Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
library(mergingTools)
## ----include=FALSE------------------------------------------------------------
library(dplyr)
library(purrr)
library(DT)
library(devtools)
devtools::load_all()
## ----echo=FALSE---------------------------------------------------------------
# Data
DT::datatable(data_hrm_raw_vignette,
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
## -----------------------------------------------------------------------------
n_pmcs <- 6
data_hrm <- mergingTools::process_raw_experiments(data = data_hrm_raw_vignette,
n_pmcs = n_pmcs)
## ----echo=FALSE---------------------------------------------------------------
DT::datatable(data_hrm[[1]],
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
DT::datatable(data_hrm[[2]],
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
DT::datatable(data_hrm[[3]],
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
## -----------------------------------------------------------------------------
anchor_hem <- "PROCESSOR_CYCLES"
data_arranged <- data_hrm %>%
purrr::map(~ .x %>% arrange(!!sym(anchor_hem)))
## ----echo=FALSE---------------------------------------------------------------
DT::datatable(data_arranged[[1]],
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
DT::datatable(data_arranged[[2]],
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
DT::datatable(data_arranged[[3]],
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
## ----message=FALSE, warning=FALSE---------------------------------------------
data_merged <- data_arranged %>%
purrr::map(~ .x %>% select(-anchor_hem)) %>%
purrr::reduce(cbind)
## -----------------------------------------------------------------------------
DT::datatable(data_merged,
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
## -----------------------------------------------------------------------------
anchor_data <- purrr::map(data_arranged, ~ .x %>% dplyr::select(anchor_hem)) %>%
unlist() %>%
stats::quantile(probs = seq(0, 1, length.out = nrow(data_merged)), type = 2) %>%
unname()
merged_data <- cbind(anchor_data, data_merged)
names(merged_data)[1] <- anchor_hem
## ----echo=FALSE---------------------------------------------------------------
DT::datatable(merged_data,
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
## -----------------------------------------------------------------------------
# Data
n_pmcs <- 6
data_much <- mergingTools::process_raw_experiments(data = data_much_raw_vignette,
n_pmcs = n_pmcs)
length(data_much)
## -----------------------------------------------------------------------------
# Compute the correlation matrix for all HEMs
cor_matrix <- mergingTools::correlation_matrix(splitted_data = data_much)
## ----echo=FALSE---------------------------------------------------------------
DT::datatable(cor_matrix ,
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE)) %>%
formatRound(columns = colnames(cor_matrix), digits=3)
## -----------------------------------------------------------------------------
dep_lvl <- 0.85
# Remove the HEMs which are linearly dependant on other HEMs
cor_matrix_independent <- mergingTools::get_independent_matrix(cor_matrix = cor_matrix, dep_lvl = dep_lvl)
## ----echo=FALSE---------------------------------------------------------------
DT::datatable(cor_matrix_independent ,
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE)) %>%
formatRound(columns = colnames(cor_matrix_independent), digits=3)
## -----------------------------------------------------------------------------
# Compute the parameters for the multivariate Gaussian distribution
mvg_params <- mergingTools::generate_mvg_params(splitted_data = data_much, cor_matrix = cor_matrix_independent)
## -----------------------------------------------------------------------------
# Simulate several MVGD and merge best on the optimal one
n_sims <- 100
n_runs <- 1000
merged_data <- mergingTools::simulate_and_merge(mvg_params = mvg_params, n_runs = n_runs, n_sims = n_sims, cor_matrix = cor_matrix_independent)
## ----echo=FALSE---------------------------------------------------------------
DT::datatable(merged_data ,
extensions = 'FixedColumns',
options = list(scrollX = TRUE,
scrollCollapse = TRUE))
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