SquareTaxaMatrix#

class pybrops.core.mat.SquareTaxaMatrix.SquareTaxaMatrix[source]#

Bases: SquareMatrix, TaxaMatrix

An abstract class for matrix wrapper objects with square taxa metadata.

The purpose of this abstract class is to merge the following interfaces:

SquareMatrix

TaxaMatrix

Methods

`adjoin`	Add additional elements to the end of the Matrix along an axis.
`adjoin_taxa`	Add additional elements to the end of the Matrix along the taxa axis.
`append`	Append values to the Matrix.
`append_taxa`	Append values to the Matrix along the taxa axis.
`concat`	Concatenate matrices together along an axis.
`concat_taxa`	Concatenate list of Matrix together along the taxa axis.
`copy`	Make a shallow copy of the Matrix.
`deepcopy`	Make a deep copy of the Matrix.
`delete`	Delete sub-arrays along an axis.
`delete_taxa`	Delete sub-arrays along the taxa axis.
`from_hdf5`	Read an object from an HDF5 file.
`group`	Sort the GroupableMatrix along an axis, then populate grouping indices.
`group_taxa`	Sort the Matrix along the taxa axis, then populate grouping indices for the taxa axis.
`incorp`	Incorporate values along the given axis before the given indices.
`incorp_taxa`	Incorporate values along the taxa axis before the given indices.
`insert`	Insert values along the given axis before the given indices.
`insert_taxa`	Insert values along the taxa axis before the given indices.
`is_grouped`	Determine whether the Matrix has been sorted and grouped.
`is_grouped_taxa`	Determine whether the Matrix has been sorted and grouped along the taxa axis.
`is_square`	Determine whether the axes lengths for the square axes are identical.
`is_square_taxa`	Determine whether the taxa axes lengths for the square axes are identical.
`lexsort`	Perform an indirect stable sort using a sequence of keys.
`lexsort_taxa`	Perform an indirect stable sort using a sequence of keys along the taxa axis.
`remove`	Remove sub-arrays along an axis.
`remove_taxa`	Remove sub-arrays along the taxa axis.
`reorder`	Reorder elements of the Matrix using an array of indices.
`reorder_taxa`	Reorder elements of the Matrix along the taxa axis using an array of indices.
`select`	Select certain values from the matrix.
`select_taxa`	Select certain values from the Matrix along the taxa axis.
`sort`	Sort slements of the Matrix using a sequence of keys.
`sort_taxa`	Sort slements of the Matrix along the taxa axis using a sequence of keys.
`to_hdf5`	Write an object to an HDF5 file.
`ungroup`	Ungroup the GroupableMatrix along an axis by removing grouping metadata.
`ungroup_taxa`	Ungroup the TaxaMatrix along the taxa axis by removing taxa group metadata.

Attributes

`mat`	Pointer to raw matrix object.
`mat_ndim`	Number of dimensions of the raw matrix.
`mat_shape`	Shape of the raw matrix.
`nsquare`	Number of axes that are square.
`nsquare_taxa`	Number of taxa axes that are square.
`ntaxa`	Number of taxa.
`square_axes`	Axis indices for axes that are square.
`square_axes_len`	Axis lengths for axes that are square.
`square_taxa_axes`	Axis indices for taxa axes that are square.
`square_taxa_axes_len`	Axis lengths for axes that are square.
`taxa`	Taxa label.
`taxa_axis`	Axis along which taxa are stored.
`taxa_grp`	Taxa group label.
`taxa_grp_len`	Taxa group length.
`taxa_grp_name`	Taxa group name.
`taxa_grp_spix`	Taxa group stop index.
`taxa_grp_stix`	Taxa group start index.

abstract __add__(value)#

Elementwise add matrices

Parameters:: value (object) – Object which to add.
Returns:: out – An object resulting from the addition.
Return type:: object

abstract __mul__(value)#

Elementwise multiply matrices

Parameters:: value (object) – Object which to multiply.
Returns:: out – An object resulting from the multiplication.
Return type:: object

abstract adjoin(values, axis, **kwargs)#

Add additional elements to the end of the Matrix along an axis.

