File:Scaling exponential distribution.webm

Summary

Description
English: PDF of exponential random variable that is being scaled by a constant factor
Беларуская: Залежнасць графіка шчыльнасці паказнікава размеркаванай выпадковай велічыні, якую дамнажаюць на канстанту, ад значэння гэтай канстанты
Date
Source Own work
Author A potato hater
WEBM development
InfoField

Python Script

Created with manim Python package

from manim import *
import numpy as np


def color_to_numpy(color):
    color = color.lstrip("#")
    return np.array([int(color[i : i + 2], 16) for i in (0, 2, 4)])


def numpy_to_color(arr):
    r, g, b = arr.round().astype(int)
    return "#%02x%02x%02x" % (r, g, b)


class ScaleExpDistribution(Scene):
    def get_rectangle_corners(self, bottom_left, top_right):
        return [
            (top_right[0], top_right[1]),
            (bottom_left[0], top_right[1]),
            (bottom_left[0], bottom_left[1]),
            (top_right[0], bottom_left[1]),
        ]

    def construct(self):
        FONT_SIZE = 96
        START_VALUE = 1
        END_VALUE = 2
        START_COLOR = color_to_numpy(YELLOW)
        END_COLOR = color_to_numpy(RED)

        t = ValueTracker(START_VALUE)

        axes = Axes(x_range=(0, 3.2, 0.5), y_range=(0, 1.1, 0.1))
        axes.add_coordinates()
        x_label = axes.get_x_axis_label("x")
        x_label.shift(0.7 * DOWN)
        y_label = axes.get_y_axis_label("f_\eta (x)")
        y_label.shift(0.8 * LEFT)

        def get_graph():
            t_value = t.get_value()
            alpha = (t_value - START_VALUE) / (END_VALUE - START_VALUE)
            color = numpy_to_color(START_COLOR + (alpha * (END_COLOR - START_COLOR)))
            xi_text = MathTex(r"\xi \sim Exp(1)", font_size=FONT_SIZE)

            number = DecimalNumber().set_color(color).set_value(t_value)
            number.font_size = FONT_SIZE
            eta_text = VGroup(
                MathTex(r"\eta = ", font_size=FONT_SIZE),
                number,
                MathTex(r"\xi", font_size=FONT_SIZE),
            ).arrange()

            dist_text = VGroup(xi_text, eta_text).arrange(DOWN)
            dist_text.to_corner(UP + RIGHT)

            rate = 1 / t_value
            exp_pdf = lambda x: rate * np.exp(-rate * x)
            graph = axes.plot(exp_pdf, x_range=(0, 3.1), color=color)

            starting_points = [0.25, 0.5, 0.75, 1, 1.25, 1.5]
            polygons = []
            for starting_point in starting_points:
                x_value = starting_point * (t_value / START_VALUE)
                polygon = Polygon(
                    *[
                        axes.c2p(*i)
                        for i in self.get_rectangle_corners(
                            (0, 0), (x_value, exp_pdf(x_value))
                        )
                    ]
                )
                polygon.stroke_width = 1
                polygon.set_stroke(WHITE)
                polygons.append(polygon)

            return VGroup(graph, *polygons, dist_text)

        graph = always_redraw(get_graph)
        self.add(axes, graph, x_label, y_label)

        self.wait()
        self.play(t.animate.set_value(END_VALUE), run_time=3, rate_func=linear)
        self.wait()

Licensing

I, the copyright holder of this work, hereby publish it under the following license:
w:en:Creative Commons
attribution share alike
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
You are free:
  • to share – to copy, distribute and transmit the work
  • to remix – to adapt the work
Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
Category:CC-BY-SA-4.0#Scaling%20exponential%20distribution.webm
Category:Self-published work Category:Exponential distribution Category:Animations of probability and statistics
Category:Animations of probability and statistics Category:CC-BY-SA-4.0 Category:Exponential distribution Category:PNG created with Python Category:Self-published work