KaneAI - World’s First E2E Software Testing Agent.Book a Demo Join TestMu Conference

How to use test_unbounded method in hypothesis

Best Python code snippet using hypothesis

LinProgramming.py

Source:LinProgramming.py

...76            if self.test_optimal() == 1:77                print("you have reached the optimal Tabular")78                print(str(self.step) + " steps were taken")79                break80            if self.test_unbounded() == 1:81                print("This Problem Is Unbounded")82                print("step reached: " + str(self.step))83                break84            if self.test_infeasible() == 1:85                print("This problem is infeasible")86                print("step reached: " + str(self.step))87                break88        rhs_j = self.prog.tab0.shape[1] - 189        for i, rhs_i in zip(self.prog.B, range(self.prog.B.size)):90            self.solution[int(i)] = self.prog.tab0[rhs_i, rhs_j]91        self.objective = self.prog.tab0[self.prog.tab0.shape[0] - 1, self.prog.tab0.shape[1] - 1]92    def jordan_exchange(self):93        self.prog.get_pivot()94        self.prog.update_col()95        self.prog.update_row()96        self.prog.update_rest()97        self.prog.tab0 = copy.copy(self.prog.tab1)98        self.prog.tab1[0:-1, 0:-1] = 099        self.step += 1100    def test_unbounded(self):101        for i in range(self.prog.tab0.shape[1] - 1):102            if sum(v >= 0 for v in self.prog.tab0[:, i]) == self.prog.tab0.shape[0]:103                return 1104    def test_optimal(self):105        tab = self.prog.tab0106        obj_arr = tab[-1:, :][0, :]107        rhs_arr = tab[:, self.prog.n_V - 1]108        if sum(n > 0 for n in obj_arr[:-1]) == 0:109            if sum(n < 0 for n in rhs_arr) == 0:110                return 1111        else:112            return 0113    def test_infeasible(self):114        tab = self.prog.tab1...

test_exact.py

Source:test_exact.py

...8            [[0.5, 0.5], [1, 0.5], [0, 1]], dtype=np.float329        )10        self.y_train = np.array([1, 1, 0], dtype=np.int)11        self.x_eval = np.array([0, 0], dtype=np.float)12    def test_unbounded(self):13        solver = ExactSolver(14            self.X_train, self.y_train,15            QpSolverFactory().create('gcd'), 1, False16        )17        perturbation = solver(self.x_eval)18        self.assertTrue(19            np.allclose(20                perturbation,21                np.array([-0.25, 0.25], dtype=self.X_train.dtype)22            )23        )24        self.assertEqual(25            perturbation.dtype, self.X_train.dtype26        )...

test_box.py

Source:test_box.py

1import numpy as np2import psdr3def test_unbounded(m = 5):4	dom = psdr.BoxDomain(-np.inf*np.ones(m), np.inf*np.ones(m))5	assert dom.is_unbounded == True6	7	dom = psdr.BoxDomain(-np.ones(m), np.ones(m))8	assert dom.is_unbounded == False9def test_point(m = 5):10	dom = psdr.BoxDomain(np.ones(m), np.ones(m))11	assert dom.is_point == True12	13	dom = psdr.BoxDomain(-np.ones(m), np.ones(m))...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.