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()