Last updated on 2017-09-23 08:48:54.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.5-4 | 60.92 | 62.70 | 123.62 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.5-4 | 65.17 | 63.07 | 128.24 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.5-4 | 316.17 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.5-4 | 325.21 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 0.5-4 | 234.00 | 510.00 | 744.00 | ERROR | |
| r-patched-linux-x86_64 | 0.5-4 | 63.75 | 123.46 | 187.21 | OK | |
| r-patched-solaris-x86 | 0.5-4 | 427.20 | NOTE | |||
| r-release-linux-x86_64 | 0.5-4 | 62.80 | 124.08 | 186.88 | OK | |
| r-release-windows-ix86+x86_64 | 0.5-4 | 252.00 | 503.00 | 755.00 | NOTE | |
| r-release-osx-x86_64 | 0.5-4 | NOTE | ||||
| r-oldrel-windows-ix86+x86_64 | 0.5-4 | 243.00 | 465.00 | 708.00 | NOTE | |
| r-oldrel-osx-x86_64 | 0.5-4 | NOTE |
Version: 0.5-4
Check: examples
Result: ERROR
Running examples in ‘sf-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: dplyr
> ### Title: Dplyr verb methods for sf objects
> ### Aliases: dplyr filter.sf dplyr arrange.sf dplyr distinct.sf dplyr
> ### group_by.sf dplyr ungroup.sf dplyr mutate.sf dplyr transmute.sf dplyr
> ### select.sf dplyr rename.sf dplyr slice.sf dplyr summarise.sf summarise
> ### dplyr gather.sf dplyr spread.sf dplyr sample_n.sf dplyr
> ### sample_frac.sf dplyr nest.sf dplyr separate.sf dplyr unite.sf dplyr
> ### inner_join.sf dplyr left_join.sf dplyr right_join.sf dplyr
> ### full_join.sf dplyr semi_join.sf dplyr anti_join.sf
>
> ### ** Examples
>
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"))
Reading layer `nc' from data source `/home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/sf/shape/nc.shp' using driver `ESRI Shapefile'
Simple feature collection with 100 features and 14 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
> nc %>% filter(AREA > .1) %>% plot()
Warning: plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
> # plot 10 smallest counties in grey:
> st_geometry(nc) %>% plot()
> nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
> title("the ten counties with smallest area")
> nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
[1] 100
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
> nc2 <- nc %>% mutate(area10 = AREA/10)
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
> nc2 <- nc %>% rename(area = AREA)
> nc %>% slice(1:2)
Simple feature collection with 2 features and 15 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -81.74107 ymin: 36.23436 xmax: -80.90344 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 2 x 16
AREA PERIMETER CNTY_ CNTY_ID NAME FIPS FIPSNO CRESS_ID BIR74 SID74
<dbl> <dbl> <dbl> <dbl> <fctr> <fctr> <dbl> <int> <dbl> <dbl>
1 0.114 1.442 1825 1825 Ashe 37009 37009 5 1091 1
2 0.061 1.231 1827 1827 Alleghany 37005 37005 3 487 0
# ... with 6 more variables: NWBIR74 <dbl>, BIR79 <dbl>, SID79 <dbl>,
# NWBIR79 <dbl>, area_cl <fctr>, geometry <simple_feature>
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
> nc %>% as.data.frame %>% summarise(mean(AREA))
mean(AREA)
1 0.12626
> library(tidyr)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.5-4
Check: tests
Result: ERROR
Running ‘aggregate.R’ [1s/1s]
Comparing ‘aggregate.Rout’ to ‘aggregate.Rout.save’ ...4c4
< Linking to GEOS 3.5.1, GDAL 2.2.1, proj.4 4.9.3
---
> Linking to GEOS 3.5.1, GDAL 2.2.0, proj.4 4.9.2
Running ‘cast.R’ [1s/1s]
Comparing ‘cast.Rout’ to ‘cast.Rout.save’ ... OK
Running ‘crs.R’ [1s/1s]
Comparing ‘crs.Rout’ to ‘crs.Rout.save’ ... OK
Running ‘dist.R’ [1s/1s]
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘dplyr.R’ [2s/2s]
Running the tests in ‘tests/dplyr.R’ failed.
