use plt.subplots() in examples as much as possible

At the recent LBL Software Carpentry Workshop, it was pointed out that there's
an inconsistency within our documentation for how to create new figures with
subplots.

Indeed, most examples were using the old way, something like:

    fig = plt.figure()
    ax = plt.subplot(111) # or plt.add_subplot(111)

This patch changes a whole bunch of instances like the above to:

    fig, ax = plt.subplots()

We should strive to have a minimal amount of constants in our code,
especially unusual ones like `111`, which only make sense to Matlab
refugees.

I have left unchanged examples which were using axes keywords passed to
subplot() and add_subplot(), since those end up transforming things like:

    figure()
    subplot(111, axisbg='w')

to

    plt.subplots(subplot_kw=dict(axisbg='w'))

which isn't necessarily better.

I also did not touch most of the user_interfaces examples, since those did not
involve using plt, but instead explicitly imported Figure, and used the OO
approach on Figure instances.

Also updated instaces where the old "import pylab as p" convention was used to
use our standard "import matplotlib.pyplot as plt"

I have also updated some, but not all uses of subplot(121) etc, but I'm a bit
exhausted after doing all of these.

Author: ivanov

CHANGELOG

@@ -90,6 +90,10 @@
 
 2012-11-09 Make plt.subplot() without arguments act as subplot(111) - PI
 
+2012-11-08 Replaced plt.figure and plt.subplot calls by the newer, more
+           convenient single call to plt.subplots() in the documentation
+           examples - PI
+
 2012-10-05 Add support for saving animations as animated GIFs. - JVDP
 
 2012-08-11 Fix path-closing bug in patches.Polygon, so that regardless

examples/animation/animate_decay.py

@@ -11,8 +11,7 @@ def data_gen():
         yield t, np.sin(2*np.pi*t) * np.exp(-t/10.)
 data_gen.t = 0
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 line, = ax.plot([], [], lw=2)
 ax.set_ylim(-1.1, 1.1)
 ax.set_xlim(0, 5)

examples/animation/histogram.py

@@ -9,8 +9,7 @@
 import matplotlib.path as path
 import matplotlib.animation as animation
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 
 # histogram our data with numpy
 data = np.random.randn(1000)

examples/animation/old_animation/animate_decay_tk_blit.py

@@ -10,8 +10,7 @@ def data_gen():
     return np.sin(2*np.pi*t) * np.exp(-t/10.)
 data_gen.t = 0
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 line, = ax.plot([], [], animated=True, lw=2)
 ax.set_ylim(-1.1, 1.1)
 ax.set_xlim(0, 5)

examples/animation/old_animation/animation_blit_gtk.py

@@ -16,8 +16,7 @@
 import matplotlib.pyplot as plt
 
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 canvas = fig.canvas
 
 fig.subplots_adjust(left=0.3, bottom=0.3) # check for flipy bugs

examples/animation/old_animation/animation_blit_gtk2.py

@@ -148,9 +148,8 @@ def update_line(self, *args):
 
 
 plt.rcParams["text.usetex"] = False
-fig = plt.figure()
 
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 ax.xaxis.set_animated(True)
 ax.yaxis.set_animated(True)
 canvas = fig.canvas

examples/animation/old_animation/animation_blit_tk.py

@@ -7,17 +7,17 @@
 matplotlib.use('TkAgg')
 
 import sys
-import pylab as p
+import matplotlib.pyplot as plt
 import numpy as npy
 import time
 
-ax = p.subplot(111)
+fig, ax = plt.subplots()
 canvas = ax.figure.canvas
 
 
 # create the initial line
 x = npy.arange(0,2*npy.pi,0.01)
-line, = p.plot(x, npy.sin(x), animated=True, lw=2)
+line, = plt.plot(x, npy.sin(x), animated=True, lw=2)
 
 def run(*args):
     background = canvas.copy_from_bbox(ax.bbox)
@@ -43,12 +43,12 @@ def run(*args):
 run.cnt = 0
 
 
-p.subplots_adjust(left=0.3, bottom=0.3) # check for flipy bugs
-p.grid() # to ensure proper background restore
-manager = p.get_current_fig_manager()
+plt.subplots_adjust(left=0.3, bottom=0.3) # check for flipy bugs
+plt.grid() # to ensure proper background restore
+manager = plt.get_current_fig_manager()
 manager.window.after(100, run)
 
-p.show()
+plt.show()
 
 
 

examples/animation/old_animation/animation_blit_wx.py

@@ -24,7 +24,7 @@
     matplotlib.backends.backend_wxagg._use_accelerator(False)
 
