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")
