Python module for for creating and manipulating an array of crops (or regions of interest) from images obtained using single-molecule microscopy.
Project description
croparray
Authors: Tim Stasevich.
Description
This module is intended for creating and manipulating an array of crops (or regions of interest) that were generated from a multicolor TIF video obtained from single-molecule microscopy.
Installation from Github repository
-
Install anaconda.
-
To create a virtual environment navigate to your local repository and use:
conda create -n croparray_env python=3.8 -y
source activate croparray_env
- To install the rest of requirements use:
pip install -r requirements.txt
Installation using PIP
- To create a virtual environment using:
conda create -n croparray_env python=3.8 -y
source activate croparray_env
- Open the terminal and use pip for the installation:
pip install croparray
Deactivating and removing the environment
- To deactivate or remove the environment from your computer use:
conda deactivate
- To remove the environment use:
conda env remove -n croparray_env
- To unistall croparray use
pip uninstall croparray
additional troubleshooting information
- If you cannot see the package installed on your computer, try using
pip3
. For example:
pip3 install croparray
Usage
- Organizes crops and measurements of spots of interest from tif images in a convenient x-array format for reduced filesize and more open and reproducible analyses.
- Visualizes crops of detected spots from super-resolution microscope images.
- Calculates the best maximum projection for each crop containing a detected spot.
- Measures intensity of detected spots within crops.
- Calculates the correlation between two equal-length, 1D signals.
- Saves the crop array as a netcdf file at output_direction/output_filename.
- Integrates with Napari for fast and convenient review of crops of detected spots.
Licenses for dependencies
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