class TestDataAxis:
def setup_method(self, method):
self._axis = np.arange(16)**2
self.axis = DataAxis(axis=self._axis)
def _test_initialisation_parameters(self, axis):
np.testing.assert_allclose(axis.axis, self._axis)
def test_initialisation_parameters(self):
self._test_initialisation_parameters(self.axis)
def test_create_axis(self):
axis = create_axis(**self.axis.get_axis_dictionary())
assert isinstance(axis, DataAxis)
self._test_initialisation_parameters(axis)
def test_axis_value(self):
assert_allclose(self.axis.axis, np.arange(16)**2)
assert self.axis.size == 16
assert not self.axis.is_uniform
def test_update_axes(self):
values = np.arange(20)**2
self.axis.axis = values.tolist()
self.axis.update_axis()
assert self.axis.size == 20
assert_allclose(self.axis.axis, values)
def test_update_axes2(self):
values = np.array([3, 4, 10, 40])
self.axis.axis = values
self.axis.update_axis()
assert_allclose(self.axis.axis, values)
def test_update_axis_from_list(self):
values = np.arange(16)**2
self.axis.axis = values.tolist()
self.axis.update_axis()
assert_allclose(self.axis.axis, values)
def test_unsorted_axis(self):
with pytest.raises(ValueError):
DataAxis(axis=np.array([10, 40, 1, 30, 20]))
def test_index_changed_event(self):
ax = self.axis
m = mock.Mock()
ax.events.index_changed.connect(m.trigger_me)
ax.index = ax.index
assert not m.trigger_me.called
ax.index += 1
assert m.trigger_me.called
def test_value_changed_event(self):
ax = self.axis
m = mock.Mock()
ax.events.value_changed.connect(m.trigger_me)
ax.value = ax.value
assert not m.trigger_me.called
ax.value = ax.value + (ax.axis[1] - ax.axis[0]) * 0.4
assert not m.trigger_me.called
ax.value = ax.value + (ax.axis[1] - ax.axis[0]) / 2
assert not m.trigger_me.called
ax.value = ax.axis[1]
assert m.trigger_me.called
def test_deepcopy(self):
ac = copy.deepcopy(self.axis)
np.testing.assert_allclose(ac.axis, np.arange(16)**2)
ac.name = 'name changed'
assert ac.name == 'name changed'
assert self.axis.name != ac.name
def test_slice_me(self):
assert self.axis._slice_me(slice(1, 5)) == slice(1, 5)
assert self.axis.size == 4
np.testing.assert_allclose(self.axis.axis, np.arange(1, 5)**2)
def test_slice_me_step(self):
assert self.axis._slice_me(slice(0, 10, 2)) == slice(0, 10, 2)
assert self.axis.size == 5
np.testing.assert_allclose(self.axis.axis, np.arange(0, 10, 2)**2)
def test_convert_to_uniform_axis(self):
scale = (self.axis.high_value - self.axis.low_value) / self.axis.size
is_binned = self.axis.is_binned
navigate = self.axis.navigate
self.axis.name = "parrot"
self.axis.units = "plumage"
s = Signal1D(np.arange(10), axes=[self.axis])
index_in_array = s.axes_manager[0].index_in_array
s.axes_manager[0].convert_to_uniform_axis()
assert isinstance(s.axes_manager[0], UniformDataAxis)
assert s.axes_manager[0].name == "parrot"
assert s.axes_manager[0].units == "plumage"
assert s.axes_manager[0].size == 16
assert s.axes_manager[0].scale == scale
assert s.axes_manager[0].offset == 0
assert s.axes_manager[0].low_value == 0
assert s.axes_manager[0].high_value == 15 * scale
assert index_in_array == s.axes_manager[0].index_in_array
assert is_binned == s.axes_manager[0].is_binned
assert navigate == s.axes_manager[0].navigate
def test_value2index(self):
assert self.axis.value2index(10.15) == 3
assert self.axis.value2index(60) == 8
assert self.axis.value2index(2.5, rounding=round) == 1
assert self.axis.value2index(2.5, rounding=math.ceil) == 2
assert self.axis.value2index(2.5, rounding=math.floor) == 1
# Test that output is integer
assert isinstance(self.axis.value2index(60), (int, np.integer))
self.axis.axis = self.axis.axis - 2
# test rounding on negative value
assert self.axis.value2index(-1.5, rounding=round) == 1
def test_value2index_error(self):
with pytest.raises(ValueError):
self.axis.value2index(226)
def test_parse_value_from_relative_string(self):
ax = self.axis
assert ax._parse_value_from_string('rel0.0') == 0.0
assert ax._parse_value_from_string('rel0.5') == 112.5
assert ax._parse_value_from_string('rel1.0') == 225.0
with pytest.raises(ValueError):
ax._parse_value_from_string('rela0.5')
with pytest.raises(ValueError):
ax._parse_value_from_string('rel1.5')
with pytest.raises(ValueError):
ax._parse_value_from_string('abcd')
def test_parse_value_from_string_with_units(self):
ax = self.axis
ax.units = 'nm'
with pytest.raises(ValueError):
ax._parse_value_from_string('0.02 um')
@pytest.mark.parametrize("use_indices", (False, True))
def test_crop(self, use_indices):
axis = DataAxis(axis=self._axis)
start, end = 4., 196.
if use_indices:
start = axis.value2index(start)
end = axis.value2index(end)
axis.crop(start, end)
assert axis.size == 12
np.testing.assert_almost_equal(axis.axis[0], 4)
np.testing.assert_almost_equal(axis.axis[-1], 169)
def test_crop_reverses_indexing(self):
# reverse indexing
axis = DataAxis(axis=self._axis)
axis.crop(-14, -2)
assert axis.size == 12
np.testing.assert_almost_equal(axis.axis[0], 4)
np.testing.assert_almost_equal(axis.axis[-1], 169)
# mixed reverses indexing
axis = DataAxis(axis=self._axis)
axis.crop(2, -2)
assert axis.size == 12
np.testing.assert_almost_equal(axis.axis[0], 4)
np.testing.assert_almost_equal(axis.axis[-1], 169)
def test_error_DataAxis(self):
with pytest.raises(ValueError):
_ = DataAxis(axis=np.arange(16)**2, _type='UniformDataAxis')
with pytest.raises(AttributeError):
self.axis.index_in_axes_manager()
with pytest.raises(IndexError):
self.axis._get_positive_index(-17)
with pytest.raises(ValueError):
self.axis._get_array_slices(slice_=slice(1,2,1.5))
with pytest.raises(IndexError):
self.axis._get_array_slices(slice_=slice(225,-1.1,1))
with pytest.raises(IndexError):
self.axis._get_array_slices(slice_=slice(225.1,0,1))
def test_update_from(self):
ax2 = DataAxis(units="plumage", name="parrot", axis=np.arange(16))
self.axis.update_from(ax2, attributes=("units", "name"))
assert ((ax2.units, ax2.name) ==
(self.axis.units, self.axis.name))
def test_calibrate(self):
with pytest.raises(TypeError, match="only for uniform axes"):
self.axis.calibrate(value_tuple=(11,12), index_tuple=(0,5))
