Pull request test

.github/workflows/main.yml

@@ -0,0 +1,34 @@
+name: CI
+
+# We can specify which Github events will trigger a CI build
+on: push
+
+# now define a single job 'build' (but could define more)
+jobs:
+
+  build:
+
+    # we can also specify the OS to run tests on
+    runs-on: ubuntu-latest
+
+    # a job is a seq of steps
+    steps:
+
+    # Next we need to checkout out repository, and set up Python
+    # A 'name' is just an optional label shown in the log - helpful to clarify progress - and can be anything
+    - name: Checkout repository
+      uses: actions/checkout@v2
+
+    - name: Set up Python 3.9
+      uses: actions/setup-python@v2
+      with:
+        python-version: "3.9"
+
+    - name: Install Python dependencies
+      run: |
+        python3 -m pip install --upgrade pip
+        pip3 install -r requirements.txt
+
+    - name: Test with PyTest
+      run: |
+        python -m pytest --cov=inflammation.models tests/test_models.py

inflammation/models.py

@@ -54,3 +54,7 @@ def daily_min(data):
     """Calculate the daily min of a 2d inflammation data array."""
     return np.min(data, axis=0)
 
+def patient_normalise(data):
+    """Normalise patient data from a 2D inflammation data array."""
+    max_data = np.max(data, axis=1)
+    return data / max_data[:, np.newaxis]

requirements.txt

@@ -0,0 +1,3 @@
+numpy
+pytest
+pytest-cov

tests/test_models.py

@@ -3,7 +3,7 @@
 import numpy as np
 import numpy.testing as npt
 import os
-
+import pytest
 
 def test_daily_mean_zeros():
     """Test that mean function works for an array of zeros."""
@@ -31,9 +31,66 @@ def test_daily_mean_integers():
     npt.assert_array_equal(daily_mean(test_input), test_result)
 
 def test_load_from_json(tmpdir):
+
     from inflammation.models import load_json
     example_path = os.path.join(tmpdir, 'example.json')
     with open(example_path, 'w') as temp_json_file:
         temp_json_file.write('[{"observations":[1, 2, 3]},{"observations":[4, 5, 6]}]')
     result = load_json(example_path)
     npt.assert_array_equal(result, [[1, 2, 3], [4, 5, 6]])
+
+
+@pytest.mark.parametrize(
+    "test, expected",
+    [
+        ([ [0, 0, 0], [0, 0, 0], [0, 0, 0] ], [0, 0, 0]),
+        ([ [4, 2, 5], [1, 6, 2], [4, 1, 9] ], [4, 6, 9]),
+        ([ [4, -2, 5], [1, -6, 2], [-4, -1, 9] ], [4, -1, 9]),
+    ])
+
+def test_daily_max(test, expected):
+    """Test max function works for zeroes, positive integers, mix of positive/negative integers."""
+    from inflammation.models import daily_max
+    npt.assert_array_equal(daily_max(np.array(test)), np.array(expected))
+
+
+@pytest.mark.parametrize(
+    "test, expected",
+    [
+        ([ [0, 0, 0], [0, 0, 0], [0, 0, 0] ], [0, 0, 0]),
+        ([ [4, 2, 5], [1, 6, 2], [4, 1, 9] ], [1, 1, 2]),
+        ([ [4, -2, 5], [1, -6, 2], [-4, -1, 9] ], [-4, -6, 2]),
+    ])
+def test_daily_min(test, expected):
+    """Test min function works for zeroes, positive integers, mix of positive/negative integers."""
+    from inflammation.models import daily_min
+    npt.assert_array_equal(daily_min(np.array(test)), np.array(expected))
+
+def test_daily_min_string():
+    """Test for TypeError when passing strings"""
+    from inflammation.models import daily_min
+
+    with pytest.raises(TypeError):
+        error_expected = daily_min ([['Hello', 'there'], ['General', 'Kenobi']])
+
+@pytest.mark.parametrize(
+    "test, expected",
+    [
+        ([ [0, 0], [0, 0], [0, 0] ], [0, 0]),
+        ([ [1, 2], [3, 4], [5, 6] ], [3, 4]),
+    ])
+def test_daily_mean(test, expected):
+    """Test mean function works for array of zeroes and positive integers."""
+    from inflammation.models import daily_mean
+    npt.assert_array_equal(daily_mean(np.array(test)), np.array(expected))
+
+@pytest.mark.parametrize(
+    "test, expected",
+    [
+        ([[1, 2, 3], [4, 5, 6], [7, 8, 9]], [[0.33, 0.67, 1], [0.67, 0.83, 1], [0.78, 0.89, 1]])
+    ])
+def test_patient_normalise(test, expected):
+    """Test normalisation works for arrays of one and positive integers.
+       Assumption that test accuracy of two decimal places is sufficient."""
+    from inflammation.models import patient_normalise
+    npt.assert_almost_equal(patient_normalise(np.array(test)), np.array(expected), decimal=2)