def _plot_on_here(self, names, ax):
"""
Assume the list of strings refer to workspace names and they are to be plotted
on this figure. If the current figure contains an image plot then
a new image plot will replace the current image. If the current figure
contains a line plot then the user will be asked what should be plotted and this
will overplot onto the figure. If the first line of the plot
:param names: A list of workspace names
:param ax: The matplotlib axes object to overplot onto
"""
if len(names) == 0:
return
# local import to avoid circular import with FigureManager
from mantidqt.plotting.functions import pcolormesh, plot_from_names, plot_surface, plot_wireframe, plot_contour
fig = self._canvas.figure
fig_type = figure_type(fig, ax)
if fig_type == FigureType.Image:
pcolormesh(names, fig=fig)
elif fig_type == FigureType.Surface:
plot_surface(names, fig=fig)
elif fig_type == FigureType.Wireframe:
plot_wireframe(names, fig=fig)
elif fig_type == FigureType.Contour:
plot_contour(names, fig=fig)
else:
plot_from_names(names, errors=(fig_type == FigureType.Errorbar),
overplot=ax, fig=fig)
def test_hidden_fit_for_images(self):
if 'ws1' in mtd:
ws1 = mtd['ws1']
else:
ws1 = Load(r'emu00006473.nxs', OutputWorkspace='ws1')[0]
pcolormesh([ws1])
manager = GlobalFigureManager.get_active()
action = manager.toolbar._actions['toggle_fit']
self.assertFalse(action.isVisible())
self.assertFalse(action.isEnabled())
def _do_plot_colorfill(self, names):
"""
Plot a colorfill from the selected workspaces
:param names: A list of workspace names
"""
try:
pcolormesh(self._ads.retrieveWorkspaces(names, unrollGroups=True))
except BaseException:
import traceback
traceback.print_exc()
def _do_plot_colorfill(self, names):
"""
Plot a colorfill from the selected workspaces
:param names: A list of workspace names
"""
try:
pcolormesh(self._ads.retrieveWorkspaces(names, unrollGroups=True))
except BaseException:
import traceback
traceback.print_exc()
def plotForce(inWS, Plot):
if Plot == 'Spectrum' or Plot == 'Both':
nHist = mtd[inWS].getNumberHistograms()
if nHist > 10:
nHist = 10
plot_list = []
for i in range(0, nHist):
plot_list.append(i)
plotSpectrum(inWS, plot_list)
if Plot == 'Contour' or Plot == 'Both':
pcolormesh(inWS)
def _do_plot_colorfill(self, names):
"""
Plot a colorfill from the selected workspaces
:param names: A list of workspace names
:param contour: An optional bool for whether to draw contour lines.
"""
try:
pcolormesh(names)
except BaseException:
import traceback
traceback.print_exc()
def test_apply_properties_applies_to_all_images_if_multiple_colorfill_plots_and_one_colorbar(
self):
fig = pcolormesh([self.ws, self.ws])
props = {
'label': 'New Label',
'colormap': 'jet',
'vmin': 0,
'vmax': 2,
'scale': 'Linear',
'interpolation': 'None'
}
if LooseVersion(matplotlib.__version__) > LooseVersion("3.1.3"):
mock_view = Mock(
get_selected_image_name=lambda: 'ws: (0, 0) - child0',
get_properties=lambda: ImageProperties(props))
else:
mock_view = Mock(
get_selected_image_name=lambda: 'ws: (0, 0) - image0',
get_properties=lambda: ImageProperties(props))
presenter = self._generate_presenter(fig=fig, view=mock_view)
presenter.apply_properties()
for ax in range(2):
image = fig.axes[ax].images[0]
if image.colorbar:
self.assertEqual('New Label', image.colorbar.ax.get_ylabel())
self.assertEqual('jet', image.cmap.name)
self.assertEqual(0, image.norm.vmin)
self.assertEqual(2, image.norm.vmax)
self.assertTrue(isinstance(image.norm, Normalize))
def plot(plot_type: SpectraSelection, plot_index: int, axis_name: str,
log_name: str, custom_log_values: List[float],
workspaces: List[Workspace]) -> None:
if len(workspaces) > 0:
matrix_ws = _create_workspace_for_group_plot(plot_type, workspaces,
plot_index, log_name,
custom_log_values)
workspace_names = [ws.name() for ws in workspaces]
title = _construct_title(workspace_names, plot_index)
if plot_type == SpectraSelection.Surface:
fig, ax = plt.subplots(subplot_kw={'projection': 'mantid3d'})
surface = ax.plot_surface(matrix_ws, cmap='viridis')
ax.set_title("Surface" + title)
ax.set_ylabel(axis_name)
fig.canvas.set_window_title("Surface" + title)
fig.colorbar(surface)
fig.show()
elif plot_type == SpectraSelection.Contour:
fig = pcolormesh([matrix_ws])
ax = fig.get_axes()[0]
ax.contour(matrix_ws, levels=2, colors='k', linewidths=0.5)
ax.set_ylabel(axis_name)
ax.set_title("Contour" + title)
fig.canvas.set_window_title("Contour" + title)
def plot_reduction(workspace_name, plot_type):
"""
Plot a given workspace based on the Plot property.
