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# Source code for matplotlib.sankey

```"""
Module for creating Sankey diagrams using matplotlib
"""

import logging
from types import SimpleNamespace

import numpy as np

from matplotlib.cbook import iterable
from matplotlib.path import Path
from matplotlib.patches import PathPatch
from matplotlib.transforms import Affine2D
from matplotlib import docstring
from matplotlib import rcParams

_log = logging.getLogger(__name__)

__author__ = "Kevin L. Davies"
__credits__ = ["Yannick Copin"]
__version__ = "2011/09/16"

# Angles [deg/90]
RIGHT = 0
UP = 1
# LEFT = 2
DOWN = 3

[docs]class Sankey(object):
"""
Sankey diagram in matplotlib

Sankey diagrams are a specific type of flow diagram, in which
the width of the arrows is shown proportionally to the flow
quantity.  They are typically used to visualize energy or
material or cost transfers between processes.
`Wikipedia (6/1/2011) <https://en.wikipedia.org/wiki/Sankey_diagram>`_

"""

def __init__(self, ax=None, scale=1.0, unit='', format='%G', gap=0.25,
margin=0.4, tolerance=1e-6, **kwargs):
"""
Create a new Sankey instance.

Optional keyword arguments:

===============   ===================================================
Field             Description
===============   ===================================================
*ax*              axes onto which the data should be plotted
If *ax* isn't provided, new axes will be created.
*scale*           scaling factor for the flows
*scale* sizes the width of the paths in order to
maintain proper layout.  The same scale is applied
to all subdiagrams.  The value should be chosen
such that the product of the scale and the sum of
the inputs is approximately 1.0 (and the product of
the scale and the sum of the outputs is
approximately -1.0).
*unit*            string representing the physical unit associated
with the flow quantities
If *unit* is None, then none of the quantities are
labeled.
*format*          a Python number formatting string to be used in
labeling the flow as a quantity (i.e., a number
times a unit, where the unit is given)
*gap*             space between paths that break in/break away
to/from the top or bottom
*radius*          inner radius of the vertical paths
*shoulder*        size of the shoulders of output arrowS
*offset*          text offset (from the dip or tip of the arrow)
*head_angle*      angle of the arrow heads (and negative of the angle
of the tails) [deg]
*margin*          minimum space between Sankey outlines and the edge
of the plot area
*tolerance*       acceptable maximum of the magnitude of the sum of
flows
The magnitude of the sum of connected flows cannot
be greater than *tolerance*.
===============   ===================================================

The optional arguments listed above are applied to all subdiagrams so
that there is consistent alignment and formatting.

If :class:`Sankey` is instantiated with any keyword arguments other
than those explicitly listed above (``**kwargs``), they will be passed
to :meth:`add`, which will create the first subdiagram.

In order to draw a complex Sankey diagram, create an instance of
:class:`Sankey` by calling it without any kwargs::

sankey = Sankey()

Then add simple Sankey sub-diagrams::

#...

Finally, create the full diagram::

sankey.finish()

Or, instead, simply daisy-chain those calls::

.. seealso::

:meth:`finish`

**Examples:**

.. plot:: gallery/specialty_plots/sankey_basics.py
"""
# Check the arguments.
if gap < 0:
raise ValueError(
"The gap is negative.\nThis isn't allowed because it "
"would cause the paths to overlap.")
if radius > gap:
raise ValueError(
"The inner radius is greater than the path spacing.\n"
"This isn't allowed because it would cause the paths to overlap.")
if head_angle < 0:
raise ValueError(
"The angle is negative.\nThis isn't allowed "
"because it would cause inputs to look like "
"outputs and vice versa.")
if tolerance < 0:
raise ValueError(
"The tolerance is negative.\nIt must be a magnitude.")

