def imshow(axes, workspace, *args, **kwargs):
'''
Essentially the same as :meth:`matplotlib.axes.Axes.imshow`.
: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 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 matrix workspace is a 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 axisaligned: ``False`` (default). If ``True``, or if the workspace has a variable
number of bins, the polygons will be aligned with the axes
'''
_setLabels2D(axes, workspace)
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
x, y, z = get_md_data2d_bin_bounds(workspace, normalization)
else:
(uneven_bins, kwargs) = get_data_uneven_flag(workspace, **kwargs)
(distribution, kwargs) = get_distribution(workspace, **kwargs)
if check_resample_to_regular_grid(workspace):
(x, y, z) = get_matrix_2d_ragged(workspace, distribution, histogram2D=True)
else:
(x, y, z) = get_matrix_2d_data(workspace, distribution, histogram2D=True)
if 'extent' not in kwargs:
if x.ndim == 2 and y.ndim == 2:
kwargs['extent'] = [x[0, 0], x[0, -1], y[0, 0], y[-1, 0]]
else:
kwargs['extent'] = [x[0], x[-1], y[0], y[-1]]
return mantid.plots.modest_image.imshow(axes, z, *args, **kwargs)
def pcolormesh(axes, workspace, *args, **kwargs):
'''
Essentially the same as :meth:`matplotlib.axes.Axes.pcolormesh`.
: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 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 matrix workspace is a 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 axisaligned: ``False`` (default). If ``True``, or if the workspace has a variable
number of bins, the polygons will be aligned with the axes
'''
_setLabels2D(axes, workspace)
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
x, y, z = get_md_data2d_bin_bounds(workspace, normalization)
else:
(aligned, kwargs) = get_data_uneven_flag(workspace, **kwargs)
(distribution, kwargs) = get_distribution(workspace, **kwargs)
if aligned:
kwargs['pcolortype'] = 'mesh'
return _pcolorpieces(axes, workspace, distribution, *args,
**kwargs)
else:
(x, y, z) = get_matrix_2d_data(workspace,
distribution,
histogram2D=True)
return axes.pcolormesh(x, y, z, *args, **kwargs)
def imshow(axes, workspace, *args, **kwargs):
'''
Essentially the same as :meth:`matplotlib.axes.Axes.imshow`.
: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 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 matrix workspace is a 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 dimensions to plot. *e.g.* to select the last two axes to plot from a
3D volume use ``indices=(5, slice(None), slice(None))`` where the 5 is the bin selected
for the first axis.
: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 last
two axes to plot from a 3D volume use ``slicepoint=(1.0, None, None)`` where the 1.0 is
the value of the dimension selected for the first axis.
:param axisaligned: ``False`` (default). If ``True``, or if the workspace has a variable
number of bins, the polygons will be aligned with the axes
:param transpose: ``bool`` to transpose the x and y axes of the plotted dimensions of an MDHistoWorkspace
'''
transpose = kwargs.pop('transpose', False)
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
x, y, z = get_md_data2d_bin_bounds(workspace, normalization, indices,
transpose)
_setLabels2D(axes, workspace, indices, transpose)
else:
(uneven_bins, kwargs) = get_data_uneven_flag(workspace, **kwargs)
(distribution, kwargs) = get_distribution(workspace, **kwargs)
if check_resample_to_regular_grid(workspace):
(x, y, z) = get_matrix_2d_ragged(workspace,
distribution,
histogram2D=True,
transpose=transpose)
else:
(x, y, z) = get_matrix_2d_data(workspace,
distribution,
histogram2D=True,
transpose=transpose)
_setLabels2D(axes, workspace, transpose=transpose)
if 'extent' not in kwargs:
if x.ndim == 2 and y.ndim == 2:
kwargs['extent'] = [x[0, 0], x[0, -1], y[0, 0], y[-1, 0]]
else:
kwargs['extent'] = [x[0], x[-1], y[0], y[-1]]
return mantid.plots.modest_image.imshow(axes, z, *args, **kwargs)
def test_get_md_data2d_bin_bounds(self):
x, y, data = funcs.get_md_data2d_bin_bounds(
self.ws_MD_2d, mantid.api.MDNormalization.NoNormalization)
# logger.error(str(coords))
np.testing.assert_allclose(x,
np.array([-3, -1.8, -0.6, 0.6, 1.8, 3]),
atol=1e-10)
np.testing.assert_allclose(y,
np.array([-10, -6, -2, 2, 6, 10.]),
atol=1e-10)
np.testing.assert_allclose(data,
np.arange(25).reshape(5, 5),
atol=1e-10)
def imshow(axes, workspace, *args, **kwargs):
'''
Essentially the same as :meth:`matplotlib.axes.Axes.imshow`.
: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 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 matrix workspace is a 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 dimensions to plot. *e.g.* to select the last two axes to plot from a
3D volume use ``indices=(5, slice(None), slice(None))`` where the 5 is the bin selected
for the first axis.
