{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Interpolation nodes in 2D"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "import matplotlib.pyplot as pt\n",
        "import numpy as np\n",
        "import modepy as mp\n",
        "\n",
        "nodes = mp.warp_and_blend_nodes(2, 10)\n",
        "pt.plot(nodes[0], nodes[1], \"x\")\n",
        "\n",
        "tri = np.array([(-1, -1), (1, -1), (-1, 1), (-1, -1)]).T\n",
        "pt.plot(nodes[0], nodes[1], \"x\")\n",
        "pt.plot(tri[0], tri[1], \"-b\")\n",
        "pt.gca().set_aspect(\"equal\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.7.4+"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}