def test_records_assortment(self): """ Check that the model records assortment. """ gens = 26 pop = Population.from_random(32) assort0 = pop.average_assortment myModel = Model( pop, h = 0.4, s = 0.6, delta = 0.3, generations = gens) myModel.go() self.assertEqual( len( myModel.desired_assortment ), gens ) self.assertEqual( assort0, myModel.desired_assortment[0] )
def test_records_fairness(self): """ Test that the model record fairness, simply by asserting that the model has a list of the length of the number of generations. """ gens = 26 pop = Population.from_random(32) fairness0 = pop.fairness myModel = Model( pop, h = 0.4, s = 0.6, delta = 0.3, generations = gens) myModel.go() self.assertEqual( len( myModel.fairness ), gens ) self.assertEqual( fairness0, myModel.fairness[0] )
def test_can_construct_with_random_pop(self): """ Assert that we can constuct the class from a random population. """ myModel = Model.from_random_pop( 16, h = 0.4, s = 0.4, delta =0.2) self.assertIsInstance( myModel, Model ) self.assertEqual( myModel.size, 16 )
def test_model_handles_mutation(self): """ Run the model for one generation, and see that mutation is taking effect. """ mod = Model.from_random_pop( 16, 0.4, 0.5, 0.1, graphs = False,\ generations = 1, mu_strat = 0.5, mu_assort = 0 ) mod.go() ##We're bascially just checking that this runs, so this is just a minimal test self.assertIsInstance(mod,Model)
def test_make_graph_returns_matplotlib_figure(self): """ Simply assert that the function returns a figure. """ myModel = Model.from_random_pop( 16, 0.4, 0.5, 0.1, graphs = False) myModel.go() fig = myModel.make_graphs() self.assertIsInstance( fig, mpl.figure.Figure )
def test_go(self): """ Can't really test the whole Model automatically in any detail, but check that the whole thing can run, and the population stays the same size """ myModel = Model.from_random_pop( 16, h = 0.4, s = 0.4, delta =0.2) myModel.go() self.assertEqual( len( myModel.Population ), len( myModel.pop0 ) ) ##Check that something has happened at least self.assertNotEqual( myModel.Population, myModel.pop0 )
def test_model_sets_final_results(self): """ The other classes will be looking for certain key words after the simulation has stopped. Check that they exist, and are sensible vaules. """ myModel = Model.from_random_pop( 16, 0.4, 0.5, 0.1 ) myModel.go() self.assertGreaterEqual( myModel.final_fairness, 0 ) self.assertLessEqual( myModel.final_fairness, 1 ) self.assertGreaterEqual( myModel.final_desired_assortment, 0 ) self.assertLessEqual( myModel.final_desired_assortment, 1 )
def test_can_be_contructed_from_function(self): """ Test that we can construct a model from a function that returns an individual. """ ##Make a function that returns a constan individual def _const_ind(): return Individual(1,1,1,1) myModel = Model.from_function( _const_ind, 12, 0.3,0.3,0.9 ) self.assertIsInstance(myModel, Model) self.assertEqual( myModel.size, 12 ) self.assertEqual( myModel.delta, 0.9 ) self.assertEqual( myModel.Population.fairness, 1 ) self.assertEqual( myModel.Population.average_assortment, 1 )
