From df97a0599cead5b87a94fa6f88ce6158807d1086 Mon Sep 17 00:00:00 2001
From: Thibault Hallouin <thibault.hallouin@inrae.fr>
Date: Tue, 3 Jan 2023 16:50:27 +0100
Subject: [PATCH] document template parameters
---
.../evalhyd/detail/determinist/elements.hpp | 40 ++++++-------
.../evalhyd/detail/determinist/evaluator.hpp | 28 +++++-----
include/evalhyd/detail/probabilist/brier.hpp | 28 +++++-----
.../evalhyd/detail/probabilist/evaluator.hpp | 8 +--
.../evalhyd/detail/probabilist/quantiles.hpp | 8 +--
include/evalhyd/evald.hpp | 56 +++++++++++--------
include/evalhyd/evalp.hpp | 52 ++++++++++-------
7 files changed, 122 insertions(+), 98 deletions(-)
diff --git a/include/evalhyd/detail/determinist/elements.hpp b/include/evalhyd/detail/determinist/elements.hpp
index 8c8fe1b..6218e6d 100644
--- a/include/evalhyd/detail/determinist/elements.hpp
+++ b/include/evalhyd/detail/determinist/elements.hpp
@@ -33,9 +33,9 @@ namespace evalhyd
// \return
// Mean observed streamflow.
// shape: (subsets, samples, series, 1)
- template <class D2>
+ template <class XD2>
inline xt::xtensor<double, 4> calc_mean_obs(
- const D2& q_obs,
+ const XD2& q_obs,
const xt::xtensor<bool, 3>& t_msk,
const std::vector<xt::xkeep_slice<int>>& b_exp,
std::size_t n_srs,
@@ -85,9 +85,9 @@ namespace evalhyd
// \return
// Mean predicted streamflow.
// shape: (subsets, samples, series, 1)
- template <class D2>
+ template <class XD2>
inline xt::xtensor<double, 4> calc_mean_prd(
- const D2& q_prd,
+ const XD2& q_prd,
const xt::xtensor<bool, 3>& t_msk,
const std::vector<xt::xkeep_slice<int>>& b_exp,
std::size_t n_srs,
@@ -128,10 +128,10 @@ namespace evalhyd
// \return
// Quadratic errors between observations and predictions.
// shape: (series, time)
- template <class D2>
+ template <class XD2>
inline xt::xtensor<double, 2> calc_quad_err(
- const D2& q_obs,
- const D2& q_prd
+ const XD2& q_obs,
+ const XD2& q_prd
)
{
return xt::square(q_obs - q_prd);
@@ -159,9 +159,9 @@ namespace evalhyd
// \return
// Quadratic errors between observations and mean observation.
// shape: (subsets, samples, series, time)
- template <class D2>
+ template <class XD2>
inline xt::xtensor<double, 4> calc_quad_obs(
- const D2& q_obs,
+ const XD2& q_obs,
const xt::xtensor<double, 4>& mean_obs,
const xt::xtensor<bool, 3>& t_msk,
std::size_t n_srs,
@@ -212,9 +212,9 @@ namespace evalhyd
// \return
// Quadratic errors between predictions and mean prediction.
// shape: (subsets, samples, series, time)
- template <class D2>
+ template <class XD2>
inline xt::xtensor<double, 4> calc_quad_prd(
- const D2& q_prd,
+ const XD2& q_prd,
const xt::xtensor<double, 4>& mean_prd,
const xt::xtensor<bool, 3>& t_msk,
std::size_t n_srs,
@@ -278,10 +278,10 @@ namespace evalhyd
// \return
// Pearson correlation coefficients.
// shape: (subsets, samples, series)
- template <class D2>
+ template <class XD2>
inline xt::xtensor<double, 3> calc_r_pearson(
- const D2& q_obs,
- const D2& q_prd,
+ const XD2& q_obs,
+ const XD2& q_prd,
const xt::xtensor<double, 4>& mean_obs,
const xt::xtensor<double, 4>& mean_prd,
const xt::xtensor<double, 4>& quad_obs,
@@ -358,10 +358,10 @@ namespace evalhyd
// \return
// Alphas, ratios of standard deviations.
