Converters

class grid2op.Converter.Converter(action_space)

This Base class should be use to implement any converter. If for some reasons

convert_act(encoded_act)

This function will transform the action, encoded somehow (for example identified by an id, represented by an integer) to a valid actions that can be processed by the environment.

Parameters

encoded_act (object) – Representation of an action, as a vector or an integer etc.

Returns

regular_act – The action corresponding to the encoded_action above converted into a format that can be processed by the environment.

Return type

grid2op.Action.Action

convert_obs(obs)

This function is used to convert an observation into something that is easier to manipulate.

Parameters

obs (grid2op.Observation.Observation) – The input observation.

Returns

transformed_obs – An different representation of the input observation, typically represented as a 1d vector that can be processed by a neural networks.

Return type

object

class grid2op.Converter.IdToAct(action_space)

This type of converter allows to represent action with unique id. Instead of manipulating complex objects, it allows to manipulate only positive integer.

The list of all actions can either be the list of all possible unary actions (see below for a complete description) or by a given pre computed list.

A “unary action” is an action that consists only in acting on one “concept” it includes:

• disconnecting a single powerline

• reconnecting a single powerline and connect it to bus xxx on its origin end and yyy on its extremity end

• changing the topology of a single substation

Examples of non unary actions include: - disconnection / reconnection of 2 or more powerlines - change of the configuration of 2 or more substations - disconnection / reconnection of a single powerline and change of the configration of a single substation

NB All the actions created automatically are unary. For the L2RPN 2019, agent could be allowed to act with non unary actions, for example by disconnecting a powerline and reconfiguring a substation. This class would not allow to do such action at one time step.

NB The actions that are initialized by default uses the “set” way and not the “change” way (see the description of grid2op.BaseAction.BaseAction for more information).

For each powerline, 5 different actions will be computed:

• disconnect it

• reconnect it and connect it to bus 1 on “origin” end ann bus 1 on “extremity” end

• reconnect it and connect it to bus 1 on “origin” end ann bus 2 on “extremity” end

• reconnect it and connect it to bus 2 on “origin” end ann bus 1 on “extremity” end

• reconnect it and connect it to bus 2 on “origin” end ann bus 2 on “extremity” end

Actions corresponding to all topologies are also used by default. See grid2op.BaseAction.ActionSpace.get_all_unitary_topologies_set() for more information.

In this converter:

• encoded_act are positive integer, representing the index of the actions.

• transformed_obs are regular observations.

convert_act(encoded_act)

In this converter, we suppose that “encoded_act” is an id of an action stored in the IdToAct.all_actions list.

Converting an id of an action (here called “act”) into a valid action is then easy: we just need to take the “act”-th element of IdToAct.all_actions.

Parameters

encoded_act (int) – The id of the action

Returns

action – The action corresponding to id “act”

Return type

grid2op.Action.Action

init_converter(all_actions=None, **kwargs)

This function is used to initialized the converter. When the converter is created, this method should be called otherwise the converter might be in an unstable state.

Parameters

• all_actions (list) – The (ordered) list of all actions that the agent will be able to perform. If given a number i the converter will return action all_actions[i]. In the “pacman” game, this vector could be [“up”, “down”, “left”, “right”], in this case “up” would be encode by 0, “down” by 1, “left” by 2 and “right” by 3. If nothing is provided, the converter will output all the unary actions possible for the environment. Be careful, computing all these actions might take some time.

• kwargs – other keyword arguments

sample()

Having define a complete set of observation an agent can do, sampling from it is now made easy.

One action amoung the n possible actions is used at random.

Returns

res – An id of an action.

Return type

int

class grid2op.Converter.ToVect(action_space)

This converters allows to manipulate the vector representation of the actions and observations.

In this converter:

• encoded_act are numpy ndarray

• transformed_obs are numpy ndarray

convert_act(encoded_act)

In this converter encoded_act is a numpy ndarray. This function transforms it back to a valid action.

Parameters

encoded_act (numpy.ndarray) – The action, representated as a vector

Returns

regular_act – The corresponding action transformed with the grid2op.BaseAction.BaseAction.from_vect().

Return type

grid2op.Action.Action

convert_obs(obs)

This converter will match the observation to a vector, using the grid2op.BaseObservation.BaseObservation.to_vect() function.

Parameters

obs (grid2op.Observation.Observation) – The observation, that will be processed into a numpy ndarray vector.

Returns

transformed_obs – The vector representation of the action.

Return type

numpy.ndarray

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