ],
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}
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return ipPerNode[elemType]
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@ -457,7 +457,7 @@ def OpenPostfile(name,type,nodal = False):
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}[type](name)
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p.extrapolation({True:'linear',False:'translate'}[nodal])
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p.moveto(1)
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return p
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@ -475,9 +475,9 @@ def ParseOutputFormat(filename,what,me):
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break
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except:
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pass
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if content == []: return format # nothing found...
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tag = ''
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tagID = 0
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for line in content:
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@ -527,7 +527,7 @@ def ParsePostfile(p,filename, outputFormat):
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'LabelOfElementalTensor': [None]*p.element_tensors(), \
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}
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# --- find labels
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# --- find labels
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for labelIndex in range(stat['NumberOfNodalScalars']):
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label = p.node_scalar_label(labelIndex)
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@ -543,17 +543,17 @@ def ParsePostfile(p,filename, outputFormat):
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label = p.element_tensor_label(labelIndex)
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stat['IndexOfLabel'][label] = labelIndex
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stat['LabelOfElementalTensor'][labelIndex] = label
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if 'User Defined Variable 1' in stat['IndexOfLabel']: # output format without dedicated names?
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stat['IndexOfLabel']['HomogenizationCount'] = stat['IndexOfLabel']['User Defined Variable 1'] # adjust first named entry
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if 'HomogenizationCount' in stat['IndexOfLabel']: # does the result file contain relevant user defined output at all?
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startIndex = stat['IndexOfLabel']['HomogenizationCount']
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stat['LabelOfElementalScalar'][startIndex] = 'HomogenizationCount'
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# We now have to find a mapping for each output label as defined in the .output* files to the output position in the post file
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# Since we know where the user defined outputs start ("startIndex"), we can simply assign increasing indices to the labels
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# given in the .output* file
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# given in the .output* file
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offset = 1
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for (name,N) in outputFormat['Homogenization']['outputs']:
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@ -595,7 +595,7 @@ def ParsePostfile(p,filename, outputFormat):
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print 'trying to assign %s at position %i+%i'%(label,startIndex,offset)
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sys.exit(1)
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offset += 1
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return stat
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@ -614,7 +614,7 @@ def SummarizePostfile(stat,where=sys.stdout,format='marc'):
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+ '\n '.join(stat['LabelOfElementalScalar']) + '\n\n')
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where.write('elemental tensors:\t%i'%stat['NumberOfElementalTensors'] + '\n\n '\
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+ '\n '.join(stat['LabelOfElementalTensor']) + '\n\n')
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return True
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@ -625,9 +625,9 @@ def SummarizePostfile(stat,where=sys.stdout,format='marc'):
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# --- input parsing
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
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Extract data from a .t16 (MSC.Marc) or .spectralOut results file.
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||||
Extract data from a .t16 (MSC.Marc) or .spectralOut results file.
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List of output variables is given by options '--ns','--es','--et','--ho','--cr','--co'.
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List of output variables is given by options '--ns','--es','--et','--ho','--cr','--co'.
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||||
|
||||
Filters and separations use 'elem','node','ip','grain', and 'x','y','z' as key words.
|
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Example:
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||||
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@ -751,12 +751,12 @@ if options.filetype is None:
|
|||
if ext in fileExtensions[theType]:
|
||||
options.filetype = theType
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||||
break
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||||
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||||
|
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if options.filetype is not None: options.filetype = options.filetype.lower()
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||||
|
||||
if options.filetype == 'marc': offset_pos = 1
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||||
else: offset_pos = 0
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||||
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||||
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||||
|
||||
# --- more sanity checks
|
||||
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||||
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|
@ -766,7 +766,7 @@ if options.filetype not in ['marc','spectral']:
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|||
|
||||
if options.filetype == 'marc':
|
||||
sys.path.append(damask.solver.Marc().libraryPath())
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||||
|
||||
|
||||
try:
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from py_post import post_open
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||||
except:
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||||
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|
@ -810,7 +810,7 @@ else:
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|||
extension = os.path.splitext(files[0])[1]
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||||
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||||
outputFormat = {}
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||||
me = {
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me = {
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'Homogenization': options.homog,
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'Crystallite': options.cryst,
|
||||
'Constitutive': options.phase,
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||||
|
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@ -823,7 +823,7 @@ for what in me:
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|||
if '_id' not in outputFormat[what]['specials']:
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||||
print "\nsection '%s' not found in <%s>"%(me[what], what)
|
||||
print '\n'.join(map(lambda x:' [%s]'%x, outputFormat[what]['specials']['brothers']))
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||||
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||||
|
||||
bg.set_message('opening result file...')
