def kline_plot(self,ktype=0):
df=self.cal_hadata()
#画K线图数据
date = df.index.strftime('%Y%m%d').tolist()
if ktype==0:
k_value = df[['adjopen','adjclose', 'adjlow','adjhigh']].values
else:
k_value = df[['ha_open','ha_close', 'ha_low', 'ha_high']].values
#引入pyecharts画图使用的是0.5.11版本，新版命令需要重写
kline = Kline(self.name+'行情走势')
kline.add('日K线图', date, k_value,
is_datazoom_show=True,is_splitline_show=False)
#加入5、20日均线
df['ma20']=df.adjclose.rolling(20).mean()
df['ma5']=df.adjclose.rolling(5).mean()
line = Line()
v0=df['ma5'].round(2).tolist()
v=df['ma20'].round(2).tolist()
line.add('5日均线', date,v0,
is_symbol_show=False,line_width=2)
line.add('20日均线', date,v,
is_symbol_show=False,line_width=2)
#成交量
bar = Bar()
bar.add('成交量', date, df['vol'],tooltip_tragger='axis',
is_legend_show=False, is_yaxis_show=False,
yaxis_max=5*max(df['vol']))
overlap = Overlap()
overlap.add(kline)
overlap.add(line,)
overlap.add(bar,yaxis_index=1, is_add_yaxis=True)
return overlap
def grids(data):
kline = Kline(data.symbol[0])
kline.add(
'',
data.index,
data.loc[:, ['open', 'close', 'low', 'high']].values,
mark_line=['max', 'min'],
mark_line_valuedim=['highest', 'lowest'],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1],
)
turnover = Bar()
turnover.add(
'',
data.index,
data['turnover'].values / pow(10, 9),
mark_line=['max', 'min'],
is_datazoom_show=True,
)
grid = Grid(page_title=data['symbol'][0], width=1800, height=900)
grid.add(kline, grid_bottom='40%')
grid.add(turnover, grid_top='65%')
grid.show_config()
return grid
def brush(data):
data = hist_sum(data)
kline = Kline()
kline.add(
'Kline',
data.index,
data.loc[:, ['open', 'close', 'low', 'high']].values,
mark_line=['max', 'min'],
mark_line_valuedim=['highest', 'lowest'],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1],
)
brush = Line()
brush.add(
'Brush',
data.index,
data.endpoint.values,
)
overlap = Overlap()
overlap.add(kline)
overlap.add(brush)
macd = Bar()
macd.add(
'MACD',
data.index,
data.hist_sum.values,
)
page = Page()
page.add(overlap)
page.add(macd)
return page
def drawKline(datadf, tradeRecorddf):
datadf["datetime"] = datadf["datetime"].dt.strftime("%Y-%m-%d %H:%M:%S")
OHLC = df[["open", "close", "low", "high"]]
OHLC = OHLC.values
DATETIME = df["datetime"].values
longOrderDF = tradeRecorddf[tradeRecorddf["direction"] == "long position"]
longOrderDF = longOrderDF[["time", "deal price", "kaiping"]].values
shortOrderDF = tradeRecorddf[tradeRecorddf["direction"] == "short position"]
shortOrderDF = shortOrderDF[["time", "deal price", "kaiping"]].values
markpointlist = []
for longorders in longOrderDF:
markpointlist.append(RedArrow(longorders[0], longorders[1], longorders[2]))
for shortorders in shortOrderDF:
markpointlist.append(GreenArrow(shortorders[0], shortorders[1], shortorders[2]))
page = Page()
grid = Grid(width=1920, height=900)
kline = Kline("candlestick")
kline.add("candlestick", DATETIME, OHLC, is_datazoom_show=True, datazoom_type='inside',
datazoom_range=[90, 100], tooltip_tragger_on='mousemove|click', tooltip_axispointer_type='cross',
is_label_show=False, mark_point_raw=markpointlist)
grid.add(kline, grid_top="3%", grid_height="95%")
page.add(grid)
now = dt.datetime.now()
today = now.strftime('%Y%m%d')
time = now.strftime("%H_%M_%S")
home = os.environ['HOME']
page.render(home + "/Pictures/" + today + "/" + "plotKlineChartandSignal" + time + ".html")
def kxian4_fun():
from pyecharts import Kline
api = ts.pro_api(
'acfe91c33583e4f34c757cfc5360f7e51eefd9f0c259f4204ea4720f')
# 取000001的前复权行情
df = ts.pro_bar(pro_api=api,
ts_code='000001.SZ',
adj='qfq',
start_date='20181201',
end_date='20181231')
df = df.sort_index(axis=0)
df1 = df[['open', 'high', 'open', 'close']]
v1 = df1.values.tolist()
kline = Kline("K 线图示例")
aa = [i for i in df1.index.format()]
kline.add(
"日K",
aa,
v1,
mark_point=["max"],
is_datazoom_show=True,
datazoom_orient="vertical",
)
return kline
def echart1(request):
template = loader.get_template('ewpyecharts.html')
line = Line("压力分析", width=1200, height=700)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高压力", attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"], mark_line=["average"])
line.add("最低压力", attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"], legend_top="50%", mark_line=["average"],
# 设置 dataZoom 控制索引为 0,1 的 x 轴，即第一个和第二个
is_datazoom_show=True, datazoom_xaxis_index=[0, 1])
v1 = [[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("考核表分析", title_top="50%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1, is_datazoom_show=True)
grid = Grid()
grid.add(line, grid_top="60%")
grid.add(kline, grid_bottom="60%")
# grid.render()
context = dict(
myechart=grid.render_embed(),
host=REMOTE_HOST,
script_list=grid.get_js_dependencies()
)
return HttpResponse(template.render(context, request))
def __init__(self,
stock_name,
jsPath='https://cdn.bootcss.com/echarts/4.1.0.rc2'):
# 使用最新的echarts js文件
online(jsPath)
# K线
self.stock_name = stock_name
self.kline = Kline(stock_name)
self.volume_bar = Bar('')
def K_line(date, v1):
kline = Kline("比特币历史价格")
kline.add(
"日K",
date,
v1,
is_datazoom_show=True,
)
return kline
def kline_chart(code, k_data):
kline = Kline("{0} K 线图".format(code), width="100%")
