Package 'plotdap'

Add ggplot2 elements to a plotdap object

Description

add_ggplot allows for plotdap ggplot maps to be modified by further ggplot2 settings

Usage

add_ggplot(plot, ...)

Arguments

plot	a plotdap object.
...	arguments passed along to geom_sf() (if method='ggplot2', otherwise ignored).

Value

A plotdap object

Examples

p <- plotdap(
  crs = "+proj=laea +y_0=0 +lon_0=155 +lat_0=-90 +ellps=WGS84 +no_defs")
p <- add_ggplot(
 p,
 ggplot2::theme_bw()
)

---

Add rerddap::griddap() data to a plotdap map

Description

add_griddap adds the data from an 'rerddap::griddap() call to a 'plotdap' map

Usage

add_griddap(
  plot,
  grid,
  var,
  fill = "viridis",
  maxpixels = 10000,
  time = mean,
  animate = FALSE,
  cumulative = FALSE,
  ...
)

Arguments

plot	a plotdap object.
grid	a griddap object.
var	a formula defining a variable, or function of variables to visualize.
fill	either a character string of length 1 matching a name in the package cmocean or a vector of color codes. This defines the colorscale used to encode values of var.
maxpixels	integer > 0. Maximum number of cells to use for the plot. If maxpixels < ncell(x), sampleRegular is used before plotting. If gridded=TRUE maxpixels may be ignored to get a larger sample
time	how to resolve multiple time frames. Choose one of the following: A function to apply to each observation at a particular location (mean is the default). A character string (of length 1) matching a time value.
animate	whether to animate over the time variable (if it exists). Currently only implemented for method='ggplot2' and requires the gganimate package.
cumulative	- if animation should be cumulative -default FALSE
...	arguments passed along to geom_sf() (if method='ggplot2', otherwise ignored).

Value

A plotdap object

Examples

# base plotting tends to be faster,
# but is less extensible plotdap("base")

# actual datasets in data folder to meet execution timings


 # murSST <- rerddap::griddap(
 #  ' jplMURSST41', latitude = c(35, 40), longitude = c(-125, -120.5),
 #   time = c('last', 'last'), fields = 'analysed_sst'
 # )

 # QMwind <- rerddap::griddap(
 #  'erdQMwindmday', time = c('2016-11-16', '2017-01-16'),
 #  latitude = c(30, 50), longitude = c(210, 240),
 #  fields = 'x_wind'
 #  )

p <- plotdap(crs = "+proj=robin")
p <- add_griddap(p, murSST, ~analysed_sst)

 # p <- plotdap(mapTitle = "Average wind over time")
 # p <- add_griddap(p, QMwind, ~x_wind)

# p <- plotdap("base", crs = "+proj=robin")
# p <- add_griddap(p, murSST, ~analysed_sst)

# layer tables on top of grids
require(magrittr)
p <- plotdap("base") %>%
  add_griddap(murSST, ~analysed_sst) %>%
  add_tabledap(sardines, ~subsample_count)

# multiple time periods
p <- plotdap("base", mapTitle = "Average wind over time")
p <- add_griddap(p, QMwind, ~x_wind)

---

Add contour lines to a plotdap object

Description

Computes isolines from a griddap data frame and appends them as a geom_sf() layer to the plotdap object's internal ggplot. Call this before add_ggplot() or print().

Usage

add_griddap_contours(
  p,
  data,
  var,
  n_breaks = 10L,
  breaks = NULL,
  lon_col = "longitude",
  lat_col = "latitude",
  color = "black",
  linewidth = 0.3,
  alpha = 1,
  crs = 4326L
)

Arguments

p	a plotdap object (result of plotdap() piped through add_griddap()). Not the result of add_ggplot().
data	data frame typically dat$data from a griddap() call.
var	character; name of the variable column to contour.
n_breaks	integer; number of evenly-spaced interior contour levels (ignored when breaks is supplied). Default 10.
breaks	numeric vector of explicit contour levels, or NULL.
lon_col	name of longitude column (default "longitude").
lat_col	name of latitude column (default "latitude").
color	contour line color (default "black").
linewidth	contour line width (default 0.3).
alpha	opacity 01 (default 1).
crs	integer EPSG code for the data (default 4326).

