`mantid.plots`¶

The functions in this module are intended to be used with matplotlib’s object oriented abstract program interface (API). matplotlib’s (stateful) functional interface is discouraged by matplotlib. The object oriented API allow for customization as well.

The plotting of a mantid.api.MatrixWorkspace or a mantid.api.IMDHistoWorkspace can happen in two different ways. The use of a mantid projection allows most matplotlib-like experience:

import matplotlib.pyplot as plt
from mantid import plots

#some code here to get a workspace, and x, y, yerr arrays

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()

If the mantid projection is not used, the plotting functions take a matplotlib.axes.Axes and a mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace, with some keywords that are specific to Mantid an the type or workspace used. While there are defaults for the labels, you can easily override them after the initial plotting is called. A useful reference is matplotlib’s anatomy of a figure.

Note

To run these usage examples please first download the usage data, and add these to your path. In MantidPlot this is done using Manage User Directories.

All of the examples below can be run with the following imports, but not all are used in all places.

from mantid.simpleapi import mtd, Load, LoadEventNexus, Rebin, ConvertUnits, SofQW, Transpose
from mantid import plots
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm

First, load some diffraction data and see what the automatic axes will be using get_axes_labels().

Load(Filename="PG3_733", OutputWorkspace="PG3_733")
print(plots.helperfunctions.get_axes_labels(mtd['PG3_733']))

Which will print the y-label then the labels for all the other axes as properly escaped for use directly in matplotlib.axes.Axes.set_xlabel().

('Counts', 'd-Spacing ($\\AA$)', 'Spectrum')

To generate a 1D plots of some spectra with mantid projection:

fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})
ax.plot(mtd['PG3_733'], 'go-', specNum=1, label='user label')
ax.errorbar(mtd['PG3_733'],  wkspIndex=2)
ax.legend()
fig.show()

or without:

fig, ax = plt.subplots()
plots.plotfunctions.plot(ax, mtd['PG3_733'], 'go-', specNum=1, label='user label')
plots.plotfunctions.errorbar(ax, mtd['PG3_733'],  wkspIndex=2)
ax.legend()
fig.show()

This example demonstrates adding multiple spectra onto a single 1D plot and overriding some of the default behavior. plot() is a normal line plot, while errorbar() adds the uncertainties. It should be warned that every call to one of the plot functions will automatically annotate the axes with the last one called being the one that takes effect.

The plot() function also allows plotting sample logs.

from mantid import plots
import matplotlib.pyplot as plt
w = LoadEventNexus(Filename='CNCS_7860_event.nxs')
fig = plt.figure()
ax1 = fig.add_subplot(211, projection = 'mantid')
ax2 = fig.add_subplot(212, projection = 'mantid')
ax1.plot(w, LogName = 'ChopperStatus5')
ax1.set_title('From run start')
ax2.plot(w, LogName = 'ChopperStatus5', FullTime = True)
ax2.set_title('Absolute time')
fig.tight_layout()
fig.show()

../../../../_images/mantid_plots_1Dlogs.png

Two common ways to look at 2D plots are contourf() and pcolormesh(). The difference between these is the contourf() calculates smooth lines of constant value, where the pcolormesh() is the actual data values. pcolormesh() is similar to pcolor(), but uses a different mechanism and returns a different object; pcolor returns a PolyCollection but pcolormesh returns a QuadMesh. It is much faster, so it is almost always preferred for large arrays.

LoadEventNexus(Filename='CNCS_7860_event.nxs', OutputWorkspace='CNCS_7860_event')
ConvertUnits(InputWorkspace='CNCS_7860_event', OutputWorkspace='CNCS_7860_event', Target='DeltaE', EMode='Direct', EFixed=3)
Rebin(InputWorkspace='CNCS_7860_event', OutputWorkspace='CNCS_7860_event', Params='-3,0.05,3')
SofQW(InputWorkspace='CNCS_7860_event', OutputWorkspace='CNCS_7860_sqw', QAxisBinning='0,0.05,3', EMode='Direct', EFixed=3)
Transpose(InputWorkspace='CNCS_7860_sqw',  OutputWorkspace='CNCS_7860_sqw')

fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})
c = ax.contourf(mtd['CNCS_7860_sqw'], norm=LogNorm())
ax.set_xlabel('awesome label')
fig.colorbar(c)
fig.show()

../../../../_images/mantid_plots_contourf.png

Similarly, showing the actual values with pcolormesh()

fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})
c = ax.pcolormesh(mtd['CNCS_7860_sqw'], norm=LogNorm())
fig.colorbar(c)
fig.show()

../../../../_images/mantid_plots_pcolormesh.png

A couple of notes about pcolor(), pcolormesh(), and pcolorfast():

If the mantid.api.MatrixWorkspace has unequal bins, the polygons/meshes will have sides not aligned with the axes. One can override this behavior by using the axisaligned keyword, and setting it to True
If the mantid.api.MatrixWorkspace has different numbers of bins the above functions will automatically use the axisaligned behavior (cannot be overriden). contour() and the like cannot plot these type of workspaces.

