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doc and black for indicator

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wangwenxi.handsome
2021-07-27 12:14:43 +00:00
parent 66971d5f0d
commit ba1c575aa9
2 changed files with 17 additions and 12 deletions
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11
qlib/backtest/high_performance_ds.py
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@@ -82,7 +82,7 @@ class BaseQuote:
the columns of data to fetch the columns of data to fetch
method : Union[str, Callable] method : Union[str, Callable]
the method apply to data. the method apply to data.
e.g ["None", "last", "all", "sum", "mean", "any", qlib/utils/resam.py/ts_data_last] e.g [None, "last", "all", "sum", "mean", "any", qlib/utils/resam.py/ts_data_last]
Return Return
---------- ----------
@@ -187,7 +187,7 @@ class BaseSingleMetric:
def apply(self, func: dict) -> "BaseSingleMetric": def apply(self, func: dict) -> "BaseSingleMetric":
"""Replace the value of metric with func(metric). """Replace the value of metric with func(metric).
Currently, the func is only qlib/backtest/order/Order.parse_dir. Currently, the func is only qlib/backtest/order/Order.parse_dir.
""" """
raise NotImplementedError(f"Please implement the 'apply' method") raise NotImplementedError(f"Please implement the 'apply' method")
@@ -426,11 +426,6 @@ class PandasOrderIndicator(BaseOrderIndicator):
for metric in metrics: for metric in metrics:
tmp_metric = PandasSingleMetric({}) tmp_metric = PandasSingleMetric({})
for indicator in indicators: for indicator in indicators:
if(metric == "trade_price"): tmp_metric = tmp_metric.add(indicator.data[metric], fill_value)
tmp_metric = tmp_metric.add(
indicator.data["trade_price"] * indicator.data["deal_amount"], fill_value
)
else:
tmp_metric = tmp_metric.add(indicator.data[metric], fill_value)
metric_dict[metric] = tmp_metric.metric metric_dict[metric] = tmp_metric.metric
return metric_dict return metric_dict

12
qlib/backtest/report.py
View File

@@ -308,8 +308,9 @@ class Indicator:
def _update_order_fulfill_rate(self): def _update_order_fulfill_rate(self):
def func(deal_amount, amount): def func(deal_amount, amount):
# deal_amount is np.NaN when there is no inner decision. So full fill rate is 0.
tmp_deal_amount = deal_amount.replace({np.NaN: 0}) tmp_deal_amount = deal_amount.replace({np.NaN: 0})
return deal_amount / tmp_deal_amount return tmp_deal_amount / amount
self.order_indicator.transfer(func, "ffr") self.order_indicator.transfer(func, "ffr")
@@ -318,12 +319,21 @@ class Indicator:
self._update_order_fulfill_rate() self._update_order_fulfill_rate()
def _agg_order_trade_info(self, inner_order_indicators: List[Dict[str, pd.Series]]): def _agg_order_trade_info(self, inner_order_indicators: List[Dict[str, pd.Series]]):
# calculate total trade amount with each inner order indicator.
def trade_amount_func(deal_amount, trade_price):
return deal_amount * trade_price
for indicator in inner_order_indicators:
indicator.transfer(trade_amount_func, "trade_price")
# sum inner order indicators with same metric.
all_metric = ["inner_amount", "deal_amount", "trade_price", "trade_value", "trade_cost", "trade_dir"] all_metric = ["inner_amount", "deal_amount", "trade_price", "trade_value", "trade_cost", "trade_dir"]
metric_dict = self.order_indicator_cls.sum_all_indicators(inner_order_indicators, all_metric, fill_value=0) metric_dict = self.order_indicator_cls.sum_all_indicators(inner_order_indicators, all_metric, fill_value=0)
for metric in metric_dict: for metric in metric_dict:
self.order_indicator.assign(metric, metric_dict[metric]) self.order_indicator.assign(metric, metric_dict[metric])
def func(trade_price, deal_amount): def func(trade_price, deal_amount):
# trade_price is np.NaN instead of inf when deal_amount is zero.
tmp_deal_amount = deal_amount.replace({0: np.NaN}) tmp_deal_amount = deal_amount.replace({0: np.NaN})
return trade_price / tmp_deal_amount return trade_price / tmp_deal_amount