def draw_survival_curves_and_histograms(simOutputs_mono, simOutputs_combo):
""" draws the survival curves and the histograms of time until HIV deaths
:param simOutputs_mono: output of a cohort simulated under mono therapy
:param simOutputs_combo: output of a cohort simulated under combination therapy
"""
# get survival curves of both treatments
survival_curves = [
simOutputs_mono.get_survival_curve(),
simOutputs_combo.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(sample_paths=survival_curves,
title='Survival curve',
x_label='Simulation time step (year)',
y_label='Number of alive patients',
legends=['Mono Therapy', 'Combination Therapy'])
# histograms of survival times
set_of_survival_times = [
simOutputs_mono.get_survival_times(),
simOutputs_combo.get_survival_times()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_survival_times,
title='Histogram of patient survival time',
x_label='Survival time (year)',
y_label='Counts',
bin_width=1,
legend=['Mono Therapy', 'Combination Therapy'],
transparency=0.6)
def draw_survival_curves_and_histograms(simOutputs_mono, simOutputs_combo):
""" draws the survival curves and the histograms of time until HIV deaths
:param simOutputs_mono: output of a cohort simulated under mono therapy
:param simOutputs_combo: output of a cohort simulated under combination therapy
"""
# get survival curves of both treatments
survival_curves = [
simOutputs_mono.get_survival_curve(),
simOutputs_combo.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(sample_paths=survival_curves,
title='Exposure of antibiotics',
x_label='Simulation time step (day)',
y_label='Number of patients using antibiotics',
legends=['Standard treatment', 'PCT-guided'])
# histograms of survival times
set_of_survival_times = [
simOutputs_mono.get_survival_times(),
simOutputs_combo.get_survival_times()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_survival_times,
title='Histogram of exposure time to antibiotics',
x_label='Exposure time to antibiotics (day)',
y_label='Counts',
bin_width=1,
legend=['Standard care', 'PCT-guided'],
transparency=0.5)
def draw_survival_curves_and_histograms(simOutputs_standard,
simOutputs_population):
""" draws the survival curves and the histograms of time until cancer
:param simOutputs_standard: output of a cohort simulated under standard testing
:param simOutputs_population: output of a cohort simulated under population testing
"""
# get survival curves of both treatments
survival_curves = [
simOutputs_standard.get_survival_curve(),
simOutputs_population.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(
sample_paths=survival_curves,
title='Survival curve',
x_label='Simulation time step (year)',
y_label='Number of alive patients',
legends=['Standard Testing', 'Population Testing'])
# histograms of survival times
set_of_survival_times = [
simOutputs_standard.get_survival_times(),
simOutputs_population.get_survival_times()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_survival_times,
title='Histogram of patient survival time',
x_label='Survival time (year)',
y_label='Counts',
bin_width=1,
legend=['Mono Therapy', 'Combination Therapy'],
transparency=0.6)
def draw_infection_curves_and_histograms(simOutputs_ANNUAL, simOutputs_SEMI):
""" draws the infection curves and the histograms of time until HIV deaths
:param simOutputs_mono: output of a cohort simulated under mono therapy
:param simOutputs_combo: output of a cohort simulated under combination therapy
"""
# histograms of infection times
set_of_infection_times = [
simOutputs_ANNUAL.get_infection_durations(),
