new initialization method

EvolutionaryAlgorithm/ea_tools.ipynb

@@ -0,0 +1,74 @@
+{
+ "nbformat": 4,
+ "nbformat_minor": 2,
+ "metadata": {
+  "language_info": {
+   "name": "python",
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   }
+  },
+  "orig_nbformat": 2,
+  "file_extension": ".py",
+  "mimetype": "text/x-python",
+  "name": "python",
+  "npconvert_exporter": "python",
+  "pygments_lexer": "ipython3",
+  "version": 3
+ },
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Statistical Tools"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "* Helper function to calculate the wheel of fortune"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def wheel_of_fortune(rank_i,n):\n",
+    "    return rank_i / (0.5 * n * (n + 1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def wheel_of_fortune_selection(items: list, item_scores:list):\n",
+    "    ordering = np.argsort(item_scores)\n",
+    "    ordering = ordering + 1\n",
+    "\n",
+    "    wheel_weights = wheel_of_fortune(ordering, len(ordering))\n",
+    "\n",
+    "    return np.random.choice(items, p=wheel_weights)\n"
+   ]
+  }
+ ]
+}

EvolutionaryAlgorithm/ea_tools.py

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+#!/usr/bin/env python3
+# coding: utf-8
+
+# # Statistical Tools
+
+import numpy as np
+
+
+# * Helper function to calculate the wheel of fortune
+
+def wheel_of_fortune(rank_i,n):
+    return rank_i / (0.5 * n * (n + 1))
+
+
+def wheel_of_fortune_selection(items: list, item_scores:list):
+    ordering = np.argsort(item_scores)
+    ordering = ordering + 1
+
+    wheel_weights = wheel_of_fortune(ordering, len(ordering))
+
+    return np.random.choice(items, p=wheel_weights)
+