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Commit fe0716dd authored by Thibault Hallouin's avatar Thibault Hallouin
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make other probabilist metrics uppercase

parent 902288a4
main 11-check-the-computation-of-the-ranks-for-ties add-determinist-to-evalp dev v0.1.2 v0.1.1 v0.1.0 v0.0.1
1 merge request!1implement quantile scores and CRPS
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+49 -49
include/evalhyd/probabilist.hpp
+ 21
− 21
View file @ fe0716dd
...@@ -42,7 +42,7 @@ namespace evalhyd ...@@ -42,7 +42,7 @@ namespace evalhyd
// check that the metrics to be computed are valid // check that the metrics to be computed are valid
utils::check_metrics( utils::check_metrics(
metrics, metrics,
{"bs", "bss", "bs_crd", "bs_lbd", "QS", "CRPS"} {"BS", "BSS", "BS_CRD", "BS_LBD", "QS", "CRPS"}
); );
// instantiate probabilist evaluator // instantiate probabilist evaluator
...@@ -53,14 +53,14 @@ namespace evalhyd ...@@ -53,14 +53,14 @@ namespace evalhyd
std::unordered_map<std::string, std::vector<std::string>> dep; std::unordered_map<std::string, std::vector<std::string>> dep;
// register potentially recurring computation elements across metrics // register potentially recurring computation elements across metrics
elt["bs"] = {"o_k", "y_k"}; elt["BS"] = {"o_k", "y_k"};
elt["bss"] = {"o_k", "bar_o"}; elt["BSS"] = {"o_k", "bar_o"};
elt["bs_crd"] = {"o_k", "bar_o", "y_k"}; elt["BS_CRD"] = {"o_k", "bar_o", "y_k"};
elt["bs_lbd"] = {"o_k", "y_k"}; elt["BS_LBD"] = {"o_k", "y_k"};
elt["qs"] = {"q_qnt"}; elt["QS"] = {"q_qnt"};
// register nested metrics (i.e. metric dependent on another metric) // register nested metrics (i.e. metric dependent on another metric)
dep["bss"] = {"bs"}; dep["BSS"] = {"BS"};
dep["QS"] = {"qs"}; dep["QS"] = {"qs"};
dep["CRPS"] = {"qs", "crps"}; dep["CRPS"] = {"qs", "crps"};
...@@ -86,8 +86,8 @@ namespace evalhyd ...@@ -86,8 +86,8 @@ namespace evalhyd
// pre-compute required dep // pre-compute required dep
for (const auto& dependency : req_dep) for (const auto& dependency : req_dep)
{ {
if ( dependency == "bs" ) if ( dependency == "BS" )
evaluator.calc_bs(); evaluator.calc_BS();
else if ( dependency == "qs" ) else if ( dependency == "qs" )
evaluator.calc_qs(); evaluator.calc_qs();
else if ( dependency == "crps" ) else if ( dependency == "crps" )
...@@ -99,33 +99,33 @@ namespace evalhyd ...@@ -99,33 +99,33 @@ namespace evalhyd
for (const auto& metric : metrics) for (const auto& metric : metrics)
{ {
if ( metric == "bs" ) if ( metric == "BS" )
{ {
if (std::find(req_dep.begin(), req_dep.end(), metric) if (std::find(req_dep.begin(), req_dep.end(), metric)
== req_dep.end()) == req_dep.end())
evaluator.calc_bs(); evaluator.calc_BS();
r.emplace_back(evaluator.bs); r.emplace_back(evaluator.BS);
} }
else if ( metric == "bss" ) else if ( metric == "BSS" )
{ {
if (std::find(req_dep.begin(), req_dep.end(), metric) if (std::find(req_dep.begin(), req_dep.end(), metric)
== req_dep.end()) == req_dep.end())
evaluator.calc_bss(); evaluator.calc_BSS();
r.emplace_back(evaluator.bss); r.emplace_back(evaluator.BSS);
} }
else if ( metric == "bs_crd" ) else if ( metric == "BS_CRD" )
{ {
if (std::find(req_dep.begin(), req_dep.end(), metric) if (std::find(req_dep.begin(), req_dep.end(), metric)
== req_dep.end()) == req_dep.end())
evaluator.calc_bs_crd(); evaluator.calc_BS_CRD();
r.emplace_back(evaluator.bs_crd); r.emplace_back(evaluator.BS_CRD);
} }
else if ( metric == "bs_lbd" ) else if ( metric == "BS_LBD" )
{ {
if (std::find(req_dep.begin(), req_dep.end(), metric) if (std::find(req_dep.begin(), req_dep.end(), metric)
== req_dep.end()) == req_dep.end())
evaluator.calc_bs_lbd(); evaluator.calc_BS_LBD();
r.emplace_back(evaluator.bs_lbd); r.emplace_back(evaluator.BS_LBD);
} }
else if ( metric == "QS" ) else if ( metric == "QS" )
{ {
......
