Pyber v0.15

.github/workflows/build-and-publish.yml

@@ -0,0 +1,187 @@
+name: Build and Publish
+
+on:
+  push:
+    branches: [main, master, Pyber_v0.15]
+    tags: ["v*"]
+  pull_request:
+    branches: [main, master, Pyber_v0.15]
+  workflow_dispatch:
+
+permissions:
+  contents: write
+
+jobs:
+  build-windows:
+    runs-on: windows-latest
+    defaults:
+      run:
+        shell: bash -el {0}
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Conda environment
+        uses: conda-incubator/setup-miniconda@v3
+        with:
+          activate-environment: pyBer
+          auto-activate-base: false
+          environment-file: environment.yml
+          channels: conda-forge
+          channel-priority: strict
+          use-mamba: true
+
+      - name: Show build environment
+        run: |
+          python --version
+          python -m pip --version
+          python -c "import os, sys; print('CONDA_PREFIX=', os.environ.get('CONDA_PREFIX')); print('PYTHON=', sys.executable)"
+
+      - name: Build Windows icon from assets
+        run: |
+          python -m pip install --upgrade pillow
+          mkdir -p build
+          python - <<'PY'
+          from pathlib import Path
+          from PIL import Image
+
+          src = Path("assets/pyBer_logo_big.png")
+          dst = Path("build/pyBer_logo_big.ico")
+          if not src.exists():
+              raise SystemExit(f"Missing icon source: {src}")
+
+          img = Image.open(src).convert("RGBA")
+          sizes = [(256, 256), (128, 128), (64, 64), (48, 48), (32, 32), (16, 16)]
+          img.save(dst, format="ICO", sizes=sizes)
+          print(f"Wrote {dst}")
+          PY
+
+      - name: Build with PyInstaller (last known good method)
+        run: |
+          BIN_DIR="$CONDA_PREFIX/Library/bin"
+          DLL_PATTERNS=(
+            "hdf5*.dll"
+            "zlib*.dll"
+            "blosc*.dll"
+            "libblosc2*.dll"
+            "libpng16*.dll"
+            "freetype*.dll"
+            "liblapack*.dll"
+            "libblas*.dll"
+            "libcblas*.dll"
+            "mkl_rt*.dll"
+            "mkl_core*.dll"
+            "mkl_intel_thread*.dll"
+            "mkl_intel_lp64*.dll"
+            "mkl_sequential*.dll"
+            "libmmd*.dll"
+            "libifcoremd*.dll"
+            "libifportmd*.dll"
+            "libiomp5md*.dll"
+            "libimalloc*.dll"
+            "svml_dispmd*.dll"
+          )
+
+          ADD_ARGS=()
+          declare -A SEEN_DLLS
+          shopt -s nullglob
+          for pattern in "${DLL_PATTERNS[@]}"; do
+            matches=("$BIN_DIR"/$pattern)
+            if [[ ${#matches[@]} -eq 0 ]]; then
+              echo "No matches for pattern: $pattern"
+              continue
+            fi
+            for dll_path in "${matches[@]}"; do
+              dll_name="$(basename "$dll_path")"
+              # Optional cluster/MPI BLACS DLLs are not required for local scipy use.
+              if [[ "$dll_name" =~ ^mkl_blacs_.*(intelmpi|msmpi).*\.dll$ ]]; then
+                echo "Skipping optional BLACS runtime: $dll_name"
+                continue
+              fi
+              if [[ -n "${SEEN_DLLS[$dll_name]:-}" ]]; then
+                continue
+              fi
+              echo "Bundling $dll_name"
+              ADD_ARGS+=(--add-binary "$dll_path;.")
+              SEEN_DLLS["$dll_name"]=1
+            done
+          done
+          shopt -u nullglob
+
+          python - <<'PY'
+          import numpy, scipy, h5py, sklearn
+          print("Import smoke test OK")
+          print("numpy:", numpy.__version__)
+          print("scipy:", scipy.__version__)
+          print("h5py:", h5py.__version__)
+          print("sklearn:", sklearn.__version__)
+          PY
+
+          python -m PyInstaller \
+            --noconfirm \
+            --clean \
+            --onefile \
+            --windowed \
+            --icon build/pyBer_logo_big.ico \
+            --add-data "assets;assets" \
+            --collect-binaries numpy \
+            --collect-binaries scipy \
+            --collect-binaries h5py \
+            --collect-binaries sklearn \
+            --exclude-module pyqtgraph.opengl \
+            --exclude-module OpenGL \
+            --name pyBer \
+            "${ADD_ARGS[@]}" \
+            pyBer/main.py
+
+      - name: Smoke test built EXE (switch to Postprocessing tab)
+        run: |
+          export PYBER_SMOKE_TEST=1
+          ./dist/pyBer.exe
+
+      - name: Upload Artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: pyber-windows-exe
+          path: dist/pyBer.exe
+          if-no-files-found: error
+
+  publish:
+    needs: [build-windows]
+    if: |
+      needs.build-windows.result == 'success' && (
+        github.event_name == 'workflow_dispatch' ||
+        (
+          github.event_name == 'push' &&
+          (github.ref == 'refs/heads/main' || github.ref == 'refs/heads/master' || github.ref == 'refs/heads/Pyber_v0.15' || startsWith(github.ref, 'refs/tags/'))
+        )
+      )
+    runs-on: ubuntu-latest
+    steps:
+      - name: Download Windows Artifact
+        uses: actions/download-artifact@v4
+        with:
+          name: pyber-windows-exe
+          path: ./publish
+
+      - name: Normalize Release Asset Name
+        run: |
+          set -euo pipefail
+          exe_path="$(find ./publish -type f -name '*.exe' | head -n 1 || true)"
+          if [[ -z "$exe_path" ]]; then
+            echo "No EXE found in downloaded artifact"
+            find ./publish -maxdepth 4 -type f -print || true
+            exit 1
+          fi
+          cp "$exe_path" ./publish/pyBer-windows.exe
+
+      - name: Create Release
+        uses: ncipollo/release-action@v1
+        with:
+          artifacts: "./publish/pyBer-windows.exe"
+          token: ${{ secrets.GITHUB_TOKEN }}
+          generateReleaseNotes: true
+          allowUpdates: true
+          tag: ${{ startsWith(github.ref, 'refs/tags/') && github.ref_name || 'latest' }}
+          name: ${{ startsWith(github.ref, 'refs/tags/') && github.ref_name || 'Latest Build' }}
+          prerelease: ${{ !startsWith(github.ref, 'refs/tags/') }}

