docimp: addition of links in md files

Author: jvdp1

doc/specs/stdlib_experimental_io.md

@@ -6,14 +6,14 @@ title: experimental_IO
 
 [TOC]
 
-## `loadtxt` - load a 2D array from a text file
+## `[[stdlib_experimental_io(module):loadtxt(interface)]]` - load a 2D array from a text file
 
 ### Description
 Loads a rank-2 `array` from a text file.
 
 ### Syntax
 
-`call loadtxt(filename, array)`
+`call [[stdlib_experimental_io(module):loadtxt(interface)]](filename, array)`
 
 ### Arguments
 
@@ -37,15 +37,15 @@ end program demo_loadtxt
 ```
 
 
-## `open` - open a file
+## `[[stdlib_experimental_io(module):open(function)]]` - open a file
 
 ### Description
 
 Returns the unit number of a file opened to read, to write, or to read and write. The file might be a text file or a binary file. All files are opened using a streamed access.
 
 ### Syntax
 
-`u = open(filename [, mode] [, iostat])`
+`u = [[stdlib_experimental_io(module):open(function)]](filename [, mode] [, iostat])`
 
 ### Arguments
 
@@ -90,14 +90,14 @@ end program demo_open
 ```
 
 
-## `savetxt` - save a 2D array into a text file
+## `[[stdlib_experimental_io(module):savetxt(interface)]]` - save a 2D array into a text file
 
 ### Description
 Saves a rank-2 `array` into a text file.
 
 ### Syntax
 
-`call savetxt(filename, array)`
+`call [[stdlib_experimental_io(module):savetxt(interface)]](filename, array)`
 
 ### Arguments
 

doc/specs/stdlib_experimental_linalg.md

@@ -6,15 +6,15 @@ title: experimental_linalg
 
 [TOC]
 
-## `diag` - Create a diagonal array or extract the diagonal elements of an array
+## `[[stdlib_experimental_linalg(module):diag(interface)]]` - Create a diagonal array or extract the diagonal elements of an array
 
 ### Description
 
 Create a diagonal array or extract the diagonal elements of an array
 
 ### Syntax
 
-`d = diag(a [, k])`
+`d = [[stdlib_experimental_linalg(module):diag(interface)]](a [, k])`
 
 ### Arguments
 
@@ -91,15 +91,15 @@ program demo_diag5
 end program demo_diag5
 ```
 
-## `eye` - Construct the identity matrix
+## `[[stdlib_experimental_linalg(module):eye(function)]]` - Construct the identity matrix
 
 ### Description
 
 Construct the identity matrix
 
 ## Syntax
 
-`I = eye(n)`
+`I = [[stdlib_experimental_linalg(module):eye(function)]](n)`
 
 ### Arguments
 
@@ -128,15 +128,15 @@ program demo_eye2
 end program demo_eye2
 ```
 
-## `trace` - Trace of a matrix
+## `[[stdlib_experimental_linalg(module):trace(interface)]]` - Trace of a matrix
 
 ### Description
 
 Trace of a matrix (rank-2 array)
 
 ### Syntax
 
-`result = trace(A)`
+`result = [stdlib_experimental_linalg(module):trace(interface)](A)`
 
 ### Arguments
 

doc/specs/stdlib_experimental_optval.md

@@ -6,7 +6,7 @@ title: experimental_optval
 
 [TOC]
 
-## `optval` - fallback value for optional arguments
+## `[[stdlib_experimental_optval(module):optval(interface)]]` - fallback value for optional arguments
 
 ### Description
 
@@ -16,7 +16,7 @@ This function is intended to be called in a procedure with one or more `optional
 
 ### Syntax
 
-`result = optval(x, default)`
+`result = [[stdlib_experimental_optval(module):optval(interface)]](x, default)`
 
 ### Arguments
 

doc/specs/stdlib_experimental_quadrature.md

@@ -6,17 +6,17 @@ title: experimental_quadrature
 
 [TOC]
 
-## `trapz` - integrate sampled values using trapezoidal rule
+## `[[stdlib_experimental_quadrature(module):trapz(interface)]]` - integrate sampled values using trapezoidal rule
 
 ### Description
 
 Returns the trapezoidal rule integral of an array `y` representing discrete samples of a function. The integral is computed assuming either equidistant abscissas with spacing `dx` or arbitary abscissas `x`.
 
