使用 stat_density_2d(geom = "polygon") 时没有渲染
Nothing rendering when using stat_density_2d(geom = "polygon")
出于某种原因，在指定 geom = "polygon" 时，stat_density_2d() 似乎不适合我，我完全被难住了。这是我的代码...
library(sf)
library(tidyverse)
library(RANN2)
library(hexbin)
library(mapproj)
options(stringsAsFactors = FALSE)
raleigh_police <- rgdal::readOGR("https://opendata.arcgis.com/datasets/24c0b37fa9bb4e16ba8bcaa7e806c615_0.geojson", "OGRGeoJSON")
raleigh_police_sf <- raleigh_police %>%
st_as_sf()
raleigh_police_sf %>%
filter(crime_description == "Burglary/Residential") %>%
st_coordinates() %>%
as_tibble() %>%
ggplot() +
stat_density_2d(aes(X, Y, fill = stat(level)), geom = "polygon")
这是我的 sessionInfo()...
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS 10.14.1
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] bindrcpp_0.2.2 mapproj_1.2.6 maps_3.3.0 hexbin_1.27.2 RANN2_0.1 forcats_0.3.0 stringr_1.3.1 dplyr_0.7.8
[9] purrr_0.2.5 readr_1.1.1 tidyr_0.8.2 tibble_1.4.2 ggplot2_3.1.0 tidyverse_1.2.1 sf_0.7-1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.0 lubridate_1.7.4 lattice_0.20-38 class_7.3-14 utf8_1.1.4 assertthat_0.2.0 rprojroot_1.3-2
[8] digest_0.6.18 R6_2.3.0 cellranger_1.1.0 plyr_1.8.4 backports_1.1.2 evaluate_0.12 e1071_1.7-0
[15] httr_1.3.1 blogdown_0.9 pillar_1.3.0 rlang_0.3.0.1 lazyeval_0.2.1 readxl_1.1.0 rstudioapi_0.8
[22] rmarkdown_1.10 labeling_0.3 rgdal_1.3-6 munsell_0.5.0 broom_0.5.0 compiler_3.5.1 modelr_0.1.2
[29] xfun_0.4 pkgconfig_2.0.2 htmltools_0.3.6 tidyselect_0.2.5 bookdown_0.7 codetools_0.2-15 fansi_0.4.0
[36] crayon_1.3.4 withr_2.1.2 MASS_7.3-51.1 grid_3.5.1 nlme_3.1-137 spData_0.2.9.4 jsonlite_1.5
[43] gtable_0.2.0 DBI_1.0.0 magrittr_1.5 units_0.6-1 scales_1.0.0 cli_1.0.1 stringi_1.2.4
[50] sp_1.3-1 xml2_1.2.0 tools_3.5.1 glue_1.3.0 hms_0.4.2 yaml_2.2.0 colorspace_1.3-2
[57] classInt_0.2-3 rvest_0.3.2 knitr_1.20 bindr_0.1.1 haven_1.1.2
我只是得到一个空白图，上面什么也没有。完全难住了。我在这里做错了什么？
更新 (2018-11-18)
原来这里的主要问题是options(stringsAsFactors = FALSE)。如果您将其注释掉并 运行 原始代码，实际上一切正常。我发现这个 GitHub Issue 这就是我尝试这样做的原因。这个问题的答案中提供了更有效的代码解决方案，他们还确保不使用 options(stringsAsFactors = FALSE).
