def plot_all_envelopes(results, outcomes, grouped, save, title):
if grouped == True:
for kpi in list(outcomes.keys())[1:]: # drop first entry (TIME)
fig, axes = envelopes(results,
density=u'kde',
outcomes_to_show=kpi,
group_by='policy',
fill=True)
if save == True:
plt.savefig('plots/scenario_basecase/' +
time.strftime('%Y%m%d') + title +
'_lines_grouped_' + kpi + '.png',
dpi=1200)
else:
print(kpi + ' was not saved')
else:
for kpi in list(outcomes.keys())[1:]: # drop first entry (TIME)
fig, axes = envelopes(results,
density=u'kde',
outcomes_to_show=kpi,
fill=True)
if save == True:
plt.savefig('plots/scenario_policies/' +
time.strftime('%Y%m%d') + title + '_lines_' + kpi +
'.png',
dpi=1200)
else:
print(kpi + ' was not saved')
def plot_individual_policies_envelopes(experiments, outcomes, policy,
outcomes_to_show):
'''Plot individual policy experiment sets'''
sliced_result = slice_results(experiments, outcomes, policy)
ig, axes = envelopes(sliced_result,
outcomes_to_show=outcomes_to_show,
fill=True,
group_by=False,
density=KDE)
print('Plot of policy: ', policy)
''' Created on Jul 8, 2014 @author: [email protected] ''' import matplotlib.pyplot as plt from ema_workbench.util import ema_logging, load_results from ema_workbench.analysis.plotting import envelopes from ema_workbench.analysis.plotting_util import KDE ema_logging.log_to_stderr(ema_logging.INFO) file_name = r'./data/1000 flu cases.tar.gz' results = load_results(file_name) # the plotting functions return the figure and a dict of axes fig, axes = envelopes(results, group_by='policy', density=KDE, fill=True) # we can access each of the axes and make changes for key, value in axes.iteritems(): # the key is the name of the outcome for the normal plot # and the name plus '_density' for the endstate distribution if key.endswith('_density'): value.set_xscale('log') plt.show()
show_envelope=True,
experiments_to_show=indices)
#n = key
#plt.savefig("./pictures/adopter_category_bounded_no.png".format(key), dpi=75)
plt.show()
print(outcome)
#print(results)
#print(results)
# the plotting functions return the figure and a dict of axes
fig, axes = envelopes(results, group_by='policy', density=KDE, fill=True)
# we can access each of the axes and make changes
for key, value in axes.iteritems():
# the key is the name of the outcome for the normal plot
# and the name plus '_density' for the endstate distribution
if key.endswith('_density'):
value.set_xscale('log')
plt.show()
''' Created on Jul 8, 2014 @author: [email protected] ''' import matplotlib.pyplot as plt from ema_workbench import ema_logging, load_results from ema_workbench.analysis.plotting import envelopes from ema_workbench.analysis.plotting_util import KDE ema_logging.log_to_stderr(ema_logging.INFO) file_name = r'./data/1000 flu cases with policies.tar.gz' experiments, outcomes = load_results(file_name) # the plotting functions return the figure and a dict of axes fig, axes = envelopes(experiments, outcomes, group_by='policy', density=KDE, fill=True) # we can access each of the axes and make changes for key, value in axes.items(): # the key is the name of the outcome for the normal plot # and the name plus '_density' for the endstate distribution if key.endswith('_density'): value.set_xscale('log') plt.show()