Data commit

Task/Entropy/Python/entropy-1.py

@@ -0,0 +1,34 @@
+from __future__ import division
+import math
+
+def hist(source):
+    hist = {}; l = 0;
+    for e in source:
+        l += 1
+        if e not in hist:
+            hist[e] = 0
+        hist[e] += 1
+    return (l,hist)
+
+def entropy(hist,l):
+    elist = []
+    for v in hist.values():
+        c = v / l
+        elist.append(-c * math.log(c ,2))
+    return sum(elist)
+
+def printHist(h):
+    flip = lambda (k,v) : (v,k)
+    h = sorted(h.iteritems(), key = flip)
+    print 'Sym\thi\tfi\tInf'
+    for (k,v) in h:
+        print '%s\t%f\t%f\t%f'%(k,v,v/l,-math.log(v/l, 2))
+
+
+
+source = "1223334444"
+(l,h) = hist(source);
+print '.[Results].'
+print 'Length',l
+print 'Entropy:', entropy(h, l)
+printHist(h)

Task/Entropy/Python/entropy-2.py

@@ -0,0 +1,8 @@
+from math import log2
+from collections import Counter
+
+def entropy(s):
+    p, lns = Counter(s), float(len(s))
+    return log2(lns) - sum(count * log2(count) for count in p.values()) / lns
+
+print(entropy("1223334444"))

Task/Entropy/Python/entropy-3.py

@@ -0,0 +1,19 @@
+def Entropy(text):
+    import math
+    log2=lambda x:math.log(x)/math.log(2)
+    exr={}
+    infoc=0
+    for each in text:
+        try:
+            exr[each]+=1
+        except:
+            exr[each]=1
+    textlen=len(text)
+    for k,v in exr.items():
+        freq  =  1.0*v/textlen
+        infoc+=freq*log2(freq)
+    infoc*=-1
+    return infoc
+
+while True:
+    print Entropy(raw_input('>>>'))