Plot_band | plot band structure from vasp and vaspkit | Data Visualization library

by hetian-chen Python Version: Current License: No License

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

kandi X-RAY | Plot_band Summary

Plot_band is a Python library typically used in Analytics, Data Visualization applications. Plot_band has no bugs, it has no vulnerabilities and it has low support. However Plot_band build file is not available. You can download it from GitHub.

plot band structure from vasp and vaspkit. some codes for ploting band strcture from vasp and vaspkit. future: plot fatband for non-collinear magnetic system.

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Support

Plot_band has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

Plot_band has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Plot_band is current.

Quality

Plot_band has 0 bugs and 0 code smells.

Security

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

Plot_band code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Plot_band does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

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

It has 52 lines of code, 5 functions and 1 files.

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

Top functions reviewed by kandi - BETA

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

function to plot band structure
Initialize the plot .
returns a dataframe
Set tick labels .
Run the main loop

Get all kandi verified functions for this library.

Plot_band Key Features

No Key Features are available at this moment for Plot_band.

Plot_band Examples and Code Snippets

No Code Snippets are available at this moment for Plot_band.

Community Discussions

Trending Discussions on Plot_band

How to calculate Multispectral Vegetation Indices using Python

QUESTION

How to calculate Multispectral Vegetation Indices using Python

Asked 2020-Nov-27 at 03:06

I am trying to calculate Multispectral Vegetation Indices from multi spectral photos, using Python.

So far, I've managed to calculate the NDVI, which is easy to implement as there are many examples online.

...

ANSWER

Answered 2020-Nov-27 at 03:06

To use the Burned Area Index, the data must be calibrated to reflectance. There are other vegetation indices:

Kauth-Thomas Transformation (tasslled cap) http://web.pdx.edu/~jduh/courses/Archive/geog481w07/Students/Marcello_TasselledCap.pdf
NDMI or NDWI https://www.usgs.gov/core-science-systems/nli/landsat/normalized-difference-moisture-index
SAVI https://www.usgs.gov/core-science-systems/nli/landsat/landsat-soil-adjusted-vegetation-index
and other exemple here https://www.usgs.gov/core-science-systems/nli/landsat/landsat-surface-reflectance-derived-spectral-indices?qt-science_support_page_related_con=0#qt-science_support_page_related_con

You can apply the different indices in python or R (which cointains pre-establish packages for the manipulation). Other options are QGIS, PCI Geomatica (license needed) and ArcMAP (license Needed).

Source https://stackoverflow.com/questions/64928713

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

Vulnerabilities

No vulnerabilities reported

Install Plot_band

You can download it from GitHub.
You can use Plot_band 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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