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%