def trail_map(data):
lon = (min(data.lon) + max(data.lon))/2
lat = (min(data.lat) + max(data.lat))/2
map_options = GMapOptions(lng=lon, lat=lat, zoom=13)
plot = GMapPlot(title="%s - Trail Map" % title, map_options=map_options, plot_width=800, plot_height=800)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
xgrid = Grid(plot=plot, dimension=0, ticker=xaxis.ticker, grid_line_dash="dashed", grid_line_color="gray")
ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker, grid_line_dash="dashed", grid_line_color="gray")
plot.renderers.extend([xgrid, ygrid])
plot.add_tools(PanTool(), WheelZoomTool(), ResetTool(), BoxSelectTool())
line_source = ColumnDataSource(dict(x=data.lon, y=data.lat, dist=data.dist))
line = Line(x="x", y="y", line_color="blue", line_width=2)
plot.add_glyph(line_source, line)
plot.x_range = DataRange1d(sources=[line_source.columns("x")])
plot.y_range = DataRange1d(sources=[line_source.columns("y")])
return plot
def large_plot(n):
from bokeh.models import (Plot, PlotContext, LinearAxis, Grid,
GlyphRenderer, ColumnDataSource, DataRange1d,
PanTool, WheelZoomTool, BoxZoomTool,
BoxSelectTool, BoxSelectionOverlay, ResizeTool,
PreviewSaveTool, ResetTool)
from bokeh.models.glyphs import Line
context = PlotContext()
objects = set([context])
for i in xrange(n):
source = ColumnDataSource(data=dict(x=[0, i + 1], y=[0, i + 1]))
xdr = DataRange1d(sources=[source.columns("x")])
ydr = DataRange1d(sources=[source.columns("y")])
plot = Plot(x_range=xdr, y_range=ydr)
xaxis = LinearAxis(plot=plot)
yaxis = LinearAxis(plot=plot)
xgrid = Grid(plot=plot, dimension=0)
ygrid = Grid(plot=plot, dimension=1)
tickers = [
xaxis.ticker, xaxis.formatter, yaxis.ticker, yaxis.formatter
]
glyph = Line(x='x', y='y')
renderer = GlyphRenderer(data_source=source, glyph=glyph)
plot.renderers.append(renderer)
pan = PanTool(plot=plot)
wheel_zoom = WheelZoomTool(plot=plot)
box_zoom = BoxZoomTool(plot=plot)
box_select = BoxSelectTool(plot=plot)
box_selection = BoxSelectionOverlay(tool=box_select)
resize = ResizeTool(plot=plot)
previewsave = PreviewSaveTool(plot=plot)
reset = ResetTool(plot=plot)
tools = [
pan, wheel_zoom, box_zoom, box_select, box_selection, resize,
previewsave, reset
]
plot.tools.append(tools)
context.children.append(plot)
objects |= set([
source, xdr, ydr, plot, xaxis, yaxis, xgrid, ygrid, renderer,
glyph, plot.tool_events
] + tickers + tools)
return context, objects
def trail_map(data):
lon = (min(data.lon) + max(data.lon)) / 2
lat = (min(data.lat) + max(data.lat)) / 2
map_options = GMapOptions(lng=lon, lat=lat, zoom=13)
plot = GMapPlot(title="%s - Trail Map" % title,
map_options=map_options,
plot_width=800,
plot_height=800)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
xgrid = Grid(plot=plot,
dimension=0,
ticker=xaxis.ticker,
grid_line_dash="dashed",
grid_line_color="gray")
ygrid = Grid(plot=plot,
dimension=1,
ticker=yaxis.ticker,
grid_line_dash="dashed",
grid_line_color="gray")
plot.renderers.extend([xgrid, ygrid])
hover = HoverTool(tooltips=[("distance", "@dist")])
plot.add_tools(hover, PanTool(), WheelZoomTool(), ResetTool(),
BoxSelectTool())
line_source = ColumnDataSource(dict(x=data.lon, y=data.lat,
dist=data.dist))
line = Line(x="x", y="y", line_color="blue", line_width=2)
plot.add_glyph(line_source, line)
plot.x_range = DataRange1d(sources=[line_source.columns("x")])
plot.y_range = DataRange1d(sources=[line_source.columns("y")])
return plot
def altitude_profile(data):
plot = Plot(title="%s - Altitude Profile" % title,
plot_width=800,
