Tweak aesthetics of plots in screenshots page.

These changes also cleanup the code a bit, as described by MEP 12.

Author: tonysyu

doc/pyplots/tex_demo.py

@@ -1,5 +1,6 @@
-#!/usr/bin/env python
 """
+Demo of TeX rendering.
+
 You can use TeX to render all of your matplotlib text if the rc
 parameter text.usetex is set.  This works currently on the agg and ps
 backends, and requires that you have tex and the other dependencies
@@ -10,26 +11,25 @@
 ~/.tex.cache
 
 """
-from matplotlib import rc
-from numpy import arange, cos, pi
-from matplotlib.pyplot import figure, axes, plot, xlabel, ylabel, title, \
-     grid, savefig, show
+import numpy as np
+import matplotlib.pyplot as plt
 
 
-rc('text', usetex=True)
-rc('font', family='serif')
-figure(1, figsize=(6,4))
-ax = axes([0.1, 0.1, 0.8, 0.7])
-t = arange(0.0, 1.0+0.01, 0.01)
-s = cos(2*2*pi*t)+2
-plot(t, s)
+# Example data
+t = np.arange(0.0, 1.0 + 0.01, 0.01)
+s = np.cos(4 * np.pi * t) + 2
 
-xlabel(r'\textbf{time (s)}')
-ylabel(r'\textit{voltage (mV)}',fontsize=16)
-title(r"\TeX\ is Number $\displaystyle\sum_{n=1}^\infty\frac{-e^{i\pi}}{2^n}$!",
-      fontsize=16, color='r')
-grid(True)
-savefig('tex_demo')
+plt.rc('text', usetex=True)
+plt.rc('font', family='serif')
+plt.plot(t, s)
 
+plt.xlabel(r'\textbf{time} (s)')
+plt.ylabel(r'\textit{voltage} (mV)',fontsize=16)
+plt.title(r"\TeX\ is Number "
+          r"$\displaystyle\sum_{n=1}^\infty\frac{-e^{i\pi}}{2^n}$!",
+          fontsize=16, color='gray')
+# Make room for the ridiculously large title.
+plt.subplots_adjust(top=0.8)
 
-show()
+plt.savefig('tex_demo')
+plt.show()

examples/api/legend_demo.py

@@ -1,41 +1,42 @@
+"""
+Demo of the legend function with a few features.
+
+In addition to the basic legend, this demo shows a few optional features:
+
+    * Custom legend placement.
+    * A keyword argument to a drop-shadow.
+    * Setting the background color.
+    * Setting the font size.
+    * Setting the line width.
+"""
 import numpy as np
 import matplotlib.pyplot as plt
 
-a = np.arange(0,3,.02)
-b = np.arange(0,3,.02)
+
+# Example data
+a = np.arange(0,3, .02)
+b = np.arange(0,3, .02)
 c = np.exp(a)
 d = c[::-1]
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
-ax.plot(a,c,'k--',a,d,'k:',a,c+d,'k')
-leg = ax.legend(('Model length', 'Data length', 'Total message length'),
-           'upper center', shadow=True)
-ax.set_ylim([-1,20])
-ax.grid(False)
-ax.set_xlabel('Model complexity --->')
-ax.set_ylabel('Message length --->')
-ax.set_title('Minimum Message Length')
-
-ax.set_yticklabels([])
-ax.set_xticklabels([])
-
-# set some legend properties.  All the code below is optional.  The
-# defaults are usually sensible but if you need more control, this
-# shows you how
-
-# the matplotlib.patches.Rectangle instance surrounding the legend
-frame  = leg.get_frame()  
-frame.set_facecolor('0.80')    # set the frame face color to light gray
-
-# matplotlib.text.Text instances
-for t in leg.get_texts():
-    t.set_fontsize('small')    # the legend text fontsize
-
-# matplotlib.lines.Line2D instances
-for l in leg.get_lines():
-    l.set_linewidth(1.5)  # the legend line width
-plt.show()
+# Create plots with pre-defined labels.
+# Alternatively, you can pass labels explicitly when calling `legend`.
+fig, ax = plt.subplots()
+ax.plot(a, c, 'k--', label='Model length')
+ax.plot(a, d, 'k:', label='Data length')
+ax.plot(a, c+d, 'k', label='Total message length')
+
+# Now add the legend with some customizations.
+legend = ax.legend(loc='upper center', shadow=True)
 
+# The frame is matplotlib.patches.Rectangle instance surrounding the legend.
+frame  = legend.get_frame()
+frame.set_facecolor('0.90')
 
