def test_heatmap_recipe(self):
source = ServerDataSource(data_url="fn://bivariate",
owner_username="******")
plot = square('A',
'B',
source=source,
plot_width=600,
plot_height=400,
title="Test Title")
plot2 = ar_downsample.heatmap(plot,
palette="Reds9",
reserve_val=0,
points=True,
client_color=True,
title="Test Title 2")
source2 = self._find_source(plot2)
self.assertEquals("Test Title 2", plot2.title)
self.assertEquals(type(source2), ServerDataSource)
transform = source2.transform
self.assertEquals(type(transform['info']), ar_downsample.Const)
self.assertEquals(type(transform['agg']), ar_downsample.Count)
self.assertEquals(type(transform['shader']), ar_downsample.Seq)
self.assertEquals(transform['shader'].out, "image")
def test_heatmap_recipe(self):
ar_downsample._loadAR()
reset_output()
sess = Session(client=app.test_client())
output_server('Census', session=sess)
source = ServerDataSource(expr={
'op': 'Field',
'args': [':leaf', 'bivariate']
})
plot = figure(plot_width=600, plot_height=400, title="Test Title")
plot.square('A', 'B', source=source)
plot2 = ar_downsample.heatmap(plot,
palette="Reds9",
reserve_val=0,
points=True,
client_color=True,
title="Test Title 2")
source2 = self._find_source(plot2)
self.assertEquals("Test Title 2", plot2.title)
self.assertEquals(type(source2), ServerDataSource)
transform = source2.transform
self.assertEquals(type(transform['info']), ar_downsample.Const)
self.assertEquals(type(transform['agg']), ar_downsample.Count)
self.assertEquals(type(transform['shader']), ar_downsample.Seq)
self.assertEquals(transform['shader'].out, "image")
def test_heatmap_recipie(self):
source = ServerDataSource(data_url="fn://bivariate", owner_username="******")
plot = square('A', 'B',
source=source,
plot_width=600,
plot_height=400,
title="Test Title")
plot2 = ar_downsample.heatmap(plot, palette=["Reds-9"], reserve_val=0, points=True, client_color=True, title="Test Title 2")
source2 = self._find_source(plot2)
self.assertEquals("Test Title 2", plot2.title)
self.assertEquals(type(source2), ServerDataSource)
transform = source2.transform
self.assertEquals(type(transform['info']), ar_downsample.Const)
self.assertEquals(type(transform['agg']), ar_downsample.Count)
self.assertEquals(type(transform['shader']), ar_downsample.Seq)
self.assertEquals(transform['shader'].out, "image")
def test_heatmap_recipe(self):
ar_downsample._loadAR()
reset_output()
sess = Session(client=app.test_client())
output_server('Census', session=sess)
source = ServerDataSource(
expr={'op': 'Field', 'args': [':leaf', 'bivariate']}
)
plot = figure(plot_width=600,
plot_height=400,
title="Test Title")
plot.square('A', 'B', source=source)
plot2 = ar_downsample.heatmap(plot, palette="Reds9", reserve_val=0, points=True, client_color=True, title="Test Title 2")
source2 = self._find_source(plot2)
self.assertEquals("Test Title 2", plot2.title)
self.assertEquals(type(source2), ServerDataSource)
transform = source2.transform
self.assertEquals(type(transform['info']), ar_downsample.Const)
self.assertEquals(type(transform['agg']), ar_downsample.Count)
self.assertEquals(type(transform['shader']), ar_downsample.Seq)
self.assertEquals(transform['shader'].out, "image")
from blaze.server.client import Client
from blaze import Data
output_server("abstractrender")
c = Client('http://localhost:5006')
d = Data(c)
source = ServerDataSource()
source.from_blaze(d.gauss, local=True)
plot = figure()
plot.square('oneA', 'oneB', color='#FF00FF', source=source)
#Server-side colored heatmap
arplot = ar.heatmap(plot, spread=3, transform=None, title="Server-rendered, uncorrected")
arplot = ar.heatmap(plot, spread=3, transform="Log", title="Server-rendered, log transformed")
arplot = ar.heatmap(plot, spread=3, title="Server-rendered, perceptually corrected")
ar.replot(plot,
agg=ar.Count(),
info=ar.Const(val=1),
shader=ar.Spread(factor=3) + ar.Cuberoot() + ar.InterpolateColor(low=(255,200,200), high=(255,0,0)),
points=True,
title="Manually process: perceptually corrected",
reserve_val=0)