kline.add(("日K"),
k_data['date'],
k_data[['open', 'close', 'low', 'high']].values.tolist(),
mark_point=["average"],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1])
return kline
def K_line(date, v1, name):
kline = Kline(name)
kline.add(
"日K",
date,
v1,
is_datazoom_show=True,
)
return kline
def test_kline_default(patched):
fixture = "kline_options.json"
patched.return_value = "1"
kline = Kline("K 线图-默认示例")
kline.add("日K", DATE, data)
actual_options = dumps_actual_options(kline.options)
expected = get_fixture_content(fixture)
for a, b in zip(actual_options.split("\n"), expected.split("\n")):
eq_(a.strip(), b.strip())
def test_grid_6():
line = Line("折线图示例", width=1200, height=700)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
legend_top="50%",
mark_line=["average"],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1])
v1 = [[2320.26, 2320.26, 2287.3,
2362.94], [2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58,
2440.38], [2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例", title_top="50%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1,
is_datazoom_show=True)
grid = Grid()
grid.add(line, grid_top="60%")
grid.add(kline, grid_bottom="60%")
grid.render()
def test_kline_default(patched):
patched.return_value = "1"
kline = Kline("K 线图-默认示例")
kline.add("日K", DATE, data)
actual_options = json.dumps(
kline.options, sort_keys=True, indent=4, cls=DefaultJsonEncoder
)
expected = get_fixture_content("kline_options.json")
for a, b in zip(actual_options.split("\n"), expected.split("\n")):
eq_(a.strip(), b.strip())
def __init__(self):
self.kline = Kline()
self.kline2 = Kline()
# 初始化一个指标线
self.line = Line()
self.line_long_win = Line()
self.line_long_loss = Line()
self.line_short_win = Line()
self.line_short_loss = Line()
def kline_chart_sh(sh_index_data):
kline = Kline("上证 K 线图", width="100%", title_top="50%")
kline.add(("日K"),
sh_index_data['date'],
sh_index_data[['open', 'close', 'low', 'high']].values.tolist(),
mark_point=["average"],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1],
legend_top="50%")
return kline
def kplot(kdata,
new=True,
axes=None,
colorup='r',
colordown='g',
width=0.6,
alpha=1.0):
"""绘制K线图
:param KData kdata: K线数据
:param bool new: 是否在新窗口中显示，只在没有指定axes时生效
:param axes: 指定的坐标轴
:param colorup: the color of the rectangle where close >= open
:param colordown: the color of the rectangle where close < open
:param width: fraction of a day for the rectangle width
:param alpha: the rectangle alpha level, 透明度(0.0~1.0) 1.0为不透明
"""
if not kdata:
print("kdata is None")
return
if axes is None:
axes = create_figure() if new else gca()
title = get_draw_title(kdata)
last_record = kdata[-1]
text = u'%s 开:%.2f 高:%.2f 低:%.2f 收:%.2f 涨幅:%.2f%%' % (
last_record.datetime.date(), last_record.openPrice,
last_record.highPrice, last_record.lowPrice, last_record.closePrice,
100 *
(last_record.closePrice - kdata[-2].closePrice) / kdata[-2].closePrice)
date_list = kdata.getDatetimeList()
if kdata.getQuery().kType == KQuery.DAY:
x_list = [d.date() for d in date_list]
else:
x_list = [d.datetime() for d in date_list]
y_list = [[k.openPrice, k.closePrice, k.lowPrice, k.highPrice]
for k in kdata]
style = gcf().get_style(axes)
kline = Kline(title, text, title_pos='center', subtitle_color='#FF0000')
kline.add(None,
x_axis=x_list,
y_axis=y_list,
mark_line=["max"],
mark_line_symbolsize=0,
mark_line_valuedim='highest',
**style)
axes.add(kline)
gcf().set_xaxis(x_list)
gcf().add_axis(axes)
return gcf()
def test_kline_default(patched):
patched.return_value = "1"
kline = Kline("K 线图-默认示例")
kline.add("日K", DATE, data)
actual_options = json.dumps(kline.options,
sort_keys=True,
indent=4,
cls=DefaultJsonEncoder)
expected = get_fixture_content("kline_options.json")
for a, b in zip(actual_options.split("\n"), expected.split("\n")):
eq_(a.strip(), b.strip())
def test_kline_datazoom_vertical():
kline = Kline("K 线图-dataZoom 垂直布局")
kline.add(
"日K",
DATE,
data,
mark_line=["max"],
is_datazoom_show=True,
datazoom_orient="vertical",
)
kline.render()
def K_line(date, v1):
kline = Kline("比特币历史价格")
kline.add(
"日K",
date,
v1,
is_datazoom_show=True,
)
overlap = Overlap()
overlap.add(kline)
overlap.render()
def k_line(stock_num):
v1, date = to_csv(stock_num)
if v1 == 0:
kline = 0
return kline
kline = Kline(stock_num, width=800, height=450)
kline.add("Daily K Line",
date,
v1,
mark_point=["max"],
is_datazoom_show=True)
return kline
def showHotRankOfCity():
ans = getEchartsK()
kline = Kline("各城市发文K线图")
kline.add(
"",
list(ans.keys()),
list(ans.values()),
mark_point=["min"],
is_datazoom_show=True,
#datazoom_orient="vertical",
)
# kline.render()
return kline
def plot_line_graph():
page = Page('back_testing')
line = Line("K 线图-dataZoom 垂直布局", width=1300, height=400, title_pos="left")
line.add(
"日K",
["2017/7/{}".format(i + 1) for i in range(31)],
[random.randint(1, 2000) for _ in range(31)],
tooltip_trigger="axis",
tooltip_axispointer_type='cross',
mark_line=["max", 'min'],
legend_top="3%",
mark_point=['average', 'max', 'min'],
is_smooth=True,
line_color='#5296de',
line_width=2.5,
# yaxis_type="log",
)
line.add("日收益", ["2017/7/{}".format(i + 1) for i in range(31)],
[random.randint(1, 2000) for _ in range(31)],
