def test_pan_scale(self): self.assertEqual(util.zoom_fit((10, 10), (0, 0, 20, 20)), [0., 0., .5, .5]) self.assertEqual(util.zoom_fit((10, 10), (5, 5, 20, 20)), [-2.5, -2.5, .5, .5]) self.assertEqual(util.zoom_fit((10, 10), (-4, -7, 20, 20)), [2., 3.5, .5, .5])
def test_pan(self): self.assertEqual(util.zoom_fit((10, 10), (0, 0, 10, 10)), [0., 0., 1., 1.]) self.assertEqual(util.zoom_fit((10, 10), (5, 5, 10, 10)), [-5., -5., 1., 1.]) self.assertEqual(util.zoom_fit((10, 10), (-4, -7, 10, 10)), [4., 7., 1., 1.])
def test_scale(self): self.assertEqual(util.zoom_fit((10, 10), (0, 0, 10, 10)), [0., 0., 1., 1.]) self.assertEqual(util.zoom_fit((10, 10), (0, 0, 20, 20)), [0., 0., .5, .5]) self.assertEqual(util.zoom_fit((10, 10), (0, 0, 5, 5)), [0., 0., 2., 2.]) self.assertEqual(util.zoom_fit((10, 10), (0, 0, 10, 20)), [0., 0., .5, .5]) self.assertEqual(util.zoom_fit((10, 10), (0, 0, 10, 20), False), [0., 0., 1., .5])
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
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) white = util.Color(255,255,255,255) black = util.Color(0,0,0,255) shape = glyphset.ShapeCodes.POINT #glyphs = glyphset.load_csv("../data/checkerboard.csv", 2, 0, 1, 3,1,1, shape) #glyphs = glyphset.load_csv("../data/circlepoints.csv", 1, 2, 3, 4,.1,.1, shape) #glyphs = glyphset.load_csv("../data/sourceforge.csv", 1, 1, 2, -1,.1,.1, shape) glyphs = glyphset.load_hdf("../data/CensusTracts.hdf5", "__data__", "LON", "LAT", None, .1, .1, shape) #glyphs = glyphset.load_hdf("../data/tweets-subset.hdf", "test", "longitude", "latitude", None, .1, .1, shape) screen = (800,600) ivt = util.zoom_fit(screen,glyphs.bounds()) with Timer("Abstract-Render") as arTimer: # image = core.render(glyphs, # infos.val(), # categories.CountCategories(), # categories.HDAlpha([red, blue]), # screen, # ivt) image = core.render(glyphs, infos.valAt(4,0), numeric.Count(), numeric.BinarySegment(white, black, 1), screen, ivt) print("screen x image -- {0} x {1}".format(screen, image.shape)) # 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) shape = glyphset.ShapeCodes.RECT glyphs = blzg.load_csv( "../data/circlepoints.csv", "x", "y", "series", schema="{r:float32, theta:float32, x:float32, y:float32, series:int32}" ) screen = (800, 600) ivt = util.zoom_fit(screen, glyphs.bounds()) with Timer("Abstract-Render") as arTimer: image = core.render( glyphs, infos.val(), blzg.CountCategories("int32"), categories.HDAlpha([red, blue, green, purple, black]), screen, ivt) # image = core.render(glyphs, # infos.valAt(4,0), # blzg.Count(), # 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) shape = glyphset.ShapeCodes.RECT glyphs = blzg.load_csv("../data/circlepoints.csv", "x", "y", "series", schema="{r:float32, theta:float32, x:float32, y:float32, series:int32}") screen = (800,600) ivt = util.zoom_fit(screen,glyphs.bounds()) with Timer("Abstract-Render") as arTimer: image = core.render(glyphs, infos.val(), blzg.CountCategories("int32"), categories.HDAlpha([red, blue, green, purple, black]), screen, ivt) # image = core.render(glyphs, # infos.valAt(4,0), # blzg.Count(), # 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