def main():
# 株価の取得(銘柄コード, 開始日, 終了日)
code = 4783
data = get_stock(code, '2017-1-1', '2017-8-21')
# データフレームの作成
df = pd.DataFrame(
{
'始値': data[1],
'終値': data[2],
'高値': data[3],
'安値': data[4]
},
index=data[0])
# グラフにプロット
fig = plt.figure()
ax = plt.subplot()
mpf.candlestick2_ohlc(ax,
df['始値'],
df['高値'],
df['安値'],
df['終値'],
width=0.5,
colorup="g",
colordown="r")
ax.grid()
ax.legend()
fig.autofmt_xdate() #x軸のオートフォーマット
plt.show()
def DrawGraph4():
import matplotlib.finance as matfin
import matplotlib.ticker as ticker
fig = plt.figure(figsize=(12,8)) # Create Empty Object with specific size
ax = fig.add_subplot(1,1,1)
#matfin.candlestick2_ohlc(ax, df['Open'], df['High'], df['Low'], df['Close'], width=0.5, colorup='red', colordown='blue')
matfin.candlestick2_ohlc(ax, df_STDEV['OP'], df_STDEV['HI'], df_STDEV['LO'], df_STDEV['CL'], width=0.5, colorup='red', colordown='blue')
#day_list = []
#name_list = []
#for i, day in enumerate(df.index):
#for i, day in enumerate(df_STDEV['DATE']):
# if (day.day == 1): # 월요일마다 'day.dayofweek == 0'
# day_list.append(i)
# name_list.append(day.strftime('%m-%d')) # 요일은 (%a)
#ax.xaxis.set_major_locator(ticker.FixedLocator(day_list))
#ax.xaxis.set_major_formatter(ticker.FixedFormatter(name_list))
#plt.title(company_name)
#plt.xlabel('Time'); #plt.ylabel('Price')
xmin = df_STDEV.index.min() - datetime.timedelta(15)
xmax = df_STDEV.index.max() + datetime.timedelta(15)
#xmin = df.index.min() - datetime.timedelta(15)
#xmax = df.index.max() + datetime.timedelta(15)
#ymin = df['Close'].min(); ymax = df['Close'].max()
#plt.xlim((xmin,xmax)) # set ONLY X-axis range
#plt.ylim((ymin,ymax)) # set ONLY Y-axis range
#plt.axis([xmin,xmax,ymin,ymax]) # set Axes [xmin,xmax,ymin,ymax]
#plt.axis('equal') # set Axes [xmin,xmax,ymin,ymax]
plt.grid(True)
plt.show()
def main():
args = get_args()
data = read_data(args)
data = data[:].iloc[0:-1]
x = np.arange(len(data.index))
y = data['close'].values
trend_reversal_analysis(15,
data,
direction=-1,
change_ratio_margins=np.concatenate([
np.linspace(0.0005, 0.005, 10),
np.linspace(0.006, 0.035, 9)
]),
max_reversal_margins=np.linspace(0.1, 1., 10),
show_as_percentage=True)
# validate_ohlc(data['open'], data['high'], data['low'], data['close'], data)
if False:
fig, ax = plt.subplots()
candlestick2_ohlc(ax,
data['open'],
data['high'],
data['low'],
data['close'],
width=0.6)
show()
validate_ohlc(data['open'], data['high'], data['low'], data['close'], data)
fig = FF.create_candlestick(data['open'],
data['high'],
data['high'] * 0.,
data['close'],
dates=data.index)
def plot_ohlcv(self, df):
fig, ax = plt.subplots()
# Plot the candlestick
candlestick2_ohlc(ax, df['open'], df['high'], df['low'], df['close'],
width=1, colorup='g', colordown='r', alpha=0.5)
# shift y-limits of the candlestick plot so that there is space
# at the bottom for the volume bar chart
pad = 0.25
yl = ax.get_ylim()
ax.set_ylim(yl[0] - (yl[1] - yl[0]) * pad, yl[1])
# Add a seconds axis for the volume overlay
ax2 = ax.twinx()
ax2.set_position(
matplotlib.transforms.Bbox([[0.125, 0.1], [0.9, 0.26]]))
# Plot the volume overlay
# bc = volume_overlay(ax2, df['open'], df['close'], df['volume'],
# colorup='g', alpha=0.5, width=1)
ax.xaxis.set_major_locator(ticker.MaxNLocator(6))
def mydate(x, pos):
try:
return df.index[int(x)]
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
plt.margins(0)
plt.show()
def his100chart(company):
company = company.lower()
df100 = history100day(company)
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick2_ohlc
#show 20 day moving averages
print("Last 100-day trade history chart")
df100["HMean"] = df100["High"].rolling(20).mean()
df100["LMean"] = df100["Low"].rolling(20).mean()
df100.reset_index(inplace=True)
fig, ax = plt.subplots()
plt.xticks(rotation=45)
plt.xlabel("Last 100 days")
plt.ylabel("USD Price")
plt.title(company + "/USD : High and Low 20 day moving averages")
candlestick2_ohlc(ax,
df100["Open"],
df100["High"],
df100["Low"],
df100["Close"],
width=1,
colorup='g')
df100.HMean.plot(ax=ax)
df100.LMean.plot(ax=ax)
plt.show()
def graphData(self, quotes):
"""Works in
http://localhost:8888/notebooks/Jupyter/OHLC%20Graphs.ipynb
