def plot_price_chart(self,
popen,
phigh,
plow,
pclose,
ax=None,
spines_col='#5998ff'):
ax.grid(True, linestyle='--', linewidth=0.3)
ax.yaxis.label.set_color('w')
ax.spines['top'].set_color(spines_col)
ax.spines['bottom'].set_color(spines_col)
ax.spines['left'].set_color(spines_col)
ax.spines['right'].set_color(spines_col)
ax.tick_params(axis='x', colors='w')
ax.tick_params(axis='y', colors='w')
ax.get_xaxis().set_visible(False)
candlestick2_ohlc(ax,
popen,
phigh,
plow,
pclose,
width=1,
colorup='#9eff15',
colordown='#ff1717')
return ax
def showCandle(self, idx):
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
nary = np.zeros((self.sizeofset, 4), dtype=float)
fxary = self.datas[idx].reshape((self.sizeofset, self.sizeofdata))
fxlabelary = self.labels[idx]
idxary = np.where(fxlabelary == 1)
idx = idxary[0][0]
plt.title('label:' + str(idx))
#ax.title = 'label:' + str(idx)
for i in range(self.sizeofset):
data = fxary[i]
nary[i] = [data[0], data[1], data[2], data[3]]
tary = nary.T
mpf.candlestick2_ohlc(ax,
opens=tary[0],
highs=tary[1],
lows=tary[2],
closes=tary[3],
width=0.7,
colorup='g',
colordown='r')
#mpf.candlestick_ohlc(ax,[op,hi,lo,cl],width=0.7, colorup='g', colordown='r')
ax.grid()
plt.show()
def graph(self):
for oneaxe in fig.axes:
oneaxe.clear()
oneaxe.legend(prop={'size': 6})
# close
df = self.getdataframe('close')
print(df)
print('-' * 25)
print(df.values[0])
df = 100 * ((df / df.values[0]) - 1)
self.dfindexdate(df)
df.plot(ax=ax0)
# dt = self.tick
# dt = 100 * ((dt / dt.values[0]) - 1)
# dt.plot(ax=ax1)
#
# # volume
# dfv = self.getdataframe('volume').pct_change()
# self.dfindexdate(dfv)
# dfv.plot(ax=ax2, width=.9, kind='bar', alpha=.8)
# ohlc btc
for i, pair in enumerate(self.pairs):
quotes = self.dfpairs[pair]
candlestick2_ohlc(axs[i],
quotes['open'],
quotes['high'],
quotes['low'],
quotes['close'],
width=0.6)
axs[i].set_title(pair, fontsize=8)
def candlechart(data, width=0.8):
fig, ax = plt.subplots()
# ローソク足
mpf.candlestick2_ohlc(ax,
opens=data.open.values,
closes=data.close.values,
lows=data.low.values,
highs=data.high.values,
width=width,
colorup='r',
colordown='b')
xdate = data.index
ax.xaxis.set_major_locator(ticker.MaxNLocator(20))
def mydate(x, pos):
try:
return xdate[int(x)]
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
ax.format_xdata = mdates.DateFormatter('%m-%d')
fig.autofmt_xdate()
fig.tight_layout()
return fig, ax
def plot_prices(self, st_id):
fig, ax = plt.subplots(1, 1)
quotes = self.strats[st_id].prices.tz_localize(pytz.timezone('UTC'))
quotes = quotes.reset_index()
candlestick2_ohlc(ax,
quotes['open'],
quotes['high'],
quotes['low'],
quotes['close'],
width=0.4,
colorup='g',
colordown='r',
alpha=0.4)
tdate = [i for i in quotes['Timestamp']]
ax.xaxis.set_major_locator(ticker.MaxNLocator(10))
ax.xaxis.set_minor_locator(ticker.MaxNLocator(40))
for trade in self.trades:
if trade.strategy_id == st_id:
index = tdate.index(trade.timestamp)
if trade.quantity > 0:
plt.plot(index, trade.price, 'go')
elif trade.quantity < 0:
plt.plot(index, trade.price, 'ro')
