Package | Description |
---|---|
com.mockturtlesolutions.snifflib.datatypes |
Contains standard classes and interfaces for storage, retrieval, and display.
|
com.mockturtlesolutions.snifflib.datatypes.database |
Base classes for the repository storage framework of the datatypes package.
|
com.mockturtlesolutions.snifflib.datatypes.workbench |
Graphical interface classes for the repository storage framework of the datatypes package.
|
com.mockturtlesolutions.snifflib.functions |
Contains standard classes and interfaces for defining functions.
|
com.mockturtlesolutions.snifflib.functions.transcendental |
Base clases and interfaces for transcendental functions.
|
com.mockturtlesolutions.snifflib.graphics |
Contains standard classes and interfaces for 2D and 3D graphics.
|
com.mockturtlesolutions.snifflib.guitools.components |
Widgets and support classes for graphical user interfaces.
|
com.mockturtlesolutions.snifflib.integration |
Contains standard classes and interfaces for performing integration.
|
com.mockturtlesolutions.snifflib.invprobs |
Contains standard classes and interfaces for solving statistical inverse problems.
|
com.mockturtlesolutions.snifflib.linalg |
Contains standard classes and interfaces for linear algebra.
|
com.mockturtlesolutions.snifflib.mcmctools.workbench |
Graphical interface classes for the repository storage framework of the mcmctools package.
|
com.mockturtlesolutions.snifflib.pde |
Contains standard classes and interfaces for numerical solution of partial differential equations.
|
com.mockturtlesolutions.snifflib.spreadsheets |
Contains standard classes and interfaces for implmenting simple programmable spreadsheets.
|
com.mockturtlesolutions.snifflib.stats |
Contains standard classes and interfaces for statistical storage classes and algorithms.
|
com.mockturtlesolutions.snifflib.testfun |
Contains some typical functions useful for testing various algorithms.
|
com.mockturtlesolutions.snifflib.util |
Contains some utility classes providing methods of broad applicability.
|
com.mockturtlesolutions.snifflib.util.database |
Base classes for the repository storage framework of the util package.
|
com.mockturtlesolutions.snifflib.xppauttools.database |
Base classes for the repository storage framework of xppauttools
|
Modifier and Type | Class and Description |
---|---|
class |
SblMatrix
Sparse DblMatrix variant.
|
Modifier and Type | Field and Description |
---|---|
static DblMatrix |
DblMatrix.E |
static DblMatrix |
DblMatrix.HALF |
protected DblMatrix |
DblSortUnit.Index |
protected DblMatrix |
DblSort.Indices |
static DblMatrix |
DblMatrix.INF |
DblMatrix |
MarkovChain.Iterations |
static DblMatrix |
DblMatrix.NaN |
static DblMatrix |
DblMatrix.NEGATIVE_INFINITY |
static DblMatrix |
DblMatrix.ONE |
static DblMatrix |
DblMatrix.PI |
static DblMatrix |
DblMatrix.POSITIVE_INFINITY |
protected DblMatrix |
DblSort.Sorted |
static DblMatrix |
DblMatrix.SQRT2 |
DblMatrix |
MarkovChain.StochasticMatrix |
static DblMatrix |
DblMatrix.TWO |
protected DblMatrix |
DblSortUnit.Value |
DblMatrix |
Subscript.Value |
static DblMatrix |
DblMatrix.ZERO |
Modifier and Type | Method and Description |
---|---|
static DblMatrix |
DblMatrix.abs(DblMatrix Y) |
DblMatrix |
DataSetAdapter.abs(java.lang.String VarA) |
static DblMatrix |
DblMatrix.acos(DblMatrix Y) |
DblMatrix |
DataSetAdapter.acos(java.lang.String VarA) |
static DblMatrix |
DblMatrix.acosh(DblMatrix Y) |
static DblMatrix |
DblMatrix.acoth(DblMatrix Y) |
static DblMatrix |
DblMatrix.acsch(DblMatrix Y) |
static DblMatrix |
DblMatrix.add(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.add(int X,
DblMatrix Y) |
DblMatrix |
DataSetAdapter.add(java.lang.String VarA,
java.lang.String VarB) |
static DblMatrix |
DblMatrix.all(DblMatrix X)
Boolean "all" down dimension 1.
|
static DblMatrix |
DblMatrix.All(DblMatrix X)
Boolean "all" inclusive of all values.
|
static DblMatrix |
DblMatrix.all(DblMatrix X,
int dim)
Boolean "all" down dimension dim.
|
DblMatrix |
DblMatrix.and(DblMatrix Z)
"And" one matrix with another.
|
DblMatrix |
SblMatrix.and(DblMatrix Z)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(DblMatrix Z,
DblMatrix X)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(DblMatrix Z,
double X)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(DblMatrix Z,
int X)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(double X,
DblMatrix Z)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(int X,
DblMatrix Z)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.anscombe(DblMatrix X)
Performs Anscombe transformation.
|
static DblMatrix |
DblMatrix.anscombe(java.lang.Double X) |
static DblMatrix |
DblMatrix.any(DblMatrix X)
Boolean "any" down dimension 1.
|
static DblMatrix |
DblMatrix.Any(DblMatrix X)
Boolean "any" inclusive of all values.
|
static DblMatrix |
DblMatrix.any(DblMatrix X,
int dim)
Boolean "any" down dimension dim.
|
DblMatrix |
DblSort.applyTo(DblMatrix x)
Permutes the input matrix along the first dimension according the
the current values of these sorted indices.
|
DblMatrix |
DblSort.applyTo(DblMatrix x,
int dim)
Permutes the input matrix along the given dimension according the
the current values of these sorted indices.
|
static DblMatrix |
DblMatrix.asech(DblMatrix Y) |
static DblMatrix |
DblMatrix.asin(DblMatrix Y) |
DblMatrix |
DataSetAdapter.asin(java.lang.String VarA) |
static DblMatrix |
DblMatrix.asinh(DblMatrix Y) |
static DblMatrix |
DblMatrix.atan(DblMatrix Y) |
DblMatrix |
DataSetAdapter.atan(java.lang.String VarA) |
static DblMatrix |
DblMatrix.atan2(DblMatrix Y,
DblMatrix X) |
DblMatrix |
DataSetAdapter.atan2(java.lang.String VarA,
java.lang.String VarB) |
static DblMatrix |
DblMatrix.atanh(DblMatrix Y) |
DblMatrix |
DblMatrix.bounds()
Return the smallest and largest values in a matrix.
|
static DblMatrix |
DblMatrix.bounds(DblMatrix X)
Return the smallest and largest values in a matrix.
|
static DblMatrix |
DblMatrix.cbrt(DblMatrix Y) |
DblMatrix |
DataSetAdapter.cbrt(java.lang.String VarA) |
protected DblMatrix |
DblMatrix.cccopy()
Copy using the current counter configuration.
|
static DblMatrix |
DblMatrix.ceil(DblMatrix Y) |
DblMatrix |
DataSetAdapter.ceil(java.lang.String VarA) |
static DblMatrix |
DblMatrix.comp(DblMatrix u,
DblMatrix v)
Return the scalar projection (or component) of u onto v.
|
DblMatrix |
DblMatrix.concat(DblMatrix B,
int dim) |
static DblMatrix |
DblMatrix.convertStringToDbl(java.lang.String in) |
DblMatrix |
DblMatrix.copy()
Make a deep copy of the matrix.
|
static DblMatrix |
DblMatrix.copySign(DblMatrix X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.copySign(DblMatrix X,
double b) |
static DblMatrix |
DblMatrix.copySign(DblMatrix X,
float Y) |
static DblMatrix |
DblMatrix.copySign(DblMatrix X,
int Y) |
static DblMatrix |
DblMatrix.cos(DblMatrix Y) |
DblMatrix |
DataSetAdapter.cos(java.lang.String VarA) |
static DblMatrix |
DblMatrix.cosh(DblMatrix Y) |
DblMatrix |
DataSetAdapter.cosh(java.lang.String VarA) |
static DblMatrix |
DblMatrix.coth(DblMatrix Y) |
static DblMatrix |
DblMatrix.csc(DblMatrix Y) |
static DblMatrix |
DblMatrix.csch(DblMatrix Y) |
DblMatrix |
DblMatrix.cumProd(int dim)
Calculate the cummulative product down the given dimension.
|
DblMatrix |
DblMatrix.cumSum(int dim)
Calculate the cummulative sum down the given dimension.
|
DblMatrix |
DblParamSet.Dblget(java.lang.String fieldname)
Provides a Dblget method.
|
static DblMatrix |
DblMatrix.degreesToRadians(DblMatrix x) |
static DblMatrix |
DblMatrix.degreesToRadians(double x) |
static DblMatrix |
DblMatrix.degreesToRadians(int x) |
static DblMatrix |
DblMatrix.det(DblMatrix X)
Returns the determinant of the square matrix.
|
DblMatrix |
DblMatrix.diag()
Get main diagonal elements of an ND matrix.
|
DblMatrix |
DblMatrix.diag(int diagonal)
Get particular diagonal.
|
static DblMatrix |
DblMatrix.diameter(DblMatrix X)
The maximum euclidean distance between columns in a matrix.
|
static DblMatrix |
DblMatrix.divide(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.divide(int X,
DblMatrix Y) |
DblMatrix |
DataSetAdapter.divide(java.lang.String VarA,
java.lang.String VarB) |
DblMatrix |
DblMatrix.divideBy(DblMatrix X)
Divide one matrix by another.
|
DblMatrix |
SblMatrix.divideBy(DblMatrix X) |
DblMatrix |
DblMatrix.divideBy(double X)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.divideBy(java.lang.Double X)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.divideBy(int X)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.dot(DblMatrix X)
Dot product of two matrices.
|
DblMatrix |
SblMatrix.dot(DblMatrix X) |
static DblMatrix |
DblMatrix.dummyCoding(DblMatrix X)
Produces a dummy-variable encoding matrix based on the unique values of the input
array.
|
static DblMatrix |
DblMatrix.dummyCoding(DblMatrix X,
boolean intercept)
Produces a dummy-variable encoding matrix based on the unique values of the input
array.
|
static DblMatrix |
DblMatrix.dummyCoding(DblMatrix X,
boolean intercept,
boolean fullrank)
Produces a dummy-variable encoding matrix based on the unique values of the input
array.
|
DblMatrix |
DblMatrix.eq(DblMatrix X)
Boolean equality comparison.
|
DblMatrix |
DblMatrix.eq(double X)
Boolean inequality comparison determining equal-to.
|
DblMatrix |
DblMatrix.eq(int X)
Boolean inequality comparison determining equal-to.
|
static DblMatrix |
DblMatrix.euclid(DblMatrix X)
Euclidean distance among columns.
|
static DblMatrix |
DblMatrix.exp(DblMatrix Y) |
DblMatrix |
DataSetAdapter.exp(java.lang.String VarA) |
static DblMatrix |
DblMatrix.expm1(DblMatrix Y) |
DblMatrix |
DataSetAdapter.expm1(java.lang.String VarA) |
static DblMatrix |
DblMatrix.factorial(DblMatrix X) |
static DblMatrix |
DblMatrix.factorial(double X) |
static DblMatrix |
DblMatrix.factorial(int X) |
static DblMatrix |
DblMatrix.fill(DblMatrix X,
int[] Size)
Create a matrix of arbitrary dimension filled with the same value.
|
static DblMatrix |
DblMatrix.fill(double X,
int[] Size)
Create a matrix of arbitrary dimension filled with the same value.
|
static DblMatrix |
DblMatrix.fill(java.lang.Double X,
int[] Size)
Create a matrix of arbitrary dimension filled with the same value.
|
static DblMatrix |
DblMatrix.fill(int X,
int[] Size)
Create a matrix of arbitrary dimension filled with the same value.
|
static DblMatrix |
DblMatrix.find(DblMatrix X) |
DblMatrix |
DblMatrix.fliplr()
Reverses order of matrix elements in left-to-right.
|
DblMatrix |
DblMatrix.flipud()
Reverses order of matrix elements in top-to-bottom.
|
static DblMatrix |
DblMatrix.floor(DblMatrix Y) |
DblMatrix |
DataSetAdapter.floor(java.lang.String VarA) |
static DblMatrix |
DblMatrix.gap(DblMatrix u,
DblMatrix v)
Returns the cosine of the angle between the two input vectors.
|
DblMatrix |
DblMatrix.geq(DblMatrix X)
Boolean inequality comparison determining greater-than-or-equal-to.
|
DblMatrix |
DblMatrix.geq(double X)
Boolean inequality comparison determining greater-than-or-equal-to.
|
DblMatrix |
DblMatrix.geq(int X)
Boolean inequality comparison determining greater-than-or-equal-to.
|
DblMatrix |
DblMatrix.getCol(DblMatrix col)
Get a particular col.
|
DblMatrix |
DblMatrix.getCol(int col)
Get a particular col.
|
DblMatrix |
DblMatrix.getDblAt(int k)
Return the scalar DblMatrix at a particular index.
|
DblMatrix |
DblSortUnit.getDblMatrix() |
static DblMatrix |
DblMatrix.getExponent(DblMatrix Y) |
DblMatrix |
DblSortUnit.getIndex() |
DblMatrix |
DblSort.getIndices()
Get the permuted indices along the sorted dimension.
|
DblMatrix |
DblMatrix.getIndices(DblMatrix I)
Get values whose indices are given in a DblMatrix.
|
DblMatrix |
DblMatrix.getIndices(int[] I)
Get values whose indices are given.
|
DblMatrix |
DblMatrix.getMap(DblMatrix MAP)
Get values from a matrix based on a logical map.
|
static DblMatrix |
DblMatrix.getNextRow(java.io.StreamTokenizer STT) |
DblMatrix |
DblParamSet.getParam(java.lang.String name) |
DblMatrix |
DblMatrix.getRow(DblMatrix row)
Get a particular row.
|
DblMatrix |
DblMatrix.getRow(int row)
Get a particular row.
|
DblMatrix |
DblSort.getSorted()
Get the sorted DblMatrix.
|
DblMatrix |
DblMatrix.getSubMatrix(Subscript[] subscripts)
Get a matrix of values by sub-indexing into an existing matrix.
|
DblMatrix |
NamedColumnMapping.getVar(DblMatrix W,
java.lang.String name)
Gets the column of the input matrix according to the current variable name mapping.
|
static DblMatrix[] |
DblMatrix.GramSchmidt(DblMatrix[] u) |
static DblMatrix[] |
DblMatrix.grid(DblMatrix[] X) |
static DblMatrix[] |
DblMatrix.grid(DblMatrix X1,
DblMatrix X2) |
static DblMatrix[] |
DblMatrix.grid(DblMatrix X1,
DblMatrix X2,
DblMatrix X3) |
DblMatrix |
DblMatrix.gt(DblMatrix X)
Boolean inequality comparison determining greater-than.
|
DblMatrix |
DblMatrix.gt(double X)
Boolean inequality comparison determining greater-than.
|
DblMatrix |
DblMatrix.gt(int X)
Boolean inequality comparison determining greater-than.
|
static DblMatrix |
DblMatrix.hypot(DblMatrix X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.hypot(double x,
double y) |
static DblMatrix |
DblMatrix.hypot(java.lang.Double x,
java.lang.Double y) |
DblMatrix |
DataSetAdapter.hypot(java.lang.String VarA,
java.lang.String VarB) |
static DblMatrix |
DblMatrix.I(DblMatrix X)
Create square identity matrix with N rows.
|
static DblMatrix |
DblMatrix.I(int N)
Create square identity matrix with N rows.
|
static DblMatrix |
DblMatrix.I(int[] size)
Create rectangular identity matrix with given size.
|
static DblMatrix |
DblMatrix.ianscombe(DblMatrix X) |
static DblMatrix |
DblMatrix.ianscombe(java.lang.Double X) |
static DblMatrix |
DblMatrix.IEEEremainder(DblMatrix Y,
DblMatrix X)
Calculate remainder.
|
static DblMatrix |
DblMatrix.IEEEremainder(DblMatrix Y,
double X) |
static DblMatrix |
DblMatrix.IEEEremainder(DblMatrix Y,
int X) |
DblMatrix |
DataSetAdapter.IEEEremainder(java.lang.String VarA,
java.lang.String VarB) |
DblMatrix |
DblMatrix.iPermute(int[] Perm) |
static DblMatrix |
DblMatrix.isInfinite(DblMatrix X)
Boolean isInfinite
|
static DblMatrix |
DblMatrix.isNaN(DblMatrix X)
Boolean isNaN
|
static DblMatrix |
DblMatrix.isReal(DblMatrix X)
Boolean isReal
Determines if elements are not NaN nor Infinite;
|
static DblMatrix |
DblMatrix.isScalar(DblMatrix X)
Determine if a matrix is sized 1x1.
|
static DblMatrix |
DblMatrix.J(DblMatrix X)
Create a column vector of ones.
|
static DblMatrix |
DblMatrix.J(int N)
Create a column vector of ones.
|
DblMatrix |
DblMatrix.kronecker(DblMatrix X)
Returns Kronecker product taken with respect to the input matrix.
|
DblMatrix |
SblMatrix.ldot(DblMatrix X)
Same as X.dot(this)
|
DblMatrix |
DblMatrix.leq(DblMatrix X)
Boolean inequality comparison determining less-than-or-equal-to.
|
DblMatrix |
DblMatrix.leq(double X)
Boolean inequality comparison determining less-than-or-equal-to.
|
DblMatrix |
DblMatrix.leq(int X)
Boolean inequality comparison determining less-than-or-equal-to.
|
static DblMatrix |
DblMatrix.load(java.io.File dat)
Loads the whitespace-delimited text file as a DblMatrix.
|
static DblMatrix |
DblMatrix.load(java.io.File dat,
int headerlines)
Loads the whitespace-delimited text file as a DblMatrix ignoring the first N lines.
|
static DblMatrix |
DblMatrix.log(DblMatrix Y) |
static DblMatrix |
DblMatrix.log(double Y) |
static DblMatrix |
DblMatrix.log(java.lang.Double Y) |
static DblMatrix |
DblMatrix.log(int Y) |
DblMatrix |
DataSetAdapter.log(java.lang.String VarA) |
static DblMatrix |
DblMatrix.log10(DblMatrix Y) |
static DblMatrix |
DblMatrix.log10(double Y) |
static DblMatrix |
DblMatrix.log10(java.lang.Double Y) |
static DblMatrix |
DblMatrix.log10(int Y) |
DblMatrix |
DataSetAdapter.log10(java.lang.String VarA) |
static DblMatrix |
DblMatrix.log1p(DblMatrix Y) |
static DblMatrix |
DblMatrix.log1p(double Y) |
static DblMatrix |
DblMatrix.log1p(java.lang.Double Y) |
static DblMatrix |
DblMatrix.log1p(int Y) |
DblMatrix |
DataSetAdapter.log1p(java.lang.String VarA) |
static DblMatrix |
DblMatrix.logGamma(DblMatrix x) |
static DblMatrix |
DblMatrix.logGamma(double x) |
static DblMatrix |
DblMatrix.logGamma(int x) |
static DblMatrix |
DblMatrix.logxy(DblMatrix X,
DblMatrix Y)
Log base x of y.
|
static DblMatrix |
DblMatrix.logxy(double X,
double Y)
Log base x of y.
|
static DblMatrix |
DblMatrix.logxy(double X,
java.lang.Double Y)
Log base x of y.
|
static DblMatrix |
DblMatrix.logxy(double X,
int Y)
Log base x of y.
|
static DblMatrix |
DblMatrix.logxy(int X,
int Y)
Log base x of y.
|
DblMatrix |
DblMatrix.lt(DblMatrix X)
Boolean inequality comparison determining less-than.
|
DblMatrix |
DblMatrix.lt(double X)
Boolean inequality comparison determining less-than.
|
DblMatrix |
DblMatrix.lt(int X)
Boolean inequality comparison determining less-than.
|
DblMatrix |
DblMatrix.max()
Calculate maximum down the first dimension.
|
DblMatrix |
DblMatrix.Max()
Calculate the grand maximum (over all elements)
|
DblMatrix |
DblMatrix.max(DblMatrix X)
Calculate maximum between two matrices.
|
static DblMatrix |
DblMatrix.Max(DblMatrix X)
Calculate the grand maximum (over all elements)
|
static DblMatrix |
DblMatrix.max(DblMatrix X,
DblMatrix Y)
Return maximum between two matrices.
|
static DblMatrix |
DblMatrix.max(DblMatrix X,
double Y)
Return maximum between a matrix and a scalar.
|
static DblMatrix |
DblMatrix.max(DblMatrix X,
java.lang.Double Y)
Return maximum between a matrix and a scalar.
|
static DblMatrix |
DblMatrix.max(DblMatrix X,
int dim)
Calculate maximum down the specified dimension.
|
static DblMatrix |
DblMatrix.max(double X,
DblMatrix Y) |
DblMatrix |
DblMatrix.max(int dim)
Calculate maximum down the specified dimension.
|
DblMatrix |
DataSetAdapter.max(java.lang.String VarA,
java.lang.String VarB) |
DblMatrix |
DblMatrix.mean()
Calculate mean down the first dimension.
|
DblMatrix |
DblMatrix.Mean()
Calculate the grand mean (over all elements)
|
static DblMatrix |
DblMatrix.Mean(DblMatrix X)
Calculate the grand mean (over all elements)
|
DblMatrix |
DblMatrix.mean(int dim)
Calculate mean down the specified dimension.
|
DblMatrix |
DblMatrix.Median()
Median of all elements
|
static DblMatrix |
DblMatrix.median(DblMatrix X)
Median of all elements
|
static DblMatrix |
DblMatrix.Median(DblMatrix X)
Median of all elements
|
DblMatrix |
DblMatrix.min()
Calculate minimum down the first dimension.
|
DblMatrix |
DblMatrix.Min()
Calculate the grand minimum (over all elements)
|
DblMatrix |
DblMatrix.min(DblMatrix X)
Calculate minimum between two matrices.
|
static DblMatrix |
DblMatrix.Min(DblMatrix X)
Calculate the grand minimum (over all elements)
|
static DblMatrix |
DblMatrix.min(DblMatrix X,
DblMatrix Y)
Return minimum between two matrices.
|
static DblMatrix |
DblMatrix.min(DblMatrix Y,
double X) |
static DblMatrix |
DblMatrix.min(DblMatrix X,
java.lang.Double Y)
Return minimum between a matrix and a scalar.
|
static DblMatrix |
DblMatrix.min(DblMatrix Y,
int X) |
static DblMatrix |
DblMatrix.min(DblMatrix Y,
java.lang.Number X) |
static DblMatrix |
DblMatrix.min(double X,
DblMatrix Y) |
DblMatrix |
DblMatrix.min(int dim)
Calculate minimum down the specified dimension.
|
static DblMatrix |
DblMatrix.min(int X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.min(java.lang.Number X,
DblMatrix Y) |
DblMatrix |
DataSetAdapter.min(java.lang.String VarA,
java.lang.String VarB) |
DblMatrix |
DblMatrix.minus(DblMatrix X)
Subtract input matrix from this matrix.
|
DblMatrix |
SblMatrix.minus(DblMatrix X) |
DblMatrix |
DblMatrix.minus(double X)
Subtract input matrix from this matrix.
|
DblMatrix |
DblMatrix.minus(int X)
Subtract input matrix from this matrix.
|
static DblMatrix |
DblMatrix.mod(DblMatrix X,
DblMatrix Y)
Modulo of X after division by Y.
|
static DblMatrix |
DblMatrix.mod(DblMatrix X,
double Y)
Modulo of X after division by Y.
|
static DblMatrix |
DblMatrix.mod(DblMatrix X,
java.lang.Double Y)
Modulo of X after division by Y.
|
static DblMatrix |
DblMatrix.mod(DblMatrix X,
int Y)
Modulo of X after division by Y.
|
static DblMatrix |
DblMatrix.multiply(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.multiply(int X,
DblMatrix Y) |
DblMatrix |
DataSetAdapter.multiply(java.lang.String VarA,
java.lang.String VarB) |
static DblMatrix |
DblMatrix.nchoosek(DblMatrix N,
DblMatrix k) |
static DblMatrix |
DblMatrix.nchoosek(double N,
double k) |
static DblMatrix |
DblMatrix.nchoosek(int N,
int k) |
DblMatrix |
DblMatrix.neq(DblMatrix X)
Boolean equality comparison determining not-equal-to.
|
DblMatrix |
DblMatrix.neq(double X)
Boolean inequality comparison determining not-equal-to.
|
DblMatrix |
DblMatrix.neq(int X)
Boolean inequality comparison determining not-equal-to.
