提交 de957570 authored 作者: slefrancois's avatar slefrancois

Corrected contradictions in sparse doc

上级 13b76018
...@@ -19,9 +19,9 @@ Note that you want SciPy >= 0.7.2 ...@@ -19,9 +19,9 @@ Note that you want SciPy >= 0.7.2
We describe the details of the compressed sparse matrix types. We describe the details of the compressed sparse matrix types.
``scipy.sparse.csc_matrix`` ``scipy.sparse.csc_matrix``
should be used if the columns are sparse. should be used if there are more rows than column (shape[0] > shape[1]).
``scipy.sparse.csr_matrix`` ``scipy.sparse.csr_matrix``
should be used if the rows are sparse. should be used if there are more columns than rows (shape[0] < shape[1]).
``scipy.sparse.lil_matrix`` ``scipy.sparse.lil_matrix``
is faster if we are modifying the array. After initial inserts, is faster if we are modifying the array. After initial inserts,
we can then convert to the appropriate sparse matrix format. we can then convert to the appropriate sparse matrix format.
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...@@ -80,7 +80,7 @@ the rows and with a matrix that have a lower number of rows, ``csr`` format is a ...@@ -80,7 +80,7 @@ the rows and with a matrix that have a lower number of rows, ``csr`` format is a
.. note:: .. note::
If shape[0] > shape[1], use ``csr`` format. Otherwise, use ``csc``. If shape[0] > shape[1], use ``csc`` format. Otherwise, use ``csr``.
Sometimes, since the sparse module is young, ops does not exist for both format. So here is Sometimes, since the sparse module is young, ops does not exist for both format. So here is
what may be the most relevent rule: what may be the most relevent rule:
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