Applying refactoring

.devcontainer/.vscode/settings.json

@@ -0,0 +1,4 @@
+{
+    "r.plot.useHttpgd": true,
+    "r.alwaysUseActiveTerminal": true
+}

.devcontainer/Dockerfile

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+FROM rocker/tidyverse:4.4.0
+
+# RUN \
+#   echo 'options(repos=c(CRAN="https://packagemanager.posit.co/cran/__linux__/bookworm/latest"))' >> ~/.Rprofile && \
+#   Rscript --vanilla -e 'getOption("repos")'
+
+# Adding R packages
+RUN install2.r Rcpp sna network networkDynamic Matrix MASS MatchIt SparseM igraph \
+  viridisLite covr testthat knitr rmarkdown ape RSiena survival RcppArmadillo
+
+RUN install2.r languageserver httpgd
+
+RUN apt-get update && apt-get install --no-install-recommends -y valgrind gdb \
+  libglpk-dev
+
+RUN Rscript --vanilla -e \
+  'remotes::install_github("USCCANA/netdiffuseR@gvegayon-preparing-release-connections")'
+
+CMD ["bash"]

.devcontainer/devcontainer.json

@@ -0,0 +1,36 @@
+// For format details, see https://aka.ms/devcontainer.json. For config options, see the
+// README at: https://github.com/devcontainers/templates/tree/main/src/cpp
+{
+	"name": "epiworldR",
+	"build": {
+		"dockerfile": "Dockerfile"
+	},
+	"customizations": {
+		"vscode": {
+			"extensions": [
+				"reditorsupport.r",
+				"rdebugger.r-debugger",
+				"quarto.quarto",
+				"tianyishi.rmarkdown"
+			]
+		}
+	},
+	"mounts": [
+        // Mount the .vscode configuration into the container
+        "source=${localWorkspaceFolder}/.devcontainer/.vscode,target=/workspaces/${localWorkspaceFolderBasename}/.vscode,type=bind,consistency=cached"
+    ]
+	// Features to add to the dev container. More info: https://containers.dev/features.
+	// "features": {},
+
+	// Use 'forwardPorts' to make a list of ports inside the container available locally.
+	// "forwardPorts": [],
+
+	// Use 'postCreateCommand' to run commands after the container is created.
+	// "postCreateCommand": "gcc -v",
+
+	// Configure tool-specific properties.
+	// "customizations": {},
+
+	// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
+	// "remoteUser": "root"
+}

.gitignore

@@ -1,6 +1,10 @@
 *_cache/
 *_files/
 .Rproj.user
+.Rhistory
+.DS_Store
+*/.DS_Store
+**/.DS_Store
 
 /.quarto/
 docs/

0-netdiffuser.qmd

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+---
+title: "Introduction to the package"
+author: "George G. Vega Yon and Aníbal Olivera M."
+date: "2025-06-24"
+date-modified: "2025-06-24"
+---
+
+```{r setup, echo=FALSE, message=FALSE, warning=FALSE}
+library(netdiffuseR)
+knitr::opts_chunk$set(comment = "#")
+```
+
+
+-   **Network thresholds** (Valente, 1995; 1996), $\tau$, are defined as the required proportion or number of neighbors that leads you to adopt a particular behavior (innovation), $a=1$. In (very) general terms\pause
+
+$$
+  a_i = \left\{\begin{array}{ll}
+  1 &\mbox{if } \tau_i\leq E_i \\
+  0 & \mbox{Otherwise}
+  \end{array}\right. \qquad
+  E_i \equiv \frac{\sum_{j\neq i}\mathbf{X}_{ij}a_j}{\sum_{j\neq i}\mathbf{X}_{ij}}
+$$
+
+Where $E_i$ is i's exposure to the innovation and $\mathbf{X}$ is the adjacency matrix (the network).
+
+-   This can be generalized and extended to include covariates and other network weighting schemes (that's what __netdiffuseR__ is all about).
+
+# netdiffuseR
+
+-   **netdiffuseR** is an R package that:
+
+    -   Allow to generalize the network threshold concept to include covariates and other network weighting schemes.
+
+    -   Is designed for Visualizing, Analyzing and Simulating network diffusion data (in general).
+
+    -   Depends on some pretty popular packages:
+
+        - _RcppArmadillo_: So it's fast,
+        - _Matrix_: So it's big,
+        - _statnet_ and _igraph_: So it's not from scratch
+
+    -   Can handle big graphs, e.g., an adjacency matrix with more than 4 billion elements (PR for RcppArmadillo).
+
+    -   Already on CRAN with +48,000 downloads since its first version, Feb 2016.
+
+    <!-- Can simulate Threshold Diffusion Models (also know as Complex Contagion) in different scenarios, including multiple simulations at once, multi-diffusion settings, and disadoption parameters. -->
+
+- **Datasets**
+
+    -   **netdiffuseR** has the three classic Diffusion Network Datasets, both as surveys:
+
+        -   `medInnovations` Doctors and the innovation of Tetracycline (1955),
+        -   `brfarmers` Brazilian farmers and the innovation of Hybrid Corn Seed (1966),
+        -   `kfamily` Korean women and Family Planning methods (1973),
+
+        and as `diffnet` objects:
+
+        -   `medInnovationsDiffNet` Doctors and the innovation of Tetracycline (1955),
+        -   `brfarmersDiffNet` Brazilian farmers and the innovation of Hybrid Corn Seed (1966),
+        -   `kfamilyDiffNet` Korean women and Family Planning methods (1973)
+
+        ```{r printing}
+        brfarmersDiffNet
+        medInnovationsDiffNet
+        kfamilyDiffNet
+        ```