class Test2d:
def setup_method(self, method):
self.s = BaseSignal(np.random.random((2, 3))) # (|3, 2)
def test_as_signal2D_T(self):
assert (self.s.data.T.shape == self.s.as_signal2D((1, 0)).data.shape)
def test_as_signal2D(self):
assert (self.s.data.shape == self.s.as_signal2D((0, 1)).data.shape)
def test_as_signal1D_T(self):
assert (self.s.data.T.shape == self.s.as_signal1D(1).data.shape)
def test_as_signal1D(self):
assert (self.s.data.shape == self.s.as_signal1D(0).data.shape)
def test_s2EELS2im2s(self):
s = self.s.as_signal1D(0)
s.set_signal_type("EELS")
im = s.as_signal2D((1, 0))
assert im.metadata.Signal.signal_type == "EELS"
s = im.as_signal1D(0)
assert s.metadata.Signal.signal_type == "EELS"
if s._lazy:
_class = _lazy_signals.LazyEELSSpectrum
else:
_class = signals.EELSSpectrum
assert isinstance(s, _class)
class Test3d:
def setUp(self):
self.s = BaseSignal(np.random.random((2, 3, 4))) # (|4, 3, 2)
def test_as_signal2D_contigous(self):
nt.assert_true(self.s.as_signal2D((0, 1)).data.flags["C_CONTIGUOUS"])
def test_as_signal2D_1(self):
nt.assert_equal(self.s.as_signal2D((0, 1)).data.shape, (2, 3, 4)) # (2| 4, 3)
def test_as_signal2D_2(self):
nt.assert_equal(self.s.as_signal2D((1, 0)).data.shape, (2, 4, 3)) # (2| 3, 4)
def test_as_signal2D_3(self):
nt.assert_equal(self.s.as_signal2D((1, 2)).data.shape, (4, 2, 3)) # (4| 3, 2)
def test_as_signal1D_contigous(self):
nt.assert_true(self.s.as_signal1D(0).data.flags["C_CONTIGUOUS"])
def test_as_signal1D_0(self):
nt.assert_equal(self.s.as_signal1D(0).data.shape, (2, 3, 4)) # (3, 2| 4)
def test_as_signal1D_1(self):
nt.assert_equal(self.s.as_signal1D(1).data.shape, (2, 4, 3)) # (4, 2| 3)
def test_as_signal1D_2(self):
nt.assert_equal(self.s.as_signal1D(2).data.shape, (3, 4, 2)) # (4, 3| 2)
def test_remove_axis(self):
im = self.s.as_signal2D((-2, -1))
im._remove_axis(-1)
nt.assert_is_instance(im, signals.Signal1D)
class Test2d:
def setUp(self):
self.s = BaseSignal(np.random.random((2, 3))) # (|3, 2)
def test_as_signal2D_T(self):
nt.assert_equal(self.s.data.T.shape,
self.s.as_signal2D((1, 0)).data.shape)
def test_as_signal2D(self):
nt.assert_equal(self.s.data.shape,
self.s.as_signal2D((0, 1)).data.shape)
def test_as_signal1D_T(self):
nt.assert_equal(self.s.data.T.shape, self.s.as_signal1D(1).data.shape)
def test_as_signal1D(self):
nt.assert_equal(self.s.data.shape, self.s.as_signal1D(0).data.shape)
def test_s2EELS2im2s(self):
s = self.s.as_signal1D(0)
s.set_signal_type("EELS")
im = s.as_signal2D((1, 0))
nt.assert_equal(im.metadata.Signal.signal_type, "EELS")
s = im.as_signal1D(0)
nt.assert_equal(s.metadata.Signal.signal_type, "EELS")
nt.assert_is_instance(s, signals.EELSSpectrum)
class Test2d:
def setup_method(self, method):
self.s = BaseSignal(np.random.random((2, 3))) # (|3, 2)
def test_as_signal2D_T(self):
assert (
self.s.data.T.shape == self.s.as_signal2D((1, 0)).data.shape)
def test_as_signal2D(self):
assert (
self.s.data.shape == self.s.as_signal2D((0, 1)).data.shape)
def test_as_signal1D_T(self):
assert (
self.s.data.T.shape == self.s.as_signal1D(1).data.shape)
def test_as_signal1D(self):
assert (
self.s.data.shape == self.s.as_signal1D(0).data.shape)
def test_s2EELS2im2s(self):
s = self.s.as_signal1D(0)
s.set_signal_type("EELS")
im = s.as_signal2D((1, 0))
assert im.metadata.Signal.signal_type == "EELS"
s = im.as_signal1D(0)
assert s.metadata.Signal.signal_type == "EELS"
if s._lazy:
_class = signals.LazyEELSSpectrum
else:
_class = signals.EELSSpectrum
assert isinstance(s, _class)
class Test1d:
def setUp(self):
self.s = BaseSignal(np.arange(2))
@nt.raises(DataDimensionError)
def test_as_signal2D(self):
nt.assert_true((self.s.data == self.s.as_signal2D((0, 1)).data).all())
def test_as_signal1D(self):
nt.assert_true((self.s.data == self.s.as_signal1D(0).data).all())
def test_set_EELS(self):
s = self.s.as_signal1D(0)
s.set_signal_type("EELS")
nt.assert_equal(s.metadata.Signal.signal_type, "EELS")
nt.assert_is_instance(s, signals.EELSSpectrum)
class Test1d:
def setUp(self):
self.s = BaseSignal(np.arange(2))
@nt.raises(DataDimensionError)
def test_as_signal2D(self):
nt.assert_true((self.s.data == self.s.as_signal2D((0, 1)).data).all())
def test_as_signal1D(self):
nt.assert_true((self.s.data == self.s.as_signal1D(0).data).all())
def test_set_EELS(self):
s = self.s.as_signal1D(0)
s.set_signal_type("EELS")
nt.assert_equal(s.metadata.Signal.signal_type, "EELS")
nt.assert_is_instance(s, signals.EELSSpectrum)
def _denoised_data_to_signal(self):
"""Converts denoised data back to a HyperSpy signal."""
