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import json
import calculators
import unittest
import utils
import urllib
from bs4 import BeautifulSoup
# import ssl
import time
from gail.gail import GailRiskCalculator
class CalculatorsTestCase(unittest.TestCase):
def setUp(self):
self.app = calculators.app.test_client()
# No special tearDown?
# def tearDown(self):
def get_NCI(self,
genetics=0,
current_age=48,
age_at_menarche=2,
age_at_first_live_birth=3,
ever_had_biopsy=0,
previous_biopsies=0,
biopsy_with_hyperplasia=0,
related_with_breast_cancer=0,
race=0):
serviceurl = "http://www.cancer.gov/bcrisktool/RiskAssessment.aspx?"
scontext = None
cgvfiveyearRiskABS = -1.1
cgvfiveyearRiskAVE = -1.1
cgvLifetimeRiskABS = -1.1
cgvLifetimeRiskAVE = -1.1
explainer = ""
if age_at_menarche == 0:
age_at_menarche = 14
elif age_at_menarche == 1:
age_at_menarche = 13
elif age_at_menarche == 2:
age_at_menarche = 10
if age_at_first_live_birth == 3:
age_at_first_live_birth = 30
elif age_at_first_live_birth == 1:
age_at_first_live_birth = 22
elif age_at_first_live_birth == 0:
# encode once at 15
age_at_first_live_birth = 15
elif age_at_first_live_birth == 2:
# encode once at 27
age_at_first_live_birth = 27
url = serviceurl + urllib.urlencode(
{"genetics": genetics, "current_age": current_age, "age_at_menarche": age_at_menarche,
"age_at_first_live_birth": age_at_first_live_birth, "ever_had_biopsy": ever_had_biopsy,
"previous_biopsies": previous_biopsies, "biopsy_with_hyperplasia": biopsy_with_hyperplasia,
"related_with_breast_cancer": related_with_breast_cancer,
"race": race})
time.sleep(0.1) # delays for 1 seconds
myhtml = urllib.urlopen(url, context=scontext).read()
soup = BeautifulSoup(myhtml, "lxml")
tags = soup.find_all('p')
explainer = explainer + str(tags[7]) + str(tags[8])
tags = soup('span', {'id': 'ctl00_cphMain_lbl5YrAbsoluteRisk'})
for x in tags: cgvfiveyearRiskABS = (float(x.get_text()[:-1]) / 100)
tags = soup('span', {'id': 'ctl00_cphMain_lbl5YrAveragRisk'})
for x in tags: cgvfiveyearRiskAVE = (float(x.get_text()[:-1]) / 100)
tags = soup('span', {'id': 'ctl00_cphMain_lblLifetimeAbsoluteRisk90'})
for x in tags: cgvLifetimeRiskABS = (float(x.get_text()[:-1]) / 100)
tags = soup('span', {'id': 'ctl00_cphMain_lblLifeTimeAverageRisk90'})
for x in tags: cgvLifetimeRiskAVE = (float(x.get_text()[:-1]) / 100)
return (utils.roundLikeNCI(cgvfiveyearRiskABS),
utils.roundLikeNCI(cgvfiveyearRiskAVE),
utils.roundLikeNCI(cgvLifetimeRiskABS),
utils.roundLikeNCI(cgvLifetimeRiskAVE))
def test_bad_calc_name(self):
print "Testing Unknown Calculator Name (For v2.0)"
# test getting the docs for a bad calc
rv = self.app.get('/api/v2.0/bad_calc')
assert rv.status_code == 501
rv = self.app.get('/api/v2.0/bad_calc/json')
assert rv.status_code == 501
rv = self.app.post('/api/v2.0/bad_calc', data="[Doesn't matter]")
assert rv.status_code == 501
def test_gail_calc_doc(self):
print "Testing GAIL Doc URLs (For v2.0)"
rv = self.app.get('/api/v2.0/gail')
assert rv.status_code == 200
assert "VisExcell API For GAIL - version 2.0" in rv.get_data()
rv = self.app.get('/api/v2.0/gail/json')
assert rv.status_code == 200
assert rv.mimetype == "application/json"
def test_gail_calc_post(self):
print "Testing getting GAIL results for (v2.0)"
post_data = {
"age": 48,
"menarch_age": 2,
"live_birth_age": 3,
"ever_had_biopsy": 1,
"num_biopsy": 2,
"first_deg_relatives": 2,
"ihyp": 1,
"race": 1
}
expected_results = {
"five_year_abs": 0.10708078148151635,
"five_year_ave": 0.011606210299941746,
"lifetime_abs": 0.59497901225876715,
"lifetime_ave": 0.1148439582786286
}
rv = self.app.post('/api/v2.0/gail',data=json.dumps(post_data),content_type='application/json')
response_obj = json.loads(rv.get_data())
self.assertEqual(response_obj["code"],200)
self.assertEqual(len(response_obj["assessment"]["results"].keys()), 4)
for ex_result in expected_results:
self.assertEqual(response_obj["assessment"]["results"][ex_result],expected_results[ex_result])
# TODO: Add bad post data to check error responses
def test_unknown_biopsies(self):
