def test_sourceplot_wavelength_counts(caplog): """test_sourceplot_wavelength but when rate=False is chosen""" bins = np.arange(0.1, 10.1, 0.1) data = DataPHA('', np.arange(10), np.ones(10), bin_lo=bins[:-1].copy(), bin_hi=bins[1:].copy()) data.units = "wave" data.rate = False # use a model that is "okay" to use with keV bins # m1 = Const1D('bgnd') m2 = Gauss1D('abs1') src = 100 * m1 * (1 - m2) * 10000 m1.c0 = 0.01 m2.pos = 5.0 m2.fwhm = 4.0 m2.ampl = 0.1 sp = SourcePlot() with caplog.at_level(logging.INFO, logger='sherpa'): sp.prepare(data, src) assert len(caplog.records) == 0 check_sourceplot_wavelength(sp)
def test_sourceplot_counts(caplog): """test_sourceplot but when rate=False is chosen""" bins = np.arange(0.1, 10.1, 0.1) data = DataPHA('', np.arange(10), np.ones(10), bin_lo=bins[:-1].copy(), bin_hi=bins[1:].copy()) data.units = "energy" data.rate = False # Note that the model evaluation in done in Angstroms # m1 = Const1D('bgnd') m2 = Gauss1D('abs1') src = 100 * m1 * (1 - m2) * 10000 m1.c0 = 0.01 m2.pos = 5.0 m2.fwhm = 4.0 m2.ampl = 0.1 sp = SourcePlot() with caplog.at_level(logging.INFO, logger='sherpa'): sp.prepare(data, src) assert len(caplog.records) == 0 check_sourceplot_energy(sp)