def convert(value, unit, axis): """: Convert value using unit to a float. If value is a sequence, return the converted sequence. = INPUT VARIABLES - value The value or list of values that need to be converted. - unit The units to use for an axis with Epoch data. = RETURN VALUE - Returns the value parameter converted to floats. """ # Delay-load due to circular dependencies. import matplotlib.testing.jpl_units as U if not cbook.is_scalar_or_string(value): return [EpochConverter.convert(x, unit, axis) for x in value] if (units.ConversionInterface.is_numlike(value) and not isinstance(value, (U.Epoch, U.Duration))): return value if unit is None: unit = EpochConverter.default_units(value, axis) if isinstance(value, U.Duration): return EpochConverter.duration2float(value) else: return EpochConverter.epoch2float(value, unit)
def convert(value, unit, axis): """: Convert value using unit to a float. If value is a sequence, return the converted sequence. = INPUT VARIABLES - value The value or list of values that need to be converted. - unit The units to use for a axis with Epoch data. = RETURN VALUE - Returns the value parameter converted to floats. """ # Delay-load due to circular dependencies. import matplotlib.testing.jpl_units as U if not cbook.is_scalar_or_string(value): return [UnitDblConverter.convert(x, unit, axis) for x in value] # If the incoming value behaves like a number, but is not a UnitDbl, # then just return it because we don't know how to convert it # (or it is already converted) if (units.ConversionInterface.is_numlike(value) and not isinstance(value, U.UnitDbl)): return value # If no units were specified, then get the default units to use. if unit is None: unit = UnitDblConverter.default_units(value, axis) # Convert the incoming UnitDbl value/values to float/floats if isinstance(axis.axes, polar.PolarAxes) and value.type() == "angle": # Guarantee that units are radians for polar plots. return value.convert("rad") return value.convert(unit)
def default_units(value, axis): # docstring inherited # Determine the default units based on the user preferences set for # default units when printing a UnitDbl. if cbook.is_scalar_or_string(value): return UnitDblConverter.defaults[value.type()] else: return UnitDblConverter.default_units(value[0], axis)
def to_array(data, maxlen=100): if NP_NEW: return np.array(data, dtype=np.unicode) if cbook.is_scalar_or_string(data): data = [data] try: vals = np.array(data, dtype=('|S', maxlen)) except UnicodeEncodeError: # this yields gibberish vals = np.array([convert_to_string(d) for d in data]) return vals
def convert(value, unit, axis): # docstring inherited if not cbook.is_scalar_or_string(value): return [UnitDblConverter.convert(x, unit, axis) for x in value] # If no units were specified, then get the default units to use. if unit is None: unit = UnitDblConverter.default_units(value, axis) # Convert the incoming UnitDbl value/values to float/floats if isinstance(axis.axes, polar.PolarAxes) and value.type() == "angle": # Guarantee that units are radians for polar plots. return value.convert("rad") return value.convert(unit)
def default_units(value, axis): """: Return the default unit for value, or None. = INPUT VARIABLES - value The value or list of values that need units. = RETURN VALUE - Returns the default units to use for value. """ if cbook.is_scalar_or_string(value): return value.frame() else: return EpochConverter.default_units(value[0], axis)
def convert(value, unit, axis): # docstring inherited # Delay-load due to circular dependencies. import matplotlib.testing.jpl_units as U if not cbook.is_scalar_or_string(value): return [EpochConverter.convert(x, unit, axis) for x in value] if unit is None: unit = EpochConverter.default_units(value, axis) if isinstance(value, U.Duration): return EpochConverter.duration2float(value) else: return EpochConverter.epoch2float(value, unit)
def default_units(value, axis): """: Return the default unit for value, or None. = INPUT VARIABLES - value The value or list of values that need units. = RETURN VALUE - Returns the default units to use for value. Return the default unit for value, or None. """ # Determine the default units based on the user preferences set for # default units when printing a UnitDbl. if cbook.is_scalar_or_string(value): return UnitDblConverter.defaults[value.type()] else: return UnitDblConverter.default_units(value[0], axis)
def convert(value, unit, axis): # docstring inherited if not cbook.is_scalar_or_string(value): return [UnitDblConverter.convert(x, unit, axis) for x in value] # If the incoming value behaves like a number, # then just return it because we don't know how to convert it # (or it is already converted) if units.ConversionInterface.is_numlike(value): return value # If no units were specified, then get the default units to use. if unit is None: unit = UnitDblConverter.default_units(value, axis) # Convert the incoming UnitDbl value/values to float/floats if isinstance(axis.axes, polar.PolarAxes) and value.type() == "angle": # Guarantee that units are radians for polar plots. return value.convert("rad") return value.convert(unit)
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 Bezier 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)s See Also -------- Sankey.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 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 if not cbook.is_scalar_or_string(labels) and len(labels) != n: raise ValueError( f"The lengths of 'flows' ({n}) and 'labels' ({len(labels)}) " f"are incompatible") else: labels = [labels] * n if trunklength < 0: raise ValueError( "'trunklength' is negative, which is not 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( 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 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( f"The value of orientations[{i}] is {orient}, " f"but it must be -1, 0, or 1") if is_input: angles[i] = UP elif not is_input: 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 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) 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: 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
