manim_express

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Install

pip install manim_express

Run in pycharm

https://stackoverflow.com/questions/44851652/how-to-allocate-a-pseudo-tty-in-which-to-run-scripts-from-ide

(Find action 'Registry' in PyCharm) named 'run.processes.with.pty' that allows to run Python processes with tty

Quick start

• Render an animation: 3b1b:SquareToCircle

  from manimlib import *
  from manim_express import GlEagerScene
  
  scene = GlEagerScene()
  circle = Circle()
  circle.set_fill(BLUE, opacity=0.5)
  circle.set_stroke(BLUE_E, width=4)
  
  square = Square()
  scene.show_creation(square)
  scene.play(ReplacementTransform(square, circle))
  
  scene.hold_on()
  

  Operating graphics:

  • hold down the d key or mouse left on the keyboard and move the mouse to change the three-dimensional perspective.
  • hold down the s key or mouse right on the keyboard and move the mouse to pan the screen
  • hold down the z or ctrl on the keyboard while scrolling the middle mouse button to zoom the screen
  • scroll the middle mouse button to move the screen up and down
  • reset camera view by pressing r
  • close the window and exit the program by pressing q or tab
  • pause the animation by pressing space or ctrl or alt
  • previews animation clip by pressing LEFT
  • next animation clip: RIGHT
  • replay current animation clip: DOWN

• manim_express vs Matplotlib:
  Eager mode usage:

  from manimlib import *
  from manim_express import GlEagerScene
  CONFIG.use_online_tex = True # If you don't have installed latex locally.
  theta = np.linspace(0, 2*np.pi, 200)
  x = np.cos(theta)
  y = np.sin(theta)
  
  scene = GlEagerScene()
  scene.plot(x, y, color=GREEN, width=2, scale_ratio=1)
  scene.show_plot()
  scene.hold_on()
  

  Object oriented usage:

  from manimlib import *
  from manim_express import GlEagerScene
  from sklearn.datasets import make_multilabel_classification 
  class ScatterExample(GlEagerScene):
      def clip_1(self):
          X1, y1 =make_multilabel_classification(n_samples=200, n_classes=4, n_features=2)
          X2, y2 =make_multilabel_classification(n_samples=200, n_classes=4, n_features=2)
          self.scatter2d(X1[:, 0], X1[:, 1], size=.05, color=BLUE)
          self.scatter2d(X2[:, 0], X2[:, 1], size=.05, color=YELLOW)
  
  ScatterExample().render()
  

  It should be noted that manim is not suitable for drawing patterns that need to be accurately realized!

Resources

• Wiki
  https://flyingframes.readthedocs.io/en/latest/index.html
  https://3b1b.github.io/manim/
  https://docs.manim.org.cn/
  https://docs.manim.org.cn/shaders/

• 3B1B videos:
  https://github.com/3b1b/videos

• export pptx

  • https://github.com/yoshiask/manim-pptx
  • https://github.com/RythenGlyth/manim-pptx
  • https://manimcommunity.github.io/manim_editor/Tutorial/index.html

Examples

• Bezier curve

  https://user-images.githubusercontent.com/32060638/159116579-083692a2-f12c-48c0-8abd-1ee147e63714.mp4

• GOA model

  https://user-images.githubusercontent.com/32060638/159116901-eafa5842-135c-47f5-85a8-c946099a160f.mp4

• GOA
  

• Apply function
  

• Double pendulum