Complete output:
> suppressPackageStartupMessages(library(sf))
> library(dplyr)
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
> nc %>% filter(AREA > .1) %>% plot()
Warning message:
plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
>
> # plot 10 smallest counties in grey:
> nc %>%
+ select(BIR74, geometry) %>%
+ plot()
>
> nc %>%
+ select(AREA, geometry) %>%
+ arrange(AREA) %>%
+ slice(1:10) %>%
+ plot(add = TRUE, col = 'grey', main ="")
>
> # select: check both when geometry is part of the selection, and when not:
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
>
> # group_by:
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
>
> # mutate:
> nc2 <- nc %>% mutate(area10 = AREA/10)
>
> # transmute:
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
>
> # rename:
> nc2 <- nc %>% rename(area = AREA)
>
> # distinct:
> nc[c(1:100,1:10),] %>% distinct() %>% nrow()
[1] 100
>
> # summarize:
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
>
> library(tidyr)
>
> # time-wide to long table, using tidyr::gather
> # stack the two SID columns for the July 1, 1974 - June 30, 1978 and July 1, 1979 - June 30, 1984 periods
> # (see https://cran.r-project.org/web/packages/spdep/vignettes/sids.pdf)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 0.5-4
Check: examples
Result: ERROR
Running examples in ‘sf-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: dplyr
> ### Title: Dplyr verb methods for sf objects
> ### Aliases: dplyr filter.sf dplyr arrange.sf dplyr distinct.sf dplyr
> ### group_by.sf dplyr ungroup.sf dplyr mutate.sf dplyr transmute.sf dplyr
> ### select.sf dplyr rename.sf dplyr slice.sf dplyr summarise.sf summarise
> ### dplyr gather.sf dplyr spread.sf dplyr sample_n.sf dplyr
> ### sample_frac.sf dplyr nest.sf dplyr separate.sf dplyr unite.sf dplyr
> ### inner_join.sf dplyr left_join.sf dplyr right_join.sf dplyr
> ### full_join.sf dplyr semi_join.sf dplyr anti_join.sf
>
> ### ** Examples
>
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"))
Reading layer `nc' from data source `/home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/sf/shape/nc.shp' using driver `ESRI Shapefile'
Simple feature collection with 100 features and 14 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
> nc %>% filter(AREA > .1) %>% plot()
Warning: plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
> # plot 10 smallest counties in grey:
> st_geometry(nc) %>% plot()
> nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
> title("the ten counties with smallest area")
> nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
[1] 100
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
> nc2 <- nc %>% mutate(area10 = AREA/10)
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
> nc2 <- nc %>% rename(area = AREA)
> nc %>% slice(1:2)
Simple feature collection with 2 features and 15 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -81.74107 ymin: 36.23436 xmax: -80.90344 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 2 x 16
AREA PERIMETER CNTY_ CNTY_ID NAME FIPS FIPSNO CRESS_ID BIR74 SID74
<dbl> <dbl> <dbl> <dbl> <fctr> <fctr> <dbl> <int> <dbl> <dbl>
1 0.114 1.442 1825 1825 Ashe 37009 37009 5 1091 1
2 0.061 1.231 1827 1827 Alleghany 37005 37005 3 487 0
# ... with 6 more variables: NWBIR74 <dbl>, BIR79 <dbl>, SID79 <dbl>,
# NWBIR79 <dbl>, area_cl <fctr>, geometry <simple_feature>
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
> nc %>% as.data.frame %>% summarise(mean(AREA))
mean(AREA)
1 0.12626
> library(tidyr)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.5-4
Check: installed package size
Result: NOTE
installed size is 12.5Mb
sub-directories of 1Mb or more:
doc 4.9Mb
libs 3.9Mb
sqlite 1.5Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-solaris-x86, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64
Version: 0.5-4
Check: examples
Result: ERROR
Running examples in ‘sf-Ex.R’ failed
The error most likely occurred in:
> ### Name: dplyr
> ### Title: Dplyr verb methods for sf objects
> ### Aliases: dplyr filter.sf dplyr arrange.sf dplyr distinct.sf dplyr
> ### group_by.sf dplyr ungroup.sf dplyr mutate.sf dplyr transmute.sf dplyr
> ### select.sf dplyr rename.sf dplyr slice.sf dplyr summarise.sf summarise
> ### dplyr gather.sf dplyr spread.sf dplyr sample_n.sf dplyr
> ### sample_frac.sf dplyr nest.sf dplyr separate.sf dplyr unite.sf dplyr
> ### inner_join.sf dplyr left_join.sf dplyr right_join.sf dplyr
> ### full_join.sf dplyr semi_join.sf dplyr anti_join.sf
>
> ### ** Examples
>
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"))
Reading layer `nc' from data source `/data/gannet/ripley/R/packages/tests-clang/sf.Rcheck/sf/shape/nc.shp' using driver `ESRI Shapefile'
Simple feature collection with 100 features and 14 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
> nc %>% filter(AREA > .1) %>% plot()
Warning: plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
> # plot 10 smallest counties in grey:
> st_geometry(nc) %>% plot()
> nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
> title("the ten counties with smallest area")
> nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
[1] 100
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
> nc2 <- nc %>% mutate(area10 = AREA/10)
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
> nc2 <- nc %>% rename(area = AREA)
> nc %>% slice(1:2)
Simple feature collection with 2 features and 15 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -81.74107 ymin: 36.23436 xmax: -80.90344 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 2 x 16
AREA PERIMETER CNTY_ CNTY_ID NAME FIPS FIPSNO CRESS_ID BIR74 SID74
<dbl> <dbl> <dbl> <dbl> <fctr> <fctr> <dbl> <int> <dbl> <dbl>
1 0.114 1.442 1825 1825 Ashe 37009 37009 5 1091 1
2 0.061 1.231 1827 1827 Alleghany 37005 37005 3 487 0
# ... with 6 more variables: NWBIR74 <dbl>, BIR79 <dbl>, SID79 <dbl>,
# NWBIR79 <dbl>, area_cl <fctr>, geometry <simple_feature>
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
> nc %>% as.data.frame %>% summarise(mean(AREA))
mean(AREA)
1 0.12626
> library(tidyr)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.5-4
Check: tests
Result: ERROR
Running ‘aggregate.R’
Comparing ‘aggregate.Rout’ to ‘aggregate.Rout.save’ ...4c4
< Linking to GEOS 3.6.1, GDAL 2.1.3, proj.4 4.9.3
---
> Linking to GEOS 3.5.1, GDAL 2.2.0, proj.4 4.9.2
Running ‘cast.R’
Comparing ‘cast.Rout’ to ‘cast.Rout.save’ ... OK
Running ‘crs.R’
Comparing ‘crs.Rout’ to ‘crs.Rout.save’ ...15,16c15
< GDAL Error 6: EPSG PCS/GCS code -1 not found in EPSG support files. Is this a valid
< EPSG coordinate system?
