HIV_2007_conventional_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define circuits and take statistics from HIV_2007 paper:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "import random\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.formula.api import ols\n",
    "\n",
    "from IPython.display import set_matplotlib_formats\n",
    "set_matplotlib_formats(\"png\", \"pdf\", \"svg\")\n",
    "\n",
    "matplotlib.style.use('ggplot')\n",
    "%matplotlib inline\n",
    "\n",
    "class Genotype:\n",
    "    mean_value = 0.0\n",
    "    min_value = 0.0\n",
    "    Q1_value = 0.0\n",
    "    median_value = 0.0\n",
    "    Q3_value = 0.0\n",
    "    max_value = 0.0\n",
    "\n",
    "class Circuit:\n",
    "    mean_value = 0.0\n",
    "    min_value = 0.0\n",
    "    Q1_value = 0.0\n",
    "    median_value = 0.0\n",
    "    Q3_value = 0.0\n",
    "    max_value = 0.0\n",
    "    \n",
    "def u_110(u_110_000: Genotype, u_110_001: Genotype, u_110_010: Genotype, u_110_011: Genotype, u_110_100: Genotype, u_110_101: Genotype, u_110_110: Genotype, u_110_111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = u_110_000.mean_value + u_110_001.mean_value + u_110_110.mean_value + u_110_111.mean_value - u_110_010.mean_value - u_110_011.mean_value - u_110_100.mean_value - u_110_101.mean_value\n",
    "    output.min_value = u_110_000.min_value + u_110_001.min_value + u_110_110.min_value + u_110_111.min_value - u_110_010.min_value - u_110_011.min_value - u_110_100.min_value - u_110_101.min_value\n",
    "    output.Q1_value = u_110_000.Q1_value + u_110_001.Q1_value + u_110_110.Q1_value + u_110_111.Q1_value - u_110_010.Q1_value - u_110_011.Q1_value - u_110_100.Q1_value - u_110_101.Q1_value\n",
    "    output.median_value = u_110_000.median_value + u_110_001.median_value + u_110_110.median_value + u_110_111.median_value - u_110_010.median_value - u_110_011.median_value - u_110_100.median_value - u_110_101.median_value\n",
    "    output.Q3_value = u_110_000.Q3_value + u_110_001.Q3_value + u_110_110.Q3_value + u_110_111.Q3_value - u_110_010.Q3_value - u_110_011.Q3_value - u_110_100.Q3_value - u_110_101.Q3_value\n",
    "    output.max_value = u_110_000.max_value + u_110_001.max_value + u_110_110.max_value + u_110_111.max_value - u_110_010.max_value - u_110_011.max_value - u_110_100.max_value - u_110_101.max_value\n",
    "    return output\n",
    "\n",
    "def u_101(u_101_000: Genotype, u_101_001: Genotype, u_101_010: Genotype, u_101_011: Genotype, u_101_100: Genotype, u_101_101: Genotype, u_101_110: Genotype, u_101_111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = u_101_000.mean_value + u_101_010.mean_value + u_101_101.mean_value + u_101_111.mean_value - u_101_001.mean_value - u_101_011.mean_value - u_101_100.mean_value - u_101_110.mean_value\n",
    "    output.min_value = u_101_000.min_value + u_101_010.min_value + u_101_101.min_value + u_101_111.min_value - u_101_001.min_value - u_101_011.min_value - u_101_100.min_value - u_101_110.min_value\n",
    "    output.Q1_value = u_101_000.Q1_value + u_101_010.Q1_value + u_101_101.Q1_value + u_101_111.Q1_value - u_101_001.Q1_value - u_101_011.Q1_value - u_101_100.Q1_value - u_101_110.Q1_value\n",
    "    output.median_value = u_101_000.median_value + u_101_010.median_value + u_101_101.median_value + u_101_111.median_value - u_101_001.median_value - u_101_011.median_value - u_101_100.median_value - u_101_110.median_value\n",
    "    output.Q3_value = u_101_000.Q3_value + u_101_010.Q3_value + u_101_101.Q3_value + u_101_111.Q3_value - u_101_001.Q3_value - u_101_011.Q3_value - u_101_100.Q3_value - u_101_110.Q3_value\n",
    "    output.max_value = u_101_000.max_value + u_101_010.max_value + u_101_101.max_value + u_101_111.max_value - u_101_001.max_value - u_101_011.max_value - u_101_100.max_value - u_101_110.max_value\n",
    "    return output\n",
    "\n",
    "def u_011(u_011_000: Genotype, u_011_001: Genotype, u_011_010: Genotype, u_011_011: Genotype, u_011_100: Genotype, u_011_101: Genotype, u_011_110: Genotype, u_011_111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = u_011_000.mean_value + u_011_100.mean_value + u_011_011.mean_value + u_011_111.mean_value - u_011_001.mean_value - u_011_101.mean_value - u_011_010.mean_value - u_011_110.mean_value\n",
    "    output.min_value = u_011_000.min_value + u_011_100.min_value + u_011_011.min_value + u_011_111.min_value - u_011_001.min_value - u_011_101.min_value - u_011_010.min_value - u_011_110.min_value\n",
    "    output.Q1_value = u_011_000.Q1_value + u_011_100.Q1_value + u_011_011.Q1_value + u_011_111.Q1_value - u_011_001.Q1_value - u_011_101.Q1_value - u_011_010.Q1_value - u_011_110.Q1_value\n",
    "    output.median_value = u_011_000.median_value + u_011_100.median_value + u_011_011.median_value + u_011_111.median_value - u_011_001.median_value - u_011_101.median_value - u_011_010.median_value - u_011_110.median_value\n",
    "    output.Q3_value = u_011_000.Q3_value + u_011_100.Q3_value + u_011_011.Q3_value + u_011_111.Q3_value - u_011_001.Q3_value - u_011_101.Q3_value - u_011_010.Q3_value - u_011_110.Q3_value\n",
    "    output.max_value = u_011_000.max_value + u_011_100.max_value + u_011_011.max_value + u_011_111.max_value - u_011_001.max_value - u_011_101.max_value - u_011_010.max_value - u_011_110.max_value\n",
    "    return output\n",
    "\n",
    "def u_111(u_111_000: Genotype, u_111_001: Genotype, u_111_010: Genotype, u_111_011: Genotype, u_111_100: Genotype, u_111_101: Genotype, u_111_110: Genotype, u_111_111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = u_111_000.mean_value + u_111_011.mean_value + u_111_101.mean_value + u_111_110.mean_value - u_111_100.mean_value - u_111_010.mean_value - u_111_001.mean_value - u_111_111.mean_value\n",
    "    output.min_value = u_111_000.min_value + u_111_011.min_value + u_111_101.min_value + u_111_110.min_value - u_111_100.min_value - u_111_010.min_value - u_111_001.min_value - u_111_111.min_value\n",
    "    output.Q1_value = u_111_000.Q1_value + u_111_011.Q1_value + u_111_101.Q1_value + u_111_110.Q1_value - u_111_100.Q1_value - u_111_010.Q1_value - u_111_001.Q1_value - u_111_111.Q1_value\n",
    "    output.median_value = u_111_000.median_value + u_111_011.median_value + u_111_101.median_value + u_111_110.median_value - u_111_100.median_value - u_111_010.median_value - u_111_001.median_value - u_111_111.median_value\n",
    "    output.Q3_value = u_111_000.Q3_value + u_111_011.Q3_value + u_111_101.Q3_value + u_111_110.Q3_value - u_111_100.Q3_value - u_111_010.Q3_value - u_111_001.Q3_value - u_111_111.Q3_value\n",
    "    output.max_value = u_111_000.max_value + u_111_011.max_value + u_111_101.max_value + u_111_110.max_value - u_111_100.max_value - u_111_010.max_value - u_111_001.max_value - u_111_111.max_value\n",