plot_height=400)
xaxis = LinearAxis(axis_label="Distance (km)")
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis(axis_label="Altitude (m)")
plot.add_layout(yaxis, 'left')
xgrid = Grid(plot=plot, dimension=0, ticker=xaxis.ticker)
ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker)
plot.renderers.extend([xgrid, ygrid])
plot.add_tools(PanTool(), WheelZoomTool(), ResetTool(), BoxSelectTool())
X, Y = data.dist, data.alt
y0 = min(Y)
patches_source = ColumnDataSource(
dict(xs=[[X[i], X[i + 1], X[i + 1], X[i]] for i in range(len(X[:-1]))],
ys=[[y0, y0, Y[i + 1], Y[i]] for i in range(len(Y[:-1]))],
color=data.colors[:-1]))
patches = Patches(xs="xs", ys="ys", fill_color="color", line_color="color")
plot.add_glyph(patches_source, patches)
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(sources=[line_source.columns("x")])
plot.y_range = DataRange1d(sources=[line_source.columns("y")])
return plot
def altitude_profile(data):
plot = Plot(title="%s - Altitude Profile" % title, plot_width=800, plot_height=400)
xaxis = LinearAxis(axis_label="Distance (km)")
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis(axis_label="Altitude (m)")
plot.add_layout(yaxis, 'left')
xgrid = Grid(plot=plot, dimension=0, ticker=xaxis.ticker)
ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker)
plot.renderers.extend([xgrid, ygrid])
plot.add_tools(PanTool(), WheelZoomTool(), ResetTool(), BoxSelectTool())
X, Y = data.dist, data.alt
y0 = min(Y)
patches_source = ColumnDataSource(dict(
xs = [ [X[i], X[i+1], X[i+1], X[i]] for i in range(len(X[:-1])) ],
ys = [ [y0, y0, Y[i+1], Y[i]] for i in range(len(Y[:-1])) ],
color = data.colors[:-1]
))
patches = Patches(xs="xs", ys="ys", fill_color="color", line_color="color")
plot.add_glyph(patches_source, patches)
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(sources=[line_source.columns("x")])
plot.y_range = DataRange1d(sources=[line_source.columns("y")])
return plot
def large_plot(n):
from bokeh.models import (Plot, PlotContext, LinearAxis, Grid, GlyphRenderer,
ColumnDataSource, DataRange1d, PanTool, WheelZoomTool, BoxZoomTool,
BoxSelectTool, BoxSelectionOverlay, ResizeTool, PreviewSaveTool,
ResetTool)
from bokeh.models.glyphs import Line
context = PlotContext()
objects = set([context])
for i in xrange(n):
source = ColumnDataSource(data=dict(x=[0, i + 1], y=[0, i + 1]))
xdr = DataRange1d(sources=[source.columns("x")])
ydr = DataRange1d(sources=[source.columns("y")])
plot = Plot(x_range=xdr, y_range=ydr)
xaxis = LinearAxis(plot=plot)
yaxis = LinearAxis(plot=plot)
xgrid = Grid(plot=plot, dimension=0)
ygrid = Grid(plot=plot, dimension=1)
tickers = [xaxis.ticker, xaxis.formatter, yaxis.ticker, yaxis.formatter]
glyph = Line(x='x', y='y')
renderer = GlyphRenderer(data_source=source, glyph=glyph)
plot.renderers.append(renderer)
pan = PanTool(plot=plot)
wheel_zoom = WheelZoomTool(plot=plot)
box_zoom = BoxZoomTool(plot=plot)
box_select = BoxSelectTool(plot=plot)
box_selection = BoxSelectionOverlay(tool=box_select)
resize = ResizeTool(plot=plot)
previewsave = PreviewSaveTool(plot=plot)
reset = ResetTool(plot=plot)
tools = [pan, wheel_zoom, box_zoom, box_select, box_selection, resize, previewsave, reset]
plot.tools.append(tools)
context.children.append(plot)
objects |= set([source, xdr, ydr, plot, xaxis, yaxis, xgrid, ygrid, renderer, glyph, plot.tool_events] + tickers + tools)
return context, objects
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)
summer_start = df.Date.irow(summer_start)
summer_end = df.Date.irow(summer_end)
calendar_end = df.Date.irow(-1)
d1 = calendar_start + (summer_start - calendar_start) / 2
d2 = summer_start + (summer_end - summer_start) / 2
d3 = summer_end + (calendar_end - summer_end) / 2
text_source = ColumnDataSource(
dict(
dates=[d1, d2, d3],
times=[dt.time(11, 30)] * 3,
texts=["CST (UTC+1)", "CEST (UTC+2)", "CST (UTC+1)"],
))
xdr = DataRange1d(sources=[source.columns("dates")])
ydr = DataRange1d(sources=[source.columns("sunrises", "sunsets")])
title = "Daylight Hours - Warsaw, Poland"
plot = Plot(title=title,
x_range=xdr,
y_range=ydr,
plot_width=800,
plot_height=400)
patch1 = Patch(x="dates", y="times", fill_color="skyblue", fill_alpha=0.8)
plot.add_glyph(patch1_source, patch1)
patch2 = Patch(x="dates", y="times", fill_color="orange", fill_alpha=0.8)
plot.add_glyph(patch2_source, patch2)
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=source, columns=columns, editable=True)
xdr = DataRange1d(sources=[source.columns("index")])
ydr = DataRange1d(sources=[source.columns("cty"), source.columns("hwy")])
plot = Plot(title=None,
x_range=xdr,
y_range=ydr,
plot_width=1000,
plot_height=300)
xaxis = LinearAxis(plot=plot)
plot.below.append(xaxis)
yaxis = LinearAxis(plot=plot)
ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker)
plot.left.append(yaxis)
cty_glyph = Circle(x="index",
y="cty",
fill_color="#396285",
size=8,
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(sources=[source1.columns("x")])
ydr1 = DataRange1d(sources=[source1.columns("y")])
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))
xdr2 = DataRange1d(sources=[source2.columns("x")])
ydr2 = DataRange1d(sources=[source2.columns("y")])
plot2 = Plot(title="Plot2", x_range=xdr2, y_range=ydr2, plot_width=400, plot_height=400)
plot2.tools.append(TapTool(plot=plot2))
plot2.add_glyph(source2, Circle(x="x", y="y", size=20, fill_color="color"))
def on_selection_change1(obj, attr, _, inds):
color = ["blue"]*N
if inds:
try:
rate = unemployment[county_id]
idx = min(int(rate/2), 5)
county_colors.append(colors[idx])
except KeyError:
county_colors.append("black")
county_source = ColumnDataSource(
data=dict(
county_xs=[us_counties[code]["lons"] for code in us_counties if us_counties[code]["state"] not in ["ak", "hi", "pr", "gu", "vi", "mp", "as"]],
county_ys=[us_counties[code]["lats"] for code in us_counties if us_counties[code]["state"] not in ["ak", "hi", "pr", "gu", "vi", "mp", "as"]],
county_colors=county_colors
)
)
xdr = DataRange1d(sources=[state_source.columns("state_xs")])
ydr = DataRange1d(sources=[state_source.columns("state_ys")])
plot = Plot(x_range=xdr, y_range=ydr, min_border=0, border_fill="white",
title="2009 Unemployment Data", plot_width=1300, plot_height=800, toolbar_location="left")
county_patches = Patches(xs="county_xs", ys="county_ys", fill_color="county_colors", fill_alpha=0.7, line_color="white", line_width=0.5)
plot.add_glyph(county_source, county_patches)
state_patches = Patches(xs="state_xs", ys="state_ys", fill_alpha=0.0, line_color="#884444", line_width=2)
plot.add_glyph(state_source, state_patches)
plot.add_tools(ResizeTool())
doc = Document()
doc.add(plot)
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(sources=[source1.columns("x")])
ydr1 = DataRange1d(sources=[source1.columns("y")])
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))
xdr2 = DataRange1d(sources=[source2.columns("x")])
ydr2 = DataRange1d(sources=[source2.columns("y")])
plot2 = Plot(title="Plot2",
x_range=xdr2,
y_range=ydr2,