|
static DblMatrix |
DblMatrix.nextAfter(DblMatrix X,
DblMatrix Y)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextAfter(DblMatrix X,
double y)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextAfter(DblMatrix X,
float b)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextAfter(double y,
DblMatrix X)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextAfter(float b,
DblMatrix X)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextUp(DblMatrix X)
Returns the floating-point value adjacent to d in the direction of positive infinity.
|
DblMatrix |
DblRandom.normRand(double Mean,
double Variance,
int[] Size)
Create a matrix whose entries are generated from a Normal(Mean,Variance)
distribution.
|
DblMatrix |
DblRandom.normRand(int[] Size)
Create a matrix whose entries are generated from a Normal(0,1)
distribution.
|
DblMatrix |
DblMatrix.nzDivideBy(DblMatrix X)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.nzDivideBy(double X)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.nzDivideBy(java.lang.Double X)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.nzDivideBy(int X)
Divide one matrix by another.
|
static DblMatrix |
DblMatrix.oldload(java.io.File dat,
int headerlines)
Loads the whitespace-delimited text file as a DblMatrix ignoring the first N lines.
|
DblMatrix |
DblMatrix.optDivideBy(DblMatrix X,
boolean nodividebyzero)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.optDivideBy(double X,
boolean nodividebyzero)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.optDivideBy(java.lang.Double X,
boolean nodividebyzero)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.optDivideBy(int X,
boolean nodividebyzero)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.or(DblMatrix Z)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(DblMatrix Z,
DblMatrix X)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(DblMatrix Z,
double X)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(DblMatrix Z,
int X)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(double X,
DblMatrix Z)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(int X,
DblMatrix Z)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.orth(DblMatrix u)
Return a vector orthogonal to the given vector.
|
static DblMatrix |
DblMatrix.orth(DblMatrix[] u)
Return a vector orthogonal to the spanning set of vectors.
|
static DblMatrix |
DblMatrix.parse(java.lang.String s)
Static method to parse a string into a DblMatrix.
|
DblMatrix |
DblMatrix.permute(int[] Perm) |
DblMatrix |
DblMatrix.plus(DblMatrix X)
Add one matrix to another.
|
DblMatrix |
SblMatrix.plus(DblMatrix X) |
DblMatrix |
DblMatrix.plus(double X)
Add one matrix to another.
|
DblMatrix |
DblMatrix.plus(int X)
Add one matrix to another.
|
static DblMatrix[] |
DblMatrix.polarToCartesian(DblMatrix theta,
DblMatrix radius) |
DblMatrix |
DblMatrix.popstd()
Calculate population standard deviation down the first dimension.
|
DblMatrix |
DblMatrix.popStd()
Calculate the grand population standard deviation (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
static DblMatrix |
DblMatrix.popStd(DblMatrix X)
Calculate the grand population standard deviation (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
DblMatrix |
DblMatrix.popstd(int dim)
Calculate population standard deviation down the specified dimension.
|
static DblMatrix |
DblMatrix.popVar(DblMatrix X)
Calculate the grand population variance (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
DblMatrix |
DblMatrix.pow(DblMatrix exponent)
Raise a Matrix to a power.
|
DblMatrix |
SblMatrix.pow(DblMatrix X) |
static DblMatrix |
DblMatrix.pow(DblMatrix Y,
DblMatrix exponent) |
static DblMatrix |
DblMatrix.pow(DblMatrix Y,
double exponent) |
static DblMatrix |
DblMatrix.pow(DblMatrix Y,
int exponent) |
DblMatrix |
DblMatrix.pow(double exponent) |
DblMatrix |
DblMatrix.pow(java.lang.Double exponent) |
static DblMatrix |
DblMatrix.pow(double Y,
DblMatrix exponent) |
DblMatrix |
DblMatrix.pow(int exponent) |
static DblMatrix |
DblMatrix.pow(int Y,
DblMatrix exponent) |
DblMatrix |
DataSetAdapter.pow(java.lang.String VarA,
java.lang.String VarB) |
static DblMatrix |
DblMatrix.Prod(DblMatrix X)
Calculate the grand product(over all elements)
|
static DblMatrix |
DblMatrix.prod(DblMatrix X,
int dim)
Multiply along the dimension dim.
|
DblMatrix |
DblMatrix.prod(int dim)
Returns product along the dimension dim.
|
static DblMatrix |
DblMatrix.proj(DblMatrix u,
DblMatrix v)
Orthogonally project column vector u onto column vector v.
|
static DblMatrix |
DblMatrix.proj(DblMatrix u,
DblMatrix[] v)
Orthogonally project column vector u onto the plane spanned by vectors v.
|
static DblMatrix |
DblMatrix.radiansToDegrees(DblMatrix x) |
static DblMatrix |
DblMatrix.radiansToDegrees(double x) |
static DblMatrix |
DblMatrix.radiansToDegrees(int x) |
DblMatrix |
DataSetAdapter.random() |
static DblMatrix |
DblMatrix.random() |
static DblMatrix |
DblMatrix.random(int N) |
DblMatrix |
DblMatrix.reorderBy(DblMatrix indices) |
static DblMatrix |
DblMatrix.replicate(DblMatrix IN,
int[] multiplicity)
Replicate a matrix of arbitrary dimension along a given dimension.
|
static DblMatrix |
DblMatrix.replicate(double input,
int[] multiplicity)
Replicate a matrix of arbitrary dimension along a given dimension.
|
static DblMatrix |
DblMatrix.replicate(int input,
int[] multiplicity)
Replicate a matrix of arbitrary dimension along a given dimension.
|
DblMatrix |
DblMatrix.reshape(int[] size) |
static DblMatrix |
DblMatrix.rint(DblMatrix Y) |
DblMatrix |
DataSetAdapter.rint(java.lang.String VarA) |
static DblMatrix |
DblMatrix.round(DblMatrix Y) |
DblMatrix |
DataSetAdapter.round(java.lang.String VarA) |
static DblMatrix |
DblMatrix.scalb(DblMatrix Y,
DblMatrix exponent)
Return d*2^{scalefactor} rounded as if performed by a single correctly rounded floating-point multiply to a member of the double value set.
|
static DblMatrix |
DblMatrix.scalb(DblMatrix X,
int scalefactor)
Return d*2^{scalefactor} rounded as if performed by a single correctly rounded floating-point multiply to a member of the double value set.
|
static DblMatrix |
DblMatrix.sec(DblMatrix Y) |
static DblMatrix |
DblMatrix.sech(DblMatrix Y) |
static DblMatrix |
DblMatrix.sign(DblMatrix X)
Sign returns 1 if X is greater than 0, 0 if X equals zero and -1 if X is less than zero.
|
static DblMatrix |
DblMatrix.sign(DblMatrix X,
DblMatrix Y)
Returns sign transfer function.
|
static DblMatrix |
DblMatrix.signum(DblMatrix Y) |
static DblMatrix |
DblMatrix.signum(double Y) |
static DblMatrix |
DblMatrix.signum(java.lang.Double Y) |
DblMatrix |
DataSetAdapter.signum(java.lang.String VarA) |
static DblMatrix |
DblMatrix.sin(DblMatrix Y) |
DblMatrix |
DataSetAdapter.sin(java.lang.String VarA) |
static DblMatrix |
DblMatrix.sinh(DblMatrix Y) |
DblMatrix |
DataSetAdapter.sinh(java.lang.String VarA) |
static DblMatrix |
DblMatrix.span(DblMatrix A,
DblMatrix B,
int N)
Create a vector that spans an upper and lower value using N steps.
|
static DblMatrix |
DblMatrix.span(double a,
double b,
int N)
Create a vector that spans an upper and lower value using N steps.
|
static DblMatrix |
DblMatrix.span(int a,
int b,
int N)
Create a vector that spans an upper and lower value using N steps.
|
static DblMatrix[] |
DblMatrix.spanningSetFor(DblMatrix N)
Find a spanning set of unit vectors for the given normal vector.
|
static DblMatrix |
DblMatrix.sqrt(DblMatrix Y) |
static DblMatrix |
DblMatrix.sqrt(double Y) |
DblMatrix |
DataSetAdapter.sqrt(java.lang.String VarA) |
DblMatrix |
DblMatrix.std()
Calculate sample standard deviation down the first dimension.
|
DblMatrix |
DblMatrix.Std() |
static DblMatrix |
DblMatrix.std(DblMatrix X) |
static DblMatrix |
DblMatrix.Std(DblMatrix X)
Calculate the grand sample standard deviation (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
DblMatrix |
DblMatrix.std(int dim)
Calculate sample standard deviation down the specified dimension.
|
static DblMatrix |
DblMatrix.subtract(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.subtract(int X,
DblMatrix Y) |
DblMatrix |
DataSetAdapter.subtract(java.lang.String VarA,
java.lang.String VarB) |
DblMatrix |
DblMatrix.Sum()
Calculate the grand sum (over all elements)
|
static DblMatrix |
DblMatrix.Sum(DblMatrix X)
Calculate the grand sum (over all elements)
|
static DblMatrix |
DblMatrix.sum(DblMatrix X,
int dim)
Sum along the dimension dim.
|
DblMatrix |
DblMatrix.sum(int dim)
Sum along the dimension dim.
|
static DblMatrix |
DblMatrix.tan(DblMatrix Y)
Returns the trigonometric tangent of an angle.
|
DblMatrix |
DataSetAdapter.tan(java.lang.String VarA) |
static DblMatrix |
DblMatrix.tanh(DblMatrix Y)
Returns the hyperbolic tangent of a double value.
|
DblMatrix |
DataSetAdapter.tanh(java.lang.String VarA) |
DblMatrix |
DblMatrix.times(DblMatrix X) |
DblMatrix |
SblMatrix.times(DblMatrix X) |
DblMatrix |
DblMatrix.times(double X) |
DblMatrix |
DblMatrix.times(java.lang.Double X) |
DblMatrix |
DblMatrix.times(int X) |
static DblMatrix[] |
DblMatrix.toArray(DblMatrix INPUT,
int dim)
Convert the input DblMatrix to an array by "slicing" along the given dimension.
|
DblMatrix |
DblParamSet.toDblVector()
Extract the values of parameters as a DblMatrix vector.
|
static DblMatrix |
DblMatrix.toDegrees(DblMatrix Y)
Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
|
DblMatrix |
DataSetAdapter.toDegrees(java.lang.String VarA) |
static DblMatrix |
DblMatrix.toRadians(DblMatrix Y)
Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
|
DblMatrix |
DataSetAdapter.toRadians(java.lang.String VarA) |
static DblMatrix |
DblMatrix.trace(DblMatrix X)
Return the trace of the given matrix.
|
DblMatrix |
DblMatrix.transpose()
Transpose a 2D matrix.
|
DblMatrix |
DblMatrix.triBwdSub(DblMatrix x)
Backward substitution using an upper triangular matrix.
|
static DblMatrix |
DblMatrix.triBwdSub(DblMatrix R,
DblMatrix x)
Backward substitution using an upper triangular matrix.
|
DblMatrix |
DblMatrix.triFwdSub(DblMatrix y)
Solve a system of linear equations using forward-substitution.
|
static DblMatrix |
DblMatrix.triFwdSub(DblMatrix R,
DblMatrix x)
Solve a system of linear equations using forward-substitution.
|
static DblMatrix |
DblMatrix.tril(DblMatrix X)
Get lower triangular portion of a matrix.
|
static DblMatrix |
DblMatrix.tril(DblMatrix X,
int diag)
Get lower triangular portion of a matrix.
|
static DblMatrix |
DblMatrix.triu(DblMatrix X)
Get lower triangular portion of a matrix.
|
static DblMatrix |
DblMatrix.triu(DblMatrix X,
int diag)
Get upper triangular portion of a matrix.
|
static DblMatrix |
DblMatrix.ulp(DblMatrix Y) |
static DblMatrix |
DblMatrix.ulp(double Y) |
static DblMatrix |
DblMatrix.ulp(java.lang.Double Y) |
DblMatrix |
DataSetAdapter.ulp(java.lang.String VarA) |
DblMatrix |
DblRandom.unifRand(double A,
double B,
int[] Size)
Create a matrix whose entries are generated from a Uniform (double A,double B)
distribution.
|
DblMatrix |
DblRandom.unifRand(int[] Size)
Create a matrix whose entries are generated from a Uniform (0,1)
distribution.
|
static DblMatrix |
DblMatrix.union(DblMatrix A,
DblMatrix B) |
static DblMatrix |
DblMatrix.unique(DblMatrix X)
Return unique elements as a DblMatrix column vector.
|
static DblMatrix |
DblMatrix.Var(DblMatrix X)
Calculate the grand sample variance (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
static DblMatrix |
DblMatrix.vec(DblMatrix Y) |
static DblMatrix |
DblMatrix.vnorm(DblMatrix u)
Returns the vector norm (length) of the input vector.
|
Modifier and Type | Method and Description |
---|---|
static DblMatrix |
DblMatrix.abs(DblMatrix Y) |
static DblMatrix |
DblMatrix.acos(DblMatrix Y) |
static DblMatrix |
DblMatrix.acosh(DblMatrix Y) |
static DblMatrix |
DblMatrix.acoth(DblMatrix Y) |
static DblMatrix |
DblMatrix.acsch(DblMatrix Y) |
static DblMatrix |
DblMatrix.add(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.add(int X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.all(DblMatrix X)
Boolean "all" down dimension 1.
|
static DblMatrix |
DblMatrix.All(DblMatrix X)
Boolean "all" inclusive of all values.
|
static DblMatrix |
DblMatrix.all(DblMatrix X,
int dim)
Boolean "all" down dimension dim.
|
DblMatrix |
DblMatrix.and(DblMatrix Z)
"And" one matrix with another.
|
DblMatrix |
SblMatrix.and(DblMatrix Z)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(DblMatrix Z,
DblMatrix X)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(DblMatrix Z,
double X)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(DblMatrix Z,
int X)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(double X,
DblMatrix Z)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.and(int X,
DblMatrix Z)
"And" one matrix with another.
|
static DblMatrix |
DblMatrix.anscombe(DblMatrix X)
Performs Anscombe transformation.
|
static DblMatrix |
DblMatrix.any(DblMatrix X)
Boolean "any" down dimension 1.
|
static DblMatrix |
DblMatrix.Any(DblMatrix X)
Boolean "any" inclusive of all values.
|
static DblMatrix |
DblMatrix.any(DblMatrix X,
int dim)
Boolean "any" down dimension dim.
|
DblMatrix |
DblSort.applyTo(DblMatrix x)
Permutes the input matrix along the first dimension according the
the current values of these sorted indices.
|
DblMatrix |
DblSort.applyTo(DblMatrix x,
int dim)
Permutes the input matrix along the given dimension according the
the current values of these sorted indices.
|
static DblMatrix |
DblMatrix.asech(DblMatrix Y) |
static DblMatrix |
DblMatrix.asin(DblMatrix Y) |
static DblMatrix |
DblMatrix.asinh(DblMatrix Y) |
static DblMatrix |
DblMatrix.atan(DblMatrix Y) |
static DblMatrix |
DblMatrix.atan2(DblMatrix Y,
DblMatrix X) |
static DblMatrix |
DblMatrix.atanh(DblMatrix Y) |
static DblMatrix |
DblMatrix.bounds(DblMatrix X)
Return the smallest and largest values in a matrix.
|
static DblMatrix |
DblMatrix.cbrt(DblMatrix Y) |
static DblMatrix |
DblMatrix.ceil(DblMatrix Y) |
static DblMatrix |
DblMatrix.comp(DblMatrix u,
DblMatrix v)
Return the scalar projection (or component) of u onto v.
|
DblMatrix |
DblMatrix.concat(DblMatrix B,
int dim) |
static java.lang.String |
DblMatrix.convertDblToString(DblMatrix in) |
static DblMatrix |
DblMatrix.copySign(DblMatrix X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.copySign(DblMatrix X,
double b) |
static DblMatrix |
DblMatrix.copySign(DblMatrix X,
float Y) |
static DblMatrix |
DblMatrix.copySign(DblMatrix X,
int Y) |
static DblMatrix |
DblMatrix.cos(DblMatrix Y) |
static DblMatrix |
DblMatrix.cosh(DblMatrix Y) |
static DblMatrix |
DblMatrix.coth(DblMatrix Y) |
static DblMatrix |
DblMatrix.csc(DblMatrix Y) |
static DblMatrix |
DblMatrix.csch(DblMatrix Y) |
void |
DblParamSet.Dblput(java.lang.String fieldname,
DblMatrix value)
Provides a Dblput method.
|
static DblMatrix |
DblMatrix.degreesToRadians(DblMatrix x) |
static DblMatrix |
DblMatrix.det(DblMatrix X)
Returns the determinant of the square matrix.
|
static DblMatrix |
DblMatrix.diameter(DblMatrix X)
The maximum euclidean distance between columns in a matrix.
|
static DblMatrix |
DblMatrix.divide(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.divide(int X,
DblMatrix Y) |
DblMatrix |
DblMatrix.divideBy(DblMatrix X)
Divide one matrix by another.
|
DblParamSet |
DblParamSet.divideBy(DblMatrix X)
Divide parameter set by scalar.
|
DblMatrix |
SblMatrix.divideBy(DblMatrix X) |
DblMatrix |
DblMatrix.dot(DblMatrix X)
Dot product of two matrices.
|
DblMatrix |
SblMatrix.dot(DblMatrix X) |
static DblMatrix |
DblMatrix.dummyCoding(DblMatrix X)
Produces a dummy-variable encoding matrix based on the unique values of the input
array.
|
static DblMatrix |
DblMatrix.dummyCoding(DblMatrix X,
boolean intercept)
Produces a dummy-variable encoding matrix based on the unique values of the input
array.
|
static DblMatrix |
DblMatrix.dummyCoding(DblMatrix X,
boolean intercept,
boolean fullrank)
Produces a dummy-variable encoding matrix based on the unique values of the input
array.
|
DblMatrix |
DblMatrix.eq(DblMatrix X)
Boolean equality comparison.
|
static DblMatrix |
DblMatrix.euclid(DblMatrix X)
Euclidean distance among columns.
|
static DblMatrix |
DblMatrix.exp(DblMatrix Y) |
static DblMatrix |
DblMatrix.expm1(DblMatrix Y) |
static DblMatrix |
DblMatrix.factorial(DblMatrix X) |
static DblMatrix |
DblMatrix.fill(DblMatrix X,
int[] Size)
Create a matrix of arbitrary dimension filled with the same value.
|
static DblMatrix |
DblMatrix.find(DblMatrix X) |
static DblMatrix |
DblMatrix.floor(DblMatrix Y) |
static DataSet |
DataSet.fromDblMatrix(DblMatrix X) |
static DataSet |
DataSet.fromDblMatrix(java.lang.String[] labels,
DblMatrix[] cols) |
static DblMatrix |
DblMatrix.gap(DblMatrix u,
DblMatrix v)
Returns the cosine of the angle between the two input vectors.
|
DblMatrix |
DblMatrix.geq(DblMatrix X)
Boolean inequality comparison determining greater-than-or-equal-to.
|
DblMatrix |
DblMatrix.getCol(DblMatrix col)
Get a particular col.
|
static DblMatrix |
DblMatrix.getExponent(DblMatrix Y) |
DblMatrix |
DblMatrix.getIndices(DblMatrix I)
Get values whose indices are given in a DblMatrix.
|
DblMatrix |
DblMatrix.getMap(DblMatrix MAP)
Get values from a matrix based on a logical map.
|
DblMatrix |
DblMatrix.getRow(DblMatrix row)
Get a particular row.
|
DblMatrix |
NamedColumnMapping.getVar(DblMatrix W,
java.lang.String name)
Gets the column of the input matrix according to the current variable name mapping.
|
static DblMatrix[] |
DblMatrix.GramSchmidt(DblMatrix[] u) |
static DblMatrix[] |
DblMatrix.grid(DblMatrix[] X) |
static DblMatrix[] |
DblMatrix.grid(DblMatrix X1,
DblMatrix X2) |
static DblMatrix[] |
DblMatrix.grid(DblMatrix X1,
DblMatrix X2,
DblMatrix X3) |
DblMatrix |
DblMatrix.gt(DblMatrix X)
Boolean inequality comparison determining greater-than.
|
static DblMatrix |
DblMatrix.hypot(DblMatrix X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.I(DblMatrix X)
Create square identity matrix with N rows.
|
static DblMatrix |
DblMatrix.ianscombe(DblMatrix X) |
static DblMatrix |
DblMatrix.IEEEremainder(DblMatrix Y,
DblMatrix X)
Calculate remainder.
|
static DblMatrix |
DblMatrix.IEEEremainder(DblMatrix Y,
double X) |
static DblMatrix |
DblMatrix.IEEEremainder(DblMatrix Y,
int X) |
static Subscript[] |
DblMatrix.indexToSubscript(DblMatrix I,
int[] Size)
Convert an index array into a Subscript[] for a given matrix Size
|
static boolean |
DblMatrix.isEqualSize(DblMatrix X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.isInfinite(DblMatrix X)
Boolean isInfinite
|
static DblMatrix |
DblMatrix.isNaN(DblMatrix X)
Boolean isNaN
|
static DblMatrix |
DblMatrix.isReal(DblMatrix X)
Boolean isReal
Determines if elements are not NaN nor Infinite;
|
static DblMatrix |
DblMatrix.isScalar(DblMatrix X)
Determine if a matrix is sized 1x1.
|
static DblMatrix |
DblMatrix.J(DblMatrix X)
Create a column vector of ones.
|
DblMatrix |
DblMatrix.kronecker(DblMatrix X)
Returns Kronecker product taken with respect to the input matrix.
|
DblMatrix |
SblMatrix.ldot(DblMatrix X)
Same as X.dot(this)
|
DblMatrix |
DblMatrix.leq(DblMatrix X)
Boolean inequality comparison determining less-than-or-equal-to.
|
static DblMatrix |
DblMatrix.log(DblMatrix Y) |
static DblMatrix |
DblMatrix.log10(DblMatrix Y) |
static DblMatrix |
DblMatrix.log1p(DblMatrix Y) |
static DblMatrix |
DblMatrix.logGamma(DblMatrix x) |
static DblMatrix |
DblMatrix.logxy(DblMatrix X,
DblMatrix Y)
Log base x of y.
|
DblMatrix |
DblMatrix.lt(DblMatrix X)
Boolean inequality comparison determining less-than.
|
void |
DblSort.mapToIndices(DblMatrix idx)
The indices will be assigned to the input vector of indices after they are permuted by
the current indices.
|
static Subscript[] |
DblMatrix.mapToSubscript(DblMatrix MAP)
Return Subscript[] indicating the non-zero entries of a DblMatrix.
|
DblMatrix |
DblMatrix.max(DblMatrix X)
Calculate maximum between two matrices.
|
static DblMatrix |
DblMatrix.Max(DblMatrix X)
Calculate the grand maximum (over all elements)
|
static DblMatrix |
DblMatrix.max(DblMatrix X,
DblMatrix Y)
Return maximum between two matrices.
|
static DblMatrix |
DblMatrix.max(DblMatrix X,
double Y)
Return maximum between a matrix and a scalar.
|
static DblMatrix |
DblMatrix.max(DblMatrix X,
java.lang.Double Y)
Return maximum between a matrix and a scalar.
|
static DblMatrix |
DblMatrix.max(DblMatrix X,
int dim)
Calculate maximum down the specified dimension.
|
static DblMatrix |
DblMatrix.max(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.Mean(DblMatrix X)
Calculate the grand mean (over all elements)
|
static DblMatrix |
DblMatrix.median(DblMatrix X)
Median of all elements
|
static DblMatrix |
DblMatrix.Median(DblMatrix X)
Median of all elements
|
DblMatrix |
DblMatrix.min(DblMatrix X)
Calculate minimum between two matrices.
|
static DblMatrix |
DblMatrix.Min(DblMatrix X)
Calculate the grand minimum (over all elements)
|
static DblMatrix |
DblMatrix.min(DblMatrix X,
DblMatrix Y)
Return minimum between two matrices.
|
static DblMatrix |
DblMatrix.min(DblMatrix Y,
double X) |
static DblMatrix |
DblMatrix.min(DblMatrix X,
java.lang.Double Y)
Return minimum between a matrix and a scalar.
|
static DblMatrix |
DblMatrix.min(DblMatrix Y,
int X) |
static DblMatrix |
DblMatrix.min(DblMatrix Y,
java.lang.Number X) |
static DblMatrix |
DblMatrix.min(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.min(int X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.min(java.lang.Number X,
DblMatrix Y) |
DblMatrix |
DblMatrix.minus(DblMatrix X)
Subtract input matrix from this matrix.
|
DblParamSet |
DblParamSet.minus(DblMatrix X)
Subtract scalar from parameter set.
|
DblMatrix |
SblMatrix.minus(DblMatrix X) |
static DblMatrix |
DblMatrix.mod(DblMatrix X,
DblMatrix Y)
Modulo of X after division by Y.
