def setup_method(self, method):
s = BaseSignal(np.random.rand(1, 2, 3, 4, 5, 6))
for ax, name in zip(s.axes_manager._axes, "abcdef"):
ax.name = name
# just to make sure in case default changes
assert s.axes_manager.signal_dimension == 6
s.estimate_poissonian_noise_variance()
self.s = s
class TestTranspose:
def setup_method(self, method):
self.s = BaseSignal(np.random.rand(1, 2, 3, 4, 5, 6))
for ax, name in zip(self.s.axes_manager._axes, "abcdef"):
ax.name = name
# just to make sure in case default changes
self.s.axes_manager.set_signal_dimension(6)
self.s.estimate_poissonian_noise_variance()
def test_signal_int_transpose(self):
t = self.s.transpose(signal_axes=2)
var = t.metadata.Signal.Noise_properties.variance
assert t.axes_manager.signal_shape == (6, 5)
assert var.axes_manager.signal_shape == (6, 5)
assert [ax.name for ax in t.axes_manager.signal_axes] == ["f", "e"]
assert isinstance(t, Signal2D)
assert isinstance(t.metadata.Signal.Noise_properties.variance, Signal2D)
def test_signal_iterable_int_transpose(self):
t = self.s.transpose(signal_axes=[0, 5, 4])
var = t.metadata.Signal.Noise_properties.variance
assert t.axes_manager.signal_shape == (6, 1, 2)
assert var.axes_manager.signal_shape == (6, 1, 2)
assert [ax.name for ax in t.axes_manager.signal_axes] == ["f", "a", "b"]
def test_signal_iterable_names_transpose(self):
t = self.s.transpose(signal_axes=["f", "a", "b"])
var = t.metadata.Signal.Noise_properties.variance
assert t.axes_manager.signal_shape == (6, 1, 2)
assert var.axes_manager.signal_shape == (6, 1, 2)
assert [ax.name for ax in t.axes_manager.signal_axes] == ["f", "a", "b"]
def test_signal_iterable_axes_transpose(self):
t = self.s.transpose(signal_axes=self.s.axes_manager.signal_axes[:2])
var = t.metadata.Signal.Noise_properties.variance
assert t.axes_manager.signal_shape == (6, 5)
assert var.axes_manager.signal_shape == (6, 5)
assert [ax.name for ax in t.axes_manager.signal_axes] == ["f", "e"]
def test_signal_one_name(self):
with pytest.raises(ValueError):
self.s.transpose(signal_axes="a")
def test_too_many_signal_axes(self):
with pytest.raises(ValueError):
self.s.transpose(signal_axes=10)
def test_navigation_int_transpose(self):
t = self.s.transpose(navigation_axes=2)
var = t.metadata.Signal.Noise_properties.variance
assert t.axes_manager.navigation_shape == (2, 1)
assert var.axes_manager.navigation_shape == (2, 1)
assert [ax.name for ax in t.axes_manager.navigation_axes] == ["b", "a"]
def test_navigation_iterable_int_transpose(self):
t = self.s.transpose(navigation_axes=[0, 5, 4])
var = t.metadata.Signal.Noise_properties.variance
assert t.axes_manager.navigation_shape == (6, 1, 2)
assert var.axes_manager.navigation_shape == (6, 1, 2)
assert [ax.name for ax in t.axes_manager.navigation_axes] == ["f", "a", "b"]
def test_navigation_iterable_names_transpose(self):
t = self.s.transpose(navigation_axes=["f", "a", "b"])
var = t.metadata.Signal.Noise_properties.variance
assert var.axes_manager.navigation_shape == (6, 1, 2)
assert t.axes_manager.navigation_shape == (6, 1, 2)
assert [ax.name for ax in t.axes_manager.navigation_axes] == ["f", "a", "b"]
def test_navigation_iterable_axes_transpose(self):
t = self.s.transpose(navigation_axes=self.s.axes_manager.signal_axes[:2])
var = t.metadata.Signal.Noise_properties.variance
assert t.axes_manager.navigation_shape == (6, 5)
assert var.axes_manager.navigation_shape == (6, 5)
assert [ax.name for ax in t.axes_manager.navigation_axes] == ["f", "e"]
def test_navigation_one_name(self):
with pytest.raises(ValueError):
self.s.transpose(navigation_axes="a")
def test_too_many_navigation_axes(self):
with pytest.raises(ValueError):
self.s.transpose(navigation_axes=10)
def test_transpose_shortcut(self):
s = self.s.transpose(signal_axes=2)
t = s.T
assert t.axes_manager.navigation_shape == (6, 5)
assert [ax.name for ax in t.axes_manager.navigation_axes] == ["f", "e"]
def test_optimize(self):
if self.s._lazy:
pytest.skip(
"LazySignal optimization is tested in test_lazy_tranpose_rechunk"
)
t = self.s.transpose(signal_axes=["f", "a", "b"], optimize=False)
assert t.data.base is self.s.data
t = self.s.transpose(signal_axes=["f", "a", "b"], optimize=True)
assert t.data.base is not self.s.data