Feature/182 add statisticswellbeingjava to calculate statistics

src/main/java/simpaths/data/filters/AgeGenderCSfilter.java

@@ -0,0 +1,33 @@
+package simpaths.data.filters;
+
+import microsim.statistics.ICollectionFilter;
+import simpaths.model.Person;
+import simpaths.model.enums.Gender;
+
+public class AgeGenderCSfilter implements ICollectionFilter {
+
+    private final Gender gender;
+    private final int ageFrom;
+    private final int ageTo;
+    public AgeGenderCSfilter(int ageFrom, int ageTo) {
+        super();
+        this.ageFrom = ageFrom;
+        this.ageTo = ageTo;
+        this.gender = null;
+    }
+    public AgeGenderCSfilter(int ageFrom, int ageTo, Gender gender) {
+        super();
+        this.ageFrom = ageFrom;
+        this.ageTo = ageTo;
+        this.gender = gender;
+    }
+
+    @Override
+    public boolean isFiltered(Object object) {
+        Person person = (Person) object;
+        if (this.gender == null)
+            return ( (person.getDag() >= ageFrom) && (person.getDag() <= ageTo) );
+        else
+            return ( (person.getDag() >= ageFrom) && (person.getDag() <= ageTo) && (person.getDgn().equals(gender)));
+    }
+}

src/main/java/simpaths/data/statistics/HealthStatistics.java

@@ -0,0 +1,338 @@
+package simpaths.data.statistics;
+
+import jakarta.persistence.Column;
+import jakarta.persistence.Entity;
+import jakarta.persistence.Id;
+import jakarta.persistence.Transient;
+import microsim.data.db.PanelEntityKey;
+import microsim.statistics.CrossSection;
+import microsim.statistics.IDoubleSource;
+import microsim.statistics.functions.MeanArrayFunction;
+import microsim.statistics.functions.PercentileArrayFunction;
+import microsim.statistics.functions.SumArrayFunction;
+import simpaths.data.filters.AgeGenderCSfilter;
+import simpaths.model.Person;
+import simpaths.model.SimPathsModel;
+import simpaths.model.enums.Gender;
+
+@Entity
+public class HealthStatistics {
+
+    @Id
+    private PanelEntityKey key = new PanelEntityKey(1L);
+
+    @Column(name = "gender")
+    private String gender;
+
+    // mental health numeric
+    @Column(name = "dhm_mean")
+    private double dhm_mean;
+
+    @Column(name = "dhm_median")
+    private double dhm_median;
+
+    @Column(name = "dhm_p_10")
+    private double dhm_p_10;
+
+    @Column(name = "dhm_p_90")
+    private double dhm_p_90;
+
+    @Column(name = "dhm_p_25")
+    private double dhm_p_25;
+
+    @Column(name = "dhm_p_75")
+    private double dhm_p_75;
+
+    // MCS score numeric
+    @Column(name = "dhe_mcs_mean")
+    private double dhe_mcs_mean;
+
+    @Column(name = "dhe_mcs_median")
+    private double dhe_mcs_median;
+
+    @Column(name = "dhe_mcs_p_10")
+    private double dhe_mcs_p_10;
+
+    @Column(name = "dhe_mcs_p_90")
+    private double dhe_mcs_p_90;
+
+    @Column(name = "dhe_mcs_p_25")
+    private double dhe_mcs_p_25;
+
+    @Column(name = "dhe_mcs_p_75")
+    private double dhe_mcs_p_75;
+
+    // PCS score numeric
+    @Column(name = "dhe_pcs_mean")
+    private double dhe_pcs_mean;
+
+    @Column(name = "dhe_pcs_median")
+    private double dhe_pcs_median;
+
