def test_grouped_ciao4_5(self):
self.run_thread('grouped_ciao4.5')
self.assertEqualWithinTol(ui.get_fit_results().statval, 18.8316, 1e-4)
self.assertEqual(ui.get_fit_results().numpoints, 46)
self.assertEqualWithinTol(self.locals['aa'].gamma.val, 1.83906, 1e-4)
self.assertEqualWithinTol(self.locals['aa'].ampl.val, 0.000301258,
1e-4)
def test_pha_intro(self):
self.run_thread('pha_intro')
# astro.ui imported as ui, instead of
# being in global namespace
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
assert covarerr[0] == approx(0.0790393, rel=1e-4)
assert covarerr[1] == approx(1.4564e-05, rel=1e-4)
assert fit_results.statval == approx(37.9079, rel=1e-4)
assert fit_results.rstat == approx(0.902569, rel=1e-4)
assert fit_results.qval == approx(0.651155, rel=1e-4)
assert self.locals['p1'].gamma.val == approx(2.15852, rel=1e-4)
assert self.locals['p1'].ampl.val == approx(0.00022484, rel=1e-4)
assert ui.calc_photon_flux() == approx(0.000469964, rel=1e-4)
assert ui.calc_energy_flux() == approx(9.614847e-13, rel=1e-4)
assert ui.calc_data_sum() == approx(706.85714092, rel=1e-4)
assert ui.calc_model_sum() == approx(638.45693377, rel=1e-4)
assert ui.calc_source_sum() == approx(0.046996409, rel=1e-4)
calc = ui.eqwidth(self.locals['p1'], ui.get_source())
assert calc == approx(-0.57731725, rel=1e-4)
calc = ui.calc_kcorr([1, 1.2, 1.4, 1.6, 1.8, 2], 0.5, 2)
expected = [0.93341286, 0.93752836, 0.94325233,
0.94990140, 0.95678054, 0.96393515]
assert calc == approx(expected, rel=1e-4)
self.assertEqual(ui.get_fit_results().nfev, 22)
self.assertEqual(ui.get_fit_results().numpoints, 44)
self.assertEqual(ui.get_fit_results().dof, 42)
def test_linepro(self):
def cmp_linepro(fit_results, mylocals, covarerr):
b1 = mylocals['b1']
assert covarerr[0] == approx(0.176282, rel=1e-4)
assert covarerr[1] == approx(0.0019578, rel=1e-4)
assert covarerr[2] == approx(0.495889, rel=1e-4)
assert fit_results.statval == approx(203.34, rel=1e-4)
assert b1.r0.val == approx(4.25557, rel=1e-4)
assert b1.beta.val == approx(0.492232, rel=1e-4)
assert b1.ampl.val == approx(11.8129, rel=1e-4)
self.assertEqual(fit_results.nfev, 17)
self.assertEqual(fit_results.numpoints, 75)
self.assertEqual(fit_results.dof, 72)
self.run_thread('linepro')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_linepro(fit_results, self.locals, covarerr)
self.assertEqual(0, fit_results.extra_output['num_parallel_map'])
self.run_thread('linepro_ncpus')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_linepro(fit_results, self.locals, covarerr)
if _ncpus != 1:
assert fit_results.extra_output['num_parallel_map'] > 0
else:
assert fit_results.extra_output['num_parallel_map'] == 0
def test_radpro(self):
def cmp_radpro(fit_results, mylocals, covarerr):
src = mylocals['src']
assert covarerr[0] == approx(9.37345, rel=1e-4)
assert covarerr[1] == approx(0.512596, rel=1e-4)
assert covarerr[2] == approx(0.0691102, rel=1e-4)
assert fit_results.statval == approx(217.450, rel=1e-4)
assert fit_results.rstat == approx(6.21287, rel=1e-4)
assert fit_results.qval == approx(0.0, rel=1e-4)
assert src.r0.val == approx(125.829, rel=1e-4)
assert src.beta.val == approx(4.1633, rel=1e-4)
assert src.xpos.val == approx(0.0, rel=1e-4)
assert src.ampl.val == approx(4.42821, rel=1e-4)
self.assertEqual(fit_results.nfev, 92)
self.assertEqual(fit_results.numpoints, 38)
self.assertEqual(fit_results.dof, 35)
self.run_thread('radpro')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_radpro(fit_results, self.locals, covarerr)
self.assertEqual(0, fit_results.extra_output['num_parallel_map'])
self.run_thread('radpro_ncpus')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_radpro(fit_results, self.locals, covarerr)
if _ncpus != 1:
assert fit_results.extra_output['num_parallel_map'] > 0
else:
assert fit_results.extra_output['num_parallel_map'] == 0
def test_sourceandbg(self):
def cmp_sourceanddbg(fit_results, mylocals, covarerr):
a1 = mylocals['a1']
b1 = mylocals['b1']
b2 = mylocals['b2']
assert covarerr[0] == approx(0.012097, rel=1e-3)
assert covarerr[1] == approx(0, rel=1e-3)
assert covarerr[2] == approx(0.000280678, rel=1e-3)
assert covarerr[3] == approx(0.00990783, rel=1e-3)
assert covarerr[4] == approx(2.25746e-07, rel=1e-3)
assert fit_results.statval == approx(947.5, rel=1e-4)
assert fit_results.rstat == approx(0.715094, rel=1e-4)
assert fit_results.qval == approx(1, rel=1e-4)
assert a1.nh.val == approx(0.0342266, rel=1e-2)
assert b1.kt.val == approx(20, rel=1e-2)
self.assertEqualWithinTol(b1.norm.val, 0.00953809, 1e-2)
self.assertEqualWithinTol(b2.kt.val, 0.563109, 1e-2)
self.assertEqualWithinTol(b2.norm.val, 1.16118e-05, 1e-2)
self.assertEqual(fit_results.numpoints, 1330)
self.assertEqual(fit_results.dof, 1325)
self.run_thread('sourceandbg')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_sourceanddbg(fit_results, self.locals, covarerr)
self.assertEqual(0, fit_results.extra_output['num_parallel_map'])
self.run_thread('sourceandbg_ncpus')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_sourceanddbg(fit_results, self.locals, covarerr)
if _ncpus != 1:
fit_results.extra_output['num_parallel_map'] > 0
else:
assert fit_results.extra_output['num_parallel_map'] == 0
def test_kernel(self):
def cmp_kernel(fit_results, mylocals, covarerr):
b1 = mylocals['b1']
assert covarerr[0] == approx(0.210895, rel=1e-4)
assert covarerr[1] == approx(0.00154839, rel=1e-4)
assert covarerr[2] == approx(0.0223859, rel=1e-4)
assert fit_results.statval == approx(98.5793, rel=1e-4)
assert b1.r0.val == approx(19.2278, rel=1e-4)
assert b1.beta.val == approx(0.555464, rel=1e-4)
assert b1.ampl.val == approx(1.93706, rel=1e-4)
self.assertEqual(fit_results.nfev, 21)
self.assertEqual(fit_results.numpoints, 75)
self.assertEqual(fit_results.dof, 72)
self.run_thread('kernel')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_kernel(fit_results, self.locals, covarerr)
self.assertEqual(0, fit_results.extra_output['num_parallel_map'])
self.run_thread('kernel_ncpus')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_kernel(fit_results, self.locals, covarerr)
if _ncpus != 1:
assert fit_results.extra_output['num_parallel_map'] > 0
else:
assert fit_results.extra_output['num_parallel_map'] == 0
def test_xmm(self):
