diff --git a/include/evalhyd/detail/determinist/elements.hpp b/include/evalhyd/detail/determinist/elements.hpp
index ab4f8955c59fb7a1bd2d1bbc4c10007f2fb526c1..74007923355a95f16279450a2fed03d9c6c68969 100644
--- a/include/evalhyd/detail/determinist/elements.hpp
+++ b/include/evalhyd/detail/determinist/elements.hpp
@@ -17,26 +17,26 @@ namespace evalhyd
{
namespace elements
{
- // Compute the mean of the observations.
- //
- // \param q_obs
- // Streamflow observations.
- // shape: (1, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Mean observed streamflow.
- // shape: (subsets, samples, series, 1)
+ /// Compute the mean of the observations.
+ ///
+ /// \param q_obs
+ /// Streamflow observations.
+ /// shape: (1, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Mean observed streamflow.
+ /// shape: (subsets, samples, series, 1)
template <class XD2>
inline xt::xtensor<double, 4> calc_mean_obs(
const XD2& q_obs,
@@ -69,26 +69,26 @@ namespace evalhyd
return mean_obs;
}
- // Compute the mean of the predictions.
- //
- // \param q_prd
- // Streamflow predictions.
- // shape: (series, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Mean predicted streamflow.
- // shape: (subsets, samples, series, 1)
+ /// Compute the mean of the predictions.
+ ///
+ /// \param q_prd
+ /// Streamflow predictions.
+ /// shape: (series, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Mean predicted streamflow.
+ /// shape: (subsets, samples, series, 1)
template <class XD2>
inline xt::xtensor<double, 4> calc_mean_prd(
const XD2& q_prd,
@@ -121,17 +121,17 @@ namespace evalhyd
return mean_prd;
}
- // Compute the quadratic error between observations and predictions.
- //
- // \param q_obs
- // Streamflow observations.
- // shape: (1, time)
- // \param q_prd
- // Streamflow predictions.
- // shape: (series, time)
- // \return
- // Quadratic errors between observations and predictions.
- // shape: (series, time)
+ /// Compute the quadratic error between observations and predictions.
+ ///
+ /// \param q_obs
+ /// Streamflow observations.
+ /// shape: (1, time)
+ /// \param q_prd
+ /// Streamflow predictions.
+ /// shape: (series, time)
+ /// \return
+ /// Quadratic errors between observations and predictions.
+ /// shape: (series, time)
template <class XD2>
inline xt::xtensor<double, 2> calc_quad_err(
const XD2& q_obs,
@@ -141,28 +141,28 @@ namespace evalhyd
return xt::square(q_obs - q_prd);
}
- // Compute the quadratic error between observations and mean observation.
- //
- // \param q_obs
- // Streamflow observations.
- // shape: (series, time)
- // \param mean_obs
- // Mean observed streamflow.
- // shape: (subsets, samples, series, 1)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param n_srs
- // Number of prediction series.
- // \param n_tim
- // Number of time steps.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Quadratic errors between observations and mean observation.
- // shape: (subsets, samples, series, time)
+ /// Compute the quadratic error between observations and mean observation.
+ ///
+ /// \param q_obs
+ /// Streamflow observations.
+ /// shape: (series, time)
+ /// \param mean_obs
+ /// Mean observed streamflow.
+ /// shape: (subsets, samples, series, 1)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_tim
+ /// Number of time steps.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Quadratic errors between observations and mean observation.
+ /// shape: (subsets, samples, series, time)
template <class XD2>
inline xt::xtensor<double, 4> calc_quad_obs(
const XD2& q_obs,
@@ -194,28 +194,28 @@ namespace evalhyd
return quad_obs;
}
- // Compute the quadratic error between predictions and mean prediction.
- //
- // \param q_prd
- // Streamflow predictions.
- // shape: (series, time)
- // \param mean_prd
- // Mean predicted streamflow.
- // shape: (subsets, samples, series, 1)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param n_srs
- // Number of prediction series.
- // \param n_tim
- // Number of time steps.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Quadratic errors between predictions and mean prediction.
- // shape: (subsets, samples, series, time)
+ /// Compute the quadratic error between predictions and mean prediction.
+ ///
+ /// \param q_prd
+ /// Streamflow predictions.
+ /// shape: (series, time)
+ /// \param mean_prd
+ /// Mean predicted streamflow.
+ /// shape: (subsets, samples, series, 1)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_tim
+ /// Number of time steps.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Quadratic errors between predictions and mean prediction.
+ /// shape: (subsets, samples, series, time)
template <class XD2>
inline xt::xtensor<double, 4> calc_quad_prd(
const XD2& q_prd,
@@ -247,41 +247,41 @@ namespace evalhyd
return quad_prd;
}
- // Compute the Pearson correlation coefficient.
- //
- // \param q_obs
- // Streamflow observations.
- // shape: (series, time)
- // \param q_prd
- // Streamflow predictions.
- // shape: (series, time)
- // \param mean_obs
- // Mean observed streamflow.
- // shape: (subsets, samples, series, 1)
- // \param mean_prd
- // Mean predicted streamflow.
