def MultiAsset(traders=None,
strategy=None,
name=None,
PnL=None,
timeseries=None):
from marketsim import rtti
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim.gen._out._isingleassettrader import ISingleAssetTrader
from marketsim import listOf
from marketsim.gen._out._imultiassetstrategy import IMultiAssetStrategy
if traders is None or rtti.can_be_casted(traders,
listOf(ISingleAssetTrader)):
if strategy is None or rtti.can_be_casted(strategy,
IMultiAssetStrategy):
if name is None or rtti.can_be_casted(name, str):
if PnL is None or rtti.can_be_casted(PnL, float):
if timeseries is None or rtti.can_be_casted(
timeseries, listOf(ITimeSerie)):
return MultiAsset_ListISingleAssetTraderIMultiAssetStrategyStringFloatListITimeSerie(
traders, strategy, name, PnL, timeseries)
raise Exception('Cannot find suitable overload for MultiAsset(' +
str(traders) + ':' + str(type(traders)) + ',' +
str(strategy) + ':' + str(type(strategy)) + ',' +
str(name) + ':' + str(type(name)) + ',' + str(PnL) + ':' +
str(type(PnL)) + ',' + str(timeseries) + ':' +
str(type(timeseries)) + ')')
def typecheck(self):
from marketsim import listOf
from marketsim.gen._out._imultiassetstrategy import IMultiAssetStrategy
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._isingleassettrader import ISingleAssetTrader
rtti.typecheck(listOf(ISingleAssetTrader), self.traders)
rtti.typecheck(IMultiAssetStrategy, self.strategy)
rtti.typecheck(str, self.name)
rtti.typecheck(float, self.PnL)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def typecheck(self):
from marketsim import listOf
from marketsim.gen._out._imultiassetstrategy import IMultiAssetStrategy
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._isingleassettrader import ISingleAssetTrader
rtti.typecheck(listOf(ISingleAssetTrader), self.traders)
rtti.typecheck(IMultiAssetStrategy, self.strategy)
rtti.typecheck(str, self.name)
rtti.typecheck(float, self.PnL)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def MultiAsset(traders = None,strategy = None,name = None,PnL = None,timeseries = None):
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._imultiassetstrategy import IMultiAssetStrategy
from marketsim.gen._out._isingleassettrader import ISingleAssetTrader
from marketsim import listOf
if traders is None or rtti.can_be_casted(traders, listOf(ISingleAssetTrader)):
if strategy is None or rtti.can_be_casted(strategy, IMultiAssetStrategy):
if name is None or rtti.can_be_casted(name, str):
if PnL is None or rtti.can_be_casted(PnL, float):
if timeseries is None or rtti.can_be_casted(timeseries, listOf(ITimeSerie)):
return MultiAsset_ListISingleAssetTraderIMultiAssetStrategyStringFloatListITimeSerie(traders,strategy,name,PnL,timeseries)
raise Exception('Cannot find suitable overload for MultiAsset('+str(traders) +':'+ str(type(traders))+','+str(strategy) +':'+ str(type(strategy))+','+str(name) +':'+ str(type(name))+','+str(PnL) +':'+ str(type(PnL))+','+str(timeseries) +':'+ str(type(timeseries))+')')
def ChooseTheBest(array=None):
from marketsim import listOf
from marketsim import rtti
if array is None or rtti.can_be_casted(array, listOf(float)):
return ChooseTheBest_ListFloat(array)
raise Exception('Cannot find suitable overload for ChooseTheBest(' +
str(array) + ':' + str(type(array)) + ')')
class Remote_IOrderBookITwoWayLinkListITimeSerie(IOrderBook, _Remote_Impl):
""" to the market by means of a *link* that introduces some latency in information propagation
"""
def __init__(self, orderbook=None, link=None, timeseries=None):
from marketsim.gen._out.orderbook._local import Local_StringFloatIntListITimeSerie as _orderbook_Local_StringFloatIntListITimeSerie
from marketsim.gen._out.orderbook._twowaylink import TwoWayLink_ILinkILink as _orderbook_TwoWayLink_ILinkILink
from marketsim import rtti
self.orderbook = orderbook if orderbook is not None else _orderbook_Local_StringFloatIntListITimeSerie(
)
self.link = link if link is not None else _orderbook_TwoWayLink_ILinkILink(
)
self.timeseries = timeseries if timeseries is not None else []
rtti.check_fields(self)
_Remote_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'orderbook': IOrderBook,
'link': ITwoWayLink,
'timeseries': listOf(ITimeSerie)
}
def __repr__(self):
return "%(orderbook)s.name^remote" % self.__dict__
def SingleAsset(orderBook=None,
strategy=None,
name=None,
amount=None,
PnL=None,
timeseries=None):
from marketsim import rtti
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim.gen._out._iorderbook import IOrderBook
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
if orderBook is None or rtti.can_be_casted(orderBook, IOrderBook):
if strategy is None or rtti.can_be_casted(strategy,
ISingleAssetStrategy):
if name is None or rtti.can_be_casted(name, str):
if amount is None or rtti.can_be_casted(amount, float):
if PnL is None or rtti.can_be_casted(PnL, float):
if timeseries is None or rtti.can_be_casted(
timeseries, listOf(ITimeSerie)):
return SingleAsset_IOrderBookISingleAssetStrategyStringFloatFloatListITimeSerie(
orderBook, strategy, name, amount, PnL,
timeseries)
raise Exception('Cannot find suitable overload for SingleAsset(' +
str(orderBook) + ':' + str(type(orderBook)) + ',' +
str(strategy) + ':' + str(type(strategy)) + ',' +
str(name) + ':' + str(type(name)) + ',' + str(amount) +
':' + str(type(amount)) + ',' + str(PnL) + ':' +
str(type(PnL)) + ',' + str(timeseries) + ':' +
str(type(timeseries)) + ')')
def Array(strategies = None):
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
from marketsim import rtti
if strategies is None or rtti.can_be_casted(strategies, listOf(ISingleAssetStrategy)):
return Array_ListISingleAssetStrategy(strategies)
raise Exception('Cannot find suitable overload for Array('+str(strategies) +':'+ str(type(strategies))+')')
class ChooseTheBest_ListISingleAssetStrategyISingleAssetStrategyIAccountIAccountFloat(
ISingleAssetStrategy, _ChooseTheBest_Impl):
""" In some moments of time the most effective strategy
is chosen and made running; other strategies are suspended.