tooltip_trigger="axis",
mark_point=['average', 'max', 'min'],
mark_line=["max", 'min'],
is_datazoom_show=True,
legend_top="3%",
is_smooth=True,
line_color='#082039',
line_width=2.5,
**style.init_style
# yaxis_type="log",
)
page.add(line)
# line.show_config()
kline = Kline("K 线图-dataZoom 水平布局",
width=1300,
height=400,
title_pos="left")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
data,
mark_point=["max"],
is_datazoom_show=True,
**style.init_style)
page.add(kline)
# kline.show_config()
page.render(FILE_DIR + 'line_graph.html')
def brush(data):
data = feature.full_data(data)
print(data.tail())
kline = Kline()
kline.add(
'Kline',
data.index,
data.loc[:, ['open', 'close', 'low', 'high']].values,
# mark_line=['max', 'min'],
# mark_line_valuedim=['highest', 'lowest'],
# is_datazoom_show=True,
# datazoom_xaxis_index=[0, 1, 2],
# datazoom_type='both',
# tooltip_axispointer_type='cross',
# is_more_utils=True,
)
brush = Line()
brush.add(
'Brush',
data.index,
data.endpoint
)
overlap = Overlap()
overlap.add(kline)
overlap.add(brush)
turnover = Bar()
turnover.add(
'',
data.index,
data.turnover.values / pow(10, 6),
mark_line=['max', 'min']
)
macd = Bar()
macd.add(
'',
data.index,
data.macdhist.values,
mark_line=['max', 'min'],
)
grid = Grid('', width='100%', height=900)
grid.add(overlap, grid_bottom='40%')
grid.add(turnover, grid_top='65%', grid_bottom='20%')
grid.add(macd, grid_top='85%')
return overlap
def test_overlap_kline_line():
import random
v1 = [
[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
attr = ["2017/7/{}".format(i + 1) for i in range(31)]
kline = Kline("Kline-Line 示例")
kline.add("日K", attr, v1)
line_1 = Line()
line_1.add("line-1", attr, [random.randint(2400, 2500) for _ in range(31)])
line_2 = Line()
line_2.add("line-2", attr, [random.randint(2400, 2500) for _ in range(31)])
overlap = Overlap()
overlap.add(kline)
overlap.add(line_1)
overlap.add(line_2)
overlap.render()
def test_overlap_kline_line():
import random
v1 = [
[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
attr = ["2017/7/{}".format(i + 1) for i in range(31)]
kline = Kline("Kline-Line 示例")
kline.add("日K", attr, v1)
line_1 = Line()
line_1.add("line-1", attr, [random.randint(2400, 2500) for _ in range(31)])
line_2 = Line()
line_2.add("line-2", attr, [random.randint(2400, 2500) for _ in range(31)])
overlap = Overlap()
overlap.add(kline)
overlap.add(line_1)
overlap.add(line_2)
overlap.render()
def test_kline_user_define_markline_style():
kline = Kline("K 线图-自定义标记点风格")
kline.add("日K", DATE, data, mark_point=["min", "max"],
mark_point_symbolsize=80,
datazoom_orient='vertical',
mark_line_valuedim=['lowest', 'highest'])
kline.show_config()
kline.render()
def test_grid_multiple_datazoom_index():
line = Line("折线图示例", width=1200, height=700)
line.add("最高气温", WEEK, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", WEEK, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"], legend_top="50%",
mark_line=["average"], is_datazoom_show=True,
datazoom_xaxis_index=[0, 1])
v1 = [[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例", title_top="50%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1,
is_datazoom_show=True)
grid = Grid()
grid.add(line, grid_top="60%")
grid.add(kline, grid_bottom="60%")
grid.render()
def plot(df):
kl=df.copy()
#计算指标
macd = talib.MACD(np.array(kl['CLOSE']), fastperiod=12, slowperiod=26, signalperiod=9)
boll = talib.BBANDS(np.array(kl['CLOSE']), timeperiod=20, nbdevup=2, nbdevdn=2, matype=0)
#绘图
page = Page(page_title='KBM')
kline = Kline()
kline.add('', list(kl.index), [list(kl[['OPEN', 'CLOSE', 'LOW', 'HIGH']].iloc[i,].values) for i in range(len(kl))],is_datazoom_show=True, datazoom_xaxis_index=[0, 1], datazoom_type="both", is_xaxislabel_align=True,tooltip_axispointer_type="cross")
line = Line(' ')
line.add('upperband', list(kl.index), boll[0].tolist())
line.add('middleband', list(kl.index), boll[1].tolist())
line.add('lowerband', list(kl.index), boll[2].tolist())
overlap1 = Overlap()
overlap1.add(kline)
overlap1.add(line)
# line=Line(' ',width=1800,height=600)
# line.add('中债国债到期收益率:10年',df.Times,df.Data[0], mark_line=0,is_datazoom_show=True,datazoom_xaxis_index=[0, 1],is_xaxislabel_align=True)
line2 = Line(' ')
line2.add('MACD', list(kl.index), macd[0].tolist())
line2.add('MACDsignal',list(kl.index), macd[1].tolist(), is_datazoom_show=True,tooltip_axispointer_type="cross")
bar = Bar(' ')
macd2 = macd[2].tolist()
macdhistUp = []
macdhistDown = []
for i in range(len(macd2)):
if (macd2[i] > 0):
macdhistUp.append(macd2[i])
macdhistDown.append(0)
else:
macdhistUp.append(0)
macdhistDown.append(macd2[i])
# bar.add('MACDhist',klt,macd[2].tolist(),is_datazoom_show=True,legend_top='65%')
bar.add('MACDhistUp', list(kl.index), macdhistUp, is_datazoom_show=True, legend_top='65%', label_color=['#ff0000'])
bar.add('MACDhistDown', list(kl.index), macdhistDown, is_datazoom_show=True, legend_top='65%', label_color=['#00ff00'])
overlap = Overlap()
overlap.add(bar)
overlap.add(line2)
grid = Grid(width=1920, height=950)
grid.add(overlap1, grid_bottom='40%')
grid.add(overlap, grid_top='70%')
# page.add(line)
# page.add(overlap)
page.add(grid)
path=os.path.abspath('.')
