Turn off warnings for tidyverse and dplyr

pull/103/head
JulioV 2020-10-23 10:41:00 -04:00
parent c41d24df45
commit 86509207ac
24 changed files with 26 additions and 42 deletions

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

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

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

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

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

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@ -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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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