def test_eigen(self):
a = SineMatrix(input_type=H_INPUT, eigen=True)
res = a.fit_transform([H2])
expected = numpy.array([[0.975557, 0.024443]])
try:
numpy.testing.assert_array_almost_equal(res, expected)
except AssertionError as e:
self.fail(e)
def test_large_to_small_transform(self):
a = SineMatrix(input_type=H_INPUT)
a.fit([H2])
res = a.transform([H])
expected = numpy.array([[0.5, 0., 0., 0.]])
try:
numpy.testing.assert_array_almost_equal(res, expected)
except AssertionError as e:
self.fail(e)
def test_eigen(self):
a = SineMatrix(input_type=H_INPUT, eigen=True)
res = a.fit_transform([H2])
expected = numpy.array([[0.975557, 0.024443]])
try:
numpy.testing.assert_array_almost_equal(
res,
expected)
except AssertionError as e:
self.fail(e)
def test_large_to_small_transform(self):
a = SineMatrix(input_type=H_INPUT)
a.fit([H2])
res = a.transform([H])
expected = numpy.array([[0.5, 0., 0., 0.]])
try:
numpy.testing.assert_array_almost_equal(
res,
expected)
except AssertionError as e:
self.fail(e)
0: {1: '1'},
1: {0: '1'},
}
H2_UNIT = numpy.array([
[2., .5, 0.],
[.25, 1., 0.],
[0., .3, 1.],
])
radius = 4.1
input_type = ("elements", "coords", "unit_cell")
X = (H2_ELES, H2_COORDS, H2_UNIT)
if __name__ == "__main__":
trans = EwaldSumMatrix(input_type=input_type, G_max=3.2, L_max=2.1)
res = trans.fit_transform([X])
print(res)
trans = SineMatrix(input_type=input_type)
res = trans.fit_transform([X])
print(res)
# Example of generallized crystal
# Any transformer can be used as it just expands the molecule using the
# unit cell and coordinates.
cm = CoulombMatrix(input_type=input_type)
trans = GenerallizedCrystal(transformer=cm,
radius=radius)
res = trans.fit_transform([X])
print(res)
def test_transform_before_fit(self):
a = SineMatrix()
with self.assertRaises(ValueError):
a.transform([H])
def test_small_to_large_transform(self):
a = SineMatrix(input_type=H_INPUT)
a.fit([H])
with self.assertRaises(ValueError):
a.transform([H2])
def test_fit(self):
a = SineMatrix()
a.fit([(H2_ELES, H2_COORDS)])
self.assertEqual(a._max_size, 2)
def test_transform_before_fit(self):
a = SineMatrix()
with self.assertRaises(ValueError):
a.transform([H])
def test_small_to_large_transform(self):
a = SineMatrix(input_type=H_INPUT)
a.fit([H])
with self.assertRaises(ValueError):
a.transform([H2])
def test_fit(self):
a = SineMatrix()
a.fit([(H2_ELES, H2_COORDS)])
self.assertEqual(a._max_size, 2)