    "    return output\n",
    "\n",
    "def a(a000: Genotype, a001: Genotype, a010: Genotype, a011: Genotype, a100: Genotype, a101: Genotype, a110: Genotype, a111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = a000.mean_value - a010.mean_value - a100.mean_value + a111.mean_value\n",
    "    output.min_value = a000.min_value - a010.min_value - a100.min_value + a111.min_value\n",
    "    output.Q1_value = a000.Q1_value - a010.Q1_value - a100.Q1_value + a111.Q1_value\n",
    "    output.median_value = a000.median_value - a010.median_value - a100.median_value + a111.median_value\n",
    "    output.Q3_value = a000.Q3_value - a010.Q3_value - a100.Q3_value + a111.Q3_value\n",
    "    output.max_value = a000.max_value - a010.max_value - a100.max_value + a111.max_value\n",
    "    return output\n",
    "\n",
    "def b(b000: Genotype, b001: Genotype, b010: Genotype, b011: Genotype, b100: Genotype, b101: Genotype, b110: Genotype, b111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = b001.mean_value - b011.mean_value - b101.mean_value + b111.mean_value\n",
    "    output.min_value = b001.min_value - b011.min_value - b101.min_value + b111.min_value\n",
    "    output.Q1_value = b001.Q1_value - b011.Q1_value - b101.Q1_value + b111.Q1_value\n",
    "    output.median_value = b001.median_value - b011.median_value - b101.median_value + b111.median_value\n",
    "    output.Q3_value = b001.Q3_value - b011.Q3_value - b101.Q3_value + b111.Q3_value\n",
    "    output.max_value = b001.max_value - b011.max_value - b101.max_value + b111.max_value\n",
    "    return output\n",
    "\n",
    "def c(c000: Genotype, c001: Genotype, c010: Genotype, c011: Genotype, c100: Genotype, c101: Genotype, c110: Genotype, c111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = c000.mean_value - c001.mean_value - c100.mean_value + c101.mean_value\n",
    "    output.min_value = c000.min_value - c001.min_value - c100.min_value + c101.min_value\n",
    "    output.Q1_value = c000.Q1_value - c001.Q1_value - c100.Q1_value + c101.Q1_value\n",
    "    output.median_value = c000.median_value - c001.median_value - c100.median_value + c101.median_value\n",
    "    output.Q3_value = c000.Q3_value - c001.Q3_value - c100.Q3_value + c101.Q3_value\n",
    "    output.max_value = c000.max_value - c001.max_value - c100.max_value + c101.max_value\n",
    "    return output\n",
    "\n",
    "def d(d000: Genotype, d001: Genotype, d010: Genotype, d011: Genotype, d100: Genotype, d101: Genotype, d110: Genotype, d111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = d010.mean_value - d011.mean_value - d110.mean_value + d111.mean_value\n",
    "    output.min_value = d010.min_value - d011.min_value - d110.min_value + d111.min_value\n",
    "    output.Q1_value = d010.Q1_value - d011.Q1_value - d110.Q1_value + d111.Q1_value\n",
    "    output.median_value = d010.median_value - d011.median_value - d110.median_value + d111.median_value\n",
    "    output.Q3_value = d010.Q3_value - d011.Q3_value - d110.Q3_value + d111.Q3_value\n",
    "    output.max_value = d010.max_value - d011.max_value - d110.max_value + d111.max_value\n",
    "    return output\n",
    "\n",
    "def e(e000: Genotype, e001: Genotype, e010: Genotype, e011: Genotype, e100: Genotype, e101: Genotype, e110: Genotype, e111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = e000.mean_value - e001.mean_value - e010.mean_value + e011.mean_value\n",
    "    output.min_value = e000.min_value - e001.min_value - e010.min_value + e011.min_value\n",
    "    output.Q1_value = e000.Q1_value - e001.Q1_value - e010.Q1_value + e011.Q1_value\n",
    "    output.median_value = e000.median_value - e001.median_value - e010.median_value + e011.median_value\n",
    "    output.Q3_value = e000.Q3_value - e001.Q3_value - e010.Q3_value + e011.Q3_value\n",
    "    output.max_value = e000.max_value - e001.max_value - e010.max_value + e011.max_value\n",
    "    return output\n",
    "\n",
    "def f(f000: Genotype, f001: Genotype, f010: Genotype, f011: Genotype, f100: Genotype, f101: Genotype, f110: Genotype, f111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = f100.mean_value - f101.mean_value - f110.mean_value + f111.mean_value\n",
    "    output.min_value = f100.min_value - f101.min_value - f110.min_value + f111.min_value\n",
    "    output.Q1_value = f100.Q1_value - f101.Q1_value - f110.Q1_value + f111.Q1_value\n",
    "    output.median_value = f100.median_value - f101.median_value - f110.median_value + f111.median_value\n",
    "    output.Q3_value = f100.Q3_value - f101.Q3_value - f110.Q3_value + f111.Q3_value\n",
    "    output.max_value = f100.max_value - f101.max_value - f110.max_value + f111.max_value\n",
    "    return output\n",
    "\n",
    "def g(g000: Genotype, g001: Genotype, g010: Genotype, g011: Genotype, g100: Genotype, g101: Genotype, g110: Genotype, g111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = g000.mean_value - g100.mean_value - g011.mean_value + g111.mean_value\n",
    "    output.min_value = g000.min_value - g100.min_value - g011.min_value + g111.min_value\n",
    "    output.Q1_value = g000.Q1_value - g100.Q1_value - g011.Q1_value + g111.Q1_value\n",
    "    output.median_value = g000.median_value - g100.median_value - g011.median_value + g111.median_value\n",
    "    output.Q3_value = g000.Q3_value - g100.Q3_value - g011.Q3_value + g111.Q3_value\n",
    "    output.max_value = g000.max_value - g100.max_value - g011.max_value + g111.max_value\n",
    "    return output\n",
    "\n",
    "def h(h000: Genotype, h001: Genotype, h010: Genotype, h011: Genotype, h100: Genotype, h101: Genotype, h110: Genotype, h111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = h001.mean_value - h010.mean_value - h101.mean_value + h110.mean_value\n",
    "    output.min_value = h001.min_value - h010.min_value - h101.min_value + h110.min_value\n",
    "    output.Q1_value = h001.Q1_value - h010.Q1_value - h101.Q1_value + h110.Q1_value\n",
    "    output.median_value = h001.median_value - h010.median_value - h101.median_value + h110.median_value\n",
    "    output.Q3_value = h001.Q3_value - h010.Q3_value - h101.Q3_value + h110.Q3_value\n",
    "    output.max_value = h001.max_value - h010.max_value - h101.max_value + h110.max_value\n",
    "    return output\n",
    "\n",
    "def i(i000: Genotype, i001: Genotype, i010: Genotype, i011: Genotype, i100: Genotype, i101: Genotype, i110: Genotype, i111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = i000.mean_value - i010.mean_value - i101.mean_value + i111.mean_value\n",
    "    output.min_value = i000.min_value - i010.min_value - i101.min_value + i111.min_value\n",
