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fix config_data bug

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This commit is contained in:
bxdd
2021-03-25 22:08:23 +08:00
parent 194217fb07
commit 5f60d18dfe
3 changed files with 30 additions and 4 deletions
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4
examples/rolling_process_data/workflow.py
View File

@@ -98,6 +98,7 @@ class RollingDataWorkflow(object):
dataset = init_instance_by_config(dataset_config)
for rolling_offset in range(self.rolling_cnt):
print(f"===========rolling{rolling_offset} start===========")
if rolling_offset:
dataset.init(
@@ -105,6 +106,8 @@ class RollingDataWorkflow(object):
"init_type": DataHandlerLP.IT_FIT_SEQ,
"start_time": datetime(train_start_time[0] + rolling_offset, *train_start_time[1:]),
"end_time": datetime(test_end_time[0] + rolling_offset, *test_end_time[1:]),
"fit_start_time": datetime(train_start_time[0] + rolling_offset, *train_start_time[1:]),
"fit_end_time": datetime(train_end_time[0] + rolling_offset, *train_end_time[1:]),
},
segment_kwargs={
"train": (
@@ -123,6 +126,7 @@ class RollingDataWorkflow(object):
)
dtrain, dvalid, dtest = dataset.prepare(["train", "valid", "test"])
print(dtrain, dvalid, dtest)
## print or dump data
print(f"===========rolling{rolling_offset} end===========")

2
qlib/data/dataset/__init__.py
View File

@@ -98,7 +98,7 @@ class DatasetH(Dataset):
raise TypeError(f"param handler_kwargs must be type dict, not {type(handler_kwargs)}")
kwargs_init = {}
kwargs_conf_data = {}
conf_data_arg = {"instruments", "start_time", "end_time"}
conf_data_arg = {"instruments", "start_time", "end_time", "fit_start_time", "fit_end_time"}
for k, v in handler_kwargs.items():
if k in conf_data_arg:
kwargs_conf_data.update({k: v})

28
qlib/data/dataset/handler.py
View File

@@ -115,8 +115,7 @@ class DataHandler(Serializable):
for k, v in kwargs.items():
if k in attr_list:
setattr(self, k, v)
else:
raise KeyError("Such config is not supported.")
def init(self, enable_cache: bool = False):
"""
@@ -405,11 +404,34 @@ class DataHandlerLP(DataHandler):
if self.drop_raw:
del self._data
def conf_data(self, **kwargs):
"""
configuration of data.
# what data to be loaded from data source
This method will be used when loading pickled handler from dataset.
The data will be initialized with different time range.
"""
attr_list = {"fit_start_time", "fit_end_time"}
for k, v in kwargs.items():
if k in attr_list:
for infer_processor in self.infer_processors:
if getattr(infer_processor, k, None):
setattr(infer_processor, k, v)
for learn_processor in self.learn_processors:
if getattr(learn_processor, k, None):
setattr(learn_processor, k, v)
super().conf_data(**kwargs)
# init type
IT_FIT_SEQ = "fit_seq" # the input of `fit` will be the output of the previous processor
IT_FIT_IND = "fit_ind" # the input of `fit` will be the original df
IT_LS = "load_state" # The state of the object has been load by pickle
def init(self, init_type: str = IT_FIT_SEQ, enable_cache: bool = False):
"""
Initialize the data of Qlib