In personalscience/taster: Personal Science CGM Analysis Web App

knitr::opts_chunk$set(echo = TRUE)
library(psiCGM)
library(tidyverse)
library(lubridate)
library(knitr)
library(kableExtra)

Setup: load theme information

This section gives a central place to make templates that can be reused across reports

library(showtext)
font_add_google("Montserrat")
showtext_auto()

psi_theme <-   theme(text = element_text(# family = "Montserrat",
                                         face = "bold", size = 15),
                     axis.text.x = element_text(size = 15, angle = 90, hjust = 1),
                     legend.title = element_blank(),
                     legend.position = "bottom")

Setup: Prepare database

Pull the data from the Tastermonial AWS database. Your credentials are kept in the local file config.yml, which is not displayed (or kept in Github)

conn_args <- config::get("dataconnection")
con <- DBI::dbConnect(
  drv = conn_args$driver,
  user = conn_args$user,
  host = conn_args$host,
  port = conn_args$port,
  dbname = conn_args$dbname,
  password = conn_args$password
)

Loads food times and other data from the Tastermonial retool database.

source("psi_db_taster_notes.R")
# from file.path(config::get("tastermonial")$datadir,"table-data.csv")
# taster_raw <- taster_raw()
taster_raw %>% names()

Glucose Reponse for Munk products

# return all users who ate foodname
glucose_for_food_df(user_id = user_df_from_db() %>% pull(user_id), foodname="munk")

username_for_id(1014)  # string value for user_id = 1014

# all named items in Tastermonial database that have an associated barcode and include the letters "Munk"

munk <- taster_raw %>% filter(!is.na(barcode)) %>% filter(str_detect(name,"Munk")) %>% select(name) %>% pull(name) 

# URL for the image associated with that name

munk_img <- taster_raw %>% filter(!is.na(barcode)) %>% filter(str_detect(name,"Munk")) %>% select(name, image ) %>% pull(image) %>% first() %>% magick::image_read()

#print(munk_img)

# all times this user ate something by that name, including the 20 minutes beforehand

munk_times <- food_times_df(user_id = lookup_id_from_name("Bude Sethaputra"), foodname = munk[1], prefixLength = 20 )
munk_times %>% head() %>% knitr::kable() %>% kableExtra::kable_styling(latex_options = "striped", position = "float_left")

# plot 
munk_times %>% transmute(t,value,meal = str_trunc(meal,25)) %>%
  ggplot(aes(x=t,y=value, color = meal)) + geom_line() +
  labs(title = "Eating Munk Pack Bars", subtitle = "August 2021") + 
  psi_theme

Moon Cheese Report

Note that the graph includes a smoothing curve.

mooncheese <- taster_raw %>% filter(!is.na(barcode)) %>% filter(str_detect(name,"Moon")) %>% select(name,image,type)
moon_img <- magick::image_read(mooncheese$image)

#magick::image_draw(magick::image_resize(moon_img, "200"))

# return all users who ate foodname
glucose_for_food_df(user_id = user_df_from_db() %>% pull(user_id), foodname="\\[Moon Cheese\\] White") %>% select(Start,Comment,user_id) %>% knitr::kable()

username_for_id(1002)  # string value for user_id = 1002

# all named items in Tastermonial database that have an associated barcode and include the reg expr "\\[Moon Cheese\\] White"

mooncheese <- taster_raw %>% filter(!is.na(barcode)) %>% filter(str_detect(name,"\\[Moon Cheese\\] White")) %>% select(name) %>% pull(name)


# all times this user ate something by that name, including the 20 minutes beforehand

moon_times <- food_times_df(user_id = lookup_id_from_name("Ayumi Blystone"), foodname ="\\[Moon Cheese\\] White" , prefixLength = 20 )
moon_times %>% head() %>%  knitr::kable() %>% kableExtra::kable_styling(latex_options = "striped", position = "float_left")

# plot 
moon_times %>% transmute(t,value,meal = str_trunc(meal,15)) %>%
  ggplot(aes(x=t,y=value, color = meal)) + geom_line() + geom_smooth() + 
  psi_theme