# for i in range(len(inlist)):
# try:
# print "load %s begin" %inlist[i]
# sys.stdout.flush()
# imIn=tsc.loadImages(inlist[i], inputFormat='tif-stack')
# print "load end"
# sys.stdout.flush()
# t_start=time.time()
# result=reg.run(imIn)
# result.exportAsTiffs(outlist[i], overwrite=True)
# t_end=time.time()
# print 'spark cluster image: ', inlist[i][len(input):], 'iter: ', iter, ' time: ', (t_end-t_start)
# except:
# print 'error ', inlist[i]
for iter in iters:
reg.prepare("/home/wb/hdfs_2d/PSF_2d.tif", iter)
for i in range(len(inlist)):
print "load %s begin" %inlist[i]
sys.stdout.flush()
imIn=tsc.loadImages(inlist[i], inputFormat='tif-stack')
print imIn.collect()
print "load end"
sys.stdout.flush()
t_start=time.time()
result=reg.run(imIn)
print "save %s end" %outlist[i]
sys.stdout.flush()
result.exportAsTiffs(outlist[i], overwrite=True)
os.makedirs(denoise)
return (in_list, out_list)
if __name__=='__main__':
inlist, outlist=fs_in_out(input, output)
conf = SparkConf().setAppName('test')
tsc=lambdaimageContext.start(conf=conf)
reg=Deconvolution('rl')
#iters=[100, 150, 200, 250]
iters=[5]
for iter in iters:
#reg.prepare("/home/jph/test/PSF_2d.tif", iter)
#reg.prepare("/home/jph/graduate_test/Version/Spark/fs_2d/PSF_50.tif", iter)
reg.prepare("/home/wb/data/deconv/PSF.tif", iter)
#reg.prepare("/home/wb/data/fs_3d/PSF_3d.tif", iter)
for i in range(len(inlist)):
try:
imIn=tsc.loadImages(inlist[i], inputFormat='tif-stack')
t_start=time.time()
result=reg.run(imIn)
result.exportAsTiffs(outlist[i], overwrite=True)
#imIn.exportAsTiffs(outlist[i], overwrite=True)
t_end=time.time()
print 'spark local image: ', inlist[i][len(input):], 'iter: ', iter, ' time: ', (t_end-t_start)
except BaseException, e:
print 'error ', inlist[i]
