Closed Minxiangliu closed 4 years ago
Check out the functions generate_noise
and uniform_to_normal
.
generate_noise
produces independent, uniformly-distributed values in the range [-1, 1] with shape (n, 2) (ie, independent pairs of random numbers). It is a random function.
uniform_to_normal
is a deterministic function that takes a number in the range [-1, 1] and returns a number in the range (-∞, ∞). This is done using inverse transform sampling. First, the number in [-1, 1] is rescaled to [0, 1]. Then, it's passed through scipy's percentage point function "ppf" for the normal distribution. These two functions combined is equivalent to sampling from the normal distribution.
How to know the probability distribution method of own real data, such as https://github.com/ConorLazarou/medium/blob/3fae4b997d1faca25e0b7395d5a71da3c2019b03/12020/visualizing_gan_uni2norm/1_uniform_to_normal_1D.py#L123-L124
How to know the value of line 123? Is there any description here? Thank you.