Timeseries Leaflet Map

Creates a timeseries leaflet map that displays point location time series data and allows playback with a slider and "Play" button.

timeseriesMap(data, meta, index = "monitorID", label = "label", ...)

Arguments

data	Dataframe that contains point location time series data. See Details.
meta	Dataframe that contains the point location metadata. See Details.
index	Column name in meta containing the unique identifier for each location.
label	Column name in meta containing the human readable label associated with each location. This is displayed when mousing over a location.
...	Additional arguments. See details.

Details

Use of this function requires data and meta dataframes that are linked by location-specific unique identifiers. In meta, each row contains location metadata associated with a unique timeseries. The unique identifiers for are found in meta[[index]]. The data dataframe uses these identifiers as column names with a separate column of data for each timeseries.

data must be a dataframe of regular time series data. The data dataframe must contain one 'datetime' column. All other columns must have the names specified in meta[[index]].

meta must be a dataframe that contains location information associated with the timeseries found in data. The meta dataframe must contain a column with the name specified with index and another with the column name specified with label.

... Additional (optional) configuration arguments:

• width -- widget width

• height -- widget_height

• colors -- colors

• breaks -- color ramp breaks

• elementId -- HTML element ID

• inputId -- shiny input ID

Note

When specifying colors and breaks, you must use the d3 idiom where the vector of colors is one longer than the vector of breaks. Everything below the lowest break gets the lowest color. Everything above the highest break gets the highest color.

Examples

library(tiotemp)

# Example using PWFSLSmoke 'ws_monitor' object

sensor <- example_pwfslsmoke_object

timeseriesMap(
  data = sensor$data,
  meta = sensor$meta,
  index = "monitorID",
  label = "siteName",
  colors = c("#00E400","#FFFF00","#FF7E00","#FF0000","#8F3F97","#7E0023"),
  breaks = c(12.0, 35.5,  55.5, 150.5, 250.5)
)

# Example using AirSensor 'airsensor' object

sensor <- example_airsensor_object

timeseriesMap(
  data = sensor$data,
  meta = sensor$meta,
  index = "deviceDeploymentID",
  label = "label"
)