def test_resample_rmd(make_data_path):
infile = make_data_path('gro_delta.txt')
ui.load_ascii_with_errors(1, infile, delta=True, func=rms)
base = ui.get_data(1)
data = Data1DAsymmetricErrs(2, base.x, base.y, base.elo, base.ehi,
base.staterror, base.syserror)
resample_data(data, RESAMPLE_BENCH, RESULTS_BENCH_RMS)
def test_AsymmetricErrors_resample_avg(self):
ui.load_ascii_with_errors(1, self.gro_delta_fname, delta=True)
tmp = ui.get_data(1)
data = Data1DAsymmetricErrs(1, tmp.x, tmp.y, tmp.elo,
tmp.ehi, tmp.staterror, tmp.syserror)
self.resample_data(data, self._resample_bench,
self._results_bench_avg)
def test_constructor_rms(make_data_path):
infile = make_data_path('gro_delta.txt')
ui.load_ascii_with_errors(1, infile, delta=True, func=rms)
base = ui.get_data(1)
data = Data1DAsymmetricErrs(2, base.x, base.y, base.elo, base.ehi,
base.staterror, base.syserror)
fit_asymmetric_err(RESULTS_BENCH_RMS, data)
def test_AsymmetricErrs_rms(self):
ui.load_ascii_with_errors(1, self.gro_delta_fname, func=self.rms,
delta=True)
tmp = ui.get_data(1)
data = Data1DAsymmetricErrs(2, tmp.x, tmp.y, tmp.elo,
tmp.ehi, tmp.staterror, tmp.syserror)
self.fit_asymmetric_err(self._results_bench_rms, data)
def test_gro_delta_rms(self):
ui.load_ascii_with_errors(1,
self.gro_delta_fname,
func=self.rms,
delta=True)
data = ui.get_data(1)
self.fit_asymmetric_err(self._results_bench_rms, data)
def test_ui(make_data_path):
infile = make_data_path('gro_delta.txt')
ui.load_ascii_with_errors(1, infile, delta=True)
ui.set_stat('leastsq')
ui.set_model('powlaw1d.p1')
ui.fit()
sample = ui.resample_data(1, 10, seed=123)
for p in ['p1.gamma', 'p1.ampl']:
assert sample[p] == pytest.approx(RESAMPLE_BENCH_10[p], rel=1e-4)
def test_warning(make_data_path):
infile = make_data_path('gro.txt')
ui.load_ascii_with_errors(1, infile)
powlaw1d = PowLaw1D('p1')
ui.set_model(powlaw1d)
ui.fit()
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
ui.resample_data(1, 3)
assert len(w) == 0
def test_warning(self):
ui.load_ascii_with_errors(1, self.gro_fname)
data = ui.get_data(1)
powlaw1d = PowLaw1D('p1')
ui.set_model(powlaw1d)
fit = Fit(data, powlaw1d)
results = fit.fit()
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
ui.resample_data(1, 3)
assert len(w) == 0
def test_ui(self, tol=1.0e-3):
# from shepa.astro.ui import *
ui.load_ascii_with_errors(1, self.gro_delta_fname, delta=True)
ui.set_stat('leastsq')
ui.set_model('powlaw1d.p1')
ui.fit()
sample = ui.resample_data(1, 10, seed=123)
self.assertEqualWithinTol(self._resample_bench_10['p1.gamma'],
sample['p1.gamma'])
self.assertEqualWithinTol(self._resample_bench_10['p1.ampl'],
sample['p1.ampl'])
def test_load_ascii_rms(filename, delta, make_data_path):
infile = make_data_path(filename)
ui.load_ascii_with_errors(1, infile, delta=delta, func=rms)
data = ui.get_data(1)
fit_asymmetric_err(RESULTS_BENCH_RMS, data)
def test_load_ascii_defaultid(filename, delta, make_data_path):
"""Use the default id"""
infile = make_data_path(filename)
ui.load_ascii_with_errors(infile, delta=delta)
data = ui.get_data()
fit_asymmetric_err(RESULTS_BENCH_AVG, data)
def test_gro_ascii(self):
ui.load_ascii_with_errors(1, self.gro_fname, delta=False)
data = ui.get_data(1)
self.fit_asymmetric_err(self._results_bench_avg, data)
