Merge pull request #158 from jvdp1/toc_md

Addition of TOCs in Markdown files

Author: jvdp1

src/stdlib_experimental_io.md

@@ -1,11 +1,8 @@
 # IO
 
-## Implemented
-
- * `loadtxt`
- * `open`
- * `savetxt`
-
+* [`loadtxt` - load a 2D array from a text file](#loadtxt---load-a-2d-array-from-a-text-file)
+* [`open` - open a file](#open---open-a-file)
+* [`savetxt` - save a 2D array into a text file](#savetxt---save-a-2d-array-into-a-text-file)
 
 ## `loadtxt` - load a 2D array from a text file
 

src/stdlib_experimental_optval.md

@@ -1,8 +1,6 @@
 # Default values for optional arguments
 
-## Implemented
-
-* `optval`
+* [`optval` - fallback value for optional arguments](#optval---fallback-value-for-optional-arguments)
 
 ## `optval` - fallback value for optional arguments
 

src/stdlib_experimental_quadrature.md

@@ -1,12 +1,14 @@
 # Numerical integration
 
-## Implemented
-
-* `trapz`
-* `trapz_weights`
+* [`trapz` - integrate sampled values using trapezoidal rule](#trapz---integrate-sampled-values-using-trapezoidal-rule)
+* [`trapz_weights` - trapezoidal rule weights for given abscissas](#trapz_weights---trapezoidal-rule-weights-for-given-abscissas)
+* [`simps` - integrate sampled values using Simpson's rule (to be implemented)](#simps---integrate-sampled-values-using-simpsons-rule-to-be-implemented)
+* [`simps_weights` - Simpson's rule weights for given abscissas (to be implemented)](#simps_weights---simpsons-rule-weights-for-given-abscissas-to-be-implemented)
 
 ## `trapz` - 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
@@ -46,6 +48,8 @@ end program
 
 ## `trapz_weights` - 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
@@ -78,7 +82,9 @@ end program
 
 ```
 
-# `simps` - integrate sampled values using Simpson's rule
+## `simps` - integrate sampled values using Simpson's rule (to be implemented)
+
+### Description
 
 Returns the Simpson's 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`. 
 
@@ -112,7 +118,9 @@ If the size of `y` is two, the result is the same as if `trapz` had been called
 
 TBD
 
-# `simps_weights` - Simpson's rule weights for given abscissas
+## `simps_weights` - Simpson's rule weights for given abscissas (to be implemented)
+
+### 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 Simpson's rule approximation to the integral.
 

src/stdlib_experimental_stats.md

@@ -1,29 +1,8 @@
 # Descriptive statistics
 
-
-## Implemented
-<!-- vim-markdown-toc GFM -->
-
 * [`mean` - mean of array elements](#mean---mean-of-array-elements)
-	* [Description](#description)
-	* [Syntax](#syntax)
-	* [Arguments](#arguments)
-	* [Return value](#return-value)
-	* [Example](#example)
 * [`moment` - central moment of array elements](#moment---central-moment-of-array-elements)
-	* [Description](#description-1)
-	* [Syntax](#syntax-1)
-	* [Arguments](#arguments-1)
-	* [Return value](#return-value-1)
-	* [Example](#example-1)
 * [`var` - variance of array elements](#var---variance-of-array-elements)
-	* [Description](#description-2)
-	* [Syntax](#syntax-2)
-	* [Arguments](#arguments-2)
-	* [Return value](#return-value-2)
-	* [Example](#example-2)
-
-<!-- vim-markdown-toc -->
 
 ## `mean` - mean of array elements