def add_rows(self, matrix_, id2row):
"""
Adds rows to a peripheral space.
Args:
matrix_: Matrix type, the matrix of the elements to be added.
id2row: list, string identifiers of the rows to be added.
Modifies the current space by appending the new rows.
All operations of the core space are projected to the new rows.
Raises:
ValueError: if attempting to add row strings which are already
in the space.
matrix of the new data is not consistent in shape
with the current data matrix.
"""
try:
self._row2id = add_items_to_dict(self.row2id, id2row)
except ValueError:
raise ValueError("Found duplicate keys when appending rows to\
peripheral space.")
if matrix_.mat.shape[0] != len(id2row):
raise ValueError("Matrix shape inconsistent with no. of rows:%s %s"
% (matrix_.mat.shape, len(id2row)))
self._id2row = self.id2row + id2row
matrix_ = self._project_core_operations(matrix_)
self._cooccurrence_matrix = self._cooccurrence_matrix.vstack(matrix_)
assert_shape_consistent(self.cooccurrence_matrix, self.id2row,
self.id2column, self.row2id, self.column2id)
def add_rows(self, matrix_, id2row):
"""
Adds rows to a peripheral space.
Args:
matrix_: Matrix type, the matrix of the elements to be added.
id2row: list, string identifiers of the rows to be added.
Modifies the current space by appending the new rows.
All operations of the core space are projected to the new rows.
Raises:
ValueError: if attempting to add row strings which are already
in the space.
matrix of the new data is not consistent in shape
with the current data matrix.
"""
try:
self._row2id = add_items_to_dict(self.row2id, id2row)
except ValueError:
raise ValueError("Found duplicate keys when appending rows to\
peripheral space.")
if matrix_.mat.shape[0] != len(id2row):
raise ValueError("Matrix shape inconsistent with no. of rows:%s %s"
% (matrix_.mat.shape, len(id2row)))
self._id2row = self.id2row + id2row
matrix_ = self._project_core_operations(matrix_)
self._cooccurrence_matrix = self._cooccurrence_matrix.vstack(matrix_)
assert_shape_consistent(self.cooccurrence_matrix, self.id2row,
self.id2column, self.row2id, self.column2id)
def __init__(self, core_space, matrix_, id2row, row2id=None):
"""
Constructor.
Args:
core_space: Space type, the core space that this is peripheral to.
matrix_: Matrix type, the data matrix of the space
id2row: list, the row elements
row2id: dictionary, maps row strings to ids. Optional, built from
id2row by default.
Returns:
A peripheral semantic space (type PeripheralSpace) on which the
core space operations have been projected. Column indexing structures
and operations are taken over from the core space.
Raises:
TypeError: if matrix_ or core_space are not of the correct type
ValueError: if element shape is not consistent with
the size of matrix rows
if the matrix and the provided row and column
indexing structures are not of consistent shapes.
"""
assert_is_instance(matrix_, Matrix)
assert_is_instance(core_space, Space)
assert_is_instance(id2row, list)
# TODO: assert it is not a peripheral space here!
if row2id is None:
row2id = list2dict(id2row)
else:
assert_dict_match_list(row2id, id2row)
column2id = core_space.column2id
id2column = core_space.id2column
self._operations = list(core_space.operations)
self._row2id = row2id
self._id2row = id2row
self._column2id = column2id
self._id2column = id2column
self._cooccurrence_matrix = self._project_core_operations(matrix_)
assert_shape_consistent(self.cooccurrence_matrix, self._id2row,
self._id2column, self._row2id, self._column2id)
self._element_shape = (self._cooccurrence_matrix.shape[1],)
def __init__(self, core_space, matrix_, id2row, row2id=None):
"""
Constructor.
Args:
core_space: Space type, the core space that this is peripheral to.
matrix_: Matrix type, the data matrix of the space
id2row: list, the row elements
row2id: dictionary, maps row strings to ids. Optional, built from
id2row by default.
Returns:
A peripheral semantic space (type PeripheralSpace) on which the
core space operations have been projected. Column indexing structures
and operations are taken over from the core space.
Raises:
TypeError: if matrix_ or core_space are not of the correct type
ValueError: if element shape is not consistent with
the size of matrix rows
if the matrix and the provided row and column
indexing structures are not of consistent shapes.
"""
assert_is_instance(matrix_, Matrix)
assert_is_instance(core_space, Space)
assert_is_instance(id2row, list)
# TODO: assert it is not a peripheral space here!
if row2id is None:
row2id = list2dict(id2row)
else:
assert_dict_match_list(row2id, id2row)
column2id = core_space.column2id
id2column = core_space.id2column
self._operations = list(core_space.operations)
self._row2id = row2id
self._id2row = id2row
self._column2id = column2id
self._id2column = id2column
self._cooccurrence_matrix = self._project_core_operations(matrix_)
assert_shape_consistent(self.cooccurrence_matrix, self._id2row,
self._id2column, self._row2id, self._column2id)
self._element_shape = (self._cooccurrence_matrix.shape[1],)
def __init__(self, matrix_, id2row, id2column, row2id=None, column2id=None,
**kwargs):
"""
Constructor.
