def Kline_plot(raw_data):
#raw_data = ts.get_hist_data('hs300', start='2015-07-01')
#raw_data.index = raw_data.index.map(str2date)
raw_data['time'] = raw_data.index
data = DataFrame(raw_data, columns=['time', 'open','close','high','low'])
alldays = DayLocator()
months = MonthLocator()
weekdays = WeekdayLocator()
month_formater = DateFormatter("%b %Y")
week_formater = DateFormatter("%m %d")
ymajorLocator = MultipleLocator(100) #将y轴主刻度标签设置为0.5的倍数
ymajorFormatter = FormatStrFormatter('%1.1f') #设置y轴标签文本的格式
yminorLocator = MultipleLocator(10) #将此y轴次刻度标签设置为0.1的倍数
fig = plt.figure()
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(weekdays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(week_formater)
ax.yaxis.set_major_locator(ymajorLocator)
ax.yaxis.set_major_formatter(ymajorFormatter)
data = np.array(data)
candlestick_ochl(ax,data,width=0.6,colordown=u'g',colorup=u'r')
ax.xaxis_date()
ax.autoscale_view()
fig.autofmt_xdate()
plt.show()
def candlestick_chart(self, time_series, interval=40, show=False, filename='candlestick.png', volume_overlay=None):
tz = get_localzone()
adjusted_time_series = []
for item in time_series:
item[0] = epoch2num(item[0])
adjusted_time_series.append(item)
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_formatter(self._date_formatter(interval, tz=tz))
days_interval = interval / 86400.0
candlestick_ochl(ax, adjusted_time_series, width=(days_interval), colorup='green', colordown='red', alpha=0.9)
ax.xaxis_date(tz=tz.zone)
ax.autoscale_view()
yticks = ax.get_yticks()
x_start = min(yticks) - ((max(yticks) - min(yticks)) * 0.60)
plt.ylim([x_start,max(yticks)])
ax.grid(True)
plt.setp( plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
if volume_overlay != None:
# Add a seconds axis for the volume overlay
ax2 = ax.twinx()
yticks = ax.get_yticks()
print('yticks', yticks)
# set the position of ax2 so that it is short (y2=0.32) but otherwise the same size as ax
ax2.set_position(matplotlib.transforms.Bbox([[0.125,0.2],[0.9,0.42]]))
#print(days_interval * len(adjusted_time_series))
#ax2.set_position([0.125, 0.2, 0.8, 0.2])
# get data from candlesticks for a bar plot
dates = [x[0] for x in adjusted_time_series]
dates = np.asarray(dates)
volume = [x[1] for x in volume_overlay]
volume = np.asarray(volume)
ax2.bar(dates,volume,color='#aaaaaa',width=(days_interval),align='center',linewidth=0.0,alpha=0.8)
#scale the x-axis tight
#ax2.set_xlim(min(dates),max(dates))
# the y-ticks for the bar were too dense, keep only every third one
ax2yticks = ax2.get_yticks()
#print('yticks', ax2yticks)
#print('yticks2', ax2yticks[::3])
ax2.set_yticks(ax2yticks[::3])
ax2.yaxis.set_label_position("right")
ax2.set_ylabel('Volume', size=20)
# format the x-ticks with a human-readable date.
#xt = ax.get_xticks()
#new_xticks = [datetime.date.isoformat(num2date(d)) for d in xt]
#ax.set_xticklabels(new_xticks,rotation=45, horizontalalignment='right')
if show:
plt.show()
else:
plt.savefig(const.DATA_DIR + '/' + filename, bbox_inches='tight')
plt.close()
def sample_513():
"""
5.1.3 k线图的绘制
:return:
"""
import matplotlib.finance as mpf
__colorup__ = "red"
__colordown__ = "green"
# 为了示例清晰，只拿出前30天的交易数据绘制蜡烛图，
tsla_part_df = tsla_df[:30]
fig, ax = plt.subplots(figsize=(14, 7))
qutotes = []
for index, (d, o, c, h, l) in enumerate(
zip(tsla_part_df.index, tsla_part_df.open, tsla_part_df.close,
tsla_part_df.high, tsla_part_df.low)):
# 蜡烛图的日期要使用matplotlib.finance.date2num进行转换为特有的数字值
d = mpf.date2num(d)
# 日期，开盘，收盘，最高，最低组成tuple对象val
val = (d, o, c, h, l)
# 加val加入qutotes
qutotes.append(val)
# 使用mpf.candlestick_ochl进行蜡烛绘制，ochl代表：open，close，high，low
mpf.candlestick_ochl(ax,
qutotes,
width=0.6,
colorup=__colorup__,
colordown=__colordown__)
ax.autoscale_view()
ax.xaxis_date()
plt.show()
def weekday_candlestick(ohlc_data, ax, fmt='%b %d', freq=7, **kwargs):
""" Wrapper function for matplotlib.finance.candlestick_ohlc
that artificially spaces data to avoid gaps from weekends """
# Convert data to numpy array
ohlc_data_arr = np.array(ohlc_data)
ohlc_data_arr2 = np.hstack([
np.arange(ohlc_data_arr[:, 0].size)[:, np.newaxis], ohlc_data_arr[:,
1:]
])
ndays = ohlc_data_arr2[:, 0] # array([0, 1, 2, ... n-2, n-1, n])
# Convert matplotlib date numbers to strings based on `fmt`
dates = mdates.num2date(ohlc_data_arr[:, 0])
date_strings = []
for date in dates:
date_strings.append(date.strftime(fmt))
# Plot candlestick chart
candlestick_ochl(ax, ohlc_data_arr2, **kwargs)
# Format x axis
ax.set_xticks(ndays[::freq])
ax.set_xticklabels(date_strings[::freq], rotation=45, ha='right')
ax.set_xlim(ndays.min(), ndays.max())
plt.show()
def plot_k_line(data):
"""
data为dataframe格式，第一列为时间，第二到5列为ochl
"""
import numpy as np
import pandas as pd
import datetime as dt
import talib
from matplotlib.pylab import date2num
import matplotlib.pyplot as plt
import matplotlib.finance as mpf
def date_to_num(dates):
num_time = []
for date in dates:
date_time = dt.datetime.strptime(date, '%Y-%m-%d')
num_date = date2num(date_time)
num_time.append(num_date)
return num_time
data['date'] = date_to_num(data['date'])
data = data.values
#成交量
fig, (ax1, ax2) = plt.subplots(2, sharex=True, figsize=(15, 5))
mpf.candlestick_ochl(ax1, data, width=1.0, colorup='g', colordown='r')
ax1.set_title('nyang')
ax1.set_ylabel('Price')
ax1.grid(True)
ax1.xaxis_date()
plt.bar(data[:, 0] - 0.25, data[:, 5], width=0.5)
ax2.set_ylabel('Volume')
ax2.grid(True)
plt.show()
def sample_513():
"""
5.1.3 k线图的绘制
:return:
"""
import matplotlib.finance as mpf
__colorup__ = "red"
__colordown__ = "green"
# 为了示例清晰，只拿出前30天的交易数据绘制蜡烛图，
tsla_part_df = tsla_df[:30]
fig, ax = plt.subplots(figsize=(14, 7))
qutotes = []
for index, (d, o, c, h, l) in enumerate(
zip(tsla_part_df.index, tsla_part_df.open, tsla_part_df.close,
tsla_part_df.high, tsla_part_df.low)):
# 蜡烛图的日期要使用matplotlib.finance.date2num进行转换为特有的数字值
d = mpf.date2num(d)
# 日期，开盘，收盘，最高，最低组成tuple对象val
val = (d, o, c, h, l)
# 加val加入qutotes
qutotes.append(val)
# 使用mpf.candlestick_ochl进行蜡烛绘制，ochl代表：open，close，high，low
mpf.candlestick_ochl(ax, qutotes, width=0.6, colorup=__colorup__,
colordown=__colordown__)
ax.autoscale_view()
ax.xaxis_date()
plt.show()
def Kline_plot(raw_data):
#raw_data = ts.get_hist_data('hs300', start='2015-07-01')
#raw_data.index = raw_data.index.map(str2date)
raw_data['time'] = raw_data.index
data = DataFrame(raw_data,
columns=['time', 'open', 'close', 'high', 'low'])
alldays = DayLocator()
months = MonthLocator()
weekdays = WeekdayLocator()
month_formater = DateFormatter("%b %Y")
week_formater = DateFormatter("%m %d")
ymajorLocator = MultipleLocator(100) #将y轴主刻度标签设置为0.5的倍数
ymajorFormatter = FormatStrFormatter('%1.1f') #设置y轴标签文本的格式
yminorLocator = MultipleLocator(10) #将此y轴次刻度标签设置为0.1的倍数
fig = plt.figure()
ax = fig.add_subplot(111)
ax.xaxis.set_major_locator(weekdays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(week_formater)
ax.yaxis.set_major_locator(ymajorLocator)
ax.yaxis.set_major_formatter(ymajorFormatter)
data = np.array(data)
candlestick_ochl(ax, data, width=0.6, colordown=u'g', colorup=u'r')
ax.xaxis_date()
ax.autoscale_view()
fig.autofmt_xdate()
plt.show()
def plotcandle(dateochl):
larray = np.asarray(dateochl)
fig = plt.figure()
ax1 = plt.subplot2grid((1, 1), (0, 0))
fnplot.candlestick_ochl(ax1,larray.tolist())
plt.show()
def plt_chart_move_avrg(chart, path=os.path.join(os.getcwd(), "tmp")):
df_tmp_full = chart.sort_values(by=["date"], ascending=True)
df_tmp = df_tmp_full.ix[:, [
'open_price', 'close_price', 'high_price', 'low_price'
]]
move_avrg_lst = [5, 10, 20, 40, 80]
fig = plt.figure()
ax = plt.subplot()
xdate = [x for x in df_tmp_full.date] # 日付
ochl = np.vstack((date2num(xdate), df_tmp.values.T)).T
mpf.candlestick_ochl(ax, ochl, width=0.7, colorup='g', colordown='r')
ax.grid() # グリッド表示
ax.set_xlim(df_tmp_full.iloc[0].date, df_tmp_full.iloc[-1].date) # x軸の範囲
fig.autofmt_xdate() # x軸のオートフォーマット
for day in move_avrg_lst:
tmp_chart = chart.loc[:,
["date", "move_avrg_" + str(day)]].sort_values(
by=["date"], ascending=True).copy()
print(tmp_chart)
ax.grid() # グリッド表示
ax.set_xlim(tmp_chart["date"].values[0],
tmp_chart["date"].values[-1]) # x軸の範囲
fig.autofmt_xdate() # x軸のオートフォーマット
plt.plot(tmp_chart["date"],
tmp_chart["move_avrg_" + str(day)],
label="day-" + str(day))
plt.legend()
plt.savefig(os.path.join(path, chart["stock_id"].values[0] +
