$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

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英文:

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

问题

我试图运行一个特定的R包，MetaLonDA，它可以分析纵向、相对丰度的微生物组数据。该包包括两个命令：1. metalonda() 用于测试一个特征，2. metalondaAll 用于测试所有特征。我无法运行第一个命令 metalonda()，因为我一直得到这个错误：$运算符对于原子向量无效。这个错误很奇怪，因为我的所有向量都是数值型的。以下是我的代码和数据。

Github页面：https://github.com/aametwally/MetaLonDA

从CRAN安装：

install.packages("MetaLonDA")
library(MetaLonDA)

从github安装：

library(devtools)
install_github("aametwally/MetaLonDA", ref = "master")
library(MetaLonDA)

创建向量：

otu <- structure(c(2547, 0, 600, 3, 17, 0, 372, 202, 0, 339, 10491,
0, 1417, 2083, 0, 325, 4521, 0, 12366, 6, 5891, 0, 0, 0, 643,
399, 0, 301, 343, 0, 1194, 9, 15835, 0, 56, 0, 20554, 0, 11336,
2, 0, 0, 538, 1104, 0, 2736, 3430, 0, 1347, 1249, 0, 977, 6455,
0, 80, 39, 0, 429, 341, 0, 156, 70, 0, 382, 186, 0, 1751, 925,
0, 0, 7634, 0, 561, 99, 0, 1067, 655, 0, 160, 654, 0, 0, 2009,
0, 139, 0, 5433, 0, 0, 0, 169, 85, 0, 406, 206, 0, 374, 236,
4, 459, 718, 51, 123, 81, 0, 623, 1992, 0, 0, 0, 344, 0, 40,
0, 304, 88, 0, 284, 1372, 0, 79, 96, 0, 130, 403, 0, 144, 61,
0, 357, 731, 40, 95, 504, 0, 2912, 9435, 0, 323, 15, 0, 485,
340, 0, 254, 100, 4, 863, 2210, 0, 32, 21, 0, 219, 443, 0, 1925,
103, 0, 327, 1420, 0, 457, 23, 0, 95, 370, 0, 68, 399, 0, 159,
932, 0, 82, 13, 0, 105, 225, 0, 244, 46, 0, 153, 786, 0, 3105,
1114, 0, 0, 1011, 0, 276, 364, 0, 604, 2936, 0, 417, 154, 0,
224, 710, 0, 55, 26, 0, 198, 254, 0, 92, 8, 0, 236, 37, 0, 243,
123, 0, 195, 161, 0, 115, 123, 0, 869, 577, 0, 1272, 730, 0,
520, 844, 0, 50, 368, 8, 5, 902, 0, 602, 52, 0, 828, 2176, 0,
338, 143, 3, 416, 1341, 31, 1032, 12727, 25637, 0, 5566, 0, 41,
11, 0, 309, 205, 0, 70, 4, 0, 359, 198, 0, 154, 60, 0, 51, 1221,
0, 3, 4, 0, 77, 85, 0, 65, 152, 0, 257, 917, 0, 136, 60, 0, 78,
746, 0), .Dim = c(6L, 49L), .Dimnames = list(c("taxa 1", "taxa 2",
"taxa 3", "taxa 4", "taxa 5", "taxa 6"), c("LID_100039", "LID_100080",
"LID_100105", "LID_100125", "LID_100194", "LID_100225", "LID_100229",
"LID_100551", "LID_101556", "LID_101558", "LID_101560", "LID_101562",
"LID_101564", "LID_101566", "LID_101569", "LID_101570", "LID_101571",
"LID_101573", "LID_101575", "LID_101577", "LID_101581", "LID_101584",
"LID_101587", "LID_101590", "LID_101591", "LID_101592", "LID_101593",
"LID_101594", "LID_101596", "LID_101597", "LID_101601", "LID_101602",
"LID_101604", "LID_101606", "LID_101608", "LID_101610", "LID_101612",
"LID_101613", "LID_101616", "LID_101617", "LID_101618", "LID_101619",
"LID_101620", "LID_101621", "LID_101622", "LID_101623", "LID_101624",
"LID_101630", "LID_101632")))

