jro_soft/compressed_sensing Files · trunk/src/src/FSfarras.py

Cleaned code, fixed bugs/errors, updated plotting part....

Cleaned code, fixed bugs/errors, updated plotting part. Improved time performance but it still needs to be optimized (CS)

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             FSfarras.py
        
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      '''

      Created on May 26, 2014

      @author: Yolian Amaro

      '''

      #import pywt

      import numpy as np

      def FSfarras():

          #function [af, sf] = FSfarras

          # Farras filters organized for the dual-tree

          # complex DWT.

          #

          # USAGE:

          #    [af, sf] = FSfarras

          # OUTPUT:

          #    af{i}, i = 1,2 - analysis filters for tree i

          #    sf{i}, i = 1,2 - synthesis filters for tree i

          # See farras, dualtree, dualfilt1.

          #

          # WAVELET SOFTWARE AT POLYTECHNIC UNIVERSITY, BROOKLYN, NY

          # http://taco.poly.edu/WaveletSoftware/

          #

          # Translated to Python by Yolian Amaro

          a1 = np.array( [

                [                0,                  0],

                [-0.08838834764832,   -0.01122679215254],

                [ 0.08838834764832,   0.01122679215254],

                [ 0.69587998903400,    0.08838834764832],

                [ 0.69587998903400,   0.08838834764832],

                [ 0.08838834764832,   -0.69587998903400],

                [-0.08838834764832,   0.69587998903400],

                [ 0.01122679215254,   -0.08838834764832],

                [ 0.01122679215254,   -0.08838834764832],

                [0,                                   0]

               ] );

          a2 = np.array([

                [ 0.01122679215254,                  0],

                [ 0.01122679215254,                  0],

                [-0.08838834764832,  -0.08838834764832],

                [ 0.08838834764832,  -0.08838834764832],

                [ 0.69587998903400,   0.69587998903400],

                [ 0.69587998903400,  -0.69587998903400],

                [ 0.08838834764832,   0.08838834764832],

                [-0.08838834764832,   0.08838834764832],

                [                0,   0.01122679215254],

                [                0,  -0.01122679215254]

              ]);

          af = np.array([  [a1,a2]  ], dtype=object)

          s1 = a1[::-1]

          s2 = a2[::-1]

          sf = np.array([  [s1,s2]  ], dtype=object)

          return af, sf

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				'''
				Created on May 26, 2014

				@author: Yolian Amaro
				'''

				#import pywt
				import numpy as np

				def FSfarras():
				#function [af, sf] = FSfarras

				# Farras filters organized for the dual-tree
				# complex DWT.
				#
				# USAGE:
				# [af, sf] = FSfarras
				# OUTPUT:
				# af{i}, i = 1,2 - analysis filters for tree i
				# sf{i}, i = 1,2 - synthesis filters for tree i
				# See farras, dualtree, dualfilt1.
				#
				# WAVELET SOFTWARE AT POLYTECHNIC UNIVERSITY, BROOKLYN, NY
				# http://taco.poly.edu/WaveletSoftware/
				#
				# Translated to Python by Yolian Amaro


				a1 = np.array( [
				[ 0, 0],
				[-0.08838834764832, -0.01122679215254],
				[ 0.08838834764832, 0.01122679215254],
				[ 0.69587998903400, 0.08838834764832],
				[ 0.69587998903400, 0.08838834764832],
				[ 0.08838834764832, -0.69587998903400],
				[-0.08838834764832, 0.69587998903400],
				[ 0.01122679215254, -0.08838834764832],
				[ 0.01122679215254, -0.08838834764832],
				[0, 0]
				] );

				a2 = np.array([
				[ 0.01122679215254, 0],
				[ 0.01122679215254, 0],
				[-0.08838834764832, -0.08838834764832],
				[ 0.08838834764832, -0.08838834764832],
				[ 0.69587998903400, 0.69587998903400],
				[ 0.69587998903400, -0.69587998903400],
				[ 0.08838834764832, 0.08838834764832],
				[-0.08838834764832, 0.08838834764832],
				[ 0, 0.01122679215254],
				[ 0, -0.01122679215254]
				]);


				af = np.array([ [a1,a2] ], dtype=object)

				s1 = a1[::-1]
				s2 = a2[::-1]

				sf = np.array([ [s1,s2] ], dtype=object)

				return af, sf