'_chart.png')) #画像保存
def getcandlecharts(codes):
chinese = mpl.font_manager.FontProperties(
fname='C:\Windows\Fonts\simhei.ttf')
plt.figure(figsize=(10, 8), facecolor='w')
index = 1
for code in codes:
print(code)
shyh = ts.get_k_data(code)
mat_shyh = shyh.as_matrix()
num_time = date_to_num(mat_shyh[:, 0])
mat_shyh[:, 0] = num_time
ax = plt.subplot(4, 4, index)
mpf.candlestick_ochl(ax,
mat_shyh,
width=0.6,
colorup="r",
colordown="g",
alpha=1.0)
plt.grid(True)
plt.xticks(rotation=30)
plt.title('%s: %.2f' % (getstockinfo(code), codes[code]),
fontproperties=chinese)
plt.xlabel("Date")
plt.ylabel("Price")
ax.xaxis_date()
index = index + 1
if index == 16:
break
plt.suptitle('2015-10-01之后上市总市值超过400亿人民币的股票', fontproperties=chinese)
plt.tight_layout(1.5)
plt.subplots_adjust(top=0.92)
plt.show()
def getcandlechart(code):
# date = time.strftime('%Y-%m-%d',time.localtime(time.time()))
# realmarket = ts.get_k_data(code=code, start="2018-05-02")
# print(realmarket)
shyh = ts.get_k_data(code)
print(shyh)
mat_shyh = shyh.as_matrix()
num_time = date_to_num(mat_shyh[:, 0])
mat_shyh[:, 0] = num_time
# print(mat_shyh[:3])
fig, ax = plt.subplots(figsize=(10, 5))
fig.subplots_adjust(bottom=0.5)
mpf.candlestick_ochl(ax,
mat_shyh,
width=0.6,
colorup="r",
colordown="g",
alpha=1.0)
chinese = mpl.font_manager.FontProperties(
fname='C:\Windows\Fonts\simhei.ttf')
plt.grid(True)
plt.xticks(rotation=30)
# plt.title(getstockinfo(code))
plt.title(getstockinfo(code), fontproperties=chinese)
plt.xlabel("Date")
plt.ylabel("Price")
ax.xaxis_date()
plt.show()
def PlotIt(self):
# 画图
self.ax.cla()
self.ax2.cla()
finan.candlestick_ochl(self.ax, self.data, colorup=u'r', colordown=u'g',
alpha=0.5)
self.ax.set_ylim(min(self.Df[:, 3]) * 0.9, max(self.Df[:, 2]) * 1.1)
self.ax.plot(self.riqi, self.MA5)
# 标注买入标志
for xu, index in enumerate(self.Buyindex):
if xu > 0:
if index == oldindex:
LocPlace += self.Df[index, 3] * 0.02
else:
oldindex = index
LocPlace = self.Df[index, 3]
else:
oldindex = index
LocPlace = self.Df[index, 3]
self.ax.text(index, LocPlace, str(self.Buy[xu]), color='b',
fontsize=10)
# 标注卖出标志
for xu, index in enumerate(self.Sellindex):
if xu > 0:
if index == oldindex:
LocPlace += 0.02 * self.Df[index, 2]
else:
oldindex = index
LocPlace = self.Df[index, 2]
else:
oldindex = index
LocPlace = self.Df[index, 2]
self.ax.text(index, LocPlace, str(self.Sell[xu]), color='k',
fontsize=10)
if len(self.Kongji) > 0:
self.title = ",".join(self.Kongji) + u" 无历史数据，已跳过\n" \
+ self.stocklist[self.index] + self.Leibie[0][0] + " " \
+ self.Leibie[0][1] + " " + str(self.index)
else:
self.title = self.Leibie[0][0] + " " + self.Leibie[0][
1] + " " + str(self.index)
self.fig.suptitle(self.title)
self.ax2.bar(self.riqi[self.pos], self.volume[self.pos], color='r',
width=1, align='center')
self.ax2.bar(self.riqi[self.neg], self.volume[self.neg], color='g',
width=1, align='center')
self.ax2.bar(self.riqi[self.neu], self.volume[self.neu], color='b',
width=1, align='center')
self.ax2.set_ylim(0, max(self.volume) + 1)
self.ax2.set_xlim(0, self.InfoRow + 1)
self.fig.canvas.draw()
def drawData(ax, _data):
"""
使用柱状图表示股市数据
"""
candlestick_ochl(ax,
_data[["date2num", "open_price", "close_price", "high_price", "low_price"]].values,
colorup="r", colordown="g", width=0.5)
ax.xaxis.set_major_locator(YearLocator())
ax.xaxis.set_major_formatter(DateFormatter('%Y'))
return ax
def draw_candlestick(self, symbol): """NOTE: Too much points in the timeseries may produce a blank plot. """ data = symbol.get_ochlv() ax = plt.subplot(111) fin.candlestick_ochl(ax, data, width=0.5, colorup=u'g', colordown=u'r', alpha=1.0) ax.xaxis_date() ax.autoscale_view()
def plot(mat_wdyx):
fig, (ax1, ax2) = plt.subplots(2, sharex=True, figsize=(15,8))
mpf.candlestick_ochl(ax1, mat_wdyx, width=1.0, colorup = 'g', colordown = 'r')
ax1.set_title('wandayuanxian')
ax1.set_ylabel('Price')
ax1.grid(True)
ax1.xaxis_date()
plt.bar(mat_wdyx[:,0]-0.25, mat_wdyx[:,5], width= 0.5)
ax2.set_ylabel('Volume')
ax2.grid(True)
return fig
def some_tt(start,end,sh):
fig = plt.figure()
ax = fig.add_subplot(111)
plt.grid()
sh.index = sh['date']
sh_data = sh[start:end]
#.loc[row_indexer,col_indexer] = value instead
sh_data['time'] = sh_data['date'].map(date2num)
df = DataFrame(sh_data, columns=['time', 'open','close','high','low'])
df = np.array(df)
candlestick_ochl(ax,df,width=0.6,colordown=u'g',colorup=u'r')
ax.set_title('Some Test')
ax.xaxis_date()
plt.show()
def some_tt(start, end, sh):
fig = plt.figure()
ax = fig.add_subplot(111)
plt.grid()
sh.index = sh['date']
sh_data = sh[start:end]
#.loc[row_indexer,col_indexer] = value instead
sh_data['time'] = sh_data['date'].map(date2num)
df = DataFrame(sh_data, columns=['time', 'open', 'close', 'high', 'low'])
df = np.array(df)
candlestick_ochl(ax, df, width=0.6, colordown=u'g', colorup=u'r')
ax.set_title('Some Test')
ax.xaxis_date()
plt.show()
def plot_candlestick(frame, ylabel='BTC/USD', candle_width=1.0, freq='1M'):
"""
Plot candlestick graph.
@param frame: bitcoin OHLC data frame to be plotted.
@param ylabel: label on the y axis.
@param candle_width: width of the candles in days.
@param freq: frequency of the plotted x labels.
"""
candlesticks = list(zip(
date2num(frame.index._mpl_repr()),
frame['open'],
frame['close'],
frame['high'],
frame['low'],
frame['amount']))
# Figure
ax0 = plt.subplot2grid((3,1), (0,0), rowspan=2)
ax1 = plt.subplot2grid((3,1), (2,0), rowspan=1, sharex=ax0)
plt.subplots_adjust(bottom=0.15)
plt.setp(ax0.get_xticklabels(), visible=False)
ax0.grid(True)
ax0.set_ylabel(ylabel, size=20)
# Candlestick
candlestick_ochl(ax0, candlesticks,
width=0.5*candle_width,
colorup='g', colordown='r')
# Get data from candlesticks for a bar plot
dates = np.asarray([x[0] for x in candlesticks])
volume = np.asarray([x[5] for x in candlesticks])
# Make bar plots and color differently depending on up/down for the day
pos = np.nonzero(frame['close'] - frame['open'] > 0)
neg = np.nonzero(frame['open'] - frame['close'] > 0)
ax1.grid(True)
ax1.bar(dates[pos], volume[pos], color='g', width=candle_width, align='center')
ax1.bar(dates[neg], volume[neg], color='r', width=candle_width, align='center')
# Scale the x-axis tight
ax1.set_xlim(min(dates),max(dates))
ax1.set_ylabel('VOLUME', size=20)
# Format the x-ticks with a human-readable date.
xt = [date2num(date) for date in pd.date_range(
start=min(frame.index),
end=max(frame.index),
freq=freq)]
ax1.set_xticks(xt)
xt_labels = [num2date(d).strftime('%Y-%m-%d\n%H:%M:%S') for d in xt]
ax1.set_xticklabels(xt_labels,rotation=45, horizontalalignment='right')
# Plot
plt.show()
return (ax0, ax1)
def draw_candlestick(quotes):
"""docstring for draw_candlestick"""
COLORUP = 'red'
COLORDOWN = 'green'
WIDTH = 0.6
fig, axes = plt.subplots(figsize=(18, 7))
candlestick_ochl(axes,
zip(mdates.date2num(quotes.index.to_pydatetime()),
quotes['open'], quotes['high'], quotes['low'],
quotes['close']),
width=WIDTH,
colorup=COLORUP,
colordown=COLORDOWN)
axes.autoscale_view()
def add_chart(self,
technical_indicator,
row=1,
plot_type='line',
color='blue'):
"""
This function adds a chart to the current figure.
"""
axes = self.current_figure.add_subplot(self.figure_rows,
1,
row,
sharex=self.figure_first_ax)
if self.figure_first_ax is None:
self.figure_first_ax = axes
try:
# Only works with ScalarFormatter
axes.ticklabel_format(style='plain')
except AttributeError:
# Ignore on error
pass
if isinstance(technical_indicator, symbol_list.Symbol): # Candlesticks
axes.set_title(str(technical_indicator))
axes.set_ylabel('Price')
cols = [
'DATE', technical_indicator.open, technical_indicator.close,
technical_indicator.high, technical_indicator.low
]
candlestick_ochl(axes, self.data_frame[cols].values, colorup=u'g')
self.add_actions(technical_indicator, axes)
else:
if not isinstance(technical_indicator, str):
# Probably forgot to submit the TI value
technical_indicator = technical_indicator.value
values = self.data_frame[str(technical_indicator)]
axes.set_title(technical_indicator)
axes.set_ylabel('Value')
if plot_type == 'line':
line, = axes.plot(self.data_frame['DATE'], values, color=color)
self.legend.append(line)
else:
bars = axes.bar(self.data_frame['DATE'],
values,
color=color,
width=0.3)
self.legend.append(bars)
self.legend_labels.append(technical_indicator)
axes.xaxis_date()
axes.autoscale_view()
