GA03FLMA-RIM01-02-CTDMOG040.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting Time Series Data from NetCDF\n",
    "\n",
    "In this example we show how to programatically download and work with OOI NetCDF time series data. We will use data from the Global Argentine Basin Flanking Subsurface Mooring A Mooring Riser CTD at 30 m. You will learn:\n",
    "\n",
    "* how to find the data you are looking for\n",
    "* how to use the machine to machine API to request data\n",
    "* how to load the NetCDF data into your notebook, once the data request has completed\n",
    "* how to plot data\n",
    "\n",
    "For the instrument in this example, you will need the Reference Designator, Stream and Data Delivery Method to make the request to the M2M API. More information about the instrument can be found here:\n",
    "http://ooi.visualocean.net/instruments/view/GA03FLMA-RIM01-02-CTDMOG040\n",
    "\n",
    "![GA03FLMA-RIM01-02-CTDMOG040](https://github.com/ooi-data-review/ooi_datateam_notebooks/raw/master/images/GA03FLMA-RIM01-02-CTDMOG040.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Login in at https://ooinet.oceanobservatories.org/ and obtain your <b>API username and API token</b> under your profile (top right corner), or use the credentials provided below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "username = 'OOIAPI-D8S960UXPK4K03'\n",
    "token = 'IXL48EQ2XY'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specify your inputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "subsite = 'GA03FLMA'\n",
    "node = 'RIM01'\n",
    "sensor = '02-CTDMOG040'\n",
    "method = 'recovered_inst'\n",
    "stream = 'ctdmo_ghqr_instrument_recovered'\n",
    "beginDT = '2016-06-01T00:00:00.000Z' # this time range encompasses all three deployments of this instrument.\n",
    "endDT = '2016-06-02T23:59:59.999Z'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Build the GET request URL and send the request to the M2M API endpoint."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_url = 'https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv'\n",
    "\n",
    "data_request_url ='/'.join((base_url,subsite,node,sensor,method,stream))\n",
    "params = {\n",
    "    'beginDT':beginDT,\n",
    "    'endDT':endDT,   \n",
    "}\n",
    "r = requests.get(data_request_url, params=params, auth=(username, token))\n",
    "data = r.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://opendap.oceanobservatories.org/thredds/catalog/ooi/ooidatateam@gmail.com/20180521T185633-GA03FLMA-RIM01-02-CTDMOG040-recovered_inst-ctdmo_ghqr_instrument_recovered/catalog.html'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['allURLs'][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check if the request has completed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "request completed\n",
      "CPU times: user 502 ms, sys: 35.5 ms, total: 538 ms\n",
      "Wall time: 30.4 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "check_complete = data['allURLs'][1] + '/status.txt'\n",
    "for i in range(1800): \n",
    "    r = requests.get(check_complete)\n",
    "    if r.status_code == requests.codes.ok:\n",
    "        print('request completed')\n",
    "        break\n",
    "    else:\n",
    "        time.sleep(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Parse the thredds server to get a list of all NetCDF files. Each deployment is seperated into a seperate netcdf file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['https://opendap.oceanobservatories.org/thredds/dodsC/ooi/ooidatateam@gmail.com/20180521T185633-GA03FLMA-RIM01-02-CTDMOG040-recovered_inst-ctdmo_ghqr_instrument_recovered/deployment0002_GA03FLMA-RIM01-02-CTDMOG040-recovered_inst-ctdmo_ghqr_instrument_recovered_20160601T000001-20160602T234501.nc']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = data['allURLs'][0]\n",
    "tds_url = 'https://opendap.oceanobservatories.org/thredds/dodsC'\n",
    "datasets = requests.get(url).text\n",
    "urls = re.findall(r'href=[\\'\"]?([^\\'\" >]+)', datasets)\n",
    "x = re.findall(r'(ooi/.*?.nc)', datasets)\n",
    "for i in x:\n",
    "    if i.endswith('.nc') == False:\n",
    "        x.remove(i)\n",
    "for i in x:\n",
    "    try:\n",
    "        float(i[-4])\n",
    "    except:\n",
    "        x.remove(i)\n",
    "datasets = [os.path.join(tds_url, i) for i in x]\n",
    "datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load all files into a single xarray dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                                  (time: 192)\n",
       "Coordinates:\n",
       "    obs                                      (time) int32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "  * time                                     (time) datetime64[ns] 2016-06-01T00:00:01 ...\n",