It can be considered as a particular case for MultiArmedBandit strategy with
*corrector* parameter set to *chooseTheBest*
"""
def __init__(self, strategies=None, account=None, performance=None):
from marketsim.gen._out.strategy._noise import Noise_IEventSideIObservableIOrder as _strategy_Noise_IEventSideIObservableIOrder
from marketsim.gen._out.strategy.account.inner._inner_virtualmarket import inner_VirtualMarket_ as _strategy_account_inner_inner_VirtualMarket_
from marketsim.gen._out.strategy.weight.trader._trader_traderefficiencytrend import trader_TraderEfficiencyTrend_Float as _strategy_weight_trader_trader_TraderEfficiencyTrend_Float
from marketsim import rtti
self.strategies = strategies if strategies is not None else [
_strategy_Noise_IEventSideIObservableIOrder()
]
self.account = account if account is not None else _strategy_account_inner_inner_VirtualMarket_(
)
self.performance = performance if performance is not None else _strategy_weight_trader_trader_TraderEfficiencyTrend_Float(
)
rtti.check_fields(self)
_ChooseTheBest_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'strategies': listOf(ISingleAssetStrategy),
'account': IFunctionIAccountISingleAssetStrategy,
'performance': IFunctionIFunctionfloatIAccount
}
def __repr__(self):
return "ChooseTheBest(%(strategies)s, %(account)s, %(performance)s)" % self.__dict__
class MultiArmedBandit_ListISingleAssetStrategyISingleAssetStrategyIAccountIAccountFloatFloatFloatListFloatListFloat(ISingleAssetStrategy,_MultiarmedBandit2_Impl):
""" In some moments of time the efficiency of the strategies is evaluated
These efficiencies are mapped into weights using *weight* and *normilizer*
functions per every strategy and *corrector* for the whole collection of weights
These weights are used to choose randomly a strategy to run for the next quant of time.
All other strategies are suspended
"""
def __init__(self, strategies = None, account = None, weight = None, normalizer = None, corrector = None):
from marketsim import rtti
from marketsim.gen._out.strategy.weight.trader._trader_traderefficiencytrend import trader_TraderEfficiencyTrend_Float as _strategy_weight_trader_trader_TraderEfficiencyTrend_Float
from marketsim.gen._out.strategy._noise import Noise_IEventSideIObservableIOrder as _strategy_Noise_IEventSideIObservableIOrder
from marketsim.gen._out.strategy.account.inner._inner_virtualmarket import inner_VirtualMarket_ as _strategy_account_inner_inner_VirtualMarket_
from marketsim.gen._out.strategy.weight.f._f_atanpow import f_AtanPow_Float as _strategy_weight_f_f_AtanPow_Float
from marketsim.gen._out.strategy.weight.array._array_identityl import array_IdentityL_ as _strategy_weight_array_array_IdentityL_
self.strategies = strategies if strategies is not None else [_strategy_Noise_IEventSideIObservableIOrder()]
self.account = account if account is not None else _strategy_account_inner_inner_VirtualMarket_()
self.weight = weight if weight is not None else _strategy_weight_trader_trader_TraderEfficiencyTrend_Float()
self.normalizer = normalizer if normalizer is not None else _strategy_weight_f_f_AtanPow_Float()
self.corrector = corrector if corrector is not None else _strategy_weight_array_array_IdentityL_()
rtti.check_fields(self)
_MultiarmedBandit2_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'strategies' : listOf(ISingleAssetStrategy),
'account' : IFunctionIAccountISingleAssetStrategy,
'weight' : IFunctionIFunctionfloatIAccount,
'normalizer' : IFunctionIFunctionfloatIFunctionfloat,
'corrector' : IFunctionIFunctionlistOffloatlistOffloat
}
def __repr__(self):
return "MultiArmedBandit(%(strategies)s, %(account)s, %(weight)s, %(normalizer)s, %(corrector)s)" % self.__dict__
class volumeLevels_IVolumeLevelsIGraphIntIntListFloatInt(ITimeSerie,_VolumeLevels_Impl):
""" Level of volume V is a price at which cumulative volume of better orders is V
"""
def __init__(self, source , graph = None, _digitsToShow = None, _smooth = None, _volumes = None, _isBuy = None):
from marketsim.gen._out.veusz._graph import Graph_String as _veusz_Graph_String
from marketsim import rtti
self.source = source
self.graph = graph if graph is not None else _veusz_Graph_String()
self._digitsToShow = _digitsToShow if _digitsToShow is not None else 4
self._smooth = _smooth if _smooth is not None else 1
self._volumes = _volumes if _volumes is not None else [30.0]
self._isBuy = _isBuy if _isBuy is not None else 1
rtti.check_fields(self)
_VolumeLevels_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'source' : IFunctionIVolumeLevels,
'graph' : IGraph,
'_digitsToShow' : int,
'_smooth' : int,
'_volumes' : listOf(float),
'_isBuy' : int
}
def __repr__(self):
return "%(source)s" % self.__dict__
def volumeLevels(source=None,
graph=None,
_digitsToShow=None,
_smooth=None,
_volumes=None,
_isBuy=None):
from marketsim.gen._out._ifunction._ifunctionivolumelevels import IFunctionIVolumeLevels
from marketsim.gen._out._igraph import IGraph
from marketsim import listOf
from marketsim import rtti
if source is None or rtti.can_be_casted(source, IFunctionIVolumeLevels):
if graph is None or rtti.can_be_casted(graph, IGraph):
if _digitsToShow is None or rtti.can_be_casted(_digitsToShow, int):
if _smooth is None or rtti.can_be_casted(_smooth, int):
if _volumes is None or rtti.can_be_casted(
_volumes, listOf(float)):
if _isBuy is None or rtti.can_be_casted(_isBuy, int):
return volumeLevels_IVolumeLevelsIGraphIntIntListFloatInt(
source, graph, _digitsToShow, _smooth,
_volumes, _isBuy)
raise Exception('Cannot find suitable overload for volumeLevels(' +
