本文整理汇总了Python中pythalesians.graphics.graphs.graphproperties.GraphProperties.display_brand_label方法的典型用法代码示例。如果您正苦于以下问题：Python GraphProperties.display_brand_label方法的具体用法？Python GraphProperties.display_brand_label怎么用？Python GraphProperties.display_brand_label使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pythalesians.graphics.graphs.graphproperties.GraphProperties的用法示例。
在下文中一共展示了GraphProperties.display_brand_label方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: plot_strategy_group_benchmark_pnl
# 需要导入模块: from pythalesians.graphics.graphs.graphproperties import GraphProperties [as 别名]
# 或者: from pythalesians.graphics.graphs.graphproperties.GraphProperties import display_brand_label [as 别名]
def plot_strategy_group_benchmark_pnl(self):
pf = PlotFactory()
gp = GraphProperties()
gp.title = self.FINAL_STRATEGY
gp.display_legend = True
gp.scale_factor = self.SCALE_FACTOR
#gp.color = 'RdYlGn'
gp.file_output = self.DUMP_PATH + self.FINAL_STRATEGY + ' (Group Benchmark PnL - cumulative).png'
# plot cumulative line of returns
pf.plot_line_graph(self.reduce_plot(self._strategy_group_benchmark_pnl), adapter = 'pythalesians', gp = gp)
# needs write stats flag turned on
try:
keys = self._strategy_group_benchmark_tsd.keys()
ir = []
for key in keys: ir.append(self._strategy_group_benchmark_tsd[key].inforatio()[0])
ret_stats = pandas.DataFrame(index = keys, data = ir, columns = ['IR'])
ret_stats = ret_stats.sort_index()
gp.file_output = self.DUMP_PATH + self.FINAL_STRATEGY + ' (Group Benchmark PnL - IR).png'
gp.display_brand_label = False
# plot ret stats
pf.plot_bar_graph(ret_stats, adapter = 'pythalesians', gp = gp)
except: pass示例2: wrapper
# 需要导入模块: from pythalesians.graphics.graphs.graphproperties import GraphProperties [as 别名]
# 或者: from pythalesians.graphics.graphs.graphproperties.GraphProperties import display_brand_label [as 别名]
gp.scale_factor = 2
gp.style_sheet = 'pythalesians'
# first use PyThalesians matplotlib wrapper
pf.plot_line_graph(daily_vals, adapter = 'pythalesians', gp = gp)
pf.plot_generic_graph(daily_vals, gp = gp, type = 'line')
# use modified 538 Matplotlib stylesheet
gp.style_sheet = '538-pythalesians'
pf.plot_line_graph(daily_vals, adapter = 'pythalesians', gp = gp)
# use miletus matplotlib stylesheet
gp.style_sheet = 'miletus-pythalesians'
pf.plot_line_graph(daily_vals, adapter = 'pythalesians', gp = gp)
# use ggplot matplotlib styleheet
gp.scale_factor = 1
gp.display_brand_label = False
gp.display_source = False
gp.style_sheet = 'ggplot-pythalesians'
gp.display_mpld3 = True
gp.html_file_output = 'demo.htm'
pf.plot_line_graph(daily_vals, adapter = 'pythalesians', gp = gp)
# now use PyThalesians bokeh wrapper (still needs a lot of work!)
gp.scale_factor = 2
gp.html_file_output = 'demo_bokeh.htm'
pf.plot_line_graph(daily_vals, adapter = 'bokeh', gp = gp)
pass