#getting output prefix
prefix = prefixes[m]
m += 1
#saving the feature matrix and labels in a binary file
#setting output file name
ofname = features_str()
if prefix:
ofname = prefix + '_' + ofname
if scale:
ofname = ofname + '.' + scaled_str()
if excluf:
excl_ofname = au.excluded_str() + au.feats_str()
if prefix:
excl_ofname = prefix + '_' + excl_ofname
if scale:
excl_ofname = excl_ofname + '.' + au.scaled_str()
filename = get_filepath(outdir, ofname, otype)
if os.path.exists(filename):
print(filename + ' already exists. Jumping to the next.')
else:
print('Creating ' + filename)
#reading mask volume
if not os.path.exists(maskf):
err = 'Mask file not found: ' + maskf
raise IOError(err)
def save_data (outdir, prefix, dataname, otype, excluding, leave, feats, labels, exclfeats, exclulabels, dmin, dmax, scale, scale_min, scale_max, lthr, uthr, thrp, absolute):
#setting output file name
ofname = au.feats_str()
if leave > -1:
ofname += '.' + au.excluded_str() + str(leave)
if absolute: ofname += '.' + au.abs_str()
if lthr: ofname += '.lthr_' + str(lthr)
if uthr: ofname += '.uthr_' + str(uthr)
if thrp: ofname += '.thrP_' + str(thrp)
if scale: ofname += '.' + au.scaled_str()
if excluding:
excl_ofname = au.excluded_str() + '_' + ofname
exclfilename = get_filepath (outdir, excl_ofname , otype)
if prefix:
ofname = prefix + '_' + ofname
excl_ofname = prefix + '_' + excl_ofname
filename = get_filepath (outdir, ofname, otype)
#writing in a text file the scaling values of this training set
if scale:
write_scalingrange_file (outdir + os.path.sep + ofname + '.scaling_range', dmin, dmax, scale_min, scale_max)
#saving binary file depending on output type
if otype == 'numpybin':
np.save (filename, feats)
if excluding:
np.save (exclfilename, exclfeats)
elif otype == 'octave':
sio.savemat (filename, {au.feats_str(): feats, au.labels_str(): labels})
if excluding:
exclulabels[exclulabels == 0] = -1
sio.savemat (exclfilename, {au.feats_str(): exclfeats, au.labels_str(): exclulabels})
elif otype == 'svmperf':
labels[labels == 0] = -1
ae.write_svmperf_dat(filename, dataname, feats, labels)
if excluding:
exclulabels[exclulabels == 0] = -1
ae.write_svmperf_dat(exclfilename, dataname, exclfeats, exclulabels)
elif otype == 'arff':
featnames = np.arange(nfeats) + 1
ae.write_arff (filename, dataname, featnames, feats, labels)
if excluding:
ae.write_arff (exclfilename, dataname, featnames, exclfeats, exclulabels)
else:
err = 'Output method not recognised!'
au.log.error(err)
sys.exit(-1)
return [filename, exclfilename]
fmt='%s')
np.savetxt(outdir + os.path.sep + au.excluded_subjlabels_str(),
exclulabels,
fmt='%i')
#saving the feature matrix and labels in a binary file
filename = set_filename(outdir, prefix + '_' + au.features_str(), otype)
print('Creating ' + filename)
if otype == 'numpybin':
np.save(filename, feats)
elif otype == 'octave':
sio.savemat(filename, {au.feats_str(): feats, au.labels_str(): labels})
elif otype == 'svmperf':
labels[labels == 0] = -1
ae.write_svmperf_dat(filename, dataname, feats, labels)
if excluf:
exclulabels[exclulabels == 0] = -1
exclfilename = set_filename(
outdir, prefix + '_' + au.excluded_str() + au.feats_str(),
otype)
ae.write_svmperf_dat(exclfilename, dataname, exclfeats,
exclulabels)
elif otype == 'arff':
featnames = np.arange(nfeats) + 1
ae.write_arff(filename, dataname, featnames, feats, labels)
# getting output prefix
prefix = prefixes[m]
m += 1
# saving the feature matrix and labels in a binary file
# setting output file name
ofname = features_str()
if prefix:
ofname = prefix + "_" + ofname
if scale:
ofname = ofname + "." + scaled_str()
if excluf:
excl_ofname = au.excluded_str() + au.feats_str()
if prefix:
excl_ofname = prefix + "_" + excl_ofname
if scale:
excl_ofname = excl_ofname + "." + au.scaled_str()
filename = get_filepath(outdir, ofname, otype)
if os.path.exists(filename):
print(filename + " already exists. Jumping to the next.")
else:
print("Creating " + filename)
# reading mask volume
if not os.path.exists(maskf):
err = "Mask file not found: " + maskf
raise IOError(err)
if excluf:
np.savetxt(outdir + os.path.sep + au.excluded_subjects_str(), exclusubjs, fmt='%s')
np.savetxt(outdir + os.path.sep + au.excluded_subjlabels_str(), exclulabels, fmt='%i')
#saving the feature matrix and labels in a binary file
filename = set_filename (outdir, prefix + '_' + au.features_str(), otype)
print ('Creating ' + filename)
if otype == 'numpybin':
np.save (filename, feats)
elif otype == 'octave':
sio.savemat (filename, {au.feats_str(): feats, au.labels_str(): labels})
elif otype == 'svmperf':
labels[labels == 0] = -1
ae.write_svmperf_dat(filename, dataname, feats, labels)
if excluf:
exclulabels[exclulabels == 0] = -1
exclfilename = set_filename(outdir, prefix + '_' + au.excluded_str() + au.feats_str(), otype)
ae.write_svmperf_dat(exclfilename, dataname, exclfeats, exclulabels)
elif otype == 'arff':
featnames = np.arange(nfeats) + 1
ae.write_arff (filename, dataname, featnames, feats, labels)
else:
err = 'Output method not recognised!'
