def test_application_doesnt_validate_document_due_to_env_var(check_integrity, monkeypatch):
monkeypatch.setenv("BOKEH_VALIDATE_DOC", "false")
a = Application()
d = Document()
d.add_root(figure())
a.initialize_document(d)
assert not check_integrity.called
def test_with_doc(self, test_plot, test_table):
from bokeh.models import Button
d = Document()
d.add_root(test_plot)
d.add_root(test_table)
assert beb._any([d], lambda x: isinstance(x, object)) is True
assert beb._any([d], lambda x: isinstance(x, Button)) is False
def test_without_widgets(self, test_plot, test_glplot, test_table, test_widget):
assert beb._use_widgets([test_plot]) is False
assert beb._use_widgets([test_plot, test_glplot]) is False
d = Document()
d.add_root(test_plot)
d.add_root(test_glplot)
assert beb._use_widgets([d]) is False
def init_plot(crawl_name):
session = Session()
document = Document()
session.use_doc(crawl_name)
session.load_document(document)
if document.context.children:
plot = document.context.children[0]
else:
output_server(crawl_name)
# TODO: Remove these when Bokeh is upgraded
# placeholders or Bokeh can't inject properly
current = np.datetime64(datetime.now())
xdr = Range1d(current, current + 1)
ydr = ["urls"]
# styling suggested by Bryan
plot = figure(title="Crawler Monitor", tools="hover",
x_axis_type="datetime", y_axis_location="right", x_range=xdr, y_range=ydr,
width=1200, height=600)
plot.toolbar_location = None
plot.xgrid.grid_line_color = None
document.add(plot)
session.store_document(document)
script = autoload_server(plot, session)
#TODO: Looks like a Bokeh bug, probably not repeatable with current code
script = script.replace("'modelid': u'", "'modelid': '")
return script
def test_width(self):
p = figure(plot_width=200, plot_height=300)
d = Document()
d.add_root(p)
util.set_single_plot_width_height(d, 400, None)
assert p.plot_width == 400
assert p.plot_height == 300
def test_document_bad_on_session_destroyed_signature(self):
doc = Document()
def destroy(a, b):
pass
with pytest.raises(ValueError):
doc.on_session_destroyed(destroy)
def test_layout(self):
p = figure(plot_width=200, plot_height=300)
d = Document()
d.add_root(row(p))
with pytest.warns(UserWarning) as warns:
util.set_single_plot_width_height(d, 400, 500)
assert len(warns) == 1
assert warns[0].message.args[0] == _SIZE_WARNING
def index():
plot = figure()
plot.circle([1,2], [3,4])
document = Document()
document.add_root(plot)
session = push_session(document)
script = autoload_server(None, session_id=session.id)
return render_template('index.html', bokeh_script=script)
def test_compute_remove_root_patch(self):
from bokeh.document import Document
d = Document()
root1 = SomeModelInTestDocument(foo=42)
child1 = AnotherModelInTestDocument(bar=43)
root1.child = child1
d.add_root(root1)
before = d.to_json()
d.remove_root(root1)
after = d.to_json()
patch = Document._compute_patch_between_json(before, after)
expected = dict(references=[],
events= [
{'kind': 'RootRemoved',
'model': {'id': None,
'type': 'SomeModelInTestDocument'}}
])
expected['events'][0]['model']['id'] = root1._id
self.assertDictEqual(expected, patch)
d2 = Document.from_json(before)
d2.apply_json_patch(patch)
self.assertEqual([], d2.roots)
def test_compute_add_root_patch(self):
from bokeh.document import Document
d = Document()
root1 = SomeModelInTestDocument(foo=42)
child1 = AnotherModelInTestDocument(bar=43)
root1.child = child1
d.add_root(root1)
before = d.to_json()
root2 = SomeModelInTestDocument(foo=57)
d.add_root(root2)
after = d.to_json()
patch = Document._compute_patch_between_json(before, after)
expected = {
"references": [{"attributes": {"child": None, "foo": 57}, "id": None, "type": "SomeModelInTestDocument"}],
"events": [{"kind": "RootAdded", "model": {"id": None, "type": "SomeModelInTestDocument"}}],
}
expected["references"][0]["id"] = root2._id
expected["events"][0]["model"]["id"] = root2._id
self.assertDictEqual(expected, patch)
d2 = Document.from_json(before)
d2.apply_json_patch(patch)
self.assertEqual(2, len(d2.roots))
self.assertEqual(42, d2.roots[0].foo)
self.assertEqual(57, d2.roots[1].foo)
def test_compute_remove_root_patch(self):
from bokeh.document import Document
d = Document()
root1 = SomeModelInTestDocument(foo=42)
child1 = AnotherModelInTestDocument(bar=43)
root1.child = child1
d.add_root(root1)
before = d.to_json()
d.remove_root(root1)
after = d.to_json()
patch = Document._compute_patch_between_json(before, after)
expected = dict(
references=[], events=[{"kind": "RootRemoved", "model": {"id": None, "type": "SomeModelInTestDocument"}}]
)
expected["events"][0]["model"]["id"] = root1._id
self.assertDictEqual(expected, patch)
d2 = Document.from_json(before)
d2.apply_json_patch(patch)
self.assertEqual([], d2.roots)
def go(self):
"""Displays the application"""
document = Document()
document.title = "UT330 UI"
document.add_root(self.tabs)
session = push_session(document)
session.show()
session.loop_until_closed()
def test_with_doc_in_child_raises_error(self):
doc = Document()
p1 = Model()
p2 = SomeModelInTestObjects(child=Model())
doc.add_root(p2.child)
self.assertIs(p1.document, None)
self.assertIs(p2.document, None)
self.assertIs(p2.child.document, doc)
with self.assertRaisesRegexp(RuntimeError, p2._id):
with _ModelInDocument([p1, p2]):
self.assertIsNot(p1.document, None)
self.assertIsNot(p2.document, None)
self.assertIs(p1.document, doc)
self.assertIs(p2.document, doc)
def get_bokeh_script(user, plot, suffix):
from .models import UserSession
document = Document()
document.add_root(plot)
document.title = suffix
with closing(push_session(document)) as session:
# Save the session id to a UserSession
UserSession.objects.create(user=user, bokeh_session_id=session.id)
# Get the script to pass into the template
script = autoload_server(None, session_id=session.id)
return script
def test_document_on_session_destroyed(self):
doc = Document()
handler = bahd.DocumentLifecycleHandler()
def destroy(session_context):
assert doc is session_context._document
session_context.status = 'Destroyed'
doc.on_session_destroyed(destroy)
session_context = MockSessionContext(doc)
handler.on_session_destroyed(session_context)
assert session_context.status == 'Destroyed'
assert session_context._document.session_destroyed_callbacks == set()
def test_with_doc_in_child_raises_error(self):
doc = Document()
p1 = Model()
p2 = SomeModelInTestObjects(child=Model())
doc.add_root(p2.child)
assert p1.document is None
assert p2.document is None
assert p2.child.document is doc
with pytest.raises(RuntimeError):
with bes._ModelInDocument([p1, p2]):
assert p1.document is not None
assert p2.document is not None
assert p1.document is doc
assert p2.document is doc
def get_bokeh_script(plot):
from .models import UserSession
document = Document()
document.add_root(plot)
with closing(push_session(document, url=bokeh_url)) as session:
# Save the session id
UserSession.objects.create(user=User.objects.get(),
bokehSessionId=session.id)
# Get the script to pass into the template
script = autoload_server(None, session_id=session.id, url=bokeh_url)
return script
def get_plot(self_or_cls, obj, doc=None, renderer=None, **kwargs):
"""
Given a HoloViews Viewable return a corresponding plot instance.
Allows supplying a document attach the plot to, useful when
combining the bokeh model with another plot.
"""
if doc is None:
doc = Document() if self_or_cls.notebook_context else curdoc()
if self_or_cls.notebook_context:
curdoc().theme = self_or_cls.theme
doc.theme = self_or_cls.theme
plot = super(BokehRenderer, self_or_cls).get_plot(obj, renderer, **kwargs)
plot.document = doc
return plot
def create_session_if_needed(self, session_id, request=None):
# this is because empty session_ids would be "falsey" and
# potentially open up a way for clients to confuse us
if len(session_id) == 0:
raise ProtocolError("Session ID must not be empty")
if session_id not in self._sessions and \
session_id not in self._pending_sessions:
future = self._pending_sessions[session_id] = gen.Future()
doc = Document()
session_context = BokehSessionContext(session_id,
self.server_context,
doc)
# using private attr so users only have access to a read-only property
session_context._request = request
# expose the session context to the document
# use the _attribute to set the public property .session_context
doc._session_context = session_context
try:
yield yield_for_all_futures(self._application.on_session_created(session_context))
except Exception as e:
log.error("Failed to run session creation hooks %r", e, exc_info=True)
self._application.initialize_document(doc)
session = ServerSession(session_id, doc, io_loop=self._loop)
del self._pending_sessions[session_id]
self._sessions[session_id] = session
session_context._set_session(session)
self._session_contexts[session_id] = session_context
# notify anyone waiting on the pending session
future.set_result(session)
if session_id in self._pending_sessions:
# another create_session_if_needed is working on
# creating this session
session = yield self._pending_sessions[session_id]
else:
session = self._sessions[session_id]
raise gen.Return(session)
def feature_scatterplot(fset_path, features_to_plot):
"""Create scatter plot of feature set.
Parameters
----------
fset_path : str
Path to feature set to be plotted.
features_to_plot : list of str
List of feature names to be plotted.
Returns
-------
(str, str)
Returns (docs_json, render_items) json for the desired plot.
"""
fset, data = featurize.load_featureset(fset_path)
fset = fset[features_to_plot]
colors = cycle(palette[5])
plots = np.array([[figure(width=300, height=200)
for j in range(len(features_to_plot))]
for i in range(len(features_to_plot))])
for (j, i), p in np.ndenumerate(plots):
if (j == i == 0):
p.title.text = "Scatterplot matrix"
p.circle(fset.values[:,i], fset.values[:,j], color=next(colors))
p.xaxis.minor_tick_line_color = None
p.yaxis.minor_tick_line_color = None
p.ygrid[0].ticker.desired_num_ticks = 2
p.xgrid[0].ticker.desired_num_ticks = 4
p.outline_line_color = None
p.axis.visible = None
plot = gridplot(plots.tolist(), ncol=len(features_to_plot), mergetools=True, responsive=True, title="Test")
# Convert plot to json objects necessary for rendering with bokeh on the
# frontend
render_items = [{'docid': plot._id, 'elementid': make_id()}]
doc = Document()
doc.add_root(plot)
docs_json_inner = doc.to_json()
docs_json = {render_items[0]['docid']: docs_json_inner}
docs_json = serialize_json(docs_json)
render_items = serialize_json(render_items)
return docs_json, render_items
def test_entire_doc_is_not_used(self):
from bokeh.document import Document
from bokeh.models import Button
fig = figure()
fig.x([0], [0])
button = Button(label="Button")
d = Document()
d.add_root(fig)
d.add_root(button)
out = bes.file_html([fig], CDN)
# this is a very coarse test but it will do
assert "bokeh-widgets" not in out
def compute_static_patch(document, models, json=None):
"""
Computes a patch to update an existing document without
diffing the json first, making it suitable for static updates
between arbitrary frames. Note that this only supports changed
attributes and will break if new models have been added since
the plot was first created.
"""
references = refs(json if json else document.to_json())
requested_updates = [m.ref['id'] for m in models]
value_refs = {}
events = []
update_types = defaultdict(list)
for ref_id, obj in references.items():
if ref_id not in requested_updates:
continue
if obj['type'] in MODEL_PRIORITY:
priority = MODEL_PRIORITY.index(obj['type'])
else:
priority = float('inf')
for key, val in obj['attributes'].items():
event = Document._event_for_attribute_change(references,
obj, key, val,
value_refs)
events.append((priority, event))
update_types[obj['type']].append(key)
events = [delete_refs(e, LOCATIONS, IGNORED_MODELS)
for _, e in sorted(events, key=lambda x: x[0])]
value_refs = {ref_id: delete_refs(val, LOCATIONS, IGNORED_MODELS)
for ref_id, val in value_refs.items()}
references = [val for val in value_refs.values()
if val is not None]
return dict(events=events, references=references)
def wrapper(*args, **kwargs):
document = Document()
session = Session(name=url, root_url=url)
session.use_doc(document.docid)
session.load_document(document)
session.publish()
document.autoadd = False
document.autostore = False
obj = func(*args, **kwargs)
obj._docid = session.docid
obj._root_url = session.root_url
document.add(obj)
session.store_document(document)
return obj
def test_uses_precedent_from_child(self):
doc = Document()
p1 = Model()
p2 = SomeModelInTestObjects(child=Model())
doc.add_root(p2.child)
self.assertIs(p1.document, None)
self.assertIs(p2.document, None)
self.assertIs(p2.child.document, doc)
with _ModelInDocument([p1, p2]):
self.assertIsNot(p1.document, None)
self.assertIsNot(p2.document, None)
self.assertIs(p1.document, doc)
self.assertIs(p2.document, doc)
self.assertIs(p1.document, None)
self.assertIs(p2.document, None)
self.assertIsNot(p2.child.document, None)
self.assertIs(p2.child.document, doc)
def test_uses_precedent(self):
# it's deliberate that the doc is on p2, so _ModelInDocument
# has to be smart about looking for a doc anywhere in the list
# before it starts inventing new documents
doc = Document()
p1 = Model()
p2 = Model()
doc.add_root(p2)
self.assertIs(p1.document, None)
self.assertIsNot(p2.document, None)
with _ModelInDocument([p1, p2]):
self.assertIsNot(p1.document, None)
self.assertIsNot(p2.document, None)
self.assertIs(p1.document, doc)
self.assertIs(p2.document, doc)
self.assertIs(p1.document, None)
self.assertIsNot(p2.document, None)
def test_document_on_session_destroyed_calls_multiple(self):
doc = Document()
