def test_range_datetime_ydim(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
ys = date_range(start, end, 10)
image = Image((self.xs, ys, self.array))
self.assertEqual(image.range(1), (start, end))
def test_range_datetime_ydim(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (-10, start, 10, end)
image = Image(np.flipud(self.array), bounds=bounds)
self.assertEqual(image.range(1), (start, end))
class ImageInterfaceTest(ComparisonTestCase):
datatype = 'image'
def setUp(self):
self.eltype = Image
self.restore_datatype = self.eltype.datatype
self.eltype.datatype = [self.datatype]
self.init_data()
def init_data(self):
self.array = np.arange(10) * np.arange(10)[:, np.newaxis]
self.image = Image(np.flipud(self.array), bounds=(-10, 0, 10, 10))
def tearDown(self):
self.eltype.datatype = self.restore_datatype
def test_init_data_tuple(self):
xs = np.arange(5)
ys = np.arange(10)
array = xs * ys[:, np.newaxis]
Image((xs, ys, array))
def test_init_data_tuple_error(self):
xs = np.arange(5)
ys = np.arange(10)
array = xs * ys[:, np.newaxis]
with self.assertRaises(DataError):
Image((ys, xs, array))
def test_init_data_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
Image(np.flipud(self.array), bounds=(start, 0, end, 10))
def test_init_data_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
Image(np.flipud(self.array), bounds=(-10, start, 10, end))
def test_init_bounds(self):
self.assertEqual(self.image.bounds.lbrt(), (-10, 0, 10, 10))
def test_init_bounds_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (start, 0, end, 10)
image = Image(np.flipud(self.array), bounds=bounds)
self.assertEqual(image.bounds.lbrt(), bounds)
def test_init_bounds_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (-10, start, 10, end)
image = Image(np.flipud(self.array), bounds=bounds)
self.assertEqual(image.bounds.lbrt(), bounds)
def test_init_densities(self):
self.assertEqual(self.image.xdensity, 0.5)
self.assertEqual(self.image.ydensity, 1)
def test_init_densities_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (start, 0, end, 10)
image = Image(np.flipud(self.array), bounds=bounds)
self.assertEqual(image.xdensity, 1e-5)
self.assertEqual(image.ydensity, 1)
def test_init_densities_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (-10, start, 10, end)
image = Image(np.flipud(self.array), bounds=bounds)
self.assertEqual(image.xdensity, 0.5)
self.assertEqual(image.ydensity, 1e-5)
def test_dimension_values_xs(self):
self.assertEqual(self.image.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_ys(self):
self.assertEqual(self.image.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_dimension_values_vdim(self):
self.assertEqual(self.image.dimension_values(2, flat=False),
self.array)
def test_index_single_coordinate(self):
self.assertEqual(self.image[0.3, 5.1], 25)
def test_slice_xaxis(self):
sliced = self.image[0.3:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 0, 6, 10))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[:, 5:8])
def test_slice_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (start, 0, end, 10)
image = Image(np.flipud(self.array), bounds=bounds)
sliced = image[start + np.timedelta64(530, 'ms'):start +
np.timedelta64(770, 'ms')]
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[:, 5:8])
def test_slice_yaxis(self):
sliced = self.image[:, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (-10, 1., 10, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, :])
def test_slice_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (-10, start, 10, end)
image = Image(np.flipud(self.array), bounds=bounds)
sliced = image[:, start + np.timedelta64(120, 'ms'):start +
np.timedelta64(520, 'ms')]
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, :])
def test_slice_both_axes(self):
sliced = self.image[0.3:5.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 1., 6, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, 5:8])
def test_slice_x_index_y(self):
sliced = self.image[0.3:5.2, 5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 5.0, 6.0, 6.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[5:6, 5:8])
