Classify theta values in CMC-theta distribution as having "High" or "Low" CMC candidate counts

decision_highCMC_identifyHighCMCThetas(cmcThetaDistrib, tau = 1)



output of the decision_highCMC_cmcThetaDistrib function


constant used to define a "high" CMC count. This number is subtracted from the maximum CMC count achieved in the CMC-theta distribution. Theta values with CMC counts above this value are considered to have "high" CMC counts.


A vector of the same length as the input containing "High" or "Low" classification based on whether the associated theta value has a High CMC Candidate count.


This function is a helper internally called in the decision_CMC function. It is exported to be used as a diagnostic tool for the High CMC method


if (FALSE) { data(fadul1.1_processed,fadul1.2_processed) comparisonDF <- purrr::map_dfr(seq(-30,30,by = 3), ~ comparison_allTogether(fadul1.1_processed, fadul1.2_processed, theta = .)) highCMCthetas <- comparisonDF %>% dplyr::mutate(cmcThetaDistribClassif = decision_highCMC_cmcThetaDistrib(cellIndex = cellIndex, x = x, y = y, theta = theta, corr = pairwiseCompCor)) %>% decision_highCMC_identifyHighCMCThetas(tau = 1) highCMCthetas %>% dplyr::filter(cmcThetaDistribClassif == "CMC Candidate") %>% ggplot2::ggplot(ggplot2::aes(x = theta,fill = thetaCMCIdentif)) + ggplot2::geom_bar(stat = "count") }