simOutputs_SEMI.get_infection_durations()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_infection_times,
title='Histogram of Infection Duration',
x_label='Infection Duration (Year)',
y_label='Counts',
bin_width=1,
legend=['Annual Treatment', 'Semi-Annual Treatment'],
transparency=0.6)
#get infection curves of both treatments
infection_curves = [
simOutputs_ANNUAL.get_infection_curve(),
simOutputs_SEMI.get_infection_curve()
]
# graph infection curve
PathCls.graph_sample_paths(sample_paths=infection_curves,
title='infection curve',
x_label='Simulation time step (year)',
y_label='Number of infected patients',
legends=['ANNUAL', '6-month'])
def draw_survival_curves_and_histograms(simOutputs_warfarin,
simOutputs_Dabigitran150):
""" draws the survival curves and the histograms of time until stoke deaths
:param simOutputs_warfarin: output of a cohort simulated under warfarin therapy
:param simOutputs_Dabigitran150: output of a cohort simulated under dab150 therapy
"""
# get survival curves of both treatments
survival_curves = [
simOutputs_warfarin.get_survival_curve(),
simOutputs_Dabigitran150.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(sample_paths=survival_curves,
title='Survival curve',
x_label='Simulation time step (year)',
y_label='Number of alive patients',
legends=['Warfarin', 'Dabigitran150 Therapy'])
# histograms of survival times
set_of_survival_times = [
simOutputs_warfarin.get_survival_times(),
simOutputs_Dabigitran150.get_survival_times()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_survival_times,
title='Histogram of patient survival time',
x_label='Survival time (year)',
y_label='Counts',
bin_width=1,
legend=['Warfarin Therapy', 'Dabigitran150 Therapy'],
transparency=0.6)
def draw_survival_curves_and_histograms(sim_output_no_drug,
sim_output_with_drug):
""" draws the survival curves and the histograms of survival time
:param sim_output_no_drug: output of a cohort simulated when drug is not available
:param sim_output_with_drug: output of a cohort simulated when drug is available
"""
# get survival curves of both treatments
survival_curves = [
sim_output_no_drug.get_survival_curve(),
sim_output_with_drug.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(sample_paths=survival_curves,
title='Survival curve',
x_label='Simulation time step',
y_label='Number of alive patients',
legends=['No Drug', 'With Drug'])
# histograms of survival times
set_of_survival_times = [
sim_output_no_drug.get_survival_times(),
sim_output_with_drug.get_survival_times()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_survival_times,
title='Histogram of patient survival time',
x_label='Survival time',
y_label='Counts',
bin_width=1,
legend=['No Drug', 'With Drug'],
transparency=0.6)
def graph_sample_paths\
(sample_paths, title, x_label, y_label, output_type=Fig.OutType.SHOW,
legends=None, transparency=1, common_color_code=None,
if_same_color=False):
"""
:param sample_paths: a list of sample paths
:param title: (string) title of the figure
:param x_label: (string) x-axis label
:param y_label: (string) y-axis label
:param output_type: select from OutType.SHOW, OutType.PDF, or OutType.JPG
:param legends: list of strings for legend
:param transparency: float (0.0 transparent through 1.0 opaque)
:param common_color_code: (string) color code if all sample paths should have the same color
'b' blue 'g' green 'r' red 'c' cyan 'm' magenta 'y' yellow 'k' black
:param if_same_color: logical, default False, if set True, paint the sample paths the same color
"""
if len(sample_paths) == 1:
raise ValueError('Only one sample path is provided. Use graph_sample_path instead.')
