Merge pull request #139 from NeurodataWithoutBorders/add_github_star_…

…badges

add github stars

docs/source/tools/caiman/caiman.rst

@@ -8,6 +8,10 @@ CaImAn
 :ref:`analysistools-caiman` is a computational toolbox for large scale Calcium Imaging Analysis, including movie
 handling, motion correction, source extraction, spike deconvolution and result visualization. CaImAn now supports reading and writing data in NWB 2.0. :bdg-link-primary:`NWB Demo  <https://github.com/flatironinstitute/caiman_use_cases/blob/main/use_cases/NWB/demo_pipeline_nwb.ipynb>` :bdg-link-primary:`Second Demo <https://github.com/flatironinstitute/CaImAn/blob/master/demos/general/demo_pipeline_NWB.py>` :bdg-link-primary:`Video Tutorial <https://www.youtube.com/watch?v=wUhKkNtSu_s>` :bdg-link-primary:`Docs <https://caiman.readthedocs.io/en/latest/>` :bdg-link-primary:`Source <https://github.com/flatironinstitute/CaImAn>`.
 
+.. image:: https://img.shields.io/github/stars/flatironinstitute/CaImAn?style=social
+    :alt: GitHub Repo stars for CaImAn
+    :target: https://github.com/flatironinstitute/CaImAn
+
 .. short_description_end
 
 .. image:: caiman_logo.png

docs/source/tools/cebra/cebra.rst

@@ -15,5 +15,9 @@ CEBRA
 :bdg-link-primary:`Docs <https://cebra.ai/docs/>`
 :bdg-link-primary:`NWB tutorial <https://stes.io/NeuroDataReHack2023/>`.
 
+.. image:: https://img.shields.io/github/stars/AdaptiveMotorControlLab/cebra?style=social
+    :alt: GitHub Repo stars for CEBRA
+    :target: https://github.com/AdaptiveMotorControlLab/cebra
+
 
 .. short_description_end

docs/source/tools/cellexplorer/cellexplorer.rst

@@ -7,6 +7,10 @@ CellExplorer
 
 :ref:`analysistools-cellexplorer`  is a graphical user interface (GUI), a standardized processing module and data structure for exploring and classifying single cells acquired using extracellular electrodes. :bdg-link-primary:`NWB Tutorial  <https://cellexplorer.org/tutorials/nwb-tutorial/>`  :bdg-link-primary:`Intro Video  <https://www.youtube.com/watch?v=GR1glNhcGIY>` :bdg-link-primary:`Video Tutorial  <https://www.youtube.com/watch?v=x2x0KkRuSak>` :bdg-link-primary:`Docs  <https://cellexplorer.org/>` :bdg-link-primary:`Source <https://github.com/petersenpeter/CellExplorer>`.
 
+.. image:: https://img.shields.io/github/stars/petersenpeter/CellExplorer?style=social
+    :alt: GitHub Repo stars for CellExplorer
+    :target: https://github.com/petersenpeter/CellExplorer
+
 .. short_description_end
 
 .. image:: CellExplorerInterface.jpeg

docs/source/tools/ciatah/ciatah.rst

@@ -7,6 +7,10 @@ CIAtah
 
 :ref:`analysistools-ciatah` (pronounced cheetah; formerly calciumImagingAnalysis) is a Matlab software package for analyzing one- and two-photon calcium imaging datasets. :bdg-link-primary:`Video tutorial <https://www.youtube.com/watch?v=I6abW3uuJJw>` :bdg-link-primary:`Docs <https://bahanonu.github.io/ciatah/>` :bdg-link-primary:`Source <https://github.com/bahanonu/calciumImagingAnalysis>`.
 
+.. image:: https://img.shields.io/github/stars/bahanonu/calciumImagingAnalysis?style=social
+    :alt: GitHub Repo stars for CIAtah
+    :target: https://github.com/bahanonu/calciumImagingAnalysis
+
 .. short_description_end
 
 .. image:: ciatah_pipeline.png

docs/source/tools/deeplabcut/deeplabcut.rst

@@ -13,6 +13,10 @@ of this framework by tracking various body parts in multiple species across a
 broad collection of behaviors.
 :bdg-link-primary:`Documentation <http://www.mackenziemathislab.org/deeplabcut>`
 
+.. image:: https://img.shields.io/github/stars/DeepLabCut/DeepLabCut?style=social
+    :alt: GitHub Repo stars for DeepLabCut
+    :target: https://github.com/DeepLabCut/DeepLabCut
+
 .. short_description_end
 
 

docs/source/tools/ecogvis/ecogvis.rst

@@ -7,6 +7,10 @@ EcogVIS
 
 :ref:`analysistools-ecogvis`  is a Python-based, time series visualizer for Electrocorticography (ECoG) signals stored in NWB files. EcogVIS makes it intuitive and simple to visualize ECoG signals from selected channels, brain regions, make annotations and mark intervals of interest. Signal processing and analysis tools will soon be added. :bdg-link-primary:`Source <https://github.com/catalystneuro/ecogVIS>`.
 
