code: def test_dense_matrix_is_transposed(self):
      mat1 = DenseMatrix(3, 2, [0, 4, 1, 6, 3, 9], isTransposed=True)
      mat = DenseMatrix(3, 2, [0, 1, 3, 4, 6, 9])
      self.assertEqual(mat1, mat)
  
      expected = [[0, 4], [1, 6], [3, 9]]
      for i in range(3):
          for j in range(2):
              self.assertEqual(mat1[i, j], expected[i][j])
      self.assertTrue(array_equal(mat1.toArray(), expected))
  
      sm = mat1.toSparse()
      self.assertTrue(array_equal(sm.rowIndices, [1, 2, 0, 1, 2]))
      self.assertTrue(array_equal(sm.colPtrs, [0, 2, 5]))
      self.assertTrue(array_equal(sm.values, [1, 3, 4, 6, 9]))
  
imports: import array
  import unittest
  from numpy import array, array_equal, zeros, arange, tile, ones, inf
  import pyspark.ml.linalg
  from pyspark.serializers import CPickleSerializer
  from pyspark.mllib.linalg import Vector, SparseVector, DenseVector, VectorUDT, _convert_to_vector, DenseMatrix, SparseMatrix, Vectors, Matrices, MatrixUDT
  from pyspark.mllib.linalg.distributed import RowMatrix, IndexedRowMatrix, IndexedRow
  from pyspark.mllib.regression import LabeledPoint
  from pyspark.sql import Row
  from pyspark.testing.mllibutils import MLlibTestCase
  from pyspark.testing.utils import have_scipy
label_desc: Use image node_id 15 for calling the VectorTests obj's underlying member method code with example usage: obj.test_dense_matrix_is_transposed() without return types