fig = plt.figure(title)
plt.title(title) # title
plt.xlabel(x_label) # x-axis label
plt.ylabel(y_label) # y-axis label
# color
color_marker_text = '-'
if not (common_color_code is None):
color_marker_text = common_color_code+color_marker_text
# x and y values
if if_same_color:
for path in sample_paths:
x_values = path.get_times()
y_values = path.get_values()
# plot
plt.plot(x_values, y_values, common_color_code, alpha=transparency)
else:
for path in sample_paths:
x_values = path.get_times()
y_values = path.get_values()
# plot
plt.plot(x_values, y_values, color_marker_text, alpha=transparency)
# add legend if provided
if not (legends is None):
if common_color_code is None:
plt.legend(legends)
else:
plt.legend([legends])
# set the minimum of y-axis to zero
plt.ylim(ymin=0) # the minimum has to be set after plotting the values
# output figure
Fig.output_figure(plt, output_type, title)
def draw_survival_curves_and_histograms(simOutputs_none, simOutputs_anticoag):
""" draws the survival curves and the histograms of time until HIV deaths
:param simOutputs_none: output of a cohort simulated under the natural history of disease
:param simOutputs_anticoag: output of a cohort simulated under angicoagulation therapy recepit
"""
# get survival curves of both treatments
survival_curves = [
simOutputs_none.get_survival_curve(),
simOutputs_anticoag.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(
sample_paths=survival_curves,
title='Survival curve',
x_label='Simulation time step (year)',
y_label='Number of alive patients',
legends=['No Therapy', 'Anticoagulation Therapy'])
# histograms of survival times
set_of_survival_times = [
simOutputs_none.get_survival_times(),
simOutputs_anticoag.get_survival_times()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_survival_times,
title='Histogram of patient survival time',
x_label='Survival time (year)',
y_label='Counts',
bin_width=1,
legend=['No Therapy', 'Anticoagulation Therapy'],
transparency=0.6)
# histograms of the number of strokes
set_of_stroke_counts = [
simOutputs_none.get_if_developed_stroke(),
simOutputs_anticoag.get_if_developed_stroke()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_stroke_counts,
title='Histogram of patient stroke counts',
x_label='Number of strokes',
y_label='Counts',
bin_width=1,
legend=['No Therapy', 'Anticoagulation Therapy'],
transparency=0.6)
def draw_stroke_histograms(simOutputs_none, simOutputs_anticoag):
set_of_strokes = [
simOutputs_none.get_numbers_of_strokes(),
simOutputs_anticoag.get_numbers_of_strokes()
]
Figs.graph_histograms(
data_sets=set_of_strokes,
title='Histogram of number of strokes',
x_label='Number of Strokes',
y_label='Counts',
bin_width=1,
legend=['No Therapy', 'Anticoagulation Therapy'],
transparency=0.6
)
def draw_reward_histograms(sim_output_fair_coin, sim_output_unfair_coin):
set_of_game_rewards = [
sim_output_fair_coin.get_rewards(),
sim_output_unfair_coin.get_rewards()
]
Fig.graph_histograms(
data_sets=set_of_game_rewards,
title='Histogram of game reward',
x_label='Game rewards',
y_label='Counts',
bin_width=50,
legend=['Fair Coin', 'Unfair Coin'],
transparency=0.6
)
def make_plots(output_fair_coin, output_biased_coin):
# makes histogram of the game rewards
# histograms of game rewards
set_of_game_rewards = [
output_fair_coin.get_rewards(),
output_biased_coin.get_rewards()
]
Figs.graph_histograms(data_sets=set_of_game_rewards,
title='Histogram of Game Rewards',
x_label='Game rewards',
y_label='Counts',
bin_width=20,
legend=['Fair coin', 'Unfair coin'],
transparency=0.6)
def draw_histogram(sim_output_fair, sim_output_unfair):
# histograms of payouts
set_of_payouts = [
sim_output_fair.get_payouts(),
sim_output_unfair.get_payouts()
]
# graph histograms
Fig.graph_histograms(data_sets=set_of_payouts,
title='Histogram of payouts',
x_label='Payouts',
y_label='Counts',
bin_width=50,
legend=['Fair Coin', 'Unfair Coin'],
transparency=0.6)
def draw_histograms(multiGames1, multiGames2):
# histograms of average rewards
set_of_rewards = [
