1 files changed, 0 insertions, 195 deletions
diff --git a/libraries/arduinoCurveFitting-master/src/curveFitting.cpp b/libraries/arduinoCurveFitting-master/src/curveFitting.cpp
deleted file mode 100644
index 7155675..0000000
--- a/libraries/arduinoCurveFitting-master/src/curveFitting.cpp
+++ /dev/null
@@ -1,195 +0,0 @@
-/*
-  curveFitting.h - Library for fitting curves to given
-  points using Least Squares method, with Cramer's rule
-  used to solve the linear equation. Max polynomial order 20.
-  Created by Rowan Easter-Robinson, August 23, 2018.
-  Released into the public domain.
-*/
-
-#include <Arduino.h>
-#include "curveFitting.h"
-
-void printMat(const char *s, ld*m, int n){
-  Serial.println(s);
-  char buf[40];
-  for (int i = 0; i < n; i++) {
-    for (int j = 0; j < n; j++) {
-      snprintf(buf, 40, "%30.4f\t", m[i*n+j]);
-      Serial.print(buf);
-    }
-    Serial.println();
-  }
-}
-
-void showmat(const char *s, ld **m, int n){
-  Serial.println(s);
-  char buf[40];
-  for (int i = 0; i < n; i++) {
-    for (int j = 0; j < n; j++){
-      snprintf(buf, 40, "%30.4f\t", m[i][j]);
-      Serial.print(buf);
-    }
-    Serial.println();
-  }
-}
-
-void cpyArray(ld *src, ld*dest, int n){
-  for (int i = 0; i < n*n; i++){
-    dest[i] = src[i];
-  }
-}
-
-void subCol(ld *mat, ld* sub, uint8_t coln, uint8_t n){
-  if (coln >= n) return;
-  for (int i = 0; i < n; i++){
-    mat[(i*n)+coln] = sub[i];
-  }
-}
-
-/*Determinant algorithm taken from https://codeforwin.org/2015/08/c-program-to-find-determinant-of-matrix.html */
-int trianglize(ld **m, int n)
-{
-  int sign = 1;
-  for (int i = 0; i < n; i++) {
-    int max = 0;
-    for (int row = i; row < n; row++)
-      if (fabs(m[row][i]) > fabs(m[max][i]))
-        max = row;
-    if (max) {
-      sign = -sign;
-      ld *tmp = m[i];
-      m[i] = m[max], m[max] = tmp;
-    }
-    if (!m[i][i]) return 0;
-    for (int row = i + 1; row < n; row++) {
-      ld r = m[row][i] / m[i][i];
-      if (!r) continue;
-      for (int col = i; col < n; col ++)
-        m[row][col] -= m[i][col] * r;
-    }
-  }
-  return sign;
-}
- 
-ld det(ld *in, int n, uint8_t prnt)
-{
-  ld *m[n];
-  m[0] = in;
- 
-  for (int i = 1; i < n; i++)
-    m[i] = m[i - 1] + n;
-  if(prnt) showmat("Matrix", m, n);
-  int sign = trianglize(m, n);
-  if (!sign)
-    return 0;
-  if(prnt) showmat("Upper triangle", m, n);
-  ld p = 1;
-  for (int i = 0; i < n; i++)
-    p *= m[i][i];
-  return p * sign;
-}
-/*End of Determinant algorithm*/
-
-//Raise x to power
-ld curveFitPower(ld base, int exponent){
-  if (exponent == 0){
-    return 1;
-  } else {
-    ld val = base;
-    for (int i = 1; i < exponent; i++){
-      val = val * base;
-    }
-    return val;
-  }
-}
-
-int fitCurve (int order, int nPoints, ld py[], int nCoeffs, ld *coeffs) {
-  uint8_t maxOrder = MAX_ORDER;
-  if (nCoeffs != order + 1) return ORDER_AND_NCOEFFS_DO_NOT_MATCH; 	// no of coefficients is one larger than the order of the equation
-  if (nCoeffs > maxOrder || nCoeffs < 2) return ORDER_INCORRECT; 		//matrix memory hard coded for max of 20 order, which is huge
-  if (nPoints < 1) return NPOINTS_INCORRECT; 							//Npoints needs to be positive and nonzero
-  int i, j;
-  ld T[MAX_ORDER] = {0}; //Values to generate RHS of linear equation
-  ld S[MAX_ORDER*2+1] = {0}; //Values for LHS and RHS of linear equation
-  ld denom; //denominator for Cramer's rule, determinant of LHS linear equation
-  ld x, y;
-  
-  ld px[nPoints]; //Generate X values, from 0 to n
-  for (i=0; i<nPoints; i++){
-	px[i] = i;
-  }
-  
-  for (i=0; i<nPoints; i++) {//Generate matrix elements
-    x = px[i];
-    y = py[i];
-    for (j = 0; j < (nCoeffs*2)-1; j++){
-      S[j] += curveFitPower(x, j); // x^j iterated , S10 S20 S30 etc, x^0, x^1...
