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Code Activity

make the prediction update more friendly (#609)

Browse Source 
* make the prediction update more friendly

* Update test_storage.py

* LabelUpdater

* Update test_storage.py

* Update test_storage.py

* Update test_storage.py

* Update test_storage.py

* Update setup.py

* Update workflow_config_lightgbm_Alpha158.yaml

* Update workflow_config_lightgbm_Alpha158.yaml

* Update workflow_config_lightgbm_Alpha158.yaml

* Update workflow_config_lightgbm_Alpha158.yaml

* Update workflow_config_lightgbm_Alpha158.yaml

* Update setup.py

* Update setup.py

* test CI only

* test CI only

* Update workflow_config_lightgbm_Alpha158.yaml

* Update setup.py

* fix "Segmentation fault" in macos

* Update test.yml

github action no longer supported ubuntu-16.04

* Update api.rst

update doc with new_lable

* Update api.rst

Co-authored-by: Wangwuyi123 <51237097+Wangwuyi123@users.noreply.github.com>
Co-authored-by: Pengrong Zhu <zhu.pengrong@foxmail.com>
This commit is contained in:
you-n-g
2021-09-30 20:54:44 +08:00
committed by GitHub
parent fc243fd29b
commit b9809a4c33
8 changed files with 233 additions and 46 deletions
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46
qlib/workflow/record_temp.py
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@@ -121,6 +121,30 @@ class SignalRecord(RecordTemp):
self.model = model
self.dataset = dataset
@staticmethod
def generate_label(dataset):
# NOTE:
# Python doesn't provide the downcasting mechanism.
# We use the trick here to downcast the class
orig_cls = dataset.__class__
dataset.__class__ = DatasetH
params = dict(segments="test", col_set="label", data_key=DataHandlerLP.DK_R)
try:
# Assume the backend handler is DataHandlerLP
raw_label = dataset.prepare(**params)
except TypeError:
# The argument number is not right
del params["data_key"]
# The backend handler should be DataHandler
raw_label = dataset.prepare(**params)
except AttributeError:
# The data handler is initialize with `drop_raw=True`...
# So raw_label is not available
raw_label = None
dataset.__class__ = orig_cls
return raw_label
def generate(self, **kwargs):
# generate prediciton
pred = self.model.predict(self.dataset)
@@ -136,28 +160,8 @@ class SignalRecord(RecordTemp):
pprint(pred.head(5))
if isinstance(self.dataset, DatasetH):
# NOTE:
# Python doesn't provide the downcasting mechanism.
# We use the trick here to downcast the class
orig_cls = self.dataset.__class__
self.dataset.__class__ = DatasetH
params = dict(segments="test", col_set="label", data_key=DataHandlerLP.DK_R)
try:
# Assume the backend handler is DataHandlerLP
raw_label = self.dataset.prepare(**params)
except TypeError:
# The argument number is not right
del params["data_key"]
# The backend handler should be DataHandler
raw_label = self.dataset.prepare(**params)
except AttributeError:
# The data handler is initialize with `drop_raw=True`...
# So raw_label is not available
raw_label = None
raw_label = self.generate_label(self.dataset)
self.recorder.save_objects(**{"label.pkl": raw_label})
self.dataset.__class__ = orig_cls
def list(self):
return ["pred.pkl", "label.pkl"]