Load and use trend lambda param.

imperialCHEPI · Aug 21, 2024 · 92aadd9 · 92aadd9
1 parent 34b3be2
commit 92aadd9
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Showing 3 changed files with 29 additions and 14 deletions.
diff --git a/src/HealthGPS.Input/model_parser.cpp b/src/HealthGPS.Input/model_parser.cpp
@@ -187,6 +187,7 @@ load_staticlinear_risk_model_definition(const nlohmann::json &opt, const Configu
     std::vector<core::DoubleInterval> policy_ranges;
     auto trend_models = std::make_unique<std::vector<LinearModelParams>>();
     auto trend_ranges = std::make_unique<std::vector<core::DoubleInterval>>();
+    auto trend_lambda = std::make_unique<std::vector<double>>();
     auto expected_trend = std::make_unique<std::unordered_map<core::Identifier, double>>();
     auto expected_trend_boxcox = std::make_unique<std::unordered_map<core::Identifier, double>>();
 
@@ -255,6 +256,7 @@ load_staticlinear_risk_model_definition(const nlohmann::json &opt, const Configu
         // Write time trend data structures.
         trend_models->emplace_back(std::move(trend_model));
         trend_ranges->emplace_back(trend_json_params["Range"].get<core::DoubleInterval>());
+        trend_lambda->emplace_back(trend_json_params["Lambda"].get<double>());
 
         // Load expected value trends.
         (*expected_trend)[key] = json_params["ExpectedTrend"].get<double>();
@@ -348,8 +350,9 @@ load_staticlinear_risk_model_definition(const nlohmann::json &opt, const Configu
         std::move(expected), std::move(expected_trend), std::move(expected_trend_boxcox),
         std::move(names), std::move(models), std::move(ranges), std::move(lambda),
         std::move(stddev), std::move(cholesky), std::move(policy_models), std::move(policy_ranges),
-        std::move(policy_cholesky), std::move(trend_models), std::move(trend_ranges), info_speed,
-        std::move(rural_prevalence), std::move(income_models), physical_activity_stddev);
+        std::move(policy_cholesky), std::move(trend_models), std::move(trend_ranges),
+        std::move(trend_lambda), info_speed, std::move(rural_prevalence), std::move(income_models),
+        physical_activity_stddev);
 }
 
 std::unique_ptr<hgps::RiskFactorModelDefinition>

diff --git a/src/HealthGPS/static_linear_model.cpp b/src/HealthGPS/static_linear_model.cpp
@@ -17,7 +17,8 @@ StaticLinearModel::StaticLinearModel(
     const std::vector<LinearModelParams> &policy_models,
     const std::vector<core::DoubleInterval> &policy_ranges, const Eigen::MatrixXd &policy_cholesky,
     std::shared_ptr<std::vector<LinearModelParams>> trend_models,
-    std::shared_ptr<std::vector<core::DoubleInterval>> trend_ranges, double info_speed,
+    std::shared_ptr<std::vector<core::DoubleInterval>> trend_ranges,
+    std::shared_ptr<std::vector<double>> trend_lambda, double info_speed,
     const std::unordered_map<core::Identifier, std::unordered_map<core::Gender, double>>
         &rural_prevalence,
     const std::unordered_map<core::Income, LinearModelParams> &income_models,
@@ -27,8 +28,8 @@ StaticLinearModel::StaticLinearModel(
       ranges_{ranges}, lambda_{lambda}, stddev_{stddev}, cholesky_{cholesky},
       policy_models_{policy_models}, policy_ranges_{policy_ranges},
       policy_cholesky_{policy_cholesky}, trend_models_{std::move(trend_models)},
-      trend_ranges_{std::move(trend_ranges)}, info_speed_{info_speed},
-      rural_prevalence_{rural_prevalence}, income_models_{income_models},
+      trend_ranges_{std::move(trend_ranges)}, trend_lambda_{std::move(trend_lambda)},
+      info_speed_{info_speed}, rural_prevalence_{rural_prevalence}, income_models_{income_models},
       physical_activity_stddev_{physical_activity_stddev} {}
 
