tut/OriEstimation/Msmoothgradient.py File Reference

Go to the source code of this file.

Namespaces

namespace Msmoothgradient

Variables

tuple par = sf.Par()

tuple input = sf.Input()

tuple output1 = sf.Output(par.string("dx_outputfilename"))

tuple output2 = sf.Output(par.string("dy_outputfilename"))

tuple n1 = input.int("n1")

tuple n2 = input.int("n2")

tuple ni = input.size(2)

tuple inputimage = np.zeros((n1,n2),'f')

tuple input_padded = Sadiabatic(inputimage)

tuple I = array(range(1,n1+1))

tuple J = array(range(1,n2+1))

tuple Imx = (3*input_padded[I+1][:,J-1]+10*input_padded[I+1][:,J]+3*input_padded[I+1][:,J+1]-3*input_padded[I-1][:,J-1]-10*input_padded[I-1][:,J]-3*input_padded[I-1][:,J+1])

tuple Imy = (3*input_padded[I-1][:,J+1]+10*input_padded[I][:,J+1]+3*input_padded[I+1][:,J+1]-3*input_padded[I-1][:,J-1]-10*input_padded[I][:,J-1]-3*input_padded[I+1][:,J-1])


Namespaces
namespace	Msmoothgradient
Variables
tuple	par = sf.Par()
tuple	input = sf.Input()
tuple	output1 = sf.Output(par.string("dx_outputfilename"))
tuple	output2 = sf.Output(par.string("dy_outputfilename"))
tuple	n1 = input.int("n1")
tuple	n2 = input.int("n2")
tuple	ni = input.size(2)
tuple	inputimage = np.zeros((n1,n2),'f')
tuple	input_padded = Sadiabatic(inputimage)
tuple	I = array(range(1,n1+1))
tuple	J = array(range(1,n2+1))
tuple	Imx = (3input_padded[I+1][:,J-1]+10input_padded[I+1][:,J]+3input_padded[I+1][:,J+1]-3input_padded[I-1][:,J-1]-10input_padded[I-1][:,J]-3input_padded[I-1][:,J+1])
tuple	Imy = (3input_padded[I-1][:,J+1]+10input_padded[I][:,J+1]+3input_padded[I+1][:,J+1]-3input_padded[I-1][:,J-1]-10input_padded[I][:,J-1]-3input_padded[I+1][:,J-1])