----------------------
- [BREAKING] `Issue 83 <https://github.com/Grid2Op/grid2op/issues/83>`_: attributes name of the Parameters class
are now more consistent with the rest of the package. Use `NB_TIMESTEP_OVERFLOW_ALLOWED`
instead of `NB_TIMESTEP_POWERFLOW_ALLOWED`, `NB_TIMESTEP_COOLDOWN_LINE` instead of `NB_TIMESTEP_LINE_STATUS_REMODIF`
and `NB_TIMESTEP_COOLDOWN_SUB` instead of `NB_TIMESTEP_TOPOLOGY_REMODIF`
- [BREAKING] `Issue 87 <https://github.com/Grid2Op/grid2op/issues/87>`_: algorithm of the environment that solves
the redispatching to make sure the environment meet the phyiscal constraints is now cast into an optimization
routine that uses `scipy.minimize` to be solved. This has a few consequences: more dispatch actions are tolerated,
computation time can be increased in some cases, when the optimization problem cannot be solved, a game
over is thrown, `scipy` is now a direct dependency of `grid2op`, code base of `grid2op` is simpler.
- [BREAKING] any attempt to use an un intialized environment (*eg* after a game over but before calling `env.reset`
will now raise a `Grid2OpException`)
- [FIXED] `Issue 84 <https://github.com/Grid2Op/grid2op/issues/84>`_: it is now possible to load multiple
environments in the same python script and perform random action on each.
- [FIXED] `Issue 86 <https://github.com/Grid2Op/grid2op/issues/86>`_: the proper symmetries are used to generate
all the actions that can "change" the buses (`SerializationActionSpace.get_all_unitary_topologies_change`).
- [FIXED] `Issue 88 <https://github.com/Grid2Op/grid2op/issues/88>`_: two flags are now used to tell the environment
whether or not to activate the possibility to dispatch a turned on generator (`forbid_dispatch_off`) and whether
or not to ignore the gen_min_uptimes and gen_min_downtime propertiers (`ignore_min_up_down_times`) that
are initialized from the Parameters of the grid now.
- [FIXED] `Issue 89 <https://github.com/Grid2Op/grid2op/issues/89>`_: pandapower backend should not be compatible
with changing the bus of the generator representing the slack bus.
- [FIXED] Greedy agents now uses the proper data types `dt_float` for the simulated reward (previously it was platform
dependant)
- [ADDED] A way to limit `EpisodeReplay` to a specific part of the episode. Two arguments have been added, namely:
`start_step` and `end_step` that default to the full episode duration.
- [ADDED] more flexibilities in `IdToAct` converter not to generate every action for both set and change for example.
This class can also serialize and de serialize the list of all actions with the save method (to serialize) and the
`init_converter` method (to read back the data).
- [ADDED] a feature to have multiple difficulty levels per dataset.
- [ADDED] a converter to transform prediction in connectivity of element into valid grid2op action. See
`Converter.ConnectivitiyConverter` for more information.
- [ADDED] a better control for the seeding strategy in `Environment` and `MultiEnvironment` to improve the
reproducibility of the experiments.
- [ADDED] a chronics class that is able to generate maintenance data "on the fly" instead of reading the from a file.
This class is particularly handy to train agents with different kind of maintenance schedule.