Merge origin/main into parameter-support-v2

Resolve conflicts from matmul chain rule PR (#67):
- subexpr.h: keep both vector_mult_expr and new matmul_expr/const types
- dense_matrix.c: adopt shared I_kron_A functions, keep update_values
- Add missing dense_matrix.h include in right_matmul.c
- Update new matmul tests to use 3-arg left_matmul signature

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: Transurgeon

include/subexpr.h

@@ -149,6 +149,42 @@ typedef struct vector_mult_expr
     expr *param_source;
 } vector_mult_expr;
 
+/* Bivariate matrix multiplication: Z = f(u) @ g(u) where both children
+ * may be composite expressions. */
+typedef struct matmul_expr
+{
+    expr base;
+    /* Jacobian workspace */
+    CSR_Matrix *term1_CSR; /* (Y^T x I_m) @ J_f */
+    CSR_Matrix *term2_CSR; /* (I_n x X) @ J_g */
+
+    /* Hessian workspace (composite only) */
+    CSR_Matrix *B;       /* cross-Hessian B(w), mk x kn */
+    CSR_Matrix *BJg;     /* B @ J_g */
+    CSC_Matrix *BJg_CSC; /* BJg in CSC */
+    int *BJg_csc_work;   /* CSR-to-CSC workspace */
+    CSR_Matrix *C;       /* J_f^T @ B @ J_g */
+    CSR_Matrix *CT;      /* C^T */
+    int *idx_map_C;
+    int *idx_map_CT;
+    int *idx_map_Hf;
+    int *idx_map_Hg;
+} matmul_expr;
+
+/* Constant scalar multiplication: y = a * child where a is a constant double */
+typedef struct const_scalar_mult_expr
+{
+    expr base;
+    double a;
+} const_scalar_mult_expr;
+
+/* Constant vector elementwise multiplication: y = a \circ child for constant a */
+typedef struct const_vector_mult_expr
+{
+    expr base;
+    double *a; /* length equals node->size */
+} const_vector_mult_expr;
+
 /* Index/slicing: y = child[indices] where indices is a list of flat positions */
 typedef struct index_expr
 {

include/utils/CSR_sum.h

@@ -14,14 +14,12 @@ void sum_csr_matrices(const CSR_Matrix *A, const CSR_Matrix *B, CSR_Matrix *C);
 
 /* Compute sparsity pattern of A + B where A, B, C are CSR matrices.
  * Fills C->p, C->i, and C->nnz; does not touch C->x. */
-void sum_csr_matrices_fill_sparsity(const CSR_Matrix *A, const CSR_Matrix *B,
-                                    CSR_Matrix *C);
+void sum_csr_alloc(const CSR_Matrix *A, const CSR_Matrix *B, CSR_Matrix *C);
 
 /* Fill only the values of C = A + B, assuming C's sparsity pattern (p and i)
  * is already filled and matches the union of A and B per row. Does not modify
  * C->p, C->i, or C->nnz. */
-void sum_csr_matrices_fill_values(const CSR_Matrix *A, const CSR_Matrix *B,
-                                  CSR_Matrix *C);
+void sum_csr_fill_values(const CSR_Matrix *A, const CSR_Matrix *B, CSR_Matrix *C);
 
 /* Compute C = diag(d1) * A + diag(d2) * B where A, B, C are CSR matrices */
 void sum_scaled_csr_matrices(const CSR_Matrix *A, const CSR_Matrix *B, CSR_Matrix *C,

include/utils/dense_matrix.h

@@ -0,0 +1,20 @@
+#ifndef DENSE_MATRIX_H
+#define DENSE_MATRIX_H
+
+#include "matrix.h"
+
+/* Dense matrix (row-major) */
+typedef struct Dense_Matrix
+{
+    Matrix base;
+    double *x;
+    double *work; /* scratch buffer, length n */
+} Dense_Matrix;
+
+/* Constructors */
+Matrix *new_dense_matrix(int m, int n, const double *data);
+
+/* Transpose helper */
+Matrix *dense_matrix_trans(const Dense_Matrix *self);
+
+#endif /* DENSE_MATRIX_H */

