Added Analysis plots and updated the reqs file

Author: NishilAmin1213

requirements.txt

@@ -3,4 +3,5 @@ pytest
 pytest-asyncio
 matplotlib~=3.9.4
 tqdm
-requests
+requests
+numpy

src/analysis/analysis.py

@@ -0,0 +1,95 @@
+from distutils.dep_util import newer_pairwise
+from idlelib.colorizer import color_config
+
+from PIL.ImageColor import colormap
+
+from src.infrastructure.file_utils import read_csv
+import matplotlib.pyplot as plt
+import numpy as np
+
+def create_size_impact_plot():
+    # 3. How does the size of a commit impact the results?
+
+    # Read data from the repo_data csv
+    repo_data = read_csv("repo_data")
+
+    # Initialize arrays to store plot points
+    x = []
+    y = []
+
+    # Iterate through each repo and create a point in the two arrays
+    for repo in repo_data:
+        # Append the commit count of the repo to X
+        x.append(int(repo['Commit Count']))
+
+        # Get the total number of tests for the repo
+        total_test_count = int(repo['Test Before']) + int(repo['Test During']) + int(repo['Test After'])
+
+        # Append the percentage of TDD for the repo to Y
+        y.append((int(repo['Test Before'])/total_test_count)*100)
+
+    # Convert arrays to numpy arrays
+    x = np.array(x)
+    y = np.array(y)
+
+    # Plot the scatter points
+    plt.scatter(x, y, c=y, cmap = 'winter')
+
+    # Calculate and plot the line of best fit
+    a, b = np.polyfit(x, y, 1)
+    plt.plot(x, a * x + b, color="red", alpha=0.5)
+
+    # Set title and axes labels
+    plt.xlabel("Commit Count")
+    plt.ylabel("Percentage of TDD")
+    plt.title("Scatter plot showing how the size of commits impacts results")
+
+    # Show the plot
+    plt.show()
+
+def create_box_plot():
+    # 2. How often is a test class (file) created (a) before, (b) after, or (c) in the same commit as a tested class (file)?
+
+    # Read data from the repo_data csv
+    repo_data = read_csv("repo_data")
+
+    # Initialize arrays to store percentages for each repo
+    before = []
+    during = []
+    after = []
+
+    # Iterate through each repo and append the before, during and after percentages to each array
+    for repo in repo_data:
+        # Get the total number of tests for the repo
+        total_test_count = int(repo['Test Before']) + int(repo['Test During']) + int(repo['Test After'])
+
+        # Append the percentage data to each array
+        before.append((int(repo['Test Before']) / total_test_count) * 100)
+        during.append((int(repo['Test During']) / total_test_count) * 100)
+        after.append((int(repo['Test After']) / total_test_count) * 100)
+
+    # Plot the box plots
+    boxplt = plt.boxplot([before, during, after], patch_artist=True, tick_labels=["Before", "During", "After"], flierprops= dict(markerfacecolor='coral'))
+
+    colors = ['lightskyblue', 'paleturquoise', 'palegreen']
+    for patch, color in zip(boxplt['boxes'], colors):
+        patch.set_facecolor(color)
+
+    # Set title and axes labels
+    plt.ylabel("Percentage")
+    plt.title("Boxplot showing how often a test is created\nbefore, during and after implementation")
+
+    # Show the plot
+    plt.show()
+
+
+create_size_impact_plot()
+create_box_plot()
+
+'''
+
+8. How does TDD adoption vary between projects?
+
+'''
+
+