Improve comments in mju_cholFactorNNZ, clarify that this function reads from the upper triangle of the source matrix.
PiperOrigin-RevId: 686113654 Change-Id: I029f9279d177f4cb9ff60396a26d64821aee3a6c
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Copybara-Service
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@@ -857,8 +857,9 @@ void mju_sqrMatTDSparse(mjtNum* res, const mjtNum* mat, const mjtNum* matT,
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mj_freeStack(d);
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}
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// compute row non-zeros of reverse-Cholesky factor L, return total
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// compute row non-zeros of reverse-Cholesky factor L, return total non-zeros
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// based on ldl_symbolic from 'Algorithm 8xx: a concise sparse Cholesky factorization package'
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// note: reads pattern from upper triangle
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int mju_cholFactorNNZ(int* L_rownnz, const int* rownnz, const int* rowadr, const int* colind,
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int n, mjData* d) {
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mj_markStack(d);
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@@ -870,18 +871,21 @@ int mju_cholFactorNNZ(int* L_rownnz, const int* rownnz, const int* rowadr, const
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parent[r] = -1;
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flag[r] = r;
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L_rownnz[r] = 1; // start with 1 for diagonal
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// loop over non-zero columns
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int start = rowadr[r];
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int end = start + rownnz[r];
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// loop over non-zero columns
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for (int p = start; p < end; p++) {
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int i = colind[p];
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for (int c = start; c < end; c++) {
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int i = colind[c];
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if (i > r) {
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// follow path from i to root of elimination tree, stop at flagged node
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// traverse from i to ancestor, stop when row is flagged
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while (flag[i] != r) {
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// find parent of i if not yet determined
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// if not yet set, set parent to current row
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if (parent[i] == -1) {
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parent[i] = r;
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}
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// increment non-zeros, flag row i, advance to parent
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L_rownnz[i]++;
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flag[i] = r;
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i = parent[i];
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@@ -892,12 +896,11 @@ int mju_cholFactorNNZ(int* L_rownnz, const int* rownnz, const int* rowadr, const
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mj_freeStack(d);
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// accumulate sum
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int sum = 0;
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// sum up all row non-zeros
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int nnz = 0;
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for (int r = 0; r < n; r++) {
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sum += L_rownnz[r];
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nnz += L_rownnz[r];
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}
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// return total non-zeros
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return sum;
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return nnz;
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}
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@@ -975,10 +975,9 @@ TEST_F(EngineUtilSparseTest, MjuCholFactorNNZ) {
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mjModel* model = LoadModelFromString(modelStr);
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mjData* d = mj_makeData(model);
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// A = [[1, 0],
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// [0, 1]]
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int nA = 2;
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mjtNum matA[4] = {1, 0, 0, 1};
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mjtNum matA[4] = {1, 0,
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0, 1};
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mjtNum sparseA[4];
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int rownnzA[2];
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int rowadrA[2];
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@@ -991,11 +990,10 @@ TEST_F(EngineUtilSparseTest, MjuCholFactorNNZ) {
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EXPECT_EQ(nnzA, 2);
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EXPECT_THAT(AsVector(rownnzA_factor, 2), ElementsAre(1, 1));
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// B = [[10, 1, 0],
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// [1, 10, 1],
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// [0, 1, 10]]
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int nB = 3;
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mjtNum matB[9] = {10, 1, 0, 1, 10, 1, 0, 1, 10};
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mjtNum matB[9] = {10, 1, 0,
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0, 10, 1,
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0, 0, 10};
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mjtNum sparseB[9];
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int rownnzB[3];
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int rowadrB[3];
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@@ -1008,11 +1006,10 @@ TEST_F(EngineUtilSparseTest, MjuCholFactorNNZ) {
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EXPECT_EQ(nnzB, 5);
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EXPECT_THAT(AsVector(rownnzB_factor, 3), ElementsAre(1, 2, 2));
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// C = [[10, 1, 0],
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// [1, 10, 0],
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// [0, 0, 10]]
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int nC = 3;
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mjtNum matC[9] = {10, 1, 0, 1, 10, 0, 0, 0, 10};
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mjtNum matC[9] = {10, 1, 0,
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0, 10, 0,
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0, 0, 10};
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mjtNum sparseC[9];
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int rownnzC[3];
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int rowadrC[3];
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@@ -1025,12 +1022,11 @@ TEST_F(EngineUtilSparseTest, MjuCholFactorNNZ) {
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EXPECT_EQ(nnzC, 4);
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EXPECT_THAT(AsVector(rownnzC_factor, 3), ElementsAre(1, 2, 1));
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// D = [[10, 1, 2, 3],
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// [1, 10, 0, 0],
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// [2, 0, 10, 1],
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// [3, 0, 1, 10]]
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int nD = 4;
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mjtNum matD[16] = {10, 1, 2, 3, 1, 10, 0, 0, 2, 0, 10, 1, 3, 0, 1, 10};
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mjtNum matD[16] = {10, 1, 2, 3,
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0, 10, 0, 0,
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0, 0, 10, 1,
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0, 0, 0, 10};
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mjtNum sparseD[16];
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int rownnzD[4];
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int rowadrD[4];
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