更新R和tidyverse后出现Mapply错误 [英] Mapply error after updating R and tidyverse
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问题描述
我一直在使用几个循环来研究拒绝采样代码.更新R和 tidyverse 后，我发现该代码不再起作用，并显示以下错误:
错误:分配的数据mapply(...)必须与现有数据兼容.i列"sampled"发生错误.x无法从< integer>到< logical>由于精度下降.*位置:1.运行`rlang :: last_error()`以查看错误发生的位置.另外:警告消息:在seq.default(x，y，na.rm = TRUE)中:多余的参数"na.rm"将被忽略 该代码以前可以工作，并且与先前的问题相关，并链接到[here] [1].我试图通过使用R(3.6)和 tidyverse (1.3.0)的较旧版本来解决(避免)此问题，但是现在我需要使用一些不兼容的其他软件包.我不希望重新编写整个代码，我希望只需要进行一些调整就可以使其与新版本的R和 tidyverse 一起使用.
编辑对于为该问题提供的初始 df ，我犯了一个错误. ID ， After_1 和 After_2 列应包含字母和数字的组合，而不仅仅是数字.示例 df 已更新.
这是一个修改后的代码示例，显示的错误与我的实际代码相同:
df <- dfsourcetemp_df<-df #temp_pithouse_join 用于动态创建的样本temp_df $ sampled<-NA#将样本列空白，因此我可以针对动态检查确定NA.temp_df％>％mutate_if(is.factor，as.character)->temp_df#将字符更改为字符for(i in 1:100){#确定要运行多少次迭代row_list< -as.list(1:nrow(temp_df))q ＜-0while(length(row_list)！= 0& q< 10){q< -q + 1#确保我们不会陷入无限循环for(j在row_list中){#此循环替换检查值skip_flag< -FALSE#初始化用于检查替换采样的跳过标志for(k in 4:5){#检查地形列if(is.na(temp_df [j，k])){#print("NA break")#打印(i)休息} else if(is.na(as.integer(temp_df [j，k]))== FALSE){#如果它已经是一个整数，那么，一个包含整数的字符向量，我们已经做到了，接下来#print(下一个整数")下一个#print(下一个整数")} else if(temp_df [j，k] =="){#检查空白值#打印(下一个空字符串")temp_df [j，k]< -NA#如果找到空白值，则替换为NA#打印(将空白固定为NA")下一个}else if(is.na(filter(temp_df，ID == as.character(temp_df [j，k]))["sampled"])){跳到最后skip_flag< -TRUE#打印(跳过标志设置")} 别的 {temp_df [j，k]< -as.integer(filter(temp_df，ID == temp_df [j，k])[6])#用这些ID的采样日期替换ID#打印(成功获取检查值")} #如果别的} #k for循环如果(skip_flag==FALSE){row_list< -row_list [row_list！= j]} 别的 {下一个}#采样部分if(skip_flag == FALSE){temp_df [j，6]< -mapply(function(x，y)if(any(is.na(x)|| is.na(y)))不适用样本(seq(x，y，na.rm = TRUE)，1)，temp_df [j，开始"]，temp_df [j，结束"])temp_df [j，7]< -i#标识运行编号if(any(as.numeric(temp_df [j，4:5])> as.numeric(temp_df [j，6])，na.rm = TRUE)){#打印(j)while(any(as.numeric(temp_df [j，4:5])> as.numeric(temp_df [j，6])，na.rm = TRUE)){temp_df [j，6]< -mapply(function(x，y)if(any(is.na(x)|| is.na(y)))不适用样本(seq(x，y，na.rm = TRUE)，1)，temp_df [j，开始"]，temp_df [j，结束"])} #尽管temp_df [j，7] = i}#如果}} #j for循环围绕j循环的#while循环包装器如果(i == 1){df2< -temp_df}别的{df2<-rbind(df2,temp_df)}#别的#清空temp_df，为下一次运行做准备temp_df< -dftemp_df $ sampled<-不适用temp_df％>％mutate_if(is.factor，as.character)->temp_df} #i for循环 这是我将以 dfsource 读取的示例数据:
