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https://github.com/triqs/dft_tools
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106 lines
3.4 KiB
ReStructuredText
106 lines
3.4 KiB
ReStructuredText
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.. index:: matplotlib plotter
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.. module:: pytriqs.plot
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.. _plotting:
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Plotting TRIQS objects
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################################
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TRIQS objects can be easily plotted, for example with the standard python plot toolkit `matplotlib
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<http://matplotlib.sourceforge.net/>`_.
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In fact, TRIQS introduces a simple :ref:`plot protocol <plot_protocol>`, which allows to plot
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objects which have a graphical representation.
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A thin layer above matplotlib
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=================================
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TRIQS defines a function *oplot*, similar to the standard matplotlib pyplot.plot function,
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but that can plot TRIQS objects (in fact *any* object, see below).
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We can reproduce the first example of the Green function tutorial :
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.. plot:: reference/python/green/example.py
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:include-source:
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:scale: 70
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The *oplot* function takes :
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* as arguments any object that implements the :ref:`plot protocol <plot_protocol>`,
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for example Green function, Density of state : in fact any object where plotting is reasonable and has been defined ...
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* string formats following objects, as in regular matplotlib, like in the example above.
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* regular options of the matplotlib *pyplot.plot* function
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* options specific to the object to be plotted : here the `x_window` tells the Green function to plot itself in a reduced window of :math:`\omega_n`.
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Multiple panels figures
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=================================
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`Only valid for matplotlib v>=1.0`.
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While one can use the regular matplotlib subfigure to make multi-panel figures,
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subplots makes it a bit more pythonic :
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.. plot:: reference/python/data_analysis/plotting/example.py
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:include-source:
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:scale: 70
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.. index:: plotting protocol
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.. _plot_protocol:
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Plot protocol [Advanced]
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===========================
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What do we need to implement to plot an object ?
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Simply a little `_plot_` method that reduces the object to a set of curves.
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This section describes the conventions on this function.
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As soon as an object defines this method, it can be plotted by the `oplot` function of `pytriqs.plot.mpl_interface`.
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See example below.
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.. function:: _plot_( OptionsDict )
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* OptionDict is a dictionnary of options.
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.. warning::
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* The method _plot_ must consume the options it uses (using e.g. the pop method of dict).
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* Other options will be passed to matplotlib, so leaving spurious options here will lead to errors.
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:rtype: a list of dict representing one curve each. These dict must have the following fields:
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* *xdata* : A 1-dimensional numpy array describing the x-axis points
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* *ydata* : A 1-dimensional numpy array describing the y-axis points
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* *label* : Label of the curve for the legend of the graph
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* *type* : a string : currently "XY" [ optional]
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and optionally :
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* *xlabel* : a label for the x axis. The last object plotted will overrule the previous ones.
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* *ylabel* : a label for the y axis. The last object plotted will overrule the previous ones.
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Example
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-------
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Here's a simple example to illustrate the protocol:
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.. plot:: reference/python/data_analysis/plotting/myobject.py
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:include-source:
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:scale: 70
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Example with options
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---------------------------
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A little bit more complex, with options.
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Note the use of the `pop method of dict <http://docs.python.org/library/stdtypes.html#dict>`_,
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which returns and removes the entry from the dict (with a default value).
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.. plot:: reference/python/data_analysis/plotting/myobject2.py
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:include-source:
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:scale: 70
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