// shape: (subsets, samples, series)
- template <class D2>
+ template <class XD2>
inline xt::xtensor<double, 3> calc_alpha(
- const D2& q_obs,
- const D2& q_prd,
+ const XD2& q_obs,
+ const XD2& q_prd,
const xt::xtensor<double, 4>& mean_obs,
const xt::xtensor<double, 4>& mean_prd,
const xt::xtensor<bool, 3>& t_msk,
@@ -419,10 +419,10 @@ namespace evalhyd
// \return
// Biases.
// shape: (subsets, samples, series)
- template <class D2>
+ template <class XD2>
inline xt::xtensor<double, 3> calc_bias(
- const D2& q_obs,
- const D2& q_prd,
+ const XD2& q_obs,
+ const XD2& q_prd,
const xt::xtensor<bool, 3>& t_msk,
const std::vector<xt::xkeep_slice<int>>& b_exp,
std::size_t n_srs,
diff --git a/include/evalhyd/detail/determinist/evaluator.hpp b/include/evalhyd/detail/determinist/evaluator.hpp
index 8e494af..03ed47a 100644
--- a/include/evalhyd/detail/determinist/evaluator.hpp
+++ b/include/evalhyd/detail/determinist/evaluator.hpp
@@ -15,13 +15,13 @@ namespace evalhyd
{
namespace determinist
{
- template <class D2, class B2>
+ template <class XD2, class XB2>
class Evaluator
{
private:
// members for input data
- const D2& q_obs;
- const D2& q_prd;
+ const XD2& q_obs;
+ const XD2& q_prd;
xt::xtensor<bool, 3> t_msk;
const std::vector<xt::xkeep_slice<int>>& b_exp;
@@ -52,7 +52,7 @@ namespace evalhyd
{
if (!mean_obs.has_value())
{
- mean_obs = elements::calc_mean_obs<D2>(
+ mean_obs = elements::calc_mean_obs<XD2>(
q_obs, t_msk, b_exp, n_srs, n_msk, n_exp
);
}
@@ -63,7 +63,7 @@ namespace evalhyd
{
if (!mean_prd.has_value())
{
- mean_prd = elements::calc_mean_prd<D2>(
+ mean_prd = elements::calc_mean_prd<XD2>(
q_prd, t_msk, b_exp, n_srs, n_msk, n_exp
);
}
@@ -74,7 +74,7 @@ namespace evalhyd
{
if (!quad_err.has_value())
{
- quad_err = elements::calc_quad_err<D2>(
+ quad_err = elements::calc_quad_err<XD2>(
q_obs, q_prd
);
}
@@ -85,7 +85,7 @@ namespace evalhyd
{
if (!quad_obs.has_value())
{
- quad_obs = elements::calc_quad_obs<D2>(
+ quad_obs = elements::calc_quad_obs<XD2>(
q_obs, get_mean_obs(), t_msk,
n_srs, n_tim, n_msk, n_exp
);
@@ -97,7 +97,7 @@ namespace evalhyd
{
if (!quad_prd.has_value())
{
- quad_prd = elements::calc_quad_prd<D2>(
+ quad_prd = elements::calc_quad_prd<XD2>(
q_prd, get_mean_prd(), t_msk,
n_srs, n_tim, n_msk, n_exp
);
@@ -109,7 +109,7 @@ namespace evalhyd
{
if (!r_pearson.has_value())
{
- r_pearson = elements::calc_r_pearson<D2>(
+ r_pearson = elements::calc_r_pearson<XD2>(
q_obs, q_prd, get_mean_obs(), get_mean_prd(),
get_quad_obs(), get_quad_prd(), t_msk, b_exp,
n_srs, n_msk, n_exp
@@ -122,7 +122,7 @@ namespace evalhyd
{
if (!alpha.has_value())
{
- alpha = elements::calc_alpha<D2>(
+ alpha = elements::calc_alpha<XD2>(
q_obs, q_prd, get_mean_obs(), get_mean_prd(),
t_msk, b_exp, n_srs, n_msk, n_exp
);
