class DimensionedSelectionTest(ComparisonTestCase):
def setUp(self):
self.img_fn = lambda: Image(np.random.rand(10, 10))
self.contour_fn = lambda: Contours([np.random.rand(10, 2)
for i in range(2)])
params = [list(range(3)) for i in range(2)]
self.img_map = HoloMap({(i, j): self.img_fn()
for i, j in product(*params)},
key_dimensions=['a', 'b'])
self.contour_map = HoloMap({(i, j): self.contour_fn()
for i, j in product(*params)},
key_dimensions=['a', 'b'])
self.ndoverlay_map = self.img_map.overlay('b')
self.overlay_map = self.img_map * self.contour_map
self.layout_map = self.ndoverlay_map + self.contour_map
self.duplicate_map = self.img_map.clone(key_dimensions=['x', 'y'])
def test_simple_holoselect(self):
self.assertEqual(self.img_map.select(a=0, b=1),
self.img_map[0, 1])
def test_simple_holoslice(self):
self.assertEqual(self.img_map.select(a=(1, 3), b=(1, 3)),
self.img_map[1:3, 1:3])
def test_simple_holo_ndoverlay_slice(self):
self.assertEqual(self.ndoverlay_map.select(a=(1, 3), b=(1, 3)),
self.ndoverlay_map[1:3, 1:3])
def test_deep_holoslice(self):
selection = self.img_map.select(a=(1,3), b=(1, 3), x=(None, 0), y=(None, 0))
self.assertEqual(selection, self.img_map[1:3, 1:3, :0, :0])
def test_deep_holooverlay_slice(self):
map_slc = self.overlay_map[1:3, 1:3]
img_slc = map_slc.map(lambda x: x[0:0.5, 0:0.5], [Image, Contours])
selection = self.overlay_map.select(a=(1,3), b=(1, 3), x=(0, 0.5), y=(0, 0.5))
self.assertEqual(selection, img_slc)
def test_deep_layout_nesting_slice(self):
hmap1 = self.layout_map.HoloMap.I[1:3, 1:3, 0:0.5, 0:0.5]
hmap2 = self.layout_map.HoloMap.II[1:3, 1:3, 0:0.5, 0:0.5]
selection = self.layout_map.select(a=(1,3), b=(1, 3), x=(0, 0.5), y=(0, 0.5))
self.assertEqual(selection, hmap1 + hmap2)
def test_spec_duplicate_dim_select(self):
selection = self.duplicate_map.select((HoloMap,), x=(0, 1), y=(1, 3))
self.assertEqual(selection, self.duplicate_map[0:1, 1:3])
def test_duplicate_dim_select(self):
selection = self.duplicate_map.select(x=(None, 0.5), y=(None, 0.5))
self.assertEqual(selection, self.duplicate_map[:.5, :.5, :.5, :.5])
class DimensionedSelectionTest(ComparisonTestCase):
def setUp(self):
self.img_fn = lambda: Image(np.random.rand(10, 10))
self.contour_fn = lambda: Contours([np.random.rand(10, 2)
for i in range(2)])
params = [list(range(3)) for i in range(2)]
self.sanitized_map = HoloMap({i: Image(i*np.random.rand(10,10))
for i in range(1,10)}, kdims=['A B'])
self.img_map = HoloMap({(i, j): self.img_fn()
for i, j in product(*params)},
kdims=['a', 'b'])
self.contour_map = HoloMap({(i, j): self.contour_fn()
for i, j in product(*params)},
kdims=['a', 'b'])
self.ndoverlay_map = self.img_map.overlay('b')
self.overlay_map = self.img_map * self.contour_map
self.layout_map = self.ndoverlay_map + self.contour_map
self.duplicate_map = self.img_map.clone(kdims=['x', 'y'])
self.overlap1 = HoloMap({i: self.img_fn() for i in range(5)})
self.overlap2 = HoloMap({i: self.img_fn() for i in range(10)})
self.overlap_layout = self.overlap1 + self.overlap2
def test_simple_holoselect(self):
self.assertEqual(self.img_map.select(a=0, b=1),
self.img_map[0, 1])
def test_simple_holoslice(self):
self.assertEqual(self.img_map.select(a=(1, 3), b=(1, 3)),
self.img_map[1:3, 1:3])
def test_sanitized_holoslice(self):
self.assertEqual(self.sanitized_map.select(A_B=(1,3)),
self.sanitized_map[1:3])
def test_simple_holo_ndoverlay_slice(self):
self.assertEqual(self.ndoverlay_map.select(a=(1, 3), b=(1, 3)),
self.ndoverlay_map[1:3, 1:3])
def test_deep_holoslice(self):
selection = self.img_map.select(a=(1,3), b=(1, 3), x=(None, 0), y=(None, 0))
self.assertEqual(selection, self.img_map[1:3, 1:3, :0, :0])
def test_deep_holooverlay_slice(self):
map_slc = self.overlay_map[1:3, 1:3]
img_slc = map_slc.map(lambda x: x[0:0.5, 0:0.5], [Image, Contours])
selection = self.overlay_map.select(a=(1,3), b=(1, 3), x=(0, 0.5), y=(0, 0.5))
self.assertEqual(selection, img_slc)
def test_deep_layout_nesting_slice(self):
hmap1 = self.layout_map.HoloMap.I[1:3, 1:3, 0:0.5, 0:0.5]