In addition to the mantid projection, there is also the mantid3d projection for 3d plots. Can be used much the same as the mantid projection, but by instead specifying mantid3d when giving the projection:

import matplotlib.pyplot as plt
from mantid import plots

#some code here to get a workspace, and x, y, yerr arrays

fig, ax = plt.subplots(subplot_kw={'projection':'mantid3d'})
ax.plot_wireframe(workspace)   #for workspaces
ax.plot_wireframe(x,y,z)       #for arrays
fig.show()

Types of functions¶

Informational

get_axes_labels()

1D Plotting

plot() - Plot lines and/or markers
errorbar() - Plot valuse with errorbars
scatter() - Make a scatter plot

2D Plotting

contour() - Draw contours at specified levels
contourf() - Draw contours at calculated levels
pcolor() - Draw a pseudocolor plot of a 2-D array
pcolorfast() - Draw a pseudocolor plot of a 2-D array
pcolormesh() - Draw a quadrilateral mesh
tripcolor() - Draw a pseudocolor plot of an unstructured triangular grid
tricontour() - Draw contours at specified levels on an unstructured triangular grid
tricontourf() - Draw contours at calculated levels on an unstructured triangular grid

3D Plotting

plot() - Draws a line plot in 3D space
scatter() - Draws a scatter plot in 3d space
plot_wireframe() - Draws a wire frame linking all adjacent data plots
plot_surface() - Draws a surface linking all adjacent data points
contour() - Draws contour lines at specified levels of the data
contourf() - Draws filled contour lines at specified levels of the data

matplotlib demonstrates the difference between uniform and nonuniform grids well in this example

Available Functions¶

When using `mantid` projection¶

class mantid.plots.MantidAxes(fig, rect, axisbg=None, frameon=True, sharex=None, sharey=None, label=u'', xscale=None, yscale=None, **kwargs)¶

This class defines the mantid projection for 2d plotting. One chooses this projection using:

import matplotlib.pyplot as plt
from mantid import plots
fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})

or:

import matplotlib.pyplot as plt
from mantid import plots
fig = plt.figure()
ax = fig.add_subplot(111,projection='mantid')

The mantid projection allows replacing the array objects with mantid workspaces.

contour(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.contour() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.contour(workspace) #for workspaces
ax.contour(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.contour()

contourf(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.contourf() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.contourf(workspace) #for workspaces
ax.contourf(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.contourf()

errorbar(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.errorbar() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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 mantid.plots.plotfunctions.errorbar()

pcolor(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.pcolor() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.pcolor(workspace) #for workspaces
ax.pcolor(x,y,C)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.pcolor()

pcolorfast(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.pcolorfast() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.pcolorfast(workspace) #for workspaces
ax.pcolorfast(x,y,C)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.pcolorfast()

pcolormesh(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.pcolormesh() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.pcolormesh(workspace) #for workspaces
ax.pcolormesh(x,y,C)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.pcolormesh()

plot(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.plot() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.plot(workspace,'rs',specNum=1) #for workspaces
ax.plot(x,y,'bo')                 #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.plot().

scatter(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.scatter() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.scatter(workspace,'rs',specNum=1) #for workspaces
ax.scatter(x,y,'bo')                 #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.scatter()

tricontour(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.tricontour() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.tricontour(workspace) #for workspaces
ax.tricontour(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.tricontour()

tricontourf(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.tricontourf() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.tricontourf(workspace) #for workspaces
ax.tricontourf(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.tricontourf()

tripcolor(*args, **kwargs)¶

If the mantid projection is chosen, it can be used the same as matplotlib.axes.Axes.tripcolor() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.tripcolor(workspace) #for workspaces
ax.tripcolor(x,y,C)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions.tripcolor()