def increment(session_context):
session_context.counter += 1
doc.on_session_destroyed(increment)
def increment_by_two(session_context):
session_context.counter += 2
doc.on_session_destroyed(increment_by_two)
handler = bahd.DocumentLifecycleHandler()
session_context = MockSessionContext(doc)
handler.on_session_destroyed(session_context)
assert session_context.counter == 3, 'DocumentLifecycleHandler did not call all callbacks'
def test_uses_precedent(self):
# it's deliberate that the doc is on p2, so _ModelInDocument
# has to be smart about looking for a doc anywhere in the list
# before it starts inventing new documents
doc = Document()
p1 = Model()
p2 = Model()
doc.add_root(p2)
assert p1.document is None
assert p2.document is not None
with bes._ModelInDocument([p1, p2]):
assert p1.document is not None
assert p2.document is not None
assert p1.document is doc
assert p2.document is doc
assert p1.document is None
assert p2.document is not None
def test_compute_one_attribute_patch(self):
from bokeh.document import Document
d = Document()
root1 = SomeModelInTestDocument(foo=42)
child1 = SomeModelInTestDocument(foo=43)
root1.child = child1
d.add_root(root1)
before = d.to_json()
root1.foo = 47
after = d.to_json()
patch = Document._compute_patch_between_json(before, after)
expected = dict(references=[],
events=[
{'attr': u'foo',
'kind': 'ModelChanged',
'model': {'id': None,
'type': 'SomeModelInTestDocument'},
'new': 47}
])
expected['events'][0]['model']['id'] = root1._id
self.assertDictEqual(expected, patch)
d2 = Document.from_json(before)
d2.apply_json_patch(patch)
self.assertEqual(root1.foo, d2.roots[0].foo)
def test_compute_one_attribute_patch(self):
from bokeh.document import Document
d = Document()
root1 = SomeModelInTestDocument(foo=42)
child1 = SomeModelInTestDocument(foo=43)
root1.child = child1
d.add_root(root1)
before = d.to_json()
root1.foo = 47
after = d.to_json()
patch = Document._compute_patch_between_json(before, after)
expected = dict(
references=[],
events=[
{
"attr": u"foo",
"kind": "ModelChanged",
"model": {"id": None, "type": "SomeModelInTestDocument"},
"new": 47,
}
],
)
expected["events"][0]["model"]["id"] = root1._id
self.assertDictEqual(expected, patch)
d2 = Document.from_json(before)
d2.apply_json_patch(patch)
self.assertEqual(root1.foo, d2.roots[0].foo)
def plot_code_iterator(self):
"""
Iterator over the single bokeh plot
:return: Tuple of js-script code for the plot and number of invalid
values
"""
for index, dummy in enumerate(self.__conf.filter_args):
if self.__index is not None and self.__index != index:
continue
document = Document()
document.title = self.__conf.description
self.__factors, self.__values, num_invalid = \
self.create_x_y_values(index)
plot = self.__create_control_chart_hist(index)
document.add_root(plot)
session_id = self.__save_user_session(document, index)
script = autoload_server(None, session_id=session_id)
yield script, num_invalid
def components(self, obj, fmt=None, comm=True, **kwargs):
"""
Returns data and metadata dictionaries containing HTML and JS
components to include render in app, notebook, or standalone
document.
"""
if isinstance(obj, Plot):
plot = obj
else:
plot, fmt = self._validate(obj, fmt)
data, metadata = {}, {}
if isinstance(plot, Viewable):
registry = list(Stream.registry.items())
objects = plot.object.traverse(lambda x: x)
dynamic, streams = False, False
for source in objects:
dynamic |= isinstance(source, DynamicMap)
streams |= any(
src is source or (src._plot_id is not None
and src._plot_id == source._plot_id)
for src, streams in registry for s in streams)
embed = (not (dynamic or streams or self.widget_mode == 'live')
or config.embed)
# This part should be factored out in Panel and then imported
# here for HoloViews 2.0, which will be able to require a
# recent Panel version.
if embed or config.comms == 'default':
comm = self.comm_manager.get_server_comm() if comm else None
doc = Document()
with config.set(embed=embed):
model = plot.layout._render_model(doc, comm)
if embed:
return render_model(model, comm)
args = (model, doc, comm)
if panel_version > '0.9.3':
from panel.models.comm_manager import CommManager
ref = model.ref['id']
manager = CommManager(comm_id=comm.id, plot_id=ref)
client_comm = self.comm_manager.get_client_comm(
on_msg=partial(plot._on_msg, ref, manager),
on_error=partial(plot._on_error, ref),
on_stdout=partial(plot._on_stdout, ref))
manager.client_comm_id = client_comm.id
args = args + (manager, )
return render_mimebundle(*args)
# Handle rendering object as ipywidget
widget = ipywidget(plot, combine_events=True)
if hasattr(widget, '_repr_mimebundle_'):
return widget._repr_mimebundle()
plaintext = repr(widget)
if len(plaintext) > 110:
plaintext = plaintext[:110] + '…'
data = {
'text/plain': plaintext,
}
if widget._view_name is not None:
data['application/vnd.jupyter.widget-view+json'] = {
'version_major': 2,
'version_minor': 0,
'model_id': widget._model_id
}
if config.comms == 'vscode':
# Unfortunately VSCode does not yet handle _repr_mimebundle_
from IPython.display import display
display(data, raw=True)
return {'text/html': '<div style="display: none"></div>'}, {}
return data, {}
else:
html = self._figure_data(plot, fmt, as_script=True, **kwargs)
data['text/html'] = html
return (data, {MIME_TYPES['jlab-hv-exec']: metadata})
xaxis = CategoricalAxis()
xaxis.major_label_text_font_size = "8pt"
xaxis.major_label_standoff = 0
xaxis.major_tick_line_color = None
xaxis.axis_line_color = None
plot.add_layout(xaxis, 'above')
hover_tool = HoverTool(plot=plot,
renderers=[rect_renderer],
tooltips=[("Holiday", "@month_holidays")])
plot.tools.append(hover_tool)
return plot
months = [[make_calendar(2014, 3 * i + j + 1) for j in range(3)]
for i in range(4)]
grid = gridplot(toolbar_location=None, children=months)
doc = Document()
doc.add_root(grid)
if __name__ == "__main__":
doc.validate()
filename = "calendars.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Calendar 2014"))
print("Wrote %s" % filename)
view(filename)
menu = [("Item 1", "item_1"), ("Item 2", "item_2"), None, ("Item 3", "item_3")]
dropdown = Dropdown(label="Dropdown button", button_type="warning", menu=menu)
dropdown.on_click(dropdown_handler)
menu = [("Item 1", "foo"), ("Item 2", "bar"), None, ("Item 3", "baz")]
split = Dropdown(label="Split button", button_type="danger", menu=menu, default_value="baz")
split.on_click(split_handler)
checkbox_group = CheckboxGroup(labels=["Option 1", "Option 2", "Option 3"], active=[0, 1])
