Tutorial is coming soon. Meanwhile, you may check the official Noise TV example.

The example showing how to build an environment runnable with Moire.

We will set up Noise TV environment, which is generating a
preudorandom array each step, then render it to a viewport as


import numpy as np

import moire

class NoiseTV:
    Welcome to the Noise TV.

    You will find nothing but a pseudorandom noise here, 24/7. Just
    relax, stare at the screen for some time, and your imagination
    could start playing games with you.


    def __init__(self):
        Initialize the environment.

        Some attributes are mandatory for this class, since Moire is
        relying on them:

            A positive integer, holding current time step number. You
            must properly increment it in ``step()`` method.
            An integer >= 1, representing the simulation speed, or
            exactly the number of steps per visualization frame.
            A flag showing if simulation is paused or running.
            A bridge class between Moire and your environment.

        self._size = 3
        self._screen = np.zeros((self._size, ), dtype=np.uint8)
        self.timestep = 0
        self.speed = 1
        self.paused = False
        self.bridge = MoireBridge

    def set_viewport(self, size):
        Set viewport (camera) size and initialize array for it.

        :param size: tuple with width and height in pixels.

        self._size = size[0] * size[1] * 3
        self._screen = np.zeros((self._size, ), dtype=np.uint8)

    def apply_speed(self, dval):
        Change the simulation speed.

        :param dval: Delta by which speed is changed.

        self.speed = max(1, (self.speed + dval))

    def toggle_pause(self):
        Toggle ``paused`` flag.

        When paused, the ``step()`` method does nothing.

        self.paused = not self.paused

    def step(self):
        Perform a single simulation step.

        ``timestep`` attribute will hold the current step number.

        if self.paused:
        self._screen = np.random.randint(0, 255, (self._size, ),
        self.timestep += 1

    def render(self):
        Render the field at the current timestep.

        You must call :meth:`set_viewport` before do any rendering.

            NumPy array of ``np.uint8`` values, ``width * height * 3``
            size. The RGB values are consecutive.

        return self._screen

class Bridge:
    """Main bridge class containing basic functions."""

    def exit_app(_env, gui):
        """Exit GUI application."""

    def speed(dspeed):
        """Change simulation speed."""
        def func(env, _gui):
            """Wrap speed applying."""
        return func

    def toggle_pause(env, _gui):
        """Pause/unpause simulation."""

    def toggle_sysinfo(_env, gui):
        """Turn system info panel on/off."""

class MoireBridge:
    """Class incapsulating the actions for Moire UI."""

    key_actions = {
        "[": Bridge.speed(-1),
        "]": Bridge.speed(1),
        "spacebar": Bridge.toggle_pause,
        "f12": Bridge.toggle_sysinfo,
        "escape": Bridge.exit_app,

def main():
    """Run the whole environment with Moire."""
    environment = NoiseTV()
    gui = moire.GUI(runnable=environment)

if __name__ == "__main__":