added the pyplot tutorial to the users guide

jdh2358 · jdh2358 · commit 9a7ba08c9ff1 · 2008-05-23T18:17:23.000Z
svn path=/trunk/matplotlib/; revision=5233
diff --git a/doc/users_guide/figures/dollar_ticks.py b/doc/users_guide/figures/dollar_ticks.py
@@ -14,7 +14,4 @@
     tick.label2On = True
     tick.label2.set_color('green')
 
-fig.savefig('dollar_ticks')
-plt.show()
-
 
diff --git a/doc/users_guide/figures/fig_axes_customize_simple.py b/doc/users_guide/figures/fig_axes_customize_simple.py
@@ -24,6 +24,4 @@
     line.set_markeredgewidth(3)
 
 
-fig.savefig('fig_axes_customize_simple')
 
-plt.show()
diff --git a/doc/users_guide/figures/fig_axes_labels_simple.py b/doc/users_guide/figures/fig_axes_labels_simple.py
@@ -16,6 +16,4 @@
     facecolor='yellow', edgecolor='yellow')
 ax2.set_xlabel('time (s)')
 
-fig.savefig('fig_axes_labels_simple')
 
-plt.show()
diff --git a/doc/users_guide/figures/fig_x.py b/doc/users_guide/figures/fig_x.py
@@ -9,5 +9,4 @@
 
 fig.lines.extend([l1, l2])
 
-fig.savefig('fig_x')
-plt.show()
+
diff --git a/doc/users_guide/figures/make.py b/doc/users_guide/figures/make.py
@@ -1,22 +1,33 @@
 #!/usr/bin/env python
 import sys, os, glob
 import matplotlib
+import IPython.Shell
 matplotlib.rcdefaults()
 matplotlib.use('Agg')
 
-def figs():
-    # each one of these will make a figure when imported
-    import dollar_ticks
-    import fig_axes_customize_simple
-    import fig_axes_labels_simple
-    import fig_x
+mplshell = IPython.Shell.MatplotlibShell('mpl')
 
+def figs():
+    print 'making figs'
+    import matplotlib.pyplot as plt
+    for fname in glob.glob('*.py'):
+        if fname==__file__: continue
+        basename, ext = os.path.splitext(fname)
+        outfile = '%s.png'%basename
+
+        if os.path.exists(outfile):
+            print '    already have %s'%outfile
+            continue
+        else:
+            print '    building %s'%fname
+        plt.gcf().clf() # we need to clear between runs
+        mplshell.magic_run(basename)
+        plt.savefig('%s.png'%basename)
     print 'all figures made'
-    for fname in glob.glob('*.pyc'):
-        os.remove(fname)
+
 
