Skip to main content

InvVectorSourceEstimate

Namespace: INVERSELIB  ·  Library: Inverse Library

Python equivalent

mne.VectorSourceEstimate in MNE-Python.

#include <inv/inv_vector_source_estimate.h>

class INVLIB::InvVectorSourceEstimate

Vector source estimate: each vertex carries a 3D orientation vector across time.

data has shape (n_vertices*3 x n_times). Rows are interleaved: [x0,y0,z0, x1,y1,z1, ...]. Use magnitude() to collapse to scalar (n_vertices x n_times) for visualisation.

Inheritance​

Public Methods​

InvVectorSourceEstimate()​

InvVectorSourceEstimate(p_sol, p_vertices, p_tmin, p_tstep)​

Construct from data and vertices.

Parameters:

  • p_sol : const Eigen::MatrixXd & Data (n_vertices*3 x n_times).

  • p_vertices : const Eigen::VectorXi & Vertex indices (n_vertices).

  • p_tmin : float Start time.

  • p_tstep : float Time step.

nVertices()​

Number of source vertices (data.rows() / 3).

magnitude()​

Compute the magnitude (L2 norm) at each vertex across time.

Returns:

vertexData(vertexIdx)​

Extract the (x, y, z) data for a specific vertex.

Parameters:

  • vertexIdx : int Local index into vertices array.

Returns:

  • Eigen::MatrixXd — Matrix (3 x n_times) for the requested vertex.

projectToNormals(normals)​

Project the 3D vectors onto surface normals to produce a signed scalar estimate.

Parameters:

  • normals : const Eigen::MatrixX3f & Surface normals (n_vertices x 3).

Returns:

Authors of this file​