matplotlib Code

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Introduction to plotting with matplotlib / pylab
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A bird's eye view
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matplotlib is a library for making 2D plots of arrays in python.
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This short guide is not meant as a complete guide or tutorial.
 There is a more comprehensive user's guide and tutorial on the matplotlib
 web-site at http://matplotlib.sf.net.
\end_inset 

 Although it has its origins in emulating the Matlab graphics commands,
 it does not require matlab, and has a pure, object oriented API.
 Although matplotlib is written primarily in python, it makes heavy use
 of Numeric/numarray and other extension code to provide good performance
 even for large arrays.
 matplotlib is designed with the philosophy that you should be able to create
 simple plots with just a few commands, or just one! If you want to see
 a histogram of your data, you shouldn't need to instantiate objects, call
 methods, set properties, and so on; it should just work.
 
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The matplotlib code is divided into three parts: the 
\shape italic 
pylab interface
\shape default 
 is the set of functions provided by the 
\family typewriter 
pylab
\family default 
 module which allow the user to create plots with code quite similar to
 matlab figure generating code.
 The matplotlib frontend or 
\shape italic 
matplotlib API
\shape default 
 is the set of classes that do the heavy lifting, creating and managing
 figures, text, lines, plots and so on.
 This is an abstract interface that knowns nothing about output formats.
 The 
\shape italic 
backends
\shape default 
 are device dependent drawing devices, aka renderers, that transform the
 frontend representation to hardcopy or a display device.
 Example backends: PS creates postscript hardcopy, SVG creates scalar vector
 graphics hardcopy, Agg creates PNG output using the high quality antigrain
 library that ships with matplotlib, GTK embeds matplotlib in a GTK application,
 GTKAgg uses the antigrain
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collapsed true

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http://antigrain.com
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 renderer to create a figure and embed it a GTK application, and so on for
 WX, Tkinter, FLTK, \SpecialChar \ldots{}
.
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For years, I used to use matlab exclusively for data analysis and visualization.
 matlab excels at making nice looking plots easy.
 When I began working with EEG data, I found that I needed to write applications
 to interact with my data, and developed and EEG analysis application in
 matlab.
 As the application grew in complexity, interacting with databases, http
 servers, manipulating complex data structures, I began to strain against
 the limitations of matlab as a programming language, and decided to start
 over in python.
 python more than makes up for all of matlab's deficiencies as a programming
 language, but I was having difficulty finding a 2D plotting package --
 for 3D VTK, which is discussed at length below more than exceeds all of
 my needs.
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When I went searching for a python plotting package, I had several requirements:
 
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Plots should look great - publication quality.
 One important requirement for me is that the text looks good (antialiased,
 etc)
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Postscript output for inclusion with LaTeX documents and publication quality
 printing
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Embeddable in a graphical user interface for application development
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The code should be mostly python so itis easy to understand and extend --
 users become developers!
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Making plots should be easy -- just a few lines of code for simple graphs
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Finding no package that suited me just right, I did what any self-respecting
 python programmer would do: rolled up my sleeves and dived in.
 Not having any real experience with computer graphics, I decided to emulate
 matlab's plotting capabilities because that is something matlab does very
 well.
 This had the added advantage that many people have a lot of matlab experience,
 and thus they can quickly get up to steam plotting in python.
 From a developer's perspective, having a fixed user interface (the pylab
 interface) has been very useful, because the guts of the code base can
 be redesigned without affecting user code.
 
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Without further ado, let's create our first figure.
 This example uses the matplotlib object oriented API.
 Most users use the pylab interface, which will be discussed next and makes
 it easier to make plots because a lot of the tedius work of creating and
 managing figures and figure windows is done for you behind the hood.
 But since the real core of the library is the object oriented API, I think
 it is a good place to start.
 If you are developing a graphical user interface or making plots on a web
 server, you probably want maximal control with no magic going on behind
 the scenes -- this is where the matplotlib API should be used.
 If you are just trying to make a figure for inclusion in a paper or if
 your working interactively from the python shell, you'll probably be happy
 with the pylab interface.
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\backslash 
lstinputlisting[caption={Creating a simple figure with the antigrain backend (generates PNG) using the object oriented matplotlib library}]{examples/mpl_agg_oo.py}
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\begin_inset Float figure
wide false
collapsed true

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\align center 

\begin_inset Graphics
	filename fig/mpl_one_two_three.png
	lyxscale 50
	width 4in

\end_inset 


\layout Caption


\begin_inset LatexCommand \label{fig:mpl_agg}

\end_inset 

A simple plot generated by the antigrain (Agg) backend .
\end_inset 


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A short pylab tutorial
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Here is about the simplest code you can use to create a figure with matplotlib
 using the pylab interface.
 In this section, I'm assuming you are using ipython in the pylab mode --
 see the ipython chapter for details.
 
