simulariatools

Overview

simulariatools is an open source package with a collection of functions and tools useful to pre and post process data for air quality modelling and assessment:

• contourPlot2() plots a production-ready contour map of a pollutant concentration field.
• plotAvgRad() plots the hourly average of solar radiation.
• plotAvgTemp() plots the average atmospheric temperature.
• plotStabilityClass() plots histograms of atmospheric stability class.
• vectorField() plots a simple vector field given two components.
• importRaster() imports a generic raster file.
• importADSOBIN() imports an ADSO/BIN raster file.
• importSurferGrd() imports a grid file.
• stabilityClass() computes atmospheric stability class.
• downloadBasemap()downloads GeoTIFF basemaps from the italian PCN.
• removeOutliers() removes time series outliers based on interquartile range.
• rollingMax() computes rolling max of a time series.

The package is developed and maintained at Simularia and it is widely used for their daily work.

If you use this package in your work, please consider citing it. Refer to its Zenodo DOI to cite it.

Installation

To install the latest release of simulariatools from CRAN:

install.packages("simulariatools")

NOTE: To import ADSO/BIN data files via importADSOBIN(), a working installation of Python3 is required. For more information about R and Python interoperability, refer to the documentation of reticulate.

Development version

To get bug fixes or to use a feature from the development version, install the development version from GitHub:

# install.packages("pak")
pak::pkg_install("Simularia/simulariatools")

Examples

Contour Plot

First, import air quality data from NetCDF or ADSO/BIN files with the appropriate convenience function:

library(simulariatools)
nox_concentration <- importRaster(
    file = "./development/conc_avg.nc",
    k = 1000,
    destaggering = TRUE,
    variable = "nox",
    verbose = TRUE
)
#> Raster statistics -----------------------------------------------
#>        X (min, max, dx)  :   496000.000   519250.000      250.000
#>        Y (min, max, dy)  :  4943000.000  4955250.000      250.000
#>      nox (min, max, mean):     0.00e+00     2.71e+00     1.52e-01
#> -----------------------------------------------------------------

Concentration data are imported as data.frame with x, y and z columns for coordinates and grid values.

str(nox_concentration)
#> 'data.frame':    4557 obs. of  3 variables:
#>  $ x: num  496125 496375 496625 496875 497125 ...
#>  $ y: num  4955125 4955125 4955125 4955125 4955125 ...
#>  $ z: num  0 0 0 0 0 0 0 0 0 0 ...

A quick contour plot, with default configuration, can be easily obtained by running contourPlot2() without any argument:

contourPlot2(nox_concentration)

The plot is customisable by using contourPlot2() arguments and by piping ggplot2 instructions with the + operator.

In the following example, the original domain is cropped, colour levels are explicitly assigned and a legend name is provided through function arguments. Furthermore, labs() and theme_minimal() functions from ggplot2 are used to remove axis labels and to change the overall theme:

library(ggplot2)
contourPlot2(
    nox_concentration,
    domain = c(502000, 519000, 4943125, 4955125, 5, 5),
    levels = c(-Inf, 0.5, 1, 1.5, 2, Inf),
    legend = "NOx [ug/m3]"
) +
    labs(x = NULL, y = NULL) +
    theme_minimal()

In order to save the last plot to file, you can directly use the ggplot2 function ggsave():

ggsave(filename = "~/path/to/myplot.png", width = 7, height = 6, dpi = 300)

Optional arguments can be used to create special versions of the plot. For example, use tile = TRUE to produce a non spatially interpolated plot:

contourPlot2(
    nox_concentration,
    tile = TRUE,
    legend = "NOx [ug/m3]"
)

Contact

Contact person:

Giuseppe Carlino (Simularia srl)

Contributors

Matteo Paolo Costa