diff --git a/src/stdlib_experimental_io.md b/src/stdlib_experimental_io.md index d90185209..7057a31c7 100644 --- a/src/stdlib_experimental_io.md +++ b/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 diff --git a/src/stdlib_experimental_optval.md b/src/stdlib_experimental_optval.md index f7e39e144..4e74ddc6c 100644 --- a/src/stdlib_experimental_optval.md +++ b/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 diff --git a/src/stdlib_experimental_quadrature.md b/src/stdlib_experimental_quadrature.md index c62638f64..8e6a4d8d9 100644 --- a/src/stdlib_experimental_quadrature.md +++ b/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. diff --git a/src/stdlib_experimental_stats.md b/src/stdlib_experimental_stats.md index debbd98a4..95891dc04 100644 --- a/src/stdlib_experimental_stats.md +++ b/src/stdlib_experimental_stats.md @@ -1,29 +1,8 @@ # Descriptive statistics - -## Implemented - - * [`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) - - ## `mean` - mean of array elements