def cmp_xmm(fres, mylocals, covarerr):
intrin = mylocals['intrin']
phard = mylocals['phard']
assert covarerr[0] == approx(0.954993, rel=1e-3)
assert covarerr[1] == approx(0.142357, rel=1e-3)
assert covarerr[2] == approx(0.00038775, rel=1e-3)
assert fres.statval == approx(118.085, rel=1e-4)
self.assertEqualWithinTol(intrin.nh.val, 11.0769, 1e-2)
self.assertEqualWithinTol(phard.phoindex.val, 1.49055, 1e-2)
self.assertEqualWithinTol(phard.norm.val, 0.00140301, 1e-2)
self.assertEqual(fres.nfev, 95)
self.assertEqual(fres.numpoints, 162)
self.assertEqual(fres.dof, 159)
self.run_thread('xmm')
fres = ui.get_fit_results()
covarerr = sqrt(fres.extra_output['covar'].diagonal())
cmp_xmm(fres, self.locals, covarerr)
self.assertEqual(0, fres.extra_output['num_parallel_map'])
self.run_thread('xmm_ncpus')
fres = ui.get_fit_results()
covarerr = sqrt(fres.extra_output['covar'].diagonal())
cmp_xmm(fres, self.locals, covarerr)
if _ncpus != 1:
assert fres.extra_output['num_parallel_map'] > 0
else:
assert fres.extra_output['num_parallel_map'] == 0
def test_spectrum(self):
def cmp_spectrum(fres, mylocals, covarerr):
abs2 = mylocals['abs2']
mek1 = mylocals['mek1']
mek2 = mylocals['mek2']
assert covarerr[0] == approx(0.00148391, rel=1e-3)
assert covarerr[1] == approx(0.0011518, rel=1e-3)
assert covarerr[2] == approx(0.00377755, rel=1e-3)
assert covarerr[3] == approx(0.00370543, rel=1e-3)
assert covarerr[4] == approx(0.0016608, rel=1e-3)
assert fres.statval == approx(0.0496819, rel=1e-4)
assert abs2.nh.val == approx(1.1015, rel=1e-4)
assert mek1.kt.val == approx(0.841025, rel=1e-4)
assert mek1.norm.val == approx(0.699761, rel=1e-4)
assert mek2.kt.val == approx(2.35845, rel=1e-4)
assert mek2.norm.val == approx(1.03724, rel=1e-4)
self.assertEqual(fres.numpoints, 446)
self.assertEqual(fres.dof, 441)
self.run_thread('spectrum')
fres = ui.get_fit_results()
covarerr = sqrt(fres.extra_output['covar'].diagonal())
cmp_spectrum(fres, self.locals, covarerr)
self.assertEqual(0, fres.extra_output['num_parallel_map'])
self.run_thread('spectrum_ncpus')
fres = ui.get_fit_results()
covarerr = sqrt(fres.extra_output['covar'].diagonal())
cmp_spectrum(fres, self.locals, covarerr)
if _ncpus != 1:
assert fres.extra_output['num_parallel_map'] > 0
else:
assert fres.extra_output['num_parallel_map'] == 0
def test_grouped_ciao4_5(self):
def cmp_grouped_ciao4_5(fres, mylocals, covarerr):
assert covarerr[0] == approx(0.104838, rel=1e-4)
assert covarerr[1] == approx(2.43937e-05, rel=1e-4)
assert fres.statval == approx(18.8316, rel=1e-4)
self.assertEqual(fres.numpoints, 46)
aamdl = mylocals['aa']
assert aamdl.gamma.val == approx(1.83906, rel=1e-4)
assert aamdl.ampl.val == approx(0.000301258, rel=1e-4)
self.run_thread('grouped_ciao4.5')
fres = ui.get_fit_results()
covarerr = sqrt(fres.extra_output['covar'].diagonal())
cmp_grouped_ciao4_5(fres, self.locals, covarerr)
self.assertEqual(0, fres.extra_output['num_parallel_map'])
self.run_thread('grouped_ciao4.5_ncpus')
fres = ui.get_fit_results()
covarerr = sqrt(fres.extra_output['covar'].diagonal())
cmp_grouped_ciao4_5(fres, self.locals, covarerr)
if _ncpus != 1:
assert fres.extra_output['num_parallel_map'] > 0
else:
assert fres.extra_output['num_parallel_map'] == 0
def test_proj_bubble(self):
def cmp_proj_bubble(mylocals, convarerr, proj, conf):
mek1 = mylocals['mek1']
assert covarerr[0] == approx(0, rel=1e-4)
assert covarerr[1] == approx(8.74608e-07, rel=1e-3)
assert mek1.kt.val == approx(17.8849, rel=1e-2)
assert mek1.norm.val == approx(4.15418e-06, rel=1e-2)
# Proj -- Upper bound of kT can't be found
#
assert proj.parmins[0] == approx(-12.048069, rel=0.01)
assert proj.parmins[1] == approx(-9.510913e-07, rel=0.01)
assert proj.parmaxes[1] == approx(2.403640e-06, rel=0.01)
assert proj.parmaxes[0] is None
assert conf.parmins[0] == approx(-12.1073, rel=0.01)
assert conf.parmaxes[0] == approx(62.0585, rel=0.01)
assert conf.parmins[1] == approx(-9.5568e-07, rel=0.01)
assert conf.parmaxes[1] == approx(2.39937e-06, rel=0.01)
self.run_thread('proj_bubble')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
proj = ui.get_proj_results()
conf = ui.get_conf_results()
cmp_proj_bubble(self.locals, covarerr, proj, conf)
self.run_thread('proj_bubble_ncpus')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
proj = ui.get_proj_results()
conf = ui.get_conf_results()
cmp_proj_bubble(self.locals, covarerr, proj, conf)
def test_simultaneous(self):
def cmp_simultaneous(fit_results, mylocals, covarerr):
abs1 = mylocals['abs1']
pl1 = mylocals['pl1']
pl2 = mylocals['pl2']
assert covarerr[0] == approx(0.397769, rel=1e-3)
assert covarerr[1] == approx(0.486058, rel=1e-3)
assert covarerr[2] == approx(1.48213e-05, rel=1e-3)
assert covarerr[3] == approx(1.54245e-05, rel=1e-3)
assert fit_results.statval == approx(7.4429, rel=1e-4)
assert fit_results.rstat == approx(0.531636, rel=1e-4)
assert fit_results.qval == approx(0.916288, rel=1e-4)
assert abs1.nh.val == approx(0.898162, rel=1e-2)
assert pl1.gamma.val == approx(1.645, rel=1e-4)
self.assertEqualWithinTol(pl1.ampl.val, 2.28323e-05, 1e-3)
self.assertEqualWithinTol(pl2.ampl.val, 2.44585e-05, 1e-3)
self.assertEqual(fit_results.numpoints, 18)
self.assertEqual(fit_results.dof, 14)
self.run_thread('simultaneous')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_simultaneous(fit_results, self.locals, covarerr)
self.assertEqual(0, fit_results.extra_output['num_parallel_map'])
self.run_thread('simultaneous_ncpus')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
cmp_simultaneous(fit_results, self.locals, covarerr)
if _ncpus != 1:
assert fit_results.extra_output['num_parallel_map'] > 0
else:
assert fit_results.extra_output['num_parallel_map'] == 0
def test_xmm(self):
self.run_thread('xmm')
self.assertEqualWithinTol(ui.get_fit_results().statval, 118.085, 1e-4)
self.assertEqualWithinTol(self.locals['intrin'].nh.val, 11.0769, 1e-2)
self.assertEqualWithinTol(self.locals['phard'].phoindex.val, 1.49055, 1e-2)
self.assertEqualWithinTol(self.locals['phard'].norm.val, 0.00140301, 1e-2)
self.assertEqual(ui.get_fit_results().nfev, 95)
self.assertEqual(ui.get_fit_results().numpoints, 162)
self.assertEqual(ui.get_fit_results().dof, 159)
def test_kernel(self):
self.run_thread('kernel')
