[miraboreasu]

Hello, I want to explore more in my VTU file (attached) besides using Paraview, I try to write a Python script (attached) to read my VTU file, like store all the results to lists, so I can do some analysis.

I have tried both two packages from this link,

https://stackoverflow.com/questions/...w-vtk-vtu-file

and they don’t work for me. Anyone can please provide a good package?

VTU looks like (too big to upload)

<?xml version='1.0'?>
<VTKFile type='UnstructuredGrid' version='0.1' byte_order='LittleEndian' compressor='vtkZLibDataCompressor'>
<UnstructuredGrid>
<Piece NumberOfPoints='1368' NumberOfCells='342'>
<PointData>
</PointData>
<CellData Scalars='area failure mode length opening 0 opening 1 opening 2 property id slip 0 slip 1 slip 2 '>
<DataArray Name='area' type='Float64' NumberOfComponents='1' format='appended' offset='0'></DataArray>
<DataArray Name='failure mode' type='Float32' NumberOfComponents='1' format='appended' offset='200'></DataArray>
<DataArray Name='length' type='Float64' NumberOfComponents='1' format='appended' offset='256'></DataArray>
<DataArray Name='opening 0' type='Float64' NumberOfComponents='1' format='appended' offset='448'></DataArray>
<DataArray Name='opening 1' type='Float64' NumberOfComponents='1' format='appended' offset='636'></DataArray>
<DataArray Name='opening 2' type='Float64' NumberOfComponents='1' format='appended' offset='824'></DataArray>
<DataArray Name='property id' type='Int32' NumberOfComponents='1' format='appended' offset='1020'></DataArray>
<DataArray Name='slip 0' type='Float64' NumberOfComponents='1' format='appended' offset='1076'></DataArray>
<DataArray Name='slip 1' type='Float64' NumberOfComponents='1' format='appended' offset='1272'></DataArray>
<DataArray Name='slip 2' type='Float64' NumberOfComponents='1' format='appended' offset='1468'></DataArray>
</CellData>
<Points>
<DataArray type='Float64' NumberOfComponents='3' format='appended' offset='1660'></DataArray>
</Points>
<Cells>
<DataArray Name='connectivity' type='Int32' NumberOfComponents='1' format='appended' offset='10776'></DataArray>
<DataArray Name='offsets' type='Int32' NumberOfComponents='1' format='appended' offset='13384'></DataArray>
<DataArray Name='types' type='UInt8' NumberOfComponents='1' format='appended' offset='14032'></DataArray>
</Cells>
</Piece>
</UnstructuredGrid>
<AppendedData encoding='base64'>
_AQAAALAKAACwCgAAhAAAAA==eNpr8DcqZXpZZtcApW95CHzSO 8FlD6NVuL8oGBfdsIPRwXbbjZ+ZCdjD6Mib3D+dtU7awWiHG9P jF+afg9OdutumeNeK2MPoR+1xk/d7ssBpbq6sCHHfx3Yw+sreC8IxLY/g9C/jUsu5/tfhNMMoGAWjYBSMglEwCkbBKBhRAACS00s5AQAAAFgFAABYBQA AFwAAAA==eNpjYGiwZ6AJHgWjYBSMgpEJAOkSEGs=AQAAALAKA ACwCgAAfAAAAA==eNp7ZJNWoPOyzP4RlF4jdGuP0eRGOB0lErJ E7Eg5nF7JmB5hiURLHzLa7/20Ak7nnJfpu97XAqfLFVXVHno2wukTTHbueyZVw+ndLvulrYHm wGilNVYy/Mo1cNqXN/him1k1nGYYBaNgFIyCUTAKRsEoGAUjCgAAE19IRQ==AQAAALAK AACwCgAAeQAAAA==eNprjTjM5qv1x64VSquteWx552KtPYxmQA NWsjnBVdbN9jB620H/d2Ln7eF06YH9patfF8PptCvbnJ9kdMLp71dywpkTy+F0gpclV7 RnFJzOS30z0etRCJzWuVobZ7nNC04zjIJRMApGwSgYBaNgFIyC EQUAe7BI/w==AQAAALAKAACwCgAAegAAAA==eNpT2OnKWrLynJ0ClN6wMHC SQ1WxPYwumiNx1VQyC07/ux/44/mHPjjNJaZg/L3AAU4zoIENXm2F84Vr7WH0hNINm/W2lcNp2SrvqdobIuG0zPRzV7KtQ+H0zJiubbUyPnCaYRSMglEw CkbBKBgFo2AUjCgAAAGTRmk=AQAAALAKAACwCgAAfwAAAA==eN pbyZ/TXv3/vd1KKP16mVQa37IKexh9te7YQqfVgXB6zr97qoZinXC66LdyqK OOA5xu+CC+n7fSCk7f/2PzL/JnM5x2WdrHOrO7HE7bJR3yP/wnEk671sUa3+YLhdOPJFq6ojO94TTDKBgFo2AUjIJRMApGwSgY UQAANVxQ6Q==AQAAAFgFAABYBQAAFgAAAA==eNpjYKAN+D8KRs EoGAUjFAAAvcL7PQ==AQAAALAKAACwCgAAfwAAAA==eNrT+e+//VG9p70OlDbQcXu25F8ynPY5Njcl2rMNTktPed8b9zEVTive013 cWm0Jp29HPLy3bPFEOG3I2vHonkcBnJbJui5wPMYGTn+59ywzb VEonGaW+PNJycIJTjcpb5q+6XsinGYYBaNgFIyCUTAKRsEoGAU jCgAA5GpUVQ==AQAAALAKAACwCgAAfwAAAA==eNqLKPxqO7fe0 z4CSmd/3P9l9b9kOC1+IF0vybMNTs+a++u+9sdUOO1gbXJcqdYSTrs9KP WfuXginP7AwjTxh0cBnP47Q/Ctf6wNnG7dvvb4g4WhcNr0K9/1lXZOcLqiYOlm9e+JcJphFIyCUTAKRsEoGAWjYBSMKAAAWBdVJ Q==AQAAALAKAACwCgAAfgAAAA==eNpz2rHo1/56T3snKH2Orzl3xb9kOG10uOlknGcbnL4l8dXM9WMqnN7AY2ga UmMJpyfM0RZfsHginBZgPbrztUcBnO5p/FLHHWsDp228T81QXhQKp+e0saamWTvB6b8nV6vmfk+E0wyjYBS MglEwCkbBKBgFo2BEAQCuUU6/AQAAAECAAABAgAAAoxoAAA==eNqlnXlcTF0fwEfaVBRCtGlVkT ZSurlFJVmTECFrCVHWKCVlqR47ZStbkSj7UjekPBJZ0iOyZcuS oni6U6F3Rs+ZO3fuez4z5/DH+37m9/n2nDn3nuW3z4z1sdcmbaJJt6hLDfvH0CTvv38FN3mmDmtoUnND 04LHzox8BiJ/wGnwzhlRNKk1PVTH2YmR07Ma+4Um0mScxaVYjVH4PHVBf9eXjT