Function reference • neuroim2

Constructors

Constructors for creating and initializing various neuroimaging objects

AbstractSparseNeuroVec-class: AbstractSparseNeuroVec

NIFTIMetaInfo() AFNIMetaInfo(): FileMetaInfo

AxisSet-class: AxisSet

AxisSet1D-class: AxisSet1D

AxisSet2D-class: AxisSet2D

AxisSet3D-class: AxisSet3D

AxisSet4D-class: AxisSet4D

AxisSet5D-class: AxisSet5D

BigNeuroVec-class: BigNeuroVec

BinaryReader(): BinaryReader

BinaryWriter(): BinaryWriter

ClusteredNeuroVol(): ClusteredNeuroVol Class

DenseNeuroVec(): DenseNeuroVec

DenseNeuroVol(): DenseNeuroVol

FileBackedNeuroVec(): FileBackedNeuroVec

H5NeuroVec(): H5NeuroVec

IndexLookupVol(): IndexLookupVol Class

LatentNeuroVec(): LatentNeuroVec

LogicalNeuroVol(): LogicalNeuroVol

MappedNeuroVec(): MappedNeuroVec

MetaInfo(): MetaInfo

NeuroBucket-class: NeuroBucket

NeuroHyperVec-class: NeuroHyperVec

NeuroObj-class: NeuroObj Base class for all data objects with a cartesion spatial represenetation

NeuroSlice(): Construct a NeuroSlice object

NeuroSpace(): Constructor function for NeuroSpace class

NeuroVec(): NeuroVec

NeuroVecSeq(): Create a NeuroVecSeq Instance

NeuroVecSource(): NeuroVecSource

NeuroVolSource(): Constructor for NeuroVolSource

NeuroVol(): Construct a NeuroVol object

ROICoords-class: ROICoords

ROIVec(): Create an instance of class ROIVec

ROIVol(): Create an instance of class ROIVol

SparseNeuroVec(): SparseNeuroVec

SparseNeuroVol(): SparseNeuroVol

S4 Classes

S4 classes for various neuroimaging objects

BinaryReader-class: BinaryReader

ColumnReader-class: ColumnReader

FileBackedNeuroVec-class: FileBackedNeuroVec

FileFormat-class: FileFormatDescriptor

NIFTIMetaInfo() AFNIMetaInfo(): FileMetaInfo

FileSource-class: FileSource

H5NeuroVec-class: H5NeuroVec

H5NeuroVol-class: H5NeuroVol

MappedNeuroVecSource(): MappedNeuroVecSource

NamedAxis-class: NamedAxis

NeuroSlice-class: NeuroSlice

NeuroSpace-class: NeuroSpace Class

NeuroVecSeq-class: NeuroVecSeq

NeuroVol-class: NeuroVol

ROI-class: ROI

ROIVec-class: ROIVec

ROIVecWindow-class: ROIVecWindow

ROIVol-class: ROIVol

ROIVolWindow-class: ROIVolWindow

SparseNeuroVecSource-class: SparseNeuroVecSource

Data Loading and Manipulation

Methods for loading and manipulating neuroimaging data

concat(): Concatenate two objects in the time dimension

mapf(): Apply a function to an object.

vols(): Extract an ordered series of 3D volumes.

neuroim2: neuroim2

data_file(): Generic function to get the name of the data file, given a file name and a FileFormat instance.

data_file_matches(): Generic function to test whether a file name conforms to the given a FileFormat instance. Will test for match to data file only

data_reader(): Generic function to create data reader

file_matches(): Generic function to test whether a file name conforms to the given FileFormat instance. Will test for match to either header file or data file

read_elements(): Read a sequence of elements from an input source

Coordinate and Dimension Operations

Methods for operating on coordinates and dimensions

space(): Extract Geometric Properties of an Image

axes(): Extract Image Axes

spacing(): Extract Voxel Dimensions of an Image

bounds(): Extract Spatial Bounds of an Image

centroid(): return the centroid of an object

coord_to_grid(): convert n-dimensional real world coordinates to grid coordinates

coord_to_index(): convert n-dimensional real world coordinates to 1D indices

grid_to_coord(): Generic function to convert N-dimensional grid coordinate coordinates to real world coordinates

grid_to_index(): Generic function to convert N-dimensional grid coordinate to 1D indices

grid_to_grid(): Generic function to convert voxel coordinates in the reference space (LPI) to native array space.