+.. image:: https://img.shields.io/github/stars/catalystneuro/ecogVIS?style=social
+    :alt: GitHub Repo stars for ecogVIS
+    :target: https://github.com/catalystneuro/ecogVIS
+
 .. short_description_end
 
 .. image:: ecogvis_screenshot.png

docs/source/tools/extract/extract.rst

@@ -13,6 +13,10 @@ performance.
 :bdg-link-primary:`NWB tutorials <https://github.com/schnitzer-lab/EXTRACT-public/tree/master/Learning%20materials/NWB%20Tutorials>`
 :bdg-link-primary:`Publication <https://www.biorxiv.org/content/10.1101/2021.03.24.436279v2>`
 
+.. image:: https://img.shields.io/github/stars/schnitzer-lab/EXTRACT-public?style=social
+    :alt: GitHub Repo stars for EXTRACT
+    :target: https://github.com/schnitzer-lab/EXTRACT-public
+
 .. short_description_end
 
 

docs/source/tools/graft/graft.rst

@@ -10,4 +10,8 @@ GraFT
 :bdg-link-primary:`NWB tutorials  <https://github.com/adamshch/GraFT-analysis/tree/main/code/nwb_tutorials>`
 :bdg-link-primary:`Cite  <https://pubmed.ncbi.nlm.nih.gov/35533160/>`
 
+.. image:: https://img.shields.io/github/stars/adamshch/GraFT-analysis?style=social
+    :alt: GitHub Repo stars for GraFT
+    :target: https://github.com/adamshch/GraFT-analysis
+
 .. short_description_end

docs/source/tools/mies/mies.rst

@@ -7,6 +7,10 @@ MIES
 
 :ref:`analysistools-mies` is a sweep based data acquisition tool written in Igor Pro. MIES has three primary user interfaces: 1) the ``WaveBuilder`` to generate stimulus sets 2) the ``DA_Ephys`` GUI to control and observe data acquisition in real time, and 3) the ``DataBrowser`` to browse acquired data. All three interfaces are intended to be operated in parallel. :bdg-link-primary:`Video tutorial <https://www.youtube.com/watch?v=Y3I-LDX-R2Q>` :bdg-link-primary:`MIES NWB Module <https://alleninstitute.github.io/MIES/IPNWB/index.html>`  :bdg-link-primary:`Docs <https://alleninstitute.github.io/MIES/index.html>` :bdg-link-primary:`Source <https://github.com/AllenInstitute/MIES>`.
 
+.. image:: https://img.shields.io/github/stars/AllenInstitute/MIES?style=social
+    :alt: GitHub Repo stars for MIES
+    :target: https://github.com/AllenInstitute/MIES
+
 .. short_description_end
 
 

docs/source/tools/neo/neo.rst

@@ -17,6 +17,9 @@ or visualization. :bdg-link-primary:`Docs <https://neo.readthedocs.io/en/stable/
 :bdg-link-primary:`Website <https://neuralensemble.org/neo/>`
 :bdg-link-primary:`Source <https://github.com/NeuralEnsemble/python-neo>`.
 
+.. image:: https://img.shields.io/github/stars/NeuralEnsemble/python-neo?style=social
+    :alt: GitHub Repo stars for NEO
+    :target: https://github.com/NeuralEnsemble/python-neo
 
 .. short_description_end
 

docs/source/tools/neurosift/neurosift.rst

@@ -8,6 +8,10 @@ Neurosift
 :ref:`analysistools-neurosift` provides interactive neuroscience visualizations in the browser. Neurosift caters to both individual users through its local mode, allowing the visualization of views directly from your device, as well as a remote access function for presenting your findings to other users on different machines.
 :bdg-link-primary:`Source <https://github.com/flatironinstitute/neurosift>`
 
+.. image:: https://img.shields.io/github/stars/flatironinstitute/neurosift?style=social
+    :alt: GitHub Repo stars for neurosift
+    :target: https://github.com/flatironinstitute/neurosift
+
 .. short_description_end
 
 With Neurosift, you have the ability to construct a multitude of synchronized visuals such as spike raster plots, audio spectrograms, videos, video annotations, position decode fields, timeseries graphs, and more.

