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@@ -0,0 +1,2 @@# Auto detect text files and perform LF normalization * text=auto
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@@ -0,0 +1,21 @@MIT License Copyright (c) 2019 Andrey Fedorov Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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@@ -0,0 +1,7 @@# arduinoCurveFitting Fit polynomial curves to given points using least squares regression. The max order of polynomial fitting is 20, this should be more than enough to fit most practical problems. All values are kept as double for precision, this works well on a Teensy due to its floating point unit and large (64 bit) double precision. the numbers required increase exponentially as the number of points or order increases. This library solves the least squares problem using Cramer's rule and a small function to calculate the determinant of each matrix. More explained in this article https://medium.com/@rowaner111/fitting-curves-to-data-on-an-arduino-part-1-how-to-use-arduinocurvefitting-a3173c6dd4ef
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@@ -0,0 +1,37 @@#include <curveFitting.h> void setup(){ Serial.begin(9600); while(!Serial); Serial.println("Starting"); char buf[100]; int xpower = 3; int order = 3; snprintf(buf, 100, "Fitting curve of order %i to data of power %i...\n", order, xpower); Serial.print(buf); double x[26]; double t[26]; for (int i = 0; i < sizeof(x)/sizeof(double); i++){ t[i] = i; x[i] = pow(i, xpower); } double coeffs[order+1]; int ret = fitCurve(order, sizeof(x)/sizeof(double), t, x, sizeof(coeffs)/sizeof(double), coeffs); if (ret == 0){ //Returned value is 0 if no error uint8_t c = 'a'; Serial.println("Coefficients are"); for (int i = 0; i < sizeof(coeffs)/sizeof(double); i++){ snprintf(buf, 100, "%c=",c++); Serial.print(buf); Serial.print(coeffs[i]); Serial.print('\t'); } } } void loop(){ }
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@@ -0,0 +1,10 @@name=CurveFitting version=1.0.6 author=Rotario <rotarioner@gmail.com> maintainer=Rotario <rotarioner@gmail.com> sentence=Fits polynomial curves to given datapoints paragraph=Fit polynomial curves to given points using least squares regression. The max order of polynomial fitting is 20, this should be more than enough to fit most practical problems. All values are kept as double for precision, this works well on a Teensy due to its floating point unit and large (64 bit) double precision. the numbers required increase exponentially as the number of points or order increases. url=https://github.com/Rotario/arduinoCurveFitting includes=curveFitting.h category=Data Processing architectures=*
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@@ -0,0 +1,195 @@/* 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, double*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, double **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(double *src, double*dest, int n){ for (int i = 0; i < n*n; i++){ dest[i] = src[i]; } } void subCol(double *mat, double* 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(double **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; double *tmp = m[i]; m[i] = m[max], m[max] = tmp; } if (!m[i][i]) return 0; for (int row = i + 1; row < n; row++) { double 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; } double det(double *in, int n, uint8_t prnt) { double *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); double p = 1; for (int i = 0; i < n; i++) p *= m[i][i]; return p * sign; } /*End of Determinant algorithm*/ //Raise x to power double curveFitPower(double base, int exponent){ if (exponent == 0){ return 1; } else { double val = base; for (int i = 1; i < exponent; i++){ val = val * base; } return val; } } int fitCurve (int order, int nPoints, double py[], int nCoeffs, double *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; double T[MAX_ORDER] = {0}; //Values to generate RHS of linear equation double S[MAX_ORDER*2+1] = {0}; //Values for LHS and RHS of linear equation double denom; //denominator for Cramer's rule, determinant of LHS linear equation double x, y; double 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... } } double 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]; } } double 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, double px[], double py[], int nCoeffs, double *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; double T[MAX_ORDER] = {0}; //Values to generate RHS of linear equation double S[MAX_ORDER*2+1] = {0}; //Values for LHS and RHS of linear equation double denom; //denominator for Cramer's rule, determinant of LHS linear equation double 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... } } double 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]; } } double 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; }
