def make_source(self):
self.source = ColumnDataSource(data=self.df)
self.source.callback = Callback(args=dict(),
code="""
var inds = cb_obj.get('selected')['1d'].indices;
var theidx = inds[0];
console.log("yep");
console.log(theidx);
$.get( "reviews", {id: theidx}, function( response ) {
$( "#section2" ).html( response );
}, "html");
console.log("done");
""")
def make_source(self):
self.source = ColumnDataSource(data=self.df)
self.source.callback = Callback(args=dict(),
code="""
var inds = cb_obj.get('selected')['1d'].indices;
var theidx = inds[0];
var d1 = cb_obj.get("data");
var brand = d1["brand"][theidx];
console.log("yep");
console.log(theidx);
$.get( "shoes", {id: brand}, function( response ) {
console.log("logging rep");
console.log(response);
console.log("done logging rep");
$( "#child" ).html( response );
}, "html");
console.log("done");
""")
self.make_brand_source()
def bokeh_plot(self):
chosen_bic = literal_eval(self.get_argument('subject'))
# prep
n_cols = len(chosen_bic['feats'])
n_lines = len(chosen_bic['objs'])
bic_mtrx = np.zeros((n_lines, n_cols), dtype=object)
objs = sorted(chosen_bic['objs'])
feats = sorted(chosen_bic['feats'])
# bokeh
objlist = []
featlist = []
# colormap = ["#444444", "#a6cee3", "#1f78b4", "#b2df8a", "#33a02c", "#fb9a99", "#e31a1c", "#fdbf6f", "#ff7f00", "#cab2d6", "#6a3d9a"]
color = []
i = 0
for obj in objs:
j = 0
for feat in feats:
objlist.append(obj)
featlist.append(feat)
color.append("#669999")
#color.append(np.random.choice(colormap))
bic_mtrx[i, j] = (obj, feat)
j += 1
i += 1
# ColumnDataSource Object
source = ColumnDataSource(data=dict(xname=objlist,
yname=featlist,
colors=color,
count=bic_mtrx.flatten()))
source.callback = Callback(args=dict(source=source),
code="""
var data = source.get('data');
var f = source.get('value');
object_p = data['xname'];
attribute_p = data['yname'];
document.write(f);
""")
p = figure(title="Matriz do Co-Grupo",
x_axis_location="above",
tools="resize, previewsave, reset, hover",
x_range=list(objs),
y_range=list(reversed(feats)),
plot_width=n_lines * 100,
plot_height=n_cols * 40,
toolbar_location="left")
p.rect('xname',
'yname',
1,
1,
source=source,
color='colors',
line_color="#000000")
p.grid.grid_line_color = None
p.axis.axis_line_color = None
p.axis.major_tick_line_color = "#000000"
p.axis.major_label_text_font_size = "10pt"
p.axis.major_label_standoff = 0
p.xaxis.major_label_orientation = np.pi / 2.5
p.border_fill = "#FFFFF0"
tap = TapTool(plot=p)
# tap = TapTool(plot=p, action=OpenURL(url="http://www.ufabc.edu.br"))
p.tools.append(tap)
hover = p.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Tupla', '@yname, @xname')])
# hover = HoverTool(plot=p, tooltips=[('Tupla', '@yname, @xname')])
# p.tools.append(hover)
# script & div tags
script, div = components(p, CDN)
# return to html
return (script, div)
def _get_plot():
years, regions, fertility_df, life_expectancy_df, population_df_size, regions_df = _get_data()
# Set-up the sources
sources = {}
region_color = regions_df['region_color']
region_color.name = 'region_color'
for year in years:
fertility = fertility_df[year]
fertility.name = 'fertility'
life = life_expectancy_df[year]
life.name = 'life'
population = population_df_size[year]
population.name = 'population'
new_df = pd.concat([fertility, life, population, region_color], axis=1)
sources['_' + str(year)] = ColumnDataSource(new_df)
dictionary_of_sources = dict(zip([x for x in years], ['_%s' % x for x in years]))
js_source_array = str(dictionary_of_sources).replace("'", "")
# Build the plot
# Set up the plot
xdr = Range1d(1, 9)
ydr = Range1d(20, 100)
plot = Plot(
x_range=xdr,
y_range=ydr,
title="",
plot_width=800,
plot_height=400,
outline_line_color=None,
toolbar_location=None,
)
AXIS_FORMATS = dict(
minor_tick_in=None,
minor_tick_out=None,
major_tick_in=None,
major_label_text_font_size="10pt",
major_label_text_font_style="normal",
axis_label_text_font_size="10pt",
axis_line_color='#AAAAAA',
major_tick_line_color='#AAAAAA',
major_label_text_color='#666666',
major_tick_line_cap="round",
axis_line_cap="round",
axis_line_width=1,
major_tick_line_width=1,
)
xaxis = LinearAxis(SingleIntervalTicker(interval=1), axis_label="Children per woman (total fertility)", **AXIS_FORMATS)
yaxis = LinearAxis(SingleIntervalTicker(interval=20), axis_label="Life expectancy at birth (years)", **AXIS_FORMATS)
plot.add_layout(xaxis, 'below')
plot.add_layout(yaxis, 'left')
# Add the year in background (add before circle)
text_source = ColumnDataSource({'year': ['%s' % years[0]]})
text = Text(x=2, y=35, text='year', text_font_size='150pt', text_color='#EEEEEE')
plot.add_glyph(text_source, text)
# Add the circle
renderer_source = sources['_%s' % years[0]]
circle_glyph = Circle(
x='fertility', y='life', size='population',
fill_color='region_color', fill_alpha=0.8,
line_color='#7c7e71', line_width=0.5, line_alpha=0.5)
circle_renderer = plot.add_glyph(renderer_source, circle_glyph)
# Add the hover (only against the circle and not other plot elements)
tooltips = "@index"
plot.add_tools(HoverTool(tooltips=tooltips, renderers=[circle_renderer]))
text_x = 7
text_y = 95
for i, region in enumerate(regions):
plot.add_glyph(Text(x=text_x, y=text_y, text=[region], text_font_size='10pt', text_color='#666666'))
plot.add_glyph(Circle(x=text_x - 0.1, y=text_y + 2, fill_color=Spectral6[i], size=10, line_color=None, fill_alpha=0.8))
text_y = text_y - 5
# Add the slider
code = """
var year = slider.get('value'),
sources = %s,
new_source_data = sources[year].get('data');
renderer_source.set('data', new_source_data);
renderer_source.trigger('change');
text_source.set('data', {'year': [String(year)]});
text_source.trigger('change');
""" % js_source_array
callback = Callback(args=sources, code=code)
slider = Slider(start=years[0], end=years[-1], value=1, step=1, title="Year", callback=callback)
callback.args["slider"] = slider
callback.args["renderer_source"] = renderer_source
callback.args["text_source"] = text_source
# Lay it out
return vplot(plot, hplot(slider))
cu1_s.callback = Callback(args=dict(cu1_avg=cu1_avg, cu1_lower=cu1_lower, cu1_upper=cu1_upper), code="""
var inds = cb_obj.get('selected')['1d'].indices;
var d = cb_obj.get('data');
var items = [];
if (inds.length == 0) { return; }
for (i = 0; i < inds.length; i++) {
items.push(d['y'][inds[i]]);
}
var ym = average(items);
var std = standardDeviation(items);
cu1_avg.get('data')['y'] = [ym, ym]
cu1_lower.get('data')['y'] = [ym - (2 * std), ym - (2 * std)]
cu1_upper.get('data')['y'] = [(2 * std) + ym, (2 * std) + ym]
cb_obj.trigger('change');
cu1_avg.trigger('change');
cu1_lower.trigger('change');
cu1_upper.trigger('change');
//define the functions needed for standard dev and average
function standardDeviation(values){
var avg = average(values);
var squareDiffs = values.map(function(value){
var diff = value - avg;
var sqrDiff = diff * diff;
return sqrDiff;
});
var avgSquareDiff = average(squareDiffs);
var stdDev = Math.sqrt(avgSquareDiff);
return stdDev;
}
function average(data){
var sum = data.reduce(function(sum, value){
return sum + value;
}, 0);
var avg = sum / data.length;
return avg;
}
""")
import numpy as np
import bokeh
from bokeh.models.widgets import Dropdown
from bokeh.io import output_file, show
from bokeh.models import Callback
from bokeh.plotting import figure
from bokeh.layouts import layout
output_file("dropdown.html")
# Dummy plot, otherwise the Dropdown button is partially hidden...
x = np.linspace(-2 * np.pi, 2 * np.pi, 100)
y = np.sin(x)
p = figure(title="Sin(x)", x_axis_label='x', y_axis_label='y')
p.line(x, y)
callback = Callback(args=None,
code="""
console.log(cb_obj)
var cm_chosen = cb_obj.get('action');
alert(cm_chosen);
""")
menu = [("Item %s" % i, "item_%s" % i) for i in range(10)]
dropdown = Dropdown(label="Dropdown button %s" % bokeh.__version__,
type="success",
menu=menu,
callback=callback)
show(layout([dropdown, p]))
toolbar_location=None,
title='Hover over points')
p.line(x, y, line_dash="4 4", line_width=1, color='gray')
# Add a circle, that is visible only when selected
source = ColumnDataSource({'x': x, 'y': y})
invisible_circle = Circle(x='x',
y='y',
fill_color='gray',
fill_alpha=0.05,
line_color=None,
size=20)
visible_circle = Circle(x='x',
y='y',
fill_color='firebrick',
fill_alpha=0.5,
line_color=None,
size=20)
cr = p.add_glyph(source,
invisible_circle,
selection_glyph=visible_circle,
nonselection_glyph=invisible_circle)
# Add a hover tool, that selects the circle
code = "source.set('selected', cb_data['index']);"
callback = Callback(args={'source': source}, code=code)
p.add_tools(
HoverTool(tooltips=None, callback=callback, renderers=[cr], mode='hline'))
show(p)
# build a dict containing the grouped data
#medals = OrderedDict(bronze=bronze, silver=silver, gold=gold)
medals = OrderedDict(bronze=bronze)
# any of the following commented are also alid Bar inputs
#medals = pd.DataFrame(medals)
#medals = list(medals.values())
output_file("barc.html")
callback = Callback(args=dict(source=bsource), code="""
var data = source.get('data');
var f = cb_obj.get('value')
fac = data['factors']
ofac = data['ofactors']
for (i = 0; i < fac.length; i++) {
fac[i] = ofac[i]
}
source.trigger('change');
""")
slider = Slider(start=-2, end=2, value=1, step=.1,
title="value", callback=callback)
#layout = vform(slider, plot)
layout = vform(slider, p1)
output_file("cb_bar.html", title="callback example")
show(layout)
def _get_plot():
years, regions, fertility_df, life_expectancy_df, population_df_size, regions_df = _get_data(
)
# Set-up the sources
sources = {}
region_color = regions_df['region_color']
region_color.name = 'region_color'
for year in years:
fertility = fertility_df[year]
fertility.name = 'fertility'
life = life_expectancy_df[year]
life.name = 'life'
population = population_df_size[year]
population.name = 'population'
new_df = pd.concat([fertility, life, population, region_color], axis=1)
sources['_' + str(year)] = ColumnDataSource(new_df)
dictionary_of_sources = dict(
zip([x for x in years], ['_%s' % x for x in years]))
js_source_array = str(dictionary_of_sources).replace("'", "")
# Build the plot
# Set up the plot
xdr = Range1d(1, 9)
ydr = Range1d(20, 100)
plot = Plot(
x_range=xdr,
y_range=ydr,
title="",
plot_width=800,
plot_height=400,
outline_line_color=None,
toolbar_location=None,
)
AXIS_FORMATS = dict(
minor_tick_in=None,
minor_tick_out=None,
major_tick_in=None,
major_label_text_font_size="10pt",
major_label_text_font_style="normal",
axis_label_text_font_size="10pt",
axis_line_color='#AAAAAA',
major_tick_line_color='#AAAAAA',
major_label_text_color='#666666',
major_tick_line_cap="round",
axis_line_cap="round",
axis_line_width=1,
major_tick_line_width=1,
)
xaxis = LinearAxis(SingleIntervalTicker(interval=1),
axis_label="Children per woman (total fertility)",
**AXIS_FORMATS)
yaxis = LinearAxis(SingleIntervalTicker(interval=20),
axis_label="Life expectancy at birth (years)",
**AXIS_FORMATS)
plot.add_layout(xaxis, 'below')
plot.add_layout(yaxis, 'left')
# Add the year in background (add before circle)
text_source = ColumnDataSource({'year': ['%s' % years[0]]})
text = Text(x=2,
y=35,
text='year',
text_font_size='150pt',
text_color='#EEEEEE')
plot.add_glyph(text_source, text)
# Add the circle
renderer_source = sources['_%s' % years[0]]
circle_glyph = Circle(x='fertility',
y='life',
size='population',
fill_color='region_color',
fill_alpha=0.8,
line_color='#7c7e71',
line_width=0.5,
line_alpha=0.5)
circle_renderer = plot.add_glyph(renderer_source, circle_glyph)
# Add the hover (only against the circle and not other plot elements)
tooltips = "@index"
plot.add_tools(HoverTool(tooltips=tooltips, renderers=[circle_renderer]))
text_x = 7
text_y = 95
for i, region in enumerate(regions):
plot.add_glyph(
Text(x=text_x,
y=text_y,
text=[region],
text_font_size='10pt',
text_color='#666666'))
plot.add_glyph(
Circle(x=text_x - 0.1,
y=text_y + 2,
fill_color=Spectral6[i],
size=10,
line_color=None,
fill_alpha=0.8))
text_y = text_y - 5
# Add the slider
code = """
var year = slider.get('value'),
sources = %s,
new_source_data = sources[year].get('data');
renderer_source.set('data', new_source_data);
renderer_source.trigger('change');
text_source.set('data', {'year': [String(year)]});
text_source.trigger('change');
""" % js_source_array
callback = Callback(args=sources, code=code)
slider = Slider(start=years[0],
end=years[-1],
value=1,
step=1,
title="Year",
callback=callback)
callback.args["slider"] = slider
callback.args["renderer_source"] = renderer_source
callback.args["text_source"] = text_source
# Lay it out
return vplot(plot, hplot(slider))
from bokeh.plotting import figure, output_file, show
x = list(range(-50, 51))
y = list(x)
source = ColumnDataSource(data=dict(x=x, y=y))
plot = figure(y_range=(-100, 100), plot_width=400, plot_height=400)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)
callback = Callback(args=dict(source=source),
code="""
var data = source.get('data');
var f = cb_obj.get('value')
x = data['x']
y = data['y']
for (i = 0; i < x.length; i++) {
y[i] = f * x[i]
}
source.trigger('change');
""")
slider = Slider(start=-2,
end=2,
value=1,
step=.1,
title="value",
callback=callback)
layout = vform(slider, plot)
output_file("boxselecttool_callback.html")
source = ColumnDataSource(data=dict(x=[], y=[], width=[], height=[]))
callback = Callback(args=dict(source=source), code="""
// get data source from Callback args
var data = source.get('data');
/// get BoxSelectTool dimensions from cb_data parameter of Callback
var geometry = cb_data['geometry'];
/// calculate Rect attributes
var width = geometry['x1'] - geometry['x0'];
var height = geometry['y1'] - geometry['y0'];
var x = geometry['x0'] + width/2;
var y = geometry['y0'] + height/2;
/// update data source with new Rect attributes
data['x'].push(x);
data['y'].push(y);
data['width'].push(width);
data['height'].push(height);
// trigger update of data source
source.trigger('change');
""")
box_select = BoxSelectTool(callback=callback)
p = figure(plot_width=400,
plot_height=400,
def make_dashboard(motors, xy_train, operating_earnings, maintenance_cost,
repair_cost, run_interval):
#calculate revenue vs time dataframe
print '...generating dashboard...'
events = get_events(motors)
events['earnings'] = 0.0
events.loc[events.state == 'operating', 'earnings'] = operating_earnings
events['expenses'] = 0.0
events.loc[events.state == 'maintenance', 'expenses'] = maintenance_cost
events.loc[events.state == 'repair', 'expenses'] = repair_cost
money = events.groupby('Time').sum()[['earnings', 'expenses']]
money['revenue'] = money.earnings - money.expenses
money['cumulative_earnings'] = money.earnings.cumsum()
money['cumulative_expenses'] = money.expenses.cumsum()
money['cumulative_revenue'] = money.revenue.cumsum()
#map the (P,T) decision surface
T_min = 50
T_max = 150
P_min = 0
P_max = 100
T_axis = np.arange(T_min, T_max, 0.5)
P_axis = np.arange(P_min, P_max, 0.5)
x, y = np.meshgrid(T_axis, P_axis)
ttf = np.zeros((len(P_axis), len(T_axis)))
import copy
m = copy.deepcopy(motors[0])
for p_idx in np.arange(len(P_axis)):
for t_idx in np.arange(len(T_axis)):
m.Temp = T_axis[t_idx]
m.Pressure = P_axis[p_idx]
ttf[p_idx, t_idx] = m.predicted_time_to_fail()
#plot decision surface
from bokeh.plotting import figure, show, output_file, ColumnDataSource, vplot
from bokeh.models import HoverTool, Callback
from bokeh.io import vform
output_file('dashboard.html', title='Smart Maintenance Dashboard')
source = ColumnDataSource(data=dict(
x=xy_train.Temp,
y=xy_train.Pressure,
ttf=xy_train.time_to_fail,
size=0.6 * xy_train.time_to_fail,
))
dec_fig = figure(x_range=[T_min, T_max],
y_range=[P_min, P_max],
title='SVM Decision Surface',
x_axis_label='Temperature',
y_axis_label='Pressure',
tools='box_zoom,reset,hover,crosshair',
width=600,
plot_height=600)
dec_fig.title_text_font_size = '18pt'
dec_fig.xaxis.axis_label_text_font_size = '14pt'
dec_fig.yaxis.axis_label_text_font_size = '14pt'
dec_fig.image(image=[-ttf],
x=[T_min],
y=[P_min],
dw=[T_max - T_min],
dh=[P_max - P_min],
palette='RdYlGn8')
dec_fig.x('x',
'y',
size='size',
source=source,
fill_alpha=0.5,
fill_color='navy',
line_color='navy',
line_width=1,
line_alpha=0.5)
hover = dec_fig.select(dict(type=HoverTool))
hover.tooltips = [
("Temperature", "@x"),
("Pressure", "@y"),
("measured lifetime", "@ttf"),
]
#plot earnings vs time
source = ColumnDataSource(data=dict(
t=money.index,
earnings=money.cumulative_earnings / 1.e6,
expenses=money.cumulative_expenses / 1.e6,
revenue=money.cumulative_revenue / 1.e6,
zero=money.cumulative_revenue * 0,
))
earn_fig = figure(title='Cumulative Earnings & Expenses',
x_axis_label='Time',
y_axis_label='Earnings & Expenses (M$)',
tools='box_zoom,reset,hover,crosshair',
width=1000,
plot_height=300,
x_range=[0, 1200],
y_range=[0, 120])
earn_fig.title_text_font_size = '15pt'
earn_fig.xaxis.axis_label_text_font_size = '11pt'
earn_fig.yaxis.axis_label_text_font_size = '11pt'
earn_fig.line('t',
'earnings',
color='blue',
source=source,
line_width=5,
legend='earnings')
earn_fig.line('t',
'expenses',
color='red',
source=source,
line_width=5,
legend='expenses')
earn_fig.legend.orientation = "bottom_right"
earn_fig.patch([0, 200, 200, 0], [0, 0, 120, 120],
color='lightsalmon',
alpha=0.35,
line_width=0)
earn_fig.patch([200, 400, 400, 200], [0, 0, 120, 120],