str(source) + ':' + str(type(source)) + ',' + str(graph) +
':' + str(type(graph)) + ',' + str(_digitsToShow) + ':' +
str(type(_digitsToShow)) + ',' + str(_smooth) + ':' +
str(type(_smooth)) + ',' + str(_volumes) + ':' +
str(type(_volumes)) + ',' + str(_isBuy) + ':' +
str(type(_isBuy)) + ')')
class Local_StringFloatIntListITimeSerie(IOrderBook, _Local_Impl):
""" Maintains two order queues for orders of different sides
"""
def __init__(self,
name=None,
tickSize=None,
_digitsToShow=None,
timeseries=None):
from marketsim import rtti
self.name = name if name is not None else "-orderbook-"
self.tickSize = tickSize if tickSize is not None else 0.01
self._digitsToShow = _digitsToShow if _digitsToShow is not None else 2
self.timeseries = timeseries if timeseries is not None else []
rtti.check_fields(self)
_Local_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'name': str,
'tickSize': float,
'_digitsToShow': int,
'timeseries': listOf(ITimeSerie)
}
def __repr__(self):
return "%(name)s" % self.__dict__
def typecheck(self):
from marketsim import rtti
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import listOf
rtti.typecheck(str, self.name)
rtti.typecheck(float, self.tickSize)
rtti.typecheck(int, self._digitsToShow)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def typecheck(self):
from marketsim import rtti
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import listOf
rtti.typecheck(str, self.name)
rtti.typecheck(float, self.tickSize)
rtti.typecheck(int, self._digitsToShow)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def typecheck(self):
from marketsim.gen._out._itwowaylink import ITwoWayLink
from marketsim import listOf
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._iorderbook import IOrderBook
rtti.typecheck(IOrderBook, self.orderbook)
rtti.typecheck(ITwoWayLink, self.link)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def typecheck(self):
from marketsim.gen._out._itwowaylink import ITwoWayLink
from marketsim import listOf
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._iorderbook import IOrderBook
rtti.typecheck(IOrderBook, self.orderbook)
rtti.typecheck(ITwoWayLink, self.link)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def typecheck(self):
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim.gen._out._ifunction._ifunctioniaccount_from_isingleassetstrategy import IFunctionIAccount_from_ISingleAssetStrategy
from marketsim import listOf
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_iaccount import IFunctionIFunctionfloat_from_IAccount
from marketsim import rtti
rtti.typecheck(listOf(ISingleAssetStrategy), self.strategies)
rtti.typecheck(IFunctionIAccount_from_ISingleAssetStrategy, self.account)
rtti.typecheck(IFunctionIFunctionfloat_from_IAccount, self.performance)
def typecheck(self):
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim.gen._out._ifunction._ifunctioniaccount_from_isingleassetstrategy import IFunctionIAccount_from_ISingleAssetStrategy
from marketsim import listOf
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_iaccount import IFunctionIFunctionfloat_from_IAccount
from marketsim import rtti
rtti.typecheck(listOf(ISingleAssetStrategy), self.strategies)
rtti.typecheck(IFunctionIAccount_from_ISingleAssetStrategy,
self.account)
rtti.typecheck(IFunctionIFunctionfloat_from_IAccount, self.performance)
def Local(name = None,tickSize = None,_digitsToShow = None,timeseries = None):
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import listOf
from marketsim import rtti
if name is None or rtti.can_be_casted(name, str):
if tickSize is None or rtti.can_be_casted(tickSize, float):
if _digitsToShow is None or rtti.can_be_casted(_digitsToShow, int):
if timeseries is None or rtti.can_be_casted(timeseries, listOf(ITimeSerie)):
return Local_StringFloatIntListITimeSerie(name,tickSize,_digitsToShow,timeseries)
raise Exception('Cannot find suitable overload for Local('+str(name) +':'+ str(type(name))+','+str(tickSize) +':'+ str(type(tickSize))+','+str(_digitsToShow) +':'+ str(type(_digitsToShow))+','+str(timeseries) +':'+ str(type(timeseries))+')')
def typecheck(self):
from marketsim import rtti
from marketsim.gen._out._ifunction._ifunctionivolumelevels import IFunctionIVolumeLevels
from marketsim.gen._out._igraph import IGraph
from marketsim import listOf
rtti.typecheck(IFunctionIVolumeLevels, self.source)
rtti.typecheck(IGraph, self.graph)
rtti.typecheck(int, self._digitsToShow)
rtti.typecheck(int, self._smooth)
rtti.typecheck(listOf(float), self._volumes)
rtti.typecheck(int, self._isBuy)
def typecheck(self):
from marketsim import rtti
from marketsim.gen._out._ifunction._ifunctionivolumelevels import IFunctionIVolumeLevels
from marketsim.gen._out._igraph import IGraph
from marketsim import listOf
rtti.typecheck(IFunctionIVolumeLevels, self.source)
rtti.typecheck(IGraph, self.graph)
rtti.typecheck(int, self._digitsToShow)
rtti.typecheck(int, self._smooth)
rtti.typecheck(listOf(float), self._volumes)
rtti.typecheck(int, self._isBuy)
def ChooseTheBest(strategies = None,account = None,performance = None):
from marketsim.gen._out._ifunction import IFunctionIFunctionfloatIAccount
from marketsim import rtti
from marketsim.gen._out._ifunction import IFunctionIAccountISingleAssetStrategy
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
if strategies is None or rtti.can_be_casted(strategies, listOf(ISingleAssetStrategy)):
if account is None or rtti.can_be_casted(account, IFunctionIAccountISingleAssetStrategy):
if performance is None or rtti.can_be_casted(performance, IFunctionIFunctionfloatIAccount):
