geology/reports/Manopkawee.ipynb

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      "source": [
        "# Coastal Endurance Washington-Oregon Shelf Surface Mooring Data Comparison Report\n",
        "\n",
        "** Evaluation Date**: 7/20/2018\n",
        "\n",
        "** Evaluator**: Pichawut Manopkawee\n",
        "\n",
        "## Review Summary\n",
        "This report summarized a data comparison report of the Coastal Endurance between Washington and Oregon Shelf Surface Mooring Data (CE07SHSM,CE02SHSM). I focus on data from the full available dataset and narrow down to one year data  between 2015/12/1 and 2016/12/1. This report is not necessarily a comprehensive review of the instruments and quality of the data available. Instead, it explains the key comparison of dataset from two different sites within the same timestamps."
      ]
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      "cell_type": "markdown",
      "source": [
        "## 1. Coastal Endurance Array"
      ]
    },
    {
      "metadata": {
        "id": "YnnF8S8sSfro",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "![Coastal Endurance Array](http://oceanobservatories.org/wp-content/uploads/2018/03/CEV-OOI-Endurance-Array.jpg)"
      ]
    },
    {
      "metadata": {
        "id": "xjqHy1udSfrp",
        "colab_type": "text"
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      "cell_type": "markdown",
      "source": [
        "In this project, I focus on Washington and Oregon shelf surface mooring data which are derived by site 2 and 5, respectively."
      ]
    },
    {
      "metadata": {
        "id": "Ucq5vh10Sfrp",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 2. Selected Instruments \n",
        "\n",
        "In this report, I will evaluate the CTD (particuarly temperature and seawater pressure), dissolved oxygen, nitrate, and 3-wavelength fluorometer (particularly chlorophyll concentration) from the Coastal Endurance on Washington and Oregon shelf. Additional instruments on the profiler are listed for reference and could be used for further evaluation.\n"
      ]
    },
    {
      "metadata": {
        "id": "JnUmHLmWSfrq",
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      "source": [
        "Instrument | Reference Designator | Method | Stream \n",
        " -- | -- | -- | --\n",
        "CTD | CE02SHSM-RID27-03-CTDBPC000 | telemetered | ctdbp_cdef_dcl_instrument\n",
        "CTD | CE07SHSM-RID27-03-CTDBPC000 | telemetered | ctdbp_cdef_dcl_instrument\n",
        "Dissolved Oxygen | CE02SHSM-RID27-04-DOSTAD000 | telemetered | dosta_abcdjm_dcl_instrument\n",
        "Dissolved Oxygen | CE07SHSM-RID27-04-DOSTAD000 | telemetered | dosta_abcdjm_dcl_instrument\n",
        "Nitrate| CE02SHSM-RID26-07-NUTNRB000 | telemetered | nutnr_b_dcl_conc_instrument\n",
        "Nitrate| CE07SHSM-RID26-07-NUTNRB000 | telemetered | nutnr_b_dcl_conc_instrument\n",
        "Fluorometer | CE02SHSM-RID27-02-FLORTD000  | telemetered | flort_sample\n",
        "Fluorometer | CE07SHSM-RID27-02-FLORTD000  | telemetered | flort_sample\n"
      ]
    },
    {
      "metadata": {
        "id": "dwC1Wsd4Sfrr",
        "colab_type": "code",
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      "cell_type": "code",
      "source": [
        "# Instrument Information\n",
        "site = 'CE02SHSM','CE07SHSM'\n",
        "node = 'RID27','RID26'\n",
        "instrument = ['03-CTDBPC000','04-DOSTAD000','07-NUTNRB000','02-FLORTD000']\n",
        "method = 'telemetered'\n",
        "stream = ['ctdbp_cdef_dcl_instrument','dosta_abcdjm_dcl_instrument','nutnr_b_dcl_conc_instrument','flort_sample']\n",
        "VOCAB_BASE_URL = 'https://ooinet.oceanobservatories.org/api/m2m/12586/vocab/inv'"
      ],
      "execution_count": 0,
      "outputs": []
    },
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      "metadata": {
        "id": "LQyxuYZ8Sfrt",
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      "cell_type": "markdown",
      "source": [
        "## 3. Time Periods of Interest\n",
        "\n",
        "In this report, we will focusng on the following time periods for evaluation:\n",
        "- April 2, 2015 to July 18, 2018 - All of Deployment 1-5 (see step 4)\n",
        "- December 1, 2015 to December 1, 2016- Deployment 2-4 (sea step 5)"
      ]
    },
    {
      "metadata": {
        "id": "fDuPlbhOSfru",
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      "cell_type": "markdown",
      "source": [
        "## 4. Related Metadata\n",
        "\n",
        "In this section, I will review some of metadata available in the system to make sure it is present and correct.\n",
        "\n",
        "Before I get started, I need to set up our Python environment with some libraries, variables and functions I will need later in this report."
