Stalta

class of dascore.transform.stalta
inherits from: PatchProcessor, DascoreBaseModel, pydantic.main.BaseModel

Stalta(
    *args ,
    samples: Any = False,
    **kwargs ,
)-> None

Compute the short-term / long-term average (STA/LTA) ratio along a patch dimension.

Parameters

Parameter	Description
samples	If True, values specified by kwargs are in samples not coordinate units.
**kwargs	Used to pass one dimension name and the short/long-term window lengths. For example `time=(0.1, 0.5)` uses windows of 0.1 and 0.5 seconds along the time axis.

Returns

PatchType A new patch containing the STA/LTA ratio.

Note

A good first guess is to choose the long-term window 5x the length of the short-term window.

Examples

import dascore as dc

p = dc.examples.example_event_2()

s = p.envelope(dim="time").stalta(time=(0.002, 0.01))
s.viz.waterfall(  # doctest: +SKIP
    cmap="RdGy_r", scale=[0, 2], scale_type="absolute"
);

Methods

Name	Description
check	Refuse a patch which does not carry what the operation needs.
chunk_contract	Return what a chunk of the output needs of the input, or None.
get_metadata	Return the ratio’s metadata, and each window and how it is rolled.
model_copy	Copy the model, dropping cached values the update invalidates.
new	Create new instance with some attributed updated.
numpy_kernel	Return the short-term rolling mean over the long-term one.
stalta	Compute the short-term / long-term average (STA/LTA) ratio along a patch dimension.
reconcile	Return metadata or a patch holding the final data; default as is.
run	Run the operation: check, get_metadata, kernel, reconcile, record.