checkbox_group.on_click(checkbox_group_handler)
radio_group = RadioGroup(labels=["Option 1", "Option 2", "Option 3"], active=0)
radio_group.on_click(radio_group_handler)
checkbox_button_group = CheckboxButtonGroup(labels=["Option 1", "Option 2", "Option 3"], active=[0, 1])
checkbox_button_group.on_click(checkbox_button_group_handler)
radio_button_group = RadioButtonGroup(labels=["Option 1", "Option 2", "Option 3"], active=0)
radio_button_group.on_click(radio_button_group_handler)
vbox = VBox(children=[button, toggle, dropdown, split, checkbox_group, radio_group, checkbox_button_group, radio_button_group])
document = Document()
document.add_root(vbox)
session = push_session(document)
session.show()
if __name__ == "__main__":
session.loop_until_closed()
def document():
return Document()
def test_setting_built_in_theme_missing(self):
obj = SomeModel()
doc = Document()
doc.add_root(obj)
with pytest.raises(ValueError):
doc.theme = 'some_theme_i_guess'
from math import sqrt, pi
import pandas as pd
from ldadata import data
from bokeh.models import ColumnDataSource, LinearAxis, CategoricalAxis, Plot, DataRange1d, FactorRange, GlyphRenderer, TapTool
from bokeh.models.glyphs import Circle, Text, Rect
from bokeh.models.widgets import TextInput, Button, Slider, HBox, VBox
from bokeh.browserlib import view
from bokeh.document import Document
from bokeh.session import Session
from bokeh.browserlib import view
document = Document()
session = Session()
session.use_doc('ldavis_server')
session.load_document(document)
print("MDSPLOT")
R = data["R"]
mds = pd.DataFrame.from_dict(data["mdsDat"])
lam = pd.DataFrame.from_dict(data["tinfo"])
barDefault2 = lam[lam.Category == "Default"]
mdswidth = 530
mdsheight = 530
def get_plot(self_or_cls,
obj,
doc=None,
renderer=None,
comm=None,
**kwargs):
"""
Given a HoloViews Viewable return a corresponding plot instance.
"""
if isinstance(obj, DynamicMap) and obj.unbounded:
dims = ', '.join('%r' % dim for dim in obj.unbounded)
msg = ('DynamicMap cannot be displayed without explicit indexing '
'as {dims} dimension(s) are unbounded. '
'\nSet dimensions bounds with the DynamicMap redim.range '
'or redim.values methods.')
raise SkipRendering(msg.format(dims=dims))
# Initialize DynamicMaps with first data item
initialize_dynamic(obj)
if not renderer:
renderer = self_or_cls
if not isinstance(self_or_cls, Renderer):
renderer = self_or_cls.instance()
if not isinstance(obj, Plot):
if not displayable(obj):
obj = collate(obj)
initialize_dynamic(obj)
with disable_pipeline():
obj = Compositor.map(obj,
mode='data',
backend=self_or_cls.backend)
plot_opts = dict(self_or_cls.plot_options(obj, self_or_cls.size),
**kwargs)
if isinstance(obj, AdjointLayout):
obj = Layout(obj)
plot = self_or_cls.plotting_class(obj)(obj,
renderer=renderer,
**plot_opts)
defaults = [kd.default for kd in plot.dimensions]
init_key = tuple(v if d is None else d
for v, d in zip(plot.keys[0], defaults))
plot.update(init_key)
else:
plot = obj
# Trigger streams which were marked as requiring an update
triggers = []
for p in plot.traverse():
if not hasattr(p, '_trigger'):
continue
for trigger in p._trigger:
if trigger not in triggers:
triggers.append(trigger)
p._trigger = []
for trigger in triggers:
Stream.trigger([trigger])
if isinstance(self_or_cls, Renderer):
self_or_cls.last_plot = plot
if comm:
plot.comm = comm
if comm or self_or_cls.mode == 'server':
if doc is None:
doc = Document() if self_or_cls.notebook_context else curdoc()
plot.document = doc
return plot
plot = Plot(title=None,
x_range=xdr,
y_range=ydr,
plot_width=300,
plot_height=300,
h_symmetry=False,
v_symmetry=False,
min_border=0,
toolbar_location=None)
glyph = Ray(x="x",
y="y",
length="l",
angle=-2.0,
line_color="#fb8072",
line_width=3)
plot.add_glyph(source, glyph)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
doc = Document()
doc.add(plot)
show(plot)
line_source = ColumnDataSource(dict(
x=data.dist,
y=data.alt,
))
line = Line(x='x', y='y', line_color="black", line_width=1)
plot.add_glyph(line_source, line)
plot.x_range = DataRange1d()
plot.y_range = DataRange1d()
return plot
data = prep_data(obiszow_mtb_xcm)
trail = trail_map(data)
altitude = altitude_profile(data)
layout = VBox(children=[altitude, trail])
doc = Document()
doc.add(layout)
if __name__ == "__main__":
filename = "trail.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Trail map and altitude profile"))
print("Wrote %s" % filename)
view(filename)
w="w1",
h="h1",
anchor="center",
global_alpha=0.2)
plot.add_glyph(source, image1)
image2 = ImageURL(url="url", x="x2", y="y2", w=20, h=20, anchor="top_left")
plot.add_glyph(source, image2)
image3 = ImageURL(url=dict(value=url), x=200, y=-100, anchor="bottom_right")
plot.add_glyph(source, image3)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
doc = Document()
doc.add_root(plot)
if __name__ == "__main__":
filename = "image_url.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Image URL Example"))
print("Wrote %s" % filename)
view(filename)
def test_doc_set():
s = state.State()
d = Document()
s.document = d
assert isinstance(s.document, Document)
assert s.document == d
def test_render_explicit_server_doc_element(self):
obj = Curve([])
doc = Document()
server_doc = bokeh_renderer.server_doc(obj, doc)
self.assertIs(server_doc, doc)
self.assertIs(bokeh_renderer.last_plot.document, doc)
angle = half_tooth(planet_teeth)
for i, j in [(+1, 0), (0, +1), (-1, 0), (0, -1)]:
glyph = Gear(x=radius * i,
y=radius * j,
module=module,
teeth=planet_teeth,
angle=angle,
fill_color=fill_color[1],
line_color=line_color)
plot.add_glyph(glyph)
return plot
doc = Document()
doc.add_root(sample_gear())
classical = classical_gear(5, 52, 24)
epicyclic = epicyclic_gear(5, 24, 12)
doc.add_root(classical)
doc.add_root(epicyclic)
if __name__ == "__main__":
filename = "gears.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Gears"))
print("Wrote %s" % filename)
view(filename)
def test_setting_built_in_theme_error(self):
obj = SomeModel()
doc = Document()
doc.add_root(obj)
with pytest.raises(ValueError):
doc.theme = 1337
def define_plot(
doc: Document,
rt_client: _StreamingClient,
channels: list,
tribe: RealTimeTribe,
inventory: Inventory,
detections: list,
map_options: dict,
plot_options: dict,
plot_length: float,
update_interval: int,
data_color: str = "grey",
lowcut: float = 1.0,
highcut: float = 10.0,
offline: bool = False,
):
"""
Set up a bokeh plot for real-time plotting.
