Documents · Verb reference

mean

Compute the mean along a dimension while keeping cubes pipe-ready.

Callable type: Grammar verb / pipe stage · Browse: Transform

Usage

from cubedynamics import verbs as v
v.mean(dim='time', *, over=None, keep_dim=True, skipna=True)

Arguments

Argument	Meaning	Default
dim	Dimension to reduce.	'time'
over	Readable alias for dim. Existing dim= calls remain supported.	None
keep_dim	Preserve the reduced dimension with length 1 to keep a (time, y, x) layout when applicable.	True
skipna	Whether to ignore NaN values during reduction.	True

Accepts

An xarray DataArray or Dataset with the dimensions required by the selected operation. VirtualCube support is operation-specific; consult the implementation notes.

Returns

A callable stage. Applying it returns the transformed xarray object (or the supported VirtualCube result).

Order / grammar behavior

Apply before reductions that remove a required dimension. Choose the reduction dimensions explicitly; keep_dim=False removes reduced axes.

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"

result = (pipe(cube) | v.mean(dim="time", keep_dim=False)).unwrap()
result.plot()
plt.show()

Works with