def test_get_spectrum_distribution_workspace(self):
# Since the workspace being plotted is a distribution, we should not
# divide by bin width whether or not normalize_by_bin_width is True
x, y, dy, dx = funcs.get_spectrum(self.ws2d_histo,
1,
True,
withDy=True,
withDx=True)
self.assertTrue(np.array_equal(x, np.array([15., 25.])))
self.assertTrue(np.array_equal(y, np.array([4, 5])))
self.assertTrue(np.array_equal(dy, np.array([3, 4])))
self.assertEqual(dx, None)
x, y, dy, dx = funcs.get_spectrum(self.ws2d_histo,
0,
False,
withDy=True,
withDx=True)
self.assertTrue(np.array_equal(x, np.array([15., 25.])))
self.assertTrue(np.array_equal(y, np.array([2, 3])))
self.assertTrue(np.array_equal(dy, np.array([1, 2])))
self.assertEqual(dx, None)
# fail case - try to find spectrum out of range
self.assertRaises(RuntimeError, funcs.get_spectrum, self.ws2d_histo,
10, True)
def test_get_spectrum(self):
# get data divided by bin width
x, y, dy, dx = funcs.get_spectrum(self.ws2d_histo, 1, False, withDy=True, withDx=True)
self.assertTrue(np.array_equal(x, np.array([15., 25.])))
self.assertTrue(np.array_equal(y, np.array([.4, .5])))
self.assertTrue(np.array_equal(dy, np.array([.3, .4])))
self.assertEqual(dx, None)
# get data not divided by bin width
x, y, dy, dx = funcs.get_spectrum(self.ws2d_histo, 0, True, withDy=True, withDx=True)
self.assertTrue(np.array_equal(x, np.array([15., 25.])))
self.assertTrue(np.array_equal(y, np.array([2, 3])))
self.assertTrue(np.array_equal(dy, np.array([1, 2])))
self.assertEqual(dx, None)
# fail case - try to find spectrum out of range
self.assertRaises(RuntimeError, funcs.get_spectrum, self.ws2d_histo, 10, True)
def plot(axes, workspace, *args, **kwargs):
'''
3D plots - line plots
:param axes: class:`matplotlib.axes.Axes3D` object that will do the plotting
:param workspace: :class:`mantid.api.MatrixWorkspace` or
:class:`mantid.api.IMDHistoWorkspace` to extract the data from
:param zdir: Which direction to use as z ('x', 'y' or 'z') when plotting a 2D set.
:param indices: Specify which slice of an MDHistoWorkspace to use when plotting. Needs to be a tuple
and will be interpreted as a list of indices. You need to use ``slice(None)`` to
select which dimension to plot. *e.g.* to select the second axis to plot from a
3D volume use ``indices=(5, slice(None), 10)`` where the 5/10 are the bins selected
for the other 2 axes.
:param slicepoint: Specify which slice of an MDHistoWorkspace to use when plotting in the dimension units.
You need to use ``None`` to select which dimension to plot. *e.g.* to select the second
axis to plot from a 3D volume use ``slicepoint=(1.0, None, 2.0)`` where the 1.0/2.0 are
the dimension selected for the other 2 axes.
'''
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
(x, y, z) = get_md_data1d(workspace, normalization, indices)
else:
(wksp_index, distribution, kwargs) = get_wksp_index_dist_and_label(workspace, **kwargs)
(x, z, _, _) = get_spectrum(workspace, wksp_index, distribution, withDy=False, withDx=False)
y_val = workspace.getAxis(1).extractValues()[wksp_index]
y = [y_val for _ in range(len(x))] # fill x size array with y value
_set_labels_3d(axes, workspace)
return axes.plot(x, y, z, *args, **kwargs)
def test_get_spectrum_with_dy_dx(self, ws):
x, y, dy, dx = funcs.get_spectrum(ws, 3, normalize_by_bin_width=False, withDy=True, withDx=True)
self.assertTrue(np.array_equal([13.5, 14.5, 15.5], x))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], y))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], dy))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], dx))
def scatter(axes, workspace, *args, **kwargs):
'''
Unpack mantid workspace and render it with matplotlib. ``args`` and
``kwargs`` are passed to :py:meth:`matplotlib.axes.Axes.scatter` after special
keyword arguments are removed. This will automatically label the
line according to the spectrum number unless specified otherwise.
