[英]inject() function from rlang package cannot work with Predict() function from rms package in R
Context语境
I am learning use tidy eval to write my own function.我正在学习使用 tidy eval 来编写我自己的 function。
If I calculate hr1
without using tidy eval, the code works fine, such as:如果我在不使用 tidy eval 的情况下计算
hr1
,则代码可以正常工作,例如:
hr1 = Predict(fit, meal.cal = q, fun = exp, ref.zero = TRUE)
When I use rlang::inject()
and rms::Predict()
jointly to calculate hr1
, an error occurs, such as:当我联合使用
rlang::inject()
和rms::Predict()
计算hr1
时,出现错误,例如:
hr1= rlang::inject(Predict(fit, ,,x = q. fun = exp, ref.zero = TRUE))
Question问题
How to use rlang::object()
and rms::Predict()
correctly jointly?如何正确联合使用
rlang::object()
和rms::Predict()
?
Reproducible code可重现的代码
library(survival)
library(rms)
data(cancer)
x = sym('meal.cal')
q = quantile(lung[[x]], probs = c(0.05, 0.35, 0.65, 0.95), na.rm = T)
fit = rlang::inject(cph(Surv(time, status) ~ rcs(!!x), data = lung))
dd = datadist(lung)
options(datadist = 'dd') # Predict() cannot work without set the options
hr1 = Predict(fit, meal.cal = q, fun = exp, ref.zero = TRUE) # Run successful
head(hr1)
# meal.cal yhat lower upper
# 1 338 1.2486497 0.7310498 2.132722
# 2 825 0.9916446 0.7766063 1.266226
# 3 1039 1.0245228 0.8826652 1.189179
# 4 1425 1.0558754 0.6322319 1.763392
#
# Response variable (y):
#
# Limits are 0.95 confidence limits
hr1= rlang::inject(Predict(fit, !!x = q, fun = exp, ref.zero = TRUE)) # Run failed
# Error: unexpected '=' in "hr1= rlang::inject(Predict(fit, !!x ="
The left-hand side of a named parameter (ie =
inside a call) must be a name, it cannot be an expression.命名参数的左侧(即调用中的
=
)必须是名称,不能是表达式。 To work around this limitation, you can use splicing here:要解决此限制,您可以在此处使用拼接:
hr1 = rlang::inject(Predict(fit, !!! setNames(list(q), "foo"), fun = exp, ref.zero = TRUE))
In general, 'rlang' allows :=
in the place of =
for named arguments to work around the R syntax limitation but for some reason inject
does not support this.通常,'rlang' 允许
:=
代替 named arguments 的=
来解决 R 语法限制,但由于某些原因, inject
不支持此功能。
As @Lionel Henry notes in the comments, another workaround is to use a regular do.call
where we need to supply the arguments in list form and we use that together with rlang::list2()
which allows the use of :=
and splicing on the lefthand side:正如@Lionel Henry 在评论中指出的那样,另一种解决方法是使用常规
do.call
,我们需要以列表形式提供 arguments 并将其与rlang::list2()
一起使用,这允许使用:=
和拼接在左手侧:
library(survival)
library(rms)
data(cancer)
do.call(Predict, rlang::list2(fit, !! x := q, fun = exp, ref.zero = TRUE))
#> meal.cal yhat lower upper
#> 1 338 1.2486497 0.7310498 2.132722
#> 2 825 0.9916446 0.7766063 1.266226
#> 3 1039 1.0245228 0.8826652 1.189179
#> 4 1425 1.0558754 0.6322319 1.763392
#>
#> Response variable (y):
#>
#> Limits are 0.95 confidence limits
Created on 2022-09-28 by the reprex package (v2.0.1)由reprex package (v2.0.1) 创建于 2022-09-28
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