GPy-ABCD 0.1.3

Usage

import GPy_ABCD

best_mods, all_mods, all_exprs = GPy_ABCD.find_best_model(X, Y,
    start_kernels = standard_start_kernels, p_rules = production_rules_all,
    restarts = 5, utility_function = 'BIC', rounds = 2, buffer = 4,
    verbose = False, parallel = True)


# Typical output printout

for mod_depth in all_mods: print(', '.join([str(mod.kernel_expression) for mod in mod_depth]) + f'\n{len(mod_depth)}')

from matplotlib import pyplot as plt
for bm in best_mods:
    print(bm.kernel_expression)
    print(bm.model.kern)
    print(bm.model.log_likelihood())
    print(bm.cached_utility_function)
    bm.model.plot()
    print(bm.interpret())

predict_X = np.linspace(FROM, TO, BY)[:, None]
preds = best_mods[0].predict(predict_X)
print(preds)

plt.show()

Note: if the parallel argument is True then the function should be called from within a if __name__ == '__main__':

Installation

pip install gpy_abcd