From 0a54917ecf58dd8b37e5131f7ce7745bbcb1ea79 Mon Sep 17 00:00:00 2001 From: James Hollway Date: Wed, 26 Oct 2022 11:40:02 +0200 Subject: [PATCH 1/6] Converted visualisation vignette to a learnr tutorial --- NEWS.md | 7 +- inst/tutorials/community/community.Rmd | 2 +- .../tutorials/visualisation/visualisation.Rmd | 58 +- .../visualisation/visualisation.html | 657 ++++++++++++++++++ vignettes/p2visualisation.Rmd.orig | 219 ------ vignettes/teaching/ggrapheg-1.png | Bin 78867 -> 0 bytes vignettes/teaching/layoutseg-1.png | Bin 164587 -> 0 bytes vignettes/teaching/migrapheg-1.png | Bin 27565 -> 0 bytes vignettes/teaching/migraphexample2-1.png | Bin 22668 -> 0 bytes vignettes/teaching/patchwork-1.png | Bin 79716 -> 0 bytes vignettes/teaching/patchwork-2.png | Bin 73799 -> 0 bytes 11 files changed, 683 insertions(+), 260 deletions(-) rename vignettes/p2visualisation.Rmd => inst/tutorials/visualisation/visualisation.Rmd (91%) create mode 100644 inst/tutorials/visualisation/visualisation.html delete mode 100644 vignettes/p2visualisation.Rmd.orig delete mode 100644 vignettes/teaching/ggrapheg-1.png delete mode 100644 vignettes/teaching/layoutseg-1.png delete mode 100644 vignettes/teaching/migrapheg-1.png delete mode 100644 vignettes/teaching/migraphexample2-1.png delete mode 100644 vignettes/teaching/patchwork-1.png delete mode 100644 vignettes/teaching/patchwork-2.png diff --git a/NEWS.md b/NEWS.md index 635d39ff..9700d084 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,8 @@ +# migraph 0.12.4 + +## Package + +- Converted 'visualisation' vignette to a learnr tutorial # migraph 0.12.3 ## Package @@ -8,7 +13,7 @@ ## Motifs - Added node names to node_motif class where available -- Added `node_brokerage_census()` and `network_network_census()` for counting Gould-Fernandez brokerage roles +- Added `node_brokerage_census()` and `network_brokerage_census()` for counting Gould-Fernandez brokerage roles # migraph 0.12.2 diff --git a/inst/tutorials/community/community.Rmd b/inst/tutorials/community/community.Rmd index 806f835a..892a8b44 100644 --- a/inst/tutorials/community/community.Rmd +++ b/inst/tutorials/community/community.Rmd @@ -1,5 +1,5 @@ --- -title: "Equivalence" +title: "Community" author: "James Hollway" output: learnr::tutorial runtime: shiny_prerendered diff --git a/vignettes/p2visualisation.Rmd b/inst/tutorials/visualisation/visualisation.Rmd similarity index 91% rename from vignettes/p2visualisation.Rmd rename to inst/tutorials/visualisation/visualisation.Rmd index 1f4e7069..d7cf5fa6 100644 --- a/vignettes/p2visualisation.Rmd +++ b/inst/tutorials/visualisation/visualisation.Rmd @@ -1,16 +1,16 @@ --- -title: "2. Visualisation" +title: "Visualisation" author: "James Hollway" -output: rmarkdown::html_vignette -vignette: > - %\VignetteIndexEntry{2. Visualisation} - %\VignetteEngine{knitr::rmarkdown} - %\VignetteEncoding{UTF-8} +output: learnr::tutorial +runtime: shiny_prerendered --- +```{r setup, include=FALSE} +library(learnr) +knitr::opts_chunk$set(echo = FALSE) +``` - -# Why we graph +## Why we graph Network visualisation is important and non-trivial. As Tufte (1983: 9) said: @@ -41,7 +41,7 @@ that network researchers have to play with: - edge shape - edge arrows -# Approaches to visualising networks in R +## Approaches to visualising networks in R There are a host of packages for plotting in R, and for plotting networks in R. @@ -65,20 +65,17 @@ This vignette introduces some functions in the `{migraph}` package for plotting visualising network data. `{migraph}` builds upon the ggplot2/ggraph engine for plotting. -# Using `{migraph}` to quickly plot network graphs +## Using `{migraph}` to quickly plot network graphs To get a basic visualisation of the network before adding various specifications, the `autographr()` function in `{migraph}` is a quick and easy way to obtain a clear first look of the network for preliminary investigations and understanding of the network. - -```r +```{r migrapheg, echo=TRUE, exercise = TRUE} library(migraph) autographr(ison_brandes) ``` - -![](teaching/migrapheg-1.png) We can also specify the colours, groups, shapes, and sizes of nodes in the `autographr()` function using the following parameters: @@ -87,56 +84,42 @@ the `autographr()` function using the following parameters: * `node_shape` * `node_size` -## Appending more +### Appending more Append `ggtitle()` to add a title. `{migraph}` works well with both `{ggplot2}` and `{ggraph}` functions that can be appended to create more tailored visualisations of the network. - -```r +```{r migraphexample2, echo=TRUE, message=FALSE, warning=FALSE, exercise = TRUE} autographr(ison_adolescents, labels = TRUE, node_size = 1.5) + ggtitle("Visualisation") ``` -![](teaching/migraphexample2-1.png) - `{migraph}` also uses the `{patchwork}` package for arranging graphs together, e.g. side-by-side or above one another. The syntax is quite straight forward and is used throughout these vignettes. - -```r +```{r patchwork, echo=TRUE, message=FALSE, warning=FALSE, exercise = TRUE} autographr(ison_adolescents) + autographr(ison_algebra) -``` - -![](teaching/patchwork-1.png) - -```r autographr(ison_adolescents) / autographr(ison_algebra) ``` -![](teaching/patchwork-2.png) - -## Layouts +### Layouts A range of graph layouts are available across the `{igraph}`, `{graphlayouts}`, and `{migraph}` packages that can be used together with `autographr()`. - -```r +```{r layoutseg, echo=TRUE, message=FALSE, warning=FALSE, exercise = TRUE} (autographr(ison_southern_women, layout = "bipartite") + ggtitle("bipartite") | autographr(ison_southern_women, layout = "hierarchy") + ggtitle("hierarchy")) / (autographr(ison_southern_women, layout = "concentric") + ggtitle("concentric") | autographr(ison_southern_women, layout = "railway") + ggtitle("railway")) ``` -![](teaching/layoutseg-1.png) - -# Using `{ggraph}` for more flexibility +## Using `{ggraph}` for more flexibility For more flexibility with visualizations, `{migraph}` users are encouraged to use the excellent `{ggraph}` package. @@ -146,8 +129,7 @@ As with `{ggplot2}`, `{ggraph}` users are expected to build a particular plot from the ground up, adding explicit layers to visualise the nodes and edges. - -```r +```{r ggrapheg, echo=TRUE, message=FALSE, warning=FALSE, exercise = TRUE} library(ggraph) ggraph(mpn_elite_mex, layout = "fr") + geom_edge_link(edge_colour = "dark grey", @@ -161,8 +143,6 @@ ggraph(mpn_elite_mex, layout = "fr") + theme_graph() + theme(legend.position = "none") ``` - -![](teaching/ggrapheg-1.png) As we can see in the code above, we can specify various aspects of the plot to tailor it to our network. @@ -211,7 +191,7 @@ or removed using "none". For more see David Schoch's [excellent resources on this](http://mr.schochastics.net/netVizR.html). -# Exporting plots to PDF +## Exporting plots to PDF We can print the plots we have made to PDF by point-and-click by selecting 'Save as PDF...' from under the 'Export' dropdown menu diff --git a/inst/tutorials/visualisation/visualisation.html b/inst/tutorials/visualisation/visualisation.html new file mode 100644 index 00000000..6eb34c44 --- /dev/null +++ b/inst/tutorials/visualisation/visualisation.html @@ -0,0 +1,657 @@ + + + + + + + + + + + + + + + + + +Visualisation + + + + + + + + + + + + + + + + + + + + + +Skip to Tutorial Content + + + +
+
+ +
+ +
+

