com.xinapse.multisliceimage.Analyze
Enum NIFTIIntent

java.lang.Object
  java.lang.Enum<NIFTIIntent>
      com.xinapse.multisliceimage.Analyze.NIFTIIntent

All Implemented Interfaces:

java.io.Serializable, java.lang.Comparable<NIFTIIntent>

public enum NIFTIIntent
extends java.lang.Enum<NIFTIIntent>

This class represents the NIFTI intents.

For probability distributions, most distributions have a number of parameters, below denoted by p1, p2, and p3, and stored in:

• intent_p1, intent_p2, intent_p3 if dataset doesn't have 5th dimension
• image data array, if dataset does have 5th dimension

Functions to compute with many of the distributions below can be found in the CDF library from U Texas.

Formulas for and discussions of these distributions can be found in the following books. These references are abbreviated to [U, C1 and C2] in the documentation below.

• [U] Univariate Discrete Distributions, NL Johnson, S Kotz, AW Kemp.
• [C1] Continuous Univariate Distributions, vol. 1, NL Johnson, S Kotz, N Balakrishnan.
• [C2] Continuous Univariate Distributions, vol. 2, NL Johnson, S Kotz, N Balakrishnan.

Enum Constant Summary

BETA
[C2, chap 25] Beta distribution (2 params): p1=a, p2=b.

BINOM
[U, chap 3] Binomial distribution (2 params):
p1 = number of trials, p2 = probability per trial.
Prob(x) = (p1 choose x) * p2^x * (1-p2)^(p1-x), for x=0,1,...,p1.

CHI
[C1, chap 18] Chi distribution (1 param): p1 = DOF.

CHISQ
[C1, chap 18] Chi-squared (1 param): p1 = DOF.

CHISQ_NONC
[C2, chap 29] Noncentral chi-squared statistic (2 params):
p1 = DOF, p2 = noncentrality parameter.

CORREL
[C2, chap 32] Correlation coefficient R (1 param):
p1 = degrees of freedom;
R/sqrt(1-R*R) is t-distributed with p1 DOF.

DISPVECT
To signify that the vector value at each voxel is to be taken as a displacement field or vector:
- dataset must have a 5th dimension
- intent must be DISPVECT
- dim[5] must be the dimensionality of the displacment vector (e.g., 3 for spatial displacement, 2 for in-plane).
This intent is specifically for displacements.

ESTIMATE
To signify that the value at each voxel is an estimate of some parameter, set intent_code = NIFTI_INTENT_ESTIMATE.

EXTVAL
[C2, chap 22] Extreme value type I (2 params):
p1 = location, p2 = scale
cdf(x) = exp(-exp(-(x-p1)/p2)).

FTEST
[C2, chap 27] Fisher F statistic (2 params):
p1 = numerator DOF,
p2 = denominator DOF.

FTEST_NONC
[C2, chap 30] Noncentral F statistic (3 params):
p1 = numerator DOF, p2 = denominator DOF,
p3 = numerator noncentrality parameter.

GAMMA
[C1, chap 17] Gamma distribution (2 params):
p1 = shape, p2 = scale.
Density(x) proportional to x^(p1-1) * exp(-p2*x).

GENMATRIX
To store an M x N matrix at each voxel:
- dataset must have a 5th dimension (dim[0]=5 and dim[5]>1)
- intent must be GENMATRIX
- dim[5] must be M*N
- intent_p1 must be M (in float format)
- intent_p2 must be N (ditto)
- the matrix values A[i][[j] are stored in row-order:
- A[0][0] A[0][1] ...

INVGAUSS
[C1, chap 15] Inverse Gaussian (2 params):
p1 = mu, p2 = lambda
Density(x) proportional to exp(-p2*(x-p1)^2/(2*p1^2*x)) / x^3 for x > 0.

LABEL
To signify that the value at each voxel is an index into some set of labels, set intent_code = NIFTI_INTENT_LABEL.

LAPLACE
[C2, chap 24] Laplace distribution (2 params):
p1 = location, p2 = scale.
Density(x) proportional to exp(-abs(x-p1)/p2).

LOGISTIC
[C2, chap 23] Logistic distribution (2 params):
p1 = location, p2 = scale.
Density(x) proportional to sech^2((x-p1)/(2*p2)).

