mirror of
https://github.com/ltcptgeneral/IdealRMT-DecisionTrees.git
synced 2026-10-08 00:28:31 +00:00
save tree file t json format for future parsing
This commit is contained in:
alu committed
1 parent
78250f83fa
commit
39fd9a1862
1 file changed
+39
-59
+39
-59
@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 8,
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"id": "d5618056",
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"metadata": {},
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"outputs": [],
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@@ -15,12 +15,13 @@
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"from sklearn.tree import export_graphviz\n",
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"import pydotplus\n",
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"from matplotlib import pyplot as plt\n",
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"from labels import mac_to_label"
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"from labels import mac_to_label\n",
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"import json"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 24,
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"id": "d336971a",
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"metadata": {},
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"outputs": [],
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@@ -32,9 +33,29 @@
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"\n",
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"# output the tree\n",
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"def get_lineage(tree, feature_names, file):\n",
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"\n",
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" threshold = dt.tree_.threshold\n",
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" features = [feature_names[i] for i in dt.tree_.feature]\n",
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" proto = []\n",
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" src = []\n",
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" dst = []\n",
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" for i, fe in enumerate(features):\n",
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" if fe == 'proto':\n",
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" proto.append(threshold[i])\n",
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" elif fe == 'src':\n",
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" if threshold[i] != -2.0:\n",
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" src.append(threshold[i])\n",
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" else:\n",
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" dst.append(threshold[i])\n",
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" proto = [int(i) for i in proto]\n",
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" src = [int(i) for i in src]\n",
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" dst = [int(i) for i in dst]\n",
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" proto.sort()\n",
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" src.sort()\n",
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" dst.sort()\n",
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"\n",
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" data = {\"proto\": proto, \"src\":src, \"dst\": dst, \"paths\": []}\n",
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"\n",
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" left = tree.tree_.children_left\n",
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" right = tree.tree_.children_right\n",
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" threshold = tree.tree_.threshold\n",
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@@ -64,29 +85,25 @@
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" return recurse(left, right, parent, lineage)\n",
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"\n",
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" for j, child in enumerate(idx):\n",
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" clause = ' when '\n",
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" clause = []\n",
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" for node in recurse(left, right, child):\n",
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" if len(str(node)) < 3:\n",
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" continue\n",
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" i = node\n",
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" \n",
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" if i[1] == 'l':\n",
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" sign = le\n",
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" else:\n",
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" sign = g\n",
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" clause = clause + i[3] + sign + str(i[2]) + ' and '\n",
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" \n",
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" # wirte the node information into text file\n",
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" if i[1] == \"l\":\n",
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" clause.append({\"feature\": i[3], \"operation\": \"<=\", \"value\": i[2]})\n",
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" \n",
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" a = list(value[node][0])\n",
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" ind = a.index(max(a))\n",
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" clause = clause[:-4] + ' then ' + str(ind)\n",
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" file.write(clause)\n",
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" file.write(\";\\n\")\n"
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" clause = {\"conditions\": clause, \"classification\": ind}\n",
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" data[\"paths\"].append(clause)\n",
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"\n",
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" return data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 16,
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"id": "b96f3403",
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"metadata": {},
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"outputs": [
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@@ -130,7 +147,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 25,
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"id": "7f36344d",
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"metadata": {},
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"outputs": [],
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@@ -138,39 +155,10 @@
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"class_names=list(mac_to_label.values())\n",
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"feature_names=['proto','src','dst']\n",
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"\n",
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"# output the tree in a text file, write it\n",
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"threshold = dt.tree_.threshold\n",
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"features = [feature_names[i] for i in dt.tree_.feature]\n",
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"proto = []\n",
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"src = []\n",
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"dst = []\n",
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"for i, fe in enumerate(features):\n",
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" \n",
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" if fe == 'proto':\n",
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" proto.append(threshold[i])\n",
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" elif fe == 'src':\n",
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" if threshold[i] != -2.0:\n",
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" src.append(threshold[i])\n",
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" else:\n",
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" dst.append(threshold[i])\n",
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"proto = [int(i) for i in proto]\n",
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"src = [int(i) for i in src]\n",
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"dst = [int(i) for i in dst]\n",
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"proto.sort()\n",
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"src.sort()\n",
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"dst.sort()\n",
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"tree = open(outputfile,\"w+\")\n",
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"tree.write(\"proto = \")\n",
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"tree.write(str(proto))\n",
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"tree.write(\";\\n\")\n",
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"tree.write(\"src = \")\n",
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"tree.write(str(src))\n",
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"tree.write(\";\\n\")\n",
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"tree.write(\"dst = \")\n",
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"tree.write(str(dst))\n",
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"tree.write(\";\\n\")\n",
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"get_lineage(dt,feature_names,tree)\n",
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"tree.close()"
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"file = open(outputfile, \"w+\")\n",
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"lineage = get_lineage(dt,feature_names,file)\n",
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"file.write(json.dumps(lineage))\n",
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"file.close()"
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]
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},
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{
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@@ -181,7 +169,7 @@
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"outputs": [
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{
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"data": {
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"image/png": 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truncated
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"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<Figure size 2500x2000 with 1 Axes>"
|
||||
]
|
||||
@@ -194,14 +182,6 @@
|
||||
"fig = plt.figure(figsize=(25,20))\n",
|
||||
"_ = plot_tree(dt, feature_names=feature_names, class_names=class_names, filled=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "03ef1012",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
||||
Reference in new issue
Block a user