end"""
# Fix the no graphics backend issue
mpl.use('TkAgg')
fig, ax = plt.subplots()
candlestick2_ohlc(
ax, quotes['Open'], quotes['High'], quotes['Low'], quotes['Close'], width=0.6)
xdate = [datetime.datetime.fromtimestamp(i) for i in quotes['Date']]
ax.xaxis.set_major_locator(ticker.MaxNLocator(6))
def mydate(x, pos):
try:
return xdate[int(x)]
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
fig.autofmt_xdate()
fig.tight_layout()
plt.show()
return
def kline(ax=None,
code=None,
data=None,
start=None,
end=None,
ktype='D',
num=DATE_NUM,
figsize=FIG_SIZE,
width=1,
colorup='w',
colordown='k',
alpha=0.5):
ax, data = _init(code,
ax=ax,
start=start,
end=end,
ktype=ktype,
data=data,
figsize=figsize)
candlestick2_ohlc(ax, data.open, data.high, data.low, data.close, width,
colorup, colordown, alpha)
# init_xtick_date(ax, data, num)
return data
def DrawGraph4():
import matplotlib.finance as matfin
import matplotlib.ticker as ticker
fig = plt.figure(figsize=(12,8)) # Create Empty Object with specific size
ax = fig.add_subplot(1,1,1)
#matfin.candlestick2_ohlc(ax, DF_stock["Open"], DF_stock["High"], DF_stock["Low"], DF_stock["Close"], width=0.5, colorup="red", colordown="blue")
matfin.candlestick2_ohlc(ax, df_STDEV["OP"], df_STDEV["HI"], df_STDEV["LO"], df_STDEV["CL"], width=0.5, colorup="red", colordown="blue")
#day_list = []
#name_list = []
#for i, day in enumerate(DF_stock.index):
#for i, day in enumerate(df_STDEV["DATE"]):
# if (day.day == 1): # 월요일마다 "day.dayofweek == 0"
# day_list.append(i)
# name_list.append(day.strftime("%m-%d")) # 요일은 (%a)
#ax.xaxis.set_major_locator(ticker.FixedLocator(day_list))
#ax.xaxis.set_major_formatter(ticker.FixedFormatter(name_list))
#plt.title(company_name)
#plt.xlabel("Time"); #plt.ylabel("Price")
xmin = df_STDEV.index.min() - datetime.timedelta(15)
xmax = df_STDEV.index.max() + datetime.timedelta(15)
#xmin = DF_stock.index.min() - datetime.timedelta(15)
#xmax = DF_stock.index.max() + datetime.timedelta(15)
#ymin = DF_stock["Close"].min(); ymax = DF_stock["Close"].max()
#plt.xlim((xmin,xmax)) # set ONLY X-axis range
#plt.ylim((ymin,ymax)) # set ONLY Y-axis range
#plt.axis([xmin,xmax,ymin,ymax]) # set Axes [xmin,xmax,ymin,ymax]
#plt.axis("equal") # set Axes [xmin,xmax,ymin,ymax]
plt.grid(True)
plt.show()
def plot_curr_time(curr_time, quotes, slices=40):
if quotes is None:
return
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
candlestick2_ohlc(ax1,
quotes['open'],
quotes['high'],
quotes['low'],
quotes['close'],
width=0.6)
vol_prof = construct_vol_profile(curr_time, quotes, slices=40)
prices = [x[0] for x in vol_prof]
vols = [x[1] for x in vol_prof]
oldMin = min(vols)
oldMax = 5000000
newMin = 0
newMax = 90
vol_scale = [
(((x - oldMin) * (newMax - newMin)) / (oldMax - oldMin)) + newMin
for x in vols
]
t = np.arange(slices)
ax2.barh(t, vol_scale, alpha=0.5)
ax1.get_yaxis().set_visible(False)
ax2.get_yaxis().set_visible(False)
ax1.get_xaxis().set_visible(False)
ax2.get_xaxis().set_visible(False)
fig.savefig('./images/' + str(curr_time) + '.png', bbox_inches='tight')
plt.close(fig)
return
def root():
upbit = Upbit()
frame = upbit.get_candles('BTC', 'days')
fig = plt.figure(figsize=(20, 16))
ax1 = fig.add_subplot(212)
ax2 = fig.add_subplot(212)
ax1 = plt.subplot2grid((4, 4), (0, 0), rowspan=3, colspan=4)
ax2 = plt.subplot2grid(
(4, 4), (3, 0), rowspan=1, colspan=4
) # ax = fig.add_subplot(111) # ax.xaxis.set_major_formatter(ticker.FixedLocator(time_list))
#frame['MA20'] = frame['tradePrice'].rolling(window=20).mean()
#frame['MA60'] = frame['tradePrice'].rolling(window=60).mean()
print(frame)
matfin.candlestick2_ohlc(ax1,
frame['openingPrice'],
frame['highPrice'],
frame['lowPrice'],
frame['tradePrice'],
width=0.5,
colorup='r',
colordown='b')
#ax1.plot(frame['MA20'], label='MA20')
#ax1.plot(frame['MA60'], label='MA60')
ax2.plot(frame['candleAccTradeVolume'])
canvas = FigureCanvas(fig)
png_output = BytesIO()
canvas.print_png(png_output)
response = make_response(png_output.getvalue())
response.headers['Content-Type'] = 'image/png'
return response
def plotCandles(o, h, l, c, ema8, ema13, ema21, ema55, pair, ax1):