 
-ax = p.subplot(111)
+fig, ax = plt.subplots()
 canvas = ax.figure.canvas
 
 

examples/animation/old_animation/draggable_legend.py

@@ -1,13 +1,12 @@
 import matplotlib.pyplot as plt
 
-
-ax = plt.subplot(111)
+fig, ax = plt.subplots()
 ax.plot([1,2,3], label="test")
 
 l = ax.legend()
 d1 = l.draggable()
 
-xy = 1, 2        
+xy = 1, 2
 txt = ax.annotate("Test", xy, xytext=(-30, 30),
                   textcoords="offset points",
                   bbox=dict(boxstyle="round",fc=(0.2, 1, 1)),

examples/animation/old_animation/gtk_timeout.py

@@ -5,8 +5,7 @@
 
 import matplotlib.pyplot as plt
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 line, = ax.plot(np.random.rand(10))
 ax.set_ylim(0, 1)
 

examples/animation/old_animation/histogram_tkagg.py

@@ -11,8 +11,7 @@
 import matplotlib.patches as patches
 import matplotlib.path as path
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 
 # histogram our data with numpy
 data = np.random.randn(1000)

examples/animation/old_animation/simple_anim_gtk.py

@@ -9,9 +9,7 @@
 
 import matplotlib.pyplot as plt
 
-fig = plt.figure()
-
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 
 def animate():
     tstart = time.time()                 # for profiling

examples/animation/old_animation/simple_anim_tkagg.py

@@ -10,8 +10,7 @@
 matplotlib.use('TkAgg') # do this before importing pylab
 
 import matplotlib.pyplot as plt
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 
 def animate():
     tstart = time.time()                   # for profiling

examples/animation/old_animation/simple_idle_wx.py

@@ -9,9 +9,7 @@
 
 import matplotlib.pyplot as plt
 
-fig = plt.figure()
-
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 t = np.arange(0, 2*np.pi, 0.1)
 line, = ax.plot(t, np.sin(t))
 dt = 0.05

examples/animation/old_animation/simple_timer_wx.py

@@ -9,9 +9,7 @@
 
 import matplotlib.pyplot as plt
 
-fig = plt.figure()
-
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 t = np.arange(0, 2*np.pi, 0.1)
 line, = ax.plot(t, np.sin(t))
 dt = 0.05

examples/animation/old_animation/strip_chart_demo.py

@@ -64,8 +64,7 @@ def update(self, *args):
 
 from pylab import figure, show
 
-fig = figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 scope = Scope(ax)
 gobject.idle_add(scope.update)
 

examples/animation/random_data.py

@@ -2,8 +2,7 @@
 import matplotlib.pyplot as plt
 import matplotlib.animation as animation
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 line, = ax.plot(np.random.rand(10))
 ax.set_ylim(0, 1)
 

examples/animation/simple_anim.py

@@ -5,8 +5,7 @@
 import matplotlib.pyplot as plt
 import matplotlib.animation as animation
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 
 x = np.arange(0, 2*np.pi, 0.01)        # x-array
 line, = ax.plot(x, np.sin(x))

examples/animation/strip_chart_demo.py

@@ -44,8 +44,7 @@ def emitter(p=0.03):
         else:
             yield np.random.rand(1)
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 scope = Scope(ax)
 
 # pass a generator in "emitter" to produce data for the update func

examples/api/README.txt

@@ -29,8 +29,7 @@ A simple example of the recommended style is::
     import numpy as np
     import matplotlib.pyplot as plt
 
-    fig = plt.figure()
-    ax = fig.add_subplot(111) # or add_axes
+    fig, ax = plt.subplots()
     ax.plot(np.random.rand(10))
     ax.set_xlabel('some x data')
     ax.set_ylabel('some y data')

examples/api/agg_oo.py

@@ -6,12 +6,10 @@
 from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
 from matplotlib.figure import Figure
 
-fig = Figure()
-canvas = FigureCanvas(fig)
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 ax.plot([1,2,3])
 ax.set_title('hi mom')
 ax.grid(True)
 ax.set_xlabel('time')
 ax.set_ylabel('volts')
-canvas.print_figure('test')
+fig.canvas.print_figure('test')

examples/api/barchart_demo.py

@@ -11,8 +11,7 @@
 ind = np.arange(N)  # the x locations for the groups
 width = 0.35       # the width of the bars
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 rects1 = ax.bar(ind, menMeans, width, color='r', yerr=menStd)
 
 womenMeans = (25, 32, 34, 20, 25)

examples/api/collections_demo.py

@@ -41,69 +41,63 @@
 # Make a list of colors cycling through the rgbcmyk series.
 colors = [colorConverter.to_rgba(c) for c in ('r','g','b','c','y','m','k')]
 
