Docstring markup fixes

src/sage/matrix/matrix_cmr_sparse.pyx

@@ -2533,9 +2533,9 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
 
         .. SEEALSO:: :meth:`binary_pivot`, :meth:`binary_pivots`, :meth:`ternary_pivots`
 
-        EXAMPLES::
+        EXAMPLES:
 
-        Single pivot on a `1`-entry:
+        Single pivot on a `1`-entry::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 10, 10, sparse=True), [
@@ -2572,7 +2572,7 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
             [ 1 -1  0  0  0  1  1 -1  1  1]
             [ 1  0  0  0  0 -1  0 -1  0  0]
 
-        Single pivot on a `-1`-entry:
+        Single pivot on a `-1`-entry::
 
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 10, 10, sparse=True), [
             ....:     [-1,  1, 0, 0, 0, -1, 0,  1, 0, 0],
@@ -2744,8 +2744,10 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
 
         A matrix `M` of rank `r` is equimodular with determinant gcd `k`
         if the following two conditions are satisfied:
+
         - for some column basis `B` of `M`, the greatest common divisor of
           the determinants of all `r`-by-`r` submatrices of `B` is `k`;
+
         - the matrix `X` such that `M=BX` is totally unimodular.
 
         OUTPUT:
@@ -2800,8 +2802,10 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
         the same determinant gcd `k`.
         A matrix `M` of rank-`r` is `k`-modular if the following two conditions
         are satisfied:
+
         - for some column basis `B` of `M`, the greatest common divisor of the
           determinants of all `r`-by-`r` submatrices of `B` is `k`;
+
         - the matrix `X` such that `M=BX` is totally unimodular.
 
         OUTPUT:
@@ -2850,8 +2854,10 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
 
         A matrix `M` of rank-`r` is `k`-equimodular if the following two
         conditions are satisfied:
+
         - for some column basis `B` of `M`, the greatest common divisor of
           the determinants of all `r`-by-`r` submatrices of `B` is `k`;
+
         - the matrix `X` such that `M=BX` is totally unimodular.
 
         If the matrix has full row rank, it is `k`-equimodular if
@@ -3165,19 +3171,21 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
     def is_network_matrix(self, *, time_limit=60.0, certificate=False,
                           row_keys=None, column_keys=None):
         r"""
-        Return whether the matrix ``self`` over `\GF{3}` or `QQ` is a network matrix.
+        Return whether the matrix ``self`` over `\GF{3}` or `\QQ` is a network matrix.
         If there is some entry not in `\{-1, 0, 1\}`, return ``False``.
 
         Let `D = (V,A)` be a digraph and let `T` be an (arbitrarily) directed
         spanning forest of the underlying undirected graph.
         The matrix `M(D,T) \in \{-1,0,1\}^{T \times (A \setminus T)}` defined via
-        `
-        M(D,T)_{a,(v,w)} := \begin{cases}
-            +1 & \text{if the unique $v$-$w$-path in $T$ passes through $a$ forwardly}, \\
-            -1 & \text{if the unique $v$-$w$-path in $T$ passes through $a$ backwardly}, \\
-            0  & \text{otherwise}
-        \end{cases}
-        `
+
+        .. MATH::
+
+            M(D,T)_{a,(v,w)} := \begin{cases}
+                +1 & \text{if the unique $v$-$w$-path in $T$ passes through $a$ forwardly}, \\
+                -1 & \text{if the unique $v$-$w$-path in $T$ passes through $a$ backwardly}, \\
+                0  & \text{otherwise}
+            \end{cases}
+
         is called the network matrix of `D` with respect to `T`.
         A matrix `M` is called network matrix if there exists a digraph `D`
         with a directed spanning forest `T` such that `M = M(D,T)`.
@@ -3189,7 +3197,7 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
         the support matrix of `M` for being graphic and
         uses camion for testing whether `M` is signed correctly.
 
