unmap
Unmap data from a pseudocolor image, with or without knowing the colormap.
Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: ieee.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.1%) to scientific vocabulary
Keywords
Repository
Unmap data from a pseudocolor image, with or without knowing the colormap.
Basic Info
- Host: GitHub
- Owner: scienxlab
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://scienxlab.org/unmap
- Size: 15.2 MB
Statistics
- Stars: 18
- Watchers: 1
- Forks: 2
- Open Issues: 8
- Releases: 4
Topics
Metadata Files
README.md
unmap
Unmap data from pseudocolor images, with or without knowledge of the colourmap. This tool has 2 main components:
- Guess the colourmap that was used for a pseudocolour visualization, in cases where it's unknown and a colourbar is not included in the image.
- 'Unmap' a pseudocolour visualization, separating the data from the image; essentially this is the opposite of what
plt.imshow()does.
Similar projects
There are some other approaches to both Task 1 (above) and Task 2:
unmap(I swear I didn't know about this tool when I named mine!) — does the data ripping part. The colourmap must be provided, but the tool also provides a way to interactively identify a colourbar in the image.- Poco et al. (GitHub) attempts to both find the colourbar in a visualization, then use it to perform Task 2. The visualization must contain a colourbar.
- Yuan et al. attempts Task 1 using deep learning. The prediction from a CNN is refined with either Laplacian eigenmapping (manifold+based dimensionality reduction, for continuous colourmaps) or DBSCAN (for categorical colourmaps).
Of these projects, only Yuan et al. ('deep colormap extraction') requires no a priori knowledge of the colourmap.
Stack Exchange questions about this topic
- Can I get numeric data from a color map?
- How to extract a colormap from a colorbar image and use it in a heatmap?
- Given a JPG of 2D colorplot colorbar how can I sample the image to extract data?
- How to reverse a colormap image to scalar values?
- Extract color table values?
- Invert not reverse a colormap in maptplotlib
Installation
You can install this package with pip:
pip install unmap
There are dev, test and docs options for installing dependencies for those purposes, eg pip install unmap[dev].
Documentation
Read the documentation, especially the examples.
Contributing
Take a look at CONTRIBUTING.md.
Testing
After cloning this repository and installing the dependencies required for testing, you can run the tests (requires pytest and pytest-cov) with
pytest
Building
This repo uses PEP 517-style packaging, with the entire build system and requirements defined in the pyproject.toml file. Read more about this and about Python packaging in general.
Building the project requires build, so first:
pip install build
Then to build unmap locally:
python -m build
The builds both .tar.gz and .whl files, either of which you can install with pip.
Owner
- Name: scien✖️lab
- Login: scienxlab
- Kind: organization
- Location: Norway
- Repositories: 2
- Profile: https://github.com/scienxlab
Citation (CITATION.cff)
cff-version: 1.2.0
title: unmap
version: 0.0
message: Please use this information to cite this work.
type: software
authors:
- given-names: Matt
family-names: Hall
email: kwinkunks@gmail.com
affiliation: None
orcid: 'https://orcid.org/0000-0002-4054-8295'
date-released: 2022-09-16
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Dependencies
- JamesIves/github-pages-deploy-action v4.2.3 composite
- actions/checkout v1 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- aiohttp *
- fsspec *
- matplotlib *
- networkx *
- numpy *
- pillow *
- scikit-image *
- scipy *
- xarray *