nc_plot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import xarray as xr\n",
    "# from bokeh.embed import json_item\n",
    "import pandas as pd\n",
    "# from bokeh.io import push_notebook, show, output_notebook\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.models import ColumnDataSource, CustomJS, Select  #, Column\n",
    "from bokeh.models.tools import HoverTool\n",
    "from bokeh.layouts import layout, column #, row\n",
    "from bokeh.models.widgets import Panel, Tabs, Div\n",
    "from json2html import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.io import output_notebook, show\n",
    "from bokeh.resources import INLINE\n",
    "\n",
    "output_notebook(INLINE) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_plottable_variables(nc_url):\n",
    "    ds = xr.open_dataset(nc_url)\n",
    "    num_dims = len(ds.dims)\n",
    "    if num_dims >= 2:\n",
    "        axis_name = 'x_axis'\n",
    "    else:\n",
    "        axis_name = 'y_axis'\n",
    "    return {axis_name: [i for i in ds if len(ds[i].shape) == num_dims]}\n",
    "\n",
    "\n",
    "def get_nc_data(nc_url, nc_variable=None, resample=None):\n",
    "    ds = xr.open_dataset(nc_url)\n",
    "    data = ds.to_dataframe()\n",
    "    data.replace(9.96921e+36, np.NaN, inplace=True)\n",
    "    if nc_variable:\n",
    "        data = data[nc_variable]\n",
    "    if resample:\n",
    "        data = data.resample(resample).mean()\n",
    "    data = pd.DataFrame(data)\n",
    "    data.dataset_metadata = ''\n",
    "    data.dataset_metadata = ds.attrs\n",
    "    data.dataset_metadata['dimension'] = list(ds.dims)\n",
    "    if nc_variable:\n",
    "        data.variable_metadata = ''\n",
    "        data.variable_metadata = ds[nc_variable].attrs\n",
    "    else:\n",
    "        data.variable_metadata = ''\n",
    "        data.variable_metadata = {i: ds[i].attrs for i in ds}\n",
    "    return data\n",
    "\n",
    "\n",
    "def get_vp_data(nc_url, nc_variable='sal', resample=None, levels=None):\n",
    "    profile = get_nc_data(nc_url, nc_variable=nc_variable)\n",
    "    if not levels:\n",
    "        if len(profile.index.names) == 2:\n",
    "            vertical_level, time_level = profile.index.names\n",
    "        else:\n",
    "            raise ValueError\n",
    "    else:\n",
    "        vertical_level, time_level = levels\n",
    "    df = profile.swaplevel()\n",
    "    profile_dict = {str(v): df.loc[[df.index.get_level_values(0)[i]]].reset_index(level=time_level, drop=True)[nc_variable].values for i, v in enumerate(df.index.unique(level=time_level))}\n",
    "    flat_df = pd.DataFrame.from_dict(profile_dict)\n",
    "    flat_df.index = df.index.unique(level=vertical_level)\n",
    "    flat_df.variable_metadata = \"\"\n",
    "    flat_df.dataset_metadata = \"\"\n",
    "    flat_df.variable_metadata = profile.variable_metadata\n",
    "    flat_df.dataset_metadata = profile.dataset_metadata\n",
    "    if 'featureType' not in flat_df.dataset_metadata:\n",
    "        flat_df.dataset_metadata['featureType'] = ''\n",
    "        flat_df.dataset_metadata['featureType'] = 'profile'\n",
    "    return flat_df\n",
    "\n",
    "\n",
    "def create_ts_plot(data):\n",
    "    data['tooltip'] = [x.strftime(\"%Y-%m-%d %H:%M:%S\") for x in data.index]\n",
    "    source = ColumnDataSource(data)\n",
    "    tools_to_show = \"box_zoom, pan,save, hover, reset, wheel_zoom\"\n",
    "    var_label = '@{'+str(data.columns[0]+'}')\n",
    "    try:\n",
    "        var_tooltip_label = str(data.variable_metadata['long_name'])\n",
    "    except KeyError:\n",
    "        var_tooltip_label = str(data.variable_metadata['standard_name'])\n",
    "    p = figure(toolbar_location=\"above\",\n",
    "               x_axis_type=\"datetime\",\n",
    "               tools=tools_to_show)  #\n",
    "    p.sizing_mode = 'stretch_width'\n",
    "    tooltips = [('Time', '@tooltip'),\n",
    "                (var_tooltip_label, var_label)\n",
    "               ]\n",
    "    hover = p.select(dict(type=HoverTool))\n",
    "    hover.formatters = {'tooltip': \"datetime\"}\n",
    "    hover.tooltips = tooltips\n",
    "    p.line(x='time',\n",
    "           y=data.columns[0],\n",
    "           source=source,\n",
    "           color='green',\n",
    "           legend_label=data.columns[0],\n",
    "           )\n",
    "    p.min_border_left = 80\n",
    "    p.min_border_right = 80\n",
    "    return p\n",
    "\n",
    "\n",
    "def create_vp_plot(data):\n",
