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docs: strip nbs output except plots and prints
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@janfb
janfb committed Sep 5, 2024
1 parent a34fd85 commit becc93c
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52 changes: 1 addition & 51 deletions tutorials/01_gaussian_amortized.ipynb
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108 changes: 1 addition & 107 deletions tutorials/02_multiround_inference.ipynb
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10 changes: 1 addition & 9 deletions tutorials/03_density_estimators.ipynb
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"WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
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"import torch\n",
"\n",
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64 changes: 3 additions & 61 deletions tutorials/04_embedding_networks.ipynb
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25,875 changes: 2 additions & 25,873 deletions tutorials/05_conditional_distributions.ipynb
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59 changes: 1 addition & 58 deletions tutorials/06_restriction_estimator.ipynb
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21 changes: 0 additions & 21 deletions tutorials/09_sampler_interface.ipynb
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"execution_count": 1,
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"WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
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10 changes: 1 addition & 9 deletions tutorials/10_diagnostics_posterior_predictive_checks.ipynb
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"cell_type": "code",
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"WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
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"source": [
"import torch\n",
"\n",
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198 changes: 3 additions & 195 deletions tutorials/11_diagnostics_simulation_based_calibration.ipynb
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"cell_type": "code",
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"WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
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"import torch\n",
"from torch import eye, ones\n",
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"cell_type": "code",
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"Drawing 1000 posterior samples: 0%| | 0/1000 [00:00<?, ?it/s]"
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"source": [
"# run SBC: for each inference we draw 1000 posterior samples.\n",
"num_posterior_samples = 1_000\n",
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"source": [
"# the tarp method returns the ECP values for a given set of alpha coverage levels.\n",
"ecp, alpha = run_tarp(\n",
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