def __init__(self, addr=None, interval=1000.00, loop=None):
if addr is None:
scheduler = default_executor().scheduler
if isinstance(scheduler, rpc):
addr = (scheduler.ip, 9786)
elif isinstance(scheduler, Scheduler):
addr = ('127.0.0.1', scheduler.services['http'].port)
self.addr = addr
self.interval = interval
self.display_notebook = False
if is_kernel() and not curstate().notebook:
output_notebook()
assert curstate().notebook
self.task_source, self.task_table = task_table_plot()
self.worker_source, self.worker_table = worker_table_plot()
self.output = vplot(self.worker_table, self.task_table)
self.client = AsyncHTTPClient()
self.loop = loop or IOLoop.current()
self.loop.add_callback(self.update)
self._pc = PeriodicCallback(self.update, self.interval, io_loop=self.loop)
self._pc.start()
def __init__(self, addr=None, interval=1000.00, loop=None):
if addr is None:
scheduler = default_executor().scheduler
if isinstance(scheduler, rpc):
addr = (scheduler.ip, 9786)
elif isinstance(scheduler, Scheduler):
addr = ('127.0.0.1', scheduler.services['http'].port)
self.addr = addr
self.interval = interval
self.display_notebook = False
if is_kernel() and not curstate().notebook:
output_notebook()
assert curstate().notebook
self.task_source, self.task_table = task_table_plot()
self.worker_source, self.worker_table = worker_table_plot()
self.output = vplot(self.worker_table, self.task_table)
self.client = AsyncHTTPClient()
self.loop = loop or IOLoop.current()
self.loop.add_callback(self.update)
self._pc = PeriodicCallback(self.update, self.interval, io_loop=self.loop)
self._pc.start()
def handle_on_msg(self, _, content, buffers):
"""
Handler for click (and potentially other) events from the user.
"""
if content == "home":
self.backward.append(None)
self.forward = []
self.generate_content()
elif content == "back":
self.forward.append(self.backward.pop())
self.generate_content(self.backward[-1])
elif content == "forward":
self.backward.append(self.forward.pop())
self.generate_content(self.backward[-1])
elif content == "init_complete":
comms_target = self.bokeh_comms_target
# TODO: Simplify this:
self.bokeh_table_handle = (bokeh_io.
_CommsHandle(bokeh_util.notebook.
get_comms(comms_target),
bokeh_io.curstate().
document,
bokeh_io.curstate().
document.to_json()))
bokeh_io._state.last_comms_handle = self.bokeh_table_handle
else:
clicked_fun = self.id_dict[content]
self.backward.append(clicked_fun)
self.forward = []
self.generate_content(clicked_fun)
def __init__(self, addr=None, interval=1.00):
if addr is None:
scheduler = default_executor().scheduler
if isinstance(scheduler, rpc):
addr = (scheduler.ip, scheduler.port)
elif isinstance(scheduler, Scheduler):
addr = ('127.0.0.1', scheduler.port)
self.cds = ColumnDataSource({k: []
for k in ['host', 'cpu', 'memory',
'zero', 'left', 'mid', 'right']})
self.display_notebook = False
self.figure = figure(height=200, width=800, y_range=(0, 100))
self.figure.logo = None
cpu = self.figure.quad(legend='cpu', left='left', right='mid',
bottom='zero', top='cpu', source=self.cds,
color=(0, 0, 255, 0.5))
memory = self.figure.quad(legend='memory', left='mid', right='right',
bottom='zero', top='memory', source=self.cds,
color=(255, 0, 0, 0.5))
self.figure.add_tools(HoverTool(renderers=[cpu, memory],
tooltips=[("host", "@host"),
("cpu", "@cpu"),
("memory", "@memory")]))
self.future = self.update(addr, interval)
if is_kernel() and not curstate().notebook:
output_notebook()
assert curstate().notebook
def __init__(self, addr=None, interval=1.00):
if addr is None:
scheduler = default_executor().scheduler
if isinstance(scheduler, rpc):
addr = (scheduler.ip, scheduler.port)
elif isinstance(scheduler, Scheduler):
addr = ('127.0.0.1', scheduler.port)
self.cds = ColumnDataSource({
k: []
for k in [
'host', 'processing', 'stacks', 'waiting', 'zero', 'left',
'mid', 'right'
]
})
self.display_notebook = False
left_range = Range1d(0, 1)
self.figure = figure(height=200, width=800, y_range=left_range)