Value

the plotdap object with contour lines added to its internal ggplot. Pipe the result to add_ggplot() or print() as usual.

Examples

## Not run: 
  library(rerddap)
  library(plotdap)

  myURL <- "https://coastwatch.pfeg.noaa.gov/erddap/"
  info <- rerddap::info("jplMURSST41", url = myURL)
  dat  <- griddap(info,
            latitude  = c(30, 50),
            longitude = c(-140, -110),
            time      = c("2020-06-15", "2020-06-15"),
            fields    = "analysed_sst")

  p <- plotdap() |>
         add_griddap(dat, ~analysed_sst)

  ## Default: 10 evenly-spaced contour levels, then render
  p |> add_griddap_contours(dat$data, "analysed_sst") |> add_ggplot()

  ## Explicit break values
  p |> add_griddap_contours(dat$data, "analysed_sst",
                             breaks = c(10, 12, 14, 16, 18, 20)) |> add_ggplot()

  ## More levels, thinner grey lines
  p |> add_griddap_contours(dat$data, "analysed_sst",
                             n_breaks = 20, color = "grey40", linewidth = 0.2) |>
       add_ggplot()

## End(Not run)

---

Add rerddap::tabledap data to a plotdap map

Description

add_tabledap adds the data from an 'rerddap::tabledap()' call to a 'plotdap' map

Usage

add_tabledap(
  plot,
  table,
  var,
  color = c("#132B43", "#56B1F7"),
  size = 1.5,
  shape = 19,
  animate = FALSE,
  cumulative = FALSE,
  ...
)

Arguments

plot	a plotdap object.
table	a tabledap object.
var	a formula defining a variable, or function of variables to visualize.
color	either a character string of length 1 matching a name in cmocean or a vector of color codes. This defines the colorscale used to encode values of var.
size	the size of the symbol.
shape	the shape of the symbol. For valid options, see the 'pch' values section on points. plot(0:25, 0:25, pch = 0:25) also gives a quick visual of the majority of possibilities.
animate	whether to animate over the time variable (if it exists). Currently only implemented for method='ggplot2' and requires the gganimate package.
cumulative	- if animation should be cumulative -default FALSE
...	arguments passed along to geom_sf() (if method='ggplot2', otherwise ignored).

Value

A plotdap object

Examples

# base plotting tends to be faster,
# but is less extensible plotdap("base")

# test datasets in data folder to meet execution timings
# code given to extract the data


sardines <- rerddap::tabledap(
 'FRDCPSTrawlLHHaulCatch',
 fields = c('latitude',  'longitude', 'time', 'scientific_name', 'subsample_count'),
  'time>=2010-01-01', 'time<=2012-01-01',
  'scientific_name="Sardinops sagax"'
  )


p <- plotdap()
p1 <- add_tabledap(p, sardines, ~subsample_count)
p2 <- add_tabledap(p, sardines, ~log2(subsample_count))

# using base R plotting
p <- plotdap("base")
p <- add_tabledap(p, sardines, ~subsample_count)

# robinson projection
p <- plotdap(crs = "+proj=robin")
p <- add_tabledap(p, sardines, ~subsample_count)

---

change bounding box in plotdap object

Description

bbox_setchanges the bounding box in an plotdap object. Particularly needed if using gganimate::animate()

Usage

bbox_set(
  plotobj,
  landmask = TRUE,
  xlim = NULL,
  ylim = NULL,
  interactive = FALSE
)

Arguments

plotobj	valid plotdap object
landmask	optional: if true land is plotted over the data
xlim	optional: new x-values of the bounding box otherwise taken from the plotdap object
ylim	optional: new y-values of the bounding box otherwise taken from the plotdap object
interactive	optional: if true creates an interactive version of the graphic

Value

a ggplot object with reset limits. If interactive is true, then returns a ggplot object that will work with the 'plotly' package.

