RankChecker Class Reference

Inheritance diagram for RankChecker:

Collaboration diagram for RankChecker:

Public Member Functions
def	initialize (self)
def	event (self)

Public Attributes
	plist
	particle list object

Detailed Description

Check if the ranks are actually what we want

Definition at line 44 of file best_candidate_selection.py.

Member Function Documentation

event()

def event

(

self

)

And check all the ranks

Definition at line 52 of file best_candidate_selection.py.

    def event(self):
        """And check all the ranks"""
        # make a list of all the values and a dict of all the extra infos
        px = []
        py = []
        einfo = defaultdict(list)
        for particle in self.plist:
            px.append(particle.getPx())
            py.append(particle.getPy())
            # get all names of existing extra infos but convert to a native list of python strings to avoid
            # possible crashes if the std::vector returned by the particle goes out of scope
            names = [str(n) for n in particle.getExtraInfoNames()]
            for n in names:
                einfo[n].append(particle.getExtraInfo(n))
 
        # check the default name is set correctly if we don't specify an output variable
        print(list(einfo.keys()))
        assert 'M_rank' in einfo.keys(), "Default name is not as expected"
 
        # Now determine the correct ranks if multiple values are allowed:
        # create a dictionary which will be value -> rank for all unique values
        # in theory we just need loop over the sorted(set(values)) but we have
        # special treatment for nans which should go always to the end of the
        # list so sort with a special key that replaces nan by inf or -inf
        # depending on sort order
        px_value_ranks = {v: i for i, v in enumerate(sorted(set(px), reverse=True,
                                                            key=lambda v: -math.inf if math.isnan(v) else v), 1)}
        py_value_ranks = {v: i for i, v in enumerate(sorted(set(py),
                                                            key=lambda v: math.inf if math.isnan(v) else v), 1)}
 
        # Ok, test if the rank from extra info actually corresponds to what we
        # want
        for v, r in zip(px, einfo["px_high_multi"]):
            print(f"Value: {v}, rank: {r}, should be: {px_value_ranks[v]}")
            assert r == px_value_ranks[v], "Rank is not correct"
 
        for v, r in zip(py, einfo["py_low_multi"]):
            print(f"Value: {v}, rank: {r}, should be: {py_value_ranks[v]}")
            assert r == py_value_ranks[v], "Rank is not correct"
 
        # so we checked multiRank=True. But for multiRank=False this is more
        # complicated because ranking a second time will destroy the order
        # of the previous sorts. But we can at least check if all the ranks
        # form a range from 1..n if we sort them
        simple_range = list(range(len(px)))
        px_single_ranks = list(sorted(int(r) - 1 for r in einfo["px_high_single"]))
        assert simple_range == px_single_ranks, "sorted ranks don't form a range from 1..n"
        # but the second two rankings are on the same variable in the same
        # order so they need to keep the order stable. so for py_low_single the
        # ranks need to be the range without sorting
        py_single_ranks = list(int(r) - 1 for r in einfo["py_low_single"])
        assert simple_range == py_single_ranks, "ranks don't form a range from 1..n"
 
 

initialize()

def initialize

(

self

)

Create particle list object

Definition at line 47 of file best_candidate_selection.py.

    def initialize(self):
        """Create particle list object"""
        
        self.plist = Belle2.PyStoreObj("e-")
 

Member Data Documentation

plist

plist

particle list object

Definition at line 50 of file best_candidate_selection.py.

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The documentation for this class was generated from the following file:

• analysis/tests/best_candidate_selection.py