def test_set_descriptor():
"""
This test checks that the set_descriptor function works as expected.
"""
test_dir = os.path.dirname(os.path.realpath(__file__))
data_correct = np.load(test_dir + "/data/CN_isopent_light_UCM.npz")
data_incorrect = np.load(test_dir + "/data/local_slatm_ch4cn_light.npz")
descriptor_correct = data_correct["arr_0"]
descriptor_incorrect = data_incorrect["arr_0"]
estimator = MRMP()
assert estimator.representation == None
estimator.set_representations(representations=descriptor_correct)
assert np.all(estimator.representation == descriptor_correct)
# Pass a descriptor with the wrong shape
try:
estimator.set_representations(representations=descriptor_incorrect)
raise Exception
except InputError:
pass
def test_fit_2():
"""
This function tests a second way of fitting the descriptor:
The premade descriptors are stored in the estimator together with the energies.
The fit method is called with the indices of the molecules we want to fit.
"""
test_dir = os.path.dirname(os.path.realpath(__file__))
data = np.load(test_dir + "/data/CN_isopent_light_UCM.npz")
descriptor = data["arr_0"]
energies = data["arr_1"]
estimator = MRMP()
estimator.set_representations(representations=descriptor)
estimator.set_properties(energies)
idx = np.arange(0, 100)
estimator.fit(idx)
import os
## ------------- ** Loading the data ** ---------------
# The data loaded contains 100 samples of the CN + isobutane data set in unsorted CM representation
current_dir = os.path.dirname(os.path.realpath(__file__))
data = np.load(current_dir + '/../test/data/CN_isopent_light_UCM.npz')
representation = data["arr_0"]
energies = data["arr_1"]
## ------------- ** Setting up the estimator ** ---------------
estimator = MRMP(iterations=7000, l2_reg=0.0)
estimator.set_representations(representations=representation)
estimator.set_properties(energies)
## ------------- ** Fitting to the data ** ---------------
idx = np.arange(0, 100)
estimator.fit(idx)
## ------------- ** Predicting and scoring ** ---------------
score = estimator.score(idx)
print("The mean absolute error is %s kJ/mol." % (str(-score)))
energies_predict = estimator.predict(idx)