Feature: isolines custom id/retain attributes #153
Assignees
Labels
feature
New feature or enhancement
Comments
|
Thanks for the positive feedback on the package. This is very motivating to continue to maintain the package :) Retaining the attributes of the input is not ideal, since in many requests to the HERE APIs (not only the isoline routing), there is more than one response (alternatives, different ranges, triplegs …), which by default would lead to duplication of attributes in the resulting sf data.frames. To ensure the possibility of joining input and output data, the order of results is the same as the order of the requests (although they are sent asynchronously to the APIs). Therefore, you can join the results to the input data by using the The isoline request is somewhat special, since by default ( library(sf)
#> Linking to GEOS 3.10.2, GDAL 3.4.2, PROJ 8.2.1; sf_use_s2() is TRUE
library(hereR)
set_verbose(TRUE)
data(poi)
# Add IDs (or use row.names if they are the default sequence)
poi$id <- seq_len(nrow(poi))
# Request isolines, without aggregating
iso = isoline(poi, aggregate = FALSE)
#> Sending 8 request(s) with 1 RPS to: 'https://isoline.router.hereapi.com/v8/isolines?...'
#> Received 8 response(s) with total size: 82.9 Kb
# non-spatial join
(iso_attr <- st_sf(merge(as.data.frame(poi), iso, by = "id", all = TRUE)))
#> Simple feature collection with 48 features and 7 fields
#> Active geometry column: geometry.x
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 6.140028 ymin: 46.00038 xmax: 9.516669 ymax: 47.58039
#> Geodetic CRS: WGS 84
#> First 10 features:
#> id city population rank departure arrival range
#> 1 1 Luzern 250000 1 2022-07-03 14:00:32 2022-07-03 14:05:32 300
#> 2 1 Luzern 250000 2 2022-07-03 14:00:32 2022-07-03 14:10:32 600
#> 3 1 Luzern 250000 3 2022-07-03 14:00:32 2022-07-03 14:15:32 900
#> 4 1 Luzern 250000 4 2022-07-03 14:00:32 2022-07-03 14:20:32 1200
#> 5 1 Luzern 250000 5 2022-07-03 14:00:32 2022-07-03 14:25:32 1500
#> 6 1 Luzern 250000 6 2022-07-03 14:00:32 2022-07-03 14:30:32 1800
#> 7 2 Lugano 105388 1 2022-07-03 14:00:32 2022-07-03 14:05:32 300
#> 8 2 Lugano 105388 2 2022-07-03 14:00:32 2022-07-03 14:10:32 600
#> 9 2 Lugano 105388 3 2022-07-03 14:00:32 2022-07-03 14:15:32 900
#> 10 2 Lugano 105388 4 2022-07-03 14:00:32 2022-07-03 14:20:32 1200
#> geometry.x geometry.y
#> 1 POINT (8.280001 47.05042) POLYGON ((8.245926 47.04895...
#> 2 POINT (8.280001 47.05042) POLYGON ((8.185501 47.04895...
#> 3 POINT (8.280001 47.05042) POLYGON ((8.107224 47.05856...
#> 4 POINT (8.280001 47.05042) POLYGON ((8.070145 47.07092...
#> 5 POINT (8.280001 47.05042) POLYGON ((7.976761 47.21924...
#> 6 POINT (8.280001 47.05042) POLYGON ((7.925949 47.24808...
#> 7 POINT (8.966677 46.00038) POLYGON ((8.954544 46.01624...
#> 8 POINT (8.966677 46.00038) POLYGON ((8.932571 46.03272...
#> 9 POINT (8.966677 46.00038) POLYGON ((8.898239 46.01761...
#> 10 POINT (8.966677 46.00038) POLYGON ((8.866653 45.98877...
# Remove IDs
poi$id <- NULL
# Request isolines, with aggregating
iso = isoline(poi, aggregate = TRUE)
#> Sending 8 request(s) with 1 RPS to: 'https://isoline.router.hereapi.com/v8/isolines?...'
