Package index • neuroim2

Visualization Helpers

Plotting utilities for slices, montages, overlays, and palettes

theme_neuro(): A minimal, publication-friendly theme for image slices
resolve_cmap(): Neuroimaging color palettes and helpers
scale_fill_neuro(): A ggplot2 fill scale with neuroimaging-friendly defaults
annotate_orientation(): Add L/R and A/P/S/I annotations (optional)
plot_montage(): Plot a montage of axial (or any-plane) slices using facetting
plot_ortho(): Orthogonal three-plane view with optional crosshairs
plot_overlay(): Composite an overlay map on a structural background
mapToColors(): Map intensity values to colors

Constructors

Constructors for creating and initializing various neuroimaging objects

AbstractSparseNeuroVec-class: AbstractSparseNeuroVec Class
AFNIMetaInfo(): Create AFNI Format Metadata Object
ArrayLike3D-class: ArrayLike3D Class
ArrayLike4D-class: ArrayLike4D Class
ArrayLike5D-class: ArrayLike5D Class
AxisSet-class: AxisSet
AxisSet1D-class: AxisSet1D
AxisSet2D-class: AxisSet2D
AxisSet3D-class: AxisSet3D Class
AxisSet4D-class: AxisSet4D Class
AxisSet5D-class: AxisSet5D Class
BigNeuroVec-class: BigNeuroVec Class
BigNeuroVec(): Create a Memory-Mapped Neuroimaging Vector
BinaryReader(): Create Binary Reader Object
BinaryWriter(): Create Binary Writer Object
BinaryWriter-class: BinaryWriter Class
ClusteredNeuroVol(): ClusteredNeuroVol Class
ClusteredNeuroVec(): ClusteredNeuroVec: Cluster-aware 4D neuroimaging data
ClusteredNeuroVec-class: ClusteredNeuroVec Class
DenseNeuroVec(): DenseNeuroVec Class
DenseNeuroVol(): DenseNeuroVol Class
FileBackedNeuroVec(): Create a File-Backed Neuroimaging Vector
IndexLookupVol(): IndexLookupVol Class
LogicalNeuroVol(): LogicalNeuroVol Class
MappedNeuroVec(): MappedNeuroVec Class
MetaInfo-class: MetaInfo Class
MetaInfo(): Create Neuroimaging Metadata Object
NeuroBucket-class: NeuroBucket
`[`(<NeuroHyperVec>,<ANY>,<ANY>,<ANY>): NeuroHyperVec Class
NeuroHyperVec(): Constructor for NeuroHyperVec class
NeuroObj-class: NeuroObj Class
NeuroSlice(): NeuroSlice: 2D Neuroimaging Data Container
NeuroSpace(): NeuroSpace: Spatial Reference System for Neuroimaging Data
NeuroVec(): NeuroVec Class
NeuroVecSeq(): NeuroVecSeq: A Container for Sequential NeuroVec Objects
NeuroVecSource(): NeuroVecSource
NeuroVecSource-class: NeuroVecSource Class
NeuroVolSource(): Constructor for NeuroVolSource
NeuroVol(): NeuroVol: 3D Neuroimaging Volume Class
NIFTIMetaInfo(): Create NIFTI Format Metadata Object
ROICoords-class: ROICoords
ROICoords(): Create ROI Coordinates Object
ROIVec(): Create an instance of class ROIVec
ROIVol(): Create ROI Volume Object
SparseNeuroVec(): SparseNeuroVec Class
SparseNeuroVol(): SparseNeuroVol Class
TimeAxis: Time axis set
NullAxis: Pre-defined null axis set
numericOrMatrix-class: numericOrMatrix Union