def draw_animation_edges(G, pos, edgelist=None, width=1.0, edge_color='k', style='solid', alpha=1.0, edge_cmap=None, edge_vmin=None, edge_vmax=None, ax=None, arrows=True, label=None, **kwds): try: import matplotlib import matplotlib.pyplot as plt import matplotlib.cbook as cb from matplotlib.colors import colorConverter, Colormap from matplotlib.collections import LineCollection import numpy except ImportError: raise ImportError("Matplotlib required for draw()") except RuntimeError: print("Matplotlib unable to open display") raise if ax is None: ax = plt.gca() if edgelist is None: edgelist = list(G.edges()) if not edgelist or len(edgelist) == 0: # no edges! return None # set edge positions box_pos = numpy.asarray([(pos[e[0]], pos[e[1]]) for e in edgelist]) p = 0.25 edge_pos = [] for edge in edgelist: src, dst = np.array(pos[edge[0]]), np.array(pos[edge[1]]) s = dst - src # src = src + p * s # Box at beginning # dst = src + (1-p) * s # Box at the end dst = src # No edge at all edge_pos.append((src, dst)) edge_pos = numpy.asarray(edge_pos) if not cb.iterable(width): lw = (width, ) else: lw = width if not cb.is_scalar_or_string(edge_color) \ and cb.iterable(edge_color) \ and len(edge_color) == len(edge_pos): if numpy.alltrue([cb.is_scalar_or_string(c) for c in edge_color]): # (should check ALL elements) # list of color letters such as ['k','r','k',...] edge_colors = tuple( [colorConverter.to_rgba(c, alpha) for c in edge_color]) elif numpy.alltrue( [not cb.is_scalar_or_string(c) for c in edge_color]): # If color specs are given as (rgb) or (rgba) tuples, we're OK if numpy.alltrue( [cb.iterable(c) and len(c) in (3, 4) for c in edge_color]): edge_colors = tuple(edge_color) else: # numbers (which are going to be mapped with a colormap) edge_colors = None else: raise ValueError( 'edge_color must consist of either color names or numbers') else: if cb.is_scalar_or_string(edge_color) or len(edge_color) == 1: edge_colors = (colorConverter.to_rgba(edge_color, alpha), ) else: raise ValueError( 'edge_color must be a single color or list of exactly m colors where m is the number or edges' ) ''' modEdgeColors = list(edge_colors) modEdgeColors = tuple(modEdgeColors + [colorConverter.to_rgba('w', alpha) for c in edge_color]) #print(modEdgeColors) edge_collection = LineCollection(np.asarray(list(edge_pos)*2), colors=modEdgeColors, linewidths=[6]*len(list(edge_colors))+[4]*len(list(edge_colors)), antialiaseds=(1,), linestyle=style, transOffset=ax.transData, ) ''' edge_collection = LineCollection( edge_pos, colors=edge_colors, linewidths=6, antialiaseds=(1, ), linestyle=style, transOffset=ax.transData, ) edge_collection.set_zorder(1) # edges go behind nodes edge_collection.set_label(label) ax.add_collection(edge_collection) tube_collection = LineCollection( edge_pos, colors=tuple([ colorConverter.to_rgba('lightgrey', alpha) for c in edge_color ]), linewidths=4, antialiaseds=(1, ), linestyle=style, transOffset=ax.transData, ) tube_collection.set_zorder(1) # edges go behind nodes tube_collection.set_label(label) ax.add_collection(tube_collection) # Note: there was a bug in mpl regarding the handling of alpha values for # each line in a LineCollection. It was fixed in matplotlib in r7184 and # r7189 (June 6 2009). We should then not set the alpha value globally, # since the user can instead provide per-edge alphas now. Only set it # globally if provided as a scalar. if cb.is_numlike(alpha): edge_collection.set_alpha(alpha) if edge_colors is None: if edge_cmap is not None: assert (isinstance(edge_cmap, Colormap)) edge_collection.set_array(numpy.asarray(edge_color)) edge_collection.set_cmap(edge_cmap) if edge_vmin is not None or edge_vmax is not None: edge_collection.set_clim(edge_vmin, edge_vmax) else: edge_collection.autoscale() box_collection = Utilities.get_boxes(edge_colors=edge_colors, edge_pos=box_pos) box_collection.set_zorder(1) # edges go behind nodes box_collection.set_label(label) ax.add_collection(box_collection) arrow_collection = Utilities.get_arrows_on_edges( edge_colors=edge_colors, edge_pos=box_pos) arrow_collection.set_zorder(0) if arrows: # Visualize them only if wanted ax.add_collection(arrow_collection) return edge_collection, box_collection, tube_collection, arrow_collection
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 not cbook.is_scalar_or_string(labels) and 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 np.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) 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: 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
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 not cbook.is_scalar_or_string(labels) and 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 np.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) 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: 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
def default_units(value, axis): # docstring inherited if cbook.is_scalar_or_string(value): return value.frame() else: return EpochConverter.default_units(value[0], axis)
def is_array(thing): if hasattr(thing, 'dtype'): return True else: return is_scalar_or_string(thing)