#> Received 8 response(s) with total size: 83 Kb
# Avoid another issue, concerning invalid spherical geometries...
# Consider converting the coordinates to a projected CRS, e.g. for Switzerland: EPSG 2056
sf::sf_use_s2(FALSE)
#> Spherical geometry (s2) switched off
poi <- st_transform(poi, 2056)
iso <- st_transform(iso, 2056)
# Spatial join
iso_attr <- st_join(iso, poi)
# Convert back to lat/lng WGS 84
(iso_attr <- st_transform(iso_attr, 4326))
#> Simple feature collection with 232 features and 7 fields
#> Geometry type: MULTIPOLYGON
#> Dimension: XY
#> Bounding box: xmin: 5.84473 ymin: 45.81848 xmax: 9.73389 ymax: 47.93335
#> Geodetic CRS: WGS 84
#> First 10 features:
#> id rank departure arrival range city population
#> 1 NA 1 2022-07-03 14:23:42 2022-07-03 14:28:42 300 Luzern 250000
#> 1.1 NA 1 2022-07-03 14:23:42 2022-07-03 14:28:42 300 Lugano 105388
#> 1.2 NA 1 2022-07-03 14:23:42 2022-07-03 14:28:42 300 Lausanne 265702
#> 1.3 NA 1 2022-07-03 14:23:42 2022-07-03 14:28:42 300 Basel 830000
#> 1.4 NA 1 2022-07-03 14:23:42 2022-07-03 14:28:42 300 Bern 275329
#> 1.5 NA 1 2022-07-03 14:23:42 2022-07-03 14:28:42 300 Zurich 1108000
#> 1.6 NA 1 2022-07-03 14:23:42 2022-07-03 14:28:42 300 Geneva 1240000
#> 1.7 NA 1 2022-07-03 14:23:42 2022-07-03 14:28:42 300 Vaduz 36281
#> 2 NA 2 2022-07-03 14:23:42 2022-07-03 14:33:42 600 <NA> NA
#> 3 NA 3 2022-07-03 14:23:42 2022-07-03 14:38:42 900 <NA> NA
#> geometry
#> 1 MULTIPOLYGON (((8.95523 46....
#> 1.1 MULTIPOLYGON (((8.95523 46....
#> 1.2 MULTIPOLYGON (((8.95523 46....
#> 1.3 MULTIPOLYGON (((8.95523 46....
#> 1.4 MULTIPOLYGON (((8.95523 46....
#> 1.5 MULTIPOLYGON (((8.95523 46....
#> 1.6 MULTIPOLYGON (((8.95523 46....
#> 1.7 MULTIPOLYGON (((8.95523 46....
#> 2 MULTIPOLYGON (((8.95523 45....
#> 3 MULTIPOLYGON (((8.95935 45....
sf::sf_use_s2(TRUE)
#> Spherical geometry (s2) switched onI hope this solves your issue? Maybe it would make more sense to set Session infodevtools::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.2.0 (2022-04-22)
#> os macOS Big Sur/Monterey 10.16
#> system x86_64, darwin17.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Europe/Zurich
#> date 2022-07-03
#> pandoc 2.18 @ /usr/local/bin/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> brio 1.1.3 2021-11-30 [1] CRAN (R 4.2.0)
#> cachem 1.0.6 2021-08-19 [1] CRAN (R 4.2.0)
#> callr 3.7.0 2021-04-20 [1] CRAN (R 4.2.0)
#> class 7.3-20 2022-01-16 [1] CRAN (R 4.2.0)
#> classInt 0.4-7 2022-06-10 [1] CRAN (R 4.2.0)
#> cli 3.3.0 2022-04-25 [1] CRAN (R 4.2.0)
#> crayon 1.5.1 2022-03-26 [1] CRAN (R 4.2.0)
#> crul 1.2.0 2021-11-22 [1] CRAN (R 4.2.0)
#> curl 4.3.2 2021-06-23 [1] CRAN (R 4.2.0)
#> data.table 1.14.2 2021-09-27 [1] CRAN (R 4.2.0)
#> DBI 1.1.3 2022-06-18 [1] CRAN (R 4.2.0)
#> desc 1.4.1 2022-03-06 [1] CRAN (R 4.2.0)
#> devtools 2.4.3 2021-11-30 [1] CRAN (R 4.2.0)
#> digest 0.6.29 2021-12-01 [1] CRAN (R 4.2.0)
#> dplyr 1.0.9 2022-04-28 [1] CRAN (R 4.2.0)
#> e1071 1.7-11 2022-06-07 [1] CRAN (R 4.2.0)
#> ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.2.0)
#> evaluate 0.15 2022-02-18 [1] CRAN (R 4.2.0)
#> fansi 1.0.3 2022-03-24 [1] CRAN (R 4.2.0)
#> fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.2.0)
#> flexpolyline 0.2.5 2021-11-19 [1] CRAN (R 4.2.0)
#> fs 1.5.2 2021-12-08 [1] CRAN (R 4.2.0)
