Documents · Verb reference

stack_radius_diagnostics

Describe how focal stack summaries change across nested support radii.

Callable type: Grammar verb / pipe stage · Browse: Synchrony and comparison

Usage

from cubedynamics import verbs as v
v.stack_radius_diagnostics(*, radii_km=None, stable_tolerance=0.02, stable_min_centers=25)

Arguments

Argument	Meaning	Default
radii_km	See implementation docstring below; no parameter-specific description supplied.	None
stable_tolerance	See implementation docstring below; no parameter-specific description supplied.	0.02
stable_min_centers	See implementation docstring below; no parameter-specific description supplied.	25

Accepts

A Dataset produced by v.local_synchrony_stack(...), including center-to-focal distances.

Returns

Nested-radius cold, warm, and Delta counts, moments, robust quantiles, step/derivative fields, and explicitly experimental stable-radius maps.

Order / grammar behavior

Build the unreduced stack first. Requested radii must be increasing and cannot create support outside the source stack; stable-radius fields retain their full experimental rule in metadata.

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"

small = cube.isel(y=slice(0, 4), x=slice(0, 4))
temperature = xr.Dataset({"tmin": small, "tmax": small})
stack = (pipe(temperature) | v.local_synchrony_stack(lower_var="tmin", upper_var="tmax", window_days=14, min_t=3, center_y_indices=range(4), center_x_indices=range(4))).unwrap()
result = (pipe(stack) | v.stack_radius_diagnostics(radii_km=(0, 10, 20, 40), stable_min_centers=3)).unwrap()
result["delta_iqr"].isel(y=1, x=1).plot.line(x="radius_km")
plt.show()

Works with