|
static DblMatrix |
DblMatrix.mod(DblMatrix X,
double Y)
Modulo of X after division by Y.
|
static DblMatrix |
DblMatrix.mod(DblMatrix X,
java.lang.Double Y)
Modulo of X after division by Y.
|
static DblMatrix |
DblMatrix.mod(DblMatrix X,
int Y)
Modulo of X after division by Y.
|
static DblMatrix |
DblMatrix.multiply(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.multiply(int X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.nchoosek(DblMatrix N,
DblMatrix k) |
DblMatrix |
DblMatrix.neq(DblMatrix X)
Boolean equality comparison determining not-equal-to.
|
static DblMatrix |
DblMatrix.nextAfter(DblMatrix X,
DblMatrix Y)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextAfter(DblMatrix X,
double y)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextAfter(DblMatrix X,
float b)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextAfter(double y,
DblMatrix X)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextAfter(float b,
DblMatrix X)
Returns the floating-point number adjacent to the first argument in the direction of the second argument.
|
static DblMatrix |
DblMatrix.nextUp(DblMatrix X)
Returns the floating-point value adjacent to d in the direction of positive infinity.
|
DblMatrix |
DblMatrix.nzDivideBy(DblMatrix X)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.optDivideBy(DblMatrix X,
boolean nodividebyzero)
Divide one matrix by another.
|
DblMatrix |
DblMatrix.or(DblMatrix Z)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(DblMatrix Z,
DblMatrix X)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(DblMatrix Z,
double X)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(DblMatrix Z,
int X)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(double X,
DblMatrix Z)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.or(int X,
DblMatrix Z)
"Or" one matrix with another.
|
static DblMatrix |
DblMatrix.orth(DblMatrix u)
Return a vector orthogonal to the given vector.
|
static DblMatrix |
DblMatrix.orth(DblMatrix[] u)
Return a vector orthogonal to the spanning set of vectors.
|
DblMatrix |
DblMatrix.plus(DblMatrix X)
Add one matrix to another.
|
DblParamSet |
DblParamSet.plus(DblMatrix X)
Add scalar to a parameter set.
|
DblMatrix |
SblMatrix.plus(DblMatrix X) |
static DblMatrix[] |
DblMatrix.polarToCartesian(DblMatrix theta,
DblMatrix radius) |
static DblMatrix |
DblMatrix.popStd(DblMatrix X)
Calculate the grand population standard deviation (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
static DblMatrix |
DblMatrix.popVar(DblMatrix X)
Calculate the grand population variance (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
DblMatrix |
DblMatrix.pow(DblMatrix exponent)
Raise a Matrix to a power.
|
DblMatrix |
SblMatrix.pow(DblMatrix X) |
static DblMatrix |
DblMatrix.pow(DblMatrix Y,
DblMatrix exponent) |
static DblMatrix |
DblMatrix.pow(DblMatrix Y,
double exponent) |
static DblMatrix |
DblMatrix.pow(DblMatrix Y,
int exponent) |
static DblMatrix |
DblMatrix.pow(double Y,
DblMatrix exponent) |
static DblMatrix |
DblMatrix.pow(int Y,
DblMatrix exponent) |
static DblMatrix |
DblMatrix.Prod(DblMatrix X)
Calculate the grand product(over all elements)
|
static DblMatrix |
DblMatrix.prod(DblMatrix X,
int dim)
Multiply along the dimension dim.
|
static DblMatrix |
DblMatrix.proj(DblMatrix u,
DblMatrix v)
Orthogonally project column vector u onto column vector v.
|
static DblMatrix |
DblMatrix.proj(DblMatrix u,
DblMatrix[] v)
Orthogonally project column vector u onto the plane spanned by vectors v.
|
static DblMatrix |
DblMatrix.proj(DblMatrix u,
DblMatrix[] v)
Orthogonally project column vector u onto the plane spanned by vectors v.
|
static DblMatrix |
DblMatrix.radiansToDegrees(DblMatrix x) |
DblMatrix |
DblMatrix.reorderBy(DblMatrix indices) |
void |
DblParamSet.replaceAllWith(DblMatrix x) |
static DblMatrix |
DblMatrix.replicate(DblMatrix IN,
int[] multiplicity)
Replicate a matrix of arbitrary dimension along a given dimension.
|
static DblMatrix |
DblMatrix.rint(DblMatrix Y) |
static DblMatrix |
DblMatrix.round(DblMatrix Y) |
boolean |
DblMatrix.sameSize(DblMatrix V)
Returns true if the given matrix has the same size as this matrix.
|
static DblMatrix |
DblMatrix.scalb(DblMatrix Y,
DblMatrix exponent)
Return d*2^{scalefactor} rounded as if performed by a single correctly rounded floating-point multiply to a member of the double value set.
|
static DblMatrix |
DblMatrix.scalb(DblMatrix X,
int scalefactor)
Return d*2^{scalefactor} rounded as if performed by a single correctly rounded floating-point multiply to a member of the double value set.
|
static DblMatrix |
DblMatrix.sec(DblMatrix Y) |
static DblMatrix |
DblMatrix.sech(DblMatrix Y) |
void |
DblMatrix.setCol(DblMatrix INPUT,
DblMatrix Col)
Set a particular col.
|
void |
DblMatrix.setCol(DblMatrix INPUT,
int col)
Set a particular col.
|
void |
DblMatrix.setDblAt(DblMatrix VALUE,
int k)
Set scalar DblMatrix at a particular index.
|
void |
DblMatrix.setDiag(DblMatrix vector)
Set main diagonal elements of a 2D matrix.
|
void |
DblMatrix.setDiag(DblMatrix vector,
int diag)
Set elements of specified diagonal of a 2D matrix.
|
void |
DblMatrix.setMap(DblMatrix X,
DblMatrix MAP)
Set values in a matrix based on a logical map.
|
void |
DblMatrix.setMap(double X,
DblMatrix MAP)
Set values in a matrix based on a logical map.
|
void |
DblMatrix.setMap(java.lang.Double X,
DblMatrix MAP)
Set values in a matrix based on a logical map.
|
void |
DblParamSet.setParam(java.lang.String name,
DblMatrix value) |
void |
DblMatrix.setRow(DblMatrix INPUT,
DblMatrix Row)
Set a particular row.
|
void |
DblMatrix.setRow(DblMatrix INPUT,
int row)
Set a particular row.
|
void |
DblMatrix.setSubMatrix(DblMatrix INPUT,
Subscript[] subscripts)
Set a matrix of values within an existing matrix.
|
void |
NamedColumnMapping.setVar(DblMatrix W,
java.lang.String name,
DblMatrix V)
Sets the column of the input matrix according to the current variable name mapping.
|
static DblMatrix |
DblMatrix.sign(DblMatrix X)
Sign returns 1 if X is greater than 0, 0 if X equals zero and -1 if X is less than zero.
|
static DblMatrix |
DblMatrix.sign(DblMatrix X,
DblMatrix Y)
Returns sign transfer function.
|
static DblMatrix |
DblMatrix.signum(DblMatrix Y) |
static DblMatrix |
DblMatrix.sin(DblMatrix Y) |
static DblMatrix |
DblMatrix.sinh(DblMatrix Y) |
static DblMatrix |
DblMatrix.span(DblMatrix A,
DblMatrix B,
int N)
Create a vector that spans an upper and lower value using N steps.
|
static DblMatrix[] |
DblMatrix.spanningSetFor(DblMatrix N)
Find a spanning set of unit vectors for the given normal vector.
|
static DblMatrix |
DblMatrix.sqrt(DblMatrix Y) |
static DblMatrix |
DblMatrix.std(DblMatrix X) |
static DblMatrix |
DblMatrix.Std(DblMatrix X)
Calculate the grand sample standard deviation (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
static DblMatrix |
DblMatrix.subtract(double X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.subtract(int X,
DblMatrix Y) |
static DblMatrix |
DblMatrix.Sum(DblMatrix X)
Calculate the grand sum (over all elements)
|
static DblMatrix |
DblMatrix.sum(DblMatrix X,
int dim)
Sum along the dimension dim.
|
static DblMatrix |
DblMatrix.tan(DblMatrix Y)
Returns the trigonometric tangent of an angle.
|
static DblMatrix |
DblMatrix.tanh(DblMatrix Y)
Returns the hyperbolic tangent of a double value.
|
static boolean |
DblMatrix.test(DblMatrix X)
Determine if contents of DblMatrix are equal to 1.
|
DblMatrix |
DblMatrix.times(DblMatrix X) |
DblParamSet |
DblParamSet.times(DblMatrix X)
Multiply parameter sets by scalar.
|
DblMatrix |
SblMatrix.times(DblMatrix X) |
static DblMatrix[] |
DblMatrix.toArray(DblMatrix INPUT,
int dim)
Convert the input DblMatrix to an array by "slicing" along the given dimension.
|
static DblMatrix |
DblMatrix.toDegrees(DblMatrix Y)
Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
|
static DblMatrix |
DblMatrix.toRadians(DblMatrix Y)
Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
|
static DblMatrix |
DblMatrix.trace(DblMatrix X)
Return the trace of the given matrix.
|
DblMatrix |
DblMatrix.triBwdSub(DblMatrix x)
Backward substitution using an upper triangular matrix.
|
static DblMatrix |
DblMatrix.triBwdSub(DblMatrix R,
DblMatrix x)
Backward substitution using an upper triangular matrix.
|
DblMatrix |
DblMatrix.triFwdSub(DblMatrix y)
Solve a system of linear equations using forward-substitution.
|
static DblMatrix |
DblMatrix.triFwdSub(DblMatrix R,
DblMatrix x)
Solve a system of linear equations using forward-substitution.
|
static DblMatrix |
DblMatrix.tril(DblMatrix X)
Get lower triangular portion of a matrix.
|
static DblMatrix |
DblMatrix.tril(DblMatrix X,
int diag)
Get lower triangular portion of a matrix.
|
static DblMatrix |
DblMatrix.triu(DblMatrix X)
Get lower triangular portion of a matrix.
|
static DblMatrix |
DblMatrix.triu(DblMatrix X,
int diag)
Get upper triangular portion of a matrix.
|
static DblMatrix |
DblMatrix.ulp(DblMatrix Y) |
static DblMatrix |
DblMatrix.union(DblMatrix A,
DblMatrix B) |
static DblMatrix |
DblMatrix.unique(DblMatrix X)
Return unique elements as a DblMatrix column vector.
|
void |
DataSet.updateFromDblMatrix(java.lang.String[] labels,
DblMatrix cols) |
void |
DataSet.updateFromDblMatrix(java.lang.String[] labels,
DblMatrix[] cols)
Update the values in this DataSet based on the corresponding values in
the given DblMatrices.
|
static DblMatrix |
DblMatrix.Var(DblMatrix X)
Calculate the grand sample variance (over all elements)
Calculates (SUM(X^2)-(1/N)(SUM(X))^2)/(N-1).
|
static DblMatrix |
DblMatrix.vec(DblMatrix Y) |
static DblMatrix |
DblMatrix.vnorm(DblMatrix u)
Returns the vector norm (length) of the input vector.
|
Constructor and Description |
---|
DblMatrix(DblMatrix X)
This construction creates a new DblMatrix from an input DblMatrix.
|
DblMatrix(MatrixSetterGetter sg,
DblMatrix X)
This construction creates a new DblMatrix from an input DblMatrix.
|
DblMatrixHashMap(java.lang.String[] fieldnames,
DblMatrix[] values) |
DblParamSet(java.lang.String[] fieldnames,
DblMatrix[] values)
Define constructor for DblParamSet.
|
DblSort(DblMatrix X,
int Dim) |
DblSortUnit(DblMatrix X,
DblMatrix Index) |
SblMatrix(DblMatrix X) |
Subscript(DblMatrix X)
Create a Subscripts instance from a vector.
|
Modifier and Type | Method and Description |
---|---|
DblMatrix |
DblMatrixTransferAgent.copyAsDblMatrix() |
DblMatrix |
DblMatrixSQL.copyAsDblMatrix()
Copy the contents of this repository storage into a new DblMatrix.
|
DblMatrix |
DblMatrixSQLite.copyAsDblMatrix()
Copy the contents of this repository storage into a new DblMatrix.
|
DblMatrix |
DblMatrixXML.copyAsDblMatrix() |
DblMatrix |
DblMatrixDOM.copyAsDblMatrix()
Copy the contents of this repository storage into a new DblMatrix.
|
DblMatrix |
DblMatrixStorage.copyAsDblMatrix()
Copy the contents of this repository storage into a new DblMatrix.
|
Modifier and Type | Method and Description |
---|---|
void |
DblMatrixTransferAgent.copyFromDblMatrix(DblMatrix x) |
void |
DblMatrixSQL.copyFromDblMatrix(DblMatrix x) |
void |
DblMatrixSQLite.copyFromDblMatrix(DblMatrix x) |
void |
DblMatrixXML.copyFromDblMatrix(DblMatrix x) |
void |
DblMatrixDOM.copyFromDblMatrix(DblMatrix x) |
void |
DblMatrixStorage.copyFromDblMatrix(DblMatrix x) |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
MatrixStorageEditorFrame.copyAsDblMatrix() |
DblMatrix |
MatrixEditorFrame.getMatrix() |
DblMatrix |
MatrixEditorPanel.getMatrix() |
Modifier and Type | Method and Description |
---|---|
void |
MatrixStorageEditorFrame.copyFromDblMatrix(DblMatrix x) |
void |
MatrixEditorFrame.setMatrix(DblMatrix x) |
void |
MatrixEditorPanel.setMatrix(DblMatrix mat) |
Modifier and Type | Method and Description |
---|---|
abstract DblMatrix |
AbstractFunction.getValueAt(DblMatrix X) |
DblMatrix |
UniUniFunction.getValueAt(DblMatrix[] X) |
DblMatrix |
MultiUniFunction.getValueAt(DblMatrix[] X) |
abstract DblMatrix |
AbstractFunction.getValueAt(DblMatrix[] X) |
DblMatrix |
UniUniFunction.getValueAt(double X) |
DblMatrix |
MultiUniFunction.getValueAt(double X) |
DblMatrix |
UniUniFunction.getValueAt(int X) |
DblMatrix |
MultiUniFunction.getValueAt(int X) |
Modifier and Type | Method and Description |
---|---|
abstract DblMatrix |
AbstractFunction.getValueAt(DblMatrix X) |
DblMatrix |
UniUniFunction.getValueAt(DblMatrix[] X) |
DblMatrix |
MultiUniFunction.getValueAt(DblMatrix[] X) |
abstract DblMatrix |
AbstractFunction.getValueAt(DblMatrix[] X) |
void |
UniUniFunction.plotOver(DblMatrix X)
Eventually this will plot the data once we get some graphics going.
|
void |
MultiUniFunction.plotOver(DblMatrix X)
Eventually this will plot the data once we get some graphics going.
|
void |
AbstractFunction.plotOver(DblMatrix X)
Eventually this will plot the data once we get some graphics going.
|
void |
UniMultiFunction.plotOver(DblMatrix[] X)
Eventually this will plot the data once we get some graphics going.
|
void |
MultiMultiFunction.plotOver(DblMatrix[] X)
Eventually this will plot the data once we get some graphics going.
|
void |
AbstractFunction.plotOver(DblMatrix[] X)
Eventually this will plot the data once we get some graphics going.
|
Modifier and Type | Method and Description |
---|---|
DblMatrix |
Log.getValueAt(DblMatrix X)
Get value at given X.
|
DblMatrix |
Exp.getValueAt(DblMatrix X)
Get value at given X.
|
DblMatrix |
Log10.getValueAt(DblMatrix X)
Get value at given X.
|
Modifier and Type | Method and Description |
---|---|
DblMatrix |
Log.getValueAt(DblMatrix X)
Get value at given X.
|
DblMatrix |
Exp.getValueAt(DblMatrix X)
Get value at given X.
|
DblMatrix |
Log10.getValueAt(DblMatrix X)
Get value at given X.
|
Modifier and Type | Field and Description |
---|---|
protected DblMatrix[] |
SLCamera.cameraBasis |
protected DblMatrix |
SLAnnotation.directionReferencePoint |
protected DblMatrix |
SLCamera.focus |
protected DblMatrix |
SLCamera.phi |
protected DblMatrix |
SLCamera.psi |
protected DblMatrix |
SLCamera.theta |
protected DblMatrix |
DefaultReportInstance.time |
protected DblMatrix |
DefaultReportInstance.value |
protected DblMatrix |
SLAnnotation.xCoord |
protected DblMatrix |
SLCamera.XLim |
protected DblMatrix |
SLAnnotation.yCoord |
protected DblMatrix |
SLCamera.YLim |
protected DblMatrix |
SLAnnotation.zCoord |
protected DblMatrix |
SLCamera.ZLim |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
SLAxes.getAxisHideThreshold() |
DblMatrix[] |
SLCamera.getCameraBasis() |
DblMatrix |
SLCamera.getCameraDirection()
Returns a unit vector (centered at the origin) indicating the direction of the camera.
|
static DblMatrix |
SLCamera.getCameraDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction of the camera.
|
DblMatrix |
SLCamera.getCameraPosition() |
DblMatrix |
SLCamera.getCameraStarboardDirection()
Returns a unit vector (centered at the origin) indicating the direction to the right of the camera.
|
static DblMatrix |
SLCamera.getCameraStarboardDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction to the right of the camera.
|
DblMatrix |
SLCamera.getCameraUpDirection()
Returns a unit vector (centered at the origin) indicating the direction up from the camera.
|
static DblMatrix |
SLCamera.getCameraUpDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction up from the camera.
|
DblMatrix |
SLCamera.getCoordinate(double[] pixel)
Return the actual coordinates for the given pixel.
|
DblMatrix |
SLPolyRegion.getCoordinate(double[] pixel) |
DblMatrix |
SLLocator.getCoordinate(double[] pixel) |
DblMatrix |
SLAxes.getCoordinate(double[] pixel)
Get the coordinate for the given screen pixel location.
|
DblMatrix |
SLGrid.getCoordinate(double[] pixel) |
DblMatrix |
SLCamera.getCoordinate(int[] pixel)
Return the actual coordinates for the given pixel.
|
DblMatrix |
SLPolyRegion.getCoordinate(int[] pixel) |
DblMatrix |
SLLocator.getCoordinate(int[] pixel) |
DblMatrix |
SLAxes.getCoordinate(int[] pixel)
Get the coordinate for the given screen pixel location.
|
DblMatrix |
SLGrid.getCoordinate(int[] pixel) |
DblMatrix |
SLCamera.getDataUnitsPerPixel()
This method does not adjust or account for digital zoom.
|
DblMatrix |
SLCamera.getDigitalZoom() |
DblMatrix |
SLAnnotation.getDirectionReferencePoint() |
DblMatrix |
SLAxes.getExtentX()
Gets the extent in the X-direction.
|
DblMatrix |
SLAxes.getExtentY()
Gets the extent in the Y-direction.
|
DblMatrix |
SLAxes.getExtentZ()
Gets the extent in the Z-direction.
|
DblMatrix |
AxesRangeSelection.getLimits() |
DblMatrix |
LpregPanel.ResultsTab.getLineNoise() |
DblMatrix |
LpregPanel.ResultsTab.getMaxXBound() |
DblMatrix |
LpregPanel.ResultsTab.getMinXBound() |
DblMatrix |
LpregPanel.ResultsTab.InvOptObjective.getParam(java.lang.String name) |
DblMatrix |
FitFrameModel.getParam(java.lang.String p) |
DblMatrix |
SLCamera.getPhi() |
DblMatrix |
SLCamera.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLPolyRegion.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLLocator.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLAxes.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLGrid.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLCamera.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLPolyRegion.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLLocator.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLAxes.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLGrid.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix[] |
LpregPanel.ResultsTab.getPoints() |
DblMatrix |
SLCamera.getPsi() |
DblMatrix |
SLAxes.getSceneCenter() |
DblMatrix |
SLStereoCameraGroup.getSeparation() |
DblMatrix |
LpregPanel.ResultsTab.getSmoothValue() |
DblMatrix |
SLCamera.getTheta() |
DblMatrix |
DefaultReportInstance.getTime() |
DblMatrix |
DefaultReportInstance.getValue() |
DblMatrix |
AxesRangeSelection.getValue() |
DblMatrix |
LpregPanel.ResultsTab.InvOptObjective.getValueAt(DblMatrix X) |
DblMatrix |
FitFrameModel.getValueAt(DblMatrix Y) |
DblMatrix |
LpregPanel.ResultsTab.InvOptObjective.getValueToMinimize() |
DblMatrix |
FitFrameModel.getValueToMinimize() |
DblMatrix |
FitFrameModel.getValueToOptimizeZoom() |
DblMatrix |
DefaultReporter.getVar(DblMatrix W,
java.lang.String name)
Gets the column of the input matrix according to the current variable name mapping.
|
DblMatrix[] |
SLSurface.getVerticesAt(int index)
Returns the vertices of the face at the given index.
|
DblMatrix |
SLLine.getXBounds() |
DblMatrix |
SLSurface.getXBounds() |
DblMatrix |
SLComponent.getXBounds()
This default implementation of getXBounds returns a vector of zeros,
essentially giving the object a reported size of zero.
|
DblMatrix |
SLPolyRegion.getXBounds() |
DblMatrix |
SLLegend.getXBounds() |
DblMatrix |
SLAnnotation.getXBounds() |
DblMatrix |
SLLine.getXData() |
DblMatrix |
Surface.getXData() |
DblMatrix |
SLSurface.getXData() |
DblMatrix |
SLLegend.getXData()
Get the x-coordinate in data units of the upper left corner of the
legend box.
|
DblMatrix |
Line.getXData() |
DblMatrix |
SLAnnotation.getXData() |
DblMatrix |
SLCamera.getXDataUnitsPerPixel()
This method does not adjust or account for digital zoom.
|
DblMatrix |
SLCamera.getXLim() |
DblMatrix |
SLPolyRegion.getXLim() |
DblMatrix |
SLLocator.getXLim() |
DblMatrix |
SLAxes.getXLim() |
DblMatrix |
SLGrid.getXLim() |
DblMatrix |
Axes.getXRange() |
DblMatrix |
SLAxes.getXRange() |
DblMatrix |
SLLine.getYBounds() |
DblMatrix |
SLSurface.getYBounds() |
DblMatrix |
SLComponent.getYBounds()
This default implementation of getYBounds returns a vector of zeros,
essentially giving the object a reported size of zero.
|
DblMatrix |
SLPolyRegion.getYBounds() |
DblMatrix |
SLLegend.getYBounds() |
DblMatrix |
SLAnnotation.getYBounds() |
DblMatrix |
SLLine.getYData() |
DblMatrix |
Surface.getYData() |
DblMatrix |
SLSurface.getYData() |
DblMatrix |
SLLegend.getYData() |
DblMatrix |
Line.getYData() |
DblMatrix |
SLAnnotation.getYData() |
DblMatrix |
SLCamera.getYDataUnitsPerPixel()
This method does not adjust or account for digital zoom.
|
DblMatrix |
SLCamera.getYLim() |
DblMatrix |
SLPolyRegion.getYLim() |
DblMatrix |
SLLocator.getYLim() |
DblMatrix |
SLAxes.getYLim() |
DblMatrix |
SLGrid.getYLim() |
DblMatrix |
Axes.getYRange() |
DblMatrix |
SLAxes.getYRange() |
DblMatrix |
SLLine.getZBounds() |
DblMatrix |
SLSurface.getZBounds() |
DblMatrix |
SLComponent.getZBounds()
This default implementation of getZBounds returns a vector of zeros,
essentially giving the object a reported size of zero.
|
DblMatrix |
SLLegend.getZBounds() |
DblMatrix |
SLAnnotation.getZBounds() |
DblMatrix |
SLLine.getZData() |
DblMatrix |
Surface.getZData() |
DblMatrix |
SLSurface.getZData() |
DblMatrix |
Line.getZData() |
DblMatrix |
SLCamera.getZLim() |
DblMatrix |
SLPolyRegion.getZLim() |
DblMatrix |
SLLocator.getZLim() |
DblMatrix |
SLAxes.getZLim() |
DblMatrix |
SLGrid.getZLim() |
DblMatrix |
ZoomDialog.getZoomValue() |
DblMatrix |
Axes.getZRange() |
DblMatrix |
SLAxes.getZRange() |
static DblMatrix |
DefaultColorMapper.luminance(java.awt.Color color)
Returns the approximate luminance of a Color.
|
static DblMatrix |
SLCamera.rotatorFor(DblMatrix tt,
DblMatrix U)
Return in R a 3D rotation matrix that rotates an angle theta about the fixed unit vector u.
|
Modifier and Type | Method and Description |
---|---|
boolean |
SLPolyRegion.contains(DblMatrix coords)
Determines whether the specified coordinates are inside this polygon.
