diff --git a/bootstrap/lecture/bootstrapsem.py b/bootstrap/lecture/bootstrapsem.py
index d8b0346..3a276bd 100644
--- a/bootstrap/lecture/bootstrapsem.py
+++ b/bootstrap/lecture/bootstrapsem.py
@@ -38,7 +38,7 @@ ax.annotate('sampling\ndistribution',
                 connectionstyle="angle3,angleA=20,angleB=120") )
 ax.annotate('bootstrap\ndistribution',
             xy=(0.13, 3.3), xycoords='data',
-            xytext=(0.25, 4), textcoords='data',
+            xytext=(0.22, 4), textcoords='data',
             arrowprops=dict(arrowstyle="->", relpos=(0.0,0.5),
                 connectionstyle="angle3,angleA=20,angleB=60") )
 ax.bar(bins[:-1]-0.25*db, hmusrs, 0.5*db, **fsB)
diff --git a/bootstrap/lecture/permutecorrelation.py b/bootstrap/lecture/permutecorrelation.py
index 2f10af8..c5f0db7 100644
--- a/bootstrap/lecture/permutecorrelation.py
+++ b/bootstrap/lecture/permutecorrelation.py
@@ -44,19 +44,19 @@ ax.annotate('Measured\ncorrelation\nis significant!',
                 connectionstyle="angle3,angleA=10,angleB=80") )
 ax.annotate('95% percentile',
             xy=(0.14, 0.9), xycoords='data',
-            xytext=(0.2, 4.0), textcoords='data', ha='left',
+            xytext=(0.18, 4.0), textcoords='data', ha='left',
             arrowprops=dict(arrowstyle="->", relpos=(0.1,0.0),
-                connectionstyle="angle3,angleA=30,angleB=70") )
+                connectionstyle="angle3,angleA=30,angleB=80") )
 ax.annotate('Distribution of\nuncorrelated\nsamples',
             xy=(-0.08, 3.6), xycoords='data',
             xytext=(-0.22, 5.0), textcoords='data', ha='left',
             arrowprops=dict(arrowstyle="->", relpos=(0.5,0.0),
-                connectionstyle="angle3,angleA=150,angleB=100") )
+                connectionstyle="angle3,angleA=150,angleB=110") )
 ax.bar(b[:-1], h, width=b[1]-b[0], **fsC)
 ax.bar(b[:-1][b[:-1]>=rq], h[b[:-1]>=rq], width=b[1]-b[0], **fsB)
 ax.plot( [rd, rd], [0, 1], **lsA)
 ax.set_xlim(-0.25, 0.35)
 ax.set_xlabel('Correlation coefficient')
-ax.set_ylabel('Probability density of H0')
+ax.set_ylabel('Prob. density of H0')
 
 plt.savefig('permutecorrelation.pdf')
diff --git a/likelihood/lecture/mlemean.py b/likelihood/lecture/mlemean.py
index 83b1bab..a1fb974 100644
--- a/likelihood/lecture/mlemean.py
+++ b/likelihood/lecture/mlemean.py
@@ -26,7 +26,7 @@ ax.set_ylim(-0.02, 0.85)
 ax.set_xticks(np.arange(0, 5))
 ax.set_yticks(np.arange(0, 0.9, 0.2))
 ax.set_xlabel('x')
-ax.set_ylabel('Probability density')
+ax.set_ylabel('Prob. density')
 s = 1
 for mu in mus :
     r = 5.0*rng.rand()+2.0
@@ -35,11 +35,11 @@ for mu in mus :
     ax.annotate('', xy=(mu, 0.02), xycoords='data',
                 xytext=(mu, 0.75), textcoords='data',
                 arrowprops=dict(arrowstyle="->", relpos=(0.5,0.5),
-                connectionstyle=cs), zorder=1)
+                connectionstyle=cs), zorder=10)
     if mu > rmu :
-        ax.text(mu-0.1, 0.04, '?', zorder=1, ha='right')
+        ax.text(mu-0.1, 0.04, '?', zorder=10, ha='right')
     else :
-        ax.text(mu+0.1, 0.04, '?', zorder=1)
+        ax.text(mu+0.1, 0.04, '?', zorder=10)
 for k, ls in enumerate([lsCm, lsBm, lsDm]) :
     ax.plot(x, g[:,k], zorder=5, **ls)
 ax.plot(xd, 0.05*rng.rand(len(xd))+0.2, zorder=10, **psAm)
diff --git a/likelihood/lecture/mlepdf.py b/likelihood/lecture/mlepdf.py
index ddbcb57..3b1a851 100644
--- a/likelihood/lecture/mlepdf.py
+++ b/likelihood/lecture/mlepdf.py
@@ -29,7 +29,7 @@ ax1.set_ylim(0.0, 0.42)
 ax1.set_xticks(np.arange(0, 11, 2))
 ax1.set_yticks(np.arange(0, 0.42, 0.1))
 ax1.set_xlabel('x')
-ax1.set_ylabel('Probability density')
+ax1.set_ylabel('Prob. density')
 ax1.plot(xx, yy, label='pdf', **lsB)
 ax1.plot(xx, yf, label='mle', **lsCm)
 kernel = st.gaussian_kde(xd)
@@ -54,7 +54,7 @@ ax2.set_xticks(np.arange(0, 11, 2))
 ax2.set_xlabel('x')
 ax2.set_ylim(0.0, 0.42)
 ax2.set_yticks(np.arange(0, 0.42, 0.1))
-ax2.set_ylabel('Probability density')
+ax2.set_ylabel('Prob. density')
 ax2.plot(xx, yy, label='pdf', **lsB)
 ax2.plot(xx, yc, label='fit', **lsCm)
 ax2.bar(b[:-1], h, np.diff(b), **fsA)
diff --git a/likelihood/lecture/mlepropline.py b/likelihood/lecture/mlepropline.py
index 906a3f2..cecd350 100644
--- a/likelihood/lecture/mlepropline.py
+++ b/likelihood/lecture/mlepropline.py
@@ -6,7 +6,7 @@ from plotstyle import *
 
