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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
@@ -1,6 +1,7 @@
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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from qlib.contrib.data.loader import Alpha158DL, Alpha360DL
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from ...data.dataset.handler import DataHandlerLP
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from ...data.dataset.processor import Processor
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from ...utils import get_callable_kwargs
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@@ -66,7 +67,7 @@ class Alpha360(DataHandlerLP):
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"class": "QlibDataLoader",
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"kwargs": {
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"config": {
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"feature": self.get_feature_config(),
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"feature": Alpha360DL.get_feature_config(),
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"label": kwargs.pop("label", self.get_label_config()),
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},
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"filter_pipe": filter_pipe,
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@@ -88,51 +89,6 @@ class Alpha360(DataHandlerLP):
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def get_label_config(self):
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return ["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"]
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@staticmethod
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def get_feature_config():
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# NOTE:
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# Alpha360 tries to provide a dataset with original price data
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# the original price data includes the prices and volume in the last 60 days.
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# To make it easier to learn models from this dataset, all the prices and volume
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# are normalized by the latest price and volume data ( dividing by $close, $volume)
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# So the latest normalized $close will be 1 (with name CLOSE0), the latest normalized $volume will be 1 (with name VOLUME0)
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# If further normalization are executed (e.g. centralization), CLOSE0 and VOLUME0 will be 0.
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fields = []
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names = []
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for i in range(59, 0, -1):
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fields += ["Ref($close, %d)/$close" % i]
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names += ["CLOSE%d" % i]
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fields += ["$close/$close"]
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names += ["CLOSE0"]
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for i in range(59, 0, -1):
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fields += ["Ref($open, %d)/$close" % i]
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names += ["OPEN%d" % i]
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fields += ["$open/$close"]
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names += ["OPEN0"]
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for i in range(59, 0, -1):
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fields += ["Ref($high, %d)/$close" % i]
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names += ["HIGH%d" % i]
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fields += ["$high/$close"]
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names += ["HIGH0"]
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for i in range(59, 0, -1):
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fields += ["Ref($low, %d)/$close" % i]
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names += ["LOW%d" % i]
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fields += ["$low/$close"]
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names += ["LOW0"]
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for i in range(59, 0, -1):
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fields += ["Ref($vwap, %d)/$close" % i]
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names += ["VWAP%d" % i]
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fields += ["$vwap/$close"]
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names += ["VWAP0"]
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for i in range(59, 0, -1):
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fields += ["Ref($volume, %d)/($volume+1e-12)" % i]
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names += ["VOLUME%d" % i]
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fields += ["$volume/($volume+1e-12)"]
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names += ["VOLUME0"]
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return fields, names
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class Alpha360vwap(Alpha360):
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def get_label_config(self):
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@@ -190,242 +146,11 @@ class Alpha158(DataHandlerLP):
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},
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"rolling": {},
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}
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return self.parse_config_to_fields(conf)
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return Alpha158DL.get_feature_config(conf)
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def get_label_config(self):
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return ["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"]
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@staticmethod
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def parse_config_to_fields(config):
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"""create factors from config
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config = {
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'kbar': {}, # whether to use some hard-code kbar features
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'price': { # whether to use raw price features
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'windows': [0, 1, 2, 3, 4], # use price at n days ago
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'feature': ['OPEN', 'HIGH', 'LOW'] # which price field to use
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},
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'volume': { # whether to use raw volume features
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'windows': [0, 1, 2, 3, 4], # use volume at n days ago
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},
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'rolling': { # whether to use rolling operator based features
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'windows': [5, 10, 20, 30, 60], # rolling windows size
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'include': ['ROC', 'MA', 'STD'], # rolling operator to use
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#if include is None we will use default operators
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'exclude': ['RANK'], # rolling operator not to use
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}
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}
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"""
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fields = []
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names = []
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if "kbar" in config:
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fields += [
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"($close-$open)/$open",
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"($high-$low)/$open",
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"($close-$open)/($high-$low+1e-12)",
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"($high-Greater($open, $close))/$open",
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"($high-Greater($open, $close))/($high-$low+1e-12)",
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"(Less($open, $close)-$low)/$open",
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"(Less($open, $close)-$low)/($high-$low+1e-12)",
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"(2*$close-$high-$low)/$open",
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"(2*$close-$high-$low)/($high-$low+1e-12)",
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]
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names += [
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"KMID",
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"KLEN",
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"KMID2",
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"KUP",
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"KUP2",
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"KLOW",
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"KLOW2",
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"KSFT",
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"KSFT2",
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]
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if "price" in config:
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windows = config["price"].get("windows", range(5))
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feature = config["price"].get("feature", ["OPEN", "HIGH", "LOW", "CLOSE", "VWAP"])
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for field in feature:
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field = field.lower()
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fields += ["Ref($%s, %d)/$close" % (field, d) if d != 0 else "$%s/$close" % field for d in windows]
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names += [field.upper() + str(d) for d in windows]
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if "volume" in config:
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windows = config["volume"].get("windows", range(5))
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fields += ["Ref($volume, %d)/($volume+1e-12)" % d if d != 0 else "$volume/($volume+1e-12)" for d in windows]
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names += ["VOLUME" + str(d) for d in windows]
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if "rolling" in config:
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windows = config["rolling"].get("windows", [5, 10, 20, 30, 60])
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include = config["rolling"].get("include", None)
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exclude = config["rolling"].get("exclude", [])
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# `exclude` in dataset config unnecessary filed
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# `include` in dataset config necessary field
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def use(x):
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return x not in exclude and (include is None or x in include)
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# Some factor ref: https://guorn.com/static/upload/file/3/134065454575605.pdf
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if use("ROC"):
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# https://www.investopedia.com/terms/r/rateofchange.asp
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# Rate of change, the price change in the past d days, divided by latest close price to remove unit
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fields += ["Ref($close, %d)/$close" % d for d in windows]
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names += ["ROC%d" % d for d in windows]
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if use("MA"):
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# https://www.investopedia.com/ask/answers/071414/whats-difference-between-moving-average-and-weighted-moving-average.asp
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# Simple Moving Average, the simple moving average in the past d days, divided by latest close price to remove unit
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fields += ["Mean($close, %d)/$close" % d for d in windows]
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names += ["MA%d" % d for d in windows]
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if use("STD"):
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# The standard diviation of close price for the past d days, divided by latest close price to remove unit
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fields += ["Std($close, %d)/$close" % d for d in windows]
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names += ["STD%d" % d for d in windows]
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if use("BETA"):
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# The rate of close price change in the past d days, divided by latest close price to remove unit
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# For example, price increase 10 dollar per day in the past d days, then Slope will be 10.
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fields += ["Slope($close, %d)/$close" % d for d in windows]
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names += ["BETA%d" % d for d in windows]
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if use("RSQR"):
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# The R-sqaure value of linear regression for the past d days, represent the trend linear
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fields += ["Rsquare($close, %d)" % d for d in windows]
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names += ["RSQR%d" % d for d in windows]
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if use("RESI"):
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# The redisdual for linear regression for the past d days, represent the trend linearity for past d days.
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fields += ["Resi($close, %d)/$close" % d for d in windows]
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names += ["RESI%d" % d for d in windows]
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if use("MAX"):
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# The max price for past d days, divided by latest close price to remove unit
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fields += ["Max($high, %d)/$close" % d for d in windows]
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names += ["MAX%d" % d for d in windows]
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if use("LOW"):
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# The low price for past d days, divided by latest close price to remove unit
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fields += ["Min($low, %d)/$close" % d for d in windows]
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names += ["MIN%d" % d for d in windows]
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if use("QTLU"):
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# The 80% quantile of past d day's close price, divided by latest close price to remove unit
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# Used with MIN and MAX
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fields += ["Quantile($close, %d, 0.8)/$close" % d for d in windows]
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names += ["QTLU%d" % d for d in windows]
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if use("QTLD"):
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# The 20% quantile of past d day's close price, divided by latest close price to remove unit
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fields += ["Quantile($close, %d, 0.2)/$close" % d for d in windows]
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names += ["QTLD%d" % d for d in windows]
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if use("RANK"):
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# Get the percentile of current close price in past d day's close price.
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# Represent the current price level comparing to past N days, add additional information to moving average.
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fields += ["Rank($close, %d)" % d for d in windows]
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names += ["RANK%d" % d for d in windows]
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if use("RSV"):
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# Represent the price position between upper and lower resistent price for past d days.
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fields += ["($close-Min($low, %d))/(Max($high, %d)-Min($low, %d)+1e-12)" % (d, d, d) for d in windows]
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names += ["RSV%d" % d for d in windows]
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if use("IMAX"):
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# The number of days between current date and previous highest price date.
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# Part of Aroon Indicator https://www.investopedia.com/terms/a/aroon.asp
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# The indicator measures the time between highs and the time between lows over a time period.
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# The idea is that strong uptrends will regularly see new highs, and strong downtrends will regularly see new lows.
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fields += ["IdxMax($high, %d)/%d" % (d, d) for d in windows]
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names += ["IMAX%d" % d for d in windows]
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if use("IMIN"):
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# The number of days between current date and previous lowest price date.
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# Part of Aroon Indicator https://www.investopedia.com/terms/a/aroon.asp
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# The indicator measures the time between highs and the time between lows over a time period.
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# The idea is that strong uptrends will regularly see new highs, and strong downtrends will regularly see new lows.
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fields += ["IdxMin($low, %d)/%d" % (d, d) for d in windows]
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names += ["IMIN%d" % d for d in windows]
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if use("IMXD"):
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# The time period between previous lowest-price date occur after highest price date.
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# Large value suggest downward momemtum.
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fields += ["(IdxMax($high, %d)-IdxMin($low, %d))/%d" % (d, d, d) for d in windows]
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names += ["IMXD%d" % d for d in windows]
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if use("CORR"):
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# The correlation between absolute close price and log scaled trading volume
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fields += ["Corr($close, Log($volume+1), %d)" % d for d in windows]
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names += ["CORR%d" % d for d in windows]
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if use("CORD"):
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# The correlation between price change ratio and volume change ratio
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fields += ["Corr($close/Ref($close,1), Log($volume/Ref($volume, 1)+1), %d)" % d for d in windows]
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names += ["CORD%d" % d for d in windows]
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if use("CNTP"):
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# The percentage of days in past d days that price go up.
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fields += ["Mean($close>Ref($close, 1), %d)" % d for d in windows]
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names += ["CNTP%d" % d for d in windows]
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if use("CNTN"):
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# The percentage of days in past d days that price go down.
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fields += ["Mean($close<Ref($close, 1), %d)" % d for d in windows]
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names += ["CNTN%d" % d for d in windows]
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if use("CNTD"):
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# The diff between past up day and past down day
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fields += ["Mean($close>Ref($close, 1), %d)-Mean($close<Ref($close, 1), %d)" % (d, d) for d in windows]
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names += ["CNTD%d" % d for d in windows]
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if use("SUMP"):
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# The total gain / the absolute total price changed
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# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
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fields += [
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"Sum(Greater($close-Ref($close, 1), 0), %d)/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d)
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for d in windows
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]
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names += ["SUMP%d" % d for d in windows]
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if use("SUMN"):
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# The total lose / the absolute total price changed
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# Can be derived from SUMP by SUMN = 1 - SUMP
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# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
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fields += [
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"Sum(Greater(Ref($close, 1)-$close, 0), %d)/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d)
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for d in windows
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]
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names += ["SUMN%d" % d for d in windows]
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if use("SUMD"):
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# The diff ratio between total gain and total lose
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# Similar to RSI indicator. https://www.investopedia.com/terms/r/rsi.asp
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fields += [
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"(Sum(Greater($close-Ref($close, 1), 0), %d)-Sum(Greater(Ref($close, 1)-$close, 0), %d))"
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"/(Sum(Abs($close-Ref($close, 1)), %d)+1e-12)" % (d, d, d)
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for d in windows
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]
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names += ["SUMD%d" % d for d in windows]
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if use("VMA"):
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# Simple Volume Moving average: https://www.barchart.com/education/technical-indicators/volume_moving_average
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fields += ["Mean($volume, %d)/($volume+1e-12)" % d for d in windows]
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names += ["VMA%d" % d for d in windows]
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if use("VSTD"):
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# The standard deviation for volume in past d days.
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fields += ["Std($volume, %d)/($volume+1e-12)" % d for d in windows]
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names += ["VSTD%d" % d for d in windows]
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if use("WVMA"):
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# The volume weighted price change volatility
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fields += [
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"Std(Abs($close/Ref($close, 1)-1)*$volume, %d)/(Mean(Abs($close/Ref($close, 1)-1)*$volume, %d)+1e-12)"
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% (d, d)
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for d in windows
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]
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names += ["WVMA%d" % d for d in windows]
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if use("VSUMP"):
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# The total volume increase / the absolute total volume changed
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fields += [
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"Sum(Greater($volume-Ref($volume, 1), 0), %d)/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)"
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% (d, d)
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for d in windows
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]
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names += ["VSUMP%d" % d for d in windows]
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if use("VSUMN"):
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# The total volume increase / the absolute total volume changed
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# Can be derived from VSUMP by VSUMN = 1 - VSUMP
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fields += [
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"Sum(Greater(Ref($volume, 1)-$volume, 0), %d)/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)"
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% (d, d)
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for d in windows
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]
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names += ["VSUMN%d" % d for d in windows]
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if use("VSUMD"):
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# The diff ratio between total volume increase and total volume decrease
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# RSI indicator for volume
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fields += [
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"(Sum(Greater($volume-Ref($volume, 1), 0), %d)-Sum(Greater(Ref($volume, 1)-$volume, 0), %d))"
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"/(Sum(Abs($volume-Ref($volume, 1)), %d)+1e-12)" % (d, d, d)
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for d in windows
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]
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names += ["VSUMD%d" % d for d in windows]
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return fields, names
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class Alpha158vwap(Alpha158):
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def get_label_config(self):
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310
qlib/contrib/data/loader.py
Normal file
310
qlib/contrib/data/loader.py
Normal file
@@ -0,0 +1,310 @@
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from qlib.data.dataset.loader import QlibDataLoader
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class Alpha360DL(QlibDataLoader):
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"""Dataloader to get Alpha360"""
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def __init__(self, config=None, **kwargs):
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_config = {
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"feature": self.get_feature_config(),
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}
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if config is not None:
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_config.update(config)
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super().__init__(config=_config, **kwargs)
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@staticmethod
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def get_feature_config():
|
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# NOTE:
|
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# Alpha360 tries to provide a dataset with original price data
|
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# the original price data includes the prices and volume in the last 60 days.
|
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# 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)
|
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# So the latest normalized $close will be 1 (with name CLOSE0), the latest normalized $volume will be 1 (with name VOLUME0)
|
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# If further normalization are executed (e.g. centralization), CLOSE0 and VOLUME0 will be 0.
|
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fields = []
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names = []
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for i in range(59, 0, -1):
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fields += ["Ref($close, %d)/$close" % i]
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names += ["CLOSE%d" % i]
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fields += ["$close/$close"]
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names += ["CLOSE0"]
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for i in range(59, 0, -1):
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fields += ["Ref($open, %d)/$close" % i]
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names += ["OPEN%d" % i]
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fields += ["$open/$close"]
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names += ["OPEN0"]
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for i in range(59, 0, -1):
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fields += ["Ref($high, %d)/$close" % i]
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names += ["HIGH%d" % i]
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fields += ["$high/$close"]
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names += ["HIGH0"]
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for i in range(59, 0, -1):
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fields += ["Ref($low, %d)/$close" % i]
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names += ["LOW%d" % i]
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fields += ["$low/$close"]
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names += ["LOW0"]
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for i in range(59, 0, -1):
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fields += ["Ref($vwap, %d)/$close" % i]
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names += ["VWAP%d" % i]
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fields += ["$vwap/$close"]
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names += ["VWAP0"]
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for i in range(59, 0, -1):
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fields += ["Ref($volume, %d)/($volume+1e-12)" % i]
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names += ["VOLUME%d" % i]
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fields += ["$volume/($volume+1e-12)"]
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names += ["VOLUME0"]
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return fields, names
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class Alpha158DL(QlibDataLoader):
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"""Dataloader to get Alpha158"""
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def __init__(self, config=None, **kwargs):
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_config = {
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"feature": self.get_feature_config(),
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||||
}
|
||||
if config is not None:
|
||||
_config.update(config)
|
||||
super().__init__(config=_config, **kwargs)
|
||||
|
||||
@staticmethod
|
||||
def get_feature_config(
|
||||
config={
|
||||
"kbar": {},
|
||||
"price": {
|
||||
"windows": [0],
|
||||
"feature": ["OPEN", "HIGH", "LOW", "VWAP"],
|
||||
},
|
||||
"rolling": {},
|
||||
}
|
||||
):
|
||||
"""create factors from config
|
||||
|
||||
config = {
|
||||
'kbar': {}, # whether to use some hard-code kbar features
|
||||
'price': { # whether to use raw price features
|
||||
'windows': [0, 1, 2, 3, 4], # use price at n days ago
|
||||
'feature': ['OPEN', 'HIGH', 'LOW'] # which price field to use
|
||||
},
|
||||
'volume': { # whether to use raw volume features
|
||||
'windows': [0, 1, 2, 3, 4], # use volume at n days ago
|
||||
},
|
||||
'rolling': { # whether to use rolling operator based features
|
||||
'windows': [5, 10, 20, 30, 60], # rolling windows size
|
||||
'include': ['ROC', 'MA', 'STD'], # rolling operator to use
|
||||
#if include is None we will use default operators
|
||||
'exclude': ['RANK'], # rolling operator not to use
|
||||
}
|
||||
}
|
||||
"""
|
||||
fields = []
|
||||
names = []
|
||||
if "kbar" in config:
|
||||
fields += [
|
||||
"($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($volume, 1)), %d)+1e-12)" % (d, d, d)
|
||||
for d in windows
|
||||
]
|
||||
names += ["VSUMD%d" % d for d in windows]
|
||||
|
||||
return fields, names
|
||||
@@ -7,7 +7,7 @@ from pathlib import Path
|
||||
import warnings
|
||||
import pandas as pd
|
||||
|
||||
from typing import Tuple, Union, List
|
||||
from typing import Tuple, Union, List, Dict
|
||||
|
||||
from qlib.data import D
|
||||
from qlib.utils import load_dataset, init_instance_by_config, time_to_slc_point
|
||||
@@ -247,10 +247,14 @@ class StaticDataLoader(DataLoader, Serializable):
|
||||
|
||||
def load(self, instruments=None, start_time=None, end_time=None) -> pd.DataFrame:
|
||||
self._maybe_load_raw_data()
|
||||
|
||||
# 1) Filter by instruments
|
||||
if instruments is None:
|
||||
df = self._data
|
||||
else:
|
||||
df = self._data.loc(axis=0)[:, instruments]
|
||||
|
||||
# 2) Filter by Datetime
|
||||
if start_time is None and end_time is None:
|
||||
return df # NOTE: avoid copy by loc
|
||||
# pd.Timestamp(None) == NaT, use NaT as index can not fetch correct thing, so do not change None.
|
||||
@@ -275,6 +279,55 @@ class StaticDataLoader(DataLoader, Serializable):
|
||||
self._data = self._config
|
||||
|
||||
|
||||
class NestedDataLoader(DataLoader):
|
||||
"""
|
||||
We have multiple DataLoader, we can use this class to combine them.
|
||||
"""
|
||||
|
||||
def __init__(self, dataloader_l: List[Dict], join="left") -> None:
|
||||
"""
|
||||
|
||||
Parameters
|
||||
----------
|
||||
dataloader_l : list[dict]
|
||||
A list of dataloader, for exmaple
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
nd = NestedDataLoader(
|
||||
dataloader_l=[
|
||||
{
|
||||
"class": "qlib.contrib.data.loader.Alpha158DL",
|
||||
}, {
|
||||
"class": "qlib.contrib.data.loader.Alpha360DL",
|
||||
"kwargs": {
|
||||
"config": {
|
||||
"label": ( ["Ref($close, -2)/Ref($close, -1) - 1"], ["LABEL0"])
|
||||
}
|
||||
}
|
||||
}
|
||||
]
|
||||
)
|
||||
join :
|
||||
it will pass to pd.concat when merging it.
|
||||
"""
|
||||
super().__init__()
|
||||
self.data_loader_l = [
|
||||
(dl if isinstance(dl, DataLoader) else init_instance_by_config(dl)) for dl in dataloader_l
|
||||
]
|
||||
self.join = join
|
||||
|
||||
def load(self, instruments=None, start_time=None, end_time=None) -> pd.DataFrame:
|
||||
df_full = None
|
||||
for dl in self.data_loader_l:
|
||||
df_current = dl.load(instruments, start_time, end_time)
|
||||
if df_full is None:
|
||||
df_full = df_current
|
||||
else:
|
||||
df_full = pd.merge(df_full, df_current, left_index=True, right_index=True, how=self.join)
|
||||
return df_full.sort_index(axis=1)
|
||||
|
||||
|
||||
class DataLoaderDH(DataLoader):
|
||||
"""DataLoaderDH
|
||||
DataLoader based on (D)ata (H)andler
|
||||
|
||||
50
tests/data_mid_layer_tests/test_dataloader.py
Normal file
50
tests/data_mid_layer_tests/test_dataloader.py
Normal file
@@ -0,0 +1,50 @@
|
||||
# TODO:
|
||||
# dump alpha 360 to dataframe and merge it with Alpha158
|
||||
|
||||
import sys
|
||||
import unittest
|
||||
import qlib
|
||||
from pathlib import Path
|
||||
|
||||
sys.path.append(str(Path(__file__).resolve().parent))
|
||||
from qlib.data.dataset.loader import NestedDataLoader
|
||||
from qlib.contrib.data.loader import Alpha158DL, Alpha360DL
|
||||
|
||||
|
||||
class TestDataLoader(unittest.TestCase):
|
||||
|
||||
def test_nested_data_loader(self):
|
||||
qlib.init()
|
||||
nd = NestedDataLoader(
|
||||
dataloader_l=[
|
||||
{
|
||||
"class": "qlib.contrib.data.loader.Alpha158DL",
|
||||
},
|
||||
{
|
||||
"class": "qlib.contrib.data.loader.Alpha360DL",
|
||||
"kwargs": {"config": {"label": (["Ref($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()
|
||||
Reference in New Issue
Block a user