color='gold',
alpha=0.35,
line_width=0)
earn_fig.patch([400, 1200, 1200, 400], [0, 0, 120, 120],
color='darkseagreen',
alpha=0.35,
line_width=0)
earn_fig.text([45], [101], ['run-to-fail'])
earn_fig.text([245], [101], ['scheduled'])
earn_fig.text([245], [90], ['maintenance'])
earn_fig.text([445], [101], ['predictive'])
earn_fig.text([445], [90], ['maintenance'])
hover = earn_fig.select(dict(type=HoverTool))
hover.tooltips = [
(" Time", "@t"),
(" earning (M$)", "@earnings"),
("expenses (M$)", "@expenses"),
]
#plot revenue vs time
rev_fig = figure(title='Cumulative Revenue',
x_axis_label='Time',
y_axis_label='Revenue (M$)',
tools='box_zoom,reset,hover,crosshair',
width=1000,
plot_height=300,
x_range=[0, 1200],
y_range=[-15, 10])
rev_fig.title_text_font_size = '15pt'
rev_fig.xaxis.axis_label_text_font_size = '11pt'
rev_fig.yaxis.axis_label_text_font_size = '11pt'
rev_fig.line('t',
'revenue',
color='green',
source=source,
line_width=5,
legend='revenue')
rev_fig.line('t',
'zero',
color='purple',
source=source,
line_width=3,
alpha=0.5,
line_dash=[10, 5])
rev_fig.legend.orientation = "bottom_right"
rev_fig.patch([0, 200, 200, 0], [-15, -15, 10, 10],
color='lightsalmon',
alpha=0.35,
line_width=0)
rev_fig.patch([200, 400, 400, 200], [-15, -15, 10, 10],
color='gold',
alpha=0.35,
line_width=0)
rev_fig.patch([400, 1200, 1200, 400], [-15, -15, 10, 10],
color='darkseagreen',
alpha=0.35,
line_width=0)
hover = rev_fig.select(dict(type=HoverTool))
hover.tooltips = [
(" Time", "@t"),
(" revenue (M$)", "@revenue"),
]
#plot number of motors vs time
N = events.groupby(['Time', 'state']).count().unstack()['id'].reset_index()
N.fillna(value=0, inplace=True)
N['total'] = N.maintenance + N.operating + N.repair
s1 = ColumnDataSource(data=dict(
Time=N.Time,
operating=N.operating,
maintenance=N.maintenance,
repair=N.repair,
total=N.total,
))
motor_fig = figure(title='Number of Motors',
x_axis_label='Time',
y_axis_label='Number of motors',
tools='box_zoom,reset,hover,crosshair',
width=1000,
plot_height=300,
x_range=[0, 1200],
y_range=[-10, 210])
motor_fig.title_text_font_size = '15pt'
motor_fig.xaxis.axis_label_text_font_size = '11pt'
motor_fig.yaxis.axis_label_text_font_size = '11pt'
motor_fig.line('Time',
'total',
color='blue',
source=s1,
line_width=3,
legend='total')
motor_fig.line('Time',
'operating',
color='green',
source=s1,
line_width=3,
legend='operating')
motor_fig.line('Time',
'maintenance',
color='orange',
source=s1,
line_width=3,
legend='maintenance')
motor_fig.line('Time',
'repair',
color='red',
source=s1,
line_width=3,
legend='repair')
motor_fig.legend.orientation = "top_right"
motor_fig.patch([0, 200, 200, 0], [-10, -10, 210, 210],
color='lightsalmon',
alpha=0.35,
line_width=0)
motor_fig.patch([200, 400, 400, 200], [-10, -10, 210, 210],
color='gold',
alpha=0.35,
line_width=0)
motor_fig.patch([400, 1200, 1200, 400], [-10, -10, 210, 210],
color='darkseagreen',
alpha=0.35,
line_width=0)
#display N table
from bokeh.models.widgets import DataTable, TableColumn
from bokeh.io import vform
columns = [
TableColumn(field='Time', title='Time'),
TableColumn(field='operating', title='operating'),