@param workspace_name Name of workspace to plot
@param plot_type Type of plot to create
"""
if plot_type == 'Spectra' or plot_type == 'Both':
num_spectra = mtd[workspace_name].getNumberHistograms()
try:
plotSpectrum(workspace_name, range(0, num_spectra))
except RuntimeError:
logger.notice('Spectrum plotting canceled by user')
can_plot_contour = mtd[workspace_name].getNumberHistograms() > 1
if (plot_type == 'Contour' or plot_type == 'Both') and can_plot_contour:
from mantidqt.plotting.functions import pcolormesh
pcolormesh(workspace_name)
def test_toggle_normalisation_applies_to_all_images_if_one_colorbar(self):
fig = pcolormesh([self.ws, self.ws])
mock_canvas = MagicMock(figure=fig)
fig_manager_mock = MagicMock(canvas=mock_canvas)
fig_interactor = FigureInteraction(fig_manager_mock)
# there should be 3 axes, 2 colorplots and 1 colorbar
self.assertEqual(3, len(fig.axes))
fig.axes[0].tracked_workspaces.values()
self.assertTrue(fig.axes[0].tracked_workspaces['ws'][0].is_normalized)
self.assertTrue(fig.axes[1].tracked_workspaces['ws'][0].is_normalized)
fig_interactor._toggle_normalization(fig.axes[0])
self.assertFalse(fig.axes[0].tracked_workspaces['ws'][0].is_normalized)
self.assertFalse(fig.axes[1].tracked_workspaces['ws'][0].is_normalized)
def test_apply_properties_applies_to_all_images_if_mixed_colorfill_plots_and_one_colorbar(
self):
# self.ws does not have common bins and has evenly spaced values on spectrum axis (gives Image)
# Also create ws with common bins, evenly spaced bin edges and uneven values on spectrum axis (gives QuadMesh)
ws = CreateWorkspace(DataX=list([0, 1, 2, 3, 4]) * 4,
DataY=range(20),
NSpec=4,
OutputWorkspace='test_ws',
VerticalAxisUnit='TOF',
VerticalAxisValues=[1, 2, 4, 10])
fig = pcolormesh([self.ws, ws])
self.assertTrue(
isinstance(fig.axes[0].images[0], matplotlib.image.AxesImage))
self.assertTrue(
isinstance(fig.axes[1].collections[0],
matplotlib.collections.QuadMesh))
props = {
'label': 'New Label',
'colormap': 'jet',
'vmin': 0,
'vmax': 2,
'scale': 'Linear',
'interpolation': 'None'
}
if LooseVersion(matplotlib.__version__) > LooseVersion("3.1.3"):
mock_view = Mock(
get_selected_image_name=lambda: 'ws: (0, 0) - child0',
get_properties=lambda: ImageProperties(props))
else:
mock_view = Mock(
get_selected_image_name=lambda: 'ws: (0, 0) - image0',
get_properties=lambda: ImageProperties(props))
presenter = self._generate_presenter(fig=fig, view=mock_view)
presenter.apply_properties()
images = datafunctions.get_images_from_figure(fig)
for image in images:
if image.colorbar:
self.assertEqual('New Label', image.colorbar.ax.get_ylabel())
self.assertEqual('jet', image.cmap.name)
self.assertEqual(0, image.norm.vmin)
self.assertEqual(2, image.norm.vmax)
self.assertTrue(isinstance(image.norm, Normalize))
def test_changes_apply_to_all_colorfill_plots_if_one_colorbar(self):
ws = WorkspaceFactory.Instance().create("Workspace2D", NVectors=1, YLength=5, XLength=5)
fig = pcolormesh([ws, ws])
# there should be 3 axes: 2 colorfill plots and 1 colorbar
self.assertEqual(3, len(fig.axes))
colorbarEditor = ColorbarAxisEditor(fig.canvas, fig.axes[2])
min_value = 1.0
max_value = 2.0
colorbarEditor.ui.editor_min.text = MagicMock(return_value=min_value)
colorbarEditor.ui.editor_max.text = MagicMock(return_value=max_value)
colorbarEditor.ui.logBox.isChecked = MagicMock(return_value=True)
colorbarEditor.changes_accepted()
for ax in range(2):
self.assertEqual(min_value, fig.axes[ax].collections[0].norm.vmin)
self.assertEqual(max_value, fig.axes[ax].collections[0].norm.vmax)
self.assertTrue(isinstance(fig.axes[ax].collections[0].norm, LogNorm))
def plotMuscat(inWS, spec_list, Plot):
if Plot == 'Totals' or Plot == 'All':
plotSpectrum(inWS + '_Totals', spec_list)
if Plot == 'Scat1' or Plot == 'All':
pcolormesh(inWS + '_1')