Group <- structure(c(2L, 1

<details>
<summary>英文:</summary>

I am trying to run a specific R package, MetaLonDA, that can analyze longitudinal, relative abundance, microbiome data. The package consists of two commands: 1. metalonda() can be used to test one feature and 2. metalondaAll that can be used to test all features. I cannot get the first command, metalonda() to run because I keep producing this error: $ operator is invalid for atomic vectors. This error is strange because all of my vectors are numeric. Below is my code and data.

Github page: https://github.com/aametwally/MetaLonDA

Install from CRAN:

install.packages(&quot;MetaLonDA&quot;)
library(MetaLonDA)


Install from github:

library(devtools)
install_github(&quot;aametwally/MetaLonDA&quot;, ref = &quot;master&quot;)
library(MetaLonDA)


Make vectors:

otu <- structure(c(2547, 0, 600, 3, 17, 0, 372, 202, 0, 339, 10491,
0, 1417, 2083, 0, 325, 4521, 0, 12366, 6, 5891, 0, 0, 0, 643,
399, 0, 301, 343, 0, 1194, 9, 15835, 0, 56, 0, 20554, 0, 11336,
2, 0, 0, 538, 1104, 0, 2736, 3430, 0, 1347, 1249, 0, 977, 6455,
0, 80, 39, 0, 429, 341, 0, 156, 70, 0, 382, 186, 0, 1751, 925,
0, 0, 7634, 0, 561, 99, 0, 1067, 655, 0, 160, 654, 0, 0, 2009,
0, 139, 0, 5433, 0, 0, 0, 169, 85, 0, 406, 206, 0, 374, 236,
4, 459, 718, 51, 123, 81, 0, 623, 1992, 0, 0, 0, 344, 0, 40,
0, 304, 88, 0, 284, 1372, 0, 79, 96, 0, 130, 403, 0, 144, 61,
0, 357, 731, 40, 95, 504, 0, 2912, 9435, 0, 323, 15, 0, 485,
340, 0, 254, 100, 4, 863, 2210, 0, 32, 21, 0, 219, 443, 0, 1925,
103, 0, 327, 1420, 0, 457, 23, 0, 95, 370, 0, 68, 399, 0, 159,
932, 0, 82, 13, 0, 105, 225, 0, 244, 46, 0, 153, 786, 0, 3105,
1114, 0, 0, 1011, 0, 276, 364, 0, 604, 2936, 0, 417, 154, 0,
224, 710, 0, 55, 26, 0, 198, 254, 0, 92, 8, 0, 236, 37, 0, 243,
123, 0, 195, 161, 0, 115, 123, 0, 869, 577, 0, 1272, 730, 0,
520, 844, 0, 50, 368, 8, 5, 902, 0, 602, 52, 0, 828, 2176, 0,
338, 143, 3, 416, 1341, 31, 1032, 12727, 25637, 0, 5566, 0, 41,
11, 0, 309, 205, 0, 70, 4, 0, 359, 198, 0, 154, 60, 0, 51, 1221,
0, 3, 4, 0, 77, 85, 0, 65, 152, 0, 257, 917, 0, 136, 60, 0, 78,
746, 0), .Dim = c(6L, 49L), .Dimnames = list(c("taxa 1", "taxa 2",
"taxa 3", "taxa 4", "taxa 5", "taxa 6"), c("LID_100039", "LID_100080",
"LID_100105", "LID_100125", "LID_100194", "LID_100225", "LID_100229",
"LID_100551", "LID_101556", "LID_101558", "LID_101560", "LID_101562",
"LID_101564", "LID_101566", "LID_101569", "LID_101570", "LID_101571",
"LID_101573", "LID_101575", "LID_101577", "LID_101581", "LID_101584",
"LID_101587", "LID_101590", "LID_101591", "LID_101592", "LID_101593",
"LID_101594", "LID_101596", "LID_101597", "LID_101601", "LID_101602",
"LID_101604", "LID_101606", "LID_101608", "LID_101610", "LID_101612",
"LID_101613", "LID_101616", "LID_101617", "LID_101618", "LID_101619",
"LID_101620", "LID_101621", "LID_101622", "LID_101623", "LID_101624",
"LID_101630", "LID_101632")))

