from __future__ import absolute_import, division, unicode_literals
from collections import defaultdict
import param
import numpy as np
from bokeh.models import BoxAnnotation, Span, Arrow, Slope
from panel.models import HTML
try:
from bokeh.models.arrow_heads import TeeHead, NormalHead
arrow_start = {'<->': NormalHead, '<|-|>': NormalHead}
arrow_end = {'->': NormalHead, '-[': TeeHead, '-|>': NormalHead,
'-': None}
except:
from bokeh.models.arrow_heads import OpenHead, NormalHead
arrow_start = {'<->': NormalHead, '<|-|>': NormalHead}
arrow_end = {'->': NormalHead, '-[': OpenHead, '-|>': NormalHead,
'-': None}
from bokeh.transform import dodge
from ...core.util import datetime_types, dimension_sanitizer, basestring
from ...element import HLine, VLine, VSpan
from ..plot import GenericElementPlot
from .element import AnnotationPlot, ElementPlot, CompositeElementPlot, ColorbarPlot
from .selection import BokehOverlaySelectionDisplay
from .styles import base_properties, fill_properties, line_properties, text_properties
from .plot import BokehPlot
from .util import date_to_integer
[docs]class TextPlot(ElementPlot, AnnotationPlot):
style_opts = text_properties+['color', 'angle', 'visible']
_plot_methods = dict(single='text', batched='text')
selection_display = None
[docs] def get_data(self, element, ranges, style):
mapping = dict(x='x', y='y', text='text')
if self.static_source:
return dict(x=[], y=[], text=[]), mapping, style
if self.invert_axes:
data = dict(x=[element.y], y=[element.x])
else:
data = dict(x=[element.x], y=[element.y])
self._categorize_data(data, ('x', 'y'), element.dimensions())
data['text'] = [element.text]
if 'text_align' not in style:
style['text_align'] = element.halign
baseline = 'middle' if element.valign == 'center' else element.valign
if 'text_baseline' not in style:
style['text_baseline'] = baseline
if 'text_font_size' not in style:
style['text_font_size'] = '%dPt' % element.fontsize
if 'color' in style:
style['text_color'] = style.pop('color')
style['angle'] = np.deg2rad(style.get('angle', element.rotation))
return (data, mapping, style)
def get_batched_data(self, element, ranges=None):
data = defaultdict(list)
zorders = self._updated_zorders(element)
for (key, el), zorder in zip(element.data.items(), zorders):
style = self.lookup_options(element.last, 'style')
style = style.max_cycles(len(self.ordering))[zorder]
eldata, elmapping, style = self.get_data(el, ranges, style)
for k, eld in eldata.items():
data[k].extend(eld)
return data, elmapping, style
[docs] def get_extents(self, element, ranges=None, range_type='combined'):
return None, None, None, None
[docs]class LabelsPlot(ColorbarPlot, AnnotationPlot):
show_legend = param.Boolean(default=False, doc="""
Whether to show legend for the plot.""")
xoffset = param.Number(default=None, doc="""
Amount of offset to apply to labels along x-axis.""")
yoffset = param.Number(default=None, doc="""
Amount of offset to apply to labels along x-axis.""")
