def plot_results(frame, save=True, plot_prefix=None, dirname='./'):
# generate each type of plot
filter_join = lambda join_with, list: join_with.join(filter(None, list))
for vary_what in ['rows', 'cols', 'clusters', 'views']:
plot_filename = filter_join('_', [plot_prefix, 'vary', vary_what])
_plot_results(frame, vary_what, plot_filename)
if save:
pu.savefig_legend_outside(plot_filename, dir=dirname)
pass
pass
return
def plot_grouped_data(dict_of_dicts, plot_parameters, plot_filename=None):
get_color_parameter = plot_parameters['get_color_parameter']
color_dict = plot_parameters['color_dict']
color_label_prepend = plot_parameters['color_label_prepend']
timing_row_to_color = lambda timing_row: \
color_dict[get_color_parameter(timing_row)]
get_marker_parameter = plot_parameters['get_marker_parameter']
marker_dict = plot_parameters['marker_dict']
marker_label_prepend = plot_parameters['marker_label_prepend']
timing_row_to_marker = lambda timing_row: \
marker_dict[get_marker_parameter(timing_row)]
vary_what = plot_parameters['vary_what']
which_kernel = plot_parameters['which_kernel']
#
fh = pylab.figure()
for configuration, run_data in dict_of_dicts.iteritems():
x = sorted(run_data.keys())
_y = [run_data[el] for el in x]
y = map(get_time_per_step, _y)
#
plot_args = dict()
first_timing_row = run_data.values()[0]
color = timing_row_to_color(first_timing_row)
plot_args['color'] = color
marker = timing_row_to_marker(first_timing_row)
plot_args['marker'] = marker
label = str(configuration)
plot_args['label'] = label
#
pylab.plot(x, y, **plot_args)
#
pylab.xlabel('# %s' % vary_what)
pylab.ylabel('time per step (seconds)')
pylab.title('Timing analysis for kernel: %s' % which_kernel)
# pu.legend_outside(bbox_to_anchor=(0.5, -.1), ncol=4, label_cmp=label_cmp)
pu.legend_outside_from_dicts(marker_dict,
color_dict,
marker_label_prepend=marker_label_prepend,
color_label_prepend=color_label_prepend,
bbox_to_anchor=(0.5, -.1),
label_cmp=label_cmp)
if plot_filename is not None:
pu.savefig_legend_outside(plot_filename)
else:
pylab.ion()
pylab.show()
return fh
def plot_grouped_data(dict_of_dicts, plot_parameters, plot_filename=None):
get_color_parameter = plot_parameters['get_color_parameter']
color_dict = plot_parameters['color_dict']
color_label_prepend = plot_parameters['color_label_prepend']
timing_row_to_color = lambda timing_row: \
color_dict[get_color_parameter(timing_row)]
get_marker_parameter = plot_parameters['get_marker_parameter']
marker_dict = plot_parameters['marker_dict']
marker_label_prepend = plot_parameters['marker_label_prepend']
timing_row_to_marker = lambda timing_row: \
marker_dict[get_marker_parameter(timing_row)]
vary_what = plot_parameters['vary_what']
which_kernel = plot_parameters['which_kernel']
#
fh = pylab.figure()
for configuration, run_data in dict_of_dicts.iteritems():
x = sorted(run_data.keys())
_y = [run_data[el] for el in x]
y = map(get_time_per_step, _y)
#
plot_args = dict()
first_timing_row = run_data.values()[0]
color = timing_row_to_color(first_timing_row)
plot_args['color'] = color
marker = timing_row_to_marker(first_timing_row)
plot_args['marker'] = marker
label = str(configuration)
plot_args['label'] = label
#
pylab.plot(x, y, **plot_args)
#
pylab.xlabel('# %s' % vary_what)
pylab.ylabel('time per step (seconds)')
pylab.title('Timing analysis for kernel: %s' % which_kernel)
# pu.legend_outside(bbox_to_anchor=(0.5, -.1), ncol=4, label_cmp=label_cmp)
pu.legend_outside_from_dicts(marker_dict, color_dict,
marker_label_prepend=marker_label_prepend, color_label_prepend=color_label_prepend,
bbox_to_anchor=(0.5, -.1), label_cmp=label_cmp)
if plot_filename is not None:
pu.savefig_legend_outside(plot_filename)
else:
pylab.ion()
pylab.show()
return fh
