Provide improved mju_sqrMatTDSparse implementation that doesn't require dense memory allocation for sparse matrices.
PiperOrigin-RevId: 516812783 Change-Id: Ieb43337831d8d3b2c7f18a7facd8e0a0f2b0eff5
This commit is contained in:
Kyle Bayes
committed by
Copybara-Service
Copybara-Service
parent
fe18e58ad2
commit
056e849273
+1
-1
@@ -18,7 +18,7 @@ General
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~500,000 ``mjtNum``'s, now only requires ~6000. Very large models can now load and run with the CG solver.
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- Modified :ref:`mju_error` and :ref:`mju_warning` to be variadic functions (support for printf-like arguments). The
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functions :ref:`mju_error_i`, :ref:`mju_error_s`, :ref:`mju_warning_i`, and :ref:`mju_warning_s` are now deprecated.
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- Implemented a performant :ref:`mju_sqrMatTDSparse` function that doesn't require dense memory allocation.
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Python bindings
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@@ -1699,7 +1699,6 @@ void mj_projectConstraint(const mjModel* m, mjData* d) {
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int* rownnzT = (int*)mj_stackAlloc(d, nv);
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int* rowadrT = (int*)mj_stackAlloc(d, nv);
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int* colindT = (int*)mj_stackAlloc(d, nv*nefc);
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int* rowsuperT = (int*)mj_stackAlloc(d, nv);
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// construct JM2 = backsubM2(J')' by rows
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for (int r=0; r<nefc; r++) {
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@@ -1786,12 +1785,11 @@ void mj_projectConstraint(const mjModel* m, mjData* d) {
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// construct supernodes
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mju_superSparse(nefc, rowsuper, rownnz, rowadr, colind);
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mju_superSparse(nv, rowsuperT, rownnzT, rowadrT, colindT);
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// AR = JM2 * JM2', uncompressed layout
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mju_sqrMatTDSparse(d->efc_AR, JM2T, JM2, NULL, nv, nefc,
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d->efc_AR_rownnz, d->efc_AR_rowadr, d->efc_AR_colind,
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rownnzT, rowadrT, colindT, rowsuperT,
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rownnzT, rowadrT, colindT, NULL,
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rownnz, rowadr, colind, rowsuper, d);
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// compress layout of AR
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@@ -1365,7 +1365,7 @@ static void HessianDirect(const mjModel* m, mjData* d, mjCGContext* ctx) {
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mju_sqrMatTDSparse(ctx->H, d->efc_J, d->efc_JT, D, nefc, nv,
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ctx->rownnz, ctx->rowadr, ctx->colind,
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d->efc_J_rownnz, d->efc_J_rowadr,
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d->efc_J_colind, d->efc_J_rowsuper,
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d->efc_J_colind, NULL,
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d->efc_JT_rownnz, d->efc_JT_rowadr,
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d->efc_JT_colind, d->efc_JT_rowsuper, d);
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+96
-123
@@ -377,6 +377,7 @@ void mju_transposeSparse(mjtNum* res, const mjtNum* mat, int nr, int nc,
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}
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// construct row supernodes
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void mju_superSparse(int nr, int* rowsuper,
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const int* rownnz, const int* rowadr, const int* colind) {
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@@ -417,149 +418,121 @@ void mju_sqrMatTDSparse(mjtNum* res, const mjtNum* mat, const mjtNum* matT,
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int* res_rownnz, int* res_rowadr, int* res_colind,
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const int* rownnz, const int* rowadr,
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const int* colind, const int* rowsuper,
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const int* rownnzT, const int* rowadrT,
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const int* colindT, const int* rowsuperT,
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const int* rownnzT, const int* rowadrT,
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const int* colindT, const int* rowsuperT,
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mjData* d) {
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// allocate space for accumulation buffer and matT
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mjMARKSTACK;
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int* chain = (int*) mj_stackAlloc(d, 2*nc);
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mjtNum* buffer = mj_stackAlloc(d, nc);
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// set uncompressed layout
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// set uncompressed layout (the following doesn't depend on this layout)
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for (int r=0; r<nc; r++) {
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res_rowadr[r] = r*nc;
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}
