def examsOutputPage(request):
import exams_model
chem_name = request.POST.get('chemical_name')
scenarios =request.POST.get('scenarios')
farm =request.POST.get('farm_pond')
mw = request.POST.get('molecular_weight')
sol = request.POST.get('solubility')
koc = request.POST.get('Koc')
vp = request.POST.get('vapor_pressure')
aem = request.POST.get('aerobic_aquatic_metabolism')
anm = request.POST.get('anaerobic_aquatic_metabolism')
aqp = request.POST.get('aquatic_direct_photolysis')
tmper = request.POST.get('temperature')
n_ph = float(request.POST.get('n_ph'))
ph_out = []
hl_out = []
for i in range(int(n_ph)):
j=i+1
ph_temp = request.POST.get('ph'+str(j))
ph_out.append(float(ph_temp))
hl_temp = float(request.POST.get('hl'+str(j)))
hl_out.append(hl_temp)
exams_obj = exams_model.exams(chem_name, scenarios, farm, mw, sol, koc, vp, aem, anm, aqp, tmper, n_ph, ph_out, hl_out)
return exams_obj
import subprocess
import numpy as np
from scipy.optimize import leastsq
import zipfile
from boto.s3.connection import S3Connection
from boto.s3.key import Key
from boto.s3.bucket import Bucket
import string
import random
import operator
import re
# from ubertool_src import keys_Picloud_S3
import keys_Picloud_S3
exams_obj = exams_model.exams('chem_name_1', 'CA Almonds MLRA-17', 'Yes', 70,
71, 72, 73, 24, 25, 26, 27, 3, [5.0, 7.0, 11.0],
[11.0, 12.0, 10.0])
def exams_pi(exams_obj):
# Generate a random ID for file save
def id_generator(size=6, chars=string.ascii_uppercase + string.digits):
return ''.join(random.choice(chars) for x in range(size))
name_temp = id_generator()
##################################################################################
######Create a folder if it does not existed, where holds calculations' output.#####
##################################################################################
cwd = os.getcwd() + '/exams_test'
print("cwd=" + cwd)
import subprocess
import numpy as np
from scipy.optimize import leastsq
import zipfile
from boto.s3.connection import S3Connection
from boto.s3.key import Key
from boto.s3.bucket import Bucket
import string
import random
import operator
import re
# from ubertool_src import keys_Picloud_S3
import keys_Picloud_S3
exams_obj = exams_model.exams('chem_name_1', 'CA Almonds MLRA-17', 'Yes', 70,
71, 72, 73, 24, 25, 26, 27, 3, [5.0, 7.0, 11.0],
[11.0, 12.0, 10.0])
def exams_pi(exams_obj):
# Generate a random ID for file save
def id_generator(size=6, chars=string.ascii_uppercase + string.digits):
return ''.join(random.choice(chars) for x in range(size))
name_temp = id_generator()
##################################################################################
######Create a folder if it does not existed, where holds calculations' output.#####
##################################################################################
cwd = os.getcwd() + '/exams_test'
print("cwd=" + cwd)
