########## ## Code for the mpl logo figure ########## import matplotlib.pyplot as plt import numpy as np  from matplotlib.cm import jet as colormap from matplotlib.ticker import NullFormatter, MultipleLocator  t, w, r = zip((0.1, 0.4, 1), (0.9, 0.3, 5), (1.7, 0.5, 7), (2.7, 0.6, 6),               (3.5, 0.3, 3), (4.5, 0.4, 4), (5.3, 0.3, 7))  fig, ax = plt.subplots(subplot_kw={'polar': True}) bars = ax.bar(t, r, width=w, bottom=0.0, lw=2, edgecolor='Black', zorder=2)  for r, bar in zip(r, bars):     bar.set_facecolor(colormap(r / 9.0))     bar.set_alpha(0.7)  ax.yaxis.set_major_locator(MultipleLocator(2))  for axis in (ax.xaxis, ax.yaxis):     axis.set_major_formatter(NullFormatter())  # no tick labels  ax.set_ylim([0, 8]) ax.grid(True)  plt.show() #################### 

########## ## Code for the 3D surface plot and the 2D random walk tajectories ########## import matplotlib.pyplot as plt import numpy as np  from mpl_toolkits.mplot3d import Axes3D from matplotlib.cm import viridis as colormap  """ Figure 1: a 3D surface plot (from matplotlib gallery) """ step = 0.04 maxval = 1.0 fig1 = plt.figure("Figure_1") ax1 = fig1.add_subplot(111, projection='3d')  # Create supporting points in polar coordinates r = np.linspace(0, 1.2, 50) p = np.linspace(0, 2*np.pi, 50) R, P = np.meshgrid(r, p) # Transform them to cartesian system X, Y = R*np.cos(P), R*np.sin(P)  Z = ((R**2 - 1)**2) ax1.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=colormap) ax1.set_zlim3d(0, 1) ax1.set_xlabel(r'$\phi_\mathrm{real}$') ax1.set_ylabel(r'$\phi_\mathrm{im}$') ax1.set_zlabel(r'$V(\phi)$')  """ Figure 2: a few examples of 2D random walk """ fig2, ax2 = plt.subplots(num="Figure_2")  prng = np.random.RandomState(123)  x = np.linspace(0, 10, 101)  def random_walk(xy0=(0.0, 0.0), nsteps=100, std=1.0):     xy = np.zeros((nsteps + 1, 2))     xy[0,:] = xy0     deltas = prng.normal(loc=0.0, scale=std, size=(nsteps, 2))     xy[1:, :] = xy[0, :] + np.cumsum(deltas, axis=0)     return xy  for cnt in range(3):     traj = random_walk()     ax2.plot(traj[:, 0], traj[:, 1], label="Traj. {c}".format(c=cnt))  ax2.legend(loc='best')  plt.show() ####################