S4 Classes

S4 classes for various neuroimaging objects

BinaryReader-class: BinaryReader Class
ColumnReader-class: ColumnReader
FileBackedNeuroVec-class: FileBackedNeuroVec Class
FileFormat-class: FileFormat Class
FileFormat-operations: File Format Operations for Neuroimaging Data
FileMetaInfo-class NIFTIMetaInfo-class AFNIMetaInfo-class: FileMetaInfo Class
FileSource-class: FileSource Class
MappedNeuroVecSource(): MappedNeuroVecSource Class
NamedAxis-class: NamedAxis
NeuroSlice-class: NeuroSlice Class
NeuroSpace-class: NeuroSpace Class
NeuroVecSeq-class: NeuroVecSeq Class
NeuroVol-class: NeuroVol Class
ROI-class: ROI
ROIVec-class: ROIVec
ROIVecWindow-class: ROIVecWindow
ROIVol-class: ROIVol
ROIVolWindow-class: ROIVolWindow
SparseNeuroVecSource-class: SparseNeuroVecSource Class
OrientationList2D: Pre-defined 2D orientation configurations
OrientationList3D: Pre-defined 3D orientation configurations

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.
vec_from_vols(): Create NeuroVec from list of NeuroVol objects
neuroim2-package neuroim2: neuroim2: neuroimaging data structures for analysis
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(): Create a 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
createNIfTIHeader(): Create an Empty NIfTI-1 Header List
linear_access(): Extract values from an array-like object using linear indexing.
image: Generic Image Method for Creating Visual Representations
scale(): Generic Scale Method
simulate_fmri(): Simulate fMRI Data

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 coordinates to real world coordinates
grid_to_index(): Generic function to convert N-dimensional grid coordinates 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.
deoblique(): Deoblique a Neuroimaging Space or Volume
LEFT_RIGHT RIGHT_LEFT ANT_POST POST_ANT INF_SUP SUP_INF: Pre-defined anatomical axes
TIME: Time axis
findAnatomy3D(): Find 3D anatomical orientation from axis abbreviations
matrixToQuatern(): Convert a Transformation Matrix to a Quaternion Representation
quaternToMatrix(): Convert Quaternion Parameters to a Transformation Matrix
apply_affine() to_matvec() from_matvec() append_diag() dot_reduce() voxel_sizes() obliquity() rescale_affine(): Affine utility functions
affine_to_orientation() orientation_transform() apply_orientation() orientation_inverse_affine() orientation_to_axcodes() axcodes_to_orientation() affine_to_axcodes(): Orientation utility functions
output_aligned_space() vox2out_vox() slice_to_volume_affine() slice2volume(): Space utility functions

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 Binary 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
spherical_roi_set(): Create Multiple Spherical Regions of Interest

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 position in image space
`[`(<ArrayLike3D>,<numeric>,<missing>,<ANY>) `[`(<ArrayLike3D>,<matrix>,<missing>,<ANY>) `[`(<ArrayLike3D>,<missing>,<missing>,<ANY>) `[`(<ArrayLike3D>,<missing>,<numeric>,<ANY>): Array-like access for 3-dimensional data structures
`[`(<ArrayLike4D>,<matrix>,<missing>,<ANY>) `[`(<ArrayLike4D>,<numeric>,<numeric>,<ANY>) `[`(<ArrayLike4D>,<numeric>,<missing>,<ANY>) `[`(<ArrayLike4D>,<integer>,<missing>,<ANY>) `[`(<ArrayLike4D>,<missing>,<missing>,<ANY>) `[`(<ArrayLike4D>,<missing>,<numeric>,<ANY>) `[`(<ClusteredNeuroVec>,<missing>,<missing>,<ANY>) `[`(<ClusteredNeuroVec>,<numeric>,<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(): Create an exhaustive searchlight iterator
searchlight_coords(): Create an exhaustive searchlight iterator for voxel coordinates using spherical_roi
random_searchlight(): Create a spherical random searchlight iterator
resampled_searchlight() bootstrap_searchlight(): Create a resampled searchlight iterator
ellipsoid_shape() cube_shape() blobby_shape(): Convenience shape generators for resampled_searchlight()
series_roi(): Extract time series from specific voxel coordinates and return as ROI object
gaussian_blur(): Gaussian Blur for Volumetric Images
guided_filter(): Edge-Preserving Guided Filter for Volumetric Images
bilateral_filter(): Apply a bilateral filter to a volumetric image
bilateral_filter_4d(): Apply a 4D bilateral filter to a NeuroVec
cgb_filter(): Correlation-guided bilateral filtering (convenience wrapper)
cgb_make_graph(): Build a correlation-guided bilateral (CGB) graph
cgb_smooth(): Apply a precomputed CGB graph to volumetric data
cgb_smooth_loro(): Leave-one-run-out smoothing helper
reorient(): Remap the grid-to-world coordinates mapping of an image.
clustered_searchlight(): Create a clustered searchlight iterator
cluster_searchlight_series(): Cluster-centroid searchlight over cluster time-series
spatial-filter: Spatial Filtering Methods for Neuroimaging Data
searchlight-methods: Searchlight Analysis Methods
laplace_enhance(): Laplacian Enhancement Filter for Volumetric Images