When using `mantid3d` projection¶

class mantid.plots.MantidAxes3D(fig, rect=None, *args, **kwargs)¶

This class defines the mantid3d projection for 3d plotting. One chooses this projection using:

import matplotlib.pyplot as plt
from mantid import plots
fig, ax = plt.subplots(subplot_kw={'projection':'mantid3d'})

or:

import matplotlib.pyplot as plt
from mantid import plots
fig = plt.figure()
ax = fig.add_subplot(111,projection='mantid3d')

The mantid3d projection allows replacing the array objects with mantid workspaces.

contour(*args, **kwargs)¶

If the mantid3d projection is chosen, it can be used the same as matplotlib.axes.Axes3D.contour() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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 mantid.plots.plotfunctions3D.contour()

contourf(*args, **kwargs)¶

If the mantid3d projection is chosen, it can be used the same as matplotlib.axes.Axes3D.contourf() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.contourf(workspace) #for workspaces
ax.contourf(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions3D.contourf()

plot(*args, **kwargs)¶

If the mantid3d projection is chosen, it can be used the same as matplotlib.axes.Axes3D.plot() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.plot(workspace) #for workspaces
ax.plot(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions3D.plot3D()

plot_surface(*args, **kwargs)¶

If the mantid3d projection is chosen, it can be used the same as matplotlib.axes.Axes3D.plot_surface() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.plot_surface(workspace) #for workspaces
ax.plot_surface(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions3D.plot_surface()

plot_wireframe(*args, **kwargs)¶

If the mantid3d projection is chosen, it can be used the same as matplotlib.axes.Axes3D.plot_wireframe() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.plot_wireframe(workspace) #for workspaces
ax.plot_wireframe(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions3D.wireframe()

scatter(*args, **kwargs)¶

If the mantid3d projection is chosen, it can be used the same as matplotlib.axes.Axes3D.scatter() for arrays, or it can be used to plot mantid.api.MatrixWorkspace or 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.scatter(workspace) #for workspaces
ax.scatter(x,y,z)     #for arrays
fig.show()

For keywords related to workspaces, see mantid.plots.plotfunctions3D.scatter()

Functions to use when mantid projection is not available¶

mantid.plots.plotfunctions.plot(axes, workspace, *args, **kwargs)¶

Unpack mantid workspace and render it with matplotlib. args and kwargs are passed to matplotlib.axes.Axes.plot() after special keyword arguments are removed. This will automatically label the line according to the spectrum number unless specified otherwise.

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from specNum – spectrum number to plot if MatrixWorkspace wkspIndex – workspace index to plot if MatrixWorkspace 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 workspace is a MatrixWorkspace histogram. 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 LogName – if specified, it will plot the corresponding sample log. The x-axis of the plot is the time difference between the log time and the first value of the proton_charge log (if available) or the sample log’s first time. StartFromLog – False by default. If True the time difference will be from the sample log’s first time, even if proton_charge log is available. FullTime – False by default. If true, the full date and time will be plotted on the axis instead of the time difference ExperimentInfo – for MD Workspaces with multiple `mantid.api.ExperimentInfo` is the ExperimentInfo object from which to extract the log. It’s 0 by default

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
specNum – spectrum number to plot if MatrixWorkspace
wkspIndex – workspace index to plot if MatrixWorkspace
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 workspace is a MatrixWorkspace histogram.
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
LogName – if specified, it will plot the corresponding sample log. The x-axis of the plot is the time difference between the log time and the first value of the proton_charge log (if available) or the sample log’s first time.
StartFromLog – False by default. If True the time difference will be from the sample log’s first time, even if proton_charge log is available.
FullTime – False by default. If true, the full date and time will be plotted on the axis instead of the time difference
ExperimentInfo – for MD Workspaces with multiple mantid.api.ExperimentInfo is the ExperimentInfo object from which to extract the log. It’s 0 by default

For matrix workspaces with more than one spectra, either specNum or wkspIndex needs to be specified. Giving both will generate a RuntimeError. There is no similar keyword for MDHistoWorkspaces. These type of workspaces have to have exactly one non integrated dimension

mantid.plots.plotfunctions.errorbar(axes, workspace, *args, **kwargs)¶

Unpack mantid workspace and render it with matplotlib. args and kwargs are passed to matplotlib.axes.Axes.errorbar() after special keyword arguments are removed. This will automatically label the line according to the spectrum number unless specified otherwise.

