tests/haldane_human_local_test.R

In eruud/test.calorimeter.r: Calorimeter processing functions

# Load necessary packages
library(pilr.api.r)
library(uuid)
library(dplyr)
library(jsonlite)
library(base64enc)
# options(stringsAsFactors = FALSE)

# Clear old values
remove(params)

options(pilr_server_default = "http://cloud.pilrhealth.com")
options(pilr_project_default = "test_lrc_bundle")
options(pilr_default_access_code = "bcb22b88-70ed-48dc-ac48-de91f2a29eed")
participant = "test5"

# Set options for server, project, access code
# options(pilr_server_default = "http://cloud.pilrhealth.com")
# options(pilr_project_default = "n2_test_project")
# options(pilr_default_access_code = "bf62c048-0f14-4e7f-a24c-8516ffd5a14c")
# participant = "test_participant_1"

# options(pilr_server_default = "http://cloud.pilrhealth.com")
# options(pilr_project_default = "n2_test_project_3")
# options(pilr_default_access_code = "f90a86ee-4196-47be-af2f-fe0b9d4340dd")
# participant = "500-0024v1"
# 
# # options(pilr_server_default = "http://cloud.pilrhealth.com")
# # options(pilr_project_default = "500_practiceproject")
# # options(pilr_default_access_code = "f0266314-7580-463c-a92e-8ea1af2e3bba")
# # participant = "500-0024v1"
# 
# event_server = "http://cloud.pilrhealth.com"
# event_project = "500_practiceproject"
# event_access_code = "f0266314-7580-463c-a92e-8ea1af2e3bba"
# event_participant = "500-0024v1"

# event_server = "http://cloud.pilrhealth.com"
# event_project = "n2_test_project_3"
# event_access_code = "f90a86ee-4196-47be-af2f-fe0b9d4340dd"
# event_participant = "500-0024v1"


# Retrieve data (can append more datasets to the list if workunit requires them)
data <- list(calrq = read_pilr(data_set = "pilrhealth:calrq:calrq_data", schema = "1", value = "all",
                               query_params = list(participant = participant)))

# Set your params (participant variables and instrument settings)
params = list(settings = read_pilr_params(data_set = "pilrhealth:calrq:calrq_data", schema = "1", instrument = "calrq", participant = participant, period = "active_period", epoch = "epoch_1"))

# Get data for human summary
data$event_tags <- list(calrq = read_pilr(data_set = "pilrhealth:time_analysis:tagged_event", schema = "1",
                                          query_params = list(participant = participant)))
data$event_tags <- data$event_tags$calrq

# data$event_tags <- list(calrq = read_pilr(pilr_server = event_server, project = event_project, data_set = "pilrhealth:time_analysis:tagged_event", schema = "1", access_code = event_access_code ,query_params = list(participant = event_participant)))
# data$event_tags <- data$event_tags$calrq

# Add package information to params
params$package <- "test.calorimeter.r"

# # Fix multiple N2 array
# testlist <- eval(parse("", n=NULL, gsub('\n', "", params$settings$multiple_n2$value, fixed = TRUE)))
# fields = list()
# for (i in 1:length(testlist$fields))
# {
#   fields[i] = list(as.data.frame(testlist$fields[[i]])) 
#   fields[[i]]$value = list(as.numeric(testlist$fields[[i]]$value[1]),list('$date' = testlist$fields[[i]]$value[2]),testlist$fields[[i]]$value[3])
#   print(i)
# }
# end
# 
# test = data.frame(matrix(1,length(fields)))
# test$fields = fields
# test <- subset(test, select = -1)
# params$settings$multiple_n2$value <- toJSON(test)

# # Fix rest duration
# testlist <- eval(parse("", n=NULL, gsub('\n', "", params$settings$rest_durations$value, fixed = TRUE)))
# fields = list()
# for (i in 1:length(testlist$fields))
# {
#   fields[i] = list(as.data.frame(testlist$fields[[i]]))
#   fields[[i]]$value[1] = list(as.numeric(testlist$fields[[i]]$value[1]))
#   fields[[i]]$value[2] = list(as.numeric(testlist$fields[[i]]$value[2]))
#   print(i)
# }
# end
# 
# test = data.frame(matrix(1,1))
# test$fields = fields
# test <- subset(test, select = -1)
# params$settings$rest_durations$value <- toJSON(test)

# Remap variables with changed names (set in job def JSON)
params$settings$volume <- params$settings$chamber_volume

# Run haldane transform
data$haldane <- apply_haldane(data, params)

# Run human summary
ret <- process_cal_human(data, params)