pre-commit changes

src/_ext.cpp

@@ -1645,7 +1645,7 @@ PYBIND11_MODULE(_ext, m) {
  [](const output_wrapper ow, const int n_jets = 1, double beta = 0, double symmetry_cut = 0.1,
  std::string symmetry_measure = "scalar_z", double R0 = 0.8, std::string recursion_choice = "larger_pt",
  /*const FunctionOfPseudoJet<PseudoJet> * subtractor = 0,*/ double mu_cut = std::numeric_limits<double>::infinity()){
- 
+
  auto css = ow.cse;
  std::vector<double> consts_groomed_px;
  std::vector<double> consts_groomed_py;

src/fastjet/__init__.py

@@ -369,11 +369,17 @@ def exclusive_jets_constituents(self, njets: int = 10) -> ak.Array:
  """
 
  raise AssertionError()
- 
+
  def exclusive_jets_softdrop_grooming(
- self, njets: int = 1, beta: int = 0, symmetry_cut: float = 0.1, symmetry_measure="scalar_z", R0: float = 0.8, recursion_choice="larger_pt",
- #subtractor: int = 0,
- mu_cut: float = float('inf'),
+ self,
+ njets: int = 1,
+ beta: int = 0,
+ symmetry_cut: float = 0.1,
+ symmetry_measure="scalar_z",
+ R0: float = 0.8,
+ recursion_choice="larger_pt",
+ # subtractor: int = 0,
+ mu_cut: float = float("inf"),
  ) -> ak.Array:
  """Performs softdrop pruning on jets.
  Args:
@@ -385,11 +391,19 @@ def exclusive_jets_softdrop_grooming(
  recursion_choice: Which recursion choice to use, found in RecursiveSymmetryCutBase.hh
  subtractor: an optional pointer to a pileup subtractor (ignored if zero)
  Returns:
- Returns an array of values from the jet after it has been groomed by softdrop."""
+ Returns an array of values from the jet after it has been groomed by softdrop.
+ """
  raise AssertionError()
 
  def exclusive_jets_energy_correlator(
- self, njets: int = 1, beta: int = 1, npoint: int = 0, angles: int = -1, alpha=0, func="generalized", normalized=True,
+ self,
+ njets: int = 1,
+ beta: int = 1,
+ npoint: int = 0,
+ angles: int = -1,
+ alpha=0,
+ func="generalized",
+ normalized=True,
  ) -> ak.Array:
  """Returns the energy correlator of each exclusive jet.
 

src/fastjet/_generalevent.py

@@ -438,53 +438,89 @@ def exclusive_jets_constituent_index(self, njets):
  )
  res = ak.Array(self._replace_multi())
  return res
- 
+
  def exclusive_jets_softdrop_grooming(
- self, njets=1, beta = 0.0, symmetry_cut = 0.1, symmetry_measure = "scalar_z", R0 = 0.8, recursion_choice = "larger_pt",
- #subtractor = 0, 
- mu_cut = float('inf'),
+ self,
+ njets=1,
+ beta=0.0,
+ symmetry_cut=0.1,
+ symmetry_measure="scalar_z",
+ R0=0.8,
+ recursion_choice="larger_pt",
+ # subtractor = 0,
+ mu_cut=float("inf"),
  ):
  if njets <= 0:
  raise ValueError("Njets cannot be <= 0")
- 
+
  self._out = []
  self._input_flag = 0
  for i in range(len(self._clusterable_level)):
  np_results = self._results[i].to_numpy_softdrop_grooming(
- njets, beta, symmetry_cut, symmetry_measure, R0, recursion_choice, #subtractor, 
- mu_cut,
- )
+ njets,
+ beta,
+ symmetry_cut,
+ symmetry_measure,
+ R0,
+ recursion_choice, # subtractor,
+ mu_cut,
+ )
 
