[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -24,7 +24,7 @@ repos:
       - id: check-ast
 
   - repo: https://github.com/PyCQA/docformatter
-    rev: v1.7.7
+    rev: v1.7.8
     hooks:
       - id: docformatter
         args:
@@ -42,7 +42,7 @@ repos:
       - id: rst-directive-colons
 
   - repo: https://github.com/PyCQA/isort
-    rev: 8.0.1
+    rev: 9.0.2
     hooks:
       - id: isort
 
@@ -81,7 +81,7 @@ repos:
       - id: nbstripout
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.15.9"
+    rev: "v0.16.10"
     hooks:
       - id: ruff
         types_or: [ python, pyi, jupyter ]

benchmark/bench_phasespace.py

@@ -11,6 +11,7 @@
 from timeit import default_timer
 
 import tensorflow as tf
+
 from phasespace import phasespace
 
 sys.path.append(os.path.dirname(__file__))

data/download_test_files.py

@@ -18,19 +18,19 @@ def _is_silent():
 FILE_URLS = [
     (
         "B2K1Gamma_RapidSim_7TeV_K1KstarNonResonant_Tree.root",
-        "https://cernbox.cern.ch/remote.php/dav/public-files/8mN10X8U7VGfaRc/B2K1Gamma_RapidSim_7TeV_K1KstarNonResonant_Tree.root",  # noqa: E501
+        "https://cernbox.cern.ch/remote.php/dav/public-files/8mN10X8U7VGfaRc/B2K1Gamma_RapidSim_7TeV_K1KstarNonResonant_Tree.root",
     ),
     (
         "B2K1Gamma_RapidSim_7TeV_Tree.root",
-        "https://cernbox.cern.ch/remote.php/dav/public-files/pr3aM8n2hPT4Pag/B2K1Gamma_RapidSim_7TeV_Tree.root",  # noqa: E501
+        "https://cernbox.cern.ch/remote.php/dav/public-files/pr3aM8n2hPT4Pag/B2K1Gamma_RapidSim_7TeV_Tree.root",
     ),
     (
         "B2KstGamma_RapidSim_7TeV_KstarNonResonant_Tree.root",
-        "https://cernbox.cern.ch/remote.php/dav/public-files/QuP2cHeISTTSLVv/B2KstGamma_RapidSim_7TeV_KstarNonResonant_Tree.root",  # noqa: E501
+        "https://cernbox.cern.ch/remote.php/dav/public-files/QuP2cHeISTTSLVv/B2KstGamma_RapidSim_7TeV_KstarNonResonant_Tree.root",
     ),
     (
         "B2KstGamma_RapidSim_7TeV_Tree.root",
-        "https://cernbox.cern.ch/remote.php/dav/public-files/EH5yrCpGko7P7Mc/B2KstGamma_RapidSim_7TeV_Tree.root",  # noqa: E501
+        "https://cernbox.cern.ch/remote.php/dav/public-files/EH5yrCpGko7P7Mc/B2KstGamma_RapidSim_7TeV_Tree.root",
     ),
 ]
 

docs/GenMultiDecay_Tutorial.ipynb

@@ -32,10 +32,10 @@
     "# Import libraries\n",
     "from pprint import pprint\n",
     "\n",
+    "import tensorflow as tf\n",
     "import zfit\n",
+    "from decaylanguage import DecayChain, DecayChainViewer, DecayMode, DecFileParser\n",
     "from particle import Particle\n",
-    "from decaylanguage import DecFileParser, DecayChainViewer, DecayChain, DecayMode\n",
-    "import tensorflow as tf\n",
     "\n",
     "from phasespace.fromdecay import GenMultiDecay"
    ]

docs/conf.py

@@ -30,7 +30,7 @@
 warnings.filterwarnings("ignore")
 
 # Suppress TensorFlow C++ logging to stderr
-import logging  # noqa: E402
+import logging
 
 logging.getLogger("tensorflow").setLevel(logging.ERROR)
 
@@ -43,7 +43,7 @@
 except ImportError:
     pass
 
-import phasespace  # noqa: E402
+import phasespace
 
 # -- General configuration ---------------------------------------------
 

src/phasespace/__init__.py

@@ -13,9 +13,9 @@
 
 __credits__ = ["Jonas Eschle <Jonas.Eschle@cern.ch>"]
 
-__all__ = ["nbody_decay", "GenParticle", "random", "to_vectors", "numpy"]
+__all__ = ["GenParticle", "nbody_decay", "numpy", "random", "to_vectors"]
 