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// compute lower-triangular uncompressed layout (nc per row)
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for (int r=0; r<nc; r++) {
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// copy chain from parent
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if (rowsuperT && r>0 && rowsuperT[r-1]>0) {
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// copy parent chain
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res_rownnz[r] = res_rownnz[r-1];
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memcpy(res_colind+res_rowadr[r], res_colind+res_rowadr[r-1],
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res_rownnz[r]*sizeof(int));
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// a dense row buffer that stores the current row in the resulting matrix
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mjtNum* buffer = mj_stackAlloc(d, nc);
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// add diagonal if rowT is not empty
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if (rownnzT[r]) {
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res_colind[res_rowadr[r]+res_rownnz[r]] = r;
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res_rownnz[r]++;
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}
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// these mark the currently set columns in the dense row buffer,
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// used for when creating the resulting sparse row
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int* markers = (int*) mj_stackAlloc(d, nc);
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for (int i=0; i<nc; i++) {
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int* cols = res_colind+res_rowadr[i];
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res_rownnz[i] = 0;
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buffer[i] = 0;
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markers[i] = 0;
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// if rowsuper, use the previous row sparsity structure
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if (rowsuperT && i>0 && rowsuperT[i-1]) {
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res_rownnz[i] = res_rownnz[i-1];
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memcpy(cols, res_colind+res_rowadr[i-1], res_rownnz[i]*sizeof(int));
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}
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// construct chain
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else {
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// clear chain accumulation buffers
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int nchain = 0;
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int inew = 0, iold = nc;
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int lastadded = -1;
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// for each nonzero c in matT_row(r), add nonzeros of mat_row(c) to chain(r)
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for (int i=0; i<rownnzT[r]; i++) {
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// save c
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int c = colindT[rowadrT[r]+i];
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// skip if a chain from same supernode was already added
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if (rowsuper && lastadded>=0 && (c-lastadded)<=rowsuper[lastadded]) {
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continue;
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} else {
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lastadded = c;
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}
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// swap chains
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int adr = inew;
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inew = iold;
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iold = adr;
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// merge chains
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int nnewchain = 0;
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adr = 0;
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int end = rowadr[c]+rownnz[c];
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for (int adr1=rowadr[c]; adr1<end; adr1++) {
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// save column index from mat
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int col_mat = colind[adr1];
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// skip column indices in chain smaller than col_mat
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while (adr<nchain && chain[iold + adr]<col_mat && chain[iold + adr]<=r) {
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chain[inew + nnewchain++] = chain[iold + adr++];
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}
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// only lower-triangular
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if (col_mat>r) {
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break;
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}
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// existing element: advance chain
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if (adr<nchain && chain[iold + adr]==col_mat) {
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adr++;
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}
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// add column index from matT
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chain[inew + nnewchain++] = col_mat;
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}
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// append the rest of the master chain
