def display_chart(self):
if not len(self.chart):
return
self.ax.clear()
# Axis ticker formatting
if len(self.chart) // 30 > len(self.chart_locator) - 1:
for index in range(
len(self.chart_locator) * 30, len(self.chart), 30):
time_format = self.chart.index[index].strftime('%H:%M')
self.chart_locator.append(index)
self.chart_formatter.append(time_format)
self.ax.xaxis.set_major_locator(ticker.FixedLocator(
self.chart_locator))
self.ax.xaxis.set_major_formatter(
ticker.FixedFormatter(self.chart_formatter))
# Axis yticks & lines
max_price = self.chart.High.max()
min_price = self.chart.Low.min()
if max_price > self.top_price or min_price < self.bottom_price:
self.top_price = math.ceil(
max_price / self.interval) * self.interval
self.bottom_price = math.floor(
min_price / self.interval) * self.interval
self.interval_prices = np.arange(self.bottom_price,
self.top_price + self.interval,
self.interval)
self.loss_cut_prices = np.arange(
self.bottom_price + self.interval - self.loss_cut,
self.top_price, self.interval)
self.ax.grid(axis='x', alpha=0.5)
self.ax.set_yticks(self.interval_prices)
for price in self.interval_prices:
self.ax.axhline(price, alpha=0.5, linewidth=0.2)
for price in self.loss_cut_prices:
self.ax.axhline(price, alpha=0.4, linewidth=0.2, color='Gray')
# Current Price Annotation
current_time = len(self.chart)
current_price = self.chart.Close.iloc[-1]
if self.chart_item_code[:3] == FUTURES_CODE:
formatted_current_price = format(current_price, ',.2f')
else:
formatted_current_price = format(current_price, ',')
# self.ax.text(current_time + 2, current_price, format(current_price, ','))
self.ax.text(current_time + 2, current_price, formatted_current_price)
# Draw Chart
candlestick2_ohlc(self.ax,
self.chart.Open,
self.chart.High,
self.chart.Low,
self.chart.Close,
width=0.4,
colorup='red',
colordown='blue')
self.fig.tight_layout()
self.canvas.draw()
def k_line(symble, title, last=-30, adjust="qfq", dprint=False):
'''
过去n天个股历史行情均线数据（k线）
param:
symble: str,股票编号"sh601727"
title: str,作图标题
last: int,过去多少天的数据,默认过去30天，例"-30"
adjust: str，默认"qfq"前复权,返回复权后数据
dprint: bool,默认false,是否打印原始数据
startday: int,行情查询起始日期（懒得转化，没写功能）
endday: int,行情查询起始日期（懒得转化，没写功能）
'''
pingan = ak.stock_zh_a_daily(symble, adjust)
df3 = pingan.reset_index().iloc[last:, :6] #取过去30天数据
df3 = df3.dropna(how='any').reset_index(drop=True) #去除空值且从零开始编号索引
df3 = df3.sort_values(by='date', ascending=True)
print(df3.info())
# 均线数据
df3['5'] = df3.close.rolling(5).mean()
df3['10'] = df3.close.rolling(10).mean()
df3.tail()
#画图
fig, ax = plt.subplots(1, 1, figsize=(8, 3), dpi=200)
candlestick2_ohlc(ax,
opens=df3['open'].values,
highs=df3['high'].values,
lows=df3['low'].values,
closes=df3['close'].values,
width=0.5,
colorup="r",
colordown="g")
# 显示最高点和最低点
ax.text(df3.high.idxmax(), df3.high.max(), s=df3.high.max(), fontsize=8)
ax.text(df3.high.idxmin(),
df3.high.min() - 2,
s=df3.high.min(),
fontsize=8)
ax.set_facecolor("white")
ax.set_title(title)
# 画均线
plt.plot(df3['5'].values, alpha=0.5, label='MA5')
plt.plot(df3['10'].values, alpha=0.5, label='MA10')
ax.legend(facecolor='white', edgecolor='white', fontsize=6)
# 修改x轴坐标
plt.xticks(ticks=np.arange(0, len(df3)),
labels=df3.date.dt.strftime('%Y-%m-%d').to_numpy())
plt.xticks(rotation=90, size=4)
# 修改y轴坐标
ax.yaxis.set_major_formatter(FormatStrFormatter('%.2f'))
plt.show()
def draw_candles(self, target_candles):
''' 取得済みチャートを描画 '''
mpf.candlestick2_ohlc(self.__axes[0],
opens=target_candles.open.values,
highs=target_candles.high.values,
lows=target_candles.low.values,
closes=target_candles.close.values,
width=0.6,
colorup='#77d879',
colordown='#db3f3f')
return {'success': 'チャートを描画', 'time': target_candles.time}
def generate_candlestick(the_opens, the_closes, the_highs, the_lows):
fig, ax = plt.subplots()
candlestick2_ohlc(ax,
the_opens,
the_closes,
the_highs,
the_lows,
width=0.6,
colorup='g',
colordown='r',
alpha=0.75)
plt.xlabel(f'Days from {amount_data} day mark')
plt.ylabel('Candle for each day')
plt.title(f'Candlestick chart of {the_stock.upper()}')
plt.show()
def days_graph(update, context):
global days
days = int(update.message.text)
ticker = "{}-{}".format(cryptocurrency, forex)
currpair = yf.Ticker(ticker)
start_date = (dt.datetime.now() - dt.timedelta(days=days - 2)).date()
df = currpair.history(period="1d",
start=start_date,
end=(dt.datetime.now() +
dt.timedelta(days=1)).date())
df.reset_index(inplace=True)
#change the percentages %m %d %y for the date format.
df["Date"] = df["Date"].dt.strftime("%m/%d/%y")
#Candlestick
fg, ax1 = plt.subplots()
candlestick2_ohlc(ax=ax1,
opens=df['Open'],
highs=df['High'],
lows=df['Low'],
closes=df['Close'],
width=0.4,
colorup='#77d879',
colordown='#db3f3f')
ax1.set_xticks(np.arange(len(df)))
ax1.set_xticklabels(
df['Date'], fontsize=7, rotation=-45, color='black'
) #the fontsize important if data too big, mag overlap yung date.
ax1.tick_params(axis='y', colors='black')
plt.title("{} Trend in the Past {} Days".format(cryptocurrency, days))
plt.ylabel("Price in {}".format(forex))
ax1.grid(True)
ax1.set_axisbelow(True)
#save, send, and delete
plt.savefig("candlestick.png")
context.bot.send_photo(chat_id=update.effective_chat.id,
photo=open("candlestick.png", "rb"))
os.remove("candlestick.png")
return ConversationHandler.END
def drawChartMarketInfo(self, wgtParent, index, dic):
fig = plt.figure(figsize=(20, 10))
ax = fig.add_subplot(111)
end = datetime.datetime.now()
start = end + datetime.timedelta(days=-90)
if index == 'KOSPI':
target = '^KS11'
value = dic["kospi_value"]
elif index == 'KOSDAQ':
target = '^KQ11'
value = dic["kosdaq_value"]
kospi_df = web.DataReader(target, "yahoo", start, end)
day_list = []
name_list = []
# 'Date' 인덱스를 컬럼으로 변환
kospi_df.reset_index(inplace=True)
for i, day in enumerate(kospi_df.Date):
if day.dayofweek == datetime.datetime.today().weekday():
day_list.append(i)
name_list.append(day.strftime('%m-%d'))
# X축 날짜 표시
ax.xaxis.set_major_locator(ticker.FixedLocator(day_list))
ax.xaxis.set_major_formatter(ticker.FixedFormatter(name_list))
# 그래프 title과 축 이름 지정
ax.set_title(index + ' INDEX : ' + value, fontsize=22)
ax.set_xlabel('Date')
# 캔들차트 그리기
candlestick2_ohlc(ax, kospi_df['Open'], kospi_df['High'],
kospi_df['Low'], kospi_df['Close'],
width=0.5, colorup='r', colordown='b')
ax.legend()
ax.grid(True, axis='y', linestyle='--')
canvas = FigureCanvas(fig)
vbxIndexes = QVBoxLayout(wgtParent)
vbxIndexes.addWidget(canvas)
canvas.draw()
def drawChart(self):
df = self.dataset
#이동 평균선을 그리기 위해 n일간의 값의 산술평균
df['MA5'] = df['Close'].rolling(5).mean()
df['MA10'] = df['Close'].rolling(10).mean()
df['MA20'] = df['Close'].rolling(20).mean()
df = df[-30:]
#인덱스 설정
dateindex = df.Date.astype('str')
df = df[[
'Open', 'High', 'Low', 'Close', 'Volume', 'MA5', 'MA10', 'MA20'
]]
fig = plt.figure(figsize=(20, 10))
ax = fig.add_subplot(111)
ax.plot(dateindex, df['MA5'], label='MA5', linewidth=0.7)
ax.plot(dateindex, df['MA10'], label='MA10', linewidth=0.7)
ax.plot(dateindex, df['MA20'], label='MA20', linewidth=0.7)
# x축을 60도로 회전
plt.xticks(rotation=60)
# X축 티커 숫자 30개로 제한
ax.xaxis.set_major_locator(ticker.MultipleLocator(1))
ax.set_title(self.stockCode, fontsize=22)
ax.set_ylabel("Price")
# ax.set_xlabel('Date')
# 차트 저장
candlestick2_ohlc(ax,
df['Open'],
df['High'],
df['Low'],
df['Close'],
width=0.5,
colorup='r',
colordown='b')
fig1 = plt.gcf()
ax.legend()
plt.grid()
plt.savefig("./static/img/" + self.stockCode + '.png', dpi=300)
def k_plot(self):
'''
画K线图
5、10、20日均线
布林带
'''
df3 = self.MA()
name = self.name
style.use('ggplot')
fig, ax = plt.subplots(1, 1, figsize=(8, 3), dpi=200)
candlestick2_ohlc(ax,
opens=df3['open'].values,
highs=df3['high'].values,
lows=df3['low'].values,
closes=df3['close'].values,
width=0.5,
colorup="r",
colordown="g")
ax.text(df3.high.idxmax() - 20,
df3.high.max(),
s=df3.high.max(),
fontsize=8)
ax.text(df3.high.idxmin() - 20,
df3.high.min(),
s=df3.high.min(),
fontsize=8)
ax.set_facecolor("white")
ax.set_title('%s(%s)' % (name, code_to_name(name)))
plt.plot(df3['5'].values, alpha=0.5, label='MA5')
plt.plot(df3['10'].values, alpha=0.5, label='MA10')
plt.plot(df3['20'].values, alpha=0.5, label='MID(MA20)', color='gray')
plt.plot(df3['upper_band'].values,
alpha=0.5,
label='UPR',
color='yellow')
plt.plot(df3['lower_band'].values, alpha=0.5, label='DN', color='blue')
ax.legend(facecolor='white', edgecolor='white', fontsize=6)
plt.xticks(ticks=np.arange(0, len(df3)),
labels=df3.date.dt.strftime('%Y-%m-%d').to_numpy())
plt.xticks(rotation=90, size=8)
ax.yaxis.set_major_formatter(FormatStrFormatter('%.2f'))
plt.show()
def plot_lines(data, plot_time, window1, window2):
data_plot = data.iloc[-plot_time:]
fig = plt.figure(facecolor='#07000d', figsize=(15, 10)) # 画布
ax = plt.subplot2grid((10, 4), (2, 0),
rowspan=4,
colspan=4,
facecolor='#07000d')
ax.grid(True, color='w', axis='y') # 网格
ax.grid(True, axis='x', alpha=0.3)
ax.yaxis.label.set_color('w') # 轴
plt.ylabel('Stock Price and Volume', color='w')
plt.xticks(ticks=np.arange(0, len(data_plot)),
labels=data_plot.date.dt.strftime('%Y-%m-%d').to_numpy(),
rotation=80,
size=8)
ax.yaxis.set_major_formatter(FormatStrFormatter('%.2f'))
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d')) # 横轴-时间
w_spin(ax)
w_tick(ax)
#kline=================================
candlestick2_ohlc(ax,
opens=data_plot['open'].values,
highs=data_plot['high'].values,
lows=data_plot['low'].values,
closes=data_plot['close'].values,
width=0.5,
colorup='red',
colordown='lime')
