def html_table(row_inp,iter):
logger.info("iteration: " + str(iter))
dose_response.append(float(row_inp[0]))
LC50.append(float(row_inp[1]))
threshold.append(float(row_inp[2]))
Input_header="""<div class="out_">
<br><H3>Batch Calculation of Iteration %s</H3>
</div>"""%(iter)
iec_obj_temp = iec_model.iec(True,True, 'batch',dose_response[iter-1],LC50[iter-1],threshold[iter-1])
iec_obj_temp.loop_indx = str(iter)
z_score_f_out.append(iec_obj_temp.z_score_f_out)
F8_f_out.append(iec_obj_temp.F8_f_out)
chance_f_out.append(iec_obj_temp.chance_f_out)
#html = iec_tables.table_all(iec_obj)
jid_all.append(iec_obj_temp.jid)
iec_obj_all.append(iec_obj_temp)
if iter == 1:
jid_batch.append(iec_obj_temp.jid)
table_all_out = iec_tables.table_all(iec_obj_temp)
html_table_temp = Input_header + table_all_out + "<br>"
return html_table_temp
def post(self):
form = cgi.FieldStorage()
LC50 = float(form.getvalue('LC50'))
threshold = float(form.getvalue('threshold'))
dose_response = float(form.getvalue('dose_response'))
iec_obj = iec_model.iec(dose_response, LC50, threshold)
text_file = open('iec/iec_description.txt','r')
x1 = text_file.read()
templatepath = os.path.dirname(__file__) + '/../templates/'
html = template.render(templatepath + '01uberheader.html', {'title':'Ubertool'})
html = html + template.render(templatepath + '02uberintroblock_wmodellinks.html', {'model':'iec','page':'output'})
html = html + template.render (templatepath + '03ubertext_links_left.html', {})
html = html + template.render(templatepath + '04uberoutput_start.html', {
'model':'iec',
'model_attributes':'IEC Output'})
html = html + iec_tables.table_all(iec_obj)
html = html + template.render(templatepath + 'export.html', {})
html = html + template.render(templatepath + '04uberoutput_end.html', {})
html = html + template.render(templatepath + '06uberfooter.html', {'links': ''})
self.response.out.write(html)
def post(self):
form = cgi.FieldStorage()
LC50 = float(form.getvalue('LC50'))
threshold = float(form.getvalue('threshold'))
dose_response = float(form.getvalue('dose_response'))
iec_obj = iec_model.iec(True,True,'single',dose_response, LC50, threshold, None)
text_file = open('iec/iec_description.txt','r')
x1 = text_file.read()
templatepath = os.path.dirname(__file__) + '/../templates/'
ChkCookie = self.request.cookies.get("ubercookie")
html = uber_lib.SkinChk(ChkCookie, "IEC Output")
html = html + template.render(templatepath + '02uberintroblock_wmodellinks.html', {'model':'iec','page':'output'})
html = html + template.render (templatepath + '03ubertext_links_left.html', {})
html = html + template.render(templatepath + '04uberoutput_start.html', {
'model':'iec',
'model_attributes':'IEC Output'})
html = html + iec_tables.timestamp(iec_obj)
html = html + iec_tables.table_all(iec_obj)
html = html + template.render(templatepath + 'export.html', {})
html = html + template.render(templatepath + '04uberoutput_end.html', {})
html = html + template.render(templatepath + '06uberfooter.html', {'links': ''})
rest_funcs.save_dic(html, iec_obj.__dict__, "iec", "single")
self.response.out.write(html)
def post(self):
form = cgi.FieldStorage()
NOI = int(form.getvalue('NOI'))
LC50 = form.getvalue('LC50')
if LC50=="Uniform":
LC50_lower=float(form.getvalue('LC50_lower'))
LC50_upper=float(form.getvalue('LC50_upper'))
LC50_pool=np.random.uniform(LC50_lower, LC50_upper, NOI)
elif LC50=="Normal":
LC50_mean=float(form.getvalue('LC50_mean'))
LC50_std=float(form.getvalue('LC50_std'))
LC50_pool=np.random.normal(LC50_mean, LC50_std, NOI)
elif LC50=="Log-normal":
LC50_mean=float(form.getvalue('LC50_mean'))
LC50_std=float(form.getvalue('LC50_std'))
LC50_pool=np.random.lognormal(LC50_mean, LC50_std, NOI)
threshold = form.getvalue('threshold')
if threshold=="Uniform":
threshold_lower=float(form.getvalue('threshold_lower'))
threshold_upper=float(form.getvalue('threshold_upper'))
threshold_pool=np.random.uniform(threshold_lower, threshold_upper, NOI)