def draw_k_v(self):
fig, (ax1, ax2) = plt.subplots(2, sharex=True, figsize=(15, 8))
mpf.candlestick_ochl(ax1,
self.mat_data,
width=0.5,
colorup='r',
colordown='k')
ax1.set_title(self.name + ':' + self.code)
ax1.set_ylabel('Price')
ax1.grid(True)
ax1.xaxis_date()
plt.bar(self.mat_data[:, 0], self.mat_data[:, 5],
width=0.5) # ? mat_data[:,0] - 0.25
ax2.set_ylabel('Volume')
ax2.grid(True)
plt.show()
def drawData(ohlcv, macd, trade_loop_back, pdays):
dif = macd['dif']
dea = macd['dea']
bar = macd['bar']
fig, axs = plt.subplots(nrows=3,
ncols=1,
facecolor=(0.5, 0.5, 0.5),
figsize=(14, 7))
draw1, draw2, draw3 = axs.ravel()
# 可视化profit_array
draw1.plot(np.array(trade_loop_back.profit_array).cumsum(),
label='profit_array')
# #print(trade_loop_back.days_array)
#
#可视化K线和交易日
qutotes = []
for index, (d, o, c, h, l) in enumerate(
zip(ohlcv.index, ohlcv.open, ohlcv.close, ohlcv.highest,
ohlcv.lowest)):
d = mpf.date2num(d)
val = (d, o, c, h, l)
qutotes.append(val)
mpf.candlestick_ochl(draw2,
qutotes,
width=0.4,
colorup="green",
colordown="red")
#draw2.autoscale_view()
#draw2.xaxis_date()
act = pdays[(pdays.stock - pdays.shift(1).stock) != 0]
# draw2.axvline(np.array([736875, 736876]), label = 'buy', color="green")
# for index, line in act[act.stock == 1].date:
# draw2.axvline(qutotes[index][0], label = 'buy', color="green")
# for index, line in act[act.stock == 0].date:
# draw2.axvline(qutotes[index][0], label = 'sell', color="red")
# draw2.axvline(np.float32(act[act.stock == 1].date), label = 'buy', color="green")
# draw2.axvline(np.float32(act[act.stock == 0].date), label = 'sell', color="red")
draw3.plot(ohlcv.index, dif, label='macd dif')
draw3.plot(ohlcv.index, dea, label='signal dea')
bar_red = np.where(bar > 0, bar, 0)
bar_green = np.where(bar < 0, bar, 0)
draw3.bar(ohlcv.index, bar_red, facecolor='red', label='hist bar')
draw3.bar(ohlcv.index, bar_green, facecolor='green', label='hist bar')
draw3.legend(loc='best')
plt.show()
def kline_imgs(input_df, stock_dir, image_save=False):
price_df = input_df.loc[:, ['date', 'open', 'close', 'high', 'low']]
date_se = input_df.loc[:, 'date'][19:]
num_imgs = price_df.shape[0] - 20 + 1
# TODO 相对位置
# price_max = price_df.max()
# price_min = price_df.min()
plt.grid(False)
# 用来储存imgs
imgs_arr = np.zeros(shape=(num_imgs, 224, 224, 3))
for num in range(num_imgs):
begin_idx = num
end_idx = num + 19
date = str(date_se[end_idx])[:10]
year = date[:4]
img_path = stock_dir + '/' + year + '/' + date + '.png'
img_df = price_df.iloc[begin_idx:end_idx + 1]
# 图像不标注日期，为了使k线连续，改为连续的数字即可（int或float都可以？）
img_df['date'] = range(20)
if image_save:
# 开始作图
fig, ax = plt.subplots()
candlestick_ochl(ax, img_df.values, colorup='g', colordown='r')
ax.set_xticks([])
ax.set_yticks([])
fig.set_size_inches(2.24 / 3, 2.24 / 3)
ax.set_facecolor('black')
fig.set_facecolor('black')
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.gca().yaxis.set_major_locator(plt.NullLocator())
plt.subplots_adjust(top=1,
bottom=0,
right=1,
left=0,
hspace=0,
wspace=0)
plt.margins(0.1, 0.1)
fig.savefig(img_path,
format='png',
facecolor='black',
dpi=300,
pad_inches=0)
plt.close('all')
imgs_arr[num] = np.array(Image.open(img_path).convert(mode='RGB'))
# imgs_arr包含最后一天,最后一天没有label,去掉
return imgs_arr[:-1]
def draw_k(self):
fig, ax = plt.subplots(figsize=(15, 5))
fig.subplots_adjust(bottom=0.5)
mpf.candlestick_ochl(ax,
self.mat_data,
width=0.6,
colorup='r',
colordown='k',
alpha=1.0)
#candlestick_ochl : time must be in float days format - see date2num
plt.grid(True)
plt.xticks(rotation=30) # 设置日期刻度旋转的角度
plt.title(self.name + ':' + self.code)
plt.xlabel('Date')
plt.ylabel('Price')
# x轴的刻度为日期
ax.xaxis_date()
plt.show()
def draw_k_svg(id_str,from_date_str,to_date_str):
u"""
Parameters:
id_str (str): - 6位数的上证股票编号
from_date_str (str): - '2016-6-20'形式的日期数据,表示起始日期
to_date_str (str): - '2016-6-20'形式的日期数据,表示结束日期
Returns:
str : - svg的字符串内容
"""
#设置x轴坐标刻度
mondays = WeekdayLocator(MONDAY) # 主要刻度
alldays = DayLocator() # 次要刻度
mondayFormatter = DateFormatter('%m-%d-%Y') # 如：2-29-2015
dayFormatter = DateFormatter('%d')
from_date = tuple((int(i) for i in from_date_str.strip().split("-")))
to_date = tuple((int(i) for i in to_date_str.strip().split("-")))
quotes_ochl = quotes_historical_yahoo_ochl(id_str+'.ss', from_date ,to_date)
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(mondayFormatter)
candlestick_ochl(ax, quotes_ochl, width=0.6, colorup='r', colordown='g')
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
ax.grid(True)
plt.title(symbol_dict.get(id_str,u"未知"))
f = BytesIO()
plt.savefig("ts_o.svg", format="svg")
plt.savefig(f, format="svg")
value = f.getvalue()
result = deal_with_svg(f)
f.close()
return result
def main():
hb = ccxt.huobipro()
hb.proxies = {
'http': 'http://127.0.0.1:8123',
'https': 'http://127.0.0.1:8123',
}
data = hb.fetch_ohlcv('BTC/USDT', '15m')
arr = np.array(data)
ohlcv = pd.DataFrame(arr,
columns=('time', 'open', 'highest', 'lowest', 'close',
'volume'))
ohlcv = ohlcv.sort_index(by='time')
timeIndex = pd.date_range(time.strftime(
'%Y-%m-%d %H:%M:%S', time.localtime(int(ohlcv.head(1).time) / 1000)),
periods=ohlcv.shape[0],
freq='15m')
ohlcv.index = timeIndex
dif, dea, bar = talib.MACD(ohlcv.close,
fastperiod=12,
slowperiod=26,
signalperiod=9)
fig, axs = plt.subplots(figsize=(14, 7))
#可视化K线和交易日
qutotes = []
for index, (d, o, c, h, l) in enumerate(
zip(ohlcv.index, ohlcv.open, ohlcv.close, ohlcv.highest,
ohlcv.lowest)):
print(d)
d = mpf.date2num(d)
print(d)
val = (d, o, c, h, l)
qutotes.append(val)
mpf.candlestick_ochl(axs,
qutotes,
width=1,
colorup="green",
colordown="red")
print(qutotes)
axs.autoscale_view()
#axs.xaxis_date()#仅日线时使用
plt.show()
def graph_data(stock):
fig = plt.figure()
ax1 = plt.subplot2grid(shape=(1, 1), loc=(0, 0))
stock_price_url = 'http://chartapi.finance.yahoo.com/instrument/1.0/' + \
stock + '/chartdata;type=quote;range=3m/csv'
source_code = urllib.request.urlopen(stock_price_url).read().decode()
stock_data = []
split_source = source_code.split('\n')
for line in split_source:
if len(line.split(',')) == 6 and 'values' not in line:
stock_data.append(line)
date, close_price, high_price, low_price, open_price, volume = np.loadtxt(
stock_data,
dtype=np.float,
delimiter=',',
unpack=True,
converters={0: bytespdate2num('%Y%m%d')})
x = 0
y = len(date)
ohlc = []
while x < y:
append_me = date[x], open_price[x], high_price[x], low_price[x], \
close_price[x], volume[x]
ohlc.append(append_me)
x += 1
candlestick_ochl(ax1, ohlc, width=0.4, colorup='g',
colordown='r') # can use hex colors
for label in ax1.xaxis.get_ticklabels():
label.set_rotation(45)
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
plt.xlabel('date')
plt.ylabel('price')
plt.title('Stock')
plt.legend()
plt.show()
def draw_tianbijun(stock):
'''
先画田碧君的趋势图片
K线以及公式图片一起画
'''
dl = DownLoad()
raw_data = dl.load_data(stock)
#raw_data.index = raw_data.index.map(str2date2)
H1 = ta.MA(np.asarray(raw_data['close']), timeperiod=8,
matype=1) #8日指数平滑均线
H2 = ta.MA(H1, timeperiod=20, matype=1)
H3 = ta.MA(np.asarray(raw_data['close']), timeperiod=8, matype=3) #8日 DEMA
H4 = ta.MA(H3, timeperiod=20, matype=1)
H5 = ta.MA(np.asarray(raw_data['close']), timeperiod=8, matype=4) #8日 DEMA
H6 = ta.MA(H5, timeperiod=20, matype=1)
#LH = ta.MA(np.asarray(raw_data['close']), timeperiod=240, matype=1) #240指数平滑均线
#high_price = ta.MAX(np.asarray(raw_data['high']), timeperiod=36)
#VAR1 = (high_price - np.asarray(raw_data['close'])) / (high_price - ta.MIN(np.asarray(raw_data['high']), timeperiod=36)) * 100
#VAR2 = ta.MA(VAR1, timeperiod=5)
#VAR3 = ta.MA(VAR2,timeperiod=8)
length = -100
fig = plt.figure()
ax = fig.add_subplot(111)
raw_data['time'] = raw_data['date'].map(date2num)
data = DataFrame(raw_data,
columns=['time', 'open', 'close', 'high', 'low'])
data = np.array(data)
candlestick_ochl(ax,
data[length:],
width=0.6,
colordown=u'g',
colorup=u'r')
plt.grid()
plt.plot(raw_data['date'][length:], H1[length:], color='r', label='H1')
#plt.plot(raw_data['date'][length:], H3[length:],color='y',label='H3')
#plt.plot(raw_data['date'][length:], H5[length:],color='k',label='H3')
plt.plot(raw_data['date'][length:], H2[length:], color='g',
label='H2') #没能解决中间周六周天节假日数据问题
plt.show()
def add_chart(self, technical_indicator, row=1, plot_type='line', color='blue'):
"""
This function adds a chart to the current figure.
