def extract_outcomes(self, simulated_patients):
""" extracts outcomes of a simulated cohort
:param simulated_patients: a list of simulated patients"""
# record patient outcomes
for patient in simulated_patients:
# survival time
if patient.stateMonitor.survivalTime is not None:
self.survivalTimes.append(patient.stateMonitor.survivalTime)
# time until AIDS
if patient.stateMonitor.timeToAIDS is not None:
self.timesToAIDS.append(patient.stateMonitor.timeToAIDS)
# discounted cost and discounted utility
self.costs.append(
patient.stateMonitor.costUtilityMonitor.totalDiscountedCost)
self.utilities.append(
patient.stateMonitor.costUtilityMonitor.totalDiscountedUtility)
# summary statistics
self.statSurvivalTime = Stat.SummaryStat(name='Survival time',
data=self.survivalTimes)
self.statTimeToAIDS = Stat.SummaryStat(name='Time until AIDS',
data=self.timesToAIDS)
self.statCost = Stat.SummaryStat(name='Discounted cost',
data=self.costs)
self.statUtility = Stat.SummaryStat(name='Discounted utility',
data=self.utilities)
# survival curve
self.nLivingPatients = Path.PrevalencePathBatchUpdate(
name='# of living patients',
initial_size=len(simulated_patients),
times_of_changes=self.survivalTimes,
increments=[-1] * len(self.survivalTimes))
def calculate_cohort_outcomes(self, initial_pop_size):
""" calculates the cohort outcomes
:param initial_pop_size: initial population size
"""
self.statSurvivalTime = Stat.SummaryStat(name='Survival Time',
data=self.survivalTimes)
self.statCost = Stat.SummaryStat(name='Discounted cost',
data=self.costs)
self.statUtility = Stat.SummaryStat(name='Discounted utility',
data=self.utilities)
self.statNumStrokes = Stat.SummaryStat(name='Total Number of Strokes',
data=self.nStrokes)
self.nLivingPatients = Path.PrevalencePathBatchUpdate(
name='# of living patients',
initial_size=initial_pop_size,
times_of_changes=self.survivalTimes,
increments=[-1] * len(self.survivalTimes))
def extract_outcomes(self, simulated_patients):
""" extracts outcomes of a simulated cohort
:param simulated_patients: a list of simulated patients"""
# record survival time and time until AIDS
for patient in simulated_patients:
if patient.stateMonitor.survivalTime is not None:
self.survivalTimes.append(patient.stateMonitor.survivalTime)
if patient.stateMonitor.timeToAIDS is not None:
self.timesToAIDS.append(patient.stateMonitor.timeToAIDS)
# calculate mean survival time
self.meanSurvivalTime = sum(self.survivalTimes) / len(
self.survivalTimes)
# calculate mean time to AIDS
self.meanTimeToAIDS = sum(self.timesToAIDS) / len(self.timesToAIDS)
# survival curve
self.nLivingPatients = Path.PrevalencePathBatchUpdate(
name='# of living patients',
initial_size=len(simulated_patients),
times_of_changes=self.survivalTimes,
increments=[-1] * len(self.survivalTimes))
# record the observations
path1.record_increment(1.2, 2)
path1.record_increment(2.3, -1)
path1.record_increment(5.1, 0)
# second sample path with initial size = 1
path2 = Path.PrevalenceSamplePath('Path 2', initial_size=0, sim_rep=1)
# record the observations
path2.record_increment(0.5, 4)
path2.record_increment(1.8, -2)
path2.record_increment(5.5, 1)
# third sample path with initial size = 1
path3 = Path.PrevalencePathBatchUpdate('Path 3',
0,
times_of_changes=[1.5, 2, 5],
increments=[2, -1, 0],
sim_rep=1)
path4 = Path.PrevalencePathBatchUpdate('Path 4',
0,
times_of_changes=[0.5, 4, 4.5],
increments=[2.5, 1, 1],
sim_rep=1)
# stats
print(path1.stat.get_mean())
# plot path 1 only
Path.plot_sample_path(sample_path=path1,
title='Plotting a single sample path',
x_label='time',
