1
0
mirror of https://github.com/microsoft/qlib.git synced 2026-07-13 15:56:57 +08:00

Nested data loader (#1822)

* nested data loader

* Amend

* add data loder test

* fix pylint error

* fix pytest error

* fix pytest error

* delete comments

* Update qlib/contrib/data/handler.py

---------

Co-authored-by: Linlang <Lv.Linlang@hotmail.com>
This commit is contained in:
you-n-g
2024-07-05 15:44:16 +08:00
committed by GitHub
parent 5190332c7e
commit a7d5a9b500
4 changed files with 417 additions and 279 deletions

View File

@@ -1,6 +1,7 @@
# Copyright (c) Microsoft Corporation. # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License. # Licensed under the MIT License.
from qlib.contrib.data.loader import Alpha158DL, Alpha360DL
from ...data.dataset.handler import DataHandlerLP from ...data.dataset.handler import DataHandlerLP
from ...data.dataset.processor import Processor from ...data.dataset.processor import Processor
from ...utils import get_callable_kwargs from ...utils import get_callable_kwargs
@@ -66,7 +67,7 @@ class Alpha360(DataHandlerLP):
"class": "QlibDataLoader", "class": "QlibDataLoader",
"kwargs": { "kwargs": {
"config": { "config": {
"feature": self.get_feature_config(), "feature": Alpha360DL.get_feature_config(),
"label": kwargs.pop("label", self.get_label_config()), "label": kwargs.pop("label", self.get_label_config()),
}, },
"filter_pipe": filter_pipe, "filter_pipe": filter_pipe,
@@ -88,51 +89,6 @@ class Alpha360(DataHandlerLP):
def get_label_config(self): def get_label_config(self):
return ["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"] return ["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"]
@staticmethod
def get_feature_config():
# NOTE:
# Alpha360 tries to provide a dataset with original price data
# the original price data includes the prices and volume in the last 60 days.
# To make it easier to learn models from this dataset, all the prices and volume
# are normalized by the latest price and volume data ( dividing by $close, $volume)
# So the latest normalized $close will be 1 (with name CLOSE0), the latest normalized $volume will be 1 (with name VOLUME0)
# If further normalization are executed (e.g. centralization), CLOSE0 and VOLUME0 will be 0.
fields = []
names = []
for i in range(59, 0, -1):
fields += ["Ref($close, %d)/$close" % i]
names += ["CLOSE%d" % i]
fields += ["$close/$close"]
names += ["CLOSE0"]
for i in range(59, 0, -1):
fields += ["Ref($open, %d)/$close" % i]
names += ["OPEN%d" % i]
fields += ["$open/$close"]
names += ["OPEN0"]
for i in range(59, 0, -1):
fields += ["Ref($high, %d)/$close" % i]
names += ["HIGH%d" % i]
fields += ["$high/$close"]
names += ["HIGH0"]
for i in range(59, 0, -1):
fields += ["Ref($low, %d)/$close" % i]
names += ["LOW%d" % i]
fields += ["$low/$close"]
names += ["LOW0"]
for i in range(59, 0, -1):
fields += ["Ref($vwap, %d)/$close" % i]
names += ["VWAP%d" % i]
fields += ["$vwap/$close"]
names += ["VWAP0"]
for i in range(59, 0, -1):
fields += ["Ref($volume, %d)/($volume+1e-12)" % i]
names += ["VOLUME%d" % i]
fields += ["$volume/($volume+1e-12)"]
names += ["VOLUME0"]
return fields, names
class Alpha360vwap(Alpha360): class Alpha360vwap(Alpha360):
def get_label_config(self): def get_label_config(self):
@@ -190,242 +146,11 @@ class Alpha158(DataHandlerLP):
}, },
"rolling": {}, "rolling": {},
} }
return self.parse_config_to_fields(conf) return Alpha158DL.get_feature_config(conf)