 def clean():
-    patterns = ['#*', '*~', '*.png']
+    patterns = ['#*', '*~', '*.png', '*pyc']
     for pattern in patterns:
         for fname in glob.glob(pattern):
             os.remove(fname)
diff --git a/doc/users_guide/figures/pyplot_formatstr.py b/doc/users_guide/figures/pyplot_formatstr.py
@@ -0,0 +1,5 @@
+import matplotlib.pyplot as plt
+plt.plot([1,2,3,4], [1,4,9,16], 'ro')
+plt.axis([0, 6, 0, 20])
+
+
diff --git a/doc/users_guide/figures/pyplot_mathtext.py b/doc/users_guide/figures/pyplot_mathtext.py
@@ -0,0 +1,12 @@
+import numpy as np
+import matplotlib.pyplot as plt
+t = np.arange(0.0, 2.0, 0.01)
+s = np.sin(2*np.pi*t)
+
+plt.plot(t,s)
+plt.title(r'$\alpha_i > \beta_i$', fontsize=20)
+plt.text(1, -0.6, r'$\sum_{i=0}^\infty x_i$', fontsize=20)
+plt.text(0.6, 0.6, r'$\mathcal{A}\mathrm{sin}(2 \omega t)$',
+         fontsize=20)
+plt.xlabel('time (s)')
+plt.ylabel('volts (mV)')
diff --git a/doc/users_guide/figures/pyplot_simple.py b/doc/users_guide/figures/pyplot_simple.py
@@ -0,0 +1,4 @@
+import matplotlib.pyplot as plt
+plt.plot([1,2,3])
+plt.ylabel('some numbers')
+
diff --git a/doc/users_guide/figures/pyplot_text.py b/doc/users_guide/figures/pyplot_text.py
@@ -0,0 +1,17 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+mu, sigma = 100, 15
+x = mu + sigma * np.random.randn(10000)
+
+# the histogram of the data
+n, bins, patches = plt.hist(x, 50, normed=1, facecolor='g', alpha=0.75)
+
+
+plt.xlabel('Smarts')
+plt.ylabel('Probability')
+plt.title('Histogram of IQ')
+plt.text(85, .025, r'$\mu=100,\ \sigma=15$')
+plt.axis([40, 160, 0, 0.03])
+plt.grid(True)
+
diff --git a/doc/users_guide/figures/pyplot_three.py b/doc/users_guide/figures/pyplot_three.py
@@ -0,0 +1,9 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+# evenly sampled time at 200ms intervals
+t = np.arange(0., 5., 0.2)
+
+# red dashes, blue squares and green triangles
+plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')
+
diff --git a/doc/users_guide/figures/pyplot_two_subplots.py b/doc/users_guide/figures/pyplot_two_subplots.py
@@ -0,0 +1,16 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+def f(t):
+    return np.exp(-t) * np.cos(2*np.pi*t)
+
+t1 = np.arange(0.0, 5.0, 0.1)
+t2 = np.arange(0.0, 5.0, 0.02)
+
+plt.figure(1)
+plt.subplot(211)
+plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')
+
+plt.subplot(212)
+plt.plot(t2, np.cos(2*np.pi*t2), 'r--')
+
diff --git a/doc/users_guide/navigation_toolbar.txt b/doc/users_guide/navigation_toolbar.txt
@@ -0,0 +1,112 @@
+Interactive navigation
+======================
+
+All figure windows come with a navigation toolbar, which can be used
+to navigate through the data set.  Here is a description of each of
+the buttons at the bottom of the toolbar
+
+.. image:: ../../lib/matplotlib/mpl-data/images/home.png
+   :scale: 100
+
+.. image:: ../../lib/matplotlib/mpl-data/images/back.png
+   :scale: 100
+
+.. image:: ../../lib/matplotlib/mpl-data/images/forward.png
+   :scale: 100
+
+The ``Forward`` and ``Back`` buttons 
+    These are akin to the web browser forward and back buttons.  They
+    are used to navigate back and forth between previously defined
+    views.  They have no meaning unless you have already navigated
+    somewhere else using the pan and zoom buttons.  This is analogous
+    to trying to click ``Back`` on your web browser before visiting a
+    new page --nothing happens.  ``Home`` always takes you to the
+    first, default view of your data.  For ``Home``, ``Forward`` and
+    ``Back``, think web browser where data views are web pages.  Use
+    the pan and zoom to rectangle to define new views.
+
+.. image:: ../../lib/matplotlib/mpl-data/images/move.png
+   :scale: 100
+
+The ``Pan/Zoom`` button 
+    This button has two modes: pan and zoom.  Click the toolbar button
+    to activate panning and zooming, then put your mouse somewhere
+    over an axes.  Press the left mouse button and hold it to pan the
+    figure, dragging it to a new position.  When you release it, the
+    data under the point where you pressed will be moved to the point
+    where you released.  If you press 'x' or 'y' while panning the
+    motion will be contrained to the x or y axis, respectively.  Press
+    the right mouse button to zoom, dragging it to a new position.
+    The x axis will be zoomed in proportionate to the rightward
+    movement and zoomed out proportionate to the leftward movement.
+    Ditto for the yaxis and up/down motions.  The point under your
+    mouse when you begin the zoom remains stationary, allowing you to
+    zoom to an arbitrary point in the figure.  You can use the
+    modifier keys 'x', 'y' or 'CONTROL' to constrain the zoom to the x
+    axes, the y axes, or aspect ratio preserve, respectively.
+
+.. image:: ../../lib/matplotlib/mpl-data/images/zoom_to_rect.png
+   :scale: 100
+
+The ``Zoom-to-rectangle`` button
+    Click this toolbar button to activate this mode.  Put your mouse
+    somewhere over and axes and press the left mouse button.  Drag the
+    mouse while holding the button to a new location and release.  The
+    axes view limits will be zoomed to the rectangle you have defined.
+    There is also an experimental 'zoom out to rectangle' in this mode
+    with the right button, which will place your entire axes in the
+    region defined by the zoom out rectangle.
+
+.. image:: ../../lib/matplotlib/mpl-data/images/subplots.png
+   :scale: 100
+
+The ``Subplot-configuration`` button
+    Use this tool to configure the parameters of the subplot: the
+    left, right, top, bottom, space between the rows and space between
+    the columns.
+
+.. image:: ../../lib/matplotlib/mpl-data/images/filesave.png
+   :scale: 100
+
+The ``Save`` button 
+    Click this button to launch a file save dialog.  You can save
+    files with the following extensions: ``png``, ``ps``, ``eps``,
+    ``svg`` and ``pdf``.
+
+
+If you are using :mod:`matplotlib.pyplot` the toolbar will be created
+automatically for every figure.  If you are writing your own user
+interface code, you can add the toolbar as a widget.  The exact syntax
+depends on your UI, but we have examples for every supported UI in the
+``matplotlib/examples/user_interfaces`` directory.  Here is some
+example code for GTK::
+
+
+    from matplotlib.figure import Figure
+    from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg as FigureCanvas
+    from matplotlib.backends.backend_gtkagg import NavigationToolbar2GTKAgg as NavigationToolbar
+
+    win = gtk.Window()
+    win.connect("destroy", lambda x: gtk.main_quit())
+    win.set_default_size(400,300)
+    win.set_title("Embedding in GTK")
+
+    vbox = gtk.VBox()
+    win.add(vbox)
+
+    fig = Figure(figsize=(5,4), dpi=100)
+    ax = fig.add_subplot(111)
+    ax.plot([1,2,3])
+
+    canvas = FigureCanvas(fig)  # a gtk.DrawingArea
+    vbox.pack_start(canvas)
+    toolbar = NavigationToolbar(canvas, win)
+    vbox.pack_start(toolbar, False, False)
+
+    win.show_all()
+    gtk.main()
+
+
+
+
+
diff --git a/doc/users_guide/pyplot_tutorial.txt b/doc/users_guide/pyplot_tutorial.txt
diff --git a/doc/users_guide/users_guide.txt b/doc/users_guide/users_guide.txt

Original file line number	Diff line number	Diff line change
`@@ -24,6 +24,4 @@`
`24`	`24`	`line.set_markeredgewidth(3)`
`25`	`25`
`26`	`26`
`27`		`-fig.savefig('fig_axes_customize_simple')`
`28`	`27`
`29`		`-plt.show()`