if __name__ == '__main__':
MOLIDS = [
's=Matsson_2009__n=Bromosulfalein',
's=Zembruski_2011__n=103268452',
's=Patel_2011__n=19',
's=Ochoa-Puentes_2011__n=131273183',
's=Jin_2006__n=Ginsenoside Rg1',
's=Matsson_2007__n=Timolol',
]
hub_lso = Hub(dset_id='bcrp', lso=True, expids=range(40000))
hub_csr = Hub(dset_id='bcrp', lso=False, expids=range(40000))
for molid, hub in product(sorted(hub_csr.mols().molids()), (hub_lso, hub_csr)):
# print molid, hub.lso
# rfr_the_loss(hub, molid)
molid, most_influential, r2, _ = regress_the_loss(hub, molid, regressor=LinearRegression())
print molid, hub.lso, r2
for infmolid, coeff in most_influential:
print '\t %.4f %s' % (coeff, infmolid)
print '-' * 80
# MOLID = 'CHEMBL1951453' # hERG
# MOLID = 'NOCAS_M43' # mutagenicity, FAILS with BAD SMELL
# MOLID = '74-83-9' # mutagenicity
# MOLID = 'Bromocriptine' # pgp-cruciani, BSEP HIT!!!
# MOLID = 'Succinylsulfathiazole' # pgp-cruciani
