unmixing | Interactive tools for spectral mixture analysis

by arthur-e Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | unmixing Summary

unmixing is a Python library typically used in Internet of Things (IoT) applications. unmixing has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Interactive tools for spectral mixture analysis of multispectral raster data in Python

Support

Quality

Security

License

Reuse

Support

unmixing has a low active ecosystem.

It has 55 star(s) with 17 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 5 have been closed. On average issues are closed in 122 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of unmixing is current.

Quality

unmixing has 0 bugs and 0 code smells.

Security

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

unmixing code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

unmixing 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

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

Build file is available. You can build the component from source.

unmixing saves you 824 person hours of effort in developing the same functionality from scratch.

It has 1891 lines of code, 125 functions and 10 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed unmixing and discovered the below as its top functions. This is intended to give you an instant insight into unmixing implemented functionality, and help decide if they suit your requirements.

Interpolate an array of endmember bands
Apply binary mask to raster
Interpolate the end member spectrogram
Plot the feature space
Reset the plot
Validate the reference image using the forward model
Rearrange an image
Predict spectra from an abundance matrix
Raise an array
Intersect two rasters
Performs a mask of the ledaps
Combine rasters
Calculates the dynamic range of a raster
Generate a mask from a raster
Convert raster coordinates to kml
Plot the spectral profile
Calculate the tasseled et al
Generate the cumulative frequency distribution plot
Get the pixel coordinates as a SHP image file
Plot a tasseled feature space
Plot the MNF feature space
Plot a list of coords
R Aasseled HASseled CAPT
Convert pixel coordinates to GeoJSON
Compute end members of a rast
Event handler
Plot a matplotlib histogram

Get all kandi verified functions for this library.

unmixing Key Features

No Key Features are available at this moment for unmixing.

unmixing Examples and Code Snippets

No Code Snippets are available at this moment for unmixing.

Community Discussions

Trending Discussions on unmixing

Trouble with the unmixing matrix from fastica toolbox in Matlab

QUESTION

Trouble with the unmixing matrix from fastica toolbox in Matlab

Asked 2020-Apr-28 at 17:53

I'm using the FastIca toolbox (https://research.ics.aalto.fi/ica/fastica/) but am confused about the orientation of the resulting W (separating/unmixing) matrix.

Let X be a n x B matrix where n is the number of signals in a data set and B is the number of time points sampled at.

I've been calculating the W matrix using:

...

ANSWER

Answered 2020-Apr-28 at 17:53

It should be Y=W*X. To be sure, you can reduce the number of component to estimate and then W should no longer be square:

Source https://stackoverflow.com/questions/61465345

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

Vulnerabilities

No vulnerabilities reported

Install unmixing

You can download it from GitHub.
You can use unmixing 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 .

Find more information at: