SavgolFilter

class of dascore.proc.filter inherits from: dascore.proc.filter._WindowFilter, PatchProcessor, DascoreBaseModel, pydantic.main.BaseModel

source

SavgolFilter(
    *args ,
    polyorder: Any ,
    samples: Any = False,
    mode: Any = interp,
    cval: Any = 0.0,
    **kwargs ,
)-> None

Applies Savgol filter along specified dimensions.

The filter will be applied over each selected dimension sequentially.

Parameters

Parameter	Description
patch	The patch to filter
polyorder	Order of polynomial
samples	If True, the values in kwargs and step represent samples along a dimension. Must be integers. Otherwise, values are assumed to have same units as the specified dimension, or have units attached.
mode	The mode for handling edges.
cval	The constant value for when mode == constant.
**kwargs	Used to specify the shape of the savgol filter in each dimension.

Note

See scipy.signal.savgol_filter for more info on implementation and arguments.

Examples

import dascore
from dascore.units import m, s
pa = dascore.get_example_patch()

# Apply second order polynomial Savgol filter
# over time dimension with 0.10 sec window.
filtered_pa_1 = pa.savgol_filter(polyorder=2, time=0.1)

# Apply Savgol filter over distance dimension using a 5 sample
# distance window.
filtered_pa_2 = pa.savgol_filter(distance=5, samples=True, polyorder=2)

# Combine distance and time filter
filtered_pa_3 = pa.savgol_filter(distance=10, time=0.1, polyorder=4)

Methods

Name	Description
check	Refuse a patch which does not carry what the operation needs.
get_metadata	Return the window along every axis, and the axes it spans.
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 along each axis in turn.
savgol_filter	Applies Savgol filter along specified dimensions.
reconcile	Return metadata or a patch holding the final data; default as is.
run	Run the operation: check, get_metadata, kernel, reconcile, record.