From 5566b44a890f539e164c18172d41af9f6d748917 Mon Sep 17 00:00:00 2001
From: Kailash Budhathoki <kbudhath@mpi-inf.mpg.de>
Date: Wed, 25 Apr 2018 13:28:38 +0200
Subject: [PATCH] acid added

---
 acid.py    | 91 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 entropy.py |  8 ++++-
 2 files changed, 98 insertions(+), 1 deletion(-)
 create mode 100644 acid.py

diff --git a/acid.py b/acid.py
new file mode 100644
index 0000000..c8f05c0
--- /dev/null
+++ b/acid.py
@@ -0,0 +1,91 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+from collections import Counter, defaultdict
+from copy import copy
+import random
+import sys
+import time
+
+from entropy import entropy
+
+
+__author__ = "Kailash Budhathoki"
+__email__ = "kbudhath@mpi-inf.mpg.de"
+__copyright__ = "Copyright (c) 2018"
+__license__ = "MIT"
+
+
+def marginals(X, Y):
+    Ys = defaultdict(list)
+    for i, x in enumerate(X):
+        Ys[x].append(Y[i])
+    return Ys
+
+
+def map_to_majority(X, Y):
+    f = dict()
+    subgroups_y = defaultdict(list)
+
+    for i, x in enumerate(X):
+        subgroups_y[x].append(Y[i])
+
+    for x, subgroup_y in subgroups_y.iteritems():
+        freq_y, _ = Counter(subgroup_y).most_common(1)[0]
+        f[x] = freq_y
+
+    return f
+
+
+def regress(X, Y):
+    # target Y, feature X
+    max_iterations = 10000
+    hx = entropy(X)
+    len_dom_y = len(set(Y))
+    f = map_to_majority(X, Y)
+
+    supp_x = list(set(X))
+    supp_y = list(set(Y))
+
+    pair = zip(X, Y)
+    res = [y - f[x] for x, y in pair]
+    cur_res_codelen = entropy(res)
+
+    j = 0
+    minimized = True
+    while j < max_iterations and minimized:
+        minimized = False
+
+        for x_to_map in supp_x:
+            best_res_codelen = sys.float_info.max
+            best_cand_y = None
+
+            for cand_y in supp_y:
+                if cand_y == f[x_to_map]:
+                    continue
+
+                res = [y - f[x] if x != x_to_map else y -
+                       cand_y for x, y in pair]
+                res_codelen = entropy(res)
+
+                if res_codelen < best_res_codelen:
+                    best_res_codelen = res_codelen
+                    best_cand_y = cand_y
+
+            if best_res_codelen < cur_res_codelen:
+                cur_res_codelen = best_res_codelen
+                f[x_to_map] = best_cand_y
+                minimized = True
+        j += 1
+    return hx + cur_res_codelen
+
+
+def acid(X, Y):
+    hxtoy = regress(X, Y)
+    hytox = regress(Y, X)
+    return (hxtoy, hytox)
+
+
+if __name__ == "__main__":
+    from test_benchmark import load_pair
+    X, Y = load_pair(99)
+    print acid(X, Y)
diff --git a/entropy.py b/entropy.py
index 40f3a0c..d4a162a 100644
--- a/entropy.py
+++ b/entropy.py
@@ -6,6 +6,12 @@
 from math import log
 
 
+__author__ = "Kailash Budhathoki"
+__email__ = "kbudhath@mpi-inf.mpg.de"
+__copyright__ = "Copyright (c) 2018"
+__license__ = "MIT"
+
+
 def entropy(sequence):
     res = 0
     n = len(sequence)
@@ -15,7 +21,7 @@ def entropy(sequence):
     return res
 
 
-if __name__=="__main__":
+if __name__ == "__main__":
     print entropy([1, 2, 1, 1, 1, 1])
     print entropy([1, 1, 1, 1, 1, 1])
     print entropy([1, 1, 1, 2, 2, 2])