def write_uber_command(self):
if show_func_seq: print('=== R ===') # rcr - not called
pdir = self.ttobj.cvars.val('proc_dir')
if os.path.isdir(pdir):
sstr = self.make_uber_command()
UTIL.write_text_to_file('%s/.orig.cmd.utt' % pdir, sstr)
def write_script(self, fname=''):
"""write processing script to a file (in the proc_dir)
- if fname is set, use it, else generate
- set rvars.file_proc and output_proc
"""
if not self.script:
print('** no script to write out')
return 1
if fname: name = fname
else: name = 'script.ttest'
# store (intended) names for calling tool to execute with
self.rvars.file_proc = name # store which file we have written to
self.rvars.output_proc = 'output.%s' % name # file for command output
if self.cvars.verb > 0: print('++ writing script to %s' % name)
# if requested, make an original copy
self.LV.retdir = SUBJ.goto_proc_dir(self.cvars.proc_dir)
if self.cvars.copy_scripts == 'yes': # make an orig copy
UTIL.write_text_to_file('.orig.%s'%name, self.script, exe=1)
rv = UTIL.write_text_to_file(name, self.script, exe=1)
self.LV.retdir = SUBJ.ret_from_proc_dir(self.LV.retdir)
return rv
def make_decon_script_old(self):
"""OLD METHOD: create the deconvolution (3dTfitter) script"""
cmd = '# ------------------------------------------------------\n' \
'# perform neuro deconvolution via 3dTfitter\n\n'
cmd += "# create response kernel\n" \
"waver -%s -peak 1 -dt %s -inline 1@1 > %s\n\n" % \
(self.kernel, self.tr, self.kfile)
if self.aname.type == '1D': prefix = 'detrend.1D'
else: prefix = 'detrend%s' % self.aname.view
polort = UTIL.get_default_polort(self.tr, self.reps)
cmd += '# detrend the input\n' \
'3dDetrend -polort %d -prefix %s %s\n\n' % \
(polort,prefix,self.infiles[0])
if self.maskset: mask = ' -mask %s \\\n' % self.maskset
else: mask = ''
if self.aname.type == '1D':
cmd += '# transpose the detrended dataset\n' \
'1dtranspose detrend.1D > detrend_tr.1D\n\n'
dname = 'detrend_tr.1D'
else:
dname = 'detrend%s' % self.aname.view
c2 = '3dTfitter -lsqfit -RHS %s \\\n' \
'%s' \
' -FALTUNG %s %s \\\n' \
' 01 0.0\n\n' % (dname,mask,self.kfile,self.prefix)
cmd += UTIL.add_line_wrappers(c2)
return UTIL.write_text_to_file(self.script, cmd, exe=1)
3dBrickStat -mask $mask -percentile $bot $step 100 -non-zero \\
$pre.abs+tlrc > $pre.abs.1D
# have percentile p-values, remove unwanted percentile rankings
1dcat $pre.abs.1D'[1..$(2)]' > $pre.at.1D
# transpose and convert t to p
1deval -a $pre.at.1D\\' -expr "fitt_t2p(a,$dof)" > $pre.p.1D
# convert p to q (** note: the minimum is not applied, we do not want it)
1deval -a $pre.p.1D -expr "a*$nv/($nv-t)" > $pre.q.1D
# put both together in output file
1dcat $pre.p.1D $pre.q.1D > $output
# ----------------------------------------
# nuke temporary files (comment out to keep)
rm -f $pre.*
"""
ss += static_script
# and write output
U.write_text_to_file(outfile, ss)
try:
os.chmod(outfile, 0o755)
except OSError as e:
print(e)
def write_uber_command(self):
pdir = self.atest.cvars.val('proc_dir')
if os.path.isdir(pdir):
sstr = self.make_uber_command()
UTIL.write_text_to_file('%s/.orig.cmd.uat' % pdir, sstr)
def make_decon_script(self):
"""create the deconvolution (3dTfitter) script"""
nups = '%02d' % self.tr_nup
trup = self.tr / self.tr_nup
penalty = '012'
kernel = self.kernel
kfile = self.kfile
# todo: include run lengths
# maybe call the 3D version
if self.aname.type != '1D': return self.make_decon_script_3d()
