From 43a8f502ede828c27e37a3092e9396821efa7850 Mon Sep 17 00:00:00 2001
From: "wangwenxi.handsome" <wangwenxi.handsome@gmail.com>
Date: Fri, 27 Aug 2021 10:48:10 +0000
Subject: [PATCH] fix bug

---
 qlib/backtest/exchange.py            |  26 ++---
 qlib/backtest/high_performance_ds.py | 158 ++++++++++++---------------
 qlib/backtest/order.py               |   2 +-
 qlib/backtest/report.py              |  16 +--
 qlib/utils/index_data.py             |  40 +++----
 qlib/utils/time.py                   |   4 +-
 6 files changed, 109 insertions(+), 137 deletions(-)

diff --git a/qlib/backtest/exchange.py b/qlib/backtest/exchange.py
index 4c726720c..347f33790 100644
--- a/qlib/backtest/exchange.py
+++ b/qlib/backtest/exchange.py
@@ -18,7 +18,7 @@ from ..config import C, REG_CN
 from ..utils.resam import resam_ts_data, ts_data_last
 from ..log import get_module_logger
 from .order import Order, OrderDir, OrderHelper
-from .high_performance_ds import PandasQuote, CN1min_NumpyQuote
+from .high_performance_ds import PandasQuote, CN1minNumpyQuote
 
 
 class Exchange:
@@ -36,7 +36,7 @@ class Exchange:
         close_cost=0.0025,
         min_cost=5,
         extra_quote=None,
-        quote_cls=CN1min_NumpyQuote,
+        quote_cls=CN1minNumpyQuote,
         **kwargs,
     ):
         """__init__
@@ -327,20 +327,20 @@ class Exchange:
 
         """
         if direction is None:
-            buy_limit = self.quote.get_data(stock_id, start_time, end_time, fields="limit_buy", method="all")
-            sell_limit = self.quote.get_data(stock_id, start_time, end_time, fields="limit_sell", method="all")
+            buy_limit = self.quote.get_data(stock_id, start_time, end_time, field="limit_buy", method="all")
+            sell_limit = self.quote.get_data(stock_id, start_time, end_time, field="limit_sell", method="all")
             return buy_limit or sell_limit
         elif direction == Order.BUY:
-            return self.quote.get_data(stock_id, start_time, end_time, fields="limit_buy", method="all")
+            return self.quote.get_data(stock_id, start_time, end_time, field="limit_buy", method="all")
         elif direction == Order.SELL:
-            return self.quote.get_data(stock_id, start_time, end_time, fields="limit_sell", method="all")
+            return self.quote.get_data(stock_id, start_time, end_time, field="limit_sell", method="all")
         else:
             raise ValueError(f"direction {direction} is not supported!")
 
     def check_stock_suspended(self, stock_id, start_time, end_time):
         # is suspended
         if stock_id in self.quote.get_all_stock():
-            return self.quote.get_data(stock_id, start_time, end_time) is None
+            return self.quote.get_data(stock_id, start_time, end_time, "$close") is None
         else:
             return True
 
@@ -411,10 +411,10 @@ class Exchange:
         return self.quote.get_data(stock_id, start_time, end_time, method=method)
 
     def get_close(self, stock_id, start_time, end_time, method=ts_data_last):
-        return self.quote.get_data(stock_id, start_time, end_time, fields="$close", method=method)
+        return self.quote.get_data(stock_id, start_time, end_time, field="$close", method=method)
 
     def get_volume(self, stock_id, start_time, end_time, method="sum"):
-        return self.quote.get_data(stock_id, start_time, end_time, fields="$volume", method=method)
+        return self.quote.get_data(stock_id, start_time, end_time, field="$volume", method=method)
 
