Example usages of charticle.

.. plot::
   :context: reset

   >>> import matplotlib
   >>> matplotlib.use('Agg')

:py:mod:`charticle.venn` examples
==================================
The :py:mod:`charticle.venn` package contains classes for Venn diagrams.


:py:class:`~charticle.venn.Venn2`
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Two-circle Venn diagrams are supported (at v0.0.2+).

.. plot::
  :context: reset
  :include-source: true

  >>> from matplotlib import pyplot as plt
  >>> from charticle.venn import Venn2
  >>> v2 = Venn2(a="chart", b="article")
  >>> v2.ab = "charticle"
  >>> _ = v2.plot()

but beware:

.. plot::
  :include-source: true
  :context: reset

  >>> from charticle.venn import Venn2
  >>> v = Venn2(title="It might be like this", a="useful", b="charticle",
  ...   sizes=Venn2.Sizes(ab=0.0))
  >>> _ = v.plot()

And you can apply these to subplots, too:

.. plot::
  :include-source: true
  :context: reset

  >>> import matplotlib.pyplot as plt
  >>> from charticle.venn import Venn2
  >>> fig = plt.figure()
  >>> fig.set_size_inches(4, 6)
  >>> v = Venn2(a="chart", b="article", ab="charticle")
  >>> ax1, ax2 = (fig.add_subplot(211), fig.add_subplot(212))
  >>> _ = v.plot(ax1)
  >>> v.title = "but really it's"
  >>> v.sizes.a *= 10
  >>> v.sizes.b *= 10
  >>> v.sizes.ab *= 0.5
  >>> _ = v.plot(ax2)

because the intersection of charts and articles is really quite tiny.


:py:class:`~charticle.venn.Venn3`
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Three-circle Venn diagrams are supported, *pace* Drew Conway's
data science (last in this section).

.. plot::
   :context: reset
   :include-source: true

   >>> from charticle.venn import Venn3
   >>> v3 = Venn3(a_name="useful", b_name = "structured", c_name="delimited")
   >>> v3.abc = "discipline"
   >>> v3.title = "Knowledge"
   >>> v3.fontsizes.title = 22
   >>> v3  #doctest: +ELLIPSIS
   Venn3(a_name='useful', b_name='structured', c_name='delimited', ...))
   >>> _ = v3.plot()


Further can set region sizes:

.. plot::
   :context: close-figs
   :include-source: true

   >>> v3.sizes
   Venn3.Sizes(a=1.0, b=1.0, c=1.0, ab=1.0, ac=1.0, bc=1.0, abc=1.0, normalize=1.0)
   >>> v3.sizes.set_single_weight(1.0) # moot
   Venn3.Sizes(a=1.0, b=1.0, c=1.0, ab=1.0, ac=1.0, bc=1.0, abc=1.0, normalize=1.0)
   >>> v3.sizes.a *= 5
   >>> v3.sizes.set_double_weight(2.0)
   Venn3.Sizes(a=5.0, b=1.0, c=1.0, ab=2.0, ac=2.0, bc=2.0, abc=1.0, normalize=1.0)
   >>> _ = v3.plot()


If regions are given a zero size, the diagram will reorganize:

.. plot::
   :include-source: true
   :context: reset

   >>> from charticle.venn import Venn3
   >>> v = Venn3(a_name='"apples"', b_name='"bananas"',  c_name="fruits")
   >>> v.a = "MacBook"
   >>> v.b = 'harebrained'
   >>> v.c = "Prunus\ndomestica,\nothers"; v.sizes.c = 3
   >>> v.ac = "Malus\ndomestica"
   >>> v.bc = "Musa\nacuminata"
   >>> v.sizes.ab = 0; v.sizes.abc = 0
   >>> _ = v.plot()

And you can still do multiple plots by passing an axis object to plot.

.. plot::
  :include-source: true
  :context: reset

  >>> import matplotlib.pyplot as plt
  >>> from charticle.venn import Venn3, FontSizes
  >>> fig = plt.figure()
  >>> fig.set_size_inches(6,13)
  >>> v = Venn3(a="mathematics", b="substantive\nexpertise",
  ...  c="hacking\nskills",
  ...  fontsizes=FontSizes(intersections=10),
  ...  sizes=Venn3.Sizes(normalize=30))
  >>> ax1, ax2, ax3, ax4 = (fig.add_subplot(411), fig.add_subplot(412),
  ...   fig.add_subplot(413), fig.add_subplot(414))
  >>> v.ab = "traditional\nresearch"; _ = v.plot(ax1)
  >>> v.ac = "machine\nlearning"; _ = v.plot(ax2)
  >>> v.bc = "danger\nzone!"; _ = v.plot(ax3)
  >>> v.abc = "data\nscience"; _ = v.plot(ax4)

:py:mod:`charticle.hierarchy` examples
======================================
The :py:mod:`charticle.hierarchy` package contains classes for pyramid
diagrams, like Maslow's hierarchy.

:py:class:`~charticle.hierarchy.Hierarchy`
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. plot::
  :context: reset
  :include-source: true

  >>> from matplotlib import pyplot as plt
  >>> from charticle.hierarchy import Hierarchy
  >>> h = Hierarchy(layer_text_defaults=dict(size='large'))
  >>> _ = h.set_layers(['Physiological', 'Safety', 'Love/belonging',
  ...		        'Esteem','Self-\nactualization'])
  >>> h.plot()
  >>> _ = plt.axis('scaled'); _ = plt.axis('off')

You may of course set the colors as a whole or override them one at a time.

.. plot::
  :context: reset
  :include-source: true

  >>> from matplotlib import pyplot as plt
  >>> from charticle.hierarchy import Hierarchy
  >>> h = Hierarchy(layer_text_defaults=dict(size='x-large'))
  >>> h.set_color_cycle('brown', 'white', 'pink')
  >>> l1 = h.add_layer(lower=0.0, upper=0.3, label='bottom')
  >>> l2 = h.add_layer(lower=0.3, upper=0.6, label='middle',
  ...                  text={'weight': 'bold'})
  >>> l3 = h.add_layer(lower=0.6, upper=1.0, label='top',
  ...                  polygon={'fill': True, 'color': 'green'})
  >>> h.plot()

There are ways to set defaults for all the layer polygon forms:

.. plot::
  :context:
  :include-source: true

  >>> h.layer_polygon_defaults["fill"] = False
  >>> h.layer_text_defaults["style"] = 'italic'
  >>> h.plot()

And it works just fine with an axis passed in:

.. plot::
  :context:
  :include-source: true

  >>> ax = plt.gca()
  >>> h.plot(ax=ax)



Future modules
==============

Plans for `charticle.xy` as well?