Group <- structure(c(2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L,
1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L), .Label = c("Female", "Male"))

Individual <- structure(c(64L, 34L, 5L, 23L, 53L, 4L, 47L, 80L, 71L, 43L, 1L,
87L, 48L, 45L, 55L, 18L, 11L, 47L, 75L, 44L, 47L, 10L, 86L, 44L,
28L, 61L, 21L, 73L, 70L, 86L, 45L, 1L, 43L, 47L, 48L, 11L, 16L,
60L, 58L, 40L, 30L, 31L, 50L, 17L, 5L, 86L, 76L, 60L, 69L), .Label = c("F100",
"F101", "F102", "F103", "F104", "F105", "F106", "F107", "F108",
"F109", "F110", "F111", "F112", "F113", "F114", "F115", "F116",
"F117", "F118", "F119", "F120", "F121", "F122", "F123", "F124",
"F125", "F126", "F127", "F128", "F129", "F130", "F131", "F132",
"F32", "F74", "F84", "F85", "F86", "F87", "F88", "F89", "F90",
"F91", "F92", "F93", "F94", "F95", "F96", "F97", "F98", "F99",
"M49", "M50", "M51", "M52", "M53", "M54", "M55", "M56", "M57",
"M58", "M59", "M60", "M61", "M62", "M63", "M64", "M65", "M66",
"M67", "M68", "M69", "M70", "M71", "M72", "M73", "M74", "M75",
"M76", "M77", "M78", "M79", "M80", "M81", "M82", "M83", "M84",
"M85", "M86"))

Time <- structure(c(13L, 5L, 2L, 6L, 4L, 1L, 12L, 3L, 44L, 45L, 44L,
43L, 42L, 42L, 40L, 41L, 39L, 38L, 36L, 37L, 34L, 35L, 33L, 32L,
8L, 9L, 7L, 7L, 26L, 27L, 23L, 22L, 24L, 21L, 28L, 29L, 25L,
19L, 20L, 14L, 15L, 16L, 17L, 18L, 18L, 11L, 10L, 30L, 31L), .Label = c("2015-02-20",
"2015-04-01", "2015-04-03", "2015-05-13", "2015-05-14", "2015-05-18",
"2015-11-25", "2016-01-09", "2016-01-12", "2016-02-02", "2016-02-13",
"2016-02-22", "2016-04-06", "2016-04-15", "2016-04-18", "2016-05-19",
"2016-05-23", "2016-07-02", "2017-06-02", "2017-06-06", "2017-06-16",
"2017-06-23", "2017-06-29", "2017-08-03", "2017-08-12", "2017-08-15",
"2017-08-21", "2017-10-03", "2017-10-06", "2017-12-02", "2017-12-21",
"2018-02-16", "2018-03-02", "2018-05-01", "2018-05-02", "2018-05-24",
"2018-06-01", "2018-06-02", "2018-06-05", "2018-06-11", "2018-06-16",
"2018-07-03", "2018-07-14", "2018-08-01", "2018-08-02"))

points = as.numeric(seq(1, 49, length.out = 49))


Run metalonda commend:

output2.metalonda.f5 = metalonda(Count = otu[5,], Time = Time, Group = Group,
ID = Individual, n.perm = 100, fit.method = "nbinomial", points = points,
text = rownames(subset_otu)[5], parall = FALSE, pvalue.threshold = 0.05,
adjust.method = "BH", time.unit = "days", ylabel = "Normalized Count",
col = c("black", "green"), prefix = "Test2_F5")


Thank you for any help you can provide. It is possible I misunderstood how to set up the vectors for the package (the instructions are outlined on the Github page linked above). 