:param axes: :class:`matplotlib.axes.Axes` object that will do the plotting
:param workspace: :class:`mantid.api.MatrixWorkspace` or :class:`mantid.api.IMDHistoWorkspace`
to extract the data from
:param specNum: spectrum number to plot if MatrixWorkspace
:param wkspIndex: workspace index to plot if MatrixWorkspace
:param distribution: ``None`` (default) asks the workspace. ``False`` means
divide by bin width. ``True`` means do not divide by bin width.
Applies only when the the workspace is a MatrixWorkspace histogram.
:param normalization: ``None`` (default) ask the workspace. Applies to MDHisto workspaces. It can override
the value from displayNormalizationHisto. It checks only if
the normalization is mantid.api.MDNormalization.NumEventsNormalization
For matrix workspaces with more than one spectra, either ``specNum`` or ``wkspIndex``
needs to be specified. Giving both will generate a :class:`RuntimeError`. There is no similar
keyword for MDHistoWorkspaces. These type of workspaces have to have exactly one non integrated
dimension
'''
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
(x, y, _) = get_md_data1d(workspace, normalization)
else:
(wkspIndex, distribution,
kwargs) = get_wksp_index_dist_and_label(workspace, **kwargs)
(x, y, _, _) = get_spectrum(workspace, wkspIndex, distribution)
_setLabels1D(axes, workspace)
return axes.scatter(x, y, *args, **kwargs)
def _get_data_for_plot(axes, workspace, kwargs, with_dy=False, with_dx=False):
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
(x, y, dy) = get_md_data1d(workspace, normalization, indices)
dx = None
axis = None
else:
axis = MantidAxType(kwargs.pop("axis", MantidAxType.SPECTRUM))
normalize_by_bin_width, kwargs = get_normalize_by_bin_width(
workspace, axes, **kwargs)
workspace_index, distribution, kwargs = get_wksp_index_dist_and_label(
workspace, axis, **kwargs)
if axis == MantidAxType.BIN:
# Overwrite any user specified xlabel
axes.set_xlabel("Spectrum")
x, y, dy, dx = get_bins(workspace, workspace_index, with_dy)
elif axis == MantidAxType.SPECTRUM:
x, y, dy, dx = get_spectrum(workspace, workspace_index,
normalize_by_bin_width, with_dy,
with_dx)
else:
raise ValueError(
"Axis {} is not a valid axis number.".format(axis))
indices = None
return x, y, dy, dx, indices, axis, kwargs
def test_get_spectrum_with_dy_dx(self, ws):
x, y, dy, dx = funcs.get_spectrum(ws, 3, distribution=False, withDy=True, withDx=True)
self.assertTrue(np.array_equal([13.5, 14.5, 15.5], x))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], y))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], dy))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], dx))
def test_get_spectrum_with_dy_dx(self, ws):
x, y, dy, dx = funcs.get_spectrum(ws, 3, distribution=False, withDy=True, withDx=True)
self.assertTrue(np.array_equal([13.5, 14.5, 15.5], x))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], y))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], dy))
self.assertTrue(np.array_equal([10.0, 11.0, 12.0], dx))
def plot(axes, workspace, *args, **kwargs):
'''
3D plots - line plots
:param axes: class:`matplotlib.axes.Axes3D` object that will do the plotting
:param workspace: :class:`mantid.api.MatrixWorkspace` or
:class:`mantid.api.IMDHistoWorkspace` to extract the data from
:param zdir: Which direction to use as z ('x', 'y' or 'z') when plotting a 2D set.
:param indices: Specify which slice of an MDHistoWorkspace to use when plotting. Needs to be a tuple
and will be interpreted as a list of indices. You need to use ``slice(None)`` to
select which dimension to plot. *e.g.* to select the second axis to plot from a
3D volume use ``indices=(5, slice(None), 10)`` where the 5/10 are the bins selected
for the other 2 axes.
:param slicepoint: Specify which slice of an MDHistoWorkspace to use when plotting in the dimension units.
You need to use ``None`` to select which dimension to plot. *e.g.* to select the second
axis to plot from a 3D volume use ``slicepoint=(1.0, None, 2.0)`` where the 1.0/2.0 are
the dimension selected for the other 2 axes.
