neuroim

Description

Data structures for analysis of neuroimaging data.

Details

none

.isExtension

Description

.isExtension

.concat4D

.extract.array

.gridToIndex3D

.gridToIndex

.indexToGrid

.getRStorage

.getDataStorage

.getDataCode

.getDataSize

.getEndian

Usage

.isExtension(fname, extension)

.concat4D(x, y, ...)

.extract.array(x, ..., drop = FALSE, indices = list(...))

.gridToIndex3D(dimensions, voxmat)

.gridToIndex(dimensions, vmat)

.indexToGrid(idx, array.dim)

.getRStorage(dataType)

.getDataStorage(code)

.getDataCode(dataType)

.getDataSize(dataType)

.getEndian(conn)

.niftiExt(filetype)

.matrixToQuatern(mat)

AFNIFileDescriptor

Description

This class supports the AFNI file format

AFNIMetaInfo

Description

Constructor for AFNIMetaInfo class

Usage

AFNIMetaInfo(descriptor, afni_header)

Arguments

Value

an instance of class AFNIMetaInfo

Base

Description

Virtual base class representing an ordered set of named axes.

Slots

ndim

the number of axes (or dimensions)

AxisSet1D

Description

A one-dimensional axis set

Slots

i

the first axis

AxisSet2D

Description

A two-dimensional axis set

Slots

j

the second axis

AxisSet3D

Description

A three-dimensional axis set

Slots

k

the third axis

AxisSet4D

Description

A four-dimensional axis set

Slots

l

the fourth axis

AxisSet5D

Description

A five-dimensional axis set

Slots

m

the fifth axis

Base

Description

Generic S4 Base class

BaseMetaInfo

Description

This is a base class to represent meta information

BaseSource

Description

This is a base class to represent a data source

Slots

metaInfo

meta information for the data source

BinaryReader

Description

Constructor for BinaryReader class

Usage

BinaryReader(input, byteOffset, dataType, bytesPerElement,
  endian = .Platform$endian)

Arguments

BinaryReader

Description

This class supports reading of bulk binary data from a connection

Slots

input

the binary input connection

byteOffset

the number of bytes to skip at the start of input

dataType

the dataType of the binary Elements

bytesPerElement

number of bytes in each data element (e.g. 4 or 8 for floating point numbers)

endian

endianness of binary input connection

BinaryWriter

Description

This class supports writing of bulk binary data to a connection

Constructor for BinaryWriter class

Usage

BinaryWriter(output, byteOffset, dataType, bytesPerElement,
  endian = .Platform$endian)

Arguments

Slots

output

the binary output connection

byteOffset

the number of bytes to skip at the start of input

dataType

the dataType of the binary Elements

bytesPerElement

number of bytes in each data element (e.g. 4 or 8 for floating point numbers)

endian

endianness of binary output connection

Create a searchlight iterator that samples regions from within a mask. Searchlight centers are sampled *without* replacement, but the same voxel can belong to multiple searchlight samples. It is in the latter sense that this is a bootstrap resampling scheme.

Description

Create a searchlight iterator that samples regions from within a mask. Searchlight centers are sampled *without* replacement, but the same voxel can belong to multiple searchlight samples. It is in the latter sense that this is a bootstrap resampling scheme.

Usage

BootstrapSearchlight(mask, radius, iter = 100)

Arguments

BrainBucket

Description

a four-dimensional image that conists of a sequence of labeled image volumes backed by a list

Constructor function for BrainBucket class

Usage

BrainBucket(volumeList)

Arguments

Value

an instance of class BrainBucket

Slots

source

the data source for the bucket volumes

labels

the names of the sub-volumes contained in the bucket

data

a list of BrainVolume instances with names corresponding to volume labels

Examples

vol1 <- BrainVolume(rnorm(24*24*24), BrainSpace(c(24,24,24), c(1,1,1)))
vol2 <- BrainVolume(rnorm(24*24*24), BrainSpace(c(24,24,24), c(1,1,1)))
vol3 <- BrainVolume(rnorm(24*24*24), BrainSpace(c(24,24,24), c(1,1,1)))
vlist <- list(vol1,vol2,vol3)
names(vlist) <- paste0("V", 1:3)
bucket <- BrainBucket(vlist)
all.equal(dim(bucket[[1]]), dim(vol1))

BrainBucketSource

Description

A class that is used to produce a BrainBucket instance

Constructor function for BrainBucketSource class

Usage

BrainBucketSource(fileName, pattern = NULL, indices = NULL)

Arguments

Slots

sourceList

a list of sources for the bucket sub-volumes

cache

a cache used to store data in memory

BrainData

Description

Base class for brain image data

Slots

source

an instance of class BaseSource to store the source of the data

space

an instance of class BrainSpace to represent the geometry of the data space

BrainFileDescriptor

Description

This class represents a neuroimaging file format

Slots

fileFormat

the name of the file format (e.g. NIfTI)

headerEncoding

the file encoding of the header file (e.g. 'raw' for binary, 'gzip' for gz compressed')

headerExtension

the file extension for the header file (e.g. 'nii' for NIfTI single files)

dataEncoding

the file encoding for the data file

dataExtension

the file extension for the data file (e.g. 'nii' for NIfTI single files)

BrainFileSource Base class for representing a data source for images. The purpose of this class is to provide a layer in between low level IO and image loading functionality.

Description

BrainFileSource

Base class for representing a data source for images. The purpose of this class is to provide a layer in between low level IO and image loading functionality.

Slots

metaInfo

meta information for the data source

BrainMetaInfo This class contains meta information from an image

Description

BrainMetaInfo

This class contains meta information from an image

This class contains meta information for an image

Usage

BrainMetaInfo(Dim, spacing, origin = rep(0, length(spacing)),
  dataType = "FLOAT", label = "",
  spatialAxes = OrientationList3D$AXIAL_LPI, additionalAxes = NullAxis)

Arguments

Value

an instance of class BrainMetaInfo

Slots

dataType

the data type code, e.g. FLOAT

Dim

image dimensions

spatialAxes

image axes for spatial dimensions (x,y,z)

additionalAxes

axes for dimensions > 3 (e.g. time, color band, direction)

spacing

voxel dimensions

origin

coordinate origin

label

name(s) of images

BrainSlice constructor

Description

BrainSlice constructor

Usage

BrainSlice(data, space, indices = NULL)

Arguments

Examples

bspace <- BrainSpace(c(64,64), spacing=c(1,1))
dat <- array(rnorm(64*64), c(64,64))
bslice <- BrainSlice(dat,bspace)
print(bslice) 

BrainSlice

Description

Two-dimensional brain image

BrainSource

Description

Base class for representing a data source for images. The purpose of this class is to provide a layer in between low level IO and image loading functionality.

Slots

metaInfo

meta information for the data source

Constructor function for BrainSpace class

Description

Constructor function for BrainSpace class

Usage

BrainSpace(Dim, spacing = NULL, origin = NULL, axes = NULL,
  trans = NULL)

Arguments

Value

an instance of class BrainSpace

Note

one should rarely need to create a new BrainSpace instance, as it will almost always be created automatically using information stored in an image header. Also, If one already has an existing image object, its BrainSpace instance can be easily extracted with the space method.

Examples

bspace <- BrainSpace(c(64,64,64), origin=c(0,0,0), spacing=c(2,2,2))
print(bspace)
origin(bspace)
axes(bspace)
trans(bspace)

BrainSpace

Description

This class represents the geometry of a brain image

Slots

Dim

the grid dimensions of the image

origin

the coordinates of the spatial origin

spacing

the dimensions (in mm) of the grid units (voxels)

axes

the set of named spatial axes

trans

an affine transformation matrix that moves from grid -> real world coordinates

inverseTrans

an inverse matrix that moves from real world -> grid coordinates

BrainSurface

Description

a three-dimensional surface consisting of a set of triangle vertices with one value per vertex.

Slots

source

the data source for the surface

mesh

the underlying mesh3d object

data

the vector of data value at each vertex of the mesh

BrainSurfaceSource

Description

A class that is used to produce a BrainSurface instance

Constructor for BrainSurfaceSource

Usage

BrainSurfaceSource(surfaceName, surfaceDataName, index = 1)

Arguments

Slots

metaInfo

a SurfaceGeometryMetaInfo instance

dataMetaInfo

a SurfaceDataMetaInfo instance

index

the index offset into the surface data matrix

BrainSurfaceVector

Description

a three-dimensional surface consisting of a set of triangle vertices with multiple values per vertex.

Slots

source

the data source for the surface

mesh

the underlying mesh3d object

mat

a matrix of values where each column contains a vector of values over the surface nodes.