.gitignore

@@ -0,0 +1,27 @@
+pyBer.spec
+build/pyBer/Analysis-00.toc
+build/pyBer/base_library.zip
+build/pyBer/EXE-00.toc
+build/pyBer/PKG-00.toc
+build/pyBer/pyBer.pkg
+build/pyBer/PYZ-00.pyz
+build/pyBer/PYZ-00.toc
+build/pyBer/warn-pyBer.txt
+build/pyBer/xref-pyBer.html
+build/pyBer/localpycs/pyimod01_archive.pyc
+build/pyBer/localpycs/pyimod02_importers.pyc
+build/pyBer/localpycs/pyimod03_ctypes.pyc
+build/pyBer/localpycs/pyimod04_pywin32.pyc
+build/pyBer/localpycs/struct.pyc
+dist/pyBer.exe
+pyBer/__pycache__/gui_postprocessing.cpython-38.pyc
+pyBer/__pycache__/gui_postprocessing.cpython-38.pyc
+pyBer/__pycache__/gui_postprocessing.cpython-38.pyc
+pyBer/__pycache__/gui_postprocessing.cpython-38.pyc
+pyBer/__pycache__/gui_postprocessing.cpython-311.pyc
+pyBer/__pycache__/main.cpython-311.pyc
+pyBer/__pycache__/gui_postprocessing.cpython-311.pyc
+pyBer/__pycache__/gui_postprocessing.cpython-38.pyc
+pyBer/__pycache__/gui_postprocessing.cpython-311.pyc
+pyBer/__pycache__
+panel_layout.json