: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 last
two axes to plot from a 3D volume use ``slicepoint=(1.0, None, None)`` where the 1.0 is
the value of the dimension selected for the first axis.
:param axisaligned: ``False`` (default). If ``True``, or if the workspace has a variable
number of bins, the polygons will be aligned with the axes
:param transpose: ``bool`` to transpose the x and y axes of the plotted dimensions of an MDHistoWorkspace
'''
transpose = kwargs.pop('transpose', False)
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
x, y, z = get_md_data2d_bin_bounds(workspace, normalization, indices, transpose)
_setLabels2D(axes, workspace, indices, transpose)
else:
(uneven_bins, kwargs) = get_data_uneven_flag(workspace, **kwargs)
(distribution, kwargs) = get_distribution(workspace, **kwargs)
if check_resample_to_regular_grid(workspace):
(x, y, z) = get_matrix_2d_ragged(workspace, distribution, histogram2D=True, transpose=transpose)
else:
(x, y, z) = get_matrix_2d_data(workspace, distribution, histogram2D=True, transpose=transpose)
_setLabels2D(axes, workspace, transpose=transpose)
if 'extent' not in kwargs:
if x.ndim == 2 and y.ndim == 2:
kwargs['extent'] = [x[0, 0], x[0, -1], y[0, 0], y[-1, 0]]
else:
kwargs['extent'] = [x[0], x[-1], y[0], y[-1]]
return mantid.plots.modest_image.imshow(axes, z, *args, **kwargs)
def imshow(axes, workspace, *args, **kwargs):
'''
Essentially the same as :meth:`matplotlib.axes.Axes.imshow`.
: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 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 matrix workspace is a 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 axisaligned: ``False`` (default). If ``True``, or if the workspace has a variable
number of bins, the polygons will be aligned with the axes
'''
_setLabels2D(axes, workspace)
if isinstance(workspace, mantid.dataobjects.MDHistoWorkspace):
(normalization, kwargs) = get_normalization(workspace, **kwargs)
x, y, z = get_md_data2d_bin_bounds(workspace, normalization)
else:
(uneven_bins, kwargs) = get_data_uneven_flag(workspace, **kwargs)
(distribution, kwargs) = get_distribution(workspace, **kwargs)
if uneven_bins:
raise Exception(
'Variable number of bins is not supported by imshow.')
else:
(x, y, z) = get_matrix_2d_data(workspace,
distribution,
histogram2D=True)
diffs = numpy.diff(x, axis=1)
x_spacing_equal = numpy.alltrue(diffs == diffs[0])
diffs = numpy.diff(y, axis=0)
y_spacing_equal = numpy.alltrue(diffs == diffs[0])
if not x_spacing_equal or not y_spacing_equal:
raise Exception('Unevenly spaced bins are not supported by imshow')
if 'extent' not in kwargs:
kwargs['extent'] = [x[0, 0], x[0, -1], y[0, 0], y[-1, 0]]
return _imshow(axes, z, *args, **kwargs)
def test_get_md_data2d_bin_bounds_indices2(self, mdws):
x, y, z = funcs.get_md_data2d_bin_bounds(mdws, False,
(slice(None), 0, slice(None)))
np.testing.assert_allclose(np.arange(-3, 3.6, 0.6), x, atol=1e-14)
np.testing.assert_allclose(range(-20, 24, 4), y)
def test_get_md_data2d_bin_bounds_indices(self, mdws):
x, y, z = funcs.get_md_data2d_bin_bounds(mdws, False,
(0, slice(None), slice(None)))
np.testing.assert_allclose(range(-10, 12, 2), x)
np.testing.assert_allclose(range(-20, 24, 4), y)
def test_get_md_data2d_bin_bounds(self):
x, y, data = funcs.get_md_data2d_bin_bounds(self.ws_MD_2d, mantid.api.MDNormalization.NoNormalization)
# logger.error(str(coords))
np.testing.assert_allclose(x, np.array([-3, -1.8, -0.6, 0.6, 1.8, 3]), atol=1e-10)
np.testing.assert_allclose(y, np.array([-10, -6, -2, 2, 6, 10.]), atol=1e-10)
np.testing.assert_allclose(data, np.arange(25).reshape(5, 5), atol=1e-10)
def test_get_md_data2d_bin_bounds_indices2(self, mdws):
x, y, z = funcs.get_md_data2d_bin_bounds(mdws, False, (slice(None),0,slice(None)))
np.testing.assert_allclose(np.arange(-3,3.6,0.6), x, atol=1e-14)
np.testing.assert_allclose(range(-20,24,4), y)
def test_get_md_data2d_bin_bounds_indices(self, mdws):
x, y, z = funcs.get_md_data2d_bin_bounds(mdws, False, (0,slice(None),slice(None)))
np.testing.assert_allclose(range(-10,12,2), x)
np.testing.assert_allclose(range(-20,24,4), y)
