added global plotstyle.py providing common formatting and colors

chapter.mk

@@ -8,8 +8,8 @@ PYPDFFILES=$(PYFILES:.py=.pdf)
 
 pythonplots : $(PYPDFFILES)
 
-$(PYPDFFILES) : %.pdf: %.py
+$(PYPDFFILES) : %.pdf: %.py ../../plotstyle.py
-	python3 $<
+	PYTHONPATH="../../" python3 $<
 
 cleanpythonplots :
 	rm -f $(PYPDFFILES)

plotstyle.py

@@ -0,0 +1,86 @@
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+
+# colors:
+colors = {
+    'red': '#CC0000',
+    'orange': '#FF9900',
+    'lightorange': '#FFCC00',
+    'yellow': '#FFFF66',
+    'green': '#99FF00',
+    'blue': '#0000FF'
+}
+
+
+def show_spines(ax, spines):
+    """ Show and hide spines.
+
+    Parameters
+    ----------
+    ax: matplotlib figure, matplotlib axis, or list of matplotlib axes
+        Axis whose spines and ticks are manipulated.
+        If figure, then apply manipulations on all axes of the figure.
+        If list of axes, apply manipulations on each of the given axes.
+    spines: string
+        Specify which spines and ticks should be shown. All other ones or hidden.
+        'l' is the left spine, 'r' the right spine, 't' the top one and 'b' the bottom one.
+        E.g. 'lb' shows the left and bottom spine, and hides the top and and right spines,
+        as well as their tick marks and labels.
+        '' shows no spines at all.
+        'lrtb' shows all spines and tick marks.
+    """
+    # collect spine visibility:
+    xspines = []
+    if 't' in spines:
+        xspines.append('top')
+    if 'b' in spines:
+        xspines.append('bottom')
+    yspines = []
+    if 'l' in spines:
+        yspines.append('left')
+    if 'r' in spines:
+        yspines.append('right')
+    # collect axes:
+    if isinstance(ax, (list, tuple)):
+        axs = ax
+    else:
+        axs = ax.get_axes()
+        if not isinstance(axs, (list, tuple)):
+            axs = [axs]
+    for ax in axs:
+        # hide spines:
+        if not 'top' in xspines:
+            ax.spines['top'].set_visible(False)
+        if not 'bottom' in xspines:
+            ax.spines['bottom'].set_visible(False)
+        if not 'left' in yspines:
+            ax.spines['left'].set_visible(False)
+        if not 'right' in yspines:
+            ax.spines['right'].set_visible(False)
+        # ticks:
+        if len(xspines) == 0:
+            ax.xaxis.set_ticks_position('none')
+            ax.set_xticks([])
+        elif len(xspines) == 1:
+            ax.xaxis.set_ticks_position(xspines[0])
+        else:
+            ax.xaxis.set_ticks_position('both')
+        if len(yspines) == 0:
+            ax.yaxis.set_ticks_position('none')
+            ax.set_yticks([])
+        elif len(yspines) == 1:
+            ax.yaxis.set_ticks_position(yspines[0])
+        else:
+            ax.yaxis.set_ticks_position('both')
+
+            
+# initialization:
+plt.xkcd()
+mpl.rcParams['figure.facecolor'] = 'white'
+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
+

regression/lecture/cubicerrors.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
+from plotstyle import colors, show_spines
 
 def create_data():
     # wikipedia:
@@ -15,18 +16,13 @@ def create_data():
 
     
 def plot_data(ax, x, y, c):
-    ax.scatter(x, y, marker='o', color='b', s=40, zorder=10)
+    ax.scatter(x, y, marker='o', color=colors['blue'], s=40, zorder=10)
     xx = np.linspace(2.1, 3.9, 100)
-    ax.plot(xx, c*xx**3.0, color='#CC0000', lw=2, zorder=5)
+    ax.plot(xx, c*xx**3.0, color=colors['red'], lw=2, zorder=5)
     for cc in [0.25*c, 0.5*c, 2.0*c, 4.0*c]:
-        ax.plot(xx, cc*xx**3.0, color='#FF9900', lw=1.5, zorder=5)
+        ax.plot(xx, cc*xx**3.0, color=colors['orange'], lw=1.5, zorder=5)
 