|
static DblMatrix |
SLCamera.getCameraDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction of the camera.
|
static DblMatrix |
SLCamera.getCameraDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction of the camera.
|
static DblMatrix |
SLCamera.getCameraStarboardDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction to the right of the camera.
|
static DblMatrix |
SLCamera.getCameraStarboardDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction to the right of the camera.
|
static DblMatrix |
SLCamera.getCameraUpDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction up from the camera.
|
static DblMatrix |
SLCamera.getCameraUpDirection(DblMatrix[] camBasis,
DblMatrix camPos)
Returns a unit vector (centered at the origin) indicating the direction up from the camera.
|
java.awt.Color |
ColorMapper.getColorFor(DblMatrix data) |
java.awt.Color |
DefaultColorMapper.getColorFor(DblMatrix data) |
java.awt.Color |
ColorMapper.getColorFor(DblMatrix[] data) |
java.awt.Color |
DefaultColorMapper.getColorFor(DblMatrix[] DATA)
Colormapping to given data.
|
int[] |
SLCamera.getPixel(DblMatrix cx,
DblMatrix cy)
Get the screen pixels of the given data (camera focus plane) coordinates using this SLLocator.
|
int[] |
SLPolyRegion.getPixel(DblMatrix x,
DblMatrix y) |
int[] |
SLLocator.getPixel(DblMatrix x,
DblMatrix y) |
int[] |
SLAxes.getPixel(DblMatrix x,
DblMatrix y) |
int[] |
SLGrid.getPixel(DblMatrix x,
DblMatrix y) |
int[] |
SLCamera.getPixel(DblMatrix x,
DblMatrix y,
DblMatrix z) |
int[] |
SLPolyRegion.getPixel(DblMatrix x,
DblMatrix y,
DblMatrix z) |
int[] |
SLLocator.getPixel(DblMatrix x,
DblMatrix y,
DblMatrix z) |
int[] |
SLAxes.getPixel(DblMatrix x,
DblMatrix y,
DblMatrix z) |
int[] |
SLGrid.getPixel(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLCamera.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLPolyRegion.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLLocator.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLAxes.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLGrid.getPixelAsDbl(DblMatrix x,
DblMatrix y) |
DblMatrix |
SLCamera.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLPolyRegion.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLLocator.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLAxes.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
DblMatrix |
SLGrid.getPixelAsDbl(DblMatrix x,
DblMatrix y,
DblMatrix z) |
float[] |
SLCamera.getPixelAsFloat(DblMatrix x,
DblMatrix y) |
float[] |
SLPolyRegion.getPixelAsFloat(DblMatrix x,
DblMatrix y) |
float[] |
SLLocator.getPixelAsFloat(DblMatrix x,
DblMatrix y) |
float[] |
SLAxes.getPixelAsFloat(DblMatrix x,
DblMatrix y) |
float[] |
SLGrid.getPixelAsFloat(DblMatrix x,
DblMatrix y) |
float[] |
SLCamera.getPixelAsFloat(DblMatrix x,
DblMatrix y,
DblMatrix z) |
float[] |
SLPolyRegion.getPixelAsFloat(DblMatrix x,
DblMatrix y,
DblMatrix z) |
float[] |
SLLocator.getPixelAsFloat(DblMatrix x,
DblMatrix y,
DblMatrix z) |
float[] |
SLAxes.getPixelAsFloat(DblMatrix x,
DblMatrix y,
DblMatrix z) |
float[] |
SLGrid.getPixelAsFloat(DblMatrix x,
DblMatrix y,
DblMatrix z) |
int[] |
SLCamera.getScreenPixel(DblMatrix cx,
DblMatrix cy)
Get the physical screen pixels of the given data (camera focus plane) coordinates using this SLLocator.
|
DblMatrix |
LpregPanel.ResultsTab.InvOptObjective.getValueAt(DblMatrix X) |
DblMatrix |
FitFrameModel.getValueAt(DblMatrix Y) |
DblMatrix |
DefaultReporter.getVar(DblMatrix W,
java.lang.String name)
Gets the column of the input matrix according to the current variable name mapping.
|
void |
SLCamera.lookAt(DblMatrix lba)
Rotate the view of the camera so that it is looking at the given coordinates.
|
Line[] |
SnifflibGraphics.mplot(DblMatrix X,
DblMatrix Y)
Plot columns of 2D matrix Y versus the single column vector in X.
|
SLLine |
SLAxes.newLine(DblMatrix x,
DblMatrix y)
Adds a new SLLine to the this SLAxes.
|
SLLine |
SLAxes.newLine(DblMatrix x,
DblMatrix y,
java.awt.Color col)
Adds a new SLLine to the this SLAxes.
|
void |
SLCamera.panAbout(DblMatrix reforigin,
DblMatrix deltatheta)
Pans the camera horizontally relative to a reference point.
|
void |
SLCamera.panAbout(DblMatrix reforigin,
DblMatrix deltatheta,
DblMatrix deltaphi)
Pans the camera relative to a reference point.
|
void |
SLCamera.panAbout(DblMatrix reforigin,
DblMatrix deltatheta,
DblMatrix deltaphi,
DblMatrix deltarho)
Pans the camera relative to a reference point.
|
Line |
SnifflibGraphics.plot(DblMatrix Y) |
Line |
SnifflibGraphics.plot(DblMatrix X,
DblMatrix Y) |
void |
SLCamera.putInFrameUsing(DblMatrix direction)
Moves camera parallel to the given vector (anchored at the origin) until
all components are "in frame".
|
static DblMatrix |
SLCamera.rotatorFor(DblMatrix tt,
DblMatrix U)
Return in R a 3D rotation matrix that rotates an angle theta about the fixed unit vector u.
|
void |
SLAxes.setAxisHideThreshold(DblMatrix c) |
void |
SLBarChart.setBarData(DblMatrix orgins,
DblMatrix extents) |
void |
SLCamera.setCameraPosition(DblMatrix x) |
void |
DefaultColorMapper.setColorMap(java.awt.Color[] vals,
DblMatrix data) |
void |
SLHistogram.setData(DblMatrix dat) |
void |
SLCamera.setDigitalZoom(DblMatrix x) |
void |
SLAnnotation.setDirectionReferencePoint(DblMatrix c) |
void |
SLAxes.setExtentX(DblMatrix ex) |
void |
SLAxes.setExtentY(DblMatrix ex) |
void |
SLAxes.setExtentZ(DblMatrix ex) |
void |
SLLegend.setLegendLocation(DblMatrix xdata,
DblMatrix ydata) |
void |
SLLine.setLineDash(DblMatrix dashpattern) |
void |
SLHistogram.setLowerBinLimit(DblMatrix x) |
void |
ColorMapper.setMaxValue(DblMatrix val) |
void |
DefaultColorMapper.setMaxValue(DblMatrix val) |
void |
ColorMapper.setMinValue(DblMatrix val) |
void |
DefaultColorMapper.setMinValue(DblMatrix val) |
void |
LpregPanel.ResultsTab.InvOptObjective.setParam(java.lang.String name,
DblMatrix value) |
void |
FitFrameModel.setParam(java.lang.String p,
DblMatrix b) |
void |
SLCamera.setPhi(DblMatrix x)
Sets the angle of rotation away from the z-axis.
|
void |
SLCamera.setPsi(DblMatrix x)
Sets the angle of axial rotation of the camera.
|
void |
SLStereoCameraGroup.setSeparation(DblMatrix c) |
void |
SLCamera.setTheta(DblMatrix x)
Sets the angle of rotation away from the x-axis.
|
void |
DefaultReportInstance.setTime(DblMatrix S) |
void |
SLHistogram.setUpperBinLimit(DblMatrix x) |
void |
DefaultReportInstance.setValue(DblMatrix S) |
void |
AxesRangeSelection.setValue(DblMatrix val) |
void |
DefaultReporter.setVar(DblMatrix W,
java.lang.String name,
DblMatrix V)
Sets the column of the input matrix according to the current variable name mapping.
|
void |
SLLine.setXData(DblMatrix X) |
void |
Surface.setXData(DblMatrix X) |
void |
SLPolyRegion.setXData(DblMatrix X) |
void |
Line.setXData(DblMatrix X) |
void |
SLAnnotation.setXData(DblMatrix x) |
void |
SLAxes.setXLim(DblMatrix xlim) |
void |
SLLine.setYData(DblMatrix Y) |
void |
Surface.setYData(DblMatrix Y) |
void |
SLPolyRegion.setYData(DblMatrix Y) |
void |
Line.setYData(DblMatrix Y) |
void |
SLAnnotation.setYData(DblMatrix y) |
void |
SLAxes.setYLim(DblMatrix ylim) |
void |
SLLine.setZData(DblMatrix Z) |
void |
Surface.setZData(DblMatrix Z) |
void |
SLPolyRegion.setZData(DblMatrix Z) |
void |
Line.setZData(DblMatrix Z) |
void |
ZoomDialog.setZoomValue(DblMatrix z) |
Surface |
SnifflibGraphics.surface(DblMatrix X) |
Surface |
SnifflibGraphics.surface(DblMatrix X,
DblMatrix Y,
DblMatrix Z) |
static void |
SLCamera.updateCameraBasis(DblMatrix[] camBasis,
DblMatrix Phi,
DblMatrix Theta,
DblMatrix Psi,
DblMatrix Position) |
static void |
SLCamera.updateCameraBasis(DblMatrix[] camBasis,
DblMatrix Phi,
DblMatrix Theta,
DblMatrix Psi,
DblMatrix Position) |
void |
GnuplotSnifflibGraphicsFilter.writeDataBlock(DblMatrix X) |
void |
GnuplotSnifflibGraphicsFilter.writeDataBlock(DblMatrix X,
DblMatrix Y) |
void |
GnuplotSnifflibGraphicsFilter.writeDataBlock(DblMatrix X,
DblMatrix Y,
DblMatrix Z) |
Constructor and Description |
---|
DefaultColorMapper(DblMatrix low,
DblMatrix high) |
LpregPanel.ResultsTab(java.lang.String tab,
DblMatrix[] Xin,
DblMatrix Yin) |
LpregPanel.ResultsTab(java.lang.String tab,
DblMatrix[] Xin,
DblMatrix Yin) |
SLGradientPaint(SLLocator locat,
DblMatrix coords1,
java.awt.Color col1,
DblMatrix coords2,
java.awt.Color col2)
Creates a 2-color linear gradient between the two given data coordinates.
|
SLLinearGradientPaint(SLLocator locat,
DblMatrix star,
DblMatrix sto,
DblMatrix frac,
java.awt.Color[] colrs,
java.awt.MultipleGradientPaint.CycleMethod meth)
Creates a 2-color linear gradient between the two given data coordinates.
|
SLRadialGradientPaint(SLLocator locat,
DblMatrix cent,
DblMatrix rad,
DblMatrix foc,
DblMatrix frac,
java.awt.Color[] colrs,
java.awt.MultipleGradientPaint.CycleMethod meth)
Creates a 2-color linear gradient between the two given data coordinates.
|
SLSurface(SLComponent parent,
DblMatrix X,
DblMatrix Y,
DblMatrix Z) |
SLSurface(SLLocator locator,
SLComponent parent,
DblMatrix X,
DblMatrix Y,
DblMatrix Z) |
SLTexturePaint(SLLocator locat,
DblMatrix origin,
DblMatrix wid,
DblMatrix heig,
java.awt.image.BufferedImage ture)
Creates a texture paint.
|
Modifier and Type | Method and Description |
---|---|
DblMatrix |
NamedParameterNode.getParameterValue() |
Modifier and Type | Method and Description |
---|---|
void |
NamedParameterNode.setParameterValue(DblMatrix x) |
Constructor and Description |
---|
NamedParameterNode(java.lang.String domain,
DblMatrix param) |
NamedParameterNode(java.lang.String domain,
java.lang.String imagepath,
DblMatrix value) |
Modifier and Type | Field and Description |
---|---|
DblMatrix |
OdeSet.absTol |
protected DblMatrix |
InterpolationQueue.desiredT |
DblMatrix |
OdeReporter.EventTimeTrace |
DblMatrix |
OdeReporter.EventTrace |
DblMatrix |
OdeSet.initDt |
DblMatrix |
OdeSet.initY |
protected DblMatrix |
OdeReporter.LastT |
DblMatrix |
OdeSet.maxDt |
DblMatrix |
OdeSet.minDt |
DblMatrix |
OdeReporter.nextInterpT |
protected DblMatrix |
InterpolationQueue.predictedY |
DblMatrix |
OdeSet.relTol |
protected DblMatrix |
OdeUpdate.suggestedNextInterval |
protected DblMatrix |
AbstractOdeSolver.T |
protected DblMatrix |
BasicODE.T |
protected DblMatrix |
Ode.T |
protected DblMatrix |
OdeReporter.T4Interp |
DblMatrix |
OdeSet.timePoints |
DblMatrix |
OdeReporter.TInterp |
protected DblMatrix |
AbstractOdeSolver.tnew |
protected DblMatrix |
OdeUpdate.Tnew |
protected DblMatrix |
AbstractOdeSolver.tnow |
DblMatrix |
OdeSet.tStart |
DblMatrix |
OdeSet.tStop |
DblMatrix |
OdeReporter.TTrace |
DblMatrix |
AbstractOdeSolver.Interp1D.X |
protected DblMatrix |
PointWiseQuadratureAlgorithm.XData |
protected DblMatrix |
AbstractOdeSolver.Y |
DblMatrix |
AbstractOdeSolver.Interp1D.Y |
protected DblMatrix |
BasicODE.Y |
protected DblMatrix |
Ode.Y |
protected DblMatrix |
OdeReporter.Y4Interp |
protected DblMatrix |
PointWiseQuadratureAlgorithm.YData |
protected DblMatrix |
OdeUpdate.Yerr |
protected DblMatrix |
AbstractOdeSolver.ynew |
protected DblMatrix |
OdeUpdate.Ynew |
protected DblMatrix |
AbstractOdeSolver.ynow |
DblMatrix |
OdeReporter.YTrace |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
OdeSet.getAbsoluteTolerance() |
DblMatrix |
Logistic.getDeriv() |
DblMatrix |
BasicODE.getDeriv() |
DblMatrix |
Exponential.getDeriv() |
abstract DblMatrix |
Ode.getDeriv() |
DblMatrix |
BasicODE.getDerivChk() |
DblMatrix |
Ode.getDerivChk()
Returns the current derivative (or rhs) but also checks for
reasonableness of the answer.
|
DblMatrix |
AbstractOdeSolver.getDesiredAccuracy(DblMatrix Yold,
DblMatrix Ynow,
DblMatrix dT)
Standard methods for determining a desired accuracy for a solution of a single integration
step.
|
DblMatrix |
OdeUpdate.getError() |
DblMatrix |
OdeReporter.getEvent() |
DblMatrix |
BasicODE.getEvents() |
DblMatrix |
Ode.getEvents() |
DblMatrix |
OdeReporter.getEventTime() |
DblMatrix |
NumericDeriv.getHessian(DblMatrix dependents)
Calculate mixed partial derivatives of components of the VectorValued
response with respect to perturbations in the components of an input
DblMatrix.
|
DblMatrix |
OdeSet.getInitialTimeStep() |
DblMatrix |
OdeSet.getInitialValue() |
DblMatrix |
DataQuad.getIntegral()
Get the integral
|
DblMatrix |
TrapzAnalyticQuadratureAlgorithm.getIntegral()
Get the integral
|
DblMatrix |
TrapzPointWiseQuadratureAlgorithm.getIntegral()
Get the integral
|
DblMatrix |
FunQuad.getIntegral()
Get the integral
|
DblMatrix |
SimpAnalyticQuadratureAlgorithm.getIntegral()
Get the integral
|
DblMatrix |
QuadratureAlgorithm.getIntegral()
Get the integral
|
abstract DblMatrix |
PointWiseQuadratureAlgorithm.getIntegral()
Get the integral
|
abstract DblMatrix |
AnalyticQuadratureAlgorithm.getIntegral()
Get the integral
|
DblMatrix |
NumericDeriv.getJacobian(DblMatrix dependents)
Calculate partial derivative of each component of the VectorValued
response with respect to perturbations in the components of an input
DblMatrix.
|
DblMatrix |
BasicODE.getJacobn() |
DblMatrix |
Ode.getJacobn() |
DblMatrix |
BasicODE.getJacobnPattern() |
DblMatrix |
Ode.getJacobnPattern() |
DblMatrix |
DataQuad.getLowerLimit()
Get the lower limit of integration.
|
DblMatrix |
FunQuad.getLowerLimit()
Get the lower limit of integration.
|
DblMatrix |
QuadratureAlgorithm.getLowerLimit()
Get the lower limit of integration.
|
DblMatrix |
PointWiseQuadratureAlgorithm.getLowerLimit()
Get the lower limit of integration.
|
DblMatrix |
AnalyticQuadratureAlgorithm.getLowerLimit()
Get the lower limit of integration.
|
DblMatrix |
OdeSet.getMaxTimeStep() |
DblMatrix |
OdeSet.getMinTimeStep() |
DblMatrix |
BasicODE.getParam(java.lang.String name) |
DblMatrix |
Ode.getParam(java.lang.String name) |
DblMatrix |
OdeModel.getPredictionAt(DblMatrix[] X)
Returns null if solution fails or could not be obtained.
|
DblMatrix |
OdeSet.getRelativeTolerance() |
DblMatrix |
OdeSet.getStartTime() |
DblMatrix |
OdeSet.getStopTime() |
DblMatrix |
OdeUpdate.getSuggestedNextInterval() |
DblMatrix |
AbstractOdeSolver.getT() |
DblMatrix |
OdeReporter.getT() |
DblMatrix |
OdeReporter.TraceQueueElement.getT() |
DblMatrix |
OdeSolution.getT() |
DblMatrix |
BasicODE.getT() |
DblMatrix |
InterpolationQueue.getT() |
DblMatrix |
Ode.getT() |
DblMatrix |
OdeSolver.getT() |
DblMatrix |
OdeSet.getTimePoints() |
DblMatrix |
OdeUpdate.getTnew() |
DblMatrix |
AnalyticQuadratureAlgorithm.getTolerance() |
DblMatrix |
DataQuad.getUpperLimit()
Get the upper limit of integration.
|
DblMatrix |
FunQuad.getUpperLimit()
Get the upper limit of integration.
|
DblMatrix |
QuadratureAlgorithm.getUpperLimit()
Get the upper limit of integration.
|
DblMatrix |
PointWiseQuadratureAlgorithm.getUpperLimit()
Get the upper limit of integration.
|
DblMatrix |
AnalyticQuadratureAlgorithm.getUpperLimit()
Get the upper limit of integration.
|
DblMatrix |
BasicODE.getValue() |
DblMatrix |
Ode.getValue() |
DblMatrix |
Ode.getValueAt(DblMatrix X)
This is provided for compatability with the AbstractFunction.
|
DblMatrix |
Ode.getValueAt(DblMatrix[] X)
This is provided for compatability with the AbstractFunction.
|
DblMatrix |
Ode.getVar(DblMatrix W,
java.lang.String name)
Gets the column of the input matrix according to the current variable name mapping.
|
DblMatrix |
Ode.getVar(java.lang.String name)
Gets the column of the Y field according to the current variable name mapping.
|
DblMatrix |
PointWiseQuadratureAlgorithm.getXData()
Get the coordinate being integrated.
|
DblMatrix |
AbstractOdeSolver.getY() |
DblMatrix |
OdeReporter.getY() |
DblMatrix |
OdeReporter.TraceQueueElement.getY() |
DblMatrix |
OdeSolution.getY() |
DblMatrix |
BasicODE.getY() |
DblMatrix |
InterpolationQueue.getY() |
DblMatrix |
Ode.getY() |
DblMatrix |
OdeSolver.getY() |
DblMatrix |
PointWiseQuadratureAlgorithm.getYData()
Get the response being integrated.
|
DblMatrix |
OdeUpdate.getYnew() |
DblMatrix |
AbstractOdeSolver.Interp1D.predict(DblMatrix XX) |
Modifier and Type | Method and Description |
---|---|
void |
InterpolationQueue.addData(DblMatrix T,
DblMatrix Y) |
void |
OdeReporter.addToEventsTrace(DblMatrix T,
DblMatrix Event) |
void |
OdeReporter.addToSolutionTrace(DblMatrix T,
DblMatrix Y) |
DblMatrix |
AbstractOdeSolver.getDesiredAccuracy(DblMatrix Yold,
DblMatrix Ynow,
DblMatrix dT)
Standard methods for determining a desired accuracy for a solution of a single integration
step.
|
DblMatrix |
NumericDeriv.getHessian(DblMatrix dependents)
Calculate mixed partial derivatives of components of the VectorValued
response with respect to perturbations in the components of an input
DblMatrix.
|
DblMatrix |
NumericDeriv.getJacobian(DblMatrix dependents)
Calculate partial derivative of each component of the VectorValued
response with respect to perturbations in the components of an input
DblMatrix.
|
DblMatrix |
OdeModel.getPredictionAt(DblMatrix[] X)
Returns null if solution fails or could not be obtained.
|
DblMatrix |
Ode.getValueAt(DblMatrix X)
This is provided for compatability with the AbstractFunction.
|
DblMatrix |
Ode.getValueAt(DblMatrix[] X)
This is provided for compatability with the AbstractFunction.
|
DblMatrix |
Ode.getVar(DblMatrix W,
java.lang.String name)
Gets the column of the input matrix according to the current variable name mapping.
|
DblMatrix |
AbstractOdeSolver.Interp1D.predict(DblMatrix XX) |
void |
OdeSet.setAbsouteTolerance(DblMatrix abs) |
void |
OdeUpdate.setError(DblMatrix E)
Generally it is best for a step integrator to implment its own error estimation.
|
void |
OdeSet.setInitialTimeStep(DblMatrix Tstep)
Some solvers may use this while others may not need or use it.
|
void |
OdeSet.setInitialValue(DblMatrix init) |
void |
DataQuad.setLowerLimit(DblMatrix L)
Set the lower limit of integration.
|
void |
FunQuad.setLowerLimit(DblMatrix L)
Set the lower limit of integration.
|
void |
QuadratureAlgorithm.setLowerLimit(DblMatrix L)
Set the lower limit of integration.
|
void |
PointWiseQuadratureAlgorithm.setLowerLimit(DblMatrix L)
Set the lower limit of integration.
|
void |
AnalyticQuadratureAlgorithm.setLowerLimit(DblMatrix L)
Set the lower limit of integration.
|
void |
OdeSet.setMaxTimeStep(DblMatrix Tstep)
Some solvers may use this while others may not need or use it.
|
void |
OdeSet.setMinTimeStep(DblMatrix Tstep) |
void |
BasicODE.setParam(java.lang.String name,
DblMatrix value) |
void |
Ode.setParam(java.lang.String name,
DblMatrix value) |
void |
OdeSet.setRelativeTolerance(DblMatrix rel) |
void |
OdeSet.setStartTime(DblMatrix start) |
void |
OdeSet.setStopTime(DblMatrix stop) |
void |
OdeUpdate.setSuggestedNextInterval(DblMatrix dT) |
void |
OdeReporter.TraceQueueElement.setT(DblMatrix T) |
void |
BasicODE.setT(DblMatrix T)
This sets the T pointer of the model to the input DblMatrix.
|
void |
Ode.setT(DblMatrix T)
This sets the T pointer of the model to the input DblMatrix.
|
void |
InterpolationQueue.setTimePoints(DblMatrix desired) |
void |
OdeSet.setTimePoints(DblMatrix t) |
void |
OdeReporter.setTInterp(DblMatrix T) |
void |
OdeUpdate.setTnew(DblMatrix tnew) |
void |
AnalyticQuadratureAlgorithm.setTolerance(DblMatrix T) |
void |
DataQuad.setUpperLimit(DblMatrix U)
Set the upper limit of integration.
|
void |
FunQuad.setUpperLimit(DblMatrix U)
Set the upper limit of integration.
|
void |
QuadratureAlgorithm.setUpperLimit(DblMatrix U)
Set the upper limit of integration.
|
void |
PointWiseQuadratureAlgorithm.setUpperLimit(DblMatrix U)
Set the upper limit of integration.
|
void |
AnalyticQuadratureAlgorithm.setUpperLimit(DblMatrix U)
Set the upper limit of integration.
|
void |
Ode.setVar(DblMatrix W,
java.lang.String name,
DblMatrix V)
Sets the column of the input matrix according to the current variable name mapping.
|
void |
Ode.setVar(java.lang.String name,
DblMatrix val)
Change the current values of the state variables according to the current variable name
mapping.
|
void |
PointWiseQuadratureAlgorithm.setXData(DblMatrix X)
Set the coordinate data being integrated.
