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127 lines
5.5 KiB
C++
127 lines
5.5 KiB
C++
#!/usr/bin/python
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# -*- coding: utf8 -*-
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# cp936
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#
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# The MIT License (MIT)
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#
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# Copyright (c) 2010-2017 fasiondog
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in all
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# copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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#===============================================================================
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# History:
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# 1. 20100224, Added by fasiondog
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#===============================================================================
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"""
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绘制亚历山大.艾尔德交易系统图形
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参见：《走进我的交易室》（2007年 地震出版社） Alexander Elder
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"""
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from pylab import plot
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from numpy import mean
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from hikyuu import QueryByIndex, constant
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from hikyuu.indicator import (Indicator, CLOSE, EMA, MACD,
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VIGOR, SAFTYLOSS, CVAL, PRICELIST)
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from hikyuu.interactive.drawplot import (create_figure,
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show_gcf,
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ax_draw_macd2,
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adjust_axes_show,
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ax_set_locator_formatter)
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def _find_ema_coefficient(closes, emas, number=66, percent=0.95):
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"""计算EMA通道系数。
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在《走进我的交易室》中，艾尔德介绍的价格通道为：
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通道上轨 ＝ EMA ＋ EMA＊通道系数
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通道下轨 ＝ EMA － EMA＊通道系数
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其中一条绘制得恰到好处的通道应能将绝大多数价格包含在内，一般调节通道系数使其能够包含95％的价格
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参数：closes：收盘价序列
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emas：收盘价对应的EMA序列
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number: 以最近多少天的数据来计算，即取最后N天的数据作为计算标准
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percent：通道包含多少的价格，如0.95表示通道将包含95%的价格
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"""
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assert len(closes)==len(emas), "数据长度不等"
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assert number>=1, "Number必须大于0"
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tmp_closes = closes[-number:]
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tmp_emas = emas[-number:]
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dev = [abs(tmp_closes[i]-tmp_emas[i]) for i in range(len(tmp_closes))]
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sortdev = sorted(dev)
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x = int(number*percent)
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x = x if len(dev)-1>x else len(dev)-1
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ix = dev.index(sortdev[x])
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return float(dev[ix])/tmp_emas[ix] if tmp_emas[ix] != 0.0 else 0.0
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def _draw_ema_pipe(axes, kdata, ema, n=22, w=0.10):
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emas = [i for i in ema]
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p = _find_ema_coefficient(list(CLOSE(kdata)), emas, number=66, percent=0.95) if w=='auto' else w
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emas_high = [i+i*p for i in emas]
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emas_low = [i-i*p for i in emas]
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emas_len = len(emas)
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PRICELIST(emas).plot(axes=axes, color='b', linestyle='-', label='%s(%s) %.2f'%(ema.name, n, emas[-1]))
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PRICELIST(emas_high).plot(axes=axes, color='b', linestyle=':', label='U%s(%.2f%%) %.2f'%(ema.name, p*100, emas_high[-1]))
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PRICELIST(emas_low).plot(axes=axes, color='b', linestyle=':', label='L%s(%.2f%%) %.2f'%(ema.name, p*100, emas_low[-1]))
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#axes.plot(emas, '-b', label='%s(%s) %.2f'%(ema.name, n, emas[-1]))
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#axes.plot(emas_high, ':b', label='U%s(%.2f%%) %.2f'%(ema.name, p*100, emas_high[-1]))
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#axes.plot(emas_low, ':b', label='L%s(%.2f%%) %.2f'%(ema.name, p*100, emas_low[-1]))
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fy1 = [ i for i in emas_low]
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fy2 = [ i for i in emas_high]
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axes.fill_between(range(emas_len),fy1,fy2,alpha=0.2, color='y' )
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def draw(stock, query=QueryByIndex(-130), ma_n=22, ma_w='auto', vigor_n=13):
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"""绘制亚历山大.艾尔德交易系统图形"""
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kdata = stock.getKData(query)
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close = CLOSE(kdata)
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ema = EMA(close, ma_n)
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sf = SAFTYLOSS(close, 10, 3, 2.0)
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vigor = VIGOR(kdata, vigor_n)
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ax1, ax2, ax3 = create_figure(3)
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kdata.plot(axes=ax1)
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_draw_ema_pipe(ax1,kdata, ema, n=ma_n, w=ma_w)
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sf.plot(axes=ax1, color='y', legend_on=True)
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#ax1.legend(loc='upper left')
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ax_draw_macd2(ax2, ema, kdata)
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vigor.plot(axes=ax3, marker='.', color='r', zero_on=True,
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legend_on=False, text_on=True)
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u = [i for i in vigor if i > 0 and i != constant.null_price]
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l = [i for i in vigor if i < 0]
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umean = mean(u)
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umax = max(u)
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lmean = mean(l)
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lmin = min(l)
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up = int(umax / umean)
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lp = int(lmin / lmean)
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for i in range(up):
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CVAL(umean * (i + 1), len(kdata)).plot(axes=ax3, color='r', linestyle='--')
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#ax3.hlines(umean * (i + 1),0,len(kdata),color='r',linestyle='--')
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for i in range(lp):
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CVAL(lmean * (i + 1), len(kdata)).plot(axes=ax3, color='g', linestyle='--')
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#ax3.hlines(lmean * (i + 1),0,len(kdata),color='g',linestyle='--')
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ax1.set_xlim((0, len(kdata)))
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ax_set_locator_formatter(ax1, kdata.getDatetimeList(), kdata.getQuery().kType)
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adjust_axes_show([ax1, ax2, ax3])
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return show_gcf()
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