QZPHPb5aunGTkvfGqu+1GadEz8rjgzBZ/X7VsRo3uMJjtFGneL2cDIbZ+TT+euo8mp3T3CVm/D52Hjzjpx/tLwEzRZUul6dP95fP54zJnym/do8qz516SdDxn57P7FTv4UTfZptFj1+gY+v7vF2PNGkUBuPPHJ iwRGrr+w7K634Pl+POD8Sm4DPg8bNznEkaRu02TbvB+KBWfxeb eC9FeDu/LJ+f43j6uf5DPrfECn7jmafLIlJCLCfgcfm6/95OG7vROf7HegZPe1bYx8/NYwN0sBb33v3Z3kTHz+UTunXU6CeX24lnA6qoaZ14K+t/6edIQm95Yv+UuvksbmVVRm0XtW06SP+bVPTocY+dzQgKZVgvfn nt3p3NBb+Dxs3BkjvU4MvE6Tr3VXXT5/F5+H7QvYOYDKpw8NiD4skJfsy+q8Qmw9B74iPm0Ko0n7/H0WMyLweS+LlkqbQJpc0ufIcPetjDybvrZjieA5lz7JS+98AJ//1bvvkdRTNPlOLriJEtt3blMOrW44SJNZjT5uysvwefNvWenbdt PkhrX//nt+qfRzEpW3ajYe+nofnxy3dE2n/B+MPOSV96UGwT5ZeOu+R4wmH5uPS8pfdfw0nxykdi9tR2dGfuD E+Lsxh/jkSIWmyy+aaWy+U5nf+MIrNCl3Ye0HBbFzIzPyzZjxgn2apJWT aXaCj83/DDjR3qOYJk9Mn7962yFG3nnI8mGJeTR5QXHx6Nh4fH73+y33cv KPkOMfTizp8kiTAvL8KqH8HLn11p2LZb+UKFze6prVdC9PGyLk clHg8wBFF5E+UDH44c6xBtSlxfERj9ozclS+9Z+yS/jv8QtJSXm0wdK15vW3yD/lgy7nazaeUOKMy/5/fF5SfuqK+N//OW8971H79KK2HHnVKcGfactj8zaJWwXP8S0pOa7T4mTD1KVvOH JUvqflCMEfKHDmtbFK8PUCuXJUHnx+2lH87xj54on/f73JyntHPw+Ij5DjjJvjmCpYaFw5Kg8+q6Sy9wuQH3qn6PP2rO If8w/CBNvCT0nmdY7K107xG5Bs+JKz76blpQm+aCWJy3ePeXs2xPonZ 119bxZMP/4HR47KL/m85fd6dhytXiDnYEkA+afmjYJ1UEVeis8ITjgvR+Dyi71HHfki sKd8aj2DtOWZc3tPVlOuUyxN3jVVWffOiJGj8l0mCZbboxpynp Hp8jtb9EXjvpsrfL5fyCdTyy4UzGhH4PK/zmXPnHr3e25DqvA8aRGN60FFDJmnoEupa00S/B0jR+XB+6ggBMttwFeO/HqhcD18xeYrI5oXXh0s0De2TbOetoW591Uto+fVGvPJ/AWpy+NjaWwejHvkWZLY+cfIwXr5U77LIOG5yz3nT8QKxJrcc0x W3rFh2nCvrjbUq2fse2E9r1N1Ok+bqklm3yOoPBh3+L0UwflXy plXda1wvmUkLn9Cq4PgXviXs68jE4Tz/86Ro/J6BgL8OY9zbq+vEJ4nXDkqv9JfW3AR1ZOjfw2uvN9CivbdjLfC 9fGNbDjqWTx0siuBy88ODx6xsE9z7pOXQr2okbFHjEqzt71XIe omCF7jCEaOzGfsTbNYxyfN+faBfq+YfTFnSsGQlHA+6RI9ofBh AY3Nnx9++UJIXlsiVU14bjDravWr8LKtkQMp5b+Fz0POBZc/MClVbJ0x7yXIW/j39zhyVL7Xt0z/IzMtiC9KC63dB1WL5rW2t1v8uchap6Za4XP+SOLyF6c5ljRet6 e0jgj1lgaR3CI4hRy6yoBir3d0Xtq5BO69P+UPFwjvpTacc2Og irjehM7D/E4wPxsqb3eBXFq7mSY/UbF2Z4cw9/LE4GrFCYdpsi48MsN5Ch+bFz23BKFe18CRq3cS6mk0Ng/sAfcJZuEFo1VEdl8kPVagSMm7ZIel1A7O1CFw+YSeQYJz7zNnX 7DXNyNH5cFnt9vi9oF0PR+Vn5vEPjeAvM0LP9Y5g8oDfT0v80x 93sc2oufm2EcwW0Ull5khxcfragwpXN7m9/N8xnlurefIE659h8hLszvA98LlY11b7yHVeTdHqjv1FM337N06 wYNsIsv79n7UqdmJwOVDvX3H2fS04vglao7dMbJu0aPY9ig6D+ ZVoiu0C39x9uOP437/Vx9G5cH+k1UPlJWf+kgwzfQP3PsuT3iOvOfIUXnw2T1DXD9i5M ++pInpU+j8TtvPI18H2hLy39n3xeoEemE3f2Ni/kmB2rS2DTYP9rnngwuhXXkuon0H9rnRsX1r5pW/yMXl47Vbn+eINN3Vq+qYdcvr3aoHXI5rO0tO057A5WF66f0dQv tKdj0WxoP1pL/xOrHEvY9ovsAO0SgpUp/iaU3h8mnu5mNHb+tLsdcXj3fGaN/GO/1NiJLfeg6jb6DyYD45qmweyMHzxuWdzVvP1VPPIiz3POwsei9f hwT+PofL36Sr9Yxi5ovKy3vt187145Oqte3Uj/gzeoXmla7vTBbwyYPRN0doi+khqDw4r89Nin8xK11LNC7wHyVN Xmngtr85F5dP/6GRn7q92UlyXe1pt/Bm9CpLiu03Reebf9t9Rzjn0vEp6R8Wz9AlJOWo/IzmW4v/NSWIqpoQgf7SLHpu5XFrO2ymdalfs+t/30u4vMhflxg15+N5eUpSDvz9uDzw92Vf2fWkxsmAw3d37ry9Ym IPCpeX5seG3VOo/OvJ7OcJ5B0/fhIoIlw5Ku81X/h9vnPktt+3iPkV0HnYvck+p6TfszA+O3HsIKWN9sRXgq13bc8Y q3FjeXdizQ+2nobKAz910R3dLQ/WMX5RoP8NnDeywqznWydcHnbvsP2P0u8pGG/aS3he80mjD93z2+k0isb1Pcf/7Qc5a7Ps3BXzT064PBhPTp5tj0uz42Tl308s67agxZ5yvsD2lx LTC1PKU/pROmMn/fb74vJsPxHz3Nh+IkaOyks7x0DcEpc/OFVc32XGHaPrI3aOMHJUHiZn+0/xeWl68hJ7YTykzR/zLsvE4yeMfGFb8XgLOg/0lnkDnw+fvslCdC+A+NCDxZ/bTQiyIHB5aXFAWBxNVr70gLg/Xfo6QeXvpq5yGGLbm+q1hW0PBv48E9Doa0i1UZku+KLM80TlwX g9Itr/X78f7JyRlb/gJ3wvV8ktP3zHZY3qIHpfIH6fPexT4YIEMwKXv7l123uVF/xcdtyPx+vcw40308aOYsf90HnNuqyB723qnNh6H49X2C3jum6w CcGL/zl9jpkmgcuXhS+wfZJhRrxQqOdfm9SdkMzTOPRBN7rXtaJcXB6 8F6sSYTzltcxxKFl5sJ9HbTU9pDhMV/S+UrYE/F5nmQ0tDzR3mFG4PNiHBqF0dUaZNiGpJyiruRVa9e9G4PJAzxt 9rEU9SSyeAvQ8vYfae/aN0aZweWl+wmRjYd5EWxdcHuiLezUry2vNGL8f2J9HFI6sqZzP fB9UfvM6jzde3lZE63pm7k2vicsGnvJRJyTXOSr/Zpjwf/mce3/ZFXE/NSNH5aXdU2Dd4fLseIx0PxgqL83PAPw6uDzwd8vd2Xht+YjBnH 135uPINboTmPWAyl/e2yL4R5PBTdvSR10xpiT1ZF704r4RWtW5uDyYF8hfkDVPAJWHx a1gfh5Z+cv2nj+VlRwotl3C4924Vzb/poYqJZlHgcpvzJ48yrNcl/Adyz43wjJjl2/YacKJk6LysLi5Bq+LmH2rjM0/ai98XuXkwQk17r+K+hOSfrBPCUmToxbZEbi8NDsC6CO4PNuPzM yL7Udm5Ki8yG//X16PrOtcVv61vs2hfop8cm9Me72gKCZu2LT7XP6KKpos1OjyqJ tYPgwqD+yNFRkHVrwLdxDtd9XI1vnSacEvtXKcKVz+dcrPgIeJ WoRkXLts5vb4hR9tCPZ6ROdheX2w94jKn5zRus8Hxxi7WR9l9B YQ/4gr2hlkF9WfwuVrvDeMPPn2kxM77sfjmTeEnpSjLCh23A+dH/4oXlVVrzvFtmsF93jjtZLsPCtOHhEqz7ZzmOfGtnOUsXn508/4g5fyyagn8lun5DLr9qJS0fAV0/mk54bl9/TE6ixQ+TkZKdHdxxhQCb/zapl8ZuWG2R6l9hpUa17JVWwezOfewBBWPokojuYVKBZvR+dTq +tMVeT45MMhY0z50UxcIFyvLvShAZ90v/jP1bQIPjYP9GrXV0O9nizpI1rPwL9wgvJc8rXQmcDlwbyOjxCe H3Wc+W4rE9pB9SQuDzu3/5kj7meRfs7D+BVncz6kO9tyzqWWzF/J7RrNCPa9is6D8UB+max+bFl5sM6SlMYH7dRm7BGwzvpVHW6IP 