コード例 #1
0
        private void StartUp()
        {
            _departments = new DepartmentInfo[1];
            _populationCells = new PopulationCell[WIDTH * HEIGHT];
            _populationCells.Initialize<PopulationCell>();

            DepartmentInfo depInfo = new DepartmentInfo();
            depInfo.Name = "TestDep";
            Random rand = new Random();
            for (int i = 0; i < 8; i++)
                depInfo.Population[i] = rand.Next(10, 500);

            depInfo.Coordinates = new Point[(WIDTH * HEIGHT)];

            for (int x = 0; x < WIDTH; x++)
                for (int y = 0; y < HEIGHT; y++)
                {
                    Point p = new Point(x, y);
                    depInfo.Coordinates[x + (y * WIDTH)] = p;
                }

            _departments = new DepartmentInfo[1] { depInfo };

            foreach (DepartmentInfo item in _departments)
                _originalCount += item.Population.Sum();
        }
コード例 #2
0
ファイル: MatrixGenerator.cs プロジェクト: HannesR-O/PSC2013
        private Tuple<int, PopulationCell>[] PopulateDepartment(DepartmentInfo depInfo, out Human[] humanArray)
        {
            List<Human> humanList = new List<Human>(depInfo.GetTotal());

            int areaSize = depInfo.Coordinates.Length;                      // number of points to be populated.
            Tuple<int, PopulationCell>[] resultArray =                      // the array which will be returned.
                new Tuple<int,PopulationCell>[areaSize];
            int resultArrayIndex = 0;                                       // running index for the array.

            Point origin = CalculateInitialPoint(depInfo.Coordinates);      // the origin as an fixpoint for every point.

            int maximumDistance = depInfo.Coordinates.Max(                  // the maximum distance possible.
                point => point.Distance(origin)) + 1;

            int[] factors = new int[maximumDistance];                       // array of factor for each distance.
            factors[0] = 225;                                               // start factor.
            for (int i = 1; i < maximumDistance; i++)                       // creating every factor for each distance.
            {
                int previousFactor = factors[i - 1];
                int minus = (int)(previousFactor / 3f / 6);
                int random = RANDOM.Next(previousFactor / 3) - minus;
                random = (int)(random * (1 - i / (float)maximumDistance));
                if (previousFactor - random <= 0) random = 5;
                factors[i] = previousFactor - random;
            }

            foreach (Point currentPoint in depInfo.Coordinates)
            {
                int currentDistance = currentPoint.Distance(origin);        // distance of this point to the origin.
                PopulationCell currentCell = new PopulationCell();

                for (int i = 0; i < 8; i++)                                 // for each age-group.
                {
                    int additionalRand = RANDOM.Next(10) - 5;
                    int numberForEvenSpread =                               // number of humans if everything would be even/the same.
                        (int)(depInfo.Population[i] / (float)areaSize);
                    int numberOfPeopleToSet =                               // number of humans to be set for this age-group.
                        (int)(numberForEvenSpread *
                        (factors[currentDistance] + additionalRand) / 100f);

                    EGender gender = (i < 4) ?                              // the first four are male, the last female.
                        EGender.Male : EGender.Female;

                    var bounds = GetAgeBounds(i);                              // the age-boundaries for the corresponding age-group.
                    int lowerAgeBound = bounds.Item1;
                    int upperAgeBound = bounds.Item2;

                    for (int setCount = 0; setCount < numberOfPeopleToSet; setCount++)
                    {
                        int thisAge = RANDOM.Next(lowerAgeBound, upperAgeBound + 1);
                        Human thisHuman = Human.Create(gender, thisAge, currentPoint.Flatten(WIDTH));
                        humanList.Add(thisHuman);
                        currentCell.Data[i]++;                              // 'adds' the human to its cell.