BrainSurfaceVectorSource

Description

A class that is used to produce a BrainSurfaceVectorSource instance

Slots

indices

the index vector of the volumes to be loaded

BrainVector

Description

Four-dimensional brain image

constructor function for virtual class BrainVector

Usage

BrainVector(data, space = NULL, mask = NULL, source = NULL, label = "")

Arguments

Value

a concrete instance of BrainVector class. If mask is provided then SparseBrainVector, otherwise DenseBrainVector

BrainVectorSource

Description

Construct a BrainVectorSource object

Usage

BrainVectorSource(fileName, indices = NULL, mask = NULL)

Arguments

Details

If a mask is supplied then it should be a LogicalBrainVolume or BrainVolume instance. If the latter, then the mask will be defined by nonzero elements of the volume.

Value

a instance deriving from BrainVectorSource

BrainVectorSource

Description

A class that is used to produce a BrainVectorSource instance

Slots

indices

the index vector of the volumes to be loaded

BrainVolume

Description

Construct a BrainVolume instance, using default (dense) implementation

Usage

BrainVolume(data, space, source = NULL, label = "", indices = NULL)

Arguments

Value

a DenseBrainVolume instance

Examples

bspace <- BrainSpace(c(64,64,64), spacing=c(1,1,1))
dat <- array(rnorm(64*64*64), c(64,64,64))
bvol <- BrainVolume(dat,bspace, label="test")
print(bvol) 

Base class for image representing 3D volumetric data.

Description

Base class for image representing 3D volumetric data.

BrainVolume BrainVolumeSource A class is used to produce a BrainVolume instance

Description

BrainVolume BrainVolumeSource

A class is used to produce a BrainVolume instance

Constructor for BrainVolumeSource

Usage

BrainVolumeSource(input, index = 1)

Arguments

Slots

index

the index of the volume to be read – must be of length 1.

ClusteredBrainVolume

Description

Three-dimensional brain image that is divided into N disjoint partitions

Construct a ClusteredBrainVolume instance

Usage

ClusteredBrainVolume(mask, clusters, labelMap = NULL, source = NULL,
  label = "")

Arguments

Value

ClusteredBrainVolume instance

Examples

bspace <- BrainSpace(c(16,16,16), spacing=c(1,1,1))
grid <- indexToGrid(bspace, 1:(16*16*16))
kres <- kmeans(grid, centers=10)
mask <- BrainVolume(rep(1, 16^3),bspace)
clusvol <- ClusteredBrainVolume(mask, kres$cluster)

ColumnReader

Description

Constructor for ColumnReader class

Usage

ColumnReader(nrow, ncol, reader)

Arguments

ColumnReader

Description

This class supports reading of data froma matrix-like stroage format

Slots

nrow

the number of rows

ncol

the number of columns

reader

a function that takes a set of column indices and returns a matrix

DenseBrainVector

Description

Four-dimensional brain image, backed by an array

constructor function for class DenseBrainVector

Usage

DenseBrainVector(data, space, source = NULL, label = "")

Arguments

Value

DenseBrainVector instance

DenseBrainVolume

Description

Three-dimensional brain image, backed by an array

Construct a DenseBrainVolume instance

Usage

DenseBrainVolume(data, space, source = NULL, label = "", indices = NULL)

Arguments

Value

DenseBrainVolume instance

FileMetaInfo

Description

This class contains meta information from an image data file

This class contains meta information for a NIfTI image file

This class contains meta information for a AFNI image file

Slots

headerFile

name of the file containing meta information

dataFile

name of the file containing data

fileDescriptor

descriptor of image file format

endian

byte order of data ('little' or 'big')

dataOffset

the number of bytes preceding the start of image data in data file

bytesPerElement

number of bytes per element

intercept

constant value added to image – multiple values allowed (must equal numer of sub-images)

slope

image multiplier – multiple values allowed (must equal numer of sub-images)

header

a list of format specific attributes

nifti_header

a list of attributes specific to the NIfTI file format

afni_header

a list of attributes specific to the AFNI file format

afni_header

a list of attributes specific to the AFNI file format

FresurferAsciiSurfaceFileDescriptor

Description

This class supports the FreesurferAsciiSurfaceFileDescriptor file format for surface geometry

FreeSurferSurfaceGeometryMetaInfo This class contains meta information for brain surface geometry

Description

FreeSurferSurfaceGeometryMetaInfo

This class contains meta information for brain surface geometry

IndexLookupVolume

Description

Three-dimensional brain image that can be used as a map between 1D grid indices and a table of values Currently used in the SparseBrainVector class.

IndexLookupVolume

Usage

IndexLookupVolume(space, indices)

Arguments

Create a Kernel object

Description

Create a Kernel object

Usage

Kernel(kerndim, vdim, FUN = dnorm, ...)

Arguments

Kernel

Description

A class representing an image kernel

Slots

width

the width in voxels of the kernel

weights

the kernel weights

voxels

the relative voxel coordinates of the kernel

coords

the relative real coordinates of the kernel

Layer

Description

create a Layer object

Usage

Layer(vol, colorMap = gray((0:255)/255, alpha = 1), thresh = c(0, 0),
  axis = 3, zero.col = "#000000", alpha = 1)

Arguments

Value

an object of class Layer

Layer

Description

A class used for displaying 2D images with color maps

Slots

vol

the BrainVolume that provides the data for the layer.

colorMap

a character vector of colors in hexadecimal rgb format. Can be generated by calls to rainbow, heat.colors, topo.colors, terrain.colors or similar functions.

thresh

cut-off value above which vlaues will be made transparent.

axis

the axis index of perpendicular to the xy plane (option: 1,2,3; default is 3)

zero.col

the color pixels with intensity of zero. This value overrides the color from the slot colorMap

alpha

the transparency of the layer

LogicalBrainVolume

Description

Three-dimensional brain image where all values are either TRUE or FALSE

Construct a LogicalBrainVolume instance

Usage

LogicalBrainVolume(data, space, source = NULL, label = "", indices = NULL)

Arguments

Value

LogicalBrainVolume instance

MNI SPACE 1MM

Description

This is a BrainSpace object encoding the geometry of the MNI_1MM template.

Usage

data(MNI_SPACE_1MM)

Format

a BrainSpace instance

Constructor for NIMLSurfaceDataMetaInfo class

Description

Constructor for NIMLSurfaceDataMetaInfo class

Usage

NIMLSurfaceDataMetaInfo(descriptor, header)

Arguments

NIMLSurfaceDataMetaInfo This class contains meta information for surface-based data for the NIML data format

Description

NIMLSurfaceDataMetaInfo

This class contains meta information for surface-based data for the NIML data format

Slots

data

the numeric data matrix of surface values (rows = nodes, columns=surface vectors)

nodeIndices

the indices of the nodes for mapping to associated surface geometry.

NIMLSurfaceFileDescriptor

Description

This class supports the NIML file format for surface-based data

NIfTIFileDescriptor

Description

This class supports the NIfTI file format

Constructor for NIfTIMetaInfo class

Description

Constructor for NIfTIMetaInfo class

Usage

NIfTIMetaInfo(descriptor, nifti_header)

Arguments

Value

an instance of class NIfTIMetaInfo

NamedAxis

Description

This class represents an axis with a name attribute

Slots

axis

the name of the axis

direction

of axis (-1,+1)

NullMetaInfo

Description

This is class is used to denote the absense of meta information

Create an instance of class ROIVolume

Description

Create an instance of class ROIVolume

Usage

ROIVolume(vspace, coords, data = rep(length(indices), 1))

Arguments

Value

an instance of class ROIVolume

ROIVolume

Description

A class that representing a volumetric region of interest (ROI).

Slots

data

the numeric data stored in the ROI

coords

the voxel coordinates of the ROI

Create an Random Searchlight iterator

Description

Create an Random Searchlight iterator

Usage

RandomSearchlight(mask, radius)

Arguments

Create A Cuboid Region of Interest

Description

Create A Cuboid Region of Interest

Usage

RegionCube(bvol, centroid, surround, fill = NULL, nonzero = FALSE)

Arguments

Value

an instance of class ROIVolume

Examples

 sp1 <- BrainSpace(c(10,10,10), c(1,1,1))
 cube <- RegionCube(sp1, c(5,5,5), 3)
 vox <- coords(cube)
 cube2 <- RegionCube(sp1, c(5,5,5), 3, fill=5)
 
 

Create A Spherical Region of Interest

Description

Create A Spherical Region of Interest

Usage

RegionSphere(bvol, centroid, radius, fill = NULL, nonzero = FALSE)

Arguments

Value

an instance of class ROIVolume

Examples

 sp1 <- BrainSpace(c(10,10,10), c(1,1,1))
 cube <- RegionSphere(sp1, c(5,5,5), 3.5)
 vox = coords(cube)

Create a square region of interest where the z-dimension is fixed at one voxel coordinate.

