nikcleju@0: # -*- coding: utf-8 -*-
nikcleju@0: """
nikcleju@17: Some utility functions.
nikcleju@0: 
nikcleju@17: Author: Nicolae Cleju
nikcleju@0: """
nikcleju@0: 
nikcleju@0: import numpy
nikcleju@0: import scipy.io
nikcleju@0: import matplotlib.pyplot as plt
nikcleju@0: import matplotlib.cm as cm
nikcleju@0: import matplotlib.colors as mcolors
nikcleju@0: 
nikcleju@0: # Sample call
nikcleju@0: #utils.loadshowmatrices_multipixels('H:\\CS\\Python\\Results\\pt_std1\\approx_pt_std1.mat', dosave=True, saveplotbase='approx_pt_std1_',saveplotexts=('png','eps','pdf'))
nikcleju@0: 
nikcleju@19: def replot_exact(filename, algonames = None, doshow=True, dosave=False, saveplotbase=None, saveplotexts=None):
nikcleju@19:     """
nikcleju@19:     Replot exact recovery results from mat file, with better axis ticks and 
nikcleju@19:     other custom tweaked options.
nikcleju@19:     """
nikcleju@19: 
nikcleju@19:     mdict = scipy.io.loadmat(filename)
nikcleju@19: 
nikcleju@19:     if algonames == None:
nikcleju@19:       if 'algonames' in mdict:
nikcleju@19:         algonames = mdict['algonames']
nikcleju@19:       else:
nikcleju@19:         print "No algonames given, and couldn't find them in mat file."
nikcleju@19:         print "Exiting."
nikcleju@19:         return
nikcleju@19:  
nikcleju@21:     withticks = ['GAP']
nikcleju@21:     withnoaxes = [algoname[0][0] for algoname in algonames if algoname not in withticks]
nikcleju@21:     loadshowmatrices_multipixels(filename, algonames, [], [], withticks, withnoaxes, doshow, dosave, saveplotbase, saveplotexts)
nikcleju@19:       
nikcleju@19: def replot_approx(filename, algonames = None, doshow=True, dosave=False, saveplotbase=None, saveplotexts=None):
nikcleju@19:     """
nikcleju@19:     Replot exact recovery results from mat file, with better axis ticks and 
nikcleju@19:     other custom tweaked options.
nikcleju@19:     """
nikcleju@19: 
nikcleju@19:     mdict = scipy.io.loadmat(filename)
nikcleju@19: 
nikcleju@19:     if algonames == None:
nikcleju@19:       if 'algosNnames' in mdict and 'algosLnames' in mdict:
nikcleju@21:         
nikcleju@21:         if mdict['algosLnames'].size is 0:
nikcleju@21:           algonames = mdict['algosNnames']
nikcleju@21:         elif mdict['algosNnames'].size is 0:
nikcleju@21:           algonames = mdict['algosLnames']
nikcleju@21:         else:
nikcleju@21:           algonames = numpy.vstack((mdict['algosNnames'], mdict['algosLnames']))
nikcleju@19:       else:
nikcleju@19:         print "No algonames given, and couldn't find them in mat file."
nikcleju@19:         print "Exiting."
nikcleju@19:         return
nikcleju@19:         
nikcleju@19:     if dosave:
nikcleju@19:       lambdas = mdict['lambdas']
nikcleju@19:     threshs = [(0.85,2,0),(0.8,2,0.4),(0.5,2,1)]
nikcleju@19:     withticks = ['GAP']
nikcleju@19:     withnoaxes = [algoname[0][0] for algoname in algonames if algoname not in withticks]
nikcleju@19:     #withnoaxes.remove('GAP')
nikcleju@19:     loadshowmatrices_multipixels(filename, algonames, lambdas, threshs, withticks, withnoaxes, doshow, dosave, saveplotbase, saveplotexts)
nikcleju@19: 
nikcleju@19: def loadshowmatrices_multipixels(filename, algonames, lambdas, threshs = [], withticks = [], withnoaxes = [], doshow=True, dosave=False, saveplotbase=None, saveplotexts=None):
nikcleju@0:   
nikcleju@0:     if dosave and (saveplotbase is None or saveplotexts is None):
nikcleju@0:       print('Error: please specify name and extensions for saving')
nikcleju@0:       raise Exception('Name or extensions for saving not specified')
nikcleju@0:       
nikcleju@0:     mdict = scipy.io.loadmat(filename)
nikcleju@19: 
nikcleju@19:     N = 10  # one data box = NxN
nikcleju@19: 
nikcleju@0:     for algonameobj in algonames:
nikcleju@0:         algoname = algonameobj[0][0]
nikcleju@0:         print algoname
nikcleju@0:         if mdict['meanmatrix'][algoname][0,0].ndim == 2:
nikcleju@0:             
nikcleju@0:             # Prepare bigger matrix
nikcleju@0:             rows,cols = mdict['meanmatrix'][algoname][0,0].shape
nikcleju@0:             bigmatrix = numpy.zeros((N*rows,N*cols))
nikcleju@0:             for i in numpy.arange(rows):
