Merge pull request #4 from onnela-lab/update

Bump package versions.

.gitignore

@@ -3,6 +3,7 @@ __pycache__
 .DS_Store
 .ipynb_checkpoints
 .Rhistory
+.vscode
 *.hpp
 *.html
 *.o

Dockerfile

@@ -11,4 +11,4 @@ RUN Rscript setup.R
 # Install Python dependencies and compile cmdstan.
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
-RUN python -m cmdstanpy.install_cmdstan --verbose --version 2.33.0
+RUN python -m cmdstanpy.install_cmdstan --verbose --version 2.36.0

getting_started/getting_started.Rmd

@@ -4,9 +4,9 @@ rendering the Rmarkdown.
 ```{r}
 install.packages(
   "cmdstanr",
-  repos = c("https://mc-stan.org/r-packages/", "http://cran.us.r-project.org")
+  repos = c("https://stan-dev.r-universe.dev", "http://cran.us.r-project.org")
 )
-install.packages("gptoolsStan", repos=c("http://cran.us.r-project.org"))
+install.packages("gptoolsStan", repos = c("http://cran.us.r-project.org"))
 ```
 
 Compile and run the model.
@@ -16,14 +16,14 @@ library(cmdstanr)
 library(gptoolsStan)
 
 model <- cmdstan_model(
-  stan_file="getting_started.stan",
-  include_paths=gptools_include_path(),
+  stan_file = "getting_started.stan",
+  include_paths = gptools_include_path(),
 )
 fit <- model$sample(
-  data=list(n=100, sigma=1, length_scale=0.1, period=1),
-  chains=1,
-  iter_warmup=500,
-  iter_sampling=50
+  data = list(n = 100, sigma = 1, length_scale = 0.1, period = 1),
+  chains = 2,
+  iter_warmup = 500,
+  iter_sampling = 50
 )
 f <- fit$draws("f")
 dim(f)