def test_0(self): points = 0 # use the same input vector for both u and v to avoid ambiguity in the order of iteration results = Feedback.call_user( self.st.power_iteration, self.ref.M_test, self.ref.x_test) if results is None: Feedback.add_feedback( 'Your function is not returning any variables.') self.fail() if Feedback.check_numpy_array_allclose('The return value from your function power_iteration', self.ref.xc, results): points += 0.5 results_hidden = Feedback.call_user( self.st.power_iteration, self.ref.M_hidden, self.ref.x_hidden) if Feedback.check_numpy_array_allclose('The return value from your function power_iteration (hidden test case)', self.ref.xc_hidden, results_hidden): points += 0.5 Feedback.set_score(points)
def test_4(self): if Feedback.check_numpy_array_allclose('right_side', self.ref.right_side, self.st.right_side): Feedback.set_score(1) else: Feedback.set_score(0)
def test_1(self): points = 0 results = feedback.call_user(self.st.array_to_scalar, self.ref.a1, self.ref.a2) ## Testing if the return values are given correctly if results is not None: if hasattr(results, '__len__'): if (len(results) != 2): feedback.add_feedback( 'Your function is not returning the correct number of variables' ) self.fail() else: (st_c, st_sumc) = results else: feedback.add_feedback( 'The return variables do not appear to be in tuple format') self.fail() else: feedback.add_feedback( 'Your function is not returning any variables.') self.fail() if feedback.check_numpy_array_allclose('c', self.ref.c, st_c, accuracy_critical=False): points += 0.5 if feedback.check_scalar('sum_c', self.ref.sum_c, st_sumc, accuracy_critical=True): points += 0.5 feedback.set_score(points)
def test_2(self): points = 0 xstar2 = convert_to_float_array(self.st.xstar2) if Feedback.check_numpy_array_allclose('xstar2', self.ref.xstar2, xstar2): points += 1 Feedback.set_score(points)
def test_1(self): points = 0 if Feedback.check_numpy_array_allclose('G', self.ref.G, self.st.G): points += 1 Feedback.set_score(points)
def test_0(self): if Feedback.check_numpy_array_allclose("x", self.ref.x, self.st.x): Feedback.set_score(1) else: Feedback.set_score(0)
def test_2(self): score = 0 if feedback.check_numpy_array_allclose("composition", self.ref.composition, self.st.composition, accuracy_critical=False): score += 1.0 feedback.set_score(score)
def test_4(self): points = 0 if Feedback.check_numpy_array_allclose('M3', self.ref.M3, self.st.M3): points += 1 Feedback.set_score(points)
def test_0(self): if Feedback.check_numpy_array_allclose('groups', self.ref.groups, self.st.groups): Feedback.set_score(1) else: Feedback.set_score(0)
def test_5(self): if Feedback.check_numpy_array_allclose('next_arr', self.ref.next_arr, self.st.next_arr): Feedback.set_score(1) else: Feedback.set_score(0)
def test_1(self): if Feedback.check_numpy_array_allclose('medians', self.ref.medians, self.st.medians): Feedback.set_score(1) else: Feedback.set_score(0)