Add playground notebook

1 files changed, 177 insertions, 0 deletions

diff --git a/pyecsca/ec/formula_gen/formula_playground.ipynb b/pyecsca/ec/formula_gen/formula_playground.ipynb
new file mode 100644
index 0000000..e84f139
--- /dev/null
+++ b/pyecsca/ec/formula_gen/formula_playground.ipynb
@@ -0,0 +1,177 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pyecsca.ec.model import ShortWeierstrassModel, MontgomeryModel, TwistedEdwardsModel\n",
+    "from pyecsca.ec.formula_gen.test import load_efd_formulas, load_library_formulas\n",
+    "from pyecsca.ec.formula_gen.formula_graph import EFDFormulaGraph\n",
+    "from pyecsca.ec.formula_gen.fliparoo import generate_fliparood_formulas, greedy_fliparoo, recursive_fliparoo\n",
+    "import pyecsca.ec.formula_gen.metrics as metrics\n",
+    "from pyecsca.ec.formula_gen.switch_sign import generate_switched_formulas\n",
+    "from tqdm.notebook import tqdm"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Draw formula\n",
+    "coordinate_name = \"jacobian\"\n",
+    "model = ShortWeierstrassModel()\n",
+    "name = \"add-1998-cmo-2\"\n",
+    "formula = load_efd_formulas(coordinate_name,model)[name]\n",
+    "graph = EFDFormulaGraph()\n",
+    "graph.construct_graph(formula)\n",
+    "graph.draw()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Draw all formulas\n",
+    "coordinate_name = \"jacobian\"\n",
+    "model = ShortWeierstrassModel()\n",
+    "for name, formula in load_efd_formulas(coordinate_name,model).items():\n",
+    "    graph = EFDFormulaGraph()\n",
+    "    graph.construct_graph(formula)\n",
+    "    graph.draw(f\"{coordinate_name}:{name}.png\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Measure similarity of fliparood formulas\n",
+    "coordinate_name = \"jacobian\"\n",
+    "model = ShortWeierstrassModel()\n",
+    "name = \"add-1998-cmo-2\"\n",
+    "formula = load_efd_formulas(coordinate_name,model)[name]\n",
+    "for fliparood in generate_fliparood_formulas(formula):\n",
+    "    print(metrics.formula_similarity(formula,fliparood))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Greedy fliparoo to connect two formulas\n",
+    "coordinate_name = \"jacobian\"\n",
+    "model = ShortWeierstrassModel()\n",
+    "name = \"add-1998-cmo-2\"\n",
+    "formula = load_efd_formulas(coordinate_name,model)[name]\n",
+    "lib_formula = load_library_formulas()[\"add-openssl-z256\"]\n",
+    "metric = lambda x: metrics.formula_similarity(x,formula)[\"ivs\"]\n",
+    "flips, closest, sim = greedy_fliparoo(lib_formula,metric)\n",
+    "print(f\"Number of flips: {flips}, similarity: {sim}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate all fliparoos for all library formulas\n",
+    "depth = 2\n",
+    "fliparood = {}\n",
+    "libs = load_library_formulas()\n",
+    "for name, formula in tqdm(libs.items()):\n",
+    "    fliparood[name] = recursive_fliparoo(formula,depth)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\" Connect the generated formulas to efd \"\"\"\n",
+    "neighborhoods = fliparood \n",
+    "for name,formulas in fliparood.items():\n",
+    "    coordinates, model = libs[name].coordinate_model.name, libs[name].coordinate_model.curve_model\n",
+    "    similarities = {}\n",
+    "    for efd_name, efd_formula in load_efd_formulas(coordinates, model.__class__).items():\n",
+    "        metric = lambda x: metrics.formula_similarity(x,efd_formula)[\"ivs\"]\n",
+    "        flips, closest_fliparoo = max(formulas, key = lambda x: metric(x[1]))\n",
+    "        similarities[efd_name] = flips, metric(closest_fliparoo)\n",
+    "    closest_efd, (flips, sim) = max(similarities.items(), key = lambda x: x[1][1])\n",
+    "    print(f\"{name}. Closest match: {closest_efd}, flips={flips}, similarity={sim}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "switch_signed = {}\n",
+    "for name, fliparoo_neighborhood in tqdm(fliparood.items()):\n",
+    "    neighb = list()\n",
+    "    for flips,flip_f in fliparoo_neighborhood:\n",
+    "        neighb.extend(generate_switched_formulas(flip_f))\n",
+    "    switch_signed[name] = neighb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\" Connect the generated formulas to efd \"\"\"\n",
+    "neighborhoods = switch_signed \n",
+    "for name,formulas in tqdm(switch_signed.items()):\n",
+    "    coordinates, model = libs[name].coordinate_model.name, libs[name].coordinate_model.curve_model\n",
+    "    similarities = {}\n",
+    "    for efd_name, efd_formula in load_efd_formulas(coordinates, model.__class__).items():\n",
+    "        metric = lambda x: metrics.formula_similarity(x,efd_formula)[\"ivs\"]\n",
+    "        closest_switch_signed = max(formulas, key = metric)\n",
+    "        similarities[efd_name] = metric(closest_switch_signed)\n",
+    "    closest_efd, sim = max(similarities.items(), key = lambda x: x[1])\n",
+    "    print(f\"{name}. Closest match: {closest_efd}, similarity={sim}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env",
+   "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": "3.10.12"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}