如前所述，这只是点级数据，他们提供的 CSV 可以很好地替代：
library(tidyverse)
rp_csv_url <- "https://opendata.arcgis.com/datasets/24c0b37fa9bb4e16ba8bcaa7e806c615_0.csv"
httr::GET(
url = rp_csv_url,
httr::write_disk(basename(rp_csv_url)), # won't overwrite if it exists unless explicitly told to so you get caching for free
httr::progress() # I suspect this is a big file so it's nice to see a progress bar
)
raleigh_police <- read_csv(basename(rp_csv_url))
mutate(
raleigh_police,
longitude = as.numeric(longitude), # they come in wonky, still
latitude = as.numeric(latitude) # they come in wonky, still
) -> raleigh_police
raleigh_police %>%
filter(crime_description == "Burglary/Residential") %>%
ggplot() +
stat_density_2d(
aes(longitude, latitude, fill = stat(level)),
color = "#2b2b2b", size=0.125, geom = "polygon"
) +
viridis::scale_fill_viridis(direction=-1, option="magma") +
hrbrthemes::theme_ipsum_rc()
如果您想将 level 变成更有意义的东西：
h <- c(MASS::bandwidth.nrd(rp_br$longitude),
MASS::bandwidth.nrd(rp_br$latitude))
dens <- MASS::kde2d(
rp_br$longitude, rp_br$latitude, h = h, n = 100
)
breaks <- pretty(range(dens$z), 10)
zdf <- data.frame(expand.grid(x = dens$x, y = dens$y), z = as.vector(dens$z))
z <- tapply(zdf$z, zdf[c("x", "y")], identity)
cl <- grDevices::contourLines(
x = sort(unique(dens$x)), y = sort(unique(dens$y)), z = dens$z,
levels = breaks
)
sp::SpatialPolygons(
lapply(1:length(cl), function(idx) {
sp::Polygons(
srl = list(sp::Polygon(
matrix(c(cl[[idx]]$x, cl[[idx]]$y), nrow=length(cl[[idx]]$x), byrow=FALSE)
)),
ID = idx
)
})
) -> cont
sp::coordinates(rp_br) <- ~longitude+latitude
然后：
data_frame(
ct = sapply(sp::over(cont, sp::geometry(rp_br), returnList = TRUE), length),
id = 1:length(ct),
lvl = sapply(cl, function(x) x$level)
) %>%
count(lvl, wt=ct) %>%
mutate(
pct = n/nrow(rp_br),
pct_lab = sprintf("%s of the points fall within this level", scales::percent(pct))
)
## # A tibble: 10 x 4
## lvl n pct pct_lab
## <dbl> <int> <dbl> <chr>
## 1 10. 7302 0.927 92.7% of the points fall within this level
## 2 20. 6243 0.792 79.2% of the points fall within this level
## 3 30. 4786 0.607 60.7% of the points fall within this level
## 4 40. 3204 0.407 40.7% of the points fall within this level
## 5 50. 1945 0.247 24.7% of the points fall within this level
## 6 60. 1277 0.162 16.2% of the points fall within this level
## 7 70. 793 0.101 10.1% of the points fall within this level
## 8 80. 474 0.0601 6.0% of the points fall within this level
## 9 90. 279 0.0354 3.5% of the points fall within this level
## 10 100. 44 0.00558 0.6% of the points fall within this level
除了在阅读和将 readOGR 更改为 read_sf 之前下载文件外，它对我来说按原样工作，保存由空几何引起的几个 NA 点的警告：
library(tidyverse)
library(sf)
#> Linking to GEOS 3.6.1, GDAL 2.1.3, PROJ 4.9.3
path <- "~/Downloads/raleigh.geojson"
download.file(
"https://opendata.arcgis.com/datasets/24c0b37fa9bb4e16ba8bcaa7e806c615_0.geojson",
path,
method = "curl"
)
raleigh_police <- sf::read_sf(path, "OGRGeoJSON")
raleigh_police %>%
filter(crime_description == "Burglary/Residential") %>%
st_coordinates() %>%
as_tibble() %>%
ggplot() +
stat_density_2d(aes(X, Y, fill = stat(level)), geom = "polygon")
#> Warning: Removed 5 rows containing non-finite values (stat_density2d).
空行：
raleigh_police %>%
filter(crime_description == "Burglary/Residential",
st_is_empty(.))
#> Simple feature collection with 5 features and 21 fields (with 5 geometries empty)
#> geometry type: POINT
#> dimension: XY
#> bbox: xmin: NA ymin: NA xmax: NA ymax: NA
#> epsg (SRID): 4326
#> proj4string: +proj=longlat +datum=WGS84 +no_defs
#> # A tibble: 5 x 22
#> OBJECTID GlobalID case_number crime_category crime_code crime_descripti…
#> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 205318 8057315… P14076062 BURGLARY/RESI… 30B Burglary/Reside…
#> 2 417488 70afb27… P15027702 BURGLARY/RESI… 30B Burglary/Reside…
#> 3 424718 bdf69fa… P18029113 BURGLARY/RESI… 30B Burglary/Reside…
#> 4 436550 711c05b… P18044139 BURGLARY/RESI… 30B Burglary/Reside…
#> 5 442091 9d7a008… P18051764 BURGLARY/RESI… 30B Burglary/Reside…
#> # … with 16 more variables: crime_type <chr>, reported_block_address <chr>,
#> # city_of_incident <chr>, city <chr>, district <chr>, reported_date <dttm>,
#> # reported_year <int>, reported_month <int>, reported_day <int>,
#> # reported_hour <int>, reported_dayofwk <chr>, latitude <dbl>,
#> # longitude <dbl>, agency <chr>, updated_date <dttm>, geometry <POINT [°]>
sessionInfo()
#> R version 3.5.1 (2018-07-02)
#> Platform: x86_64-apple-darwin15.6.0 (64-bit)
#> Running under: macOS 10.14.1
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] sf_0.7-1 forcats_0.3.0 stringr_1.3.1
#> [4] dplyr_0.7.99.9000 purrr_0.2.5 readr_1.2.0
#> [7] tidyr_0.8.2 tibble_1.4.99.9005 ggplot2_3.1.0
#> [10] tidyverse_1.2.1
#>
#> loaded via a namespace (and not attached):
#> [1] tidyselect_0.2.5 haven_1.1.2 lattice_0.20-35
#> [4] colorspace_1.3-2 htmltools_0.3.6 yaml_2.2.0
#> [7] rlang_0.3.0.1 e1071_1.7-0 pillar_1.3.0.9001
#> [10] glue_1.3.0 withr_2.1.2 DBI_1.0.0
#> [13] modelr_0.1.2 readxl_1.1.0 plyr_1.8.4
#> [16] munsell_0.5.0 gtable_0.2.0 cellranger_1.1.0
#> [19] rvest_0.3.2 evaluate_0.12 labeling_0.3
#> [22] knitr_1.20 class_7.3-14 broom_0.5.0
#> [25] Rcpp_0.12.19.3 scales_1.0.0 backports_1.1.2
#> [28] classInt_0.2-3 jsonlite_1.5 hms_0.4.2.9001
#> [31] digest_0.6.18 stringi_1.2.4 grid_3.5.1
#> [34] rprojroot_1.3-2 cli_1.0.1 tools_3.5.1
#> [37] magrittr_1.5 lazyeval_0.2.1 crayon_1.3.4
#> [40] pkgconfig_2.0.2 MASS_7.3-51 xml2_1.2.0
#> [43] spData_0.2.9.4 lubridate_1.7.4 assertthat_0.2.0
#> [46] rmarkdown_1.10 httr_1.3.1 R6_2.3.0
#> [49] units_0.6-1 nlme_3.1-137 compiler_3.5.1
出于某种原因，在指定 geom = "polygon" 时，stat_density_2d() 似乎不适合我，我完全被难住了。这是我的代码...
library(sf)
library(tidyverse)
library(RANN2)
library(hexbin)
library(mapproj)
options(stringsAsFactors = FALSE)
raleigh_police <- rgdal::readOGR("https://opendata.arcgis.com/datasets/24c0b37fa9bb4e16ba8bcaa7e806c615_0.geojson", "OGRGeoJSON")
raleigh_police_sf <- raleigh_police %>%
st_as_sf()
raleigh_police_sf %>%
filter(crime_description == "Burglary/Residential") %>%
st_coordinates() %>%
as_tibble() %>%
ggplot() +
stat_density_2d(aes(X, Y, fill = stat(level)), geom = "polygon")
这是我的 sessionInfo()...
