SclType |
Scaling Operation |
Par1 |
Par2 |

sctMeanCenter |
The values of the array are scaled in such a way that the mean becomes zero. |
in: ignored out: mean |
in: ignored out: 0 |

sctStandardize |
The values are scaled to a zero mean and a standard deviation of 1.0. |
in: ignored out: mean |
in: ignored out: std.dev |

sctConstSum |
The values are scaled to a constant sum defined by the parameter Par1. |
in: intended sum out: actual sum before the scaling |
in: ignored out: 0 |

sctConstSquaredSum |
The values are scaled to a constant sum of squared values. The sum is defined by the parameter Par1. |
in: intended sum out: actual sum before the scaling |
in: ignored out: 0 |

sctMaxAbs |
The values are scaled in such a way that the maximum absolute value becomes Par1 |
in: intended maximum out: actual maximum of the absolute values of the minimum and maximum before the scaling |
in: ignored out: 0 |

sctRange |
The data values are scaled to cover a range between Par1 and Par2 |
in: intended lower value out: actual lowest value before the scaling |
in: intended upper value out: actual highest value before the scaling |

sctSquash |
The data values are compressed by a sigmoid function ("squashing function") to the interval [-1,+1]. The parameter Par1 specifies the origin of the squashing function, the parameter Par2 defines the slope of the function. |
in: origin of the squashing function out: same as in |
in: slope of the squashing function out: same as in |

sctQNormalize |
The data is scaled to zero median and a difference between the median and the q-percentile of 1.0, with q (in %) given by the parameter Par1. |
in: probability q (>50 and <100) out: median |
in: ignored out: difference of the quantile and the median before the scaling |