SvdEntropy

SVD entropy: how many independent components the signal's history spans.

SvdEntropy py

data

entropy

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

Slots

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

Parameters

`svd`

Name	Type	Default	Range	Doc
`order`	`int`	`3`	`2 … 20`	Dimension of the delay embedding.
`delay`	`int`	`1`	`1 … 100`	Samples between embedding coordinates.
`normalize`	`bool`	`true`		Scale to 0..1 against an even spread.

`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/svd_entropy.py.

node-bundles/complexity/svd_entropy.py

"""SvdEntropy — how many independent components a signal's own history has, from antropy.

Embeds the signal in a delay space and reads the spread of its singular values: a rhythm needs
few, noise needs all. The last axis is time and is consumed; every axis before it survives.
"""

import antropy
import numpy as np
import goofi


class SvdEntropy(goofi.Node):
    """SVD entropy: how many independent components the signal's history spans."""

    TAGS = ["analysis"]
    INPUTS = {"data": goofi.InputSlot(goofi.DataType.ARRAY, required=True)}
    OUTPUTS = {"entropy": goofi.DataType.ARRAY}
    PARAMS = {
        "svd": {
            "order": goofi.IntParam(3, 2, 20, doc="Dimension of the delay embedding."),
            "delay": goofi.IntParam(1, 1, 100, doc="Samples between embedding coordinates."),
            "normalize": goofi.BoolParam(True, doc="Scale to 0..1 against an even spread."),
        }
    }

    def process(self, data):
        p = self.params.svd
        return np.apply_along_axis(
            antropy.svd_entropy,
            -1,
            np.asarray(data.data, dtype=np.float64),
            order=p.order,
            delay=p.delay,
            normalize=p.normalize,
        ).astype(np.float32)

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