def get_label_config(self): def get_label_config(self):
return ["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"] return ["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"]
@staticmethod
def parse_config_to_fields(config):
"""create factors from config
config = {
'kbar': {}, # whether to use some hard-code kbar features
'price': { # whether to use raw price features
'windows': [0, 1, 2, 3, 4], # use price at n days ago
'feature': ['OPEN', 'HIGH', 'LOW'] # which price field to use
},
'volume': { # whether to use raw volume features
'windows': [0, 1, 2, 3, 4], # use volume at n days ago
},
'rolling': { # whether to use rolling operator based features
'windows': [5, 10, 20, 30, 60], # rolling windows size
'include': ['ROC', 'MA', 'STD'], # rolling operator to use
#if include is None we will use default operators
'exclude': ['RANK'], # rolling operator not to use
}
}
"""
fields = []
names = []
if "kbar" in config:
fields += [
"($close-$open)/$open",
"($high-$low)/$open",
"($close-$open)/($high-$low+1e-12)",
"($high-Greater($open, $close))/$open",
"($high-Greater($open, $close))/($high-$low+1e-12)",
"(Less($open, $close)-$low)/$open",
"(Less($open, $close)-$low)/($high-$low+1e-12)",
"(2*$close-$high-$low)/$open",
"(2*$close-$high-$low)/($high-$low+1e-12)",
]
names += [
"KMID",
"KLEN",
"KMID2",
"KUP",
"KUP2",
"KLOW",
"KLOW2",
"KSFT",
"KSFT2",
]
if "price" in config:
windows = config["price"].get("windows", range(5))
feature = config["price"].get("feature", ["OPEN", "HIGH", "LOW", "CLOSE", "VWAP"])
for field in feature:
field = field.lower()
fields += ["Ref($%s, %d)/$close" % (field, d) if d != 0 else "$%s/$close" % field for d in windows]
names += [field.upper() + str(d) for d in windows]
if "volume" in config:
windows = config["volume"].get("windows", range(5))
fields += ["Ref($volume, %d)/($volume+1e-12)" % d if d != 0 else "$volume/($volume+1e-12)" for d in windows]
names += ["VOLUME" + str(d) for d in windows]
if "rolling" in config:
windows = config["rolling"].get("windows", [5, 10, 20, 30, 60])
include = config["rolling"].get("include", None)
exclude = config["rolling"].get("exclude", [])
# `exclude` in dataset config unnecessary filed
# `include` in dataset config necessary field
def use(x):
return x not in exclude and (include is None or x in include)
# Some factor ref: https://guorn.com/static/upload/file/3/134065454575605.pdf
if use("ROC"):
# https://www.investopedia.com/terms/r/rateofchange.asp
# Rate of change, the price change in the past d days, divided by latest close price to remove unit
fields += ["Ref($close, %d)/$close" % d for d in windows]
names += ["ROC%d" % d for d in windows]
if use("MA"):
# https://www.investopedia.com/ask/answers/071414/whats-difference-between-moving-average-and-weighted-moving-average.asp
# Simple Moving Average, the simple moving average in the past d days, divided by latest close price to remove unit
fields += ["Mean($close, %d)/$close" % d for d in windows]
names += ["MA%d" % d for d in windows]
if use("STD"):
# The standard diviation of close price for the past d days, divided by latest close price to remove unit
fields += ["Std($close, %d)/$close" % d for d in windows]
names += ["STD%d" % d for d in windows]
if use("BETA"):
# The rate of close price change in the past d days, divided by latest close price to remove unit
# For example, price increase 10 dollar per day in the past d days, then Slope will be 10.
fields += ["Slope($close, %d)/$close" % d for d in windows]
names += ["BETA%d" % d for d in windows]
if use("RSQR"):
# The R-sqaure value of linear regression for the past d days, represent the trend linear
fields += ["Rsquare($close, %d)" % d for d in windows]
names += ["RSQR%d" % d for d in windows]
if use("RESI"):
# The redisdual for linear regression for the past d days, represent the trend linearity for past d days.
fields += ["Resi($close, %d)/$close" % d for d in windows]
names += ["RESI%d" % d for d in windows]
if use("MAX"):
# The max price for past d days, divided by latest close price to remove unit
fields += ["Max($high, %d)/$close" % d for d in windows]
names += ["MAX%d" % d for d in windows]
if use("LOW"):
# The low price for past d days, divided by latest close price to remove unit
fields += ["Min($low, %d)/$close" % d for d in windows]
names += ["MIN%d" % d for d in windows]
if use("QTLU"):
# The 80% quantile of past d day's close price, divided by latest close price to remove unit
# Used with MIN and MAX
fields += ["Quantile($close, %d, 0.8)/$close" % d for d in windows]
names += ["QTLU%d" % d for d in windows]
if use("QTLD"):
# The 20% quantile of past d day's close price, divided by latest close price to remove unit
fields += ["Quantile($close, %d, 0.2)/$close" % d for d in windows]
names += ["QTLD%d" % d for d in windows]
if use("RANK"):
# Get the percentile of current close price in past d day's close price.
# Represent the current price level comparing to past N days, add additional information to moving average.
fields += ["Rank($close, %d)" % d for d in windows]
names += ["RANK%d" % d for d in windows]
if use("RSV"):
# Represent the price position between upper and lower resistent price for past d days.
fields += ["($close-Min($low, %d))/(Max($high, %d)-Min($low, %d)+1e-12)" % (d, d, d) for d in windows]
names += ["RSV%d" % d for d in windows]
if use("IMAX"):
# The number of days between current date and previous highest price date.
# Part of Aroon Indicator https://www.investopedia.com/terms/a/aroon.asp
# The indicator measures the time between highs and the time between lows over a time period.
# The idea is that strong uptrends will regularly see new highs, and strong downtrends will regularly see new lows.
fields += ["IdxMax($high, %d)/%d" % (d, d) for d in windows]
names += ["IMAX%d" % d for d in windows]
if use("IMIN"):
# The number of days between current date and previous lowest price date.
# Part of Aroon Indicator https://www.investopedia.com/terms/a/aroon.asp
# The indicator measures the time between highs and the time between lows over a time period.
# The idea is that strong uptrends will regularly see new highs, and strong downtrends will regularly see new lows.
fields += ["IdxMin($low, %d)/%d" % (d, d) for d in windows]
names += ["IMIN%d" % d for d in windows]
if use("IMXD"):
# The time period between previous lowest-price date occur after highest price date.
# Large value suggest downward momemtum.
fields += ["(IdxMax($high, %d)-IdxMin($low, %d))/%d" % (d, d, d) for d in windows]
names += ["IMXD%d" % d for d in windows]
if use("CORR"):
# The correlation between absolute close price and log scaled trading volume
fields += ["Corr($close, Log($volume+1), %d)" % d for d in windows]
names += ["CORR%d" % d for d in windows]
if use("CORD"):
# The correlation between price change ratio and volume change ratio
fields += ["Corr($close/Ref($close,1), Log($volume/Ref($volume, 1)+1), %d)" % d for d in windows]
names += ["CORD%d" % d for d in windows]
if use("CNTP"):
# The percentage of days in past d days that price go up.
fields += ["Mean($close>Ref($close, 1), %d)" % d for d in windows]
names += ["CNTP%d" % d for d in windows]
if use("CNTN"):
# The percentage of days in past d days that price go down.
fields += ["Mean($close<Ref($close, 1), %d)" % d for d in windows]
names += ["CNTN%d" % d for d in windows]
if use("CNTD"):
# The diff between past up day and past down day
fields += ["Mean($close>Ref($close, 1), %d)-Mean($close<Ref($close, 1), %d)" % (d, d) for d in windows]
names += ["CNTD%d" % d for d in windows]
if use("SUMP"):
# The total gain / the absolute total price changed
# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
fields += [
"Sum(Greater($close-Ref($close, 1), 0), %d)/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d)
for d in windows
]
names += ["SUMP%d" % d for d in windows]
if use("SUMN"):
# The total lose / the absolute total price changed
# Can be derived from SUMP by SUMN = 1 - SUMP
# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
fields += [
"Sum(Greater(Ref($close, 1)-$close, 0), %d)/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d)
for d in windows
]
names += ["SUMN%d" % d for d in windows]
if use("SUMD"):
# The diff ratio between total gain and total lose
# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
fields += [
"(Sum(Greater($close-Ref($close, 1), 0), %d)-Sum(Greater(Ref($close, 1)-$close, 0), %d))"
"/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d, d)
for d in windows
]
names += ["SUMD%d" % d for d in windows]
if use("VMA"):
# Simple Volume Moving average: https://www.barchart.com/education/technical-indicators/volume_moving_average
fields += ["Mean($volume, %d)/($volume+1e-12)" % d for d in windows]
names += ["VMA%d" % d for d in windows]
if use("VSTD"):
# The standard deviation for volume in past d days.
fields += ["Std($volume, %d)/($volume+1e-12)" % d for d in windows]
names += ["VSTD%d" % d for d in windows]
if use("WVMA"):
# The volume weighted price change volatility
fields += [
"Std(Abs($close/Ref($close, 1)-1)*$volume, %d)/(Mean(Abs($close/Ref($close, 1)-1)*$volume, %d)+1e-12)"
% (d, d)
for d in windows
]
names += ["WVMA%d" % d for d in windows]
if use("VSUMP"):
# The total volume increase / the absolute total volume changed
fields += [
"Sum(Greater($volume-Ref($volume, 1), 0), %d)/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)"
% (d, d)
for d in windows
]
names += ["VSUMP%d" % d for d in windows]
if use("VSUMN"):
# The total volume increase / the absolute total volume changed
# Can be derived from VSUMP by VSUMN = 1 - VSUMP
fields += [
"Sum(Greater(Ref($volume, 1)-$volume, 0), %d)/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)"
% (d, d)
for d in windows
]
names += ["VSUMN%d" % d for d in windows]
if use("VSUMD"):
# The diff ratio between total volume increase and total volume decrease
# RSI indicator for volume
fields += [
"(Sum(Greater($volume-Ref($volume, 1), 0), %d)-Sum(Greater(Ref($volume, 1)-$volume, 0), %d))"
"/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)" % (d, d, d)
for d in windows
]
names += ["VSUMD%d" % d for d in windows]
return fields, names
class Alpha158vwap(Alpha158): class Alpha158vwap(Alpha158):
def get_label_config(self): def get_label_config(self):

310
qlib/contrib/data/loader.py Normal file
View File

@@ -0,0 +1,310 @@
from qlib.data.dataset.loader import QlibDataLoader
class Alpha360DL(QlibDataLoader):
"""Dataloader to get Alpha360"""
def __init__(self, config=None, **kwargs):
_config = {
"feature": self.get_feature_config(),
}
if config is not None:
_config.update(config)
super().__init__(config=_config, **kwargs)
@staticmethod
def get_feature_config():
# NOTE:
# Alpha360 tries to provide a dataset with original price data
# the original price data includes the prices and volume in the last 60 days.
# To make it easier to learn models from this dataset, all the prices and volume
# are normalized by the latest price and volume data ( dividing by $close, $volume)
# So the latest normalized $close will be 1 (with name CLOSE0), the latest normalized $volume will be 1 (with name VOLUME0)
# If further normalization are executed (e.g. centralization), CLOSE0 and VOLUME0 will be 0.
fields = []
names = []
for i in range(59, 0, -1):
fields += ["Ref($close, %d)/$close" % i]
names += ["CLOSE%d" % i]
fields += ["$close/$close"]
names += ["CLOSE0"]
for i in range(59, 0, -1):
fields += ["Ref($open, %d)/$close" % i]
names += ["OPEN%d" % i]
fields += ["$open/$close"]
names += ["OPEN0"]
for i in range(59, 0, -1):
fields += ["Ref($high, %d)/$close" % i]
names += ["HIGH%d" % i]
fields += ["$high/$close"]
names += ["HIGH0"]
for i in range(59, 0, -1):
fields += ["Ref($low, %d)/$close" % i]
names += ["LOW%d" % i]
fields += ["$low/$close"]
names += ["LOW0"]
for i in range(59, 0, -1):
fields += ["Ref($vwap, %d)/$close" % i]
names += ["VWAP%d" % i]
fields += ["$vwap/$close"]
names += ["VWAP0"]
for i in range(59, 0, -1):
fields += ["Ref($volume, %d)/($volume+1e-12)" % i]
names += ["VOLUME%d" % i]
fields += ["$volume/($volume+1e-12)"]
names += ["VOLUME0"]
return fields, names
class Alpha158DL(QlibDataLoader):
"""Dataloader to get Alpha158"""
def __init__(self, config=None, **kwargs):
_config = {
"feature": self.get_feature_config(),
}
if config is not None:
_config.update(config)
super().__init__(config=_config, **kwargs)
@staticmethod
def get_feature_config(
config={
"kbar": {},
"price": {
"windows": [0],
"feature": ["OPEN", "HIGH", "LOW", "VWAP"],
},
"rolling": {},
}
):
"""create factors from config
config = {
'kbar': {}, # whether to use some hard-code kbar features
'price': { # whether to use raw price features
'windows': [0, 1, 2, 3, 4], # use price at n days ago
'feature': ['OPEN', 'HIGH', 'LOW'] # which price field to use
},
'volume': { # whether to use raw volume features
'windows': [0, 1, 2, 3, 4], # use volume at n days ago
},
'rolling': { # whether to use rolling operator based features
'windows': [5, 10, 20, 30, 60], # rolling windows size
'include': ['ROC', 'MA', 'STD'], # rolling operator to use
#if include is None we will use default operators
'exclude': ['RANK'], # rolling operator not to use
}
}
"""
fields = []
names = []
if "kbar" in config:
fields += [
"($close-$open)/$open",
"($high-$low)/$open",
"($close-$open)/($high-$low+1e-12)",
"($high-Greater($open, $close))/$open",
"($high-Greater($open, $close))/($high-$low+1e-12)",
"(Less($open, $close)-$low)/$open",
"(Less($open, $close)-$low)/($high-$low+1e-12)",
"(2*$close-$high-$low)/$open",
"(2*$close-$high-$low)/($high-$low+1e-12)",
]
names += [
"KMID",
"KLEN",
"KMID2",
"KUP",
"KUP2",
"KLOW",
"KLOW2",
"KSFT",
"KSFT2",
]
if "price" in config:
windows = config["price"].get("windows", range(5))
feature = config["price"].get("feature", ["OPEN", "HIGH", "LOW", "CLOSE", "VWAP"])
for field in feature:
field = field.lower()
fields += ["Ref($%s, %d)/$close" % (field, d) if d != 0 else "$%s/$close" % field for d in windows]
names += [field.upper() + str(d) for d in windows]
if "volume" in config:
windows = config["volume"].get("windows", range(5))
fields += ["Ref($volume, %d)/($volume+1e-12)" % d if d != 0 else "$volume/($volume+1e-12)" for d in windows]
names += ["VOLUME" + str(d) for d in windows]
if "rolling" in config:
windows = config["rolling"].get("windows", [5, 10, 20, 30, 60])
include = config["rolling"].get("include", None)
exclude = config["rolling"].get("exclude", [])
# `exclude` in dataset config unnecessary filed
# `include` in dataset config necessary field
def use(x):
return x not in exclude and (include is None or x in include)
# Some factor ref: https://guorn.com/static/upload/file/3/134065454575605.pdf
if use("ROC"):
# https://www.investopedia.com/terms/r/rateofchange.asp
# Rate of change, the price change in the past d days, divided by latest close price to remove unit
fields += ["Ref($close, %d)/$close" % d for d in windows]
names += ["ROC%d" % d for d in windows]
if use("MA"):
# https://www.investopedia.com/ask/answers/071414/whats-difference-between-moving-average-and-weighted-moving-average.asp
# Simple Moving Average, the simple moving average in the past d days, divided by latest close price to remove unit
fields += ["Mean($close, %d)/$close" % d for d in windows]
names += ["MA%d" % d for d in windows]
if use("STD"):
# The standard diviation of close price for the past d days, divided by latest close price to remove unit
fields += ["Std($close, %d)/$close" % d for d in windows]
names += ["STD%d" % d for d in windows]
if use("BETA"):
# The rate of close price change in the past d days, divided by latest close price to remove unit
# For example, price increase 10 dollar per day in the past d days, then Slope will be 10.
fields += ["Slope($close, %d)/$close" % d for d in windows]
names += ["BETA%d" % d for d in windows]
if use("RSQR"):
# The R-sqaure value of linear regression for the past d days, represent the trend linear
fields += ["Rsquare($close, %d)" % d for d in windows]
names += ["RSQR%d" % d for d in windows]
if use("RESI"):
# The redisdual for linear regression for the past d days, represent the trend linearity for past d days.
fields += ["Resi($close, %d)/$close" % d for d in windows]
names += ["RESI%d" % d for d in windows]
if use("MAX"):
# The max price for past d days, divided by latest close price to remove unit
fields += ["Max($high, %d)/$close" % d for d in windows]
names += ["MAX%d" % d for d in windows]
if use("LOW"):
# The low price for past d days, divided by latest close price to remove unit
fields += ["Min($low, %d)/$close" % d for d in windows]
names += ["MIN%d" % d for d in windows]
if use("QTLU"):
# The 80% quantile of past d day's close price, divided by latest close price to remove unit
# Used with MIN and MAX
fields += ["Quantile($close, %d, 0.8)/$close" % d for d in windows]
names += ["QTLU%d" % d for d in windows]
if use("QTLD"):
# The 20% quantile of past d day's close price, divided by latest close price to remove unit
fields += ["Quantile($close, %d, 0.2)/$close" % d for d in windows]
names += ["QTLD%d" % d for d in windows]
if use("RANK"):
# Get the percentile of current close price in past d day's close price.
# Represent the current price level comparing to past N days, add additional information to moving average.
fields += ["Rank($close, %d)" % d for d in windows]
names += ["RANK%d" % d for d in windows]
if use("RSV"):
# Represent the price position between upper and lower resistent price for past d days.
fields += ["($close-Min($low, %d))/(Max($high, %d)-Min($low, %d)+1e-12)" % (d, d, d) for d in windows]
names += ["RSV%d" % d for d in windows]
if use("IMAX"):
# The number of days between current date and previous highest price date.
# Part of Aroon Indicator https://www.investopedia.com/terms/a/aroon.asp
# The indicator measures the time between highs and the time between lows over a time period.
# The idea is that strong uptrends will regularly see new highs, and strong downtrends will regularly see new lows.
fields += ["IdxMax($high, %d)/%d" % (d, d) for d in windows]
names += ["IMAX%d" % d for d in windows]
if use("IMIN"):
# The number of days between current date and previous lowest price date.
# Part of Aroon Indicator https://www.investopedia.com/terms/a/aroon.asp
# The indicator measures the time between highs and the time between lows over a time period.
# The idea is that strong uptrends will regularly see new highs, and strong downtrends will regularly see new lows.
fields += ["IdxMin($low, %d)/%d" % (d, d) for d in windows]
names += ["IMIN%d" % d for d in windows]
if use("IMXD"):
# The time period between previous lowest-price date occur after highest price date.
# Large value suggest downward momemtum.
fields += ["(IdxMax($high, %d)-IdxMin($low, %d))/%d" % (d, d, d) for d in windows]
names += ["IMXD%d" % d for d in windows]
if use("CORR"):
# The correlation between absolute close price and log scaled trading volume
fields += ["Corr($close, Log($volume+1), %d)" % d for d in windows]
names += ["CORR%d" % d for d in windows]
if use("CORD"):
# The correlation between price change ratio and volume change ratio
fields += ["Corr($close/Ref($close,1), Log($volume/Ref($volume, 1)+1), %d)" % d for d in windows]
names += ["CORD%d" % d for d in windows]
if use("CNTP"):
# The percentage of days in past d days that price go up.
fields += ["Mean($close>Ref($close, 1), %d)" % d for d in windows]
names += ["CNTP%d" % d for d in windows]
if use("CNTN"):
# The percentage of days in past d days that price go down.
fields += ["Mean($close<Ref($close, 1), %d)" % d for d in windows]
names += ["CNTN%d" % d for d in windows]
if use("CNTD"):
# The diff between past up day and past down day
fields += ["Mean($close>Ref($close, 1), %d)-Mean($close<Ref($close, 1), %d)" % (d, d) for d in windows]
names += ["CNTD%d" % d for d in windows]
if use("SUMP"):
# The total gain / the absolute total price changed
# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
fields += [
"Sum(Greater($close-Ref($close, 1), 0), %d)/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d)
for d in windows
]
names += ["SUMP%d" % d for d in windows]
if use("SUMN"):
# The total lose / the absolute total price changed
# Can be derived from SUMP by SUMN = 1 - SUMP
# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
fields += [
"Sum(Greater(Ref($close, 1)-$close, 0), %d)/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d)
for d in windows
]
names += ["SUMN%d" % d for d in windows]
if use("SUMD"):
# The diff ratio between total gain and total lose
# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
fields += [
"(Sum(Greater($close-Ref($close, 1), 0), %d)-Sum(Greater(Ref($close, 1)-$close, 0), %d))"
"/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d, d)
for d in windows
]
names += ["SUMD%d" % d for d in windows]
if use("VMA"):
# Simple Volume Moving average: https://www.barchart.com/education/technical-indicators/volume_moving_average
fields += ["Mean($volume, %d)/($volume+1e-12)" % d for d in windows]
names += ["VMA%d" % d for d in windows]
if use("VSTD"):
# The standard deviation for volume in past d days.
fields += ["Std($volume, %d)/($volume+1e-12)" % d for d in windows]
names += ["VSTD%d" % d for d in windows]
if use("WVMA"):
# The volume weighted price change volatility
fields += [
"Std(Abs($close/Ref($close, 1)-1)*$volume, %d)/(Mean(Abs($close/Ref($close, 1)-1)*$volume, %d)+1e-12)"
% (d, d)
for d in windows
]
names += ["WVMA%d" % d for d in windows]
if use("VSUMP"):
# The total volume increase / the absolute total volume changed
fields += [
"Sum(Greater($volume-Ref($volume, 1), 0), %d)/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)"
% (d, d)
for d in windows
]
names += ["VSUMP%d" % d for d in windows]
if use("VSUMN"):
# The total volume increase / the absolute total volume changed
# Can be derived from VSUMP by VSUMN = 1 - VSUMP
fields += [
"Sum(Greater(Ref($volume, 1)-$volume, 0), %d)/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)"
% (d, d)
for d in windows
]
names += ["VSUMN%d" % d for d in windows]
if use("VSUMD"):
# The diff ratio between total volume increase and total volume decrease
# RSI indicator for volume
fields += [
"(Sum(Greater($volume-Ref($volume, 1), 0), %d)-Sum(Greater(Ref($volume, 1)-$volume, 0), %d))"
"/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)" % (d, d, d)
for d in windows
]
names += ["VSUMD%d" % d for d in windows]
return fields, names

