added analytical 2D rad dcf

[mxlutz]

I added an analytical DCF for 2D radial trajectories.

So far, I tried them with the direct_reconstruction example, might make sense to include it somewhere else and also to implement some tests.

Addresses Issue #154

[github-actions]

Coverage Report

File	Stmts	Miss	Cover	Missing
src/mrpro
_version.py	6	2	67%	7–8
src/mrpro/algorithms/csm
inati.py	24	1	96%	44
walsh.py	16	1	94%	53
src/mrpro/algorithms/dcf
dcf_radial.py	25	2	92%	45, 86
dcf_voronoi.py	58	2	97%	15, 95
src/mrpro/algorithms/optimizers
adam.py	22	1	95%	104
pdhg.py	81	3	96%	178–179, 185
pgd.py	53	4	92%	107, 152–155
src/mrpro/algorithms/reconstruction
DirectReconstruction.py	28	16	43%	59–79, 93
IterativeSENSEReconstruction.py	13	1	92%	79
Reconstruction.py	50	22	56%	42, 54–56, 80–87, 108–117
RegularizedIterativeSENSEReconstruction.py	41	17	59%	97–101, 115–140
src/mrpro/data
AcqInfo.py	145	5	97%	42, 121–122, 124, 233
CsmData.py	29	3	90%	15, 84–86
DcfData.py	45	8	82%	18, 66, 78–83
EncodingLimits.py	73	3	96%	33, 123, 126
IData.py	59	8	86%	118, 132, 159–167
IHeader.py	136	12	91%	69–72, 253, 257, 261, 265, 299–303
KData.py	201	29	86%	113–114, 129, 136, 147–157, 166, 174, 183, 217, 239–241, 277–278, 333–344, 473, 475, 545
KHeader.py	141	21	85%	24, 109–115, 142, 190, 197–198, 201, 208, 225–232, 240–251
KNoise.py	31	15	52%	39–52, 56–61
KTrajectory.py	108	3	97%	166, 168, 188
MoveDataMixin.py	140	18	87%	28, 126, 142, 156–158, 220, 336–338, 351, 430, 450–451, 453, 468–469, 471
QData.py	39	7	82%	42, 65–73
Rotation.py	719	35	95%	101, 199, 336, 434, 478, 496, 583, 585, 594, 628, 630, 693, 770, 775, 778, 793, 810, 815, 891, 1079, 1084, 1087, 1111, 1115, 1243, 1245, 1253–1254, 1318, 1400, 1703, 1855, 1890, 1894, 2084
SpatialDimension.py	232	20	91%	34, 104, 148, 154, 274–276, 289–291, 325, 343, 356, 369, 382, 395, 404–405, 420, 429
acq_filters.py	12	1	92%	47
src/mrpro/data/traj_calculators
KTrajectoryCalculator.py	27	1	96%	84
KTrajectoryIsmrmrd.py	19	1	95%	57
src/mrpro/operators
CartesianSamplingOp.py	96	4	96%	124, 163, 238, 305
ConstraintsOp.py	60	2	97%	46, 48
EndomorphOperator.py	32	2	94%	52, 58
FiniteDifferenceOp.py	27	2	93%	40, 105
FourierOp.py	90	3	97%	185, 257, 262
Functional.py	77	9	88%	20–22, 117, 119, 226–228, 242
GridSamplingOp.py	136	9	93%	71–72, 81–82, 89–90, 93, 95, 97
LinearOperator.py	201	8	96%	107, 217, 244, 251, 292, 301, 309, 326
LinearOperatorMatrix.py	162	19	88%	82, 119, 152, 161, 166, 175–178, 191–194, 202–203, 208–209, 221, 310, 337, 364
MultiIdentityOp.py	13	2	85%	43, 48
NonUniformFastFourierOp.py	188	10	95%	69, 96, 206, 208, 241, 243, 319, 373, 423, 428
Operator.py	79	2	97%	32, 88
ProximableFunctionalSeparableSum.py	39	3	92%	50, 103, 110
SliceProjectionOp.py	174	8	95%	45, 62, 64, 70, 206, 227, 260, 300
WaveletOp.py	119	5	96%	151, 169, 204, 209, 232
ZeroPadOp.py	16	1	94%	30
src/mrpro/phantoms
brainweb.py	275	31	89%	325–335, 371, 427–430, 452–453, 458–459, 461–462, 466, 474, 481–482, 520, 586–587, 606–609, 620, 622, 657–658, 671
src/mrpro/utils
filters.py	62	2	97%	44, 49
indexing.py	170	1	99%	331
reshape.py	95	2	98%	110, 301
slice_profiles.py	47	6	87%	21, 37, 116–119, 152
sliding_window.py	34	1	97%	34
split_idx.py	10	2	80%	43, 47
summarize_tensorvalues.py	12	3	75%	23, 25, 27
typing.py	69	55	20%	9–235
unit_conversion.py	60	14	77%	32, 40, 42, 49, 51, 58, 60, 69, 80, 82, 101, 103, 124, 126
zero_pad_or_crop.py	31	6	81%	26, 30, 55, 58, 61, 64
TOTAL	5940	474	92%

Tests	Skipped	Failures	Errors	Time
2753	0 💤	0 ❌	0 🔥	1m 49s ⏱️

[github-actions]

📚 Documentation

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[fzimmermann89]

I would leave the examples as-is.

The function should not be in dcf_voronoi, but in dcf_radial.py
you can import the dcf1d from voronoi.

Please also consider if the comments are really useful.
By default, try to have code that is self explanatory and avoid comments that describe what you are doing, such as
"# Compute the angle using atan2(vy, vx) instead of arccos"
instead, describe in a short sentence what the basic idea of the function is (either in docstring or as comment) and then only add comments to explain why you do things in a certain way if it is not obvious.

Can if not isinstance(center_idx, int): ever be false?

it would be great to write some unit tests, see tests for some examples

[mxlutz]

Thanks for the feedback Felix, I changed everything accordingly and implemented a simple test comparing the results to a 2D rad equidistant dcf