self.assertEqualWithinTol(ui.get_fit_results().statval, 98.5793, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].r0.val, 19.2278, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].beta.val, 0.555464, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].ampl.val, 1.93706, 1e-4)
self.assertEqual(ui.get_fit_results().nfev,21)
self.assertEqual(ui.get_fit_results().numpoints,75)
self.assertEqual(ui.get_fit_results().dof,72)
def test_linepro(self):
self.run_thread('linepro')
self.assertEqualWithinTol(ui.get_fit_results().statval, 203.34, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].r0.val, 4.25557, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].beta.val, 0.492232, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].ampl.val, 11.8129, 1e-4)
self.assertEqual(ui.get_fit_results().nfev,17)
self.assertEqual(ui.get_fit_results().numpoints,75)
self.assertEqual(ui.get_fit_results().dof,72)
def test_radpro_psf(self):
self.run_thread('radpro_psf')
self.assertEqualWithinTol(ui.get_fit_results().statval, 200.949, 1e-4)
self.assertEqualWithinTol(self.locals['src'].r0.val, 83.0997, 1e-4)
self.assertEqualWithinTol(self.locals['src'].beta.val, 2.97737, 1e-4)
self.assertEqualWithinTol(self.locals['src'].ampl.val, 5.27604, 1e-4)
self.assertEqual(ui.get_fit_results().nfev,48)
self.assertEqual(ui.get_fit_results().numpoints,38)
self.assertEqual(ui.get_fit_results().dof,35)
def test_histo(self):
self.run_thread('histo')
assert ui.get_fit_results().statval == approx(14.7264, rel=1e-4)
assert self.locals['g1'].fwhm.val == approx(0.0232473, rel=1e-4)
assert self.locals['g1'].pos.val == approx(1.26713, rel=1e-4)
assert self.locals['g1'].ampl.val == approx(40.4503, rel=1e-4)
# self.assertEqual(ui.get_fit_results().nfev, 19)
self.assertEqual(ui.get_fit_results().numpoints, 50)
self.assertEqual(ui.get_fit_results().dof, 47)
def test_kernel(self):
self.run_thread('kernel')
self.assertEqualWithinTol(ui.get_fit_results().statval, 98.5793, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].r0.val, 19.2278, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].beta.val, 0.555464, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].ampl.val, 1.93706, 1e-4)
self.assertEqual(ui.get_fit_results().nfev, 21)
self.assertEqual(ui.get_fit_results().numpoints, 75)
self.assertEqual(ui.get_fit_results().dof, 72)
def test_radpro_psf(self):
self.run_thread('radpro_psf')
assert ui.get_fit_results().statval == approx(200.949, rel=1e-4)
assert self.locals['src'].r0.val == approx(83.0997, rel=1e-4)
assert self.locals['src'].beta.val == approx(2.97737, rel=1e-4)
assert self.locals['src'].ampl.val == approx(5.27604, rel=1e-4)
self.assertEqual(ui.get_fit_results().nfev, 48)
self.assertEqual(ui.get_fit_results().numpoints, 38)
self.assertEqual(ui.get_fit_results().dof, 35)
def test_radpro_psf(self):
self.run_thread('radpro_psf')
self.assertEqualWithinTol(ui.get_fit_results().statval, 200.949, 1e-4)
self.assertEqualWithinTol(self.locals['src'].r0.val, 83.0997, 1e-4)
self.assertEqualWithinTol(self.locals['src'].beta.val, 2.97737, 1e-4)
self.assertEqualWithinTol(self.locals['src'].ampl.val, 5.27604, 1e-4)
self.assertEqual(ui.get_fit_results().nfev, 48)
self.assertEqual(ui.get_fit_results().numpoints, 38)
self.assertEqual(ui.get_fit_results().dof, 35)
def test_xmm(self):
self.run_thread('xmm')
self.assertEqualWithinTol(ui.get_fit_results().statval, 118.085, 1e-4)
self.assertEqualWithinTol(self.locals['intrin'].nh.val, 11.0769, 1e-2)
self.assertEqualWithinTol(self.locals['phard'].phoindex.val, 1.49055, 1e-2)
self.assertEqualWithinTol(self.locals['phard'].norm.val, 0.00140301, 1e-2)
self.assertEqual(ui.get_fit_results().nfev,95)
self.assertEqual(ui.get_fit_results().numpoints,162)
self.assertEqual(ui.get_fit_results().dof,159)
def test_histo(self):
self.run_thread('histo')
self.assertEqualWithinTol(ui.get_fit_results().statval, 14.7264, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].fwhm.val, 0.0232473, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].pos.val, 1.26713, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ampl.val, 40.4503, 1e-4)
# self.assertEqual(ui.get_fit_results().nfev,19)
self.assertEqual(ui.get_fit_results().numpoints, 50)
self.assertEqual(ui.get_fit_results().dof, 47)
def test_histo(self):
self.run_thread('histo')
self.assertEqualWithinTol(ui.get_fit_results().statval, 14.7264, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].fwhm.val, 0.0232473, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].pos.val, 1.26713, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ampl.val, 40.4503, 1e-4)
#self.assertEqual(ui.get_fit_results().nfev,19)
self.assertEqual(ui.get_fit_results().numpoints,50)
self.assertEqual(ui.get_fit_results().dof,47)
def test_linepro(self):
self.run_thread('linepro')
self.assertEqualWithinTol(ui.get_fit_results().statval, 203.34, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].r0.val, 4.25557, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].beta.val, 0.492232, 1e-4)
self.assertEqualWithinTol(self.locals['b1'].ampl.val, 11.8129, 1e-4)
self.assertEqual(ui.get_fit_results().nfev, 17)
self.assertEqual(ui.get_fit_results().numpoints, 75)
self.assertEqual(ui.get_fit_results().dof, 72)
def test_spectrum(self):
self.run_thread('spectrum')
self.assertEqualWithinTol(ui.get_fit_results().statval, 0.0496819, 1e-4)
self.assertEqualWithinTol(self.locals['abs2'].nh.val, 1.1015, 1e-4)
self.assertEqualWithinTol(self.locals['mek1'].kt.val, 0.841025, 1e-4)
self.assertEqualWithinTol(self.locals['mek1'].norm.val, 0.699761, 1e-4)
self.assertEqualWithinTol(self.locals['mek2'].kt.val, 2.35845, 1e-4)
self.assertEqualWithinTol(self.locals['mek2'].norm.val, 1.03724, 1e-4)
self.assertEqual(ui.get_fit_results().numpoints,446)
self.assertEqual(ui.get_fit_results().dof,441)
def test_psf2d(self):
self.run_thread('psf')
self.assertEqualWithinTol(ui.get_fit_results().statval, 4066.78, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].fwhm.val, 2.80117, 1e-2)
self.assertEqualWithinTol(self.locals['g1'].ypos.val, 77.2271, 1e-2)
self.assertEqualWithinTol(self.locals['g1'].xpos.val, 88.661, 1e-2)
self.assertEqualWithinTol(self.locals['g1'].ampl.val, 166.649, 1e-2)
# self.assertEqual(ui.get_fit_results().nfev,342)
self.assertEqual(ui.get_fit_results().numpoints, 4899)
