napari-cosmos-ts

napari-cosmos-ts

napari plugin for colocalization single-molecule spectroscopy (CoSMoS) time series (TS) analysis

    napari plugin for colocalization single-molecule spectroscopy (CoSMoS) time series (TS) analysis.

    1. Install the conda package manager. Simplest is to download Miniconda and run the installer.
    2. Create a virtual python environment named napari-env (or name it whatever you want) in which to install napari and this plugin. In a command shell or terminal run the following command:
    conda create --name napari-env python
    1. Activate your virtual environment. !!! Note you will have to do this every time you open a new command shell or terminal. In a command shell or terminal run the following command:
    conda activate napari-env
    1. Install napari and napari-cosmos-ts into your virtual environment. In a command shell or terminal where you have activated your virtual environment run the following command:
    pip install "napari[all]" napari-cosmos-ts
    1. Activate your virtual environment (see Install, replace napari-env with the name of your environment). In a command shell or terminal run the following command:
    conda activate napari-env
    1. Launch the napari viewer. In a command shell or terminal where you have activated your virtual environment run the following command:
    napari
    1. Launch the napari-cosmos-ts plugin. From the napari viewer Plugins menu, select Colocalization Single-Molecule Time Series (napari-cosmos-ts). This should bring up a docked widget within the viewer. Now you are good to go!

    Version:

    • 0.1.2

    Last updated:

    • 12 April 2024

    First released:

    • 11 April 2024

    License:

    Supported data:

    • Information not submitted

    Plugin type:

    GitHub activity:

    • Stars: 1
    • Forks: 0
    • Issues + PRs: 0

    Python versions supported:

    Operating system:

    • Information not submitted

    Requirements:

    • napari>=0.4.19.post1
    • pyqtgraph>=0.13.4
    • pystackreg>=0.2.7
    • pycpd>=2.0.0

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