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      "source": [
        "\n# Logo of the POT toolbox\n\n<div class=\"alert alert-info\"><h4>Note</h4><p>Example added in release: 0.8.2.</p></div>\n\nIn this example we plot the logo of the POT toolbox.\n\nThis logo is that it is done 100% in Python and generated using\nmatplotlib and plotting the solution of the EMD solver from POT.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
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      "source": [
        "# Author: Remi Flamary <remi.flamary@polytechnique.edu>\n#\n# License: MIT License\n\n# sphinx_gallery_thumbnail_number = 1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import numpy as np\nimport matplotlib.pyplot as pl\nimport ot"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Data for logo\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# Letter P\np1 = np.array(\n    [\n        [0, 6.0],\n        [0, 5],\n        [0, 4],\n        [0, 3],\n        [0, 2],\n        [0, 1],\n    ]\n)\np2 = np.array(\n    [\n        [1.5, 6],\n        [2, 4],\n        [2, 5],\n        [1.5, 3],\n        [0.5, 2],\n        [0.5, 1],\n    ]\n)\n\n# Letter O\no1 = np.array(\n    [\n        [0, 6.0],\n        [-1, 5],\n        [-1.5, 4],\n        [-1.5, 3],\n        [-1, 2],\n        [0, 1],\n    ]\n)\no2 = np.array(\n    [\n        [1, 6.0],\n        [2, 5],\n        [2.5, 4],\n        [2.5, 3],\n        [2, 2],\n        [1, 1],\n    ]\n)\n\n# Scaling and translation for letter O\no1[:, 0] += 6.4\no2[:, 0] += 6.4\no1[:, 0] *= 0.6\no2[:, 0] *= 0.6\n\n# Letter T\nt1 = np.array(\n    [\n        [-1, 6.0],\n        [-1, 5],\n        [0, 4],\n        [0, 3],\n        [0, 2],\n        [0, 1],\n    ]\n)\nt2 = np.array(\n    [\n        [1.5, 6.0],\n        [1.5, 5],\n        [0.5, 4],\n        [0.5, 3],\n        [0.5, 2],\n        [0.5, 1],\n    ]\n)\n\n# Translating the T\nt1[:, 0] += 7.1\nt2[:, 0] += 7.1\n\n# Concatenate all letters\nx1 = np.concatenate((p1, o1, t1), axis=0)\nx2 = np.concatenate((p2, o2, t2), axis=0)\n\n# Horizontal and vertical scaling\nsx = 1.0\nsy = 0.5\nx1[:, 0] *= sx\nx1[:, 1] *= sy\nx2[:, 0] *= sx\nx2[:, 1] *= sy"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Plot the logo (clear background)\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# Solve OT problem between the points\nM = ot.dist(x1, x2, metric=\"euclidean\")\nT = ot.emd([], [], M)\n\npl.figure(1, (3.5, 1.1))\npl.clf()\n# plot the OT plan\nfor i in range(M.shape[0]):\n    for j in range(M.shape[1]):\n        if T[i, j] > 1e-8:\n            pl.plot(\n                [x1[i, 0], x2[j, 0]],\n                [x1[i, 1], x2[j, 1]],\n                color=\"k\",\n                alpha=0.6,\n                linewidth=3,\n                zorder=1,\n            )\n# plot the samples\npl.plot(x1[:, 0], x1[:, 1], \"o\", markerfacecolor=\"C3\", markeredgecolor=\"k\")\npl.plot(x2[:, 0], x2[:, 1], \"o\", markerfacecolor=\"b\", markeredgecolor=\"k\")\n\n\npl.axis(\"equal\")\npl.axis(\"off\")\n\n# Save logo file\n# pl.savefig('logo.svg', dpi=150, transparent=True, bbox_inches='tight')\n# pl.savefig('logo.png', dpi=150, transparent=True, bbox_inches='tight')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Plot the logo (dark background)\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "pl.figure(2, (3.5, 1.1), facecolor=\"darkgray\")\npl.clf()\n# plot the OT plan\nfor i in range(M.shape[0]):\n    for j in range(M.shape[1]):\n        if T[i, j] > 1e-8:\n            pl.plot(\n                [x1[i, 0], x2[j, 0]],\n                [x1[i, 1], x2[j, 1]],\n                color=\"w\",\n                alpha=0.8,\n                linewidth=3,\n                zorder=1,\n            )\n# plot the samples\npl.plot(x1[:, 0], x1[:, 1], \"o\", markerfacecolor=\"w\", markeredgecolor=\"w\")\npl.plot(x2[:, 0], x2[:, 1], \"o\", markerfacecolor=\"w\", markeredgecolor=\"w\")\n\npl.axis(\"equal\")\npl.axis(\"off\")\n\n# Save logo file\n# pl.savefig('logo_dark.svg', dpi=150, transparent=True, bbox_inches='tight')\n# pl.savefig('logo_dark.png', dpi=150, transparent=True, bbox_inches='tight')"
      ]
    }
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