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