-fig = plt.figure()
+fig, axes = plt.subplots(2,2)
+((ax1, ax2), (ax3, ax4)) = axes # unpack the axes
+
 
-a = fig.add_subplot(2,2,1)
 col = collections.LineCollection([spiral], offsets=xyo,
-                                transOffset=a.transData)
+                                transOffset=ax1.transData)
 trans = fig.dpi_scale_trans + transforms.Affine2D().scale(1.0/72.0)
 col.set_transform(trans)  # the points to pixels transform
     # Note: the first argument to the collection initializer
     # must be a list of sequences of x,y tuples; we have only
     # one sequence, but we still have to put it in a list.
-a.add_collection(col, autolim=True)
+ax1.add_collection(col, autolim=True)
     # autolim=True enables autoscaling.  For collections with
     # offsets like this, it is neither efficient nor accurate,
     # but it is good enough to generate a plot that you can use
     # as a starting point.  If you know beforehand the range of
     # x and y that you want to show, it is better to set them
     # explicitly, leave out the autolim kwarg (or set it to False),
-    # and omit the 'a.autoscale_view()' call below.
+    # and omit the 'ax1.autoscale_view()' call below.
 
 # Make a transform for the line segments such that their size is
 # given in points:
 col.set_color(colors)
 
-a.autoscale_view()  # See comment above, after a.add_collection.
-a.set_title('LineCollection using offsets')
+ax1.autoscale_view()  # See comment above, after ax1.add_collection.
+ax1.set_title('LineCollection using offsets')
 
 
 # The same data as above, but fill the curves.
-
-a = fig.add_subplot(2,2,2)
-
 col = collections.PolyCollection([spiral], offsets=xyo,
-                                transOffset=a.transData)
+                                transOffset=ax2.transData)
 trans = transforms.Affine2D().scale(fig.dpi/72.0)
 col.set_transform(trans)  # the points to pixels transform
-a.add_collection(col, autolim=True)
+ax2.add_collection(col, autolim=True)
 col.set_color(colors)
 
 
-a.autoscale_view()
-a.set_title('PolyCollection using offsets')
+ax2.autoscale_view()
+ax2.set_title('PolyCollection using offsets')
 
 # 7-sided regular polygons
 
-a = fig.add_subplot(2,2,3)
-
 col = collections.RegularPolyCollection(7,
                                         sizes = np.fabs(xx)*10.0, offsets=xyo,
-                                        transOffset=a.transData)
+                                        transOffset=ax3.transData)
 trans = transforms.Affine2D().scale(fig.dpi/72.0)
 col.set_transform(trans)  # the points to pixels transform
-a.add_collection(col, autolim=True)
+ax3.add_collection(col, autolim=True)
 col.set_color(colors)
-a.autoscale_view()
-a.set_title('RegularPolyCollection using offsets')
+ax3.autoscale_view()
+ax3.set_title('RegularPolyCollection using offsets')
 
 
 # Simulate a series of ocean current profiles, successively
 # offset by 0.1 m/s so that they form what is sometimes called
 # a "waterfall" plot or a "stagger" plot.
 
-a = fig.add_subplot(2,2,4)
-
 nverts = 60
 ncurves = 20
 offs = (0.1, 0.0)
@@ -118,14 +112,14 @@
     segs.append(curve)
 
 col = collections.LineCollection(segs, offsets=offs)
-a.add_collection(col, autolim=True)
+ax4.add_collection(col, autolim=True)
 col.set_color(colors)
-a.autoscale_view()
-a.set_title('Successive data offsets')
-a.set_xlabel('Zonal velocity component (m/s)')
-a.set_ylabel('Depth (m)')
+ax4.autoscale_view()
+ax4.set_title('Successive data offsets')
+ax4.set_xlabel('Zonal velocity component (m/s)')
+ax4.set_ylabel('Depth (m)')
 # Reverse the y-axis so depth increases downward
-a.set_ylim(a.get_ylim()[::-1])
+ax4.set_ylim(ax4.get_ylim()[::-1])
 
 
 plt.show()

examples/api/compound_path.py

@@ -23,8 +23,7 @@
 
 pathpatch = PathPatch(path, facecolor='None', edgecolor='green')
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 ax.add_patch(pathpatch)
 ax.set_title('A compound path')
 

examples/api/date_demo.py

@@ -28,8 +28,7 @@
 datafile = cbook.get_sample_data('goog.npy')
 r = np.load(datafile).view(np.recarray)
 
-fig = plt.figure()
-ax = fig.add_subplot(111)
+fig, ax = plt.subplots()
 ax.plot(r.date, r.adj_close)