forked from 170010011/fr
118 lines
3.8 KiB
Python
118 lines
3.8 KiB
Python
"""
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Stacked area plot for 1D arrays inspired by Douglas Y'barbo's stackoverflow
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answer:
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http://stackoverflow.com/questions/2225995/how-can-i-create-stacked-line-graph-with-matplotlib
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(http://stackoverflow.com/users/66549/doug)
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"""
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import numpy as np
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import matplotlib.cbook as cbook
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__all__ = ['stackplot']
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def stackplot(axes, x, *args,
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labels=(), colors=None, baseline='zero',
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**kwargs):
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"""
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Draw a stacked area plot.
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Parameters
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----------
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x : 1d array of dimension N
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y : 2d array (dimension MxN), or sequence of 1d arrays (each dimension 1xN)
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The data is assumed to be unstacked. Each of the following
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calls is legal::
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stackplot(x, y) # where y is MxN
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stackplot(x, y1, y2, y3, y4) # where y1, y2, y3, y4, are all 1xNm
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baseline : {'zero', 'sym', 'wiggle', 'weighted_wiggle'}
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Method used to calculate the baseline:
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- ``'zero'``: Constant zero baseline, i.e. a simple stacked plot.
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- ``'sym'``: Symmetric around zero and is sometimes called
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'ThemeRiver'.
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- ``'wiggle'``: Minimizes the sum of the squared slopes.
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- ``'weighted_wiggle'``: Does the same but weights to account for
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size of each layer. It is also called 'Streamgraph'-layout. More
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details can be found at http://leebyron.com/streamgraph/.
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labels : Length N sequence of strings
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Labels to assign to each data series.
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colors : Length N sequence of colors
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A list or tuple of colors. These will be cycled through and used to
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colour the stacked areas.
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**kwargs
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All other keyword arguments are passed to `.Axes.fill_between`.
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Returns
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-------
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list of `.PolyCollection`
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A list of `.PolyCollection` instances, one for each element in the
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stacked area plot.
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"""
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y = np.row_stack(args)
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labels = iter(labels)
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if colors is not None:
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axes.set_prop_cycle(color=colors)
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# Assume data passed has not been 'stacked', so stack it here.
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# We'll need a float buffer for the upcoming calculations.
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stack = np.cumsum(y, axis=0, dtype=np.promote_types(y.dtype, np.float32))
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cbook._check_in_list(['zero', 'sym', 'wiggle', 'weighted_wiggle'],
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baseline=baseline)
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if baseline == 'zero':
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first_line = 0.
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elif baseline == 'sym':
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first_line = -np.sum(y, 0) * 0.5
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stack += first_line[None, :]
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elif baseline == 'wiggle':
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m = y.shape[0]
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first_line = (y * (m - 0.5 - np.arange(m)[:, None])).sum(0)
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first_line /= -m
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stack += first_line
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elif baseline == 'weighted_wiggle':
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total = np.sum(y, 0)
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# multiply by 1/total (or zero) to avoid infinities in the division:
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inv_total = np.zeros_like(total)
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mask = total > 0
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inv_total[mask] = 1.0 / total[mask]
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increase = np.hstack((y[:, 0:1], np.diff(y)))
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below_size = total - stack
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below_size += 0.5 * y
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move_up = below_size * inv_total
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move_up[:, 0] = 0.5
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center = (move_up - 0.5) * increase
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center = np.cumsum(center.sum(0))
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first_line = center - 0.5 * total
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stack += first_line
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# Color between x = 0 and the first array.
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color = axes._get_lines.get_next_color()
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coll = axes.fill_between(x, first_line, stack[0, :],
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facecolor=color, label=next(labels, None),
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**kwargs)
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coll.sticky_edges.y[:] = [0]
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r = [coll]
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# Color between array i-1 and array i
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for i in range(len(y) - 1):
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color = axes._get_lines.get_next_color()
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r.append(axes.fill_between(x, stack[i, :], stack[i + 1, :],
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facecolor=color, label=next(labels, None),
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**kwargs))
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return r
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