if foldno:
mdir += '_' + foldno
#setting the stats folder
statsdir = outdir + os.path.sep + au.stats_str()
if expname:
statsdir += '_' + expname
if foldno:
statsdir += '_' + foldno
#setting a string with step parameters
step_params = ' ' + measure_fname + ' ' + mdir
absolute_str = ''
if absval:
absolute_str = ' ' + au.abs_str()
step_params += absolute_str
leave_str = ''
if leave > -1:
leave_str = ' excluding subject ' + str(leave)
step_params += leave_str
#checking if this measure has already been done
endstep = au.measure_str() + step_params
stepdone = au.is_done(chkf, endstep)
#add pluses to output dir if it already exists
if stepdone:
while os.path.exists(mdir):
mdir += '+'
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]
mdir += '_' + foldno
#setting the stats folder
statsdir = outdir + os.path.sep + au.stats_str()
if expname:
statsdir += '_' + expname
if foldno:
statsdir += '_' + foldno
#setting a string with step parameters
step_params = ' ' + measure_fname + ' ' + mdir
absolute_str = ''
if absval:
absolute_str = ' ' + au.abs_str()
step_params += absolute_str
leave_str = ''
if leave > -1:
leave_str = ' excluding subject ' + str(leave)
step_params += leave_str
#checking if this measure has already been done
endstep = au.measure_str() + step_params
stepdone = au.is_done(chkf, endstep)
#add pluses to output dir if it already exists
if stepdone:
while os.path.exists (mdir):
mdir += '+'
