NIFTy merge requestshttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests2019-12-06T08:18:54Zhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/388Fix usage of print to logging2019-12-06T08:18:54ZGordian EdenhoferFix usage of print to loggingThis change is purely for consistency sake and a little bit pedantic :DThis change is purely for consistency sake and a little bit pedantic :Dhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/389Swap order of arguments of ScalingOperator2019-12-06T08:25:26ZGordian EdenhoferSwap order of arguments of ScalingOperatorMake the ScalingOperator consistent with `from_global_data`, `full` and
possibly other operators which take the domain as first argument. This
breaks the currently enforced consistency with the `DiagonalOperator`
which takes a field as f...Make the ScalingOperator consistent with `from_global_data`, `full` and
possibly other operators which take the domain as first argument. This
breaks the currently enforced consistency with the `DiagonalOperator`
which takes a field as first argument and the domain only as an optional
keyword argument.
Fixes #279.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/391Add a change log entry for correlated fields2019-12-06T13:10:20ZPhilipp Arrasparras@mpa-garching.mpg.deAdd a change log entry for correlated fieldsSolves #277 Solves #277 https://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/354WIP: Independent sl amplitudes2019-12-06T15:26:35ZPhilipp Arrasparras@mpa-garching.mpg.deWIP: Independent sl amplitudeshttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/387Remove standard MPI parallelization2019-12-06T16:45:52ZPhilipp Arrasparras@mpa-garching.mpg.deRemove standard MPI parallelizationhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/396Cosmetics2019-12-09T09:47:20ZPhilipp Arrasparras@mpa-garching.mpg.deCosmeticshttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/397Unbreak MetricGaussianKL_MPI in nifty62019-12-09T13:36:11ZGordian EdenhoferUnbreak MetricGaussianKL_MPI in nifty6In commit eda70a19f7, the internal config handling scheme was removed
without ensuring that MetricGaussianKL_MPI is imported. This lead to a
state in which the MPI version of the KL is never imported. Fix this by
always importing MetricG...In commit eda70a19f7, the internal config handling scheme was removed
without ensuring that MetricGaussianKL_MPI is imported. This lead to a
state in which the MPI version of the KL is never imported. Fix this by
always importing MetricGaussianKL_MPI in __init__.py.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/394Introduce partial insert2019-12-10T11:28:21ZPhilipp Arrasparras@mpa-garching.mpg.deIntroduce partial insertSolves #280 Solves #280 https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/399Fix new finalize method2019-12-17T11:19:06ZPhilipp HaimFix new finalize methodThe way the new PowerDistrubutor was built didn't work for N_copies!=0. This should fix that.The way the new PowerDistrubutor was built didn't work for N_copies!=0. This should fix that.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/398Switch FFT to scipy.fft2019-12-20T11:20:56ZMartin ReineckeSwitch FFT to scipy.fftThis gets rid of the `pypocketfft` dependency, but can only be merged once `scipy` 1.4 has been released.This gets rid of the `pypocketfft` dependency, but can only be merged once `scipy` 1.4 has been released.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/400Add one_over() to MultiField2020-01-20T21:11:11ZPhilipp Arrasparras@mpa-garching.mpg.deAdd one_over() to MultiFieldhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/401Gauss sampling dtype2020-01-21T20:35:51ZPhilipp Arrasparras@mpa-garching.mpg.deGauss sampling dtypehttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/403operator.py: Raise not-implemented in matmul call2020-01-23T12:58:54ZGordian Edenhoferoperator.py: Raise not-implemented in matmul callContrary to other overloaded operators, the `__matmul__` call apparently
needs to raise an exception instead of returning `NotImplemented`. This
behaviour can be seen for example in:
```python
psp = ift.RGSpace(512)
m = ift.MaskOperator...Contrary to other overloaded operators, the `__matmul__` call apparently
needs to raise an exception instead of returning `NotImplemented`. This
behaviour can be seen for example in:
```python
psp = ift.RGSpace(512)
m = ift.MaskOperator(ift.Field.from_raw(psp, np.random.randint(0, 2, 512)))
m(ift.from_random("normal", m.domain).val) is NotImplemented
```
which should be invalid and raise an exception but previously returned
`True` instead.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/402Scalable energies22020-01-23T13:40:59ZReimar H LeikeScalable energies2make the Scaling Operator preserve the metric, such that one can temper the likelihood with:
likelihood = likelihood.scale(scalar)
without breaking the code.make the Scaling Operator preserve the metric, such that one can temper the likelihood with:
likelihood = likelihood.scale(scalar)
without breaking the code.Martin ReineckeMartin Reineckehttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/395Introduce `nifty6.mpi` namespace2020-01-23T13:42:48ZLukas PlatzIntroduce `nifty6.mpi` namespaceAs proposed by @reimar in #278, MPI parallelization can be done through specialized operators like the `MetricGaussianKL_MPI`.
The current state of the `do_cleanup` branch does not import them by default (as that would fail without mp...As proposed by @reimar in #278, MPI parallelization can be done through specialized operators like the `MetricGaussianKL_MPI`.
The current state of the `do_cleanup` branch does not import them by default (as that would fail without mpi4py installed) and provides no easy way of importing them, making it necessary to write their full file path to import them: `from nifty6.minimization.metric_gaussian_kl_mpi import MetricGaussianKL_MPI`
This patch proposes to introduce a `nifty6.mpi` namespace, from which all MPI-related components can be directly imported like `from nifty6.mpi import MetricGaussianKL_MPI`.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/406README: add build instructions for docs2020-01-31T11:02:52ZLukas PlatzREADME: add build instructions for docsNo functional changesNo functional changeshttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/405fix NIFTy 5 ASCL citation2020-01-31T11:03:38ZLukas Platzfix NIFTy 5 ASCL citationProbably got mangled in the 5 -> 6 rename.
Citation fixup, no functional changes.Probably got mangled in the 5 -> 6 rename.
Citation fixup, no functional changes.https://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/404getting_started_mf cleanup2020-01-31T11:03:54ZLukas Platzgetting_started_mf cleanuppolishing for better readabilitypolishing for better readabilityhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/merge_requests/408Fix FieldZeroPadder2020-02-19T16:45:19ZPhilipp FrankFix FieldZeroPadder