docs/source/tools/nwbwidgets/nwbwidgets.rst

@@ -6,7 +6,11 @@ NWB Widgets
 .. short_description_start
 
 :ref:`analysistools-nwbwidgets` is a library of widgets for visualization NWB data in a Jupyter notebook (or lab).
-The widgets make it easy to navigate through the hierarchical structure of the NWB file and visualize specific data elements. It is designed to work out-of-the-box with NWB 2.0 files and to be easy to extend. :bdg-link-primary:`Source <https://github.com/NeurodataWithoutBorders/nwb-jupyter-widgets>` :bdg-link-primary:`Docs <https://nwb-widgets.readthedocs.io>`
+The widgets make it easy to navigate through the hierarchical structure of the NWB file and visualize specific data elements. It is designed to work out-of-the-box with NWB 2.0 files and to be easy to extend. :bdg-link-primary:`Source <https://github.com/NeurodataWithoutBorders/nwbwidgets>` :bdg-link-primary:`Docs <https://nwb-widgets.readthedocs.io>`
+
+.. image:: https://img.shields.io/github/stars/NeurodataWithoutBorders/nwbwidgets?style=social
+    :alt: GitHub Repo stars for NWB Widgets
+    :target: https://github.com/NeurodataWithoutBorders/nwbwidgets
 
 .. short_description_end
 

docs/source/tools/openephys/openephys.rst

@@ -7,6 +7,10 @@ OpenEphys GUI
 
 :ref:`acquisitiontools-openephys` is a modular, open-source software for extracellular electrophysiology. Built by neuroscientists, for neuroscientists, OpenEphys GUI has all the features needed to acquire and visualize electrophysiology data, while making it easy to add new modules written in C++. The GUI allows the user to configure processing pipelines by mixing and matching modules. Using the NWB format plugin, users can record data directly in NWB format via the OpenEphys GUI. --- **OpenEphys GUI:** :bdg-link-primary:`Docs <https://open-ephys.github.io/gui-docs/User-Manual/>` :bdg-link-primary:`Website <https://open-ephys.org/gui>` :bdg-link-primary:`Source <https://github.com/open-ephys/plugin-GUI>`  ---  **NWB Plugin for OpenEphys**: :bdg-link-primary:`Docs <https://open-ephys.github.io/gui-docs/User-Manual/Recording-data/NWB-format.html>`  :bdg-link-primary:`Source <https://github.com/open-ephys-plugins/nwb-format>`
 
+.. image:: https://img.shields.io/github/stars/open-ephys-plugins/nwb-format?style=social
+    :alt: GitHub Repo stars for the NWB format plugin
+    :target: https://github.com/open-ephys-plugins/nwb-format
+
 .. short_description_end
 
 .. image:: openephys_gui_screenshot.png

docs/source/tools/optinist/optinist.rst

@@ -7,6 +7,11 @@ OptiNiSt
 
 :ref:`analysistools-optinist` (Optical Neuroimage Studio) is a GUI based workflow pipeline tools for processing two-photon calcium imaging data. :bdg-link-primary:`Source <https://github.com/oist/optinist/>` :bdg-link-primary:`Docs <https://optinist.readthedocs.io/en/latest/>`
 
+.. image:: https://img.shields.io/github/stars/oist/optinist?style=social
+    :alt: GitHub Repo stars for Optinist
+    :target: https://github.com/oist/optinist
+
+
 .. short_description_end
 
 OptiNiSt helps researchers try multiple data analysis methods, visualize the results, and construct the data analysis pipelines easily and quickly on GUI. OptiNiSt's data-saving format follows NWB standards.

docs/source/tools/patchview/patchview.rst

@@ -10,6 +10,10 @@ PatchView
 :bdg-link-primary:`Source <https://github.com/ZeitgeberH/patchview>`
 :bdg-link-primary:`Publication <https://joss.theoj.org/papers/10.21105/joss.04706>`
 
+.. image:: https://img.shields.io/github/stars/ZeitgeberH/patchview?style=social
+    :alt: GitHub Repo stars for PatchView
+    :target: https://github.com/ZeitgeberH/patchview
+
 .. short_description_end
 
 .. image:: patchview.png

docs/source/tools/pynapple/pynapple.rst

@@ -1,13 +1,17 @@
 .. _analysistools-pynapple:
 
 pynapple
-------------
+---------
 
 .. short_description_start
 
 :ref:`analysistools-pynapple` is a unified toolbox for integrated analysis of multiple data sources. Designed to be "plug & play", users define and import their own time-relevant variables. Supported data sources include, but are not limited to, electrophysiology, calcium imaging, and motion capture data. Pynapple contains integrated functions for common neuroscience analyses, including cross-correlograms, tuning curves, decoding and perievent time histogram.
 :bdg-link-primary:`Docs <https://pynapple-org.github.io/pynapple/>` :bdg-link-primary:`DANDI Demo <https://pynapple-org.github.io/pynapple/generated/gallery/tutorial_pynapple_dandi/>` :bdg-link-primary:`Source <https://github.com/pynapple-org/pynapple>` :bdg-link-primary:`Twitter <https://twitter.com/thepynapple>`
 
