Add "Available since version" to function reference

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,6 +1,7 @@
 #### Submission Checklist
 
 - [ ] Builds locally 
+- [ ] New functions marked with `` `r since("VERSION")` ``
 - [ ] Declare copyright holder and open-source license: see below
 
 #### Summary

README.md

@@ -85,7 +85,7 @@ This repository uses
 [GitHub Pages](https://help.github.com/categories/github-pages-basics)
 to serve the
 [project pages](https://help.github.com/articles/user-organization-and-project-pages/#project-pages-sites) site
-with URL `https://mc-stan.org/docs`.
+with URL https://mc-stan.org/docs.
 The publishing strategy is to serve the contents of the directory `docs` on branch `master`.
 The `docs` directory contains an empty file named `.nojekyll` so that GitHub will treat the contents
 as pre-generated HTML instead of trying to run [jekyll](https://jekyllrb.com).

src/.gitignore

@@ -0,0 +1,7 @@
+*.aux
+*.fdb_latexmk
+*.fls
+*.idx
+*.ilg
+*.ind
+*.toc

src/functions-reference/array_operations.Rmd

@@ -24,24 +24,28 @@ with respect to the combination operation (min, max, sum, or product).
 
 `real` **`min`**`(array[] real x)`<br>\newline
 The minimum value in x, or $+\infty$ if x is size 0.
+`r since("2.0")`
 
 <!-- int; min; (array[] int x); -->
 \index{{\tt \bfseries min }!{\tt (array[] int x): int}|hyperpage}
 
 `int` **`min`**`(array[] int x)`<br>\newline
 The minimum value in x, or error if x is size 0.
+`r since("2.0")`
 
 <!-- real; max; (array[] real x); -->
 \index{{\tt \bfseries max }!{\tt (array[] real x): real}|hyperpage}
 
 `real` **`max`**`(array[] real x)`<br>\newline
 The maximum value in x, or $-\infty$ if x is size 0.
+`r since("2.0")`
 
 <!-- int; max; (array[] int x); -->
 \index{{\tt \bfseries max }!{\tt (array[] int x): int}|hyperpage}
 
 `int` **`max`**`(array[] int x)`<br>\newline
 The maximum value in x, or error if x is size 0.
+`r since("2.0")`
 
 ### Sum, product, and log sum of exp
 
@@ -52,18 +56,21 @@ The maximum value in x, or error if x is size 0.
 The sum of the elements in x, defined for $x$ of size $N$ by \[
 \text{sum}(x) = \begin{cases} \sum_{n=1}^N x_n & \text{if} N > 0
 \\[4pt] 0 & \text{if} N = 0 \end{cases} \]
+`r since("2.1")`
 
 <!-- real; sum; (array[] real x); -->
 \index{{\tt \bfseries sum }!{\tt (array[] real x): real}|hyperpage}
 
 `real` **`sum`**`(array[] real x)`<br>\newline
 The sum of the elements in x; see definition above.
+`r since("2.0")`
 
 <!-- real; prod; (array[] real x); -->
 \index{{\tt \bfseries prod }!{\tt (array[] real x): real}|hyperpage}
 
 `real` **`prod`**`(array[] real x)`<br>\newline
 The product of the elements in x, or 1 if x is size 0.
+`r since("2.0")`
 
 <!-- real; prod; (array[] int x); -->
 \index{{\tt \bfseries prod }!{\tt (array[] int x): real}|hyperpage}
@@ -72,13 +79,15 @@ The product of the elements in x, or 1 if x is size 0.
 The product of the elements in x, \[ \text{product}(x) = \begin{cases}
 \prod_{n=1}^N x_n & \text{if} N > 0 \\[4pt] 1 & \text{if} N = 0
 \end{cases} \]
+`r since("2.0")`
 
 <!-- real; log_sum_exp; (array[] real x); -->
 \index{{\tt \bfseries log\_sum\_exp }!{\tt (array[] real x): real}|hyperpage}
 
