fixationmodel

A least-squares offline method to test if tracked gaze points resemble a fixation.

1. Install

With pip:

$ pip install fixationmodel

2. Usage

A data structure we call pointlist is used for point sequences. It is a list of points, where each point is a list [x, y].

The usage is simple:

>>> import fixationmodel
>>> rawdata = [
    [130.012, 404.231],
    [129.234, 403.478],
    [None, None],
    [133.983, 450.044],
    ...
]
>>> results = fixationmodel.fit(rawdata)
>>> print(results)
{
    'centroid': [344.682, 200.115],
    'mean_squared_error': 0.000166802
}

3. API

3.1. fixationmodel.fit(gazepointlist)

Parameter:

gazepointlist: a list of [x, y] points i.e. a list of lists.

Return dict with following keys:

centroid: a list [x, y], the most probable target of the fixation
mean_squared_error: the average squared error for a point.

3.2. fixationmodel.version

Gives the current version string:

>>> fixationmodel.version
'1.2.3'

4. For developers

4.1. Virtualenv

Use virtualenv:

$ virtualenv -p python3.5 fixationmodel-py
$ cd fixationmodel-py
$ source bin/activate
...
$ deactivate

4.2. Testing

Follow instructions to install pyenv and then either run quick tests:

$ python3.5 setup.py test

or comprehensive tests for multiple Python versions in tox.ini:

$ pyenv local 2.6.9 2.7.10 3.2.6 3.3.6 3.4.3 3.5.0
$ eval "$(pyenv init -)"
$ pyenv rehash
$ tox

4.3. Publishing to PyPI

Follow python packaging instructions:

Create an unpacked sdist: $ python setup.py sdist
Create a universal wheel: $ python setup.py bdist_wheel --universal
Go to PyPI and register the project by filling the package form by uploading fixationmodel.egg-info/PKG_INFO file.
Upload the package with twine:
1. Sign the dist: $ gpg --detach-sign -a dist/fixa...0.1.2*
2. Upload: twine upload dist/fixa...0.1.2* (will ask your PyPI password)
Package published!

Updating the package takes same steps except the 3rd.

5. Versioning

Semantic Versioning 2.0.0

6. License

MIT License

Metadata

Release files for fixationmodel 0.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for fixationmodel 0.1.3
File	Size	Uploaded
fixationmodel-0.1.3.tar.gz	4.4 kB	Dec 9, 2015	Details

Built distribution (wheel)

Table of built distributions (wheels) for fixationmodel 0.1.3
File	Interpreter	ABI	Platform	Reset
fixationmodel-0.1.3-py2.py3-none-any.whl 5.5 kB Dec 9, 2015	Python 2, Python 3	none	any	Details

Total release size: 9.9 kB

Release files / fixationmodel-0.1.3.tar.gz

Download URL	fixationmodel-0.1.3.tar.gz
Size	4.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`37ef50093d306a43c222d8a17d0ff04a0d0e7de2e503185de80fb57e750b4ea3`
BLAKE2b-256 checksum How to use checksums	`f4c481d34e30f3a69f2612749d021590318cf3b487fc8626aa59f8ef74df3b27`
Upload date	Dec 9, 2015
Uploaded using Trusted Publishing? What is trusted publishing?	No

Release files / fixationmodel-0.1.3-py2.py3-none-any.whl

Download URL	fixationmodel-0.1.3-py2.py3-none-any.whl
Size	5.5 kB
Tags	Python 2 Python 3
SHA-256 checksum How to use checksums	`8d8b1fc86c2c14271229ef1777cd48885c03e4057326fb3ad261a62fe1902971`
BLAKE2b-256 checksum How to use checksums	`84392507a65d8ed5f26d3757b73d43fd45535abec8b09ab031e78e33cf608c31`
Upload date	Dec 9, 2015
Uploaded using Trusted Publishing? What is trusted publishing?	No