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
neuro-resample: Resampling Methods for Neuroimaging Objects

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(<ClusteredNeuroVec>) length(<NeuroVec>) length(<NeuroVecSeq>) length(<ROIVol>) length(<ROICoords>): Get length of NeuroVec object
neuro-ops: Arithmetic and Comparison Operations for Neuroimaging Objects

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.
make_time_weights(): Build smooth time weights from motion/outlier metrics
prepare_confounds(): Prepare weighted nuisance projectors for each run
resample(): Resample an Image to Match the Space of Another Image
resample_to(): Resample an image with readable method names
neuro-downsample: Downsampling Methods for Neuroimaging Objects
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(): Fill Disjoint Sets of Values with the Output of a Function
split_reduce(): 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

IO

Methods for input-output operations

read_vec(): read_vec
read_vol(): Load an image volume from a file
read_image(): read_image
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 a BinaryReader or BinaryWriter
ColumnReader(): Create Column Reader Object
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
read_vol_list(): read_vol_list
read_hyper_vec(): Read a 5D image as a NeuroHyperVec

NIfTI Extensions

Classes and functions for working with NIfTI header extensions

NiftiExtension(): Create a NIfTI Extension
NiftiExtensionCodes: Known NIfTI Extension Codes
ecode_name(): Get Extension Code Name
extensions(): Get Extensions from an Object
parse_extension(): Parse NIfTI Extension Data
parse_afni_extension(): Parse AFNI Extension
get_afni_attribute(): Get AFNI Attribute from Extension
list_afni_attributes(): List AFNI Attributes in Extension