 ### Syntax
 
-`result = trapz(y, x)`
+`result = [[stdlib_experimental_quadrature(module):trapz(interface)]](y, x)`
 
-`result = trapz(y, dx)`
+`result = [[stdlib_experimental_quadrature(module):trapz(interface)]](y, dx)`
 
 ### Arguments
 
@@ -44,18 +44,18 @@ program demo_trapz
 ! 22.0
     print *, trapz(y, 0.5) 
 ! 11.0
-end program
+end program demo_trapz
 ```
 
-## `trapz_weights` - trapezoidal rule weights for given abscissas
+## `[[stdlib_experimental_quadrature(module):trapz_weights(interface)]]` - trapezoidal rule weights for given abscissas
 
 ### Description
 
 Given an array of abscissas `x`, computes the array of weights `w` such that if `y` represented function values tabulated at `x`, then `sum(w*y)` produces a trapezoidal rule approximation to the integral.
 
 ### Syntax
 
-`result = trapz_weights(x)`
+`result = [[stdlib_experimental_quadrature(module):trapz_weights(interface)]](x)`
 
 ### Arguments
 
@@ -79,7 +79,7 @@ program demo_trapz_weights
     w = trapz_weight(x)
     print *, dot_product(w, y)
 ! 22.0
-end program
+end program demo_trapz_weights
 
 ```
 

doc/specs/stdlib_experimental_stats.md

@@ -6,7 +6,7 @@ title: experimental_stats
 
 [TOC]
 
-## `cov` - covariance of array elements
+## `[[stdlib_experimental_stats(module):cov(interface)]]` - covariance of array elements
 
 ### Description
 
@@ -25,7 +25,7 @@ The scaling can be changed with the logical argument `corrected`. If `corrected`
 
 ### Syntax
 
-`result = cov(array, dim [, mask [, corrected]])`
+`result = [[stdlib_experimental_stats(module):cov(interface)]](array, dim [, mask [, corrected]])`
 
 ### Arguments
 
@@ -62,17 +62,17 @@ program demo_cov
 end program demo_cov
 ```
 
-## `mean` - mean of array elements
+## `[[stdlib_experimental_stats(module):mean(interface)]]` - mean of array elements
 
 ### Description
 
 Returns the mean of all the elements of `array`, or of the elements of `array` along dimension `dim` if provided, and if the corresponding element in `mask` is `true`.
 
 ### Syntax
 
-`result = mean(array [, mask])`
+`result = [[stdlib_experimental_stats(module):mean(interface)]](array [, mask])`
 
-`result = mean(array, dim [, mask])`
+`result = [[stdlib_experimental_stats(module):mean(interface)]](array, dim [, mask])`
 
 ### Arguments
 
@@ -106,7 +106,7 @@ program demo_mean
 end program demo_mean
 ```
 
-## `moment` - central moments of array elements
+## `[[stdlib_experimental_stats(module):moment(interface)]]` - central moments of array elements
 
 ### Description
 
@@ -131,9 +131,9 @@ The _k_-th order moment about `center` is defined as :
 
 ### Syntax
 
-`result = moment(array, order [, center [, mask]])`
+`result = [[stdlib_experimental_stats(module):moment(interface)]](array, order [, center [, mask]])`
 
-`result = moment(array, order, dim [, center [, mask]])`
+`result = [[stdlib_experimental_stats(module):moment(interface)]](array, order, dim [, center [, mask]])`
 
 ### Arguments
 
@@ -173,7 +173,7 @@ program demo_moment
 end program demo_moment
 ```
 
-## `var` - variance of array elements
+## `[[stdlib_experimental_stats(module):var(interface)]]` - variance of array elements
 
 ### Description
 
@@ -192,9 +192,9 @@ The use of the term `n-1` for scaling is called Bessel 's correction. The scalin
 
 ### Syntax
 
-`result = var(array [, mask [, corrected]])`
+`result = [[stdlib_experimental_stats(module):var(interface)]](array [, mask [, corrected]])`
 
-`result = var(array, dim [, mask [, corrected]])`
+`result = [[stdlib_experimental_stats(module):var(interface)]](array, dim [, mask [, corrected]])`
 
 ### Arguments