Source code for holoviews.plotting.bokeh.widgets

from __future__ import unicode_literals

import math
import json
from functools import partial

import param
import numpy as np
from bokeh.models.widgets import Select, Slider, AutocompleteInput, TextInput, Div
from bokeh.layouts import widgetbox, row, column

from ...core import Store, NdMapping, OrderedDict
from ...core.util import (drop_streams, unique_array, isnumeric,
                          wrap_tuple_streams, unicode)
from ..renderer import MIME_TYPES
from ..widgets import NdWidget, SelectionWidget, ScrubberWidget
from .util import serialize_json



[docs]class BokehServerWidgets(param.Parameterized): """ BokehServerWidgets create bokeh widgets corresponding to all the key dimensions found on a BokehPlot instance. It currently supports to types of widgets sliders (which may be discrete or continuous) and dropdown widgets letting you select non-numeric values. """ display_options = param.Dict(default={}, doc=""" Additional options controlling display options of the widgets.""") editable = param.Boolean(default=False, doc=""" Whether the slider text fields should be editable. Disabled by default for a more compact widget layout.""") position = param.ObjectSelector(default='right', objects=['right', 'left', 'above', 'below']) sizing_mode = param.ObjectSelector(default='fixed', objects=['fixed', 'stretch_both', 'scale_width', 'scale_height', 'scale_both']) width = param.Integer(default=250, doc=""" Width of the widget box in pixels""") basejs = param.String(default=None, precedence=-1, doc=""" Defines the local CSS file to be loaded for this widget.""") extensionjs = param.String(default=None, precedence=-1, doc=""" Optional javascript extension file for a particular backend.""") css = param.String(default=None, precedence=-1, doc=""" Defines the local CSS file to be loaded for this widget.""") def __init__(self, plot, renderer=None, **params): super(BokehServerWidgets, self).__init__(**params) self.plot = plot streams = [] for stream in plot.streams: if any(k in plot.dimensions for k in stream.contents): streams.append(stream) self.dimensions, self.keys = drop_streams(streams, plot.dimensions, plot.keys) if renderer is None: backend = Store.current_backend self.renderer = Store.renderers[backend] else: self.renderer = renderer # Create mock NdMapping to hold the common dimensions and keys self.mock_obj = NdMapping([(k, None) for k in self.keys], kdims=list(self.dimensions)) self.widgets, self.lookups = self.get_widgets() self.subplots = {} if self.plot.renderer.mode == 'default': self.attach_callbacks() self.state = self.init_layout() self._queue = [] self._active = False
[docs] @classmethod def create_widget(self, dim, holomap=None, editable=False): """" Given a Dimension creates bokeh widgets to select along that dimension. For numeric data a slider widget is created which may be either discrete, if a holomap is supplied or the Dimension.values are set, or a continuous widget for DynamicMaps. If the slider is discrete the returned mapping defines a mapping between values and labels making it possible sync the two slider and label widgets. For non-numeric data a simple dropdown selection widget is generated. """ label, mapping = None, None if holomap is None: if dim.values: if dim.default is None: default = dim.values[0] elif dim.default not in dim.values: raise ValueError("%s dimension default %r is not in dimension values: %s" % (dim, dim.default, dim.values)) else: default = dim.default value = dim.values.index(default) if all(isnumeric(v) for v in dim.values): values = sorted(dim.values) labels = [unicode(dim.pprint_value(v)) for v in values] if editable: label = AutocompleteInput(value=labels[value], completions=labels, title=dim.pprint_label) else: label = Div(text='<b>%s</b>' % dim.pprint_value_string(labels[value])) widget = Slider(value=value, start=0, end=len(dim.values)-1, title=None, step=1) mapping = list(enumerate(zip(values, labels))) else: values = [(v, dim.pprint_value(v)) for v in dim.values] widget = Select(title=dim.pprint_label, value=values[value][0], options=values) else: start = dim.soft_range[0] if dim.soft_range[0] else dim.range[0] end = dim.soft_range[1] if dim.soft_range[1] else dim.range[1] dim_range = end - start int_type = isinstance(dim.type, type) and issubclass(dim.type, int) if dim.step is not None: step = dim.step elif isinstance(dim_range, int) or int_type: step = 1 else: step = 10**((round(math.log10(dim_range))-3)) if dim.default is None: default = start elif (dim.default < start or dim.default > end): raise ValueError("%s dimension default %r is not in the provided range: %s" % (dim, dim.default, (start, end))) else: default = dim.default if editable: label = TextInput(value=str(default), title=dim.pprint_label) else: label = Div(text='<b>%s</b>' % dim.pprint_value_string(default)) widget = Slider(value=default, start=start, end=end, step=step, title=None) else: values = (dim.values if dim.values else list(unique_array(holomap.dimension_values(dim.name)))) if dim.default is None: default = values[0] elif dim.default not in values: raise ValueError("%s dimension default %r is not in dimension values: %s" % (dim, dim.default, values)) else: default = dim.default if isinstance(values[0], np.datetime64) or isnumeric(values[0]): values = sorted(values) labels = [dim.pprint_value(v) for v in values] value = values.index(default) if editable: label = AutocompleteInput(value=labels[value], completions=labels, title=dim.pprint_label) else: label = Div(text='<b>%s</b>' % (dim.pprint_value_string(labels[value]))) widget = Slider(value=value, start=0, end=len(values)-1, title=None, step=1) else: labels = [dim.pprint_value(v) for v in values] widget = Select(title=dim.pprint_label, value=default, options=list(zip(values, labels))) mapping = list(enumerate(zip(values, labels))) return widget, label, mapping
[docs] def get_widgets(self): """ Creates a set of widgets representing the dimensions on the plot object used to instantiate the widgets class. """ widgets = OrderedDict() mappings = {} for dim in self.mock_obj.kdims: holomap = None if self.plot.dynamic else self.mock_obj widget, label, mapping = self.create_widget(dim, holomap, self.editable) if label is not None and not isinstance(label, Div): label.on_change('value', partial(self.on_change, dim, 'label')) widget.on_change('value', partial(self.on_change, dim, 'widget')) widgets[dim.pprint_label] = (label, widget) if mapping: mappings[dim.pprint_label] = OrderedDict(mapping) return widgets, mappings
def init_layout(self): widgets = [widget for d in self.widgets.values() for widget in d if widget] wbox = widgetbox(widgets, width=self.width) if self.position in ['right', 'below']: plots = [self.plot.state, wbox] else: plots = [wbox, self.plot.state] layout_fn = row if self.position in ['left', 'right'] else column layout = layout_fn(plots, sizing_mode=self.sizing_mode) return layout
[docs] def attach_callbacks(self): """ Attach callbacks to interact with Comms. """ pass
def on_change(self, dim, widget_type, attr, old, new): self._queue.append((dim, widget_type, attr, old, new)) if not self._active: self.plot.document.add_timeout_callback(self.update, 50) self._active = True
[docs] def update(self): """ Handle update events on bokeh server. """ if not self._queue: return dim, widget_type, attr, old, new = self._queue[-1] self._queue = [] dim_label = dim.pprint_label label, widget = self.widgets[dim_label] if widget_type == 'label': if isinstance(label, AutocompleteInput): value = [new] widget.value = value else: widget.value = float(new) elif label: lookups = self.lookups.get(dim_label) if not self.editable: if lookups: new = lookups[widget.value][1] label.text = '<b>%s</b>' % dim.pprint_value_string(new) elif isinstance(label, AutocompleteInput): text = lookups[new][1] label.value = text else: label.value = dim.pprint_value(new) key = [] for dim, (label, widget) in self.widgets.items(): lookups = self.lookups.get(dim) if label and lookups: val = lookups[widget.value][0] else: val = widget.value key.append(val) key = wrap_tuple_streams(tuple(key), self.plot.dimensions, self.plot.streams) self.plot.update(key) self._active = False
class BokehWidget(NdWidget): css = param.String(default='bokehwidgets.css', doc=""" Defines the local CSS file to be loaded for this widget.""") extensionjs = param.String(default='bokehwidgets.js', doc=""" Optional javascript extension file for a particular backend.""") def _get_data(self): # Get initial frame to draw immediately msg, metadata = self.renderer.components(self.plot, comm=False) data = super(BokehWidget, self)._get_data() return dict(data, init_html=msg['text/html'], init_js=msg[MIME_TYPES['js']], plot_id=self.plot.state._id) def encode_frames(self, frames): if self.export_json: self.save_json(frames) frames = {} else: frames = json.dumps(frames).replace('</', r'<\/') return frames def get_frames(self): nframes = len(self.plot) if self.embed: self.plot.update(nframes-1) frames = OrderedDict([(idx, self._plot_figure(idx)) for idx in range(nframes)]) else: frames = {} return self.encode_frames(frames) def _plot_figure(self, idx, fig_format='json'): """ Returns the figure in html format on the first call and """ self.plot.update(idx) if self.embed: patch = self.renderer.diff(self.plot, binary=False) msg = serialize_json(dict(content=patch.content, root=self.plot.state._id)) return msg class BokehSelectionWidget(BokehWidget, SelectionWidget): pass class BokehScrubberWidget(BokehWidget, ScrubberWidget): pass