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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def fill_edge_matrix(nsrcs, match_dict):
 """ Create and fill a matrix with the graph 'edges' between sources. Parameters nsrcs : int number of sources (used to allocate the size of the matrix) match_dict : dict((int,int):
float) Each entry gives a pair of source indices, and the corresponding measure (either distance or sigma) Returns ------- e_matrix : `~numpy.ndarray` numpy.ndarray((nsrcs,nsrcs)) filled with zeros except for the matches, which are filled with the edge measures (either distances or sigmas) """

    e_matrix = np.zeros((nsrcs, nsrcs))
    for k, v in match_dict.items():
        e_matrix[k[0], k[1]] = v
    return e_matrix