Why we graph

+

Network visualisation is important and non-trivial. As Tufte (1983: +9) said:

+
+

“At their best, graphics are instruments for reasoning about +quantitative information. Often the most effective way to describe, +explore, and summarize a set of numbers – even a very large set – is to +look at pictures of those numbers”

+
+

Brandes et al (1999) argue that visualising networks demands thinking +about:

+
    +
  • substance: a concise and precise delivery of insights to +the researcher and/or readers
  • +
  • design: the ergonomics of function are 98% of the purpose +of good design, aesthetics only 2%
  • +
  • and algorithm: the features of the e.g. the layout +algorithm
  • +
+

While there may be many dead-ends to exploratory visualisation, it is +worth taking the time to make sure that your main points are easy to +appreciate.

+

On her excellent +and helpful website, Katya Ognyanova outlines some key dimensions of +control that network researchers have to play with:

+
    +
  • vertex position (layout)
  • +
  • vertex shape
  • +
  • vertex color
  • +
  • vertex size
  • +
  • vertex labels
  • +
  • edge color
  • +
  • edge size
  • +
  • edge shape
  • +
  • edge arrows
  • +
+
+
+

Approaches to visualising networks in R

+

There are a host of packages for plotting in R, and for plotting +networks in R. Plotting in R is typically based around two main +approaches: the ‘base’ approach in R by default, and the ‘grid’ approach +made popular by the famous and very flexible {ggplot2} +package.1 Approaches to plotting +graphs or networks in R can be similarly divided.

+

The two classic packages are {igraph} and +{sna}, both building upon the base R graphics engine. Newer +packages {ggnetwork} +and {ggraph} +build upon a grid approach.2 This vignette introduces some +functions in the {migraph} package for plotting and +visualising network data. {migraph} builds upon the +ggplot2/ggraph engine for plotting.

+
+
+
+
    +
  1. ‘gg’ stands for the Grammar of Graphics.↩︎

  2. +
  3. Others include: ‘Networkly’ for creating 2-D +and 3-D interactive networks that can be rendered with plotly and can be +easily integrated into shiny apps or markdown documents; ‘visNetwork’ +interacts with javascript (vis.js) to make interactive networks (http://datastorm-open.github.io/visNetwork/); and +‘networkD3’ interacts with javascript (D3) to make interactive networks +(https://www.r-bloggers.com/2016/10/network-visualization-part-6-d3-and-r-networkd3/).↩︎

  4. +
+
+
+

Using {migraph} to quickly plot network graphs

+

To get a basic visualisation of the network before adding various +specifications, the autographr() function in +{migraph} is a quick and easy way to obtain a clear first +look of the network for preliminary investigations and understanding of +the network.

+
+
library(migraph)
+autographr(ison_brandes)
+ +
+

We can also specify the colours, groups, shapes, and sizes of nodes +in the autographr() function using the following +parameters:

+
    +
  • node_colour
  • +
  • node_shape
  • +
  • node_size
  • +
+
+

Appending more

+

Append ggtitle() to add a title. {migraph} +works well with both {ggplot2} and {ggraph} +functions that can be appended to create more tailored visualisations of +the network.

+
+
autographr(ison_adolescents,
+           labels = TRUE,
+           node_size = 1.5) + 
+  ggtitle("Visualisation")
+ +
+

{migraph} also uses the {patchwork} package +for arranging graphs together, e.g. side-by-side or above one another. +The syntax is quite straight forward and is used throughout these +vignettes.

+
+
autographr(ison_adolescents) + autographr(ison_algebra)
+autographr(ison_adolescents) / autographr(ison_algebra)
+ +
+
+
+

Layouts

+

A range of graph layouts are available across the +{igraph}, {graphlayouts}, and +{migraph} packages that can be used together with +autographr().

+
+
(autographr(ison_southern_women, layout = "bipartite") + ggtitle("bipartite") |
+autographr(ison_southern_women, layout = "hierarchy") + ggtitle("hierarchy")) /
+(autographr(ison_southern_women, layout = "concentric") + ggtitle("concentric") |
+   autographr(ison_southern_women, layout = "railway") + ggtitle("railway"))
+ +
+
+
+
+

Using {ggraph} for more flexibility

+

For more flexibility with visualizations, {migraph} +users are encouraged to use the excellent {ggraph} package. +{ggraph} is built upon the venerable {ggplot2} +package and works with tbl_graph and igraph +objects. As with {ggplot2}, {ggraph} users are +expected to build a particular plot from the ground up, adding explicit +layers to visualise the nodes and edges.

