def grade(element_html, element_index, data):
element = lxml.html.fragment_fromstring(element_html)
name = pl.get_string_attrib(element, 'answers_name')
# Get weight
weight = pl.get_integer_attrib(element, 'weight', 1)
# Get true answer (if it does not exist, create no grade - leave it
# up to the question code)
a_tru = data['correct_answers'].get(name, None)
if a_tru is None:
return data
# Get submitted answer (if it does not exist, score is zero)
a_sub = data['submitted_answers'].get(name, None)
if a_sub is None:
data['partial_scores'][name] = {'score': 0, 'weight': weight}
return data
# Get method of comparison, with relabs as default
comparison = pl.get_string_attrib(element, 'comparison', 'relabs')
# Compare submitted answer with true answer
if comparison == 'relabs':
rtol = pl.get_float_attrib(element, 'rtol', 1e-5)
atol = pl.get_float_attrib(element, 'atol', 1e-8)
correct = pl.is_correct_scalar_ra(a_sub, a_tru, rtol, atol)
elif comparison == 'sigfig':
digits = pl.get_integer_attrib(element, 'digits', 2)
eps_digits = pl.get_integer_attrib(element, 'eps_digits', 3)
correct = pl.is_correct_scalar_sf(a_sub, a_tru, digits, eps_digits)
elif comparison == 'decdig':
digits = pl.get_integer_attrib(element, 'digits', 2)
eps_digits = pl.get_integer_attrib(element, 'eps_digits', 3)
correct = pl.is_correct_scalar_dd(a_sub, a_tru, digits, eps_digits)
else:
raise ValueError('method of comparison "%s" is not valid' % comparison)
if correct:
data['partial_scores'][name] = {'score': 1, 'weight': weight}
else:
data['partial_scores'][name] = {'score': 0, 'weight': weight}
return data
def grade(element_html, data):
element = lxml.html.fragment_fromstring(element_html)
name = pl.get_string_attrib(element, 'answers-name')
# Get weight
weight = pl.get_integer_attrib(element, 'weight', WEIGHT_DEFAULT)
# Get true answer (if it does not exist, create no grade - leave it
# up to the question code)
a_tru = pl.from_json(data['correct_answers'].get(name, None))
if a_tru is None:
return
# Get submitted answer (if it does not exist, score is zero)
a_sub = data['submitted_answers'].get(name, None)
if a_sub is None:
data['partial_scores'][name] = {'score': 0, 'weight': weight}
return
# If submitted answer is in a format generated by pl.to_json, convert it
# back to a standard type (otherwise, do nothing)
a_sub = pl.from_json(a_sub)
# Cast both submitted and true answers as np.float64, because...
#
# If the method of comparison is relabs (i.e., using relative and
# absolute tolerance) then np.allclose is applied to check if the
# submitted and true answers are the same. If either answer is an
# integer outside the range of int64...
#
# https://docs.scipy.org/doc/numpy-1.13.0/user/basics.types.html
#
# ...then numpy throws this error:
#
# TypeError: ufunc 'isfinite' not supported for the input types, and
# the inputs could not be safely coerced to any supported types
# according to the casting rule ''safe''
#
# Casting as np.float64 avoids this error. This is reasonable in any case,
# because <pl-number-input> accepts double-precision floats, not ints.
#
if np.iscomplexobj(a_sub) or np.iscomplexobj(a_tru):
a_sub = np.complex128(a_sub)
a_tru = np.complex128(a_tru)
else:
a_sub = np.float64(a_sub)
a_tru = np.float64(a_tru)
# Get method of comparison, with relabs as default
comparison = pl.get_string_attrib(element, 'comparison',
COMPARISON_DEFAULT)
# Compare submitted answer with true answer
if comparison == 'relabs':
rtol = pl.get_float_attrib(element, 'rtol', RTOL_DEFAULT)
atol = pl.get_float_attrib(element, 'atol', ATOL_DEFAULT)
correct = pl.is_correct_scalar_ra(a_sub, a_tru, rtol, atol)
elif comparison == 'sigfig':
digits = pl.get_integer_attrib(element, 'digits', DIGITS_DEFAULT)
correct = pl.is_correct_scalar_sf(a_sub, a_tru, digits)
elif comparison == 'decdig':
digits = pl.get_integer_attrib(element, 'digits', DIGITS_DEFAULT)
correct = pl.is_correct_scalar_dd(a_sub, a_tru, digits)
else:
raise ValueError('method of comparison "%s" is not valid' % comparison)
if correct:
data['partial_scores'][name] = {'score': 1, 'weight': weight}
else:
data['partial_scores'][name] = {'score': 0, 'weight': weight}
def grade(element_html, data):
element = lxml.html.fragment_fromstring(element_html)
name = pl.get_string_attrib(element, 'answers-name')
allow_partial_credit = pl.get_boolean_attrib(element,
'allow-partial-credit', False)
# Get weight
weight = pl.get_integer_attrib(element, 'weight', 1)
# Get method of comparison, with relabs as default
comparison = pl.get_string_attrib(element, 'comparison', 'relabs')