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while (adr<nchain && chain[iold + adr]<=r) {
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chain[inew + nnewchain++] = chain[iold + adr++];
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}
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// assign newchain
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nchain = nnewchain;
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}
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// copy chain
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res_rownnz[r] = nchain;
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if (nchain) {
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memcpy(res_colind+res_rowadr[r], chain+inew, nchain*sizeof(int));
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}
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}
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}
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// compute matrix data given uncompressed layout
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for (int r=0; r<nc; r++) {
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// clear buffer[colind] for this chain
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int adr = res_rowadr[r];
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for (int i=0; i<res_rownnz[r]; i++) {
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buffer[res_colind[adr+i]] = 0;
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}
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// res_row(r) = sum_c ( matT(r,c) * diag(c) * mat_row(c) )
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for (int i=0; i<rownnzT[r]; i++) {
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// save c and matT(r,c)*diag(c)
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int c = colindT[rowadrT[r]+i];
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mjtNum matTrc = matT[rowadrT[r]+i];
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if (diag) {
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matTrc *= diag[c];
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}
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// process row
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int end = rowadr[c]+rownnz[c];
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for (int adr=rowadr[c]; adr<end; adr++) {
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// get column index from mat, only lower-triangular
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int adr1;
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if ((adr1=colind[adr])>r) {
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// iterate through each row of M'
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int end = rowadrT[i] + rownnzT[i];
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for (int r = rowadrT[i]; r<end; r++) {
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int t = colindT[r];
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mjtNum v = diag ? matT[r] * diag[t] : matT[r];
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for (int c=rowadr[t]; c<rowadr[t]+rownnz[t]; c++) {
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int cc = colind[c];
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// ignore upper triangle
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if (cc>i) {
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break;
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}
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// add to buffer
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buffer[adr1] += matTrc*mat[adr];
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buffer[cc] += v*mat[c];
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// only need to insert nnz if not marked
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if (!markers[cc]) {
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markers[cc] = 1;
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// since i is the rightmost column, it can be inserted at the end
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if (cc==i) {
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cols[res_rownnz[i]++] = cc;
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continue;
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}
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// insert col in order via binary search
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int l = 0, h = res_rownnz[i];
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while (l<h) {
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int m = (l + h) >> 1;
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if (cols[m]<cc) {
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l = m + 1;
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} else {
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h = m;
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}
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}
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// cc is the rightmost column so far, it can be inserted at the end
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if (l==res_rownnz[i]) {
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cols[l] = cc;
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res_rownnz[i]++;
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continue;
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}
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// move the cols to the right
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h = res_rownnz[i];
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while (l<h) {
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cols[h] = cols[h-1];
