{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# Example usage\n",
    "\n",
    "The main goal of `codino` is to convert amino acid (AA) frequencies to codon design (CD), and vice versa."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "source": [
    "import codino\n",
    "\n",
    "print(codino.__version__)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1.1\n"
     ]
    }
   ],
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Users should initialise a `Converter`."
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "outputs": [],
   "source": [
    "from codino.process import Converter\n",
    "\n",
    "c = Converter()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "The two useful methods within a `Converter` are `cd_to_aa()` and `aa_to_cd()`, which converts a CD to AA frequencies and vice versa."
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "outputs": [
    {
     "data": {
      "text/plain": "True"
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# input the expected nucleotide frequencies at each position\n",
    "c.cd_to_aa(first={\"A\": 1}, second={\"T\": 1}, third={\"G\": 1})\n",
    "\n",
    "# input the desired AA frequencies\n",
    "first, second, third = c.aa_to_cd(aa={'D': 0.4, 'N': 0.6})\n",
    "\n",
    "# you can check the output by converting the codon design back to AA frequencies\n",
    "c.cd_to_aa(first, second, third) == {'D': 0.4, 'N': 0.6}"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "For more complex examples, the conversion of the AA frequencies to a CD will be an estimate."
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "outputs": [
    {
     "data": {
      "text/plain": "False"
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_aa = {'A': 0.1771,\n",
    "          'D': 0.208131,\n",
    "          'E': 0.18456899999999998,\n",
    "          'I': 0.031694,\n",
    "          'K': 0.055131,\n",
    "          'M': 0.028106000000000003,\n",
    "          'N': 0.062169,\n",
    "          'T': 0.0529,\n",
    "          'V': 0.2002}\n",
    "\n",
    "first, second, third = c.aa_to_cd(aa=exp_aa)\n",
    "pred_aa = c.cd_to_aa(first, second, third)\n",
    "\n",
    "pred_aa == exp_aa"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "In this case, it can be helpful to obtain the error between the expected and predicted AA frequencies."
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average error per AA ==> 0.0055103958222222325\n",
      "Total error across AAs ==> 0.049593562400000096\n"
     ]
    }
   ],
   "source": [
    "errors = [abs(pred_aa[a] - exp_aa[a]) for a in exp_aa]\n",
    "\n",
    "print(f'Average error per AA ==> {sum(errors)/len(errors)}')\n",
    "\n",
    "print(f'Total error across AAs ==> {sum(errors)}')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
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