include/evalhyd/probabilist/evaluator.h
+ 8
− 8
View file @ fe0716dd
...@@ -34,10 +34,10 @@ namespace evalhyd ...@@ -34,10 +34,10 @@ namespace evalhyd
xt::xtensor<double, 2> crps; xt::xtensor<double, 2> crps;
// members for evaluation metrics // members for evaluation metrics
xt::xtensor<double, 2> bs; xt::xtensor<double, 2> BS;
xt::xtensor<double, 2> bs_crd; xt::xtensor<double, 2> BS_CRD;
xt::xtensor<double, 2> bs_lbd; xt::xtensor<double, 2> BS_LBD;
xt::xtensor<double, 2> bss; xt::xtensor<double, 2> BSS;
xt::xtensor<double, 2> QS; xt::xtensor<double, 2> QS;
xt::xtensor<double, 2> CRPS; xt::xtensor<double, 2> CRPS;
...@@ -54,10 +54,10 @@ namespace evalhyd ...@@ -54,10 +54,10 @@ namespace evalhyd
void calc_crps(); void calc_crps();
// methods to compute metrics // methods to compute metrics
void calc_bs(); void calc_BS();
void calc_bs_crd(); void calc_BS_CRD();
void calc_bs_lbd(); void calc_BS_LBD();
void calc_bss(); void calc_BSS();
void calc_QS(); void calc_QS();
void calc_CRPS(); void calc_CRPS();
}; };
......
include/evalhyd/probabilist/evaluator_brier.cpp
+ 19
− 19
View file @ fe0716dd
...@@ -25,14 +25,14 @@ namespace evalhyd ...@@ -25,14 +25,14 @@ namespace evalhyd
// \require y_k: // \require y_k:
// Event probability forecast. // Event probability forecast.
// shape: (thresholds, time) // shape: (thresholds, time)
// \assign bs: // \assign BS:
// 2D array of Brier score for each threshold. // 2D array of Brier score for each threshold.
// shape: (thresholds, 1) // shape: (thresholds, 1)
void Evaluator::calc_bs() void Evaluator::calc_BS()
{ {
// return computed Brier score(s) // return computed Brier score(s)
// $BS = \frac{1}{n} \sum_{k=1}^{n} (o_k - y_k)^2$ // $BS = \frac{1}{n} \sum_{k=1}^{n} (o_k - y_k)^2$
bs = xt::mean(xt::square(o_k - y_k), -1, xt::keep_dims); BS = xt::mean(xt::square(o_k - y_k), -1, xt::keep_dims);
} }
// Compute the calibration-refinement decomposition of the Brier score // Compute the calibration-refinement decomposition of the Brier score
...@@ -49,11 +49,11 @@ namespace evalhyd ...@@ -49,11 +49,11 @@ namespace evalhyd
// \require y_k: // \require y_k:
// Event probability forecast. // Event probability forecast.
// shape: (thresholds, time) // shape: (thresholds, time)
// \assign bs_crd: // \assign BS_CRD:
// 2D array of Brier score components (reliability, resolution, // 2D array of Brier score components (reliability, resolution,
// uncertainty) for each threshold. // uncertainty) for each threshold.