+    @Column(name = "dhe_pcs_p_10")
+    private double dhe_pcs_p_10;
+
+    @Column(name = "dhe_pcs_p_90")
+    private double dhe_pcs_p_90;
+
+    @Column(name = "dhe_pcs_p_25")
+    private double dhe_pcs_p_25;
+
+    @Column(name = "dhe_pcs_p_75")
+    private double dhe_pcs_p_75;
+
+    // Life Satisfaction numeric
+    @Column(name = "dls_mean")
+    private double dls_mean;
+
+    @Column(name = "dls_median")
+    private double dls_median;
+
+    @Column(name = "dls_p_10")
+    private double dls_p_10;
+
+    @Column(name = "dls_p_90")
+    private double dls_p_90;
+
+    @Column(name = "dls_p_25")
+    private double dls_p_25;
+
+    @Column(name = "dls_p_75")
+    private double dls_p_75;
+
+    @Column(name = "qualys")
+    private double qalys;
+
+    @Column(name = "wellbys")
+    private double wellbys;
+
+    //N
+    @Column(name = "N")
+    private int N;
+
+    @Transient
+    final static double WELLBEING_MEASURE_ADJUSTMENT = (double) 11 / 7;
+
+    public void setGender(String gender) {
+        this.gender = gender;
+    }
+
+    public void setDhm_mean(double dhm_mean) {
+        this.dhm_mean = dhm_mean;
+    }
+
+    public void setDhm_median(double dhm_median) {
+        this.dhm_median = dhm_median;
+    }
+
+    public void setDhm_p_10(double dhm_p_10) {
+        this.dhm_p_10 = dhm_p_10;
+    }
+
+    public void setDhm_p_90(double dhm_p_90) {
+        this.dhm_p_90 = dhm_p_90;
+    }
+
+    public void setDhm_p_25(double dhm_p_25) {
+        this.dhm_p_25 = dhm_p_25;
+    }
+
+    public void setDhm_p_75(double dhm_p_75) {
+        this.dhm_p_75 = dhm_p_75;
+    }
+
+    public void setDhe_mcs_mean(double dhe_mcs_mean) {
+        this.dhe_mcs_mean = dhe_mcs_mean;
+    }
+
+    public void setDhe_mcs_median(double dhe_mcs_median) {
+        this.dhe_mcs_median = dhe_mcs_median;
+    }
+
+    public void setDhe_mcs_p_10(double dhe_mcs_p_10) {
+        this.dhe_mcs_p_10 = dhe_mcs_p_10;
+    }
+
+    public void setDhe_mcs_p_90(double dhe_mcs_p_90) {
+        this.dhe_mcs_p_90 = dhe_mcs_p_90;
+    }
+
+    public void setDhe_mcs_p_25(double dhe_mcs_p_25) {
+        this.dhe_mcs_p_25 = dhe_mcs_p_25;
+    }
+
+    public void setDhe_mcs_p_75(double dhe_mcs_p_75) {
+        this.dhe_mcs_p_75 = dhe_mcs_p_75;
+    }
+
+    public void setDhe_pcs_mean(double dhe_pcs_mean) {
+        this.dhe_pcs_mean = dhe_pcs_mean;
+    }
+
+    public void setDhe_pcs_median(double dhe_pcs_median) {
+        this.dhe_pcs_median = dhe_pcs_median;
+    }
+
+    public void setDhe_pcs_p_10(double dhe_pcs_p_10) {
+        this.dhe_pcs_p_10 = dhe_pcs_p_10;
+    }
+
+    public void setDhe_pcs_p_90(double dhe_pcs_p_90) {
+        this.dhe_pcs_p_90 = dhe_pcs_p_90;
+    }
+
+    public void setDhe_pcs_p_25(double dhe_pcs_p_25) {
+        this.dhe_pcs_p_25 = dhe_pcs_p_25;
+    }
+
+    public void setDhe_pcs_p_75(double dhe_pcs_p_75) {
+        this.dhe_pcs_p_75 = dhe_pcs_p_75;
+    }
+
+    public void setDls_mean(double dls_mean) {
+        this.dls_mean = dls_mean;
+    }
+
+    public void setDls_median(double dls_median) {
+        this.dls_median = dls_median;
+    }
+
+    public void setDls_p_10(double dls_p_10) {
