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https://github.com/microsoft/qlib.git
synced 2026-06-06 05:51:17 +08:00
rename group -> fields_group
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@@ -182,7 +182,7 @@ def _mount_nfs_uri(C):
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LOG.warning(f"{_remote_uri} on {_mount_path} is already mounted")
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def init_from_yaml_conf(conf_path):
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def init_from_yaml_conf(conf_path, **kwargs):
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"""init_from_yaml_conf
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:param conf_path: A path to the qlib config in yml format
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@@ -190,5 +190,6 @@ def init_from_yaml_conf(conf_path):
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with open(conf_path) as f:
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config = yaml.load(f, Loader=yaml.FullLoader)
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config.update(kwargs)
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default_conf = config.pop("default_conf", "client")
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init(default_conf, **config)
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@@ -23,7 +23,7 @@ class ALPHA360_Denoise(DataHandlerLP):
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}
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learn_processors = [
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{"class": "DropnaLabel", "kwargs": {"group": "label"}},
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{"class": "DropnaLabel", "kwargs": {"fields_group": "label"}},
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{"class": "CSZScoreNorm", "kwargs": {"fields_group": "label"}},
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]
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infer_processors = [
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@@ -96,7 +96,7 @@ class ALPHA360(DataHandlerLP):
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}
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learn_processors = [
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{"class": "DropnaLabel", "kwargs": {"group": "label"}},
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{"class": "DropnaLabel", "kwargs": {"fields_group": "label"}},
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{"class": "CSZScoreNorm", "kwargs": {"fields_group": "label"}},
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]
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infer_processors = [
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@@ -74,16 +74,16 @@ class Processor(Serializable):
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class DropnaProcessor(Processor):
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def __init__(self, group=None):
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self.group = group
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def __init__(self, fields_group=None):
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self.fields_group = fields_group
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def __call__(self, df):
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return df.dropna(subset=get_group_columns(df, self.group))
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return df.dropna(subset=get_group_columns(df, self.fields_group))
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class DropnaLabel(DropnaProcessor):
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def __init__(self, group="label"):
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super().__init__(group=group)
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def __init__(self, fields_group="label"):
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super().__init__(fields_group=fields_group)
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def is_for_infer(self) -> bool:
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"""The samples are dropped according to label. So it is not usable for inference"""
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