self.figure.extra_y_ranges = {'waiting': Range1d(start=0, end=1)}
self.figure.add_layout(
LinearAxis(y_range_name='waiting', axis_label='waiting'), 'right')
self.figure.logo = None
proc = self.figure.quad(legend='processing',
left='left',
right='mid',
bottom='zero',
top='nprocessing',
source=self.cds,
color=(0, 0, 255, 0.5))
wait = self.figure.quad(legend='waiting',
left='mid',
right='right',
bottom='zero',
top='waiting',
source=self.cds,
y_range_name='waiting',
color=(255, 0, 0, 0.5))
self.figure.add_tools(
HoverTool(renderers=[proc, wait],
tooltips=[("host", "@host"),
("processing", "@processing"),
("waiting", "@waiting")]))
self.future = self.update(addr, interval)
if is_kernel() and not curstate().notebook:
output_notebook()
assert curstate().notebook
def show_figure(fig):
from bokeh.document import Document
from bokeh.io import curstate, show
if fig.document is None:
doc = Document()
doc.add_root(fig)
curstate().document = doc
fig.__dict__["_handle"] = show(fig)
def __init__(self, addr=None, interval=1.00):
if addr is None:
scheduler = default_executor().scheduler
if isinstance(scheduler, rpc):
addr = (scheduler.ip, scheduler.port)
elif isinstance(scheduler, Scheduler):
addr = ('127.0.0.1', scheduler.port)
self.cds = ColumnDataSource({
k: []
for k in ['host', 'cpu', 'memory', 'zero', 'left', 'mid', 'right']
})
self.display_notebook = False
self.figure = figure(height=200, width=800, y_range=(0, 100))
self.figure.logo = None
cpu = self.figure.quad(legend='cpu',
left='left',
right='mid',
bottom='zero',
top='cpu',
source=self.cds,
color=(0, 0, 255, 0.5))
memory = self.figure.quad(legend='memory',
left='mid',
right='right',
bottom='zero',
top='memory',
source=self.cds,
color=(255, 0, 0, 0.5))
self.figure.add_tools(
HoverTool(renderers=[cpu, memory],
tooltips=[("host", "@host"), ("cpu", "@cpu"),
("memory", "@memory")]))
self.future = self.update(addr, interval)
if is_kernel() and not curstate().notebook:
output_notebook()
assert curstate().notebook
def setup_chosen(fpath):
try:
df = pd.DataFrame.from_csv(fpath)
except Exception as exc:
msg = str(exc)
MessageBox.text = msg
dfcols = list(df.columns)
ChosenSource = ColumnDataSource()
ChosenSource.data = bu.column_data_source_data_from_df(df)
ChosenSource.name = "ChosenSource"
ChosenTable = bu.data_table(source=ChosenSource,
columns=dfcols,
width=800)
ChosenTable.name = "ChosenTable"
metadf = bu.df_summary(df)
MetaSource = ColumnDataSource()
MetaSource.name = "MetaSource"
MetaSource.data = bu.column_data_source_data_from_df(metadf)
MetaTable = bu.data_table(source=MetaSource,
columns=list(metadf.columns),
width=600)
MetaTable.name = "MetaTable"
RowFilter.value = ("# enter row filter conditions here")
ScatterPlotX = Select(options = dfcols,
value=dfcols[0])
ScatterPlotX.name = 'ScatterPlotX'
ScatterPlotY = Select(options = dfcols,
value=dfcols[-1])
ScatterPlotY.name = 'ScatterPlotY'
ScatterSource = ColumnDataSource()
ScatterSource.name = 'ScatterSource'
ScatterSource.data = dict(X=ChosenSource.data[ScatterPlotX.value],
Y=ChosenSource.data[ScatterPlotY.value])
ScatterPlot = Figure(height=500, width=600)
res = ScatterPlot.scatter(x='X',
y='Y',
source=ScatterSource)
res.name = "srender"
ScatterPlot.name = 'ScatterPlot'
layout= column(MessageBox, CloseButton,
RowFilter,
ColumnChooser,
column(bu.child_in_widgetbox(MetaTable),
bu.child_in_widgetbox(ChosenTable)),
row(ScatterPlotX, ScatterPlotY, MakeScatterPlot),
ScatterPlot,)
MakeScatterPlot.on_click(functools.partial(make_scatter, dom=layout))
currentstate = bio.curstate()
return layout
def __init__(self, addr=None, interval=1.00):
if addr is None:
scheduler = default_executor().scheduler
if isinstance(scheduler, rpc):
addr = (scheduler.ip, scheduler.port)
elif isinstance(scheduler, Scheduler):
addr = ('127.0.0.1', scheduler.port)
self.cds = ColumnDataSource({k: []
for k in ['host', 'processing', 'stacks', 'waiting',
'zero', 'left', 'mid', 'right']})
self.display_notebook = False
left_range = Range1d(0, 1)
