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MultiLabelBinarizer.ts
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MultiLabelBinarizer.ts
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/* eslint-disable */
/* NOTE: This file is auto-generated. Do not edit it directly. */
import crypto from 'node:crypto'
import { PythonBridge, NDArray, ArrayLike, SparseMatrix } from '@/sklearn/types'
/**
Transform between iterable of iterables and a multilabel format.
Although a list of sets or tuples is a very intuitive format for multilabel data, it is unwieldy to process. This transformer converts between this intuitive format and the supported multilabel format: a (samples x classes) binary matrix indicating the presence of a class label.
[Python Reference](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MultiLabelBinarizer.html)
*/
export class MultiLabelBinarizer {
id: string
opts: any
_py: PythonBridge
_isInitialized: boolean = false
_isDisposed: boolean = false
constructor(opts?: {
/**
Indicates an ordering for the class labels. All entries should be unique (cannot contain duplicate classes).
*/
classes?: ArrayLike
/**
Set to `true` if output binary array is desired in CSR sparse format.
@defaultValue `false`
*/
sparse_output?: boolean
}) {
this.id = `MultiLabelBinarizer${crypto.randomUUID().split('-')[0]}`
this.opts = opts || {}
}
get py(): PythonBridge {
return this._py
}
set py(pythonBridge: PythonBridge) {
this._py = pythonBridge
}
/**
Initializes the underlying Python resources.
This instance is not usable until the `Promise` returned by `init()` resolves.
*/
async init(py: PythonBridge): Promise<void> {
if (this._isDisposed) {
throw new Error(
'This MultiLabelBinarizer instance has already been disposed'
)
}
if (this._isInitialized) {
return
}
if (!py) {
throw new Error(
'MultiLabelBinarizer.init requires a PythonBridge instance'
)
}
this._py = py
await this._py.ex`
import numpy as np
from sklearn.preprocessing import MultiLabelBinarizer
try: bridgeMultiLabelBinarizer
except NameError: bridgeMultiLabelBinarizer = {}
`
// set up constructor params
await this._py.ex`ctor_MultiLabelBinarizer = {'classes': np.array(${
this.opts['classes'] ?? undefined
}) if ${this.opts['classes'] !== undefined} else None, 'sparse_output': ${
this.opts['sparse_output'] ?? undefined
}}
ctor_MultiLabelBinarizer = {k: v for k, v in ctor_MultiLabelBinarizer.items() if v is not None}`
await this._py
.ex`bridgeMultiLabelBinarizer[${this.id}] = MultiLabelBinarizer(**ctor_MultiLabelBinarizer)`
this._isInitialized = true
}
/**
Disposes of the underlying Python resources.
Once `dispose()` is called, the instance is no longer usable.
*/
async dispose() {
if (this._isDisposed) {
return
}
if (!this._isInitialized) {
return
}
await this._py.ex`del bridgeMultiLabelBinarizer[${this.id}]`
this._isDisposed = true
}
/**
Fit the label sets binarizer, storing [classes\_](../../glossary.html#term-classes_).
*/
async fit(opts: {
/**
A set of labels (any orderable and hashable object) for each sample. If the `classes` parameter is set, `y` will not be iterated.
*/
y?: any
}): Promise<any> {
if (this._isDisposed) {
throw new Error(
'This MultiLabelBinarizer instance has already been disposed'
)
}
if (!this._isInitialized) {
throw new Error('MultiLabelBinarizer must call init() before fit()')
}
// set up method params
await this._py.ex`pms_MultiLabelBinarizer_fit = {'y': ${
opts['y'] ?? undefined
}}
pms_MultiLabelBinarizer_fit = {k: v for k, v in pms_MultiLabelBinarizer_fit.items() if v is not None}`
// invoke method
await this._py
.ex`res_MultiLabelBinarizer_fit = bridgeMultiLabelBinarizer[${this.id}].fit(**pms_MultiLabelBinarizer_fit)`
// convert the result from python to node.js
return this
._py`res_MultiLabelBinarizer_fit.tolist() if hasattr(res_MultiLabelBinarizer_fit, 'tolist') else res_MultiLabelBinarizer_fit`
}
/**
Fit the label sets binarizer and transform the given label sets.
