How to use the vega-dataflow.ingest function in vega-dataflow

groups.forEach(g => {
      const n = g.length;
      if (n <= dof) {
        pulse.dataflow.warn('Skipping regression with more parameters than data points.');
        return;
      }

      const model = fit(g, _.x, _.y, order);

      if (_.params) {
        // if parameter vectors requested return those
        values.push(ingest({
          keys: g.dims,
          coef: model.coef,
          rSquared: model.rSquared
        }));
        return;
      }

      const dom = domain || extent(g, _.x),
            add = p => {
              const t = {};
              for (let i=0; i

groups.forEach(g => {
    const q = quantiles(g, p);

    for (let i=0; i

var src = this.value,
      gen = this.generator, t;

  if (!src.length || _.modified()) {
    for (var prop in _) {
      if (isFunction(gen[prop])) {
        gen[prop](_[prop]);
      }
    }
  }

  t = gen();
  if (src.length) {
    pulse.mod.push(replace(src[0], t));
  } else {
    pulse.add.push(ingest(t));
  }
  src[0] = t;

  return pulse;
};

function defaultItemCreate() {
  return ingest({});
}

add = p => {
              const t = {};
              for (let i=0; i

prototype.newtuple = function(t, p) {
  var names = this._dnames,
      dims = this._dims,
      x = {}, i, n;

  for (i=0, n=dims.length; i

values = sampleCurve(method, domain, minsteps, maxsteps).map(v => {
          var tuple = {};
          tuple[as[0]] = v[0];
          tuple[as[1]] = v[1];
          return ingest(tuple);
        });

function cross(input, a, b, filter) {
  var data = [],
      t = {},
      n = input.length,
      i = 0,
      j, left;

  for (; i

tree.each(function(node) {
      var t = node.data,
          p = node.parent && node.parent.data;
      if (p && lut[tupleid(t)] && lut[tupleid(p)]) {
        out.add.push(ingest({source: p, target: t}));
      }
    });
    this.value = out.add;