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fix comments

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bxdd
2021-07-03 18:42:40 +00:00
parent 8dd5788bac
commit ecf2f24d59
3 changed files with 23 additions and 21 deletions
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16
examples/nested_decision_execution/workflow.py
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@@ -124,14 +124,14 @@ class NestedDecisionExecutionWorkflow:
def _init_qlib(self): def _init_qlib(self):
"""initialize qlib""" """initialize qlib"""
provider_uri_day = "/data/stock_data/huaxia/qlib" # provider_uri_day = "/data/stock_data/huaxia/qlib"
provider_uri_1min = "/data2/stock_data/huaxia_1min_qlib" # provider_uri_1min = "/data2/stock_data/huaxia_1min_qlib"
# provider_uri_day = "~/.qlib/qlib_data/cn_data" # target_dir provider_uri_day = "~/.qlib/qlib_data/cn_data" # target_dir
# GetData().qlib_data(target_dir=provider_uri_day, region=REG_CN, version="v2", exists_skip=True) GetData().qlib_data(target_dir=provider_uri_day, region=REG_CN, version="v2", exists_skip=True)
# provider_uri_1min = HIGH_FREQ_CONFIG.get("provider_uri") provider_uri_1min = HIGH_FREQ_CONFIG.get("provider_uri")
# GetData().qlib_data( GetData().qlib_data(
# target_dir=provider_uri_1min, interval="1min", region=REG_CN, version="v2", exists_skip=True target_dir=provider_uri_1min, interval="1min", region=REG_CN, version="v2", exists_skip=True
# ) )
provider_uri_map = {"1min": provider_uri_1min, "day": provider_uri_day} provider_uri_map = {"1min": provider_uri_1min, "day": provider_uri_day}
client_config = { client_config = {
"calendar_provider": { "calendar_provider": {

8
qlib/data/dataset/storage.py
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@@ -37,8 +37,12 @@ class BaseHandlerStorage:
Return the original data instead of copy if possible. Return the original data instead of copy if possible.
proc_func: Callable proc_func: Callable
please refer to the doc of DataHandler.fetch please refer to the doc of DataHandler.fetch
"""
Returns
-------
pd.DataFrame
the dataframe fetched
"""
raise NotImplementedError("fetch is method not implemented!") raise NotImplementedError("fetch is method not implemented!")
@staticmethod @staticmethod
@@ -46,6 +50,7 @@ class BaseHandlerStorage:
raise NotImplementedError("from_df method is not implemented!") raise NotImplementedError("from_df method is not implemented!")
def is_proc_func_supported(self): def is_proc_func_supported(self):
"""whether the arg `proc_func` in `fetch` method is supported."""
raise NotImplementedError("is_proc_func_supported method is not implemented!") raise NotImplementedError("is_proc_func_supported method is not implemented!")
@@ -113,4 +118,5 @@ class HasingStockStorage(BaseHandlerStorage):
return pd.concat(fetch_stock_df_list, sort=False, copy=~fetch_orig) return pd.concat(fetch_stock_df_list, sort=False, copy=~fetch_orig)
def is_proc_func_supported(self): def is_proc_func_supported(self):
"""the arg `proc_func` in `fetch` method is not supported in HasingStockStorage"""
return False return False

20
qlib/utils/resam.py
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@@ -3,6 +3,8 @@ import datetime
import numpy as np import numpy as np
import pandas as pd import pandas as pd
from functools import partial
from typing import Tuple, List, Union, Optional, Callable from typing import Tuple, List, Union, Optional, Callable
from . import lazy_sort_index from . import lazy_sort_index
@@ -284,21 +286,15 @@ def get_valid_value(series, last=True):
return series.fillna(method="ffill").iloc[-1] if last else series.fillna(method="bfill").iloc[0] return series.fillna(method="ffill").iloc[-1] if last else series.fillna(method="bfill").iloc[0]
def ts_data_last(ts_feature): def _ts_data_valid(ts_feature, last=False):
"""get the last not nan value of pd.Series|DataFrame with single level index""" """get the first/last not nan value of pd.Series|DataFrame with single level index"""
if isinstance(ts_feature, pd.DataFrame): if isinstance(ts_feature, pd.DataFrame):
return ts_feature.apply(lambda column: get_valid_value(column, last=True)) return ts_feature.apply(lambda column: get_valid_value(column, last=last))
elif isinstance(ts_feature, pd.Series): elif isinstance(ts_feature, pd.Series):
return get_valid_value(ts_feature, last=True) return get_valid_value(ts_feature, last=last)
else: else:
raise TypeError(f"ts_feature should be pd.DataFrame/Series, not {type(ts_feature)}") raise TypeError(f"ts_feature should be pd.DataFrame/Series, not {type(ts_feature)}")
def ts_data_first(ts_feature): ts_data_last = partial(_ts_data_valid, last=False)
"""get the first not nan value of pd.Series|DataFrame with single level index""" ts_data_first = partial(_ts_data_valid, last=True)
if isinstance(ts_feature, pd.DataFrame):
return ts_feature.apply(lambda column: get_valid_value(column, last=False))
elif isinstance(ts_feature, pd.Series):
return get_valid_value(ts_feature, last=False)
else:
raise TypeError(f"ts_feature should be pd.DataFrame/Series, not {type(ts_feature)}")