+
+
library(ggraph)
+ggraph(mpn_elite_mex, layout = "fr") + 
+  geom_edge_link(edge_colour = "dark grey", 
+                  arrow = arrow(angle = 45,
+                                length = unit(2, "mm"),
+                                type = "closed"),
+                  end_cap = circle(3, "mm")) +
+  geom_node_point(size = 2.5, shape = 19, colour = "blue") +
+  geom_node_text(aes(label=name), family = "serif", size = 2.5) +
+  scale_edge_width(range = c(0.3,1.5)) +
+  theme_graph() +
+  theme(legend.position = "none")
+ +
+

As we can see in the code above, we can specify various aspects of +the plot to tailor it to our network. Firstly, we can alter the +layout of the network using the layout = +argument to create a clearer visualisation of the ties between nodes. +This is especially important for larger networks, where nodes and ties +are more easily obscured or misrepresented. In {ggraph}, +the default layout is the “stress” layout. The “stress” layout is a safe +choice because it is deterministic and fits well with almost any graph, +but it is also a good idea to explore and try out other layouts on your +data. More layouts can be found in the {graphlayouts} and +{igraph} R packages. To use a layout from the +{igraph} package, enter only the last part of the layout +algorithm name (eg. layout = "mds" for +“layout_with_mds”).

+

Secondly, using geom_node_point() which draws the nodes +as geometric shapes (circles, squares, or triangles), we can specify the +presentation of nodes in the network in terms of their +shape (shape=, choose from 1 to 21), size +(size=), or colour (colour=). We can +also use aes() to match to node attributes. To add labels, +use geom_node_text() or geom_node_label() +(draws labels within a box). The font (family=), font size +(size=), and colour (colour=) of the labels +can be specified.

+

Thirdly, we can also specify the presentation of +edges in the network. To draw edges, we use +geom_edge_link0() or geom_edge_link(). Using +the latter function makes it possible to draw a straight line with a +gradient. The following features can be tailored either globally or +matched to specific edge attributes using aes():

+
    +
  • colour: edge_colour=

  • +
  • width: edge_width=

  • +
  • linetype: edge_linetype=

  • +
  • opacity: edge_alpha=

  • +
+

For directed graphs, arrows can be drawn using the +arrow= argument and the arrow() function from +{ggplot2}. The angle, length, arrowhead type, and padding +between the arrowhead and the node can also be specified.

+

To change the position of the legend, add the theme() +function from {ggplot2}. The legend can be positioned at +the top, bottom, left, or right, or removed using “none”.

+

For more see David Schoch’s excellent resources on +this.

+
+
+

Exporting plots to PDF

+

We can print the plots we have made to PDF by point-and-click by +selecting ‘Save as PDF…’ from under the ‘Export’ dropdown menu in the +plots panel tab of RStudio.

+

If you want to do this programmatically, say because you want to +record how you have saved it so that you can e.g. make some changes to +the parameters at some point, this is also not too difficult.

+

After running the (gg-based) plot you want to save, use the command +ggsave("my_filename.pdf") to save your plot as a PDF to +your working directory. If you want to save it somewhere else, you will +need to specify the file path (or change the working directory, but that +might be more cumbersome). If you want to save it as a different +filetype, replace .pdf with e.g. .png or +.jpeg. See ?ggsave for more. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+ + + + + + +
+ +
+ +
+
+
+
+ + +
+