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h--;
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}
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// insert
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cols[l] = cc;
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res_rownnz[i]++;
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}
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}
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}
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// copy buffer
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adr = res_rowadr[r];
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for (int i=0; i<res_rownnz[r]; i++) {
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res[adr+i] = buffer[res_colind[adr+i]];
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end = res_rownnz[i];
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// rowsuperT: reuse sparsity, copy into res
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if (rowsuperT && rowsuperT[i]) {
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for (int r=0; r<end; r++) {
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res[res_rowadr[i] + r] = buffer[cols[r]];
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buffer[cols[r]] = 0;
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}
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} else {
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// clear out buffers since sparsity cannot be reused
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for (int r=0; r<end; r++) {
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int cc = cols[r];
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res[res_rowadr[i] + r] = buffer[cc];
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res_colind[res_rowadr[i] + r] = cc;
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buffer[cc] = 0;
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markers[cc] = 0;
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}
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}
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}
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// make symmetric; uncompressed layout
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for (int r=1; r<nc; r++) {
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int end = nc*r+res_rownnz[r]-1;
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for (int adr=nc*r; adr<end; adr++) {
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// add to row given by column index
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int adr1 = nc*res_colind[adr] + res_rownnz[res_colind[adr]]++;
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res[adr1] = res[adr];
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res_colind[adr1] = r;
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// fill upper triangle
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for (int i=0; i<nc; i++) {
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int end = res_rowadr[i] + res_rownnz[i] - 1;
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for (int j=res_rowadr[i]; j<end; j++) {
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int adr = res_rowadr[res_colind[j]] + res_rownnz[res_colind[j]]++;
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res[adr] = res[j];
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res_colind[adr] = i;
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}
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}
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@@ -66,8 +66,8 @@ MJAPI void mju_transposeSparse(mjtNum* res, const mjtNum* mat, int nr, int nc,
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const int* rownnz, const int* rowadr, const int* colind);
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// construct row supernodes
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void mju_superSparse(int nr, int* rowsuper,
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const int* rownnz, const int* rowadr, const int* colind);
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MJAPI void mju_superSparse(int nr, int* rowsuper,
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const int* rownnz, const int* rowadr, const int* colind);
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// compute sparse M'*diag*M (diag=NULL: compute M'*M), res has uncompressed layout
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MJAPI void mju_sqrMatTDSparse(mjtNum* res, const mjtNum* mat, const mjtNum* matT,
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@@ -28,6 +28,7 @@ namespace {
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using CombineFuncPtr = decltype(&mju_combineSparse);
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using TransposeFuncPtr = decltype(&mju_transposeSparse);
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using SqrMatTDFuncPtr = decltype(&mju_sqrMatTDSparse);
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// number of steps to roll out before benchmarking
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static const int kNumWarmupSteps = 500;
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@@ -39,6 +40,117 @@ std::vector<mjtNum> AsVector(const mjtNum* array, int n) {
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// ----------------------------- old functions --------------------------------
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void ABSL_ATTRIBUTE_NOINLINE mju_sqrMatTDSparse_baseline(
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mjtNum* res, const mjtNum* mat, const mjtNum* matT, const mjtNum* diag,
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int nr, int nc, int* res_rownnz, int* res_rowadr, int* res_colind,
