scivex-core 0.1.1

Scivex — Tensors, linear algebra, FFT, and math primitives
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# scivex-core

The foundation crate of the Scivex ecosystem. Provides N-dimensional tensors,
linear algebra, FFT, and math primitives — all implemented from scratch with
zero external dependencies for math.

## Highlights

- **Tensor<T>** — Dynamic N-dimensional array with row-major storage and broadcasting
- **BLAS Level 1-3** — `dot`, `axpy`, `nrm2`, `gemv`, `gemm` from scratch
- **Matrix decompositions** — LU, QR, Cholesky, SVD, Eigendecomposition, Schur
- **Linear solvers** — `solve(A, b)`, `inv(A)`, `det(A)`, `lstsq(A, b)`
- **Sparse matrices** — COO, CSR, CSC formats with conversion and arithmetic
- **FFT** — Real and complex transforms (Cooley-Tukey radix-2), IFFT
- **PRNG** — xoshiro256** with normal/uniform/exponential sampling
- **Interpolation** — Linear, polynomial, and cubic spline interpolation
- **Special functions** — Gamma, beta, erf, bessel, and more
- **35+ math functions** — sin, cos, exp, ln, sqrt, abs, etc. (element-wise on tensors)
- **Generic** — All operations generic over `Scalar > Float > Real` trait hierarchy

## Usage

```rust
use scivex_core::prelude::*;

let a = Tensor::<f64>::from_vec(vec![1.0, 2.0, 3.0, 4.0], &[2, 2]);
let b = Tensor::<f64>::from_vec(vec![5.0, 6.0, 7.0, 8.0], &[2, 2]);

// Arithmetic with broadcasting
let c = &a + &b;

// Linear algebra
let lu = scivex_core::linalg::LuDecomposition::decompose(&a).unwrap();
let svd = scivex_core::linalg::SvdDecomposition::decompose(&a).unwrap();
let eig = scivex_core::linalg::EigenDecomposition::decompose(&a).unwrap();

// FFT
let spectrum = scivex_core::fft::rfft(&signal);
```

## License

MIT