146 lines
5.4 KiB
Python
146 lines
5.4 KiB
Python
from .base_aquire_agent import Base_Aquire_Agent
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import random
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class Price_Believe_Aquire_Agent(Base_Aquire_Agent):
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"""
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Aquire agent with internal price believe system.
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"""
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def __init__(self, simulation, business, resource, exchanges: list, lr, max_price_adj_rate) -> None:
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super().__init__(simulation, business, resource, exchanges)
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self.lr = lr
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self.max_price_adj_rate = max_price_adj_rate
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self.price_believe = {i: 1 for i in range(len(self.exchanges))}
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self.open_orders = {i: [] for i in range(len(self.exchanges))}
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self.open_qty = 0
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self.hp_threshold=0.25
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self.lp_threshold=0.90
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def tick(self, tick, episode):
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order_error = self.open_qty+self.target_error()
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if order_error < 0:
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# aquire based on current price believe
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cx_id = self.select_best_cx()
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order = self.order_resource(
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self.price_believe[cx_id], order_error*-1, cx_id)
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if not order == None:
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self.register_order(cx_id, order)
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else:
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# order failed due to missing balance.. we need to adjust our price believe
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self.collect_balance_from_cxs()
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self.collect_resource_from_cxs(self.resource)
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self.update_believe(cx_id, -1)
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self.tick_open_orders()
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def select_best_cx(self):
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best_id = -1
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best = 999999999
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for cx_id in range(len(self.exchanges)):
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cx = self.exchanges[cx_id]
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available = (cx.get_total_supply(self.resource) > 0)
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if available:
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potential = 1*self.price_believe[cx_id]
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else:
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continue
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if potential < best:
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best = potential
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best_id = cx_id
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if best_id == -1:
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best_id = random.randint(0, len(self.exchanges)-1)
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return best_id
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def register_order(self, cx_id, order):
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self.open_orders[cx_id].append({
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'id': order.order_id,
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'lifetime': self.max_price_adj_rate,
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'leaves': order.leaves_qty
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})
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if order.leaves_qty != order.qty:
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self.update_trades()
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def tick_open_orders(self) -> int:
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"""
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Removes 1 from pending orders timeout timer and cancels timeed out orders.
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Returns ids of orders that timeed out.
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"""
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self.open_qty = 0
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for cx_id in range(len(self.exchanges)):
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cx = self.exchanges[cx_id]
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cx_orders = self.open_orders[cx_id]
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for i in cx_orders:
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# Check for each order if it is fullfiled or if it is timed
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o = self.orders[cx_id][i["id"]]
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leaves = o.leaves_qty
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if o.leaves_qty == 0:
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# order is done
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self.open_orders[cx_id].remove(i) # remove order from open
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self.update_believe(cx_id, -1) # update price believe
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self.collect_balance_from_cxs()
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self.collect_resource_from_cxs(self.resource)
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continue
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if not (i["leaves"] == leaves):
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# update in order
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i["leaves"] = leaves
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self.update_trades()
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# reset lifetime
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i["lifetime"] = self.max_price_adj_rate
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if i["lifetime"] > 0:
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self.open_qty += o.leaves_qty
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i["lifetime"] -= 1 # subtract lifetime
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else:
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# timeout
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self.update_trades()
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modifier =0
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success=self.calc_order_success(cx,o)
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if success>=self.lp_threshold:
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modifier=-1
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elif success<=self.hp_threshold:
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modifier=1
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cx.cancel_order(i["id"])
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self.collect_balance_from_cxs()
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self.collect_resource_from_cxs(self.resource)
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self.update_believe(cx_id, modifier)
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self.open_orders[cx_id].remove(i)
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def calc_order_success(self, cx, o):
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"""
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Calculate how we should adjust the price belive
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"""
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buy = o.qty-o.leaves_qty
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buyperc = buy/o.qty
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dem = cx.total_supply[self.resource]+buy
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if dem == 0:
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dem = 1
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coverage = buy/dem
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base_success = max([coverage, buyperc])
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return base_success
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def update_believe(self, cx_id, modifier):
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"""
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Updates the believe based on the modifier.
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If positive will add lr to believe
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If negative will sub lr to believe
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"""
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self.price_believe[cx_id] += modifier*self.lr
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if self.price_believe[cx_id] < 0:
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self.price_believe[cx_id] = 0
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def reset(self, episode):
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# Clean shop for today
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for cx_id in range(len(self.exchanges)):
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cx = self.exchanges[cx_id]
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cx_orders = self.open_orders[cx_id]
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for i in cx_orders:
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cx.cancel_order(i["id"])
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self.collect_balance_from_cxs()
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self.collect_resource_from_cxs(self.resource)
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# book keeping
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self.update_trades()
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self.open_orders = {i: [] for i in range(len(self.exchanges))}
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self.orders = {i: {} for i in range(len(self.exchanges))}
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return super().reset(episode)
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