RectangularMovingWindowStandardization¶
Standardize the signal in a sliding rectangular window.
This node estimates the running mean and running standard deviation in a rectangular window (that is, with equal weighting). Then, each sample is converted to z scores by subtracting the running mean and dividing by the running standard deviation, which are estimated from the k samples prior to that sample. This filter maintains internal state to work seamlessly across chunk boundaries. On the first window length samples, the result will not yet be standardized fully since the filter first needs to collect sufficient data. Version 1.0.0
Ports/Properties¶
data¶
Data to process.
means¶
Estimated averages. This is an additional diagnostic.
stddevs¶
Estimated standard deviations. This is an additioanl diagnostic.
window_length¶
Length of sliding window. This is the window length over which the variance of the signal is estimated.
window_length_unit¶
Unit in which the window length is given.
ignore_nans¶
If activated the channels containing nan values are ignored.
from_to_stream¶
Apply scaling from a stream to another stream.
epsilon¶
Smallest possible standard deviation, to prevent division by zero.
set_breakpoint¶
Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.
metadata¶
User-definable meta-data associated with the node. Usually reserved for technical purposes.