self.assertEqual(ui.get_fit_results().dof, 4895)
def test_spectrum(self):
self.run_thread('spectrum')
self.assertEqualWithinTol(ui.get_fit_results().statval, 0.0496819, 1e-4)
self.assertEqualWithinTol(self.locals['abs2'].nh.val, 1.1015, 1e-4)
self.assertEqualWithinTol(self.locals['mek1'].kt.val, 0.841025, 1e-4)
self.assertEqualWithinTol(self.locals['mek1'].norm.val, 0.699761, 1e-4)
self.assertEqualWithinTol(self.locals['mek2'].kt.val, 2.35845, 1e-4)
self.assertEqualWithinTol(self.locals['mek2'].norm.val, 1.03724, 1e-4)
self.assertEqual(ui.get_fit_results().numpoints, 446)
self.assertEqual(ui.get_fit_results().dof, 441)
def test_psf2d(self):
self.run_thread('psf')
self.assertEqualWithinTol(ui.get_fit_results().statval, 4066.78, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].fwhm.val, 2.80117, 1e-2)
self.assertEqualWithinTol(self.locals['g1'].ypos.val, 77.2271, 1e-2)
self.assertEqualWithinTol(self.locals['g1'].xpos.val, 88.661, 1e-2)
self.assertEqualWithinTol(self.locals['g1'].ampl.val, 166.649, 1e-2)
#self.assertEqual(ui.get_fit_results().nfev,342)
self.assertEqual(ui.get_fit_results().numpoints,4899)
self.assertEqual(ui.get_fit_results().dof,4895)
def test_psf2d(self):
self.run_thread('psf')
assert ui.get_fit_results().statval == approx(4066.78, rel=1e-4)
assert self.locals['g1'].fwhm.val == approx(2.80117, rel=1e-2)
assert self.locals['g1'].ypos.val == approx(77.2271, rel=1e-2)
assert self.locals['g1'].xpos.val == approx(88.661, rel=1e-2)
assert self.locals['g1'].ampl.val == approx(166.649, rel=1e-2)
# self.assertEqual(ui.get_fit_results().nfev, 342)
self.assertEqual(ui.get_fit_results().numpoints, 4899)
self.assertEqual(ui.get_fit_results().dof, 4895)
def test_simultaneous(self):
self.run_thread('simultaneous')
self.assertEqualWithinTol(ui.get_fit_results().statval, 7.4429, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 0.531636, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.916288, 1e-4)
self.assertEqualWithinTol(self.locals['abs1'].nh.val, 0.898162, 1e-2)
self.assertEqualWithinTol(self.locals['pl1'].gamma.val, 1.645, 1e-4)
self.assertEqualWithinTol(self.locals['pl1'].ampl.val, 2.28323e-05, 1e-3)
self.assertEqualWithinTol(self.locals['pl2'].ampl.val, 2.44585e-05, 1e-3)
self.assertEqual(ui.get_fit_results().numpoints, 18)
self.assertEqual(ui.get_fit_results().dof, 14)
def test_lev3fft(self):
self.run_thread('lev3fft', scriptname='bar.py')
self.assertEqualWithinTol(self.locals['src'].fwhm.val, 0.04418584, 1e-4)
self.assertEqualWithinTol(self.locals['src'].xpos.val, 150.016, 1e-4)
self.assertEqualWithinTol(self.locals['src'].ypos.val, 2.66493839, 1e-4)
self.assertEqualWithinTol(self.locals['src'].ampl.val, 1.56090546, 1e-4)
self.assertEqualWithinTol(self.locals['bkg'].c0.val, -1.513700715, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().istatval, 19496.3, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().statval, 592.32647, 1e-4)
self.assertEqual(ui.get_fit_results().numpoints, 3307)
self.assertEqual(ui.get_fit_results().dof, 3302)
def test_lev3fft(self):
self.run_thread('lev3fft', scriptname='bar.py')
self.assertEqualWithinTol(self.locals['src'].fwhm.val, 0.04418584, 1e-4)
self.assertEqualWithinTol(self.locals['src'].xpos.val, 150.016, 1e-4)
self.assertEqualWithinTol(self.locals['src'].ypos.val, 2.66493839, 1e-4)
self.assertEqualWithinTol(self.locals['src'].ampl.val, 1.56090546, 1e-4)
self.assertEqualWithinTol(self.locals['bkg'].c0.val, -1.513700715, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().istatval, 19496.3, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().statval, 592.32647, 1e-4)
self.assertEqual(ui.get_fit_results().numpoints, 3307)
self.assertEqual(ui.get_fit_results().dof, 3302)
def test_simultaneous(self):
self.run_thread('simultaneous')
self.assertEqualWithinTol(ui.get_fit_results().statval, 7.4429, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 0.531636, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.916288, 1e-4)
self.assertEqualWithinTol(self.locals['abs1'].nh.val, 0.898162, 1e-2)
self.assertEqualWithinTol(self.locals['pl1'].gamma.val, 1.645, 1e-4)
self.assertEqualWithinTol(self.locals['pl1'].ampl.val, 2.28323e-05, 1e-3)
self.assertEqualWithinTol(self.locals['pl2'].ampl.val, 2.44585e-05, 1e-3)
self.assertEqual(ui.get_fit_results().numpoints,18)
self.assertEqual(ui.get_fit_results().dof,14)
def test_pileup(self):
self.run_thread('pileup')
self.assertEqualWithinTol(ui.get_fit_results().statval, 53.6112, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 1.44895, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.0379417, 1e-4)
self.assertEqualWithinTol(self.locals['jdp'].alpha.val, 0.522593, 1e-1)
self.assertEqualWithinTol(self.locals['jdp'].f.val, 0.913458, 1e-2)
self.assertEqualWithinTol(self.locals['abs1'].nh.val, 6.12101, 1e-2)
self.assertEqualWithinTol(self.locals['power'].gamma.val, 1.41887, 1e-2)
self.assertEqualWithinTol(self.locals['power'].ampl.val, 0.00199457, 1e-2)
self.assertEqual(ui.get_fit_results().numpoints,42)
self.assertEqual(ui.get_fit_results().dof,37)
def test_sourceandbg(self):
self.run_thread('sourceandbg')
self.assertEqualWithinTol(ui.get_fit_results().statval, 947.5, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 0.715094, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 1, 1e-4)
self.assertEqualWithinTol(self.locals['a1'].nh.val, 0.0342266, 1e-2)
self.assertEqualWithinTol(self.locals['b1'].kt.val, 20, 1e-2)
self.assertEqualWithinTol(self.locals['b1'].norm.val, 0.00953809, 1e-2)
self.assertEqualWithinTol(self.locals['b2'].kt.val, 0.563109, 1e-2)
self.assertEqualWithinTol(self.locals['b2'].norm.val, 1.16118e-05, 1e-2)
self.assertEqual(ui.get_fit_results().numpoints,1330)
self.assertEqual(ui.get_fit_results().dof,1325)
def test_sourceandbg(self):
self.run_thread('sourceandbg')
self.assertEqualWithinTol(ui.get_fit_results().statval, 947.5, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 0.715094, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 1, 1e-4)
self.assertEqualWithinTol(self.locals['a1'].nh.val, 0.0342266, 1e-2)
self.assertEqualWithinTol(self.locals['b1'].kt.val, 20, 1e-2)
self.assertEqualWithinTol(self.locals['b1'].norm.val, 0.00953809, 1e-2)