 fig = plt.figure()
 spec = gridspec.GridSpec(nrows=1, ncols=2, wspace=0.3,
-                         **adjust_fs(fig, left=5.5))
+                         **adjust_fs(fig, left=5.5, top=1))
 spec1 = gridspec.GridSpecFromSubplotSpec(1, 2, spec[0, 0], width_ratios=[3, 1], wspace=0.0)
 spec2 = gridspec.GridSpecFromSubplotSpec(1, 2, spec[0, 1], width_ratios=[3, 1], wspace=0.0)
 
@@ -34,7 +34,7 @@ ax.set_ylabel('y')
 ax.plot(x, y, label='data', zorder=10, **psAm)
 ax.plot(xx, yy, label='original', zorder=5, **lsB)
 ax.plot(xx, yf, label='fit', zorder=7, **lsCm)
-ax.legend(loc='upper left', bbox_to_anchor=(0.0, 1.15))
+ax.legend(loc='upper left', bbox_to_anchor=(-0.05, 1.2))
 
 ax = fig.add_subplot(spec1[0, 1])
 ax.show_spines('l')
diff --git a/plotstyle.py b/plotstyle.py
index 06aa015..7e3ba8c 100644
--- a/plotstyle.py
+++ b/plotstyle.py
@@ -2,7 +2,11 @@ import matplotlib as mpl
 import matplotlib.pyplot as plt
 from mpl_toolkits.mplot3d import Axes3D
 
-xkcd_style = False
+# Set to true if you want xkcd-type sketchy plots:
+xkcd_style = True
+
+# matplotlib major version:
+mpl_major = int(mpl.__version__.split('.')[0])
 
 # default size of figure:
 figure_width = 15.0  # cm, should be set according to \textwidth in the latex document
@@ -26,7 +30,7 @@ colors['white'] = '#FFFFFF'
 #colors_bendalab_vivid['green'] = '#30D700'
 #colors_bendalab_vivid['blue'] = '#0020C0'
 
-# line styles for plot():
+# general settings for plot styles:
 lwthick = 3.0
 lwthin = 1.8
 mainline = {'linestyle': '-', 'linewidth': lwthick}
@@ -35,9 +39,12 @@ largemarker = {'marker': 'o', 'markersize': 9, 'markeredgecolor': colors['white'
 smallmarker = {'marker': 'o', 'markersize': 6, 'markeredgecolor': colors['white'], 'markeredgewidth': 1}
 largelinepoints = {'linestyle': '-', 'linewidth': lwthick, 'marker': 'o', 'markersize': 10, 'markeredgecolor': colors['white'], 'markeredgewidth': 1}
 smalllinepoints = {'linestyle': '-', 'linewidth': 1.4, 'marker': 'o', 'markersize': 7, 'markeredgecolor': colors['white'], 'markeredgewidth': 1}
-filllw = 1
+filllw = 1.0
 fillec = colors['white']
 fillalpha = 0.4
+filledge = {'linewidth': filllw, 'joinstyle': 'round'}
+if int(mpl.__version__.split('.')[0]) < 2:
+    del filledge['joinstyle']
 
 # helper lines:
 lsSpine = {'c': colors['black'], 'linestyle': '-', 'linewidth': 1, 'clip_on': False}
@@ -71,7 +78,7 @@ psA = dict({'color': colors['blue'], 'linestyle': 'none'}, **largemarker)
 psAm = dict({'color': colors['blue'], 'linestyle': 'none'}, **smallmarker)
 lpsA = dict({'color': colors['blue']}, **largelinepoints)
 lpsAm = dict({'color': colors['blue']}, **smalllinepoints)
-fsA = {'facecolor': colors['blue'], 'edgecolor': fillec, 'linewidth': filllw}
+fsA = dict({'facecolor': colors['blue'], 'edgecolor': fillec}, **filledge)
 fsAs = {'facecolor': colors['blue'], 'edgecolor': 'none'}
 fsAa = {'facecolor': colors['blue'], 'edgecolor': 'none', 'alpha': fillalpha}
 
