lbm-caiman-python 1.0.1

Light Beads Microscopy 2P Calcium Imaging Pipeline.

LBM-CaImAn-Python

Installation | Notebooks

Python implementation of the Light Beads Microscopy (LBM) computational pipeline.

For the MATLAB implementation, see here

Installation

Installation requires an active conda installation.

Note: Sometimes conda or mamba will get stuck at a step, such as creating an environment or installing a package. Pressing Enter on your keyboard can sometimes help it continue when it pauses.

1. Install mamba into your base environment:

:exclamation: This step may take 10 minutes and display several messages like "Solving environment: failed with..." but it should eventually install mamba.

conda activate base 
conda install -c conda-forge mamba

2. Create a new environment and install mesmerize-core

• Here, we use the -n flag to name the environment lbm , but you can name it whatever you'd like.
• This step will install Python, mesmerize-core, CaImAn, and all required dependencies for those packages.

conda create -n lbm -c conda-forge mesmerize-core

If you already have CaImAn installed:

conda install -n name-of-env-with-caiman mesmerize-core

Activate the environment and install caimanmanager:

• if you used a name other than lbm, be sure to match the name you use here.

conda activate lbm
caimanmanager install

3. Install LBM-CaImAn-Python from pip:

Install the minimal lbm_caiman_python:

pip install lbm_caiman_python

4. Install scanreader:

pip install git+https://github.com/atlab/scanreader.git

5. (Optional) Install mesmerize-viz:

Several notebooks make use of mesmerize-viz for visualizing registration/segmentation results.

pip install https://github.com/kushalkolar/mesmerize-viz.git

:exclamation: Harware requirements The large CNMF visualizations with contours etc. usually require either a dedicated GPU or integrated GPU with access to at least 1GB of VRAM.

https://www.youtube.com/watch?v=GWvaEeqA1hw

For Developers

To get the newest version of this package:

git clone https://github.com/MillerBrainObservatory/LBM-CaImAn-Python.git

cd LBM-CaImAn-Python

pip install ".[docs]"

Troubleshooting

Conda Slow / Stalling

if conda is behaving slow, clean the conda installation and update conda-forge:

conda clean -a

conda update -c conda-forge --all

Don't forget to press enter a few times if conda is taking a long time.

Recommended Conda Distribution

The recommended conda installer is miniforge.

This is a community-driven conda/mamba installer with pre-configured packages specific to conda-forge.

This helps avoid conda-channel conflicts and avoids any issues with the Anaconda TOS.

You can install the installer from a unix command line:

curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh"

bash Miniforge3-$(uname)-$(uname -m).sh

Or download the installer for your operating system here.

Graphics Driver Issues

If you are attempting to use fastplotlib and receive errors about graphics drivers, see the fastplotlib driver documentation.

Pipeline Steps:

1. Motion Correction
   • Template creation
   • Rigid registration
   • Piecewise-rigid registration
2. Segmentation
   • Iterative CNMF segmentation
   • Deconvolution
   • Refinement
3. Collation
   • Lateral offset correction (between z-planes)
   • Collate images and metadata into a single volume

Requirements

• caiman
• mesmerize-core
• numpy
• scipy