@saehrimnir/druidjs / MINFOTree

Class: MINFOTree<T>

Defined in: dimred/MINFOTree.js:37

Minimum Information Trees (MINFO Trees)

A visualization method for clustered high-dimensional data. It reads the cluster labels on a k-nearest-neighbor graph as a q-state Potts model, weights the edges by an information-geometric curvature derived from it, and keeps the minimum spanning tree of that weighted graph.

projection returns 2D coordinates like any other method here, but the tree is the actual output — read edges to draw it.

Template

T

See

• https://doi.org/10.1109/ACCESS.2025.3602730
• TopoMap for another spanning-tree-based projection.

Extends

• DR

Type Parameters

Type Parameter	Description
T extends InputType

Constructors

Constructor

new MINFOTree<T>(X: T, parameters?: Partial<ParametersMINFOTree>): MINFOTree<T>;

Defined in: dimred/MINFOTree.js:45

Minimum Information Trees.

Parameters

Parameter	Type	Description
X	T	The high-dimensional data.
parameters?	Partial<ParametersMINFOTree>	Object containing parameterization of the DR method.

Returns

MINFOTree<T>

See

https://doi.org/10.1109/ACCESS.2025.3602730

Overrides

DR.constructor

Properties

Property	Type	Inherited from	Defined in
__input	T	DR.__input	dimred/DR.js:46
_beta	number | undefined	-	dimred/MINFOTree.js:513
_curvature	Float64Array<ArrayBufferLike> | undefined	-	dimred/MINFOTree.js:514
_D	number	DR._D	dimred/DR.js:28
_edges	WeightedEdge[] | undefined	-	dimred/MINFOTree.js:528
_is_initialized	boolean	DR._is_initialized	dimred/DR.js:34
_labels	Int32Array<ArrayBufferLike> | undefined	-	dimred/MINFOTree.js:510
_N	number	DR._N	dimred/DR.js:30
_parameters	ParametersMINFOTree	DR._parameters	dimred/DR.js:49
_q	number | undefined	-	dimred/MINFOTree.js:169
_randomizer	Randomizer	DR._randomizer	dimred/DR.js:32
_type	"array" | "matrix" | "typed"	DR._type	dimred/DR.js:54
X	Matrix	DR.X	dimred/DR.js:56
Y	Matrix	DR.Y	dimred/DR.js:58

Accessors

beta

Get Signature

get beta(): number;

Defined in: dimred/MINFOTree.js:111

The maximum pseudo-likelihood estimate of the Potts inverse temperature.

Returns

number

---

curvature

Get Signature

get curvature(): Float64Array<ArrayBufferLike>;

Defined in: dimred/MINFOTree.js:101

The information curvature S_i per point, normalised as the edge weighting uses it.

Returns

Float64Array<ArrayBufferLike>

---

edges

Get Signature

get edges(): WeightedEdge[];

Defined in: dimred/MINFOTree.js:81

The edges of the Minimum Information Tree, as [u, v, weight] over row indices of X, ascending by weight. This is the method's real output — projection is one drawing of it.

Returns

WeightedEdge[]

---

labels

Get Signature

get labels(): Int32Array<ArrayBufferLike>;

Defined in: dimred/MINFOTree.js:91

The cluster label per point, whether supplied or computed in step 1.

Returns

Int32Array<ArrayBufferLike>

Labels, remapped to 0 … q-1.

---

projection

Get Signature

get projection(): T;

Defined in: dimred/DR.js:219

Returns

T

The projection in the type of input X.

Inherited from

DR.projection

Methods

[dispose]()

dispose: void;

Defined in: dimred/DR.js:320

Alias of release for the using declaration, so a hand-driven run frees its buffers when the block exits. Note that transform and a completed or break-ed generator() already release on their own — this only matters for a generator abandoned part way.

using tsne = new TSNE(X, { d: 2 });
const steps = tsne.generator(500);
steps.next(); // buffers released when the enclosing block exits

Returns

void

Inherited from

DR.[dispose]

---

check_init()

check_init(): DR<T, ParametersMINFOTree>;

Defined in: dimred/DR.js:210

If the respective DR method has an init function, call it before transform.

