const XLSX = require('xlsx');
const tf = require("@tensorflow/tfjs");
//const tf = require("@tensorflow/tfjs-node");

function worksheet_to_csv_url(worksheet) {
  /* generate CSV */
  const csv = XLSX.utils.sheet_to_csv(worksheet);

  /* CSV -> Uint8Array -> Blob */
  const u8 = new TextEncoder().encode(csv);
  const blob = new Blob([u8], { type: "text/csv" });

  /* generate a blob URL */
  return URL.createObjectURL(blob);
}

(async() => { try {
  /* fetch file */
  const f = await fetch("https://docs.sheetjs.com/cd.xls");
  const ab = await f.arrayBuffer();
  /* parse file and get first worksheet */
  const wb = XLSX.read(ab);
  const ws = wb.Sheets[wb.SheetNames[0]];

  /* generate blob URL */
  const url = worksheet_to_csv_url(ws);

  /* feed to tf.js */
  const dataset = tf.data.csv(url, {
    hasHeader: true,
    configuredColumnsOnly: true,
    columnConfigs:{
      "Horsepower": {required: false, default: 0},
      "Miles_per_Gallon":{required: false, default: 0, isLabel:true}
    }
  });

  /* pre-process data */
  let flat = dataset
    .map(({xs,ys}) =>({xs: Object.values(xs), ys: Object.values(ys)}))
    .filter(({xs,ys}) => [...xs,...ys].every(v => v>0));

  /* normalize manually :( */
  let minX = Infinity, maxX = -Infinity, minY = Infinity, maxY = -Infinity;
  await flat.forEachAsync(({xs, ys}) => {
    minX = Math.min(minX, xs[0]); maxX = Math.max(maxX, xs[0]);
    minY = Math.min(minY, ys[0]); maxY = Math.max(maxY, ys[0]);
  });
  flat = flat.map(({xs, ys}) => ({xs:xs.map(v => (v-minX)/(maxX - minX)),ys:ys.map(v => (v-minY)/(maxY-minY))}));
  flat = flat.batch(32);

  /* build and train model */
  const model = tf.sequential();
  model.add(tf.layers.dense({inputShape: [1], units: 1}));
  model.compile({ optimizer: tf.train.sgd(0.000001), loss: 'meanSquaredError' });
  await model.fitDataset(flat, { epochs: 100, callbacks: { onEpochEnd: async (epoch, logs) => {
    console.error(`${epoch}:${logs.loss}`);
  }}});

  /* predict values */
  const inp = tf.linspace(0, 1, 9);
  const pred = model.predict(inp);
  const xs = await inp.dataSync(), ys = await pred.dataSync();

  for (let i=0; i<xs.length; ++i) {
    console.log([xs[i] * (maxX - minX) + minX, ys[i] * (maxY - minY) + minY].join(" "));
  }
} catch(e) { console.error(`ERROR: ${String(e)}`); }})();