@@ -81,7 +88,7 @@ psB = dict({'color': colors['red'], 'linestyle': 'none'}, **largemarker)
 psBm = dict({'color': colors['red'], 'linestyle': 'none'}, **smallmarker)
 lpsB = dict({'color': colors['red']}, **largelinepoints)
 lpsBm = dict({'color': colors['red']}, **smalllinepoints)
-fsB = {'facecolor': colors['red'], 'edgecolor': fillec, 'linewidth': filllw}
+fsB = dict({'facecolor': colors['red'], 'edgecolor': fillec}, **filledge)
 fsBs = {'facecolor': colors['red'], 'edgecolor': 'none'}
 fsBa = {'facecolor': colors['red'], 'edgecolor': 'none', 'alpha': fillalpha}
 
@@ -89,7 +96,7 @@ lsC = dict({'color': colors['lightorange']}, **mainline)
 lsCm = dict({'color': colors['lightorange']}, **minorline)
 psC = dict({'color': colors['lightorange'], 'linestyle': 'none'}, **largemarker)
 psCm = dict({'color': colors['lightorange'], 'linestyle': 'none'}, **smallmarker)
-fsC = {'facecolor': colors['lightorange'], 'edgecolor': fillec, 'linewidth': filllw}
+fsC = dict({'facecolor': colors['lightorange'], 'edgecolor': fillec}, **filledge)
 fsCs = {'facecolor': colors['lightorange'], 'edgecolor': 'none'}
 fsCa = {'facecolor': colors['lightorange'], 'edgecolor': 'none', 'alpha': fillalpha}
 
@@ -97,17 +104,17 @@ lsD = dict({'color': colors['orange']}, **mainline)
 lsDm = dict({'color': colors['orange']}, **minorline)
 psD = dict({'color': colors['orange'], 'linestyle': 'none'}, **largemarker)
 psDm = dict({'color': colors['orange'], 'linestyle': 'none'}, **smallmarker)
-fsD = {'facecolor': colors['orange'], 'edgecolor': fillec, 'linewidth': filllw}
+fsD = dict({'facecolor': colors['orange'], 'edgecolor': fillec}, **filledge)
 fsDs = {'facecolor': colors['orange'], 'edgecolor': 'none'}
 
 lsE = dict({'color': colors['yellow']}, **mainline)
 lsEm = dict({'color': colors['yellow']}, **minorline)
 psE = dict({'color': colors['yellow'], 'linestyle': 'none'}, **largemarker)
 psEm = dict({'color': colors['yellow'], 'linestyle': 'none'}, **smallmarker)
-fsE = {'facecolor': colors['yellow'], 'edgecolor': fillec, 'linewidth': filllw}
+fsE = dict({'facecolor': colors['yellow'], 'edgecolor': fillec}, **filledge)
 fsEs = {'facecolor': colors['yellow'], 'edgecolor': 'none'}
 
-fsF = {'facecolor': colors['green'], 'edgecolor': fillec, 'linewidth': filllw}
+fsF = dict({'facecolor': colors['green'], 'edgecolor': fillec}, **filledge)
 fsFs = {'facecolor': colors['green'], 'edgecolor': 'none'}
 
 # factor for scaling widths of bars in a bar plot:
@@ -270,7 +277,7 @@ def axis_label(label, unit=None):
     if not unit:
         return label
     elif xkcd_style:
-        return '%s / %s' % (label, unit)
+        return '%s/%s' % (label, unit)
     else:
         return '%s [%s]' % (label, unit)
 
@@ -326,7 +333,7 @@ def set_zlabel(ax, label, unit=None, **kwargs):
     ax.set_zlabel_orig(axis_label(label, unit), **kwargs)
 
