refilc-plus/lib/ui/mobile/goal_planner/goal_planner.dart
2024-10-03 18:47:25 +02:00

191 lines
5.2 KiB
Dart

/*
* Maintainer: DarK
* Translated from C version
* Minimal Working Fixed @ 2022.12.25
* ##Please do NOT modify if you don't know whats going on##
*
* Issue: #59
*
* Future changes / ideas:
* - `best` should be configurable
*/
import 'dart:math';
import 'package:refilc_kreta_api/models/category.dart';
import 'package:refilc_kreta_api/models/grade.dart';
import 'package:refilc_kreta_api/models/subject.dart';
import 'package:refilc_kreta_api/models/teacher.dart';
import 'package:flutter/foundation.dart' show listEquals;
/// Generate list of grades that achieve the wanted goal.
/// After generating possible options, it (when doing so would NOT result in empty list) filters with two criteria:
/// - Plan should not contain more than 15 grades
/// - Plan should not contain only one type of grade
///
/// **Usage**:
///
/// ```dart
/// List<int> GoalPlanner(double goal, List<Grade> grades).solve().plan
/// ```
class GoalPlanner {
final double goal;
final List<Grade> grades;
List<Plan> plans = [];
GoalPlanner(this.goal, this.grades);
bool _allowed(int grade) => grade > goal;
void _generate(Generator g) {
// Exit condition 1: Generator has working plan.
if (g.currentAvg.avg >= goal) {
plans.add(Plan(g.plan));
return;
}
// Exit condition 2: Generator plan will never work.
if (!_allowed(g.gradeToAdd)) {
return;
}
for (int i = g.max; i >= 0; i--) {
int newGradeToAdd = g.gradeToAdd - 1;
List<int> newPlan =
GoalPlannerHelper._addToList<int>(g.plan, g.gradeToAdd, i);
Avg newAvg = GoalPlannerHelper._addToAvg(g.currentAvg, g.gradeToAdd, i);
int newN = GoalPlannerHelper.howManyNeeded(
newGradeToAdd,
grades +
newPlan
.map((e) => Grade(
id: '',
date: DateTime(0),
value: GradeValue(e, '', '', 100),
teacher: Teacher.fromString(''),
description: '',
form: '',
groupId: '',
type: GradeType.midYear,
subject: GradeSubject.fromJson({}),
mode: Category.fromJson({}),
seenDate: DateTime(0),
writeDate: DateTime(0),
))
.toList(),
goal);
_generate(Generator(newGradeToAdd, newN, newAvg, newPlan));
}
}
List<Plan> solve() {
_generate(
Generator(
5,
GoalPlannerHelper.howManyNeeded(
5,
grades,
goal,
),
Avg(GoalPlannerHelper.averageEvals(grades),
GoalPlannerHelper.weightSum(grades)),
[],
),
);
// Calculate Statistics
for (var e in plans) {
e.sum = e.plan.fold(0, (int a, b) => a + b);
e.avg = e.sum / e.plan.length;
e.sigma = sqrt(
e.plan.map((i) => pow(i - e.avg, 2)).fold(0, (num a, b) => a + b) /
e.plan.length);
}
// filter without aggression
if (plans.where((e) => e.plan.length < 30).isNotEmpty) {
plans.removeWhere((e) => !(e.plan.length < 30));
}
if (plans.where((e) => e.sigma > 1).isNotEmpty) {
plans.removeWhere((e) => !(e.sigma > 1));
}
return plans;
}
}
class Avg {
final double avg;
final double n;
Avg(this.avg, this.n);
}
class Generator {
final int gradeToAdd;
final int max;
final Avg currentAvg;
final List<int> plan;
Generator(this.gradeToAdd, this.max, this.currentAvg, this.plan);
}
class Plan {
final List<int> plan;
int sum = 0;
double avg = 0;
int med = 0; // currently
int mod = 0; // unused
double sigma = 0;
Plan(this.plan);
String get dbString {
var finalString = '';
for (var i in plan) {
finalString += "$i,";
}
return finalString;
}
@override
bool operator ==(other) => other is Plan && listEquals(plan, other.plan);
@override
int get hashCode => Object.hashAll(plan);
}
class GoalPlannerHelper {
static Avg _addToAvg(Avg base, int grade, int n) =>
Avg((base.avg * base.n + grade * n) / (base.n + n), base.n + n);
static List<T> _addToList<T>(List<T> l, T e, int n) {
if (n == 0) return l;
List<T> tmp = l;
for (int i = 0; i < n; i++) {
tmp = tmp + [e];
}
return tmp;
}
static int howManyNeeded(int grade, List<Grade> base, double goal) {
double avg = averageEvals(base);
double wsum = weightSum(base);
if (avg >= goal) return 0;
if (grade * 1.0 == goal) return -1;
int candidate = (wsum * (avg - goal) / (goal - grade)).floor();
return (candidate * grade + avg * wsum) / (candidate + wsum) < goal
? candidate + 1
: candidate;
}
static double averageEvals(List<Grade> grades, {bool finalAvg = false}) {
double average = grades
.map((e) => e.value.value * e.value.weight / 100.0)
.fold(0.0, (double a, double b) => a + b) /
weightSum(grades, finalAvg: finalAvg);
return average.isNaN ? 0.0 : average;
}
static double weightSum(List<Grade> grades, {bool finalAvg = false}) => grades
.map((e) => finalAvg ? 1 : e.value.weight / 100)
.fold(0, (a, b) => a + b);
}