multiGames1.get_all_total_rewards(),
multiGames2.get_all_total_rewards()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_rewards,
title='Histogram of total rewards (in 10 games)',
x_label='Rewards',
y_label='Counts',
bin_width=15,
legend=['50%', '45%'],
transparency=0.5,
x_range=[-1500, 1000])
def draw_histograms(multi_cohort_fair_coin, multi_cohort_unfair_coin):
set_of_game_rewards = [
multi_cohort_fair_coin.get_all_mean_reward(),
multi_cohort_unfair_coin.get_all_mean_reward()
]
# graph histograms
Fig.graph_histograms(
data_sets=set_of_game_rewards,
title='Histogram of average game reward',
x_label='Game reward',
y_label='Counts',
bin_width=50,
legend=['Fair Coin', 'Unfair Coin'],
transparency=0.5,
# x_range=[-50, 0]
)
def make_plots(games_fair_coin, games_biased_coin):
# histograms of total game rewards
set_of_game_rewards = [
games_fair_coin.get_all_total_rewards(),
games_biased_coin.get_all_total_rewards()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_game_rewards,
title="Histogram of the Gambler's Total Rewards from 10 Games",
x_label='Total Rewards',
y_label='Count',
bin_width=40,
legend=['Fair coin', 'Unfair coin'],
transparency=0.6,
)
def draw_histograms(multi_cohort_fair, multi_cohort_unfair):
""" draws the histograms of average survival time
:param multi_cohort_fair: multiple cohorts simulated when using fair coins
:param multi_cohort_unfair: multiple cohorts simulated when using unfair coins
"""
# histograms of average survival times
set_of_game_rewards = [
multi_cohort_fair.get_all_total_rewards(),
multi_cohort_unfair.get_all_total_rewards()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_game_rewards,
title='Histogram of average game rewards',
x_label='Game rewards',
y_label='Counts',
legend=['Fair coin', 'Unfair coin'],
transparency=0.5,
x_range=[0, 20])
def draw_survival_curves_and_histograms(sim_output_fair_coin,
sim_output_unfair_coin):
""" draws the histograms of game rewards
:param sim_output_fair_coin: output of a set of games simulated when the coin is fair
:param sim_output_unfair_coin: output of a set of games simulated when the coin is unfair
"""
# histograms of game rewards
set_of_game_rewards = [
sim_output_fair_coin.get_rewards(),
sim_output_unfair_coin.get_rewards()
]
# graph histograms
Figs.graph_histograms(data_sets=set_of_game_rewards,
title='Histogram of Game Rewards',
x_label='Game rewards',
y_label='Counts',
bin_width=20,
legend=['Fair coin', 'Unfair coin'],
transparency=0.6)
def graph_sample_path(sample_path, title, x_label, y_label,
output_type=Fig.OutType.SHOW, legend=None, color_code=None):
"""
produces a sample path
:param sample_path: a sample path
:param title: (string) title of the figure
:param x_label: (string) x-axis label
:param y_label: (string) y-axis label
:param output_type: select from OutType.SHOW, OutType.PDF, or OutType.JPG
:param legend: string for the legend
:param color_code: (string) 'b' blue 'g' green 'r' red 'c' cyan 'm' magenta 'y' yellow 'k' black
"""
fig = plt.figure(title)
plt.title(title) # title
plt.xlabel(x_label) # x-axis label
plt.ylabel(y_label) # y-axis label
# x and y values
x_values = sample_path.get_times()
y_values = sample_path.get_values()
# color
color_marker_text = '-'
if not (color_code is None):
color_marker_text = color_code + color_marker_text
# plot
plt.plot(x_values, y_values, color_marker_text)
# add legend if provided
if not (legend is None):
plt.legend([legend])
# set the minimum of y-axis to zero
plt.ylim(ymin=0) # the minimum has to be set after plotting the values
# output figure
Fig.output_figure(plt, output_type, title)
def draw_histograms(multigamesetsfair, multigamesetsunfair):
""" draws the histograms of average survival time
:param multi_cohort_no_drug: multiple cohorts simulated when drug is not available
:param multi_cohort_with_drug: multiple cohorts simulated when drug is available
"""
# histograms of average survival times
totalreward = [
multigamesetsfair.get_all_total_rewards(),