index_to_coord(): convert 1d indices to n-dimensional real world coordinates

index_to_grid(): Convert 1d indices to n-dimensional grid coordinates

dim_of(): Get the length of a given dimension of an object

drop_dim(): Drop a Dimension from an Object

add_dim(): Add a Dimension to an Object

ndim(): Extract the number of dimensions of an object

voxels(): extract voxel coordinates

which_dim(): Find Dimensions of a Given Axis

trans(): Extract image coordinate transformation

inverse_trans(): Extract inverse image coordinate transformation

origin(): Extract Image Origin

perm_mat(): Extract permutation matrix associated with an image

strip_extension(): Generic function to strip extension from file name, given a FileFormat instance.

ROI and Clustering

Methods for working with regions of interest and clustering

partition(): Partition an image into a set of disjoint clusters

patch_set(): Generate a set of coordinate "patches" of fixed size from an image object.

split_clusters(): Cut an object into a list of spatial or spatiotemporal clusters

centroids(): Return a matrix of centroids of an object

conn_comp(): Connected components

conn_comp_3D(): Extract connected components from a 3D mask

coords(): Extract coordinates from an object

cuboid_roi(): Create A Cuboid Region of Interest

num_clusters(): Number of Clusters

slices(): Extract an ordered series of 2D slices from a 3D or 4D object

slice(): Extract image slice

vectors(): Extract an ordered list of 1D vectors.

values(): Extract Data Values of an Object

Kernel and Extraction

Methods for kernel operations and feature extraction

Kernel(): Create a Kernel object from a function of distance from kernel center

Kernel-class: Kernel

embed_kernel(): Generic function to position kernel in a postion in image space

`[`(<ArrayLike3D>,<numeric>,<missing>,<ANY>) `[`(<ArrayLike3D>,<matrix>,<missing>,<ANY>) `[`(<ArrayLike3D>,<missing>,<missing>,<ANY>) `[`(<ArrayLike3D>,<missing>,<numeric>,<ANY>) `[`(<NeuroVol>,<ROICoords>,<missing>,<ANY>): Array-like access for 3-dimensional data structures

`[`(<ArrayLike4D>,<matrix>,<missing>,<ANY>) `[`(<ArrayLike4D>,<numeric>,<numeric>,<ANY>) `[`(<ArrayLike4D>,<numeric>,<missing>,<ANY>) `[`(<ArrayLike4D>,<missing>,<missing>,<ANY>) `[`(<ArrayLike4D>,<missing>,<numeric>,<ANY>): Array-like access for 4-dimensional data structures

spherical_roi(): Create a Spherical Region of Interest

square_roi(): Create a square region of interest

searchlight_coords() searchlight(): Create an exhaustive searchlight iterator that only returns voxel coordinates

random_searchlight(): Create a spherical random searchlight iterator

bootstrap_searchlight(): Create a spherical searchlight iterator that samples regions from within a mask

series_roi() series(): Extract one or more series from object and return as ROI object

gaussian_blur(): Blur a volumetric image with an isotropic discrete Gaussian kernel

guided_filter(): Filter a volumetric image with an edge-preserving "guided" filter

bilateral_filter(): Apply a bilateral filter to a volumetric image

reorient(): Remap the grid-to-world coordinates mapping of an image.

clustered_searchlight(): Create a clustered searchlight iterator

Lookup and Mapping

Methods for looking up and mapping neuroimaging data

lookup(): Index Lookup operation

map_values(): Map Values from One Set to Another Using a User-supplied Lookup Table

resample(): Resample an Image to Match the Space of Another Image

Data Access and Indexing

Methods for accessing and indexing neuroimaging data

sub_vector(): Generic function to extract a sub-vector from a NeuroVec object.