cmd = '# ------------------------------------------------------\n' \
'# perform neuro deconvolution via 3dTfitter\n\n'
cmd += '# make and copy files into output directory\n' \
'set outdir = %s\n' \
'if ( ! -d $outdir ) mkdir $outdir\n\n' % self.outdir
# get a list of (hopefully shortened) file labels
llist = UTIL.list_minus_glob_form(self.infiles)
llen = len(self.infiles)
fix = 0
if len(llist) != llen: fix = 1
else:
if llist[0] == self.infiles[0]: fix = 1
if fix: llist = ['%02d.ts' % (ind + 1) for ind in range(llen)]
else:
llist = ['%02d.%s' % (ind + 1, llist[ind]) for ind in range(llen)]
# when copying file in, use 1dtranspose if they are horizontal
adata = LD.AfniData(self.infiles[0], verb=self.verb)
if not adata: return 1
# rcr - in progress? unused: adata, nt, transp
if adata.nrows == 1:
nt = adata.ncols * self.tr_nup
trstr = '(no transpose on read)'
trchr = ''
else:
nt = adata.nrows * self.tr_nup
transp = 1
trstr = '(transpose on read)'
trchr = '\\\''
cmd += 'set files = ( %s )\n' \
'set labels = ( %s )\n\n' \
'cp -pv $files $outdir\n' \
'cd $outdir\n\n' \
% (' '.join(self.infiles), ' '.join(llist))
if self.kfile_in: kfile = self.kfile_in
else:
# generate a response kernel using 3dDeconvolve
if kernel == 'GAM': ntk = int(12 / trup + 0.5)
elif kernel == 'BLOCK': ntk = int(15 / trup + 0.5)
else:
print('** only GAM/BLOCK basis functions are allowed now')
return 1
if kernel == 'BLOCK': kernel = 'BLOCK(0.1,1)'
tmpc = '# create response kernel\n' \
'3dDeconvolve -nodata %d %g -polort -1 \\\n' \
' -num_stimts 1 -stim_times 1 "1D:0" "%s" \\\n' \
' -x1D %s -x1D_stop\n\n' % (ntk, trup, kernel, kfile)
cmd += UTIL.add_line_wrappers(tmpc)
pind = 0
cmd += '# process each input file\n' \
'foreach findex ( `count -digits 2 1 $#files` )\n' \
' # no zero-padding in shell index\n' \
' set ival = `ccalc -i $findex`\n' \
' set infile = $files[$ival]:t\n' \
' set label = $labels[$ival]\n\n' \
polort = UTIL.get_default_polort(self.tr, self.reps)
olab = 'p%02d.det.$label.1D' % pind
cmd += ' # detrend the input %s\n' \
' 3dDetrend -polort %d -prefix %s $infile%s\n\n' \
% (trstr, polort, olab, trchr)
pind += 1
ilab = olab
olab = 'p%02d.det.tr.$label.1D' % pind
cmd += ' # transpose the detrended dataset\n' \
' 1dtranspose %s > %s\n\n' % (ilab, olab)
pind += 1
ilab = olab
olab = 'p%02d.up%s.$label.1D' % (pind, nups)
cmd += ' # upsample by factor of %d\n' \
' 1dUpsample %d %s > %s\n\n' \
% (self.tr_nup, self.tr_nup, ilab, olab)
sfile_up = olab # save original detrended upsample label
pind += 1
ilab = olab
olab = 'p%02d.neuro.up%s.$label.1D' % (pind, nups)
tmpc = ' 3dTfitter -RHS %s \\\n' \
' -FALTUNG %s %s \\\n' \
' 012 -2 -l2lasso -6\n\n' % (ilab,kfile,olab)
cmd += UTIL.add_line_wrappers(tmpc)
pind += 1
ilab = olab
olab = 'p%02d.neuro.up%s.tr.$label.1D' % (pind, nups)
cmd += ' # transpose the neuro signal\n' \
' 1dtranspose %s > %s\n\n' % (ilab, olab)
pind += 1
ilab = olab
olab = 'p%02d.reconv.up%s.tr.$label.1D' % (pind, nups)
cmd += ' # reconvolve the neuro signal to compare with orig\n'\
' set nt = `cat %s | wc -l`\n' \
' waver -FILE %g %s -input %s \\\n' \
' -numout $nt > %s\n\n' \
% (ilab, trup, kfile, ilab, olab)
rfile_up = olab # save reconvolved label
cmd += 'end\n\n\n'
cmd += 'echo "compare upsample input to reconvolved result via:"\n' \
'echo "set label = %s"\n' \
'echo "1dplot -one %s %s"\n\n' \
% (llist[0], sfile_up, rfile_up)
return UTIL.write_text_to_file(self.script, cmd, exe=1)