model-lmn-boundary

Model-based (Shue magnetopause) LMN boundary frame

Where boundary-minimum-variance derives the boundary normal from the field rotation itself (MVA), this skill derives it from a model magnetopause (Shue et al.) evaluated at the spacecraft position. The two are complementary: the model normal does not depend on the field having a clean planar rotation, so it works where MVA fails (poor eigenvalue separation) and gives an independent number to validate a trusted MVA normal against.

When to use

• "Give me an LMN normal that does NOT depend on the field rotation" (e.g. MVA eigenvalue ratio was too low to trust).
• "Rotate B into the model (Shue) magnetopause boundary-normal frame for this crossing."
• "Cross-check my MVA normal against the model magnetopause normal" — agreement strengthens the boundary identification.

Tool chain (all existing)

load_data_source → browse_data_parameters → fetch_data_product (B in GSM + spacecraft position) → build the (N,3,3) LMN matrix via the lmn_matrix_make backend (below) → apply it with the apply-rotation-matrix skill (tvector_rotate) → render_tplot, all inside a create_spedas_analysis_bundle. Cross-reference boundary-minimum-variance (data-driven LMN) and magnetopause-lmn-analysis (full field+plasma crossing study).

Backend (VERIFIED contract)

Two pyspedas functions, both operating on tplot variables — they STORE results, they do not return arrays:

• pyspedas.cotrans_tools.lmn_matrix_make.lmn_matrix_make(pos_var_name, mag_var_name, trange=None, hro2=False, newname=None)
  • Inputs: names of two already-stored tplot variables — pos_var_name (spacecraft position, GSM, (M,3)) and mag_var_name (B in GSM, (N,3)). Evaluates the Shue magnetopause model at the position to get the local normal and builds the L/M/N basis.
  • Returns: the name of a stored tplot variable holding the (N,3,3) LMN rotation-matrix stack — NOT the array. Retrieve the matrix with get_data(<name>) → (times, (N,3,3) array).
  • hro2=True selects the alternate (Shue 1998 vs. earlier) magnetopause parametrization; trange clips the interval.
• pyspedas.cotrans_tools.gsm2lmn.gsm2lmn(times, Rxyz, Bxyz, swdata=None)
  • Lower-level: takes raw arrays (times, position Rxyz, field Bxyz, optional solar-wind swdata) and returns B rotated into LMN. The matrix path above plus tvector_rotate is preferred (consistent with apply-rotation-matrix); use gsm2lmn only when you already have the arrays in hand.