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# This file is adapted from the DeepGlo Project. https://github.com/rajatsen91/deepglo
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import pandas as pd
import numpy as np
[docs]class TimeCovariates(object):
def __init__(self, start_date, num_ts=100, freq="H", normalized=True):
self.start_date = start_date
self.num_ts = num_ts
self.freq = freq
self.normalized = normalized
self.dti = pd.date_range(self.start_date, periods=self.num_ts, freq=self.freq)
def _minute_of_hour(self):
minutes = np.array(self.dti.minute, dtype=np.float)
if self.normalized:
minutes = minutes / 59.0 - 0.5
return minutes
def _hour_of_day(self):
hours = np.array(self.dti.hour, dtype=np.float)
if self.normalized:
hours = hours / 23.0 - 0.5
return hours
def _day_of_week(self):
dayWeek = np.array(self.dti.dayofweek, dtype=np.float)
if self.normalized:
dayWeek = dayWeek / 6.0 - 0.5
return dayWeek
def _day_of_month(self):
dayMonth = np.array(self.dti.day, dtype=np.float)
if self.normalized:
dayMonth = dayMonth / 30.0 - 0.5
return dayMonth
def _day_of_year(self):
dayYear = np.array(self.dti.dayofyear, dtype=np.float)
if self.normalized:
dayYear = dayYear / 364.0 - 0.5
return dayYear
def _month_of_year(self):
monthYear = np.array(self.dti.month, dtype=np.float)
if self.normalized:
monthYear = monthYear / 11.0 - 0.5
return monthYear
def _week_of_year(self):
weekYear = np.array(self.dti.weekofyear, dtype=np.float)
if self.normalized:
weekYear = weekYear / 51.0 - 0.5
return weekYear
[docs] def get_covariates(self):
MOH = self._minute_of_hour().reshape(1, -1)
HOD = self._hour_of_day().reshape(1, -1)
DOM = self._day_of_month().reshape(1, -1)
DOW = self._day_of_week().reshape(1, -1)
DOY = self._day_of_year().reshape(1, -1)
MOY = self._month_of_year().reshape(1, -1)
WOY = self._week_of_year().reshape(1, -1)
all_covs = [MOH, HOD, DOM, DOW, DOY, MOY, WOY]
return np.vstack(all_covs)