      ]
    },
    {
      "metadata": {
        "id": "P4W6GeDtSfrv",
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      "cell_type": "code",
      "source": [
        "USERNAME = ''\n",
        "TOKEN =  ''\n",
        "\n",
        "DATA_API = 'https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/'\n",
        "VOCAB_API = 'https://ooinet.oceanobservatories.org/api/m2m/12586/vocab/inv'\n",
        "ASSET_API = 'https://ooinet.oceanobservatories.org/api/m2m/12587'\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "xnc8KZTuvCfZ",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# First, we need to add some more Python libraries\n",
        "import requests\n",
        "import datetime\n",
        "import time\n",
        "import pandas as pd"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
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        "colab_type": "code",
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            "startup": false,
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          }
        },
        "outputId": "332e5ac7-ccff-4a5d-e6f4-755abdc5a92b"
      },
      "cell_type": "code",
      "source": [
        "range(len(instrument))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "range(0, 4)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "metadata": {
        "id": "uYsTVr5rtHXg",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# convert timestamps\n",
        "  \n",
        "def convert_time(ms):\n",
        "  if ms != None:\n",
        "    return datetime.datetime.utcfromtimestamp(ms/1000)\n",
        "  else:\n",
        "    return None\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "RPZGeA7GSfr4",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 4a. Vocabulary Metadata\n",
        "\n",
        "This is a review of basic vocabulary information (metadata) from the system to make sure that I work on the right instrument."
      ]
    },
    {
      "metadata": {
        "id": "83f7J3TIZW8T",
        "colab_type": "code",
        "slideshow": {
          "slide_type": "slide"
        },
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 215
        },
        "outputId": "1432a4cb-1bba-4912-a035-1845470d33a0",
        "executionInfo": {
          "elapsed": 593,
          "status": "ok",
          "timestamp": 1529033591260,
          "user": {
            "displayName": "Sage Lichtenwalner",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "107661401208389246829"
          },
          "user_tz": 240
        }
      },
      "cell_type": "code",
      "source": [
        "# Create the request URL (3 different ways)\n",
        "# request_url = VOCAB_BASE_URL + '/'+site+'/'+ node+'/'+instrument # Good\n",
        "# request_url = \"%s/%s/%s/%s\" % (VOCAB_BASE_URL,site,node,instrument) # Better\n",
        "for i in range(len(instrument)):\n",
        "    request_url ='/'.join((VOCAB_BASE_URL,site,node,instrument[i])) # Python wizard best\n",
        "    \n",
        "# Retrieve vocabulary information for a given instrument\n",
        "    r = requests.get(request_url, auth=(USERNAME, TOKEN))\n",
        "    data = r.json()\n",
        "    print(i,data)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0 [{'@class': '.VocabRecord', 'model': 'SBE 16plusV2', 'manufacturer': 'Sea-Bird', 'vocabId': 75, 'refdes': 'CE02SHSM-RID27-03-CTDBPC000', 'instrument': 'CTD', 'tocL1': 'Coastal Endurance', 'tocL2': 'Oregon Shelf Surface Mooring', 'tocL3': 'Near Surface Instrument Frame', 'mindepth': 7.0, 'maxdepth': 7.0}]\n",
            "1 [{'@class': '.VocabRecord', 'model': 'Optode 4831', 'manufacturer': 'Aanderaa', 'vocabId': 76, 'refdes': 'CE02SHSM-RID27-04-DOSTAD000', 'instrument': 'Dissolved Oxygen', 'tocL1': 'Coastal Endurance', 'tocL2': 'Oregon Shelf Surface Mooring', 'tocL3': 'Near Surface Instrument Frame', 'mindepth': 7.0, 'maxdepth': 7.0}]\n",
            "2 []\n",
            "3 [{'@class': '.VocabRecord', 'model': 'ECO Triplet-w', 'manufacturer': 'WET Labs', 'vocabId': 74, 'refdes': 'CE02SHSM-RID27-02-FLORTD000', 'instrument': '3-Wavelength Fluorometer', 'tocL1': 'Coastal Endurance', 'tocL2': 'Oregon Shelf Surface Mooring', 'tocL3': 'Near Surface Instrument Frame', 'mindepth': 7.0, 'maxdepth': 7.0}]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "u-E04txvSfr8",
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      "cell_type": "markdown",
      "source": [
        "These look good, except the nitrate concentration. No basic vocabulary information is provided in from this instrument even if the instrument was deployed."