fig.autofmt_xdate()
plt.title("Strategy " + str(st_id) + " prices")
plt.show(block=False)
def SuppRes(df0):
df_open = df0.Open.copy()
df_high = df0.High.copy()
df_low = df0.Low.copy()
df_close = df0.Close.copy()
df_support = argrelmin(df_low.values, order=5)
support_prices = df_low[df_support[0]]
support_prices_lower = df_open[df_support[0]]
resistance = argrelmax(df_high.values, order=5)
resistance_prices = df_high[resistance[0]]
resistance_prices_higher = df_open[resistance[0]]
print('Support prices', support_prices)
print('Support:', df_support)
print('Resistance:', resistance)
resistance_prices
fig, ax = plt.subplots(figsize=[15, 9])
candlestick2_ohlc(ax, df0['Open'], df0['High'], df0['Low'], df0['Close'], colorup='green', colordown='red',
width=0.5)
plt.scatter(df_support, support_prices)
plt.scatter(resistance, resistance_prices)
# plt.plot(np.unique(df_support), np.poly1d(np.polyfit(df_support, support_prices, 1))(np.unique(df_support)))
plt.show()
def _draw_chart(self, df):
data = df.head(30)
date = pd.to_datetime(data.index)
xlist = [v.strftime("%m/%d") for v in date]
self.chart.clear()
ax = self.chart.add_subplot(111)
dlist = range(len(xlist))
ax.xaxis.set_major_locator(ticker.FixedLocator(dlist))
ax.xaxis.set_major_formatter(ticker.FixedFormatter(xlist))
ax.invert_xaxis()
mpl.candlestick2_ohlc(ax,
data["Open"],
data["High"],
data["Low"],
data["Close"],
width=0.5,
colorup='r',
colordown='b')
#ax.legend(loc='best')
ax.grid()
self.canvas.draw()
def plot_levels_on_candlestick(
df,
levels,
only_good=False,
path=None,
formatter=mdates.DateFormatter('%y-%m-%d %H:%M:%S')):
ohlc = df[['Date', 'Open', 'High', 'Low', 'Close']].copy()
ohlc["Date"] = pd.to_datetime(ohlc['Date'])
ohlc["Date"] = ohlc["Datetime"].apply(lambda x: mdates.date2num(x))
f1, ax = plt.subplots(figsize=(10, 5))
candlestick2_ohlc(ax,
closes=ohlc.Close.values,
opens=ohlc.Open.values,
highs=ohlc.High.values,
lows=ohlc.Low.values,
colordown='red',
colorup='green')
_plot_levels(ax, levels, only_good)
if path:
plt.savefig(path)
else:
plt.show()
plt.close()
def plot(self):
''' plot some random stuff '''
# random data
#data = [random.random() for i in range(50)]
# create an axis
ax = self.figure.add_subplot(111)
# discards the old graph
# ax.hold(False) # deprecated, see above
print self.currentData['Open'], self.currentData[
'High'], self.currentData['Low'], self.currentData['Close']
candlestick2_ohlc(ax,
self.currentData['Open'],
self.currentData['High'],
self.currentData['Low'],
self.currentData['Close'],
width=0.6)
# plot data
#ax.plot(data, 'x-')
# refresh canvas
self.canvas.draw()
def show_candlestick(ohlc):
fig, ax = plt.subplots()
# ローソク足
mpf.candlestick2_ohlc(ax,
opens=ohlc['1_open'].values,
closes=ohlc['4_close'].values,
lows=ohlc['3_low'].values,
highs=ohlc['2_high'].values,
width=0.2,
colorup='r',
colordown='b')
# x軸を時間にする
xdate = ohlc.index
ax.xaxis.set_major_locator(ticker.MaxNLocator(6))
f = lambda x, y: mydate(x, ohlc)
ax.xaxis.set_major_formatter(ticker.FuncFormatter(f))
ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
fig.autofmt_xdate()
fig.tight_layout()
plt.show()
def func_plot_type1(Open, High, Low, Close, indicator, result):
plt.figure()
# ax1
ax1 = plt.subplot(211)
mpf.candlestick2_ohlc(ax1, Open, High, Low, Close, width=0.5, colorup='green', colordown='red')
# x = list(range(len(data_HA)))
# y = data_HA.HA_High.values
# p = data_PS.values # data_CT.values
# q = data_CT.bar_idx_live.values
# for i,j in zip(x,y):
# ax1.text(i,j, '%d' % p[i])
# ax1.text(i,j-20, '%d' % q[i])
ax1.fill_between(range(len(Close)), [Close.max()]*len(Close), [Close.min()]*len(Close),
where=indicator== 1, facecolor='green', alpha=0.5)
ax1.fill_between(range(len(Close)), [Close.max()]*len(Close), [Close.min()]*len(Close),
where=indicator==-1, facecolor='red', alpha=0.5)
# ax2
ax2 = plt.subplot(212, sharex=ax1)
plt.plot(result[0])
plt.title('Accumulated Return = %s ; Trade Number = %s ; Return per Trade= %s bp' % (result[0][-1], result[1], result[0][-1]/result[1]*10000))
plt.show()
def candlesticks(cls, df, start_date, end_date):
quotes = Strategy.slicebydate(df, start_date, end_date)
fig, ax = plt.subplots()
# candle.candlestick2_ohlc(ax,quotes['Open'],quotes['High'],quotes['Low'],quotes['Close'],width=0.6,colorup='#53AA03',colordown="#C20074")
candle.candlestick2_ohlc(
ax,
quotes['Open'],
quotes['High'],
quotes['Low'],
quotes['Close'],
width=0.6,
colorup='#10069D',
colordown="#34E5DA") # color up is blue and down is cyan
xdate = [i.to_pydatetime() 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()
plt.plot()
def candlechart(data, width=0.6):
fig, ax = plt.subplots()
print(data)
# ローソク足
mpf.candlestick2_ohlc(
ax,
opens=data.open.values,
closes=data.close.values,
lows=data.low.values,
highs=data.high.values,
width=width,
colorup='#77d879',
colordown='#db3f3f')
xticks_number = 12
xticks_index = range(0, len(data), xticks_number)
xticks_display = [data.time.values[i][11:16] for i in xticks_index]
# 時間を切り出すため、先頭12文字目から取る
fig.autofmt_xdate()
fig.tight_layout()
plt.sca(ax)
plt.xticks(xticks_index, xticks_display)
plt.legend()
plt.show()
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()
mplf.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')
plt.show()
def get_graphs(self, indicators: list):
data = self.get_dataframe(indicators)
xdate = [datetime.fromtimestamp(datetime.strptime(str(date[:-3]), '%b %d %Y %H:').timestamp()) \
for date in data['date']]
fig, ax = plt.subplots(len(data.keys()) - 4 + 1, sharex=True, dpi=1000)
candlestick2_ohlc(ax[0], data['open'], data['high'], data['low'], data['close'], width=0.6)
ax[0].xaxis.set_major_locator(ticker.MaxNLocator(20))
def chart_date(x, pos):
try:
return xdate[int(x)]
except IndexError:
return ''
ax[0].xaxis.set_major_formatter(ticker.FuncFormatter(chart_date))
fig.autofmt_xdate()
fig.tight_layout()
i = 1
for indicator in list(data.keys())[5:]:
ax[i].plot(data[indicator])
i += 1
plt.show()
fig.savefig(self.skin.name)
output = {}
for indicator in list(data.keys())[4:]:
output[indicator] = data[indicator][-1]
return output
