Commit aeb25645 authored by daniel.schellhorn's avatar daniel.schellhorn
Browse files

added non-relative path references to GetDate while implementing zip...

added non-relative path references to GetDate while implementing zip extraction, adding SetProxyPythonPath.py in phase and links in experiments in phase
parent dd7370d1
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The matlab code to implement the 2D phase retrieval of the coded diffraction pattern (CDP) problem using the RRR algorithm.
To run the code, execute the following command in terminal:
octave cdp.m
or run the script octave cdp.m in matlab.
function RRR_cdp_image(b, y, sol, D)
%% input parameters
beta = 0.5 ;
epsilon = 1.e-5 ;
iter_max = 100000 ;
L = size(D, 1) ;
height = size(D, 2) ;
width = size(D, 3) ;
%% The inverse of the diagonal terms of 1/n * Hermitian(A) * A
inv_diag = zeros(height, width) ;
for i = 1:L
for j = 1:height
for k = 1:width
inv_diag(j, k) = inv_diag(j, k) + abs(D(i, j, k))^2 ;
end
end
end
inv_diag = 1 ./ inv_diag ;
iter_arr = [] ;
err_arr = [] ;
cur_sol = zeros(height, width, 3) ;
for iter = 1:iter_max
rms_diff = 0. ;
norm_y = 0. ;
for c = 1:3
b_c = squeeze(b(:, :, :, c)) ;
y_c = squeeze(y(:, :, :, c)) ;
p1 = proj1(D, inv_diag, y_c, L, height, width) ;
p2 = proj2(b_c, 2*p1 - y_c) ;
delta_y = p2 - p1 ;
for k = 1:L
rms_diff = rms_diff + norm(squeeze(delta_y(k, :, :)))^2 ;
norm_y = norm_y + norm(squeeze(y_c(k, :, :)))^2 ;
end
y_c = y_c + beta*delta_y ;
y(:, :, :, c) = y_c ;
end
rms_diff = beta*sqrt(rms_diff / norm_y) ;
if (iter < 10 || mod(iter, 10) == 0)
norm1 = 0. ;
norm2 = 0. ;
for c = 1:3
x_c = reshape(squeeze(sol(:, :, c)), height*width, 1) ;
y_c = squeeze(y(:, :, :, c)) ;
p1 = proj1(D, inv_diag, y_c, L, height, width) ;
cur_sol(:, :, c) = Ainv(D, inv_diag, p1, L, height, width) ;
x_cur = reshape(squeeze(cur_sol(:, :, c)), height*width, 1) ;
norm1 = norm1 + norm(x_c - x_cur*sign(x_cur'*x_c))^2 ;
norm2 = norm2 + norm(x_c)^2 ;
end
filename = ['reconst-cornell-iter', int2str(iter), '.jpg'] ;
cur_img = uint8(round(abs(cur_sol))) ;
imwrite(cur_img, filename) ;
err_val = sqrt(norm1/norm2) ;
iter_arr = [iter_arr, iter] ;
err_arr = [err_arr, err_val] ;
[err_val, rms_diff]
if (rms_diff < epsilon)
break ;
end
end
end
fp = fopen('phasing-error.dat', 'w') ;
for i = 1:length(err_arr)
fprintf(fp, '%d %1.5e\n', iter_arr(i), err_arr(i)) ;
end
fclose(fp) ;
end
%% pseudo-inverse of A
function x1 = Ainv(D, inv_diag, y, L, height, width)
x1 = zeros(height, width) ;
for l = 1:L
x1 = x1 + squeeze(conj(D(l, :, :))) .* ifft2(squeeze(y(l, :, :))) ;
end
x1 = x1 .* inv_diag ;
end
%% projections
function y1 = proj1(D, inv_diag, y, L, height, width)
x1 = Ainv(D, inv_diag, y, L, height, width) ;
y1 = zeros(L, height, width) ;
for i = 1:L
y1(i, :, :) = fft2(squeeze(D(i, :, :)) .* x1) ;
end
end
function y2 = proj2(b, y)
y2 = b .* sign(y) ;
end
L = 3 ;
stanford = double(imread('stanford.jpg')) ;
cornell = double(imread('cornell.jpg')) ;
height = size(cornell, 1) ;
width = size(cornell, 2) ;
%% generate random coded diffraction pattern
D = zeros(L, height, width) ;
for i = 1:L
D(i, :, :) = exp(1i*floor(rand(height, width)*4)*pi/2) ;
end
b = zeros(L, height, width, 3) ; % data
y = zeros(L, height, width, 3) ; % initial guess
for c = 1:3
for i = 1:L
phase_mask = squeeze(D(i, :, :)) ;
b(i, :, :, c) = abs(fft2(phase_mask .* cornell(:, :, c))) ;
y(i, :, :, c) = fft2(phase_mask .* stanford(:, :, c)) ;
end
end
RRR_cdp_image(b, y, cornell, D) ;
## phase retrieval benchmarks
### RRR: Simple Phase Retrieval
This program is deliberately minimalist so as not to obscure the structure of the algorithm.
It needs the [FFTW3 library](http://www.fftw.org).
The program is set up for solving the benchmarks described in:
> "Benchmark problems for phase retrieval", V. Elser, T.-Y. Lan & T. Bendory
To compile:
```
gcc -O2 RRR.c -lm -lfftw3 -o RRR
```
To run:
```
./RRR [datafile] [supp] [powgoal] [beta] [iterlimit] [trials] [resultfile] &
```
- datafile: one of the benchmark datafiles (data/data100E, data/data140E, ...)
- supp: support size = 8*N, N = 100, 140, ... is the number of atoms
- powgoal: fractional power in support
- beta: RRR parameter
- iterlimit: RRR iteration limit (long int)
- trials: number of random starts
- resultfile: ASCII file of the iteration counts for each trial
Example:
```
./RRR data/data100E 800 .95 .5 1000 5 results100E &
```
Solutions are written to a file named sol (M x M table of floats).
Send comments, bug reports, to: ve10@cornell.edu
/*
-----------------------------------
RRR: Simple Phase Retrieval
-----------------------------------
This program is deliberately minimalist so as not to obscure
the structure of the algorithm. It needs the FFTW3 library:
http://www.fftw.org
The program is set up for solving the benchmarks described in:
"Benchmark problems for phase retrieval", V. Elser, T.-Y. Lan & T. Bendory
To compile:
gcc -O2 RRR.c -lm -lfftw3 -o RRR
To run:
./RRR [datafile] [supp] [powgoal] [beta] [iterlimit] [trials] [resultfile] &
datafile: one of the benchmark datafiles (data100E, data140E, ...)
supp: support size = 8*N, N = 100, 140, ... is the number of atoms
powgoal: fractional power in support
beta: RRR parameter
iterlimit: RRR iteration limit (long int)
trials: number of random starts
resultfile: ASCII file of the iteration counts for each trial
Example:
./RRR data/data100E 800 .95 .5 1000 5 results100E &
Solutions are written to a file named sol (M x M table of floats).
*/
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <math.h>
#include <complex.h>
#include <fftw3.h>