self.assertEqualWithinTol(self.locals['b2'].kt.val, 0.563109, 1e-2)
self.assertEqualWithinTol(self.locals['b2'].norm.val, 1.16118e-05, 1e-2)
self.assertEqual(ui.get_fit_results().numpoints, 1330)
self.assertEqual(ui.get_fit_results().dof, 1325)
def test_pileup(self):
self.run_thread('pileup')
self.assertEqualWithinTol(ui.get_fit_results().statval, 53.6112, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 1.44895, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.0379417, 1e-4)
self.assertEqualWithinTol(self.locals['jdp'].alpha.val, 0.522593, 1e-1)
self.assertEqualWithinTol(self.locals['jdp'].f.val, 0.913458, 1e-2)
self.assertEqualWithinTol(self.locals['abs1'].nh.val, 6.12101, 1e-2)
self.assertEqualWithinTol(self.locals['power'].gamma.val, 1.41887, 1e-2)
self.assertEqualWithinTol(self.locals['power'].ampl.val, 0.00199457, 1e-2)
self.assertEqual(ui.get_fit_results().numpoints, 42)
self.assertEqual(ui.get_fit_results().dof, 37)
def test_spatial(self):
self.run_thread('spatial')
self.assertEqualWithinTol(ui.get_fit_results().statval, -59229.749441, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].fwhm.val, 61.5615, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].xpos.val, 4070.45, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ypos.val, 4251.35, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ampl.val, 22.1269, 1e-4)
self.assertEqualWithinTol(self.locals['g2'].fwhm.val, 6.20409, 1e-4)
self.assertEqualWithinTol(self.locals['g2'].xpos.val, 4070.78, 1e-4)
self.assertEqualWithinTol(self.locals['g2'].ypos.val, 4249.33, 1e-4)
self.assertEqualWithinTol(self.locals['g2'].ampl.val, 226.563, 1e-4)
#self.assertEqual(ui.get_fit_results().nfev,371)
self.assertEqual(ui.get_fit_results().numpoints,4881)
self.assertEqual(ui.get_fit_results().dof,4877)
def test_spatial(self):
self.run_thread('spatial')
self.assertEqualWithinTol(ui.get_fit_results().statval, -59229.749441, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].fwhm.val, 61.5615, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].xpos.val, 4070.45, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ypos.val, 4251.35, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ampl.val, 22.1269, 1e-4)
self.assertEqualWithinTol(self.locals['g2'].fwhm.val, 6.20409, 1e-4)
self.assertEqualWithinTol(self.locals['g2'].xpos.val, 4070.78, 1e-4)
self.assertEqualWithinTol(self.locals['g2'].ypos.val, 4249.33, 1e-4)
self.assertEqualWithinTol(self.locals['g2'].ampl.val, 226.563, 1e-4)
# self.assertEqual(ui.get_fit_results().nfev,371)
self.assertEqual(ui.get_fit_results().numpoints, 4881)
self.assertEqual(ui.get_fit_results().dof, 4877)
def test_fpsf2d(self):
self.run_thread('fpsf')
self.assertEqualWithinTol(ui.get_fit_results().statval, -4053.6635, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].xlow.val, -4.70832, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].xhi.val, 164.687, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].ylow.val, 0.83626, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].yhi.val, 142.603, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].ampl.val, 0.956766, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].fwhm.val, 6.420237, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].xpos.val, 88.940712, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ypos.val, 76.577265, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ampl.val, 36344.48324, 1e-4)
#self.assertEqual(ui.get_fit_results().nfev,978)
self.assertEqual(ui.get_fit_results().numpoints,4899)
self.assertEqual(ui.get_fit_results().dof,4895)
def test_fpsf2d(self):
self.run_thread('fpsf')
self.assertEqualWithinTol(ui.get_fit_results().statval, -4053.6635, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].xlow.val, -4.70832, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].xhi.val, 164.687, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].ylow.val, 0.83626, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].yhi.val, 142.603, 1e-4)
# self.assertEqualWithinTol(self.locals['b1'].ampl.val, 0.956766, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].fwhm.val, 6.420237, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].xpos.val, 88.940712, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ypos.val, 76.577265, 1e-4)
self.assertEqualWithinTol(self.locals['g1'].ampl.val, 36344.48324, 1e-4)
# self.assertEqual(ui.get_fit_results().nfev,978)
self.assertEqual(ui.get_fit_results().numpoints, 4899)
self.assertEqual(ui.get_fit_results().dof, 4895)
def test_eqwith_err1(make_data_path, restore_xspec_settings):
def check1(e0, e1, e2):
assert e0 == approx(0.028335201547206704, rel=1.0e-3)
assert e1 == approx(-0.00744118799274448756, rel=1.0e-3)
assert e2 == approx(0.0706249544851336, rel=1.0e-3)
ui.set_xsabund('angr')
ui.set_xsxsect('bcmc')
ui.load_pha(make_data_path('3c273.pi'))
ui.notice(0.5, 7.0)
ui.set_stat("chi2datavar")
ui.set_method("simplex")
ui.set_model('powlaw1d.p1+gauss1d.g1')
g1.fwhm = 0.1
g1.pos = 2.0
ui.freeze(g1.pos, g1.fwhm)
ui.fit()
numpy.random.seed(2345)
e = ui.eqwidth(p1, p1 + g1, error=True, niter=100)
check1(e[0], e[1], e[2])
params = e[3]
numpy.random.seed(2345)
e = ui.eqwidth(p1, p1 + g1, error=True, params=params, niter=100)
check1(e[0], e[1], e[2])
parvals = ui.get_fit_results().parvals
assert parvals[0] == approx(1.9055272902160334, rel=1.0e-3)
assert parvals[1] == approx(0.00017387966749772638, rel=1.0e-3)
assert parvals[2] == approx(1.279415076070516e-05, rel=1.0e-3)
def test_ARFModelPHA(self):
from sherpa.astro import ui
ui.load_pha(self.make_path("3c120_meg_1.pha"))
# remove the RMF to ensure this is an ARF-only analysis
# (which is what is needed to trigger the bug that lead to #699)
ui.get_data().set_rmf(None)
ui.group_counts(20)
ui.notice(0.5, 6)
ui.subtract()
ui.set_model(ui.xsphabs.abs1 * (ui.xsapec.bubble + ui.powlaw1d.p1))
ui.set_xsabund('angr')
ui.set_xsxsect('vern')
abs1.nh = 0.163
abs1.nh.freeze()
p1.ampl = 0.017
p1.gamma = 1.9
bubble.kt = 0.5
bubble.norm = 4.2e-5
tol = 1.0e-2
ui.set_method_opt('ftol', tol)
ui.fit()
result = ui.get_fit_results()
assert result.numpoints == self._fit_using_ARFModelPHA['numpoints']
assert result.dof == self._fit_using_ARFModelPHA['dof']
def test_radpro_dm(self):
