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Interface: INeuroHyperVec

Defined in: src/hypervec/INeuroHyperVec.ts:113

Interface for high-dimensional neuroimaging data

Properties

spatialDim

ts
spatialDim: [number, number, number];

Defined in: src/hypervec/INeuroHyperVec.ts:117

Spatial dimensions [x, y, z]


space

ts
space: NeuroSpace;

Defined in: src/hypervec/INeuroHyperVec.ts:122

Spatial coordinate system


dimensions

ts
dimensions: DimensionInfo[];

Defined in: src/hypervec/INeuroHyperVec.ts:127

Information about non-spatial dimensions


ndim

ts
ndim: number;

Defined in: src/hypervec/INeuroHyperVec.ts:132

Total number of dimensions (spatial + non-spatial)


shape

ts
shape: number[];

Defined in: src/hypervec/INeuroHyperVec.ts:137

Shape of the full array


size

ts
size: number;

Defined in: src/hypervec/INeuroHyperVec.ts:142

Total number of elements

Methods

getSubVolume()

ts
getSubVolume(indices): NeuroVol | NeuroVec;

Defined in: src/hypervec/INeuroHyperVec.ts:148

Get a sub-volume by specifying indices for non-spatial dimensions

Parameters

indices

Record<string, number | number[]>

Map of dimension name to index or slice

Returns

NeuroVol | NeuroVec


getVoxelSeries()

ts
getVoxelSeries(
   x, 
   y, 
   z, 
   dims?): number[];

Defined in: src/hypervec/INeuroHyperVec.ts:157

Get a time series for a specific voxel across specified dimensions

Parameters

x

number

X coordinate

y

number

Y coordinate

z

number

Z coordinate

dims?

string[]

Dimensions to extract (default: all non-spatial)

Returns

number[]


setSubVolume()

ts
setSubVolume(indices, data): void;

Defined in: src/hypervec/INeuroHyperVec.ts:164

Set data for a sub-volume

Parameters

indices

Record<string, number | number[]>

Indices for non-spatial dimensions

data

NeuroVol | NeuroVec

Data to set

Returns

void


reduce()

ts
reduce(dims, options): INeuroHyperVec;

Defined in: src/hypervec/INeuroHyperVec.ts:171

Reduce along specified dimensions

Parameters

dims

string[]

Dimension names to reduce

options

ReductionOptions

Reduction options

Returns

INeuroHyperVec


mapAlong()

ts
mapAlong(dims, fn): INeuroHyperVec;

Defined in: src/hypervec/INeuroHyperVec.ts:178

Apply function along specified dimensions

Parameters

dims

string[]

Dimensions to map over

fn

(data) => NeuroVol

Function to apply

Returns

INeuroHyperVec


concat()

ts
concat(other, dim): INeuroHyperVec;

Defined in: src/hypervec/INeuroHyperVec.ts:185

Concatenate with another hypervec along a dimension

Parameters

other

INeuroHyperVec

Other hypervec

dim

string

Dimension name

Returns

INeuroHyperVec


split()

ts
split(dim, indices): INeuroHyperVec[];

Defined in: src/hypervec/INeuroHyperVec.ts:192

Split along a dimension

Parameters

dim

string

Dimension to split

indices

number[]

Indices where to split

Returns

INeuroHyperVec[]


permute()

ts
permute(order): INeuroHyperVec;

Defined in: src/hypervec/INeuroHyperVec.ts:198

Permute dimensions

Parameters

order

string[]

New dimension order by name

Returns

INeuroHyperVec


extractFeatures()

ts
extractFeatures(options): object;

Defined in: src/hypervec/INeuroHyperVec.ts:204

Extract features using dimensionality reduction

Parameters

options

FeatureExtractionOptions

Feature extraction options

Returns

object

components
ts
components: INeuroHyperVec;
loadings
ts
loadings: number[][];
explainedVariance?
ts
optional explainedVariance?: number[];

correlateAlong()

ts
correlateAlong(dim1, dim2): number[][];

Defined in: src/hypervec/INeuroHyperVec.ts:215

Compute correlation between different conditions/subjects

Parameters

dim1

string

First dimension name

dim2

string

Second dimension name

Returns

number[][]


glm()

ts
glm(designMatrix, contrastMatrix): object;

Defined in: src/hypervec/INeuroHyperVec.ts:222

Apply GLM across time or conditions

Parameters

designMatrix

number[][]

Design matrix

contrastMatrix

number[][]

Contrast matrix

Returns

object

beta
ts
beta: INeuroHyperVec;
tstat
ts
tstat: NeuroVol;
pval
ts
pval: NeuroVol;

toArray()

ts
toArray(): Float32Array;

Defined in: src/hypervec/INeuroHyperVec.ts:231

Convert to dense array (use with caution for large data)

Returns

Float32Array


save()

ts
save(filename, format?): Promise<void>;

Defined in: src/hypervec/INeuroHyperVec.ts:238

Save to file

Parameters

filename

string

Output filename

format?

string

Format (hdf5, nifti-5d, custom)

Returns

Promise<void>


view()

ts
view(spec): INeuroHyperVec;

Defined in: src/hypervec/INeuroHyperVec.ts:244

Create a view with reordered/subsetted dimensions

Parameters

spec

Record<string, number | number[] | "all">

Specification for the view

Returns

INeuroHyperVec


clone()

ts
clone(): INeuroHyperVec;

Defined in: src/hypervec/INeuroHyperVec.ts:249

Clone the hypervec

Returns

INeuroHyperVec


dispose()

ts
dispose(): void;

Defined in: src/hypervec/INeuroHyperVec.ts:254

Dispose of resources

Returns

void

Released under the MIT License.