============
 Annotation
============

.. contents:: Table of Contents
   :depth: 3

.. _annotations-tutorial:

Basic annotation
================

The uses of the basic :func:`~matplotlib.pyplot.text` will place text
at an arbitrary position on the Axes.  A common use case of text is to
annotate some feature of the plot, and the
:func:`~matplotlib.Axes.annotate` method provides helper functionality
to make annotations easy.  In an annotation, there are two points to
consider: the location being annotated represented by the argument
``xy`` and the location of the text ``xytext``.  Both of these
arguments are ``(x,y)`` tuples.

.. plot:: mpl_examples/pyplots/annotation_basic.py
   :include-source:


In this example, both the ``xy`` (arrow tip) and ``xytext`` locations
(text location) are in data coordinates.  There are a variety of other
coordinate systems one can choose -- you can specify the coordinate
system of ``xy`` and ``xytext`` with one of the following strings for
``xycoords`` and ``textcoords`` (default is 'data')

====================  ====================================================
argument              coordinate system
====================  ====================================================
  'figure points'     points from the lower left corner of the figure
  'figure pixels'     pixels from the lower left corner of the figure
  'figure fraction'   0,0 is lower left of figure and 1,1 is upper right
  'axes points'       points from lower left corner of axes
  'axes pixels'       pixels from lower left corner of axes
  'axes fraction'     0,0 is lower left of axes and 1,1 is upper right
  'data'              use the axes data coordinate system
====================  ====================================================

For example to place the text coordinates in fractional axes
coordinates, one could do::

    ax.annotate('local max', xy=(3, 1),  xycoords='data',
                xytext=(0.8, 0.95), textcoords='axes fraction',
                arrowprops=dict(facecolor='black', shrink=0.05),
                horizontalalignment='right', verticalalignment='top',
                )

For physical coordinate systems (points or pixels) the origin is the
bottom-left of the figure or axes.

Optionally, you can enable drawing of an arrow from the text to the annotated
point by giving a dictionary of arrow properties in the optional keyword
argument ``arrowprops``.


==================== =====================================================
``arrowprops`` key   description
==================== =====================================================
width                the width of the arrow in points
frac                 the fraction of the arrow length occupied by the head
headwidth            the width of the base of the arrow head in points
shrink               move the tip and base some percent away from
                     the annotated point and text

\*\*kwargs           any key for :class:`matplotlib.patches.Polygon`,
                     e.g., ``facecolor``
==================== =====================================================


In the example below, the ``xy`` point is in native coordinates
(``xycoords`` defaults to 'data').  For a polar axes, this is in
(theta, radius) space.  The text in this example is placed in the
fractional figure coordinate system. :class:`matplotlib.text.Text`
keyword args like ``horizontalalignment``, ``verticalalignment`` and
``fontsize`` are passed from `~matplotlib.Axes.annotate` to the
``Text`` instance.

.. plot:: mpl_examples/pyplots/annotation_polar.py
   :include-source:

For more on all the wild and wonderful things you can do with
annotations, including fancy arrows, see :ref:`plotting-guide-annotation`
and :ref:`pylab_examples-annotation_demo`.


Do not proceed unless you have already read :ref:`annotations-tutorial`,
:func:`~matplotlib.pyplot.text` and :func:`~matplotlib.pyplot.annotate`!


.. _plotting-guide-annotation:

Advanced Annotation
===================


Annotating with Text with Box
-----------------------------

Let's start with a simple example.

.. plot:: users/plotting/examples/annotate_text_arrow.py


The :func:`~matplotlib.pyplot.text` function in the pyplot module (or
text method of the Axes class) takes bbox keyword argument, and when
given, a box around the text is drawn. ::

    bbox_props = dict(boxstyle="rarrow,pad=0.3", fc="cyan", ec="b", lw=2)
    t = ax.text(0, 0, "Direction", ha="center", va="center", rotation=45,
                size=15,
                bbox=bbox_props)


The patch object associated with the text can be accessed by::

    bb = t.get_bbox_patch()

The return value is an instance of FancyBboxPatch and the patch
properties like facecolor, edgewidth, etc. can be accessed and
modified as usual. To change the shape of the box, use the *set_boxstyle*
method. ::

  bb.set_boxstyle("rarrow", pad=0.6)

The arguments are the name of the box style with its attributes as
keyword arguments. Currently, following box styles are implemented.