                        depInfo.Population[i]--;                            // 'removes' the human out of the population.
                    }
                }

                areaSize--;                                                 // 'removes' point from rest-area.

                resultArray[resultArrayIndex++] = new Tuple<int, PopulationCell>(
                        currentPoint.Flatten(WIDTH), currentCell);
            }

            humanArray = humanList.ToArray();
            humanList = null;
            return resultArray;
        }
コード例 #3
0
ファイル: MatrixGenerator.cs プロジェクト: HannesR-O/PSC2013
        /// <summary>
        /// The standard method to populate.
        /// </summary>
        private Tuple<int, PopulationCell>[] Populate(DepartmentInfo depInfo, out Human[] humanArray)
        {
            // the count of cells.
            int areaSize = depInfo.Coordinates.Length;

            // precalculating humans. (~ +- 10%)
            for (int i = 0; i < depInfo.Population.Length; ++i)
                depInfo.Population[i] = (int)Math.Round(
                    depInfo.Population[i] * (1 - (RANDOM.Next(20) - 10) / 100f));

            // initializing array.
            var resultArray = new Tuple<int, PopulationCell>[areaSize];
            int resultIndex = 0;

            // the origin used as fixpoint.
            Point origin = CalculateInitialPoint(depInfo.Coordinates);

            // maximum distance possible. (returns a relative small number)
            int maxDistance = depInfo.Coordinates.Max(p => p.Distance(origin)) + 1;

            // array of factors
            double[] factors = new double[maxDistance];
            factors[0] = 1.5;                           // start factor.
            for (int i = 1; i < maxDistance; i++)       // creating every factor for each distance.
            {
                //TODO | dj | randomise
                // (-(1/maxDistance * i)^2 + 1.75) * 100
                double one = 1d / maxDistance * i;
                double two = Math.Pow(one, 2);
                double three = factors[0];
                double four = three - two;
                factors[i] = four;
            }

            // array for each age-group, holding a list of Tuple of cell-indices and count.
            Queue<Tuple<int, ushort>>[] agesOfCells = new Queue<Tuple<int, ushort>>[8];
            agesOfCells.Initialize<Queue<Tuple<int, ushort>>>();

            int humanCount = 0;

            // going through all points and set the counts.
            foreach (Point point in depInfo.Coordinates)
            {
                PopulationCell cell = new PopulationCell();
                int cellIndex = point.Flatten(WIDTH);

                double factor = factors[point.Distance(origin)];
                for (int i = 0; i < 8; ++i)
                {
                    ushort toSet = (ushort)Math.Round(depInfo.Population[i] / (double)areaSize * factor);
                    cell.Data[i] = toSet;
                    agesOfCells[i].Enqueue(new Tuple<int,ushort>(cellIndex, toSet));
                    depInfo.Population[i] -= toSet;
                    //if (cell.Data[i] == 0)
                    //    Console.WriteLine("0 people in {0}", cellIndex);
                }
                if (cell.Total == 0 && depInfo.Population.Sum() != 0)
                {
                    int j = 0;
                    do
                    {
                        j = RANDOM.Next(8);
                    } while (depInfo.Population[j] == 0);

                    cell.Data[j] = 1;
                    agesOfCells[j].Enqueue(new Tuple<int,ushort>(cellIndex, 1));
                    depInfo.Population[j] -= 1;
                }
                areaSize--;

                humanCount += cell.Total;

                resultArray[resultIndex++] = new Tuple<int,PopulationCell>(cellIndex, cell);
            }

            // initializing human array
            humanArray = new Human[humanCount];
            int humanIndex = 0;

            // going through all ages and creating the humans.
            for (int i = 0; i < 8; ++i)
            {
                var queue = agesOfCells[i];
                var bounds = GetAgeBounds(i);

                // age-bounds (for random).
                int lowerAge = bounds.Item1;
                int upperAge = bounds.Item2;

                // gender.
                EGender gender = (i < 4) ? EGender.Male : EGender.Female;