"""
axes = self.current_figure.add_subplot(self.figure_rows,
1,
row,
sharex=self.figure_first_ax)
if self.figure_first_ax is None:
self.figure_first_ax = axes
try:
# Only works with ScalarFormatter
axes.ticklabel_format(style='plain')
except AttributeError:
# Ignore on error
pass
if isinstance(technical_indicator, symbol_list.Symbol): # Candlesticks
axes.set_title(str(technical_indicator))
axes.set_ylabel('Price')
cols = ['DATE',
technical_indicator.open,
technical_indicator.close,
technical_indicator.high,
technical_indicator.low]
candlestick_ochl(axes, self.data_frame[cols].values, colorup=u'g')
self.add_actions(technical_indicator, axes)
else:
if not isinstance(technical_indicator, str):
# Probably forgot to submit the TI value
technical_indicator = technical_indicator.value
values = self.data_frame[str(technical_indicator)]
axes.set_title(technical_indicator)
axes.set_ylabel('Value')
if plot_type == 'line':
line, = axes.plot(self.data_frame['DATE'], values, color=color)
self.legend.append(line)
else:
bars = axes.bar(self.data_frame['DATE'], values, color=color, width=0.3)
self.legend.append(bars)
self.legend_labels.append(technical_indicator)
axes.xaxis_date()
axes.autoscale_view()
def generateGraph(self, quotes):
self.clearGraphData()
self.ax = self.fig.add_subplot(111)
self.ax.set_title(_("Session candlestick graph"))
#Set axis labels and grid overlay properites
self.ax.set_xlabel(_("Sessions"), fontsize=12)
self.ax.set_ylabel("$", fontsize=12)
self.ax.grid(color='g', linestyle=':', linewidth=0.2)
candlestick_ochl(self.ax,
quotes,
width=0.50,
colordown='r',
colorup='g',
alpha=1.00)
self.graphBox.layout().addWidget(self.canvas)
self.canvas.draw()
def candle_print(symbol, nmin, start, end):
db = conn['Ctp_Bar_{}'.format(nmin)]
coll = db[symbol]
rs = coll.find({'datetime': {'$gte': parse(start), '$lt': parse(end)}}).sort('datetime', 1)
rs = list(rs)
df = pd.DataFrame(rs)
print 'bar count:', len(df)
if not len(df):
return
fields = ['datetime', 'open', 'close', 'high', 'low', 'volume', 'symbol', 'openInterest', ]
fields = ['datetime', 'open', 'close', 'high', 'low', 'volume', 'openInterest']
df = df[fields]
# data = df.as_matrix()
data = df.values
# write into file
df.to_csv('{}-{}-{}-{}.csv'.format(symbol, nmin, start, end))
def date_to_num(dates):
num_time = []
for date in dates:
num_date = mpl.dates.date2num(date)
num_time.append(num_date)
return num_time
# xx = date_to_num(data[:,0])
data[:, 0] = range(0, len(data))
fig, ax = plt.subplots(figsize=(15, 8))
fig.subplots_adjust(bottom=0.5)
# ax.set_xticks(range(0,len(data)))
mpf.candlestick_ochl(ax, data, width=0.6, colorup='r', colordown='g', alpha=1.0)
plt.grid(True)
# 设置日期刻度旋转的角度
plt.xticks(rotation=30)
plt.title(symbol + ' bar:' + nmin)
plt.xlabel('Date')
plt.ylabel('Price')
def kline_imgs(input_df, stock_dir, image_save=False, img_shape=(112, 112)):
price_df = input_df.loc[:, ['date', 'open', 'close', 'high', 'low']]
date_se = input_df.loc[:, 'date'][19:]
num_imgs = price_df.shape[0] - 20 + 1
# TODO 相对位置
# price_max = price_df.max()
# price_min = price_df.min()
plt.grid(False)
# 用来储存imgs
row_pix, col_pix = img_shape
imgs_arr = np.zeros(shape=(num_imgs, row_pix, col_pix, 3), dtype='uint8')
bar = ProgressBar(total=num_imgs)
for num in range(num_imgs):
begin_idx = num
end_idx = num + 19
date = str(date_se[end_idx])[:10]
year = date[:4]
img_path = stock_dir + '/' + year + '/' + date + '.png'
img_df = pd.DataFrame(price_df.iloc[begin_idx:end_idx + 1])
# 图像不标注日期，为了使k线连续，改为连续的数字即可（int或float都可以？）
img_df.loc[:, 'date'] = list(range(20))
if image_save:
# 开始作图
fig, ax = plt.subplots()
candlestick_ochl(ax, img_df.values, width=0.005, colorup='g', colordown='r')
ax.set_xticks([])
ax.set_yticks([])
fig.set_size_inches(row_pix / 300, col_pix / 300)
ax.set_facecolor('black')
fig.set_facecolor('black')
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.gca().yaxis.set_major_locator(plt.NullLocator())
plt.subplots_adjust(top=1, bottom=0, right=1, left=0, hspace=0, wspace=0)
plt.margins(0.1, 0.1)
fig.savefig(img_path, format='png', facecolor='black', dpi=300, pad_inches=0)
plt.close('all')
imgs_arr[num] = np.array(Image.open(img_path).convert(mode='RGB'))
bar.move()
bar.log('generating kline imgs')
# imgs_arr不包含前19天
return imgs_arr
def pancan(*args):
if args[0] is not None:
symbol = args[0]
else:
symbol = "GOOG"
# get the data on a symbol
data = get_data_yahoo(symbol, datetime.now() - timedelta(days=90))
close_price = data['Adj Close']
# format time properly
dates = data.index.to_pydatetime()
times = mdates.date2num(dates)
# make an array of tuples in the specific order needed
q = izip(times, data['Open'], data['Close'], data['High'], data['Low'])
# construct and show the plot
plt.figure(figsize=(10, 4))
ax1 = plt.gca()
ax1.xaxis_date()
candlestick_ochl(ax1, q, width=0.6, colorup='g', colordown='r')
close_price.plot()
plt.savefig("static/candle.png")
plt.clf()
def plot_(self, list):
"""利用plot画K线"""
fig = plt.figure(facecolor='#07000d',
figsize=(self.parameter['ax_width'],
self.parameter['ax_high']))
ax = plt.subplot2grid((6, 4), (1, 0),
rowspan=4,
colspan=4,
axisbg='#07000d')
#fig, ax = plt.subplots(facecolor='#07000d', figsize=(self.parameter['ax_width'], self.parameter['ax_high']))
fig.subplots_adjust(bottom=0.2)
# 设置X轴刻度为日期时间
ax.xaxis_date()
# 设置legend
plt.legend(labels=['a', 'b'], loc='best')
plt.title(u"{}-{} HistSpreadPrice".format(self.histCode1,
self.histCode2),
color='r')
plt.ylabel("spreadPrice")
plt.xticks(rotation=45) # 45°
plt.yticks()
ax.yaxis.label.set_color("b") # Y轴图例文字蓝色
# 边框上色
ax.spines['top'].set_color('#5998ff')
ax.spines['right'].set_color('#5998ff')
ax.spines['left'].set_color("#5998ff")
ax.spines['bottom'].set_color("#5998ff")
ax.tick_params(axis='x', colors='w')
ax.tick_params(axis='y', colors='w')
# ax 绘图Axes的实例
# width 图像中红绿矩形的宽度,代表天数
# alpha 矩形的颜色的透明度
# colorup 收盘价格大于开盘价格时的颜色
mpf.candlestick_ochl(ax,
list,
width=.9,
colorup='g',
colordown='r',
alpha=.9)
plt.grid()
def drawPicture(df):
#绘图部分
candleDf = df.as_matrix()
num_time = exectue.date_to_num(candleDf[:, 0])
candleDf[:, 0] = num_time
fig, ax = plt.subplots(figsize=(20, 5))
fig.subplots_adjust(bottom=0.1)
mpf.candlestick_ochl(ax,
candleDf,
width=1,
colorup='r',
colordown='g',
alpha=1.0)
plt.grid(True)
# 设置日期刻度旋转的角度
plt.xticks(rotation=30)
plt.title(ts_code)
plt.xlabel('Date')
plt.ylabel('Price')
# x轴的刻度为日期
ax.xaxis_date()
def plot(self):
dates = list(map(pltdates.datestr2num, self.dates[:self.position + 1]))
values = zip(dates, self.open[:self.position + 1],
self.close[:self.position + 1],
self.high[:self.position + 1],
self.low[:self.position + 1])
fig, ax = plt.subplots()
fig.subplots_adjust(bottom=0.2)
finance.candlestick_ochl(ax, values, width=60 / 86400)
plt.plot(self.buy_orders['x'], self.buy_orders['y'], 'g^')
plt.plot(self.sell_orders['x'], self.sell_orders['y'], 'rv')
self._plot_indicators(dates)
ax.xaxis_date()
plt.setp(plt.gca().get_xticklabels(),
rotation=45,
horizontalalignment='right')
plt.show()
def draw_result(self, start, end, sh):
fig = plt.figure()
ax = fig.add_subplot(311)
self.raw_data.index = self.raw_data['date']
raw_data = self.raw_data[start:end]
raw_data['time'] = raw_data['date'].map(date2num)
#K线 信号
data = DataFrame(raw_data,
columns=['time', 'open', 'close', 'high', 'low'])
data = np.array(data)
candlestick_ochl(ax, data, width=0.6, colordown=u'g', colorup=u'r')
plt.grid()
plt.plot(raw_data['date'], raw_data['H1'], color='r', label='H1')
plt.plot(raw_data['date'], raw_data['H2'], color='y', label='H2')
#大盘
ax = fig.add_subplot(312)
plt.grid()
sh.index = sh['date']
sh_data = sh[start:end]
sh_data['time'] = sh_data['date'].map(date2num)
df = DataFrame(sh_data,
columns=['time', 'open', 'close', 'high', 'low'])
print df['time']
df = np.array(df)
candlestick_ochl(ax, df, width=0.6, colordown=u'g', colorup=u'r')
#收益图
plt.subplot(3, 1, 3)
plt.grid()
print len(self.money), len(raw_data.index)
plt.plot(raw_data['date'], self.money)
# plt.subplot(3,1,3)
# plt.grid()
# plt.plot(raw_data['date'], raw_data['line1'], color='b',label='line1')
plt.show()
def draw_result(self,start,end,sh):
fig = plt.figure()
ax = fig.add_subplot(311)
self.raw_data.index = self.raw_data['date']
raw_data = self.raw_data[start:end]
raw_data['time'] = raw_data['date'].map(date2num)
#K线 信号
data = DataFrame(raw_data, columns=['time', 'open','close','high','low'])
data = np.array(data)
candlestick_ochl(ax,data,width=0.6,colordown=u'g',colorup=u'r')
plt.grid()
plt.plot(raw_data['date'], raw_data['H1'], color='r',label='H1')
plt.plot(raw_data['date'], raw_data['H2'], color='y',label='H2')
#大盘
ax = fig.add_subplot(312)
plt.grid()
sh.index = sh['date']
sh_data = sh[start:end]
sh_data['time'] = sh_data['date'].map(date2num)
df = DataFrame(sh_data, columns=['time', 'open','close','high','low'])
print df['time']
df = np.array(df)
candlestick_ochl(ax,df,width=0.6,colordown=u'g',colorup=u'r')
#收益图
plt.subplot(3,1,3)
plt.grid()
print len(self.money),len(raw_data.index)
plt.plot(raw_data['date'],self.money)
# plt.subplot(3,1,3)
# plt.grid()
# plt.plot(raw_data['date'], raw_data['line1'], color='b',label='line1')
plt.show()
def draw_tianbijun(stock):
'''
先画田碧君的趋势图片
K线以及公式图片一起画
'''
dl = DownLoad()
raw_data = dl.load_data(stock)
#raw_data.index = raw_data.index.map(str2date2)
H1 = ta.MA(np.asarray(raw_data['close']), timeperiod=8,matype=1) #8日指数平滑均线
H2 = ta.MA(H1, timeperiod=20,matype=1)
H3 = ta.MA(np.asarray(raw_data['close']), timeperiod=8,matype=3) #8日 DEMA
H4 = ta.MA(H3, timeperiod=20,matype=1)
H5 = ta.MA(np.asarray(raw_data['close']), timeperiod=8,matype=4) #8日 DEMA
H6 = ta.MA(H5, timeperiod=20,matype=1)
#LH = ta.MA(np.asarray(raw_data['close']), timeperiod=240, matype=1) #240指数平滑均线
#high_price = ta.MAX(np.asarray(raw_data['high']), timeperiod=36)
#VAR1 = (high_price - np.asarray(raw_data['close'])) / (high_price - ta.MIN(np.asarray(raw_data['high']), timeperiod=36)) * 100
#VAR2 = ta.MA(VAR1, timeperiod=5)
#VAR3 = ta.MA(VAR2,timeperiod=8)
length = -100
fig = plt.figure()
ax = fig.add_subplot(111)
raw_data['time'] = raw_data['date'].map(date2num)
data = DataFrame(raw_data, columns=['time', 'open','close','high','low'])
data = np.array(data)
candlestick_ochl(ax,data[length:],width=0.6,colordown=u'g',colorup=u'r')
plt.grid()
plt.plot(raw_data['date'][length:], H1[length:],color='r',label='H1')
#plt.plot(raw_data['date'][length:], H3[length:],color='y',label='H3')
#plt.plot(raw_data['date'][length:], H5[length:],color='k',label='H3')
