code: def plot_custom_season(
      m, comp_name, quantile, multiplicative=False, df_name="__df__"
  ):
      """Plot any seasonal component of the forecast.
  
      Parameters
      ----------
          m : NeuralProphet
              Fitted model
          comp_name : str
              Name of seasonality component
          quantile : float
              The quantile for which the custom season is plotted
          multiplicative : bool
              Flag whether to set y axis as percentage
          df_name : str
              Name of dataframe to refer to data params from original keys of train dataframes
  
              Note
              ----
              Only used for local normalization in global modeling
      Returns
      -------
          Dictionary with plotly traces, xaxis and yaxis
  
      """
  
      traces = []
      line_width = 2
  
      t_i, predicted = predict_one_season(
          m,
          quantile=quantile,
          name=comp_name,
          n_steps=300,
          df_name=df_name,
      )
      traces = []
  
      traces.append(
          go.Scatter(
              name=comp_name,
              x=t_i,
              y=predicted,
              mode="lines",
              line=dict(color=color, width=line_width),
              fill="none",
          )
      )
      padded_range = get_dynamic_axis_range(t_i, type="numeric")
      xaxis = go.layout.XAxis(
          title=f"One period: {comp_name}",
          range=padded_range,
      )
      yaxis = go.layout.YAxis(
          rangemode="normal",
          title=go.layout.yaxis.Title(text=f"Seasonality: {comp_name}"),
      )
  
      if multiplicative:
          yaxis.update(tickformat=".1%", hoverformat=".4%")
  
      return {"traces": traces, "xaxis": xaxis, "yaxis": yaxis}
  
file_path: neural_prophet/neuralprophet/plot_model_parameters_plotly.py
imports: import datetime
  import logging
  import numpy
  import pandas
  from neuralprophet.plot_utils import predict_one_season, predict_season_from_dates
label_desc: Use image node_id 9 for calling a global function with example usage: plot_custom_season(m, comp_name, quantile, multiplicative, df_name) and returns: dict