ci: tests, README steps, format check and dependabot

.github/dependabot.yml

@@ -0,0 +1,9 @@
+version: 2
+updates:
+  - package-ecosystem: github-actions
+    directory: /
+    schedule:
+      interval: monthly
+    groups:
+      actions:
+        patterns: ["*"]

.github/workflows/ci.yml

@@ -0,0 +1,21 @@
+name: Tests
+on:
+  push:
+    branches: [main]
+  pull_request:
+permissions:
+  contents: read
+jobs:
+  pytest:
+    runs-on: ubuntu-latest
+    timeout-minutes: 40
+    env:
+      MPLBACKEND: Agg
+      CI: "true"
+    steps:
+      - uses: actions/checkout@v7
+      - uses: astral-sh/setup-uv@v10.3.0
+        with:
+          enable-cache: true
+      - name: Run pytest
+        run: uv run --python 3.13 --group dev pytest -q

.github/workflows/lint.yml

@@ -10,3 +10,4 @@ jobs:
       - uses: actions/checkout@v7
       - uses: astral-sh/setup-uv@v10.3.0
       - run: uvx ruff@0.17.1 check
+      - run: uvx ruff@0.17.1 format --check

.github/workflows/readme.yml

@@ -0,0 +1,8 @@
+name: readme
+on:
+  push:
+    branches: [main]
+  pull_request:
+jobs:
+  readme:
+    uses: NaNIsaac/.github/.github/workflows/readme.yml@main

README.md

@@ -10,13 +10,19 @@ Each folder under `runs/` is one self-contained experiment (config, simulation,
 
 ## Install
 
-Uses [uv](https://docs.astral.sh/uv/) and Python 3.13. `torch` is pulled from the PyTorch CUDA 12.8 index.
+Uses [uv](https://docs.astral.sh/uv/) and Python 3.13. `torch` is pulled from the PyTorch CUDA 12.8 index (PyPI on macOS).
 
 ```bash
 git clone https://github.com/NaNIsaac/ReflectoExp.git
 cd ReflectoExp
+```
+
+Install the dependencies and the `reflecto_exp` package:
+
+<!-- test -->
+```bash
 uv sync
-uv pip install -e .     # installs the reflecto_exp package
+uv pip install -e .
 ```
 
 The refnx-based experiments (exp02, exp03) also need `uv pip install refnx`, which is not a declared dependency.

main.py

@@ -24,6 +24,7 @@ def get_venv_python() -> Path:
 
     return venv_python
 
+
 def find_exp_folder(exp_num: int, runs_dir_path: Path = Path("./runs")) -> Path:
     """
     runs 폴더 내에서 exp{num} 또는 exp0{num}으로 시작하는 폴더를 찾습니다.
@@ -52,6 +53,7 @@ def find_exp_folder(exp_num: int, runs_dir_path: Path = Path("./runs")) -> Path:
 
     return found_folder
 
+
 def run_main(target_folder: Path):
     """
     찾은 폴더 내부의 main.py를 가상환경 Python으로 실행합니다.
@@ -72,15 +74,16 @@ def run_main(target_folder: Path):
         subprocess.run(
             [str(venv_python), "main.py"],
             cwd=target_folder,  # 작업 디렉토리를 해당 실험 폴더로 변경
-            check=True
+            check=True,
         )
     except subprocess.CalledProcessError as e:
         print("-" * 50)
         print(f"💥 [Fail] 실행 중 오류 발생 (Exit code: {e.returncode})")
 
+
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description='Run experiment based on ID')
-    parser.add_argument('exp_num', type=int, help='Experiment number (e.g., 5)')
+    parser = argparse.ArgumentParser(description="Run experiment based on ID")
+    parser.add_argument("exp_num", type=int, help="Experiment number (e.g., 5)")
 
     args = parser.parse_args()
 

