-
Notifications
You must be signed in to change notification settings - Fork 2
/
DrawChart.py
200 lines (161 loc) · 6.37 KB
/
DrawChart.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
# k线图绘制描述当日最高价与当日最低价
# 开盘低于收盘时显示盈利红，开盘低于收盘时显示亏损绿
# 绘制方法
# 首先我们找到该日或某一周期的最高和最低价，垂直地连成一条直线
# 然后再找出当日或某一周期的开市和收市价，把这二个价位连接成一条狭长的长方柱体
# 假如当日或某一周期的收市价较开市价为高（即低开高收），我们便以红色来表示，或是在柱体上留白，这种柱体就称之为"阳线"
# 如果当日或某一周期的收市价较开市价为低（即高开低收），我们则以绿色表示，又或是在住柱上涂黑色，这柱体就是"阴线"
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from numpy import *
from matplotlib.dates import DateFormatter, DayLocator, num2date
from matplotlib.finance import candlestick_ohlc as candle1
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.path import Path
from CandlestickCharts.FetchStockData import StockInMongo
def candle_chart1(stock):
'draw candlestick chart'
fig = plt.figure(facecolor='black')
plt.style.use('dark_background')
# 获取子图对象
ex = fig.add_subplot(1, 1, 1)
# 绘制日k线图
candle1(ex, stock.ohlc_quotes(), width=1, colorup='r', colordown='g')
# 设置刻度格式%y-%m-%d,每次间隔15天
ex.xaxis.set_major_locator(DayLocator(bymonthday=range(1, 32), interval=15))
ex.xaxis.set_major_formatter(DateFormatter("%Y-%m-%d"))
# 获得股票开盘日期
dates = stock.get_dates()
ex.set_xlim(dates.min(), dates.max())
print("重复获取数据待处理")
# 设置刻度
for label in ex.xaxis.get_ticklabels():
label.set_rotation(45)
ex.set_ylabel("price")
ex.set_title(stock.get_stockname())
plt.grid(True)
plt.show()
def candle_with_MTM(code,width=0.5,timelength=6):
"""
:param stock: 股票代码
:param timeLength: 时间跨度
:return:
"""
fig = plt.figure(facecolor='black')
plt.style.use('dark_background')
ax = fig.add_subplot(2, 1, 1)
stockmongo=StockInMongo(code,timelength)
stocklist=stockmongo.get_stocklist()
for candle in stocklist:
date = candle['date']
open = candle['open']
high = candle['high']
low = candle['low']
close = candle['close']
verts = [(date - width, open),
(date - width, close),
(date + width, close),
(date + width, open),
(date - width, open)]
codes = [Path.MOVETO,
Path.LINETO,
Path.LINETO,
Path.LINETO,
Path.CLOSEPOLY]
path = Path(verts, codes)
if open<=close:
patch = patches.PathPatch(path, facecolor='r', edgecolor='r')
ax.plot([date, date], [low, high], color='r')
else:
patch = patches.PathPatch(path, facecolor='g', edgecolor='g')
ax.plot([date, date], [low, high], color='g')
ax.add_patch(patch)
# 格式化刻度信息 设置刻度格式%y-%m-%d,每次间隔30天
ax.xaxis.set_major_locator(DayLocator(bymonthday=range(1, 32), interval=30))
ax.xaxis.set_major_formatter(DateFormatter("%Y-%m-%d"))
for tick in ax.xaxis.get_major_ticks():
tick.label1.set_fontsize(10)
dates = stockmongo.get_dates()
lows = stockmongo.get_lows()
highs=stockmongo.get_highs()
ax.set_ylim(lows.min()-5, highs.max()+5)
ax.set_xlim(dates.min(), dates.max())
for label in ax.xaxis.get_ticklabels():
label.set_rotation(30)
ax.set_ylabel("price")
ax.set_title(code)
plt.grid(True)
ex=fig.add_subplot(2, 1, 2)
poordata=stockmongo.get_poorMtm()
pmtm=poordata['mtms']
dateMtm = poordata["dates"]
poorMtm = plt.plot(dateMtm, pmtm, color='b',label="poor-MTM")
plt.legend(loc=2)
# 设置为次坐标轴
ex2=ex.twinx()
dmtm=stockmongo.get_divisionMtm()['mtms']
divisionMtm=plt.plot(dateMtm,dmtm,color='g',label="division-MTM")
plt.legend(loc=1)
ex.xaxis.set_major_locator(DayLocator(bymonthday=range(1, 32), interval=30))
ex.xaxis.set_major_formatter(DateFormatter("%Y-%m-%d"))
for label in ex.xaxis.get_ticklabels():
label.set_rotation(30)
for tick in ex.xaxis.get_major_ticks():
tick.label1.set_fontsize(10)
ex.set_xlim(dates.min(), dates.max())
plt.grid(True)
plt.show()
def candle_chart2(stockdata, width):
"""
draw candlesticks by auto define function
candles: Candlestick type
width: width of rectangle
dates: Stock‘s dates
"""
candles = stockdata.transform_candles()
fig = plt.figure(facecolor='black')
plt.style.use('dark_background')
canvas = FigureCanvas(fig)
ax = fig.add_subplot(1, 1, 1)
print(len(candles))
for candle in candles:
mapdata = candle.get_kdata()
date = mapdata['date']
open = mapdata['open']
high = mapdata['high']
low = mapdata['low']
close = mapdata['close']
verts = [(date - width, open),
(date - width, close),
(date + width, close),
(date + width, open),
(date - width, open)]
codes = [Path.MOVETO,
Path.LINETO,
Path.LINETO,
Path.LINETO,
Path.CLOSEPOLY]
path = Path(verts, codes)
if candle.is_positive():
patch = patches.PathPatch(path, facecolor='r', edgecolor='r')
ax.plot([date, date], [low, high], color='r')
else:
patch = patches.PathPatch(path, facecolor='g', edgecolor='g')
ax.plot([date, date], [low, high], color='g')
ax.add_patch(patch)
# 格式化刻度信息 设置刻度格式%y-%m-%d,每次间隔30天
ax.xaxis.set_major_locator(DayLocator(bymonthday=range(1, 32), interval=30))
ax.xaxis.set_major_formatter(DateFormatter("%Y-%m-%d"))
dates = stockdata.get_dates()
lows = stockdata.get_lows()
ax.set_ylim(5, 20)
ax.set_xlim(dates.min(), dates.max())
print(type(dates))
# print("重复获取数据")
# 设置刻度样式
for label in ax.xaxis.get_ticklabels():
label.set_rotation(45)
ax.set_ylabel("price")
ax.set_title(stockdata.get_stockname())
plt.grid(True)
plt.show()