Migrating to the typed dense API

Versions 1.5.0 and 1.6.0 do not remove or deprecate IMatrix, TMatrixKit, IVector, or their methods. Migration is opt-in.

Use case	Compatibility API	Typed allocating API	Repeated/high-performance form
Construct	`TMatrixKit.CreateFromArray`	`TDenseDoubleMatrix.FromValues`	`Zeros`, then checked writes
Multiply	`A.Multiply(B)`	`Multiply(A, B)`	`MultiplyInto(A, B, Destination)`
Solve	Previously required inverse multiplication or an iterative method	`Solve(A, B)`	`FactorLU(A).Solve(B)`
Positive-definite solve	`Cholesky` plus caller glue	`FactorCholesky(A).Solve(B)`	Reuse the factor
Tall least squares	Compatibility `QRDecomposition` plus caller glue	`LeastSquares(A,B,Info)`	`FactorQR(A).SolveLeastSquaresWithInfo(B,Info)`
Rank-revealing least squares	Compatibility rank/QR methods have different tolerances and result contracts	`RankRevealingLeastSquares(A,B,Info)`	Reuse `FactorPivotedQR(A)`
Pseudoinverse/minimum norm	Compatibility `PseudoInverse` materializes a matrix	`MinimumNormSolve(A,B,Info)`	Reuse `FactorSVD(A)` without forming the pseudoinverse
Full symmetric/Hermitian eigen	Compatibility `EigenDecomposition` is double-real and has legacy ordering/error behavior	`FactorSymmetricEigen` / `FactorHermitianEigen`	Reuse the immutable factor outputs
Submatrix	Copying `GetSubMatrix`	Mutable retained-owner `View`	Reuse the view handle
Compatibility bridge	Already `IMatrix`	`TDenseDoubleMatrix.FromIMatrix`	Keep data typed to avoid repeated copies

Conversions between IMatrix/TMatrixArray and typed matrices are deep copies. FromVector also copies an array into matrix-owned storage. Clone copies; interface assignment and View alias.

The typed API uses SizeInt dimensions and zero-based indices. Existing IMatrix dimensions remain Integer, so a conversion back to IMatrix inherits that API's limit. Conversion never hides this copy and never removes the original matrix.

The compatibility QR, SVD, Cholesky, and eigen methods remain source compatible. They are not silently routed through the typed implementation: their shapes, ordering, tolerance, error, and ownership contracts differ. Opting in means constructing the matching typed matrix, which is a deep copy when starting from IMatrix.

Do not migrate PseudoInverse(B).Multiply(...) literally. Express the task:


X := MinimumNormSolve(A, B, Info);

This uses the reusable compact SVD directly, does not form an inverse or pseudoinverse, supports multiple right-hand sides, and reports numerical rank and backward error. For a known full-rank tall problem, prefer LeastSquares; for uncertain rank where a basic solution is enough, use RankRevealingLeastSquares.

For ordinary code, prefer the allocating function:


C := Multiply(A, B);

For a loop, allocate the destination once:


C := TDenseDoubleMatrix.Zeros(A.Rows, B.Cols);

for Iteration := 1 to IterationCount do

  MultiplyInto(A, B, C);

The 1.5 MultiplyInto implementation guarantees correct overlapping aliases by using a temporary. This is deterministic and safe, but a non-overlapping destination avoids retaining unnecessary aliases and communicates intent.