# 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]