Coverage for python/gsfit/database_readers/st40_spider_mdsplus/setup_plasma.py: 0%
44 statements
« prev ^ index » next coverage.py v7.16.2, created at 2026-10-14 15:25 +0000
1import typing
2from typing import TYPE_CHECKING
4import gsfit_rs
5import numpy as np
6import numpy.typing as npt
7from gsfit_rs import Plasma
9if TYPE_CHECKING:
10 from . import DatabaseReader
13def setup_plasma(
14 self: "DatabaseReader",
15 pulseNo: int,
16 settings: dict[str, typing.Any],
17 times_to_reconstruct: npt.NDArray[np.float64],
18) -> Plasma:
19 """
20 This method initialises the Rust `Plasma` class.
22 :param pulseNo: Pulse number, used to read from the database
23 :param settings: Dictionary containing the JSON settings read from the `settings` directory
24 :param times_to_reconstruct: Times the equilibrium will be solved at [second]
26 **This method is specific to ST40's experimental MDSplus database.**
28 See `python/gsfit/database_readers/interface.py` for more details on how a new database_reader should be implemented.
29 """
31 # Initial plasma conditions
32 initial_guess_ip = settings["GSFIT_code_settings.json"]["initial_guess"]["ip"]
33 initial_guess_cur_r = settings["GSFIT_code_settings.json"]["initial_guess"]["cur_r"]
34 initial_guess_cur_z = settings["GSFIT_code_settings.json"]["initial_guess"]["cur_z"]
35 initial_guess_minor_radius = settings["GSFIT_code_settings.json"]["initial_guess"]["minor_radius"]
36 initial_guess_elongation = settings["GSFIT_code_settings.json"]["initial_guess"]["elongation"]
38 # Numerical settings the Grad-Shafranov solve is run with
39 n_iter_max = settings["GSFIT_code_settings.json"]["numerics"]["n_iter_max"]
40 n_iter_min = settings["GSFIT_code_settings.json"]["numerics"]["n_iter_min"]
41 n_iter_no_vertical_feedback = settings["GSFIT_code_settings.json"]["numerics"]["n_iter_no_vertical_feedback"]
42 grad_shafranov_deviation_tolerance = settings["GSFIT_code_settings.json"]["numerics"]["grad_shafranov_deviation_tolerance"]
43 use_anderson_mixing = settings["GSFIT_code_settings.json"]["numerics"]["anderson_mixing"]["use"]
44 anderson_mixing_from_previous_iter = settings["GSFIT_code_settings.json"]["numerics"]["anderson_mixing"]["mixing_from_previous_iter"]
45 # The pressure at the plasma boundary. Integrating `p'` leaves the pressure defined up to a constant, which
46 # GSFit historically fixed by demanding zero pressure at the boundary. Setting `free` makes it a degree of
47 # freedom of the fit instead. `.get` is used so that older settings directories keep working
48 pressure_edge_settings = settings["source_function_p_prime.json"].get(
49 "pressure_edge", settings["GSFIT_code_settings.json"]["numerics"].get("pressure_edge", {})
50 )
51 pressure_edge_free = pressure_edge_settings.get("free", False)
52 pressure_edge_regularisation_weight = pressure_edge_settings.get("regularisation_weight", 1.0e-4)
54 # Set the source functions types
55 p_prime_source_function: gsfit_rs.EfitPolynomial
56 ff_prime_source_function: gsfit_rs.EfitPolynomial
58 if settings["source_function_p_prime.json"]["method"] == "efit_polynomial":
59 n_dof = settings["source_function_p_prime.json"]["efit_polynomial"]["n_dof"]
60 regularisations = np.array(settings["source_function_p_prime.json"]["efit_polynomial"]["regularizations"])
61 # If `regularisations` is [[]] in the json file, will be interpreted by numpy as having size (1, 0).