|
void |
OdeReporter.TraceQueueElement.setY(DblMatrix Y) |
void |
BasicODE.setY(DblMatrix Y)
This sets the Y pointer of the model to the input DblMatrix.
|
void |
Ode.setY(DblMatrix Y)
This sets the Y pointer of the model to the input DblMatrix.
|
void |
PointWiseQuadratureAlgorithm.setYData(DblMatrix Y)
Set the response data being integrated.
|
void |
OdeUpdate.setYnew(DblMatrix ynew) |
Constructor and Description |
---|
AbstractOdeSolver.Interp1D(DblMatrix X,
DblMatrix Y) |
AbstractOdeSolver.Interp1D(DblMatrix X,
DblMatrix Y,
java.lang.String method) |
DataQuad(DblMatrix Y)
Integrate Y assuming X has unit spacing.
|
DataQuad(DblMatrix X,
DblMatrix Y)
Integrate Y given the abscissae in X.
|
DataQuad(DblMatrix X,
DblMatrix Y,
DblMatrix L,
DblMatrix U)
Integrate function from the upper to the lower limit of integration.
|
DataQuad(DblMatrix X,
DblMatrix Y,
double L,
double U)
Integrate function from the upper to the lower limit of integration.
|
DataQuad(DblMatrix X,
DblMatrix Y,
int L,
int U)
Integrate data from the upper to the lower limit of integration.
|
FunQuad(AbstractFunction FUN,
DblMatrix L,
DblMatrix U)
Integrate function from the upper to the lower limit of integration.
|
OdeModel(OdeSolver s,
DblMatrix[] X,
DblMatrix Y) |
OdeModel(OdeSolver s,
DblMatrix[] X,
DblMatrix Y) |
OdeReporter.TraceQueueElement(DblMatrix T,
DblMatrix Y) |
PointWiseQuadratureAlgorithm(DblMatrix X,
DblMatrix Y) |
TrapzPointWiseQuadratureAlgorithm(DblMatrix X,
DblMatrix Y) |
Modifier and Type | Field and Description |
---|---|
DblMatrix |
Lpreg.Alpha |
DblMatrix |
LpregDiagnostics.beta |
protected DblMatrix |
Polint.C |
protected DblMatrix |
Polint.D |
DblMatrix |
LpregDiagnostics.design |
protected DblMatrix |
Pzextr.dY |
protected DblMatrix |
Polint.dY |
DblMatrix |
GCVSmoothMethod.InitialSmoothParameter |
protected DblMatrix |
Pzextr.lastx |
DblMatrix |
Lpreg.Model |
DblMatrix |
LpregDiagnostics.pbias |
DblMatrix[] |
LpregDiagnostics.pci |
DblMatrix |
LpregDiagnostics.pcov |
DblMatrix |
Lpreg.PilotNWRSS |
protected DblMatrix |
Pzextr.qcol |
DblMatrix |
Lpreg.RemTerms |
DblMatrix |
Lpreg.RobustTol |
DblMatrix |
Lpreg.RWeights |
DblMatrix |
AbstractSmoothMethod.SmoothParameter |
DblMatrix[] |
Lpreg.sufficientX |
DblMatrix |
Lpreg.sufficientY |
protected DblMatrix |
NMSimplex.Temperature |
DblMatrix |
ParameterValuePair.Value |
DblMatrix[] |
Lpreg.X |
protected DblMatrix |
Dbracket.X |
protected DblMatrix |
Pzextr.X |
protected DblMatrix |
Interp1D.X |
DblMatrix |
LpregDiagnostics.y |
DblMatrix |
Lpreg.Y |
protected DblMatrix |
Pzextr.Y |
protected DblMatrix |
Polint.Y |
protected DblMatrix |
Interp1D.Y |
protected DblMatrix |
Interp1D.Yerr |
protected DblMatrix |
Interp1D.Yhat |
protected DblMatrix |
Pzextr.yz |
Modifier and Type | Method and Description |
---|---|
static DblMatrix |
DistributedStatisticalModel.convertStringToDbl(java.lang.String in) |
DblMatrix |
Lpreg.derivative(DblMatrix[] xx,
int v) |
DblMatrix |
KernelDensityEstimator.derivative(DblMatrix[] xx,
int v)
Return the derivative of the density.
|
DblMatrix |
Lpreg.derivative(DblMatrix xx,
int v) |
DblMatrix |
Lpreg.derivativeSingleThread(DblMatrix[] xx,
int v)
Predict derivative at the points in xx;
|
DblMatrix |
Lpreg.derivativeSingleThread(DblMatrix xx,
int v) |
DblMatrix |
SimulatedAnnealing.evaluateTemperature() |
DblMatrix |
DiffEvol.evaluateTemperature() |
DblMatrix |
NMSimplex.evaluateTemperature()
Determine the temperature for a simulated annealing schedule.
|
DblMatrix |
MetropolisHastings.getAlpha() |
DblMatrix |
MCMCSampler.getAlpha() |
abstract DblMatrix |
AbstractBandwidthMethod.getBandwidth(Lpreg Reg,
DblMatrix X) |
DblMatrix |
BandwidthMethod.getBandwidth(Lpreg reg,
DblMatrix xx) |
DblMatrix |
NNBandwidth.getBandwidth(Lpreg Reg,
DblMatrix thisxx) |
DblMatrix |
DiffEvol.getBestValue()
Get the scalar value at the estimated parameter value.
|
abstract DblMatrix |
VisualScalarOptimizer.getBestValue()
Get the scalar value at the estimated parameter value.
|
DblMatrix |
NMSimplex.getBestValue()
Get the scalar value at the estimated parameter value.
|
DblMatrix |
LpregDiagnostics.getBeta() |
DblMatrix |
BatesWatts.getBoxPctBias() |
DblMatrix[] |
KernelDensityEstimator.getConfidenceRegion(DblMatrix prob)
Returns the lower and upper limits of the (approximately symmetric) density region having the requested area.
|
DblMatrix |
LpregDiagnostics.getDesign() |
DblMatrix |
DistributedStatisticalModel.getDistributedParam(java.lang.String paramname) |
DblMatrix |
Pzextr.getError()
Return the estimated error of extrapolation.
|
DblMatrix |
Interp1D.getError()
Return the estimated error in prediction.
|
DblMatrix |
NMSimplex.getFitnessValue(DblParamSet param)
Get the fitness value for a particular parameter set.
|
DblMatrix |
Lpreg.getGCV() |
DblMatrix |
Lpreg.getHat(DblMatrix[] xx) |
DblMatrix |
BatesWatts.getIN() |
DblMatrix |
InitialConditionSource.getInitialConditionFor(java.lang.String varname) |
DblMatrix |
DefaultInitialConditionSource.getInitialConditionFor(java.lang.String varname) |
DblMatrix |
FixedSmoothMethod.getLastSmoothParameter()
Convenience method returning the fixed smooth parameter.
|
DblMatrix |
GCVSmoothMethod.getLastSmoothParameter() |
DblMatrix |
PenalizedLikelihood.getLikelihoodPenalty() |
DblMatrix |
MetropolisHastings.getLogBayesFactor() |
DblMatrix |
MCMCSampler.getLogBayesFactor() |
DblMatrix |
ScalarRootLocator.getLowerBound() |
DblMatrix |
BatesWatts.getMaxIN() |
DblMatrix |
BatesWatts.getMaxPE() |
DblMatrix |
Optimizable.getMinimizationValues() |
DblMatrix |
ProposalDistribution.getMixingParam(java.lang.String name) |
DblMatrix |
AbstractProposalDistribution.getMixingParam(java.lang.String name) |
DblMatrix |
Lpreg.getModel()
Return the current linear model specification.
|
DblMatrix |
StatisticalModel.getMSE()
Returns the MSE.
|
DblMatrix |
KernelDensityEstimator.getNormalizingConstant()
Estimates the density integral between the minimum and maximum data points.
|
DblMatrix |
KernelDensityEstimator.getNormalizingConstant(DblMatrix L,
DblMatrix U)
Estimates the un-normalized density integral between the given lower and upper limits.
|
DblMatrix |
StatisticalModel.getParam(java.lang.String name) |
DblMatrix |
DistributedStatisticalModel.getParam(java.lang.String name) |
DblMatrix |
KernelDensityEstimator.ConfidenceRegionObjective.getParam(java.lang.String name) |
DblMatrix |
MyQuadratic.getParam(java.lang.String name) |
DblMatrix |
NamedParameters.getParam(java.lang.String name) |
DblMatrix |
AbstractSimplexObjective.getParam(java.lang.String p) |
DblMatrix |
DistributedStatisticalModel.getParamSuper(java.lang.String name)
Provides access to the StatisticalModel super class method getParam.
|
DblMatrix |
BatesWatts.getPE() |
DblMatrix |
PenalizedLikelihood.getPenalizedLikelihood() |
DblMatrix |
StatisticalModel.getPosteriorParam(java.lang.String name) |
DblMatrix |
LpregDiagnostics.getPredBias() |
DblMatrix[] |
LpregDiagnostics.getPredCI() |
DblMatrix |
Interp1D.getPrediction()
Return the prediction.
|
abstract DblMatrix |
StatisticalModel.getPredictionAt(DblMatrix[] X) |
DblMatrix |
GaussianProposal.getPredictionAt(DblMatrix[] X) |
DblMatrix |
LpregDiagnostics.getPredVar() |
DblMatrix |
StatisticalModel.getPriorParam(java.lang.String name) |
DblMatrix |
PriorProbability.getPriorProbability() |
DblMatrix |
PosteriorProbability.getPriorProbability() |
DblMatrix |
ScalarRootLocator.getResult()
Get the root of the function located between the specified lower and upper bounds.
|
DblMatrix |
SmoothMethod.getSmoothParameter(Lpreg Reg,
DblMatrix xx) |
abstract DblMatrix |
AbstractSmoothMethod.getSmoothParameter(Lpreg Reg,
DblMatrix xx) |
DblMatrix |
FixedSmoothMethod.getSmoothParameter(Lpreg reg,
DblMatrix thisxx) |
DblMatrix |
GCVSmoothMethod.getSmoothParameter(Lpreg reg,
DblMatrix thisxx)
Since the GCV smoothing parameter is global the specified coordinates
are ignored.
|
DblMatrix |
SumOfSquares.getSumOfSquares() |
DblMatrix |
ScalarRootLocator.getTargetValue() |
DblMatrix |
SimulatedAnnealing.getTemperature() |
DblMatrix |
DiffEvol.getTemperature() |
DblMatrix |
NMSimplex.getTemperature()
Get a temperature for a simulated annealing schedule.
|
DblMatrix |
ScalarRootLocator.getTolerance() |
DblMatrix |
ScalarRootLocator.getUpperBound() |
DblMatrix |
VectorValued.getValue() |
DblMatrix |
StatisticalModel.getValueAt(DblMatrix Y) |
DblMatrix |
KernelDensityEstimator.ConfidenceRegionObjective.getValueAt(DblMatrix X) |
DblMatrix |
OptimizableScalar.getValueAt(DblMatrix Y) |
DblMatrix |
MyQuadratic.getValueAt(DblMatrix x) |
DblMatrix |
AbstractSimplexObjective.getValueAt(DblMatrix Y) |
DblMatrix |
StatisticalModel.getValueAt(DblMatrix[] X) |
DblMatrix |
StatisticalModel.getValueAt(DblParamSet P) |
DblMatrix |
StatisticalModel.getValueToMinimize() |
DblMatrix |
KernelDensityEstimator.ConfidenceRegionObjective.getValueToMinimize() |
DblMatrix |
OptimizableScalar.getValueToMinimize() |
DblMatrix |
MyQuadratic.getValueToMinimize() |
abstract DblMatrix |
AbstractSimplexObjective.getValueToMinimize() |
DblMatrix |
WeightAlgorithm.getWeight(DblMatrix D)
Get the weight of a particular value.
|
abstract DblMatrix |
AbstractWeightAlgorithm.getWeight(DblMatrix D)
Get the weight of a particular value.
|
DblMatrix |
UniformWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
Weight.getWeight(DblMatrix D) |
DblMatrix |
NormalWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
StdRobustWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
TricubeWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
TriweightWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
EpanechnikovWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
BiweightWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix[] |
StatisticalModel.getX() |
DblMatrix[] |
Lpreg.getXdata() |
abstract DblMatrix[] |
AbstractBandwidthMethod.getXlocal() |
DblMatrix[] |
BandwidthMethod.getXlocal() |
DblMatrix[] |
NNBandwidth.getXlocal() |
DblMatrix |
StatisticalModel.getY() |
DblMatrix |
LpregDiagnostics.getY() |
DblMatrix |
Lpreg.getYdata() |
abstract DblMatrix |
AbstractBandwidthMethod.getYlocal() |
DblMatrix |
BandwidthMethod.getYlocal() |
DblMatrix |
NNBandwidth.getYlocal() |
DblMatrix |
StatisticalModel.likelihood()
Returns the default likelihood of zero.
|
DblMatrix |
Likelihood.likelihood()
Return the likelihood evaluated for the given DataSet.
|
static DblMatrix |
Lpreg.modelDesign(DblMatrix[] X,
DblMatrix model)
Create a design matrix from a model matrix.
|
DblMatrix |
StatisticalModel.negLogLikelihood()
Returns the default negative log likelihood of INF.
|
DblMatrix |
Likelihood.negLogLikelihood()
Return the negative of the log-likelihood evaluated at
the given Y values.
|
DblMatrix |
BayesianLinear.negLogLikelihood() |
DblMatrix |
GCVSmoothMethod.optimize(Lpreg reg) |
DblMatrix |
Lpreg.predict(DblMatrix xx) |
DblMatrix |
KernelDensityEstimator.predict(DblMatrix xx) |
DblMatrix |
Lpreg.predict(DblMatrix[] xx) |
DblMatrix |
KernelDensityEstimator.predict(DblMatrix[] xx) |
DblMatrix[] |
Polint.predictAt(DblMatrix xx)
Make a Nth order polynomial interpolation (or extrapolation) at the given data point.
|
DblMatrix |
Pzextr.predictAtZero()
Extrapolate to zero.
|
DblMatrix |
Lpreg.predictConcurrent(DblMatrix xx) |
DblMatrix |
Lpreg.predictConcurrent(DblMatrix[] xx) |
DblMatrix |
Lpreg.predictSingleThread(DblMatrix[] xx) |
DblMatrix |
KernelDensityEstimator.predictUnNormalized(DblMatrix xx) |
DblMatrix |
KernelDensityEstimator.predictUnNormalized(DblMatrix[] xx)
Predicts the density at the given value(s).
|
DblMatrix |
Lpreg.regress(DblMatrix Y,
DblMatrix Design)
Solve least squares problem using QR decomposition.
|
DblMatrix |
StatisticalModel.residuals()
Returns the default residual of zero.
|
DblMatrix |
StatisticalModel.sumNegLogLikelihood()
Return the sum of the negative log likelihood
|
Modifier and Type | Method and Description |
---|---|
void |
Pzextr.addToLowest(DblMatrix xest,
DblMatrix yest)
Propagate tableau.
|
int[] |
Dbracket.bracket(DblMatrix xx)
Find a bracketing interval about a given data point.
|
static java.lang.String |
DistributedStatisticalModel.convertDblToString(DblMatrix in) |
protected void |
DistributedStatisticalModel.declareDistributedParameter(java.lang.String p,
DblMatrix v) |
protected boolean |
DistributedStatisticalModel.declareIfNotDistributedParameter(java.lang.String p,
DblMatrix v) |
protected boolean |
StatisticalModel.declareIfNotParameter(java.lang.String p,
DblMatrix v)
Convenience method that declares a parameter and sets
a initial (default) value for that parameter only if the
parameter is not already declared.
|
protected boolean |
StatisticalModel.declareIfNotPriorParameter(java.lang.String p,
DblMatrix v)
Convenience method that declares a parameter and sets
a initial (default) value for that parameter only if the
parameter is not already declared.
|
void |
StatisticalModel.declareParameter(java.lang.String p,
DblMatrix v)
Convenience method that declares a parameter and sets
a initial (default) value for that parameter.
|
void |
DistributedStatisticalModel.declareParameter(java.lang.String p,
DblMatrix v) |
void |
DistributedStatisticalModel.declareParameterSuper(java.lang.String p,
DblMatrix v) |
protected void |
StatisticalModel.declarePriorParameter(java.lang.String p,
DblMatrix v)
Convenience method that declares a parameter and sets
a initial (default) value for that parameter.
|
DblMatrix |
Lpreg.derivative(DblMatrix[] xx,
int v) |
DblMatrix |
KernelDensityEstimator.derivative(DblMatrix[] xx,
int v)
Return the derivative of the density.
|
DblMatrix |
Lpreg.derivative(DblMatrix xx,
int v) |
DblMatrix |
Lpreg.derivativeSingleThread(DblMatrix[] xx,
int v)
Predict derivative at the points in xx;
|
DblMatrix |
Lpreg.derivativeSingleThread(DblMatrix xx,
int v) |
LpregDiagnostics |
Lpreg.diagnosticsSingleThread(DblMatrix[] xx) |
LpregDiagnostics |
Lpreg.diagnosticsSingleThread(DblMatrix[] xx,
int v)
Get diagnostics for the prediction of the vth derivative.
|
abstract DblMatrix |
AbstractBandwidthMethod.getBandwidth(Lpreg Reg,
DblMatrix X) |
DblMatrix |
BandwidthMethod.getBandwidth(Lpreg reg,
DblMatrix xx) |
DblMatrix |
NNBandwidth.getBandwidth(Lpreg Reg,
DblMatrix thisxx) |
int[] |
Dbracket.getCenteredWindow(DblMatrix xx,
int m)
Return a window of m points centered about the value X.
|
DblMatrix[] |
KernelDensityEstimator.getConfidenceRegion(DblMatrix prob)
Returns the lower and upper limits of the (approximately symmetric) density region having the requested area.
|
DblMatrix |
Lpreg.getHat(DblMatrix[] xx) |
DblMatrix |
KernelDensityEstimator.getNormalizingConstant(DblMatrix L,
DblMatrix U)
Estimates the un-normalized density integral between the given lower and upper limits.
|
abstract DblMatrix |
StatisticalModel.getPredictionAt(DblMatrix[] X) |
DblMatrix |
GaussianProposal.getPredictionAt(DblMatrix[] X) |
DblMatrix |
SmoothMethod.getSmoothParameter(Lpreg Reg,
DblMatrix xx) |
abstract DblMatrix |
AbstractSmoothMethod.getSmoothParameter(Lpreg Reg,
DblMatrix xx) |
DblMatrix |
FixedSmoothMethod.getSmoothParameter(Lpreg reg,
DblMatrix thisxx) |
DblMatrix |
GCVSmoothMethod.getSmoothParameter(Lpreg reg,
DblMatrix thisxx)
Since the GCV smoothing parameter is global the specified coordinates
are ignored.
|
DblMatrix |
StatisticalModel.getValueAt(DblMatrix Y) |
DblMatrix |
KernelDensityEstimator.ConfidenceRegionObjective.getValueAt(DblMatrix X) |
DblMatrix |
OptimizableScalar.getValueAt(DblMatrix Y) |
DblMatrix |
MyQuadratic.getValueAt(DblMatrix x) |
DblMatrix |
AbstractSimplexObjective.getValueAt(DblMatrix Y) |
DblMatrix |
StatisticalModel.getValueAt(DblMatrix[] X) |
DblMatrix |
WeightAlgorithm.getWeight(DblMatrix D)
Get the weight of a particular value.
|
abstract DblMatrix |
AbstractWeightAlgorithm.getWeight(DblMatrix D)
Get the weight of a particular value.
|
DblMatrix |
UniformWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
Weight.getWeight(DblMatrix D) |
DblMatrix |
NormalWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
StdRobustWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
TricubeWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
TriweightWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
EpanechnikovWeightAlgorithm.getWeight(DblMatrix D) |
DblMatrix |
BiweightWeightAlgorithm.getWeight(DblMatrix D) |
int[] |
Dbracket.hunt(DblMatrix xx)
Return a single index bracket of a scalar X.
|
static DblMatrix |
Lpreg.modelDesign(DblMatrix[] X,
DblMatrix model)
Create a design matrix from a model matrix.
|
static DblMatrix |
Lpreg.modelDesign(DblMatrix[] X,
DblMatrix model)
Create a design matrix from a model matrix.
|
DblMatrix |
Lpreg.predict(DblMatrix xx) |
DblMatrix |
KernelDensityEstimator.predict(DblMatrix xx) |
DblMatrix |
Lpreg.predict(DblMatrix[] xx) |
DblMatrix |
KernelDensityEstimator.predict(DblMatrix[] xx) |
DblMatrix[] |
Polint.predictAt(DblMatrix xx)
Make a Nth order polynomial interpolation (or extrapolation) at the given data point.
|
void |
Interp1D.predictAt(DblMatrix xx)
Make predictions at points in vector by polynomial interpolation (or extrapolation).
|
DblMatrix |
Lpreg.predictConcurrent(DblMatrix xx) |
DblMatrix |
Lpreg.predictConcurrent(DblMatrix[] xx) |
DblMatrix |
Lpreg.predictSingleThread(DblMatrix[] xx) |
DblMatrix |
KernelDensityEstimator.predictUnNormalized(DblMatrix xx) |
DblMatrix |
KernelDensityEstimator.predictUnNormalized(DblMatrix[] xx)
Predicts the density at the given value(s).
|
DblMatrix |
Lpreg.regress(DblMatrix Y,
DblMatrix Design)
Solve least squares problem using QR decomposition.
|
void |
LpregDiagnostics.setBeta(DblMatrix in) |
void |
KernelDensityEstimator.setData(DblMatrix X)
Assumes a univariate density.
|
void |
KernelDensityEstimator.setData(DblMatrix[] X)
Assumes a (possibly) multivariate density.
|
void |
Lpreg.setData(DblMatrix[] Xin,
DblMatrix Yin) |
void |
Lpreg.setData(DblMatrix[] Xin,
DblMatrix Yin) |
void |
LpregDiagnostics.setDesign(DblMatrix in) |
void |
DistributedStatisticalModel.setDistributedParam(java.lang.String paramname,
DblMatrix value) |
void |
GCVSmoothMethod.setInitialSmoothParameter(DblMatrix S) |
void |
GaussianProposal.setLogNormal(java.lang.String param,
DblMatrix mixing)
Sets up the given parameter to be sampled from a Log-Normal distribution
with the given standard deviation.
|
void |
ScalarRootLocator.setLowerBound(DblMatrix x) |
void |
ProposalDistribution.setMixingParam(java.lang.String name,
DblMatrix x) |
void |
AbstractProposalDistribution.setMixingParam(java.lang.String name,
DblMatrix x) |
void |
Lpreg.setModel(DblMatrix m)
Set the current linear model specification.
|
void |
GaussianProposal.setOrderRestriction(java.lang.String[] ord_params,
DblMatrix mixing) |
void |
StatisticalModel.setParam(java.lang.String name,
DblMatrix value) |
void |
DistributedStatisticalModel.setParam(java.lang.String name,
DblMatrix value) |
void |
KernelDensityEstimator.ConfidenceRegionObjective.setParam(java.lang.String name,
DblMatrix value) |
void |
MyQuadratic.setParam(java.lang.String name,
DblMatrix value) |
void |
NamedParameters.setParam(java.lang.String name,
DblMatrix value) |
void |
AbstractSimplexObjective.setParam(java.lang.String p,
DblMatrix b) |
void |
DistributedStatisticalModel.setParamSuper(java.lang.String name,
DblMatrix value)
Provides access to the StatisticalModel super class method setParam.
|
void |
StatisticalModel.setPosteriorParam(java.lang.String name,
DblMatrix value) |
void |
LpregDiagnostics.setPredBias(DblMatrix in) |
void |
LpregDiagnostics.setPredCI(DblMatrix[] ci) |
void |
LpregDiagnostics.setPredVar(DblMatrix in) |
void |
StatisticalModel.setPriorParam(java.lang.String name,
DblMatrix value) |
void |
FixedSmoothMethod.setSmoothParameter(DblMatrix S) |
void |
GCVSmoothMethod.setSmoothParameter(DblMatrix S) |
void |
ScalarRootLocator.setTargetValue(DblMatrix c) |
void |
SimulatedAnnealing.setTemperature(DblMatrix temp) |
void |
DiffEvol.setTemperature(DblMatrix temp) |
void |
NMSimplex.setTemperature(DblMatrix temp)
Set a temperature for a simulated annealing schedule.
|
void |
ScalarRootLocator.setTolerance(DblMatrix x) |
void |
ScalarRootLocator.setUpperBound(DblMatrix x) |
void |
StatisticalModel.setX(DblMatrix[] X) |
void |
StatisticalModel.setY(DblMatrix Y) |
void |
LpregDiagnostics.setY(DblMatrix in) |
boolean |
DblParamSetSimplex.smallerDiameter(DblMatrix tol)
Calculate diameter of parameter values.
