Help for package sfcentral

Title:

Spatial Centrality and Dispersion Statistics

Version:

0.1.3

Date:

2025-09-11

Maintainer:

Gabriel V. Gaona <gabo@gavg712.com>

Description:

Compute centrographic statistics (central points, standard distance, standard deviation ellipse, standard deviation box) for observations taken at point locations in 2D or 3D. The 'sfcentral' library was inspired in 'aspace' package but conceived to be used in a spatial 'tidyverse' context.

URL:

https://gavg712.gitlab.io/sfcentral/, https://gitlab.com/gavg712/sfcentral

BugReports:

https://gitlab.com/gavg712/sfcentral/-/issues

Language:

en-US

License:

GPL (≥ 3)

Encoding:

UTF-8

RoxygenNote:

7.3.2

Imports:

geodist (≥ 0.0.7), Hmisc (≥ 4.6.0), lwgeom (≥ 0.2.0), scales (≥ 1.2.0), sf (≥ 1.0.8), stats

Suggests:

ggplot2 (≥ 3.3.6), testthat (≥ 3.0.0)

Config/testthat/edition:

NeedsCompilation:

Packaged:

2025-09-11 17:31:14 UTC; gabo

Author:

Gabriel V. Gaona

[aut, cre]

Repository:

CRAN

Date/Publication:

2025-09-11 18:10:02 UTC

sfcentral: Spatial Centrality and Dispersion Statistics

Description

Author(s)

Maintainer: Gabriel V. Gaona gabo@gavg712.com (ORCID)

Spatial centrality

Description

Functions to find spatial measures of gravity centers.

Usage

st_central_point(.x, .y, ...)

## S3 method for class 'sfg'
st_central_point(
  .x,
  .y = NULL,
  weights = NULL,
  method = c("mean", "median", "geometric", "feature", "min.dist"),
  ...
)

## S3 method for class 'sf'
st_central_point(
  .x,
  .y = NULL,
  weights = NULL,
  method = c("mean", "median", "geometric", "feature", "min.dist"),
  ...
)

## S3 method for class 'sfc'
st_central_point(
  .x,
  .y = NULL,
  weights = NULL,
  method = c("mean", "median", "geometric", "feature", "min.dist"),
  ...
)

Arguments

.x, .y

sf points 2D or 3D

...

arguments to be passed to or from other methods

weights

Numeric. Used in for weighted Mean Center. Has to be same length as number of points.

method

Character. Type of center point to calculate

dist

Atomic numeric, Default 100. Starting distance value for center moving during iterations.

Details

Spatial centers are spatial measures of the gravity center.

methods options are: "mean" is the mean center (equivalent to centroid of the points) calculated by the arithmetic mean of each axis; "geometric", is the corresponding geometric mean of each axis; "median", is the median center, a pair of c(median(x), median(y)) coordinates; "feature", is a minimization of the sum of distances from ith point to every point; "min.dist", is iterative looking for the closest point in bbox of .x that minimizes the sum of distances from ith point to every point in the dataset

Value

"Simple Features" of length 1.

Note

Inspired on ⁠aspace::*()⁠ from Ron Buliung & Randy Bui (2012)

Author(s)

Gabriel Gaona

Examples

requireNamespace("ggplot2", quietly = TRUE)
library(sf, quietly = TRUE)
library(ggplot2)
bbx <- matrix(c(697047,9553483,
                696158,9560476,
                700964,9561425,
                701745,9555358),
              byrow = TRUE,
              ncol = 2)
bbx <- st_multipoint(bbx)
bbx <- st_cast(bbx,"POLYGON")
bbx <- st_sfc(bbx, crs = 31992)
set.seed(1234)
points <- st_sf(geometry = st_sample(bbx, 100))
mean_center <- st_central_point(points, method = "mean")
median_center <- st_central_point(points, method = "median")
geom_center <- st_central_point(points, method = "geometric")
central_feature <- st_central_point(points, method = "feature")
min_dist_center <- st_central_point(points, method = "min.dist")
ggplot() +
  geom_sf(data = points, color = "steelblue", size = 0.5) +
  geom_sf(data = mean_center, color = "blue", size = 3) +
  geom_sf(data = median_center, color = "red") +
  geom_sf(data = geom_center, color = "grey80") +
  geom_sf(data = central_feature, color = "orange") +
  geom_sf(data = min_dist_center, color = "green")

Standard deviation box calculator in 2D or 3D

Description

Calculate the spatial deviation box from a points sf dataset. #' @author Gabriel Gaona

Usage

st_sd_box(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfg'
st_sd_box(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sf'
st_sd_box(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfc'
st_sd_box(.x, centre = NULL, weights = NULL, ...)

Arguments

.x

sf points 2D or 3D

centre

Numeric. Coordinates 2D or 3D of central point. Default NULL, performs a calculation of mean_centre() from point localities

weights

Numeric. Same length of number of .x.