结构(列表(ID = c("A1"，"A2"，"A3"，"A4"，"A5"，"A6"，"A7"，"A8"，"A9"，"A10"，"A11"，"A12"，"A13"，"A14"，"A15"，"A16"，"A17"，"A18"，"A19"，"A20"，"A21"，"A22"，"A23"，"A24"，"A25"，"A26", "A27", "A28", "A29", "A30"), 开始 = c(1, 1, 1, 1, 1,50、50、50、50、50、100、100、100、100、100、200、200、300、250，350、300、300、400、500、400、400、450、500、550、500)，End = c(1000，1000、1000、1000、1000、950、950、950、950、950、1000、1000，1000、1000、900、800、900、750、650、650、600、850、700、600，600，700，550，550，600，550)，After_1 = c("A3"，"，"，"，"A3"，"，"，"，"，"，"，"A11"，"，"A11"，"，，"，，"，，"，"，"，"A21"，"，"，"，"，"，"，"，"A28")，After_2 = c("，"，"，"，"A2"，"，"，"，"，"，"，"，"，"A12"，"，"，"，"，"，"，"，"，，"，，"，，"，，"，，"，，"，)采样= c(NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA，NA))，类= c("spec_tbl_df"，"tbl_df"，"tbl"，"data.frame")，row.names = c(NA，-30L)，spec =结构(list(cols = list(ID = 结构(列表()，类 = c(collector_character"，collector"))，开始=结构(list()，类= c("collector_double"，"collector"))，结束=结构体(list()，类= c("collector_double"，"collector"))，之后_1 =结构(list()，类= c("collector_character"，"collector"))，之后_2 =结构(list()，类= c("collector_character"，"collector"))，采样=结构体(list()，类= c("collector_logical"，"collector"))))，默认=结构(list()，类= c("collector_guess"，收藏家"))，跳过= 1)，类="col_spec"))```[1]:https://stackoverflow.com/questions/58653809/sample-using-start-and-end-values-within-a-loop-in-r 解决方案
我要感谢那些提供替代方法来尝试解决此问题的人.该问题似乎是由dplyr的较旧版本引起的.出现错误时我正在使用dplyr 0.8.3，但是代码现在可以在dplyr 1.0.0上使用.
I have been working on a rejection sampling code using several loops.
After updating R and tidyverse I found that the code no longer works, displaying the following error:
Error: Assigned data `mapply(...)` must be compatible with existing data.
i Error occurred for column `sampled`.
x Can't convert from <integer> to <logical> due to loss of precision.
* Locations: 1.
Run `rlang::last_error()` to see where the error occurred.
In addition: Warning message:
In seq.default(x, y, na.rm = TRUE) :
extra argument ‘na.rm’ will be disregarded
The code worked previously, and is related to a previous question, linked [here][1].
I have tried to work through (avoid) the issue by using older versions of R (3.6) and tidyverse (1.3.0), but now I have some additional packages that I need to use which are incompatible with older versions of R. I'm not looking to rework the entire code, and I hoping that it will only take a few tweaks to get it working with the newer versions of R and tidyverse.
Edit I made a mistake regarding the initial df I provided for this question. Columns ID, After_1, and After_2 should have contained a combination of letters and numbers instead of only numbers. The example df has been updated.
Here is a modified code example that is displaying the same errors as my actual code:
df <- dfsource
temp_df<-df #temp_pithouse_join used for dynamically created samples
temp_df$sampled <- NA #blanking out the sample column so I can check against NA for the dynamic detereminatination.