    "    output.Q1_value = i000.Q1_value - i010.Q1_value - i101.Q1_value + i111.Q1_value\n",
    "    output.median_value = i000.median_value - i010.median_value - i101.median_value + i111.median_value\n",
    "    output.Q3_value = i000.Q3_value - i010.Q3_value - i101.Q3_value + i111.Q3_value\n",
    "    output.max_value = i000.max_value - i010.max_value - i101.max_value + i111.max_value\n",
    "    return output\n",
    "\n",
    "def j(j000: Genotype, j001: Genotype, j010: Genotype, j011: Genotype, j100: Genotype, j101: Genotype, j110: Genotype, j111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = j001.mean_value - j100.mean_value - j011.mean_value + j110.mean_value\n",
    "    output.min_value = j001.min_value - j100.min_value - j011.min_value + j110.min_value\n",
    "    output.Q1_value = j001.Q1_value - j100.Q1_value - j011.Q1_value + j110.Q1_value\n",
    "    output.median_value = j001.median_value - j100.median_value - j011.median_value + j110.median_value\n",
    "    output.Q3_value = j001.Q3_value - j100.Q3_value - j011.Q3_value + j110.Q3_value\n",
    "    output.max_value = j001.max_value - j100.max_value - j011.max_value + j110.max_value\n",
    "    return output\n",
    "\n",
    "def k(k000: Genotype, k001: Genotype, k010: Genotype, k011: Genotype, k100: Genotype, k101: Genotype, k110: Genotype, k111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = k000.mean_value - k001.mean_value - k110.mean_value + k111.mean_value\n",
    "    output.min_value = k000.min_value - k001.min_value - k110.min_value + k111.min_value\n",
    "    output.Q1_value = k000.Q1_value - k001.Q1_value - k110.Q1_value + k111.Q1_value\n",
    "    output.median_value = k000.median_value - k001.median_value - k110.median_value + k111.median_value\n",
    "    output.Q3_value = k000.Q3_value - k001.Q3_value - k110.Q3_value + k111.Q3_value\n",
    "    output.max_value = k000.max_value - k001.max_value - k110.max_value + k111.max_value\n",
    "    return output\n",
    "\n",
    "def l(l000: Genotype, l001: Genotype, l010: Genotype, l011: Genotype, l100: Genotype, l101: Genotype, l110: Genotype, l111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = l010.mean_value - l100.mean_value - l011.mean_value + l101.mean_value\n",
    "    output.min_value = l010.min_value - l100.min_value - l011.min_value + l101.min_value\n",
    "    output.Q1_value = l010.Q1_value - l100.Q1_value - l011.Q1_value + l101.Q1_value\n",
    "    output.median_value = l010.median_value - l100.median_value - l011.median_value + l101.median_value\n",
    "    output.Q3_value = l010.Q3_value - l100.Q3_value - l011.Q3_value + l101.Q3_value\n",
    "    output.max_value = l010.max_value - l100.max_value - l011.max_value + l101.max_value\n",
    "    return output\n",
    "\n",
    "def m(m000: Genotype, m001: Genotype, m010: Genotype, m011: Genotype, m100: Genotype, m101: Genotype, m110: Genotype, m111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = -2*m000.mean_value + m001.mean_value + m010.mean_value + m100.mean_value - m111.mean_value\n",
    "    output.min_value = -2*m000.min_value + m001.min_value + m010.min_value + m100.min_value - m111.min_value\n",
    "    output.Q1_value = -2*m000.Q1_value + m001.Q1_value + m010.Q1_value + m100.Q1_value - m111.Q1_value\n",
    "    output.median_value = -2*m000.median_value + m001.median_value + m010.median_value + m100.median_value - m111.median_value\n",
    "    output.Q3_value = -2*m000.Q3_value + m001.Q3_value + m010.Q3_value + m100.Q3_value - m111.Q3_value\n",
    "    output.max_value = -2*m000.max_value + m001.max_value + m010.max_value + m100.max_value - m111.max_value\n",
    "    return output\n",
    "\n",
    "def n(n000: Genotype, n001: Genotype, n010: Genotype, n011: Genotype, n100: Genotype, n101: Genotype, n110: Genotype, n111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = -n000.mean_value + n011.mean_value + n101.mean_value + n110.mean_value - 2*n111.mean_value\n",
    "    output.min_value = -n000.min_value + n011.min_value + n101.min_value + n110.min_value - 2*n111.min_value\n",
    "    output.Q1_value = -n000.Q1_value + n011.Q1_value + n101.Q1_value + n110.Q1_value - 2*n111.Q1_value\n",
    "    output.median_value = -n000.median_value + n011.median_value + n101.median_value + n110.median_value - 2*n111.median_value\n",
    "    output.Q3_value = -n000.Q3_value + n011.Q3_value + n101.Q3_value + n110.Q3_value - 2*n111.Q3_value\n",
    "    output.max_value = -n000.max_value + n011.max_value + n101.max_value + n110.max_value - 2*n111.max_value\n",
    "    return output\n",
    "\n",
    "def o(o000: Genotype, o001: Genotype, o010: Genotype, o011: Genotype, o100: Genotype, o101: Genotype, o110: Genotype, o111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = -o001.mean_value + o010.mean_value + o100.mean_value - 2*o110.mean_value + o111.mean_value\n",
    "    output.min_value = -o001.min_value + o010.min_value + o100.min_value - 2*o110.min_value + o111.min_value\n",
    "    output.Q1_value = -o001.Q1_value + o010.Q1_value + o100.Q1_value - 2*o110.Q1_value + o111.Q1_value\n",
    "    output.median_value = -o001.median_value + o010.median_value + o100.median_value - 2*o110.median_value + o111.median_value\n",
    "    output.Q3_value = -o001.Q3_value + o010.Q3_value + o100.Q3_value - 2*o110.Q3_value + o111.Q3_value\n",
    "    output.max_value = -o001.max_value + o010.max_value + o100.max_value - 2*o110.max_value + o111.max_value\n",
    "    return output\n",
    "\n",
    "def p(p000: Genotype, p001: Genotype, p010: Genotype, p011: Genotype, p100: Genotype, p101: Genotype, p110: Genotype, p111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = p000.mean_value - 2*p001.mean_value + p011.mean_value + p101.mean_value - p110.mean_value\n",
    "    output.min_value = p000.min_value - 2*p001.min_value + p011.min_value + p101.min_value - p110.min_value\n",
    "    output.Q1_value = p000.Q1_value - 2*p001.Q1_value + p011.Q1_value + p101.Q1_value - p110.Q1_value\n",
    "    output.median_value = p000.median_value - 2*p001.median_value + p011.median_value + p101.median_value - p110.median_value\n",
    "    output.Q3_value = p000.Q3_value - 2*p001.Q3_value + p011.Q3_value + p101.Q3_value - p110.Q3_value\n",
    "    output.max_value = p000.max_value - 2*p001.max_value + p011.max_value + p101.max_value - p110.max_value\n",
    "    return output\n",
    "\n",
    "def q(q000: Genotype, q001: Genotype, q010: Genotype, q011: Genotype, q100: Genotype, q101: Genotype, q110: Genotype, q111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = q001.mean_value - q010.mean_value + q100.mean_value - 2*q101.mean_value + q111.mean_value\n",
