ml5-save/src/NeuralNetwork/NeuralNetworkUtils.js

ml5 save

class NeuralNetworkUtils {
  constructor(options) {
    this.options = options || {};
  }

  /**
   * normalizeValue
   * @param {*} value 
   * @param {*} min 
   * @param {*} max 
   */
  // eslint-disable-next-line class-methods-use-this
  normalizeValue(value, min, max) {
    return ((value - min) / (max - min))
  }

  /**
   * unNormalizeValue
   * @param {*} value 
   * @param {*} min 
   * @param {*} max 
   */
  // eslint-disable-next-line class-methods-use-this
  unnormalizeValue(value, min, max) {
    return ((value * (max - min)) + min)
  }

  /**
   * getMin
   * @param {*} _array 
   */
  // eslint-disable-next-line no-unused-vars, class-methods-use-this
  getMin(_array) {
    // return Math.min(..._array)
    return _array.reduce((a, b) => {
      return Math.min(a, b);
    });
  }

  /**
   * getMax
   * @param {*} _array 
   */
  // eslint-disable-next-line no-unused-vars, class-methods-use-this
  getMax(_array) {
    return _array.reduce((a, b) => {
      return Math.max(a, b);
    });
    // return Math.max(..._array)
  }

  /**
   * checks whether or not a string is a json
   * @param {*} str
   */
  // eslint-disable-next-line class-methods-use-this
  isJsonOrString(str) {
    try {
      JSON.parse(str);
    } catch (e) {
      return false;
    }
    return true;
  }

  /**
   * zipArrays
   * @param {*} arr1 
   * @param {*} arr2 
   */
  // eslint-disable-next-line no-unused-vars, class-methods-use-this
  zipArrays(arr1, arr2) {
    if (arr1.length !== arr2.length) {
      console.error('arrays do not have the same length')
      return [];
    }

    const output = [...new Array(arr1.length).fill(null)].map((item, idx) => {
      return {
        ...arr1[idx],
        ...arr2[idx]
      }
    })

    return output;
  }

  /**
   * createLabelsFromArrayValues
   * @param {*} incoming 
   * @param {*} prefix 
   */
  // eslint-disable-next-line class-methods-use-this
  createLabelsFromArrayValues(incoming, prefix) {
    let labels;
    if (Array.isArray(incoming)) {
      labels = incoming.map((v, idx) => `${prefix}_${idx}`)
    }
    return labels;
  }

  /**
   * takes an array and turns it into a json object 
   * where the labels are the keys and the array values
   * are the object values
   * @param {*} incoming 
   * @param {*} labels 
   */
  // eslint-disable-next-line class-methods-use-this
  formatDataAsObject(incoming, labels) {
    let result = {};

    if (Array.isArray(incoming)) {
      incoming.forEach((item, idx) => {
        const label = labels[idx];
        result[label] = item;
      });
      return result;
    } else if (typeof incoming === 'object') {
      result = incoming;
      return result;
    }

    throw new Error('input provided is not supported or does not match your output label specifications')
  }

  /**
   * returns a datatype of the value as string
   * @param {*} val 
   */
  // eslint-disable-next-line class-methods-use-this
  getDataType(val) {
    let dtype = typeof val;

    if (dtype === 'object') {
      if (Array.isArray(val)) {
        dtype = 'array'
      }
    }

    return dtype;
  }

}

const neuralNetworkUtils = () => {
  const instance = new NeuralNetworkUtils();
  return instance;
}

export default neuralNetworkUtils();