Note: This software is in alpha stage of development
(See also "Alternative installation" below)
You can use and/or develop SpikeForest2 with codepod. Tested in Linux, should also work on a Mac.
Prerequisites: docker and codepod
First clone this repo:
git clone https://github.com/flatironinstitute/spikeforest2
Next, set the KBUCKET_CACHE_DIR environment variable. This is where the cached files from kbucket will go. For example, you could use export KBUCKET_CACHE_DIR=/tmp/sha1-cache
If you want to use a conda virtual environment (e.g. spikeforest2), run
conda create -n spikeforest2 python=3.6
conda activate spikeforest2
Install codepod
pip install spikeforest2
Then run the ./codepod_run.sh convenience script in the repo
cd spikeforest2
./codepod_run.sh
This will download a docker image (may take some time depending on your internet connection) and put you in a container with a fully-functional development environment.
Once inside the container you can run the following to open vscode
code .
Once in codepod, you may run the unit tests via
pytest
To run the slower, more thorough, tests:
pytest -m slow -s
# The -s flag is for verbose output, which may not be what you want
# This will download singularity containers, which may take some time
# depending on your internet connection
(Please notify if the following gets out-of-sync with the project directory structure)
devel: Utilities specific to development of SpikeForest, including instructions on preparing the docker image for codepod, a script to run when codepod is started, and a script for auto-formatting the python code for pep8 compliance.
mountaintools: Contains the MountainTools such as batcho, cairio, kbucket, mlprocessors, and vdomr. These tools are not specific to spike sorting.
repos: Related repositories. See note below.
simplot: A work-in-progress JavaScript library for interactive plotting.
spikextractors: A snapshot of the SpikeExtractors project.
spikeforest: A python module used for both spike sorting and visualization.
spikeforest_analysis: A python module using by spike sorting scripts and analysis scripts. Contains the core processing routines.
spikeforestwidgets: Some vdomr widgets used by the GUIs.
spikesorters: Wrappers of the spike sorting algorithms.
spiketoolkit: An old snapshot of the SpikeToolkit project.
spikewidgets: An old snapshot of the SpikeWidgets project.
working: The SpikeForest analysis scripts. Contains scripts for preparing recordings, running spike sorting, comparing with ground truth, and assembling results for the websites.
.codepod.yml: Configuration file for codepod
.gitignore: Files that git should ignore
codepod_run.sh: Run this to open the project using codepod (see above).
pytest.ini: Configuration file for pytest
README.md: This readme file
LICENSE: The license file for this project. See also license files for individual components within subdirectories.
requirements.txt: The python package dependencies
setup_colab.sh: Convenience script to set up a google colaboratory runtime
setup_jp_proxy_widget.sh: Convenience script for using vdomr in jupyter notebooks
setup_python.sh: Convenience script for installing python dependencies (not necessary when using codepod, see below)
setup.py: The setup file for this python package (see below)
This is a meta repository that is meant to be used in development/editable mode.
To install using conda, first create a conda environment with python 3.6:
conda create -n spikeforest2 python=3.6
conda activate spikeforest2
Then run the following
# See: setup_python.sh
pip install -r requirements.txt
python setup.py develop
cd mountaintools
pip install -r requirements.txt
python setup.py develop
To run GUI tools, run
conda install -c anaconda pyqt
and test using
gui/sfbrowser/start_sfbrowser.py
To run colab jupyter notebooks in a local runtime, we recommend chrome browser or chromium-browser. Firefox browser may not properly connect to the local runtime environment. You must run the following prior to using colab with a local runtime:
# colab (see setup_colab.sh)
pip install jupyter_http_over_ws
jupyter serverextension enable --py jupyter_http_over_ws
In addition, if you want to use some of the interactive graphics within jupyterlab, do the following:
./setup_jp_proxy_widget.sh
The repo/ directory contains a snapshot of a number of different dependent projects. These may or may not be up-to-date with the associated stand-alone packages. In this way, spikeforest2 is a snapshot project that contains all the necessary code, and is less susceptible to breaking changes in other packages.