#5日10日均线=====================================
plot_mat = pd.DataFrame()
plot_mat['close'] = data['close']
mov_avg_1 = plot_mat['close'].rolling(window=window1).mean() # x日均线
mov_avg_2 = plot_mat['close'].rolling(window=window2).mean()
ax.plot(range(plot_time),
mov_avg_1.iloc[-plot_time:],
'lightyellow',
label='short_time',
linewidth=1.5)
ax.plot(range(plot_time),
mov_avg_2.iloc[-plot_time:],
'cyan',
label='long_time',
linewidth=1.5)
#成交量图====================================
Volume = data_plot[['date',
'volume']].groupby(by='date').sum().reset_index()
ax_1 = ax.twinx() # 共享绘图区域
ax_1.fill_between(range(plot_time),
0,
Volume.volume.values,
facecolor='#00ffe8',
alpha=0.4)
ax_1.grid(False)
ax_1.set_ylim(0, 4 * Volume.volume.values.max())
w_spin(ax_1)
w_tick(ax_1)
#涨跌幅图=====================================
ax_2 = plt.subplot2grid((10, 4), (0, 0),
sharex=ax,
rowspan=2,
colspan=4,
facecolor='#07000d')
data_plot2 = data.iloc[-plot_time - 1:]
raw_time = datef_p_strf(data_plot, '%Y-%m-%d')
daily_return = data_plot2['close'].pct_change().dropna()
ax_2.plot(raw_time, daily_return, 'cyan', linewidth=2)
plt.ylabel('Rise and Fall', color='w')
ax_2.axhline(0.03, color='lightcoral')
ax_2.axhline(0, color='lightgreen')
ax_2.set_yticks([0, 0.03])
ax_2.fill_between(raw_time, daily_return, 0.03, where=(daily_return >= 0.03),\
facecolors='lightcoral')
ax_2.fill_between(raw_time, daily_return, 0, where=(daily_return <= 0),\
facecolors='lightgreen')
w_spin(ax_2)
ax.tick_params(axis='y', colors='w')
#唐奇安通道=========================================
ax_3 = plt.subplot2grid((10, 4), (7, 0),
sharex=ax,
rowspan=4,
colspan=4,
facecolor='#07000d')
data_close = data_plot['close']
data_high = data['high']
data_low = data['low']
upbound = []
downbound = []
for i in range(plot_time):
upbound.append(max(data_high.iloc[-plot_time + i - 20:-plot_time + i]))
downbound.append(min(data_low.iloc[-plot_time + i - 20:-plot_time +
i]))
ax_3.plot(raw_time, upbound, 'cyan', linewidth=1)
ax_3.plot(raw_time, downbound, 'cyan', linewidth=1)
ax_3.plot(raw_time, data_close, 'orange', linewidth=2)
w_spin(ax_3)
w_tick(ax_3)
ax_3.grid(True, color='w', axis='y') # 网格
ax_3.grid(True, axis='x', alpha=0.3)
ax_3.tick_params(axis='x', colors='#07000d')
plt.ylabel('Dochian Channel', color='w')
#========================================
# plt.savefig('dsw_test.jpg')
plt.show()
def display_chart(self):
chart = self.futures.chart
if not len(chart):
return
self.trader.ax.clear()
# Axis ticker formatting
if len(chart) // 30 > len(self.chart_locator) - 1:
for index in range(len(self.chart_locator) * 30, len(chart), 30):
time_format = chart.index[index].strftime('%H:%M')
self.chart_locator.append(index)
self.chart_formatter.append(time_format)
self.trader.ax.xaxis.set_major_locator(ticker.FixedLocator(self.chart_locator))
self.trader.ax.xaxis.set_major_formatter(ticker.FixedFormatter(self.chart_formatter))
# Axis yticks & lines
max_price = chart.High.max()
min_price = chart.Low.min()
if max_price > self.top_price or min_price < self.bottom_price:
self.top_price = math.ceil(max_price / self.interval) * self.interval
self.bottom_price = math.floor(min_price / self.interval) * self.interval
self.interval_prices = numpy.arange(self.bottom_price, self.top_price + self.interval, self.interval)
self.loss_cut_prices = numpy.arange(self.bottom_price + self.interval - self.loss_cut, self.top_price, self.interval)
self.trader.ax.grid(axis='x', alpha=0.5)
self.trader.ax.set_yticks(self.interval_prices)
for price in self.interval_prices:
self.trader.ax.axhline(price, alpha=0.5, linewidth=0.2)
for price in self.loss_cut_prices:
self.trader.ax.axhline(price, alpha=0.4, linewidth=0.2, color='Gray')
# Current Price Annotation
current_time = len(chart)
current_price = chart.Close.iloc[-1]
self.trader.ax.text(current_time + 0.5, current_price, format(current_price, ',.2f'))
# Moving average
x = range(0, len(chart))
self.trader.ax.plot(x, chart.MA5, label='MA5', color='Magenta')
self.trader.ax.plot(x, chart.MA10, label='MA10', color='RoyalBlue')
self.trader.ax.plot(x, chart.MA20, label='MA20', color='Gold')
self.trader.ax.legend(loc='best')
# Slope
x_range = range(len(chart) - 1, len(chart) + 1)
self.slope = numpy.polyfit(x_range, chart.MA5[-2:], 1)
x = range(len(chart) - 20, len(chart))
y = numpy.poly1d(self.slope)
self.trader.ax.plot(x, y(x), color='Sienna')
# Set lim
x2 = len(chart)
x1 = x2 - self.chart_scope
if x1 < 0:
x1 = 0
elif x1 > x2 - 1:
x1 = x2 - 1
y1 = self.get_min_price(x1, x2) - 0.1
y2 = self.get_max_price(x1, x2) + 0.1
self.trader.ax.set_xlim(x1, x2)
