def test_bounds_index(self):
# ascending
bounds = self.data_source.get_bounds(index=0)
self.assertEqual(bounds, (0, 1))
# descending
myarray = arange(20)[::-1].reshape(10, 2)
data_source = MultiArrayDataSource(myarray, sort_order='descending')
bounds = data_source.get_bounds(index=0)
self.assertEqual(bounds, (18, 19))
# no order
myarray = array([[12, 3], [0, 9], [2, 18], [3, 10]])
data_source = MultiArrayDataSource(myarray, sort_order="none")
bounds = data_source.get_bounds(index=0)
self.assertEqual(bounds, (3, 12))
def test_init_defaults(self):
data_source = MultiArrayDataSource()
assert_array_equal(data_source._data, empty(shape=(0, 1), dtype=float))
# XXX this doesn't match AbstractDataSource's interface
self.assertEqual(data_source.value_dimension, 1)
self.assertEqual(data_source.sort_order, "ascending")
self.assertFalse(data_source.is_masked())
def test_bounds_all_nans(self):
myarray = empty((10, 2))
myarray[:, :] = nan
data_source = MultiArrayDataSource(myarray)
bounds = data_source.get_bounds()
self.assertTrue(isnan(bounds[0]))
self.assertTrue(isnan(bounds[1]))
def _create_plot_component():
# Create some data
numpts = 400
x = sort(random(numpts))
y = random(numpts)
xs = ArrayDataSource(x, sort_order='ascending')
ys = ArrayDataSource(y)
vectorlen = 15
vectors = array((random(numpts) * vectorlen, random(numpts) * vectorlen)).T
vector_ds = MultiArrayDataSource(vectors)
xrange = DataRange1D()
xrange.add(xs)
yrange = DataRange1D()
yrange.add(ys)
quiverplot = QuiverPlot(index=xs,
value=ys,
vectors=vector_ds,
index_mapper=LinearMapper(range=xrange),
value_mapper=LinearMapper(range=yrange),
bgcolor="white")
add_default_axes(quiverplot)
add_default_grids(quiverplot)
# Attach some tools to the plot
quiverplot.tools.append(PanTool(quiverplot, constrain_key="shift"))
zoom = ZoomTool(quiverplot)
quiverplot.overlays.append(zoom)
container = OverlayPlotContainer(quiverplot, padding=50)
return container
def test_get_data_no_data(self):
data_source = MultiArrayDataSource()
assert_array_equal(data_source.get_data(),
empty(shape=(0, 1), dtype=float))
def setUp(self):
self.myarray = arange(20).reshape(10, 2)
self.data_source = MultiArrayDataSource(self.myarray)
def test_bounds_empty(self):
data_source = MultiArrayDataSource()
bounds = data_source.get_bounds()
# XXX this is sort of inconsistent with test_bounds_all_nans()
self.assertEqual(bounds, (0, 0))
def _get_plot_multiline(self):
if self.data is None or len(self.data.shape) == 1:
return
numpoints = self.data.shape[1]
if self.scale_type == 'Time':
index_x = self._create_dates(numpoints, start=self.first_day)
else:
index_x = np.arange(numpoints)
index_y = np.linspace(1, self.data.shape[0], self.data.shape[0])
xs = ArrayDataSource(index_x)
xrange = DataRange1D()
xrange.add(xs)
ys = ArrayDataSource(index_y)
yrange = DataRange1D()
yrange.add(ys)
# The data source for the MultiLinePlot.
ds = MultiArrayDataSource(data=self.data)
corr_plot = \
MultiLinePlot(
index=xs,
yindex=ys,
index_mapper=LinearMapper(range=xrange),
value_mapper=LinearMapper(range=yrange),
value=ds,
global_max=self.data.max(),
global_min=self.data.min())
corr_plot.value_mapper.range.low = 0
corr_plot.value_mapper.range.high = self.data.shape[0] + 1
self.multi_line_plot_renderer = corr_plot
plot = Plot(title=self.p_title)
if self.scale_type == 'Time':
# Just the last axis shows tick_labels
bottom_axis = PlotAxis(component=plot,
orientation="bottom",
title=self.x_lbl,
tick_generator=ScalesTickGenerator(
scale=CalendarScaleSystem()))
else:
bottom_axis = PlotAxis(orientation='bottom',
title=self.x_lbl,
title_font="modern 12",
tick_visible=True,
small_axis_style=True,
axis_line_visible=False,
component=plot)
if self.y_lbl_type == 'Custom' and \
len(self.y_labels) == self.data.shape[0]:
# a new value in the list defaults to None so raise an error before
# the operator ends inputing it.
left_axis = LabelAxis(component=plot,
orientation='left',
title=self.x_lbl,
mapper=corr_plot.value_mapper,
tick_interval=1.0,
labels=self.y_labels,
positions=index_y)
else:
left_axis = PlotAxis(
component=plot,
orientation='left',
title=self.y_lbl,
title_font="modern 12",
#title_spacing=0,
tick_label_font="modern 8",
tick_visible=True,
small_axis_style=True,
axis_line_visible=False,
ensure_labels_bounded=True,
#tick_label_color="transparent",
mapper=corr_plot.value_mapper)
plot.overlays.extend([bottom_axis, left_axis])
plot.add(corr_plot)
plot.padding_bottom = 50
return plot
