diff --git a/tests/test_determinist.cpp b/tests/test_determinist.cpp
index 1420056b3ed3ad68534886a210c6f64000a275a4..decdf97cef9b02b689d58be8f3ac2adc3d38dfe9 100644
--- a/tests/test_determinist.cpp
+++ b/tests/test_determinist.cpp
@@ -21,6 +21,11 @@
using namespace xt::placeholders; // required for `_` to work
+
+std::vector<std::string> all_metrics_d = {
+ "RMSE", "NSE", "KGE", "KGEPRIME"
+};
+
std::tuple<xt::xtensor<double, 2>, xt::xtensor<double, 2>> load_data_d()
{
// read in data
@@ -152,32 +157,26 @@ TEST(DeterministTests, TestMasks)
xt::view(masks, 0, xt::range(0, 20)) = 0;
// compute scores using masks to subset whole record
- std::vector<std::string> metrics =
- {"RMSE", "NSE", "KGE", "KGEPRIME"};
-
std::vector<xt::xarray<double>> metrics_masked =
- evalhyd::evald(observed, predicted, metrics, {}, {}, {}, masks);
+ evalhyd::evald(observed, predicted, all_metrics_d, {}, {}, {}, masks);
// compute scores on pre-computed subset of whole record
xt::xtensor<double, 2> obs = xt::view(observed, xt::all(), xt::range(20, _));
xt::xtensor<double, 2> prd = xt::view(predicted, xt::all(), xt::range(20, _));
std::vector<xt::xarray<double>> metrics_subset =
- evalhyd::evald(obs, prd, metrics);
+ evalhyd::evald(obs, prd, all_metrics_d);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_d.size(); m++)
{
EXPECT_TRUE(xt::allclose(metrics_masked[m], metrics_subset[m]))
- << "Failure for (" << metrics[m] << ")";
+ << "Failure for (" << all_metrics_d[m] << ")";
}
}
TEST(DeterministTests, TestMaskingConditions)
{
- std::vector<std::string> metrics =
- {"RMSE", "NSE", "KGE", "KGEPRIME"};
-
// read in data
xt::xtensor<double, 2> observed;
xt::xtensor<double, 2> predicted;
@@ -195,7 +194,7 @@ TEST(DeterministTests, TestMaskingConditions)
std::vector<xt::xarray<double>> metrics_q_conditioned =
evalhyd::evald(
- observed, predicted, metrics,
+ observed, predicted, all_metrics_d,
{}, {}, {}, masks, q_conditions
);
@@ -204,17 +203,17 @@ TEST(DeterministTests, TestMaskingConditions)
evalhyd::evald(
xt::eval(xt::where((observed < 2000) | (observed > 3000), observed, NAN)),
predicted,
- metrics
+ all_metrics_d
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_d.size(); m++)
{
EXPECT_TRUE(
xt::allclose(
metrics_q_conditioned[m], metrics_q_preconditioned[m]
)
- ) << "Failure for (" << metrics[m] << ")";
+ ) << "Failure for (" << all_metrics_d[m] << ")";
}
// conditions on streamflow statistics _____________________________________
@@ -228,7 +227,7 @@ TEST(DeterministTests, TestMaskingConditions)
std::vector<xt::xarray<double>> metrics_q_conditioned_ =
evalhyd::evald(
- observed, predicted, metrics,
+ observed, predicted, all_metrics_d,
{}, {}, {}, masks, q_conditions_
);
@@ -237,17 +236,17 @@ TEST(DeterministTests, TestMaskingConditions)
evalhyd::evald(
xt::eval(xt::where(observed >= mean, observed, NAN)),
predicted,
- metrics
+ all_metrics_d
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_d.size(); m++)
{
EXPECT_TRUE(
xt::allclose(
metrics_q_conditioned_[m], metrics_q_preconditioned_[m]
)
- ) << "Failure for (" << metrics[m] << ")";
+ ) << "Failure for (" << all_metrics_d[m] << ")";
}
// conditions on temporal indices __________________________________________
@@ -259,7 +258,7 @@ TEST(DeterministTests, TestMaskingConditions)
std::vector<xt::xarray<double>> metrics_t_conditioned =
