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        "description": "coo_utils works with numpy and scipy.sparse (2D only) to store\ncompressed multidimensional arrays both in memory and on disks. This can\nDRASTICALLY reduce the space required.\n\nIn reality, what is stored is a list-of-lists containing sparse matrix\nnodes in the scipy.sparse.coo_matrix format. The storage format can\neither be normal or differenced (helpful for same-value blocks data).\n\nSome terms used in the code:\n----------------------------\n\nCooHD: list (or deeply nested list(s)) of scipy.sparse.coo_matrix's (HD means higher-dimensional)\n\nnnzs: An array with the same shape as the nested lists in the cooHD (aka without the 2 coo_matrix dimensions) that gives the length of each coo_matrix (nnz) at each node of the tree\n\nRCD: A sparse array represented as a flat row-column-data matrix. Multi-dimensional shape data is recoverable using the nnzs array\n\nThe disk storage format uses the RCD fomat for maximum simplicity:\n------------------------------------------------------------------\n\n\\*_rcd.npy    -  The rcd matrix stored in the .npy format (int32)\n\n\\*_nnzs.npy   -  The nnzs array store in .npy format (int)\n\n\\*_shape.txt  -  a simple text file with the full shape of the array in comma-separated plain text",
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