Revision: 5234
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5234&view=rev
Author: jdh2358
Date: 2008-05-23 11:29:43 -0700 (Fri, 23 May 2008)
Log Message:
-----------
added the pyplot tutorial to the users guide
Modified Paths:
--------------
trunk/matplotlib/doc/users_guide/artist_api_tut.txt
trunk/matplotlib/doc/users_guide/pyplot_tutorial.txt
Modified: trunk/matplotlib/doc/users_guide/artist_api_tut.txt
===================================================================
--- trunk/matplotlib/doc/users_guide/artist_api_tut.txt 2008-05-23 18:17:23 UTC
(rev 5233)
+++ trunk/matplotlib/doc/users_guide/artist_api_tut.txt 2008-05-23 18:29:43 UTC
(rev 5234)
@@ -1,6 +1,6 @@
-**********************************
-The matplotlib Artist API tutorial
-**********************************
+***************
+Artist tutorial
+***************
There are three layers to the matplotlib API. The FigureCanvas is the
area onto which the figure is drawn, the Renderer is the object which
@@ -198,8 +198,8 @@
at http://matplotlib.sourceforge.net/api.pdf for a listing of
properties for a give object.
-Getting at the objects to customize them
-========================================
+Object containers
+=================
Now that we know how to inspect set the properties of a given
object we want to configure, we need to now how to get at that
@@ -213,8 +213,8 @@
section we'll review where the various container objects store the
Artists that you want to get at.
-The Figure container
---------------------
+Figure container
+----------------
The top level container Artist is the matplotlib.figure.Figure, and it
contains everything in the figure. The background of the figure is a
@@ -263,9 +263,11 @@
In [191]: fig = plt.figure()
- In [192]: l1 = matplotlib.lines.Line2D([0, 1], [0, 1],
transform=fig.transFigure, figure=fig)
+ In [192]: l1 = matplotlib.lines.Line2D([0, 1], [0, 1],
+ transform=fig.transFigure, figure=fig)
- In [193]: l2 = matplotlib.lines.Line2D([0, 1], [1, 0],
transform=fig.transFigure, figure=fig)
+ In [193]: l2 = matplotlib.lines.Line2D([0, 1], [1, 0],
+ transform=fig.transFigure, figure=fig)
In [194]: fig.lines.extend([l1, l2])
@@ -290,8 +292,8 @@
================
===============================================================
-The Axes container
-------------------
+Axes container
+--------------
The matplotlib.axes.Axes is the center of the matplotlib universe --
it contains the vast majority of all the Artists used in a figure with
@@ -523,47 +525,19 @@
grid Turn the grid on or off for the major or minor ticks
======================
=========================================================
-Try creating the figure below
+Here is an example, not recommended for its beauty, which customizes
+the axes and tick properties
+.. literalinclude:: figures/fig_axes_customize_simple.py
+
.. image:: figures/fig_axes_customize_simple.png
:scale: 75
-Exercise solution::
- import numpy as np
- import matplotlib.pyplot as plt
- # plt.figure creates a matplotlib.figure.Figure instance
- fig = plt.figure()
- rect = fig.figurePatch # a rectangle instance
- rect.set_facecolor('lightgoldenrodyellow')
+Tick containers
+---------------
- ax1 = fig.add_axes([0.1, 0.3, 0.4, 0.4])
- rect = ax1.axesPatch
- rect.set_facecolor('lightslategray')
-
-
- for label in ax1.xaxis.get_ticklabels():
- # label is a Text instance
- label.set_color('red')
- label.set_rotation(45)
- label.set_fontsize(16)
-
- for line in ax1.yaxis.get_ticklines():
- # line is a Line2D instance
- line.set_color('green')
- line.set_markersize(25)
- line.set_markeredgewidth(3)
-
- fig.savefig('figures/fig_axes_customize_simple.png', dpi=150)
- fig.savefig('figures/fig_axes_customize_simple.eps')
- plt.show()
-
-
-
-The Tick containers
--------------------
-
The matplotlib.axis.Tick is the final container object in our descent
from the Figure to the Axes to the Axis to the Tick. The Tick
contains the tick and grid line instances, as well as the label
@@ -588,26 +562,9 @@
============== ==========================================================
Here is an example which sets the formatter for the upper ticks with
-dollar signs and colors them green on the right side of the yaxis::
+dollar signs and colors them green on the right side of the yaxis
- import numpy as np
- import matplotlib.pyplot as plt
- import matplotlib.ticker as ticker
+.. literalinclude:: figures/dollar_ticks.py
- fig = plt.figure()
- ax = fig.add_subplot(111)
- ax.plot(100*np.random.rand(20))
-
- formatter = ticker.FormatStrFormatter('$%1.2f')
- ax.yaxis.set_major_formatter(formatter)
-
- for tick in ax.yaxis.get_major_ticks():
- tick.label1On = False
- tick.label2On = True
- tick.label2.set_color('green')
-
- plt.show()
-
-
.. image:: figures/dollar_ticks.png
:scale: 75
Modified: trunk/matplotlib/doc/users_guide/pyplot_tutorial.txt
===================================================================
--- trunk/matplotlib/doc/users_guide/pyplot_tutorial.txt 2008-05-23
18:17:23 UTC (rev 5233)
+++ trunk/matplotlib/doc/users_guide/pyplot_tutorial.txt 2008-05-23
18:29:43 UTC (rev 5234)
@@ -1,6 +1,6 @@
-****************************
-A matplotlib.pyplot tutorial
-****************************
+***************
+pyplot tutorial
+***************
:mod:`matplotlib.pyplot` is a collection of functions that make
matplotlib work like matlab. Each ``pyplot`` function makes some
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