O1: update theoretical plots

one_run_audit/plot.py

@@ -1,21 +1,94 @@
+import time
+import math
+import concurrent.futures
 import numpy as np
 import matplotlib.pyplot as plt
-from tqdm import tqdm
 from equations import get_eps_audit
 
 
-delta = 1e-5
+def compute_y(x_values, p, delta, proportion_correct, key):
-p_value = 0.05
+    return key, [get_eps_audit(x, x, math.floor(x *proportion_correct),  delta, p) for x in x_values]
 
-x_values = np.floor((1.5)**np.arange(30)).astype(int)
-x_values = np.concatenate([x_values[x_values < 60000], [60000]])
-y_values = [get_eps_audit(x, x, x, delta, p_value) for x in tqdm(x_values)]
 
-plt.xscale('log')
+def get_plots():
-plt.plot(x_values, y_values, marker='o')
+    final_values = dict()
-plt.xlabel("Number of samples guessed correctly")
+    mul = 1.5 #1.275 #1.5
-plt.ylabel("ε value audited")
+    max = 60000 #2000 #60000
-plt.title("Maximum possible ε from audit")
 
-# 5. Save the plot as a PNG
+    x_values = np.floor((mul)**np.arange(30)).astype(int)
-plt.savefig("/dev/shm/my_plot.png", dpi=300, bbox_inches='tight')
+    x_values = np.concatenate([x_values[x_values < max], [max]])
+
+    with concurrent.futures.ProcessPoolExecutor(max_workers=16) as executor:
+        start_time = time.time()
+        futures = [
+            executor.submit(compute_y, x_values, 0.05,  0.0, 1.0, "y11"),
+            executor.submit(compute_y, x_values, 0.05, 1e-6, 1.0, "y12"),
+            executor.submit(compute_y, x_values, 0.05, 1e-4, 1.0, "y13"),
+            executor.submit(compute_y, x_values, 0.05, 1e-2, 1.0, "y14"),
+            executor.submit(compute_y, x_values, 0.01,  0.0, 1.0, "y21"),
+            executor.submit(compute_y, x_values, 0.01, 1e-6, 1.0, "y22"),
+            executor.submit(compute_y, x_values, 0.01, 1e-4, 1.0, "y23"),
+            executor.submit(compute_y, x_values, 0.01, 1e-2, 1.0, "y24"),
+            executor.submit(compute_y, x_values, 0.05,  0.0, 0.9, "y31"),
+            executor.submit(compute_y, x_values, 0.05, 1e-6, 0.9, "y32"),
+            executor.submit(compute_y, x_values, 0.05, 1e-4, 0.9, "y33"),
+            executor.submit(compute_y, x_values, 0.05, 1e-2, 0.9, "y34"),
+            executor.submit(compute_y, x_values, 0.01,  0.0, 0.9, "y41"),
+            executor.submit(compute_y, x_values, 0.01, 1e-6, 0.9, "y42"),
+            executor.submit(compute_y, x_values, 0.01, 1e-4, 0.9, "y43"),
+            executor.submit(compute_y, x_values, 0.01, 1e-2, 0.9, "y44"),
+        ]
+
+        for future in concurrent.futures.as_completed(futures):
+            k, v = future.result()
+            final_values[k] = v
+        print(f"Took: {time.time()-start_time}s")
+
+    return final_values, x_values
+
+
+def plot_to(value_set, x_values, title, fig_name):
+    plt.xscale('log')
+    plt.plot(x_values, value_set[0], marker='o', label='δ=0')
+    plt.plot(x_values, value_set[1], marker='o', label='δ=1e-6')
+    plt.plot(x_values, value_set[2], marker='o', label='δ=1e-4')
+    plt.plot(x_values, value_set[3], marker='o', label='δ=1e-2')
+
+    plt.xlabel("Number of samples attacked")
+    plt.ylabel("Maximum ε lower-bound from audit")
+    plt.title(title)
+    plt.legend()
+    plt.savefig(fig_name, dpi=300, bbox_inches='tight')
+
+
+def main():
+    final_values, x_values = get_plots()
+
+    plot_to(
+        [final_values[f"y1{i}"] for i in range(1,5)],
+        x_values,
+        "Maximum ε audit with p-value=0.05 and 100% MIA accuracy",
+        "/dev/shm/plot_05_100.png"
+    )
+    plot_to(
+        [final_values[f"y1{i}"] for i in range(1,5)],
+        x_values,
+        "Maximum ε audit with p-value=0.01 and 100% MIA accuracy",
+        "/dev/shm/plot_01_100.png"
+    )
+    plot_to(
+        [final_values[f"y1{i}"] for i in range(1,5)],
+        x_values,
+        "Maximum ε audit with p-value=0.05 and 90% MIA accuracy",
+        "/dev/shm/plot_05_90.png"
+    )
+    plot_to(
+        [final_values[f"y1{i}"] for i in range(1,5)],
+        x_values,
+        "Maximum ε audit with p-value=0.01 and 90% MIA accuracy"
+        "/dev/shm/plot_01_90.png"
+    )
+
+
+if __name__ == '__main__':
+    main()