-        EXAMPLES:
+        EXAMPLES::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 3, 2, sparse=True),
@@ -3221,11 +3229,11 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: K33 = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 5, 4, sparse=True),
-            ....:                           [[-1, -1, -1, -1],
-            ....:                            [ 1,  1,  0,  0],
-            ....:                            [ 0,  0,  1,  1],
-            ....:                            [ 1,  0,  1,  0],
-            ....:                            [ 0,  1,  0,  1]]); K33
+            ....:                             [[-1, -1, -1, -1],
+            ....:                              [ 1,  1,  0,  0],
+            ....:                              [ 0,  0,  1,  1],
+            ....:                              [ 1,  0,  1,  0],
+            ....:                              [ 0,  1,  0,  1]]); K33
             [-1 -1 -1 -1]
             [ 1  1  0  0]
             [ 0  0  1  1]
@@ -3612,21 +3620,21 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
 
         INPUT:
 
-        - ``certificate``: ``False`` or ``True``
-          If ``True``, then return
+        - ``certificate`` -- boolean (default: ``False``);
+          if ``True``, then return
           a :class:`DecompositionNode` if ``self`` is totally unimodular;
           a submatrix with determinant not in `\{0, \pm1\}` if not.
 
-        - ``stop_when_nonTU`` -- boolean (default: ``True``)
+        - ``stop_when_nonTU`` -- boolean (default: ``True``);
           Whether to stop decomposing once not TU is determined.
 
           For a description of other parameters, see :meth:`_set_cmr_seymour_parameters`
 
         - ``row_keys`` -- a finite or enumerated family of arbitrary objects
-        that index the rows of the matrix
+          that index the rows of the matrix
 
         - ``column_keys`` -- a finite or enumerated family of arbitrary objects
-        that index the columns of the matrix
+          that index the columns of the matrix
 
         EXAMPLES::
 
@@ -3685,6 +3693,7 @@ cdef class Matrix_cmr_chr_sparse(Matrix_cmr_sparse):
 
         If the matrix is totally unimodular, it always returns
         a full decomposition as a certificate::
+
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 9, 9, sparse=True),
             ....:                           [[-1,-1,-1,-1, 0, 0, 0, 0, 0],
             ....:                            [1, 1, 0, 0, 0, 0, 0, 0, 0],

src/sage/matrix/seymour_decomposition.pyx

@@ -889,7 +889,7 @@
             ((((0, 0), (0, 1), (0, 2), (0, 3)), ((0, 'a'), (0, 'b'), (0, 'c'), (0, 'd'))),
             (((1, 'a'), (1, 'b')), ((1, 0), (1, 1), (1, 2))))
 
-        ``row_keys``, ``column_keys`` of ``summands`` are disjoint:
+        ``row_keys``, ``column_keys`` of ``summands`` are disjoint::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: from sage.matrix.seymour_decomposition import DecompositionNode
@@ -901,7 +901,8 @@
             sage: node = DecompositionNode.one_sum(*certificate.child_nodes())
             Traceback (most recent call last):
             ...
-            ValueError: keys must be disjoint, got summand_row_keys=('a', 'e'), summand_column_keys=('a', 'b')
+            ValueError: keys must be disjoint, got
+            summand_row_keys=('a', 'e'), summand_column_keys=('a', 'b')
 
             sage: result, certificate = M2.is_totally_unimodular(certificate=True,
             ....:                                                row_keys=range(4),
@@ -911,7 +912,8 @@
             ....:                                  column_keys='abce')
             Traceback (most recent call last):
             ...
-            ValueError: inconsistent column_keys, got column_keys=('a', 'b', 'c', 'e'), should be a permutation of ['a', 'b', 'c', 'd']
+            ValueError: inconsistent column_keys, got column_keys=('a', 'b', 'c', 'e'),
+            should be a permutation of ['a', 'b', 'c', 'd']
         """
         summand_ids = kwds.pop('summand_ids', None)
         row_keys = kwds.pop('row_keys', None)
@@ -1829,21 +1831,21 @@
 
         INPUT:
 
-        - ``stop_when_nonTU`` -- boolean
-        Whether to stop decomposing once being non-TU is determined.
+        - ``stop_when_nonTU`` -- boolean;
+          whether to stop decomposing once being non-TU is determined.
 
