25751a7b98
PiperOrigin-RevId: 909290647 Change-Id: I77ae2352b20abf96ef7b48ae32b03a1f4098604e
163 lines
8.1 KiB
C
163 lines
8.1 KiB
C
// Copyright 2021 DeepMind Technologies Limited
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef MUJOCO_SRC_ENGINE_ENGINE_UTIL_SOLVE_H_
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#define MUJOCO_SRC_ENGINE_ENGINE_UTIL_SOLVE_H_
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#include <mujoco/mjdata.h>
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#include <mujoco/mjexport.h>
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#include <mujoco/mjtnum.h>
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#ifdef __cplusplus
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extern "C" {
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#endif
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// Cholesky decomposition: mat = L*L'; return rank
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MJAPI int mju_cholFactor(mjtNum* mat, int n, mjtNum mindiag);
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// Cholesky solve
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MJAPI void mju_cholSolve(mjtNum* res, const mjtNum* mat, const mjtNum* vec, int n);
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// Cholesky rank-one update: L*L' +/- x*x'; return rank
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MJAPI int mju_cholUpdate(mjtNum* mat, mjtNum* x, int n, int flg_plus);
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// sparse reverse-order Cholesky decomposition: mat = L'*L; return 'rank'
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// mat must be lower-triangular, have preallocated space for fill-in
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MJAPI int mju_cholFactorSparse(mjtNum* mat, int n, mjtNum mindiag,
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int* rownnz, const int* rowadr, int* colind, mjData* d);
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// symbolic reverse-Cholesky: compute both L (CSR) and LT (CSC) structures
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// if L_colind is NULL, perform counting logic (fill rownnz/rowadr arrays and return total nnz)
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// if L_colind is not NULL, assume rownnz/rowadr are precomputed and fill colind/map arrays
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// reads pattern from upper triangle
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// based on ldl_symbolic from 'Algorithm 8xx: a concise sparse Cholesky factorization package'
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MJAPI int mju_cholFactorSymbolic(int* L_colind, int* L_rownnz, int* L_rowadr,
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int* LT_colind, int* LT_rownnz, int* LT_rowadr, int* LT_map,
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const int* rownnz, const int* rowadr, const int* colind,
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int n, mjData* d);
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// numeric reverse-Cholesky: compute L values given fixed sparsity pattern, returns rank
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// L_colind must already contain the correct sparsity pattern (from mju_cholFactorSymbolic)
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// LT_map[k] gives index in L for LT_colind[k]
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MJAPI int mju_cholFactorNumeric(mjtNum* L, int n, mjtNum mindiag,
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const int* L_rownnz, const int* L_rowadr, const int* L_colind,
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const int* LT_rownnz, const int* LT_rowadr, const int* LT_colind,
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const int* LT_map, const mjtNum* H,
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const int* H_rownnz, const int* H_rowadr, const int* H_colind,
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mjData* d);
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// sparse reverse-order Cholesky solve
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void mju_cholSolveSparse(mjtNum* res, const mjtNum* mat, const mjtNum* vec, int n,
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const int* rownnz, const int* rowadr, const int* colind);
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// sparse reverse-order Cholesky rank-one update: L'*L +/i x*x'; return rank
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// x is sparse, change in sparsity pattern of mat is not allowed
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MJAPI int mju_cholUpdateSparse(mjtNum* mat, const mjtNum* x, int n, int flg_plus,
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const int* rownnz, const int* rowadr, const int* colind,
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int x_nnz, const int* x_ind, mjData* d);
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// band-dense Cholesky decomposition
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// returns minimum value in the factorized diagonal, or 0 if rank-deficient
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// mat has (ntotal-ndense) x nband + ndense x ntotal elements
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// the first (ntotal-ndense) x nband store the band part, left of diagonal, inclusive
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// the second ndense x ntotal store the band part as entire dense rows
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// add diagadd+diagmul*mat_ii to diagonal before factorization
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MJAPI mjtNum mju_cholFactorBand(mjtNum* mat, int ntotal, int nband, int ndense,
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mjtNum diagadd, mjtNum diagmul);
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// solve (mat*mat')*res = vec with band-Cholesky decomposition
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MJAPI void mju_cholSolveBand(mjtNum* res, const mjtNum* mat, const mjtNum* vec,
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int ntotal, int nband, int ndense);
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// convert banded matrix to dense matrix, fill upper triangle if flg_sym>0
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MJAPI void mju_band2Dense(mjtNum* res, const mjtNum* mat, int ntotal, int nband, int ndense,
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mjtByte flg_sym);
