Smoo

Notebooks_Unused/n_search_fail.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "47f4a073",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%reload_ext autoreload\n",
+        "%autoreload 2"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "282a714d",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from cereeberus import Interleave, MapperGraph, ReebGraph\n",
+        "\n",
+        "import cereeberus.data.ex_reebgraphs as ex_rg\n",
+        "import cereeberus.data.ex_mappergraphs as ex_mg"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "e191f088",
+      "metadata": {},
+      "source": [
+        "# Create torus and line mappers of mismatched heights"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "d1a6c618",
+      "metadata": {},
+      "source": [
+        "### It works when the difference is 1"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "6c6b8ae9",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "line = ex_mg.line(a=0, b= 16)\n",
+        "torus = ex_mg.torus(a=0, b =2, c = 13, d = 17)\n",
+        "myInt = Interleave(torus, line)\n",
+        "result = myInt.fit()\n",
+        "dist_result = myInt.dist_fit() # dist_fit function optimizes with the distance matrix\n",
+        "print(f\"Interleaving distance: {result}\")\n",
+        "print(f\"Interleaving distance (with dist_fit): {dist_result}\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "30459cf0",
+      "metadata": {},
+      "source": [
+        "### But fails when the difference is more than 1"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "ee3dea41",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "line = ex_mg.line(a =0, b= 16)\n",
+        "torus = ex_mg.torus(a=0, b =2, c = 13, d = 18)\n",
+        "myInt = Interleave(torus, line)\n",
+        "result = myInt.fit()\n",
+        "dist_result = myInt.dist_fit() # dist_fit function optimizes with the distance matrix\n",
+        "print(f\"Interleaving distance: {result}\")\n",
+        "print(f\"Interleaving distance (with dist_fit): {dist_result}\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "b442c31a",
+      "metadata": {},
+      "source": [
+        "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."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "c17be785",
+      "metadata": {},
+      "source": []
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "interleavingenv",
+      "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": "3.12.3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}

Notebooks_Unused/sandbox_fixing_optimization.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "3d7c8bc8",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%reload_ext autoreload\n",
+        "%autoreload 2"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "a632ce73",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from cereeberus import Interleave, MapperGraph, Assignment\n",
+        "import cereeberus.data.ex_mappergraphs as ex_mg\n",
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import networkx as nx"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "44844a7b",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "mg1 = ex_mg.line(0, 20)\n",
+        "mg2 = ex_mg.torus(0, 2, 17, 18)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "0657e22b",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "myInt = Interleave(mg1, mg2)\n",
+        "myInt.fit(verbose=True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "6a5a4786",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from cereeberus import ReebGraph\n",
+        "import numpy as np"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "88cb17ae",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Example point cloud (you can replace this with your own)\n",
+        "points = np.random.rand(500, 3)  # 500 points in 3D\n",
+        "\n",
+        "# Define a scalar function on these points — say, height (z-coordinate)\n",
+        "values = points[:, 2]\n",
+        "\n",
+        "# Build and compute the Reeb graph\n",
+        "rg = ReebGraph()\n"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "interleavingenv",
+      "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": "3.12.3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}