@@ -134,7 +134,7 @@ namespace evalhyd
{
if (!bias.has_value())
{
- bias = elements::calc_bias<D2>(
+ bias = elements::calc_bias<XD2>(
q_obs, q_prd, t_msk, b_exp, n_srs, n_msk, n_exp
);
}
@@ -143,9 +143,9 @@ namespace evalhyd
public:
// constructor method
- Evaluator(const D2& obs,
- const D2& prd,
- const B2& msk,
+ Evaluator(const XD2& obs,
+ const XD2& prd,
+ const XB2& msk,
const std::vector<xt::xkeep_slice<int>>& exp) :
q_obs{obs}, q_prd{prd}, b_exp{exp}
{
diff --git a/include/evalhyd/detail/probabilist/brier.hpp b/include/evalhyd/detail/probabilist/brier.hpp
index 70293fc..fec0f09 100644
--- a/include/evalhyd/detail/probabilist/brier.hpp
+++ b/include/evalhyd/detail/probabilist/brier.hpp
@@ -23,10 +23,10 @@ namespace evalhyd
// \return
// Event observed outcome.
// shape: (thresholds, time)
- template<class V1D2>
+ template<class XV1D2>
inline xt::xtensor<double, 2> calc_o_k(
- const V1D2& q_obs,
- const V1D2& q_thr
+ const XV1D2& q_obs,
+ const XV1D2& q_thr
)
{
// determine observed realisation of threshold(s) exceedance
@@ -100,10 +100,10 @@ namespace evalhyd
// \return
// Event probability forecast.
// shape: (thresholds, time)
- template<class V2D4, class V1D2>
+ template<class XV2D4, class XV1D2>
inline xt::xtensor<double, 2> calc_y_k(
- const V2D4& q_prd,
- const V1D2& q_thr,
+ const XV2D4& q_prd,
+ const XV1D2& q_thr,
std::size_t n_mbr
)
{
@@ -171,10 +171,10 @@ namespace evalhyd
// \return
// Brier score for each subset and for each threshold.
// shape: (subsets, samples, thresholds)
- template <class V1D2>
+ template <class XV1D2>
inline xt::xtensor<double, 3> calc_BS(
const xt::xtensor<double, 2>& bs,
- const V1D2& q_thr,
+ const XV1D2& q_thr,
const xt::xtensor<bool, 2>& t_msk,
const std::vector<xt::xkeep_slice<int>>& b_exp,
std::size_t n_thr,
@@ -253,9 +253,9 @@ namespace evalhyd
// Brier score components (reliability, resolution, uncertainty)
// for each subset and for each threshold.
// shape: (subsets, samples, thresholds, components)
- template <class V1D2>
+ template <class XV1D2>
inline xt::xtensor<double, 4> calc_BS_CRD(
- const V1D2& q_thr,
+ const XV1D2& q_thr,
const xt::xtensor<double, 2>& o_k,
const xt::xtensor<double, 2>& y_k,
const xt::xtensor<double, 3>& bar_o,
@@ -402,9 +402,9 @@ namespace evalhyd
// Brier score components (type 2 bias, discrimination, sharpness)
// for each subset and for each threshold.
// shape: (subsets, samples, thresholds, components)
- template <class V1D2>
+ template <class XV1D2>
inline xt::xtensor<double, 4> calc_BS_LBD(
- const V1D2& q_thr,
+ const XV1D2& q_thr,
const xt::xtensor<double, 2>& o_k,
const xt::xtensor<double, 2>& y_k,
const xt::xtensor<bool, 2>& t_msk,
@@ -560,10 +560,10 @@ namespace evalhyd
// \return
// Brier skill score for each subset and for each threshold.