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from specNum – spectrum number to plot if MatrixWorkspace wkspIndex – workspace index to plot if MatrixWorkspace 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 workspace is a MatrixWorkspace histogram. 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

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
specNum – spectrum number to plot if MatrixWorkspace
wkspIndex – workspace index to plot if MatrixWorkspace
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 workspace is a MatrixWorkspace histogram.
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

mantid.plots.plotfunctions.scatter(axes, workspace, *args, **kwargs)¶

Unpack mantid workspace and render it with matplotlib. args and kwargs are passed to matplotlib.axes.Axes.scatter() after special keyword arguments are removed. This will automatically label the line according to the spectrum number unless specified otherwise.

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from specNum – spectrum number to plot if MatrixWorkspace wkspIndex – workspace index to plot if MatrixWorkspace 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 workspace is a MatrixWorkspace histogram. 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

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
specNum – spectrum number to plot if MatrixWorkspace
wkspIndex – workspace index to plot if MatrixWorkspace
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 workspace is a MatrixWorkspace histogram.
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

mantid.plots.plotfunctions.contour(axes, workspace, *args, **kwargs)¶

Essentially the same as matplotlib.axes.Axes.contour() but calculates the countour levels. Currently this only works with workspaces that have a constant number of bins between spectra.

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from 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. 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

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
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.
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

mantid.plots.plotfunctions.contourf(axes, workspace, *args, **kwargs)¶

Essentially the same as matplotlib.axes.Axes.contourf() but calculates the countour levels. Currently this only works with workspaces that have a constant number of bins between spectra.

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from 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. 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

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
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.
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

mantid.plots.plotfunctions.pcolor(axes, workspace, *args, **kwargs)¶

Essentially the same as matplotlib.axes.Axes.pcolor()

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from 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. 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 axisaligned – `False` (default). If `True`, or if the workspace has a variable number of bins, the polygons will be aligned with the axes

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
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.
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
axisaligned – False (default). If True, or if the workspace has a variable number of bins, the polygons will be aligned with the axes

mantid.plots.plotfunctions.pcolorfast(axes, workspace, *args, **kwargs)¶

Essentially the same as matplotlib.axes.Axes.pcolorfast()

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from 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. 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 axisaligned – `False` (default). If `True`, or if the workspace has a variable number of bins, the polygons will be aligned with the axes

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
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.
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
axisaligned – False (default). If True, or if the workspace has a variable number of bins, the polygons will be aligned with the axes

mantid.plots.plotfunctions.pcolormesh(axes, workspace, *args, **kwargs)¶

Essentially the same as matplotlib.axes.Axes.pcolormesh().

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from 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. 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 axisaligned – `False` (default). If `True`, or if the workspace has a variable number of bins, the polygons will be aligned with the axes

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
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.
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
axisaligned – False (default). If True, or if the workspace has a variable number of bins, the polygons will be aligned with the axes

mantid.plots.plotfunctions.tripcolor(axes, workspace, *args, **kwargs)¶

To be used with non-uniform grids. Currently this only works with workspaces that have a constant number of bins between spectra or with MDHistoWorkspaces.

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from 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. 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

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
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.
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

See matplotlib.axes.Axes.tripcolor() for more information.

mantid.plots.plotfunctions.tricontour(axes, workspace, *args, **kwargs)¶

Essentially the same as mantid.plots.contour(), but works for non-uniform grids. Currently this only works with workspaces that have a constant number of bins between spectra or with MDHistoWorkspaces.

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from 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. 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

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
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.
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

See matplotlib.axes.Axes.tricontour() for more information.

mantid.plots.plotfunctions.tricontourf(axes, workspace, *args, **kwargs)¶

Essentially the same as mantid.plots.contourf(), but works for non-uniform grids. Currently this only works with workspaces that have a constant number of bins between spectra or with MDHistoWorkspaces.

Parameters:

Parameters:	axes – `matplotlib.axes.Axes` object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from 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. 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

axes – matplotlib.axes.Axes object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
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.
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

See matplotlib.axes.Axes.tricontourf() for more information.