-    }
-    for (j = 0; j < nCoeffs; j++){
-      T[j] += y * curveFitPower(x, j); //y * x^j iterated, S01 S11 S21 etc, x^0*y, x^1*y, x^2*y...
-    }
-  }
-
-  ld masterMat[nCoeffs*nCoeffs]; //Master matrix LHS of linear equation
-  for (i = 0; i < nCoeffs ;i++){//index by matrix row each time
-    for (j = 0; j < nCoeffs; j++){//index within each row
-      masterMat[i*nCoeffs+j] = S[i+j];
-    }
-  }
-  
-  ld mat[nCoeffs*nCoeffs]; //Temp matrix as det() method alters the matrix given
-  cpyArray(masterMat, mat, nCoeffs);
-  denom = det(mat, nCoeffs, CURVE_FIT_DEBUG);
-  cpyArray(masterMat, mat, nCoeffs);
-
-  //Generate cramers rule mats
-  for (i = 0; i < nCoeffs; i++){ //Temporary matrix to substitute RHS of linear equation as per Cramer's rule
-    subCol(mat, T, i, nCoeffs);
-    coeffs[nCoeffs-i-1] = det(mat, nCoeffs, CURVE_FIT_DEBUG)/denom; //Coefficients are det(M_i)/det(Master)
-    cpyArray(masterMat, mat, nCoeffs);
-  }
-  return 0;
-}
-
-int fitCurve (int order, int nPoints, ld px[], ld py[], int nCoeffs, ld *coeffs) {
-  uint8_t maxOrder = MAX_ORDER;
-  if (nCoeffs != order + 1) return ORDER_AND_NCOEFFS_DO_NOT_MATCH; 	//Number of coefficients is one larger than the order of the equation
-  if(nCoeffs > maxOrder || nCoeffs < 2) return ORDER_INCORRECT; 		//Matrix memory hard coded for max of 20 order, which is huge
-  if (nPoints < 1) return NPOINTS_INCORRECT; 							//Npoints needs to be positive and nonzero
-  int i, j;
-  ld T[MAX_ORDER] = {0}; //Values to generate RHS of linear equation
-  ld S[MAX_ORDER*2+1] = {0}; //Values for LHS and RHS of linear equation
-  ld denom; //denominator for Cramer's rule, determinant of LHS linear equation
-  ld x, y;
-  
-  for (i=0; i<nPoints; i++) {//Generate matrix elements
-    x = px[i];
-    y = py[i];
-    for (j = 0; j < (nCoeffs*2)-1; j++){
-      S[j] += curveFitPower(x, j); // x^j iterated , S10 S20 S30 etc, x^0, x^1...
-    }
-    for (j = 0; j < nCoeffs; j++){
-      T[j] += y * curveFitPower(x, j); //y * x^j iterated, S01 S11 S21 etc, x^0*y, x^1*y, x^2*y...
-    }
-  }
-
-  ld masterMat[nCoeffs*nCoeffs]; //Master matrix LHS of linear equation
-  for (i = 0; i < nCoeffs ;i++){//index by matrix row each time
-    for (j = 0; j < nCoeffs; j++){//index within each row
-      masterMat[i*nCoeffs+j] = S[i+j];
-    }
-  }
-  
-  ld mat[nCoeffs*nCoeffs]; //Temp matrix as det() method alters the matrix given
-  cpyArray(masterMat, mat, nCoeffs);
-  denom = det(mat, nCoeffs, CURVE_FIT_DEBUG);
-  cpyArray(masterMat, mat, nCoeffs);
-
-  //Generate cramers rule mats
-  for (i = 0; i < nCoeffs; i++){ //Temporary matrix to substitute RHS of linear equation as per Cramer's rule
-    subCol(mat, T, i, nCoeffs);
-    coeffs[nCoeffs-i-1] = det(mat, nCoeffs, CURVE_FIT_DEBUG)/denom; //Coefficients are det(M_i)/det(Master)
-    cpyArray(masterMat, mat, nCoeffs);
-  }
-  return 0;
-}