def test_contour_recipe(self): source = ServerDataSource(data_url="fn://bivariate", owner_username="******") plot = figure(plot_width=600, plot_height=400, title="Test Title") plot.square('A', 'B', source=source) 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_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_contour_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.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_contour_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.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")
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") # 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") # # Multiple categories source = ServerDataSource() source.from_blaze(d.gauss, local=True) plot = figure() plot.square("oneA", "oneB", color="cats", source=source) arplot = ar.hdalpha(plot, spread=5, title="Multiple categories") show(plot)
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()
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") # Multiple categories source = ServerDataSource(data_url="fn://gauss", owner_username="******") plot2 = square('oneA', 'oneB', color='cats', source=source) ar.hdalpha(plot2, spread=5, title="Multiple categories") show()
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()