 
-def common_format():
+def common_style():
     """ Set some rc parameter.
     """
     mpl.rcParams['figure.figsize'] = cm_size(figure_width, figure_height)
@@ -337,6 +344,8 @@ def common_format():
     mpl.rcParams['figure.subplot.wspace'] = 0.4
     mpl.rcParams['figure.subplot.hspace'] = 0.6
     mpl.rcParams['figure.facecolor'] = 'white'
+    mpl.rcParams['figure.edgecolor'] = 'none'
+    mpl.rcParams['figure.frameon'] = False   
     mpl.rcParams['xtick.direction'] = 'out'
     mpl.rcParams['ytick.direction'] = 'out'
     mpl.rcParams['xtick.major.width'] = 1.25
@@ -380,7 +389,7 @@ def sketch_style():
     global bar_fac
     bar_fac = 0.9
     plt.xkcd()
-    common_format()
+    common_style()
     mpl.rcParams['legend.fontsize'] = 'medium'
     mpl.rcParams['xtick.labelsize'] = 'medium'
     mpl.rcParams['ytick.labelsize'] = 'medium'
@@ -394,7 +403,7 @@ def plain_style():
     global bar_fac
     bar_fac = 1.0
     plt.rcdefaults()
-    common_format()
+    common_style()
     mpl.rcParams['font.family'] = 'sans-serif'
     mpl.rcParams['legend.fontsize'] = 'x-small'
     mpl.rcParams['xtick.labelsize'] = 'small'
diff --git a/pointprocesses/lecture/firingrates.py b/pointprocesses/lecture/firingrates.py
index b7029fa..087e7ee 100644
--- a/pointprocesses/lecture/firingrates.py
+++ b/pointprocesses/lecture/firingrates.py
@@ -149,7 +149,7 @@ def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
     ax1.show_spines('b')
     ax1.vlines(times[times < (100000*dt)], ymin=0, ymax=1, color=colors['blue'], lw=1.5)
     #ax1.set_ylabel('Spikes')
-    ax1.text(-0.105, 0.5, 'Spikes', transform=ax1.transAxes,
+    ax1.text(-0.13, 0.5, 'Spikes', transform=ax1.transAxes,
              rotation='vertical', va='center')
     ax1.set_xlim(2.5, 3.5)
     ax1.set_ylim(-0.2, 1)
@@ -159,7 +159,7 @@ def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
     ax2.plot(time, inst_rate, color=colors['orange'], lw=2)
     ax2.text(1.0, 1.0, 'instantaneous rate', transform=ax2.transAxes, ha='right')
     #ax2.set_ylabel('Rate', 'Hz')
-    ax2.text(-0.105, 0.5, axis_label('Rate', 'Hz'), transform=ax2.transAxes,
+    ax2.text(-0.13, 0.5, axis_label('Rate', 'Hz'), transform=ax2.transAxes,
              rotation='vertical', va='center')
     ax2.set_xlim(2.5, 3.5)
     ax2.set_ylim(0, 300)
@@ -170,7 +170,7 @@ def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
     ax3.plot(time, binn_rate, color=colors['orange'], lw=2)
     ax3.text(1.0, 1.0, 'binned rate', transform=ax3.transAxes, ha='right')
     #ax3.set_ylabel('Rate', 'Hz')
-    ax3.text(-0.105, 0.5, axis_label('Rate', 'Hz'), transform=ax3.transAxes,
+    ax3.text(-0.13, 0.5, axis_label('Rate', 'Hz'), transform=ax3.transAxes,
              rotation='vertical', va='center')
     ax3.set_xlim(2.5, 3.5)
     ax3.set_ylim(0, 300)
@@ -182,7 +182,7 @@ def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
     ax4.text(1.0, 1.0, 'convolved rate', transform=ax4.transAxes, ha='right')
     ax4.set_xlabel('Time', 's')
     #ax4.set_ylabel('Rate', 'Hz')
-    ax4.text(-0.105, 0.5, axis_label('Rate', 'Hz'), transform=ax4.transAxes,
+    ax4.text(-0.13, 0.5, axis_label('Rate', 'Hz'), transform=ax4.transAxes,
              rotation='vertical', va='center')
     ax4.set_xlim(2.5, 3.5)
     ax4.set_xticks([2.5, 2.75, 3.0, 3.25, 3.5])
diff --git a/pointprocesses/lecture/isimethod.py b/pointprocesses/lecture/isimethod.py
index 750b840..ef28b8f 100644
--- a/pointprocesses/lecture/isimethod.py
+++ b/pointprocesses/lecture/isimethod.py
@@ -31,7 +31,7 @@ def setup_axis(spikes_ax, rate_ax):
     spikes_ax.show_spines('')
     spikes_ax.set_yticks([])
     spikes_ax.set_ylim(-0.2, 1.0)
-    spikes_ax.text(-0.1, 0.5, 'Spikes', transform=spikes_ax.transAxes, rotation='vertical', va='center')
+    spikes_ax.text(-0.11, 0.5, 'Spikes', transform=spikes_ax.transAxes, rotation='vertical', va='center')
     spikes_ax.set_xlim(-1, 500)
     spikes_ax.set_xticklabels([])
     #spikes_ax.set_xticklabels(np.arange(0., 600, 100))
@@ -39,7 +39,7 @@ def setup_axis(spikes_ax, rate_ax):
     spikes_ax.show_spines('lb')
     rate_ax.set_xlabel('Time', 'ms')
     #rate_ax.set_ylabel('Firing rate', 'Hz')
-    rate_ax.text(-0.1, 0.5, axis_label('Rate', 'Hz'), transform=rate_ax.transAxes,
+    rate_ax.text(-0.11, 0.5, axis_label('Rate', 'Hz'), transform=rate_ax.transAxes,
                  rotation='vertical', va='center')
     rate_ax.set_xlim(0, 500)
     #rate_ax.set_xticklabels(np.arange(0., 600, 100))
@@ -126,7 +126,7 @@ def plot_isi_method():
         t_start = 1000*spike_times[i-1]
         t = 1000*spike_times[i]
         spikes_ax.plot([t_start, t_start], [0., 1.], color=colors['blue'], lw=2)
-        spikes_ax.annotate(s='', xy=(t_start, 0.5), xytext=(t,0.5), arrowprops=dict(arrowstyle='<->'), color=colors['red'])
+        spikes_ax.annotate('', xy=(t_start, 0.5), xytext=(t,0.5), arrowprops=dict(arrowstyle='<->'), color=colors['red'])
         spikes_ax.text(0.5*(t_start+t), 1.05, 
                     "{0:.0f}".format((t - t_start)),
                     color=colors['red'], ha='center')
diff --git a/pointprocesses/lecture/pointprocessscetchA.eps b/pointprocesses/lecture/pointprocessscetchA.eps