# Deprecated options
color_index = param.ClassSelector(default=None, class_=(basestring, int),
allow_None=True, doc="""
Deprecated in favor of color style mapping, e.g. `color=dim('color')`""")
selection_display = BokehOverlaySelectionDisplay()
style_opts = base_properties + text_properties + ['cmap', 'angle']
_nonvectorized_styles = base_properties + ['cmap']
_plot_methods = dict(single='text', batched='text')
_batched_style_opts = text_properties
[docs] def get_data(self, element, ranges, style):
style = self.style[self.cyclic_index]
if 'angle' in style and isinstance(style['angle'], (int, float)):
style['angle'] = np.deg2rad(style.get('angle', 0))
dims = element.dimensions()
coords = (1, 0) if self.invert_axes else (0, 1)
xdim, ydim, tdim = (dimension_sanitizer(dims[i].name) for i in coords+(2,))
mapping = dict(x=xdim, y=ydim, text=tdim)
data = {d: element.dimension_values(d) for d in (xdim, ydim)}
if self.xoffset is not None:
mapping['x'] = dodge(xdim, self.xoffset)
if self.yoffset is not None:
mapping['y'] = dodge(ydim, self.yoffset)
data[tdim] = [dims[2].pprint_value(v) for v in element.dimension_values(2)]
self._categorize_data(data, (xdim, ydim), element.dimensions())
cdim = element.get_dimension(self.color_index)
if cdim is None:
return data, mapping, style
cdata, cmapping = self._get_color_data(element, ranges, style, name='text_color')
if dims[2] is cdim and cdata:
# If color dim is same as text dim, rename color column
data['text_color'] = cdata[tdim]
mapping['text_color'] = dict(cmapping['text_color'], field='text_color')
else:
data.update(cdata)
mapping.update(cmapping)
return data, mapping, style
[docs]class LineAnnotationPlot(ElementPlot, AnnotationPlot):
style_opts = line_properties + ['level', 'visible']
apply_ranges = param.Boolean(default=False, doc="""
Whether to include the annotation in axis range calculations.""")
_allow_implicit_categories = False
_plot_methods = dict(single='Span')
selection_display = None
[docs] def get_data(self, element, ranges, style):
data, mapping = {}, {}
dim = 'width' if isinstance(element, HLine) else 'height'
if self.invert_axes:
dim = 'width' if dim == 'height' else 'height'
mapping['dimension'] = dim
loc = element.data
if isinstance(loc, datetime_types):
loc = date_to_integer(loc)
mapping['location'] = loc
return (data, mapping, style)
def _init_glyph(self, plot, mapping, properties):
"""
Returns a Bokeh glyph object.
"""
box = Span(level=properties.get('level', 'glyph'), **mapping)
plot.renderers.append(box)
return None, box
[docs] def get_extents(self, element, ranges=None, range_type='combined'):
loc = element.data
if isinstance(element, VLine):
dim = 'x'
elif isinstance(element, HLine):
dim = 'y'
if self.invert_axes:
dim = 'x' if dim == 'y' else 'x'
ranges[dim]['soft'] = loc, loc
return super(LineAnnotationPlot, self).get_extents(element, ranges, range_type)
[docs]class BoxAnnotationPlot(ElementPlot, AnnotationPlot):
apply_ranges = param.Boolean(default=False, doc="""
Whether to include the annotation in axis range calculations.""")
style_opts = line_properties + fill_properties + ['level', 'visible']
_allow_implicit_categories = False
_plot_methods = dict(single='BoxAnnotation')
selection_display = None
[docs] def get_data(self, element, ranges, style):
data, mapping = {}, {}
kwd_dim1 = 'left' if isinstance(element, VSpan) else 'bottom'
kwd_dim2 = 'right' if isinstance(element, VSpan) else 'top'
if self.invert_axes:
kwd_dim1 = 'bottom' if kwd_dim1 == 'left' else 'left'
kwd_dim2 = 'top' if kwd_dim2 == 'right' else 'right'
locs = element.data
if isinstance(locs, datetime_types):
locs = [date_to_integer(loc) for loc in locs]
mapping[kwd_dim1] = locs[0]
mapping[kwd_dim2] = locs[1]
return (data, mapping, style)
def _init_glyph(self, plot, mapping, properties):
"""
Returns a Bokeh glyph object.
"""
box = BoxAnnotation(level=properties.get('level', 'glyph'), **mapping)
plot.renderers.append(box)
return None, box
[docs]class SlopePlot(ElementPlot, AnnotationPlot):
style_opts = line_properties + ['level']
_plot_methods = dict(single='Slope')
selection_display = None
[docs] def get_data(self, element, ranges, style):
data, mapping = {}, {}
gradient, intercept = element.data
if self.invert_axes:
if gradient == 0:
gradient = np.inf, np.inf
else:
gradient, intercept = 1/gradient, -(intercept/gradient)
mapping['gradient'] = gradient
mapping['y_intercept'] = intercept
return (data, mapping, style)
def _init_glyph(self, plot, mapping, properties):
"""
Returns a Bokeh glyph object.
