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')