def runSCG(args):
fileName, spcereg, offset, seq, batch, l, readIterFunc = args
reader = HairDataReader(fileName, {'type':'anim2'})
mat = []
reader.seek(seq*batch)
for i in xrange(batch):
res = readIterFunc(reader, i, mat, offset, spcereg)
if res is None:
logging.warning("Unexpected break at runSCG, frame %d" % i)
break
reader.close()
printMP(l, "Finish read batch %d..." % seq)
return seq, mat
def SCGetMatrixAndHeaderMP(fileName, readIterFunc, nFrame=None):
reader = HairDataReader(fileName, {'type':'anim2'})
factor = para.factor
offset = factor * 3
spcereg = para.lambda_balance # regularize the space item
if not nFrame:
nFrame = reader.nFrame
print "Reading frame %d :" % nFrame
pool = Pool()
m = Manager()
l = m.Lock()
batchsz = 10
job_args = [(fileName, spcereg, offset, i, batchsz, l, readIterFunc) for i in xrange(nFrame/batchsz) ]
mat = pool.map(runSCG, job_args)
pool.close()
reader.close()
mat.sort(key=lambda x: x[0])
mat2 = []
for item in mat:
for arr in item[1]:
mat2.append(arr)
mat = None
X = np.hstack(mat2).transpose()
mat2 = None
print "\rFinished Reading!"
header = HairHeader()
header.nParticle = reader.nParticle
header.factor = factor
header.nHair = header.nParticle / factor
assert(X.dtype==np.float64)
return X, header, XWrapper(X, offset*2)
