Class: BigNeuroVec

Defined in: src/vector/BigNeuroVec.ts:287

BigNeuroVec - Memory-mapped neuroimaging vector data.

This class provides efficient handling of large 4D neuroimaging data by using memory-mapped arrays that remain on disk.

Direct translation of Python's BigNeuroVec class.

Implements

• NeuroVec

Constructors

Constructor

new BigNeuroVec(
   dataOrFilename, 
   spaceOrShape?, 
   options?): BigNeuroVec;

Defined in: src/vector/BigNeuroVec.ts:313

Creates a BigNeuroVec instance.

Can be initialized in two ways:

1. With data and space (creates a backing file, or keeps the data in memory when storage: 'memory')
2. With filename and shape (opens or creates file)

volumeSpace is the 3D space of each volume, including its affine. When omitted, it is derived from the time-first space without orientation.

shareData (memory storage only) uses the memory of data directly instead of copying it, so later writes are visible through both. It applies when data already has the storage dtype on a little-endian host.

Parameters

dataOrFilename

string | TypedArray

spaceOrShape?

number[] | NeuroSpace

options?

filename?

string

mode?

string

dtype?

string

storage?

"file" | "memory"

volumeSpace?

NeuroSpace

shareData?

boolean

Returns

BigNeuroVec

Properties

filename

readonly filename: string;

Defined in: src/vector/BigNeuroVec.ts:292

---

mode

readonly mode: string;

Defined in: src/vector/BigNeuroVec.ts:293

---

space

readonly space: NeuroSpace;

Defined in: src/vector/BigNeuroVec.ts:294

Implementation of

NeuroVec.space

---

storage

readonly storage: "file" | "memory";

Defined in: src/vector/BigNeuroVec.ts:296

'memory' when there is no backing file.

Accessors

volumeSpace

Get Signature

get volumeSpace(): NeuroSpace;

Defined in: src/vector/BigNeuroVec.ts:423

The 3D space of each volume (dims, spacing, origin and affine).

Returns

NeuroSpace

---

data

Get Signature

get data(): TypedArray;

Defined in: src/vector/BigNeuroVec.ts:430

Returns

TypedArray

---

values

Get Signature

get values(): TypedArray;

Defined in: src/vector/BigNeuroVec.ts:435

Returns

TypedArray

---

length

Get Signature

get length(): number;

Defined in: src/vector/BigNeuroVec.ts:439

Returns

number

Implementation of

NeuroVec.length

---

dim

Get Signature

get dim(): number[];

Defined in: src/vector/BigNeuroVec.ts:443

Returns

number[]

Implementation of

NeuroVec.dim

---

shape

Get Signature

get shape(): number[];

Defined in: src/vector/BigNeuroVec.ts:447

Returns

number[]

---

spacing

Get Signature

get spacing(): number[];

Defined in: src/vector/BigNeuroVec.ts:451

Returns

number[]

Implementation of

NeuroVec.spacing

---

origin

Get Signature

get origin(): number[];

Defined in: src/vector/BigNeuroVec.ts:455

Returns

number[]

Implementation of

NeuroVec.origin

Methods

getVolume()

getVolume(t): NeuroVol;

Defined in: src/vector/BigNeuroVec.ts:462

Get volume at time point t

Parameters

t

number

Returns

NeuroVol

Implementation of

NeuroVec.getVolume

---

getSeries()

getSeries(
   i, 
   j, 
   k): number[];

Defined in: src/vector/BigNeuroVec.ts:488

Get time series at voxel (i, j, k)

Parameters

i

number

j

number

k

number

Returns

number[]

Implementation of

NeuroVec.getSeries

---

getData()

getData(): TypedArray;

Defined in: src/vector/BigNeuroVec.ts:499

Get all data (loads into memory)

Returns

TypedArray

Implementation of

NeuroVec.getData

---

getRange()

getRange(): [number, number];

Defined in: src/vector/BigNeuroVec.ts:506

Get data range [min, max]

Returns

[number, number]

Implementation of

NeuroVec.getRange

---

getAt()

getAt(
   i, 
   j, 
   k, 
   t): number;

Defined in: src/vector/BigNeuroVec.ts:541

Get value at 4D index (interface uses i,j,k,t order)

Parameters

i

number

j

number

k

number

t

number

Returns

number

Implementation of

NeuroVec.getAt

---

setAt()

setAt(
   i, 
   j, 
   k, 
   t, 
   value): void;

Defined in: src/vector/BigNeuroVec.ts:548

Set value at 4D index (interface uses i,j,k,t order)

Parameters

i

number

j

number

k

number

t

number

value

number

Returns

void

Implementation of

NeuroVec.setAt

---

series()

series(
   x, 
   y?, 
   z?): TypedArray;

Defined in: src/vector/BigNeuroVec.ts:555

Parameters

x

number | number[][]

y?

number

z?

number

Returns

TypedArray

---

subVector()

subVector(indices): BigNeuroVec;

Defined in: src/vector/BigNeuroVec.ts:585

Parameters

indices

number | number[]

Returns

BigNeuroVec

---

vols()

vols(indices?): NeuroVol[];

Defined in: src/vector/BigNeuroVec.ts:641

Parameters

indices?

number[]

Returns

NeuroVol[]

---

processChunks()

processChunks<T>(
   func, 
   chunkSize?, 
   axis?): T[];

Defined in: src/vector/BigNeuroVec.ts:671

Process data in chunks to avoid loading entire dataset into memory

Type Parameters

T

T

Parameters

func

(chunk) => T

chunkSize?

number = 100

axis?

number = 0

Returns

T[]

---

flush()

flush(): void;

Defined in: src/vector/BigNeuroVec.ts:714

Flush memory-mapped data to disk

Returns

void

---

close()

close(): void;

Defined in: src/vector/BigNeuroVec.ts:721

Close the memory-mapped file

Returns

void

---

cleanup()

cleanup(): void;

Defined in: src/vector/BigNeuroVec.ts:728

Clean up temporary files

Returns

void

---

toString()

toString(): string;

Defined in: src/vector/BigNeuroVec.ts:735

Returns a string representation of an object.

Returns

string