# Create axes if necessary.
if ax is None:
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, xticks=[], yticks=[])

self.diagrams = []

# Store the inputs.
self.ax = ax
self.unit = unit
self.format = format
self.scale = scale
self.gap = gap
self.shoulder = shoulder
self.offset = offset
self.margin = margin
self.pitch = np.tan(np.pi * (1 - head_angle / 180.0) / 2.0)
self.tolerance = tolerance

# Initialize the vertices of tight box around the diagram(s).
self.extent = np.array((np.inf, -np.inf, np.inf, -np.inf))

# If there are any kwargs, create the first subdiagram.
if len(kwargs):

def _arc(self, quadrant=0, cw=True, radius=1, center=(0, 0)):
"""
Return the codes and vertices for a rotated, scaled, and translated
90 degree arc.

Optional keyword arguments:

===============   ==========================================
Keyword           Description
===============   ==========================================
*quadrant*        uses 0-based indexing (0, 1, 2, or 3)
*cw*              if True, clockwise
*center*          (x, y) tuple of the arc's center
===============   ==========================================
"""
# Note:  It would be possible to use matplotlib's transforms to rotate,
# scale, and translate the arc, but since the angles are discrete,
# it's just as easy and maybe more efficient to do it here.
ARC_CODES = [Path.LINETO,
Path.CURVE4,
Path.CURVE4,
Path.CURVE4,
Path.CURVE4,
Path.CURVE4,
Path.CURVE4]
# Vertices of a cubic Bezier curve approximating a 90 deg arc
# These can be determined by Path.arc(0,90).
ARC_VERTICES = np.array([[1.00000000e+00, 0.00000000e+00],
[1.00000000e+00, 2.65114773e-01],
[8.94571235e-01, 5.19642327e-01],
[7.07106781e-01, 7.07106781e-01],
[5.19642327e-01, 8.94571235e-01],
[2.65114773e-01, 1.00000000e+00],
# Insignificant
# [6.12303177e-17, 1.00000000e+00]])
[0.00000000e+00, 1.00000000e+00]])
if quadrant == 0 or quadrant == 2:
if cw:
vertices = ARC_VERTICES
else:
vertices = ARC_VERTICES[:, ::-1]  # Swap x and y.
elif quadrant == 1 or quadrant == 3:
# Negate x.
if cw:
# Swap x and y.
vertices = np.column_stack((-ARC_VERTICES[:, 1],
ARC_VERTICES[:, 0]))
else:
vertices = np.column_stack((-ARC_VERTICES[:, 0],
ARC_VERTICES[:, 1]))
if quadrant > 1:
radius = -radius  # Rotate 180 deg.
return list(zip(ARC_CODES, radius * vertices +
np.tile(center, (ARC_VERTICES.shape[0], 1))))

def _add_input(self, path, angle, flow, length):
"""
Add an input to a path and return its tip and label locations.
"""
if angle is None:
return [0, 0], [0, 0]
else:
x, y = path[-1][1]  # Use the last point as a reference.
dipdepth = (flow / 2) * self.pitch
if angle == RIGHT:
x -= length
dip = [x + dipdepth, y + flow / 2.0]
path.extend([(Path.LINETO, [x, y]),
(Path.LINETO, dip),
(Path.LINETO, [x, y + flow]),
(Path.LINETO, [x + self.gap, y + flow])])
label_location = [dip[0] - self.offset, dip[1]]
else:  # Vertical
x -= self.gap
if angle == UP:
sign = 1
else:
sign = -1

dip = [x - flow / 2, y - sign * (length - dipdepth)]
if angle == DOWN:
else:

# Inner arc isn't needed if inner radius is zero
cw=angle == UP,
y - sign * self.radius)))
else:
path.append((Path.LINETO, [x, y]))
path.extend([(Path.LINETO, [x, y - sign * length]),
(Path.LINETO, dip),
(Path.LINETO, [x - flow, y - sign * length])])
cw=angle == DOWN,
y - sign * self.radius)))
path.append((Path.LINETO, [x - flow, y + sign * flow]))
label_location = [dip[0], dip[1] - sign * self.offset]

return dip, label_location

def _add_output(self, path, angle, flow, length):
"""
Append an output to a path and return its tip and label locations.

.. note:: *flow* is negative for an output.
"""
if angle is None:
return [0, 0], [0, 0]
else:
x, y = path[-1][1]  # Use the last point as a reference.
tipheight = (self.shoulder - flow / 2) * self.pitch
if angle == RIGHT:
x += length
tip = [x + tipheight, y + flow / 2.0]
path.extend([(Path.LINETO, [x, y]),
(Path.LINETO, [x, y + self.shoulder]),
(Path.LINETO, tip),
(Path.LINETO, [x, y - self.shoulder + flow]),
(Path.LINETO, [x, y + flow]),
(Path.LINETO, [x - self.gap, y + flow])])
label_location = [tip[0] + self.offset, tip[1]]
else:  # Vertical
x += self.gap
if angle == UP:
sign = 1
else:
sign = -1

tip = [x - flow / 2.0, y + sign * (length + tipheight)]
if angle == UP:
else:
# Inner arc isn't needed if inner radius is zero
cw=angle == UP,
y + sign * self.radius)))
else:
path.append((Path.LINETO, [x, y]))
path.extend([(Path.LINETO, [x, y + sign * length]),
(Path.LINETO, [x - self.shoulder,
y + sign * length]),
(Path.LINETO, tip),
(Path.LINETO, [x + self.shoulder - flow,
y + sign * length]),
(Path.LINETO, [x - flow, y + sign * length])])
cw=angle == DOWN,
y + sign * self.radius)))
path.append((Path.LINETO, [x - flow, y + sign * flow]))
label_location = [tip[0], tip[1] + sign * self.offset]
return tip, label_location

def _revert(self, path, first_action=Path.LINETO):
"""
A path is not simply revertable by path[::-1] since the code
specifies an action to take from the **previous** point.
"""
reverse_path = []
next_code = first_action
for code, position in path[::-1]:
reverse_path.append((next_code, position))
next_code = code
return reverse_path
# This might be more efficient, but it fails because 'tuple' object
# doesn't support item assignment:
# path[1] = path[1][-1:0:-1]
# path[1][0] = first_action
# path[2] = path[2][::-1]
# return path

[docs]    @docstring.dedent_interpd
def add(self, patchlabel='', flows=None, orientations=None, labels='',
trunklength=1.0, pathlengths=0.25, prior=None, connect=(0, 0),
rotation=0, **kwargs):
"""
Add a simple Sankey diagram with flows at the same hierarchical level.

Return value is the instance of :class:`Sankey`.

Optional keyword arguments:

===============   ===================================================
Keyword           Description
===============   ===================================================
*patchlabel*      label to be placed at the center of the diagram
Note: *label* (not *patchlabel*) will be passed to
the patch through ``**kwargs`` and can be used to
create an entry in the legend.
*flows*           array of flow values
By convention, inputs are positive and outputs are
negative.
*orientations*    list of orientations of the paths
Valid values are 1 (from/to the top), 0 (from/to
the left or right), or -1 (from/to the bottom).  If
*orientations* == 0, inputs will break in from the
left and outputs will break away to the right.
*labels*          list of specifications of the labels for the flows
Each value may be *None* (no labels), '' (just
label the quantities), or a labeling string.  If a
single value is provided, it will be applied to all
flows.  If an entry is a non-empty string, then the
quantity for the corresponding flow will be shown
below the string.  However, if the *unit* of the
main diagram is None, then quantities are never
shown, regardless of the value of this argument.
*trunklength*     length between the bases of the input and output
groups
*pathlengths*     list of lengths of the arrows before break-in or
after break-away
If a single value is given, then it will be applied
to the first (inside) paths on the top and bottom,
and the length of all other arrows will be
justified accordingly.  The *pathlengths* are not
applied to the horizontal inputs and outputs.
*prior*           index of the prior diagram to which this diagram
should be connected
*connect*         a (prior, this) tuple indexing the flow of the
prior diagram and the flow of this diagram which
should be connected
If this is the first diagram or *prior* is *None*,
*connect* will be ignored.
