示例#1
0
#    print s_without.percentile(survivals, 0.5)
#except: pass


s= Simulator(iters=50000, age=age, ca125=True, model=Model)
s.run()

s.clear_survival_curves()

s.add_survival_curve(start_states=[S_Start], 
                        end_states=[S_DeadCancer, S_DeadChemo])

s.add_survival_curve(start_states=[S_Start], 
                        end_states=[S_DeadAge])

s.draw_survival_curves(name="crossing_curves.png")



#s.draw_histograms({
#    "Quality Years" : 
#       lambda pt: int(CostEvaluator.EvaluatePatient(pt)['quality']),
#    "Cost" : 
#        lambda pt: int(CostEvaluator.EvaluatePatient(pt)['cost']),
#    "Rounds of Chemo" : 
#        lambda pt: math.ceil(pt.ChemoCount())
#    }, names=["quality_years", "cost", "rounds"]
#    )
#
示例#2
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from  Simulator import Simulator
from States import S_Start, S_DeadCancer, S_DeadAge, S_DeadChemo
from numpy import average
import ConundrumModel as Model

s= Simulator(iters=10000, age=60, ca125=True, model=Model)
s.run()
print average([len(p.states) for p in s.patients])


s.clear_survival_curves()

s.add_survival_curve(start_states=[S_Start], 
                        end_states=[S_DeadCancer])

s.add_survival_curve(start_states=[S_Start], 
                        end_states=[S_DeadChemo])

s.add_survival_curve(start_states=[S_Start], 
                        end_states=[S_DeadAge])

s.draw_survival_curves(name="conundrum.png")
示例#3
0
from  Simulator import Simulator
from States import S_Start, S_DeadAge 

import HW1_model as Model

for time_increment in [1.0, 1./12, 1./52, 1./365]:
    s= Simulator(iters=5000, age=60, model=Model, time_increment = 1.0 / 52)
    s.run()
    
    
    s.clear_survival_curves()
    
    s.add_survival_curve(start_states=[S_Start], 
                            end_states=[S_DeadAge])
    
    s.draw_survival_curves(name="Survival_HW_1.%s"%time_increment)