Dear All
I am using Worm to make some easy simulation  with
  RESTRICT_MEASUREMENTS[N]=30

I understand that:

If I set up the chemical potential correctly, then the MC algorithm encounters enough trajectories with N=30 and
the output files contain resuls averagen only over trajectories with N=30 - approximation of the canonical ensemble.

This is confirmed by user-experience and my weak recollecion of advide I have received here about oen year ago.

But if I set the chemical potential wrongly then the average number of particles from the Grand canonical point of view is for example 45, and there are not enough (maybe even 0) trajectories to sample with N=30.

In this case the output files contain somethink that makes the following python "result getter":

********************** get.py ***********************
import pyalps
import sys

rf=pyalps.getResultFiles(prefix=sys.argv[1])
data = pyalps.loadMeasurements(rf)
obl=pyalps.loadObservableList(rf)

*******************************************************

behave rude: it says Floating point exception. and quits (even if only one of let say 500 output files is corrupt).

Of course adjusting the chemical pontential is the key, but this seems to be complicated in a case where the phase diagram is complicated (I would have to
do some form of extrapolation or binary search to get the right mu). On the other hand I see no other way to solve it.

Another way to deal with that is to generate input files containing only one set of input parameters - this way each datapoint has its own prefix. It is not complicated, but somehow contrary to the idea behind the current format of the input data. Morover it is likely to make a bookkeeping mess.

I have two questions:
1. is there a way to read these "faulty", "undersampled" ouput files without "Floating point exception." (I could then set up calculations for let say 10 different values of mu an choose mu that gave the closes answer - the simplest to code).
2. is there some easy way to make the MC autoadjust the chemical potential ?


Regards,
Mateusz Lacki