from __future__ import absolute_import, division, unicode_literals
import param
import numpy as np
from matplotlib.collections import LineCollection, PolyCollection
from ...core.data import Dataset
from ...core.options import Cycle, abbreviated_exception
from ...core.util import basestring, unique_array, search_indices, is_number, isscalar
from ...util.transform import dim
from ..mixins import ChordMixin
from ..util import process_cmap, get_directed_graph_paths
from .element import ColorbarPlot
from .util import filter_styles
[docs]class GraphPlot(ColorbarPlot):
arrowhead_length = param.Number(default=0.025, doc="""
If directed option is enabled this determines the length of the
arrows as fraction of the overall extent of the graph.""")
directed = param.Boolean(default=False, doc="""
Whether to draw arrows on the graph edges to indicate the
directionality of each edge.""")
# Deprecated options
color_index = param.ClassSelector(default=None, class_=(basestring, int),
allow_None=True, doc="""
Deprecated in favor of color style mapping, e.g. `node_color=dim('color')`""")
edge_color_index = param.ClassSelector(default=None, class_=(basestring, int),
allow_None=True, doc="""
Deprecated in favor of color style mapping, e.g. `edge_color=dim('color')`""")
style_opts = ['edge_alpha', 'edge_color', 'edge_linestyle', 'edge_linewidth',
'node_alpha', 'node_color', 'node_edgecolors', 'node_facecolors',
'node_linewidth', 'node_marker', 'node_size', 'visible', 'cmap',
'edge_cmap', 'node_cmap']
_style_groups = ['node', 'edge']
_nonvectorized_styles = [
'edge_alpha', 'edge_linestyle', 'edge_cmap', 'cmap', 'visible',
'node_marker'
]
filled = False
def _compute_styles(self, element, ranges, style):
elstyle = self.lookup_options(element, 'style')
color = elstyle.kwargs.get('node_color')
cdim = element.nodes.get_dimension(self.color_index)
cmap = elstyle.kwargs.get('cmap', 'tab20')
if cdim:
cs = element.nodes.dimension_values(self.color_index)
# Check if numeric otherwise treat as categorical
if cs.dtype.kind == 'f':
style['node_c'] = cs
else:
factors = unique_array(cs)
cmap = color if isinstance(color, Cycle) else cmap
if isinstance(cmap, dict):
colors = [cmap.get(f, cmap.get('NaN', {'color': self._default_nan})['color'])
for f in factors]
else:
colors = process_cmap(cmap, len(factors))
cs = search_indices(cs, factors)
style['node_facecolors'] = [colors[v%len(colors)] for v in cs]
style.pop('node_color', None)
if 'node_c' in style:
self._norm_kwargs(element.nodes, ranges, style, cdim)
elif color and 'node_color' in style:
style['node_facecolors'] = style.pop('node_color')
style['node_edgecolors'] = style.pop('node_edgecolors', 'none')
if is_number(style.get('node_size')):
style['node_s'] = style.pop('node_size')**2
edge_cdim = element.get_dimension(self.edge_color_index)
if not edge_cdim:
if not isscalar(style.get('edge_color')):
opt = 'edge_facecolors' if self.filled else 'edge_edgecolors'
style[opt] = style.pop('edge_color')
return style
elstyle = self.lookup_options(element, 'style')
cycle = elstyle.kwargs.get('edge_color')
idx = element.get_dimension_index(edge_cdim)
cvals = element.dimension_values(edge_cdim)
if idx in [0, 1]:
factors = element.nodes.dimension_values(2, expanded=False)
elif idx == 2 and cvals.dtype.kind in 'uif':
factors = None
else:
factors = unique_array(cvals)
if factors is None or (factors.dtype.kind == 'f' and idx not in [0, 1]):
style['edge_c'] = cvals
else:
cvals = search_indices(cvals, factors)
factors = list(factors)
cmap = elstyle.kwargs.get('edge_cmap', 'tab20')
cmap = cycle if isinstance(cycle, Cycle) else cmap
if isinstance(cmap, dict):
colors = [cmap.get(f, cmap.get('NaN', {'color': self._default_nan})['color'])
for f in factors]
else:
colors = process_cmap(cmap, len(factors))
style['edge_colors'] = [colors[v%len(colors)] for v in cvals]
style.pop('edge_color', None)
if 'edge_c' in style:
self._norm_kwargs(element, ranges, style, edge_cdim, prefix='edge_')
else:
style.pop('edge_cmap', None)
return style
def get_data(self, element, ranges, style):
with abbreviated_exception():
style = self._apply_transforms(element, ranges, style)
xidx, yidx = (1, 0) if self.invert_axes else (0, 1)
pxs, pys = (element.nodes.dimension_values(i) for i in range(2))
dims = element.nodes.dimensions()
self._compute_styles(element, ranges, style)
if 'edge_vmin' in style:
