Add CustomHolidayFeatureSet (#13)

* Add CustomHolidayFeatureSet

Add CustomHolidayFeatureSet

* Add tests for CustomHolidayFeatureSet

Add tests for CustomHolidayFeatureSet

* Adding to init py

Adding to init py

pts/feature/__init__.py

@@ -1,4 +1,4 @@
-from .holiday import SPECIAL_DATE_FEATURES, SpecialDateFeatureSet, CustomDateFeatureSet
+from .holiday import SPECIAL_DATE_FEATURES, SpecialDateFeatureSet, CustomDateFeatureSet, CustomHolidayFeatureSet
 from .lag import get_lags_for_frequency, get_fourier_lags_for_frequency
 from .time_feature import (
     DayOfMonth,

pts/feature/holiday.py

@@ -293,3 +293,84 @@ class CustomDateFeatureSet:
                 for ref_date in self.reference_dates
             ]
         )
+    
+class CustomHolidayFeatureSet:
+    """
+    Implements calculation of holiday features. The CustomHolidayFeatureSet is
+    applied on a pandas Series with Datetimeindex and returns a 2D array of
+    the shape (len(dates), num_features), where num_features are the number
+    of holidays.
+
+    Note that for lower than daily granularity the distance to the holiday is
+    still computed on a per-day basis.
+
+    Example use:
+
+        >>> from gluonts.time_feature.holiday import (
+        ...    squared_exponential_kernel,
+        ...    SpecialDateFeatureSet,
+        ...    CHRISTMAS_DAY,
+        ...    CHRISTMAS_EVE
+        ... )
+        >>> import pandas as pd
+        >>> from pandas.tseries.holiday import Holiday
+        >>> cfs = CustomHolidayFeatureSet([Holiday("New Years Day", month=1, day=1), Holiday("Christmas Day", month=12, day=25)])
+        >>> date_indices = pd.date_range(
+        ...     start="2016-12-24",
+        ...     end="2016-12-31",
+        ...     freq='D'
+        ... )
+        >>> cfs(date_indices)
+        array([[1., 0., 0., 0., 0., 0., 0., 0.],
+               [0., 1., 0., 0., 0., 0., 0., 0.]])
+
+    Example use for using a squared exponential kernel:
+
+        >>> kernel = squared_exponential_kernel(alpha=1.0)
+        >>> sfs = SpecialDateFeatureSet([Holiday("New Years Day", month=1, day=1), Holiday("Christmas Day", month=12, day=25)], kernel)
+        >>> sfs(date_indices)
+        array([[1.00000000e+00, 3.67879441e-01, 1.83156389e-02, 1.23409804e-04,
+                1.12535175e-07, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
+               [3.67879441e-01, 1.00000000e+00, 3.67879441e-01, 1.83156389e-02,
+                1.23409804e-04, 1.12535175e-07, 0.00000000e+00, 0.00000000e+00]])
+
+    """
+
+    def __init__(
+        self,
+        custom_holidays: List[Holiday],
+        kernel_function: Callable[[int], int] = indicator,
+    ):
+        """
+        Parameters
+        ----------
+        feature_names
+            list of strings with holiday names for which features should be created.
+        kernel_function
+            kernel function to pass the feature value based
+            on distance in days. Can be indicator function (default),
+            exponential_kernel, squared_exponential_kernel or user defined.
+        """
+        self.custom_holidays = custom_holidays
+        self.kernel_function = kernel_function
+
+    def __call__(self, dates):
+        """
+        Transform a pandas series with timestamps to holiday features.
+
+        Parameters
+        ----------
+        dates
+            Pandas series with Datetimeindex timestamps.
+        """
+        return np.vstack(
+            [
+                np.hstack(
+                    [
+                        self.kernel_function(distance_to_holiday(custom_holiday)(index))
+                        for index in dates
+                    ]
+                )
+                for custom_holiday in self.custom_holidays
+            ]
+        ) 

test/feature/test_holiday.py

@@ -15,6 +15,8 @@
 import numpy as np
 import pandas as pd
 import pytest
+from pandas.tseries.holiday import Holiday
+
 
 # First-party imports
 from pts.feature.holiday import (
@@ -272,3 +274,18 @@ def test_custom_date_feature_set():
     assert(np.sum(cfs(date_indices) - sfs(date_indices)) == 0), "Features don't match"
         
 
+def test_custom_holiday_feature_set():
+
+    custom_holidays = [Holiday("New Years Day", month=1, day=1), Holiday("Christmas Day", month=12, day=25)]
+
+    kernel = exponential_kernel(alpha=1.0)
+
+    cfs = CustomHolidayFeatureSet(custom_holidays, kernel)
+    sfs = SpecialDateFeatureSet([NEW_YEARS_DAY, CHRISTMAS_DAY], kernel)
+
+    date_indices = pd.date_range(
+            start=pd.to_datetime('20191101', format='%Y%m%d'),
+            end=pd.to_datetime('20200131', format='%Y%m%d'),
+            freq='D')
+
+    assert(np.sum(cfs(date_indices) - sfs(date_indices)) == 0), "Features don't match"