Parameters:

values (Matrix or numpy.ndarray) – Values are appended to append to the Matrix.
axis (int) – The axis along which values are adjoined.
kwargs (dict) – Additional keyword arguments.

Returns:

out – A copy of mat with values appended to axis. Note that adjoin does not occur in-place: a new Matrix is allocated and filled.

Return type:

Matrix

abstract adjoin_taxa(values, taxa, taxa_grp, **kwargs)#

Add additional elements to the end of the Matrix along the taxa axis.

Parameters:

values (Matrix, numpy.ndarray) – Values are appended to adjoin to the Matrix.
taxa (numpy.ndarray) – Taxa names to adjoin to the Matrix.
taxa_grp (numpy.ndarray) – Taxa groups to adjoin to the Matrix.
kwargs (dict) – Additional keyword arguments.

Returns:

out – A copy of TaxaMatrix with values appended to axis. Note that adjoin does not occur in-place: a new TaxaMatrix is allocated and filled.

Return type:

TaxaMatrix

abstract append(values, axis, **kwargs)#

Append values to the Matrix.

Parameters:

values (Matrix, numpy.ndarray) – Values are appended to append to the matrix.
axis (int) – The axis along which values are appended.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract append_taxa(values, taxa, taxa_grp, **kwargs)#

Append values to the Matrix along the taxa axis.

Parameters:

values (Matrix, numpy.ndarray) – Values are appended to append to the matrix.
taxa (numpy.ndarray) – Taxa names to append to the Matrix.
taxa_grp (numpy.ndarray) – Taxa groups to append to the Matrix.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract classmethod concat(mats, axis, **kwargs)#

Concatenate matrices together along an axis.

Parameters:

mats (Sequence of Matrix) – List of Matrix to concatenate. The matrices must have the same shape, except in the dimension corresponding to axis.
axis (int) – The axis along which the arrays will be joined.
kwargs (dict) – Additional keyword arguments

Returns:

out – The concatenated matrix. Note that concat does not occur in-place: a new Matrix is allocated and filled.

Return type:

Matrix

abstract classmethod concat_taxa(mats, **kwargs)#

Concatenate list of Matrix together along the taxa axis.

Parameters:

mats (Sequence of Matrix) – List of Matrix to concatenate. The matrices must have the same shape, except in the dimension corresponding to axis.
kwargs (dict) – Additional keyword arguments

Returns:

out – The concatenated TaxaMatrix. Note that concat does not occur in-place: a new TaxaMatrix is allocated and filled.

Return type:

TaxaMatrix

abstract copy()#

Make a shallow copy of the Matrix.

Returns:: out – A shallow copy of the original Matrix.
Return type:: Matrix

abstract deepcopy(memo)#

Make a deep copy of the Matrix.

Parameters:: memo (dict) – Dictionary of memo metadata.
Returns:: out – A deep copy of the original Matrix.
Return type:: Matrix

abstract delete(obj, axis, **kwargs)#

Delete sub-arrays along an axis.

Parameters:

obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.
axis (int) – The axis along which to delete the subarray defined by obj.
kwargs (dict) – Additional keyword arguments.

Returns:

out – A Matrix with deleted elements. Note that concat does not occur in-place: a new Matrix is allocated and filled.

Return type:

Matrix

abstract delete_taxa(obj, **kwargs)#

Delete sub-arrays along the taxa axis.

Parameters:

obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.
kwargs (dict) – Additional keyword arguments.

Returns:

out – A TaxaMatrix with deleted elements. Note that concat does not occur in-place: a new TaxaMatrix is allocated and filled.

Return type:

TaxaMatrix

abstract classmethod from_hdf5(filename, groupname)#

Read an object from an HDF5 file.

Parameters:

filename (str, Path, h5py.File) – If str, an HDF5 file name from which to read. If Path, an HDF5 file name from which to read. If h5py.File, an opened HDF5 file from which to read.
groupname (str, None) – If str, an HDF5 group name under which object data is stored. If None, object is read from base HDF5 group.

Returns:

out – An object read from an HDF5 file.

Return type:

HDF5InputOutput

abstract group(axis, **kwargs)#

Sort the GroupableMatrix along an axis, then populate grouping indices.

