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 |