       "    pressure                                 (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    lat                                      (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    lon                                      (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "Data variables:\n",
       "    deployment                               (time) int32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    id                                       (time) |S64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    conductivity                             (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctd_time                                 (time) datetime64[ns] dask.array<shape=(192,), chunksize=(100,)>\n",
       "    driver_timestamp                         (time) datetime64[ns] dask.array<shape=(192,), chunksize=(100,)>\n",
       "    inductive_id                             (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ingestion_timestamp                      (time) datetime64[ns] dask.array<shape=(192,), chunksize=(100,)>\n",
       "    internal_timestamp                       (time) datetime64[ns] dask.array<shape=(192,), chunksize=(100,)>\n",
       "    port_timestamp                           (time) datetime64[ns] dask.array<shape=(192,), chunksize=(100,)>\n",
       "    preferred_timestamp                      (time) object dask.array<shape=(192,), chunksize=(100,)>\n",
       "    pressure_temp                            (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    provenance                               (time) |S64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    serial_number                            (time) object dask.array<shape=(192,), chunksize=(100,)>\n",
       "    temperature                              (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_pressure                  (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_temperature               (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_conductivity              (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    practical_salinity                       (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    density                                  (time) float64 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_pressure_qc_executed      (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_pressure_qc_results       (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_temperature_qc_executed   (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_temperature_qc_results    (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_conductivity_qc_executed  (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    ctdmo_seawater_conductivity_qc_results   (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    density_qc_executed                      (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    density_qc_results                       (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    practical_salinity_qc_executed           (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "    practical_salinity_qc_results            (time) float32 dask.array<shape=(192,), chunksize=(100,)>\n",
       "Attributes:\n",
       "    _NCProperties:                      version=1|netcdflibversion=4.4.1.1|hd...\n",
       "    node:                               RIM01\n",
       "    comment:                            \n",
       "    publisher_email:                    \n",
       "    sourceUrl:                          http://oceanobservatories.org/\n",
       "    collection_method:                  recovered_inst\n",
       "    stream:                             ctdmo_ghqr_instrument_recovered\n",
       "    featureType:                        point\n",
       "    creator_email:                      \n",
       "    publisher_name:                     Ocean Observatories Initiative\n",
       "    date_modified:                      2018-05-21T18:56:44.208144\n",
       "    keywords:                           \n",
       "    cdm_data_type:                      Point\n",
       "    references:                         More information can be found at http...\n",
       "    Metadata_Conventions:               Unidata Dataset Discovery v1.0\n",
       "    date_created:                       2018-05-21T18:56:44.208138\n",
       "    id:                                 GA03FLMA-RIM01-02-CTDMOG040-recovered...\n",
       "    requestUUID:                        90967e60-ed5d-4d40-a51e-793408e3d8b9\n",
       "    contributor_role:                   \n",
       "    summary:                            Dataset Generated by Stream Engine fr...\n",
       "    keywords_vocabulary:                \n",
       "    institution:                        Ocean Observatories Initiative\n",