</details>


# 答案1
**得分**: 1

首先要注意的是，你可以从Hadley Wickham的[「Advanced R」第22章](https://adv-r.hadley.nz/debugging.html)中学习如何在R中进行调试，这一章节解释了我在这个回答中将要使用的所有方法。

## 1. 定位错误

我主要使用`debug()`来深入了解函数调用堆栈，对于你的情况，它从以下部分开始：

```R
debug(MetaLonDA::metalonda)
output2.metalonda.f5 &lt;- MetaLonDA::metalonda(
  Count = otu[5,], 
  Time = Time, 
  Group = Group,
  ID = Individual, 
  n.perm = 100, 
  fit.method = &quot;nbinomial&quot;, 
  points = points,
  parall = FALSE, 
  pvalue.threshold = 0.05,
  adjust.method = &quot;BH&quot;, 
  time.unit = &quot;days&quot;, 
  ylabel = &quot;Normalized Count&quot;,
  col = c(&quot;black&quot;, &quot;green&quot;), 
  prefix = &quot;Test2_F5&quot;
)

如果你正确地跟随它，你可能会在这里遇到错误。注意到MetaLonDA包使用tryCatch()来尝试处理可能的错误。

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

在这一点上，你可以尝试调用tryCatch()内的函数，以确保函数MetaLonDA::curveFitting()是发生错误的地方。

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

然后退出调试模式（在控制台中使用Q）并执行以下操作：

undebug(MetaLonDA::metalonda)  # 退出metalonda的调试...
debug(MetaLonDA::curveFitting)  # ...并深入挖掘

经过多次迭代，你可能会发现错误消息来自于gss::mkphi.tp()，而真正的问题是gss::mkterm()（调用了gss::mkphi.tp()）向前传递了错误的参数。这个问题追溯到了你的Time对象，它不是一个向量。

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

2. 回到手册

你可以查看MetaLonDA::metalonda()的手册。它指出，Time、Group和ID参数都应该是向量。在你的情况下，它们都不是，不幸的是。

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

&gt; is.vector(Time)
[1] FALSE
&gt; is.vector(Individual)
[1] FALSE
&gt; is.vector(Group)
[1] FALSE

所以我尝试了以下对数据的更改：

Group &lt;- 
  c(2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L,
    1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L,
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
    2L, 2L, 2L, 2L)

Individual &lt;- 
  c(64L, 34L, 5L, 23L, 53L, 4L, 47L, 80L, 71L, 43L, 1L,
    87L, 48L, 45L, 55L, 18L, 11L, 47L, 75L, 44L, 47L, 10L, 86L, 44L,
    28L, 61L, 21L, 73L, 70L, 86L, 45L, 1L, 43L, 47L, 48L, 11L, 16L,
    60L, 58L, 40L, 30L, 31L, 50L, 17L, 5L, 86L, 76L, 60L, 69L)

Time &lt;- 
  c(13L, 5L, 2L, 6L, 4L, 1L, 12L, 3L, 44L, 45L, 44L,
    43L, 42L, 42L, 40L, 41L, 39L, 38L, 36L, 37L, 34L, 35L, 33L, 32L,
    8L, 9L, 7L, 7L, 26L, 27L, 23L, 22L, 24L, 21L, 28L, 29L, 25L,
    19L, 20L, 14L, 15L, 16L, 17L, 18L, 18L, 11L, 10L, 30L, 31L)

output2.metalonda.f5 &lt;- metalonda(
  Count = otu[5,], 
  Time = Time, 
  Group = Group,
  ID = Individual, 
  n.perm = 100, 
  fit.method = &quot;nbinomial&quot;, 
  points = points,
  parall = FALSE, 
  pvalue.threshold = 0.05,
  adjust.method = &quot;BH&quot;, 
  time.unit = &quot;days&quot;, 
  ylabel = &quot;Normalized Count&quot;,
  col = c(&quot;black&quot;, &quot;green&quot;), 
  prefix = &quot;Test2_F5&quot;
)

启动MetaLonDA 
正在可视化特征 =  0 
启动曲线拟合 
拟合：NB SS 
正在可视化特征的样条 =  0 
计算拟合曲线下的面积 
开始排列 
<details>
<summary>英文:</summary>
First things first: you can learn debugging in R from Hadley Wickham&#39;s [「Advanced R」 chapter 22](https://adv-r.hadley.nz/debugging.html), this chapter explains all the methods I will use in this answer.
## 1. Locate the bug
I mainly use `debug()` to dive into the function call stacks, in your case it starts with this:
```R
debug(MetaLonDA::metalonda)
output2.metalonda.f5 &lt;- MetaLonDA::metalonda(
Count = otu[5,], 
Time = Time, 
Group = Group,
ID = Individual, 
n.perm = 100, 
fit.method = &quot;nbinomial&quot;, 
points = points,
parall = FALSE, 
pvalue.threshold = 0.05,
adjust.method = &quot;BH&quot;, 
time.unit = &quot;days&quot;, 
ylabel = &quot;Normalized Count&quot;,
col = c(&quot;black&quot;, &quot;green&quot;), 
prefix = &quot;Test2_F5&quot;
)

