First, install common dependencies in the conda env with Python>=3.9 (>=3.11 not yet tested)

• pip install neura-library

Install all dependencies using

• pip install neura-library[all]

Install the minimal required dependencies according to usage purpose . For example:

• Choices in []: atlas, scanner, calimg, segmentation, model, track, gpu, profile, imagelib, tools, all
• Use atlas module: pip install neura-library[atlas]
• Use segmentation module: pip install neura-library[segmentation]

For developer for anyone want to contribute, run also:

• pip install neura-library[dev]
• Setup pre-commit by: pre-commit install
• Do dry run ruff lint check by: ruff check .

• neuralib.atlas.ccf: Customized hierarchical classification for the mouse brain atlas
• neuralib.atlas.brainrender: cli-based wrapper for brainrender
• neuralib.atlas.cellatlas: Volume and cell types counts for each brain region, refer to Cell Atlas
• neuralib.atlas.ibl: Slice view plotting wrapper for ibllib and iblatlas

• neuralib.calimg.scan_image: Data acquired from ScanImage ( under DEV)
• neuralib.calimg.scanbox: Data acquired from Scanbox
• neuralib.calimg.suite2p: Result parser for suite2p
• neuralib.calimg.spikes: dF/F to spike activity (OASIS/Cascade)

• neuralib.segmentation.cellpose: Result Parser and batch running for cellpose
• neuralib.segmentation.stardist: Result Parser and batch running for stardist

neuralib.model.bayes_decoding: Position decoding using population neuronal activity

neuralib.model.rastermap: Run and result parser for rastermap

• neuralib.tracking.deeplabcut: Result parser for DeepLabCut

• neuralib.tracking.facemap: Result parser for facemap

neuralib.argp: Use argparse as dataclass field

neuralib.persistence: caching the analyzed results (i.e., concatenation for statistic purpose)

neuralib.bokeh_model: Interactive dashboard visualization

neuralib.sqlp: Python functions to build a SQL (sqlite3) statement.

neuralib.plot: Module for general plotting purpose

neuralib.imglib: Image processing library (under DEV)

neuralib.tools.gspread: Google spreadsheet API wrapper for read/write

neuralib.tools.slack_bot: Real-time slack notification bot for analysis pipeline

neuralib.util.cli_args: run script as subprocess

neuralib.util.color_logging: logging with color format

neuralib.util.gpu: OS-dependent gpu info

neuralib.util.profile_test: simple benchmark profile testing

neuralib.util.table: rich table visualization

neuralib.util.segments: Epoch or value segments