*rotation*        angle of rotation of the diagram [deg]
*rotation* is ignored if this diagram is connected
to an existing one (using *prior* and *connect*).
The interpretation of the *orientations* argument
will be rotated accordingly (e.g., if *rotation*
== 90, an *orientations* entry of 1 means to/from
the left).
===============   ===================================================

Valid kwargs are :meth:`matplotlib.patches.PathPatch` arguments:

%(Patch)s

As examples, ``fill=False`` and ``label='A legend entry'``.
By default, ``facecolor='#bfd1d4'`` (light blue) and
``linewidth=0.5``.

The indexing parameters (*prior* and *connect*) are zero-based.

The flows are placed along the top of the diagram from the inside out
in order of their index within the *flows* list or array.  They are
placed along the sides of the diagram from the top down and along the
bottom from the outside in.

If the sum of the inputs and outputs is nonzero, the discrepancy
will appear as a cubic Bezier curve along the top and bottom edges of
the trunk.

.. seealso::

:meth:`finish`
"""
# Check and preprocess the arguments.
if flows is None:
flows = np.array([1.0, -1.0])
else:
flows = np.array(flows)
n = flows.shape[0]  # Number of flows
if rotation is None:
rotation = 0
else:
# In the code below, angles are expressed in deg/90.
rotation /= 90.0
if orientations is None:
orientations = [0, 0]
if len(orientations) != n:
raise ValueError(
"orientations and flows must have the same length.\n"
"orientations has length %d, but flows has length %d."
% (len(orientations), n))
if labels != '' and getattr(labels, '__iter__', False):
# iterable() isn't used because it would give True if labels is a
# string
if len(labels) != n:
raise ValueError(
"If labels is a list, then labels and flows must have the "
"same length.\nlabels has length %d, but flows has length %d."
% (len(labels), n))
else:
labels = [labels] * n
if trunklength < 0:
raise ValueError(
"trunklength is negative.\nThis isn't allowed, because it would "
"cause poor layout.")
if np.abs(np.sum(flows)) > self.tolerance:
_log.info("The sum of the flows is nonzero (%f).\nIs the "
"system not at steady state?", np.sum(flows))
scaled_flows = self.scale * flows
gain = sum(max(flow, 0) for flow in scaled_flows)
loss = sum(min(flow, 0) for flow in scaled_flows)
if not (0.5 <= gain <= 2.0):
_log.info(
"The scaled sum of the inputs is %f.\nThis may "
"cause poor layout.\nConsider changing the scale so"
" that the scaled sum is approximately 1.0.", gain)
if not (-2.0 <= loss <= -0.5):
_log.info(
"The scaled sum of the outputs is %f.\nThis may "
"cause poor layout.\nConsider changing the scale so"
" that the scaled sum is approximately 1.0.", gain)
if prior is not None:
if prior < 0:
raise ValueError("The index of the prior diagram is negative.")
if min(connect) < 0:
raise ValueError(
"At least one of the connection indices is negative.")
if prior >= len(self.diagrams):
raise ValueError(
"The index of the prior diagram is %d, but there are "
"only %d other diagrams.\nThe index is zero-based."
% (prior, len(self.diagrams)))
if connect[0] >= len(self.diagrams[prior].flows):
raise ValueError(
"The connection index to the source diagram is %d, but "
"that diagram has only %d flows.\nThe index is zero-based."
% (connect[0], len(self.diagrams[prior].flows)))
if connect[1] >= n:
raise ValueError(
"The connection index to this diagram is %d, but this diagram"
"has only %d flows.\n The index is zero-based."
