mars.tensor.random.vonmises¶

mars.tensor.random.
vonmises
(mu, kappa, size=None, chunk_size=None, gpu=None, dtype=None)[source]¶ Draw samples from a von Mises distribution.
Samples are drawn from a von Mises distribution with specified mode (mu) and dispersion (kappa), on the interval [pi, pi].
The von Mises distribution (also known as the circular normal distribution) is a continuous probability distribution on the unit circle. It may be thought of as the circular analogue of the normal distribution.
 Parameters
mu (float or array_like of floats) – Mode (“center”) of the distribution.
kappa (float or array_like of floats) – Dispersion of the distribution, has to be >=0.
size (int or tuple of ints, optional) – Output shape. If the given shape is, e.g.,
(m, n, k)
, thenm * n * k
samples are drawn. If size isNone
(default), a single value is returned ifmu
andkappa
are both scalars. Otherwise,np.broadcast(mu, kappa).size
samples are drawn.chunk_size (int or tuple of int or tuple of ints, optional) – Desired chunk size on each dimension
gpu (bool, optional) – Allocate the tensor on GPU if True, False as default
dtype (datatype, optional) – Datatype of the returned tensor.
 Returns
out – Drawn samples from the parameterized von Mises distribution.
 Return type
Tensor or scalar
See also
scipy.stats.vonmises
probability density function, distribution, or cumulative density function, etc.
Notes
The probability density for the von Mises distribution is
\[p(x) = \frac{e^{\kappa cos(x\mu)}}{2\pi I_0(\kappa)},\]where \(\mu\) is the mode and \(\kappa\) the dispersion, and \(I_0(\kappa)\) is the modified Bessel function of order 0.
The von Mises is named for Richard Edler von Mises, who was born in AustriaHungary, in what is now the Ukraine. He fled to the United States in 1939 and became a professor at Harvard. He worked in probability theory, aerodynamics, fluid mechanics, and philosophy of science.
References
 1
Abramowitz, M. and Stegun, I. A. (Eds.). “Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, 9th printing,” New York: Dover, 1972.
 2
von Mises, R., “Mathematical Theory of Probability and Statistics”, New York: Academic Press, 1964.
Examples
Draw samples from the distribution:
>>> import mars.tensor as mt
>>> mu, kappa = 0.0, 4.0 # mean and dispersion >>> s = mt.random.vonmises(mu, kappa, 1000)
Display the histogram of the samples, along with the probability density function:
>>> import matplotlib.pyplot as plt >>> from scipy.special import i0 >>> plt.hist(s.execute(), 50, normed=True) >>> x = mt.linspace(mt.pi, mt.pi, num=51) >>> y = mt.exp(kappa*mt.cos(xmu))/(2*mt.pi*i0(kappa)) >>> plt.plot(x.execute(), y.execute(), linewidth=2, color='r') >>> plt.show()