      ]
    },
    {
      "metadata": {
        "id": "ThpCOBeqSfr8",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 4b. Deployment Information\n",
        "This is some information about the deployments for this instrument. I will grab all of the deployments available in the system and then output the date ranges, latitude/longitude, asset ID, and sensor ID for each.  "
      ]
    },
    {
      "metadata": {
        "id": "hfOt4Pni2S1C",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "7a43daa5-d884-49e6-81e3-393397e23fb3",
        "executionInfo": {
          "elapsed": 869,
          "status": "ok",
          "timestamp": 1528212559448,
          "user": {
            "displayName": "Sage Lichtenwalner",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "107661401208389246829"
          },
          "user_tz": 240
        }
      },
      "cell_type": "code",
      "source": [
        "# Setup the API request url\n",
        "df = pd.DataFrame() # Setup empty array\n",
        "for i in range(len(instrument)): \n",
        "    data_request_url = ASSET_API + '/events/deployment/query'\n",
        "    params = {\n",
        "      'beginDT':'2015-04-02T00:00:00.000Z',\n",
        "      'endDT':'2018-07-18T00:00:00.000Z',\n",
        "      'refdes':site+'-'+node+'-'+instrument[i]}\n",
        "\n",
        "    # Grab the information from the server\n",
        "    r = requests.get(data_request_url, params=params, auth=(USERNAME, TOKEN))\n",
        "    data = r.json()\n",
        "\n",
        "    for d in data:\n",
        "      df = df.append({\n",
        "          'deployment': d['deploymentNumber'],\n",
        "          'start': convert_time(d['eventStartTime']),\n",
        "          'stop': convert_time(d['eventStopTime']),\n",
        "          'latitude': d['location']['latitude'],\n",
        "          'longitude': d['location']['longitude'],\n",
        "          'sensor': d['sensor']['uid'],\n",
        "          'asset_id': d['sensor']['assetId'],\n",
        "        }, ignore_index=True)\n",
        "df"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>asset_id</th>\n",
              "      <th>deployment</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>sensor</th>\n",
              "      <th>start</th>\n",
              "      <th>stop</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1676.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>44.63833</td>\n",
              "      <td>-124.30388</td>\n",
              "      <td>CGINS-CTDBPC-50012</td>\n",
              "      <td>2015-04-02 20:15:00</td>\n",
              "      <td>2015-09-22 07:48:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>791.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>44.63538</td>\n",
              "      <td>-124.30252</td>\n",
              "      <td>CGINS-CTDBPC-07243</td>\n",
              "      <td>2015-10-07 21:10:00</td>\n",
              "      <td>2016-05-16 21:09:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1586.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>44.63565</td>\n",
              "      <td>-124.30427</td>\n",
              "      <td>CGINS-CTDBPC-50057</td>\n",
              "      <td>2016-05-17 21:23:00</td>\n",
              "      <td>2016-09-28 15:52:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1678.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>44.63929</td>\n",
              "      <td>-124.30404</td>\n",
              "      <td>CGINS-CTDBPC-50011</td>\n",
              "      <td>2016-09-26 21:25:00</td>\n",
              "      <td>2017-04-22 13:24:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1683.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>44.63580</td>\n",
              "      <td>-124.30388</td>\n",
              "      <td>CGINS-CTDBPC-50014</td>\n",
              "      <td>2017-04-20 17:23:00</td>\n",
              "      <td>2017-10-15 19:06:32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>946.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>44.63925</td>\n",
              "      <td>-124.30407</td>\n",
              "      <td>CGINS-CTDBPC-50188</td>\n",
              "      <td>2017-10-10 02:21:08</td>\n",
