Tinyarray

Tinyarrays are similar to NumPy arrays, but optimized for small sizes. Common operations on very small arrays are to 3-7 times faster than with NumPy (with NumPy 1.6 it used to be up to 35 times), and 3 times less memory is used to store them. Tinyarrays are useful if you need many small arrays of numbers, and cannot combine them into a few large ones. (The resulting code is still much slower than C, but it may now be fast enough.)

Unlike Python's built-in tuples, Tinyarrays support mathematical operations like element-wise addition and matrix multiplication. Unlike Numpy arrays, Tinyarrays can be used as dictionary keys because they are hashable and immutable.

The module's interface is a subset of that of NumPy and thus should be familiar to many. Whenever an operation is missing from Tinyarray, NumPy functions can be used directly with Tinyarrays.

Tinyarray is licensed under the "simplified BSD License". See LICENSE.rst.

Website: https://gitlab.kwant-project.org/kwant/tinyarray

Please report bugs here: https://gitlab.kwant-project.org/kwant/tinyarray/issues

Source code

Source tarballs are available at http://downloads.kwant-project.org/tinyarray/

Clone the Git repository with

git clone https://gitlab.kwant-project.org/kwant/tinyarray.git

Installation

You can build from source with the usual

pip install tinyarray

You can also download the source tarball (or clone it from git) and use

python setup.py install

Prepared packages exist for

• Windows

  Use Christoph Gohlke's installer.

• Ubuntu and derivatives

  sudo apt-add-repository ppa:kwant-project/ppa
  sudo apt-get update
  sudo apt-get install python-tinyarray

• Debian and derivatives

  1. Add the following lines to /etc/apt/sources.list:

     deb http://downloads.kwant-project.org/debian/ stable main
     deb-src http://downloads.kwant-project.org/debian/ stable main

  2. (Optional) Add the OpenPGP key used to sign the repositories by executing:

     sudo apt-key adv --keyserver pgp.mit.edu --recv-key C3F147F5980F3535

  3. Update the package data, and install:

     sudo apt-get update
     sudo apt-get install python-tinyarray

• Mac OS X

  Follow the instructions for installing "Kwant" but install py27-tinyarray instead of py27-kwant etc.

Usage example

The following example shows that in simple cases Tinyarray works just as NumPy.

from math import sin, cos, sqrt
import tinyarray as ta

# Make a vector.
v = ta.array([1.0, 2.0, 3.0])

# Make a rotation matrix.
alpha = 0.77
c, s = cos(alpha), sin(alpha)
rot_z = ta.array([[c, -s, 0],
                  [s,  c, 0],
                  [0,  0, 1]])

# Rotate the vector, normalize, and print it.
v = ta.dot(rot_z, v)
v /= sqrt(ta.dot(v, v))
print v

Documentation

The module's interface is a basic subset of NumPy and hence should be familiar to many Python programmers. All functions are simplified versions of their NumPy counterparts. The module's docstring serves as main documentation. To see it, run in Python:

import tinyarray as ta
help(ta)

Or in the system shell:

pydoc tinyarray

Authors

The principal developer of Tinyarray is Christoph Groth (SPSMS-INAC-CEA Grenoble). His contributions are part of his work at CEA, the French Commissariat à l'énergie atomique et aux énergies alternatives.

The author can be reached at christoph.groth@cea.fr.

Other people that have contributed to Tinyarray include

• Michael Wimmer (Leiden University)
• Joseph Weston (SPSMS-INAC-CEA Grenoble)