# Client-side colored heatmap
# I think this has been broken for a while?
# ar.heatmap(plot, spread=3, client_color=True, palette="Reds9", title="Client-colored")
from bokeh.plotting import square, output_server, show
from bokeh.objects import ServerDataSource
import bokeh.transforms.ar_downsample as ar
"""
In order to run this example, you have to execute
./bokeh-server -D remotedata
the remote data directory in the bokeh checkout has the sample data for this example
In addition, you must install ArrayManagement from this branch (soon to be master)
https://github.com/ContinuumIO/ArrayManagement
"""
output_server("Census")
# 2010 US Census tracts
source = ServerDataSource(data_url="/defaultuser/CensusTracts.hdf5", owner_username="******")
plot = square(
'LON', 'LAT',
source=source,
plot_width=600,
plot_height=400,
title="Census Tracts")
ar.heatmap(plot, palette=["Reds-9"], reserve_val=0, points=True, client_color=True, title="Census Tracts (Client Colors)")
ar.heatmap(plot, low=(255, 200, 200), points=True, title="Census Tracts (Server Colors)")
ar.contours(plot, title="ISO Contours")
show()
import numpy as np
from bokeh.plotting import square, output_server, image, show
from bokeh.models import ServerDataSource
import bokeh.transforms.ar_downsample as ar
output_server("abstractrender")
source = ServerDataSource(data_url="fn://gauss", owner_username="******")
plot = square('oneA', 'oneB', color='#FF00FF', source=source)
#Server-side colored heatmap
ar.heatmap(plot,
spread=3,
transform=None,
title="Server-rendered, uncorrected")
ar.heatmap(plot,
spread=3,
transform="Log",
title="Server-rendered, log transformed")
ar.heatmap(plot, spread=3, title="Server-rendered, perceptually corrected")
ar.replot(plot,
agg=ar.Count(),
info=ar.Const(val=1),
shader=ar.Spread(factor=3) + ar.Cuberoot() +
ar.InterpolateColor(low=(255, 200, 200), high=(255, 0, 0)),
points=True,
title="Manually process: perceptually corrected",
reserve_val=0)
# Client-side colored heatmap
the remote data directory in the bokeh checkout has the sample data for this example
In addition, you must install ArrayManagement from this branch (soon to be master)
https://github.com/ContinuumIO/ArrayManagement
"""
output_server("Census")
# 2010 US Census tracts
source = ServerDataSource(data_url="/defaultuser/CensusTracts.hdf5",
owner_username="******")
plot = square('LON',
'LAT',
source=source,
plot_width=600,
plot_height=400,
title="Census Tracts")
ar.heatmap(plot,
palette=["Reds-9"],
reserve_val=0,
points=True,
client_color=True,
title="Census Tracts (Client Colors)")
ar.heatmap(plot,
low=(255, 200, 200),
points=True,
title="Census Tracts (Server Colors)")
ar.contours(plot, title="ISO Contours")
show()
import numpy as np
from bokeh.plotting import square, output_server, image, show
from bokeh.models import ServerDataSource
import bokeh.transforms.ar_downsample as ar
output_server("abstractrender")
source = ServerDataSource(data_url="fn://gauss", owner_username="******")
plot = square('oneA', 'oneB', color='#FF00FF', source=source)
#Server-side colored heatmap
ar.heatmap(plot, spread=3, transform=None, title="Server-rendered, uncorrected")
ar.heatmap(plot, spread=3, transform="Log", title="Server-rendered, log transformed")
ar.heatmap(plot, spread=3, title="Server-rendered, perceptually corrected")
ar.replot(plot,
agg=ar.Count(),
info=ar.Const(val=1),
shader=ar.Spread(factor=3) + ar.Cuberoot() + ar.InterpolateColor(low=(255,200,200), high=(255,0,0)),
points=True,
title="Manually process: perceptually corrected",
reserve_val=0)
# Client-side colored heatmap
ar.heatmap(plot, spread=3, client_color=True, palette="Reds9", title="Client-colored")
# Contours come in the same framework, but since the results of the shader are lines you use a different plotting function...
colors = ["#C6DBEF", "#9ECAE1", "#6BAED6", "#4292C6", "#2171B5", "#08519C", "#08306B"]
ar.contours(plot, palette=colors, title="ISO Contours")
