Replicate existing channels pattern for storing which stats to calc

src/HealthGPS/analysis_module.cpp

@@ -63,20 +63,9 @@ void AnalysisModule::initialise_vector(RuntimeContext &context) {
     // `factors` vector.
     size_t num_stats_to_calc = context.mapping().entries().size() - factors_to_calculate_.size();
 
-    // But we calculate the mean and standard deviation of each factor, so we need to multiply by 2
-    num_stats_to_calc *= 2;
-
-    // We also want to calculate the prevalence and incidence of each disease
-    num_stats_to_calc += 2 * context.diseases().size();
-
-    // We also want to keep the count, deaths, and emigrations
-    num_stats_to_calc += 3;
-
-    // We also want to calculate the normal, overweight, obese, and above weight prevalence
-    num_stats_to_calc += 4;
-
-    // Finally, we want to calculate the mean and standard deviation of YLL, YLD, and DALY
-    num_stats_to_calc += 6;
+    // And for each factor, we calculate the stats described in `stats_to_calculate_`, so we
+    // multiply the number of stats to calculate by the number of factors to calculate stats for.
+    num_stats_to_calc *= stats_to_calculate_.size();
 
     // The product of the number of bins for each factor can be used to calculate the size of the
     // `calculated_stats_` in the next step
@@ -573,6 +562,37 @@ void AnalysisModule::initialise_output_channels(RuntimeContext &context) {
     channels_.emplace_back("std_daly");
 }
 
+void AnalysisModule::initialise_stats_to_calc(RuntimeContext &context) {
+    if (!stats_to_calculate_.empty()) {
+        return;
+    }
+
+    stats_to_calculate_.push_back("count");
+    stats_to_calculate_.push_back("deaths");
+    stats_to_calculate_.push_back("emigrations");
+
+    for (const auto &factor : context.mapping().entries()) {
+        stats_to_calculate_.push_back("mean_" + factor.key().to_string());
+        stats_to_calculate_.push_back("std_" + factor.key().to_string());
+    }
+
+    for (const auto &disease : context.diseases()) {
+        stats_to_calculate_.push_back("prevalence_" + disease.code.to_string());
+        stats_to_calculate_.push_back("incidence_" + disease.code.to_string());
+    }
+
+    stats_to_calculate_.push_back("normal_weight");
+    stats_to_calculate_.push_back("over_weight");
+    stats_to_calculate_.push_back("obese_weight");
+    stats_to_calculate_.push_back("above_weight");
+    stats_to_calculate_.push_back("mean_yll");
+    stats_to_calculate_.push_back("std_yll");
+    stats_to_calculate_.push_back("mean_yld");
+    stats_to_calculate_.push_back("std_yld");
+    stats_to_calculate_.push_back("mean_daly");
+    stats_to_calculate_.push_back("std_daly");
+}
+
 std::unique_ptr<AnalysisModule> build_analysis_module(Repository &repository,
                                                       const ModelInput &config) {
     auto analysis_entity = repository.manager().get_disease_analysis(config.settings().country());

src/HealthGPS/analysis_module.h

@@ -46,6 +46,7 @@ class AnalysisModule final : public UpdatableModule {
     WeightModel weight_classifier_;
     DoubleAgeGenderTable residual_disability_weight_;
     std::vector<std::string> channels_;
+    std::vector<std::string> stats_to_calculate_;
     unsigned int comorbidities_;
     std::string name_{"Analysis"};
     std::vector<core::Identifier> factors_to_calculate_ = {"Gender"_id, "Age"_id};