...

ignored

Value

Depends on input, "coords" returns a data.frame of 2 or 3 columns and 4 or 8 point coordinates. "param" returns a data.frame with center coordinates, standard deviation in each axis, space(area for 2D, volume for 3D) and number of dimensions in coordinates.

Examples

 requireNamespace("ggplot2", quietly = TRUE)
 library(sf, quietly = TRUE)
 library(ggplot2)
 bbx <- matrix(c(697047,9553483,
                 696158,9560476,
                 700964,9561425,
                 701745,9555358),
               byrow = TRUE,
               ncol = 2)
 bbx <- st_multipoint(bbx)
 bbx <- st_cast(bbx,"POLYGON")
 bbx <- st_sfc(bbx, crs = 31992)
 set.seed(1234)
 points <- st_sf(geometry = st_sample(bbx, 100))
 SD_BOX <- st_sd_box(points)
 ggplot() +
   geom_sf(data = SD_BOX, fill = NA, color = "darkolivegreen") +
   geom_sf(data = points, color = "steelblue", size = 0.5)

Standard deviation distance calculator

Description

Calculate the spatial deviation distance from a points sf dataset.

Usage

st_sd_distance(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfg'
st_sd_distance(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sf'
st_sd_distance(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfc'
st_sd_distance(.x, centre = NULL, weights = NULL, ...)

Arguments

.x

sf points 2D or 3D

centre

One central point of class sf, sfc, numeric (length 2), matrix (2 col, 1 row), data.frame (2 col, 1 row), or list (length 2). Default NULL, means a calculation of the st_central_point() from .x localities.

weights

Numeric. Same length as number of points in .x.

...

other parameters for sf::st_distance()

Value

A sf "POLYGON" with attribute:

radius (standard deviation distance)
area surrounding,
perimeter,
center coordinates,
weighted indicator if weights were used or not in the calculation.

Author(s)

Gabriel Gaona

Examples

  requireNamespace("ggplot2", quietly = TRUE)
  library(sf, quietly = TRUE)
  library(ggplot2)
  bbx <- matrix(c(697047,9553483,
                  696158,9560476,
                  700964,9561425,
                  701745,9555358),
                byrow = TRUE,
                ncol = 2)
  bbx <- st_multipoint(bbx)
  bbx <- st_cast(bbx,"POLYGON")
  bbx <- st_sfc(bbx, crs = 31992)
  set.seed(1234)
  points <- st_sf(geometry = st_sample(bbx, 100))
  SDD <- st_sd_distance(points)
  ggplot() +
    geom_sf(data = SDD, fill = NA, color = "darkolivegreen") +
    geom_sf(data = points, color = "steelblue", size = 0.5)

Standard deviation ellipse calculator

Description

Calculate the spatial deviation ellipse from a points sf dataset.

Usage

st_sd_ellipse(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfg'
st_sd_ellipse(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sf'
st_sd_ellipse(.x, centre = NULL, weights = NULL, ...)

## S3 method for class 'sfc'
st_sd_ellipse(.x, centre = NULL, weights = NULL, ...)

Arguments

.x

sf points 2D or 3D

centre

Numeric. Coordinates 2D of central point. Default NULL, performs a calculation of mean_centre() from point localities

weights

Numeric. Same length of number of points.

...

ignored

Value

simple features as "POLYGON" with attribute: center coordinates, values for mayor and minor axis radius (sigma.x and sigma.y), rotation (theta and theta_corrected) and geometry properties (eccentricity, area and perimeter)

Author(s)

Gabriel Gaona

Examples

  requireNamespace("ggplot2", quietly = TRUE)
  library(sf, quietly = TRUE)
  library(ggplot2)
  bbx <- matrix(c(697047,9553483,
                  696158,9560476,
                  700964,9561425,
                  701745,9555358),
                byrow = TRUE,
                ncol = 2)
  bbx <- st_multipoint(bbx)
  bbx <- st_cast(bbx,"POLYGON")
  bbx <- st_sfc(bbx, crs = 31992)
  set.seed(1234)
  points <- st_sf(geometry = st_sample(bbx, 100))
  SDE <- st_sd_ellipse(points)
  ggplot() +
    geom_sf(data = SDE, fill = NA, color = "darkolivegreen") +
    geom_sf(data = points, color = "steelblue", size = 0.5)

sfcentral: Spatial Centrality and Dispersion Statistics

Description

Author(s)

See Also

Spatial centrality

Description

Usage

Arguments

Details

Value

Note

Author(s)

Examples

Standard deviation box calculator in 2D or 3D

Description

Usage

Arguments

Value

Examples

Standard deviation distance calculator

Description

Usage

Arguments

Value

Author(s)

Examples

Standard deviation ellipse calculator

Description

Usage

Arguments

Value

Author(s)

Examples