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=source, columns=columns, editable=True)
# TODO: rewrite this using plotting API {{{
xdr = DataRange1d(sources=[source.columns("index")])
ydr = DataRange1d(sources=[source.columns("cty"), source.columns("hwy")])
plot = Plot(title=None, x_range=xdr, y_range=ydr, plot_width=1000, plot_height=300)
xaxis = LinearAxis(plot=plot)
plot.below.append(xaxis)
yaxis = LinearAxis(plot=plot)
ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker)
plot.left.append(yaxis)
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 = GlyphRenderer(data_source=source, glyph=cty_glyph)
hwy = GlyphRenderer(data_source=source, glyph=hwy_glyph)
tooltips = [
("Manufacturer", "@manufacturer"),
("Model", "@model"),
("Displacement", "@displ"),
sprint["Country"] = sprint.Abbrev.map(lambda abbr: abbrev_to_country[abbr])
sprint["Medal"] = sprint.Medal.map(lambda medal: medal.lower())
sprint["Speed"] = 100.0 / sprint.Time
sprint["MetersBack"] = 100.0 * (1.0 - t0 / sprint.Time)
sprint["MedalFill"] = sprint.Medal.map(lambda medal: fill_color[medal])
sprint["MedalLine"] = sprint.Medal.map(lambda medal: line_color[medal])
sprint["SelectedName"] = sprint[["Name", "Medal", "Year"]].apply(
tuple, axis=1).map(lambda args: selected_name(*args))
source = ColumnDataSource(sprint)
title = "Usain Bolt vs. 116 years of Olympic sprinters"
xdr = Range1d(
start=sprint.MetersBack.max() + 2,
end=0) # XXX: +2 is poor-man's padding (otherwise misses last tick)
ydr = DataRange1d(sources=[source.columns("Year")],
rangepadding=0.05) # XXX: should be 2 years (both sides)
plot = Plot(title=title,
x_range=xdr,
y_range=ydr,
plot_width=1000,
plot_height=600,
toolbar_location=None,
outline_line_color=None)
xticker = SingleIntervalTicker(interval=5, num_minor_ticks=0)
xaxis = LinearAxis(ticker=xticker,
axis_line_color=None,
major_tick_line_color=None,
axis_label="Meters behind 2012 Bolt",
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 bokeh.embed import file_html
from bokeh.models.glyphs import Circle
from bokeh.models import (Plot, DataRange1d, DatetimeAxis, ColumnDataSource,
PanTool, WheelZoomTool)
from bokeh.resources import INLINE
x = arange(-2 * pi, 2 * pi, 0.1)
y = sin(x)
# Create an array of times, starting at the current time, and extending
# for len(x) number of hours.
times = np.arange(len(x)) * 3600000 + time.time()
source = ColumnDataSource(data=dict(x=x, y=y, times=times))
xdr = DataRange1d(sources=[source.columns("times")])
ydr = DataRange1d(sources=[source.columns("y")])
plot = Plot(x_range=xdr, y_range=ydr, min_border=80)
circle = Circle(x="times", y="y", fill_color="red", size=5, line_color="black")
plot.add_glyph(source, circle)
plot.add_layout(DatetimeAxis(), 'below')
plot.add_layout(DatetimeAxis(), 'left')
plot.add_tools(PanTool(), WheelZoomTool())
doc = Document()
doc.add(plot)
calendar_start = df.Date.irow(0)
summer_start = df.Date.irow(summer_start)
summer_end = df.Date.irow(summer_end)
calendar_end = df.Date.irow(-1)
d1 = calendar_start + (summer_start - calendar_start)/2
d2 = summer_start + (summer_end - summer_start)/2
d3 = summer_end + (calendar_end - summer_end)/2
text_source = ColumnDataSource(dict(
dates = [d1, d2, d3],
times = [dt.time(11, 30)]*3,
texts = ["CST (UTC+1)", "CEST (UTC+2)", "CST (UTC+1)"],
))
xdr = DataRange1d(sources=[source.columns("dates")])
ydr = DataRange1d(sources=[source.columns("sunrises", "sunsets")])
title = "Daylight Hours - Warsaw, Poland"
plot = Plot(
title=title,
x_range=xdr, y_range=ydr,
plot_width=800, plot_height=400
)
