def _join_array_by_indices(left, right, lefti, righti, string_cols=None):
"""Join (horizontally) two arrays, taking pairs of rows given in indices
"""
def prepare(arr, inds, str_cols):
try:
newarr = arr[inds]
except IndexError:
newarr = np.full_like(arr, np.nan)
else:
empty = np.full(arr.shape[1], np.nan)
if str_cols:
assert arr.dtype == object
empty = empty.astype(object)
empty[str_cols] = ''
newarr[inds == -1] = empty
return newarr
left_width = left.shape[1]
str_left = [i for i in string_cols or () if i < left_width]
str_right = [
i - left_width for i in string_cols or () if i >= left_width
]
res = hstack((prepare(left, lefti,
str_left), prepare(right, righti, str_right)))
return res
def _setup_plot(self, new=False):
emb_x, emb_y = self.embedding[:, 0], self.embedding[:, 1]
coords = np.vstack((emb_x, emb_y)).T
data = self.data
primitive_metas = tuple(a for a in data.domain.metas
if a.is_primitive())
keys = [k for k, a in enumerate(data.domain.metas) if a.is_primitive()]
data_metas = data.metas[:, keys].astype(float)
attributes = self.data.domain.attributes + (self.variable_x, self.variable_y) + \
primitive_metas
domain = Domain(attributes=attributes,
class_vars=self.data.domain.class_vars)
if data_metas is not None:
data_x = (self.data.X, coords, data_metas)
else:
data_x = (self.data.X, coords)
data = Table.from_numpy(domain, X=hstack(data_x), Y=self.data.Y)
subset_data = data[
self._subset_mask] if self._subset_mask is not None else None
self.graph.new_data(data, subset_data=subset_data, new=new)
self.graph.update_data(self.variable_x, self.variable_y, True)
self.connect_pairs()
def test_hstack(self):
numpy = np.array([[1., 2.], [3., 4.]])
csr = sp.csr_matrix(numpy)
csc = sp.csc_matrix(numpy)
self.assertCorrectArrayType(hstack([numpy, numpy]),
shape=(2, 4),
sparsity="dense")
self.assertCorrectArrayType(hstack([csr, numpy]),
shape=(2, 4),
sparsity="sparse")
self.assertCorrectArrayType(hstack([numpy, csc]),
shape=(2, 4),
sparsity="sparse")
self.assertCorrectArrayType(hstack([csc, csr]),
shape=(2, 4),
sparsity="sparse")
def test_hstack(self):
numpy = np.array([[1., 2.], [3., 4.]])
csr = sp.csr_matrix(numpy)
csc = sp.csc_matrix(numpy)
self.assertCorrectArrayType(
hstack([numpy, numpy]),
shape=(2, 4), sparsity="dense")
self.assertCorrectArrayType(
hstack([csr, numpy]),
shape=(2, 4), sparsity="sparse")
self.assertCorrectArrayType(
hstack([numpy, csc]),
shape=(2, 4), sparsity="sparse")
self.assertCorrectArrayType(
hstack([csc, csr]),
shape=(2, 4), sparsity="sparse")
def construct_output_data_table(embedded_images, embeddings):
if sparse.issparse(embedded_images.X):
X = util.hstack((embedded_images.X, embeddings))
else:
X = util.hstack((embedded_images.X, embeddings))
Y = embedded_images.Y
attributes = [
ContinuousVariable.make('n{:d}'.format(d))
for d in range(embeddings.shape[1])
]
attributes = list(embedded_images.domain.attributes) + attributes
domain = Domain(attributes=attributes,
class_vars=embedded_images.domain.class_vars,
metas=embedded_images.domain.metas)
return Table(domain, X, Y, embedded_images.metas)
def _setup_plot(self, new=False):
emb_x, emb_y = self.embedding[:, 0], self.embedding[:, 1]
coords = np.vstack((emb_x, emb_y)).T
data = self.data
attributes = data.domain.attributes + (self.variable_x, self.variable_y)
domain = Domain(attributes=attributes,
class_vars=data.domain.class_vars,
metas=data.domain.metas)
data = Table.from_numpy(domain, X=hstack((data.X, coords)),
Y=data.Y, metas=data.metas)
subset_data = data[self._subset_mask] if self._subset_mask is not None else None
self.graph.new_data(data, subset_data=subset_data, new=new)
self.graph.update_data(self.variable_x, self.variable_y, True)
self.connect_pairs()
def _setup_plot(self, new=False):
emb_x, emb_y = self.embedding[:, 0], self.embedding[:, 1]
coords = np.vstack((emb_x, emb_y)).T
data = self.data
attributes = data.domain.attributes + (self.variable_x, self.variable_y)
domain = Domain(attributes=attributes,
class_vars=data.domain.class_vars,
metas=data.domain.metas)
data = Table.from_numpy(domain, X=hstack((data.X, coords)),
Y=data.Y, metas=data.metas)
subset_data = data[self._subset_mask] if self._subset_mask is not None else None
self.graph.new_data(data, subset_data=subset_data, new=new)
self.graph.update_data(self.variable_x, self.variable_y, True)
self.connect_pairs()
def _join_array_by_indices(left, right, indices, string_cols=None):
"""Join (horizontally) two arrays, taking pairs of rows given in indices
"""
def prepare(arr, inds, str_cols):
try:
newarr = arr[inds]
except IndexError:
newarr = np.full_like(arr, np.nan)
else:
empty = np.full(arr.shape[1], np.nan)
if str_cols:
assert arr.dtype == object
empty = empty.astype(object)
empty[str_cols] = ''
newarr[inds == -1] = empty
return newarr
left_width = left.shape[1]
str_left = [i for i in string_cols or () if i < left_width]
str_right = [i - left_width for i in string_cols or () if i >= left_width]
res = hstack((prepare(left, indices[0], str_left),
prepare(right, indices[1], str_right)))
return res
