def test_pem_model(**kwargs): ''' Test weibull survival model on simulated dataset ''' d = load_test_dataset(n=20) dlong = load_test_dataset_long() testfit = survivalstan.fit_stan_survival_model( model_cohort='test model', model_code=model_code, df=dlong, sample_col='index', timepoint_end_col='end_time', event_col='end_failure', formula='~ age + sex', iter=num_iter, chains=2, seed=9001, make_inits=make_inits, FIT_FUN=stancache.cached_stan_fit, **kwargs) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], element='baseline') survivalstan.utils.plot_pp_survival([testfit]) survivalstan.utils.plot_observed_survival(df=d, time_col='t', event_col='event') return (testfit)
def test_pem_model(**kwargs): ''' Test weibull survival model on simulated dataset ''' d = load_test_dataset(n=20) dlong = load_test_dataset_long() testfit = survivalstan.fit_stan_survival_model( model_cohort = 'test model', model_code = model_code, df = dlong, sample_col = 'index', timepoint_end_col = 'end_time', event_col = 'end_failure', formula = '~ age + sex', iter = num_iter, chains = 2, seed = 9001, make_inits = make_inits, FIT_FUN = stancache.cached_stan_fit, **kwargs ) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], element='baseline') survivalstan.utils.plot_pp_survival([testfit]) survivalstan.utils.plot_observed_survival(df=d, time_col='t', event_col='event') return(testfit)
def test_pem_null_model(force=True, **kwargs): ''' Test NULL survival model on flchain dataset ''' dlong = load_test_dataset_long() testfit = survivalstan.fit_stan_survival_model( model_cohort = 'test model', model_code = model_code, df = dlong, sample_col = 'index', timepoint_end_col = 'end_time', event_col = 'end_failure', group_col = 'sex', formula = '~ 1', iter = num_iter, chains = 2, seed = 9001, make_inits = make_inits, FIT_FUN = stancache.cached_stan_fit, **kwargs ) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], trans=np.exp, element='grp_coefs') survivalstan.utils.plot_coefs([testfit], element='baseline') return(testfit)
def test_pem_null_model(force=True, **kwargs): ''' Test NULL survival model on flchain dataset ''' dlong = sim_test_dataset_long() testfit = survivalstan.fit_stan_survival_model( model_cohort='test model', model_code=model_code, df=dlong, sample_col='index', timepoint_end_col='end_time', event_col='end_failure', formula='~ 1', iter=num_iter, chains=2, seed=9001, make_inits=make_inits, FIT_FUN=stancache.cached_stan_fit, **kwargs) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], trans=np.exp, element='grp_coefs') survivalstan.utils.plot_coefs([testfit], element='baseline') survivalstan.utils.plot_pp_survival([testfit]) return (testfit)
def test_null_pem_model(**kwargs): ''' Test weibull survival model on simulated dataset ''' d = load_test_dataset(n=20) dlong = survivalstan.prep_data_long_surv(df=d, time_col='t', event_col='event') testfit = survivalstan.fit_stan_survival_model( model_cohort = 'test model', model_code = model_code, df = dlong, sample_col = 'index', timepoint_end_col = 'end_time', event_col = 'end_failure', formula = '~ 1', iter = num_iter, chains = 2, seed = 9001, make_inits = make_inits, FIT_FUN = stancache.cached_stan_fit, **kwargs ) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], element='baseline') survivalstan.utils.plot_pp_survival([testfit]) survivalstan.utils.plot_observed_survival(df=d, time_col='t', event_col='event') fitsum = survivalstan.utils.filter_stan_summary([testfit], pars='baseline') fitsum = survivalstan.utils.filter_stan_summary(testfit['fit'], remove_nan=True) survivalstan.utils.print_stan_summary([testfit], pars='lp__') survivalstan.utils.plot_stan_summary([testfit], pars='log_baseline_raw') return(testfit)
def test_pem_model(**kwargs): ''' Test survival model on test dataset ''' dlong = load_test_dataset_long() testfit = survivalstan.fit_stan_survival_model( model_cohort = 'test model', model_code = model_code, df = dlong, sample_col = 'index', timepoint_end_col = 'end_time', event_col = 'end_failure', formula = '~ age + sex', iter = num_iter, chains = 2, seed = 9001, make_inits = make_inits, FIT_FUN = stancache.cached_stan_fit, **kwargs ) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], trans=np.exp, element='grp_coefs') survivalstan.utils.plot_coefs([testfit], element='baseline') survivalstan.utils.plot_coefs([testfit], element='beta_time') survivalstan.utils.plot_coefs([testfit], element='beta_time', trans=np.exp) survivalstan.utils.plot_pp_survival([testfit]) survivalstan.utils.plot_time_betas(models=[testfit], y='beta', x='end_time', coefs=[testfit['x_names'][0]]) survivalstan.utils.plot_time_betas(models=[testfit], y='exp(beta)') survivalstan.utils.plot_time_betas(models=[testfit], y='exp(beta)', ylim=[0, 4]) first_beta = survivalstan.utils.extract_time_betas([testfit], coefs=[testfit['x_names'][0]]) survivalstan.utils.plot_time_betas(df=first_beta, by=['coef'], y='beta', x='end_time') return(testfit)
