diff options
Diffstat (limited to 'numpy/lib/shape_base.py')
| -rw-r--r-- | numpy/lib/shape_base.py | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py index cbc4641d8..a3fbee3d5 100644 --- a/numpy/lib/shape_base.py +++ b/numpy/lib/shape_base.py @@ -69,13 +69,13 @@ def take_along_axis(arr, indices, axis): Parameters ---------- - arr: ndarray (Ni..., M, Nk...) + arr : ndarray (Ni..., M, Nk...) Source array - indices: ndarray (Ni..., J, Nk...) + indices : ndarray (Ni..., J, Nk...) Indices to take along each 1d slice of `arr`. This must match the dimension of arr, but dimensions Ni and Nj only need to broadcast against `arr`. - axis: int + axis : int The axis to take 1d slices along. If axis is None, the input array is treated as if it had first been flattened to 1d, for consistency with `sort` and `argsort`. @@ -190,16 +190,16 @@ def put_along_axis(arr, indices, values, axis): Parameters ---------- - arr: ndarray (Ni..., M, Nk...) + arr : ndarray (Ni..., M, Nk...) Destination array. - indices: ndarray (Ni..., J, Nk...) + indices : ndarray (Ni..., J, Nk...) Indices to change along each 1d slice of `arr`. This must match the dimension of arr, but dimensions in Ni and Nj may be 1 to broadcast against `arr`. - values: array_like (Ni..., J, Nk...) + values : array_like (Ni..., J, Nk...) values to insert at those indices. Its shape and dimension are broadcast to match that of `indices`. - axis: int + axis : int The axis to take 1d slices along. If axis is None, the destination array is treated as if a flattened 1d view had been created of it. @@ -649,7 +649,7 @@ def column_stack(tup): arrays = [] for v in tup: - arr = array(v, copy=False, subok=True) + arr = asanyarray(v) if arr.ndim < 2: arr = array(arr, copy=False, subok=True, ndmin=2).T arrays.append(arr) @@ -775,7 +775,7 @@ def array_split(ary, indices_or_sections, axis=0): # indices_or_sections is a scalar, not an array. Nsections = int(indices_or_sections) if Nsections <= 0: - raise ValueError('number sections must be larger than 0.') + raise ValueError('number sections must be larger than 0.') from None Neach_section, extras = divmod(Ntotal, Nsections) section_sizes = ([0] + extras * [Neach_section+1] + @@ -1088,8 +1088,8 @@ def kron(a, b): ----- The function assumes that the number of dimensions of `a` and `b` are the same, if necessary prepending the smallest with ones. - If `a.shape = (r0,r1,..,rN)` and `b.shape = (s0,s1,...,sN)`, - the Kronecker product has shape `(r0*s0, r1*s1, ..., rN*SN)`. + If ``a.shape = (r0,r1,..,rN)`` and ``b.shape = (s0,s1,...,sN)``, + the Kronecker product has shape ``(r0*s0, r1*s1, ..., rN*SN)``. The elements are products of elements from `a` and `b`, organized explicitly by:: |