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const int* rownnz, const int* rowadr, const int* colind,
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const int* rowsuper, const int* rownnzT, const int* rowadrT,
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const int* colindT, const int* rowsuperT, mjData* d) {
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mjMARKSTACK;
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int* chain = (int*)mj_stackAlloc(d, 2 * nc);
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mjtNum* buffer = mj_stackAlloc(d, nc);
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for (int r = 0; r < nc; r++) {
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res_rowadr[r] = r * nc;
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}
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for (int r = 0; r < nc; r++) {
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if (rowsuperT && r > 0 && rowsuperT[r - 1] > 0) {
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res_rownnz[r] = res_rownnz[r - 1];
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memcpy(res_colind + res_rowadr[r], res_colind + res_rowadr[r - 1],
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res_rownnz[r] * sizeof(int));
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if (rownnzT[r]) {
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res_colind[res_rowadr[r] + res_rownnz[r]] = r;
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res_rownnz[r]++;
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}
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} else {
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int nchain = 0;
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int inew = 0, iold = nc;
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int lastadded = -1;
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for (int i = 0; i < rownnzT[r]; i++) {
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int c = colindT[rowadrT[r] + i];
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if (rowsuper && lastadded >= 0 &&
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(c - lastadded) <= rowsuper[lastadded]) {
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continue;
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} else {
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lastadded = c;
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}
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int adr = inew;
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inew = iold;
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iold = adr;
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int nnewchain = 0;
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adr = 0;
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int end = rowadr[c] + rownnz[c];
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for (int adr1 = rowadr[c]; adr1 < end; adr1++) {
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int col_mat = colind[adr1];
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while (adr < nchain && chain[iold + adr] < col_mat &&
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chain[iold + adr] <= r) {
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chain[inew + nnewchain++] = chain[iold + adr++];
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}
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if (col_mat > r) {
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break;
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}
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if (adr < nchain && chain[iold + adr] == col_mat) {
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adr++;
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}
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chain[inew + nnewchain++] = col_mat;
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}
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while (adr < nchain && chain[iold + adr] <= r) {
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chain[inew + nnewchain++] = chain[iold + adr++];
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}
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nchain = nnewchain;
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}
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res_rownnz[r] = nchain;
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if (nchain) {
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memcpy(res_colind + res_rowadr[r], chain + inew, nchain * sizeof(int));
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}
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}
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}
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for (int r = 0; r < nc; r++) {
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int adr = res_rowadr[r];
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for (int i = 0; i < res_rownnz[r]; i++) {
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buffer[res_colind[adr + i]] = 0;
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}
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for (int i = 0; i < rownnzT[r]; i++) {
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int c = colindT[rowadrT[r] + i];
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mjtNum matTrc = matT[rowadrT[r] + i];
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if (diag) {
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matTrc *= diag[c];
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}
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int end = rowadr[c] + rownnz[c];
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for (int adr = rowadr[c]; adr < end; adr++) {
