Package index • neuroim2

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.

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

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

bootstrap_searchlight(): Create a bootstrap spherical searchlight iterator

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

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.

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

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

Miscellaneous

Miscellaneous methods and functions

`[`(<NeuroHyperVec>,<ANY>,<ANY>,<ANY>): NeuroHyperVec Class

`[[`(<NeuroVecSeq>,<numeric>): Extract Element from NeuroVecSeq

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

`[`(<ROIVol>,<numeric>,<missing>,<ANY>) `[`(<ROIVol>,<logical>,<missing>,<ANY>): Extract or replace parts of an object

`[`(<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

`[`(<AbstractSparseNeuroVec>,<numeric>,<numeric>,<ANY>): Extractor Method for AbstractSparseNeuroVec

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

dim(<ClusteredNeuroVec>) dim(<FileMetaInfo>) dim(<NeuroObj>) dim(<NeuroSpace>) dim(<ROICoords>) dim(<ROIVol>): 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(<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(<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: conversion from NeuroVol to LogicalNeuroVol

as.dense(<ClusteredNeuroVol>) as.dense(<SparseNeuroVol>) 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(<SparseNeuroVec>): 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_nifti_header(): Construct a Minimal NIfTI-1 Header from a NeuroVol

close(<BinaryReader>) close(<BinaryWriter>): Close a BinaryReader or BinaryWriter

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

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

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(<NeuroVol>,<SparseNeuroVol>) Arith(<NeuroVec>,<NeuroVec>) Arith(<SparseNeuroVec>,<SparseNeuroVec>): Arithmetic Operations

Compare(<SparseNeuroVol>,<numeric>) Compare(<numeric>,<SparseNeuroVol>) Compare(<NeuroVec>,<NeuroVec>): Comparison Operations

Summary(<SparseNeuroVec>) Summary(<SparseNeuroVol>) Summary(<DenseNeuroVol>): Summary method for Neuroimaging objects

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(<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

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

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(<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.

ndim(<AxisSet>): Get number of dimensions in axis set

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

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(<AxisSet2D>): Get permutation matrix from axis set

perm_mat(<AxisSet3D>): Get permutation matrix from axis set

perm_mat(): Extract permutation matrix associated with an image

read_elements(<BinaryReader>,<numeric>): Read Elements from Binary Reader

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(<NeuroHyperVec>,<ANY>): Series method for NeuroHyperVec

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_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

None: Pre-defined null axis