clifro (version 3.2-5)

windrose: Plot a windrose

Description

Plot a windrose showing the wind speed and direction for given facets using ggplot2.

Usage

windrose(
  speed,
  direction,
  facet,
  n_directions = 12,
  n_speeds = 5,
  speed_cuts = NA,
  col_pal = "GnBu",
  ggtheme = c("grey", "gray", "bw", "linedraw", "light", "minimal", "classic"),
  legend_title = "Wind Speed",
  calm_wind = 0,
  variable_wind = 990,
  n_col = 1,
  ...
)

Arguments

speed

numeric vector of wind speeds.

direction

numeric vector of wind directions.

facet

character or factor vector of the facets used to plot the various windroses.

n_directions

the number of direction bins to plot (petals on the rose). The number of directions defaults to 12.

n_speeds

the number of equally spaced wind speed bins to plot. This is used if speed_cuts is NA (default 5).

speed_cuts

numeric vector containing the cut points for the wind speed intervals, or NA (default).

col_pal

character string indicating the name of the RColorBrewer colour palette to be used for plotting, see 'Theme Selection' below.

ggtheme

character string (partially) matching the ggtheme to be used for plotting, see 'Theme Selection' below.

legend_title

character string to be used for the legend title.

calm_wind

the upper limit for wind speed that is considered calm (default 0).

variable_wind

numeric code for variable winds (if applicable).

n_col

The number of columns of plots (default 1).

...

further arguments passed to theme.

Value

a ggplot object.

Theme Selection

For black and white windroses that may be preferred if plots are to be used in journal articles for example, recommended ggthemes are 'bw', 'linedraw', 'minimal' or 'classic' and the col_pal should be 'Greys'. Otherwise, any of the sequential RColorBrewer colour palettes are recommended for colour plots.

Details

This is intended to be used as a stand-alone function for any wind dataset. A different windrose is plotted for each level of the faceting variable which is coerced to a factor if necessary. The facets will generally be the station where the data were collected, seasons or dates. Currently only one faceting variable is allowed and is passed to facet_wrap with the formula ~facet.

See Also

theme for more possible arguments to pass to windrose.

Examples

# NOT RUN {
# Create some dummy wind data with predominant south to westerly winds, and
# occasional yet higher wind speeds from the NE (not too dissimilar to
# Auckland).

wind_df = data.frame(wind_speeds = c(rweibull(80, 2, 4), rweibull(20, 3, 9)),
                     wind_dirs = c(rnorm(80, 135, 55), rnorm(20, 315, 35)) %% 360,
                     station = rep(rep(c("Station A", "Station B"), 2),
                                   rep(c(40, 10), each = 2)))

# Plot a simple windrose using all the defaults, ignoring any facet variable
with(wind_df, windrose(wind_speeds, wind_dirs))

# Create custom speed bins, add a legend title, and change to a B&W theme
with(wind_df, windrose(wind_speeds, wind_dirs,
                       speed_cuts = c(3, 6, 9, 12),
                       legend_title = "Wind Speed\n(m/s)",
                       legend.title.align = .5,
                       ggtheme = "bw",
                       col_pal = "Greys"))

# Note that underscore-separated arguments come from the windrose method, and
# period-separated arguments come from ggplot2::theme().

# Include a facet variable with one level
with(wind_df, windrose(wind_speeds, wind_dirs, "Artificial Auckland Wind"))

# Plot a windrose for each level of the facet variable (each station)
with(wind_df, windrose(wind_speeds, wind_dirs, station, n_col = 2))

# }
# NOT RUN {
# Save the plot as a png to the current working directory
library(ggplot2)
ggsave("my_windrose.png")
# }
# NOT RUN {
# }