  ==========   ==============   ==========================
  Class        Name             Attrs
  ==========   ==============   ==========================
  Circle       ``circle``       pad=0.3
  DArrow       ``darrow``       pad=0.3
  LArrow       ``larrow``       pad=0.3
  RArrow       ``rarrow``       pad=0.3
  Round        ``round``        pad=0.3,rounding_size=None
  Round4       ``round4``       pad=0.3,rounding_size=None
  Roundtooth   ``roundtooth``   pad=0.3,tooth_size=None
  Sawtooth     ``sawtooth``     pad=0.3,tooth_size=None
  Square       ``square``       pad=0.3
  ==========   ==============   ==========================

.. plot:: mpl_examples/pylab_examples/fancybox_demo2.py


Note that the attribute arguments can be specified within the style
name with separating comma (this form can be used as "boxstyle" value
of bbox argument when initializing the text instance) ::

   bb.set_boxstyle("rarrow,pad=0.6")




Annotating with Arrow
---------------------

The :func:`~matplotlib.pyplot.annotate` function in the pyplot module
(or annotate method of the Axes class) is used to draw an arrow
connecting two points on the plot. ::

    ax.annotate("Annotation",
                xy=(x1, y1), xycoords='data',
                xytext=(x2, y2), textcoords='offset points',
                )

This annotates a point at ``xy`` in the given coordinate (``xycoords``)
with the text at ``xytext`` given in ``textcoords``. Often, the
annotated point is specified in the *data* coordinate and the annotating
text in *offset points*.
See :func:`~matplotlib.pyplot.annotate` for available coordinate systems.

An arrow connecting two points (xy & xytext) can be optionally drawn by
specifying the ``arrowprops`` argument. To draw only an arrow, use
empty string as the first argument. ::

    ax.annotate("",
                xy=(0.2, 0.2), xycoords='data',
                xytext=(0.8, 0.8), textcoords='data',
                arrowprops=dict(arrowstyle="->",
                                connectionstyle="arc3"),
                )

.. plot:: users/plotting/examples/annotate_simple01.py

The arrow drawing takes a few steps.

1. a connecting path between two points are created. This is
   controlled by ``connectionstyle`` key value.

2. If patch object is given (*patchA* & *patchB*), the path is clipped to
   avoid the patch.

3. The path is further shrunk by given amount of pixels (*shrinkA*
   & *shrinkB*)

4. The path is transmuted to arrow patch, which is controlled by the
   ``arrowstyle`` key value.


.. plot:: users/plotting/examples/annotate_explain.py


The creation of the connecting path between two points is controlled by
``connectionstyle`` key and the following styles are available.

   ==========   =============================================
   Name         Attrs
   ==========   =============================================
   ``angle``    angleA=90,angleB=0,rad=0.0
   ``angle3``   angleA=90,angleB=0
   ``arc``      angleA=0,angleB=0,armA=None,armB=None,rad=0.0
   ``arc3``     rad=0.0
   ``bar``      armA=0.0,armB=0.0,fraction=0.3,angle=None
   ==========   =============================================

Note that "3" in ``angle3`` and ``arc3`` is meant to indicate that the
resulting path is a quadratic spline segment (three control
points). As will be discussed below, some arrow style options can only
be used when the connecting path is a quadratic spline.

The behavior of each connection style is (limitedly) demonstrated in the
example below. (Warning : The behavior of the ``bar`` style is currently not
well defined, it may be changed in the future).

.. plot:: users/plotting/examples/connectionstyle_demo.py


The connecting path (after clipping and shrinking) is then mutated to
an arrow patch, according to the given ``arrowstyle``.

    ==========   =============================================
    Name         Attrs
    ==========   =============================================
    ``-``        None
    ``->``       head_length=0.4,head_width=0.2
    ``-[``       widthB=1.0,lengthB=0.2,angleB=None
    ``|-|``      widthA=1.0,widthB=1.0
    ``-|>``      head_length=0.4,head_width=0.2
    ``<-``       head_length=0.4,head_width=0.2
    ``<->``      head_length=0.4,head_width=0.2
    ``<|-``      head_length=0.4,head_width=0.2
    ``<|-|>``    head_length=0.4,head_width=0.2
    ``fancy``    head_length=0.4,head_width=0.4,tail_width=0.4
    ``simple``   head_length=0.5,head_width=0.5,tail_width=0.2
    ``wedge``    tail_width=0.3,shrink_factor=0.5
    ==========   =============================================

.. plot:: mpl_examples/pylab_examples/fancyarrow_demo.py

Some arrowstyles only work with connection styles that generate a
quadratic-spline segment. They are ``fancy``, ``simple``, and ``wedge``.
For these arrow styles, you must use the "angle3" or "arc3" connection
style.

