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Summarise z values over binned wind data.

Source: R/stat_summary_wind_2d.R
stat_summary_wind_2d.Rd

Binning is done by StatWind, so input data tostat_summary_wind() should be original unbinned data. Depending on the groups argument, binning is either done 2-dimensional over cartesian u and v wind vectors (calculated from input data; then, stat_summary_wind() yields results similar to openair::polarPlot()) or 1-dimensional over wind direction or wind velocity bins, respectively.

Usage

stat_summary_wind_2d(
  data = NULL,
  mapping = NULL,
  geom = "raster",
  position = "identity",
  ...,
  fun = "mean",
  fun.args = list(),
  nmin = 1,
  ws_max = NA,
  bins = 10^2,
  smooth = TRUE,
  k = 100,
  extrapolate = TRUE,
  dist = 0.1,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

data

The data to be displayed in this layer. Requires input data including at least three columns carrying information regarding: * wind direction (in °) * wind velocity * z-values (e.g. air pollutant concentration)

mapping

ggplot2 mapping, e.g. aes(wd = wd, ws = ws, z = NOx); requires wd, ws, z

geom

The geometric object to use display the data (in this case: raster).

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

  • The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

  • A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

  • For more information and other ways to specify the position, see the layer position documentation.

...

other arguments passed on to ggplot2::layer() as params = list(...).

fun

function or list of functions for summary.

fun.args

a list of extra arguments to pass to fun.

nmin

numeric, minimum number of values for fun, if n < nmin: NA is returned

ws_max

numeric or NA, maximum wind velocity for binning: above ws_max, z is set NA

bins

numeric, number of bins over the range of values if !groups %in% c("u", "v")

smooth

TRUE/FALSE, applies if groups = c("u", "v"); should smoothing of summary results should be performed using fit_gam_surface()?

k

numeric, applies if smooth = TRUE; degree of smoothing in smooth term in fit_gam_surface()

extrapolate

TRUE/FALSE, applies if smooth = TRUE; fit_gam_surface() returns extrapolated (predicted) values for u, v coordinates that otherwise would have have NA for summarised z if extrapolate = TRUE, those values are returned (to a certain degree depending on the value of dist)

dist

numeric, fraction of 1, applies if smooth = TRUE and extrapolate = TRUE; maximum distance to next coordinate-pair at which the result of fit_gam_surface(z) should be returned

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

Value

ggplot2 layer

Aesthetics

  • wd: wind direction in degrees

  • ws: wind velocity

  • z: z values to be summarised

Computed variables

  • If groups = c("u", "v"): a tibble is returned, binned over u and v, with variables:

  • wd: wind direction corresponding to midpoint value of u and v

  • ws: wind velocity corresponding to midpoint value of u and v

  • wd_class: new bins over wd considering binwidth

  • ws_class: new bins over ws considering binwidth and ws_max

  • u: bins over u (from input wd and ws)

  • v: bins over v (from input wd and ws)

  • z: result from fun(z, ...)

  • If groups = NULL: groups = "wd". In this case, bins are calculated over wind direction; a tibble including wd_class and summarised z is returned

  • groups can be strings for other varibables in data; then fun is applied over those; a tibble including groups and summarised z is returned

Examples

library(ggplot2)

fn <- rOstluft.data::f("Zch_Stampfenbachstrasse_2010-2014.csv")

df <- rOstluft::read_airmo_csv(fn) %>%
  rOstluft::rolf_to_openair()

ggplot(df, aes(x = stat(u), y = stat(v), fill = stat(z))) +
  stat_summary_wind_2d(mapping = aes(wd = wd, ws = ws, z = NO2), bins = 50^2) +
  coord_cartpolar() +
  scale_fill_viridis_c(na.value = NA)
#> Warning: Removed 767 rows containing non-finite outside the scale range
#> (`stat_summary_wind2d()`).
#> Warning: Removed 991 rows containing missing values or values outside the scale range
#> (`geom_raster()`).