ajout fonctions de base pour parse des données et les analyser

main.py

@@ -0,0 +1,36 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+from generate_data import *
+from analyze import *
+from poll import *
+
+def plot_temperature_data(df, recent_count=None):
+    plt.figure(figsize=(10, 5))
+    
+    # Check if recent_count is specified and valid
+    if recent_count is not None and recent_count > 0:
+        df = df.tail(recent_count)  # Slice the DataFrame to get the last 'recent_count' rows
+    
+    plt.plot(df['time'], df['value'], label='Temperature', color='tab:red')
+    plt.title('Temperature Over Time')
+    plt.xlabel('Time')
+    plt.ylabel('Temperature (°C)')
+    plt.grid(True)
+    plt.legend()
+    plt.xticks(rotation=45)  # Rotates the x-axis labels to make them more readable
+    plt.tight_layout()  # Adjusts subplot params so that the subplot(s) fits in to the figure area.
+    plt.show()
+
+# Load the data from the CSV file
+df  = generate_greenhouse_data("datasets/greenhouse.csv")
+plot_temperature_data(df)
+df2 = sample_every_kth_point(df,50)
+
+diff1 = distribution_of_differences(df, 'value')
+diff2 = distribution_of_differences(df2, 'value')
+
+diff1 = diff1[diff1 <= 10]
+diff2 = diff2[diff2 <= 10]
+
+plot_histogram(diff1,bins=20, title='Distribution of Absolute Differences (Original Data)')
+plot_histogram(diff2, bins=20, title='Distribution of Absolute Differences (Sampled Data)')