    "    output.min_value = q001.min_value - q010.min_value + q100.min_value - 2*q101.min_value + q111.min_value\n",
    "    output.Q1_value = q001.Q1_value - q010.Q1_value + q100.Q1_value - 2*q101.Q1_value + q111.Q1_value\n",
    "    output.median_value = q001.median_value - q010.median_value + q100.median_value - 2*q101.median_value + q111.median_value\n",
    "    output.Q3_value = q001.Q3_value - q010.Q3_value + q100.Q3_value - 2*q101.Q3_value + q111.Q3_value\n",
    "    output.max_value = q001.max_value - q010.max_value + q100.max_value - 2*q101.max_value + q111.max_value\n",
    "    return output\n",
    "\n",
    "def r(r000: Genotype, r001: Genotype, r010: Genotype, r011: Genotype, r100: Genotype, r101: Genotype, r110: Genotype, r111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = r000.mean_value - 2*r010.mean_value + r011.mean_value - r101.mean_value + r110.mean_value\n",
    "    output.min_value = r000.min_value - 2*r010.min_value + r011.min_value - r101.min_value + r110.min_value\n",
    "    output.Q1_value = r000.Q1_value - 2*r010.Q1_value + r011.Q1_value - r101.Q1_value + r110.Q1_value\n",
    "    output.median_value = r000.median_value - 2*r010.median_value + r011.median_value - r101.median_value + r110.median_value\n",
    "    output.Q3_value = r000.Q3_value - 2*r010.Q3_value + r011.Q3_value - r101.Q3_value + r110.Q3_value\n",
    "    output.max_value = r000.max_value - 2*r010.max_value + r011.max_value - r101.max_value + r110.max_value\n",
    "    return output\n",
    "\n",
    "def s(s000: Genotype, s001: Genotype, s010: Genotype, s011: Genotype, s100: Genotype, s101: Genotype, s110: Genotype, s111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = s000.mean_value - 2*s100.mean_value - s011.mean_value + s101.mean_value + s110.mean_value\n",
    "    output.min_value = s000.min_value - 2*s100.min_value - s011.min_value + s101.min_value + s110.min_value\n",
    "    output.Q1_value = s000.Q1_value - 2*s100.Q1_value - s011.Q1_value + s101.Q1_value + s110.Q1_value\n",
    "    output.median_value = s000.median_value - 2*s100.median_value - s011.median_value + s101.median_value + s110.median_value\n",
    "    output.Q3_value = s000.Q3_value - 2*s100.Q3_value - s011.Q3_value + s101.Q3_value + s110.Q3_value\n",
    "    output.max_value = s000.max_value - 2*s100.max_value - s011.max_value + s101.max_value + s110.max_value\n",
    "    return output\n",
    "\n",
    "def t(t000: Genotype, t001: Genotype, t010: Genotype, t011: Genotype, t100: Genotype, t101: Genotype, t110: Genotype, t111: Genotype) -> Circuit:\n",
    "    output = Circuit()\n",
    "    output.mean_value = t001.mean_value + t010.mean_value - t100.mean_value - 2*t011.mean_value + t111.mean_value\n",
    "    output.min_value = t001.min_value + t010.min_value - t100.min_value - 2*t011.min_value + t111.min_value\n",
    "    output.Q1_value = t001.Q1_value + t010.Q1_value - t100.Q1_value - 2*t011.Q1_value + t111.Q1_value\n",
    "    output.median_value = t001.median_value + t010.median_value - t100.median_value - 2*t011.median_value + t111.median_value\n",
    "    output.Q3_value = t001.Q3_value + t010.Q3_value - t100.Q3_value - 2*t011.Q3_value + t111.Q3_value\n",
    "    output.max_value = t001.max_value + t010.max_value - t100.max_value - 2*t011.max_value + t111.max_value\n",
    "    return output\n",
    "\n",
    "w000 = Genotype()\n",
    "w001 = Genotype()\n",
    "w010 = Genotype()\n",
    "w011 = Genotype()\n",
    "w100 = Genotype()\n",
    "w101 = Genotype()\n",
    "w110 = Genotype()\n",
    "w111 = Genotype()\n",
    "\n",
    "w000.mean_value = 1.58\n",
    "w001.mean_value = 1.195\n",
    "w010.mean_value = 1.133\n",
    "w011.mean_value = 1.43\n",
    "w100.mean_value = 1.441\n",
    "w101.mean_value = 1.232\n",
    "w110.mean_value = 1.294\n",
    "w111.mean_value = 1.045\n",
    "\n",
    "w000.min_value = 0.1917\n",
    "w001.min_value = 0.5344\n",
    "w010.min_value = -0.3355\n",
    "w011.min_value = 1.0\n",
    "w100.min_value = 0.4771\n",
    "w101.min_value = 0.301\n",
    "w110.min_value = 0.6021\n",
    "w111.min_value = -0.4771\n",
    "\n",
    "w000.Q1_value = 1.477\n",
    "w001.Q1_value = 0.699\n",
    "w010.Q1_value = 1.144\n",
    "w011.Q1_value = 1.25\n",
    "w100.Q1_value = 1.347\n",
    "w101.Q1_value = 0.8673\n",
    "w110.Q1_value = 1.161\n",
    "w111.Q1_value = 0.9472\n",
    "\n",
    "w000.median_value = 1.641\n",
    "w001.median_value = 1.188\n",
    "w010.median_value = 1.296\n",
    "w011.median_value = 1.515\n",
    "w100.median_value = 1.465\n",
    "w101.median_value = 1.342\n",
    "w110.median_value = 1.37\n",
    "w111.median_value = 1.179\n",
    "\n",
    "w000.Q3_value = 1.791\n",
    "w001.Q3_value = 1.771\n",
    "w010.Q3_value = 1.487\n",
    "w011.Q3_value = 1.636\n",
    "w100.Q3_value = 1.789\n",
    "w101.Q3_value = 1.584\n",
    "w110.Q3_value = 1.537\n",
    "w111.Q3_value = 1.385\n",
    "\n",
    "w000.max_value = 2.053\n",
    "w001.max_value = 1.785\n",
    "w010.max_value = 1.531\n",
    "w011.max_value = 1.724\n",
    "w100.max_value = 1.875\n",
    "w101.max_value = 1.887\n",
    "w110.max_value = 1.692\n",
    "w111.max_value = 1.79"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data structure for circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               u_110   u_101   u_011   u_111       a       b       c       d  \\\n",
      "Mean         -0.1220 -0.3700  0.6420  0.7220  0.0510 -0.4220  0.1760 -0.5460   \n",
      "Min          -0.5915 -2.9335  0.0897  1.8959 -0.4270 -1.2437 -0.5188 -2.4147   \n",
      "1st quartile -0.3241 -0.0215  1.1499  0.6181 -0.0668 -0.4711  0.2983 -0.3198   \n",
      "Median       -0.2400 -0.0800  0.6040  0.7400  0.0590 -0.4900  0.3300 -0.4100   \n",
      "3rd quartile -0.0120 -0.4860  0.2220  0.1160 -0.1000 -0.0640 -0.1850 -0.3010   \n",
      "Max           0.3030  0.1850  0.5470  0.3750  0.4370 -0.0360  0.2800 -0.0950   \n",
      "\n",
      "                   e       f   ...         k       l       m       n       o  \\\n",
      "Mean          0.6820 -0.0400   ...    0.1360 -0.5060 -0.4360  0.2860 -0.1640   \n",
      "Min           0.9928 -0.9031   ...   -1.4219 -1.5116  0.7697  2.6656 -2.0741   \n",
      "1st quartile  0.8840  0.2659   ...    0.5642 -0.5857 -0.7112 -0.0931  0.4172   \n",
      "Median        0.6720 -0.0680   ...    0.2620 -0.3420 -0.5120  0.2280  0.0120   \n",
      "3rd quartile  0.1690  0.0530   ...   -0.1320 -0.3540  0.0800  0.1960 -0.1840   \n",
      "Max           0.4610  0.0860   ...    0.3660 -0.1810 -0.7050 -0.3300  0.0270   \n",
      "\n",
      "                   p       q       r       s       t  \n",
      "Mean          0.5580  0.0840  0.8060 -0.2060 -0.9280  \n",
