在 HDF5 (PyTables) 中存储 numpy 稀疏矩阵 [英] Storing numpy sparse matrix in HDF5 (PyTables)

问题描述

我在用 PyTables 存储 numpy csr_matrix 时遇到问题.我收到此错误:

I am having trouble storing a numpy csr_matrix with PyTables. I'm getting this error:

TypeError: objects of type ``csr_matrix`` are not supported in this context, sorry; supported objects are: NumPy array, record or scalar; homogeneous list or tuple, integer, float, complex or string

我的代码:

f = tables.openFile(path,'w')

atom = tables.Atom.from_dtype(self.count_vector.dtype)
ds = f.createCArray(f.root, 'count', atom, self.count_vector.shape)
ds[:] = self.count_vector
f.close()

有什么想法吗?

谢谢

推荐答案

CSR 矩阵可以从它的 data、indices 和 indptr属性.这些只是常规的 numpy 数组，因此将它们作为 3 个单独的数组存储在 pytables 中应该没有问题，然后将它们传递回 csr_matrix 的构造函数.请参阅 scipy 文档.

A CSR matrix can be fully reconstructed from its data, indices and indptr attributes. These are just regular numpy arrays, so there should be no problem storing them as 3 separate arrays in pytables, then passing them back to the constructor of csr_matrix. See the scipy docs.

Pietro 的回答指出 shape 成员也应该被存储

Pietro's answer has pointed out that the shape member should also be stored

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