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det_verify.Rd
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/det_verify.R
\name{det_verify}
\alias{det_verify}
\alias{det_verify.harp_det_point_df}
\title{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,
...
)
\method{det_verify}{harp_det_point_df}(
.fcst,
parameter,
thresholds = NULL,
groupings = "lead_time",
circle = NULL,
hexbin = TRUE,
num_bins = 30,
show_progress = TRUE,
fcst_model = NULL,
...
)
}
\arguments{
\item{.fcst}{A \code{harp_df} or \code{harp_list} object with tables that have a column
for observations, or a single forecast table.}
\item{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 \code{{{}}}.}
\item{thresholds}{A numeric vector of thresholds for which to compute the
threshold based scores. Set to NULL (the default) to only compute summary
scores.}
\item{groupings}{The groups for which to compute the scores. See
\link[dplyr]{group_by} for more information of how grouping works.}
\item{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 \code{2 * pi}
for radians.}
\item{hexbin}{Logical. Whether to compute hexbins for forecast, observation
pairs. Defaults to \code{TRUE}. See \link{bin_fcst_obs} for more details.}
\item{num_bins}{The number of bins into which to partition observations for
the hexbin computation.}
\item{show_progress}{Logical - whether to show progress bars. Defaults to
\code{TRUE}.}
\item{...}{Reserved for methods.}
\item{fcst_model}{The name of the forecast model to use in the \code{fcst_model}
column of the output. If the function is dispatched on a \code{harp_list}
object, the names of the \code{harp_list} are automatically used.}
}
\description{
Compute verification scores for deterministic forecasts.
}