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)
