SampleEntropy

Sample entropy: how rarely a pattern that recurred keeps recurring.

SampleEntropy py

data

entropy

Type name: signal:SampleEntropy
Plane: signal
Tags: analysis
Language: python
Tier: in-process
Bundle: complexity
Source: node-bundles/complexity/sample_entropy.py
Availability: available

Slots

Slot	Direction	Type
`data`	input	ARRAY
`entropy`	output	ARRAY

Parameters

`sample`

Name	Type	Default	Range	Doc
`order`	`int`	`2`	`1 … 10`	How many samples make one pattern.
`metric`	`string`	`chebyshev`	`chebyshev \| euclidean`	How far apart two patterns may be to match.
`approximate`	`bool`	`false`		Count a pattern as matching itself: approximate entropy, the older biased form.

`common`

Name	Type	Default	Range	Doc
`autotrigger`	`bool`	`false`		Run on the node's own schedule, instead of waiting for an input frame. Turn this on for sources; leave it off for transforms driven by their input.
`max_frequency`	`float`	`0`	`0 … 100`	Rate cap for this node, read through `frequency_mode`. 0 means uncapped — the node runs as often as the scheduler and its inputs allow.
`frequency_mode`	`string`	`updates_per_second`	`updates_per_second \| seconds_per_update`	How to read `max_frequency`: as a rate in Hz (updates per second), or as a period in seconds between updates — convenient for very slow nodes.

Source

The current source of this node, as it stands in the goofi repository at node-bundles/complexity/sample_entropy.py.

node-bundles/complexity/sample_entropy.py

"""SampleEntropy — how unpredictable a signal is, from antropy.

Counts how often a short pattern that recurred keeps recurring one sample longer; a signal that
is regular scores near 0. The last axis is time and is consumed; every axis before it survives.
"""

import antropy
import numpy as np
import goofi


class SampleEntropy(goofi.Node):
    """Sample entropy: how rarely a pattern that recurred keeps recurring."""

    TAGS = ["analysis"]
    INPUTS = {"data": goofi.InputSlot(goofi.DataType.ARRAY, required=True)}
    OUTPUTS = {"entropy": goofi.DataType.ARRAY}
    PARAMS = {
        "sample": {
            "order": goofi.IntParam(2, 1, 10, doc="How many samples make one pattern."),
            "metric": goofi.StringParam(
                "chebyshev", ["chebyshev", "euclidean"], doc="How far apart two patterns may be to match."
            ),
            "approximate": goofi.BoolParam(
                False, doc="Count a pattern as matching itself: approximate entropy, the older biased form."
            ),
        }
    }

    def process(self, data):
        p = self.params.sample
        measure = antropy.app_entropy if p.approximate else antropy.sample_entropy
        return np.apply_along_axis(
            measure, -1, np.asarray(data.data, dtype=np.float64), order=p.order, metric=p.metric
        ).astype(np.float32)

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This reference describes goofi 3.1.0(537cd394), generated from a running instance on 2026-09-06.