     def get_deal_price(self, stock_id, start_time, end_time, direction: OrderDir, method=ts_data_last):
         if direction == OrderDir.SELL:
@@ -423,7 +423,7 @@ class Exchange:
             pstr = self.buy_price
         else:
             raise NotImplementedError(f"This type of input is not supported")
-        deal_price = self.quote.get_data(stock_id, start_time, end_time, fields=pstr, method=method)
+        deal_price = self.quote.get_data(stock_id, start_time, end_time, field=pstr, method=method)
         if method is not None and (np.isclose(deal_price, 0.0) or np.isnan(deal_price)):
             self.logger.warning(f"(stock_id:{stock_id}, trade_time:{(start_time, end_time)}, {pstr}): {deal_price}!!!")
             self.logger.warning(f"setting deal_price to close price")
@@ -441,7 +441,7 @@ class Exchange:
         assert start_time is not None and end_time is not None, "the time range must be given"
         if stock_id not in self.quote.get_all_stock():
             return None
-        return self.quote.get_data(stock_id, start_time, end_time, fields="$factor", method=ts_data_last)
+        return self.quote.get_data(stock_id, start_time, end_time, field="$factor", method=ts_data_last)
 
     def generate_amount_position_from_weight_position(
         self, weight_position, cash, start_time, end_time, direction=OrderDir.BUY
@@ -684,7 +684,7 @@ class Exchange:
                     order.stock_id,
                     order.start_time,
                     order.end_time,
-                    fields=limit[1],
+                    field=limit[1],
                     method="sum",
                 )
                 vol_limit_num.append(limit_value)
@@ -693,7 +693,7 @@ class Exchange:
                     order.stock_id,
                     order.start_time,
                     order.end_time,
-                    fields=limit[1],
+                    field=limit[1],
                     method=ts_data_last,
                 )
                 vol_limit_num.append(limit_value - dealt_order_amount[order.stock_id])
diff --git a/qlib/backtest/high_performance_ds.py b/qlib/backtest/high_performance_ds.py
index f17f6e14c..d125fadc8 100644
--- a/qlib/backtest/high_performance_ds.py
+++ b/qlib/backtest/high_performance_ds.py
@@ -2,21 +2,19 @@
 # Licensed under the MIT License.
 
 
-from builtins import ValueError, isinstance
 from functools import lru_cache
 import logging
 from typing import List, Text, Union, Callable, Iterable, Dict
 from collections import OrderedDict
 
 import inspect
-import bisect
 import pandas as pd
 import numpy as np
 
-from ..utils.index_data import IndexData
+from ..utils.index_data import IndexData, SingleData
 from ..utils.resam import resam_ts_data, ts_data_last
 from ..log import get_module_logger
-from ..utils.time import if_single_data
+from ..utils.time import is_single_value
 
 
 class BaseQuote:
@@ -39,10 +37,10 @@ class BaseQuote:
         stock_id: str,
         start_time: Union[pd.Timestamp, str],
         end_time: Union[pd.Timestamp, str],
-        fields: Union[str, None] = None,
+        field: Union[str],
         method: Union[str, Callable, None] = None,
-    ) -> Union[None, Union[int, float, bool], "IndexData"]:
-        """get the specific fields of stock data during start time and end_time,
+    ) -> Union[None, int, float, bool, "IndexData"]:
+        """get the specific field of stock data during start time and end_time,
            and apply method to the data.
 
            Example:
@@ -63,22 +61,13 @@ class BaseQuote:
 
                 this function is used for three case:
 
-                1. Both fields and method are not None. It returns int/float/bool.
-                    print(get_data(stock_id="SH600000", start_time="2010-01-04", end_time="2010-01-06", fields="$close", method="last"))
+                1. method is not None. It returns int/float/bool.
+                    print(get_data(stock_id="SH600000", start_time="2010-01-04", end_time="2010-01-06", field="$close", method="last"))
 
                     85.713585
 
-                2. Both fields and method are None. It returns np.ndarray.
-                    print(get_data(stock_id="SH600000", start_time="2010-01-04", end_time="2010-01-06", fields=None, method=None))
-
-                    [
-                        [86.778313, 16162960.0],
-                        [87.433578, 28117442.0],
-                        [85.713585, 23632884.0],
-                    ]
-
-                3. fields is not None, and method is None. It returns IndexData.
-                    print(get_data(stock_id="SH600000", start_time="2010-01-04", end_time="2010-01-06", fields="$close", method=None))
+                2. method is None. It returns IndexData.
+                    print(get_data(stock_id="SH600000", start_time="2010-01-04", end_time="2010-01-06", field="$close", method=None))
 
                     IndexData([86.778313, 87.433578, 85.713585], [2010-01-04, 2010-01-05, 2010-01-06])
 
