class_docstr: Sankey diagram.
  
    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>`_
docstr: Add a simple Sankey diagram with flows at the same hierarchical level.
  
  Parameters
  ----------
  patchlabel : str
      Label to be placed at the center of the diagram.
      Note that *label* (not *patchlabel*) can be passed as keyword
      argument to create an entry in the legend.
  
  flows : list of float
      Array of flow values.  By convention, inputs are positive and
      outputs are negative.
  
      Flows are placed along the top of the diagram from the inside out
      in order of their index within *flows*.  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 Bézier curve along
      the top and bottom edges of the trunk.
  
  orientations : list of {-1, 0, 1}
      List of orientations of the flows (or a single orientation to be
      used for all flows).  Valid values are 0 (inputs from
      the left, outputs to the right), 1 (from and to the top) or -1
      (from and to the bottom).
  
  labels : list of (str or None)
      List of labels for the flows (or a single label to be used for all
      flows).  Each label may be *None* (no label), or a labeling string.
      If an entry is a (possibly 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 : float
      Length between the bases of the input and output groups (in
      data-space units).
  
  pathlengths : list of float
      List of lengths of the vertical 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 : int
      Index of the prior diagram to which this diagram should be
      connected.
  
  connect : (int, int)
      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 : float
      Angle of rotation of the diagram in degrees.  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).  *rotation* is ignored if this diagram is connected to an
      existing one (using *prior* and *connect*).
  
  Returns
  -------
  Sankey
      The current `.Sankey` instance.
  
  Other Parameters
  ----------------
  **kwargs
     Additional keyword arguments set `matplotlib.patches.PathPatch`
     properties, listed below.  For example, one may want to use
     ``fill=False`` or ``label="A legend entry"``.
  
  %(Patch:kwdoc)s
  
  See Also
  --------
  Sankey.finish
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code: 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.
  
      Parameters
      ----------
      patchlabel : str
          Label to be placed at the center of the diagram.
          Note that *label* (not *patchlabel*) can be passed as keyword
          argument to create an entry in the legend.
  
      flows : list of float
          Array of flow values.  By convention, inputs are positive and
          outputs are negative.
  
          Flows are placed along the top of the diagram from the inside out
          in order of their index within *flows*.  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 Bézier curve along
          the top and bottom edges of the trunk.
  
      orientations : list of {-1, 0, 1}
          List of orientations of the flows (or a single orientation to be
          used for all flows).  Valid values are 0 (inputs from
          the left, outputs to the right), 1 (from and to the top) or -1
          (from and to the bottom).
  
      labels : list of (str or None)
          List of labels for the flows (or a single label to be used for all
          flows).  Each label may be *None* (no label), or a labeling string.
          If an entry is a (possibly 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 : float
          Length between the bases of the input and output groups (in
          data-space units).
  
      pathlengths : list of float
          List of lengths of the vertical 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 : int
          Index of the prior diagram to which this diagram should be
          connected.
  
      connect : (int, int)
          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 : float
          Angle of rotation of the diagram in degrees.  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).  *rotation* is ignored if this diagram is connected to an
          existing one (using *prior* and *connect*).
  
      Returns
      -------
      Sankey
          The current `.Sankey` instance.
  
      Other Parameters
      ----------------
      **kwargs
         Additional keyword arguments set `matplotlib.patches.PathPatch`
         properties, listed below.  For example, one may want to use
         ``fill=False`` or ``label="A legend entry"``.
  
      %(Patch:kwdoc)s
  
      See Also
      --------
      Sankey.finish
      """
      # Check and preprocess the arguments.
      flows = (
          np.array([1.0, -1.0]) if flows is None else 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
      try:
          orientations = np.broadcast_to(orientations, n)
      except ValueError:
          raise ValueError(
              f"The shapes of 'flows' {np.shape(flows)} and 'orientations' "
              f"{np.shape(orientations)} are incompatible"
          ) from None
      try:
          labels = np.broadcast_to(labels, n)
      except ValueError:
          raise ValueError(
              f"The shapes of 'flows' {np.shape(flows)} and 'labels' "
              f"{np.shape(labels)} are incompatible"
          ) from None
      if trunklength < 0:
          raise ValueError(
              "'trunklength' is negative, which is not allowed because it "
              "would cause poor layout"
          )
      if abs(np.sum(flows)) > self.tolerance:
          _log.info(
              "The sum of the flows is nonzero (%f; patchlabel=%r); "
              "is the system not at steady state?",
              np.sum(flows),
              patchlabel,
          )
      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 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(
                  f"The index of the prior diagram is {prior}, but there "
                  f"are only {len(self.diagrams)} other diagrams"
              )
          if connect[0] >= len(self.diagrams[prior].flows):
              raise ValueError(
                  "The connection index to the source diagram is {}, but "
                  "that diagram has only {} flows".format(
                      connect[0], len(self.diagrams[prior].flows)
                  )
              )
          if connect[1] >= n:
              raise ValueError(
                  f"The connection index to this diagram is {connect[1]}, "
                  f"but this diagram has only {n} flows"
              )
          if self.diagrams[prior].angles[connect[0]] is None:
              raise ValueError(
                  f"The connection cannot be made, which may occur if the "
                  f"magnitude of flow {connect[0]} of diagram {prior} is "
                  f"less than the specified tolerance"
              )
          flow_error = (
              self.diagrams[prior].flows[connect[0]] + flows[connect[1]]
          )
          if abs(flow_error) >= self.tolerance:
              raise ValueError(
                  f"The scaled sum of the connected flows is {flow_error}, "
                  f"which is not within the tolerance ({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 is_input is False:
                  # 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(
                      f"The value of orientations[{i}] is {orient}, "
                      f"but it must be -1, 0, or 1"
                  )
              if is_input:
                  angles[i] = UP
              elif is_input is False:
                  angles[i] = DOWN
  
      # Justify the lengths of the paths.
      if np.iterable(pathlengths):
          if len(pathlengths) != n:
              raise ValueError(
                  f"The lengths of 'flows' ({n}) and 'pathlengths' "
                  f"({len(pathlengths)}) are incompatible"
              )
      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 is_input is False:
                  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 is_input is False:
                  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 is_input is False:
                      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, gain / 2.0],  # Upper left
          )
      ]
  
      # 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 is_input is False:
              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 is_input is False:
              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 is_input is False:
              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 mpl.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 = self.ax._get_patches_for_fill.get_next_color()
      patch = PathPatch(Path(vertices, codes), fc=fc, lw=lw, **kwargs)
      self.ax.add_patch(patch)
  
      # 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:
              if isinstance(self.format, str):
                  quantity = self.format % abs(number) + self.unit
              elif callable(self.format):
                  quantity = self.format(number)
              else:
                  raise TypeError(
                      "format must be callable or a format string"
                  )
              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
  
file_path: matplotlib/lib/matplotlib/sankey.py
imports: import logging
  from types import SimpleNamespace
  import numpy
  import matplotlib
  from matplotlib.path import Path
  from matplotlib.patches import PathPatch
  from matplotlib.transforms import Affine2D
  from matplotlib import _docstring
label_desc: Use image node_id 6 for calling the Sankey obj's underlying member method code with example usage: obj.add(patchlabel, flows, orientations, labels, trunklength, pathlengths, prior, connect, rotation) and returns: self, None, unknown