+        this.dls_p_10 = dls_p_10;
+    }
+
+    public void setDls_p_90(double dls_p_90) {
+        this.dls_p_90 = dls_p_90;
+    }
+
+    public void setDls_p_25(double dls_p_25) {
+        this.dls_p_25 = dls_p_25;
+    }
+
+    public void setDls_p_75(double dls_p_75) {
+        this.dls_p_75 = dls_p_75;
+    }
+
+    public void setN(int n) {
+        N = n;
+    }
+
+    public void setQalys(double qalys) {
+        this.qalys = qalys;
+    }
+
+    public void setWellbys(double wellbys) {
+        this.wellbys = wellbys;
+    }
+
+    public void update(SimPathsModel model, String gender_s) {
+
+
+        AgeGenderCSfilter ageGenderCSfilter;
+
+        if (gender_s.equals("Total")) {
+            ageGenderCSfilter = new AgeGenderCSfilter(18, 65);
+        } else {
+            ageGenderCSfilter = new AgeGenderCSfilter(18, 65, Gender.valueOf(gender_s));
+        }
+
+        // set gender
+        setGender(gender_s);
+
+        // dhm score
+        CrossSection.Double personsDhm = new CrossSection.Double(model.getPersons(), Person.DoublesVariables.Dhm); // Get cross section of simulated individuals and their mental health using the IDoubleSource interface implemented by Person class.
+        personsDhm.setFilter(ageGenderCSfilter);
+
+
+        MeanArrayFunction dhm_mean_f = new MeanArrayFunction(personsDhm); // Create MeanArrayFunction
+        dhm_mean_f.applyFunction();
+        setDhm_mean(dhm_mean_f.getDoubleValue(IDoubleSource.Variables.Default));
+
+        PercentileArrayFunction percDhm_f = new PercentileArrayFunction(personsDhm);
+        percDhm_f.applyFunction();
+
+        setDhm_p_10(percDhm_f.getDoubleValue(PercentileArrayFunction.Variables.P10));
+        setDhm_p_25(percDhm_f.getDoubleValue(PercentileArrayFunction.Variables.P25));
+        setDhm_median(percDhm_f.getDoubleValue(PercentileArrayFunction.Variables.P50));
+        setDhm_p_75(percDhm_f.getDoubleValue(PercentileArrayFunction.Variables.P75));
+        setDhm_p_90(percDhm_f.getDoubleValue(PercentileArrayFunction.Variables.P90));
+
+        // mcs score
+        CrossSection.Double personsMCS = new CrossSection.Double(model.getPersons(), Person.DoublesVariables.Dhe_mcs);
+        personsMCS.setFilter(ageGenderCSfilter);
+
+
+        MeanArrayFunction dhe_mcs_mean_f = new MeanArrayFunction(personsMCS); // Create MeanArrayFunction
+        dhe_mcs_mean_f.applyFunction();
+        setDhe_mcs_mean(dhe_mcs_mean_f.getDoubleValue(IDoubleSource.Variables.Default));
+
+        PercentileArrayFunction perc_dhe_mcs_f = new PercentileArrayFunction(personsMCS);
+        perc_dhe_mcs_f.applyFunction();
+
+        setDhe_mcs_p_10(perc_dhe_mcs_f.getDoubleValue(PercentileArrayFunction.Variables.P10));
+        setDhe_mcs_p_25(perc_dhe_mcs_f.getDoubleValue(PercentileArrayFunction.Variables.P25));
+        setDhe_mcs_median(perc_dhe_mcs_f.getDoubleValue(PercentileArrayFunction.Variables.P50));
+        setDhe_mcs_p_75(perc_dhe_mcs_f.getDoubleValue(PercentileArrayFunction.Variables.P75));
+        setDhe_mcs_p_90(perc_dhe_mcs_f.getDoubleValue(PercentileArrayFunction.Variables.P90));
+
+        // pcs score