 RiskFactorModelType StaticLinearModel::type() const noexcept { return RiskFactorModelType::Static; }
@@ -210,9 +211,8 @@ void StaticLinearModel::update_trends(RuntimeContext &context, Person &person) c
         // Load trend and apply inverse BoxCox transform.
         auto trend_name = core::Identifier{names_[i].to_string() + "_trend"};
         double trend = person.risk_factors.at(trend_name);
-        // TODO: use trend_lambda_[i] below
-        // double boxcox_factor = pow(expected_trend_boxcox_->at(names_[i]), elapsed_time);
-        // trend = boxcox_factor * inverse_box_cox(trend, trend_lambda_[i]);
+        double boxcox_factor = pow(expected_trend_boxcox_->at(names_[i]), elapsed_time);
+        trend = boxcox_factor * inverse_box_cox(trend, (*trend_lambda_)[i]);
 
         // Apply trend to risk factor.
         double factor = person.risk_factors.at(names_[i]);
@@ -435,7 +435,8 @@ StaticLinearModelDefinition::StaticLinearModelDefinition(
     std::vector<double> stddev, Eigen::MatrixXd cholesky,
     std::vector<LinearModelParams> policy_models, std::vector<core::DoubleInterval> policy_ranges,
     Eigen::MatrixXd policy_cholesky, std::unique_ptr<std::vector<LinearModelParams>> trend_models,
-    std::unique_ptr<std::vector<core::DoubleInterval>> trend_ranges, double info_speed,
+    std::unique_ptr<std::vector<core::DoubleInterval>> trend_ranges,
+    std::unique_ptr<std::vector<double>> trend_lambda, double info_speed,
     std::unordered_map<core::Identifier, std::unordered_map<core::Gender, double>> rural_prevalence,
     std::unordered_map<core::Income, LinearModelParams> income_models,
     double physical_activity_stddev)
@@ -445,8 +446,9 @@ StaticLinearModelDefinition::StaticLinearModelDefinition(
       stddev_{std::move(stddev)}, cholesky_{std::move(cholesky)},
       policy_models_{std::move(policy_models)}, policy_ranges_{std::move(policy_ranges)},
       policy_cholesky_{std::move(policy_cholesky)}, trend_models_{std::move(trend_models)},
-      trend_ranges_{std::move(trend_ranges)}, info_speed_{info_speed},
-      rural_prevalence_{std::move(rural_prevalence)}, income_models_{std::move(income_models)},
+      trend_ranges_{std::move(trend_ranges)}, trend_lambda_{std::move(trend_lambda)},
+      info_speed_{info_speed}, rural_prevalence_{std::move(rural_prevalence)},
+      income_models_{std::move(income_models)},
       physical_activity_stddev_{physical_activity_stddev} {
 
     if (names_.empty()) {
@@ -482,6 +484,9 @@ StaticLinearModelDefinition::StaticLinearModelDefinition(
     if (trend_ranges_->empty()) {
         throw core::HgpsException("Time trend ranges list is empty");
     }
+    if (trend_lambda_->empty()) {
+        throw core::HgpsException("Time trend lambda list is empty");
+    }
     if (rural_prevalence_.empty()) {
         throw core::HgpsException("Rural prevalence mapping is empty");
     }
@@ -502,7 +507,8 @@ std::unique_ptr<RiskFactorModel> StaticLinearModelDefinition::create_model() con
     return std::make_unique<StaticLinearModel>(
         expected_, expected_trend_, expected_trend_boxcox_, names_, models_, ranges_, lambda_,
         stddev_, cholesky_, policy_models_, policy_ranges_, policy_cholesky_, trend_models_,
-        trend_ranges_, info_speed_, rural_prevalence_, income_models_, physical_activity_stddev_);
+        trend_ranges_, trend_lambda_, info_speed_, rural_prevalence_, income_models_,
+        physical_activity_stddev_);
 }
 
