Commit e6d55f5c authored by Benoit Martin's avatar Benoit Martin

Merge branch '24_version_file_not_found' into ci

parents 3d88d9cc 5560f266
......@@ -4,8 +4,10 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
## [4.0.0] - 2018-06-11
## [4.0.0] - 2018-06-14
### Added
- Bugfix: version file not found. issue #24
- Easy install with `conda install -c pytorch -c conda-forge -c anaconda -c aramislab deformetrica`, without any manual compilation.
- All existing deformetrica functionalities now work with 2d or 3d gray level images.
- A L-BFGS optimization method can now be used for registration, regression, deterministic and bayesian atlases.
......
### Deformetrica 4.0.0
# Deformetrica 4.0.0
- Installation: `conda install -c pytorch -c conda-forge -c anaconda -c aramislab deformetrica` (Mac OS X or Linux distributions)
- Documentation: [wiki](https://gitlab.icm-institute.org/aramislab/deformetrica/wikis/home)
- Website: [www.deformetrica.org](http://www.deformetrica.org/)
Website: [www.deformetrica.org](http://www.deformetrica.org/)
### Archived repositories
**Deformetrica** is a software for the statistical analysis of 2D and 3D shape data. It essentially computes deformations of the 2D or 3D ambient space, which, in turn, warp any object embedded in this space, whether this object is a curve, a surface, a structured or unstructured set of points, an image, or any combination of them.
_Deformetrica_ comes with three main applications:
- **registration** : estimates the best possible deformation between two sets of objects;
- **atlas construction** : estimates an average object configuration from a collection of object sets, and the deformations from this average to each sample in the collection;
- **geodesic regression** : estimates an object time-series constrained to match as closely as possible a set of observations indexed by time.
_Deformetrica_ has very little requirements about the data it can deal with. In particular, it does __not__ require point correspondence between objects!
## Install
- **Requirements**: [Anaconda 3](https://www.anaconda.com/download), Linux or Mac OS X distributions
- **Best practice**: `conda env create -n deformetrica && source activate deformetrica`
- **Conda install**: `conda install -c pytorch -c conda-forge -c anaconda -c aramislab deformetrica`
- **Run** an [example](https://gitlab.icm-institute.org/aramislab/deformetrica/tree/master/examples): `deformetrica model.xml data_set.xml optimization_parameters.xml`
- **Documentation**: [wiki](https://gitlab.icm-institute.org/aramislab/deformetrica/wikis/home)
## Community
- **Need help?** Ask the [Deformetrica Google group](https://groups.google.com/forum/#!forum/deformetrica).
- Spotted an **issue**? Have a **feature request**? Let us know in the (dedicated Gitlab section)[https://gitlab.icm-institute.org/aramislab/deformetrica/issues].
## References
Deformetrica relies on a control-points-based instance of the Large Deformation Diffeomorphic Metric Mapping framework, introduced in [\[Durrleman et al. 2014\]](https://linkinghub.elsevier.com/retrieve/pii/S1053811914005205). Are fully described in this article the **shooting**, **registration**, and **deterministic atlas** applications. Equipped with those fundamental building blocks, additional applications have been successively developed:
- the bayesian atlas application, described in [\[Gori et al. 2017\]](https://hal.archives-ouvertes.fr/hal-01359423/);
- the geodesic regression application, described in [\[Fishbaugh et al. 2017\]](https://www.medicalimageanalysisjournal.com/article/S1361-8415(17)30044-0/fulltext);
- the parallel transport application, described in [\[Louis et al. 2018\]](https://www.researchgate.net/publication/319136479_Parallel_transport_in_shape_analysis_a_scalable_numerical_scheme);
- the longitudinal atlas application, described in [\[Bône et al. 2018\]](https://www.researchgate.net/publication/324037371_Learning_distributions_of_shape_trajectories_from_longitudinal_datasets_a_hierarchical_model_on_a_manifold_of_diffeomorphisms).
# Archived repositories
- Deformetrica 3: [deformetrica-legacy2](https://gitlab.icm-institute.org/aramislab/deformetrica-legacy2)
- Deformetrica 2.1: [deformetrica-legacy](https://gitlab.icm-institute.org/aramislab/deformetrica-legacy)
......@@ -14,7 +14,7 @@ except ImportError: # for pip <= 9.0.3
setup(
name='Deformetrica',
version=open('VERSION').read(),
version=open('VERSION', encoding='utf-8').read(),
url='http://www.deformetrica.org',
description='Software for the statistical analysis of 2D and 3D shape data.',
long_description=open('README.md', encoding='utf-8').read(),
......@@ -32,7 +32,7 @@ setup(
},
classifiers=[
'Framework :: Deformetrica',
'Development Status :: 4.0.0 - dev',
'Development Status :: 4.0.1',
'Environment :: Console',
'Operating System :: OS Independent',
'Programming Language :: Python',
......
......@@ -18,15 +18,6 @@ from launch.compute_shooting import run_shooting
from support.utilities.general_settings import Settings
def info():
version = open(os.path.dirname(os.path.realpath(__file__)) + '/../VERSION').read()
return """
##############################
##### Deformetrica {version} #####
##############################
""".format(version=version)
def main():
import logging
logger = logging.getLogger(__name__)
......@@ -60,9 +51,6 @@ def main():
logger.debug('Using verbosity level: ' + args.verbosity)
logging.basicConfig(level=log_level, format=logger_format)
# Basic info printing
logger.info(info())
"""
Read xml files, set general settings, and call the adapted function.
"""
......
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