diff --git a/CMakeLists.txt b/CMakeLists.txt
index bff6e9365d385b61e9db6d2ba080fac0f5b8f0c3..4e0cfc77977f1211ee849b10e1359d84e393a5cf 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -7,7 +7,7 @@ cmake_minimum_required(VERSION 3.15)
project(
EvalHyd
LANGUAGES CXX
- VERSION 0.1.0
+ VERSION 0.1.1
DESCRIPTION "Utility to evaluate streamflow predictions"
)
diff --git a/changelog.rst b/changelog.rst
index bbc1cb24d2e30e758d3858d056455d4972dd8336..d47ce60b53d322c48ef57e5f4bb0af60165a7a96 100644
--- a/changelog.rst
+++ b/changelog.rst
@@ -6,6 +6,31 @@
Yet to be versioned and released. Only available from *dev* branch until then.
+
+v0.1.1
+------
+
+Released on 2023-06-16.
+
+.. rubric:: Scope changes
+
+* remove `"WSS"` and `"AWI"` as probabilistic evaluation metric because of the
+ arbitrary nature of using the sample climatology as reference/benchmark
+ (`CPP#7 <https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-cpp/-/issues/7>`_)
+
+.. rubric:: Bug fixes
+
+* fix irrelevant rank check failure when passing arrays (and not tensors)
+ (`CPP#6 <https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-cpp/-/issues/6>`_,
+ `R#4 <https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-r/-/issues/4>`_)
+* fix crashing conditional masking functionality at runtime with certain
+ compilers on Windows (in particular when building with Rtools for R>4.1.3) due
+ to the presence of square brackets in the regular expressions that do not seem
+ supported
+ (`R#6 <https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-r/-/issues/6>`_)
+* fix bug when using calendar year as block for the bootstrapping functionality
+ (`CPP#8 <https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-cpp/-/issues/8>`_)
+
v0.1.0
------
diff --git a/include/evalhyd/detail/determinist/efficiencies.hpp b/include/evalhyd/detail/determinist/efficiencies.hpp
index df893670f3f70e4b900903e9417d368f5a3c0ce4..b5d230249aae761f65d8b102a877631a66cad75a 100644
--- a/include/evalhyd/detail/determinist/efficiencies.hpp
+++ b/include/evalhyd/detail/determinist/efficiencies.hpp
@@ -809,4 +809,4 @@ namespace evalhyd
}
}
-#endif //EVALHYD_DETERMINIST_EFFICIENCIES_HPP
\ No newline at end of file
+#endif //EVALHYD_DETERMINIST_EFFICIENCIES_HPP
diff --git a/include/evalhyd/detail/determinist/errors.hpp b/include/evalhyd/detail/determinist/errors.hpp
index 646bbd4ad0776c7c97c4cb4f5a0bbbb7922125a3..4c778e20f362f2a4ee33cb7dbe629ff946c79032 100644
--- a/include/evalhyd/detail/determinist/errors.hpp
+++ b/include/evalhyd/detail/determinist/errors.hpp
@@ -478,4 +478,4 @@ namespace evalhyd
}
}
-#endif //EVALHYD_DETERMINIST_ERRORS_HPP
\ No newline at end of file
+#endif //EVALHYD_DETERMINIST_ERRORS_HPP
diff --git a/include/evalhyd/detail/masks.hpp b/include/evalhyd/detail/masks.hpp
index d1d503e257a826f6448f199c42265daa874fcd65..fe40d078f6cd4836b63fd72499a96c56ffbb9382 100644
--- a/include/evalhyd/detail/masks.hpp
+++ b/include/evalhyd/detail/masks.hpp
@@ -35,7 +35,10 @@ namespace evalhyd
// observed or predicted (median or mean for probabilist) streamflow
