def plotMccEnerRelation(complx_id): # loading weight_fn = "/work/jaydy/dat/08ff_opt" weight = np.loadtxt(weight_fn) # lnr_ff = Lnr_ff('08ff_all_decoy.h5', 'all_set') lnr_ff = Lnr_ff("all_decoy.h5", "all_set") all_set = lnr_ff.loadH5() mcc = all_set[:, 0] ener = all_set[:, 1:] total_ener = np.dot(ener, weight) mcc_total = np.column_stack((mcc, total_ener)) # sampling sample_sz = 2000 if sample_sz <= mcc_total.shape[0]: mcc_total = sortMccTotalByMcc(mcc_total) sampled_mcc_total = np.vstack(row for row in sampleMccTotalByMcc(mcc_total, sample_sz)) mcc_total = sampled_mcc_total mcc, ener = mcc_total[:, 0], mcc_total[:, 1] # scatter_ofn = 'weighted_lnr' + '_scatter.pdf' scatter_ofn = complx_id + "_scatter.pdf" plot.scatter(mcc, ener, ofn=scatter_ofn, x_label="mcc", y_label="diff") # line_ofn = 'weighted_lnr' + '_line.pdf' line_ofn = complx_id + "_line.pdf" plot.two_scales(ener, mcc, ofn=line_ofn, right_label="ener", left_label="diff")