import _ from 'lodash';
import dataProcessor from '../dataProcessor';

describe('dataProcessor', () => {
  let ctx = {};

  beforeEach(() => {
    ctx.datapoints = [
      [[10, 1500000000000], [2, 1500000001000], [7, 1500000002000], [1, 1500000003000]],
      [[9, 1500000000000],  [3, 1500000001000], [4, 1500000002000], [8, 1500000003000]],
    ];
  });

  describe('When apply groupBy() functions', () => {
    it('should return series average', () => {
      let aggregateBy = dataProcessor.metricFunctions['groupBy'];
      const avg2s = _.map(ctx.datapoints, (dp) => aggregateBy('2s', 'avg', dp));
      expect(avg2s).toEqual([
        [[6, 1500000000000], [4, 1500000002000]],
        [[6, 1500000000000], [6, 1500000002000]],
      ]);

      const avg10s = _.map(ctx.datapoints, (dp) => aggregateBy('10s', 'avg', dp));
      expect(avg10s).toEqual([
        [[5, 1500000000000]],
        [[6, 1500000000000]],
      ]);

      // not aligned
      const dp = [[10, 1500000001000], [2, 1500000002000], [7, 1500000003000], [1, 1500000004000]];
      expect(aggregateBy('2s', 'avg', dp)).toEqual([
        [10, 1500000000000], [4.5, 1500000002000], [1, 1500000004000]
      ]);
    });
  });

  describe('When apply aggregateBy() functions', () => {
    it('should return series average', () => {
      let aggregateBy = dataProcessor.metricFunctions['aggregateBy'];
      const avg1s = aggregateBy('1s', 'avg', ctx.datapoints);
      expect(avg1s).toEqual([
        [9.5, 1500000000000], [2.5, 1500000001000], [5.5, 1500000002000], [4.5, 1500000003000]
      ]);

      const avg10s = aggregateBy('10s', 'avg', ctx.datapoints);
      expect(avg10s).toEqual([
        [5.5, 1500000000000]
      ]);
    });
  });
});