Description

Create a square region of interest where the z-dimension is fixed at one voxel coordinate.

Usage

RegionSquare(bvol, centroid, surround, fill = NULL, nonzero = FALSE,
  fixdim = 3)

Arguments

Value

an instance of class ROIVolume.

Examples

 sp1 <- BrainSpace(c(10,10,10), c(1,1,1))
 square <- RegionSquare(sp1, c(5,5,5), 1)
 vox <- coords(square)
 ## a 3 X 3 X 1 grid
 nrow(vox) == 9

Create an exhaustive searchlight iterator

Description

Create an exhaustive searchlight iterator

Usage

Searchlight(mask, radius)

Arguments

SparseBrainVector

Description

a sparse four-dimensional brain image, backed by a matrix, where each column represents a vector spanning the fourth dimension (e.g. time)

constructs a SparseBrainVector object

Usage

SparseBrainVector(data, space, mask, source = NULL, label = "")

Arguments

Slots

mask

the mask defining the sparse domain

data

the matrix of series, where rows span across voxel space and columns span the fourth dimensions

map

instance of class IndexLookupVolume is used to map between spatial and index/row coordinates

Examples

bspace <- BrainSpace(c(10,10,10,100), c(1,1,1))
mask <- array(rnorm(10*10*10) > .5, c(10,10,10))
mat <- matrix(rnorm(sum(mask)), 100, sum(mask))
svec <- SparseBrainVector(mat, bspace,mask)
length(indices(svec)) == sum(mask)

SparseBrainVectorSource

Description

A class that is used to produce a SparseBrainVector instance

constructs a SparseBrainVectorSource object

Usage

SparseBrainVectorSource(metaInfo, indices, mask)

Arguments

Slots

mask

the subset of voxels that will be stored in memory

SparseBrainVolume

Description

Three-dimensional brain image, backed by a sparseVector for Matrix package

Construct a SparseBrainVolume instance

Usage

SparseBrainVolume(data, space, indices = NULL, source = NULL, label = "")

Arguments

Details

Image data is backed by Matrix::sparseVector.

Value

SparseBrainVolume instance

Slots

data

a sparseVector instance

Examples

data <- 1:10
indices <- seq(1,1000, length.out=10)
bspace <- BrainSpace(c(64,64,64), spacing=c(1,1,1))
sparsevol <- SparseBrainVolume(data,bspace,indices=indices)
densevol <- BrainVolume(data,bspace,indices=indices)
sum(sparsevol) == sum(densevol)

Constructor for SurfaceDataMetaInfo class

Description

Constructor for SurfaceDataMetaInfo class

Usage

SurfaceDataMetaInfo(descriptor, header)

Arguments

SurfaceDataMetaInfo This class contains meta information for surface-based data (the values that map to a surface geometry)

Description

SurfaceDataMetaInfo

This class contains meta information for surface-based data (the values that map to a surface geometry)

Slots

headerFile

name of the file containing meta information

dataFile

name of the file containing data

fileDescriptor

descriptor of image file format

nodeCount

the number of nodes for which surface data exists

nels

the number of data vectors (typically the number of columns in the surface data matrix; nels = 1 for a single surface data set)

label

a label indicating the type of surface (e.g. white, pial, inflated, flat, spherical)

Constructor for SurfaceGeometryMetaInfo class

Description

Constructor for SurfaceGeometryMetaInfo class

Usage

SurfaceGeometryMetaInfo(descriptor, header)

Arguments

SurfaceGeometryMetaInfo This class contains meta information for brain surface geometry

Description

SurfaceGeometryMetaInfo

This class contains meta information for brain surface geometry

Slots

headerFile

name of the file containing meta information

dataFile

name of the file containing data

fileDescriptor

descriptor of image file format

vertices

the number of surface vertices

faces

the number of faces

embedDimension

the dimensionality of the embedding

label

a label indicating the type of surface (e.g. white, pial, inflated, flat, spherical)

extract labeled volume from BrainBucket

Description

extract labeled volume from BrainBucket

Usage

## S4 method for signature 'BrainBucket,index,missing,ANY'
x[i]

Arguments

extract data from ROIVolume

Description

extract data from ROIVolume

Usage

## S4 method for signature 'ROIVolume,numeric,missing,ANY'
x[i, j, drop]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVector,missing,missing,ANY'
x[i, j, k, m, ...,
  drop = TRUE]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVector,missing,numeric,ANY'
x[i, j, k, m, ...,
  drop = TRUE]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVector,numeric,missing,ANY'
x[i, j, k, m, ...,
  drop = TRUE]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVector,numeric,numeric,ANY'
x[i, j, k, m, ...,
  drop = TRUE]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVolume,matrix,missing,ANY'
x[i, j, k, ...,
  drop = TRUE]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVolume,missing,missing,ANY'
x[i, j, k, ...,
  drop = TRUE]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVolume,missing,numeric,ANY'
x[i, j, k, ...,
  drop = TRUE]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVolume,numeric,missing,missing'
x[i, j, k, ..., drop]

Arguments

extractor

Description

extractor

Usage

## S4 method for signature 'SparseBrainVolume,numeric,numeric,ANY'
x[i, j, k, ...,
  drop = TRUE]

Arguments

extract labeled volume from BrainBucket

Description

extract labeled volume from BrainBucket

Usage

## S4 method for signature 'BrainBucket,index,missing'
x[[i]]

Arguments

Generic function to add a dimension to an object

Description

Generic function to add a dimension to an object

add dimension to BrainSpace

Usage

addDim(x, n)

## S4 method for signature 'BrainSpace,numeric'
addDim(x, n)

Arguments

Examples

x = BrainSpace(c(10,10,10), c(1,1,1))
x1 <- addDim(x, 10)
ndim(x1) == 4
dim(x1)[4] == 10

conversion from DenseBrainVolume to array

Description

conversion from DenseBrainVolume to array

conversion from SparseBrainVolume to array

conversion from SparseBrainVolume to numeric

conversion from BrainVolume to LogicalBrainVolume

conversion from DenseBrainVolume to LogicalBrainVolume

conversion from ClusteredBrainVolume to LogicalBrainVolume

conversion from BrainVolume to array

convert BrainData instance to array

Description

convert BrainData instance to array

Usage

## S4 method for signature 'BrainData'
as.array(x)

Arguments

as.list

Description

convert SparseBrainVector to list of DenseBrainVolume

convert a BrainVector to list of volumes.

Usage

## S4 method for signature 'SparseBrainVector'
as.list(x)

## S4 method for signature 'BrainVector'
as.list(x)

Arguments

as.logical

Description

Convert BrainVolume to linkS4class{LogicalBrainVolume}

Usage

## S4 method for signature 'BrainVolume'
as.logical(x)

Arguments

Details

the image values will be converted to using R base function as.logical and wrapped in LogicalBrainVolume

Value

an instance of linkS4class{LogicalBrainVolume}

Convert to a LogicalBrainVolume

Description

Convert to a LogicalBrainVolume

Usage

as.mask(x, indices)

## S4 method for signature 'BrainVolume,missing'
as.mask(x)

## S4 method for signature 'BrainVolume,numeric'
as.mask(x, indices)

Arguments

convert BrainData instance to matrix

Description

convert BrainData instance to matrix

Usage

## S4 method for signature 'BrainData'
as.matrix(x)

Arguments

as.matrix

Description

convert SparseBrainVector to matrix

convert a DenseBrainVector to a matrix

Usage

## S4 method for signature 'SparseBrainVector'
as.matrix(x)

## S4 method for signature 'DenseBrainVector'
as.matrix(x)

Arguments

Convert SparseBrainVolume to numeric

Description

Convert SparseBrainVolume to numeric

Usage

## S4 method for signature 'SparseBrainVolume'
as.numeric(x)

Arguments

as.raster

Description

as.raster

Usage

## S4 method for signature 'Layer'
as.raster(x, zpos)

Arguments

Convert to from dense to sparse representation

Description

Convert to from dense to sparse representation

Usage

as.sparse(x, mask, ...)