index 2c18dd1..2383569 100644
--- a/pointprocesses/lecture/pointprocessscetchA.eps
+++ b/pointprocesses/lecture/pointprocessscetchA.eps
@@ -1,7 +1,7 @@
 %!PS-Adobe-2.0 EPSF-2.0
 %%Title: pointprocessscetchA.tex
-%%Creator: gnuplot 5.0 patchlevel 5
-%%CreationDate: Tue Jan  7 10:05:37 2020
+%%Creator: gnuplot 4.6 patchlevel 4
+%%CreationDate: Tue Oct 27 23:58:04 2020
 %%DocumentFonts: 
 %%BoundingBox: 50 50 373 135
 %%EndComments
@@ -18,7 +18,6 @@ gnudict begin
 /Dashlength 1 def
 /Landscape false def
 /Level1 false def
-/Level3 false def
 /Rounded true def
 /ClipToBoundingBox false def
 /SuppressPDFMark false def
@@ -30,11 +29,11 @@ gnudict begin
 %
 /vshift -73 def
 /dl1 {
-  10.0 Dashlength userlinewidth gnulinewidth div mul mul mul
+  10.0 Dashlength mul mul
   Rounded { currentlinewidth 0.75 mul sub dup 0 le { pop 0.01 } if } if
 } def
 /dl2 {
-  10.0 Dashlength userlinewidth gnulinewidth div mul mul mul
+  10.0 Dashlength mul mul
   Rounded { currentlinewidth 0.75 mul add } if
 } def
 /hpt_ 31.5 def
@@ -48,7 +47,7 @@ gnudict begin
   } if
 } def
 %
-% Gnuplot Prolog Version 5.1 (Oct 2015)
+% Gnuplot Prolog Version 4.6 (September 2012)
 %
 %/SuppressPDFMark true def
 %
@@ -65,11 +64,11 @@ gnudict begin
 /vpt2 vpt 2 mul def
 /hpt2 hpt 2 mul def
 /Lshow {currentpoint stroke M 0 vshift R 
-	Blacktext {gsave 0 setgray textshow grestore} {textshow} ifelse} def
+	Blacktext {gsave 0 setgray show grestore} {show} ifelse} def
 /Rshow {currentpoint stroke M dup stringwidth pop neg vshift R
-	Blacktext {gsave 0 setgray textshow grestore} {textshow} ifelse} def
+	Blacktext {gsave 0 setgray show grestore} {show} ifelse} def
 /Cshow {currentpoint stroke M dup stringwidth pop -2 div vshift R 
-	Blacktext {gsave 0 setgray textshow grestore} {textshow} ifelse} def
+	Blacktext {gsave 0 setgray show grestore} {show} ifelse} def
 /UP {dup vpt_ mul /vpt exch def hpt_ mul /hpt exch def
   /hpt2 hpt 2 mul def /vpt2 vpt 2 mul def} def
 /DL {Color {setrgbcolor Solid {pop []} if 0 setdash}
@@ -83,7 +82,7 @@ gnudict begin
 /PL {stroke userlinewidth setlinewidth
 	Rounded {1 setlinejoin 1 setlinecap} if} def
 3.8 setmiterlimit
-% Classic Line colors (version 5.0)
+% Default Line colors
 /LCw {1 1 1} def
 /LCb {0 0 0} def
 /LCa {0 0 0} def
@@ -96,21 +95,19 @@ gnudict begin
 /LC6 {0 0 0} def
 /LC7 {1 0.3 0} def
 /LC8 {0.5 0.5 0.5} def
-% Default dash patterns (version 5.0)
-/LTB {BL [] LCb DL} def
+% Default Line Types
 /LTw {PL [] 1 setgray} def
-/LTb {PL [] LCb DL} def
+/LTb {BL [] LCb DL} def
 /LTa {AL [1 udl mul 2 udl mul] 0 setdash LCa setrgbcolor} def
 /LT0 {PL [] LC0 DL} def
-/LT1 {PL [2 dl1 3 dl2] LC1 DL} def
-/LT2 {PL [1 dl1 1.5 dl2] LC2 DL} def
-/LT3 {PL [6 dl1 2 dl2 1 dl1 2 dl2] LC3 DL} def
-/LT4 {PL [1 dl1 2 dl2 6 dl1 2 dl2 1 dl1 2 dl2] LC4 DL} def
-/LT5 {PL [4 dl1 2 dl2] LC5 DL} def
-/LT6 {PL [1.5 dl1 1.5 dl2 1.5 dl1 1.5 dl2 1.5 dl1 6 dl2] LC6 DL} def
-/LT7 {PL [3 dl1 3 dl2 1 dl1 3 dl2] LC7 DL} def
-/LT8 {PL [2 dl1 2 dl2 2 dl1 6 dl2] LC8 DL} def
-/SL {[] 0 setdash} def
+/LT1 {PL [4 dl1 2 dl2] LC1 DL} def
+/LT2 {PL [2 dl1 3 dl2] LC2 DL} def
+/LT3 {PL [1 dl1 1.5 dl2] LC3 DL} def
+/LT4 {PL [6 dl1 2 dl2 1 dl1 2 dl2] LC4 DL} def
+/LT5 {PL [3 dl1 3 dl2 1 dl1 3 dl2] LC5 DL} def
+/LT6 {PL [2 dl1 2 dl2 2 dl1 6 dl2] LC6 DL} def
+/LT7 {PL [1 dl1 2 dl2 6 dl1 2 dl2 1 dl1 2 dl2] LC7 DL} def
+/LT8 {PL [2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 2 dl2 2 dl1 4 dl2] LC8 DL} def
 /Pnt {stroke [] 0 setdash gsave 1 setlinecap M 0 0 V stroke grestore} def
 /Dia {stroke [] 0 setdash 2 copy vpt add M
   hpt neg vpt neg V hpt vpt neg V
@@ -332,14 +329,9 @@ gnudict begin
 %
 /languagelevel where
  {pop languagelevel} {1} ifelse
-dup 2 lt
-	{/InterpretLevel1 true def
-	 /InterpretLevel3 false def}
-	{/InterpretLevel1 Level1 def
-	 2 gt
-	    {/InterpretLevel3 Level3 def}
-	    {/InterpretLevel3 false def}
-	 ifelse }
+ 2 lt
+	{/InterpretLevel1 true def}
+	{/InterpretLevel1 Level1 def}
  ifelse
 %
 % PostScript level 2 pattern fill definitions
@@ -428,7 +420,6 @@ Level1 {Level1PatternFill} {Level2PatternFill} ifelse
 /Symbol-Oblique /Symbol findfont [1 0 .167 1 0 0] makefont
 dup length dict begin {1 index /FID eq {pop pop} {def} ifelse} forall
 currentdict end definefont pop
-%
 Level1 SuppressPDFMark or 
 {} {
 /SDict 10 dict def
@@ -438,42 +429,14 @@ systemdict /pdfmark known not {
 SDict begin [
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diff --git a/pointprocesses/lecture/pointprocessscetchB.pdf b/pointprocesses/lecture/pointprocessscetchB.pdf
index c9d4fdc..2055658 100644
Binary files a/pointprocesses/lecture/pointprocessscetchB.pdf and b/pointprocesses/lecture/pointprocessscetchB.pdf differ
diff --git a/regression/lecture/gradient.py b/regression/lecture/gradient.py
index a191eeb..ec4b53f 100644
--- a/regression/lecture/gradient.py
+++ b/regression/lecture/gradient.py
@@ -24,7 +24,7 @@ ax.set_xlabel('x')
 ax.set_ylabel('y', rotation='horizontal')
 ax.set_xticks(np.arange(x1, x2+0.1, 1.0))
 ax.set_yticks(np.arange(x1, x2+0.1, 1.0))
-ax.contour(X, Y, Z, linewidths=2, zorder=0)
+ax.contour(X, Y, Z, linewidths=2, cmap='jet', zorder=0)
 