# MAIN FRAME.
# =============================================================
# - CANDLESTICK SUB-PLOT.
# =============================================================
ax1.clear();
ax1.set_title(pair)
ax1.set_facecolor('black')
candlestick2_ohlc(ax1, o, h, l, c, width=0.6, colorup='g', colordown='r')
ax1.plot(ema8, linewidth=1, color='cyan');
ax1.plot(ema13, linewidth=1, color='purple');
ax1.plot(ema21, linewidth=1, color='orange');
ax1.plot(ema55, linewidth=1, color='yellow');
lastclose = c[len(c) - 1];
lastopen = o[len(o) - 1];
if(lastclose > lastopen):
ax1.axhline(y=lastclose, color='g', linestyle='--')
elif(lastclose < lastopen):
ax1.axhline(y=lastclose, color='r', linestyle='--')
else:
ax1.axhline(y=lastclose, color='b', linestyle='--')
plt.gcf();
def check_db_data(cls,
code,
start_date,
end_date,
table,
db='server_db',
dbname='big-data',
db2='server_db',
dbname2='big-data',
path='f://zjf//check_data//'):
if table == None: raise Exception("table can't be empty")
data = KlineData(location=db,
dbname=dbname).read_data(code=code,
start_date=start_date,
end_date=end_date,
kline=table,
timemerge=True)
data = data.sort_values(by=['date'], ascending=True)
data2 = KlineData(location=db2,
dbname=dbname2).read_data(code=code,
start_date=start_date,
end_date=end_date,
kline=table,
timemerge=True)
data2 = data2.sort_values(by=['date'], ascending=True)
print('start draw.......')
# fig, ax = plt.subplots()
# fig.subplots_adjust(bottom=0.2)
ax = plt.subplot(211)
# plt.title('本地')
ax.set_xticks([])
candlestick2_ohlc(ax,
data.open,
data.high,
data.low,
data.close,
width=1,
colorup='red',
colordown='green')
plt.title(db + '--' + table + '--' + code)
ax = plt.subplot(212)
# plt.title('远程')
plt.title(db2 + '--' + table + '--' + code)
candlestick2_ohlc(ax,
data2.open,
data2.high,
data2.low,
data2.close,
width=1,
colorup='red',
colordown='green')
# plt.show()
File.check_file(path=path)
ax.set_xticks([])
plt.savefig(path + table + '.png', transparent=True)
plt.close()
def main():
#start = datetime.datetime(2016, 3, 1)
#end = datetime.datetime(2016, 3, 31)
#skhynix = web.DataReader("078930.KS", "yahoo", start, end)
stockInfo = StockReader.getStockItem("026260").tail(30)
stockInfo['MA5'] = stockInfo['Adj Close'].rolling(window=5).mean()
stockInfo['MA20'] = stockInfo['Adj Close'].rolling(window=20).mean()
stockInfo['MA60'] = stockInfo['Adj Close'].rolling(window=60).mean()
stockInfo['MA120'] = stockInfo['Adj Close'].rolling(window=120).mean()
#print(stockInfo)
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(311)
day_list = []
name_list = []
for i, day in enumerate(stockInfo.index):
#if day.dayofweek == 0:
day_list.append(i)
name_list.append(day.strftime('%d'))
#name_list.append(day.strftime('%Y-%m-%d') + '(Mon)')
#else:
# print(day.weekday())
print(day_list)
print(name_list)
ax.text(.5, .9, 'centered title',
horizontalalignment='center',
transform=ax.transAxes)
ax.xaxis.set_major_locator(ticker.FixedLocator(day_list))
ax.xaxis.set_major_formatter(ticker.FixedFormatter(name_list))
matfin.candlestick2_ohlc(ax, stockInfo['Open'], stockInfo['High'], stockInfo['Low'], stockInfo['Close'], width=0.5,
colorup='r', colordown='b')
plt.grid()
print(stockInfo['Volume'])
ax = fig.add_subplot(312)
ax.bar(stockInfo['Volume'].index, stockInfo['Volume'], width=0.8)
plt.grid()
plt.figure(1)
plt.subplot(313)
plt.plot(stockInfo.index, stockInfo['MA5'], label="MA5")
plt.plot(stockInfo.index, stockInfo['MA20'], label="MA20")
plt.plot(stockInfo.index, stockInfo['MA60'], label="MA60")
#plt.plot(stockInfo.index, stockInfo['MA120'], label="MA120")
plt.legend(loc='best')
plt.grid()
plt.show()
def plotKWithNoGap(ohlcDF, figureSize=(30,8), tickWin=5):
from matplotlib.finance import candlestick2_ohlc
fig, ax = plt.subplots(figsize=figureSize)
candlestick2_ohlc(ax, ohlcDF['OPEN'], ohlcDF['HIGH'], ohlcDF['LOW'], ohlcDF['CLOSE'], width=0.7, colorup='g', colordown='r')
ax.xaxis.set_ticks(np.arange(0, len(ohlcDF), tickWin))
ax.xaxis.set_major_formatter(MyFormatter(ohlcDF.index))
ax.set_xlim(-1, len(ohlcDF))
fig.autofmt_xdate() # 自动调整x轴日期显示效果
plt.grid(True)
plt.show()
def plot_tech_indicators(Open, high, Low, Close, tech_data, indicators):
fig,ax = plt.subplots()
candlestick2_ohlc(ax, Open, High, Low, Close, width=0.6)
#create a general color scheme
colors = ['r','g','b','y','v']
col = 0
for indicator in indicators:
plt.plot(list(tech_data[indicator]), colors[col])
col += 1
#add legend
plt.show()
def check(cls, code, start_date, end_date):
table = 'kline_min5'
table2 = 'tmp_kline_min5'
path = 'f:/zjf/data/check6/'
data = KlineData.read_data(code=code,
start_date=start_date,
end_date=end_date,
kline=table,
timemerge=True)
if len(data) <= 0:
return
data = data.sort_values(by=['date'], ascending=True)
data = data[data.time <= 955]
data2 = KlineData.read_data(code=code,
start_date=start_date,
end_date=end_date,
kline=table2,
timemerge=True)
if len(data2) <= 0:
return
data2 = data2.sort_values(by=['date'], ascending=True)
data2 = data2[data2.time <= 955]
print('start draw.......')