self.trader.ax.set_ylim(y1, y2)
# After price data acquired
if self.start_time:
self.annotate_chart(current_time, x1, x2, y1, y2)
# Draw chart
candlestick2_ohlc(self.trader.ax, chart.Open, chart.High, chart.Low, chart.Close,
width=0.4, colorup='red', colordown='blue')
self.trader.fig.tight_layout()
self.trader.canvas.draw()
def showGraph(self, term):
self.change_value.emit(ZERO)
df = self.df
ndf = df.copy()
curr = 0
idx = 0
for i, row in df.iterrows():
if idx == 0:
curr = i
# curr = dt.strptime(row['date'], "%Y.%m.%d")
else:
timeGap = (dt.strptime(df.loc[curr]['date'], "%Y.%m.%d") -
dt.strptime(row['date'], "%Y.%m.%d")).days
if abs(timeGap) < term:
if row['high'] > df.loc[curr]['high']:
ndf.loc[curr, 'high'] = row['high']
if row['low'] > df.loc[curr]['low']:
ndf.loc[curr, 'low'] = row['low']
ndf.loc[curr, 'close'] = row['close']
ndf.drop(index=i, inplace=True)
else:
curr = i
idx += 1
self.change_value.emit(TWENTY_FIVE)
self.fig.clear()
ax = self.fig.add_subplot(111)
ax.plot(ndf['date'],
ndf['close'].rolling(window=5).mean(),
label="5",
linewidth=0.7)
ax.plot(ndf['date'],
ndf['close'].rolling(window=20).mean(),
label="20",
linewidth=0.7)
ax.plot(ndf['date'],
ndf['close'].rolling(window=60).mean(),
label="60",
linewidth=0.7)
ax.plot(ndf['date'],
ndf['close'].rolling(window=120).mean(),
label="120",
linewidth=0.7)
candlestick2_ohlc(ax,
ndf['open'],
ndf['high'],
ndf['low'],
ndf['close'],
width=1,
colorup='r',
colordown='b')
self.change_value.emit(FIFTY)
self.fig.suptitle("candle")
ax.set_xlabel("date")
ax.set_ylabel("stock price")
# ax.tick_params(axis='x', labelrotation=20)
ax.autoscale_view()
self.change_value.emit(SEVENTY_FIVE)
ax.xaxis.set_major_locator(ticker.MaxNLocator(5))
ax.legend(loc=1) # legend 위치
self.canvas.draw()
self.change_value.emit(A_HUNDRED)
def csvCandle(data, inc, name):
#CSV version - volume and dates are broken
print("-----loading from csv-----", name)
plt.figure(inc)
data.reset_index(inplace=True)
df_volume = data['Adj Close']
plt.xticks(rotation=45)
plt.xlabel("Date")
plt.ylabel("Price")
plt.suptitle(name)
ax1 = plt.subplot2grid((6, 1), (0, 0), rowspan=5, colspan=1)
ax2 = plt.subplot2grid((6, 1), (5, 0), rowspan=5, colspan=1, sharex=ax1)
ax2.set_title('Volume')
#date functions cause viewlimit crash due to same datetime reason as resample() issue, dont use
#ax1.xaxis_date()
#ax1.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
try:
candlestick2_ohlc(ax1,
data['Open'],
data['High'],
data['Low'],
data['Close'],
width=.6,
colorup='#00eeff',
colordown='#ff0044',
alpha=.4)
except:
print('ERROR candlestick2_ohlc failed')
main()
#fills volume visual with data
ax2.fill_between(data.index, data['Volume'].values, 0)
#add spacing between subplots
plt.subplots_adjust(hspace=0.7)
#formats the y axis ticker to represent dollars
formatter = ticker.FormatStrFormatter('$%1.2f')
ax1.yaxis.set_major_formatter(formatter)
for tick in ax1.yaxis.get_major_ticks():
tick.label1.set_visible(False)
tick.label2.set_visible(True)
#tick.label2.set_color('green')
#sets ticker to the left side
ax1.yaxis.tick_left()
ax1.yaxis.set_label_position("left")
ax1.grid(b=True, which='major', color='grey', linestyle='-', alpha=0.4)
#maximizes window
#this backend is: TkAgg
manager = plt.get_current_fig_manager()
manager.resize(*manager.window.maxsize())
return
def pic(df, name, folder_name):
Path("/content/"+folder_name+"/").mkdir(parents=True, exist_ok=True)
fig = plt.figure()
ax_1 = fig.add_subplot(2, 2, 1)
candlestick2_ohlc(ax_1, df["Open"], df["High"], df["Low"], df["Close"], width=0.6)
plt.savefig("/content/"+folder_name+"/"+name + ".png")
def drawchart_stock(code, wgtParent):
# 차트 시작 일자 설정 (조회일로 부터 90일 전)
start = datetime.datetime.now() + datetime.timedelta(days=-90)
# DB에서 90일치 종목코드에 대한 주가정보 데이터프레임으로 가져오기
conn = sqlite3.connect(dbpath, isolation_level=None)
cur = conn.cursor()
query = "SELECT * FROM STOCK_PRICE WHERE code = '" + code + "' AND Date >= '" + start.strftime('%Y-%m-%d') + "'"
result = cur.execute(query)
cols = [column[0] for column in result.description]
stock_df = pd.DataFrame.from_records(data=result.fetchall(), columns=cols)
stock_df['Date2'] = pd.to_datetime(stock_df['Date'])
print(stock_df)
# 차트 그리기
fig = plt.figure()
ax = fig.add_subplot(111)
day_list = []
name_list = []
for i, day in enumerate(stock_df['Date2']):
print('[{}] {}'.format(i, day))
# if day.dayofweek == datetime.datetime.today().weekday():
day_list.append(i)
name_list.append(day.strftime('%m-%d'))
print(pd.DataFrame([day_list, name_list]))
# X축 날짜 표시
ax.xaxis.set_major_locator(ticker.FixedLocator(day_list))
