def test_scatterplot_one_variable():
numpy.random.seed(1234)
observations = numpy.random.normal(loc=1, size=(25, 100))
y = numpy.mean(observations, axis=1)
canvas, axes, mark = toyplot.scatterplot(y)
assert_canvas_matches(canvas, "scatterplot-one-variable")
def test_scatterplot_one_variable():
numpy.random.seed(1234)
observations = numpy.random.normal(loc=1, size=(25, 100))
y = numpy.mean(observations, axis=1)
canvas, axes, mark = toyplot.scatterplot(y)
assert_canvas_matches(canvas, "scatterplot-one-variable")
def tsne_samples(self, **kwargs):
"""
t-distrubuted stochastic neighbor embedding
"""
res = self.pca_samples()
mod = TSNE(**kwargs)
res2 = mod.fit_transform(res)
# plot results
canvas, _, _ = toyplot.scatterplot(
res2[:, 0],
res2[:, 1],
width=400,
height=350,
title=self.phenos.index,
size=15,
opacity=0.7,
color=(toyplot.color.CategoricalMap().colors(
self.phenos[self.trait]), ),
)
toyplot.browser.show(canvas)
def _draw_scatter(self, dataX, dataY):
"""
2-D scatterplot...
"""
# iterate through colors and shapes
colors = toyplot.color.brewer.palette("Paired")
colorshapes = itertools.product(["o", "s", "d", "v"], colors)
# color dictionary applied grey to NaN (masked) labels
cdict = {
"NaN": {
"fill": 'rgba(74.1%,74.1%,74.1%,1.000)',
'stroke': 'none',
},
}
# apply same color to fill or stroke for edges in each direction
labels = set(self.df.ulabel[self.df.sisters == 0])
labels = labels - {"NaN"}
for label, colorshape in zip(labels, colorshapes):
shape, color = colorshape
# set ->
cdict[label] = {
"marker": shape,
"stroke": "none",
"fill": toyplot.color.to_css(color),
}
# set <-
alt = "{1},{0}".format(*label.split(","))
cdict[alt] = {
"shape": shape,
"stroke": toyplot.color.to_css(color),
"stroke-width": 1.5,
"fill": 'rgba(100%,100%,100%,1.000)',
}
# generate markers for each test
markers = []
for idx in self.df.index:
if self.df.sisters[idx]:
mark = toyplot.marker.create(
shape="o",
size=3, # + (ml.df.aprop[idx] / ml.df.aprop.max()) * 10,# * 35,
mstyle=cdict["NaN"])
else:
mark = toyplot.marker.create(
shape='o',
size=3 + (self.df.aprop[idx] / self.df.aprop.max()) * 10,# * 35,
mstyle=cdict[self.df.label[idx]],
)
markers.append(mark)
canvas, axes, mark = toyplot.scatterplot(
dataX,
dataY,
width=400, height=400,
marker=markers,
title=self.df.label,
)
axes.x.label.text = "t-SNE axis 1"
axes.y.label.text = "t-SNE axis 2"
return canvas, axes, mark