page.render(path+'\\plot\\KBM.html')
def test_kline_user_define_markline_style():
title = "K 线图-自定义标记点风格"
kline = Kline(title)
kline.add(
"日K",
DATE,
data,
mark_point=["min", "max"],
mark_point_symbolsize=80,
datazoom_orient="vertical",
mark_line_valuedim=["lowest", "highest"],
)
kline.render()
actual_content = get_default_rendering_file_content()
assert "lowest" in actual_content
assert "highest" in actual_content
assert json.dumps(title) in actual_content
def kplot(kdata, new=True, axes=None,
colorup='r', colordown='g', width=0.6, alpha=1.0):
"""绘制K线图
:param KData kdata: K线数据
:param bool new: 是否在新窗口中显示，只在没有指定axes时生效
:param axes: 指定的坐标轴
:param colorup: the color of the rectangle where close >= open
:param colordown: the color of the rectangle where close < open
:param width: fraction of a day for the rectangle width
:param alpha: the rectangle alpha level, 透明度(0.0~1.0) 1.0为不透明
"""
if not kdata:
print("kdata is None")
return
if axes is None:
axes = create_figure() if new else gca()
title = get_draw_title(kdata)
last_record = kdata[-1]
text = u'%s 开:%.2f 高:%.2f 低:%.2f 收:%.2f 涨幅:%.2f%%' % (
last_record.datetime.date(),
last_record.openPrice, last_record.highPrice,
last_record.lowPrice, last_record.closePrice,
100*(last_record.closePrice-kdata[-2].closePrice)/kdata[-2].closePrice)
date_list = kdata.getDatetimeList()
if kdata.getQuery().kType == KQuery.DAY:
x_list = [d.date() for d in date_list]
else:
x_list = [d.datetime() for d in date_list]
y_list = [[k.openPrice, k.closePrice, k.lowPrice, k.highPrice] for k in kdata]
style = gcf().get_style(axes)
kline = Kline(title, text, title_pos='center', subtitle_color='#FF0000')
kline.add(None, x_axis=x_list, y_axis=y_list,
mark_line=["max"], mark_line_symbolsize=0,
mark_line_valuedim='highest',
**style)
axes.add(kline)
gcf().set_xaxis(x_list)
gcf().add_axis(axes)
return gcf()
def plot(self, code=None):
"""plot the market_data"""
if code is None:
path_name = '.' + os.sep + 'QA_' + self.type + \
'_codepackage_' + self.if_fq + '.html'
kline = Kline('CodePackage_' + self.if_fq + '_' + self.type,
width=1360, height=700, page_title='QUANTAXIS')
data_splits = self.splits()
for i_ in range(len(data_splits)):
data = []
axis = []
for dates, row in data_splits[i_].data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
kline.add(self.code[i_], axis, data, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info(
'The Pic has been saved to your path: %s' % path_name)
else:
data = []
axis = []
for dates, row in self.select_code(code).data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
path_name = '.{}QA_{}_{}_{}.html'.format(
os.sep, self.type, code, self.if_fq)
kline = Kline('{}__{}__{}'.format(code, self.if_fq, self.type),
width=1360, height=700, page_title='QUANTAXIS')
kline.add(code, axis, data, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info(
'The Pic has been saved to your path: {}'.format(path_name))
def k():
import talib
import numpy as np
import tushare as ts
from pyecharts import Grid, Bar, Line, Kline, Overlap
data = ts.get_k_data('399300',
index=True,
start='2017-01-01',
end='2017-06-31')
ochl = data[['open', 'close', 'high', 'low']]
ochl_tolist = [ochl.ix[i].tolist() for i in range(len(ochl))]
sma_10 = talib.SMA(np.array(data['close']), 10)
sma_30 = talib.SMA(np.array(data['close']), 30)
kline = Kline()
kline.add("日K", data['date'], ochl_tolist, is_datazoom_show=True)
line = Line()
line.add('10 日均线',
data['date'],
sma_10,
is_fill=False,
line_opacity=0.8,
is_smooth=True)
line.add('30 日均线',
data['date'],
sma_30,
is_fill=False,
line_opacity=0.8,
is_smooth=True)
bar = Bar()
bar.add("成交量", data['date'], data['volume'], is_stack=True)
overlap = Overlap()
overlap.add(kline)
overlap.add(line)
#overlap.add(bar)
return overlap.render_embed()
def kline_plot(name, ktype=0):
df = cal_hadata(name) # 画K线图数据
# date = df.index.strftime('%Y%m%d').tolist()
date = df.trade_date.tolist()
# date = df['trade_date'].values.dt.strftime('%Y.%m.%d').tolist
# date = df.index.tolist()
if ktype == 0:
k_value = df[['open', 'close', 'low', 'high']].values
else:
k_value = df[['ha_open', 'ha_close', 'ha_low', 'ha_high']].values
# 引入pyecharts画图使用的是0.5.11版本，新版命令需要重写
from pyecharts import Kline, Line, Bar, Scatter, Overlap
kline = Kline(name + '行情走势')
kline.add('日K线图',
date,
k_value,
is_datazoom_show=True,
is_splitline_show=False)
# 加入5、20日均线
df['ma20'] = df.close.rolling(20).mean()
df['ma5'] = df.close.rolling(5).mean()
line = Line()
v0 = df['ma5'].round(2).tolist()
v = df['ma20'].round(2).tolist()
line.add('5日均线', date, v0, is_symbol_show=False, line_width=2)
line.add('20日均线', date, v, is_symbol_show=False, line_width=2)
# 成交量
bar = Bar()
bar.add('成交量',
date,
df['vol'],
tooltip_tragger='axis',
is_legend_show=False,
is_yaxis_show=False,
yaxis_max=5 * max(df['vol']))
overlap = Overlap()
overlap.add(kline)
overlap.add(line, )
overlap.add(bar, yaxis_index=1, is_add_yaxis=True)
# display(HTML(overlap._repr_html_()))
# warnings.filterwarnings("ignore")
return overlap
