Package: element-calcium-imaging
DataJoint Element for Functional Calcium ImagingDataJoint Element for functional calcium imaging withScanImage,Scanbox,Nikon NIS-Elements,
andBruker Prairie Viewacquisition software; andSuite2p,CaImAn, andEXTRACTanalysis
software. DataJoint Elements collectively standardize and automate
data collection and analysis for neuroscience experiments. Each Element is a modular
pipeline for data storage and processing with corresponding database tables that can be
combined with other Elements to assemble a fully functional pipeline. This repository
also provides a tutorial environment and notebooks to learn the pipeline.Experiment FlowchartData Pipeline DiagramWe have designed three variations of the pipeline to handle different use cases.
Displayed above is the defaultimagingschema.  Details on all of theimagingschemas can be found in theData
Pipelinedocumentation page.Getting StartedInstall from PyPIpipinstallelement-calcium-imagingInteractive tutorial on GitHub CodespacesDocumentationSupportIf you need help getting started or run into any errors, please open a GitHub Issue
or contact our team by email atsupport@datajoint.com.Interactive TutorialThe easiest way to learn about DataJoint Elements is to use the tutorial notebooks within the included interactive environment configured usingDev Container.Launch EnvironmentHere are some options that provide a great experience:(recommended) Cloud-based EnvironmentLaunch usingGitHub Codespacesusing the+option which willCreate codespace on mainin the codebase repository on your fork with default options. For more control, see the...where you may createNew with options....Build time for a codespace is a few minutes. This is done infrequently and cached for convenience.Start time for a codespace is less than 1 minute. This will pull the built codespace from cache when you need it.Tip: Each month, GitHub renews afree-tierquota of compute and storage. Typically we run into the storage limits before anything else since Codespaces consume storage while stopped. It is best to delete Codespaces when not actively in use and recreate when needed. We'll soon be creating prebuilds to avoid larger build times. Once any portion of your quota is reached, you will need to wait for it to be reset at the end of your cycle or add billing info to your GitHub account to handle overages.Tip: GitHub auto names the codespace but you can rename the codespace so that it is easier to identify later.Local EnvironmentNote: Access to example data is currently limited to MacOS and Linux due to the s3fs utility. Windows users are recommended to use the above environment.InstallGitInstallDockerInstallVSCodeInstall the VSCodeDev Containers extensiongit clonethe codebase repository and open it in VSCodeUse theDev Containers extensiontoReopen in Container(More info is in theGetting startedincluded with the extension.)You will know your environment has finished loading once you either see a terminal open related toRunning postStartCommandwith a final message ofDoneor theREADME.mdis opened inPreview.Once the environment has launched, please run the following command in the terminal:MYSQL_VER=8.0 docker compose -f docker-compose-db.yaml up --build -dInstructionsWe recommend you start by navigating to thenotebooksdirectory on the left panel and go through thetutorial.ipynbJupyter notebook. Execute the cells in the notebook to begin your walk through of the tutorial.Once you are done, see the options available to you in the menu in the bottom-left corner. For example, in Codespace you will have an option toStop Current Codespacebut when running Dev Container on your own machine the equivalent option isReopen folder locally. By default, GitHub will also automatically stop the Codespace after 30 minutes of inactivity.  Once the Codespace is no longer being used, we recommend deleting the Codespace.