('Selmaps_with_tiles/glikman11_selfunc_ndwfs.dat', 1.71, 6),
('Selmaps_with_tiles/glikman11_selfunc_dls.dat', 2.05, 6),
('Selmaps_with_tiles/yang16_sel.dat', 14555.0, 17),
('Selmaps_with_tiles/mcgreer13_dr7selfunc.dat', 6248.0, 8),
('Selmaps_with_tiles/mcgreer13_s82selfunc.dat', 235.0, 8),
('Selmaps_with_tiles/jiang16main_selfunc.dat', 11240.0, 18),
('Selmaps_with_tiles/jiang16overlap_selfunc.dat', 4223.0, 18),
('Selmaps_with_tiles/jiang16s82_selfunc.dat', 277.0, 18),
('Selmaps_with_tiles/willott10_cfhqsdeepsel.dat', 4.47, 10),
('Selmaps_with_tiles/willott10_cfhqsvwsel.dat', 494.0, 10),
('Selmaps_with_tiles/kashikawa15_sel.dat', 6.5, 11),
('Selmaps_with_tiles/giallongo15_sel.dat', 0.047, 7),
('Selmaps_with_tiles/ukidss_sel_4.dat', 3370.0, 19),
('Selmaps_with_tiles/banados_sel_4.dat', 2500.0, 20)]
lfg1 = lf(quasar_files=qlumfiles, selection_maps=selnfiles, pnum=[3, 4, 2, 5])
g = np.array([
-7.95061036, 1.15284665, -0.12037541, -18.64592897, -4.52638114,
0.47207865, -0.01890026, -3.35945526, -0.26211017, -2.47899576, 0.978408,
3.76233908, 10.96715636, -0.33557835
])
method = 'Nelder-Mead'
b = lfg1.bestfit(g, method=method)
lfg1.prior_min_values = np.array([
-15.0, 0.0, -5.0, -30.0, -10.0, 0.0, -2.0, -7.0, -5.0, -10.0, -10.0, 0.0,
-10.0, -2.0
])
('Data_new/willott10_cfhqsdeepsel.dat', 0.1, 0.025, 4.47, 10),
('Data_new/willott10_cfhqsvwsel.dat', 0.1, 0.025, 494.0, 10),
('Data_new/kashikawa15_sel.dat', 0.05, 0.05, 6.5, 11)
]
#('Data_new/giallongo15_sel.dat', 0.0, 0.0, 0.047, 7),
#('Data_new/ukidss_sel_4.dat', 0.1, 0.1, 3370.0, 19),
#('Data_new/banados_sel_4.dat', 0.1, 0.1, 2500.0, 20)]
case = 0
if case == 0:
# Currently favoured model
lfg = lf(quasar_files=qlumfiles,
selection_maps=selnfiles,
pnum=[3, 4, 2, 5])
g = np.array([
-7.95061036, 1.15284665, -0.12037541, -18.64592897, -4.52638114,
0.47207865, -0.01890026, -3.35945526, -0.26211017, -2.47899576,
0.978408, 3.76233908, 10.96715636, -0.33557835
])
lfg.prior_min_values = np.array([
-15.0, 0.0, -5.0, -30.0, -10.0, 0.0, -2.0, -7.0, -5.0, -10.0, -10.0,
0.0, -10.0, -2.0
])
lfg.prior_max_values = np.array([
-5.0, 10.0, 5.0, -10.0, -1.0, 2.0, 2.0, -1.0, 5.0, 10.0, 10.0, 10.0,
200.0, 2.0