ubic.gemma.core.datastructure.matrix

Class ExpressionDataDoubleMatrixUtil

java.lang.Object

ubic.gemma.core.datastructure.matrix.ExpressionDataDoubleMatrixUtil

public class ExpressionDataDoubleMatrixUtil
extends Object

Perform various computations on ExpressionDataMatrices (usually in-place).

Author:

pavlidis

Constructor Summary

Constructors

Constructor and Description
ExpressionDataDoubleMatrixUtil()

Method Summary

Modifier and Type	Method and Description
static void	addMatrices(ExpressionDataDoubleMatrix a, ExpressionDataDoubleMatrix b) Add two matrices.
static ExpressionDataDoubleMatrix	ensureLog2Scale(QuantitationType quantitationType, ExpressionDataDoubleMatrix dmatrix) Ensures that the given matrix is on a Log2 scale.
static ExpressionDataDoubleMatrix	filterAndLog2Transform(QuantitationType quantitationType, ExpressionDataDoubleMatrix dmatrix) Log2 transform if necessary, do any required filtering prior to analysis.
static ScaleType	findScale(QuantitationType quantitationType, DoubleMatrix<CompositeSequence,BioMaterial> namedMatrix)
static void	logTransformMatrix(ExpressionDataDoubleMatrix matrix) Log-transform the values in the matrix (base 2).
static void	maskMatrix(ExpressionDataDoubleMatrix matrix, ExpressionDataBooleanMatrix mask) Use the mask matrix to turn some values in a matrix to NaN.
static void	scalarDivideMatrix(ExpressionDataDoubleMatrix matrix, double dividend) Divide all values by the dividend
static void	subtractMatrices(ExpressionDataDoubleMatrix a, ExpressionDataDoubleMatrix b) Subtract two matrices.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ExpressionDataDoubleMatrixUtil

public ExpressionDataDoubleMatrixUtil()

Method Detail

filterAndLog2Transform

public static ExpressionDataDoubleMatrix filterAndLog2Transform(QuantitationType quantitationType,
                                                                ExpressionDataDoubleMatrix dmatrix)

Log2 transform if necessary, do any required filtering prior to analysis. Count data is converted to log2CPM (but we store log2cpm as the processed data, so that is what would generally be used).

Parameters:

quantitationType - QT

dmatrix - matrix

Returns:

ee data double matrix

ensureLog2Scale

public static ExpressionDataDoubleMatrix ensureLog2Scale(QuantitationType quantitationType,
                                                         ExpressionDataDoubleMatrix dmatrix)

Ensures that the given matrix is on a Log2 scale. ! Does not update the QT !

Parameters:

quantitationType - the quantitation type to be checked for the scale.

dmatrix - the matrix to be transformed to a log2 scale if necessary.

Returns:

a data matrix that is guaranteed to be on a log2 scale.

findScale

public static ScaleType findScale(QuantitationType quantitationType,
                                  DoubleMatrix<CompositeSequence,BioMaterial> namedMatrix)

Parameters:

quantitationType - QT

namedMatrix - named matrix

Returns:

ScaleType

See Also:

for a related implementation.

subtractMatrices

public static void subtractMatrices(ExpressionDataDoubleMatrix a,
                                    ExpressionDataDoubleMatrix b)

Subtract two matrices. Ideally, they matrices are conformant, but if they are not (as some rows are sometimes missing for some quantitation types), this method attempts to handle it anyway (see below). The rows and columns do not have to be in the same order, but they do have to have the same column keys and row keys (with the exception of missing rows). The result is stored in a. (a - b). If the number of rows are not the same, and/or the rows have different keys in the two matrices, some rows will simply not get subtracted and a warning will be issued.

Parameters:

a - matrix a

b - matrix b

Throws:

IllegalArgumentException - if the matrices are not column-conformant.

logTransformMatrix

public static void logTransformMatrix(ExpressionDataDoubleMatrix matrix)

Log-transform the values in the matrix (base 2). Non-positive values (which have no logarithm defined) are entered as NaN.

Parameters:

matrix - matrix

addMatrices

public static void addMatrices(ExpressionDataDoubleMatrix a,
                               ExpressionDataDoubleMatrix b)

Add two matrices. Ideally, they matrices are conformant, but if they are not (as some rows are sometimes missing for some quantitation types), this method attempts to handle it anyway (see below). The rows and columns do not have to be in the same order, but they do have to have the same column keys and row keys (with the exception of missing rows). The result is stored in a. If the number of rows are not the same, and/or the rows have different keys in the two matrices, some rows will simply not get added and a warning will be issued.

Parameters:

a - matrix a

b - matrix b

Throws:

IllegalArgumentException - if the matrices are not column-conformant.

scalarDivideMatrix

public static void scalarDivideMatrix(ExpressionDataDoubleMatrix matrix,
                                      double dividend)

Divide all values by the dividend

Parameters:

matrix - matrix

dividend - dividend

Throws:

IllegalArgumentException - if dividend == 0.

maskMatrix

public static void maskMatrix(ExpressionDataDoubleMatrix matrix,
                              ExpressionDataBooleanMatrix mask)

Use the mask matrix to turn some values in a matrix to NaN. Ideally, they matrices are conformant, but if they are not (as some rows are sometimes missing for some quantitation types), this method attempts to handle it anyway (see below). The rows and columns do not have to be in the same order, but they do have to have the same column keys and row keys (with the exception of missing rows). The result is stored in matrix.

Parameters:

matrix - matrix

mask - if null, masking is not attempted.