Package | Description |
---|---|
apps | |
numerics | |
simulation.geometry.elements | |
tractography |
Modifier and Type | Field and Description |
---|---|
static Vector3D |
SphFuncPICoCalibrationData.DT1_E1 |
static Vector3D |
SphFuncPICoCalibrationData.DT1_E2 |
static Vector3D |
SphFuncPICoCalibrationData.DT1_E3 |
static Vector3D |
SphFuncPICoCalibrationData.DT2_E1 |
static Vector3D |
SphFuncPICoCalibrationData.DT2_E2 |
static Vector3D |
SphFuncPICoCalibrationData.DT2_E3 |
Constructor and Description |
---|
RGB_ScalarImage(Vector3D[][][][] vecs,
double[] voxelDims,
double[][][] scalars,
double minScalar,
double maxScalar) |
Modifier and Type | Field and Description |
---|---|
Vector3D[] |
EigenSystem3D.eigenvectors |
static Vector3D |
Rotations.X_AXIS |
static Vector3D |
Rotations.Y_AXIS |
static Vector3D |
Rotations.Z_AXIS |
Modifier and Type | Method and Description |
---|---|
Vector3D |
Vector3D.cross(Vector3D v)
Gives vector (cross) product of this with another vector.
|
Vector3D |
BinghamDistribution.e1()
Eigenvector corresponding to the smallest eigenvalue of T.
|
Vector3D |
BinghamDistribution.e2()
Eigenvector corresponding to the second eigenvalue of T.
|
Vector3D |
BinghamDistribution.e3()
Eigenvector corresponding to the largest eigenvalue of T.
|
Vector3D[] |
ACG_Distribution.eigenvectors() |
Vector3D[] |
TwoFibreWatsonFitter.getMus() |
Vector3D[] |
TwoFibreFixedPropWatsonFitter.getMus() |
static Vector3D[] |
TwoFibreBinghamFitter.getMus(double[] params) |
Vector3D |
WatsonDistribution.meanAxis() |
Vector3D |
Vector3D.minus(Vector3D v)
Subtract another vector from this one.
|
Vector3D |
Vector3D.negated()
Get the negated version of this vector
|
Vector3D |
WatsonDistribution.nextVector() |
Vector3D |
BinghamDistribution.nextVector() |
Vector3D |
AxialDistribution.nextVector()
Gets the next Vector from the distribution.
|
Vector3D |
ACG_Distribution.nextVector() |
Vector3D |
WatsonDistribution.nextVector(double k) |
static Vector3D |
WatsonDistribution.nextVector(double meanTheta,
double meanPhi,
double k,
java.util.Random ran) |
static Vector3D |
BinghamDistribution.nextVector(Vector3D[] axes,
double k1,
double k2,
double logNormC,
java.util.Random ran) |
Vector3D |
WatsonDistribution.nextVector(Vector3D mean,
double k) |
static Vector3D |
WatsonDistribution.nextVector(Vector3D mean,
double k,
java.util.Random r) |
Vector3D |
Vector3D.normalized() |
Vector3D |
Vector3D.plus(Vector3D v)
Add another vector to this one.
|
Vector3D |
Vector3D.rotate(double alpha,
Vector3D axis) |
static Vector3D |
Rotations.rotateVector(Vector3D original,
RealMatrix rot)
Apply a rotation matric to a vector.
|
static Vector3D |
Rotations.rotateVector(Vector3D original,
Vector3D axis,
double theta)
Rotate original by angle theta about axis.
|
Vector3D |
Vector3D.scaled(double factor)
Scale vector by some constant.
|
static Vector3D |
Vector3D.vectorFromSPC(double r,
double theta,
double phi)
Get a Cartesian vector from the spherical polar coordinates.
|
Modifier and Type | Method and Description |
---|---|
Vector3D |
Vector3D.cross(Vector3D v)
Gives vector (cross) product of this with another vector.
|
Point3D |
Point3D.displace(Vector3D v) |
double |
Vector3D.dot(Vector3D v)
Gives scalar (dot) product of this with another vector.
|
static RealMatrix |
ACG_Fitter.findA(Vector3D[] sampleVecs)
Finds the covariance matrix A of the ACG
distribution.
|
double[] |
TwoFibreBinghamFitter.fitEstimatedParams(Vector3D[] initAxes,
double[] initKs,
double ftol)
Runs the minimization and returns the answer.
|
double[] |
TwoFibreACGFitter.fitEstimatedParams(Vector3D dt1E1Vec,
Vector3D dt2E1Vec,
double ftol)
Runs the minimization and returns the answer.