temp_df %>% mutate_if(is.factor, as.character) -> temp_df #change factors to characters
for (i in 1:100){ #determines how many iterations to run
row_list<-as.list(1:nrow(temp_df))
q<-0
while(length(row_list)!=0 & q<10){
q<-q+1 #to make sure that we don't spinning off in an infinite loop
for(j in row_list){ #this loop replaces the check values
skip_flag<-FALSE #initialize skip flag used to check the replacement sampling
for(k in 4:5){ #checking the topoafter columns
if(is.na(temp_df[j,k])){
# print("NA break")
# print(i)
break
} else if(is.na(as.integer(temp_df[j,k]))==FALSE) { #if it's already an integer, well, a character vector containing an integer, we already did this, next
# print("integer next")
next
# print("integer next")
} else if(temp_df[j,k]==""){ #check for blank values
# print("empty string next")
temp_df[j,k]<-NA #if blank value found, replace with NA
# print("fixed blank to NA")
next
}
else if(is.na(filter(temp_df,ID==as.character(temp_df[j,k]))["sampled"])) { #if the replacement has not yet been generated, move on, but set flag to jump this to the end
skip_flag<-TRUE
# print("skip flag set")
} else {
temp_df[j,k]<-as.integer(filter(temp_df,ID==temp_df[j,k])[6]) #replacing IDs with the sampled dates of those IDs
# print("successful check value grab")
} #if-else
} #k for loop
if(skip_flag==FALSE){
row_list<-row_list[row_list!=j]
} else {
next
}
#sampling section
if(skip_flag==FALSE){
temp_df[j,6]<-mapply(function(x, y) if(any(is.na(x) || is.na(y))) NA else
sample(seq(x, y, na.rm = TRUE), 1), temp_df[j,"Start"], temp_df[j,"End"])
temp_df[j,7]<-i #identifying the run number
if(any(as.numeric(temp_df[j,4:5])>as.numeric(temp_df[j,6]),na.rm=TRUE)){
# print(j)
while(any(as.numeric(temp_df[j,4:5])>as.numeric(temp_df[j,6]),na.rm=TRUE)){
temp_df[j,6]<-mapply(function(x, y) if(any(is.na(x) || is.na(y))) NA else
sample(seq(x, y, na.rm = TRUE), 1), temp_df[j,"Start"], temp_df[j,"End"])
} #while
temp_df[j,7]=i
}#if
}
} #j for loop
} #while loop wrapper around j loop
if(i==1){
df2<-temp_df
}else{
df2<-rbind(df2,temp_df)
}#else
#blank out temp_df to prepare for another run
temp_df<-df
temp_df$sampled <- NA
temp_df %>% mutate_if(is.factor, as.character) -> temp_df
}#i for loop
And here is the sample data to use which I would read in as dfsource:
structure(list(ID = c("A1", "A2", "A3", "A4", "A5", "A6", "A7",
"A8", "A9", "A10", "A11", "A12", "A13", "A14", "A15", "A16",
"A17", "A18", "A19", "A20", "A21", "A22", "A23", "A24", "A25",
"A26", "A27", "A28", "A29", "A30"), Start = c(1, 1, 1, 1, 1,
50, 50, 50, 50, 50, 100, 100, 100, 100, 100, 200, 200, 300, 250,
350, 300, 300, 400, 500, 400, 400, 450, 500, 550, 500), End = c(1000,
1000, 1000, 1000, 1000, 950, 950, 950, 950, 950, 1000, 1000,
1000, 1000, 900, 800, 900, 750, 650, 650, 600, 850, 700, 600,
600, 700, 550, 550, 600, 550), After_1 = c("A3", "", "", "",
"A3", "", "", "", "", "", "", "A11", "", "A11", "", "", "", "",
"", "", "", "A21", "", "", "", "", "", "", "", "A28"), After_2 = c("",
"", "", "", "A2", "", "", "", "", "", "", "", "", "A12", "",
"", "", "", "", "", "", "", "", "", "", "", "", "", "", ""),
sampled = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA)), class = c("spec_tbl_df", "tbl_df", "tbl", "data.frame"
), row.names = c(NA, -30L), spec = structure(list(cols = list(
ID = structure(list(), class = c("collector_character", "collector"
)), Start = structure(list(), class = c("collector_double",
"collector")), End = structure(list(), class = c("collector_double",
"collector")), After_1 = structure(list(), class = c("collector_character",
"collector")), After_2 = structure(list(), class = c("collector_character",
"collector")), sampled = structure(list(), class = c("collector_logical",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), skip = 1), class = "col_spec"))```
[1]: https://stackoverflow.com/questions/58653809/sample-using-start-and-end-values-within-a-loop-in-r
解决方案
I want to thank those of you that offered alternate methods to try to deal with this problem. The issue seems to have been caused by an older version of dplyr. I was using dplyr 0.8.3 when I was getting the error, but the code is now working with dplyr 1.0.0.
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