v0.8.0

Internal changes:

• Dropped legacy Python 2 support. MadMiner now only supports Python 3.6+.
• Replace string templating to make use of Python 3.6 f-strings.
• Fixed typos and doc-strings inconsistencies throughout the codebase.

For more information: #438

v0.7.6

New features:

• Prototype implementation of joint score computations with finite differences (with MadMiner.finite_differences())

Bug fixes:

• Fixed event loading breaking with h5py version 3.0

Internal changes:

• Improved platform independence by using the gzip module rather than calling the gunzip program

Documentation:

• New tutorial notebook for the finite difference setup

v0.7.5

New features:

• New keyword order in MadMiner.run(), which can be set to 'nlo' to set the systematics card in a way compatible with NLO event generation (which remains not really supported for now)
• Preliminary implementation of the quadratic model proposed by https://arxiv.org/abs/2007.10356

Bug fixes:

• Fixed a critical bug in the morphing-aware likelihood ratio estimator

v0.7.4

Bug fixes

• Fixed a bug in the setup.py introduced in v0.7.3, see #432

v0.7.3

Internal changes:

• Disentangled and cleaned up the dependencies. pip install madminer will now only install the dependencies that are necessary for the core library, not the additional dependencies used in the examples or documentation. New options like pip install madminer[examples] can be used to install these.

v0.7.2

API changes:

• Improved the support for Python 2 (a necessary evil for MadGraph): in the MadMiner.run() functions, using python2_override=True without providing the keyword initial_command will now lead to the Python 2 executable being prepended to the Python path. See #423.

Documentation:

• Updated docstrings, see #420.

We're very happy to welcome our new contributor @Sinclert, who initiated and implemented both of these fixes!

v0.7.1

Bug fixes:

• Various small bug fixes.

Internal changes:

• Refactoring the code structure, moving to more submodules. The API and functionality is unchanged. One can now directly import from the madminer namespace, e.g. as from madminer import MadMiner (but the old from madminer.core import MadMiner will still work).

v0.7.0

New features:

• New madminer.likelihood class will let the user define more powerful likelihood functions, construct a profile likelihood, and fit with more flexibility.

Documentation:

• Updated tutorial notebooks.

v0.6.4

New features:

• New Fisher information geometry functionality in the madminer.fisherinformation.InformationGeometry class.
• The Fisher information can now be computed from likelihood ratio estimators as well.
• Added early_stopping_patience keyword to ML training functions.

Bug fixes:

• Fixed a bug in DelphesReader.

Documentation:

• Updated and fixed tutorials.

v0.6.3

New features:

• Morphing-aware likelihood ratio estimators. See https://arxiv.org/abs/1805.00020 for a description. Implemented in madminer.ml.MorphingAwareRatioEstimator.
• Gradient clipping can now be set with the keyword clip_gradient in the estimator train() functions.