load_sparse.py

# Load a sparse matrix.

import numpy as np
from scipy import sparse

def mymethod():
    print 'hi'

def load_sparse(filename, dtype=np.float32):
    with file(filename) as input:
        ny,nx = input.readline().strip().split()
        nelems = int(input.readline().strip())

        data = np.empty(nelems, dtype=dtype)
        indices = []
        indptr = []
        for line in input:
            y,x,val = line.strip().split()
            data[len(indices)] = float(val)
            while int(y) >= len(indptr):
                indptr.append(len(indices))
            indices.append(int(x))
        indptr.append(len(indices))
            
        if len(indices) != len(data): raise IOError('Not enough data')
        if len(indptr) != int(ny)+1: raise IOError('Not enough rows')
        return sparse.csr_matrix((data,indices,indptr), dtype=dtype)

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