Package Health Score

82 / 100

security
No known security issues
popularity
Influential project
maintenance
Sustainable
community
Active

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classic
39

Popularity

Influential project

GitHub Stars: 689
Forks: 54
Contributors: 20

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package colorcet, we found that it has been starred 689 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Feb 29, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

CC-BY License

Security Policy

We found a way for you to contribute to the project! Looks like colorcet is missing a security policy.

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Maintenance

Sustainable

Commit Frequency

Open Issues: 2
Open PR: 0
Last Release: 9 months ago
Last Commit: 2 months ago

Further analysis of the maintenance status of colorcet based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Sustainable.

We found that colorcet demonstrates a positive version release cadence with at least one new version released in the past 12 months.

In the past month we didn't find any pull request activity or change in issues status has been detected for the GitHub repository.

Community

Active

Readme: Yes
Contributing.md: No
Code of Conduct: Yes
Contributors: 20
Funding: No

With more than 10 contributors for the colorcet repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: >=3.7

Age: 8 years
Latest Release: 9 months ago
Dependencies: 0 Direct
Versions: 23
Maintainers: 3
Wheels: OS Independent

Not sure how to use colorcet?

To help you get started, we've collected the most common ways that colorcet is being used within popular public projects.

HCsoft-RD / shaolin / shaolin / dashboards / colormap.py View on Github

def __init__(self,**kwargs):
        
        # Collapse all colormap aliases into a single string, and then sort by it
        inverse = {}
        inv_rev = {}
        for k,v in cc.cm.items():
            if not k[-2:] == "_r":
                inverse[v] = inverse.get(v, [])
                inverse[v].insert(0,k)
            else:
                inv_rev[v] = inverse.get(v, [])
                inv_rev[v].insert(0,k)
        all_cms = {',  '.join(reversed(v)):k for (k,v) in inverse.items()}.items()
        rev_cms = {',  '.join(reversed(v)):k for (k,v) in inv_rev.items()}.items()
        self._all_cmaps = dict([i for i in all_cms])
        self._rev_cmaps = dict([i for i in rev_cms])
        self._div_cms = dict([i for i in all_cms if "diverging" in i[0]])
        self._iso_cms = dict([i for i in all_cms if "isoluminant" in i[0]])
        self._linear_cms = dict([i for i in all_cms if "linear" in i[0]])
        self._cycle_cms = dict([i for i in all_cms if "cyclic" in i[0]])
        self._alias_cms = dict([(x.split(',')[1].lstrip(' '),v) for x,v in self._all_cmaps.items() if ',' in x])
        control_box = ['c$N=seaborn_palette',

View more ways to use colorcet

Colorcet: Collection of perceptually uniform colormaps


Build Status
Coverage
Latest dev release
Latest release
Python
Docs

What is it?

Colorcet is a collection of perceptually uniform colormaps for use with Python plotting programs like bokeh, matplotlib, holoviews, and datashader based on the set of perceptually uniform colormaps created by Peter Kovesi at the Center for Exploration Targeting.

Installation

Colorcet supports Python 3.7 and greater on Linux, Windows, or Mac and can be installed with conda:

conda install colorcet

or with pip:

python -m pip install colorcet

To work with JupyterLab you will also need the PyViz JupyterLab extension:

conda install -c conda-forge jupyterlab
jupyter labextension install @pyviz/jupyterlab_pyviz

Once you have installed JupyterLab and the extension launch it with:

jupyter-lab

If you want to try out the latest features between releases, you can get the latest dev release by installing:

conda install -c pyviz/label/dev colorcet

For more information take a look at Getting Started.

Learning more

You can see all the details about the methods used to create these colormaps in Peter Kovesi's 2015 arXiv paper. Other useful background is available in a 1996 paper from IBM.

The Matplotlib project also has a number of relevant resources, including an excellent 2015 SciPy talk, the viscm tool for creating maps like the four in mpl, the cmocean site collecting a set of maps created by viscm, and the discussion of how the mpl maps were created.

Samples

Some of the Colorcet colormaps that have short, memorable names (which are probably the most useful ones) are visible here:

But the complete set of 100+ is shown in the User Guide.

FAQs

What is colorcet?

Collection of perceptually uniform colormaps. Visit Snyk Advisor to see a full health score report for colorcet, including popularity, security, maintenance & community analysis.

Is colorcet popular?

The python package colorcet receives a total of 207,979 weekly downloads. As such, colorcet popularity was classified as an influential project. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is colorcet well maintained?

We found indications that colorcet maintenance is sustainable demonstrating some project activity. We saw a total of 20 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is colorcet safe to use?

The python package colorcet was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 21 November-2024, at 03:58 (UTC).

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colorcet

Collection of perceptually uniform colormaps For more information about how to use this package see README

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Not sure how to use colorcet?

Colorcet: Collection of perceptually uniform colormaps

What is it?

Installation

Learning more

Samples

FAQs

What is colorcet?

Is colorcet popular?

Is colorcet well maintained?

Is colorcet safe to use?

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Fix identified vulnerabilities

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Package Health Score

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Direct Usage Popularity

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Commit Frequency

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Not sure how to use colorcet?

Colorcet: Collection of perceptually uniform colormaps

What is it?

Installation

Learning more

Samples

FAQs

What is colorcet?

Is colorcet popular?

Is colorcet well maintained?

Is colorcet safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

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