class_docstr: Class for visualizing predictions of univariate anomaly detection & forecasting models.
class_docstr_tok: ["Class","for","visualizing","predictions","of","univariate","anomaly","detection","&","forecasting","models","."]
docstr: :return: Time splitting train from test.
docstr_tok: [":","return",":","Time","splitting","train","from","test","."]
code: def t_split(self):
      """
      :return: Time splitting train from test.
      """
      if self.y_prev is not None:
          return self.y_prev.index[-1]
      if self.yhat_prev is not None:
          return self.yhat_prev.index[-1]
      return None
  
imports: import logging
  from typing import Dict
  from copy import copy
  from matplotlib.colors import to_rgb
  from matplotlib.dates import AutoDateLocator, AutoDateFormatter
  import matplotlib.pyplot
  import numpy
  import pandas
  import plotly
  import plotly.graph_objects
  from plotly.subplots import make_subplots
  from merlion.utils import TimeSeries, UnivariateTimeSeries
label_desc: Use image node_id 4 for calling the Figure obj's underlying member method code with example usage: obj.t_split() and returns: None, self, self