ó Ìniãó&•SrSSKr"SS\5rg)z/Abstract base class for environment randomizer.éNcó`•\rSrSrSr\R r\RS5r Sr Sr Sr g)ÚEnvRandomizerBaseéz«Abstract base class for environment randomizer. Randomizes physical parameters of the objects in the simulation and adds perturbations to the stepping of the simulation. có•g)aRandomize the simulated_objects in the environment. Will be called at when env is reset. The physical parameters will be fixed for that episode and be randomized again in the next environment.reset(). Args: env: The Minitaur gym environment to be randomized. N©©ÚselfÚenvs Úi/home/james-whalen/.local/lib/python3.13/site-packages/pybullet_envs/minitaur/envs/env_randomizer_base.pyÚ randomize_envÚEnvRandomizerBase.randomize_envs€ð ócó•g)a_Randomize environment steps. Will be called at every environment step. It is NOT recommended to use this for force / torque disturbance because pybullet applyExternalForce/Torque only persist for single simulation step not the entire env step which can contain multiple simulation steps. Args: env: The Minitaur gym environment to be randomized. Nrrs r Úrandomize_stepÚ EnvRandomizerBase.randomize_steps€ð rcó•g)aJRandomize simulation sub steps. Will be called at every simulation step. This is the correct place to add random forces/torques. Args: env: The Minitaur gym environment to be randomized. sub_step_index: Index of sub step, from 0 to N-1. N is the action repeat. num_sub_steps: Number of sub steps, equals to action repeat. Nr)r r Úsub_step_indexÚ num_sub_stepss r Úrandomize_sub_stepÚ$EnvRandomizerBase.randomize_sub_step)s€ð rrN) Ú__name__Ú __module__Ú __qualname__Ú__firstlineno__Ú__doc__ÚabcÚABCMetaÚ __metaclass__Úabstractmethodr rrÚ__static_attributes__rrr rrs4†ñð —+‘+€-à×Ññ  óð  ò  õ  rr)rrÚobjectrrrr Úr"sðÙ5ã ô. ˜õ. r