Updating news and minor updates to README.md

UofUEpiBio · Jun 11, 2024 · 5931ee8 · 5931ee8
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diff --git a/NEWS.md b/NEWS.md
@@ -1,5 +1,7 @@
 # epiworldR 0.3-0 (dev)
 
+* Starting version 0.3-0, `epiworldR` is versioned using the same version as the C++ library, `epiworld`.
+
 * Adds the new mixing models `ModelSIRMixing` and `ModelSEIRMixing`.
 
 * Ports the `Entity` class. Entities are used to group agents within a model.

diff --git a/README.Rmd b/README.Rmd
@@ -62,10 +62,10 @@ install.packages("epiworldR")
 
 # Examples
 
-This R package includes several popular epidemiological models including
+This R package includes several popular epidemiological models, including
 [SIS](https://en.wikipedia.org/w/index.php?title=Compartmental_models_in_epidemiology&oldid=1155757336#Variations_on_the_basic_SIR_model){target="_blank"},
 [SIR](https://en.wikipedia.org/w/index.php?title=Compartmental_models_in_epidemiology&oldid=1155757336#The_SIR_model){target="_blank"}, and
-[SEIR](https://en.wikipedia.org/w/index.php?title=Compartmental_models_in_epidemiology&oldid=1155757336#The_SEIR_model){target="_blank"} using either a fully connected graph (similar to a compartmental model) or a user-defined network. Here are some examples:
+[SEIR](https://en.wikipedia.org/w/index.php?title=Compartmental_models_in_epidemiology&oldid=1155757336#The_SEIR_model){target="_blank"} using either a fully connected graph (similar to a compartmental model) or a user-defined network.
 
 ## SIR model using a random graph
 
@@ -274,9 +274,9 @@ citation("epiworldR")
 
 # Existing Alternatives
 
-Several alternatives to `epiworldR` exist and provide researchers with a range of options, each with its own unique features and strengths, enabling the exploration and analysis of infectious disease dynamics through agent-based modeling. Below is a manually curated table of existing alternatives including ABM [@ABM], abmR [@abmR], cystiSim [@cystiSim], villager [@villager], and RNetLogo [@RNetLogo].
+Several alternatives to `epiworldR` exist and provide researchers with a range of options, each with its own unique features and strengths, enabling the exploration and analysis of infectious disease dynamics through agent-based modeling. Below is a manually curated table of existing alternatives, including ABM [@ABM], abmR [@abmR], cystiSim [@cystiSim], villager [@villager], and RNetLogo [@RNetLogo].
 
-| Package                                                                     | Multiple Viruses | Multiple Tools | Multiple Runs | Global Actions | Built-In Epi Models | Dependencies                                                                                             | Activity                                                                                                               |
+| Package                                                                     | Multiple Viruses | Multiple Tools | Multiple Runs | Global Actions | Built-In Epi Models |  Dependencies                                                                                             | Activity                                                                                                               |
 |:--------|:--------|:--------|:--------|:--------|---------|:--------|:--------|
 | [**epiworldR**](https://cran.r-project.org/package=epiworldR)               | yes              | yes            | yes           | yes            | yes                 | [![status](https://tinyverse.netlify.com/badge/epiworldR)](https://CRAN.R-project.org/package=epiworldR) | [![Activity](https://img.shields.io/github/last-commit/UofUEpiBio/epiworldR)](https://github.com/UofUEpiBio/epiworldR) |
 | [**ABM**](https://cran.r-project.org/package=ABM)                           | \-               | \-             | \-            | yes            | yes                 | [![status](https://tinyverse.netlify.com/badge/ABM)](https://CRAN.R-project.org/package=ABM)             | [![Activity](https://img.shields.io/github/last-commit/junlingm/ABM)](https://github.com/junlingm/ABM)                 |
@@ -296,4 +296,4 @@ You may want to check out other R packages for agent-based modeling: [`ABM`](htt
 
 ## Code of Conduct
 
-Please note that the epiworldR project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
+The epiworldR project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
diff --git a/README.md b/README.md
@@ -78,16 +78,15 @@ install.packages("epiworldR")
 
 # Examples
 
-This R package includes several popular epidemiological models including
-<a
+This R package includes several popular epidemiological models,
+including <a
 href="https://en.wikipedia.org/w/index.php?title=Compartmental_models_in_epidemiology&amp;oldid=1155757336#Variations_on_the_basic_SIR_model"
 target="_blank">SIS</a>, <a
 href="https://en.wikipedia.org/w/index.php?title=Compartmental_models_in_epidemiology&amp;oldid=1155757336#The_SIR_model"
 target="_blank">SIR</a>, and <a
 href="https://en.wikipedia.org/w/index.php?title=Compartmental_models_in_epidemiology&amp;oldid=1155757336#The_SEIR_model"
 target="_blank">SEIR</a> using either a fully connected graph (similar
-to a compartmental model) or a user-defined network. Here are some
-examples:
+to a compartmental model) or a user-defined network.
 
 ## SIR model using a random graph
 
@@ -141,8 +140,8 @@ summary(sir)
 #> Number of entities  : 0
 #> Days (duration)     : 50 (of 50)
 #> Number of viruses   : 1
-#> Last run elapsed t  : 165.00ms
-#> Last run speed      : 30.23 million agents x day / second
+#> Last run elapsed t  : 153.00ms
+#> Last run speed      : 32.61 million agents x day / second
 #> Rewiring            : off
 #> 
 #> Global events:
@@ -229,8 +228,8 @@ summary(model_seirconn)
 #> Number of entities  : 0
 #> Days (duration)     : 100 (of 100)
 #> Number of viruses   : 2
-#> Last run elapsed t  : 39.00ms
-#> Last run speed      : 25.12 million agents x day / second
+#> Last run elapsed t  : 40.00ms
+#> Last run speed      : 24.55 million agents x day / second
 #> Rewiring            : off
 #> 
 #> Global events:
@@ -537,7 +536,7 @@ Several alternatives to `epiworldR` exist and provide researchers with a
 range of options, each with its own unique features and strengths,
 enabling the exploration and analysis of infectious disease dynamics
 through agent-based modeling. Below is a manually curated table of
-existing alternatives including ABM \[@ABM\], abmR \[@abmR\], cystiSim
+existing alternatives, including ABM \[@ABM\], abmR \[@abmR\], cystiSim
 \[@cystiSim\], villager \[@villager\], and RNetLogo \[@RNetLogo\].
 
 | Package                                                       | Multiple Viruses | Multiple Tools | Multiple Runs | Global Actions | Built-In Epi Models | Dependencies                                                                                             | Activity                                                                                                               |
@@ -565,7 +564,6 @@ target="_blank"><code>RNetLogo</code></a>.
 
 ## Code of Conduct
 
-Please note that the epiworldR project is released with a [Contributor
-Code of
+The epiworldR project is released with a [Contributor Code of
 Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html).
 By contributing to this project, you agree to abide by its terms.