FlowPeaks
This module uses the flowPeaks algorithm to assign events to clusters in an unsupervized manner.
-
Name
The operation name; determines the name of the new metadata
-
X Channel, Y Channel
The channels to apply the mixture model to.
-
X Scale, Y Scale
Re-scale the data in Channel before fitting.
-
h, h0
Scalar values that control the smoothness of the estimated distribution. Increasing h makes it “rougher,” while increasing h0 makes it smoother.
-
tol
How readily should clusters be merged? Must be between 0 and 1.
-
Merge Distance
How far apart can clusters be before they are merged?
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By
A list of metadata attributes to aggregate the data before estimating the model. For example, if the experiment has two pieces of metadata,
Time
andDox
, settingby
to["Time", "Dox"]
will fit the model separately to each subset of the data with a unique combination ofTime
andDox
.