// shape: (subsets, samples, thresholds)
- template <class V1D2>
+ template <class XV1D2>
inline xt::xtensor<double, 3> calc_BSS(
const xt::xtensor<double, 2>& bs,
- const V1D2& q_thr,
+ const XV1D2& q_thr,
const xt::xtensor<double, 2>& o_k,
const xt::xtensor<double, 3>& bar_o,
const xt::xtensor<bool, 2>& t_msk,
diff --git a/include/evalhyd/detail/probabilist/evaluator.hpp b/include/evalhyd/detail/probabilist/evaluator.hpp
index 7f0e2eb..e58fb3e 100644
--- a/include/evalhyd/detail/probabilist/evaluator.hpp
+++ b/include/evalhyd/detail/probabilist/evaluator.hpp
@@ -16,13 +16,13 @@ namespace evalhyd
{
namespace probabilist
{
- template <class D2, class D4, class B4>
+ template <class XD2, class XD4, class XB4>
class Evaluator
{
private:
using view1d_xtensor2d_double_type = decltype(
xt::view(
- std::declval<const D2&>(),
+ std::declval<const XD2&>(),
std::declval<std::size_t>(),
xt::all()
)
@@ -30,7 +30,7 @@ namespace evalhyd
using view2d_xtensor4d_double_type = decltype(
xt::view(
- std::declval<const D4&>(),
+ std::declval<const XD4&>(),
std::declval<std::size_t>(),
std::declval<std::size_t>(),
xt::all(),
@@ -40,7 +40,7 @@ namespace evalhyd
using view2d_xtensor4d_bool_type = decltype(
xt::view(
- std::declval<const B4&>(),
+ std::declval<const XB4&>(),
std::declval<std::size_t>(),
std::declval<std::size_t>(),
xt::all(),
diff --git a/include/evalhyd/detail/probabilist/quantiles.hpp b/include/evalhyd/detail/probabilist/quantiles.hpp
index c05273d..b4963c5 100644
--- a/include/evalhyd/detail/probabilist/quantiles.hpp
+++ b/include/evalhyd/detail/probabilist/quantiles.hpp
@@ -20,9 +20,9 @@ namespace evalhyd
// \return
// Streamflow forecast quantiles.
// shape: (quantiles, time)
- template <class V2D4>
+ template <class XV2D4>
inline xt::xtensor<double, 2> calc_q_qnt(
- const V2D4& q_prd
+ const XV2D4& q_prd
)
{
return xt::sort(q_prd, 0);
@@ -42,9 +42,9 @@ namespace evalhyd
// \return
// Quantile scores for each time step.
// shape: (quantiles, time)
- template <class V1D2>
+ template <class XV1D2>
inline xt::xtensor<double, 2> calc_qs(
- const V1D2 &q_obs,
+ const XV1D2 &q_obs,
const xt::xtensor<double, 2>& q_qnt,
std::size_t n_mbr
)
diff --git a/include/evalhyd/evald.hpp b/include/evalhyd/evald.hpp
index c10ed21..2efb647 100644
--- a/include/evalhyd/evald.hpp
+++ b/include/evalhyd/evald.hpp
@@ -21,16 +21,26 @@ namespace evalhyd
///
/// \rst
///
+ /// :Template Parameters:
+ ///
+ /// XD2: Any 2-dimensional container class storing numeric elements
+ /// (e.g. ``xt::xtensor<double, 2>``, ``xt::pytensor<double, 2>``,
+ /// ``xt::rtensor<double, 2>``, etc.).
+ ///
+ /// XB2: Any 2-dimensional container class storing boolean elements
+ /// (e.g. ``xt::xtensor<bool, 4>``, ``xt::pytensor<bool, 4>``,
+ /// ``xt::rtensor<bool, 4>``, etc.).
