def test_default(self): info = infos.encode(["other", "one", "two"], defcat=0) self.assertEqual(0, info("other")) self.assertEqual(1, info("one")) self.assertEqual(2, info("two")) self.assertEqual(0, info("stuff")) self.assertEqual(0, info("more"))
def test(self): info = infos.encode(["zero", "one", "two"]) self.assertEqual(0, info("zero")) self.assertEqual(1, info("one")) self.assertEqual(2, info("two")) self.assertEqual(3, info("stuff")) self.assertEqual(3, info("more"))
def _create_plot_component(): red = util.Color(255, 0, 0, 255) green = util.Color(0, 255, 0, 255) blue = util.Color(0, 0, 255, 255) purple = util.Color(125, 0, 255, 255) white = util.Color(255, 255, 255, 255) black = util.Color(0, 0, 0, 255) clear = util.Color(0, 0, 0, 0) with Timer("Loeading") as arTimer: #glyphs = npg.load_csv("../data/circlepoints.csv", 1, 2, 3, 4) #glyphs = npg.load_hdf("../data/CensusTracts.hdf5", "__data__", "LAT", "LON") glyphs = npg.load_hdf("../data/tweets-subset.hdf", "test", "longitude", "latitude", vc="lang_primary") screen = (800, 600) ivt = util.zoom_fit(screen, glyphs.bounds()) with Timer("Abstract-Render") as arTimer: image = core.render( glyphs, infos.encode(["Arabic", "English", "Turkish", "Russian"]), npg.PointCountCategories(), npg.Spread(2) + categories.HDAlpha( [red, blue, green, purple, black], alphamin=.3, log=True), screen, ivt) # image = core.render(glyphs, # infos.valAt(4,0), # npg.PointCount(), # npg.Spread(1) + numeric.BinarySegment(white, black, 1), # screen, # ivt) # Create a plot data object and give it this data pd = ArrayPlotData() pd.set_data("imagedata", image) # Create the plot plot = Plot(pd) img_plot = plot.img_plot("imagedata")[0] # Tweak some of the plot properties plot.title = "Abstract Rendering" plot.padding = 50 return plot
def _create_plot_component(): red = util.Color(255,0,0,255) green = util.Color(0,255,0,255) blue = util.Color(0,0,255,255) purple = util.Color(125,0,255,255) white = util.Color(255,255,255,255) black = util.Color(0,0,0,255) clear = util.Color(0,0,0,0) with Timer("Loeading") as arTimer: #glyphs = npg.load_csv("../data/circlepoints.csv", 1, 2, 3, 4) glyphs = npg.load_hdf("../data/CensusTracts.hdf5", "__data__", "LAT", "LON") #glyphs = npg.load_hdf("../data/tweets-subset.hdf", "test", # "longitude", "latitude", vc="lang_primary") screen = (800,600) ivt = util.zoom_fit(screen,glyphs.bounds()) with Timer("Abstract-Render") as arTimer: image = core.render(glyphs, infos.encode(["Arabic","English","Turkish","Russian"]), npg.PointCountCategories(), npg.Spread(2) + categories.HDAlpha([red, blue, green, purple, black], alphamin=.3, log=True), screen, ivt) # image = core.render(glyphs, # infos.valAt(4,0), # npg.PointCount(), # npg.Spread(1) + numeric.BinarySegment(white, black, 1), # screen, # ivt) # Create a plot data object and give it this data pd = ArrayPlotData() pd.set_data("imagedata", image) # Create the plot plot = Plot(pd) img_plot = plot.img_plot("imagedata")[0] # Tweak some of the plot properties plot.title = "Abstract Rendering" plot.padding = 50 return plot