Metadata-Version: 1.1
Name: fastspt
Version: 13.1
Summary: A library to perform kinetic modeling of fast single particle tracking experiments
Home-page: https://gitlab.com/tjian-darzacq-lab/Spot-On-cli/
Author: Maxime Woringer, Anders Sejr Hansen
Author-email: maxime.woringer@berkeley.edu
License: GPLv3+
Description: Spot-On (cli)
        -------
        
        This repository collects a series of scripts to analyze data from single particle tracking experiments. The code was initially written by Anders Sejr Hansen and translated to Python by Maxime Woringer. A [Matlab version](https://gitlab.com/tjian-darzacq-lab/spot-on-matlab) exists and is maintained by Anders Sejr Hansen.
        
        This repository only includes the commandline analysis pipeline. A graphical user interface (GUI) is available for a more user-friendly analysis, but is not included in this repository. This repository contains the command-line version, that can be used independently from the GUI.
        
        Although the functions and methods can be called directly, we provide a walk-through tutorial as a [Jupyter](http://jupyter.org) notebook. 
        
        # Dependencies
        
        - numpy
        - scipy
        - lmfit
        
        Optional: jupyter
        
        Your package manager may provide precompiled versions of `numpy` and `scipy`. In that case, it might be worth using those libraries, because compilation can take a significant amount of time.
        
        # Installation (from pip)
        
        `pip install fastspt`
        
        # Installation (from this Gitlab) repository
        
        ## Install dependencies
        `pip install -r requirements.txt`
        
        Alternatively, you can install the dependencies manually by typing:
        `pip install numpy scipy lmfit`
        
        Optional : `pip install jupyter`
        
        ## Install fastSPT
        
        Simply run (as root): `python setup.py install`
        
        Check that it worked: `python -c "import fastspt"`
        
        
        # Tutorial
        A short tutorial, demonstrating the capabilities of the software, is available as a Jupyter notebook. 
        
        See `fastSPT_tutorial.ipynb`. The tutorial is also available online: **address of the page**
        
        **Document here how to open a Jupyter notebook**
        
        # Usage
        ## Main functions
        ## Input file format
        ## Caveats
        
        # References
        
        # License
        This program is released under the GNU General Public License version 3 or upper (GPLv3+).
        
        
            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 3 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/>.
        
        # Deploying (developer only)
        ```
        python setup.py sdist
        gpg --detach-sign -a dist/fastspt-11.4.tar.gz
        twine upload dist/fastspt-11.4.tar.gz dist/fastspt-11.4.tar.gz.asc
        ```
        # Authors
        
        # Bugs/suggestions
        Send to bugtracker or to email.
        
Keywords: single particle tracking SPT kinetic modelling
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