"""
slope = Slope(level=properties.get('level', 'glyph'), **mapping)
plot.add_layout(slope)
return None, slope
[docs] def get_extents(self, element, ranges=None, range_type='combined'):
return None, None, None, None
[docs]class SplinePlot(ElementPlot, AnnotationPlot):
"""
Draw the supplied Spline annotation (see Spline docstring).
Does not support matplotlib Path codes.
"""
style_opts = line_properties + ['visible']
_plot_methods = dict(single='bezier')
selection_display = None
[docs] def get_data(self, element, ranges, style):
if self.invert_axes:
data_attrs = ['y0', 'x0', 'cy0', 'cx0', 'cy1', 'cx1', 'y1', 'x1']
else:
data_attrs = ['x0', 'y0', 'cx0', 'cy0', 'cx1', 'cy1', 'x1', 'y1']
verts = np.array(element.data[0])
inds = np.where(np.array(element.data[1])==1)[0]
data = {da: [] for da in data_attrs}
skipped = False
for vs in np.split(verts, inds[1:]):
if len(vs) != 4:
skipped = len(vs) > 1
continue
for x, y, xl, yl in zip(vs[:, 0], vs[:, 1], data_attrs[::2], data_attrs[1::2]):
data[xl].append(x)
data[yl].append(y)
if skipped:
self.param.warning(
'Bokeh SplinePlot only support cubic splines, unsupported '
'splines were skipped during plotting.')
data = {da: data[da] for da in data_attrs}
return (data, dict(zip(data_attrs, data_attrs)), style)
[docs]class ArrowPlot(CompositeElementPlot, AnnotationPlot):
style_opts = (['arrow_%s' % p for p in line_properties+fill_properties+['size']] +
text_properties)
_style_groups = {'arrow': 'arrow', 'text': 'text'}
_draw_order = ['arrow_1', 'text_1']
selection_display = None
[docs] def get_data(self, element, ranges, style):
plot = self.state
label_mapping = dict(x='x', y='y', text='text')
arrow_mapping = dict(x_start='x_start', x_end='x_end',
y_start='y_start', y_end='y_end')
# Compute arrow
x1, y1 = element.x, element.y
axrange = plot.x_range if self.invert_axes else plot.y_range
span = (axrange.end - axrange.start) / 6.
if element.direction == '^':
x2, y2 = x1, y1-span
label_mapping['text_baseline'] = 'top'
elif element.direction == '<':
x2, y2 = x1+span, y1
label_mapping['text_align'] = 'left'
label_mapping['text_baseline'] = 'middle'
elif element.direction == '>':
x2, y2 = x1-span, y1
label_mapping['text_align'] = 'right'
label_mapping['text_baseline'] = 'middle'
else:
x2, y2 = x1, y1+span
label_mapping['text_baseline'] = 'bottom'
arrow_data = {'x_end': [x1], 'y_end': [y1],
'x_start': [x2], 'y_start': [y2]}
# Define arrowhead
arrow_mapping['arrow_start'] = arrow_start.get(element.arrowstyle, None)
arrow_mapping['arrow_end'] = arrow_end.get(element.arrowstyle, NormalHead)
# Compute label
if self.invert_axes:
label_data = dict(x=[y2], y=[x2])
else:
label_data = dict(x=[x2], y=[y2])
label_data['text'] = [element.text]
return ({'text_1': label_data, 'arrow_1': arrow_data},
{'arrow_1': arrow_mapping, 'text_1': label_mapping}, style)
def _init_glyph(self, plot, mapping, properties, key):
"""
Returns a Bokeh glyph object.
