NIFTy merge requestshttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests2023-01-13T11:29:43Zhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/832Better Lanczos interface2023-01-13T11:29:43ZGordian EdenhoferBetter Lanczos interfaceWhile this path contains the changes for a working geomap implementation, it is mostly about minor changes to the interface of the Lanczos algorithm.While this path contains the changes for a working geomap implementation, it is mostly about minor changes to the interface of the Lanczos algorithm.Gordian EdenhoferGordian Edenhoferhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/191Better minimizers2017-09-28T01:18:16ZTheo SteiningerBetter minimizershttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/319Better __repr__ for FieldAdapter2019-04-27T17:34:06ZMartin ReineckeBetter __repr__ for FieldAdapterhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/392Boost performance of correlated fields2019-12-06T13:54:20ZPhilipp Arrasparras@mpa-garching.mpg.deBoost performance of correlated fieldsSolves the issue that for correlated fields with several amplitude models `PowerDistributor` calls unnecessarily often `special_add_at` and `bincounts`.
Solve #281Solves the issue that for correlated fields with several amplitude models `PowerDistributor` calls unnecessarily often `special_add_at` and `bincounts`.
Solve #281https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/164Branch master2017-07-14T00:09:08ZTheo SteiningerBranch masterhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/791bugfix2022-09-26T15:02:59ZJakob Knollmuellerbugfix@parras@parrasJakob KnollmuellerJakob Knollmuellerhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/372build in log1p as a nonlinearity instead of as an operator2019-11-15T10:51:19ZReimar H Leikebuild in log1p as a nonlinearity instead of as an operatorI was lazy when I first build the student t energy and only made log1p as an operator, though it should be treated like all other local nonlinearities. This branch is fixing this and should be uncontroversial.I was lazy when I first build the student t energy and only made log1p as an operator, though it should be treated like all other local nonlinearities. This branch is fixing this and should be uncontroversial.Martin ReineckeMartin Reineckehttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/173Byebye fixed point voodoo2017-07-20T22:42:16ZMartin ReineckeByebye fixed point voodooRemoves some fairly complicated code from the code base, since it is unused. The essential parts are only commented out, though, in case we might need it again.Removes some fairly complicated code from the code base, since it is unused. The essential parts are only commented out, though, in case we might need it again.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/194Byebye zerocenter2017-09-28T01:59:36ZMartin ReineckeByebye zerocenterhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/868Cfm demo sliders2024-01-12T18:36:19ZDavid GorbunovCfm demo slidersiPython Notebook visualizing how the typical CFM parameters impact one drawn examplary sample. @gedenhofiPython Notebook visualizing how the typical CFM parameters impact one drawn examplary sample. @gedenhofhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/758CFM: Deprecate complicated dofdex2022-04-12T12:59:22ZPhilipp Arrasparras@mpa-garching.mpg.deCFM: Deprecate complicated dofdex@pfrank @jroth As discussed previously.
This change will help to maintain the correlated field model. Note that no functionality is lost. If users want to use nontrivial dofdexes, they can instantiate the CorrelatedFieldModel multiple t...@pfrank @jroth As discussed previously.
This change will help to maintain the correlated field model. Note that no functionality is lost. If users want to use nontrivial dofdexes, they can instantiate the CorrelatedFieldModel multiple times.
My plan is to remove this deprecation warning and the advanced dofdex features in approx 2 months (if noone objects).
@mtr @veberle @gedenhof what do you think?https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/564Cfm fix2020-08-12T15:14:33ZPhilipp Arrasparras@mpa-garching.mpg.deCfm fixMartin ReineckeMartin Reineckehttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/715Cf zero mode2021-12-08T09:49:45ZJakob RothCf zero modeallow disabling zeromode in cf modelallow disabling zeromode in cf modelhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/126Changed h5py install script to pip.2017-05-16T21:48:52ZTheo SteiningerChanged h5py install script to pip.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/91Changed RGSpace fft smoothing kernel to be Gaussian, added some2017-05-10T22:52:48ZTheo SteiningerChanged RGSpace fft smoothing kernel to be Gaussian, added someDocstringsDocstringshttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/839change from last to latest2023-02-02T16:41:18ZVincent Eberlechange from last to latest#359#359Martin ReineckeMartin Reineckehttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/344Changes in BlockDiagonalOperator and LogRGSpace2019-09-26T11:50:56ZPhilipp HaimChanges in BlockDiagonalOperator and LogRGSpaceWhen None is passed as operator, BlockDiagonalOperator will treat it as a unity operator, not changing the corresponding field when applied. draw_sample will act like ScalingOperator with factor 1.
get_default_codomain of LogRGSpace now...When None is passed as operator, BlockDiagonalOperator will treat it as a unity operator, not changing the corresponding field when applied. draw_sample will act like ScalingOperator with factor 1.
get_default_codomain of LogRGSpace now changes the harmonic attribute of new space instead of always setting it to True.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/783change to pip install for bugfix2022-08-31T10:03:39ZPhilipp Arrasparras@mpa-garching.mpg.dechange to pip install for bugfixPhilipp Arrasparras@mpa-garching.mpg.dePhilipp Arrasparras@mpa-garching.mpg.dehttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/782change to pip install for bugfix2022-08-19T13:02:35ZVincent Eberlechange to pip install for bugfix# BUGFIX
Our CI fails because the astropy version we are using (installed by apt-get install python3-astropy)
is still using the deprecated function ```numpy.asscalar```.
This bug is fixed in a newer astropy version that one gets by ins...# BUGFIX
Our CI fails because the astropy version we are using (installed by apt-get install python3-astropy)
is still using the deprecated function ```numpy.asscalar```.
This bug is fixed in a newer astropy version that one gets by installing via pip.
@mtr @parras what do you think?
Alternatively we could go for an older version of numpy. But I prefer this approach.Vincent EberleVincent Eberlehttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/677check for NaN values during CG iteration2021-08-31T10:30:00ZMartin Reineckecheck for NaN values during CG iteration