# This test is completely redundant to test_radpro above.
# The only difference is that here I test if using DM syntax
# in the file name returns the correct arrays from CRATES.
# Since any other I/O backend would not understand DM syntax,
# I make this test a no-op unless CRATES is used as the I/O
# backend. SMD 05/23/13
if self.is_crates_io:
self.run_thread('radpro_dm')
fres = ui.get_fit_results()
covarerr = sqrt(fres.extra_output['covar'].diagonal())
assert covarerr[0] == approx(9.37344776, rel=1e-4)
assert covarerr[1] == approx(0.51259645, rel=1e-4)
assert covarerr[2] == approx(0.06911017, rel=1e-4)
assert fres.statval == approx(217.450, rel=1e-4)
assert fres.rstat == approx(6.21287, rel=1e-4)
assert fres.qval == approx(0.0, rel=1e-4)
srcmdl = self.locals['src']
assert srcmdl.r0.val == approx(125.829, rel=1e-4)
assert srcmdl.beta.val == approx(4.1633, rel=1e-4)
assert srcmdl.xpos.val == approx(0.0, rel=1e-4)
assert srcmdl.ampl.val == approx(4.42821, rel=1e-4)
self.assertEqual(fres.nfev, 92)
self.assertEqual(fres.numpoints, 38)
self.assertEqual(fres.dof, 35)
def test_user_stat_unit():
given_stat_error = [1.1, 2.2, 3.3]
given_sys_error = [10.1, 10.2, 10.3]
def calc_stat(data, _model, staterror, syserror=None, weight=None):
# Make sure values are being injected correctly
np.testing.assert_array_equal(given_stat_error, staterror)
np.testing.assert_array_equal(given_sys_error, syserror)
return 3.235, np.ones_like(data)
xdata = [1, 2, 3]
ydata = xdata
ui.load_arrays(1, xdata, ydata, None, given_sys_error, Data1D)
ui.set_model(1, 'polynom1d.p')
ui.load_user_stat('customstat', calc_stat, lambda x: given_stat_error)
ui.set_stat(eval('customstat'))
try:
ui.fit(1)
except StatErr:
pytest.fail("Call should not be throwing any exception (bug #341)")
# Test the result is what we made the user stat return
assert 3.235 == ui.get_fit_results().statval
def fit(self, conf = False):
ui.ignore(None, None)
ui.notice(self.start, self.stop)
self.set_source()
ui.fit(1)
if conf:
ui.conf()
res = ui.get_fit_results()
for line in (self.H2lines + self.nonH2lines):
sourcename = line['source'].split('.')[1]
print sourcename
for p in ['pos', 'fwhm', 'ampl']:
n = '{0}.{1}'.format(sourcename, p)
_place_val(line, p, ui.get_par(n).val)
self.const = ui.get_par('c1.c0').val
self.redchi2 = res.rstat
if conf:
res = ui.get_conf_results()
for line in (self.H2lines + self.nonH2lines):
sourcename = line['source'].split('.')[1]
for p in ['pos', 'fwhm', 'ampl']:
n = '{0}.{1}'.format(sourcename, p)
parmin, parmax = _parminmax(res, n)
line[p+'_max'] = parmax
line[p+'_min'] = parmin
# deal with error on const
parmin, parmax = _parminmax(res, 'c1.c0')
self.const_min = parmin
self.const_max = parmax
def test_background():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
kT_sim = 1.0
Z_sim = 0.0
norm_sim = 4.0e-2
nH_sim = 0.04
redshift = 0.01
exp_time = (200., "ks")
area = (1000., "cm**2")
fov = (10.0, "arcmin")
prng = 24
agen = ApecGenerator(0.05, 12.0, 5000, broadening=False)
spec = agen.get_spectrum(kT_sim, Z_sim, redshift, norm_sim)
spec.apply_foreground_absorption(norm_sim)
events = make_background(area, exp_time, fov, (30.0, 45.0), spec, prng=prng)
events.write_simput_file("bkgnd", overwrite=True)
instrument_simulator("bkgnd_simput.fits", "bkgnd_evt.fits",
exp_time, "sq_acisi_cy19", [30.0, 45.0],
overwrite=True, foreground=False, ptsrc_bkgnd=False,
instr_bkgnd=False,
prng=prng)
write_spectrum("bkgnd_evt.fits", "background_evt.pi", overwrite=True)
os.system("cp %s %s ." % (arf.filename, rmf.filename))
load_user_model(mymodel, "wapec")
add_user_pars("wapec", ["nH", "kT", "metallicity", "redshift", "norm"],
[0.01, 4.0, 0.2, redshift, norm_sim*0.8],
parmins=[0.0, 0.1, 0.0, -20.0, 0.0],
parmaxs=[10.0, 20.0, 10.0, 20.0, 1.0e9],
parfrozen=[False, False, False, True, False])
load_pha("background_evt.pi")
set_stat("cstat")
set_method("simplex")
ignore(":0.5, 8.0:")
set_model("wapec")
fit()
res = get_fit_results()
assert np.abs(res.parvals[0]-nH_sim)/nH_sim < 0.1
assert np.abs(res.parvals[1]-kT_sim)/kT_sim < 0.05
assert np.abs(res.parvals[2]-Z_sim) < 0.05
assert np.abs(res.parvals[3]-norm_sim)/norm_sim < 0.05
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_point_source():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
nH_sim = 0.02
norm_sim = 1.0e-4
alpha_sim = 0.95
redshift = 0.02
exp_time = (100., "ks")
area = (3000., "cm**2")
spec = Spectrum.from_powerlaw(alpha_sim, redshift, norm_sim,
emin=0.1, emax=11.5, nbins=2000)
spec.apply_foreground_absorption(nH_sim, model="tbabs")
positions = [(30.01, 45.0)]
events = make_point_sources(area, exp_time, positions, (30.0, 45.0),
spec, prng=prng)
events.write_simput_file("ptsrc", overwrite=True)
instrument_simulator("ptsrc_simput.fits", "ptsrc_evt.fits",
exp_time, "sq_aciss_cy19", [30.0, 45.0],
overwrite=True, foreground=False, ptsrc_bkgnd=False,
instr_bkgnd=False,
prng=prng)
write_spectrum("ptsrc_evt.fits", "point_source_evt.pi", overwrite=True)
os.system("cp %s %s ." % (arf.filename, rmf.filename))
load_user_model(mymodel, "tplaw")
add_user_pars("tplaw", ["nH", "norm", "redshift", "alpha"],
[0.02, norm_sim*0.8, redshift, 0.9],
parmins=[0.0, 0.0, 0.0, 0.1],
parmaxs=[10.0, 1.0e9, 10.0, 10.0],
parfrozen=[True, False, True, False])
load_pha("point_source_evt.pi")
set_stat("cstat")
set_method("simplex")
ignore(":0.4, 9.0:")
set_model("tplaw")
fit()
res = get_fit_results()
assert np.abs(res.parvals[0]-norm_sim)/norm_sim < 0.05
assert np.abs(res.parvals[1]-alpha_sim)/alpha_sim < 0.05
