def draw_k_easy(self):
fig, ax = plt.subplots(figsize=(15, 5))
mpf.plot_day_summary_oclh(ax,
self.mat_data,
colorup='r',
colordown='k')
plt.grid(True)
ax.xaxis_date()
plt.title(self.name + ':' + self.code)
plt.ylabel('Price')
plt.show()
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()
#
date1 = (2013, 10, 20)
date2 = (2013, 11, 10)
ticker = 'IBM'
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
quotes = getData(ticker, date1, date2)
if len(quotes) == 0:
raise SystemExit
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(weekFormatter)
ax.xaxis.set_minor_formatter(dayFormatter)
plot_day_summary_oclh(ax, quotes, ticksize=3)
candlestick_ohlc(ax, quotes, width=0.6)
ax.xaxis_date()
ax.autoscale_view()
plt.setp(plt.gca().get_xticklabels(), rotation=80, horizontalalignment='right')
plt.figtext(0.35, 0.45, '10/29: Open, High, Low, Close')
plt.figtext(0.35, 0.42, ' 177.62, 182.32, 177.50, 182.12')
plt.figtext(0.35, 0.32, 'Black ==> Close > Open ')
plt.figtext(0.35, 0.28, 'Red ==> Close < Open ')
plt.title('Candlesticks for IBM from 10/20/2013 to 11/10/2013')
plt.ylabel('Price')
plt.xlabel('Date')
plt.show()
plt.setp(plt.gca().get_xticklabels(), rotation=30)
plt.show()
#------------------------------------------------
import matplotlib.finance as mpf
import matplotlib.pyplot as plt
start = (2014, 5, 1)
end = (2014, 6, 30)
quotes = mpf.quotes_historical_yahoo_ochl('^GDAXI', start, end)
fig, ax = plt.subplots(figsize=(8, 5))
fig.subplots_adjust(bottom=0.2)
mpf.plot_day_summary_oclh(ax, quotes, colorup='b', colordown='r')
plt.grid(True)
ax.xaxis_date()
# dates on the x-axis
plt.title('DAX Index')
plt.ylabel('index level')
plt.setp(plt.gca().get_xticklabels(), rotation=30)
plt.show()
#------------------------------------------------
d = loaddict("./", "pickle")
data_list = []
for block in d:
dt = datetime.datetime.utcfromtimestamp(
block['id']) + datetime.timedelta(hours=8)
# mpf库中要求的顺序是：时间、开盘价、最高价、最低价、收盘价
data_list.append((date2num(dt), block['open'], block['high'], block['low'],
block['close']))
fig, ax = plt.subplots()
ax.xaxis_date()
ax.set_title('BTC/USDT')
mpf.candlestick_ohlc(ax,
data_list,
colorup='green',
colordown='r',
width=0.005)
plt.grid()
plt.show()
'''
fig, ax = plt.subplots(figsize=(15,5))
mpf.plot_day_summary_oclh(ax, data_list,colorup='g', colordown='r')
plt.grid(True)
ax.xaxis_date()
plt.title('wandayuanxian 17')
plt.ylabel('Price')
plt.grid()
plt.show()
'''
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()
plt.xlabel('Date')
plt.ylabel('Price')
# x轴的刻度为日期
ax.xaxis_date ()
###candlestick_ochl()函数的参数
# ax 绘图Axes的实例
# mat_wdyx 价格历史数据
# width 图像中红绿矩形的宽度,代表天数
# colorup 收盘价格大于开盘价格时的颜色
# colordown 低于开盘价格时矩形的颜色
# alpha 矩形的颜色的透明度
######################一下为绘制美国图#############
fig, ax = plt.subplots(figsize=(15,5))
mpf.plot_day_summary_oclh(ax, mat_wdyx,colorup='g', colordown='r')
plt.grid(True)
ax.xaxis_date()
plt.title('wandayuanxian 17')
plt.ylabel('Price')
#################以下为绘制K线和交易量图######################
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)
#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)
#Plotting candlestick and barcharts
quotes=np.array(mpf.quotes_historical_yahoo_ochl('YHOO',start,end))
fig,(ax1,ax2)=plt.subplots(2,sharex=True,figsize=(8,6))
mpf.candlestick_ochl(ax1,quotes,width=0.6,colorup='b',colordown='r')
ax1.set_title('Yahoo Inc.')
ax1.grid(True)
ax1.xaxis_date()
plt.bar(quotes[:,0]-0.25,quotes[:,5],width=0.5)
ax2.set_ylabel('volume')