ax.xaxis.set_major_formatter(ticker.FixedFormatter(name_list))
plt.xticks(rotation=45)
# 그래프 title과 축 이름 지정
ax.set_title(stock_df['Name'].unique()[0], fontsize=22)
# ax.set_xlabel('Date')
# 캔들차트 그리기
candlestick2_ohlc(ax, stock_df['Open'], stock_df['High'],
stock_df['Low'], stock_df['Close'],
width=0.5, colorup='r', colordown='b')
ax.legend()
ax.grid(True, axis='x', linestyle='--')
plt.grid()
if __name__ == '__main__':
plt.show()
else:
canvas = FigureCanvas(fig)
vbxIndexes = QVBoxLayout(wgtParent)
vbxIndexes.addWidget(canvas)
canvas.draw()
# 화면 표시
# canvas = FigureCanvas(fig)
# vbxIndexes = QVBoxLayout(wgtParent)
# vbxIndexes.addWidget(canvas)
# canvas.draw()
# commit 및 종료
conn.commit()
conn.close()
return
def __create(self):
# マージン設定
matplotlib.rcParams['axes.xmargin'] = 0.001 # X軸
matplotlib.rcParams['axes.ymargin'] = 0.05 # Y軸
# グラフ設定
self.__fig = plt.figure(figsize=(self.__width, self.__height))
self.__fig.autofmt_xdate()
plt.subplots_adjust(wspace=0.0, hspace=0.0) # グラフ間余白
# チャート配置割り
grids = {
k: self.__yaxis[k]['gridspec'] if k in self.__yaxis.keys() else 1
for k in self.__indicators.keys()
}
total_grid = sum(grids.values())
#total_grid = len(self.__indicators.keys())
gs = gridspec.GridSpec(total_grid, 1)
# X軸列設定
lst_x = range(len(self.__df.index))
ax_idx = 0
grid = 0
ax0 = None
for k, g in grids.items():
if grid == 0: # 最上段チャートはタイトル設定
# axis作成
ax = plt.subplot(gs[grid:grid + g, 0])
ax0 = ax # X軸同期のため
# タイトル
ax.set_title(self.__title['title'],
loc=self.__title['loc'],
fontsize=self.__title['fontsize'])
else:
# axis作成
ax = plt.subplot(gs[grid:grid + g, 0],
sharex=ax0) # 最上段チャートにX軸同期
# 最下段チャートはX軸目盛り設定
if grid + g == total_grid:
ax.xaxis.set_major_locator(ticker.MaxNLocator(10))
if self.__xaxis['col'] in self.__df.columns:
xcol = self.__df[self.__xaxis['col']].values
else:
xcol = self.__df.index.values
def mydate(x, pos):
try:
if self.__xaxis['converter'] == None:
return x
else:
return self.__xaxis['converter'](xcol[int(x)])
except IndexError:
return ''
ax.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
else:
# x軸目盛り非表示
ax.tick_params(labelbottom=False, bottom=False)
# 枠線設定
axis = ['top', 'bottom', 'left', 'right']
line_width = [1, 1, 1, 1]
for a, w in zip(axis, line_width):
ax.spines[a].set_visible(True)
ax.spines[a].set_linewidth(w)
ax.spines[a].set_color('dimgray')
# 背景色設定
color_idx = ax_idx % len(self.__backcolor)
ax.patch.set_facecolor(self.__backcolor[color_idx])
ax.set_axisbelow(True) # グリッドがプロットした点や線の下に隠れる
#メモリの長さ,太さ, ラベルサイズの調整
ax.tick_params(direction='out', length=1, width=1, labelsize=10)
#ax.ticklabel_format(useOffset=False, style='plain') # オフセットと科学表記を無効
ax.yaxis.set_major_formatter(
ticker.ScalarFormatter(useMathText=True)) # Y軸目盛りを10のべき乗表記
# インジケータ設定
has_label = False
for indi in self.__indicators[k]:
# candlestick
if indi['type'] == 'candlestick':
mpf.candlestick2_ohlc(
ax,
opens=self.__df[indi['open']].values,
highs=self.__df[indi['high']].values,
lows=self.__df[indi['low']].values,
closes=self.__df[indi['close']].values,
width=indi['width'],
colorup=indi['upcolor'],
colordown=indi['downcolor'])
# line
elif indi['type'] == 'line':
ax.plot(lst_x,
self.__df[indi['y']],
color=indi['color'],
linewidth=indi['linewidth'],
linestyle=indi['linestyle'],
label=indi['label'])
# bar
elif indi['type'] == 'bar':
ax.bar(lst_x,
self.__df[indi['y']],
color=indi['color'],
width=indi['width'],
label=indi['label'])
# mark
elif indi['type'] == 'mark':
ax.scatter(lst_x,
self.__df[indi['y']],
marker=indi['marker'],
s=indi['size'],
c=indi['color'])
# band
elif indi['type'] == 'band':
ax.fill_between(
lst_x,
self.__df[indi['y1']],
self.__df[indi['y2']],
where=self.__df[indi['y1']] >= self.__df[indi['y2']],
facecolor=indi['upcolor'],
alpha=indi['alpha'],
interpolate=True)
ax.fill_between(
lst_x,
self.__df[indi['y1']],
self.__df[indi['y2']],
where=self.__df[indi['y1']] <= self.__df[indi['y2']],
facecolor=indi['downcolor'],
alpha=indi['alpha'],
interpolate=True)
ax.plot(lst_x,
self.__df[indi['y1']],
lst_x,
self.__df[indi['y2']],
color=indi['linecolor'],
linewidth=indi['linewidth'],
label=indi['label'])
# ラベル設定チェック
if indi['type'] != 'candlestick' and indi[
'label'] != None and len(indi['label']) > 0:
has_label = True
# X軸グリッド
ax.xaxis.grid(self.__xaxis['grid'],
which='major',
linestyle='dotted',
color='lightgray')
if k in self.__yaxis.keys():
# Y軸グリッド
ax.yaxis.grid(self.__yaxis[k]['grid'],
which='major',
linestyle='dotted',
color='lightgray')
# Y軸ラベル
ax.set_ylabel(self.__yaxis[k]['title'],
fontsize=12,
color='dimgray')
# 凡例表示
if self.__yaxis[k]['legend'] and has_label:
ax.legend()
grid += g
ax_idx += 1
def get_candle(coin, type, term, min=1):
if type == 'd':
link = "https://api.upbit.com/v1/candles/days"
params = {"count": term, "market": coin}
response = requests.get(link, params=params)
response = json.loads(response.text)
data = []
for r in response:
temp_data = {
"Date": r["candle_date_time_kst"][5:10],
"open": float(r["opening_price"]),
"high": float(r["high_price"]),
"low": float(r["low_price"]),
"close": float(r["trade_price"]),
}
data.append(temp_data)
df = pd.DataFrame(data,
columns=['Date', 'open', 'high', 'low', 'close'])
df = df[::-1]
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111)
ax.set_title(coin, fontsize=22)
ax.xaxis.set_major_locator(plt.MaxNLocator(20))
ax.set_xlabel('Date')
ax.plot(df['Date'], df['close'])
ax.ticklabel_format(axis='y', style='plain')
plt.gca().yaxis.set_major_formatter(
StrMethodFormatter('{x:,.1f}')) # No decimal places
candlestick2_ohlc(ax,
df['open'],
df['high'],
df['low'],
df['close'],
width=0.5,
colorup='r',
colordown='b')
plt.grid()
newdir = 'img/output{}.png'.format(random.randint(100, 999))
plt.savefig(newdir)
print(newdir)
return newdir
elif type == 'm':
link = "https://api.upbit.com/v1/candles/minutes/{}".format(min)
params = {"count": term, "market": coin}
response = requests.get(link, params=params)
response = json.loads(response.text)
data = []
if int(min) >= 15:
for r in response:
temp_data = {
"Date": r["candle_date_time_kst"],
"open": float(r["opening_price"]),
"high": float(r["high_price"]),
"low": float(r["low_price"]),
"close": float(r["trade_price"]),
}
data.append(temp_data)
maxloc = 5
else:
for r in response:
temp_data = {
"Date": r["candle_date_time_kst"][11:19],
"open": float(r["opening_price"]),
"high": float(r["high_price"]),
"low": float(r["low_price"]),
"close": float(r["trade_price"]),
}
data.append(temp_data)
maxloc = 15
df = pd.DataFrame(data,
columns=['Date', 'open', 'high', 'low', 'close'])
df = df[::-1]
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111)
ax.set_title(coin, fontsize=22)
ax.xaxis.set_major_locator(plt.MaxNLocator(maxloc))
ax.set_xlabel('Date')
ax.plot(df['Date'], df['close'])
ax.ticklabel_format(axis='y', style='plain')
plt.gca().yaxis.set_major_formatter(
StrMethodFormatter('{x:,.1f}')) # No decimal places
candlestick2_ohlc(ax,
df['open'],
df['high'],
df['low'],
df['close'],
width=0.5,
colorup='r',
colordown='b')
plt.grid()
newdir = 'img/output{}.png'.format(random.randint(100, 999))
plt.savefig(newdir)
return newdir
elif type == 'w' or type == 'mo':
if type == 'w':
link = "https://api.upbit.com/v1/candles/weeks"
elif type == 'mo':
link = "https://api.upbit.com/v1/candles/months"
params = {"count": term, "market": coin}
response = requests.get(link, params=params)
response = json.loads(response.text)
data = []
for r in response:
temp_data = {
"Date": r["candle_date_time_kst"],
"open": float(r["opening_price"]),
"high": float(r["high_price"]),
"low": float(r["low_price"]),
"close": float(r["trade_price"]),
}
data.append(temp_data)
maxloc = 5
df = pd.DataFrame(data,
columns=['Date', 'open', 'high', 'low', 'close'])
df = df[::-1]
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111)
ax.set_title(coin, fontsize=22)
ax.xaxis.set_major_locator(plt.MaxNLocator(maxloc))
ax.set_xlabel('Date')
ax.plot(df['Date'], df['close'])
ax.ticklabel_format(axis='y', style='plain')
plt.gca().yaxis.set_major_formatter(
StrMethodFormatter('{x:,.1f}')) # No decimal places
candlestick2_ohlc(ax,
df['open'],
df['high'],
df['low'],
df['close'],
width=0.5,
colorup='r',
colordown='b')
plt.grid()
newdir = 'img/output{}.png'.format(random.randint(100, 999))
plt.savefig(newdir)
return newdir
def display_chart(self):
chart = self.leverage.chart
if not len(chart):
return
self.trader.ax.clear()
# Axis ticker formatting
if len(chart) // 30 > len(self.chart_locator) - 1:
for index in range(len(self.chart_locator) * 30, len(chart), 30):
time_format = chart.index[index].strftime('%H:%M')
self.chart_locator.append(index)
self.chart_formatter.append(time_format)
self.trader.ax.xaxis.set_major_locator(
ticker.FixedLocator(self.chart_locator))
self.trader.ax.xaxis.set_major_formatter(
ticker.FixedFormatter(self.chart_formatter))
# Axis yticks & lines
max_price = chart.High.max()
min_price = chart.Low.min()
if max_price > self.top_price or min_price < self.bottom_price:
self.top_price = math.ceil(
max_price / self.interval) * self.interval
self.bottom_price = math.floor(
min_price / self.interval) * self.interval
self.interval_prices = list(