+.. image:: https://img.shields.io/github/stars/pynapple-org/pynapple?style=social
+    :alt: GitHub Repo stars for pynapple
+    :target: https://github.com/pynapple-org/pynapple
+
 .. short_description_end
 
 .. image:: GraphicAbstract.png

docs/source/tools/sleap/sleap.rst

@@ -1,7 +1,7 @@
 .. _analysistools-sleap:
 
 SLEAP
-----------
+-----
 
 .. short_description_start
 
@@ -11,6 +11,10 @@ number of animals and includes an advanced labeling/training GUI for active
 learning and proofreading.
 :bdg-link-primary:`Documentation <https://sleap.ai>`
 
+.. image:: https://img.shields.io/github/stars/talmolab/sleap?style=social
+    :alt: GitHub Repo stars for SLEAP
+    :target: https://github.com/talmolab/sleap
+
 .. short_description_end
 
 

docs/source/tools/spikeinterface/spikeinterface.rst

@@ -7,6 +7,10 @@ SpikeInterface
 
 :ref:`analysistools-spikeinterface` is a collection of Python modules designed to improve the accessibility, reliability, and reproducibility of spike sorting and all its associated computations. :bdg-link-primary:`Video tutorial <https://www.youtube.com/watch?v=fvKG_-xQ4D8>` :bdg-link-primary:`Demo Notebook <https://github.com/SpikeInterface/spiketutorials/tree/master/Official_Tutorial_SI_0.96_Oct22>` :bdg-link-primary:`Docs  <https://spikeinterface.readthedocs.io/en/latest/>` :bdg-link-primary:`Source  <https://github.com/SpikeInterface>`
 
+.. image:: https://img.shields.io/github/stars/SpikeInterface/spikeinterface?style=social
+    :alt: GitHub Repo stars for SpikeInterface
+    :target: https://github.com/SpikeInterface/spikeinterface
+
 .. short_description_end
 
 With SpikeInterface, users can:

docs/source/tools/spyglass/spyglass.rst

@@ -9,6 +9,10 @@ Spyglass
 :bdg-link-primary:`Docs <https://lorenfranklab.github.io/spyglass/>`
 :bdg-link-primary:`Source <https://github.com/LorenFrankLab/spyglass>`.
 
+.. image:: https://img.shields.io/github/stars/LorenFrankLab/spyglass?style=social
+    :alt: GitHub Repo stars for Spyglass
+    :target: https://github.com/LorenFrankLab/spyglass
+
 .. short_description_end
 
 .. image:: Spyglass.png

docs/source/tools/suite2p/suite2p.rst

@@ -7,6 +7,10 @@ suite2p
 
 :ref:`analysistools-suite2p` is an imaging processing pipeline written in Python . suite2p includes modules for 1) Registration, 2) Cell detection, 3) Spike detection, and a 4) Visualization GUI. :bdg-link-primary:`Video Tutorial <https://www.youtube.com/watch?v=Ey9_xVPinmo>` :bdg-link-primary:`Docs <https://suite2p.readthedocs.io/en/latest/>` :bdg-link-primary:`Source <https://github.com/MouseLand/suite2p>`.
 
+.. image:: https://img.shields.io/github/stars/MouseLand/suite2p?style=social
+    :alt: GitHub Repo stars for suite2p
+    :target: https://github.com/MouseLand/suite2p
+
 .. short_description_end
 
 .. only:: html

docs/source/tools/visiomode/visiomode.rst

@@ -7,6 +7,10 @@ Visiomode
 
 :ref:`analysistools-visiomode` is an open-source platform for building touchscreen-based behavioral tasks for rodents. It leverages the inherent flexibility of touchscreens to offer a simple yet adaptable software and hardware platform. Visiomode is built on the Raspberry Pi computer combining a web-based interface and powerful plug-in system with an operant chamber that can be adapted to generate a wide range of behavioral tasks. :bdg-link-primary:`Docs <https://www.visiomode.org>` :bdg-link-primary:`Source <https://github.com/DuguidLab/visiomode>` :bdg-link-primary:`Publication <https://doi.org/10.1016/j.jneumeth.2022.109779>`
 
+.. image:: https://img.shields.io/github/stars/DuguidLab/visiomode?style=social
+    :alt: GitHub Repo stars for visiomode
+    :target: https://github.com/DuguidLab/visiomode
+
 .. short_description_end
 
 .. image:: visiomode_graphical_abstract.png