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Add some hyperlinks. Clean up formatting.
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doc/users_guide/introduction.txt

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Introduction
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************
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matplotlib is a library for making 2D plots of arrays in python.
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Although it has its origins in emulating the MATLAB™ graphics
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commands, it does not require MATLAB™, and can be used in a pythonic,
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object oriented way. Although matplotlib is written primarily in pure
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python, it makes heavy use of NumPy and other extension
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matplotlib is a library for making 2D plots of arrays in `Python
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<http://www.python.org>`_. Although it has its origins in emulating
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the `MATLAB™ <http://www.mathworks.com>`_ graphics commands, it does
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not require MATLAB™, and can be used in a Pythonic, object oriented
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way. Although matplotlib is written primarily in pure Python, it
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makes heavy use of `NumPy <http://www.numpy.org>`_ and other extension
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code to provide good performance even for large arrays.
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matplotlib is designed with the philosophy that you should be able to
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create simple plots with just a few commands, or just one! If you
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want to see a histogram of your data, you shouldn't need to
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instantiate objects, call methods, set properties, and so it; it
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instantiate objects, call methods, set properties, and so on; it
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should just work.
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For years, I used to use MATLAB™ exclusively for data analysis and
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application in MATLAB™. As the application grew in complexity,
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interacting with databases, http servers, manipulating complex data
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structures, I began to strain against the limitations of MATLAB™ as a
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programming language, and decided to start over in python. python
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programming language, and decided to start over in Python. Python
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more than makes up for all of matlab's deficiencies as a programming
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language, but I was having difficulty finding a 2D plotting package
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(for 3D VTK more than exceeds all of my needs).
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(for 3D `VTK <http://www.vtk.org/>`_) more than exceeds all of my needs).
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When I went searching for a python plotting package, I had several
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When I went searching for a Python plotting package, I had several
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requirements:
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* Plots should look great - publication quality. One important
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requirement for me is that the text looks good (antialiased, etc)
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requirement for me is that the text looks good (antialiased, etc.)
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* Postscript output for inclusion with TeX documents
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* Embeddable in a graphical user interface for application
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development
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* Code should be easy enough that I can understand it and extend
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it.
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it
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* Making plots should be easy.
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* Making plots should be easy
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Finding no package that suited me just right, I did what any
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self-respecting python programmer would do: rolled up my sleeves and
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self-respecting Python programmer would do: rolled up my sleeves and
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dived in. Not having any real experience with computer graphics, I
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decided to emulate MATLAB™'s plotting capabilities because that is
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something MATLAB™ does very well. This had the added advantage that
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many people have a lot of MATLAB™ experience, and thus they can quickly
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get up to steam plotting in python. From a developer's perspective,
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having a fixed user interface (the pylab interface) has
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many people have a lot of MATLAB™ experience, and thus they can
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quickly get up to steam plotting in python. From a developer's
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perspective, having a fixed user interface (the pylab interface) has
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been very useful, because the guts of the code base can be redesigned
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without affecting user code.
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The matplotlib code is conceptually divided into three parts: the
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*pylab interface* is the set of functions provided by
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:mod:`matplotlib.pylab` which allow the user to create plots with
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code quite similar to MATLAB™ figure generating code. The
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*matplotlib frontend* or *matplotlib API* is the set of
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classes that do the heavy lifting, creating and managing figures, text,
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lines, plots and so on. This is an abstract interface that knows
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nothing about output. The *backends* are device dependent
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drawing devices, aka renderers, that transform the frontend
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representation to hardcopy or a display device. Example backends: PS
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creates postscript hardcopy, SVG creates scalar vector graphics
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hardcopy, Agg creates PNG output using the high quality antigrain
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library that ships with matplotlib --- http://antigrain.com, GTK
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embeds matplotlib in a GTK application, GTKAgg uses the antigrain
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renderer to create a figure and embed it a GTK application, and so on
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for WX, Tkinter, FLTK...
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:mod:`matplotlib.pylab` which allow the user to create plots with code
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quite similar to MATLAB™ figure generating code. The *matplotlib
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frontend* or *matplotlib API* is the set of classes that do the heavy
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lifting, creating and managing figures, text, lines, plots and so on.
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This is an abstract interface that knows nothing about output. The
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*backends* are device dependent drawing devices, aka renderers, that
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transform the frontend representation to hardcopy or a display device.
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Example backends: PS creates `PostScript®
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<http://http://www.adobe.com/products/postscript/>`_ hardcopy, SVG
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creates `Scalable Vector Graphics <http://www.w3.org/Graphics/SVG/>`_
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hardcopy, Agg creates PNG output using the high quality `Anti-Grain
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Geometry <http://www.antigrain.com>`_ library that ships with
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matplotlib, GTK embeds matplotlib in a `Gtk+ <http://www.gtk.org/>`_
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application, GTKAgg uses the Anti-Grain renderer to create a figure
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and embed it a Gtk+ application, and so on for `PDF
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<http://www.adobe.com/products/acrobat/adobepdf.html>`_, `WxWidgets
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<http://www.wxpython.org/>`_, `Tkinter
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<http://docs.python.org/lib/module-Tkinter.html>`_ etc.
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matplotlib is used by many people in many different contexts. Some
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people want to automatically generate postscript files to send to a
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people want to automatically generate PostScript® files to send to a
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printer or publishers. Others deploy matplotlib on a web application
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server to generate PNG output for inclusion in dynamically generated
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web pages. Some use matplotlib interactively from the python shell in
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Tkinter on windows. My primary use is to embed matplotlib in a GTK
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EEG application that runs on windows, linux and OS X.
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server to generate PNG output for inclusion in dynamically-generated
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web pages. Some use matplotlib interactively from the Python shell in
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Tkinter on Windows®. My primary use is to embed matplotlib in a Gtk+
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EEG application that runs on Windows, Linux and Macintosh OS X.
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Because there are so many ways people want to use a plotting library,
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there is a certain amount of complexity inherent in configuring the
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library so that it will work naturally the way you want it to. Before
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diving into these details, let's first explore matplotlib's simplicity
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library so that it will work naturally the way you want it to. Before
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diving into these details, let's first explore matplotlib's simplicity
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by comparing a typical matplotlib script with its analog in MATLAB™.
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--- JDH
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--- JDH

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