def test_replot_result_type(self):
ar_downsample._loadAR()
source = ServerDataSource(data_url="fn://bivariate",
owner_username="******")
plot = square('A', 'B', source=source)
expected = {
"image": "Image",
"image_rgb": "ImageRGBA",
"multi_line": "MultiLine"
}
shaders = dict()
for name in dir(ar_downsample):
item = getattr(ar_downsample, name)
if isinstance(item, ar_downsample.Shader):
shaders[item] = item.out
for shader_class in shaders:
shader = shader_class()
rslt = ar_downsample.replot(plot, shader=shader)
self.assertEquals(
expected[shader.out],
self._glyphspec(rslt)['type'],
"Error with {0}. Expected {1}, recieved {2}".format(
str(shader_class), expected[shader.out],
self._glyphspec(rslt)))
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_replot_remove(self):
self.assertIsNotNone(self.bokeh_server, "Server failed to start, cannot tests")
ar_downsample._loadAR()
output_server("Census")
source = ServerDataSource(data_url="fn://bivariate", owner_username="******")
plot = square('A', 'B', source=source)
ar_downsample.replot(plot, remove_original=False)
self.assertTrue(plot in curdoc().context.children, "Not retained")
ar_downsample.replot(plot, remove_original=True)
self.assertTrue(plot not in curdoc().context.children, "Not removed")
try:
ar_downsample.replot(plot, remove_original=True)
except:
self.assertTrue(False, "Error reploting plot not in curdoc")
def test_replot_remove(self):
self.assertIsNotNone(self.bokeh_server,
"Server failed to start, cannot tests")
ar_downsample._loadAR()
output_server("Census")
source = ServerDataSource(data_url="fn://bivariate",
owner_username="******")
plot = square('A', 'B', source=source)
ar_downsample.replot(plot, remove_original=False)
self.assertTrue(plot in curdoc().context.children, "Not retained")
ar_downsample.replot(plot, remove_original=True)
self.assertTrue(plot not in curdoc().context.children, "Not removed")
try:
ar_downsample.replot(plot, remove_original=True)
except:
self.assertTrue(False, "Error reploting plot not in curdoc")
def test_contour_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.contours(plot, title="Contour")
source2 = self._find_source(plot2)
self.assertEquals("Contour", 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, "multi_line")
def test_replot_result_type(self):
ar_downsample._loadAR()
source = ServerDataSource(data_url="fn://bivariate", owner_username="******")
plot = square('A', 'B', source=source)
expected = {"image": "Image", "image_rgb": "ImageRGBA", "multi_line": "MultiLine"}
shaders = dict()
for name in dir(ar_downsample):
item = getattr(ar_downsample, name)
if hasattr(item, "out"):
shaders[item] = getattr(item, "out")
for shader_class in shaders:
shader = shader_class()
rslt = ar_downsample.replot(plot, shader=shader)
self.assertEquals(expected[shader.out], self._glyphspec(rslt)['type'],
"Error with {0}. Expected {1}, recieved {2}"
.format(str(shader_class), expected[shader.out], self._glyphspec(rslt)))
def test_source(self):
ar_downsample._loadAR()
source = ServerDataSource(data_url="fn://bivariate", owner_username="******")
plot = square('A', 'B', source=source)
agg = ar_downsample.CountCategories()
info = ar_downsample.Const(val=1)
shader = ar_downsample.InterpolateColor()
new_source = ar_downsample.source(plot, agg=agg, info=info, shader=shader)
self.assertIsNotNone(new_source.transform)
trans = new_source.transform
self.assertEquals(trans['resample'], 'abstract rendering')
self.assertEquals(trans['agg'], agg)
self.assertEquals(trans['info'], info)
self.assertEquals(trans['shader'], shader)
self.assertEquals(trans['glyphspec'], self._glyphspec(plot))
self.assertEquals(trans['points'], False)
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_contour_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.contours(plot, title="Contour")
source2 = self._find_source(plot2)
self.assertEquals("Contour", 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, "multi_line")
def test_replot_property_transfer(self):