---
> GDAL Error 6: EPSG PCS/GCS code -1 not found in EPSG support files. Is this a valid EPSG coordinate system?
28,29c27
< GDAL Error 6: EPSG PCS/GCS code 999999 not found in EPSG support files. Is this a valid
< EPSG coordinate system?
---
> GDAL Error 6: EPSG PCS/GCS code 999999 not found in EPSG support files. Is this a valid EPSG coordinate system?
47c45
< [1] "+proj=sterea +lat_0=52.15616055555555 +lon_0=5.38763888888889 +k=0.9999079 +x_0=155000 +y_0=463000 +ellps=bessel +towgs84=565.4171,50.3319,465.5524,-0.398957,0.343988,-1.87740,4.0725 +units=m +no_defs"
---
> [1] "+proj=sterea +lat_0=52.15616055555555 +lon_0=5.38763888888889 +k=0.9999079 +x_0=155000 +y_0=463000 +ellps=bessel +towgs84=565.2369,50.0087,465.658,-0.406857,0.350733,-1.87035,4.0812 +units=m +no_defs"
Running ‘dist.R’
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘dplyr.R’
Running ‘empty.R’
Comparing ‘empty.Rout’ to ‘empty.Rout.save’ ... OK
Running ‘gdal_geom.R’
Comparing ‘gdal_geom.Rout’ to ‘gdal_geom.Rout.save’ ... OK
Running ‘geos.R’
Comparing ‘geos.Rout’ to ‘geos.Rout.save’ ... OK
Running ‘graticule.R’
Comparing ‘graticule.Rout’ to ‘graticule.Rout.save’ ... OK
Running ‘grid.R’
Comparing ‘grid.Rout’ to ‘grid.Rout.save’ ... OK
Running ‘plot.R’ [20s/20s]
Comparing ‘plot.Rout’ to ‘plot.Rout.save’ ... OK
Running ‘read.R’
Comparing ‘read.Rout’ to ‘read.Rout.save’ ...158c158
< Error in st_write(c("foo", "bar")) : inherits(obj, "sf") is not TRUE
---
> Error : inherits(obj, "sf") is not TRUE
160c160
< Error in guess_driver(dns) : length(dsn) == 1 is not TRUE
---
> Error : length(dsn) == 1 is not TRUE
Running ‘roundtrip.R’ [13s/13s]
Comparing ‘roundtrip.Rout’ to ‘roundtrip.Rout.save’ ... OK
Running ‘sfc.R’
Comparing ‘sfc.Rout’ to ‘sfc.Rout.save’ ...354,355c354
< Error in st_polygonize.sfc(st_sfc(x)) :
< inherits(x, "sfc_LINESTRING") || inherits(x, "sfc_MULTILINESTRING") is not TRUE
---
> Error : inherits(x, "sfc_LINESTRING") || inherits(x, "sfc_MULTILINESTRING") is not TRUE
377c376
< "3.6.1" "2.1.3" "4.9.3"
---
> "3.5.1" "2.2.0" "4.9.2"
Running ‘sfg.R’
Comparing ‘sfg.Rout’ to ‘sfg.Rout.save’ ... OK
Running ‘testthat.R’ [13s/13s]
Comparing ‘testthat.Rout’ to ‘testthat.Rout.save’ ...23c23
< Dataset /data/gannet/ripley/R/packages/tests-clang/sf.Rcheck/tests/testthat/x.gpkg already exists: remove first, use update=TRUE to append,
---
> Dataset /home/edzer/git/sf.Rcheck/tests/testthat/x.gpkg already exists: remove first, use update=TRUE to append,
29c29
< OK: 462 SKIPPED: 9 FAILED: 0
---
> OK: 540 SKIPPED: 0 FAILED: 0
Running ‘units.R’
Comparing ‘units.Rout’ to ‘units.Rout.save’ ... OK
Running ‘wkb.R’
Comparing ‘wkb.Rout’ to ‘wkb.Rout.save’ ... OK
Running the tests in ‘tests/dplyr.R’ failed.