              "      <td>2018-04-04 13:57:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1662.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>44.63567</td>\n",
              "      <td>-124.30418</td>\n",
              "      <td>CGINS-CTDBPC-50007</td>\n",
              "      <td>2018-04-03 01:17:00</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>972.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>44.63833</td>\n",
              "      <td>-124.30388</td>\n",
              "      <td>CGINS-DOSTAD-00223</td>\n",
              "      <td>2015-04-02 20:15:00</td>\n",
              "      <td>2015-09-22 07:48:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2858.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>44.63538</td>\n",
              "      <td>-124.30252</td>\n",
              "      <td>CGINS-DOSTAD-00482</td>\n",
              "      <td>2015-10-07 21:10:00</td>\n",
              "      <td>2016-05-16 21:09:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>192.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>44.63565</td>\n",
              "      <td>-124.30427</td>\n",
              "      <td>CGINS-DOSTAD-00313</td>\n",
              "      <td>2016-05-17 21:23:00</td>\n",
              "      <td>2016-09-28 15:52:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>940.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>44.63929</td>\n",
              "      <td>-124.30404</td>\n",
              "      <td>CGINS-DOSTAD-00217</td>\n",
              "      <td>2016-09-26 21:25:00</td>\n",
              "      <td>2017-04-22 13:24:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>964.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>44.63580</td>\n",
              "      <td>-124.30388</td>\n",
              "      <td>CGINS-DOSTAD-00220</td>\n",
              "      <td>2017-04-20 17:23:00</td>\n",
              "      <td>2017-10-15 19:06:32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2846.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>44.63925</td>\n",
              "      <td>-124.30407</td>\n",
              "      <td>CGINS-DOSTAD-00484</td>\n",
              "      <td>2017-10-10 02:21:08</td>\n",
              "      <td>2018-04-04 13:57:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>972.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>44.63567</td>\n",
              "      <td>-124.30418</td>\n",
              "      <td>CGINS-DOSTAD-00223</td>\n",
              "      <td>2018-04-03 01:17:00</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1268.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>44.63833</td>\n",
              "      <td>-124.30388</td>\n",
              "      <td>CGINS-FLORTD-01123</td>\n",
              "      <td>2015-04-02 20:15:00</td>\n",
              "      <td>2015-09-22 07:48:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2473.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>44.63538</td>\n",
              "      <td>-124.30252</td>\n",
              "      <td>CGINS-FLORTD-01303</td>\n",
              "      <td>2015-10-07 21:10:00</td>\n",
              "      <td>2016-05-16 21:09:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1198.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>44.63565</td>\n",
              "      <td>-124.30427</td>\n",
              "      <td>CGINS-FLORTD-01152</td>\n",
              "      <td>2016-05-17 21:23:00</td>\n",
              "      <td>2016-09-28 15:52:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1196.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>44.63929</td>\n",
              "      <td>-124.30404</td>\n",
              "      <td>CGINS-FLORTD-01153</td>\n",
              "      <td>2016-09-26 21:25:00</td>\n",
              "      <td>2017-04-22 13:24:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>1757.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>44.63580</td>\n",
              "      <td>-124.30388</td>\n",
              "      <td>CGINS-FLORTD-01290</td>\n",
              "      <td>2017-04-20 17:23:00</td>\n",
              "      <td>2017-10-15 19:06:32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1196.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>44.63925</td>\n",
