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"SS\#5r$"SS5r%SSjr&SSSjjr'"SS5r(g!\a!r\ R8R'S 5\eSrCff=f!\a \RD"S5 Surr!Nf=f)z(Utilities of visualising an environment.) annotations)deque)Callable) TYPE_CHECKINGN)Envlogger)ActTypeObsType)DependencyNotInstalled)Axes)Surface)EventzGpygame is not installed, run `pip install "gymnasium[classic_control]"`TkAggAmatplotlib is not installed, run `pip install "gymnasium[other]"`NNc\rSrSrSrSrg)MissingKeysToAction(zORaised when the environment does not have a default ``keys_to_action`` mapping.N)__name__ __module__ __qualname____firstlineno____doc____static_attributes__rN/home/james-whalen/.local/lib/python3.13/site-packages/gymnasium/utils/play.pyrr(sYrrcb\rSrSrSrS S SjjrS S SjjrS S SjjrSSjrSr g) PlayableGame,zOWraps an environment allowing keyboard inputs to interact with the environment.NcPURS;a[SURS35eXlURU5UlUR U5Ul[RRUR [R5Ul /Ul SUl g)a Wraps an environment with a dictionary of keyboard buttons to action and if to zoom in on the environment. Args: env: The environment to play keys_to_action: The dictionary of keyboard tuples and action value zoom: If to zoom in on the environment render > rgb_arrayrgb_array_listzsPlayableGame wrapper works only with rgb_array and rgb_array_list render modes, but your environment render_mode = .TN) render_mode ValueErrorenv_get_relevant_keys relevant_keys_get_video_size video_sizepygamedisplayset_mode RESIZABLEscreen pressed_keysrunning)selfr'keys_to_actionzooms r__init__PlayableGame.__init__/s ??"A A669oo5FaI  !44^D..t4nn--doov?O?OP  rcUcURRS5(a!URRS5"5nOEURRce[ URRR S35e[ U[5(de[[SUR55/55nU$)Nget_keys_to_actionzk does not have explicit key to action mapping, please specify one manually, `play(env, keys_to_action=...)`c38# UHn[U5v M g7fN)list.0ks r 2PlayableGame._get_relevant_keys..Xs H2GQa2Gs) r'has_wrapper_attrget_wrapper_attrspecrid isinstancedictsetsumkeys)r3r4r)s rr(PlayableGame._get_relevant_keysKs  !xx(()=>>!%!:!:;O!P!Rxx}}000)xx}}''()SS.$////C H.2E2E2G H"MN rc<URR5n[U[5(aUSnUb[U[R 5(deUR SUR S4nUb"[USU-5[USU-54nU$)Nr)r'renderrFr<npndarrayshapeint)r3r5renderedr+s rr*PlayableGame._get_video_size[s88??$ h % %|H# 8RZZ(H(HHHnnQ'):;  jmd23SA9M5NOJrc*UR[R:XagURUR;a&UR R UR5 gUR[R:XaSUlggUR[R:XaAURUR;a&UR RUR5 ggUR[R:XaSUlgUR[R:XakURURS- nURURS- n[!X25nX@RS-X@RS-4Ulgg)zProcesses a PyGame event. In particular, this function is used to keep track of which buttons are currently pressed and to exit the :func:`play` function when the PyGame window is closed. Args: event: The event to process FrrNN)typer,KEYDOWNkeyr)r1appendK_ESCAPEr2KEYUPremoveQUIT WINDOWRESIZEDxr+ymin)r3event scale_width scale_heightscales r process_eventPlayableGame.process_eventgs$ :: 'yyD...!!((3foo-$ . ZZ6<< 'yyD...!!((3/ ZZ6;; & DL ZZ6// /''DOOA$66K 77T__Q%77L 2E$q'995??STCU;UVDO 0r)r'r1r)r2r0r+r)r'rr4z!dict[tuple[int, ...], int] | Noner5 float | Noner;)r4zdict[tuple[int], int] | NonereturnrH)r5rirjtuple[int, int])rcr) rrrrrr6r(r*rgrrrrrr,sUY =A!  : :>B:  Wrrc[U[R5(aUR[R:Xde[ R RU(aURSS5OU5n[ RRXB5nUR5nUSUS- S- nUSUS- S- nURS5 URXFU45 g)zDisplays a numpy array on screen. Args: screen: The screen to show the array on arr: The array to show video_size: The video size of the screen transpose: If to transpose the array on the screen rrN)rrrN)rFrPrQdtypeuint8r, surfarray make_surfaceswapaxes transformrfget_sizefillblit)r0arrr+ transposepyg_img surface_size width_offset height_offsets r display_arrr}s c2:: & &399+@@ @++)CLLA,>QTUG$$W9G??$L Ojm3q8L!!_z!