Commit 7f8389b6 authored by Gregor Moenke's avatar Gregor Moenke

Update README.md

parent beab5b99
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Tools for time-frequency analysis of noisy time series. The
accompanying manuscript "Optimal time frequency analysis for biological data - pyBOAT"
can be found [here](https://biorxiv.org/cgi/content/short/2020.04.29.067744v2).
can be found [here](https://biorxiv.org/cgi/content/short/2020.04.29.067744v3).
Questions, comments etc. please to <gregor.moenke@embl.de>.
### Features ###
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Finally hitting ```Install``` will download and install pyBOAT. Thereafter,
pyBOAT can be started by simply clicking on ```Launch``` inside the Navigator.
#### Updates
In case you see a little blue arrow next to the version number, this means
an update is available. Clicking on that cogwheel icon in the upper right corner
allows to run the update and install the latest version of pyBOAT.
#### Installation with Anaconda on the commandline ####
For this, the download and installation of [miniconda](https://docs.conda.io/en/latest/miniconda.html)
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#### Data import ####
Just open your saved time-series data by using ``` Open ```
In general pyBOAT expects tabular data, with each column
representing a signal. Just open your saved time-series data by using ``` Open ```
from the (small) main window. Supported input formats are:
``` .xls, .xlsx, .csv, .tsv``` and ```.txt ```. For other file
extensions, white space separation of the data is assumed.
Please see examples of the supported formats in the
``` example_data ``` directory of this repository.
In case you want to interpolate missing data or you want to define your own
separator, the ```Import..``` button will spawn a menu with further options.
#### Analysis ####
After successful import, you can simply click on the table representing
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