feat: initial release

Assisted-by: GLM 5.3 Flash

doc.go

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+// Copyright (c) 2026 Petr Balvín <opensource@petrbalvin.org> (https://petrbalvin.org)
+// SPDX-License-Identifier: MIT
+
+// Package tensor is the public facade of the library: every exported
+// symbol of every domain package is re-exported here under one name,
+// so user code imports only "sourcedock.dev/petrbalvin/tensor" and
+// writes tensor.Everything. The implementations live in the domain
+// packages (linalg, signal, integrate, stats, optim, io, grad) and the
+// shared array core in internal/core.
+//
+// # What it is
+//
+// A scientific computing library in pure Go: no cgo, no GPU stack, no
+// third-party dependencies. Arrays over int64, float32, float64 and
+// complex128 with a strict promotion ladder and loud shape errors;
+// dense and sparse linear algebra through eigensolvers, decompositions
+// and Krylov methods; Fourier, cosine/sine, wavelet and continuous
+// wavelet transforms; ordinary differential equations with events and
+// adjoint sensitivities; PDE evolution in one and two space dimensions;
+// quadrature and cubature; distributions, inference and linear
+// regression with classical errors; global and local optimisation; and
+// a reverse-mode differentiable core that covers the arithmetic, the
+// transforms and the second-order questions alike.
+//
+// # A tour in one breath
+//
+//	z, _ := tensor.MatMul2D(a, b)              // dense linear algebra
+//	spec, _ := tensor.FFT(x)                   // transforms, any length
+//	end, _ := tensor.IntegrateODE(f, 0, 1, y0, tensor.ODEOptions{})
+//	res, _ := tensor.LinearRegression(X, y)    // full inference
+//	loss.Backward()                            // exact gradients
+//	xs, _ := tensor.MinimiseNewtonCG(f, x0, tensor.NewtonCGOptions{})
+//
+// The examples in this documentation are executable and checked by
+// the test suite; the examples/ directory carries the longer
+// workflows (ODE parameter fitting, PSF deconvolution, HMC sampling,
+// spectral analysis).
+//
+// # The guarantees
+//
+//   - Deterministic: parallel kernels reduce in a fixed order, so a
+//     given element order gives bit-identical results run to run;
+//     SetNumCPU pins the parallelism.
+//   - Loud: a shape mismatch, a singular matrix, an exhausted solver
+//     budget or a CFL violation is an error naming itself, never a
+//     silently wrong number.
+//   - Immutable: operations never modify their inputs.
+//   - Reproducible: the generator is xoshiro256++ seeded through
+//     splitmix64, stable across Go releases, and Substream hands out
+//     the provably distinct members of one seed's stream family.
+//
+// # Conventions
+//
+// Functions return (value, error) and wrap errors with context;
+// scalars come back as Scalar when the dtype follows the input. The
+// names are the library's own: consistent with the established
+// patterns here rather than borrowed from any other array library.
+package tensor