*/
async fit_transform(opts: {
/**
A set of labels (any orderable and hashable object) for each sample. If the `classes` parameter is set, `y` will not be iterated.
*/
y?: any
}): Promise<NDArray | SparseMatrix[]> {
if (this._isDisposed) {
throw new Error(
'This MultiLabelBinarizer instance has already been disposed'
)
}
if (!this._isInitialized) {
throw new Error(
'MultiLabelBinarizer must call init() before fit_transform()'
)
}
// set up method params
await this._py.ex`pms_MultiLabelBinarizer_fit_transform = {'y': ${
opts['y'] ?? undefined
}}
pms_MultiLabelBinarizer_fit_transform = {k: v for k, v in pms_MultiLabelBinarizer_fit_transform.items() if v is not None}`
// invoke method
await this._py
.ex`res_MultiLabelBinarizer_fit_transform = bridgeMultiLabelBinarizer[${this.id}].fit_transform(**pms_MultiLabelBinarizer_fit_transform)`
// convert the result from python to node.js
return this
._py`res_MultiLabelBinarizer_fit_transform.tolist() if hasattr(res_MultiLabelBinarizer_fit_transform, 'tolist') else res_MultiLabelBinarizer_fit_transform`
}
/**
Get metadata routing of this object.
Please check [User Guide](../../metadata_routing.html#metadata-routing) on how the routing mechanism works.
*/
async get_metadata_routing(opts: {
/**
A [`MetadataRequest`](sklearn.utils.metadata_routing.MetadataRequest.html#sklearn.utils.metadata_routing.MetadataRequest "sklearn.utils.metadata_routing.MetadataRequest") encapsulating routing information.
*/
routing?: any
}): Promise<any> {
if (this._isDisposed) {
throw new Error(
'This MultiLabelBinarizer instance has already been disposed'
)
}
if (!this._isInitialized) {
throw new Error(
'MultiLabelBinarizer must call init() before get_metadata_routing()'
)
}
// set up method params
await this._py
.ex`pms_MultiLabelBinarizer_get_metadata_routing = {'routing': ${
opts['routing'] ?? undefined
}}
pms_MultiLabelBinarizer_get_metadata_routing = {k: v for k, v in pms_MultiLabelBinarizer_get_metadata_routing.items() if v is not None}`
// invoke method
await this._py
.ex`res_MultiLabelBinarizer_get_metadata_routing = bridgeMultiLabelBinarizer[${this.id}].get_metadata_routing(**pms_MultiLabelBinarizer_get_metadata_routing)`
// convert the result from python to node.js
return this
._py`res_MultiLabelBinarizer_get_metadata_routing.tolist() if hasattr(res_MultiLabelBinarizer_get_metadata_routing, 'tolist') else res_MultiLabelBinarizer_get_metadata_routing`
}
/**
Transform the given indicator matrix into label sets.
*/
async inverse_transform(opts: {
/**
A matrix containing only 1s ands 0s.
*/
yt?: NDArray | SparseMatrix[]
}): Promise<any> {
if (this._isDisposed) {
throw new Error(
'This MultiLabelBinarizer instance has already been disposed'
)
}
if (!this._isInitialized) {
throw new Error(
'MultiLabelBinarizer must call init() before inverse_transform()'
)
}
// set up method params
await this._py
.ex`pms_MultiLabelBinarizer_inverse_transform = {'yt': np.array(${
opts['yt'] ?? undefined
}) if ${opts['yt'] !== undefined} else None}
pms_MultiLabelBinarizer_inverse_transform = {k: v for k, v in pms_MultiLabelBinarizer_inverse_transform.items() if v is not None}`
// invoke method
await this._py
.ex`res_MultiLabelBinarizer_inverse_transform = bridgeMultiLabelBinarizer[${this.id}].inverse_transform(**pms_MultiLabelBinarizer_inverse_transform)`
// convert the result from python to node.js
return this
._py`res_MultiLabelBinarizer_inverse_transform.tolist() if hasattr(res_MultiLabelBinarizer_inverse_transform, 'tolist') else res_MultiLabelBinarizer_inverse_transform`
}
/**
Set output container.
