Package ubic.basecode.math

Class MatrixStats

java.lang.Object
ubic.basecode.math.MatrixStats
public class MatrixStats extends Object
Author:
pavlidis

  • Constructor Details

    • MatrixStats

      public MatrixStats()

  • Method Details

    • colSums

      public static <R, C> DoubleMatrix1D colSums(DoubleMatrix<R,C> data)
      NaN values are omitted from calculations.
      Type Parameters:
      R -
      C -
      Parameters:
      data -
      Returns:
      column sums

    • convertToLog2

      public static <R, C> void convertToLog2(DoubleMatrix<R,C> matrix, double base)
      Convert a log_b-transformed data set to log 2.
      Parameters:
      matrix -
      base - the current base

    • convertToLog2Cpm

      public static <R, C> DoubleMatrix<R,C> convertToLog2Cpm(DoubleMatrix<R,C> matrix, DoubleMatrix1D librarySize)
      Convert a count matrix to log2 counts per million. Equivalent to t(log2(t(counts+0.5)/(lib.size+1)*1e6)) in R. (NOTE: originally this did the operation in place)
      Parameters:
      matrix -
      librarySize - if null, it will default to colSums(matrix).
      Returns:

    • correlationMatrix

      public static <R, C> DoubleMatrix<R,R> correlationMatrix(DoubleMatrix<R,C> data)
      Compute the correlation matrix of the rows of a matrix.
      Parameters:
      data -
      Returns:
      a symmetric matrix that has the rows and columns set to be the names of the rows of the input.

    • correlationMatrix

      public static <R, C> SparseDoubleMatrix<R,R> correlationMatrix(DoubleMatrix<R,C> data, double threshold)
      Parameters:
      data - DenseDoubleMatrix2DNamed
      threshold - only correlations with absolute values above this level are stored (others are Double.NaN)
      Returns:
      a sparse symmetric matrix that has the rows and columns set to be the names of the rows of the input. The diagonal is set to Double.NaN

    • doubleStandardize

      public static <R, C> DoubleMatrix<R,C> doubleStandardize(DoubleMatrix<R,C> matrix)
      Iteratively standardize the columns and rows of the matrix.
      Parameters:
      data -

    • logTransform

      public static <R, C> void logTransform(DoubleMatrix<R,C> matrix)
      Log-transform the values in a matrix (log base 2). Values that are less than or equal to zero are left as Double.NaN.
      Parameters:
      matrixToNormalize -

    • max

      public static <R, C> double max(DoubleMatrix<R,C> matrix)
      Compute the maximum value in the matrix.
      Parameters:
      matrix - DenseDoubleMatrix2DNamed
      Returns:
      the largest value in the matrix

    • min

      public static <R, C> double min(DoubleMatrix<R,C> matrix)
      Find the minimum of the entire matrix.
      Parameters:
      matrix - DenseDoubleMatrix2DNamed
      Returns:
      the smallest value in the matrix

    • nanStatusMatrix

      public static boolean[][] nanStatusMatrix(double[][] data)
      Parameters:
      data -
      Returns:
      matrix indicating whether each value in the input matix is NaN.

    • rbfNormalize

      public static <R, C> void rbfNormalize(DoubleMatrix<R,C> matrixToNormalize, double sigma)
      Normalize a matrix in place to be a transition matrix. Assumes that values operate such that small values like p values represent closer distances, and the values are probabilities.

      Each point is first transformed via v' = exp(-v/sigma). Then the values for each node's edges are adjusted to sum to 1.

      Parameters:
      matrixToNormalize -
      sigma - a scaling factor for the input values.

    • selfSquaredMatrix

      public static double[][] selfSquaredMatrix(double[][] input)
      Parameters:
      input - raw double 2-d matrix
      Returns:
      the element-by-element product (not matrix product) of the matrix.

    • standardize

      public static <R, C> DoubleMatrix<R,C> standardize(DoubleMatrix<R,C> matrix)
      Scale the rows of the matrix; returns a new matrix.
      Type Parameters:
      R -
      C -
      Parameters:
      data -
      Returns:

    • cov2cor

      public static DoubleMatrix2D cov2cor(DoubleMatrix2D cov)
      Scale a covariance matrix to the corresponding correlation matrix.
      Parameters:
      cov - a symmetric matrix of covariances
      Returns:

    • unLogTransform

      public static <R, C> void unLogTransform(DoubleMatrix<R,C> matrix)
      Undo log2 transform.
      Type Parameters:
      R -
      C -
      Parameters:
      matrix -