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285 lines
7.8 KiB
ReStructuredText
Executable file
285 lines
7.8 KiB
ReStructuredText
Executable file
.. _matplotlibscreenshots:
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**********************
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Screenshots
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**********************
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Here you will find a host of example figures with the code that
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generated them
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Simple Plot
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===========
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The most basic :func:`~matplotlib.pyplot.plot`, with text labels
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.. plot:: mpl_examples/pylab_examples/simple_plot.py
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.. _screenshots_subplot_demo:
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Subplot demo
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============
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Multiple regular axes (numrows by numcolumns) are created with the
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:func:`~matplotlib.pyplot.subplot` command.
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.. plot:: mpl_examples/pylab_examples/subplot_demo.py
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.. _screenshots_histogram_demo:
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Histograms
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==========
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The :func:`~matplotlib.pyplot.hist` command automatically generates
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histograms and will return the bin counts or probabilities
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.. plot:: mpl_examples/pylab_examples/histogram_demo.py
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.. _screenshots_path_demo:
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Path demo
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=========
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You can add aribitrary paths in matplotlib as of release 0.98. See
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the :mod:`matplotlib.path`.
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.. plot:: mpl_examples/api/path_patch_demo.py
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.. _screenshots_mplot3d_surface:
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mplot3d
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=========
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The mplot3d toolkit (see :ref:`toolkit_mplot3d-tutorial` and
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:ref:`mplot3d-examples-index`) has support for simple 3d graphs
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including surface, wireframe, scatter, and bar charts (added in
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matlpotlib-0.99). Thanks to John Porter, Jonathon Taylor and Reinier
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Heeres for the mplot3d toolkit. The toolkit is included with all
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standard matplotlib installs.
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.. plot:: mpl_examples/mplot3d/surface3d_demo.py
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.. _screenshots_ellipse_demo:
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Ellipses
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========
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In support of the
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`Phoenix <http://www.jpl.nasa.gov/news/phoenix/main.php>`_ mission to
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Mars, which used matplotlib in ground tracking of the spacecraft,
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Michael Droettboom built on work by Charlie Moad to provide an
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extremely accurate 8-spline approximation to elliptical arcs (see
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:class:`~matplotlib.patches.Arc`) in the viewport. This
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provides a scale free, accurate graph of the arc regardless of zoom
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level
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.. plot:: mpl_examples/pylab_examples/ellipse_demo.py
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.. _screenshots_barchart_demo:
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Bar charts
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==========
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The :func:`~matplotlib.pyplot.bar`
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command takes error bars as an optional argument. You can also use up
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and down bars, stacked bars, candlestick bars, etc, ... See
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`bar_stacked.py <examples/pylab_examples/bar_stacked.py>`_ for another example.
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You can make horizontal bar charts with the
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:func:`~matplotlib.pyplot.barh` command.
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.. plot:: mpl_examples/pylab_examples/barchart_demo.py
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.. _screenshots_pie_demo:
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Pie charts
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==========
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The :func:`~matplotlib.pyplot.pie` command
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uses a matlab(TM) compatible syntax to produce pie charts. Optional
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features include auto-labeling the percentage of area, exploding one
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or more wedges out from the center of the pie, and a shadow effect.
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Take a close look at the attached code that produced this figure; nine
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lines of code.
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.. plot:: mpl_examples/pylab_examples/pie_demo.py
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.. _screenshots_table_demo:
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Table demo
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==========
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The :func:`~matplotlib.pyplot.table` command will place a text table
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on the axes
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.. plot:: mpl_examples/pylab_examples/table_demo.py
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.. _screenshots_scatter_demo:
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Scatter demo
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============
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The :func:`~matplotlib.pyplot.scatter` command makes a scatter plot
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with (optional) size and color arguments. This example plots changes
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in Google stock price from one day to the next with the sizes coding
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trading volume and the colors coding price change in day i. Here the
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alpha attribute is used to make semitransparent circle markers with
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the Agg backend (see :ref:`what-is-a-backend`)
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.. plot:: mpl_examples/pylab_examples/scatter_demo2.py
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.. _screenshots_slider_demo:
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Slider demo
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===========
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Matplotlib has basic GUI widgets that are independent of the graphical
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user interface you are using, allowing you to write cross GUI figures
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and widgets. See matplotlib.widgets and the widget `examples
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<examples/widgets>`
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.. plot:: mpl_examples/widgets/slider_demo.py
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.. _screenshots_fill_demo:
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Fill demo
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=========
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The :func:`~matplotlib.pyplot.fill` command lets you
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plot filled polygons. Thanks to Andrew Straw for providing this
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function
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.. plot:: mpl_examples/pylab_examples/fill_demo.py
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.. _screenshots_date_demo:
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Date demo
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=========
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You can plot date data with major and minor ticks and custom tick
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formatters for both the major and minor ticks; see matplotlib.ticker
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and matplotlib.dates for details and usage.
