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