indices(): Extract indices

length(<NeuroVec>) length(<NeuroVecSeq>) length(<ROIVol>): Get length of NeuroVec. This is the number of volumes in the volume vector (e.g. the 4th image dimension)

Scaling and Resampling

Methods for splitting, scaling, processing, and resampling neuroimaging data

scale_series(): 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.

resample(): Resample an Image to Match the Space of Another Image

split_blocks(): Cut a vector-valued object into a list of sub-blocks

split_clusters(): Cut an object into a list of spatial or spatiotemporal clusters

split_fill split_fill,NeuroVol,factor,function-method: Fill Disjoint Sets of Values with the Output of a Function

split_reduce split_reduce,matrix,integer,function-method split_reduce,matrix,integer,missing-method split_reduce,matrix,factor,missing-method split_reduce,matrix,factor,function-method split_reduce,NeuroVec,factor,function-method split_reduce,NeuroVec,factor,missing-method: Summarize Subsets of an Object by Splitting by Row and Applying a Summary Function

split_scale(): Center and/or Scale Row-subsets of a Matrix or Matrix-like Object

Visualization and Rendering

Methods for visualizing and rendering neuroimaging data

render(): Render an image to create a drawable image.

render_slice(): Render a slice at z coordinate

IO

Methods for input-output operations

read_vec(): read_vec

read_vol(): Load an image volume from a file

write_elements(): Write a sequence of elements from an input source

write_vec(): Write a 4d image vector to disk

write_vol(): Write a 3d image volume to disk

close(<BinaryReader>) close(<BinaryWriter>): close

ColumnReader(): ColumnReader

header_file(): Generic function to get the name of the header file, given a file name and a FileFormat instance.

header_file_matches(): Generic function to test whether a file name conforms to the given FileFormat instance. Will test for match to header file only

read_columns(): Read a set of column vector from an input source (e.g. ColumnReader)

read_header(): read header information of an image file

read_meta_info(): Generic function to read image meta info given a file and a FileFormat instance.

read_vol_list(): read_vol_list

Miscellaneous

Miscellaneous methods and functions

`[[`(<NeuroVec>,<numeric>): [[

`[[`(<NeuroVecSeq>,<numeric>): [[

`[[`(<LatentNeuroVec>,<numeric>) `[[`(<SparseNeuroVec>,<numeric>): [[

`[`(<ArrayLike3D>,<numeric>,<missing>,<ANY>) `[`(<ArrayLike3D>,<matrix>,<missing>,<ANY>) `[`(<ArrayLike3D>,<missing>,<missing>,<ANY>) `[`(<ArrayLike3D>,<missing>,<numeric>,<ANY>) `[`(<NeuroVol>,<ROICoords>,<missing>,<ANY>): Array-like access for 3-dimensional data structures

`[`(<ArrayLike4D>,<matrix>,<missing>,<ANY>) `[`(<ArrayLike4D>,<numeric>,<numeric>,<ANY>) `[`(<ArrayLike4D>,<numeric>,<missing>,<ANY>) `[`(<ArrayLike4D>,<missing>,<missing>,<ANY>) `[`(<ArrayLike4D>,<missing>,<numeric>,<ANY>): Array-like access for 4-dimensional data structures