 # gradients:
 xxg = [-1.1, 1.4, -1.0]
@@ -35,8 +35,8 @@ for xg, yg in zip(xxg, yyg) :
     ax.scatter(xg, yg, c='k', s=100, zorder=10)
     ax.quiver([xg, xg], [yg, yg], [g[0], 0.0], [0.0, g[1]], units='xy', angles='uv', scale_units='x', scale=0.5, zorder=10)
     ax.quiver([xg], [yg], [g[0]], [g[1]], units='xy', angles='uv', scale_units='x', scale=0.5, zorder=10, lw=2)
-ax.text(-0.8, -1.5, '$\partial f/\partial x$', ha='center', zorder=20)
-ax.text(-1.55, -0.8, '$\partial f/\partial y$', va='center', rotation='vertical', zorder=20)
-ax.text(-0.4, -0.8, r'$\nabla f$', ha='left', zorder=20)
+ax.text(-0.8, -1.4, '$\partial f/\partial x$', ha='center', zorder=20)
+ax.text(-1.45, -0.8, '$\partial f/\partial y$', va='center', rotation='vertical', zorder=20)
+ax.text(-0.5, -0.8, r'$\nabla f$', ha='left', zorder=20)
 
 plt.savefig('gradient.pdf')
diff --git a/statistics/lecture/diehistograms.py b/statistics/lecture/diehistograms.py
index 91200f7..2458412 100644
--- a/statistics/lecture/diehistograms.py
+++ b/statistics/lecture/diehistograms.py
@@ -2,7 +2,6 @@ import numpy as np
 import matplotlib.pyplot as plt
 from plotstyle import *
 