Visualisation

+

James Hollway

+
+ + +
+
+
+
+ + +
+
+ + + + + + + + + + + + + + + + diff --git a/vignettes/p2visualisation.Rmd.orig b/vignettes/p2visualisation.Rmd.orig deleted file mode 100644 index 06bc23ee..00000000 --- a/vignettes/p2visualisation.Rmd.orig +++ /dev/null @@ -1,219 +0,0 @@ ---- -title: "2. Visualisation" -author: "James Hollway" -output: rmarkdown::html_vignette -vignette: > - %\VignetteIndexEntry{2. Visualisation} - %\VignetteEngine{knitr::rmarkdown} - %\VignetteEncoding{UTF-8} ---- - -```{r, include = FALSE} -knitr::opts_chunk$set( - collapse = TRUE, - comment = "#>", - fig.cap = "", - fig.path = "teaching/" -) -``` - -# Why we graph - -Network visualisation is important and non-trivial. -As Tufte (1983: 9) said: - -> "At their best, graphics are instruments for reasoning about quantitative information. Often the most effective way to describe, explore, and summarize a set of numbers – even a very large set – is to look at pictures of those numbers" - -Brandes et al (1999) argue that visualising networks demands thinking about: - -- _substance_: a concise and precise delivery of insights to the researcher and/or readers -- _design_: the ergonomics of function are 98% of the purpose of good design, aesthetics only 2% -- and _algorithm_: the features of the e.g. the layout algorithm - -While there may be many dead-ends to exploratory visualisation, -it is worth taking the time to make sure that your main points are -easy to appreciate. - -On [her excellent and helpful website](https://kateto.net/network-visualization), -Katya Ognyanova outlines some key dimensions of control -that network researchers have to play with: - -- vertex position (layout) -- vertex shape -- vertex color -- vertex size -- vertex labels -- edge color -- edge size -- edge shape -- edge arrows - -# Approaches to visualising networks in R - -There are a host of packages for plotting in R, -and for plotting networks in R. -Plotting in R is typically based around two main approaches: -the 'base' approach in R by default, -and the 'grid' approach made popular by the famous and very flexible `{ggplot2}` package.^['gg' stands for the Grammar of Graphics.] -Approaches to plotting _graphs_ or _networks_ in R can be similarly divided. - -The two classic packages are `{igraph}` and `{sna}`, both building upon the base R graphics engine. -Newer packages [`{ggnetwork}`](https://www.r-bloggers.com/2016/03/ggnetwork-network-geometries-for-ggplot2/) and -[`{ggraph}`](https://ggraph.data-imaginist.com/index.html) build upon a grid approach.^[ -Others include: 'Networkly' for creating 2-D and 3-D interactive networks -that can be rendered with plotly and can be easily integrated into -shiny apps or markdown documents; -'visNetwork' interacts with javascript (vis.js) to make interactive networks -(http://datastorm-open.github.io/visNetwork/); and -'networkD3' interacts with javascript (D3) to make interactive networks -(https://www.r-bloggers.com/2016/10/network-visualization-part-6-d3-and-r-networkd3/). -] -This vignette introduces some functions in the `{migraph}` package for plotting and -visualising network data. -`{migraph}` builds upon the ggplot2/ggraph engine for plotting. - -# Using `{migraph}` to quickly plot network graphs - -To get a basic visualisation of the network before adding various specifications, -the `autographr()` function in `{migraph}` is a quick and easy way -to obtain a clear first look of the network -for preliminary investigations and understanding of the network. - -```{r migrapheg, echo=TRUE} -library(migraph) -autographr(ison_brandes) -``` - -We can also specify the colours, groups, shapes, and sizes of nodes in -the `autographr()` function using the following parameters: - -* `node_colour` -* `node_shape` -* `node_size` - -## Appending more - -Append `ggtitle()` to add a title. -`{migraph}` works well with both `{ggplot2}` and `{ggraph}` functions -that can be appended to create more tailored visualisations -of the network. - -```{r migraphexample2, echo=TRUE, message=FALSE, warning=FALSE} -autographr(ison_adolescents, - labels = TRUE, - node_size = 1.5) + - ggtitle("Visualisation") -``` - -`{migraph}` also uses the `{patchwork}` package for arranging -graphs together, e.g. side-by-side or above one another. -The syntax is quite straight forward and is used throughout these vignettes. - -```{r patchwork, echo=TRUE, message=FALSE, warning=FALSE} -autographr(ison_adolescents) + autographr(ison_algebra) -autographr(ison_adolescents) / autographr(ison_algebra) -``` - -## Layouts - -A range of graph layouts are available across the `{igraph}`, `{graphlayouts}`, and `{migraph}` packages -that can be used together with `autographr()`. - -```{r layoutseg, echo=TRUE, message=FALSE, warning=FALSE} -(autographr(ison_southern_women, layout = "bipartite") + ggtitle("bipartite") | -autographr(ison_southern_women, layout = "hierarchy") + ggtitle("hierarchy")) / -(autographr(ison_southern_women, layout = "concentric") + ggtitle("concentric") | - autographr(ison_southern_women, layout = "railway") + ggtitle("railway")) -``` - -# Using `{ggraph}` for more flexibility - -For more flexibility with visualizations, -`{migraph}` users are encouraged to use the excellent `{ggraph}` package. -`{ggraph}` is built upon the venerable `{ggplot2}` package -and works with `tbl_graph` and `igraph` objects. -As with `{ggplot2}`, `{ggraph}` users are expected to build -a particular plot from the ground up, -adding explicit layers to visualise the nodes and edges. - -```{r ggrapheg, echo=TRUE, message=FALSE, warning=FALSE} -library(ggraph) -ggraph(mpn_elite_mex, layout = "fr") + - geom_edge_link(edge_colour = "dark grey", - arrow = arrow(angle = 45, - length = unit(2, "mm"), - type = "closed"), - end_cap = circle(3, "mm")) + - geom_node_point(size = 2.5, shape = 19, colour = "blue") + - geom_node_text(aes(label=name), family = "serif", size = 2.5) + - scale_edge_width(range = c(0.3,1.5)) + - theme_graph() + - theme(legend.position = "none") -``` - -As we can see in the code above, we can specify various aspects of the plot to -tailor it to our network. -Firstly, we can alter the **layout** of the network using the `layout =` argument -to create a clearer visualisation of the ties between nodes. -This is especially important for larger networks, where nodes and ties are more -easily obscured or misrepresented. -In `{ggraph}`, the default layout is the "stress" layout. -The "stress" layout is a safe choice because it is deterministic and -fits well with almost