8PkOaDy4D3df3Q6IcqaiXuC99R8iX+qanlHbH5ox/E2Sb36Uq/CklnzTTP0nM37MZBa+r41Xw+XB/ooOXSJvrFYvBjkuZ62L1Wbet6GwuX3f75efqS9DcH2P/F4V1P93XKmaRKS5zAqD/QJas6d7JfBqpzv2a7d0GODPg+gcHmwrmB55jA/hqy8huPe4BKBnV/+e78wead9A8c/ybQwJdj5gOg8Ow9Pep4qKu/xe7x6rh/+rvj5hc/D/NLsPGB8HuSrvdn9UXvF1y4cu9J+0JELlq9NKFwejCeyLyXkIG6 Dy7PjZMy82HEyRo7Ks+M0jJwdp8HnwXyeHR+bU+hdkSuZZ3X7a e2zxLSqXFxeWh4jeG+4PLAL/o52HRJMM3FnkD/qYj3xi+O6HgQuL80PA9OjZOVhdjH7/pBuR8N4mN4Lq6NB5UGcyXf+mi90fl9C0o6zfzppVuYiRwKXT1Y vO/lNTZtg15/xeIZ2PzNXyXf977xlznNU3ix2yPDM4j6cuhViRwfT3jssOXEWV B7ENdLm1CkGBpqK5gXqGKtT3qdn1JsQuHzrvn4pc54nKi/NjoD5GWTlDwaM32exgE/aebmeURTLO8pfNmtLQLjg84G3Zf4mfGxebUm1WD4HMy92/g0jR+VhdWew/w4qD8uLhvmZUXm2nSlZ73D1j3ngJw0fqDGxm7aV6LwFflKPwvn HFbMcKVwexEumJd7cN9WO8XuA+liLELkc/x6W2DyYz9UAP7H6D0YOq2OSlQd2q9/j9SmVPBdCMo626irfuTqrDYXLB2d9vD9uE02mzHw5TbGYuTcvX 3F7vSuGJmt4igGV7xk5Ku8wu0SXl0eT425NTJu7iNl3d9WIrKw Kmsw57m+2Q8zeR+WBHt9m98sexaZ1Ir0C6PEpu2Z0PpfC3COov I9yT6dO9+0I9v7j8eRLXa5mnXTm5Omh8uw6eWZfsPPLGTkqfzh zjXfzvx05ecs9CZ+wYTtVKLZfAZ1n5yNKz/NB5aXl0cHyEGTlZ204/0JLj5/LrtsW6LF7X7jVNfEItr8WnXcPfLLs3DMeddw1nWVv/tU7QjuvvSnFvm/ReW+zYec3C/ZDRsKtDePE7jU/nm1LfjSftHzX03K9Ah+b19X9NqSItKbYdf88XtHJN8eClslz9C hUHryX3g7suBWQA382Lg/ygtpq/VJZ2N2Ocw5cXppcNH1MjRMuD8YtHcNeD0AOqwOSlYfZ3a3r46v MdjqMZ/ubpPsBUPmfcpqd1c2sCXZ8m8dre3WFfJ9EU04ePioP4homKUnV cbOHUJJ2xLqwezy3o0ycGpWXlqcB67MhK59ppLw5KJYmj/LeLLghVtc/+quWyaktNFnhN0UvyFWszwwiz47XMu+FXQfLyFF5cJ7eeDC2z6 z9TLwe5IENTvz7n5xYMwqXV5yTtJmnpcnJW7ty46S7u1w9J48L lZ8UtdH11QY+2V3RYJxCW7E6zYqhU8Jj+WTL97U65Bsam5cWR4 b1sZGVB/nuait9V07PMWD6PPxXR0N0K7odcVefwuWB3zv11HrFF+V2Ijmo Q+/kX9z+kfJAbB5WN91qj9ySuc4axrPtecnzsPKPedi+gPWBQeW/GY2eHh2uw4mrLpzf47BSW0eiQ15rvgMuD8aD1TXA8nhl5YFePV L94hieuYNovYE8QiXL4yr9aS0ClwfjgrwPSTnI+8Dl2X4c6XFk VB4W14P1kUDlQb7a67Wfn64uY85bUF/q0yYoXLWXAoXLw/pWuawW7x8kvc8VjJcWhwXnCi5vKb/y4M31Npy8X9WW3gk+Dz85SdpxqDysbpq9D6XXWcN4aesc5Mvj8 mDfqS3iDxi4htsH6WWkvF/XKEsClx+e19hzQYkrwdZbBf8dkydf/O0tCLbeis7D4krs/DbpcSgYD+qxL71Iqq8q+CDyJwD7JCdbQT1oR28Cl+8c6Wb3sbE rxb7feLwkD585ZqrcPBBUfphO7Z2HT2ky4dZZI36kmB819e289 GaafHDO5pVcDB+bz0uPutps8yNXsi/QWcMBVt89NTl5hqh8dmLbjif92xGSdfeZPivVwr72I9h949B5a ecMLM8BlQf9CSTlsDpEWfnRvhPuXXDW4MQ1NnymbNJmqxCSfgZ UHowL60MF67MhKw+rW4T1IUTlwWdY3ROIB/4pD+tzBdNDUHlYnBQWp5aVn2/9yTy9xpCTtxBX2tH56AwLiq2Po/P6QeWbxxa6cPoyLf/4tTRQVZ+S9LOh8qGlcQXvb/Yn2HUDPF6loYZJSKkDwa4bQOeL9yi8dayiyZgTNbuKYhj5Iq+C nMIimlSe+CZp1WZ8HsQJtHTq+KVRTN4RiBP8raI9T1VVg8Dl2X Ua0uvcUXnwGdaXFRYHkZUHcUSDPdfDCh4bcPocds1OPrenDRMn ReVhfnVYn1JUXpqeBuuTKSsPztOnMTFjfayYukhQx9FZsU+Gn1 i8DJVv0Q2qW3LUinNvKnSY6j/qpQ7FrndE5+96x24oOdyVE3dQuxR2LN3IhmLbPeg8O09Lep83V B7WFxfmZ0Dln7/yiwmgDQm2/5XHe5lxSs7bdzBHT0blYX4VWJwXlQd6gIPGOvW0i10563Bhkp2 esc4AApcH44H8I1n1KFn5LpvT7b+P68lZtx+Md/ifqzXh5Emi8rC+BDA/Ayp/+4H4fS+9zg6VlxbHgfVxkpV/MJTeGzq62kmyL2VYvOMQv0wNiv190XlYXwLYc0DlwXoyPfbXxA qxelKgx6vtaYrU7TOewOVXpPj45AbwyR3FoyefThWrR7ivU6w5 lE/GPR4rF5LIyFF5YLduCu8fYrHYRjQueH/9cz5nd/ybuWdReacNcZudnbsRkn0vrff50h2uOXLiRKg8iMOF5fYrirpk LzpPQByuavJJhZ+LmHgQKt+UbnbGtkaZ0xdlS8ahdwaatpw++a h8S/UoTbthypy+RsXZzgWZH1wJtl8NnV8dMkvDv46r997QsYoc9caG GGqjxOo3gsqvH2Nb5vXKimL3FePxFj+49SNjlSWnzhGVh/WNh/VhQOVBPUNT5Uj3NVl2nDrrb45UQ/s7TL4xKg/qwN9f6aQVt8yck6dk9O6Sp7dDb2we9N0Kubr1s6X/Z1FcG/RxqthmfLCLrQE2D54XLI8ads/KygO7ZmxJ1IaMGkXRuQHs50DzxN4NySSFy4O45JJrBrP6PGT6l YE+Oy9Gdw31vcD0YUPlYXlxMDsLlddrv3XUMUM+qfb94qYHYnl TP/cELPdw4ZONNapklFieFSrfQJ9dMLulO6duyGP7zqm9Rhlw6lxQ ebn9V573CbLi9D1zmLv33vYSfUqyTzUqD/K6Z85926UltpfofYE+wlsfyg9PCe9K4PKwuAYszx+Vh9UFwPLE UPlxfnMOFk8x4fR9SqqYN0U/ujuxxnE6K18XlYfVHbA56XUKMB4Wt4XlOaPypV0alG9oGnH6Rj a4Ow9qdNHn5EGh8mA8WB9sWB6RrDwsrgSzc1F58BnWtxaWxyUr D/xEXR9kefl27cXxg51euTO1IPJxLi6vWPlXeOgZO8667ThH5y/fszYEu181On/pRxvLlNltKcm4ldq4qStt9G05fdhQeba+Jb2ODJU3MCn+0qBO5 0raTd7N0bal86w5flRUPm7a1NijU+udJPMq9Q/mJfRYbcXp04vKw+J6sDwoVH7AqOCvn43cOXp19OjgUerRbpw+i qg8rK4HlqeHyqeF++cmCe79qunLDWaL3fsl1nMONPrxySEWN47 eFOsTi8rD6iZgecKovHXWpHxvC0NO3myfBWN2VSjIE5J9DFB5c M72ix1B5TQw/lJwzn6Oswv55aFK4fJgPrA+6rDfaZKV90msinIvtuP4RQuaNK6 WefXl2FmoPIh3kr96XpqVPIKQtIOmD1/x+NsqBwKXB3XNU3esWFsxTZFTx63U5dyNf81tsHlgF7z8MjO5W 5yT6L2AOJxd+zf+Sp8MsXml/bMDia3yhGTfhoMRIeEGC6w5fbRQefDeYX2uYH3mZeXB5xFX6u/O0H6UK5nn8Ghre7+s0C4ULg/67BiefeHZ9IKRg/zInj3jG83qjLB5YJf9s8jHK2C8uei9gPrShyd7qRXteu+Ey0uL C8N+x0RWHtb3DHaPo/IW+yzzFUycOXmDZHmC7RZzV06dOyoP+91Y2O/kovIg3/rdpYMp/olMv1DQP3r5oYvFDaY6FC7PT7vdaLHekdO34Xa/H7WvE3pQknEWVB6Wtw+r40blTxjpTYhaQ5MO3Q0a698yz21Tav