Documents · Verb reference
timing_synchrony
Measure whether one-to-one matched events happen at similar times.
Callable type: Grammar verb / pipe stage · Browse: Synchrony and comparison
Usage
from cubedynamics import verbs as v
v.timing_synchrony(*, event_anchor='start', match_tolerance='7D', score='exponential', timescale='3D', spatial_mode='neighbors', radius_km=None, k_neighbors=None, reference=None)
Arguments
| Argument | Meaning | Default |
|---|---|---|
| event_anchor | See implementation docstring below; no parameter-specific description supplied. | 'start' |
| match_tolerance | See implementation docstring below; no parameter-specific description supplied. | '7D' |
| score | See implementation docstring below; no parameter-specific description supplied. | 'exponential' |
| timescale | See implementation docstring below; no parameter-specific description supplied. | '3D' |
| spatial_mode | See implementation docstring below; no parameter-specific description supplied. | 'neighbors' |
| radius_km | See implementation docstring below; no parameter-specific description supplied. | None |
| k_neighbors | See implementation docstring below; no parameter-specific description supplied. | None |
| reference | See implementation docstring below; no parameter-specific description supplied. | None |
Accepts
EventResult -> synchrony Dataset with lag and unmatched-event diagnostics.
Returns
EventResult -> synchrony Dataset with lag and unmatched-event diagnostics.
Order / grammar behavior
EventResult -> synchrony Dataset with lag and unmatched-event diagnostics.
Minimal example
Run from the repository root after python -m pip install -e '.[vignettes]'. Uses the checked observational PRISM fixture; no network is required.
from pathlib import Path
import xarray as xr
import matplotlib.pyplot as plt
from cubedynamics import pipe, verbs as v
# Frozen, reviewed PRISM observations; run from the repository root.
path = Path("tests/fixtures/real_data/prism_boulder_january_2024.nc")
with xr.open_dataset(path, engine="scipy") as observed:
cube = observed["tmax"].load()
assert cube.attrs["units"] == "degC"
events = (pipe(cube) | v.threshold_state(threshold=0, direction="below") | v.detect_events()).unwrap()
result = (pipe(events) | v.timing_synchrony(spatial_mode="reference", reference="center")).unwrap()
result["timing_synchrony"].squeeze().plot()
plt.show()
Works with
EventResult -> synchrony Dataset with lag and unmatched-event diagnostics.
See also
Implementation notes
No additional implementation notes in the current docstring.
Implementation source. Signatures and descriptions on this page are generated from this checkout, not hand-maintained copies.