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lines changed Original file line number Diff line number Diff line change
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+ import warnings
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+
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import arviz as az
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import numpy as np
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import pymc as pm
@@ -146,6 +148,8 @@ def fit_INLA(
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return_latent_posteriors : bool = True ,
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** sampler_kwargs ,
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) -> az .InferenceData :
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+ warnings .warn ("Currently only valid for a nested normal model. WIP." , UserWarning )
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+
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model = pm .modelcontext (model )
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# Check if latent field is Gaussian
Original file line number Diff line number Diff line change @@ -26,6 +26,7 @@ def rng():
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return np .random .default_rng (seed )
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+ @pytest .mark .filterwarnings ("ignore:Currently only valid for a nested normal model. WIP." )
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def test_non_gaussian_latent (rng ):
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"""
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INLA should raise an error if trying to use a non-Gaussian latent
@@ -45,6 +46,7 @@ def test_non_gaussian_latent(rng):
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pmx .fit (method = "INLA" , x = x )
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+ @pytest .mark .filterwarnings ("ignore:Currently only valid for a nested normal model. WIP." )
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def test_non_precision_MvNormal (rng ):
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"""
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INLA should raise an error if trying to use a latent not in precision form
@@ -67,6 +69,7 @@ def test_non_precision_MvNormal(rng):
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pmx .fit (method = "INLA" , x = x )
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+ @pytest .mark .filterwarnings ("ignore:Currently only valid for a nested normal model. WIP." )
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def test_3_layer_normal (rng ):
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"""
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Test INLA against a simple toy problem:
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