multigamesetsunfair.get_all_total_rewards()
]
# graph histograms
Figs.graph_histograms(
data_sets= totalreward,
title='Histogram of total reward',
x_label='Reward',
y_label='Counts',
bin_width=50,
legend=['Fair coin', 'Unfair coin'],
transparency=0.5,
)
def draw_reward_histograms(sim_output_fair_coin, sim_output_unfair_coin):
""" draws the histograms of game rewards
:param sim_output_fair_coin: output of a cohort simulated game-set with a fair coin
:param sim_output_unfair_coin: output of a cohort simulated game-set with an unfair coin
"""
# histograms of game rewards
set_of_game_rewards = [
sim_output_fair_coin.get_rewards(),
sim_output_unfair_coin.get_rewards()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_game_rewards,
title='Histogram of game reward',
x_label='Game rewards',
y_label='Counts',
bin_width=50,
legend=['Fair Coin', 'Unfair Coin'],
transparency=0.6
)
def draw_histograms(multi_games_fair_coin, multi_games_unfair_coin):
""" draws the histograms of average game rewards
:param multi_games_fair_coin: multiple sets of games simulated when the coin is fair
:param multi_games_unfair_coin: multiple sets of games simulated when the coin is unfair
"""
# histograms of average game rewards
set_of_game_rewards = [
multi_games_fair_coin.get_all_total_rewards(),
multi_games_unfair_coin.get_all_total_rewards()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_game_rewards,
title="Histogram of the Gambler's Average Total Game Rewards",
x_label='Mean Game Rewards',
y_label='Count',
bin_width=40,
legend=['Fair coin', 'Unfair coin'],
transparency=0.6,
)
def draw_survival_curves_and_histograms(sim_output_1, sim_output_2):
""" draws the survival curves and the histograms of survival time
:param sim_output_no_drug: output of a cohort simulated when drug is not available
:param sim_output_with_drug: output of a cohort simulated when drug is available
"""
# histograms of rewards
set_of_rewards = [
sim_output_1.get_rewards(),
sim_output_2.get_rewards()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_rewards,
title='Histogram of rewards',
x_label='Rewards',
y_label='Counts',
bin_width=15,
legend=['50%', '45%'],
transparency=0.6
)
def Simulate(self, number_of_flips, number_of_realizations):
self.number_of_flips = number_of_flips
self.number_of_realizations = number_of_realizations
gamecost = -250 # cost of playing the game
totalwinnings = 0 # initialize total winnings
winningslist = [] # empty list to place each game's winnging into and then graph
losecount = 0 # keep track of any time you lose money
for j in range(0, self.number_of_realizations):
fliplist = "" # create an empty string
for i in range(0, self.number_of_flips): # iterate through 20 flips, treating 1's as heads and 0's as tails
fliplist = fliplist + str((numpy.random.binomial(1, self.flip_probability))) #per https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.binomial.html, add each flip to fliplist
winnings = gamecost+(100*(fliplist.count("001"))) # find the number of Tails, Tails, Heads, multiply by fifty, add to cost of game to find winnings
winningslist.append(winnings) # append winningslist with each games winnings
if winnings < 0:
losecount = losecount +1 # if winnings are less than 0, add to losecount
totalwinnings = totalwinnings + winnings # add all the realizations of winnings together
averagewinnings = '${:,.2f}'.format((totalwinnings/self.number_of_realizations)) # find the average winnings
# print("Expected reward: ", averagewinnings) # print the average winnings
# Problem 1
FigureSupport.graph_histogram(
observations=winningslist,
title='Histogram of Game Winnings (1000 Games)',
x_label='Game Winnings (Dollars)',
y_label='Count')
print("Problem 1: It appears that the minimum award is approximately $ -250 while the maximum award is approximately $ 250")
# Problem 2
loseprob = losecount/self.number_of_realizations
print("Problem 2: Probability of Losing Money: ",loseprob)
def draw_survival_curves_and_histograms(simOutputs_no_therapy, simOutputs_anticoagulation):
