def test_rasterize_ndoverlay(self):
ds = Dataset([(0.2, 0.3, 0), (0.4, 0.7, 1), (0, 0.99, 2)], kdims=['x', 'y', 'z'])
ndoverlay = ds.to(Points, ['x', 'y'], [], 'z').overlay()
expected = Image(([0.25, 0.75], [0.25, 0.75], [[1, 0], [2, 0]]),
vdims=['Count'])
img = rasterize(ndoverlay, dynamic=False, x_range=(0, 1), y_range=(0, 1),
width=2, height=2)
self.assertEqual(img, expected)
def test_rasterize_ndoverlay(self):
ds = Dataset([(0.2, 0.3, 0), (0.4, 0.7, 1), (0, 0.99, 2)], kdims=['x', 'y', 'z'])
ndoverlay = ds.to(Points, ['x', 'y'], [], 'z').overlay()
expected = Image(([0.25, 0.75], [0.25, 0.75], [[1, 0], [2, 0]]),
vdims=['Count'])
img = rasterize(ndoverlay, dynamic=False, x_range=(0, 1), y_range=(0, 1),
width=2, height=2)
self.assertEqual(img, expected)
def visits_plot(dsets_visits, filters_to_metrics, summarized_visits=None):
if not summarized_visits:
pass
plot = None
dfc = None
for filt, metrics in filters_to_metrics.items():
for metric in metrics:
df = dsets_visits[filt][metric].compute()
# drop inf/nan values
with pd.option_context('mode.use_inf_as_na', True):
df = df.dropna(subset = [metric])
label = '{} - {}'.format(filt, metric)
df[label] = minmax_scale(df[metric])
df = df.groupby('visit')
df = df[label].median().reset_index()
if dfc is None:
dfc = df.set_index('visit')
else:
dfc = dfc.merge(df.set_index('visit'), on='visit',
how='outer', sort=True)
dfc = dfc.stack(dropna=False, level=-1).reset_index()
dfc = dfc.rename(columns={'level_1':'filters', 0:'median'})
dfc['visit'] = dfc['visit'].astype(str)
ds = hv.Dataset(dfc, kdims=['visit','filters'], vdims=['median'])
plot = ds.to(hv.Curve, 'visit', 'median').overlay('filters')
plot = plot.opts(hv.opts.Curve(tools=['hover']))
plot = plot.redim(y=hv.Dimension('median', range=(-1,1)))
# Now we rename the axis
xlabel = 'visit'
ylabel = 'normalized median'
grid_style = {'grid_line_color': 'white', 'grid_line_alpha': 0.2}
#
# return plot.options(responsive=True, height=200, show_grid=True,
# xlabel=xlabel, ylabel=ylabel,
# xrotation=45, bgcolor="black", gridstyle=grid_style)
return plot.opts(show_legend=False, show_grid=True,
gridstyle=grid_style,
xlabel=xlabel, ylabel=ylabel,
responsive=True, aspect=5,
bgcolor='black', xrotation=45)
