code: def plot_samples(samples, parameters, y_axis_label):
      plt.figure(figsize=(8, 4))
      for val, param in zip(samples, parameters):
          plt.plot(tf.squeeze(val), label=param_to_name[param])
      plt.legend(bbox_to_anchor=(1.0, 1.0))
      plt.xlabel("HMC iteration")
      plt.ylabel(y_axis_label)
  
file_path: GPflow/notebooks/advanced/mcmc.pct.py
imports: import matplotlib.pyplot
  import numpy
  import tensorflow
  import tensorflow_probability
  from multiclass_classification import colors, plot_from_samples
  from tensorflow_probability import distributions
  import gpflow
  from gpflow import set_trainable
  from gpflow.ci_utils import reduce_in_tests
label_desc: Use image node_id 3 for calling a global function with example usage: plot_samples(samples, parameters, y_axis_label) without return types