Runnable examples demonstrating Zigen's features. Each example is self-contained.
zig build run-<example_name>| Example | Command | Description |
|---|---|---|
| basic_matrix.zig | zig build run-basic_matrix |
Matrix creation, arithmetic, transpose, inverse, linear system solve |
| matrix_operations.zig | zig build run-matrix_operations |
Element access, slicing, block operations, norms, condition numbers |
| Example | Command | Description |
|---|---|---|
| linear_algebra.zig | zig build run-linear_algebra |
LU, QR, Cholesky, SVD decompositions; determinant, solve, least-squares |
| dynamic_decompositions.zig | zig build run-dynamic_decompositions |
Runtime-sized LU/QR/Cholesky/SVD/EigenSolver with zero-allocation workspace reuse |
| Example | Command | Description |
|---|---|---|
| sparse_systems.zig | zig build run-sparse_systems |
CSR sparse matrix build, SpMV, SparseLU/Cholesky, MatrixMarket I/O |
| iterative_solvers.zig | zig build run-iterative_solvers |
Conjugate Gradient, BiCGSTAB for large sparse systems |
| Example | Command | Description |
|---|---|---|
| geometry.zig | zig build run-geometry |
Quaternions, rotations, SLERP, rigid body transforms, axis-angle |
| Example | Command | Description |
|---|---|---|
| data_analysis.zig | zig build run-data_analysis |
PCA via SVD, covariance matrix, principal components |
| image_processing.zig | zig build run-image_processing |
Convolution kernels, Gaussian blur, edge detection via matrices |
Getting Started → basic_matrix, matrix_operations
Linear Algebra → linear_algebra, dynamic_decompositions
Sparse & Iterative → sparse_systems, iterative_solvers
Geometry → geometry
Applications → data_analysis, image_processing