def agdriftOutputPage(request):
import agdrift_model
drop_size = request.POST.get('drop_size')
ecosystem_type = request.POST.get('ecosystem_type')
application_method = request.POST.get('application_method')
boom_height = request.POST.get('boom_height')
orchard_type = request.POST.get('orchard_type')
application_rate = request.POST.get('application_rate')
aquatic_type = request.POST.get('aquatic_type')
distance = request.POST.get('distance')
calculation_input = request.POST.get('calculation_input')
agdrift_obj = agdrift_model.agdrift(True, True, 'single', drop_size, ecosystem_type, application_method, boom_height, orchard_type, application_rate, distance, aquatic_type, calculation_input, None)
return agdrift_obj
def html_table(row,iter):
drop_size.append(str(row[0]))
ecosystem_type.append(str(row[1]))
application_method.append(str(row[2]))
boom_height.append(str(row[3]))
orchard_type.append(str(row[4]))
application_rate.append(float(row[5]))
distance.append(float(row[6]))
aquatic_type.append(str(row[7]))
calculation_input.append(str(row[8]))
Input_header="""<div class="out_">
<br><H3>Batch Calculation of Iteration {0!s}</H3>
</div>""".format((iter))
agdrift_obj_temp = agdrift_model.agdrift(True,True,'batch',drop_size[iter-1],ecosystem_type[iter-1], application_method[iter-1],boom_height[iter-1],orchard_type[iter-1],application_rate[iter-1],distance[iter-1],aquatic_type[iter-1],calculation_input[iter-1],)
agdrift_obj_temp.loop_indx = str(iter)
init_avg_dep_foa_out.append(agdrift_obj_temp.init_avg_dep_foa)
avg_depo_lbac_out.append(agdrift_obj_temp.avg_depo_lbac)
avg_depo_gha_out.append(agdrift_obj_temp.avg_depo_gha)
deposition_ngL_out.append(agdrift_obj_temp.deposition_ngL)
deposition_mgcm_out.append(agdrift_obj_temp.deposition_mgcm)
nasae_out.append(agdrift_obj_temp.nasae)
y_out.append(agdrift_obj_temp.y)
x_out.append(agdrift_obj_temp.x)
express_y_out.append(agdrift_obj_temp.express_y)
jid_all.append(agdrift_obj_temp.jid)
agdrift_obj_all.append(agdrift_obj_temp)
if iter == 1:
jid_batch.append(agdrift_obj_temp.jid)
table_all_out = agdrift_tables.table_all(agdrift_obj_temp)
html_table_temp = Input_header + table_all_out + "<br>"
return html_table_temp
def html_table(row,iter):
drop_size.append(str(row[0]))
ecosystem_type.append(str(row[1]))
application_method.append(str(row[2]))
boom_height.append(str(row[3]))
orchard_type.append(str(row[4]))
application_rate.append(float(row[5]))
distance.append(float(row[6]))
aquatic_type.append(str(row[7]))
calculation_input.append(str(row[8]))
Input_header="""<div class="out_">
<br><H3>Batch Calculation of Iteration %s</H3>
</div>"""%(iter)
agdrift_obj_temp = agdrift_model.agdrift(True,True,'batch',drop_size[iter-1],ecosystem_type[iter-1], application_method[iter-1],boom_height[iter-1],orchard_type[iter-1],application_rate[iter-1],distance[iter-1],aquatic_type[iter-1],calculation_input[iter-1],)
agdrift_obj_temp.loop_indx = str(iter)
init_avg_dep_foa_out.append(agdrift_obj_temp.init_avg_dep_foa)
avg_depo_lbac_out.append(agdrift_obj_temp.avg_depo_lbac)
avg_depo_gha_out.append(agdrift_obj_temp.avg_depo_gha)
deposition_ngL_out.append(agdrift_obj_temp.deposition_ngL)
deposition_mgcm_out.append(agdrift_obj_temp.deposition_mgcm)
nasae_out.append(agdrift_obj_temp.nasae)
y_out.append(agdrift_obj_temp.y)
x_out.append(agdrift_obj_temp.x)
express_y_out.append(agdrift_obj_temp.express_y)
jid_all.append(agdrift_obj_temp.jid)
agdrift_obj_all.append(agdrift_obj_temp)
if iter == 1:
jid_batch.append(agdrift_obj_temp.jid)
table_all_out = agdrift_tables.table_all(agdrift_obj_temp)
html_table_temp = Input_header + table_all_out + "<br>"
return html_table_temp
import agdrift_model
import os
import unittest
from StringIO import StringIO
import csv
# agdrift_obj = agdrift_model.agdrift(True, True, 'single', drop_size, ecosystem_type, application_method, boom_height, orchard_type, application_rate, distance, aquatic_type, calculation_input, None)
agdrift_obj = agdrift_model.agdrift(True, True, 'qaqc', "Fine", "EPA Pond",
"Aerial", "", "", "0.5", "225", "1", "0.5",
None)
import agdrift_model import os import unittest from StringIO import StringIO import csv # agdrift_obj = agdrift_model.agdrift(True, True, 'single', drop_size, ecosystem_type, application_method, boom_height, orchard_type, application_rate, distance, aquatic_type, calculation_input, None) agdrift_obj = agdrift_model.agdrift(True, True, 'qaqc', "Fine", "EPA Pond", "Aerial", "", "", "0.5", "225", "1", "0.5", None)