'''
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
(x, y, z) = get_md_data1d(workspace, normalization, indices)
else:
(wksp_index, distribution,
kwargs) = get_wksp_index_dist_and_label(workspace, **kwargs)
(x, z, _, _) = get_spectrum(workspace,
wksp_index,
distribution,
withDy=False,
withDx=False)
y_val = workspace.getAxis(1).extractValues()[wksp_index]
y = [y_val for _ in range(len(x))] # fill x size array with y value
_set_labels_3d(axes, workspace)
return axes.plot(x, y, z, *args, **kwargs)
def test_get_spectrum_non_distribution_workspace(self):
# get data divided by bin width
x, y, dy, dx = funcs.get_spectrum(self.ws2d_non_distribution, 1,
normalize_by_bin_width=True,
withDy=True, withDx=True)
self.assertTrue(np.array_equal(x, np.array([15., 25.])))
self.assertTrue(np.array_equal(y, np.array([0.4, 0.5])))
self.assertTrue(np.array_equal(dy, np.array([0.3, 0.4])))
self.assertEqual(dx, None)
# get data not divided by bin width
x, y, dy, dx = funcs.get_spectrum(self.ws2d_non_distribution, 1,
normalize_by_bin_width=False,
withDy=True, withDx=True)
self.assertTrue(np.array_equal(x, np.array([15., 25.])))
self.assertTrue(np.array_equal(y, np.array([4, 5])))
self.assertTrue(np.array_equal(dy, np.array([3, 4])))
self.assertEqual(dx, None)
# fail case - try to find spectrum out of range
self.assertRaises(RuntimeError, funcs.get_spectrum,
self.ws2d_non_distribution, 10, True)
def scatter(axes, workspace, *args, **kwargs):
'''
Unpack mantid workspace and render it with matplotlib. ``args`` and
``kwargs`` are passed to :py:meth:`matplotlib.axes.Axes.scatter` after special
keyword arguments are removed. This will automatically label the
line according to the spectrum number unless specified otherwise.
:param axes: :class:`matplotlib.axes.Axes` object that will do the plotting
:param workspace: :class:`mantid.api.MatrixWorkspace` or :class:`mantid.api.IMDHistoWorkspace`
to extract the data from
:param specNum: spectrum number to plot if MatrixWorkspace
:param wkspIndex: workspace index to plot if MatrixWorkspace
:param distribution: ``None`` (default) asks the workspace. ``False`` means
divide by bin width. ``True`` means do not divide by bin width.
Applies only when the the workspace is a MatrixWorkspace histogram.
:param normalization: ``None`` (default) ask the workspace. Applies to MDHisto workspaces. It can override
the value from displayNormalizationHisto. It checks only if
the normalization is mantid.api.MDNormalization.NumEventsNormalization
:param indices: Specify which slice of an MDHistoWorkspace to use when plotting. Needs to be a tuple
and will be interpreted as a list of indices. You need to use ``slice(None)`` to
select which dimension to plot. *e.g.* to select the second axis to plot from a
3D volume use ``indices=(5, slice(None), 10)`` where the 5/10 are the bins selected
for the other 2 axes.
:param slicepoint: Specify which slice of an MDHistoWorkspace to use when plotting in the dimension units.
You need to use ``None`` to select which dimension to plot. *e.g.* to select the second
axis to plot from a 3D volume use ``slicepoint=(1.0, None, 2.0)`` where the 1.0/2.0 are
the dimension selected for the other 2 axes.
For matrix workspaces with more than one spectra, either ``specNum`` or ``wkspIndex``
needs to be specified. Giving both will generate a :class:`RuntimeError`. There is no similar
keyword for MDHistoWorkspaces. These type of workspaces have to have exactly one non integrated
dimension
'''
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
(x, y, _) = get_md_data1d(workspace, normalization, indices)
_setLabels1D(axes, workspace, indices)
else:
(wkspIndex, distribution,
kwargs) = get_wksp_index_dist_and_label(workspace, **kwargs)
(x, y, _, _) = get_spectrum(workspace, wkspIndex, distribution)
_setLabels1D(axes, workspace)
return axes.scatter(x, y, *args, **kwargs)
def plot(axes, workspace, *args, **kwargs):
'''
3D plots - line plots
:param axes: class:`matplotlib.axes.Axes3D` object that will do the plotting
:param workspace: :class:`mantid.api.MatrixWorkspace` or
:class:`mantid.api.IMDHistoWorkspace` to extract the data from
:param zdir: Which direction to use as z ('x', 'y' or 'z') when plotting a 2D set.