signal = BaseSignal(self.Y_)
if self._signal_type == "spectrum":
return signal.as_signal1D(2)
if self._signal_type == "image":
return signal.as_signal2D((1, 2))
class Test3d:
def setup_method(self, method):
self.s = BaseSignal(np.random.random((2, 3, 4))) # (|4, 3, 2)
def test_as_signal2D_contigous(self):
if self.s._lazy:
pytest.skip("Dask array flags not supported")
assert self.s.as_signal2D((0, 1)).data.flags['C_CONTIGUOUS']
def test_as_signal2D_1(self):
assert (
self.s.as_signal2D((0, 1)).data.shape == (2, 3, 4)) # (2| 4, 3)
def test_as_signal2D_2(self):
assert (
self.s.as_signal2D((1, 0)).data.shape == (2, 4, 3)) # (2| 3, 4)
def test_as_signal2D_3(self):
assert (
self.s.as_signal2D((1, 2)).data.shape == (4, 2, 3)) # (4| 3, 2)
def test_as_signal1D_contigous(self):
if self.s._lazy:
pytest.skip("Dask array flags not supported")
assert self.s.as_signal1D(0).data.flags['C_CONTIGUOUS']
def test_as_signal1D_0(self):
assert (
self.s.as_signal1D(0).data.shape == (2, 3, 4)) # (3, 2| 4)
def test_as_signal1D_1(self):
assert (
self.s.as_signal1D(1).data.shape == (2, 4, 3)) # (4, 2| 3)
def test_as_signal1D_2(self):
assert (
self.s.as_signal1D(2).data.shape == (3, 4, 2)) # (4, 3| 2)
def test_remove_axis(self):
im = self.s.as_signal2D((-2, -1))
im._remove_axis(-1)
assert isinstance(im, signals.Signal1D)
class Test3d:
def setup_method(self, method):
self.s = BaseSignal(np.random.random((2, 3, 4))) # (|4, 3, 2)
def test_as_signal2D_contigous(self):
if self.s._lazy:
pytest.skip("Dask array flags not supported")
assert self.s.as_signal2D((0, 1)).data.flags['C_CONTIGUOUS']
def test_as_signal2D_1(self):
assert (
self.s.as_signal2D((0, 1)).data.shape == (2, 3, 4)) # (2| 4, 3)
def test_as_signal2D_2(self):
assert (
self.s.as_signal2D((1, 0)).data.shape == (2, 4, 3)) # (2| 3, 4)
def test_as_signal2D_3(self):
assert (
self.s.as_signal2D((1, 2)).data.shape == (4, 2, 3)) # (4| 3, 2)
def test_as_signal1D_contigous(self):
if self.s._lazy:
pytest.skip("Dask array flags not supported")
assert self.s.as_signal1D(0).data.flags['C_CONTIGUOUS']
def test_as_signal1D_0(self):
assert (
self.s.as_signal1D(0).data.shape == (2, 3, 4)) # (3, 2| 4)
def test_as_signal1D_1(self):
assert (
self.s.as_signal1D(1).data.shape == (2, 4, 3)) # (4, 2| 3)
def test_as_signal1D_2(self):
assert (
self.s.as_signal1D(2).data.shape == (3, 4, 2)) # (4, 3| 2)
def test_remove_axis(self):
im = self.s.as_signal2D((-2, -1))
im._remove_axis(-1)
assert isinstance(im, signals.Signal1D)
class Test1d:
def setup_method(self, method):
self.s = BaseSignal(np.arange(2))
def test_as_signal2D(self):
with pytest.raises(DataDimensionError):
assert (self.s.data == self.s.as_signal2D((0, 1)).data).all()
def test_as_signal1D(self):
assert (self.s.data == self.s.as_signal1D(0).data).all()
def test_set_EELS(self):
s = self.s.as_signal1D(0)
s.set_signal_type("EELS")
assert s.metadata.Signal.signal_type == "EELS"
if s._lazy:
_class = _lazy_signals.LazyEELSSpectrum
else:
_class = signals.EELSSpectrum
assert isinstance(s, _class)
class Test1d:
def setup_method(self, method):
self.s = BaseSignal(np.arange(2))
def test_as_signal2D(self):
with pytest.raises(DataDimensionError):
assert (self.s.data == self.s.as_signal2D(
(0, 1)).data).all()
def test_as_signal1D(self):
assert (self.s.data == self.s.as_signal1D(0).data).all()