any graph, but it is also a good idea to explore and try -out other layouts on your data. -More layouts can be found in the `{graphlayouts}` and `{igraph}` R packages. -To use a layout from the `{igraph}` package, enter only the last part of the layout -algorithm name (eg. `layout = "mds"` for "layout_with_mds"). - -Secondly, using `geom_node_point()` which draws the nodes as geometric shapes -(circles, squares, or triangles), we can specify the presentation of **nodes** -in the network in terms of their *shape* (`shape=`, choose from 1 to 21), -*size* (`size=`), or *colour* (`colour=`). We can also use `aes()` to match to -node attributes. To add labels, use `geom_node_text()` or -`geom_node_label()` (draws labels within a box). The font (`family=`), -font size (`size=`), and colour (`colour=`) of the labels can be specified. - -Thirdly, we can also specify the presentation of **edges** in the network. -To draw edges, we use `geom_edge_link0()` or `geom_edge_link()`. -Using the latter function makes it possible to draw a straight line with a -gradient. -The following features can be tailored either globally or matched to specific -edge attributes using `aes()`: - -* *colour*: `edge_colour=` - -* *width*: `edge_width=` - -* *linetype*: `edge_linetype=` - -* *opacity*: `edge_alpha=` - -For directed graphs, arrows can be drawn using the `arrow=` argument and the -`arrow()` function from `{ggplot2}`. The angle, length, arrowhead type, and -padding between the arrowhead and the node can also be specified. - -To change the position of the legend, add the `theme()` function from `{ggplot2}`. -The legend can be positioned at the top, bottom, left, or right, -or removed using "none". - -For more see David Schoch's [excellent resources on this](http://mr.schochastics.net/netVizR.html). - -# Exporting plots to PDF - -We can print the plots we have made to PDF by point-and-click -by selecting 'Save as PDF...' from under the 'Export' dropdown menu -in the plots panel tab of RStudio. - -If you want to do this programmatically, -say because you want to record how you have saved it so that you can -e.g. make some changes to the parameters at some point, -this is also not too difficult. - -After running the (gg-based) plot you want to save, -use the command `ggsave("my_filename.pdf")` to save your plot -as a PDF to your working directory. -If you want to save it somewhere else, you will need to 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zXvjX{TREJs#`k%%Ow-OObGtO*n+b@LYJS^Pj(W`5?JTzeLVay$JSA2Bzge%q#`H=$ zXG{GyABSR;PEyyr@M}y-cH>NCtwD_OcgV{ZTipdvR>FKBbp+`2v@cwt%^v zhwb!sm;EW5USSeKn0Uj`iuKv3@a2h?<>L0T=oQR;Y!UQheLzvu5_yGLfkr*E>31%e zmxNs}IADX`4f4=z?Ma7rfLVXjLEW;%kvN1Q0}7uc5VKltII=Ts9Gobh8 zD3Fb$U|R!i?zUUN{*JOjQ;%;bxi{hd;*9$)F4hD8vMy!+d?ftu1{LA*i#zWB!$UhT Y{L3pANA}Jv0^G~;w9TnJGi=2F0ij)$R{#J2 From 8470b97e1c9c3b585215327b908841de4784c0f2 Mon Sep 17 00:00:00 2001 From: James Hollway Date: Wed, 26 Oct 2022 11:40:49 +0200 Subject: [PATCH 2/6] Brokerage census functions get their own documentation page --- NEWS.md | 2 ++ R/motif_census.R | 42 ++++++++++++++++--------------- man/brokerage_census.Rd | 55 +++++++++++++++++++++++++++++++++++++++++ man/network_census.Rd | 18 +------------- man/node_census.Rd | 12 +-------- 5 files changed, 81 insertions(+), 48 deletions(-) create mode 100644 man/brokerage_census.Rd diff --git a/NEWS.md b/NEWS.md index 9700d084..fbe0047c 100644 --- a/NEWS.md +++ b/NEWS.md @@ -3,6 +3,8 @@ ## Package - Converted 'visualisation' vignette to a learnr tutorial +- Brokerage census gets their own documentation page + # migraph 0.12.3 ## Package diff --git a/R/motif_census.R b/R/motif_census.R index b3f6b0da..28669605 100644 --- a/R/motif_census.R +++ b/R/motif_census.R @@ -216,24 +216,6 @@ node_path_census <- function(object){ make_node_motif(out, object) } -#' @describeIn node_census Returns the Gould-Fernandez brokerage -#' roles played by nodes in a network. -#' @importFrom sna brokerage -#' @references -#' Gould, R.V. and Fernandez, R.M. 1989. -#' “Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks.” -#' _Sociological Methodology_, 19: 89-126. -#' @examples -#' node_brokerage_census(ison_networkers, "Discipline") -#' @export -node_brokerage_census <- function(object, membership, standardized = FALSE){ - out <- sna::brokerage(as_network(object), node_attribute(object, membership)) - out <- if(standardized) out$z.nli else out$raw.nli - colnames(out) <- c("Coordinator", "Itinerant", "Gatekeeper", - "Representative", "Liaison", "Total") - make_node_motif(out, object) -} - #' Censuses of motifs at the network level #' #' @name network_census @@ -330,14 +312,34 @@ network_mixed_census <- function (object, object2) { make_network_motif(res, object) } -#' @describeIn network_census Returns the Gould-Fernandez brokerage -#' roles in a network. +#' Censuses of brokerage motifs +#' +#' @name brokerage_census +#' @family motifs +#' @inheritParams node_census +NULL + +#' @describeIn brokerage_census Returns the Gould-Fernandez brokerage +#' roles played by nodes in a network. #' @importFrom sna brokerage #' @references #' Gould, R.V. and Fernandez, R.M. 1989. #' “Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks.” #' _Sociological Methodology_, 19: 89-126. #' @examples +#' node_brokerage_census(ison_networkers, "Discipline") +#' @export +node_brokerage_census <- function(object, membership, standardized = FALSE){ + out <- sna::brokerage(as_network(object), node_attribute(object, membership)) + out <- if(standardized) out$z.nli else out$raw.nli + colnames(out) <- c("Coordinator", "Itinerant", "Gatekeeper", + "Representative", "Liaison", "Total") + make_node_motif(out, object) +} + +#' @describeIn brokerage_census Returns the Gould-Fernandez brokerage +#' roles in a network. +#' @examples #' network_brokerage_census(ison_networkers, "Discipline") #' @export network_brokerage_census <- function(object, membership, standardized = FALSE){ diff --git a/man/brokerage_census.Rd b/man/brokerage_census.Rd new file mode 100644 index 00000000..8cb9cbee --- /dev/null +++ b/man/brokerage_census.Rd @@ -0,0 +1,55 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/motif_census.R +\name{brokerage_census} +\alias{brokerage_census} +\alias{node_brokerage_census} +\alias{network_brokerage_census} +\title{Censuses of brokerage motifs} +\usage{ +node_brokerage_census(object, membership, standardized = FALSE) + +network_brokerage_census(object, membership, standardized = FALSE) +} +\arguments{ +\item{object}{An object of a migraph-consistent class: +\itemize{ +\item matrix (adjacency or incidence) from \code{{base}} R +\item edgelist, a data frame from \code{{base}} R or tibble from \code{{tibble}} +\item igraph, from the \code{{igraph}} package +\item network, from the \code{{network}} package +\item tbl_graph, from the \code{{tidygraph}} package +}} + +\item{membership}{A vector of partition membership as integers.