-import tensorflow.experimental.numpy as numpy
+from tensorflow.experimental import numpy
 
 from . import random
 from .phasespace import GenParticle, nbody_decay, to_vectors

src/phasespace/fromdecay/__init__.py

@@ -8,7 +8,7 @@
 
 import sys
 
-from .genmultidecay import GenMultiDecay  # noqa: F401
+from .genmultidecay import GenMultiDecay
 
 try:
     import zfit  # noqa: F401

src/phasespace/fromdecay/genmultidecay.py

@@ -6,6 +6,7 @@
 import tensorflow as tf
 import tensorflow.experimental.numpy as tnp
 from particle import Particle
+
 from phasespace import GenParticle
 
 from .mass_functions import DEFAULT_CONVERTER
@@ -28,9 +29,9 @@ def __init__(self, gen_particles: list[tuple[float, GenParticle]]):
     def from_dict(
         cls,
         dec_dict: dict,
-        mass_converter: dict[str, Callable] = None,
-        tolerance: float = None,
-        particle_model_map: dict[str, str] = None,
+        mass_converter: dict[str, Callable] | None = None,
+        tolerance: float | None = None,
+        particle_model_map: dict[str, str] | None = None,
     ):
         """Create a ``GenMultiDecay`` instance from a dict in the ``DecayLanguage`` package format.
 
@@ -215,7 +216,7 @@ def _unique_name(name: str, preexisting_particles: set[str]) -> str:
     name += " [0]"
     i = 1
     while name in preexisting_particles:
-        name = name[: name.rfind("[")] + f"[{str(i)}]"
+        name = name[: name.rfind("[")] + f"[{i!s}]"
         i += 1
     preexisting_particles.add(name)
     return name
@@ -254,7 +255,7 @@ def _recursively_traverse(
     mass_converter: dict[str, Callable],
     particle_model_map: dict[str, str],
     tolerance: float,
-    preexisting_particles: set[str] = None,
+    preexisting_particles: set[str] | None = None,
 ) -> list[tuple[float, GenParticle]]:
     """Create all possible GenParticles by recursively traversing a dict from DecayLanguage, see Examples.
 

src/phasespace/kinematics.py

@@ -7,6 +7,7 @@
 """Basic kinematics."""
 
 import tensorflow.experimental.numpy as tnp
+
 from phasespace.backend import function, function_jit
 
 

src/phasespace/phasespace.py

@@ -97,9 +97,7 @@ class GenParticle:
             converted to array-like.
     """
 
-    def __init__(
-        self, name: str, mass: Callable | int | float | np.typing.ArrayLike
-    ) -> None:  # noqa
+    def __init__(self, name: str, mass: Callable | float | np.typing.ArrayLike) -> None:
         self.name = name
         self.children = []
         self._mass_val = mass
@@ -185,7 +183,7 @@ def get_mass(
 
     @property
     def has_fixed_mass(self):
-        """bool: Is the mass a callable function?"""
+        """Bool: Is the mass a callable function?"""
         return not callable(self._mass)
 
     def set_children(self, *children):
@@ -222,12 +220,12 @@ def set_children(self, *children):
 
     @property
     def has_children(self):
-        """bool: Does the particle have children?"""
+        """Bool: Does the particle have children?"""
         return bool(self.children)
 
     @property
     def has_grandchildren(self):
-        """bool: Does the particle have grandchildren?"""
+        """Bool: Does the particle have grandchildren?"""
         if not self.children:
             return False
         return any(child.has_children for child in self.children)
@@ -257,14 +255,13 @@ def _preprocess(momentum, n_events):
         if len(momentum.shape) not in (1, 2):
             raise ValueError(f"Bad shape for momentum -> {list(momentum.shape)}")
         # Check compatibility of inputs
-        if len(momentum.shape) == 2:
-            if n_events is not None:
-                momentum_shape = momentum.shape[0]
-                if momentum_shape is None:
-                    momentum_shape = tf.shape(momentum)[0]
-                    momentum_shape = tnp.asarray(momentum_shape, tnp.int64)
-                else:
-                    momentum_shape = tnp.asarray(momentum_shape, dtype=tnp.int64)
+        if len(momentum.shape) == 2 and n_events is not None:
+            momentum_shape = momentum.shape[0]
+            if momentum_shape is None:
+                momentum_shape = tf.shape(momentum)[0]
+                momentum_shape = tnp.asarray(momentum_shape, tnp.int64)
+            else:
+                momentum_shape = tnp.asarray(momentum_shape, dtype=tnp.int64)
                 # tf.assert_equal(
                 #     n_events,
                 #     momentum_shape,
@@ -698,9 +695,8 @@ def generate(
                 f"The number of events requested ({n_events}) doesn't match the boost_to input size "
                 f"of {boost_to.shape}"
             )
-            if n_events is not None:
-                if boost_to.shape[0] not in (n_events, 1):
-                    raise ValueError(message)
+            if n_events is not None and boost_to.shape[0] not in (n_events, 1):
+                raise ValueError(message)
         if not isinstance(n_events, tf.Variable):
             n_events = tnp.asarray(n_events, dtype=tnp.int64)
         weights, weights_max, parts, _ = self._recursive_generate(
@@ -754,7 +750,6 @@ def generate_tensor(
             ValueError: If ``n_events`` and the size of ``boost_to`` don't match.
             See ``GenParticle.generate_unnormalized``.
         """
-
         # Run generation
         raise RuntimeError(
             "This function is removed. Use `generate` which does not return a Tensor as well."
@@ -775,7 +770,9 @@ def __init__(self):
         )
 
 
-def nbody_decay(mass_top: float, masses: list, top_name: str = "", names: list = None):
+def nbody_decay(
+    mass_top: float, masses: list, top_name: str = "", names: list | None = None
+):
     """Shortcut to build an n-body decay of a GenParticle.
 