## S4 method for signature 'DenseBrainVector,LogicalBrainVolume'
as.sparse(x, mask)

## S4 method for signature 'DenseBrainVector,numeric'
as.sparse(x, mask)

## S4 method for signature 'DenseBrainVolume,LogicalBrainVolume'
as.sparse(x, mask)

## S4 method for signature 'DenseBrainVolume,numeric'
as.sparse(x, mask)

Arguments

Details

mask can be an integer vector of 1D indices or a mask volume of class LogicalBrainVolume

Examples

bvol <- BrainVolume(array(runif(24*24*24), c(24,24,24)), BrainSpace(c(24,24,24), c(1,1,1)))
indmask <- sort(sample(1:(24*24*24), 100))
svol <- as.sparse(bvol, indmask)


mask <- LogicalBrainVolume(runif(length(indmask)), space=space(bvol), indices=indmask)
sum(mask) == 100

convert BrainData instance to vector

Description

convert BrainData instance to vector

Usage

## S4 method for signature 'BrainData'
as.vector(x)

Arguments

Generic getter function to extract image axes

Description

Generic getter function to extract image axes

Usage

axes(x)

## S4 method for signature 'BrainSpace'
axes(x)

## S4 method for signature 'BrainData'
axes(x)

Arguments

Generic function to convert 1-dimensional real axis coordinates along a single axis dimension to an 1D index along the same axis

Description

Generic function to convert 1-dimensional real axis coordinates along a single axis dimension to an 1D index along the same axis

Usage

axisToIndex(x, real, dimNum)

## S4 method for signature 'BrainSpace,numeric,numeric'
axisToIndex(x, real, dimNum)

Arguments

Value

a vector of axis indices

Generic function to extract the spatial bounds (origin + dim * spacing) of an image param x the object

Description

Generic function to extract the spatial bounds (origin + dim * spacing) of an image param x the object

bounds

Usage

bounds(x)

## S4 method for signature 'BrainSpace'
bounds(x)

## S4 method for signature 'BrainData'
bounds(x)

Arguments

Value

a matrix where each row contains the min (column 1) and max (column 2) bounds of the image dimension from 1 to ndim(image).

Examples

bspace <- BrainSpace(c(10,10,10), c(2,2,2))
b <- bounds(bspace)
nrow(b) == ndim(bspace)
ncol(b) == 2

close

Description

close

Usage

## S4 method for signature 'BinaryReader'
close(con)

## S4 method for signature 'BinaryWriter'
close(con)

Arguments

clusterCenters

Description

clusterCenters

Usage

clusterCenters(x, features, FUN)

## S4 method for signature 'ClusteredBrainVolume,matrix,missing'
clusterCenters(x, features)

Arguments

Concatenate two objects

Description

Concatenate two objects

Usage

concat(x, y, ...)

## S4 method for signature 'SparseBrainVector,SparseBrainVector'
concat(x, y, ...)

## S4 method for signature 'BrainVector,BrainVolume'
concat(x, y, ...)

## S4 method for signature 'BrainVolume,BrainVector'
concat(x, y, ...)

## S4 method for signature 'BrainVector,BrainVector'
concat(x, y, ...)

## S4 method for signature 'DenseBrainVolume,DenseBrainVolume'
concat(x, y, ...)

Arguments

Details

The x and y images must have compatible dimensions. a BrainVolume can be concatenated to BrainVector, and vice versa. See examples.

Note

dimensions of x and y must be equal

Examples

bv1 <- BrainVolume(rep(1,1000), BrainSpace(c(10,10,10), c(1,1,1)))
bv2 <- BrainVolume(rep(2,1000), BrainSpace(c(10,10,10), c(1,1,1)))
bv3 <- concat(bv1,bv2)
inherits(bv3, "BrainVector")

bv4 <- concat(bv3, bv1)
dim(bv4)[4] == 3
bv5 <- concat(bv1, bv3)
dim(bv4)[4] == 3

bv6 <- concat(bv4,bv5)
dim(bv6)[4] == 6

Find connected components

Description

Find connected components

find connected components in BrainVolume

Usage

connComp(x, ...)

## S4 method for signature 'BrainVolume'
connComp(x, threshold = 0, clusterTable = TRUE,
  localMaxima = TRUE, localMaximaDistance = 15)

Arguments

Extract connected components from a 3D mask

Description

Extract connected components from a 3D mask

Usage

connComp3D(mask)

Arguments

Value

a two-element list of the connected components (cluster index and cluster size) The first element index is a 3D array containing the cluster index of the connected component for each voxel. The second element size is a 3D array consisting of the size of the connected component inhabited by each voxel.

Generic function to convert N-dimensional real world coordinates to grid coordinates

Description

Generic function to convert N-dimensional real world coordinates to grid coordinates

Usage

coordToGrid(x, coords)

## S4 method for signature 'BrainSpace,matrix'
coordToGrid(x, coords)

## S4 method for signature 'BrainSpace,numeric'
coordToGrid(x, coords)

## S4 method for signature 'BrainVolume,matrix'
coordToGrid(x, coords)

Arguments

Value

a matrix of grid coordinates

Generic function to convert N-dimensional real world coordinates to 1D indices

Description

Generic function to convert N-dimensional real world coordinates to 1D indices

Usage

coordToIndex(x, coords)

## S4 method for signature 'BrainSpace,matrix'
coordToIndex(x, coords)

## S4 method for signature 'BrainSpace,numeric'
coordToIndex(x, coords)

## S4 method for signature 'BrainVolume,matrix'
coordToIndex(x, coords)

Arguments

Value

a vector of indices

Extract coordinates

Description

Extract coordinates

coords

Usage

coords(x, ...)

## S4 method for signature 'ROIVolume'
coords(x)

## S4 method for signature 'SparseBrainVector'
coords(x, i)

## S4 method for signature 'IndexLookupVolume'
coords(x, i)

Arguments

Generic function to get the name of the data file, given a file name and a BrainFileDescriptor instance.

Description

Generic function to get the name of the data file, given a file name and a BrainFileDescriptor instance.

Usage

dataFile(x, fileName)

## S4 method for signature 'BrainFileDescriptor,character'
dataFile(x, fileName)

Arguments

Value

the correct header name

Generic function to test whether a file name conforms to the given a BrainFileDescriptor instance. Will test for match to data file only

Description

Generic function to test whether a file name conforms to the given a BrainFileDescriptor instance. Will test for match to data file only

Usage

dataFileMatches(x, fileName)

## S4 method for signature 'BrainFileDescriptor,character'
dataFileMatches(x, fileName)

Arguments

Value

TRUE for match, FALSE otherwise

Generic function to create data reader

Description

Generic function to create data reader

Usage

dataReader(x, offset)

## S4 method for signature 'NIfTIMetaInfo'
dataReader(x, offset = 0)

## S4 method for signature 'AFNIMetaInfo'
dataReader(x, offset = 0)

## S4 method for signature 'NIMLSurfaceDataMetaInfo'
dataReader(x)

Arguments

dim of BrainData object

Description

dim of BrainData object

Usage

## S4 method for signature 'BrainData'
dim(x)

Arguments

dim

Description

dim

Usage

## S4 method for signature 'BrainSpace'
dim(x)

Arguments

dim of FileMetaInfo

Description

dim of FileMetaInfo

Usage

## S4 method for signature 'FileMetaInfo'
dim(x)

Arguments

Generic function to drop a dimension from an object

Description

Generic function to drop a dimension from an object

Usage

dropDim(x, dimnum)

## S4 method for signature 'AxisSet2D,numeric'
dropDim(x, dimnum)

## S4 method for signature 'AxisSet2D,missing'
dropDim(x, dimnum)

## S4 method for signature 'AxisSet3D,numeric'
dropDim(x, dimnum)

## S4 method for signature 'AxisSet3D,missing'
dropDim(x, dimnum)

## S4 method for signature 'BrainSpace,numeric'
dropDim(x, dimnum)

## S4 method for signature 'BrainSpace,missing'
dropDim(x)

Arguments

Examples

x = BrainSpace(c(10,10,10), c(1,1,1))
x1 <- dropDim(x)
ndim(x1) == 2
dim(x1)[2] == 10

Generic functions to apply a function to each series of a 4D image That is, if the 4th dimension is 'time' each series is a 1D time series.

Description

Generic functions to apply a function to each series of a 4D image That is, if the 4th dimension is 'time' each series is a 1D time series.

Usage

eachSeries(x, FUN, withIndex, ...)

## S4 method for signature 'SparseBrainVector,'function',logical'
eachSeries(x, FUN,
  withIndex = FALSE, ...)

## S4 method for signature 'BrainVector,'function',missing'
eachSeries(x, FUN,
  withIndex = FALSE, ...)

Arguments

Details

when x is a SparseBrainVector eachSeries only iterates over nonzero series.