See [Introducing the set\_output API](../../auto_examples/miscellaneous/plot_set_output.html#sphx-glr-auto-examples-miscellaneous-plot-set-output-py) for an example on how to use the API.
*/
async set_output(opts: {
/**
Configure output of `transform` and `fit\_transform`.
*/
transform?: 'default' | 'pandas'
}): Promise<any> {
if (this._isDisposed) {
throw new Error(
'This MultiLabelBinarizer instance has already been disposed'
)
}
if (!this._isInitialized) {
throw new Error(
'MultiLabelBinarizer must call init() before set_output()'
)
}
// set up method params
await this._py.ex`pms_MultiLabelBinarizer_set_output = {'transform': ${
opts['transform'] ?? undefined
}}
pms_MultiLabelBinarizer_set_output = {k: v for k, v in pms_MultiLabelBinarizer_set_output.items() if v is not None}`
// invoke method
await this._py
.ex`res_MultiLabelBinarizer_set_output = bridgeMultiLabelBinarizer[${this.id}].set_output(**pms_MultiLabelBinarizer_set_output)`
// convert the result from python to node.js
return this
._py`res_MultiLabelBinarizer_set_output.tolist() if hasattr(res_MultiLabelBinarizer_set_output, 'tolist') else res_MultiLabelBinarizer_set_output`
}
/**
Transform the given label sets.
*/
async transform(opts: {
/**
A set of labels (any orderable and hashable object) for each sample. If the `classes` parameter is set, `y` will not be iterated.
*/
y?: any
}): Promise<any> {
if (this._isDisposed) {
throw new Error(
'This MultiLabelBinarizer instance has already been disposed'
)
}
if (!this._isInitialized) {
throw new Error('MultiLabelBinarizer must call init() before transform()')
}
// set up method params
await this._py.ex`pms_MultiLabelBinarizer_transform = {'y': ${
opts['y'] ?? undefined
}}
pms_MultiLabelBinarizer_transform = {k: v for k, v in pms_MultiLabelBinarizer_transform.items() if v is not None}`
// invoke method
await this._py
.ex`res_MultiLabelBinarizer_transform = bridgeMultiLabelBinarizer[${this.id}].transform(**pms_MultiLabelBinarizer_transform)`
// convert the result from python to node.js
return this
._py`res_MultiLabelBinarizer_transform.tolist() if hasattr(res_MultiLabelBinarizer_transform, 'tolist') else res_MultiLabelBinarizer_transform`
}
/**
A copy of the `classes` parameter when provided. Otherwise it corresponds to the sorted set of classes found when fitting.
*/
get classes_(): Promise<NDArray> {
if (this._isDisposed) {
throw new Error(
'This MultiLabelBinarizer instance has already been disposed'
)
}
if (!this._isInitialized) {
throw new Error(
'MultiLabelBinarizer must call init() before accessing classes_'
)
}
return (async () => {
// invoke accessor
await this._py
.ex`attr_MultiLabelBinarizer_classes_ = bridgeMultiLabelBinarizer[${this.id}].classes_`
// convert the result from python to node.js
return this
._py`attr_MultiLabelBinarizer_classes_.tolist() if hasattr(attr_MultiLabelBinarizer_classes_, 'tolist') else attr_MultiLabelBinarizer_classes_`
})()
}
}