def on_finish(self, timestmap):
self.on_trading_finish(timestmap)
# show the result
if self.draw_result:
import plotly.io as pio
pio.renderers.default = "browser"
reader = AccountStatsReader(trader_names=[self.trader_name])
df = reader.data_df
drawer = Drawer(main_data=NormalData(
df.copy()[['trader_name', 'timestamp', 'all_value']],
category_field='trader_name'))
drawer.draw_line(show=True)
def draw(self,
render='html',
file_name=None,
width=None,
height=None,
title=None,
keep_ui_state=True,
annotation_df=None,
target_type: TargetType = TargetType.open_long):
if target_type == TargetType.open_long:
df = self.open_long_df.copy()
elif target_type == TargetType.open_short:
df = self.open_short_df.copy()
df['target_type'] = target_type.value
if pd_is_not_null(df):
drawer = Drawer(
NormalData(df=df, annotation_df=annotation_df, time_field='timestamp', is_timeseries=True))
drawer.draw_table(render=render, file_name=file_name, width=width, height=height, title=title,
keep_ui_state=keep_ui_state)
def draw(self,
render='html',
file_name=None,
width=None,
height=None,
title=None,
keep_ui_state=True,
annotation_df=None,
target_type: TargetType = TargetType.open_long):
if target_type == TargetType.open_long:
df = self.open_long_df.copy()
elif target_type == TargetType.open_short:
df = self.open_short_df.copy()
df['target_type'] = target_type.value
if pd_is_not_null(df):
df = df.reset_index(drop=False)
drawer = Drawer(df)
drawer.draw_table(width=width, height=height, title=title,
keep_ui_state=keep_ui_state)
def result_drawer(self) -> Drawer:
return Drawer(NormalData(df=self.result_df))
def pipe_drawer(self) -> Drawer:
drawer = Drawer(NormalData(df=self.pipe_df))
return drawer
def draw_line(self, show=True):
drawer = Drawer(main_data=NormalData(
self.data_df.copy()[['trader_name', 'timestamp', 'all_value']],
category_field='trader_name'))
return drawer.draw_line(show=show)
self.filters += filter
else:
self.filters = filter
super().__init__(Order,
None,
None,
None,
None,
None,
None,
the_timestamp,
start_timestamp,
end_timestamp,
columns,
self.filters,
order,
None,
level,
category_field='trader_name',
time_field='timestamp',
computing_window=None)
if __name__ == '__main__':
reader = AccountStatsReader(trader_names=['000338_ma_trader'])
drawer = Drawer(main_data=NormalData(
reader.data_df.copy()[['trader_name', 'timestamp', 'all_value']],
category_field='trader_name'))
drawer.draw_line()
def factor_drawer(self) -> Drawer:
drawer = Drawer(NormalData(df=self.factor_df))
return drawer
entity_ids: List[str] = None, exchanges: List[str] = None, codes: List[str] = None,
the_timestamp: Union[str, pd.Timestamp] = None, start_timestamp: Union[str, pd.Timestamp] = None,
end_timestamp: Union[str, pd.Timestamp] = None,
columns: List = ['id', 'entity_id', 'timestamp', 'level', 'open', 'close', 'high', 'low'],
filters: List = None, order: object = None, limit: int = None,
level: Union[str, IntervalLevel] = IntervalLevel.LEVEL_1DAY, category_field: str = 'entity_id',
time_field: str = 'timestamp', computing_window: int = None, keep_all_timestamp: bool = False,
fill_method: str = 'ffill', effective_number: int = None,
accumulator: Accumulator = None, need_persist: bool = False, dry_run: bool = False,
adjust_type: Union[AdjustType, str] = None, window=30) -> None:
self.adjust_type = adjust_type
transformer = TopBottomTransformer(window=window)
super().__init__(entity_schema, provider, entity_provider, entity_ids, exchanges, codes, the_timestamp,
start_timestamp, end_timestamp, columns, filters, order, limit, level, category_field,
time_field, computing_window, keep_all_timestamp, fill_method, effective_number, transformer,
accumulator, need_persist, dry_run, adjust_type)
if __name__ == '__main__':
factor = TopBottomFactor(codes=['601318'], start_timestamp='2005-01-01',
end_timestamp=now_pd_timestamp(),
level=IntervalLevel.LEVEL_1DAY, window=120)
print(factor.factor_df)
data_reader1 = DataReader(codes=['601318'], data_schema=Stock1dKdata, entity_schema=Stock)
drawer = Drawer(main_df=data_reader1.data_df, factor_df=factor.factor_df[['top', 'bottom']])
drawer.draw_kline()
rects = []
duans = []
for index, item in duan_df.iterrows():
if len(duans) == 4:
x = duans[0][0]
x1 = duans[3][0]
if duans[0][1] < duans[1][1]:
y, y1 = intersect((duans[0][1], duans[1][1]), (duans[2][1], duans[3][1]))
else:
y, y1 = intersect((duans[1][1], duans[0][1]), (duans[3][1], duans[2][1]))
rects.append(((x, y), (x1, y1)))
duans = []
else:
duans.append((index[1], item.value))
drawer = Drawer(main_df=df, factor_df_list=[flag_df[['value']], duan_df], annotation_df=flag_df)
fig = drawer.draw_kline(show=False)
for rect in rects:
fig.add_shape(type="rect",
x0=rect[0][0], y0=rect[0][1], x1=rect[1][0], y1=rect[1][1],
line=dict(
color="RoyalBlue",
width=2,
),
fillcolor="LightSkyBlue",
)
fig.update_shapes(dict(xref='x', yref='y'))
fig.show()
# the __all__ is generated
__all__ = ['Direction', 'Fenxing', 'KState', 'DuanState', 'a_include_b', 'is_including', 'get_direction', 'is_up',