DjzZE0Oc7oTnWR2O/QofJyu86GDjfmk8WFBH1YrO/TtnEebUME3Nf15Xrfo2lsfsIN/+W9Jxly8gr8XCbsnumrz8mDQuVBnfbq3WtWGrvacfqQZDlOfG4 2oTgXl48IHfBr4kdbjl2w/8772jr3fpzfgULlwfuG/Y4erI+NrDyou4wx3+N1WJnZL6D/YHDa6Feuz/sRuDzMrof9ThAqr7m4/f64hYYcv/Sh7dNOLhlvzfmdLFR+yrOUhXdSaXLj/MHxRwOZffGXhl79gMs0+c6zMsxhFR+b/x84OUeGAQAAAGAVAABgFQAAkQcAAA==eNot2NMSIAgSBMCxbdu 2bdu2bdu2dse2bdu2bXvmMuL2IT+hoqs6QIAAAQISiMAEISjBC E4IQhKK0IQhLOEITwQiEonIRCEq0YhODGISi9jEIS7xiE8CEpK IxCQhKclITgpSkorUpCEt6UhPBjKSicxkISvZyE4OcpKL3OQhL/nITwEKUojCFKEoxShOCUpSitKUoSzlKE8FKlKJylShKtWoTg1q Uova1KEu9ahPAxrSiMY0oSnNaE4LWtKK1rShLe1oTwc60onOdK Er3ehOD3rSi970oS/96M8ABjKIwQxhKMMYzghGMorRjGEs4xjPBCYyiclMYSrTmM4MZ jKLf/iX2cxhLvOYzwIWsojFLGEpy1jOClayitWsYS3rWM8GNrKJzWxh K9vYzg52sovd7GEv+9jPAQ5yiMMc4SjHOM4JTnKK05zhLOc4zw UuconLXOEq17jODW5yi9vc4S73uM8DHvKIxzzhKc94zgte8orX vOEt73jPBz7yic984Svf+M4PfvKL3/zhb4D/hz8ggQhMEIISjOCEICShCE0YwhKO8EQgIpGITBSiEo3oxCAmsY hNHOISj/gkICGJSEwSkpKM5KQgJalITRrSko70ZCAjmchMFrKSjezkICe5 yE0e8pKP/BSgIIUoTBGKUozilKAkpShNGcpSjvJUoCKVqEwVqlKN6tSgJrW oTR3qUo/6NKAhjWhME5rSjOa0oCWtaE0b2tKO9nSgI53oTBe60o3u9KAnv ehNH/rSj/4MYCCDGMwQhjKM4YxgJKMYzRjGMo7xTGAik5jMFKYyjenMYCaz +Id/mc0c5jKP+SxgIYtYzBKWsozlrGAlq1jNGtayjvVsYCOb2MwWtr KN7exgJ7vYzR72so/9HOAghzjMEY5yjOOc4CSnOM0ZznKO81zgIpe4zBWuco3r3OAmt 7jNHe5yj/s84CGPeMwTnvKM57zgJa94zRve8o73fOAjn/jMF77yje/84Ce/+M0f/v53+AMSiMAEISjBCE4IQhKK0IQhLOEITwQiEonIRCEq0YhODGI Si9jEIS7xiE8CEpKIxCQhKclITgpSkorUpCEt6UhPBjKSicxkI SvZyE4OcpKL3OQhL/nITwEKUojCFKEoxShOCUpSitKUoSzlKE8FKlKJylShKtWoTg1q Uova1KEu9ahPAxrSiMY0oSnNaE4LWtKK1rShLe1oTwc60onOdK Er3ehOD3rSi970oS/96M8ABjKIwQxhKMMYzghGMorRjGEs4xjPBCYyiclMYSrTmM4MZ jKLf/iX2cxhLvOYzwIWsojFLGEpy1jOClayitWsYS3rWM8GNrKJzWxh K9vYzg52sovd7GEv+9jPAQ5yiMMc4SjHOM4JTnKK05zhLOc4zw UuconLXOEq17jODW5yi9vc4S73uM8DHvKIxzzhKc94zgte8orX vOEt73jPBz7yic984Svf+M4PfvKL3/zh73+lPyCBCEwQghKM4IQgJKEITRjCEo7wRCAikYhMFKISjejE ICaxiE0c4hKP+CQgIYlITBKSkozkpCAlqUhNGtKSjvRkICOZyE wWspKN7OQgJ7nITR7yko/8FKAghShMEYpSjOKUoCSlKE0ZylKO8lSgIpWoTBWqUo3q1KAmt ahNHepSj/o0oCGNaEwTmtKM5rSgJa1oTRva0o72dKAjnehMF7rSje70oCe9 6E0f+tKP/gxgIIMYzBCGMozhjGAkoxjNGMYyjvFMYCKTmMwUpjKN6cxgJrP 4h3+ZzRzmMo/5LGAhi1jMEpayjOWsYCWrWM0a1rKO9WxgI5vYzBa2so3t7GAnu 9jNHvayj/0c4CCHOMwRjnKM45zgJKc4zRnOco7zXOAil7jMFa5yjevc4Ca3 