# fig, ax = plt.subplots()
# fig.subplots_adjust(bottom=0.2)
ax = plt.subplot(211)
# plt.title('本地')
ax.set_xticks([])
candlestick2_ohlc(ax,
data.open,
data.high,
data.low,
data.close,
width=1,
colorup='red',
colordown='green')
plt.title(table + '--' + code)
ax = plt.subplot(212)
# plt.title('远程')
plt.title(table2 + '--' + code)
candlestick2_ohlc(ax,
data2.open,
data2.high,
data2.low,
data2.close,
width=1,
colorup='red',
colordown='green')
File.check_file(path=path)
ax.set_xticks([])
plt.savefig(path + code + '.png', transparent=True)
plt.close()
def plot_graph(self, stockName):
df = pd.read_csv(stockName)
fig, ax = plt.subplots()
try:
candlestick2_ohlc(ax, df['open'], df['high'], df['low'], df['close'], width=0.9)
plt.xlabel('Date')
plt.ylabel('Price')
print("Plotting -> {}".format(stockName))
stock_plot = stockName.split('.csv')[0].split('/')[1]
plt.title("Stock Graph For {}".format(stock_plot))
plt.savefig('Visualizations/candlestick_{}.png'.format(stock_plot))
except:
print("Error -> {}".format(stockName))
def candlestick(self, start_date=None, end_date=None, figsize=None):
self._make_sure_has_run()
temp = self._df.loc[start_date:end_date]
fig, ax = plt.subplots(figsize=figsize)
ax.set_title(self.__str__(), size=13)
xdates = [i.strftime("%Y-%m-%d") for i in temp.index]
steps = int(math.ceil(len(temp)/62.0))
ax.set_xticks(np.arange(len(temp), step = steps))
ax.set_xticklabels(xdates[::steps], rotation=90)
candlestick2_ohlc(ax,temp['ha_open'],temp['ha_high'],temp['ha_low'],temp['ha_last'],width=0.6, colorup='#77d879', colordown='#db3f3f')
def plot(data, name):
n = len(data['close'])
fig, ax = plt.subplots(3, sharex=True)
candlestick2_ohlc(ax[0],
data['open'],
data['high'],
data['low'],
data['close'],
width=0.6)
ax[1].plot(data['btc_equ'])
ax[2].plot(data['average_gains'])
ax[0].set_title(name)
plt.show()
def showSignalPoint(self):
dfSignal = pd.read_csv(self.path + 'MinEquity.csv')
dfSignal.columns = [
'dt', 'equity', 'open', 'high', 'low', 'close', 'volume',
'openInt', 'dire', 'sprice', 'svolume'
]
temcolum = np.arange(dfSignal.index.size)
dfSignal['num'] = temcolum
longsignal = dfSignal[dfSignal.loc[:, 'dire'] > 0]
longx = longsignal['num']
longy = longsignal.loc[:, 'sprice']
shortsignal = dfSignal[dfSignal.loc[:, 'dire'] < 0]
shortx = shortsignal['num']
shorty = shortsignal.loc[:, 'sprice']
#
fig1 = plt.figure('signal draw')
ax1 = plt.subplot(111)
# plt.xaxis_date()
plt.xticks(rotation=45)
mf.candlestick2_ohlc(plt.axes(),
dfSignal.loc[:, 'open'],
dfSignal.loc[:, 'high'],
dfSignal.loc[:, 'low'],
dfSignal.loc[:, 'close'],
width=0.75,
colorup=u'r',
colordown=u'g',
alpha=1)
for i in range(dfSignal.shape[1] - 12):
plt.plot(dfSignal.index,
dfSignal.iloc[:, i + 9],
'.-',
label=dfSignal.columns[i + 9])
plt.scatter(longx, longy, s=160, c='m', marker='^', label='long')
plt.scatter(shortx, shorty, s=160, c='k', marker='v', label='short')
ax2 = ax1.twinx()
ax2.plot(dfSignal.loc[:, 'equity'], c='r')
plt.legend()
plt.grid()
plt.tight_layout()
plt.savefig(self.path + 'Signal.png')
plt.show()
fig1.clear()
plt.close()
def plot_candlestick1(data, ax=None, title_label=None):
'''
matplotlib implementation.
