def ax_draw_sys_signal(axes, kdata, sys, style=2):
"""
"""
refdates = kdata.getDatetimeList()
date_index = dict([(d, i) for i, d in enumerate(refdates)])
ylim = axes.get_ylim()
height = ylim[1] - ylim[0]
if style == 1:
arrow_buy = dict(arrowstyle="->")
arrow_sell = arrow_buy
else:
arrow_buy = dict(facecolor='red', frac=0.5)
arrow_sell = dict(facecolor='blue', frac=0.5)
buy_request = sys.getBuyTradeRequest()
sell_request = sys.getSellTradeRequest()
text_request = ''
if buy_request.valid:
text_request = u'建议买入 止损： %.2f' % (buy_request.stoploss)
color = 'r'
if sell_request.valid:
text_request = u'建议卖出 来源: %s' % (getSystemPartName(sell_request.part))
color = 'b'
if buy_request.valid or sell_request.valid:
axes.text(0.99,
0.03,
text_request,
horizontalalignment='right',
verticalalignment='bottom',
transform=axes.transAxes,
color=color)
dates = sys.getTradeRecordList()
for d in dates:
if not date_index.has_key(d.datetime):
continue
pos = date_index[d.datetime]
krecord = kdata[pos]
if d.business == BUSINESS.BUY:
axes.annotate('SG', (pos, krecord.lowPrice - height * 0.01),
(pos, krecord.lowPrice - height * 0.1),
arrowprops=arrow_buy,
horizontalalignment='center',
verticalalignment='bottom',
color='red')
elif d.business == BUSINESS.SELL:
text = getSystemPartName(d.part)
axes.annotate(text, (pos, krecord.highPrice + height * 0.01),
(pos, krecord.highPrice + height * 0.1),
arrowprops=arrow_sell,
horizontalalignment='center',
verticalalignment='top',
color='blue')
else:
None
def TradeList_to_np(t_list):
"""转化为numpy结构数组"""
t_type = np.dtype({'names':['交易日期','证券代码', '证券名称', '业务名称',
'计划交易价格', '实际成交价格', '目标价格',
'成交数量', '佣金', '印花税', '过户费',
'其它成本', '交易总成本', '止损价',
'现金余额', '信号来源'],
'formats':['datetime64[D]','U10','U20', 'U10', 'd', 'd', 'd',
'i', 'd', 'd', 'd', 'd','d', 'd', 'd', 'U5']})
return np.array([(t.datetime, t.stock.market_code, t.stock.name,
getBusinessName(t.business), t.planPrice,
t.realPrice, t.goalPrice, t.number,
t.cost.commission, t.cost.stamptax,
t.cost.transferfee, t.cost.others,
t.cost.total, t.stoploss, t.cash,
getSystemPartName(t.part)
) for t in t_list], dtype=t_type)
def TradeList_to_np(t_list):
"""转化为numpy结构数组"""
t_type = np.dtype({'names':['交易日期','证券代码', '证券名称', '业务名称',
'计划交易价格', '实际成交价格', '目标价格',
'成交数量', '佣金', '印花税', '过户费',
'其它成本', '交易总成本', '止损价',
'现金余额', '信号来源'],
'formats':['datetime64[D]','U10','U20', 'U10', 'd', 'd', 'd',
'i', 'd', 'd', 'd', 'd','d', 'd', 'd', 'U5']})
return np.array([(t.datetime, t.stock.market_code, t.stock.name,
getBusinessName(t.business), t.planPrice,
t.realPrice, t.goalPrice, t.number,
t.cost.commission, t.cost.stamptax,
t.cost.transferfee, t.cost.others,
t.cost.total, t.stoploss, t.cash,
getSystemPartName(t.part)
) for t in t_list], dtype=t_type)