✨ add static analysis and test workflow, add dwi-to-conductivity workflow (#2)

* add static analysis and test workflow

* add badge

* add anisotropic conductivity workflow

* add pyright config

* restructure package, add license header

Co-authored-by: Bryn Lloyd <[email protected]>

Author: dyollb

.github/workflows/deploy_and_test.yml

@@ -0,0 +1,57 @@
+name: CI
+
+on:
+  workflow_dispatch:
+  push:
+    branches: [ main ]
+    paths-ignore:
+      - "*.md"
+      - "*.png"
+      - "*.gif"
+      - "*.svg"
+      - "docs/**"
+      - ".vscode/**"
+  pull_request:
+    branches: [ main ]
+    paths-ignore:
+      - "*.md"
+      - "*.png"
+      - "*.gif"
+      - "*.svg"
+      - "docs/**"
+      - ".vscode/**"
+
+jobs:
+  build-and-test:
+      name: python ${{ matrix.python-version }}
+      runs-on: windows-latest
+      strategy:
+        fail-fast: false
+        max-parallel: 4
+        matrix:
+          python-version: ['3.6']
+      steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+        with:
+          path: scripts_src
+      - name: Setup python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Pip cache
+        uses: actions/cache@v2
+        with:
+          path: ~/.cache/pip
+          key: ${{ runner.os }}-pip-{{ matrix.python-version }}
+          restore-keys: |
+            ${{ runner.os }}-pip
+      - name: Pip install
+        working-directory: scripts_src
+        run: pip install ".[test]"
+      - name: Test
+        working-directory: scripts_src
+        run: pytest tests
+      - name: Static analysis
+        working-directory: scripts_src
+        run: mypy src tests

README.md

@@ -1,7 +1,9 @@
 # Sim4Life Python Scripts
+[![Build Actions Status](https://github.com/dyollb/s4l-scripts/workflows/CI/badge.svg)](https://github.com/dyollb/s4l-scripts/actions)
+[![License](https://img.shields.io/badge/license-MIT-green.svg)](https://https://opensource.org/licenses/MIT)
 This is just a random collection of [Sim4Life](https://zmt.swiss/sim4life/) Python scripts.
 
-Sim4Life is a simulation platform for life scrience applications to investigate interaction between man-made devices and living organisms (e.g. active implants, mobile phones, neuro-stimulation, thermal heating, ...).
+Sim4Life is a simulation platform for life science applications to investigate interaction between man-made devices and living organisms (e.g. active implants, mobile phones, neuro-stimulation, thermal heating, ...).
 It features a powerful CAD/surface-based modeling environment and GPU accelerated physics solvers, enabling simulations with extremely complex anatomical models, such as the [Virtual Population](https://itis.swiss/virtual-population/virtual-population/overview/).
 
 

mypy.ini

@@ -6,5 +6,5 @@ warn_unused_configs = True
 
 # Thirdparties:
 
-[mypy-s4l_v1.*,numpy,XCore,XCoreModeling,XPostProcessor,EmPostPro,Extractors,XRendererUI,win32gui]
+[mypy-s4l_v1.*,setuptools,numpy,nibabel,dipy.*,XCore,XCoreModeling,ImageModeling,MeshModeling,XPostProcessor,EmPostPro,Extractors,XRendererUI,win32gui]
 ignore_missing_imports = True

pyrightconfig.json

@@ -0,0 +1,12 @@
+{
+    "include": [
+        "src/",
+        "tests/",
+        "scripts/"
+    ],
+    "exclude": [
+    ],
+    "useLibraryCodeForTypes": true,
+    "reportPrivateImportUsage": false,
+    "reportMissingImports": "warning"
+}

requirements-test.txt

@@ -0,0 +1,2 @@
+mypy==0.920
+pytest==6.2.5

requirements.txt

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+dipy==1.4.1
+nibabel==3.2.1
+numpy==1.19.5
+scipy==1.5.4

setup.py

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+# -*- coding: utf-8 -*-
+
+from setuptools import setup, find_packages
+
+
+install_requirements = [i.strip() for i in open("requirements.txt").readlines()]
+extra_requirements = [i.strip() for i in open("requirements-test.txt").readlines()]
+
+with open("README.md") as f:
+    readme = f.read()
+
+with open("LICENSE") as f:
+    license = f.read()
+
+setup(
+    name="s4l_scripts",
+    version="0.1.0",
+    description="Collection of Sim4Life scripts",
+    long_description=readme,
+    author="Bryn Lloyd",
+    author_email="[email protected]",
+    url="https://github.com/dyollb/s4l-scripts.git",
+    license=license,
+    install_requires=install_requirements,
+    extras_require={"test": extra_requirements},
+    packages=find_packages(where="src"),
+    package_dir={
+        "": "src",
+    },
+)