              "      <td>-124.30407</td>\n",
              "      <td>CGINS-FLORTD-01153</td>\n",
              "      <td>2017-10-10 02:21:08</td>\n",
              "      <td>2018-04-04 13:57:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>1757.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>44.63567</td>\n",
              "      <td>-124.30418</td>\n",
              "      <td>CGINS-FLORTD-01290</td>\n",
              "      <td>2018-04-03 01:17:00</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    asset_id  deployment  latitude  longitude              sensor  \\\n",
              "0     1676.0         1.0  44.63833 -124.30388  CGINS-CTDBPC-50012   \n",
              "1      791.0         2.0  44.63538 -124.30252  CGINS-CTDBPC-07243   \n",
              "2     1586.0         3.0  44.63565 -124.30427  CGINS-CTDBPC-50057   \n",
              "3     1678.0         4.0  44.63929 -124.30404  CGINS-CTDBPC-50011   \n",
              "4     1683.0         5.0  44.63580 -124.30388  CGINS-CTDBPC-50014   \n",
              "5      946.0         6.0  44.63925 -124.30407  CGINS-CTDBPC-50188   \n",
              "6     1662.0         7.0  44.63567 -124.30418  CGINS-CTDBPC-50007   \n",
              "7      972.0         1.0  44.63833 -124.30388  CGINS-DOSTAD-00223   \n",
              "8     2858.0         2.0  44.63538 -124.30252  CGINS-DOSTAD-00482   \n",
              "9      192.0         3.0  44.63565 -124.30427  CGINS-DOSTAD-00313   \n",
              "10     940.0         4.0  44.63929 -124.30404  CGINS-DOSTAD-00217   \n",
              "11     964.0         5.0  44.63580 -124.30388  CGINS-DOSTAD-00220   \n",
              "12    2846.0         6.0  44.63925 -124.30407  CGINS-DOSTAD-00484   \n",
              "13     972.0         7.0  44.63567 -124.30418  CGINS-DOSTAD-00223   \n",
              "14    1268.0         1.0  44.63833 -124.30388  CGINS-FLORTD-01123   \n",
              "15    2473.0         2.0  44.63538 -124.30252  CGINS-FLORTD-01303   \n",
              "16    1198.0         3.0  44.63565 -124.30427  CGINS-FLORTD-01152   \n",
              "17    1196.0         4.0  44.63929 -124.30404  CGINS-FLORTD-01153   \n",
              "18    1757.0         5.0  44.63580 -124.30388  CGINS-FLORTD-01290   \n",
              "19    1196.0         6.0  44.63925 -124.30407  CGINS-FLORTD-01153   \n",
              "20    1757.0         7.0  44.63567 -124.30418  CGINS-FLORTD-01290   \n",
              "\n",
              "                 start                 stop  \n",
              "0  2015-04-02 20:15:00  2015-09-22 07:48:00  \n",
              "1  2015-10-07 21:10:00  2016-05-16 21:09:00  \n",
              "2  2016-05-17 21:23:00  2016-09-28 15:52:00  \n",
              "3  2016-09-26 21:25:00  2017-04-22 13:24:00  \n",
              "4  2017-04-20 17:23:00  2017-10-15 19:06:32  \n",
              "5  2017-10-10 02:21:08  2018-04-04 13:57:00  \n",
              "6  2018-04-03 01:17:00                 None  \n",
              "7  2015-04-02 20:15:00  2015-09-22 07:48:00  \n",
              "8  2015-10-07 21:10:00  2016-05-16 21:09:00  \n",
              "9  2016-05-17 21:23:00  2016-09-28 15:52:00  \n",
              "10 2016-09-26 21:25:00  2017-04-22 13:24:00  \n",
              "11 2017-04-20 17:23:00  2017-10-15 19:06:32  \n",
              "12 2017-10-10 02:21:08  2018-04-04 13:57:00  \n",
              "13 2018-04-03 01:17:00                 None  \n",
              "14 2015-04-02 20:15:00  2015-09-22 07:48:00  \n",
              "15 2015-10-07 21:10:00  2016-05-16 21:09:00  \n",
              "16 2016-05-17 21:23:00  2016-09-28 15:52:00  \n",
              "17 2016-09-26 21:25:00  2017-04-22 13:24:00  \n",
              "18 2017-04-20 17:23:00  2017-10-15 19:06:32  \n",
              "19 2017-10-10 02:21:08  2018-04-04 13:57:00  \n",
              "20 2018-04-03 01:17:00                 None  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "metadata": {
        "id": "Vdzy0ZUOSfr_",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 4c. Annotations\n",
        "\n",
        "Finally, let's pull any relevant annotations for the CTD, dissolved oxygen, nitrogen, and 3-wavelength fluorometer instruments."