// shape: (thresholds, components) // shape: (thresholds, components)
void Evaluator::calc_bs_crd() void Evaluator::calc_BS_CRD()
{ {
// declare internal variables // declare internal variables
// shape: (bins, thresholds, time) // shape: (bins, thresholds, time)
...@@ -71,7 +71,7 @@ namespace evalhyd ...@@ -71,7 +71,7 @@ namespace evalhyd
// initialise output variable // initialise output variable
// shape: (components, thresholds) // shape: (components, thresholds)
bs_crd = xt::zeros<double>({n_thr, n_cmp}); BS_CRD = xt::zeros<double>({n_thr, n_cmp});
// compute range of forecast values $y_i$ // compute range of forecast values $y_i$
y_i = xt::arange<double>(double(n_mbr + 1)) / n_mbr; y_i = xt::arange<double>(double(n_mbr + 1)) / n_mbr;
...@@ -103,7 +103,7 @@ namespace evalhyd ...@@ -103,7 +103,7 @@ namespace evalhyd
// calculate reliability = // calculate reliability =
// $\frac{1}{n} \sum_{i=1}^{I} N_i (y_i - \bar{o_i})^2$ // $\frac{1}{n} \sum_{i=1}^{I} N_i (y_i - \bar{o_i})^2$
xt::col(bs_crd, 0) = xt::col(BS_CRD, 0) =
xt::sum( xt::sum(
xt::square( xt::square(
xt::view(y_i, xt::all(), xt::newaxis()) xt::view(y_i, xt::all(), xt::newaxis())
...@@ -114,7 +114,7 @@ namespace evalhyd ...@@ -114,7 +114,7 @@ namespace evalhyd
// calculate resolution = // calculate resolution =
// $\frac{1}{n} \sum_{i=1}^{I} N_i (\bar{o_i} - \bar{o})^2$ // $\frac{1}{n} \sum_{i=1}^{I} N_i (\bar{o_i} - \bar{o})^2$
xt::col(bs_crd, 1) = xt::col(BS_CRD, 1) =
xt::sum( xt::sum(
xt::square( xt::square(
bar_o_i - bar_o bar_o_i - bar_o
...@@ -123,7 +123,7 @@ namespace evalhyd ...@@ -123,7 +123,7 @@ namespace evalhyd
) / n; ) / n;
// calculate uncertainty = $\bar{o} (1 - \bar{o})$ // calculate uncertainty = $\bar{o} (1 - \bar{o})$
xt::col(bs_crd, 2) = bar_o * (1 - bar_o); xt::col(BS_CRD, 2) = bar_o * (1 - bar_o);
} }
// Compute the likelihood-base rate decomposition of the Brier score // Compute the likelihood-base rate decomposition of the Brier score
...@@ -137,11 +137,11 @@ namespace evalhyd ...@@ -137,11 +137,11 @@ namespace evalhyd
// \require y_k: // \require y_k:
// Event probability forecast. // Event probability forecast.
// shape: (thresholds, time) // shape: (thresholds, time)
// \return bs_lbd: // \return BS_LBD:
// 2D array of Brier score components (type 2 bias, discrimination, // 2D array of Brier score components (type 2 bias, discrimination,
// sharpness) for each threshold. // sharpness) for each threshold.