"""
:param simOutputs_no_therapy: no therapy
:param simOutputs_anticoagulation: anticoagulation
:return:
"""
# get survival curves of both treatments
survival_curves = [
simOutputs_no_therapy.get_survival_curve(),
simOutputs_anticoagulation.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(
sample_paths=survival_curves,
title='Survival curve',
x_label='Simulation time step (year)',
y_label='Number of alive patients',
legends=['No Therapy', 'Anticoagulation Therapy']
)
# histograms of survival times
set_of_survival_times = [
simOutputs_no_therapy.get_survival_times(),
simOutputs_anticoagulation.get_survival_times()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_survival_times,
title='Histogram of patient survival time',
x_label='Survival time (year)',
y_label='Counts',
bin_width=1,
legend=['No Therapy', 'Anticoagualtion Therapy'],
transparency=0.6
)
def draw_histograms(multi_cohort_UnfairCoin, multi_cohort_FairCoin):
""" draws the histograms of average survival time
:param multi_cohort_no_drug: multiple cohorts simulated when drug is not available
:param multi_cohort_with_drug: multiple cohorts simulated when drug is available
"""
# histograms of average survival times
set_of_survival_times = [
multi_cohort_UnfairCoin.get_mean_total_reward(),
multi_cohort_FairCoin.get_mean_total_reward()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_survival_times,
title='Histogram of average patient survival time',
x_label='Survival time',
y_label='Counts',
bin_width=1,
legend=['No Drug', 'With Drug'],
transparency=0.5,
x_range=[6, 20]
)
def histograms(sim_output_fair_coin, sim_output_unfair_coin):
""" draws the histograms of rewards
:param sim_output_fair_coin: output of a set of games simulated with a fair coin
:param sim_output_unfair_coin: output of a set of games simulated with an unfair coin
"""
# histograms of survival times
set_of_rewards = [
sim_output_fair_coin.get_rewards(),
sim_output_unfair_coin.get_rewards()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_rewards,
title="Histogram of Rewards from 1000 Games obtained from the steady-state simulation model",
x_label="Game Rewards",
y_label="Frequency",
bin_width=25,
legend=['Fair Coin', 'Unfair Coin'],
transparency=0.5
)
def draw_histograms(multi_cohort_fair_coin, multi_cohort_unfair_coin):
""" draws the histograms of average survival time
:param multi_cohort_fair_coin: multiple gamesets simulated when the coin is fair
:param multi_cohort_unfair_coin: multiple gamesets simulated when the coin is unfair
"""
# histograms of game rewards
set_of_game_rewards = [
multi_cohort_fair_coin.get_all_mean_reward(),
multi_cohort_unfair_coin.get_all_mean_reward()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_game_rewards,
title='Histogram of average game reward',
x_label='Game reward',
y_label='Counts',
bin_width=50,
legend=['Fair Coin', 'Unfair Coin'],
transparency=0.5,
# x_range=[-50, 0]
)
def draw_survival_curves_and_histograms(simOutputs_anti, simOutputs_none):
""" draws the survival curves and the histograms of time until STROKE deaths
:param simOutputs_anti: output of a cohort simulated under ANTI therapy
:param simOutputs_none: output of a cohort simulated under NONE therapy
"""
# get survival curves of both treatments
survival_curves = [
simOutputs_anti.get_survival_curve(),
simOutputs_none.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(
sample_paths=survival_curves,
title='Survival curve',
x_label='Simulation time step (year)',
y_label='Number of alive patients',
legends=['Anticoagulant Therapy', 'None Therapy']
)
# histograms of survival times
set_of_survival_times = [
simOutputs_anti.get_survival_times(),
simOutputs_none.get_survival_times()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_survival_times,
title='Histogram of patient survival time',
x_label='Survival time (year)',
y_label='Counts',
bin_width=1,
legend=['Anticoagulant Therapy', 'None Therapy'],
transparency=0.6
)
def draw_survival_curves_and_histograms(simOutputs_warfarin,