Defines a moving data stream and a map.
Parameters
----------
doc
Bokeh document to edit - usually called as a partial
rt_client
RealTimeClient streaming data
channels
Channels to plot
tribe
Tribe to plot
inventory
Inventory to plot
detections
Detections to plot - should be a list that is updated in place.
map_options
Dictionary of options for the map
plot_options
Dictionary of options for plotting in general
plot_length
Length of data plot
update_interval
Update frequency in seconds
data_color
Colour to data stream
lowcut
Lowcut for filtering data stream
highcut
Highcut for filtering data stream
offline
Flag to set time-stamps to data time-stamps if True, else timestamps
will be real-time
"""
# Set up the data source
Logger.info("Getting stream to define plot")
stream = rt_client.stream.copy().split().detrend()
if lowcut and highcut:
stream.filter("bandpass", freqmin=lowcut, freqmax=highcut)
title = "Streaming data: {0}-{1} Hz bandpass".format(lowcut, highcut)
elif lowcut:
stream.filter("highpass", lowcut)
title = "Streaming data: {0} Hz highpass".format(lowcut)
elif highcut:
stream.filter("lowpass", highcut)
title = "Streaming data: {0} Hz lowpass".format(highcut)
else:
title = "Raw streaming data"
stream.merge()
Logger.info(f"Have the stream: \n{stream}")
template_lats, template_lons, template_alphas, template_ids = (
[], [], [], [])
for template in tribe:
try:
origin = (template.event.preferred_origin() or
template.event.origins[0])
except IndexError:
continue
template_lats.append(origin.latitude)
template_lons.append(origin.longitude % 360)
template_alphas.append(0)
template_ids.append(template.event.resource_id.id.split("/")[-1])
station_lats, station_lons, station_ids = ([], [], [])
for network in inventory:
for station in network:
station_lats.append(station.latitude)
station_lons.append(station.longitude % 360)
station_ids.append(station.code)
# Get plot bounds in web mercator
Logger.info("Defining map")
transformer = Transformer.from_crs(
"epsg:4326", "epsg:3857", always_xy=True)
try:
min_lat, min_lon, max_lat, max_lon = (
min(template_lats + station_lats),
min(template_lons + station_lons),
max(template_lats + station_lats),
max(template_lons + station_lons))
except ValueError as e:
Logger.error(e)
Logger.info("Setting map bounds to NZ")
min_lat, min_lon, max_lat, max_lon = (-47., 165., -34., 179.9)
Logger.info(f"Map bounds: {min_lon}, {min_lat} - {max_lon}, {max_lat}")
bottom_left = transformer.transform(min_lon, min_lat)
top_right = transformer.transform(max_lon, max_lat)
map_x_range = (bottom_left[0], top_right[0])
map_y_range = (bottom_left[1], top_right[1])
template_x, template_y = ([], [])
for lon, lat in zip(template_lons, template_lats):
_x, _y = transformer.transform(lon, lat)
template_x.append(_x)
template_y.append(_y)
station_x, station_y = ([], [])
for lon, lat in zip(station_lons, station_lats):
_x, _y = transformer.transform(lon, lat)
station_x.append(_x)
station_y.append(_y)
template_source = ColumnDataSource({
'y': template_y, 'x': template_x,
'lats': template_lats, 'lons': template_lons,
'template_alphas': template_alphas, 'id': template_ids})
station_source = ColumnDataSource({
'y': station_y, 'x': station_x,
'lats': station_lats, 'lons': station_lons, 'id': station_ids})
Logger.info("Allocated data sources")
trace_sources = {}
trace_data_range = {}
# Allocate empty arrays
for channel in channels:
tr = stream.select(id=channel)[0]
times = np.arange(
tr.stats.starttime.datetime,
(tr.stats.endtime + tr.stats.delta).datetime,
step=dt.timedelta(seconds=tr.stats.delta))
data = tr.data
trace_sources.update(
{channel: ColumnDataSource({'time': times, 'data': data})})
trace_data_range.update({channel: (data.min(), data.max())})
# Set up the map to go on the left side
Logger.info("Adding features to map")
map_plot = figure(
title="Template map", x_range=map_x_range, y_range=map_y_range,
x_axis_type="mercator", y_axis_type="mercator", **map_options)
url = 'http://a.basemaps.cartocdn.com/rastertiles/voyager/{Z}/{X}/{Y}.png'
attribution = "Tiles by Carto, under CC BY 3.0. Data by OSM, under ODbL"
map_plot.add_tile(WMTSTileSource(url=url, attribution=attribution))
map_plot.circle(
x="x", y="y", source=template_source, fill_color="firebrick",
line_color="grey", line_alpha=.2,
fill_alpha="template_alphas", size=10)
map_plot.triangle(
x="x", y="y", size=10, source=station_source, color="blue", alpha=1.0)
# Set up the trace plots
Logger.info("Setting up streaming plot")
trace_plots = []
if not offline:
now = dt.datetime.utcnow()
else:
now = max([tr.stats.endtime for tr in stream]).datetime
p1 = figure(
y_axis_location="right", title=title,
x_range=[now - dt.timedelta(seconds=plot_length), now],
plot_height=int(plot_options["plot_height"] * 1.2),
**{key: value for key, value in plot_options.items()
if key != "plot_height"})
p1.yaxis.axis_label = None
p1.xaxis.axis_label = None
p1.min_border_bottom = 0
p1.min_border_top = 0
if len(channels) != 1:
p1.xaxis.major_label_text_font_size = '0pt'
p1_line = p1.line(
x="time", y='data', source=trace_sources[channels[0]],
color=data_color, line_width=1)
legend = Legend(items=[(channels[0], [p1_line])])
p1.add_layout(legend, 'right')
datetick_formatter = DatetimeTickFormatter(
days=["%m/%d"], months=["%m/%d"],
hours=["%m/%d %H:%M:%S"], minutes=["%m/%d %H:%M:%S"],
seconds=["%m/%d %H:%M:%S"], hourmin=["%m/%d %H:%M:%S"],
minsec=["%m/%d %H:%M:%S"])
p1.xaxis.formatter = datetick_formatter
# Add detection lines
Logger.info("Adding detection artists")
detection_source = _get_pick_times(detections, channels[0])
detection_source.update(
{"pick_values": [[
int(min(stream.select(id=channels[0])[0].data) * .9),
int(max(stream.select(id=channels[0])[0].data) * .9)]
for _ in detection_source['picks']]})
detection_sources = {channels[0]: ColumnDataSource(detection_source)}
detection_lines = MultiLine(
xs="picks", ys="pick_values", line_color="red", line_dash="dashed",
line_width=1)
p1.add_glyph(detection_sources[channels[0]], detection_lines)
trace_plots.append(p1)
if len(channels) > 1:
for i, channel in enumerate(channels[1:]):
p = figure(
x_range=p1.x_range,
y_axis_location="right", **plot_options)
p.yaxis.axis_label = None
p.xaxis.axis_label = None
p.min_border_bottom = 0