|
||||
p = OpenPostfile(filename+extension,options.filetype,options.nodal)
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||||
bg.set_message('parsing result file...')
|
||||
|
|
@ -834,7 +834,7 @@ if options.filetype == 'marc':
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|||
# --- sanity check for output variables
|
||||
# for mentat variables (nodalScalar,elemScalar,elemTensor) we simply have to check whether the label
|
||||
# is found in the stat[indexOfLabel] dictionary for user defined variables (homogenizationResult,
|
||||
# crystalliteResult,constitutiveResult) we have to check the corresponding outputFormat, since the
|
||||
# crystalliteResult,constitutiveResult) we have to check the corresponding outputFormat, since the
|
||||
# namescheme in stat['IndexOfLabel'] is different
|
||||
|
||||
for opt in ['nodalScalar','elemScalar','elemTensor','homogenizationResult','crystalliteResult','constitutiveResult']:
|
||||
|
|
@ -856,13 +856,13 @@ if options.info:
|
|||
print '\n\n',p
|
||||
|
||||
SummarizePostfile(stat)
|
||||
|
||||
|
||||
print '\nUser Defined Outputs'
|
||||
for what in me:
|
||||
print '\n ',what,':'
|
||||
for output in outputFormat[what]['outputs']:
|
||||
print ' ',output
|
||||
|
||||
|
||||
sys.exit(0)
|
||||
|
||||
|
||||
|
|
@ -900,12 +900,12 @@ if options.nodalScalar:
|
|||
myElemID = 0
|
||||
myIpID = 0
|
||||
myGrainID = 0
|
||||
|
||||
|
||||
# generate an expression that is only true for the locations specified by options.filter
|
||||
filter = substituteLocation(options.filter, [myElemID,myNodeID,myIpID,myGrainID], myNodeCoordinates)
|
||||
if filter != '' and not eval(filter): # for all filter expressions that are not true:...
|
||||
continue # ... ignore this data point and continue with next
|
||||
|
||||
|
||||
# --- group data locations
|
||||
# generate a unique key for a group of separated data based on the separation criterium for the location
|
||||
grp = substituteLocation('#'.join(options.sep), [myElemID,myNodeID,myIpID,myGrainID], myNodeCoordinates)
|
||||
|
|
@ -925,7 +925,7 @@ if options.nodalScalar:
|
|||
myNodeCoordinates) # incrementally update average location
|
||||
groups[index[grp]].append([myElemID,myNodeID,myIpID,myGrainID,0]) # append a new list defining each group member
|
||||
memberCount += 1
|
||||
|
||||
|
||||
else:
|
||||
for e in xrange(stat['NumberOfElements']):
|
||||
if e%1000 == 0:
|
||||
|
|
@ -943,22 +943,22 @@ else:
|
|||
and int(p.element_scalar(e, stat['IndexOfLabel']['GrainCount'])[0].value))\
|
||||
or 1):
|
||||
myGrainID = g + 1
|
||||
|
||||
|
||||
# --- filter valid locations
|
||||
# generates an expression that is only true for the locations specified by options.filter
|
||||
filter = substituteLocation(options.filter, [myElemID,myNodeID,myIpID,myGrainID], myIpCoordinates[n])
|
||||
filter = substituteLocation(options.filter, [myElemID,myNodeID,myIpID,myGrainID], myIpCoordinates[n])
|
||||
if filter != '' and not eval(filter): # for all filter expressions that are not true:...