+ ///
/// :Parameters:
///
- /// q_obs: ``xt::xtensor<double, 2>``
+ /// q_obs: ``XD2``
/// Streamflow observations. Time steps with missing observations
/// must be assigned `NAN` values. Those time steps will be ignored
/// both in the observations and the predictions before the
/// *metrics* are computed.
/// shape: (1, time)
///
- /// q_prd: ``xt::xtensor<double, 2>``
+ /// q_prd: ``XD2``
/// Streamflow predictions. Time steps with missing predictions
/// must be assigned `NAN` values. Those time steps will be ignored
/// both in the observations and the predictions before the
@@ -62,7 +72,7 @@ namespace evalhyd
/// `Pushpalatha et al. (2012)
/// <https://doi.org/10.1016/j.jhydrol.2011.11.055>`_.
///
- /// t_msk: ``xt::xtensor<bool, 2>``, optional
+ /// t_msk: ``XB2``, optional
/// Mask used to temporally subset of the whole streamflow time series
/// (where True/False is used for the time steps to include/discard in
/// the subset). If provided, masks must feature the same number of
@@ -144,15 +154,15 @@ namespace evalhyd
/// evalhyd::evald(obs, prd, {"NSE"}, "none", 1, -9, msk);
///
/// \endrst
- template <class D2, class B2>
+ template <class XD2, class XB2>
std::vector<xt::xarray<double>> evald(
- const xt::xexpression<D2>& q_obs,
- const xt::xexpression<D2>& q_prd,
+ const xt::xexpression<XD2>& q_obs,
+ const xt::xexpression<XD2>& q_prd,
const std::vector<std::string>& metrics,
const std::string& transform = "none",
double exponent = 1,
double epsilon = -9,
- const xt::xexpression<B2>& t_msk = B2({}),
+ const xt::xexpression<XB2>& t_msk = XB2({}),
const xt::xtensor<std::array<char, 32>, 1>& m_cdt = {},
const std::unordered_map<std::string, int>& bootstrap =
{{"n_samples", -9}, {"len_sample", -9}, {"summary", 0}},
@@ -160,13 +170,13 @@ namespace evalhyd
)
{
// check ranks of tensors
- if (xt::get_rank<D2>::value != 2)
+ if (xt::get_rank<XD2>::value != 2)
{
throw std::runtime_error(
"observations and/or predictions are not two-dimensional"
);
}
- if (xt::get_rank<B2>::value != 2)
+ if (xt::get_rank<XB2>::value != 2)
{
throw std::runtime_error(
"temporal masks are not two-dimensional"
@@ -174,10 +184,10 @@ namespace evalhyd
}
// retrieve real types of the expressions
- const D2& q_obs_ = q_obs.derived_cast();
- const D2& q_prd_ = q_prd.derived_cast();
+ const XD2& q_obs_ = q_obs.derived_cast();
+ const XD2& q_prd_ = q_prd.derived_cast();
- const B2& t_msk_ = t_msk.derived_cast();
+ const XB2& t_msk_ = t_msk.derived_cast();
// check that the metrics to be computed are valid
utils::check_metrics(
@@ -243,7 +253,7 @@ namespace evalhyd
// else if m_cdt provided, use them to generate t_msk
else if (m_cdt.size() > 0)
{
- B2 c_msk = xt::zeros<bool>({n_msk, n_tim});
+ XB2 c_msk = xt::zeros<bool>({n_msk, n_tim});
for (std::size_t m = 0; m < n_msk; m++)
{
@@ -258,14 +268,14 @@ namespace evalhyd
// if neither t_msk nor m_cdt provided, generate dummy mask
else
{
- return B2({xt::ones<bool>({std::size_t{1}, n_tim})});
+ return XB2({xt::ones<bool>({std::size_t{1}, n_tim})});
}
};
auto msk = gen_msk();
// apply streamflow transformation if requested
- auto q_transform = [&](const D2& q)
