Commit 06efd40b by Peter Baratta

Comment capitalization

parent 2b9d78df
......@@ -452,9 +452,12 @@ class FormulaResponseTest(ResponseTest):
# Expect such a large answer to be marked incorrect
input_formula = "x*1e999"
self.assert_grade(problem, input_formula, "incorrect")
# Expect such a large negative answer to be marked incorrect
input_formula = "-x*1e999"
self.assert_grade(problem, input_formula, "incorrect")
def test_grade_nan(self):
# attempt to produce a value which causes the student's answer to be
# Attempt to produce a value which causes the student's answer to be
# evaluated to nan. See if this is resolved correctly.
sample_dict = {'x': (1, 2)}
......@@ -465,7 +468,7 @@ class FormulaResponseTest(ResponseTest):
tolerance="1%",
answer="x")
# Expect an incorrect answer (+ nan) to be marked incorrect
# right now this evaluates to 'nan' for a given x (Python implementation-dependent)
# Right now this evaluates to 'nan' for a given x (Python implementation-dependent)
input_formula = "10*x + 0*1e999"
self.assert_grade(problem, input_formula, "incorrect")
# Expect an correct answer (+ nan) to be marked incorrect
......@@ -756,18 +759,19 @@ class NumericalResponseTest(ResponseTest):
answer=4,
tolerance="10%")
correct_responses = []
incorrect_responses = ["1e999"]
incorrect_responses = ["1e999", "-1e999"]
self.assert_multiple_grade(problem, correct_responses, incorrect_responses)
def test_grade_nan(self):
# attempt to produce a value which causes the student's answer to be
# Attempt to produce a value which causes the student's answer to be
# evaluated to nan. See if this is resolved correctly.
problem = self.build_problem(question_text="What is 2 + 2 approximately?",
explanation="The answer is 4",
answer=4,
tolerance="10%")
correct_responses = []
# right now these evaluate to 'nan'
# Right now these evaluate to `nan`
# `4 + nan` should be incorrect
incorrect_responses = ["0*1e999", "4 + 0*1e999"]
self.assert_multiple_grade(problem, correct_responses, incorrect_responses)
......
......@@ -23,7 +23,9 @@ def compare_with_tolerance(v1, v2, tol):
tolerance = evaluator(dict(), dict(), tol)
if isinf(v1) or isinf(v2):
# because the other numerical comparison does not work with infinities
# If an input is infinite, we can end up with `abs(v1-v2)` and
# `tolerance` both equal to infinity. Then, below we would have
# `inf <= inf` which is a fail. Instead, compare directly.
return v1 == v2
else:
return abs(v1 - v2) <= tolerance
......
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