src/anisotropic_conductivity/README.md

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+# Subject-specific anatomical model with anisotropic conductivity from diffusion weighted imaging
+This folder contains scripts to create a subject-specific head model with inhomogeneous anisotropic conductivity distribution in Sim4Life, e.g. for transcranial electric/magnetic stimulation simulations. The workflow demonstrates how to reconstruct diffusion weighted images to diffusion tensor fields compatible with Sim4Life.
+
+The file [main.py](main.py) implements the top-level workflow. The example downloads a demo dataset from the [Stanford digital repository](https://purl.stanford.edu/ng782rw8378) using the open-source package [dipy](https://dipy.org/). The key steps include:
+
+- download the data
+- reconstruct diffusion tensors and convert to Sim4Life ordering
+- import diffusion tensors and evaluate conductivity based on [Tuch et al.](https://www.pnas.org/content/98/20/11697.short) in Sim4Life
+- visualize largest eigenvector of conductivity tensors
+- convert label infos to a Sim4Life-compatible tissue list format
+- import labels and extract surface model in Sim4Life
+- setup Ohmic Quasi-Stationary simulation with inhom. anisotropic conductivity

flythru_script/quaternions/__init__.py src/anisotropic_conductivity/__init__.py

@@ -0,0 +1,60 @@
+# Copyright (c) 2021 The Foundation for Research on Information Technologies in Society (IT'IS).
+#
+# This file is part of s4l-scripts
+# (see https://github.com/dyollb/s4l-scripts).
+#
+# This software is released under the MIT License.
+#  https://opensource.org/licenses/MIT
+
+from pathlib import Path
+from typing import Dict, List
+import shutil
+
+from dipy.data import (
+    fetch_stanford_hardi,
+    fetch_stanford_labels,
+    fetch_stanford_t1,
+    get_fnames,
+)
+
+
+def download_small_dwi_data(download_dir: Path) -> Dict[str, List[Path]]:
+    """Download small test dwi data, no t1 or labels are provided
+
+    Args:
+        download_dir: specify folder where data is copied
+    """
+    download_dir.mkdir(exist_ok=True)
+    files = []
+    for f in get_fnames(name="small_25"):
+        files.append(Path(download_dir) / Path(f).name)
+        shutil.copyfile(Path(f), files[-1])
+    return {"dwi": files}
+
+
+def download_stanford_data(download_dir: Path) -> Dict[str, List[Path]]:
+    """Download standford dwi data, t1 image and labelfield
+
+    Args:
+        download_dir: specify folder where data is copied
+    """
+
+    def _fetch_and_copy(fetch_fun):
+        files, dipy_dir = fetch_fun()
+        for f in files.keys():
+            shutil.copyfile(Path(dipy_dir) / f, Path(download_dir) / f)
+        return [download_dir / f for f in files.keys()]
+
+    download_dir.mkdir(exist_ok=True)
+    dwi_files = _fetch_and_copy(fetch_stanford_hardi)
+    t1_files = _fetch_and_copy(fetch_stanford_t1)
+    label_files = _fetch_and_copy(fetch_stanford_labels)
+    return {"dwi": dwi_files, "t1": t1_files, "labels": label_files}
+
+
+if __name__ == "__main__":
+    output_dir = Path("/Users/lloyd/Models/StandfordData")
+    files = download_stanford_data(download_dir=output_dir)
+
+    for f in output_dir.glob("*.*"):
+        print(f)

