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Tools to Visualize CM SAF NetCDF Data
The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (< https://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsafvis' R-package provides a collection of R-operators for the analysis and visualization of CM SAF NetCDF data. CM SAF climate data records are provided for free via (< https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (< http://www.cmsaf.eu/R_toolbox>).
Visualise Correlations
An investigative tool designed to help users visualize correlations between variables in their datasets. This package aims to provide an easy and effective way to explore and visualize these correlations, making it easier to interpret and communicate results.
'Fitbit' Visualizations
Connection to the 'Fitbit' Web API < https://dev.fitbit.com/build/reference/web-api/> by including 'ggplot2' Visualizations, 'Leaflet' and 3-dimensional 'Rayshader' Maps. The 3-dimensional 'Rayshader' Map requires the installation of the 'CopernicusDEM' R package which includes the 30- and 90-meter elevation data.
A Toolbox for Manipulating and Assessing Colors and Palettes
Carries out mapping between assorted color spaces including RGB, HSV, HLS,
CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB, and polar CIELAB.
Qualitative, sequential, and diverging color palettes based on HCL colors
are provided along with corresponding ggplot2 color scales.
Color palette choice is aided by an interactive app (with either a Tcl/Tk
or a shiny graphical user interface) and shiny apps with an HCL color picker and a
color vision deficiency emulator. Plotting functions for displaying
and assessing palettes include color swatches, visualizations of the
HCL space, and trajectories in HCL and/or RGB spectrum. Color manipulation
functions include: desaturation, lightening/darkening, mixing, and
simulation of color vision deficiencies (deutanomaly, protanomaly, tritanomaly).
Details can be found on the project web page at < https://colorspace.R-Forge.R-project.org/>
and in the accompanying scientific paper: Zeileis et al. (2020, Journal of Statistical
Software,
Utility Functions and Data Sets for Data Visualization
Supporting materials for a course and book on data visualization. It contains utility functions for graphs and several sample data sets. See Healy (2019)
Item Pool Visualization
Generate plots based on the Item Pool Visualization concept for
latent constructs. Item Pool Visualizations are used to display the
conceptual structure of a set of items (self-report or psychometric).
Dantlgraber, Stieger, & Reips (2019)
Visualization and Analytics for the Cryptoverse
Providing data to quickly visualize and analyze data from several cryptocurrencies.
Visualizing Classification Results
Tools to visualize the results of a classification of cases.
The graphical displays include stacked plots, silhouette plots, quasi residual plots, and class maps.
Implements the techniques described and illustrated in Raymaekers, Rousseeuw and Hubert (2021), Class maps for visualizing classification results, Technometrics, appeared online.
Visualization for Seismic Tomography
Aimed at seismic tomography, the package plots tomographic images, and allows one to interact and query three-dimensional tomographic models. Vertical cross-sectional cuts can be extracted by mouse click. Geographic information can be added easily.
Antares Visualizations
Visualize results generated by Antares, a powerful open source software developed by RTE to simulate and study electric power systems (more information about 'Antares' here: < https://github.com/AntaresSimulatorTeam/Antares_Simulator>). This package provides functions that create interactive charts to help 'Antares' users visually explore the results of their simulations.