'''
if ax is None:
fig, ax = plt.subplots(1, 1, figsize=(16, 8))
candlestick2_ohlc(ax,
data['open'],
data['high'],
data['low'],
data['close'],
width=1)
return
def candlestick():
class Data:
def __init__(self, index, start, date):
self.index = index
self.start = start
self.date = date
def get(self):
return web.DataReader(self.index, 'google', self.start, self.date)
class rol_mean_plot:
def __init__(self, data, window):
self.data = data
self.window = window
def rol_mean(self):
return self.data.rolling(window=self.window).mean().plot(
subplots=False, grid=True, figsize=(8, 6))
def plot(y, window):
rol_mean_plot.rol_mean(rol_mean_plot(y, window))
index = input('\nEnter the Index:\n\n>>> ')
start = input('Enter the initial date [YYYY, MM, DD]:\n\n>>> ')
dt = start.split(',')
start = datetime.datetime(int(dt[0]), int(dt[1]), int(dt[2]))
end = input('Enter the end date [YYYY, MM, DD]:\n\n>>> ')
st = end.split(',')
end = datetime.datetime(int(st[0]), int(st[1]), int(st[2]))
# dateRange = pd.date_range(start, end, freq='D')
quotes = Data.get(Data(index, start, end))
fig, ax = plt.subplots(figsize=(8, 6))
candlestick2_ohlc(ax,
quotes['Open'],
quotes['High'],
quotes['Low'],
quotes['Close'],
width=0.6)
plt.xticks(rotation=45)
plt.title('Stock Index {}'.format(index))
plt.xlabel('Days in period [{} - {}]'.format(start, end))
plt.ylabel('{} Price'.format(index))
plt.show()
def plot(data, columnNames=None, timeColumnName=None,
majorLocatorStep=20, majorOffset=0, minorLocatorStep=5, minorOffset=0,
displayMinor=False, timeFormat='%Y-%m-%d', rotation=45,
stickWidth=0.6, alpha=1):
'''
根据所给的数据，画出蜡烛图
@param:
data: 原始数据，要求为pandas.DataFrame的形式，默认的有open, close, high
low这四列，反之需要通过columnNames参数提供，依次的顺序为openName,
closeName, highName, lowName,若要画出时间轴，则需要数据中有date列，
否则则需要通过使用的时候通过timeFormat来提供
columnNames: 默认data中有open, close, high, low这些列，反之则需要自行提供
timeColumnName: 当需要画以时间为横轴的图时，需要提供时间列的列名
majorLocatorStep: 主刻度间隔，默认为间隔20个数据
minorLocatorStep: 副刻度间隔，默认为间隔5个数据
displayMinor: 是否在副刻度上也标明时间或者顺序下标，默认不标明
majorFormat: 解析时间列主刻度的方法，需按照datetime中的形式解析，默认为%Y-%m-%d
minorFormat: 解析时间列副刻度的方法，需按照datetime中的形式解析，默认为%Y-%m-%d
rotation: 横轴值旋转度数，默认旋转45度
stickWidth: 蜡烛图的宽度，默认为0.6
alpha: 蜡烛图颜色的深度，默认为1
'''
plt.style.use('seaborn-ticks')
fig, ax = plt.subplots()
if not columnNames is None:
openName, closeNames, highName, lowName = columnNames
else:
openName, closeNames, highName, lowName = ('open', 'close', 'high', 'low')
opens, closes, highs, lows = data[openName].tolist(), data[closeNames].tolist(), data[
highName].tolist(), data[lowName].tolist()
fig.subplots_adjust(bottom=0.2)
majorLocator = ticker.IndexLocator(majorLocatorStep, majorOffset)
ax.xaxis.set_major_locator(majorLocator)
minorLocator = ticker.IndexLocator(minorLocatorStep, minorOffset)
ax.xaxis.set_minor_locator(minorLocator)
if not timeColumnName is None:
times = data[timeColumnName].tolist()
time_formatterSetting(ax, times, majorLocatorStep, majorOffset, timeFormat,
displayMinor, minorLocatorStep, minorOffset)
finance.candlestick2_ohlc(ax, opens, highs, lows, closes, width=stickWidth,
colorup='r', colordown='g', alpha=alpha)
plt.setp(ax.get_xticklabels(), rotation=rotation)
if displayMinor:
plt.setp(ax.xaxis.get_minorticklabels(), rotation=rotation)
xmin, xmax = plt.xlim()
plt.xlim(xmin=xmin-1)
plt.grid(True)
plt.show()
def plot_p(df):
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick2_ohlc
fig, ax = plt.subplots()
candlestick2_ohlc(ax,
df['price_open'].values,
df['price_high'].values,
df['price_low'].values,
df['price_close'].values,
width=0.6,
colorup='g',
colordown='r',
alpha=1)
plt.show()
print('Done.')
def save_to_file(df, filename):
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick2_ohlc
fig, ax = plt.subplots()
candlestick2_ohlc(ax,
df['price_open'].values,
df['price_high'].values,
df['price_low'].values,
df['price_close'].values,
width=0.6,
colorup='g',
colordown='r',
alpha=1)
plt.savefig(filename)
plt.close(fig)
def DrawCandleChart(self):
count = self.CommTR.dynamicCall("GetMultiRowCount()")
value = {}
rowvalue = []
for i in range(0, 6):
for j in range(0, count):
x = self.CommTR.dynamicCall("GetMultiData(int, QString)", j, i)
rowvalue.append(x)
value[i] = rowvalue
rowvalue = []
value[0] = pd.to_datetime(value[0])
daeshin = {
'open': value[2],
'high': value[3],
'low': value[4],
'close': value[5]
}
daeshin_day = DataFrame(daeshin,
columns=['open', 'high', 'low', 'close'],
index=value[0])
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111)