- px = ak.unflatten(ak.Array(ak.contents.NumpyArray(np_results[0])), ak.Array(ak.contents.NumpyArray(np_results[4])), highlevel=False)
- py = ak.unflatten(ak.Array(ak.contents.NumpyArray(np_results[1])), ak.Array(ak.contents.NumpyArray(np_results[4])), highlevel=False)
- pz = ak.unflatten(ak.Array(ak.contents.NumpyArray(np_results[2])), ak.Array(ak.contents.NumpyArray(np_results[4])), highlevel=False)
- E = ak.unflatten(ak.Array(ak.contents.NumpyArray(np_results[3])), ak.Array(ak.contents.NumpyArray(np_results[4])), highlevel=False)
+ px = ak.unflatten(
+ ak.Array(ak.contents.NumpyArray(np_results[0])),
+ ak.Array(ak.contents.NumpyArray(np_results[4])),
+ highlevel=False,
+ )
+ py = ak.unflatten(
+ ak.Array(ak.contents.NumpyArray(np_results[1])),
+ ak.Array(ak.contents.NumpyArray(np_results[4])),
+ highlevel=False,
+ )
+ pz = ak.unflatten(
+ ak.Array(ak.contents.NumpyArray(np_results[2])),
+ ak.Array(ak.contents.NumpyArray(np_results[4])),
+ highlevel=False,
+ )
+ E = ak.unflatten(
+ ak.Array(ak.contents.NumpyArray(np_results[3])),
+ ak.Array(ak.contents.NumpyArray(np_results[4])),
+ highlevel=False,
+ )
  jetpt = ak.Array(ak.contents.NumpyArray(np_results[5]))
  jeteta = ak.Array(ak.contents.NumpyArray(np_results[6]))
  jetphi = ak.Array(ak.contents.NumpyArray(np_results[7]))
  jetmass = ak.Array(ak.contents.NumpyArray(np_results[8]))
  jetE = ak.Array(ak.contents.NumpyArray(np_results[9]))
  jetpz = ak.Array(ak.contents.NumpyArray(np_results[10]))
 
- self._out.append(ak.zip({
- "constituents":
- ak.zip(
- {"px": px, "py": py, "pz": pz, "E": E}, depth_limit=2),
- "msoftdrop": jetmass,
- "ptsoftdrop": jetpt,
- "etasoftdrop": jeteta,
- "phisoftdrop": jetphi,
- "Esoftdrop": jetE,
- "pzsoftdrop": jetpz,},
- depth_limit=1
+ self._out.append(
+ ak.zip(
+ {
+ "constituents": ak.zip(
+ {"px": px, "py": py, "pz": pz, "E": E}, depth_limit=2
+ ),
+ "msoftdrop": jetmass,
+ "ptsoftdrop": jetpt,
+ "etasoftdrop": jeteta,
+ "phisoftdrop": jetphi,
+ "Esoftdrop": jetE,
+ "pzsoftdrop": jetpz,
+ },
+ depth_limit=1,
  )
  )
  res = ak.Array(self._replace_multi())
  return res
 
-
  def exclusive_jets_energy_correlator(
- self, njets=1, n_point=0, angles: int = -1, beta=1, alpha=0, func="generalized", normalized=True,
+ self,
+ njets=1,
+ n_point=0,
+ angles: int = -1,
+ beta=1,
+ alpha=0,
+ func="generalized",
+ normalized=True,
  ):
  if njets <= 0:
  raise ValueError("Njets cannot be <= 0")