evalhyd::evald(
- observed, predicted, metrics,
+ observed, predicted, all_metrics_d,
{}, {}, {}, masks, t_conditions
);
@@ -268,25 +267,22 @@ TEST(DeterministTests, TestMaskingConditions)
evalhyd::evald(
xt::eval(xt::view(observed, xt::all(), xt::range(0, 100))),
xt::eval(xt::view(predicted, xt::all(), xt::range(0, 100))),
- metrics
+ all_metrics_d
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_d.size(); m++)
{
EXPECT_TRUE(
xt::allclose(
metrics_t_conditioned[m], metrics_t_subset[m]
)
- ) << "Failure for (" << metrics[m] << ")";
+ ) << "Failure for (" << all_metrics_d[m] << ")";
}
}
TEST(DeterministTests, TestMissingData)
{
- std::vector<std::string> metrics =
- {"RMSE", "NSE", "KGE", "KGEPRIME"};
-
// read in data
xt::xtensor<double, 2> observed;
xt::xtensor<double, 2> predicted;
@@ -303,9 +299,9 @@ TEST(DeterministTests, TestMissingData)
// compute metrics with observations containing NaN values
std::vector<xt::xarray<double>> metrics_nan =
- evalhyd::evald(observed, predicted, metrics);
+ evalhyd::evald(observed, predicted, all_metrics_d);
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_d.size(); m++)
{
for (std::size_t p = 0; p < predicted.shape(0); p++)
{
@@ -320,7 +316,7 @@ TEST(DeterministTests, TestMissingData)
evalhyd::evald(
xt::eval(xt::view(obs, xt::newaxis(), xt::all())),
xt::eval(xt::view(prd, xt::newaxis(), xt::all())),
- {metrics[m]}
+ {all_metrics_d[m]}
);
// compare to check results are the same
@@ -329,16 +325,13 @@ TEST(DeterministTests, TestMissingData)
xt::view(metrics_nan[m], p),
metrics_sbs[0]
)
- ) << "Failure for (" << metrics[m] << ")";
+ ) << "Failure for (" << all_metrics_d[m] << ")";
}
}
}
TEST(DeterministTests, TestBootstrap)
{
- std::vector<std::string> metrics =
- {"RMSE", "NSE", "KGE", "KGEPRIME"};
-
// read in data
std::ifstream ifs;
@@ -363,7 +356,7 @@ TEST(DeterministTests, TestBootstrap)
evalhyd::evald(
xt::eval(xt::view(observed, xt::newaxis(), xt::all())),
predicted,
- metrics,
+ all_metrics_d,
{}, // transform
{}, // exponent
{}, // epsilon
@@ -388,16 +381,16 @@ TEST(DeterministTests, TestBootstrap)
evalhyd::evald(
xt::eval(xt::view(observed_x3, xt::newaxis(), xt::all())),
predicted_x3,
- metrics
+ all_metrics_d
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_d.size(); m++)
{
EXPECT_TRUE(
xt::allclose(
metrics_bts[m], metrics_rep[m]
)
- ) << "Failure for (" << metrics[m] << ")";
+ ) << "Failure for (" << all_metrics_d[m] << ")";
}
}
diff --git a/tests/test_probabilist.cpp b/tests/test_probabilist.cpp
index be6cb4fb7c7015d979656698932aee8e6349258f..8a54c25261ffc8b119046fd1ef34b5feb3dc0beb 100644
--- a/tests/test_probabilist.cpp
+++ b/tests/test_probabilist.cpp
@@ -21,6 +21,13 @@
using namespace xt::placeholders; // required for `_` to work
+
+std::vector<std::string> all_metrics_p = {
+ "BS", "BSS", "BS_CRD", "BS_LBD",
+ "QS", "CRPS",
+ "POD", "POFD", "FAR", "CSI", "ROCSS"
+};
+
std::tuple<xt::xtensor<double, 1>, xt::xtensor<double, 2>> load_data_p()
{
// read in data
@@ -419,8 +426,6 @@ TEST(ProbabilistTests, TestMasks)
// compute scores using masks to subset whole record
xt::xtensor<double, 2> thresholds = {{690, 534, 445}};
- std::vector<std::string> metrics =
- {"BS", "BSS", "BS_CRD", "BS_LBD", "QS", "CRPS"};
std::vector<xt::xarray<double>> metrics_masked =
evalhyd::evalp(
@@ -428,7 +433,7 @@ TEST(ProbabilistTests, TestMasks)
