wk0.9.3 package

Lightweight Well-Known Geometry Parsing

Circle accessors

2D Circle Vectors

Deprecated functions

Grid cell operators

Extract values from a grid

Index snap functions

Subset grid objects

Grid information

Compute overview grid tile

Extract normalized grid tiles

Raster-like objects

Test handlers for handling of unknown size vectors

S3 details for crc objects

S3 details for grid objects

S3 details for rct objects

S3 Details for wk_wkb

S3 Details for wk_wkt

S3 details for xy objects

Plot grid objects

Rectangle accessors and operators

2D rectangle vectors

Vctrs methods

2D bounding rectangles

Chunking strategies

Count geometry components

Compare CRS objects

Special CRS values

CRS object generic methods

Set and get vector CRS

Debug filters and handlers

Create example geometry objects

Extract simple geometries

Format well-known geometry for printing

Handle specific regions of objects

Use data.frame with wk

Read geometry vectors

Handler interface for grid objects

Copy a geometry vector

Set and get vector geodesic edge interpolation

Create lines, polygons, and collections

Extract feature-level meta

Orient polygon coordinates

Plot well-known geometry vectors

Validate well-known binary and well-known text

Set coordinate values

Affine transformer

Transform using explicit coordinate values

Generic transform class

Apply coordinate transformations

Translate geometry vectors

Extract vertices

Do nothing

Write geometry vectors

wk: Lightweight Well-Known Geometry Parsing

Convert well-known binary to hex

Mark lists of raw vectors as well-known binary

Mark character vectors as well-known text

XY vector extractors

Efficient point vectors

Provides a minimal R and C++ API for parsing well-known binary and well-known text representation of geometries to and from R-native formats. Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are useful in R only if the information they contain can be accessed in R, for which high-performance functions are provided here.

Maintainer: Dewey Dunnington License: MIT + file LICENSE Last published: 2024-09-06

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