Source code for holoviews.plotting.bokeh.annotation

from collections import defaultdict

import param
import numpy as np
from bokeh.models import Span, Arrow, Div as BkDiv
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 ...core.util import datetime_types, dimension_sanitizer, basestring
from ...element import HLine
from ..plot import GenericElementPlot
from .element import (ElementPlot, CompositeElementPlot, ColorbarPlot,
                      text_properties, line_properties)
from .plot import BokehPlot
from .util import date_to_integer


class TextPlot(ElementPlot):

    style_opts = text_properties+['color']
    _plot_methods = dict(single='text', batched='text')

    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')
        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

    def get_extents(self, element, ranges=None):
        return None, None, None, None



class LabelsPlot(ColorbarPlot):

    color_index = param.ClassSelector(default=None, class_=(basestring, int),
                                      allow_None=True, doc="""
      Index of the dimension from which the color will the drawn""")

    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.""")

    style_opts = text_properties + ['cmap']

    _plot_methods = dict(single='text', batched='text')
    _batched_style_opts = text_properties

    def get_data(self, element, ranges, style):
        style = self.style[self.cyclic_index]
        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:
            data[xdim] = data[xdim] + self.xoffset
        if self.yoffset is not None:
            data[ydim] = data[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')
        data['text_color'] = cdata[dimension_sanitizer(cdim.name)]
        mapping['text_color'] = cmapping['text_color']
        return data, mapping, style



class LineAnnotationPlot(ElementPlot):

    style_opts = line_properties

    _plot_methods = dict(single='Span')

    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='annotation', **mapping)
        plot.renderers.append(box)
        return None, box

    def get_extents(self, element, ranges=None):
        return None, None, None, None



[docs]class SplinePlot(ElementPlot): """ Draw the supplied Spline annotation (see Spline docstring). Does not support matplotlib Path codes. """ style_opts = line_properties _plot_methods = dict(single='bezier') 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.warning('Bokeh SplitPlot 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)
class ArrowPlot(CompositeElementPlot): style_opts = (['arrow_%s' % p for p in line_properties+['size']] + text_properties) _style_groups = {'arrow': 'arrow', 'label': 'text'} def get_data(self, element, ranges, style): plot = self.state label_mapping = dict(x='x', y='y', text='text') # 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_opts = {'x_end': x1, 'y_end': y1, 'x_start': x2, 'y_start': y2} # Define arrowhead arrow_opts['arrow_start'] = arrow_start.get(element.arrowstyle, None) arrow_opts['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 ({'label': label_data}, {'arrow': arrow_opts, 'label': label_mapping}, style) def _init_glyph(self, plot, mapping, properties, key): """ Returns a Bokeh glyph object. """ properties.pop('legend', None) if key == 'arrow': properties.pop('source') arrow_end = mapping.pop('arrow_end') arrow_start = mapping.pop('arrow_start') start = arrow_start(**properties) if arrow_start else None end = arrow_end(**properties) if arrow_end else None glyph = Arrow(start=start, end=end, **dict(**mapping)) else: properties = {p if p == 'source' else 'text_'+p: v for p, v in properties.items()} glyph, _ = super(ArrowPlot, self)._init_glyph( plot, mapping, properties, 'text_1') plot.renderers.append(glyph) return None, glyph def get_extents(self, element, ranges=None): return None, None, None, None class DivPlot(BokehPlot, GenericElementPlot): height = param.Number(default=300) width = param.Number(default=300) finalize_hooks = param.HookList(default=[], doc=""" Optional list of hooks called when finalizing a column. The hook is passed the plot object and the displayed object, and other plotting handles can be accessed via plot.handles.""") _stream_data = False 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'] def get_data(self, element, ranges, style): return element.data, {}, style 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 = BkDiv(text=data, width=self.width, height=self.height) self.handles['plot'] = div self._execute_hooks(element) self.drawn = True return div 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.handles['plot'].text = text