}49M KK  KK 67rc URUS9 Uc^URS5(aURS5"5nO1URce[ URR S35eUce[ U[5(deUR5Hsup[ U [5(a+[U 5S:de[SU 55(deO[ U [[45(deXR;aMse 0n UR5H<up[ U [5(aU 4n [[SU 555n XU 'M> [!X U5nUcUR"R%SS 5nS unn[&R(R+5nUR,(GaU(aS nURUS9nOUS Ld[UR.5S:acU R%[[UR.55U5n UnUR1U 5unnnnnU=(d UnUbU"UUU UUUU5 UbmUR35n[ U[45(aUS nUb[ U[6R85(de[;UR<UXR>S 9 [&R@R%5HnURCU5 M [&RDRG5 URIU5 UR,(aGM[&RJ"5 g)aAllows the user to play the environment using a keyboard. If playing in a turn-based environment, set wait_on_player to True. Args: env: Environment to use for playing. transpose: If this is ``True``, the output of observation is transposed. Defaults to ``True``. fps: Maximum number of steps of the environment executed every second. If ``None`` (the default), ``env.metadata["render_fps""]`` (or 30, if the environment does not specify "render_fps") is used. zoom: Zoom the observation in, ``zoom`` amount, should be positive float callback: If a callback is provided, it will be executed after every step. It takes the following input: * obs_t: observation before performing action * obs_tp1: observation after performing action * action: action that was executed * rew: reward that was received * terminated: whether the environment is terminated or not * truncated: whether the environment is truncated or not * info: debug info keys_to_action: Mapping from keys pressed to action performed. Different formats are supported: Key combinations can either be expressed as a tuple of unicode code points of the keys, as a tuple of characters, or as a string where each character of the string represents one key. For example if pressing 'w' and space at the same time is supposed to trigger action number 2 then ``key_to_action`` dict could look like this: >>> key_to_action = { ... # ... ... (ord('w'), ord(' ')): 2 ... # ... ... } or like this: >>> key_to_action = { ... # ... ... ("w", " "): 2 ... # ... ... } or like this: >>> key_to_action = { ... # ... ... "w ": 2 ... # ... ... } If ``None``, default ``key_to_action`` mapping for that environment is used, if provided. seed: Random seed used when resetting the environment. If None, no seed is used. noop: The action used when no key input has been entered, or the entered key combination is unknown. wait_on_player: Play should wait for a user action Example: >>> import gymnasium as gym >>> import numpy as np >>> from gymnasium.utils.play import play >>> play(gym.make("CarRacing-v3", render_mode="rgb_array"), # doctest: +SKIP ... keys_to_action={ ... "w": np.array([0, 0.7, 0], dtype=np.float32), ... "a": np.array([-1, 0, 0], dtype=np.float32), ... "s": np.array([0, 0, 1], dtype=np.float32), ... "d": np.array([1, 0, 0], dtype=np.float32), ... "wa": np.array([-1, 0.7, 0], dtype=np.float32), ... "dw": np.array([1, 0.7, 0], dtype=np.float32), ... "ds": np.array([1, 0, 1], dtype=np.float32), ... "as": np.array([-1, 0, 1], dtype=np.float32), ... }, ... noop=np.array([0, 0, 0], dtype=np.float32) ... ) Above code works also if the environment is wrapped, so it's particularly useful in verifying that the frame-level preprocessing does not render the game unplayable. If you wish to plot real time statistics as you play, you can use :class:`PlayPlot`. Here's a sample code for plotting the reward for last 150 steps. >>> from gymnasium.utils.play import PlayPlot, play >>> def callback(obs_t, obs_tp1, action, rew, terminated, truncated, info): ... return [rew,] >>> plotter = PlayPlot(callback, 150, ["reward"]) # doctest: +SKIP >>> play(gym.make("CartPole-v1"), callback=plotter.callback) # doctest: +SKIP )seedNr9zJ does not have explicit key to action mapping, please specify one manuallyrc3N# UHn[U[[45v M g7fr;)rFstrrSr=s rr@play.. s>#Qz!c3Z00#s#%c3f# UH'n[U[5(a [U5OUv M) g7fr;)rFrord)r>rYs rr@rs%Xz#s333s8<s/1 render_fps)TNFrM)rxr+)&resetrBrCrDrrErFrGitemstuplelenallrrS action_spacesortedrmetadatagetr,timeClockr2r1steprOr<rPrQr}r0r+rcrgr-fliptickquit)r'rxfpsr5callbackr4rnoopwait_on_playerrYactionkey_code_to_actionkey_combinationkey_codegamedoneobsclockprev_obsrew terminated truncatedinforTrcs rplayrs@II4I    4 5 5 112FGIN88' ''%88;;- ..   %% % nd + ++ +%++-  c5 ! !s8a< <>#>>> >>cC:.. ..))))).#1#7#7#9 os + +.0O XX X (.8$ $:  6D {ll|R0ID# KK   E ,,, D)))&C u $D,=,=(>(B'++E&9J9J2K,LdSFH47HHV4D 1Cj)T*D#3ZDQ ?zz|H(D))#B<'Jx,L,L LL  X  \\%%'E   u %(  33 ,,,4 KKMrcT\rSrSrSrSSjrSSjrSrg) PlayPloti?aProvides a callback to create live plots of arbitrary metrics when using :func:`play`. This class is instantiated with a function that accepts information about a single environment transition: - obs_t: observation before performing action - obs_tp1: observation after performing action - action: action that was executed - rew: reward that was received - terminated: whether the environment is terminated or not - truncated: whether the environment is truncated or not - info: debug info It should return a list of metrics that are computed from this data. For instance, the function may look like this:: >>> def compute_metrics(obs_t, obs_tp, action, reward, terminated, truncated, info): ... return [reward, info["cumulative_reward"], np.linalg.norm(action)] :class:`PlayPlot` provides the method :meth:`callback` which will pass its arguments along to that function and uses the returned values to update live plots of the metrics. Typically, this :meth:`callback` will be used in conjunction with :func:`play` to see how the metrics evolve as you play:: >>> plotter = PlayPlot(compute_metrics, horizon_timesteps=200, # doctest: +SKIP ... plot_names=["Immediate Rew.", "Cumulative Rew.", "Action Magnitude"]) >>> play(your_env, callback=plotter.callback) # doctest: +SKIP cXlX lX0l[c [ S5e[ UR5n[R "U5uUlUlUS:XaUR/Ul[URU5HupVURU5 M SUl [U5Vs/sHnSPM snUl [U5Vs/sH n[US9PM snUlgs snfs snf)aConstructor of :class:`PlayPlot`. The function ``callback`` that is passed to this constructor should return a list of metrics that is of length ``len(plot_names)``. Args: callback: Function that computes metrics from environment transitions horizon_timesteps: The time horizon used for the live plots plot_names: List of plot titles Raises: DependencyNotInstalled: If matplotlib is not installed NrrNr)maxlen) data_callbackhorizon_timesteps plot_namespltr rsubplotsfigaxzip set_titletrangecur_plotrdata)r3rrr num_plotsaxisname_s rr6PlayPlot.__init__[s &!2$ ;(S ( LL3$' >wwiDGdggz2JD NN4 3:? :J+K:JQD:J+K >CI>NO>NU"34>NO ,LOs 9 C6C;c URXX4XVU5n[XR5HupU RU 5 M U=RS- sl[ SURUR - 5URp[UR5HupUbUR5 URU R[X5[URU 5SS9URU 'URU RX5 M [c [!S5e[R""S5 g)alThe callback that calls the provided data callback and adds the data to the plots. Args: obs_t: The observation at time step t obs_tp1: The observation at time step t+1 action: The action rew: The reward terminated: If the environment is terminated truncated: If the environment is truncated info: The information from the environment rNrNblue)crgư>)rrrrZrmaxr enumeraterr]rscatterrr<set_xlimrr pause)r3obs_tobs_tp1rrrrrpointspoint data_seriesxminxmaxiplots rrPlayPlot.callback~s*## F #&fii"8 E   u %#9 ! DFFT%;%;;rsu."$ !+2$ " !NN7# Z)ZSWSWl8 8$82A8NR80" $NR d dd d  d  d L d d ddNiiM  )) * *Q    ! KKST OJ!s*CC+C(C##C(+D  D