common Namespace Reference

Functions
def	Mv (nu, X)
	Matérn kernel. More...
def	Matern_kernel (x, nu=1, rho=1)
def	SM_kernel (x, a)
	Shifted Matern kernel. More...
def	GM_kernel (x, nu, rho, a)
	Generalized Matern kernel. More...
def	EP_kernel (x, a)
	Exponential-polynomial kernel. More...
def	vf2tau (vf, sigma=1, strategy=0)
	Volume fraction to Tau (and vice-versa) More...
def	tau2vf (tau, sigma=1, strategy=0)
def	Cov2S2 (tau, g, strategy=0)
def	FourierOfGaussian (noise)
	Fourier Transform of Gaussian Noise. More...
def	compute_Sphericity (V, A)
	Inclusion geometry. More...
def	Expectation (X)
	Basic probability tools. More...
def	Variance (X, m=None)
def	SpacialCovariance (X)
def	compute_ProbaDist (data, bins=None)
	Compute probability distribution (from data) More...
def	fit_ProbaDist (x, p, type='LogNormal')
	Fit a probability with LogNormal (or Normal) More...
def	autocorrelation (X)
	Autocorrelation of an image. More...
def	slope_by_fft (C)
def	dens_Exponential (x, lmbda=1)
	Probability densities. More...
def	dens_Normal (x, m=0, sigma=1)
def	dens_LogNormal (x, m=0, sigma=1)
def	MC_estimate_Covariance (RandomField, nsamples=100, nbins=None)
	Estimate covariance using Monte-Carlo. More...

Function Documentation

autocorrelation()

def common.autocorrelation

(

X

)

Autocorrelation of an image.

compute_ProbaDist()

def common.compute_ProbaDist	(		data,
			bins = None
	)

Compute probability distribution (from data)

compute_Sphericity()

def common.compute_Sphericity	(		V,
			A
	)

Inclusion geometry.

Cov2S2()

def common.Cov2S2	(		tau,
			g,
			strategy = 0
	)

dens_Exponential()

def common.dens_Exponential	(		x,
			lmbda = 1
	)

Probability densities.

dens_LogNormal()

def common.dens_LogNormal	(		x,
			m = 0,
			sigma = 1
	)

dens_Normal()

def common.dens_Normal	(		x,
			m = 0,
			sigma = 1
	)

EP_kernel()

def common.EP_kernel	(		x,
			a
	)

Exponential-polynomial kernel.

Expectation()

def common.Expectation

(

X

)

Basic probability tools.

fit_ProbaDist()

def common.fit_ProbaDist	(		x,
			p,
			type = 'LogNormal'
	)

Fit a probability with LogNormal (or Normal)

FourierOfGaussian()

def common.FourierOfGaussian

(

noise

)

Fourier Transform of Gaussian Noise.

GM_kernel()

def common.GM_kernel	(		x,
			nu,
			rho,
			a
	)

Generalized Matern kernel.

Matern_kernel()

def common.Matern_kernel	(		x,
			nu = 1,
			rho = 1
	)

MC_estimate_Covariance()

def common.MC_estimate_Covariance	(		RandomField,
			nsamples = 100,
			nbins = None
	)

Estimate covariance using Monte-Carlo.

Mv()

def common.Mv	(		nu,
			X
	)

Matérn kernel.

slope_by_fft()

def common.slope_by_fft

(

C

)

SM_kernel()

def common.SM_kernel	(		x,
			a
	)

Shifted Matern kernel.

SpacialCovariance()

def common.SpacialCovariance

(

X

)

tau2vf()

def common.tau2vf	(		tau,
			sigma = 1,
			strategy = 0
	)

Variance()

def common.Variance	(		X,
			m = None
	)

vf2tau()

def common.vf2tau	(		vf,
			sigma = 1,
			strategy = 0
	)

Volume fraction to Tau (and vice-versa)