Skip to main content

A plugin to visualize, deskew, and combine Snouty data.

Project description

snouty-viewer

License MIT PyPI Python Version tests codecov napari hub

Description

Easy to use plugin for opening raw Snouty files and converting them to native view.

Allows for saving to ome.tif files with corresponding OME-XML based metadata.

Also allows for bulk deskewing and saving directories.

Example

Intended Audience & Supported Data

This plugin is intended for those using a SOLS (Snouty) microscope collected via Alfred Millett-Sikking's code.

This plugin accepts a folder with at least subdirectories of data and metadata as an input.

Quickstart

A. Getting the plugin working (choose either a or b, you don't have to do both)

a. Through pip-install:

  1. pip install snouty-viewer (within a virtual environment of Python 3.8, 3.9, or 3.10 recommended)
  2. Open up napari

b. Through Napari:

  1. Open up napari
  2. Plugins > Install/Uninstall plugins
  3. Search for "snouty-viewer"
  4. Install
  5. (Maybe need to) reopen napari

B. Viewing raw Snouty data

  • Drag and drop a root folder of your Snouty data. This is the folder that includes the data and metadata subfolders.
  • Select "Snouty Viewer" for opening.

C. Converting raw Snouty data to its native view

  1. Click plugins, snouty-viewer -> Native View
  2. Select the file you want to convert
  3. Press Deskew

D. Saving your native view file

  1. Select the channel (or multi-channel) layer you want to save
  2. File > Save Selected Layer(s)...
  3. Select where you want to save your file
  4. Title your file, ".ome.tif" will automatically be appended.
  5. Save with "Snouty Writer"
  6. Wait (this could take a few minutes depending on your file's size and your hardware)

E. Batch saving

  1. Click plugins, snouty-viewer -> Batch Deskew & Save
  2. Input a directory (without quotes) that contains 1 or more Snouty-acquired directories.
  3. If you want to view your deskewed outputs, check the box.
  4. If you want to automatically save the deskewed outputs, check the box.
  5. Press Deskew and save
  6. Wait (this could take a few minutes depending on your files' sizes and your hardware)

Getting Help


This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.

Installation

You can install snouty-viewer via pip:

pip install snouty-viewer

To install latest development version :

pip install git+https://github.com/aelefebv/snouty-viewer.git

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

License

Distributed under the terms of the MIT license, "snouty-viewer" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

snouty_viewer-0.2.tar.gz (11.7 kB view details)

Uploaded Source

Built Distribution

snouty_viewer-0.2-py3-none-any.whl (11.2 kB view details)

Uploaded Python 3

File details

Details for the file snouty_viewer-0.2.tar.gz.

File metadata

  • Download URL: snouty_viewer-0.2.tar.gz
  • Upload date:
  • Size: 11.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for snouty_viewer-0.2.tar.gz
Algorithm Hash digest
SHA256 2ec167cafcf0ad4740e43df3fd37035a980d3b1ff1d07b864b836cbbd80a891e
MD5 f847793d97a978ebc8b5207ba03b8110
BLAKE2b-256 06107ac5dc60c38e29259ba823eeefbe9a8c8be0c169624d274d0b7bd93c37ca

See more details on using hashes here.

File details

Details for the file snouty_viewer-0.2-py3-none-any.whl.

File metadata

  • Download URL: snouty_viewer-0.2-py3-none-any.whl
  • Upload date:
  • Size: 11.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for snouty_viewer-0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 e561ebe2c5a0169dd77bfd61df5be97d49b630eeb1fa7b879baaa8ee899089d1
MD5 f128d0f9a123457ae6c30b2e40b3d59c
BLAKE2b-256 ce791437d1f77727890727ae01c865d66948a9a142c07de81ab1b5d0a096690a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page