Examples

bvec <- BrainVector(array(rnorm(24*24*24*24), c(24,24,24,24)), BrainSpace(c(24,24,24,24), c(1,1,1)))
res <- eachSeries(bvec, mean)
length(res) == 24*24*24

Generic functions to apply a function to each (2D) slice of an image

Description

Generic functions to apply a function to each (2D) slice of an image

Usage

eachSlice(x, FUN, withIndex, ...)

## S4 method for signature 'BrainVolume,'function',missing'
eachSlice(x, FUN)

## S4 method for signature 'BrainVolume,'function',logical'
eachSlice(x, FUN, withIndex)

Arguments

Generic function to apply a function to each volume of a four-dimensional image

Description

Generic function to apply a function to each volume of a four-dimensional image

Usage

eachVolume(x, FUN, withIndex, mask, ...)

## S4 method for signature 'SparseBrainVector,'function',logical,missing'
eachVolume(x, FUN,
  withIndex = FALSE, mask, ...)

## S4 method for signature 'SparseBrainVector,'function',missing,missing'
eachVolume(x, FUN,
  withIndex, mask, ...)


  ## S4 method for signature 
## 'SparseBrainVector,‘function',missing,LogicalBrainVolume’
eachVolume(x,
  FUN, withIndex, mask, ...)

## S4 method for signature 'BrainVector,'function',missing,missing'
eachVolume(x, FUN, withIndex,
  mask, ...)

## S4 method for signature 'BrainVector,'function',missing,BrainVolume'
eachVolume(x, FUN,
  withIndex, mask, ...)

## S4 method for signature 'BrainVector,'function',missing,missing'
eachVolume(x, FUN, withIndex,
  mask, ...)

## S4 method for signature 'BrainBucket,'function',missing,missing'
eachVolume(x, FUN, withIndex,
  mask, ...)

## S4 method for signature 'BrainBucket,'function',logical,ANY'
eachVolume(x, FUN, withIndex,
  mask, ...)

## S4 method for signature 'BrainVector,'function',logical,ANY'
eachVolume(x, FUN, withIndex,
  mask, ...)

Arguments

Value

a list of results of apply FUN to each volume.

Examples

bvec <- BrainVector(array(rnorm(24*24*24*24), c(24,24,24,24)), BrainSpace(c(24,24,24,24), c(1,1,1)))
res <- eachVolume(bvec, mean)

res <- eachVolume(bvec, function(x,i) median(x), withIndex=TRUE)

Generic function to test whether a file name conforms to the given BrainFileDescriptor instance. Will test for match to either header file or data file

Description

Generic function to test whether a file name conforms to the given BrainFileDescriptor instance. Will test for match to either header file or data file

Usage

fileMatches(x, fileName)

## S4 method for signature 'BrainFileDescriptor,character'
fileMatches(x, fileName)

Arguments

Value

TRUE for match, FALSE otherwise

Generic function to map values from one set to another using a user-supplied lookup table

Description

Generic function to map values from one set to another using a user-supplied lookup table

Usage

fill(x, lookup)

## S4 method for signature 'BrainVolume,list'
fill(x, lookup)

## S4 method for signature 'BrainVolume,matrix'
fill(x, lookup)

Arguments

Value

a new object where the original values have been filled in with the values in the lookup table

Examples

x <- BrainSpace(c(10,10,10), c(1,1,1))
vol <- BrainVolume(sample(1:10, 10*10*10, replace=TRUE), x)

## lookup table is list
lookup <- lapply(1:10, function(i) i*10)
ovol <- fill(vol, lookup)

## lookup table is matrix. First column is key, second column is value
names(lookup) <- 1:length(lookup)
lookup.mat <- cbind(as.numeric(names(lookup)), unlist(lookup))
ovol2 <- fill(vol, lookup.mat)
all.equal(as.vector(ovol2), as.vector(ovol))

Generic function to convert N-dimensional grid coordinate coordinates to real world coordinates Generic function to convert N-dimensional grid coordinates to real world coordinates

Description

Generic function to convert N-dimensional grid coordinate coordinates to real world coordinates Generic function to convert N-dimensional grid coordinates to real world coordinates

Usage

gridToCoord(x, coords)

## S4 method for signature 'BrainSpace,matrix'
gridToCoord(x, coords)

## S4 method for signature 'BrainVolume,matrix'
gridToCoord(x, coords)

Arguments

Value

a matrix of real coordinates

Generic function to convert N-dimensional grid coordinate to 1D indices

Description

Generic function to convert N-dimensional grid coordinate to 1D indices

Usage

gridToIndex(x, coords)

## S4 method for signature 'BrainSlice,matrix'
gridToIndex(x, coords)

## S4 method for signature 'BrainSpace,matrix'
gridToIndex(x, coords)

## S4 method for signature 'BrainSpace,numeric'
gridToIndex(x, coords)

## S4 method for signature 'BrainVolume,matrix'
gridToIndex(x, coords)

## S4 method for signature 'BrainVolume,numeric'
gridToIndex(x, coords)

Arguments

Value

a vector of indices

Generic function to get the name of the header file, given a file name and a BrainFileDescriptor instance.

Description

Generic function to get the name of the header file, given a file name and a BrainFileDescriptor instance.

Usage

headerFile(x, fileName)

## S4 method for signature 'BrainFileDescriptor,character'
headerFile(x, fileName)

Arguments

Value

the correct header name

Generic function to test whether a file name conforms to the given BrainFileDescriptor instance. Will test for match to header file only

Description

Generic function to test whether a file name conforms to the given BrainFileDescriptor instance. Will test for match to header file only

Usage

headerFileMatches(x, fileName)

## S4 method for signature 'BrainFileDescriptor,character'
headerFileMatches(x, fileName)

Arguments

Value

TRUE for match, FALSE otherwise

image

Description

image

image

Usage

## S4 method for signature 'BrainVolume'
image(x, slice, col = gray((0:255)/255, alpha = 1),
  zero.col = "#000000", axis = 3, ...)

## S4 method for signature 'Overlay'
image(x, zpos, axis = 3)

## S4 method for signature 'Layer'
image(x, zpos, axis = 3)

Arguments

imageGrid

Description

Display a set of images slices in a 2D montage

Usage

imageGrid(layer, gridDim = c(3, 3), zstart, zend, panelSize = 3,
  panelUnit = "inches", interpolate = FALSE, fontCol = "red")

Arguments

Generic function to convert 1D indices to N-dimensional real world coordinates

Description

Generic function to convert 1D indices to N-dimensional real world coordinates

Usage

indexToCoord(x, idx)

## S4 method for signature 'BrainSpace,index'
indexToCoord(x, idx)

## S4 method for signature 'BrainVolume,index'
indexToCoord(x, idx)

Arguments

Value

a matrix of real coordinates

Examples

bvol <- BrainVolume(array(0, c(10,10,10)), BrainSpace(c(10,10,10), c(1,1,1)))
idx <- 1:10
g <- indexToCoord(bvol, idx)
idx2 <- coordToIndex(bvol, g)
all.equal(idx, idx2)

Generic function to convert 1D indices to N-dimensional grid coordinates

Description

Generic function to convert 1D indices to N-dimensional grid coordinates

Usage

indexToGrid(x, idx)

## S4 method for signature 'BrainSlice,index'
indexToGrid(x, idx)

## S4 method for signature 'BrainSpace,index'
indexToGrid(x, idx)

## S4 method for signature 'BrainVector,index'
indexToGrid(x, idx)

## S4 method for signature 'BrainVolume,index'
indexToGrid(x, idx)

Arguments

Value

a matrix of grid coordinates

Examples

 
 bvol <- BrainVolume(array(0, c(10,10,10)), BrainSpace(c(10,10,10), c(1,1,1)))
 idx <- 1:10
 g <- indexToGrid(bvol, idx)
 bvol[g]

Extract indices

Description

Extract indices

indices

Usage

indices(x)

## S4 method for signature 'ROIVolume'
indices(x)

## S4 method for signature 'SparseBrainVector'
indices(x)

## S4 method for signature 'IndexLookupVolume'
indices(x)

Arguments

Generic getter to extract inverse image coordinate transformation

Description

Generic getter to extract inverse image coordinate transformation

Usage

inverseTrans(x)

## S4 method for signature 'BrainSpace'
inverseTrans(x)

## S4 method for signature 'BrainData'
inverseTrans(x)

Arguments

Examples

bspace <- BrainSpace(c(10,10,10), c(2,2,2))
itrans <- inverseTrans(bspace)
identical(trans(bspace) %*% inverseTrans(bspace), diag(4))

Get length of BrainVector. This is the numbe rof volumes in the volume vector (e.g. the 4th image dimension)

Description

Get length of BrainVector. This is the numbe rof volumes in the volume vector (e.g. the 4th image dimension)

Usage

## S4 method for signature 'ROIVolume'
length(x)

## S4 method for signature 'BrainVector'
length(x)

Arguments

loadBucket

Description

load a BrainBucket object from file

Usage

loadBucket(fileName, pattern = NULL, indices = NULL)

Arguments

Generic function to load data from a data source

Description

Generic function to load data from a data source

load a BrainSurface

loadData

Load data from a BrainBucketSource

load a BrainVolume

Usage

loadData(x, ...)

