GaussianFilter

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

source

GaussianFilter(
    *args ,
    samples: Any = False,
    mode: Any = reflect,
    cval: Any = 0.0,
    truncate: Any = 4.0,
    **kwargs ,
)-> None

Applies a Gaussian filter along specified dimensions.

Parameters

Parameter	Description
patch	The patch to filter
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.
truncate	Truncate the filter kernel length to this many standard deviations.
**kwargs	Used to specify the sigma value (standard deviation) for desired dimensions.

Examples

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

# Apply Gaussian smoothing along time axis.
pa_1 = pa.gaussian_filter(time=0.1)

# Apply Gaussian filter over distance dimension
# using a 3 sample standard deviation.
pa_2 = pa.gaussian_filter(samples=True, distance=3)

# Apply filter to time and distance axis.
pa_3 = pa.gaussian_filter(time=0.1, distance=3)

Note

See scipy.ndimage.gaussian_filter for more info on implementation and arguments.

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 smoothed along the axes.
gaussian_filter	Applies a Gaussian 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.