Prusa MINI Firmware overview
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Go to the source code of this file.
Classes | |
struct | linear_fit_data |
Functions | |
void | incremental_LSF_reset (struct linear_fit_data *lsf) |
void | incremental_WLSF (struct linear_fit_data *lsf, const float &x, const float &y, const float &z, const float &w) |
void | incremental_WLSF (struct linear_fit_data *lsf, const xy_pos_t &pos, const float &z, const float &w) |
void | incremental_LSF (struct linear_fit_data *lsf, const float &x, const float &y, const float &z) |
void | incremental_LSF (struct linear_fit_data *lsf, const xy_pos_t &pos, const float &z) |
int | finish_incremental_LSF (struct linear_fit_data *) |
void incremental_LSF_reset | ( | struct linear_fit_data * | lsf | ) |
void incremental_WLSF | ( | struct linear_fit_data * | lsf, |
const float & | x, | ||
const float & | y, | ||
const float & | z, | ||
const float & | w | ||
) |
void incremental_LSF | ( | struct linear_fit_data * | lsf, |
const float & | x, | ||
const float & | y, | ||
const float & | z | ||
) |
void incremental_LSF | ( | struct linear_fit_data * | lsf, |
const xy_pos_t & | pos, | ||
const float & | z | ||
) |
int finish_incremental_LSF | ( | struct linear_fit_data * | lsf | ) |
Marlin 3D Printer Firmware Copyright (c) 2019 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.