WebDescription. The nsparseMatrix class is a virtual class of sparse “pattern” matrices, i.e., binary matrices conceptually with TRUE / FALSE entries. Only the positions of the … The dgCMatrix class is a class of sparse numeric matrices in the compressed, sparse, column-oriented format. In this implementation the non-zero elements in the columns are sorted into increasing row order. dgCMatrix is the “standard” class for sparse numeric matrices in the Matrix package.
Perform nonnegative matrix factorization in R - Stack Overflow
WebShow the sparsity (as a count or proportion) of a matrix. For example, .99 sparsity means 99% of the values are zero. Similarly, a sparsity of 0 means the matrix is fully dense. Usage sparsity (x, proportion = TRUE) Arguments x The matrix, stored as an ordinary R matrix or as a "simple triplet matrix" (from the slam package). proportion WebR Documentation Performs counts per million (CPM) data normalization Description This function normalizes the count data present in a given matrix using counts per million normalization (CPM). Each gene count for each cell is divided by the total counts for that cell and multiplied by 1e6. No log-transformation is applied. Usage food wars 6.sezon
Removing rows from a sparse matrix of class "dgCMatrix" in R
WebNov 29, 2013 · Part of R Language Collective Collective 1 I create a sparseMatrix, save it to a MatrixMarket format using writeMM - the sparse matrix automatically changes to a ngTMatrix class (from dgCMatrix). I load it back using readMM and plot the matrix. Everything is fine except that I cannot using the simple xlim, ylim to control the axis. WebAug 2, 2024 · Part of R Language Collective Collective. 3. Consider this simple sparse matrix. > (X <- sparseMatrix (c (1, 2, 1), c (1, 1, 2), x = 0:2)) 2 x 2 sparse Matrix of class "dgCMatrix" [1,] 0 2 [2,] 1 . How can I convert it into a matrix indicating if the corresponding element is non-empty? Here is what I'm doing now, but being 0 does not equal to ... WebMar 29, 2014 · 1 Answer Sorted by: 1 Yes, indeed: kcca () from package kernlab currently can only work with traditional R matrices (which are dense ). Some inspection of the code, and one example do suggest that indeed, not too many changes may be needed and enhance the kernlab package to also work with sparseMatrix objects from the Matrix … food warning labels examples