Add support for new feature

.gitignore

@@ -1,6 +1,7 @@
 # IDEs
 .vscode/
 .idea/
+.venv/
 
 # Intermediate Coverage file
 .coverage

README.md

@@ -1,17 +1,34 @@
-# Introduction
+# Inflam
+![Continuous Integration build in GitHub Actions](https://github.com/JBello1610/python-intermediate-inflammation/workflows/CI/badge.svg?branch=main)
 
-This is a template software project repository used by the [Intermediate Research Software Development Skills In Python](https://github.com/carpentries-incubator/python-intermediate-development).
+Inflam is a data management system written in Python that manages trial data used in clinical inflammation studies.
 
-## Purpose
+## Main Features
+Here are some  key features of Inflam:
 
-This repository is intended to be used as a code template which is copied by learners at [Intermediate Research Software Development Skills In Python](https://github.com/carpentries-incubator/python-intermediate-development) course.
-This can be done using the `Use this template` button towards the top right of this repo's GitHub page.
+- Provide basic statistical analyses over clinical trial data
+- Ability ti woek on trial data in Comma0-Seperated Value (CSV) format.
+- Generate plots of trial data.
+- Analytical functions and views can be easily extended based on its Model-View-Controller architecture
 
-This software project is not finished, is currently failing to run and contains some code style issues. It is used as a starting point for the course - issues will be fixed and code will be added in a number of places during the course by learners in their own copies of the repository, as course topics are introduced.
+## Prerequisites
+Inflam requires the following Python packages:
 
-## Tests
+- [NumPy](https://www.numpy.org/) - makes use of NumPy's statistical functions.
+- [Matplotlib](https://matplotlib.org/stable/index.html) - uses Matplotlib to generate statistical plots
 
-Several tests have been implemented already, some of which are currently failing.
-These failing tests set out the requirements for the additional code to be implemented during the workshop.
+The following optional packages are required to run Inflam's unit tests:
 
-The tests should be run using `pytest`, which will be introduced during the workshop.
+- [pytest](https://docs.pytest.org/stable/) - Inflam's unit tests are written using pytest
+- [pytest-cov](https://pypi.org/project/pytest-cov/) - Adds test coverage stats to unit testing
+
+## Installation
+Can be installed and run by cloning this git repository and running the below commands:
+
+```bash
+git clone [email protected]:JBello1610/python-intermediate-inflammation.git
+
+cd python-intermediate-inflammation/
+
+python inflammation-analysis.py
+```

inflammation-analysis.py

@@ -27,7 +27,8 @@ def main(args):
     for filename in InFiles:
         inflammation_data = models.load_csv(filename)
 
-        view_data = {'average': models.daily_mean(inflammation_data), 'max': models.daily_max(inflammation_data), 'min': models.daily_min(inflammation_data)}
+        view_data = {'average': models.daily_mean(inflammation_data), 'max': models.daily_max(inflammation_data), 'min': models.daily_min(inflammation_data), **(models.s_dev(inflammation_data))}
+
 
         views.visualize(view_data)
 

inflammation/models.py

@@ -2,8 +2,8 @@
 
 The Model layer is responsible for the 'business logic' part of the software.
 
-Patients' data is held in an inflammation table (2D array) where each row contains 
-inflammation data for a single patient taken over a number of days 
+Patients' data is held in an inflammation table (2D array) where each row contains
+inflammation data for a single patient taken over a number of days
 and each column represents a single day across all patients.
 """
 
@@ -16,7 +16,8 @@ def load_csv(filename):
 
     :param filename: Filename of CSV to load
     """
-    return np.loadtxt(fname=filename, delimiter=',')
+    return np.loadtxt(fname=filename, delimiter=",")
+
 
 def load_json(filename):
     """Load a numpy array from a JSON document.
@@ -34,10 +35,9 @@ def load_json(filename):
     :param filename: Filename of CSV to load
 
     """
-    with open(filename, 'r', encoding='utf-8') as file:
+    with open(filename, "r", encoding="utf-8") as file:
         data_as_json = json.load(file)
-        return [np.array(entry['observations']) for entry in data_as_json]
-
+        return [np.array(entry["observations"]) for entry in data_as_json]
 
 
 def daily_mean(data):
@@ -54,3 +54,13 @@ def daily_min(data):
     """Calculate the daily min of a 2d inflammation data array."""
     return np.min(data, axis=0)
 
+
+def s_dev(data):
+    """Computes and returns standard deviation for data."""
+    mean_of_data = np.mean(data, axis=0)
+    devs = []
+    for entry in data:
+        devs.append((entry - mean_of_data) * (entry - mean_of_data))
+
+    standard_dev = sum(devs) / len(data)
+    return {"standard deviation": np.sqrt(standard_dev)}

tests/test_models.py

@@ -3,15 +3,14 @@
 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."""
     from inflammation.models import daily_mean
 
-    test_input = np.array([[0, 0],
-                           [0, 0],
-                           [0, 0]])
+    test_input = np.array([[0, 0], [0, 0], [0, 0]])
     test_result = np.array([0, 0])
 
     # Need to use Numpy testing functions to compare arrays
@@ -22,18 +21,33 @@ def test_daily_mean_integers():
     """Test that mean function works for an array of positive integers."""
     from inflammation.models import daily_mean
 
-    test_input = np.array([[1, 2],
-                           [3, 4],
-                           [5, 6]])
+    test_input = np.array([[1, 2], [3, 4], [5, 6]])
     test_result = np.array([3, 4])
 
     # Need to use Numpy testing functions to compare arrays
     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:
+
+    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(
+    "data, expected_standard_deviation",
+    [
+        ([0, 0, 0], 0.0),
+        ([1.0, 1.0, 1.0], 0),
+        ([1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 5.0, 5.0, 10.0], 2.4088314876309775),
+    ],
+)
+def test_daily_standard_deviation(data, expected_standard_deviation):
+    from inflammation.models import s_dev
+
+    result_data = s_dev(data)["standard deviation"]
+    npt.assert_approx_equal(result_data, expected_standard_deviation)