def test_matrix_inverses_raise_error_if_disabled():
grader = MatrixGrader(answers='A^2',
variables=['A'],
sample_from={'A': RealMatrices()},
negative_powers=False)
match = 'Negative matrix powers have been disabled.'
with raises(MathArrayError, match=match):
grader(None, 'A^3*A^-1')['ok']
def test_wrong_answer_type_error_messages_with_scalars():
"""
Check that answer shape errors are raised correctly when answer or student_input
is a scalar.
These are worth checking separately because the numbers do not have 'shape'
attributes.
"""
grader = MatrixGrader(answers='[1, 2, 3]',
max_array_dim=2,
answer_shape_mismatch=dict(is_raised=True,
msg_detail='type'))
match = 'Expected answer to be a vector, but input is a scalar'
with raises(InputTypeError, match=match):
grader(None, '10')
grader = MatrixGrader(answers='10',
max_array_dim=2,
answer_shape_mismatch=dict(is_raised=True,
msg_detail='type'))
match = 'Expected answer to be a scalar, but input is a vector'
with raises(InputTypeError, match=match):
grader(None, '[1, 2, 3]')
def test_works_with_matrixgrader():
grader = MatrixGrader(answers={
'comparer_params': ['x*A*B^2'],
'comparer':
LinearComparer(proportional=0.6, offset=0.4, linear=0.2)
},
variables=['x', 'A', 'B'],
sample_from={
'A': RealMatrices(),
'B': RealMatrices()
},
max_array_dim=2)
assert grader(None, 'x*A*B^2')['grade_decimal'] == 1.0
assert grader(None, '2*x*A*B^2')['grade_decimal'] == 0.6
assert grader(None, 'x*A*B^2 + 5*[[1, 1], [1, 1]]')['grade_decimal'] == 0.4
assert grader(None,
'3*x*A*B^2 + 5*[[1, 1], [1, 1]]')['grade_decimal'] == 0.2
assert grader(None, 'x*A*B^2 + x*[[1, 1], [1, 1]]')['grade_decimal'] == 0
assert grader(None, '0*A')['grade_decimal'] == 0
def test_identity_dim_provides_identity():
no_identity = MatrixGrader()
assert no_identity.constants.get('I', None) is None
grader = MatrixGrader(identity_dim=4)
assert equal_as_arrays(grader.constants['I'], identity(4))
def test_wrong_answer_type_error_messages():
# Note: our convention is that single-row matrix and vectors cannot
# be compared, [[1, 2, 3]] are graded as different [1, 2, 3]
# (and, in particular, incomparable)
grader = MatrixGrader(answers='[[1, 2, 3]]',
max_array_dim=2,
answer_shape_mismatch=dict(is_raised=True,
msg_detail='shape'))
match = (r'Expected answer to be a matrix of shape \(rows: 1, cols: 3\), '
r'but input is a vector of length 3')
with raises(InputTypeError, match=match):
grader(None, '[1, 2, 3]')
grader = MatrixGrader(answers='[[1, 2, 3]]',
max_array_dim=2,
answer_shape_mismatch=dict(is_raised=True,
msg_detail='type'))
match = 'Expected answer to be a matrix, but input is a vector'
with raises(InputTypeError, match=match):
grader(None, '[1, 2, 3]')
grader = MatrixGrader(answers='[[1, 2, 3]]',
max_array_dim=2,
answer_shape_mismatch=dict(is_raised=False,
msg_detail='shape'))
msg = ('Expected answer to be a matrix of shape (rows: 1, cols: 3), '
'but input is a vector of length 3')
assert grader(None, '[1, 2, 3]') == {
'ok': False,
'grade_decimal': 0,
'msg': msg
}
grader = MatrixGrader(answers='[[1, 2, 3]]',
max_array_dim=2,
answer_shape_mismatch=dict(is_raised=False,
msg_detail='type'))
msg = 'Expected answer to be a matrix, but input is a vector'
assert grader(None, '[1, 2, 3]') == {
'ok': False,
'grade_decimal': 0,
'msg': msg
}
msg = 'Expected answer to be a matrix, but input is a matrix of incorrect shape'
assert grader(None, '[[1, 2, 3, 4]]') == {
'ok': False,
'grade_decimal': 0,
'msg': msg
}
grader = MatrixGrader(answers='[[1, 2, 3]]',
max_array_dim=2,
answer_shape_mismatch=dict(is_raised=False,
msg_detail=None))
assert grader(None, '[1, 2, 3]') == {
'ok': False,
'grade_decimal': 0,
'msg': ''
}
def test_matrix_inverses_work_if_not_disabled():
grader = MatrixGrader(answers='A^2',
variables=['A'],
sample_from={'A': RealMatrices()})
assert grader(None, 'A^3*A^-1')['ok']