using System;
using System.Collections.Generic;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Xml.Schema;

namespace FeatureDetectionLib
{
    public static class Algo
    {
        public static float[,] CalculateGaussianFilter(int _size, float _sig)
        {
            int d = _size / 2;

            var result = new float[_size, _size];

            for (int i = -d; i <= d; i++)
            {
                for (int j = -d; j <= d; j++)
                {
                    result[i + d, j + d] = (float)((1 / (2 * Math.PI * Math.Pow(_sig, 2))) * Math.Exp(- (i * i + j * j) / (2 * _sig * _sig)));
                }
            }

            return result;
        }

        public static void SaveGaussianFilterToImage(float[,] _filter, string _path)
        {
            var img = new Bitmap(_filter.GetLength(1), _filter.GetLength(0));

            var nfilter = Normalize(_filter, 255);

            for (int i = 0; i < img.Width; i++)
                for (int j = 0; j < img.Height; j++)
                {
                    var value = (byte)nfilter[i, j];
                    var pixel = Color.FromArgb(value, value, value);
                    img.SetPixel(i, j, pixel);
                }

            img.Save(_path);
        }

        public static float[,] Normalize(float[,] _matrix, float _max)
        {
            var max = float.MinValue;
            var min = float.MaxValue;

            for (int i = 0; i < _matrix.GetLength(0); i++)
                for (int j = 0; j < _matrix.GetLength(1); j++)
                {
                    if (_matrix[i, j] > max)
                        max = _matrix[i, j];
                    if (_matrix[i, j] < min)
                        min = _matrix[i, j];
                }

            var result = new float[_matrix.GetLength(0), _matrix.GetLength(1)];
            for (int i = 0; i < _matrix.GetLength(0); i++)
                for (int j = 0; j < _matrix.GetLength(1); j++)
                    result[i, j] = (byte)((_matrix[i, j] - min) / (max - min) * _max);

            return result;
        }

        public static float[,] Convolution(float[,] _matrix, float[,] _ker)
        {
            var hdelta = (_ker.GetLength(0) - 1) / 2;
            var wdelta = (_ker.GetLength(1) - 1) / 2;

            var tmpmatrix = new float
                [_matrix.GetLength(0) + _ker.GetLength(0) - 1,
                _matrix.GetLength(1) + _ker.GetLength(1) - 1];

            for (int i = 0; i < _matrix.GetLength(0); i++)
            {
                for (int j = 0; j < _matrix.GetLength(1); j++)
                {
                    tmpmatrix[hdelta + i, wdelta + j] = _matrix[i, j];
                }
            }

            for (int i = 0; i < hdelta; i++)
            {
                for (int j = 0; j < wdelta; j++)
                {
                    tmpmatrix[i, j] = _matrix[0, 0];
                    tmpmatrix[i, _matrix.GetLength(1) + j + wdelta] = _matrix[0, _matrix.GetLength(1) - 1];
                }
            }

            for (int i = _matrix.GetLength(0) + hdelta; i < _matrix.GetLength(0) + hdelta * 2; i++)
            {
                for (int j = 0; j < wdelta; j++)
                {
                    tmpmatrix[i, j] = _matrix[0, 0];
                    tmpmatrix[i, _matrix.GetLength(1) + j + wdelta] = _matrix[0, _matrix.GetLength(1) - 1];
                }
            }

            for (int i = 0; i < _matrix.GetLength(0); i++)
            {
                for (int j = 0; j < wdelta; j++)
                {
                    tmpmatrix[i + hdelta, j] = _matrix[i, 0];
                    tmpmatrix[i + hdelta, _matrix.GetLength(1) + j + wdelta] = _matrix[i, _matrix.GetLength(1) - 1];
                }
            }

            for (int i = 0; i < wdelta; i++)
            {
                for (int j = 0; j < _matrix.GetLength(1); j++)
                {
                    tmpmatrix[i, j + wdelta] = _matrix[i, 0];
                    tmpmatrix[_matrix.GetLength(0) + i + hdelta, j + wdelta] = _matrix[_matrix.GetLength(0) - 1, j];
                }
            }

            var r = new float[_matrix.GetLength(0), _matrix.GetLength(1)];

            for (int i = 0; i < _matrix.GetLength(0); i++)
            {
                for (int j = 0; j < _matrix.GetLength(1); j++)
                {
                    var sum = 0.0f;
                    for (int k = 0; k < _ker.GetLength(0); k++)
                        for (int l = 0; l < _ker.GetLength(1); l++)
                            sum += tmpmatrix[i + k, j + l] * _ker[k, l];
                    r[i, j] = sum;
                }
            }

            return r;
        }

        public static float[,] LoadMatrixFromFile(string _path)
        {
            var img = (Bitmap)Bitmap.FromFile(_path);

            var result = new float[img.Width, img.Height];

            for (int i = 0; i < img.Width; i++)
                for (int j = 0; j < img.Height; j++)
                {
                    var value = img.GetPixel(i, j);
                    result[i, j] = (value.R + value.G + value.B)/3.0f;
                }

            return result;
        }

        public static void SaveMatrixToFile(float[,] _matrix, string _path)
        {
            var img = new Bitmap(_matrix.GetLength(1), _matrix.GetLength(0));

            var nmatrix = Normalize(_matrix, 255);

            for (int i = 0; i < img.Width; i++)
                for (int j = 0; j < img.Height; j++)
                {
                    var value = (byte)nmatrix[i, j];
                    var pixel = Color.FromArgb(value, value, value);
                    img.SetPixel(i, j, pixel);
                }

            img.Save(_path);
        }

        public static float[,] MatrixSubtraction(float[,] _fst, float[,] _snd)
        {
            var result = new float[_fst.GetLength(0), _fst.GetLength(1)];

            for (int i = 0; i < _fst.GetLength(0); i++)
                for (int j = 0; j < _fst.GetLength(1); j++)
                    result[i, j] = _fst[i,j] - _snd[i,j];
            return result;
        }
    }
}