 `real` **`log_sum_exp`**`(array[] real x)`<br>\newline
 The natural logarithm of the sum of the exponentials of the elements
 in x, or $-\infty$ if the array is empty.
+`r since("2.0")`
 
 ### Sample mean, variance, and standard deviation
 
@@ -102,6 +111,7 @@ The sample mean of the elements in x. For an array $x$ of size $N >
 0$, \[ \text{mean}(x) \ = \ \bar{x} \ = \ \frac{1}{N} \sum_{n=1}^N
 x_n. \] It is an error to the call the mean function with an array of
 size $0$.
+`r since("2.0")`
 
 <!-- real; variance; (array[] real x); -->
 \index{{\tt \bfseries variance }!{\tt (array[] real x): real}|hyperpage}
@@ -112,6 +122,7 @@ The sample variance of the elements in x. For $N > 0$, \[
 - \bar{x})^2 & \text{if } N > 1 \\[4pt] 0 & \text{if } N = 1
 \end{cases} \] It is an error to call the `variance` function with an
 array of size 0.
+`r since("2.0")`
 
 <!-- real; sd; (array[] real x); -->
 \index{{\tt \bfseries sd }!{\tt (array[] real x): real}|hyperpage}
@@ -121,6 +132,7 @@ The sample standard deviation of elements in x. \[ \text{sd}(x) =
 \begin{cases} \sqrt{\, \text{variance}(x)} & \text{if } N > 1 \\[4pt]
 0 & \text{if } N = 0 \end{cases} \] It is an error to call the `sd`
 function with an array of size 0.
+`r since("2.0")`
 
 ### Euclidean distance and squared distance
 
@@ -132,24 +144,28 @@ The Euclidean distance between x and y, defined by \[
 \text{distance}(x,y) \ = \ \sqrt{\textstyle \sum_{n=1}^N (x_n -
 y_n)^2} \] where `N` is the size of x and y. It is an error to call
 `distance` with arguments of unequal size.
+`r since("2.2")`
 
 <!-- real; distance; (vector x, row_vector y); -->
 \index{{\tt \bfseries distance }!{\tt (vector x, row\_vector y): real}|hyperpage}
 
 `real` **`distance`**`(vector x, row_vector y)`<br>\newline
 The Euclidean distance between x and y
+`r since("2.2")`
 
 <!-- real; distance; (row_vector x, vector y); -->
 \index{{\tt \bfseries distance }!{\tt (row\_vector x, vector y): real}|hyperpage}
 
 `real` **`distance`**`(row_vector x, vector y)`<br>\newline
 The Euclidean distance between x and y
+`r since("2.2")`
 
 <!-- real; distance; (row_vector x, row_vector y); -->
 \index{{\tt \bfseries distance }!{\tt (row\_vector x, row\_vector y): real}|hyperpage}
 
 `real` **`distance`**`(row_vector x, row_vector y)`<br>\newline
 The Euclidean distance between x and y
+`r since("2.2")`
 
 <!-- real; squared_distance; (vector x, vector y); -->
 \index{{\tt \bfseries squared\_distance }!{\tt (vector x, vector y): real}|hyperpage}
@@ -160,24 +176,28 @@ The squared Euclidean distance between x and y, defined by \[
 \textstyle \sum_{n=1}^N (x_n - y_n)^2, \] where `N` is the size of x
 and y. It is an error to call `squared_distance` with arguments of
 unequal size.
+`r since("2.7")`
 
 <!-- real; squared_distance; (vector x, row_vector y); -->
 \index{{\tt \bfseries squared\_distance }!{\tt (vector x, row\_vector y): real}|hyperpage}
 
 `real` **`squared_distance`**`(vector x, row_vector y)`<br>\newline
 The squared Euclidean distance between x and y
+`r since("2.26")`
 
 <!-- real; squared_distance; (row_vector x, vector y); -->
 \index{{\tt \bfseries squared\_distance }!{\tt (row\_vector x, vector y): real}|hyperpage}
 
