Documents · Verb reference
occurrence_synchrony
Measure whether states occur at the same times across locations.
Callable type: Grammar verb / pipe stage · Browse: Synchrony and comparison
Usage
from cubedynamics import verbs as v
v.occurrence_synchrony(*, spatial_mode='neighbors', radius_km=None, k_neighbors=None, reference=None, method='jaccard', window=None, stride=None, state_var='state')
Arguments
| Argument | Meaning | Default |
|---|---|---|
| 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 |
| method | See implementation docstring below; no parameter-specific description supplied. | 'jaccard' |
| window | See implementation docstring below; no parameter-specific description supplied. | None |
| stride | See implementation docstring below; no parameter-specific description supplied. | None |
| state_var | See implementation docstring below; no parameter-specific description supplied. | 'state' |
Accepts
State cube -> synchrony Dataset. Reference/neighborhood modes return maps; all-pairs returns edge data; regional returns time-series summaries.
Returns
State cube -> synchrony Dataset. Reference/neighborhood modes return maps; all-pairs returns edge data; regional returns time-series summaries.
Order / grammar behavior
State cube -> synchrony Dataset. Reference/neighborhood modes return maps; all-pairs returns edge data; regional returns time-series summaries.
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"
state = (pipe(cube) | v.threshold_state(threshold=0, direction="below")).unwrap()
result = (pipe(state) | v.occurrence_synchrony(spatial_mode="reference", reference="center")).unwrap()
result["occurrence_synchrony"].squeeze().plot()
plt.show()
Works with
State cube -> synchrony Dataset. Reference/neighborhood modes return maps; all-pairs returns edge data; regional returns time-series summaries.
See also
- Related workflow
- 06 · From cold observations to event evidence
- Learn: verbs
- Noun library
- Verbs by purpose
- All public callables (A–Z)
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.