code: def decode_one(self, vector, return_as_datetime=False):
      if sum(vector) == 0:
          decoded = None
  
      else:
          if self.sinusoidal:
              vector = list(map(lambda x: np.arcsin(x), vector))[::2]
          c = self.constants
  
          year = max(0, round(vector[0] * c["year"]))
          month = max(1, min(12, round(vector[1] * c["month"])))
          day_constant = calendar.monthrange(year, month)[-1]
          day = max(
              1, min(round(vector[2] * day_constant), day_constant)
          )
          hour = max(0, min(23, round(vector[4] * c["hour"])))
          minute = max(0, min(59, round(vector[5] * c["minute"])))
          second = max(0, min(59, round(vector[6] * c["second"])))
  
          dt = datetime.datetime(
              year=year,
              month=month,
              day=day,
              hour=hour,
              minute=minute,
              second=second,
          )
  
          if return_as_datetime is True:
              decoded = dt
          else:
              decoded = round(dt.timestamp())
  
      return decoded
  
file_path: lightwood/lightwood/encoder/datetime/datetime_sin_normalizer.py
imports: import datetime
  import calendar
  import numpy
  import pandas
  import torch
  from lightwood.encoder.base import BaseEncoder
  from collections.abc import Iterable
  from lightwood.helpers.general import is_none
label_desc: Use image node_id 6 for calling the DatetimeNormalizerEncoder obj's underlying member method code with example usage: obj.decode_one(vector, return_as_datetime) and returns: decoded