|
Modifier and Type | Method and Description |
---|---|
static DblMatrix |
CholFact.Chol(DblMatrix A)
Cholesky decomposition
Returns lower triangular matrix L such that input matrix A = L*L'.
|
static DblMatrix |
CholFact.CholBksb(DblMatrix L,
DblMatrix b)
Cholesky back-substitution.
|
DblMatrix |
SVDFact.conditionNumber() |
DblMatrix |
SVDAlgorithm.conditionNumber()
Returns the condition number of the decomposed matrix.
|
abstract DblMatrix |
AbstractSVDAlgorithm.conditionNumber()
Returns the condition number of the decomposed matrix.
|
DblMatrix |
NRSVDAlgorithm.conditionNumber() |
static DblMatrix |
VectorNorm.EuclidNorm(DblMatrix X)
Euclidean vector norm
|
DblMatrix |
NRQRAlgorithm.getA() |
DblMatrix |
NRQRAlgorithm.getD() |
DblMatrix |
NRQRAlgorithm.getFullQ()
Returns an m-by-m Q matrix when the matrix being decomposed was m-by-n.
|
DblMatrix |
QRAlgorithm.getFullQ()
Get the orthogonal matrix Q of the QR decomposition.
|
abstract DblMatrix |
AbstractQRAlgorithm.getFullQ() |
DblMatrix |
SparseHHQRAlgorithm.getFullQ() |
DblMatrix |
QRFact.getFullQ() |
DblMatrix |
ModiClarkeQRAlgorithm.getFullQ() |
DblMatrix |
NRQRAlgorithm.getFullR()
Returns an m-by-n R matrix when the matrix being decomposed was m-by-n.
|
DblMatrix |
QRAlgorithm.getFullR()
Get the lower triangular matrix R of the QR decomposition.
|
abstract DblMatrix |
AbstractQRAlgorithm.getFullR()
Get the lower triangular matrix R of the QR decomposition.
|
DblMatrix |
SparseHHQRAlgorithm.getFullR() |
DblMatrix |
QRFact.getFullR() |
DblMatrix |
ModiClarkeQRAlgorithm.getFullR() |
abstract DblMatrix |
AbstractLUAlgorithm.getL() |
DblMatrix |
LUFact.getL() |
DblMatrix |
NRLUAlgorithm.getL() |
DblMatrix |
LUAlgorithm.getL()
Get the lower triangular L of the LU decomposition.
|
DblMatrix |
VectorNormAlgorithm.getNorm(DblMatrix X) |
DblMatrix |
PVectorNormAlgorithm.getNorm(DblMatrix X)
Return the norm.
|
DblMatrix |
EuclideanVectorNormAlgorithm.getNorm(DblMatrix X)
Return the norm.
|
DblMatrix |
InfinityVectorNormAlgorithm.getNorm(DblMatrix X)
Return the norm.
|
abstract DblMatrix |
AbstractVectorNormAlgorithm.getNorm(DblMatrix X) |
DblMatrix |
VectorNorm.getNorm(DblMatrix X)
Return the norm.
|
DblMatrix |
OneVectorNormAlgorithm.getNorm(DblMatrix X)
Return the norm.
|
DblMatrix |
NRQRAlgorithm.getQ()
Returns the economy sized m-by-n Q for the decomposition of an m-by-n matrix.
|
DblMatrix |
QRAlgorithm.getQ()
Get the orthogonal matrix Q of the QR decomposition.
|
abstract DblMatrix |
AbstractQRAlgorithm.getQ() |
DblMatrix |
SparseHHQRAlgorithm.getQ() |
DblMatrix |
QRFact.getQ() |
DblMatrix |
ModiClarkeQRAlgorithm.getQ() |
DblMatrix |
NRQRAlgorithm.getR()
Get the upper triangular matrix R of the QR decomposition.
|
DblMatrix |
QRAlgorithm.getR()
Get the lower triangular matrix R of the QR decomposition.
|
abstract DblMatrix |
AbstractQRAlgorithm.getR()
Get the lower triangular matrix R of the QR decomposition.
|
DblMatrix |
SparseHHQRAlgorithm.getR() |
DblMatrix |
QRFact.getR() |
DblMatrix |
ModiClarkeQRAlgorithm.getR() |
DblMatrix |
SVDFact.getU() |
abstract DblMatrix |
AbstractLUAlgorithm.getU()
Get the upper triangular matrix U of the LU decomposition.
|
DblMatrix |
SVDAlgorithm.getU()
Get an orthonormal basis for the range of the decomposed matrix.
|
abstract DblMatrix |
AbstractSVDAlgorithm.getU()
Get an orthonormal basis for the range of the decomposed matrix.
|
DblMatrix |
LUFact.getU() |
DblMatrix |
NRLUAlgorithm.getU() |
DblMatrix |
NRSVDAlgorithm.getU() |
DblMatrix |
LUAlgorithm.getU()
Get the upper triangular matrix U of the LU decomposition.
|
DblMatrix |
SVDFact.getV() |
DblMatrix |
SVDAlgorithm.getV()
Get an orthonormal basis for the nullspace of the decomposed matrix.
|
abstract DblMatrix |
AbstractSVDAlgorithm.getV()
Get an orthonormal basis for the nullspace of the decomposed matrix.
|
DblMatrix |
NRSVDAlgorithm.getV() |
DblMatrix |
SVDFact.getW() |
DblMatrix |
SVDAlgorithm.getW()
Get the singular values of the matrix.
|
abstract DblMatrix |
AbstractSVDAlgorithm.getW()
Get the singular values of the matrix.
|
DblMatrix |
NRSVDAlgorithm.getW() |
static DblMatrix |
VectorNorm.InfNorm(DblMatrix X)
Infinity vector norm.
|
DblMatrix |
SVDFact.nullspace()
Return an orthonormal basis for the nullspace of the decomposed matrix.
|
DblMatrix |
SVDAlgorithm.nullspace()
Return an orthonormal basis for the nullspace of the decomposed matrix.
|
abstract DblMatrix |
AbstractSVDAlgorithm.nullspace()
Return an orthonormal basis for the nullspace of the decomposed matrix.
|
DblMatrix |
NRSVDAlgorithm.nullspace() |
static DblMatrix |
NRSVDAlgorithm.nullspace(DblMatrix X) |
static DblMatrix |
VectorNorm.OneNorm(DblMatrix X)
One vector norm
|
static DblMatrix |
VectorNorm.PNorm(DblMatrix X,
double P)
P-vector norm
|
static DblMatrix |
VectorNorm.PNorm(DblMatrix X,
int P)
P-vector norm
|
DblMatrix |
NRQRAlgorithm.QtransDot(DblMatrix Y)
Return the result of Q'*X for the input X.
|
DblMatrix |
QRAlgorithm.QtransDot(DblMatrix Y)
Multiply input by transpose of Q.
|
abstract DblMatrix |
AbstractQRAlgorithm.QtransDot(DblMatrix X) |
DblMatrix |
SparseHHQRAlgorithm.QtransDot(DblMatrix X) |
DblMatrix |
QRFact.QtransDot(DblMatrix Y) |
DblMatrix |
ModiClarkeQRAlgorithm.QtransDot(DblMatrix X) |
DblMatrix |
NRQRAlgorithm.rsolve(DblMatrix Y)
Solve the System R*b = Y for b given Y.
|
DblMatrix |
NRQRAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
QRAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
SVDFact.solveSystem(DblMatrix Y) |
abstract DblMatrix |
AbstractQRAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
abstract DblMatrix |
AbstractLUAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
SVDAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
SparseHHQRAlgorithm.solveSystem(DblMatrix X) |
abstract DblMatrix |
AbstractSVDAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
QRFact.solveSystem(DblMatrix Y) |
DblMatrix |
LUFact.solveSystem(DblMatrix b) |
DblMatrix |
NRLUAlgorithm.solveSystem(DblMatrix b)
Solves the set of n linear equations A*X = B.
|
DblMatrix |
ModiClarkeQRAlgorithm.solveSystem(DblMatrix X) |
DblMatrix |
NRSVDAlgorithm.solveSystem(DblMatrix b)
Solves the systems A*x = b for given right hand side b.
|
DblMatrix |
LUAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
Modifier and Type | Method and Description |
---|---|
static DblMatrix |
CholFact.Chol(DblMatrix A)
Cholesky decomposition
Returns lower triangular matrix L such that input matrix A = L*L'.
|
static DblMatrix |
CholFact.CholBksb(DblMatrix L,
DblMatrix b)
Cholesky back-substitution.
|
static DblMatrix |
VectorNorm.EuclidNorm(DblMatrix X)
Euclidean vector norm
|
DblMatrix |
VectorNormAlgorithm.getNorm(DblMatrix X) |
DblMatrix |
PVectorNormAlgorithm.getNorm(DblMatrix X)
Return the norm.
|
DblMatrix |
EuclideanVectorNormAlgorithm.getNorm(DblMatrix X)
Return the norm.
|
DblMatrix |
InfinityVectorNormAlgorithm.getNorm(DblMatrix X)
Return the norm.
|
abstract DblMatrix |
AbstractVectorNormAlgorithm.getNorm(DblMatrix X) |
DblMatrix |
VectorNorm.getNorm(DblMatrix X)
Return the norm.
|
DblMatrix |
OneVectorNormAlgorithm.getNorm(DblMatrix X)
Return the norm.
|
static DblMatrix |
VectorNorm.InfNorm(DblMatrix X)
Infinity vector norm.
|
static DblMatrix |
NRSVDAlgorithm.nullspace(DblMatrix X) |
static DblMatrix |
VectorNorm.OneNorm(DblMatrix X)
One vector norm
|
static DblMatrix |
VectorNorm.PNorm(DblMatrix X,
double P)
P-vector norm
|
static DblMatrix |
VectorNorm.PNorm(DblMatrix X,
int P)
P-vector norm
|
DblMatrix |
NRQRAlgorithm.QtransDot(DblMatrix Y)
Return the result of Q'*X for the input X.
|
DblMatrix |
QRAlgorithm.QtransDot(DblMatrix Y)
Multiply input by transpose of Q.
|
abstract DblMatrix |
AbstractQRAlgorithm.QtransDot(DblMatrix X) |
DblMatrix |
SparseHHQRAlgorithm.QtransDot(DblMatrix X) |
DblMatrix |
QRFact.QtransDot(DblMatrix Y) |
DblMatrix |
ModiClarkeQRAlgorithm.QtransDot(DblMatrix X) |
DblMatrix |
NRQRAlgorithm.rsolve(DblMatrix Y)
Solve the System R*b = Y for b given Y.
|
DblMatrix |
NRQRAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
QRAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
SVDFact.solveSystem(DblMatrix Y) |
abstract DblMatrix |
AbstractQRAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
abstract DblMatrix |
AbstractLUAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
SVDAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
SparseHHQRAlgorithm.solveSystem(DblMatrix X) |
abstract DblMatrix |
AbstractSVDAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
DblMatrix |
QRFact.solveSystem(DblMatrix Y) |
DblMatrix |
LUFact.solveSystem(DblMatrix b) |
DblMatrix |
NRLUAlgorithm.solveSystem(DblMatrix b)
Solves the set of n linear equations A*X = B.
|
DblMatrix |
ModiClarkeQRAlgorithm.solveSystem(DblMatrix X) |
DblMatrix |
NRSVDAlgorithm.solveSystem(DblMatrix b)
Solves the systems A*x = b for given right hand side b.
|
DblMatrix |
LUAlgorithm.solveSystem(DblMatrix Y)
Solve a linear system (X*b = Y) returning the coeficients
as a DblMatrix.
|
Constructor and Description |
---|
AbstractLUAlgorithm(DblMatrix X) |
AbstractQRAlgorithm(DblMatrix X) |
AbstractSVDAlgorithm(DblMatrix X) |
CholFact(DblMatrix X)
Default DblMatrix constructor.
|
LUFact(DblMatrix X)
Construction using the default algorithm.
|
ModiClarkeQRAlgorithm(DblMatrix X) |
NRLUAlgorithm(DblMatrix X) |
NRQRAlgorithm(DblMatrix X)
Construct with a DblMatrix.
|
NRSVDAlgorithm(DblMatrix ain) |
QRFact(DblMatrix X)
Construction using the default algorithm.
|
SparseHHQRAlgorithm(DblMatrix X) |
SVDFact(DblMatrix X)
Construction using the default algorithm.
|
Modifier and Type | Method and Description |
---|---|
DblMatrix |
WedgePanel.runLikelihoodScript() |
Modifier and Type | Field and Description |
---|---|
protected DblMatrix |
AbstractInitialCondition.defaultValue |
protected DblMatrix |
AbstractDiffusionCoef.defaultValue |
protected DblMatrix |
AbstractDiffuse.dt |
protected DblMatrix |
NDGrid.LowerBounds |
protected DblMatrix |
AbstractDiffuse.time |
protected DblMatrix |
AbstractBoundaryValueProblem.time |
protected DblMatrix |
AbstractBoundaryValueProblem.tstep |
protected DblMatrix |
AbstractDiffuse.tstop |
protected DblMatrix |
AbstractDiffuse.u |
protected DblMatrix |
AbstractBoundaryValueProblem.u |
protected DblMatrix |
NDGrid.UpperBounds |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
AbstractInitialCondition.getCoef(DblMatrix X)
Set the initial condition value.
|
DblMatrix |
InitialCondition.getCoef(DblMatrix X)
Get the values of the initial condition at the points in X.
|
DblMatrix |
BoundsCoefInterface.getCoef(DblMatrix X)
Get the values of the bounds coefficient at the points in X.
|
DblMatrix |
InitialConditionInterface.getCoef(DblMatrix X)
Get the values of the initial condition at the points in X.
|
DblMatrix |
AbstractDiffusionCoef.getCoef(DblMatrix X,
DblMatrix T)
Set the diffusion coefficient value.
|
DblMatrix |
DiffusionCoefInterface.getCoef(DblMatrix X,
DblMatrix T)
Get the values of the diffusion coefficient at the points in X.
|
DblMatrix[] |
NDGrid.getCoords(int I)
Get the coordinates according to this grid at index I.
|
DblMatrix[] |
NDGrid.getCoords(Subscript[] coords)
Get the coordinates according to this grid at index I.
|
DblMatrix |
AbstractInitialCondition.getDefaultValue()
Get the default value.
|
DblMatrix |
AbstractDiffusionCoef.getDefaultValue()
Get the default value.
|
DblMatrix |
DiffusionCoefInterface.getDefaultValue()
Get the default value.
|
DblMatrix |
InitialCondition.getDefaultValue()
Get the default value.
|
DblMatrix |
BoundsCoefInterface.getDefaultValue()
Get the default value.
|
DblMatrix |
InitialConditionInterface.getDefaultValue()
Get the default value.
|
DblMatrix |
StrangStage.getFractionalStep()
Returns the fraction of a time step for which this stage's solver
should be run.
|
DblMatrix |
NDGrid.getMinStep()
Return the minimum step over all dimensions.
|
DblMatrix |
AbstractDiffuse.getParam(java.lang.String name) |
DblMatrix |
BVP.getParam(java.lang.String name) |
DblMatrix |
Diffuse.getParam(java.lang.String name) |
DblMatrix |
StrangSplitter.getParam(java.lang.String name) |
DblMatrix |
AbstractBoundaryValueProblem.getParam(java.lang.String name) |
DblMatrix |
CrankNicholson.getRHSA() |
DblMatrix |
CrankNicholson.getRHSB() |
DblMatrix |
PartialDifferentialEquation.getSolution() |
DblMatrix |
AbstractDiffuse.getSolution()
Returns the solution matrix after solving over the time interval.
|
DblMatrix |
StrangStage.getSolution() |
DblMatrix |
BVP.getSolution() |
DblMatrix |
Diffuse.getSolution() |
DblMatrix |
StrangSplitter.getSolution() |
DblMatrix |
AbstractBoundaryValueProblem.getSolution() |
DblMatrix |
NDGrid.getSpatialStepAt(int index,
int dimension,
double perturb1,
double perturb2)
Gets the spatial step in dimension dim over index I as calculated as the difference in spatial
locations X(d,I+p1)-X(d,I+p2).
|
DblMatrix |
NDGrid.getSpatialStepAt(int index,
int dimension,
int perturb1,
int perturb2)
Gets the spatial step in dimension dim over index I as calculated as the sum across
the two spatial steps h(d,I+p1)+h(d,I+p2).
|
DblMatrix |
FractionalStep.getStep() |
DblMatrix |
StrangSplitter.getStep()
Get the current time step.
|
DblMatrix |
AbstractDiffuse.getTime() |
DblMatrix |
PdeReportInstance.getTime() |
DblMatrix |
StrangStage.getTime()
Returns the fraction of a time step for which this stage's solver
should be run.
|
DblMatrix |
FractionalStep.getTime() |
DblMatrix |
StrangSplitter.getTime() |
DblMatrix |
AbstractBoundaryValueProblem.getTime() |
DblMatrix |
AbstractBoundaryValueProblem.getTimeStep() |
DblMatrix |
StrangSplitter.getTstart() |
DblMatrix |
StrangSplitter.getTstop() |
DblMatrix |
PdeReportInstance.getU() |
DblMatrix[] |
NDGrid.getUCoords(int I,
int ghostpts)
Gets spatial grid points corresponding to the values in U but adjusting for presence of ghost points.
|
DblMatrix[] |
NDGrid.getUCoords(Subscript[] coords_in,
int ghostpts)
Gets spatial grid points corresponding to the values in U but adjusting for presence of ghost points.
|
DblMatrix |
NDGrid.getUSpatialStepAt(int index,
int dimension,
double perturb1,
double perturb2,
int ghostpts) |
DblMatrix |
NDGrid.getUSpatialStepAt(int index,
int dimension,
int perturb1,
int perturb2,
int ghostpts) |
abstract DblMatrix |
AbstractBoundaryCondition.getValueAt(DblMatrix[] x) |
abstract DblMatrix |
AbstractDiffusionCoefficient.getValueAt(DblMatrix[] X) |
DblMatrix |
PDECoefficient.getValueAt(DblMatrix[] x) |
DblMatrix |
DiffusionCoefficient.getValueAt(DblMatrix[] X) |
DblMatrix |
NeummanCondition.getValueAt(DblMatrix[] x) |
DblMatrix |
DefaultDiffusionCoefficient.getValueAt(DblMatrix[] x) |
DblMatrix |
BoundaryValueCondition.getValueAt(DblMatrix[] x) |
DblMatrix |
DefaultBoundaryCondition.getValueAt(DblMatrix[] x) |
DblMatrix |
BoundaryCondition.getValueAt(DblMatrix[] X) |
DblMatrix |
BoundaryCoefficient.getValueAt(DblMatrix[] x) |
DblMatrix |
DirichletCondition.getValueAt(DblMatrix[] x) |
abstract DblMatrix |
AbstractBoundaryCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
abstract DblMatrix |
AbstractDiffusionCoefficient.getValueAt(DblMatrix[] X,
DblMatrix T) |
DblMatrix |
PDECoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DiffusionCoefficient.getValueAt(DblMatrix[] X,
DblMatrix T) |
DblMatrix |
NeummanCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DefaultDiffusionCoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
BoundaryValueCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DefaultBoundaryCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
BoundaryCondition.getValueAt(DblMatrix[] X,
DblMatrix T) |
DblMatrix |
BoundaryCoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DirichletCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
Modifier and Type | Method and Description |
---|---|
void |
StrangSplitter.add(FractionalStep s,
DblMatrix fractional)
Add a StrangStage to the end of the queue.
|
void |
StrangSplitter.add(FractionalStep s,
DblMatrix fractional,
int j)
Insert a StrangStage at the jth position in the queue.
|
DblMatrix |
AbstractInitialCondition.getCoef(DblMatrix X)
Set the initial condition value.
|
DblMatrix |
InitialCondition.getCoef(DblMatrix X)
Get the values of the initial condition at the points in X.
|
DblMatrix |
BoundsCoefInterface.getCoef(DblMatrix X)
Get the values of the bounds coefficient at the points in X.
|
DblMatrix |
InitialConditionInterface.getCoef(DblMatrix X)
Get the values of the initial condition at the points in X.
|
DblMatrix |
AbstractDiffusionCoef.getCoef(DblMatrix X,
DblMatrix T)
Set the diffusion coefficient value.
|
DblMatrix |
DiffusionCoefInterface.getCoef(DblMatrix X,
DblMatrix T)
Get the values of the diffusion coefficient at the points in X.
|
abstract DblMatrix |
AbstractBoundaryCondition.getValueAt(DblMatrix[] x) |
abstract DblMatrix |
AbstractDiffusionCoefficient.getValueAt(DblMatrix[] X) |
DblMatrix |
PDECoefficient.getValueAt(DblMatrix[] x) |
DblMatrix |
DiffusionCoefficient.getValueAt(DblMatrix[] X) |
DblMatrix |
NeummanCondition.getValueAt(DblMatrix[] x) |
DblMatrix |
DefaultDiffusionCoefficient.getValueAt(DblMatrix[] x) |
DblMatrix |
BoundaryValueCondition.getValueAt(DblMatrix[] x) |
DblMatrix |
DefaultBoundaryCondition.getValueAt(DblMatrix[] x) |
DblMatrix |
BoundaryCondition.getValueAt(DblMatrix[] X) |
DblMatrix |
BoundaryCoefficient.getValueAt(DblMatrix[] x) |
DblMatrix |
DirichletCondition.getValueAt(DblMatrix[] x) |
abstract DblMatrix |
AbstractBoundaryCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
abstract DblMatrix |
AbstractBoundaryCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
abstract DblMatrix |
AbstractDiffusionCoefficient.getValueAt(DblMatrix[] X,
DblMatrix T) |
abstract DblMatrix |
AbstractDiffusionCoefficient.getValueAt(DblMatrix[] X,
DblMatrix T) |
DblMatrix |
PDECoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
PDECoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DiffusionCoefficient.getValueAt(DblMatrix[] X,
DblMatrix T) |
DblMatrix |
DiffusionCoefficient.getValueAt(DblMatrix[] X,
DblMatrix T) |
DblMatrix |
NeummanCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
NeummanCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DefaultDiffusionCoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DefaultDiffusionCoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
BoundaryValueCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
BoundaryValueCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DefaultBoundaryCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DefaultBoundaryCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
BoundaryCondition.getValueAt(DblMatrix[] X,
DblMatrix T) |
DblMatrix |
BoundaryCondition.getValueAt(DblMatrix[] X,
DblMatrix T) |
DblMatrix |
BoundaryCoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
BoundaryCoefficient.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DirichletCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
DblMatrix |
DirichletCondition.getValueAt(DblMatrix[] x,
DblMatrix time) |
void |
AbstractInitialCondition.setDefaultValue(DblMatrix N)
Set the default value.
|
void |
AbstractDiffusionCoef.setDefaultValue(DblMatrix N)
Set the default value.
|
void |
DiffusionCoefInterface.setDefaultValue(DblMatrix N)
Set the default value.
|
void |
InitialCondition.setDefaultValue(DblMatrix N)
Set the default value.
|
void |
BoundsCoefInterface.setDefaultValue(DblMatrix N)
Set the default value.
|
void |
InitialConditionInterface.setDefaultValue(DblMatrix N)
Set the default value.
|
void |
StrangStage.setFractionalStep(DblMatrix fdt)
Sets the fraction of a time step for which this stage's solver
should be run.
|
void |
StrangStage.setInitialCondition(DblMatrix c) |
void |
FractionalStep.setInitialCondition(DblMatrix u) |
void |
StrangSplitter.setInitialCondition(DblMatrix uu) |
void |
AbstractDiffuse.setParam(java.lang.String name,
DblMatrix value) |
void |
BVP.setParam(java.lang.String name,
DblMatrix value) |
void |
Diffuse.setParam(java.lang.String name,
DblMatrix value) |
void |
StrangSplitter.setParam(java.lang.String name,
DblMatrix value) |
void |
AbstractBoundaryValueProblem.setParam(java.lang.String name,
DblMatrix value) |
void |
StrangStage.setStartTime(DblMatrix time) |
void |
StrangStage.setStep(DblMatrix dt) |
void |
FractionalStep.setStep(DblMatrix dt) |
void |
StrangSplitter.setStep(DblMatrix t)
Set the time step.
