Releases: austin-hoover/ment
Releases · austin-hoover/ment
v1.1.5
Small changes to examples.
Full Changelog: v1.1.4...v1.1.5
v1.1.4
- Add 6D reconstruction example from paper "N-dimensional maximum-entropy tomography via particle sampling".
- Add traditional 2D CT example with comparisons to FBP and SART on high-resolution images.
- Automatically normalize projections passed to MENT.
- Fix histogram fractional threshold.
- Enforce learning rate between 0 and 1 in Gauss-Seidel updates
- Create new integration method in which the density is evaluated on the entire N-dimensional grid and summed over the integration axes. This is a faster method that can work well in 2D/3D. The method can be turned on by setting
integration_loop=False
inment.MENT
class.
Full Changelog: v1.1.3...v1.1.4
v1.1.3
What's Changed
- Example 4D nonlinear ring example in #8
- Add 4D SNS example in #9
- Improved covariance matrix fitter
- Improved Metropolis Hastings sampler debugger
Full Changelog: v1.1.2...v1.1.3
v1.1.2
v1.1.1
Fix bug when initializing MENT with no arguments.
v1.1.0
- Added new prior
UniformSphericalPrior
and added truncate option to Gaussian prior. - Cleaned up MCMC sampler, added noise option, added documentation
- Added
sample
, andcov
methods toHistogramND
class. - Added
sample
, andstd
methods toHistogramND
class. - Added
CovFitter
class to fit ND covariance matrices to measurements using evolutionary optimization. - Added longitudinal phase space tomography example using PyORBIT.
- Fixed a few bugs.
Full Changelog: v1.0.2...v1.1.0
v1.0.2
Version