TableColumn(field='maintenance', title='maintenance'),
TableColumn(field='repair', title='repair'),
TableColumn(field='total', title='total'),
]
s2 = s1.clone()
N_table = DataTable(source=s2, columns=columns, width=600, height=300)
s1.callback = Callback(args=dict(s2=s2),
code="""
var inds = cb_obj.get('selected')['1d'].indices;
var d1 = cb_obj.get('data');
var d2 = s2.get('data');
d2['Time'] = []
d2['operating'] = []
d2['maintenance'] = []
d2['repair'] = []
d2['total'] = []
for (i = 0; i < inds.length; i++) {
d2['Time'].push(d1['Time'][inds[i]])
d2['operating'].push(d1['operating'][inds[i]])
d2['maintenance'].push(d1['maintenance'][inds[i]])
d2['repair'].push(d1['repair'][inds[i]])
d2['total'].push(d1['total'][inds[i]])
}
s2.trigger('change');
""")
#export plot to html and return
plot_grid = vplot(dec_fig, earn_fig, rev_fig, motor_fig, vform(N_table))
show(plot_grid, new='tab')
return money, events, N
"""
p1 = figure(title='Pan and Zoom Here',
x_range=(0, 100),
y_range=(0, 100),
tools='box_zoom,wheel_zoom,pan,reset',
plot_width=400,
plot_height=400)
p1.scatter(x,
y,
radius=radii,
fill_color=colors,
fill_alpha=0.6,
line_color=None)
p1.x_range.callback = Callback(args=dict(source=source, range=p1.x_range),
code=jscode % ('x', 'width'))
p1.y_range.callback = Callback(args=dict(source=source, range=p1.y_range),
code=jscode % ('y', 'height'))
p2 = figure(title='See Zoom Window Here',
x_range=(0, 100),
y_range=(0, 100),
tools='',
plot_width=400,
plot_height=400)
p2.scatter(x,
y,
radius=radii,
fill_color=colors,
fill_alpha=0.6,
line_color=None)
tools="lasso_select",
title="Select Here")
p.circle('x', 'y', color='color', size=8, source=s, alpha=0.4)
s2 = ColumnDataSource(data=dict(ym=[0.5, 0.5]))
p.line(x=[0, 1], y='ym', color="orange", line_width=5, alpha=0.6, source=s2)
s.callback = Callback(args=dict(s2=s2),
code="""
var inds = cb_obj.get('selected')['1d'].indices;
var d = cb_obj.get('data');
var ym = 0
if (inds.length == 0) { return; }
for (i = 0; i < d['color'].length; i++) {
d['color'][i] = "navy"
}
for (i = 0; i < inds.length; i++) {
d['color'][inds[i]] = "firebrick"
ym += d['y'][inds[i]]
}
ym /= inds.length
s2.get('data')['ym'] = [ym, ym]
cb_obj.trigger('change');
s2.trigger('change');
""")
show(p)
callback = Callback(args=dict(source=source),
code="""
var data = source.get('data');
var f = cb_obj.get('value')
fill = data['fill_color']
allc = data['all_color']
fc = data['first_color']
sc = data['second_color']
tc = data['third_color']
foc = data['fourth_color']
if (f == 4) {
for (i = 0; i < fill.length; i++) {
fill[i] = allc[i]
}
}
if (f == 3) {
for (i = 0; i < fill.length; i++) {
fill[i] = fc[i]
}
}
if (f == 2) {
for (i = 0; i < fill.length; i++) {
fill[i] = sc[i]
}
}
if (f == 1) {
for (i = 0; i < fill.length; i++) {
fill[i] = tc[i]
}
}
if (f == 0) {
for (i = 0; i < fill.length; i++) {
fill[i] = foc[i]
}
}
source.trigger('change');
""")
#First plot
s1 = ColumnDataSource(data=dict(x=x, y=y))
p1 = figure(tools=["lasso_select"], plot_width=600, plot_height=400)
p1.scatter('x', 'y', fill_color='black', line_color=None, size=10, source=s1)