NEURONAME
To signify that the value at each voxel is an index into the NeuroNames labels set, set intent_code = NIFTI_INTENT_NEURONAME.

NONE
The default: no intention is indicated in the header.

NORMAL
[C1, chap 13] Normal distribution (2 params):
p1 = mean, p2 = standard deviation.

POINTSET
To signify that the vector value at each voxel is really a spatial coordinate (e.g., the vertices or nodes of a surface mesh):
- dataset must have a 5th dimension
- intent must be POINTSET
- dim[0] = 5
- dim[1] = number of points
- dim[2] = dim[3] = dim[4] = 1
- dim[5] must be the dimensionality of space (e.g., 3 => 3D space).
- intent_name may describe the object these points come from (e.g., "pial", "gray/white" , "EEG", "MEG").

POISSON
[U, chap 4] Poisson distribution (1 param): p1 = mean.
Prob(x) = exp(-p1) * p1^x / x! , for x=0,1,2,....

PVAL
Data is a 'p-value' (no params).

QUATERNION
To signify that the vector value at each voxel is a quaternion:
- dataset must have a 5th dimension
- intent must be QUATERNION
- dim[0] = 5
- dim[5] = 4
- datatype should be a floating point type.

SYMMATRIX
To store an NxN symmetric matrix at each voxel:
- dataset must have a 5th dimension
- intent must be SYMMATRIX
- dim[5] must be N*(N+1)/2
- intent_p1 must be N (in float format)
- the matrix values A[i][[j] are stored in row-order:
- A[0][0]
- A[1][0] A[1][1]
- A[2][0] A[2][1] A[2][2]
- etc.: row-by-row.

TRIANGLE
To signify that the vector value at each voxel is really a triple of indexes (e.g., forming a triangle) from a pointset dataset:
- dataset must have a 5th dimension
- intent must be TRIANGLE
- dim[0] = 5
- dim[1] = number of triangles
- dim[2] = dim[3] = dim[4] = 1
- dim[5] = 3
- datatype should be an integer type (preferably INT)
- the data values are indexes (0,1,...) into a pointset dataset.

TTEST
[C2, chap 28] Student t statistic (1 param): p1 = DOF.

TTEST_NONC
[C2, chap 31] Noncentral t statistic (2 params):
p1 = DOF, p2 = noncentrality parameter.

UNIFORM
[C2, chap 26] Uniform distribution: p1 = lower end, p2 = upper end.

VECTOR
To signify that the vector value at each voxel is to be taken as a displacement field or vector:
- dataset must have a 5th dimension
- intent must be NIFTI_INTENT_DISPVECT
- dim[5] must be the dimensionality of the displacment vector (e.g., 3 for spatial displacement, 2 for in-plane).
This intent is for general vectors.

WEIBULL
[C1, chap 21] Weibull distribution (3 params):
p1 = location, p2 = scale, p3 = power.
Density(x) proportional to ((x-p1)/p2)^(p3-1) * exp(-((x-p1)/p2)^p3) for x > p1.

ZSCORE
[C1, chap 13] Standard normal (0 params): Density = N(0,1).

Method Summary

boolean	isStatistic() Indicates whether this NIFTIIntent is a statistic intent.
static void	main(java.lang.String[] args) Run a self-test on the NIFTIIntent class.
java.lang.String	toString() Returns a string describing this NIFTIIntent.
static NIFTIIntent	valueOf(java.lang.String name) Returns the enum constant of this type with the specified name.
static NIFTIIntent[]	values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class java.lang.Enum

clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, valueOf

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Detail

NONE

public static final NIFTIIntent NONE

The default: no intention is indicated in the header.

CORREL

public static final NIFTIIntent CORREL

[C2, chap 32] Correlation coefficient R (1 param):
p1 = degrees of freedom;
R/sqrt(1-R*R) is t-distributed with p1 DOF.

TTEST

public static final NIFTIIntent TTEST

[C2, chap 28] Student t statistic (1 param): p1 = DOF.

FTEST

public static final NIFTIIntent FTEST

[C2, chap 27] Fisher F statistic (2 params):
p1 = numerator DOF,
p2 = denominator DOF.