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peds-pc311:~> pylab
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Python 2.3.3 (#2, Apr 13 2004, 17:41:29)
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Type "copyright", "credits" or "license" for more information.
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IPython 0.6.12_cvs -- An enhanced Interactive Python.
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?       -> Introduction to IPython's features.
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%magic  -> Information about IPython's 'magic' % functions.
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help    -> Python's own help system.
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object? -> Details about 'object'.
 ?object also works, ?? prints more.
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  Welcome to pylab, a matplotlib-based Python environment
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    help(matplotlib) -> generic matplotlib information
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    help(pylab)      -> matlab-compatible commands from matplotlib
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    help(plotting)   -> plotting commands
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In [1]: plot([1,2,3,4])
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\begin_inset Float figure
wide false
collapsed true

\layout Standard
\align center 

\begin_inset Graphics
	filename fig/mpl_toolbar.png
	lyxscale 50
	width 5in

\end_inset 


\layout Caption


\begin_inset LatexCommand \label{fig:mpl_toolbar}

\end_inset 

The matplotlib toolbar used to navigate around your figure
\end_inset 


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If your settings are correct, a figure window should popup and you should
 be able to interact with it.
 That's a lot less typing than our initial example using the object oriented
 API in which you had to manually create the Figure, Axes and so on!
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Try clicking on the navigation toolbar at the bottom of the figure -- the
 toolbar is shown in Figure
\begin_inset LatexCommand \ref{fig:mpl_toolbar}

\end_inset 

.
 The first three buttons from left to right in Figure
\begin_inset LatexCommand \ref{fig:mpl_toolbar}

\end_inset 

 are 
\shape italic 
home
\shape default 
, 
\shape italic 
back
\shape default 
 and 
\shape italic 
forward
\shape default 
.
 These byttons are are akin to the web browser 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 as described below.
 This is analogous to trying to click 
\family typewriter 
Back
\family default 
 on your web browser before visiting a new page --nothing happens.
 The home button always takes you to the first, default view of your data.
 
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The next to button moving right is the pan/zoom button, which looks like
 a cross with arrows on the end (a 
\shape italic 
fleur
\shape default 
).
 The pan/zoom button button has two modes: pan and zoom (no surprise there,
 right?).
 Click this toolbar button to activate this mode; you should see 
\begin_inset Quotes eld
\end_inset 

pan/zoom mode
\begin_inset Quotes erd
\end_inset 

 show up in the status bar.
 Then put your mouse somewhere over an axes.
 To activate panning: press the left mouse button and hold it, dragging
 it to a new position.
 If you press 
\family typewriter 
x
\family default 
 or 
\family typewriter 
y
\family default 
 while panning, the motion will be contrained to the x or y axis, respectively
 .
 To activate zooming, press the right mouse button, 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 
\family typewriter 
x
\family default 
, 
\family typewriter 
y
\family default 
 or 
\family typewriter 
CONTROL
\family default 
 to constrain the zoom to the x axes, the y axes, or aspect ratio preserve,
 respectively.
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The
\shape italic 
 
\shape default 
next button moving right is the
\shape italic 
 zoom to rectangle button
\shape default 
 which has a magnifying glass over a piece of paper.
 The button is striaghtforward and works in the standard way; when you click
 it, you should see that it is activated by looking for 
\begin_inset Quotes eld
\end_inset 

Zoom to rect mode
\begin_inset Quotes erd
\end_inset 

 in the status bar, and then you select the rectangular region you want
 to zoom in on.
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The final button is the
\shape italic 
 save button
\shape default 
, which will save your figure in the current view.
 All of the *Agg backends know how to save the following image types: PNG,
 PS, EPS, SVG.
 
