我有一个简单的问题，但无法解决。我有一个C_temp 16x16矩阵（size = 16），是从另一个矩阵复制来的。
C_temp = np.zeros((size, size))
C_temp = np.copy(C_in)
然后，我有一个置换列表（或numpy数组，我不知道这是否重要）：
print('index_reorder =', index_reorder)给出：
index_reorder = ', array([2, 4, 0, 5, 1, 3, 7, 8]))
我想进行由index_reorder沿x axis和y axis指示的排列。
C_temp = np.copy(C_in)
C_temp = C_temp[:, index_reorder]
C_temp = C_temp[index_reorder, :]
C_new = np.copy(C_temp)
但是不幸的是，新矩阵C_new的大小减小为8x8。
这不是我想要得到的：我想为C_new矩阵(16x16)保持相同的大小，即在保持置换矩阵C_temp的整个大小的同时进行置换。
如何执行此全局置换？
我相信这被称为“就地置换”，不是吗？
UPDATE 1：以下是C_in矩阵16x16]的示例>
C_in = ', array([[ 5.39607129e+06, 1.79979372e+06, -2.46370980e+06, -1.12590397e+06, 2.54997996e+03, -3.48237530e+02, 1.77139942e+05, 2.10555125e+04, -2.24912032e+05, -9.79292472e+01, -1.63415352e+05, -8.65388775e+01, -8.10556705e+04, -6.40511456e+01, 1.31499502e+04, -4.80973452e+01], [ 1.79979372e+06, 1.85207497e+07, -5.97280544e+06, -4.86527342e+05, -9.46833729e+05, -2.10321296e+05, -7.71198259e+05, -8.88750203e+04, -1.66150873e+06, -3.20782728e+02, -1.45257426e+06, -2.86060423e+02, -1.10641471e+06, -2.17539743e+02, -9.34181143e+05, -1.77667406e+02], [-2.46370980e+06, -5.97280544e+06, 3.36326384e+06, 5.88733451e+05, 3.35606646e+05, 8.96417015e+04, 1.12240864e+05, 1.35483472e+04, 6.10023925e+05, 1.26679014e+02, 5.65166386e+05, 1.21455772e+02, 4.43234727e+05, 9.80424886e+01, 3.68206009e+05, 8.44106515e+01], [-1.12590397e+06, -4.86527342e+05, 5.88733451e+05, 3.34731505e+05, -3.26665859e+04, -7.14038524e+03, -7.25370986e+04, -8.44842826e+03, 4.40874561e+04, 2.82933253e+01, 2.77238713e+04, 2.47986977e+01, 7.27381187e+03, 1.80784440e+01, -1.87787106e+04, 1.31142301e+01], [ 2.54997996e+03, -9.46833729e+05, 3.35606646e+05, -3.26665859e+04, 7.90884228e+04, 1.92364617e+04, 5.66130910e+04, 6.70772964e+03, 1.07063410e+05, 1.46143888e+01, 9.53013920e+04, 1.33963997e+01, 7.42574771e+04, 1.04791841e+01, 6.58013341e+04, 8.95530786e+00], [-3.48237530e+02, -2.10321296e+05, 8.96417015e+04, -7.14038524e+03, 1.92364617e+04, 4.99000202e+03, 1.10082611e+04, 1.34941127e+03, 2.41927165e+04, 3.26733542e+00, 2.31011986e+04, 3.22432044e+00, 1.88491639e+04, 2.65297382e+00, 1.72802490e+04, 2.36016813e+00], [ 1.77139942e+05, -7.71198259e+05, 1.12240864e+05, -7.25370986e+04, 5.66130910e+04, 1.10082611e+04, 9.36434428e+04, 1.07348807e+04, 6.09534507e+04, 3.44072173e+00, 5.90764148e+04, 4.26292063e+00, 5.10904441e+04, 4.37089791e+00, 5.24285786e+04, 5.06825219e+00], [ 2.10555125e+04, -8.88750203e+04, 1.35483472e+04, -8.44842826e+03, 6.70772964e+03, 1.34941127e+03, 1.07348807e+04, 1.48215248e+03, 2.49002654e+03, 1.40557890e-01, 5.84713359e+03, 4.21925848e-01, 7.21719030e+03, 6.17446227e-01, 9.39064037e+03, 9.07789891e-01], [-2.24912032e+05, -1.66150873e+06, 6.10023925e+05, 4.40874561e+04, 1.07063410e+05, 2.41927165e+04, 6.09534507e+04, 2.49002654e+03, 5.91760033e+05, 9.77850970e+01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [-9.79292472e+01, -3.20782728e+02, 