def candLestick_mode():
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", ["2019/1/{}".format(i + 1) for i in range(31)], v1)
kline.render('kline.html')
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 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 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 plot(self, code=None):
if code is None:
data=[]
axis=[]
for dates,row in self.data.iterrows():
open,high,low,close=row[1:5]
datas=[open,close,low,high]
axis.append(dates[0])
data.append(datas)
path_name='.\QA_'+self.type+'_'+self.code[0]+'_'+self.if_fq+'.html'
kline=Kline(self.code[0]+'__'+self.if_fq+'__'+self.type,width=1360,height=700)
kline.add(self.code[0],axis,data,mark_point=["max","min"], is_datazoom_show=True,datazoom_orient='horizontal')
kline.render(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_'+self.type+'_'+code+'_'+self.if_fq+'.html'
kline=Kline(code+'__'+self.if_fq+'__'+self.type,width=1360,height=700)
kline.add(code,axis,data,mark_point=["max","min"], is_datazoom_show=True,datazoom_orient='horizontal')
kline.render(path_name)
QA_util_log_info('The Pic has been saved to your path: %s'%path_name)
def draw_kline_pic(title: str,
labels: list,
data_package: list,
y_min: int = 0,
y_max: int = 100,
y_formatter: str = "元人民币",
path: str = './charts/k_line.html'):
"""
K线图
:param title: 画图标题
:param labels: 图例
:param data_package: 数据包
:param y_min: y轴最小值
:param y_max: y轴最大值
:param y_formatter: y轴的格式化
:param path: 保存的路径
"""
style = Style(title_top="#fff", title_pos="left", width=1920, height=900)
kline = Kline(title=title, renderer='svg', **style.init_style)
kline.add('日K',
labels,
data_package,
yaxis_min=y_min,
yaxis_max=y_max,
yaxis_formatter=y_formatter,
mark_line=["min", "max"],
mark_point=["min", "max"],
is_datazoom_show=True,
datazoom_type="both",
datazoom_range=[80, 100])
kline.render(path=path)
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 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 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 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 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 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_not_set():
from pyecharts import Kline
kline = Kline("K 线图-默认示例")
kline.add("日K", [], [])
kline._option["series"][0]["itemStyle"] = {"normal": {"borderColor": NULL}}
content = kline._repr_html_()
assert '"borderColor": null' in content
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 K_line(date, v1, name):
kline = Kline(name)
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 test_kline_user_define_markline_style():
kline = Kline("K 线图示例 - 自定义标记线风格")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
data,
mark_line=["max"],
mark_line_symbolsize=0,
datazoom_orient='vertical',
mark_line_valuedim='close')
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,
)
return kline
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 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 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 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 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_datastruct(__stock_hq_base, code=None):
if code is None:
path_name = '.' + os.sep + 'QA_' + __stock_hq_base.type + \
'_codepackage_' + __stock_hq_base.if_fq + '.html'
kline = Kline('CodePackage_' + __stock_hq_base.if_fq + '_' +
__stock_hq_base.type,
width=1360,
height=700,
page_title='QUANTAXIS')
data_splits = __stock_hq_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(__stock_hq_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 __stock_hq_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_' + __stock_hq_base.type + \
'_' + code + '_' + __stock_hq_base.if_fq + '.html'
kline = Kline(code + '__' + __stock_hq_base.if_fq + '__' +
__stock_hq_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 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 test_kline_datazoom_vertical():
kline = Kline("K 线图示例 - dataZoom 垂直布局")
kline.add(
"日K",
["2017/7/{}".format(i + 1) for i in range(31)],
data,
mark_line=["max"],
is_datazoom_show=True,
datazoom_orient='vertical',
)
kline.render()
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 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 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 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_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 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_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 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 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 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 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()
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_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(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()