Complete output:
> suppressPackageStartupMessages(library(sf))
> library(dplyr)
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
> nc %>% filter(AREA > .1) %>% plot()
Warning message:
plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
>
> # plot 10 smallest counties in grey:
> nc %>%
+ select(BIR74, geometry) %>%
+ plot()
>
> nc %>%
+ select(AREA, geometry) %>%
+ arrange(AREA) %>%
+ slice(1:10) %>%
+ plot(add = TRUE, col = 'grey', main ="")
>
> # select: check both when geometry is part of the selection, and when not:
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
>
> # group_by:
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
>
> # mutate:
> nc2 <- nc %>% mutate(area10 = AREA/10)
>
> # transmute:
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
>
> # rename:
> nc2 <- nc %>% rename(area = AREA)
>
> # distinct:
> nc[c(1:100,1:10),] %>% distinct() %>% nrow()
[1] 100
>
> # summarize:
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
>
> library(tidyr)
>
> # time-wide to long table, using tidyr::gather
> # stack the two SID columns for the July 1, 1974 - June 30, 1978 and July 1, 1979 - June 30, 1984 periods
> # (see https://cran.r-project.org/web/packages/spdep/vignettes/sids.pdf)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.5-4
Check: examples
Result: ERROR
Running examples in ‘sf-Ex.R’ failed
The error most likely occurred in:
> ### Name: dplyr
> ### Title: Dplyr verb methods for sf objects
> ### Aliases: dplyr filter.sf dplyr arrange.sf dplyr distinct.sf dplyr
> ### group_by.sf dplyr ungroup.sf dplyr mutate.sf dplyr transmute.sf dplyr
> ### select.sf dplyr rename.sf dplyr slice.sf dplyr summarise.sf summarise
> ### dplyr gather.sf dplyr spread.sf dplyr sample_n.sf dplyr
> ### sample_frac.sf dplyr nest.sf dplyr separate.sf dplyr unite.sf dplyr
> ### inner_join.sf dplyr left_join.sf dplyr right_join.sf dplyr
> ### full_join.sf dplyr semi_join.sf dplyr anti_join.sf
>
> ### ** Examples
>
> library(dplyr)
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"))
Reading layer `nc' from data source `/data/gannet/ripley/R/packages/tests-devel/sf.Rcheck/sf/shape/nc.shp' using driver `ESRI Shapefile'
Simple feature collection with 100 features and 14 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
> nc %>% filter(AREA > .1) %>% plot()
Warning: plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
> # plot 10 smallest counties in grey:
> st_geometry(nc) %>% plot()
> nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
> title("the ten counties with smallest area")
> nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
[1] 100
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
> nc2 <- nc %>% mutate(area10 = AREA/10)
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
> nc2 <- nc %>% rename(area = AREA)
> nc %>% slice(1:2)
Simple feature collection with 2 features and 15 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -81.74107 ymin: 36.23436 xmax: -80.90344 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 2 x 16
AREA PERIMETER CNTY_ CNTY_ID NAME FIPS FIPSNO CRESS_ID BIR74 SID74
<dbl> <dbl> <dbl> <dbl> <fctr> <fctr> <dbl> <int> <dbl> <dbl>
1 0.114 1.442 1825 1825 Ashe 37009 37009 5 1091 1
2 0.061 1.231 1827 1827 Alleghany 37005 37005 3 487 0
# ... with 6 more variables: NWBIR74 <dbl>, BIR79 <dbl>, SID79 <dbl>,
# NWBIR79 <dbl>, area_cl <fctr>, geometry <simple_feature>
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
> nc %>% as.data.frame %>% summarise(mean(AREA))
mean(AREA)
1 0.12626
> library(tidyr)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.5-4
Check: tests
Result: ERROR
Running ‘aggregate.R’
Comparing ‘aggregate.Rout’ to ‘aggregate.Rout.save’ ...4c4
< Linking to GEOS 3.6.1, GDAL 2.1.3, proj.4 4.9.3
---
> Linking to GEOS 3.5.1, GDAL 2.2.0, proj.4 4.9.2
Running ‘cast.R’
Comparing ‘cast.Rout’ to ‘cast.Rout.save’ ... OK
Running ‘crs.R’
Comparing ‘crs.Rout’ to ‘crs.Rout.save’ ...15,16c15
< GDAL Error 6: EPSG PCS/GCS code -1 not found in EPSG support files. Is this a valid
< EPSG coordinate system?
---
> GDAL Error 6: EPSG PCS/GCS code -1 not found in EPSG support files. Is this a valid EPSG coordinate system?
28,29c27
< GDAL Error 6: EPSG PCS/GCS code 999999 not found in EPSG support files. Is this a valid
< EPSG coordinate system?
---
> GDAL Error 6: EPSG PCS/GCS code 999999 not found in EPSG support files. Is this a valid EPSG coordinate system?