def isolated_candle_graph():
conn = MySQLdb.connect(host='localhost',
user='******',
passwd='pickle',#
db='pickledb') # falsified information
cursor = conn.cursor()
sql = "SELECT * FROM ddr"
cursor.execute(sql)
result = cursor.fetchall()
print(result)
df = pd.DataFrame(list(result), columns=["Date", "Open", "High", "Low", "Close", "Adj_Close", "Volume"])
fig, ax = plt.subplots()
mpl_finance.candlestick2_ohlc(ax, df.Open, df.High, df.Low, df.Close,
width=0.6, colorup='r', colordown='c', alpha=1)
df = df.set_index(df["Date"])
xdate = df.index
def mydate(x, pos):
try:
return xdate[int(x)]
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
plt.show()
def chart(plan, id, symbol, time, date): #UP-
name = id + "_" + str(time)
total = 0
for i in plan.keys():
if i == id:
for ii in plan.get(i)['strat'].keys():
total += 1
df = hd.handler().candle_data(symbol,
plan.get(i)['strat'][ii], 20)
fig, ax = plt.subplots(figsize=(15, 10))
candlestick2_ohlc(ax,
df.open,
df.high,
df.low,
df.close,
width=0.5,
colorup='g',
colordown='r')
ax.set_title(
f"{symbol} with {plan.get(i)['strat'][ii]} Minutes Candle",
fontsize=18)
if not os.path.exists(f'./DATA/charts/{date}'): #UP-
os.makedirs(f'./DATA/charts/{date}') #UP-
plt.savefig(f'./DATA/charts/{date}/{name}_{total}.svg') #UP-
plt.clf()
def make_gs(CODE, where):
for code in CODE:
url = "https://navercomp.wisereport.co.kr/v2/company/c1040001.aspx?cmp_cd=" + code + "&cn="
html = req.urlopen(url)
soup = BeautifulSoup(html, 'html.parser')
name = soup.select("span.name")[0].text # 회사명 넣기
data = fdr.DataReader(code, dt(2018,10,1), dt(2019,12,1)).iloc[:,:5]
idx = data.index.astype(str)
ma = fdr.DataReader(code, dt(2018,10,1),dt(2019,12,1)).ix[:,-3]
ma5 = fdr.DataReader(code, dt(2018,9,20),dt(2019,12,1)).ix[:,-3].rolling(window=5).mean()[4:]
ma20 = fdr.DataReader(code, dt(2018,8,30),dt(2019,12,1)).ix[:,-3].rolling(window=20).mean()[19:]
ma60 = fdr.DataReader(code, dt(2018,7,4),dt(2019,12,1)).ix[:,-3].rolling(window=60).mean()[59:]
ma120 = fdr.DataReader(code, dt(2018,4,4),dt(2019,12,1)).ix[:,-3].rolling(window=120).mean()[119:]
fig, ax = plt.subplots(figsize=(12,7)) # 여기서 차트 크기를 조정 할 수 있습니다.
# 이동평균선을 차트에 추가 합니다.
ax.plot(idx, ma5, label='5일', color='green', linewidth=2.5)
ax.plot(idx, ma20, label='20일', color='red', linewidth=2.5)
ax.plot(idx, ma60, label='60일', color='orange', linewidth=2.5)
ax.plot(idx, ma120, label='120일', color='purple', linewidth=2.5)
# 아래 명령어를 통해 시고저종 데이터를 사용하여 캔들 차트를 그립니다.
candlestick2_ohlc(ax,data['Open'],data['High'], data['Low'],data['Close'],width=0.6, colorup = 'red', colordown ='blue')
ax.xaxis.set_major_locator(ticker.MaxNLocator(6))
# 아래는 날짜 인덱싱을 위한 함수 입니다.
def mydate(x,pos):
try:
return idx[int(x-0.5)]
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
plt.title(name + ' , ' + code, size = 20)
plt.xlabel('년/월',fontsize=15)
plt.ylabel('가격(원)',fontsize=15)
plt.grid(color='#BDBDBD', linestyle='--', linewidth=0.5 )
plt.legend(loc='best')
plt.axvline(x='2018-12-03', color='black')
fig.autofmt_xdate()
plt.savefig(where + name + '.png')
