https://github.com/SymbolixAU/spatialdatatable
Convenience functions for doing spatial calculations on data.tables
https://github.com/SymbolixAU/spatialdatatable
Last synced: 4 months ago
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Convenience functions for doing spatial calculations on data.tables
- Host: GitHub
- URL: https://github.com/SymbolixAU/spatialdatatable
- Owner: SymbolixAU
- Created: 2017-06-26T22:11:56.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2018-05-15T05:27:49.000Z (almost 7 years ago)
- Last Synced: 2024-08-13T07:13:40.703Z (8 months ago)
- Language: R
- Homepage:
- Size: 8.79 MB
- Stars: 30
- Watchers: 8
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
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- jimsghstars - SymbolixAU/spatialdatatable - Convenience functions for doing spatial calculations on data.tables (R)
README
## Spatial Data Table
## Summary
A `spatial.data.table` object is an extension of `data.table`. All the usual operations on a `data.table` (should) work within a `spatial.data.table` too. If not, please let me know by filing an issue.
This package includes convenience functions for doing spatial calculations with data in `data.table` and `spatial.data.table` objects. Notably I have re-written a set of `geosphere::dist_` functions in C++ (using `Rcpp`) by stripping out some of the unnecessary matrix-conversions. The functions also work in the `j` argument of `data.table`, so as per usual `data.table` operations you only have to pass in un-quoted column names.
You can also
- convert `sp` and `sf` objects into `spatial.data.table` using `toSDT()`
- encod `sf` objects (LINESTRINGS, POLYGONS and MULTIPOLYGONS) into polylines (Google's polyline) using `EncodeSF()`
## Installation
Install the developent version using `devtools`
```
devtools::install_github("SymbolixAU/spatialdatatable")
```
## Why I made this package
The driving factor behind developing `spatialdatatable` was to simplify the process of doing distance calculations within a `data.table`, which was driven by writing an [efficient haversine calculation](https://www.symbolix.com.au/blog-main/j26ynx6awfl32brcaxdjxnwalwmmbc) that falls naturally within the `j` argument of `data.table`.
I also wanted to make use of [Google's Encoded Polyline format](https://developers.google.com/maps/documentation/utilities/polylinealgorithm) for storing lines and polygons. The benefit of which is reduced object size
```
library(sf)
## example data that comes with the sf library
filename <- system.file("shape/nc.shp", package="sf")
sf <- st_read(filename)
object.size(sf)
135168 bytes
sdt <- EncodeSF(sf)
object.size(sdt)
50032 bytes
```
The `EncodeSF()` function takes the geometry information from the `sf` object and encodes it using Google's encoding algorithm (without losing any of the other data), and then stores it in a `spatial.data.table` object.
```
sf
# Simple feature collection with 2 features and 1 field
# geometry type: LINESTRING
# dimension: XY
# bbox: xmin: -80.19 ymin: 18.466 xmax: -64.757 ymax: 32.321
# epsg (SRID): NA
# proj4string: NA
# id sf_line
# 1 line1 LINESTRING(-80.19 25.774, -...
# 2 line2 LINESTRING(-70.579 28.745, ...
sdt[1:5, .(.id, lineId, hole, NAME, polyline)]
# .id lineId hole NAME polyline
# 1: 1 1 FALSE Ashe u_d|EtsgpNmmFphLyEbc...
# 2: 2 1 FALSE Alleghany or}|EhdznNyvA~Ce_Dli...
# 3: 3 1 FALSE Surry }re|EbcajNakAf|BqKby...
# 4: 4 1 FALSE Currituck mtt|E`o|nMkpBhs@~I``...
# 5: 4 1 FALSE Currituck m~b~Ev``oMJcqDfwAe}O...
```