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#   CONFIGURATIONS FOR STATISTICAL DOWNSCALING EXPERIMENT WITH VARIATIONAL CME PROCESS WITH INDIVIDUALS NOISE
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# MODEL SPECIFICATIONS
model:
  # Name of model to use
  name: 'variational_cmp'

  # CME regularization parameter
  lbda: 0.00001

  # Number of inducing points
  n_inducing_points: 800

  # Whether to use noised individuals model or not
  use_individuals_noise: True

  # Random seed for inducing points selection
  seed: 42


# DATASET
dataset:
  # Path to fields to load
  path: 'experiments/downscaling/data/orog_clt_albisccp_pctisccp_ttop_lat360_lon720_195003.nc'

  # Names of fields used as covariates
  covariate_fields_names:
    - 'orog'        # Surface Altitude
    - 'albisccp'    # Cloud Albedo
    - 'clt'         # Total Cloud Coverage

  # Names of fields used as mediating covariates
  bags_fields_names:
    - 'pctisccp'    # Mean Cloud Top Pressure

  # Name of field to use as target
  target_field_name: 'ttop'   # Cloud Top Temperature

  # Downsampling block size
  block_size:
    - 17             # height
    - 17             # width

  # Random seed for dataset generation
  seed: 42



# TRAINING
training:
  # Name of model to use
  name: 'variational_cmp'

  # Fraction of missing bags
  missing_bags_fraction: 0.5

  # Whether to use noised individuals model or not
  use_individuals_noise: True

  # Learning rate
  lr: 0.01

  # Number of iterations
  n_epochs: 701

  # Batch size
  batch_size: 64

  # Number of samples used for batch CMO estimation
  batch_size_cme: 400

  # Weight of KL term in ELBO
  beta: 1

  # Plot end of epoch inference every n epoch
  plot_every: 100

  # Log end of epoch inference every n epoch
  log_every: 5

  # Random seed used to choose shuffle dataset
  seed: 42



# EVALUATION
evaluation:
