croparray 0.1.1

Python module for for creating and manipulating an array of crops (or regions of interest) from images obtained using single-molecule microscopy.

croparray

Authors: Tim Stasevich and Luis Aguilera.

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.

Documentation

• Documentation is accessible via croparray.readthedocs

Colab implementation

• Implementation in Google Colab

Local installation from the Github repository

• Install anaconda.

• Clone the Github repository

    git clone https://github.com/Colorado-State-University-Stasevich-Lab/croparray.git

• 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

• To install napari use:

python -m pip install "napari[all]"

Local 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

• To install napari use:

python -m pip install "napari[all]"

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

Installing from yml env

• To creating an environment file (yml) use:

source activate croparray_env
conda env export > croparray_env.yml

• ToCreate an environment from this yml file.

conda env create -f croparray_env.yml

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

• License for Napari: BSD-3-Clause License. Copyright (c) 2018, Napari. All rights reserved.

• License for xarray: Apache License. Version 2.0, January 2004. Copyright 2014-2019, xarray Developers