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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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LPSE data for ray-based CBET test cases

Authors: Follett, R. K.;

LPSE data for ray-based CBET test cases

Abstract

This dataset contains field data from LPSE simulations for the purpose of validating ray-based CBET models. The input parameters required to replicate these results are given in the Physics of Plasmas paper "Validation of ray-based cross-beam energy transfer models." All of the data is stored in HDF5 files. Each file has three data sets: Ez, xAxis, and yAxis (the 1-D datset does not have yAxis). Here is an example of the Matlab code to open and plot one of the 2-D files: filename = 'two_beam_at_caustic.h5'; hInfo = h5info(filename ); data = h5read(filename , '/Ez'); xAxis = h5read(filename , '/x_axis'); yAxis = h5read(filename , '/y_axis'); figure(1); clf; imagesc(yAxis, xAxis, data), colorbar, axis xy Here is an example of the Python code to open and plot one of the 2-D files: import h5py import matplotlib.pyplot as plt filename = 'two_beam_at_caustic.h5' f = h5py.File(filename, 'r') Ez = list(f["Ez"]) x_axis = list(f["x_axis"]) y_axis = list(f["y_axis"]) plt.figure() plt.pcolormesh(x_axis,y_axis,Ez) plt.colorbar() plt.show()

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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