问题描述
醒来发现一个奇怪的新问题。对于我的一个脚本，按 CTRL+S 保存被解释为 SHIFT+CTRL+S 并保存，同时还获取活动文件（即运行整个文件）。在 RStudio 中手动按下保存按钮具有相同的效果。即使在这个脚本中，这也是新行为，我没有在其他地方找到任何关于脚本中可能导致问题的信息。我已经更新了 R、RStudio 和一些没有效果的软件包。我没有收到任何错误消息，但经常使用 CTRL+S 进行保存是我工作流程中非常本能的部分 - 知道是什么把它搞砸了吗？
这是我的会话信息：
R version 4.1.0 (2021-05-18)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 11.4
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/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] rgdal_1.5-23 rJava_1.0-4 rgeos_0.5-5 dismo_1.3-3
[5] raster_3.4-13 mapdata_2.3.0 maps_3.3.0 maptools_1.1-1
[9] sp_1.4-5 ggx_0.1.1 ggridges_0.5.3 RColorBrewer_1.1-2
[13] ggsci_2.9 ggpubr_0.4.0 forcats_0.5.1 stringr_1.4.0
[17] dplyr_1.0.7 purrr_0.3.4 readr_1.4.0 tidyr_1.1.3
[21] tibble_3.1.2 ggplot2_3.3.5 tidyverse_1.3.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.6 lubridate_1.7.10 lattice_0.20-44 assertthat_0.2.1
[5] utf8_1.2.1 R6_2.5.0 cellranger_1.1.0 plyr_1.8.6
[9] backports_1.2.1 reprex_2.0.0 httr_1.4.2 pillar_1.6.1
[13] rlang_0.4.11 curl_4.3.2 readxl_1.3.1 rstudioapi_0.13
[17] data.table_1.14.0 car_3.0-11 foreign_0.8-81 munsell_0.5.0
[21] broom_0.7.8 compiler_4.1.0 modelr_0.1.8 pkgconfig_2.0.3
[25] tidyselect_1.1.1 codetools_0.2-18 rio_0.5.27 fansi_0.5.0
[29] Crayon_1.4.1 dbplyr_2.1.1 withr_2.4.2 grid_4.1.0
[33] jsonlite_1.7.2 gtable_0.3.0 lifecycle_1.0.0 DBI_1.1.1
[37] magrittr_2.0.1 scales_1.1.1 zip_2.2.0 cli_2.5.0
[41] stringi_1.6.2 carData_3.0-4 ggsignif_0.6.2 fs_1.5.0
[45] xml2_1.3.2 ellipsis_0.3.2 generics_0.1.0 vctrs_0.3.8
[49] openxlsx_4.2.4 tools_4.1.0 glue_1.4.2 hms_1.1.0
[53] abind_1.4-5 colorspace_2.0-2 rstatix_0.7.0 rvest_1.0.0
[57] haven_2.4.1
这是我的脚本。要点是我有 42 个物种的坐标数据框，对于每个物种，我只需要在每个 1 平方公里的网格单元内采样一个点。我今天添加了循环，所以我猜这可能是触发它的原因？
library(tidyverse)
library(ggplot2)
library(ggpubr)
library(ggsci)
library(RColorBrewer)
library(ggridges)
library(ggx)
library(maptools)
library(maps)
library(mapdata)
library(dismo)
library(rgeos)
library(rJava)
library(raster)
library(rgdal)
library(sp)
# read in full dataset of all distributions
data <- read.csv("final_dists_ALL_20Apr2021.csv",header = TRUE,sep = ",",na.strings = "")
data$species <- as.factor(data$species)
data$coordinateUncertaintyInMeters <- as.numeric(data$coordinateUncertaintyInMeters)
#### TEST #####
# make a test subset for costaricanum
test <- data %>% filter(species == "costaricanum" &
(coordinateUncertaintyInMeters <= 1000 | is.na(coordinateUncertaintyInMeters)))
# turn coordinates into SpatialPointsDataFrame object
coordinates(test) <- ~ decimalLongitude + decimalLatitude
# create a RasterLayer with the extent of the study area
r <- raster(test)
# set the resolution of the cells to 1 km
res(r) <- 0.00001
# expand (extend) the extent of the RasterLayer a little
r <- extend(r,extent(r) + 1)
# sample
test_sample <- gridSample(test,r,n = 1)
# attach data info to subsample coords
test <- data %>% filter(species == "costaricanum")
test_sample <- data.frame(test_sample)
sample <- left_join(test_sample,test,by = c("decimalLongitude" = "decimalLongitude","decimalLatitude" = "decimalLatitude"))
sample <- sample %>% distinct(decimalLongitude,decimalLatitude,.keep_all = TRUE)
##### LOOP #####
species_list <- levels(data$species)
for (i in 1:length(species_list)) {
test <- data %>% filter(species == species_list[i] &
(coordinateUncertaintyInMeters <= 1000 | is.na(coordinateUncertaintyInMeters)))
coordinates(test) <- ~ decimalLongitude + decimalLatitude
r <- raster(test)
res(r) <- 0.00001
r <- extend(r,extent(r) + 1)
test_sample <- gridSample(test,n = 1)
test <- data %>% filter(species == species_list[i])
test_sample <- data.frame(test_sample)
sample <- left_join(test_sample,"decimalLatitude" = "decimalLatitude"))
sample <- sample %>% distinct(decimalLongitude,.keep_all = TRUE)
write.csv(sample,paste0("1km_sub_",species_list[i],".csv"),row.names = F)
}
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
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