+ auto q_transform = [&](const XD2& q)
{
if ( transform == "none" || (transform == "pow" && exponent == 1))
{
@@ -273,7 +283,7 @@ namespace evalhyd
}
else if ( transform == "sqrt" )
{
- return D2(xt::sqrt(q));
+ return XD2(xt::sqrt(q));
}
else if ( transform == "inv" )
{
@@ -283,7 +293,7 @@ namespace evalhyd
epsilon = xt::mean(q_obs_)() * 0.01;
}
- return D2(1. / (q + epsilon));
+ return XD2(1. / (q + epsilon));
}
else if ( transform == "log" )
{
@@ -293,7 +303,7 @@ namespace evalhyd
epsilon = xt::mean(q_obs_)() * 0.01;
}
- return D2(xt::log(q + epsilon));
+ return XD2(xt::log(q + epsilon));
}
else if ( transform == "pow" )
{
@@ -305,11 +315,11 @@ namespace evalhyd
epsilon = xt::mean(q_obs_)() * 0.01;
}
- return D2(xt::pow(q + epsilon, exponent));
+ return XD2(xt::pow(q + epsilon, exponent));
}
else
{
- return D2(xt::pow(q, exponent));
+ return XD2(xt::pow(q, exponent));
}
}
else
@@ -320,8 +330,8 @@ namespace evalhyd
}
};
- const D2 obs = q_transform(q_obs_);
- const D2 prd = q_transform(q_prd_);
+ const XD2 obs = q_transform(q_obs_);
+ const XD2 prd = q_transform(q_prd_);
// generate bootstrap experiment if requested
std::vector<xt::xkeep_slice<int>> exp;
@@ -349,7 +359,7 @@ namespace evalhyd
}
// instantiate determinist evaluator
- determinist::Evaluator<D2, B2> evaluator(obs, prd, msk, exp);
+ determinist::Evaluator<XD2, XB2> evaluator(obs, prd, msk, exp);
// retrieve or compute requested metrics
std::vector<xt::xarray<double>> r;
diff --git a/include/evalhyd/evalp.hpp b/include/evalhyd/evalp.hpp
index 0a48ae3..89088ad 100644
--- a/include/evalhyd/evalp.hpp
+++ b/include/evalhyd/evalp.hpp
@@ -21,16 +21,30 @@ namespace evalhyd
///
/// \rst
///
+ /// :Template Parameters:
+ ///
+ /// XD2: Any 2-dimensional container class storing numeric elements
+ /// (e.g. ``xt::xtensor<double, 2>``, ``xt::pytensor<double, 2>``,
+ /// ``xt::rtensor<double, 2>``, etc.).
+ ///
+ /// XD4: Any 4-dimensional container class storing numeric elements
+ /// (e.g. ``xt::xtensor<double, 4>``, ``xt::pytensor<double, 4>``,
+ /// ``xt::rtensor<double, 4>``, etc.).
+ ///
+ /// XB4: Any 4-dimensional container class storing boolean elements
+ /// (e.g. ``xt::xtensor<bool, 4>``, ``xt::pytensor<bool, 4>``,
+ /// ``xt::rtensor<bool, 4>``, etc.).
+ ///
/// :Parameters:
///
- /// q_obs: ``xt::xtensor<double, 2>``
+ /// q_obs: ``XD2``
/// Streamflow observations. Time steps with missing observations
/// must be assigned `NAN` values. Those time steps will be ignored
/// both in the observations and the predictions before the
/// *metrics* are computed.
/// shape: (sites, time)
///
- /// q_prd: ``xt::xtensor<double, 4>``
+ /// q_prd: ``XD4``
/// Streamflow predictions. Time steps with missing predictions
/// must be assigned `NAN` values. Those time steps will be ignored
/// both in the observations and the predictions before the
@@ -40,11 +54,11 @@ namespace evalhyd
/// metrics: ``std::vector<std::string>``
/// The sequence of evaluation metrics to be computed.
///
- /// q_thr: ``xt::xtensor<double, 2>``, optional
+ /// q_thr: ``XD2``, optional
/// Streamflow exceedance threshold(s).
