Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/matplotlib/stackplot.py

@@ -0,0 +1,117 @@
+"""
+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