Example #1
0
def generate_exponential_data(num_frames, num_measurements, scale):
    prior_pops = ensemble_fitter.get_prior_pops(num_frames)
    predictions = np.random.exponential(scale, size=(num_frames, num_measurements))
    return prior_pops, predictions
Example #2
0
def generate_gaussian_data(num_frames, num_measurements):
    prior_pops = ensemble_fitter.get_prior_pops(num_frames)
    predictions = np.random.normal(size=(num_frames, num_measurements))
    return prior_pops, predictions
Example #3
0
def generate_uniform_data(num_frames, num_measurements):
    prior_pops = ensemble_fitter.get_prior_pops(num_frames)
    predictions = np.random.uniform(0.0, 1.0, size=(num_frames, num_measurements))
    return prior_pops, predictions