Event Statistics Summary
- Cross-section statistics
- Error messages
- Multiparton-interactions statistics
At the end of the run you will want to write out the final statistics
on number of events generated, the corresponding cross sections and
the number of errors encountered. This is done with the
pythia.stat() method, assuming pythia is an
instance of the Pythia class.The method is steered entirely
by settings values, see here.
Note that further methods for user access to generated
cross sections and event weights are documented on the
Cross Sections and Weights
page.
Cross-section statistics
The ProcessLevel::statistics() method cannot be accessed
directly, but only via the Pythia::stat() call above.
When called it will loop over the list of existing processes, and for
each write out name, code, the number of tried, selected and accepted
events, the cross section and the estimated error on the latter.
The three different event numbers are related to the Monte Carlo method
used, whereby an initial upper estimate of the cross section is used to
select a large number of trial phase-space points, whereof then not all
survive. Rejections are normally done by the internal machinery, but can
also be obtained by user hooks.
Therefore:
- tried events reflect the original number of
phase-space points probed, as part of the upper estimate;
- selected events correspond to those that survive
the internal Monte-Carlo selection procedure;
- accepted events are those that also survive
the additional user cuts.
In most runs there would be no user hooks implemented, and then the
numbers of selected and of accepted events will agree. Aborted events
(see below) usually appear in the selected statistics but not in the
accepted one.
For Les Houches events the total cross section will be correctly
displayed; however the (optional) error value will not be used, so that
the reported error will be smaller than the correct statistical ones,
and often vanish completely. Furthermore, while the number of events
is shown for each user process, the cross section is only for the sum
of them.
Error messages
When Pythia is run, errors may occur, and give rise to warning messages.
These may be of varying severity, as follows:
- Abort means things went seriously wrong, and the
initialization or event generation failed. In the former case it is
not possible to generate events at all, in the latter the current
event is flawed and should be skipped. In either case the respective
method,
Pythia::init() or Pythia::next(),
then also returns the value false. There are occasions
where an abort may be deliberate, such as when a file of Les Houches
Events is read and the end of the file is reached.
- Error normally is less severe. Typically the program will
back up one step and try again. There are cases where this is not possible,
in particular during the initialization and the generation of a hard
process, and then the error may be followed by an abort as a direct
consequence (with two separate messages).
- Warning is even less severe. In some cases the program will
try again, with good chances of success, in others no measure at all
need to be taken.
The error messages is handled by a small part of the Info
class. It is handed any abort, error or warning messages during the event
generation phase, and will store each distinct message, with a counter
for how many times it is issued. Thus it is possible to limit the number
of identical messages issued, currently hardcoded so that each kind of
error message is only printed once
(static const int TIMESTOPRINT = 1).
This can be overridden by the calling routine, so that all messages of
this kind are shown, which is particularly relevant for the
initialization stage.
The summary table printed by Pythia::stat()
provides a table with all the different messages issued, in
alphabetical order, with the total number of times each was generated.
Multiparton-interactions statistics
If you call Pythia::stat() with
Stat:showPartonLevel = true also statistics on multiparton
interactions is printed, comprising a list of all allowed subprocesses
with how many times each of them has been generated. For the nondiffractive
process this also includes the hardest interaction, while else the
hardest process is excluded from the statistics. (This is because
the hardest process is of the same character and generated by the same
machinery in the former case but not in the latter. Also, for the
former case only, the standard statistics listing only lists
nondiffractive as one single process, i.e. does not further specify
the character of the hardest subprocess, so there is not any overlap
between the two.)