def test_get_depth_threshold_mask_connections_both(self):
conn = {
0: {
1: '1'
},
1: {
0: '1',
2: '1'
},
2: {
1: '1',
3: '1'
},
3: {
2: '1',
4: '1'
},
4: {
3: '1'
},
}
res = get_depth_threshold_mask_connections(conn,
min_depth=2,
max_depth=2)
expected = numpy.array([
[False, False, True, False, False],
[False, False, False, True, False],
[True, False, False, False, True],
[False, True, False, False, False],
[False, False, True, False, False],
])
try:
numpy.testing.assert_equal(res, expected)
except AssertionError as e:
self.fail(e)
def _para_transform(self, X, y=None):
'''
A single instance of the transform procedure
This is formulated in a way that the transformations can be done
completely parallel with map.
Parameters
----------
X : object
An object to use for the transform
Returns
-------
value : array, shape=(n_atoms, len(self._elements) * self.segments)
The features extracted from the molecule
'''
if self._elements is None:
msg = "This %s instance is not fitted yet. Call 'fit' first."
raise ValueError(msg % type(self).__name__)
try:
smoothing_func = SMOOTHING_FUNCTIONS[self.smoothing]
except KeyError:
msg = "The value '%s' is not a valid spacing type."
raise KeyError(msg % self.smoothing)
pair_idxs = {key: i for i, key in enumerate(self._elements)}
data = self.convert_input(X)
vector = numpy.zeros((len(data.elements), len(self._elements),
3, self.segments))
try:
theta_func = SPACING_FUNCTIONS[self.spacing]
except KeyError:
msg = "The value '%s' is not a valid spacing type."
raise KeyError(msg % self.spacing)
theta = numpy.linspace(theta_func(self.start), theta_func(self.end),
self.segments)
mat = get_depth_threshold_mask_connections(data.connections,
max_depth=self.max_depth)
coords = numpy.array(data.coords)
distances = coords - coords[:, None, :]
for i, ele1 in enumerate(data.elements):
for j, ele2 in enumerate(data.elements):
if i == j or not mat[i, j]:
continue
for k in xrange(3):
diff = theta - theta_func(distances[i, j, k])
value = smoothing_func(self.slope * diff)
vector[i, pair_idxs[ele2], k] += value
return vector.reshape(len(data.elements), -1)
def test_get_depth_threshold_mask_connections_all(self):
conn = {
0: {1: '1'},
1: {0: '1'},
2: {3: '1'},
3: {2: '1'},
}
res = get_depth_threshold_mask_connections(conn, max_depth=0)
try:
numpy.testing.assert_equal(res,
numpy.ones((len(conn), len(conn))))
except AssertionError as e:
self.fail(e)
def test_get_depth_threshold_mask_connections_min(self):
conn = {
0: {1: '1'},
1: {0: '1', 2: '1'},
2: {1: '1', 3: '1'},
3: {2: '1'},
}
res = get_depth_threshold_mask_connections(conn, min_depth=2)
expected = numpy.array([
[False, False, True, True],
[False, False, False, True],
[True, False, False, False],
[True, True, False, False],
])
try:
numpy.testing.assert_equal(res, expected)
except AssertionError as e:
self.fail(e)