Examples

p <- plotdap()
p <- add_tabledap(p, sardines, ~subsample_count)
xlim = c(-125, -115)
ylim <- c(30., 50.)
p <- bbox_set(p, xlim = xlim, ylim = ylim)

---

murSST Data

Description

pre-Download of murSST in 'add_griddap()' example so that example can run within CRAN Time limits

Usage

murSST

Format

An object of class griddap_nc (inherits from nc, data.frame) with 0 rows and 2 columns.

Details

obtained using the 'rerddap' command murSST <- griddap( 'jplMURSST41', latitude = c(22, 51), longitude = c(-140, -105), time = c('last', 'last'), fields = 'analysed_sst' )

---

Visualize rerddap data

Description

Visualize data returned from rerddap servers. Use plotdap() to initialize a plot, specify the plotting method (specifically, 'base' or 'ggplot2'), and set some global options/parameters. Then use add_tabledap() and/or add_griddap() to add "layers" of actual data to be visualized.

Usage

plotdap(
  method = c("ggplot2", "base"),
  mapData = maps::map("world", plot = FALSE, fill = TRUE),
  crs = NULL,
  datum = sf::st_crs(4326),
  mapTitle = NULL,
  mapFill = "gray80",
  mapColor = "gray90",
  ...
)

Arguments

method	the plotting method. Currently ggplot2 and base plotting are supported.
mapData	an object coercable to an sf object via st_as_sf().
crs	a coordinate reference system: integer with the epsg code, or character with proj4string.
datum	crs that provides datum to use when generating graticules. Set to NULL to hide the graticule.
mapTitle	a title for the map.
mapFill	fill used for the map.
mapColor	color used to draw boundaries of the map.
...	arguments passed along to geom_sf() (if method='ggplot2', otherwise ignored).

Details

The "ggplot2" method is slower than "base" (especially for high-res grids/rasters), but is more flexible/extensible. Additional ggplot2 layers, as well as scale defaults, labels, theming, etc. may be modified via the add_ggplot() function. See the mapping vignette for an introduction and overview of rerddap's visualization methods – browseVignettes(package = "rerddap").

Value

A plotdap object

Author(s)

Carson Sievert

See Also

tabledap(), griddap()

Examples

# base plotting tends to be faster (especially for grids),
# but is less extensible plotdap("base")

 plotdap()
 plotdap("base")

---

Print a ggplot plotdap object

Description

Print a ggplot plotdap object

Usage

## S3 method for class 'ggplotdap'
print(x, ...)

Arguments

x	a ggplotdap object
...	currently unused

---

Print a plotdap object

Description

Print a plotdap object

Usage

## S3 method for class 'plotdap'
print(x, ...)

Arguments

x	a plotdap object
...	currently unused

---

QMwind Data

Description

pre-Download of QMwind in 'add_griddap()' example so that example can run within CRAN Time limits

Usage

QMwind

Format

An object of class griddap_nc (inherits from nc, data.frame) with 0 rows and 2 columns.

Details

obtained using the 'rerddap' command wind <- griddap('erdQMwindmday', time = c('2016-11-16', '2017-01-16'), latitude = c(30, 50), longitude = c(210, 240), fields = 'x_wind') )

---

sardine Data

Description

pre-Download of sardine data in 'add_tabledap()' example so that example can run within CRAN Time limits

Usage

sardines

Format

An object of class tabledap (inherits from data.frame) with 56 rows and 5 columns.

Details

obtained using the 'rerddap' command sardines <- tabledap( 'FRDCPSTrawlLHHaulCatch', fields = c('latitude', 'longitude', 'time', ' scientific_name', 'subsample_count'), 'time>=2010-01-01', 'time<=2012-01-01', 'scientific_name="Sardinops sagax"') )

---