def test_index_x_slice_y(self):
sliced = self.image[3.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (2.0, 1.0, 4.0, 5.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, 6:7])
def test_range_xdim(self):
self.assertEqual(self.image.range(0), (-10, 10))
def test_range_datetime_xdim(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (start, 0, end, 10)
image = Image(np.flipud(self.array), bounds=bounds)
self.assertEqual(image.range(0), (start, end))
def test_range_ydim(self):
self.assertEqual(self.image.range(1), (0, 10))
def test_range_datetime_ydim(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (-10, start, 10, end)
image = Image(np.flipud(self.array), bounds=bounds)
self.assertEqual(image.range(1), (start, end))
def test_range_vdim(self):
self.assertEqual(self.image.range(2), (0, 81))
def test_dimension_values_xcoords(self):
self.assertEqual(self.image.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_datetime_xcoords(self):
start = np.datetime64(dt.datetime.today())
end = start + np.timedelta64(1, 's')
bounds = (start, 0, end, 10)
image = Image(np.flipud(self.array), bounds=bounds)
self.assertEqual(image.dimension_values(0, expanded=False),
date_range(start, end, 10))
def test_dimension_values_ycoords(self):
self.assertEqual(self.image.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_sample_xcoord(self):
ys = np.linspace(0.5, 9.5, 10)
zs = [0, 7, 14, 21, 28, 35, 42, 49, 56, 63]
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
self.image):
self.assertEqual(self.image.sample(x=5),
Curve((ys, zs), kdims=['y'], vdims=['z']))
def test_sample_ycoord(self):
xs = np.linspace(-9, 9, 10)
zs = [0, 4, 8, 12, 16, 20, 24, 28, 32, 36]
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
self.image):
self.assertEqual(self.image.sample(y=5),
Curve((xs, zs), kdims=['x'], vdims=['z']))
def test_sample_coords(self):
arr = np.arange(10) * np.arange(5)[np.newaxis].T
xs = np.linspace(0.12, 0.81, 10)
ys = np.linspace(0.12, 0.391, 5)
img = Image((xs, ys, arr),
kdims=['x', 'y'],
vdims=['z'],
datatype=[self.datatype])
sampled = img.sample([(0.15, 0.15), (0.15, 0.4), (0.8, 0.4),
(0.8, 0.15)])
self.assertIsInstance(sampled, Table)
yidx = [0, 4, 4, 0]
xidx = [0, 0, 9, 9]
table = Table((xs[xidx], ys[yidx], arr[yidx, xidx]),
kdims=['x', 'y'],
vdims=['z'])
self.assertEqual(sampled, table)
def test_reduce_to_scalar(self):
self.assertEqual(self.image.reduce(['x', 'y'], function=np.mean),
20.25)
def test_reduce_x_dimension(self):
ys = np.linspace(0.5, 9.5, 10)
zs = [0., 4.5, 9., 13.5, 18., 22.5, 27., 31.5, 36., 40.5]
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
Image):
self.assertEqual(self.image.reduce(x=np.mean),
Curve((ys, zs), kdims=['y'], vdims=['z']))
def test_reduce_y_dimension(self):
xs = np.linspace(-9, 9, 10)
zs = [0., 4.5, 9., 13.5, 18., 22.5, 27., 31.5, 36., 40.5]
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
Image):
self.assertEqual(self.image.reduce(y=np.mean),
Curve((xs, zs), kdims=['x'], vdims=['z']))
def test_dataset_reindex_constant(self):
selected = Dataset(self.image.select(x=0))
reindexed = selected.reindex(['y'])
data = Dataset(selected.columns(['y', 'z']), kdims=['y'], vdims=['z'])
self.assertEqual(reindexed, data)
def test_dataset_reindex_non_constant(self):
ds = Dataset(self.image)
reindexed = ds.reindex(['y'])
data = Dataset(ds.columns(['y', 'z']), kdims=['y'], vdims=['z'])
self.assertEqual(reindexed, data)
def test_aggregate_with_spreadfn(self):
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
self.image):
agg = self.image.aggregate('x', np.mean, np.std)
xs = self.image.dimension_values('x', expanded=False)
mean = self.array.mean(axis=0)
std = self.array.std(axis=0)
self.assertEqual(
agg, Curve((xs, mean, std), kdims=['x'], vdims=['z', 'z_std']))
class ImageInterfaceTest(ComparisonTestCase):
datatype = 'image'
def setUp(self):
self.eltype = Image
self.restore_datatype = self.eltype.datatype
self.eltype.datatype = [self.datatype]
