sameSVD

Author: Pramit Ghosh

Description

sameSVD stands for Similarity and Affinity Measures for Spatial Vector Data

This package is still under development and many of the objectives of this package are yet to be implemented or conceptualized.

The objective of this package is to establish (if required) and implement measures of (self-)similarity and (self-)affinity for spatial vector data represented in accordance with the Simple Features (officially Simple Features Access) specifications, as standardized by OGC and ISO.

Present Status

	Similarity	Affinity
Self	- *POINT [done] - *LINESTRING [done] - *POLYGON [done]	- *POINT [not implemented yet] - *LINESTRING [not implemented yet] - *POLYGON [not implemented yet] to be implemented using box-counting dimension
Others	- *POINT [?] - LINESTRING [turning angles] - POLYGON [turning angles] - MULTILINESTRING [?] - MULTIPOLYGON [?]	- *POINT [?] - *LINESTRING [?] - *POLYGON [?] need suitable algorithms to implement

Installation

Dependencies

In order to install this package, the following packages are required as a pre-requisite.

• sf

In addition, the following packages are also suggested. These are mostly required to knit the vignettes and run certain tests.

• rnaturalearth
• rnaturalearthdata
• rgeos

These can be installed by running the following command in R:

install.packages(c("sf", "rnaturalearth", "rnaturalearthdata", "rgeos"))

Installing sameSVD

This package can be installed as follows

install.packages("remotes")
library(remotes)
install_github("pramitghosh/sameSVD")

Usage

The Box-Counting dimension can be calculated using bcd(). The following example illustrates the usage.

library(sameSVD)
library(rnaturalearth)
deutschland = ne_countries(scale = "medium", country = "Germany", returnclass = "sf")
bcd(deutschland, plot = TRUE)

A more detailed illustration along with the internal working can be found in the vignettes.