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int adr1;
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if ((adr1 = colind[adr]) > r) {
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break;
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}
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buffer[adr1] += matTrc * mat[adr];
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}
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}
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adr = res_rowadr[r];
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for (int i = 0; i < res_rownnz[r]; i++) {
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res[adr + i] = buffer[res_colind[adr + i]];
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}
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}
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for (int r = 1; r < nc; r++) {
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int end = res_rowadr[r] + res_rownnz[r] - 1;
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for (int adr = res_rowadr[r]; adr < end; adr++) {
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int adr1 = res_rowadr[res_colind[adr]] + res_rownnz[res_colind[adr]]++;
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res[adr1] = res[adr];
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res_colind[adr1] = r;
|
||||
}
|
||||
}
|
||||
|
||||
mjFREESTACK;
|
||||
}
|
||||
|
||||
// transpose sparse matrix (uncompressed)
|
||||
void ABSL_ATTRIBUTE_NOINLINE transposeSparse_baseline(
|
||||
mjtNum* res, const mjtNum* mat, int nr, int nc, int* res_rownnz,
|
||||
@@ -426,8 +538,79 @@ BM_transposeSparse_old(benchmark::State& state) {
|
||||
MujocoErrorTestGuard guard;
|
||||
BM_transposeSparse(state, &transposeSparse_baseline);
|
||||
}
|
||||
|
||||
BENCHMARK(BM_transposeSparse_old);
|
||||
|
||||
static void BM_sqrMatTDSparse(benchmark::State& state, SqrMatTDFuncPtr func) {
|
||||
static mjModel* m = LoadModelFromPath("humanoid100/humanoid100.xml");
|
||||
mjData* d = mj_makeData(m);
|
||||
|
||||
// force use of sparse matrices
|
||||
m->opt.jacobian = mjJAC_SPARSE;
|
||||
|
||||
// warm-up rollout to get a typical state
|
||||
while (d->time < 2) {
|
||||
mj_step(m, d);
|
||||
}
|
||||
|
||||
// allocate
|
||||
mjMARKSTACK;
|
||||
mjtNum* H = mj_stackAlloc(d, m->nv * m->nv);
|
||||
int* rownnz = (int*)mj_stackAlloc(d, m->nv);
|
||||
int* rowadr = (int*)mj_stackAlloc(d, m->nv);
|
||||
int* colind = (int*)mj_stackAlloc(d, m->nv * m->nv);
|
||||
|
||||
// compute D corresponding to quad states
|
||||
mjtNum* D = mj_stackAlloc(d, d->nefc);
|
||||
for (int i = 0; i < d->nefc; i++) {
|
||||
if (d->efc_state[i] == mjCNSTRSTATE_QUADRATIC) {
|
||||
D[i] = d->efc_D[i];
|
||||
} else {
|
||||
D[i] = 0;
|
||||
}
|
||||
}
|
||||
|
||||
// time benchmark
|
||||
if (func) {
|
||||
for (auto s : state) {
|
||||
// compute H = J'*D*J, uncompressed layout
|
||||
func(H, d->efc_J, d->efc_JT, D, d->nefc, m->nv, rownnz, rowadr, colind,
|
||||
d->efc_J_rownnz, d->efc_J_rowadr, d->efc_J_colind, NULL,
|
||||
d->efc_JT_rownnz, d->efc_JT_rowadr, d->efc_JT_colind,
|
||||
d->efc_JT_rowsuper, d);
|
||||
}
|
||||
} else {
|
||||
for (auto s : state) {
|
||||
// baseline depends on efc_J_rowsuper
|
||||
mju_superSparse(d->nefc, d->efc_J_rowsuper,
|
||||
d->efc_J_rownnz, d->efc_J_rowadr, d->efc_J_colind);
|
||||
|
||||
// compute H = J'*D*J, uncompressed layout
|
||||
mju_sqrMatTDSparse_baseline(H, d->efc_J, d->efc_JT, D, d->nefc, m->nv, rownnz, rowadr, colind,
|
||||
d->efc_J_rownnz, d->efc_J_rowadr, d->efc_J_colind, d->efc_J_rowsuper,
|
||||
d->efc_JT_rownnz, d->efc_JT_rowadr, d->efc_JT_colind,
|
||||
d->efc_JT_rowsuper, d);
|
||||
}
|
||||
}
|
||||
|
||||
// finalize
|
||||
mjFREESTACK;
|
||||
mj_deleteData(d);
|
||||
state.SetItemsProcessed(state.iterations());
|
||||
}
|
||||
|
||||
void ABSL_ATTRIBUTE_NO_TAIL_CALL
|
||||
BM_sqrMatTDSparse_new(benchmark::State& state) {
|
||||
MujocoErrorTestGuard guard;
|
||||
BM_sqrMatTDSparse(state, &mju_sqrMatTDSparse);
|
||||
}
|
||||
BENCHMARK(BM_sqrMatTDSparse_new);
|
||||
|
||||
void ABSL_ATTRIBUTE_NO_TAIL_CALL
|
||||
BM_sqrMatTDSparse_old(benchmark::State& state) {
|
||||
MujocoErrorTestGuard guard;
|
||||
BM_sqrMatTDSparse(state, nullptr);
|
||||
}
|
||||
BENCHMARK(BM_sqrMatTDSparse_old);
|
||||
|
||||
} // namespace
|
||||
} // namespace mujoco
|
||||
|
||||
@@ -18,6 +18,7 @@
|
||||
|
||||
#include <gmock/gmock.h>
|
||||
#include <gtest/gtest.h>
|
||||
#include <mujoco/mujoco.h>
|
||||
#include "test/fixture.h"
|
||||
|
||||
namespace mujoco {
|
||||
@@ -180,5 +181,549 @@ TEST_F(EngineUtilSparseTest, MjuTransposeNullMatrix) {
|
||||
EXPECT_THAT(rowadrT, ElementsAre(0, 0, 0, 0, 0, 0, 0, 0, 0, 0));
|
||||
}
|
||||
|
||||
static constexpr char modelStr[] = R"(<mujoco/>)";
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse1) {
|
||||
// 0 0 0
|
||||
// M = 0 0 0
|
||||
// 0 0 0
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colind[] = {0, 1, 2, 0, 1, 2, 0, 1, 2};
|
||||
int rownnz[] = {3, 3, 3};
|
||||
int rowadr[] = {0, 3, 6};
|
||||
|
||||
mjtNum matT[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindT[] = {0, 1, 2, 0, 1, 2, 0, 1, 2};
|
||||
int rownnzT[] = {3, 3, 3};
|
||||
int rowadrT[] = {0, 3, 6};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, NULL, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(0, 0, 0, 0, 0, 0, 0, 0, 0));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 2, 0, 1, 2, 0, 1, 2));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(3, 3, 3));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse2) {
|
||||
// 2 -1 1
|
||||
// M = 1 2 -1
|
||||
// 2 2 3
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {2, -1, 1, 2, -1, 2, 2, 2, 3};
|
||||
int colind[] = {0, 1, 2, 0, 1, 2, 0, 1, 2};
|
||||
int rownnz[] = {3, 3, 3};
