def test_conversion_fits2hdf(xy_fitted_joint_likelihood):
jl, _, _ = xy_fitted_joint_likelihood # type: JointLikelihood, None, None
jl.restore_best_fit()
ar = jl.results # type: MLEResults
ar2 = jl.results
analysis_set = AnalysisResultsSet([ar, ar2])
analysis_set.set_bins("testing", [-1, 1], [3, 5], unit="s")
temp_file = "_analysis_set_test.fits"
analysis_set.write_to(temp_file, overwrite=True)
convert_fits_analysis_result_to_hdf(temp_file)
analysis_set_reloaded = load_analysis_results_hdf("_analysis_set_test.h5")
# Test they are the same
assert len(analysis_set_reloaded) == len(analysis_set)
for res1, res2 in zip(analysis_set, analysis_set_reloaded):
_results_are_same(res1, res2)
def test_analysis_set_input_output_hdf(xy_fitted_joint_likelihood):
# Collect twice the same analysis results just to see if we can
# save them in a file as set of results
jl, _, _ = xy_fitted_joint_likelihood # type: JointLikelihood, None, None
jl.restore_best_fit()
ar = jl.results # type: MLEResults
ar2 = jl.results
analysis_set = AnalysisResultsSet([ar, ar2])
analysis_set.set_bins("testing", [-1, 1], [3, 5], unit="s")
temp_file = "_analysis_set_test_hdf"
analysis_set.write_to(temp_file, overwrite=True, as_hdf=True)
analysis_set_reloaded = load_analysis_results_hdf(temp_file)
os.remove(temp_file)
# Test they are the same
assert len(analysis_set_reloaded) == len(analysis_set)
for res1, res2 in zip(analysis_set, analysis_set_reloaded):
_results_are_same(res1, res2)
def test_analysis_results_input_output_hdf(xy_fitted_joint_likelihood):
jl, _, _ = xy_fitted_joint_likelihood # type: JointLikelihood, None, None
jl.restore_best_fit()
ar = jl.results # type: MLEResults
temp_file = "__test_mle.h5"
ar.write_to(temp_file, overwrite=True, as_hdf=True)
ar_reloaded = load_analysis_results_hdf(temp_file)
os.remove(temp_file)
_results_are_same(ar, ar_reloaded)