Args:
matrix_: Matrix type, the data matrix of the space
id2row: list, the row elements
id2column: list, the column elements
row2id: dictionary, maps row strings to ids. Optional, built from
id2row by default.
column2id: dictionary, maps col strings to ids. Optional, built
from id2column by default
operations: list of operations already performed on the input
matrix, Optional, by default set to empty.
element_shape: tuple of int, the shape on row elements. Optional,
by default row elements are one-dimensional and element_shape is
(no_cols, ). Used in 3D composition.
Returns:
A semantic space (type Space)
Raises:
TypeError: if matrix_ is not of the correct type
ValueError: if element shape is not consistent with
the size of matrix rows
if the matrix and the provided row and column
indexing structures are not of consistent shapes.
"""
assert_is_instance(matrix_, Matrix)
assert_valid_kwargs(kwargs, ["operations", "element_shape"])
assert_is_instance(id2row, list)
assert_is_instance(id2column, list)
if row2id is None:
row2id = list2dict(id2row)
else:
assert_dict_match_list(row2id, id2row)
if column2id is None:
column2id = list2dict(id2column)
else:
assert_dict_match_list(column2id, id2column)
assert_shape_consistent(matrix_, id2row, id2column, row2id, column2id)
self._cooccurrence_matrix = matrix_
self._row2id = row2id
self._id2row = id2row
self._column2id = column2id
self._id2column = id2column
if "operations" in kwargs:
self._operations = kwargs["operations"]
else:
self._operations = []
if "element_shape" in kwargs:
elem_shape = kwargs["element_shape"]
if prod(elem_shape) != self._cooccurrence_matrix.shape[1]:
raise ValueError("Trying to assign invalid element shape:\
element_shape: %s, matrix columns: %s"
% (str(elem_shape),
str(self._cooccurrence_matrix.shape[1])))
# NOTE: watch out here, can cause bugs, if we change the dimension
# of a regular space and we do not create a new space
self._element_shape = kwargs["element_shape"]
else:
self._element_shape = (self._cooccurrence_matrix.shape[1],)
def set_cooccurrence_matrix(self, matrix_):
assert_is_instance(matrix_, Matrix)
assert_shape_consistent(matrix_, self.row2id, self.id2row,
self.column2id, self.id2column)
self._cooccurrence_matrix = matrix_
def __init__(self,
matrix_,
id2row,
id2column,
row2id=None,
column2id=None,
operations=[],
element_shape=None):
"""
Constructor.
Args:
matrix_: Matrix type, the data matrix of the space
id2row: list, the row elements
id2column: list, the column elements
row2id: dictionary, maps row strings to ids. Optional, built from
id2row by default.
column2id: dictionary, maps col strings to ids. Optional, built
from id2column by default
operations: list of operations already performed on the input
matrix, Optional, by default set to empty.
element_shape: tuple of int, the shape on row elements. Optional,
by default row elements are one-dimensional and element_shape is
(no_cols, ). Used in 3D composition.
Returns:
A semantic space (type Space)
Raises:
TypeError: if matrix_ is not of the correct type
ValueError: if element shape is not consistent with
the size of matrix rows
if the matrix and the provided row and column
indexing structures are not of consistent shapes.
"""
assert_is_instance(matrix_, Matrix)
assert_is_instance(id2row, list)
assert_is_instance(id2column, list)
if row2id is None:
row2id = list2dict(id2row)
else:
assert_dict_match_list(row2id, id2row)
if column2id is None:
column2id = list2dict(id2column)
else:
assert_dict_match_list(column2id, id2column)
assert_shape_consistent(matrix_, id2row, id2column, row2id, column2id)
self._cooccurrence_matrix = matrix_
self._row2id = row2id
self._id2row = id2row
self._column2id = column2id
self._id2column = id2column
self._operations = operations
if element_shape:
if prod(element_shape) != self._cooccurrence_matrix.shape[1]:
raise ValueError("Trying to assign invalid element shape:\
element_shape: %s, matrix columns: %s" %
(str(element_shape),
str(self._cooccurrence_matrix.shape[1])))
# NOTE: watch out here, can cause bugs, if we change the dimension
# of a regular space and we do not create a new space
self._element_shape = element_shape
else:
self._element_shape = (self._cooccurrence_matrix.shape[1], )
def set_cooccurrence_matrix(self, matrix_):
assert_is_instance(matrix_, Matrix)
assert_shape_consistent(matrix_, self.row2id, self.id2row,
self.column2id, self.id2column)
self._cooccurrence_matrix = matrix_