def make_plot_RMACCURACYFM(self):
# This graph shows the time spent training vs. the data set size
exp_no = RMACCURACYFM
plot_dir = OUTPUT_DIR + "rm_accuracyfm/"
os.mkdir(plot_dir)
gnuplot_script = open(plot_dir + 'plot.gp', 'w')
print >> gnuplot_script, """
set terminal png nocrop enhanced size 400, 400
set output "plot.png"
set xlabel "Granularity"
set ylabel "Median Error"
set nokey
set title "Reverse Mapping Accuracy vs. FM (%s)"
""" % self._exp.name
mi = int(numpy.floor(2 * self._exp.rm_granularities[0] - self._exp.rm_granularities[1]))
ma = int(numpy.ceil(2 * self._exp.rm_granularities[-1] - self._exp.rm_granularities[-2]))
print >> gnuplot_script, "set xrange [%d:%d]" % (mi, ma)
print >> gnuplot_script, 'plot "rm_times" with errorbars, "rm_times" with lines',
print >> gnuplot_script, '\n',
gnuplot_script.close()
out_file = open(plot_dir + "rm_times", 'w')
for gran in self._exp.rm_granularities:
times = self._rm_results[gran][exp_no]
avg, lower, upper = misc.doublesided( abs(x[0]) for x in times ) # FIXME : only works for 1 parameter!
print >> out_file, "%d %f %f %f" % (gran, avg, lower, upper)
out_file.close()
curdir = os.path.abspath('.')
os.chdir(plot_dir)
os.system('gnuplot ' +'plot.gp')
os.chdir(curdir)
def make_plot_FMACCURACY(self):
# This graph shows the time spent training vs. the data set size
# THIS ONLY DOES ONE SLP RIGHT NOW!!! (for fires!) TODO FIXME
exp_no = FMACCURACY
plot_dir = OUTPUT_DIR + "fm_accuracy/"
os.mkdir(plot_dir)
# gotta find the max deviation seen, ever, so that I can make all the
# graphs have the same y-scale
maerr = 0.0
for reg, params in self._exp.regressions:
label = labelize(reg, params)
for training_size in self._exp.training_sizes:
key = (label, training_size)
maxerror = max([ abs(x) for x in self._fm_results[key][exp_no]]) # FIXME
maerr = max(maerr, maxerror)
for reg, params in self._exp.regressions:
label = labelize(reg, params)
gnuplot_script = open(plot_dir + 'plot-%s.gp' % reg.name, 'w')
print >> gnuplot_script, """
set terminal png nocrop enhanced size 400, 400
set output "plot-%s.png"
set xlabel "Data Set Size"
set ylabel "Median Error"
set key top right
set title "Forward Mapping Accuracy (%s)"
""" % (reg.name, self._exp.name)
mi = int(numpy.floor(2 * self._exp.training_sizes[0] - self._exp.training_sizes[1]))
ma = int(numpy.ceil(2 * self._exp.training_sizes[-1] - self._exp.training_sizes[-2]))
print >> gnuplot_script, "set xrange [%d:%d]" % (mi, ma)
print >> gnuplot_script, "set yrange [0:%.4f]" % (maerr * 1.1 * MAGIC_YSCALE_FM_ACCURACY)
print >> gnuplot_script, 'plot ',
out_file = open(plot_dir + "%s" % reg.name, 'w')
print >> gnuplot_script, '"%s" with errorbars' % reg.name,
for training_size in self._exp.training_sizes:
key = (label, training_size)
# this is the list of deviations
errors = [ abs(x) for x in self._fm_results[key][exp_no]] # FIXME
# average them
median, lower, upper = misc.doublesided(errors)
print >> out_file, "%d %f %f %f" % (training_size, median, lower, upper)
out_file.close()
print >> gnuplot_script, '\n',
gnuplot_script.close()
curdir = os.path.abspath('.')
os.chdir(plot_dir)
os.system('gnuplot ' + 'plot-%s.gp' % reg.name)
os.chdir(curdir)
