def _pcolormesh_nonortho(axes, workspace, to_display, *args, **kwargs):
'''
Essentially the same as :meth:`matplotlib.axes.Axes.pcolormesh` and adds arguments related to
plotting slices on nonorthogonal axes. It requires a non-standard Axes type. See
https://matplotlib.org/examples/axes_grid/demo_curvelinear_grid.html.
NOTE: Do NOT make this part of the public API until a discussion has been had about whether this
api is sensible. It is placed here for testing purposes and is used in the sliceviewer.
: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 to_display: Callable accepting two numpy arrays to transfrom from nonorthogonal
coordinates to orthogonal display
:param transpose: ``bool`` to transpose the x and y axes of the plotted dimensions of an MDHistoWorkspace
'''
transpose = kwargs.pop('transpose', False)
(normalization, kwargs) = get_normalization(workspace, **kwargs)
indices, kwargs = get_indices(workspace, **kwargs)
x, y, z = get_md_data2d_bin_bounds(workspace,
indices=indices,
normalization=normalization,
transpose=transpose)
X, Y = numpy.meshgrid(x, y)
xx, yy = to_display(X, Y)
_setLabels2D(axes, workspace, indices, transpose)
return axes.pcolormesh(xx, yy, 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:
(aligned, kwargs) = check_resample_to_regular_grid(workspace, **kwargs)
(normalize_by_bin_width,
kwargs) = get_normalize_by_bin_width(workspace, axes, **kwargs)
(distribution, kwargs) = get_distribution(workspace, **kwargs)
if aligned:
(x, y, z) = get_matrix_2d_ragged(workspace,
normalize_by_bin_width,
histogram2D=True,
transpose=transpose)
else:
(x, y, z) = get_matrix_2d_data(workspace,
distribution=distribution,
histogram2D=True,
transpose=transpose)
_setLabels2D(axes,
workspace,
transpose=transpose,
normalize_by_bin_width=normalize_by_bin_width)
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 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)