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.. plot:: mpl_examples/api/date_demo.py
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.. _screenshots_jdh_demo:
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Financial charts
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================
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You can make much more sophisticated financial plots. This example
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emulates one of the `ChartDirector
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<http://www.advsofteng.com/gallery_finance.html>`_ financial plots.
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Some of the data in the plot, are real financial data, some are random
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traces that I used since the goal was to illustrate plotting
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techniques, not market analysis!
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.. plot:: mpl_examples/pylab_examples/finance_work2.py
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.. _screenshots_basemap_demo:
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Basemap demo
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============
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Jeff Whitaker provided this example showing how to efficiently plot a
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collection of lines over a colormap image using the
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:ref:`toolkit_basemap` . Many map projections are handled via the
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proj4 library: cylindrical equidistant, mercator, lambert conformal
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conic, lambert azimuthal equal area, albers equal area conic and
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stereographic. See the `tutorial
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<http://www.scipy.org/wikis/topical_software/Maps>`_ entry on the wiki.
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.. plot:: pyplots/plotmap.py
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.. _screenshots_log_demo:
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Log plots
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=========
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The :func:`~matplotlib.pyplot.semilogx`,
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:func:`~matplotlib.pyplot.semilogy` and
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:func:`~matplotlib.pyplot.loglog` functions generate log scaling on the
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respective axes. The lower subplot uses a base10 log on the xaxis and
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a base 4 log on the yaxis. Thanks to Andrew Straw, Darren Dale and
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Gregory Lielens for contributions to the log scaling
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infrastructure.
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.. plot:: mpl_examples/pylab_examples/log_demo.py
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.. _screenshots_polar_demo:
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Polar plots
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===========
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The :func:`~matplotlib.pyplot.polar` command generates polar plots.
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.. plot:: mpl_examples/pylab_examples/polar_demo.py
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.. _screenshots_legend_demo:
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Legends
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=======
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The :func:`~matplotlib.pyplot.legend` command automatically
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generates figure legends, with Matlab compatible legend placement
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commands. Thanks to Charles Twardy for input on the legend
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command
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.. plot:: mpl_examples/pylab_examples/legend_demo.py
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.. _screenshots_mathtext_examples_demo:
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Mathtext_examples
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=================
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A sampling of the many TeX expressions now supported by matplotlib's
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internal mathtext engine. The mathtext module provides TeX style
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mathematical expressions using `freetype2
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<http://freetype.sourceforge.net/index2.html>`_ and the BaKoMa
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computer modern or `STIX <http://www.stixfonts.org>`_ fonts. See the
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:mod:`matplotlib.mathtext` module for additional. matplotlib mathtext
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is an independent implementation, and does not required TeX or any
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external packages installed on your computer. See the tutorial at
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:ref:`mathtext-tutorial`.
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.. plot:: mpl_examples/pylab_examples/mathtext_examples.py
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.. _screenshots_tex_demo:
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Native TeX rendering
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====================
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Although matplotlib's internal math rendering engine is quite
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powerful, sometimes you need TeX, and matplotlib supports external TeX
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rendering of strings with the *usetex* option.
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.. plot:: pyplots/tex_demo.py
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.. _screenshots_eeg_demo:
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EEG demo
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=========
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You can embed matplotlib into pygtk, wxpython, Tk, FLTK or Qt
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applications. Here is a screenshot of an eeg viewer called pbrain
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which is part of the NeuroImaging in Python suite `NIPY
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<http://neuroimaging.scipy.org>`_. Pbrain is written in pygtk using
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matplotlib. The lower axes uses :func:`~matplotlib.pyplot.specgram`
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to plot the spectrogram of one of the EEG channels. For an example of
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how to use the navigation toolbar in your applications, see
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:ref:`user_interfaces-embedding_in_gtk2`. If you want to use
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matplotlib in a wx application, see
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:ref:`user_interfaces-embedding_in_wx2`. If you want to work with
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`glade <http://glade.gnome.org>`_, see
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:ref:`user_interfaces-mpl_with_glade`.
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.. image:: ../_static/eeg_small.png
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