# Crate na

## Modules

• [Reexported at the root of this crate.] Data structures for vector and matrix computations.
• [Reexported at the root of this crate.] Data structures for points and usual transformations (rotations, isometries, etc.)
• [Reexported at the root of this crate.] Factorization of real matrices.
• Traits implemented by scalar, non-SIMD, types.
• Traits implemented by SIMD types and non-SIMD types.

## Macros

• Construct a dynamic matrix directly from data.
• Construct a dynamic column vector directly from data.
• Construct a fixed-size matrix directly from data.
• Construct a fixed-size point directly from data.
• Construct a fixed-size column vector directly from data.

## Structs

• A array-based statically sized matrix data storage.
• The bidiagonalization of a general matrix.
• The Cholesky decomposition of a symmetric-definite-positive matrix.
• The QR decomposition (with column pivoting) of a general matrix.
• A complex number in Cartesian form.
• An allocator based on `ArrayStorage` and `VecStorage` for statically-sized and dynamically-sized matrices respectively.
• A dual quaternion.
• Dim of dynamically-sized algebraic entities.
• Euclidean norm.
• LU decomposition with full row and column pivoting.
• Hessenberg decomposition of a general matrix.
• A direct isometry, i.e., a rotation followed by a translation (aka. a rigid-body motion).
• LU decomposition with partial (row) pivoting.
• Lp norm.
• The most generic column-major matrix (and vector) type.
• A point in an euclidean space.
• A 3D orthographic projection stored as a homogeneous 4x4 matrix.
• A sequence of row or column permutations.
• A 3D perspective projection stored as a homogeneous 4x4 matrix.
• The QR decomposition of a general matrix.
• A quaternion. See the type alias `UnitQuaternion = Unit<Quaternion>` for a quaternion that may be used as a rotation.
• A reflection wrt. a plane.
• A rotation matrix.
• Singular Value Decomposition of a general matrix.
• A scale which supports non-uniform scaling.
• Schur decomposition of a square matrix.
• A similarity, i.e., an uniform scaling, followed by a rotation, followed by a translation.
• Eigendecomposition of a symmetric matrix.
• Tridiagonalization of a symmetric matrix.
• A transformation matrix in homogeneous coordinates.
• A translation.
• UDU factorization.
• L-infinite norm aka. Chebytchev norm aka. uniform norm aka. suppremum norm.
• A wrapper that ensures the underlying algebraic entity has a unit norm.
• A Vec-based matrix data storage. It may be dynamically-sized.
• A matrix data storage for a matrix view. Only contains an internal reference to another matrix data storage.
• A mutable matrix data storage for mutable matrix view. Only contains an internal mutable reference to another matrix data storage.

## Enums

• Tag representing an affine `Transform`. Its bottom-row is equal to `(0, 0 ... 0, 1)`.
• Tag representing the most general (not necessarily inversible) `Transform` type.
• Tag representing the most general inversible `Transform` type.

## Constants

• The constant dimension 0 .
• The constant dimension 1.
• The constant dimension 2 .
• The constant dimension 3 .
• The constant dimension 4 .
• The constant dimension 5 .
• The constant dimension 6 .
• The constant dimension 7 .
• The constant dimension 8 .
• The constant dimension 9 .
• The constant dimension 10 .
• The constant dimension 11 .
• The constant dimension 12 .
• The constant dimension 13 .
• The constant dimension 14 .
• The constant dimension 15 .
• The constant dimension 16 .
• The constant dimension 17 .
• The constant dimension 18 .
• The constant dimension 19 .
• The constant dimension 20 .
• The constant dimension 21 .
• The constant dimension 22 .
• The constant dimension 23 .
• The constant dimension 24 .
• The constant dimension 25 .
• The constant dimension 26 .
• The constant dimension 27 .
• The constant dimension 28 .
• The constant dimension 29 .
• The constant dimension 30 .
• The constant dimension 31 .
• The constant dimension 32 .
• The constant dimension 33 .
• The constant dimension 34 .
• The constant dimension 35 .
• The constant dimension 36 .
• The constant dimension 37 .
• The constant dimension 38 .
• The constant dimension 39 .
• The constant dimension 40 .
• The constant dimension 41 .
• The constant dimension 42 .
• The constant dimension 43 .
• The constant dimension 44 .
• The constant dimension 45 .
• The constant dimension 46 .
• The constant dimension 47 .
• The constant dimension 48 .
• The constant dimension 49 .
• The constant dimension 50 .
• The constant dimension 51 .
• The constant dimension 52 .
• The constant dimension 53 .
• The constant dimension 54 .
• The constant dimension 55 .
• The constant dimension 56 .
• The constant dimension 57 .
• The constant dimension 58 .
• The constant dimension 59 .
• The constant dimension 60 .
• The constant dimension 61 .
• The constant dimension 62 .
• The constant dimension 63 .
• The constant dimension 64 .
• The constant dimension 65 .
• The constant dimension 66 .
• The constant dimension 67 .
• The constant dimension 68 .
• The constant dimension 69 .
• The constant dimension 70 .
• The constant dimension 71 .
• The constant dimension 72 .
• The constant dimension 73 .
• The constant dimension 74 .
• The constant dimension 75 .
• The constant dimension 76 .
• The constant dimension 77 .
• The constant dimension 78 .
• The constant dimension 79 .
• The constant dimension 80 .
• The constant dimension 81 .
• The constant dimension 82 .
• The constant dimension 83 .
• The constant dimension 84 .
• The constant dimension 85 .
• The constant dimension 86 .
• The constant dimension 87 .
• The constant dimension 88 .
• The constant dimension 89 .
• The constant dimension 90 .
• The constant dimension 91 .
• The constant dimension 92 .
• The constant dimension 93 .
• The constant dimension 94 .
• The constant dimension 95 .
• The constant dimension 96 .
• The constant dimension 97 .
• The constant dimension 98 .
• The constant dimension 99 .
• The constant dimension 100 .
• The constant dimension 101 .
• The constant dimension 102 .
• The constant dimension 103 .
• The constant dimension 104 .
• The constant dimension 105 .
• The constant dimension 106 .
• The constant dimension 107 .
• The constant dimension 108 .
• The constant dimension 109 .
• The constant dimension 110 .
• The constant dimension 111 .
• The constant dimension 112 .
• The constant dimension 113 .
• The constant dimension 114 .
• The constant dimension 115 .
• The constant dimension 116 .
• The constant dimension 117 .
• The constant dimension 118 .
• The constant dimension 119 .
• The constant dimension 120 .
• The constant dimension 121 .
• The constant dimension 122 .
• The constant dimension 123 .
• The constant dimension 124 .
• The constant dimension 125 .
• The constant dimension 126 .
• The constant dimension 127 .