     If the particle names are not given, the top particle is called 'top' and the
@@ -831,7 +828,7 @@ def to_vectors(particles: dict[str, tf.Tensor]) -> dict[str, vector.Momentum]:
     newparticles = {}
     for name, particle in particles.items():
         px, py, pz, e = np.moveaxis(particle, -1, 0)  # numpy "unstack"
-        newparticles[name] = vector.array(dict(px=px, py=py, pz=pz, energy=e))
+        newparticles[name] = vector.array({"px": px, "py": py, "pz": pz, "energy": e})
     return newparticles
 
 

tests/fromdecay/test_fromdecay.py

@@ -5,6 +5,7 @@
 import pytest
 from decaylanguage import DecayChain, DecayMode
 from numpy.testing import assert_almost_equal
+
 from phasespace.fromdecay import GenMultiDecay
 from phasespace.fromdecay.mass_functions import DEFAULT_CONVERTER
 

tests/fromdecay/test_mass_functions.py

@@ -2,12 +2,13 @@
 
 from collections.abc import Callable
 
-import phasespace.fromdecay.mass_functions as mf
 import pytest
 import tensorflow as tf
 import tensorflow_probability as tfp
 from particle import Particle
 
+import phasespace.fromdecay.mass_functions as mf
+
 _kstarz = Particle.from_evtgen_name("K*0")
 KSTARZ_MASS = _kstarz.mass
 KSTARZ_WIDTH = _kstarz.width

tests/helpers/decays.py

@@ -8,6 +8,7 @@
 
 import tensorflow as tf
 import tensorflow_probability as tfp
+
 from phasespace import GenParticle
 
 # Use RapidSim values (https://github.com/gcowan/RapidSim/blob/master/config/particles.dat)

tests/test_chain.py

@@ -11,11 +11,12 @@
 
 import numpy as np
 import pytest
+
 from phasespace import GenParticle
 
 sys.path.append(os.path.dirname(__file__))
 
-from .helpers import decays  # noqa: E402
+from .helpers import decays
 
 
 def test_name_clashes():

tests/test_generate.py

@@ -10,12 +10,13 @@
 import sys
 
 import numpy as np
-import phasespace
 import pytest
 
+import phasespace
+
 sys.path.append(os.path.dirname(__file__))
 
-from .helpers import decays  # noqa: E402
+from .helpers import decays
 
 B0_MASS = decays.B0_MASS
 PION_MASS = decays.PION_MASS

tests/test_nbody_decay.py

@@ -7,6 +7,7 @@
 """Test n-body decay generator."""
 
 import pytest
+
 from phasespace import nbody_decay
 
 from .helpers import decays

tests/test_physics.py

@@ -25,12 +25,13 @@
 import matplotlib.pyplot as plt
 import tensorflow as tf
 import uproot
+
 from phasespace import phasespace
 
 sys.path.append(os.path.dirname(__file__))
 
-from .helpers import decays, rapidsim  # noqa: E402
-from .helpers.plotting import make_norm_histo  # noqa: E402
+from .helpers import decays, rapidsim
+from .helpers.plotting import make_norm_histo
 
 BASE_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
 PLOT_DIR = os.path.join(BASE_PATH, "tests", "plots")
@@ -191,12 +192,12 @@ def run_kstargamma(input_file, kstar_width, b_at_rest, suffix, use_vector):
         booster = booster.transpose()
         if use_vector:
             booster = vector.array(
-                dict(
-                    px=booster[:, 0],
-                    py=booster[:, 1],
-                    pz=booster[:, 2],
-                    e=booster[:, 3],
-                )
+                {
+                    "px": booster[:, 0],
+                    "py": booster[:, 1],
+                    "pz": booster[:, 2],
+                    "e": booster[:, 3],
+                }
             )
         rapidsim_getter = rapidsim.get_tree
     decay = decays.b0_to_kstar_gamma(kstar_width=kstar_width)

tests/test_random.py

@@ -1,8 +1,9 @@
 import numpy as np
-import phasespace as phsp
 import pytest
 import tensorflow as tf
 
+import phasespace as phsp
+
 
 @pytest.mark.parametrize(
     "seed", [lambda: 15, lambda: tf.random.Generator.from_seed(15)]