def getDataMacroRegion():
"""
Retorna um dictionary com todas as micro-regioes
function() -> dictionary
"""
# from scipy.spatial.distance import euclidean
dic = {}
lista = MongoDB.list_all_macro_regions()
for i in lista:
d = {}
if i['region'] not in dic:
dic[i['region']] = {}
for j in lista:
if i['region'] != j['region']:
# d[j['region']] = float("{0:.4f}".format(euclidean( [i['lng'], i['lat']], [ j['lng'], j['lat'] ])))
d[j['region']] = float("{0:.3f}".format(haversine(i['lng'], i['lat'], j['lng'], j['lat'] )))
dic[i['region']] = d
lista = MongoDB.list_all_macro_regions()
for i in lista:
dic[i['region']]['Price/m²'] = float("{0:.2f}".format(i['price_by_meter']))
dic[i['region']]['Residents'] = int(i['residents'])
dic[i['region']]['Occupied Private Housing'] = int(i['occupied_private_housing'])
dic[i['region']]['Residents Per Household'] = float("{0:.2f}".format(i['residents_per_household']))
dic[i['region']]['Hospital'] = int(i['hospital'])
dic[i['region']]['UBS'] = int(i['ubs'])
dic[i['region']]['UPA'] = int(i['upa'])
dic[i['region']]['University'] = int(i['university'])
dic[i['region']]['Bank'] = int(i['bank'])
dic[i['region']]['Shopping'] = int(i['shopping'])
dic[i['region']]['Delegacy'] = int(i['delegacy'])
dic[i['region']]['Market'] = int(i['market'])
dic[i['region']]['School'] = int(i['school'])
return dict(sorted(dic.items()))
def listAllMacroRegions(): """ Retorna todas as micro-regiões consolidadas function() -> list """ lista = MongoDB.list_all_macro_regions() return lista
def listTableMoreInputs():
"""
Retorna a tabela com dos dados que serão escolhidos para compor a sulção de analise regressiva
function() -> list, matrix (list of lists)
"""
l = MongoDB.list_all_macro_regions()
regions = {}
for i in l:
if i['region'] not in regions:
regions[i['region']] = {}
for k,v in sorted(i.items()):
if k not in [ '_id', 'lat', 'lng', 'qtd', 'type', 'region']:
regions[i['region']][k] = v
regionsList = []
isFirstLine = True
matrix = {}
for r, values in sorted(regions.items()):
regionsList.append(r)
for k,v in sorted(values.items()):
if k not in matrix:
matrix[k] = []
if k == 'price_by_meter':
matrix[k].append(float("{0:.2f}".format(v)))
else:
matrix[k].append(v)
return regionsList, matrix
