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        "\n# Using describe to evaluate the integrity of your visualization\n\nThe downside to using dimensionality reduction to visualize your data is that\nsome variance will likely be removed. To help get a sense for the integrity of your low\ndimensional visualizations, we built the `describe` function, which computes\nthe covariance (samples by samples) of both the raw and reduced datasets, and\nplots their correlation.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      },
      "outputs": [],
      "source": [
        "# Code source: Andrew Heusser\n# License: MIT\n\n# import\nimport hypertools as hyp\nimport numpy as np\n\n# load example data\ngeo = hyp.load('weights_sample')\ndata = geo.get_data()\n\n# plot\nhyp.describe(data)"
      ]
    }
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