hmap2 = self.layout_map.HoloMap.II[1:3, 1:3, 0:0.5, 0:0.5]
selection = self.layout_map.select(a=(1,3), b=(1, 3), x=(0, 0.5), y=(0, 0.5))
self.assertEqual(selection, hmap1 + hmap2)
def test_spec_duplicate_dim_select(self):
selection = self.duplicate_map.select((HoloMap,), x=(0, 1), y=(1, 3))
self.assertEqual(selection, self.duplicate_map[0:1, 1:3])
def test_duplicate_dim_select(self):
selection = self.duplicate_map.select(x=(None, 0.5), y=(None, 0.5))
self.assertEqual(selection, self.duplicate_map[:.5, :.5, :.5, :.5])
def test_overlap_select(self):
selection = self.overlap_layout.select(Default=(6, None))
self.assertEqual(selection, self.overlap1.clone(shared_data=False) + self.overlap2[6:])
class DimensionedSelectionTest(ComparisonTestCase):
def setUp(self):
self.img_fn = lambda: Image(np.random.rand(10, 10))
self.contour_fn = lambda: Contours(
[np.random.rand(10, 2) for i in range(2)])
self.datetime_fn = lambda: Curve(([
dt.datetime(2000, 1, 1),
dt.datetime(2000, 1, 2),
dt.datetime(2000, 1, 3)
], np.random.rand(3)), 'time', 'x')
params = [list(range(3)) for i in range(2)]
self.sanitized_map = HoloMap(
{i: Image(i * np.random.rand(10, 10))
for i in range(1, 10)},
kdims=['A B'])
self.img_map = HoloMap(
{(i, j): self.img_fn()
for i, j in product(*params)},
kdims=['a', 'b'])
self.contour_map = HoloMap(
{(i, j): self.contour_fn()
for i, j in product(*params)},
kdims=['a', 'b'])
self.ndoverlay_map = self.img_map.overlay('b')
self.overlay_map = self.img_map * self.contour_map
self.layout_map = self.ndoverlay_map + self.contour_map
self.duplicate_map = self.img_map.clone(kdims=['x', 'y'])
self.overlap1 = HoloMap({i: self.img_fn() for i in range(5)})
self.overlap2 = HoloMap({i: self.img_fn() for i in range(10)})
self.overlap_layout = self.overlap1 + self.overlap2
def test_simple_holoselect(self):
self.assertEqual(self.img_map.select(a=0, b=1), self.img_map[0, 1])
def test_simple_holoslice(self):
self.assertEqual(self.img_map.select(a=(1, 3), b=(1, 3)),
self.img_map[1:3, 1:3])
def test_function_holoslice(self):
self.assertEqual(
self.img_map.select(a=lambda x: 1 <= x < 3,
b=lambda x: 1 <= x < 3), self.img_map[1:3,
1:3])
def test_sanitized_holoslice(self):
self.assertEqual(self.sanitized_map.select(A_B=(1, 3)),
self.sanitized_map[1:3])
def test_simple_holo_ndoverlay_slice(self):
self.assertEqual(self.ndoverlay_map.select(a=(1, 3), b=(1, 3)),
self.ndoverlay_map[1:3, 1:3])
def test_deep_holoslice(self):
selection = self.img_map.select(a=(1, 3),
b=(1, 3),
x=(None, 0),
y=(None, 0))
self.assertEqual(selection, self.img_map[1:3, 1:3, :0, :0])
def test_deep_holooverlay_slice(self):
map_slc = self.overlay_map[1:3, 1:3]
img_slc = map_slc.map(lambda x: x[0:0.5, 0:0.5], [Image, Contours])
selection = self.overlay_map.select(a=(1, 3),
b=(1, 3),
x=(0, 0.5),
y=(0, 0.5))
self.assertEqual(selection, img_slc)
def test_deep_layout_nesting_slice(self):
hmap1 = self.layout_map.HoloMap.I[1:3, 1:3, 0:0.5, 0:0.5]
hmap2 = self.layout_map.HoloMap.II[1:3, 1:3, 0:0.5, 0:0.5]
selection = self.layout_map.select(a=(1, 3),
b=(1, 3),
x=(0, 0.5),
y=(0, 0.5))
self.assertEqual(selection, hmap1 + hmap2)
def test_spec_duplicate_dim_select(self):
selection = self.duplicate_map.select((HoloMap, ), x=(0, 1), y=(1, 3))
self.assertEqual(selection, self.duplicate_map[0:1, 1:3])
def test_duplicate_dim_select(self):
selection = self.duplicate_map.select(x=(None, 0.5), y=(None, 0.5))
self.assertEqual(selection, self.duplicate_map[:.5, :.5, :.5, :.5])
def test_overlap_select(self):
selection = self.overlap_layout.select(Default=(6, None))
self.assertEqual(
selection,
self.overlap1.clone(shared_data=False) + self.overlap2[6:])
def test_datetime_select(self):
s, e = '1999-12-31', '2000-1-2'
curve = self.datetime_fn()
overlay = curve * self.datetime_fn()
for el in [curve, overlay]:
self.assertEqual(el.select(time=(s, e)), el[s:e])
self.assertEqual(
el.select(time=(dt.datetime(1999, 12, 31),
dt.datetime(2000, 1, 2))), el[s:e])
if pd:
self.assertEqual(
el.select(time=(pd.Timestamp(s), pd.Timestamp(e))),
el[pd.Timestamp(s):pd.Timestamp(e)])