// e.g. q{>9.} q{<9} q{>=99.0} q{<=99} q{>9,<99} q{==9} q{!=9}
std::regex exp_q (
- R"((q_obs|q_prd_median|q_prd_mean)\{(((<|>|<=|>=|==|!=)(mean,?|median,?|qtl[0-1]\.[0-9]+,?|[0-9]+\.?[0-9]*,?))+)\})"
+ R"((q_obs|q_prd_median|q_prd_mean)\{(((<|>|<=|>=|==|!=)(mean,?|median,?|qtl(0|1)\.(0|1|2|3|4|5|6|7|8|9)+,?|(0|1|2|3|4|5|6|7|8|9)+\.?(0|1|2|3|4|5|6|7|8|9)*,?))+)\})"
+ // NOTE: this should be `R"((q_obs|q_prd_median|q_prd_mean)\{(((<|>|<=|>=|==|!=)(mean,?|median,?|qtl[0-1]\.[0-9]+,?|[0-9]+\.?[0-9]*,?))+)\})"`
+ // but there is a bug in the building chain for R packages
+ // https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-r/-/issues/6
);
for (std::sregex_iterator i =
@@ -51,7 +54,12 @@ namespace evalhyd
std::vector<std::vector<std::string>> conditions;
// pattern supported to specify masking conditions based on streamflow
- std::regex ex (R"((<|>|<=|>=|==|!=)(mean|median|qtl[0-1]\.[0-9]+|[0-9]+\.?[0-9]*))");
+ std::regex ex (
+ R"((<|>|<=|>=|==|!=)(mean|median|qtl(0|1)\.(0|1|2|3|4|5|6|7|8|9)+|(0|1|2|3|4|5|6|7|8|9)+\.?(0|1|2|3|4|5|6|7|8|9)*))"
+ // NOTE: this should be `R"((<|>|<=|>=|==|!=)(mean|median|qtl[0-1]\.[0-9]+|[0-9]+\.?[0-9]*))"`
+ // but there is a bug in the building chain for R packages
+ // https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-r/-/issues/6
+ );
for (std::sregex_iterator j =
std::sregex_iterator(str.begin(), str.end(), ex);
@@ -92,7 +100,12 @@ namespace evalhyd
// pattern supported to specify conditions to generate masks on time index
// e.g. t{0:10} t{0:10,20:30} t{0,1,2,3} t{0:10,30,40,50} t{:}
- std::regex exp_t (R"((t)\{(:|([0-9]+:[0-9]+,?|[0-9]+,?)+)\})");
+ std::regex exp_t (
+ R"((t)\{(:|((0|1|2|3|4|5|6|7|8|9)+:(0|1|2|3|4|5|6|7|8|9)+,?|(0|1|2|3|4|5|6|7|8|9)+,?)+)\})"
+ // NOTE: this should be `R"((t)\{(:|([0-9]+:[0-9]+,?|[0-9]+,?)+)\})"`
+ // but there is a bug in the building chain for R packages
+ // https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-r/-/issues/6
+ );
for (std::sregex_iterator i =
std::sregex_iterator(msk_str.begin(), msk_str.end(), exp_t);
@@ -114,7 +127,12 @@ namespace evalhyd
else
{
// pattern supported to specify masking conditions based on time index
- std::regex e (R"([0-9]+:[0-9]+|[0-9]+)");
+ std::regex e (
+ R"((0|1|2|3|4|5|6|7|8|9)+:(0|1|2|3|4|5|6|7|8|9)+|(0|1|2|3|4|5|6|7|8|9)+)"
+ // NOTE: this should be `R"([0-9]+:[0-9]+|[0-9]+)"`
+ // but there is a bug in the building chain for R packages
+ // https://gitlab.irstea.fr/HYCAR-Hydro/evalhyd/evalhyd-r/-/issues/6
+ );
for (std::sregex_iterator j =
std::sregex_iterator(s.begin(), s.end(), e);
diff --git a/include/evalhyd/detail/probabilist/cdf.hpp b/include/evalhyd/detail/probabilist/cdf.hpp
index e0cf0b146c8a9d65554bc43e416075c1b4d83c1a..1b02c2cbbb993172f6d78666537aa036ae22111f 100644
--- a/include/evalhyd/detail/probabilist/cdf.hpp
+++ b/include/evalhyd/detail/probabilist/cdf.hpp
@@ -198,4 +198,4 @@ namespace evalhyd
}
}
-#endif //EVALHYD_PROBABILIST_CDF_HPP
\ No newline at end of file
+#endif //EVALHYD_PROBABILIST_CDF_HPP