- // shape: (subsets, samples, series, 1)
- // \param quad_obs
- // Quadratic errors between observations and mean observation.
- // shape: (subsets, samples, series, time)
- // \param quad_prd
- // Quadratic errors between predictions and mean prediction.
- // shape: (subsets, samples, series, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Pearson correlation coefficients.
- // shape: (subsets, samples, series)
+ /// Compute the Pearson correlation coefficient.
+ ///
+ /// \param q_obs
+ /// Streamflow observations.
+ /// shape: (series, time)
+ /// \param q_prd
+ /// Streamflow predictions.
+ /// shape: (series, time)
+ /// \param mean_obs
+ /// Mean observed streamflow.
+ /// shape: (subsets, samples, series, 1)
+ /// \param mean_prd
+ /// Mean predicted streamflow.
+ /// shape: (subsets, samples, series, 1)
+ /// \param quad_obs
+ /// Quadratic errors between observations and mean observation.
+ /// shape: (subsets, samples, series, time)
+ /// \param quad_prd
+ /// Quadratic errors between predictions and mean prediction.
+ /// shape: (subsets, samples, series, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Pearson correlation coefficients.
+ /// shape: (subsets, samples, series)
template <class XD2>
inline xt::xtensor<double, 3> calc_r_pearson(
const XD2& q_obs,
@@ -333,35 +333,35 @@ namespace evalhyd
return r_pearson;
}
- // Compute alpha.
- //
- // \param q_obs
- // Streamflow observations.
- // shape: (series, time)
- // \param q_prd
- // Streamflow predictions.
- // shape: (series, time)
- // \param mean_obs
- // Mean observed streamflow.
- // shape: (subsets, samples, series, 1)
- // \param mean_prd
- // Mean predicted streamflow.
- // shape: (subsets, samples, series, 1)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Alphas, ratios of standard deviations.
- // shape: (subsets, samples, series)
+ /// Compute alpha.
+ ///
+ /// \param q_obs
+ /// Streamflow observations.
+ /// shape: (series, time)
+ /// \param q_prd
+ /// Streamflow predictions.
+ /// shape: (series, time)
+ /// \param mean_obs
+ /// Mean observed streamflow.
+ /// shape: (subsets, samples, series, 1)
+ /// \param mean_prd
+ /// Mean predicted streamflow.
+ /// shape: (subsets, samples, series, 1)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Alphas, ratios of standard deviations.
+ /// shape: (subsets, samples, series)
template <class XD2>
inline xt::xtensor<double, 3> calc_alpha(
const XD2& q_obs,
@@ -400,29 +400,29 @@ namespace evalhyd
return alpha;
}
- // Compute the bias.
- //
- // \param q_obs
- // Streamflow observations.
- // shape: (series, time)
- // \param q_prd
- // Streamflow predictions.
- // shape: (series, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Biases.
- // shape: (subsets, samples, series)
+ /// Compute the bias.
+ ///
+ /// \param q_obs
+ /// Streamflow observations.
+ /// shape: (series, time)
+ /// \param q_prd
+ /// Streamflow predictions.
+ /// shape: (series, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Biases.
+ /// shape: (subsets, samples, series)
template <class XD2>
inline xt::xtensor<double, 3> calc_bias(
const XD2& q_obs,
diff --git a/include/evalhyd/detail/determinist/metrics.hpp b/include/evalhyd/detail/determinist/metrics.hpp
index 5a2d502b255eb4c708344663c6b318ae5c5c83c7..8ee318f0cfadff8f4c4933c79c85f1fbf3c5a6d1 100644
--- a/include/evalhyd/detail/determinist/metrics.hpp
+++ b/include/evalhyd/detail/determinist/metrics.hpp
@@ -16,26 +16,26 @@ namespace evalhyd
{
namespace metrics
{
- // Compute the root-mean-square error (RMSE).
- //
- // \param quad_err
- // Quadratic errors between observations and predictions.
- // shape: (series, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Root-mean-square errors.
- // shape: (series, subsets, samples)
+ /// Compute the root-mean-square error (RMSE).
+ ///
+ /// \param quad_err
+ /// Quadratic errors between observations and predictions.
+ /// shape: (series, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Root-mean-square errors.
+ /// shape: (series, subsets, samples)
inline xt::xtensor<double, 3> calc_RMSE(
const xt::xtensor<double, 2>& quad_err,
const xt::xtensor<bool, 3>& t_msk,
@@ -66,29 +66,29 @@ namespace evalhyd
return RMSE;
}
- // Compute the Nash-Sutcliffe Efficiency (NSE).
- //
- // \param quad_err
- // Quadratic errors between observations and predictions.
- // shape: (series, time)
- // \param quad_obs
- // Quadratic errors between observations and mean observation.
- // shape: (subsets, samples, series, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (subsets, series, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Nash-Sutcliffe efficiencies.
- // shape: (series, subsets, samples)
+ /// Compute the Nash-Sutcliffe Efficiency (NSE).