# p.min_border_top = 0
p_line = p.line(
x="time", y="data", source=trace_sources[channel],
color=data_color, line_width=1)
legend = Legend(items=[(channel, [p_line])])
p.add_layout(legend, 'right')
p.xaxis.formatter = datetick_formatter
# Add detection lines
detection_source = _get_pick_times(detections, channel)
detection_source.update(
{"pick_values": [[
int(min(stream.select(id=channel)[0].data) * .9),
int(max(stream.select(id=channel)[0].data) * .9)]
for _ in detection_source['picks']]})
detection_sources.update({
channel: ColumnDataSource(detection_source)})
detection_lines = MultiLine(
xs="picks", ys="pick_values", line_color="red",
line_dash="dashed", line_width=1)
p.add_glyph(detection_sources[channel], detection_lines)
trace_plots.append(p)
if i != len(channels) - 2:
p.xaxis.major_label_text_font_size = '0pt'
plots = gridplot([[map_plot, column(trace_plots)]])
previous_timestamps = {
channel: stream.select(id=channel)[0].stats.endtime
for channel in channels}
def update():
Logger.debug("Plot updating")
_stream = rt_client.stream.split().detrend()
if lowcut and highcut:
_stream.filter("bandpass", freqmin=lowcut, freqmax=highcut)
elif lowcut:
_stream.filter("highpass", lowcut)
elif highcut:
_stream.filter("lowpass", highcut)
_stream.merge()
for _i, _channel in enumerate(channels):
try:
_tr = _stream.select(id=_channel)[0]
except IndexError:
Logger.debug("No channel for {0}".format(_channel))
continue
new_samples = int(_tr.stats.sampling_rate * (
previous_timestamps[_channel] - _tr.stats.endtime))
if new_samples == 0:
Logger.debug("No new data for {0}".format(_channel))
continue
_new_data = _tr.slice(
starttime=previous_timestamps[_channel])
new_times = np.arange(
_new_data.stats.starttime.datetime,
(_tr.stats.endtime + _tr.stats.delta).datetime,
step=dt.timedelta(seconds=_tr.stats.delta))
new_data = {'time': new_times[1:], 'data': _new_data.data[1:]}
Logger.debug("Channl: {0}\tNew times: {1}\t New data: {2}".format(
_tr.id, new_data["time"].shape, new_data["data"].shape))
trace_sources[_channel].stream(
new_data=new_data,
rollover=int(plot_length * _tr.stats.sampling_rate))
new_picks = _get_pick_times(detections, _channel)
new_picks.update({
'pick_values': [
[int(np.nan_to_num(
trace_sources[_channel].data['data']).max() * .9),
int(np.nan_to_num(
trace_sources[_channel].data['data']).min() * .9)]
for _ in new_picks['picks']]})
detection_sources[_channel].data = new_picks
previous_timestamps.update({_channel: _tr.stats.endtime})
Logger.debug("New data plotted for {0}".format(_channel))
if not offline:
now = dt.datetime.utcnow()
else:
try:
now = max([tr.stats.endtime for tr in _stream]).datetime
except ValueError:
return
trace_plots[0].x_range.start = now - dt.timedelta(seconds=plot_length)
trace_plots[0].x_range.end = now
_update_template_alphas(
detections, tribe, decay=plot_length, now=now,
datastream=template_source)
Logger.info("Adding callback")
doc.add_periodic_callback(update, update_interval)
doc.title = "EQcorrscan Real-time plotter"
doc.add_root(plots)
Logger.info("Plot defined")
data=dict(
lat=df['Latitude'],
lon=df['Longitude'],
)
)
circle = Circle(x="lon", y="lat", size=5, fill_alpha=0.5, fill_color="magenta", line_alpha=0.3, line_color="black")
plot.add_glyph(source, circle)
slider = Slider(start=0, end=6, value=1, step=1, title="Weekdays")
pan = PanTool()
wheel_zoom = WheelZoomTool()
box_select = BoxSelectTool()
plot.add_tools(pan, wheel_zoom, box_select)
overlay = BoxSelectionOverlay(tool=box_select)
plot.add_layout(overlay)
# layout = vform(slider, plot)
doc = Document()
# doc.add(slider)
doc.add(plot, slider)
if __name__ == "__main__":
filename = "maps.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Google Maps Example"))
print("Wrote %s" % filename)
view(filename)
def _doc_modifier(doc: Document) -> None:
grid = _create_ui_components()
doc.add_root(grid)
plot.add_glyph(text_source, text)
return plot
xattrs = ["petal_length", "petal_width", "sepal_width", "sepal_length"]
yattrs = list(reversed(xattrs))
plots = []
for y in yattrs:
row = []
for x in xattrs:
xax = (y == yattrs[-1])
yax = (x == xattrs[0])
text = x if (x == y) else None
plot = make_plot(x, y, xax, yax, text)
row.append(plot)
plots.append(row)
grid = GridPlot(children=plots)
doc = Document()
doc.add_root(grid)
if __name__ == "__main__":
filename = "iris_splom.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Iris Data SPLOM"))
print("Wrote %s" % filename)
view(filename)
CategoricalAxis(axis_label='Date',
major_label_orientation=pi / 2,
**axis_defaults), 'below')
bk_page.children = [
Div(text=bk_section0_text, sizing_mode='scale_both'),
Div(text=bk_section1_text1, sizing_mode='scale_both'),
plot_kf,
Div(text=bk_section1_text2, sizing_mode='scale_both'),
plot_kc,
Div(text=bk_section1_text3, sizing_mode='scale_both'),
plot_sc,
Div(text=bk_section1_text4, sizing_mode='scale_both'),
plot_dc,
Div(text=bk_section2_text1, sizing_mode='scale_both'),
pop_dt,
Div(text=bk_section3_text1, sizing_mode='scale_both'),
Div(text=bk_section3_text2, sizing_mode='scale_both'),
Div(text=bk_section3_text3, sizing_mode='scale_both'),
plot_tm,
Div(text=bk_section3_text4, sizing_mode='scale_both'),
]
doc = Document()
doc.add_root(bk_page)
doc.validate()
filename = 'index.html'
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "New York Times - Climate Change"))
view(filename)
)
plot.add_glyph(text_source, text)
return plot
xattrs = ["petal_length", "petal_width", "sepal_width", "sepal_length"]
yattrs = list(reversed(xattrs))
plots = []
for y in yattrs:
row = []
for x in xattrs:
xax = (y == yattrs[-1])
yax = (x == xattrs[0])
text = x if (x==y) else None
plot = make_plot(x, y, xax, yax, text)
row.append(plot)
plots.append(row)
grid = GridPlot(children=plots, title="iris_splom")
doc = Document()
doc.add(grid)
if __name__ == "__main__":
filename = "iris_splom.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Iris Data SPLOM"))
print("Wrote %s" % filename)
view(filename)
class DataTables(object):
def __init__(self):
self.document = Document()
self.manufacturer_filter = None
self.model_filter = None
self.transmission_filter = None
self.drive_filter = None
self.class_filter = None
self.source = ColumnDataSource()
self.update_data()
