Ejemplo n.º 1
0
def grid_BIKE2(pdr, alphas_log, y_id = 'Solubility_log_mol_l'):
	print "BIKE with (A+B)+W"

	xM1 = jpd.pd_get_xM( pdr, radius=6, nBits=4096)
	xM2 = jpd.pd_get_xM_MACCSkeys( pdr)

	yV = jpd.pd_get_yV( pdr, y_id = y_id)

	#A1 = jpyx.calc_tm_sim_M( xM1)
	#A2 = jpyx.calc_tm_sim_M( xM2)
	#A = np.concatenate( ( A1, A2), axis = 1)
	xM = np.concatenate( ( xM1, xM2), axis = 1)
	A = jpyx.calc_tm_sim_M( xM1)
	print A.shape

	molw_l = jchem.rdkit_molwt( pdr.SMILES.tolist())
	print np.shape( molw_l)
	A_molw = jchem.add_new_descriptor( A, molw_l)
	print A_molw.shape

	gs = jgrid.gs_Ridge( A_molw, yV, alphas_log=alphas_log)
	jutil.show_gs_alpha( gs.grid_scores_)
	
	jgrid.cv( 'Ridge', A_molw, yV, alpha = gs.best_params_['alpha'])
	
	return gs
Ejemplo n.º 2
0
def grid_MLR_B(pdr, alphas_log, y_id = 'Solubility_log_mol_l'):
	print "MLR with B"

	xM2 = jpd.pd_get_xM_MACCSkeys( pdr)

	xM_molw = xM2
	yV = jpd.pd_get_yV( pdr, y_id = y_id)

	gs = jgrid.gs_Ridge( xM_molw, yV, alphas_log=alphas_log)
	jutil.show_gs_alpha( gs.grid_scores_)
	
	jgrid.cv( 'Ridge', xM_molw, yV, alpha = gs.best_params_['alpha'])
	
	return gs
Ejemplo n.º 3
0
def grid_MLR_A(pdr, alphas_log, y_id = 'Solubility_log_mol_l'):
	print "MLR with A"

	xM1 = jpd.pd_get_xM( pdr, radius=6, nBits=4096)

	xM_molw = xM1
	yV = jpd.pd_get_yV( pdr, y_id = y_id)

	gs = jgrid.gs_Ridge( xM_molw, yV, alphas_log=alphas_log)
	jutil.show_gs_alpha( gs.grid_scores_)
	
	jgrid.cv( 'Ridge', xM_molw, yV, alpha = gs.best_params_['alpha'])
	
	return gs