+ ///
+ /// \param quad_err
+ /// Quadratic errors between observations and predictions.
+ /// shape: (series, time)
+ /// \param quad_obs
+ /// Quadratic errors between observations and mean observation.
+ /// shape: (subsets, samples, series, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (subsets, series, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Nash-Sutcliffe efficiencies.
+ /// shape: (series, subsets, samples)
inline xt::xtensor<double, 3> calc_NSE(
const xt::xtensor<double, 2>& quad_err,
const xt::xtensor<double, 4>& quad_obs,
@@ -127,26 +127,26 @@ namespace evalhyd
return NSE;
}
- // Compute the Kling-Gupta Efficiency (KGE).
- //
- // \param r_pearson
- // Pearson correlation coefficients.
- // shape: (subsets, samples, series)
- // \param alpha
- // Alphas, ratios of standard deviations.
- // shape: (subsets, samples, series)
- // \param bias
- // Biases.
- // shape: (subsets, samples, series)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Kling-Gupta efficiencies.
- // shape: (series, subsets, samples)
+ /// Compute the Kling-Gupta Efficiency (KGE).
+ ///
+ /// \param r_pearson
+ /// Pearson correlation coefficients.
+ /// shape: (subsets, samples, series)
+ /// \param alpha
+ /// Alphas, ratios of standard deviations.
+ /// shape: (subsets, samples, series)
+ /// \param bias
+ /// Biases.
+ /// shape: (subsets, samples, series)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Kling-Gupta efficiencies.
+ /// shape: (series, subsets, samples)
inline xt::xtensor<double, 3> calc_KGE(
const xt::xtensor<double, 3>& r_pearson,
const xt::xtensor<double, 3>& alpha,
@@ -175,32 +175,32 @@ namespace evalhyd
return KGE;
}
- // Compute the modified Kling-Gupta Efficiency (KGEPRIME).
- //
- // \param mean_obs
- // Mean observed streamflow.
- // shape: (subsets, samples, series, 1)
- // \param mean_prd
- // Mean predicted streamflow.
- // shape: (subsets, samples, series, 1)
- // \param r_pearson
- // Pearson correlation coefficients.
- // shape: (subsets, samples, series)
- // \param alpha
- // Alphas, ratios of standard deviations.
- // shape: (subsets, samples, series)
- // \param bias
- // Biases.
- // shape: (subsets, samples, series)
- // \param n_srs
- // Number of prediction series.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Modified Kling-Gupta efficiencies.
- // shape: (series, subsets, samples)
+ /// Compute the modified Kling-Gupta Efficiency (KGEPRIME).
+ ///
+ /// \param mean_obs
+ /// Mean observed streamflow.
+ /// shape: (subsets, samples, series, 1)
+ /// \param mean_prd
+ /// Mean predicted streamflow.
+ /// shape: (subsets, samples, series, 1)
+ /// \param r_pearson
+ /// Pearson correlation coefficients.
+ /// shape: (subsets, samples, series)
+ /// \param alpha
+ /// Alphas, ratios of standard deviations.
+ /// shape: (subsets, samples, series)
+ /// \param bias
+ /// Biases.
+ /// shape: (subsets, samples, series)
+ /// \param n_srs
+ /// Number of prediction series.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Modified Kling-Gupta efficiencies.
+ /// shape: (series, subsets, samples)
inline xt::xtensor<double, 3> calc_KGEPRIME(
const xt::xtensor<double, 4>& mean_obs,
const xt::xtensor<double, 4>& mean_prd,
diff --git a/include/evalhyd/detail/probabilist/brier.hpp b/include/evalhyd/detail/probabilist/brier.hpp
index 1c6824311004e4281f0a914fa4995bb4fd4eca1e..945fe7532ae7d25c8e864d7372f64a79a2881cf4 100644
--- a/include/evalhyd/detail/probabilist/brier.hpp
+++ b/include/evalhyd/detail/probabilist/brier.hpp
@@ -23,17 +23,17 @@ namespace evalhyd
{
namespace elements
{
- // Determine observed realisation of threshold(s) exceedance.
- //
- // \param q_obs
- // Streamflow observations.
- // shape: (sites, time)
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \return
- // Event observed outcome.
- // shape: (sites, thresholds, time)
+ /// Determine observed realisation of threshold(s) exceedance.
+ ///
+ /// \param q_obs
+ /// Streamflow observations.
+ /// shape: (sites, time)
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \return
+ /// Event observed outcome.
+ /// shape: (sites, thresholds, time)
template<class XD2>
inline xt::xtensor<double, 3> calc_o_k(
const XD2& q_obs,
@@ -56,30 +56,30 @@ namespace evalhyd
}
- // Determine mean observed realisation of threshold(s) exceedance.
- //
- // \param o_k
- // Event observed outcome.
- // shape: (sites, thresholds, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Mean event observed outcome.
- // shape: (sites, lead times, subsets, samples, thresholds)
+ /// Determine mean observed realisation of threshold(s) exceedance.
+ ///
+ /// \param o_k
+ /// Event observed outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Mean event observed outcome.