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Let's make the same figure we made using the object oriented API above,
 ie Figure
\begin_inset LatexCommand \ref{fig:mpl_agg}

\end_inset 

, but this time using the pylab 
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from pylab import *
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plot([1,2,3])
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title('hi mom')
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grid(True)
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xlabel('time')
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ylabel('volts')
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savefig('../fig/mpl_one_two_three.png')
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show()
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As you can see there is basically a direct translation between the OO interface
 and the pylab interface.
 When 
\family typewriter 
plot
\family default 
 is called, the pylab interface makes a call to the function 
\family typewriter 
gca()
\family default 
 (``get current axes'') to get a reference to the current axes.
 
\family typewriter 
gca
\family default 
 in turn, makes a call to 
\family typewriter 
gcf
\family default 
 (
\begin_inset Quotes eld
\end_inset 

get current figure
\begin_inset Quotes erd
\end_inset 

) to get a reference to the current figure.
 
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gcf
\family default 
, finding that no figure has been created, creates the default figure using
 
\family typewriter 
figure() 
\family default 
and returns it.
 
\family typewriter 
gca
\family default 
 will then return the current axes of that figure if it exists, or create
 the default axes 
\family typewriter 
subplot(111)
\family default 
 if it does not.
 The last line show is a GUI independent way of actually creating a figure
 window, and is not required for image backends such as postscript.
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Thus a lot happens under the hood when you call plot, but for the most part
 you don't need to think about it -- it just works.
 The important thing to understand is that the pylab interface has a state,
 and keeps track of the current figure and axes.
 All plotting commands target the current axes, and you can manipulate which
 ones are current
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\backslash 
lstinputlisting[caption={Creating multiple subplots and plotting multiple lines in a single plot command}]{examples/mpl_subplot_demo.py}
\end_inset 


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\begin_inset Float figure
wide false
collapsed true

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\align center 

\begin_inset Graphics
	filename fig/mpl_subplot_demo.png
	lyxscale 50
	width 4in

\end_inset 


\layout Caption


\begin_inset LatexCommand \label{fig:mpl_subplot}

\end_inset 

It's easy to create multiple axes and subplots.
\end_inset 


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In addition to creating multiple subplots, this example contains a couple
 of new things.
 In the first plot command, the return value is stored as 
\family typewriter 
l1, l2
\family default 
 and the 
\family typewriter 
set
\family default 
 command is used to change a default line property.
 
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l1, l2 = plot(t1, f(t1), 'bo', t2, f(t2), 'k--')
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set(l1, markerfacecolor='g')
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\family typewriter 
l1
\family default 
 and 
\family typewriter 
l2
\family default 
 are 
\family typewriter 
matplotlib.lines.Line2D
\family default 
 instances and they are created by the 
\family typewriter 
plot
\family default 
 command and added to the current axes.
 This is the typical mode of operation of the axes plot commands: they create
 a bunch of primitive objects (lines, polygons, text, images), add them
 to the axes, and return them.
 In this example, the line's 
\family typewriter 
markerfacecolor
\family default 
 property is set with the 
\family typewriter 
set
\family default 
 command.
 In the next section, we'll look into matplotlibs 
\family typewriter 
set
\family default 
 and 
\family typewriter 
get
\family default 
 introspection system and show how to use it to customize your lines, polygons,
 text instances and images.
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Set and get introspection
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Everything that goes into a matplotlib figure, including the 
\family typewriter 
Figure
\family default 
 itself, are all objects dervied from a single base class 
\family typewriter 
Artist, 
\family default 
and the pylab 
\family typewriter 
set
\family default 
 and 
\family typewriter 
get
\family default 
 commands provide a unified way to configure them.
 Let's create a simple plot of random circles, and use that to explore how
 
\family typewriter 
set
\family default 
 and get work.
 First the basic plot -- we'll store the return value as lines.
 Note that 
\family typewriter 
plot
\family default 
 always returns a 
\shape italic 
list
\shape default 
 of lines; in the example above there were two lines 
\family typewriter 
l1
\family default 
 and 
\family typewriter 
l2
\family default 
, and in the example below there is only a single element of the list lines.
 No matter: 
\family typewriter 
set
\family default 
 and 
\family typewriter 
get
\family default 
 will work on a single instance or a sequence of instances
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In [6]: x = rand(20); y = rand(20)
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In [7]: lines = plot(x,y,'o')
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In [8]: type(lines)       
\color blue
# plot always returns a list
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Out[8]: <type 'list'>
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In [9]: len(lines)        
\color blue
# even if it has a single element
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Out[9]: 1
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The simple figure that was created, a scattering of blue circles at random
 locations, is shown in Figure
\begin_inset LatexCommand \ref{fig:mpl_setget1}