`[`(<AbstractSparseNeuroVec>,<numeric>,<numeric>,<ANY>): extractor

`[`(<SparseNeuroVol>,<numeric>,<numeric>,<ANY>): extractor

`[`(<ROIVol>,<numeric>,<missing>,<ANY>) `[`(<ROIVol>,<logical>,<missing>,<ANY>): subset an ROIVol

dim(<FileMetaInfo>): dim of FileMetaInfo

dim(<NeuroSpace>): dim

dim(<NeuroObj>): dim of NeuroObj object

dim_of(): Get the length of a given dimension of an object

drop(<NeuroVec>): drop

drop_dim(): Drop a Dimension from an Object

length(<NeuroVec>) length(<NeuroVecSeq>) length(<ROIVol>): Get length of NeuroVec. This is the number of volumes in the volume vector (e.g. the 4th image dimension)

show(<AxisSet1D>): show an AxisSet1D

show(<AxisSet2D>): show an AxisSet2D

show(<AxisSet3D>): show an AxisSet3D

show(<AxisSet4D>): show an AxisSet4D

show(<ClusteredNeuroVol>): show a ClusteredNeuroVol

show(<FileMetaInfo>): show a FileMetaInfo

show(<NamedAxis>): show an NamedAxis

show(<NeuroSlice>): show a NeuroSlice

show(<NeuroSpace>): show a NeuroSpace

show(<NeuroVec>): show a NeuroVec

show(<NeuroVecSource>): show a NeuroVecSource

show(<NeuroVol>): show a NeuroVol

show(<ROIVec>): show an ROIVec

show(<ROIVol>): show an ROIVol

show(<SparseNeuroVec>): show a SparseNeuroVec

show(<SparseNeuroVol>): show a SparseNeuroVol

as: conversion from NeuroVol to LogicalNeuroVol

as.dense(<ClusteredNeuroVol>) as.dense(<ROIVol>): Coerce ROIVol to DenseNeuroVol using as.dense method

as.dense(): Convert to dense representation

as.list(<FileBackedNeuroVec>) as.list(<NeuroVec>) as.list(<SparseNeuroVec>): as.list

as.logical(<NeuroVol>): as.logical

as.mask(<NeuroVol>,<missing>) as.mask(<NeuroVol>,<numeric>): Convert NeuroVol to a mask

as.mask(): Convert to a LogicalNeuroVol

as.matrix(<FileBackedNeuroVec>) as.matrix(<NeuroVec>) as.matrix(<ROIVec>) as.matrix(<SparseNeuroVec>): convert a NeuroVec to a matrix

as.numeric(<SparseNeuroVol>): Convert SparseNeuroVol to numeric

as.sparse(<DenseNeuroVec>,<LogicalNeuroVol>) as.sparse(<DenseNeuroVec>,<numeric>) as.sparse(<DenseNeuroVol>,<LogicalNeuroVol>) as.sparse(<DenseNeuroVol>,<numeric>): Convert DenseNeuroVec to sparse representation using mask

as.sparse(): Convert to from dense to sparse representation

close(<BinaryReader>) close(<BinaryWriter>): close

plot(<NeuroSlice>) plot(<NeuroVol>): plot an NeuroVol as a series of 2D slices

Arith(<NeuroVec>,<NeuroVol>): Arithmetic Operations for NeuroVec and NeuroVol

Arith(<ROIVol>,<ROIVol>): This function performs arithmetic operations on two ROIVol objects.

Arith(<SparseNeuroVol>,<SparseNeuroVol>) Arith(<DenseNeuroVol>,<DenseNeuroVol>) Arith(<DenseNeuroVec>,<DenseNeuroVec>) Arith(<SparseNeuroVol>,<NeuroVol>) Arith(<SparseNeuroVec>,<SparseNeuroVec>) Arith(<NeuroVec>,<NeuroVec>): Perform arithmetic operations between two SparseNeuroVol objects

Compare(<SparseNeuroVol>,<numeric>) Compare(<numeric>,<SparseNeuroVol>): Compare a SparseNeuroVol object with a numeric value

Summary(<SparseNeuroVec>): Summary of SparseNeuroVec

Summary(<SparseNeuroVol>): Summary of SparseNeuroVol

add_dim(): Add a Dimension to an Object

axes(): Extract Image Axes

bounds(): Extract Spatial Bounds of an Image

centroid(): return the centroid of an object

centroids(): Return a matrix of centroids of an object

concat(): Concatenate two objects in the time dimension

conn_comp(): Connected components

coord_to_grid(): convert n-dimensional real world coordinates to grid coordinates

coord_to_index(): convert n-dimensional real world coordinates to 1D indices

coords(<IndexLookupVol>) coords(<ROICoords>) coords(<AbstractSparseNeuroVec>): Extract coordinates from an IndexLookupVol object

data_file(): Generic function to get the name of the data file, given a file name and a FileFormat instance.