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS 10.14.1
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] bindrcpp_0.2.2 mapproj_1.2.6 maps_3.3.0 hexbin_1.27.2 RANN2_0.1 forcats_0.3.0 stringr_1.3.1 dplyr_0.7.8
[9] purrr_0.2.5 readr_1.1.1 tidyr_0.8.2 tibble_1.4.2 ggplot2_3.1.0 tidyverse_1.2.1 sf_0.7-1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.0 lubridate_1.7.4 lattice_0.20-38 class_7.3-14 utf8_1.1.4 assertthat_0.2.0 rprojroot_1.3-2
[8] digest_0.6.18 R6_2.3.0 cellranger_1.1.0 plyr_1.8.4 backports_1.1.2 evaluate_0.12 e1071_1.7-0
[15] httr_1.3.1 blogdown_0.9 pillar_1.3.0 rlang_0.3.0.1 lazyeval_0.2.1 readxl_1.1.0 rstudioapi_0.8
[22] rmarkdown_1.10 labeling_0.3 rgdal_1.3-6 munsell_0.5.0 broom_0.5.0 compiler_3.5.1 modelr_0.1.2
[29] xfun_0.4 pkgconfig_2.0.2 htmltools_0.3.6 tidyselect_0.2.5 bookdown_0.7 codetools_0.2-15 fansi_0.4.0
[36] crayon_1.3.4 withr_2.1.2 MASS_7.3-51.1 grid_3.5.1 nlme_3.1-137 spData_0.2.9.4 jsonlite_1.5
[43] gtable_0.2.0 DBI_1.0.0 magrittr_1.5 units_0.6-1 scales_1.0.0 cli_1.0.1 stringi_1.2.4
[50] sp_1.3-1 xml2_1.2.0 tools_3.5.1 glue_1.3.0 hms_0.4.2 yaml_2.2.0 colorspace_1.3-2
[57] classInt_0.2-3 rvest_0.3.2 knitr_1.20 bindr_0.1.1 haven_1.1.2
我只是得到一个空白图，上面什么也没有。完全难住了。我在这里做错了什么？
更新 (2018-11-18)
原来这里的主要问题是options(stringsAsFactors = FALSE)。如果您将其注释掉并 运行 原始代码，实际上一切正常。我发现这个 GitHub Issue 这就是我尝试这样做的原因。这个问题的答案中提供了更有效的代码解决方案，他们还确保不使用 options(stringsAsFactors = FALSE).
如前所述，这只是点级数据，他们提供的 CSV 可以很好地替代：
library(tidyverse)
rp_csv_url <- "https://opendata.arcgis.com/datasets/24c0b37fa9bb4e16ba8bcaa7e806c615_0.csv"
httr::GET(
url = rp_csv_url,
httr::write_disk(basename(rp_csv_url)), # won't overwrite if it exists unless explicitly told to so you get caching for free
httr::progress() # I suspect this is a big file so it's nice to see a progress bar
)
raleigh_police <- read_csv(basename(rp_csv_url))
mutate(
raleigh_police,
longitude = as.numeric(longitude), # they come in wonky, still
latitude = as.numeric(latitude) # they come in wonky, still
) -> raleigh_police
raleigh_police %>%
filter(crime_description == "Burglary/Residential") %>%
ggplot() +
stat_density_2d(
aes(longitude, latitude, fill = stat(level)),
color = "#2b2b2b", size=0.125, geom = "polygon"
) +
viridis::scale_fill_viridis(direction=-1, option="magma") +
hrbrthemes::theme_ipsum_rc()
如果您想将 level 变成更有意义的东西：
h <- c(MASS::bandwidth.nrd(rp_br$longitude),
MASS::bandwidth.nrd(rp_br$latitude))
dens <- MASS::kde2d(
rp_br$longitude, rp_br$latitude, h = h, n = 100
)
breaks <- pretty(range(dens$z), 10)
zdf <- data.frame(expand.grid(x = dens$x, y = dens$y), z = as.vector(dens$z))
z <- tapply(zdf$z, zdf[c("x", "y")], identity)
cl <- grDevices::contourLines(
x = sort(unique(dens$x)), y = sort(unique(dens$y)), z = dens$z,
levels = breaks
)
sp::SpatialPolygons(
lapply(1:length(cl), function(idx) {
sp::Polygons(
srl = list(sp::Polygon(
matrix(c(cl[[idx]]$x, cl[[idx]]$y), nrow=length(cl[[idx]]$x), byrow=FALSE)
)),
ID = idx
)
})
) -> cont
sp::coordinates(rp_br) <- ~longitude+latitude
然后：
data_frame(
ct = sapply(sp::over(cont, sp::geometry(rp_br), returnList = TRUE), length),
id = 1:length(ct),
lvl = sapply(cl, function(x) x$level)
) %>%
count(lvl, wt=ct) %>%
mutate(
pct = n/nrow(rp_br),
pct_lab = sprintf("%s of the points fall within this level", scales::percent(pct))
)
## # A tibble: 10 x 4
## lvl n pct pct_lab
## <dbl> <int> <dbl> <chr>
## 1 10. 7302 0.927 92.7% of the points fall within this level
## 2 20. 6243 0.792 79.2% of the points fall within this level
## 3 30. 4786 0.607 60.7% of the points fall within this level
## 4 40. 3204 0.407 40.7% of the points fall within this level
## 5 50. 1945 0.247 24.7% of the points fall within this level
## 6 60. 1277 0.162 16.2% of the points fall within this level
## 7 70. 793 0.101 10.1% of the points fall within this level
## 8 80. 474 0.0601 6.0% of the points fall within this level
## 9 90. 279 0.0354 3.5% of the points fall within this level
## 10 100. 44 0.00558 0.6% of the points fall within this level
除了在阅读和将 readOGR 更改为 read_sf 之前下载文件外，它对我来说按原样工作，保存由空几何引起的几个 NA 点的警告：
library(tidyverse)
library(sf)
#> Linking to GEOS 3.6.1, GDAL 2.1.3, PROJ 4.9.3
path <- "~/Downloads/raleigh.geojson"
download.file(
"https://opendata.arcgis.com/datasets/24c0b37fa9bb4e16ba8bcaa7e806c615_0.geojson",
path,
method = "curl"
)
raleigh_police <- sf::read_sf(path, "OGRGeoJSON")
raleigh_police %>%
filter(crime_description == "Burglary/Residential") %>%
st_coordinates() %>%
as_tibble() %>%
ggplot() +
stat_density_2d(aes(X, Y, fill = stat(level)), geom = "polygon")
#> Warning: Removed 5 rows containing non-finite values (stat_density2d).
