Package: dcl-stats-n-plots
dcl_stats_n_plotsThis repository is part of theDCLwidgetsseries. These repositories
are dedicated to foster the joint development of tools and resources by
theDefense Circuits Lab. The
intended use of each tool may vary greatly from very lab- and/or
analysis-specific problems, to tools and resources that may be of use
also for other researchers. The common goal for each repository,
however, is to provide the tool as an interactive, userfriendly, and
intuitive GUI (usually based onipywidgets, hence the
name), such that the user needs little to no coding expertise.List of all repositories of the DCLwidgets series:dcl_stats_n_plots:
A widget to compute statistics and plot the data with several options
to customize the plotDCL_to_NWB: A widget to
convert datasets acquired in the DCL into the NWB file formatBSc_MS: A widget to annotate
the corners of a maze within video files and save the corresponding x-
and y-coordinatesAbout this widgetThe purpose of this widget is to make everyday life in the lab a little
easier, as it helps you to compute statistical tests and to create
highly customizable plots that visualize your data. The widget also
enables you to select exactly which statistical results you would like
to annotate within the plots. This way, statistical analysis and
visualization of your data is what it should be - simple & fast!Please get in touch if you have any feedback, questions, or feature
requests for us!InstallationUsing conda:Although thedcl_stats_n_plotspackage itself is only available onPiPy, we yet recommend
installation via conda - especially if you would like to use the GUI.
Simply recreate the conda environment on your local machine by running
the following command in your command line or terminal (e.g. Anaconda
prompt). You can find the corresponding “environment.yml” file in the
GitHub repo
(here).
Just make sure to place the file either in the current working directory
(usually displayed at the beginning of each line in your terminal), or
to provide the entire filepath (e.g. something like:
“C:\Users\dsege\Downloads\environment.yml”):With the “environment.yml” file in your current working directory:conda env create -file environment.ymlWith the “environment.yml” file in a different directory:conda env create -file PATH\TO\THE\FILE\environment.ymlThis will install all dependencies that are required to usedcl_stats_n_plost, including its GUI version.NoteThis installation was so far only tested on Linux (Ubuntu 20.04.4)
using conda 22.9.0NoteIf you would like to contribute to the development ofdcl_stats_n_plostyou are more than welcome! On top of the regular
user installation, you will, however, also need to installnbdevin
the same environment. Simply follow all the steps above and once you
have verified that everything was installed correcty, simply run in
the same conda environment:conda install -c fastai nbdevIf you are new tonbdev, you´d probably also want to check out their
comprehensive tutorials and walkthroughshere. I will also add some more
contribution guidelines to this repository soon. In the meantime, feel
free to get in touch! :-)Using pip:Despite thedcl_stats_n_plotspackage itself is only available via
pypi.org, we still highly recommend to follow the installation
guidelines “using conda” above, especially if you´d like to use its GUI
functionalities. If you´d still want to go down this route, here´s your
install command:pip install dcl-stats-n-plotsHow to use.. the documentation, including the comprehensive tutorials, is
currently being updated ..Next stepsThere are some major reorganizations planned:This repository will be shifted / forked / re-created under the
recently established GitHub organisations page of the Defense
Circuits Lab, i.e. somewherehereWhen this migration is performed, the new repository (ideally also
the package) will be renamed tostats_n_plotsas the prefix to
link it to the DCL will no longer be requiredOnce the migration was successfully completed, the documentation
will be updated to eventually match the “refactored” version, which
actually already includes some new statistical tests compared to the
old version, as well as additional functions inteded to improve
usability (like exporting & importing your current plotting
settings)Finally, once the documentation regarding the usage ofdcl_stats_n_plotswas updated, I will add some information and
guidelines for contribution to this packageOnce the steps listed above are all completed, there are plenty of ideas
for how to continue developing this package further:integrate tests (especially with the improved CI of nbdev v2 and also
once additional contributors join)add additional statistical tests & plots (e.g. Kolmogorov-Smirnov test
for goodness of fit for cumulative probability functions, or linear &
linear mixed effect models, ..)add additional customization options (optional hue column, fonts, ..)improve how configs are export and imported, ideally to include all
settings (type of plot, color scheme, …)create DCL-default configsfix bugs ;-)