.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples\2-examples\1.3_Intro_to_Bayesian_Inference.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_2-examples_1.3_Intro_to_Bayesian_Inference.py: Uniform Prior, single observation ================================= .. GENERATED FROM PYTHON SOURCE LINES 7-23 .. code-block:: default # sphinx_gallery_thumbnail_number = -1 import arviz as az import matplotlib.pyplot as plt import pyro import torch from matplotlib.ticker import StrMethodFormatter from gempy_probability.plot_posterior import PlotPosterior from _aux_func import infer_model y_obs = torch.tensor([2.12]) y_obs_list = torch.tensor([2.12, 2.06, 2.08, 2.05, 2.08, 2.09, 2.19, 2.07, 2.16, 2.11, 2.13, 1.92]) pyro.set_rng_seed(4003) .. GENERATED FROM PYTHON SOURCE LINES 24-32 .. code-block:: default az_data = infer_model( distributions_family="uniform_distribution", data=y_obs ) az.plot_trace(az_data) plt.show() .. image-sg:: /examples/2-examples/images/sphx_glr_1.3_Intro_to_Bayesian_Inference_001.png :alt: $\mu$, $\mu$, $\sigma$, $\sigma$ :srcset: /examples/2-examples/images/sphx_glr_1.3_Intro_to_Bayesian_Inference_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none Warmup: 0%| | 0/1100 [00:00, ?it/s] Warmup: 2%|▏ | 17/1100 [00:00, 169.94it/s, step size=1.52e-01, acc. prob=0.746] Warmup: 3%|▍ | 38/1100 [00:00, 191.85it/s, step size=2.03e-02, acc. prob=0.751] Warmup: 5%|▋ | 58/1100 [00:00, 142.24it/s, step size=9.72e-02, acc. prob=0.775] Warmup: 7%|▊ | 74/1100 [00:00, 146.05it/s, step size=1.23e-01, acc. prob=0.780] Warmup: 9%|█ | 96/1100 [00:00, 165.39it/s, step size=3.69e-01, acc. prob=0.763] Sample: 11%|█▏ | 116/1100 [00:00, 175.30it/s, step size=2.71e-01, acc. prob=0.567] 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GENERATED FROM PYTHON SOURCE LINES 33-47 .. code-block:: default p = PlotPosterior(az_data) p.create_figure(figsize=(9, 5), joyplot=False, marginal=True, likelihood=True) p.plot_marginal(var_names=['$\mu$', '$\sigma$'], plot_trace=False, credible_interval=.93, kind='kde', joint_kwargs={'contour': True, 'pcolormesh_kwargs': {}}, joint_kwargs_prior={'contour': False, 'pcolormesh_kwargs': {}}) p.axjoin.set_xlim(1.96, 2.22) p.plot_normal_likelihood('$\mu$', '$\sigma$', '$y$', iteration=-6, hide_lines=True) p.likelihood_axes.set_xlim(1.70, 2.40) plt.show() .. image-sg:: /examples/2-examples/images/sphx_glr_1.3_Intro_to_Bayesian_Inference_002.png :alt: Likelihood :srcset: /examples/2-examples/images/sphx_glr_1.3_Intro_to_Bayesian_Inference_002.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 48-58 License ======= The code in this case study is copyrighted by Miguel de la Varga and licensed under the new BSD (3-clause) license: https://opensource.org/licenses/BSD-3-Clause The text and figures in this case study are copyrighted by Miguel de la Varga and licensed under the CC BY-NC 4.0 license: https://creativecommons.org/licenses/by-nc/4.0/ Make sure to replace the links with actual hyperlinks if you're using a platform that supports it (e.g., Markdown or HTML). Otherwise, the plain URLs work fine for plain text. .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 9.452 seconds) .. _sphx_glr_download_examples_2-examples_1.3_Intro_to_Bayesian_Inference.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: 1.3_Intro_to_Bayesian_Inference.py <1.3_Intro_to_Bayesian_Inference.py>` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: 1.3_Intro_to_Bayesian_Inference.ipynb <1.3_Intro_to_Bayesian_Inference.ipynb>` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_