self.figure = figure(height=200, width=800, y_range=left_range)
self.figure.extra_y_ranges = {'waiting': Range1d(start=0, end=1)}
self.figure.add_layout(LinearAxis(y_range_name='waiting',
axis_label='waiting'), 'right')
self.figure.logo = None
proc = self.figure.quad(legend='processing', left='left', right='mid',
bottom='zero', top='nprocessing', source=self.cds,
color=(0, 0, 255, 0.5))
wait = self.figure.quad(legend='waiting', left='mid', right='right',
bottom='zero', top='waiting', source=self.cds,
y_range_name='waiting', color=(255, 0, 0, 0.5))
self.figure.add_tools(HoverTool(renderers=[proc, wait],
tooltips=[("host", "@host"),
("processing", "@processing"),
("waiting", "@waiting")]))
self.future = self.update(addr, interval)
if is_kernel() and not curstate().notebook:
output_notebook()
assert curstate().notebook
def test(self):
self.assertEqual(io.curstate(), io._state)
def test(self):
self.assertEqual(io.curstate(), io._state)
import pandas as pd
import numpy as np
import numpy.matlib
import matplotlib.pyplot as plt
from yahoo_finance import Share
from datetime import datetime
from bokeh.models import DatetimeTickFormatter
from datetime import timedelta
def nix(val, lst):
return [x for x in lst if x != val]
# Let source be the data I am using to plot.
curstate().autoadd = False
# Create a dictionary for table
source_table = ColumnDataSource(data=dict(
Forecast=[], AQuarter=[], OneFourth=[], OneThird=[], TwoThird=[]))
columnsD = [
TableColumn(field="Forecast", title="Days past Current"),
TableColumn(field="AQuarter", title="96% Confidence"),
TableColumn(field="OneFourth", title="80% Confidence"),
TableColumn(field="OneThird", title="60% Confidence"),
]
data_table = DataTable(source=source_table,
columns=columnsD,
width=1050,
height=300,
row_headers=False,
editable=True)
#CloseButton.on_click(close_session)
CloseButton.callback = close_browser_js
TextBox.on_change("value", update_textbox)
def set_message(text):
global MessageBox
MessageBox.text = text
layout = column(MessageBox, TextBox, CloseButton)
oldcurdoc = bio.curdoc()
currentstate = bio.curstate()
TheDoc = Document(title="NewDoc")
TheDoc.add_root(layout)
def get_function_name(stackpos=1):
''' call me to get your name
:return: name of the calling function
'''
# my_name = inspect.stack()[0][3]
caller = inspect.stack()[stackpos][3]
return caller
def session_update():
msg = get_function_name()
def revive(self):
self.terminated = False
curstate().reset()
import json
import sys
import numpy as np
from numpy import pi
from bokeh.plotting import figure, output_file, show, ColumnDataSource
from bokeh import palettes
from bokeh.models import HoverTool,HBox, VBox, Select
from bokeh.models.widgets import Dropdown
from bokeh.io import output_file, show, vform, curdoc, curstate
from bokeh.charts import Bar, Scatter
import pandas as pd
from bokeh.models.renderers import GlyphRenderer
import pandas.core.series
curstate().autoadd = False
session = push_session(curdoc())
# read json file
with open('data/content_data.json') as datafile:
input_data = json.load(datafile)
# extract attribute names
data = input_data['data']
data_attributes = map(lambda a: a['attributes'], data)
attributes_name = list(set([item['name'] for sublist in data_attributes for item in sublist]))
# global state
selected_attribute = attributes_name[1]
selected_points = []
table_selected_attribute=selected_attribute
from bokeh.io import show, output_file, curstate
from bokeh.plotting import figure
from bokeh.models import Button, CustomJS
from bokeh.layouts import column
f1 = figure()
f1.x(x=[1, 2, 3], y=[3, 2, 1])
main_row = column(f1)
b = Button(label='Add plot',
callback=CustomJS(args=dict(main_row=main_row),
code="""
f = Bokeh.Plotting.figure();
f.cross({x: [1, 2, 3], y: [3, 2, 1]});
main_row.children.push(f);
main_row.properties.children.change.emit();
"""))
main_row.children.append(b)
output_file('bokeh_add_plot_no_server.html')
curstate().file['resources'].js_components.append('bokeh-api')
show(main_row)
