ift issueshttps://gitlab.mpcdf.mpg.de/groups/ift/-/issues2018-01-19T08:55:37Zhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/65Profile Field.dot2018-01-19T08:55:37ZTheo SteiningerProfile Field.dotField.dot uses the DiagonalOperator in order to do dot products that only affect certain spaces of the partner. Maybe the fields are unnecessarily copied -> profiling is needed to ensure efficiency.Field.dot uses the DiagonalOperator in order to do dot products that only affect certain spaces of the partner. Maybe the fields are unnecessarily copied -> profiling is needed to ensure efficiency.Theo SteiningerTheo Steininger2018-01-19https://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/8Profile the d2o.bincount method2016-05-26T11:09:57ZTheo SteiningerProfile the d2o.bincount methodThe d2o.bincount method scales well with MPI parallelization but compared to single-core np.bincount has a rather big overhead. The d2o.bincount method scales well with MPI parallelization but compared to single-core np.bincount has a rather big overhead. Theo SteiningerTheo Steiningerhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/263Properly implementing a convolution2019-03-14T15:09:48ZJulia StadlerProperly implementing a convolutionMy response convolves the signal with a non-spherical PSF, which is specified by a field with the same domain as the signal. To avoid issues with periodic boundaries I apply a zero padding, so the exact steps are:
* zero-pad the PSF fro...My response convolves the signal with a non-spherical PSF, which is specified by a field with the same domain as the signal. To avoid issues with periodic boundaries I apply a zero padding, so the exact steps are:
* zero-pad the PSF from the center, apply a Fourier transform and construct a DiagonalOperator from the result
* zero-pad the signal from the right/top and apply a Fourier transform
* apply the PSF-operator to the signal field followed by an inverse Fourier transform
* apply the adjoint signal zero padding operation
* take the real value
The problem with this procedure is that it reduces the flux at the borders of the image, where the PSF smears the additional zeros out to the pixels I'm interested in. I attached two plots to illustrate the problem, on shows how point sources are smeared out to the opposite side of the image without zero padding, the other how the zero padding leaks into the image at the border. The signal contains two point sources which get brighter with with bin number and equally the PSF gets wider.
Has anyone encountered a similar problem before? Or are there any nifty tools to tackle this, I'm not aware of? My approach would be to extend the signal field beyond the data region and to include a mask in the response to account for that. .Or is there a smarter approach?![data_no-zero-padding](/uploads/90b1f2e428d6316b0f4886ec40535fe4/data_no-zero-padding.png)
![data_outer-zero-padding](/uploads/75851eacc3174eccb9be766b57bdad28/data_outer-zero-padding.png)https://gitlab.mpcdf.mpg.de/ift/pyHealpix/-/issues/2pybind11 must already be installed2018-01-19T08:58:18ZTheo Steiningerpybind11 must already be installedWithout pybind11 being already installed the installation terminates with
```
./pyHealpix.cc:30:31: fatal error: pybind11/pybind11.h: No such file or directory
#include <pybind11/pybind11.h>
```
Doing a ``pip install pybind11`` solves...Without pybind11 being already installed the installation terminates with
```
./pyHealpix.cc:30:31: fatal error: pybind11/pybind11.h: No such file or directory
#include <pybind11/pybind11.h>
```
Doing a ``pip install pybind11`` solves the problem.https://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/125pyfftw tests are not being run2017-05-16T21:20:26ZMartin Reineckepyfftw tests are not being runI just noticed that continuous integration does not run pyfftw tests, even when the package should be available. This accounts for the 2400 tests that are currently skipped in the pipelines.
I'm not sure why this happens. The relevant te...I just noticed that continuous integration does not run pyfftw tests, even when the package should be available. This accounts for the 2400 tests that are currently skipped in the pipelines.
I'm not sure why this happens. The relevant tests in `test_fft_operator.py` are guarded by
```
if module == "fftw" and "pyfftw" not in di:
raise SkipTest
```
which looks correct to me.https://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/75Python 3 support2017-08-22T17:06:03ZTheo SteiningerPython 3 supporthttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/211Question on generate_posterior_sample()2018-02-06T10:58:22ZMartin ReineckeQuestion on generate_posterior_sample()Currently the code for generate_posterior sample contains the line
`power = sqrt(power_analyze(self.S.diagonal()))`
According to @reimar, this should actually read:
`power = power_analyze(sqrt(self.S.diagonal()))`
@kjako, any objecti...Currently the code for generate_posterior sample contains the line
`power = sqrt(power_analyze(self.S.diagonal()))`
According to @reimar, this should actually read:
`power = power_analyze(sqrt(self.S.diagonal()))`
@kjako, any objections?https://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/121Questions on FieldType and FieldArray2017-05-28T06:56:12ZMartin ReineckeQuestions on FieldType and FieldArrayIt seems we forgot to discuss (and document) FieldType and FieldArray...