plt.plot(raw_data['date'][length:], H2[length:], color='g',label='H2') #没能解决中间周六周天节假日数据问题
plt.show()
def graphData(stockData, color_palette):
date = stockData['date']
openp = stockData['openp']
closep = stockData['closep']
highp = stockData['highp']
lowp = stockData['lowp']
volume = stockData['volume']
# matplotlibs candlecharts uses tuples
x = 0
y = len(date)
candleAr = []
while x < y:
appendLine = date[x],openp[x],closep[x],highp[x],lowp[x]
candleAr.append(appendLine)
x= x+1
# Define colors for plot
bg_color = color_palette['bg_color']
text_color = color_palette['text_color']
spine_color = color_palette['spine_color']
up_color = color_palette['up_color']
down_color = color_palette['down_color']
vol_color = color_palette['vol_color']
# Define figsize and candle width (depends on tick amount)
fig_width = max(min(round(len(date)/10), 14),8)
candle_width = (len(date) < 30)*0.2 + (len(date) < 100)*0.2 + (len(date) < 200)*0.1 + 0.3
# Create figure and axes with dark color
fig = plt.figure(facecolor=bg_color, figsize=(fig_width, 6))
ax1 = plt.subplot2grid((5, 4), (0, 0), rowspan=4, colspan=4, axisbg=bg_color)
ax1.grid(True, color=text_color)
candlestick_ochl(ax1, candleAr, width=candle_width, colorup=up_color, colordown=down_color)
ax1.set_xlabel('Date')
ax1.set_ylabel('Stock price')
ax1.yaxis.label.set_color(text_color)
#Border and tick colors
ax1.spines['bottom'].set_color(spine_color)
ax1.spines['top'].set_color(spine_color)
ax1.spines['left'].set_color(spine_color)
ax1.spines['right'].set_color(spine_color)
ax1.tick_params(axis='y', colors=text_color)
ax1.tick_params(axis='x', colors=text_color)
ax1.xaxis.set_major_formatter(plt.NullFormatter())
ax1.axes.get_xaxis().set_ticklabels([])
ax2 = plt.subplot2grid((5,4), (4,0), rowspan=4, colspan=4, sharex = ax1, axisbg=bg_color)
ax2.plot(date, volume, vol_color, linewidth=.8)
volumeMin = volume.min()
ax2.fill_between(date, volumeMin, volume, facecolor=vol_color, alpha=.5)
ax2.set_ylabel('Volume', color=text_color)
ax2.spines['bottom'].set_color(spine_color)
ax2.spines['top'].set_color(spine_color)
ax2.spines['left'].set_color(spine_color)
ax2.spines['right'].set_color(spine_color)
ax2.tick_params(axis='y', colors=text_color)
ax2.tick_params(axis='x', colors=text_color)
ax2.axes.get_yaxis().set_ticklabels([])
ax2.grid(False)
# For some reason autfill can't recognize this
ax2.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(45)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.subplots_adjust(bottom=.19, left= .09, right=.93, top=.95, wspace=0.2, hspace=.0)
plt.show()
def graph_data(stock):
fig = plt.figure(facecolor='#f0f0f0')
ax1 = plt.subplot2grid(shape=(6, 1), loc=(0, 0), rowspan=1, colspan=1)
plt.title(stock)
plt.ylabel('H-L')
ax2 = plt.subplot2grid(shape=(6, 1), loc=(1, 0), rowspan=4, colspan=1,
sharex=ax1)
plt.ylabel('price')
ax2v = ax2.twinx()
ax3 = plt.subplot2grid(shape=(6, 1), loc=(5, 0), rowspan=1, colspan=1,
sharex=ax1)
plt.ylabel('MAvgs')
stock_price_url = 'http://chartapi.finance.yahoo.com/instrument/1.0/' + \
stock + '/chartdata;type=quote;range=1y/csv'
source_code = urllib.request.urlopen(stock_price_url).read().decode()
stock_data = []
split_source = source_code.split('\n')
for line in split_source:
if len(line.split(',')) == 6 and 'values' not in line:
stock_data.append(line)
date, close_price, high_price, low_price, open_price, volume = np.loadtxt(
stock_data,
dtype=np.float,
delimiter=',',
unpack=True,
converters={0: bytespdate2num('%Y%m%d')})
x = 0
y = len(date)
ohlc = []
while x < y:
append_me = date[x], open_price[x], high_price[x], low_price[x], \
close_price[x], volume[x]
ohlc.append(append_me)
x += 1
ma1 = moving_average(close_price, MA1)
ma2 = moving_average(close_price, MA2)
start = len(date[MA2 - 1:])
h_l = list(map(high_miinus_low, high_price, low_price))
ax1.plot_date(date[-start:], h_l[-start:], '-', label='H-L')
ax1.yaxis.set_major_locator(mticker.MaxNLocator(nbins=5, prune='lower'))
candlestick_ochl(ax2, ohlc[-start:], width=0.4, colorup='g',
colordown='r') # can use hex colors
ax2.grid(True)
bbox_props = dict(boxstyle='round', facecolor='y', edgecolor='k', lw=1)
ax2.annotate(str(close_price[-1]), xy=(date[-1], close_price[-1]),
xytext=(date[-1] + 4, close_price[-1]), bbox=bbox_props)
ax2v.plot([], [], color='#007983', label='Volume', alpha=0.4)
ax2v.fill_between(date[-start:], 0, volume[-start:], facecolor='#007983',
alpha=0.4)
ax2v.axes.yaxis.set_ticklabels([])
ax2v.grid(False)
ax2v.set_ylim(0, 2 * volume.max())
ax2.yaxis.set_major_locator(mticker.MaxNLocator(prune='upper'))
ax2.yaxis.set_major_locator(mticker.MaxNLocator(prune='lower'))
ax3.plot(date[-start:], ma1[-start:], linewidth=1, label=str(MA1) + 'MA')
ax3.plot(date[-start:], ma2[-start:], linewidth=1, label=str(MA2) + 'MA')
ax3.yaxis.set_major_locator(mticker.MaxNLocator(prune='upper', nbins=5))
for label in ax3.xaxis.get_ticklabels():
label.set_rotation(45)
ax3.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax3.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax3.fill_between(date[-start:], ma2[-start:], ma1[-start:],
where=(ma1[-start:] < ma2[-start:]),
facecolor='r', edgecolor='r', alpha=0.5)
ax3.fill_between(date[-start:], ma2[-start:], ma1[-start:],
where=(ma1[-start:] > ma2[-start:]),
facecolor='g', edgecolor='g', alpha=0.5)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.subplots_adjust(left=0.11, bottom=0.24, right=0.90, top=0.90,
wspace=0.2, hspace=0)
ax1.legend()
leg = ax1.legend(loc=9, ncol=1, prop={'size': 11})
leg.get_frame().set_aplha = 0.4
ax2v.legend()
leg = ax2v.legend(loc=9, ncol=1, prop={'size': 11})
leg.get_frame().set_aplha = 0.4
ax3.legend()
leg = ax3.legend(loc=8, ncol=2, prop={'size': 11})
leg.get_frame().set_aplha = 0.4
plt.show()
fig.savefig('google.png', facecolor='#f0f0f0')
#Plotting financial plots
import matplotlib.finance as mpf
start=(2014,5,1)
end=(2014,6,30)
#Get historic prices of German DAX index ^GDAXI
quotes=mpf.quotes_historical_yahoo_ochl('^GDAXI',start,end)
#Data comes out as Open, High,Low,Close,and Volume
quotes[:2]
#Create candlestick plots
fig,ax=plt.subplots(figsize=(7,5))
fig.subplots_adjust(bottom=0.2)
mpf.candlestick_ochl(ax,quotes,width=0.6,colorup='b',colordown='r')
plt.grid(True)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(),rotation=30)
#Create daily summary plots
fig,ax=plt.subplots(figsize=(7,5))
fig.subplots_adjust(bottom=0.2)
mpf.plot_day_summary_oclh(ax,quotes,colorup='b',colordown='r')
plt.grid(True)
ax.xaxis_date()
plt.title('DAX Index')
plt.ylabel('index level')
plt.setp(plt.gca().get_xticklabels(),rotation=30)
def _plot(data, ax, **kwds):
candles = candlestick_ochl(ax, data.values,
**kwds)
return candles
def graphData(stock,MA1,MA2):
stockFile = loadStock(stock)
stockFile = stockFile[1:100]
try:
date, closep, highp, lowp, openp, volume = np.loadtxt(stockFile,delimiter=',', unpack=True,
converters={ 0: bytespdate2num('%Y%m%d')})
x = 0
y = len(date)
newAr = []
while x < y:
appendLine = date[x],openp[x],highp[x],lowp[x],closep[x],volume[x]
newAr.append(appendLine)
x+=1
Av1 = movingaverage(closep, MA1)
Av2 = movingaverage(closep, MA2)
print(closep)
SP = len(date[MA2-1:])
cA,cD = pywt.dwt(closep,'haar')
#SMA
#--------------------------------------
fig = plt.figure(facecolor='#07000d')
ax1 = plt.subplot2grid((6,4), (1,0), rowspan=4, colspan=4, axisbg='#07000d')
candlestick_ochl(ax1, newAr[-SP:], width=.6, colorup='#53c156', colordown='#ff1717')
Label1 = str(MA1)+' SMA'
Label2 = str(MA2)+' SMA'
newDate = date[-SP:]
newDate = newDate[1::2]
ax1.plot(newDate[-SP/2:],cA[-SP/2:],'#e1edf9',label=Label1, linewidth=1.5)
ax1.plot(newDate[-SP/2:],cD[-SP/2:],'#4ee6fd',label=Label2, linewidth=1.5)
ax1.grid(True, color='w')
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax1.yaxis.label.set_color("w")
ax1.spines['bottom'].set_color("#5998ff")
ax1.spines['top'].set_color("#5998ff")
ax1.spines['left'].set_color("#5998ff")
ax1.spines['right'].set_color("#5998ff")
ax1.tick_params(axis='y', colors='w')
plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper'))
ax1.tick_params(axis='x', colors='w')
plt.ylabel('Stock price and Volume')
maLeg = plt.legend(loc=9, ncol=2, prop={'size':7},
fancybox=True, borderaxespad=0.)
maLeg.get_frame().set_alpha(0.4)
textEd = pylab.gca().get_legend().get_texts()
pylab.setp(textEd[0:5], color = 'w')
ax1.yaxis.set_major_locator(mticker.MaxNLocator(nbins=5, prune='upper'))
for label in ax1.xaxis.get_ticklabels():
label.set_rotation(45)
plt.suptitle(stock.upper(),color='w')
plt.setp(ax1.get_xticklabels(), visible=True)
# ax1.annotate('Big news!',(date[510],Av1[510]),
# xytext=(0.8, 0.9), textcoords='axes fraction',
# arrowprops=dict(facecolor='white', shrink=0.05),
# fontsize=14, color = 'w',
# horizontalalignment='right', verticalalignment='bottom')
plt.subplots_adjust(left=.09, bottom=.14, right=.94, top=.95, wspace=.20, hspace=0)
plt.show()
# fig.savefig('example.png',facecolor=fig.get_facecolor())
except Exception as e:
print('main loop',str(e))
def graphData(stock,MA1,MA2):
stockFile = loadStock(stock)
try:
date, closep, highp, lowp, openp, volume = np.loadtxt(stockFile,delimiter=',', unpack=True,
converters={ 0: bytespdate2num('%Y%m%d')})
x = 0
y = len(date)
newAr = []
while x < y:
appendLine = date[x],openp[x],highp[x],lowp[x],closep[x],volume[x]
newAr.append(appendLine)
x+=1
Av1 = movingaverage(closep, MA1)
Av2 = movingaverage(closep, MA2)
SP = len(date[MA2-1:])
fig = plt.figure(facecolor='#07000d')
ax1 = plt.subplot2grid((6,4), (1,0), rowspan=4, colspan=4, axisbg='#07000d')
candlestick_ochl(ax1, newAr[-SP:], width=.6, colorup='#53c156', colordown='#ff1717')
Label1 = str(MA1)+' SMA'
Label2 = str(MA2)+' SMA'
#SMA
#--------------------------------------
ax1.plot(date[-SP:],Av1[-SP:],'#e1edf9',label=Label1, linewidth=1.5)
ax1.plot(date[-SP:],Av2[-SP:],'#4ee6fd',label=Label2, linewidth=1.5)
ax1.grid(True, color='w')
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax1.yaxis.label.set_color("w")
ax1.spines['bottom'].set_color("#5998ff")
ax1.spines['top'].set_color("#5998ff")
ax1.spines['left'].set_color("#5998ff")
ax1.spines['right'].set_color("#5998ff")
ax1.tick_params(axis='y', colors='w')
plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper'))
ax1.tick_params(axis='x', colors='w')
plt.ylabel('Stock price and Volume')
#RSI
#--------------------------------------
maLeg = plt.legend(loc=9, ncol=2, prop={'size':7},
fancybox=True, borderaxespad=0.)