# blacklist = ['900280', '036800', '115310', '208710', '101330', '063760', '088130', '031980',
# '036830', '183300', '269620', '241790', '039440', '011170']
# 과거기준으로 하려면?
ma = fdr.DataReader(code, dt(2017,12,1),dt(2018,12,1)).ix[:,-3]
ma5 = fdr.DataReader(code, dt(2017,11,27),dt(2018,12,1)).ix[:,-3].rolling(window=5).mean()[4:]
ma20 = fdr.DataReader(code, dt(2017,11,6),dt(2018,12,1)).ix[:,-3].rolling(window=20).mean()[19:]
ma60 = fdr.DataReader(code, dt(2017,9,1),dt(2018,12,1)).ix[:,-3].rolling(window=60).mean()[59:]
ma120 = fdr.DataReader(code, dt(2017,6,8),dt(2018,12,1)).ix[:,-3].rolling(window=120).mean()[119:]
def show_graph(ohlc):
ax = plt.subplot()
ax.grid(color='gray', linestyle='--', linewidth=0.5)
mpf.candlestick2_ohlc(ax, ohlc.open.values, ohlc.high.values,
ohlc.low.values, ohlc.close.values, 0.5, 'r',
'b')
plt.show()
def candle_stick(self, wrangled):
fig = plt.figure(figsize = (28,5))
ax = fig.add_subplot(1,1,1)
mplfin.candlestick2_ohlc(ax, width=1, colorup='r', colordown='b',
opens = wrangled['Adj. Open'], highs = wrangled['Adj. High'],
lows = wrangled['Adj. Low'], closes = wrangled['Adj. Close'])
plt.savefig(str(os.getcwd()).replace('\\','/')+'/images/candlestick.png')
plt.close()
def createChart(self):
fig, ax = plt.subplots(figsize=(8, 4))
candlestick2_ohlc(ax,
self.data['Open'],
self.data['High'],
self.data['Low'],
self.data['Close'],
width=0.4)
xs = len(self.data)
locs = [0, 20, 40, 60, 80, 100, 120, xs - 1]
plt.xticks(locs, self.data.loc[locs, 'Date'])
a = self.data.sort_values('Date',
ascending=False).reset_index(drop=True)
ma = a.loc[0:8, 'Close'].mean()
plt.hlines(ma, xs, xs + 1, colors="blue")
plt.text(x=xs + 2, y=ma, s="8", fontsize=8, color='b')
ma = a.loc[0:21, 'Close'].mean()
plt.hlines(ma, xs, xs + 2, colors="blue")
plt.text(x=xs + 3, y=ma, s="21", fontsize=8, color='b')
ma = a.loc[0:50, 'Close'].mean()
plt.hlines(ma, xs, xs + 4, colors="blue")
plt.text(x=xs + 5, y=ma, s="50", fontsize=8, color='b')
ma = a.loc[0:100, 'Close'].mean()
plt.hlines(ma, xs, xs + 6, colors="blue")
plt.text(x=xs + 7, y=ma, s="100", fontsize=8, color='b')
self.squeeze()
sq = self.squeezeLen()
plt.text(x=80,
y=self.data["Low"].min(),
s="Daily Squeeze = " + str(sq),
fontsize=8,
color='b')
self.squeezeWeekly()
sq = self.squeezeLenWeekly()
plt.text(x=110,
y=self.data["Low"].min(),
s="Weekly Squeeze = " + str(sq),
fontsize=8,
color='b')
fig.autofmt_xdate()
fig.tight_layout()
figfile = BytesIO()
fig.savefig(figfile, format='png')
figfile.seek(0)
figdata_png = base64.b64encode(figfile.getvalue()).decode('utf-8')
self.chartURI = 'data:image/png;base64,{}'.format(figdata_png)
plt.close()
def plot_ohlc(ax, ep, o, h, l, c, datetime_display_span="h"):
max_price = max(h)
min_price = min(l)
old_val = -1
datecolor = "dodgerblue"
do_show = False
for i in range(len(ep)):
t = ep[i]
d = lib.epoch2dt(t)
if datetime_display_span == "d":
if d.hour == 0 and d.day != old_val:
do_show = True
old_val = d.day
if datetime_display_span == "h":
if d.minute == 0 and d.hour != old_val:
do_show = True
old_val = d.hour
