MNT: quick notebook to test MRS during development

Author: Lucas-Prates

test_mrs.ipynb

@@ -0,0 +1,176 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Quick test notebook for MRS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
+   "source": [
+    "# We import these lines for debugging purposes, only works on Jupyter Notebook\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from rocketpy.simulation.multivariate_rejection_sampler import MultivariateRejectionSampler\n",
+    "from rocketpy import MonteCarlo\n",
+    "from scipy.stats import norm\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "montecarlo_filepath = \"docs/notebooks/monte_carlo_analysis/monte_carlo_analysis_outputs/monte_carlo_class_example\"\n",
+    "mrs_filepath = \"mrs\"\n",
+    "old_mass_pdf = norm(15.426, 0.5).pdf\n",
+    "new_mass_pdf = norm(15, 0.5) .pdf\n",
+    "distribution_dict = {\n",
+    "    \"mass\": (old_mass_pdf, new_mass_pdf),\n",
+    "}\n",
+    "mrs = MultivariateRejectionSampler(\n",
+    "    montecarlo_filepath=montecarlo_filepath,\n",
+    "    mrs_filepath=mrs_filepath,\n",
+    "    distribution_dict=distribution_dict,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "107.0"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mrs.expected_sample_size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mrs.sample()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The following input file was imported: mrs.inputs.txt\n",
+      "A total of 109 simulations results were loaded from the following output file: mrs.outputs.txt\n",
+      "\n",
+      "The following error file was imported: mrs.errors.txt\n"
+     ]
+    }
+   ],
+   "source": [
+    "mrs_results = MonteCarlo(mrs_filepath, None, None, None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "A total of 109 simulations results were loaded from the following output file: mrs.outputs.txt\n",
+      "\n",
+      "The following input file was imported: mrs.inputs.txt\n",
+      "The following error file was imported: mrs.errors.txt\n"
+     ]
+    }
+   ],
+   "source": [
+    "mrs_results.import_results()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "MRS mass mean after resample: 15.029610376989238\n",
+      "MRS mass std after resample: 0.5213162519453568\n"
+     ]
+    }
+   ],
+   "source": [
+    "mrs_mass_list = []\n",
+    "for single_input_dict in mrs_results.inputs_log:\n",
+    "    mrs_mass_list.append(single_input_dict[\"mass\"])\n",
+    "\n",
+    "print(f\"MRS mass mean after resample: {np.mean(mrs_mass_list)}\")\n",
+    "print(f\"MRS mass std after resample: {np.std(mrs_mass_list)}\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "testnotebook",
+   "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": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}