for a in 3000 4000 6000 12000 24000 120000; do
export b=`cat snn.train.$a`
echo $a `/home/jl/programs/ocaml/PAC_bounds/compare_gauss -L 0.25 -L 1 -m 100 -d 25 -delta 0.1 -weight_n_var forjcl.0.03.${a}.1 -margins margin.0.03.${a}.1 -measure_count 1000 -measured_err $b | grep complexity | cut -d ' ' -f 3`
done > pb_complexity

for a in 3000 4000 6000 12000 24000 120000; do
export b=`cat snn.train.$a`
echo $a `/home/jl/programs/ocaml/PAC_bounds/compare_gauss -L 0.25 -L 1 -m 100 -d 25 -delta 0.1 -weight_n_var forjcl.0.03.${a}.1 -margins margin.0.03.${a}.1 -measure_count 1000 -measured_err $b | grep "PAC-Bayes bound" | cut -d ' ' -f 3`
done > pb_bound

for a in 3000 4000 6000 12000 24000 120000; do
export b=`cat snn.train.$a`
echo $a `/home/jl/programs/ocaml/PAC_bounds/compare_gauss -L 0.25 -L 1 -m 100 -d 25 -delta 0.1 -weight_n_var forjcl.0.03.${a}.1 -margins margin.0.03.${a}.1 -measure_count 1000 -measured_err $b | grep "anchenko" | cut -d ' ' -f 3`
done > panchenko_bound

for a in 3000 4000 6000 12000 24000 120000; do
export b=`cat snn.train.$a`
echo $a `/home/jl/programs/ocaml/PAC_bounds/compare_gauss -L 0.25 -L 1 -m 100 -d 25 -delta 0.1 -weight_n_var forjcl.0.03.${a}.1 -margins margin.0.03.${a}.1 -measure_count 1000 -measured_err $b | grep "empirical" | cut -d '=' -f 2`
done > train_error

gnuplot plot
gnuplot plot_complexity