Subtracting data sets

It can be very useful to subtract two data sets from each other, e.g. to look for diffuse magnetic scattering. In DMCpy, two data sets with the same A3 can be subtracted from each other. An example of a code is below. The subtraction is perfomed on the DataSet and 3DViewer, plotQPlane, and plotCut1D can be used on the subtracted data.

from DMCpy import DataSet,DataFile,_tools

# Give file number and folder the file is stored in.
scanNumbers = '8540'
folder = 'data/SC'
year = 2022

filePath = _tools.fileListGenerator(scanNumbers,folder,year=year)

# # # load dataFiles
dataFiles = [DataFile.loadDataFile(dFP) for dFP in filePath]

# load data files and make data set
ds = DataSet.DataSet(dataFiles)

# run the Interactive Viewer
df = ds[0]
IA1 = df.InteractiveViewer()
IA1.set_clim(0,20)
IA1.set_clim_zIntegrated(0,1000)

IA1.fig.savefig('figure0.png',format='png')

# # # subtract dataSets. Needs to be loaded same way as the first DataSet
if True:
   scanNumbers_sub = '8553'
   filePath_sub = _tools.fileListGenerator(scanNumbers_sub,folder,year=year)

   dataFiles_sub = [DataFile.loadDataFile(dFP_sub) for dFP_sub in filePath_sub]

   ds_sub = DataSet.DataSet(dataFiles_sub)

   # we can choose if we write the subtracted data into the original data file or if we make a new file.
   ds.directSubtractDS(ds_sub,saveToFile=True,saveToNewFile='subtracted_data.hdf')

   #saveToFile (bool): If True, save background to data file, else save in RAM (default False)
   #saveToNewFile (string) If provided, and saveToFile is True, save a new file with the background subtraction (default False)

# run the Interactive Viewer
IA2 = df.InteractiveViewer()
IA2.set_clim(0,20)
IA2.set_clim_zIntegrated(0,1000)

IA2.fig.savefig('figure1.png',format='png')

Viewer = ds.Viewer3D(0.03,0.03,0.03,rlu=False)
Viewer.set_clim(0,0.001)
zSteps = Viewer.Z.shape[-1]
Viewer.setPlane(int(zSteps/2)-1)
Viewer.ax.axis('equal')

fig = Viewer.ax.get_figure()
fig.savefig('figure2.png',format='png')

# # # mask data
if True:
   for df in ds:
      df.mask[:,:,300:400] = True

Viewer2 = ds.Viewer3D(0.03,0.03,0.03,rlu=False)
Viewer2.set_clim(0,0.001)
Viewer2.setPlane(int(zSteps/2)-1)
Viewer2.ax.axis('equal')

fig2 = Viewer2.ax.get_figure()
fig2.savefig('figure3.png',format='png')

The above code takes the data from the A3 scan file dmc2022n008540 and subtracts dmc2022n008553. The files are meaured under identical conditions and we expect a good subtraction. We see in both interactive Viewer and 3DViewer that we have good subtractoin, but the Cu rings from the sample can is still visible together with some intensity on the 111-reflection.

First data overview

Second data overview with background subtraction and A3 step 114

Third data overview with background subtraction and A3 step 114

Fourth data overview with a mask between detector pixcel 300 and 400