def testSyntheticLogGaussianCoxModel(self):
num_train_points = 100
dataset = data.synthetic_log_gaussian_cox_process()
self.assertEqual((num_train_points, 2), dataset['train_locations'].shape)
self.assertEqual((num_train_points,), dataset['train_extents'].shape)
self.assertEqual((num_train_points,), dataset['train_counts'].shape)
def synthetic_log_gaussian_cox_process():
"""Log-Gaussian Cox Process model.
This dataset was simulated by constructing a 10 by 10 grid of equidistant 2D
locations with spacing = 1, and then sampling from the prior to determine the
counts at those locations.
Returns:
target: StanModel.
"""
dataset = data.synthetic_log_gaussian_cox_process()
return log_gaussian_cox_process.log_gaussian_cox_process(**dataset)
def __init__(self):
dataset = data.synthetic_log_gaussian_cox_process()
super(SyntheticLogGaussianCoxProcess,
self).__init__(name='synthetic_log_gaussian_cox_process',
pretty_name='Synthetic Log-Gaussian Cox Process',
**dataset)