Packaging

. github/workflows/github-actions-demo.yml

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+name: Sagittal_Average python package
+run-name: ${{ github.actor }} is testing out GitHub Actions 🚀
+on: [push]
+jobs:
+  Explore-GitHub-Actions:
+    runs-on: ubuntu-latest
+    steps:
+      - run: echo "🎉 The job was automatically triggered by a ${{ github.event_name }} event."
+      - run: echo "🐧 This job is now running on a ${{ runner.os }} server hosted by GitHub!"
+      - run: echo "🔎 The name of your branch is ${{ github.ref }} and your repository is ${{ github.repository }}."
+      - name: Check out repository code
+        uses: actions/checkout@v3
+      - run: echo "💡 The ${{ github.repository }} repository has been cloned to the runner."
+      - run: echo "🖥️ The workflow is now ready to test your code on the runner."
+      - name: List files in the repository
+        run: |
+          ls ${{ github.workspace }}
+      - run: echo "🍏 This job's status is ${{ job.status }}."
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.10"]
+
+    steps:
+      - uses: actions/checkout@v3
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install the dependencies
+        run: |
+          python -m pip install --upgrade pip
+      - name: Install the package
+        run: |
+          pip install -e .
+      - name: Test with pytest
+        run: |
+          pytest

.gitignore

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+Sagittal_Average.egg-info/
+
+.pytest_cache
+Sagittal_Average/__pycache__
+Sagittal_Average/tests/__pycache__
+
+Sagittal_Average/tests/brain_average.csv
+Sagittal_Average/tests/brain_sample.csv
+
+brain_sample.csv
+brain_average.csv

CITATION.md

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+If you wish to refer to this course, please cite the URL
+http://github-pages.ucl.ac.uk/rsd-engineeringcourse/
+
+Portions of the material are taken from [Software Carpentry](http://software-carpentry.org/)

LICENSE.md

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+(C) University College London 2014
+
+This "sagittal_average" example package is granted into the public domain.

READMD.md

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+This is a very simple example package used as part of the UCL
+[Research Software Engineering with Python](development.rc.ucl.ac.uk/training/engineering) course.
+
+## Installation
+
+```bash
+pip install git+git://github.com/ucl-rits/greeter
+pip install git+git://github.com/chongfengling/sagittal_average_packaging
+```
+
+## Usage
+
+Invoke the tool with `sagittal_average_run <file_input> <file_output>` or use it on your own library:
+
+```python
+from Sagittal_Average import sagittal_brain
+
+sagittal_brain.run_averages(file_input, file_output)
+```

Sagittal_Average/command.py

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+from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
+from .sagittal_brain import *
+
+
+def process():
+    parser = ArgumentParser(
+        description="Calculates the average for each sagittal-horizontal plane.",
+        formatter_class=ArgumentDefaultsHelpFormatter,
+    )
+    parser.add_argument(
+        "file_input",
+        nargs="?",
+        default="brain_sample.csv",
+        help="Input CSV file with the results from scikit-brain binning algorithm.",
+    )
+    parser.add_argument(
+        "--file_output",
+        "-o",
+        default="brain_average.csv",
+        help="Name of the output CSV file.",
+    )
+    arguments = parser.parse_args()
+
+    run_averages(arguments.file_input, arguments.file_output)
+    # print('processed')
+
+
+if __name__ == "__main__":
+    process()

Sagittal_Average/sagittal_brain.py

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+from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
+
+import numpy as np
+
+
+def run_averages(file_input="brain_sample.csv", file_output="brain_average.csv"):
+    """
+    Calculates the average through the coronal planes
+    The input file should has as many columns as coronal planes
+    The rows are intersections of the sagittal/horizontal planes
+
+    The result is the average for each sagittal/horizontal plane (rows)
+    """
+    # Open the file to analyse
+    planes = np.loadtxt(file_input, dtype=int, delimiter=",")
+
+    # Calculates the averages through the sagittal/horizontal planes
+    # and makes it as a row vector
+    averages = planes.mean(axis=1)[np.newaxis, :]
+
+    # write it out on my file
+    np.savetxt(file_output, averages, fmt="%.1f", delimiter=",")

Sagittal_Average/tests/test_sth.py

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+import numpy as np
+from Sagittal_Average.sagittal_brain import *
+def test_sth():
+    data_input = np.zeros((20, 20))
+    data_input[-1, :] = 1
+    np.savetxt("brain_sample.csv", data_input, fmt='%d', delimiter=',')
+
+    # The expected result is all zeros, except the last one, it should be 1
+    expected = np.zeros(20)
+    expected[-1] = 1
+
+    run_averages(file_input="brain_sample.csv",
+             file_output="brain_average.csv")
+
+    result = np.loadtxt("brain_average.csv",  delimiter=',')
+
+    np.testing.assert_array_equal(result, expected)

setup.py

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+from setuptools import setup, find_packages
+
+setup(
+    name="Sagittal_Average",
+    version="0.1.2",
+    packages=find_packages(),
+    entry_points={
+        'console_scripts':['sagittal_average_run = Sagittal_Average.command:process']
+    }
+)