 } // namespace hgps
diff --git a/src/HealthGPS/static_linear_model.h b/src/HealthGPS/static_linear_model.h
@@ -36,6 +36,7 @@ class StaticLinearModel final : public RiskFactorAdjustableModel {
     /// @param policy_cholesky Cholesky decomposition of the intervention policy covariance matrix
     /// @param trend_models The linear models used to compute a person's risk factor trends
     /// @param trend_ranges The value range of each risk factor trend
+    /// @param trend_lambda The lambda values of the risk factor trends
     /// @param info_speed The information speed of risk factor updates
     /// @param rural_prevalence Rural sector prevalence for age groups and sex
     /// @param income_models The income models for each income category
@@ -52,7 +53,8 @@ class StaticLinearModel final : public RiskFactorAdjustableModel {
         const std::vector<core::DoubleInterval> &policy_ranges,
         const Eigen::MatrixXd &policy_cholesky,
         std::shared_ptr<std::vector<LinearModelParams>> trend_models,
-        std::shared_ptr<std::vector<core::DoubleInterval>> trend_ranges, double info_speed,
+        std::shared_ptr<std::vector<core::DoubleInterval>> trend_ranges,
+        std::shared_ptr<std::vector<double>> trend_lambda, double info_speed,
         const std::unordered_map<core::Identifier, std::unordered_map<core::Gender, double>>
             &rural_prevalence,
         const std::unordered_map<core::Income, LinearModelParams> &income_models,
@@ -126,6 +128,7 @@ class StaticLinearModel final : public RiskFactorAdjustableModel {
     const Eigen::MatrixXd &policy_cholesky_;
     std::shared_ptr<std::vector<LinearModelParams>> trend_models_;
     std::shared_ptr<std::vector<core::DoubleInterval>> trend_ranges_;
+    std::shared_ptr<std::vector<double>> trend_lambda_;
     const double info_speed_;
     const std::unordered_map<core::Identifier, std::unordered_map<core::Gender, double>>
         &rural_prevalence_;
@@ -151,6 +154,7 @@ class StaticLinearModelDefinition : public RiskFactorAdjustableModelDefinition {
     /// @param policy_cholesky Cholesky decomposition of the intervention policy covariance matrix
     /// @param trend_models The linear models used to compute a person's risk factor trends
     /// @param trend_ranges The value range of each risk factor trend
+    /// @param trend_lambda The lambda values of the risk factor trends
     /// @param info_speed The information speed of risk factor updates
     /// @param rural_prevalence Rural sector prevalence for age groups and sex
     /// @param income_models The income models for each income category
@@ -166,7 +170,8 @@ class StaticLinearModelDefinition : public RiskFactorAdjustableModelDefinition {
         std::vector<LinearModelParams> policy_models,
         std::vector<core::DoubleInterval> policy_ranges, Eigen::MatrixXd policy_cholesky,
         std::unique_ptr<std::vector<LinearModelParams>> trend_models,
-        std::unique_ptr<std::vector<core::DoubleInterval>> trend_ranges, double info_speed,
+        std::unique_ptr<std::vector<core::DoubleInterval>> trend_ranges,
+        std::unique_ptr<std::vector<double>> trend_lambda, double info_speed,
         std::unordered_map<core::Identifier, std::unordered_map<core::Gender, double>>
             rural_prevalence,
         std::unordered_map<core::Income, LinearModelParams> income_models,
@@ -189,6 +194,7 @@ class StaticLinearModelDefinition : public RiskFactorAdjustableModelDefinition {
     Eigen::MatrixXd policy_cholesky_;
     std::shared_ptr<std::vector<LinearModelParams>> trend_models_;
     std::shared_ptr<std::vector<core::DoubleInterval>> trend_ranges_;
+    std::shared_ptr<std::vector<double>> trend_lambda_;
     double info_speed_;
     std::unordered_map<core::Identifier, std::unordered_map<core::Gender, double>>
         rural_prevalence_;