Source code for holoviews.plotting.bokeh.annotation

from __future__ import absolute_import, division, unicode_literals

from collections import defaultdict

try:
    from html import escape
except:
    from cgi import escape

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=escape(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)