data_file_matches(): Generic function to test whether a file name conforms to the given a FileFormat instance. Will test for match to data file only

data_reader(): Generic function to create data reader

embed_kernel(): Generic function to position kernel in a postion in image space

file_matches(): Generic function to test whether a file name conforms to the given FileFormat instance. Will test for match to either header file or data file

grid_to_coord(): Generic function to convert N-dimensional grid coordinate coordinates to real world coordinates

grid_to_grid(): Generic function to convert voxel coordinates in the reference space (LPI) to native array space.

grid_to_index(): Generic function to convert N-dimensional grid coordinate to 1D indices

header_file(): Generic function to get the name of the header file, given a file name and a FileFormat instance.

header_file_matches(): Generic function to test whether a file name conforms to the given FileFormat instance. Will test for match to header file only

index_to_coord(): convert 1d indices to n-dimensional real world coordinates

index_to_grid(): Convert 1d indices to n-dimensional grid coordinates

inverse_trans(): Extract inverse image coordinate transformation

mapf(): Apply a function to an object.

map_values(): Map Values from One Set to Another Using a User-supplied Lookup Table

ndim(): Extract the number of dimensions of an object

num_clusters(<ClusteredNeuroVol>): Number of Clusters

origin(): Extract Image Origin

partition(): Partition an image into a set of disjoint clusters

patch_set(<NeuroVol>,<numeric>,<missing>) patch_set(<NeuroVol>,<numeric>,<LogicalNeuroVol>): Create a patch set from a NeuroVol object

perm_mat(): Extract permutation matrix associated with an image

read_columns(): Read a set of column vector from an input source (e.g. ColumnReader)

read_elements(): Read a sequence of elements from an input source

read_meta_info(): Generic function to read image meta info given a file and a FileFormat instance.

reorient(): Remap the grid-to-world coordinates mapping of an image.

resample(<NeuroVol>,<NeuroSpace>): Resample a NeuroVol object to match a NeuroSpace object

resample(<NeuroVol>,<NeuroVol>): Resample a NeuroVol object

scale_series(): 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.

series_roi() series(): Extract one or more series from object and return as ROI object

slice(): Extract image slice

slices(): Extract an ordered series of 2D slices from a 3D or 4D object

space(): Extract Geometric Properties of an Image

spacing(): Extract Voxel Dimensions of an Image

split_blocks(): Cut a vector-valued object into a list of sub-blocks

split_clusters(): Cut an object into a list of spatial or spatiotemporal clusters

split_fill split_fill,NeuroVol,factor,function-method: Fill Disjoint Sets of Values with the Output of a Function

split_reduce split_reduce,matrix,integer,function-method split_reduce,matrix,integer,missing-method split_reduce,matrix,factor,missing-method split_reduce,matrix,factor,function-method split_reduce,NeuroVec,factor,function-method split_reduce,NeuroVec,factor,missing-method: Summarize Subsets of an Object by Splitting by Row and Applying a Summary Function

split_scale(): Center and/or Scale Row-subsets of a Matrix or Matrix-like Object

strip_extension(): Generic function to strip extension from file name, given a FileFormat instance.

sub_vector(): Generic function to extract a sub-vector from a NeuroVec object.

trans(): Extract image coordinate transformation

values(): Extract Data Values of an Object

vectors(): Extract an ordered list of 1D vectors.

vols(): Extract an ordered series of 3D volumes.

voxels(): extract voxel coordinates

which_dim(): Find Dimensions of a Given Axis

write_elements(): Write a sequence of elements from an input source

write_vec(): Write a 4d image vector to disk

write_vol(): Write a 3d image volume to disk