nima 0.11.9

Numerical IMage Analyses.

NImA

A library and a command-line interface (CLI) designed to assist with image analysis tasks using scipy.ndimage and scikit-image.

Features

• Bias and Flat Correction
• Automatic Cell Segmentation
• Multi-Ratio Ratiometric Imaging, enabling users to analyze multiple ratios with ease.

Installation

You can get the library directly from PyPI using pip:

pip install nima

Alternatively, you can use pipx to install it in an isolated environment:

pipx install nima

To enable auto completion for the nima command, follow these steps:

1. Generate the completion script by running the following command:

   _CLOP_COMPLETE=bash_source nima > ~/.local/bin/nima-complete.bash
   

2. Source the generated completion script to enable auto completion:

   source ~/.local/bin/nima-complete.bash
   

Usage

Library

To use nima in your python code, import it as follows:

from nima import nima, generat, utils

Command-Line Interface (CLI)

The CLI for this project provides two main commands: nima and bima. You can find detailed usage information and examples in the documentation. Here are some examples of how to use each command:

nima

The nima command is used to perform multi-ratio ratiometric imaging analyses on multi-channel TIFF time-lapse stacks.

To perform multi-ratio ratiometric imaging analyses on a multichannel TIFF time-lapse stack, use the following command:

nima <TIFFSTK> CHANNELS

Replace <TIFFSTK> with the path to the TIFF time-lapse stack file, and CHANNELS with the channel names. By default, the channels are set to ["G", "R", "C"].

bima

The bima command is used to compute bias, dark, and flat corrections.

To estimate the detector bias frame:

bima bias <FPATH>

Replace <FPATH> with the paths to the bias stack (Light Off - 0 acquisition time).

To estimate the system dark (multi-channel) frame:

bima dark <FPATH>

Replace <FPATH> with the paths to the dark stack (Light Off - Long acquisition time).

Note: The estimation of the system dark may be removed in future versions because it risks being redundant with the flat estimation. It is likely to be removed soon.

To estimate the system flat (multi-channel) frame:

bima flat --bias <BIAS_PATH> <FPATH>

Replace <FPATH> with the path to the tf8 stack and <BIAS_PATH> with the path to the bias image.

TODO

• jaxtyping

ImFrame: TypeAlias = Float32[Array, "height width"]  # noqa: F722
ImSequence: TypeAlias = Float32[Array, "time height width"]  # noqa: F722
DIm: TypeAlias = dict[str, ImSequence]

Contributing

Contributions to the project are welcome!

If you are interested in contributing to the project, please read our contributing and development environment guides, which outline the guidelines and conventions that we follow for contributing code, documentation, and other resources.

License

We use a shared copyright model that enables all contributors to maintain the copyright on their contributions - see the revised BSD license for details.

Acknowledgments

Special thanks to the developers of scipy.ndimage and scikit-image for their invaluable contributions to image processing in Python.