old_contents: # Licensed under an MIT open source license - see LICENSE
  
  '''
  KS p-values for different properties.
  '''
  
  import numpy as np
  from pandas import read_csv
  import matplotlib.pyplot as p
  import numpy as np
  import seaborn as sn
  sn.set_context('talk')
  sn.set_style('ticks')
  sn.mpl.rc("figure", figsize=(7, 9))
  
  # Widths
  
  widths = read_csv("width_ks_table_pvals.csv")
  
  widths.index = widths["Unnamed: 0"]
  del widths["Unnamed: 0"]
  
  widths_arr = np.asarray(widths)
  
  widths_arr[np.arange(0, 14), np.arange(0, 14)] = 1.0
  
  widths_arr = -np.log10(widths_arr)
  
  # p.figure(figsize=(12, 10))
  p.subplot(211)
  # p.xlabel("Widths")
  p.imshow(widths_arr, origin='lower', cmap='binary', interpolation='nearest')
  p.xticks(np.arange(0, 14), [], rotation=90)
  p.yticks(np.arange(0, 14), widths.columns)
  
  p.figtext(0.05, 0.95, "a)", fontsize=20)
  
  cb = p.colorbar()
  cb.set_label(r'$-\log_{10}$ p-value')
  cb.solids.set_edgecolor("face")
  # p.tight_layout()
  
  # p.show()
  # Curvature
  
  curve = read_csv("curvature_ks_table_pvals.csv")
  
  curve.index = curve["Unnamed: 0"]
  del curve["Unnamed: 0"]
  
  curve_arr = np.asarray(curve)
  
  curve_arr[np.arange(0, 14), np.arange(0, 14)] = 1.0
  
  curve_arr = -np.log10(curve_arr)
  
  # p.figure(figsize=(12, 10))
  p.subplot(212)
  # p.xlabel("Curvature")
  p.imshow(curve_arr, interpolation='nearest', origin='lower', cmap='binary')
  p.xticks(np.arange(0, 14), curve.columns, rotation=90)
  p.yticks(np.arange(0, 14), curve.columns)
  
  p.figtext(0.05, 0.55, "b)", fontsize=20)
  
  cb = p.colorbar()
  cb.set_label(r'$-\log_{10}$ p-value')
  cb.solids.set_edgecolor("face")
  
  p.tight_layout()
  
  p.show()
  
new_contents: # Licensed under an MIT open source license - see LICENSE
  
  '''
  KS p-values for different properties.
  '''
  
  import numpy as np
  from pandas import read_csv
  import matplotlib.pyplot as p
  import numpy as np
  import seaborn as sn
  sn.set_context('talk')
  sn.set_style('ticks')
  sn.mpl.rc("figure", figsize=(7, 9))
  
  # Widths
  
  widths = read_csv("width_ks_table_pvals.csv")
  
  widths.index = widths["Unnamed: 0"]
  del widths["Unnamed: 0"]
  
  widths_arr = np.asarray(widths)
  
  widths_arr[np.arange(0, 14), np.arange(0, 14)] = 1.0
  
  widths_arr = -np.log10(widths_arr)
  
  # p.figure(figsize=(12, 10))
  p.subplot(211)
  # p.xlabel("Widths")
  p.imshow(widths_arr, origin='lower', cmap='binary', interpolation='nearest')
  p.xticks(np.arange(0, 14), [], rotation=90)
  p.yticks(np.arange(0, 14), widths.columns)
  
  p.figtext(0.05, 0.95, "a)", fontsize=20)
  
  cb = p.colorbar()
  cb.set_label(r'$-\log_{10}$ p-value')
  cb.solids.set_edgecolor("face")
  p.tight_layout()
  
  p.show()
  # Curvature
  
  curve = read_csv("curvature_branches_ks_table_pvals.csv")
  
  curve.index = curve["Unnamed: 0"]
  del curve["Unnamed: 0"]
  
  curve_arr = np.asarray(curve)
  
  curve_arr[np.arange(0, 14), np.arange(0, 14)] = 1.0
  
  curve_arr = -np.log10(curve_arr)
  
  # p.figure(figsize=(12, 10))
  p.subplot(212)
  # p.xlabel("Curvature")
  p.imshow(curve_arr, interpolation='nearest', origin='lower', cmap='binary')
  p.xticks(np.arange(0, 14), curve.columns, rotation=90)
  p.yticks(np.arange(0, 14), curve.columns)
  
  p.figtext(0.05, 0.55, "b)", fontsize=20)
  
  cb = p.colorbar()
  cb.set_label(r'$-\log_{10}$ p-value')
  cb.solids.set_edgecolor("face")
  
  p.tight_layout()
  
  p.show()
  
subject: Use branches