@@ -89,7 +78,7 @@ class BaseQuote:
             closed start time for backtest
         end_time : Union[pd.Timestamp, str]
             closed end time for backtest
-        fields : Union[str, None]
+        field : str
             the columns of data to fetch
         method : Union[str, Callable, None]
             the method apply to data.
@@ -97,7 +86,8 @@ class BaseQuote:
 
         Return
         ----------
-        Union[None, Union[int, float, bool], IndexData]
+        Union[None, int, float, bool, IndexData]
+            None means there is no stock data from data source.
             please refer to Example as following.
         """
 
@@ -115,32 +105,21 @@ class PandasQuote(BaseQuote):
     def get_all_stock(self):
         return self.data.keys()
 
-    def get_data(self, stock_id, start_time, end_time, fields=None, method=None):
-        if fields is None and method is not None:
-            raise ValueError(f"method must be None when fields is None")
-
-        if fields is None:
-            stock_data = resam_ts_data(self.data[stock_id], start_time, end_time, method=method)
-        elif isinstance(fields, str):
-            stock_data = resam_ts_data(self.data[stock_id][fields], start_time, end_time, method=method)
-        else:
-            raise ValueError(f"fields must be None, str")
-
+    def get_data(self, stock_id, start_time, end_time, field, method=None):
+        stock_data = resam_ts_data(self.data[stock_id][field], start_time, end_time, method=method)
         if stock_data is None:
             return None
-        elif isinstance(stock_data, (bool, np.bool_, int, float, np.signedinteger, np.floating)):
+        elif isinstance(stock_data, (bool, np.bool_, int, float, np.number)):
             return stock_data
         elif isinstance(stock_data, pd.Series):
             return IndexData.Series(stock_data)
-        elif isinstance(stock_data, pd.DataFrame):
-            return stock_data.values
         else:
             raise ValueError(f"stock data from resam_ts_data must be a number, pd.Series or pd.DataFrame")
 
 
-class CN1min_NumpyQuote(BaseQuote):
+class CN1minNumpyQuote(BaseQuote):
     def __init__(self, quote_df: pd.DataFrame):
-        """CN1min_NumpyQuote
+        """CN1minNumpyQuote
 
         Parameters
         ----------
@@ -153,48 +132,37 @@ class CN1min_NumpyQuote(BaseQuote):
         for stock_id, stock_val in quote_df.groupby(level="instrument"):
             quote_dict[stock_id] = IndexData.DataFrame(stock_val.droplevel(level="instrument"))
         self.data = quote_dict
-        self.freq = np.timedelta64(1, "m")
+        self.freq = pd.Timedelta(minutes=1)
 
     def get_all_stock(self):
         return self.data.keys()
 
     @lru_cache(maxsize=512)
-    def get_data(self, stock_id, start_time, end_time, fields=None, method=None):
-        if fields is None and method is not None:
-            raise ValueError(f"method must be None when fields is None")
-
+    def get_data(self, stock_id, start_time, end_time, field, method=None):
         # check stock id
         if stock_id not in self.get_all_stock():
             return None
 
         # single data
         # If it don't consider the classification of single data, it will consume a lot of time.
-        if if_single_data(start_time, end_time, self.freq):
+        if is_single_value(start_time, end_time, self.freq):
             now_index_map = self.data[stock_id].index_map
             now_columns_map = self.data[stock_id].columns_map
             if start_time not in now_index_map:
                 return None
-            if fields is None:
-                return self.data[stock_id].values[now_index_map[start_time]]
             else:
-                return self.data[stock_id].values[now_index_map[start_time], now_columns_map[fields]]
+                return self.data[stock_id].values[now_index_map[start_time], now_columns_map[field]]
 
         # multi data
         else:
-            if fields is None and method is None:
-                stock_data = self.data[stock_id].loc(start_time, end_time)
-                if stock_data.empty:
-                    return None
-                else:
-                    return stock_data.values
-            elif fields is not None and method is None:
-                stock_data = self.data[stock_id].loc(start_time, end_time, fields)
+            if method is None:
+                stock_data = self.data[stock_id].loc(start_time, end_time, field)
                 if stock_data.empty:
                     return None
                 else:
                     return stock_data
-            elif fields is not None and method is not None:
-                stock_data = self.data[stock_id].loc(start_time, end_time, fields)
+            else:
+                stock_data = self.data[stock_id].loc(start_time, end_time, field)
                 if stock_data.empty:
                     return None
                 elif len(stock_data) == 1:
@@ -231,6 +199,20 @@ class BaseSingleMetric:
     """
 
     def __init__(self, metric: Union[dict, pd.Series]):
+        """Single data structure for each metric.
+
+        Parameters
+        ----------
+        metric : Union[dict, pd.Series]
+            keys/index is stock_id, value is the metric value.
+            for example:
+                SH600068    NaN
+                SH600079    1.0
+                SH600266    NaN
+                           ...
+                SZ300692    NaN
+                SZ300719    NaN,
+        """
         raise NotImplementedError(f"Please implement the `__init__` method")
 
     def __add__(self, other: Union["BaseSingleMetric", int, float]) -> "BaseSingleMetric":
@@ -277,7 +259,7 @@ class BaseSingleMetric:
     def abs(self) -> "BaseSingleMetric":
         raise NotImplementedError(f"Please implement the `abs` method")
 
-    def astype(self, type: type) -> "BaseSingleMetric":
+    def astype(self, dtype: type) -> "BaseSingleMetric":
         raise NotImplementedError(f"Please implement the `astype` method")
 
     @property
@@ -316,7 +298,8 @@ class BaseOrderIndicator:
         to inherit the BaseSingleMetric.
     """
 
-    def __init__(self):
+    def __init__(self, data):
+        self.data = data
         self.logger = get_module_logger("online operator")
 
     def assign(self, col: str, metric: Union[dict, pd.Series]):
@@ -358,8 +341,13 @@ class BaseOrderIndicator:
         BaseSingleMetric
             new metric.
         """
-
-        raise NotImplementedError(f"Please implement the 'transfer' method")
+        func_sig = inspect.signature(func).parameters.keys()
+        func_kwargs = {sig: self.data[sig] for sig in func_sig}
+        tmp_metric = func(**func_kwargs)
+        if new_col is not None:
+            self.data[new_col] = tmp_metric
+        else:
+            return tmp_metric
 
     def get_metric_series(self, metric: str) -> pd.Series:
         """return the single metric with pd.Series format.
@@ -378,8 +366,8 @@ class BaseOrderIndicator:
 
         raise NotImplementedError(f"Please implement the 'get_metric_series' method")
 
-    def get_index_data(self, metric) -> IndexData.Series:
-        """get one metric with the format of IndexData.Series
+    def get_index_data(self, metric) -> SingleData:
+        """get one metric with the format of SingleData
 
         Parameters
         ----------
@@ -389,7 +377,7 @@ class BaseOrderIndicator:
         Return
         ------
         IndexData.Series
-            one metric with the format of IndexData.Series
+            one metric with the format of SingleData
         """
 
         raise NotImplementedError(f"Please implement the 'get_index_data' method")
@@ -431,6 +419,9 @@ class BaseOrderIndicator:
 
 
 class SingleMetric(BaseSingleMetric):
+    def __init__(self, metric):
+        self.metric = metric
+
     def __add__(self, other):
         if isinstance(other, (int, float)):
             return self.__class__(self.metric + other)
@@ -502,7 +493,7 @@ class SingleMetric(BaseSingleMetric):
 class PandasSingleMetric(SingleMetric):
     """Each SingleMetric is based on pd.Series."""
 
-    def __init__(self, metric: Union[dict, pd.Series]):
+    def __init__(self, metric: Union[dict, pd.Series] = {}):
         if isinstance(metric, dict):
             self.metric = pd.Series(metric)
         elif isinstance(metric, pd.Series):
@@ -522,13 +513,17 @@ class PandasSingleMetric(SingleMetric):
     def abs(self):
         return self.__class__(self.metric.abs())
 
-    def astype(self, type):
-        return self.__class__(self.metric.astype(type))
+    def astype(self, dtype):
+        return self.__class__(self.metric.astype(dtype))
 
     @property
     def empty(self):
         return self.metric.empty
 
+    @property
+    def index(self):
+        return list(self.metric.index)
+
     def add(self, other, fill_value=None):
         return self.__class__(self.metric.add(other.metric, fill_value=fill_value))
 
@@ -538,6 +533,9 @@ class PandasSingleMetric(SingleMetric):
     def apply(self, func: Callable):
         return self.__class__(self.metric.apply(func))
 
