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
# Convert true answer to numpy
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')
# 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
# Convert submitted answer to numpy
a_sub = np.array(a_sub)
# If true and submitted answers have different shapes, score is zero
if not (a_sub.shape == a_tru.shape):
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_ndarray2D_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_ndarray2D_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_ndarray2D_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
# 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')
# 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)
# Wrap submitted answer in an ndarray (if it's already one, this does nothing)
a_sub = np.array(a_sub)
# If true and submitted answers have different shapes, score is zero
if not (a_sub.shape == a_tru.shape):
data['partial_scores'][name] = {'score': 0, 'weight': weight}
return
# 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_ndarray2D_ra(a_sub, a_tru, rtol, atol)
elif comparison == 'sigfig':
digits = pl.get_integer_attrib(element, 'digits', DIGITS_DEFAULT)
correct = pl.is_correct_ndarray2D_sf(a_sub, a_tru, digits)
elif comparison == 'decdig':
digits = pl.get_integer_attrib(element, 'digits', DIGITS_DEFAULT)
correct = pl.is_correct_ndarray2D_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')
# 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 = 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')
# 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)
# Wrap submitted answer in an ndarray (if it's already one, this does nothing)
a_sub = np.array(a_sub)
# If true and submitted answers have different shapes, score is zero
if not (a_sub.shape == a_tru.shape):
data['partial_scores'][name] = {'score': 0, 'weight': weight}
return
# 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-2)
atol = pl.get_float_attrib(element, 'atol', 1e-8)
correct = pl.is_correct_ndarray2D_ra(a_sub, a_tru, rtol, atol)
elif comparison == 'sigfig':
digits = pl.get_integer_attrib(element, 'digits', 2)
correct = pl.is_correct_ndarray2D_sf(a_sub, a_tru, digits)
elif comparison == 'decdig':
digits = pl.get_integer_attrib(element, 'digits', 2)
correct = pl.is_correct_ndarray2D_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}