def test_paramprompt_eof(caplog):
"""What happens when we end early?"""
s = Session()
s._add_model_types(sherpa.models.basic)
cpt1 = s.create_model_component('const1d', 'bob')
cpt2 = s.create_model_component('gauss1d', 'fred')
s.paramprompt(True)
assert len(caplog.records) == 0
with pytest.raises(EOFError):
with SherpaVerbosity('INFO'):
with patch("sys.stdin", StringIO("\n5,1,5\n2\n")):
s.set_source(bob + fred)
assert len(caplog.records) == 0
assert cpt1.c0.val == pytest.approx(1)
assert cpt1.c0.min < -3e38
assert cpt1.c0.max > 3e38
assert cpt2.fwhm.val == pytest.approx(5)
assert cpt2.fwhm.min == pytest.approx(1)
assert cpt2.fwhm.max == pytest.approx(5)
assert cpt2.pos.val == pytest.approx(2)
assert cpt2.pos.min < -3e38
assert cpt2.pos.max > 3e38
assert cpt2.ampl.val == pytest.approx(1)
assert cpt2.ampl.min < -3e38
assert cpt2.ampl.max > 3e38
def test_paramprompt_single_parameter_check_invalid_max_out_of_bound(caplog):
"""Note this creates two warnings"""
s = Session()
s._add_model_types(sherpa.models.basic)
s.paramprompt(True)
assert len(caplog.records) == 0
with SherpaVerbosity('INFO'):
with patch("sys.stdin", StringIO(",,typo\n,,-200")):
s.set_source("scale1d.bob")
assert len(caplog.records) == 2
lname, lvl, msg = caplog.record_tuples[0]
assert lname == "sherpa.ui.utils"
assert lvl == logging.INFO
assert msg == "Please provide a float value; could not convert string to float: 'typo'"
lname, lvl, msg = caplog.record_tuples[1]
assert lname == "sherpa.models.parameter"
assert lvl == logging.WARN
assert msg == "parameter bob.c0 greater than new maximum; bob.c0 reset to -200"
mdl = s.get_model_component('bob')
assert mdl.c0.val == pytest.approx(-200)
assert mdl.c0.min < -3e38
assert mdl.c0.max == pytest.approx(-200)
def test_paramprompt_multi_parameter(caplog):
"""Check that paramprompt works with multiple parameters"""
s = Session()
s._add_model_types(sherpa.models.basic)
cpt1 = s.create_model_component('const1d', 'bob')
cpt2 = s.create_model_component('gauss1d', 'fred')
s.paramprompt(True)
assert len(caplog.records) == 0
with SherpaVerbosity('INFO'):
with patch("sys.stdin", StringIO("\n5,1,5\n\n-5, -5, 0")):
s.set_source(bob + fred)
assert len(caplog.records) == 0
assert cpt1.c0.val == pytest.approx(1)
assert cpt1.c0.min < -3e38
assert cpt1.c0.max > 3e38
assert cpt2.fwhm.val == pytest.approx(5)
assert cpt2.fwhm.min == pytest.approx(1)
assert cpt2.fwhm.max == pytest.approx(5)
assert cpt2.pos.val == pytest.approx(0)
assert cpt2.pos.min < -3e38
assert cpt2.pos.max > 3e38
assert cpt2.ampl.val == pytest.approx(-5)
assert cpt2.ampl.min == pytest.approx(-5)
assert cpt2.ampl.max == pytest.approx(0)
def test_paramprompt_single_parameter_check_too_many_commas(caplog):
"""Check we tell users there was a problem"""
s = Session()
s._add_model_types(sherpa.models.basic)
s.paramprompt(True)
assert len(caplog.records) == 0
with SherpaVerbosity('INFO'):
with patch("sys.stdin", StringIO(",,,,\n12")):
s.set_source("scale1d.bob")
assert len(caplog.records) == 1
lname, lvl, msg = caplog.record_tuples[0]
assert lname == "sherpa.ui.utils"
assert lvl == logging.INFO
assert msg == "Error: Please provide a comma-separated list of floats; e.g. val,min,max"
mdl = s.get_model_component('bob')
assert mdl.c0.val == pytest.approx(12)
assert mdl.c0.min < -3e38
assert mdl.c0.max > 3e38
# remove the bob symbol from the global table
s.clean()
def test_est_errors_works_single_parameter(mdlcls, method, getter, clean_ui):
"""This is issue #1397.
Rather than require XSPEC, we create a subclass of the Parameter
class to check it works. We are not too concerned with the actual
results hence the relatively low tolerance on the numeric checks.
"""
mdl = mdlcls()
ui.load_arrays(1, [1, 2, 3, 4], [4, 2, 1, 3.5])
ui.set_source(mdl)
with SherpaVerbosity("ERROR"):
ui.fit()
# this is where #1397 fails with Const2
method(mdl.con)
atol = 1e-4
assert ui.calc_stat() == pytest.approx(0.7651548418626658, abs=atol)
results = getter()
assert results.parnames == (f"{mdl.name}.con", )
assert results.sigma == pytest.approx(1.0)
assert results.parvals == pytest.approx((2.324060647544594, ), abs=atol)
# The covar errors are -/+ 1.3704388763054511
# conf -1.3704388763054511 / +1.3704388763054514
# proj -1.3704388762971822 / +1.3704388763135826
#
err = 1.3704388763054511
assert results.parmins == pytest.approx((-err, ), abs=atol)
assert results.parmaxes == pytest.approx((err, ), abs=atol)
def test_paramprompt_single_parameter_check_invalid_max(caplog):
s = Session()
s._add_model_types(sherpa.models.basic)
s.paramprompt(True)
assert len(caplog.records) == 0
with SherpaVerbosity('INFO'):
with patch("sys.stdin", StringIO("-2,,typo\n-200,,-2")):
s.set_source("scale1d.bob")
assert len(caplog.records) == 1
lname, lvl, msg = caplog.record_tuples[0]
assert lname == "sherpa.ui.utils"
assert lvl == logging.INFO
assert msg == "Please provide a float value; could not convert string to float: 'typo'"
mdl = s.get_model_component('bob')
assert mdl.c0.val == pytest.approx(-200)
assert mdl.c0.min < -3e38
assert mdl.c0.max == pytest.approx(-2)
# remove the bob symbol from the global table
s.clean()
def check_imgdata_unconvolved(caplog):
"""What is the behavior when we do not add the PSF to plot_pvalue?
Note we add a check of the screen output here.
"""
# include a check of the screen output
#
with caplog.at_level('INFO', logger='sherpa'):
with SherpaVerbosity('INFO'):
ui.plot_pvalue(c1, c1 + g1, num=40, bins=5)
assert len(caplog.records) == 1
lname, lvl, msg = caplog.record_tuples[0]
assert lname == 'sherpa.ui.utils'
assert lvl == logging.INFO
# Do not use equality tests for the numeric values in case
# there are numpy-version differences in the number of
# significant figures.
#
toks = msg.split('\n')
assert len(toks) == 5
assert toks[0] == 'Likelihood Ratio Test'
assert toks[1].startswith('null statistic = 2391.2696')
assert toks[2].startswith('alt statistic = 353.82')
assert toks[3].startswith('likelihood ratio = 2037.446')
assert toks[4] == 'p-value < 0.025'
tmp = ui.get_pvalue_results()
assert tmp.null == pytest.approx(2391.2696310023503)
assert tmp.alt == pytest.approx(353.8235336370698)
assert tmp.lr == pytest.approx(2037.4460973652804)
assert tmp.samples.shape == (40, 1)
assert tmp.stats.shape == (40, 2)
assert tmp.ratios.shape == (40, )
tmp = ui.get_pvalue_plot(2037.4460973652804)
assert tmp.lr == pytest.approx(2037.4460973652804)
assert tmp.xlabel == 'Likelihood Ratio'
assert tmp.ylabel == 'Frequency'
assert tmp.title == 'Likelihood Ratio Distribution'
assert tmp.ratios.shape == (40, )
assert tmp.xlo.shape == (6, )
assert tmp.xhi.shape == (6, )
assert tmp.y.shape == (6, )
def test_logging_verbosity_contextmanager(caplog):
with caplog.at_level(logging.INFO, logger='sherpa'):
logger = logging.getLogger('sherpa.some_module')
logger.warning('1: should be seen')
assert len(caplog.records) == 1
with SherpaVerbosity('ERROR'):
logger.warning('2: Should not be seen')
assert len(caplog.records) == 1
logger.warning('3: should be seen')
assert len(caplog.records) == 2
def test_paramprompt_single_parameter_combo_works(caplog):
s = Session()
s._add_model_types(sherpa.models.basic)
s.paramprompt(True)
assert len(caplog.records) == 0
with SherpaVerbosity('INFO'):
with patch("sys.stdin", StringIO("-2,-10,10")):
s.set_source("scale1d.bob")
assert len(caplog.records) == 0
mdl = s.get_model_component('bob')
assert mdl.c0.val == pytest.approx(-2)
assert mdl.c0.min == pytest.approx(-10)
assert mdl.c0.max == pytest.approx(10)
def test_load_data(loader, make_data_path, clean_astro_ui, caplog):
"""Ensure that loading a single file to a non-integer id works.
This is just to make sure that the support for PHA2 files in both
load_data and load_pha does not change the single-file case.
"""
infile = make_data_path('3c273.pi')
bgfile = make_data_path('3c273_bg.pi')
arf = make_data_path('3c273.arf')
rmf = make_data_path('3c273.rmf')
assert ui.list_data_ids() == []
with SherpaVerbosity('INFO'):
loader('foo', infile)
assert ui.list_data_ids() == ['foo']
msg1 = f"systematic errors were not found in file '{infile}'"
msg2 = f"statistical errors were found in file '{infile}' \n" + \
"but not used; to use them, re-read with use_errors=True"
msg3 = f"read ARF file {arf}"
msg4 = f"read RMF file {rmf}"
msg5 = f"systematic errors were not found in file '{bgfile}'"
msg6 = f"statistical errors were found in file '{bgfile}' \n" + \
"but not used; to use them, re-read with use_errors=True"
msg7 = f"read background file {bgfile}"
assert caplog.record_tuples[0] == ('sherpa.astro.io', logging.WARNING,
msg1)
assert caplog.record_tuples[1] == ('sherpa.astro.io', logging.INFO, msg2)
assert caplog.record_tuples[2] == ('sherpa.astro.io', logging.INFO, msg3)
assert caplog.record_tuples[3] == ('sherpa.astro.io', logging.INFO, msg4)
assert caplog.record_tuples[4] == ('sherpa.astro.io', logging.WARNING,
msg5)
assert caplog.record_tuples[5] == ('sherpa.astro.io', logging.INFO, msg6)
assert caplog.record_tuples[6] == ('sherpa.astro.io', logging.INFO, msg7)
assert len(caplog.records) == 7
def test_paramprompt_single_parameter_max_works(caplog):
s = Session()
s._add_model_types(sherpa.models.basic)
s.paramprompt(True)
assert len(caplog.records) == 0
with SherpaVerbosity('INFO'):
with patch("sys.stdin", StringIO(",,100")):
s.set_source("scale1d.bob")
assert len(caplog.records) == 0
mdl = s.get_model_component('bob')
assert mdl.c0.val == pytest.approx(1)
assert mdl.c0.min < -3e38
assert mdl.c0.max == pytest.approx(100)
# remove the bob symbol from the global table
s.clean()
report('pha.get_filter()')
pha.units = 'channel'
report('pha.get_filter()')
plot.prepare(pha)
plot.plot(xlog=True, ylog=True)
pha.units = 'energy'
savefig('pha_filtered_channel.png')
# Grouping
os.chdir(basedir)
print(f'--> jumping to {basedir}')
from sherpa.utils.logging import SherpaVerbosity
with SherpaVerbosity('ERROR'):
pha1 = read_pha('3c273.pi')
pha2 = read_pha('3c273.pi')
pha3 = read_pha('3c273.pi')
os.chdir(cwd)
pha1.notice(0.5, 7)
pha2.notice(0.5, 7)
pha3.notice(0.5, 7)
pha1.ungroup()
pha3.group_counts(40)
plt.subplot(2, 1, 1)
plot.prepare(pha1)
def test_write_pha_fits_with_extras_roundtrip(tmp_path, caplog):
"""PHA-I with grouping/quality/errors/header
This covers issue #488 - that is, should the output use the correct
data type for columns? At present the code does not.
"""
chans = np.arange(1, 5, dtype=np.int32)
counts = np.asarray([1, 0, 3, 2], dtype=np.int32)
grouping = np.asarray([1, -1, 1, 1], dtype=np.int16)
quality = np.asarray([0, 0, 0, 2], dtype=np.int16)
etime = 1023.4
bscal = 0.05
ascal = np.asarray([1, 1, 0.9, 0.9])
hdr = {"TELESCOP": "CHANDRA", "INSTRUME": "ACIS", "FILTER": "NONE",
"CHANTYPE": "PI",
"DETCHANS": 10, # This intentionally does not match the data
"OBJECT": "Made up source",
"CORRFILE": "None",
# This will cause a warning when reading in the file
"ANCRFILE": "made-up-ancrfile.fits",
# "structural keywords" which match DETCHANS
"TLMIN1": 1, "TLMAX1": 10}
pha = DataPHA("testy",
chans.astype(np.float64),
counts.astype(np.float32),
grouping=grouping.astype(np.float32),
quality=quality.astype(np.float64),
exposure=etime,
backscal=bscal,
areascal=ascal,
header=hdr)
outfile = tmp_path / "out.pi"
io.write_pha(str(outfile), pha, ascii=False, clobber=False)
pha = None
assert len(caplog.record_tuples) == 0
with SherpaVerbosity("INFO"):
inpha = io.read_pha(str(outfile))
assert len(caplog.record_tuples) == 1
lname, lvl, msg = caplog.record_tuples[0]
assert lname == "sherpa.astro.io"
assert lvl == logging.WARNING
# message depends on the backend
if backend_is("crates"):
assert msg.startswith("File ")
assert msg.endswith("/made-up-ancrfile.fits does not exist.")
elif backend_is("pyfits"):
assert msg.startswith("file '")
assert msg.endswith("/made-up-ancrfile.fits' not found")
assert isinstance(inpha, DataPHA)
assert inpha.channel == pytest.approx(chans)
assert inpha.counts == pytest.approx(counts)
assert inpha.grouping == pytest.approx(grouping)
assert inpha.quality == pytest.approx(quality)
assert inpha.exposure == pytest.approx(etime)
assert inpha.backscal == pytest.approx(bscal)
assert inpha.areascal == pytest.approx(ascal)
for field in ["staterror", "syserror", "bin_lo", "bin_hi"]:
assert getattr(inpha, field) is None
assert inpha.grouped
assert not inpha.subtracted
assert inpha.units == "channel"
assert inpha.rate
assert inpha.plot_fac == 0
assert inpha.response_ids == []
assert inpha.background_ids == []
if backend_is("crates"):
check_write_pha_fits_with_extras_roundtrip_crates(outfile, etime, bscal)
elif backend_is("pyfits"):
check_write_pha_fits_with_extras_roundtrip_pyfits(outfile, etime, bscal)
else:
raise RuntimeError(f"Unknown io backend: {io.backend}")