self.assertIsNotNone(self.bokeh_server,
"Server failed to start, cannot tests")
ar_downsample._loadAR()
output_server("Census")
source = ServerDataSource(data_url="fn://bivariate",
owner_username="******")
plot_width = 612
plot_height = 408
plot_title = "Test title"
plot = square('A',
'B',
source=source,
plot_width=plot_width,
plot_height=plot_height,
title=plot_title)
ar_plot = ar_downsample.replot(plot)
self.assertEquals(ar_plot.plot_width, plot_width,
"Plot width not transfered")
self.assertEquals(ar_plot.plot_height, plot_height,
"Plot height not transfered")
self.assertEquals(ar_plot.title, plot_title,
"Plot title not transfered")
plot_width = 612
plot_height = 408
plot_title = "Test title"
ar_plot = ar_downsample.replot(plot,
title=plot_title,
plot_width=plot_width,
plot_height=plot_height)
self.assertEquals(ar_plot.plot_width, plot_width,
"Plot width override failed")
self.assertEquals(ar_plot.plot_height, plot_height,
"Plot height override failed")
self.assertEquals(ar_plot.title, plot_title,
"Plot title override failed")
def test_source(self):
ar_downsample._loadAR()
source = ServerDataSource(data_url="fn://bivariate",
owner_username="******")
plot = square('A', 'B', source=source)
agg = ar_downsample.CountCategories()
info = ar_downsample.Const(val=1)
shader = ar_downsample.InterpolateColor()
new_source = ar_downsample.source(plot,
agg=agg,
info=info,
shader=shader)
self.assertIsNotNone(new_source.transform)
trans = new_source.transform
self.assertEquals(trans['resample'], 'abstract rendering')
self.assertEquals(trans['agg'], agg)
self.assertEquals(trans['info'], info)
self.assertEquals(trans['shader'], shader)
self.assertEquals(trans['glyphspec'], self._glyphspec(plot))
self.assertEquals(trans['points'], False)
def test_replot_property_transfer(self):
self.assertIsNotNone(self.bokeh_server, "Server failed to start, cannot tests")
ar_downsample._loadAR()
output_server("Census")
source = ServerDataSource(data_url="fn://bivariate", owner_username="******")
plot_width = 612
plot_height = 408
plot_title = "Test title"
plot = square('A', 'B', source=source, plot_width=plot_width, plot_height=plot_height, title=plot_title)
ar_plot = ar_downsample.replot(plot)
self.assertEquals(ar_plot.plot_width, plot_width, "Plot width not transfered")
self.assertEquals(ar_plot.plot_height, plot_height, "Plot height not transfered")
self.assertEquals(ar_plot.title, plot_title, "Plot title not transfered")
plot_width = 612
plot_height = 408
plot_title = "Test title"
ar_plot = ar_downsample.replot(plot, title=plot_title, plot_width=plot_width, plot_height=plot_height)
self.assertEquals(ar_plot.plot_width, plot_width, "Plot width override failed")
self.assertEquals(ar_plot.plot_height, plot_height, "Plot height override failed")
self.assertEquals(ar_plot.title, plot_title, "Plot title override failed")
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()
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
import numpy as np
from bokeh.plotting import square, output_server, image, show
from bokeh.objects import ServerDataSource
import bokeh.transforms.ar_downsample as ar
#from bokeh.transforms import line_downsample
output_server("abstractrender")
source = ServerDataSource(data_url="fn://uniform", owner_username="******")
plot = square('oneA','oneB',color='#FF00FF',source=source)
# Simple heat-map: bin the counts ('tis the default configuration....)
heatmap =ar.source(plot, palette=["Reds-9"])
image(source=heatmap, title="Heatmap", reserve_val=0, **ar.mapping(heatmap))
#image(source=heatmap, reserve_val=0, reserve_color=0xaaaaaa, **ar.mapping(heatmap))
###Perceptually corrected heat-map. Cube-root then bin
percepmap = ar.source(plot, shader=ar.Cuberoot(), palette=["Reds-9"])
image(source=percepmap, title="Perceptually corrected", reserve_val=0, **ar.mapping(percepmap))
### Contours come in the same framework, but since the results of the shader are lines you use a different plotting function...