namelist = []
daylist = []
#for day in daeshin_day.index:
# namelist.append(day.strftime('%d'))
#daylist = range(len(daeshin_day))
for i, day in enumerate(daeshin_day.index):
if day.dayofweek == 0:
daylist.append(i)
namelist.append(day.strftime('%m/%d(Mon)'))
ax.xaxis.set_major_locator(ticker.FixedLocator(daylist))
ax.xaxis.set_major_formatter(ticker.FixedFormatter(namelist))
matfin.candlestick2_ohlc(ax,
daeshin_day['open'],
daeshin_day['high'],
daeshin_day['low'],
daeshin_day['close'],
width=0.5,
colorup='r',
colordown='b')
plt.grid()
plt.show()
def plot_security_k(ax,_dfquotes,begin,_locatormulti=40):
"""
plot k graph with ma5,10,20,30 line
Args:
_dfquotes (dataframe): the seurity dataframe which include'openPrice''closePrice''highestPrice''lowestPrice''tradeDate'
ax : matplotlib ax object
begin : the index of first k bar, _dfquotes[begin:] will be plot
_locatormulti (int): adjust the axis's ticker display interval
Returns:
lineandbars : return candlestick2_ohlc's lineandbars objects
Examples:
>>
"""
global _tickerstart
global dfquotes
dfquotes = _dfquotes
_tickerstart = begin
lineandbars = maf.candlestick2_ohlc(ax,dfquotes[u'openPrice'][_tickerstart:].values,\
dfquotes[u'highestPrice'][_tickerstart:].values,\
dfquotes[u'lowestPrice'][_tickerstart:].values,\
dfquotes[u'closePrice'][_tickerstart:].values,\
colorup='r',colordown='g',width=0.5,alpha=1.0)
#adjust the k graph's color
lineandbars[1].set_edgecolor(lineandbars[1].get_facecolor())
lineandbars[0].set_color(lineandbars[1].get_facecolor())
_multilocator = int((len(dfquotes)-_tickerstart)/_locatormulti)#超过40个交易日，日期刻度单位加一天
ax.xaxis.set_major_locator(MultipleLocator(1+_multilocator))
ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
plt.gcf().autofmt_xdate()
plotEMA([5,10,20,30],dfquotes[u'closePrice'].values,_tickerstart)
for label in ax.xaxis.get_ticklabels():
label.set_rotation(90)
return lineandbars
def plot_with_price(quotes, save_to_file=None, min_max=[]):
# fig = plt.figure()
fig, ax = plt.subplots(figsize=(30, 15))
# ax.set_xlim([1,2])
# ax.set_ylim(min_max)
candlestick2_ohlc(ax,
quotes['open'],
quotes['high'],
quotes['low'],
quotes['close'],
width=0.6)
xdate = [i for i in quotes.index]
ax.xaxis.set_major_locator(ticker.MaxNLocator(6))
def mydate(x, pos):
try:
return xdate[int(x)]
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
ax2 = ax.twinx()
# ax2.set_ylim([0,5000])
# Plot the volume overlay
bc = volume_overlay(ax2,
quotes['open'],
quotes['close'],
quotes['volume'],
colorup='g',
alpha=0.1,
width=1)
ax2.add_collection(bc)
fig.autofmt_xdate()
fig.tight_layout()
# plt.show()
if (save_to_file is not None):
plt.savefig(save_to_file)
def stock_week_tech_analysis(code):
print("stock techinical analysis start to parse the stock on week level" +
str(code))
dff = ts.get_hist_data(code, start='2016-01-04', ktype='W')
df = dff[::-1]
df
macd, macdsignal, macdhist = ta.MACD(np.array(df['close']),
fastperiod=12,
slowperiod=26,
signalperiod=9)
ma5 = ta.MA(np.array(df['close']), 5, matype=0)
ma10 = ta.MA(np.array(df['close']), 10, matype=0)
ma20 = ta.MA(np.array(df['close']), 20, matype=0)
# ma20 = ta.MA(np.array(df['close'],20,mtype=0)
print("the close[-1] is " + str(df['close'][-1]) + " and the ma5[-1] is " +
str(ma5[-1]) + "and the ma20[-1] is " + str(ma20[-1]))
if ma5[-1] > ma20[-1]:
if df['close'][-1] > ma5[-1]:
print(" the stock " + str(code) + " is bull! ")
if ma5[-1] < ma20[-1]:
if df['close'][-1] < ma5[-1]:
print(" the stock " + str(code) + " is bear! ")
fig = plt.figure()
fig.subplots_adjust(bottom=0.1)
fig.subplots_adjust(hspace=0)
gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1])
ax0 = plt.subplot(gs[0])
candles = candlestick2_ohlc(ax0,
np.array(df['open']),
df['high'],
df['low'],
df['close'],
width=1,
colorup='r',
colordown='g')
ax0.plot(
ma5,
color='black',
lw=2,
)
ax0.plot(ma20, color='yellow', lw=2)
ax0.plot(ma10, color='green', lw=2)
# trying to plot the trending line of the stock
maxidx = df['close'].idxmax(axis=1)
minidx = df['close'].idxmin(axis=1)
# dmax = time.strptime(maxidx,"%Y-%m-%d") ;
# dmin = time.strptime(minidx,"%Y-%m-%d") ;
if maxidx > minidx:
maxidx2 = df['close'][:minidx].idxmax(axis=1)
minidx2 = df['close'][maxidx:].idxmin(axis=1)
else:
maxidx2 = df['close'][minidx:].idxmax(axis=1)
minidx2 = df['close'][:maxidx].idxmin(axis=1)
ax0.plot([df['close'][:maxidx].count(), df['close'][:maxidx2].count()],
[df['close'][maxidx], df['close'][maxidx2]])
