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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 _column_reduction(self):
 """ Column reduction and reduction transfer steps from LAPJV algorithm """

        #assign each column to its lowest cost row, ensuring that only row
        #or column is assigned once
        i1, j = np.unique(np.argmin(self.c, axis=0), return_index=True)
        self._x[i1] = j

        #if problem is solved, return
        if len(i1) == self.n:
            return False

        self._y[j] = i1

        #reduction_transfer
        #tempc is array with previously assigned matchings masked
        self._v = np.min(self.c, axis=0)
        tempc = self.c.copy()
        tempc[i1, j] = np.inf
        mu = np.min(tempc[i1, :] - self._v[None, :], axis=1)
        self._v[j] -= mu
        return True