makeFig.ipynb

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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "474d626e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import holoviews as hv\n",
    "hv.extension('bokeh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33d2f3e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df = pd.read_csv('calout.csv',index_col=0)\n",
    "df = pd.read_csv('https://raw.githubusercontent.com/computational-sediment-hyd/1DSWEwithSmallerDx/main/calout.csv',index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a4fc45d",
   "metadata": {},
   "source": [
    "# zb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1f38902",
   "metadata": {},
   "outputs": [],
   "source": [
    "ib = 1/400\n",
    "fig0 = hv.Curve((df.Distance,df.Zb), label='Zb').options(show_grid=True, ylabel='elevation[m]', xlabel='distance[m]' ,color='k') \\\n",
    " * hv.Curve((df.Distance,df.Distance*ib), label='Zb_base').options(show_grid=True, ylabel='elevation[m]', xlabel='distance[m]' ,color='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8bf2c77",
   "metadata": {},
   "outputs": [],
   "source": [
    "hv.extension('bokeh')\n",
    "fig0o = fig0.options(width=500, legend_position='bottom_right')\n",
    "# d = hv.save(fig0o, 'zb.html')\n",
    "fig0o "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96a80e55",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig0o2 = fig0.options(xlim=(3110, 3130), ylim=(7, 9), width=500)\n",
    "# d = hv.save(fig0o2, 'zb2.html')\n",
    "fig0o2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9cbd7f1",
   "metadata": {},
   "source": [
    "# calout1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5c13e19",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = hv.Curve((df.Distance,df.Zb), label='Zb').options(show_grid=True, ylabel='elevation[m]', xlabel='distance[m]' ,color='k') \\\n",
    "* hv.Curve((df.Distance, df.Zb + df['Nonuniform']), label='Nonuniform' ).options(color='b') \\\n",
    "* hv.Curve((df.Distance, df.Zb + df['Unsteady Collacated']), label='Unsteady Collacated').options(color='r') \\\n",
    "* hv.Curve((df.Distance, df.Zb + df['Unsteady Staggered']), label='Unsteady Staggered').options(color='g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb016a94",
   "metadata": {},
   "outputs": [],
   "source": [
    "figo = fig.options(width=500, legend_position='bottom_right')\n",
    "# d = hv.save(figo, 'calout1.html')\n",
    "figo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc898e49",
   "metadata": {},
   "source": [
    "# calout2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "990db05d",
   "metadata": {},
   "outputs": [],
   "source": [
    "figo2 = fig.options(xlim=(3110, 3130), ylim=(7, 12), width=500, height=600, legend_position='top')\n",
    "# d = hv.save(figo2, 'calout2.html')\n",
    "figo2"
   ]
  }
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