notebooks/function_test.ipynb

@@ -15,7 +15,7 @@
     "from reflecto.simulate.simulator import ParamSet, build_structure, compute_refl\n",
     "\n",
     "wavelen: float = 1.54  # (nm)\n",
-    "tth_min: float = 0.1   # degree\n",
+    "tth_min: float = 0.1  # degree\n",
     "tth_max: float = 6.0\n",
     "q_n: int = 200\n",
     "tths: np.ndarray = np.linspace(tth_min, tth_max, q_n)\n",
@@ -54,7 +54,7 @@
     "fig, ax = plt.subplots(1, 1, figsize=(8, 5))\n",
     "ax.plot(qs, refl)\n",
     "ax.plot(qs, refl2)\n",
-    "ax.set_yscale('log')\n",
+    "ax.set_yscale(\"log\")\n",
     "\n",
     "plt.show()"
    ]
@@ -84,7 +84,7 @@
     "slds = [f.sld for f in films]\n",
     "fig, ax = plt.subplots(1, 1, figsize=(8, 5))\n",
     "ax.plot(qs, refl)\n",
-    "ax.set_yscale('log')"
+    "ax.set_yscale(\"log\")"
    ]
   },
   {
@@ -101,8 +101,8 @@
     "# Manual: 평균 30분 (1800초) ~ 60분 범위\n",
     "# Hybrid: 평균 2초 ~ 4초 범위\n",
     "means = [1800, 3]\n",
-    "labels = ['Manual Fitting\\n(Expert)', 'Hybrid Pipeline\\n(Ours)']\n",
-    "colors = ['#bdbdbd', '#2e7d32'] # 회색 vs 초록색\n",
+    "labels = [\"Manual Fitting\\n(Expert)\", \"Hybrid Pipeline\\n(Ours)\"]\n",
+    "colors = [\"#bdbdbd\", \"#2e7d32\"]  # 회색 vs 초록색\n",
     "\n",
     "fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(5, 6))\n",
     "fig.subplots_adjust(hspace=0.1)  # 위아래 그래프 간격 조절\n",
@@ -113,32 +113,32 @@
     "\n",
     "# 축 범위 설정 (Broken Axis 효과)\n",
     "ax1.set_ylim(1500, 2000)  # 위쪽 그래프: 1500~2000초 구간\n",
-    "ax2.set_ylim(0, 100)      # 아래쪽 그래프: 0~100초 구간\n",
+    "ax2.set_ylim(0, 100)  # 아래쪽 그래프: 0~100초 구간\n",
     "\n",
     "# 위쪽 그래프의 X축 눈금 제거\n",
-    "ax1.spines['bottom'].set_visible(False)\n",
-    "ax2.spines['top'].set_visible(False)\n",
+    "ax1.spines[\"bottom\"].set_visible(False)\n",
+    "ax2.spines[\"top\"].set_visible(False)\n",
     "ax1.xaxis.tick_top()\n",
     "ax1.tick_params(labeltop=False)  # 위쪽 라벨 제거\n",
     "ax2.xaxis.tick_bottom()\n",
     "\n",
     "# 빗금(Diagonal lines)으로 잘린 부분 표현\n",
-    "d = .015\n",
-    "kwargs = {'transform': ax1.transAxes, 'color': 'k', 'clip_on': False}\n",
-    "ax1.plot((-d, +d), (-d, +d), **kwargs)        # top-left diagonal\n",
+    "d = 0.015\n",
+    "kwargs = {\"transform\": ax1.transAxes, \"color\": \"k\", \"clip_on\": False}\n",
+    "ax1.plot((-d, +d), (-d, +d), **kwargs)  # top-left diagonal\n",
     "ax1.plot((1 - d, 1 + d), (-d, +d), **kwargs)  # top-right diagonal\n",
     "\n",
     "kwargs.update(transform=ax2.transAxes)  # switch to the bottom axes\n",
     "ax2.plot((-d, +d), (1 - d, 1 + d), **kwargs)  # bottom-left diagonal\n",
     "ax2.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs)  # bottom-right diagonal\n",
     "\n",
     "# 텍스트 라벨 추가 (가장 중요!)\n",
-    "ax1.text(0, 1850, \"~ 30 mins\", ha='center', va='bottom', fontsize=14, fontweight='bold')\n",
-    "ax2.text(1, 10, \"< 3 sec\", ha='center', va='bottom', fontsize=14, fontweight='bold', color='#2e7d32')\n",
+    "ax1.text(0, 1850, \"~ 30 mins\", ha=\"center\", va=\"bottom\", fontsize=14, fontweight=\"bold\")\n",
+    "ax2.text(1, 10, \"< 3 sec\", ha=\"center\", va=\"bottom\", fontsize=14, fontweight=\"bold\", color=\"#2e7d32\")\n",
     "\n",
     "# 제목 및 Y축 라벨\n",
-    "ax1.set_title(\"Processing Time per Scan\", fontsize=14, fontweight='bold', pad=20)\n",
-    "fig.text(0.02, 0.5, 'Time (seconds)', va='center', rotation='vertical', fontsize=12)\n",
+    "ax1.set_title(\"Processing Time per Scan\", fontsize=14, fontweight=\"bold\", pad=20)\n",
+    "fig.text(0.02, 0.5, \"Time (seconds)\", va=\"center\", rotation=\"vertical\", fontsize=12)\n",
     "\n",
     "plt.show()"
    ]

