Aggregate

class of dascore.proc.aggregate
inherits from: dascore.proc.aggregate._Reduction, PatchProcessor, DascoreBaseModel, pydantic.main.BaseModel

source

Aggregate(
    *args ,
    dim: Any = None,
    method: Any = mean,
    dim_reduce: Any = empty,
)-> None

Aggregate values along a specified dimension.

Note

The output stays on the patch’s array backend. A method the array API standard has no name for, such as a median or a callable, runs through NumPy and warns before the result is converted back; most shortcuts, such as Patch.mean, avoid that round trip, so prefer one where it fits.

Parameters

Parameter	Description
patch	The input Patch.
dim	The dimension along which aggregations are to be performed. If None, apply aggregation to all dimensions sequentially. If a sequence, apply sequentially in order provided.

dim_reduce	How to reduce the dimensional coordinate associated with the aggregated axis. Can be the name of any valid aggregator, a callable, “empty” (the default) which returns a length 1 partial coord, or “squeeze” which drops the coordinate. For dimensions with datetime or timedelta datatypes, if the operation fails it will automatically be applied to the coordinates converted to floats then the output converted back to the appropriate time type.
method	The aggregation to apply along dimension. Options are: first last max mean median min std sum

Examples

import numpy as np
import dascore as dc
patch = dc.get_example_patch()

# Calculate mean along time axis
patch_time = patch.aggregate("time", method=np.nanmean)

# Calculate median distance along distance dimension
patch_dist = patch.aggregate("distance", method=np.nanmedian)

# Calculate the mean, and remove the associated dimension
patch_mean_no_dim = patch.aggregate(
    "time", method="mean", dim_reduce="squeeze"
)

# Aggregate by the min value and keep the mean of the dimension
patch_mean_min = patch.aggregate(
    "distance", method="min", dim_reduce="mean",
)

Methods

Name	Description
check	Refuse a patch which does not carry what the operation needs.
get_metadata	Return the reduced metadata, and each reduced axis in turn.
kernel	Return the data reduced along each axis in turn.
model_copy	Copy the model, dropping cached values the update invalidates.
new	Create new instance with some attributed updated.
aggregate	Aggregate values along a specified dimension.
reconcile	Return metadata or a patch holding the final data; default as is.
run	Run the operation: check, get_metadata, kernel, reconcile, record.

Parameters

See Also

Examples

Methods