In order to inform future improvements in jointcal's performance, we need to do some profiling on 10, 50, and 100 visits, to see how the performance of the different components (e.g. outlier rejection, matrix construction, solving) scale with the number of visits. In addition to the general profiling code in the stack, jointcal has a task-specific profiling option that separates the algorithm profiling from the data reading portion.
Hsin-Fang Chiang: do you know if there is a tract of data on lsst-dev that has roughly 100 visits in it? If we do not have 100 visits available on lsst-dev, we can use whatever tract has the largest number.