ZSCORE

public static final NIFTIIntent ZSCORE

[C1, chap 13] Standard normal (0 params): Density = N(0,1).

CHISQ

public static final NIFTIIntent CHISQ

[C1, chap 18] Chi-squared (1 param): p1 = DOF. Density(x) proportional to exp(-x/2) * x^(p1/2-1).

BETA

public static final NIFTIIntent BETA

[C2, chap 25] Beta distribution (2 params): p1=a, p2=b. Density(x) proportional to x^(a-1) * (1-x)^(b-1).

BINOM

public static final NIFTIIntent BINOM

[U, chap 3] Binomial distribution (2 params):
p1 = number of trials, p2 = probability per trial.
Prob(x) = (p1 choose x) * p2^x * (1-p2)^(p1-x), for x=0,1,...,p1.

GAMMA

public static final NIFTIIntent GAMMA

[C1, chap 17] Gamma distribution (2 params):
p1 = shape, p2 = scale.
Density(x) proportional to x^(p1-1) * exp(-p2*x).

POISSON

public static final NIFTIIntent POISSON

[U, chap 4] Poisson distribution (1 param): p1 = mean.
Prob(x) = exp(-p1) * p1^x / x! , for x=0,1,2,....

NORMAL

public static final NIFTIIntent NORMAL

[C1, chap 13] Normal distribution (2 params):
p1 = mean, p2 = standard deviation.

FTEST_NONC

public static final NIFTIIntent FTEST_NONC

[C2, chap 30] Noncentral F statistic (3 params):
p1 = numerator DOF, p2 = denominator DOF,
p3 = numerator noncentrality parameter.

CHISQ_NONC

public static final NIFTIIntent CHISQ_NONC

[C2, chap 29] Noncentral chi-squared statistic (2 params):
p1 = DOF, p2 = noncentrality parameter.

LOGISTIC

public static final NIFTIIntent LOGISTIC

[C2, chap 23] Logistic distribution (2 params):
p1 = location, p2 = scale.
Density(x) proportional to sech^2((x-p1)/(2*p2)).

LAPLACE

public static final NIFTIIntent LAPLACE

[C2, chap 24] Laplace distribution (2 params):
p1 = location, p2 = scale.
Density(x) proportional to exp(-abs(x-p1)/p2).

UNIFORM

public static final NIFTIIntent UNIFORM

[C2, chap 26] Uniform distribution: p1 = lower end, p2 = upper end.

TTEST_NONC

public static final NIFTIIntent TTEST_NONC

[C2, chap 31] Noncentral t statistic (2 params):
p1 = DOF, p2 = noncentrality parameter.

WEIBULL

public static final NIFTIIntent WEIBULL

[C1, chap 21] Weibull distribution (3 params):
p1 = location, p2 = scale, p3 = power.
Density(x) proportional to ((x-p1)/p2)^(p3-1) * exp(-((x-p1)/p2)^p3) for x > p1.

CHI

public static final NIFTIIntent CHI

[C1, chap 18] Chi distribution (1 param): p1 = DOF. Density(x) proportional to x^(p1-1) * exp(-x^2/2) for x > 0.
p1 = 1 = 'half normal' distribution
p1 = 2 = Rayleigh distribution
p1 = 3 = Maxwell-Boltzmann distribution.

INVGAUSS

public static final NIFTIIntent INVGAUSS

[C1, chap 15] Inverse Gaussian (2 params):
p1 = mu, p2 = lambda
Density(x) proportional to exp(-p2*(x-p1)^2/(2*p1^2*x)) / x^3 for x > 0.

EXTVAL

public static final NIFTIIntent EXTVAL

[C2, chap 22] Extreme value type I (2 params):
p1 = location, p2 = scale
cdf(x) = exp(-exp(-(x-p1)/p2)).

PVAL

public static final NIFTIIntent PVAL

Data is a 'p-value' (no params).

ESTIMATE

public static final NIFTIIntent ESTIMATE

To signify that the value at each voxel is an estimate of some parameter, set intent_code = NIFTI_INTENT_ESTIMATE. The name of the parameter may be stored in intent_name.

LABEL

public static final NIFTIIntent LABEL

To signify that the value at each voxel is an index into some set of labels, set intent_code = NIFTI_INTENT_LABEL. The filename with the labels may stored in aux_file.

