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  • Thibault Hallouin's avatar
    refactor determinist Evaluator · b4abca9f
    Thibault Hallouin authored 
    including:
- extracting the element/intermediate/metric calculations from the
  `determinist::Evaluator` class
- introducing new getter methods in `determinist::Evaluator` class
  that handle the element/intermediate/metric inter-dependencies
  internally to the object
- removing external inter-dependencies handling from `evald`
    b4abca9f
utils.hpp 4.16 KiB
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#ifndef EVALHYD_UTILS_HPP
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#define EVALHYD_UTILS_HPP
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#include <unordered_map>
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#include <unordered_set>
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#include <vector>
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#include <stdexcept>
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#include <xtensor/xtensor.hpp>
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#include <xtensor/xrandom.hpp>
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namespace evalhyd
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{
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    namespace utils
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    {
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        /// Procedure to check that all elements in the list of metrics are
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        /// valid metrics.
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        ///
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        /// \param [in] requested_metrics:
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        ///     Vector of strings for the metric(s) to be computed.
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        /// \param [in] valid_metrics:
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        ///     Vector of strings for the metric(s) to can be computed.
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        inline void check_metrics (
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                const std::vector<std::string>& requested_metrics,
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                const std::vector<std::string>& valid_metrics
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        )
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        {
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            for (const auto& metric : requested_metrics)
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            {
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                if (std::find(valid_metrics.begin(), valid_metrics.end(), metric)
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                        == valid_metrics.end())
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                {
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                    throw std::runtime_error(
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                            "invalid evaluation metric: " + metric
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                    );
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                }
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            }
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        }
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        /// Procedure to check that all elements for a bootstrap experiment
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        /// are provided and valid.
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        ///
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        /// \param [in] bootstrap:
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        ///     Map of parameters for the bootstrap experiment.
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        inline void check_bootstrap (
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                const std::unordered_map<std::string, int>& bootstrap
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        )
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        {
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            // check n_samples
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            if (bootstrap.find("n_samples") == bootstrap.end())
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            {
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                throw std::runtime_error(
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                        "number of samples missing for bootstrap"
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                );
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            }
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            // check len_sample
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            if (bootstrap.find("len_sample") == bootstrap.end())
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            {
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                throw std::runtime_error(
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                        "length of sample missing for bootstrap"
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                );
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            }
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            // check summary
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            if (bootstrap.find("summary") == bootstrap.end())
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            {
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                throw std::runtime_error(
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                        "summary missing for bootstrap"
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                );
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            }
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            auto s = bootstrap.find("summary")->second;
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            // TODO: change upper bound when mean+stddev and quantiles implemented
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if ((s < 0) || (s > 0)) { throw std::runtime_error( "invalid value for bootstrap summary" ); } // set seed if (bootstrap.find("seed") == bootstrap.end()) { xt::random::seed(time(nullptr)); } else { xt::random::seed(bootstrap.find("seed")->second); } } namespace evalp { /// Procedure to check that optional parameters are provided /// as arguments when required metrics need them. /// /// \param [in] metrics: /// Vector of strings for the metric(s) to be computed. /// \param [in] thresholds: /// Array of thresholds for metrics based on exceedance events. inline void check_optionals ( const std::vector<std::string>& metrics, const xt::xtensor<double, 2>& thresholds ) { std::vector<std::string>threshold_metrics = {"BS", "BS_CRD", "BS_LBD", "BSS"}; for (const auto& metric : metrics) { if (std::find(threshold_metrics.begin(), threshold_metrics.end(), metric) != threshold_metrics.end()) { if (thresholds.size() < 1) { throw std::runtime_error( "missing thresholds *q_thr* required to " "compute " + metric ); } } } } } } } #endif //EVALHYD_UTILS_HPP