diff --git a/include/evalhyd/detail/probabilist/contingency.hpp b/include/evalhyd/detail/probabilist/contingency.hpp
index 0c3aa0ecd0fd669558eb7b69d0e602aca2ac6fad..a4685e4aec83615ebad1c612d3fbcdb72b42f97b 100644
--- a/include/evalhyd/detail/probabilist/contingency.hpp
+++ b/include/evalhyd/detail/probabilist/contingency.hpp
@@ -541,4 +541,4 @@ namespace evalhyd
}
}
-#endif //EVALHYD_PROBABILIST_CONTINGENCY_HPP
\ No newline at end of file
+#endif //EVALHYD_PROBABILIST_CONTINGENCY_HPP
diff --git a/include/evalhyd/detail/probabilist/evaluator.hpp b/include/evalhyd/detail/probabilist/evaluator.hpp
index 6293ea29e546df8f9f3756608d213aa4e5773a9e..976145c58817f529c2786a246665c7eac55c5eb9 100644
--- a/include/evalhyd/detail/probabilist/evaluator.hpp
+++ b/include/evalhyd/detail/probabilist/evaluator.hpp
@@ -76,7 +76,6 @@ namespace evalhyd
xtl::xoptional<xt::xtensor<double, 5>, bool> itv_bnds;
xtl::xoptional<xt::xtensor<double, 4>, bool> obs_in_itv;
xtl::xoptional<xt::xtensor<double, 4>, bool> itv_width;
- xtl::xoptional<xt::xtensor<double, 6>, bool> clim_bnds;
// members for intermediate evaluation metrics
// (i.e. before the reduction along the temporal axis)
@@ -124,9 +123,7 @@ namespace evalhyd
xtl::xoptional<xt::xtensor<double, 5>, bool> CR;
xtl::xoptional<xt::xtensor<double, 5>, bool> AW;
xtl::xoptional<xt::xtensor<double, 5>, bool> AWN;
- xtl::xoptional<xt::xtensor<double, 5>, bool> AWI;
xtl::xoptional<xt::xtensor<double, 5>, bool> WS;
- xtl::xoptional<xt::xtensor<double, 5>, bool> WSS;
// > Multi-variate
xtl::xoptional<xt::xtensor<double, 4>, bool> ES;
@@ -367,19 +364,6 @@ namespace evalhyd
return itv_width.value();
};
-
- xt::xtensor<double, 6> get_clim_bnds()
- {
- if (!clim_bnds.has_value())
- {
- clim_bnds = elements::calc_clim_bnds(
- q_obs, get_c_lvl(), t_msk, b_exp,
- n_sit, n_ldt, n_itv, n_msk, n_exp
- );
- }
- return clim_bnds.value();
- };
-
// methods to compute intermediate metrics
xt::xtensor<double, 4> get_bs()
{
@@ -798,17 +782,6 @@ namespace evalhyd
return AWN.value();
};
- xt::xtensor<double, 5> get_AWI()
- {
- if (!AWI.has_value())
- {
- AWI = metrics::calc_AWI(
- get_AW(), get_clim_bnds()
- );
- }
- return AWI.value();
- };
-
xt::xtensor<double, 5> get_WS()
{
if (!WS.has_value())
@@ -821,18 +794,6 @@ namespace evalhyd
return WS.value();
};
- xt::xtensor<double, 5> get_WSS()
- {
- if (!WSS.has_value())
- {
- WSS = metrics::calc_WSS(
- q_obs, get_c_lvl(), get_clim_bnds(), get_WS(),
- t_msk, b_exp, n_sit, n_ldt, n_itv, n_msk, n_exp
- );
- }
- return WSS.value();
- };
-
xt::xtensor<double, 4> get_ES()
{
if (!ES.has_value())
diff --git a/include/evalhyd/detail/probabilist/intervals.hpp b/include/evalhyd/detail/probabilist/intervals.hpp
index c36a235838ead80eec395b4ccd342684217b5afc..adbd487b592ab4903210072e9ae01836ba41e0ac 100644
--- a/include/evalhyd/detail/probabilist/intervals.hpp
+++ b/include/evalhyd/detail/probabilist/intervals.hpp
@@ -123,119 +123,6 @@ namespace evalhyd
return (u - l);
}
-
- /// Compute the bounds of the climatology corresponding to the
- /// confidence levels.
- ///
- /// \param q_obs
- /// Streamflow predictions.
