PsyUtils

The psyutils package is a collection of utility functions useful for generating visual stimuli and image analysis in Python. It is a work in progress, and changes as I work. It includes various helper functions for dealing with images, including creating and applying various filters in the frequency domain.

It is NOT an experimental display software package. It is intended to compliment something like PsychoPy.

It is intended only for internal use in my science at this stage. It is provided publicly to facilitate reproducibility of research. Use these functions at your own risk. Everything, including testing, is incomplete and open to change at any time.

Submodules

image. The image subpackage includes functions for filtering images and creating filtered noise stimuli, and otherwise interacting with images.
dist: functions for creating probability distributions over axes. Currently just used to create filters.
im_data. The im_data subpackage includes images and data for testing purposes.
files: contains helper functions for working with directories and file structures.
misc. This is a miscellaneous subpackage.

Example Use

You could do things like this::

import numpy as np
import psyutils as pu
im = np.random.uniform(size=(256, 256))
filt = pu.image.make_filter_lowpass(im_size, cutoff=8)
im2 = pu.image.filter_image(im, filt)
pu.image.show_im(im2)

Dependencies

See setup.py for current dependencies.

Building

To build the package, use:

python3 -m pip install --user --upgrade setuptools wheel
python3 setup.py sdist bdist_wheel

Testing

You can run unit tests by typing

nosetests -v --with-coverage --cover-package=psyutils

from the command line in the project's parent directory.

TODO

more unit tests for filters, axes, windowing, misc
check documentation for filters
improve sphinx docs and linking

Contributions

Thomas Wallis wrote the package. Many image processing functions are based on Matlab code from Peter Bex's lab. I also adapted some stuff from the scikit-image package.

Thanks To

Many of the image processing functions are based on Matlab functions originally written by Peter Bex. Tom Wallis also thanks Matthias Kümmerer and David Janssen for Python help and suggestions.

bveliqi/PsyUtils