Lecture 6: Analysis

[Pages:218]Lecture 6: Analysis

Random number generation

Often, generating random numbers can be useful when developing code. the numpy library contains functions for doing this.

In [3]: import numpy as np

In [4]: help(np.random)

Help on package numpy.random in numpy:

NAME numpy.random

DESCRIPTION ======================== Random Number Generation ========================

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Utility functions

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random_sample

Uniformly distributed floa

ts over ``[0, 1)``.

random

Alias for `random_sample`.

bytes

Uniformly distributed rand

om bytes.

random_integers

Uniformly distributed inte

gers in a given range.

permutation

Randomly permute a sequenc

e / generate a random sequence.

shuffle

Randomly permute a sequenc

e in place. seed

erator. choice

ay.

Seed the random number gen Random sample from 1-D arr

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Compatibility functions

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rand

Uniformly distributed valu

es.

randn

Normally distributed value

s.

ranf

Uniformly distributed floa

ting point numbers.

randint

Uniformly distributed inte

gers in a given range.

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Univariate distributions

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beta

Beta distribution over ``

[0, 1]``.

binomial

Binomial distribution.

chisquare

:math:`\chi^2` distributio

n.

exponential

Exponential distribution.

f

F (Fisher-Snedecor) distri

bution.

gamma

Gamma distribution.

geometric

Geometric distribution.

gumbel

Gumbel distribution.

hypergeometric

Hypergeometric distributio

n.

laplace

Laplace distribution.

logistic

Logistic distribution.

lognormal

Log-normal distribution.

logseries

Logarithmic series distrib

ution.

negative_binomial Negative binomial distribu

tion.

noncentral_chisquare Non-central chi-square dis

tribution.

noncentral_f

Non-central F distributio

n.

normal

Normal / Gaussian distribu

tion.

pareto

Pareto distribution.

poisson

Poisson distribution.

power

Power distribution.

rayleigh

Rayleigh distribution.

triangular

Triangular distribution.

uniform

Uniform distribution.

vonmises

Von Mises circular distrib

ution.

wald

Wald (inverse Gaussian) di

stribution.

weibull

Weibull distribution.

zipf

Zipf's distribution over r

anked data.

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Multivariate distributions

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dirichlet

Multivariate generalizatio

n of Beta distribution.

multinomial

Multivariate generalizatio

n of the binomial distribution.

multivariate_normal Multivariate generalizatio

n of the normal distribution.

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Standard distributions

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standard_cauchy

Standard Cauchy-Lorentz di

stribution.

standard_exponential Standard exponential distr

ibution.

standard_gamma

Standard Gamma distributio

n.

standard_normal

Standard normal distributi

on.

standard_t

Standard Student's t-distr

ibution. ==================== ==========================

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Internal functions

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get_state

Get tuple representing int

ernal state of generator.

set_state

Set state of generator.

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PACKAGE CONTENTS info mtrand setup tests (package)

FUNCTIONS beta(...) method of mtrand.RandomState instance beta(a, b, size=None)

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