src/fastjet/_multievent.py

@@ -214,52 +214,94 @@ def exclusive_jets_constituent_index(self, njets):
  )
  out = ak.Array(ak.contents.ListOffsetArray(ak.index.Index64(off), out.layout))
  return out
- 
+
  def exclusive_jets_softdrop_grooming(
- self, njets=1, beta = 0.0, symmetry_cut = 0.1, symmetry_measure = "scalar_z", R0 = 0.8, recursion_choice = "larger_pt",
- #subtractor = 0, 
- mu_cut = float('inf'),
+ self,
+ njets=1,
+ beta=0.0,
+ symmetry_cut=0.1,
+ symmetry_measure="scalar_z",
+ R0=0.8,
+ recursion_choice="larger_pt",
+ # subtractor = 0,
+ mu_cut=float("inf"),
  ):
  if njets <= 0:
  raise ValueError("Njets cannot be <= 0")
  np_results = self._results.to_numpy_softdrop_grooming(
- njets, beta, symmetry_cut, symmetry_measure, R0, recursion_choice, #subtractor, 
+ njets,
+ beta,
+ symmetry_cut,
+ symmetry_measure,
+ R0,
+ recursion_choice, # subtractor,
  mu_cut,
  )
 
- px = ak.unflatten(ak.Array(ak.contents.NumpyArray(np_results[0])), ak.Array(ak.contents.NumpyArray(np_results[4])), highlevel=False)
- py = ak.unflatten(ak.Array(ak.contents.NumpyArray(np_results[1])), ak.Array(ak.contents.NumpyArray(np_results[4])), highlevel=False)
- pz = ak.unflatten(ak.Array(ak.contents.NumpyArray(np_results[2])), ak.Array(ak.contents.NumpyArray(np_results[4])), highlevel=False)
- E = ak.unflatten(ak.Array(ak.contents.NumpyArray(np_results[3])), ak.Array(ak.contents.NumpyArray(np_results[4])), highlevel=False)
+ px = ak.unflatten(
+ ak.Array(ak.contents.NumpyArray(np_results[0])),
+ ak.Array(ak.contents.NumpyArray(np_results[4])),
+ highlevel=False,
+ )
+ py = ak.unflatten(
+ ak.Array(ak.contents.NumpyArray(np_results[1])),
+ ak.Array(ak.contents.NumpyArray(np_results[4])),
+ highlevel=False,
+ )
+ pz = ak.unflatten(
+ ak.Array(ak.contents.NumpyArray(np_results[2])),
+ ak.Array(ak.contents.NumpyArray(np_results[4])),
+ highlevel=False,
+ )
+ E = ak.unflatten(
+ ak.Array(ak.contents.NumpyArray(np_results[3])),
+ ak.Array(ak.contents.NumpyArray(np_results[4])),
+ highlevel=False,
+ )
  jetpt = ak.Array(ak.contents.NumpyArray(np_results[5]))
  jeteta = ak.Array(ak.contents.NumpyArray(np_results[6]))
  jetphi = ak.Array(ak.contents.NumpyArray(np_results[7]))
  jetmass = ak.Array(ak.contents.NumpyArray(np_results[8]))
  jetE = ak.Array(ak.contents.NumpyArray(np_results[9]))
  jetpz = ak.Array(ak.contents.NumpyArray(np_results[10]))
 
- out = ak.zip({
- "constituents":
- ak.zip(
- {"px": px, "py": py, "pz": pz, "E": E}, depth_limit=2),
- "msoftdrop": jetmass,
- "ptsoftdrop": jetpt,
- "etasoftdrop": jeteta,
- "phisoftdrop": jetphi,
- "Esoftdrop": jetE,
- "pzsoftdrop": jetpz,},
- depth_limit=1
+ out = ak.zip(
+ {
+ "constituents": ak.zip(
+ {"px": px, "py": py, "pz": pz, "E": E}, depth_limit=2
+ ),
+ "msoftdrop": jetmass,
+ "ptsoftdrop": jetpt,
+ "etasoftdrop": jeteta,
+ "phisoftdrop": jetphi,
+ "Esoftdrop": jetE,
+ "pzsoftdrop": jetpz,
+ },
+ depth_limit=1,
  )
 