Miscellaneous

Miscellaneous methods and functions

`[`(<NeuroHyperVec>,<ANY>,<ANY>,<ANY>): NeuroHyperVec Class
`[[`(<NeuroVecSeq>,<numeric>): Extract Element from NeuroVecSeq
`[[`(<AbstractSparseNeuroVec>,<numeric>): [[
`[`(<DenseNeuroVol>,<numeric>,<missing>,<ANY>) `[`(<DenseNeuroVol>,<integer>,<missing>,<ANY>) `[[`(<NeuroVec>,<numeric>) `[`(<NeuroVol>,<ROICoords>,<missing>,<ANY>) `[`(<NeuroVol>,<ROIVol>,<missing>,<ANY>) `[`(<DenseNeuroVol>,<ROIVol>,<missing>,<ANY>) `[`(<SparseNeuroVol>,<numeric>,<numeric>,<ANY>) `[`(<ROIVol>,<numeric>,<missing>,<ANY>) `[`(<ROIVol>,<logical>,<missing>,<ANY>) `[`(<ROIVol>,<ROICoords>,<missing>,<ANY>) `[`(<ROIVol>,<matrix>,<missing>,<ANY>) `[`(<ROIVol>,<missing>,<missing>,<ANY>) `[`(<ROIVol>,<missing>,<numeric>,<ANY>) `[`(<ROIVol>,<numeric>,<numeric>,<ANY>) `[`(<ROIVol>,<logical>,<numeric>,<ANY>) `[`(<ROIVol>,<ROICoords>,<numeric>,<ANY>) `[`(<ROIVol>,<matrix>,<numeric>,<ANY>) `[`(<ROICoords>,<numeric>,<missing>,<ANY>) `[`(<AbstractSparseNeuroVec>,<numeric>,<numeric>,<ANY>): [[
`[`(<ArrayLike3D>,<numeric>,<missing>,<ANY>) `[`(<ArrayLike3D>,<matrix>,<missing>,<ANY>) `[`(<ArrayLike3D>,<missing>,<missing>,<ANY>) `[`(<ArrayLike3D>,<missing>,<numeric>,<ANY>): Array-like access for 3-dimensional data structures
`[`(<ArrayLike4D>,<matrix>,<missing>,<ANY>) `[`(<ArrayLike4D>,<numeric>,<numeric>,<ANY>) `[`(<ArrayLike4D>,<numeric>,<missing>,<ANY>) `[`(<ArrayLike4D>,<integer>,<missing>,<ANY>) `[`(<ArrayLike4D>,<missing>,<missing>,<ANY>) `[`(<ArrayLike4D>,<missing>,<numeric>,<ANY>) `[`(<ClusteredNeuroVec>,<missing>,<missing>,<ANY>) `[`(<ClusteredNeuroVec>,<numeric>,<numeric>,<ANY>): Array-like access for 4-dimensional data structures
dim(<ClusteredNeuroVec>) dim(<FileMetaInfo>) dim(<NeuroObj>) dim(<NeuroHyperVec>) dim(<NeuroSpace>) dim(<ROIVol>) dim(<ROICoords>): Get Dimensions of FileMetaInfo Object
dim_of(): Get the length of a given dimension of an object
drop(<NeuroVec>): Drop a dimension
drop(): Generic Drop Method
drop_dim(): Drop a Dimension from an Object
length(<ClusteredNeuroVec>) length(<NeuroVec>) length(<NeuroVecSeq>) length(<ROIVol>) length(<ROICoords>): Get length of NeuroVec object
show(<NiftiExtension>): NiftiExtension Class
show(<NiftiExtensionList>): NiftiExtensionList Class
show(<NamedAxis>) show(<AxisSet1D>) show(<AxisSet2D>) show(<AxisSet3D>) show(<AxisSet4D>) show(<ClusteredNeuroVec>) show(<ClusteredNeuroVol>) show(<IndexLookupVol>) show(<MappedNeuroVec>) show(<FileMetaInfo>) show(<NeuroHyperVec>) show(<NeuroSlice>) show(<NeuroSpace>) show(<NeuroVecSource>) show(<NeuroVec>) show(<DenseNeuroVec>) show(<NeuroVecSeq>) show(<DenseNeuroVol>) show(<NeuroVol>) show(<SparseNeuroVol>) show(<Kernel>) show(<ROIVol>) show(<ROICoords>) show(<ROIVec>) show(<SparseNeuroVec>): Show method for NamedAxis objects
as-ClusteredNeuroVol-DenseNeuroVol coerce,ClusteredNeuroVol,DenseNeuroVol-method: Convert ClusteredNeuroVol to DenseNeuroVol
as.array(<ClusteredNeuroVol>) as.array(<SparseNeuroVol>) as.array(<SparseNeuroVec>): Convert ClusteredNeuroVol to a base array
as.array(): Generic as.array Method
as.dense(<ClusteredNeuroVol>) as.dense(<SparseNeuroVol>) as.dense(<DenseNeuroVol>) as.dense(<ROIVol>) as.dense(<SparseNeuroVec>): Coerce SparseNeuroVol to DenseNeuroVol