|
||||
int rowadr[] = {0, 3, 6};
|
||||
|
||||
mjtNum matT[] = {2, 2, 2, -1, -1, 2, 1, 2, 3};
|
||||
int colindT[] = {0, 1, 2, 0, 1, 2, 0, 1, 2};
|
||||
int rownnzT[] = {3, 3, 3};
|
||||
int rowadrT[] = {0, 3, 6};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, NULL, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(12, 0, 12, 0, 6, 3, 12, 3, 14));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 2, 0, 1, 2, 0, 1, 2));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(3, 3, 3));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse3) {
|
||||
// 1 2 0
|
||||
// M = 0 3 0
|
||||
// 4 0 0
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 2, 3, 4};
|
||||
int colind[] = {0, 1, 1, 0};
|
||||
int rownnz[] = {2, 1, 1};
|
||||
int rowadr[] = {0, 2, 3};
|
||||
|
||||
mjtNum matT[] = {1, 4, 2, 3};
|
||||
int colindT[] = {0, 2, 0, 1};
|
||||
int rownnzT[] = {2, 2, 0};
|
||||
int rowadrT[] = {0, 2, 4};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mjtNum diag[] = {2, 3, 4};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(66, 4, 0, 4, 35, 0, 0, 0, 0));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 0, 0, 1, 0, 0, 0, 0));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(2, 2, 0));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse4) {
|
||||
// 1 0 2
|
||||
// M = 0 0 3
|
||||
// 4 0 0
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 2, 3, 4};
|
||||
int colind[] = {0, 2, 2, 0};
|
||||
int rownnz[] = {2, 1, 1};
|
||||
int rowadr[] = {0, 2, 3};
|
||||
|
||||
mjtNum matT[] = {1, 4, 2, 3};
|
||||
int colindT[] = {0, 2, 0, 1};
|
||||
int rownnzT[] = {2, 0, 2};
|
||||
int rowadrT[] = {0, 2, 2};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mjtNum diag[] = {2, 3, 4};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(66, 4, 0, 0, 0, 0, 4, 35, 0));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 2, 0, 0, 0, 0, 0, 2, 0));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(2, 0, 2));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse5) {
|
||||
// 1 0 4
|
||||
// M = 0 0 0
|
||||
// 2 3 0
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 4, 2, 3};
|
||||
int colind[] = {0, 2, 0, 1};
|
||||
int rownnz[] = {2, 0, 2};
|
||||
int rowadr[] = {0, 2, 2};
|
||||
|
||||
mjtNum matT[] = {1, 2, 3, 4};
|
||||
int colindT[] = {0, 2, 2, 0};
|
||||
int rownnzT[] = {2, 1, 1};
|
||||
int rowadrT[] = {0, 2, 3};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, NULL, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(5, 6, 4, 6, 9, 0, 4, 16, 0));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 2, 0, 1, 0, 0, 2, 0));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(3, 2, 2));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse6) {
|
||||
// 1 0 2
|
||||
// M = 0 2 0
|
||||
// 0 0 3
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 2, 2, 3};
|
||||
int colind[] = {0, 2, 1, 2};
|
||||
int rownnz[] = {2, 1, 1};
|
||||
int rowadr[] = {0, 2, 3};
|
||||
|
||||
mjtNum matT[] = {1, 2, 2, 3};
|
||||
int colindT[] = {0, 1, 0, 2};
|
||||
int rownnzT[] = {1, 1, 2};
|
||||
int rowadrT[] = {0, 1, 2};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, NULL, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(1, 2, 0, 4, 0, 0, 2, 13, 0));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 2, 0, 1, 0, 0, 0, 2, 0));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(2, 1, 2));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse7) {
|
||||
// 1 2
|
||||
// M = 0 3
|
||||
// 4 0
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 2, 3, 4};
|
||||
int colind[] = {0, 1, 1, 0};
|
||||
int rownnz[] = {2, 1, 1};
|
||||
int rowadr[] = {0, 2, 3};
|
||||
|
||||
mjtNum matT[] = {1, 4, 2, 3};
|
||||
int colindT[] = {0, 2, 0, 1};
|
||||
int rownnzT[] = {2, 2};
|
||||
int rowadrT[] = {0, 2};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0};
|
||||
int rowadrH[] = {0, 0};
|
||||
|
||||
mjtNum diag[] = {2, 3, 4};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 3, 2, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(66, 4, 4, 35));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 0, 1));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(2, 2));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 2));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse8) {
|
||||
// M = 1 0 4
|
||||
// 2 3 0
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 4, 2, 3};
|
||||
int colind[] = {0, 2, 0, 1};
|
||||
int rownnz[] = {2, 2};
|
||||
int rowadr[] = {0, 2};
|
||||
|
||||
mjtNum matT[] = {1, 2, 3, 4};
|
||||
int colindT[] = {0, 1, 1, 0};
|
||||
int rownnzT[] = {2, 1, 1};
|
||||
int rowadrT[] = {0, 2, 3};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mjtNum diag[] = {2, 3};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 2, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(14, 18, 8, 18, 27, 0, 8, 32, 0));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 2, 0, 1, 0, 0, 2, 0));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(3, 2, 2));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse9) {
|
||||
// 1 2 2
|
||||
// M = 1 3 4
|
||||
// 4 4 4
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 2, 2, 1, 3, 4, 4, 4, 4};
|
||||
int colind[] = {0, 1, 2, 0, 1, 2, 0, 1, 2};
|
||||
int rownnz[] = {3, 3, 3};
|
||||
int rowadr[] = {0, 3, 6};
|
||||
|
||||
mjtNum matT[] = {1, 1, 4, 2, 3, 4, 2, 4, 4};
|
||||
int colindT[] = {0, 1, 2, 0, 1, 2, 0, 1, 2};
|
||||
int rownnzT[] = {3, 3, 3};
|
||||
int rowadrT[] = {0, 3, 6};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mjtNum diag[] = {2, 3, 4};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
NULL, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(69, 77, 80, 77, 99, 108, 80, 108, 120));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 2, 0, 1, 2, 0, 1, 2));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(3, 3, 3));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse10) {