'''
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
(x, y, z) = get_md_data1d(workspace, normalization)
else:
(wksp_index, distribution, kwargs) = get_wksp_index_dist_and_label(workspace, **kwargs)
(x, z, _, _) = get_spectrum(workspace, wksp_index, distribution, withDy=False, withDx=False)
y_val = workspace.getAxis(1).extractValues()[wksp_index]
y = [y_val for _ in range(len(x))] # fill x size array with y value
_set_labels_3d(axes, workspace)
return axes.plot(x, y, z, *args, **kwargs)
def _get_data_for_plot(axes, workspace, kwargs, with_dy=False, with_dx=False):
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
(x, y, dy) = get_md_data1d(workspace, normalization, indices)
dx = None
else:
axis = kwargs.pop("axis", MantidAxType.SPECTRUM)
workspace_index, distribution, kwargs = get_wksp_index_dist_and_label(workspace, axis, **kwargs)
if axis == MantidAxType.BIN:
# Overwrite any user specified xlabel
axes.set_xlabel("Spectrum")
x, y, dy, dx = get_bins(workspace, workspace_index, with_dy)
elif axis == MantidAxType.SPECTRUM:
x, y, dy, dx = get_spectrum(workspace, workspace_index, distribution, with_dy, with_dx)
else:
raise ValueError("Axis {} is not a valid axis number.".format(axis))
indices = None
return x, y, dy, dx, indices, kwargs
def scatter(axes, workspace, *args, **kwargs):
'''
Unpack mantid workspace and render it with matplotlib. ``args`` and
``kwargs`` are passed to :py:meth:`matplotlib.axes.Axes.scatter` after special
keyword arguments are removed. This will automatically label the
line according to the spectrum number unless specified otherwise.
:param axes: :class:`matplotlib.axes.Axes` object that will do the plotting
:param workspace: :class:`mantid.api.MatrixWorkspace` or :class:`mantid.api.IMDHistoWorkspace`
to extract the data from
:param specNum: spectrum number to plot if MatrixWorkspace
:param wkspIndex: workspace index to plot if MatrixWorkspace
:param distribution: ``None`` (default) asks the workspace. ``False`` means
divide by bin width. ``True`` means do not divide by bin width.
Applies only when the the workspace is a MatrixWorkspace histogram.
:param normalization: ``None`` (default) ask the workspace. Applies to MDHisto workspaces. It can override
the value from displayNormalizationHisto. It checks only if
the normalization is mantid.api.MDNormalization.NumEventsNormalization
:param indices: Specify which slice of an MDHistoWorkspace to use when plotting. Needs to be a tuple
and will be interpreted as a list of indices. You need to use ``slice(None)`` to
select which dimension to plot. *e.g.* to select the second axis to plot from a
3D volume use ``indices=(5, slice(None), 10)`` where the 5/10 are the bins selected
for the other 2 axes.
:param slicepoint: Specify which slice of an MDHistoWorkspace to use when plotting in the dimension units.
You need to use ``None`` to select which dimension to plot. *e.g.* to select the second
axis to plot from a 3D volume use ``slicepoint=(1.0, None, 2.0)`` where the 1.0/2.0 are
the dimension selected for the other 2 axes.
For matrix workspaces with more than one spectra, either ``specNum`` or ``wkspIndex``
needs to be specified. Giving both will generate a :class:`RuntimeError`. There is no similar
keyword for MDHistoWorkspaces. These type of workspaces have to have exactly one non integrated
dimension
'''
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
(x, y, _) = get_md_data1d(workspace, normalization, indices)
_setLabels1D(axes, workspace, indices)
else:
(wkspIndex, distribution, kwargs) = get_wksp_index_dist_and_label(workspace, **kwargs)
(x, y, _, _) = get_spectrum(workspace, wkspIndex, distribution)
_setLabels1D(axes, workspace)
return axes.scatter(x, y, *args, **kwargs)
def plot(axes, workspace, *args, **kwargs):
'''
3D plots - line plots
:param axes: class:`matplotlib.axes.Axes3D` object that will do the plotting
:param workspace: :class:`mantid.api.MatrixWorkspace` or
:class:`mantid.api.IMDHistoWorkspace` to extract the data from
:param zdir: Which direction to use as z ('x', 'y' or 'z') when plotting a 2D set.
'''
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
(x, y, z) = get_md_data1d(workspace, normalization)
else:
(wksp_index, distribution,
kwargs) = get_wksp_index_dist_and_label(workspace, **kwargs)
(x, z, _, _) = get_spectrum(workspace,
wksp_index,
distribution,
withDy=False,
withDx=False)
y_val = workspace.getAxis(1).extractValues()[wksp_index]
y = [y_val for _ in range(len(x))] # fill x size array with y value
_set_labels_3d(axes, workspace)
return axes.plot(x, y, z, *args, **kwargs)