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@@ -0,0 +1,40 @@/* 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. */ #ifndef curveFit_h #define curveFit_h #include <Arduino.h> #define MAX_ORDER 20 #ifndef CURVE_FIT_DEBUG #define CURVE_FIT_DEBUG 0 #endif /* Enum for error messages */ enum curveFitERROR{ ORDER_AND_NCOEFFS_DO_NOT_MATCH = -1, ORDER_INCORRECT = -2, NPOINTS_INCORRECT = -3 }; /* Matrix Helper Functions */ void printMat(const char *s, double*m, int n); void showmat(const char *s, double **m, int n); void cpyArray(double *src, double*dest, int n); void subCol(double *mat, double* sub, uint8_t coln, uint8_t n); double curveFitPower(double base, int exponent); /* Determinant matrix functions */ int trianglize(double **m, int n); double det(double *in, int n, uint8_t prnt); /* Curve fitting functions */ int fitCurve (int order, int nPoints, double py[], int nCoeffs, double *coeffs); int fitCurve (int order, int nPoints, double px[], double py[], int nCoeffs, double *coeffs); #endif
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@@ -0,0 +1,61 @@/* detectorBuilding.cpp - Library for Detector Building utility functions Created by Anthony Wang, February 21, 2020. Released into the public domain. */ #include "Arduino.h" #include "detectorBuilding.h" const int LED_R = 4, LED_G = 3, LED_B = 2, THERM = 0; // Device component pins const double R_k = 10000, V_in = 5, analog_max = 1023; // Device constants // Temperature conversions inline double f2c(double f) { return (f - 32) * 5 / 9; } // Fahrenheit to Celsius inline double c2f(double c) { return c * 9 / 5 + 32; } // Celsius to Fahrenheit inline double k2c(double k) { return k - 273.15; } // Kelvin to Celsius inline double c2k(double c) { return c + 273.15; } // Celsius to Kelvin inline double f2k(double f) { return c2k(f2c(f)); } // Fahrenheit to Kelvin inline double k2f(double k) { return c2f(k2c(k)); } // Kelvin to Fahrenheit // Analog to digital conversion inline double a2d(int a) { return V_in * a / analog_max; } inline int d2a(double d) { return d * analog_max / V_in; } // Utility functions // No C++ standard library :( void sort(double a[], int n) { // Bubble sort // Slow but n < 30 so OK // Too lazy to implement a fast sort for (int i = 0; i < n; i++) { for (int j = 0; j < n - 1; j++) { if (a[j] > a[j + 1]) { double tmp = a[j]; a[j] = a[j + 1]; a[j + 1] = tmp; } } } } // Calculations: Steinhart-hart stuff // Probably unused but can include anyways void calculate() { sort(V, n); sort(T, n); double R[n], L[n], Y[n], G[n]; for (int i = 0; i < n; i++) R[i] = R_k * (V_in / V[i] - 1); for (int i = 0; i < n; i++) L[i] = log(R[i]); for (int i = 0; i < n; i++) Y[i] = 1 / c2k(T[i]); for (int i = 0; i < n; i += 3) { G[i + 1] = (Y[i + 1] - Y[i]) / (L[i + 1] - L[i]); G[i + 2] = (Y[i + 2] - Y[i]) / (L[i + 2] - L[i]); } for (int i = 0; i < n; i += 3) { // Don't ask how this works C[i / 3] = (G[i + 2] - G[i + 1]) / (L[i + 2] - L[i + 1]) / (L[i] + L[i + 1] + L[i + 2]); B[i / 3] = G[i + 1] - C[i / 3] * (L[i] * L[i] + L[i] * L[i + 1] + L[i + 1] * L[i + 1]); A[i / 3] = Y[i] - L[i] * (B[i / 3] + L[i] * L[i] * C[i / 3]); } for (int i = 0; i < n; i += 3) V_mid[i / 3] = (i ? (V[i - 1] + V[i]) / 2 : V[i]); }
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@@ -0,0 +1,14 @@/* detectorBuilding.h - Library for Detector Building utility functions Created by Anthony Wang, February 21, 2020. Released into the public domain. */ #ifndef detectorBuilding_h #define detectorBuilding_h #include "Arduino.h" #endif
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@@ -0,0 +1,1 @@For information on installing libraries, see: http://www.arduino.cc/en/Guide/Libraries
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