\end_inset 

.
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\begin_inset Float figure
wide false
collapsed true

\layout Standard
\align center 

\begin_inset Graphics
	filename fig/mpl_set_get1.png
	lyxscale 20
	width 4in

\end_inset 


\layout Caption


\begin_inset LatexCommand \label{fig:mpl_setget1}

\end_inset 

The default marker plot, before marker customization
\end_inset 


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To see a listing of the properties of the line, and what their current values
 are, call 
\family typewriter 
get(lines)
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In [17]: get(lines)
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    alpha = 1.0
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    antialiased or aa = True
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    clip_on = True
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    color or c = blue
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    figure = <matplotlib.figure.Figure instance at 0xb45351ec>
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    label =
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    linestyle or ls = None
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    linewidth or lw = 0.5
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    marker = o
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    markeredgecolor or mec = black
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    markeredgewidth or mew = 0.5
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    markerfacecolor or mfc = blue
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    markersize or ms = 6.0
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    transform = <Affine object at 0x8560fd4>
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    visible = True
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    xdata = [ 0.92011374  0.21795347  0.09758196  0.9608943   0.82332173  0.08097414]...
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    ydata = [ 0.86377059  0.25058593  0.04721988  0.22290987  0.23596015  0.39763723]...
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and to see the same listing of properties with information on legal values
 you can set them to, call 
\family typewriter 
set(lines)
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In [19]: set(lines)
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    alpha: float
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    antialiased or aa: [True | False]
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    clip_box: a matplotlib.transform.Bbox instance
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    clip_on: [True | False]
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    color or c: any matplotlib color - see help(colors)
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    dashes: sequence of on/off ink in points
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    data: (array xdata, array ydata)
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    data_clipping: [True | False]
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    figure: a matplotlib.figure.Figure instance
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    label: any string
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    linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' ]
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    linewidth or lw: float value in points
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    lod: [True | False]
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    marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4' | '<' | '>' | 'D' |
 'H' | '^' | '_' | 'd' | 'h' | 'o' | 'p' | 's' | 'v' | 'x' | '|' ]
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    markeredgecolor or mec: any matplotlib color - see help(colors)
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    markeredgewidth or mew: float value in points
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    markerfacecolor or mfc: any matplotlib color - see help(colors)
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    markersize or ms: float
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    transform: a matplotlib.transform transformation instance
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    visible: [True | False]
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    xclip: (xmin, xmax)
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    xdata: array
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    yclip: (ymin, ymax)
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    ydata: array
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    zorder: any number
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OK, we have a lot of options here.
  Let's change the marker properties, and add a linesytle
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In [20]: set(lines, markerfacecolor='green', markeredgecolor='red',
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   ....:  markersize=20, markeredgewidth=3, linestyle='--', linewidth=3)
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\layout Standard

That's a lot of typing, but to great effect!  The same data set now has
 quite a different appearance, which is shown in Figure
\begin_inset LatexCommand \ref{fig:mpl_setget2}

\end_inset 

.
 Note in the long listing output of the set(lines) command above the markerfacec
olor settable property is listed as
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markerfacecolor or mfc: any matplotlib color - see help(colors)
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The 
\family typewriter 
markerfacecolor
\family default 
 has an alias 
\family typewriter 
mfc
\family default 
 to save typing, and common colornames have abbreviations too, so the 
\family typewriter 
set
\family default 
 command above could just as well be written
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In [20]: set(lines, mfc='g', mec='r', ms=20, mew=3, ls='--', lw=3)
\layout LyX-Code


