move modules to subdirectory

[imago.git] / imago_pack / cs.py

diff --git a/imago_pack/cs.py b/imago_pack/cs.py
new file mode 100644 (file)
index 0000000..7c91119
--- /dev/null
+++ b/imago_pack/cs.py
@@ -0,0 +1,71 @@
+"""Cuckoo search optimization"""
+
+import random
+import lhs
+from math import sin, gamma, pi
+
+class Space(object):
+    def __init__(self, dimension, bound, d_function, n_nest):
+        self.pa = 0.25 #parameter
+        self.dimension = dimension
+        self.bound = bound
+        self.d_function = d_function
+        self.nests = [(d_function(*p), p) for p in lhs.latin_hypercube(dimension, bound, n_nest)]
+        self.best_value, self.best = max(self.nests)
+
+def new_nest(space):
+        position = [2 * space.bound * random.random() 
+                    - space.bound for _ in xrange(space.dimension)]
+        value = space.d_function(*position)
+        return (value, position)
+
+def get_cuckoos(space):
+    beta = 1.5
+    sigma = (gamma(1. + beta) * sin(pi * beta / 2.) / (gamma((1. + beta) / 2.) *
+             beta * 2. ** ((beta - 1.) / 2))) ** (1. / beta)
+    u_a = [[random.gauss(0, 1) * sigma for _ in xrange(space.dimension)] for _ in
+         xrange(len(space.nests))]
+    v_a = [[random.gauss(0, 1) for _ in xrange(space.dimension)] for _ in
+         xrange(len(space.nests))]
+    r_a = [[random.gauss(0, 1) for _ in xrange(space.dimension)] for _ in
+         xrange(len(space.nests))]
+    step = [[u / abs(v) ** (1. / beta) for (u, v) in zip(u_l, v_l)]
+            for (u_l, v_l) in zip(u_a, v_a)]
+    stepsize = [[0.01 * st * (n_e - be) for (st, n_e, be) 
+                in zip(step_l, n_l, space.best)]
+                for (step_l, (_, n_l)) in zip(step, space.nests)]
+    s = [[n + st * r for (n, st, r) in zip(n_l, st_l, r_l)]
+         for ((_, n_l), st_l, r_l) in zip(space.nests, stepsize, r_a)]
+    cuckoos = [[min(max(st, - space.bound), space.bound) for st in st_l]
+         for st_l in s]
+    return [(space.d_function(*c), c) for c in cuckoos]
+
+def get_empty(space):
+    r = random.random()
+    r_arr = [[random.random() for _ in xrange(space.dimension)] for _ in
+             xrange(len(space.nests))]
+    perm1 = [n for (_, n) in space.nests]
+    random.shuffle(perm1)
+    perm2 = [n for (_, n) in space.nests]
+    random.shuffle(perm2)
+    stepsize = [[p1 - p2 for (p1, p2) in zip (p1l, p2l)] for (p1l, p2l) in
+                zip(perm1, perm2)]
+    step = [[(r * p * (1 if random.random() > space.pa else 0)) for p in n] for n in stepsize]
+    empty = [[(p + s) for (p, s) in zip(sl, n)] 
+            for (sl, (_, n)) in zip(step, space.nests)]
+    empty = [[min(max(st, - space.bound), space.bound) for st in st_l]
+         for st_l in empty]
+    return [(space.d_function(*e), e) for e in empty]
+
+def next_turn(space):
+    cuckoos = get_cuckoos(space)
+    space.nests = [max(n, m) for (n, m) in zip(space.nests, cuckoos)]
+    nests = get_empty(space)
+    space.nests = [max(n, m) for (n, m) in zip(space.nests, nests)]
+    space.best_value, space.best = max(space.nests)
+
+def optimize(dimension, boundary, function_d, n_nest, n_turns):
+    space = Space(dimension, boundary, function_d, n_nest)
+    for _ in xrange(n_turns):
+        next_turn(space)
+    return space.best