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DAMASK_EICMD
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This commit is contained in:
Martin Diehl 2018-12-09 12:37:27 +01:00
parent 65165ffc5e
commit d43dfa569b
1 changed files with 9 additions and 9 deletions
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18
processing/post/postResults.py
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@ -852,7 +852,7 @@ print('\n')
if options.nodalScalar:
Npoints = stat['NumberOfNodes']
for n in range(Npoints):
if Npoints > 100 and e%(Npoints//100) == 0: # report in 1% steps if possible and avoid modulo by zero
if Npoints > 100 and e%(Npoints//100) == 0: # report in 1% steps if possible and avoid modulo by zero
damask.util.print_progress(iteration=n,total=Npoints,prefix='2/3: scanning nodes ')
myNodeID = p.node_id(n)
myNodeCoordinates = [p.node(n).x, p.node(n).y, p.node(n).z]
@ -862,27 +862,27 @@ if options.nodalScalar:
# 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
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)
if grp not in index: # create a new group if not yet present
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
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],
[myElemID,myNodeID,myIpID,myGrainID]) # keep only if unique average location
[myElemID,myNodeID,myIpID,myGrainID]) # keep only if unique average location
groups[index[grp]][0][4:] = mapIncremental('','avg',
len(groups[index[grp]])-1,
groups[index[grp]][0][4:],
myNodeCoordinates) # incrementally update average location
groups[index[grp]].append([myElemID,myNodeID,myIpID,myGrainID,0]) # append a new list defining each group member
myNodeCoordinates) # incrementally update average location
groups[index[grp]].append([myElemID,myNodeID,myIpID,myGrainID,0]) # append a new list defining each group member
memberCount += 1
print('\n')
@ -1030,7 +1030,7 @@ for incCount,position in enumerate(locations): # walk through locations
Ngroups = len(groups)
for j,group in enumerate(groups):
f = incCount*Ngroups + j
if (Ngroups*Nincs) > 100 and f%((Ngroups*Nincs)//100) == 0: # report in 1% steps if possible and avoid modulo by zero
if (Ngroups*Nincs) > 100 and f%((Ngroups*Nincs)//100) == 0: # report in 1% steps if possible and avoid modulo by zero
damask.util.print_progress(iteration=f,total=Ngroups*Nincs,prefix='3/3: processing points ')
N = 0 # group member counter
for (e,n,i,g,n_local) in group[1:]: # loop over group members