STSLIB::StatsAdjacency Class Reference

Builds the sparse spatial and spatio-temporal neighbourhood graphs that define cluster support for permutation tests. More...

#include <sts_adjacency.h>

Static Public Member Functions
static Eigen::SparseMatrix< int >	fromChannelPositions (const FIFFLIB::FiffInfo &info, const QStringList &picks=QStringList())
static Eigen::SparseMatrix< int >	fromSourceSpace (const Eigen::MatrixX3i &tris, int nVertices)
static Eigen::SparseMatrix< int >	fromSourceSpaceTemporal (const Eigen::MatrixX3i &tris, int nVertices, int nTimes)
static Eigen::SparseMatrix< int >	chain (int n)
static Eigen::SparseMatrix< int >	combine (const QList< Eigen::SparseMatrix< int > > &dims)

Detailed Description

Builds the sparse spatial and spatio-temporal neighbourhood graphs that define cluster support for permutation tests.

Adjacency matrix construction for spatial clustering.

Definition at line 75 of file sts_adjacency.h.

Member Function Documentation

chain()

SparseMatrix< int > StatsAdjacency::chain ( int n )

static

Adjacency of a regular 1-D grid of n points (each linked to its two neighbours), the meaning of an integer dimension in mne.stats.combine_adjacency.

Parameters

[in]

n

Number of points.

Returns

Sparse adjacency matrix (n x n), no diagonal.

Definition at line 47 of file sts_adjacency.cpp.

combine()

SparseMatrix< int > StatsAdjacency::combine ( const QList< Eigen::SparseMatrix< int > > & dims )

static

Combine the adjacency of several dimensions, as mne.stats.combine_adjacency: points are flattened in C order (the last dimension varies fastest), two points are adjacent when they differ in one dimension and are adjacent there, and every point is adjacent to itself.

Parameters

[in]

dims

Square 0/1 adjacency per dimension (diagonals are ignored).

Returns

Sparse adjacency matrix over the product of the dimensions.

Definition at line 62 of file sts_adjacency.cpp.

fromChannelPositions()

SparseMatrix< int > StatsAdjacency::fromChannelPositions ( const FIFFLIB::FiffInfo & info, const QStringList & picks = QStringList() )

static

Build a spatial adjacency matrix from channel positions in FiffInfo. Uses a distance threshold of 3x the median nearest-neighbor distance.

Parameters

[in]	info	FiffInfo with channel positions.
[in]	picks	Optional list of channel names to include. If empty, all channels are used.

Returns

Sparse adjacency matrix (symmetric, nChannels x nChannels).

Definition at line 101 of file sts_adjacency.cpp.

fromSourceSpace()

SparseMatrix< int > StatsAdjacency::fromSourceSpace ( const Eigen::MatrixX3i & tris, int nVertices )

static

Build a spatial adjacency matrix from a triangulated source space.

Parameters

[in]	tris	Triangle definitions (nTris x 3, vertex indices).
[in]	nVertices	Total number of vertices.

Returns

Sparse adjacency matrix (symmetric, nVertices x nVertices).

Definition at line 177 of file sts_adjacency.cpp.

fromSourceSpaceTemporal()

SparseMatrix< int > StatsAdjacency::fromSourceSpaceTemporal ( const Eigen::MatrixX3i & tris, int nVertices, int nTimes )

static

Build a spatio-temporal adjacency matrix from a triangulated source space.

Constructs a (nVertices*nTimes) x (nVertices*nTimes) adjacency matrix where spatial neighbors come from the triangle mesh and temporal neighbors connect each vertex to itself at t-1 and t+1. The linear index is vertex * nTimes + time.

Parameters

[in]	tris	Triangle definitions (nTris x 3, vertex indices).
[in]	nVertices	Total number of vertices.
[in]	nTimes	Number of time points.

Returns

Sparse adjacency matrix (symmetric, nVertices*nTimes x nVertices*nTimes).

Since

2.2.0

Definition at line 202 of file sts_adjacency.cpp.

---

The documentation for this class was generated from the following files:

• src/libraries/sts/sts_adjacency.h
• src/libraries/sts/sts_adjacency.cpp