as.dense(): Convert to dense representation
as.list(<FileBackedNeuroVec>) as.list(<NeuroVec>) as.list(<SparseNeuroVec>): Convert FileBackedNeuroVec to List
as.logical(<NeuroVol>) as.logical(<ROIVol>): as.logical
as.mask(<NeuroVol>,<missing>) as.mask(<NeuroVol>,<numeric>): Convert NeuroVol to a mask
as.mask(): Convert to a LogicalNeuroVol
as.matrix(<ClusteredNeuroVec>) as.matrix(<MappedNeuroVec>) as.matrix(<NeuroVec>) as.matrix(<DenseNeuroVec>) as.matrix(<ROIVec>) as.matrix(<AbstractSparseNeuroVec>): convert a NeuroVec to a matrix
as.matrix(): Generic as.matrix Method
as.numeric(<SparseNeuroVol>) as.numeric(<ROIVol>): Convert SparseNeuroVol to numeric
as.raster: Generic Method for Converting Objects to Raster Format
as.sparse(<DenseNeuroVec>,<LogicalNeuroVol>) as.sparse(<DenseNeuroVec>,<numeric>) as.sparse(<DenseNeuroVol>,<LogicalNeuroVol>) as.sparse(<DenseNeuroVol>,<numeric>) as.sparse(<ROIVol>,<ANY>): Convert DenseNeuroVec to sparse representation using mask
as.sparse(): Convert to from dense to sparse representation
as.vector(<SparseNeuroVol>): Convert SparseNeuroVol to a base vector
as_canonical(): Reorient Image to Canonical (RAS+) Orientation
as_mmap(): Convert a NeuroVec to a memory-mapped representation
as_nifti_header(): Construct a Minimal NIfTI-1 Header from a NeuroVol
close(<BinaryReader>) close(<BinaryWriter>): Close a BinaryReader or BinaryWriter
plot(<NeuroSlice>,<ANY>) plot(<NeuroVol>,<missing>) plot(<NeuroVol>,<NeuroVol>): Plot a NeuroSlice
plot_montage(): Plot a montage of axial (or any-plane) slices using facetting
plot_ortho(): Orthogonal three-plane view with optional crosshairs
plot_overlay(): Composite an overlay map on a structural background
Arith(<SparseNeuroVol>,<SparseNeuroVol>) Arith(<ROIVol>,<ROIVol>) Arith(<DenseNeuroVol>,<DenseNeuroVol>) Arith(<DenseNeuroVec>,<DenseNeuroVec>) Arith(<SparseNeuroVol>,<NeuroVol>) Arith(<NeuroVol>,<SparseNeuroVol>) Arith(<SparseNeuroVec>,<SparseNeuroVec>) Arith(<NeuroVec>,<NeuroVec>) Arith(<NeuroVec>,<NeuroVol>) Arith(<NeuroVol>,<NeuroVec>) Arith(<DenseNeuroVol>,<numeric>) Arith(<numeric>,<DenseNeuroVol>) Arith(<SparseNeuroVol>,<numeric>) Arith(<numeric>,<SparseNeuroVol>) Arith(<ClusteredNeuroVol>,<ClusteredNeuroVol>) Arith(<ClusteredNeuroVol>,<numeric>) Arith(<numeric>,<ClusteredNeuroVol>) Arith(<ClusteredNeuroVol>,<NeuroVol>) Arith(<NeuroVol>,<ClusteredNeuroVol>): Arithmetic Operations
Compare(<DenseNeuroVol>,<DenseNeuroVol>) Compare(<DenseNeuroVol>,<numeric>) Compare(<numeric>,<DenseNeuroVol>) Compare(<SparseNeuroVol>,<numeric>) Compare(<numeric>,<SparseNeuroVol>) Compare(<NeuroVec>,<NeuroVec>): Comparison Operations
Logic(<DenseNeuroVol>,<DenseNeuroVol>) Logic(<SparseNeuroVol>,<SparseNeuroVol>) Logic(<SparseNeuroVol>,<NeuroVol>) Logic(<NeuroVol>,<SparseNeuroVol>) Logic(<NeuroVol>,<logical>) Logic(<logical>,<NeuroVol>): Logic Operations for Neuroimaging Volumes
Summary(<SparseNeuroVec>) Summary(<SparseNeuroVol>) Summary(<DenseNeuroVol>): Summary Methods for Neuroimaging Objects
add_dim(): Add a Dimension to an Object
axcodes(): Get Orientation Axis Codes