      ]
    },
    {
      "metadata": {
        "id": "cbRbYWRQ8OTi",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 114
        },
        "outputId": "9452824a-9422-42f4-ea1e-c718e74077e6",
        "executionInfo": {
          "elapsed": 384,
          "status": "ok",
          "timestamp": 1528212563820,
          "user": {
            "displayName": "Sage Lichtenwalner",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "107661401208389246829"
          },
          "user_tz": 240
        }
      },
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame() # Setup empty array\n",
        "\n",
        "nodes = dict(RID27=['03-CTDBPC000','04-DOSTAD000','02-FLORTD000'],RID26=['07-NUTNRB000'])\n",
        "sites = ['CE07SHSM','CE02SHSM']\n",
        "\n",
        "for node, instrument in nodes.items():\n",
        "    for site in sites:\n",
        "        substr='{}-{}'.format(site, node)\n",
        "        for ins in instrument:\n",
        "            refdes ='{}-{}'.format(substr, ins)\n",
        "\n",
        "            params = {\n",
        "                'beginDT':int(datetime.date(2015,4,2).strftime('%s'))*1000,\n",
        "                'endDT':int(datetime.date(2018,7,18).strftime('%s'))*1000,\n",
        "                'refdes':refdes\n",
        "            }\n",
        "            r = requests.get(ANNO_API, params=params, auth=(USERNAME, TOKEN))\n",
        "            data = r.json()\n",
        "\n",
        "            for d in data:\n",
        "                df = df.append({\n",
        "                'annotation': d['annotation'],\n",
        "                'start': convert_time(d['beginDT']),\n",
        "                'stop': convert_time(d['endDT']),\n",
        "                'site': d['subsite'],\n",
        "                'node': d['node'],\n",
        "                'sensor': d['sensor'],\n",
        "                'id': d['id']\n",
        "                }, ignore_index=True)\n",
        "                pd.set_option('display.max_colwidth', -1) # Show the full annotation text\n",
        "df"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>annotation</th>\n",
              "      <th>id</th>\n",
              "      <th>node</th>\n",
              "      <th>sensor</th>\n",
              "      <th>site</th>\n",
              "      <th>start</th>\n",
              "      <th>stop</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CE07SHSM no longer able to recharge batteries (PSC)\\r\\r\\n\\r\\r\\nThe mooring stopped receiving power from photo voltaic panel #1 of 4 on Nov-2. By Nov-20, the mooring stopped receiving power from two more solar panels (PV2 &amp; PV4) and one of two wind turbines (WT2). This indicates the Power System Controller (PSC) they connect to is failing. Mooring components will be shut down as the mooring loses the ability to recharge its batteries.\\r\\r\\n\\r\\r\\n</td>\n",
              "      <td>1237.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>CE07SHSM</td>\n",
              "      <td>2017-12-15 14:05:22</td>\n",
              "      <td>2017-12-15 14:05:22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CE07SHSM no longer able to recharge batteries (PSC)\\r\\r\\n\\r\\r\\nThe mooring stopped receiving power from photo voltaic panel #1 of 4 on Nov-2. By Nov-20, the mooring stopped receiving power from two more solar panels (PV2 &amp; PV4) and one of two wind turbines (WT2). This indicates the Power System Controller (PSC) they connect to is failing. Mooring components will be shut down as the mooring loses the ability to recharge its batteries.\\r\\r\\n\\r\\r\\n</td>\n",
              "      <td>1237.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>CE07SHSM</td>\n",
              "      <td>2017-12-15 14:05:22</td>\n",
              "      <td>2017-12-15 14:05:22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CE07SHSM no longer able to recharge batteries (PSC)\\r\\r\\n\\r\\r\\nThe mooring stopped receiving power from photo voltaic panel #1 of 4 on Nov-2. By Nov-20, the mooring stopped receiving power from two more solar panels (PV2 &amp; PV4) and one of two wind turbines (WT2). This indicates the Power System Controller (PSC) they connect to is failing. Mooring components will be shut down as the mooring loses the ability to recharge its batteries.\\r\\r\\n\\r\\r\\n</td>\n",