+ /// shape: (sites, lead times, subsets, samples, thresholds)
inline xt::xtensor<double, 5> calc_bar_o(
const xt::xtensor<double, 3>& o_k,
const xt::xtensor<bool, 4>& t_msk,
@@ -122,17 +122,17 @@ namespace evalhyd
return bar_o;
}
- // Determine number of forecast members exceeding threshold(s)
- //
- // \param q_prd
- // Streamflow predictions.
- // shape: (sites, lead times, members, time)
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \return
- // Number of forecast members exceeding threshold(s).
- // shape: (sites, lead times, thresholds, time)
+ /// Determine number of forecast members exceeding threshold(s)
+ ///
+ /// \param q_prd
+ /// Streamflow predictions.
+ /// shape: (sites, lead times, members, time)
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \return
+ /// Number of forecast members exceeding threshold(s).
+ /// shape: (sites, lead times, thresholds, time)
template<class XD4, class XD2>
inline xt::xtensor<double, 4> calc_sum_f_k(
const XD4& q_prd,
@@ -164,16 +164,16 @@ namespace evalhyd
}
}
- // Determine forecast probability of threshold(s) exceedance to occur.
- //
- // \param sum_f_k
- // Number of forecast members exceeding threshold(s).
- // shape: (sites, lead times, thresholds, time)
- // \param n_mbr
- // Number of ensemble members.
- // \return
- // Event probability forecast.
- // shape: (sites, lead times, thresholds, time)
+ /// Determine forecast probability of threshold(s) exceedance to occur.
+ ///
+ /// \param sum_f_k
+ /// Number of forecast members exceeding threshold(s).
+ /// shape: (sites, lead times, thresholds, time)
+ /// \param n_mbr
+ /// Number of ensemble members.
+ /// \return
+ /// Event probability forecast.
+ /// shape: (sites, lead times, thresholds, time)
inline xt::xtensor<double, 4> calc_y_k(
const xt::xtensor<double, 4>& sum_f_k,
std::size_t n_mbr
@@ -188,17 +188,17 @@ namespace evalhyd
namespace intermediate
{
- // Compute the Brier score for each time step.
- //
- // \param o_k
- // Observed event outcome.
- // shape: (sites, thresholds, time)
- // \param y_k
- // Event probability forecast.
- // shape: (sites, lead times, thresholds, time)
- // \return
- // Brier score for each threshold for each time step.
- // shape: (sites, lead times, thresholds, time)
+ /// Compute the Brier score for each time step.
+ ///
+ /// \param o_k
+ /// Observed event outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param y_k
+ /// Event probability forecast.
+ /// shape: (sites, lead times, thresholds, time)
+ /// \return
+ /// Brier score for each threshold for each time step.
+ /// shape: (sites, lead times, thresholds, time)
inline xt::xtensor<double, 4> calc_bs(
const xt::xtensor<double, 3>& o_k,
const xt::xtensor<double, 4>& y_k
@@ -216,33 +216,33 @@ namespace evalhyd
namespace metrics
{
- // Compute the Brier score (BS).
- //
- // \param bs
- // Brier score for each threshold for each time step.
- // shape: (sites, lead times, thresholds, time)
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Brier score for each subset and for each threshold.
- // shape: (sites, lead times, subsets, samples, thresholds)
+ /// Compute the Brier score (BS).
+ ///
+ /// \param bs
+ /// Brier score for each threshold for each time step.
+ /// shape: (sites, lead times, thresholds, time)
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Brier score for each subset and for each threshold.
+ /// shape: (sites, lead times, subsets, samples, thresholds)
template <class XD2>
inline xt::xtensor<double, 5> calc_BS(
const xt::xtensor<double, 4>& bs,
@@ -298,45 +298,45 @@ namespace evalhyd
return BS;
}
- // Compute the calibration-refinement decomposition of the Brier score
- // into reliability, resolution, and uncertainty.
- //
- // BS = reliability - resolution + uncertainty
- //
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \param o_k
- // Observed event outcome.
- // shape: (sites, thresholds, time)
- // \param y_k
- // Event probability forecast.
- // shape: (sites, lead times, thresholds, time)
- // \param bar_o
- // Mean event observed outcome.
- // shape: (sites, lead times, subsets, samples, thresholds)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_mbr
- // Number of ensemble members.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Brier score components (reliability, resolution, uncertainty)
- // for each subset and for each threshold.
- // shape: (sites, lead times, subsets, samples, thresholds, components)
+ /// Compute the calibration-refinement decomposition of the Brier score
+ /// into reliability, resolution, and uncertainty.
+ ///
+ /// BS = reliability - resolution + uncertainty
+ ///
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \param o_k
+ /// Observed event outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param y_k
+ /// Event probability forecast.
+ /// shape: (sites, lead times, thresholds, time)
+ /// \param bar_o
+ /// Mean event observed outcome.
+ /// shape: (sites, lead times, subsets, samples, thresholds)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_mbr
+ /// Number of ensemble members.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Brier score components (reliability, resolution, uncertainty)
+ /// for each subset and for each threshold.