- /// shape: (sites, time)
- /// \param c_lvl
- /// Confidence levels for the predictive intervals.
- /// shape: (intervals,)
- /// \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_itv
- /// Number of predictive intervals.
- /// \param n_msk
- /// Number of temporal subsets.
- /// \param n_exp
- /// Number of bootstrap samples.
- /// \return
- /// Climatology bounds.
- /// shape: (sites, lead times, subsets, samples, intervals, bounds)
- template <class XD2>
- inline xt::xtensor<double, 6> calc_clim_bnds(
- const XD2& q_obs,
- const xt::xtensor<double, 1>& c_lvl,
- const xt::xtensor<bool, 4>& t_msk,
- const std::vector<xt::xkeep_slice<int>>& b_exp,
- std::size_t n_sit,
- std::size_t n_ldt,
- std::size_t n_itv,
- std::size_t n_msk,
- std::size_t n_exp
- )
- {
- // compute "climatology" average width
- xt::xtensor<double, 6> clim_bnds =
- xt::zeros<double>({n_sit, n_ldt, n_msk, n_exp,
- n_itv, std::size_t {2}});
-
- // determine quantiles forming the predictive intervals
- // from the confidence levels
- xt::xtensor<double, 2> quantiles =
- xt::zeros<double>({n_itv, std::size_t {2}});
- xt::col(quantiles, 0) = 0.5 - c_lvl / 200.;
- xt::col(quantiles, 1) = 0.5 + c_lvl / 200.;
-
- // compute variable one mask at a time to minimise memory imprint
- for (std::size_t m = 0; m < n_msk; m++)
- {
- // apply the mask
- // (using NaN workaround until reducers work on masked_view)
- auto q_obs_masked = xt::where(
- xt::view(t_msk, xt::all(), xt::all(), m, xt::all()),
- xt::view(q_obs, xt::all(), xt::newaxis(), xt::all()),
- NAN
- );
-
- // compute variable one sample at a time
- for (std::size_t e = 0; e < n_exp; e++)
- {
- // apply the bootstrap sampling
- auto q_obs_masked_sampled =
- xt::view(q_obs_masked, xt::all(), xt::all(), b_exp[e]);
-
- // compute "climatology" interval
- for (std::size_t s = 0; s < n_sit; s++)
- {
- for (std::size_t l = 0; l < n_ldt; l++)
- {
- for (std::size_t i = 0; i < n_itv; i++)
- {
- auto obs = xt::view(q_obs_masked_sampled,
- s, l, xt::all());
- auto obs_filtered =
- xt::filter(obs, !xt::isnan(obs));
-
- if (obs_filtered.size() > 0)
- {
- // lower bound
- xt::view(clim_bnds, s, l, m, e, i, 0) =
- xt::quantile(
- obs_filtered,
- {quantiles(i, 0)}
- )();
- // upper bound
- xt::view(clim_bnds, s, l, m, e, i, 1) =
- xt::quantile(
- obs_filtered,
- {quantiles(i, 1)}
- )();
- }
- else
- {
- xt::view(clim_bnds, s, l, m, e, i, xt::all()) =
- NAN;
- }
-
- }
- }
- }
- }
- }
-
- return clim_bnds;
- }
}
namespace intermediate
@@ -487,34 +374,6 @@ namespace evalhyd
- std::numeric_limits<double>::infinity());
}
- /// Compute the Average Width Index (AWI).
- ///
- /// \param AW
- /// Average widths.
- /// shape: (sites, lead times, subsets, samples, intervals)
- /// \param clim_bnds
- /// Climatology bounds.
- /// shape: (sites, lead times, subsets, samples, intervals, bounds)
- /// \return
- /// Average width indices.
- /// shape: (sites, lead times, subsets, samples, intervals)
- inline xt::xtensor<double, 5> calc_AWI(
- const xt::xtensor<double, 5>& AW,
- const xt::xtensor<double, 6>& clim_bnds
- )
- {
- // compute "climatology" average width
- auto AW_clim =
- xt::view(clim_bnds, xt::all(), xt::all(), xt::all(),
- xt::all(), xt::all(), 1)
- - xt::view(clim_bnds, xt::all(), xt::all(), xt::all(),
- xt::all(), xt::all(), 0);
-
- return xt::where(AW_clim > 0,
- 1 - (AW / AW_clim),
- - std::numeric_limits<double>::infinity());
- }
-
/// Compute the Winkler scores (WS), also known as interval score.
