view stdparams_exact.py @ 15:a27cfe83fe12

Changing, changing, trying to get a common framework for batch jobs

# -*- coding: utf-8 -*-
"""
Created on Wed Dec 07 14:04:40 2011

@author: ncleju
"""

import numpy
from algos import *

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'] = 50.0
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=50, sigma = 2, delta and rho full resolution (0.05 step), lambdas = 0, 1e-4, 1e-2, 1, 100, 10000
# Do save data, do save plots, don't show plots
params1 = dict()
params1['algos'] = exact_gap,exact_sl0,exact_bp_cvxopt,exact_ompeps,exact_tst       # tuple of algorithms
params1['d'] = 50.0;
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), lambdas = 0, 1e-4, 1e-2, 1, 100, 10000
# Do save data, do save plots, don't show plots
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')