def test_parameter_linked():
p = Parameter('foo', 'x1', 1.2)
q = Parameter('bar', 'x2', 2.2)
p.val = 2 + q
r = p._repr_html_()
assert r is not None
assert '<summary>Parameter</summary>' in r
assert '<table class="model">' in r
assert '<th class="model-odd">foo</th><td>x1</td><td>linked</td><td>4.2</td><td colspan="2">⇐ 2 + bar.x2</td><td></td></tr>' in r
set_stat('chi2gehrels')
pl = get_fit_plot(id)
myplot = dict(counts=int(get_data(id).counts.sum()),
background_counts=int(get_bkg(id).counts.sum()),
data=pl.dataplot.y.tolist(),
dataerr=pl.dataplot.yerr.tolist(),
x=pl.dataplot.x.tolist(),
xerr=pl.dataplot.xerr.tolist(),
instances=[])
for row in a.get_equal_weighted_posterior():
for p, v in zip(parameters, row):
p.val = v
pl = get_fit_plot(id)
myplot['instances'].append(pl.modelplot.y.tolist())
srcnh.val = 20
pl = get_fit_plot(id)
myplot['unabsorbed'] = pl.modelplot.y.tolist()
galabso.nH = 0
pl = get_fit_plot(id)
myplot['nogal'] = pl.modelplot.y.tolist()
set_full_model(id, get_bkg_model(id) * get_bkg_scale(id))
pl = get_fit_plot(id)
myplot['background'] = pl.modelplot.y.tolist()
set_stat('cstat')
json.dump(myplot, open('%sfit.json' % outputfiles_basename, 'w'))
if not os.path.exists('%sfit2.json' % outputfiles_basename) and id2:
print('collecting fit2 plot data')
set_analysis(id2, 'ener', 'counts')
print('collecting fit plot data')
set_analysis(id, 'ener', 'counts')
group_counts(id, 40)
set_stat('chi2gehrels')
pl = get_fit_plot(id)
myplot = dict(counts=int(get_data(id).counts.sum()), background_counts=int(get_bkg(id).counts.sum()),
data=pl.dataplot.y.tolist(), dataerr=pl.dataplot.yerr.tolist(),
x=pl.dataplot.x.tolist(), xerr=pl.dataplot.xerr.tolist(),
instances=[])
for row in a.get_equal_weighted_posterior():
for p, v in zip(parameters, row):
p.val = v
pl = get_fit_plot(id)
myplot['instances'].append(pl.modelplot.y.tolist())
srcnh.val = 20
pl = get_fit_plot(id)
myplot['unabsorbed'] = pl.modelplot.y.tolist()
galabso.nH = 0
pl = get_fit_plot(id)
myplot['nogal'] = pl.modelplot.y.tolist()
set_full_model(id, get_bkg_model(id) * get_bkg_scale(id))
pl = get_fit_plot(id)
myplot['background'] = pl.modelplot.y.tolist()
set_stat('cstat')
json.dump(myplot, open('%sfit.json' % outputfiles_basename, 'w'))
if not os.path.exists('%sfit2.json' % outputfiles_basename) and id2:
print('collecting fit2 plot data')
set_analysis(id2, 'ener', 'counts')