patch1 = Patch(x="dates", y="times", fill_color="skyblue", fill_alpha=0.8)
plot.add_glyph(patch1_source, patch1)
patch2 = Patch(x="dates", y="times", fill_color="orange", fill_alpha=0.8)
plot.add_glyph(patch2_source, patch2)
t0 = sprint.Time[0]
sprint["Abbrev"] = sprint.Country
sprint["Country"] = sprint.Abbrev.map(lambda abbr: abbrev_to_country[abbr])
sprint["Medal"] = sprint.Medal.map(lambda medal: medal.lower())
sprint["Speed"] = 100.0/sprint.Time
sprint["MetersBack"] = 100.0*(1.0 - t0/sprint.Time)
sprint["MedalFill"] = sprint.Medal.map(lambda medal: fill_color[medal])
sprint["MedalLine"] = sprint.Medal.map(lambda medal: line_color[medal])
sprint["SelectedName"] = sprint[["Name", "Medal", "Year"]].apply(tuple, axis=1).map(lambda args: selected_name(*args))
source = ColumnDataSource(sprint)
title = "Usain Bolt vs. 116 years of Olympic sprinters"
xdr = Range1d(start=sprint.MetersBack.max()+2, end=0) # XXX: +2 is poor-man's padding (otherwise misses last tick)
ydr = DataRange1d(sources=[source.columns("Year")], rangepadding=0.05) # XXX: should be 2 years (both sides)
plot = Plot(title=title, x_range=xdr, y_range=ydr, plot_width=1000, plot_height=600, toolbar_location=None, outline_line_color=None)
xticker = SingleIntervalTicker(interval=5, num_minor_ticks=0)
xaxis = LinearAxis(ticker=xticker, axis_line_color=None, major_tick_line_color=None,
axis_label="Meters behind 2012 Bolt", axis_label_text_font_size="10pt", axis_label_text_font_style="bold")
plot.add_layout(xaxis, "below")
xgrid = Grid(dimension=0, ticker=xaxis.ticker, grid_line_dash="dashed")
plot.add_layout(xgrid)
yticker = SingleIntervalTicker(interval=12, num_minor_ticks=0)
yaxis = LinearAxis(ticker=yticker, major_tick_in=-5, major_tick_out=10)
plot.add_layout(yaxis, "right")
radius = dict(value=5, units="screen")
medal_glyph = Circle(x="MetersBack", y="Year", radius=radius, fill_color="MedalFill", line_color="MedalLine", fill_alpha=0.5)
class DataTables(object):
def __init__(self):
self.document = Document()
self.session = Session()
self.session.use_doc('data_tables_server')
self.session.load_document(self.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(self.create())
self.session.store_document(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)
xdr = DataRange1d(sources=[self.source.columns("index")])
ydr = DataRange1d(sources=[self.source.columns("cty"), self.source.columns("hwy")])
plot = Plot(title=None, x_range=xdr, y_range=ydr, plot_width=800, plot_height=300)
xaxis = LinearAxis(plot=plot)
plot.below.append(xaxis)
yaxis = LinearAxis(plot=plot)
ygrid = Grid(plot=plot, dimension=1, ticker=yaxis.ticker)
plot.left.append(yaxis)
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 = GlyphRenderer(data_source=self.source, glyph=cty_glyph)
hwy = GlyphRenderer(data_source=self.source, glyph=hwy_glyph)
tooltips = [
("Manufacturer", "@manufacturer"),
("Model", "@model"),
("Displacement", "@displ"),
("Year", "@year"),
("Cylinders", "@cyl"),
("Transmission", "@trans"),
("Drive", "@drv"),
("Class", "@class"),
]
cty_hover_tool = HoverTool(plot=plot, renderers=[cty], tooltips=tooltips + [("City MPG", "@cty")])
hwy_hover_tool = HoverTool(plot=plot, renderers=[hwy], tooltips=tooltips + [("Highway MPG", "@hwy")])
select_tool = BoxSelectTool(plot=plot, renderers=[cty, hwy], dimensions=['width'])
plot.tools.extend([cty_hover_tool, hwy_hover_tool, select_tool])
plot.renderers.extend([cty, hwy, ygrid])
controls = VBox(children=[manufacturer_select, model_select, transmission_select, drive_select, class_select], width=200)
