comparison stdparams_exact.py @ 17:7fdf964f4edd

Added docstrings to files and functions

 # -*- coding: utf-8 -*-
 """
-Created on Wed Dec 07 14:04:40 2011
+Defines standard parameters for exact reconstruction simulation
+Author: Nicolae Cleju
+"""
+__author__ = "Nicolae Cleju"
+__license__ = "GPL"
+__email__ = "[e-mail]"
 
-@author: ncleju
-"""
 
 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'] = 50.0
 paramstest['sigma'] = 1.2

 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
+# 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'] = 50.0;
+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['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
+# 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)