os.chdir(curdir)
shutil.rmtree(tmpdir)
def print_fit():
res = sau.get_fit_results()
print("Fit success : \t", res.succeeded)
print("Fit results:")
print("Numpoints :\t", res.numpoints)
print("dof :\t\t", res.dof)
print("Final statistic value : \t", res.statval)
print("Fitted parameters:")
for index, parn in enumerate(res.parnames):
print(parn, "\t\t{0:.3e}".format(res.parvals[index]))
def test_lev3fft(self):
self.run_thread("lev3fft", scriptname="bar.py")
# self.assertEqualWithinTol(ui.get_source().lhs.fwhm.val, 0.0034705, 1e-4)
# self.assertEqualWithinTol(ui.get_source().lhs.xpos.val, 150.016, 1e-4)
# self.assertEqualWithinTol(ui.get_source().lhs.ypos.val, 2.66587, 1e-4)
# self.assertEqualWithinTol(ui.get_source().lhs.ampl.val, 0.0117411, 1e-4)
# self.assertEqualWithinTol(ui.get_source().rhs.c0.val, 0.0190897, 1e-4)
self.assertEqualWithinTol(self.locals["src"].fwhm.val, 0.0034705, 1e-4)
self.assertEqualWithinTol(self.locals["src"].xpos.val, 150.016, 1e-4)
self.assertEqualWithinTol(self.locals["src"].ypos.val, 2.66587, 1e-4)
self.assertEqualWithinTol(self.locals["src"].ampl.val, 0.0117411, 1e-4)
self.assertEqualWithinTol(self.locals["bkg"].c0.val, 0.0190897, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().istatval, 19496.3, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().statval, 607.09, 1e-4)
self.assertEqual(ui.get_fit_results().numpoints, 3307)
self.assertEqual(ui.get_fit_results().dof, 3302)
def fit_adjuster_set(coeffs, adj_idxs, method='simplex'):
"""
Find best fit parameters for an arbitrary subset of adjustors
specified by the array ``adj_idxs``. The input ``coeffs`` are
the best-fit adjustor coefficients for the last iteration.
"""
import sherpa.astro.ui as ui
dummy_data = np.zeros(100)
dummy_times = np.arange(100)
ui.load_arrays(1, dummy_times, dummy_data)
ui.set_method(method)
ui.get_method().config.update(SHERPA_CONFIGS.get(method, {}))
calc_model = CalcModel()
ui.load_user_model(calc_model, 'axo_mod') # sets global axo_mod
parnames = []
for adj_idx in adj_idxs:
parnames.append('adj_{}'.format(adj_idx))
ui.add_user_pars('axo_mod', parnames)
ui.set_model(1, 'axo_mod')
coeffs = coeffs.copy() # Don't modify input coeffs
coeffs[coeffs < 0] = 0 # Don't allow negative coeffs
# Set frozen, min, and max attributes for each axo_mod parameter
for adj_idx, par in zip(adj_idxs, axo_mod.pars):
par.min = -1000
par.max = 1000
par.val = coeffs[adj_idx]
print 'Setting {} to {}'.format(adj_idx, par.val)
# Compute base adjusted displacements assuming all the fitted actuators
# have zero drive level.
coeffs[adj_idxs] = 0
base_adj_displ = M_2d.dot(coeffs)
m_2d = M_2d[:, adj_idxs].copy()
print m_2d.shape
calc_stat = CalcStat(base_adj_displ, m_2d, DISPL_X)
ui.load_user_stat('axo_stat', calc_stat, lambda x: np.ones_like(x))
ui.set_stat(axo_stat)
calc_model.set_calc_stat(calc_stat)
ui.fit(1)
# Update coeffs with the values determined in fitting
for adj_idx, par in zip(adj_idxs, axo_mod.pars):
coeffs[adj_idx] = abs(par.val)
return coeffs, ui.get_fit_results()
def test_pha_intro(self):
self.run_thread("pha_intro")
# astro.ui imported as ui, instead of
# being in global namespace
self.assertEqualWithinTol(ui.get_fit_results().statval, 37.9079, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 0.902569, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.651155, 1e-4)
self.assertEqualWithinTol(self.locals["p1"].gamma.val, 2.15852, 1e-4)
self.assertEqualWithinTol(self.locals["p1"].ampl.val, 0.00022484, 1e-4)
self.assertEqualWithinTol(ui.calc_photon_flux(), 0.000469964, 1e-4)
self.assertEqualWithinTol(ui.calc_energy_flux(), 9.614847e-13, 1e-4)
self.assertEqualWithinTol(ui.calc_data_sum(), 706.85714092, 1e-4)
self.assertEqualWithinTol(ui.calc_model_sum(), 638.45693377, 1e-4)
self.assertEqualWithinTol(ui.calc_source_sum(), 0.046996409, 1e-4)
self.assertEqualWithinTol(ui.eqwidth(self.locals["p1"], ui.get_source()), -0.57731725, 1e-4)
self.assertEqualWithinTol(
ui.calc_kcorr([1, 1.2, 1.4, 1.6, 1.8, 2], 0.5, 2),
[0.93341286, 0.93752836, 0.94325233, 0.94990140, 0.95678054, 0.96393515],
1e-4,
)
self.assertEqual(ui.get_fit_results().nfev, 22)
self.assertEqual(ui.get_fit_results().numpoints, 44)
self.assertEqual(ui.get_fit_results().dof, 42)
def check_chi2():
"""Execute this function after fitting to see if the
best-fit chi2 reported matches the formula coded here"""
import sherpa.astro.ui as sau
chi2 = sau.get_fit_results().statval
print('chi2 from fit: {0}'.format(chi2))
data = sau.get_dep()
model = sau.get_model_plot().y
error = np.where(model > data, sau.get_syserror(), sau.get_staterror())
chi = ((data - model) / error) # Chi per bin
chi2 = chi ** 2 # Chi^2 per bin
print('chi2 re-computed: {0}'.format(chi2.sum()))
def test_radpro(self):
self.run_thread('radpro')
self.assertEqualWithinTol(ui.get_fit_results().statval, 217.450, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 6.21287, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.0, 1e-4)
self.assertEqualWithinTol(self.locals['src'].r0.val, 125.829, 1e-4)
self.assertEqualWithinTol(self.locals['src'].beta.val, 4.1633, 1e-4)
self.assertEqualWithinTol(self.locals['src'].xpos.val, 0.0, 1e-4)
self.assertEqualWithinTol(self.locals['src'].ampl.val, 4.42821, 1e-4)
self.assertEqual(ui.get_fit_results().nfev,92)
self.assertEqual(ui.get_fit_results().numpoints,38)
self.assertEqual(ui.get_fit_results().dof,35)
def plot_chips(self, filename=''):
ui.plot_fit_delchi(1)
fig = plt.gcf()
