# Configuration file for the data dimensionality sensitivity experiment
# ==============================================================================

# Defaults
defaults:
  - _self_

  # Simulation settings
  - /simulator: t_simulator #ty_simulator

  # Model parametrization
  - /models@EconML_CausalForestDML: EconML_CausalForestDML
  - /models@EconML_DML: EconML_DML
  - /models@EconML_DMLOrthoForest: EconML_DMLOrthoForest
  - /models@EconML_DRLearner: EconML_DRLearner
  - /models@EconML_DROrthoForest: EconML_DROrthoForest
  - /models@EconML_ForestDRLearner: EconML_ForestDRLearner
  - /models@EconML_LinearDML: EconML_LinearDML
  - /models@EconML_LinearDRLearner: EconML_LinearDRLearner
  - /models@EconML_SparseLinearDML: EconML_SparseLinearDML
  - /models@EconML_SparseLinearDRLearner: EconML_SparseLinearDRLearner #EconML_SparseLinearDRLearner
  - /models@EconML_SLearner_Lasso: EconML_SLearner_Lasso
  - /models@EconML_TLearner_Lasso: EconML_TLearner_Lasso
  - /models@EconML_XLearner_Lasso: EconML_XLearner_Lasso

  - /models@Torch_SLearner: Torch_SLearner
  - /models@Torch_TLearner: Torch_TLearner
  - /models@Torch_XLearner: Torch_XLearner
  - /models@Torch_DRLearner: Torch_DRLearner
  - /models@Torch_RLearner: Torch_RLearner
  - /models@Torch_TARNet: Torch_TARNet
  - /models@Torch_DragonNet: Torch_DragonNet
  - /models@Torch_DragonNet_2: Torch_DragonNet_2
  - /models@Torch_DragonNet_4: Torch_DragonNet_4
  - /models@Torch_ULearner: Torch_ULearner
  - /models@Torch_RALearner: Torch_RALearner
  - /models@Torch_PWLearner: Torch_PWLearner
  - /models@Torch_FlexTENet: Torch_FlexTENet
  - /models@Torch_CRFNet_0_01: Torch_CRFNet_0_01
  - /models@Torch_CRFNet_0_001: Torch_CRFNet_0_001
  - /models@Torch_CRFNet_0_0001: Torch_CRFNet_0_0001
  - /models@Torch_ActionNet: Torch_ActionNet

  - /models@DiffPOLearner: DiffPOLearner

# EXPERIMENT AND DATA
# ==============================================================================
experiment_name: "data_dimensionality_sensitivity"
# ==============================================================================

# EXPERIMENTAL KNOB
# ==============================================================================
# Cohort sizes to be tested
data_dims: [500, 1000, 1500, 2000, 2500, 3000] #[1000, 4000, 7000, 11000, 15000, 18000] #[25,32,40,47,55]

compare_axis: "propensity" # "num_important_features"

sim_propensity_type: "none_pred"
sim_alpha: 1
propensity_scales: [0, 2, 100]
sample_sizes: [0.5, 1] # [0.3,0.6,0.9]
n_samples: null
important_feature_nums: [5, 10] # [5, 10, 15, 20, 25, 30, 35, 40, 45, 50]
# ==============================================================================