62 # Which would be interpreted as (n_regularisations, n_dof). So it would cause an error
63 if regularisations.shape == (1, 0):
64 regularisations = np.zeros((0, n_dof), dtype=np.float64)
65 p_prime_source_function = gsfit_rs.EfitPolynomial(n_dof, regularisations)
66 else:
67 raise ValueError(f"Unknown method for p_prime source function: {settings['source_function_p_prime.json']['method']}")
69 if settings["source_function_ff_prime.json"]["method"] == "efit_polynomial":
70 n_dof = settings["source_function_ff_prime.json"]["efit_polynomial"]["n_dof"]
71 regularisations = np.array(settings["source_function_ff_prime.json"]["efit_polynomial"]["regularizations"])
72 # If `regularisations` is [[]] in the json file, will be interpreted by numpy as having size (1, 0).
73 # Which would be interpreted as (n_regularisations, n_dof). So it would cause an error
74 if regularisations.shape == (1, 0):
75 regularisations = np.zeros((0, n_dof), dtype=np.float64)
76 ff_prime_source_function = gsfit_rs.EfitPolynomial(n_dof, regularisations)
78 # Grid size and shape
79 n_r = settings["GSFIT_code_settings.json"]["grid"]["n_r"]
80 n_z = settings["GSFIT_code_settings.json"]["grid"]["n_z"]
81 r_min = settings["GSFIT_code_settings.json"]["grid"]["r_min"]
82 r_max = settings["GSFIT_code_settings.json"]["grid"]["r_max"]
83 z_min = settings["GSFIT_code_settings.json"]["grid"]["z_min"]
84 z_max = settings["GSFIT_code_settings.json"]["grid"]["z_max"]
86 # Normalised poloidal flux grid
87 n_psi_n = settings["GSFIT_code_settings.json"]["n_psi_n"]
88 psi_n = np.linspace(0.0, 1.0, n_psi_n).astype(np.float64)
90 # Initialise the Plasma Rust class
91 plasma = Plasma(
92 n_r,
93 n_z,
94 r_min,
95 r_max,
96 z_min,
97 z_max,
98 psi_n, # BUXTON: perhaps better to send in `n_psi_n`
99 p_prime_source_function,
100 ff_prime_source_function,
101 initial_guess_ip,
102 initial_guess_cur_r,
103 initial_guess_cur_z,
104 initial_guess_minor_radius,
105 initial_guess_elongation,
106 n_iter_max,
107 n_iter_min,
108 n_iter_no_vertical_feedback,
109 grad_shafranov_deviation_tolerance,
110 use_anderson_mixing,
111 anderson_mixing_from_previous_iter,
112 times_to_reconstruct,
113 pressure_edge_free,
114 pressure_edge_regularisation_weight,
115 )
117 return plasma
120# import typing
121# from typing import TYPE_CHECKING
123# import gsfit_rs
124# import numpy as np
125# import numpy.typing as npt
126# from gsfit_rs import Plasma
127# from st40_database import GetData # type: ignore[import-not-found]
129# if TYPE_CHECKING:
130# from . import DatabaseReader
133# def setup_plasma(
134# self: "DatabaseReader",
135# pulseNo: int,
136# settings: dict[str, typing.Any],
137# ) -> Plasma:
138# """
139# This method initialises the Rust `Plasma` class.
141# :param pulseNo: Pulse number, used to read from the database
142# :param settings: Dictionary containing the JSON settings read from the `settings` directory
144# **This method is specific to ST40's ASTRA stored on MDSplus.**
146# See `python/gsfit/database_readers/interface.py` for more details on how a new database_reader should be implemented.