Functions to use when mantid3d projection is not available¶

mantid.plots.plotfunctions3D.plot(axes, workspace, *args, **kwargs)¶

3D plots - line plots

Parameters:	axes – class:matplotlib.axes.Axes3D object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from zdir – Which direction to use as z (‘x’, ‘y’ or ‘z’) when plotting a 2D set.

mantid.plots.plotfunctions3D.scatter(axes, workspace, *args, **kwargs)¶

Scatter plots

Parameters:

Parameters:	axes – class:matplotlib.axes.Axes3D object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from zdir – Which direction to use as z (‘x’, ‘y’ or ‘z’) when plotting a 2D set. s – Size in points^2. It is a scalar or an array of the same length as x and y. c – A color. c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped to colors using the cmap and norm specified via kwargs (see below). Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. c can be a 2-D array in which the rows are RGB or RGBA, however, including the case of a single row to specify the same color for all points. depthshade – Whether or not to shade the scatter markers to give the appearance of depth. Default is True.

axes – class:matplotlib.axes.Axes3D object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
zdir – Which direction to use as z (‘x’, ‘y’ or ‘z’) when plotting a 2D set.
s – Size in points^2. It is a scalar or an array of the same length as x and y.
c – A color. c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped to colors using the cmap and norm specified via kwargs (see below). Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. c can be a 2-D array in which the rows are RGB or RGBA, however, including the case of a single row to specify the same color for all points.
depthshade – Whether or not to shade the scatter markers to give the appearance of depth. Default is True.

mantid.plots.plotfunctions3D.plot_wireframe(axes, workspace, *args, **kwargs)¶

Wire-frame plot

Parameters:

Parameters:	axes – class:matplotlib.axes.Axes3D object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from rstride – Array row stride (step size), defaults to 1 cstride – Array column stride (step size), defaults to 1 rcount – Use at most this many rows, defaults to 50 ccount – Use at most this many columns, defaults to 50

axes – class:matplotlib.axes.Axes3D object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
rstride – Array row stride (step size), defaults to 1
cstride – Array column stride (step size), defaults to 1
rcount – Use at most this many rows, defaults to 50
ccount – Use at most this many columns, defaults to 50

mantid.plots.plotfunctions3D.plot_surface(axes, workspace, *args, **kwargs)¶

Surface plots

Parameters:

Parameters:	axes – class:matplotlib.axes.Axes3D object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from rstride – Array row stride (step size), defaults to 1 cstride – Array column stride (step size), defaults to 1 rcount – Use at most this many rows, defaults to 50 ccount – Use at most this many columns, defaults to 50 color – Color of the surface patches cmap – A colormap for the surface patches. norm – An instance of Normalize to map values to colors vmin – Minimum value to map vmax – Maximum value to map shade – Whether to shade the facecolors facecolors – Face colors for the individual patches

axes – class:matplotlib.axes.Axes3D object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
rstride – Array row stride (step size), defaults to 1
cstride – Array column stride (step size), defaults to 1
rcount – Use at most this many rows, defaults to 50
ccount – Use at most this many columns, defaults to 50
color – Color of the surface patches
cmap – A colormap for the surface patches.
norm – An instance of Normalize to map values to colors
vmin – Minimum value to map
vmax – Maximum value to map
shade – Whether to shade the facecolors
facecolors – Face colors for the individual patches

mantid.plots.plotfunctions3D.contour(axes, workspace, *args, **kwargs)¶

Contour plots

Parameters:

Parameters:	axes – class:matplotlib.axes.Axes3D object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from extend3d – Whether to extend contour in 3D (default: False) stride – Stride (step size) for extending contour zdir – The direction to use: x, y or z (default) offset – If specified plot a projection of the contour lines on this position in plane normal to zdir

axes – class:matplotlib.axes.Axes3D object that will do the plotting
workspace – mantid.api.MatrixWorkspace or mantid.api.IMDHistoWorkspace to extract the data from
extend3d – Whether to extend contour in 3D (default: False)
stride – Stride (step size) for extending contour
zdir – The direction to use: x, y or z (default)
offset – If specified plot a projection of the contour lines on this position in plane normal to zdir

mantid.plots.plotfunctions3D.contourf(axes, workspace, *args, **kwargs)¶

Filled Contour plots

Parameters:	axes – class:matplotlib.axes.Axes3D object that will do the plotting workspace – `mantid.api.MatrixWorkspace` or `mantid.api.IMDHistoWorkspace` to extract the data from zdir – The direction to use: x, y or z (default) offset – If specified plot a projection of the filled contour on this position in plane normal to zdir

mantid.plots¶

Types of functions¶

Available Functions¶

When using mantid projection¶

When using mantid3d projection¶

Functions to use when mantid projection is not available¶

Functions to use when mantid3d projection is not available¶

Helper functions¶

`mantid.plots`¶

When using `mantid` projection¶

When using `mantid3d` projection¶