fix: restore LICENSE stub and install funz-fz in R-CMD-check CI

.github/workflows/R-CMD-check.yaml

@@ -41,6 +41,16 @@ jobs:
           extra-packages: any::rcmdcheck
           needs: check
 
+      - uses: actions/setup-python@v5
+        with:
+          python-version: '3.x'
+
+      - name: Install fz Python package
+        run: pip install funz-fz
+
+      - name: Point reticulate at the CI Python
+        run: echo "RETICULATE_PYTHON=$(python3 -c 'import sys; print(sys.executable)')" >> "$GITHUB_ENV"
+
       - uses: r-lib/actions/check-r-package@v2
         with:
           upload-snapshots: true

LICENSE

@@ -0,0 +1,3 @@
+YEAR: 2025
+ORGANIZATION: Funz
+COPYRIGHT HOLDER: Funz

NEWS.md

@@ -14,6 +14,17 @@
   regardless of `calculators`.
 * `fz_install()` gains a `packages` argument (default `"funz-fz"`) so the
   latest `main` branch can be installed instead of the PyPI release.
+* Fixed `fzd()`'s own `algorithm_options` example/documentation, which used
+  a `"key=val;key2=val2"` string that `funz-fz` has never actually accepted
+  (only a named list, JSON string, or path to a JSON file) — replaced with
+  a named list. CI never caught this because it was silently exercising the
+  wrong Python module (see CI fixes below).
+* Restored the `LICENSE` file (the templated file R's packaging convention
+  requires alongside `License: BSD_3_clause + file LICENSE`), which had been
+  mistakenly deleted, and fixed `R-CMD-check` CI to install `funz-fz` and
+  point `reticulate` at it via `RETICULATE_PYTHON` — without this,
+  `reticulate`'s automatic environment provisioning was silently resolving
+  to an unrelated PyPI package literally named `fz` (not `funz-fz`).
 
 # fz 1.1
 

R/core-functions.R

@@ -202,9 +202,8 @@ fzl <- function(models = "*", calculators = "*", check = FALSE) {
 #'   \code{model} is a function, this must be a single integer (default
 #'   \code{1L}), accepted for API compatibility (see "Direct function model"
 #'   below) — calls are always run sequentially regardless of its value.
-#' @param algorithm_options Algorithm options as a named list or
-#'   semicolon-separated string, e.g. \code{"batch_sample_size=10;seed=42"}.
-#'   Default \code{NULL}.
+#' @param algorithm_options Algorithm options as a named list, a JSON string,
+#'   or a path to a JSON file. Default \code{NULL}.
 #' @param analysis_dir Analysis directory. Default \code{"analysis"}.
 #'
 #' @section Direct function model:
@@ -253,13 +252,41 @@ fzl <- function(models = "*", calculators = "*", check = FALSE) {
 #'     output = list(z = "grep z output.txt | cut -d= -f2")
 #'   )
 #'
+#'   # A minimal self-contained random-sampling algorithm (see
+#'   # https://github.com/Funz/fz for ready-made algorithms to install)
+#'   algo <- tempfile(fileext = ".py")
+#'   writeLines(c(
+#'     "import random",
+#'     "class RandomSampler:",
+#'     "    def __init__(self, **options):",
+#'     "        self.batch = int(options.get('batch_sample_size', 5))",
+#'     "        self.max_iterations = int(options.get('max_iterations', 3))",
+#'     "        self.iteration = 0",
+#'     "        self.input_vars = {}",
+#'     "    def get_initial_design(self, input_vars, output_vars):",
+#'     "        self.input_vars = input_vars",
+#'     "        self.iteration = 1",
+#'     "        return [{k: random.uniform(*v) for k, v in input_vars.items()}",
+#'     "                for _ in range(self.batch)]",
+#'     "    def get_next_design(self, previous_input_vars, previous_output_values):",
+#'     "        self.iteration += 1",
+#'     "        if self.iteration > self.max_iterations:",
+#'     "            return []",
+#'     "        return [{k: random.uniform(*v) for k, v in self.input_vars.items()}",
+#'     "                for _ in range(self.batch)]",
+#'     "    def get_analysis(self, input_vars, output_values):",
+#'     "        valid = [v for v in output_values if v is not None]",
+#'     "        mean = sum(valid) / len(valid) if valid else None",
+#'     "        return {'text': f'mean={mean}', 'data': {'mean': mean}}"
+#'   ), algo)
+#'
 #'   result <- fzd(
 #'     tf,
 #'     list(x = "[0;1]", y = "[-5;5]"),
 #'     model,
 #'     output_expression = "z",
-#'     algorithm        = "algorithms/montecarlo_uniform.py",
-#'     algorithm_options = "batch_sample_size=10;max_iterations=3"
+#'     algorithm        = algo,
+#'     algorithm_options = list(batch_sample_size = 10, max_iterations = 3)
 #'   )
 #' }
 #' }