NEURONAME

public static final NIFTIIntent NEURONAME

To signify that the value at each voxel is an index into the NeuroNames labels set, set intent_code = NIFTI_INTENT_NEURONAME.

GENMATRIX

public static final NIFTIIntent GENMATRIX

To store an M x N matrix at each voxel:
- dataset must have a 5th dimension (dim[0]=5 and dim[5]>1)
- intent must be GENMATRIX
- dim[5] must be M*N
- intent_p1 must be M (in float format)
- intent_p2 must be N (ditto)
- the matrix values A[i][[j] are stored in row-order:
- A[0][0] A[0][1] ... A[0][N-1]
- A[1][0] A[1][1] ... A[1][N-1]
- etc., until
- A[M-1][0] A[M-1][1] ... A[M-1][N-1].

SYMMATRIX

public static final NIFTIIntent SYMMATRIX

To store an NxN symmetric matrix at each voxel:
- dataset must have a 5th dimension
- intent must be SYMMATRIX
- dim[5] must be N*(N+1)/2
- intent_p1 must be N (in float format)
- the matrix values A[i][[j] are stored in row-order:
- A[0][0]
- A[1][0] A[1][1]
- A[2][0] A[2][1] A[2][2]
- etc.: row-by-row.

DISPVECT

public static final NIFTIIntent DISPVECT

To signify that the vector value at each voxel is to be taken as a displacement field or vector:
- dataset must have a 5th dimension
- intent must be DISPVECT
- dim[5] must be the dimensionality of the displacment vector (e.g., 3 for spatial displacement, 2 for in-plane).
This intent is specifically for displacements.

VECTOR

public static final NIFTIIntent VECTOR

To signify that the vector value at each voxel is to be taken as a displacement field or vector:
- dataset must have a 5th dimension
- intent must be NIFTI_INTENT_DISPVECT
- dim[5] must be the dimensionality of the displacment vector (e.g., 3 for spatial displacement, 2 for in-plane).
This intent is for general vectors.

POINTSET

public static final NIFTIIntent POINTSET

To signify that the vector value at each voxel is really a spatial coordinate (e.g., the vertices or nodes of a surface mesh):
- dataset must have a 5th dimension
- intent must be POINTSET
- dim[0] = 5
- dim[1] = number of points
- dim[2] = dim[3] = dim[4] = 1
- dim[5] must be the dimensionality of space (e.g., 3 => 3D space).
- intent_name may describe the object these points come from (e.g., "pial", "gray/white" , "EEG", "MEG").

TRIANGLE

public static final NIFTIIntent TRIANGLE

To signify that the vector value at each voxel is really a triple of indexes (e.g., forming a triangle) from a pointset dataset:
- dataset must have a 5th dimension
- intent must be TRIANGLE
- dim[0] = 5
- dim[1] = number of triangles
- dim[2] = dim[3] = dim[4] = 1
- dim[5] = 3
- datatype should be an integer type (preferably INT)
- the data values are indexes (0,1,...) into a pointset dataset.

QUATERNION

public static final NIFTIIntent QUATERNION

To signify that the vector value at each voxel is a quaternion:
- dataset must have a 5th dimension
- intent must be QUATERNION
- dim[0] = 5
- dim[5] = 4
- datatype should be a floating point type.

Method Detail

values

public static NIFTIIntent[] values()

Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:

for (NIFTIIntent c : NIFTIIntent.values())
    System.out.println(c);

Returns:

an array containing the constants of this enum type, in the order they are declared

valueOf

public static NIFTIIntent valueOf(java.lang.String name)

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

java.lang.IllegalArgumentException - if this enum type has no constant with the specified name

java.lang.NullPointerException - if the argument is null

isStatistic

public boolean isStatistic()

Indicates whether this NIFTIIntent is a statistic intent.

Returns:

true if this is a statistic intent.

toString

public java.lang.String toString()

Returns a string describing this NIFTIIntent.

Overrides:

toString in class java.lang.Enum<NIFTIIntent>

Returns:

a string describing this NIFTIIntent.

main

public static void main(java.lang.String[] args)

Run a self-test on the NIFTIIntent class.

Parameters:

args - ignored.