if do_show:
if c[i] >= (max_price + min_price) / 2:
yval = min_price
else:
yval = max_price
ax.axvline(i, c=datecolor)
ax.annotate("%02d-%02d\n%02d:%02d" %
(int(d.month), int(d.day), int(d.hour), int(d.minute)),
(i, yval),
size=30,
color=datecolor,
horizontalalignment="left")
do_show = False
mid_price = (max_price + min_price) / 2
ax.axhline(y=max_price, color=datecolor)
ax.annotate(max_price, (0, max_price),
size=30,
color=datecolor,
horizontalalignment="right")
ax.axhline(y=mid_price, color=datecolor)
ax.annotate(mid_price, (0, mid_price),
size=30,
color=datecolor,
horizontalalignment="right")
ax.axhline(y=min_price, color=datecolor)
ax.annotate(min_price, (0, min_price),
size=30,
color=datecolor,
horizontalalignment="right")
mpl_finance.candlestick2_ohlc(ax,
opens=o,
closes=c,
lows=l,
highs=h,
width=0.8,
colorup='lightgray',
colordown='grey',
alpha=1)
def draw_ohlc(self): #data의 변동이 있을때만 다시 그리기
self.topAxax.cla()
mpl_finance.candlestick2_ohlc(self.topAxax,
self.data['open'][-self.start:],
self.data['high'][-self.start:],
self.data['low'][-self.start:],
self.data['close'][-self.start:],
width=0.5,
colorup='r',
colordown='b')
def PlotCandleAll(self):
candlestick2_ohlc(ax,
self.data['Open'].values,
self.data['High'].values,
self.data['Low'].values,
self.data['Close'].values,
width=0.6,
colorup='g',
colordown='r',
alpha=1)
def draw_K_line(data):
"""
绘制K线图
:param data:
:return:
"""
# year_2018 = df['2018-01-01':'2018-07-31']
fig, ax = plt.subplots(figsize=(16, 9))
candlestick2_ohlc(ax, data.Open, data.High, data.Low,
data.Close, width=.5, alpha=.6)
plt.show()
def plot_price_and_eval(o, h, l, c, eval):
# Plotting data and result
fig, axes = plt.subplots(nrows=1, ncols=1)
candlestick2_ohlc(axes, o, h, l, c, colorup='black', colordown='b', width=0.3)
for i in range(0, len(eval)):
if eval[i] > 0:
plt.axvline(i, c='green')
elif eval[i] < 0:
plt.axvline(i, c='red')
plt.show()
def plot(csv,sell_time):
df=pd.read_csv(csv)
date=df['Date']
open=df['Open']
high=df['High']
low=df['Low']
close=df['Close']
fig=plt.figure(figsize=(7,5))
graph=fig.add_subplot(1,1,1)
graph.plot(date,close,color='red')
candlestick2_ohlc(graph,open,high,low,close,colorup="blue",colordown="red",width=2,alpha=0.5)
def plot_stock_price(self):
df = self.__data_center.query('TradeData.Stock.Daily', '600000.SSE')
df = df[df['trade_date'] > years_ago(1)]
# df['trade_date'] = df['trade_date'].apply(lambda d: mdates.date2num(d.to_pydatetime()))
adjust_ratio = df['adj_factor']
price_open = df['open'] * adjust_ratio
price_close = df['close'] * adjust_ratio
price_high = df['high'] * adjust_ratio
price_low = df['low'] * adjust_ratio
self.__figure.clear()
ax1 = self.__figure.add_subplot(2, 1, 1)
ax2 = self.__figure.add_subplot(2, 1, 2)
time_serial = pd.to_datetime(df['trade_date'], format="%Y/%m/%d")
# ax1 = plt.subplot2grid((3, 1), (0, 0), rowspan=2, colspan=1) # 佔全圖2/3的子圖一
ax1.set_xticks(range(0, len(time_serial), 10)) # 設定X軸座標
ax1.set_xticklabels(time_serial) # 設定X軸標籤
mpf.candlestick2_ohlc(ax1, df['open'], df['high'], df['low'], df['close'], width=0.6, colorup='r',
