aggregate_interpolate_points: Interpolate and temporal aggregate DWD values
In whamer/papros: PAthogen PROgnosis System

Description Usage Arguments Value Author(s) Examples

View source: R/aggregate_interpolate_points.R

This functions interpolates points based on a dataframe containing coordinates, an aim variable, an aim dataset and a parameter such as a date, by which the interpolations are divided

aggregate_interpolate_points(
  dataframe,
  coords,
  epsg,
  DateTime,
  infection,
  incubation,
  aim_variable,
  outputfile,
  trans_epsg = FALSE,
  co_variables = FALSE,
  procedure = c("ked", "ok", "idw"),
  progressbar = TRUE
)

`dataframe`	dataframe containing the aim variable and if "ked" should be applied the covariables
`coords`	vector containing names of the columns containing x and y coordinate values
`epsg`	number of the EPSG code of the "coords" information
`DateTime`	name of the DateTime column
`infection`	duration of the assumed infection
`incubation`	duration of the assumed incubation
`aim_variable`	Character string with the name of the aim variable
`outputfile`	SpatialPointsDataframe, SpatialGridDataFrame or raster which should be filled with predictions; requires covariables for "ked"
`trans_epsg`	default = FALSE, number of the EPSG code the "coords" information should be transformed to
`co_variables`	default = FALSE, vector of covariables if needed
`procedure`	default = c("ked","ok","idw"); vector containing the interpolation technic to be used; the first method is used and if this does not work out, the second, and so on
`progressbar`	default = TRUE; should a progressbar be generated?

a dataframe or a SpatialPointsDataFrame containing information about DWD locations in Germany

Wolfgang Hamer

# Download example data
shdat <- download_statewide_hourly_station_data(state = "Schleswig-Holstein", coord = TRUE)

shdat2 <- shdat %>%
    filter(DateTime < sort(unique(shdat$DateTime))[50])

example <- aggregate_interpolate_points(dataframe = shdat2,
                                       coords = c("lon","lat"),
                                       DateTime = "DateTime",
                                       infection=2,
                                       incubation=8,
                                       aim_variable ="Temperature",
                                       outputfile=c(1000,1000),
                                       co_variables = FALSE,
                                       procedure = c("ked","ok","idw"),
                                       epsg = 4326,
                                       trans_epsg = 25832)
plot(example[[1]])