return ChooseTheBest_ListISingleAssetStrategyISingleAssetStrategyIAccountIAccountFloat(strategies,account,performance)
raise Exception('Cannot find suitable overload for ChooseTheBest('+str(strategies) +':'+ str(type(strategies))+','+str(account) +':'+ str(type(account))+','+str(performance) +':'+ str(type(performance))+')')
def Remote(orderbook = None,link = None,timeseries = None):
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._itwowaylink import ITwoWayLink
from marketsim import listOf
from marketsim.gen._out._iorderbook import IOrderBook
if orderbook is None or rtti.can_be_casted(orderbook, IOrderBook):
if link is None or rtti.can_be_casted(link, ITwoWayLink):
if timeseries is None or rtti.can_be_casted(timeseries, listOf(ITimeSerie)):
return Remote_IOrderBookITwoWayLinkListITimeSerie(orderbook,link,timeseries)
raise Exception('Cannot find suitable overload for Remote('+str(orderbook) +':'+ str(type(orderbook))+','+str(link) +':'+ str(type(link))+','+str(timeseries) +':'+ str(type(timeseries))+')')
def typecheck(self):
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._iorderbook import IOrderBook
rtti.typecheck(IOrderBook, self.orderBook)
rtti.typecheck(ISingleAssetStrategy, self.strategy)
rtti.typecheck(str, self.name)
rtti.typecheck(float, self.amount)
rtti.typecheck(float, self.PnL)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def typecheck(self):
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._iorderbook import IOrderBook
rtti.typecheck(IOrderBook, self.orderBook)
rtti.typecheck(ISingleAssetStrategy, self.strategy)
rtti.typecheck(str, self.name)
rtti.typecheck(float, self.amount)
rtti.typecheck(float, self.PnL)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def volumeLevels(source = None,graph = None,_digitsToShow = None,_smooth = None,_volumes = None,_isBuy = None):
from marketsim.gen._out._ifunction import IFunctionIVolumeLevels
from marketsim.gen._out._igraph import IGraph
from marketsim import listOf
from marketsim import rtti
if source is None or rtti.can_be_casted(source, IFunctionIVolumeLevels):
if graph is None or rtti.can_be_casted(graph, IGraph):
if _digitsToShow is None or rtti.can_be_casted(_digitsToShow, int):
if _smooth is None or rtti.can_be_casted(_smooth, int):
if _volumes is None or rtti.can_be_casted(_volumes, listOf(float)):
if _isBuy is None or rtti.can_be_casted(_isBuy, int):
return volumeLevels_IVolumeLevelsIGraphIntIntListFloatInt(source,graph,_digitsToShow,_smooth,_volumes,_isBuy)
raise Exception('Cannot find suitable overload for volumeLevels('+str(source) +':'+ str(type(source))+','+str(graph) +':'+ str(type(graph))+','+str(_digitsToShow) +':'+ str(type(_digitsToShow))+','+str(_smooth) +':'+ str(type(_smooth))+','+str(_volumes) +':'+ str(type(_volumes))+','+str(_isBuy) +':'+ str(type(_isBuy))+')')
def typecheck(self):
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim.gen._out._ifunction._ifunctioniaccount_from_isingleassetstrategy import IFunctionIAccount_from_ISingleAssetStrategy
from marketsim import listOf
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_iaccount import IFunctionIFunctionfloat_from_IAccount
from marketsim import rtti
from marketsim.gen._out._ifunction._ifunctionifunctionlistoffloat_from_listoffloat import IFunctionIFunctionlistOffloat_from_listOffloat
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_ifunctionfloat import IFunctionIFunctionfloat_from_IFunctionfloat
rtti.typecheck(listOf(ISingleAssetStrategy), self.strategies)
rtti.typecheck(IFunctionIAccount_from_ISingleAssetStrategy, self.account)
rtti.typecheck(IFunctionIFunctionfloat_from_IAccount, self.weight)
rtti.typecheck(IFunctionIFunctionfloat_from_IFunctionfloat, self.normalizer)
rtti.typecheck(IFunctionIFunctionlistOffloat_from_listOffloat, self.corrector)
def SingleAsset(orderBook = None,strategy = None,name = None,amount = None,PnL = None,timeseries = None):
from marketsim import rtti
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim.gen._out._iorderbook import IOrderBook
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
if orderBook is None or rtti.can_be_casted(orderBook, IOrderBook):
if strategy is None or rtti.can_be_casted(strategy, ISingleAssetStrategy):
if name is None or rtti.can_be_casted(name, str):
if amount is None or rtti.can_be_casted(amount, float):
if PnL is None or rtti.can_be_casted(PnL, float):
if timeseries is None or rtti.can_be_casted(timeseries, listOf(ITimeSerie)):
return SingleAsset_IOrderBookISingleAssetStrategyStringFloatFloatListITimeSerie(orderBook,strategy,name,amount,PnL,timeseries)
raise Exception('Cannot find suitable overload for SingleAsset('+str(orderBook) +':'+ str(type(orderBook))+','+str(strategy) +':'+ str(type(strategy))+','+str(name) +':'+ str(type(name))+','+str(amount) +':'+ str(type(amount))+','+str(PnL) +':'+ str(type(PnL))+','+str(timeseries) +':'+ str(type(timeseries))+')')
def MultiArmedBandit(strategies=None, account=None, weight=None, normalizer=None, corrector=None):
from marketsim.gen._out._ifunction._ifunctionifunctionlistoffloat_from_listoffloat import (
IFunctionIFunctionlistOffloat_from_listOffloat,
)
from marketsim import rtti
from marketsim.gen._out._ifunction._ifunctioniaccount_from_isingleassetstrategy import (
IFunctionIAccount_from_ISingleAssetStrategy,
)
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_ifunctionfloat import (
IFunctionIFunctionfloat_from_IFunctionfloat,
)
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_iaccount import (
IFunctionIFunctionfloat_from_IAccount,
)