## S4 method for signature 'BrainSurfaceSource'
loadData(x)

## S4 method for signature 'SparseBrainVectorSource'
loadData(x)

## S4 method for signature 'BrainVectorSource'
loadData(x, mmap = FALSE)

## S4 method for signature 'BrainBucketSource'
loadData(x, key)

## S4 method for signature 'BrainVolumeSource'
loadData(x)

Arguments

Value

an instance of class BrainVector

an instance of class BrainVolume

load Freesurfer ascii surface

Description

load Freesurfer ascii surface

Usage

loadFSSurface(mesh)

Arguments

load an surface from a set of files

Description

load an surface from a set of files

Usage

loadSurface(surfaceName, surfaceDataName)

Arguments

Value

an instance of the class BrainSurface

loadVector

Description

load an image volume from a file

Usage

loadVector(fileName, indices = NULL, mask = NULL)

Arguments

Value

an BrainVector object

Load an image volume from a file

Description

Load an image volume from a file

Usage

loadVolume(fileName, index = 1)

Arguments

Value

an instance of the class DenseBrainVolume

Examples

fname <- system.file("extdata", "global_mask.nii", package="neuroim")
x <- loadVolume(fname)
print(dim(x))
space(x)

loadVolList

Description

load a list of image volumes and return a BrainVector instance

Usage

loadVolumeList(fileNames, mask = NULL)

Arguments

Value

an instance of class BrainVector

Index Lookup operation

Description

Index Lookup operation

lookup

Usage

lookup(x, i, ...)

## S4 method for signature 'SparseBrainVector,numeric'
lookup(x, i)

## S4 method for signature 'IndexLookupVolume,numeric'
lookup(x, i)

Arguments

makeVector

Description

Construct a BrainVector instance, using default (dense) implementation

Usage

makeVector(data, refdata, source = NULL, label = "")

Arguments

Value

DenseBrainVector instance

makeVolume

Description

Construct a BrainVolume instance, using default (dense) implementation

Usage

makeVolume(data = NULL, refvol, source = NULL, label = "",
  indices = NULL)

Arguments

Value

DenseBrainVolume instance

Examples

bspace <- BrainSpace(c(64,64,64), spacing=c(1,1,1))
dat <- array(rnorm(64*64*64), c(64,64,64))
bvol <- BrainVolume(dat,bspace, label="test")
bvol2 <- makeVolume(dat, bvol)
all.equal(as.array(bvol),as.array(bvol2))
data <- 1:10
indices = seq(1,1000, length.out=10)
bvol3 <- makeVolume(data,bvol,indices=indices)
sum(bvol3) == sum(data)

Generic function to apply a function to an object

Description

Generic function to apply a function to an object

apply a kernel function to a BrainVolume

Usage

map(x, m, ...)

## S4 method for signature 'BrainVolume,Kernel'
map(x, m, mask = NULL)

Arguments

mapToColors

Description

map an matrix of intensity values to a matrix of color values.

Usage

mapToColors(imslice, col = heat.colors(128, alpha = 1),
  zero.col = "#00000000", alpha = 1)

Arguments

given two named axes return AxisSet2D singleton

Description

given two named axes return AxisSet2D singleton

Usage

matchAnatomy2D(axis1, axis2)

Arguments

given three named axes return AxisSet3D singleton

Description

given three named axes return AxisSet3D singleton

Usage

matchAnatomy3D(axis1, axis2, axis3)

Arguments

matrixToVolumeList converts a matrix to a list of BrainVolumes with values filled at grid coordinates determined by the vox argument.

Description

matrixToVolumeList converts a matrix to a list of BrainVolumes with values filled at grid coordinates determined by the vox argument.

Usage

matrixToVolumeList(voxmat, mat, mask, default = NA)

Arguments

Value

a list of BrainVolume instances, one for each column of mat

mergePartitions

Description

mergePartitions

merge partititons in a ClusteredBrainVolume

Usage

mergePartitions(x, K, features, ...)

## S4 method for signature 'ClusteredBrainVolume,numeric,matrix'
mergePartitions(x, K, features)

Arguments

names

Description

names

Usage

## S4 method for signature 'BrainBucketSource'
names(x)

## S4 method for signature 'BrainBucket'
names(x)

Arguments

Generic function to extract the number of dimensions of an object

Description

Generic function to extract the number of dimensions of an object

Usage

ndim(x, ...)

## S4 method for signature 'AxisSet'
ndim(x, ...)

## S4 method for signature 'BrainData'
ndim(x)

## S4 method for signature 'BrainSpace'
ndim(x)

Arguments

Examples

x = BrainSpace(c(10,10,10), c(1,1,1))
ndim(x) == 3
x = BrainSpace(c(10,10,10,3), c(1,1,1,1))
ndim(x) == 4

numClusters

Description

numClusters

get number of clusters in a ClusteredBrainVolume

Usage

numClusters(x)

## S4 method for signature 'ClusteredBrainVolume'
numClusters(x)

Arguments

Generic getter to extract image origin

Description

Generic getter to extract image origin

Usage

origin(x)

## S4 method for signature 'BrainSpace'
origin(x)

## S4 method for signature 'BrainData'
origin(x)

Arguments

Examples

bspace <- BrainSpace(c(10,10,10), c(2,2,2))
origin(bspace)

overlay two objects

Description

overlay two objects

overlay

Usage

overlay(x, y, ...)

## S4 method for signature 'Layer,Layer'
overlay(x, y)

## S4 method for signature 'Overlay,Layer'
e1 + e2

## S4 method for signature 'Layer,Layer'
e1 + e2

Arguments

partition

Description

partition

partition a ClusteredBrainVolume into K spatial disjoint components for every existing partition in the volume

Usage

partition(x, K, features, ...)

## S4 method for signature 'ClusteredBrainVolume,numeric,matrix'
partition(x, K, features,
  method = "kmeans")

Arguments

Extract permutation matrix

Description

Extract permutation matrix

permMat

Usage

permMat(x, ...)

## S4 method for signature 'AxisSet2D'
permMat(x, ...)

Arguments

pick

Description

pick

Usage

pick(x, mask, ...)

Arguments

Generic function to print an object

Description

Generic function to print an object

Usage

print(x, ...)

Arguments

print a AxisSet2D instance

Description

print a AxisSet2D instance

Usage

## S4 method for signature 'AxisSet2D'
print(x, ...)

Arguments

print a AxisSet3D instance

Description

print a AxisSet3D instance

Usage

## S4 method for signature 'AxisSet3D'
print(x, ...)

Arguments

print a NamedAxis

Description

print a NamedAxis

Usage

## S4 method for signature 'NamedAxis'
print(x, ...)

Arguments

readAFNIHeader

Description

readAFNIHeader

Usage

readAFNIHeader(fileName)

Arguments

Generic function to read a set of column vector from an input source (e.g. ColumnReader)

Description

Generic function to read a set of column vector from an input source (e.g. ColumnReader)

Usage

readColumns(x, columnIndices)

## S4 method for signature 'ColumnReader,numeric'
readColumns(x, columnIndices)

Arguments

Value

a matrix consisting of the requested column vectors

Generic function to read a sequence of elements from an input source

Description

Generic function to read a sequence of elements from an input source

readElements

Usage

readElements(x, numElements)

## S4 method for signature 'BinaryReader,numeric'
readElements(x, numElements)

Arguments

Value

the elements as a vector

read header information of an image file

Description

read header information of an image file

Usage

readHeader(fileName)

Arguments

Value

an instance of class FileMetaInfo

Generic function to read image meta info given a file and a BrainFileDescriptor instance.

Description

Generic function to read image meta info given a file and a BrainFileDescriptor instance.

Usage

readMetaInfo(x, fileName)

## S4 method for signature 'NIfTIFileDescriptor'
readMetaInfo(x, fileName)

## S4 method for signature 'AFNIFileDescriptor'
readMetaInfo(x, fileName)

## S4 method for signature 'NIMLSurfaceFileDescriptor'
readMetaInfo(x, fileName)

## S4 method for signature 'FreesurferAsciiSurfaceFileDescriptor'
readMetaInfo(x, fileName)

Arguments

Render an image to create a drawable image.

