你能写出粒子群优化算法优化Gabor变换的Python代码么

当然可以！下面是代码：

import numpy as np

def PSO_Gabor(func, x0, bounds, niters=100, nparticles=20, w=0.5, c1=1, c2=1):
    nparams = len(bounds)
    x = np.zeros((nparticles, nparams))
    v = np.zeros_like(x)
    pbest = np.zeros_like(x)
    fitness = np.zeros(nparticles)
    gbest = np.zeros(nparams)
    gbest_fitness = np.inf
    
    for i in range(nparticles):
        x[i,:] = x0 + np.random.uniform(-1, 1, size=nparams)
        v[i,:] = np.random.uniform(-1, 1, size=nparams)
        pbest[i,:] = x[i,:]
        fitness[i] = func(x[i,:])
        if fitness[i] < gbest_fitness:
            gbest_fitness = fitness[i]
            gbest = x[i,:]
    
    for _ in range(niters):
        for i in range(nparticles):
            v[i,:] = w*v[i,:] + c1*np.random.uniform(0,1,size=nparams)*(pbest[i,:] - x[i,:]) + c2*np.random.uniform(0,1,size=nparams)*(gbest - x[i,:])
            x[i,:] = np.clip(x[i,:] + v[i,:], bounds[:,0], bounds[:,1])
            fitness[i] = func(x[i,:])
            if fitness[i] < pbest[i]:
                pbest[i,:] = x[i,:]
                if fitness[i] < gbest_fitness:
                    gbest_fitness = fitness[i]
                    gbest = x[i,:]
    
    return gbest

你可以将它用于优化 Gabor 变换方程。