import numpy as np import os def data_loader(opt): # Load datasets # './datasets/train/180_60/u_OR_xPhys/mod1.npy' as default density_load_path = os.path.join(opt.dataroot, opt.phase, str(opt.nelx)+'_'+str(opt.nely), 'xPhys', opt.mod+'.npy') displace_load_path = os.path.join(opt.dataroot, opt.phase, str(opt.nelx)+'_'+str(opt.nely), 'u', opt.mod+'.npy') global_density = np.load(density_load_path) # (nely , nelx) global_displace = np.load(displace_load_path) # ( (nely+1)*(nelx+1)*2 , 1 ) global_displace = global_displace.reshape(opt.nelx+1, opt.nely+1, 2) global_displace = np.dstack((global_displace[:,:,0].T, global_displace[:,:,1].T)) # -> ( (nelx+1), (nelx+1), 2 ) m=opt.ms_ratio N=(m+1)**2 global_nely=global_density.shape[0] global_nelx=global_density.shape[1] coarse_nely = int(global_nely/m) coarse_nelx = int(global_nelx/m) # Generate coarse mesh density coarse_density=np.zeros(shape=(coarse_nely*coarse_nelx,m*m)) for ely in range(coarse_nely): for elx in range(coarse_nelx): coarse_density[elx + ely * m] = global_density[ely * m : (ely + 1) * m, elx * m : (elx + 1) * m].flatten() print(coarse_density.shape) # Generate coarse mesh displacement coarse_displace=np.zeros(shape=(coarse_nely*coarse_nelx,4,2)) for ely in range(coarse_nely): for elx in range(coarse_nelx): coarse_displace[elx + ely * m][0] = global_displace[ely * m, elx * m, :] coarse_displace[elx + ely * m][1] = global_displace[ely * m, (elx+1) * m, :] coarse_displace[elx + ely * m][2] = global_displace[(ely+1) * m, elx * m, :] coarse_displace[elx + ely * m][3] = global_displace[(ely+1) * m, (elx+1) * m, :] print(coarse_displace.shape) # Generate fine mesh displacement fine_displace=np.zeros(shape=(coarse_nely*coarse_nelx, ((m+1)**2) * 2)) for ely in range(coarse_nely): for elx in range(coarse_nelx): fine_displace[elx + ely * m] = global_displace[ely*m : (ely+1)*m+1, elx*m : (elx+1)*m+1, :].flatten() print(fine_displace.shape) return global_density, global_displace, coarse_density, coarse_displace, fine_displace if __name__=='__main__': from options.train_options import TrainOptions opt = TrainOptions().parse() data_loader(opt)