47c45
< [1] "+proj=sterea +lat_0=52.15616055555555 +lon_0=5.38763888888889 +k=0.9999079 +x_0=155000 +y_0=463000 +ellps=bessel +towgs84=565.4171,50.3319,465.5524,-0.398957,0.343988,-1.87740,4.0725 +units=m +no_defs"
---
> [1] "+proj=sterea +lat_0=52.15616055555555 +lon_0=5.38763888888889 +k=0.9999079 +x_0=155000 +y_0=463000 +ellps=bessel +towgs84=565.2369,50.0087,465.658,-0.406857,0.350733,-1.87035,4.0812 +units=m +no_defs"
Running ‘dist.R’
Comparing ‘dist.Rout’ to ‘dist.Rout.save’ ... OK
Running ‘dplyr.R’
Running ‘empty.R’
Comparing ‘empty.Rout’ to ‘empty.Rout.save’ ... OK
Running ‘gdal_geom.R’
Comparing ‘gdal_geom.Rout’ to ‘gdal_geom.Rout.save’ ... OK
Running ‘geos.R’ [10s/12s]
Comparing ‘geos.Rout’ to ‘geos.Rout.save’ ... OK
Running ‘graticule.R’
Comparing ‘graticule.Rout’ to ‘graticule.Rout.save’ ... OK
Running ‘grid.R’
Comparing ‘grid.Rout’ to ‘grid.Rout.save’ ... OK
Running ‘plot.R’ [21s/24s]
Comparing ‘plot.Rout’ to ‘plot.Rout.save’ ... OK
Running ‘read.R’
Comparing ‘read.Rout’ to ‘read.Rout.save’ ...158c158
< Error in st_write(c("foo", "bar")) : inherits(obj, "sf") is not TRUE
---
> Error : inherits(obj, "sf") is not TRUE
160c160
< Error in guess_driver(dns) : length(dsn) == 1 is not TRUE
---
> Error : length(dsn) == 1 is not TRUE
Running ‘roundtrip.R’ [14s/18s]
Comparing ‘roundtrip.Rout’ to ‘roundtrip.Rout.save’ ... OK
Running ‘sfc.R’
Comparing ‘sfc.Rout’ to ‘sfc.Rout.save’ ...354,355c354
< Error in st_polygonize.sfc(st_sfc(x)) :
< inherits(x, "sfc_LINESTRING") || inherits(x, "sfc_MULTILINESTRING") is not TRUE
---
> Error : inherits(x, "sfc_LINESTRING") || inherits(x, "sfc_MULTILINESTRING") is not TRUE
377c376
< "3.6.1" "2.1.3" "4.9.3"
---
> "3.5.1" "2.2.0" "4.9.2"
Running ‘sfg.R’
Comparing ‘sfg.Rout’ to ‘sfg.Rout.save’ ... OK
Running ‘testthat.R’ [14s/17s]
Comparing ‘testthat.Rout’ to ‘testthat.Rout.save’ ...23c23
< Dataset /data/gannet/ripley/R/packages/tests-devel/sf.Rcheck/tests/testthat/x.gpkg already exists: remove first, use update=TRUE to append,
---
> Dataset /home/edzer/git/sf.Rcheck/tests/testthat/x.gpkg already exists: remove first, use update=TRUE to append,
29c29
< OK: 462 SKIPPED: 9 FAILED: 0
---
> OK: 540 SKIPPED: 0 FAILED: 0
Running ‘units.R’
Comparing ‘units.Rout’ to ‘units.Rout.save’ ... OK
Running ‘wkb.R’
Comparing ‘wkb.Rout’ to ‘wkb.Rout.save’ ... OK
Running the tests in ‘tests/dplyr.R’ failed.
Complete output:
> suppressPackageStartupMessages(library(sf))
> library(dplyr)
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
> nc %>% filter(AREA > .1) %>% plot()
Warning message:
plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
>
> # plot 10 smallest counties in grey:
> nc %>%
+ select(BIR74, geometry) %>%
+ plot()
>
> nc %>%
+ select(AREA, geometry) %>%
+ arrange(AREA) %>%
+ slice(1:10) %>%
+ plot(add = TRUE, col = 'grey', main ="")
>
> # select: check both when geometry is part of the selection, and when not:
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
>
> # group_by:
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
>
> # mutate:
> nc2 <- nc %>% mutate(area10 = AREA/10)
>
> # transmute:
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
>
> # rename:
> nc2 <- nc %>% rename(area = AREA)
>
> # distinct:
> nc[c(1:100,1:10),] %>% distinct() %>% nrow()
[1] 100
>
> # summarize:
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
>
> library(tidyr)
>
> # time-wide to long table, using tidyr::gather
> # stack the two SID columns for the July 1, 1974 - June 30, 1978 and July 1, 1979 - June 30, 1984 periods
> # (see https://cran.r-project.org/web/packages/spdep/vignettes/sids.pdf)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.5-4
Check: running examples for arch ‘i386’
Result: ERROR
Running examples in 'sf-Ex.R' failed
The error most likely occurred in:
> ### Name: dplyr
> ### Title: Dplyr verb methods for sf objects
> ### Aliases: dplyr filter.sf dplyr arrange.sf dplyr distinct.sf dplyr
> ### group_by.sf dplyr ungroup.sf dplyr mutate.sf dplyr transmute.sf dplyr
> ### select.sf dplyr rename.sf dplyr slice.sf dplyr summarise.sf summarise
> ### dplyr gather.sf dplyr spread.sf dplyr sample_n.sf dplyr
> ### sample_frac.sf dplyr nest.sf dplyr separate.sf dplyr unite.sf dplyr
> ### inner_join.sf dplyr left_join.sf dplyr right_join.sf dplyr
