Ejemplo n.º 1
0
    def test_kernel_set_get_in_offsets(self):
        print("kernel_set_get_in_offsets")
        dataset = self.dataset
        muons = dataset.structs["Muon"][0]
        arr = muons.pt.copy()
        sel_ev = self.NUMPY_LIB.ones(muons.numevents(),
                                     dtype=self.NUMPY_LIB.bool)
        sel_mu = self.NUMPY_LIB.ones(muons.numobjects(),
                                     dtype=self.NUMPY_LIB.bool)
        inds = self.NUMPY_LIB.zeros(muons.numevents(),
                                    dtype=self.NUMPY_LIB.int8)

        #set the pt of the first muon in each event to 1
        inds[:] = 0
        target = self.NUMPY_LIB.ones(muons.numevents(), dtype=muons.pt.dtype)

        kernels.set_in_offsets(self.ha, muons.offsets, arr, inds, target,
                               sel_ev, sel_mu)

        print("checking set_in_offsets")
        asnp = self.NUMPY_LIB.asnumpy
        self.assertTrue(
            verify_set_in_offsets(asnp(muons.offsets), asnp(inds), asnp(arr),
                                  asnp(target)))

        print("checking get_in_offsets")
        z = kernels.get_in_offsets(self.ha, muons.offsets, arr, inds, sel_ev,
                                   sel_mu)

        self.assertTrue(
            verify_get_in_offsets(asnp(muons.offsets), asnp(inds), asnp(arr),
                                  asnp(target), asnp(z)))

        return muons.numevents()
Ejemplo n.º 2
0
def analyze_data_function(data, parameters):
    ret = Results()

    num_events = data["num_events"]
    muons = data["Muon"]
    mu_pt = nplib.sqrt(muons.Px**2 + muons.Py**2)
    muons.attrs_data["pt"] = mu_pt

    mask_events = nplib.ones(muons.numevents(), dtype=nplib.bool)
    mask_muons_passing_pt = muons.pt > parameters["muons_ptcut"]
    num_muons_event = kernels.sum_in_offsets(backend, muons.offsets,
                                             mask_muons_passing_pt,
                                             mask_events, muons.masks["all"],
                                             nplib.int8)
    mask_events_dimuon = num_muons_event == 2

    #get the leading muon pt in events that have exactly two muons
    inds = nplib.zeros(num_events, dtype=nplib.int32)
    leading_muon_pt = kernels.get_in_offsets(backend, muons.offsets, muons.pt,
                                             inds, mask_events_dimuon,
                                             mask_muons_passing_pt)

    #compute a weighted histogram
    weights = nplib.ones(num_events, dtype=nplib.float32)
    bins = nplib.linspace(0, 300, 101, dtype=nplib.float32)
    hist_muons_pt = Histogram(*kernels.histogram_from_vector(
        backend, leading_muon_pt[mask_events_dimuon],
        weights[mask_events_dimuon], bins))

    #save it to the output
    ret["hist_leading_muon_pt"] = hist_muons_pt
    return ret
Ejemplo n.º 3
0
def test_kernel_get_in_offsets(dataset):
    muons = dataset.structs["Muon"][0]
    sel_ev = nplib.ones(muons.numevents(), dtype=nplib.bool)
    sel_mu = nplib.ones(muons.numobjects(), dtype=nplib.bool)
    inds = nplib.zeros(muons.numevents(), dtype=nplib.int8)
    inds[:] = 0
    z = kernels.get_in_offsets(backend, muons.offsets, muons.pt, inds, sel_ev,
                               sel_mu)
Ejemplo n.º 4
0
 def test_kernel_get_in_offsets(self):
     dataset = self.dataset
     muons = dataset.structs["Muon"][0]
     sel_ev = self.NUMPY_LIB.ones(muons.numevents(),
                                  dtype=self.NUMPY_LIB.bool)
     sel_mu = self.NUMPY_LIB.ones(muons.numobjects(),
                                  dtype=self.NUMPY_LIB.bool)
     inds = self.NUMPY_LIB.zeros(muons.numevents(),
                                 dtype=self.NUMPY_LIB.int8)
     inds[:] = 0
     z = kernels.get_in_offsets(self.ha, muons.offsets, muons.pt, inds,
                                sel_ev, sel_mu)
     return muons.numevents()