+ /// shape: (sites, lead times, subsets, samples, thresholds, components)
template <class XD2>
inline xt::xtensor<double, 6> calc_BS_CRD(
const XD2& q_thr,
@@ -486,40 +486,40 @@ namespace evalhyd
return BS_CRD;
}
- // Compute the likelihood-base rate decomposition of the Brier score
- // into type 2 bias, discrimination, and sharpness (a.k.a. refinement).
- //
- // BS = type 2 bias - discrimination + sharpness
- //
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \param o_k
- // Observed event outcome.
- // shape: (sites, thresholds, time)
- // \param y_k
- // Event probability forecast.
- // shape: (sites, lead times, thresholds, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Brier score components (type 2 bias, discrimination, sharpness)
- // for each subset and for each threshold.
- // shape: (sites, lead times, subsets, samples, thresholds, components)
+ /// Compute the likelihood-base rate decomposition of the Brier score
+ /// into type 2 bias, discrimination, and sharpness (a.k.a. refinement).
+ ///
+ /// BS = type 2 bias - discrimination + sharpness
+ ///
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \param o_k
+ /// Observed event outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param y_k
+ /// Event probability forecast.
+ /// shape: (sites, lead times, thresholds, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Brier score components (type 2 bias, discrimination, sharpness)
+ /// for each subset and for each threshold.
+ /// shape: (sites, lead times, subsets, samples, thresholds, components)
template <class XD2>
inline xt::xtensor<double, 6> calc_BS_LBD(
const XD2& q_thr,
@@ -679,39 +679,39 @@ namespace evalhyd
return BS_LBD;
}
- // Compute the Brier skill score (BSS).
- //
- // \param bs
- // Brier score for each threshold for each time step.
- // shape: (sites, lead times, thresholds, time)
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \param o_k
- // Observed event outcome.
- // shape: (sites, thresholds, time)
- // \param bar_o
- // Mean event observed outcome.
- // shape: (sites, lead times, subsets, samples, thresholds)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Brier skill score for each subset and for each threshold.
- // shape: (sites, lead times, subsets, samples, thresholds)
+ /// Compute the Brier skill score (BSS).
+ ///
+ /// \param bs
+ /// Brier score for each threshold for each time step.
+ /// shape: (sites, lead times, thresholds, time)
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \param o_k
+ /// Observed event outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param bar_o
+ /// Mean event observed outcome.
+ /// shape: (sites, lead times, subsets, samples, thresholds)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Brier skill score for each subset and for each threshold.
+ /// shape: (sites, lead times, subsets, samples, thresholds)
template <class XD2>
inline xt::xtensor<double, 5> calc_BSS(
const xt::xtensor<double, 4>& bs,
diff --git a/include/evalhyd/detail/probabilist/contingency.hpp b/include/evalhyd/detail/probabilist/contingency.hpp
index 6d07a059a4335474c6faaa9734f267b83d1df88c..dbae492e084e5008a4c714742338c9a5fa9ca84a 100644
--- a/include/evalhyd/detail/probabilist/contingency.hpp
+++ b/include/evalhyd/detail/probabilist/contingency.hpp
@@ -35,16 +35,16 @@ namespace evalhyd
// +-----+-----+
//
- // Determine alerts based on forecast.
- //
- // \param sum_f_k
- // Number of forecast members exceeding threshold(s).
- // shape: (sites, lead times, thresholds, time)
- // \param n_mbr
- // Number of ensemble members.
- // \return
- // Alerts based on forecast.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Determine alerts based on forecast.
+ ///
+ /// \param sum_f_k
+ /// Number of forecast members exceeding threshold(s).
+ /// shape: (sites, lead times, thresholds, time)
+ /// \param n_mbr
+ /// Number of ensemble members.
+ /// \return
+ /// Alerts based on forecast.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_a_k(
const xt::xtensor<double, 3>& sum_f_k,
std::size_t n_mbr
@@ -61,17 +61,17 @@ namespace evalhyd
xt::all(), xt::newaxis(), xt::newaxis());
}
- // Determine hits ('a' in contingency table).
- //
- // \param o_k
- // Observed event outcome.
- // shape: (sites, thresholds, time)
- // \param a_k
- // Alerts based on forecast.
- // shape: (sites, lead times, levels, thresholds, time)
- // \return
- // Hits.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Determine hits ('a' in contingency table).
+ ///
+ /// \param o_k
+ /// Observed event outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param a_k
+ /// Alerts based on forecast.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \return
+ /// Hits.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_ct_a(
const xt::xtensor<double, 3>& o_k,
const xt::xtensor<double, 5>& a_k
@@ -83,17 +83,17 @@ namespace evalhyd
&& xt::equal(a_k, 1.);
}
- // Determine false alarms ('b' in contingency table).
- //
- // \param o_k
- // Observed event outcome.
- // shape: (sites, thresholds, time)
- // \param a_k
- // Alerts based on forecast.
- // shape: (sites, lead times, levels, thresholds, time)
- // \return
- // False alarms.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Determine false alarms ('b' in contingency table).
