"""
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 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)