def test_pem_model(**kwargs): ''' Test survival model on test dataset ''' dlong = load_test_dataset_long() testfit = survivalstan.fit_stan_survival_model( model_cohort='test model', model_code=model_code, df=dlong, sample_col='index', timepoint_end_col='end_time', event_col='end_failure', formula='~ age + sex', iter=num_iter, chains=2, seed=9001, make_inits=make_inits, FIT_FUN=stancache.cached_stan_fit, **kwargs) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], trans=np.exp, element='grp_coefs') survivalstan.utils.plot_coefs([testfit], element='baseline') survivalstan.utils.plot_coefs([testfit], element='beta_time') survivalstan.utils.plot_coefs([testfit], element='beta_time', trans=np.exp) survivalstan.utils.plot_pp_survival([testfit]) survivalstan.utils.plot_time_betas(models=[testfit], y='beta', x='end_time', coefs=[testfit['x_names'][0]]) survivalstan.utils.plot_time_betas(models=[testfit], y='exp(beta)') survivalstan.utils.plot_time_betas(models=[testfit], y='exp(beta)', ylim=[0, 4]) first_beta = survivalstan.utils.extract_time_betas( [testfit], coefs=[testfit['x_names'][0]]) survivalstan.utils.plot_time_betas(df=first_beta, by=['coef'], y='beta', x='end_time') return (testfit)
def test_pem_model_sim_covar_with_form(): dlong = sim_test_dataset_long() testfit = survivalstan.fit_stan_survival_model( model_cohort = 'test model', model_code = model_code, df = dlong, formula = 'surv(event_status=end_failure, time=end_time, subject=index) ~ age + sex', iter = num_iter, chains = 2, seed = 9001, make_inits = make_inits, FIT_FUN = stancache.cached_stan_fit, ) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], element='baseline') return(testfit)
def test_model_with_formula(): ''' Test survival model using `surv` syntax ''' d = load_test_dataset() testfit = survivalstan.fit_stan_survival_model( model_cohort = 'test model', model_code = model_code, df = d, formula = 'surv(event_status=event, time=t) ~ age + sex', iter = num_iter, chains = 2, seed = 9001, make_inits = make_inits, FIT_FUN = stancache.cached_stan_fit, ) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) return(testfit)
def test_pem_model_sim_covar_with_form(): dlong = sim_test_dataset_long() testfit = survivalstan.fit_stan_survival_model( model_cohort='test model', model_code=model_code, df=dlong, formula= 'surv(event_status=end_failure, time=end_time, subject=index) ~ age + sex', iter=num_iter, chains=2, seed=9001, make_inits=make_inits, FIT_FUN=stancache.cached_stan_fit, ) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) survivalstan.utils.plot_coefs([testfit], element='baseline') return (testfit)
def test_model(**kwargs): ''' Test weibull survival model on simulated dataset ''' d = sim_test_dataset() testfit = survivalstan.fit_stan_survival_model( model_cohort='test model', model_code=model_code, df=d, time_col='t', event_col='event', formula='~ age + sex', iter=num_iter, chains=2, seed=9001, make_inits=make_inits, FIT_FUN=stancache.cached_stan_fit, **kwargs) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) return (testfit)
def test_null_model(**kwargs): ''' Test NULL survival model on flchain dataset ''' d = load_test_dataset() testfit = survivalstan.fit_stan_survival_model( model_cohort='test model', model_code=model_code, df=d, time_col='t', event_col='event', formula='~ 1', iter=num_iter, chains=2, seed=9001, make_inits=make_inits, FIT_FUN=stancache.cached_stan_fit, drop_intercept=False, **kwargs) ok_('fit' in testfit) ok_('coefs' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) return (testfit)
def test_null_model(**kwargs): ''' Test NULL survival model on flchain dataset ''' d = load_test_dataset() testfit = survivalstan.fit_stan_survival_model( model_cohort = 'test model', model_code = model_code, df = d, time_col = 't', event_col = 'event', formula = '~ 1', iter = num_iter, chains = 2, seed = 9001, make_inits = make_inits, FIT_FUN = stancache.cached_stan_fit, ) ok_('fit' in testfit) ok_('coefs' in testfit) ok_('loo' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) return(testfit)
def test_model(**kwargs): ''' Test weibull survival model on simulated dataset ''' d = sim_test_dataset() testfit = survivalstan.fit_stan_survival_model( model_cohort = 'test model', model_code = model_code, df = d, time_col = 't', event_col = 'event', formula = '~ age + sex', iter = num_iter, chains = 2, seed = 9001, make_inits = make_inits, FIT_FUN = stancache.cached_stan_fit, drop_intercept = False, **kwargs ) ok_('fit' in testfit) ok_('coefs' in testfit) survivalstan.utils.plot_coefs([testfit]) survivalstan.utils.plot_coefs([testfit], trans=np.exp) return(testfit)