+ ///
+ /// \param o_k
+ /// Observed event outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param a_k
+ /// Alerts based on forecast.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \return
+ /// False alarms.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_ct_b(
const xt::xtensor<double, 3>& o_k,
const xt::xtensor<double, 5>& a_k
@@ -105,17 +105,17 @@ namespace evalhyd
&& xt::equal(a_k, 1.);
}
- // Determine misses ('c' in contingency table).
- //
- // \param o_k
- // Observed event outcome.
- // shape: (sites, thresholds, time)
- // \param a_k
- // Alerts based on forecast.
- // shape: (sites, lead times, levels, thresholds, time)
- // \return
- // Misses.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Determine misses ('c' in contingency table).
+ ///
+ /// \param o_k
+ /// Observed event outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param a_k
+ /// Alerts based on forecast.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \return
+ /// Misses.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_ct_c(
const xt::xtensor<double, 3>& o_k,
const xt::xtensor<double, 5>& a_k
@@ -127,17 +127,17 @@ namespace evalhyd
&& xt::equal(a_k, 0.);
}
- // Determine correct rejections ('d' in contingency table).
- //
- // \param o_k
- // Observed event outcome.
- // shape: (sites, thresholds, time)
- // \param a_k
- // Alerts based on forecast.
- // shape: (sites, lead times, levels, thresholds, time)
- // \return
- // Correct rejections.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Determine correct rejections ('d' in contingency table).
+ ///
+ /// \param o_k
+ /// Observed event outcome.
+ /// shape: (sites, thresholds, time)
+ /// \param a_k
+ /// Alerts based on forecast.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \return
+ /// Correct rejections.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_ct_d(
const xt::xtensor<double, 3>& o_k,
const xt::xtensor<double, 5>& a_k
@@ -152,17 +152,17 @@ namespace evalhyd
namespace intermediate
{
- // Compute the probability of detection for each time step.
- //
- // \param ct_a
- // Hits.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param ct_c
- // Misses.
- // shape: (sites, lead times, levels, thresholds, time)
- // \return
- // Probability of detection for each time step.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Compute the probability of detection for each time step.
+ ///
+ /// \param ct_a
+ /// Hits.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param ct_c
+ /// Misses.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \return
+ /// Probability of detection for each time step.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_pod(
const xt::xtensor<double, 5>& ct_a,
const xt::xtensor<double, 5>& ct_c
@@ -171,17 +171,17 @@ namespace evalhyd
return ct_a / (ct_a + ct_c);
}
- // Compute the probability of false detection for each time step.
- //
- // \param ct_b
- // False alarms.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param ct_d
- // Correct rejections.
- // shape: (sites, lead times, levels, thresholds, time)
- // \return
- // Probability of false detection for each time step.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Compute the probability of false detection for each time step.
+ ///
+ /// \param ct_b
+ /// False alarms.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param ct_d
+ /// Correct rejections.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \return
+ /// Probability of false detection for each time step.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_pofd(
const xt::xtensor<double, 5>& ct_b,
const xt::xtensor<double, 5>& ct_d
@@ -190,17 +190,17 @@ namespace evalhyd
return ct_b / (ct_b + ct_d);
}
- // Compute the false alarm ratio for each time step.
- //
- // \param ct_a
- // Hits.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param ct_b
- // False alarms.
- // shape: (sites, lead times, levels, thresholds, time)
- // \return
- // False alarm ratio for each time step.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Compute the false alarm ratio for each time step.
+ ///
+ /// \param ct_a
+ /// Hits.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param ct_b
+ /// False alarms.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \return
+ /// False alarm ratio for each time step.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_far(
const xt::xtensor<double, 5>& ct_a,
const xt::xtensor<double, 5>& ct_b
@@ -209,20 +209,20 @@ namespace evalhyd
return ct_b / (ct_a + ct_b);
}
- // Compute the critical success index for each time step.
- //
- // \param ct_a
- // Hits.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param ct_b
- // False alarms.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param ct_c
- // Misses.
- // shape: (sites, lead times, levels, thresholds, time)
- // \return
- // Critical success index for each time step.
- // shape: (sites, lead times, levels, thresholds, time)
+ /// Compute the critical success index for each time step.
+ ///
+ /// \param ct_a
+ /// Hits.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param ct_b
+ /// False alarms.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param ct_c
+ /// Misses.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \return
+ /// Critical success index for each time step.
+ /// shape: (sites, lead times, levels, thresholds, time)
inline xt::xtensor<double, 5> calc_csi(
const xt::xtensor<double, 5>& ct_a,
const xt::xtensor<double, 5>& ct_b,
@@ -300,36 +300,36 @@ namespace evalhyd
}
}
- // Compute the probability of detection (POD),
- // also known as 'hit rate'.
- //
- // \param pod
- // Probability of detection for each time step.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_mbr
- // Number of ensemble members.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Probabilities of detection.
- // shape: (sites, lead times, subsets, samples, levels, thresholds)
+ /// Compute the probability of detection (POD),
+ /// also known as 'hit rate'.
