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Following PR #61, in the Playing with Toys notebook, in the Hypothesis Testing (low stats) section using the toybased calculator is yielding nans in the calculation:
CLs_obs, CLs_exp = pyhf.infer.hypotest(
1.0, # null hypothesis
[5.0, 7.0] + model.config.auxdata,
model,
test_stat="qtilde",
return_expected_set=True,
calctype="toybased",
ntoys=1000,
track_progress=False,
)
print(f" Observed CLs: {CLs_obs:.4f}")
for expected_value, n_sigma in zip(CLs_exp, np.arange(-2, 3)):
print(f"Expected CLs({n_sigma:2d} σ): {expected_value:.4f}")/usr/local/venv/lib/python3.10/site-packages/scipy/optimize/_optimize.py:353: RuntimeWarning: Values in x were outside bounds during a minimize step, clipping to bounds
warnings.warn("Values in x were outside bounds during a " Observed CLs: nan
Expected CLs(-2 σ): 0.0000
Expected CLs(-1 σ): 0.0452
Expected CLs( 0 σ): 0.1756
Expected CLs( 1 σ): 0.4375
Expected CLs( 2 σ): 1.0000
/usr/local/venv/lib/python3.10/site-packages/pyhf/infer/calculators.py:864: RuntimeWarning: invalid value encountered in divide
CLs = tensorlib.astensor(CLsb / CLb)Metadata
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