Mapytex/pymath/stat/random_generator.py

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#/usr/bin/env python
# -*- coding:Utf-8 -*-
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from random import randint, uniform, gauss, choice
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def random_generator(length,\
distrib = gauss, rd_args = (0,1), \
nbr_format = lambda x:round(x,2), \
v_min = None, v_max = None, \
exact_mean = None):
""" Generate a random list of value
:param length: length of the dataset
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:param distrib: Distribution of the data set. It can be a function or string from ["randint", "uniform", "gauss", "choice"]
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:param rd_args: arguments to pass to distrib
:param nbr_format: function which format value
:param v_min: minimum accepted value
:param v_max: maximum accepted value
:param exact_mean: if set, the last generated number will be create in order that the computed mean is exacly equal to "exact_mean"
>>> random_generator(10)
>>> random_generator(10, distrib = uniform, rd_args = (5, 10))
>>> random_generator(10, distrib = "uniform", rd_args = (5, 10))
>>> random_generator(10, v_min = 0)
>>> random_generator(10, exact_mean = 0)
>>> random_generator(10, distrib = gauss, rd_args = (50,20), nbr_format = int)
"""
# if exact_mean is set, we create automaticaly only length-1 value
if exact_mean != None:
length = length - 1
# build function to test created values
if v_min == None:
v1 = lambda x: True
else:
v1 = lambda x: x >= v_min
if v_max == None:
v2 = lambda x: True
else:
v2 = lambda x: x <= v_max
validate = lambda x : v1(x) and v2(x)
# get distrib function
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distribs = {"gauss": gauss, "uniform": uniform, "randint":randint, "choice":choice}
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try:
distrib(*rd_args)
except TypeError:
distrib = distribs[distrib]
# building values
data = []
for _ in range(length):
valid = False
while not valid:
v = nbr_format(distrib(*rd_args))
valid = validate(v)
data.append(v)
# Build last value
if exact_mean != None:
last_v = nbr_format((length+1) * exact_mean - sum(data))
if not validate(last_v):
raise ValueError("Can't build the last value. Conflict between v_min/v_max and exact_mean")
data.append(last_v)
return data
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