view tests/sl0_test.py @ 18:a8ff9a881d2f

GAP test almost working. For some data the results are not the same because of representation error, so the test doesn't fully work for now. But the results seem to be accurate.

# -*- coding: utf-8 -*-
"""
Created on Sat Nov 05 20:29:02 2011
Test SL0 algorithm
@author: Nic
"""


import numpy as np
import numpy.linalg
import scipy.io
import unittest
from pyCSalgos.SL0.SL0 import SL0

class SL0results(unittest.TestCase):
  def testResults(self):
    mdict = scipy.io.loadmat('SL0testdata.mat')
    
    # A = system matrix
    # Y = matrix with measurements (on columns)
    # sigmamin = vector with sigma_min
    for A,Y,sigmamin,Xr in zip(mdict['cellA'].squeeze(),mdict['cellY'].squeeze(),mdict['sigmamin'].squeeze(),mdict['cellXr'].squeeze()):
      for i in np.arange(Y.shape[1]):
        
        # Fix numpy error "LapackError: Parameter a has non-native byte order in lapack_lite.dgesdd"
        A = A.newbyteorder('=')
        Y = Y.newbyteorder('=')
        sigmamin = sigmamin.newbyteorder('=')
        Xr = Xr.newbyteorder('=')
        
        xr = SL0(A, Y[:,i], sigmamin)
        
        # check if found solution is the same as the correct cslution
        diff = numpy.linalg.norm(xr - Xr[:,i])
        self.assertTrue(diff < 1e-12)
    #        err1 = numpy.linalg.norm(Y[:,i] - np.dot(A,xr))
    #        err2 = numpy.linalg.norm(Y[:,i] - np.dot(A,Xr[:,i]))
    #        norm1 = numpy.linalg.norm(xr,1)
    #        norm2 = numpy.linalg.norm(Xr[:,i],1)
    #                
    #        # Make a more robust condition:
    #        #  OK;    if   solutions are close enough (diff < 1e-6)
    #        #              or
    #        #              (
    #        #               Python solution fulfills the constraint better (or up to 1e-6 worse)
    #        #                 and
    #        #               Python solution has l1 norm no more than 1e-6 larger as the reference solution
    #        #                 (i.e. either norm1 < norm2   or   norm1>norm2 not by more than 1e-6)
    #        #              )
    #        #        
    #        #  ERROR: else        
    #        differr  = err1 - err2    # intentionately no abs(), since err1` < err2 is good
    #        diffnorm = norm1 - norm2  # intentionately no abs(), since norm1 < norm2 is good
    #        if diff < 1e-6 or (differr < 1e-6 and (diffnorm < 1e-6)):
    #          isok = True
    #        else:
    #          isok = False
    #        self.assertTrue(isok)
        
        #diff = numpy.linalg.norm(xr - Xr[:,i])
        #if diff > 1e-6:
        #    self.assertTrue(diff < 1e-6)

  
if __name__ == "__main__":
    #import cProfile
    #cProfile.run('unittest.main()', 'profres')
    unittest.main()    
    #suite = unittest.TestLoader().loadTestsFromTestCase(CompareResults)
    #unittest.TextTestRunner(verbosity=2).run(suite)