v1.6.4

.github/pull_request_template.md

@@ -4,7 +4,6 @@
 
 - Documentation
   - [ ] DESCRIPTION file version is bumped by the appropriate increment (major, minor, patch)
-  - [ ] Date in DESCRIPTION is correct
   - [ ] Longer functions are commented inline or broken down into helper functions to help debugging
 - PR form
   - [ ] Title indicates expected version number

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: migraph
 Title: Inferential Methods for Multimodal and Other Networks 
-Version: 1.6.3
+Version: 1.6.4
 Description: A set of tools for testing networks.
    It includes functions for univariate and multivariate 
    conditional uniform graph and quadratic assignment procedure testing,
@@ -19,7 +19,7 @@ Encoding: UTF-8
 LazyData: true
 Depends:
     R (>= 4.1.0),
-    manynet (>= 2.0.0),
+    manynet (>= 2.1.2),
     autograph (>= 0.4.0),
     netrics
 Imports: 

NEWS.md

@@ -1,3 +1,13 @@
+# migraph 1.6.4
+
+2026-06-22
+
+## Package
+
+- Updated manynet dependency to 1.2.1 to fix reverse dependency issue
+- Updated pull request template
+- Updated README to make reference to `{netrics}` too
+
 # migraph 1.6.3
 
 2026-06-19

README.Rmd

@@ -78,7 +78,7 @@ The package is intended as a software companion to the book:
 Cambridge University Press: Cambridge.
 
 Most datasets used in the book are included in this package,
-and `{manynet}` and `{migraph}` together implement most methods discussed in the book.
+and `{manynet}`, `{netrics}`, and `{migraph}` together implement most methods discussed in the book.
 Since many of theses datasets and routines are discussed and analysed more there,
 if you like the package(s) please check out the book, and vice versa.
 
@@ -181,6 +181,11 @@ other excellent R packages such as
 [`{tnet}`](https://toreopsahl.com/tnet/),
 and [`{xUCINET}`](https://sites.google.com/view/asnr-2022/xucinet?authuser=0).
 
+As one of the stocnet packages, `{migraph}` is designed to work seamlessly with the other stocnet packages,
+including [`{manynet}`](https://stocnet.github.io/manynet/), 
+[`{autograph}`](https://stocnet.github.io/autograph/), and
+[`{netrics}`](https://stocnet.github.io/netrics/).
+
 ## Funding details
 
 Most work on this package has been funded by the Swiss National Science Foundation (SNSF)

README.md

@@ -70,10 +70,10 @@ The package is intended as a software companion to the book:
 > Cambridge University Press: Cambridge.
 
 Most datasets used in the book are included in this package, and
-`{manynet}` and `{migraph}` together implement most methods discussed in
-the book. Since many of theses datasets and routines are discussed and
-analysed more there, if you like the package(s) please check out the
-book, and vice versa.
+`{manynet}`, `{netrics}`, and `{migraph}` together implement most
+methods discussed in the book. Since many of theses datasets and
+routines are discussed and analysed more there, if you like the
+package(s) please check out the book, and vice versa.
 
 ## How does migraph help?
 
@@ -82,8 +82,7 @@ conditional uniform graph (CUG) or quadratic assignment procedure (QAP)
 distributions using:
 
 - `test_configuration()`, `test_distribution()`, `test_fit()`,
-  `test_gof()`, `test_permutation()`, `test_random()`,
-  `test_tutorials()`
+  `test_gof()`, `test_permutation()`, `test_random()`
 
 <img src="https://www.jameshollway.com/post/migraph/tests-2.png" alt="Plot showing the results of a QAP test"/>
 
@@ -109,21 +108,7 @@ package:
 ``` r
 library(migraph)
 run_tute()
-#> Checking tutorials in stocnet packages ■■■■■■■■■■■ 33% | …
-#> # A tibble: 10 × 3
-#>    package   name      title                   
-#>    <chr>     <chr>     <chr>                   
-#>  1 manynet   tutorial0 Intro to R              
-#>  2 manynet   tutorial1 Data                    
-#>  3 autograph tutorial2 Visualisation           
-#>  4 manynet   tutorial3 Centrality              
-#>  5 manynet   tutorial4 Cohesion and Community  
-#>  6 manynet   tutorial5 Position and Equivalence
-#>  7 manynet   tutorial6 Topology and Resilience 
-#>  8 migraph   tutorial7 Diffusion and Learning  
-#>  9 migraph   tutorial8 Diversity and Regression
-#> 10 migraph   tutorial9 Modelling with ERGMs
-#> ℹ You can run a tutorial by typing e.g `run_tute('tutorial1')` or `run_tute('Data')` into the console.
+#> # A tibble: 0 × 0
 # run_tute("tutorial5")
 ```
 
@@ -198,6 +183,12 @@ currently available in other excellent R packages such as
 [`{tnet}`](https://toreopsahl.com/tnet/), and
 [`{xUCINET}`](https://sites.google.com/view/asnr-2022/xucinet?authuser=0).
 
+As one of the stocnet packages, `{migraph}` is designed to work
+seamlessly with the other stocnet packages, including
+[`{manynet}`](https://stocnet.github.io/manynet/),
+[`{autograph}`](https://stocnet.github.io/autograph/), and
+[`{netrics}`](https://stocnet.github.io/netrics/).
+
 ## Funding details
 
 Most work on this package has been funded by the Swiss National Science

cran-comments.md

@@ -1,12 +1,12 @@
 ## Test environments
 
-* local R installation, aarch64-apple-darwin20, R 4.5.1
-* macOS 14.7.6 (on Github), R 4.5.1
-* Microsoft Windows Server 2022 10.0.20348 (on Github), R 4.5.1
-* Ubuntu 24.04.2 (on Github), R 4.5.1
+* local R installation, aarch64-apple-darwin23, R 4.6.0
+* macOS 15.7.7 (on Github), R 4.6.0
+* Microsoft Windows Server 2025 10.0.26100 (on Github), R 4.6.0
+* Ubuntu 24.04.4 (on Github), R 4.6.0
 
 ## R CMD check results
 
 0 errors | 0 warnings | 0 notes
 
-- Fixes reverse dependency issues for 'manynet' (and 'netrics')
+- Updated manynet dependency to 1.2.1 to fix reverse dependency issue