AFM-Learn

v0.8.3

A Python package for visualizing and analyzing Atomic Force Microscopy(AFM) and Piezoelectric Force Microscopy(PFM) experimental data, offering tools to process, visualize, and extract meaningful insights from AFM images and measurements. For more information about how to use this package see README

Latest version published 2 months ago

License: MIT

PyPI

GitHub

Package Health Score

67 / 100

security
Security review needed
popularity
Small
maintenance
Healthy
community
Sustainable

Popularity

Small

GitHub Stars: 2.13K
Forks: 185
Contributors: 60

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package AFM-Learn, we found that it has been starred 2,127 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Oct 16, 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
1
M
0
L

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

License

MIT

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 30
Open PR: 6
Last Release: 2 months ago
Last Commit: 2 months ago

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

We found that AFM-Learn demonstrates a positive version release cadence with at least one new version released in the past 3 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

Sustainable

Readme: Yes
Contributing.md: Yes
Code of Conduct: No
Contributors: 60
Funding: Yes

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

We found a way for you to contribute to the project! Looks like AFM-Learn is missing a Code of Conduct.

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Package

Python Versions Compatibility: Unspecified

Age: 3 months
Latest Release: 2 months ago
Dependencies: 4 Direct / 21 Total
Versions: 10
Maintainers: 0
Wheels: OS Independent

Readme

AFM-Learn

> A Python package for visualizing and analyzing Atomic Force > Microscopy(AFM) and Piezoelectric Force Microscopy(PFM) experimental > data, offering tools to process, visualize, and extract meaningful > insights from AFM images and measurements.

This Python package provides a suite of tools for the visualization and analysis of Atomic Force Microscopy (AFM) experimental data. Designed for researchers working with AFM techniques, the package simplifies the processing of raw AFM data, including height, amplitude, and phase images. The built-in functionality allows users to visualize AFM scans in image and video if temporal dependent data, apply filters for noise reduction, and extract key metrics such as roughness, feature dimensions, and ferroelectric domain structures.

Key features: - Support for multiple AFM data formats (e.g., .spm, .afm, .ibw). - Real-time 2D and 3D visualization of AFM data. - Data filtering and smoothing techniques. - Tools for extracting quantitative measurements from AFM images. - Customizable workflows for domain structure analysis.

This package is particularly useful for materials science researchers and AFM users who want to streamline data processing and explore advanced data processing and analysis.

Note

This project has been set up using PyScaffold 4.6. For details and usage information on PyScaffold see .

AFM-Learn dependencies

imutils opencv-python seaborn xrayutilities

FAQs

What is AFM-Learn?

A Python package for visualizing and analyzing Atomic Force Microscopy(AFM) and Piezoelectric Force Microscopy(PFM) exp... Visit Snyk Advisor to see a full health score report for AFM-Learn, including popularity, security, maintenance & community analysis.

Is AFM-Learn popular?

We’re still processing downloads data for the python package AFM-Learn. Visit the popularity section on Snyk Advisor to see the full popularity analysis.

Is AFM-Learn well maintained?

We found that AFM-Learn demonstrated a healthy version release cadence and project activity. It has a community of 60 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is AFM-Learn safe to use?

While scanning the latest version of AFM-Learn, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 10 December-2024, at 02:51 (UTC).

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Readme

AFM-Learn

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AFM-Learn dependencies

FAQs

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Source Code

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