View File

@@ -7,7 +7,7 @@ from pathlib import Path
import warnings import warnings
import pandas as pd import pandas as pd
from typing import Tuple, Union, List from typing import Tuple, Union, List, Dict
from qlib.data import D from qlib.data import D
from qlib.utils import load_dataset, init_instance_by_config, time_to_slc_point from qlib.utils import load_dataset, init_instance_by_config, time_to_slc_point
@@ -247,10 +247,14 @@ class StaticDataLoader(DataLoader, Serializable):
def load(self, instruments=None, start_time=None, end_time=None) -> pd.DataFrame: def load(self, instruments=None, start_time=None, end_time=None) -> pd.DataFrame:
self._maybe_load_raw_data() self._maybe_load_raw_data()
# 1) Filter by instruments
if instruments is None: if instruments is None:
df = self._data df = self._data
else: else:
df = self._data.loc(axis=0)[:, instruments] df = self._data.loc(axis=0)[:, instruments]
# 2) Filter by Datetime
if start_time is None and end_time is None: if start_time is None and end_time is None:
return df # NOTE: avoid copy by loc return df # NOTE: avoid copy by loc
# pd.Timestamp(None) == NaT, use NaT as index can not fetch correct thing, so do not change None. # pd.Timestamp(None) == NaT, use NaT as index can not fetch correct thing, so do not change None.
@@ -275,6 +279,55 @@ class StaticDataLoader(DataLoader, Serializable):
self._data = self._config self._data = self._config
class NestedDataLoader(DataLoader):
"""
We have multiple DataLoader, we can use this class to combine them.
"""
def __init__(self, dataloader_l: List[Dict], join="left") -> None:
"""
Parameters
----------
dataloader_l : list[dict]
A list of dataloader, for exmaple
.. code-block:: python
nd = NestedDataLoader(
dataloader_l=[
{
"class": "qlib.contrib.data.loader.Alpha158DL",
}, {
"class": "qlib.contrib.data.loader.Alpha360DL",
"kwargs": {
"config": {
"label": ( ["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"])
}
}
}
]
)
join :
it will pass to pd.concat when merging it.
"""
super().__init__()
self.data_loader_l = [
(dl if isinstance(dl, DataLoader) else init_instance_by_config(dl)) for dl in dataloader_l
]
self.join = join
def load(self, instruments=None, start_time=None, end_time=None) -> pd.DataFrame:
df_full = None
for dl in self.data_loader_l:
df_current = dl.load(instruments, start_time, end_time)
if df_full is None:
df_full = df_current
else:
df_full = pd.merge(df_full, df_current, left_index=True, right_index=True, how=self.join)
return df_full.sort_index(axis=1)
class DataLoaderDH(DataLoader): class DataLoaderDH(DataLoader):
"""DataLoaderDH """DataLoaderDH
DataLoader based on (D)ata (H)andler DataLoader based on (D)ata (H)andler

View File

@@ -0,0 +1,50 @@
# TODO:
# dump alpha 360 to dataframe and merge it with Alpha158
import sys
import unittest
import qlib
from pathlib import Path
sys.path.append(str(Path(__file__).resolve().parent))
from qlib.data.dataset.loader import NestedDataLoader
from qlib.contrib.data.loader import Alpha158DL, Alpha360DL
class TestDataLoader(unittest.TestCase):
def test_nested_data_loader(self):
qlib.init()
nd = NestedDataLoader(
dataloader_l=[
{
"class": "qlib.contrib.data.loader.Alpha158DL",
},
{
"class": "qlib.contrib.data.loader.Alpha360DL",
"kwargs": {"config": {"label": (["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"])}},
},
]
)
# Of course you can use StaticDataLoader
dataset = nd.load()
assert dataset is not None
columns = dataset.columns.tolist()
columns_list = [tup[1] for tup in columns]
for col in Alpha158DL.get_feature_config()[1]:
assert col in columns_list
for col in Alpha360DL.get_feature_config()[1]:
assert col in columns_list
assert "LABEL0" in columns_list
# Then you can use it wth DataHandler;
if __name__ == "__main__":
unittest.main()