def adoption_rate(geog, id, to_date, partners):
if not to_date:
to_date = datetime.date.today()
adopt_rate_data = run_query(shared_sql.adoption_rate_totals(geog, id, to_date, partners))[0]
if(adopt_rate_data and adopt_rate_data['tot_per']):
return (adopt_rate_data['tot_adopt_per']*100)/adopt_rate_data['tot_per']
else:
return 0
def adoption_rate(geog, id, to_date, partners):
if not to_date:
to_date = datetime.date.today()
adopt_rate_data = run_query(shared_sql.adoption_rate_totals(geog, id, to_date, partners))[0]
if(adopt_rate_data and adopt_rate_data['tot_per']):
return (adopt_rate_data['tot_adopt_per']*100)/adopt_rate_data['tot_per']
else:
return 0
def adoption_module(request):
geog, id = get_geog_id(request)
from_date, to_date, partners = get_dates_partners(request)
geog_list = [None,'COUNTRY','STATE','DISTRICT','BLOCK','VILLAGE']
if(geog not in geog_list):
raise Http404()
totals = run_query(shared_sql.get_totals(geog, id, from_date, to_date, partners, values_to_fetch=['tot_att', 'tot_ado', 'tot_scr']))[0]
#total adoptions, total distinct practice adopted, distinct farmer adopting
main_stats = run_query(adoption_analytics_sql.adoption_tot_ado(geog, id, from_date, to_date, partners))[0]
main_stats['tot_ado'] = totals['tot_ado'] if totals['tot_ado'] is not None else 0
#Adoption rate
date_var = to_date if to_date else str(datetime.date.today())
adopt_rate_data = run_query(shared_sql.adoption_rate_totals(geog, id, date_var, partners))[0]
if(adopt_rate_data and adopt_rate_data['tot_per']):
main_stats.update(adopt_rate = (adopt_rate_data['tot_adopt_per']*100)/adopt_rate_data['tot_per'])
main_stats.update(avg_ado_per_farmer = adopt_rate_data['tot_active_adop'] / adopt_rate_data['tot_per'])
else:
main_stats.update(adopt_rate = 0)
main_stats.update(avg_ado_per_farmer = 0)
#Probability of Adoption
if(totals['tot_att'] and main_stats['tot_ado']):
main_stats.update(adopt_prob = float(main_stats['tot_ado'])/float(totals['tot_att']) * 100)
else:
main_stats.update(adopt_prob = 0)
#Number of practices repeated adopted by same farmer
repeat_pract_per = run_query_raw(adoption_analytics_sql.adoption_repeat_adoption_practice_count(geog, id, from_date, to_date, partners))
if repeat_pract_per != None and main_stats['tot_farmers']:
main_stats.update(repeat_pract = float(repeat_pract_per[0][0] * 100)/main_stats['tot_farmers'])
else:
main_stats.update(repeat_pract = 0)
#Avg adoption per Video
tot_vids_seen = run_query(video_analytics_sql.video_tot_scr(geog=geog,id=id,from_date=from_date,to_date=to_date,partners=partners))[0]['count']
if tot_vids_seen and main_stats['tot_ado']:
main_stats.update(avg_ado_per_vid = float(main_stats['tot_ado']) / tot_vids_seen)
else:
main_stats.update(avg_ado_per_vid = 0)
#Avg adoption per Screening
if(totals['tot_scr'] and main_stats['tot_ado']):
main_stats.update(avg_ado_per_scr = float(main_stats['tot_ado']) / float(totals['tot_scr']))
else:
main_stats.update(avg_ado_per_scr = 0)
search_box_params = views.common.get_search_box(request)
get_req_url = request.META['QUERY_STRING']
get_req_url = '&'.join([i for i in get_req_url.split('&') if i[:4]!='geog' and i[:2]!='id'])
return render_to_response('adoption_module.html', dict(search_box_params = search_box_params,
get_req_url = get_req_url,
**main_stats
))
def adoption_module(request):
geog, id = get_geog_id(request)
from_date, to_date, partners = get_dates_partners(request)
geog_list = [None,'COUNTRY','STATE','DISTRICT','BLOCK','VILLAGE']
if(geog not in geog_list):
raise Http404()
totals = run_query(shared_sql.get_totals(geog, id, from_date, to_date, partners, values_to_fetch=['tot_att', 'tot_ado', 'tot_scr']))[0]
#total adoptions, total distinct practice adopted, distinct farmer adopting
main_stats = run_query(adoption_analytics_sql.adoption_tot_ado(geog, id, from_date, to_date, partners))[0]
main_stats['tot_ado'] = totals['tot_ado'] if totals['tot_ado'] is not None else 0
#Adoption rate
date_var = to_date if to_date else (datetime.datetime.utcnow() - datetime.timedelta(1)).strftime('%Y-%m-%d')
adopt_rate_data = run_query(shared_sql.adoption_rate_totals(geog, id, date_var, partners))[0]
if(adopt_rate_data and adopt_rate_data['tot_per']):
main_stats.update(adopt_rate = (adopt_rate_data['tot_adopt_per']*100)/adopt_rate_data['tot_per'])
main_stats.update(avg_ado_per_farmer = adopt_rate_data['tot_active_adop'] / adopt_rate_data['tot_per'])
else:
main_stats.update(adopt_rate = 0)
main_stats.update(avg_ado_per_farmer = 0)
#Probability of Adoption
if(totals['tot_att'] and main_stats['tot_ado']):
main_stats.update(adopt_prob = float(main_stats['tot_ado'])/float(totals['tot_att']) * 100)
else:
main_stats.update(adopt_prob = 0)
#Number of practices repeated adopted by same farmer
repeat_pract_per = run_query_raw(adoption_analytics_sql.adoption_repeat_adoption_practice_count(geog, id, from_date, to_date, partners))
if repeat_pract_per != None and main_stats['tot_farmers']:
main_stats.update(repeat_pract = float(repeat_pract_per[0][0] * 100)/main_stats['tot_farmers'])
else:
main_stats.update(repeat_pract = 0)
#Avg adoption per Video
tot_vids_seen = run_query(video_analytics_sql.video_tot_scr(geog=geog,id=id,from_date=from_date,to_date=to_date,partners=partners))[0]['count']
if tot_vids_seen and main_stats['tot_ado']:
main_stats.update(avg_ado_per_vid = float(main_stats['tot_ado']) / tot_vids_seen)
else:
main_stats.update(avg_ado_per_vid = 0)
#Avg adoption per Screening
if(totals['tot_scr'] and main_stats['tot_ado']):
main_stats.update(avg_ado_per_scr = float(main_stats['tot_ado']) / float(totals['tot_scr']))
else:
main_stats.update(avg_ado_per_scr = 0)
search_box_params = views.common.get_search_box(request)
get_req_url = request.META['QUERY_STRING']
get_req_url = '&'.join([i for i in get_req_url.split('&') if i[:4]!='geog' and i[:2]!='id'])
return render_to_response('adoption_module.html', dict(search_box_params = search_box_params,
get_req_url = get_req_url,
**main_stats
))