top_panel = HBox(children=[controls, plot])
layout = VBox(children=[top_panel, data_table])
return layout
def on_manufacturer_change(self, obj, attr, _, value):
self.manufacturer_filter = None if value == "All" else value
self.update_data()
def on_model_change(self, obj, attr, _, value):
self.model_filter = None if value == "All" else value
self.update_data()
def on_transmission_change(self, obj, attr, _, value):
self.transmission_filter = None if value == "All" else value
self.update_data()
def on_drive_change(self, obj, attr, _, value):
self.drive_filter = None if value == "All" else value
self.update_data()
def on_class_change(self, obj, 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)
self.session.store_document(self.document)
def run(self, do_view=False, poll_interval=0.5):
link = self.session.object_link(self.document.context)
print("Please visit %s to see the plots" % link)
if do_view: view(link)
print("\npress ctrl-C to exit")
self.session.poll_document(self.document)
from bokeh.models.glyphs import Quad
from bokeh.plotting import show
N = 9
x = np.linspace(-2, 2, N)
y = x**2
source = ColumnDataSource(
dict(
left=x,
top=y,
right=x - x**3 / 10 + 0.3,
bottom=y - x**2 / 10 + 0.5,
))
xdr = DataRange1d(sources=[source.columns("left", "right")])
ydr = DataRange1d(sources=[source.columns("top", "bottom")])
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 = Quad(left="left",
right="right",
top="top",
from bokeh.sampledata.iris import flowers
colormap = {'setosa': 'red', 'versicolor': 'green', 'virginica': 'blue'}
flowers['color'] = flowers['species'].map(lambda x: colormap[x])
source = ColumnDataSource(data=dict(petal_length=flowers['petal_length'],
petal_width=flowers['petal_width'],
sepal_length=flowers['sepal_length'],
sepal_width=flowers['sepal_width'],
color=flowers['color']))
text_source = ColumnDataSource(data=dict(xcenter=[125], ycenter=[135]))
xdr = DataRange1d(sources=[
source.columns("petal_length", "petal_width", "sepal_length",
"sepal_width")
])
ydr = DataRange1d(sources=[
source.columns("petal_length", "petal_width", "sepal_length",
"sepal_width")
])
def make_plot(xname, yname, xax=False, yax=False, text=None):
plot = Plot(x_range=xdr,
y_range=ydr,
background_fill="#efe8e2",
border_fill='white',
title="",
min_border=2,
h_symmetry=False,
source = ColumnDataSource(
data=dict(
petal_length=flowers['petal_length'],
petal_width=flowers['petal_width'],
sepal_length=flowers['sepal_length'],
sepal_width=flowers['sepal_width'],
color=flowers['color']
)
)
text_source = ColumnDataSource(
data=dict(xcenter=[125], ycenter=[135])
)
xdr = DataRange1d(sources=[source.columns("petal_length", "petal_width", "sepal_length", "sepal_width")])
ydr = DataRange1d(sources=[source.columns("petal_length", "petal_width", "sepal_length", "sepal_width")])
def make_plot(xname, yname, xax=False, yax=False, text=None):
plot = Plot(
x_range=xdr, y_range=ydr, background_fill="#efe8e2",
border_fill='white', title="", min_border=2, h_symmetry=False, v_symmetry=False,
plot_width=250, plot_height=250)
circle = Circle(x=xname, y=yname, fill_color="color", fill_alpha=0.2, size=4, line_color="color")
plot.add_glyph(source, circle)
xticker = BasicTicker()
if xax:
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
)
from bokeh.session import Session
document = Document()
session = Session()
session.use_doc('line_animate')
session.load_document(document)
x = linspace(-2*pi, 2*pi, 1000)
x_static = linspace(-2*pi, 2*pi, 1000)
y = sin(x)
z = cos(x)
