numpy.random commonly used functions
Random number generation function parameter has two components: low / high and the size / length / shape
Simple random number generation
| Function name | Katachisan | effect |
|---|---|---|
| rand | (D 0, d 1, d n) | [0,1) uniformly distributed prescribed shape |
| random | ([size]) | [0,1) evenly distributed continuously, a prescribed shape |
| randn | (D 0, d 1, d n) | Standard normal distribution, a predetermined shape |
| Randine | (low[, high, size, dtype]) | Discrete uniform distribution, on the specified lower limit / shape |
Notes: [size]: int or tuple of ints; [] denotes optional parameters; default distribution is uniform, except at the end of a normal n
Distribution function
In accordance with the low, high specific distribution pattern generated
- beta(a, b[, size])
- binomial (n, p [, size]) binomial
- exponential ([scale, size]) exponential distribution
- f(dfnum, dfden[, size]) F分布
- gamma(shape[, scale, size]) Gamma分布
- geometric (p [, size]) Geometric Distribution
- normal ([loc, scale, size]) normal
- uniform ([low, high, size]) discrete uniform distribution
See detailed official document:
https://docs.scipy.org/doc/numpy/reference/routines.random.html?highlight=random#module-numpy.random