+    def reindex(self, index, fill_value):
+        return self.__class__(self.metric.reindex(index, fill_value=fill_value))
+
 
 class PandasOrderIndicator(BaseOrderIndicator):
     """
@@ -552,15 +550,6 @@ class PandasOrderIndicator(BaseOrderIndicator):
     def assign(self, col: str, metric: Union[dict, pd.Series]):
         self.data[col] = PandasSingleMetric(metric)
 
-    def transfer(self, func: Callable, new_col: str = None) -> Union[None, PandasSingleMetric]:
-        func_sig = inspect.signature(func).parameters.keys()
-        func_kwargs = {sig: self.data[sig] for sig in func_sig}
-        tmp_metric = func(**func_kwargs)
-        if new_col is not None:
-            self.data[new_col] = tmp_metric
-        else:
-            return tmp_metric
-
     def get_index_data(self, metric):
         if metric in self.data:
             return IndexData.Series(self.data[metric].metric)
@@ -577,7 +566,7 @@ class PandasOrderIndicator(BaseOrderIndicator):
         return {k: v.metric for k, v in self.data.items()}
 
     @staticmethod
-    def sum_all_indicators(order_indicator, indicators: list, metrics: Union[str, List[str]], fill_value=None):
+    def sum_all_indicators(order_indicator, indicators: list, metrics: Union[str, List[str]], fill_value=0):
         if isinstance(metrics, str):
             metrics = [metrics]
         for metric in metrics:
@@ -589,26 +578,17 @@ class PandasOrderIndicator(BaseOrderIndicator):
 
 class NumpyOrderIndicator(BaseOrderIndicator):
     """
-    The data structure is OrderedDict(str: IndexData.Series).
+    The data structure is OrderedDict(str: SingleData).
     Each IndexData.Series is one metric.
     Str is the name of metric.
     """
 
     def __init__(self):
-        self.data: Dict[str, IndexData.Series] = OrderedDict()
+        self.data: Dict[str, SingleData] = OrderedDict()
 
     def assign(self, col: str, metric: dict):
         self.data[col] = IndexData.Series(metric)
 
-    def transfer(self, func: Callable, new_col: str = None) -> Union[None, IndexData.Series]:
-        func_sig = inspect.signature(func).parameters.keys()
-        func_kwargs = {sig: self.data[sig] for sig in func_sig}
-        tmp_metric = func(**func_kwargs)
-        if new_col is not None:
-            self.data[new_col] = tmp_metric
-        else:
-            return tmp_metric
-
     def get_index_data(self, metric):
         if metric in self.data:
             return self.data[metric]
@@ -616,7 +596,7 @@ class NumpyOrderIndicator(BaseOrderIndicator):
             return IndexData.Series()
 
     def get_metric_series(self, metric: str) -> Union[pd.Series]:
-        return self.data[metric].to_pd_series()
+        return self.data[metric].to_series()
 
     def to_series(self) -> Dict[str, pd.Series]:
         tmp_metric_dict = {}
diff --git a/qlib/backtest/order.py b/qlib/backtest/order.py
index 42af5f24e..e169ffd64 100644
--- a/qlib/backtest/order.py
+++ b/qlib/backtest/order.py
@@ -109,7 +109,7 @@ class Order:
         return self.direction * 2 - 1
 
     @staticmethod
-    def parse_dir(direction: Union[str, int, np.integer, OrderDir, np.ndarray]) -> OrderDir:
+    def parse_dir(direction: Union[str, int, np.integer, OrderDir, np.ndarray]) -> Union[OrderDir, np.ndarray]:
         if isinstance(direction, OrderDir):
             return direction
         elif isinstance(direction, (int, float, np.integer, np.floating)):
diff --git a/qlib/backtest/report.py b/qlib/backtest/report.py
index 31c3e7b0a..e29921da6 100644
--- a/qlib/backtest/report.py
+++ b/qlib/backtest/report.py
@@ -4,15 +4,14 @@
 
 from collections import OrderedDict
 import pathlib
-from typing import Dict, List, Tuple
+from typing import Dict, List, Tuple, Union
 
 import numpy as np
 import pandas as pd
 
 from qlib.backtest.exchange import Exchange
 from qlib.backtest.order import BaseTradeDecision, Order, OrderDir
-
-from .high_performance_ds import PandasOrderIndicator, NumpyOrderIndicator
+from .high_performance_ds import PandasOrderIndicator, NumpyOrderIndicator, SingleMetric
 from ..utils.index_data import IndexData, SingleData
 from ..tests.config import CSI300_BENCH
 from ..utils.resam import get_higher_eq_freq_feature, resam_ts_data
@@ -305,8 +304,9 @@ class Indicator:
 
     def _update_order_fulfill_rate(self):
         def func(deal_amount, amount):
-            # deal_amount is np.NaN when there is no inner decision. So full fill rate is 0.
-            tmp_deal_amount = deal_amount.replace({np.NaN: 0})
+            # deal_amount is np.NaN or None when there is no inner decision. So full fill rate is 0.
+            tmp_deal_amount = deal_amount.reindex(amount.index, 0)
+            tmp_deal_amount = tmp_deal_amount.replace({np.NaN: 0})
             return tmp_deal_amount / amount
 
         self.order_indicator.transfer(func, "ffr")
@@ -385,7 +385,7 @@ class Indicator:
         if price_s is None:
             return None, None
 
-        if isinstance(price_s, (int, float, np.signedinteger, np.floating)):
+        if isinstance(price_s, (int, float, np.number)):
             price_s = IndexData.Series(price_s, [trade_start_time])
         elif isinstance(price_s, SingleData):
             pass
@@ -400,7 +400,7 @@ class Indicator:
 
         if agg == "vwap":
             volume_s = trade_exchange.get_volume(inst, trade_start_time, trade_end_time, method=None)
-            if isinstance(volume_s, (int, float, np.floating)):
+            if isinstance(volume_s, (int, float, np.number)):
                 volume_s = IndexData.Series(volume_s, [trade_start_time])
             volume_s = volume_s.reindex(price_s.index)
         elif agg == "twap":
@@ -414,7 +414,7 @@ class Indicator:
 
     def _agg_base_price(
         self,
-        inner_order_indicators: List[Dict[str, pd.Series]],
+        inner_order_indicators: List[Dict[str, Union[SingleMetric, SingleData]]],
         decision_list: List[Tuple[BaseTradeDecision, pd.Timestamp, pd.Timestamp]],
         trade_exchange: Exchange,
         pa_config: dict = {},
diff --git a/qlib/utils/index_data.py b/qlib/utils/index_data.py
index 8c0d1874e..8a92cfcf5 100644
--- a/qlib/utils/index_data.py
+++ b/qlib/utils/index_data.py
@@ -35,7 +35,7 @@ class IndexData:
             return MultiData(data, index, columns)
 
     @staticmethod
-    def concat(data_list, axis=0):
+    def concat(data_list: Union["SingleData"], axis=0) -> "MultiData":
         """concat all SingleData by index.
         TODO: now just for SingleData.
 
@@ -50,7 +50,7 @@ class IndexData:
             the MultiData with ndim == 2
         """
         if axis == 0:
-            raise NotImplementedError(f"please implement this fuc when axis == 0")
+            raise NotImplementedError(f"please implement this func when axis == 0")
         elif axis == 1:
             # get all index and row
             all_index = set()
@@ -90,7 +90,7 @@ class BaseData:
         raise NotImplementedError(f"please implement _align_index func")
 
     def __add__(self, other):
-        if isinstance(other, (int, float, np.floating)):
+        if isinstance(other, (int, float, np.number)):
             return self.__class__(self.data + other, *self.index_columns)
         elif isinstance(other, self.__class__):
             tmp_data1, tmp_data2 = self._align_index(other)
@@ -99,7 +99,7 @@ class BaseData:
             return NotImplemented
 
     def __sub__(self, other):
-        if isinstance(other, (int, float, np.floating)):
+        if isinstance(other, (int, float, np.number)):
             return self.__class__(self.data - other, *self.index_columns)
         elif isinstance(other, self.__class__):
             tmp_data1, tmp_data2 = self._align_index(other)
@@ -108,7 +108,7 @@ class BaseData:
             return NotImplemented
 
     def __rsub__(self, other):
-        if isinstance(other, (int, float, np.floating)):
+        if isinstance(other, (int, float, np.number)):
             return self.__class__(other - self.data, *self.index_columns)
         elif isinstance(other, self.__class__):
             tmp_data1, tmp_data2 = self._align_index(other)
@@ -117,7 +117,7 @@ class BaseData:
             return NotImplemented
 