README.md

@@ -66,11 +66,12 @@ The GUI exposes seven explicit output definitions:
 - **Lasso**: sparse regression (requires `scikit-learn`)
 - **RLM (HuberT)**: robust linear model via IRLS + Huber weighting (no extra dependency)
 
-### Export
-- Export processed output to:
-  - CSV (`time`, `output`, optional `dio`)
-  - HDF5 with raw, baseline, and metadata fields
-- Drag-and-drop support for preprocessing and post-processing files.
+### Export
+- Export processed output to:
+  - CSV with configurable fields (`time` always included; raw/isobestic/output/DIO selectable)
+  - HDF5 with configurable raw/output/DIO/baseline datasets plus metadata
+- Export field selection is saved and restored through the preprocessing configuration file.
+- Drag-and-drop support for preprocessing and post-processing files.
 
 ---
 

environment.yml

@@ -1,37 +1,31 @@
-name: pyBer
-channels:
-  - conda-forge
-  - defaults
-
-dependencies:
-  # Core interpreter
-  - python=3.11
-
-  # Numeric + signal processing
-  - numpy>=1.24
-  - scipy>=1.10
-  - pyqtgraph>=0.13
-  # File IO (Doric H5)
-  - h5py>=3.9
-
-  # Baseline correction
-  - pybaselines>=1.1
-
-  # GUI
-  - pyside6>=6.6
-
-
-  - scikit-learn>=1.3
-
-  # Quality-of-life / packaging
-  - pip
-  - setuptools
-  - wheel
-
-
-  - matplotlib>=3.8
+name: pyBer
+channels:
+  - conda-forge
 
+dependencies:
+  # Core
+  - python=3.11
 
+  # Numeric and signal processing
+  - libblas=*=*openblas
+  - liblapack=*=*openblas
+  - libcblas=*=*openblas
+  - numpy>=1.24
+  - scipy>=1.10
+  - h5py>=3.9
+  - scikit-learn>=1.3
+  - pybaselines>=1.1
   - pandas>=2.0
+  - openpyxl>=3.1
+
+  # GUI
+  - pyside6>=6.6
+  - pyqtgraph>=0.13
+  - matplotlib>=3.8
+
+  # Quality-of-life / packaging
+  - pip
+  - setuptools
+  - wheel
   - pyinstaller>=6.0
   - pyinstaller-hooks-contrib>=2024.0

preprocessing_config.json

@@ -0,0 +1,28 @@
+{
+  "artifact_detection_enabled": true,
+  "artifact_overlay_visible": true,
+  "filtering_enabled": true,
+  "parameters": {
+    "artifact_detection_enabled": true,
+    "artifact_mode": "Adaptive MAD (windowed)",
+    "mad_k": 25.0,
+    "adaptive_window_s": 1.0,
+    "artifact_pad_s": 0.5,
+    "lowpass_hz": 2.1,
+    "filter_order": 1,
+    "target_fs_hz": 120.0,
+    "baseline_method": "arpls",
+    "baseline_lambda": 100000000000.0,
+    "baseline_diff_order": 2,
+    "baseline_max_iter": 50,
+    "baseline_tol": 0.001,
+    "asls_p": 0.01,
+    "output_mode": "zscore (motion corrected with fitted ref)",
+    "invert_polarity": false,
+    "reference_fit": "OLS (recommended)",
+    "lasso_alpha": 0.001,
+    "rlm_huber_t": 1.345,
+    "rlm_max_iter": 50,
+    "rlm_tol": 1e-06
+  }
+}