-    ax.spines["right"].set_visible(False)
+    show_spines(ax, 'lb')
-    ax.spines["top"].set_visible(False)
-    ax.yaxis.set_ticks_position('left')
-    ax.xaxis.set_ticks_position('bottom')
-    ax.tick_params(direction="out", width=1.25)
-    ax.tick_params(direction="out", width=1.25)
     ax.set_xlabel('Size x / m')
     ax.set_ylabel('Weight y / kg')
     ax.set_xlim(2, 4)
@@ -36,12 +32,7 @@ def plot_data(ax, x, y, c):
     
     
 def plot_data_errors(ax, x, y, c):
-    ax.spines["right"].set_visible(False)
+    show_spines(ax, 'lb')
-    ax.spines["top"].set_visible(False)
-    ax.yaxis.set_ticks_position('left')
-    ax.xaxis.set_ticks_position('bottom')
-    ax.tick_params(direction="out", width=1.25)
-    ax.tick_params(direction="out", width=1.25)
     ax.set_xlabel('Size x / m')
     #ax.set_ylabel('Weight y / kg')
     ax.set_xlim(2, 4)
@@ -54,23 +45,18 @@ def plot_data_errors(ax, x, y, c):
                 xytext=(3.4, 70), textcoords='data', ha='left',
                 arrowprops=dict(arrowstyle="->", relpos=(0.9,1.0),
                 connectionstyle="angle3,angleA=50,angleB=-30") )
-    ax.scatter(x[:40], y[:40], color='b', s=10, zorder=0)
+    ax.scatter(x[:40], y[:40], color=colors['blue'], s=10, zorder=0)
     inxs = [3, 10, 11, 17, 18, 21, 28, 30, 33]
-    ax.scatter(x[inxs], y[inxs], color='b', s=40, zorder=10)
+    ax.scatter(x[inxs], y[inxs], color=colors['blue'], s=40, zorder=10)
     xx = np.linspace(2.1, 3.9, 100)
-    ax.plot(xx, c*xx**3.0, color='#CC0000', lw=2)
+    ax.plot(xx, c*xx**3.0, color=colors['red'], lw=2)
     for i in inxs :
         xx = [x[i], x[i]]
         yy = [c*x[i]**3.0, y[i]]
-        ax.plot(xx, yy, color='#FF9900', lw=2, zorder=5)
+        ax.plot(xx, yy, color=colors['orange'], lw=2, zorder=5)
 
 def plot_error_hist(ax, x, y, c):
-    ax.spines["right"].set_visible(False)
+    show_spines(ax, 'lb')
-    ax.spines["top"].set_visible(False)
-    ax.yaxis.set_ticks_position('left')
-    ax.xaxis.set_ticks_position('bottom')
-    ax.tick_params(direction="out", width=1.25)
-    ax.tick_params(direction="out", width=1.25)
     ax.set_xlabel('Squared error')
     ax.set_ylabel('Frequency')
     bins = np.arange(0.0, 1250.0, 100)
@@ -85,18 +71,16 @@ def plot_error_hist(ax, x, y, c):
                 xytext=(800, 3), textcoords='data', ha='left',
                 arrowprops=dict(arrowstyle="->", relpos=(0.0,0.2),
                 connectionstyle="angle3,angleA=10,angleB=90") )
-    ax.hist(errors, bins, color='#FF9900')
+    ax.hist(errors, bins, color=colors['orange'])
 
 
 
 if __name__ == "__main__":
     x, y, c = create_data()
-    plt.xkcd()
     fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(7., 2.6))
     plot_data(ax1, x, y, c)
     plot_data_errors(ax2, x, y, c)
     #plot_error_hist(ax2, x, y, c)
-    fig.set_facecolor("white")
     fig.tight_layout()
     fig.savefig("cubicerrors.pdf")
     plt.close()

regression/lecture/cubicfunc.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
+from plotstyle import colors, show_spines
 
 if __name__ == "__main__":
     # wikipedia:
@@ -12,21 +13,15 @@ if __name__ == "__main__":
     noise = rng.randn(len(x))*50
     y += noise
     
-    plt.xkcd()
     fig, ax = plt.subplots(figsize=(7., 3.6))
     
