#!/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)

# ---------------------------------------------------------------------------
# execution parameters
set iterations  = 10            # 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_runs 4 -run_time 690 \
        -tr 2                                   \
        -pre_stim_rest 0 -post_stim_rest 10     \
        -rand_post_stim_rest no                 \
        -add_timing_class stim 12               \
        -add_timing_class tnull 10              \
        -add_timing_class rest 0.5 1.5 4 dist=decay_fixed \
        -add_stim_class NMA 10 stim rest        \
        -add_stim_class NMS 10 stim rest        \
        -add_stim_class HMA 10 stim rest        \
        -add_stim_class HMS 10 stim rest        \
        -add_stim_class NULL 14 tnull INSTANT   \
        -prefix threat_app.$iter                \
      #                                         \
      # might not need to edit below here...    \
        -write_event_list events.$iter.txt      \
        -show_timing_stats                      \
        -seed $seed                             \
        -save_3dd_cmd cmd.3dd.$iter.txt >& 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.$iter.txt >& out.3dD.$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)