|
void |
TwoFibreFixedPropWatsonFitter.fitEstimatedParams(Vector3D mu1,
Vector3D mu2,
double innerCone1,
double outerCone1,
double innerCone2,
double outerCone2,
double initK1,
double initK2,
int attemptsOnCone)
Make estimates of the initial parameters and attempt a minimisation with each.
|
void |
TwoFibreFixedPropWatsonFitter.fitEstimatedParams(Vector3D mu1,
Vector3D mu2,
int attemptsOnCone)
Two cones are defined for each mean axis, centered on the mean axis.
|
static double |
WatsonFitter.fitKappa(EigenSystem3D eig,
Vector3D[] sampleVecs)
Fits kappa for a sample of vectors.
|
static double |
WatsonFitter.fitKappa(Vector3D[] sampleVecs)
Fits kappa for a sample of vectors.
|
static BinghamDistribution |
BinghamDistribution.getBinghamDistribution(Vector3D[] axes,
double[] kappas,
java.util.Random random) |
static BinghamDistribution |
BinghamDistribution.getBinghamDistribution(Vector3D[] axes,
double k1,
double k2,
java.util.Random random) |
static double |
WatsonFitter.getBipolarConfidenceCone(EigenSystem3D eig,
Vector3D[] sampleVecs,
double alpha)
Get the semi-vertical angle of the 100(1 - \alpha)% confidence cone around \mu.
|
double[] |
TwoFibreBinghamFitter.getParams(Vector3D[] initAxes,
double[] initKs)
Gets the parameter array for fObj.
|
static RealMatrix |
Rotations.getRotMat(Vector3D r,
double theta)
Computes the rotation matrix that rotates by angle theta about axis
r = (rx, ry, rz).
|
static RealMatrix |
Rotations.getRotMat(Vector3D vec,
Vector3D targetAxis)
Get rotation matrix of one vector onto another vector.
|
static double |
WatsonFitter.ksTest(Vector3D[] sampleVecs,
Vector3D mu,
double kappa)
Calculate goodness according to the Kolmogorov-Smirnov test.
|
static double |
WatsonFitter.ksTest(Vector3D[] sampleVecs,
Vector3D mu,
double kappa)
Calculate goodness according to the Kolmogorov-Smirnov test.
|
static double |
WatsonFitter.kuiperTest(Vector3D mu,
Vector3D[] sampleVecs) |
static double |
WatsonFitter.kuiperTest(Vector3D mu,
Vector3D[] sampleVecs) |
double |
WatsonDistribution.logPDF(Vector3D x)
Evaluate the pdf of the distribution.
|
double |
BinghamDistribution.logPDF(Vector3D x)
Evaluate the pdf of the distribution.
|
double |
ACG_Distribution.logPDF(Vector3D x)
Gets the log pdf of the distribution.
|
double |
WatsonDistribution.logPDF(Vector3D x,
double k)
Evaluate the pdf of the distribution.
|
static double |
WatsonDistribution.logPDF(Vector3D mean,
Vector3D x,
double k)
Evaluate the pdf of any Watson distribution.
|
Vector3D |
Vector3D.minus(Vector3D v)
Subtract another vector from this one.
|
static Vector3D |
BinghamDistribution.nextVector(Vector3D[] axes,
double k1,
double k2,
double logNormC,
java.util.Random ran) |
Vector3D |
WatsonDistribution.nextVector(Vector3D mean,
double k) |
static Vector3D |
WatsonDistribution.nextVector(Vector3D mean,
double k,
java.util.Random r) |
double |
WatsonDistribution.pdf(Vector3D x)
Evaluate the pdf of the distribution.
|
double |
BinghamDistribution.pdf(Vector3D x)
Evaluate the pdf of the distribution.
|
double |
AxialDistribution.pdf(Vector3D v)
Gets the probability density for a given unit vector.
|
double |
ACG_Distribution.pdf(Vector3D x)
Gets the pdf of the distribution.
|
static double |
BinghamDistribution.pdf(Vector3D[] axes,
double[] bingPars,
Vector3D x)
Evaluate the pdf of the distribution.
|
static double |
BinghamDistribution.pdf(Vector3D[] axes,
double[] bingPars,
Vector3D x)
Evaluate the pdf of the distribution.
|
double |
WatsonDistribution.pdf(Vector3D x,
double k)
Evaluate the pdf of the distribution.
|
static double |
WatsonDistribution.pdf(Vector3D mean,
Vector3D x,
double k)
Evaluate the pdf of any Watson distribution.
|
Vector3D |
Vector3D.plus(Vector3D v)
Add another vector to this one.