if strategies is None or rtti.can_be_casted(strategies, listOf(ISingleAssetStrategy)):
if account is None or rtti.can_be_casted(account, IFunctionIAccount_from_ISingleAssetStrategy):
if weight is None or rtti.can_be_casted(weight, IFunctionIFunctionfloat_from_IAccount):
if normalizer is None or rtti.can_be_casted(normalizer, IFunctionIFunctionfloat_from_IFunctionfloat):
if corrector is None or rtti.can_be_casted(
corrector, IFunctionIFunctionlistOffloat_from_listOffloat
):
return MultiArmedBandit_ListISingleAssetStrategyISingleAssetStrategyIAccountIAccountFloatFloatFloatListFloatListFloat(
strategies, account, weight, normalizer, corrector
)
raise Exception(
"Cannot find suitable overload for MultiArmedBandit("
+ str(strategies)
+ ":"
+ str(type(strategies))
+ ","
+ str(account)
+ ":"
+ str(type(account))
+ ","
+ str(weight)
+ ":"
+ str(type(weight))
+ ","
+ str(normalizer)
+ ":"
+ str(type(normalizer))
+ ","
+ str(corrector)
+ ":"
+ str(type(corrector))
+ ")"
)
def MultiArmedBandit(strategies = None,account = None,weight = None,normalizer = None,corrector = None):
from marketsim.gen._out._ifunction._ifunctionifunctionlistoffloat_from_listoffloat import IFunctionIFunctionlistOffloat_from_listOffloat
from marketsim import rtti
from marketsim.gen._out._ifunction._ifunctioniaccount_from_isingleassetstrategy import IFunctionIAccount_from_ISingleAssetStrategy
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_ifunctionfloat import IFunctionIFunctionfloat_from_IFunctionfloat
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_iaccount import IFunctionIFunctionfloat_from_IAccount
if strategies is None or rtti.can_be_casted(strategies, listOf(ISingleAssetStrategy)):
if account is None or rtti.can_be_casted(account, IFunctionIAccount_from_ISingleAssetStrategy):
if weight is None or rtti.can_be_casted(weight, IFunctionIFunctionfloat_from_IAccount):
if normalizer is None or rtti.can_be_casted(normalizer, IFunctionIFunctionfloat_from_IFunctionfloat):
if corrector is None or rtti.can_be_casted(corrector, IFunctionIFunctionlistOffloat_from_listOffloat):
return MultiArmedBandit_ListISingleAssetStrategyISingleAssetStrategyIAccountIAccountFloatFloatFloatListFloatListFloat(strategies,account,weight,normalizer,corrector)
raise Exception('Cannot find suitable overload for MultiArmedBandit('+str(strategies) +':'+ str(type(strategies))+','+str(account) +':'+ str(type(account))+','+str(weight) +':'+ str(type(weight))+','+str(normalizer) +':'+ str(type(normalizer))+','+str(corrector) +':'+ str(type(corrector))+')')
def Local(name=None, tickSize=None, _digitsToShow=None, timeseries=None):
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import listOf
from marketsim import rtti
if name is None or rtti.can_be_casted(name, str):
if tickSize is None or rtti.can_be_casted(tickSize, float):
if _digitsToShow is None or rtti.can_be_casted(_digitsToShow, int):
if timeseries is None or rtti.can_be_casted(
timeseries, listOf(ITimeSerie)):
return Local_StringFloatIntListITimeSerie(
name, tickSize, _digitsToShow, timeseries)
raise Exception('Cannot find suitable overload for Local(' + str(name) +
':' + str(type(name)) + ',' + str(tickSize) + ':' +
str(type(tickSize)) + ',' + str(_digitsToShow) + ':' +
str(type(_digitsToShow)) + ',' + str(timeseries) + ':' +
str(type(timeseries)) + ')')
def Remote(orderbook=None, link=None, timeseries=None):
from marketsim import rtti
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim.gen._out._iorderbook import IOrderBook
from marketsim.gen._out._itwowaylink import ITwoWayLink
from marketsim import listOf
if orderbook is None or rtti.can_be_casted(orderbook, IOrderBook):
if link is None or rtti.can_be_casted(link, ITwoWayLink):
if timeseries is None or rtti.can_be_casted(
timeseries, listOf(ITimeSerie)):
return Remote_IOrderBookITwoWayLinkListITimeSerie(
orderbook, link, timeseries)
raise Exception('Cannot find suitable overload for Remote(' +
str(orderbook) + ':' + str(type(orderbook)) + ',' +
str(link) + ':' + str(type(link)) + ',' + str(timeseries) +
':' + str(type(timeseries)) + ')')
class ChooseTheBest_ListFloat(IFunctionlistOffloat, _ChooseTheBest_Impl):
""" having 1 at the index of the maximal element and 0 are at the rest
"""
def __init__(self, array=None):
from marketsim import rtti
self.array = array if array is not None else []
rtti.check_fields(self)
_ChooseTheBest_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {'array': listOf(float)}
def __repr__(self):
return "ChooseTheBest(%(array)s)" % self.__dict__
class IdentityL_ListFloat(IFunctionlistOffloat, _Identity_Impl):
"""
"""
def __init__(self, array=None):
from marketsim import rtti
self.array = array if array is not None else []
rtti.check_fields(self)
_Identity_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {'array': listOf(float)}
def __repr__(self):
return "IdentityL(%(array)s)" % self.__dict__
def ChooseTheBest(strategies=None, account=None, performance=None):
from marketsim.gen._out._ifunction import IFunctionIFunctionfloatIAccount
from marketsim import rtti
from marketsim.gen._out._ifunction import IFunctionIAccountISingleAssetStrategy
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
if strategies is None or rtti.can_be_casted(strategies,
listOf(ISingleAssetStrategy)):
if account is None or rtti.can_be_casted(
account, IFunctionIAccountISingleAssetStrategy):
if performance is None or rtti.can_be_casted(
performance, IFunctionIFunctionfloatIAccount):
return ChooseTheBest_ListISingleAssetStrategyISingleAssetStrategyIAccountIAccountFloat(
strategies, account, performance)