If you follow it correctly, you may encounter the error at here. Noticing the package MetaLonDA uses tryCatch() to try to handle possible errors.

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

At this point, you can try call the function inside the tryCatch() to make sure that the function MetaLonDA::curveFitting() is where the error happened.

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

Then quit debug mode (by Q in console) and:

undebug(MetaLonDA::metalonda)  # quit debugging metalonda...
debug(MetaLonDA::curveFitting)  # ...and start digging deeper

After several iterations, you may locate the error message come from gss::mkphi.tp(), and the real problem is that gss::mkterm() (which calls gss::mkphi.tp()) passed wrong argument to former. That problem happens way back to your Time object, which is not a vector.

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

2. Back to the manual

You can check the MetaLonDA::metalonda()'s manual. It says that Time, Group and ID argument should all be vectors. In your case they are all not, unfortunately.

$ operator is invalid for atomic vectors ERROR while running R packages MetaLonDA

&gt; is.vector(Time)
[1] FALSE
&gt; is.vector(Individual)
[1] FALSE
&gt; is.vector(Group)
[1] FALSE

So I tried with these changes on data:

Group &lt;- 
  c(2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L,
    1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L,
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
    2L, 2L, 2L, 2L)

Individual &lt;- 
  c(64L, 34L, 5L, 23L, 53L, 4L, 47L, 80L, 71L, 43L, 1L,
    87L, 48L, 45L, 55L, 18L, 11L, 47L, 75L, 44L, 47L, 10L, 86L, 44L,
    28L, 61L, 21L, 73L, 70L, 86L, 45L, 1L, 43L, 47L, 48L, 11L, 16L,
    60L, 58L, 40L, 30L, 31L, 50L, 17L, 5L, 86L, 76L, 60L, 69L)

Time &lt;- 
  c(13L, 5L, 2L, 6L, 4L, 1L, 12L, 3L, 44L, 45L, 44L,
    43L, 42L, 42L, 40L, 41L, 39L, 38L, 36L, 37L, 34L, 35L, 33L, 32L,
    8L, 9L, 7L, 7L, 26L, 27L, 23L, 22L, 24L, 21L, 28L, 29L, 25L,
    19L, 20L, 14L, 15L, 16L, 17L, 18L, 18L, 11L, 10L, 30L, 31L)

output2.metalonda.f5 &lt;- metalonda(
  Count = otu[5,], 
  Time = Time, 
  Group = Group,
  ID = Individual, 
  n.perm = 100, 
  fit.method = &quot;nbinomial&quot;, 
  points = points,
  parall = FALSE, 
  pvalue.threshold = 0.05,
  adjust.method = &quot;BH&quot;, 
  time.unit = &quot;days&quot;, 
  ylabel = &quot;Normalized Count&quot;,
  col = c(&quot;black&quot;, &quot;green&quot;), 
  prefix = &quot;Test2_F5&quot;
)