1.26679014e+02, 2.82933253e+01, 1.46143888e+01, 3.26733542e+00, 3.44072173e+00, 1.40557890e-01, 9.77850970e+01, 2.42137019e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [-1.63415352e+05, -1.45257426e+06, 5.65166386e+05, 2.77238713e+04, 9.53013920e+04, 2.31011986e+04, 5.90764148e+04, 5.84713359e+03, 0.00000000e+00, 0.00000000e+00, 4.84422452e+05, 8.24104281e+01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [-8.65388775e+01, -2.86060423e+02, 1.21455772e+02, 2.47986977e+01, 1.33963997e+01, 3.22432044e+00, 4.26292063e+00, 4.21925848e-01, 0.00000000e+00, 0.00000000e+00, 8.24104281e+01, 2.11226210e-02, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [-8.10556705e+04, -1.10641471e+06, 4.43234727e+05, 7.27381187e+03, 7.42574771e+04, 1.88491639e+04, 5.10904441e+04, 7.21719030e+03, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 3.50093152e+05, 6.00111232e+01, 0.00000000e+00, 0.00000000e+00], [-6.40511456e+01, -2.17539743e+02, 9.80424886e+01, 1.80784440e+01, 1.04791841e+01, 2.65297382e+00, 4.37089791e+00, 6.17446227e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 6.00111232e+01, 1.57248915e-02, 0.00000000e+00, 0.00000000e+00], [ 1.31499502e+04, -9.34181143e+05, 3.68206009e+05, -1.87787106e+04, 6.58013341e+04, 1.72802490e+04, 5.24285786e+04, 9.39064037e+03, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.83150690e+05, 4.74239664e+01], [-4.80973452e+01, -1.77667406e+02, 8.44106515e+01, 1.31142301e+01, 8.95530786e+00, 2.36016813e+00, 5.06825219e+00, 9.07789891e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 4.74239664e+01, 1.26116519e-02]]))和输出
C_new矩阵：
C_new = ', array([[ 3.36326384e+06, 3.35606646e+05, -2.46370980e+06, 8.96417015e+04, -5.97280544e+06, 5.88733451e+05, 1.35483472e+04, 6.10023925e+05], [ 3.35606646e+05, 7.90884228e+04, 2.54997996e+03, 1.92364617e+04, -9.46833729e+05, -3.26665859e+04, 6.70772964e+03, 1.07063410e+05], [-2.46370980e+06, 2.54997996e+03, 5.39607129e+06, -3.48237530e+02, 1.79979372e+06, -1.12590397e+06, 2.10555125e+04, -2.24912032e+05], [ 8.96417015e+04, 1.92364617e+04, -3.48237530e+02, 4.99000202e+03, -2.10321296e+05, -7.14038524e+03, 1.34941127e+03, 2.41927165e+04], [-5.97280544e+06, -9.46833729e+05, 1.79979372e+06, -2.10321296e+05, 1.85207497e+07, -4.86527342e+05, -8.88750203e+04, -1.66150873e+06], [ 5.88733451e+05, -3.26665859e+04, -1.12590397e+06, -7.14038524e+03, -4.86527342e+05, 3.34731505e+05, -8.44842826e+03, 4.40874561e+04], [ 1.35483472e+04, 6.70772964e+03, 2.10555125e+04, 1.34941127e+03, -8.88750203e+04, -8.44842826e+03, 1.48215248e+03, 2.49002654e+03], [ 6.10023925e+05, 1.07063410e+05, -2.24912032e+05, 2.41927165e+04, -1.66150873e+06, 4.40874561e+04, 2.49002654e+03, 5.91760033e+05]]))我只想根据行/列的
index_reorder向量来交换行/列（即看起来像置换？）。>
我有一个简单的问题，但无法解决。我有一个C_temp 16x16矩阵（大小= 16），是从另一个矩阵复制的。 C_temp = np.zeros（（（size，size））...
如您所知，问题是index_reorder仅包含重新排序的元素。
解决方案是，将其扩展为所有元素的完整排列。如果元素应保留在原位，只需在其旧位置写入索引，以便它们保留。