raise Exception('Cannot find suitable overload for ChooseTheBest(' +
str(strategies) + ':' + str(type(strategies)) + ',' +
str(account) + ':' + str(type(account)) + ',' +
str(performance) + ':' + str(type(performance)) + ')')
class Array_ListISingleAssetStrategy(ISingleAssetStrategy, _Array_Impl):
"""
"""
def __init__(self, strategies=None):
from marketsim.gen._out.strategy._noise import Noise_IEventSideIObservableIOrder as _strategy_Noise_IEventSideIObservableIOrder
from marketsim import rtti
self.strategies = strategies if strategies is not None else [
_strategy_Noise_IEventSideIObservableIOrder()
]
rtti.check_fields(self)
_Array_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {'strategies': listOf(ISingleAssetStrategy)}
def __repr__(self):
return "Array(%(strategies)s)" % self.__dict__
def typecheck(self):
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim.gen._out._ifunction._ifunctioniaccount_from_isingleassetstrategy import (
IFunctionIAccount_from_ISingleAssetStrategy,
)
from marketsim import listOf
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_iaccount import (
IFunctionIFunctionfloat_from_IAccount,
)
from marketsim import rtti
from marketsim.gen._out._ifunction._ifunctionifunctionlistoffloat_from_listoffloat import (
IFunctionIFunctionlistOffloat_from_listOffloat,
)
from marketsim.gen._out._ifunction._ifunctionifunctionfloat_from_ifunctionfloat import (
IFunctionIFunctionfloat_from_IFunctionfloat,
)
rtti.typecheck(listOf(ISingleAssetStrategy), self.strategies)
rtti.typecheck(IFunctionIAccount_from_ISingleAssetStrategy, self.account)
rtti.typecheck(IFunctionIFunctionfloat_from_IAccount, self.weight)
rtti.typecheck(IFunctionIFunctionfloat_from_IFunctionfloat, self.normalizer)
rtti.typecheck(IFunctionIFunctionlistOffloat_from_listOffloat, self.corrector)
class SingleAsset_IOrderBookISingleAssetStrategyStringFloatFloatListITimeSerie(
ISingleAssetTrader, _SingleAsset_Impl):
"""
"""
def __init__(self,
orderBook,
strategy=None,
name=None,
amount=None,
PnL=None,
timeseries=None):
from marketsim.gen._out.strategy._noise import Noise_IEventSideIObservableIOrder as _strategy_Noise_IEventSideIObservableIOrder
from marketsim import rtti
self.orderBook = orderBook
self.strategy = strategy if strategy is not None else _strategy_Noise_IEventSideIObservableIOrder(
)
self.name = name if name is not None else "-trader-"
self.amount = amount if amount is not None else 0.0
self.PnL = PnL if PnL is not None else 0.0
self.timeseries = timeseries if timeseries is not None else []
rtti.check_fields(self)
_SingleAsset_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'orderBook': IOrderBook,
'strategy': ISingleAssetStrategy,
'name': str,
'amount': float,
'PnL': float,
'timeseries': listOf(ITimeSerie)
}
def __repr__(self):
return "%(name)s" % self.__dict__
def ChooseTheBest(array = None):
from marketsim import listOf
from marketsim import rtti
if array is None or rtti.can_be_casted(array, listOf(float)):
return ChooseTheBest_ListFloat(array)
raise Exception('Cannot find suitable overload for ChooseTheBest('+str(array) +':'+ str(type(array))+')')
class volumeLevels_IVolumeLevelsIGraphIntIntListFloatInt(
ITimeSerie, VolumeLevels_Impl):
""" **Time serie holding volume levels of an asset**
Level of volume V is a price at which cumulative volume of better orders is V
Parameters are:
**source**
**graph**
**_digitsToShow**
**_smooth**
**_volumes**
**_isBuy**
"""
def __init__(self,
source,
graph=None,
_digitsToShow=None,
_smooth=None,
_volumes=None,
_isBuy=None):
from marketsim.gen._out.veusz._graph import Graph_String as _veusz_Graph_String
from marketsim import deref_opt
self.source = source
self.graph = graph if graph is not None else deref_opt(
_veusz_Graph_String())
self._digitsToShow = _digitsToShow if _digitsToShow is not None else 4
self._smooth = _smooth if _smooth is not None else 1
self._volumes = _volumes if _volumes is not None else [30.0]
self._isBuy = _isBuy if _isBuy is not None else 1
VolumeLevels_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'source': IFunctionIVolumeLevels,
'graph': IGraph,
'_digitsToShow': int,
'_smooth': int,
'_volumes': listOf(float),
'_isBuy': int
}
def __repr__(self):
return "%(source)s" % dict([(name, getattr(self, name))
for name in self._properties.iterkeys()])
def bind_ex(self, ctx):
if self.__dict__.get('_bound_ex', False): return
self.__dict__['_bound_ex'] = True
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
self.__dict__['_ctx_ex'] = ctx.updatedFrom(self)
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.bind_ex(self.__dict__['_ctx_ex'])
else:
v.bind_ex(self.__dict__['_ctx_ex'])
self.source.bind_ex(self._ctx_ex)
self.graph.bind_ex(self._ctx_ex)
self.bind_impl(self.__dict__['_ctx_ex'])
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.bind_ex(self.__dict__['_ctx_ex'])
self.__dict__['_processing_ex'] = False
def reset_ex(self, generation):
if self.__dict__.get('_reset_generation_ex', -1) == generation: return
self.__dict__['_reset_generation_ex'] = generation
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.reset_ex(generation)
else:
v.reset_ex(generation)
self.source.reset_ex(generation)
self.graph.reset_ex(generation)
self.reset()
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.reset_ex(generation)
self.__dict__['_processing_ex'] = False
def typecheck(self):
from marketsim import rtti
from marketsim.gen._out._ifunction._ifunctionivolumelevels import IFunctionIVolumeLevels
from marketsim.gen._out._igraph import IGraph
from marketsim import listOf