     def __mul__(self, other):
-        if isinstance(other, (int, float, np.floating)):
+        if isinstance(other, (int, float, np.number)):
             return self.__class__(self.data * other, *self.index_columns)
         elif isinstance(other, self.__class__):
             tmp_data1, tmp_data2 = self._align_index(other)
@@ -126,7 +126,7 @@ class BaseData:
             return NotImplemented
 
     def __truediv__(self, other):
-        if isinstance(other, (int, float, np.floating)):
+        if isinstance(other, (int, float, np.number)):
             return self.__class__(self.data / other, *self.index_columns)
         elif isinstance(other, self.__class__):
             tmp_data1, tmp_data2 = self._align_index(other)
@@ -135,7 +135,7 @@ class BaseData:
             return NotImplemented
 
     def __eq__(self, other):
-        if isinstance(other, (int, float, np.floating)):
+        if isinstance(other, (int, float, np.number)):
             return self.__class__(self.data == other, *self.index_columns)
         elif isinstance(other, self.__class__):
             tmp_data1, tmp_data2 = self._align_index(other)
@@ -144,7 +144,7 @@ class BaseData:
             return NotImplemented
 
     def __gt__(self, other):
-        if isinstance(other, (int, float, np.floating)):
+        if isinstance(other, (int, float, np.number)):
             return self.__class__(self.data > other, *self.index_columns)
         elif isinstance(other, self.__class__):
             tmp_data1, tmp_data2 = self._align_index(other)
@@ -153,7 +153,7 @@ class BaseData:
             return NotImplemented
 
     def __lt__(self, other):
-        if isinstance(other, (int, float, np.floating)):
+        if isinstance(other, (int, float, np.number)):
             return self.__class__(self.data < other, *self.index_columns)
         elif isinstance(other, self.__class__):
             tmp_data1, tmp_data2 = self._align_index(other)
@@ -169,9 +169,9 @@ class BaseData:
         tmp_data = np.absolute(self.data)
         return self.__class__(tmp_data, *self.index_columns)
 
-    def astype(self, type):
+    def astype(self, dtype):
         """change the type of data."""
-        tmp_data = self.data.astype(type)
+        tmp_data = self.data.astype(dtype)
         return self.__class__(tmp_data, *self.index_columns)
 
     def replace(self, to_replace: dict):
@@ -234,7 +234,7 @@ class BaseData:
 
 
 class SingleData(BaseData):
-    def __init__(self, data: Union[int, float, np.floating, list, np.ndarray] = [], index: Union[list, pd.Index] = []):
+    def __init__(self, data: Union[int, float, np.number, list] = [], index: Union[list, pd.Index] = []):
         """A data structure of index and numpy data.
         It's used to replace pd.Series due to high-speed.
 
@@ -301,6 +301,8 @@ class SingleData(BaseData):
         SingleData
             reindex data
         """
+        if self.index == index:
+            return self
         tmp_data = np.full(len(index), fill_value, dtype=np.float64)
         for index_id, index_item in enumerate(index):
             if index_item in self.index:
@@ -323,17 +325,7 @@ class SingleData(BaseData):
         """
         return dict(zip(self.index, self.data.tolist()))
 
-    def to_frame(self):
-        """convert SingleData to MultiData.
-
-        Returns
-        -------
-        MultiData
-            data with the MultiData format.
-        """
-        return MultiData(self.data[:, np.newaxis], self.index)
-
-    def to_pd_series(self):
+    def to_series(self):
         return pd.Series(self.data, index=self.index)
 
     def __getitem__(self, index: Union["SingleData", int, str]):
diff --git a/qlib/utils/time.py b/qlib/utils/time.py
index e9ae82c5f..2b2a9d8ec 100644
--- a/qlib/utils/time.py
+++ b/qlib/utils/time.py
@@ -38,8 +38,8 @@ def get_min_cal(shift: int = 0) -> List[time]:
     return cal
 
 
-def if_single_data(start_time, end_time, freq):
-    """Is there only one piece of data to obtain.
+def is_single_value(start_time, end_time, freq):
+    """Is there only one piece of data for cn stock market.
 
     Parameters
     ----------