SANS Data Reduction Steps

SANS Data Reduction Steps

The SANS data reduction pipeline is very simple.

1. convert data to Measurement object newdata=Measurement(data) data[i,j]=Measurement(counts, variance_counts), where i,j represent coordinates of a pixel on the detector.
2. Convert to a monitor of 10^8 . To do this, multiply newdata=data*mon0/mon, where mon0 is original monitor, given by metadata[run.moncnt] and mon is the new monitor and mon=1e8.
3. Solid Angle Correction
4. Dead Time Correction
5. You are given Transmission_{s+c}, Transmission_{c}, and Transmission_{E}. You make these Measurements, then (T_{s+c}=Sum(Transmission_{s+c})/Sum(Transmission{Empty}), where these are summed over a box defined by its bottom left and top right corner. Similarly, for T_c
6. \(\Sigma_{cor}\) =(I_{sample+background}-I_{blocked_beam})/T_{sample+cell}-(I_{empty_cell}-I_{blocked_beam})/T_{cell}
7. Generate the normalized_detector_sensitivity "image" by taking a plexiglass measurement file (turning it into a measurement) and dividing it my its mean intensity.
8. \(I_{cal}=\frac{\Sigma_{cor}}{I_{normalized\_detector\_sensitivity\_measurement}} \)
9. Put on absolute scale (units of \( cm^{-1} \))
10. Convert to Q
11. Radial Averaging

Detector

Each pixel is a square and 0.508 cm on a side There are 128x128 pixels.
Pixel size should be stored in det.calx1 and det.caly1 but it seems that the example data at least has the old, incorrect, value of 0.50 cm

The origin for the detector is at the bottom left corner. The center of the beam is given by (det.beamx,det.beamy). L2 is given by det.dis in metadata returned from data.py