"""
Jarvis does model hyperparameter tuning on pipelines and models
to find the best features and model that works for a problem.
"""

import numpy as np
from collections import OrderedDict
from scipy.optimize import (
    differential_evolution
)
from forecasting_toolkit.feature_preprocessing.timeseries.pipelines import (
    feature_preprocessing_pipeline_factory_v1,
    feature_preprocessing_pipeline_factory_v2,
    feature_preprocessing_pipeline_factory_v3
)
from forecasting_toolkit.models.model_factory.baseline_models import (
    linear_regressor_pipeline_factory,
    gbt_regressor_pipeline_factory,
    xgb_regressor_pipeline_factory
)
from forecasting_toolkit.automl.constraints import (
    get_gbt_regressor_model_contraints
)


# Feature Preprocessing Search Space
FEATURE_PREPROCESSING_SEARCH_SPACE = [
    {
        'name': 'feature_preprocessing_v1',
        'pipeline_factory': feature_preprocessing_pipeline_factory_v1
    },
    {
        'name': 'feature_preprocessing_v2',
        'pipeline_factory': feature_preprocessing_pipeline_factory_v2
    },
    {
        'name': 'feature_preprocessing_v3',
        'pipeline_factory': feature_preprocessing_pipeline_factory_v3
    },

]

# Model Search Space
MODEL_SEARCH_SPACE = [
    {
        'name': 'gbt_regressor_pipeline',
        'model_factory': gbt_regressor_pipeline_factory,
        'constraints': get_gbt_regressor_model_contraints()
    }
]


def solve(model_factory_pool=MODEL_SEARCH_SPACE,
            feature_preprocessing_pool=FEATURE_PREPROCESSING_SEARCH_SPACE):
    """
    Search Space of 
    """
    raise NotImplementedError("Not Implemented Yet")