} + +\item{standardized}{Whether the score should be standardized +into a \emph{z}-score indicating how many standard deviations above +or below the average the score lies.} +} +\description{ +Censuses of brokerage motifs +} +\section{Functions}{ +\itemize{ +\item \code{node_brokerage_census()}: Returns the Gould-Fernandez brokerage +roles played by nodes in a network. + +\item \code{network_brokerage_census()}: Returns the Gould-Fernandez brokerage +roles in a network. + +}} +\examples{ +node_brokerage_census(ison_networkers, "Discipline") +network_brokerage_census(ison_networkers, "Discipline") +} +\references{ +Gould, R.V. and Fernandez, R.M. 1989. +“Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks.” +\emph{Sociological Methodology}, 19: 89-126. +} +\seealso{ +Other motifs: +\code{\link{network_census}}, +\code{\link{node_census}} +} +\concept{motifs} diff --git a/man/network_census.Rd b/man/network_census.Rd index 0131ea18..d5b99921 100644 --- a/man/network_census.Rd +++ b/man/network_census.Rd @@ -5,7 +5,6 @@ \alias{network_dyad_census} \alias{network_triad_census} \alias{network_mixed_census} -\alias{network_brokerage_census} \title{Censuses of motifs at the network level} \source{ Alejandro Espinosa 'netmem' @@ -16,8 +15,6 @@ network_dyad_census(object) network_triad_census(object) network_mixed_census(object, object2) - -network_brokerage_census(object, membership, standardized = FALSE) } \arguments{ \item{object}{An object of a migraph-consistent class: @@ -30,12 +27,6 @@ network_brokerage_census(object, membership, standardized = FALSE) }} \item{object2}{A second, two-mode migraph-consistent object.} - -\item{membership}{A vector of partition membership as integers.} - -\item{standardized}{Whether the score should be standardized -into a \emph{z}-score indicating how many standard deviations above -or below the average the score lies.} } \description{ Censuses of motifs at the network level @@ -49,16 +40,12 @@ Censuses of motifs at the network level \item \code{network_mixed_census()}: Returns a census of triad motifs that span a one-mode and a two-mode network -\item \code{network_brokerage_census()}: Returns the Gould-Fernandez brokerage -roles in a network. - }} \examples{ network_dyad_census(ison_algebra) network_triad_census(ison_adolescents) marvel_friends <- to_unsigned(ison_marvel_relationships, "positive") (mixed_cen <- network_mixed_census(marvel_friends, ison_marvel_teams)) -network_brokerage_census(ison_networkers, "Discipline") } \references{ Davis, James A., and Samuel Leinhardt. 1967. @@ -68,13 +55,10 @@ Hollway, James, Alessandro Lomi, Francesca Pallotti, and Christoph Stadtfeld. 20 “Multilevel Social Spaces: The Network Dynamics of Organizational Fields.” \emph{Network Science} 5(2): 187–212. \doi{10.1017/nws.2017.8} - -Gould, R.V. and Fernandez, R.M. 1989. -“Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks.” -\emph{Sociological Methodology}, 19: 89-126. } \seealso{ Other motifs: +\code{\link{brokerage_census}}, \code{\link{node_census}} } \concept{motifs} diff --git a/man/node_census.Rd b/man/node_census.Rd index 4e928765..e546ad34 100644 --- a/man/node_census.Rd +++ b/man/node_census.Rd @@ -6,7 +6,6 @@ \alias{node_triad_census} \alias{node_quad_census} \alias{node_path_census} -\alias{node_brokerage_census} \title{Censuses of nodes' motifs} \usage{ node_tie_census(object) @@ -16,8 +15,6 @@ node_triad_census(object) node_quad_census(object) node_path_census(object) - -node_brokerage_census(object, membership, standardized = FALSE) } \arguments{ \item{object}{An object of a migraph-consistent class: @@ -102,9 +99,6 @@ in motifs of four nodes. \item \code{node_path_census()}: Returns the shortest path lengths of each node to every other node in the network. -\item \code{node_brokerage_census()}: Returns the Gould-Fernandez brokerage -roles played by nodes in a network. - }} \examples{ task_eg <- to_named(to_uniplex(ison_algebra, "task_tie")) @@ -113,7 +107,6 @@ task_eg <- to_named(to_uniplex(ison_algebra, "task_tie")) node_quad_census(ison_southern_women) node_path_census(ison_adolescents) node_path_census(ison_southern_women) -node_brokerage_census(ison_networkers, "Discipline") } \references{ Davis, James A., and Samuel Leinhardt. 1967. @@ -133,13 +126,10 @@ Opsahl, Tore, Filip Agneessens, and John Skvoretz. 2010. "Node centrality in weighted networks: Generalizing degree and shortest paths". \emph{Social Networks} 32(3): 245-51. \doi{10.1016/j.socnet.2010.03.006}. - -Gould, R.V. and Fernandez, R.M. 1989. -“Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks.” -\emph{Sociological Methodology}, 19: 89-126. } \seealso{ Other motifs: +\code{\link{brokerage_census}}, \code{\link{network_census}} } \concept{motifs} From cacab50164d094e145e4650ef6584a6254aa884d Mon Sep 17 00:00:00 2001 From: James Hollway Date: Wed, 26 Oct 2022 11:41:10 +0200 Subject: [PATCH 3/6] Deleted troublesome COW URLs --- NEWS.md | 1 + R/data_mpn.R | 6 ++---- man/mpn_cow.Rd | 6 ++---- 3 files changed, 5 insertions(+), 8 deletions(-) diff --git a/NEWS.md b/NEWS.md index fbe0047c..b75e3677 100644 --- a/NEWS.md +++ b/NEWS.md @@ -3,6 +3,7 @@ ## Package - Converted 'visualisation' vignette to a learnr tutorial +- Deleted troublesome URLs to correlatesofwar.org - Brokerage census gets their own documentation page # migraph 0.12.3 diff --git a/R/data_mpn.R b/R/data_mpn.R index 5d681f78..89e41a94 100644 --- a/R/data_mpn.R +++ b/R/data_mpn.R @@ -334,8 +334,7 @@ NULL #' \href{https://www.cambridge.org/core/books/multimodal-political-networks/43EE8C192A1B0DCD65B4D9B9A7842128}{\emph{Multimodal Political Networks}}. #' Cambridge University Press. Cambridge University Press. #' @source -#' The Correlates of War Project. 2012. -#' \href{https://correlatesofwar.org/data-sets/bilateral-trade/}{\emph{Trade}}. +#' The Correlates of War Project. 2012. \emph{Trade}. #' #' Barbieri, Katherine and Omar Keshk. 2012. #' Correlates of War Project Trade Data Set Codebook, Version 3.0. @@ -348,8 +347,7 @@ NULL #' @rdname mpn_cow #' @usage data(mpn_cow_igo) #' @source -#' The Correlates of War Project. 2019. -#' \href{https://correlatesofwar.org/data-sets/IGOs/}{\emph{Intergovernmental Organization v3}}. +#' The Correlates of War Project. 