Description

Discrete Cosine Transform(DCT) transforms a real-valued sequence in the time domain into another real-valued sequence with same length in the frequency domain.

Parameters

Name Description Type Required？ Default Value
inverse If true, perform inverse transformation(e.g. inverse DCT/inverse FFT). Otherwise perform (forward) transformation. Default: false Boolean false
selectedCol Name of the selected column used for processing String ✓
outputCol Name of the output column String null
reservedCols Names of the columns to be retained in the output table String[] null

Script Example

Code

  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()

Results

  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