first commit

sho/api.py

@@ -0,0 +1,70 @@
+import numpy as np
+
+def sphere(x,offset=0.5):
+    """Computes the square of a multi-dimensional vector x."""
+    f = 0
+    for i in range(len(x)):
+        f += (x[i]-offset)**2
+    return f
+
+def square(sol,scale=1):
+    """Gnerate a random vector close at thegiven scale to the given sol."""
+    return sol + np.random.random(len(sol))*scale
+
+def greedy(objective_function, dimension, iterations, target=1e-3, neighborhood=square, scale=1/100, history=None):
+    """Search the given objective_function of the given dimension,
+    during the given number of iterations, generating solution
+    with the given neighborhood.
+    Returns the best value of the function and the best solution."""
+    best_sol = np.random.random(dimension)
+    best_val = objective_function(best_sol)
+    for i in range(iterations):
+        sol = neighborhood(best_sol,scale)
+        val = objective_function(sol)
+        if val < best_val:
+            best_val = val
+            best_sol = sol
+        if history is not None:
+            history.append((val,sol))
+        if val < target: # Assume the optimum is zero
+            break
+    return best_val, best_sol
+
+
+if __name__=="__main__":
+    import matplotlib.pyplot as plt
+    from mpl_toolkits.mplot3d import Axes3D
+    import argparse
+    import plot
+
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("-d", "--dim", metavar="NB", default=2, type=int,
+            help="Number of dimensions")
+
+    functions = {"sphere":sphere}
+    parser.add_argument("-f", "--func", metavar="NAME", choices=functions, default="sphere",
+            help="Objective function")
+
+    parser.add_argument("-i", "--iter", metavar="NB", default=1000, type=int,
+            help="Maximum number of iterations")
+
+    parser.add_argument("-t", "--target", metavar="VAL", default=1e-3, type=float,
+            help="Function value target delta")
+
+    parser.add_argument("-s", "--seed", metavar="VAL", default=0, type=int,
+            help="Random pseudo-generator seed (0 for epoch)")
+
+    asked = parser.parse_args()
+
+    np.random.seed(asked.seed)
+
+    history = []
+    val,sol = greedy(functions[asked.func], asked.dim, asked.iter, asked.target, square, 0.03, history)
+
+    fig = plt.figure()
+    ax = fig.gca(projection='3d')
+    shape = (20,20)
+    plot.surface(ax, shape, sphere)
+    plot.path(ax, shape, history)
+    plt.show()