new_contents: import numpy
  import unittest
  import zerosum.nash
  
  num_random_trials = 100
  strategy_count = 16
  
  class TestNash(unittest.TestCase):
      def test_random(self):
          for i in range(num_random_trials):
              payoff_matrix = numpy.random.normal(size = (strategy_count, strategy_count))
              row_result, col_result = zerosum.nash.nash(payoff_matrix)
              # Both results should have the same value (with opposite sign).
              numpy.testing.assert_allclose(row_result.value, -col_result.value)
              row_payoffs = numpy.average(payoff_matrix, axis = 1, weights = col_result.strategy)
              col_payoffs = numpy.average(payoff_matrix, axis = 0, weights = row_result.strategy)
              # Value should be close to the best possible expected payoff.
              numpy.testing.assert_allclose(numpy.max(row_payoffs), row_result.value)
              numpy.testing.assert_allclose(numpy.min(col_payoffs), -col_result.value)
  
subject: add nash test