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More cleanup with copilot
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‎Notebooks_Unused/experiments/experiments_with_line_torus/run_exprimetns_loop_line.ipynb‎

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‎Notebooks_Unused/n_search_fail.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "47f4a073",
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"metadata": {},
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"outputs": [],
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"source": [
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"%reload_ext autoreload\n",
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"%autoreload 2"
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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": 6,
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"id": "282a714d",
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"metadata": {},
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"outputs": [],
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"source": [
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"from cereeberus import Interleave, MapperGraph, ReebGraph\n",
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"\n",
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"import cereeberus.data.ex_reebgraphs as ex_rg\n",
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"import cereeberus.data.ex_mappergraphs as ex_mg"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e191f088",
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"metadata": {},
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"source": [
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"# Create torus and line mappers of mismatched heights"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d1a6c618",
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"metadata": {},
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"source": [
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"### It works when the differnce is 1"
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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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"id": "6c6b8ae9",
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"metadata": {},
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"outputs": [
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"cells": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Interleaving distance: 3\n",
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"Interleaving distance (with dist_fit): 3\n"
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]
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}
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],
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"source": [
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"line = ex_mg.line(a=0, b= 16)\n",
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"torus = ex_mg.torus(a=0, b =2, c = 13, d = 17)\n",
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"myInt = Interleave(torus, line)\n",
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"result = myInt.fit()\n",
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"dist_result = myInt.dist_fit() # dist_fit function optimizes with the distance matrix\n",
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"print(f\"Interleaving distance: {result}\")\n",
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"print(f\"Interleaving distance (with dist_fit): {dist_result}\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "30459cf0",
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"metadata": {},
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"source": [
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"### But fails when the difference is more than 1"
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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": 9,
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"id": "ee3dea41",
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"metadata": {},
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"outputs": [
4+
"cell_type": "code",
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"execution_count": null,
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"id": "47f4a073",
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"metadata": {},
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"outputs": [],
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"source": [
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"%reload_ext autoreload\n",
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"%autoreload 2"
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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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"id": "282a714d",
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"metadata": {},
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"outputs": [],
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"source": [
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"from cereeberus import Interleave, MapperGraph, ReebGraph\n",
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"\n",
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"import cereeberus.data.ex_reebgraphs as ex_rg\n",
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"import cereeberus.data.ex_mappergraphs as ex_mg"
25+
]
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},
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{
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"cell_type": "markdown",
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"id": "e191f088",
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"metadata": {},
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"source": [
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"# Create torus and line mappers of mismatched heights"
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]
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},
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{
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"ename": "KeyError",
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"evalue": "17",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[9], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m torus \u001b[38;5;241m=\u001b[39m ex_mg\u001b[38;5;241m.\u001b[39mtorus(a\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m, b \u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m, c \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m13\u001b[39m, d \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m18\u001b[39m)\n\u001b[1;32m 3\u001b[0m myInt \u001b[38;5;241m=\u001b[39m Interleave(torus, line)\n\u001b[0;32m----> 4\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mmyInt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 5\u001b[0m dist_result \u001b[38;5;241m=\u001b[39m myInt\u001b[38;5;241m.\u001b[39mdist_fit() \u001b[38;5;66;03m# dist_fit function optimizes with the distance matrix\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInterleaving distance: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mresult\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
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"File \u001b[0;32m~/Library/CloudStorage/OneDrive-MichiganStateUniversity/Documents/Research/Projects/Interleaving_to_ML/ceREEBerus/cereeberus/cereeberus/distance/interleave.py:66\u001b[0m, in \u001b[0;36mInterleave.fit\u001b[0;34m(self, pulp_solver, verbose, max_n_for_error)\u001b[0m\n\u001b[1;32m 64\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m min_n \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m checked_results:\n\u001b[1;32m 65\u001b[0m myAssgn \u001b[38;5;241m=\u001b[39m Assignment(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mF, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mG, n\u001b[38;5;241m=\u001b[39mmin_n)\n\u001b[0;32m---> 66\u001b[0m prob_status \u001b[38;5;241m=\u001b[39m \u001b[43mmyAssgn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptimize\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpulp_solver\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpulp_solver\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 68\u001b[0m checked_results[min_n] \u001b[38;5;241m=\u001b[39m (prob_status, myAssgn)\n\u001b[1;32m 70\u001b[0m prob_status, myAssgn \u001b[38;5;241m=\u001b[39m checked_results[min_n]\n",
