/* * aptdec - A lightweight FOSS (NOAA) APT decoder * Copyright (C) 2019-2022 Xerbo (xerbo@protonmail.com) * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include "algebra.h" #include // Find the best linear equation to estimate the value of the // dependent variable from the independent variable linear_t linear_regression(const float *independent, const float *dependent, size_t len) { // Calculate mean of the dependent and independent variables (this is the centoid) float dependent_mean = 0.0f; float independent_mean = 0.0f; for (size_t i = 0; i < len; i++) { dependent_mean += dependent[i] / (float)len; independent_mean += independent[i] / (float)len; } // Calculate slope float a = 0.0f; { float a_numerator = 0.0f; float a_denominator = 0.0f; for (size_t i = 0; i < len; i++) { a_numerator += (independent[i] - independent_mean) * (dependent[i] - dependent_mean); a_denominator += powf(independent[i] - independent_mean, 2.0f); } a = a_numerator / a_denominator; } // We can now solve for the y-intercept since we know the slope // and the centoid, which the line must pass through float b = dependent_mean - a * independent_mean; // printf("y(x) = %fx + %f\n", a, b); return (linear_t){a, b}; } float linear_calc(float x, linear_t line) { return x * line.a + line.b; } float quadratic_calc(float x, quadratic_t quadratic) { return x * x * quadratic.a + x * quadratic.b + quadratic.c; }