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DAMASK_EICMD
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introduced moving of multiple seeds at the same time 

introduced more suitable check for convergence of the first bin. Improvements in bringing seeds with a size outside the range of the target closer are no longer invisible
This commit is contained in:
Martin Diehl 2015-04-14 12:42:35 +00:00
parent 7e0b79a33c
commit 64764b0902
1 changed files with 20 additions and 11 deletions
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31
processing/pre/seeds_fromDistribution.py
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@ -76,11 +76,17 @@ class myThread (threading.Thread):
s.release()
if randReset: # new direction because current one led to worse fit
selectedMs = random.randrange(1,maxSeeds)
direction = np.array(((random.random()-0.5)*delta[0],
(random.random()-0.5)*delta[1],
(random.random()-0.5)*delta[2]))
randReset = False
NmoveGrains = random.randrange(1,maxSeeds)
selectedMs = []
direction = []
for i in xrange(NmoveGrains):
selectedMs.append(random.randrange(1,nMicrostructures))
direction.append(np.array(((random.random()-0.5)*delta[0],
(random.random()-0.5)*delta[1],
(random.random()-0.5)*delta[2])))
perturbedSeedsVFile.close() # reset virtual file
perturbedSeedsVFile = StringIO()
@ -92,9 +98,9 @@ class myThread (threading.Thread):
outputAlive=True
ms = 1
while outputAlive and perturbedSeedsTable.data_read(): # perturbe selected microstructure
if ms == selectedMs:
if ms in selectedMs:
direction+=direction
newCoords=np.array(tuple(map(float,perturbedSeedsTable.data[0:3]))+direction)
newCoords=np.array(tuple(map(float,perturbedSeedsTable.data[0:3]))+direction[i])
newCoords=np.where(newCoords>=1.0,newCoords-1.0,newCoords) # ensure that the seeds remain in the box (move one side out, other side in)
newCoords=np.where(newCoords <0.0,newCoords+1.0,newCoords)
perturbedSeedsTable.data[0:3]=[format(f, '8.6f') for f in newCoords]
@ -123,8 +129,8 @@ class myThread (threading.Thread):
currentError.append(np.sqrt(np.square(np.array(target[i]['histogram']-currentHist[i])).sum()))
if currentError[0]>0.0: # as long as not all grains are within the range of the target, use the deviation to left and right as error
currentError[0] =((target[0]['bins'][0]-np.min(currentData))**2.0+
(target[0]['bins'][1]-np.max(currentData))**2.0)**0.5
currentError[0] *=((target[0]['bins'][0]-np.min(currentData))**2.0+
(target[0]['bins'][1]-np.max(currentData))**2.0)**0.5 # norm of deviations by number of usual bin deviation
s.acquire() # do the evaluation serially
bestMatch = match
#--- count bin classes with no mismatch ----------------------------------------------------------------------
@ -271,15 +277,18 @@ for i in xrange(nMicrostructures):
# as long as not all grain sizes are within the range, the error is the deviation to left and right
if target[0]['error'] > 0.0:
target[0]['error'] =((target[0]['bins'][0]-np.min(initialData))**2.0+
(target[0]['bins'][1]-np.max(initialData))**2.0)**0.5
target[0]['error'] *=((target[0]['bins'][0]-np.min(initialData))**2.0+
(target[0]['bins'][1]-np.max(initialData))**2.0)**0.5
match=0
for i in xrange(nMicrostructures):
if target[i]['error'] > 0.0: break
match = i+1
if options.maxseeds < 1: maxSeeds = initialMicrostructures
if options.maxseeds < 1:
maxSeeds = initialMicrostructures
else:
maxSeeds = options.maxseeds
if match >0: print 'Stage %i cleared'%match
sys.stdout.flush()