.. image:: https://travis-ci.org/losonczylab/sima.svg?branch=master :target: https://travis-ci.org/losonczylab/sima/
.. image:: https://ci.appveyor.com/api/projects/status/q3bgxcoget1xef33/branch/master?svg=true :target: https://ci.appveyor.com/project/nbdanielson/sima
.. image:: https://coveralls.io/repos/losonczylab/sima/badge.png :target: https://coveralls.io/r/losonczylab/sima
.. image:: https://badges.gitter.im/Join%20Chat.svg :alt: Join the chat at https://gitter.im/losonczylab/sima :target: https://gitter.im/losonczylab/sima?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
.. Removed until the docs are building properly .. image:: https://readthedocs.org/projects/sima/badge/?version=latest :target: https://sima.readthedocs.org/en/latest/
SIMA (Sequential IMage Analysis) is an Open Source package for analysis of time-series imaging data arising from fluorescence microscopy. The functionality of this package includes:
The included ROI Buddy software provides a graphical user interface (GUI) supporting the following functionality:
For complete documentation go to http://www.losonczylab.org/sima
Python <http://python.org>_ 2.7 numpy <http://www.scipy.org>_ >= 1.6.2scipy <http://www.scipy.org>_ >= 0.13.0scikit-image <http://scikit-image.org>_ >= 0.9.3 (0.11.0 recommended)scikit-learn <http://scikit-learn.org>_ >= 0.11shapely <https://pypi.python.org/pypi/Shapely> >= 1.2.14 (Windows users: be sure to install from Christophe Gohlke's built wheels <http://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely>)pillow <https://pypi.python.org/pypi/Pillow>_ >= 2.6.1future <https://pypi.python.org/pypi/future>_ >= 0.14OpenCV <http://opencv.org>_ >= 2.4.8, required for segmentation,
registration of ROIs across multiple datasets, and the ROI Buddy GUIpicos <http://picos.zib.de>_ >= 1.0.2, required for spike inference (>= 1.1 required for Python 3)pyfftw <https://pypi.python.org/pypi/pyFFTW>_, allows faster performance of some motion correction methods when installed together with FFTW.h5py <http://www.h5py.org>_ >= 2.2.1 (2.3.1 recommended), required for HDF5 file format bottleneck <http://pypi.python.org/pypi/Bottleneck>_ >=0.8, for faster calculationsmatplotlib <http://matplotlib.org>_ >= 1.2.1, for saving extraction summary plotsmdp <http://mdp-toolkit.sourceforge.net>_, required for ICA demixing of
channelsIf you build the package from source, you may also need:
Cython <http://cython.org>_If you are using the spike inference feature, we strongly recommend installing
MOSEK <https://www.mosek.com/>_ (free for academic use) which greatly speeds
up the inference.
If you use SIMA for your research, please cite the following paper in any resulting publications:
Kaifosh P, Zaremba J, Danielson N, and Losonczy A. SIMA: Python software for analysis of dynamic fluorescence imaging data. Frontiers in Neuroinformatics. 2014 Aug 27; 8:77. doi: 10.3389/fninf.2014.00080. <http://dx.doi.org/10.3389/fninf.2014.00080>_
Unless otherwise specified in individual files, all code is
Copyright (C) 2014 The Trustees of Columbia University in the City of New York.
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.