From ceab96bea39f1fb7447a5fa8811c40fdeeacdf0e Mon Sep 17 00:00:00 2001
From: Manos <manos@delkappa.com>
Date: Fri, 8 Oct 2021 20:14:06 +0200
Subject: [PATCH] lmdk_bgt: Tested dynamic

---
 code/lib/lmdk_bgt.py | 52 ++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 52 insertions(+)

diff --git a/code/lib/lmdk_bgt.py b/code/lib/lmdk_bgt.py
index 8ff6a7f..b4b8518 100644
--- a/code/lib/lmdk_bgt.py
+++ b/code/lib/lmdk_bgt.py
@@ -343,6 +343,58 @@ def adaptive(seq, lmdks, epsilon, inc_rt, dec_rt):
   return rls_data, bgts, skipped
 
 
+def dynamic(seq, lmdks, epsilon, inc_rt, dec_rt):
+  '''
+    Dynamic budget allocation.
+
+    Parameters:
+      seq - The point sequence.
+      lmdks - The landmarks.
+      epsilon - The available privacy budget.
+      inc_rt - Sampling rate increase rate.
+      dec_rt - Sampling rate decrease rate.
+    Returns:
+      rls_data - The perturbed data.
+      bgts - The privacy budget allocation.
+      skipped - The number of skipped releases.
+  '''
+  # Uniform budget allocation
+  bgts = uniform(seq, lmdks, epsilon)
+  # Released
+  rls_data = [None]*len(seq)
+  # The sampling rate
+  samp_rt = 1
+  # Track landmarks
+  lmdk_cur = 0
+  # Track skipped releases
+  skipped = 0
+  for i, p in enumerate(seq):
+    # Check if current point is a landmark
+    if lmdk_lib.is_landmark(p, lmdks):
+      lmdk_cur += 1
+    # Get coordinates
+    loc = (p[1], p[2])
+    if i > 0:
+      eps_dis = bgts[i]*.5
+      dis = lmdk_lib.add_laplace_noise(distance((rls_data[i - 1][1], rls_data[i - 1][2]), loc).km*1000, 1.0, eps_dis)
+      bgts[i] -= eps_dis
+    if i == 0 or distance((rls_data[i - 1][1], rls_data[i - 1][2]), loc).km*1000 > 1/bgts[i]:
+      # Add noise to original data
+      new_loc = lmdk_lib.add_polar_noise(loc, bgts[i])
+      rls_data[i] = [p[0], new_loc[0], new_loc[1], p[3]]
+    else:
+      skipped += 1
+      # Skip current release and approximate with previous
+      rls_data[i] = rls_data[i - 1]
+      if lmdk_lib.is_landmark(p, lmdks):
+        # Allocate the current budget to the following releases uniformly
+        for j in range(i + 1, len(seq)):
+          bgts[j] += bgts[i]/(len(lmdks) - lmdk_cur + 1)
+      # No budget was spent
+      bgts[i] = 0
+  return rls_data, bgts, skipped
+
+
 def adaptive_cont(seq, lmdks, epsilon, inc_rt, dec_rt):
   '''
     Adaptive budget allocation.