source = ColumnDataSource(data=dict(x=x, y=y, z=z, x_static=x_static))
xdr = DataRange1d(sources=[source.columns("x")])
xdr_static = DataRange1d(sources=[source.columns("x_static")])
ydr = DataRange1d(sources=[source.columns("y")])
plot = Plot(x_range=xdr_static, y_range=ydr, min_border=50)
line_glyph = Line(x="x", y="y", line_color="blue")
plot.add_glyph(source, line_glyph)
line_glyph2 = Line(x="x", y="z", line_color="red")
plot.add_glyph(source, line_glyph2)
plot.add_layout(LinearAxis(), 'below')
plot.add_layout(LinearAxis(), 'left')
plot.add_tools(PanTool(), WheelZoomTool())
from bokeh.models.glyphs import Quad
from bokeh.plotting import show
N = 9
x = np.linspace(-2, 2, N)
y = x**2
source = ColumnDataSource(dict(
left=x,
top=y,
right=x-x**3/10 + 0.3,
bottom=y-x**2/10 + 0.5,
)
)
xdr = DataRange1d(sources=[source.columns("left", "right")])
ydr = DataRange1d(sources=[source.columns("top", "bottom")])
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 = Quad(left="left", right="right", top="top", bottom="bottom", fill_color="#b3de69")
plot.add_glyph(source, glyph)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
ColumnDataSource, PanTool, WheelZoomTool
)
from bokeh.resources import INLINE
x = arange(-2 * pi, 2 * pi, 0.1)
y = sin(x)
# Create an array of times, starting at the current time, and extending
# for len(x) number of hours.
times = np.arange(len(x)) * 3600000 + time.time()
source = ColumnDataSource(
data=dict(x=x, y=y, times=times)
)
xdr = DataRange1d(sources=[source.columns("times")])
ydr = DataRange1d(sources=[source.columns("y")])
plot = Plot(x_range=xdr, y_range=ydr, min_border=80)
circle = Circle(x="times", y="y", fill_color="red", size=5, line_color="black")
plot.add_glyph(source, circle)
plot.add_layout(DatetimeAxis(), 'below')
plot.add_layout(DatetimeAxis(), 'left')
plot.add_tools(PanTool(), WheelZoomTool())
doc = Document()
doc.add(plot)
import numpy as np
from bokeh.document import Document
from bokeh.models import ColumnDataSource, DataRange1d, Plot, LinearAxis, Grid
from bokeh.models.markers import CircleX
from bokeh.plotting import show
N = 9
x = np.linspace(-2, 2, N)
y = x**2
sizes = np.linspace(10, 20, N)
source = ColumnDataSource(dict(x=x, y=y, sizes=sizes))
xdr = DataRange1d(sources=[source.columns("x")])
ydr = DataRange1d(sources=[source.columns("y")])
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 = CircleX(x="x", y="y", size="sizes", line_color="#dd1c77", fill_color=None)
plot.add_glyph(source, glyph)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
from bokeh.models import (Plot, DataRange1d, LinearAxis, Grid,
ColumnDataSource, PanTool, WheelZoomTool)
from bokeh.resources import INLINE
from bokeh.sampledata.iris import flowers
colormap = {'setosa': 'red', 'versicolor': 'green', 'virginica': 'blue'}
flowers['color'] = flowers['species'].map(lambda x: colormap[x])
source = ColumnDataSource(data=dict(petal_length=flowers['petal_length'],
petal_width=flowers['petal_width'],
sepal_length=flowers['sepal_length'],
sepal_width=flowers['sepal_width'],
color=flowers['color']))
xdr = DataRange1d(sources=[source.columns("petal_length")])
ydr = DataRange1d(sources=[source.columns("petal_width")])
plot = Plot(x_range=xdr, y_range=ydr, min_border=80, title="Iris Data")
circle = Circle(x="petal_length",
y="petal_width",
size=10,
fill_color="color",
fill_alpha=0.2,
line_color="color")
plot.add_glyph(source, circle)
xaxis = LinearAxis(axis_label="petal length", bounds=(1, 7), major_tick_in=0)
plot.add_layout(xaxis, 'below')