#Second plot
s2 = ColumnDataSource(data=dict(x=[], y=[], y2=[]))
p2 = figure(plot_width=400, plot_height=400, tools=[])
m1 = ColumnDataSource(m1) #Actual Datasource for the second plot
p2.line(np.arange(0, 100, 1), 'y', source=s2) # From original data - series 1
p2.line(np.arange(0, 100, 1), 'y2', source=s2) # From original data - series 2
s1.callback = Callback(args=dict(s2=s2, m1=m1),
code="""
var inds = cb_obj.get('selected')['1d'].indices;
var d1 = m1.get('data');
var d2 = s2.get('data');
d2['y'] = []
d2['y2'] = []
for (i = 0; i < 11; i++) {o
d2['y'].push(d1[inds['0']][i]),
d2['y2'].push(d1[inds['1']][i])
}
s2.trigger('change');
""")
layout = hplot(p1, p2)
show(layout)
output_file("callback.html")
x = [random() for x in range(500)]
y = [random() for y in range(500)]
s1 = ColumnDataSource(data=dict(x=x, y=y))
p1 = figure(plot_width=400, plot_height=400, tools="lasso_select", title="Select Here")
p1.circle('x', 'y', source=s1, alpha=0.6)
s2 = ColumnDataSource(data=dict(x=[], y=[]))
p2 = figure(plot_width=400, plot_height=400, x_range=(0, 1), y_range=(0, 1),
tools="", title="Watch Here")
p2.circle('x', 'y', source=s2, alpha=0.6)
s1.callback = Callback(args=dict(s2=s2), code="""
var inds = cb_obj.get('selected')['1d'].indices;
var d1 = cb_obj.get('data');
var d2 = s2.get('data');
d2['x'] = []
d2['y'] = []
for (i = 0; i < inds.length; i++) {
d2['x'].push(d1['x'][inds[i]])
d2['y'].push(d1['y'][inds[i]])
}
s2.trigger('change');
""")
layout = hplot(p1, p2)
show(layout)
def build_map(data, variables, years=None, plot_width=800,
x_range=[70, 140], y_range=[10, 60], title=""):
#aspect_ratio = (x_range[1] - x_range[0]) / (y_range[1] - y_range[0])
#plot_height = int(plot_width / aspect_ratio)
plot_height = plot_width
x_range = Range1d(x_range[0], x_range[1])
y_range = Range1d(y_range[0], y_range[1])
plot = Plot(
x_range=x_range,
y_range=y_range,
title=title,
plot_width=plot_width,
plot_height=plot_height,
**PLOT_FORMATS)
if years is None:
tt_year = '—'
tt_var = variables[0]
color_column = '{}_color'.format(variables[0])
else:
tt_year = '@active_year'
tt_var = 'active_value'
color_column = 'active_color'
tooltip = """<span class='tooltip-text year'>{}</span>
<span class='tooltip-text country'>@alpha @name_zh @name_en</span>
<span class='tooltip-text value'>@{}</span>""".format(tt_year, tt_var)
plot.add_tools(HoverTool(tooltips=tooltip))
source = ColumnDataSource(data)
countries = Patches(
xs='xs',
ys='ys',
fill_color=color_column,
line_color='#000000'
)
renderer = plot.add_glyph(source, countries)
if years is None:
return plot
callback = Callback(code="""
var year = select.get('value');
var data = source.get('data');
var i = %d;
data['active_color'] = data[year + '_color'];
data['active_value'] = data[year];
while (--i >= 0) {
// Instead of doing this I'd like to
// be able to change the hover tool
data['active_year'][i] = year;
}
source.trigger('change');
""" % len(years))
select = Select(title="Year", options=years, value=years[-1],
callback=callback)
callback.args = {
'select': select,
'source': source
}
layout = vplot(select, plot)
return layout