Hello!
I have been using Optseq to help optimize my task design and recently have decided to give RSFgen a try. I think I have taken the correct initial steps but I now have a folder full of hundreds of files and am unclear as to what the next step is and how to obtain a single stimulus timing file that I could use to program my task. Here is what I ran:
#!/bin/tcsh
# try to find reasonable random event related timing given the experimental
# parameters
# ---------------------------------------------------------------------------
# some experiment parameters (most can be inserted directly into the
# make_random_timing.py command)
set num_stim = 7
set num_runs = 2
set pre_rest = 10 # min rest before first stim (for magnet steady state)
set post_rest = 10 # min rest after last stim (for trailing BOLD response)
set min_rest = 0 # minimum rest after each stimulus
set tr = 2.5 # used in 3dDeconvolve, if not make_random_timing.py
# (options that take multiple values can also take just one if they are
# all the same, such as with this example)
#
# set stim_durs = "3.5 3.5 3.5 3.5 3.5 3.5 3.5"
# set stim_reps = "10 10 10 10 10 5 5"
# set run_lengths = "300 300 300"
set stim_durs = "3.5 3.5 3.5 3.5 3.5 3.5 3.5"
set stim_reps = "10 10 10 10 10 5 5"
set run_lengths = 250
set labels = "M_Neutral E_Neutral E_Fear E_Anger Pain M_Fear M_Anger"
# ---------------------------------------------------------------------------
# execution parameters
set iterations = 100 # number of iterations to compare
set seed = 1234567 # initial random seed
set outdir = stim_results # directory that all results are under
set LCfile = NSD_sums # file to store norm. std. dev. sums in
# set pattern = LC # search pattern for LC[0], say
set pattern = 'norm. std.' # search pattern for normalized stdev vals
# ===========================================================================
# start the work
# ===========================================================================
# ------------------------------------------------------------
# recreate $outdir each time
if ( -d $outdir ) then
echo "** removing output directory, $outdir ..."
\rm -fr $outdir
endif
echo "++ creating output directory, $outdir ..."
mkdir $outdir
if ( $status ) then
echo "failure, cannot create output directory, $outdir"
exit
endif
# move into the output directory and begin work
cd $outdir
# create empty LC file
echo -n "" > $LCfile
echo -n "iteration (of $iterations): 0000"
# ------------------------------------------------------------
# run the test many times
foreach iter (`count -digits 4 1 $iterations`)
# make some other random seed
@ seed = $seed + 1
# create randomly ordered stimulus timing files
# (consider: -tr_locked -save_3dd_cmd tempfile)
make_random_timing.py -num_stim $num_stim -stim_dur $stim_durs \
-num_runs $num_runs -run_time $run_lengths \
-num_reps $stim_reps -prefix stimes.$iter \
-pre_stim_rest $pre_rest -post_stim_rest $post_rest \
-min_rest $min_rest \
-stim_labels $labels \
-seed $seed \
-tr $tr \
-show_timing_stats \
-save_3dd_cmd cmd.3dd.$iter \
>& out.mrt.$iter
# consider: sed 's/GAM/"TENT(0,15,7)"/' tempfile > cmd.3dd.$iter
# rm -f tempfile
# now evaluate the stimulus timings
tcsh cmd.3dd.$iter >& out.3dD.$iter
# save the sum of the 3 LC values
set nums = ( `awk -F= '/'"$pattern"'/ {print $2}' out.3dD.${iter}` )
# make a quick ccalc command
set sstr = $nums[1]
foreach num ( $nums[2-] )
set sstr = "$sstr + $num"
end
set num_sum = `ccalc -expr "$sstr"`
echo -n "$num_sum = $sstr : " >> $LCfile
echo "iteration $iter, seed $seed" >> $LCfile
echo -n "\b\b\b\b$iter"
end
echo ""
echo "done, results are in '$outdir', LC sums are in '$LCfile'"
echo consider the command: "sort -n $outdir/$LCfile | head -1"
# note that if iter 042 seems to be the best, consider these commands:
#
# cd stim_results
# set iter = 042
# timing_tool.py -multi_timing stimes.${iter}_0* \
# -run_len $run_lengths -multi_stim_dur $stim_durs \
# -multi_show_isi_stats
# tcsh cmd.3dd.$iter
# 1dplot X.xmat.1D'[6..$]'
# 1dplot sum_ideal.1D
#
# - timing_tool.py will give useful statistics regarding ISI durations
# (should be similar to what is seen in output file out.mrt.042)
# - run cmd.3dd.$iter to regenerate that X martix (to create actual regressors)
# - the first 1dplot command will show the actual regressors
# (note that 6 = 2*$num_runs)
# - the second will plot the sum of the regressor (an integrity check)
# (note that sum_ideal.1D is produced by cmd.3dd.$iter, along with X.xmat.1D)
Thanks for your help!!