print "Testing for unknown biopsy bug (using v1.0)"
post_data = {
"age": 40,
"menarch_age": 2,
"live_birth_age": 0,
"ever_had_biopsy": 0,
"num_biopsy": 0,
"first_deg_relatives": 0,
"ihyp": 99,
"race": 3
}
ever_had_vals = [0,99]
num_vals = [0,1,2]
hyp_vals = [0,1,99]
for nv in num_vals:
post_data["num_biopsy"] = nv
for ehv in ever_had_vals:
post_data["ever_had_biopsy"] = ehv
for hv in hyp_vals:
post_data["ihyp"] = hv
# print "-------"
# print post_data
rv = self.app.post('/api/v1.0/gail', data=json.dumps(post_data), content_type="application/json")
output = json.loads(rv.get_data())
fyr = utils.roundLikeNCI(output["results"]["five_year_abs"])
fyra = utils.roundLikeNCI(output["results"]["five_year_ave"])
ltr = utils.roundLikeNCI(output["results"]["lifetime_abs"])
ltra = utils.roundLikeNCI(output["results"]["lifetime_ave"])
# print "Ours:\t5yr: %.4f\t5ave: %.4f\tLTR: %.4f\tLTA: %.4f" % (fyr,fyra,ltr,ltra)
cleaned_ever_had, cleaned_number, cleaned_hyp = GailRiskCalculator.clean_biopsy_inputs(post_data["ever_had_biopsy"], post_data["num_biopsy"],post_data["ihyp"])
(nci_fyr,nci_fyra,nci_ltr,nci_ltra) = self.get_NCI(current_age=post_data["age"],
age_at_menarche=post_data["menarch_age"],
age_at_first_live_birth=post_data["live_birth_age"],
ever_had_biopsy=cleaned_ever_had, # post_data["ever_had_biopsy"],
previous_biopsies=cleaned_number, # post_data["num_biopsy"],
biopsy_with_hyperplasia=cleaned_hyp, # post_data["ihyp"],
related_with_breast_cancer=post_data["first_deg_relatives"],
race=post_data["race"])
# print "NCIs:\t5yr: %.4f\t5ave: %.4f\tLTR: %.4f\tLTA: %.4f" % (fyr, fyra, ltr, ltra)
self.assertEqual((fyr, fyra, ltr, ltra),(nci_fyr,nci_fyra,nci_ltr,nci_ltra), "Inputs: %r" % post_data)
def test_calculations_valid_inputs(self):
print "Testing for valid inputs (using v1.0)"
test_inputs = [{"age": 42, "menarch_age": 2, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 1},
{"age": 50, "menarch_age": 2, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 1},
{"age": 68, "menarch_age": 2, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 1},
{"age": 42, "menarch_age": 0, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 1, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 2, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 0, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 0, "live_birth_age": 1, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 0, "live_birth_age": 2, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 0, "live_birth_age": 3, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 0, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 0, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 1, "ihyp": 99, "race": 3},
{"age": 42, "menarch_age": 0, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 2, "ihyp": 99, "race": 3},]
races_to_test = [1,2,7,8,9,10,11,12] # (3 is tested in above)
for r in races_to_test:
test_inputs.append({"age": 42, "menarch_age": 2, "live_birth_age": 0, "ever_had_biopsy": 0, "num_biopsy": 0, "first_deg_relatives": 0, "ihyp": 99, "race": r})
for post_data in test_inputs:
# print post_data
rv = self.app.post('/api/v1.0/gail', data=json.dumps(post_data), content_type="application/json")
output = json.loads(rv.get_data())
fyr = utils.roundLikeNCI(output["results"]["five_year_abs"])
fyra = utils.roundLikeNCI(output["results"]["five_year_ave"])
ltr = utils.roundLikeNCI(output["results"]["lifetime_abs"])
ltra = utils.roundLikeNCI(output["results"]["lifetime_ave"])
(nci_fyr, nci_fyra, nci_ltr, nci_ltra) = self.get_NCI(current_age=post_data["age"],
age_at_menarche=post_data["menarch_age"],
age_at_first_live_birth=post_data["live_birth_age"],
ever_had_biopsy=post_data["ever_had_biopsy"],
previous_biopsies=post_data["num_biopsy"],
biopsy_with_hyperplasia=post_data["ihyp"],
related_with_breast_cancer=post_data[
"first_deg_relatives"],
race=post_data["race"])
self.assertEqual((fyr, fyra, ltr, ltra), (nci_fyr, nci_fyra, nci_ltr, nci_ltra), "Inputs: %r" % post_data)
if __name__ == '__main__':
unittest.main()