///
/// \param ws
@@ -554,95 +413,6 @@ namespace evalhyd
ws, t_msk, b_exp, n_sit, n_ldt, n_itv, n_msk, n_exp
);
}
-
- /// Compute the Winkler skill scores (WSS).
- ///
- /// \param q_obs
- /// Streamflow predictions.
- /// shape: (sites, time)
- /// \param c_lvl
- /// Confidence levels for the predictive intervals.
- /// shape: (intervals,)
- /// \param clim_bnds
- /// Climatology bounds.
- /// shape: (sites, lead times, subsets, samples, intervals, bounds)
- /// \param WS
- /// Winkler scores.
- /// shape: (sites, lead times, subsets, samples, intervals)
- /// \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_itv
- /// Number of predictive intervals.
- /// \param n_msk
- /// Number of temporal subsets.
- /// \param n_exp
- /// Number of bootstrap samples.
- /// \return
- /// Winkler skill scores.
- /// shape: (sites, lead times, subsets, samples, intervals)
- template <class XD2>
- inline xt::xtensor<double, 5> calc_WSS(
- const XD2& q_obs,
- const xt::xtensor<double, 1>& c_lvl,
- const xt::xtensor<double, 6>& clim_bnds,
- const xt::xtensor<double, 5>& WS,
- const xt::xtensor<bool, 4>& t_msk,
- const std::vector<xt::xkeep_slice<int>>& b_exp,
- std::size_t n_sit,
- std::size_t n_ldt,
- std::size_t n_itv,
- std::size_t n_msk,
- std::size_t n_exp
- )
- {
- // compute "climatology" Winkler score
- xt::xtensor<double, 5> WS_clim =
- xt::zeros<double>({n_sit, n_ldt, n_msk, n_exp, n_itv});
-
- for (std::size_t l = 0; l < n_ldt; l++)
- {
- for (std::size_t m = 0; m < n_msk; m++)
- {
- for (std::size_t e = 0; e < n_exp; e++)
- {
- auto ws_clim = intermediate::calc_ws(
- q_obs, c_lvl,
- xt::view(clim_bnds, xt::all(), l, xt::newaxis(),
- m, e, xt::all(), xt::all(),
- xt::newaxis())
- );
-
- // apply the mask
- // (using NaN workaround until reducers work on masked_view)
- auto ws_clim_masked = xt::where(
- xt::view(t_msk, xt::all(), l, m, xt::newaxis(), xt::all()),
- xt::view(ws_clim, xt::all(), l, xt::all(), xt::all()),
- NAN
- );
-
- // apply the bootstrap sampling
- auto ws_clim_masked_sampled =
- xt::view(ws_clim_masked, xt::all(), xt::all(), b_exp[e]);
-
- xt::view(WS_clim, xt::all(), l, m, e, xt::all()) =
- xt::nanmean(ws_clim_masked_sampled, -1);
- }
- }
- }
-
- // compute the Winkler skill score
- return xt::where(WS_clim > 0,
- 1 - (WS / WS_clim),
- - std::numeric_limits<double>::infinity());
- }
}
}
}
diff --git a/include/evalhyd/detail/probabilist/ranks.hpp b/include/evalhyd/detail/probabilist/ranks.hpp
index ee3029006470993397eb619cfbda6aebeff8eb0f..ea68e6d0aa623e441ce1262b1e27c579fd244c19 100644
--- a/include/evalhyd/detail/probabilist/ranks.hpp
+++ b/include/evalhyd/detail/probabilist/ranks.hpp
@@ -449,4 +449,4 @@ namespace evalhyd
}
}
-#endif //EVALHYD_PROBABILIST_RANKS_HPP
\ No newline at end of file
+#endif //EVALHYD_PROBABILIST_RANKS_HPP
diff --git a/include/evalhyd/detail/uncertainty.hpp b/include/evalhyd/detail/uncertainty.hpp
index 25b13af0957e7552f52fe648564f2abc67be0054..af55fc2425c19b68bdaba70488d9305b60478825 100644
--- a/include/evalhyd/detail/uncertainty.hpp
+++ b/include/evalhyd/detail/uncertainty.hpp
