def test_world_component_ids(self):
derived = IndexedData(self.data, (None, 2, None, 4, None))
assert derived.world_component_ids == []
derived_with_coords = IndexedData(self.data_with_coords,
(None, 2, None, 4, None))
assert_equal(
derived_with_coords.get_data(
derived_with_coords.world_component_ids[0]),
self.data_with_coords.get_data(
self.data_with_coords.world_component_ids[0])[:, 2, :, 4, :])
assert_equal(
derived_with_coords.get_data(
derived_with_coords.world_component_ids[1]),
self.data_with_coords.get_data(
self.data_with_coords.world_component_ids[2])[:, 2, :, 4, :])
assert_equal(
derived_with_coords.get_data(
derived_with_coords.world_component_ids[2]),
self.data_with_coords.get_data(
self.data_with_coords.world_component_ids[4])[:, 2, :, 4, :])
def test_indexed(self):
# Here we slice two of the dimensions and then compare the results to a
# manually sliced dataset.
derived = IndexedData(self.data, (None, 2, None, 4, None))
manual = Data()
manual.add_component(self.data[self.x_id][:, 2, :, 4, :], label=self.x_id)
manual.add_component(self.data[self.y_id][:, 2, :, 4, :], label=self.y_id)
assert derived.label == 'Test data[:,2,:,4,:]'
assert derived.shape == manual.shape
assert [str(c) for c in derived.main_components] == [str(c) for c in manual.main_components]
assert derived.get_kind(self.x_id) == manual.get_kind(self.x_id)
for view in [None, (1, slice(None), slice(1, 4))]:
assert_equal(derived.get_data(self.x_id, view=view),
manual.get_data(self.x_id, view=view))
assert_equal(derived.get_mask(self.subset_state, view=view),
manual.get_mask(self.subset_state, view=view))
bounds = [2, (-5, 5, 10), (-3, 3, 10)]
assert_equal(derived.compute_fixed_resolution_buffer(bounds=bounds, target_cid=self.x_id),
manual.compute_fixed_resolution_buffer(bounds=bounds, target_cid=self.x_id))
assert_equal(derived.compute_statistic('mean', self.x_id),
manual.compute_statistic('mean', self.x_id))
assert_equal(derived.compute_statistic('mean', self.x_id, axis=2),
manual.compute_statistic('mean', self.x_id, axis=2))
assert_equal(derived.compute_statistic('mean', self.x_id, subset_state=self.subset_state),
manual.compute_statistic('mean', self.x_id, subset_state=self.subset_state))
assert_equal(derived.compute_histogram([self.x_id], range=[(0, 1000)], bins=[30]),
manual.compute_histogram([self.x_id], range=[(0, 1000)], bins=[30]))
assert_equal(derived.compute_histogram([self.x_id], range=[(0, 1000)], bins=[30], subset_state=self.subset_state),
manual.compute_histogram([self.x_id], range=[(0, 1000)], bins=[30], subset_state=self.subset_state))
def test_identity(self):
# In this test, we don't actually slice any dimensions
derived = IndexedData(self.data, (None,) * 5)
assert derived.label == 'Test data[:,:,:,:,:]'
assert derived.shape == self.data.shape
assert [str(c) for c in derived.main_components] == [str(c) for c in self.data.main_components]
assert derived.get_kind(self.x_id) == self.data.get_kind(self.x_id)
for view in [None, (1, slice(None), slice(None), slice(1, 4), slice(0, 7, 2))]:
assert_equal(derived.get_data(self.x_id, view=view),
self.data.get_data(self.x_id, view=view))
assert_equal(derived.get_mask(self.subset_state, view=view),
self.data.get_mask(self.subset_state, view=view))
bounds = [2, (-5, 5, 10), 3, 4, (-3, 3, 10)]
assert_equal(derived.compute_fixed_resolution_buffer(bounds=bounds, target_cid=self.x_id),
self.data.compute_fixed_resolution_buffer(bounds=bounds, target_cid=self.x_id))
assert_equal(derived.compute_statistic('mean', self.x_id),
self.data.compute_statistic('mean', self.x_id))
assert_equal(derived.compute_statistic('mean', self.x_id, axis=2),
self.data.compute_statistic('mean', self.x_id, axis=2))
assert_equal(derived.compute_statistic('mean', self.x_id, subset_state=self.subset_state),
self.data.compute_statistic('mean', self.x_id, subset_state=self.subset_state))
assert_equal(derived.compute_histogram([self.x_id], range=[(0, 1000)], bins=[30]),
self.data.compute_histogram([self.x_id], range=[(0, 1000)], bins=[30]))
assert_equal(derived.compute_histogram([self.x_id], range=[(0, 1000)], bins=[30], subset_state=self.subset_state),
self.data.compute_histogram([self.x_id], range=[(0, 1000)], bins=[30], subset_state=self.subset_state))
def test_indexed(self):
