功能介绍

对数据进行离散余弦变换。

参数说明

名称 中文名称 描述 类型 是否必须？ 默认值
inverse 是否为逆变换 是否为逆变换，false表示正变换，true表示逆变换。默认正变换。 Boolean false
selectedCol 选中的列名 计算列对应的列名 String ✓
outputCol 输出结果列 输出结果列列名，可选，默认null String null
reservedCols 算法保留列名 算法保留列 String[] null

脚本示例

脚本代码

  1. data = np.array([
  2.     ["-0.6264538 0.1836433"],
  3.     ["-0.8356286 1.5952808"],
  4.     ["0.3295078 -0.8204684"],
  5.     ["0.4874291 0.7383247"],
  6.     ["0.5757814 -0.3053884"],
  7.     ["1.5117812 0.3898432"],
  8.     ["-0.6212406 -2.2146999"],
  9.     ["11.1249309 9.9550664"],
  10.     ["9.9838097 10.9438362"],
  11.     ["10.8212212 10.5939013"],
  12.     ["10.9189774 10.7821363"],
  13.     ["10.0745650 8.0106483"],
  14.     ["10.6198257 9.9438713"],
  15.     ["9.8442045 8.5292476"],
  16.     ["9.5218499 10.4179416"],
  17. ])
  19. df_data = pd.DataFrame({
  20.     "features": data[:, 0],
  21. })
  23. data = dataframeToOperator(df_data, schemaStr='features string', op_type='batch')
  25. dct = DctBatchOp() \
  26.     .setSelectedCol("features") \
  27.     .setOutputCol("result")
  29. dct.linkFrom(data).print()

脚本运行结果

  1.                  features                                    result
  2. 0    -0.6264538 0.1836433  -0.31311430733060563 -0.5728251528295567
  3. 1    -0.8356286 1.5952808    0.5371552219632794 -1.7189125211901217
  4. 2    0.3295078 -0.8204684   -0.34716156955541605 0.8131559692231375
  5. 3     0.4874291 0.7383247    0.866738824045179 -0.17740998012986753
  6. 4    0.5757814 -0.3053884    0.19119672388537412 0.6230811409567939
  7. 5     1.5117812 0.3898432     1.3446515085097996 0.7933299678708727
  8. 6   -0.6212406 -2.2146999      -2.005312758591568 1.126745876574769
  9. 7    11.1249309 9.9550664     14.905809038224113 0.8272191210194105
  10. 8    9.9838097 10.9438362    14.798080330160849 -0.6788412482687869
  11. 9   10.8212212 10.5939013     15.142778339690611 0.1607394427886475
  12. 10  10.9189774 10.7821363    15.345004656570287 0.09676126975502636
  13. 11   10.0745650 8.0106483     12.788176963635138 1.4594094943741613
  14. 12   10.6198257 9.9438713      14.54072959496546 0.4779719400128842
  15. 13    9.8442045 8.5292476     12.991992573716212 0.9298149409580412
  16. 14   9.5218499 10.4179416    14.099561785095878 -0.6336325176349823