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qlib/qlib/contrib/report/analysis_position/report.py
2021-04-22 14:13:36 +08:00

214 lines
6.8 KiB
Python

# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import pandas as pd
from ..graph import SubplotsGraph, BaseGraph
def _calculate_maximum(df: pd.DataFrame, is_ex: bool = False):
"""
:param df:
:param is_ex:
:return:
"""
if is_ex:
end_date = df["cum_ex_return_wo_cost_mdd"].idxmin()
start_date = df.loc[df.index <= end_date]["cum_ex_return_wo_cost"].idxmax()
else:
end_date = df["return_wo_mdd"].idxmin()
start_date = df.loc[df.index <= end_date]["cum_return_wo_cost"].idxmax()
return start_date, end_date
def _calculate_mdd(series):
"""
Calculate mdd
:param series:
:return:
"""
return series - series.cummax()
def _calculate_report_data(df: pd.DataFrame) -> pd.DataFrame:
"""
:param df:
:return:
"""
index_names = df.index.names
df.index = df.index.strftime("%Y-%m-%d")
report_df = pd.DataFrame()
report_df["cum_bench"] = df["bench"].cumsum()
report_df["cum_return_wo_cost"] = df["return"].cumsum()
report_df["cum_return_w_cost"] = (df["return"] - df["cost"]).cumsum()
# report_df['cum_return'] - report_df['cum_return'].cummax()
report_df["return_wo_mdd"] = _calculate_mdd(report_df["cum_return_wo_cost"])
report_df["return_w_cost_mdd"] = _calculate_mdd((df["return"] - df["cost"]).cumsum())
report_df["cum_ex_return_wo_cost"] = (df["return"] - df["bench"]).cumsum()
report_df["cum_ex_return_w_cost"] = (df["return"] - df["bench"] - df["cost"]).cumsum()
report_df["cum_ex_return_wo_cost_mdd"] = _calculate_mdd((df["return"] - df["bench"]).cumsum())
report_df["cum_ex_return_w_cost_mdd"] = _calculate_mdd((df["return"] - df["cost"] - df["bench"]).cumsum())
# return_wo_mdd , return_w_cost_mdd, cum_ex_return_wo_cost_mdd, cum_ex_return_w
report_df["turnover"] = df["turnover"]
report_df.sort_index(ascending=True, inplace=True)
report_df.index.names = index_names
return report_df
def _report_figure(df: pd.DataFrame) -> [list, tuple]:
"""
:param df:
:return:
"""
# Get data
report_df = _calculate_report_data(df)
# Maximum Drawdown
max_start_date, max_end_date = _calculate_maximum(report_df)
ex_max_start_date, ex_max_end_date = _calculate_maximum(report_df, True)
index_name = report_df.index.name
_temp_df = report_df.reset_index()
_temp_df.loc[-1] = 0
_temp_df = _temp_df.shift(1)
_temp_df.loc[0, index_name] = "T0"
_temp_df.set_index(index_name, inplace=True)
_temp_df.iloc[0] = 0
report_df = _temp_df
# Create figure
_default_kind_map = dict(kind="ScatterGraph", kwargs={"mode": "lines+markers"})
_temp_fill_args = {"fill": "tozeroy", "mode": "lines+markers"}
_column_row_col_dict = [
("cum_bench", dict(row=1, col=1)),
("cum_return_wo_cost", dict(row=1, col=1)),
("cum_return_w_cost", dict(row=1, col=1)),
("return_wo_mdd", dict(row=2, col=1, graph_kwargs=_temp_fill_args)),
("return_w_cost_mdd", dict(row=3, col=1, graph_kwargs=_temp_fill_args)),
("cum_ex_return_wo_cost", dict(row=4, col=1)),
("cum_ex_return_w_cost", dict(row=4, col=1)),
("turnover", dict(row=5, col=1)),
("cum_ex_return_w_cost_mdd", dict(row=6, col=1, graph_kwargs=_temp_fill_args)),
("cum_ex_return_wo_cost_mdd", dict(row=7, col=1, graph_kwargs=_temp_fill_args)),
]
_subplot_layout = dict()
for i in range(1, 8):
# yaxis
_subplot_layout.update({"yaxis{}".format(i): dict(zeroline=True, showline=True, showticklabels=True)})
_show_line = i == 7
_subplot_layout.update({"xaxis{}".format(i): dict(showline=_show_line, type="category", tickangle=45)})
_layout_style = dict(
height=1200,
title=" ",
shapes=[
{
"type": "rect",
"xref": "x",
"yref": "paper",
"x0": max_start_date,
"y0": 0.55,
"x1": max_end_date,
"y1": 1,
"fillcolor": "#d3d3d3",
"opacity": 0.3,
"line": {
"width": 0,
},
},
{
"type": "rect",
"xref": "x",
"yref": "paper",
"x0": ex_max_start_date,
"y0": 0,
"x1": ex_max_end_date,
"y1": 0.55,
"fillcolor": "#d3d3d3",
"opacity": 0.3,
"line": {
"width": 0,
},
},
],
)
_subplot_kwargs = dict(
shared_xaxes=True,
vertical_spacing=0.01,
rows=7,
cols=1,
row_width=[1, 1, 1, 3, 1, 1, 3],
print_grid=False,
)
figure = SubplotsGraph(
df=report_df,
layout=_layout_style,
sub_graph_data=_column_row_col_dict,
subplots_kwargs=_subplot_kwargs,
kind_map=_default_kind_map,
sub_graph_layout=_subplot_layout,
).figure
return (figure,)
def report_graph(report_df: pd.DataFrame, show_notebook: bool = True) -> [list, tuple]:
"""display backtest report
Example:
.. code-block:: python
from qlib.contrib.evaluate import backtest
from qlib.contrib.strategy import TopkDropoutStrategy
# backtest parameters
bparas = {}
bparas['limit_threshold'] = 0.095
bparas['account'] = 1000000000
sparas = {}
sparas['topk'] = 50
sparas['n_drop'] = 230
strategy = TopkDropoutStrategy(**sparas)
report_normal_df, _ = backtest(pred_df, strategy, **bparas)
qcr.analysis_position.report_graph(report_normal_df)
:param report_df: **df.index.name** must be **date**, **df.columns** must contain **return**, **turnover**, **cost**, **bench**.
.. code-block:: python
return cost bench turnover
date
2017-01-04 0.003421 0.000864 0.011693 0.576325
2017-01-05 0.000508 0.000447 0.000721 0.227882
2017-01-06 -0.003321 0.000212 -0.004322 0.102765
2017-01-09 0.006753 0.000212 0.006874 0.105864
2017-01-10 -0.000416 0.000440 -0.003350 0.208396
:param show_notebook: whether to display graphics in notebook, the default is **True**.
:return: if show_notebook is True, display in notebook; else return **plotly.graph_objs.Figure** list.
"""
report_df = report_df.copy()
fig_list = _report_figure(report_df)
if show_notebook:
BaseGraph.show_graph_in_notebook(fig_list)
else:
return fig_list