Fix tabbing

apps/api/src/scripts/analyze.ts

@@ -1,87 +1,87 @@
 import {
-  type Levels,
-  DEFAULT_STANDARDS_DATA,
+    type Levels,
+    DEFAULT_STANDARDS_DATA,
 } from "@blade-and-brawn/calculator";
 import { Activity, clamp, Gender, range } from "@blade-and-brawn/calculator";
 import { levenbergMarquardt as LM } from "ml-levenberg-marquardt";
 
 for (const activity of Object.values(Activity)) {
-  const DATASET_MAX_LEVEL = 5;
-  const NEW_LEVEL_COUNT = 2;
-  const RATIO_CLAMP = 1.4;
+    const DATASET_MAX_LEVEL = 5;
+    const NEW_LEVEL_COUNT = 2;
+    const RATIO_CLAMP = 1.4;
 
-  function expDecayModel([A, B, C]: number[]) {
-    return (i: number) => A! * Math.exp(-B! * i) + C!;
-  }
-
-  for (const gender of Object.values(Gender)) {
-    const standardsByGender = DEFAULT_STANDARDS_DATA[activity].standards.filter(
-      (s) => s["metrics"].gender === gender,
-    );
-    const ages = [...new Set(standardsByGender.map((s) => s.metrics.age))];
-    for (const age of ages) {
-      const standards = standardsByGender.filter(
-        (s) => s.metrics.age === age,
-      );
-
-      const data = {
-        x: [] as number[],
-        y: [] as number[],
-      };
-
-      const isIncreasing =
-        standards[0]!.levels["2"]! > standards[0]!.levels["1"]!;
-
-      for (const i of range(DATASET_MAX_LEVEL).slice(0, -1)) {
-        const level = i + 1;
-        const progressionRatios: number[] = [];
-        for (const standard of standards) {
-          const curr = standard.levels[level]!;
-          const next = standard.levels[level]!;
-          progressionRatios.push(
-            isIncreasing ? next / curr : curr / next,
-          );
-        }
-
-        const sum = progressionRatios.reduce((p, c) => p + c, 0);
-        const progressionRatioAvg = sum / progressionRatios.length;
-
-        data.x.push(i);
-        data.y.push(progressionRatioAvg);
-      }
-
-      const fittedParams = LM(data, expDecayModel, {
-        initialValues: [0.4, 0.5, 1.1],
-        minValues: [0.0, 0.0, 1.02],
-        maxValues: [1.0, 2.0, 1.25],
-        maxIterations: 200,
-      });
-      const getDecayRatio = (i: number) =>
-        clamp(
-          expDecayModel(fittedParams.parameterValues)(i),
-          1,
-          RATIO_CLAMP,
-        );
-
-      // UPDATE THE DATA
-      for (const standard of standards) {
-        const newLevels: Levels = {};
-
-        let prev = standard.levels["1"]!;
-        for (const i of range(NEW_LEVEL_COUNT)) {
-          const level = i + 1;
-          const ratio = getDecayRatio(level - NEW_LEVEL_COUNT);
-          prev = isIncreasing ? prev / ratio : prev * ratio;
-          newLevels[level] = Math.round(prev);
-        }
-
-        const oldLevels = standard.levels as Levels;
-        for (const i of range(DATASET_MAX_LEVEL)) {
-          const level = i + 1;
-          newLevels[level + NEW_LEVEL_COUNT] = oldLevels[level]!;
-        }
-        standard.levels = newLevels;
-      }
+    function expDecayModel([A, B, C]: number[]) {
+        return (i: number) => A! * Math.exp(-B! * i) + C!;
+    }
+
+    for (const gender of Object.values(Gender)) {
+        const standardsByGender = DEFAULT_STANDARDS_DATA[
+            activity
+        ].standards.filter((s) => s["metrics"].gender === gender);
+        const ages = [...new Set(standardsByGender.map((s) => s.metrics.age))];
+        for (const age of ages) {
+            const standards = standardsByGender.filter(
+                (s) => s.metrics.age === age,
+            );
+
+            const data = {
+                x: [] as number[],
+                y: [] as number[],
+            };
+
+            const isIncreasing =
+                standards[0]!.levels["2"]! > standards[0]!.levels["1"]!;
+
+            for (const i of range(DATASET_MAX_LEVEL).slice(0, -1)) {
+                const level = i + 1;
+                const progressionRatios: number[] = [];
+                for (const standard of standards) {
+                    const curr = standard.levels[level]!;
+                    const next = standard.levels[level]!;
+                    progressionRatios.push(
+                        isIncreasing ? next / curr : curr / next,
+                    );
+                }
+
+                const sum = progressionRatios.reduce((p, c) => p + c, 0);
+                const progressionRatioAvg = sum / progressionRatios.length;
+
+                data.x.push(i);
+                data.y.push(progressionRatioAvg);
+            }
+
+            const fittedParams = LM(data, expDecayModel, {
+                initialValues: [0.4, 0.5, 1.1],
+                minValues: [0.0, 0.0, 1.02],
+                maxValues: [1.0, 2.0, 1.25],
+                maxIterations: 200,
+            });
+            const getDecayRatio = (i: number) =>
+                clamp(
+                    expDecayModel(fittedParams.parameterValues)(i),
+                    1,
+                    RATIO_CLAMP,
+                );
+
+            // UPDATE THE DATA
+            for (const standard of standards) {
+                const newLevels: Levels = {};
+
+                let prev = standard.levels["1"]!;
+                for (const i of range(NEW_LEVEL_COUNT)) {
+                    const level = i + 1;
+                    const ratio = getDecayRatio(level - NEW_LEVEL_COUNT);
+                    prev = isIncreasing ? prev / ratio : prev * ratio;
+                    newLevels[level] = Math.round(prev);
+                }
+
+                const oldLevels = standard.levels as Levels;
+                for (const i of range(DATASET_MAX_LEVEL)) {
+                    const level = i + 1;
+                    newLevels[level + NEW_LEVEL_COUNT] = oldLevels[level]!;
+                }
+                standard.levels = newLevels;
+            }
+        }
     }
-  }
 }