If the annotation string is given, the patchA is set to the bbox patch
of the text by default.

.. plot:: users/plotting/examples/annotate_simple02.py

As in the text command, a box around the text can be drawn using
the ``bbox`` argument.

.. plot:: users/plotting/examples/annotate_simple03.py

By default, the starting point is set to the center of the text
extent.  This can be adjusted with ``relpos`` key value. The values
are normalized to the extent of the text. For example, (0,0) means
lower-left corner and (1,1) means top-right.

.. plot:: users/plotting/examples/annotate_simple04.py


Placing Artist at the anchored location of the Axes
---------------------------------------------------

There are classes of artists that can be placed at an anchored location
in the Axes. A common example is the legend.  This type of artist can
be created by using the OffsetBox class. A few predefined classes are
available in ``mpl_toolkits.axes_grid.anchored_artists``. ::

    from mpl_toolkits.axes_grid.anchored_artists import AnchoredText
    at = AnchoredText("Figure 1a",
                      prop=dict(size=8), frameon=True,
                      loc=2,
                      )
    at.patch.set_boxstyle("round,pad=0.,rounding_size=0.2")
    ax.add_artist(at)


.. plot:: users/plotting/examples/anchored_box01.py


The *loc* keyword has same meaning as in the legend command.

A simple application is when the size of the artist (or collection of
artists) is known in pixel size during the time of creation. For
example, If you want to draw a circle with fixed size of 20 pixel x 20
pixel (radius = 10 pixel), you can utilize
``AnchoredDrawingArea``. The instance is created with a size of the
drawing area (in pixels), and arbitrary artists can added to the
drawing area. Note that the extents of the artists that are added to
the drawing area are not related to the placement of the drawing
area itself. Only the initial size matters. ::

    from mpl_toolkits.axes_grid.anchored_artists import AnchoredDrawingArea

    ada = AnchoredDrawingArea(20, 20, 0, 0,
                              loc=1, pad=0., frameon=False)
    p1 = Circle((10, 10), 10)
    ada.drawing_area.add_artist(p1)
    p2 = Circle((30, 10), 5, fc="r")
    ada.drawing_area.add_artist(p2)

The artists that are added to the drawing area should not have a
transform set (it will be overridden) and the dimensions of those
artists are interpreted as a pixel coordinate, i.e., the radius of the
circles in above example are 10 pixels and 5 pixels, respectively.

.. plot:: users/plotting/examples/anchored_box02.py

Sometimes, you want your artists to scale with the data coordinate (or
coordinates other than canvas pixels). You can use
``AnchoredAuxTransformBox`` class. This is similar to
``AnchoredDrawingArea`` except that the extent of the artist is
determined during the drawing time respecting the specified transform. ::

  from mpl_toolkits.axes_grid.anchored_artists import AnchoredAuxTransformBox

  box = AnchoredAuxTransformBox(ax.transData, loc=2)
  el = Ellipse((0,0), width=0.1, height=0.4, angle=30)  # in data coordinates!
  box.drawing_area.add_artist(el)

The ellipse in the above example will have width and height
corresponding to 0.1 and 0.4 in data coordinateing and will be
automatically scaled when the view limits of the axes change.

.. plot:: users/plotting/examples/anchored_box03.py

As in the legend, the bbox_to_anchor argument can be set.  Using the
HPacker and VPacker, you can have an arrangement(?) of artist as in the
legend (as a matter of fact, this is how the legend is created).

.. plot:: users/plotting/examples/anchored_box04.py

Note that unlike the legend, the ``bbox_transform`` is set
to IdentityTransform by default.

Using Complex Coordinates with Annotations
------------------------------------------

The Annotation in matplotlib supports several types of coordinates as
described in :ref:`annotations-tutorial`. For an advanced user who wants
more control, it supports a few other options.

