Data commit

Task/Logistic-curve-fitting-in-epidemiology/Java/logistic-curve-fitting-in-epidemiology.java

@@ -0,0 +1,74 @@
+import java.util.List;
+import java.util.function.Function;
+
+public class LogisticCurveFitting {
+    private static final double K = 7.8e9;
+    private static final int N0 = 27;
+
+    private static final List<Double> ACTUAL = List.of(
+        27.0, 27.0, 27.0, 44.0, 44.0, 59.0, 59.0, 59.0, 59.0, 59.0, 59.0, 59.0, 59.0, 60.0, 60.0,
+        61.0, 61.0, 66.0, 83.0, 219.0, 239.0, 392.0, 534.0, 631.0, 897.0, 1350.0, 2023.0, 2820.0,
+        4587.0, 6067.0, 7823.0, 9826.0, 11946.0, 14554.0, 17372.0, 20615.0, 24522.0, 28273.0,
+        31491.0, 34933.0, 37552.0, 40540.0, 43105.0, 45177.0, 60328.0, 64543.0, 67103.0,
+        69265.0, 71332.0, 73327.0, 75191.0, 75723.0, 76719.0, 77804.0, 78812.0, 79339.0,
+        80132.0, 80995.0, 82101.0, 83365.0, 85203.0, 87024.0, 89068.0, 90664.0, 93077.0,
+        95316.0, 98172.0, 102133.0, 105824.0, 109695.0, 114232.0, 118610.0, 125497.0,
+        133852.0, 143227.0, 151367.0, 167418.0, 180096.0, 194836.0, 213150.0, 242364.0,
+        271106.0, 305117.0, 338133.0, 377918.0, 416845.0, 468049.0, 527767.0, 591704.0,
+        656866.0, 715353.0, 777796.0, 851308.0, 928436.0, 1000249.0, 1082054.0, 1174652.0
+    );
+
+    private static double f(double r) {
+        var sq = 0.0;
+        var len = ACTUAL.size();
+        for (int i = 0; i < len; i++) {
+            var eri = Math.exp(r * i);
+            var guess = (N0 * eri) / (1.0 + N0 * (eri - 1.0) / K);
+            var diff = guess - ACTUAL.get(i);
+            sq += diff * diff;
+        }
+        return sq;
+    }
+
+    private static double solve(Function<Double, Double> fn) {
+        return solve(fn, 0.5, 0.0);
+    }
+
+    private static double solve(Function<Double, Double> fn, double guess, double epsilon) {
+        double delta;
+        if (guess != 0.0) {
+            delta = guess;
+        } else {
+            delta = 1.0;
+        }
+
+        var f0 = fn.apply(guess);
+        var factor = 2.0;
+
+        while (delta > epsilon && guess != guess - delta) {
+            var nf = fn.apply(guess - delta);
+            if (nf < f0) {
+                f0 = nf;
+                guess -= delta;
+            } else {
+                nf = fn.apply(guess + delta);
+                if (nf < f0) {
+                    f0 = nf;
+                    guess += delta;
+                } else {
+                    factor = 0.5;
+                }
+            }
+
+            delta *= factor;
+        }
+
+        return guess;
+    }
+
+    public static void main(String[] args) {
+        var r = solve(LogisticCurveFitting::f);
+        var r0 = Math.exp(12.0 * r);
+        System.out.printf("r = %.16f, R0 = %.16f\n", r, r0);
+    }
+}