空行：
raleigh_police %>%
filter(crime_description == "Burglary/Residential",
st_is_empty(.))
#> Simple feature collection with 5 features and 21 fields (with 5 geometries empty)
#> geometry type: POINT
#> dimension: XY
#> bbox: xmin: NA ymin: NA xmax: NA ymax: NA
#> epsg (SRID): 4326
#> proj4string: +proj=longlat +datum=WGS84 +no_defs
#> # A tibble: 5 x 22
#> OBJECTID GlobalID case_number crime_category crime_code crime_descripti…
#> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 205318 8057315… P14076062 BURGLARY/RESI… 30B Burglary/Reside…
#> 2 417488 70afb27… P15027702 BURGLARY/RESI… 30B Burglary/Reside…
#> 3 424718 bdf69fa… P18029113 BURGLARY/RESI… 30B Burglary/Reside…
#> 4 436550 711c05b… P18044139 BURGLARY/RESI… 30B Burglary/Reside…
#> 5 442091 9d7a008… P18051764 BURGLARY/RESI… 30B Burglary/Reside…
#> # … with 16 more variables: crime_type <chr>, reported_block_address <chr>,
#> # city_of_incident <chr>, city <chr>, district <chr>, reported_date <dttm>,
#> # reported_year <int>, reported_month <int>, reported_day <int>,
#> # reported_hour <int>, reported_dayofwk <chr>, latitude <dbl>,
#> # longitude <dbl>, agency <chr>, updated_date <dttm>, geometry <POINT [°]>
sessionInfo()
#> R version 3.5.1 (2018-07-02)
#> Platform: x86_64-apple-darwin15.6.0 (64-bit)
#> Running under: macOS 10.14.1
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] sf_0.7-1 forcats_0.3.0 stringr_1.3.1
#> [4] dplyr_0.7.99.9000 purrr_0.2.5 readr_1.2.0
#> [7] tidyr_0.8.2 tibble_1.4.99.9005 ggplot2_3.1.0
#> [10] tidyverse_1.2.1
#>
#> loaded via a namespace (and not attached):
#> [1] tidyselect_0.2.5 haven_1.1.2 lattice_0.20-35
#> [4] colorspace_1.3-2 htmltools_0.3.6 yaml_2.2.0
#> [7] rlang_0.3.0.1 e1071_1.7-0 pillar_1.3.0.9001
#> [10] glue_1.3.0 withr_2.1.2 DBI_1.0.0
#> [13] modelr_0.1.2 readxl_1.1.0 plyr_1.8.4
#> [16] munsell_0.5.0 gtable_0.2.0 cellranger_1.1.0
#> [19] rvest_0.3.2 evaluate_0.12 labeling_0.3
#> [22] knitr_1.20 class_7.3-14 broom_0.5.0
#> [25] Rcpp_0.12.19.3 scales_1.0.0 backports_1.1.2
#> [28] classInt_0.2-3 jsonlite_1.5 hms_0.4.2.9001
#> [31] digest_0.6.18 stringi_1.2.4 grid_3.5.1
#> [34] rprojroot_1.3-2 cli_1.0.1 tools_3.5.1
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