Parameters:

axis (int) – The axis along which values are grouped.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract group_taxa(**kwargs)#

Sort the Matrix along the taxa axis, then populate grouping indices for the taxa axis.

Parameters:: kwargs (dict) – Additional keyword arguments.
Return type:: None

abstract incorp(obj, values, axis, **kwargs)#

Incorporate values along the given axis before the given indices.

Parameters:

obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is incorporated.
values (numpy.ndarray) – Values to incorporate into the matrix.
axis (int) – The axis along which values are incorporated.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract incorp_taxa(obj, values, taxa, taxa_grp, **kwargs)#

Incorporate values along the taxa axis before the given indices.

Parameters:

obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is incorporated.
values (Matrix, numpy.ndarray) – Values to incorporate into the matrix.
taxa (numpy.ndarray) – Taxa names to incorporate into the Matrix.
taxa_grp (numpy.ndarray) – Taxa groups to incorporate into the Matrix.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract insert(obj, values, axis, **kwargs)#

Insert values along the given axis before the given indices.

Parameters:

obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is inserted.
values (ArrayLike) – Values to insert into the matrix.
axis (int) – The axis along which values are inserted.
kwargs (dict) – Additional keyword arguments.

Returns:

out – A Matrix with values inserted. Note that insert does not occur in-place: a new Matrix is allocated and filled.

Return type:

Matrix

abstract insert_taxa(obj, values, taxa, taxa_grp, **kwargs)#

Insert values along the taxa axis before the given indices.

Parameters:

obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is inserted.
values (Matrix, numpy.ndarray) – Values to insert into the matrix.
taxa (numpy.ndarray) – Taxa names to insert into the Matrix.
taxa_grp (numpy.ndarray) – Taxa groups to insert into the Matrix.
kwargs (dict) – Additional keyword arguments.

Returns:

out – A TaxaMatrix with values inserted. Note that insert does not occur in-place: a new TaxaMatrix is allocated and filled.

Return type:

TaxaMatrix

abstract is_grouped(axis, **kwargs)#

Determine whether the Matrix has been sorted and grouped.

Parameters:

axis (int) – Axis along which to determine whether elements have been sorted and grouped.
kwargs (dict) – Additional keyword arguments.

Returns:

grouped – True or False indicating whether the Matrix has been sorted and grouped.

Return type:

bool

abstract is_grouped_taxa(**kwargs)#

Determine whether the Matrix has been sorted and grouped along the taxa axis.

Parameters:: kwargs (dict) – Additional keyword arguments.
Returns:: grouped – True or False indicating whether the Matrix has been sorted and grouped.
Return type:: bool

abstract is_square()#

Determine whether the axes lengths for the square axes are identical.

Returns:: out – True if all square axes are the same length. False if not all square axes are the same length.
Return type:: bool

abstract is_square_taxa()[source]#

Determine whether the taxa axes lengths for the square axes are identical.

Returns:: out – True if all square taxa axes are the same length. False if not all square taxa axes are the same length.
Return type:: bool

abstract lexsort(keys, axis, **kwargs)#

Perform an indirect stable sort using a sequence of keys.

Parameters:

keys (A (k, N) array or tuple containing k (N,)-shaped sequences) – The k different columns to be sorted. The last column (or row if keys is a 2D array) is the primary sort key.
axis (int) – Axis to be indirectly sorted.
kwargs (dict) – Additional keyword arguments.

Returns:

indices – Array of indices that sort the keys along the specified axis.

Return type:

A (N,) ndarray of ints

abstract lexsort_taxa(keys, **kwargs)#

Perform an indirect stable sort using a sequence of keys along the taxa axis.

Parameters:

keys (A (k, N) array or tuple containing k (N,)-shaped sequences) – The k different columns to be sorted. The last column (or row if keys is a 2D array) is the primary sort key.
kwargs (dict) – Additional keyword arguments.

Returns:

indices – Array of indices that sort the keys along the specified axis.

Return type:

A (N,) ndarray of ints

abstract property mat: object#: Pointer to raw matrix object.

abstract property mat_ndim: int#: Number of dimensions of the raw matrix.

abstract property mat_shape: tuple#: Shape of the raw matrix.

abstract property nsquare: int#: Number of axes that are square.

abstract property nsquare_taxa: int#: Number of taxa axes that are square.

abstract property ntaxa: int#: Number of taxa.

abstract remove(obj, axis, **kwargs)#

Remove sub-arrays along an axis.

