doodle-docs/doodle.interact.animation/Interpolation

Interpolation

sealed trait Interpolation[A]

An Interpolation represents a range of values between a starting and ending value. The interpolation is also optionally transformed by an easing function. The starting value is mapped to 0.0 and the ending value to 1.0. When a number of steps is specified the interpolation is transformed into a transducer, which may be run or composed with other transducers.

Interpolations may be transformed by map and product (functor and semigroupal) to construct more complex interpolations.

The differences between an interpolation and a transducer are as follows:

  • An interpolation specifies a start and end value. When a number of steps is given it becomes a transducer. When interpolations are combined in parallel, with product, they always take the same amount of time when converted to a transducer. Transducers combined in parallel may take differing amounts of time.

  • A transducer can represent arbitrary FSMs, while an interpolation moves from start to end value.

  • Transducers can be run. Interpolations must be transformed to transducers to run.

Companion:
object
Source:
Interpolation.scala
class Object
trait Matchable
class Any
class Closed[A]
class HalfOpen[A]
class Map[A, B]
class Product[A, B]
class WithEasing[A]

Value members

Concrete methods

def forSteps(steps: Long): Transducer[A]

Create a transducer that will produce the given number of values before it stops. So, for example, calling forSteps(2) will create a transducer that produces 2 values before it stops.

Create a transducer that will produce the given number of values before it stops. So, for example, calling forSteps(2) will create a transducer that produces 2 values before it stops.

The number of steps must be non-negative. 0 steps means a transducer that stops immediately. 1 step will produce the start value for a half-open interval and the stop value for a closed interval.

Source:
Interpolation.scala
def map[B](f: A => B): Interpolation[B]

Transform the output of this interpolation with the given function.

Transform the output of this interpolation with the given function.

Source:
Interpolation.scala
def product[B](that: Interpolation[B]): Interpolation[(A, B)]

Combine this Interpolation in parallel with that Interpolation.

Combine this Interpolation in parallel with that Interpolation.

Source:
Interpolation.scala
def withEasing(easing: Easing): Interpolation[A]

Apply an easing function to this interpolation.

Apply an easing function to this interpolation.

Map the range in this interpolation to 0.0 and 1.0, pass through the given easing function, and then map back to the original domain.

Source:
Interpolation.scala