{
  "cells": [
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "##### Edit the four numeric parameters on the right (*SDMT, VFT, SCR*, and *SWR*) and press the **Play** button below to calculate the HD Composite Cognition Score (CCS)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SQ-mj4125A1g",
        "outputId": "faa8dc34-8eca-4d3b-c409-7ac9e83abf71"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CCS = 0.83\n",
            "Group 2: medium CCS, Motor medium risk\n"
          ]
        }
      ],
      "source": [
        "from numpy import array\n",
        "\n",
        "v = array([0.51,0.4,0.54,0.54])\n",
        "σ = array([10.62,5.07,13.07,16.23])\n",
        "μ = array([42.90,19.30,66.43,86.14])\n",
        "\n",
        "def CCS(X):\n",
        "  return ((v/σ)*(X-μ)).sum()\n",
        "\n",
        "#@title Prodromic average scores:\n",
        "\n",
        "SDMT = 45 #@param {type:\"integer\"}\n",
        "VFT = 25 #@param {type:\"integer\"}\n",
        "SCR = 70 #@param {type:\"integer\"}\n",
        "SWR = 90 #@param {type:\"integer\"}\n",
        "\n",
        "\n",
        "X = array([SDMT, VFT, SCR, SWR], dtype=int)\n",
        "if (X<0).any():\n",
        "  print(\"Test scores can not be negative\")\n",
        "else:\n",
        "  ccs = CCS(X)\n",
        "  print(\"CCS = %.2f\"%ccs)\n",
        "  if ccs<-2.375:\n",
        "    print(\"Group 1: Low CCS, Motor high risk\")\n",
        "  elif ccs<2.375:\n",
        "    print(\"Group 2: medium CCS, Motor medium risk\")\n",
        "  else:\n",
        "    print(\"Group 3: high CCS, Motor low risk\")"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}