You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
96 lines
3.1 KiB
96 lines
3.1 KiB
/**
|
|
* Marlin 3D Printer Firmware
|
|
* Copyright (C) 2016 MarlinFirmware [https://github.com/MarlinFirmware/Marlin]
|
|
*
|
|
* Based on Sprinter and grbl.
|
|
* Copyright (C) 2011 Camiel Gubbels / Erik van der Zalm
|
|
*
|
|
* 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 3 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 <http://www.gnu.org/licenses/>.
|
|
*
|
|
*/
|
|
|
|
/**
|
|
* Least Squares Best Fit By Roxy and Ed Williams
|
|
*
|
|
* This algorithm is high speed and has a very small code footprint.
|
|
* Its results are identical to both the Iterative Least-Squares published
|
|
* earlier by Roxy and the QR_SOLVE solution. If used in place of QR_SOLVE
|
|
* it saves roughly 10K of program memory. It also does not require all of
|
|
* coordinates to be present during the calculations. Each point can be
|
|
* probed and then discarded.
|
|
*
|
|
*/
|
|
|
|
#include "MarlinConfig.h"
|
|
|
|
#if ENABLED(AUTO_BED_LEVELING_UBL) // Currently only used by UBL, but is applicable to Grid Based (Linear) Bed Leveling
|
|
|
|
#include "macros.h"
|
|
#include <math.h>
|
|
|
|
#include "least_squares_fit.h"
|
|
|
|
void incremental_LSF_reset(struct linear_fit_data *lsf) {
|
|
lsf->n = 0;
|
|
lsf->A = 0.0; // probably a memset() can be done to zero
|
|
lsf->B = 0.0; // this whole structure
|
|
lsf->D = 0.0;
|
|
lsf->xbar = lsf->ybar = lsf->zbar = 0.0;
|
|
lsf->x2bar = lsf->y2bar = lsf->z2bar = 0.0;
|
|
lsf->xybar = lsf->xzbar = lsf->yzbar = 0.0;
|
|
lsf->max_absx = lsf->max_absy = 0.0;
|
|
}
|
|
|
|
void incremental_LSF(struct linear_fit_data *lsf, float x, float y, float z) {
|
|
lsf->xbar += x;
|
|
lsf->ybar += y;
|
|
lsf->zbar += z;
|
|
lsf->x2bar += x*x;
|
|
lsf->y2bar += y*y;
|
|
lsf->z2bar += z*z;
|
|
lsf->xybar += x*y;
|
|
lsf->xzbar += x*z;
|
|
lsf->yzbar += y*z;
|
|
lsf->max_absx = (fabs(x) > lsf->max_absx) ? fabs(x) : lsf->max_absx;
|
|
lsf->max_absy = (fabs(y) > lsf->max_absy) ? fabs(y) : lsf->max_absy;
|
|
lsf->n++;
|
|
return;
|
|
}
|
|
|
|
int finish_incremental_LSF(struct linear_fit_data *lsf) {
|
|
float DD, N;
|
|
|
|
N = (float) lsf->n;
|
|
lsf->xbar /= N;
|
|
lsf->ybar /= N;
|
|
lsf->zbar /= N;
|
|
lsf->x2bar = lsf->x2bar/N - lsf->xbar*lsf->xbar;
|
|
lsf->y2bar = lsf->y2bar/N - lsf->ybar*lsf->ybar;
|
|
lsf->z2bar = lsf->z2bar/N - lsf->zbar*lsf->zbar;
|
|
lsf->xybar = lsf->xybar/N - lsf->xbar*lsf->ybar;
|
|
lsf->yzbar = lsf->yzbar/N - lsf->ybar*lsf->zbar;
|
|
lsf->xzbar = lsf->xzbar/N - lsf->xbar*lsf->zbar;
|
|
|
|
DD = lsf->x2bar*lsf->y2bar - lsf->xybar*lsf->xybar;
|
|
if (fabs(DD) <= 1e-10*(lsf->max_absx+lsf->max_absy))
|
|
return -1;
|
|
|
|
lsf->A = (lsf->yzbar*lsf->xybar - lsf->xzbar*lsf->y2bar) / DD;
|
|
lsf->B = (lsf->xzbar*lsf->xybar - lsf->yzbar*lsf->x2bar) / DD;
|
|
lsf->D = -(lsf->zbar + lsf->A*lsf->xbar + lsf->B*lsf->ybar);
|
|
return 0;
|
|
}
|
|
#endif
|
|
|
|
|
|
|