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"File \u001b[0;32m~/Library/CloudStorage/OneDrive-MichiganStateUniversity/Documents/Research/Projects/Interleaving_to_ML/ceREEBerus/cereeberus/cereeberus/distance/interleave.py:1816\u001b[0m, in \u001b[0;36mAssignment.optimize\u001b[0;34m(self, pulp_solver)\u001b[0m\n\u001b[1;32m 1804\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21moptimize\u001b[39m(\u001b[38;5;28mself\u001b[39m, pulp_solver \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m 1805\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Uses the ILP to find the best interleaving distance bound, returns the loss value found. Further, it stores the optimal phi and psi maps which can be returned using the ``self.phi`` and ``self.psi`` attributes respectively.\u001b[39;00m\n\u001b[1;32m 1806\u001b[0m \u001b[38;5;124;03m This function requires the `pulp` package to be installed.\u001b[39;00m\n\u001b[1;32m 1807\u001b[0m \u001b[38;5;124;03m \u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1813\u001b[0m \u001b[38;5;124;03m \u001b[39;00m\n\u001b[1;32m 1814\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1816\u001b[0m map_dict, prob_status \u001b[38;5;241m=\u001b[39m \u001b[43msolve_ilp\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpulp_solver\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mpulp_solver\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1818\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m prob_status \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mOptimal\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 1819\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
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"File \u001b[0;32m~/Library/CloudStorage/OneDrive-MichiganStateUniversity/Documents/Research/Projects/Interleaving_to_ML/ceREEBerus/cereeberus/cereeberus/distance/ilp.py:169\u001b[0m, in \u001b[0;36msolve_ilp\u001b[0;34m(myAssgn, pulp_solver, verbose)\u001b[0m\n\u001b[1;32m 167\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m up_or_down \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mup\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;66;03m#NOTE: the change in block indices\u001b[39;00m\n\u001b[1;32m 168\u001b[0m bou_n \u001b[38;5;241m=\u001b[39m myAssgn\u001b[38;5;241m.\u001b[39mB_up(other_map, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mn\u001b[39m\u001b[38;5;124m'\u001b[39m)[block]\u001b[38;5;241m.\u001b[39mget_array()\n\u001b[0;32m--> 169\u001b[0m bou_0 \u001b[38;5;241m=\u001b[39m \u001b[43mmyAssgn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mB_up\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstarting_map\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m0\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[43mblock\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241m.\u001b[39mget_array()\n\u001b[1;32m 170\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m starting_map \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mF\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 171\u001b[0m map_V \u001b[38;5;241m=\u001b[39m myAssgn\u001b[38;5;241m.\u001b[39mphi(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m0\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mV\u001b[39m\u001b[38;5;124m'\u001b[39m)[block\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m]\u001b[38;5;241m.\u001b[39mget_array()\n",
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"File \u001b[0;32m~/Library/CloudStorage/OneDrive-MichiganStateUniversity/Documents/Research/Projects/Interleaving_to_ML/ceREEBerus/cereeberus/cereeberus/distance/labeled_blocks.py:539\u001b[0m, in \u001b[0;36mLabeledBlockMatrix.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 529\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__getitem__\u001b[39m(\u001b[38;5;28mself\u001b[39m, key):\n\u001b[1;32m 530\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 531\u001b[0m \u001b[38;5;124;03m Get the i'th block matrix.\u001b[39;00m\n\u001b[1;32m 532\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 537\u001b[0m \u001b[38;5;124;03m The item from the block matrix.\u001b[39;00m\n\u001b[1;32m 538\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 539\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mblocks\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m\n",
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"\u001b[0;31mKeyError\u001b[0m: 17"
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]
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"cell_type": "markdown",
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"id": "d1a6c618",
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"metadata": {},
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"source": [
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"### It works when the difference is 1"
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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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"id": "6c6b8ae9",
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"metadata": {},
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"outputs": [],
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"source": [
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"line = ex_mg.line(a=0, b= 16)\n",
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"torus = ex_mg.torus(a=0, b =2, c = 13, d = 17)\n",
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"myInt = Interleave(torus, line)\n",
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"result = myInt.fit()\n",
54+
"dist_result = myInt.dist_fit() # dist_fit function optimizes with the distance matrix\n",
55+
"print(f\"Interleaving distance: {result}\")\n",
56+
"print(f\"Interleaving distance (with dist_fit): {dist_result}\")"
57+
]
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},
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{
60+
"cell_type": "markdown",
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"id": "30459cf0",
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"metadata": {},
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"source": [
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"### But fails when the difference is more than 1"
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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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"id": "ee3dea41",
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"metadata": {},
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"outputs": [],
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"source": [
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"line = ex_mg.line(a =0, b= 16)\n",
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"torus = ex_mg.torus(a=0, b =2, c = 13, d = 18)\n",
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"myInt = Interleave(torus, line)\n",
77+
"result = myInt.fit()\n",
78+
"dist_result = myInt.dist_fit() # dist_fit function optimizes with the distance matrix\n",
79+
"print(f\"Interleaving distance: {result}\")\n",
80+
"print(f\"Interleaving distance (with dist_fit): {dist_result}\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b442c31a",
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"metadata": {},
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"source": [
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"I checked the code and I think the problem is in the boundary matrix computation. Which affects the edge-vertex parallelogram checks. Tried fixing, but haven't figured it out yet."
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]
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},
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{
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"cell_type": "markdown",
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"id": "c17be785",
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"metadata": {},
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "interleavingenv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
96115
}
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],
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"source": [
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"line = ex_mg.line(a =0, b= 16)\n",
100-
"torus = ex_mg.torus(a=0, b =2, c = 13, d = 18)\n",
101-
"myInt = Interleave(torus, line)\n",
102-
"result = myInt.fit()\n",
103-
"dist_result = myInt.dist_fit() # dist_fit function optimizes with the distance matrix\n",
104-
"print(f\"Interleaving distance: {result}\")\n",
105-
"print(f\"Interleaving distance (with dist_fit): {dist_result}\")"
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]
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},
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{
109-
"cell_type": "markdown",
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"id": "b442c31a",
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"metadata": {},
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"source": [
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"I checked the code and I think the problem is in the boundary matrix computation. Which affects the edge-vertex parallelogram checks. Tried fixing, but haven't figured it out yet."
114-
]
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},
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{
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"cell_type": "markdown",
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"id": "c17be785",
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"metadata": {},
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "interleavingenv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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"nbformat": 4,
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"nbformat_minor": 5
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}

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