old_contents: from beauty import *
  #### Parameters I chose arbitrarily
  USE_TEX = True      # whether or not to render *all* text w/latex
  USE_SERIFS = False   # serif vs san-serif font (computer modern)
  LEGEND_FONT_SIZE = TICK_FONT_SIZE = 9
  TITLE_FONT_SIZE = LABEL_FONT_SIZE = 10.5
  
  DPI = 150 # Font size adjustments should scale with this
  
  #### Automatic parameter setting
  # Figure size/scale
  matplotlib.rc('savefig', dpi=DPI)
  matplotlib.rc('figure', dpi=DPI, figsize=(2,2))
  # Font
  matplotlib.rc('xtick',labelsize=TICK_FONT_SIZE)
  matplotlib.rc('ytick',labelsize=TICK_FONT_SIZE)
  matplotlib.rc('axes', labelsize=LABEL_FONT_SIZE, titlesize=TITLE_FONT_SIZE)
  matplotlib.rc('legend', fontsize=LEGEND_FONT_SIZE)
  
  if USE_SERIFS:
      matplotlib.rc('font', **{'family':'serif', 'serif':['Computer Modern Roman']})
  else:
      matplotlib.rc('font', **{'family':'sans-serif', 'sans-serif':['Computer Modern Sans serif']})
      if USE_TEX:
          matplotlib.rcParams['text.latex.preamble'].append('\usepackage{sfmath}')
  matplotlib.rcParams.update({'text.usetex':USE_TEX})
  
  ### Colors modeled after d3.js's `category10` color scale
  ### (defined like this so it's easy to use 'beauty.blue' as a color)
  blue = '#1f77b4'
  darkblue = dim(blue, 0.75)
  
  orange = '#ff7f0e'
  darkorange = dim(orange, 0.75)
  
  green =  '#2ca02c'
  darkgreen = dim(green, 0.75)
  
  red =  '#d62728'
  darkred = dim(red, 0.75)
  
  purple = '#9467bd'
  darkpurple = dim(purple, 0.75)
  
  brown = '#8c564b'
  darkbrown = dim(brown, 0.75)
  
  pink = '#e377c2'
  darkpink = dim(pink, 0.75)
  
  yellow =  '#bcbd22'
  darkyellow = dim(yellow, 0.75)
  
  cyan = '#17becf'
  darkcyan = dim(cyan, 0.75)
  
  # Similar to matlab/matplotlib for the first few, but diverges to match category10,
  # and avoids using both red and green together too early
  matplotlib.rc('axes',
          color_cycle=[blue, green, orange, cyan, purple, red, yellow, pink])
  
new_contents: from beauty import *
  #### Parameters I chose arbitrarily
  USE_TEX = True      # whether or not to render *all* text w/latex
  USE_SERIFS = False   # serif vs san-serif font (computer modern)
  LEGEND_FONT_SIZE = TICK_FONT_SIZE = 9
  TITLE_FONT_SIZE = LABEL_FONT_SIZE = 10.5
  
  DPI = 150 # Font size adjustments should scale with this
  
  #### Automatic parameter setting
  # Figure size/scale
  matplotlib.rc('savefig', dpi=DPI)
  matplotlib.rc('figure', dpi=DPI, figsize=(2,2))
  # Font
  matplotlib.rc('xtick',labelsize=TICK_FONT_SIZE)
  matplotlib.rc('ytick',labelsize=TICK_FONT_SIZE)
  matplotlib.rc('axes', labelsize=LABEL_FONT_SIZE, titlesize=TITLE_FONT_SIZE)
  matplotlib.rc('legend', fontsize=LEGEND_FONT_SIZE)
  
  if USE_SERIFS:
      matplotlib.rc('font', **{'family':'serif', 'serif':['Computer Modern Roman']})
  else:
      matplotlib.rc('font', **{'family':'sans-serif', 'sans-serif':['Computer Modern Sans serif']})
      if USE_TEX:
          matplotlib.rcParams['text.latex.preamble'].append('\usepackage{sfmath}')
  matplotlib.rcParams.update({'text.usetex':USE_TEX})
  
  ### Colors modeled after d3.js's `category10` color scale
  ### (defined like this so it's easy to use 'beauty.blue' as a color)
  blue = '#1f77b4'
  darkblue = dim(blue, 0.75)
  
  orange = '#ff7f0e'
  darkorange = dim(orange, 0.75)
  
  green =  '#2ca02c'
  darkgreen = dim(green, 0.75)
  
  red =  '#d62728'
  darkred = dim(red, 0.75)
  
  purple = '#9467bd'
  darkpurple = dim(purple, 0.75)
  
  brown = '#8c564b'
  darkbrown = dim(brown, 0.75)
  
  pink = '#e377c2'
  darkpink = dim(pink, 0.75)
  
  yellow =  '#bcbd22'
  darkyellow = dim(yellow, 0.75)
  
  cyan = '#17becf'
  darkcyan = dim(cyan, 0.75)
  
  gray = '#c7c7c7'
  
  # Similar to matlab/matplotlib for the first few, but diverges to match category10,
  # and avoids using both red and green together too early
  matplotlib.rc('axes',
          color_cycle=[blue, green, orange, cyan, purple, red, yellow, pink])
  
subject: Add gray to list of colors