Commit 3912e7e4 authored by Martin Reinecke's avatar Martin Reinecke
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add a file describing the differences to NIFTy nightly

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Significant differences between NIFTy nightly and nifty2go
1) Field domains in nifty2go are stored in DomainTuple objects, which makes
comparisons between domains and computation of axis indices etc. much simpler
and more efficient.
No impact on the user ... these objects are generated whenever needed and
have all necessary functions to make them look like tuples of spaces.
2) In nifty2go an operator's domain and target refer to the _full_ domains of
the input and output fields read/written by times(), adjoint_times() etc.
In NIFTy nightly, domain and target only refer to the (sub-)domain on
which the operator actually acts. This leads to complications like the need
for the "default_spaces" argument in the operator constructor and the
"spaces" keywords in all operator calls.
Advantages of the nifty2go approach:
- less error-prone and easier to understand; less code overall
- operators have more knowledge and may tune themselves better
- difficulties with the design of ComposedOperator (issue 152) resolve
themselves automatically
- operators cannot be used as flexibly as before; in a few circumstances
it will be necessary to create more operator objects than with the current
However, I have not found any such situation in the current code base, so
it appears to be rare.
3) nifty2go is based on numpy arrays, not D2O objects.
For the moment, there is absolutely no MPI support.
My goal is to reintroduce this via the "data object" interface shown in the
"data_objects/" subdirectory. In principle, all operations on arrays within
NIFTy have to be carried out via calls to the data object module (or method
calls of classes defined there). By simply changing the data object module,
one could have a numpy backend or a D2O backend or something completely
I'm optimistic that this can work, but don't have a demonstration yet.
4) Spaces no longer have a weight() method; it has been replaced by
scalar_dvol() and dvol() methods, which return the scalar volume element,
if available, or a numpy array with all volume elements for the respective
By using scalar_dvol() whenever possible, one can save quite some
time when computing Field.weight().
5) renamings:
get_distance_array -> get_k_length_array
get_unique_distances -> get_unique_k_lengths
(to be specific which "distances" are meant and to make more clear why this
only exists for harmonic spaces)
kindex -> k_lengths
(because this is not an index)
6) In nifty2go, PowerSpace is not a harmonic space.
7) In nifty2go, parallel probing should work (needs systematic testing)
8) In nifty2go, the DiagonalOperator is always constructed from a bare Field,
and its diagonal() method always returns the same bare Field.
This requires a few explicit weight() calls in other places of the code,
but it should reduce the overall amount of confusion (I hope).
In NIFTY nightly, the Fields going into and comping out of the
DiagonalOperator are treated as non-bare.
I can live with either convention, but seem to recall a remark by Torsten(?)
that the bare version is more intuitive.
9) Many default arguments have been removed in nifty2go, wherever there is no
sensible default (in my opinion). My personal impression is that this has
actually made the demos more readable, but I'm sure not everyone will agree
10) Plotting has been replaced by something very minimalistic but usable.
Currently supported output formats are PDF and PNG.
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