h5sparse

Scipy sparse matrix in HDF5.

Installation

pip install h5sparse

Testing

• for single environment:

  python setup.py test

• for all environments:

  tox

Examples

Create dataset

In [1]: importscipy.sparseasss
...: importh5sparse
...: importnumpyasnp
...:
In [2]: sparse_matrix=ss.csr_matrix([[0, 1, 0],
...: [0, 0, 1],
...: [0, 0, 0],
...: [1, 1, 0]],
...: dtype=np.float64)
In [3]: # create dataset from scipy sparse matrix
...: withh5sparse.File("test.h5") ash5f:
...: h5f.create_dataset('sparse/matrix', data=sparse_matrix)
In [4]: # you can also create dataset from another dataset
...: withh5sparse.File("test.h5") ash5f:
...: h5f.create_dataset('sparse/matrix2', data=h5f['sparse/matrix'])
In [5]: # you can also create dataset using the formats that original h5py accepts
...: withh5sparse.File("test.h5") ash5f:
...: h5f.create_dataset('sparse/matrix3', data=[1,2,3])

Read dataset

In [6]: h5f=h5sparse.File("test.h5")
In [7]: h5f['sparse/matrix'][1:3]
Out[7]:
<2x3sparsematrixoftype'<class 'numpy.float64'>'with1storedelementsinCompressedSparseRowformat>In [8]: h5f['sparse/matrix'][1:3].toarray()
Out[8]:
array([[ 0., 0., 1.],
[ 0., 0., 0.]])
In [9]: h5f['sparse']['matrix'][1:3].toarray()
Out[9]:
array([[ 0., 0., 1.],
[ 0., 0., 0.]])
In [10]: h5f['sparse']['matrix'][2:].toarray()
Out[10]:
array([[ 0., 0., 0.],
[ 1., 1., 0.]])
In [11]: h5f['sparse']['matrix'][:2].toarray()
Out[11]:
array([[ 0., 1., 0.],
[ 0., 0., 1.]])
In [12]: h5f['sparse']['matrix'][-2:].toarray()
Out[12]:
array([[ 0., 0., 0.],
[ 1., 1., 0.]])
In [13]: h5f['sparse']['matrix'][:-2].toarray()
Out[13]:
array([[ 0., 1., 0.],
[ 0., 0., 1.]])
In [14]: h5f['sparse']['matrix'][()].toarray()
Out[14]:
array([[ 0., 1., 0.],
[ 0., 0., 1.],
[ 0., 0., 0.],
[ 1., 1., 0.]])
In [15]: importh5pyIn [16]: h5py_h5f=h5py.File("test.h5")
In [17]: h5sparse.Group(h5py_h5f.id)['sparse/matrix'][()]
Out[17]:
<4x3sparsematrixoftype'<class 'numpy.float64'>'with4storedelementsinCompressedSparseRowformat>In [18]: h5sparse.Group(h5py_h5f['sparse'].id)['matrix'][()]
Out[18]:
<4x3sparsematrixoftype'<class 'numpy.float64'>'with4storedelementsinCompressedSparseRowformat>In [19]: h5sparse.Dataset(h5py_h5f['sparse/matrix'])[()]
Out[19]:
<4x3sparsematrixoftype'<class 'numpy.float64'>'with4storedelementsinCompressedSparseRowformat>

Append dataset

In [20]: to_append=ss.csr_matrix([[0, 1, 1],
...: [1, 0, 0]],
...: dtype=np.float64)
In [21]: h5f.create_dataset('matrix', data=sparse_matrix, chunks=(100000,),
...: maxshape=(None,))
In [22]: h5f['matrix'].append(to_append)
In [23]: h5f['matrix'][()]
Out[23]:
<6x3sparsematrixoftype'<class 'numpy.float64'>'with7storedelementsinCompressedSparseRowformat>In [24]: h5f['matrix'][()].toarray()
Out[24]:
array([[ 0., 1., 0.],
[ 0., 0., 1.],
[ 0., 0., 0.],
[ 1., 1., 0.],
[ 0., 1., 1.],
[ 1., 0., 0.]])