d2s

0th

Percentile

Dense to sparse conversion

Convert data from dense representation (matrix) to sparse representation (list of data frames).

Usage
d2s(
X,
zero = 0,
threshold = 1e-16,
verbose= TRUE
)
Arguments
X

A d x N numeric matrix where N is the number of data points --- each column is an observation, and d is the dimensionality. Column-observation representation promotes cache locality.

zero

A numeric value. Elements in X satisfying abs(X[i] - zero) <= threshold are treated as zeros. Default 0.

threshold

A numeric value, explained above.

verbose

A boolean value. TRUE prints progress.

Value

A list of size N. Value[[i]] is a 2-column data frame. The 1st column is a sorted integer vector of the indexes of nonzero dimensions. Values in these dimensions are stored in the 2nd column as a numeric vector.

• d2s
Examples
# NOT RUN {
N = 2000L
d = 3000L
X = matrix(rnorm(N * d) + 2, nrow = d)
# Fill many zeros in X:
X = apply(X, 2, function(x) {
x[sort(sample(d, d * runif(1, 0.95, 0.99)))] = 0; x})
# Get the sparse version of X.
sparseX = GMKMcharlie::d2s(X)
str(sparseX[1:5])
# }
Documentation reproduced from package GMKMcharlie, version 1.0.3, License: GPL-3

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