{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "%gui qt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Scatter plot and histograms\n\nA scatter plot of 2D points with matching histograms.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import numpy as np\n\nimport vispy.plot as vp\n\nnp.random.seed(2324)\nn = 100000\ndata = np.empty((n, 2))\nlasti = 0\nfor i in range(1, 20):\n    nexti = lasti + (n - lasti) // 2\n    scale = np.abs(np.random.randn(2)) + 0.1\n    scale[1] = scale.mean()\n    data[lasti:nexti] = np.random.normal(size=(nexti-lasti, 2),\n                                         loc=np.random.randn(2),\n                                         scale=scale / i)\n    lasti = nexti\ndata = data[:lasti]\n\n\ncolor = (0.3, 0.5, 0.8)\nn_bins = 100\n\nfig = vp.Fig(show=False)\nline = fig[0:4, 0:4].plot(data, symbol='o', width=0,\n                          face_color=color + (0.02,), edge_color=None,\n                          marker_size=4)\nline.set_gl_state(depth_test=False)\nfig[4, 0:4].histogram(data[:, 0], bins=n_bins, color=color, orientation='h')\nfig[0:4, 4].histogram(data[:, 1], bins=n_bins, color=color, orientation='v')\n\nif __name__ == '__main__':\n    fig.show(run=True)"
      ]
    }
  ],
  "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": "3.9.19"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}