text: import numpy as np
  import re
  
  import matplotlib.pyplot as plt
  import matplotlib as mpl
  plt.rcParams["font.family"] = "Times New Roman"
  mpl.rcParams['xtick.direction'] = 'in'
  mpl.rcParams['ytick.direction'] = 'in'
  fontsize = 9
  mpl.rcParams['axes.labelsize'] = fontsize
  mpl.rcParams['xtick.labelsize'] = fontsize
  mpl.rcParams['ytick.labelsize'] = fontsize
  mpl.rcParams['legend.fontsize'] = fontsize
  #mpl.rcParams['title.fontsize'] = fontsize
  mpl.rcParams['font.size'] = fontsize
  mpl.rcParams['axes.titlepad'] = 7
  mpl.rcParams['savefig.dpi'] = 300
  plt.rcParams["figure.figsize"] = [4, 3]
  
  take_ln = True
  moving_avg = True
  save = True
  save_val = True
  window_size = 2500
  dataset_num = 8
  mean_from_last = 20000
  remove_repeats = True #Caused by starting from the same counter multiple times
  
  scale = 1
  ratio = 1.618
  width = scale * 3.3
  height = (width / 1.618)
  num_data_to_use = 20000
  num_hist_bins = 200
  mse_x_to = 0.012
  
  f = plt.figure()
  
  labels_sets = [["1/17.9", "1/27.3", "1/38.2", "1/50.0", "1/60.5", "1/73.7", "1/87.0"]]
  
  
  sets = [[74, 71, 75, 72, 77, 73, 76]]
  
  f = plt.figure()
  ax = f.add_subplot(111)
  
  losses_sets = []
  iters_sets = []
  for i, (data_nums, labels) in enumerate(zip(sets, labels_sets)):
  
      #ax._frameon = False
  
      #ax = f.add_subplot(1, 2, i+1)
      ax.xaxis.set_ticks_position('both')
      ax.yaxis.set_ticks_position('both')
      ax.tick_params(labeltop=False, labelright=False)
      ax.minorticks_on()
      for j, dataset_num in enumerate(data_nums):
          if not i:
              hist_loc = ("Z:/Jeffrey-Ede/models/stem-random-walk-nin-20-"+str(dataset_num)+"/")
              hist_file = hist_loc+"mses.npy"
          else:
              hist_file = f"Z:/Jeffrey-Ede/models/stem-random-walk-nin-20-68/mses-{dataset_num}.npy"
  
          mses = np.load(hist_file) /2
          #for x in mses: print(x)
          #print(np.mean(mses), np.std(mses))
          #print(len([x for x in mses if x >= 10]))
          mses = [np.sqrt(x) for x in mses if x < 0.05]
  
          bins, edges = np.histogram(mses, 100)
              
          edges = 0.5*(edges[:-1] + edges[1:])
  
          ax.plot(edges, bins, label=labels[j], linewidth=1)
  
      ax.set_ylabel('Frequency')
      ax.set_xlabel('Root Mean Squared Error')
  
      #ax.set_ylim(-100, 2175)
  
      plt.legend(loc='upper right', frameon=False, fontsize=8)
  
      plt.minorticks_on()
      
  #f.subplots_adjust(wspace=0.22, hspace=0.26)
  #f.subplots_adjust(left=.00, bottom=.00, right=1., top=1.)
  
  #f.set_size_inches(width, height)
  
  save_loc =  "Z:/Jeffrey-Ede/models/stem-random-walk-nin-figures/partial_hist.png"
  plt.savefig( save_loc, bbox_inches='tight', )
  
  #plt.gcf().clear()
  