I am new to RooFit and I am trying to fit azimuthal modulations in the fragmentation of hadrons.
These are large datasets that are binned in several kinematic variables.
At first, I tried to do an unbinned LH fit putting the data in a RooDataSet. Each entry had 7 entries. Three bins and 4 angles. I was planning to fit the counts differential in the 4 angles.
However, this quickly ran into memory allocation errors. Since the internal data structure is a TTree I was hoping it would be swapped out to disk, but no.
The second attempt was using binned histograms. These are histograms with ~1M bins. So my naive estimate was, given that each entry is a double and maybe there are members to keep track of weights etc. that each histogram should use at most about 100MB memory. However, the memory usage is an order of magnitude larger and leads to a memory allocation seg fault as well.
So my question is twofold:
-What memory usage should I expect per entry of RooDataHist?
-Is there a procedure to process large datasets that are differential in many variables. Either unbinned using RooDataSet or using RooDataHist but with many bins?