-        - ``stop_when_nonnetwork`` -- boolean
-        Whether to stop decomposing once being non-network is determined.
+        - ``stop_when_nonnetwork`` -- boolean;
+          whether to stop decomposing once being non-network is determined.
 
-        - ``stop_when_nonconetwork`` -- boolean
-        Whether to stop decomposing once being non-conetwork is determined.
+        - ``stop_when_nonconetwork`` -- boolean;
+          whether to stop decomposing once being non-conetwork is determined.
 
-        - ``stop_when_nonnetwork_and_nonconetwork`` -- boolean
-        Whether to stop decomposing once not being network
-        and not being conetwork is determined.
+        - ``stop_when_nonnetwork_and_nonconetwork`` -- boolean;
+          whether to stop decomposing once not being network
+          and not being conetwork is determined.
 
-          For a description of other parameters, see
-          :meth:`sage.matrix.matrix_cmr_sparse._set_cmr_seymour_parameters`
+        For a description of other parameters, see
+        :meth:`sage.matrix.matrix_cmr_sparse._set_cmr_seymour_parameters`.
 
         EXAMPLES::
 
@@ -2896,7 +2898,7 @@
             sage: C.child_indices()
             (((r0, r1, r2, r3), (c0, c1, c2, c3, +r2+r3)),
             ((+c0+c3, r2, r3, r4, r5), (c0, c3, c4, c5)))
             sage: C.block_matrix_form()
             [ 1  0  1  1  0  0]
             [ 0  1  1  1  0  0]
             [ 1  0  1  0  1  1]
@@ -3013,9 +3015,9 @@
         If ``self.base_ring()`` is `\GF{2}`, then return edges.
         If ``self.base_ring()`` is `\GF{3}` or `\ZZ`, then arcs.
 
-        EXAMPLES::
+        EXAMPLES:
 
-        Undirected graph:
+        Undirected graph::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 3, 2, sparse=True),
@@ -3031,7 +3033,7 @@
             sage: certificate.coforest_edges()
             ((2, 7), (1, 12))
 
-        Directed graph:
+        Directed graph::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 3, 2, sparse=True),
@@ -3143,9 +3145,9 @@
         r"""
         Actually the cograph of matrix, in the case where it is not graphic.
 
-        EXAMPLES::
+        EXAMPLES:
 
-        Undirected graph:
+        Undirected graph::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 4, 5, sparse=True),
@@ -3169,7 +3171,7 @@
             sage: G.edges(sort=True)
             [(0, 2, None), (0, 5, None), (0, 7, None), (1, 2, None), (1, 5, None), (1, 7, None), (2, 8, None), (5, 8, None), (7, 8, None)]
 
-        Directed graph:
+        Directed graph::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 4, 5, sparse=True),
@@ -3288,9 +3290,9 @@
         r"""
         Return the cograph of matrix.
 
-        EXAMPLES::
+        EXAMPLES:
 
-        Undirected graph:
+        Undirected graph::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 3, 2, sparse=True),
@@ -3313,7 +3315,7 @@
             sage: certificate.cograph_coforest_edges()
             ((1, 2), (2, 7), (7, 1))
 
-        Directed graph:
+        Directed graph::
 
             sage: from sage.matrix.matrix_cmr_sparse import Matrix_cmr_chr_sparse
             sage: M = Matrix_cmr_chr_sparse(MatrixSpace(ZZ, 3, 2, sparse=True),

src/sage/matroids/linear_matroid.pyx

@@ -3808,8 +3808,8 @@ cdef class BinaryMatroid(LinearMatroid):
           to check graphicness:
 
           - ``None`` -- an algorithm based on [GG2012]_.
-          - ``"cmr"`` -- an algorithm based on [BW1988b]_.
-          the optional package "cmr" is required.
+          - ``"cmr"`` -- an algorithm based on [BW1988b]_;
+            the optional package "cmr" is required.
 
         OUTPUT: