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add one-sided and double-sided interval distinction

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Никита Тырин 2025-05-23 12:19:03 +03:00
parent 03cdfa01b0
commit 5e0ecc9cc9
1 changed files with 25 additions and 2 deletions
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27
views.py
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@ -251,6 +251,7 @@ class UpperLimitView(APIView):
# BAYESIAN IMPLEMENTATION VIA POISSON_CONF_INTERVAL
# **************************************************************
# double sided interval
low, high = poisson_conf_interval(
n=N,
background=B,
@ -262,26 +263,42 @@ class UpperLimitView(APIView):
bayesian_count_ul = high[0]
bayesian_count_ll = low[0]
bayesian_count_UL = (
sp.gammaincinv(
N + 1, confidence_level * sp.gammaincc(N + 1, B) + sp.gammainc(N + 1, B)
)
- B
)
bayesian_rate_ul = bayesian_count_ul / t / EEF # count rate limits
bayesian_rate_ll = bayesian_count_ll / t / EEF
bayesian_rate_UL = bayesian_count_UL / t / EEF
bayesian_flux_ul = bayesian_rate_ul * ECF # flux limits
bayesian_flux_ll = bayesian_rate_ll * ECF
bayesian_flux_UL = bayesian_rate_UL * ECF
# CLASSICAL IMPLEMENTATION VIA GAMMAINCCINV
# ****************************************************************
classic_count_ul = sp.gammainccinv(N + 1, 1 - confidence_level) - B
classic_count_ll = sp.gammainccinv(N, confidence_level) - B
# confidence level for the double sided interval
cl2 = (1 + confidence_level) / 2
# double sided interval
classic_count_ul = sp.gammainccinv(N + 1, 1 - cl2) - B
classic_count_ll = sp.gammainccinv(N, cl2) - B
# one sided interval
classic_count_UL = sp.gammainccinv(N + 1, 1 - confidence_level) - B
if not np.isfinite(classic_count_ll) or classic_count_ll < 0:
classic_count_ll = 0.0
classic_rate_ul = classic_count_ul / t / EEF # count rate limits
classic_rate_ll = classic_count_ll / t / EEF
classic_rate_UL = classic_count_UL / t / EEF
classic_flux_ul = classic_rate_ul * ECF # flux limits
classic_flux_ll = classic_rate_ll * ECF
classic_flux_UL = classic_rate_UL * ECF
# FLUX ESTIMATION
# ****************************************************************
@ -392,17 +409,23 @@ class UpperLimitView(APIView):
# frequentist limits
"ClassicUpperLimit": classic_count_ul,
"ClassicLowerLimit": classic_count_ll,
"ClassicOneSideUL": classic_count_UL,
"ClassicCountRateUpperLimit": classic_rate_ul,
"ClassicCountRateLowerLimit": classic_rate_ll,
"ClassicCountRateOneSideUL": classic_rate_UL,
"ClassicFluxUpperLimit": classic_flux_ul,
"ClassicFluxLowerLimit": classic_flux_ll,
"ClassicFluxOneSideUL": classic_flux_UL,
# bayesian limits
"BayesianUpperLimit": bayesian_count_ul,
"BayesianLowerLimit": bayesian_count_ll,
"BayesianOneSideUL": bayesian_count_UL,
"BayesianCountRateUpperLimit": bayesian_rate_ul,
"BayesianCountRateLowerLimit": bayesian_rate_ll,
"BayesianCountRateOneSideUL": bayesian_rate_UL,
"BayesianFluxUpperLimit": bayesian_flux_ul,
"BayesianFluxLowerLimit": bayesian_flux_ll,
"BayesianFluxOneSideUL": bayesian_flux_UL,
# flux 'center value' estimate
"FluxEstimate": Flux,
# raw data