text: # %% Load packages
  
  import numpy as np
  
  import kanga.plots as ps
  
  from bnn_mcmc_examples.examples.mlp.noisy_xor.setting1.mcmc.constants import num_chains
  from bnn_mcmc_examples.examples.mlp.noisy_xor.setting1.mcmc.metropolis_hastings.constants import (
      sampler_output_path, sampler_output_run_paths
  )
  
  # %% Load correlation matrices
  
  mc_cor_mats = []
  for i in range(num_chains):
      mc_cor_mats.append(np.loadtxt(sampler_output_run_paths[i].joinpath('mc_cor.csv'), delimiter=',', skiprows=0))
  mc_cor_mats = np.stack(mc_cor_mats)
  
  mean_mc_cor_mat = np.loadtxt(sampler_output_path.joinpath('mean_mc_cor.csv'), delimiter=',', skiprows=0)
  
  # %% Plot heat maps of correlation matrices
  
  for i in range(num_chains):
      ps.cor_heatmap(mc_cor_mats[i], fname=sampler_output_run_paths[i].joinpath('mc_cor.png'))
  
  ps.cor_heatmap(mean_mc_cor_mat, fname=sampler_output_path.joinpath('mean_mc_cor.png'))
  