 `real` **`squared_distance`**`(row_vector x, vector y)`<br>\newline
 The squared Euclidean distance between x and y
+`r since("2.26")`
 
 <!-- real; squared_distance; (row_vector x, row_vector y); -->
 \index{{\tt \bfseries squared\_distance }!{\tt (row\_vector x, row\_vector y): real}|hyperpage}
 
 `real` **`squared_distance`**`(row_vector x, row_vector y)`<br>\newline
 The Euclidean distance between x and y
+`r since("2.26")`
 
 ### Quantile
 
@@ -193,12 +213,14 @@ Sample quantiles in Statistical Packages (R's default quantile function).
 
 `real` **`quantile`**`(data array[] real x, data real p)`<br>\newline
 The p-th quantile of x
+`r since("2.27")`
 
 <!-- array[] real; quantile; (data array[] real x, data array[] real p); -->
 \index{{\tt \bfseries quantile }!{\tt (data array[] real x, data array[] real p): real}|hyperpage}
 
 `array[] real` **`quantile`**`(data array[] real x, data array[] real p)`<br>\newline
 An array containing the quantiles of x given by the array of probabilities p
+`r since("2.27")`
 
 ## Array size and dimension function
 
@@ -238,6 +260,7 @@ extract the dimensions of vectors and matrices.
 `array[] int` **`dims`**`(T x)`<br>\newline
 Return an integer array containing the dimensions of x; the type of
 the argument T can be any Stan type with up to 8 array dimensions.
+`r since("2.0")`
 
 <!-- int; num_elements; (array[] T x); -->
 \index{{\tt \bfseries num\_elements }!{\tt (array[] T x): int}|hyperpage}
@@ -248,6 +271,7 @@ elements in contained arrays, vectors, and matrices. T can be any
 array type. For example, if `x` is of type `array[4, 3] real` then
 `num_elements(x)` is 12, and if `y` is declared as `array[5] matrix[3, 4] y`,
 then `size(y)` evaluates to 60.
+`r since("2.5")`
 
 <!-- int; size; (array[] T x); -->
 \index{{\tt \bfseries size }!{\tt (array[] T x): int}|hyperpage}
@@ -257,6 +281,7 @@ Return the number of elements in the array x; the type of the array T
 can be any type, but the size is just the size of the top level array,
 not the total number of elements contained. For example, if `x` is of
 type `array[4, 3] real` then `size(x)` is 4.
+`r since("2.0")`
 
 ## Array broadcasting {#array-broadcasting}
 
@@ -270,18 +295,21 @@ arrays.
 
 `array[] T` **`rep_array`**`(T x, int n)`<br>\newline
 Return the n array with every entry assigned to x.
+`r since("2.0")`
 
 <!-- array[,] T; rep_array; (T x, int m, int n); -->
 \index{{\tt \bfseries rep\_array }!{\tt (T x, int m, int n): array[,] T}|hyperpage}
 
 `array [,] T` **`rep_array`**`(T x, int m, int n)`<br>\newline
 Return the m by n array with every entry assigned to x.
+`r since("2.0")`
 
 <!-- array[,,] T; rep_array; (T x, int k, int m, int n); -->
 \index{{\tt \bfseries rep\_array }!{\tt (T x, int k, int m, int n): array[,,] T}|hyperpage}
 
 `array[,,] T` **`rep_array`**`(T x, int k, int m, int n)`<br>\newline
 Return the k by m by n array with every entry assigned to x.
+`r since("2.0")`
 
 For example, `rep_array(1.0,5)` produces a real array (type `array[] real`)
 of size 5 with all values set to 1.0.  On the other hand,
@@ -343,6 +371,7 @@ After the assignment to `b`, the value for `b[j, k, m, n]` is equal to
 Return the concatenation of two arrays in the order of the arguments.
 T must be an N-dimensional array of any Stan type (with a maximum N of
 7). All dimensions but the first must match.
+`r since("2.18")`
 