if comparison == 'relabs':
rtol = pl.get_float_attrib(element, 'rtol', 1e-2)
atol = pl.get_float_attrib(element, 'atol', 1e-8)
elif comparison == 'sigfig':
digits = pl.get_integer_attrib(element, 'digits', 2)
elif comparison == 'decdig':
digits = pl.get_integer_attrib(element, 'digits', 2)
else:
raise ValueError('method of comparison "%s" is not valid' % comparison)
# Get true answer (if it does not exist, create no grade - leave it
# up to the question code)
a_tru = pl.from_json(data['correct_answers'].get(name, None))
if a_tru is None:
return
# Wrap true answer in ndarray (if it already is one, this does nothing)
a_tru = np.array(a_tru)
# Throw an error if true answer is not a 2D numpy array
if a_tru.ndim != 2:
raise ValueError('true answer must be a 2D array')
else:
m, n = np.shape(a_tru)
number_of_correct = 0
feedback = {}
for i in range(m):
for j in range(n):
each_entry_name = name + str(n * i + j + 1)
a_sub = data['submitted_answers'].get(each_entry_name, None)
# Get submitted answer (if it does not exist, score is zero)
if a_sub is None:
data['partial_scores'][name] = {'score': 0, 'weight': weight}
return
# If submitted answer is in a format generated by pl.to_json, convert it
# back to a standard type (otherwise, do nothing)
a_sub = pl.from_json(a_sub)
# Compare submitted answer with true answer
if comparison == 'relabs':
correct = pl.is_correct_scalar_ra(a_sub, a_tru[i, j], rtol,
atol)
elif comparison == 'sigfig':
correct = pl.is_correct_scalar_sf(a_sub, a_tru[i, j], digits)
elif comparison == 'decdig':
correct = pl.is_correct_scalar_dd(a_sub, a_tru[i, j], digits)
if correct:
number_of_correct += 1
feedback.update({each_entry_name: 'correct'})
else:
feedback.update({each_entry_name: 'incorrect'})
if number_of_correct == m * n:
data['partial_scores'][name] = {'score': 1, 'weight': weight}
else:
if not allow_partial_credit:
score_value = 0
else:
score_value = number_of_correct / (m * n)
data['partial_scores'][name] = {
'score': score_value,
'weight': weight,
'feedback': feedback
}
def grade(element_html, data):
element = lxml.html.fragment_fromstring(element_html)
name = pl.get_string_attrib(element, 'answers-name')
allow_partial_credit = pl.get_boolean_attrib(element, 'allow-partial-credit', False)
# Get weight
weight = pl.get_integer_attrib(element, 'weight', 1)
# Get method of comparison, with relabs as default
comparison = pl.get_string_attrib(element, 'comparison', 'relabs')
if comparison == 'relabs':
rtol = pl.get_float_attrib(element, 'rtol', 1e-2)
atol = pl.get_float_attrib(element, 'atol', 1e-8)
elif comparison == 'sigfig':
digits = pl.get_integer_attrib(element, 'digits', 2)
elif comparison == 'decdig':
digits = pl.get_integer_attrib(element, 'digits', 2)
else:
raise ValueError('method of comparison "%s" is not valid' % comparison)
# Get true answer (if it does not exist, create no grade - leave it
# up to the question code)
a_tru = pl.from_json(data['correct_answers'].get(name, None))
if a_tru is None:
return
# Wrap true answer in ndarray (if it already is one, this does nothing)
a_tru = np.array(a_tru)
# Throw an error if true answer is not a 2D numpy array
if a_tru.ndim != 2:
raise ValueError('true answer must be a 2D array')
else:
m, n = np.shape(a_tru)
number_of_correct = 0
feedback = {}
for i in range(m):
for j in range(n):
each_entry_name = name + str(n * i + j + 1)
a_sub = data['submitted_answers'].get(each_entry_name, None)
# Get submitted answer (if it does not exist, score is zero)
if a_sub is None:
data['partial_scores'][name] = {'score': 0, 'weight': weight}
return
# If submitted answer is in a format generated by pl.to_json, convert it
# back to a standard type (otherwise, do nothing)
a_sub = pl.from_json(a_sub)
# Compare submitted answer with true answer
if comparison == 'relabs':
correct = pl.is_correct_scalar_ra(a_sub, a_tru[i, j], rtol, atol)
elif comparison == 'sigfig':
correct = pl.is_correct_scalar_sf(a_sub, a_tru[i, j], digits)
elif comparison == 'decdig':
correct = pl.is_correct_scalar_dd(a_sub, a_tru[i, j], digits)
if correct:
number_of_correct += 1
feedback.update({each_entry_name: 'correct'})
else:
feedback.update({each_entry_name: 'incorrect'})
if number_of_correct == m * n:
data['partial_scores'][name] = {'score': 1, 'weight': weight}
else:
if not allow_partial_credit:
score_value = 0
else:
score_value = number_of_correct / (m * n)
data['partial_scores'][name] = {'score': score_value, 'weight': weight, 'feedback': feedback}