nikcleju@0:               for j in numpy.arange(cols):
nikcleju@0:                 bigmatrix[i*N:i*N+N,j*N:j*N+N] = mdict['meanmatrix'][algoname][0,0][i,j]
nikcleju@19:             
nikcleju@19:             for thrval,width,color in threshs:
nikcleju@19:               bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0],bigmatrix,N,thrval,width,color)
nikcleju@19: 
nikcleju@19:             #bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0],bigmatrix,10,0.95,2,0)
nikcleju@19:             #bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0],bigmatrix,10,0.8, 2,0.4)
nikcleju@19:             #bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0],bigmatrix,10,0.5, 2,1)
nikcleju@19:             
nikcleju@0: #                # Mark 95% border
nikcleju@0: #                if mdict['meanmatrix'][algoname][0,0][i,j] > thresh:
nikcleju@0: #                  # Top border
nikcleju@0: #                  if mdict['meanmatrix'][algoname][0,0][i-1,j] < thresh and i>0:
nikcleju@0: #                    bigmatrix[i*N:i*N+border,j*N:j*N+N] = bordercolor
nikcleju@0: #                  # Bottom border
nikcleju@0: #                  if mdict['meanmatrix'][algoname][0,0][i+1,j] < thresh and i<rows-1:
nikcleju@0: #                    bigmatrix[i*N+N-border:i*N+N,j*N:j*N+N] = bordercolor                
nikcleju@0: #                  # Left border
nikcleju@0: #                  if mdict['meanmatrix'][algoname][0,0][i,j-1] < thresh and j>0:
nikcleju@0: #                    bigmatrix[i*N:i*N+N,j*N:j*N+border] = bordercolor
nikcleju@0: #                  # Right border (not very probable)
nikcleju@0: #                  if j<cols-1 and mdict['meanmatrix'][algoname][0,0][i,j+1] < thresh:
nikcleju@0: #                    bigmatrix[i*N:i*N+N,j*N+N-border:j*N+N] = bordercolor
nikcleju@0:                     
nikcleju@0:             plt.figure()
nikcleju@7:             plt.imshow(bigmatrix, cmap=cm.gray, norm=mcolors.Normalize(0,1), interpolation='nearest',origin='lower')
nikcleju@19:             
nikcleju@19:             if algoname in withticks:
nikcleju@8:               int_setticks()
nikcleju@19:             if algoname in withnoaxes:
nikcleju@8:               plt.gca().get_xaxis().set_visible(False)
nikcleju@8:               plt.gca().get_yaxis().set_visible(False)
nikcleju@7:               
nikcleju@0:             if dosave:
nikcleju@0:               for ext in saveplotexts:
nikcleju@0:                 plt.savefig(saveplotbase + algoname + '.' + ext, bbox_inches='tight')            
nikcleju@0:         elif mdict['meanmatrix'][algoname][0,0].ndim == 3:
nikcleju@0:             if dosave:
nikcleju@0:               ilbd = 0          
nikcleju@0:               
nikcleju@0:             for matrix in mdict['meanmatrix'][algoname][0,0]:
nikcleju@0:               
nikcleju@0:                 # Prepare bigger matrix
nikcleju@0:                 rows,cols = matrix.shape
nikcleju@0:                 bigmatrix = numpy.zeros((N*rows,N*cols))
nikcleju@0:                 for i in numpy.arange(rows):
nikcleju@0:                   for j in numpy.arange(cols):
nikcleju@0:                     bigmatrix[i*N:i*N+N,j*N:j*N+N] = matrix[i,j]
nikcleju@19: 
nikcleju@19:                 for thrval,width,color in threshs:
nikcleju@19:                   bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0][ilbd],bigmatrix,N,thrval,width,color)
nikcleju@19: 
nikcleju@19:                 #bigmatrix = int_drawseparation(matrix,bigmatrix,10,0.95,2,0)
nikcleju@19:                 #bigmatrix = int_drawseparation(matrix,bigmatrix,10,0.8, 2,0.4)
nikcleju@19:                 #bigmatrix = int_drawseparation(matrix,bigmatrix,10,0.5, 2,1)
nikcleju@0: #                    # Mark 95% border
nikcleju@0: #                    if matrix[i,j] > thresh:
nikcleju@0: #                      # Top border
nikcleju@0: #                      if matrix[i-1,j] < thresh and i>0:
nikcleju@0: #                        bigmatrix[i*N:i*N+border,j*N:j*N+N] = bordercolor
nikcleju@0: #                      # Bottom border
nikcleju@0: #                      if matrix[i+1,j] < thresh and i<rows-1:
nikcleju@0: #                        bigmatrix[i*N+N-border:i*N+N,j*N:j*N+N] = bordercolor                
nikcleju@0: #                      # Left border