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())),
- metrics,
+ all_metrics_p,
thresholds,
"high",
// shape: (sites [1], lead times [1], subsets [1], time [t])
@@ -442,24 +447,22 @@ TEST(ProbabilistTests, TestMasks)
xt::eval(xt::view(observed, xt::newaxis(), xt::range(20, _))),
// shape: (sites [1], lead times [1], members [m], time [t-20])
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::range(20, _))),
- metrics,
+ all_metrics_p,
thresholds,
"high"
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_p.size(); m++)
{
EXPECT_TRUE(xt::allclose(metrics_masked[m], metrics_subset[m]))
- << "Failure for (" << metrics[m] << ")";
+ << "Failure for (" << all_metrics_p[m] << ")";
}
}
TEST(ProbabilistTests, TestMaskingConditions)
{
xt::xtensor<double, 2> thresholds = {{690, 534, 445}};
- std::vector<std::string> metrics =
- {"BS", "BSS", "BS_CRD", "BS_LBD", "QS", "CRPS"};
// read in data
xt::xtensor<double, 1> observed_;
@@ -483,7 +486,7 @@ TEST(ProbabilistTests, TestMaskingConditions)
evalhyd::evalp(
xt::eval(observed),
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::all())),
- metrics,
+ all_metrics_p,
thresholds,
"high",
masks,
@@ -495,19 +498,20 @@ TEST(ProbabilistTests, TestMaskingConditions)
evalhyd::evalp(
xt::eval(xt::where((observed < 2000) | (observed > 3000), observed, NAN)),
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::all())),
- metrics,
+ all_metrics_p,
thresholds,
"high"
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_p.size(); m++)
{
EXPECT_TRUE(
- xt::allclose(
- metrics_q_conditioned[m], metrics_q_preconditioned[m]
- )
- ) << "Failure for (" << metrics[m] << ")";
+ xt::sum(xt::isclose(metrics_q_conditioned[m],
+ metrics_q_preconditioned[m],
+ 1e-05, 1e-08, true))
+ == xt::xscalar<double>(metrics_q_conditioned[m].size())
+ ) << "Failure for (" << all_metrics_p[m] << ")";
}
// conditions on streamflow statistics _____________________________________
@@ -524,7 +528,7 @@ TEST(ProbabilistTests, TestMaskingConditions)
evalhyd::evalp(
xt::eval(observed),
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::all())),
- metrics,
+ all_metrics_p,
thresholds,
"high",
masks,
@@ -536,19 +540,20 @@ TEST(ProbabilistTests, TestMaskingConditions)
evalhyd::evalp(
xt::eval(xt::where(q_prd_mean >= median, observed, NAN)),
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::all())),
- metrics,
+ all_metrics_p,
thresholds,
"high"
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_p.size(); m++)
{
EXPECT_TRUE(
- xt::allclose(
- metrics_q_conditioned_[m], metrics_q_preconditioned_[m]
- )
- ) << "Failure for (" << metrics[m] << ")";
+ xt::sum(xt::isclose(metrics_q_conditioned_[m],
+ metrics_q_preconditioned_[m],
+ 1e-05, 1e-08, true))
+ == xt::xscalar<double>(metrics_q_conditioned_[m].size())
+ ) << "Failure for (" << all_metrics_p[m] << ")";
}
// conditions on temporal indices __________________________________________
@@ -562,7 +567,7 @@ TEST(ProbabilistTests, TestMaskingConditions)
evalhyd::evalp(
xt::eval(observed),
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::all())),
- metrics,
+ all_metrics_p,
thresholds,
"high",
masks,
@@ -574,19 +579,20 @@ TEST(ProbabilistTests, TestMaskingConditions)
evalhyd::evalp(
xt::eval(xt::view(observed_, xt::newaxis(), xt::range(0, 100))),
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::range(0, 100))),
