Create an archival timeseries plot for one or more monitors

This function assembles various layers to create a production-ready archival timeseries plot for one or more monitors.

monitor_ggTimeseries_archival(
  monitor,
  startdate = NULL,
  enddate = NULL,
  id = NULL,
  style = c("large", "small"),
  title = NULL,
  timezone = NULL,
  ...
)

Arguments

monitor

A mts_monitor object.

startdate

Desired start date (integer or character in ymd format or POSIXct).

enddate

Desired end date (integer or character in ymd format or POSIXct).

id

vector of deviceDeploymentIDs to include in the plot. If more than one, different monitors will be plotted in different colors.

style

Plot style. small or large. style = small is appropriate for plots 450x450px or smaller; style = large is appropriate for plots larger than 450x450px.

title

Plot title. If NULL, a suitable title will be constructed.

timezone

Olson timezone name for x-axis scale and date parsing. If NULL the timezone of the specified monitor will be used.

...

Arguments passed onto ggplot_pm25Timeseries.

Value

A ggplot object.

Examples

library(AirMonitorPlots)

AirMonitor::NW_Megafires %>%
  monitor_ggTimeseries_archival(
    startdate = 20150809,
    enddate = 20150820,
    id = "d01b991c53583048_160690012_03",
    timezone = "America/Los_Angeles"
 )
#> Warning: The following aesthetics were dropped during statistical transformation: x and
#> y.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: Removed 805 rows containing missing values or values outside the scale range
#> (`geom_pm25points()`).
#> Warning: Removed 805 rows containing missing values or values outside the scale range
#> (`geom_path()`).


AirMonitor::Carmel_Valley %>%
  AirMonitor::monitor_trimDate() %>%
  monitor_ggTimeseries_archival()
#> Warning: The following aesthetics were dropped during statistical transformation: x and
#> y.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: Removed 9 rows containing missing values or values outside the scale range
#> (`geom_pm25points()`).
#> Warning: Removed 11 rows containing missing values or values outside the scale range
#> (`geom_path()`).