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)
