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Von Mises Fisher Distribution
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.. automodule:: pymaniprob.docs.basics


.. plot::

    >>> import numpy as np
    >>> import matplotlib.pyplot as plt
    >>> # Build a vector of 10000 normal deviates with variance 0.5^2 and mean 2
    >>> mu, sigma = 2, 0.5
    >>> v = np.random.normal(mu,sigma,10000)
    >>> # Plot a normalized histogram with 50 bins
    >>> plt.hist(v, bins=50, density=1)       # matplotlib version (plot)
    >>> plt.show()
    >>> # Compute the histogram with numpy and then plot it
    >>> (n, bins) = np.histogram(v, bins=50, density=True)  # NumPy version (no plot)
    >>> plt.plot(.5*(bins[1:]+bins[:-1]), n)
    >>> plt.show()