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Feature stack base #1671

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Merged
merged 9 commits into from
Jan 27, 2013
Merged

Feature stack base #1671

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24f537f
[ENH] added baseline feature to stacked graph.
Tillsten Jan 10, 2013
b21b348
pep8 compliance
Tillsten Jan 10, 2013
6f7a769
Fix typos
dmcdougall Jan 16, 2013
6975bcb
Add stackplot baseline demo
dmcdougall Jan 16, 2013
ff8cce4
Update changelog and whats_new
dmcdougall Jan 16, 2013
6dc5887
Add stackplot baseline test
dmcdougall Jan 16, 2013
f318d39
Remove text from regression test output
dmcdougall Jan 17, 2013
339ca4e
Vectorise the loops
dmcdougall Jan 17, 2013
6b4678b
Add docstring to example funtion
dmcdougall Jan 22, 2013
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2 changes: 2 additions & 0 deletions 2 CHANGELOG
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Original file line number Diff line number Diff line change
@@ -1,5 +1,7 @@
2013-01-07 Add framealpha keyword argument to legend - PO

2013-01-16 Till Stensitzki added a baseline feature to stackplot

2012-12-22 Added classes for interpolation within triangular grids
(LinearTriInterpolator) and to find the triangles in which points
lie (TrapezoidMapTriFinder) to matplotlib.tri module. - IMT
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7 changes: 7 additions & 0 deletions 7 doc/users/whats_new.rst
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Expand Up @@ -22,6 +22,13 @@ revision, see the :ref:`github-stats`.
new in matplotlib-1.3
=====================

Baselines for stackplot
-----------------------
Till Stensitzki added non-zero baselines to :func:`~matplotlib.pyplot.stackplot`.
They may be symmetric or weighted.

.. plot:: mpl_examples/pylab_examples/stackplot_demo2.py

Initialize a rotated rectangle
------------------------------
Damon McDougall extended the :class:`~matplotlib.patches.Rectangle` constructor
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26 changes: 26 additions & 0 deletions 26 examples/pylab_examples/stackplot_demo2.py
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@@ -0,0 +1,26 @@
import numpy as np
import matplotlib.pyplot as plt

np.random.seed(0)
def layers(n, m):
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I know its only an example, but a docstring would be nice here - something which focuses on the purpose of the function, rather than its args/kwargs.

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Actually, this is not uncommon to do in the examples. IIRC, the sphinx
doc-builder will take the docstring portion of the example, and render it
as ReST text above the source code portion. If one feels like having a
docstring there, feel free. The more the better.

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Sure thing :)

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Explanation of the code:
This is just a direct copy of the original code. All it does is calculating random Gaussians.

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Done in bd204e1.

"""
Return *n* random Gaussian mixtures, each of length *m*.
"""
def bump(a):
x = 1 / (.1 + np.random.random())
y = 2 * np.random.random() - .5
z = 10 / (.1 + np.random.random())
for i in range(m):
w = (i / float(m) - y) * z
a[i] += x * np.exp(-w * w)
a = np.zeros((m, n))
for i in range(n):
for j in range(5):
bump(a[:, i])
return a

d = layers(3, 100)

plt.subplots()
plt.stackplot(range(100), d.T, baseline='wiggle')
plt.show()
54 changes: 49 additions & 5 deletions 54 lib/matplotlib/stackplot.py
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Expand Up @@ -25,6 +25,16 @@ def stackplot(axes, x, *args, **kwargs):

Keyword arguments:

*baseline* : ['zero', 'sym', 'wiggle', 'weighted_wiggle']
Method used to calculate the baseline. 'zero' is just a
simple stacked plot. 'sym' is symmetric around zero and
is sometimes called `ThemeRiver`. 'wiggle' minimizes the
sum of the squared slopes. 'weighted_wiggle' does the
same but weights to account for size of each layer.
It is also called `Streamgraph`-layout. More details
can be found at http://www.leebyron.com/else/streamgraph/.


*colors* : A list or tuple of colors. These will be cycled through and
used to colour the stacked areas.
All other keyword arguments are passed to
Expand All @@ -44,17 +54,51 @@ def stackplot(axes, x, *args, **kwargs):
if colors is not None:
axes.set_color_cycle(colors)

baseline = kwargs.pop('baseline', 'zero')
# Assume data passed has not been 'stacked', so stack it here.
y_stack = np.cumsum(y, axis=0)
stack = np.cumsum(y, axis=0)

r = []
if baseline == 'zero':
first_line = 0.

elif baseline == 'sym':
first_line = -np.sum(y, 0) * 0.5
stack += first_line[None, :]

elif baseline == 'wiggle':
m = y.shape[0]
first_line = (y * (m - 0.5 - np.arange(0, m)[:, None])).sum(0)
first_line /= -m
stack += first_line

elif baseline == 'weighted_wiggle':
m, n = y.shape
center = np.zeros(n)
total = np.sum(y, 0)
increase = np.hstack((y[:, 0:1], np.diff(y)))
below_size = total - stack
below_size += 0.5 * y
move_up = below_size / total
move_up[:, 0] = 0.5
center = (move_up - 0.5) * increase
center = np.cumsum(center.sum(0))
first_line = center - 0.5 * total
stack += first_line
else:
errstr = "Baseline method %s not recognised. " % baseline
errstr += "Expected 'zero', 'sym', 'wiggle' or 'weighted_wiggle'"
raise ValueError(errstr)

# Color between x = 0 and the first array.
r.append(axes.fill_between(x, 0, y_stack[0, :],
facecolor=axes._get_lines.color_cycle.next(), **kwargs))
r.append(axes.fill_between(x, first_line, stack[0, :],
facecolor=axes._get_lines.color_cycle.next(),
**kwargs))

# Color between array i-1 and array i
for i in xrange(len(y) - 1):
r.append(axes.fill_between(x, y_stack[i, :], y_stack[i + 1, :],
facecolor=axes._get_lines.color_cycle.next(), **kwargs))
color = axes._get_lines.color_cycle.next()
r.append(axes.fill_between(x, stack[i, :], stack[i + 1, :],
facecolor= color,
**kwargs))
return r
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