#> generics 0.1.2 2022-01-31 [1] CRAN (R 4.2.0)
#> glue 1.6.2 2022-02-24 [1] CRAN (R 4.2.0)
#> hereR * 0.8.2.9000 2022-06-30 [1] local
#> htmltools 0.5.2 2021-08-25 [1] CRAN (R 4.2.0)
#> httpcode 0.3.0 2020-04-10 [1] CRAN (R 4.2.0)
#> jsonlite 1.8.0 2022-02-22 [1] CRAN (R 4.2.0)
#> KernSmooth 2.23-20 2021-05-03 [1] CRAN (R 4.2.0)
#> knitr 1.39 2022-04-26 [1] CRAN (R 4.2.0)
#> lifecycle 1.0.1 2021-09-24 [1] CRAN (R 4.2.0)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.2.0)
#> memoise 2.0.1 2021-11-26 [1] CRAN (R 4.2.0)
#> pillar 1.7.0 2022-02-01 [1] CRAN (R 4.2.0)
#> pkgbuild 1.3.1 2021-12-20 [1] CRAN (R 4.2.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.2.0)
#> pkgload 1.2.4 2021-11-30 [1] CRAN (R 4.2.0)
#> prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.2.0)
#> processx 3.5.3 2022-03-25 [1] CRAN (R 4.2.0)
#> proxy 0.4-27 2022-06-09 [1] CRAN (R 4.2.0)
#> ps 1.7.0 2022-04-23 [1] CRAN (R 4.2.0)
#> purrr 0.3.4 2020-04-17 [1] CRAN (R 4.2.0)
#> R6 2.5.1 2021-08-19 [1] CRAN (R 4.2.0)
#> Rcpp 1.0.8.3 2022-03-17 [1] CRAN (R 4.2.0)
#> remotes 2.4.2 2021-11-30 [1] CRAN (R 4.2.0)
#> rlang 1.0.2 2022-03-04 [1] CRAN (R 4.2.0)
#> rmarkdown 2.14 2022-04-25 [1] CRAN (R 4.2.0)
#> rprojroot 2.0.3 2022-04-02 [1] CRAN (R 4.2.0)
#> rstudioapi 0.13 2020-11-12 [1] CRAN (R 4.2.0)
#> s2 1.0.7 2021-09-28 [1] CRAN (R 4.2.0)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.2.0)
#> sf * 1.0-7 2022-03-07 [1] CRAN (R 4.2.0)
#> stringi 1.7.6 2021-11-29 [1] CRAN (R 4.2.0)
#> stringr 1.4.0 2019-02-10 [1] CRAN (R 4.2.0)
#> testthat 3.1.4 2022-04-26 [1] CRAN (R 4.2.0)
#> tibble 3.1.7 2022-05-03 [1] CRAN (R 4.2.0)
#> tidyselect 1.1.2 2022-02-21 [1] CRAN (R 4.2.0)
#> units 0.8-0 2022-02-05 [1] CRAN (R 4.2.0)
#> usethis 2.1.6 2022-05-25 [1] CRAN (R 4.2.0)
#> utf8 1.2.2 2021-07-24 [1] CRAN (R 4.2.0)
#> vctrs 0.4.1 2022-04-13 [1] CRAN (R 4.2.0)
#> withr 2.5.0 2022-03-03 [1] CRAN (R 4.2.0)
#> wk 0.6.0 2022-01-03 [1] CRAN (R 4.2.0)
#> xfun 0.31 2022-05-10 [1] CRAN (R 4.2.0)
#> yaml 2.3.5 2022-02-21 [1] CRAN (R 4.2.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/4.2/Resources/library
#>
#> ────────────────────────────────────────────────────────────────────────────── |
|
Hi, thanks for the detailed reply! I didn't realize that the isoline function maintained the order of the source points. That's really helpful. |
|
Thanks for the feedback, |
|
Nice, thanks! |
munterfi
added a commit
that referenced
this issue
Jul 24, 2022
Set `aggregate = FALSE` as default in `isoline()`, closes #153.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Description
Hello, thanks for the great package. I often use the isolines feature with an sf of many source points. I'd like to retain attributes of my source points in the output, either a meaningful id column that I can join to other data or just retaining all columns. As is, the function returns a set of isolines that have a new id number that I can't join to other datasets. I've used a lot of hacky workarounds to retain identifying columns, like looping through points one at a time instead of doing the single API call.
Is this possible to do with some option that I'm missing? If not, it would be a great feature to add.
The text was updated successfully, but these errors were encountered: