python_sparseclass

import sparse_functions
class GetAttr(type):
    def __getitem__(cls, x):
        return getattr(cls, x)
class Sparse:
    __metaclass__ = GetAttr
    """ Class for sparse matrices"""
    # This is the constructor when dimensions and sparsity are specified
    def __init__(self, *args):
        # The name of the helper function is sparse_gen
        if len(args) == 3:
            num_row = args[0]
            num_col = args[1]
            spar = args[2]
            if ((type(args[0]) is not int) or (type(args[1]) is not int)):
                raise TypeError('The first two arguments should be integers!')
            elif not ((args[0] > 0) and (args[1] > 0)):
                raise ValueError('The first two agruments should be positive!')
            elif not ((args[2] < 1) and (args[2] > 0)):
                raise ValueError('Sparsity must be between 0 and 1!')
            self.sparse_rep = sparse_functions.sparse_gen(num_row, num_col, spar)
        elif len(args) == 1:
            if (type(args[0] is not list)):
                raise TypeError('The only argument supplied should be a list!')
            # The list of lists matrix is provided convert it to sparse
            self.sparse_rep = sparse_functions.mat2sparse(arg[0])
        else:
            raise AttributeError('Invalid number of arguments. There should be either one argument or three arguments!')
    # Overload the addition operation
    def __add__(a,b):
        # Here we can make use of the already defined functions
        return sparse_functions.sparse_add(a,b)
    # Overload the subtraction operator
    def __sub__(a,b):
        return sparse_functions.sparse_add(a,-b)
    # Overload the print function
    def __str__(self):
        sparse_functions.sparse_print(self)