""" Created on 26 sep. 2011 @author: jhkwakkel """ import matplotlib.pyplot as plt from expWorkbench import load_results from analysis.graphs import envelopes data = load_results(r"../../../src/analysis/1000 flu cases.cPickle") fig = envelopes(data, column="policy") plt.savefig("basicEnvelope.png", dpi=75)
def perform_experiments(): logger = EMAlogging.log_to_stderr(level=EMAlogging.INFO) model = SalinizationModel(r"C:\eclipse\workspace\EMA-workbench\models\salinization", "verzilting") model.step = 4 ensemble = SimpleModelEnsemble() ensemble.set_model_structure(model) policies=[{'name': 'no policy', 'file': r'\verzilting 2.vpm'}, {'name': 'policy group 8', 'file': r'\group 8 best policy.vpm'}, {'name': 'policy other group', 'file': r'\other group best policy.vpm'}, {'name': 'policies combined', 'file': r'\best policies combined.vpm'} ] ensemble.add_policies(policies) ensemble.parallel = True nr_of_experiments = 1000 results = ensemble.perform_experiments(nr_of_experiments) return results if __name__ == "__main__": results = perform_experiments() fig = graphs.envelopes(results, column='policy') plt.show() save_results(results, 'salinization policys both groups.cPickle')
@author: jhkwakkel ''' import numpy as np import matplotlib.pyplot as plt from expWorkbench import load_results from analysis import prim from expWorkbench import EMAlogging from analysis.graphs import envelopes EMAlogging.log_to_stderr(EMAlogging.INFO) results = load_results(r'C:\workspace\EMA-workbench\models\TFSC_all_policies.cPickle') envelopes(results, column='policy', categories=['adaptive policy', 'ap with op']) #exp, res = results # ##get out only the results related to the last policy #exp, res = results # #logical = exp['policy'] == 'adaptive policy' #exp = exp[logical] # #temp_res = {} #for key, value in res.items(): # temp_res[key] = value[logical] #res = temp_res #
# if checkarray[i,-1]< 0.6: # count +=1 # # print count # envelopes(load_results(r'CESUN_4Policies_1000.cPickle'), outcomes=outcomes, # column = 'policy',categories=['no policy', # 'basic policy', # 'adaptive policy', # 'optimized adaptive'], # fill=True, categorieslabels= ['No Policy', 'Basic Policy', # 'Adaptive Policy', # 'Optimized Adaptive Policy']) # envelopes(results, outcomes=outcomes, column='policy', fill=True) plt.show() # import matplotlib # # matplotlib.rc('font', weight='bold') # matplotlib.rc('font', size=14) # # ## results = load_results(r'CESUN_optimized_1000.cPickle') ## # monitor1 = results[1]['monitor for Trigger subsidy T2'] # monitor2 = results[1]['monitor for Trigger subsidy T3'] # monitor3 = results[1]['monitor for Trigger subsidy T4'] # monitor4 = results[1]['monitor for Trigger addnewcom']
# count +=1 # # print count # envelopes(load_results(r'CESUN_4Policies_1000.cPickle'), outcomes=outcomes, # column = 'policy',categories=['no policy', # 'basic policy', # 'adaptive policy', # 'optimized adaptive'], # fill=True, categorieslabels= ['No Policy', 'Basic Policy', # 'Adaptive Policy', # 'Optimized Adaptive Policy']) # envelopes(results, outcomes=outcomes, column = 'policy', fill=True) plt.show() # import matplotlib # # matplotlib.rc('font', weight='bold') # matplotlib.rc('font', size=14) # # ## results = load_results(r'CESUN_optimized_1000.cPickle') ## # monitor1 = results[1]['monitor for Trigger subsidy T2'] # monitor2 = results[1]['monitor for Trigger subsidy T3'] # monitor3 = results[1]['monitor for Trigger subsidy T4'] # monitor4 = results[1]['monitor for Trigger addnewcom']
''' Created on 26 sep. 2011 @author: jhkwakkel ''' import matplotlib.pyplot as plt from expWorkbench import load_results from analysis.graphs import envelopes data = load_results(r'../../../src/analysis/1000 flu cases.cPickle') fig = envelopes(data, column='policy') plt.savefig("basicEnvelope.png", dpi=75)
''' Created on 7 Sep 2011 @author: chamarat ''' import matplotlib.pyplot as plt from expWorkbench import load_results from analysis.graphs import envelopes results = load_results(r'.\data\TFSC_policies.cPickle') fig = envelopes(results, column='policy', fill=True, legend=False) fig = plt.gcf() fig.set_size_inches(15,5) plt.savefig("policycomparison.png", dpi=75)
''' Created on 26 sep. 2011 @author: jhkwakkel ''' import matplotlib.pyplot as plt from expWorkbench import load_results from analysis.graphs import envelopes data = load_results(r'../../../src/analysis/1000 flu cases.cPickle') fig = envelopes(data, column='policy', categories=['static policy', 'adaptive policy']) plt.show()
''' Created on 7 Sep 2011 @author: chamarat ''' import matplotlib.pyplot as plt from expWorkbench import load_results from analysis.graphs import envelopes results = load_results(r'.\data\TFSC_policies.cPickle') fig = envelopes(results, column='policy', fill=True, legend=False) fig = plt.gcf() fig.set_size_inches(15, 5) plt.savefig("policycomparison.png", dpi=75)