% (connect[1], n))
if self.diagrams[prior].angles[connect[0]] is None:
raise ValueError(
"The connection cannot be made.  Check that the magnitude "
"of flow %d of diagram %d is greater than or equal to the "
"specified tolerance." % (connect[0], prior))
flow_error = (self.diagrams[prior].flows[connect[0]] +
flows[connect[1]])
if abs(flow_error) >= self.tolerance:
raise ValueError(
"The scaled sum of the connected flows is %f, which is not "
"within the tolerance (%f)." % (flow_error, self.tolerance))

# Determine if the flows are inputs.
are_inputs = [None] * n
for i, flow in enumerate(flows):
if flow >= self.tolerance:
are_inputs[i] = True
elif flow <= -self.tolerance:
are_inputs[i] = False
else:
_log.info(
"The magnitude of flow %d (%f) is below the "
"tolerance (%f).\nIt will not be shown, and it "
"cannot be used in a connection."
% (i, flow, self.tolerance))

# Determine the angles of the arrows (before rotation).
angles = [None] * n
for i, (orient, is_input) in enumerate(zip(orientations, are_inputs)):
if orient == 1:
if is_input:
angles[i] = DOWN
elif not is_input:
# Be specific since is_input can be None.
angles[i] = UP
elif orient == 0:
if is_input is not None:
angles[i] = RIGHT
else:
if orient != -1:
raise ValueError(
"The value of orientations[%d] is %d, "
"but it must be [ -1 | 0 | 1 ]." % (i, orient))
if is_input:
angles[i] = UP
elif not is_input:
angles[i] = DOWN

# Justify the lengths of the paths.
if iterable(pathlengths):
if len(pathlengths) != n:
raise ValueError(
"If pathlengths is a list, then pathlengths and flows must "
"have the same length.\npathlengths has length %d, but flows "
"has length %d." % (len(pathlengths), n))
else:  # Make pathlengths into a list.
urlength = pathlengths
ullength = pathlengths
lrlength = pathlengths
lllength = pathlengths
d = dict(RIGHT=pathlengths)
pathlengths = [d.get(angle, 0) for angle in angles]
# Determine the lengths of the top-side arrows
# from the middle outwards.
for i, (angle, is_input, flow) in enumerate(zip(angles, are_inputs,
scaled_flows)):
if angle == DOWN and is_input:
pathlengths[i] = ullength
ullength += flow
elif angle == UP and not is_input:
pathlengths[i] = urlength
urlength -= flow  # Flow is negative for outputs.
# Determine the lengths of the bottom-side arrows
# from the middle outwards.
for i, (angle, is_input, flow) in enumerate(reversed(list(zip(
angles, are_inputs, scaled_flows)))):
if angle == UP and is_input:
pathlengths[n - i - 1] = lllength
lllength += flow
elif angle == DOWN and not is_input:
pathlengths[n - i - 1] = lrlength
lrlength -= flow
# Determine the lengths of the left-side arrows
# from the bottom upwards.
has_left_input = False
for i, (angle, is_input, spec) in enumerate(reversed(list(zip(
angles, are_inputs, zip(scaled_flows, pathlengths))))):
if angle == RIGHT:
if is_input:
if has_left_input:
pathlengths[n - i - 1] = 0
else:
has_left_input = True
# Determine the lengths of the right-side arrows
# from the top downwards.
has_right_output = False
for i, (angle, is_input, spec) in enumerate(zip(
angles, are_inputs, list(zip(scaled_flows, pathlengths)))):
if angle == RIGHT:
if not is_input:
if has_right_output:
pathlengths[i] = 0
else:
has_right_output = True