uM0d7nKP+zzgIY94zBOe8oznvOAlr3jNG97yjvd84COf+MwXvv KN7/zgJ7/4zR/+/jf4AxKIwAQhKMEITghCEorQhCEs4QhPBCISichEISrRiE4MYhK L2MQhLvGITwISkojEJCEpyUhOClKSitSkIS3pSE8GMpKJzGQhK 9nITg5ykovc5CEv+chPAQpSiMIUoSjFKE4JSlKK0pShLOUoTwU qUonKVKEq1ahODWpSi9rUoS71qE8DGtKIxjShKc1oTgta0orWt KEt7WhPBzrSic50oSvd6E4PetKL3vShL/3ozwAGMojBDGEowxjOCEYyitGMYSzjGM8EJjKJyUxhKtOYzgxm Mot/+JfZzGEu85jPAhayiMUsYSnLWM4KVrKK1axhLetYzwY2sonNbG Er29jODnayi93sYS/72M8BDnKIwxzhKMc4zglOcorTnOEs5zjPBS5yictc4SrXuM4Nb nKL29zhLve4zwMe8ojHPOEpz3jOC17yite84S3veM8HPvKJz3z hK9/4zg9+8ovf/OHvf8++gAQiMEEISjCCE4KQhCI0YQhLOMITgYhEIjJRiEo0ohO DmMQiNnGISzzik4CEJCIxSUhKMpKTgpSkIjVpSEs60pOBjGQiM 1nISjayk4Oc5CI3echLPvJTgIIUojBFKEoxilOCkpSiNGUoSzn KU4GKVKIyVahKNarzP3UXmEs=AQAAAFgFAABYBQAA1AEAAA==e NoNz5GyKgoAQNHefefOBEEQBEEQBEEQBEEQBEEQBEEQBEEQBEE QBEEQBEEQBEEQBEEQBEEQBEEQBEFwIAjumtnrA/ZPIBAIEiJMhCgx4iRIkiJNhiw58hQoUqJMhSo16jRo0qJNhy49 +gwYMmLMhCkz5ixYsmLNhi079hw4cuLMhSs37jx48uLNLx++BP 4LBH4IEiJMhCgx4iRIkiJNhiw58hQoUqJMhSo16jRo0qJNhy49 +gwYMmLMhCkz5ixYsmLNhi079hw4cuLMhSs37jx48uLNLx++BP 74J0iIMBGixIiTIEmKNBmy5MhToEiJMhWq1KjToEmLNh269Ogz YMiIMROmzJizYMmKNRu27Nhz4MiJMxeu3Ljz4MmLN798+BL43z 9BQoSJECVGnARJUqTJkCVHngJFSpSpUKVGnQZNWrTp0KVHnwFD RoyZMGXGnAVLVqzZsGXHngNHTpy5cOXGnQdPXrz55cOXwI8IEi JMhCgx4iRIkiJNhiw58hQoUqJMhSo16jRo0qJNhy49+gwYMmLM hCkz5ixYsmLNhi079hw4cuLMhSs37jx48uLNLx++BP76J0iIMB GixIiTIEmKNBmy5MhToEiJMhWq/ANGp6RoAQAAAFYBAABWAQAADQAAAA==eNrj4BgF1AcAKqcKsQ= =
</AppendedData>
</VTKFile>

[joshwilliams]

I have found this package named Vedo to be very good for VTK operations -- not sure how it works for VTU, but worth trying.

[foo_bar]

You can also checkout VTUinterface for I/O. It uses the standard VTK wrapper for Python, but is simpler to use and also has some added functionalities.

[TCCMT]

Hello,

I'm currently facing the same issue. I have tried using meshio, but gives an error since the data in the vtu file is "Appended". I get the following message:

Unknown data format 'append'.
Error: Couldn't read file <file-name>.vtu as vtu

Also, I was not able to make it work with xml.

Any guidance?

[foo_bar]

The data format is called 'appended' and not 'append'. So this is very likely a typo.