code: def setup(self, n, min_only, format):
      rng = np.random.default_rng(1234)
      if format == "random":
          # make a random connectivity matrix
          data = scipy.sparse.rand(
              n,
              n,
              density=0.2,
              format="csc",
              random_state=42,
              dtype=np.bool_,
          )
          data.setdiag(np.zeros(n, dtype=np.bool_))
          self.data = data
      elif format == "star":
          rows = [0 for i in range(n - 1)] + [
              i + 1 for i in range(n - 1)
          ]
          cols = [i + 1 for i in range(n - 1)] + [
              0 for i in range(n - 1)
          ]
          weights = [i + 1 for i in range(n - 1)] * 2
          self.data = scipy.sparse.csr_matrix(
              (weights, (rows, cols)), shape=(n, n)
          )
      # choose some random vertices
      v = np.arange(n)
      rng.shuffle(v)
      self.indices = v[: int(n * 0.1)]
  
imports: import numpy
  import scipy.sparse
  from .common import Benchmark, safe_import
label_desc: Use image node_id 1 for calling the Dijkstra obj's underlying member method code with example usage: obj.setup(n, min_only, format) without return types