ellipsoid_fit_python | Find ellipsoid fit for arbitrary data | Data Manipulation library

by aleksandrbazhin Python Version: Current License: MIT

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kandi X-RAY | ellipsoid_fit_python Summary

ellipsoid_fit_python is a Python library typically used in Utilities, Data Manipulation, Numpy applications. ellipsoid_fit_python has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However ellipsoid_fit_python build file is not available. You can download it from GitHub.

Find ellipsoid fit for arbitrary data with python/numpy, plot it or write to file.

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Support

ellipsoid_fit_python has a low active ecosystem.

It has 50 star(s) with 15 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 8 have been closed. On average issues are closed in 4 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ellipsoid_fit_python is current.

Quality

ellipsoid_fit_python has 0 bugs and 0 code smells.

Security

ellipsoid_fit_python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

ellipsoid_fit_python code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ellipsoid_fit_python is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

ellipsoid_fit_python releases are not available. You will need to build from source code and install.

ellipsoid_fit_python has no build file. You will be need to create the build yourself to build the component from source.

ellipsoid_fit_python saves you 54 person hours of effort in developing the same functionality from scratch.

It has 142 lines of code, 3 functions and 4 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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ellipsoid_fit_python Key Features

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ellipsoid_fit_python Examples and Code Snippets

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Community Discussions

Trending Discussions on ellipsoid_fit_python

Fitting 3D ellipsoid to points in 3D space - different methods, different answers

QUESTION

Fitting 3D ellipsoid to points in 3D space - different methods, different answers

Asked 2021-Mar-24 at 19:23

I have a large 3D point cloud that I'm trying to define the shape, size and volume of. I'm using scipy.spatial.convexHull to find the convex hull of the point cloud which gives me the volume of the point cloud and I'm then using the vertices of the convex hull to fit an ellipsoid to that to define the size and shape. I identified two possible python modules for fitting of the ellipsoid : pyEllipsoid_Fit (https://github.com/marksemple/pyEllipsoid_Fit) and ellipsoid_fit_python (https://github.com/aleksandrbazhin/ellipsoid_fit_python) which both seem to derived from the same MATLAB library by Yury Petrov. This all sounds pretty simple.

I've shown a reduced set of points from my convex hull to give an idea of its shape but it's about 30,000 points in the cloud and the convex hull has about 2,000 vertices.

...

ANSWER

Answered 2021-Mar-24 at 19:23

In comparing these two approaches, both use a least squares approach but ellipsoid_fit_LS is assuming that the major axes of the ellipse align with (x, y, z) whereas the matlab knock-offs don't make this assumption. That is, they are more general and will produce better fits for ellipsoids that are tilted relative to the coordinate axes but therefore have more parameters to fit.

Good but different fits to data are always like this, with similar but not identical results. In general, a good start is to choose a fitting algorithm that has the fewest free parameters as possible but is consistent with the data and your model.

Source https://stackoverflow.com/questions/66780826

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install ellipsoid_fit_python

You can download it from GitHub.
You can use ellipsoid_fit_python like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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