simOutputs_dabigatran_110,
simOutputs_dabigatran_150):
# draws the survival curves and the histograms of time until death
# get survival curves of all treatments
survival_curves = [
simOutputs_warfarin.get_survival_curve(),
simOutputs_dabigatran_110.get_survival_curve(),
simOutputs_dabigatran_150.get_survival_curve()
]
# graph survival curve
PathCls.graph_sample_paths(
sample_paths=survival_curves,
title='Survival curve',
x_label='Simulation time step (year)',
y_label='Number of alive patients',
legends=['Warfarin', 'Dabigatran 110', 'Dabigatran 150'])
# histograms of survival times
set_of_survival_times = [
simOutputs_warfarin.get_survival_times(),
simOutputs_dabigatran_110.get_survival_times(),
simOutputs_dabigatran_150.get_survival_times()
]
# graph histograms
Figs.graph_histograms(
data_sets=set_of_survival_times,
title='Histogram of patient survival time',
x_label='Survival time (year)',
y_label='Counts',
bin_width=0.5,
legend=['Warfarin', 'Dabigatran 110', 'Dabigatran 150'],
transparency=0.6)
def get_ave_reward(self):
""" returns the average reward from all games"""
return sum(self._gameRewards) / len(self._gameRewards)
def get_game_times(self):
return self._gametimes
def get_game_rewards(self):
return self._gameRewards
games = SetOfGames(prob_head=0.5, n_games=1000)
# print the average reward
print('Expected reward when the probability of head is 0.5:', games.get_ave_reward())
print min(games.get_game_rewards()), max(games.get_game_rewards())
# create a histogram of patient survival time
FigSupport.graph_histogram(
observations= games.get_game_rewards(),
title="Histogram of Rewards Distribution",
x_label="The amount of money we win(dollar)",
y_label="Count",
x_range=[min(games.get_game_rewards()),max(games.get_game_rewards())])
# In 20 times filp, we would expect the maximum money we won achieved at 6 time all win "TTH":
# So the maximum reward should be 6*100-250=350
# and the mininum reward shoule be 6*0-250 = -250
#get mean number of strokes without the drug
cohort = MarkovCls.Cohort(id=0, therapy=P.Therapies.withoutdrug)
simOutput = cohort.simulate()
strokecount_mean_CI_text = F.format_estimate_interval(
estimate=simOutput.get_sumState_timeToSTROKE().get_mean(),
interval=simOutput.get_sumState_timeToSTROKE().get_t_CI(alpha=Data.ALPHA),
deci=2)
print(
" Estimate of mean times of stroke and {:.{prec}%} confidence interval without drug is... :"
.format(1 - Data.ALPHA, prec=0), strokecount_mean_CI_text)
# graph histogram for this non-drug group
Figs.graph_histogram(
data=simOutput.get_these_stroke_times(),
title=
'Stroke Count if the Patient Does Not Receive the Heart-Drug Intervention',
x_label='Survival time (years)',
y_label='Stroke Counts (#)',
bin_width=1)
####NOW for the ppl with the drug ######
#get mean number of strokes with the drug
Adjusted_Cohort = MarkovCls.Cohort(id=0, therapy=P.Therapies.newdrug)
new_simOutputs = Adjusted_Cohort.simulate()
new_strokecount_mean_CI_text = F.format_estimate_interval(
estimate=new_simOutputs.get_sumState_timeToSTROKE().get_mean(),
interval=new_simOutputs.get_sumState_timeToSTROKE().get_t_CI(
alpha=Data.ALPHA),
deci=2)
print(
return sum(self._CountTotalLoss)/sum(self._CountTotalWin)
class SetOfGamesOutcomes:
def __init__(self, simulated_set_outcomes):
# extracts outcomes of the simulated set of games
self._simulated_set_outcomes = simulated_set_outcomes
#not sure if I should move forward with this piece
# run trail of 1000 games to calculate expected reward
games = SetOfGames(prob_head=0.5, n_games=1000)
# print the average reward
print('Expected reward when the probability of head is 0.5:', games.get_ave_reward())
# print the prob of loss
print ('Probability of losing money', games.get_prob_loss())
# Histogram of rewards for 1000 games
FigSupport.graph_histogram(
observations= SetOfGames.get_reward(games),
title='Histogram of Rewards',
x_label='Reward',
y_label='Count')
# Answer 1: min is -150, max is 250
# Answer 2: Prob of losing money is 100%