ch.add_label(0.5, 0.97, self.name + '_'+filename,
["coordsys", ch.FRAME_NORM])
res = ui.get_fit_results()
ch.add_label(0.2,0.92, '\\chi^2_{{red}} = {0:3.1f}'.format(res.rstat),
["coordsys", ch.FRAME_NORM])
for i in range(len(res.parnames)):
ch.add_label(0.2,0.88-i*0.02,
'{0} = {1:8.5g}'.format(res.parnames[i],
res.parvals[i]), ["coordsys", ch.FRAME_NORM])
ch.print_window(os.path.join(self.plotpath,
self.name + filename + self.printfiletype),
{"clobber": True, 'dpi': 300})
def test_basic(self):
self.run_thread("basic")
self.assertEqualWithinTol(ui.get_fit_results().statval, 151.827, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 16.8697, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 3.68798e-28, 1e-4)
self.assertEqualWithinTol(self.locals["m1"].c0.val, 1.49843, 1e-4)
self.assertEqualWithinTol(self.locals["m1"].c1.val, 0.1447, 1e-4)
self.assertEqualWithinTol(self.locals["m1"].c2.val, 0.0322936, 1e-4)
self.assertEqualWithinTol(self.locals["m1"].c3.val, -0.00277729, 1e-4)
self.assertEqualWithinTol(self.locals["m2"].c0.val, 1.75548, 1e-4)
self.assertEqualWithinTol(self.locals["m2"].c1.val, 0.198455, 1e-4)
self.assertEqual(ui.get_fit_results().nfev, 9)
self.assertEqual(ui.get_fit_results().numpoints, 11)
self.assertEqual(ui.get_fit_results().dof, 9)
def test_eqwith_err(make_data_path, restore_xspec_settings):
def check(a0, a1, a2):
assert a0 == approx(0.16443033244310976, rel=1e-3)
assert a1 == approx(0.09205564216156815, rel=1e-3)
assert a2 == approx(0.23933118287470895, rel=1e-3)
ui.set_method('neldermead')
ui.set_stat('cstat')
ui.set_xsabund('angr')
ui.set_xsxsect('bcmc')
ui.load_data(make_data_path('12845.pi'))
ui.notice(0.5, 7)
ui.set_model("xsphabs.gal*xszphabs.zabs*(powlaw1d.p1+xszgauss.g1)")
ui.set_par(gal.nh, 0.08)
ui.freeze(gal)
ui.set_par(zabs.redshift, 0.518)
ui.set_par(g1.redshift, 0.518)
ui.set_par(g1.Sigma, 0.01)
ui.freeze(g1.Sigma)
ui.set_par(g1.LineE, min=6.0, max=7.0)
ui.fit()
numpy.random.seed(12345)
result = ui.eqwidth(p1, p1 + g1, error=True, niter=100)
check(result[0], result[1], result[2])
params = result[3]
numpy.random.seed(12345)
result = ui.eqwidth(p1, p1 + g1, error=True, params=params, niter=100)
check(result[0], result[1], result[2])
parvals = ui.get_fit_results().parvals
assert parvals[0] == approx(0.6111340686157877, rel=1.0e-3)
assert parvals[1] == approx(1.6409785803466297, rel=1.0e-3)
assert parvals[2] == approx(8.960926761312153e-05, rel=1.0e-3)
assert parvals[3] == approx(6.620017726014523, rel=1.0e-3)
assert parvals[4] == approx(1.9279114810359657e-06, rel=1.0e-3)
def test_basic(self):
# In data1.dat for this test, there is a comment with one
# word at the beginning -- deliberately would break when reading
# with DM ASCII kernel, but passes because we have Sherpa code
# to bypass that.
self.run_thread('basic')
self.assertEqualWithinTol(ui.get_fit_results().statval, 151.827, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 16.8697, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 3.68798e-28, 1e-4)
self.assertEqualWithinTol(self.locals['m1'].c0.val, 1.49843, 1e-4)
self.assertEqualWithinTol(self.locals['m1'].c1.val, 0.1447, 1e-4)
self.assertEqualWithinTol(self.locals['m1'].c2.val, 0.0322936, 1e-4)
self.assertEqualWithinTol(self.locals['m1'].c3.val, -0.00277729, 1e-4)
self.assertEqualWithinTol(self.locals['m2'].c0.val, 1.75548, 1e-4)
self.assertEqualWithinTol(self.locals['m2'].c1.val, 0.198455, 1e-4)
self.assertEqual(ui.get_fit_results().nfev,9)
self.assertEqual(ui.get_fit_results().numpoints,11)
self.assertEqual(ui.get_fit_results().dof,9)
def test_radpro_dm(self):
# This test is completely redundant to test_radpro above.
# The only difference is that here I test if using DM syntax
# in the file name returns the correct arrays from CRATES.
# Since any other I/O backend would not understand DM syntax,
# I make this test a no-op unless CRATES is used as the I/O
# backend. SMD 05/23/13
if (True == self.is_crates_io):
self.run_thread('radpro_dm')
self.assertEqualWithinTol(ui.get_fit_results().statval, 217.450, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 6.21287, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.0, 1e-4)
self.assertEqualWithinTol(self.locals['src'].r0.val, 125.829, 1e-4)
self.assertEqualWithinTol(self.locals['src'].beta.val, 4.1633, 1e-4)
self.assertEqualWithinTol(self.locals['src'].xpos.val, 0.0, 1e-4)
self.assertEqualWithinTol(self.locals['src'].ampl.val, 4.42821, 1e-4)
self.assertEqual(ui.get_fit_results().nfev,92)
self.assertEqual(ui.get_fit_results().numpoints,38)
self.assertEqual(ui.get_fit_results().dof,35)
b1, b2 = pars
return BoxBOD.model(x, b1, b2)
ui.load_user_model(boxbod_func, "boxbod")
ui.add_user_pars("boxbod", ["b1", "b2"])
bb = boxbod
ui.set_model(bb)
bb.b1, bb.b2 = BoxBOD.p0[0], BoxBOD.p0[1]
# Perform fit
ui.set_stat('chi2datavar')
#ui.set_method('levmar') # ['levmar', 'moncar', 'neldermead', 'simplex']
ui.set_method_opt('xtol', 1e-10)
ui.fit() # Compute best-fit parameters
ui.set_covar_opt('eps', 1e-5) # @todo: Why does this parameter have no effect
ui.covariance() # Compute covariance matrix (i.e. errors)
#ui.conf() # Compute profile errors
#ui.show_all() # Print a very nice summary of your session to less
# Report results
fr = ui.get_fit_results()
cr = ui.get_covar_results()
# Report results (we have to apply the s factor ourselves)
popt = np.array(fr.parvals)
chi2 = fr.statval
s_factor = np.sqrt(chi2 / fr.dof)
perr = s_factor * np.array(cr.parmaxes)
report_results('sherpa', popt, perr, chi2)
