Biased Coin implementation in Python

biased coin python.ipynb

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   "source": [
    "import random"
   ]
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   "source": [
    "treatment_groups = [0 for i in range(5)]"
   ]
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   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(75*5):\n",
    "    g = random.choice(list(range(5)))\n",
    "    treatment_groups[g] += 1"
   ]
  },
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   "cell_type": "code",
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   "metadata": {},
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     "data": {
      "text/plain": [
       "[72, 74, 88, 70, 71]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "treatment_groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "treatment_groups = [0 for i in range(5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def biased_coin(groups, current_assignment):\n",
    "    total_weight = sum([75-i for i in current_assignment])\n",
    "    weights = [(75-i)/total_weight for i in current_assignment]\n",
    "    return random.choices(list(range(5)), weights)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "treatment_groups = [0 for i in range(5)]\n",
    "for i in range(75*5):\n",
    "    g = biased_coin(list(range(5)), treatment_groups)\n",
    "    treatment_groups[g] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[75, 75, 75, 75, 75]"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "treatment_groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "treatment_groups = [0 for i in range(5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "def biased_coin2(groups, current_assignment):\n",
    "    total_weight = sum([75-i for i in current_assignment])\n",
    "    weights = [75-i for i in current_assignment]\n",
    "    cum_weights = [sum(weights[:i+1]) for i in range(5)]\n",
    "    i = random.randint(0, total_weight)\n",
    "    for j in range(5):\n",
    "        if i <= cum_weights[j]:\n",
    "            return j"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "treatment_groups = [0 for i in range(5)]\n",
    "for i in range(75*5):\n",
    "    g = biased_coin2(list(range(5)), treatment_groups)\n",
    "    treatment_groups[g] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[75, 75, 75, 75, 75]"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "treatment_groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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