Mode |
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 before scaling |
*in:* ignored
*out:* 0 |

sctStandardize |
The values are scaled to a zero mean and a standard deviation of 1.0. This normalisation is also known as "standard normal variate" (SNV). |
*in:* ignored
*out:* mean before scaling |
*in:* ignored
*out:* std.dev before scaling |

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 p-percentile of 1.0, with p (in %) given by the parameter Par1. |
*in:* probability p (>50 and <100)
*out:* median |
*in:* ignored
*out:* difference d of the quantile and the median before the scaling |