+ ///
+ /// \param pod
+ /// Probability of detection for each time step.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_mbr
+ /// Number of ensemble members.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Probabilities of detection.
+ /// shape: (sites, lead times, subsets, samples, levels, thresholds)
template <class XD2>
inline xt::xtensor<double, 6> calc_POD(
const xt::xtensor<double, 5>& pod,
@@ -350,36 +350,36 @@ namespace evalhyd
);
}
- // Compute the probability of detection (POFD),
- // also known as 'false alarm rate'.
- //
- // \param pofd
- // Probability of false detection for each time step.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_mbr
- // Number of ensemble members.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Probabilities of false detection.
- // shape: (sites, lead times, subsets, samples, levels, thresholds)
+ /// Compute the probability of detection (POFD),
+ /// also known as 'false alarm rate'.
+ ///
+ /// \param pofd
+ /// Probability of false detection for each time step.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_mbr
+ /// Number of ensemble members.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Probabilities of false detection.
+ /// shape: (sites, lead times, subsets, samples, levels, thresholds)
template <class XD2>
inline xt::xtensor<double, 6> calc_POFD(
const xt::xtensor<double, 5>& pofd,
@@ -400,35 +400,35 @@ namespace evalhyd
);
}
- // Compute the false alarm ratio (FAR).
- //
- // \param far
- // False alarm ratio for each time step.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_mbr
- // Number of ensemble members.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // False alarm ratios.
- // shape: (sites, lead times, subsets, samples, levels, thresholds)
+ /// Compute the false alarm ratio (FAR).
+ ///
+ /// \param far
+ /// False alarm ratio for each time step.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_mbr
+ /// Number of ensemble members.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// False alarm ratios.
+ /// shape: (sites, lead times, subsets, samples, levels, thresholds)
template <class XD2>
inline xt::xtensor<double, 6> calc_FAR(
const xt::xtensor<double, 5>& far,
@@ -449,35 +449,35 @@ namespace evalhyd
);
}
- // Compute the critical success index (CSI).
- //
- // \param csi
- // Critical success index for each time step.
- // shape: (sites, lead times, levels, thresholds, time)
- // \param q_thr
- // Streamflow exceedance threshold(s).
- // shape: (sites, thresholds)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_thr
- // Number of thresholds.
- // \param n_mbr
- // Number of ensemble members.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Critical success indices.
- // shape: (sites, lead times, subsets, samples, levels, thresholds)
+ /// Compute the critical success index (CSI).
+ ///
+ /// \param csi
+ /// Critical success index for each time step.
+ /// shape: (sites, lead times, levels, thresholds, time)
+ /// \param q_thr
+ /// Streamflow exceedance threshold(s).
+ /// shape: (sites, thresholds)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_thr
+ /// Number of thresholds.
+ /// \param n_mbr
+ /// Number of ensemble members.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Critical success indices.
+ /// shape: (sites, lead times, subsets, samples, levels, thresholds)
template <class XD2>
inline xt::xtensor<double, 6> calc_CSI(
const xt::xtensor<double, 5>& csi,
@@ -498,17 +498,17 @@ namespace evalhyd
);
}
- // Compute the relative operating characteristic skill score (ROCSS).
- //
- // \param POD
- // Probabilities of detection.
- // shape: (sites, lead times, subsets, samples, levels, thresholds)
- // \param POFD
- // Probabilities of false detection.
- // shape: (sites, lead times, subsets, samples, levels, thresholds)
- // \return
- // ROC skill scores.
- // shape: (sites, lead times, subsets, samples, thresholds)
+ /// Compute the relative operating characteristic skill score (ROCSS).
+ ///
+ /// \param POD
+ /// Probabilities of detection.
+ /// shape: (sites, lead times, subsets, samples, levels, thresholds)
+ /// \param POFD
+ /// Probabilities of false detection.
+ /// shape: (sites, lead times, subsets, samples, levels, thresholds)
+ /// \return
+ /// ROC skill scores.
+ /// shape: (sites, lead times, subsets, samples, thresholds)
template <class XD2>
inline xt::xtensor<double, 5> calc_ROCSS(
const xt::xtensor<double, 6>& POD,
diff --git a/include/evalhyd/detail/probabilist/quantiles.hpp b/include/evalhyd/detail/probabilist/quantiles.hpp
index ca3d668d941c4cb274c3d171c04284e971438f00..471f8b3af6c68bdc0ca051e0c76e53675649bffa 100644
--- a/include/evalhyd/detail/probabilist/quantiles.hpp
+++ b/include/evalhyd/detail/probabilist/quantiles.hpp
@@ -23,14 +23,14 @@ namespace evalhyd
{
namespace elements
{
- // Compute the forecast quantiles from the ensemble members.
- //
- // \param q_prd
- // Streamflow predictions.
- // shape: (sites, lead times, members, time)
- // \return
- // Streamflow forecast quantiles.
- // shape: (sites, lead times, quantiles, time)
+ /// Compute the forecast quantiles from the ensemble members.