"""
properties = {k: v for k, v in properties.items() if 'legend' not in k}
if key == 'arrow_1':
source = properties.pop('source')
arrow_end = mapping.pop('arrow_end')
arrow_start = mapping.pop('arrow_start')
for p in ('alpha', 'color'):
v = properties.pop(p, None)
for t in ('line', 'fill'):
if v is None:
continue
key = '_'.join([t, p])
if key not in properties:
properties[key] = v
start = arrow_start(**properties) if arrow_start else None
end = arrow_end(**properties) if arrow_end else None
line_props = {p: v for p, v in properties.items() if p.startswith('line_')}
renderer = Arrow(start=start, end=end, source=source,
**dict(line_props, **mapping))
glyph = renderer
else:
properties = {p if p == 'source' else 'text_'+p: v
for p, v in properties.items()}
renderer, glyph = super(ArrowPlot, self)._init_glyph(
plot, mapping, properties, key)
plot.renderers.append(renderer)
return renderer, glyph
[docs] def get_extents(self, element, ranges=None, range_type='combined'):
return None, None, None, None
[docs]class DivPlot(BokehPlot, GenericElementPlot, AnnotationPlot):
height = param.Number(default=300)
width = param.Number(default=300)
sizing_mode = param.ObjectSelector(default=None, objects=[
'fixed', 'stretch_width', 'stretch_height', 'stretch_both',
'scale_width', 'scale_height', 'scale_both', None], doc="""
How the component should size itself.
* "fixed" :
Component is not responsive. It will retain its original
width and height regardless of any subsequent browser window
resize events.
* "stretch_width"
Component will responsively resize to stretch to the
available width, without maintaining any aspect ratio. The
height of the component depends on the type of the component
and may be fixed or fit to component's contents.
* "stretch_height"
Component will responsively resize to stretch to the
available height, without maintaining any aspect ratio. The
width of the component depends on the type of the component
and may be fixed or fit to component's contents.
* "stretch_both"
Component is completely responsive, independently in width
and height, and will occupy all the available horizontal and
vertical space, even if this changes the aspect ratio of the
component.
* "scale_width"
Component will responsively resize to stretch to the
available width, while maintaining the original or provided
aspect ratio.
* "scale_height"
Component will responsively resize to stretch to the
available height, while maintaining the original or provided
aspect ratio.
* "scale_both"
Component will responsively resize to both the available
width and height, while maintaining the original or provided
aspect ratio.
""")
finalize_hooks = param.HookList(default=[], doc="""
Deprecated; use hooks options instead.""")
hooks = param.HookList(default=[], doc="""
Optional list of hooks called when finalizing a plot. The
hook is passed the plot object and the displayed element, and
other plotting handles can be accessed via plot.handles.""")
_stream_data = False
selection_display = None
def __init__(self, element, plot=None, **params):
super(DivPlot, self).__init__(element, **params)
self.callbacks = []
self.handles = {} if plot is None else self.handles['plot']
self.static = len(self.hmap) == 1 and len(self.keys) == len(self.hmap)
[docs] def get_data(self, element, ranges, style):
return element.data, {}, style
[docs] def initialize_plot(self, ranges=None, plot=None, plots=None, source=None):
"""
Initializes a new plot object with the last available frame.
"""
# Get element key and ranges for frame
element = self.hmap.last
key = self.keys[-1]
self.current_frame = element
self.current_key = key
data, _, _ = self.get_data(element, ranges, {})
div = HTML(text=data, width=self.width, height=self.height,
sizing_mode=self.sizing_mode)
self.handles['plot'] = div
self._execute_hooks(element)
self.drawn = True
return div
[docs] def update_frame(self, key, ranges=None, plot=None):
"""
Updates an existing plot with data corresponding
to the key.
"""
element = self._get_frame(key)
text, _, _ = self.get_data(element, ranges, {})
self.state.update(text=text, sizing_mode=self.sizing_mode)
