pymarket.statistics.maximum_traded_volume module

pymarket.statistics.maximum_traded_volume.maximum_traded_volume(bids, *args, reservation_prices={})

Parameters:

• bids (pd.DataFrame) – Collections of bids
• reservation_prices (dict of floats or None, (Default value = None)) – A maping from user ids to reservation prices. If no reservation price for a user is given, his bid will be assumed to be his true value.

Returns:

• status (str) – Status of the optimization problem. Desired output is ‘Optimal’
• objective (float) – Maximum tradable volume that can be obtained
• variables (dict) – A set of values achieving the objective. Maps a pair of bids to the quantity traded by them.

Examples

>>> bm = pm.BidManager()
>>> bm.add_bid(1, 3, 0)
0
>>> bm.add_bid(1, 2, 1)
1
>>> bm.add_bid(1.5, 1, 2, False)
2
>>> s, o, v = maximum_traded_volume(bm.get_df())
>>> s
'Optimal'
>>> o
1.5
>>> v
OrderedDict([((0, 2), 0.5), ((1, 2), 1.0)])

pymarket.statistics.maximum_traded_volume.percentage_traded(bids, transactions, reservation_prices={}, **kwargs)

Calculates from the transaction dataframe the percentage of the total maximum possible traded quantity.

Parameters:

• (pandas dataframe) (transactions) – Table with all the submited bids
• (pandas dataframe) – Table with all the transactions that ocurred in the market
• (dict, optional) (reservation_prices) – Reservation prices of the different participants. If None, the bids will be assumed to be the truthfull values.

Returns:

ratio – The ratio of the maximum social welfare achieved by the collection of transactions.

Return type:

float

Examples

Only bid 0 and 2 trade 1 unit. That represents the 66% of all that could have been traded.

>>> tm = pm.TransactionManager()
>>> bm = pm.BidManager()
>>> bm.add_bid(1, 3, 0)
0
>>> bm.add_bid(1, 2, 1)
1
>>> bm.add_bid(1.5, 1, 2, False)
2
>>> tm.add_transaction(0, 1, 2, 2, False)
0
>>> tm.add_transaction(2, 1, 2, 0, False)
1
>>> percentage_traded(bm.get_df(), tm.get_df())
0.6666666666666666