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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 bids_to_pwl(self, bids):
 """ Updates the piece-wise linear total cost function using the given bid blocks. Based on off2case.m from MATPOWER by Ray Zimmerman, developed at PSERC Cornell. See U{http://www.pserc.cornell.edu/matpower/} for more info. """

        assert self.is_load
        # Apply only those bids associated with this dispatchable load.
        vl_bids = [bid for bid in bids if bid.vLoad == self]
        # Filter out zero quantity bids.
        gt_zero = [bid for bid in vl_bids if round(bid.quantity, 4) > 0.0]
        # Ignore withheld offers.
        valid_bids = [bid for bid in gt_zero if not bid.withheld]

        p_bids = [v for v in valid_bids if not v.reactive]
        q_bids = [v for v in valid_bids if v.reactive]

        if p_bids:
            self.p_cost = self._offbids_to_points(p_bids, True)
            self.pcost_model = PW_LINEAR
            self.online = True
        else:
            self.p_cost = [(0.0, 0.0), (self.p_max, 0.0)]
            self.pcost_model = PW_LINEAR
            logger.info("No valid active power bids for dispatchable load "
                        "[%s], shutting down." % self.name)
            self.online = False

        if q_bids:
            self.q_cost = self._offbids_to_points(q_bids, True)
            self.qcost_model = PW_LINEAR
            self.online = True
        else:
            self.q_cost = [(self.q_min, 0.0), (0.0, 0.0), (self.q_max, 0.0)]
            self.qcost_model = PW_LINEAR
#            logger.info("No valid bids for dispatchable load, shutting down.")
#            self.online = False

        self._adjust_limits()