code: def templateClusterAllocationOneDimensionData(
      self,
      branching_factor=5,
      max_node_entries=10,
      initial_diameter=1.0,
      type_measurement=measurement_type.CENTROID_EUCLIDEAN_DISTANCE,
      entry_size_limit=20,
  ):
      input_data = (
          [[random()] for _ in range(10)]
          + [[random() + 4] for _ in range(10)]
          + [[random() + 8] for _ in range(10)]
          + [[random() + 12] for _ in range(10)]
      )
  
      birch_instance = birch(
          input_data,
          4,
          branching_factor,
          max_node_entries,
          initial_diameter,
          type_measurement,
          entry_size_limit,
      )
      birch_instance.process()
      clusters = birch_instance.get_clusters()
  
      assert len(clusters) == 4
      for cluster in clusters:
          assert len(cluster) == 10
  
imports: import unittest
  import matplotlib
  from pyclustering.samples.definitions import SIMPLE_SAMPLES, FCPS_SAMPLES
  from pyclustering.utils import read_sample
  from pyclustering.container.cftree import measurement_type
  from pyclustering.cluster.encoder import type_encoding
  from pyclustering.cluster.birch import birch
  from random import random
label_desc: Use image node_id 30 for calling the BirchUnitTest obj's underlying member method code with example usage: obj.templateClusterAllocationOneDimensionData(branching_factor, max_node_entries, initial_diameter, type_measurement, entry_size_limit) without return types