|
void |
AbstractDiffuse.setTime(DblMatrix t) |
void |
FractionalStep.setTime(DblMatrix dt) |
void |
StrangSplitter.setTime(DblMatrix t) |
void |
AbstractBoundaryValueProblem.setTime(DblMatrix t) |
void |
AbstractBoundaryValueProblem.setTimeStep(DblMatrix dt) |
void |
StrangSplitter.setTstart(DblMatrix t) |
void |
StrangSplitter.setTstop(DblMatrix t) |
Constructor and Description |
---|
AbstractDiffusionCoef(DblMatrix N) |
AbstractInitialCondition(DblMatrix N) |
Diffuse(NDGrid Grid,
DblMatrix Tstart,
DblMatrix Tstop)
Instantiate a diffusion object by giving a grid and a starting and stopping time.
|
NDGrid(DblMatrix Xgrid)
Construct a 1D grid using the given points as coordinate vector.
|
NDGrid(DblMatrix X,
DblMatrix Y)
Construct a 2D grid using the given points as coordinate vector.
|
NDGrid(DblMatrix X,
DblMatrix Y,
DblMatrix Z)
Construct a 3D grid using the given points as coordinate vector.
|
NDGrid(DblMatrix L,
DblMatrix U,
int N)
Creates Cartesean grid with N points in each dimension.
|
NDGrid(DblMatrix L,
DblMatrix U,
int[] N)
Creates Cartesean grid with N[d] points in dimension d.
|
PdeReportInstance(NDGrid g,
DblMatrix u,
DblMatrix t) |
StrangStage(FractionalStep s,
DblMatrix fdt)
Constructs a Strang splitting stage using fractional step solver
s and fractional time step fdt.
|
Modifier and Type | Method and Description |
---|---|
DblMatrix |
DefaultSpreadsheetPanel.getDblMatrixFor(java.lang.String range) |
DblMatrix |
MyrtleSheetAPI.getDblMatrixFor(java.lang.String str)
Extracts a range of sheet cells' values interpreted as double's.
|
DblMatrix |
DefaultSpreadsheetPanel.getDblMatrixForBookmark(java.lang.String mark) |
DblMatrix |
MyrtleSheetAPI.getDblMatrixForBookmark(java.lang.String range)
Extracts a range of sheet cells' values interpreted as double's.
|
DblMatrix |
DefaultSpreadsheetPanel.getDblMatrixForRange(java.lang.String range) |
DblMatrix |
MyrtleSheetAPI.getDblMatrixForRange(java.lang.String range)
Extracts a range of sheet cells' values interpreted as double's.
|
DblMatrix |
SpreadsheetEntryMatrix.getValuesAsDblMatrix() |
static DblMatrix |
SpreadsheetEntryMatrix.isNaN(SpreadsheetEntryMatrix X)
Boolean isNaN
|
DblMatrix |
DefaultSpreadsheetPanel.parseDblMatrix(java.lang.Object arg0) |
static DblMatrix |
AbstractReservedFunction.parseDblMatrix(java.lang.Object arg0,
DefaultSpreadsheetPanel p) |
Modifier and Type | Method and Description |
---|---|
static java.lang.String[][] |
SpreadsheetEntryMatrix.getValuesAsStringMatrix(DblMatrix x) |
void |
DefaultSpreadsheetPanel.pasteDblMatrixAt(DblMatrix X,
int startrow,
int startcol) |
void |
DefaultSpreadsheetTable.pasteDblMatrixAt(DblMatrix X,
int startrow,
int startcol) |
void |
DefaultSpreadsheetPanel.pasteDblMatrixAt(DefaultSpreadsheetTable tabl,
DblMatrix X,
int startrow,
int startcol) |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
FCDF.cdf(DblMatrix X) |
abstract DblMatrix |
ProbabilityDensity.cdf(DblMatrix X) |
DblMatrix |
TDistribution.cdf(DblMatrix xx)
CDF of the T distribution.
|
DblMatrix |
NormalDistribution.cdf(DblMatrix xx)
CDF of the Normal distribution.
|
DblMatrix |
BernoulliDistribution.cdf(DblMatrix X) |
DblMatrix |
UniformDistribution.cdf(DblMatrix xx)
CDF of the Normal distribution.
|
DblMatrix |
DiscreteUniformDistribution.cdf(DblMatrix xx)
CDF of the Normal distribution.
|
DblMatrix |
GammaDistribution.cdf(DblMatrix xx)
CDF of the Normal distribution.
|
DblMatrix |
BinomialDistribution.cdf(DblMatrix X) |
DblMatrix |
FDistribution.cdf(DblMatrix F)
CDF of the F distribution.
|
DblMatrix |
ChiSqDistribution.cdf(DblMatrix xx)
Returns the CDF of the Chi-Squared distribution.
|
DblMatrix |
HypergeometricDistribution.cdf(DblMatrix xx)
CDF of the Hypergeometric distribution.
|
DblMatrix |
CDF.cdf(DblMatrix X) |
DblMatrix |
PoissonDistribution.cdf(DblMatrix X) |
DblMatrix |
NormalDistribution.cdf(double xx) |
DblMatrix |
NormalDistribution.cdf(java.lang.Double xx) |
DblMatrix |
ChiSqDistribution.cdf(java.lang.Double x)
Returns the CDF of the Chi-Squared distribution.
|
DblMatrix |
ChiSqDistribution.cdf(int x)
Returns the CDF of the Chi-Squared distribution.
|
DblMatrix |
HypergeometricDistribution.cdf(int xx)
CDF of the Hypergeometric distribution.
|
abstract DblMatrix |
ProbabilityDensity.criticalValue(DblMatrix Pvalue) |
DblMatrix |
TDistribution.criticalValue(DblMatrix cdfval)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
NormalDistribution.criticalValue(DblMatrix p)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
BernoulliDistribution.criticalValue(DblMatrix cdfvals) |
DblMatrix |
UniformDistribution.criticalValue(DblMatrix p)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
DiscreteUniformDistribution.criticalValue(DblMatrix p)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
GammaDistribution.criticalValue(DblMatrix cdfvals)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
BinomialDistribution.criticalValue(DblMatrix cdfval) |
DblMatrix |
FDistribution.criticalValue(DblMatrix cdfvals)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
ChiSqDistribution.criticalValue(DblMatrix cdfval)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
HypergeometricDistribution.criticalValue(DblMatrix cdfval)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
InvCDF.criticalValue(DblMatrix Pvalue) |
DblMatrix |
PoissonDistribution.criticalValue(DblMatrix cdfval) |
DblMatrix |
NormalDistribution.criticalValue(double xx) |
DblMatrix |
NormalDistribution.criticalValue(java.lang.Double xx) |
DblMatrix |
ProbabilityDensity.getAssumedProbability() |
DblMatrix |
ProbabilityDensity.getParam(java.lang.String name) |
DblMatrix |
FCDF.getPredictionAt(DblMatrix[] X) |
DblMatrix |
NormPDF.getPredictionAt(DblMatrix[] X) |
DblMatrix |
FCDF.getValueAt(DblMatrix F) |
DblMatrix |
ProbabilityDensity.getValueAt(DblMatrix X) |
DblMatrix |
NormPDF.getValueAt(DblMatrix X) |
DblMatrix |
ECDF.getValueAt(DblMatrix x) |
DblMatrix |
FCDF.getValueToMinimize()
Returns the CDF at the current X value for the current parameter settings.
|
DblMatrix |
ProbabilityDensity.getValueToMinimize() |
DblMatrix |
FCDF.getVariable() |
DblMatrix |
TDistribution.getVariable() |
DblMatrix |
NormalDistribution.getVariable() |
DblMatrix |
UniformDistribution.getVariable() |
DblMatrix |
GammaDistribution.getVariable() |
DblMatrix |
FDistribution.getVariable() |
DblMatrix |
ChiSqDistribution.getVariable() |
DblMatrix |
HypergeometricDistribution.getVariable() |
DblMatrix |
ProbabilityDensity.getVariableValue() |
abstract DblMatrix |
ProbabilityDensity.hasSupport(DblMatrix X)
Returns 1 if the density has the input value in its support set (domain)
and 0 otherwise.
|
DblMatrix |
TDistribution.hasSupport(DblMatrix X) |
DblMatrix |
NormalDistribution.hasSupport(DblMatrix X) |
DblMatrix |
BernoulliDistribution.hasSupport(DblMatrix X) |
DblMatrix |
UniformDistribution.hasSupport(DblMatrix X) |
DblMatrix |
DiscreteUniformDistribution.hasSupport(DblMatrix X) |
DblMatrix |
GammaDistribution.hasSupport(DblMatrix X) |
DblMatrix |
BinomialDistribution.hasSupport(DblMatrix X) |
DblMatrix |
FDistribution.hasSupport(DblMatrix X) |
DblMatrix |
ChiSqDistribution.hasSupport(DblMatrix X) |
DblMatrix |
HypergeometricDistribution.hasSupport(DblMatrix X) |
DblMatrix |
PoissonDistribution.hasSupport(DblMatrix X) |
DblMatrix |
TDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
NormalDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
BernoulliDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
UniformDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
DiscreteUniformDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
GammaDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
FDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
ChiSqDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
HypergeometricDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
PoissonDistribution.mean()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
TDistribution.median()
Returns the median of the distribution for the currently configured parameters.
|
DblMatrix |
BernoulliDistribution.median()
Returns the median of the distribution for the currently configured parameters.
|
DblMatrix |
DiscreteUniformDistribution.median()
Returns the median of the distribution for the currently configured parameters.
|
DblMatrix |
GammaDistribution.median()
Returns the median the distribution for the currently configured parameters.
|
DblMatrix |
PoissonDistribution.median()
Returns the median of the distribution for the currently configured parameters.
|
DblMatrix |
TDistribution.mode()
Returns the mode of the distribution for the currently configured parameters.
|
DblMatrix |
BernoulliDistribution.mode()
Returns the median of the distribution for the currently configured parameters.
|
DblMatrix |
DiscreteUniformDistribution.mode()
Returns the mode of the distribution for the currently configured parameters.
|
DblMatrix |
GammaDistribution.mode()
Returns the mode the distribution for the currently configured parameters.
|
DblMatrix |
FDistribution.mode()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
ChiSqDistribution.mode()
Returns the mode of the distribution for the currently configured parameters.
|
DblMatrix |
HypergeometricDistribution.mode()
Returns the mode of the distribution for the currently configured parameters.
|
DblMatrix |
PoissonDistribution.mode()
Returns the mode of the distribution for the currently configured parameters.
|
abstract DblMatrix |
ProbabilityDensity.pdf(DblMatrix X) |
DblMatrix |
TDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
NormalDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
BernoulliDistribution.pdf(DblMatrix X) |
DblMatrix |
UniformDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
DiscreteUniformDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
GammaDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
BinomialDistribution.pdf(DblMatrix X) |
DblMatrix |
FDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
ChiSqDistribution.pdf(DblMatrix x)
Returns the value of the density function at X.
|
DblMatrix |
HypergeometricDistribution.pdf(DblMatrix R)
Returns the value of the density function at X.
|
DblMatrix |
PoissonDistribution.pdf(DblMatrix X) |
DblMatrix |
NormalDistribution.pdf(double xx) |
DblMatrix |
NormalDistribution.pdf(java.lang.Double xx) |
DblMatrix |
ChiSqDistribution.pdf(java.lang.Double x)
Returns the PDF of the Chi-Squared distribution.
|
DblMatrix |
ChiSqDistribution.pdf(int x)
Returns the PDF of the Chi-Squared distribution.
|
DblMatrix |
HypergeometricDistribution.pdf(int r)
Returns the value of the density function at X.
|
DblMatrix |
ProbabilityDensity.random(int N)
Return N random draws from this distribution.
|
DblMatrix |
TDistribution.random(int N)
Return N random draws from this distribution.
|
DblMatrix |
NormalDistribution.random(int N)
Return N random draws from this distribution.
|
DblMatrix |
BernoulliDistribution.random(int nn) |
DblMatrix |
UniformDistribution.random(int N)
Return N random draws from this distribution.
|
DblMatrix |
DiscreteUniformDistribution.random(int n)
Return N random draws from this distribution.
|
DblMatrix |
GammaDistribution.random(int N)
Return N random draws from this distribution.
|
DblMatrix |
BinomialDistribution.random(int nn) |
DblMatrix |
FDistribution.random(int N)
Return N random draws from this distribution.
|
DblMatrix |
ChiSqDistribution.random(int N)
Return N random draws from this distribution.
|
DblMatrix |
HypergeometricDistribution.random(int n)
Return N random draws from this distribution.
|
DblMatrix |
PoissonDistribution.random(int nn) |
DblMatrix |
UniformDistribution.random(int[] N)
Return matrix of the given size containing random draws from this distribution.
|
DblMatrix |
TDistribution.variance()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
NormalDistribution.variance()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
BernoulliDistribution.variance()
Returns the variance of the distribution for the currently configured parameters.
|
DblMatrix |
UniformDistribution.variance()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
DiscreteUniformDistribution.variance()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
GammaDistribution.variance()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
FDistribution.variance()
Returns the variance of the distribution for the currently configured parameters.
|
DblMatrix |
ChiSqDistribution.variance()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
HypergeometricDistribution.variance()
Returns the expected value of the distribution for the currently configured parameters.
|
DblMatrix |
PoissonDistribution.variance()
Returns the variance of the distribution for the currently configured parameters.
|
Modifier and Type | Method and Description |
---|---|
void |
ProbabilityDensity.assumeProbability(DblMatrix a) |
DblMatrix |
FCDF.cdf(DblMatrix X) |
abstract DblMatrix |
ProbabilityDensity.cdf(DblMatrix X) |
DblMatrix |
TDistribution.cdf(DblMatrix xx)
CDF of the T distribution.
|
DblMatrix |
NormalDistribution.cdf(DblMatrix xx)
CDF of the Normal distribution.
|
DblMatrix |
BernoulliDistribution.cdf(DblMatrix X) |
DblMatrix |
UniformDistribution.cdf(DblMatrix xx)
CDF of the Normal distribution.
|
DblMatrix |
DiscreteUniformDistribution.cdf(DblMatrix xx)
CDF of the Normal distribution.
|
DblMatrix |
GammaDistribution.cdf(DblMatrix xx)
CDF of the Normal distribution.
|
DblMatrix |
BinomialDistribution.cdf(DblMatrix X) |
DblMatrix |
FDistribution.cdf(DblMatrix F)
CDF of the F distribution.
|
DblMatrix |
ChiSqDistribution.cdf(DblMatrix xx)
Returns the CDF of the Chi-Squared distribution.
|
DblMatrix |
HypergeometricDistribution.cdf(DblMatrix xx)
CDF of the Hypergeometric distribution.
|
DblMatrix |
CDF.cdf(DblMatrix X) |
DblMatrix |
PoissonDistribution.cdf(DblMatrix X) |
abstract DblMatrix |
ProbabilityDensity.criticalValue(DblMatrix Pvalue) |
DblMatrix |
TDistribution.criticalValue(DblMatrix cdfval)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
NormalDistribution.criticalValue(DblMatrix p)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
BernoulliDistribution.criticalValue(DblMatrix cdfvals) |
DblMatrix |
UniformDistribution.criticalValue(DblMatrix p)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
DiscreteUniformDistribution.criticalValue(DblMatrix p)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
GammaDistribution.criticalValue(DblMatrix cdfvals)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
BinomialDistribution.criticalValue(DblMatrix cdfval) |
DblMatrix |
FDistribution.criticalValue(DblMatrix cdfvals)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
ChiSqDistribution.criticalValue(DblMatrix cdfval)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
HypergeometricDistribution.criticalValue(DblMatrix cdfval)
For an input value C returns x such that P(X<=x) = C.
|
DblMatrix |
InvCDF.criticalValue(DblMatrix Pvalue) |
DblMatrix |
PoissonDistribution.criticalValue(DblMatrix cdfval) |
DblMatrix |
FCDF.getPredictionAt(DblMatrix[] X) |
DblMatrix |
NormPDF.getPredictionAt(DblMatrix[] X) |
DblMatrix |
FCDF.getValueAt(DblMatrix F) |
DblMatrix |
ProbabilityDensity.getValueAt(DblMatrix X) |
DblMatrix |
NormPDF.getValueAt(DblMatrix X) |
DblMatrix |
ECDF.getValueAt(DblMatrix x) |
abstract DblMatrix |
ProbabilityDensity.hasSupport(DblMatrix X)
Returns 1 if the density has the input value in its support set (domain)
and 0 otherwise.
|
DblMatrix |
TDistribution.hasSupport(DblMatrix X) |
DblMatrix |
NormalDistribution.hasSupport(DblMatrix X) |
DblMatrix |
BernoulliDistribution.hasSupport(DblMatrix X) |
DblMatrix |
UniformDistribution.hasSupport(DblMatrix X) |
DblMatrix |
DiscreteUniformDistribution.hasSupport(DblMatrix X) |
DblMatrix |
GammaDistribution.hasSupport(DblMatrix X) |
DblMatrix |
BinomialDistribution.hasSupport(DblMatrix X) |
DblMatrix |
FDistribution.hasSupport(DblMatrix X) |
DblMatrix |
ChiSqDistribution.hasSupport(DblMatrix X) |
DblMatrix |
HypergeometricDistribution.hasSupport(DblMatrix X) |
DblMatrix |
PoissonDistribution.hasSupport(DblMatrix X) |
abstract DblMatrix |
ProbabilityDensity.pdf(DblMatrix X) |
DblMatrix |
TDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
NormalDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
BernoulliDistribution.pdf(DblMatrix X) |
DblMatrix |
UniformDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
DiscreteUniformDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
GammaDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
BinomialDistribution.pdf(DblMatrix X) |
DblMatrix |
FDistribution.pdf(DblMatrix X)
Returns the value of the density function at X.
|
DblMatrix |
ChiSqDistribution.pdf(DblMatrix x)
Returns the value of the density function at X.
|
DblMatrix |
HypergeometricDistribution.pdf(DblMatrix R)
Returns the value of the density function at X.
|
DblMatrix |
PoissonDistribution.pdf(DblMatrix X) |
void |
GammaDistribution.setAlpha(DblMatrix u) |
void |
GammaDistribution.setBeta(DblMatrix beta) |
void |
FDistribution.setDDF(DblMatrix m) |
void |
TDistribution.setDF(DblMatrix m) |
void |
ChiSqDistribution.setDF(DblMatrix m) |
void |
UniformDistribution.setHigh(DblMatrix b) |
void |
PoissonDistribution.setLambda(DblMatrix m) |
void |
UniformDistribution.setLow(DblMatrix a) |
void |
HypergeometricDistribution.setM(DblMatrix m) |
void |
NormalDistribution.setMean(DblMatrix u) |
void |
DiscreteUniformDistribution.setN(DblMatrix a) |
void |
BinomialDistribution.setN(DblMatrix m) |
void |
HypergeometricDistribution.setN(DblMatrix m) |
void |
FDistribution.setNDF(DblMatrix m) |
void |
BernoulliDistribution.setP(DblMatrix m) |
void |
BinomialDistribution.setP(DblMatrix m) |
void |
ProbabilityDensity.setParam(java.lang.String name,
DblMatrix value) |
void |
HypergeometricDistribution.setS(DblMatrix m) |
void |
NormalDistribution.setStd(DblMatrix sig) |
void |
FCDF.setVariable(DblMatrix ff) |
void |
TDistribution.setVariable(DblMatrix ff) |
void |
NormalDistribution.setVariable(DblMatrix ff) |
void |
UniformDistribution.setVariable(DblMatrix ff) |
void |
GammaDistribution.setVariable(DblMatrix ff) |
void |
FDistribution.setVariable(DblMatrix ff) |
void |
ChiSqDistribution.setVariable(DblMatrix ff) |
void |
HypergeometricDistribution.setVariable(DblMatrix ff) |
void |
ProbabilityDensity.setVariableValue(DblMatrix X) |
void |
NormalDistribution.setVariance(DblMatrix sigsq) |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
Constant.getParam(java.lang.String name) |
DblMatrix |
HollingI.getParam(java.lang.String name) |
DblMatrix |
Quadratic.getParam(java.lang.String name) |
DblMatrix |
Cubic.getParam(java.lang.String name) |
DblMatrix |
HollingIII.getParam(java.lang.String name) |
DblMatrix |
HollingII.getParam(java.lang.String name) |
DblMatrix |
Constant.getPredictionAt(DblMatrix[] X) |
DblMatrix |
HollingI.getPredictionAt(DblMatrix[] X) |
DblMatrix |
Quadratic.getPredictionAt(DblMatrix[] X) |
DblMatrix |
Linear.getPredictionAt(DblMatrix[] X) |
DblMatrix |
Cubic.getPredictionAt(DblMatrix[] X) |
DblMatrix |
HollingIII.getPredictionAt(DblMatrix[] X) |
DblMatrix |
HollingII.getPredictionAt(DblMatrix[] X) |
DblMatrix |
MichaelisMenten.getPredictionAt(DblMatrix[] X) |
DblMatrix |
Constant.getValueAt(DblMatrix X) |
DblMatrix |
HollingI.getValueAt(DblMatrix X) |
DblMatrix |
Quadratic.getValueAt(DblMatrix X) |
DblMatrix |
Cubic.getValueAt(DblMatrix X) |
DblMatrix |
HollingIII.getValueAt(DblMatrix X) |
DblMatrix |
HollingII.getValueAt(DblMatrix X) |
DblMatrix |
MichaelisMenten.negLogLikelihood()
Provides negative log likelihood for Michaelis-Menten using the assumption of
i.i.d Gaussian errors.
|
DblMatrix |
Linear.residuals() |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
Constant.getPredictionAt(DblMatrix[] X) |
DblMatrix |
HollingI.getPredictionAt(DblMatrix[] X) |
DblMatrix |
Quadratic.getPredictionAt(DblMatrix[] X) |
DblMatrix |
Linear.getPredictionAt(DblMatrix[] X) |
DblMatrix |
Cubic.getPredictionAt(DblMatrix[] X) |
DblMatrix |
HollingIII.getPredictionAt(DblMatrix[] X) |
DblMatrix |
HollingII.getPredictionAt(DblMatrix[] X) |
DblMatrix |
MichaelisMenten.getPredictionAt(DblMatrix[] X) |
DblMatrix |
Constant.getValueAt(DblMatrix X) |
DblMatrix |
HollingI.getValueAt(DblMatrix X) |
DblMatrix |
Quadratic.getValueAt(DblMatrix X) |
DblMatrix |
Cubic.getValueAt(DblMatrix X) |
DblMatrix |
HollingIII.getValueAt(DblMatrix X) |
DblMatrix |
HollingII.getValueAt(DblMatrix X) |
void |
Constant.setParam(java.lang.String name,
DblMatrix value) |
void |
HollingI.setParam(java.lang.String name,
DblMatrix value) |
void |
Quadratic.setParam(java.lang.String name,
DblMatrix value) |
void |
Cubic.setParam(java.lang.String name,
DblMatrix value) |
void |
HollingIII.setParam(java.lang.String name,
DblMatrix value) |
void |
HollingII.setParam(java.lang.String name,
DblMatrix value) |
Constructor and Description |
---|
Constant(DblMatrix a) |
Linear(DblMatrix a,
DblMatrix b) |
Modifier and Type | Field and Description |
---|---|
DblMatrix |
ForwardDifferenceMapping.A |
protected DblMatrix |
Pulse.Conc |
DblMatrix |
NNCalc.Distances |
DblMatrix |
QTreeNode.Extent |
protected DblMatrix |
BarElement.extents |
DblMatrix |
QTreeNode.Indices |
protected DblMatrix |
Qdecomp.LowerBounds |
protected DblMatrix |
QTreeNode.MaxExtent |
protected DblMatrix |
Qdecomp.MaxExtent |
protected DblMatrix |
QTreeNode.MinExtent |
protected DblMatrix |
Qdecomp.MinExtent |
DblMatrix |
NNCalc.NearestDistances |
DblMatrix[] |
NNCalc.NearestXData |
DblMatrix |
QTreeNode.Node |
protected DblMatrix |
BarElement.origin |
DblMatrix |
Nhood.SelectedStencil |
protected DblMatrix |
Nhood.Stencil |
DblMatrix |
Nhood.StencilValues |
DblMatrix |
NhoodSum.Sum |
protected DblMatrix |
QTreeNode.Threshold |
protected DblMatrix |
Qdecomp.Threshold |
protected DblMatrix |
Pulse.Toff |
protected DblMatrix |
Pulse.Ton |
protected DblMatrix |
Qdecomp.UpperBounds |
DblMatrix |
NhoodSum.X |
DblMatrix[] |
NNCalc.XData |
DblMatrix[] |
QTreeNode.XData |
DblMatrix |
QTreeNode.YData |
Modifier and Type | Method and Description |
---|---|
DblMatrix[] |
QTreeNode.alphacube()
Split via an "alphabetic" ordering of the bits from the series 0 to 2^this.Dimension.
|
static DblMatrix |
Sequence.altharmonic(int M)
Returns alternating harmonic sequence with nth term (-1)^(n+1)/n.
