setting up directory structure and .toml file for package creation

.gitignore

@@ -0,0 +1,165 @@
+# Default .gitignore by github when initiating a repo
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.pyc
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

.vscode/settings.json

@@ -0,0 +1,7 @@
+{
+    "python.testing.pytestArgs": [
+        "tests"
+    ],
+    "python.testing.unittestEnabled": false,
+    "python.testing.pytestEnabled": true
+}

pyproject.toml

@@ -0,0 +1,22 @@
+[project]
+name = "sagittal_average"         # Name of the package
+version = "0.1.2"                 # Version of the package
+description = "Brain stuff"
+dependencies = [                  # Adding dependency installation
+    "numpy", "pathlib", "argparse"  
+]
+readme = "README.md"              # Path to the README file
+requires-python = ">=3.8"         # Minimum Python version
+license = {file = "LICENSE"}      # License file or name
+
+[build-system]
+requires = ["setuptools>=42", "wheel"]  # Tools needed to build the package
+build-backend = "setuptools.build_meta" # Build backend
+
+[project.scripts]
+sagittal_average_run = "sagittal_average.command:process" # Creating a run command
+
+[tool.hatch.build.targets.wheel]
+packages = [
+  "src/sagittal_average",
+]

src/sagittal_average/command.py

@@ -0,0 +1,14 @@
+from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
+import numpy as np
+from sagittal_average.sagittal_brain import run_averages
+
+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)

sagittal_brain.py → src/sagittal_average/sagittal_brain.py

@@ -16,19 +16,19 @@ def run_averages(file_input='brain_sample.csv', file_output='brain_average.csv')
 
     # Calculates the averages through the sagittal/horizontal planes
     # and makes it as a row vector
-    averages = planes.mean(axis=0)[np.newaxis, :]
+    averages = planes.mean(axis=1)[np.newaxis, :]
 
     # write it out on my file
     np.savetxt(file_output, averages, fmt='%.1f', delimiter=',')
 
 
-if __name__ == "__main__":
-    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()
+# if __name__ == "__main__":
+#     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)
+#     run_averages(arguments.file_input, arguments.file_output)

tests/test_python_file.py

@@ -0,0 +1,33 @@
+import numpy as np
+
+TEST_DIR = '/Users/sirbucks/Desktop/UCL/Coding/COMP0233_Research_SWE_Python/session_7/part2/sagittal_average/'
+
+import numpy as np
+from pathlib import Path
+import tempfile
+from src.sagittal_average.sagittal_brain import run_averages
+
+def test_sagittal_average():
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # Create an input dataset
+        data_input = np.zeros((20, 20))
+        data_input[-1, :] = 1
+
+        # Save it into a file in the temporary directory
+        input_file = Path(temp_dir) / "brain_sample.csv"
+        np.savetxt(input_file, data_input, fmt='%d', delimiter=',')
+
+        # Create an array with expected result
+        expected = np.zeros(20)
+        expected[-1] = 1
+
+        # Call the function with the files in the temporary directory
+        output_file = Path(temp_dir) / "brain_average.csv"
+        run_averages(file_input=str(input_file), 
+                     file_output=str(output_file))
+
+        # Load the result
+        result = np.loadtxt(output_file, delimiter=',')
+
+        # Compare the result with the expected values
+        np.testing.assert_array_equal(result, expected)