# Begin the subpaths, and smooth the transition if the sum of the flows
# is nonzero.
urpath = [(Path.MOVETO, [(self.gap - trunklength / 2.0),  # Upper right
gain / 2.0]),
(Path.LINETO, [(self.gap - trunklength / 2.0) / 2.0,
gain / 2.0]),
(Path.CURVE4, [(self.gap - trunklength / 2.0) / 8.0,
gain / 2.0]),
(Path.CURVE4, [(trunklength / 2.0 - self.gap) / 8.0,
-loss / 2.0]),
(Path.LINETO, [(trunklength / 2.0 - self.gap) / 2.0,
-loss / 2.0]),
(Path.LINETO, [(trunklength / 2.0 - self.gap),
-loss / 2.0])]
llpath = [(Path.LINETO, [(trunklength / 2.0 - self.gap),  # Lower left
loss / 2.0]),
(Path.LINETO, [(trunklength / 2.0 - self.gap) / 2.0,
loss / 2.0]),
(Path.CURVE4, [(trunklength / 2.0 - self.gap) / 8.0,
loss / 2.0]),
(Path.CURVE4, [(self.gap - trunklength / 2.0) / 8.0,
-gain / 2.0]),
(Path.LINETO, [(self.gap - trunklength / 2.0) / 2.0,
-gain / 2.0]),
(Path.LINETO, [(self.gap - trunklength / 2.0),
-gain / 2.0])]
lrpath = [(Path.LINETO, [(trunklength / 2.0 - self.gap),  # Lower right
loss / 2.0])]
ulpath = [(Path.LINETO, [self.gap - trunklength / 2.0,  # Upper left
gain / 2.0])]

# Add the subpaths and assign the locations of the tips and labels.
tips = np.zeros((n, 2))
label_locations = np.zeros((n, 2))
# Add the top-side inputs and outputs from the middle outwards.
for i, (angle, is_input, spec) in enumerate(zip(
angles, are_inputs, list(zip(scaled_flows, pathlengths)))):
if angle == DOWN and is_input:
tips[i, :], label_locations[i, :] = self._add_input(
ulpath, angle, *spec)
elif angle == UP and not is_input:
tips[i, :], label_locations[i, :] = self._add_output(
urpath, angle, *spec)
# Add the bottom-side inputs and outputs from the middle outwards.
for i, (angle, is_input, spec) in enumerate(reversed(list(zip(
angles, are_inputs, list(zip(scaled_flows, pathlengths)))))):
if angle == UP and is_input:
tip, label_location = self._add_input(llpath, angle, *spec)
tips[n - i - 1, :] = tip
label_locations[n - i - 1, :] = label_location
elif angle == DOWN and not is_input:
tip, label_location = self._add_output(lrpath, angle, *spec)
tips[n - i - 1, :] = tip
label_locations[n - i - 1, :] = label_location
# Add the left-side inputs from the bottom upwards.
has_left_input = False
for i, (angle, is_input, spec) in enumerate(reversed(list(zip(
angles, are_inputs, list(zip(scaled_flows, pathlengths)))))):
if angle == RIGHT and is_input:
if not has_left_input:
# Make sure the lower path extends
# at least as far as the upper one.
if llpath[-1][1][0] > ulpath[-1][1][0]:
llpath.append((Path.LINETO, [ulpath[-1][1][0],
llpath[-1][1][1]]))
has_left_input = True
tip, label_location = self._add_input(llpath, angle, *spec)
tips[n - i - 1, :] = tip
label_locations[n - i - 1, :] = label_location
# Add the right-side outputs from the top downwards.
has_right_output = False
for i, (angle, is_input, spec) in enumerate(zip(
angles, are_inputs, list(zip(scaled_flows, pathlengths)))):
if angle == RIGHT and not is_input:
if not has_right_output:
# Make sure the upper path extends
# at least as far as the lower one.
if urpath[-1][1][0] < lrpath[-1][1][0]:
urpath.append((Path.LINETO, [lrpath[-1][1][0],
urpath[-1][1][1]]))
has_right_output = True
tips[i, :], label_locations[i, :] = self._add_output(
urpath, angle, *spec)
# Trim any hanging vertices.
if not has_left_input:
ulpath.pop()
llpath.pop()
if not has_right_output:
lrpath.pop()
urpath.pop()

# Concatenate the subpaths in the correct order (clockwise from top).
path = (urpath + self._revert(lrpath) + llpath + self._revert(ulpath) +
[(Path.CLOSEPOLY, urpath[0][1])])

# Create a patch with the Sankey outline.
codes, vertices = zip(*path)
vertices = np.array(vertices)

def _get_angle(a, r):
if a is None:
return None
else:
return a + r

if prior is None:
if rotation != 0:  # By default, none of this is needed.
