Lint code

.github/workflows/pkgdown.yaml

@@ -12,7 +12,7 @@ on:
 name: pkgdown
 
 jobs:
-  distribution-check:
+  pkgdown:
     runs-on: ubuntu-latest
     container:
       image: fedora:latest
@@ -48,7 +48,7 @@ jobs:
       run: |
         devtools::document()
         devtools::load_all()
-        pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE)
+        pkgdown::build_site_github_pages(new_process = FALSE, install = TRUE)
         pkgdown::build_reference(topics = 'random_walk')
       shell: Rscript {0}
 

DESCRIPTION

@@ -4,10 +4,9 @@ Title: Labyrinth: A Simulation of Knowledge Networks
 Version: 0.3.0
 Date: 2023-12-31
 Authors@R: c(
-    person("Yinchun","Su", role = c("aut", "cre"),
-      email = "[email protected]"),
-    person("Junwei", "Han", role = "ctb",
-      email = "[email protected]"))
+    person("Junwei","Han", role = c("aut", "cre", "ctb"),
+      email = "[email protected]"),
+    person("Yinchun", "Su", role = "aut")
 Maintainer: Junwei Han <[email protected]>
 Description: One paragraph description of what the package does
        as one or more full sentences. I can use Config/testthat/parallel as 

NEWS.md

@@ -1,3 +1,7 @@
+## labyrinth v0.3.0
+
+* Updated docs
+
 ## labyrinth v0.2.3
 
 * Added `predict()` function
@@ -51,4 +55,3 @@
 ## labyrinth v0.0.1
 
 * Initial submission
-

R/data.R

@@ -358,4 +358,3 @@
 #' drug_id <- drug_annot$drug_id
 #' hist(table(drug_id))
 "drug_annot"
-

R/utils.R

@@ -165,7 +165,7 @@ load_data <- function(required_file) {
   user_dir <- R_user_dir("labyrinth", which = "data")
   model_path <- file.path(user_dir, required_file)
   data_path <- system.file("extdata", required_file, package = "labyrinth")
-  
+
   e <- new.env()
   if (file.exists(data_path)) {
     load(data_path, envir = e)
@@ -189,7 +189,7 @@ load_data <- function(required_file) {
       }
     }
   }
-  
+
   variable_name <- ls(envir = e)
   return(e[[variable_name[1]]])
 }

README.md

@@ -31,12 +31,12 @@ I developed and tested `labyrinth` on Fedora Linux version 38 and 39. While this
 
 We recommended these dependencies to be installed:
 
-- **R (≥ 4.3.0)**: We developed this R package using R version 4.3.3.
+- **R (≥ 4.3.0)**: We developed this R package using R version 4.3.x.
 - **Python**: Python is required for drawing plots in demos. It is recommended to have Python and `seaborn` installed, as the `reticulate` package will use the system's Python installation.
 - **OpenMP**: This package uses OpenMP for parallelization and multithreading if OpenMP exists. Having OpenMP installed can significantly improve performance.
 - **Intel oneAPI Math Kernel Library (oneMKL)**: This library can further enhance mathematical performance, especially on Intel processors. oneMKL is not required but highly recommended.
 
-It would takes less than ten minutes to install this package. If you encounter any issues while running this package on other operating system, please open an [issue](https://github.com/randef1ned/labyrinth/issues).
+It would takes less than ten minutes to install this package. If you encounter any issues while running this package on other operating system, please open an issue.
 
 
 ## Before installation
@@ -98,7 +98,7 @@ Or you can download the pre-built binary packages from [Releases](https://github
 
 ## Usage
 
-Load the package using `library(labyrinth)`. We provide a vignette for the package that can be called using: `vignette("labyrinth")`. Alternatively, you can view the online version on [website](https://labyrinth.yinchun.su/articles/labyrinth) or [GitHub](doc/labyrinth_knit.md). The examples I provided would take several minutes to run on a normal desktop computer. Basically that is all you have to know.
+Load the package using `library(labyrinth)`. We provide a vignette for the package that can be called using: `vignette("labyrinth")`. Alternatively, you can view the online version on [GitHub](doc/labyrinth_knit.md), or [`pkgdown` documentation](https://labyrinth.yinchun.su/articles/labyrinth). The examples I provided would take several minutes to run on a normal desktop computer. Basically that is all you have to know.
 
 [This documentation](doc/training_knit.md) contains information about the contents and the necessary information for training the model used in this project. The `tools/` folder contains all the code and scripts required for constructing your own model, so that you can understand the technical details. Besides, you can refer to [this documentation](doc/preface_knit.md) for the background and inspirations behind the overall workflow of `labyrinth.
 

doc/labyrinth_knit.md

@@ -15,11 +15,11 @@ WSL](https://github.com/WhitewaterFoundry/Fedora-Remix-for-WSL).
 
 To get started, you will need to prepare the following dependencies.
 
-1.  **Fedora** or **Red Hat Enterprise Linux** with or without WSL.
+1. **Fedora** or **Red Hat Enterprise Linux** with or without WSL.
 
-2.  **R 4.3**.
+2. **R 4.3**.
 
-3.  **Required libraries**.
+3. **Required libraries**.
 
 ``` r
 # pROC ggthemes 
@@ -225,11 +225,7 @@ p1 + p2 + plot_layout(guides = 'collect') +
   theme(legend.position = 'bottom')
 ```
 
-<div class="figure">
-
-<img src="img/unnamed-chunk-5-1.png" />
-</div>
-![](img/unnamed-chunk-5-1.png)
+![Figure 3](../vignettes/img/unnamed-chunk-5-1.png)
 
 ### Reproducibility statement
 

doc/preface_knit.md

@@ -530,7 +530,7 @@ fields, which is defined as the number of articles retrieved using
 
 <div class="figure">
 
-<img src="img/banana.png" alt="\label{fig:banana}**Bibliometric analysis for drug repurposing. **Drug repurposing gains significant attention since 2010. We adopted banana scale to depict this trend." width="100%" />
+<img src="../vignettes/img/banana.png" alt="\label{fig:banana}**Bibliometric analysis for drug repurposing. **Drug repurposing gains significant attention since 2010. We adopted banana scale to depict this trend." width="100%" />
 <p class="caption">
 **Bibliometric analysis for drug repurposing. **Drug repurposing gains
 significant attention since 2010. We adopted banana scale to depict this