74 lines
1.9 KiB
Python
74 lines
1.9 KiB
Python
import numpy
|
|
|
|
from .models import DB
|
|
|
|
|
|
def getTemps(session):
|
|
model, scenario = session['datasets'].split(',')
|
|
data = DB.getTemps(session['minyear'],
|
|
session['maxyear'],
|
|
session['community_data']['id'],
|
|
model,
|
|
scenario)
|
|
return data
|
|
|
|
|
|
def avg_air_temp(temps):
|
|
year_counter, total = 0, 0
|
|
for temp in temps:
|
|
total += sum(temp[1])
|
|
year_counter += 1
|
|
return total / (year_counter * 12)
|
|
|
|
|
|
def ann_air_indices(temps):
|
|
ATI, AFI = 0.0, 0.0
|
|
# TODO: drop numpy
|
|
indices = numpy.zeros((len(temps), 2), dtype='int')
|
|
months = [0.0 for m in range(12)]
|
|
days = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
|
|
i = 0
|
|
for year in temps:
|
|
j = 0
|
|
for month in months:
|
|
months[j] = days[j] * year[1][j]
|
|
j += 1
|
|
|
|
for ind in months:
|
|
if ind >= 0.0:
|
|
ATI = ATI + ind
|
|
else:
|
|
AFI = AFI + ind
|
|
indices[i, 0], indices[i, 1] = int(ATI), int(AFI)
|
|
ATI, AFI = 0.0, 0.0
|
|
i += 1
|
|
return indices
|
|
|
|
|
|
def avg_air_indices(indices):
|
|
# TODO: drop numpy
|
|
temp = numpy.average(indices, axis=0)
|
|
return (int(temp[0]), int(temp[1]))
|
|
|
|
|
|
def des_air_indices(indices):
|
|
if indices.shape[0] > 2:
|
|
# TODO: drop numpy
|
|
ati = numpy.sort(indices[:, 0])
|
|
afi = numpy.sort(indices[:, 1])
|
|
dti = (ati[-1] + ati[-2] + ati[-3]) / 3.0
|
|
dfi = (afi[0] + afi[1] + afi[2]) / 3.0
|
|
return (int(dti), int(dfi))
|
|
else:
|
|
return (None, None)
|
|
|
|
|
|
def communitiesSelect():
|
|
return [(c.id, c.name) for c in DB.getCommunities()]
|
|
|
|
|
|
def datasetsSelect():
|
|
return [("{0.modelname},{0.scenario}".format(d),
|
|
"{x} ({d.resolution}) - {d.modelname} {d.scenario}".format(d=d,
|
|
x=d.datatype.title()))
|
|
for d in DB.getDatasets()]
|