nikcleju@0: #                      if matrix[i,j-1] < thresh and j>0:
nikcleju@0: #                        bigmatrix[i*N:i*N+N,j*N:j*N+border] = bordercolor
nikcleju@0: #                      # Right border (not very probable)
nikcleju@0: #                      if j<cols-1 and matrix[i,j+1] < thresh:
nikcleju@0: #                        bigmatrix[i*N:i*N+N,j*N+N-border:j*N+N] = bordercolor
nikcleju@0:                 
nikcleju@0:                 plt.figure()
nikcleju@0:                 #plt.imshow(matrix, cmap=cm.gray, interpolation='nearest',origin='lower')
nikcleju@5:                 plt.imshow(bigmatrix, cmap=cm.gray, norm=mcolors.Normalize(0,1), interpolation='nearest',origin='lower')
nikcleju@19: 
nikcleju@19:                 #plt.gca().get_xaxis().set_visible(False)
nikcleju@19:                 #plt.gca().get_yaxis().set_visible(False)
nikcleju@7:                 #int_setticks()
nikcleju@19:                 if algoname in withticks:
nikcleju@19:                   int_setticks()
nikcleju@19:                 if algoname in withnoaxes:
nikcleju@19:                   plt.gca().get_xaxis().set_visible(False)
nikcleju@19:                   plt.gca().get_yaxis().set_visible(False)                
nikcleju@19:                 
nikcleju@0:                 if dosave:
nikcleju@0:                   for ext in saveplotexts:
nikcleju@0:                     plt.savefig(saveplotbase + algoname + ('_lbd%.0e' % lambdas[ilbd]) + '.' + ext, bbox_inches='tight')
nikcleju@19:                 
nikcleju@19:                 ilbd = ilbd + 1                
nikcleju@0:     if doshow:
nikcleju@0:       plt.show()
nikcleju@0:     print "Finished."    
nikcleju@21: 
nikcleju@21: def replot_ProveEll1(filename, algonames=None, doshow=True, dosave=False, saveplotbase=None, saveplotexts=None):
nikcleju@21: 
nikcleju@21:   """
nikcleju@21:   Plot ...
nikcleju@21:   The files are saved in the current folder.
nikcleju@21:   """
nikcleju@21: 
nikcleju@21:   mdict = scipy.io.loadmat(filename)
nikcleju@21: 
nikcleju@21:   if algonames == None:
nikcleju@21:     if 'algosNnames' in mdict and 'algosLnames' in mdict:
nikcleju@21:       algonames = numpy.vstack((mdict['algosNnames'], mdict['algosLnames']))
nikcleju@21:     else:
nikcleju@21:       print "No algonames given, and couldn't find them in mat file."
nikcleju@21:       print "Exiting."
nikcleju@21:       return
nikcleju@21: 
nikcleju@21:   lambdas = mdict['lambdas']
nikcleju@21: 
nikcleju@21:   toplot = numpy.zeros((len(lambdas),len(algonames)))
nikcleju@21:   
nikcleju@21:   idxcol = 0
nikcleju@21:   for algonameobj in algonames:
nikcleju@21:     algoname = algonameobj[0][0]
nikcleju@21:     if mdict['meanmatrix'][algoname][0,0].ndim == 2:
nikcleju@21:       toplot[:,idxcol] = (1 - mdict['meanmatrix'][algoname][0,0]) * numpy.ones(len(lambdas))
nikcleju@21:     elif mdict['meanmatrix'][algoname][0,0].ndim == 3:
nikcleju@21:       for ilbd in numpy.arange(len(lambdas)):
nikcleju@21:         toplot[ilbd,idxcol] = 1 - mdict['meanmatrix'][algoname][0,0][ilbd][0,0]
nikcleju@21:     idxcol = idxcol + 1
nikcleju@21: 
nikcleju@21:   plt.figure()
nikcleju@21:   plt.plot(toplot)
nikcleju@21:   #plt.legend([algonameobj[0][0] for algonameobj in algonames])
nikcleju@21:   plt.legend(['NESTA', r'ABS-$\lambda$: BP'])
nikcleju@21: 
nikcleju@21:   ax = plt.gca()
nikcleju@21: 
nikcleju@21:   fewerticks = [0,3,6,9]
nikcleju@21:   xticklabels = []
nikcleju@21:   for i in range(lambdas.size):
nikcleju@21:     if i in fewerticks:
nikcleju@21:       xticklabels.append('{:g}'.format(lambdas[i,0]))
nikcleju@21:     else:
nikcleju@21:       xticklabels.append('')
nikcleju@21:   ax.set_xticklabels(xticklabels)
nikcleju@21:   #ax.set_xlabel(r'Value of $\lambda$', size=60)
nikcleju@21:   ax.set_xlabel(r'$\lambda$', size=40)
nikcleju@21:   for label in ax.get_xticklabels():
nikcleju@21:     label.set_fontsize(20) 
nikcleju@21:   for label in ax.get_yticklabels():
nikcleju@21:     label.set_fontsize(20)
nikcleju@21:   for ext in saveplotexts:
nikcleju@21:     plt.savefig(saveplotbase + '.' + ext, bbox_inches='tight')
nikcleju@21: 
nikcleju@21:   if doshow:
nikcleju@21:     plt.show()
nikcleju@21:   print "Finished."   
