add tests with 1D tensors for all deterministic metrics

tests/test_determinist.cpp

@@ -8,7 +8,8 @@
 
 #include "evalhyd/evald.hpp"
 
-TEST(DeterministTests, TestMetrics) {
+TEST(DeterministTests, TestMetrics2D)
+{
     // read in data
     std::ifstream ifs;
     ifs.open("./data/q_obs.csv");
@@ -21,7 +22,7 @@ TEST(DeterministTests, TestMetrics) {
     );
     ifs.close();
 
-    // compute scores (both with 2D and 1D tensors)
+    // compute scores (with 2D tensors)
     std::vector<xt::xarray<double>> metrics =
             evalhyd::evald<xt::xtensor<double, 2>>(
                     observed, predicted, {"RMSE", "NSE", "KGE", "KGEPRIME"}
@@ -61,48 +62,42 @@ TEST(DeterministTests, TestMetrics) {
     EXPECT_TRUE(xt::allclose(metrics[3], kgeprime));
 }
 
-TEST(DeterministTests, TestNSE_1d2d) {
+TEST(DeterministTests, TestMetrics1D)
+{
     // read in data
     std::ifstream ifs;
     ifs.open("./data/q_obs.csv");
-    xt::xtensor<double, 2> observed_2d =xt::load_csv<int>(ifs);
+    xt::xtensor<double, 1> observed = xt::squeeze(xt::load_csv<int>(ifs));
     ifs.close();
 
-    xt::xtensor<double, 1> observed_1d = xt::squeeze(observed_2d);
-
     ifs.open("./data/q_prd.csv");
-    xt::xtensor<double, 2> predicted_2d = xt::view(
-            xt::load_csv<double>(ifs), xt::range(0, 5), xt::all()
+    xt::xtensor<double, 1> predicted = xt::row(
+            xt::view(xt::load_csv<double>(ifs), xt::range(0, 5), xt::all()), 0
     );
     ifs.close();
 
-    xt::xtensor<double, 1> predicted_1d = xt::row(predicted_2d, 0);
-
-    // compute scores (both with 2D and 1D tensors)
-    std::vector<xt::xarray<double>> metrics_2d =
-            evalhyd::evald<xt::xtensor<double, 2>>(
-                    observed_2d, predicted_2d, {"NSE"}
-            );
-
-    std::vector<xt::xarray<double>> metrics_1d =
+    // compute scores (with 1D tensors)
+    std::vector<xt::xarray<double>> metrics =
             evalhyd::evald<xt::xtensor<double, 1>>(
-                    observed_1d, predicted_1d, {"NSE"}
+                    observed, predicted, {"RMSE", "NSE", "KGE", "KGEPRIME"}
             );
 
-    // check results (both with 2D and 1D tensors)
-    xt::xtensor<double, 2> nse =
-            {{0.71891219},
-             {0.7190249},
-             {0.71835777},
-             {0.71810361},
-             {0.71776748}};
-    EXPECT_TRUE(xt::allclose(metrics_2d[0], nse));
-
-    xt::xtensor<double, 1> nse_1d = {0.71891219};
-    EXPECT_TRUE(xt::allclose(metrics_1d[0], nse[0]));
+    // check results on all metrics
+    xt::xtensor<double, 1> rmse = {777.034272};
+    EXPECT_TRUE(xt::allclose(metrics[0], rmse));
+
+    xt::xtensor<double, 1> nse = {0.718912};
+    EXPECT_TRUE(xt::allclose(metrics[1], nse));
+
+    xt::xtensor<double, 1> kge = {0.748088};
+    EXPECT_TRUE(xt::allclose(metrics[2], kge));
+
+    xt::xtensor<double, 1> kgeprime = {0.813141};
+    EXPECT_TRUE(xt::allclose(metrics[3], kgeprime));
 }
 
-TEST(DeterministTests, TestNSE_transform) {
+TEST(DeterministTests, TestTransform)
+{
     // read in data
     std::ifstream ifs;
     ifs.open("./data/q_obs.csv");

tests/test_probabilist.cpp

@@ -9,7 +9,8 @@
 
 using namespace xt::placeholders;  // required for `_` to work
 
-TEST(ProbabilistTests, TestBrier) {
+TEST(ProbabilistTests, TestBrier)
+{
     // read in data
     std::ifstream ifs;
     ifs.open("./data/q_obs.csv");
@@ -59,7 +60,8 @@ TEST(ProbabilistTests, TestBrier) {
     EXPECT_TRUE(xt::allclose(metrics[3], bs_lbd));
 }
 
-TEST(ProbabilistTests, TestQuantiles) {
+TEST(ProbabilistTests, TestQuantiles)
+{
     // read in data
     std::ifstream ifs;
     ifs.open("./data/q_obs.csv");
@@ -103,10 +105,10 @@ TEST(ProbabilistTests, TestQuantiles) {
     xt::xtensor<double, 3> crps =
             {{{ 257.412129}}};
     EXPECT_TRUE(xt::allclose(metrics[1], crps));
-
 }
 
-TEST(ProbabilistTests, TestMasks) {
+TEST(ProbabilistTests, TestMasks)
+{
     // read in data
     std::ifstream ifs;
     ifs.open("./data/q_obs.csv");
@@ -155,5 +157,4 @@ TEST(ProbabilistTests, TestMasks) {
     {
         EXPECT_TRUE(xt::allclose(metrics_masked[0], metrics_subset[0]));
     }
-
 }
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