code: def get_plot_directory(model):
      r"""Get the plot output directory of a model.
  
      Parameters
      ----------
      model : alphapy.Model
          The model object with directory information.
  
      Returns
      -------
      plot_directory : str
          The output directory to write the plot.
  
      """
      directory = model.specs["directory"]
      plot_directory = SSEP.join([directory, "plots"])
      return plot_directory
  
imports: from alphapy.estimators import get_estimators
  from alphapy.globals import BSEP, PSEP, SSEP, USEP
  from alphapy.globals import ModelType
  from alphapy.globals import Partition, datasets
  from alphapy.globals import Q1, Q3
  from alphapy.utilities import remove_list_items
  from bokeh.plotting import figure, show, output_file
  import itertools
  import logging
  import math
  import matplotlib
  import matplotlib.pyplot
  from mpl_toolkits.mplot3d import Axes3D
  import numpy
  import pandas
  from scipy import interp
  import seaborn
  from sklearn.calibration import calibration_curve
  from sklearn.inspection import partial_dependence
  from sklearn.inspection import plot_partial_dependence
  from sklearn.metrics import auc
  from sklearn.metrics import confusion_matrix
  from sklearn.metrics import roc_curve
  from sklearn.model_selection import cross_val_score
  from sklearn.model_selection import learning_curve
  from sklearn.model_selection import StratifiedKFold
  from sklearn.model_selection import train_test_split
  from sklearn.model_selection import validation_curve
  from sklearn.utils.multiclass import unique_labels
label_desc: Use image node_id 3 for calling a global function with example usage: get_plot_directory(model) and returns: plot_directory