      "Min          -0.1782  0.2679  2.1638 -0.8594 -2.7553  \n",
      "1st quartile  1.0353  0.1146  0.7327 -0.4387 -1.0568  \n",
      "Median        0.7520 -0.1480  0.5920 -0.0920 -0.8320  \n",
      "3rd quartile -0.0680  0.2900  0.4060 -0.3020 -0.4180  \n",
      "Max           0.4020  0.1450  0.5200  0.1580 -0.2170  \n",
      "\n",
      "[6 rows x 24 columns]\n"
     ]
    },
    {
     "data": {
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aM6wGQQY6cy1LOyaWd4SlZXrdiUx7htUgyEBnrhRQXATQEVgAWDXOkWEmlrxlLG65577W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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fabec085828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "circuit = pd.DataFrame(index=(\"Mean\", \"Min\", \"1st quartile\", \"Median\", \"3rd quartile\", \"Max\"))\n",
    "\n",
    "circuit[\"u_110\"] = [u_110(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "                u_110(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "                u_110(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "                u_110(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "                u_110(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "                u_110(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "\n",
    "circuit[\"u_101\"] = [u_101(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "                u_101(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "                u_101(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "                u_101(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "                u_101(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "                u_101(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "\n",
    "circuit[\"u_011\"] = [u_011(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "                u_011(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "                u_011(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "                u_011(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "                u_011(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "                u_011(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "\n",
    "circuit[\"u_111\"] = [u_111(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "                u_111(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "                u_111(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "                u_111(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "                u_111(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "                u_111(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "\n",
    "circuit[\"a\"] = [a(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "                a(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "                a(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "                a(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "                a(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "                a(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"b\"] = [b(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               b(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               b(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               b(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               b(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               b(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"c\"] = [c(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               c(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               c(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               c(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               c(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               c(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"d\"] = [d(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               d(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               d(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               d(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               d(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               d(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"e\"] = [e(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               e(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               e(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               e(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               e(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               e(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"f\"] = [f(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               f(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               f(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               f(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               f(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               f(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"g\"] = [g(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               g(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               g(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               g(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               g(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               g(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"h\"] = [h(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"h\"] = [h(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               h(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"i\"] = [i(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               i(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               i(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               i(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               i(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               i(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"j\"] = [j(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               j(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               j(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               j(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               j(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               j(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"k\"] = [k(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               