Add GIRF sequence creator with triangles and YAML

[OErbil]

Files for simple GIRF sequence creation using triangular gradients. The YAML file is used to adjust parameters. The py files reads in the parameters, creates the desired sequence, creates a specifically named folder (named by the user) and saves the sequence and the YAML parameters used into that folder. This way, one never loses the parameters required to recreate the specific sequence. Reconstruction will be added later.

[github-actions]

Coverage Report

File	Stmts	Miss	Cover	Missing
/home/runner/.local/lib/python3.12/site-packages/mrseq
_version.py	7	7	0%	2–9
/home/runner/.local/lib/python3.12/site-packages/mrseq/preparations
t2_prep.py	51	1	98%	195
/home/runner/.local/lib/python3.12/site-packages/mrseq/scripts
radial_flash.py	140	11	92%	101, 104, 259, 345, 403–408, 428, 434
spiral_flash.py	120	10	92%	95, 231, 313, 363–368, 387, 393
t1_inv_rec_gre_single_line.py	93	9	90%	162, 255, 298–303, 330, 336
t1_inv_rec_se_single_line.py	106	9	92%	219, 316, 375–380, 407, 413
t1_molli_bssfp.py	141	13	91%	216, 282–284, 299, 374, 428–433, 454, 460
t1_t2_spiral_cmrf.py	149	12	92%	89, 95, 114, 168, 385, 432–437, 463, 469
t1rho_se_single_line.py	102	8	92%	310, 367–372, 399, 405
t2_multi_echo_se_single_line.py	96	9	91%	162, 261, 314–319, 344, 350
t2_t2prep_flash.py	143	15	90%	103, 226, 243, 277–279, 291, 367, 429–434, 454, 460
t2star_multi_echo_flash.py	145	14	90%	114, 233, 280–282, 294, 390, 452–457, 477, 483
/home/runner/.local/lib/python3.12/site-packages/mrseq/utils
ismrmrd.py	93	2	98%	173, 179
sequence_helper.py	59	4	93%	105, 133–134, 162
trajectory.py	149	3	98%	45, 87, 354
TOTAL	1725	127	93%

Tests	Skipped	Failures	Errors	Time
377	0 💤	0 ❌	0 🔥	1m 38s ⏱️

[fzimmermann89]

Some comments as a third party who is not involved in mrseq but keeps an eye on it:

I also appreciate reproducible configuration in general.

But I also enjoy the homogeneity of the different
sequences that Christoph and Patrick came up with in mrseq. If you look a bit around, they follow some patterns. Most importantly, instead of global constants or config files, they whole sequence is a function with arguments.

This has two advantages:
First, you can just use it within python by importing the script and calling if, for example in a loop.
Second, you could combine it with jsonargparse to get the reproducible configuration "for free". Although, I have not tried it in mrseq yet (this is what I use for ML stuff).
You can do jsonargparse.CLI(main) and it will look at the arguments of main and set up argument and yaml parser for it (you can also customize here quite a bit)

Maybe you find the time to match the style of the other sequences AND could try out if jsonargparse helps for the yaml parsing?
Even if you don't use it here, it might still be a useful tool for your own research

Cheers
Felix