Releases: zfit/phasespace
Releases · zfit/phasespace
Fix optional dependency
vector
was accidentially imported and therefore required.
Vector support and Python 3.12
1.10.2 (16 Apr 2024)
Add support for Python 3.12, drop support for 3.8
Major Features and Improvements
- integrating
vector <https://vector.readthedocs.io/en/latest/index.html>
_ support forgenerate
:boost_to
can be a Momentum Lorentz vector and return the boosted particles as a vector usingas_vectors=True
.
Requirement changes
Upgrade to TensorFlow > 0.16
Support Python 3.11
Add support for Python 3.11, drop support for 3.7
Pin and upgrade dependencies
Requirement changes
- upgrade to zfit >= 0.10.0 and zfit-physics >= 0.3.0
- pinning uproot and awkward to ~4 and ~1, respectively
Python 3.10 and TensorFlow > 2.7
Upgraded Python and TensorFlow version.
Added tf
and tensorflow
extra to requirements. If you intend to use
phasespace with TensorFlow in the future (and not another backend like numpy or JAX),
make sure to always install with phasespace[tf]
.
Requirement changes
- upgrade to TensorFlow >= 2.7
- Python from 3.7 to 3.10 is now supported
1.6.0
- Improved GenMultiDecay to have better control on the decay mass of non-stable particles.
- Added a
particle_model_map
argument to theGenMultiDecay
class. This is a
dict where the key is a particle name and the value is a mass function name.
The feature can be seen in the
GenMultiDecay Tutorial <https://github.com/zfit/phasespace/blob/master/docs/GenMultiDecay_Tutorial.ipynb>
_.
1.5.0
New feature allows to build a DecayChain using decaylanguage and generating with phasespace
What's Changed
- DecayLanguage compatibility by @simonthor in #63
- drop Python 3.6 support by @jonas-eschle in #69
Full Changelog: 1.4.2...1.5.0
Allow TensorFlow 2.7
What's Changed
- README - fix charge in GenParticle example by @eduardo-rodrigues in #61
- build: support TF 2.7 by @redeboer in #66
Python 3.9 and TF 2.5 support
Major Features and Improvements
- Support Python 3.9
- Support TensorFlow 2.5
- improved compilation in tf.functions, use of XLA where applicable
- developer: modernization of setup, CI and more
Thanks
- Remco de Boer for many commits and cleanups
Eager execution and deterministic behavior
Major Features and Improvements
- Python 3.8 support
- Allow eager execution by setting with
tf.config.run_functions_eagerly(True)
or the environment variable "PHASESPACE_EAGER" - Deterministic random number generation via seed
ortf.random.Generator
instance
Behavioral changes
Bug fixes and small changes
Requirement changes
- tighten TensorFlow to 2.3/2.4
- tighten TensorFlow Probability to 0.11/0.12
Thanks
- Remco de Boer and Stefan Pflüger for discussions on random number genration