hugo-site/content/posts/2024/source/analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "import re\n",
    "import numpy as np\n",
    "from cds2py import plot_svg\n",
    "from datetime import datetime, date\n",
    "from collections import namedtuple\n",
    "from slugify import slugify\n",
    "from quantiphy import Quantity\n",
    "from tabulate import tabulate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('diet.csv') as csvfile:\n",
    "    data = list(csv.reader(csvfile, delimiter=','))\n",
    "\n",
    "DietEntry = namedtuple(\"DietEntry\", [slugify(elem).replace(\"-\",\"_\") for elem in data[0]])\n",
    "\n",
    "def quantify_elem(elem:str, field:str):\n",
    "    if field == \"date\":\n",
    "        return datetime.strptime(elem,\"%Y-%m-%d\")\n",
    "    elif field == \"completed\":\n",
    "        return elem == \"true\"\n",
    "    elif field.split(\"_\")[-1] == \"mg\":\n",
    "        return Quantity(float(elem)*1e-3, units=\"g\")\n",
    "    elif field.split(\"_\")[-1] == \"ug\":\n",
    "        return Quantity(float(elem)*1e-6, units=\"g\")\n",
    "    elif field.split(\"_\")[-1] == \"iu\":\n",
    "        return Quantity(float(elem)*1e-6/40, units=\"g\")\n",
    "    elif field.split(\"_\")[-1] == \"kcal\":\n",
    "        return Quantity(float(elem)*1e3, units=\"cal\")\n",
    "    else:\n",
    "        return Quantity(elem, units=field.split(\"_\")[-1])\n",
    "\n",
    "quantities = [\n",
    "    DietEntry(\n",
    "        *[\n",
    "            quantify_elem(value, DietEntry._fields[index])\n",
    "            for index,value in enumerate(elem)\n",
    "        ]\n",
    "    ) for elem in data[1:]\n",
    "]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "darray = np.array(quantities)[:,1:-1].astype(float)\n",
    "Names = [re.sub(\" [kmiu]\",\" \", elem.replace(\"_\",\" \")).replace(\" u\",\" g\") for elem in DietEntry._fields[1:-1]]\n",
    "metric_table = np.vstack(\n",
    "        ( Names, [ Quantity(elem).render(prec=2) for elem in darray.mean(axis=0) ], [ Quantity(elem).render(prec=2) for elem in darray.std(axis=0) ]  )\n",
    "    )\n",
    "\n",
    "with open(\"diet.table\",\"w\") as mdfile:\n",
    "    mdfile.write(\n",
    "        tabulate( metric_table.T, headers=[\"Metric\", \"Average\", \"Deviation\"],)\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import importlib.resources as rsc\n",
    "import json\n",
    "import re\n",
    "import nutrimetrics.resources.dri\n",
    "\n",
    "src_txt = rsc.read_text(nutrimetrics.resources.dri,\"ear-male.json\")\n",
    "average_requirement = json.loads(re.sub(\"//.*\",\"\",src_txt))[\"dietary_reference_intakes\"]\n",
    "src_txt = rsc.read_text(nutrimetrics.resources.dri,\"rda-male.json\")\n",
    "average_allowance = json.loads(re.sub(\"//.*\",\"\",src_txt))[\"dietary_reference_intakes\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "folate\n",
      "vitamin-a\n",
      "vitamin-c\n",
      "vitamin-d\n",
      "vitamin-e\n",
      "calcium\n",
      "copper\n",
      "iron\n",
      "magnesium\n",
      "manganese\n",
      "phosphorus\n",
      "potassium\n",
      "selenium\n",
      "sodium\n",
      "zinc\n"
     ]
    }
   ],
   "source": [
    "\n",
    "for name, average, _ in metric_table.T:\n",
    "    nutrient = name.replace(\" \",\"-\").replace(\"-g\",\"\")\n",
    "    if nutrient in average_requirement:\n",
    "        print(nutrient)\n",
    "        # print(Quantity(average_requirement[nutrient],units=\"g\")/Quantity(average, units=\"g\"))"
   ]
  }
 ],
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