Plot a time series of vertical profiles of class `vpts`

.

```
# S3 method for vpts
plot(
x,
xlab = "time",
ylab = "height [m]",
quantity = "dens",
log = NA,
barbs = TRUE,
barbs_height = 10,
barbs_time = 20,
barbs_dens_min = 5,
zlim,
legend_ticks,
legend.ticks,
main,
barbs.h = 10,
barbs.t = 20,
barbs.dens = 5,
na_color = "#C8C8C8",
nan_color = "white",
n_color = 1000,
palette = NA,
...
)
```

- x
A vp class object inheriting from class

`vpts`

.- xlab
A title for the x-axis.

- ylab
A title for the y-axis.

- quantity
Character string with the quantity to plot, one of '

`dens`

','`eta`

','`dbz`

','`DBZH`

' for density, reflectivity, reflectivity factor and total reflectivity factor, respectively.- log
Logical, whether to display

`quantity`

data on a logarithmic scale.- barbs
Logical, whether to overlay speed barbs.

- barbs_height
Integer, number of barbs to plot in altitudinal dimension.

- barbs_time
Integer, number of barbs to plot in temporal dimension.

- barbs_dens_min
Numeric, lower threshold in aerial density of individuals for plotting speed barbs in individuals/km^3.

- zlim
Optional numerical atomic vector of length 2, specifying the range of

`quantity`

values to plot.- legend_ticks
Numeric atomic vector specifying the ticks on the color bar.

- legend.ticks
Deprecated argument, use legend_ticks instead.

- main
A title for the plot.

- barbs.h
Deprecated argument, use barbs_height instead.

- barbs.t
Deprecated argument, use barbs_time instead.

- barbs.dens
Deprecated argument, use barbs_dens_min instead.

- na_color
Color to use for NA values, see class

`vpts`

conventions.- nan_color
Color to use for NaN values, see class

`vpts`

conventions.- n_color
The number of colors (>=1) to be in the palette.

- palette
(Optional) character vector of hexadecimal color values defining the plot color scale, e.g. output from viridis

- ...
Additional arguments to be passed to the low level image plotting function.

Aerial abundances can be visualized in four related quantities, as specified
by argument `quantity`

:

- "
`dens`

" the aerial density of individuals. This quantity is dependent on the assumed radar cross section (RCS) in the

`x$attributes$how$rcs_bird`

attribute- "
`eta`

" reflectivity. This quantity is independent of the value of the

`rcs_bird`

attribute- "
`dbz`

" reflectivity factor. This quantity is independent of the value of the

`rcs_bird`

attribute, and corresponds to the dBZ scale commonly used in weather radar meteorology. Bioscatter by birds tends to occur at much higher reflectivity factors at S-band than at C-band- "
`DBZH`

" total reflectivity factor. This quantity equals the reflectivity factor of all scatterers (biological and meteorological scattering combined)

Aerial velocities can be visualized in three related quantities, as specified
by argument `quantity`

:

- "
`ff`

" ground speed. The aerial velocity relative to the ground surface in m/s.

- "
`u`

" eastward ground speed component in m/s.

- "
`v`

" northward ground speed component in m/s.

In the speed barbs, each half flag represents 2.5 m/s, each full flag 5 m/s, each pennant (triangle) 25 m/s

```
# locate example file:
ts <- example_vpts
# plot density of individuals for the first 500 time steps, in the altitude
# layer 0-3000 m.
plot(ts[1:500], ylim = c(0, 3000))
#> Warning: Irregular time-series: missing profiles will not be visible. Use 'regularize_vpts' to make time series regular.
# plot total reflectivity factor (rain, birds, insects together):
plot(ts[1:500], ylim = c(0, 3000), quantity = "DBZH")
#> Warning: Irregular time-series: missing profiles will not be visible. Use 'regularize_vpts' to make time series regular.
# regularize the time grid, which includes empty (NA) profiles at
# time steps without data:
ts_regular <- regularize_vpts(ts)
#> projecting on 300 seconds interval grid...
plot(ts_regular)
# change the color of missing NA data to red
plot(ts_regular, na_color="red")
# change the color palette:
plot(ts_regular[1:1000], ylim = c(0, 3000), palette=viridis::viridis(1000))
# change and inverse the color palette:
plot(ts_regular[1:1000], ylim = c(0, 3000), palette=rev(viridis::viridis(1000, option="A")))
# plot the speed profile:
plot(ts_regular[1:1000], quantity="ff")
# plot the northward speed component:
plot(ts_regular[1:1000], quantity="v")
# plot speed profile with more legend ticks,
plot(ts_regular[1:1000], quantity="ff", legend_ticks=seq(0,20,2), zlim=c(0,20))
```