BiWavelet

This command performs bivariate wavelet analysis on a contiguous data set.

Syntax

BiWavelet [options];

Menu Equivalent

Analysis→Contiguous Data→Wavelet→Bivariate Wavelets

Button Equivalent

Available Options

• Function = Haar | FTH | MexHat | Morlet | Sine | TTH | STH | Boater | Sombrero | WSW | MSW | NSW
• Wrap = Yes | No
• MaxScale = Number
• ScaleFactor = Number
• Permute = Yes | No
• Permutations = Number
• Interval = Number
• PermScale = Yes | No
• PermPos = Yes | No
• Save = Yes | No
• ScaleName = Name
• PosName = Name
• Data1 = Name | #Number
• Data2 = Name | #Number
• Column1 = Name | #Number
• Column2 = Name | #Number
• Row1 = Name | #Number
• Row2 = Name | #Number
• XCol1 = [Name | #Number, Name | #Number]
• XCol2 = [Name | #Number, Name | #Number]
• YCol1 = [Name | #Number, Name | #Number]
• YCol2 = [Name | #Number, Name | #Number]
• ZCol1 = [Name | #Number, Name | #Number]
• ZCol2 = [Name | #Number, Name | #Number]
• XYPlane1 = Name | #Number
• XYPlane2 = Name | #Number
• XZPlane1 = Name | #Number
• XZPlane2 = Name | #Number
• YZPlane1 = Name | #Number
• YZPlane2 = Name | #Number

Description of options

Function = Haar | FTH | MexHat | Morlet | Sine | TTH | STH | Boater | Sombrero | WSW | MSW | NSW

The Function parameter specifies the wavelet template or kernel used in the analysis. WSW, MSW, and NSW imply three-dimensional analysis three-dimensional analysis and require the matrices specified by Data1 and Data2 to be three-dimensional. TTH, STH, Boater and Sombrero imply two-dimensional analysis, while the remaining methods all imply one-dimensional analysis. A method must be specified; there is no default.

Wrap = Yes | No

If Function refers to a one-dimensional analysis, this parameter controls whether the ends of the data transect will be wrapped or remain linear. The default is No.

MaxScale = Number

This specifies the maximum scale (as a percent of the size of the data matrix) over which to calculate the wavelet. This value can generally range from 0 to 50. The default is 10.

ScaleFactor = Number

This value is used to indicate the scale of the data quadrats. For example, if each quadrat is 10cm in size and you wish the results to be presented in meters, ScaleFactor should equal 0.1. On the other hand if you wish the results to be presented in cm, ScaleFactor should equal 10. It has no direct impact on the analysis; it only affects the units of the output. The default is 1.0.

Permute = Yes | No

Specifies whether a randomization tests is being performed to estimate null distributions. Permutation parameters include Permutations, Interval, PermScale, and PermPos.

Permutations = Number

When Permute = Yes, this controls the number of permutations that are being performed in the permutation test. The default is 999 (the minimum is 49).

Interval = Number

When Permute = Yes, specifies the width of the null distribution interval to be determined by the permutation test. The default is 0.95.

PermScale = Yes | No

When Permute = Yes, specifies whether a permutation test should be used to set a null distribution for the scale variance. The default is Yes.

PermPos = Yes | No

When Permute = Yes, specifies whether a permutation test should be used to set a null distribution for the positional variance. The default is No.

Save = Yes | No

Controls whether the output is saved into independent matrices. The default is No.

ScaleName = Name

When Save = Yes, this specifies the name of the output matrix for the scale variance. This name cannot be identical to the names of any other matrices already in memory.

PosName = Name

When Save = Yes, this specifies the name of the output matrix for the positional variance. This name cannot be identical to the names of any other matrices already in memory.

Data1, Data2 = Name | #Number

Specifies the data matrices. These can be rectangular or 3D data matrices.

The following options apply when Data1/Data2 refer to two-dimensional data matrices and Function refers to a one-dimensional analysis.

Column1, Column2 = Name | #Number

Row1, Row2 = Name | #Number

These specify the column or row in each matrix containing the one-dimensional data array to perform the bivariate wavelet analysis on. You cannot specify a column and row from the same matrix (e.g., Column1 and Row1), but can choose a column from one matrix and a row from the other.

The following options apply when Data1/Data2 refer to three-dimensional data matrices and Function refers to a one-dimensional analysis.

XCol1, XCol2 = [Name | #Number, Name | #Number]

YCol1, YCol2 = [Name | #Number, Name | #Number]

ZCol1, ZCol2 = [Name | #Number, Name | #Number]

For three-dimensional data matrices and one-dimensional analyses, these specify the specific column to be analyzed by the specified Function. Only one of these parameters (X, Y, or Z) can be used for each matrix in the analysis.

The following options apply when Data1/Data2 refer to three-dimensional data matrices and Function refers to a two-dimensional analysis.

XYPlane1, XYPlane2 = Name | #Number

XZPlane1, XZPlane2 = Name | #Number

YZPlane1, YZPlane2 = Name | #Number

For three-dimensional data matrices and two-dimensional analyses, these specify which plane is to be analyzed by the specified Function. Only a single of these parameters (X, Y, or Z) can be used for each matrix in the analysis.