+ ///
+ /// \param q_prd
+ /// Streamflow predictions.
+ /// shape: (sites, lead times, members, time)
+ /// \return
+ /// Streamflow forecast quantiles.
+ /// shape: (sites, lead times, quantiles, time)
template <class XD4>
inline xt::xtensor<double, 4> calc_q_qnt(
const XD4& q_prd
@@ -42,17 +42,17 @@ namespace evalhyd
namespace intermediate
{
- // Compute the quantile scores for each time step.
- //
- // \param q_obs
- // Streamflow observations.
- // shape: (sites, time)
- // \param q_qnt
- // Streamflow quantiles.
- // shape: (sites, lead times, quantiles, time)
- // \return
- // Quantile scores for each time step.
- // shape: (sites, lead times, quantiles, time)
+ /// Compute the quantile scores for each time step.
+ ///
+ /// \param q_obs
+ /// Streamflow observations.
+ /// shape: (sites, time)
+ /// \param q_qnt
+ /// Streamflow quantiles.
+ /// shape: (sites, lead times, quantiles, time)
+ /// \return
+ /// Quantile scores for each time step.
+ /// shape: (sites, lead times, quantiles, time)
template <class XD2>
inline xt::xtensor<double, 4> calc_qs(
const XD2 &q_obs,
@@ -82,20 +82,20 @@ namespace evalhyd
return qs;
}
- // Compute the continuous rank probability score(s) based
- // on quantile scores for each time step, and integrating using the
- // trapezoidal rule.
- //
- // /!\ The number of quantiles must be sufficiently large so that the
- // cumulative distribution is smooth enough for the numerical
- // integration to be accurate.
- //
- // \param qs
- // Quantile scores for each time step.
- // shape: (sites, lead times, quantiles, time)
- // \return
- // CRPS for each time step.
- // shape: (sites, lead times, time)
+ /// Compute the continuous rank probability score(s) based
+ /// on quantile scores for each time step, and integrating using the
+ /// trapezoidal rule.
+ ///
+ /// /!\ The number of quantiles must be sufficiently large so that the
+ /// cumulative distribution is smooth enough for the numerical
+ /// integration to be accurate.
+ ///
+ /// \param qs
+ /// Quantile scores for each time step.
+ /// shape: (sites, lead times, quantiles, time)
+ /// \return
+ /// CRPS for each time step.
+ /// shape: (sites, lead times, time)
inline xt::xtensor<double, 3> calc_crps(
const xt::xtensor<double, 4>& qs,
std::size_t n_mbr
@@ -109,30 +109,30 @@ namespace evalhyd
namespace metrics
{
- // Compute the quantile score (QS).
- //
- // \param qs
- // Quantile scores for each time step.
- // shape: (sites, lead times, quantiles, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_mbr
- // Number of ensemble members.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // Quantile scores.
- // shape: (sites, lead times, subsets, samples, quantiles)
+ /// Compute the quantile score (QS).
+ ///
+ /// \param qs
+ /// Quantile scores for each time step.
+ /// shape: (sites, lead times, quantiles, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_mbr
+ /// Number of ensemble members.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// Quantile scores.
+ /// shape: (sites, lead times, subsets, samples, quantiles)
inline xt::xtensor<double, 5> calc_QS(
const xt::xtensor<double, 4>& qs,
const xt::xtensor<bool, 4>& t_msk,
@@ -178,29 +178,29 @@ namespace evalhyd
return QS;
}
- // Compute the continuous rank probability score (CRPS) based
- // on quantile scores.
- //
- // \param crps
- // CRPS for each time step.
- // shape: (sites, lead times, time)
- // \param t_msk
- // Temporal subsets of the whole record.
- // shape: (sites, lead times, subsets, time)
- // \param b_exp
- // Boostrap samples.
- // shape: (samples, time slice)
- // \param n_sit
- // Number of sites.
- // \param n_ldt
- // Number of lead times.
- // \param n_msk
- // Number of temporal subsets.
- // \param n_exp
- // Number of bootstrap samples.
- // \return
- // CRPS.
- // shape: (sites, lead times, subsets, samples)
+ /// Compute the continuous rank probability score (CRPS) based
+ /// on quantile scores.
+ ///
+ /// \param crps
+ /// CRPS for each time step.
+ /// shape: (sites, lead times, time)
+ /// \param t_msk
+ /// Temporal subsets of the whole record.
+ /// shape: (sites, lead times, subsets, time)
+ /// \param b_exp
+ /// Boostrap samples.
+ /// shape: (samples, time slice)
+ /// \param n_sit
+ /// Number of sites.
+ /// \param n_ldt
+ /// Number of lead times.
+ /// \param n_msk
+ /// Number of temporal subsets.
+ /// \param n_exp
+ /// Number of bootstrap samples.
+ /// \return
+ /// CRPS.
+ /// shape: (sites, lead times, subsets, samples)
inline xt::xtensor<double, 4> calc_CRPS(
const xt::xtensor<double, 3>& crps,
const xt::xtensor<bool, 4>& t_msk,