style['edge_clim'] = (style.pop('edge_vmin'), style.pop('edge_vmax'))
if 'edge_c' in style:
style['edge_array'] = style.pop('edge_c')
if self.directed:
xdim, ydim = element.nodes.kdims[:2]
x_range = ranges[xdim.name]['combined']
y_range = ranges[ydim.name]['combined']
arrow_len = np.hypot(y_range[1]-y_range[0], x_range[1]-x_range[0])*self.arrowhead_length
paths = get_directed_graph_paths(element, arrow_len)
else:
paths = element._split_edgepaths.split(datatype='array', dimensions=element.edgepaths.kdims)
if self.invert_axes:
paths = [p[:, ::-1] for p in paths]
return {'nodes': (pxs, pys), 'edges': paths}, style, {'dimensions': dims}
[docs] def get_extents(self, element, ranges, range_type='combined'):
return super(GraphPlot, self).get_extents(element.nodes, ranges, range_type)
[docs] def init_artists(self, ax, plot_args, plot_kwargs):
# Draw edges
color_opts = ['c', 'cmap', 'vmin', 'vmax', 'norm']
groups = [g for g in self._style_groups if g != 'edge']
edge_opts = filter_styles(plot_kwargs, 'edge', groups, color_opts)
if 'c' in edge_opts:
edge_opts['array'] = edge_opts.pop('c')
paths = plot_args['edges']
if self.filled:
coll = PolyCollection
if 'colors' in edge_opts:
edge_opts['facecolors'] = edge_opts.pop('colors')
else:
coll = LineCollection
edgecolors = edge_opts.pop('edgecolors', None)
edges = coll(paths, **edge_opts)
if edgecolors is not None:
edges.set_edgecolors(edgecolors)
ax.add_collection(edges)
# Draw nodes
xs, ys = plot_args['nodes']
groups = [g for g in self._style_groups if g != 'node']
node_opts = filter_styles(plot_kwargs, 'node', groups)
nodes = ax.scatter(xs, ys, **node_opts)
return {'nodes': nodes, 'edges': edges}
def _update_nodes(self, element, data, style):
nodes = self.handles['nodes']
xs, ys = data['nodes']
nodes.set_offsets(np.column_stack([xs, ys]))
if 'node_facecolors' in style:
nodes.set_facecolors(style['node_facecolors'])
if 'node_edgecolors' in style:
nodes.set_edgecolors(style['node_edgecolors'])
if 'node_c' in style:
nodes.set_array(style['node_c'])
if 'node_vmin' in style:
nodes.set_clim((style['node_vmin'], style['node_vmax']))
if 'node_norm' in style:
nodes.norm = style['norm']
if 'node_linewidth' in style:
nodes.set_linewidths(style['node_linewidth'])
if 'node_s' in style:
sizes = style['node_s']
if isscalar(sizes):
nodes.set_sizes([sizes])
else:
nodes.set_sizes(sizes)
def _update_edges(self, element, data, style):
edges = self.handles['edges']
paths = data['edges']
edges.set_paths(paths)
edges.set_visible(style.get('visible', True))
if 'edge_facecolors' in style:
edges.set_facecolors(style['edge_facecolors'])
if 'edge_edgecolors' in style:
edges.set_edgecolors(style['edge_edgecolors'])
if 'edge_array' in style:
edges.set_array(style['edge_array'])
elif 'edge_colors' in style:
if self.filled:
edges.set_facecolors(style['edge_colors'])
else:
edges.set_edgecolors(style['edge_colors'])
if 'edge_clim' in style:
edges.set_clim(style['edge_clim'])
if 'edge_norm' in style:
edges.norm = style['edge_norm']
if 'edge_linewidth' in style:
edges.set_linewidths(style['edge_linewidth'])
[docs] def update_handles(self, key, axis, element, ranges, style):
data, style, axis_kwargs = self.get_data(element, ranges, style)
self._update_nodes(element, data, style)
self._update_edges(element, data, style)
return axis_kwargs
[docs]class TriMeshPlot(GraphPlot):
filled = param.Boolean(default=False, doc="""
Whether the triangles should be drawn as filled.""")
style_opts = GraphPlot.style_opts + ['edge_facecolors']
def get_data(self, element, ranges, style):
edge_color = style.get('edge_color')
if edge_color not in element.nodes:
edge_color = self.edge_color_index
simplex_dim = element.get_dimension(edge_color)
vertex_dim = element.nodes.get_dimension(edge_color)
if not isinstance(self.edge_color_index, int) and vertex_dim and not simplex_dim:
simplices = element.array([0, 1, 2])
z = element.nodes.dimension_values(vertex_dim)
z = z[simplices].mean(axis=1)
element = element.add_dimension(vertex_dim, len(element.vdims), z, vdim=True)
# Ensure the edgepaths for the triangles are generated before plotting
element.edgepaths
return super(TriMeshPlot, self).get_data(element, ranges, style)
[docs]class ChordPlot(ChordMixin, GraphPlot):
labels = param.ClassSelector(class_=(basestring, dim), doc="""
The dimension or dimension value transform used to draw labels from.""")