2019. \emph{Intergovernmental Organization v3}. #' @references #' Pevehouse, Jon C.W., Timothy Nordstron, Roseanne W McManus, Anne Spencer Jamison. 2020. #' “Tracking Organizations in the World: The Correlates of War IGO Version 3.0 datasets”. diff --git a/man/mpn_cow.Rd b/man/mpn_cow.Rd index 3bc31c8c..09329be8 100644 --- a/man/mpn_cow.Rd +++ b/man/mpn_cow.Rd @@ -56,14 +56,12 @@ }\if{html}{\out{}} } \source{ -The Correlates of War Project. 2012. -\href{https://correlatesofwar.org/data-sets/bilateral-trade/}{\emph{Trade}}. +The Correlates of War Project. 2012. \emph{Trade}. Barbieri, Katherine and Omar Keshk. 2012. Correlates of War Project Trade Data Set Codebook, Version 3.0. -The Correlates of War Project. 2019. -\href{https://correlatesofwar.org/data-sets/IGOs/}{\emph{Intergovernmental Organization v3}}. +The Correlates of War Project. 2019. \emph{Intergovernmental Organization v3}. } \usage{ data(mpn_cow_trade) From 9f179c3b92d0b1157b17bfd3bbcc4244f5447a59 Mon Sep 17 00:00:00 2001 From: James Hollway Date: Wed, 26 Oct 2022 11:41:38 +0200 Subject: [PATCH 4/6] Added rsconnect suggest to fix pkgdown issue --- .github/workflows/pushrelease.yml | 1 + DESCRIPTION | 5 +++-- README.Rmd | 20 ++++++++++++++++++++ README.md | 30 ++++++++++++++++++++++++++++-- 4 files changed, 52 insertions(+), 4 deletions(-) diff --git a/.github/workflows/pushrelease.yml b/.github/workflows/pushrelease.yml index e66d1d92..57ad108f 100644 --- a/.github/workflows/pushrelease.yml +++ b/.github/workflows/pushrelease.yml @@ -165,6 +165,7 @@ jobs: extra-packages: | any::rcmdcheck any::pkgdown + any::rsconnect needs: check - name: Install package diff --git a/DESCRIPTION b/DESCRIPTION index 620246d0..7c194acf 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: migraph Title: Tools for Multimodal Network Analysis -Version: 0.12.3 -Date: 2022-10-25 +Version: 0.12.4 +Date: 2022-10-26 Description: A set of tools for analysing multimodal networks. All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, @@ -49,6 +49,7 @@ Suggests: Rgraphviz, rmarkdown, roxygen2, + rsconnect, testthat Authors@R: c(person(given = "James", diff --git a/README.Rmd b/README.Rmd index 785a8ed8..17812b97 100644 --- a/README.Rmd +++ b/README.Rmd @@ -237,6 +237,26 @@ This gives you access to the compiled vignettes in html form, as well as the original source (an Rmarkdown file), and just the R code without any of the annotations. +### Tutorials + +We are however moving away from the use of vignettes in this package, +in favour of smaller and more interactive `{learnr}` tutorials. +Since version 0.12.3, many of the previous vignettes are instead +available as tutorials, more will be converted soon, +and those that have been converted will continue to be updated and enriched. + +To access the tutorials, you will need to have the additional package `{learnr}` installed: +`install.packages("learnr")`. +Then we would first suggest that you check to see which vignettes are currently available: + +```{r learnr-tutes} +learnr::available_tutorials("migraph") +``` + +You can then choose to begin a tutorial using the following command: e.g. +`learnr::run_tutorial("equivalence", "migraph")`. +For more details on the `{learnr}` package, see [here](https://rstudio.github.io/learnr/). + ## Relationship to other packages It draws together, updates, and builds upon many functions currently available in diff --git a/README.md b/README.md index 1cff254f..b9eea27c 100644 --- a/README.md +++ b/README.md @@ -161,8 +161,9 @@ function names wherever possible. #### Motifs -- Censuses: `node_path_census()`, `node_quad_census()`, - `node_tie_census()`, `node_triad_census()`, `network_dyad_census()`, +- Censuses: `node_brokerage_census()`, `node_path_census()`, + `node_quad_census()`, `node_tie_census()`, `node_triad_census()`, + `network_brokerage_census()`, `network_dyad_census()`, `network_mixed_census()`, `network_triad_census()` #### Models @@ -250,6 +251,31 @@ This gives you access to the compiled vignettes in html form, as well as the original source (an Rmarkdown file), and just the R code without any of the annotations. +### Tutorials + +We are however moving away from the use of vignettes in this package, in +favour of smaller and more interactive `{learnr}` tutorials. Since +version 0.12.3, many of the previous vignettes are instead available as +tutorials, more will be converted soon, and those that have been +converted will continue to be updated and enriched. + +To access the tutorials, you will need to have the additional package +`{learnr}` installed: `install.packages("learnr")`. Then we would first +suggest that you check to see which vignettes are currently available: + +``` r +learnr::available_tutorials("migraph") +#> Available tutorials: +#> * migraph +#> - community : "Equivalence" +#> - equivalence : "Equivalence" +``` + +You can then choose to begin a tutorial using the following command: +e.g. `learnr::run_tutorial("equivalence", "migraph")`. For more details +on the `{learnr}` package, see +[here](https://rstudio.github.io/learnr/). + ## Relationship to other packages It draws together, updates, and builds upon many functions currently From 5a40acfa8e7f1a9713cfc06c95e7240510cfc640 Mon Sep 17 00:00:00 2001 From: James Hollway Date: Wed, 26 Oct 2022 12:17:42 +0200 Subject: [PATCH 5/6] Moved extra arguments from node_census to brokerage_census --- R/motif_census.R | 8 ++++---- man/node_census.Rd | 6 ------ man/reexports.Rd | 2 +- 3 files changed, 5 insertions(+), 11 deletions(-) diff --git a/R/motif_census.R b/R/motif_census.R index 28669605..f5c38e25 100644 --- a/R/motif_census.R +++ b/R/motif_census.R @@ -9,10 +9,6 @@ #' @name node_census #' @family motifs #' @inheritParams is -#' @param membership A vector of partition membership as integers. -#' @param standardized Whether the score should be standardized -#' into a _z_-score indicating how many standard deviations above -#' or below the average the score lies. #' @importFrom igraph vcount graph.neighborhood delete_vertices triad_census NULL @@ -317,6 +313,10 @@ network_mixed_census <- function (object, object2) { #' @name brokerage_census #' @family motifs #' @inheritParams node_census +#' @param membership A vector of partition membership as integers. +#' @param standardized Whether the score should be standardized +#' into a _z_-score indicating how many standard deviations above +#' or below the average the score lies. NULL #' @describeIn brokerage_census Returns the Gould-Fernandez brokerage diff --git a/man/node_census.Rd b/man/node_census.Rd index e546ad34..a65bbd08 100644 --- a/man/node_census.Rd +++ b/man/node_census.Rd @@ -25,12 +25,6 @@ node_path_census(object) \item network, from the \code{{network}} package \item tbl_graph, from the \code{{tidygraph}} package }} - -\item{membership}{A vector of partition membership as integers.