def __kline(self, **kwargs):
overlap = Overlap()
oclh = self.__df[['open', 'close', 'low', 'high']].values.tolist()
kline = Kline(self.title)
kline.add("",
self.__date,
oclh,
is_datazoom_show=True,
tooltip_tragger='axis',
tooltip_axispointer_type='cross',
datazoom_xaxis_index=self.xaxis,
is_xaxis_show=False)
# pyechars have no public options
kline._option.get('yAxis')[0].update(scale=True,
splitArea={"show": False})
overlap.add(kline)
if kwargs.get('MA') is not None:
mas = kwargs.get('MA')
overlap.add(self.__ma(*mas))
return overlap
def plot_datastruct(_quotation_base, code=None):
if code is None:
path_name = '.' + os.sep + 'QA_' + _quotation_base.type + \
'_codepackage_' + _quotation_base.if_fq + '.html'
kline = Kline('CodePackage_' + _quotation_base.if_fq + '_' + _quotation_base.type,
width=1360, height=700, page_title='QUANTAXIS')
data_splits = _quotation_base.splits()
for i_ in range(len(data_splits)):
data = []
axis = []
for dates, row in data_splits[i_].data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
kline.add(_quotation_base.code[i_], axis, data, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info('The Pic has been saved to your path: %s' % path_name)
else:
data = []
axis = []
for dates, row in _quotation_base.select_code(code).data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
path_name = '.' + os.sep + 'QA_' + _quotation_base.type + \
'_' + code + '_' + _quotation_base.if_fq + '.html'
kline = Kline(code + '__' + _quotation_base.if_fq + '__' + _quotation_base.type,
width=1360, height=700, page_title='QUANTAXIS')
kline.add(code, axis, data, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info('The Pic has been saved to your path: %s' % path_name)
def k_demo():
v1 = [[2320.26, 2320.26, 2287.3,
2362.94], [2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58,
2440.38], [2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例")
kline.add(
"日K",
["2017/7/{}".format(i + 1) for i in range(31)],
v1,
is_datazoom_show=True,
)
return kline
def test_kline_datazoom_horizontal():
kline = Kline("K 线图示例 - dataZoom 水平布局")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
data,
mark_point=["max"],
is_datazoom_show=True)
kline.render()
def draw(code):
import pandas as pd
stock = pd.read_csv(code + '.csv',
usecols=[0, 1, 2, 3, 4, 5, 6],
encoding='gbk')
stock.head()
stock_new = stock.iloc[:180, :]
stock_new_sorted = stock_new.sort_values('日期', ascending=True)
stock_new_sorted.head()
from pyecharts import Kline
stock_code = stock_new_sorted['股票代码'][0]
stock_name = stock_new_sorted['名称'][0]
index = stock_new_sorted['日期']
v = [[o, close, lowest, highest] for o, close, lowest, highest in zip(
stock_new_sorted['开盘价'], stock_new_sorted['收盘价'],
stock_new_sorted['最低价'], stock_new_sorted['最高价'])]
kline = Kline()
kline.add(stock_name + '(' + stock_code + ')' + '日K线图',
index,
v,
mark_point=["max"],
is_datazoom_show=True)
kline.render()
def graphpage(labels,mode_combo,startdate,enddate,optInterval,width1, height1):
#optInterval='D/W/M' labels
startdate = startdate.replace("/","-")#convert to tushare readable date
enddate = enddate.replace("/","-")
page = Page()
for label in labels: # generate numbers of graphs according to numbers of queries in treewidget
label1 = re.split("-", label)
overlap = Overlap()
if label1[2]!="分笔" and label1[2]!="季度饼图": #"K线" "复权" "历史分钟"
if mode_combo == "复权":
#if optInterval == "qfq" or optInterval == "hfq":#复权
array = ts.get_h_data(label1[1], start=startdate, end=enddate, autype="qfq")
array = array.sort_index()
time = array.index.format() # 日期正是index
elif mode_combo == "K线":
#elif optInterval.isalnum() :#历史K线
array = ts.get_k_data(label1[1], start=startdate, end=enddate, ktype=optInterval)
time = array['date'].tolist() # array.date
elif mode_combo == "历史分钟":
array_bfr = ts.get_tick_data(label1[1], date=startdate)
array_bfr.sort_values("time")
a = startdate + " " + array_bfr["time"]
array_bfr["time"] = a
array_bfr["time"] = pd.to_datetime(a)
array_bfr = array_bfr.set_index("time")
if label1[2] != "Volume" and label1[2] != "Amount":
price_df = array_bfr["price"].resample(optInterval).ohlc() # resample重新取样,选出ohlc=open/high/low，提取除价格之外另外4列.close,tushare是ohcl
price_df = price_df.dropna()
array = price_df
time = price_df.index.format()
elif label1[2] == "Volume":
vols = array_bfr["volume"].resample(optInterval).sum() #resample重新取样，累加间隔内数值 relevant data processing algorithm taken from Jimmy, Creator of Tushare
vols = vols.dropna()
vol_df = pd.DataFrame(vols, columns=["volume"])
array = vol_df
time = vol_df.index.format()
else:
amounts = array_bfr["amount"].resample(optInterval).sum()
amounts = amounts.dropna()
amount_df = pd.DataFrame(amounts, columns=["amount"])
array = amount_df
time = amount_df.index.format()
#绘图方法
if label1[2] == 'Kline':
re_array = array[['open', 'close', 'high', 'low']]
data_li = list(row.tolist() for index, row in re_array.iterrows()) # data_list = list(re_array.as_matrix())
close = array['close'].tolist()