Parameters:

obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.
axis (int) – The axis along which to remove the subarray defined by obj.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract remove_taxa(obj, **kwargs)#

Remove sub-arrays along the taxa axis.

Parameters:

obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract reorder(indices, axis, **kwargs)#

Reorder elements of the Matrix using an array of indices. Note this modifies the Matrix in-place.

Parameters:

indices (A (N,) ndarray of ints, Sequence of ints) – Array of indices that reorder the matrix along the specified axis.
axis (int) – Axis to be reordered.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract reorder_taxa(indices, **kwargs)#

Reorder elements of the Matrix along the taxa axis using an array of indices. Note this modifies the Matrix in-place.

Parameters:

indices (A (N,) ndarray of ints) – Array of indices that reorder the matrix along the specified axis.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract select(indices, axis, **kwargs)#

Select certain values from the matrix.

Parameters:

indices (ArrayLike (Nj, ...)) – The indices of the values to select.
axis (int) – The axis along which values are selected.
kwargs (dict) – Additional keyword arguments.

Returns:

out – The output matrix with values selected. Note that select does not occur in-place: a new Matrix is allocated and filled.

Return type:

Matrix

abstract select_taxa(indices, **kwargs)#

Select certain values from the Matrix along the taxa axis.

Parameters:

indices (array_like (Nj, ...)) – The indices of the values to select.
kwargs (dict) – Additional keyword arguments.

Returns:

out – The output TaxaMatrix with values selected. Note that select does not occur in-place: a new TaxaMatrix is allocated and filled.

Return type:

TaxaMatrix

abstract sort(keys, axis, **kwargs)#

Sort slements of the Matrix using a sequence of keys. Note this modifies the Matrix in-place.

Parameters:

keys (A (k, N) array or tuple containing k (N,)-shaped sequences) – The k different columns to be sorted. The last column (or row if keys is a 2D array) is the primary sort key.
axis (int) – Axis to be indirectly sorted.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract sort_taxa(keys, **kwargs)#

Sort slements of the Matrix along the taxa axis using a sequence of keys. Note this modifies the Matrix in-place.

Parameters:

keys (A (k, N) array or tuple containing k (N,)-shaped sequences) – The k different columns to be sorted. The last column (or row if keys is a 2D array) is the primary sort key.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract property square_axes: tuple#: Axis indices for axes that are square.

abstract property square_axes_len: tuple#: Axis lengths for axes that are square.

abstract property square_taxa_axes: tuple#: Axis indices for taxa axes that are square.

abstract property square_taxa_axes_len: tuple#: Axis lengths for axes that are square.

abstract property taxa: object#: Taxa label.

abstract property taxa_axis: int#: Axis along which taxa are stored.

abstract property taxa_grp: object#: Taxa group label.

abstract property taxa_grp_len: object#: Taxa group length.

abstract property taxa_grp_name: object#: Taxa group name.

abstract property taxa_grp_spix: object#: Taxa group stop index.

abstract property taxa_grp_stix: object#: Taxa group start index.

abstract to_hdf5(filename, groupname, overwrite)#

Write an object to an HDF5 file.

Parameters:

filename (str, Path, h5py.File) – If str, an HDF5 file name to which to write. If Path, an HDF5 file path to which to write. If h5py.File, an opened HDF5 file to which to write.
groupname (str, None) – If str, an HDF5 group name under which object data is stored. If None, object is written to the base HDF5 group.
overwrite (bool) – Whether to overwrite values in an HDF5 file if a field already exists.

Return type:

None

abstract ungroup(axis, **kwargs)#

Ungroup the GroupableMatrix along an axis by removing grouping metadata.

Parameters:

axis (int) – The axis along which values should be ungrouped.
kwargs (dict) – Additional keyword arguments.

Return type:

None

abstract ungroup_taxa(**kwargs)#

Ungroup the TaxaMatrix along the taxa axis by removing taxa group metadata.

Parameters:: kwargs (dict) – Additional keyword arguments.
Return type:: None