|
Vector3D |
Vector3D.rotate(double alpha,
Vector3D axis) |
static DT |
Rotations.rotateTensor(DT original,
Vector3D newE1)
Rotate a tensor so that it's e1 is aligned with vector.
|
static Vector3D |
Rotations.rotateVector(Vector3D original,
RealMatrix rot)
Apply a rotation matric to a vector.
|
static Vector3D |
Rotations.rotateVector(Vector3D original,
Vector3D axis,
double theta)
Rotate original by angle theta about axis.
|
void |
TwoFibreFixedPropWatsonFitter.setInitParams(Vector3D mu1,
Vector3D mu2,
double k1,
double k2)
Set an initial estimate of the parameters.
|
void |
TwoFibreBipolarWatsonFitter.setInitParams(Vector3D mu1,
Vector3D mu2,
double k1,
double k2)
Set an initial estimate of the parameters.
|
static double |
WatsonDistribution.sumLogPDF(Vector3D mean,
Vector3D[] x,
double k)
Calculate the log likelihood of a set of axes.
|
static double |
WatsonDistribution.sumLogPDF(Vector3D mean,
Vector3D[] x,
double k)
Calculate the log likelihood of a set of axes.
|
static RealMatrix |
SphericalDistributionFitter.tBar(Vector3D[] sampleVecs) |
static EigenSystem3D |
SphericalDistributionFitter.tBarEigenSystem(Vector3D[] sampleVecs) |
static double |
WatsonFitter.testBipolarRotSymm(EigenSystem3D eig,
Vector3D mu,
Vector3D[] sampleVecs)
Test of rotational symmetry for a bipolar distribution.
|
static double |
WatsonFitter.testBipolarRotSymm(EigenSystem3D eig,
Vector3D mu,
Vector3D[] sampleVecs)
Test of rotational symmetry for a bipolar distribution.
|
static double |
WatsonFitter.testGirdleRotSymm(EigenSystem3D eig,
Vector3D mu,
Vector3D[] sampleVecs)
Test rotational symmetry for a girdle distribution.
|
static double |
WatsonFitter.testGirdleRotSymm(EigenSystem3D eig,
Vector3D mu,
Vector3D[] sampleVecs)
Test rotational symmetry for a girdle distribution.
|
static double[] |
Vector3D.thetaPhi(Vector3D v) |
Constructor and Description |
---|
ACG_Distribution(Vector3D[] evecs,
double[] sigmaSqs,
java.util.Random r) |
BinghamDistribution(Vector3D[] axes,
double k1,
double k2,
double normC,
java.util.Random random) |
EigenSystem3D(Vector3D[] vectors,
double[] values) |
TwoFibreACGFitter(Vector3D[] vecs) |
TwoFibreBinghamFitter(Vector3D[] vecs) |
TwoFibreBipolarWatsonFitter(Vector3D[] axes) |
TwoFibreFixedPropWatsonFitter(Vector3D[] axes,
double prop) |
TwoFibreWatsonFitter(Vector3D[] axes) |
Vector3D(Vector3D v) |
WatsonDistribution(Vector3D mean,
double k,
java.util.Random r) |
WatsonDistribution(Vector3D mean,
java.util.Random r) |
Constructor and Description |
---|
FacetCylinder(Vector3D P,
double r,
int N,
double p)
constructor with default alignment
|
FacetCylinder(Vector3D V,
Vector3D P,
double r,
int N,
double p)
constructor.
|
Modifier and Type | Method and Description |
---|---|
Vector3D[] |
HistBin.getDirsList() |
Vector3D[] |
BS_DT_TractographyImage.getEigenvectors(int i,
int j,
int k)
Gets a new bootstrap estimate at every call.
|
Vector3D[] |
TractographyImage.getPDs(int i,
int j,
int k) |
Vector3D[] |
PICoTractographyImage.getPDs(int i,
int j,
int k)
Gets a new sample from each PICo PDF in this voxel.
|
Vector3D[] |
DT_TractographyImage.getPDs(int i,
int j,
int k) |
Vector3D[] |
BootstrapTractographyImage.getPDs(int i,
int j,
int k)
Gets a new bootstrap estimate at every call.
|
Vector3D[] |
BayesDiracTractographyImage.getPDs(int i,
int j,
int k) |
Vector3D[] |
TractographyImage.getPDs(int i,
int j,
int k,
Vector3D fibreOrientation) |
Vector3D[] |
BayesDiracTractographyImage.getPDs(int i,
int j,
int k,
Vector3D fibreOrientation) |
Vector3D[] |
SimplePICoRandomizer.getRandomizedPDs(int i,
int j,
int k) |
Vector3D[] |
PICoRandomizer.getRandomizedPDs(int i,
int j,
int k)
Randomizes the PDs in the voxel (i,j,k) and returns them.