self.init_data()
def init_data(self):
self.array = np.arange(10) * np.arange(10)[:, np.newaxis]
self.image = Image(np.flipud(self.array), bounds=(-10, 0, 10, 10))
def tearDown(self):
self.eltype.datatype = self.restore_datatype
def test_init_bounds(self):
self.assertEqual(self.image.bounds.lbrt(), (-10, 0, 10, 10))
def test_init_densities(self):
self.assertEqual(self.image.xdensity, 0.5)
self.assertEqual(self.image.ydensity, 1)
def test_dimension_values_xs(self):
self.assertEqual(self.image.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_ys(self):
self.assertEqual(self.image.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_dimension_values_vdim(self):
self.assertEqual(self.image.dimension_values(2, flat=False),
self.array)
def test_index_single_coordinate(self):
self.assertEqual(self.image[0.3, 5.1], 25)
def test_slice_xaxis(self):
sliced = self.image[0.3:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 0, 6, 10))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[:, 5:8])
def test_slice_yaxis(self):
sliced = self.image[:, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (-10, 1., 10, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, :])
def test_slice_both_axes(self):
sliced = self.image[0.3:5.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 1., 6, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, 5:8])
def test_slice_x_index_y(self):
sliced = self.image[0.3:5.2, 5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 5.0, 6.0, 6.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[5:6, 5:8])
def test_index_x_slice_y(self):
sliced = self.image[3.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (2.0, 1.0, 4.0, 5.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, 6:7])
def test_range_xdim(self):
self.assertEqual(self.image.range(0), (-10, 10))
def test_range_ydim(self):
self.assertEqual(self.image.range(1), (0, 10))
def test_range_vdim(self):
self.assertEqual(self.image.range(2), (0, 81))
def test_dimension_values_xcoords(self):
self.assertEqual(self.image.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_ycoords(self):
self.assertEqual(self.image.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_sample_xcoord(self):
ys = np.linspace(0.5, 9.5, 10)
zs = [0, 7, 14, 21, 28, 35, 42, 49, 56, 63]
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
self.image):
self.assertEqual(self.image.sample(x=5),
Curve((ys, zs), kdims=['y'], vdims=['z']))
def test_sample_ycoord(self):
xs = np.linspace(-9, 9, 10)
zs = [0, 4, 8, 12, 16, 20, 24, 28, 32, 36]
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
self.image):
self.assertEqual(self.image.sample(y=5),
Curve((xs, zs), kdims=['x'], vdims=['z']))
def test_reduce_to_scalar(self):
self.assertEqual(self.image.reduce(['x', 'y'], function=np.mean),
20.25)
def test_reduce_x_dimension(self):
ys = np.linspace(0.5, 9.5, 10)
zs = [0., 4.5, 9., 13.5, 18., 22.5, 27., 31.5, 36., 40.5]
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
Image):
self.assertEqual(self.image.reduce(x=np.mean),
Curve((ys, zs), kdims=['y'], vdims=['z']))
def test_reduce_y_dimension(self):
xs = np.linspace(-9, 9, 10)
zs = [0., 4.5, 9., 13.5, 18., 22.5, 27., 31.5, 36., 40.5]
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
Image):
self.assertEqual(self.image.reduce(y=np.mean),
Curve((xs, zs), kdims=['x'], vdims=['z']))
def test_dataset_reindex_constant(self):
selected = Dataset(self.image.select(x=0))
reindexed = selected.reindex(['y'])
data = Dataset(selected.columns(['y', 'z']), kdims=['y'], vdims=['z'])
self.assertEqual(reindexed, data)
def test_dataset_reindex_non_constant(self):
ds = Dataset(self.image)
reindexed = ds.reindex(['y'])
data = Dataset(ds.columns(['y', 'z']), kdims=['y'], vdims=['z'])
self.assertEqual(reindexed, data)
def test_aggregate_with_spreadfn(self):
with DatatypeContext([self.datatype, 'dictionary', 'dataframe'],
self.image):
agg = self.image.aggregate('x', np.mean, np.std)
xs = self.image.dimension_values('x', expanded=False)
mean = self.array.mean(axis=0)
std = self.array.std(axis=0)
