def get_fev1fvc(sentence):
fev1fvc_list = []
# Running a loop on the range in which fev1/fvc value could be found.
# Includes ratios both exprecessed as percent and decimal, > 100% is for predicted values
for x,y in [(0,2),(10,180)]:
fev1_fvc = ve.run("fev1/fvc", sentence, x, y)
if json.loads(fev1_fvc)['querySuccess']:
for i in range(json.loads(fev1_fvc)['measurementCount']):
fev1fvc_dict = {}
fev1fvc_dict['type'] = "fev1_fvc_ratio"
fev1fvc_dict['text'] = json.loads(fev1_fvc)['measurementList'][i]['text']
fev1fvc_dict['condition'] = json.loads(fev1_fvc)['measurementList'][i]['condition']
fev1fvc_dict['x'] = json.loads(fev1_fvc)['measurementList'][i]['x']
fev1fvc_dict['y'] = json.loads(fev1_fvc)['measurementList'][i]['y']
clean_text = json.loads(fev1_fvc)['measurementList'][i]['text'].replace(')','').replace('(','')
sentence = sentence.replace(')','').replace('(','')
fev1_fvc_units = re.findall(clean_text+r'\s?(%)?',sentence)[0]
if fev1_fvc_units == '%':
fev1_fvc_units = re.findall(clean_text+r'\s?(% ?pred|% ?of ?pred| ?%)',sentence)[0]
if fev1_fvc_units == '':
fev1_fvc_units = ve.EMPTY_FIELD
fev1fvc_dict['units'] = fev1_fvc_units
fev1fvc_list.append(fev1fvc_dict)
else:
None
return fev1fvc_list
def get_fev1(sentence):
fev1_list = []
# Includes values in ml, l and % predicted
for x,y in [(0,6),(20,190),(300,6000)]:
fev1 = ve.run("fev1", sentence, x, y)
if json.loads(fev1)['querySuccess']:
for i in range(json.loads(fev1)['measurementCount']):
fev1_dict = {}
fev1_dict['type'] = "fev1"
fev1_dict['text'] = json.loads(fev1)['measurementList'][i]['text']
fev1_dict['condition'] = json.loads(fev1)['measurementList'][i]['condition']
fev1_dict['x'] = json.loads(fev1)['measurementList'][i]['x']
fev1_dict['y'] = json.loads(fev1)['measurementList'][i]['y']
clean_text = json.loads(fev1)['measurementList'][i]['text'].replace(')','').replace('(','')
sentence = sentence.replace(')','').replace('(','')
fev1_units = re.findall( clean_text +r'\s?(ml|cc|l|L|ML|CC|%)?',sentence)[0]
if fev1_units == '%':
fev1_units = re.findall( clean_text +r'\s?(% ?predicted|% ?of ?predicted|% ?pred|% ?of ?pred| ?%)',sentence)[0]
if fev1_units == '':
fev1_units = ve.EMPTY_FIELD
fev1_dict['units'] = fev1_units
fev1_list.append(fev1_dict)
else:
None
return fev1_list
def _compare_results(term_string,
test_data,
minval,
maxval,
enumlist=None,
is_case_sensitive=False,
denom_only=False,
values_before_terms=False):
"""
Run the value extractor on the test data using the supplied term string
and check the results.
"""
for sentence, expected_list in test_data.items():
# run value extractor on the next test sentence
json_result = ve.run(term_string,
sentence,
minval,
maxval,
str_enumlist=enumlist,
is_case_sensitive=is_case_sensitive,
is_denom_only=denom_only,
values_before_terms=values_before_terms)
num_expected = len(expected_list)
is_mismatched = False
if 0 == num_expected and ve.EMPTY_RESULT == json_result:
# expected not to find anything and actually did not
continue
elif num_expected > 0 and ve.EMPTY_RESULT == json_result:
is_mismatched = True
value_result = None
if not is_mismatched:
# load the json result and decode as a ValueResult namedtuple
result_data = json.loads(json_result)
value_result = ve.ValueResult(**result_data)
# check that len(computed) == len(expected)
if is_mismatched or (value_result.measurementCount != num_expected):
print('\tMismatch in computed vs. expected results: ')
print('\tSentence: {0}'.format(sentence))
print('\tComputed: ')
if value_result is None:
print('\t\tNone')
else:
for m in value_result.measurementList:
print('\t\t{0}'.format(m))
print('\tExpected: ')
for e in expected_list:
print('\t\t{0}'.format(e))
return False
# check fields
failures = []
for i, value in enumerate(value_result.measurementList):
computed = value['matchingTerm']
expected = expected_list[i].term
failures = _compare_fields('matching term', computed, expected,
failures)
computed = value['x']
expected = expected_list[i].x
failures = _compare_fields('x', computed, expected, failures)
computed = value['y']
expected = expected_list[i].y
failures = _compare_fields('y', computed, expected, failures)
computed = value['condition']
expected = expected_list[i].condition
failures = _compare_fields('condition', computed, expected,
failures)
if len(failures) > 0:
print(sentence)
for f in failures:
print(f)
return False
return True