// shape: (thresholds, components) // shape: (thresholds, components)
void Evaluator::calc_bs_lbd() void Evaluator::calc_BS_LBD()
{ {
// declare internal variables // declare internal variables
// shape: (bins, thresholds, time) // shape: (bins, thresholds, time)
...@@ -160,7 +160,7 @@ namespace evalhyd ...@@ -160,7 +160,7 @@ namespace evalhyd
// declare and initialise output variable // declare and initialise output variable
// shape: (components, thresholds) // shape: (components, thresholds)
bs_lbd = xt::zeros<double>({n_thr, n_cmp}); BS_LBD = xt::zeros<double>({n_thr, n_cmp});
// set the range of observed values $o_j$ // set the range of observed values $o_j$
o_j = {0., 1.}; o_j = {0., 1.};
...@@ -196,7 +196,7 @@ namespace evalhyd ...@@ -196,7 +196,7 @@ namespace evalhyd
// calculate type 2 bias = // calculate type 2 bias =
// $\frac{1}{n} \sum_{j=1}^{J} M_j (o_j - \bar{y_j})^2$ // $\frac{1}{n} \sum_{j=1}^{J} M_j (o_j - \bar{y_j})^2$
xt::col(bs_lbd, 0) = xt::col(BS_LBD, 0) =
xt::sum( xt::sum(
xt::square( xt::square(
xt::view(o_j, xt::all(), xt::newaxis()) xt::view(o_j, xt::all(), xt::newaxis())
...@@ -207,7 +207,7 @@ namespace evalhyd ...@@ -207,7 +207,7 @@ namespace evalhyd
// calculate discrimination = // calculate discrimination =
// $\frac{1}{n} \sum_{j=1}^{J} M_j (\bar{y_j} - \bar{y})^2$ // $\frac{1}{n} \sum_{j=1}^{J} M_j (\bar{y_j} - \bar{y})^2$
xt::col(bs_lbd, 1) = xt::col(BS_LBD, 1) =
xt::sum( xt::sum(
xt::square( xt::square(
bar_y_j - bar_y bar_y_j - bar_y
...@@ -217,7 +217,7 @@ namespace evalhyd ...@@ -217,7 +217,7 @@ namespace evalhyd
// calculate sharpness = // calculate sharpness =
// $\frac{1}{n} \sum_{k=1}^{n} (\bar{y_k} - \bar{y})^2$ // $\frac{1}{n} \sum_{k=1}^{n} (\bar{y_k} - \bar{y})^2$
xt::col(bs_lbd, 2) = xt::col(BS_LBD, 2) =
xt::sum( xt::sum(
xt::square( xt::square(
y_k - y_k -
...@@ -235,13 +235,13 @@ namespace evalhyd ...@@ -235,13 +235,13 @@ namespace evalhyd
// \require bar_o: // \require bar_o:
// Mean event observed outcome. // Mean event observed outcome.
// shape: (thresholds,) // shape: (thresholds,)
// \require bs: // \require BS:
// Brier score(s). // Brier score(s).
// shape: (thresholds,) // shape: (thresholds,)
// \assign bss: // \assign BSS:
// 2D array of Brier skill score for each threshold. // 2D array of Brier skill score for each threshold.
// shape: (thresholds, 1) // shape: (thresholds, 1)
void Evaluator::calc_bss() void Evaluator::calc_BSS()
{ {
// calculate reference Brier score(s) // calculate reference Brier score(s)
// $BS_{ref} = \frac{1}{n} \sum_{k=1}^{n} (o_k - \bar{o})^2$ // $BS_{ref} = \frac{1}{n} \sum_{k=1}^{n} (o_k - \bar{o})^2$
...@@ -256,7 +256,7 @@ namespace evalhyd ...@@ -256,7 +256,7 @@ namespace evalhyd
// return computed Brier skill score(s) // return computed Brier skill score(s)
// $BSS = 1 - \frac{BS}{BS_{ref}} // $BSS = 1 - \frac{BS}{BS_{ref}}
bss = 1 - (bs / bs_ref); BSS = 1 - (BS / bs_ref);
} }
} }
} }
tests/test_probabilist.cpp
+ 1
− 1
View file @ fe0716dd
...@@ -24,7 +24,7 @@ TEST(ProbabilistTests, TestBrier) { ...@@ -24,7 +24,7 @@ TEST(ProbabilistTests, TestBrier) {
std::vector<xt::xtensor<double, 2>> metrics = std::vector<xt::xtensor<double, 2>> metrics =
evalhyd::probabilist::evaluate( evalhyd::probabilist::evaluate(
{"bs", "bss", "bs_crd", "bs_lbd"}, {"BS", "BSS", "BS_CRD", "BS_LBD"},
xt::transpose(observed), xt::transpose(forecast), xt::transpose(observed), xt::transpose(forecast),
thresholds thresholds
); );
......
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