k(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               k(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               k(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               k(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               k(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"l\"] = [l(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               l(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               l(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               l(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               l(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               l(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"m\"] = [m(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               m(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               m(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               m(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               m(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               m(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"n\"] = [n(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               n(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               n(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               n(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               n(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               n(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"o\"] = [o(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               o(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               o(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               o(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               o(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               o(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"p\"] = [p(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               p(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               p(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               p(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               p(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               p(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"q\"] = [q(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               q(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               q(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               q(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               q(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               q(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"r\"] = [r(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               r(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               r(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               r(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               r(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               r(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"s\"] = [s(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               s(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               s(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               s(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               s(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               s(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "circuit[\"t\"] = [t(w000, w001, w010, w011, w100, w101, w110, w111).mean_value,\n",
    "               t(w000, w001, w010, w011, w100, w101, w110, w111).min_value,\n",
    "               t(w000, w001, w010, w011, w100, w101, w110, w111).Q1_value,\n",
    "               t(w000, w001, w010, w011, w100, w101, w110, w111).median_value,\n",
    "               t(w000, w001, w010, w011, w100, w101, w110, w111).Q3_value,\n",
    "               t(w000, w001, w010, w011, w100, w101, w110, w111).max_value]\n",
    "\n",
    "# circuit_transposed = circuit.transpose()\n",
    "circuit_transposed = circuit\n",
    "# circuit_transposed[\"From rank order\"] = [1, -1, 1, -1, 1, 0, 0, 1, 0, -1, 0, -1, 0, 0, 0, 1, 0, 1, 0, -1]\n",
    "print(circuit)\n",
    "circuit_transposed.plot.box(figsize=(14,10))\n",
    "plt.xticks(rotation='horizontal', size=\"10\")\n",
    "plt.yticks(size=\"10\")\n",
    "plt.savefig(\"HIV_2007_conventional_stats.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Functions to get stats from row data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Returns k closes to the means values from the given list of lists:\n",
    "def closest_to_mean(fit_data_list, k, mean_type=\"mean\"):\n",
    "    if mean_type == \"mean\":\n",
    "        means = [np.mean(fit_data_list[j]) for j in range(len(fit_data_list))]\n",
    "    elif mean_type == \"median\":\n",
    "        means = [np.median(fit_data_list[j]) for j in range(len(fit_data_list))]\n",
    "    fit_data_list_copy = []\n",
    "    for r in range(len(fit_data_list)):\n",
    "        copy = [fit_data_list[r][l] for l in range(len(fit_data_list[r]))]\n",
    "        fit_data_list_copy.append(copy)\n",
    "    output = []\n",
    "    for r in range(k):\n",
    "        output_r = []\n",
    "        for l in range(len(means)):\n",
    "            close_to_mean_index = (np.abs(fit_data_list_copy[l] - means[l])).argmin()\n",
    "            output_r.append(fit_data_list_copy[l][close_to_mean_index])\n",
    "            del fit_data_list_copy[l][close_to_mean_index]\n",
    "        output.append(output_r)\n",
    "    return output\n",
    "\n",
    "# Given data file and mutations of genotypes, returns DataFrame with equal number of replicates across genotypes.\n",
    "# The number of replicates is taken to be max across genotypes, that is, = num of replicates of the genotype with\n",
    "# smallest number of replicates across genotypes\n",
    "def get_mean_fitness(data_file, mutations, sites, mean_type=\"\"):\n",
    "    sites = [0] + sites  # This is specific to the data file. Column 0 contains fitness, column 1 names.\n",
    "    values = pd.read_csv(data_file, usecols=sites)\n",
    "    values.iloc[:, 0] = np.log10(values.iloc[:, 0])\n",
    "    size = len(values.iloc[:, 1])\n",
    "    f000 = []\n",
    "    f001 = []\n",
    "    f010 = []\n",
    "    f100 = []\n",
    "    f011 = []\n",
    "    f101 = []\n",
    "    f110 = []\n",
    "    f111 = []\n",
    "    for s in range(size):\n",
    "        if (values.iloc[s, 1] == mutations[0][0]) & (values.iloc[s, 2] == mutations[1][0]) &\\\n",
    "                (values.iloc[s, 3] == mutations[2][0]):\n",
    "            f000.append(values.iloc[s, 0])\n",
    "        elif (values.iloc[s, 1] == mutations[0][0]) & (values.iloc[s, 2] == mutations[1][0]) &\\\n",
    "                (values.iloc[s, 3] == mutations[2][1]):\n",
    "            f001.append(values.iloc[s, 0])\n",
    "        elif (values.iloc[s, 1] == mutations[0][0]) & (values.iloc[s, 2] == mutations[1][1]) &\\\n",
    "                (values.iloc[s, 3] == mutations[2][0]):\n",
    "            f010.append(values.iloc[s, 0])\n",
    "        elif (values.iloc[s, 1] == mutations[0][1]) & (values.iloc[s, 2] == mutations[1][0]) &\\\n",
    "                (values.iloc[s, 3] == mutations[2][0]):\n",
    "            f100.append(values.iloc[s, 0])\n",
    "        elif (values.iloc[s, 1] == mutations[0][0]) & (values.iloc[s, 2] == mutations[1][1]) &\\\n",
    "                (values.iloc[s, 3] == mutations[2][1]):\n",
    "            f011.append(values.iloc[s, 0])\n",
    "        elif (values.iloc[s, 1] == mutations[0][1]) & (values.iloc[s, 2] == mutations[1][0]) &\\\n",
    "                (values.iloc[s, 3] == mutations[2][1]):\n",
    "            f101.append(values.iloc[s, 0])\n",
    "        elif (values.iloc[s, 1] == mutations[0][1]) & (values.iloc[s, 2] == mutations[1][1]) &\\\n",
    "                (values.iloc[s, 3] == mutations[2][0]):\n",
    "            f110.append(values.iloc[s, 0])\n",
    "        elif (values.iloc[s, 1] == mutations[0][1]) & (values.iloc[s, 2] == mutations[1][1]) &\\\n",
    "                (values.iloc[s, 3] == mutations[2][1]):\n",
    "            f111.append(values.iloc[s, 0])\n",
    "    f = [f000, f001, f010, f011, f100, f101, f110, f111]\n",
    "    sample_length = min(len(f000), len(f001), len(f010), len(f011), len(f100), len(f101), len(f110), len(f111))\n",
    "    f_ctm = closest_to_mean(f, sample_length)\n",
    "    f_all_combinations = []\n",
    "    output = pd.DataFrame(f_ctm)\n",
    "    output.columns = [\"w000\", \"w001\", \"w010\", \"w011\", \"w100\", \"w101\", \"w110\", \"w111\"]\n",
    "    return output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get data from the file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "HIV_data_file = \"2007_HIV_data.csv\"\n",
    "mutations_BPS = [[\"L\", \"M\"],  # mutations: L to M, M to V, t to Y\n",
    "                 [\"M\", \"V\"],\n",
    "                 [\"t\", \"Y\"]]\n",
    "sites_BPS = [88, 244, 275]  # sites: PRO L90M, RT M184V, RT T215Y\n",
    "row_data = get_mean_fitness(HIV_data_file, mutations_BPS, sites_BPS)\n",
    "row_data_shuffled = get_mean_fitness(HIV_data_file, mutations_BPS, sites_BPS)\n",
    "\n",
    "# Takes this many of possible combinations of genotypes:\n",
    "num_duplicates = 40\n",
    "for shuffles in range(num_duplicates - 1):\n",
    "    row_data_shuffled = row_data_shuffled.append(row_data, ignore_index = True)\n",
    "np.random.shuffle(row_data_shuffled.w000)\n",
    "np.random.shuffle(row_data_shuffled.w001)\n",
    "np.random.shuffle(row_data_shuffled.w010)\n",
    "np.random.shuffle(row_data_shuffled.w011)\n",
    "np.random.shuffle(row_data_shuffled.w100)\n",
    "np.random.shuffle(row_data_shuffled.w101)\n",
    "np.random.shuffle(row_data_shuffled.w110)\n",
    "np.random.shuffle(row_data_shuffled.w111)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "T-test:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "200\n",
      "      Statistic       p-value Result From rank order\n",
      "u011  14.625531  2.246290e-33      +             +/-\n",
      "u101  -7.054469  2.804809e-11      -             +/-\n",
      "u110 -11.474083  1.015882e-23      -             +/-\n",
      "u111  13.200852  5.437401e-29      +               +\n",
      "a     -8.892382  3.644218e-16      -               +\n",
      "b    -13.699889  1.585908e-30      -               -\n",
      "c      3.281998  1.217304e-03      +               +\n",
      "d    -26.858337  4.225517e-68      -               -\n",
      "e     16.639435  1.562263e-39      +               +\n",
      "f      1.130381  2.596761e-01    +/-             +/-\n",
      "g    -24.817730  7.798713e-63      -             +/-\n",
      "h     -2.173976  3.088717e-02      -               +\n",
      "i      3.704126  2.747530e-04      +             +/-\n",
      "j    -14.743473  9.746044e-34      -               -\n",
      "k      4.489123  1.209573e-05      +             +/-\n",
      "l    -18.846490  3.883221e-46      -               -\n",
      "m     -5.350038  2.405458e-07      -             +/-\n",
      "n     16.259903  2.222872e-38      +             +/-\n",
      "o      2.724432  7.014631e-03      +             +/-\n",
      "p      9.741351  1.392962e-18      +               +\n",
      "q     -1.180268  2.393025e-01    +/-             +/-\n",
      "r     18.178601  3.693095e-44      +               +\n",
      "s    -12.622155  3.246133e-27      -             +/-\n",
      "t    -24.599309  2.945313e-62      -               -\n"
     ]
    }
   ],
   "source": [
    "def u111_num(u111_000, u111_001, u111_010, u111_011, u111_100, u111_101, u111_110, u111_111):\n",
    "    output = u111_000 - u111_001 - u111_010 - u111_100 + u111_011 + u111_101 + u111_110 - u111_111\n",
    "    return output\n",
    "\n",
    "def u110_num(u110_000, u110_001, u110_010, u110_011, u110_100, u110_101, u110_110, u110_111):\n",
    "    output = u110_000 + u110_001 - u110_010 - u110_100 - u110_011 - u110_101 + u110_110 + u110_111\n",
    "    return output\n",
    "\n",
    "def u101_num(u101_000, u101_001, u101_010, u101_011, u101_100, u101_101, u101_110, u101_111):\n",
    "    output = u101_000 - u101_001 + u101_010 - u101_100 - u101_011 + u101_101 - u101_110 + u101_111\n",
    "    return output\n",
    "\n",
    "def u011_num(u011_000, u011_001, u011_010, u011_011, u011_100, u011_101, u011_110, u011_111):\n",
    "    output = u011_000 - u011_001 - u011_010 + u011_100 + u011_011 - u011_101 - u011_110 + u011_111\n",
    "    return output\n",
    "\n",
    "def a_num(a000, a001, a010, a011, a100, a101, a110, a111):\n",
    "    output = a000 - a010 - a100 + a111\n",
    "    return output\n",
    "\n",
    "def b_num(b000, b001, b010, b011, b100, b101, b110, b111):\n",
    "    output = b001 - b011 - b101 + b111\n",
    "    return output\n",
    "\n",
    "def c_num(c000, c001, c010, c011, c100, c101, c110, c111):\n",
    "    output = c000 - c001 - c100 + c101\n",
    "    return output\n",
    "\n",
    "def d_num(d000, d001, d010, d011, d100, d101, d110, d111):\n",
    "    output = d010 - d011 - d110 + d111\n",
    "    return output\n",
