def save_sparse_matrix(data, fmt, filepath):
"""
Save a scipy sparse matrix in the specified format. Row and column
indices will be converted to 1-indexed if you specify a plain text
format (tsv, csv, mm). Note that zero entries are guaranteed to be
saved in tsv or csv format.
Parameters
----------
data : scipy sparse matrix to save
fmt : str
Specifies the file format to write:
- tsv
- csv
- mm (MatrixMarket)
- npz (save as npz archive of numpy arrays)
- fsm (mrec.sparse.fast_sparse_matrix)
filepath : str
The file to load.
"""
if fmt == 'tsv':
m = data.tocoo()
with open(filepath, 'w') as out:
for u, i, v in izip(m.row, m.col, m.data):
print >> out, '{0}\t{1}\t{2}'.format(u + 1, i + 1, v)
elif fmt == 'csv':
m = data.tocoo()
with open(filepath, 'w') as out:
for u, i, v in izip(m.row, m.col, m.data):
print >> out, '{0},{1},{2}'.format(u + 1, i + 1, v)
elif fmt == 'mm':
mmwrite(filepath, data)
elif fmt == 'npz':
savez(data.tocoo(), filepath)
elif fmt == 'fsm':
fast_sparse_matrix(data).save(filepath)
else:
raise ValueError('unknown output format: {0}'.format(fmt))
def save_sparse_matrix(data,fmt,filepath):
"""
Save a scipy sparse matrix in the specified format. Row and column
indices will be converted to 1-indexed if you specify a plain text
format (tsv, csv, mm). Note that zero entries are guaranteed to be
saved in tsv or csv format.
Parameters
----------
data : scipy sparse matrix to save
fmt : str
Specifies the file format to write:
- tsv
- csv
- mm (MatrixMarket)
- npz (save as npz archive of numpy arrays)
- fsm (mrec.sparse.fast_sparse_matrix)
filepath : str
The file to load.
"""
if fmt == 'tsv':
m = data.tocoo()
with open(filepath,'w') as out:
for u,i,v in izip(m.row,m.col,m.data):
print >>out,'{0}\t{1}\t{2}'.format(u+1,i+1,v)
elif fmt == 'csv':
m = data.tocoo()
with open(filepath,'w') as out:
for u,i,v in izip(m.row,m.col,m.data):
print >>out,'{0},{1},{2}'.format(u+1,i+1,v)
elif fmt == 'mm':
mmwrite(filepath,data)
elif fmt == 'npz':
savez(data.tocoo(),filepath)
elif fmt == 'fsm':
fast_sparse_matrix(data).save(filepath)
else:
raise ValueError('unknown output format: {0}'.format(fmt))
def save_sparse_matrix(data,fmt,filepath):
"""
Save a scipy sparse matrix in the specified format. Row and column
indices will be converted to 1-indexed if you specify a plain text
format (tsv, csv, mm).
Parameters
----------
data : scipy sparse matrix to save
fmt : str
Specifies the file format to write:
- tsv
- csv
- mm (MatrixMarket)
- npz (save as npz archive of numpy arrays)
- fsm (mrec.sparse.fast_sparse_matrix)
filepath : str
The file to load.
"""
if fmt == 'tsv':
row,col = data.nonzero()
out = open(filepath,'w')
for u,i,v in izip(row,col,data.data):
print >>out,'{0}\t{1}\t{2}'.format(u+1,i+1,v)
elif fmt == 'csv':
row,col = data.nonzero()
out = open(filepath,'w')
for u,i,v in izip(row,col,data.data):
print >>out,'{0},{1},{2}'.format(u+1,i+1,v)
elif fmt == 'mm':
mmwrite(filepath,data)
elif fmt == 'npz':
return savez(data,filepath)
elif fmt == 'fsm':
fast_sparse_matrix.load(dataset).save(filepath)
else:
raise ValueError('unknown output format: {0}'.format(fmt))