colordown='k', alpha=1) # 畫出K線圖
ax1.tick_params('x', bottom=False, labelbottom=False) # 子圖一不顯示X軸標籤
ax1.set_axisbelow(True) # 設定格線在最底圖層
ax1.grid(True) # 畫格線
# ax2 = plt.subplot2grid((3, 1), (2, 0), rowspan=1, colspan=1, sharex=ax1) # 佔全圖1/3的子圖二，設定X軸座標與子圖一相同
mpf.volume_overlay(ax2, df['open'], df['close'], df['amount'] / 1000, colorup='b', colordown='b',
width=0.6, alpha=1) # 畫出成交量
ax2.set_axisbelow(True) # 設定格線在最底圖層
ax2.grid(True) # 畫格線
plt.gcf().autofmt_xdate() # 斜放X軸標籤
self.__canvas.draw()
# mpf.candlestick2_ochl(axes, price_open, price_close, price_high, price_low, colorup='r', colordown='g')
#
# axes.set_xlabel('日期')
# axes.set_ylabel('价格')
# axes.set_xlim(0, len(df['trade_date']))
# axes.set_xticks(range(0, len(df['trade_date']), 15))
#
# time_serial = pd.to_datetime(df['trade_date'], format="%Y/%m/%d")
# axes.set_xticklabels([time_serial[x] for x in axes.get_xticks()]) # 标签设置为日期
#
# # X-轴每个ticker标签都向右倾斜45度
# for label in axes.xaxis.get_ticklabels():
# label.set_rotation(45)
# label.set_fontsize(10) # 设置标签字体
# plt.show()
self.__canvas.draw()
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])
reversed_daeshin_day = daeshin_day[::-1]
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(reversed_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))
def passDtype(n):
return np.array(n, dtype=float)
matfin.candlestick2_ohlc(ax,
passDtype(reversed_daeshin_day['open']),
passDtype(reversed_daeshin_day['high']),
passDtype(reversed_daeshin_day['low']),
passDtype(reversed_daeshin_day['close']),
width=0.5,
colorup='r',
colordown='b')
plt.grid()
plt.show()
def _candle(ohlc, ma=None, volume=False, figsize=(10, 8)):
# plt.rcParams['font.family'] = 'Times New Roman'
plt.rcParams['font.size'] = 20
fig, ax = plt.subplots(figsize=figsize)
# candle plot
width = 0.8
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')
# moving average
if ma is not None and type(ma) == list:
for _ma in ma:
sma = ohlc.close.rolling(_ma).mean()
v_stack = np.vstack((range(len(sma)), sma.values.T)).T
ax.plot(v_stack[:, 0], v_stack[:, 1], label="ma(%i)" % _ma)
plt.legend(loc="upper left")
# volume
if volume:
ax2 = ax.twinx() # connect two axis
ax2.plot(ohlc.volume.values,
label="volume",
marker=".",
linestyle=":",
color="black")
plt.legend(loc="upper right")
# x axis -> time
xdate = ohlc.index
ax.xaxis.set_major_locator(ticker.MaxNLocator(10))
ax.grid(True)
def mydate(x, pos):
try:
return xdate[int(x)]
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
fig.autofmt_xdate()
fig.tight_layout()
return fig, ax
import pandas_datareader.data as web
import datetime
import matplotlib.pyplot as plt
import mpl_finance
start = datetime.datetime(2016, 3, 1)
end = datetime.datetime(2016, 3, 31)
skhynix = web.DataReader("000660.KS", "yahoo", start, end)
#print(skhynix)
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111)
mpl_finance.candlestick2_ohlc(ax, skhynix['Open'], skhynix['High'], skhynix['Low'], skhynix['Close'],
width=0.5, colorup='r', colordown='b')
plt.show()
