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Interaction with scipy.sparse matrices.
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Currently only includes to_coo helpers.
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é )Ú annotations)Ú TYPE_CHECKINGÚIterableN)Úlib)Ú
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IndexLabelÚnpt)Únotna)Ú factorize)Ú
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MultiIndex)ÚSeriesr ©ÚpartsZwholec C sH t |}dd | D } t j| t kr.tdt j| |krDtdd S )Nc S s g | ] }t |qS © )Úset©Ú.0Úxr r ú]d:\z\workplace\vscode\pyvenv\venv\Lib\site-packages\pandas/core/arrays/sparse/scipy_sparse.pyÚ
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<listcomp>! s z'_check_is_partition.<locals>.<listcomp>z4Is not a partition because intersection is not null.z2Is not a partition because union is not the whole.)r Ú intersectionÚ
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For a MultiIndexed sparse Series `ss`, return `ax_coords` and `ax_labels`,
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where `ax_coords` are the coordinates along one of the two axes of the
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destination sparse matrix, and `ax_labels` are the labels from `ss`' Index
|
which correspond to these coordinates.
|
|
Parameters
|
----------
|
ss : Series
|
levels : tuple/list
|
valid_ilocs : numpy.ndarray
|
Array of integer positions of valid values for the sparse matrix in ss.
|
sort_labels : bool, default False
|
Sort the axis labels before forming the sparse matrix. When `levels`
|
refers to a single level, set to True for a faster execution.
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|
Returns
|
-------
|
ax_coords : numpy.ndarray (axis coordinates)
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ax_labels : list (axis labels)
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é r c s g | ]} j |¡ ¡ qS r )ÚindexZget_level_valuesZto_numpy)r Zlvl©Ússr r r L s z#_levels_to_axis.<locals>.<listcomp>)Úsort)Úlenr Úcodesr r Zfast_zipr Útolist)r! r r r Z ax_coordsZ ax_labelsZ levels_valuesr$ r r r Ú_levels_to_axis( s ÿr& ©r ©r zatuple[np.ndarray, npt.NDArray[np.intp], npt.NDArray[np.intp], list[IndexLabel], list[IndexLabel]])Ú
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For an arbitrary MultiIndexed sparse Series return (v, i, j, ilabels,
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jlabels) where (v, (i, j)) is suitable for passing to scipy.sparse.coo
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constructor, and ilabels and jlabels are the row and column labels
|
respectively.
|
|
Parameters
|
----------
|
ss : Series
|
row_levels : tuple/list
|
column_levels : tuple/list
|
sort_labels : bool, default False
|
Sort the row and column labels before forming the sparse matrix.
|
When `row_levels` and/or `column_levels` refer to a single level,
|
set to `True` for a faster execution.
|
|
Returns
|
-------
|
values : numpy.ndarray
|
Valid values to populate a sparse matrix, extracted from
|
ss.
|
i_coords : numpy.ndarray (row coordinates of the values)
|
j_coords : numpy.ndarray (column coordinates of the values)
|
i_labels : list (row labels)
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j_labels : list (column labels)
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)r )
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}
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Convert a sparse Series to a scipy.sparse.coo_matrix using index
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levels row_levels, column_levels as the row and column
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labels respectively. Returns the sparse_matrix, row and column labels.
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r Né z-to_coo requires MultiIndex with nlevels >= 2.zADuplicate index entries are not allowed in to_coo transformation.c s g | ]} j |¡qS r ©r Z_get_level_numberr r r r r ¤ s z(sparse_series_to_coo.<locals>.<listcomp>c s g | ]} j |¡qS r r2 r r r r r ¥ s )r) r* r )Úshape) Ú scipy.sparser r, r Z is_uniquer0 ÚsparseZ
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coo_matrixr# ) r! r) r* r ÚscipyÚvÚiÚjÚrowsÚcolumnsZ sparse_matrixr r r Úsparse_series_to_coo s( ÿ ÿ
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Convert a scipy.sparse.coo_matrix to a Series with type sparse.
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|
Parameters
|
----------
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A : scipy.sparse.coo_matrix
|
dense_index : bool, default False
|
|
Returns
|
-------
|
Series
|
|
Raises
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------
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TypeError if A is not a coo_matrix
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