Merge pull request #86 from ShantanuKodgirwar/fix-CI

Fix CI

Author: dannielsantiago

.github/workflows/test.yml

@@ -5,23 +5,24 @@ on:
     branches: [main]
   pull_request:
     branches: [main]
+  workflow_dispatch:
 
 jobs:
   build:
 
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.12", "3.13"]
+        python-version: ["3.11", "3.12", "3.13"]
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6.0.2
       - name: Install uv and set the python version
-        uses: astral-sh/setup-uv@v5
+        uses: astral-sh/setup-uv@v8.0.0
         with:
-          version: "0.5.16"
           python-version: ${{ matrix.python-version }}
-      - name: Install the project
-        run: uv sync
+          cache-dependency-glob: "pyproject.toml"
+      - name: Install the project with `dev`
+        run: uv sync --extra dev
       - name: Run tests
         run: uv run pytest tests

PtyLab/io/readHdf5.py

@@ -96,7 +96,7 @@ def getOrientation(filename):
     with h5py.File(str(filename), "r") as archive:
         if "orientation" in archive.keys():
             orientation = np.array(archive["orientation"]).ravel()[0].astype(int)
-    return int(orientation)
+    return int(orientation) if orientation is not None else None
 
 
 def checkDataFields(filename, requiredFields):

PtyLab/utils/visualisation.py

@@ -120,7 +120,7 @@ def complexPlot(rgb, ax=None, pixelSize=1, axisUnit="pixel"):
     scalar_mappable = mpl.cm.ScalarMappable(norm=norm, cmap=mpl.cm.hsv)
     scalar_mappable.set_array([])
     cbar = plt.colorbar(scalar_mappable, ax=ax, cax=cax, ticks=[-np.pi, 0, np.pi])
-    cbar.ax.set_yticklabels(["$-\pi$", "0", "$\pi$"])
+    cbar.ax.set_yticklabels([r"$-\pi$", "0", r"$\pi$"])
     return im
 
 

README.md

@@ -1,6 +1,7 @@
 # PtyLab.py: Unified Ptychography Toolbox
 ![Python 3.10+](https://img.shields.io/badge/python-3.10+-green.svg)
-![Tests](https://github.com/ShantanuKodgirwar/PtyLabX/actions/workflows/test.yml/badge.svg)
+![Version](https://img.shields.io/badge/version-0.2.3-blue.svg)
+![Tests](https://github.com/PtyLab/PtyLab.py/actions/workflows/test.yml/badge.svg)
 
 PtyLab is an inverse modeling toolbox for Conventional (CP) and Fourier (FP) ptychography in a unified framework. For more information please check the [paper](https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-9-13763&id=529026).
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ptylab"
-version = "0.2.3"
+version = "0.2.4"
 description = "A cross-platform, open-source inverse modeling toolbox for conventional and Fourier ptychography"
 authors = [
     { name = "Lars Loetgering", email = "lars.loetgering@fulbrightmail.org" },

tests/conftest.py

@@ -0,0 +1,38 @@
+import numpy as np
+import h5py
+import pytest
+from pathlib import Path
+
+
+@pytest.fixture(scope="session", autouse=True)
+def generate_simu_hdf5():
+    """Generate a minimal simu.hdf5 if it doesn't exist (CI-friendly).
+
+    Tests that call easyInitialize("example:simulation_cpm") resolve to
+    example_data/simu.hdf5. This fixture ensures that file exists before
+    any test runs, so no real dataset needs to be committed to the repo.
+    If the file already exists (e.g. locally), it is left untouched.
+    """
+    example_data_dir = Path(__file__).parent.parent / "example_data"
+    example_data_dir.mkdir(exist_ok=True)
+    hdf5_path = example_data_dir / "simu.hdf5"
+
+    if hdf5_path.exists():
+        yield hdf5_path
+        return
+
+    rng = np.random.default_rng(42)
+    Nd, N_frames = 64, 20
+
+    ptychogram = rng.random((N_frames, Nd, Nd)).astype(np.float32)
+    encoder = rng.uniform(-1e-3, 1e-3, (N_frames, 2))
+
+    with h5py.File(hdf5_path, "w") as hf:
+        hf.create_dataset("ptychogram", data=ptychogram, dtype="f")
+        hf.create_dataset("encoder", data=encoder, dtype="f")
+        hf.create_dataset("dxd", data=np.array(75e-6))
+        hf.create_dataset("zo", data=np.array(0.1))
+        hf.create_dataset("wavelength", data=np.array(632e-9))
+        hf.create_dataset("entrancePupilDiameter", data=np.array(170e-6))
+
+    yield hdf5_path