{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask\n",
    "\n",
    "dask.config.set(scheduler=\"single-threaded\")\n",
    "\n",
    "\n",
    "url = (\n",
    "    \"http://www.smast.umassd.edu:8080/thredds/dodsC/FVCOM/NECOFS/\"\n",
    "    \"Forecasts/NECOFS_GOM3_FORECAST.nc\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from netCDF4 import Dataset\n",
    "\n",
    "from odvc.parse_formula_terms import get_formula_terms_variables\n",
    "\n",
    "nc = Dataset(url)\n",
    "\n",
    "var = get_formula_terms_variables(nc)\n",
    "\n",
    "var"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from odvc.parse_formula_terms import get_formula_terms\n",
    "\n",
    "formula_terms = get_formula_terms(var[0])\n",
    "\n",
    "formula_terms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from odvc.parse_formula_terms import get_formula_terms_dims\n",
    "\n",
    "dims = get_formula_terms_dims(nc, formula_terms)\n",
    "\n",
    "dims"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from odvc.parse_formula_terms import z_shape\n",
    "\n",
    "new_shape = z_shape(nc, dims)\n",
    "\n",
    "new_shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from odvc.parse_formula_terms import prepare_arrays\n",
    "\n",
    "arrays = prepare_arrays(nc, formula_terms, new_shape)\n",
    "\n",
    "arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from odvc import ocean_sigma_coordinate\n",
    "\n",
    "z = ocean_sigma_coordinate(arrays[\"sigma\"], arrays[\"eta\"], arrays[\"depth\"])\n",
    "print(z.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "salt = nc.get_variables_by_attributes(\n",
    "    standard_name=\"sea_water_salinity\",\n",
    ")[0]\n",
    "temp = nc.get_variables_by_attributes(\n",
    "    standard_name=\"sea_water_potential_temperature\",\n",
    ")[0]\n",
    "\n",
    "s = salt[-1, :, 175]\n",
    "t = temp[-1, :, 175]\n",
    "p = z[-1, :, 175]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits import axisartist\n",
    "from mpl_toolkits.axes_grid1 import host_subplot\n",
    "\n",
    "\n",
    "def adjust_xlim(ax, offset):\n",
    "    x1, x2 = ax.get_xlim()\n",
    "    ax.set_xlim(x1 - offset, x2 + offset)\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(6, 9))\n",
    "fig.subplots_adjust(bottom=0.1, top=0.85)\n",
    "ax0 = host_subplot(111, axes_class=axisartist.Axes)\n",
    "\n",
    "ax0.invert_yaxis()\n",
    "ax1 = ax0.twiny()\n",
    "\n",
    "new_axis0 = ax0.get_grid_helper().new_fixed_axis\n",
    "new_axis1 = ax1.get_grid_helper().new_fixed_axis\n",
    "\n",
    "ax0.axis[\"top\"] = new_axis0(loc=\"top\", axes=ax0, offset=(0, 0))\n",
    "ax1.axis[\"top\"] = new_axis1(loc=\"top\", axes=ax1, offset=(0, 40))\n",
    "\n",
    "ax0.axis[\"bottom\"].toggle(all=False)\n",
    "ax1.axis[\"bottom\"].toggle(all=False)\n",
    "\n",
    "ax0.set_ylabel(\"Depth (m)\")\n",
    "ax0.set_xlabel(\"Temperature (\\xb0C)\")\n",
    "ax1.set_xlabel(r\"Salinity (g kg$^{-1}$)\")\n",
    "\n",
    "kw = {\"linewidth\": 2.5}\n",
    "(l0,) = ax0.plot(t, -p, **kw)\n",
    "(l1,) = ax1.plot(s, -p, **kw)\n",
    "\n",
    "adjust_xlim(ax0, offset=0.05)\n",
    "adjust_xlim(ax1, offset=0.05)\n",
    "\n",
    "ax0.axis[\"top\"].label.set_color(l0.get_color())\n",
    "ax1.axis[\"top\"].label.set_color(l1.get_color())"
   ]
  }
 ],
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