|
||||
continue # ... ignore this data point and continue with next
|
||||
|
||||
|
||||
# --- group data locations
|
||||
# generates a unique key for a group of separated data based on the separation criterium for the location
|
||||
grp = substituteLocation('#'.join(options.sep), [myElemID,myNodeID,myIpID,myGrainID], myIpCoordinates[n])
|
||||
|
||||
grp = substituteLocation('#'.join(options.sep), [myElemID,myNodeID,myIpID,myGrainID], myIpCoordinates[n])
|
||||
|
||||
if grp not in index: # create a new group if not yet present
|
||||
index[grp] = groupCount
|
||||
groups.append([[0,0,0,0,0.0,0.0,0.0]]) # initialize with avg location
|
||||
groupCount += 1
|
||||
|
||||
|
||||
groups[index[grp]][0][:4] = mapIncremental('','unique',
|
||||
len(groups[index[grp]])-1,
|
||||
groups[index[grp]][0][:4],
|
||||
|
|
@ -1055,12 +1055,12 @@ for incCount,position in enumerate(locations): # walk through locations
|
|||
+'"%(dirname + os.sep + options.prefix + os.path.split(filename)[1],increments[incCount],options.suffix)')
|
||||
else:
|
||||
outFilename = '%s.txt'%(dirname + os.sep + options.prefix + os.path.split(filename)[1] + options.suffix)
|
||||
|
||||
|
||||
if not fileOpen:
|
||||
file = open(outFilename,'w')
|
||||
fileOpen = True
|
||||
file.write('2\theader\n')
|
||||
file.write(scriptID + '\t' + ' '.join(sys.argv[1:]))
|
||||
file.write(scriptID + '\t' + ' '.join(sys.argv[1:]) + '\n')
|
||||
headerWritten = False
|
||||
|
||||
file.flush()
|
||||
|
|
@ -1097,7 +1097,7 @@ for incCount,position in enumerate(locations): # walk through locations
|
|||
|
||||
if options.elemScalar:
|
||||
for label in options.elemScalar:
|
||||
if assembleHeader:
|
||||
if assembleHeader:
|
||||
header += [''.join( label.split() )]
|
||||
newby.append({'label':label,
|
||||
'len':1,
|
||||
|
|
@ -1105,17 +1105,17 @@ for incCount,position in enumerate(locations): # walk through locations
|
|||
|
||||
if options.elemTensor:
|
||||
for label in options.elemTensor:
|
||||
if assembleHeader:
|
||||
if assembleHeader:
|
||||
header += heading('.',[[''.join( label.split() ),component]
|
||||
for component in ['intensity','t11','t22','t33','t12','t23','t13']])
|
||||
myTensor = p.element_tensor(p.element_sequence(e),stat['IndexOfLabel'][label])[n_local]
|
||||
newby.append({'label':label,
|
||||
'len':7,
|
||||
'content':[ myTensor.intensity,
|
||||
'content':[ myTensor.intensity,
|
||||
myTensor.t11, myTensor.t22, myTensor.t33,
|
||||
myTensor.t12, myTensor.t23, myTensor.t13,
|
||||
]})
|
||||
|
||||
|
||||
if options.homogenizationResult or \
|
||||
options.crystalliteResult or \
|
||||
options.constitutiveResult:
|
||||
|
|
@ -1135,7 +1135,7 @@ for incCount,position in enumerate(locations): # walk through locations
|
|||
try:
|
||||
newby.append({'label':label,
|
||||
'len':length,
|
||||
'content':[ p.element_scalar(p.element_sequence(e),stat['IndexOfLabel'][head])[n_local].value
|
||||
'content':[ p.element_scalar(p.element_sequence(e),stat['IndexOfLabel'][head])[n_local].value
|
||||
for head in thisHead ]})
|
||||
except KeyError:
|
||||
print '\nDAMASK outputs seem missing from "post" section of the *.dat file!'
|
||||
|
|
@ -1165,7 +1165,7 @@ for incCount,position in enumerate(locations): # walk through locations
|
|||
group[0] + \
|
||||
mappedResult)
|
||||
) + '\n')
|
||||
|
||||
|
||||
if fileOpen:
|
||||
file.close()
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue