class_docstr: Bitmap Algorithm.
  This method breaks time series into chunks and uses the frequency of similar chunks
  to determine anomaly scores.
  The ideas are from this paper:
  Assumption-Free Anomaly Detection in Time Series(http://alumni.cs.ucr.edu/~ratana/SSDBM05.pdf).
class_docstr_tok: ["Bitmap","Algorithm",".","This","method","breaks","time","series","into","chunks","and","uses","the","frequency","of","similar","chunks","to","determine","anomaly","scores",".","The","ideas","are","from","this","paper",":","Assumption-Free","Anomaly","Detection","in","Time","Series","(","http",":","\/\/alumni.cs.ucr.edu\/~ratana\/SSDBM05.pdf",")","."]
docstr: Generate SAX representation for all values of the time series.
docstr_tok: ["Generate","SAX","representation","for","all","values","of","the","time","series","."]
code: def _generate_SAX(self):
      """
      Generate SAX representation for all values of the time series.
      """
      sections = {}
      self.value_min = self.time_series.min()
      self.value_max = self.time_series.max()
      # Break the whole value range into different sections.
      section_height = (
          self.value_max - self.value_min
      ) / self.precision
      for section_number in range(self.precision):
          sections[section_number] = (
              self.value_min + section_number * section_height
          )
      # Generate SAX representation.
      self.sax = "".join(
          self._generate_SAX_single(sections, value)
          for value in self.time_series.values
      )
  
file_path: luminol/src/luminol/algorithms/anomaly_detector_algorithms/bitmap_detector.py
imports: from collections import defaultdict
  from copy import copy
  import math
  from luminol import exceptions
  from luminol.algorithms.anomaly_detector_algorithms import AnomalyDetectorAlgorithm
  from luminol.modules.time_series import TimeSeries
  from luminol.constants import DEFAULT_BITMAP_PRECISION, DEFAULT_BITMAP_CHUNK_SIZE, DEFAULT_BITMAP_LAGGING_WINDOW_SIZE_PCT, DEFAULT_BITMAP_LEADING_WINDOW_SIZE_PCT, DEFAULT_BITMAP_MINIMAL_POINTS_IN_WINDOWS, DEFAULT_BITMAP_MAXIMAL_POINTS_IN_WINDOWS
label_desc: Use image node_id 4 for calling the BitmapDetector obj's underlying member method code with example usage: obj._generate_SAX() without return types