-sketch_style()
 # roll the die:
 rng = np.random.RandomState(57281)
 x1 = rng.randint(1, 7, 100)
@@ -27,6 +26,9 @@ ax2.set_xlabel('x')
 ax2.set_ylim(0, 0.23)
 ax2.set_ylabel('Probability')
 ax2.plot([0.2, 6.8], [1.0/6.0, 1.0/6.0], zorder=-10, **lsAm)
-ax2.hist([x2, x1], bins, density=True, zorder=-5, **fs)
+if mpl_major > 1:
+    ax2.hist([x2, x1], bins, density=True, zorder=-5, **fs)
+else:
+    ax2.hist([x2, x1], bins, normed=True, zorder=-5, **fs)
 fig.subplots_adjust(left=0.125)
 fig.savefig('diehistograms.pdf')
diff --git a/statistics/lecture/displayunivariatedata.py b/statistics/lecture/displayunivariatedata.py
index 31977fe..64604c0 100644
--- a/statistics/lecture/displayunivariatedata.py
+++ b/statistics/lecture/displayunivariatedata.py
@@ -4,7 +4,6 @@ import matplotlib.gridspec as gridspec
 from scipy.stats import gaussian_kde
 from plotstyle import *
 
-sketch_style()
 #rng = np.random.RandomState(981)
 #data = rng.randn(40, 1) + 4.0
 rng = np.random.RandomState(1981)
@@ -19,9 +18,11 @@ fig = plt.figure(figsize=cm_size(figure_width, 1.1*figure_height))
 spec = gridspec.GridSpec(nrows=1, ncols=2, width_ratios=[3, 1], wspace=0.1,
                          **adjust_fs(fig, left=4.0))
 
-ax = fig.add_subplot(spec[0, 0])
+ax = fig.add_subplot(spec[0, 0], label='1')
 wh = ax.boxplot( data, positions=[boxpos], widths=[barwidth], whis=100.0, patch_artist=True)
+mediancolor = 'k'
 wh['medians'][0].set_linewidth(4)
+wh['medians'][0].set_color(mediancolor)
 wh['whiskers'][0].set_linewidth(2)
 wh['whiskers'][1].set_linewidth(2)
 wh['whiskers'][0].set_linestyle('-')
@@ -34,6 +35,16 @@ wh['caps'][1].set_color(whiskercolor)
 wh['boxes'][0].set_facecolor('#99ff00')
 ax.set_xlim(0.0, 4.8)
 ax.set_ylim( 0.0, 8.0)
+ax.set_xticklabels([])
+
+ax = fig.add_subplot(spec[0, 0], label='2')
+ax.set_xlim(0.0, 4.8)
+ax.set_xticks([scatterpos, barpos, boxpos])
+ax.set_xticklabels(['(1) data', '(2) bar\n plot', '(3) box-\nwhisker'], fontsize='medium')
+ax.set_ylabel('x')
+ax.set_ylim( 0.0, 8.0)
+
+# annotate box whisker:
 ax.annotate('maximum',
             xy=(boxpos, 6.5), xycoords='data',
             xytext=(boxpos-1*barwidth, 7.6), textcoords='data', ha='left',
@@ -49,14 +60,6 @@ ax.annotate('median',
             xytext=(boxpos+0.1*barwidth, 4.2), textcoords='data', ha='left',
             arrowprops=dict(arrowstyle="->", relpos=(0.8,0.0),
             connectionstyle="angle3,angleA=-60,angleB=20") )
-ax.set_xticklabels([])
-
-ax = fig.add_subplot(spec[0, 0])
-ax.set_xlim(0.0, 4.8)
-ax.set_xticks([scatterpos, barpos, boxpos])
-ax.set_xticklabels(['(1) data', '(2) bar\n plot', '(3) box-\nwhisker'], fontsize='medium')
-ax.set_ylabel('x')
-ax.set_ylim( 0.0, 8.0)
 
 # scatter data points according to their density:
 kernel = gaussian_kde(data)
@@ -67,7 +70,10 @@ ax.plot(scatterpos+barwidth*x*(rng.rand(len(data))-0.5), data, **psA)
 barmean = np.mean(data)
 barstd = np.std(data)
 ew = 0.2
-ax.bar([barpos-0.5*barwidth], [barmean], barwidth, **fsC)
+if mpl_major > 1:
+    ax.bar([barpos], [barmean], barwidth, **fsC)
+else:
+    ax.bar([barpos-0.5*barwidth], [barmean], barwidth, **fsC)
 ax.plot([barpos, barpos], [barmean-barstd, barmean+barstd], **lsMarker)
 ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean-barstd, barmean-barstd], **lsMarker)
 ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean+barstd, barmean+barstd], **lsMarker)
diff --git a/statistics/lecture/kerneldensity.py b/statistics/lecture/kerneldensity.py
index 2b608a0..503ac46 100644
--- a/statistics/lecture/kerneldensity.py
+++ b/statistics/lecture/kerneldensity.py
@@ -1,6 +1,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.gridspec as gridspec
+import matplotlib.ticker as ticker
 from plotstyle import *
 
