Repository: numpy/numpy
File: numpy/linalg/_linalg.py (Python)

Code before:
        case. In case the number of dimensions in the input array is
        greater than 2 then a stack of the matrices with above properties
        is returned.
    R : ndarray of float or complex, optional
        The upper-triangular matrix or a stack of upper-triangular
        matrices if the number of dimensions in the input array is greater
        than 2.
    (h, tau) : ndarrays of np.double or np.cdouble, optional
        The array h contains the Householder reflectors that generate q
        along with r. The tau array contains scaling factors for the
        reflectors. In the deprecated  'economic' mode only h is returned.

    Raises
    ------
    LinAlgError
        If factoring fails.

    See Also
    --------
    scipy.linalg.qr : Similar function in SciPy.
    scipy.linalg.rq : Compute RQ decomposition of a matrix.

    Notes
    -----
    When mode is 'reduced' or 'complete', the result will be a namedtuple with
    the attributes `Q` and `R`.

    This is an interface to the LAPACK routines ``dgeqrf``, ``zgeqrf``,
    ``dorgqr``, and ``zungqr``.

    For more information on the qr factorization, see for example:
    https://en.wikipedia.org/wiki/QR_factorization

    Subclasses of `ndarray` are preserved except for the 'raw' mode. So if
    `a` is of type `matrix`, all the return values will be matrices too.

    New 'reduced', 'complete', and 'raw' options for mode were added in
    NumPy 1.8.0 and the old option 'full' was made an alias of 'reduced'.  In
    addition the options 'full' and 'economic' were deprecated.  Because
    'full' was the previous default and 'reduced' is the new default,
    backward compatibility can be maintained by letting `mode` default.
    The 'raw' option was added so that LAPACK routines that can multiply
    arrays by q using the Householder reflectors can be used. Note that in
    this case the returned arrays are of type np.double or np.cdouble and
    the h array is transposed to be FORTRAN compatible.  No routines using
    the 'raw' return are currently exposed by numpy, but some are available
    in lapack_lite and just await the necessary work.

    Examples
    --------
    >>> import numpy as np

Review comment (suggestion):
The parameters need double back-quotes to be rendered as code, now that they are outside the "Returns" block. This change is needed below as well.
```suggestion
    the attributes ``Q`` and ``R``.
```

Code after:
        case. In case the number of dimensions in the input array is
        greater than 2 then a stack of the matrices with above properties
        is returned.
    R : ndarray of float or complex, optional
        The upper-triangular matrix or a stack of upper-triangular
        matrices if the number of dimensions in the input array is greater
        than 2.
    (h, tau) : ndarrays of np.double or np.cdouble, optional
        The array h contains the Householder reflectors that generate q
        along with r. The tau array contains scaling factors for the
        reflectors. In the deprecated  'economic' mode only h is returned.

    Raises
    ------
    LinAlgError
        If factoring fails.

    See Also
    --------
    scipy.linalg.qr : Similar function in SciPy.
    scipy.linalg.rq : Compute RQ decomposition of a matrix.

    Notes
    -----
    When mode is 'reduced' or 'complete', the result will be a namedtuple with
    the attributes ``Q`` and ``R``.

    This is an interface to the LAPACK routines ``dgeqrf``, ``zgeqrf``,
    ``dorgqr``, and ``zungqr``.

    For more information on the qr factorization, see for example:
    https://en.wikipedia.org/wiki/QR_factorization

    Subclasses of `ndarray` are preserved except for the 'raw' mode. So if
    `a` is of type `matrix`, all the return values will be matrices too.

    New 'reduced', 'complete', and 'raw' options for mode were added in
    NumPy 1.8.0 and the old option 'full' was made an alias of 'reduced'.  In
    addition the options 'full' and 'economic' were deprecated.  Because
    'full' was the previous default and 'reduced' is the new default,
    backward compatibility can be maintained by letting `mode` default.
    The 'raw' option was added so that LAPACK routines that can multiply
    arrays by q using the Householder reflectors can be used. Note that in
    this case the returned arrays are of type np.double or np.cdouble and
    the h array is transposed to be FORTRAN compatible.  No routines using
    the 'raw' return are currently exposed by numpy, but some are available
    in lapack_lite and just await the necessary work.

    Examples
    --------
    >>> import numpy as np