Using the Consibio Cloud Package

library(consibiocloudclient)

# After loading our package, try and make a api status call.
result <- get_test()
status <- result$status
time <- result$time

login("bob@helloworld.com")

logout()

set_project_id(target_project)

options("consibio.project_id" = "your_project_id")

library(consibiocloudclient)

# Login 
login("bob@helloworld.com") # This will shows a prompt to enter password. If you wan't to use a static password (not recommended), set CONSIBIO_PASSWORD as env. variable before trying to login

# Get user
get_users_me()

# Get projects
projects <- get_projects()
target_project <- names(projects)[1]

# Set target project (can also be done with the native R function: options(consibio.project_id = target_project))
set_project_id(target_project)

# Get project
project <- get_project()

# Get devices
devices <- get_devices()

# Get elements
elements <- get_elements()

# Make list with elements
element_ids <- names(elements)

# Limit the scope to maximum 25 elements, which are the maximum amount of elements that can be fetched at once
element_ids <- element_ids[1:25]

# Get datalog
to_time <- Sys.time()
from_time <- to_time - 1 * 24 * 60 * 60 # 1 days
df <- get_datalog(element_ids, from_time, to_time)

############
# Element checks before plotting the data
############
# Get the elements from the df without data, but was queried
elements_without_data <- c() # Initialize an empty vector to store the elements without data
# Loop over each element in element_ids If the element is not in df$element_id, add it to elements_without_data
for (element in element_ids)
  if (!element %in% df$element_id)
    elements_without_data <- c(elements_without_data, element)
# print(elements_without_data)

# Find the elements in element_ids that are in df$element_id
elements_with_data <- setdiff(element_ids, elements_without_data)
# print(elements_with_data)

# Print a single line statement with the total, with and without
sprintf(
  "Got %d elements with data, and %d witout.",
  length(elements_with_data),
  length(elements_without_data)
)


############
# Example on how to print a plot with the dataframe values, where we use the name and color of each fetched element
############
# Create a data frame with the element IDs, names, and colors
df_element_default <- data.frame(
  element_id = names(elements),
  name = sapply(elements, function(x)
    x$name),
  color = sapply(elements, function(x)
    x$color)
)

# Merge the element data frame with the original data frame
df_extended <- merge(df, df_element_default, by = "element_id", all.x = TRUE)

# df_extended <- df_extended[df_extended$element_id == "jedBIJcmzw6tGLKvmtbm",] # Limit to a single element, if you need to test something

if (!require(ggplot2)) {
  install.packages("ggplot2")
}
library(ggplot2)

# Create a line plot with `ggplot2`
render_without_colors <- TRUE # If the colors are identical, or similar, the plot will replace the existing scales. If so, it's possible to render without the colors
if (render_without_colors) {
  ggplot(df_extended,
         aes(
           x = timestamp,
           y = value,
           color = name,
           group = element_id
         )) +
    geom_line() +
    labs(title = "Consibio Cloud Plot", x = "Timestamp", y = "Value") +
    theme(plot.title = element_text(hjust = 0.5)) +
    scale_color_manual(
      values = setNames(df_extended$color, df_extended$name),
      guide = guide_legend(title = "Element Name")
    ) +
    scale_x_datetime(date_labels = "%Y-%m-%d %H:%M:%S")
} else{
  ggplot(df_extended,
         aes(
           x = timestamp,
           y = value,
           color = color,
           group = element_id
         )) +
    geom_line() +
    labs(title = "Consibio Cloud Plot", x = "Timestamp", y = "Value") +
    theme(plot.title = element_text(hjust = 0.5)) +
    scale_color_identity() +
    guides(color = guide_legend(title = "Element Name")) +
    scale_color_discrete(labels = df_extended$name) +
    scale_x_datetime(date_labels = "%Y-%m-%d %H:%M:%S")
}

# Logout
logout() # Will remove username and user_id. Please reset your R-session to remove any tokens (which are saved automatically in memory)