*[Fully-coherent MCMC search on data containing a single glitch](docs/fully_coherent_search_using_MCMC_on_glitching_data.md)
*[Semi-coherent MCMC glitch-search on data containing a single glitch](docs/semi_coherent_glitch_search_using_MCMC_on_glitching_data.md)
*[Semi-coherent MCMC glitch-search on data containing two glitches](docs/semi_coherent_glitch_search_with_two_glitches_using_MCMC_on_glitching_data.md)
*[Semi-coherent Follow-Up MCMC search (dynamically changing the coherence time)](docs/follow_up.md)
For documentation, please use the [wiki](https://gitlab.aei.uni-hannover.de/GregAshton/PyFstat/wikis/home).
## Installation
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...
@@ -35,8 +17,27 @@ the stripped down [miniconda](http://conda.pydata.org/miniconda.html)
installation, or the full-featured
[anaconda](https://www.continuum.io/downloads)(these are essentially the
same, but the `anaconda` version installs a variety of useful packages such as
`numpy` and `scipy` by default). Instructions to install miniconda/anaconda
are provided in the links.
`numpy` and `scipy` by default).
The fastest/easiest method is to follow your OS instructions
[here](https://conda.io/docs/install/quick.html) which will install Miniconda.
For the rest of this tutorial, we will make use of `pip` to install modules (
not all packages can be installed with `conda` and for those using alternatives