{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Compare Kriging\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\nfrom gstools import Gaussian, krige\n\n# condtions\ncond_pos = [0.3, 1.9, 1.1, 3.3, 4.7]\ncond_val = [0.47, 0.56, 0.74, 1.47, 1.74]\n# resulting grid\ngridx = np.linspace(0.0, 15.0, 151)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "A gaussian variogram model.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "model = Gaussian(dim=1, var=0.5, len_scale=2)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Two kriged fields. One with simple and one with ordinary kriging.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "kr1 = krige.Simple(model=model, mean=1, cond_pos=cond_pos, cond_val=cond_val)\nkr2 = krige.Ordinary(model=model, cond_pos=cond_pos, cond_val=cond_val)\nkr1(gridx)\nkr2(gridx)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "plt.plot(gridx, kr1.field, label=\"simple kriged field\")\nplt.plot(gridx, kr2.field, label=\"ordinary kriged field\")\nplt.scatter(cond_pos, cond_val, color=\"k\", zorder=10, label=\"Conditions\")\nplt.legend()\nplt.show()"
      ]
    }
  ],
  "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": "3.7.9"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}