Turn off warnings for tidyverse and dplyr

renv/activate.R

@@ -1,6 +1,8 @@
 
 local({
 
+  options(tidyverse.quiet = TRUE)
+
   # the requested version of renv
   version <- "0.10.0"
 
@@ -302,7 +304,7 @@ local({
     renv_bootstrap_validate_version(version)
   
     # load the project
-    renv::load(project)
+    renv::load(project, quiet = TRUE)
   
     TRUE
   

src/data/application_categories.R

@@ -1,7 +1,7 @@
 source("renv/activate.R")
 
 library(tidyr)
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(stringr)
 library("rvest")
 

src/data/assign_to_day_segment.R

@@ -1,5 +1,5 @@
 library("tidyverse")
-library("lubridate")
+library("lubridate", warn.conflicts = F)
 options(scipen=999)
 
 day_type_delay <- function(day_type, include_past_periodic_segments){

src/data/download_fitbit_data.R

@@ -1,6 +1,6 @@
 source("renv/activate.R")
 library(RMySQL)
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(readr)
 library(stringr)
 library(yaml)

src/data/download_phone_data.R

@@ -2,7 +2,7 @@ source("renv/activate.R")
 source("src/data/unify_utils.R")
 library(RMySQL)
 library(stringr)
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(readr)
 library(yaml)
 library(lubridate)

src/data/join_visible_and_connected_wifi.R

@@ -1,18 +0,0 @@
-source("renv/activate.R")
-library("dplyr")
-
-if(!is.null(snakemake@input[["visible_access_points"]]) && is.null(snakemake@input[["connected_access_points"]])){
-  wifi_data <- read.csv(snakemake@input[["visible_access_points"]], stringsAsFactors = FALSE)
-  wifi_data <- wifi_data %>% mutate(connected = 0)
-} else if(is.null(snakemake@input[["visible_access_points"]]) && !is.null(snakemake@input[["connected_access_points"]])){
-  wifi_data <- read.csv(snakemake@input[["connected_access_points"]], stringsAsFactors = FALSE)
-  wifi_data <- wifi_data %>% mutate(connected = 1)
-} else if(!is.null(snakemake@input[["visible_access_points"]]) && !is.null(snakemake@input[["connected_access_points"]])){
-  visible_access_points <- read.csv(snakemake@input[["visible_access_points"]], stringsAsFactors = FALSE)
-  visible_access_points <- visible_access_points %>% mutate(connected = 0)
-  connected_access_points <- read.csv(snakemake@input[["connected_access_points"]], stringsAsFactors = FALSE)
-  connected_access_points <- connected_access_points %>% mutate(connected = 1)
-  wifi_data <- bind_rows(visible_access_points, connected_access_points) %>% arrange(timestamp)
-}
-
-write.csv(wifi_data, snakemake@output[[1]], row.names = FALSE)

src/data/phone_sensed_bins.R

@@ -1,6 +1,6 @@
 source("renv/activate.R")
 
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(tidyr)
 
 all_sensors <- snakemake@input[["all_sensors"]]

src/data/phone_sensed_timestamps.R

@@ -1,5 +1,5 @@
 source("renv/activate.R")
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(readr)
 library(tidyr)
 library(purrr)

src/data/phone_valid_sensed_days.R

@@ -1,5 +1,5 @@
 source("renv/activate.R")
-library("dplyr")
+library("dplyr", warn.conflicts = F)
 library("tidyr")
 
 phone_sensed_bins <- read.csv(snakemake@input[["phone_sensed_bins"]])

src/data/process_location_types.R

@@ -1,5 +1,5 @@
 source("renv/activate.R")
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(readr)
 library(tidyr)
 

src/data/unify_utils.R

@@ -1,4 +1,4 @@
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(stringr)
 
 unify_ios_screen <- function(ios_screen){

src/features/entry.R

@@ -1,6 +1,6 @@
 source("renv/activate.R")
 source("src/features/utils/utils.R")
-library("dplyr")
+library("dplyr",warn.conflicts = F)
 library("tidyr")
 
 sensor_data_files <- snakemake@input

src/features/join_features_from_providers.R

@@ -1,7 +1,7 @@
 source("renv/activate.R")
 
 library("tidyr")
-library("dplyr")
+library("dplyr", warn.conflicts = F)
 
 location_features_files <- snakemake@input[["location_features"]]
 location_features <- setNames(data.frame(matrix(ncol = 1, nrow = 0)), c("local_segment"))

src/features/phone_activity_recognition/episodes/activity_recognition_episodes.R

@@ -1,5 +1,5 @@
 source("renv/activate.R")
-library("dplyr")
+library("dplyr", warn.conflicts = F)
 
 activity_recognition <- read.csv(snakemake@input[[1]])
 

src/features/phone_battery/episodes/battery_episodes.R

@@ -1,5 +1,5 @@
 source("renv/activate.R")
-library("dplyr")
+library("dplyr", warn.conflicts = F)
 
 battery <- read.csv(snakemake@input[[1]])
 

src/features/phone_bluetooth/rapids/main.R

@@ -1,4 +1,4 @@
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(tidyr)
 
 compute_bluetooth_feature <- function(data, feature, day_segment){

src/features/phone_locations/barnett/main.R

@@ -1,5 +1,5 @@
 source("renv/activate.R")
-library("dplyr")
+library("dplyr", warn.conflicts = F)
 library("stringr")
 
 # Load Ian Barnett's code. Taken from https://scholar.harvard.edu/ibarnett/software/gpsmobility

src/features/phone_screen/episodes/screen_episodes.R

@@ -1,6 +1,6 @@
 source("renv/activate.R")
 
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(tidyr)
 library(stringr)
 

src/features/phone_wifi_connected/rapids/main.R

@@ -1,4 +1,4 @@
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 
 compute_wifi_feature <- function(data, feature, day_segment){
   data <- data %>% filter_data_by_segment(day_segment)

src/features/phone_wifi_visible/rapids/main.R

@@ -1,4 +1,4 @@
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 
 compute_wifi_feature <- function(data, feature, day_segment){
   data <- data %>% filter_data_by_segment(day_segment)

src/features/utils/resample_episodes.R

@@ -1,6 +1,6 @@
 source("renv/activate.R")
 library("tibble")
-library("dplyr")
+library("dplyr", warn.conflicts = F)
 library("tidyr")
 library("tibble")
 options(scipen=999)

src/models/clean_features_for_model.R

@@ -1,6 +1,6 @@
 source("renv/activate.R")
 library(tidyr)
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 
 filter_participant_without_enough_days <- function(clean_features, days_before_threshold, days_after_threshold){
   clean_features$day_type <- ifelse(clean_features$day_idx < 0, -1, ifelse(clean_features$day_idx > 0, 1, 0))

src/models/merge_features_for_individual_model.R

@@ -2,11 +2,11 @@ source("renv/activate.R")
 
 library(tidyr)
 library(purrr)
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library("methods")
 library("mgm")
 library("qgraph")
-library("dplyr")
+library("dplyr", warn.conflicts = F)
 library("scales")
 library("ggplot2")
 library("purrr")

src/models/merge_features_for_population_model.R

@@ -2,7 +2,7 @@ source("renv/activate.R")
 
 library(tidyr)
 library(purrr)
-library(dplyr)
+library("dplyr", warn.conflicts = F)
 library(stringr)
 
 feature_files  <- snakemake@input[["feature_files"]]