- BINOMIAL
- DISCRETEUNIFORM
- ERLANG
- GEOMETRIC
- HYPERGEOMETRIC
- NORMAL
- LOGNORMAL
- NEGATIVEEXPONENTIAL
- POISSON
- UNIFORM
- WEIBULL
- RESEED
- NUM_METHODS
This class generates random numbers. The random numbers can be from a wide variety of distributions.
All the functions return the samples in an Array of user specified shape. The vector specifying the shape must contain only positive values, otherwise and an AipsError exception will be thrown.
The copy constructor uses copy semantics
The assignment operator uses copy semantics
The destructor deletes all data allocated within this class
Generates a random number from the binomial distribution. This models drawing items from a pool. The 'number' parameter indicates how many items are in the pool, and the 'prob' parameter indicates the probability of drawing an item. The returned samples are the number of items actually drawn. The number parameter must be a non-negative integer, and the probablity must be between zero and one; otherwise an AipsError exception is thrown. The returned samples will be a non-negative integers that cannot be greater than the number of items in the pool.
Generates a random number from the discrete uniform distribution. If the low value is higher than the high value an AipsError exception is thrown.
Generates a random number from the Erlang distribution. The mean cannot be zero and the variance must be positive; otherwise and AipsError exception will be thrown.
Generates a random number from the geometric distribution. The probability must be a non-negative value less than one; otherwise and AipsError exception will be thrown.
Generates a random number from the hyper-geometric distribution. The variance must be positive and the mean must be non-zero and cannot be bigger than the square-root of the variance; otherwise and AipsError exception will be thrown.
Generates a random number from the normal or Gaussian distribution. The mean and variance can be any values.
Generates a random number from the log-normal distribution. The mean must be non-zero and variance must be positive; otherwise and AipsError exception will be thrown.
Generates a random number from the negative exponential distribution. The mean can be any value.
Generates a random number from the Poisson distribution. The mean must be non-negative; otherwise and AipsError exception will be thrown.
Generates a random number from the uniform distribution. If the low value cannot be higher than the high value; otherwise and AipsError exception will be thrown. The low value may be returned unlike the high value.
Generates a random number from the Weibull distribution. The alpha parameter cannot be zero; otherwise and AipsError exception will be thrown.
Specify a new seed to the random number generator. This allows you to get reproducable random numbers.
return the name of this object type the distributed object system. This function is required as part of the DO system
the returned vector contains the names of all the methods which may be used via the distributed object system. This function is required as part of the DO system
the returned vector contains the names of all the methods which are to trivial to warrent automatic logging. This function is required as part of the DO system
Run the specified method. This is the function used by the distributed object system to invoke any of the specified member functions in thi s class.