notebooks/Dfs2 - Slicing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c73e34e2",
   "metadata": {},
   "source": [
    "# Dfs2 - Slicing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "963f1862-ff56-4520-b725-735120582730",
   "metadata": {},
   "outputs": [],
   "source": [
    "import mikeio\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6db61453-4896-47f3-a21a-0ce51828a3d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mikeio.Dataset>\n",
       "dims: (time:3, y:31, x:31)\n",
       "time: 2004-01-01 00:00:00 - 2004-01-03 00:00:00 (3 records)\n",
       "geometry: Grid2D (ny=31, nx=31)\n",
       "items:\n",
       "  0:  Sign. Wave Height <Significant wave height> (meter)\n",
       "  1:  Peak Wave Period <Wave period> (second)\n",
       "  2:  Mean Wave Direction <Mean Wave Direction> (degree)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = mikeio.read(\"../tests/testdata/waves.dfs2\")\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "04424048",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds[0].plot()\n",
    "plt.axvline(x=1400,color='k',linestyle='dashed', label=\"Transect\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d104e5c0",
   "metadata": {},
   "source": [
    "1. Use `Dataset/DataArray.sel` with physical coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d0cc2021",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='y', ylabel='time'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.sel(x=1400)[0].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9ab02cc",
   "metadata": {},
   "source": [
    "2. Use grid coordinates with `Dataset/DataArray.isel`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "50b964bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([27]), None)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.geometry.find_index(x=1400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f1b055b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='y', ylabel='time'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.isel(x=27)[0].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "15fe099a-3ab1-42e7-8bd9-fae8ffafe122",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds.sel(x=1400).to_dfs(\"waves_x1400.dfs1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6f082813-fb3f-492e-a01a-f5d6f6d5f3a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mikeio.Dataset>\n",
       "dims: (time:3, x:31)\n",
       "time: 2004-01-01 00:00:00 - 2004-01-03 00:00:00 (3 records)\n",
       "geometry: Grid1D (n=31, dx=50)\n",
       "items:\n",
       "  0:  Sign. Wave Height <Significant wave height> (meter)\n",
       "  1:  Peak Wave Period <Wave period> (second)\n",
       "  2:  Mean Wave Direction <Mean Wave Direction> (degree)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dsnew = mikeio.read(\"waves_x1400.dfs1\")\n",
    "dsnew"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "201950ec-1b7f-4ce6-8ab8-5aa8c21cbac5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.remove(\"waves_x1400.dfs1\")"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "767d51c1340bd893661ea55ea3124f6de3c7a262a8b4abca0554b478b1e2ff90"
  },
  "kernelspec": {
   "display_name": "Python 3.8.10 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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