|
||||
// 1 1 1
|
||||
// M = 2 2 2
|
||||
// 3 3 3
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 1, 1, 2, 2, 2, 3, 3, 3};
|
||||
int colind[] = {0, 1, 2, 0, 1, 2, 0, 1, 2};
|
||||
int rownnz[] = {3, 3, 3};
|
||||
int rowadr[] = {0, 3, 6};
|
||||
|
||||
mjtNum matT[] = {1, 2, 3, 1, 2, 3, 1, 2, 3};
|
||||
int colindT[] = {0, 1, 2, 0, 1, 2, 0, 1, 2};
|
||||
int rownnzT[] = {3, 3, 3};
|
||||
int rowadrT[] = {0, 3, 6};
|
||||
int superowT[] = {2, 1, 0};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mjtNum diag[] = {1, 1, 1};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
superowT, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(14, 14, 14, 14, 14, 14, 14, 14, 14));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 2, 0, 1, 2, 0, 1, 2));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(3, 3, 3));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse11) {
|
||||
// 1 1 1
|
||||
// M = 0 0 0
|
||||
// 0 3 3
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 1, 1, 3, 3};
|
||||
int colind[] = {0, 1, 2, 1, 2};
|
||||
int rownnz[] = {3, 0, 2};
|
||||
int rowadr[] = {0, 3, 3};
|
||||
|
||||
mjtNum matT[] = {1, 1, 3, 1, 3};
|
||||
int colindT[] = {0, 0, 2, 0, 2};
|
||||
int rownnzT[] = {1, 2, 2};
|
||||
int rowadrT[] = {0, 1, 3};
|
||||
int superowT[] = {0, 1, 0};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0};
|
||||
|
||||
mjtNum diag[] = {1, 1, 1};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 3, 3, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
superowT, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(1, 1, 1, 1, 10, 10, 1, 10, 10));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 2, 0, 1, 2, 0, 1, 2));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(3, 3, 3));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 3, 6));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse12) {
|
||||
// 1 1 1 1
|
||||
// M = 0 0 0 0
|
||||
// 0 0 3 3
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 1, 1, 1, 3, 3};
|
||||
int colind[] = {0, 1, 2, 3, 2, 3};
|
||||
int rownnz[] = {4, 0, 2};
|
||||
int rowadr[] = {0, 4, 4};
|
||||
|
||||
mjtNum matT[] = {1, 1, 1, 3, 1, 3};
|
||||
int colindT[] = {0, 0, 0, 2, 0, 2};
|
||||
int rownnzT[] = {1, 1, 2, 2};
|
||||
int rowadrT[] = {0, 1, 2, 4};
|
||||
int superowT[] = {1, 0, 1, 0};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0, 0};
|
||||
|
||||
mjtNum diag[] = {1, 1, 1};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 3, 4, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
superowT, data);
|
||||
|
||||
EXPECT_THAT(matH,
|
||||
ElementsAre(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 10, 10, 1, 1, 10, 10));
|
||||
EXPECT_THAT(colindH,
|
||||
ElementsAre(0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(4, 4, 4, 4));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 4, 8, 12));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse13) {
|
||||
// 1 1 0 0 0
|
||||
// M = 1 1 0 0 0
|
||||
// 1 1 0 0 0
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 1, 1, 1, 1, 1};
|
||||
int colind[] = {0, 1, 0, 1, 0, 1};
|
||||
int rownnz[] = {2, 2, 2};
|
||||
int rowadr[] = {0, 2, 4};
|
||||
|
||||
mjtNum matT[] = {1, 1, 1, 1, 1, 1};
|
||||
int colindT[] = {0, 1, 2, 0, 1, 2};
|
||||
int rownnzT[] = {3, 3, 0, 0, 0};
|
||||
int rowadrT[] = {0, 3, 6, 6, 6};
|
||||
int superowT[] = {1, 0, 2, 1, 0};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0, 0, 0};
|
||||
|
||||
mjtNum diag[] = {1, 1, 1};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, diag, 3, 5, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
superowT, data);
|
||||
|
||||
EXPECT_THAT(matH, ElementsAre(3, 3, 0, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0));
|
||||
EXPECT_THAT(colindH, ElementsAre(0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(2, 2, 0, 0, 0));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 5, 10, 15, 20));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
TEST_F(EngineUtilSparseTest, MjuSqrMatTDSparse14) {
|
||||
// M = 1 1 1 1 2 2 2
|
||||
|
||||
mjModel* model = LoadModelFromString(modelStr);
|
||||
mjData* data = mj_makeData(model);
|
||||
|
||||
mjtNum mat[] = {1, 1, 1, 1, 2, 2, 2};
|
||||
int colind[] = {0, 1, 2, 3, 4, 5, 6};
|
||||
int rownnz[] = {7};
|
||||
int rowadr[] = {0};
|
||||
|
||||
mjtNum matT[] = {1, 1, 1, 1, 2, 2, 2};
|
||||
int colindT[] = {0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzT[] = {1, 1, 1, 1, 1, 1, 1};
|
||||
int rowadrT[] = {0, 1, 2, 3, 4, 5, 6};
|
||||
int superowT[] = {3, 2, 1, 0, 2, 1, 0};
|
||||
|
||||
mjtNum matH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int colindH[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
|
||||
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int rownnzH[] = {0, 0, 0, 0, 0, 0, 0};
|
||||
int rowadrH[] = {0, 0, 0, 0, 0, 0, 0};
|
||||
|
||||
mju_sqrMatTDSparse(matH, mat, matT, NULL, 1, 7, rownnzH, rowadrH, colindH,
|
||||
rownnz, rowadr, colind, NULL, rownnzT, rowadrT, colindT,
|
||||
superowT, data);
|
||||
|
||||
EXPECT_THAT(
|
||||
matH, ElementsAre(1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2,
|
||||
2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 2, 2, 2,
|
||||
2, 4, 4, 4, 2, 2, 2, 2, 4, 4, 4));
|
||||
EXPECT_THAT(colindH,
|
||||
ElementsAre(0, 1, 2, 3, 4, 5, 6, 0, 1, 2, 3, 4, 5, 6, 0, 1, 2, 3,
|
||||
4, 5, 6, 0, 1, 2, 3, 4, 5, 6, 0, 1, 2, 3, 4, 5, 6, 0,
|
||||
1, 2, 3, 4, 5, 6, 0, 1, 2, 3, 4, 5, 6
|
||||
|
||||
));
|
||||
EXPECT_THAT(rownnzH, ElementsAre(7, 7, 7, 7, 7, 7, 7));
|
||||
EXPECT_THAT(rowadrH, ElementsAre(0, 7, 14, 21, 28, 35, 42));
|
||||
|
||||
mj_deleteData(data);
|
||||
mj_deleteModel(model);
|
||||
}
|
||||
|
||||
} // namespace
|
||||
} // namespace mujoco
|
||||
|
||||
Reference in New Issue
Block a user