> ### full_join.sf dplyr semi_join.sf dplyr anti_join.sf
>
> ### ** Examples
>
> library(dplyr)
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"))
Reading layer `nc' from data source `D:\temp\Rtmp6fEH3t\RLIBS_12770719753bb\sf\shape\nc.shp' using driver `ESRI Shapefile'
Simple feature collection with 100 features and 14 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
> nc %>% filter(AREA > .1) %>% plot()
Warning: plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
> # plot 10 smallest counties in grey:
> st_geometry(nc) %>% plot()
> nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
> title("the ten counties with smallest area")
> nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
[1] 100
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
> nc2 <- nc %>% mutate(area10 = AREA/10)
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
> nc2 <- nc %>% rename(area = AREA)
> nc %>% slice(1:2)
Simple feature collection with 2 features and 15 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -81.74107 ymin: 36.23436 xmax: -80.90344 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 2 x 16
AREA PERIMETER CNTY_ CNTY_ID NAME FIPS FIPSNO CRESS_ID BIR74 SID74
<dbl> <dbl> <dbl> <dbl> <fctr> <fctr> <dbl> <int> <dbl> <dbl>
1 0.114 1.442 1825 1825 Ashe 37009 37009 5 1091 1
2 0.061 1.231 1827 1827 Alleghany 37005 37005 3 487 0
# ... with 6 more variables: NWBIR74 <dbl>, BIR79 <dbl>, SID79 <dbl>,
# NWBIR79 <dbl>, area_cl <fctr>, geometry <simple_feature>
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
> nc %>% as.data.frame %>% summarise(mean(AREA))
mean(AREA)
1 0.12626
> library(tidyr)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.5-4
Check: running examples for arch ‘x64’
Result: ERROR
Running examples in 'sf-Ex.R' failed
The error most likely occurred in:
> ### Name: dplyr
> ### Title: Dplyr verb methods for sf objects
> ### Aliases: dplyr filter.sf dplyr arrange.sf dplyr distinct.sf dplyr
> ### group_by.sf dplyr ungroup.sf dplyr mutate.sf dplyr transmute.sf dplyr
> ### select.sf dplyr rename.sf dplyr slice.sf dplyr summarise.sf summarise
> ### dplyr gather.sf dplyr spread.sf dplyr sample_n.sf dplyr
> ### sample_frac.sf dplyr nest.sf dplyr separate.sf dplyr unite.sf dplyr
> ### inner_join.sf dplyr left_join.sf dplyr right_join.sf dplyr
> ### full_join.sf dplyr semi_join.sf dplyr anti_join.sf
>
> ### ** Examples
>
> library(dplyr)
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
> nc = st_read(system.file("shape/nc.shp", package="sf"))
Reading layer `nc' from data source `D:\temp\Rtmp6fEH3t\RLIBS_12770719753bb\sf\shape\nc.shp' using driver `ESRI Shapefile'
Simple feature collection with 100 features and 14 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
> nc %>% filter(AREA > .1) %>% plot()
Warning: plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
> # plot 10 smallest counties in grey:
> st_geometry(nc) %>% plot()
> nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
> title("the ten counties with smallest area")
> nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
[1] 100
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf" "grouped_df" "tbl_df" "tbl" "data.frame"
> nc2 <- nc %>% mutate(area10 = AREA/10)
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf" "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74" "SID79" "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf" "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf" "data.frame"
> nc2 <- nc %>% rename(area = AREA)
> nc %>% slice(1:2)
Simple feature collection with 2 features and 15 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -81.74107 ymin: 36.23436 xmax: -80.90344 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 2 x 16
AREA PERIMETER CNTY_ CNTY_ID NAME FIPS FIPSNO CRESS_ID BIR74 SID74
<dbl> <dbl> <dbl> <dbl> <fctr> <fctr> <dbl> <int> <dbl> <dbl>
1 0.114 1.442 1825 1825 Ashe 37009 37009 5 1091 1
2 0.061 1.231 1827 1827 Alleghany 37005 37005 3 487 0
# ... with 6 more variables: NWBIR74 <dbl>, BIR79 <dbl>, SID79 <dbl>,
# NWBIR79 <dbl>, area_cl <fctr>, geometry <simple_feature>
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
Simple feature collection with 4 features and 2 fields
geometry type: MULTIPOLYGON
dimension: XY
bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
epsg (SRID): 4267
