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Fix: Handle zero valid samples in importance_reweight to avoid ValueError crash #40

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Merged
kmzzhang merged 1 commit into from
Aug 12, 2025
Merged

Fix: Handle zero valid samples in importance_reweight to avoid ValueError crash #40

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4 changes: 4 additions & 0 deletions src/nbi/engine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -633,6 +633,10 @@ def importance_reweight(self, x_obs, x, y):
log_weights = loglike + logprior - logproposal

bad = np.isnan(log_weights) + np.isinf(log_weights)
valid_weights = log_weights[~bad]
if len(valid_weights) == 0:
print("All log weights are NaN or Inf — skipping this round!")

Copilot AI Aug 7, 2025

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Using print() for warnings is not ideal. Consider using the logging module or warnings.warn() for better control over diagnostic output and to follow Python best practices.

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print("All log weights are NaN or Inf — skipping this round!")
warnings.warn("All log weights are NaN or Inf — skipping this round!")

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return np.zeros_like(log_weights)
log_weights -= log_weights[~bad].max()

weights = np.exp(log_weights)
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