sync bench with polaris - compression tests

bench/qc_simulation/analysis/Notes.md

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+# Benchmark analysis scripts
+## Usage
+### Compression tests
+
+1. `compression_scaling_analysis` - print nicely formatted data from each json in glob provided as first argument
+2. `Compression_quality.ipynb`  - notebook to analyze quality and scaling of compression
+
+## Tracktable maxcut_qaoa instances
+
+M29
+`data/preprocess/qaoa_maxcut/
+
+ - p=1 N=256
+ - p=3 N=64
+ - p=5 N=42
+ - p=6 N=
+
+With compression:

bench/qc_simulation/analysis/compression_project_repo_link

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+../../../../../quantum-simulation-compressed/plots

bench/qc_simulation/analysis/run_compression.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "filename = '../data/circuits/qaoa_maxcut_fixangle/3regfix_N30_p5.jsonterms'\n",
+    "assert Path(filename).is_file()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using file ../data/circuits/qaoa_maxcut_fixangle/3regfix_N30_p5.jsonterms. hostname: x3006c0s19b0n0. Python: Python 3.10.9.\n"
+     ]
+    }
+   ],
+   "source": [
+    "!echo \"Using file {filename}. hostname: $(hostname). Python: $(python --version).\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pkgenv = \"PYTHONPATH=/home/danlkv/QTensor:/home/danlkv/QTensor/qtree\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2023-11-03 05:58:45.525317: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE3 SSE4.1 SSE4.2 AVX AVX2 FMA\n",
+      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "/home/danlkv/QTensor/qtensor/compression/szx/src\n",
+      "\u001b[1mNAME\u001b[0m\n",
+      "    main.py\n",
+      "\n",
+      "\u001b[1mSYNOPSIS\u001b[0m\n",
+      "    main.py \u001b[4mCOMMAND\u001b[0m\n",
+      "\n",
+      "\u001b[1mCOMMANDS\u001b[0m\n",
+      "    \u001b[1m\u001b[4mCOMMAND\u001b[0m\u001b[0m is one of the following:\n",
+      "\n",
+      "     echo\n",
+      "       Simple mapper that just echoes stuff\n",
+      "\n",
+      "     estimate\n",
+      "       Estimate the parameters of a simulator\n",
+      "\n",
+      "     generate\n",
+      "\n",
+      "     preprocess\n",
+      "\n",
+      "     simulate\n",
+      "       Simulate the quantum circuit\n"
+     ]
+    }
+   ],
+   "source": [
+    "!export {pkgenv}; ../main.py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Preprocess"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "in_preprocessed = \"../data/preprocess/compress/qaoa_e/slicesvar/3regfix_N30_p5.jsonterms_Orgreedy_0.02_20_M27\"\n",
+    "assert Path(preprocess).is_file()\n",
+    "import sys\n",
+    "sys.path.append('../')\n",
+    "sys.path.append('/home/danlkv/QTensor/qtree')\n",
+    "sys.path.append('/home/danlkv/QTensor')\n",
+    "from main import Main"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3regfix_N30_p5.jsonterms_Orgreedy_0.02_20_M26\n",
+      "3regfix_N30_p5.jsonterms_Orgreedy_0.02_20_M27\n",
+      "3regfix_N30_p5.jsonterms_Orgreedy_0.02_20_M28\n",
+      "3regfix_N30_p5.jsonterms_Orgreedy_0.02_20_M29\n",
+      "index.csv\n"
+     ]
+    }
+   ],
+   "source": [
+    "out_dir = \"../data/preprocess/compress/qaoa_e/slicesvar/\"\n",
+    "!ls {out_dir}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "zsh:export:1: not valid in this context: {pkgenv}\n"
+     ]
+    }
+   ],
+   "source": [
+    "out_dir = '../data/preprocess/compress/qaoa_e/slicesvar2/3regfix_N30_p5.jsonterms_Orgreedy_0.02_20_M27'\n",
+    "Main.simulate(in_preprocessed, 'qtensor_energy', M='26,27,28,29', S=1, after_slice='TD-reuse')\n",
+    "!export {pkgenv}; ./main.py simulate {preprocess} data/preprocess/compress/qaoa_e/slicesvar/\\\\{in_file\\}_O\\{O\\}_M\\{M\\} --O rgreedy_0.02_20 --sim=qtensor_energy --M 26,27,28,29 --S 1 --after_slice=TD-reuse"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}