 1. :class:`~matplotlib.transforms.Transform` instance. For example, ::

      ax.annotate("Test", xy=(0.5, 0.5), xycoords=ax.transAxes)

    is identical to ::

      ax.annotate("Test", xy=(0.5, 0.5), xycoords="axes fraction")

    With this, you can annotate a point in other axes. ::

      ax1, ax2 = subplot(121), subplot(122)
      ax2.annotate("Test", xy=(0.5, 0.5), xycoords=ax1.transData,
                   xytext=(0.5, 0.5), textcoords=ax2.transData,
                   arrowprops=dict(arrowstyle="->"))

 2. :class:`~matplotlib.artist.Artist` instance. The xy value (or
    xytext) is interpreted as a fractional coordinate of the bbox
    (return value of *get_window_extent*) of the artist. ::

      an1 = ax.annotate("Test 1", xy=(0.5, 0.5), xycoords="data",
                        va="center", ha="center",
                        bbox=dict(boxstyle="round", fc="w"))
      an2 = ax.annotate("Test 2", xy=(1, 0.5), xycoords=an1, # (1,0.5) of the an1's bbox
                        xytext=(30,0), textcoords="offset points",
                        va="center", ha="left",
                        bbox=dict(boxstyle="round", fc="w"),
                        arrowprops=dict(arrowstyle="->"))

    .. plot:: users/plotting/examples/annotate_simple_coord01.py

    Note that it is your responsibility that the extent of the
    coordinate artist (*an1* in above example) is determined before *an2*
    gets drawn. In most cases, it means that *an2* needs to be drawn
    later than *an1*.


 3. A callable object that returns an instance of either
    :class:`~matplotlib.transforms.BboxBase` or
    :class:`~matplotlib.transforms.Transform`. If a transform is
    returned, it is the same as 1 and if a bbox is returned, it is the same
    as 2.  The callable object should take a single argument of the
    renderer instance. For example, the following two commands give
    identical results ::

      an2 = ax.annotate("Test 2", xy=(1, 0.5), xycoords=an1,
                        xytext=(30,0), textcoords="offset points")
      an2 = ax.annotate("Test 2", xy=(1, 0.5), xycoords=an1.get_window_extent,
                        xytext=(30,0), textcoords="offset points")


 4. A tuple of two coordinate specifications. The first item is for the
    x-coordinate and the second is for the y-coordinate. For example, ::

      annotate("Test", xy=(0.5, 1), xycoords=("data", "axes fraction"))

    0.5 is in data coordinates, and 1 is in normalized axes coordinates.
    You may use an artist or transform as with a tuple. For example,

    .. plot:: users/plotting/examples/annotate_simple_coord02.py
       :include-source:


 5. Sometimes, you want your annotation with some "offset points", not from the
    annotated point but from some other point.
    :class:`~matplotlib.text.OffsetFrom` is a helper class for such cases.

    .. plot:: users/plotting/examples/annotate_simple_coord03.py
      :include-source:

    You may take a look at this example :ref:`pylab_examples-annotation_demo3`.

Using ConnectorPatch
--------------------

The ConnectorPatch is like an annotation without text. While the annotate
function is recommended in most situations, the ConnectorPatch is useful when
you want to connect points in different axes. ::

  from matplotlib.patches import ConnectionPatch
  xy = (0.2, 0.2)
  con = ConnectionPatch(xyA=xy, xyB=xy, coordsA="data", coordsB="data",
                        axesA=ax1, axesB=ax2)
  ax2.add_artist(con)

The above code connects point xy in the data coordinates of ``ax1`` to
point xy in the data coordinates of ``ax2``. Here is a simple example.

.. plot:: users/plotting/examples/connect_simple01.py


While the ConnectorPatch instance can be added to any axes, you may want to add
it to the axes that is latest in drawing order to prevent overlap by other
axes.


Advanced Topics
~~~~~~~~~~~~~~~

Zoom effect between Axes
------------------------

mpl_toolkits.axes_grid.inset_locator defines some patch classes useful
for interconnecting two axes. Understanding the code requires some
knowledge of how mpl's transform works. But, utilizing it will be
straight forward.


.. plot:: mpl_examples/pylab_examples/axes_zoom_effect.py


Define Custom BoxStyle
----------------------

You can use a custom box style. The value for the ``boxstyle`` can be a
callable object in the following forms.::

        def __call__(self, x0, y0, width, height, mutation_size,
                     aspect_ratio=1.):
            """
            Given the location and size of the box, return the path of
            the box around it.

              - *x0*, *y0*, *width*, *height* : location and size of the box
              - *mutation_size* : a reference scale for the mutation.
              - *aspect_ratio* : aspect-ratio for the mutation.
            """
            path = ...
            return path

Here is a complete example.

.. plot:: users/plotting/examples/custom_boxstyle01.py

However, it is recommended that you derive from the
matplotlib.patches.BoxStyle._Base as demonstrated below.

.. plot:: users/plotting/examples/custom_boxstyle02.py
   :include-source:


Similarly, you can define a custom ConnectionStyle and a custom ArrowStyle.
See the source code of ``lib/matplotlib/patches.py`` and check
how each style class is defined.