ax0.plot([df['close'][:minidx].count(), df['close'][:minidx2].count()],
[df['close'][minidx], df['close'][minidx2]])
# ax0.plot(minidx,df['close'][minidx],minidx2,df['close'][minidx2]) ;
plt.show()
def main():
# 株価の取得(銘柄コード, 開始日, 終了日)
code = 3906
today = datetime.date.today()
print(today)
todaystr = today.strftime('%Y-%m-%d')
data = get_stock(code, '2017-6-1', todaystr)
print(todaystr)
print("^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^")
# データフレームの作成
df = pd.DataFrame(
{
'始値': data[1],
'終値': data[2],
'高値': data[3],
'安値': data[4]
},
index=data[0])
print(df)
# グラフにプロット
fig = plt.figure()
ax = plt.subplot()
mpf.candlestick2_ohlc(ax,
df['始値'],
df['高値'],
df['安値'],
df['終値'],
width=0.5,
colorup="g",
colordown="r")
ax.set_xticklabels(
[(df.index[int(x)].strftime("%Y/%M/%D") if x <= df.shape[0] else x)
for x in ax.get_xticks()],
rotation=90)
ax.set_xlim([0, df.shape[0]]) # 横軸の範囲はデータの個数(df.shape[0]個)までに変更しておく
ax.grid()
ax.legend()
fig.autofmt_xdate() #x軸のオートフォーマット
plt.show()
def plotKWithNoGap(ohlcDF, figureSize=(30, 8), tickWin=5):
from matplotlib.finance import candlestick2_ohlc
fig, ax = plt.subplots(figsize=figureSize)
candlestick2_ohlc(ax,
ohlcDF['OPEN'],
ohlcDF['HIGH'],
ohlcDF['LOW'],
ohlcDF['CLOSE'],
width=0.7,
colorup='g',
colordown='r')
ax.xaxis.set_ticks(np.arange(0, len(ohlcDF), tickWin))
ax.xaxis.set_major_formatter(MyFormatter(ohlcDF.index))
ax.set_xlim(-1, len(ohlcDF))
fig.autofmt_xdate() # 自动调整x轴日期显示效果
plt.grid(True)
plt.show()
def candle(conn, size):
cur = conn.cursor()
cur.execute("""SELECT open FROM """ + env.sname + """ ORDER BY id DESC""")
open = np.array(cur.fetchall())[:, 0]
cur.execute("""SELECT high FROM """ + env.sname + """ ORDER BY id DESC""")
high = np.array(cur.fetchall())[:, 0]
cur.execute("""SELECT low FROM """ + env.sname + """ ORDER BY id DESC""")
low = np.array(cur.fetchall())[:, 0]
cur.execute("""SELECT close FROM """ + env.sname + """ ORDER BY id DESC""")
close = np.array(cur.fetchall())[:, 0]
cur.execute("""SELECT date FROM """ + env.sname + """ ORDER BY id DESC""")
date = np.array(cur.fetchall())[:, 0]
cur.execute("""SELECT volume FROM """ + env.sname +
""" ORDER BY id DESC""")
volume = np.array(cur.fetchall())[:, 0]
day_list = []
name_list = []
for i, day in enumerate(date[len(date) - size:]):
if day.weekday() == 0:
day_list.append(i)
name_list.append(day.strftime('%m/%d'))
fig = plt.figure(figsize=(24, 16))
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(ticker.FixedLocator(day_list))
ax.xaxis.set_major_formatter(ticker.FixedFormatter(name_list))
matfin.candlestick2_ohlc(ax,
np.ndarray.tolist(open[len(date) - size:]),
np.ndarray.tolist(high[len(date) - size:]),
np.ndarray.tolist(low[len(date) - size:]),
np.ndarray.tolist(close[len(date) - size:]),
width=0.5,
colorup='r',
colordown='b')
plt.title(env.sname + ' ' + str(size) + ' Days')
plt.show()
plt.gcf().clear()
cur.execute("""SELECT * FROM """ + env.sname + """ ORDER BY id DESC""")
all = np.array(cur.fetchall())[:, :]
return all
def display_candlestick(ohlc, candle_width=0.8, width=20, height=10):
plt.figure(figsize=(width, height), dpi=80)
ax = plt.subplot()
return mpf.candlestick2_ohlc(
ax,
ohlc['Open'], ohlc['High'], ohlc['Low'], ohlc['Close'],
width=candle_width,
colorup='blue', colordown='red',
)
def get_plot_candlesticks_dataframe(data_frame, ax):
candlestick2_ohlc(ax,
data_frame[PriceStrings.STR_PRICE_OPEN.value],
data_frame[PriceStrings.STR_PRICE_HIGH.value],
data_frame[PriceStrings.STR_PRICE_LOW.value],
data_frame[PriceStrings.STR_PRICE_CLOSE.value],
width=0.8,
colorup='#008000',
colordown='#FF0000',
alpha=1)
# xdate = [datetime.datetime.fromtimestamp(i) for i in dataframe[PriceStrings.STR_PRICE_TIME.value]]
xdate = data_frame[PriceStrings.STR_PRICE_TIME.value].values
ax.xaxis.set_major_locator(ticker.MaxNLocator(6))
def get_date(x, pos):
try:
return xdate[int(x)]
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(get_date))
def plot_candle_chart(df, pic_name='candle_chart'):
# 对数据进行整理
df.set_index(df['交易日期'], drop=True, inplace=True)
df = df[['开盘价', '最高价', '最低价', '收盘价']]
# 作图
ll = np.arange(0, len(df), 1)
my_xticks = df.index[ll].date
fig, ax = plt.subplots()
candlestick2_ohlc(ax, df['开盘价'].values, df['最高价'].values, df['最低价'].values, df['收盘价'].values,
width=0.6, colorup='r', colordown='g', alpha=1)
plt.xticks(ll, my_xticks)
plt.xticks(rotation=60)
plt.title(pic_name)
plt.subplots_adjust(left=0.09, bottom=0.20, right=0.94, top=0.90, wspace=0.2, hspace=0)
