def test_linear_too_few_comparisons():
FormulaGrader.set_default_comparer(LinearComparer())
grader = FormulaGrader(samples=2)
with raises(
ConfigError,
match='Cannot perform linear comparison with less than 3 samples'):
grader('1.5', '1.5')
# Ensure that NumericalGrader does not use the same default comparer as FormulaGrader
grader = NumericalGrader()
assert grader('1.5', '1.5')['ok']
FormulaGrader.reset_default_comparer()
def test_default_comparer():
"""Tests setting and resetting default_comparer"""
def silly_comparer(comparer_params_eval, student_eval, utils):
return utils.within_tolerance(1, student_eval)
FormulaGrader.set_default_comparer(silly_comparer)
silly_grader = FormulaGrader(answers='pi')
FormulaGrader.reset_default_comparer()
grader = FormulaGrader(answers='pi')
silly_grader.config['answers'][0]['expect']['comparer'] is silly_comparer
assert silly_grader(None, '1')['ok']
grader.config['answers'][0]['expect']['comparer'] is equality_comparer
assert not grader(None, '1')['ok']
assert grader(None, '3.141592653')['ok']
def test_scaling_partial_credit():
FormulaGrader.set_default_comparer(LinearComparer())
grader = FormulaGrader(answers=('m*c^2', {
'expect': 'm*c^3',
'grade_decimal': 0.1
}),
variables=['m', 'c'])
FormulaGrader.reset_default_comparer()
expected = {
'ok':
'partial',
'grade_decimal':
0.1 * 0.5,
# This message is a bit awkward ... in this situation, probably better to set up
# a different LinearComparer for the common wrong answers, if you want to do that.
# Or only use an linear comparer for the correct answer, and use equality_compaer
# for the common wrong answers.
# Anyway, I'm just testing the partial credit scaling
'msg':
'The submitted answer differs from an expected answer by a constant factor.',
}
assert grader(None, '4*m*c^3') == expected