maLeg.get_frame().set_alpha(0.4)
textEd = pylab.gca().get_legend().get_texts()
pylab.setp(textEd[0:5], color = 'w')
volumeMin = 0
ax0 = plt.subplot2grid((6,4), (0,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d')
rsi = rsiFunc(closep)
rsiCol = '#c1f9f7'
posCol = '#386d13'
negCol = '#8f2020'
ax0.plot(date[-SP:], rsi[-SP:], rsiCol, linewidth=1.5)
ax0.axhline(70, color=negCol)
ax0.axhline(30, color=posCol)
ax0.fill_between(date[-SP:], rsi[-SP:], 70, where=(rsi[-SP:]>=70), facecolor=negCol, edgecolor=negCol, alpha=0.5)
ax0.fill_between(date[-SP:], rsi[-SP:], 30, where=(rsi[-SP:]<=30), facecolor=posCol, edgecolor=posCol, alpha=0.5)
ax0.set_yticks([30,70])
ax0.yaxis.label.set_color("w")
ax0.spines['bottom'].set_color("#5998ff")
ax0.spines['top'].set_color("#5998ff")
ax0.spines['left'].set_color("#5998ff")
ax0.spines['right'].set_color("#5998ff")
ax0.tick_params(axis='y', colors='w')
ax0.tick_params(axis='x', colors='w')
plt.ylabel('RSI')
#MACD
#--------------------------------------
ax1v = ax1.twinx()
ax1v.fill_between(date[-SP:],volumeMin, volume[-SP:], facecolor='#00ffe8', alpha=.4)
ax1v.axes.yaxis.set_ticklabels([])
ax1v.grid(False)
###Edit this to 3, so it's a bit larger
ax1v.set_ylim(0, 3*volume.max())
ax1v.spines['bottom'].set_color("#5998ff")
ax1v.spines['top'].set_color("#5998ff")
ax1v.spines['left'].set_color("#5998ff")
ax1v.spines['right'].set_color("#5998ff")
ax1v.tick_params(axis='x', colors='w')
ax1v.tick_params(axis='y', colors='w')
ax2 = plt.subplot2grid((6,4), (5,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d')
fillcolor = '#00ffe8'
nslow = 26
nfast = 12
nema = 9
emaslow, emafast, macd = computeMACD(closep)
ema9 = ExpMovingAverage(macd, nema)
ax2.plot(date[-SP:], macd[-SP:], color='#4ee6fd', lw=2)
ax2.plot(date[-SP:], ema9[-SP:], color='#e1edf9', lw=1)
ax2.fill_between(date[-SP:], macd[-SP:]-ema9[-SP:], 0, alpha=0.5, facecolor=fillcolor, edgecolor=fillcolor)
plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper'))
ax2.spines['bottom'].set_color("#5998ff")
ax2.spines['top'].set_color("#5998ff")
ax2.spines['left'].set_color("#5998ff")
ax2.spines['right'].set_color("#5998ff")
ax2.tick_params(axis='x', colors='w')
ax2.tick_params(axis='y', colors='w')
plt.ylabel('MACD', color='w')
ax2.yaxis.set_major_locator(mticker.MaxNLocator(nbins=5, prune='upper'))
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(45)
plt.suptitle(stock.upper(),color='w')
plt.setp(ax0.get_xticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), visible=False)
# ax1.annotate('Big news!',(date[510],Av1[510]),
# xytext=(0.8, 0.9), textcoords='axes fraction',
# arrowprops=dict(facecolor='white', shrink=0.05),
# fontsize=14, color = 'w',
# horizontalalignment='right', verticalalignment='bottom')
plt.subplots_adjust(left=.09, bottom=.14, right=.94, top=.95, wspace=.20, hspace=0)
plt.show()
# fig.savefig('example.png',facecolor=fig.get_facecolor())
except Exception as e:
print('main loop',str(e))
def CandleStickPlotting(plotdata):
mondays = WeekdayLocator(MONDAY) # major ticks on the mondays
alldays = DayLocator() # minor ticks on the days
weekFormatter = DateFormatter('%b %d') # e.g., Jan 12
dayFormatter = DateFormatter('%d') # e.g., 12
title = 'Candlestick diagram'
#and then following the official example.
ala=np.matrix(plotdata)
#print SP
fig = plt.figure()
#fig, ax = plt.subplot2grid((6,1), (0,0), rowspan=2, colspan=1)
ax = plt.subplot2grid((6,1), (0,0), rowspan=3, colspan=1)
plt.title('DSV stocks')
ax2 = ax.twinx()
ax3 = plt.subplot2grid((6,1), (3,0), rowspan=2,colspan=1, sharex=ax)
# set the position of ax2 so that it is short (y2=0.32) but otherwise the same size as ax
#ax2.set_position(matplotlib.transforms.Bbox([[0.125,0.1],[0.9,0.32]]))
fig.subplots_adjust(bottom=0.2)
ax.xaxis.set_major_locator(mondays)
ax.xaxis.set_minor_locator(alldays)
ax.xaxis.set_major_formatter(weekFormatter)
#if ave1:
SP = len(ala[:,0])
candlestick_ochl(ax2, plotdata, width=0.6, colorup='#00ff00',colordown='#ff0000', alpha=0.4)
#volume_overlay3(ax, plotdata, colorup='#00ff00', colordown='#ff0000', width=0.6, alpha=0.4)
ax3.plot( ala[:,0], ala[:,2], 'g-', linewidth=0.4)
# 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.yaxis.tick_right()
ax2.yaxis.tick_left()
# make bar plots and color differently depending on up/down for the day
dates = np.squeeze(np.asarray(np.transpose(ala[:,0])))
vol = np.squeeze(np.asarray(np.transpose(ala[:,5])))
pos = ala[:,1]-ala[:,2]<0
neg = ala[:,1]-ala[:,2]>0
pos = np.squeeze(np.asarray(pos))
neg = np.squeeze(np.asarray(neg))
ax.bar(dates[pos],vol[pos],color='green',alpha=0.8)#,width=1,align='center')
ax.bar(dates[neg],vol[neg],color='#df3a01',alpha=0.8)#,width=1,align='center')
#x = np.arange(0.0, 2, 0.01)
#y1 = np.sin(2*np.pi*x)
#print np.squeeze(np.asarray(np.transpose(ala[:,0])))
#ax.bar(ala[:,0],ala[:,5],color='cyan', alpha=0.4)#width=1,align='center'
#ax.fill_between(np.squeeze(np.asarray(np.transpose(ala[:,0]))), np.squeeze(np.asarray(np.transpose(ala[:,5]))), 0,color='blue')#,color='blue', alpha=0.4)
#scale the x-axis tight
#ax.set_xlim(min(ala[:,0]),max(ala[:,0]))
plt.setp(ax.get_xticklabels(), visible=False)
ax.set_ylim(0, 3*max(ala[:,5]))
ax.set_yticks([0,max(ala[:,5])])
# the y-ticks for the bar were too dense, keep only every third one
#yticks = ax2.get_yticks()
#ax2.set_yticks(yticks[::3])
ax.yaxis.set_label_position("right")
ax.set_ylabel('Volume', size=12)
ax2.yaxis.set_label_position("left")
ax2.set_ylabel('Price', size=12)
# format the x-ticks with a human-readable date.
xt = ax3.get_xticks()
new_xticks = [datetime.date(num2date(d)) for d in xt]
ax3.set_xticklabels(new_xticks,rotation=45, horizontalalignment='right')
ax.patch.set_facecolor('gray')
#plt.tight_layout()
plt.setp( plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
#plt.hod(True)
#plt.show()
savefig('foo.pdf', facecolor='gray', edgecolor='gray')#fig.get_facecolor()
def plotGraph(stock, date, SP, prices, volume, sma1, sma2, smap1, smap2, rsi, macd, ema9):
try:
fig = plt.figure(facecolor='#07000d')
ax1 = plt.subplot2grid((9,4), (1,0), rowspan=4, colspan=4, axisbg='#07000d')
candlestick_ochl(ax1, prices[-SP:], width=.6, colorup='#53c156', colordown='#ff1717')
Label1 = str(smap1)+' SMA'
Label2 = str(smap2)+' SMA'
ax1.plot(date[-SP:],sma1[-SP:],'#e1edf9',label=Label1, linewidth=1.5)
ax1.plot(date[-SP:],sma2[-SP:],'#4ee6fd',label=Label2, linewidth=1.5)
ax1.grid(True, color='w')
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax1.yaxis.label.set_color("w")
ax1.spines['bottom'].set_color("#5998ff")
ax1.spines['top'].set_color("#5998ff")
ax1.spines['left'].set_color("#5998ff")
ax1.spines['right'].set_color("#5998ff")
ax1.tick_params(axis='y', colors='w')
plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper'))
ax1.tick_params(axis='x', colors='w')
plt.ylabel('Stock price and Volume')
maLeg = plt.legend(loc=9, ncol=2, prop={'size':7},
fancybox=True, borderaxespad=0.)
maLeg.get_frame().set_alpha(0.4)
textEd = pylab.gca().get_legend().get_texts()
pylab.setp(textEd[0:5], color = 'w')
volumeMin = 0
ax0 = plt.subplot2grid((9,4), (0,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d')
rsiCol = '#c1f9f7'
posCol = '#386d13'
negCol = '#8f2020'
ax0.plot(date[-SP:], rsi[-SP:], rsiCol, linewidth=1.5)
ax0.axhline(70, color=negCol)
ax0.axhline(30, color=posCol)
ax0.fill_between(date[-SP:], rsi[-SP:], 70, where=(rsi[-SP:]>=70), facecolor=negCol, edgecolor=negCol, alpha=0.5)
ax0.fill_between(date[-SP:], rsi[-SP:], 30, where=(rsi[-SP:]<=30), facecolor=posCol, edgecolor=posCol, alpha=0.5)
ax0.set_yticks([30,70])
ax0.yaxis.label.set_color("w")
ax0.spines['bottom'].set_color("#5998ff")
ax0.spines['top'].set_color("#5998ff")
ax0.spines['left'].set_color("#5998ff")
ax0.spines['right'].set_color("#5998ff")
ax0.tick_params(axis='y', colors='w')
ax0.tick_params(axis='x', colors='w')
plt.ylabel('RSI')
ax1v = ax1.twinx()
ax1v.fill_between(date[-SP:],volumeMin, volume[-SP:], facecolor='#00ffe8', alpha=.4)
ax1v.axes.yaxis.set_ticklabels([])
ax1v.grid(False)
###Edit this to 3, so it's a bit larger
ax1v.set_ylim(0, 3*volume.max())
ax1v.spines['bottom'].set_color("#5998ff")
ax1v.spines['top'].set_color("#5998ff")
ax1v.spines['left'].set_color("#5998ff")
ax1v.spines['right'].set_color("#5998ff")
ax1v.tick_params(axis='x', colors='w')
ax1v.tick_params(axis='y', colors='w')
ax2 = plt.subplot2grid((9,4), (5,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d')
fillcolor = '#00ffe8'
ax2.plot(date[-SP:], macd[-SP:], color='#4ee6fd', lw=2)
ax2.plot(date[-SP:], ema9[-SP:], color='#e1edf9', lw=1)
ax2.fill_between(date[-SP:], macd[-SP:]-ema9[-SP:], 0, alpha=0.5, facecolor=fillcolor, edgecolor=fillcolor)
plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper'))
ax2.spines['bottom'].set_color("#5998ff")
ax2.spines['top'].set_color("#5998ff")
ax2.spines['left'].set_color("#5998ff")
ax2.spines['right'].set_color("#5998ff")
ax2.tick_params(axis='x', colors='w')
ax2.tick_params(axis='y', colors='w')
plt.ylabel('MACD', color='w')
ax2.yaxis.set_major_locator(mticker.MaxNLocator(nbins=5, prune='upper'))
plt.suptitle(stock,color='w')
plt.setp(ax0.get_xticklabels(), visible=False)
### add this ####
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
