''' Measure convergence on the GDSC drug sensitivity dataset, with the Gaussian + Exponential model. ''' import sys, os project_location = os.path.dirname(__file__) + "/../../../../" sys.path.append(project_location) from BMF_Priors.code.models.bmf_gaussian_exponential import BMF_Gaussian_Exponential from BMF_Priors.data.drug_sensitivity.load_data import load_gdsc_ic50_integer from BMF_Priors.experiments.convergence.convergence_experiment import measure_convergence_time import matplotlib.pyplot as plt ''' Run the experiment. ''' R, M = load_gdsc_ic50_integer() model_class = BMF_Gaussian_Exponential settings = { 'R': R, 'M': M, 'K': 20, 'hyperparameters': { 'alpha': 1., 'beta': 1., 'lamb': 0.1 }, 'init': 'random', 'iterations': 200, } fout_performances = './results/performances_gaussian_exponential.txt' fout_times = './results/times_gaussian_exponential.txt'
Gamma model. ''' import sys, os project_location = os.path.dirname(__file__)+"/../../../../" sys.path.append(project_location) from BMF_Priors.code.models.bmf_poisson_gamma import BMF_Poisson_Gamma from BMF_Priors.data.drug_sensitivity.load_data import load_gdsc_ic50_integer from BMF_Priors.experiments.convergence.convergence_experiment import measure_convergence_time import matplotlib.pyplot as plt ''' Run the experiment. ''' R, M = load_gdsc_ic50_integer() model_class = BMF_Poisson_Gamma settings = { 'R': R, 'M': M, 'K': 20, 'hyperparameters': { 'a':1., 'b':1. }, 'init': 'random', 'iterations': 200, } fout_performances = './results/performances_poisson_gamma.txt' fout_times = './results/times_poisson_gamma.txt' repeats = 10 performances, times = measure_convergence_time( repeats, model_class, settings, fout_performances, fout_times)