Revision: 6426
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6426&view=rev
Author: efiring
Date: 2008-11-21 00:06:53 +0000 (Fri, 21 Nov 2008)
Log Message:
-----------
Add an embryonic usage_faq.rst, based on a reply to a question on the list
Modified Paths:
--------------
trunk/matplotlib/doc/faq/index.rst
Added Paths:
-----------
trunk/matplotlib/doc/faq/usage_faq.rst
Modified: trunk/matplotlib/doc/faq/index.rst
===================================================================
--- trunk/matplotlib/doc/faq/index.rst 2008-11-20 23:03:17 UTC (rev 6425)
+++ trunk/matplotlib/doc/faq/index.rst 2008-11-21 00:06:53 UTC (rev 6426)
@@ -15,6 +15,6 @@
:maxdepth: 2
installing_faq.rst
- usage.rst
+ usage_faq.rst
howto_faq.rst
troubleshooting_faq.rst
Added: trunk/matplotlib/doc/faq/usage_faq.rst
===================================================================
--- trunk/matplotlib/doc/faq/usage_faq.rst (rev 0)
+++ trunk/matplotlib/doc/faq/usage_faq.rst 2008-11-21 00:06:53 UTC (rev
6426)
@@ -0,0 +1,82 @@
+.. _usage-faq:
+
+***************
+Usage
+***************
+
+.. contents::
+ :backlinks: none
+
+.. _pylab:
+
+Matplotlib, pylab, and pyplot: how are they related?
+====================================================
+
+Matplotlib is the whole package; :mod:`pylab` is a module in matplotlib
+that gets
+installed alongside :mod:`matplotlib`; and :mod:`matplotlib.pyplot` is a
+module in matplotlib.
+
+Pyplot provides a Matlab-style state-machine interface to
+the underlying object-oriented plotting library in matplotlib.
+
+Pylab combines the pyplot functionality (for plotting) with the numpy
+functionality (for mathematics and for working with arrays)
+in a single namespace, making that namespace
+(or environment) even more Matlab-like. This is what you get if
+you use the
+*ipython* shell with the *-pylab* option, which imports everything
+from pylab and makes plotting fully interactive.
+
+We have been gradually converting the matplotlib examples
+from pure Matlab-style, using "from pylab import \*", to a preferred
+style in which pyplot is used for some convenience functions, either
+pyplot or the object-oriented style is used for the remainder of the
+plotting code, and numpy is used explicitly for numeric array operations.
+
+In this preferred style, the imports at the top are::
+
+ import matplotlib.pyplot as plt
+ import numpy as np
+
+Then one calls, for example, np.arange, np.zeros, np.pi, plt.figure,
+plt.plot, plt.show, etc.
+
+Example, pure Matlab-style::
+
+ from pylab import *
+ x = arange(0, 10, 0.2)
+ y = sin(x)
+ plot(x, y)
+ show()
+
+Now in preferred style, but still using pyplot interface::
+
+ import matplotlib.pyplot as plt
+ import numpy as np
+ x = np.arange(0, 10, 0.2)
+ y = np.sin(x)
+ plt.plot(x, y)
+ plt.show()
+
+And using pyplot convenience functions, but object-orientation for the rest::
+
+ import matplotlib.pyplot as plt
+ import numpy as np
+ x = np.arange(0, 10, 0.2)
+ y = np.sin(x)
+ fig = plt.figure()
+ ax = fig.add_subplot(111)
+ ax.plot(x, y)
+ plt.show()
+
+So, why do all the extra typing required as one moves away from the pure
+matlab-style? For very simple things like this example, the only
+advantage is educational: the wordier styles are more explicit, more
+clear as to where things come from and what is going on. For more
+complicated applications, the explicitness and clarity become
+increasingly valuable, and the richer and more complete object-oriented
+interface will likely make the program easier to write and maintain.
+
+
+
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