Returns

DR<T, ParametersMINFOTree>

Inherited from

DR.check_init

---

generator()

generator(): Generator<T, T, void>;

Defined in: dimred/MINFOTree.js:564

Computes the projection.

Returns

Generator<T, T, void>

A generator yielding the intermediate steps of the projection.

Overrides

DR.generator

---

init()

init(): MINFOTree<T>;

Defined in: dimred/MINFOTree.js:507

Runs steps 1-5: labels, k-NNG, β, curvature, information graph and its spanning tree.

Returns

MINFOTree<T>

Overrides

DR.init

---

parameter()

Call Signature

parameter(): ParametersMINFOTree;

Defined in: dimred/DR.js:82

Get all Parameters.

Returns

ParametersMINFOTree

Inherited from

DR.parameter

Call Signature

parameter<K>(name: K): ParametersMINFOTree[K];

Defined in: dimred/DR.js:88

Get value of given parameter.

Type Parameters

Type Parameter	Description
K extends keyof ParametersMINFOTree

Parameters

Parameter	Type	Description
name	K	Name of the parameter.

Returns

ParametersMINFOTree[K]

Inherited from

DR.parameter

Call Signature

parameter<K>(name: K, value: ParametersMINFOTree[K]): MINFOTree<T>;

Defined in: dimred/DR.js:95

Set value of given parameter.

Type Parameters

Type Parameter	Description
K extends keyof ParametersMINFOTree

Parameters

Parameter	Type	Description
name	K	Name of the parameter.
value	ParametersMINFOTree[K]	Value of the parameter to set.

Returns

MINFOTree<T>

Inherited from

DR.parameter

---

release()

release(): MINFOTree<T>;

Defined in: dimred/DR.js:302

Hands back the WASM buffers this instance is holding.

Only needed after driving generator() by hand and stopping early — a plain transform(), or a for…of over generator() (including one you break), already releases when it ends. It frees only this method's buffers, never another running instance's, and the next run simply reallocates, so it is safe to call at any time, more than once, and while other instances are mid-run.

Returns

MINFOTree<T>

Example

const tsne = new TSNE(X, { d: 2 });
const steps = tsne.generator(500);
steps.next();
tsne.release(); // stop early and give the buffers back

Inherited from

DR.release

---

transform()

transform(): T;

Defined in: dimred/MINFOTree.js:538

Computes the projection.

Returns

T

Overrides

DR.transform

---

transform_async()

transform_async(...args: unknown[]): Promise<T>;

Defined in: dimred/DR.js:241

Computes the projection.

Parameters

Parameter	Type	Description
...args	unknown[]	Arguments the transform method of the respective DR method takes.

Returns

Promise<T>

The dimensionality reduced dataset.

Inherited from

DR.transform_async

---

generator()

static generator<T>(X: T, parameters?: Partial<ParametersMINFOTree>): Generator<T, T, void>;

Defined in: dimred/MINFOTree.js:586

Type Parameters

Type Parameter	Description
T extends InputType

Parameters

Parameter	Type	Description
X	T	-
parameters?	Partial<ParametersMINFOTree>	-

Returns

Generator<T, T, void>

Overrides

DR.generator

---

transform()

static transform<T>(X: T, parameters?: Partial<ParametersMINFOTree>): T;

Defined in: dimred/MINFOTree.js:575

Type Parameters

Type Parameter	Description
T extends InputType

Parameters

Parameter	Type	Description
X	T	-
parameters?	Partial<ParametersMINFOTree>	-

Returns

T

Overrides

DR.transform

---

transform_async()

static transform_async<T>(X: T, parameters?: Partial<ParametersMINFOTree>): Promise<T>;

Defined in: dimred/MINFOTree.js:598

Type Parameters

Type Parameter	Description
T extends InputType

Parameters

Parameter	Type	Description
X	T	-
parameters?	Partial<ParametersMINFOTree>	-

Returns

Promise<T>

Overrides

DR.transform_async