nikcleju@0:     
nikcleju@0: def appendtomatfile(filename, toappend, toappendname):
nikcleju@0:   mdict = scipy.io.loadmat(filename)
nikcleju@0:   mdict[toappendname] = toappend
nikcleju@0:   try:
nikcleju@0:     scipy.io.savemat(filename, mdict)
nikcleju@0:   except:
nikcleju@0:     print "Save error"  
nikcleju@0:   
nikcleju@0:   # To save to a cell array, create an object array:
nikcleju@0:   #  >>> obj_arr = np.zeros((2,), dtype=np.object)
nikcleju@0:   #  >>> obj_arr[0] = 1
nikcleju@0:   #  >>> obj_arr[1] = 'a string'    
nikcleju@0:   
nikcleju@0: def int_drawseparation(matrix,bigmatrix,N,thresh,border,bordercolor):
nikcleju@0:   rows,cols = matrix.shape
nikcleju@0:   for i in numpy.arange(rows):
nikcleju@0:     for j in numpy.arange(cols):
nikcleju@0:       # Mark border
nikcleju@0:       # Use top-left corner of current square for reference
nikcleju@0:       if matrix[i,j] > thresh:
nikcleju@0:         # Top border
nikcleju@0:         if matrix[i-1,j] < thresh and i>0:
nikcleju@0:           bigmatrix[i*N:i*N+border,j*N:j*N+N] = bordercolor
nikcleju@0:         # Bottom border
nikcleju@0:         if i<rows-1 and matrix[i+1,j] < thresh:
nikcleju@0:           bigmatrix[i*N+N-border:i*N+N,j*N:j*N+N] = bordercolor                
nikcleju@0:         # Left border
nikcleju@0:         if matrix[i,j-1] < thresh and j>0:
nikcleju@0:           bigmatrix[i*N:i*N+N,j*N:j*N+border] = bordercolor
nikcleju@0:         # Right border (not very probable)
nikcleju@0:         if j<cols-1 and matrix[i,j+1] < thresh:
nikcleju@0:           bigmatrix[i*N:i*N+N,j*N+N-border:j*N+N] = bordercolor  
nikcleju@0:   
nikcleju@7:   return bigmatrix
nikcleju@19: 
nikcleju@7:   
nikcleju@7: def int_setticks():
nikcleju@7: 
nikcleju@8:   #ticks = [10, 94, 179]
nikcleju@8:   #ticklabels = ["0.05", "0.5", "0.95"]
nikcleju@8:   ticks = [10, 179]
nikcleju@8:   ticklabels = ["0.05", "0.95"]
nikcleju@7: 
nikcleju@7:   ax = plt.gca()
nikcleju@7:   ax.set_xticks(ticks)
nikcleju@7:   ax.set_xticklabels(ticklabels)
nikcleju@7:   ax.set_yticks(ticks)
nikcleju@7:   ax.set_yticklabels(ticklabels)
nikcleju@7:   
nikcleju@7:   for label in ax.get_xticklabels():
nikcleju@7:     label.set_fontsize(42) 
nikcleju@7:   for label in ax.get_yticklabels():
nikcleju@7:     label.set_fontsize(42)
nikcleju@7:     
nikcleju@8:   ax.set_xlabel(r'$\delta$', size=60)
nikcleju@8:   ax.set_ylabel(r'$\rho$', size=60)
nikcleju@8: