Statistics and PDF output
This pages discusses how to extract statistics from a Walker simulation. See also the Walker examples.
Supported statistics and PDFs
Supported at this time are ordinary and central statistical moments of arbitrary-length products and arbitrary number of 1D, 2D, and 3D probability density functions (PDF) with sample spaces of ordinary and/or central sample space variables.
Definitions and nomenclature
- Upper-case letters denote a full random variable, e.g.,
X
- Lower-case letters denote a fluctuation about the mean, i.e.,
x=X-<X>
- Letters can be augmented by a field ID, i.e.,
X2
is the full variable of the second component of the vectorX
, whilex1=X1-<X1>
is the fluctuation about the mean of the first component of vectorX
. - If the field ID is unspecified, it defaults to the first field, i.e.,
X = X1
,x = x1
, etc. - Statistical moments of arbitrary-length products can be computed. Examples:
<X>
- mean,<xx>
- variance,<xxx>
- third central moment,<xy>
- covariance of X and Y,<x1y2>
- covariance of the first component of vectorX
and the second component of vectorY
- In general, arbitrary-length products can be estimated that make up a statistical moment, using any number and combinations of upper and lower-case letters and their field IDs
<[A-Za-z][1-9]...>
. - A statistical moment is ordinary if and only if all of its terms are ordinary. A central moment has at least one term that is central, i.e., a fluctuation about its mean.
- Examples of ordinary moments:
<X>
,<XX>
,<XYZ>
, etc. - Examples of central moments:
<x1x2>
,<Xy>
,<XYz>
, etc.
- Examples of ordinary moments:
- Estimation of PDFs can be done using either ordinary or central sample space variables. Examples:
p(X)
denotes the univariate PDF of the full variableX
,f(x1,x2)
denotes the bivariate joint PDF of the fluctuations of the variablesx1
andx2
about their respective means,g(X,y,Z2)
denotes the trivariate joint PDF of variablesX
,y=Y-<Y>
, andZ2
Example control file section for statistics output
statistics interval 2 # Output statistics every 2nd time step <X1> <X2> <x1x1> <x2x2> <x1x2> <R> <rr> <R2> <r2r2> <R3> <r3r3> <r1r2> <r1r3> <r2r3> <K1> <k1k1> <k2k2> <K1K1> <k3> #<H1> <H2> <h1h1> <h2h2> <h1h2> #<x1z2Uy2> <Y2> <y1y1> <y2y2> <y1y2> #<x1x2Z1z2> end
Example control file section for PDF output
pdfs interval 10 # Output PDFs every 10th time step filetype txt # Use txt file output policy overwrite # Overwrite previous time step with new one centering elem # Use element-centering for sample space format scientific # Use 'scientific' floats in txt file output precision 4 # Use 4 digits percision for floats in txt output # Univariate PDF "O2" of the full variable O2 with bin size 0.05 and # explicitly specified sample space extents 0.0 and 1.0 (min and max) O2( O2 : 5.0e-2 ; 0 1 ) # Bivariate PDF "f2" of the fluctuating variables o1 and o2 with bin sizes # 0.05 in both sample space dimensions f2( o1 o2 ; 5.0e-2 5.0e-2 ) # Bivariate PDF "mypdf" of the fluctuating variables o1 and o2 with bin sizes # 0.05 in both sample space dimensions and explicitly specified sample space # extents, { xmin, xmax, ymin, ymax } = { -2, 2, -2, 2 } mypdf( o1 o2 : 5.0e-2 5.0e-2 ; -2 2 -2 2 ) # Trivariate PDF "f3" of full variables O1, O2, and O3 with bin sizes 0.1 in # all dimensions of the sample space f3( O1 O2 O1 : 1.0e-1 1.0e-1 1.0e-1 ) # Trivariate PDF "newpdf" of full variables O1, O2, and O3 with bin sizes # 0.1 in all dimensions of the sample space and explicitly specified sample # space extents, { xmin, xmax, ymin, ymax, zmin, zmax } = { 0, 1, 0, 1, # -0.5, -0.5 } newpdf( O1 O2 O1 : 1.0e-1 1.0e-1 1.0e-1 ; 0 1 0 1 -0.5 0.5 ) end