view stdparams_exact.py @ 21:d395461b92ae tip

Lots and lots of modifications. Approximate recovery script working.

# -*- coding: utf-8 -*-
"""
Defines standard parameters for exact reconstruction simulation
Author: Nicolae Cleju
"""
__author__ = "Nicolae Cleju"
__license__ = "GPL"
__email__ = "[e-mail]"


import numpy

# Solver algorithms to run
from algos import *


# Test parameters
paramstest = dict()
paramstest['algos'] = exact_gap,exact_sl0,exact_bp,exact_ompeps,exact_tst       # tuple of algorithms
#paramstest['algos'] = exact_bp_cvxopt,       # tuple of algorithms
paramstest['d'] = 200.0
paramstest['sigma'] = 1.2
paramstest['deltas'] = numpy.array([0.05, 0.45, 0.95])
paramstest['rhos'] = numpy.array([0.05, 0.45, 0.95])
#deltas = numpy.array([0.6])
#deltas = numpy.arange(0.05,1.,0.05)
#rhos = numpy.array([0.05])
paramstest['numvects'] = 10; # Number of vectors to generate
paramstest['SNRdb'] = 100.;    # This is norm(signal)/norm(noise), so power, not energy
paramstest['savedataname'] = 'exact_pt_stdtest.mat'
paramstest['saveplotbase'] = 'exact_pt_stdtest_'
paramstest['saveplotexts'] = ('png','pdf','eps')

# Standard parameters 1
# All algorithms, 100 vectors
# d = 200, sigma = 1.2, delta and rho full resolution (0.05 step)
# Virtually no noise (100db)
params1 = dict()
params1['algos'] = exact_gap,exact_sl0,exact_bp_cvxopt,exact_ompeps,exact_tst       # tuple of algorithms
params1['d'] = 200.0;
params1['sigma'] = 1.2
params1['deltas'] = numpy.arange(0.05,1.,0.05)
params1['rhos'] = numpy.arange(0.05,1.,0.05)
params1['numvects'] = 100; # Number of vectors to generate
params1['SNRdb'] = 100.;    # This is norm(signal)/norm(noise), so power, not energy
params1['savedataname'] = 'exact_pt_std1.mat'
params1['saveplotbase'] = 'exact_pt_std1_'
params1['saveplotexts'] = ('png','pdf','eps')

        
# Standard parameters 2
# All algorithms, 100 vectors
# d = 20, sigma = 10, delta and rho full resolution (0.05 step)
# Virtually no noise (100db)
params2 = dict()
params2['algos'] = exact_gap,exact_sl0,exact_bp_cvxopt,exact_ompeps,exact_tst       # tuple of algorithms
params2['d'] = 20.0
params2['sigma'] = 10.0
params2['deltas'] = numpy.arange(0.05,1.,0.05)
params2['rhos'] = numpy.arange(0.05,1.,0.05)
params2['numvects'] = 100; # Number of vectors to generate
params2['SNRdb'] = 100.;    # This is norm(signal)/norm(noise), so power, not energy
params2['savedataname'] = 'exact_pt_std2.mat'
params2['saveplotbase'] = 'exact_pt_std2_'
params2['saveplotexts'] = ('png','pdf','eps')