Generate non-normal distributions with known mean, variance, skewness and kurtosis
Project description
non-normal
Generate non-normal distributions with given a mean, variance, skewness and kurtosis
Installation
Installs cleanly with a single invocation of the standard Python package tool:
$ pip install non-normal
Usage
from non_normal import fleishman
# Input parameters for non-normal field
mean = 0
var = 1
skew = 2
ekurt = 6
size = 2**20
# Create an instance of the Fleishman class
ff = fleishman.Fleishman(mean=mean, var=var, skew=skew, ekurt=ekurt, size=size)
# Generate the field
ff.gen_field()
non_normal_data = ff.field
# Measure the stats of the generated samples
ff.field_stats
>>> {
'mean': 0.00029969955054414245,
'var': 1.0019932680714605,
'skew': 2.011601878030434,
'ekurt': 6.139570248892955
}
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