self.document.add_root((self.create()))
self.session = push_session(self.document)
def create(self):
manufacturers = sorted(mpg["manufacturer"].unique())
models = sorted(mpg["model"].unique())
transmissions = sorted(mpg["trans"].unique())
drives = sorted(mpg["drv"].unique())
classes = sorted(mpg["class"].unique())
manufacturer_select = Select(title="Manufacturer:", value="All", options=["All"] + manufacturers)
manufacturer_select.on_change('value', self.on_manufacturer_change)
model_select = Select(title="Model:", value="All", options=["All"] + models)
model_select.on_change('value', self.on_model_change)
transmission_select = Select(title="Transmission:", value="All", options=["All"] + transmissions)
transmission_select.on_change('value', self.on_transmission_change)
drive_select = Select(title="Drive:", value="All", options=["All"] + drives)
drive_select.on_change('value', self.on_drive_change)
class_select = Select(title="Class:", value="All", options=["All"] + classes)
class_select.on_change('value', self.on_class_change)
columns = [
TableColumn(field="manufacturer", title="Manufacturer", editor=SelectEditor(options=manufacturers), formatter=StringFormatter(font_style="bold")),
TableColumn(field="model", title="Model", editor=StringEditor(completions=models)),
TableColumn(field="displ", title="Displacement", editor=NumberEditor(step=0.1), formatter=NumberFormatter(format="0.0")),
TableColumn(field="year", title="Year", editor=IntEditor()),
TableColumn(field="cyl", title="Cylinders", editor=IntEditor()),
TableColumn(field="trans", title="Transmission", editor=SelectEditor(options=transmissions)),
TableColumn(field="drv", title="Drive", editor=SelectEditor(options=drives)),
TableColumn(field="class", title="Class", editor=SelectEditor(options=classes)),
TableColumn(field="cty", title="City MPG", editor=IntEditor()),
TableColumn(field="hwy", title="Highway MPG", editor=IntEditor()),
]
data_table = DataTable(source=self.source, columns=columns, editable=True)
plot = Plot(title=None, x_range= DataRange1d(), y_range=DataRange1d(), plot_width=1000, plot_height=300)
# Set up x & y axis
plot.add_layout(LinearAxis(), 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
# Add Glyphs
cty_glyph = Circle(x="index", y="cty", fill_color="#396285", size=8, fill_alpha=0.5, line_alpha=0.5)
hwy_glyph = Circle(x="index", y="hwy", fill_color="#CE603D", size=8, fill_alpha=0.5, line_alpha=0.5)
cty = plot.add_glyph(self.source, cty_glyph)
hwy = plot.add_glyph(self.source, hwy_glyph)
# Add the tools
tooltips = [
("Manufacturer", "@manufacturer"),
("Model", "@model"),
("Displacement", "@displ"),
("Year", "@year"),
("Cylinders", "@cyl"),
("Transmission", "@trans"),
("Drive", "@drv"),
("Class", "@class"),
]
cty_hover_tool = HoverTool(renderers=[cty], tooltips=tooltips + [("City MPG", "@cty")])
hwy_hover_tool = HoverTool(renderers=[hwy], tooltips=tooltips + [("Highway MPG", "@hwy")])
select_tool = BoxSelectTool(renderers=[cty, hwy], dimensions=['width'])
plot.add_tools(cty_hover_tool, hwy_hover_tool, select_tool)
controls = VBox(children=[
manufacturer_select, model_select, transmission_select,
drive_select, class_select])
top_panel = HBox(children=[controls, plot])
layout = VBox(children=[top_panel, data_table])
return layout
def on_manufacturer_change(self, attr, _, value):
self.manufacturer_filter = None if value == "All" else value
self.update_data()
def on_model_change(self, attr, _, value):
self.model_filter = None if value == "All" else value
self.update_data()
def on_transmission_change(self, attr, _, value):
self.transmission_filter = None if value == "All" else value
self.update_data()
def on_drive_change(self, attr, _, value):
self.drive_filter = None if value == "All" else value
self.update_data()
def on_class_change(self, attr, _, value):
self.class_filter = None if value == "All" else value
self.update_data()
def update_data(self):
df = mpg
if self.manufacturer_filter:
df = df[df["manufacturer"] == self.manufacturer_filter]
if self.model_filter:
df = df[df["model"] == self.model_filter]
if self.transmission_filter:
df = df[df["trans"] == self.transmission_filter]
if self.drive_filter:
df = df[df["drv"] == self.drive_filter]
if self.class_filter:
df = df[df["class"] == self.class_filter]
self.source.data = ColumnDataSource.from_df(df)
def run(self, do_view=False, poll_interval=0.5):
if do_view:
self.session.show()
self.session.loop_until_closed()
class Population(object):
year = 2010
location = "World"
def __init__(self):
from bokeh.models import ColumnDataSource
from bokeh.document import Document
from bokeh.session import Session
from bokeh.sampledata.population import load_population
self.document = Document()
self.session = Session()
self.session.use_doc('population_reveal')
self.session.load_document(self.document)
self.df = load_population()
self.source_pyramid = ColumnDataSource(data=dict())
# just render at the initialization
self._render()
def _render(self):
self.pyramid_plot()
self.create_layout()
self.document.add(self.layout)
self.update_pyramid()
def pyramid_plot(self):
from bokeh.models import (Plot, DataRange1d, LinearAxis, Grid,
Legend, SingleIntervalTicker)
from bokeh.models.glyphs import Quad
xdr = DataRange1d(sources=[self.source_pyramid.columns("male"),
self.source_pyramid.columns("female")])
ydr = DataRange1d(sources=[self.source_pyramid.columns("groups")])
self.plot = Plot(title="Widgets", x_range=xdr, y_range=ydr,
plot_width=600, plot_height=600)
xaxis = LinearAxis()
self.plot.add_layout(xaxis, 'below')
yaxis = LinearAxis(ticker=SingleIntervalTicker(interval=5))
self.plot.add_layout(yaxis, 'left')
self.plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
self.plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
male_quad = Quad(left="male", right=0, bottom="groups", top="shifted",
fill_color="#3B8686")
male_quad_glyph = self.plot.add_glyph(self.source_pyramid, male_quad)
female_quad = Quad(left=0, right="female", bottom="groups", top="shifted",
fill_color="#CFF09E")
female_quad_glyph = self.plot.add_glyph(self.source_pyramid, female_quad)
self.plot.add_layout(Legend(legends=dict(Male=[male_quad_glyph],
Female=[female_quad_glyph])))
def on_year_change(self, obj, attr, old, new):
self.year = int(new)
self.update_pyramid()