147# """
149# # Initial plasma conditions
150# initial_guess_ip = settings["GSFIT_code_settings.json"]["initial_guess"]["ip"]
151# initial_guess_cur_r = settings["GSFIT_code_settings.json"]["initial_guess"]["cur_r"]
152# initial_guess_cur_z = settings["GSFIT_code_settings.json"]["initial_guess"]["cur_z"]
154# # Set the source functions types
155# p_prime_source_function: gsfit_rs.EfitPolynomial
156# ff_prime_source_function: gsfit_rs.EfitPolynomial
158# if settings["source_function_p_prime.json"]["method"] == "efit_polynomial":
159# n_dof = settings["source_function_p_prime.json"]["efit_polynomial"]["n_dof"]
160# regularisations = np.array(settings["source_function_p_prime.json"]["efit_polynomial"]["regularizations"])
161# p_prime_source_function = gsfit_rs.EfitPolynomial(n_dof, regularisations)
162# elif settings["source_function_p_prime.json"]["method"] == "efit_polynomial":
163# n_dof = settings["source_function_p_prime.json"]["efit_polynomial"]["n_dof"]
164# regularisations = np.array(settings["source_function_p_prime.json"]["efit_polynomial"]["regularizations"])
165# p_prime_source_function = gsfit_rs.EfitPolynomial(n_dof, regularisations)
166# else:
167# raise ValueError(f"Unknown method for p_prime source function: {settings['source_function_p_prime.json']['method']}")
169# if settings["source_function_ff_prime.json"]["method"] == "efit_polynomial":
170# n_dof = settings["source_function_ff_prime.json"]["efit_polynomial"]["n_dof"]
171# regularisations = np.array(settings["source_function_ff_prime.json"]["efit_polynomial"]["regularizations"])
172# ff_prime_source_function = gsfit_rs.EfitPolynomial(n_dof, regularisations)
173# elif settings["source_function_ff_prime.json"]["method"] == "efit_polynomial":
174# n_dof = settings["source_function_ff_prime.json"]["efit_polynomial"]["n_dof"]
175# regularisations = np.array(settings["source_function_ff_prime.json"]["efit_polynomial"]["regularizations"])
176# ff_prime_source_function = gsfit_rs.EfitPolynomial(n_dof, regularisations)
178# # Grid size and shape
179# n_r = settings["GSFIT_code_settings.json"]["grid"]["n_r"]
180# n_z = settings["GSFIT_code_settings.json"]["grid"]["n_z"]
181# r_min = settings["GSFIT_code_settings.json"]["grid"]["r_min"]
182# r_max = settings["GSFIT_code_settings.json"]["grid"]["r_max"]
183# z_min = settings["GSFIT_code_settings.json"]["grid"]["z_min"]
184# z_max = settings["GSFIT_code_settings.json"]["grid"]["z_max"]
186# # Normalised poloidal flux grid
187# n_psi_n = settings["GSFIT_code_settings.json"]["n_psi_n"]
188# psi_n = np.linspace(0.0, 1.0, n_psi_n).astype(np.float64)
190# # Limiter
191# elmag_run_name = settings["GSFIT_code_settings.json"]["database_reader"]["st40_astra_mdsplus"]["elmag_run_name"]
192# elmag = GetData(12050, f"ELMAG#{elmag_run_name}", is_fail_quiet=False)
193# limit_pts_r = typing.cast(npt.NDArray[np.float64], elmag.get("LIMITER.LIMIT_PTS.R"))
194# limit_pts_z = typing.cast(npt.NDArray[np.float64], elmag.get("LIMITER.LIMIT_PTS.Z"))
196# # Vacuum vessel where the plasma is allowed to be
197# vessel_r = limit_pts_r
198# vessel_z = limit_pts_z
200# # Add lower MC tiles
201# limit_pts_r = np.append(limit_pts_r, 0.7103)
202# limit_pts_z = np.append(limit_pts_z, -0.3131)
203# # Add upper MC tiles
204# limit_pts_r = np.append(limit_pts_r, 0.7103)
205# limit_pts_z = np.append(limit_pts_z, 0.3031)
207# # Initialise the Plasma Rust class
208# plasma = Plasma(
209# n_r,
210# n_z,
211# r_min,
212# r_max,
213# z_min,
214# z_max,
215# psi_n, # BUXTON: perhaps better to send in `n_psi_n`
216# limit_pts_r,
217# limit_pts_z,
218# vessel_r,
219# vessel_z,
220# p_prime_source_function,
221# ff_prime_source_function,
222# initial_guess_ip,
223# initial_guess_cur_r,
224# initial_guess_cur_z,
225# )
227# return plasma