angles = [_get_angle(angle, rotation) for angle in angles]
rotate = Affine2D().rotate_deg(rotation * 90).transform_affine
tips = rotate(tips)
label_locations = rotate(label_locations)
vertices = rotate(vertices)
text = self.ax.text(0, 0, s=patchlabel, ha='center', va='center')
else:
rotation = (self.diagrams[prior].angles[connect[0]] -
angles[connect[1]])
angles = [_get_angle(angle, rotation) for angle in angles]
rotate = Affine2D().rotate_deg(rotation * 90).transform_affine
tips = rotate(tips)
offset = self.diagrams[prior].tips[connect[0]] - tips[connect[1]]
translate = Affine2D().translate(*offset).transform_affine
tips = translate(tips)
label_locations = translate(rotate(label_locations))
vertices = translate(rotate(vertices))
kwds = dict(s=patchlabel, ha='center', va='center')
text = self.ax.text(*offset, **kwds)
if rcParams['_internal.classic_mode']:
fc = kwargs.pop('fc', kwargs.pop('facecolor', '#bfd1d4'))
lw = kwargs.pop('lw', kwargs.pop('linewidth', 0.5))
else:
fc = kwargs.pop('fc', kwargs.pop('facecolor', None))
lw = kwargs.pop('lw', kwargs.pop('linewidth', None))
if fc is None:
fc = next(self.ax._get_patches_for_fill.prop_cycler)['color']
patch = PathPatch(Path(vertices, codes), fc=fc, lw=lw, **kwargs)

# Add the path labels.
texts = []
for number, angle, label, location in zip(flows, angles, labels,
label_locations):
if label is None or angle is None:
label = ''
elif self.unit is not None:
quantity = self.format % abs(number) + self.unit
if label != '':
label += "\n"
label += quantity
texts.append(self.ax.text(x=location[0], y=location[1],
s=label,
ha='center', va='center'))
# Text objects are placed even they are empty (as long as the magnitude
# of the corresponding flow is larger than the tolerance) in case the
# user wants to provide labels later.

# Expand the size of the diagram if necessary.
self.extent = (min(np.min(vertices[:, 0]),
np.min(label_locations[:, 0]),
self.extent[0]),
max(np.max(vertices[:, 0]),
np.max(label_locations[:, 0]),
self.extent[1]),
min(np.min(vertices[:, 1]),
np.min(label_locations[:, 1]),
self.extent[2]),
max(np.max(vertices[:, 1]),
np.max(label_locations[:, 1]),
self.extent[3]))
# Include both vertices _and_ label locations in the extents; there are
# where either could determine the margins (e.g., arrow shoulders).

# Add this diagram as a subdiagram.
self.diagrams.append(
SimpleNamespace(patch=patch, flows=flows, angles=angles, tips=tips,
text=text, texts=texts))

# Allow a daisy-chained call structure (see docstring for the class).
return self

[docs]    def finish(self):
"""
Adjust the axes and return a list of information about the Sankey
subdiagram(s).

Return value is a list of subdiagrams represented with the following
fields:

===============   ===================================================
Field             Description
===============   ===================================================
*patch*           Sankey outline (an instance of
:class:`~maplotlib.patches.PathPatch`)
*flows*           values of the flows (positive for input, negative
for output)
*angles*          list of angles of the arrows [deg/90]
For example, if the diagram has not been rotated,
an input to the top side will have an angle of 3
(DOWN), and an output from the top side will have
an angle of 1 (UP).  If a flow has been skipped
(because its magnitude is less than *tolerance*),
then its angle will be *None*.
*tips*            array in which each row is an [x, y] pair
indicating the positions of the tips (or "dips") of
the flow paths
If the magnitude of a flow is less the *tolerance*
for the instance of :class:`Sankey`, the flow is
skipped and its tip will be at the center of the
diagram.
*text*            :class:`~matplotlib.text.Text` instance for the
label of the diagram
*texts*           list of :class:`~matplotlib.text.Text` instances
for the labels of flows
===============   ===================================================

.. seealso::