#plt.subplots_adjust(left=.09, bottom=.14, right=.94, top=.95, wspace=.20, hspace=0)
plt.show()
fig.savefig('example.png',facecolor=fig.get_facecolor())
except Exception,e:
print 'plotGraph',str(e)
newAr = []
while x < y:
appendLine = date[x],openp[x],closep[x],highp[x],lowp[x],volume[x]
newAr.append(appendLine)
x+=1
Av1 = movingaverage(closep, MA1)
Av2 = ExpMovingAverage(closep, MA2)
SP = len(date[MA2-1:])
fig = plt.figure(facecolor='#07000d')
# Plotting the main price graph
ax1 = plt.subplot2grid((7,4), (1,0), rowspan=4, colspan=4, axisbg='#07000d')
candlestick_ochl(ax1, newAr[-SP:], width=.6, colorup='#53c156', colordown='#ff1717')
Label1 = 'SMA '+str(Av1[-1]) #+str(Av1[-1])
Label2 = str("%.2f" % updatingMoneyWave(highp, lowp, closep, nextMWPrice = True))+' new Price' #+str(Av2[-1])
ax1.plot(date[-SP:],Av1[-SP:],'#e1edf9',label=Label1, linewidth=1.5)
ax1.plot(date[-SP:],Av2[-SP:],'#4ee6fd',label=Label2, linewidth=1.5)
ax1.grid(True, color='w')
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
ax1.yaxis.label.set_color("w")
ax1.spines['bottom'].set_color("#5998ff")
ax1.spines['top'].set_color("#5998ff")
ax1.spines['left'].set_color("#5998ff")
ax1.spines['right'].set_color("#5998ff")
def vGraphData(sSymbol, date, closep, highp, lowp, openp, volume,
iShortSMA=10, iLongSMA=50,
iRsiUpper=70, iRsiLower=30,
iMacdSlow=26, iMacdFast=12, iMacdEma=9,
bUseTalib=False,
):
if bUseTalib:
import talib
x = 0
y = len(date)
newAr = []
while x < y:
appendLine = (date[x], openp[x], closep[x], highp[x], lowp[x], volume[x],)
newAr.append(appendLine)
x+=1
if bUseTalib:
Av1 = talib.SMA(closep, iShortSMA)
Av2 = talib.SMA(closep, iLongSMA)
else:
Av1 = nSMA(closep, iShortSMA)
Av2 = nSMA(closep, iLongSMA)
SP = len(date[iLongSMA-1:])
fig = plt.figure(facecolor='#07000d')
ax1 = plt.subplot2grid((6,4), (1,0), rowspan=4, colspan=4, axisbg='#07000d')
candlestick_ochl(ax1, newAr[-SP:], width=.6, colorup='#53c156', colordown='#ff1717')
Label1 = str(iShortSMA)+' SMA'
Label2 = str(iLongSMA)+' SMA'
ax1.plot(date[-SP:],Av1[-SP:],'#e1edf9',label=Label1, linewidth=1.5)
ax1.plot(date[-SP:],Av2[-SP:],'#4ee6fd',label=Label2, linewidth=1.5)
uSpinesFg = "#5998ff"
ax1.grid(True, color='white')
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
ax1.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%Y-%m'))
ax1.yaxis.label.set_color("w")
ax1.spines['bottom'].set_color(uSpinesFg)
ax1.spines['top'].set_color(uSpinesFg)
ax1.spines['left'].set_color(uSpinesFg)
ax1.spines['right'].set_color(uSpinesFg)
ax1.tick_params(axis='y', colors='white')
plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper'))
ax1.tick_params(axis='x', colors='white')
plt.ylabel('Stock price and Volume')
maLeg = plt.legend(loc=9, ncol=2, prop={'size': 7},
fancybox=True, borderaxespad=0.0)
maLeg.get_frame().set_alpha(0.4)
oLegend = pylab.gca().get_legend()
if oLegend:
# AttributeError: 'NoneType' object has no attribute 'get_texts'
textEd = oLegend.get_texts()
pylab.setp(textEd[0:5], color = 'white')
volumeMin = 0
ax0 = plt.subplot2grid((6,4), (0,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d')
rsi = rsiFunc(closep)
rsiCol = '#c1f9f7'
posCol = '#386d13'
negCol = '#8f2020'
ax0.plot(date[-SP:], rsi[-SP:], rsiCol, linewidth=1.5)
ax0.axhline(iRsiUpper, color=negCol)
ax0.axhline(iRsiLower, color=posCol)
ax0.fill_between(date[-SP:], rsi[-SP:], iRsiUpper, where=(rsi[-SP:]>=iRsiUpper), facecolor=negCol, edgecolor=negCol, alpha=0.5)
ax0.fill_between(date[-SP:], rsi[-SP:], iRsiLower, where=(rsi[-SP:]<=iRsiLower), facecolor=posCol, edgecolor=posCol, alpha=0.5)
ax0.set_yticks([iRsiLower, iRsiUpper])
ax0.yaxis.label.set_color("w")
ax0.spines['bottom'].set_color(uSpinesFg)
ax0.spines['top'].set_color(uSpinesFg)
ax0.spines['left'].set_color(uSpinesFg)
ax0.spines['right'].set_color(uSpinesFg)
ax0.tick_params(axis='y', colors='white')
ax0.tick_params(axis='x', colors='white')
plt.ylabel('RSI')
uVolumeFg = '#00ffe8'
ax1v = ax1.twinx()
ax1v.fill_between(date[-SP:],volumeMin, volume[-SP:], facecolor=uVolumeFg, alpha=.4)
ax1v.axes.yaxis.set_ticklabels([])
ax1v.grid(False)
###Edit this to 3, so it's a bit larger
ax1v.set_ylim(0, 3*volume.max())
ax1v.spines['bottom'].set_color(uSpinesFg)
ax1v.spines['top'].set_color(uSpinesFg)
ax1v.spines['left'].set_color(uSpinesFg)
ax1v.spines['right'].set_color(uSpinesFg)
ax1v.tick_params(axis='x', colors='white')
ax1v.tick_params(axis='y', colors='white')
ax2 = plt.subplot2grid((6,4), (5,0), sharex=ax1, rowspan=1, colspan=4, axisbg='#07000d')
uMacdFill = '#00ffe8'
emaslow, emafast, macd = computeMACD(closep, slow=iMacdSlow, fast=iMacdFast)
ema9 = ExpMovingAverage(macd, iMacdEma)
ax2.plot(date[-SP:], macd[-SP:], color='#4ee6fd', lw=2)
ax2.plot(date[-SP:], ema9[-SP:], color='#e1edf9', lw=1)
ax2.fill_between(date[-SP:], macd[-SP:]-ema9[-SP:], 0,
alpha=0.5, facecolor=uMacdFill, edgecolor=uMacdFill)
plt.gca().yaxis.set_major_locator(mticker.MaxNLocator(prune='upper'))
ax2.spines['bottom'].set_color(uSpinesFg)
ax2.spines['top'].set_color(uSpinesFg)
ax2.spines['left'].set_color(uSpinesFg)
ax2.spines['right'].set_color(uSpinesFg)
ax2.tick_params(axis='x', colors='white')
ax2.tick_params(axis='y', colors='white')
plt.ylabel('MACD', color='w')
ax2.yaxis.set_major_locator(mticker.MaxNLocator(nbins=5, prune='upper'))
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(45)
plt.suptitle(sSymbol.upper(), color='white')
plt.setp(ax0.get_xticklabels(), visible=False)
### add this ####
plt.setp(ax1.get_xticklabels(), visible=False)
## ax1.annotate('Big news!',(date[510],Av1[510]),
## xytext=(0.8, 0.9), textcoords='axes fraction',
## arrowprops=dict(facecolor='white', shrink=0.05),
## fontsize=14, color = 'w',
## horizontalalignment='right', verticalalignment='bottom')
plt.subplots_adjust(left=.09, bottom=.14, right=.94, top=.95, wspace=.20, hspace=0)
plt.show()
def graphData(stock, plotStock, dataDict):
try:
stockFile = 'data/'+stock+'.txt'
date, openp, highp, lowp, closep, volume, adjclose = np.loadtxt(stockFile,delimiter=',',unpack=True,
converters={0: mdates.strpdate2num('%Y-%m-%d')})
niftyFile = 'data/nsei.txt'
dateNifty, openpNifty, highpNifty, lowpNifty, closepNifty, volumeNifty, adjclosep = np.loadtxt(niftyFile,delimiter=',',unpack=True,
converters={0: mdates.strpdate2num('%Y-%m-%d')})
date = np.flipud(date)
openp = np.flipud(openp)
highp = np.flipud(highp)
lowp = np.flipud(lowp)
closep = np.flipud(closep)
volume = np.flipud(volume)
dateNifty = np.flipud(dateNifty)
closepNifty = np.flipud(closepNifty)
print 'Drawing main chart...'
x = 0
numOfDates = len(date)
print "no of Dates: ", numOfDates
numOfDatesNifty = len(dateNifty)
print "no of Dates in Nifty: ", numOfDatesNifty
candleArray = []
otherDataList = np.repeat(0.0, numOfDatesNifty)
print "len of candleArray", len(candleArray)
while x < numOfDatesNifty:
if plotStock == False:
# create otherDataList for FII
key = num2date(date[x])
try:
otherDataList[x] = dataDict[key]
except Exception, e:
#suppress this message if we are ploting stock because EPS date is very limited
if plotStock == False:
print 'No FII data for date: ' , str(e)
otherDataList[x] = 0
else:
#in most of the cases, reduntant data is present in stocks from yahoo. Delete stock data not present
#in nifty
if date[x] != dateNifty[x]:
print num2date(date[x]), num2date(dateNifty[x])
date = np.delete(date, x)
openp = np.delete(openp, x)
highp = np.delete(highp, x)
lowp = np.delete(lowp, x)
closep = np.delete(closep, x)
volume = np.delete(volume, x)
#otherDataList = np.delete(otherDataList, x)
continue
else:
otherDataList[x] = closep[x]/closepNifty[x]*100
#create candlArray in expected order for candlestic_ochl
#maintain the below order of variables
appendLine = date[x],openp[x],closep[x],highp[x],lowp[x]
candleArray.append(appendLine)
x+=1
print "len of candleArray", len(candleArray)
print 'len of otherdata', len(otherDataList)
#print candleArray
global MA1
global MA2
if len(date) > MA2:
draw_MA = 1
label1 = str(MA1)+' SMA'
label2 = str(MA2)+' SMA'
else:
#skip MA ploting if no of candles are less than the bigger MA
draw_MA = 0
print 'skip MA'
if draw_MA==1:
Av1 = movingAverage(closep, MA1)
Av2 = movingAverage(closep, MA2)
fig = plt.figure(facecolor=blackThemeBG)
fig.canvas.set_window_title(stock)
mainChart = plt.subplot2grid((7,4), (0,0), rowspan=5, colspan=4, axisbg=blackThemeBG)
candlestick_ochl(mainChart, candleArray, width=.75, colorup=blackThemeColorUp, colordown=blackThemeColorDown)
if draw_MA==1:
mainChart.plot(date[MA1:], Av1[MA1:], fastMA, label=label1, linewidth=1.5)
mainChart.plot(date[MA2:], Av2[MA2:], slowMA, label=label2, linewidth=1.5)
mainChart.grid(True, color='w')
mainChart.xaxis.set_major_locator(mticker.MaxNLocator(10))
mainChart.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
mainChart.yaxis.label.set_color("w")
setAllSpineColor(mainChart, spinesColor)
mainChart.tick_params(axis='y', colors='w')
plt.ylabel('Stock Price')
if draw_MA==1:
plt.legend(loc=3, prop={'size':7}, fancybox=True)
maLeg = plt.legend(loc=3, ncol=1, prop={'size':7}, fancybox=True, borderaxespad=0.)
maLeg.get_frame().set_alpha(0.4)
if plotStock == 1 and NiftyOverlay == True:
plotNiftyOverlay(mainChart)
print 'Drawing main chart... Done'
if plotStock == 1:
plotVolume(mainChart, date, volume)
print 'Drawing EPS/FII chart...'