kline = Kline(label1[0] + "-" + optInterval, width=width1*10/11, height = (height1*10/11) / len(labels))
kline.add(label1[0], time, data_li, is_datazoom_show=True, datazoom_type="slider", yaxis_interval=1)
overlap.add(kline)
if len(close) > 10:
ma10 = calculateMa(close, 10)
line1 = Line(title_color="#C0C0C0")
line1.add(label1[0] + "-" + "MA10", time, ma10)
overlap.add(line1)
if len(close) > 20:
ma20 = calculateMa(close, 20)
line2 = Line(title_color="#C0C0C0")
line2.add(label1[0] + "-" + "MA20", time, ma20)
overlap.add(line2)
if len(close) > 30:
ma30 = calculateMa(close, 30)
line3 = Line(title_color="#C0C0C0")
line3.add(label1[0] + "-" + "MA30", time, ma30)
overlap.add(line3)
page.add(overlap)
else:#When label1[2]==open/close/volume
if label1[2] == 'Open':
list_aft = array['open'].tolist()
elif label1[2] == 'Close':
list_aft = close
elif label1[2] == 'High':
list_aft = array['high'].tolist()
elif label1[2] == 'Low':
list_aft = array['low'].tolist()
elif label1[2] == 'Volume':#volume
list_aft = array['volume'].tolist()
else:#amount
list_aft = array['amount'].tolist()
line = Line(label1[0] + "-" + label1[2], width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(labels))
line.add(label1[0] + "-" + label1[2], time, list_aft, is_datazoom_show=True, yaxis_max="dataMax",
yaxis_min="dataMin", datazoom_type="slider")
overlap.add(line)
page.add(overlap)
elif label1[2]=="分笔":
array = ts.get_tick_data(label1[1], date=startdate)
array = array.sort_values("time")
date = array["time"].tolist()
amount = array["amount"].tolist()
atype = array["type"].tolist()
price = array["price"].tolist()
flag = ["bar" for i in date]
for idx, val in enumerate(atype):
if val == "卖盘":
amount[idx] = -amount[idx]
if val == "中性盘":
amount[idx] = 0
returnarray = list(zip(date, amount, flag, price))
form = [e[1] for e in returnarray]
time = [d[0] for d in returnarray]
bar = Bar(label1[0] + "-" + label1[2], width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(labels))
bar.add(label1[0] + "-" + label1[2], time, form, is_datazoom_show=True, datazoom_type="slider", yaxis_min="dataMin", yaxis_max="dataMax")
overlap.add(bar)
line = Line(label1[0] + "price", width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(labels))
price = [e[3] for e in returnarray]
line.add(label1[0] + "price", time, price, yaxis_min="dataMin", yaxis_max="dataMax", is_datazoom_show=True,
datazoom_type="slider",
yaxis_type="value")
overlap.add(line, yaxis_index=1, is_add_yaxis=True)
page.add(overlap)
elif label1[2]=="季度饼图":
datestr = startdate.split("-")
thisyear = datestr[0]
df2 = ts.top10_holders(code=label1[1], gdtype="1")
test = df2[1]["quarter"].tolist()
df_ready = df2[1]
idxlist = []
for idx, val in enumerate(test):
a = val.split("-")
if a[0] == thisyear:
# print a[0],idx
idxlist.append(idx)
thing = df_ready.loc[idxlist]
thing = thing.sort_values(["quarter", "name"])
# print a[0],id
name = thing["name"].tolist()
value = thing["hold"].tolist()
quarter = thing["quarter"].tolist()
namearray = [name[i:i + 10] for i in range(0, len(name), 10)]
valuearray = [value[j:j + 10] for j in range(0, len(value), 10)]
quarterarray = [quarter[k:k + 10] for k in range(0, len(quarter), 10)]
flag = ["pie" for i in namearray]
num = [len(value) for k in namearray]
returnarray = list(zip(namearray, valuearray, quarterarray, flag, num))
timeline = Timeline(is_auto_play=False, timeline_bottom=0) # zip(namearray,valuearray,quarter,flag,num)
namearray = [c[0] for c in returnarray]
valuearray = [d[1] for d in returnarray]
quarter = [e[2] for e in returnarray]
num = returnarray[0][4]
for x in range(0, int(num / 10)):
list1 = valuearray[x]
names = namearray[x]
quarters = quarter[x][0]
for idx, val in enumerate(list1):
list1[idx] = float(val)
pie = Pie(label1[0] + "-" + "前十股东", width=width1 * 10 / 11, height=(height1 * 10 / 11))
pie.add(label1[0] + "-" + "前十股东", names, list1, radius=[30, 55], is_legend_show=False,
is_label_show=True, label_formatter="{b}: {c}\n{d}%")
timeline.add(pie, quarters)
# namearray = [y for y in namearray[x]]
timeline.render()
page.render()
def test_kline_datazoom_horizontal():
kline = Kline("K 线图-dataZoom 水平布局")
kline.add("日K", DATE, data,
mark_point=["max"], is_datazoom_show=True)
kline.render()
def test_kline_default():
kline = Kline("K 线图-默认示例")
kline.add("日K", DATE, data)
kline.render()
def test_grid():
# grid_0
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%")
bar.add("商家B", attr, v2, is_stack=True, grid_bottom="60%")
line = Line("折线图示例", title_top="50%")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_top="50%")
bar.grid(line.get_series(), grid_top="60%")
bar.show_config()
bar.render()
# grid_1
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter(width=1200, is_grid=True)
scatter.add("散点图示例", v1, v2, grid_left="60%", legend_pos="70%")
es = EffectScatter()
es.add("动态散点图示例", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6, legend_pos="20%")
scatter.grid(es.get_series(), grid_right="60%")
scatter.show_config()
scatter.render()
