Mercurial > hg > absrec
view utils.py @ 19:2837cfeaf353
Fixed plot functions in utils.py
Started working for test_approx.py
author | Nic Cleju <nikcleju@gmail.com> |
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date | Thu, 05 Apr 2012 13:59:22 +0300 |
parents | 7fdf964f4edd |
children | d395461b92ae |
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# -*- coding: utf-8 -*- """ Some utility functions. Author: Nicolae Cleju """ import numpy import scipy.io import matplotlib.pyplot as plt import matplotlib.cm as cm import matplotlib.colors as mcolors # Sample call #utils.loadshowmatrices_multipixels('H:\\CS\\Python\\Results\\pt_std1\\approx_pt_std1.mat', dosave=True, saveplotbase='approx_pt_std1_',saveplotexts=('png','eps','pdf')) def replot_exact(filename, algonames = None, doshow=True, dosave=False, saveplotbase=None, saveplotexts=None): """ Replot exact recovery results from mat file, with better axis ticks and other custom tweaked options. """ mdict = scipy.io.loadmat(filename) if algonames == None: if 'algonames' in mdict: algonames = mdict['algonames'] else: print "No algonames given, and couldn't find them in mat file." print "Exiting." return loadshowmatrices_multipixels(filename, algonames, [], [], algonames, [], doshow, dosave, saveplotbase, saveplotexts) def replot_approx(filename, algonames = None, doshow=True, dosave=False, saveplotbase=None, saveplotexts=None): """ Replot exact recovery results from mat file, with better axis ticks and other custom tweaked options. """ mdict = scipy.io.loadmat(filename) if algonames == None: if 'algosNnames' in mdict and 'algosLnames' in mdict: algonames = numpy.vstack((mdict['algosNnames'], mdict['algosLnames'])) else: print "No algonames given, and couldn't find them in mat file." print "Exiting." return if dosave: lambdas = mdict['lambdas'] threshs = [(0.85,2,0),(0.8,2,0.4),(0.5,2,1)] withticks = ['GAP'] withnoaxes = [algoname[0][0] for algoname in algonames if algoname not in withticks] #withnoaxes.remove('GAP') loadshowmatrices_multipixels(filename, algonames, lambdas, threshs, withticks, withnoaxes, doshow, dosave, saveplotbase, saveplotexts) def loadshowmatrices_multipixels(filename, algonames, lambdas, threshs = [], withticks = [], withnoaxes = [], doshow=True, dosave=False, saveplotbase=None, saveplotexts=None): if dosave and (saveplotbase is None or saveplotexts is None): print('Error: please specify name and extensions for saving') raise Exception('Name or extensions for saving not specified') mdict = scipy.io.loadmat(filename) N = 10 # one data box = NxN for algonameobj in algonames: algoname = algonameobj[0][0] print algoname if mdict['meanmatrix'][algoname][0,0].ndim == 2: # Prepare bigger matrix rows,cols = mdict['meanmatrix'][algoname][0,0].shape bigmatrix = numpy.zeros((N*rows,N*cols)) for i in numpy.arange(rows): for j in numpy.arange(cols): bigmatrix[i*N:i*N+N,j*N:j*N+N] = mdict['meanmatrix'][algoname][0,0][i,j] for thrval,width,color in threshs: bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0],bigmatrix,N,thrval,width,color) #bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0],bigmatrix,10,0.95,2,0) #bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0],bigmatrix,10,0.8, 2,0.4) #bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0],bigmatrix,10,0.5, 2,1) # # Mark 95% border # if mdict['meanmatrix'][algoname][0,0][i,j] > thresh: # # Top border # if mdict['meanmatrix'][algoname][0,0][i-1,j] < thresh and i>0: # bigmatrix[i*N:i*N+border,j*N:j*N+N] = bordercolor # # Bottom border # if mdict['meanmatrix'][algoname][0,0][i+1,j] < thresh and i<rows-1: # bigmatrix[i*N+N-border:i*N+N,j*N:j*N+N] = bordercolor # # Left border # if mdict['meanmatrix'][algoname][0,0][i,j-1] < thresh and j>0: # bigmatrix[i*N:i*N+N,j*N:j*N+border] = bordercolor # # Right border (not very probable) # if j<cols-1 and mdict['meanmatrix'][algoname][0,0][i,j+1] < thresh: # bigmatrix[i*N:i*N+N,j*N+N-border:j*N+N] = bordercolor plt.figure() plt.imshow(bigmatrix, cmap=cm.gray, norm=mcolors.Normalize(0,1), interpolation='nearest',origin='lower') if algoname in withticks: int_setticks() if algoname in withnoaxes: plt.gca().get_xaxis().set_visible(False) plt.gca().get_yaxis().set_visible(False) if dosave: for ext in saveplotexts: plt.savefig(saveplotbase + algoname + '.' + ext, bbox_inches='tight') elif mdict['meanmatrix'][algoname][0,0].ndim == 3: if dosave: ilbd = 0 for matrix in mdict['meanmatrix'][algoname][0,0]: # Prepare bigger matrix rows,cols = matrix.shape bigmatrix = numpy.zeros((N*rows,N*cols)) for i in numpy.arange(rows): for j in numpy.arange(cols): bigmatrix[i*N:i*N+N,j*N:j*N+N] = matrix[i,j] for thrval,width,color in threshs: bigmatrix = int_drawseparation(mdict['meanmatrix'][algoname][0,0][ilbd],bigmatrix,N,thrval,width,color) #bigmatrix = int_drawseparation(matrix,bigmatrix,10,0.95,2,0) #bigmatrix = int_drawseparation(matrix,bigmatrix,10,0.8, 2,0.4) #bigmatrix = int_drawseparation(matrix,bigmatrix,10,0.5, 2,1) # # Mark 95% border # if matrix[i,j] > thresh: # # Top border # if matrix[i-1,j] < thresh and i>0: # bigmatrix[i*N:i*N+border,j*N:j*N+N] = bordercolor # # Bottom border # if matrix[i+1,j] < thresh and i<rows-1: # bigmatrix[i*N+N-border:i*N+N,j*N:j*N+N] = bordercolor # # Left border # if matrix[i,j-1] < thresh and j>0: # bigmatrix[i*N:i*N+N,j*N:j*N+border] = bordercolor # # Right border (not very probable) # if j<cols-1 and matrix[i,j+1] < thresh: # bigmatrix[i*N:i*N+N,j*N+N-border:j*N+N] = bordercolor plt.figure() #plt.imshow(matrix, cmap=cm.gray, interpolation='nearest',origin='lower') plt.imshow(bigmatrix, cmap=cm.gray, norm=mcolors.Normalize(0,1), interpolation='nearest',origin='lower') #plt.gca().get_xaxis().set_visible(False) #plt.gca().get_yaxis().set_visible(False) #int_setticks() if algoname in withticks: int_setticks() if algoname in withnoaxes: plt.gca().get_xaxis().set_visible(False) plt.gca().get_yaxis().set_visible(False) if dosave: for ext in saveplotexts: plt.savefig(saveplotbase + algoname + ('_lbd%.0e' % lambdas[ilbd]) + '.' + ext, bbox_inches='tight') ilbd = ilbd + 1 if doshow: plt.show() print "Finished." def appendtomatfile(filename, toappend, toappendname): mdict = scipy.io.loadmat(filename) mdict[toappendname] = toappend try: scipy.io.savemat(filename, mdict) except: print "Save error" # To save to a cell array, create an object array: # >>> obj_arr = np.zeros((2,), dtype=np.object) # >>> obj_arr[0] = 1 # >>> obj_arr[1] = 'a string' def int_drawseparation(matrix,bigmatrix,N,thresh,border,bordercolor): rows,cols = matrix.shape for i in numpy.arange(rows): for j in numpy.arange(cols): # Mark border # Use top-left corner of current square for reference if matrix[i,j] > thresh: # Top border if matrix[i-1,j] < thresh and i>0: bigmatrix[i*N:i*N+border,j*N:j*N+N] = bordercolor # Bottom border if i<rows-1 and matrix[i+1,j] < thresh: bigmatrix[i*N+N-border:i*N+N,j*N:j*N+N] = bordercolor # Left border if matrix[i,j-1] < thresh and j>0: bigmatrix[i*N:i*N+N,j*N:j*N+border] = bordercolor # Right border (not very probable) if j<cols-1 and matrix[i,j+1] < thresh: bigmatrix[i*N:i*N+N,j*N+N-border:j*N+N] = bordercolor return bigmatrix def int_setticks(): #ticks = [10, 94, 179] #ticklabels = ["0.05", "0.5", "0.95"] ticks = [10, 179] ticklabels = ["0.05", "0.95"] ax = plt.gca() ax.set_xticks(ticks) ax.set_xticklabels(ticklabels) ax.set_yticks(ticks) ax.set_yticklabels(ticklabels) for label in ax.get_xticklabels(): label.set_fontsize(42) for label in ax.get_yticklabels(): label.set_fontsize(42) ax.set_xlabel(r'$\delta$', size=60) ax.set_ylabel(r'$\rho$', size=60)