packaging

.github/workflows/pytest.yml

@@ -0,0 +1,28 @@
+name: Python package
+
+on: [push]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.8", "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 dependencies
+        # This case we are only updating pip, but you could add other dependencies needed.
+        run: |
+          python -m pip install --upgrade pip
+      - name: Test with pytest
+        run: |
+          pytest
+      - name: Install package #reinstall the package everytime it tests
+        run: |
+          pip install .

.gitignore

@@ -0,0 +1,3 @@
+brain_average.csv/
+brain_expected.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 2022
+
+This "sagittal_average" example package is granted into the public domain.

README.md

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+# Sagittal Average
+
+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
+
+Browse to the directory where this file lives, and run:
+```bash
+pip install .
+```
+That command will download any dependencies we have
+
+
+## Usage
+
+Invoke the tool with `sagittal_average_run <input_file_Dir>` or use it on your own library:
+
+```python
+from sagittal_average import sagittal_brain
+
+sagittal_brain.run_averages("input_file.csv", "ouput_file.csv")
+```

brain_average.csv

@@ -1 +1 @@
-10.5,11.5,12.5,13.5,14.5,15.5,16.5,17.5,18.5,19.5,20.5,21.5,22.5,23.5,24.5,25.5,26.5,27.5,28.5,29.5
+0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0

brain_expected.csv

@@ -0,0 +1,3 @@
+0.000000
+0.000000
+1.000000

brain_sample.csv

@@ -1,20 +1,20 @@
-1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
-2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21
-3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22
-4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23
-5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24
-6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25
-7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26
-8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27
-9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28
-10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29
-11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30
-12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31
-13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32
-14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33
-15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34
-16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35
-17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36
-18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37
-19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38
-20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1

mt_dir_4_testing/mt.py

@@ -0,0 +1,4 @@
+
+
+
+

sagittal_average.egg-info/PKG-INFO

@@ -0,0 +1,10 @@
+Metadata-Version: 2.1
+Name: sagittal-average
+Version: 0.1.0
+Summary: UNKNOWN
+Home-page: UNKNOWN
+License: UNKNOWN
+Platform: UNKNOWN
+
+UNKNOWN
+

sagittal_average.egg-info/SOURCES.txt

@@ -0,0 +1,13 @@
+setup.py
+sagittal_average/__init__.py
+sagittal_average/command.py
+sagittal_average/sagittal_brain.py
+sagittal_average.egg-info/PKG-INFO
+sagittal_average.egg-info/SOURCES.txt
+sagittal_average.egg-info/dependency_links.txt
+sagittal_average.egg-info/entry_points.txt
+sagittal_average.egg-info/requires.txt
+sagittal_average.egg-info/top_level.txt
+sagittal_average/test/__init__.py
+sagittal_average/test/test_call_command.py
+sagittal_average/test/test_sagittal_brain.py

sagittal_average.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

sagittal_average.egg-info/entry_points.txt

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+[console_scripts]
+sagittal_average_run = sagittal_average.command:process
+

sagittal_average.egg-info/requires.txt

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+numpy

sagittal_average.egg-info/top_level.txt

@@ -0,0 +1 @@
+sagittal_average

sagittal_average/command.py

@@ -0,0 +1,16 @@
+from sagittal_average.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)
+
+
+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, :] #axis must =1 to average over rows and not =0 which will av over columns
+
+    # 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()
+
+#     run_averages(arguments.file_input, arguments.file_output)

sagittal_average/test/test_call_command.py

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+import subprocess
+
+
+#must run this file in terminal
+#these basically just let us run terminal commands when we run this python file from a terminal
+
+subprocess.run(["ls", "-aF"], shell=True) #lists all files in current dir
+subprocess.run(["ls", "-lh"], shell=True) #lists all files in current dir (in seperate linesw details)
+subprocess.run(["echo", 'hello world'], shell=True) #prints hello world in the screen
+subprocess.run(["date",  '+%Y%m%d'], shell=True) #prints today's date with the selected format
+subprocess.run(["wc", "-l", "sagittal_brain.py"], shell=True) #counts the number of lines of the sagittal_brain.py file
+subprocess.run(["wc", "-c", "AFileThatDoesNot.exist"], shell=True) #which should counts the number of characters, but should fail as the file doesn't exist

sagittal_average/test/test_sagittal_brain.py

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+from sagittal_average.sagittal_brain import *
+import subprocess
+#RUN FROM BASH TERMINAL
+
+import numpy as np
+
+
+# sample = np.array([[0,0,0], [0,0,0], [1,1,1]])
+# np.savetxt('brain_sample.csv', sample, delimiter=',', fmt='%i') #save as csv and integers
+
+# expected = np.asarray([0., 0., 1.])
+# np.savetxt('brain_expected.csv',expected, delimiter=',', fmt='%f') #save as csv and integers
+# #NB: ik the expected csv looks different format to the output the arrays are the same format which is what matters for testing
+
+
+
+
+# subprocess.run(['python', 'sagittal_brain.py'], shell=True) #run the main py file and create the brain_average result file
+
+# read_output = np.loadtxt('brain_average.csv', delimiter=',') #read the file (ie convert to array)
+
+
+# #test:
+# np.testing.assert_array_equal(read_output, expected)
+
+
+
+def test_brain(): #create the above into a function for pytest
+    data_input = np.zeros((20, 20)) #20x20 instead of 1x3 like before
+    data_input[-1, :] = 1 #make last row = 1
+
+    np.savetxt("brain_sample.csv", data_input, fmt='%d', delimiter=',')
+
+
+    # The expeted 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=',')
+
+
+    return np.testing.assert_array_equal(result, expected)
+
+

setup.py

@@ -0,0 +1,14 @@
+from setuptools import setup, find_packages
+
+setup(
+    name="sagittal_average",  
+    version="0.1.0",
+    packages=find_packages(),
+    install_requires=['numpy'],
+    entry_points={
+        'console_scripts': [
+            'sagittal_average_run = sagittal_average.command:process']}
+)
+
+#The name of the package above is NOT the name that you type when doing `import ...` 
+#bc that name is the name of the folder which command.py is in ???