Start MetaLonDA 
Visualizing Feature =  0 
Start Curve Fitting 
Fitting: NB SS 
Visualizing Splines of Feature =  0 
Calculate Area Under the Fitted Curves 
Start Permutation 
|=======================================================================================================| 100%
p-value Adjustment Method =  BH 
Visualizing Significant Intervals of Feature =  0 
Warning message:
`guides(&lt;scale&gt; = FALSE)` is deprecated. Please use `guides(&lt;scale&gt; = &quot;none&quot;)` instead. 
&gt;

I do not know where you get the .Label attribute, nor if it means something. So the result may be unreasonable. I'm just trying to run it correctly from an engineer's perspective. Hope this would help your.

PS: sessioninfo::session_info()

─ Session info ────────────────────────────────────────────────────────────────────────────────────────────────
setting  value
version  R version 4.1.3 (2022-03-10)
os       Ubuntu 20.04.5 LTS
system   x86_64, linux-gnu
ui       RStudio
language (EN)
collate  en_US.UTF-8
ctype    en_US.UTF-8
tz       Etc/UTC
date     2023-05-30
rstudio  2022.02.2+485 Prairie Trillium (server)
pandoc   2.5 @ /usr/bin/pandoc
─ Packages ────────────────────────────────────────────────────────────────────────────────────────────────────
! package        * version date (UTC) lib source
P assertthat       0.2.1   2019-03-21 [?] RSPM (R 4.1.0)
P BiocManager      1.30.16 2021-06-15 [?] RSPM (R 4.1.0)
P bit              4.0.4   2020-08-04 [?] RSPM (R 4.1.0)
P bit64            4.0.5   2020-08-30 [?] RSPM (R 4.1.0)
P cli              3.6.1   2023-03-23 [?] CRAN (R 4.1.3)
codetools        0.2-18  2020-11-04 [2] CRAN (R 4.1.3)
P colorspace       2.0-3   2022-02-21 [?] RSPM (R 4.1.0)
P crayon           1.5.1   2022-03-26 [?] RSPM (R 4.1.0)
P DBI              1.1.3   2022-06-18 [?] CRAN (R 4.1.3)
P digest           0.6.29  2021-12-01 [?] RSPM (R 4.1.0)
P doParallel       1.0.17  2022-02-07 [?] RSPM (R 4.1.0)
P dplyr            1.0.8   2022-02-08 [?] RSPM (R 4.1.0)
P ellipsis         0.3.2   2021-04-29 [?] RSPM (R 4.1.0)
P fansi            1.0.3   2022-03-24 [?] RSPM (R 4.1.0)
P farver           2.1.0   2021-02-28 [?] RSPM (R 4.1.0)
P forcats          0.5.1   2021-01-27 [?] RSPM (R 4.1.0)
P foreach          1.5.2   2022-02-02 [?] RSPM (R 4.1.0)
P formatR          1.12    2022-03-31 [?] RSPM (R 4.1.0)
P fs               1.5.2   2021-12-08 [?] RSPM (R 4.1.0)
P futile.logger    1.4.3   2016-07-10 [?] RSPM (R 4.1.0)
P futile.options   1.0.1   2018-04-20 [?] RSPM (R 4.1.0)
P generics         0.1.2   2022-01-31 [?] RSPM (R 4.1.0)
P ggplot2          3.3.5   2021-06-25 [?] RSPM (R 4.1.0)
P ggsci            2.9     2018-05-14 [?] RSPM (R 4.1.0)