#contour = ar.source(glyphs=plot, agg=ar.Count(), info=ar.Const(1), shader=ar.Contour(9))
#multi_line(source=countour, palette=["reds-9"])
#
#
##Alternative: aggregator as an incomplete resampler
#aggregator = ar.source(ar.count(), ar.const(1), ar.touches()) ### Aggregator is incomplete without shader and glyphs. Can add either to it
#shader = ar.Cuberoot()+ar.Interpolate(0,9) + ar.Floor()
import numpy as np
from bokeh.plotting import square, output_server, image, show
from bokeh.objects import ServerDataSource
import bokeh.transforms.ar_downsample as ar
#from bokeh.transforms import line_downsample
output_server("abstractrender")
source = ServerDataSource(data_url="fn://gauss", owner_username="******")
plot = square('oneA', 'oneB', color='#FF00FF', source=source)
# Simple heat-map: bin the counts ('tis the default configuration....)
heatmap =ar.source(plot, palette=["Reds-9"])
image(source=heatmap, title="Heatmap", reserve_val=0, **ar.mapping(heatmap))
#Perceptually corrected heat-map. Cube-root then bin
percepmap = ar.source(plot, shader=ar.Cuberoot(), palette=["Reds-9"])
image(source=percepmap, title="Perceptually corrected", reserve_val=0, **ar.mapping(percepmap))
# 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.replot(plot, title="ISO Contours", shader=ar.Contour(levels=len(colors)), line_color=colors)
#"""
#In order to run the 'stocks' example, you have to execute
#./bokeh-server -D remotedata
#
#The remote data directory in the bokeh checkout has the sample data for this example
import numpy as np
from bokeh.plotting import square, output_server, image, show
from bokeh.objects import ServerDataSource
import bokeh.transforms.ar_downsample as ar
#from bokeh.transforms import line_downsample
output_server("Census")
#2010 US Census tracts
source = ServerDataSource(data_url="/defaultuser/CensusTracts.hdf5", owner_username="******")
plot = square( 'LON','LAT',source=source)
heatmap = ar.source(plot, palette=["Reds-9"], points=True)
image(source=heatmap, title="Census Tracts", reserve_val=0, plot_width=600, plot_height=400, **ar.mapping(heatmap))
show()
#aggregator = ar.source(ar.count(), ar.const(1), ar.touches()) ### Aggregator is incomplete without shader and glyphs. Can add either to it
#shader = ar.Cuberoot()+ar.Interpolate(0,9) + ar.Floor()
#image(source=plot+aggregator+shader, palette=["reds-9"]) ###Implement aggregator.__radd__ to get a plot and .__add__ to get a shader
"""
In order to run the 'stocks' 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
"""
#Stock-data plotting
#source = ServerDataSource(data_url="/defaultuser/AAPL.hdf5", owner_username="******")
#plot = square('volume','close',color='#FF00FF',source=source)
#percepmap = ar.source(plot, shader=ar.Cuberoot(), palette=["Reds-9"])
#image(source=percepmap, title="Perceptually corrected (Stocks)", reserve_val=0, **ar.mapping(percepmap))
#2010 US Census tracts
source = ServerDataSource(data_url="/defaultuser/CensusTracts.hdf5", owner_username="******")
plot = square( 'INTPTLONG','INTPTLAT',source=source)
heatmap = ar.source(plot, palette=["Reds-9"])
image(source=heatmap, title="Census Tracts", reserve_val=0, **ar.mapping(heatmap))
show()