       "    naming_authority:                   org.oceanobservatories\n",
       "    feature_Type:                       point\n",
       "    infoUrl:                            http://oceanobservatories.org/\n",
       "    license:                            \n",
       "    contributor_name:                   \n",
       "    uuid:                               90967e60-ed5d-4d40-a51e-793408e3d8b9\n",
       "    creator_name:                       Ocean Observatories Initiative\n",
       "    title:                              Data produced by Stream Engine versio...\n",
       "    sensor:                             02-CTDMOG040\n",
       "    standard_name_vocabulary:           NetCDF Climate and Forecast (CF) Meta...\n",
       "    acknowledgement:                    \n",
       "    Conventions:                        CF-1.6\n",
       "    project:                            Ocean Observatories Initiative\n",
       "    source:                             GA03FLMA-RIM01-02-CTDMOG040-recovered...\n",
       "    publisher_url:                      http://oceanobservatories.org/\n",
       "    creator_url:                        http://oceanobservatories.org/\n",
       "    nodc_template_version:              NODC_NetCDF_TimeSeries_Orthogonal_Tem...\n",
       "    subsite:                            GA03FLMA\n",
       "    processing_level:                   L2\n",
       "    history:                            2018-05-21T18:56:44.208062 generated ...\n",
       "    Manufacturer:                       Sea-Bird Electronics\n",
       "    ModelNumber:                        SBE 37-IM\n",
       "    SerialNumber:                       37-13560\n",
       "    Description:                        CTD Mooring (Inductive): CTDMO Series G\n",
       "    FirmwareVersion:                    Not specified.\n",
       "    SoftwareVersion:                    Not specified.\n",
       "    AssetUniqueID:                      CGINS-CTDMOG-13560\n",
       "    Notes:                              Not specified.\n",
       "    Owner:                              Woods Hole Oceanographic Institution\n",
       "    RemoteResources:                    []\n",
       "    ShelfLifeExpirationDate:            Not specified.\n",
       "    Mobile:                             False\n",
       "    AssetManagementRecordLastModified:  2018-05-21T12:22:47.870000\n",
       "    time_coverage_start:                2016-06-01T00:00:01\n",
       "    time_coverage_end:                  2016-06-02T23:45:01\n",
       "    time_coverage_resolution:           P895.31S\n",
       "    geospatial_lat_min:                 -42.49457\n",
       "    geospatial_lat_max:                 -42.49457\n",
       "    geospatial_lat_units:               degrees_north\n",
       "    geospatial_lat_resolution:          0.1\n",
       "    geospatial_lon_min:                 -42.92112\n",
       "    geospatial_lon_max:                 -42.92112\n",
       "    geospatial_lon_units:               degrees_east\n",
       "    geospatial_lon_resolution:          0.1\n",
       "    geospatial_vertical_units:          meters\n",
       "    geospatial_vertical_resolution:     0.1\n",
       "    geospatial_vertical_positive:       down\n",
       "    DODS.strlen:                        7\n",
       "    DODS.dimName:                       string7\n",
       "    DODS_EXTRA.Unlimited_Dimension:     obs"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xr.open_mfdataset(datasets)\n",
    "ds = ds.swap_dims({'obs': 'time'})\n",
    "ds = ds.chunk({'time': 100})\n",
    "ds = ds.sortby('time') # data from different deployments can overlap so we want to sort all data by time stamp.\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the dataset using matplotlib, working under the hood of xarray."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1)\n",
    "fig.set_size_inches(16, 6)\n",
    "\n",
    "ds['ctdmo_seawater_pressure'].plot(linestyle = 'None', \n",
    "                                   marker='.', \n",
    "                                   markersize=3,\n",
    "                                   ax=ax)\n",
    "\n",
    "ax.invert_yaxis()\n",
    "ax.grid()\n",
    "\n",
    "plt.title('Global Argentine Basin Flanking Subsurface Mooring A Mooring Riser CTD (30 m)')\n",
    "plt.ylabel('Pressure (dbar)')\n",
    "plt.xlabel('Time \\n Deployments 1 - 3')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This CTD is supposed to be stationary at around 30 m depth in the water column, but violent storms in the southern himisphere can draw the CTD mooring chain down by hundreds of meters. More information about the Flanking Subsurface Mooring A can be found [here](http://oceanobservatories.org/site/ga03flma/)."
   ]
  }
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