C++实现的不含任何第三方库的savgol滤波算法，精度可与Opencv的媲美

# savgol C++ implementation of Savitzky Golay Filter based on the original paper : "Smoothing and Differentiation of Data by Simplified Least Squares Procedures" by A.Savitzky and M. J.E Golay". [1] * The implementation is close to the original publication with corrections taken from [2] . The convolution weights for each given window size are stored in a constexpr map. * there is no padding implemented so far. The data points at the bounds left unchanged. ## usage ```cpp #include <vector> #include "savgol.hpp" std::vector<float> data{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; std::vector<double> filtered_data; filter::savgol(data.begin(), data.end(), sd::back_inserter(filtered_data),filter::SmoothQuadCubic(5) ); ``` ## implementation ### available Convolution Operators > SmoothQuadCubic : > SmoothQuarticQuintic : > DeriveQuadFirst : --- > SmoothGaussian: to make comparisions to SG filter, the gaussian kernel is approximated by binominal coefficients, taken from Pascals triangle. > SmoothAverage: to make comparisions to SG filter, convolution weights are constant =1. > > ### available window sizes * as presentented in the original paper the window sizes are odd numbers, up to a size of 25 ### Demonstration  [1] A. Savitzky, M. J. E. Golay: Smoothing and Differentiation of Data by Simplified Least Squares Procedures. In: Analytical Chemistry. Volume 36, No. 8, June 1964, p. 1627�1639, [doi:10.1021/ac60214a047](doi:10.1021/ac60214a047). [2] J. Steiner, Y. Termonia, J. Deltour: Comments on Smoothing And Differentiation Of Data By Simplified Least Square Procedure In: Analytical Chemistry. Volume 44, No. 11, 1. Sept 1972, p. 1906�1909