def on_location_change(self, obj, attr, old, new):
self.location = new
self.update_pyramid()
def create_layout(self):
from bokeh.models.widgets import Select, HBox, VBox
years = list(map(str, sorted(self.df.Year.unique())))
locations = sorted(self.df.Location.unique())
year_select = Select(title="Year:", value="2010", options=years)
location_select = Select(title="Location:", value="World", options=locations)
year_select.on_change('value', self.on_year_change)
location_select.on_change('value', self.on_location_change)
controls = HBox(year_select, location_select)
self.layout = VBox(controls, self.plot)
def update_pyramid(self):
pyramid = self.df[(self.df.Location == self.location) & (self.df.Year == self.year)]
male = pyramid[pyramid.Sex == "Male"]
female = pyramid[pyramid.Sex == "Female"]
total = male.Value.sum() + female.Value.sum()
male_percent = -male.Value / total
female_percent = female.Value / total
groups = male.AgeGrpStart.tolist()
shifted = groups[1:] + [groups[-1] + 5]
self.source_pyramid.data = dict(
groups=groups,
shifted=shifted,
male=male_percent,
female=female_percent,
)
self.session.store_document(self.document)
from __future__ import print_function
from numpy import pi, arange, sin, cos
from bokeh.browserlib import view
from bokeh.document import Document
from bokeh.models.glyphs import Circle
from bokeh.models import (
Plot, DataRange1d, LinearAxis, Grid,
ColumnDataSource, PanTool, WheelZoomTool
)
from bokeh.client import push_session
document = Document()
session = push_session(document)
x = arange(-2*pi, 2*pi, 0.1)
y = sin(x)
r = (cos(x)+1) * 6 + 6
source = ColumnDataSource(data=dict(x=x, y=y, r=r))
xdr = DataRange1d()
ydr = DataRange1d()
plot = Plot(x_range=xdr, y_range=ydr, min_border=80)
circle = Circle(
x="x", y="y", size="r",
fill_color="red", line_color="black"
)
from bokeh.session import Session
from bokeh.widgets import (
VBox,
HBox,
Paragraph,
Icon,
Button,
Toggle,
Dropdown,
CheckboxGroup,
RadioGroup,
CheckboxButtonGroup,
RadioButtonGroup,
)
document = Document()
session = Session()
session.use_doc('buttons_server')
session.load_document(document)
def button_handler():
print("button_handler: click")
session.store_document(document)
def toggle_handler(active):
print("toggle_handler: %s" % active)
session.store_document(document)
from __future__ import print_function
import numpy as np
import sympy as sy
from bokeh.client import push_session
from bokeh.document import Document
from bokeh.models.glyphs import Line
from bokeh.models import Plot, Range1d, LinearAxis, ColumnDataSource, Grid, Legend
from bokeh.models.widgets import Slider, TextInput, Dialog
from bokeh.models.layouts import WidgetBox, Column
document = Document()
session = push_session(document)
xs = sy.Symbol('x')
expr = sy.exp(-xs) * sy.sin(xs)
order = 1
def taylor(fx, xs, order, x_range=(0, 1), n=200):
x0, x1 = x_range
x = np.linspace(float(x0), float(x1), n)
fy = sy.lambdify(xs, fx, modules=['numpy'])(x)
tx = fx.series(xs, n=order).removeO()
if tx.is_Number:
ty = np.zeros_like(x)
ty.fill(float(tx))
else:
from __future__ import print_function
import numpy as np
from bokeh.models import ColumnDataSource, DataRange1d, Plot, LinearAxis, Grid, Circle, VBox, HBox, Button, TapTool
from bokeh.document import Document
from bokeh.session import Session
from bokeh.browserlib import view
document = Document()
session = Session()
session.use_doc('linked_tap_server')
session.load_document(document)
N = 9
x = np.linspace(-2, 2, N)
y = x**2
source1 = ColumnDataSource(dict(x=x, y=y, size=[20] * N))
xdr1 = DataRange1d()
ydr1 = DataRange1d()
plot1 = Plot(title="Plot1",
x_range=xdr1,
y_range=ydr1,
plot_width=400,
plot_height=400)
plot1.tools.append(TapTool(plot=plot1))
plot1.add_glyph(source1, Circle(x="x", y="y", size="size", fill_color="red"))
source2 = ColumnDataSource(dict(x=x, y=y, color=["blue"] * N))
http://localhost:8000/widget.html
"""
from __future__ import print_function
from numpy import pi
from bokeh.document import Document
from bokeh.client import push_session
from bokeh.embed import autoload_server
from bokeh.models import (Plot, DataRange1d, LinearAxis, CategoricalAxis,
Legend, HBox, VBox, ColumnDataSource, Grid, Line,
SingleIntervalTicker, Quad, Select, FactorRange)
from bokeh.sampledata.population import load_population
document = Document()
session = push_session(document)
df = load_population()
revision = 2012
year = 2010
location = "World"
years = [str(x) for x in sorted(df.Year.unique())]
locations = sorted(df.Location.unique())
source_pyramid = ColumnDataSource(data=dict())
plot.add_layout(
Label(x=500,
y=320,
x_units='screen',
y_units='screen',
text='Replace GOOGLE_API_KEY with your own key',
text_color='red',
text_align='center'))
plot.title.text = "Cities of the world with a population over 5,000 people."
circle = Circle(x="lng",
y="lat",
size=5,
line_color=None,
fill_color='firebrick',
fill_alpha=0.2)
plot.add_glyph(ColumnDataSource(data), circle)
plot.add_tools(PanTool(), WheelZoomTool())
doc = Document()
doc.add_root(plot)
if __name__ == "__main__":
doc.validate()
filename = "maps_cities.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Google Maps - World cities Example"))
print("Wrote %s" % filename)
view(filename)
text_area,
select,
multi_select,
multi_choice,
slider,
range_slider,
date_slider,
date_range_slider,
spinner,
color_picker,
date_picker,
paragraph,
div,
pre_text,
]),
tabs,
]),
table,
])
doc = Document()
doc.add_root(widgets)
if __name__ == "__main__":
doc.validate()
filename = "widgets.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Widgets"))
print("Wrote %s" % filename)
view(filename)
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
plot.add_tools(HoverTool())
tab = Panel(child=plot, title=title, closable=True)
return tab
def make_tabs(objs):
return Tabs(tabs=[make_tab(title, obj) for title, obj in objs], width=600)
layout = Column(children=[
Paragraph(text="Only Image and ImageRGBA glyphs are not demonstrated."),
make_tabs(glyphs),
make_tabs(markers)
])
doc = Document()
doc.add_root(layout)
if __name__ == "__main__":
doc.validate()
filename = "glyphs.html"
with open(filename, "w") as f:
f.write(file_html(doc, INLINE, "Glyphs"))
print("Wrote %s" % filename)
view(filename)