def errorbar(axes, workspace, *args, **kwargs):
"""
Same as the cli PlotCut but returns the relevant axes object.
"""
from mslice.app.presenters import get_cut_plotter_presenter
cur_fig = plt.gcf()
cur_canvas = cur_fig.canvas
_check_workspace_name(workspace)
workspace = get_workspace_handle(workspace)
if not isinstance(workspace, HistogramWorkspace):
raise RuntimeError("Incorrect workspace type.")
presenter = get_cut_plotter_presenter()
plot_over = kwargs.pop('plot_over', True)
intensity_range = kwargs.pop('intensity_range', (None, None))
label = kwargs.pop('label', None)
label = workspace.name if label is None else label
en_conversion_allowed = kwargs.pop('en_conversion', True)
cut_axis, int_axis = tuple(workspace.axes)
# Checks that current cut has consistent units with previous
if plot_over:
cached_cuts = presenter.get_cache(axes)
if cached_cuts:
if (cut_axis.units != cached_cuts[0].cut_axis.units):
raise RuntimeError('Cut axes not consistent with current plot. '
'Expected {}, got {}'.format(cached_cuts[0].cut_axis.units, cut_axis.units))
# Checks whether we should do an energy unit conversion
if 'DeltaE' in cut_axis.units and cut_axis.e_unit != cached_cuts[0].cut_axis.e_unit:
if en_conversion_allowed:
_rescale_energy_cut_plot(presenter, cached_cuts, cut_axis.e_unit)
else:
raise RuntimeError('Wrong energy unit for cut. '
'Expected {}, got {}'.format(cached_cuts[0].cut_axis.e_unit, cut_axis.e_unit))
plotfunctions.errorbar(axes, workspace.raw_ws, label=label, *args, **kwargs)
axes.set_ylim(*intensity_range) if intensity_range is not None else axes.autoscale()
intensity_min, intensity_max = axes.get_ylim()
if cur_canvas.manager.window.action_toggle_legends.isChecked():
leg = axes.legend(fontsize='medium')
leg.draggable()
axes.set_xlabel(get_display_name(cut_axis), picker=CUT_PICKER_TOL_PTS)
axes.set_ylabel(CUT_INTENSITY_LABEL, picker=CUT_PICKER_TOL_PTS)
if not plot_over:
cur_canvas.set_window_title(workspace.name)
cur_canvas.manager.update_grid()
if not cur_canvas.manager.has_plot_handler():
cur_canvas.manager.add_cut_plot(presenter, workspace.name)
cur_fig.canvas.draw()
axes.pchanged() # This call is to let the waterfall callback know to update
cut = Cut(cut_axis, int_axis, intensity_min, intensity_max, workspace.norm_to_one, width='')
cut.workspace_name = workspace.parent
presenter.save_cache(axes, cut, plot_over)
return axes.lines
def _data_update(artists, workspace):
# errorbar with workspaces can only return a single container
container_orig = artists[0]
# It is not possible to simply reset the error bars so
# we have to plot new lines but ensure we don't reorder them on the plot!
orig_idx = self.containers.index(container_orig)
container_orig.remove()
# The container does not remove itself from the containers list
# but protect this just in case matplotlib starts doing this
try:
self.containers.remove(container_orig)
except ValueError:
pass
# this gets pushed back onto the containers list
container_new = plotfunctions.errorbar(self, workspace, **kwargs)
self.containers.insert(orig_idx, container_new)
self.containers.pop()
# update line properties to match original
orig_flat, new_flat = cbook.flatten(container_orig), cbook.flatten(container_new)
for artist_orig, artist_new in zip(orig_flat, new_flat):
artist_new.update_from(artist_orig)
# ax.relim does not support collections...
self._update_line_limits(container_new[0])
self.autoscale()
return container_new
def _data_update(artists, workspace):
# errorbar with workspaces can only return a single container
container_orig = artists[0]
# It is not possible to simply reset the error bars so
# we have to plot new lines but ensure we don't reorder them on the plot!
orig_idx = self.containers.index(container_orig)
container_orig.remove()
# The container does not remove itself from the containers list
# but protect this just in case matplotlib starts doing this
try:
self.containers.remove(container_orig)
except ValueError:
pass
# this gets pushed back onto the containers list
container_new = plotfunctions.errorbar(self, workspace,
**kwargs)
self.containers.insert(orig_idx, container_new)
self.containers.pop()
# update line properties to match original
orig_flat, new_flat = cbook.flatten(
container_orig), cbook.flatten(container_new)
for artist_orig, artist_new in zip(orig_flat, new_flat):
artist_new.update_from(artist_orig)
# ax.relim does not support collections...
self._update_line_limits(container_new[0])
self.autoscale()
return container_new
def errorbar(self, *args, **kwargs):
"""
If the **mantid** projection is chosen, it can be
used the same as :py:meth:`matplotlib.axes.Axes.errorbar` for arrays,
or it can be used to plot :class:`mantid.api.MatrixWorkspace`
or :class:`mantid.api.IMDHistoWorkspace`. You can have something like::
import matplotlib.pyplot as plt
from mantid import plots
...
fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})
ax.errorbar(workspace,'rs',specNum=1) #for workspaces
ax.errorbar(x,y,yerr,'bo') #for arrays
fig.show()
For keywords related to workspaces, see :func:`plotfunctions.errorbar`
"""
if helperfunctions.validate_args(*args):
logger.debug('using plotfunctions')
def _data_update(artists, workspace):
# errorbar with workspaces can only return a single container
container_orig = artists[0]
# It is not possible to simply reset the error bars so
# we have to plot new lines but ensure we don't reorder them on the plot!
orig_idx = self.containers.index(container_orig)
container_orig.remove()
# The container does not remove itself from the containers list
# but protect this just in case matplotlib starts doing this
try:
self.containers.remove(container_orig)
except ValueError:
pass
# this gets pushed back onto the containers list
container_new = plotfunctions.errorbar(self, workspace,
**kwargs)
self.containers.insert(orig_idx, container_new)
self.containers.pop()
# update line properties to match original
orig_flat, new_flat = cbook.flatten(
container_orig), cbook.flatten(container_new)
for artist_orig, artist_new in zip(orig_flat, new_flat):
artist_new.update_from(artist_orig)
# ax.relim does not support collections...
self._update_line_limits(container_new[0])
self.autoscale()
return container_new
workspace = args[0]
spec_num = self._get_spec_number(workspace, kwargs)
return self.track_workspace_artist(workspace,
plotfunctions.errorbar(
self, *args, **kwargs),
_data_update,
spec_num=spec_num)
else:
return Axes.errorbar(self, *args, **kwargs)
def _data_update(artists, workspace, new_kwargs=None):
if self.lines:
self.set_autoscaley_on(autoscale_on_update)
# errorbar with workspaces can only return a single container
container_orig = artists[0]
# It is not possible to simply reset the error bars so
# we have to plot new lines but ensure we don't reorder them on the plot!
orig_idx = self.containers.index(container_orig)
container_orig.remove()
# The container does not remove itself from the containers list
# but protect this just in case matplotlib starts doing this
try:
self.containers.remove(container_orig)
except ValueError:
pass
# this gets pushed back onto the containers list
if new_kwargs:
container_new = plotfunctions.errorbar(self, workspace,
**new_kwargs)
else:
container_new = plotfunctions.errorbar(self, workspace,
**kwargs)
self.containers.insert(orig_idx, container_new)
self.containers.pop()
# Update joining line
if container_new[0] and container_orig[0]:
container_new[0].update_from(container_orig[0])
# Update caps
for orig_caps, new_caps in zip(container_orig[1], container_new[1]):
new_caps.update_from(orig_caps)
# Update bars
for orig_bars, new_bars in zip(container_orig[2], container_new[2]):
new_bars.update_from(orig_bars)
# Re-plotting in the config dialog will assign this attr
if hasattr(container_orig, 'errorevery'):
setattr(container_new, 'errorevery', container_orig.errorevery)
# ax.relim does not support collections...
self._update_line_limits(container_new[0])
self.set_autoscaley_on(True)
return container_new
def errorbar(self, *args, **kwargs):
"""
If the **mantid** projection is chosen, it can be
used the same as :py:meth:`matplotlib.axes.Axes.errorbar` for arrays,
or it can be used to plot :class:`mantid.api.MatrixWorkspace`
or :class:`mantid.api.IMDHistoWorkspace`. You can have something like::
import matplotlib.pyplot as plt
from mantid import plots
...
fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})
ax.errorbar(workspace,'rs',specNum=1) #for workspaces
ax.errorbar(x,y,yerr,'bo') #for arrays
fig.show()
For keywords related to workspaces, see :func:`plotfunctions.errorbar`
"""
if helperfunctions.validate_args(*args):
logger.debug('using plotfunctions')
def _data_update(artists, workspace):
# errorbar with workspaces can only return a single container
container_orig = artists[0]
# It is not possible to simply reset the error bars so
# we have to plot new lines but ensure we don't reorder them on the plot!
orig_idx = self.containers.index(container_orig)
container_orig.remove()
# The container does not remove itself from the containers list
# but protect this just in case matplotlib starts doing this
try:
self.containers.remove(container_orig)
except ValueError:
pass
# this gets pushed back onto the containers list
container_new = plotfunctions.errorbar(self, workspace, **kwargs)
self.containers.insert(orig_idx, container_new)
self.containers.pop()
# update line properties to match original
orig_flat, new_flat = cbook.flatten(container_orig), cbook.flatten(container_new)
for artist_orig, artist_new in zip(orig_flat, new_flat):
artist_new.update_from(artist_orig)
# ax.relim does not support collections...
self._update_line_limits(container_new[0])
self.autoscale()
return container_new
workspace = args[0]
spec_num = self._get_spec_number(workspace, kwargs)
return self.track_workspace_artist(workspace,
plotfunctions.errorbar(self, *args, **kwargs),
_data_update, spec_num=spec_num)
else:
return Axes.errorbar(self, *args, **kwargs)
def test_1d_errorbars(self):
fig, ax = plt.subplots()
funcs.errorbar(ax, self.ws2d_histo, 'rs', specNum=1)
funcs.errorbar(ax, self.ws2d_histo, specNum=2, linewidth=6)
funcs.errorbar(ax, self.ws_MD_1d, 'bo')
def test_1d_errorbars(self):
fig, ax = plt.subplots()
funcs.errorbar(ax, self.ws2d_histo, 'rs', specNum=1)
funcs.errorbar(ax, self.ws2d_histo, specNum=2, linewidth=6)
funcs.errorbar(ax, self.ws_MD_1d, 'bo')
def errorbar(self, *args, **kwargs):
"""
If the **mantid** projection is chosen, it can be
used the same as :py:meth:`matplotlib.axes.Axes.errorbar` for arrays,
or it can be used to plot :class:`mantid.api.MatrixWorkspace`
or :class:`mantid.api.IMDHistoWorkspace`. You can have something like::
import matplotlib.pyplot as plt
from mantid import plots
...
fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})
ax.errorbar(workspace,'rs',specNum=1) #for workspaces
ax.errorbar(x,y,yerr,'bo') #for arrays
fig.show()
For keywords related to workspaces, see :func:`plotfunctions.errorbar`
"""
if helperfunctions.validate_args(*args):
logger.debug('using plotfunctions')
autoscale_on_update = kwargs.pop("autoscale_on_update", True)
def _data_update(artists, workspace, new_kwargs=None):
if self.lines:
self.set_autoscaley_on(autoscale_on_update)
# errorbar with workspaces can only return a single container
container_orig = artists[0]
# It is not possible to simply reset the error bars so
# we have to plot new lines but ensure we don't reorder them on the plot!
orig_idx = self.containers.index(container_orig)
container_orig.remove()
# The container does not remove itself from the containers list
# but protect this just in case matplotlib starts doing this
try:
self.containers.remove(container_orig)
except ValueError:
pass
# this gets pushed back onto the containers list
if new_kwargs:
container_new = plotfunctions.errorbar(self, workspace,
**new_kwargs)
else:
container_new = plotfunctions.errorbar(self, workspace,
**kwargs)
self.containers.insert(orig_idx, container_new)
self.containers.pop()
# Update joining line
if container_new[0] and container_orig[0]:
container_new[0].update_from(container_orig[0])
# Update caps
for orig_caps, new_caps in zip(container_orig[1], container_new[1]):
new_caps.update_from(orig_caps)
# Update bars
for orig_bars, new_bars in zip(container_orig[2], container_new[2]):
new_bars.update_from(orig_bars)
# Re-plotting in the config dialog will assign this attr
if hasattr(container_orig, 'errorevery'):
setattr(container_new, 'errorevery', container_orig.errorevery)
# ax.relim does not support collections...
self._update_line_limits(container_new[0])
self.set_autoscaley_on(True)
return container_new
workspace = args[0]
spec_num = self.get_spec_number(workspace, kwargs)
is_normalized, kwargs = get_normalize_by_bin_width(workspace, self,
**kwargs)
if self.lines:
self.set_autoscaley_on(autoscale_on_update)
artist = self.track_workspace_artist(
workspace, plotfunctions.errorbar(self, *args, **kwargs),
_data_update, spec_num, is_normalized)
self.set_autoscaley_on(True)
return artist
else:
return Axes.errorbar(self, *args, **kwargs)