range(self.bottom_price, self.top_price + self.interval,
self.interval))
self.loss_cut_prices = list(
range(self.bottom_price + self.interval - self.loss_cut,
self.top_price, self.interval))
self.trader.ax.grid(axis='x', alpha=0.5)
self.trader.ax.set_yticks(self.interval_prices)
for price in self.interval_prices:
self.trader.ax.axhline(price, alpha=0.5, linewidth=0.2)
for price in self.loss_cut_prices:
self.trader.ax.axhline(price,
alpha=0.4,
linewidth=0.2,
color='Gray')
# Current Price Annotation
current_time = len(chart)
current_price = chart.Close.iloc[-1]
self.trader.ax.text(current_time + 2, current_price,
format(current_price, ','))
if self.reference_price:
self.annotate_chart(current_time)
# Moving average
x = range(0, len(chart))
self.trader.ax.plot(x, chart.MA5, label='MA5')
self.trader.ax.plot(x, chart.MA10, label='MA10')
self.trader.ax.plot(x, chart.MA20, label='MA20')
self.trader.ax.legend(loc='best')
# Slope
slope_x = range(len(chart) - 1, len(chart) + 1)
slope = numpy.polyfit(slope_x, chart.MA5[-2:], 1)
x = range(len(chart) - 20, len(chart))
y = numpy.poly1d(slope)
self.trader.ax.plot(x, y(x))
# Draw Chart
candlestick2_ohlc(self.trader.ax,
chart.Open,
chart.High,
chart.Low,
chart.Close,
width=0.4,
colorup='red',
colordown='blue')
self.trader.fig.tight_layout()
self.trader.canvas.draw()
def buyStock(stockDf, codeNum, companyName, stockBuySell):
# 그래프에서 날짜를 표시가기위해 datetime64 형의 인덱스를 String화하여 연도-월-일 형태로 저장
candlesticks_df = stockDf.tail(200)
day_list = []
name_list = []
for i, day in enumerate(candlesticks_df.index):
if day.dayofweek == 0: # 월요일에 해당하는 날짜값만 x축에 표시하기 위함
day_list.append(i)
name_list.append(day.strftime('%y-%m-%d'))
candlesticks_df = candlesticks_df.reset_index()
# 한글 폰트 지정
font_name = font_manager.FontProperties(
fname="c:/Windows/Fonts/malgun.ttf").get_name()
rc('font', family=font_name)
fig, ax = plt.subplots(figsize=(20, 10))
ax.xaxis.set_major_locator(ticker.FixedLocator(day_list))
ax.xaxis.set_major_formatter(ticker.FixedFormatter(name_list))
ax.plot(candlesticks_df.index,
list(candlesticks_df.Conversion),
label="전환선",
linewidth=0.7,
color='#0496ff')
ax.plot(candlesticks_df.index,
list(candlesticks_df.Standard),
label="기준선",
linewidth=0.7,
color='#991515')
ax.plot(candlesticks_df.index,
list(candlesticks_df.Prespan1),
label="선행스팬1",
linewidth=0.7,
color='#008000')
ax.plot(candlesticks_df.index,
list(candlesticks_df.Prespan2),
label="선행스팬2",
linewidth=0.7,
color='#ff0000')
ax.plot(candlesticks_df.index,
list(candlesticks_df.Laggingspan),
label="후행스팬",
linewidth=0.7,
color='black')
# green cloud
ax.fill_between(candlesticks_df.index, candlesticks_df['Prespan1'], candlesticks_df['Prespan2'], \
where=candlesticks_df['Prespan1'] > candlesticks_df['Prespan2'], facecolor='#008000', interpolate=True, alpha=0.25)
# red cloud
ax.fill_between(candlesticks_df.index, candlesticks_df['Prespan1'], candlesticks_df['Prespan2'], \
where=candlesticks_df['Prespan2'] > candlesticks_df['Prespan1'], facecolor='#ff0000', interpolate=True, alpha=0.25)
candlestick2_ohlc(ax, candlesticks_df['Open'], candlesticks_df['High'], candlesticks_df['Low'], \
candlesticks_df['Close'], width=0.6, colorup='r', colordown='b', alpha=0.5)
plt.xticks(rotation=45)
plt.grid()
# Chart info
title = companyName + " (" + codeNum + ")"
bgcolor = '#131722'
grid_color = '#363c4e'
spines_color = '#d9d9d9'
# Axes
plt.title(title, fontsize=20)
plt.xlabel('날짜', fontsize=15)
plt.ylabel('주가(원)', fontsize=15)
ax.grid(linewidth='0.3')
ax.spines['bottom'].set_color(spines_color)
ax.spines['top'].set_color(spines_color)
ax.spines['right'].set_color(spines_color)
ax.spines['left'].set_color(spines_color)
fig.tight_layout()
ax.autoscale_view()
plt.legend(loc='upper right', fontsize=15)
tempToday = str(date.today())
createFolder("./" + tempToday + "/매수추천")
createFolder("./" + tempToday + "/매도추천")
# stockBuySell = True 경우 매수 추천 저장
if stockBuySell == True:
tempStr = "./" + tempToday + "/매수추천/매수추천 - " + companyName + "(" + tempToday + ").png"
plt.savefig(tempStr)
print(companyName + "매수추천 저장 완료")
# stockBuySell = False 경우 매도 추천 저장
elif stockBuySell == False:
tempStr = "./" + tempToday + "/매도추천/매도추천 - " + companyName + "(" + tempToday + ").png"
plt.savefig(tempStr)
print(companyName + "매도추천 저장 완료")
import yfinance as yf
import matplotlib.pyplot as plt
from mplfinance.original_flavor import candlestick2_ohlc
import matplotlib.dates as mdt
import datetime as dt
start = '2020-05-13'
end = '2020-07-07'
acao = yf.download('SHOW3.SA', start, end)
acao.reset_index(inplace=True)
fig, ax = plt.subplots()
plt.title('SHOW3')