# grid_2
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, width=1200, title_pos="65%", is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%", grid_left="60%")
bar.add("商家B", attr, v2, is_stack=True, grid_bottom="60%", grid_left="60%", legend_pos="80%")
line = Line("折线图示例")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_pos="20%")
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add("es", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0], effect_scale=6,
legend_top="50%", legend_pos="20%")
bar.grid(line.get_series(), grid_bottom="60%", grid_right="60%")
bar.grid(scatter.get_series(), grid_top="60%", grid_left="60%")
bar.grid(es.get_series(), grid_top="60%", grid_right="60%")
bar.show_config()
bar.render()
# grid_3
line = Line("折线图示例", width=1200, is_grid=True)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"],
mark_line=["average"], grid_right="65%")
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_pos="20%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos="45%")
pie.add("", attr, v1, radius=[30, 55], legend_pos="65%", legend_orient='vertical')
line.grid(pie.get_series(), grid_left="60%")
line.show_config()
line.render()
# grid_4
line = Line("折线图示例", width=1200, is_grid=True)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"],
mark_line=["average"], grid_right="60%")
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_pos="20%", grid_right="60%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
value = [20, 40, 60, 80, 100, 120]
v1 = [[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例", title_pos="60%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1, legend_pos="80%")
line.grid(kline.get_series(), grid_left="55%")
line.show_config()
line.render()
# grid_5
import random
x_axis = ["12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a", "11a",
"12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p", "10p", "11p"]
y_aixs = ["Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday", "Sunday"]
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heatmap = HeatMap("热力图示例", height=700, is_grid=True)
heatmap.add("热力图直角坐标系", x_axis, y_aixs, data, is_visualmap=True, visual_top="45%",
visual_text_color="#000", visual_orient='horizontal', grid_bottom="60%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", title_top="52%")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True, legend_top="50%")
heatmap.grid(bar.get_series(), grid_top="60%")
heatmap.show_config()
heatmap.render()
def test_kline():
# kline_0
v1 = [[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1)
kline.show_config()
kline.render()
# kline_1
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1, mark_point=["max"], is_datazoom_show=True)
kline.show_config()
kline.render()
# kline_2
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1, mark_point=["max"],
is_datazoom_show=True, datazoom_orient='vertical')
kline.show_config()
kline.render()
def test_more():
page = Page()
# line
line = Line("折线图示例")
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
)
# pie
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图-圆环图示例", title_pos="center")
pie.add(
"",
CLOTHES,
v1,
radius=[40, 75],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
page.add([line, pie])
# kline
v1 = [
[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22],
]
kline = Kline("K 线图示例")
kline.add(
"日K",
["2017/7/{}".format(i + 1) for i in range(31)],
v1,
is_datazoom_show=True,
)
page.add(kline)
# radar
schema = [
("销售", 6500),
("管理", 16000),
("信息技术", 30000),
("客服", 38000),
("研发", 52000),
("市场", 25000),
]
v1 = [[4300, 10000, 28000, 35000, 50000, 19000]]
v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]
radar = Radar("雷达图示例")
radar.config(schema)
radar.add("预算分配", v1, is_splitline=True, is_axisline_show=True)
radar.add(
"实际开销",
v2,
label_color=["#4e79a7"],
is_area_show=False,
legend_selectedmode="single",
)
page.add(radar)
# scatter3d
import random
data = [
[
random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100),
]
for _ in range(80)
]
scatter3D = Scatter3D("3D 散点图示例", width=1200, height=600)
scatter3D.add("", data, is_visualmap=True, visual_range_color=RANGE_COLOR)
page.add(scatter3D)
# wordcloud
name = [
"Sam S Club",
"Macys",
"Amy Schumer",
"Jurassic World",
"Charter Communications",
"Chick Fil A",
"Planet Fitness",
"Pitch Perfect",
"Express",
"Home",
"Johnny Depp",
"Lena Dunham",
"Lewis Hamilton",
"KXAN",
"Mary Ellen Mark",
"Farrah Abraham",
"Rita Ora",
"Serena Williams",
"NCAA baseball tournament",
"Point Break",
]
value = [
10000,
6181,
4386,
4055,
2467,
2244,
1898,
1484,
1112,
965,
847,
582,
555,
550,
462,
366,
360,
282,
273,
265,
]
wordcloud = WordCloud(width=1300, height=620)
wordcloud.add("", name, value, word_size_range=[30, 100], rotate_step=66)
page.add(wordcloud)
# liquid
liquid = Liquid("水球图示例")
liquid.add("Liquid", [0.6])
page.add(liquid)
assert len(page) == 7
assert isinstance(page[0], Line)
assert (
("echarts" in page.js_dependencies)
or ("echarts.min" in page.js_dependencies)
)
page.render()