Description

Render an image to create a drawable image.

Usage

render(x, width, height, colmap, ...)

## S4 method for signature 'BrainSlice,numeric,numeric,character'
render(x, width, height,
  colmap, zero.col = "#000000FF", alpha = 1, units = "mm")

Arguments

Render a slice at z coordinate

Description

Render a slice at z coordinate

Usage

renderSlice(x, zpos, width, height, colmap, ...)

## S4 method for signature 'Overlay,numeric,numeric,numeric,missing'
renderSlice(x, zpos, width,
  height, zero.col = "#000000FF", units = "mm")

## S4 method for signature 'Layer,numeric,numeric,numeric,missing'
renderSlice(x, zpos, width,
  height, colmap, zero.col = "#000000FF", units = "mm")

Arguments

Generic functions to scale (center and/or normalize by standard deviation) each series of a 4D image That is, if the 4th dimension is 'time' each series is a 1D time series.

Description

Generic functions to scale (center and/or normalize by standard deviation) each series of a 4D image That is, if the 4th dimension is 'time' each series is a 1D time series.

Usage

scaleSeries(x, center, scale)

## S4 method for signature 'BrainVector,logical,logical'
scaleSeries(x, center, scale)

## S4 method for signature 'BrainVector,missing,logical'
scaleSeries(x, center, scale)

## S4 method for signature 'BrainVector,missing,missing'
scaleSeries(x, center, scale)

## S4 method for signature 'BrainVector,logical,missing'
scaleSeries(x, center, scale)

Arguments

Examples

bvec <- BrainVector(array(rnorm(24*24*24*24), c(24,24,24,24)), BrainSpace(c(24,24,24,24), c(1,1,1)))
res <- scaleSeries(bvec, TRUE, TRUE)

Extract vector series from object

Description

Extract vector series from object

Usage

series(x, i, ...)

## S4 method for signature 'SparseBrainVector,matrix'
series(x, i)

## S4 method for signature 'SparseBrainVector,numeric'
series(x, i, j, k)

## S4 method for signature 'BrainVector,matrix'
series(x, i)

## S4 method for signature 'BrainVector,numeric'
series(x, i, j, k)

Arguments

seriesIter

Description

Construct a series iterator

Usage

seriesIter(x)

## S4 method for signature 'SparseBrainVector'
seriesIter(x)

## S4 method for signature 'BrainVector'
seriesIter(x)

Arguments

Value

an iter object from the iterators package.

Methods (by class)

• SparseBrainVector: get a seriesIter for a SparseBrainVector instance

• BrainVector: get a series iterator for a BrainVector instance

Examples

## create a BrainVector with 10X10X10X10, where the last dimension is 
## by convention the fourth dimension.
bvec <- BrainVector(array(rnorm(10*10*10*10), rep(10,4)), BrainSpace(rep(10,4), c(1,1,1)))
iter <- seriesIter(bvec)

## compute mean of each series
library(foreach)
library(iterators)
foreach(i=iter, .combine=c) %do% { mean(i) }
iter <- seriesIter(bvec)

## combine all series into a matrix
foreach(i=iter, .combine=rbind) %do% { i }

## scale all series, add as columns in matrix.
foreach(i=seriesIter(bvec), .combine=cbind) %do% { scale(i) }

show an AxisSet1D

Description

show an AxisSet1D

Usage

## S4 method for signature 'AxisSet1D'
show(object)

Arguments

show an AxisSet2D

Description

show an AxisSet2D

Usage

## S4 method for signature 'AxisSet2D'
show(object)

Arguments

show an AxisSet3D

Description

show an AxisSet3D

Usage

## S4 method for signature 'AxisSet3D'
show(object)

Arguments

show an AxisSet4D

Description

show an AxisSet4D

Usage

## S4 method for signature 'AxisSet4D'
show(object)

Arguments

show a BaseMetaInfo

Description

show a BaseMetaInfo

Usage

## S4 method for signature 'BaseMetaInfo'
show(object)

Arguments

show a BrainSpace

Description

show a BrainSpace

Usage

## S4 method for signature 'BrainSpace'
show(object)

Arguments

show a BrainVector

Description

show a BrainVector

Usage

## S4 method for signature 'BrainVector'
show(object)

Arguments

show a BrainVectorSource

Description

show a BrainVectorSource

Usage

## S4 method for signature 'BrainVectorSource'
show(object)

Arguments

show a BrainVolume

Description

show a BrainVolume

Usage

## S4 method for signature 'BrainVolume'
show(object)

Arguments

show a FileMetaInfo

Description

show a FileMetaInfo

Usage

## S4 method for signature 'FileMetaInfo'
show(object)

Arguments

show an NamedAxis

Description

show an NamedAxis

Usage

## S4 method for signature 'NamedAxis'
show(object)

Arguments

show a NullMetaInfo

Description

show a NullMetaInfo

Usage

## S4 method for signature 'NullMetaInfo'
show(object)

Arguments

show an ROIVolime

Description

show an ROIVolime

Usage

## S4 method for signature 'ROIVolume'
show(object)

Arguments

show a SparseBrainVector

Description

show a SparseBrainVector

Usage

## S4 method for signature 'SparseBrainVector'
show(object)

Arguments

show an SurfaceDataMetaInfo

Description

show an SurfaceDataMetaInfo

Usage

## S4 method for signature 'SurfaceDataMetaInfo'
show(object)

Arguments

show an SurfaceGeometryMetaInfo

Description

show an SurfaceGeometryMetaInfo

Usage

## S4 method for signature 'SurfaceGeometryMetaInfo'
show(object)

Arguments

Extract a 2D slice from an image volume

Description

Extract a 2D slice from an image volume

Usage

slice(x, zlevel, along, orientation, ...)

## S4 method for signature 'BrainVolume,numeric,numeric,character'
slice(x, zlevel, along,
  orientation)

Arguments

sliceData

Description

extract a 2D slice from a BrainVolume instance.

Usage

sliceData(vol, slice, axis = 3)

Arguments

Generic function to extract geometric properties of an image.

Description

Generic function to extract geometric properties of an image.

Usage

space(x, ...)

## S4 method for signature 'BrainData'
space(x)

## S4 method for signature 'BrainSpace'
space(x)

## S4 method for signature 'IndexLookupVolume'
space(x)

Arguments

Value

an object representing the geometric space of the image of type BrainSpace

Examples

x = BrainSpace(c(10,10,10), c(1,1,1))
vol <- BrainVolume(rnorm(10*10*10), x)
identical(x,space(vol))

Generic function to extract the voxel dimensions of an image

Description

Generic function to extract the voxel dimensions of an image

spacing

Usage

spacing(x)

## S4 method for signature 'BrainData'
spacing(x)

## S4 method for signature 'BrainSpace'
spacing(x)

Arguments

Value

a numeric vector

Examples

bspace <- BrainSpace(c(10,10,10), c(2,2,2))
all.equal(spacing(bspace), c(2,2,2))

Generic function to fill disjoint sets of values with the output of a function

Description

Generic function to fill disjoint sets of values with the output of a function

Usage

splitFill(x, fac, FUN)

## S4 method for signature 'BrainVolume,factor,'function''
splitFill(x, fac, FUN)

Arguments

Details

FUN can either return a scalar for each input vector or a vector equal to the length of the input vector. If it returns a scalar then every voxel in the set will be filled with that value in the output vector.

