fig = plt.figure(figsize=(10, 10)) ax = fig.gca(projection="3d") # # Plot Rosenbrock surface X = arange(-30, 30, 0.05) Y = arange(-30, 30, 0.05) X, Y = meshgrid(X, Y) # from spot_setup_rosenbrock import spot_setup # from spot_setup_griewank import spot_setup from spotpy.examples.spot_setup_ackley import spot_setup Z = np.zeros(X.shape) for i in xrange(X.shape[0]): for j in xrange(X.shape[1]): sim = spot_setup().simulation([X[i, j], Y[i, j]]) like = spotpy.objectivefunctions.rmse(sim, [0]) Z[i, j] = like surf_Rosen = ax.plot_surface(X, Y, Z, rstride=5, linewidth=0, cmap=cm.rainbow) ax.set_xlabel("x") ax.set_ylabel("y") ax.set_zlabel("RMSE") plt.tight_layout() plt.savefig("Griewank3d.tif", dpi=300) # surf_Rosen = ax.plot_surface(X_Rosen, Y_Rosen, Z_Rosen, rstride=1, cstride=1, # cmap=cm.coolwarm, linewidth=0, antialiased=False, alpha = 0.3)
:author: Tobias Houska This class holds the example code from the ackley tutorial web-documention. ''' from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import spotpy from spotpy.examples.spot_setup_ackley import spot_setup #Create samplers for every algorithm: results=[] spot_setup=spot_setup() rep=5000 sampler=spotpy.algorithms.mc(spot_setup, dbname='ackleyMC', dbformat='csv') sampler.sample(rep) results.append(sampler.getdata()) # sampler=spotpy.algorithms.lhs(spot_setup, dbname='ackleyLHS', dbformat='csv') sampler.sample(rep) results.append(sampler.getdata()) sampler=spotpy.algorithms.mle(spot_setup, dbname='ackleyMLE', dbformat='csv') sampler.sample(rep) results.append(sampler.getdata()) sampler=spotpy.algorithms.mcmc(spot_setup, dbname='ackleyMCMC', dbformat='csv')
fig = plt.figure(figsize=(10, 10)) ax = fig.gca(projection='3d') # # Plot Rosenbrock surface X = arange(-30, 30, 0.05) Y = arange(-30, 30, 0.05) X, Y = meshgrid(X, Y) #from spot_setup_rosenbrock import spot_setup #from spot_setup_griewank import spot_setup from spotpy.examples.spot_setup_ackley import spot_setup Z = np.zeros(X.shape) for i in range(X.shape[0]): for j in range(X.shape[1]): sim = spot_setup().simulation([X[i, j], Y[i, j]]) like = spotpy.objectivefunctions.rmse(sim, [0]) Z[i, j] = like surf_Rosen = ax.plot_surface(X, Y, Z, rstride=5, linewidth=0, cmap=cm.rainbow) ax.set_xlabel('x') ax.set_ylabel('y') ax.set_zlabel('RMSE') plt.tight_layout() plt.savefig('Griewank3d.tif', dpi=300) #surf_Rosen = ax.plot_surface(X_Rosen, Y_Rosen, Z_Rosen, rstride=1, cstride=1, # cmap=cm.coolwarm, linewidth=0, antialiased=False, alpha = 0.3) # Adjust axes #ax.set_zlim(0, 600)
This file is part of Statistical Parameter Estimation Tool (SPOTPY). :author: Tobias Houska This class holds the example code from the ackley tutorial web-documention. ''' from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import spotpy from spotpy.examples.spot_setup_ackley import spot_setup #Create samplers for every algorithm: results = [] spot_setup = spot_setup() rep = 5000 sampler = spotpy.algorithms.mc(spot_setup, dbname='ackleyMC', dbformat='csv') sampler.sample(rep) results.append(sampler.getdata()) # sampler = spotpy.algorithms.lhs(spot_setup, dbname='ackleyLHS', dbformat='csv') sampler.sample(rep) results.append(sampler.getdata()) sampler = spotpy.algorithms.mle(spot_setup, dbname='ackleyMLE', dbformat='csv') sampler.sample(rep) results.append(sampler.getdata()) sampler = spotpy.algorithms.mcmc(spot_setup,