Pathologies

How can we judge the quality of a data set? There are several possibilities:

1. numerical indicators, like R-values, I/sigma and the like
2. graphical representations

This article serves to demonstrate pathological cases. It collects examples for

1. problems with the hardware (e.g. detector, beamline, goniostat, beam, cryo)
2. problems with the crystal
3. problems with data processing

Hardware problems

Scale factor plot in case of spindle problems

The scale factor is printed, in INTEGRATE.LP, for every frame (column 3). This plot shows spikes indicating that the spindle went too fast every 13 frames or so (but the spindle went slow in the adjacent frames). Needless to say, this problem is quite detrimental to data quality.

Mosaicity plots in case of spindle problems

The same data set: the mosaicity estimates of individual frames (column 10 in INTEGRATE.LP) is very much influenced by this.

The same problem, but a different data set: here, the mosaicity estimates of individual frames are influenced in a different way, and a different way of oscillation results. This is not seen very well here since the period is on the order of 13 frames.

Zoomed version of the above. The oscillations are better visible.