JSON wrapper function for kwb.heatsine::run_optimisation

run_optimisation(
  data_sw_selected,
  data_gw_selected,
  retardation_factor = 1.8,
  sw_monitoring_id = attr(data_sw_selected, "monitoring_id"),
  gw_monitoring_id = attr(data_gw_selected, "monitoring_id"),
  limits = c(100, 500),
  tolerance = 0.001,
  debug = FALSE
)

Arguments

data_sw_selected	data.frame with daily data temperature data of surface water monitoring point with columns "date" (format: "YYYY-MM-DD") and "value" (format: double, temperature in degree Celsius) for selected time period
data_gw_selected	data.frame with daily data temperature data of groundwater monitoring point with columns "date" (format: "YYYY-MM-DD") and "value" (format: double, temperature in degree Celsius) for selected time period
retardation_factor	hydraulic retardation factor (default: 2)
sw_monitoring_id	optional label for surface water monitoring id (default: "surface-water monitoring point" or attr(data_sw_selected, "monitoring_id") if data imported with `load_temperature_from_csv`), otherwise can be any user-defined character string to be used as label for the monitoring point
gw_monitoring_id	optional label for groundwater monitoring id (default: "surface-water monitoring point" or attr(data_sw_selected, "monitoring_id") if data imported with `load_temperature_from_csv`), otherwise can be any user-defined character string to be used as label for the monitoring point
limits	minimum/maximum period length for sinus optimisation in days (default: c(100, 500))
tolerance	the desired accuracy (default: 0.001
debug	show debug messages (default: FALSE)

Value

json list with sim/observation data ("data") fit parameters ("paras"), goodness-of-fit values ("gof") traveltimes ("traveltimes") and special (min, max, turning) points ("points") as returned by get_predictions