@@ -76,7 +76,16 @@ namespace evalhyd
int start_yr = v_tm.front().tm_year + 1900;
int end_yr = v_tm.back().tm_year + 1900;
- // assume start of year block as start of time series
+ // deal with special case with a start on 1st of January
+ // (note: use string rather than *tm_yday* member of time_point
+ // because *tm_yday* is not set when using `std::get_time`)
+ if (datetimes[0].substr(5, 5) == "01-01")
+ {
+ // add one year to make sure last year is included in loop
+ end_yr += 1;
+ }
+
+ // take start of year block as start of time series
std::tm start_hy = v_tm.front();
xt::xtensor<int, 1> year_blocks = xt::zeros<int>({v_tm.size()});
@@ -100,7 +109,7 @@ namespace evalhyd
if ((n_days != 365) && (n_days != 366))
{
throw std::runtime_error(
- "year starting in " + std::to_string(y)
+ "year starting in " + std::to_string(y - 400)
+ " is incomplete"
);
}
diff --git a/include/evalhyd/evald.hpp b/include/evalhyd/evald.hpp
index 19cbdbcecde37ea6f5e82ce593c273916d04bae4..9ddeeadf1ddb42ba5caed1bc54748ce24b351be2 100644
--- a/include/evalhyd/evald.hpp
+++ b/include/evalhyd/evald.hpp
@@ -210,19 +210,25 @@ namespace evalhyd
xtl::missing<const std::vector<std::string>>()
)
{
- // check ranks of tensors
- if (xt::get_rank<XD2>::value != 2)
+ // check ranks of expressions if they are tensors
+ if (xt::get_rank<XD2>::value != SIZE_MAX)
{
- throw std::runtime_error(
- "observations and/or predictions and/or thresholds "
- "are not two-dimensional"
- );
+ if (xt::get_rank<XD2>::value != 2)
+ {
+ throw std::runtime_error(
+ "observations and/or predictions and/or thresholds "
+ "are not two-dimensional"
+ );
+ }
}
- if (xt::get_rank<XB3>::value != 3)
+ if (xt::get_rank<XB3>::value != SIZE_MAX)
{
- throw std::runtime_error(
- "temporal masks are not three-dimensional"
- );
+ if (xt::get_rank<XB3>::value != 3)
+ {
+ throw std::runtime_error(
+ "temporal masks are not three-dimensional"
+ );
+ }
}
// retrieve real types of the expressions
@@ -366,7 +372,7 @@ namespace evalhyd
}
else
{
- return XB3({});
+ return XB3(xt::zeros<bool>({0, 0, 0}));
}
};
const XB3 c_msk = gen_msk();
diff --git a/include/evalhyd/evalp.hpp b/include/evalhyd/evalp.hpp
index d7e1d4279985fec564b21f41b21043edf22768ad..c04412097f925f675cb5750037086c421dceda9e 100644
--- a/include/evalhyd/evalp.hpp
+++ b/include/evalhyd/evalp.hpp
@@ -166,7 +166,7 @@ namespace evalhyd
///
/// .. code-block:: c++
///
- /// evalhyd::evalp(obs, prd, {"CRPS"});
+ /// evalhyd::evalp(obs, prd, {"CRPS_FROM_QS"});
///
/// \endrst
template <class XD2, class XD4, class XB4 = xt::xtensor<bool, 4>,
@@ -190,24 +190,35 @@ namespace evalhyd
xtl::missing<const std::vector<std::string>>()
)
{
- // check ranks of tensors
- if (xt::get_rank<XD2>::value != 2)
+ // check ranks of expressions if they are tensors
+ if (xt::get_rank<XD2>::value != SIZE_MAX)
{
- throw std::runtime_error(
- "observations and/or thresholds are not two-dimensional"
- );
+ if (xt::get_rank<XD2>::value != 2)
+ {
+ throw std::runtime_error(
+ "observations and/or thresholds are not two-dimensional"
+ );
+ }
}
- if (xt::get_rank<XD4>::value != 4)
+