proj4string: +proj=longlat +datum=NAD27 +no_defs
# A tibble: 4 x 3
area_cl `mean(AREA)` geometry
<fctr> <dbl> <simple_feature>
1 (0,0.1] 0.07602857 <MULTIPOLYGON...>
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
> nc %>% as.data.frame %>% summarise(mean(AREA))
mean(AREA)
1 0.12626
> library(tidyr)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.5-4
Check: running tests for arch ‘i386’
Result: ERROR
Running 'aggregate.R' [2s]
Comparing 'aggregate.Rout' to 'aggregate.Rout.save' ...4c4
< Linking to GEOS 3.6.1, GDAL 2.2.0, proj.4 4.9.3
---
> Linking to GEOS 3.5.1, GDAL 2.2.0, proj.4 4.9.2
Running 'cast.R' [2s]
Comparing 'cast.Rout' to 'cast.Rout.save' ... OK
Running 'crs.R' [1s]
Comparing 'crs.Rout' to 'crs.Rout.save' ... OK
Running 'dist.R' [2s]
Comparing 'dist.Rout' to 'dist.Rout.save' ...38,41c38,41
< [1,] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 -5.820766e-11
< [2,] 2.328306e-10 0.000000e+00 0.000000e+00 8.731149e-11 0.000000e+00
< [3,] 2.328306e-10 0.000000e+00 0.000000e+00 2.910383e-11 0.000000e+00
< [4,] 0.000000e+00 8.731149e-11 2.910383e-11 0.000000e+00 -1.455192e-11
---
> [1,] -2.328306e-10 0.000000e+00 0.000000e+00 0.000000e+00 0
> [2,] 2.328306e-10 0.000000e+00 0.000000e+00 2.910383e-11 0
> [3,] 0.000000e+00 0.000000e+00 0.000000e+00 1.455192e-11 0
> [4,] 0.000000e+00 2.910383e-11 1.455192e-11 0.000000e+00 0
50,53c50,53
< [1,] 0.000000e+00 0 0 0 0
< [2,] 0.000000e+00 0 0 0 0
< [3,] -1.776357e-15 0 0 0 0
< [4,] 0.000000e+00 0 0 0 0
---
> [1,] 0 0 0 0 0
> [2,] 0 0 0 0 0
> [3,] 0 0 0 0 0
> [4,] 0 0 0 0 0
Running 'dplyr.R' [3s]
Running 'empty.R' [1s]
Comparing 'empty.Rout' to 'empty.Rout.save' ... OK
Running 'gdal_geom.R' [2s]
Comparing 'gdal_geom.Rout' to 'gdal_geom.Rout.save' ...92c92
< GDAL has 70 drivers
---
> GDAL has 78 drivers
361a362,372
> Geometry set for 2 features
> geometry type: POLYGON
> dimension: XY
> bbox: xmin: -35.72958 ymin: 14.27042 xmax: 12.72958 ymax: 57.72958
> epsg (SRID): 4326
> proj4string: +proj=longlat +datum=WGS84 +no_defs
> POLYGON ((12.7295779513082 52, 12.721725763855 ...
> POLYGON ((-24.2704220486918 20, -24.27827423614...
> Warning message:
> In st_buffer.sfc(sfc, units::set_units(0.1, rad)) :
> st_buffer does not correctly buffer longitude/latitude data, dist needs to be in decimal degrees.
Running 'geos.R' [10s]
Comparing 'geos.Rout' to 'geos.Rout.save' ... OK
Running 'graticule.R' [5s]
Comparing 'graticule.Rout' to 'graticule.Rout.save' ... OK
Running 'grid.R' [2s]
Comparing 'grid.Rout' to 'grid.Rout.save' ... OK
Running 'plot.R' [17s]
Comparing 'plot.Rout' to 'plot.Rout.save' ... OK
Running 'read.R' [2s]
Comparing 'read.Rout' to 'read.Rout.save' ...158c158
< Error in st_write(c("foo", "bar")) : inherits(obj, "sf") is not TRUE
---
> Error : inherits(obj, "sf") is not TRUE
160c160
< Error in guess_driver(dns) : length(dsn) == 1 is not TRUE
---
> Error : length(dsn) == 1 is not TRUE
264c264
< Integer64 values larger than 9.0072e+015 lost significance after conversion to double;
---
> Integer64 values larger than 9.0072e+15 lost significance after conversion to double;
319,320d318
< Warning message:
< call dbDisconnect() when finished working with a connection
Running 'roundtrip.R' [8s]
Comparing 'roundtrip.Rout' to 'roundtrip.Rout.save' ... OK
Running 'sfc.R' [3s]
Comparing 'sfc.Rout' to 'sfc.Rout.save' ...354,355c354
< Error in st_polygonize.sfc(st_sfc(x)) :
< inherits(x, "sfc_LINESTRING") || inherits(x, "sfc_MULTILINESTRING") is not TRUE
---
> Error : inherits(x, "sfc_LINESTRING") || inherits(x, "sfc_MULTILINESTRING") is not TRUE
377c376
< "3.6.1" "2.2.0" "4.9.3"
---
> "3.5.1" "2.2.0" "4.9.2"
Running 'sfg.R' [1s]
Comparing 'sfg.Rout' to 'sfg.Rout.save' ... OK
Running 'testthat.R' [12s]
Comparing 'testthat.Rout' to 'testthat.Rout.save' ...23c23
< Dataset d:\RCompile\CRANpkg\local\3.5\sf.Rcheck\tests_i386\testthat\x.gpkg already exists: remove first, use update=TRUE to append,
---
> Dataset /home/edzer/git/sf.Rcheck/tests/testthat/x.gpkg already exists: remove first, use update=TRUE to append,
29c29
< OK: 462 SKIPPED: 9 FAILED: 0
---
> OK: 540 SKIPPED: 0 FAILED: 0
Running 'units.R' [1s]
Comparing 'units.Rout' to 'units.Rout.save' ... OK
Running 'wkb.R' [1s]
Comparing 'wkb.Rout' to 'wkb.Rout.save' ... OK
Running the tests in 'tests/dplyr.R' failed.
