hvplot.ipynb

{
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   "id": "b4fbad44-178b-453c-aa89-84f25b5d66db",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import holoviews as hv\n",
    "import hvplot.xarray\n",
    "import panel as pn\n",
    "import numpy as np\n",
    "\n",
    "hv.renderer('bokeh').webgl = False "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10032e25-265e-4567-a596-550a7669ebe7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(var, title=None):\n",
    "    if not title:\n",
    "        try:\n",
    "            title = f\"{ds[var].attrs['long_name']}\"\n",
    "        except KeyError:\n",
    "            title = f\"{var}\"\n",
    "    else:\n",
    "        title=title\n",
    "    if 'featureType' in ds.attrs:\n",
    "        featureType = ds.attrs['featureType']\n",
    "    else:\n",
    "        featureType = None\n",
    "    if featureType == 'timeSeries':\n",
    "        var_coord = [i for i in ds.coords if ds.coords.dtypes[i] == np.dtype('<M8[ns]')]\n",
    "        axis_arguments = {'y': ds[var], 'grid':True, 'title': title, 'widget_location': 'bottom', 'responsive': True}\n",
    "    if featureType and featureType != \"timeSeries\":\n",
    "        axis_arguments = {'x': ds[var], 'grid':True, 'title': title, 'widget_location': 'bottom', 'responsive': True}\n",
    "    try:\n",
    "        plot_widget =  ds[var].hvplot.line(**axis_arguments)\n",
    "    except TypeError:\n",
    "        plot_widget =  ds[var].hvplot.line()\n",
    "    except ValueError:\n",
    "        axis_arguments = {'x': var, 'grid':True, 'title': title, 'widget_location': 'bottom', 'responsive': True}\n",
    "        plot_widget =  ds[var].hvplot.line(**axis_arguments)\n",
    "    return plot_widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a961158c-fc4e-4f0f-890d-1f31756c9bea",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"qlwXxbz0QQiE6qLALjaFlQ.nc\"\n",
    "ds = xr.open_dataset(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03e5cd69-61a8-4666-9acc-e511764c1ba3",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb309b35-4d3f-4306-9c96-7892a4a32ff3",
   "metadata": {},
   "outputs": [],
   "source": [
    "plot('dw')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5776723-4aa1-4903-870b-f5e6e39d11a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "plot('ws')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40ac5369-53c3-4921-a55e-b128ae9d0253",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "plottable_vars = [i for i in ds if (list(ds[i].dims) == list(ds.coords) or list(ds[i].dims) == list(ds.coords)[::-1])] \n",
    "ds.coords.values(), ds.sizes, plottable_vars, ds.attrs['featureType']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f58447be-e99b-4cdc-b882-4b23a2feb841",
   "metadata": {},
   "outputs": [],
   "source": [
    "time_coord = [i for i in ds.coords if ds.coords.dtypes[i] == np.dtype('<M8[ns]')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e5d10909-d2cc-44a9-bcb0-d8ad1b22fa89",
   "metadata": {},
   "outputs": [],
   "source": [
    "time_coord"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4fcef8b6-1da1-423b-9b8e-346a00cd8506",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds.indexes[time_coord[0]].min(), ds.indexes[time_coord[0]].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "abe7d18d-23e4-41bc-b2b7-a4856206fc86",
   "metadata": {},
   "outputs": [],
   "source": [
    "mapping_var_names = {}\n",
    "for i in plottable_vars:\n",
    "    if int(len(list(ds[i].coords)) != 0):\n",
    "        try:\n",
    "            title = f\"{ds[i].attrs['long_name']} [{i}]\"\n",
    "        except KeyError:\n",
    "            title = f\"{i}\"\n",
    "        mapping_var_names[i] = title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d14268c-b7e8-4320-ab78-e27174e80487",
   "metadata": {},
   "outputs": [],
   "source": [
    "mapping_var_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88dcfe11-42dc-44e8-8277-6658dc905722",
   "metadata": {},
   "outputs": [],
   "source": [
    "common_values = {j:[value for value in list(ds[j].coords) if value in list(ds.dims)] for j in ds}\n",
    "common_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5f23ce79-a5c3-4d57-bff5-c3a716a771c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "var_coord = [i for i in ds.coords if ds.coords.dtypes[i] == np.dtype('<M8[ns]')]\n",
    "var_coord"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "105f2a75-0765-48bb-a6fa-b85512e4477a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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