Optimize Loading times
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Sewmina
182
lib/Analytics.dart
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182
lib/Analytics.dart
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import 'package:flutter/material.dart';
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import 'package:font_awesome_flutter/font_awesome_flutter.dart';
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import 'package:intl/intl.dart';
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import 'package:tasktracker/AvgDay.dart';
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import 'package:tasktracker/main.dart';
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import 'Data.dart';
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import 'DebugHelper.dart';
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import 'User.dart' as User;
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class AnalyticsPage extends StatefulWidget {
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const AnalyticsPage({Key? key}) : super(key: key);
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@override
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State<AnalyticsPage> createState() => _AnalyticsPageState();
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}
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class _AnalyticsPageState extends State<AnalyticsPage> {
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@override
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Widget build(BuildContext context) {
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// for (var value in avgActs) {
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// Debug.LogResponse('${value.taskType.name} : ${DateFormat('HH:mm').format(value.startTime)} - ${DateFormat('HH:mm').format(value.endTime)}');
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// }
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return Scaffold(
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appBar: AppBar(title: Row(
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children: [FaIcon(FontAwesomeIcons.chartLine),SizedBox(width: 15,), Text("Analytics")],
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)),
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drawer: navDrawer(context, 1),
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body: Container(
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padding: EdgeInsets.all(8),
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child:Column(
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children: [
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Card(
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child: Container(
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padding: EdgeInsets.symmetric(horizontal: 15, vertical: 5),
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child: Column(
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children: [
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Row(
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mainAxisAlignment: MainAxisAlignment.spaceBetween,
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children: [
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Text('Average Day',style: TextStyle(fontSize: 17)),
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MaterialButton(
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color: Colors.green,
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onPressed: (){
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Navigator.of(context).push(MaterialPageRoute(builder: (context)=> AvgDayPage()));
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},
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child: Text('More...'),
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)
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],
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),
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Divider(),
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],
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),
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)
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)
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],
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)
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)
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);
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}
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}
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class AnalyticTools{
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static double dailyThreshold = 0.9;
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static int activityGroupingThreshold = 4;
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static List<Activity> getAverageDayActs(DateTimeRange range){
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int totalDays = range.end.difference(range.start).inDays;
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Map<TaskType, List<AvgActData>> avgActs = <TaskType, List<AvgActData>>{};
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Map<TaskType, List<DateTimeRange>> acts = <TaskType, List<DateTimeRange>>{};
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List<Activity> listToReturn = [];
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//PASS 1: Split Activities and mark their time range
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User.activities.forEach((element) {
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if(element.startTime.isAfter(range.start) && element.endTime.isBefore(range.end)){
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//Eligible activity to calculate
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if(acts.containsKey(element.taskType)){
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acts[element.taskType]!.add(DateTimeRange(start: element.startTime, end: element.endTime));
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}else{
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acts.putIfAbsent(element.taskType, () => [DateTimeRange(start: element.startTime, end: element.endTime)]);
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}
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}
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});
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Debug.Log('Analysing ${acts.length} activities');
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//PASS 2: Calculate avg Time Range for each Activity
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acts.forEach((key, value) {
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if(value.length < totalDays * dailyThreshold){
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//Not a frequent Activity,
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}else{
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//Iterate through the time ranges of this activity
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for (var _actTime in value) {
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DateTime _start = DateTime(0,0,0,_actTime.start.hour, _actTime.start.minute);
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DateTime _end = DateTime(0,0,0,_actTime.end.hour, _actTime.end.minute);
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if(_start.isAfter(_end)){Debug.LogError('${key.name} start after end? : $_start, $_end'); continue;}
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DateTimeRange actTime = DateTimeRange(start: _start, end: _end);
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if(!avgActs.containsKey(key)){
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avgActs.putIfAbsent(key, () => []);
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}
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if(avgActs[key]!.isEmpty){
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//No need to check groups. No groups exists.
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avgActs[key]!.add(AvgActData(actTime, 1, 1));
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}else{
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//Check for the closest time group
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bool foundGroup = false;
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for(int i = 0; i < avgActs[key]!.length; i++){
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if(foundGroup){continue;}
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DateTimeRange avgTime = avgActs[key]![i].avgRange;
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int count = avgActs[key]![i].count;
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if(actTime.start.difference(avgTime.start).inHours.abs() < activityGroupingThreshold && actTime.end.difference(avgTime.end).inHours.abs() < activityGroupingThreshold){
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foundGroup = true;
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int curStartMin = (avgTime.start.hour * 60) + avgTime.start.minute;
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int curEndMin = (avgTime.end.hour * 60) + avgTime.end.minute;
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int newStartMin = (actTime.start.hour * 60) + actTime.start.minute;
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int newEndMin = (actTime.end.hour * 60) + actTime.end.minute;
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int avgStartMin = ((curStartMin + newStartMin)/2).toInt();
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int avgEndMin = ((curEndMin + newEndMin)/2).toInt();
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Debug.Log('Avged : ${key.name} [$i] : ${avgStartMin} - ${avgEndMin}');
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if(avgStartMin > avgEndMin){
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//Malfunctioned
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Debug.LogError('Start is after End? Wut???\nAvged : ${key.name}[$i] : ${avgStartMin} - ${avgEndMin}');
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}else {
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DateTime baseline = DateTime(0, 0, 0, 0, 0);
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// avgActs[key]!.keys.toList()[i] =
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// DateTimeRange(start: baseline.add(Duration(minutes: avgStartMin)), end: baseline.add(Duration(minutes: avgEndMin)));
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// avgActs[key]!.values.toList()[i]++;
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//avgActs[key]!.removeWhere((key, value) => key==avgTime);
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avgActs[key]![i].avgRange = DateTimeRange(start: baseline.add(Duration(minutes: avgStartMin)), end: baseline.add(Duration(minutes: avgEndMin)));
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avgActs[key]![i].count++;
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}
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break;
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}
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}
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if(!foundGroup){
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avgActs[key]!.add(AvgActData(actTime, 1, 1));
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}
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}
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}
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}
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});
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//PASS 3: Prepare the Activity list to return
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avgActs.forEach((key, value) {
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value.sort((a,b) => b.count.compareTo(a.count));
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value.forEach((element) {
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Activity thisAct = Activity(key, element.avgRange.start, element.avgRange.end);
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Debug.LogResponse(
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'${thisAct.taskType.name} (${element.count}) -> (${element.dailyCountAvg}) : ${DateFormat('HH:mm').format(thisAct.startTime)} - ${DateFormat('HH:mm').format(
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thisAct.endTime)}');
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if(element.count < totalDays * dailyThreshold/2){
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Debug.Log('Ignoring due to DailyThreshold, ${element.count} < ${totalDays * dailyThreshold/2}');
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}else {
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listToReturn.add(thisAct);
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}
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});
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// value.forEach((act, count) {
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//
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// });
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});
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return listToReturn;
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}
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}
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class AvgActData{
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AvgActData(this.avgRange, this.count, this.dailyCountAvg);
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DateTimeRange avgRange;
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int count;
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double dailyCountAvg;
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}
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