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: Get IQR of predicted values.
docstr_tok: ["Get","IQR","of","predicted","values","."]
code: def get_yhat_iqr(self):
      """Get IQR of predicted values."""
      if self.yhat_iqr is not None and self.yhat_prev_iqr is not None:
          return self.yhat_prev_iqr + self.yhat_iqr
      elif self.yhat_prev_iqr is not None:
          return self.yhat_prev_iqr
      elif self.yhat_iqr is not None:
          return self.yhat_iqr
      else:
          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 7 for calling the Figure obj's underlying member method code with example usage: obj.get_yhat_iqr() and returns: unknown, self, self, None