knit_expand()A few simple examples:
library(knitr)
knit_expand(text = "The value of pi is {{pi}}.")
## [1] "The value of pi is 3.14159265358979."
knit_expand(text = "The value of a is {{a}}, so a + 1 is {{a+1}}.", a = rnorm(1))
## [1] "The value of a is -0.428141902201812, so a + 1 is 0.571858097798188."
knit_expand(text = "The area of a circle with radius {{r}} is {{pi*r^2}}", r = 5)
## [1] "The area of a circle with radius 5 is 78.5398163397448"
Any number of variables:
knit_expand(text = "a is {{a}} and b is {{b}}, with my own pi being {{pi}} instead of {{base::pi}}",
a = 1, b = 2, pi = 3)
## [1] "a is 1 and b is 2, with my own pi being 3 instead of 3.14159265358979"
Custom delimiter <% %>:
knit_expand(text = "I do not like curly braces, so use % with <> instead: a is <% a %>.",
a = 8, delim = c("<%", "%>"))
## [1] "I do not like curly braces, so use % with <> instead: a is 8."
The pyexpander delimiter:
knit_expand(text = "hello $(LETTERS[24]) and $(pi)!", delim = c("$(", ")"))
## [1] "hello X and 3.14159265358979!"
Arbitrary R code:
knit_expand(text = "you cannot see the value of x {{x=rnorm(1)}}but it is indeed created: x = {{x}}")
## [1] "you cannot see the value of x but it is indeed created: x = -0.339063272871435"
res = knit_expand(text = c(" x | x^2", "{{x=1:5;paste(sprintf(\"%2d | %3d\", x, x^2), collapse = \"\n\")}}"))
cat(res)
## x | x^2
## 1 | 1
## 2 | 4
## 3 | 9
## 4 | 16
## 5 | 25
The m4 example: http://en.wikipedia.org/wiki/M4_(computer_language)
res = knit_expand(text = c("{{i=0;h2=function(x){i<<-i+1;sprintf(\"<h2>%d. %s</h2>\", i, x)} }}<html>",
"{{h2(\"First Section\")}}", "{{h2(\"Second Section\")}}", "{{h2(\"Conclusion\")}}",
"</html>"))
cat(res)
## <html>
## <h2>1. First Section</h2>
## <h2>2. Second Section</h2>
## <h2>3. Conclusion</h2>
## </html>
Build regression models based on a template; loop through all variables in mtcars:
src = lapply(names(mtcars)[-1], function(i) {
knit_expand(text = c("# Regression on {{i}}", "```{r lm-{{i}}}", "lm(mpg~{{i}}, data=mtcars)",
"```"))
})
# knit the source
res = knit_child(text = unlist(src))
res = paste("<pre><code>", gsub("^\\s*|\\s*$", "", res), "</code></pre>", sep = "")
# Regression on cyl
```r
lm(mpg ~ cyl, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ cyl, data = mtcars)
##
## Coefficients:
## (Intercept) cyl
## 37.88 -2.88
```
# Regression on disp
```r
lm(mpg ~ disp, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ disp, data = mtcars)
##
## Coefficients:
## (Intercept) disp
## 29.5999 -0.0412
```
# Regression on hp
```r
lm(mpg ~ hp, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ hp, data = mtcars)
##
## Coefficients:
## (Intercept) hp
## 30.0989 -0.0682
```
# Regression on drat
```r
lm(mpg ~ drat, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ drat, data = mtcars)
##
## Coefficients:
## (Intercept) drat
## -7.52 7.68
```
# Regression on wt
```r
lm(mpg ~ wt, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ wt, data = mtcars)
##
## Coefficients:
## (Intercept) wt
## 37.29 -5.34
```
# Regression on qsec
```r
lm(mpg ~ qsec, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ qsec, data = mtcars)
##
## Coefficients:
## (Intercept) qsec
## -5.11 1.41
```
# Regression on vs
```r
lm(mpg ~ vs, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ vs, data = mtcars)
##
## Coefficients:
## (Intercept) vs
## 16.62 7.94
```
# Regression on am
```r
lm(mpg ~ am, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ am, data = mtcars)
##
## Coefficients:
## (Intercept) am
## 17.15 7.24
```
# Regression on gear
```r
lm(mpg ~ gear, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ gear, data = mtcars)
##
## Coefficients:
## (Intercept) gear
## 5.62 3.92
```
# Regression on carb
```r
lm(mpg ~ carb, data = mtcars)
```
```
##
## Call:
## lm(formula = mpg ~ carb, data = mtcars)
##
## Coefficients:
## (Intercept) carb
## 25.87 -2.06
```