+        CrossSection.Double personsPCS = new CrossSection.Double(model.getPersons(), Person.DoublesVariables.Dhe_pcs);
+        personsPCS.setFilter(ageGenderCSfilter);
+
+
+        MeanArrayFunction dhe_pcs_mean_f = new MeanArrayFunction(personsPCS); // Create MeanArrayFunction
+        dhe_pcs_mean_f.applyFunction();
+        setDhe_pcs_mean(dhe_pcs_mean_f.getDoubleValue(IDoubleSource.Variables.Default));
+
+        PercentileArrayFunction perc_dhe_pcs_f = new PercentileArrayFunction(personsPCS);
+        perc_dhe_pcs_f.applyFunction();
+
+        setDhe_pcs_p_10(perc_dhe_pcs_f.getDoubleValue(PercentileArrayFunction.Variables.P10));
+        setDhe_pcs_p_25(perc_dhe_pcs_f.getDoubleValue(PercentileArrayFunction.Variables.P25));
+        setDhe_pcs_median(perc_dhe_pcs_f.getDoubleValue(PercentileArrayFunction.Variables.P50));
+        setDhe_pcs_p_75(perc_dhe_pcs_f.getDoubleValue(PercentileArrayFunction.Variables.P75));
+        setDhe_pcs_p_90(perc_dhe_pcs_f.getDoubleValue(PercentileArrayFunction.Variables.P90));
+
+        // Life Satisfaction score
+        CrossSection.Double personsDls = new CrossSection.Double(model.getPersons(), Person.DoublesVariables.Dls);
+        personsDls.setFilter(ageGenderCSfilter);
+
+
+        MeanArrayFunction dls_mean_f = new MeanArrayFunction(personsDls); // Create MeanArrayFunction
+        dls_mean_f.applyFunction();
+        setDls_mean(dls_mean_f.getDoubleValue(IDoubleSource.Variables.Default));
+
+        PercentileArrayFunction perc_dls_f = new PercentileArrayFunction(personsDls);
+        perc_dls_f.applyFunction();
+
+        setDls_p_10(perc_dls_f.getDoubleValue(PercentileArrayFunction.Variables.P10));
+        setDls_p_25(perc_dls_f.getDoubleValue(PercentileArrayFunction.Variables.P25));
+        setDls_median(perc_dls_f.getDoubleValue(PercentileArrayFunction.Variables.P50));
+        setDls_p_75(perc_dls_f.getDoubleValue(PercentileArrayFunction.Variables.P75));
+        setDls_p_90(perc_dls_f.getDoubleValue(PercentileArrayFunction.Variables.P90));
+
+        // QALYS as sum of EQ5D
+        CrossSection.Double personEQ5D = new CrossSection.Double(model.getPersons(), Person.DoublesVariables.He_eq5d);
+        personEQ5D.setFilter(ageGenderCSfilter);
+
+        SumArrayFunction.Double qalys = new SumArrayFunction.Double(personEQ5D);
+        qalys.applyFunction();
+        setQalys(qalys.getDoubleValue(IDoubleSource.Variables.Default));
+
+        // WELLBYs as sum of 'points' in 0-10-scale life satisfaction (adjusted)
+
+        SumArrayFunction.Double wellbys = new SumArrayFunction.Double(personsDls);
+        wellbys.applyFunction();
+
+
+        setWellbys(wellbys.getDoubleValue(IDoubleSource.Variables.Default) * WELLBEING_MEASURE_ADJUSTMENT);
+
+        // count
+        CrossSection.Integer n_persons = new CrossSection.Integer(model.getPersons(), Person.class, "getPersonCount", true);
+        n_persons.setFilter(ageGenderCSfilter);
+
+        SumArrayFunction.Integer count_f = new SumArrayFunction.Integer(n_persons);
+        count_f.applyFunction();
+        setN(count_f.getIntValue(IDoubleSource.Variables.Default));
+    }
+}