- metrics,
+ all_metrics_p,
thresholds,
"high"
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_p.size(); m++)
{
EXPECT_TRUE(
- xt::allclose(
- metrics_t_conditioned[m], metrics_t_subset[m]
- )
- ) << "Failure for (" << metrics[m] << ")";
+ xt::sum(xt::isclose(metrics_t_conditioned[m],
+ metrics_t_subset[m],
+ 1e-05, 1e-08, true))
+ == xt::xscalar<double>(metrics_t_conditioned[m].size())
+ ) << "Failure for (" << all_metrics_p[m] << ")";
}
}
@@ -594,8 +600,6 @@ TEST(ProbabilistTests, TestMissingData)
{
xt::xtensor<double, 2> thresholds
{{ 4., 5. }};
- std::vector<std::string> metrics =
- {"BS", "BSS", "BS_CRD", "BS_LBD", "QS", "CRPS"};
// compute metrics on series with NaN
xt::xtensor<double, 4> forecast_nan {{
@@ -616,7 +620,7 @@ TEST(ProbabilistTests, TestMissingData)
evalhyd::evalp(
observed_nan,
forecast_nan,
- metrics,
+ all_metrics_p,
thresholds,
"high"
);
@@ -636,7 +640,7 @@ TEST(ProbabilistTests, TestMissingData)
evalhyd::evalp(
observed_pp1,
forecast_pp1,
- metrics,
+ all_metrics_p,
thresholds,
"high"
);
@@ -655,29 +659,29 @@ TEST(ProbabilistTests, TestMissingData)
evalhyd::evalp(
observed_pp2,
forecast_pp2,
- metrics,
+ all_metrics_p,
thresholds,
"high"
);
// check that numerical results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_p.size(); m++)
{
// for leadtime 1
EXPECT_TRUE(
- xt::allclose(
- xt::view(metrics_nan[m], xt::all(), 0),
- xt::view(metrics_pp1[m], xt::all(), 0)
- )
- ) << "Failure for (" << metrics[m] << ", " << "leadtime 1)";
+ xt::sum(xt::isclose(xt::view(metrics_nan[m], xt::all(), 0),
+ xt::view(metrics_pp1[m], xt::all(), 0),
+ 1e-05, 1e-08, true))
+ == xt::xscalar<double>(metrics_pp1[m].size())
+ ) << "Failure for (" << all_metrics_p[m] << ", " << "leadtime 1)";
// for leadtime 2
EXPECT_TRUE(
- xt::allclose(
- xt::view(metrics_nan[m], xt::all(), 1),
- xt::view(metrics_pp2[m], xt::all(), 0)
- )
- ) << "Failure for (" << metrics[m] << ", " << "leadtime 2)";
+ xt::sum(xt::isclose(xt::view(metrics_nan[m], xt::all(), 1),
+ xt::view(metrics_pp2[m], xt::all(), 0),
+ 1e-05, 1e-08, true))
+ == xt::xscalar<double>(metrics_pp2[m].size())
+ ) << "Failure for (" << all_metrics_p[m] << ", " << "leadtime 2)";
}
}
@@ -685,8 +689,6 @@ TEST(ProbabilistTests, TestBootstrap)
{
xt::xtensor<double, 2> thresholds
{{ 33.87, 55.67 }};
- std::vector<std::string> metrics =
- {"BS", "BSS", "BS_CRD", "BS_LBD", "QS", "CRPS"};
// read in data
std::ifstream ifs;
@@ -712,7 +714,7 @@ TEST(ProbabilistTests, TestBootstrap)
evalhyd::evalp(
xt::eval(xt::view(observed, xt::newaxis(), xt::all())),
xt::eval(xt::view(predicted, xt::newaxis(), xt::newaxis(), xt::all(), xt::all())),
- metrics,
+ all_metrics_p,
thresholds,
"high", // events
xt::xtensor<bool, 4>({}), // t_msk
@@ -736,18 +738,18 @@ TEST(ProbabilistTests, TestBootstrap)
evalhyd::evalp(
xt::eval(xt::view(observed_x3, xt::newaxis(), xt::all())),
xt::eval(xt::view(predicted_x3, xt::newaxis(), xt::newaxis(), xt::all(), xt::all())),
- metrics,
+ all_metrics_p,
thresholds,
"high"
);
// check results are identical
- for (std::size_t m = 0; m < metrics.size(); m++)
+ for (std::size_t m = 0; m < all_metrics_p.size(); m++)
{
EXPECT_TRUE(
xt::allclose(
metrics_bts[m], metrics_rep[m]
)
- ) << "Failure for (" << metrics[m] << ")";
+ ) << "Failure for (" << all_metrics_p[m] << ")";
}
}
\ No newline at end of file