transpose data in input files

So that the files for the tests look like typical files `evalhyd` would
expect, rather than its transposed version.

tests/data/q_obs.csv

-2520
-2270
-2130
-1950
-1820
-1680
-1590
-1560
-1570
-1450
-1410
-1370
-1350
-1280
-1230
-1290
-1320
-1210
-1160
-1120
-1130
-1120
-1100
-1070
-1050
-1060
-1590
-2280
-2300
-2480
-2250
-2800
-3490
-9270
-7180
-4210
-3160
-2600
-2260
-2630
-5160
-5430
-4420
-8780
-5270
-3890
-3840
-4120
-3410
-2840
-2530
-2200
-1960
-1810
-1820
-2470
-2980
-3710
-3160
-4330
-3760
-4300
-3200
-9720
-10200
-5410
-3980
-4560
-4290
-3560
-3140
-2860
-2530
-2300
-2120
-1890
-1770
-1690
-1620
-1550
-1490
-1380
-1320
-1290
-1270
-1230
-1200
-1210
-1430
-1220
-1200
-1250
-1200
-1100
-1080
-1060
-1030
-1000
-977
-965
-944
-924
-910
-873
-829
-805
-776
-753
-735
-728
-706
-689
-661
-638
-635
-629
-639
-725
-712
-870
-856
-1120
-886
-722
-738
-997
-723
-642
-610
-593
-1930
-1740
-1470
-3100
-1740
-1190
-949
-798
-725
-653
-618
-590
-3210
-2120
-1080
-864
-749
-660
-608
-585
-563
-538
-504
-494
-1070
-717
-660
-803
-654
-666
-796
-899
-843
-698
-1040
-681
-804
-2810
-1630
-1360
-1000
-768
-631
-595
-548
-498
-523
-604
-568
-691
-509
-459
-564
-468
-421
-414
-406
-398
-385
-350
-329
-322
-332
-322
-302
-315
-378
-420
-374
-309
-262
-236
-234
-230
-215
-218
-206
-202
-200
-199
-196
-193
-207
-651
-529
-466
-347
-279
-252
-226
-205
-179
-192
-200
-215
-236
-281
-217
-340
-314
-282
-228
-195
-192
-199
-186
-177
-161
-157
-395
-509
-1020
-704
-394
-354
-299
-268
-245
-258
-277
-255
-241
-225
-223
-229
-227
-224
-220
-218
-228
-241
-242
-257
-249
-261
-309
-495
-675
-416
-398
-360
-729
-491
-402
-467
-1200
-622
-424
-420
-552
-447
-374
-657
-588
-593
-480
-419
-409
-723
-731
-744
-565
-503
-468
-455
-1270
-1730
-967
-2290
-1790
-1090
-946
-791
-734
-719
-681
-758
-934
-814
-737
-707
+2520,2270,2130,1950,1820,1680,1590,1560,1570,1450,1410,1370,1350,1280,1230,1290,1320,1210,1160,1120,1130,1120,1100,1070,1050,1060,1590,2280,2300,2480,2250,2800,3490,9270,7180,4210,3160,2600,2260,2630,5160,5430,4420,8780,5270,3890,3840,4120,3410,2840,2530,2200,1960,1810,1820,2470,2980,3710,3160,4330,3760,4300,3200,9720,10200,5410,3980,4560,4290,3560,3140,2860,2530,2300,2120,1890,1770,1690,1620,1550,1490,1380,1320,1290,1270,1230,1200,1210,1430,1220,1200,1250,1200,1100,1080,1060,1030,1000,977,965,944,924,910,873,829,805,776,753,735,728,706,689,661,638,635,629,639,725,712,870,856,1120,886,722,738,997,723,642,610,593,1930,1740,1470,3100,1740,1190,949,798,725,653,618,590,3210,2120,1080,864,749,660,608,585,563,538,504,494,1070,717,660,803,654,666,796,899,843,698,1040,681,804,2810,1630,1360,1000,768,631,595,548,498,523,604,568,691,509,459,564,468,421,414,406,398,385,350,329,322,332,322,302,315,378,420,374,309,262,236,234,230,215,218,206,202,200,199,196,193,207,651,529,466,347,279,252,226,205,179,192,200,215,236,281,217,340,314,282,228,195,192,199,186,177,161,157,395,509,1020,704,394,354,299,268,245,258,277,255,241,225,223,229,227,224,220,218,228,241,242,257,249,261,309,495,675,416,398,360,729,491,402,467,1200,622,424,420,552,447,374,657,588,593,480,419,409,723,731,744,565,503,468,455,1270,1730,967,2290,1790,1090,946,791,734,719,681,758,934,814,737,707

tests/test_determinist.cpp

@@ -13,14 +13,14 @@ TEST(DeterministTests, TestNSE) {
     // read in data
     std::ifstream ifs;
     ifs.open("./data/q_obs.csv");
-    xt::xtensor<double, 2> observed_2d = xt::transpose(xt::load_csv<int>(ifs));
+    xt::xtensor<double, 2> observed_2d =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::transpose(xt::load_csv<double>(ifs)), xt::range(0, 5), xt::all()
+            xt::load_csv<double>(ifs), xt::range(0, 5), xt::all()
     );
     ifs.close();
 

tests/test_probabilist.cpp

@@ -24,8 +24,7 @@ TEST(ProbabilistTests, TestBrier) {
 
     std::vector<xt::xtensor<double, 2>> metrics =
             evalhyd::evalp(
-                    xt::transpose(observed), xt::transpose(predicted),
-                    {"BS", "BSS", "BS_CRD", "BS_LBD"},
+                    observed, predicted, {"BS", "BSS", "BS_CRD", "BS_LBD"},
                     thresholds
             );