    "\n",
    "def e_num(e000, e001, e010, e011, e100, e101, e110, e111):\n",
    "    output = e000 - e001 - e010 + e011\n",
    "    return output\n",
    "\n",
    "def f_num(f000, f001, f010, f011, f100, f101, f110, f111):\n",
    "    output = f100 - f101 - f110 + f111\n",
    "    return output\n",
    "\n",
    "def g_num(g000, g001, g010, g011, g100, g101, g110, g111):\n",
    "    output = g000 - g100 - g011 + g111\n",
    "    return output\n",
    "\n",
    "def h_num(h000, h001, h010, h011, h100, h101, h110, h111):\n",
    "    output = h001 - h010 - h101 + h110\n",
    "    return output\n",
    "\n",
    "def i_num(i000, i001, i010, i011, i100, i101, i110, i111):\n",
    "    output = i000 - i010 - i101 + i111\n",
    "    return output\n",
    "\n",
    "def j_num(j000, j001, j010, j011, j100, j101, j110, j111):\n",
    "    output = j001 - j100 - j011 + j110\n",
    "    return output\n",
    "\n",
    "def k_num(k000, k001, k010, k011, k100, k101, k110, k111):\n",
    "    output = k000 - k001 - k110 + k111\n",
    "    return output\n",
    "\n",
    "def l_num(l000, l001, l010, l011, l100, l101, l110, l111):\n",
    "    output = l010 - l100 - l011 + l101\n",
    "    return output\n",
    "\n",
    "def m_num(m000, m001, m010, m011, m100, m101, m110, m111):\n",
    "    output = -2*m000 + m001 + m010 + m100 - m111\n",
    "    return output\n",
    "\n",
    "def n_num(n000, n001, n010, n011, n100, n101, n110, n111):\n",
    "    output = -n000 + n011 + n101 + n110 - 2*n111\n",
    "    return output\n",
    "\n",
    "def o_num(o000, o001, o010, o011, o100, o101, o110, o111):\n",
    "    output = -o001 + o010 + o100 - 2*o110 + o111\n",
    "    return output\n",
    "\n",
    "def p_num(p000, p001, p010, p011, p100, p101, p110, p111):\n",
    "    output = p000 - 2*p001 + p011 + p101 - p110\n",
    "    return output\n",
    "\n",
    "def q_num(q000, q001, q010, q011, q100, q101, q110, q111):\n",
    "    output = q001 - q010 + q100 - 2*q101 + q111\n",
    "    return output\n",
    "\n",
    "def r_num(r000, r001, r010, r011, r100, r101, r110, r111):\n",
    "    output = r000 - 2*r010 + r011 - r101 + r110\n",
    "    return output\n",
    "\n",
    "def s_num(s000, s001, s010, s011, s100, s101, s110, s111):\n",
    "    output = s000 - 2*s100 - s011 + s101 + s110\n",
    "    return output\n",
    "\n",
    "def t_num(t000, t001, t010, t011, t100, t101, t110, t111):\n",
    "    output = t001 + t010 - t100 - 2*t011 + t111\n",
    "    return output\n",
    "\n",
    "print(len(row_data_shuffled))\n",
    "\n",
    "u011_ttest = stats.ttest_1samp(u011_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "u101_ttest = stats.ttest_1samp(u101_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "u110_ttest = stats.ttest_1samp(u110_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "u111_ttest = stats.ttest_1samp(u111_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "a_ttest = stats.ttest_1samp(a_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "b_ttest = stats.ttest_1samp(b_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "c_ttest = stats.ttest_1samp(c_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "d_ttest = stats.ttest_1samp(d_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "e_ttest = stats.ttest_1samp(e_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "f_ttest = stats.ttest_1samp(f_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "g_ttest = stats.ttest_1samp(g_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "h_ttest = stats.ttest_1samp(h_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "i_ttest = stats.ttest_1samp(i_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "j_ttest = stats.ttest_1samp(j_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "k_ttest = stats.ttest_1samp(k_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "l_ttest = stats.ttest_1samp(l_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "m_ttest = stats.ttest_1samp(m_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "n_ttest = stats.ttest_1samp(n_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "o_ttest = stats.ttest_1samp(o_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "p_ttest = stats.ttest_1samp(p_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "q_ttest = stats.ttest_1samp(q_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "r_ttest = stats.ttest_1samp(r_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "s_ttest = stats.ttest_1samp(s_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "t_ttest = stats.ttest_1samp(t_num(row_data_shuffled.w000, row_data_shuffled.w001, row_data_shuffled.w010, row_data_shuffled.w011, row_data_shuffled.w100,\n",
    "                                  row_data_shuffled.w101, row_data_shuffled.w110, row_data_shuffled.w111), 0, nan_policy=\"omit\")\n",
    "\n",
    "p_values = pd.DataFrame(index=[\"u011\",\"u101\",\"u110\",\"u111\",\"a\", \"b\", \"c\", \"d\", \"e\", \"f\", \"g\", \"h\", \"i\", \"j\", \"k\", \"l\", \"m\", \"n\", \"o\", \"p\",\n",
    "                               \"q\", \"r\", \"s\", \"t\"])\n",
    "p_values[\"Statistic\"] = [u011_ttest[0], u101_ttest[0], u110_ttest[0], u111_ttest[0],\n",
    "                         a_ttest[0], b_ttest[0], c_ttest[0], d_ttest[0], e_ttest[0], f_ttest[0], g_ttest[0],\n",
    "                         h_ttest[0], i_ttest[0], j_ttest[0], k_ttest[0], l_ttest[0], m_ttest[0], n_ttest[0],\n",
    "                         o_ttest[0], p_ttest[0], q_ttest[0], r_ttest[0], s_ttest[0], t_ttest[0]]\n",
    "p_values[\"p-value\"] = [u011_ttest[1], u101_ttest[1], u110_ttest[1], u111_ttest[1],\n",
    "                       a_ttest[1], b_ttest[1], c_ttest[1], d_ttest[1], e_ttest[1], f_ttest[1], g_ttest[1],\n",
    "                       h_ttest[1], i_ttest[1], j_ttest[1], k_ttest[1], l_ttest[1], m_ttest[1], n_ttest[1],\n",
    "                       o_ttest[1], p_ttest[1], q_ttest[1], r_ttest[1], s_ttest[1], t_ttest[1]]\n",
    "result = []\n",
    "for index, row in p_values.iterrows():\n",
    "    if row[\"p-value\"] < 0.05:\n",
    "        if row[\"Statistic\"] < 0:\n",
    "            result.append(\"-\")\n",
    "        elif row.Statistic > 0:\n",
    "            result.append(\"+\")\n",
    "    else:\n",
    "        result.append(\"+/-\")\n",
    "p_values[\"Result\"] = result\n",
    "p_values[\"From rank order\"] = [\"+/-\", \"+/-\", \"+/-\", \"+\", \"+\", \"-\", \"+\", \"-\", \"+\",\n",
    "                               \"+/-\", \"+/-\", \"+\", \"+/-\", \"-\", \"+/-\", \"-\", \"+/-\",\n",
    "                               \"+/-\", \"+/-\", \"+\", \"+/-\", \"+\", \"+/-\", \"-\"]\n",
    "print(p_values)"
   ]
  }
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