Compute verification scores for deterministic forecasts.

Usage

det_verify(
  .fcst,
  parameter,
  thresholds = NULL,
  groupings = "lead_time",
  circle = NULL,
  hexbin = TRUE,
  num_bins = 30,
  show_progress = TRUE,
  ...
)

# S3 method for harp_det_point_df
det_verify(
  .fcst,
  parameter,
  thresholds = NULL,
  groupings = "lead_time",
  circle = NULL,
  hexbin = TRUE,
  num_bins = 30,
  show_progress = TRUE,
  fcst_model = NULL,
  ...
)

Arguments

.fcst: A harp_df or harp_list object with tables that have a column for observations, or a single forecast table.
parameter: The name of the column for the observations data. Can be the column name, quoted, or unquoted. If a variable it should be embraced - i.e. wrapped in {{}}.
thresholds: A numeric vector of thresholds for which to compute the threshold based scores. Set to NULL (the default) to only compute summary scores.
groupings: The groups for which to compute the scores. See group_by for more information of how grouping works.
circle: If set the parameter is assumed to be cyclic for bias calculations. Should be this distance around a circle in the units of the parameter, so would typically have a value of 360 for degrees or 2 * pi for radians.
hexbin: Logical. Whether to compute hexbins for forecast, observation pairs. Defaults to TRUE. See bin_fcst_obs for more details.
num_bins: The number of bins into which to partition observations for the hexbin computation.
show_progress: Logical - whether to show progress bars. Defaults to TRUE.
...: Reserved for methods.
fcst_model: The name of the forecast model to use in the fcst_model column of the output. If the function is dispatched on a harp_list object, the names of the harp_list are automatically used.