nikcleju@4: # -*- coding: utf-8 -*-
nikcleju@4: """
nikcleju@4: Created on Mon Oct 24 21:17:49 2011
nikcleju@4: 
nikcleju@4: @author: Nic
nikcleju@4: 
nikcleju@4: Test RecommendedTST algorithm
nikcleju@5: u"""
nikcleju@4: 
nikcleju@4: import numpy as np
nikcleju@4: import numpy.linalg
nikcleju@4: import scipy.io
nikcleju@4: import unittest
nikcleju@4: from pyCSalgos.RecomTST.RecommendedTST import RecommendedTST
nikcleju@4: 
nikcleju@4: class RecomTSTresults(unittest.TestCase):
nikcleju@4:   def testResults(self):
nikcleju@4:     mdict = scipy.io.loadmat('RecomTSTtestdata.mat')
nikcleju@4:     
nikcleju@4:     # A = system matrix
nikcleju@4:     # Y = matrix with measurements (on columns)
nikcleju@4:     # X0 = matrix with initial solutions (on columns)
nikcleju@4:     # Eps = vector with epsilon
nikcleju@4:     # Xr = matrix with correct solutions (on columns)
nikcleju@4:     for A,Y,X0,Tol,Xr in zip(mdict['cellA'].squeeze(),mdict['cellY'].squeeze(),mdict['cellX0'].squeeze(),mdict['cellTol'].squeeze(),mdict['cellXr'].squeeze()):
nikcleju@4:       for i in np.arange(Y.shape[1]):
nikcleju@4:         xr = RecommendedTST(A, Y[:,i], nsweep=300, tol=Tol.squeeze()[i], xinitial=X0[:,i])
nikcleju@4:         
nikcleju@4:         # check if found solution is the same as the correct cslution
nikcleju@4:         diff = numpy.linalg.norm(xr - Xr[:,i])
nikcleju@5:         err1 = numpy.linalg.norm(Y[:,i] - np.dot(A,xr))
nikcleju@5:         err2 = numpy.linalg.norm(Y[:,i] - np.dot(A,Xr[:,i]))
nikcleju@5:         norm1 = numpy.linalg.norm(xr,1)
nikcleju@5:         norm2 = numpy.linalg.norm(Xr[:,i],1)
nikcleju@5:                 
nikcleju@5:         # Make a more robust condition:
nikcleju@4:         #  OK;    if   solutions are close enough (diff < 1e-6)
nikcleju@4:         #              or
nikcleju@4:         #              (
nikcleju@5:         #               Python solution fulfills the constraint better (or up to 1e-6 worse)
nikcleju@4:         #                 and
nikcleju@4:         #               Python solution has l1 norm no more than 1e-6 larger as the reference solution
nikcleju@4:         #                 (i.e. either norm1 < norm2   or   norm1>norm2 not by more than 1e-6)
nikcleju@4:         #              )
nikcleju@4:         #        
nikcleju@5:         #  ERROR: else        
nikcleju@5:         differr  = err1 - err2    # intentionately no abs(), since err1` < err2 is good
nikcleju@5:         diffnorm = norm1 - norm2  # intentionately no abs(), since norm1 < norm2 is good
nikcleju@5:         if diff < 1e-6 or (differr < 1e-6 and (diffnorm < 1e-6)):
nikcleju@5:           isok = True
nikcleju@5:         else:
nikcleju@5:           isok = False
nikcleju@5:         self.assertTrue(isok)
nikcleju@5:         
nikcleju@5:         #diff = numpy.linalg.norm(xr - Xr[:,i])
nikcleju@5:         #if diff > 1e-6:
nikcleju@5:         #    self.assertTrue(diff < 1e-6)
nikcleju@5: 
nikcleju@4:   
nikcleju@4: if __name__ == "__main__":
nikcleju@7:     #import cProfile
nikcleju@7:     #cProfile.run('unittest.main()', 'profres')
nikcleju@7:     unittest.main()    
nikcleju@4:     #suite = unittest.TestLoader().loadTestsFromTestCase(CompareResults)
nikcleju@7:     #unittest.TextTestRunner(verbosity=2).run(suite)