import json

import gradio as gr
from gr_app2 import args, GradioApp

demo = gr.Blocks(**args.block)

with demo:
    app = GradioApp()

    md__title = gr.Markdown(**args.md__title)

    with gr.Row():
        with gr.Column():
            file__historical = gr.File(**args.file__historical)

        with gr.Column():
            file__future = gr.File(**args.file__future)
            md__future = gr.Markdown(**args.md__future)

    with gr.Row():
        btn__load_historical_demo = gr.Button("Load Demo Historical Data")
        btn__load_future_demo = gr.Button("Load Demo Future Data")

    with gr.Row():
        number__n_predict = gr.Number(
            value=app.n_predict,
            **args.number__n_predict)

        number__window_length = gr.Number(
            value=app.window_length,
            **args.number__window_length
        )

        textbox__target_column = gr.Textbox(
            value=app.target_column,
            **args.textbox__target_column
        )

        number__n_predict.change(
            app.number__n_predict__change,
            [number__n_predict]
        )

        number__window_length.change(
            app.number__window_length__change,
            [number__window_length]
        )

        textbox__target_column.change(
            app.textbox__target_column__change,
            [textbox__target_column]
        )

    # ---------- #
    # Data Views #
    # ---------- #

    with gr.Tabs():
        with gr.Tab('Table View'):
            df__table_view = gr.Dataframe(**args.df__table_view)

        with gr.Tab('Chart View'):
            dropdown__chart_view_filter = gr.Dropdown(
                multiselect=True,
                label='Filter')
            plot__chart_view = gr.Plot()

        with gr.Tab('Seasonality and Auto Correlation'):
            dropdown__seasonality_decompose = gr.Dropdown(
                label='Please select column to decompose')

            with gr.Row():
                plot__seasonality_decompose = gr.Plot()
                plot_acg_pacf = gr.Plot()

        with gr.Tab('Correlations'):
            btn__plot_correlation = gr.Button('Plot Correlations')
            plot__correlation = gr.Plot()

            btn__plot_correlation.click(
                app.btn__plot_correlation__click,
                [],
                [plot__correlation]
            )

        with gr.Tab("Data Profile"):
            btn__profiling = gr.Button('Profile Data')
            md__profiling = gr.Markdown()
            plot__change_points = gr.Plot()

        dropdown__seasonality_decompose.change(
            app.dropdown__seasonality_decompose__change,
            [dropdown__seasonality_decompose],
            [plot__seasonality_decompose,
             plot_acg_pacf]
        )

        btn__profiling.click(
            app.btn__profiling__click,
            [],
            [md__profiling,
             plot__change_points]
        )

    # ---------------------- #
    # Fit data to forecaster #
    # ---------------------- #

    btn__fit_data = gr.Button(**args.btn__fit_data)

    # =========== #
    # Forecasting #
    # =========== #

    column__models = gr.Column(visible=True)

    with column__models:
        md__fit_ready = gr.Markdown(**args.md__fit_ready)

        md__forecast_data_info = gr.Markdown()

        # ------------- #
        # Model Configs #
        # ------------- #

        with gr.Row():
            checkbox__round_results = gr.Checkbox(
                app.round_results,
                label='Round Results',
                interactive=True)

            checkbox__round_results.change(
                app.checkbox__round_results__change,
                [checkbox__round_results],
                []
            )

        gr.Markdown('## Models')
        # ------- #
        # XGBoost #
        # ------- #
        with gr.Tab('XGBoost'):

            with gr.Row():
                checkbox__xgboost_cv = gr.Checkbox(
                    app.xgboost_cv, label='Cross Validation')
                checkbox__xgboost_round = gr.Checkbox(
                    app.xgboost.round_result,
                    label='Round Result',
                    interactive=True)

                checkbox__xgboost_round.change(
                    app.checkbox__xgboost_round__change,
                    [checkbox__xgboost_round],
                    []
                )

            with gr.Row():
                with gr.Column():
                    textbox__xgboost_params = gr.Textbox(
                        interactive=True,
                        value=app.xgboost_params)

                    btn__set_xgboost_params = gr.Button("Set Params")

                json_xgboost_params = gr.JSON(
                    value=app.xgboost_params,
                    **args.json_xgboost_params)

                btn__set_xgboost_params.click(
                    app.btn__set_xgboost_params__click,
                    [textbox__xgboost_params],
                    [json_xgboost_params])

            btn__train_xgboost = gr.Button("Forecast with XGBoost Model")

            plot__xgboost_result = gr.Plot()

            with gr.Row():
                df__xgboost_result = gr.Dataframe()
                file__xgboost_result = gr.File()

            btn__train_xgboost.click(
                app.btn__train_xgboost__click,
                [],
                [plot__xgboost_result,
                 file__xgboost_result,
                 df__xgboost_result])

        # ------- #
        # Prophet #
        # ------- #
        with gr.Tab('Prophet'):
            gr.Markdown('Prophet')

            btn__forecast_with_prophet = gr.Button(
                **args.btn__forecast_with_prophet)

            plot__prophet_result = gr.Plot()

            with gr.Row():
                df__prophet_result = gr.DataFrame()
                file__prophet_result = gr.File()

        btn__forecast_with_prophet.click(
            app.btn__forecast_with_prophet__click,
            [],
            [plot__prophet_result,
             file__prophet_result,
             df__prophet_result]
        )

    # --------- #
    # Operators #
    # --------- #

    file__historical.upload(
        app.file__historical__upload,
        [file__historical],
        [df__table_view,
         dropdown__chart_view_filter,
         dropdown__seasonality_decompose,
         plot__chart_view])

    file__future.upload(
        app.file__future__upload,
        [file__future],
        [df__table_view,
         dropdown__chart_view_filter,
         dropdown__seasonality_decompose,
         plot__chart_view,
         number__n_predict])

    btn__fit_data.click(
        app.btn__fit_data__click,
        [],
        [
            number__n_predict,
            number__window_length,
            file__historical,
            file__future,
            btn__fit_data,
            column__models,
            btn__load_historical_demo,
            btn__load_future_demo,
            md__forecast_data_info,
        ])

    btn__load_historical_demo.click(
        app.btn__load_historical_demo__click,
        [],
        [df__table_view,
         dropdown__chart_view_filter,
         dropdown__seasonality_decompose,
         plot__chart_view,]
    )

    btn__load_future_demo.click(
        app.btn__load_future_demo__click,
        [],
        [df__table_view,
         dropdown__chart_view_filter,
         dropdown__seasonality_decompose,
         plot__chart_view,
         number__n_predict]
    )

    dropdown__chart_view_filter.change(
        app.dropdown__chart_view_filter__change,
        [dropdown__chart_view_filter],
        [plot__chart_view]
    )

demo.launch()