numn = 5
numpy.random.seed(68)
m = Model.ModelNNKelly(hidden_layers=[11, 17],
output_layer=[
'ImH', 'ImHu', 'ImHd', 'ReH', 'ReHu', 'ReHd',
'ImHt', 'ImHtu', 'ImHtd', 'ImE', 'ImEu', 'ImEd',
'ReE', 'ReEu', 'ReEd', 'ImEt', 'ImEtu', 'ImEtd'
],
useDR=['ReHu', 'ReHd', 'ReEu', 'ReEd'],
flavored=['ImH', 'ReH', 'ImHt', 'ImE', 'ReE', 'ImEt'])
_lg.info('New model created: {}'.format(m.__class__))
th = Approach.BM10tw2(m)
th.name = "fNNDR-J15-p22"
f = Fitter.FitterBrain(pts, th, nnets=numn, nbatch=30, minprob=0.0000001)
th.fitpoints = f.fitpoints
f.verbose = 1
_lg.info('Start fit to {} data points'.format(len(f.fitpoints)))
f.fitgood()
_lg.info('{} NNs {} {:.1f}/{} p={:.3g}'.format(numn, th.name,
*th.chisq(f.fitpoints)))
_lg.info('Done. Emailing log file.')
utils.mailfile('*****@*****.**', '*****@*****.**',
'[CAL] {}: fit {} is done'.format(basename,
th.name), logfilename)