|
DblMatrix |
Lentz.convergent() |
DblMatrix |
Lentz.convergent(int n) |
DblMatrix |
ValueSimplex.dd(int pidx)
Returns the DeWall algorithm's "Delaunay distance" for the vertex whose index is specified.
|
DblMatrix |
RefSimplex.dd(java.lang.Integer pidx)
Returns the DeWall algorithm's "Delaunay distance" for the vertex whose index is specified.
|
DblMatrix |
Simplex.dd(java.lang.Integer pidx) |
DblMatrix |
Triangulation.DTFE()
Returns the Delaunay tessellation field estimator (DTFE).
|
abstract DblMatrix |
AbstractErfAlgorithm.erf(DblMatrix x) |
DblMatrix |
Erf.erf(DblMatrix X) |
DblMatrix |
IncGammaErfAlgorithm.erf(DblMatrix X) |
DblMatrix |
ErfAlgorithm.erf(DblMatrix x) |
abstract DblMatrix |
AbstractErfAlgorithm.erfc(DblMatrix x) |
DblMatrix |
Erf.erfc(DblMatrix x) |
DblMatrix |
IncGammaErfAlgorithm.erfc(DblMatrix x) |
DblMatrix |
ErfAlgorithm.erfc(DblMatrix x) |
DblMatrix |
IncGammaContFracFun.evenTermA(int j)
Return the jth even A term (i.e.
|
DblMatrix |
IncGammaContFracFun.evenTermB(int j)
Return the jth even B term (i.e.
|
static DblMatrix |
Sequence.fibonacci(DblMatrix n)
Returns the specified terms of the Fibonacci sequence.
|
static DblMatrix |
Sequence.fibonacci(int n)
Returns the nth term of the Fibonacci sequence.
|
static DblMatrix |
Sequence.fibonaccis(int n)
Returns the first n terms of the Fibonacci sequence.
|
static DblMatrix |
Gradient.full(DblMatrix[] H,
int order,
int symmetry_type) |
DblMatrix |
GammaAlgorithm.gamma(DblMatrix X) |
abstract DblMatrix |
AbstractGammaAlgorithm.gamma(DblMatrix Z) |
DblMatrix |
TothGammaAlgorithm.gamma(DblMatrix Z) |
DblMatrix |
Gamma.gamma(DblMatrix Z) |
DblMatrix |
ValueSimplex.get(int j) |
DblMatrix |
ForwardDifferenceMapping.getA()
Return the forward difference matrix.
|
abstract DblMatrix |
RadialGradientGridElementPainter.getCenter(GridElement elem) |
DblMatrix |
BarElement.getCentroid() |
DblMatrix |
RefSimplex.getCentroid() |
DblMatrix |
ValueSimplex.getCentroid() |
DblMatrix |
GridElement.getCentroid() |
DblMatrix |
RefSimplex.getCircumcenter() |
DblMatrix |
ValueSimplex.getCircumcenter() |
DblMatrix |
RefSimplex.getCircumradius() |
DblMatrix |
ValueSimplex.getCircumradius() |
DblMatrix |
BarElement.getCoords()
Returns the data coordinates as a matrix.
|
DblMatrix |
RefSimplex.getCoords()
Returns the data coordinates as a matrix.
|
DblMatrix |
GridElement.getCoords() |
abstract DblMatrix |
GradientGridElementPainter.getCoords1(GridElement elem) |
abstract DblMatrix |
GradientGridElementPainter.getCoords2(GridElement elem) |
DblMatrix |
BarElement.getCoordsOf(java.lang.Integer vert) |
DblMatrix |
RefSimplex.getCoordsOf(java.lang.Integer row)
Returns the data coordinates at the given index.
|
DblMatrix |
GridElement.getCoordsOf(java.lang.Integer idx) |
DblMatrix |
RefSimplex.getData() |
DblMatrix |
RadialGradientGridElementPainter.getFocus(GridElement elem)
This default convenience implementation returns null for the focus.
|
DblMatrix |
LinearGradientGridElementPainter.getFractions(GridElement elem)
This default convenience implementation returns a vector containing only 0.0f and 1.0f.
|
DblMatrix |
RadialGradientGridElementPainter.getFractions(GridElement elem)
This default convenience implementation returns a vector containing only 0.0f and 1.0f.
|
DblMatrix[] |
Gradient.getGradient() |
abstract DblMatrix |
TextureGridElementPainter.getHeight(GridElement elem) |
DblMatrix |
ZeroCross.getLocations() |
DblMatrix |
SeriesInvErfAlgorithm.getLogCk(int k) |
DblMatrix |
ZeroCross.getMagnitudes() |
DblMatrix |
MatrixBuilder.getMatrix() |
DblMatrix |
MatrixBuilder.getMaxVal() |
DblMatrix |
MatrixBuilder.getMinVal() |
abstract DblMatrix |
TextureGridElementPainter.getOrigin(GridElement elem) |
DblMatrix |
Erf.getParam(java.lang.String name) |
DblMatrix |
BarElement.getPerimeter() |
DblMatrix |
RefSimplex.getPerimeter()
Returns the perimeter (2D only) of this simplex.
|
DblMatrix |
GridElement.getPerimeter() |
DblMatrix |
Triangulation.getPerturbationSize() |
DblMatrix |
TothGammaAlgorithm.getPredictionAt(DblMatrix[] X) |
DblMatrix |
NRLogGammaAlgorithm.getPredictionAt(DblMatrix[] X) |
DblMatrix |
NRIncBetaAlgorithm.getPredictionAt(DblMatrix[] X) |
abstract DblMatrix |
RadialGradientGridElementPainter.getRadius(GridElement elem) |
DblMatrix |
Lentz.getResult() |
abstract DblMatrix |
LinearGradientGridElementPainter.getStart(GridElement elem) |
DblMatrix |
Nhood.getStencil()
Get the current stencil.
|
DblMatrix |
MatrixBuilder.getStepVal() |
abstract DblMatrix |
LinearGradientGridElementPainter.getStop(GridElement elem) |
DblMatrix |
NhoodSum.getSum() |
DblMatrix |
Lentz.getTol() |
DblMatrix |
Triangulation.getTolerance() |
DblMatrix |
RefSimplex.getTolerance() |
DblMatrix |
Triangulation.getTriangulation() |
DblMatrix |
Triangulation.VertexTracker.getValue() |
DblMatrix |
AbstractIncBetaAlgorithm.getValueAt(DblMatrix Z) |
DblMatrix |
AbstractGammaAlgorithm.getValueAt(DblMatrix Z) |
DblMatrix |
Gamma.getValueAt(DblMatrix Z) |
DblMatrix |
Erf.getValueAt(DblMatrix Y) |
DblMatrix |
Pulse.getValueAt(DblMatrix tnow) |
DblMatrix |
IncBeta.getValueAt(DblMatrix Z) |
DblMatrix |
AbstractLogGammaAlgorithm.getValueAt(DblMatrix Z) |
DblMatrix |
LogGamma.getValueAt(DblMatrix Z) |
DblMatrix |
RefSimplex.IntersectObjective.getValueToMinimize() |
DblMatrix |
Erf.getValueToMinimize() |
DblMatrix |
BarElement.getVolume() |
DblMatrix |
RefSimplex.getVolume()
Returns the volume (area in 2D) of this simplex.
|
DblMatrix |
GridElement.getVolume() |
abstract DblMatrix |
TextureGridElementPainter.getWidth(GridElement elem) |
DblMatrix |
DoubleContFracFun.getX() |
static DblMatrix |
PseudoRandom.haltonSeq(int[] INDICES,
int NDIMS)
Returns a matrix representing NDIMS separate Halton sequences each having only the sequence
indices indicated.
|
static DblMatrix |
PseudoRandom.haltonSeq(int NUMPTS,
int NDIMS)
Returns a matrix representing NDIMS separate Halton sequences each having NUMPTS entries.
|
static DblMatrix |
PseudoRandom.haltonSeq(int NUMPTS,
int[] PRIMES)
Returns a matrix representing P.length separate Halton sequences each having NUMPTS entries.
|
static DblMatrix |
Sequence.harmonic(int M)
Returns harmonic sequence with nth term 1/n.
|
static DblMatrix |
Sequence.harmonic(int M,
double a,
double b)
Returns general harmonic sequence with nth term 1/(a*n+b).
|
DblMatrix |
Pulse.hv(DblMatrix x,
double sharpness)
Return smooth approximation to a Heaviside.
|
abstract DblMatrix |
AbstractIncBetaAlgorithm.incBeta(DblMatrix Z,
DblMatrix a,
DblMatrix b) |
DblMatrix |
NRIncBetaAlgorithm.incBeta(DblMatrix xx,
DblMatrix aa,
DblMatrix bb)
incBeta(X,a,b)
Calculates the incomplete beta algorithm for parameters a and b
at the point X.
|
DblMatrix |
IncBeta.incBeta(DblMatrix Z,
DblMatrix a,
DblMatrix b) |
DblMatrix |
IncBetaAlgorithm.incBeta(DblMatrix x,
DblMatrix a,
DblMatrix b) |
DblMatrix |
SeriesIncGamma.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.incGamma(DblMatrix x,
DblMatrix alpha) |
abstract DblMatrix |
AbstractIncGammaAlgorithm.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
InvErfAlgorithm.invErf(DblMatrix x) |
abstract DblMatrix |
AbstractInvErfAlgorithm.invErf(DblMatrix x) |
DblMatrix |
RootFinderInvErfAlgorithm.invErf(DblMatrix x) |
DblMatrix |
Erf.invErf(DblMatrix p) |
DblMatrix |
SeriesInvErfAlgorithm.invErf(DblMatrix X) |
DblMatrix |
AsymptoticInvErfAlgorithm.invErf(DblMatrix x) |
static DblMatrix |
Sequence.invfibonacci(DblMatrix x)
For given Fibonacci numbers returns their index n.
|
static DblMatrix |
Sequence.invfibonacci(int x)
For a given Fibonacci number returns the index n.
|
DblMatrix |
LogGammaAlgorithm.logGamma(DblMatrix X) |
DblMatrix |
NRLogGammaAlgorithm.logGamma(DblMatrix Z) |
abstract DblMatrix |
AbstractLogGammaAlgorithm.logGamma(DblMatrix Z) |
DblMatrix |
LogGamma.logGamma(DblMatrix Z) |
DblMatrix |
LogGamma.logGamma(double x) |
DblMatrix |
LogGamma.logGamma(int x) |
DblMatrix |
SeriesIncGamma.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
SeriesIncGamma.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
AbstractIncGammaAlgorithm.normIncGamma(DblMatrix x,
DblMatrix alpha)
Return the normalized incomplete gamma.
|
DblMatrix |
IncGamma.normIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
Triangulation.normOntoPlane(DblMatrix point,
DblMatrix pointOn,
int dim) |
static DblMatrix |
Sequence.primes(int M)
Returns sequence of the first n prime numbers.
|
static DblMatrix |
Sequence.pseq(int M,
double p)
Returns a p-sequence with the nth term 1/(n^p).
|
DblMatrix |
QuadTreeFun.quadEval(DblMatrix[] XData,
DblMatrix YData)
This method should take a Quad's XData and YData and return
a DblMatrix the same size as the YData.
|
static DblMatrix |
Triangulation.regionToTriangulation(java.util.Vector region) |
DblMatrix |
DoubleContFracFun.remainder(int j) |
DblMatrix |
Triangulation.SplittingPlane.sideOfWall(DblMatrix pt)
Returns a number whose absolute value is the distance of the point to the
wall and the sign indicates which "side" of the plane the point is on.
|
static DblMatrix[][] |
Qdecomp.solveBin(DblMatrix[] XData,
DblMatrix YData,
DblMatrix CenterOfQuad,
java.lang.String Method,
DblMatrix Indices)
Solve the binning problem for a newly formed quad.
|
DblMatrix |
IncGammaContFracFun.termA(int j) |
DblMatrix |
IncGammaContFracFun.termB(int j) |
DblMatrix |
SeriesIncGamma.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
SeriesIncGamma.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
VolumeGridElementMapping.valueFor(GridElement elem) |
DblMatrix |
GridElementMapping.valueFor(GridElement elem) |
DblMatrix |
PerimeterGridElementMapping.valueFor(GridElement elem) |
Modifier and Type | Method and Description |
---|---|
void |
ValueSimplex.add(DblMatrix vert) |
void |
ValueSimplex.add(int idx,
DblMatrix vert) |
void |
NhoodMapping.applyMapping(int home,
DblMatrix StencilCodes,
int[] indices)
Operates only on a vector of StencilCodes and an int[] of
indices where those StencilCoded functions should be implemented and
the index of the "home" node (usually the center node).
|
void |
NhoodSum.applyMapping(int index,
DblMatrix codes,
int[] indices) |
void |
ForwardDifferenceMapping.applyMapping(int index,
DblMatrix codes,
int[] indices)
Implement the NhoodMapping applyMapping interface.
|
static java.util.Vector |
Triangulation.circleRegion(DblMatrix center,
DblMatrix rad,
int Npts)
Produces a Delaunay triangulation of a circle in 2 dimensions.
|
abstract DblMatrix |
AbstractErfAlgorithm.erf(DblMatrix x) |
DblMatrix |
Erf.erf(DblMatrix X) |
DblMatrix |
IncGammaErfAlgorithm.erf(DblMatrix X) |
DblMatrix |
ErfAlgorithm.erf(DblMatrix x) |
abstract DblMatrix |
AbstractErfAlgorithm.erfc(DblMatrix x) |
DblMatrix |
Erf.erfc(DblMatrix x) |
DblMatrix |
IncGammaErfAlgorithm.erfc(DblMatrix x) |
DblMatrix |
ErfAlgorithm.erfc(DblMatrix x) |
static DblMatrix |
Sequence.fibonacci(DblMatrix n)
Returns the specified terms of the Fibonacci sequence.
|
static DblMatrix |
Gradient.full(DblMatrix[] H,
int order,
int symmetry_type) |
DblMatrix |
GammaAlgorithm.gamma(DblMatrix X) |
abstract DblMatrix |
AbstractGammaAlgorithm.gamma(DblMatrix Z) |
DblMatrix |
TothGammaAlgorithm.gamma(DblMatrix Z) |
DblMatrix |
Gamma.gamma(DblMatrix Z) |
DblSort |
NNCalc.getKNearest(DblMatrix[] refpt)
Get the K-nearest neighbors about the Ith coordinate.
|
DblMatrix |
TothGammaAlgorithm.getPredictionAt(DblMatrix[] X) |
DblMatrix |
NRLogGammaAlgorithm.getPredictionAt(DblMatrix[] X) |
DblMatrix |
NRIncBetaAlgorithm.getPredictionAt(DblMatrix[] X) |
DblMatrix |
AbstractIncBetaAlgorithm.getValueAt(DblMatrix Z) |
DblMatrix |
AbstractGammaAlgorithm.getValueAt(DblMatrix Z) |
DblMatrix |
Gamma.getValueAt(DblMatrix Z) |
DblMatrix |
Erf.getValueAt(DblMatrix Y) |
DblMatrix |
Pulse.getValueAt(DblMatrix tnow) |
DblMatrix |
IncBeta.getValueAt(DblMatrix Z) |
DblMatrix |
AbstractLogGammaAlgorithm.getValueAt(DblMatrix Z) |
DblMatrix |
LogGamma.getValueAt(DblMatrix Z) |
DblMatrix |
Pulse.hv(DblMatrix x,
double sharpness)
Return smooth approximation to a Heaviside.
|
abstract DblMatrix |
AbstractIncBetaAlgorithm.incBeta(DblMatrix Z,
DblMatrix a,
DblMatrix b) |
DblMatrix |
NRIncBetaAlgorithm.incBeta(DblMatrix xx,
DblMatrix aa,
DblMatrix bb)
incBeta(X,a,b)
Calculates the incomplete beta algorithm for parameters a and b
at the point X.
|
DblMatrix |
IncBeta.incBeta(DblMatrix Z,
DblMatrix a,
DblMatrix b) |
DblMatrix |
IncBetaAlgorithm.incBeta(DblMatrix x,
DblMatrix a,
DblMatrix b) |
DblMatrix |
SeriesIncGamma.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.incGamma(DblMatrix x,
DblMatrix alpha) |
abstract DblMatrix |
AbstractIncGammaAlgorithm.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.incGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
InvErfAlgorithm.invErf(DblMatrix x) |
abstract DblMatrix |
AbstractInvErfAlgorithm.invErf(DblMatrix x) |
DblMatrix |
RootFinderInvErfAlgorithm.invErf(DblMatrix x) |
DblMatrix |
Erf.invErf(DblMatrix p) |
DblMatrix |
SeriesInvErfAlgorithm.invErf(DblMatrix X) |
DblMatrix |
AsymptoticInvErfAlgorithm.invErf(DblMatrix x) |
static DblMatrix |
Sequence.invfibonacci(DblMatrix x)
For given Fibonacci numbers returns their index n.
|
boolean |
ValueSimplex.isInside(DblMatrix Po) |
int |
Qdecomp.locate(DblMatrix[] refpt)
Search the quadtree for a quad that contains the given coordinate.
|
DblMatrix |
LogGammaAlgorithm.logGamma(DblMatrix X) |
DblMatrix |
NRLogGammaAlgorithm.logGamma(DblMatrix Z) |
abstract DblMatrix |
AbstractLogGammaAlgorithm.logGamma(DblMatrix Z) |
DblMatrix |
LogGamma.logGamma(DblMatrix Z) |
DblMatrix |
SeriesIncGamma.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.lowerIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
SeriesIncGamma.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.lowerNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
AbstractIncGammaAlgorithm.normIncGamma(DblMatrix x,
DblMatrix alpha)
Return the normalized incomplete gamma.
|
DblMatrix |
IncGamma.normIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
Triangulation.normOntoPlane(DblMatrix point,
DblMatrix pointOn,
int dim) |
DblMatrix |
QuadTreeFun.quadEval(DblMatrix[] XData,
DblMatrix YData)
This method should take a Quad's XData and YData and return
a DblMatrix the same size as the YData.
|
DblMatrix |
QuadTreeFun.quadEval(DblMatrix[] XData,
DblMatrix YData)
This method should take a Quad's XData and YData and return
a DblMatrix the same size as the YData.
|
static java.util.Vector |
Triangulation.rectangleRegion(DblMatrix corner,
DblMatrix len,
int Npts)
Produces a Delaunay triangulation of a rectangular region.
|
void |
ValueSimplex.replace(int idx,
DblMatrix vert) |
int |
Qdecomp.rlocate(DblMatrix[] refpt,
int queryLevel,
int quadIndex)
Search the quadtree for a quad that contains the given coordinate.
|
void |
RefSimplex.setData(DblMatrix r) |
void |
Triangulation.VertexTracker.setDistance(DblMatrix d) |
void |
MatrixBuilder.setMatrix(DblMatrix X) |
void |
MatrixBuilder.setMaxVal(DblMatrix A) |
void |
MatrixBuilder.setMinVal(DblMatrix A) |
void |
Erf.setParam(java.lang.String name,
DblMatrix value) |
void |
Triangulation.setPerturbationSize(DblMatrix c) |
void |
Qdecomp.setQuadResponse(DblMatrix newYData,
int I)
Set the response data for the given quad.
|
void |
Nhood.setStencil(DblMatrix Stencil)
Users can specify there own neighborhood stencil.
|
void |
MatrixBuilder.setStepVal(DblMatrix A) |
void |
Lentz.setTol(DblMatrix e) |
void |
Triangulation.setTolerance(DblMatrix tol) |
void |
RefSimplex.setTolerance(DblMatrix tol) |
void |
DoubleContFracFun.setX(DblMatrix x) |
DblMatrix |
Triangulation.SplittingPlane.sideOfWall(DblMatrix pt)
Returns a number whose absolute value is the distance of the point to the
wall and the sign indicates which "side" of the plane the point is on.
|
static DblMatrix[][] |
Qdecomp.solveBin(DblMatrix[] XData,
DblMatrix YData,
DblMatrix CenterOfQuad,
java.lang.String Method,
DblMatrix Indices)
Solve the binning problem for a newly formed quad.
|
static DblMatrix[][] |
Qdecomp.solveBin(DblMatrix[] XData,
DblMatrix YData,
DblMatrix CenterOfQuad,
java.lang.String Method,
DblMatrix Indices)
Solve the binning problem for a newly formed quad.
|
static java.util.Vector |
Triangulation.sphereRegion(DblMatrix center,
DblMatrix rad,
int Npts)
Produces a Delaunay triangulation of a sphere (hypersphere) in N dimensions.
|
boolean |
RefSimplex.surroundsCoords(DblMatrix Po)
Returns true if the given coordinate is contained within this simplex.
|
boolean |
Simplex.surroundsCoords(DblMatrix Po) |
DblMatrix |
SeriesIncGamma.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.upperIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
SeriesIncGamma.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGammaAlgorithm.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
ContFracIncGamma.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
IncGamma.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
DblMatrix |
CompositeIncGammaAlgorithm.upperNormIncGamma(DblMatrix x,
DblMatrix alpha) |
Constructor and Description |
---|
BarChart(DblMatrix dataX,
DblMatrix heights) |
BarElement(DblMatrix orig,
DblMatrix exts) |
DoubleContFracFun(DblMatrix x) |
Gradient(DblMatrix Yin) |
Gradient(DblMatrix[] X,
DblMatrix Y) |
Gradient(DblMatrix[] X,
DblMatrix Y) |
Gradient(DblMatrix X,
DblMatrix Y) |
Gradient(StatisticalModel F,
DblMatrix[] Xin) |
IncBeta(DblMatrix a,
DblMatrix b) |
IncGammaContFracFun(DblMatrix X,
DblMatrix A) |
NhoodSum(DblMatrix xx)
Construct an NhoodMapping that will calculate the cardinal sums for a matrix X.
|
NNCalc(DblMatrix[] XData)
DblMatrix constructor.
|
Pulse(DblMatrix ton,
DblMatrix toff,
DblMatrix conc) |
Qdecomp(DblMatrix[] XData,
DblMatrix YData)
Default constructor.
|
Qdecomp(DblMatrix[] XData,
DblMatrix YData)
Default constructor.
|
RefSimplex(DblMatrix dat) |
RefSimplex(DblMatrix dat,
DblMatrix rowofidxs)
For a row vector of integer indices and corresponding reference data.
|
Triangulation(DblMatrix dat) |
ValueSimplex(DblMatrix X) |
ZeroCross(DblMatrix yy)
Use this construction when finding the zero-crossings in point-wise data.
|
Modifier and Type | Method and Description |
---|---|
DblMatrix |
GridElementTransferAgent.getCentroid() |
DblMatrix |
GridElementDOM.getCentroid() |
DblMatrix |
GridElementXML.getCentroid() |
DblMatrix |
GridElementTransferAgent.getCoords() |
DblMatrix |
GridElementDOM.getCoords() |
DblMatrix |
GridElementXML.getCoords() |
DblMatrix |
GridElementDOM.getCoordsOf(java.lang.Integer row) |
DblMatrix |
GridElementXML.getCoordsOf(java.lang.Integer row) |
protected static DblMatrix |
GridElementTransferAgent.getNextRow(java.io.StreamTokenizer STT) |
DblMatrix |
GridElementTransferAgent.getPerimeter()
Returns the perimeter (2D only) of this simplex.
|
DblMatrix |
GridElementDOM.getPerimeter()
Returns the perimeter (2D only) of this simplex.
|
DblMatrix |
GridElementXML.getPerimeter()
Returns the perimeter (2D only) of this simplex.
|
DblMatrix |
GridElementTransferAgent.getVolume()
Returns the volume (area in 2D) of this element.
|
DblMatrix |
GridElementDOM.getVolume()
Returns the volume (area in 2D) of this element.
|
DblMatrix |
GridElementXML.getVolume() |
DblMatrix |
GridElementStorage.getXData()
Gets just the x-coordinate data for this GridElementStorage.
|
DblMatrix |
GridElementTransferAgent.getXData() |
DblMatrix |
GridElementDOM.getXData() |
DblMatrix |
GridElementXML.getXData() |
DblMatrix |
GridElementStorage.getYData()
Gets just the y-coordinate data for this GridElementStorage.
|
DblMatrix |
GridElementTransferAgent.getYData() |
DblMatrix |
GridElementDOM.getYData() |
DblMatrix |
GridElementXML.getYData() |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
XppOdeStatisticalModel.getPredictionAt(DblMatrix[] xx) |
DblMatrix |
XppOdeStatisticalModel.likelihood() |
Modifier and Type | Method and Description |
---|---|
DblMatrix |
XppOdeStatisticalModel.getPredictionAt(DblMatrix[] xx) |
Copyright © 2011, 2013. Daniel P. Dougherty