P ggthemes         4.2.4   2021-01-20 [?] RSPM (R 4.1.0)
P glue             1.6.2   2022-02-24 [?] RSPM (R 4.1.0)
P gss              2.2-4   2023-03-15 [?] CRAN (R 4.1.3)
P gtable           0.3.0   2019-03-25 [?] RSPM (R 4.1.0)
P iterators        1.0.14  2022-02-05 [?] RSPM (R 4.1.0)
P knitr            1.38    2022-03-25 [?] RSPM (R 4.1.0)
P labeling         0.4.2   2020-10-20 [?] RSPM (R 4.1.0)
P lambda.r         1.2.4   2019-09-18 [?] RSPM (R 4.1.0)
lattice          0.20-45 2021-09-22 [2] CRAN (R 4.1.3)
P lifecycle        1.0.3   2022-10-07 [?] CRAN (R 4.1.3)
P lsa              0.73.2  2020-05-04 [?] RSPM (R 4.1.0)
P magrittr         2.0.3   2022-03-30 [?] RSPM (R 4.1.0)
P MetaLonDA      * 1.1.8   2019-12-18 [?] CRAN (R 4.1.3)
P munsell          0.5.0   2018-06-12 [?] RSPM (R 4.1.0)
P openxlsx         4.2.5   2021-12-14 [?] RSPM (R 4.1.0)
P pillar           1.7.0   2022-02-01 [?] RSPM (R 4.1.0)
P pkgconfig        2.0.3   2019-09-22 [?] RSPM (R 4.1.0)
P plyr             1.8.7   2022-03-24 [?] RSPM (R 4.1.0)
P pracma           2.4.2   2022-09-22 [?] CRAN (R 4.1.3)
P purrr            1.0.1   2023-01-10 [?] CRAN (R 4.1.3)
P R6               2.5.1   2021-08-19 [?] RSPM (R 4.1.0)
P Rcpp             1.0.8.3 2022-03-17 [?] RSPM (R 4.1.0)
renv             0.15.4  2022-03-03 [1] CRAN (R 4.1.3)
P rlang            1.1.1   2023-04-28 [?] CRAN (R 4.1.3)
P rstudioapi       0.13    2020-11-12 [?] RSPM (R 4.1.0)
P scales           1.2.0   2022-04-13 [?] RSPM (R 4.1.0)
P sessioninfo      1.2.2   2021-12-06 [?] RSPM (R 4.1.0)
P showtext         0.9-6   2023-05-03 [?] CRAN (R 4.1.3)
P showtextdb       3.0     2020-06-04 [?] RSPM (R 4.1.0)
P SnowballC        0.7.0   2020-04-01 [?] RSPM (R 4.1.0)
P stringi          1.7.6   2021-11-29 [?] RSPM (R 4.1.0)
P stringr          1.4.0   2019-02-10 [?] RSPM (R 4.1.0)
P sysfonts         0.8.8   2022-03-13 [?] RSPM (R 4.1.0)
P tibble           3.1.6   2021-11-07 [?] RSPM (R 4.1.0)
P tidyr            1.2.0   2022-02-01 [?] RSPM (R 4.1.0)
P tidyselect       1.1.2   2022-02-21 [?] RSPM (R 4.1.0)
P tzdb             0.3.0   2022-03-28 [?] RSPM (R 4.1.0)
P utf8             1.2.2   2021-07-24 [?] RSPM (R 4.1.0)
P vctrs            0.6.2   2023-04-19 [?] CRAN (R 4.1.3)
P VennDiagram      1.7.3   2022-04-12 [?] RSPM (R 4.1.0)
P vroom            1.5.7   2021-11-30 [?] RSPM (R 4.1.0)
P xfun             0.30    2022-03-02 [?] RSPM (R 4.1.0)
P zip              2.2.0   2021-05-31 [?] RSPM (R 4.1.0)
P zoo              1.8-10  2022-04-15 [?] RSPM (R 4.1.0)

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  • 本文由 发表于 2023年5月30日 01:30:40
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