Function _reshape_2D

lib/matplotlib/cbook.py:1425–1482

Use Fortran ordering to convert ndarrays and lists of iterables to lists of 1D arrays. Lists of iterables are converted by applying `numpy.asanyarray` to each of their elements. 1D ndarrays are returned in a singleton list containing them. 2D ndarrays are converted to the lis

(X, name)

def _reshape_2D(X, name):
    """
    Use Fortran ordering to convert ndarrays and lists of iterables to lists of
    1D arrays.

    Lists of iterables are converted by applying `numpy.asanyarray` to each of
    their elements.  1D ndarrays are returned in a singleton list containing
    them.  2D ndarrays are converted to the list of their *columns*.

    *name* is used to generate the error message for invalid inputs.
    """

    # Unpack in case of e.g. Pandas or xarray object
    X = _unpack_to_numpy(X)

    # Iterate over columns for ndarrays.
    if isinstance(X, np.ndarray):
        X = X.transpose()

        if len(X) == 0:
            return [[]]
        elif X.ndim == 1 and np.ndim(X[0]) == 0:
            # 1D array of scalars: directly return it.
            return [X]
        elif X.ndim in [1, 2]:
            # 2D array, or 1D array of iterables: flatten them first.
            return [np.reshape(x, -1) for x in X]
        else:
            raise ValueError(f'{name} must have 2 or fewer dimensions')

    # Iterate over list of iterables.
    if len(X) == 0:
        return [[]]

    result = []
    is_1d = True
    for xi in X:
        # check if this is iterable, except for strings which we
        # treat as singletons.
        if not isinstance(xi, str):
            try:
                iter(xi)
            except TypeError:
                pass
            else:
                is_1d = False
        xi = np.asanyarray(xi)
        nd = np.ndim(xi)
        if nd > 1:
            raise ValueError(f'{name} must have 2 or fewer dimensions')
        result.append(xi.reshape(-1))

    if is_1d:
        # 1D array of scalars: directly return it.
        return [np.reshape(result, -1)]
    else:
        # 2D array, or 1D array of iterables: use flattened version.
        return result