\begin_inset Float figure
wide false
collapsed false

\layout Standard
\align center 

\begin_inset Graphics
	filename fig/mpl_set_get2.png
	lyxscale 20
	width 4in

\end_inset 


\layout Caption


\begin_inset LatexCommand \label{fig:mpl_setget2}

\end_inset 

The default marker plot, before marker customization
\end_inset 


\layout Standard

Another nice thing about matplotlib properties is that you can pass them
 in as keyword arguments to 
\family typewriter 
plot
\family default 
 and they will have the same effect, eg, you can create the identical plot
 with
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In [22]: plot(x, y, 'o', mfc='g', mec='r', ms=20, mew=3, ls='--', lw=3)
\layout LyX-Code

Out[22]: [<matplotlib.lines.Line2D instance at 0xb40db42c>]
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\layout Standard

As noted above, 
\emph on 
set
\emph default 
 and get work on any Artist, so you can configure your axes or text instances
 this way.
  Eg, xlabel returns a matplotlib.text.Text instance
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In [23]: t = xlabel('time (s)')
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In [24]: set(t)
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    alpha: float
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    backgroundcolor: any matplotlib color - see help(colors)
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    bbox: rectangle prop dict plus key 'pad' which is a pad in points
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    clip_box: a matplotlib.transform.Bbox instance
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    clip_on: [True | False]
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    color: any matplotlib color - see help(colors)
\layout LyX-Code

    family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace'
 ]
\layout LyX-Code

    figure: a matplotlib.figure.Figure instance
\layout LyX-Code

    fontproperties: a matplotlib.font_manager.FontProperties instance
\layout LyX-Code

    horizontalalignment or ha: [ 'center' | 'right' | 'left' ]
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    label: any string
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    lod: [True | False]
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    multialignment: ['left' | 'right' | 'center' ]
\layout LyX-Code

    name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]
\layout LyX-Code

    position: (x,y)
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    rotation: [ angle in degrees 'vertical' | 'horizontal'
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    size or fontsize: [ size in points | relative size eg 'smaller', 'x-large'
 ]    style or fontstyle: [ 'normal' | 'italic' | 'oblique']
\layout LyX-Code

    text: string
\layout LyX-Code

    transform: a matplotlib.transform transformation instance
\layout LyX-Code

    variant: [ 'normal' | 'small-caps' ]
\layout LyX-Code

    verticalalignment or va: [ 'center' | 'top' | 'bottom' ]
\layout LyX-Code

    visible: [True | False]
\layout LyX-Code

    weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold'
 | 'ultralight']
\layout LyX-Code

    x: float
\layout LyX-Code

    y: float
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    zorder: any number
\layout LyX-Code

\layout Standard

So you have a lot of possibilities to customize your text!  The most common
 things people what to do are change the font size and color; the results
 of this command on the xlabel are shown in Figure
\begin_inset LatexCommand \ref{fig:mpl_setget2}

\end_inset 

.
\layout LyX-Code

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In [25]: set(t, fontsize=20, color='darkslategray') 
\layout Section

A common interface to Numeric and numarray
\layout Standard

Currently the python computing community is in a state of having too many
 array pacakges, none of which satisfy everyone's needs.
 Although Numeric and numarray both provide the same set of core functions,
 they are organized differently, and matplotlib provides a compatibility
 later so you can use either one in your matplotlib scripts without having
 to change your code.
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Several numarray/Numeric developers are codevelopers of matplotlib, giving
 matplotlib full Numeric and numarray compatibility, thanks in large part
 to Todd Miller's 
\family typewriter 
matplotlib.numerix
\family default 
 module and the numarray compatibility layer for extension code.
 This allows you to choose between Numeric or numarray at the prompt or
 in a config file.
 Thus when you do
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\color blue
# import matplotlib and all the numerix functions
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from pylab import *
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you'll not only get all the matplotlib pylab interface commands, but most
 of the Numeric or numarray package as well (depending on your 
\family typewriter 
numerix
\family default 
 setting).
 All of the array creation and manipulation functions are imported, such
 as 
\family typewriter 
array
\family default 
, 
\family typewriter 
arange
\family default 
, 
\family typewriter 
take
\family default 
, 
\family typewriter 
where
\family default 
, etc, as are the external module functions which reside in
\family typewriter 
 mlab, fft
\family default 
 and 
\family typewriter 
linear_algebra.

