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Add 1 / r^2 prior on magnitude of the vector
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1 changed files with 8 additions and 1 deletions
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@ -925,10 +925,17 @@ def PV_validation_model(models, distmod_hyperparams_per_model,
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inference_method : str
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Either `mike` or `bayes`.
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"""
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ll = 0.0
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field_calibration_params = sample_calibration(
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**field_calibration_hyperparams)
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ll = 0.0
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# We sample the components of Vext with a uniform prior, which means
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# there is a |Vext|^2 prior, we correct for this so that the sampling
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# is effecitvely uniformly in magnitude of Vext and angles.
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if "Vext" in field_calibration_params:
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ll -= jnp.log(jnp.sum(field_calibration_params["Vext"]**2))
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for n in range(len(models)):
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model = models[n]
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name = model.name
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