elif threshold=="Normal":
threshold_mean=float(form.getvalue('threshold_mean'))
threshold_std=float(form.getvalue('threshold_std'))
threshold_pool=np.random.normal(threshold_mean, threshold_std, NOI)
elif threshold=="Log-normal":
threshold_mean=float(form.getvalue('threshold_mean'))
threshold_std=float(form.getvalue('threshold_std'))
threshold_pool=np.random.lognormal(threshold_mean, threshold_std, NOI)
dose_response = form.getvalue('dose_response')
if dose_response=="Uniform":
dose_response_lower=float(form.getvalue('dose_response_lower'))
dose_response_upper=float(form.getvalue('dose_response_upper'))
dose_response_pool=np.random.uniform(dose_response_lower, dose_response_upper, NOI)
elif dose_response=="Normal":
dose_response_mean=float(form.getvalue('dose_response_mean'))
dose_response_std=float(form.getvalue('dose_response_std'))
dose_response_pool=np.random.normal(dose_response_mean, dose_response_std, NOI)
elif dose_response=="Log-normal":
dose_response_mean=float(form.getvalue('dose_response_mean'))
dose_response_std=float(form.getvalue('dose_response_std'))
dose_response_pool=np.random.lognormal(dose_response_mean, dose_response_std, NOI)
z_score_f_pool=[]
F8_f_pool=[]
chance_f_pool=[]
for i in range(NOI):
iec_obj_temp = iec_model.iec(True, True, dose_response_pool[i], LC50_pool[i], threshold_pool[i])
z_score_f_pool.append(iec_obj_temp.z_score_f_out)
F8_f_pool.append(iec_obj_temp.F8_f_out)
chance_f_pool.append(iec_obj_temp.chance_f_out)
templatepath = os.path.dirname(__file__) + '/../templates/'
ChkCookie = self.request.cookies.get("ubercookie")
html = uber_lib.SkinChk(ChkCookie, "IEC Uncertainty Output")
html = html + template.render(templatepath + '02uberintroblock_wmodellinks.html', {'model':'iec','page':'output'})
html = html + template.render (templatepath + '03ubertext_links_left.html', {})
html = html + template.render(templatepath + '04uberoutput_start.html', {
'model':'iec',
'model_attributes':'IEC Uncertainty Output'})
html = html + iec_tables.timestamp()
html = html + iec_tables.table_all_un(LC50_pool, threshold_pool, dose_response_pool, z_score_f_pool, F8_f_pool, chance_f_pool)
num_bin_z_score = int(1+3.3*np.log10(len(z_score_f_pool)))
num_bin_chance_f = int(1+3.3*np.log10(len(chance_f_pool)))
html = html + '<div>'
html = html + hist_plot(z_score_f_pool, num_bin_z_score, 'Z Score', id_generator(), 1) + '<br>'
html = html + hist_plot(chance_f_pool, num_bin_chance_f, 'Chance F', id_generator(), 2) + '<br>'
html = html + '</div>'
html = html + template.render(templatepath + 'export.html', {})
html = html + template.render(templatepath + '04uberoutput_end.html', {})
html = html + template.render(templatepath + '06uberfooter.html', {'links': ''})
self.response.out.write(html)
out_fun_chance_f.append(self.iec_obj.chance_f_out)
testFailureMessage = "Test of function name: %s expected: %s != calculated: %s" % ("Chance_f",self.iec_obj.chance_f_out,fun)
self.assertEqual(round(fun,3),round(self.chance_f_out,3),testFailureMessage)
def suite(TestCaseName, **kwargs):
suite = unittest.TestSuite()
set_globals(**kwargs)
suite.addTest(unittest.makeSuite(TestCaseName))
stream = StringIO()
runner = unittest.TextTestRunner(stream=stream, verbosity=2)
result = runner.run(suite)
stream.seek(0)
test_out=stream.read()
return test_out
iec_obj = iec_model.iec(True,True,dose_response[0],LC50[0],threshold[0])
iec_obj.set_unit_testing_variables()
iec_obj.z_score_f_out_expected = z_score_f_out[0]
iec_obj.F8_f_out_expected = F8_f_out[0]
iec_obj.chance_f_out_expected = chance_f_out[0]
test_suite_z_score_f_out = suite(TestCase_z_score_f_out, iec_obj=iec_obj)
test_suite_F8_f_out = suite(TestCase_F8_f_out, iec_obj=iec_obj)
test_suite_chance_f_out = suite(TestCase_chance_f_out, iec_obj=iec_obj)
class IecQaqcPage(webapp.RequestHandler):
def get(self):
text_file1 = open('iec/iec_description.txt','r')
x = text_file1.read()
