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Align a signal to its peak

Question

Where is the peak after aligning each cycle?

See every package-generated example · Read the complete analysis pipeline

When to use

Use this to place a recurring signal peak at a common origin for shape comparison.

Example figure

Align a signal to its peak output generated by Circadian Workbench

This deterministic example is calculated by the peak_aligned_profile action and drawn by render_peak_aligned_profile_svg, the same renderer used for publication export. Empty or withheld elements are therefore visible exactly as they are in a real result.

import circadian_workbench as cw

cw.call("peak_aligned_profile", recording={"path": "mouse01.awd"}, peak_period="morning")

Required inputs and controls

The public function is the registered action below. settings= is accepted as a friendlier alias for config= by cw.call; the calculation stores the complete normalized config in provenance.

Function reference

cw.call("peak_aligned_profile", recording, config=None, peak_period, anchor_amplitude=None, peak_options=None)

Arguments and parameters

Name Type Required Default Units Meaning
recording recording spec yes — - The record to analyse: {'path': 'data/m01.awd'} (a bare path string also works), {'demo': true} for the built-in deterministic record, {'inline': {'filename': ..., 'text': ...}} for tabular text, {'trace': {'hours': [...], 'values': [...], 'name': ...}} for one elapsed-time trace, or {'channels': {'hours': [...], 'values': {'reporter_a': [...], 'reporter_b': [...]}}} for several measurements from one subject. A returned processed_trace spec retains transformed values, their original clock, source identity and explicit processing history. Versioned recording_snapshot specs are self-contained numeric inputs for replaying in-memory Recording objects; they do not invoke a raw-activity importer.
config object no null - Partial scientific settings. Omitted or None values use the shared installed defaults; invalid fresh values are rejected. Run describe_config for names, meanings, units, bounds and choices. Explicitly load old saved mappings with load_saved_settings to report compatibility conversions.
peak_period string yes — - Peak to detect and align: morning (07:00-14:00) or evening (17:00-22:00).
anchor_amplitude float no null activity amplitude Optional established participant peak amplitude. When supplied, the unsmoothed aligned profile is scaled so time zero equals this value.
peak_options object no null - Peak-alignment options: alignment_window_hours, smoothing_window_bins, polynomial_order, minimum_peak_distance_hours, active_window_hours, and allow_window_max_fallback.

Every nested config key, default, allowed value, and purpose is listed in the complete configuration reference.

How it works

A peak is detected in the chosen clock-time window and the profile is shifted around that peak.

$$ t_{\mathrm{relative}}=t-t_{\mathrm{peak}} $$

Implementation: analysis.py::peak_aligned_profile.

Outputs and interpretation

The result includes relative time, aligned values, detected peak and alignment settings.

cw.call returns a Result: use .data for calculated values, .warnings for scientific qualifications, .provenance for version and input identity, .script for an equivalent replay script, and .files for saved outputs.

Limitations

The window and peak choice control which feature is aligned; inspect the candidates for ambiguous peaks.

Example

The figure above is a real package result from a seeded, redistributable synthetic dataset. The flat gallery bundle retains figure_data_peak-aligned-profile.csv, a standalone plot_peak-aligned-profile.py, source hashes, an editable SVG, and a rendered preview.

Methods text

The profile was aligned to the detected peak within the declared peak window.

See also

Compare measurement channels · Measure population synchrony · Map phase across space · Analysis index · Gallery