easings 3.1.0

Customizable Optimized Easing Functions for Python

Easings

Description

Customizable Optimized Easing Functions for Python.

Installation

pip install easings

Usage

Ease values between 0 and 1:

import easings

progress = easings.back_in_out(
    progress = 0.5,
    bounce_const = easings.both_back_consts[0.1]
)

print(progress)

Easing values with a start and end value using an Easer

import easings

easer = easings.Easer(4, 12)

value = easer.value(easings.poly_in_out, 0.5, 2)

print(value)

Using a Bézier curve

import numpy as np

import easings

points = np.array([[0, 0], [1, 2], [3, 3], [4, 0]])

curve = easings.curves.Bezier(points)

print(curve.point(0.4))

Using a Catmull-Rom spline

import numpy as np

import easings

points = np.array([[0, 0], [1, 2], [2, 4], [3, 3], [4, 1], [5, 2], [6, 0], [7, -1], [8, 1], [9, 3], [10, 2]])

spline = easings.splines.Catmull(points)

print(spline.point(1.2))

License

CC0 1.0 Universal (CC0 1.0) Public Domain Dedication.