solprop.backends.numba_cpu.field_plasma

Own the held field-current streams, transforms and frequency assembly.

Classes

HeldWorkspace(problem, shape, *, embedded, ...)

Allocate the field-current streams and plan their transforms once.

class solprop.backends.numba_cpu.field_plasma.HeldWorkspace(problem, shape, *, embedded, flag, threads)

Bases: object

Allocate the field-current streams and plan their transforms once.

Modal and planar routes project both products before their temporal FFTs. Radial routes transform three nodal streams, combine and crop them, then make one real projection on interleaved spectral components. Cartesian and line routes combine on physical nodes before the transverse transform.

Parameters:

problemsolprop.translate.problem.KernelProblem

Validated field-grid problem with plasma channels.

shapetuple of int

Chunk node-component rows and temporal transform rows.

embeddedbool

Whether the modal quadrature has an embedded projection for its alarm.

flagstr

Existing FFTW planning policy.

threadsint

Existing temporal FFT thread count.

assemble(destination, *, coarse=False)

Transform projected currents and add their active-bin polarisation.

Parameters:

destinationnumpy.ndarray

Fine non-plasma polarisation spectrum, updated in place.

coarsebool

Use the embedded quadrature’s projected current streams.

memory_ledger()

List every owned buffer and the measured transform-plan heap growth.

Returns:

dict

Persistent bytes, including partial-chunk padding and embedded rows.

products(gate, slope, count)

Write both complete current products and clear unused chunk rows.

Parameters:

gate, slopenumpy.ndarray

Fine-grid temporal collar and its analytic derivative, in 1 and s⁻¹.

countint

Populated node-component rows; rows beyond this are padding.

project(projection, embedded, n_modes, *, first, count)

Project each current product onto modal rows before transformation.

Parameters:

projectionnumpy.ndarray

Scaled projection for this chunk.

embeddednumpy.ndarray or None

Scaled embedded-rule projection of the same nodes.

n_modesint

Propagated modes, before the separate state-component axis.

firstbool

Overwrite the output on the first chunk; accumulate later chunks.

countint

Active node-component rows.

project_radial(polarisation, projection, destination, *, first, count)

Transform nodal P, gJ and g’J, combine, then project once in frequency.

Parameters:

polarisationnumpy.ndarray

This chunk’s collared non-plasma polarisation.

projectionnumpy.ndarray

Scaled real radial projection for the current nodes.

destinationnumpy.ndarray

Full modal fine spectrum, accumulated at the coarse bins.

firstbool

Clear the whole destination before the first chunk.

countint

Populated node-component rows.