@debut/plugin-neurofilter/dist/neurohelper.js

Neuro filter plugin for debute

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.NeuroHelper = void 0;
const brain_js_1 = require("brain.js");
const community_core_1 = require("@debut/community-core");
class NeuroHelper {
    constructor(botName, nnOptions = {}) {
        this.trained = false;
        this.trainingSet = [];
        this.botData = community_core_1.utils.cli.getBotData(botName);
        this.nn = new brain_js_1.NeuralNetwork({
            hiddenLayers: [64, 32, 16],
            activation: 'sigmoid',
            leakyReluAlpha: 0.01,
            ...nnOptions,
        });
    }
    addTrainingData(data) {
        this.trainingSet.push(data);
    }
    updateTrainingOut(id, output) {
        const target = this.trainingSet.find((item) => item.id === id);
        if (!target) {
            return;
        }
        target.output = [output];
    }
    train(options = {}) {
        this.trainingSet.forEach((data) => {
            if (!data || data.output === null) {
                throw 'Training data is invalid';
            }
        });
        console.log('Traning data size:', this.trainingSet.length);
        console.log('\n---- Neuro Training ----\n');
        this.nn.train(this.trainingSet, {
            iterations: 40000,
            errorThresh: 0.006,
            logPeriod: 1000,
            log: true,
            ...options,
        });
    }
    run(input) {
        // @ts-ignore
        return this.nn.run(input)[0];
    }
    save(ticker) {
        const path = `${this.botData.src}/neuroData/${ticker}.json`;
        community_core_1.utils.file.ensureFile(path);
        community_core_1.utils.file.saveFile(path, this.nn.toJSON());
    }
    load(ticker) {
        const path = `${this.botData.src}/neuroData/${ticker}.json`;
        const data = community_core_1.utils.file.readFile(path);
        if (data) {
            this.nn.fromJSON(JSON.parse(data));
            this.trained = true;
        }
    }
}
exports.NeuroHelper = NeuroHelper;
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