Merge pull request #5 from ltcptgeneral/Parser

Fix range bug in TreeCompress, update parser to autofail non-singular…

CompressedTreeParser.ipynb

@@ -0,0 +1,128 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "938dec51",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import argparse\n",
+    "from sklearn.tree import DecisionTreeClassifier, plot_tree, _tree\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from sklearn.tree import export_graphviz\n",
+    "import pydotplus\n",
+    "from matplotlib import pyplot as plt\n",
+    "from labels import mac_to_label\n",
+    "import json\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "442624c7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Set1 = pd.read_csv('data.csv').values.tolist()\n",
+    "X = [i[0:3] for i in Set1]\n",
+    "Y =[i[3] for i in Set1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "12ad454d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "predict_Yt = []\n",
+    "with open('compressed_tree.json', 'r') as file:\n",
+    "    data = json.load(file)\n",
+    "    classes = data[\"classes\"]\n",
+    "    for x in X:\n",
+    "        counter = 0\n",
+    "        class_set = []\n",
+    "        for feature in reversed(data['layers']): #Have to reverse this list due to structure of the data.csv file and how it aligns with the compressed tree layers\n",
+    "            for node in data['layers'][feature]:\n",
+    "                if node['min'] is None:\n",
+    "                    if x[counter] < node['max']:\n",
+    "                        class_set.append(node['classes'])\n",
+    "                        break #is this an issue?\n",
+    "                    else:\n",
+    "                        continue\n",
+    "                elif node['max'] is None:\n",
+    "                    if node['min'] < x[counter]:\n",
+    "                        class_set.append(node['classes'])\n",
+    "                        break #is this an issue?\n",
+    "                    else:\n",
+    "                        continue\n",
+    "                elif node['min'] < x[counter] and x[counter] < node['max']:\n",
+    "                    class_set.append(node['classes'])\n",
+    "                    break #is this an issue?\n",
+    "\n",
+    "            counter += 1\n",
+    "        result = set(class_set[0])\n",
+    "        for s in class_set[1:]:\n",
+    "            result.intersection_update(s)\n",
+    "\n",
+    "        #predict_Yt.append(list(result))\n",
+    "        #print(result)\n",
+    "        if len(result) == 1:\n",
+    "            prediction = list(result)[0]\n",
+    "            pred_class = classes[prediction]\n",
+    "            predict_Yt.append(pred_class)\n",
+    "        else:\n",
+    "            predict_Yt.append(None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "8b4c56b6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.8448217242194891\n"
+     ]
+    }
+   ],
+   "source": [
+    "correct = 0\n",
+    "for i in range(len(Y)):\n",
+    "    prediction = predict_Yt[i]\n",
+    "    if prediction != None and Y[i] == prediction:\n",
+    "        correct += 1\n",
+    "\n",
+    "print(correct / len(Y))"
+   ]
+  }
+ ],
+ "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": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

TreeCompress.ipynb

@@ -109,13 +109,13 @@
     "\t\tvalue = condition[\"value\"]\n",
     "\n",
     "\t\t# move the min/max for the corresponding feature in compressed\n",
-    "\t\tif operation == \"<=\" and compressed[feature][\"min\"] is None:\n",
+    "\t\tif operation == \"<=\" and compressed[feature][\"max\"] is None:\n",
     "\t\t\tcompressed[feature][\"max\"] = value\n",
-    "\t\telif operation == \">\" and compressed[feature][\"max\"] is None:\n",
+    "\t\telif operation == \">\" and compressed[feature][\"min\"] is None:\n",
     "\t\t\tcompressed[feature][\"min\"] = value\n",
-    "\t\telif operation == \"<=\" and value < compressed[feature][\"min\"]:\n",
+    "\t\telif operation == \"<=\" and value < compressed[feature][\"max\"]:\n",
     "\t\t\tcompressed[feature][\"max\"] = value\n",
-    "\t\telif operation == \">\" and value > compressed[feature][\"max\"]:\n",
+    "\t\telif operation == \">\" and value > compressed[feature][\"min\"]:\n",
     "\t\t\tcompressed[feature][\"min\"] = value\n",
     "\n",
     "\tpath[\"compressed\"] = compressed"

TreeToRMT.ipynb

@@ -263,7 +263,7 @@
       "[1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
       "id mapping: \n",
       "[['dst_range', 'dst_meta'], ['src_range', 'src_meta'], ['protocl_range', 'protocl_meta'], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]\n",
-      "TCAM bits: 3584\n",
+      "TCAM bits: 3520\n",
       "RAM bits:  522\n"
      ]
     }