def graphpage(items,startdate,enddate,option,width1, height1): #labels:复权ork线or分笔 option:hfq, qfq or 15, 30, D, etc
page = Page()
for i in items:#generate numbers of graphs according to numbers of queries in treewidget
j = re.split("-",i)
if len(j)==3:
a = generateline(j[1],j[2],startdate,enddate,option)#stock number, Type, startdate, enddate, 30 or 15 or days
if a is None:
continue
time = [d[0] for d in a]#get time from returned dictionary
if j[2]!="Kline":
if len(a[0])==4 and a[0][2]=="bar": #for 分笔data
overlap = Overlap()
form = [e[1] for e in a]
bar = Bar(j[0] + "-" + j[2], width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(items))
bar.add(j[0] + "-" + j[2], time, form, yaxis_min = "dataMin",yaxis_max = "dataMax",is_datazoom_show = True, datazoom_type = "slider")
overlap.add(bar)
line = Line(j[0] + "price", width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(items))
price = [e[3] for e in a]
line.add(j[0] + "price", time, price, yaxis_min = "dataMin",yaxis_max = "dataMax", is_datazoom_show = True, datazoom_type = "slider",
yaxis_type="value")
overlap.add(line,yaxis_index=1, is_add_yaxis=True)
page.add(overlap)
if len(a[0])==5 and a[0][3]=="pie":
overlap = Overlap()
timeline = Timeline(is_auto_play=False, timeline_bottom=0) #zip(namearray,valuearray,quarter,flag,num)
namearray = [c[0] for c in a]
valuearray = [d[1] for d in a]
quarter = [e[2] for e in a]
num = a[0][4]
for x in range(0, num / 10):
list1 = valuearray[x]
names = namearray[x]
quarters = quarter[x][0]
for idx, val in enumerate(list1):
list1[idx] = float(val)
pie = Pie(j[0]+"-"+"前十股东".decode("utf-8"),width=width1 * 10 / 11, height=(height1 * 10 / 11))
pie.add(j[0]+"-"+"前十股东".decode("utf-8"), names, list1, radius=[30, 55], is_legend_show=False,
is_label_show=True, label_formatter = "{b}: {c}\n{d}%")
# print list
# print names
# print quarterarray
timeline.add(pie, quarters)
# namearray = [y for y in namearray[x]]
timeline.render()
return
#need more statement
else:
form = [e[1] for e in a]#for not分笔 data
line = Line(j[0] + "-" + j[2], width=width1*10/11, height=(height1*10/11)/len(items))
line.add(j[0] + "-" + j[2], time, form, is_datazoom_show=True, datazoom_type="slider",yaxis_min="dataMin",yaxis_max="dataMax")
page.add(line)
else:
overlap = Overlap()#for k线
close = zip(*a)[2]
candle = [[x[1], x[2], x[3], x[4]] for x in a]
candlestick = Kline(j[0] + "-" + j[2], width=width1*10/11, height = (height1*10/11) / len(items))
candlestick.add(j[0], time, candle, is_datazoom_show=True, datazoom_type="slider",yaxis_interval = 1)
overlap.add(candlestick)
if len(close)>10:
ma10 = calculateMa(close, 10)
line1 = Line(title_color="#C0C0C0")
line1.add(j[0] + "-" + "MA10", time, ma10)
overlap.add(line1)
if len(close)>20:
ma20 = calculateMa(close, 20)
line2 = Line(title_color="#C0C0C0")
line2.add(j[0] + "-" + "MA20", time, ma20)
overlap.add(line2)
if len(close)>30:
ma30 = calculateMa(close, 30)
line3 = Line(title_color="#C0C0C0")
line3.add(j[0] + "-" + "MA30", time, ma30)
overlap.add(line3)
page.add(overlap)
else:
for k in range(1, len(j)/3):#if graphs are combined
j[3*k-1] = re.sub("\n&","",j[3*k-1])
sizearray=[]
#if j[1] != "Candlestick"
layout = Overlap()
for i in xrange(0, len(j),3):
array = j[i:i +3]
b = generateline(array[1],array[2],startdate,enddate,option)
if b is None:
continue
btime = [d[0] for d in b]
if array[2] != "Kline":
if len(b[0])==4 and b[0][2]=="bar":
form = [e[1] for e in b]
bar = Bar(array[0] + "-" + array[2], width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(items))
bar.add(array[0] + "-" + array[2], btime, form, is_datazoom_show=True, datazoom_type="slider",
yaxis_min="dataMin", yaxis_max="dataMax")
layout.add(bar)
line = Line(array[0] + "price", width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(items))
price = [e[3] for e in b]
line.add(array[0] + "price", btime, price, is_datazoom_show=True, datazoom_type="slider",
yaxis_min="dataMin", yaxis_type="value")
layout.add(line, yaxis_index=1, is_add_yaxis=True)
else:
line = Line(array[0] + "-" + array[2],width=width1*10/11, height=(height1*10/11) / len(items))
line.add(array[0]+"-"+array[2], btime, b, is_datazoom_show=True, yaxis_max = "dataMax", yaxis_min = "dataMin",datazoom_type="slider")
layout.add(line)
else:
candle = [[x[1], x[2], x[3], x[4]] for x in b]
candlestick = Kline(array[0] + "-" + array[1], width=width1*10/11,
height=(height1*10/11) / len(items))
candlestick.add(array[0], btime, candle, is_datazoom_show=True, datazoom_type=["slider"])
#if i == 0:
close = zip(*b)[2]
if len(close)>10:
ma10 = calculateMa(close, 10)
line4 = Line(title_color="#C0C0C0")
line4.add(array[0] + "-" + "MA10", btime, ma10)
layout.add(line4)
if len(close)>20:
ma20 = calculateMa(close, 20)
line5 = Line(title_color="#C0C0C0")
line5.add(array[0] + "-" + "MA20", btime, ma20)
layout.add(line5)
if len(close)>30:
ma30 = calculateMa(close, 30)
line6 = Line(title_color="#C0C0C0")
line6.add(array[0] + "-" + "MA30", btime, ma30)
layout.add(line6)
layout.add(candlestick)
page.add(layout)
page.render()