  return out
 
  def exclusive_jets_energy_correlator(
- self, njets=1, beta=1, npoint=0, angles=-1, alpha=0, func="generalized", normalized=True,
+ self,
+ njets=1,
+ beta=1,
+ npoint=0,
+ angles=-1,
+ alpha=0,
+ func="generalized",
+ normalized=True,
  ):
  if njets <= 0:
  raise ValueError("Njets cannot be <= 0")
  np_results = self._results.to_numpy_energy_correlators(
- njets, beta, npoint, angles, alpha, func, normalized,
+ njets,
+ beta,
+ npoint,
+ angles,
+ alpha,
+ func,
+ normalized,
  )
  out = ak.Array(ak.contents.NumpyArray(np_results))
  return out

src/fastjet/_pyjet.py

@@ -145,22 +145,46 @@ def exclusive_jets_constituent_index(self, njets=10):
 
  def exclusive_jets_constituents(self, njets=10):
  return self._internalrep.exclusive_jets_constituents(njets)
- 
+
  def exclusive_jets_softdrop_grooming(
- self, njets=1, beta = 0.0, symmetry_cut = 0.1, symmetry_measure = "scalar_z", R0 = 0.8, recursion_choice = "larger_pt",
- #subtractor = 0, 
- mu_cut = float('inf'),
+ self,
+ njets=1,
+ beta=0.0,
+ symmetry_cut=0.1,
+ symmetry_measure="scalar_z",
+ R0=0.8,
+ recursion_choice="larger_pt",
+ # subtractor = 0,
+ mu_cut=float("inf"),
  ):
  return self._internalrep.exclusive_jets_softdrop_grooming(
- njets, beta, symmetry_cut, symmetry_measure, R0, recursion_choice, #subtractor, 
+ njets,
+ beta,
+ symmetry_cut,
+ symmetry_measure,
+ R0,
+ recursion_choice, # subtractor,
  mu_cut,
  )
 
  def exclusive_jets_energy_correlator(
- self, njets=1, beta=1, npoint=0, angles=-1, alpha=0, func="generalized", normalized=True
+ self,
+ njets=1,
+ beta=1,
+ npoint=0,
+ angles=-1,
+ alpha=0,
+ func="generalized",
+ normalized=True,
  ):
  return self._internalrep.exclusive_jets_energy_correlator(
- njets, beta, npoint, angles, alpha, func, normalized,
+ njets,
+ beta,
+ npoint,
+ angles,
+ alpha,
+ func,
+ normalized,
  )
 
  def exclusive_jets_lund_declusterings(self, njets=10):
@@ -445,25 +469,38 @@ def exclusive_jets_constituents(self, njets=10):
  return _dak_dispatch(self, "exclusive_jets_constituents", njets=njets)
 
  def exclusive_jets_softdrop_grooming(
- self, njets=1, beta = 0.0, symmetry_cut = 0.1, symmetry_measure = "scalar_z", R0 = 0.8, recursion_choice = "larger_pt",
- #subtractor = 0, 
- mu_cut = float('inf'),
+ self,
+ njets=1,
+ beta=0.0,
+ symmetry_cut=0.1,
+ symmetry_measure="scalar_z",
+ R0=0.8,
+ recursion_choice="larger_pt",
+ # subtractor = 0,
+ mu_cut=float("inf"),
  ):
  return _dak_dispatch(
  self,
  "exclusive_jets_softdrop_grooming",
- njets=njets, 
- beta=beta, 
- symmetry_cut=symmetry_cut, 
- symmetry_measure=symmetry_measure, 
- R0=R0, 
- recursion_choice=recursion_choice, 
- #subtractor=subtractor, 
+ njets=njets,
+ beta=beta,
+ symmetry_cut=symmetry_cut,
+ symmetry_measure=symmetry_measure,
+ R0=R0,
+ recursion_choice=recursion_choice,
+ # subtractor=subtractor,
  mu_cut=mu_cut,
  )
 
  def exclusive_jets_energy_correlator(
- self, njets=1, beta=1, npoint=0, angles=-1, alpha=0, func="generalized", normalized=False,
+ self,
+ njets=1,
+ beta=1,
+ npoint=0,
+ angles=-1,
+ alpha=0,
+ func="generalized",
+ normalized=False,
  ):
  return _dak_dispatch(
  self,