+ if (xt::get_rank<XD4>::value != SIZE_MAX)
{
- throw std::runtime_error(
- "predictions are not four-dimensional"
- );
+ if (xt::get_rank<XD4>::value != 4)
+ {
+ throw std::runtime_error(
+ "predictions are not four-dimensional"
+ );
+ }
}
- if (xt::get_rank<XB4>::value != 4)
+
+ if (xt::get_rank<XB4>::value != SIZE_MAX)
{
- throw std::runtime_error(
- "temporal masks are not four-dimensional"
- );
+ if (xt::get_rank<XB4>::value != 4)
+ {
+ throw std::runtime_error(
+ "temporal masks are not four-dimensional"
+ );
+ }
}
// retrieve real types of the expressions
@@ -229,7 +240,7 @@ namespace evalhyd
"QS", "CRPS_FROM_QS",
"POD", "POFD", "FAR", "CSI", "ROCSS",
"RANK_HIST", "DS", "AS",
- "CR", "AW", "AWN", "AWI", "WS", "WSS",
+ "CR", "AW", "AWN", "WS",
"ES"}
);
@@ -368,7 +379,7 @@ namespace evalhyd
}
else
{
- return XB4({});
+ return XB4(xt::zeros<bool>({0, 0, 0, 0}));
}
};
const XB4 c_msk = gen_msk();
@@ -536,24 +547,12 @@ namespace evalhyd
uncertainty::summarise_p(evaluator.get_AWN(), summary)
);
}
- else if ( metric == "AWI" )
- {
- r.emplace_back(
- uncertainty::summarise_p(evaluator.get_AWI(), summary)
- );
- }
else if ( metric == "WS" )
{
r.emplace_back(
uncertainty::summarise_p(evaluator.get_WS(), summary)
);
}
- else if ( metric == "WSS" )
- {
- r.emplace_back(
- uncertainty::summarise_p(evaluator.get_WSS(), summary)
- );
- }
else if ( metric == "ES" )
{
r.emplace_back(
diff --git a/tests/expected/evalp/AWI.csv b/tests/expected/evalp/AWI.csv
deleted file mode 100644
index 8b3b7e7f9598b23911dc06f440d71572b99b48e5..0000000000000000000000000000000000000000
--- a/tests/expected/evalp/AWI.csv
+++ /dev/null
@@ -1 +0,0 @@
-0.9821120161733,0.9880951944476
diff --git a/tests/expected/evalp/WSS.csv b/tests/expected/evalp/WSS.csv
deleted file mode 100644
index fd929dabd8f58354be587455dcbd4402d6a9f83d..0000000000000000000000000000000000000000
--- a/tests/expected/evalp/WSS.csv
+++ /dev/null
@@ -1 +0,0 @@
-0.6621887740287,0.4360388849930
diff --git a/tests/test_probabilist.cpp b/tests/test_probabilist.cpp
index 65b16cdde5c4e0b30280bed9a96a8cfea6f36ba9..f4e53f71cc694abffe77c5d5287af2fa6124c4c9 100644
--- a/tests/test_probabilist.cpp
+++ b/tests/test_probabilist.cpp
@@ -35,7 +35,7 @@ std::vector<std::string> all_metrics_p = {
"QS", "CRPS_FROM_QS",
"POD", "POFD", "FAR", "CSI", "ROCSS",
"RANK_HIST", "DS", "AS",
- "CR", "AW", "AWN", "AWI", "WS", "WSS",
+ "CR", "AW", "AWN", "WS",
"ES"
};
@@ -263,7 +263,7 @@ TEST(ProbabilistTests, TestIntervals)
auto expected = load_expected_p();
// compute scores
- std::vector<std::string> metrics = {"CR", "AW", "AWN", "AWI", "WS", "WSS"};
+ std::vector<std::string> metrics = {"CR", "AW", "AWN", "WS"};
std::vector<xt::xarray<double>> results =
evalhyd::evalp(
@@ -271,7 +271,7 @@ TEST(ProbabilistTests, TestIntervals)
xt::eval(xt::view(observed, xt::newaxis(), xt::all())),
// shape: (sites [1], lead times [1], members [m], time [t])
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::all())),
- {"CR", "AW", "AWN", "AWI", "WS", "WSS"},
+ {"CR", "AW", "AWN", "WS"},
xt::xtensor<double, 2>({}),
"", // events
{30., 80.} // c_lvl