optional xkcd plot style

plotstyle.py

@@ -1,6 +1,8 @@
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 
+xkcd_style = False
+
 # colors:
 colors = {
     'red': '#CC0000',
@@ -99,8 +101,38 @@ def show_spines(ax, spines):
             ax.yaxis.set_ticks_position('both')
 
 
+def set_xlabel(ax, label, unit=None):
+    if not unit:
+        ax.set_xlabel(label)
+    elif xkcd_style:
+        ax.set_xlabel('%s / %s' % (label, unit))
+    else:
+        ax.set_xlabel('%s [%s]' % (label, unit))
+
+        
+def set_ylabel(ax, label, unit=None):
+    if not unit:
+        ax.set_ylabel(label)
+    elif xkcd_style:
+        ax.set_ylabel('%s / %s' % (label, unit))
+    else:
+        ax.set_ylabel('%s [%s]' % (label, unit))
+
+            
 # initialization:
-plt.xkcd()
+if xkcd_style:
+    plt.xkcd()
+    bar_fac = 0.9
+    mpl.rcParams['xtick.major.size'] = 6
+    mpl.rcParams['ytick.major.size'] = 6
+else:
+    bar_fac = 1.0
+    mpl.rcParams['font.family'] = 'sans-serif'
+    mpl.rcParams['xtick.labelsize'] = 'small'
+    mpl.rcParams['ytick.labelsize'] = 'small'
+    mpl.rcParams['xtick.major.size'] = 2.5
+    mpl.rcParams['ytick.major.size'] = 2.5
+    mpl.rcParams['legend.fontsize'] = 'x-small'
 mpl.rcParams['figure.facecolor'] = 'white'
 #mpl.rcParams['axes.spines.left'] = True    # newer matplotlib only
 #mpl.rcParams['axes.spines.bottom'] = True
@@ -108,8 +140,6 @@ mpl.rcParams['figure.facecolor'] = 'white'
 #mpl.rcParams['axes.spines.right'] = False
 mpl.rcParams['xtick.direction'] = 'out'
 mpl.rcParams['ytick.direction'] = 'out'
-mpl.rcParams['xtick.major.size'] = 6
-mpl.rcParams['ytick.major.size'] = 6
 mpl.rcParams['xtick.major.width'] = 1.25
 mpl.rcParams['ytick.major.width'] = 1.25
 

simulations/lecture/normaldata.py

@@ -2,7 +2,7 @@ import numpy as np
 import scipy.stats as st
 import matplotlib.pyplot as plt
 import matplotlib.gridspec as gridspec
-from plotstyle import colors, cm_size, show_spines
+from plotstyle import colors, cm_size, show_spines, set_xlabel, set_ylabel, bar_fac
 
 if __name__ == "__main__":
     # wikipedia:
@@ -21,8 +21,8 @@ if __name__ == "__main__":
     ax1 = fig.add_subplot(spec[0, 0])
     show_spines(ax1, 'lb')
     ax1.scatter(indices, data, c=colors['blue'], edgecolor='white', s=50)
-    ax1.set_xlabel('index')
+    set_xlabel(ax1, 'index')
-    ax1.set_ylabel('Weight / kg')
+    set_ylabel(ax1, 'Weight', 'kg')
     ax1.set_xlim(-10, 310)
     ax1.set_ylim(0, 370)
     ax1.set_yticks(np.arange(0, 351, 100))
@@ -31,11 +31,11 @@ if __name__ == "__main__":
     show_spines(ax2, 'lb')
     xx = np.arange(0.0, 350.0, 0.5)
     yy = st.norm.pdf(xx, mu, sigma)
-    ax2.plot(yy, xx, color=colors['red'])
+    ax2.plot(yy, xx, color=colors['red'], lw=2)
     bw = 20.0
     h, b = np.histogram(data, np.arange(0, 401, bw))
-    ax2.barh(b[:-1], h/np.sum(h)/(b[1]-b[0]), fc=colors['yellow'], height=0.9*bw, align='edge')
+    ax2.barh(b[:-1], h/np.sum(h)/(b[1]-b[0]), fc=colors['yellow'], height=bar_fac*bw, align='edge')
-    ax2.set_xlabel('pdf / 1/kg')
+    set_xlabel(ax2, 'pdf', '1/kg')
     ax2.set_xlim(0, 0.012)
     ax2.set_xticks([0, 0.005, 0.01])
     ax2.set_xticklabels(['0', '0.005', '0.01'])

simulations/lecture/staticnonlinearity.py

@@ -2,7 +2,7 @@ import numpy as np
 import scipy.stats as st
 import matplotlib.pyplot as plt
 import matplotlib.gridspec as gridspec
-from plotstyle import colors, cm_size, show_spines
+from plotstyle import colors, cm_size, show_spines, set_xlabel, set_ylabel, bar_fac
 
 def boltzmann(x, x0, k):
     return 1.0/(1.0+np.exp(-k*(x-x0)))
@@ -27,8 +27,8 @@ if __name__ == "__main__":
     show_spines(ax1, 'lb')
     ax1.plot(xx, yy, colors['red'], lw=2)
     ax1.scatter(x, y, c=colors['blue'], edgecolor='white', s=50)
-    ax1.set_xlabel('Hair deflection / nm')
+    set_xlabel(ax1, 'Hair deflection', 'nm')
-    ax1.set_ylabel('Open probability')
+    set_ylabel(ax1, 'Open probability')
     ax1.set_xlim(-20, 20)
     ax1.set_ylim(-0.2, 1.17)
     ax1.set_xticks(np.arange(-20.0, 21.0, 10.0))
@@ -41,11 +41,11 @@ if __name__ == "__main__":
     ax2.plot(xg, yg, colors['red'], lw=2)
     bw = 0.05
     h, b = np.histogram(y-boltzmann(x, x0, k), np.arange(-1.0, 1.01, bw))
-    ax2.bar(b[:-1], h/np.sum(h)/(b[1]-b[0]), fc=colors['yellow'], width=0.9*bw, align='edge')
+    ax2.bar(b[:-1], h/np.sum(h)/(b[1]-b[0]), fc=colors['yellow'], width=bar_fac*bw, align='edge')
-    ax2.set_xlabel('residuals')
+    set_xlabel(ax2, 'residuals', 'nm')
-    ax2.set_ylabel('pdf')
+    set_ylabel(ax2, 'pdf')
     ax2.set_xlim(-0.3, 0.3)
-    #ax2.set_ylim(0, 370)
+    ax2.set_ylim(0, 5.05)
     #ax2.set_xticks([0, 0.005, 0.01])
     #ax2.set_xticklabels(['0', '0.005', '0.01'])
     #ax2.set_yticks(np.arange(0, 351, 100))