} - -\item{standardized}{Whether the score should be standardized -into a \emph{z}-score indicating how many standard deviations above -or below the average the score lies.} } \description{ These functions include ways to take a census of the positions of nodes diff --git a/man/reexports.Rd b/man/reexports.Rd index 435fd39a..4f385d74 100644 --- a/man/reexports.Rd +++ b/man/reexports.Rd @@ -40,7 +40,7 @@ below to see their documentation. \item{ggplot2}{\code{\link[ggplot2]{aes}}, \code{\link[ggplot2]{ggplot}}, \code{\link[ggplot2]{ggsave}}, \code{\link[ggplot2:labs]{ggtitle}}, \code{\link[ggplot2]{labs}}, \code{\link[ggplot2:labs]{xlab}}, \code{\link[ggplot2:labs]{ylab}}} - \item{igraph}{\code{\link[igraph:make_bipartite_graph]{is_bipartite}}, \code{\link[igraph:is_igraph]{is.igraph}}} + \item{igraph}{\code{\link[igraph:is_igraph]{is.igraph}}, \code{\link[igraph:make_bipartite_graph]{is_bipartite}}} \item{network}{\code{\link[network:network]{as.network}}, \code{\link[network:network]{is.network}}} From f32757e72b618c77affd0cc62dd65ef602b5ca5a Mon Sep 17 00:00:00 2001 From: James Hollway Date: Wed, 26 Oct 2022 13:54:19 +0200 Subject: [PATCH 6/6] Updated community documentation a little --- R/member_community.R | 32 +++++++++++++++++++++++++++++--- man/community.Rd | 41 ++++++++++++++++++++++++++++++++++++++--- 2 files changed, 67 insertions(+), 6 deletions(-) diff --git a/R/member_community.R b/R/member_community.R index b23b1367..db7d64c0 100644 --- a/R/member_community.R +++ b/R/member_community.R @@ -62,7 +62,12 @@ node_kernighanlin <- function(object){ make_node_member(out, object) } -#' @describeIn community The walktrap algorithm +#' @describeIn community A hierarchical, agglomerative algorithm based on random walks. +#' @section Walktrap: +#' The general idea is that random walks on a network are more likely to stay +#' within the same community because few edges lead outside a community. +#' By repeating random walks of 4 steps many times, +#' information about the hierarchical merging of communities is collected. #' @param times Integer indicating number of simulations/walks used. #' By default, `times=50`. #' @examples @@ -75,7 +80,19 @@ node_walktrap <- function(object, times = 50){ } -#' @describeIn community The edge-betweenness algorithm +#' @describeIn community A hierarchical, decomposition algorithm +#' where edges are removed in decreasing order of the number of +#' shortest paths passing through the edge, +#' resulting in a hierarchical representation of group membership. +#' @section Edge-betweenness: +#' This is motivated by the idea that edges connecting different groups +#' are more likely to lie on multiple shortest paths when they are the +#' only option to go from one group to another. +#' This method yields good results but is very slow because of +#' the computational complexity of edge-betweenness calculations and +#' the betweenness scores have to be re-calculated after every edge removal. +#' Networks of ~700 nodes and ~3500 ties are around the upper size limit +#' that are feasible with this approach. #' @examples #' node_edge_betweenness(ison_adolescents) #' @export @@ -86,7 +103,16 @@ node_edge_betweenness <- function(object){ } -#' @describeIn community The fast-greedy algorithm +#' @describeIn community A hierarchical, agglomerative algorithm, +#' that tries to optimize modularity in a greedy manner. +#' @section Fast-greedy: +#' Initially, each node is assigned a separate community. +#' Communities are then merged iteratively such that each merge +#' yields the largest increase in the current value of modularity, +#' until no further increases to the modularity are possible. +#' The method is fast and recommended as a first approximation +#' because it has no parameters to tune. +#' However, it is known to suffer from a resolution limit. #' @examples #' node_fast_greedy(ison_adolescents) #' @export diff --git a/man/community.Rd b/man/community.Rd index c930a0dd..f66deafd 100644 --- a/man/community.Rd +++ b/man/community.Rd @@ -38,13 +38,48 @@ Community graph partitioning algorithms partitioning algorithm that results in a graph with two equally-sized communities -\item \code{node_walktrap()}: The walktrap algorithm +\item \code{node_walktrap()}: A hierarchical, agglomerative algorithm based on random walks. -\item \code{node_edge_betweenness()}: The edge-betweenness algorithm +\item \code{node_edge_betweenness()}: A hierarchical, decomposition algorithm +where edges are removed in decreasing order of the number of +shortest paths passing through the edge, +resulting in a hierarchical representation of group membership. -\item \code{node_fast_greedy()}: The fast-greedy algorithm +\item \code{node_fast_greedy()}: A hierarchical, agglomerative algorithm, +that tries to optimize modularity in a greedy manner. }} +\section{Walktrap}{ + +The general idea is that random walks on a network are more likely to stay +within the same community because few edges lead outside a community. +By repeating random walks of 4 steps many times, +information about the hierarchical merging of communities is collected. +} + +\section{Edge-betweenness}{ + +This is motivated by the idea that edges connecting different groups +are more likely to lie on multiple shortest paths when they are the +only option to go from one group to another. +This method yields good results but is very slow because of +the computational complexity of edge-betweenness calculations and +the betweenness scores have to be re-calculated after every edge removal. +Networks of ~700 nodes and ~3500 ties are around the upper size limit +that are feasible with this approach. +} + +\section{Fast-greedy}{ + +Initially, each node is assigned a separate community. +Communities are then merged iteratively such that each merge +yields the largest increase in the current value of modularity, +until no further increases to the modularity are possible. +The method is fast and recommended as a first approximation +because it has no parameters to tune. +However, it is known to suffer from a resolution limit. +} + \examples{ node_kernighanlin(ison_adolescents) node_kernighanlin(ison_southern_women)