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content: update old goddoc.org urls to pkg.go.dev #21

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18 changes: 9 additions & 9 deletions content/authors/admin/_index.md
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Expand Up @@ -59,15 +59,15 @@ user_groups:
Gonum is a set of packages designed to make writing numerical and scientific
algorithms productive, performant, and scalable.

Gonum contains libraries for [matrices and linear algebra](https://godoc.org/gonum.org/v1/gonum/mat);
[statistics](https://godoc.org/gonum.org/v1/gonum/stat),
[probability](https://godoc.org/gonum.org/v1/gonum/stat/distuv)
[distributions](https://godoc.org/gonum.org/v1/gonum/stat/distmv),
and [sampling](https://godoc.org/gonum.org/v1/gonum/stat/sampleuv); tools for
[function differentiation](https://godoc.org/gonum.org/v1/gonum/diff/fd),
[integration](https://godoc.org/gonum.org/v1/gonum/integrate/quad),
and [optimization](https://godoc.org/gonum.org/v1/gonum/optimize);
[network](https://godoc.org/gonum.org/v1/gonum/graph) creation and analysis; and more.
Gonum contains libraries for [matrices and linear algebra](https://pkg.go.dev/gonum.org/v1/gonum/mat);
[statistics](https://pkg.go.dev/gonum.org/v1/gonum/stat),
[probability](https://pkg.go.dev/gonum.org/v1/gonum/stat/distuv)
[distributions](https://pkg.go.dev/gonum.org/v1/gonum/stat/distmv),
and [sampling](https://pkg.go.dev/gonum.org/v1/gonum/stat/sampleuv); tools for
[function differentiation](https://pkg.go.dev/gonum.org/v1/gonum/diff/fd),
[integration](https://pkg.go.dev/gonum.org/v1/gonum/integrate/quad),
and [optimization](https://pkg.go.dev/gonum.org/v1/gonum/optimize);
[network](https://pkg.go.dev/gonum.org/v1/gonum/graph) creation and analysis; and more.

We encourage you to [get started](post/intro_to_gonum) with Go and Gonum if

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28 changes: 14 additions & 14 deletions content/post/intro_to_gonum.md
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Expand Up @@ -29,15 +29,15 @@ This makes Gonum similar to [numpy](https://www.numpy.org) and
[Julia](https://julialang.org/) and [Matlab](https://www.mathworks.com/)
which are full programming languages.

Gonum contains libraries for [matrices and linear algebra](https://godoc.org/gonum.org/v1/gonum/mat);
[statistics](https://godoc.org/gonum.org/v1/gonum/stat),
[probability](https://godoc.org/gonum.org/v1/gonum/stat/distuv)
[distributions](https://godoc.org/gonum.org/v1/gonum/stat/distmv),
and [sampling](https://godoc.org/gonum.org/v1/gonum/stat/sampleuv); tools for
[function differentiation](https://godoc.org/gonum.org/v1/gonum/diff/fd),
[integration](https://godoc.org/gonum.org/v1/gonum/integrate/quad),
and [optimization](https://godoc.org/gonum.org/v1/gonum/optimize);
[network](https://godoc.org/gonum.org/v1/gonum/graph) creation and analysis; and more.
Gonum contains libraries for [matrices and linear algebra](https://pkg.go.dev/gonum.org/v1/gonum/mat);
[statistics](https://pkg.go.dev/gonum.org/v1/gonum/stat),
[probability](https://pkg.go.dev/gonum.org/v1/gonum/stat/distuv)
[distributions](https://pkg.go.dev/gonum.org/v1/gonum/stat/distmv),
and [sampling](https://pkg.go.dev/gonum.org/v1/gonum/stat/sampleuv); tools for
[function differentiation](https://pkg.go.dev/gonum.org/v1/gonum/diff/fd),
[integration](https://pkg.go.dev/gonum.org/v1/gonum/integrate/quad),
and [optimization](https://pkg.go.dev/gonum.org/v1/gonum/optimize);
[network](https://pkg.go.dev/gonum.org/v1/gonum/graph) creation and analysis; and more.

## Why use Gonum

Expand Down Expand Up @@ -133,21 +133,21 @@ without an official specification.
### Learning Gonum
The best way to learn about particular packages and functions is through
the source code documentation.
The godoc [website](https://godoc.org) automatically generates documentation
The godoc [website](https://pkg.go.dev) automatically generates documentation
pages from publically available source code.
For most Go packages (not just Gonum), going to `https://godoc.org/<package-import-path>`
For most Go packages (not just Gonum), going to `https://pkg.go.dev/<package-import-path>`
will give you documentation about that particular package.
For example, `https://godoc.org/gonum.org/v1/gonum/mat` will give documentation
For example, `https://pkg.go.dev/gonum.org/v1/gonum/mat` will give documentation
about Gonum's matrix package, as well as documentation for specific functions.
Go to `https://godoc.org/gonum.org/v1/gonum/graph/topo` and you will see
Go to `https://pkg.go.dev/gonum.org/v1/gonum/graph/topo` and you will see
documentation about our graph topology routines, for example for finding the
"strongly connected components" of a graph.
Note that sometimes godoc lists functions below the relevant type, for example
the function to create a new dense matrix `mat.NewDense`, is listed under the
`Dense` type.
At the bottom of the index you will see a list of specific code examples,
and at the very bottom of the godoc page, you can see a list of subpackages,
if any (for instance, scroll to the bottom of `https://godoc.org/gonum.org/v1/gonum/stat`).
if any (for instance, scroll to the bottom of `https://pkg.go.dev/gonum.org/v1/gonum/stat`).

Please also check future posts on this blog for extended commentary on Gonum
packages and their effective use.
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4 changes: 2 additions & 2 deletions content/post/intro_to_stats_with_gonum.md
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Expand Up @@ -9,7 +9,7 @@ summary = "The first of a series of short posts providing an introduction and co
_The following was cross-posted (with minor changes) from [sbinet.github.io/posts/2017-10-04-intro-to-stats-with-gonum](https://sbinet.github.io/posts/2017-10-04-intro-to-stats-with-gonum/)_

This is the first of a series of short posts providing an introduction and code examples for using the Gonum packages.
This first post focuses on computing basic statistics using the [stat](https://godoc.org/gonum.org/v1/gonum/stat) package.
This first post focuses on computing basic statistics using the [stat](https://pkg.go.dev/gonum.org/v1/gonum/stat) package.

This first post is based off the content of this blog post:

Expand Down Expand Up @@ -108,7 +108,7 @@ uses the unbiased sample variance (_ie:_ the divisor is `len(xs)-1`):
16.891029423927957
```

If one wants the uncorrected estimator, [stat.Moment](https://godoc.org/gonum.org/v1/gonum/stat#Moment) can be used instead.
If one wants the uncorrected estimator, [stat.Moment](https://pkg.go.dev/gonum.org/v1/gonum/stat#Moment) can be used instead.

With this quite blunt tool, we can analyse some real data from real life.
We will use a dataset pertaining to the salary of European developers, all 1147 of them :).
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