Value

a new object where the original values have been replaced by the function output

Examples

## summarize with mean -- FUN returns a scalar
x = BrainSpace(c(10,10,10), c(1,1,1))
vol <- BrainVolume(rnorm(10*10*10), x)
fac <- factor(rep(1:10, length.out=1000))
ovol.mean <- splitFill(vol, fac, mean)
identical(dim(ovol.mean), dim(vol))
length(unique(as.vector(ovol.mean))) == 10
## transform by reversing vector -- FUN returns a vector.
ovol2 <- splitFill(vol, fac, rev)

Generic function to summarize subsets of an object by first splitting by row and then "reducing" by a summary function

Description

Generic function to summarize subsets of an object by first splitting by row and then "reducing" by a summary function

Usage

splitReduce(x, fac, FUN)

## S4 method for signature 'matrix,integer,'function''
splitReduce(x, fac, FUN)

## S4 method for signature 'matrix,integer,missing'
splitReduce(x, fac)

## S4 method for signature 'matrix,factor,missing'
splitReduce(x, fac)

## S4 method for signature 'matrix,factor,'function''
splitReduce(x, fac, FUN)

## S4 method for signature 'BrainVector,factor,'function''
splitReduce(x, fac, FUN)

## S4 method for signature 'BrainVector,factor,missing'
splitReduce(x, fac, FUN)

Arguments

Details

if FUN is supplied it must take a vector and return a single scalar value. If it returns more than one value, an error will occur.

if x is a BrainVector instance then voxels (dims 1:3) are treated as columns and time-series (dim 4) as rows. The summary function then is applied to groups of voxels. However, if the goal is to apply a function to groups of time-points, then this can be achieved as follows:

splitReduce(t(as.matrix(bvec)), fac)

Value

a new matrix where the original values have been reduced

Examples

mat = matrix(rnorm(100*100), 100, 100)
fac = sample(1:3, nrow(mat), replace=TRUE)
## compute column means of each sub-matrix
ms <- splitReduce(mat, fac)
all.equal(row.names(ms), levels(fac))

## compute column medians of each sub-matrix
ms <- splitReduce(mat, fac, median)

## compute time-series means grouped over voxels. 
## Here, \code{length(fac)} must equal the number of voxels: \code{prod(dim(bvec)[1:3]}
bvec <- BrainVector(array(rnorm(24*24*24*24), c(24,24,24,24)), BrainSpace(c(24,24,24,24), c(1,1,1)))
fac <- factor(sample(1:3, prod(dim(bvec)[1:3]), replace=TRUE))
ms <- splitReduce(bvec, fac)
ms2 <- splitReduce(bvec, fac, mean)
all.equal(row.names(ms), levels(fac))
all.equal(ms,ms2)

Generic function to center/scale row-subsets of a matrix or matrix-like object

Description

Generic function to center/scale row-subsets of a matrix or matrix-like object

Usage

splitScale(x, f, center, scale)

## S4 method for signature 'matrix,factor,logical,logical'
splitScale(x, f, center = TRUE,
  scale = TRUE)

## S4 method for signature 'matrix,factor,missing,missing'
splitScale(x, f)

Arguments

Value

a new matrix or matrix-like object where the original rows have been grouped by f and then centered and/or scaled for each grouping

Examples

M <- matrix(rnorm(1000), 10, 100)
fac <- factor(rep(1:2, each=5))
Ms <- splitScale(M, fac)

## correctly centered
all(abs(apply(Ms[fac == 1,], 2, mean)) < .000001)
all(abs(apply(Ms[fac == 2,], 2, mean)) < .000001)

# correctly scaled
all.equal(apply(Ms[fac == 1,], 2, sd), rep(1, ncol(Ms)))
all.equal(apply(Ms[fac == 2,], 2, sd), rep(1, ncol(Ms)))

Generic function to strip extension from file name, given a BrainFileDescriptor instance.

Description

Generic function to strip extension from file name, given a BrainFileDescriptor instance.

Usage

stripExtension(x, fileName)

## S4 method for signature 'BrainFileDescriptor,character'
stripExtension(x, fileName)

Arguments

Value

fileName without extension

Generic function to extract a sub-vector from a BrainVector object.

Description

Generic function to extract a sub-vector from a BrainVector object.

Usage

subVector(x, i, ...)

## S4 method for signature 'SparseBrainVector,numeric'
subVector(x, i)

## S4 method for signature 'DenseBrainVector,numeric'
subVector(x, i)

Arguments

Value

a BrainVector object that is a sub-vector of the supplied object.

Examples

bvec <- BrainVector(array(rnorm(24*24*24*24), c(24,24,24,24)), BrainSpace(c(24,24,24,24), c(1,1,1)))
vec <- subVector(bvec,1:2)
all.equal(2, dim(vec)[4])

vec <- subVector(bvec, c(1,3,5,7))
all.equal(4, dim(vec)[4])

mask <- LogicalBrainVolume(rep(TRUE, 24*24*24), BrainSpace(c(24,24,24), c(1,1,1)))
svec <- SparseBrainVector(array(rnorm(24*24*24*24), c(24,24,24,24)), 
BrainSpace(c(24,24,24,24), c(1,1,1)), mask)
vec <- subVector(svec, c(1,3,5))
all.equal(3, dim(vec)[4])

Generic function to extract a set of series from a 4D image

Description

Generic function to extract a set of series from a 4D image

Usage

takeSeries(x, indices, ...)

Arguments

Generic function to extract a one or more individual volumes from a four-dimensional image

Description

Generic function to extract a one or more individual volumes from a four-dimensional image

Usage

takeVolume(x, i, ...)

## S4 method for signature 'SparseBrainVector,numeric'
takeVolume(x, i, merge = FALSE)

## S4 method for signature 'BrainVector,numeric'
takeVolume(x, i, merge = FALSE)

Arguments

Value

a list of BrainVolume elements

Examples

bvec <- BrainVector(array(rnorm(24*24*24*24), c(24,24,24,24)), BrainSpace(c(24,24,24,24), c(1,1,1)))
vol <- takeVolume(bvec,1)
all.equal(dim(vol), c(24,24,24))

vol <- takeVolume(bvec,1:3)
length(vol) == 3
class(vol) == "list"

tesselate

Description

tesselate

tesselate a LogicalBrainVolume into K spatial disjoint components

Usage

tesselate(x, K, ...)

## S4 method for signature 'LogicalBrainVolume,numeric'
tesselate(x, K, features = NULL,
  spatialWeight = 4)

Arguments

Generic getter to extract image coordinate transformation

Description

Generic getter to extract image coordinate transformation

Usage

trans(x)

## S4 method for signature 'BrainMetaInfo'
trans(x)

## S4 method for signature 'NIfTIMetaInfo'
trans(x)

## S4 method for signature 'BrainSpace'
trans(x)

## S4 method for signature 'BrainData'
trans(x)

Arguments

Details

This function returns a transformation that can be used to go from "grid coordinates" to "real world coordinates" in millimeters.

This function returns a transformation that can be used to go from "grid coordinates" to "real world coordinates" in millimeters. see BrainSpace

Examples

bspace <- BrainSpace(c(10,10,10), c(2,2,2))
trans(bspace)
all.equal(dim(trans(bspace)), c(4,4))

Generic function to extract data values of object

Description

Generic function to extract data values of object

Usage

values(x, ...)

## S4 method for signature 'ROIVolume'
values(x, ...)

Arguments

extract voxel coordinates

Description

extract voxel coordinates

Usage

voxels(x, ...)

## S4 method for signature 'Kernel'
voxels(x, centerVoxel = NULL)

Arguments

Generic function to write a sequence of elements from an input source

Description

Generic function to write a sequence of elements from an input source

writeElements

Usage

writeElements(x, els)

## S4 method for signature 'BinaryWriter,numeric'
writeElements(x, els)

Arguments

Generic function to write a 4D image vector to disk

Description

Generic function to write a 4D image vector to disk

Usage

writeVector(x, fileName, format, dataType)

## S4 method for signature 'BrainVector,character,missing,missing'
writeVector(x, fileName)

## S4 method for signature 'BrainVector,character,character,missing'
writeVector(x, fileName,
  format)

## S4 method for signature 'BrainVector,character,missing,character'
writeVector(x, fileName,
  dataType)

Arguments

Examples

bvec <- BrainVector(array(0, c(10,10,10,10)), BrainSpace(c(10,10,10,10), c(1,1,1)))
## Not run: 
writeVector(bvol, "out.nii")
writeVector(bvol, "out.nii.gz")
writeVector(bvec, "out.nii")
writeVector(bvec, "out.nii.gz")

## End(Not run)

Generic function to write a 3D image volume to disk

Description

Generic function to write a 3D image volume to disk

Usage

writeVolume(x, fileName, format, dataType)

## S4 method for signature 'BrainVolume,character,missing,missing'
writeVolume(x, fileName)

## S4 method for signature 'ClusteredBrainVolume,character,missing,missing'
writeVolume(x,
  fileName)

## S4 method for signature 'BrainVolume,character,character,missing'
writeVolume(x, fileName,
  format)

## S4 method for signature 'BrainVolume,character,missing,character'
writeVolume(x, fileName,
  dataType)

Arguments

Details

The output format will be inferred from file extension.

The output format will be inferred from file extension. writeVolume(x, "out.nii") outputs a NIFTI file. writeVolume(x, "out.nii.gz") outputs a gzipped NIFTI file.

No other file output formats are currently supported.

Examples

bvol <- BrainVolume(array(0, c(10,10,10)), BrainSpace(c(10,10,10), c(1,1,1)))
## Not run: 
writeVolume(bvol, "out.nii")
writeVolume(bvol, "out.nii.gz")

## End(Not run)