class_docstr: HOG1D transform.
  
  This class is to calculate the HOG1D transform of a
  dataframe of time series data. Works by splitting
  the time series num_intervals times, and calculate
  a histogram of gradients within each interval.
  
  Parameters
  ----------
      num_intervals   : int, length of interval.
      num_bins        : int, num bins in the histogram.
      scaling_factor  : float, a constant that is multiplied
                        to modify the distribution.
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docstr: Calculate the HOG1Ds given a time series.
  
  Parameters
  ----------
  X : a numpy array of shape = [time_series_length]
  
  Returns
  -------
  HOG1Ds : a numpy array of shape = [num_intervals*num_bins].
           It contains the histogram of each gradient within
           each interval.
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code: def _calculate_hog1ds(self, X):
      """Calculate the HOG1Ds given a time series.
  
      Parameters
      ----------
      X : a numpy array of shape = [time_series_length]
  
      Returns
      -------
      HOG1Ds : a numpy array of shape = [num_intervals*num_bins].
               It contains the histogram of each gradient within
               each interval.
      """
      # Firstly, split the time series into approx equal
      # length intervals
      splitTimeSeries = self._split_time_series(X)
      HOG1Ds = []
  
      for x in range(len(splitTimeSeries)):
          HOG1Ds.extend(self._get_hog1d(splitTimeSeries[x]))
  
      return HOG1Ds
  
file_path: sktime/sktime/transformations/panel/hog1d.py
imports: import math
  import numbers
  import numpy
  import pandas
  from sktime.datatypes._panel._convert import from_nested_to_2d_array
  from sktime.transformations.base import BaseTransformer
label_desc: Use image node_id 3 for calling the HOG1DTransformer obj's underlying member method code with example usage: obj._calculate_hog1ds(X) and returns: HOG1Ds