def test_3d_contour(self):
fig = plt.figure()
ax = fig.add_subplot(111, projection='mantid3d')
funcs.contour(ax, self.ws2d_histo_rag)
funcs.contourf(ax, self.ws2d_histo, vmin=0)
self.assertRaises(ValueError, funcs.contour, ax,
self.ws2d_point_uneven)
def contour(self, *args, **kwargs):
"""
If the **mantid3d** projection is chosen, it can be
used the same as :py:meth:`matplotlib.axes.Axes3D.contour` 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':'mantid3d'})
ax.contour(workspace) #for workspaces
ax.contour(x,y,z) #for arrays
fig.show()
For keywords related to workspaces, see :func:`plotfunctions3D.contour`
"""
if helperfunctions.validate_args(*args):
logger.debug('using plotfunctions3D')
return plotfunctions3D.contour(self, *args, **kwargs)
else:
return Axes3D.contour(self, *args, **kwargs)
def contour(self, *args, **kwargs):
"""
If the **mantid3d** projection is chosen, it can be
used the same as :py:meth:`matplotlib.axes.Axes3D.contour` 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':'mantid3d'})
ax.contour(workspace) #for workspaces
ax.contour(x,y,z) #for arrays
fig.show()
For keywords related to workspaces, see :func:`plotfunctions3D.contour`
"""
if helperfunctions.validate_args(*args):
logger.debug('using plotfunctions3D')
return plotfunctions3D.contour(self, *args, **kwargs)
else:
return Axes3D.contour(self, *args, **kwargs)
def test_3d_contour(self):
fig = plt.figure()
ax = fig.add_subplot(111, projection='mantid3d')
funcs.contour(ax, self.ws2d_histo_rag)
funcs.contourf(ax, self.ws2d_histo, vmin=0)
self.assertRaises(ValueError, funcs.contour, ax, self.ws2d_point_uneven)