aswi2021tri-musketyri-gitlab/Server/ServerApp/Predictor/FeatureExtractor.cs @ 22211075

//
// Author: Roman Kalivoda
//

using System.Collections.Generic;
using System;
using ServerApp.Parser.Parsers;
using ServerApp.Parser.OutputInfo;
using System.Linq;

namespace ServerApp.Predictor
{
    /// <summary>
    /// A class responsible for preparation of features for classifiers.
    /// </summary>
    public class FeatureExtractor
    {
        /// <summary>
        /// A DataParser instance used to access info objects.
        /// </summary>
        private readonly IDataParser dataParser;

        private Dictionary<string, int> buildingsToAreas;

        /// <summary>
        /// Instantiates new FeatureExtractor class.
        /// </summary>
        /// <param name="dataParser">Data parser used to access training data.</param>
        public FeatureExtractor(IDataParser dataParser, Dictionary<string, int> buildingsToAreas)
        {
            this.dataParser = dataParser;
            this.buildingsToAreas = buildingsToAreas;
        }

        /// <summary>
        /// TODO comment
        /// </summary>
        /// <param name="area"></param>
        /// <param name="startDate"></param>
        /// <param name="endDate"></param>
        /// <param name="interval"></param>
        /// <param name="wholeDay"></param>
        /// <returns></returns>
        public List<ModelInput> PrepareTrainingInput(int area, DateTime startDate, DateTime endDate, int interval = 1, bool wholeDay = true)
        {
            dataParser.Parse(startDate, endDate, interval, wholeDay);
            List<string> buildings = new List<string>();

            // find all buildings in area
            foreach (KeyValuePair<string, int> kvp in buildingsToAreas)
            {
                if (kvp.Value == area)
                {
                    buildings.Add(kvp.Key);
                }
            }

            var res = new List<ModelInput>();
            foreach (WeatherInfo val in dataParser.WeatherList)
            {
                res.Add(new ModelInput
                {
                    Temp = (float)val.temp,
                    Time = val.startTime,
                    Wind = (float)val.wind,
                    Rain = (float)val.rain,
                });
            }

            List<ActivityInfo> attendance = dataParser.AttendanceList;
            foreach (ModelInput input in res)
            {
                List<int> amounts = new List<int>();
                List<int> maxima = new List<int>();
                foreach (string building in buildings)
                {

                    amounts.Add(attendance.Where(activity => activity.building.Equals(building) && activity.startTime.Equals(input.Time)).Select(activity => activity.amount).First());
                    maxima.Add(attendance.Where(activity => activity.building.Equals(building)).Select(activity => activity.amount).Max());
                }
                double ratio = amounts.Sum() / (double)maxima.Sum();
                input.Label = RatioToLabel(ratio);
            }

            return res;
        }

        private string RatioToLabel(double ratio)
        {
            if (ratio < 0.1f)
            {
                return "10%";
            } else if (ratio < 0.2f)
            {
                return "20%";
            } else if (ratio < 0.3f)
            {
                return "30%";
            } else if (ratio < 0.4f)
            {
                return "40%";
            } else if (ratio < 0.5f)
            {
                return "50%";
            } else if (ratio < 0.6f)
            {
                return "60%";
            } else if(ratio < 0.7f) {
                return "70%";
            } else if (ratio < 0.8f)
            {
                return "80%";
            } else if (ratio < 0.9f)
            {
                return "90%";
            } else
            {
                return "100%";
            }
        }

        private double LabelToRatio(string label)
        {
            if (label.Equals("10%")) {
                return 0.1f;
            }
            else if (label.Equals("20%"))  {
                return 0.2f;
            }
            else if (label.Equals("30%")) {
                return 0.3f;
            }
            else if (label.Equals("40%")) {
                return 0.4f;
            }
            else if (label.Equals("50%")) {
                return 0.5f;
            }
            else if (label.Equals("60%")) {
                return 0.6f;
            }
            else if (label.Equals("70%")) {
                return 0.7f;
            }
            else if (label.Equals("80%")) {
                return 0.8f;
            }
            else if (label.Equals("90%")) {
                return 0.9f;
            }
            else
            {
                return 1.0f;
            }
        }
    }
}