Decimate

class of dascore.proc.resample
inherits from: dascore.proc.resample._DecimateFields, PatchProcessor, DascoreBaseModel, pydantic.main.BaseModel

source

Decimate(
    *args ,
    filter_type: Any = iir,
    copy: Any = True,
    **kwargs ,
)-> None

Decimate a patch along a dimension.

Parameters

Parameter	Description
patch	The patch to decimate.
filter_type	Anti-aliasing filter: `"iir"`, `"fir"`, or None. None disables pre-filtering and may cause aliasing.
copy	Copy the sliced data so it does not retain the original array. Applies only when `filter_type` is None.
**kwargs	Dimension and factor; `time=10` decimates the time axis by 10.

Note

Uses scipy.signal.decimate when filter_type is specified; otherwise, takes every nth sample along the dimension.
If the decimation dimension is small, this can fail due to lack of padding values.
Coordinates measured on the decimated dimension are decimated with it: taking every nth value of a dimension takes every nth value of everything indexed by it.
With a filter, missing samples (holes in the step) raise; use split_gaps or fill_gaps first.

Examples

import dascore as dc
patch = dc.get_example_patch()
decimated_irr = patch.decimate(time=10, filter_type='iir')
# Example using fir along distance dimension
decimated_fir = patch.decimate(distance=10, filter_type='fir')

Methods

Name	Description
check	Refuse a patch which does not carry what the operation needs.
get_metadata	Return the decimated coordinates, the axis, factor and slices.
kernel	Return the data sliced on its own backend; filtered by numpy.
model_copy	Copy the model, dropping cached values the update invalidates.
new	Create new instance with some attributed updated.
numpy_kernel	Return the data filtered and decimated by scipy, or sliced.
decimate	Decimate a patch along a 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