Module compute::prelude[−][src]

Re-exports

`pub use crate::distributions::*;`
`pub use crate::functions::*;`
`pub use crate::integrate::*;`
`pub use crate::linalg::*;`
`pub use crate::optimize::*;`
`pub use crate::predict::*;`
`pub use crate::signal::*;`
`pub use crate::statistics::*;`
`pub use crate::timeseries::*;`
`pub use crate::validation::*;`

This module defines forward automatic differentiation. This mode of autodiff is most efficient when computing deriviatives with more inputs than outputs. It is also useful for computing Jacobian products.

Structs

F	A generic forward differentiation `Dual` number.

Traits

Float	Generic trait for floating point numbers
FloatConst
NumCast	An interface for casting between machine scalars.
One	Defines a multiplicative identity element for `Self`.
ReduceOrder	A Helper trait to drop the highest order derivative.
ToPrimitive	A generic trait for converting a value to a number.
Zero	Defines an additive identity element for `Self`.

Functions

diff	Evaluates the derivative of `f` at `x0`
grad	Evaluates the gradient of `f` at `x0`

Type Definitions