concepts.benchmark.algorithm_env.sort_envs.ListSortingEnv#

class ListSortingEnv[source]#

Bases: RandomizedEnv

Env for sorting a random permutation.

Methods

close()

Override close in your subclass to perform any necessary cleanup.

generate_data(nr_data_points)

get_state()

Compute the state given the array.

make(nr_numbers[, limit_episode_steps, seed])

oracle_policy(state)

Oracle policy: Swap the first two numbers that are not sorted.

render([mode])

Renders the environment.

reset(**kwargs)

Restart: Generate a random permutation.

reset_nr_numbers(n)

seed([seed])

deprecated:

function that sets the seed for the environment's random number generator(s).

step(action)

Action: Swap the numbers at the index \(i\) and \(j\).

Attributes

action_space

array

The underlying array to be sorted.

metadata

np_random

Returns the environment's internal _np_random that if not set will initialise with a random seed.

nr_numbers

The number of numbers in the array.

observation_space

reward_range

spec

unwrapped

Returns the base non-wrapped environment.

__init__(nr_numbers, np_random=None, seed=None)[source]#

Initialize the environment.

Parameters:
  • nr_numbers (int) – The number of numbers in the array.

  • np_random (RandomState | None) –

  • seed (int | None) –

__new__(**kwargs)#
close()#

Override close in your subclass to perform any necessary cleanup.

Environments will automatically close() themselves when garbage collected or when the program exits.

generate_data(nr_data_points)[source]#
Parameters:

nr_data_points (int) –

get_state()[source]#

Compute the state given the array.

classmethod make(nr_numbers, limit_episode_steps=True, seed=None)[source]#
Parameters:
  • nr_numbers (int) –

  • limit_episode_steps (bool) –

  • seed (int | None) –

Return type:

Env

oracle_policy(state)[source]#

Oracle policy: Swap the first two numbers that are not sorted.

render(mode='human')#

Renders the environment.

A set of supported modes varies per environment. (And some third-party environments may not support rendering at all.) By convention, if mode is:

  • human: render to the current display or terminal and return nothing. Usually for human consumption.

  • rgb_array: Return a numpy.ndarray with shape (x, y, 3), representing RGB values for an x-by-y pixel image, suitable for turning into a video.

  • ansi: Return a string (str) or StringIO.StringIO containing a terminal-style text representation. The text can include newlines and ANSI escape sequences (e.g. for colors).

Note

Make sure that your class’s metadata ‘render_modes’ key includes the list of supported modes. It’s recommended to call super() in implementations to use the functionality of this method.

Example

>>> import numpy as np
>>> class MyEnv(Env):
...    metadata = {'render_modes': ['human', 'rgb_array']}
...
...    def render(self, mode='human'):
...        if mode == 'rgb_array':
...            return np.array(...) # return RGB frame suitable for video
...        elif mode == 'human':
...            ... # pop up a window and render
...        else:
...            super().render(mode=mode) # just raise an exception
Parameters:

mode – the mode to render with, valid modes are env.metadata[“render_modes”]

reset(**kwargs)[source]#

Restart: Generate a random permutation.

reset_nr_numbers(n)[source]#
seed(seed=None)#
Deprecated:

function that sets the seed for the environment’s random number generator(s).

Use env.reset(seed=seed) as the new API for setting the seed of the environment.

Note

Some environments use multiple pseudorandom number generators. We want to capture all such seeds used in order to ensure that there aren’t accidental correlations between multiple generators.

Parameters:

seed (Optional int) – The seed value for the random number geneartor

Returns:

Returns the list of seeds used in this environment’s random

number generators. The first value in the list should be the “main” seed, or the value which a reproducer should pass to ‘seed’. Often, the main seed equals the provided ‘seed’, but this won’t be true if seed=None, for example.

Return type:

seeds (List[int])

step(action)[source]#

Action: Swap the numbers at the index \(i\) and \(j\).

property action_space#
property array#

The underlying array to be sorted.

metadata = {'render_modes': []}#
property np_random: RandomState#

Returns the environment’s internal _np_random that if not set will initialise with a random seed.

property nr_numbers#

The number of numbers in the array.

property observation_space#
reward_range = (-inf, inf)#
spec = None#
property unwrapped: Env#

Returns the base non-wrapped environment.

Returns:

The base non-wrapped gym.Env instance

Return type:

Env