nphelper - convenient numpy helper functions
This package contains some convenient helper function for numpy. Nothing fancy, but quite useful. It works with python 2.7, 3.4, and 3.5.
Install
Simply install via pip
:
pip install nphelper
nphelper
only depends on numpy
.
Usage / Features
Create block arrays (in matlabs's [A A; B B]
spirit):
>>> from nphelper import block
>>> A = np.array([[1, 2, 3]])
>>> B = np.array([[2, 3, 4]])
>>> C = np.ones((2, 6))
>>> block([[A, B], [C]])
array([[1, 2, 3, 2, 3, 4],
[[1, 1, 1, 1, 1, 1],
[[1, 1, 1, 1, 1, 1]])
Compute the cartesian product (similar to itertools.product
):
>>> from nphelper import cartesian_product
>>> cartesian_product([[1, 2], [3, 4]])
array([[1, 3],
[1, 4],
[2, 3],
[2, 4]])
Easily multiply many arrays without the cubersome dot
syntax. It's also
much faster than dot because it selects the fastest evaluation order.
(This is part of numpy 1.10.0.)
>>> from nphelper import multi_dot
>>> A = np.random.random((10000, 100))
>>> B = np.random.random((100, 1000))
>>> C = np.random.random((1000, 5))
>>> D = np.random.random((5, 333))
>>> # Sick of this?
>>> np.dot(np.dot(np.dot(A, B), C), D) # doctest: +SKIP
>>> # Or this?
>>> A.dot(B).dot(C).dot(D) # doctest: +SKIP
>>> # Use multi_dot
>>> multi_dot([A, B, C, D]) # doctest: +SKIP
- TODO along, maxalong, minalong, sumalong, meanalong, stdalong, varalong
Dev
Run the tests
Run tox
to run the tests for python 2.7, 3.4, and 3.5:
tox
You might have to install addiotional dependencies to run the tests:
- ``py.test``, - ``nose``, - ``python2.7-dev``, - ``python3.4-dev``, and - ``python3.5-dev``.
Build the Docs
cd doc make html
You might have to install addiotional dependencies:
pip install sphinx sphinx_rtd_theme