test_probabilist.cpp

#include <fstream>
#include <vector>
#include <tuple>
#include <array>
#include <gtest/gtest.h>
#include <xtensor/xtensor.hpp>
#include <xtensor/xview.hpp>
#include <xtensor/xsort.hpp>
#include <xtensor/xmanipulation.hpp>
#include <xtensor/xcsv.hpp>

#include "evalhyd/evalp.hpp"

#ifndef EVALHYD_DATA_DIR
#error "need to define data directory"
#endif

using namespace xt::placeholders;  // required for `_` to work

std::tuple<xt::xtensor<double, 1>, xt::xtensor<double, 2>> load_data_p()
{
    // read in data
    std::ifstream ifs;
    ifs.open(EVALHYD_DATA_DIR "/q_obs.csv");
    xt::xtensor<double, 1> observed = xt::squeeze(xt::load_csv<int>(ifs));
    ifs.close();

    ifs.open(EVALHYD_DATA_DIR "/q_prd.csv");
    xt::xtensor<double, 2> predicted = xt::load_csv<double>(ifs);
    ifs.close();

    return std::make_tuple(observed, predicted);
}

TEST(ProbabilistTests, TestBrier)
{
    // read in data
    xt::xtensor<double, 1> observed;
    xt::xtensor<double, 2> predicted;
    std::tie(observed, predicted) = load_data_p();

    // compute scores
    xt::xtensor<double, 2> thresholds = {{690, 534, 445, NAN}};

    std::vector<xt::xarray<double>> metrics =
            evalhyd::evalp<xt::xtensor<double, 2>, xt::xtensor<double, 4>, xt::xtensor<bool, 4>>(
                    // shape: (sites [1], time [t])
                    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())),
                    {"BS", "BSS", "BS_CRD", "BS_LBD"},
                    thresholds
            );

    // check results
    // Brier scores
    xt::xtensor<double, 5> bs =
            {{{{{0.10615136, 0.07395622, 0.08669186, NAN}}}}};
    EXPECT_TRUE(
            xt::sum(xt::isclose(metrics[0], bs, 1e-05, 1e-08, true))
            == xt::xscalar<double>(4)
    );

    // Brier skill scores
    xt::xtensor<double, 5> bss =
            {{{{{0.5705594, 0.6661165, 0.5635126, NAN}}}}};
    EXPECT_TRUE(
            xt::sum(xt::isclose(metrics[1], bss, 1e-05, 1e-08, true))
            == xt::xscalar<double>(4)
    );