Last 13 lines of output:
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
>
> library(tidyr)
>
> # time-wide to long table, using tidyr::gather
> # stack the two SID columns for the July 1, 1974 - June 30, 1978 and July 1, 1979 - June 30, 1984 periods
> # (see https://cran.r-project.org/web/packages/spdep/vignettes/sids.pdf)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.5-4
Check: running tests for arch ‘x64’
Result: ERROR
Running 'aggregate.R' [1s]
Comparing 'aggregate.Rout' to 'aggregate.Rout.save' ...4c4
< Linking to GEOS 3.6.1, GDAL 2.2.0, proj.4 4.9.3
---
> Linking to GEOS 3.5.1, GDAL 2.2.0, proj.4 4.9.2
Running 'cast.R' [1s]
Comparing 'cast.Rout' to 'cast.Rout.save' ... OK
Running 'crs.R' [1s]
Comparing 'crs.Rout' to 'crs.Rout.save' ... OK
Running 'dist.R' [3s]
Comparing 'dist.Rout' to 'dist.Rout.save' ... OK
Running 'dplyr.R' [3s]
Running 'empty.R' [1s]
Comparing 'empty.Rout' to 'empty.Rout.save' ... OK
Running 'gdal_geom.R' [2s]
Comparing 'gdal_geom.Rout' to 'gdal_geom.Rout.save' ...92c92
< GDAL has 70 drivers
---
> GDAL has 78 drivers
361a362,372
> Geometry set for 2 features
> geometry type: POLYGON
> dimension: XY
> bbox: xmin: -35.72958 ymin: 14.27042 xmax: 12.72958 ymax: 57.72958
> epsg (SRID): 4326
> proj4string: +proj=longlat +datum=WGS84 +no_defs
> POLYGON ((12.7295779513082 52, 12.721725763855 ...
> POLYGON ((-24.2704220486918 20, -24.27827423614...
> Warning message:
> In st_buffer.sfc(sfc, units::set_units(0.1, rad)) :
> st_buffer does not correctly buffer longitude/latitude data, dist needs to be in decimal degrees.
Running 'geos.R' [10s]
Comparing 'geos.Rout' to 'geos.Rout.save' ... OK
Running 'graticule.R' [5s]
Comparing 'graticule.Rout' to 'graticule.Rout.save' ... OK
Running 'grid.R' [2s]
Comparing 'grid.Rout' to 'grid.Rout.save' ... OK
Running 'plot.R' [17s]
Comparing 'plot.Rout' to 'plot.Rout.save' ... OK
Running 'read.R' [3s]
Comparing 'read.Rout' to 'read.Rout.save' ...158c158
< Error in st_write(c("foo", "bar")) : inherits(obj, "sf") is not TRUE
---
> Error : inherits(obj, "sf") is not TRUE
160c160
< Error in guess_driver(dns) : length(dsn) == 1 is not TRUE
---
> Error : length(dsn) == 1 is not TRUE
264c264
< Integer64 values larger than 9.0072e+015 lost significance after conversion to double;
---
> Integer64 values larger than 9.0072e+15 lost significance after conversion to double;
Running 'roundtrip.R' [12s]
Comparing 'roundtrip.Rout' to 'roundtrip.Rout.save' ... OK
Running 'sfc.R' [3s]
Comparing 'sfc.Rout' to 'sfc.Rout.save' ...354,355c354
< Error in st_polygonize.sfc(st_sfc(x)) :
< inherits(x, "sfc_LINESTRING") || inherits(x, "sfc_MULTILINESTRING") is not TRUE
---
> Error : inherits(x, "sfc_LINESTRING") || inherits(x, "sfc_MULTILINESTRING") is not TRUE
377c376
< "3.6.1" "2.2.0" "4.9.3"
---
> "3.5.1" "2.2.0" "4.9.2"
Running 'sfg.R' [1s]
Comparing 'sfg.Rout' to 'sfg.Rout.save' ... OK
Running 'testthat.R' [14s]
Comparing 'testthat.Rout' to 'testthat.Rout.save' ...23c23
< Dataset d:\RCompile\CRANpkg\local\3.5\sf.Rcheck\tests_x64\testthat\x.gpkg already exists: remove first, use update=TRUE to append,
---
> Dataset /home/edzer/git/sf.Rcheck/tests/testthat/x.gpkg already exists: remove first, use update=TRUE to append,
29c29
< OK: 462 SKIPPED: 9 FAILED: 0
---
> OK: 540 SKIPPED: 0 FAILED: 0
Running 'units.R' [2s]
Comparing 'units.Rout' to 'units.Rout.save' ... OK
Running 'wkb.R' [2s]
Comparing 'wkb.Rout' to 'wkb.Rout.save' ... OK
Running the tests in 'tests/dplyr.R' failed.
Last 13 lines of output:
2 (0.1,0.12] 0.11206667 <MULTIPOLYGON...>
3 (0.12,0.15] 0.13422727 <MULTIPOLYGON...>
4 (0.15,0.25] 0.19039286 <MULTIPOLYGON...>
> nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
>
> library(tidyr)
>
> # time-wide to long table, using tidyr::gather
> # stack the two SID columns for the July 1, 1974 - June 30, 1978 and July 1, 1979 - June 30, 1984 periods
> # (see https://cran.r-project.org/web/packages/spdep/vignettes/sids.pdf)
> nc %>% select(SID74, SID79, geometry) %>% gather(VAR, SID, -geometry) %>% summary()
Error in melt_dataframe(data, id_idx - 1L, gather_idx - 1L, as.character(key_var), :
STRING_PTR() can only be applied to a 'character', not a 'list'
Calls: %>% ... <Anonymous> -> gather.data.frame -> melt_dataframe -> .Call
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.5-4
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘microbenchmark’
Flavor: r-patched-solaris-x86