def test_set_EELS(self):
s = self.s.as_signal1D(0)
s.set_signal_type("EELS")
assert s.metadata.Signal.signal_type == "EELS"
if s._lazy:
_class = signals.LazyEELSSpectrum
else:
_class = signals.EELSSpectrum
assert isinstance(s, _class)
class Test3d:
def setUp(self):
self.s = BaseSignal(np.random.random((2, 3, 4))) # (|4, 3, 2)
def test_as_signal2D_contigous(self):
nt.assert_true(self.s.as_signal2D((0, 1)).data.flags['C_CONTIGUOUS'])
def test_as_signal2D_1(self):
nt.assert_equal(self.s.as_signal2D((0, 1)).data.shape,
(2, 3, 4)) # (2| 4, 3)
def test_as_signal2D_2(self):
nt.assert_equal(self.s.as_signal2D((1, 0)).data.shape,
(2, 4, 3)) # (2| 3, 4)
def test_as_signal2D_3(self):
nt.assert_equal(self.s.as_signal2D((1, 2)).data.shape,
(4, 2, 3)) # (4| 3, 2)
def test_as_signal1D_contigous(self):
nt.assert_true(self.s.as_signal1D(0).data.flags['C_CONTIGUOUS'])
def test_as_signal1D_0(self):
nt.assert_equal(self.s.as_signal1D(0).data.shape,
(2, 3, 4)) # (3, 2| 4)
def test_as_signal1D_1(self):
nt.assert_equal(self.s.as_signal1D(1).data.shape,
(2, 4, 3)) # (4, 2| 3)
def test_as_signal1D_2(self):
nt.assert_equal(self.s.as_signal1D(2).data.shape,
(3, 4, 2)) # (4, 3| 2)
def test_remove_axis(self):
im = self.s.as_signal2D((-2, -1))
im._remove_axis(-1)
nt.assert_is_instance(im, signals.Signal1D)
class Test2d:
def setUp(self):
self.s = BaseSignal(np.random.random((2, 3))) # (|3, 2)
def test_as_signal2D_T(self):
nt.assert_equal(self.s.data.T.shape, self.s.as_signal2D((1, 0)).data.shape)
def test_as_signal2D(self):
nt.assert_equal(self.s.data.shape, self.s.as_signal2D((0, 1)).data.shape)
def test_as_signal1D_T(self):
nt.assert_equal(self.s.data.T.shape, self.s.as_signal1D(1).data.shape)
def test_as_signal1D(self):
nt.assert_equal(self.s.data.shape, self.s.as_signal1D(0).data.shape)
def test_s2EELS2im2s(self):
s = self.s.as_signal1D(0)
s.set_signal_type("EELS")
im = s.as_signal2D((1, 0))
nt.assert_equal(im.metadata.Signal.signal_type, "EELS")
s = im.as_signal1D(0)
nt.assert_equal(s.metadata.Signal.signal_type, "EELS")
nt.assert_is_instance(s, signals.EELSSpectrum)
def to_signal(self, mask=None):
"""
Creates a hyperspy.Signal1D object with the same spectral image.
The resulting hyperspy.Signal1D contains the full spectral image.
Returns
----------
s : hyperspy.Signal1D
hyperspy object
"""
(nz, ny, nx, nf) = np.shape(self.spec_im)
dx = (self.x_array[1] - self.x_array[0])
dy = (self.y_array[1] - self.y_array[0])
(units, scale) = self.get_unit_scaling()
dx *= scale
dy *= scale
spec_name = 'index'
if self.spec_units in ['nm', 'um']:
spec_name = 'Wavelength'
elif self.spec_units == 'eV':
spec_name = 'E'
dict_y = {'name': 'y', 'units': units, 'scale': dy, 'size': ny}
dict_x = {'name': 'x', 'units': units, 'scale': dx, 'size': nx}
dict_f = {
'name': spec_name,
'units': self.spec_units,
'scale': self.spec_x_array[1] - self.spec_x_array[0],
'size': nf,
'offset': self.spec_x_array[0]
}
dict_z = {'name': 'z', 'units': units, 'size': nz}
if nz == 1:
s = Signal1D(np.squeeze(self.spec_im),
axes=[dict_y, dict_x, dict_f],
mask=mask)
s.change_dtype('float64')
return s
else:
dz = (self.z_array[1] - self.z_array[0]) * scale
dict_z['scale'] = dz
s = BaseSignal(self.spec_im, axes=[dict_z, dict_y, dict_x, dict_f])
s.change_dtype('float64')
return s.as_signal1D(0)