 For example, the following code appends two three dimensional arrays
 of matrices together. Note that all dimensions except the first match.
@@ -372,64 +401,74 @@ as a real array of size 3, with values \[ \text{v} = (1, -10.3,
 
 `array[] real` **`sort_asc`**`(array[] real v)`<br>\newline
 Sort the elements of v in ascending order
+`r since("2.0")`
 
 <!-- array[] int; sort_asc; (array[] int v); -->
 \index{{\tt \bfseries sort\_asc }!{\tt (array[] int v): array[] int}|hyperpage}
 
 `array[] int` **`sort_asc`**`(array[] int v)`<br>\newline
 Sort the elements of v in ascending order
+`r since("2.0")`
 
 <!-- array[] real; sort_desc; (array[] real v); -->
 \index{{\tt \bfseries sort\_desc }!{\tt (array[] real v): array[] real}|hyperpage}
 
 `array[] real` **`sort_desc`**`(array[] real v)`<br>\newline
 Sort the elements of v in descending order
+`r since("2.0")`
 
 <!-- array[] int; sort_desc; (array[] int v); -->
 \index{{\tt \bfseries sort\_desc }!{\tt (array[] int v): array[] int}|hyperpage}
 
 `array[] int` **`sort_desc`**`(array[] int v)`<br>\newline
 Sort the elements of v in descending order
+`r since("2.0")`
 
 <!-- array[] int; sort_indices_asc; (array[] real v); -->
 \index{{\tt \bfseries sort\_indices\_asc }!{\tt (array[] real v): array[] int}|hyperpage}
 
 `array[] int` **`sort_indices_asc`**`(array[] real v)`<br>\newline
 Return an array of indices between 1 and the size of v, sorted to
 index v in ascending order.
+`r since("2.3")`
 
 <!-- array[] int; sort_indices_asc; (array[] int v); -->
 \index{{\tt \bfseries sort\_indices\_asc }!{\tt (array[] int v): array[] int}|hyperpage}
 
 `array[] int` **`sort_indices_asc`**`(array[] int v)`<br>\newline
 Return an array of indices between 1 and the size of v, sorted to
 index v in ascending order.
+`r since("2.3")`
 
 <!-- array[] int; sort_indices_desc; (array[] real v); -->
 \index{{\tt \bfseries sort\_indices\_desc }!{\tt (array[] real v): array[] int}|hyperpage}
 
 `array[] int` **`sort_indices_desc`**`(array[] real v)`<br>\newline
 Return an array of indices between 1 and the size of v, sorted to
 index v in descending order.
+`r since("2.3")`
 
 <!-- array[] int; sort_indices_desc; (array[] int v); -->
 \index{{\tt \bfseries sort\_indices\_desc }!{\tt (array[] int v): array[] int}|hyperpage}
 
 `array[] int` **`sort_indices_desc`**`(array[] int v)`<br>\newline
 Return an array of indices between 1 and the size of v, sorted to
 index v in descending order.
+`r since("2.3")`
 
 <!-- int; rank; (array[] real v, int s); -->
 \index{{\tt \bfseries rank }!{\tt (array[] real v, int s): int}|hyperpage}
 
 `int` **`rank`**`(array[] real v, int s)`<br>\newline
 Number of components of v less than v[s]
+`r since("2.0")`
 
 <!-- int; rank; (array[] int v, int s); -->
 \index{{\tt \bfseries rank }!{\tt (array[] int v, int s): int}|hyperpage}
 
 `int` **`rank`**`(array[] int v, int s)`<br>\newline
 Number of components of v less than v[s]
+`r since("2.0")`
 
 ## Reversing functions {#reversing-functions}
 
@@ -444,3 +483,4 @@ array of size 3, with values
 
 `array[] T` **`reverse`**`(array[] T v)`<br>\newline
 Return a new array containing the elements of the argument in reverse order.
+`r since("2.23")`