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29 lines
851 B
29 lines
851 B
2 years ago
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import numpy as np
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def Ms_u_reshape(u_data, coarse_nelx, coarse_nely, m):
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nelx=coarse_nelx*m
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nely=coarse_nely*m
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u_data = u_data.reshape(coarse_nelx,coarse_nely,m+1,m+1,2)
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u_data = u_data.swapaxes(1,2).reshape(coarse_nelx*(m+1), coarse_nely*(m+1), 2)
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idx_x=np.arange(coarse_nelx*(m+1))[::m+1]
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idx_x=np.delete(idx_x,0)
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idx_x=np.delete(np.arange(coarse_nelx*(m+1)),idx_x)
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idx_y=np.arange(coarse_nely*(m+1))[::m+1]
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idx_y=np.delete(idx_y,0)
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idx_y=np.delete(np.arange(coarse_nely*(m+1)),idx_y)
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return u_data[idx_x.reshape(nelx+1,1),idx_y.reshape(1,nely+1)]
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if __name__=='__main__':
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pred=np.load('results/pred.npy')
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u=np.load('datasets/train/180_60/u/mod2.npy')
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print(u.shape)
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print(pred.shape)
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recv_u = Ms_u_reshape(pred, 36, 12, 5)
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print(recv_u-u.reshape(181,61,2))
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