# 保存数据
plt.savefig(pic_name+'.png')
import pandas as pd import matplotlib.pyplot as plt from matplotlib.finance import candlestick2_ohlc quotes = pd.read_csv(r'D:\USDRUB_160101_180323.txt') fig, ax = plt.subplots() candlestick2_ohlc(ax,quotes['open'],quotes['high'],quotes['low'],quotes['close'], width=0.5) plt.show()
def plot_candlestick(sub,ax1,point =10, mount_flag = 0, direction = u'不买不卖'):
sub=sub[sub.LOWEST_PRICE > 0]
sub.reset_index(len(sub),inplace=True)
del sub['index']
step = len(sub)/point
if step < 1:
step = 1
baseline = range(len(sub)/step+1)
baseline = [int(x) * step for x in baseline]
if len(sub) <= baseline[-1]:
baseline = baseline[:-1]
# baseline = range(len(sub))
listLabels = sub['TRADE_DATE'].values
max_price = max(sub['HIGHEST_PRICE'].values)
min_price = min(sub['LOWEST_PRICE'].values)
plot_max = max_price * 1.05
plot_min = min_price * 0.95
candlestick2_ohlc(ax1, sub['OPEN_PRICE'],sub['HIGHEST_PRICE'], sub['LOWEST_PRICE'],sub['CLOSE_PRICE'], width=0.8, colorup='#ff1717',colordown='#53c156', alpha =1);
if direction == u'卖出':
ax1.plot(max(sub.index.values),sub['HIGHEST_PRICE'].values[-1],'gv')
elif direction == u'买入':
ax1.plot(max(sub.index.values),sub['LOWEST_PRICE'].values[-1],'r^')
## 成交量
# ax2=ax1.twinx()
ax2 = ax1
if mount_flag == 1:
plot_delta = plot_max - plot_min
bar_height = plot_delta/5
mount_min = plot_min - bar_height
sub['Mount']=sub['DEAL_AMOUNT'].astype(np.float64)*bar_height/max(sub['DEAL_AMOUNT'].values) ##归一化后的成交量
upframe = sub[sub.CLOSE_PRICE > sub.OPEN_PRICE]
downframe = sub[sub.CLOSE_PRICE < sub.OPEN_PRICE]
ax2.bar(downframe.index.values,downframe['Mount'].values,bottom=mount_min,color='#53c156', edgecolor='black',width=0.5)
ax2.bar(upframe.index.values,upframe['Mount'].values,bottom=mount_min,color='#ff1717', edgecolor='black',width=0.5)
ax2.set_ylim([mount_min*0.95,plot_max])
else:
ax2.set_ylim([plot_min*0.95,plot_max])
##均线
colors = ['r-','m-','b-','c-','y-']
mas = [5,10,20,60,120]
linearr = []
desarr = []
for count in range(0,5):
ma = mas[count]
color = colors[count]
line,=ax1.plot(sub.index.values,sub['mean%s'%ma].values,color)
# line,=ax1.plot(sub.index.values,sub['mean5'].values,color='r-')
linearr.append(line)
desarr.append("mean%s"%ma)
ax1.set_ylabel("Price")
ax1.set_xticks(baseline)
ax1.set_xticklabels(listLabels[baseline],fontdict={'size':8})
if max(baseline)> len(sub):
ax1.set_xlim([min(baseline)-2,max(baseline)+2])
else:
ax1.set_xlim([min(baseline)-2,len(sub)+2])
if direction == u'不买不卖':
ax1.legend(linearr,desarr,loc='upper left',ncol=3)
ax1.grid(True)
def candlechart(fig, ax, ohlc, width=0.8):
return mpf.candlestick2_ohlc(ax, opens=ohlc.open.values, closes=ohlc.close.values,
lows=ohlc.low.values, highs=ohlc.high.values,
width=width, colorup='r', colordown='b')
a=range(len(df_daily.index))
new=[]
for i in a:
if i%365==0:
new.append(i)
x=df_daily.index.strftime('%Y')
# In[ ]:
fig = plt.figure(figsize=(18,4))
ax1 = plt.subplot(1,1,1)
plt.ylabel('Price')
plt.xlabel('Date')
plt.xticks(new,x[new], rotation=45)
candlestick2_ohlc(ax1,o,h,l,c,width=1,colorup='k',colordown='r')
ax1.autoscale_view()
fig.autofmt_xdate()
# In[ ]:
df_daily['log_returns_close']= np.log(df_daily['price']['close']) - np.log(df_daily['price']['close'].shift(1))
df_daily['log_returns_open']= np.log(df_daily['price']['open']) - np.log(df_daily['price']['open'].shift(1))
df_daily['log_returns_high']= np.log(df_daily['price']['high']) - np.log(df_daily['price']['high'].shift(1))
df_daily['log_returns_low']= np.log(df_daily['price']['low']) - np.log(df_daily['price']['low'].shift(1))
# In[ ]:
df_daily.drop(df_daily.head(1).index,inplace=True)
ticknames = getMonthNames(r.date, tickindex)
formatter = IndexDateFormatter(date2num(r.date), '%m/%d/%y')
millionformatter = FuncFormatter(millions)
thousandformatter = FuncFormatter(thousands)
fig = plt.figure()
fig.subplots_adjust(bottom=0.1)
fig.subplots_adjust(hspace=0)
gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1])
ax0 = plt.subplot(gs[0])
candles = candlestick2_ohlc(ax0, r.open, r.high, r.low, r.close, width=1, colorup='g', colordown='r')
ma05 = MA(r.adj_close, 5, type='simple')
ma20 = MA(r.close, 20, type='simple')
ma60 = MA(r.adj_close, 60, type='simple')
Don20Hi = DonchianHi(r.high, 20)
Don20Lo = DonchianLo(r.low, 20)
BB20 = BB(r.close, 20)
ma05[:5]=np.NaN
ma20[:20]=np.NaN
ma60[:60]=np.NaN
ax0.plot(ma05, color='black', lw=2, label='MA (5)')
