blur_sigmas: Standard deviation of Gaussian blur

In tdarec: A 'recipes' Extension for Persistent Homology and Its Vectorizations

Standard deviation of Gaussian blur

Description

The standard deviation of the noise function convolved with array values to induce blur in raster data.

Usage

blur_sigmas(range = c(unknown(), unknown()), trans = transform_log1p())

Arguments

range	A two-element vector holding the defaults for the smallest and largest possible values, respectively. If a transformation is specified, these values should be in the transformed units.
trans	A trans object from the scales package, such as scales::transform_log10() or scales::transform_reciprocal(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

Details

The gaussian blur step deploys blur(). See there for definitions and references.

get_blur_range() varies the parameter logarithmically from 0 to an order of magnitude greater than the blur() default.

Value

A param object or list of param objects.

Examples

img_dat <- data.frame(img = I(list(volcano)))

(blur_man <- blur_sigmas(range = c(0, 3)))
grid_regular(blur_man)

(blur_fin <- blur_sigmas() %>% get_blur_range(x = img_dat))
grid_regular(blur_fin)

tdarec documentation built on June 8, 2025, 10:41 a.m.