rtti.typecheck(IFunctionIVolumeLevels, self.source)
rtti.typecheck(IGraph, self.graph)
rtti.typecheck(int, self._digitsToShow)
rtti.typecheck(int, self._smooth)
rtti.typecheck(listOf(float), self._volumes)
rtti.typecheck(int, self._isBuy)
def registerIn(self, registry):
if self.__dict__.get('_id', False): return
self.__dict__['_id'] = True
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
registry.insert(self)
self.source.registerIn(registry)
self.graph.registerIn(registry)
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.registerIn(registry)
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.registerIn(registry)
else:
v.registerIn(registry)
self.__dict__['_processing_ex'] = False
def bind_impl(self, ctx):
VolumeLevels_Impl.bind_impl(self, ctx)
def reset(self):
VolumeLevels_Impl.reset(self)
def typecheck(self):
from marketsim import rtti
from marketsim import listOf
rtti.typecheck(listOf(float), self.array)
class Local_StringFloatIntListITimeSerie(IOrderBook, Local_Impl):
""" **Order book for a single asset in a market.**
Maintains two order queues for orders of different sides
Parameters are:
**name**
**tickSize**
**_digitsToShow**
**timeseries**
"""
def __init__(self,
name=None,
tickSize=None,
_digitsToShow=None,
timeseries=None):
self.name = name if name is not None else "-orderbook-"
self.tickSize = tickSize if tickSize is not None else 0.01
self._digitsToShow = _digitsToShow if _digitsToShow is not None else 2
self.timeseries = timeseries if timeseries is not None else []
Local_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'name': str,
'tickSize': float,
'_digitsToShow': int,
'timeseries': listOf(ITimeSerie)
}
def __repr__(self):
return "%(name)s" % dict([(name, getattr(self, name))
for name in self._properties.iterkeys()])
def bind_ex(self, ctx):
if self.__dict__.get('_bound_ex', False): return
self.__dict__['_bound_ex'] = True
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
self.__dict__['_ctx_ex'] = ctx.updatedFrom(self)
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.bind_ex(self.__dict__['_ctx_ex'])
else:
v.bind_ex(self.__dict__['_ctx_ex'])
for x in self.timeseries:
x.bind_ex(self._ctx_ex)
self.bind_impl(self.__dict__['_ctx_ex'])
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.bind_ex(self.__dict__['_ctx_ex'])
self.__dict__['_processing_ex'] = False
def reset_ex(self, generation):
if self.__dict__.get('_reset_generation_ex', -1) == generation: return
self.__dict__['_reset_generation_ex'] = generation
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.reset_ex(generation)
else:
v.reset_ex(generation)
for x in self.timeseries:
x.reset_ex(generation)
self.reset()
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.reset_ex(generation)
self.__dict__['_processing_ex'] = False
def typecheck(self):
from marketsim import rtti
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import listOf
rtti.typecheck(str, self.name)
rtti.typecheck(float, self.tickSize)
rtti.typecheck(int, self._digitsToShow)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def registerIn(self, registry):
if self.__dict__.get('_id', False): return
self.__dict__['_id'] = True
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
registry.insert(self)
for x in self.timeseries:
x.registerIn(registry)
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.registerIn(registry)
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.registerIn(registry)
else:
v.registerIn(registry)
self.__dict__['_processing_ex'] = False
def bind_impl(self, ctx):
Local_Impl.bind_impl(self, ctx)
def reset(self):
Local_Impl.reset(self)
def typecheck(self):
from marketsim import rtti
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
rtti.typecheck(listOf(ISingleAssetStrategy), self.strategies)
class IFunctionIFunctionlistOffloat_from_listOffloat(object):
_types = [meta.function((listOf(float), ), IFunctionlistOffloat)]
_types.append(IFunctionobject_from_listOffloat)
_types.append(IFunctionIFunctionobject_from_listOffloat)
_types.append(IFunctionIFunctionlistOfobject_from_listOffloat)
pass
class Remote_IOrderBookITwoWayLinkListITimeSerie(IOrderBook, Remote_Impl):
""" **Represent an *orderbook* from point of view of a remote trader connected**
to the market by means of a *link* that introduces some latency in information propagation
Parameters are:
**orderbook**
**link**
**timeseries**
"""
def __init__(self, orderbook=None, link=None, timeseries=None):
from marketsim.gen._out.orderbook._local import Local_StringFloatIntListITimeSerie as _orderbook_Local_StringFloatIntListITimeSerie
from marketsim import deref_opt
from marketsim.gen._out.orderbook._twowaylink import TwoWayLink_ILinkILink as _orderbook_TwoWayLink_ILinkILink
self.orderbook = orderbook if orderbook is not None else deref_opt(
_orderbook_Local_StringFloatIntListITimeSerie())
self.link = link if link is not None else deref_opt(
_orderbook_TwoWayLink_ILinkILink())
self.timeseries = timeseries if timeseries is not None else []
Remote_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'orderbook': IOrderBook,
'link': ITwoWayLink,
'timeseries': listOf(ITimeSerie)
}
def __repr__(self):
return "%(orderbook)s.name^remote" % dict([(name, getattr(
self, name)) for name in self._properties.iterkeys()])
def bind_ex(self, ctx):
if self.__dict__.get('_bound_ex', False): return
self.__dict__['_bound_ex'] = True
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
self.__dict__['_ctx_ex'] = ctx.updatedFrom(self)
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.bind_ex(self.__dict__['_ctx_ex'])
else:
v.bind_ex(self.__dict__['_ctx_ex'])
self.orderbook.bind_ex(self._ctx_ex)
self.link.bind_ex(self._ctx_ex)
for x in self.timeseries:
x.bind_ex(self._ctx_ex)
self.bind_impl(self.__dict__['_ctx_ex'])
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.bind_ex(self.__dict__['_ctx_ex'])
self.__dict__['_processing_ex'] = False
def reset_ex(self, generation):
if self.__dict__.get('_reset_generation_ex', -1) == generation: return
self.__dict__['_reset_generation_ex'] = generation
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.reset_ex(generation)
else:
v.reset_ex(generation)
self.orderbook.reset_ex(generation)
self.link.reset_ex(generation)
for x in self.timeseries:
x.reset_ex(generation)
self.reset()
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.reset_ex(generation)
self.__dict__['_processing_ex'] = False
def typecheck(self):
from marketsim.gen._out._itwowaylink import ITwoWayLink
from marketsim import listOf
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._iorderbook import IOrderBook
rtti.typecheck(IOrderBook, self.orderbook)
rtti.typecheck(ITwoWayLink, self.link)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def registerIn(self, registry):
if self.__dict__.get('_id', False): return
self.__dict__['_id'] = True
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
registry.insert(self)
self.orderbook.registerIn(registry)
self.link.registerIn(registry)
for x in self.timeseries:
x.registerIn(registry)
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.registerIn(registry)
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.registerIn(registry)
else:
v.registerIn(registry)
self.__dict__['_processing_ex'] = False
def bind_impl(self, ctx):
Remote_Impl.bind_impl(self, ctx)
def reset(self):
Remote_Impl.reset(self)
class SingleAsset_IOrderBookISingleAssetStrategyStringFloatFloatListITimeSerie(
ISingleAssetTrader, SingleAsset_Impl):
""" **A trader that trades a single asset on a single market**
Parameters are:
**orderBook**
order book for the asset being traded
**strategy**
strategy run by the trader
**name**
**amount**
current position of the trader (number of assets that it owns)
**PnL**
current trader balance (number of money units that it owns)
**timeseries**
defines what data should be gathered for the trader
"""
def __init__(self,
orderBook,
strategy=None,
name=None,
amount=None,
PnL=None,
timeseries=None):
from marketsim.gen._out.strategy._empty import Empty_ as _strategy_Empty_
from marketsim import deref_opt
self.orderBook = orderBook
self.strategy = strategy if strategy is not None else deref_opt(
_strategy_Empty_())
self.name = name if name is not None else "-trader-"
self.amount = amount if amount is not None else 0.0
self.PnL = PnL if PnL is not None else 0.0
self.timeseries = timeseries if timeseries is not None else []
SingleAsset_Impl.__init__(self)
@property
def label(self):
return repr(self)
_properties = {
'orderBook': IOrderBook,
'strategy': ISingleAssetStrategy,
'name': str,
'amount': float,
'PnL': float,
'timeseries': listOf(ITimeSerie)
}
def __repr__(self):
return "%(name)s" % dict([(name, getattr(self, name))
for name in self._properties.iterkeys()])
def bind_ex(self, ctx):
if self.__dict__.get('_bound_ex', False): return
self.__dict__['_bound_ex'] = True
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
self.__dict__['_ctx_ex'] = ctx.updatedFrom(self)
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.bind_ex(self.__dict__['_ctx_ex'])
else:
v.bind_ex(self.__dict__['_ctx_ex'])
self.orderBook.bind_ex(self._ctx_ex)
self.strategy.bind_ex(self._ctx_ex)
for x in self.timeseries:
x.bind_ex(self._ctx_ex)
self.bind_impl(self.__dict__['_ctx_ex'])
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.bind_ex(self.__dict__['_ctx_ex'])
self.__dict__['_processing_ex'] = False
def reset_ex(self, generation):
if self.__dict__.get('_reset_generation_ex', -1) == generation: return
self.__dict__['_reset_generation_ex'] = generation
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.reset_ex(generation)
else:
v.reset_ex(generation)
self.orderBook.reset_ex(generation)
self.strategy.reset_ex(generation)
for x in self.timeseries:
x.reset_ex(generation)
self.reset()
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.reset_ex(generation)
self.__dict__['_processing_ex'] = False
def typecheck(self):
from marketsim.gen._out._isingleassetstrategy import ISingleAssetStrategy
from marketsim import listOf
from marketsim.gen._out._itimeserie import ITimeSerie
from marketsim import rtti
from marketsim.gen._out._iorderbook import IOrderBook
rtti.typecheck(IOrderBook, self.orderBook)
rtti.typecheck(ISingleAssetStrategy, self.strategy)
rtti.typecheck(str, self.name)
rtti.typecheck(float, self.amount)
rtti.typecheck(float, self.PnL)
rtti.typecheck(listOf(ITimeSerie), self.timeseries)
def registerIn(self, registry):
if self.__dict__.get('_id', False): return
self.__dict__['_id'] = True
if self.__dict__.get('_processing_ex', False):
raise Exception('cycle detected')
self.__dict__['_processing_ex'] = True
registry.insert(self)
self.orderBook.registerIn(registry)
self.strategy.registerIn(registry)
for x in self.timeseries:
x.registerIn(registry)
if hasattr(self, '_subscriptions'):
for s in self._subscriptions:
s.registerIn(registry)
if hasattr(self, '_internals'):
for t in self._internals:
v = getattr(self, t)
if type(v) in [list, set]:
for w in v:
w.registerIn(registry)
else:
v.registerIn(registry)
self.__dict__['_processing_ex'] = False
def bind_impl(self, ctx):
SingleAsset_Impl.bind_impl(self, ctx)
def reset(self):
SingleAsset_Impl.reset(self)
