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"""

Stacked area plot for 1D arrays inspired by Douglas Y'barbo's stackoverflow

answer:

https://stackoverflow.com/q/2225995/

(https://stackoverflow.com/users/66549/doug)

"""

import numpy as np

from matplotlib import _api

__all__ = ['stackplot']

def stackplot(axes, x, *args,

labels=(), colors=None, baseline='zero',

**kwargs):

"""

Draw a stacked area plot.

Parameters

----------

x : (N,) array-like

y : (M, N) array-like

The data is assumed to be unstacked. Each of the following

calls is legal::

stackplot(x, y) # where y has shape (M, N)

stackplot(x, y1, y2, y3) # where y1, y2, y3, y4 have length N

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 : list of str, optional

A sequence of labels to assign to each data series. If unspecified,

then no labels will be applied to artists.

colors : list of color, optional

A sequence of colors to be cycled through and used to color the stacked

areas. The sequence need not be exactly the same length as the number

of provided *y*, in which case the colors will repeat from the

beginning.

If not specified, the colors from the Axes property cycle will be used.

data : indexable object, optional

DATA_PARAMETER_PLACEHOLDER

**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))

_api.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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