## Traits

• Trait implemented by rotations that can be used inside of an `Isometry` or `Similarity`.
• Trait alias for `Add` and `AddAssign` with result of type `Self`.
• Trait alias for `Div` and `DivAssign` with result of type `Self`.
• Trait alias for `Mul` and `MulAssign` with result of type `Self`.
• Trait alias for `Sub` and `SubAssign` with result of type `Self`.
• Trait shared by all complex fields and its subfields (like real numbers).
• Trait implemented by any type that can be used as a dimension. This includes type-level integers and `Dyn` (for dimensions not known at compile-time).
• Trait implemented exclusively by type-level integers.
• A range with a size that may be known at compile-time.
• Trait implemented by fields, i.e., complex numbers and floats.
• Trait of vector with components implementing the `RealField` trait.
• Trait of vector with components implementing the `BaseFloat` trait.
• Marker trait indicating that a storage is stored contiguously in memory.
• Trait implemented by `Dyn`.
• Trait implemented by `Dyn` and type-level integers different from `U1`.
• A trait for abstract matrix norms.
• Trait implemented by entities scan be be normalized and put in an `Unit` struct.
• Trait grouping most common operations on points.
• Trait grouping most common operations on vectors.
• The trait shared by all matrix data storage.
• Trait implemented by matrix data storage that can provide a mutable access to its elements.
• Trait shared by all reals.
• A matrix storage that can be reshaped in-place.
• The basic scalar type for all structures of `nalgebra`.
• Lane-wise generalization of `bool` for SIMD booleans.
• Lane-wise generalisation of `ComplexField` for SIMD complex fields.
• Lane-wise generalization of the standard `PartialOrd` for SIMD values.
• Lanewise generalization of `RealField` for SIMD reals.
• Base trait for every SIMD types.
• SliceRangeDeprecated
A range with a size that may be known at compile-time.
• Trait shared by all matrix data storage that don’t contain any uninitialized elements.
• Trait shared by all mutable matrix data storage that don’t contain any uninitialized elements.
• Indicates that `Self` is a more specific `Transform` category than `Other`.
• Indicates that `Self` is a more general `Transform` category than `Other`.
• Trait implemented by phantom types identifying the projective transformation type.
• Traits that gives the `Transform` category that is compatible with the result of the multiplication of transformations with categories `Self` and `Other`.

## Functions

• absDeprecated
The absolute value of `a`.
• The center of two points.
• Returns a reference to the input value clamped to the interval `[min, max]`.
• Converts an object from one type to an equivalent or more general one.
• Converts an object from one type to an equivalent or more general one.
• Use with care! Same as `try_convert` but without any property checks.
• Use with care! Same as `try_convert` but without any property checks.
• The distance between two points.
• The squared distance between two points.
• infDeprecated
Returns the infimum of `a` and `b`.
• inf_supDeprecated
Returns simultaneously the infimum and supremum of `a` and `b`.
• Indicates if `try_convert` will succeed without actually performing the conversion.
• Same as `cmp::max`.
• Same as `cmp::min`.
• Gets the multiplicative identity element.
• Clamp `value` between `min` and `max`. Returns `None` if `value` is not comparable to `min` or `max`.
• Compare `a` and `b` using a partial ordering relation.
• Returns `true` iff `a` and `b` are comparable and `a >= b`.
• Returns `true` iff `a` and `b` are comparable and `a > b`.
• Returns `true` iff `a` and `b` are comparable and `a <= b`.
• Returns `true` iff `a` and `b` are comparable and `a < b`.
• Return the maximum of `a` and `b` if they are comparable.
• Return the minimum of `a` and `b` if they are comparable.
• Sorts two values in increasing order using a partial ordering.
• supDeprecated
Returns the supremum of `a` and `b`.
• Attempts to convert an object to a more specific one.
• Attempts to convert an object to a more specific one.
• Performs a LU decomposition to overwrite `out` with the inverse of `matrix`.
• Computes the wilkinson shift, i.e., the 2x2 symmetric matrix eigenvalue to its tailing component `tnn`.
• Wraps `val` into the range `[min, max]` using modular arithmetics.
• Gets the additive identity element.