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NIFTI1_INTENT_CODES

nifti1 intent codes, to describe intended meaning of dataset contents. More...

Defines

#define NIFTI_INTENT_CORREL   2
#define NIFTI_INTENT_TTEST   3
#define NIFTI_INTENT_FTEST   4
#define NIFTI_INTENT_ZSCORE   5
#define NIFTI_INTENT_CHISQ   6
#define NIFTI_INTENT_BETA   7
#define NIFTI_INTENT_BINOM   8
#define NIFTI_INTENT_GAMMA   9
#define NIFTI_INTENT_POISSON   10
#define NIFTI_INTENT_NORMAL   11
#define NIFTI_INTENT_FTEST_NONC   12
#define NIFTI_INTENT_CHISQ_NONC   13
#define NIFTI_INTENT_LOGISTIC   14
#define NIFTI_INTENT_LAPLACE   15
#define NIFTI_INTENT_UNIFORM   16
#define NIFTI_INTENT_TTEST_NONC   17
#define NIFTI_INTENT_WEIBULL   18
#define NIFTI_INTENT_CHI   19
#define NIFTI_INTENT_INVGAUSS   20
#define NIFTI_INTENT_EXTVAL   21
#define NIFTI_INTENT_PVAL   22
#define NIFTI_INTENT_LOGPVAL   23
#define NIFTI_INTENT_LOG10PVAL   24
#define NIFTI_FIRST_STATCODE   2
#define NIFTI_LAST_STATCODE   24
#define NIFTI_INTENT_ESTIMATE   1001
#define NIFTI_INTENT_LABEL   1002
#define NIFTI_INTENT_NEURONAME   1003
#define NIFTI_INTENT_GENMATRIX   1004
#define NIFTI_INTENT_SYMMATRIX   1005
#define NIFTI_INTENT_DISPVECT   1006
#define NIFTI_INTENT_VECTOR   1007
#define NIFTI_INTENT_POINTSET   1008
#define NIFTI_INTENT_TRIANGLE   1009
#define NIFTI_INTENT_QUATERNION   1010
#define NIFTI_INTENT_DIMLESS   1011
#define NIFTI_INTENT_TIME_SERIES   2001
#define NIFTI_INTENT_NODE_INDEX   2002
#define NIFTI_INTENT_RGB_VECTOR   2003
#define NIFTI_INTENT_RGBA_VECTOR   2004
#define NIFTI_INTENT_SHAPE   2005

Detailed Description

nifti1 intent codes, to describe intended meaning of dataset contents.

Define Documentation

#define NIFTI_FIRST_STATCODE   2
 

Smallest intent_code that indicates a statistic.

#define NIFTI_INTENT_BETA   7
 

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

#define NIFTI_INTENT_BINOM   8
 

[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.

#define NIFTI_INTENT_CHI   19
 

[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.

#define NIFTI_INTENT_CHISQ   6
 

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

#define NIFTI_INTENT_CHISQ_NONC   13
 

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

#define NIFTI_INTENT_DIMLESS   1011
 

Dimensionless value - no params - although, as in _ESTIMATE the name of the parameter may be stored in intent_name.

#define NIFTI_INTENT_DISPVECT   1006
 

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_code 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)

#define NIFTI_INTENT_ESTIMATE   1001
 

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.

#define NIFTI_INTENT_EXTVAL   21
 

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

#define NIFTI_INTENT_FTEST   4
 

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

#define NIFTI_INTENT_FTEST_NONC   12
 

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

#define NIFTI_INTENT_GAMMA   9
 

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

#define NIFTI_INTENT_GENMATRIX   1004
 

To store an M x N matrix at each voxel:

  • dataset must have a 5th dimension (dim[0]=5 and dim[5]>1)
  • intent_code must be NIFTI_INTENT_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]

#define NIFTI_INTENT_INVGAUSS   20
 

[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.

#define NIFTI_INTENT_LABEL   1002
 

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.

#define NIFTI_INTENT_LAPLACE   15
 

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

#define NIFTI_INTENT_LOG10PVAL   24
 

Data is log10(p-value) (no params). To be safe, a program should compute p = pow(10.,-abs(this_value)). The nifti_stats.c library returns this_value as positive, so that this_value = -log10(p).

#define NIFTI_INTENT_LOGISTIC   14
 

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

#define NIFTI_INTENT_LOGPVAL   23
 

Data is ln(p-value) (no params). To be safe, a program should compute p = exp(-abs(this_value)). The nifti_stats.c library returns this_value as positive, so that this_value = -log(p).

#define NIFTI_INTENT_NEURONAME   1003
 

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

#define NIFTI_INTENT_NODE_INDEX   2002
 

To signify that the value at each location is a node index, from a complete surface dataset.

#define NIFTI_INTENT_NORMAL   11
 

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

#define NIFTI_INTENT_POINTSET   1008
 

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_code must be NIFTI_INTENT_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").

#define NIFTI_INTENT_POISSON   10
 

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

#define NIFTI_INTENT_PVAL   22
 

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

#define NIFTI_INTENT_QUATERNION   1010
 

To signify that the vector value at each voxel is a quaternion:

  • dataset must have a 5th dimension
  • intent_code must be NIFTI_INTENT_QUATERNION
  • dim[0] = 5
  • dim[5] = 4
  • datatype should be a floating point type

#define NIFTI_INTENT_RGBA_VECTOR   2004
 

To signify that the vector value at each location is a 4 valued RGBA vector, of whatever type.

  • dataset must have a 5th dimension
  • dim[0] = 5
  • dim[1] = number of nodes
  • dim[2] = dim[3] = dim[4] = 1
  • dim[5] = 4

#define NIFTI_INTENT_RGB_VECTOR   2003
 

To signify that the vector value at each location is an RGB triplet, of whatever type.

  • dataset must have a 5th dimension
  • dim[0] = 5
  • dim[1] = number of nodes
  • dim[2] = dim[3] = dim[4] = 1
  • dim[5] = 3

#define NIFTI_INTENT_SHAPE   2005
 

To signify that the value at each location is a shape value, such as the curvature.

#define NIFTI_INTENT_SYMMATRIX   1005
 

To store an NxN symmetric matrix at each voxel:

  • dataset must have a 5th dimension
  • intent_code must be NIFTI_INTENT_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

#define NIFTI_INTENT_TIME_SERIES   2001
 

To signify that the value at each location is from a time series.

#define NIFTI_INTENT_TRIANGLE   1009
 

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_code must be NIFTI_INTENT_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 DT_INT32)
  • the data values are indexes (0,1,...) into a pointset dataset.

#define NIFTI_INTENT_TTEST   3
 

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

#define NIFTI_INTENT_TTEST_NONC   17
 

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

#define NIFTI_INTENT_UNIFORM   16
 

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

#define NIFTI_INTENT_WEIBULL   18
 

[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.

#define NIFTI_INTENT_ZSCORE   5
 

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

#define NIFTI_LAST_STATCODE   24
 

Largest intent_code that indicates a statistic.

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