w4m_filter_zero_imputation: Impute missing values to zero for W4M data matrix
In HegemanLab/w4mclassfilter: W4M Class Filter

Description Usage Arguments Value Author(s) See Also Examples

Substitute zero for missing or negative intensity values in W4M data matrix

1	w4m_filter_zero_imputation(m)

`m`	matrix: W4M data matrix potentially containing NA or negative values

matrix: input data matrix with zeros substituted for negative or NA values

Art Eschenlauer, esch0041@umn.edu

https://github.com/HegemanLab/w4mclassfilter

http://workflow4metabolomics.org/

# input contains negative and missing values
my_input <- matrix(c(NA,1,-1,2), ncol = 2, nrow = 2)

# expected output converts negative and missing values to zero
my_expected <- matrix(c(0,1,0,2), ncol = 2, nrow = 2)

# run the imputation method to generate actual output
my_output <- w4m_filter_zero_imputation(my_input)

# validate actual output against expected output
all.equal(my_output, my_expected, check.attributes = FALSE)