self.assertEqual(
agg, Curve((xs, mean, std), kdims=['x'], vdims=['z', 'z_std']))
class Image_ImageInterfaceTests(InterfaceTests):
"""
Tests for ImageInterface
"""
datatype = 'image'
element = Image
data_type = np.ndarray
def init_grid_data(self):
self.xs = np.linspace(-9, 9, 10)
self.ys = np.linspace(0.5, 9.5, 10)
self.array = np.arange(10) * np.arange(10)[:, np.newaxis]
def init_data(self):
self.image = Image(np.flipud(self.array), bounds=(-10, 0, 10, 10))
def test_init_data_tuple(self):
xs = np.arange(5)
ys = np.arange(10)
array = xs * ys[:, np.newaxis]
Image((xs, ys, array))
def test_init_data_tuple_error(self):
xs = np.arange(5)
ys = np.arange(10)
array = xs * ys[:, np.newaxis]
with self.assertRaises(DataError):
Image((ys, xs, array))
def test_bounds_mismatch(self):
with self.assertRaises(ValueError):
Image((range(10), range(10), np.random.rand(10, 10)), bounds=0.5)
def test_init_data_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10)
Image((xs, self.ys, self.array))
def test_init_data_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10)
Image((self.xs, ys, self.array))
def test_init_bounds(self):
self.assertEqual(self.image.bounds.lbrt(), (-10, 0, 10, 10))
def test_init_bounds_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10)
bounds = (start, 0, end, 10)
image = Image((xs, self.ys, self.array), bounds=bounds)
self.assertEqual(image.bounds.lbrt(), bounds)
def test_init_bounds_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10)
bounds = (-10, start, 10, end)
image = Image((self.xs, ys, self.array))
self.assertEqual(image.bounds.lbrt(), bounds)
def test_init_densities(self):
self.assertEqual(self.image.xdensity, 0.5)
self.assertEqual(self.image.ydensity, 1)
def test_init_densities_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10)
image = Image((xs, self.ys, self.array))
self.assertEqual(image.xdensity, 1e-5)
self.assertEqual(image.ydensity, 1)
def test_init_densities_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10)
image = Image((self.xs, ys, self.array))
self.assertEqual(image.xdensity, 0.5)
self.assertEqual(image.ydensity, 1e-5)
def test_dimension_values_xs(self):
self.assertEqual(self.image.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_ys(self):
self.assertEqual(self.image.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_dimension_values_vdim(self):
self.assertEqual(self.image.dimension_values(2, flat=False),
self.array)
def test_index_single_coordinate(self):
self.assertEqual(self.image[0.3, 5.1], 25)
def test_slice_xaxis(self):
sliced = self.image[0.3:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 0, 6, 10))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[:, 5:8])
def test_slice_datetime_xaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
bounds = (start, 0, end, 10)
xs = date_range(start, end, 10)
image = Image((xs, self.ys, self.array), bounds=bounds)
sliced = image[start+np.timedelta64(530, 'ms'): start+np.timedelta64(770, 'ms')]
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[:, 5:8])
def test_slice_yaxis(self):
sliced = self.image[:, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (-10, 1., 10, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, :])
def test_slice_datetime_yaxis(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10)
image = Image((self.xs, ys, self.array))
sliced = image[:, start+np.timedelta64(120, 'ms'): start+np.timedelta64(520, 'ms')]
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, :])
def test_slice_both_axes(self):
sliced = self.image[0.3:5.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 1., 6, 5))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, 5:8])
def test_slice_x_index_y(self):
sliced = self.image[0.3:5.2, 5.2]
self.assertEqual(sliced.bounds.lbrt(), (0, 5.0, 6.0, 6.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[5:6, 5:8])
def test_index_x_slice_y(self):
sliced = self.image[3.2, 1.2:5.2]
self.assertEqual(sliced.bounds.lbrt(), (2.0, 1.0, 4.0, 5.0))
self.assertEqual(sliced.xdensity, 0.5)
self.assertEqual(sliced.ydensity, 1)
self.assertEqual(sliced.dimension_values(2, flat=False),
self.array[1:5, 6:7])
def test_range_xdim(self):
self.assertEqual(self.image.range(0), (-10, 10))
def test_range_datetime_xdim(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10)
image = Image((xs, self.ys, self.array))
self.assertEqual(image.range(0), (start, end))
def test_range_ydim(self):
self.assertEqual(self.image.range(1), (0, 10))
def test_range_datetime_ydim(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10)
image = Image((self.xs, ys, self.array))
self.assertEqual(image.range(1), (start, end))
def test_range_vdim(self):
self.assertEqual(self.image.range(2), (0, 81))
def test_dimension_values_xcoords(self):
self.assertEqual(self.image.dimension_values(0, expanded=False),
np.linspace(-9, 9, 10))
def test_dimension_values_datetime_xcoords(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
xs = date_range(start, end, 10)
image = Image((xs, self.ys, self.array))
self.assertEqual(image.dimension_values(0, expanded=False),
date_range(start, end, 10))
def test_dimension_values_ycoords(self):
self.assertEqual(self.image.dimension_values(1, expanded=False),
np.linspace(0.5, 9.5, 10))
def test_sample_xcoord(self):
ys = np.linspace(0.5, 9.5, 10)
zs = [0, 7, 14, 21, 28, 35, 42, 49, 56, 63]
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.image):
self.assertEqual(self.image.sample(x=5),
Curve((ys, zs), kdims=['y'], vdims=['z']))
def test_sample_ycoord(self):
xs = np.linspace(-9, 9, 10)
zs = [0, 4, 8, 12, 16, 20, 24, 28, 32, 36]
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.image):
self.assertEqual(self.image.sample(y=5),
Curve((xs, zs), kdims=['x'], vdims=['z']))
def test_sample_coords(self):
arr = np.arange(10)*np.arange(5)[np.newaxis].T
xs = np.linspace(0.12, 0.81, 10)
ys = np.linspace(0.12, 0.391, 5)
img = Image((xs, ys, arr), kdims=['x', 'y'], vdims=['z'], datatype=[self.datatype])
sampled = img.sample([(0.15, 0.15), (0.15, 0.4), (0.8, 0.4), (0.8, 0.15)])
self.assertIsInstance(sampled, Table)
yidx = [0, 4, 4, 0]
xidx = [0, 0, 9, 9]
table = Table((xs[xidx], ys[yidx], arr[yidx, xidx]), kdims=['x', 'y'], vdims=['z'])
self.assertEqual(sampled, table)
def test_reduce_to_scalar(self):
self.assertEqual(self.image.reduce(['x', 'y'], function=np.mean),
20.25)
def test_reduce_x_dimension(self):
ys = np.linspace(0.5, 9.5, 10)
zs = [0., 4.5, 9., 13.5, 18., 22.5, 27., 31.5, 36., 40.5]
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], Image):
self.assertEqual(self.image.reduce(x=np.mean),
Curve((ys, zs), kdims=['y'], vdims=['z']))
def test_reduce_y_dimension(self):
xs = np.linspace(-9, 9, 10)
zs = [0., 4.5, 9., 13.5, 18., 22.5, 27., 31.5, 36., 40.5]
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], Image):
self.assertEqual(self.image.reduce(y=np.mean),
Curve((xs, zs), kdims=['x'], vdims=['z']))
def test_dataset_reindex_constant(self):
with DatatypeContext([self.datatype, 'dictionary', 'dataframe', 'grid'], self.image):
selected = Dataset(self.image.select(x=0))
reindexed = selected.reindex(['y'])
data = Dataset(selected.columns(['y', 'z']),
kdims=['y'], vdims=['z'])
self.assertEqual(reindexed, data)
def test_dataset_reindex_non_constant(self):
with DatatypeContext([self.datatype, 'dictionary', 'dataframe', 'grid'], self.image):
ds = Dataset(self.image)
reindexed = ds.reindex(['y'])
data = Dataset(ds.columns(['y', 'z']),
kdims=['y'], vdims=['z'])
self.assertEqual(reindexed, data)
def test_aggregate_with_spreadfn(self):
with DatatypeContext([self.datatype, 'dictionary' , 'dataframe'], self.image):
agg = self.image.aggregate('x', np.mean, np.std)
xs = self.image.dimension_values('x', expanded=False)
mean = self.array.mean(axis=0)
std = self.array.std(axis=0)
self.assertEqual(agg, Curve((xs, mean, std), kdims=['x'],
vdims=['z', 'z_std']))
def test_range_datetime_ydim(self):
start = np.datetime64(dt.datetime.today())
end = start+np.timedelta64(1, 's')
ys = date_range(start, end, 10)
image = Image((self.xs, ys, self.array))
self.assertEqual(image.range(1), (start, end))
