code: def setup(self, shape, cost_type):
      cost_func = {
          "uniform": random_uniform,
          "spatial": random_spatial,
          "logarithmic": random_logarithmic,
          "integer": random_integer,
          "binary": random_binary,
      }[cost_type]
  
      self.cost_matrix = cost_func(shape)
  
file_path: scipy/benchmarks/benchmarks/optimize_lap.py
imports: from concurrent.futures import ThreadPoolExecutor, wait
  import numpy
  from .common import Benchmark, safe_import
label_desc: Use image node_id 1 for calling the LinearAssignment obj's underlying member method code with example usage: obj.setup(shape, cost_type) without return types