\family default 
 
\layout Standard

Even if you don't want to import all of the numerix symbols from the pytlab
 interface, to make your matplotlib scripts as portable as possible with
 respect to your choice of array packages, it is advised not to explicitly
 import Numeric or numarray.
 Rather, you should use 
\family typewriter 
matplotlib.numerix
\family default 
 where possible, either by using the functions imported by
\family typewriter 
 pylab
\family default 
, or by explicitly importing the 
\family typewriter 
numerix
\family default 
 module, as in 
\layout LyX-Code


\color blue
# create a numerix namespace
\layout LyX-Code

import matplotlib.numerix as n
\layout LyX-Code

from matplotlib.numerix.mlab import mean
\layout LyX-Code

x = n.arange(100)
\layout LyX-Code

y = n.take(x, range(10,20))
\layout LyX-Code

print mean(y)
\layout Standard

For the remainder of this manual, the term 
\family typewriter 
numerix
\family default 
 is used to mean either the Numeric or numarray package.
 To select numarray or Numeric from the prompt, run your matplotlib script
 with
\layout LyX-Code

  > python myscript.py --numarray  
\color blue
# use numarray
\layout LyX-Code

  > python myscript.py --Numeric   
\color blue
# use Numeric
\layout Standard

Typically, however, users will choose one or the other and make this setting
 in their rc file using either 
\family typewriter 
numerix : Numeric
\family default 
 or 
\family typewriter 
numerix : numarray
\family default 
.
 
\layout Section

Customizing the default behavior with the rc file
\layout Standard

matplotlib is designed to work in a variety of settings: some people use
 it in "batch mode" on a web server to create images they never look at.
 Others use graphical user interfaces (GUIs) to interact with their plots.
 Thus you must customize matplotlib to work like you want it to with the
 customization file 
\family typewriter 
.matplotlibrc
\family default 
, in which you can set whether you want to just create images or use a GUI
 (the backend setting), and whether you want to work interactively from
 the shell (the interactive setting).
 Almost all of the matplotlib settings and figure properties can be customized
 with this file, which is installed with the rest of the matplotlib data
 (fonts, icons, etc) into a directory determined by distutils.
 Before compiling matplotlib, it resides in the same dir as 
\family typewriter 
setup.py
\family default 
 and will be copied into your install path.
 Typical locations for this file are
\family typewriter 
 
\layout LyX-Code

C:
\backslash 
Python23
\backslash 
share
\backslash 
matplotlib
\backslash 
.matplotlibrc 
\color blue
# on Microsoft windows
\color default
 /usr/local/share/matplotlib/.matplotlibrc  
\color blue
# on linux/UNIX machines
\layout Standard

By default, the installer will overwrite the existing file in the install
 path, so if you want to preserve your's, please move it to your 
\family typewriter 
HOME
\family default 
 dir and set the environment variable if necessary.
 In the rc file, you can set your backend , your numerix setting , whether
 you'll be working interactively and default values for most of the figure
 properties.
 
\layout Standard

In the RC file, blank lines, or lines starting with a comment symbol, are
 ignored, as are trailing comments.
 Other lines must have the format
\layout LyX-Code

 key : val 
\color blue
# optional comment
\color default
 
\layout Standard

where 
\shape italic 
key
\shape default 
 is some property like 
\family typewriter 
backend
\family default 
, 
\family typewriter 
lines.linewidth
\family default 
, or 
\family typewriter 
figure.figsize
\family default 
 and 
\shape italic 
val
\shape default 
 is the value of that property.
 Example entries for these properties are
\layout LyX-Code


\color blue
# this is a comment and is ignored 
\layout LyX-Code

backend         : GTKAgg    
\color blue
# the default backend 
\layout LyX-Code

lines.linewidth : 0.5       
\color blue
# line width in points
\color default
 
\layout LyX-Code

figure.figsize  : 8, 6      
\color blue
# figure size in inches 
\layout Standard

A complete sample rc file is included with the matplotlib distribution and
 available online.
\begin_inset Foot
collapsed true

\layout Standard

http://matplotlib.sourceforge.net/.matplotlibrc
\end_inset 


\layout Section

Nonlinear transformations: log and polar
\layout Section

Scatter plots
\layout Section

Histograms and bar charts
\layout Section

Spectral analysis
\layout Section

Images
\layout Section

Customizing text and mathematical expressions
\layout Section

Event handling: Tracking the mouse and keyboard
\the_end