plt.xlabel('')
plt.ylabel('')
candlestick2_ohlc(ax, acao.Open, acao.High, acao.Low, acao.Close, width=1, colorup='g')
plt.savefig('meugrafico.png')
plt.show()
def PlotOHLC(charts: Charts,
trigger_queue=None,
extra_plot1=None,
extra_plot2=None,
chart_style='ohlc',
fast_ema=None,
normal_ema=None,
slow_ema=None,
plot_bb=False,
bb_sample_num=50,
sigma=2,
rsi=None,
plot_obv=False,
plot_volume=False):
"""arrange subplots"""
if rsi and (plot_obv or plot_volume):
big_rowspan = 70
small_rowspan = 15
rsi_pos = big_rowspan
obv_pos = rsi_pos + small_rowspan
elif rsi or plot_obv or plot_volume:
big_rowspan = 80
small_rowspan = 20
rsi_pos = big_rowspan
obv_pos = big_rowspan
else:
big_rowspan = 100
small_rowspan = 0
rsi_pos = big_rowspan
obv_pos = big_rowspan
if trigger_queue:
triggers = ConvertTriggersForPlot(charts, trigger_queue)
else:
triggers = None
for market_name in charts.close:
"""add figure number"""
global TEST_GLOBAL_plt_fig_num
TEST_GLOBAL_plt_fig_num += 1
plt.figure(TEST_GLOBAL_plt_fig_num)
# plt.get_current_fig_manager().full_screen_toggle()
"""do the plotting"""
ax1 = plt.subplot2grid((100, 1), (0, 0),
rowspan=big_rowspan,
colspan=1)
# ax1.set_facecolor('#4B4B4B')
# plt.xticks(np.arange(charts.chart_lengths[market_name]), charts.date_unix[market_name], rotation=15) # not showing the value of x bottom right
# plt.locator_params(axis='x', nbins=6) # shows only the original lines when chart is zoomed
if fast_ema:
ax1.plot(EMA_rolling(charts.close[market_name], window=fast_ema),
color='C0',
label=str(fast_ema) + ' EMA',
alpha=.7)
if normal_ema:
ax1.plot(EMA_rolling(charts.close[market_name], window=normal_ema),
color='gold',
label=str(normal_ema) + ' EMA',
alpha=.7)
if slow_ema:
ax1.plot(EMA_rolling(charts.close[market_name], window=slow_ema),
color='red',
label=str(slow_ema) + ' EMA',
alpha=.7)
if plot_bb:
bb = BolingerBands_rolling(SMA_rolling(charts.close[market_name],
window=bb_sample_num),
StandardDev_rolling(
charts.close[market_name],
window=bb_sample_num),
sigma=sigma)
ax1.plot(bb["Upper"],
color='purple',
label='BB (' + str(bb_sample_num) + ', ' + str(sigma) +
')',
alpha=.7)
ax1.plot(bb["Lower"], color='purple', alpha=.7)
if trigger_queue:
ax1.plot(triggers["buy"][market_name],
color='darkgreen',
marker='^',
linestyle='',
alpha=.8)
ax1.plot(triggers["sell"][market_name],
color='darkred',
marker='v',
linestyle='',
alpha=.8)
if extra_plot1:
dimensions = np.shape(extra_plot1[market_name])[0]
if dimensions:
for layer in range(0, dimensions):
ax1.plot(extra_plot1[market_name][layer], color='green')
else:
ax1.plot(extra_plot1[market_name], color='green')
if extra_plot2:
dimensions = np.shape(extra_plot2[market_name])[0]
if dimensions:
for layer in range(0, dimensions):
ax1.plot(extra_plot2[market_name][layer], color='red')
else:
ax1.plot(extra_plot2[market_name], color='red')
if 'ohlc' == chart_style:
candlestick2_ohlc(ax1,
opens=list(charts.open[market_name]),
highs=list(charts.high[market_name]),
lows=list(charts.low[market_name]),
closes=list(charts.close[market_name]),
colorup='#14E3C5',
colordown='#F45A5A',
width=1,
alpha=1.0)
else: # 'line' == chart_style
ax1.plot(charts.close[market_name], color='green')
ax1.grid(True)
ax1.set_title(market_name)
ax1.set_ylabel('Price')
if fast_ema or normal_ema or slow_ema or plot_bb:
ax1.legend()
if rsi:
ax2 = plt.subplot2grid((100, 1), (rsi_pos, 0),
sharex=ax1,
rowspan=small_rowspan,
colspan=1)
rsi_line = RSI_rolling(charts.close[market_name], window=rsi)
ax2.plot(rsi_line, color='C0')
ax2.axhline(y=70, color='red', linestyle='--', alpha=.5)
ax2.axhline(y=30, color='green', linestyle='--', alpha=.6)
ax2.set_ylim(bottom=0, top=100)
ax2.set_ylabel(str(rsi) + ' RSI')
ax2.set_yticks([30, 70])
ax2.xaxis.grid()
# plt.connect('button_press_event', DrawVerticalLine)
if plot_obv or plot_volume:
ax3 = plt.subplot2grid((100, 1), (obv_pos, 0),
sharex=ax1,
rowspan=small_rowspan,
colspan=1)
if plot_volume:
if not plot_obv:
ax3_vol = ax3
else:
ax3_vol = ax3.twinx()
volume_overlay(ax3_vol,
charts.open[market_name],
charts.close[market_name],
charts.volume[market_name],
colorup='#14E3C5',
colordown='#F45A5A',
width=1,
alpha=.6)
ax3_vol.set_ylim(0, max(charts.volume[market_name]))
ax3_vol.set_ylabel('Volume')
ax3_vol.get_yaxis().set_label_position('left')
ax3_vol.get_yaxis().tick_left()
if plot_obv:
obv = OBV_rolling(charts, market_name)
ax3.plot(obv, color='darkblue', label='OBV')
ax3.set_ylim(bottom=min(obv), top=max(obv))
ax3.legend()
ax3.get_yaxis().set_ticks([])
ax3.xaxis.grid()
plt.xlim(xmin=-1, xmax=charts.chart_lengths[market_name] + 1)