|
Vector3D[] |
PICoBootstrapRandomizer.getRandomizedPDs(int i,
int j,
int k) |
Vector3D[] |
BayesDiracRandomizer.getRandomizedPDs(int i,
int j,
int k)
Samples from the likelihood function in this voxel, does not consider the prior fibre orientation.
|
Vector3D[] |
BayesDiracRandomizer.getRandomizedPDs(int i,
int j,
int k,
Vector3D previousDir)
Samples from the posterior distribution in this voxel.
|
Vector3D |
TendInterpolator.getTrackingDirection(int i,
int j,
int k,
Vector3D previousDirection) |
Vector3D |
VectorLinearInterpolator.getTrackingDirection(Point3D point,
int pdIndex,
boolean direction)
Get the initial tracking direction, given a pdIndex and a seed point.
|
Vector3D |
TendInterpolator.getTrackingDirection(Point3D point,
int pdIndex,
boolean direction)
Get the initial tracking direction, given a pdIndex and a seed point.
|
Vector3D |
NeighbourChoiceInterpolator.getTrackingDirection(Point3D point,
int pdIndex,
boolean direction)
Get the initial tracking direction, given a pdIndex and a seed point.
|
Vector3D |
ImageInterpolator.getTrackingDirection(Point3D point,
int pdIndex,
boolean direction)
Gets the initial tracking direction, given a pdIndex and a seed point.
|
Vector3D |
DT_LinearInterpolator.getTrackingDirection(Point3D point,
int pdIndex,
boolean direction)
Get the initial tracking direction, given a pdIndex and a seed point.
|
Vector3D |
VectorLinearInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection) |
Vector3D |
TendInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection) |
Vector3D |
NeighbourChoiceInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection)
Get the tracking direction at some point.
|
Vector3D |
ImageInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection)
Gets tracking direction at some point.
|
Vector3D |
DT_LinearInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection) |
Modifier and Type | Method and Description |
---|---|
void |
Histogram.add(Vector3D direction,
double eig1,
double eig2) |
void |
HistBin.addDirToList(Vector3D direction) |
Vector3D[] |
TractographyImage.getPDs(int i,
int j,
int k,
Vector3D fibreOrientation) |
Vector3D[] |
BayesDiracTractographyImage.getPDs(int i,
int j,
int k,
Vector3D fibreOrientation) |
Vector3D[] |
BayesDiracRandomizer.getRandomizedPDs(int i,
int j,
int k,
Vector3D previousDir)
Samples from the posterior distribution in this voxel.
|
Vector3D |
TendInterpolator.getTrackingDirection(int i,
int j,
int k,
Vector3D previousDirection) |
Vector3D |
VectorLinearInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection) |
Vector3D |
TendInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection) |
Vector3D |
NeighbourChoiceInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection)
Get the tracking direction at some point.
|
Vector3D |
ImageInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection)
Gets tracking direction at some point.
|
Vector3D |
DT_LinearInterpolator.getTrackingDirection(Point3D point,
Vector3D previousDirection) |
double |
SimplePICoRandomizer.pdf(int i,
int j,
int k,
int pdIndex,
Vector3D v) |
double |
PICoRandomizer.pdf(int i,
int j,
int k,
int pdIndex,
Vector3D v)
Evaluates the PDF for a vector at voxel (i,j,k).
|
double |
PICoBootstrapRandomizer.pdf(int i,
int j,
int k,
int pdIndex,
Vector3D v)
Evaluates the PDF for a vector at voxel (i,j,k).
|
void |
TargetCP_Image.setDirectional(Vector3D v)
Call this method to split the streamlines in two at the seed point and produce
separate connection probability maps from each.
|
void |
ConnectivitySegmentedImage.setDirectional(Vector3D v)
Call this method to split the streamlines in two at the seed point and produce
separate connection probability maps from each.
|
Constructor and Description |
---|
BallStickTractographyImage(Vector3D[][][][] vecs,
int[][][] npds,
double[] voxelDims)
Constructs an image directly from an array of vectors.
|
PD_TractographyImage(Vector3D[][][][] vectors,
double[] voxelDims,
int vectorsPerPD) |
TractographyImage(Vector3D[][][][] vectors,
double[] voxelDims,
int vectorsPerPD)
Matlab constructor.
|
VoxelList(Voxel[] voxels,
int seedPointIndex,
double xVoxelDim,
double yVoxelDim,
double zVoxelDim,
Vector3D tanAtSeed,
Vector3D negativeTanAtSeed) |