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(<ROIVol>) 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(<NIFTIMetaInfo>) data_reader(<AFNIMetaInfo>): Create Data Reader for AFNI Format
downsample(): Downsample an Image
embed_kernel(): Generic function to position kernel in a position in image space
extension(): Get Extension by Code
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 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 coordinates to 1D indices
has_extensions(): Check if Extensions are Present
header(): Access NIfTI Header Information
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
indices(<IndexLookupVol>) indices(<ROIVol>) indices(<ROIVec>) indices(<AbstractSparseNeuroVec>): Get Indices from an IndexLookupVol Object
inverse_trans(): Extract inverse image coordinate transformation
labels(<ClusteredNeuroVec>): Get Labels from ClusteredNeuroVec
linear_access(<DenseNeuroVol>,<numeric>) linear_access(<DenseNeuroVec>,<numeric>) linear_access(<DenseNeuroVol>,<integer>) linear_access(<DenseNeuroVec>,<integer>) linear_access(<FileBackedNeuroVec>,<numeric>) linear_access(<MappedNeuroVec>,<numeric>) linear_access(<NeuroHyperVec>,<ANY>) linear_access(<NeuroVecSeq>,<numeric>) linear_access(<SparseNeuroVol>,<numeric>) linear_access(<AbstractSparseNeuroVec>,<numeric>): Linear Access Method for FileBackedNeuroVec
load_data(<MappedNeuroVecSource>) load_data(<NeuroVecSource>) load_data(<NeuroVolSource>) load_data(<SparseNeuroVecSource>): Load image data from a NeuroVecSource object
lookup(<IndexLookupVol>,<numeric>) lookup(<AbstractSparseNeuroVec>,<numeric>): Lookup Values in an IndexLookupVol Object
mapf(): Apply a function to an object.
map_values(): Map Values from One Set to Another Using a User-supplied Lookup Table
mask(): Extract Mask from Neuroimaging Object
matricized_access(): Extract values from a 4D tensor using a matrix of time-space indices.
mean(<DenseNeuroVec>) mean(<SparseNeuroVec>) mean(<NeuroVec>): Temporal Mean of a NeuroVec
meta_info(): Lightweight metadata for neuroimaging files
ndim(): Extract the number of dimensions of an object
`!`(<DenseNeuroVol>) `!`(<SparseNeuroVol>): Logical Negation for Neuroimaging Volumes
num_clusters(): 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_meta_info(): Generic function to read image meta info given a file
reorient(): Remap the grid-to-world coordinates mapping of an image.
resample(): Resample an Image to Match the Space of Another Image
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() series_roi(<NeuroVec>,<matrix>) series_roi(<NeuroVec>,<ROICoords>) series_roi(<NeuroVec>,<LogicalNeuroVol>) series_roi(<NeuroVec>,<numeric>) series_roi(<NeuroVecSeq>,<matrix>): Extract one or more series from 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(): Fill Disjoint Sets of Values with the Output of a Function
split_reduce(): 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_clusters(): Select a Subset of Clusters
sub_vector(): Generic function to extract a sub-vector from a NeuroVec object.
summary(<NeuroVol>) summary(<DenseNeuroVec>) summary(<SparseNeuroVec>): Summary of Neuroimaging Objects
temporal_access(): Extract full sparse rows across time.
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
None: Pre-defined null axis