class_docstr: Very simple model of a power system.
  Real life is more complicated!
  
  Parameters
  ----------
  num_dams: int
      number of dams to be managed
  depth: int
      number of layers in the neural networks
  width: int
      number of neurons per hidden layer
  year_to_day_ratio: float = 2.
      Ratio between std of consumption in the year and std of consumption in the day.
  constant_to_year_ratio: float
      Ratio between constant baseline consumption and std of consumption in the year.
  back_to_normal: float
      Part of the variability which is forgotten at each time step.
  consumption_noise: float
      Instantaneous variability.
  num_thermal_plants: int
      Number of thermal plants.
  num_years: float
      Number of years.
  failure_cost: float
      Cost of not satisfying the demand. Equivalent to an expensive infinite capacity thermal plant.
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code: def get_num_vars(self) -> tp.List[tp.Any]:
      return [m.dimension for m in self.dam_agents]
  
file_path: nevergrad/nevergrad/functions/powersystems/core.py
imports: import typing
  from math import pi, cos, sin
  import matplotlib.pyplot
  import numpy
  from nevergrad.parametrization import parameter
  from ..base import ExperimentFunction
label_desc: Use image node_id 2 for calling the PowerSystem obj's underlying member method code with example usage: obj.get_num_vars() and returns: unknown