if plotStock == True:
epsChart= plt.subplot2grid((7,4), (5,0), sharex=mainChart, rowspan=1, colspan=4, axisbg=blackThemeBG)
epsChart.xaxis.set_visible(False)
else:
epsChart= plt.subplot2grid((7,4), (5,0), sharex=mainChart, rowspan=2, colspan=4, axisbg=blackThemeBG)
epsChart.xaxis.set_visible(True)
setAllSpineColor(epsChart, spinesColor)
epsChart.tick_params(axis='y', colors='w')
epsChart.tick_params(axis='x', colors='w')
epsChart.yaxis.label.set_color("w")
epsChart.grid(True, color='w')
if plotStock == True:
plt.ylabel('Relative Strength')
else:
plt.ylabel('FII Data')
epsChart.bar(date, otherDataList, color=epsBarColor, linewidth=0)
#enable if you want lable pad to move further
#epsChart.yaxis.labelpad = 20
if plotStock == True:
RS_MA = 200
RS_AV = movingAverage(otherDataList, RS_MA)
global TypeMansfield
"""
MRP = (( RP(today) / sma(RP(today), n)) - 1 ) * 100
Full details can be found in below link,
http://www.trade2win.com/boards/technical-analysis/134944-stan-weinsteins-stage-analysis-97.html#post2137398
"""
MansfieldRPI = np.repeat(0.0, numOfDatesNifty)
x = 0
while x < numOfDatesNifty:
MansfieldRPI[x] = (otherDataList[x]/RS_AV[x] - 1)*100
x +=1
if TypeMansfield == True:
epsChart.plot(dateNifty[RS_MA:], MansfieldRPI[RS_MA:], "#FFFF00", linewidth=1.5)
#Draw a horizontal line --- on 0
epsChart.plot([min(dateNifty),max(dateNifty)], [0, 0], '--', color='w')
else:
epsChart.plot(dateNifty, otherDataList, '#b93904', linewidth=1.5)
epsChart.plot(dateNifty[RS_MA:], RS_AV[RS_MA:], slowMA, linewidth=1.5)
epsChart.tick_params(axis='x', colors='w')
epsChart.tick_params(axis='y', colors='w')
print 'Drawing EPS chart.. Done'
for label in mainChart.xaxis.get_ticklabels():
label.set_rotation(90)
if plotStock == 0:
for label in epsChart.xaxis.get_ticklabels():
label.set_rotation(45)
plt.xlabel('Date', color='w')
plt.suptitle(stock+' Stock Price', color='w')
plt.setp(mainChart.get_xticklabels(), visible=False)
plt.subplots_adjust(left=.09, bottom=.18, right=.94, top=.94, wspace=.20, hspace=0)
plt.show()
fig.savefig('example.png', facecolor=fig.get_facecolor())
matplotlib.rcParams.update({'savefig.facecolor':fig.get_facecolor()})
today = date.today()
start = (today.year - 1, today.month, today.day)
alldays = DayLocator()
months = MonthLocator()
month_formatter = DateFormatter("%b %Y")
# 从财经频道下载股价数据
symbol = 'BIDU' # 百度的股票代码
quotes = quotes_historical_yahoo_ochl(symbol, start, today)
# 创建figure对象，这是绘图组件的顶层容器
fig = plt.figure()
# 增加一个子图
ax = fig.add_subplot(111)
# x轴上的主定位器设置为月定位器，该定位器负责x轴上较粗的刻度
ax.xaxis.set_major_locator(months)
# x轴上的次定位器设置为日定位器，该定位器负责x轴上较细的刻度
ax.xaxis.set_minor_locator(alldays)
# x轴上的主格式化器设置为月格式化器，该格式化器负责x轴上较粗刻度的标签
ax.xaxis.set_major_formatter(month_formatter)
# 使用matplotlib.finance包的candlestick函数绘制k线图
candlestick_ochl(ax, quotes)
# 将x轴上的标签格式化为日期
fig.autofmt_xdate()
plt.title('Baidu, Inc. (BIDU)')
plt.show()
def candlestickData(stock,MA1,MA2):
try:
stockFile = 'dataDaily/'+stock+'.txt'
date,closep,highp,lowp,openp,volume = np.loadtxt(stockFile,delimiter=',',unpack=True,
converters={0:mdates.strpdate2num('%Y%m%d')})
# use while loop to build candlestick DATA set
x = 0
y = len(date)
candleAr = []
while x < y:
appendLine = date[x],openp[x],closep[x],highp[x],lowp[x],volume[x]
candleAr.append(appendLine)
x+=1
# generate moving average
Av1 = movingaverage(closep, MA1)
Av2 = movingaverage(closep, MA2)
SP = len(date[MA2-1:]) # starting point
#
label1 = str(MA1)+' SMA'
label2 = str(MA2)+' SMA'
#print len(Av1),len(Av2),len(date)
#print len(date),SP
#print date[-SP:],Av1[-SP:]
#time.sleep(5)
#fig = plt.figure()
fig = plt.figure(facecolor='#07000d') # background color
# subplot 1: price
#ax1 = plt.subplot(2,1,1)#(2,3,6), 2X3, and at place 6
ax1 = plt.subplot2grid((5,4),(0,0),rowspan=4,colspan=4,axisbg='#07000d')
# candle stick plot
# make change to vline in candlestick()
#candlestick(ax1,candleAr,width=0.8,colorup='#9eff15',colordown='#ff1717')
candlestick_ochl(ax1,candleAr,width=0.8,colorup='#9eff15',colordown='#ff1717')
#plot moving average
ax1.plot(date[-SP:],Av1[-SP:],'#6998ff',label=label1,linewidth=1.5)
ax1.plot(date[-SP:],Av2[-SP:],'#e1edf9',label=label2,linewidth=1.5)
#ax1.plot(date[MA1-1:],Av1[:],'#6998ff',label=label1,linewidth=1.5)
#ax1.plot(date[MA2-1:],Av2[:],'#e1edf9',label=label2,linewidth=1.5)
#
ax1.yaxis.label.set_color('w')
ax1.spines['bottom'].set_edgecolor('#5998ff')
ax1.spines['top'].set_edgecolor('#5998ff')
ax1.spines['left'].set_edgecolor('#5998ff')
ax1.spines['right'].set_edgecolor('#5998ff')
ax1.tick_params(axis='y',colors='w')
# label
#plt.xlabel('Date')
plt.ylabel('Price ($)',color='w')
plt.suptitle(stock,color='w')
# plot legend
plt.legend(loc=2,prop={'size':6})
# fill color
#volumeMin = volume.min()
volumeMin = 0
# set tick label
plt.setp(ax1.get_xticklabels(),visible=False)
#grid
ax1.grid(True,color='w')
ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))
#ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
for label in ax1.xaxis.get_ticklabels():
label.set_rotation(45)
# subplot 2: volume
#ax2 = plt.subplot(2,1,2,sharex=ax1) #share axis, sync the axis
ax2 = plt.subplot2grid((5,4),(4,0),sharex=ax1,rowspan=1,colspan=4,axisbg='#07000d') # shared axis
# remove y axis tick lable for subplot2
ax2.axes.yaxis.set_ticklabels([])
ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
#
ax2.yaxis.label.set_color('w')
ax2.spines['bottom'].set_edgecolor('#5998ff')
ax2.spines['top'].set_edgecolor('#5998ff')
ax2.spines['left'].set_edgecolor('#5998ff')
ax2.spines['right'].set_edgecolor('#5998ff')
ax2.tick_params(axis='x',colors='w')
ax2.tick_params(axis='y',colors='w')
#ax2.bar(date,volume)
ax2.plot(date,volume,'#00ffe8',linewidth=.8)
ax2.fill_between(date,volumeMin,volume,facecolor='#00ffe8',alpha=.5)
ax2.grid(False)
plt.xlabel('Date')
plt.ylabel('Volume')
for label in ax2.xaxis.get_ticklabels():
label.set_rotation(45)
#adjust plot spaces
plt.subplots_adjust(left=.09,bottom=.17,right=.93,top=.93,wspace=.20,hspace=.00)
plt.show()
fig.savefig('example.png',facecolor=fig.get_facecolor())
except Exception, e:
print 'failed main loop',str(e)
def _do_plot_candle(date, p_open, high, low, close, volume, view_index, symbol, day_sum, save, minute):
"""
绘制不可交互的k线图
param date: 融时间序列交易日时间，pd.DataFrame.index对象
:param p_open: 金融时间序列开盘价格序列，np.array对象
:param high: 金融时间序列最高价格序列，np.array对象
:param low: 金融时间序列最低价格序列，np.array对象
:param close: 金融时间序列收盘价格序列，np.array对象
:param volume: 金融时间序列成交量序列，np.array对象
:param symbol: symbol str对象
:param day_sum: 端线图 matplotlib的版本有些有bug显示不对
:param save: 是否保存可视化结果在本地
:param minute: 是否是绘制分钟k线图
"""
# 需要内部import不然每次import abupy都有warning，特别是子进程很烦人
try:
# noinspection PyUnresolvedReferences, PyDeprecation
import matplotlib.finance as mpf
except ImportError:
# 2.2 才会有
# noinspection PyUnresolvedReferences, PyDeprecation
import matplotlib.mpl_finance as mpf
if not g_only_draw_price:
# 成交量，价格都绘制
# noinspection PyTypeChecker
fig, (ax1, ax2) = plt.subplots(2, sharex=True, figsize=(20, 12))
else:
# 只绘制价格
fig, ax1 = plt.subplots(figsize=(6, 6))
if day_sum:
# 端线图绘制
qutotes = []
for index, (d, o, c, l, h) in enumerate(zip(date, p_open, close, low, high)):
d = index if minute else mpf.date2num(d)
val = (d, o, c, l, h)
qutotes.append(val)
# plot_day_summary_oclh接口，与mpf.candlestick_ochl不同，即数据顺序为开收低高
mpf.plot_day_summary_oclh(ax1, qutotes, ticksize=5, colorup=__colorup__, colordown=__colordown__)
else:
# k线图绘制
qutotes = []
for index, (d, o, c, h, l) in enumerate(zip(date, p_open, close, high, low)):
d = index if minute else mpf.date2num(d)
val = (d, o, c, h, l)
qutotes.append(val)
# mpf.candlestick_ochl即数据顺序为开收高低
mpf.candlestick_ochl(ax1, qutotes, width=0.6, colorup=__colorup__, colordown=__colordown__)
if not g_only_draw_price:
# 开始绘制成交量
ax1.set_title(symbol)
ax1.set_ylabel('ochl')
ax1.grid(True)
if not minute:
ax1.xaxis_date()
if view_index is not None:
# 开始绘制买入交易日，卖出交易日，重点突出的点位
e_list = date.tolist()
# itertools.cycle循环使用备选的颜色
for v, csColor in zip(view_index, itertools.cycle(K_PLT_MAP_STYLE)):
try:
v_ind = e_list.index(v)
except Exception as e:
# logging.exception(e)
logging.debug(e)
# 向前倒一个
v_ind = len(close) - 1
label = symbol + ': ' + str(date[v_ind])
ax1.plot(v, close[v_ind], 'ro', markersize=12, markeredgewidth=4.5,
markerfacecolor='None', markeredgecolor=csColor, label=label)
# 因为candlestick_ochl 不能label了，所以使用下面的显示文字
# noinspection PyUnboundLocalVariable
ax2.plot(v, 0, 'ro', markersize=12, markeredgewidth=0.5,
markerfacecolor='None', markeredgecolor=csColor, label=label)
plt.legend(loc='best')
# 成交量柱子颜色，收盘价格 > 开盘，即红色
# noinspection PyTypeChecker
bar_red = np.where(close >= p_open, volume, 0)
# 成交量柱子颜色，开盘价格 > 收盘。即绿色
# noinspection PyTypeChecker
bar_green = np.where(p_open > close, volume, 0)
date = date if not minute else np.arange(0, len(date))
ax2.bar(date, bar_red, facecolor=__colorup__)
ax2.bar(date, bar_green, facecolor=__colordown__)
ax2.set_ylabel('volume')
ax2.grid(True)
ax2.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=30)
else:
ax1.grid(False)
if save:
# 保存可视化结果在本地
from pylab import savefig
save_dir = os.path.join(K_SAVE_CACHE_PNG_ROOT, ABuDateUtil.current_str_date())
png_dir = os.path.join(save_dir, symbol)
ABuFileUtil.ensure_dir(png_dir)
r_cnt = 0
while True:
png_name = '{}{}.png'.format(png_dir, '' if r_cnt == 0 else '-{}'.format(r_cnt))
if not ABuFileUtil.file_exist(png_name):
break
r_cnt += 1
# noinspection PyUnboundLocalVariable
savefig(png_name)
fig.clf()
plt.close(fig)
else:
"""
save 了就不show了
"""
plt.show()