plasma_plots.gvec

Read GVEC’s evaluation Datasets in plasma-plots’ conventions.

GVEC <https://gvec.readthedocs.io>_ evaluates an equilibrium into xarray Datasets (state.evaluate(...), state.evaluate_sfl(...), gvec.Evaluations) with the dimensions rad, pol, tor, the flux coordinates rho, theta, zeta (or the Boozer angles theta_B, zeta_B, or the PEST angle theta_P) over them, vectors along xyz, the position as the variable pos and LaTeX symbol attributes. from_gvec() returns the same data the way the rest of plasma-plots reads it:

• the dimensions are the flux coordinates themselves: rho, theta/theta_B/theta_P and zeta/zeta_B, so rho=0.5 or zeta=0 selects and x="zeta" draws;
• pos becomes the physical coordinates X, Y, Z of every variable (for coords="physical", 3-D views and the vector calculus on the mapped domain), and X1, X2 (GVEC’s reference coordinates, R and Z for the cylindrical map), theta_P and the logical angles of a Boozer or PEST grid become coordinates as well;
• xyz becomes component;
• each symbol becomes a label ($\iota$), which plots use for axes and color bars;
• the angles get a period attribute (2π, and 2π/nfp toroidally), from which the mode spectra take their periods and full-torus mode numbers, and the coordinate_lines overlay its lines;
• GVEC’s quadrature weights (rad_weight, pol_weight, tor_weight) become rho_weight, theta_weight, zeta_weight, which integrals use. GVEC’s toroidal weight counts every field period; zeta_weight is divided by nfp, so that an integral covers the sampled grid (one field period) as on every other grid: multiply by nfp for the device;
• the number of field periods (N_FP) is the nfp attribute of the Dataset and of every variable.

The .plasma accessor applies from_gvec() by itself to GVEC data, so ev.mod_B.plasma.plot.slice(x="zeta", y="theta", rho=1.0) needs no call. Call it once on the whole Dataset to attach the geometry to every variable first: a single variable such as ev.mod_B doesn’t carry pos. GVEC itself is not needed.

Examples

>>> import plasma_plots
>>> ev = plasma_plots.from_gvec(
...     state.evaluate(
...         "mod_B", "pos", "iota", "N_FP", rho=11, theta=32, zeta=24
...     )
... )
>>> ev.mod_B.plasma.plot.slice(
...     coords="physical",
...     plane="RZ",
...     zeta=0.0,
...     overlays={"coordinate_lines": {"rho": 5, "theta": 8}},
... )
>>> ev.iota.plasma.plot.lineout(rationals=4)

Attributes

Name	Description
AXES	No description.
GRID_VARIABLES	No description.
GVEC_DIMS	No description.
POLOIDAL	No description.
TOROIDAL	No description.

Functions

Name	Description
from_gvec	Return GVEC evaluations in plasma-plots' conventions; see plasma_plots.gvec.
is_gvec	Whether data is still in GVEC's layout.

AXESattributemodule attribute#

View source

AXES = {'rad': ('rho'), 'pol': ('theta_B', 'theta_P', 'theta'), 'tor': ('zeta_B', 'zeta')}

GRID_VARIABLESattributemodule attribute#

View source

GRID_VARIABLES = ('X1', 'X2', 'theta_P', 'theta', 'zeta', 'theta_B', 'zeta_B')

GVEC_DIMSattributemodule attribute#

View source

GVEC_DIMS = ('rad', 'pol', 'tor')

POLOIDALattributemodule attribute#

View source

POLOIDAL = ('theta', 'theta_B', 'theta_P')

TOROIDALattributemodule attribute#

View source

TOROIDAL = ('zeta', 'zeta_B')

from_gvecfunction#

View source

def from_gvec(data: xr.DataArray | xr.Dataset, *, nfp: int | None = None) -> xr.DataArray | xr.Dataset

Return GVEC evaluations in plasma-plots’ conventions; see plasma_plots.gvec.

Data that is not in GVEC’s layout (see is_gvec()) comes back with only the steps that apply, so calling it twice is harmless.

Parameters

Name	Type	Default	Description
data	xarray.Dataset or xarray.DataArray	required	A Dataset from state.evaluate(...), state.evaluate_sfl(...) or gvec.Evaluations (also after to_netcdf and open_dataset), or one of its variables.
nfp	int	None	The number of field periods. Default: the N_FP variable (evaluate "N_FP" with the rest), else an nfp attribute, else from a toroidal grid that spans one field period uniformly (GVEC’s default grid); without one, the toroidal angle gets no period.

Returns

xarray.Dataset or xarray.DataArray

The same data, of the same type, with the dimensions rho, theta/theta_B/ theta_P, zeta/zeta_B and component, the coordinates X, Y, Z (from pos), X1, X2, labels from the symbol attributes, the angles’ period and the nfp attribute.

Examples

>>> ev = from_gvec(
...     state.evaluate("mod_B", "pos", "N_FP", rho=11, theta=32, zeta=24)
... )
>>> ev.mod_B.plasma.plot.panels(
...     sweep="zeta", coords="physical", plane="RZ", nrows=1, ncols=3
... )
>>> boozer = from_gvec(
...     state.evaluate_sfl(
...         "mod_B", "pos", rho=[0.5], theta=32, zeta=24, sfl="boozer"
...     )
... )
>>> boozer.mod_B.plasma.plot.slice(x="zeta_B", y="theta_B", rho=0.5)

is_gvecfunction#

View source

def is_gvec(data: xr.DataArray | xr.Dataset) -> bool

Whether data is still in GVEC’s layout.

That is a rad, pol or tor dimension with one of GVEC’s flux coordinates on it.

Parameters

Name	Type	Description
data	xarray.DataArray or xarray.Dataset	The data.

Returns

bool

True for GVEC’s evaluations (before from_gvec()), False otherwise.