Add get_train_times as defined in the book page 106 on CV.

.gitignore

@@ -1 +1,4 @@
-.idea/*
+.idea/*
+__pycache__
+test_reports
+.coverage

mlfinlab/cross_validation/__init__.py

@@ -0,0 +1,9 @@
+"""
+Functions derived from Chapter 7: Cross Validation
+"""
+
+from mlfinlab.cross_validation.cross_validation import get_train_times
+
+__all__ = [
+    'get_train_times',
+]

mlfinlab/cross_validation/cross_validation.py

@@ -0,0 +1,21 @@
+"""
+Implements the book chapter 7 on Cross Validation for financial data
+"""
+
+import pandas as pd
+
+
+def get_train_times(observations: pd.Series, test_times: pd.Series) -> pd.Series:  # pragma: no cover
+    """
+    Given test_times, find the times of the training observations.
+    —observations.index: Time when the observation started.
+    —observations.value: Time when the observation ended.
+    —test_times: Times of testing observations.
+    """
+    train = observations.copy(deep=True)
+    for start_ix, end_ix in test_times.iteritems():
+        df0 = train[(start_ix <= train.index) & (train.index <= end_ix)].index  # train starts within test
+        df1 = train[(start_ix <= train) & (train <= end_ix)].index  # train ends within test
+        df2 = train[(train.index <= start_ix) & (end_ix <= train)].index  # train envelops test
+        train = train.drop(df0.union(df1).union(df2))
+    return train

mlfinlab/tests/test_cross_validation.py

@@ -0,0 +1,115 @@
+"""
+Tests the cross validation technique described in Ch.7 of the book
+"""
+import unittest
+import os
+import pandas as pd
+
+from mlfinlab.cross_validation.cross_validation import get_train_times
+
+
+class TestCrossValidation(unittest.TestCase):
+    """
+    Test the functionality of the time series cross validation technique
+    """
+
+    def __init__(self, *args):
+        super().__init__(*args)
+        self.verbose = False
+
+    def log(self, msg):
+        """
+        Simple method to suppress debugging strings
+        """
+        if self.verbose:  # pragma: no cover
+            print(msg)
+
+    def setUp(self):
+
+        """
+        This is how the observations dataset looks like
+        2019-01-01 00:00:00   2019-01-01 00:02:00
+        2019-01-01 00:01:00   2019-01-01 00:03:00
+        2019-01-01 00:02:00   2019-01-01 00:04:00
+        2019-01-01 00:03:00   2019-01-01 00:05:00
+        2019-01-01 00:04:00   2019-01-01 00:06:00
+        2019-01-01 00:05:00   2019-01-01 00:07:00
+        2019-01-01 00:06:00   2019-01-01 00:08:00
+        2019-01-01 00:07:00   2019-01-01 00:09:00
+        2019-01-01 00:08:00   2019-01-01 00:10:00
+        2019-01-01 00:09:00   2019-01-01 00:11:00
+        """
+
+        pwd_path = os.path.dirname(__file__)
+        self.log(f"pwd_path= {pwd_path}")
+
+        self.observations = pd.Series(
+            index=pd.date_range(start='2019-01-01 00:00:00', periods=10, freq='T'),
+            data=pd.date_range(start='2019-01-01 00:02:00', periods=10, freq='T'),
+        )
+        self.log(self.observations)
+
+    def test_get_train_times_1(self):
+        """
+        Tests the get_train_times method for the case where the train STARTS within test
+        """
+        test_times = pd.Series(
+            index=pd.date_range(start='2019-01-01 00:01:00', periods=1, freq='T'),
+            data=pd.date_range(start='2019-01-01 00:02:00', periods=1, freq='T'),
+        )
+        self.log(f"test_times=\n{test_times}")
+        train_times_ret = get_train_times(self.observations, test_times)
+        self.log(f"train_times_ret=\n{train_times_ret}")
+
+        train_times_ok = pd.Series(
+            index=pd.date_range(start='2019-01-01 00:03:00', end='2019-01-01 00:09:00', freq='T'),
+            data=pd.date_range(start='2019-01-01 00:05:00', end='2019-01-01 00:11:00', freq='T'),
+        )
+        self.log(f"train_times=\n{train_times_ok}")
+
+        self.assertTrue(train_times_ret.equals(train_times_ok), "train dataset doesn't match")
+
+    def test_get_train_times_2(self):
+        """
+        Tests the get_train_times method for the case where the train ENDS within test
+        """
+        test_times = pd.Series(
+            index=pd.date_range(start='2019-01-01 00:08:00', periods=1, freq='T'),
+            data=pd.date_range(start='2019-01-01 00:11:00', periods=1, freq='T'),
+        )
+        self.log(f"test_times=\n{test_times}")
+        train_times_ret = get_train_times(self.observations, test_times)
+        self.log(f"train_times_ret=\n{train_times_ret}")
+
+        train_times_ok = pd.Series(
+            index=pd.date_range(start='2019-01-01 00:00:00', end='2019-01-01 00:05:00', freq='T'),
+            data=pd.date_range(start='2019-01-01 00:02:00', end='2019-01-01 00:07:00', freq='T'),
+        )
+        self.log(f"train_times=\n{train_times_ok}")
+
+        self.assertTrue(train_times_ret.equals(train_times_ok), "train dataset doesn't match")
+
+    def test_get_train_times_3(self):
+        """
+        Tests the get_train_times method for the case where the train ENVELOPES test
+        """
+        test_times = pd.Series(
+            index=pd.date_range(start='2019-01-01 00:06:00', periods=1, freq='T'),
+            data=pd.date_range(start='2019-01-01 00:08:00', periods=1, freq='T'),
+        )
+        self.log(f"test_times=\n{test_times}")
+        train_times_ret = get_train_times(self.observations, test_times)
+        self.log(f"train_times_ret=\n{train_times_ret}")
+
+        train_times_ok1 = pd.Series(
+            index=pd.date_range(start='2019-01-01 00:00:00', end='2019-01-01 00:03:00', freq='T'),
+            data=pd.date_range(start='2019-01-01 00:02:00', end='2019-01-01 00:05:00', freq='T'),
+        )
+        train_times_ok2 = pd.Series(
+            index=pd.date_range(start='2019-01-01 00:09:00', end='2019-01-01 00:09:00', freq='T'),
+            data=pd.date_range(start='2019-01-01 00:11:00', end='2019-01-01 00:11:00', freq='T'),
+        )
+        train_times_ok = pd.concat([train_times_ok1, train_times_ok2])
+        self.log(f"train_times=\n{train_times_ok}")
+
+        self.assertTrue(train_times_ret.equals(train_times_ok), "train dataset doesn't match")

scripts/run_tests.py

@@ -1,3 +1,7 @@
+"""
+Helper module used to tun tests
+"""
+
 import unittest
 import xmlrunner