-    ax.scatter(x, y, marker='o', color='b', s=40, zorder=10)
+    ax.scatter(x, y, marker='o', color=colors['blue'], s=40, zorder=10)
     xx = np.linspace(2.1, 3.9, 100)
-    ax.plot(xx, c*xx**3.0, color='#CC0000', lw=3, zorder=5)
+    ax.plot(xx, c*xx**3.0, color=colors['red'], lw=3, zorder=5)
     for cc in [0.25*c, 0.5*c, 2.0*c, 4.0*c]:
-        ax.plot(xx, cc*xx**3.0, color='#FF9900', lw=2, zorder=5)
+        ax.plot(xx, cc*xx**3.0, color=colors['orange'], lw=2, zorder=5)
     
-    ax.spines["right"].set_visible(False)
+    show_spines(ax, 'lb')
-    ax.spines["top"].set_visible(False)
-    ax.yaxis.set_ticks_position('left')
-    ax.xaxis.set_ticks_position('bottom')
-    ax.tick_params(direction="out", width=1.25)
-    ax.tick_params(direction="out", width=1.25)
     ax.set_xlabel('Size x / m')
     ax.set_ylabel('Weight y / kg')
     ax.set_xlim(2, 4)
@@ -34,7 +29,6 @@ if __name__ == "__main__":
     ax.set_xticks(np.arange(2.0, 4.1, 0.5))
     ax.set_yticks(np.arange(0, 401, 100))
     
-    fig.set_facecolor("white")
     fig.subplots_adjust(0.11, 0.16, 0.98, 0.97)
     fig.savefig("cubicfunc.pdf")
     plt.close()

regression/lecture/cubicmse.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
+from plotstyle import colors, show_spines
 
 def create_data():
     # wikipedia:
@@ -38,9 +39,9 @@ def plot_mse(ax, x, y, c, cs):
     for i, cc in enumerate(ccs):
         mses[i] = np.mean((y-(cc*x**3.0))**2.0)
         
-    ax.plot(ccs, mses, 'b', lw=2, zorder=10)
+    ax.plot(ccs, mses, colors['blue'], lw=2, zorder=10)
-    ax.scatter(cs, ms, color='#cc0000', s=40, zorder=20)
+    ax.scatter(cs, ms, color=colors['red'], s=40, zorder=20)
-    ax.scatter(cs[-1], ms[-1], color='#FF9900', s=60, zorder=30)
+    ax.scatter(cs[-1], ms[-1], color=colors['orange'], s=60, zorder=30)
     for i in range(4):
         ax.annotate('',
                     xy=(cs[i+1]+0.2, ms[i+1]), xycoords='data',
@@ -49,12 +50,7 @@ def plot_mse(ax, x, y, c, cs):
                     connectionstyle="angle3,angleA=10,angleB=70") )
         
     
-    ax.spines["right"].set_visible(False)
+    show_spines(ax, 'lb')
-    ax.spines["top"].set_visible(False)
-    ax.yaxis.set_ticks_position('left')
-    ax.xaxis.set_ticks_position('bottom')
-    ax.tick_params(direction="out", width=1.25)
-    ax.tick_params(direction="out", width=1.25)
     ax.set_xlabel('c')
     ax.set_ylabel('mean squared error')
     ax.set_xlim(0, 10)
@@ -63,14 +59,9 @@ def plot_mse(ax, x, y, c, cs):
     ax.set_yticks(np.arange(0, 30001, 10000))
     
 def plot_descent(ax, cs, mses):
-    ax.plot(np.arange(len(mses))+1, mses, '-o', c='#cc0000', mew=0, ms=8)
+    ax.plot(np.arange(len(mses))+1, mses, '-o', c=colors['red'], mew=0, ms=8)
     
-    ax.spines["right"].set_visible(False)
+    show_spines(ax, 'lb')
-    ax.spines["top"].set_visible(False)
-    ax.yaxis.set_ticks_position('left')
-    ax.xaxis.set_ticks_position('bottom')
-    ax.tick_params(direction="out", width=1.25)
-    ax.tick_params(direction="out", width=1.25)
     ax.set_xlabel('iteration')
     #ax.set_ylabel('mean squared error')
     ax.set_xlim(0, 10.5)
@@ -83,11 +74,9 @@ def plot_descent(ax, cs, mses):
 if __name__ == "__main__":
     x, y, c = create_data()
     cs, mses = gradient_descent(x, y)
-    plt.xkcd()
     fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(7., 2.6))
     plot_mse(ax1, x, y, c, cs)
     plot_descent(ax2, cs, mses)
-    fig.set_facecolor("white")
     fig.tight_layout()
     fig.savefig("cubicmse.pdf")
     plt.close()