src/anisotropic_conductivity/download_data.py

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+# Copyright (c) 2021 The Foundation for Research on Information Technologies in Society (IT'IS).
+#
+# This file is part of s4l-scripts
+# (see https://github.com/dyollb/s4l-scripts).
+#
+# This software is released under the MIT License.
+#  https://opensource.org/licenses/MIT
+
+import numpy as np
+from pathlib import Path
+from typing import Dict
+
+
+def load_stanford_label_info(file_path: Path) -> Dict[int, str]:
+    """Load tissue names and labels from stanford example dataset
+
+    Args:
+        file_path: label info file to parse
+
+    The file is assumed to by in CSV format with 3 columns, where the first row is a header, e.g.
+
+        new label, freesurfer label, freesurfer name
+        1, 2, "Left-Cerebral-White-Matter"
+        1, 41, "Right-Cerebral-White-Matter"
+        1, 77, "WM-hypointensities"
+        ...
+    """
+    with open(file_path, "r") as f:
+        lines = f.readlines()
+    label_info: Dict[int, str] = {}
+    for line in lines[1:]:
+        parts = line.split(",")
+        if len(parts) != 3:
+            continue
+        label = int(parts[0].strip())
+        name = parts[2].strip().strip('"').replace(" ", "_")
+        if label in label_info:
+            label_info[label] += f"_{name}"
+        else:
+            label_info[label] = name
+    return label_info
+
+
+def save_iseg_label_info(label_info: Dict[int, str], file_path: Path):
+    """save label info dictionary as iSEG compatible tissue list
+
+    Args:
+        tissue_list: input label info dictionary
+        file_path: tissue list file
+
+    Example file:
+        V7
+        N3
+        C0.00 0.00 1.00 0.50 Bone
+        C0.00 1.00 0.00 0.50 Fat
+        C1.00 0.00 0.00 0.50 Skin
+    """
+    max_label = max(label_info.keys())
+    tissue_names = [f"tissue{i}" for i in range(max_label + 1)]
+    for id, name in label_info.items():
+        tissue_names[id] = name
+
+    with open(file_path, "w") as f:
+        print("V7", file=f)
+        print(f"N{max_label}", file=f)
+        for i in range(1, max_label):
+            r, g, b = np.random.rand(), np.random.rand(), np.random.rand()
+            print(f"C{r:.2f} {g:.2f} {b:.2f} 0.50 {tissue_names[i]}", file=f)
+
+
+if __name__ == "__main__":
+    label_info_file = Path("/Users/lloyd/Models/StandfordData") / "label_info.txt"
+    label_info = load_stanford_label_info(label_info_file)
+    save_iseg_label_info(label_info, label_info_file.parent / "label_info_iseg.txt")

src/anisotropic_conductivity/load_labels.py

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+# Copyright (c) 2021 The Foundation for Research on Information Technologies in Society (IT'IS).
+#
+# This file is part of s4l-scripts
+# (see https://github.com/dyollb/s4l-scripts).
+#
+# This software is released under the MIT License.
+#  https://opensource.org/licenses/MIT
+
+import sys
+from pathlib import Path
+
+from .download_data import download_stanford_data
+from .load_labels import load_stanford_label_info, save_iseg_label_info
+from .reconstruct_diffusion_tensors import reconstruct_diffusion_tensors
+
+
+def import_in_sim4life(
+    t1_file: Path, seg_file: Path, tissuelist_file: Path, s4l_tensors_file: Path
+):
+    try:
+        import s4l_v1 as s4l
+        import ImageModeling  # TODO: make sure this works with s4l
+        import MeshModeling  # TODO: make sure this works with s4l
+    except ImportError as error:
+        print("ERROR: Could not import Sim4Life Python modules", sys.exc_info()[0])
+        return
+
+    # not used, but nice to visualize model with MRI
+    t1_image = ImageModeling.ImportImage(t1_file)
+
+    # import label field
+    labelfield = ImageModeling.ImportImage(
+        seg_file, as_labelfield=True, tissuelist_path=tissuelist_file
+    )
+
+    # extract surface-based model
+    surfaces = MeshModeling.ExtractSurface(labelfield, min_edge_length=0.5)
+
+    # load dwi data, compute conductivity
+    # s4l.analysis.import(s4l_tensors_file) ?
+
+
+def main():
+    data_dir = Path("/Users/lloyd/Models/StandfordData")
+    files = download_stanford_data(download_dir=data_dir)
+
+    # reconstruct DTI using the dipy package
+    bvec_file = next(f for f in files["dwi"] if f.name.endswith("bvec"))
+    s4l_tensors_file = bvec_file.parent / bvec_file.name.replace(".bvec", "_s4l.nii.gz")
+    reconstruct_diffusion_tensors(bvec_file, s4l_tensors_file)
+
+    # convert label infos so we get tissue names in Sim4Life
+    label_info_file = next(f for f in files["labels"] if f.name.endswith("txt"))
+    iseg_tissue_list_file = label_info_file.parent / label_info_file.name.replace(
+        ".txt", "_iseg.txt"
+    )
+    label_infos = load_stanford_label_info(label_info_file)
+    save_iseg_label_info(label_infos, iseg_tissue_list_file)
+
+    # load image and segmentation data in Sim4Life
+    labels_file = next(f for f in files["labels"] if f.name.endswith("nii.gz"))
+    t1_file = files["t1"][0]
+
+    assert labels_file.exists()
+    assert t1_file.exists()
+
+
+if __name__ == "__main__":
+    main()