docstr: From an initial design, it selects the locations randomly, according to the specified design_type generation scheme.
  :param model_space: set to true when the samples need to be obtained for the input domain of the model
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code: def __init__(self, space, design_type, num_samples=10000):
      """
      From an initial design, it selects the locations randomly, according to the specified design_type generation scheme.
      :param model_space: set to true when the samples need to be obtained for the input domain of the model
  
      """
      super(RandomAnchorPointsGenerator, self).__init__(
          space, design_type, num_samples
      )
  
imports: import logging
  import numpy
  from ..experiment_design import initial_design
  from ..core.errors import FullyExploredOptimizationDomainError
  from ..core.task.space import Design_space
label_desc: Use image node_id 1 to create a new RandomAnchorPointsGenerator object from inherited base classes: AnchorPointsGenerator with example: obj = RandomAnchorPointsGenerator(space, design_type, num_samples)