- could they be merged into a single class? FieldType seems unused, except as a parent of FieldArray.
- FieldType::process() seems unused and seems rather carel...It seems we forgot to discuss (and document) FieldType and FieldArray...
- could they be merged into a single class? FieldType seems unused, except as a parent of FieldArray.
- FieldType::process() seems unused and seems rather careless about errors. Do we need to keep this?https://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/232Random seed in extra/tests2018-04-26T15:01:09ZPhilipp Arrasparras@mpa-garching.mpg.deRandom seed in extra/testsIf one calls tests like `nifty4.extra.consistency_check(op)` the random seed afterwards is different. Would it be sensible to reset the numpy random seed?If one calls tests like `nifty4.extra.consistency_check(op)` the random seed afterwards is different. Would it be sensible to reset the numpy random seed?https://gitlab.mpcdf.mpg.de/ift/pyHealpix/-/issues/1README: Add flags to configure2017-05-24T10:11:22ZTheo SteiningerREADME: Add flags to configureOne could add the flags `--enable-openmp --enable-native-optimizations` to the install instructions.One could add the flags `--enable-openmp --enable-native-optimizations` to the install instructions.Martin ReineckeMartin Reineckehttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/297Really obsolete Nifty docs are still online2020-05-14T06:58:53ZMartin ReineckeReally obsolete Nifty docs are still onlineI searched online for "nifty documentation" today, and the second hit was
https://wwwmpa.mpa-garching.mpg.de/ift/nifty/start.html
Can we please remove these completely obsolete files from the public internet? Our potential users might b...I searched online for "nifty documentation" today, and the second hit was
https://wwwmpa.mpa-garching.mpg.de/ift/nifty/start.html
Can we please remove these completely obsolete files from the public internet? Our potential users might be grateful :)Torsten EnsslinTorsten Ensslinhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/283Reduce licensing boilerplate2020-05-13T11:36:01ZGordian EdenhoferReduce licensing boilerplateIf we really feel the need to put licensing boilerplate in every source file, let's at least make it concise by e.g. using https://spdx.org/ids.If we really feel the need to put licensing boilerplate in every source file, let's at least make it concise by e.g. using https://spdx.org/ids.https://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/55Reduce rg_power_space to generic power_space2016-07-22T20:57:33ZTheo SteiningerReduce rg_power_space to generic power_spaceThe rg_power_space can be made generic enough to be suitable for all spaces.
The power_indices get injected as a reference to the certain class.
The space-specific parameters get passed in terms of the paradict. -> The __init__ of th...The rg_power_space can be made generic enough to be suitable for all spaces.
The power_indices get injected as a reference to the certain class.
The space-specific parameters get passed in terms of the paradict. -> The __init__ of the (RG/LM)PowerIndices classes must be changed such that it accepts paradicts. Theo SteiningerTheo Steiningerhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/393Register `Likelihood` as PyTree2024-01-21T17:49:36ZGordian EdenhoferRegister `Likelihood` as PyTreeIf `Likelihood` would be a registered PyTree, we could compile `draw_sample(likelihood, primals, *a, **k)` and the data would be traced instead of inlined (I think)!If `Likelihood` would be a registered PyTree, we could compile `draw_sample(likelihood, primals, *a, **k)` and the data would be traced instead of inlined (I think)!Gordian EdenhoferGordian Edenhoferhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/296Releasing NIFTy 6?2020-05-22T07:46:13ZMartin ReineckeReleasing NIFTy 6?I have the impression that we have enough new features to justify a NIFTy 6 release.
Does anyone have feature suggestions which should go into the code before the release?I have the impression that we have enough new features to justify a NIFTy 6 release.
Does anyone have feature suggestions which should go into the code before the release?https://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/394remove .envrc2023-11-27T15:01:57ZVincent Eberleremove .envrchttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/387remove flake.lock2023-11-27T15:01:48ZVincent Eberleremove flake.lockhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/386remove flake.nix2023-11-27T15:01:24ZVincent Eberleremove flake.nixhttps://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/115Remove "Makefile"2017-05-28T06:56:12ZMartin ReineckeRemove "Makefile"Is this file needed for anything? It has not been updated for two years and seems disconnected from the rest of the package.Is this file needed for anything? It has not been updated for two years and seems disconnected from the rest of the package.https://gitlab.mpcdf.mpg.de/ift/nifty/-/issues/35Remove MPI from nifty configuration2017-05-09T21:39:14ZTheo SteiningerRemove MPI from nifty configurationThe spaces check for a valid comm, still. Until this is removed, gdi and gc must provide information about them.
-> remove MPI related stuff from nifty_config:
- dependency_injector
- nifty_configuration.register(...)The spaces check for a valid comm, still. Until this is removed, gdi and gc must provide information about them.
-> remove MPI related stuff from nifty_config:
- dependency_injector
- nifty_configuration.register(...)Theo SteiningerTheo Steininger