+# Set the fontsize
+for label in legend.get_texts():
+    label.set_fontsize('large')
 
+for label in legend.get_lines():
+    label.set_linewidth(1.5)  # the legend line width
+plt.show()

examples/pylab_examples/barchart_demo.py

@@ -1,44 +1,43 @@
-
-#!/usr/bin/env python
+"""
+Bar chart demo with pairs of bars grouped for easy comparison.
+"""
 import numpy as np
 import matplotlib.pyplot as plt
 
-N = 5
-menMeans = (20, 35, 30, 35, 27)
-menStd =   (2, 3, 4, 1, 2)
 
-ind = np.arange(N)  # the x locations for the groups
-width = 0.35       # the width of the bars
+n_groups = 5
 
+means_men = (20, 35, 30, 35, 27)
+std_men = (2, 3, 4, 1, 2)
 
-plt.subplot(111)
-rects1 = plt.bar(ind, menMeans, width,
-                    color='r',
-                    yerr=menStd,
-                    error_kw=dict(elinewidth=6, ecolor='pink'))
+means_women = (25, 32, 34, 20, 25)
+std_women = (3, 5, 2, 3, 3)
 
-womenMeans = (25, 32, 34, 20, 25)
-womenStd =   (3, 5, 2, 3, 3)
-rects2 = plt.bar(ind+width, womenMeans, width,
-                    color='y',
-                    yerr=womenStd,
-                    error_kw=dict(elinewidth=6, ecolor='yellow'))
+index = np.arange(n_groups)
+bar_width = 0.35
 
-# add some
-plt.ylabel('Scores')
-plt.title('Scores by group and gender')
-plt.xticks(ind+width, ('G1', 'G2', 'G3', 'G4', 'G5') )
+opacity = 0.4
+error_config = {'ecolor': '0.3'}
 
-plt.legend( (rects1[0], rects2[0]), ('Men', 'Women') )
+rects1 = plt.bar(index, means_men, bar_width,
+                 alpha=opacity,
+                 color='b',
+                 yerr=std_men,
+                 error_kw=error_config,
+                 label='Men')
 
-def autolabel(rects):
-    # attach some text labels
-    for rect in rects:
-        height = rect.get_height()
-        plt.text(rect.get_x()+rect.get_width()/2., 1.05*height, '%d'%int(height),
-                ha='center', va='bottom')
+rects2 = plt.bar(index + bar_width, means_women, bar_width,
+                 alpha=opacity,
+                 color='r',
+                 yerr=std_women,
+                 error_kw=error_config,
+                 label='Women')
 
-autolabel(rects1)
-autolabel(rects2)
+plt.xlabel('Group')
+plt.ylabel('Scores')
+plt.title('Scores by group and gender')
+plt.xticks(index + bar_width, ('A', 'B', 'C', 'D', 'E'))
+plt.legend()
 
+plt.tight_layout()
 plt.show()

examples/pylab_examples/legend_demo.py

@@ -1,46 +1,42 @@
-#!/usr/bin/env python
-# Thanks to Charles Twardy for this example
-#
-#See http://matplotlib.org/examples/pylab_examples/legend_demo2.html
-# for an example controlling which lines the legend uses and the order
-# they are drawn in.
+"""
+Demo of the legend function with a few features.
 
+In addition to the basic legend, this demo shows a few optional features:
+
+    * Custom legend placement.
+    * A keyword argument to a drop-shadow.
+    * Setting the background color.
+    * Setting the font size.
+    * Setting the line width.
+"""
 import numpy as np
 import matplotlib.pyplot as plt
 
-a = np.arange(0,3,.02)
-b = np.arange(0,3,.02)
+
+# Example data
+a = np.arange(0,3, .02)
+b = np.arange(0,3, .02)
 c = np.exp(a)
 d = c[::-1]
 