    "    ds = ColumnDataSource(data)\n",
    "    #tools_to_show = \"box_zoom, pan,save, hover, reset, wheel_zoom\"\n",
    "    var_label = '@{' + str(data.columns[0] + '}')\n",
    "    p = figure(toolbar_location=\"above\",\n",
    "               x_axis_type=\"linear\")\n",
    "    p.sizing_mode = 'stretch_width'\n",
    "    select = Select(title=\"Profile-record:\", options=list(data.columns))\n",
    "    try:\n",
    "        vertical_level, time_level = data.dataset_metadata['dimension']\n",
    "    except KeyError:\n",
    "        vertical_level, time_level = ('obsdepth', 'time')\n",
    "    try:\n",
    "        var_tooltip_label = str(data.variable_metadata['long_name'])\n",
    "    except KeyError:\n",
    "        var_tooltip_label = str(data.variable_metadata['standard_name'])\n",
    "    hover = HoverTool(tooltips=[(\"Depth\", \"@\"+vertical_level),\n",
    "                                (var_tooltip_label, '@{' + var_label + '}')])\n",
    "\n",
    "    p.add_tools(hover)\n",
    "    p.y_range.flipped = True\n",
    "    line_renderer = p.line(data.columns[0],\n",
    "                           vertical_level,\n",
    "                           source=ds,\n",
    "                           color='green',\n",
    "                           )\n",
    "\n",
    "    handler = CustomJS(args=dict(line_renderer=line_renderer),\n",
    "                       code=\"\"\"\n",
    "       line_renderer.glyph.x = {field: cb_obj.value};       \n",
    "    \"\"\")\n",
    "    select.js_on_change('value', handler)\n",
    "    p.min_border_left = 80\n",
    "    p.min_border_right = 80\n",
    "    return column(select, p, sizing_mode=\"stretch_width\")\n",
    "\n",
    "\n",
    "def create_page(data):\n",
    "    if data.dataset_metadata['featureType'] == 'timeSeries':\n",
    "        plot = create_ts_plot(data)\n",
    "    if data.dataset_metadata['featureType'] == 'profile':\n",
    "        plot = create_vp_plot(data)\n",
    "    try:\n",
    "        title = data.variable_metadata['long_name']\n",
    "    except KeyError:\n",
    "        title = data.variable_metadata['standard_name']\n",
    "    # summary = data.dataset_metadata['summary']\n",
    "    dataset_metadata = json2html.convert(json=data.dataset_metadata,\n",
    "                                         table_attributes=\"id=\\\"dataset-metadata\\\" \")\n",
    "    variable_metadata = json2html.convert(json=data.variable_metadata,\n",
    "                                          table_attributes=\"id=\\\"variable-metadata\\\" class=\\\"table table-bordered table-hover\\\"\")\n",
    "    title_div = Div(text=\"\"\"<h1><b>{title}</b></h1>\"\"\".format(title=title))\n",
    "\n",
    "    dataset_metadata_div = Div(text=\"\"\"{dataset_metadata}\"\"\".format(dataset_metadata=dataset_metadata))\n",
    "\n",
    "    variable_metadata_div = Div(text=\"\"\"<p>{variable_metadata}</p>\"\"\".format(variable_metadata=variable_metadata))\n",
    "\n",
    "    metadata_layout = layout([\n",
    "        [title_div],\n",
    "        [variable_metadata_div, dataset_metadata_div],\n",
    "    ], sizing_mode='stretch_width')\n",
    "    tab1 = Panel(child=plot, title=\"Plot\")\n",
    "    tab2 = Panel(child=metadata_layout, title=\"Metadata\")\n",
    "    tabs = Tabs(tabs=[tab1, tab2])\n",
    "    return tabs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ts_url = 'https://hyrax.epinux.com/opendap/local_data/SN99938.nc'\n",
    "vp_url = 'https://hyrax.epinux.com/opendap/local_data/ctdiaoos_gi2007_2009.nc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Vertical profile\n",
    "vp_variable = get_plottable_variables(vp_url)\n",
    "vp_data = get_vp_data(vp_url, vp_variable['x_axis'][0])\n",
    "vp_plot = create_page(vp_data)\n",
    "show(vp_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Time Series profile\n",
    "ts_variable = get_plottable_variables(ts_url)\n",
    "ts_data = get_nc_data(ts_url, ts_variable['y_axis'][0])\n",
    "ts_plot = create_page(ts_data)\n",
    "show(ts_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ts_url = 'https://thredds.met.no/thredds/dodsC/arcticdata/obsSynop/01205'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Time Series profile\n",
    "ts_variable = get_plottable_variables(ts_url)\n",
    "ts_data = get_nc_data(ts_url, ts_variable['y_axis'][0])\n",
    "ts_plot = create_page(ts_data)\n",
    "show(ts_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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