include/utils/linalg_dense_sparse_matmuls.h

@@ -0,0 +1,26 @@
+#ifndef LINALG_DENSE_SPARSE_H
+#define LINALG_DENSE_SPARSE_H
+
+#include "CSC_Matrix.h"
+#include "CSR_Matrix.h"
+#include "matrix.h"
+
+/* C = (I_p kron A) @ J via the polymorphic Matrix interface.
+ * A is dense m x n, J is (n*p) x k in CSC, C is (m*p) x k in CSC. */
+// TODO: maybe we can replace these with I_kron_X functionality?
+CSC_Matrix *I_kron_A_alloc(const Matrix *A, const CSC_Matrix *J, int p);
+void I_kron_A_fill_values(const Matrix *A, const CSC_Matrix *J, CSC_Matrix *C);
+
+/* Sparsity and values of C = (Y^T kron I_m) @ J where Y is k x n, J is (m*k) x p,
+   and C is (m*n) x p. Y is given in column-major dense format. */
+CSR_Matrix *YT_kron_I_alloc(int m, int k, int n, const CSC_Matrix *J);
+void YT_kron_I_fill_values(int m, int k, int n, const double *Y, const CSC_Matrix *J,
+                           CSR_Matrix *C);
+
+/* Sparsity and values of C = (I_n kron X) @ J where X is m x k (col-major dense),
+   J is (k*n) x p, and C is (m*n) x p. */
+CSR_Matrix *I_kron_X_alloc(int m, int k, int n, const CSC_Matrix *J);
+void I_kron_X_fill_values(int m, int k, int n, const double *X, const CSC_Matrix *J,
+                          CSR_Matrix *C);
+
+#endif /* LINALG_DENSE_SPARSE_H */

include/utils/linalg_sparse_matmuls.h

@@ -1,9 +1,8 @@
 #ifndef LINALG_H
 #define LINALG_H
 
-/* Forward declarations */
-struct CSR_Matrix;
-struct CSC_Matrix;
+#include "CSC_Matrix.h"
+#include "CSR_Matrix.h"
 
 /* Compute sparsity pattern and values for the matrix-matrix multiplication
    C = (I_p kron A) @ J where A is m x n, J is (n*p) x k, and C is (m*p) x k,
@@ -15,32 +14,28 @@ struct CSC_Matrix;
     * Mathematically it corresponds to  C = [A @ J1; A @ J2; ...; A @ Jp],
       where J = [J1; J2; ...; Jp]
 */
-struct CSC_Matrix *block_left_multiply_fill_sparsity(const struct CSR_Matrix *A,
-                                                     const struct CSC_Matrix *J,
-                                                     int p);
+CSC_Matrix *block_left_multiply_fill_sparsity(const CSR_Matrix *A,
+                                              const CSC_Matrix *J, int p);
 
-void block_left_multiply_fill_values(const struct CSR_Matrix *A,
-                                     const struct CSC_Matrix *J,
-                                     struct CSC_Matrix *C);
+void block_left_multiply_fill_values(const CSR_Matrix *A, const CSC_Matrix *J,
+                                     CSC_Matrix *C);
 
 /* Compute y = kron(I_p, A) @ x where A is m x n and x is(n*p)-length vector.
    The output y is m*p-length vector corresponding to
    y = [A @ x1; A @ x2; ...; A @ xp] where x is divided into p blocks of n
    elements.
 */
-void block_left_multiply_vec(const struct CSR_Matrix *A, const double *x, double *y,
-                             int p);
+void block_left_multiply_vec(const CSR_Matrix *A, const double *x, double *y, int p);
 
 /* Fill values of C = A @ B where A is CSR, B is CSC.
  * C must have sparsity pattern already computed.
  */
-void csr_csc_matmul_fill_values(const struct CSR_Matrix *A,
-                                const struct CSC_Matrix *B, struct CSR_Matrix *C);
+void csr_csc_matmul_fill_values(const CSR_Matrix *A, const CSC_Matrix *B,
+                                CSR_Matrix *C);
 
 /* C = A @ B where A is CSR, B is CSC. Result C is CSR.
  * Allocates and precomputes sparsity pattern. No workspace required.
  */
-struct CSR_Matrix *csr_csc_matmul_alloc(const struct CSR_Matrix *A,
-                                        const struct CSC_Matrix *B);
+CSR_Matrix *csr_csc_matmul_alloc(const CSR_Matrix *A, const CSC_Matrix *B);
 
 #endif /* LINALG_H */

include/utils/matrix.h

@@ -42,21 +42,11 @@ typedef struct Sparse_Matrix
     CSR_Matrix *csr;
 } Sparse_Matrix;
 
-/* Dense matrix (row-major) */
-typedef struct Dense_Matrix
-{
-    Matrix base;
-    double *x;
-    double *work; /* scratch buffer, length n */
-} Dense_Matrix;
-
 /* Constructors */
 Matrix *new_sparse_matrix(const CSR_Matrix *A);
-Matrix *new_dense_matrix(int m, int n, const double *data);
 
