lyng/docs/Matrix.md

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# Matrix (`lyng.matrix`)
`lyng.matrix` adds dense immutable `Matrix` and `Vector` types for linear algebra.
Import it when you need matrix or vector arithmetic:
```lyng
import lyng.matrix
```
## Construction
Create vectors from a flat list and matrices from nested row lists:
```lyng
import lyng.matrix
val v: Vector = vector([1, 2, 3])
val m: Matrix = matrix([[1, 2, 3], [4, 5, 6]])
assertEquals([1.0, 2.0, 3.0], v.toList())
assertEquals([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], m.toList())
```
Factory methods are also available:
```lyng
import lyng.matrix
val z: Vector = Vector.zeros(3)
val i: Matrix = Matrix.identity(3)
val m: Matrix = Matrix.zeros(2, 4)
```
All elements are standard double-precision numeric values internally.
## Shapes
Matrices may have any rectangular geometry:
```lyng
import lyng.matrix
val a: Matrix = matrix([[1, 2, 3], [4, 5, 6]])
assertEquals(2, a.rows)
assertEquals(3, a.cols)
assertEquals([2, 3], a.shape)
assertEquals(false, a.isSquare)
```
Vectors expose:
- `size`
- `length` as an alias of `size`
## Matrix Operations
Supported matrix operations:
- `+` and `-` for element-wise matrix arithmetic
- `*` for matrix-matrix product
- `*` and `/` by a scalar
- `transpose()`
- `trace()`
- `rank()`
- `determinant()`
- `inverse()`
- `solve(rhs)` for `Vector` or `Matrix` right-hand sides
Example:
```lyng
import lyng.matrix
val a: Matrix = matrix([[1, 2, 3], [4, 5, 6]])
val b: Matrix = matrix([[7, 8], [9, 10], [11, 12]])
val product: Matrix = a * b
assertEquals([[58.0, 64.0], [139.0, 154.0]], product.toList())
assertEquals([[1.0, 4.0], [2.0, 5.0], [3.0, 6.0]], a.transpose().toList())
```
Inverse and solve:
```lyng
import lyng.matrix
val a: Matrix = matrix([[4, 7], [2, 6]])
val rhs: Vector = vector([1, 0])
val inv: Matrix = a.inverse()
val x: Vector = a.solve(rhs)
assert(abs(a.determinant() - 10.0) < 1e-9)
assert(abs(inv.get(0, 0) - 0.6) < 1e-9)
assert(abs(x.get(0) - 0.6) < 1e-9)
```
## Vector Operations
Supported vector operations:
- `+` and `-`
- scalar `*` and `/`
- `dot(other)`
- `norm()`
- `normalize()`
- `cross(other)` for 3D vectors
- `outer(other)` producing a matrix
```lyng
import lyng.matrix
val a: Vector = vector([1, 2, 3])
val b: Vector = vector([2, 0, 0])
assertEquals(2.0, a.dot(b))
assertEquals([0.2672612419124244, 0.5345224838248488, 0.8017837257372732], a.normalize().toList())
```
## Indexing and Slicing
`Matrix` supports both method-style indexing and bracket syntax.
Scalar access:
```lyng
import lyng.matrix
val m: Matrix = matrix([[1, 2, 3], [4, 5, 6]])
assertEquals(6.0, m.get(1, 2))
assertEquals(6.0, m[1, 2])
```
Bracket indexing accepts two selectors: `[row, col]`.
Each selector may be either:
- an `Int`
- a `Range`
Examples:
```lyng
import lyng.matrix
val m: Matrix = matrix([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
assertEquals(7.0, m[1, 2])
val columnSlice: Matrix = m[0..2, 2]
val topLeft: Matrix = m[0..1, 0..1]
val tail: Matrix = m[1.., 1..]
assertEquals([[3.0], [7.0], [11.0]], columnSlice.toList())
assertEquals([[1.0, 2.0], [5.0, 6.0]], topLeft.toList())
assertEquals([[6.0, 7.0, 8.0], [10.0, 11.0, 12.0]], tail.toList())
```
Shape rules:
- `m[Int, Int]` returns a `Real`
- `m[Range, Int]` returns an `Nx1` `Matrix`
- `m[Int, Range]` returns a `1xM` `Matrix`
- `m[Range, Range]` returns a submatrix
Open-ended ranges are supported:
- `m[..1, ..1]`
- `m[1.., 1..]`
- `m[.., 2]`
Stepped ranges are not supported in matrix slicing.
Slices currently return new matrices, not views.
## Rows and Columns
If you want plain lists instead of a sliced matrix:
```lyng
import lyng.matrix
val a: Matrix = matrix([[1, 2, 3], [4, 5, 6]])
assertEquals([4.0, 5.0, 6.0], a.row(1))
assertEquals([2.0, 5.0], a.column(1))
```
## Backend Notes
The matrix module uses a platform-specific backend where available and falls back to pure Kotlin where needed.
The public Lyng API stays the same across platforms.