rand-number-gen 0.1

Random Number Generator

Random Number Package

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random number generator

This module implement random number from the specified distribution.

Real-valued distributions

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The following functions generate specific real-valued distributions. Function parameters are named after the corresponding variables in the distribution’s equation.

1. uniform(size)

   Return the 'size random floating point numbers in the range [0.0, 1.0).

2. gaussian(size)

3. binomial(trials,probability,size)

   return samples from a binomial distribution, where each sample is equal to the number of successes over the n trials.

4. chisquare(df,size)

   return samples from a chi-square distribution. Parameters:
   a. df : int or array_like of ints;Number of degrees of freedom. b. size : int or tuple of ints, Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. If size is None (default), a single value is returned if df is a scalar. Otherwise, np.array(df).size samples are drawn.

5. weibull(size) return samples from a Weibull distribution. Parameters: a : float or array_like of floats Shape of the distribution. Should be greater than zero. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. If size is None (default), a single value is returned if a is a scalar. Otherwise, np.array(a).size samples are drawn.

6. exponential(scale,size) return samples from an exponential distribution. Parameters: scale : float or array_like of floats The scale parameter, \beta = 1/\lambda. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. If size is None (default), a single value is returned if scale is a scalar. Otherwise, np.array(scale).size samples are drawn.

7. poisson(lam,size) return samples from a poisson distribution. Parameters: lam : float or array_like of floats Expectation of interval, should be >= 0. A sequence of expectation intervals must be broadcastable over the requested size. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. If size is None (default), a single value is returned if lam is a scalar. Otherwise, np.array(lam).size samples are drawn.