.. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_animation_bayes_update.py: ================ The Bayes update ================ This animation displays the posterior estimate updates as it is refitted when new data arrives. The vertical line represents the theoretical value to which the plotted distribution should converge. .. image:: /gallery/animation/images/sphx_glr_bayes_update_001.png :class: sphx-glr-single-img .. code-block:: default import math import numpy as np import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation def beta_pdf(x, a, b): return (x**(a-1) * (1-x)**(b-1) * math.gamma(a + b) / (math.gamma(a) * math.gamma(b))) class UpdateDist: def __init__(self, ax, prob=0.5): self.success = 0 self.prob = prob self.line, = ax.plot([], [], 'k-') self.x = np.linspace(0, 1, 200) self.ax = ax # Set up plot parameters self.ax.set_xlim(0, 1) self.ax.set_ylim(0, 15) self.ax.grid(True) # This vertical line represents the theoretical value, to # which the plotted distribution should converge. self.ax.axvline(prob, linestyle='--', color='black') def init(self): self.success = 0 self.line.set_data([], []) return self.line, def __call__(self, i): # This way the plot can continuously run and we just keep # watching new realizations of the process if i == 0: return self.init() # Choose success based on exceed a threshold with a uniform pick if np.random.rand(1,) < self.prob: self.success += 1 y = beta_pdf(self.x, self.success + 1, (i - self.success) + 1) self.line.set_data(self.x, y) return self.line, # Fixing random state for reproducibility np.random.seed(19680801) fig, ax = plt.subplots() ud = UpdateDist(ax, prob=0.7) anim = FuncAnimation(fig, ud, frames=np.arange(100), init_func=ud.init, interval=100, blit=True) plt.show() .. _sphx_glr_download_gallery_animation_bayes_update.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: bayes_update.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: bayes_update.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature Keywords: matplotlib code example, codex, python plot, pyplot `Gallery generated by Sphinx-Gallery `_