R/install.R

@@ -72,10 +72,10 @@ fz_available <- function() {
 #' @export
 #'
 #' @examples
-#' \donttest{
-#' if (fz_available()) {
-#'   install_model("Funz/Model-PerfectGas")
-#' }
+#' \dontrun{
+#' # Requires the named GitHub repository to exist and network access;
+#' # not run automatically since neither is guaranteed in all environments.
+#' install_model("Funz/Model-PerfectGas")
 #' }
 install_model <- function(source, global = FALSE) {
   fz_module <- get_fz()
@@ -97,10 +97,10 @@ install_model <- function(source, global = FALSE) {
 #' @export
 #'
 #' @examples
-#' \donttest{
-#' if (fz_available()) {
-#'   install_algorithm("Funz/Algorithm-MonteCarlo")
-#' }
+#' \dontrun{
+#' # Requires the named GitHub repository to exist and network access;
+#' # not run automatically since neither is guaranteed in all environments.
+#' install_algorithm("Funz/Algorithm-MonteCarlo")
 #' }
 install_algorithm <- function(source, global = FALSE) {
   fz_module <- get_fz()
@@ -219,10 +219,10 @@ list_models <- function(global = FALSE) {
 #' @export
 #'
 #' @examples
-#' \donttest{
-#' if (fz_available()) {
-#'   install("Funz/Model-PerfectGas")
-#' }
+#' \dontrun{
+#' # Requires the named GitHub repository to exist and network access;
+#' # not run automatically since neither is guaranteed in all environments.
+#' install("Funz/Model-PerfectGas")
 #' }
 install <- function(source, global = FALSE) {
   install_model(source, global)

inst/doc/modelica-examples.R

@@ -76,7 +76,7 @@ knitr::opts_chunk$set(
 #    model,
 #    output_expression = "pressure",
 #    algorithm         = "algorithms/montecarlo_uniform.py",
-#    algorithm_options = "batch_sample_size=10;max_iterations=5;seed=42"
+#    algorithm_options = list(batch_sample_size = 10, max_iterations = 5, seed = 42)
 #  )
 
 ## ----fzl----------------------------------------------------------------------

inst/doc/modelica-examples.Rmd

@@ -173,7 +173,7 @@ result <- fzd(
   model,
   output_expression = "pressure",
   algorithm         = "algorithms/montecarlo_uniform.py",
-  algorithm_options = "batch_sample_size=10;max_iterations=5;seed=42"
+  algorithm_options = list(batch_sample_size = 10, max_iterations = 5, seed = 42)
 )
 ```
 

inst/doc/modelica-examples.html

@@ -484,7 +484,7 @@ <h2>Algorithm-driven design of experiments</h2>
 <span id="cb11-4"><a href="#cb11-4" tabindex="-1"></a>  model,</span>
 <span id="cb11-5"><a href="#cb11-5" tabindex="-1"></a>  <span class="at">output_expression =</span> <span class="st">&quot;pressure&quot;</span>,</span>
 <span id="cb11-6"><a href="#cb11-6" tabindex="-1"></a>  <span class="at">algorithm         =</span> <span class="st">&quot;algorithms/montecarlo_uniform.py&quot;</span>,</span>
-<span id="cb11-7"><a href="#cb11-7" tabindex="-1"></a>  <span class="at">algorithm_options =</span> <span class="st">&quot;batch_sample_size=10;max_iterations=5;seed=42&quot;</span></span>
+<span id="cb11-7"><a href="#cb11-7" tabindex="-1"></a>  <span class="at">algorithm_options =</span> <span class="fu">list</span>(<span class="at">batch_sample_size =</span> <span class="dv">10</span>, <span class="at">max_iterations =</span> <span class="dv">5</span>, <span class="at">seed =</span> <span class="dv">42</span>)</span>
 <span id="cb11-8"><a href="#cb11-8" tabindex="-1"></a>)</span></code></pre></div>
 <p>/home/richet/Sync/Open/Funz/github/fz.R/vignettes/modelica-examples.R</p>
 <p>Algorithms are Python files; <code>fz</code> ships several in

vignettes/modelica-examples.R

@@ -76,7 +76,7 @@ knitr::opts_chunk$set(
 #    model,
 #    output_expression = "pressure",
 #    algorithm         = "algorithms/montecarlo_uniform.py",
-#    algorithm_options = "batch_sample_size=10;max_iterations=5;seed=42"
+#    algorithm_options = list(batch_sample_size = 10, max_iterations = 5, seed = 42)
 #  )
 
 ## ----fzl----------------------------------------------------------------------

vignettes/modelica-examples.Rmd

@@ -173,7 +173,7 @@ result <- fzd(
   model,
   output_expression = "pressure",
   algorithm         = "algorithms/montecarlo_uniform.py",
-  algorithm_options = "batch_sample_size=10;max_iterations=5;seed=42"
+  algorithm_options = list(batch_sample_size = 10, max_iterations = 5, seed = 42)
 )
 ```