pyproject.toml

@@ -82,9 +82,18 @@ url = "https://download.pytorch.org/whl/cu128"
 explicit = true
 
 [tool.uv.sources]
-torch = [{ index = "pytorch-cu128" }]
-torchvision = [{ index = "pytorch-cu128" }]
-torchaudio = [{ index = "pytorch-cu128" }]
+torch = [{ index = "pytorch-cu128", marker = "sys_platform != 'darwin'" }]
+torchvision = [{ index = "pytorch-cu128", marker = "sys_platform != 'darwin'" }]
+torchaudio = [{ index = "pytorch-cu128", marker = "sys_platform != 'darwin'" }]
+
+# GenX lists wxpython for its GUI, which this project never starts. PyPI has no Linux wheel for it,
+# so on Linux uv would compile it and fail without GTK headers.
+[tool.uv]
+override-dependencies = ["wxpython; sys_platform != 'linux'"]
+
+[tool.pytest.ini_options]
+pythonpath = ["src"]
+testpaths = ["tests"]
 
 [tool.ruff]
 line-length = 150
@@ -110,5 +119,6 @@ combine-as-imports = true
 
 [dependency-groups]
 dev = [
+    "pytest>=9.0.2",
     "ruff>=0.14.3",
 ]

runs/exp01_quan_class/dataset.py

@@ -28,12 +28,7 @@ class ParamQuantizer:
       q.quantize(param) -> np.ndarray([t_idx, r_idx, s_idx])
     """
 
-    def __init__(
-        self,
-        thickness_bins: np.ndarray | None = None,
-        roughness_bins: np.ndarray | None = None,
-        sld_bins: np.ndarray | None = None
-    ):
+    def __init__(self, thickness_bins: np.ndarray | None = None, roughness_bins: np.ndarray | None = None, sld_bins: np.ndarray | None = None):
         # sensible defaults (units: nm for thickness, Å for roughness, 1e-6 Å^-2 or user convention)
         self.thickness_bins = np.linspace(0.0, 200.0, 51) if thickness_bins is None else np.asarray(thickness_bins)
         self.roughness_bins = np.linspace(0.0, 10.0, 21) if roughness_bins is None else np.asarray(roughness_bins)
@@ -103,11 +98,14 @@ def quantize(self, param: ParamSet) -> np.ndarray:
         t = float(param.thickness)
         r = float(param.roughness)
         s = float(param.sld)
-        return np.array([
-            self._quantize_array(np.asarray([t]), self.thickness_bins)[0],
-            self._quantize_array(np.asarray([r]), self.roughness_bins)[0],
-            self._quantize_array(np.asarray([s]), self.sld_bins)[0],
-        ], dtype=np.int64)
+        return np.array(
+            [
+                self._quantize_array(np.asarray([t]), self.thickness_bins)[0],
+                self._quantize_array(np.asarray([r]), self.roughness_bins)[0],
+                self._quantize_array(np.asarray([s]), self.sld_bins)[0],
+            ],
+            dtype=np.int64,
+        )
 
     def quantize_multi(self, thickness_arr: np.ndarray, roughness_arr: np.ndarray, sld_arr: np.ndarray) -> np.ndarray:
         """Vectorized quantize for arrays per-layer. Returns shape (n_layers, 3)."""
@@ -214,7 +212,7 @@ def __getitem__(self, idx):
         self._ensure_open()
         hf = self._hf
 
-        refl = hf["R"][idx]           # (q_len,) or (q_len, ...)
+        refl = hf["R"][idx]  # (q_len,) or (q_len, ...)
         thick = hf["thickness"][idx]  # (n_layers,)
         rough = hf["roughness"][idx]
         sld = hf["sld"][idx]