API reference

This page gives an overview of all public classes and functions within the pysecs package.

SECS Class

The primary class to set up a Spherical Elementary Current System is the SECS class.

SECS([sec_df_loc, sec_cf_loc])

Spherical Elementary Current System (SECS).

SECS Methods

The fit() and predict() methods can be called on the created system to fit to data and then predict at any other location.

SECS.fit(obs_loc, obs_B[, obs_std, epsilon, ...])	Fits the SECS to the given observations.
SECS.fit_unit_currents()	Set all SECs to a unit current amplitude.
SECS.from_observations(obs_loc, r_shell[, ...])	Build a SECS with an automatically generated grid.
SECS.predict(pred_loc[, J, return_var])	Calculate the predicted magnetic field or currents.
SECS.predict_B(pred_loc[, return_var])	Calculate the predicted magnetic fields.
SECS.predict_J(pred_loc[, return_var])	Calculate the predicted currents.
SECS.has_df	Whether this system has any divergence free currents.
SECS.has_cf	Whether this system has any curl free currents.
SECS.nsec	The number of elementary currents in this system.

Temporal estimation

The KalmanSECS class couples time steps together with a state-space model on the SEC amplitudes, estimated with a Kalman filter and Rauch-Tung-Striebel smoother.

KalmanSECS(secs, tau[, prior_std, ...])	Kalman filter / smoother for time series of SECS amplitudes.
KalmanSECS.fit(obs_loc, obs_B, times[, obs_std])	Run the filter (and smoother) over a time series of observations.
KalmanSECS.predict(pred_loc[, J, return_var])	Predict magnetic fields or currents from the estimated amplitudes.
KalmanSECS.predict_B(pred_loc[, return_var])	Predict magnetic fields; see predict().
KalmanSECS.predict_J(pred_loc[, return_var])	Predict currents; see predict().

Grid generation

SECS.from_observations builds a grid automatically with make_grid, which can also be called directly for more control.

make_grid(obs_loc, r_shell[, spacing, ...])	Build a regular SECS grid covering an observation network.
make_image_grid(grid, r_shell)	Copy a grid's latitude/longitude nodes onto a shell at another radius.

Additional functions

The helper functions create the geometrical transforms going from a pole to observation point are described below.

T_df(obs_loc, sec_loc)	Calculate the divergence free magnetic field transfer function.
T_cf(obs_loc, sec_loc)	Calculate the curl free magnetic field transfer function.
J_df(obs_loc, sec_loc)	Calculate the divergence free current density transfer function.
J_cf(obs_loc, sec_loc)	Calculate the curl free current density transfer function.
calc_angular_distance(latlon1, latlon2)	Calculate the angular distance between a set of points.
calc_bearing(latlon1, latlon2)	Calculate the bearing (direction) between a set of points.