diff options
Diffstat (limited to 'numpy/lib')
| -rw-r--r-- | numpy/lib/arraypad.py | 4 | ||||
| -rw-r--r-- | numpy/lib/function_base.py | 2 | ||||
| -rw-r--r-- | numpy/lib/index_tricks.py | 3 | ||||
| -rw-r--r-- | numpy/lib/shape_base.py | 2 | ||||
| -rw-r--r-- | numpy/lib/utils.py | 2 |
5 files changed, 6 insertions, 7 deletions
diff --git a/numpy/lib/arraypad.py b/numpy/lib/arraypad.py index e6ebd97e4..042f587e0 100644 --- a/numpy/lib/arraypad.py +++ b/numpy/lib/arraypad.py @@ -619,10 +619,10 @@ def pad(array, pad_width, mode=None, **kwargs): where - vector: ndarray + vector : ndarray A rank 1 array already padded with zeros. Padded values are vector[:pad_tuple[0]] and vector[-pad_tuple[1]:]. - iaxis_pad_width: tuple + iaxis_pad_width : tuple A 2-tuple of ints, iaxis_pad_width[0] represents the number of values padded at the beginning of vector where iaxis_pad_width[1] represents the number of values padded at diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index cd79dd67f..914d7b580 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -2917,7 +2917,7 @@ def median(a, axis=None, out=None, overwrite_input=False): Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output, but the type (of the output) will be cast if necessary. - overwrite_input : bool optional + overwrite_input : bool, optional If True, then allow use of memory of input array (a) for calculations. The input array will be modified by the call to median. This will save memory when you do not need to preserve diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py index 9c58bf747..c77424f71 100644 --- a/numpy/lib/index_tricks.py +++ b/numpy/lib/index_tricks.py @@ -675,7 +675,8 @@ def fill_diagonal(a, val, wrap=False): Value to be written on the diagonal, its type must be compatible with that of the array a. - wrap: bool For tall matrices in NumPy version up to 1.6.2, the + wrap : bool + For tall matrices in NumPy version up to 1.6.2, the diagonal "wrapped" after N columns. You can have this behavior with this option. This affect only tall matrices. diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py index 575f6149d..fcabbace4 100644 --- a/numpy/lib/shape_base.py +++ b/numpy/lib/shape_base.py @@ -681,12 +681,10 @@ def kron(a,b): See Also -------- - outer : The outer product Notes ----- - The function assumes that the number of dimenensions 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)`, diff --git a/numpy/lib/utils.py b/numpy/lib/utils.py index 2e70bfd15..d7492def8 100644 --- a/numpy/lib/utils.py +++ b/numpy/lib/utils.py @@ -835,7 +835,7 @@ def _lookfor_generate_cache(module, import_modules, regenerate): Module for which to generate docstring cache import_modules : bool Whether to import sub-modules in packages. - regenerate: bool + regenerate : bool Re-generate the docstring cache Returns |