 # normal distribution:
@@ -37,35 +38,39 @@ spec = gridspec.GridSpec(nrows=2, ncols=2, wspace=0.35, hspace=0.3,
                          **adjust_fs(fig, left=5.5, top=0.2, bottom=2.7))
 
 ax = fig.add_subplot(spec[0, 0])
-ax.set_xlabel('x')
 ax.set_xlim(-3.2, 3.2)
-ax.set_xticks(np.arange(-3.0, 3.1, 1.0))
+ax.xaxis.set_major_locator(ticker.MultipleLocator(1.0))
+ax.xaxis.set_major_formatter(ticker.NullFormatter())
 ax.set_ylabel('p(x)')
 ax.set_ylim(0.0, 0.49)
-ax.set_yticks(np.arange(0.0, 0.41, 0.1))
-#ax.plot(x, g, '-b', lw=2, zorder=-1)
-ax.hist(r, np.arange(-4.1, 4, 0.4), density=True, zorder=-5, **fsC)
+ax.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
+if mpl_major > 1:
+    ax.hist(r, np.arange(-4.1, 4, 0.4), density=True, zorder=-5, **fsC)
+else:
+    ax.hist(r, np.arange(-4.1, 4, 0.4), normed=True, zorder=-5, **fsC)
 
 ax = fig.add_subplot(spec[1, 0])
 ax.set_xlabel('x')
 ax.set_xlim(-3.2, 3.2)
-ax.set_xticks(np.arange(-3.0, 3.1, 1.0))
+ax.xaxis.set_major_locator(ticker.MultipleLocator(1.0))
 ax.set_ylabel('p(x)')
 ax.set_ylim(0.0, 0.49)
-ax.set_yticks(np.arange(0.0, 0.41, 0.1))
-#ax.plot(x, g, '-b', lw=2, zorder=-1)
-ax.hist(r, np.arange(-4.3, 4, 0.4), density=True, zorder=-5, **fsC)
+ax.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
+if mpl_major > 1:
+    ax.hist(r, np.arange(-4.3, 4, 0.4), density=True, zorder=-5, **fsC)
+else:
+    ax.hist(r, np.arange(-4.3, 4, 0.4), normed=True, zorder=-5, **fsC)
 
 ax = fig.add_subplot(spec[:, 1])
 ax.set_xlabel('x')
 ax.set_xlim(-3.2, 3.2)
-ax.set_xticks(np.arange(-3.0, 3.1, 1.0))
+ax.xaxis.set_major_locator(ticker.MultipleLocator(1.0))
 ax.set_ylabel('Prob. density p(x)')
 ax.set_ylim(0.0, 0.49)
 ax.set_yticks(np.arange(0.0, 0.41, 0.1))
 kd, xx = kerneldensity(r, -3.2, 3.2, 0.2)
 ax.fill_between(xx, 0.0, kd, zorder=-5, **fsDs)
 ax.plot(xx, kd, '-', zorder=-1, **lsB)
-fig.subplots_adjust(left=0.15)
+
 fig.savefig('kerneldensity.pdf')
 
diff --git a/statistics/lecture/pdfhistogram.py b/statistics/lecture/pdfhistogram.py
index cccd146..33e6cf4 100644
--- a/statistics/lecture/pdfhistogram.py
+++ b/statistics/lecture/pdfhistogram.py
@@ -8,7 +8,7 @@ x = np.arange(-4.0, 4.0, 0.01)
 g = np.exp(-0.5*x*x)/np.sqrt(2.0*np.pi)
 r = rng.randn(100)
 
-fig, (ax1, ax2) = plt.subplots(1, 2)
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=cm_size(figure_width, 1.1*figure_height))
 ax1.set_xlabel('x')
 ax1.set_xlim(-3.2, 3.2)
 ax1.set_xticks(np.arange(-3.0, 3.1, 1.0))
@@ -24,8 +24,12 @@ ax2.set_ylabel('Probab. density p(x)')
 ax2.set_ylim(0.0, 0.44)
 ax2.set_yticks(np.arange(0.0, 0.41, 0.1))
 ax2.plot(x, g, zorder=-1, **lsA)
-ax2.hist(r, 5, density=True, zorder=-10, **fsB)
-ax2.hist(r, 20, density=True, zorder=-5, **fsC)
+if mpl_major > 1:
+    ax2.hist(r, 5, density=True, zorder=-10, **fsB)
+    ax2.hist(r, 20, density=True, zorder=-5, **fsC)
+else:
+    ax2.hist(r, 5, normed=True, zorder=-10, **fsB)
+    ax2.hist(r, 20, normed=True, zorder=-5, **fsC)
 
 fig.savefig('pdfhistogram.pdf')
 
diff --git a/statistics/lecture/pdfprobabilities.py b/statistics/lecture/pdfprobabilities.py
index 3e9e3c6..87928e3 100644
--- a/statistics/lecture/pdfprobabilities.py
+++ b/statistics/lecture/pdfprobabilities.py
@@ -10,7 +10,7 @@ x2=1.0
 
 fig, ax = plt.subplots(figsize=cm_size(figure_width, 1.2*figure_height))
 ax.set_xlabel('x')
-ax.set_ylabel('Probability density p(x)')
+ax.set_ylabel('Prob. density p(x)')
 ax.set_ylim(0.0, 0.46)
 ax.set_yticks(np.arange(0.0, 0.45, 0.1))
 ax.annotate('Gaussian',