def dezing_brickframe(pnum): mu=1.5 instack=read_image_set(pnum) outim=np.empty_like(instack) tifffile.imsave("/dls/science/users/kny48981/instack.tif",instack) dezing.setup(instack,outim,mu,2) dezing.run(instack,outim) dezing.cleanup(instack,outim) tifffile.imsave("/dls/science/users/kny48981/outstack.tif",outim)
def dezing_brickframe(pnum): mu = 1.5 instack = read_image_set(pnum) outim = np.empty_like(instack) tifffile.imsave("/dls/science/users/kny48981/instack.tif", instack) dezing.setup(instack, outim, mu, 2) dezing.run(instack, outim) dezing.cleanup(instack, outim) tifffile.imsave("/dls/science/users/kny48981/outstack.tif", outim)
def main(): #inim3,outim=get_image_array() inim3,outim=construct_test_array() tifffile.imsave("in.tif",inim3[:,:,0]) tifffile.imsave("inflop.tif",inim3[0,:,:]) print "in test_pymain: array shape is:",inim3.shape mu=float(sys.argv[1]) npad=2 dezing.setup_size(inim3.shape,mu,npad) dezing.run(inim3,outim) dezing.cleanup() tifffile.imsave("out%f.tif" % mu ,outim[10,:,:])
def main(): #inim3,outim=get_image_array() inim3, outim = construct_test_array() tifffile.imsave("in.tif", inim3[:, :, 0]) tifffile.imsave("inflop.tif", inim3[0, :, :]) print "in test_pymain: array shape is:", inim3.shape mu = float(sys.argv[1]) npad = 2 dezing.setup_size(inim3.shape, mu, npad) dezing.run(inim3, outim) dezing.cleanup() tifffile.imsave("out%f.tif" % mu, outim[10, :, :])
def filter_frame(self, data): logging.debug("Running Dezing Frame") result = np.empty_like(data) dezing.run(data, result) logging.debug("Finished Dezing Frame") return result
def filter_frames(self, data): result = np.empty_like(data[0]) logging.debug("Python: calling cython funciton dezing.run") (retval, self.warnflag, self.errflag) = dezing.run(data[0], result) return result
def _dezing(self, data): result = np.empty_like(data) (retval, self.warnflag, self.errflag) = dezing.run(data, result) return result
def filter_frame(self, data): logging.debug("Running Dezing Frame") result=np.empty_like(data) dezing.run(data,result) logging.debug("Finished Dezing Frame") return result
def filter_frames(self, data): result = np.empty_like(data[0]) dezing.run(data[0], result) return result