import { orderBy, maxBy, minBy } from 'lodash';
import { SeriesData } from './dataset';

/**
 * 平滑采样算法
 * @description 为了能够使用category type 的 x轴，需要坐标均匀的数据，但是真实数据很难刚好卡在step上，所以我们需要做linear插值补充点，然后再通过scatter散点得到step相近点的坐标
 * @param data [xdim, ydim, ...][]
 * @param smoothWeight
 * @param dataZoom 图表的缩放情况
 */
export const smoothData = (
  data: SeriesData[],
  smoothWeight: number,
  dataZoom: { startValue: number | undefined; endValue: number | undefined },
) => {
  const range = [10, 200]; // 最大点数和最小点数
  const sv = [
    // specialValues
    minBy(data, '[0]'), // left
    maxBy(data, '[1]'), // top
    maxBy(data, '[0]'), // right
    minBy(data, '[1]'), // bottom
  ];
  const orderedData = orderBy(
    data.filter(
      (o) =>
        (dataZoom.startValue !== undefined &&
          o[0] >= dataZoom.startValue &&
          dataZoom.endValue !== undefined &&
          o[0] <= dataZoom.endValue) ||
        sv.includes(o),
    ),
    '[0]',
    'asc',
  );
  const xMax =
    dataZoom.endValue === undefined
      ? orderedData[orderedData.length - 1][0]
      : dataZoom.endValue;
  const xMin =
    dataZoom.startValue === undefined ? orderedData[0][0] : dataZoom.startValue;
  const step = Math.round(
    (xMax - xMin) / ((range[1] - range[0]) * (1 - smoothWeight) + range[0]),
  );
  const res: SeriesData[] = [];
  let x = xMin;
  orderedData.forEach((o, i) => {
    if (sv.includes(o)) {
      res.push(o);
      return;
    }
    if (o[0] >= x) {
      res.push(o);
      x += step;
    }
  });
  return res;
};