99ecdf59af
Use macros that explicitly avoid double-evaluation and can be used for any datatype, replacing `min`, `max`, `abs`, `fabs`, `labs`, and `FABS`. Co-Authored-By: ejtagle <ejtagle@hotmail.com>
88 lines
2.9 KiB
C
88 lines
2.9 KiB
C
/**
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* Marlin 3D Printer Firmware
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* Copyright (C) 2016 MarlinFirmware [https://github.com/MarlinFirmware/Marlin]
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*
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* Based on Sprinter and grbl.
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* Copyright (C) 2011 Camiel Gubbels / Erik van der Zalm
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>.
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*
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*/
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/**
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* Incremental Least Squares Best Fit By Roxy and Ed Williams
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*
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* This algorithm is high speed and has a very small code footprint.
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* Its results are identical to both the Iterative Least-Squares published
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* earlier by Roxy and the QR_SOLVE solution. If used in place of QR_SOLVE
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* it saves roughly 10K of program memory. And even better... the data
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* fed into the algorithm does not need to all be present at the same time.
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* A point can be probed and its values fed into the algorithm and then discarded.
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*
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*/
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#ifndef _LEAST_SQUARES_FIT_H_
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#define _LEAST_SQUARES_FIT_H_
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#include "../inc/MarlinConfig.h"
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#include <math.h>
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struct linear_fit_data {
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float xbar, ybar, zbar,
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x2bar, y2bar, z2bar,
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xybar, xzbar, yzbar,
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max_absx, max_absy,
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A, B, D, N;
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};
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void inline incremental_LSF_reset(struct linear_fit_data *lsf) {
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memset(lsf, 0, sizeof(linear_fit_data));
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}
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void inline incremental_WLSF(struct linear_fit_data *lsf, const float &x, const float &y, const float &z, const float &w) {
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// weight each accumulator by factor w, including the "number" of samples
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// (analogous to calling inc_LSF twice with same values to weight it by 2X)
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lsf->xbar += w * x;
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lsf->ybar += w * y;
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lsf->zbar += w * z;
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lsf->x2bar += w * x * x; // don't use sq(x) -- let compiler re-use w*x four times
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lsf->y2bar += w * y * y;
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lsf->z2bar += w * z * z;
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lsf->xybar += w * x * y;
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lsf->xzbar += w * x * z;
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lsf->yzbar += w * y * z;
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lsf->N += w;
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lsf->max_absx = MAX(ABS(w * x), lsf->max_absx);
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lsf->max_absy = MAX(ABS(w * y), lsf->max_absy);
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}
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void inline incremental_LSF(struct linear_fit_data *lsf, const float &x, const float &y, const float &z) {
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lsf->xbar += x;
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lsf->ybar += y;
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lsf->zbar += z;
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lsf->x2bar += sq(x);
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lsf->y2bar += sq(y);
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lsf->z2bar += sq(z);
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lsf->xybar += x * y;
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lsf->xzbar += x * z;
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lsf->yzbar += y * z;
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lsf->max_absx = MAX(ABS(x), lsf->max_absx);
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lsf->max_absy = MAX(ABS(y), lsf->max_absy);
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lsf->N += 1.0;
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}
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int finish_incremental_LSF(struct linear_fit_data *);
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#endif // _LEAST_SQUARES_FIT_H_
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