-/* Transpose helpers */
+/* Transpose helper */
 Matrix *sparse_matrix_trans(const Sparse_Matrix *self, int *iwork);
-Matrix *dense_matrix_trans(const Dense_Matrix *self);
 
 /* Free helper */
 static inline void free_matrix(Matrix *m)

include/utils/mini_numpy.h

@@ -23,4 +23,14 @@ void scaled_ones(double *result, int size, double value);
 /* Naive implementation of Z = X @ Y, X is m x k, Y is k x n, Z is m x n */
 void mat_mat_mult(const double *X, const double *Y, double *Z, int m, int k, int n);
 
+/* Compute v = (Y kron I_m) @ w where Y is k x n (col-major), w has
+   length m*n, and v has length m*k.  Equivalently, reshape w as the
+   m x n matrix W (col-major) and compute v = vec(W @ Y^T). */
+void Y_kron_I_vec(int m, int k, int n, const double *Y, const double *w, double *v);
+
+/* Compute v = (I_n kron X^T) @ w where X is m x k (col-major), w has
+   length m*n, and v has length k*n.  Equivalently, reshape w as the
+   m x n matrix W (col-major) and compute v = vec(X^T @ W). */
+void I_kron_XT_vec(int m, int k, int n, const double *X, const double *w, double *v);
+
 #endif /* MINI_NUMPY_H */

src/affine/add.c

@@ -45,8 +45,7 @@ static void jacobian_init_impl(expr *node)
     node->jacobian = new_csr_matrix(node->size, node->n_vars, nnz_max);
 
     /* fill sparsity pattern  */
-    sum_csr_matrices_fill_sparsity(node->left->jacobian, node->right->jacobian,
-                                   node->jacobian);
+    sum_csr_alloc(node->left->jacobian, node->right->jacobian, node->jacobian);
 }
 
 static void eval_jacobian(expr *node)
@@ -56,8 +55,7 @@ static void eval_jacobian(expr *node)
     node->right->eval_jacobian(node->right);
 
     /* sum children's jacobians */
-    sum_csr_matrices_fill_values(node->left->jacobian, node->right->jacobian,
-                                 node->jacobian);
+    sum_csr_fill_values(node->left->jacobian, node->right->jacobian, node->jacobian);
 }
 
 static void wsum_hess_init_impl(expr *node)
@@ -71,8 +69,7 @@ static void wsum_hess_init_impl(expr *node)
     node->wsum_hess = new_csr_matrix(node->n_vars, node->n_vars, nnz_max);
 
     /* fill sparsity pattern of hessian */
-    sum_csr_matrices_fill_sparsity(node->left->wsum_hess, node->right->wsum_hess,
-                                   node->wsum_hess);
+    sum_csr_alloc(node->left->wsum_hess, node->right->wsum_hess, node->wsum_hess);
 }
 
 static void eval_wsum_hess(expr *node, const double *w)
@@ -82,8 +79,8 @@ static void eval_wsum_hess(expr *node, const double *w)
     node->right->eval_wsum_hess(node->right, w);
 
     /* sum children's wsum_hess */
-    sum_csr_matrices_fill_values(node->left->wsum_hess, node->right->wsum_hess,
-                                 node->wsum_hess);
+    sum_csr_fill_values(node->left->wsum_hess, node->right->wsum_hess,
+                        node->wsum_hess);
 }
 
 static bool is_affine(const expr *node)

src/affine/hstack.c

@@ -124,7 +124,7 @@ static void wsum_hess_init_impl(expr *node)
     {
         expr *child = hnode->args[i];
         copy_csr_matrix(H, hnode->CSR_work);
-        sum_csr_matrices_fill_sparsity(hnode->CSR_work, child->wsum_hess, H);
+        sum_csr_alloc(hnode->CSR_work, child->wsum_hess, H);
     }
 }
 
@@ -140,7 +140,7 @@ static void wsum_hess_eval(expr *node, const double *w)
         expr *child = hnode->args[i];
         child->eval_wsum_hess(child, w + row_offset);
         copy_csr_matrix(H, hnode->CSR_work);
-        sum_csr_matrices_fill_values(hnode->CSR_work, child->wsum_hess, H);
+        sum_csr_fill_values(hnode->CSR_work, child->wsum_hess, H);
         row_offset += child->size;
     }
 }

src/affine/left_matmul.c

@@ -17,7 +17,7 @@
  */
 #include "affine.h"
 #include "subexpr.h"
-#include "utils/matrix.h"
+#include "utils/dense_matrix.h"
 #include <assert.h>
 #include <stdio.h>
 #include <stdlib.h>