-ax = plt.subplot(111)
-plt.plot(a,c,'k--',a,d,'k:',a,c+d,'k')
-plt.legend(('Model length', 'Data length', 'Total message length'),
-           'upper center', shadow=True, fancybox=True)
-plt.ylim([-1,20])
-plt.grid(False)
-plt.xlabel('Model complexity --->')
-plt.ylabel('Message length --->')
-plt.title('Minimum Message Length')
-
-plt.setp(plt.gca(), 'yticklabels', [])
-plt.setp(plt.gca(), 'xticklabels', [])
-
-# set some legend properties.  All the code below is optional.  The
-# defaults are usually sensible but if you need more control, this
-# shows you how
-leg = plt.gca().get_legend()
-ltext  = leg.get_texts()  # all the text.Text instance in the legend
-llines = leg.get_lines()  # all the lines.Line2D instance in the legend
-frame  = leg.get_frame()  # the patch.Rectangle instance surrounding the legend
-
-# see text.Text, lines.Line2D, and patches.Rectangle for more info on
-# the settable properties of lines, text, and rectangles
-frame.set_facecolor('0.80')      # set the frame face color to light gray
-plt.setp(ltext, fontsize='small')    # the legend text fontsize
-plt.setp(llines, linewidth=1.5)      # the legend linewidth
-#leg.draw_frame(False)           # don't draw the legend frame
-plt.show()
+# Create plots with pre-defined labels.
+# Alternatively, you can pass labels explicitly when calling `legend`.
+fig, ax = plt.subplots()
+ax.plot(a, c, 'k--', label='Model length')
+ax.plot(a, d, 'k:', label='Data length')
+ax.plot(a, c+d, 'k', label='Total message length')
 
+# Now add the legend with some customizations.
+legend = ax.legend(loc='upper center', shadow=True)
 
+# The frame is matplotlib.patches.Rectangle instance surrounding the legend.
+frame  = legend.get_frame()
+frame.set_facecolor('0.90')
 
+# Set the fontsize
+for label in legend.get_texts():
+    label.set_fontsize('large')
+
+for label in legend.get_lines():
+    label.set_linewidth(1.5)  # the legend line width
+plt.show()

examples/pylab_examples/polar_demo.py

@@ -1,64 +1,17 @@
-#!/usr/bin/env python
-#
-# matplotlib now has a PolarAxes class and a polar function in the
-# matplotlib interface.  This is considered alpha and the interface
-# may change as we work out how polar axes should best be integrated
-#
-# The only function that has been tested on polar axes is "plot" (the
-# pylab interface function "polar" calls ax.plot where ax is a
-# PolarAxes) -- other axes plotting functions may work on PolarAxes
-# but haven't been tested and may need tweaking.
-#
-# you can get a PolarSubplot instance by doing, for example
-#
-#   subplot(211, polar=True)
-#
-# or a PolarAxes instance by doing
-#   axes([left, bottom, width, height], polar=True)
-#
-# The view limits (eg xlim and ylim) apply to the lower left and upper
-# right of the rectangular box that surrounds to polar axes.  e.g., if
-# you have
-#
-#  r = arange(0,1,0.01)
-#  theta = 2*pi*r
-#
-# the lower left corner is 5/4pi, sqrt(2) and the
-# upper right corner is 1/4pi, sqrt(2)
-#
-# you could change the radial bounding box (zoom out) by setting the
-# ylim (radial coordinate is the second argument to the plot command,
-# as in MATLAB, though this is not advised currently because it is not
-# clear to me how the axes should behave in the change of view limits.
-# Please advise me if you have opinions.  Likewise, the pan/zoom
-# controls probably do not do what you think they do and are better
-# left alone on polar axes.  Perhaps I will disable them for polar
-# axes unless we come up with a meaningful, useful and functional
-# implementation for them.
-#
-# See the pylab rgrids and thetagrids functions for
-# information on how to customize the grid locations and labels
-import matplotlib
+"""
+Demo of a line plot on a polar axis.
+"""
 import numpy as np
-from matplotlib.pyplot import figure, show, rc, grid
+import matplotlib.pyplot as plt
 
-# radar green, solid grid lines
-rc('grid', color='#316931', linewidth=1, linestyle='-')
-rc('xtick', labelsize=15)
-rc('ytick', labelsize=15)
-
-# force square figure and square axes looks better for polar, IMO
-width, height = matplotlib.rcParams['figure.figsize']
-size = min(width, height)
-# make a square figure
-fig = figure(figsize=(size, size))
-ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True, axisbg='#d5de9c')
 
 r = np.arange(0, 3.0, 0.01)
-theta = 2*np.pi*r
-ax.plot(theta, r, color='#ee8d18', lw=3)
+theta = 2 * np.pi * r
+
+ax = plt.subplot(111, polar=True)
+ax.plot(theta, r, color='r', linewidth=3)
 ax.set_rmax(2.0)
-grid(True)
+ax.grid(True)
 
-ax.set_title("And there was much rejoicing!", fontsize=20)
-show()
+ax.set_title("A line plot on a polar axis", va='bottom')
+plt.show()