                // for each cell.
                while (queue.Count > 0)
                //foreach (Tuple<int, ushort> cellTuple in queue)
                {
                    var cellTuple = queue.Dequeue();

                    int cellIndex = cellTuple.Item1;
                    ushort count = cellTuple.Item2;

                    // for each human (who shall be created).
                    ushort c = count;
                    while (c-- > 0)
                    //for (int c = 0; c < count; ++c)
                    {
                        int thisHumanAge = RANDOM.Next(lowerAge, upperAge + 1);
                        Human thisHuman = Human.Create(gender, thisHumanAge, cellIndex);
                        humanArray[humanIndex++] = thisHuman;
                    }
                }

                agesOfCells[i] = null;  // not necessary, but who knows :P
            }

            return resultArray;
        }
コード例 #4
0
ファイル: MatrixGenerator.cs プロジェクト: HannesR-O/PSC2013
        /// <summary>
        /// The Dummy-implementation.
        /// </summary>
        private Tuple<int, PopulationCell>[] DummyPopulate(DepartmentInfo depInfo, out Human[] humanArray)
        {
            int areaSize = depInfo.Coordinates.Length;

            Tuple<int, PopulationCell>[] tmpArray = new Tuple<int, PopulationCell>[areaSize];
            int tmpCounter = 0;
            humanArray = new Human[depInfo.GetTotal()];
            int humanCounter = 0;

            int[] popsPerPoint = depInfo.Population.Select(x => x / areaSize).ToArray();

            foreach (Point point in depInfo.Coordinates)
            {
                PopulationCell cell = new PopulationCell();

                for (int i = 0; i < 8; i++)
                {
                    EGender gender = (i < 4) ? EGender.Male : EGender.Female;

                    var bounds = GetAgeBounds(i);
                    int lowerAgeBound = bounds.Item1;
                    int upperAgeBound = bounds.Item2;

                    for (int n = 0; n < popsPerPoint[i]; n++)
                    {
                        int thisAge = RANDOM.Next(lowerAgeBound, upperAgeBound + 1);
                        humanArray[humanCounter++] = Human.Create(gender, thisAge, point.Flatten(WIDTH));
                        cell.Data[i]++;
                    }
                }

                tmpArray[tmpCounter++] = new Tuple<int, PopulationCell>(point.Flatten(WIDTH), cell);

            }

            return tmpArray;
        }
コード例 #5
0
        /// <summary>
        /// Reads the previously given file and
        /// tries to interpret its content file
        /// as an array of DepartmenInfos.
        /// </summary>
        /// <returns>The DepartmentInfo-Array.</returns>
        public DepartmentInfo[] ReadFile()
        {
            WriteMessage("Reading file...");

            var depInfList = new List<DepartmentInfo>();

            ZipArchive archive = ZipFile.OpenRead(Path);
            Stream stream = archive.GetEntry("map").Open();

            using (StreamReader sr = new StreamReader(stream))
            {
                while (!sr.EndOfStream)
                {
                    DepartmentInfo depInf = new DepartmentInfo();
                    string[] s = sr.ReadLine().Split('|');
                    depInf.Name = s[0];                                 // Name
                    for (int i = 1; i < 9; i++)                         // Population(s)
                        depInf.Population[i - 1] = int.Parse(s[i]);
                    depInf.Coordinates = new Point[s.Length - 9];
                    for (int i = 9; i < s.Length; i++)                  // Coordinates
                    {
                        string[] pArr = s[i].Split(':');
                        depInf.Coordinates[i - 9] = new Point(
                            int.Parse(pArr[0]), int.Parse(pArr[1]));
                    }

                    depInfList.Add(depInf);
                    IterationPassed.Raise(this, new ContinuationEventArgs() { Continuing = true });
                }
            }
            stream.Close();
            archive.Dispose();
            IterationPassed.Raise(this, new ContinuationEventArgs() { Finished = true });

            return depInfList.ToArray();
        }