/// shape: (sites, thresholds)
///
- /// t_msk: ``xt::xtensor<bool, 4>``, optional
+ /// t_msk: ``XB4``, optional
/// Mask(s) used to generate temporal subsets of the whole streamflow
/// time series (where True/False is used for the time steps to
/// include/discard in a given subset). If not provided and neither
@@ -122,13 +136,13 @@ namespace evalhyd
/// evalhyd::evalp(obs, prd, {"CRPS"});
///
/// \endrst
- template <class D2, class D4, class B4>
+ template <class XD2, class XD4, class XB4>
std::vector<xt::xarray<double>> evalp(
- const xt::xexpression<D2>& q_obs,
- const xt::xexpression<D4>& q_prd,
+ const xt::xexpression<XD2>& q_obs,
+ const xt::xexpression<XD4>& q_prd,
const std::vector<std::string>& metrics,
- const xt::xexpression<D2>& q_thr = D2({}),
- const xt::xexpression<B4>& t_msk = B4({}),
+ const xt::xexpression<XD2>& q_thr = XD2({}),
+ const xt::xexpression<XB4>& t_msk = XB4({}),
const xt::xtensor<std::array<char, 32>, 2>& m_cdt = {},
const std::unordered_map<std::string, int>& bootstrap =
{{"n_samples", -9}, {"len_sample", -9}, {"summary", 0}},
@@ -136,19 +150,19 @@ namespace evalhyd
)
{
// check ranks of tensors
- if (xt::get_rank<D2>::value != 2)
+ if (xt::get_rank<XD2>::value != 2)
{
throw std::runtime_error(
"observations and/or thresholds are not two-dimensional"
);
}
- if (xt::get_rank<D4>::value != 4)
+ if (xt::get_rank<XD4>::value != 4)
{
throw std::runtime_error(
"predictions are not four-dimensional"
);
}
- if (xt::get_rank<B4>::value != 4)
+ if (xt::get_rank<XB4>::value != 4)
{
throw std::runtime_error(
"temporal masks are not four-dimensional"
@@ -156,11 +170,11 @@ namespace evalhyd
}
// retrieve real types of the expressions
- const D2& q_obs_ = q_obs.derived_cast();
- const D4& q_prd_ = q_prd.derived_cast();
- const D2& q_thr_ = q_thr.derived_cast();
+ const XD2& q_obs_ = q_obs.derived_cast();
+ const XD4& q_prd_ = q_prd.derived_cast();
+ const XD2& q_thr_ = q_thr.derived_cast();
- const B4& t_msk_ = t_msk.derived_cast();
+ const XB4& t_msk_ = t_msk.derived_cast();
// check that the metrics to be computed are valid
utils::check_metrics(
@@ -268,7 +282,7 @@ namespace evalhyd
// generate masks from conditions if provided
auto gen_msk = [&]()
{
- B4 c_msk = xt::zeros<bool>({n_sit, n_ltm, n_msk, n_tim});
+ XB4 c_msk = xt::zeros<bool>({n_sit, n_ltm, n_msk, n_tim});
if (m_cdt.size() > 0)
{
for (std::size_t s = 0; s < n_sit; s++)
@@ -290,7 +304,7 @@ namespace evalhyd
return c_msk;
};
- const B4 c_msk = gen_msk();
+ const XB4 c_msk = gen_msk();
// generate bootstrap experiment if requested
std::vector<xt::xkeep_slice<int>> b_exp;
@@ -341,7 +355,7 @@ namespace evalhyd
xt::view(c_msk, s, l, xt::all(), xt::all()) :
xt::view(t_msk_, s, l, xt::all(), xt::all()));
- probabilist::Evaluator<D2, D4, B4> evaluator(
+ probabilist::Evaluator<XD2, XD4, XB4> evaluator(
q_obs_v, q_prd_v, q_thr_v, t_msk_v, b_exp
);
--
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