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RL Training pipeline on 5-min data (#1415)

Browse Source 
* Workflow runnable

* CI

* Slight changes to make the workflow runnable. The changes of handler/provider should be reverted before merging.

* Train experiment successful

* Refine handler & provider

* CI issues

* Resolve PR comments

* Resolve PR comments

* CI issues

* Fix test issue

* Black
This commit is contained in:
Huoran Li
2023-01-18 16:17:06 +08:00
committed by GitHub
parent d8764660dc
commit d8fc9aea6b
9 changed files with 153 additions and 57 deletions
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57
qlib/contrib/data/highfreq_handler.py
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@@ -113,8 +113,11 @@ class HighFreqGeneralHandler(DataHandlerLP):
fit_end_time=None,
drop_raw=True,
day_length=240,
freq="1min",
columns=["$open", "$high", "$low", "$close", "$vwap"],
):
self.day_length = day_length
self.columns = columns
infer_processors = check_transform_proc(infer_processors, fit_start_time, fit_end_time)
learn_processors = check_transform_proc(learn_processors, fit_start_time, fit_end_time)
@@ -124,7 +127,7 @@ class HighFreqGeneralHandler(DataHandlerLP):
"kwargs": {
"config": self.get_feature_config(),
"swap_level": False,
"freq": "1min",
"freq": freq,
},
}
super().__init__(
@@ -160,19 +163,13 @@ class HighFreqGeneralHandler(DataHandlerLP):
)
return feature_ops
fields += [get_normalized_price_feature("$open", 0)]
fields += [get_normalized_price_feature("$high", 0)]
fields += [get_normalized_price_feature("$low", 0)]
fields += [get_normalized_price_feature("$close", 0)]
fields += [get_normalized_price_feature("$vwap", 0)]
names += ["$open", "$high", "$low", "$close", "$vwap"]
for column_name in self.columns:
fields.append(get_normalized_price_feature(column_name, 0))
names.append(column_name)
fields += [get_normalized_price_feature("$open", self.day_length)]
fields += [get_normalized_price_feature("$high", self.day_length)]
fields += [get_normalized_price_feature("$low", self.day_length)]
fields += [get_normalized_price_feature("$close", self.day_length)]
fields += [get_normalized_price_feature("$vwap", self.day_length)]
names += ["$open_1", "$high_1", "$low_1", "$close_1", "$vwap_1"]
for column_name in self.columns:
fields.append(get_normalized_price_feature(column_name, self.day_length))
names.append(column_name + "_1")
# calculate and fill nan with 0
fields += [
@@ -258,14 +255,17 @@ class HighFreqGeneralBacktestHandler(DataHandler):
start_time=None,
end_time=None,
day_length=240,
freq="1min",
columns=["$close", "$vwap", "$volume"],
):
self.day_length = day_length
self.columns = set(columns)
data_loader = {
"class": "QlibDataLoader",
"kwargs": {
"config": self.get_feature_config(),
"swap_level": False,
"freq": "1min",
"freq": freq,
},
}
super().__init__(
@@ -279,21 +279,24 @@ class HighFreqGeneralBacktestHandler(DataHandler):
fields = []
names = []
template_paused = f"Cut({{0}}, {self.day_length * 2}, None)"
template_fillnan = "FFillNan({0})"
template_if = "If(IsNull({1}), {0}, {1})"
fields += [
template_paused.format(template_fillnan.format("$close")),
]
names += ["$close0"]
if "$close" in self.columns:
template_paused = f"Cut({{0}}, {self.day_length * 2}, None)"
template_fillnan = "FFillNan({0})"
template_if = "If(IsNull({1}), {0}, {1})"
fields += [
template_paused.format(template_fillnan.format("$close")),
]
names += ["$close0"]
fields += [
template_paused.format(template_if.format(template_fillnan.format("$close"), "$vwap")),
]
names += ["$vwap0"]
if "$vwap" in self.columns:
fields += [
template_paused.format(template_if.format(template_fillnan.format("$close"), "$vwap")),
]
names += ["$vwap0"]
fields += [template_paused.format("If(IsNull({0}), 0, {0})".format("$volume"))]
names += ["$volume0"]
if "$volume" in self.columns:
fields += [template_paused.format("If(IsNull({0}), 0, {0})".format("$volume"))]
names += ["$volume0"]
return fields, names