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// convert dense matrix to banded matrix
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MJAPI void mju_dense2Band(mjtNum* res, const mjtNum* mat, int ntotal, int nband, int ndense);
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// multiply band-diagonal matrix with vector, include upper triangle if flg_sym>0
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MJAPI void mju_bandMulMatVec(mjtNum* res, const mjtNum* mat, const mjtNum* vec,
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int ntotal, int nband, int ndense, int nvec, mjtByte flg_sym);
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// address of diagonal element i in band-dense matrix representation
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MJAPI int mju_bandDiag(int i, int ntotal, int nband, int ndense);
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// dense LU factorization with partial pivoting
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// factorizes n x n row-major matrix A in-place into L and U
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// L has unit diagonal (not stored), U has explicit diagonal
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// pivot stores row permutation: row i of original = row pivot[i] of result
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// return 1 if successful, 0 if singular (diagonal element < mjMINVAL)
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MJAPI int mju_factorLU(mjtNum* A, int n, int* pivot);
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// solve A*x = b given LU factorization of A, LU and pivot are output of mju_factorLU
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MJAPI void mju_solveLU(mjtNum* x, const mjtNum* LU, const mjtNum* b, const int* pivot, int n);
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// sparse reverse-order LU factorization, assume tree topology (only dofs in index, if given)
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// LU = L + U; original = (U+I) * L; scratch is size n
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void mju_factorLUSparse(mjtNum *LU, int n, int* scratch,
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const int *rownnz, const int *rowadr, const int *colind, const int *index);
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// solve mat*res=vec given LU factorization of mat (only dofs in index, if given)
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void mju_solveLUSparse(mjtNum *res, const mjtNum *LU, const mjtNum* vec, int n,
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const int *rownnz, const int *rowadr, const int* diag, const int *colind,
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const int *index);
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// solve 3x3 linear system A*x = b using Gaussian elimination
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void mju_solve3(mjtNum x[3], const mjtNum A[9], const mjtNum b[3]);
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// eigenvalue decomposition of symmetric 3x3 matrix
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MJAPI int mju_eig3(mjtNum eigval[3], mjtNum eigvec[9], mjtNum quat[4], const mjtNum mat[9]);
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// solve QCQP in 2 dimensions:
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// min 0.5*x'*A*x + x'*b s.t. sum (xi/di)^2 <= r^2
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// return 0 if unconstrained, 1 if constrained
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MJAPI int mju_QCQP2(mjtNum* res, const mjtNum* Ain, const mjtNum* bin, const mjtNum* d, mjtNum r);
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// solve QCQP in 3 dimensions:
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// min 0.5*x'*A*x + x'*b s.t. sum (xi/di)^2 <= r^2
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// return 0 if unconstrained, 1 if constrained
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MJAPI int mju_QCQP3(mjtNum* res, const mjtNum* Ain, const mjtNum* bin, const mjtNum* d, mjtNum r);
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// solve QCQP in n<=5 dimensions:
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// min 0.5*x'*A*x + x'*b s.t. sum (xi/di)^2 <= r^2
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// return 0 if unconstrained, 1 if constrained
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int mju_QCQP(mjtNum* res, const mjtNum* Ain, const mjtNum* bin, const mjtNum* d, mjtNum r, int n);
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// solve box-constrained Quadratic Program
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// min 0.5*x'*H*x + x'*g s.t. lower <= x <=upper
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// return rank of unconstrained subspace or -1 on failure
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MJAPI int mju_boxQP(mjtNum* res, mjtNum* R, int* index,
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const mjtNum* H, const mjtNum* g, int n,
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const mjtNum* lower, const mjtNum* upper);
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// allocate memory for box-constrained Quadratic Program
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MJAPI void mju_boxQPmalloc(mjtNum** res, mjtNum** R, int** index,
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mjtNum** H, mjtNum** g, int n,
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mjtNum** lower, mjtNum** upper);
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// minimize 0.5*x'*H*x + x'*g s.t. lower <= x <=upper, explicit options (see implementation)
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MJAPI int mju_boxQPoption(mjtNum* res, mjtNum* R, int* index,
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const mjtNum* H, const mjtNum* g, int n,
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const mjtNum* lower, const mjtNum* upper,
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int maxiter, mjtNum mingrad, mjtNum backtrack,
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mjtNum minstep, mjtNum armijo,
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char* log, int logsz);
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#ifdef __cplusplus
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}
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#endif
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#endif // MUJOCO_SRC_ENGINE_ENGINE_UTIL_SOLVE_H_
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