# Deprecated options
label_index = param.ClassSelector(default=None, class_=(basestring, int),
allow_None=True, doc="""
Index of the dimension from which the node labels will be drawn""")
style_opts = GraphPlot.style_opts + ['text_font_size', 'label_offset']
_style_groups = ['edge', 'node', 'arc']
def get_data(self, element, ranges, style):
data, style, plot_kwargs = super(ChordPlot, self).get_data(element, ranges, style)
angles = element._angles
paths = []
for i in range(len(element.nodes)):
start, end = angles[i:i+2]
vals = np.linspace(start, end, 20)
paths.append(np.column_stack([np.cos(vals), np.sin(vals)]))
data['arcs'] = paths
if 'node_c' in style:
style['arc_array'] = style['node_c']
style['arc_clim'] = style['node_vmin'], style['node_vmax']
style['arc_cmap'] = style['node_cmap']
elif 'node_facecolors' in style:
style['arc_colors'] = style['node_facecolors']
style['arc_linewidth'] = 10
label_dim = element.nodes.get_dimension(self.label_index)
labels = self.labels
if label_dim and labels:
self.param.warning(
"Cannot declare style mapping for 'labels' option "
"and declare a label_index; ignoring the label_index.")
elif label_dim:
labels = label_dim
if isinstance(labels, basestring):
labels = element.nodes.get_dimension(labels)
if labels is None:
return data, style, plot_kwargs
nodes = element.nodes
if element.vdims:
values = element.dimension_values(element.vdims[0])
if values.dtype.kind in 'uif':
edges = Dataset(element)[values>0]
nodes = list(np.unique([edges.dimension_values(i) for i in range(2)]))
nodes = element.nodes.select(**{element.nodes.kdims[2].name: nodes})
offset = style.get('label_offset', 1.05)
xs, ys = (nodes.dimension_values(i)*offset for i in range(2))
if isinstance(labels, dim):
text = labels.apply(element, flat=True)
else:
text = element.nodes.dimension_values(labels)
text = [labels.pprint_value(v) for v in text]
angles = np.rad2deg(np.arctan2(ys, xs))
data['text'] = (xs, ys, text, angles)
return data, style, plot_kwargs
[docs] def init_artists(self, ax, plot_args, plot_kwargs):
artists = {}
if 'arcs' in plot_args:
color_opts = ['c', 'cmap', 'vmin', 'vmax', 'norm']
groups = [g for g in self._style_groups if g != 'arc']
edge_opts = filter_styles(plot_kwargs, 'arc', groups, color_opts)
paths = plot_args['arcs']
edges = LineCollection(paths, **edge_opts)
ax.add_collection(edges)
artists['arcs'] = edges
artists.update(super(ChordPlot, self).init_artists(ax, plot_args, plot_kwargs))
if 'text' in plot_args:
fontsize = plot_kwargs.get('text_font_size', 8)
labels = []
for (x, y, l, a) in zip(*plot_args['text']):
label = ax.annotate(l, xy=(x, y), xycoords='data', rotation=a,
horizontalalignment='left', fontsize=fontsize,
verticalalignment='center', rotation_mode='anchor')
labels.append(label)
artists['labels'] = labels
return artists
def _update_arcs(self, element, data, style):
edges = self.handles['arcs']
paths = data['arcs']
edges.set_paths(paths)
edges.set_visible(style.get('visible', True))
if 'arc_array' in style:
edges.set_array(style['arc_array'])
if 'arc_clim' in style:
edges.set_clim(style['arc_clim'])
if 'arc_norm' in style:
edges.set_norm(style['arc_norm'])
if 'arc_colors' in style:
edges.set_edgecolors(style['arc_colors'])
elif 'arc_edgecolors' in style:
edges.set_edgecolors(style['arc_edgecolors'])
def _update_labels(self, ax, element, data, style):
labels = self.handles.get('labels', [])
for label in labels:
try:
label.remove()
except:
pass
if 'text' not in data:
self.handles['labels'] = []
return
labels = []
fontsize = style.get('text_font_size', 8)
for (x, y, l, a) in zip(*data['text']):
label = ax.annotate(l, xy=(x, y), xycoords='data', rotation=a,
horizontalalignment='left', fontsize=fontsize,
verticalalignment='center', rotation_mode='anchor')
labels.append(label)
self.handles['labels'] = labels
[docs] def update_handles(self, key, axis, element, ranges, style):
data, style, axis_kwargs = self.get_data(element, ranges, style)
self._update_nodes(element, data, style)
self._update_edges(element, data, style)
self._update_arcs(element, data, style)
self._update_labels(axis, element, data, style)
return axis_kwargs
