#
# def computegrid(self):
# pass
#
if __name__ == '__main__':
fname = r'D:\test\SJY\asc'
csvfile = r'D:\test\SJY\with9factors\settlements_samplePredictions.csv'
lambdafile = r'D:\test\SJY\with9factors\settlements.lambdas'
fs = FeatureSpace(fname)
ss = SampleSet(csvfile)
l = Lambdas(lambdafile)
l.parselambdafile()
ss.getbgvalues(fs)
dt = ss.getfeatures()
for nm in dt.columns:
for v in l.lambdas:
if nm in v.name:
print(nm, v)
res = []
for v in l.lambdas:
if isinstance(v, Product):
g1, g2 = v.name
pp = v.eval(ss.csv[g1], ss.csv[g2]) * v.lam
res.append(pp)
elif isinstance(v, Lam):
g1 = v.name
pp = v.eval(ss.csv[g1]) * v.lam
res.append(pp)