# Here we slice two of the dimensions and then compare the results to a
# manually sliced dataset.
derived = IndexedData(self.data, (None, 2, None, 4, None))
manual = Data()
manual.add_component(self.data[self.x_id][:, 2, :, 4, :],
label=self.x_id)
manual.add_component(self.data[self.y_id][:, 2, :, 4, :],
label=self.y_id)
assert derived.label == 'Test data[:,2,:,4,:]'
assert derived.shape == manual.shape
assert [str(c) for c in derived.main_components
] == [str(c) for c in manual.main_components]
assert derived.get_kind(self.x_id) == manual.get_kind(self.x_id)
for view in [None, (1, slice(None), slice(1, 4))]:
assert_equal(derived.get_data(self.x_id, view=view),
manual.get_data(self.x_id, view=view))
assert_equal(derived.get_mask(self.subset_state, view=view),
manual.get_mask(self.subset_state, view=view))
bounds = [2, (-5, 5, 10), (-3, 3, 10)]
assert_equal(
derived.compute_fixed_resolution_buffer(bounds=bounds,
target_cid=self.x_id),
manual.compute_fixed_resolution_buffer(bounds=bounds,
target_cid=self.x_id))
assert_equal(derived.compute_statistic('mean', self.x_id),
manual.compute_statistic('mean', self.x_id))
assert_equal(derived.compute_statistic('mean', self.x_id, axis=2),
manual.compute_statistic('mean', self.x_id, axis=2))
assert_equal(
derived.compute_statistic('mean',
self.x_id,
subset_state=self.subset_state),
manual.compute_statistic('mean',
self.x_id,
subset_state=self.subset_state))
assert_equal(
derived.compute_histogram([self.x_id],
range=[(0, 1000)],
bins=[30]),
manual.compute_histogram([self.x_id], range=[(0, 1000)],
bins=[30]))
assert_equal(
derived.compute_histogram([self.x_id],
range=[(0, 1000)],
bins=[30],
subset_state=self.subset_state),
manual.compute_histogram([self.x_id],
range=[(0, 1000)],
bins=[30],
subset_state=self.subset_state))
def test_identity(self):
# In this test, we don't actually slice any dimensions
derived = IndexedData(self.data, (None, ) * 5)
assert derived.label == 'Test data[:,:,:,:,:]'
assert derived.shape == self.data.shape
assert [str(c) for c in derived.main_components
] == [str(c) for c in self.data.main_components]
assert derived.get_kind(self.x_id) == self.data.get_kind(self.x_id)
for view in [
None, (1, slice(None), slice(None), slice(1,
4), slice(0, 7, 2))
]:
assert_equal(derived.get_data(self.x_id, view=view),
self.data.get_data(self.x_id, view=view))
assert_equal(derived.get_mask(self.subset_state, view=view),
self.data.get_mask(self.subset_state, view=view))
bounds = [2, (-5, 5, 10), 3, 4, (-3, 3, 10)]
assert_equal(
derived.compute_fixed_resolution_buffer(bounds=bounds,
target_cid=self.x_id),
self.data.compute_fixed_resolution_buffer(bounds=bounds,
target_cid=self.x_id))
assert_equal(derived.compute_statistic('mean', self.x_id),
self.data.compute_statistic('mean', self.x_id))
assert_equal(derived.compute_statistic('mean', self.x_id, axis=2),
self.data.compute_statistic('mean', self.x_id, axis=2))
assert_equal(
derived.compute_statistic('mean',
self.x_id,
subset_state=self.subset_state),
self.data.compute_statistic('mean',
self.x_id,
subset_state=self.subset_state))
assert_equal(
derived.compute_histogram([self.x_id],
range=[(0, 1000)],
bins=[30]),
self.data.compute_histogram([self.x_id],
range=[(0, 1000)],
bins=[30]))
assert_equal(
derived.compute_histogram([self.x_id],
range=[(0, 1000)],
bins=[30],
subset_state=self.subset_state),
self.data.compute_histogram([self.x_id],
range=[(0, 1000)],
bins=[30],
subset_state=self.subset_state))
def test_pixel_component_ids(self):
derived = IndexedData(self.data, (None, 2, None, 4, None))
assert_equal(
derived.get_data(derived.pixel_component_ids[1]),
self.data.get_data(self.data.pixel_component_ids[2])[:, 2, :,
4, :])
def test_pixel_component_ids(self):
derived = IndexedData(self.data, (None, 2, None, 4, None))
assert_equal(derived.get_data(derived.pixel_component_ids[1]),
self.data.get_data(self.data.pixel_component_ids[2])[:, 2, :, 4, :])