              "      <td>1237.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>CE07SHSM</td>\n",
              "      <td>2017-12-15 14:05:22</td>\n",
              "      <td>2017-12-15 14:05:22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>The Satlantic ISUS instrument has been discontinued, and all OOI ISUS units have been converted to the Sea-Bird SUNA model. A new data parser is in development, and any resulting data gaps will be filled once the parser has been delivered and the data are processed.</td>\n",
              "      <td>1412.0</td>\n",
              "      <td>RID26</td>\n",
              "      <td>07-NUTNRB000</td>\n",
              "      <td>CE07SHSM</td>\n",
              "      <td>2017-12-22 19:00:30</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CE07SHSM no longer able to recharge batteries (PSC)\\r\\r\\n\\r\\r\\nThe mooring stopped receiving power from photo voltaic panel #1 of 4 on Nov-2. By Nov-20, the mooring stopped receiving power from two more solar panels (PV2 &amp; PV4) and one of two wind turbines (WT2). This indicates the Power System Controller (PSC) they connect to is failing. Mooring components will be shut down as the mooring loses the ability to recharge its batteries.\\r\\r\\n\\r\\r\\n</td>\n",
              "      <td>1237.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>CE07SHSM</td>\n",
              "      <td>2017-12-15 14:05:22</td>\n",
              "      <td>2017-12-15 14:05:22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Communications with instruments on the NSIF for CE02SHSM are offline. Monitoring current draws to the NSIF shows a pattern of increased and expected current draws every 15 minutes, corresponding to the instrument sampling schedules. This suggests that the DCLs and attached instruments are still operating, but communications to the system are offline, reason unknown.\\n\\nAffected systems are:\\nCPM2\\n\\nDCL26\\nADCPT\\nVELPT\\nPHSEN\\nuCSPP (acoustic modem communications)\\nNUTNR\\nSPKIR\\n\\nDCL27\\nOPTAAFLORT\\nDOSTA\\nCTDBP\\n\\nNSIF communicated starting again early on the 14th. Logs from NSIF systems indicate that the systems and instruments are still working, pointing to a communications issue between the NSIF and the surface buoy telemetry system.</td>\n",
              "      <td>865.0</td>\n",
              "      <td>RID26</td>\n",
              "      <td>None</td>\n",
              "      <td>CE02SHSM</td>\n",
              "      <td>2017-05-09 00:00:00</td>\n",
              "      <td>2017-05-14 00:00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Communications with instruments on the NSIF for CE02SHSM are offline. Monitoring current draws to the NSIF shows a pattern of increased and expected current draws every 15 minutes, corresponding to the instrument sampling schedules. This suggests that the DCLs and attached instruments are still operating, but communications to the system are offline, reason unknown.\\n\\nAffected systems are:\\nCPM2\\n\\nDCL26\\nADCPT\\nVELPT\\nPHSEN\\nuCSPP (acoustic modem communications)\\nNUTNR\\nSPKIR\\n\\nDCL27\\nOPTAAFLORT\\nDOSTA\\nCTDBP\\n\\nNSIF communicated starting again early on the 14th. Logs from NSIF systems indicate that the systems and instruments are still working, pointing to a communications issue between the NSIF and the surface buoy telemetry system.</td>\n",
              "      <td>877.0</td>\n",
              "      <td>RID26</td>\n",
              "      <td>None</td>\n",
              "      <td>CE02SHSM</td>\n",
              "      <td>2017-05-09 00:00:00</td>\n",
              "      <td>2017-05-14 00:00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>NUTNR has been showing light values equivalent to dark values (i.e. all zeros) since 2 August.</td>\n",
              "      <td>880.0</td>\n",
              "      <td>RID26</td>\n",
              "      <td>07-NUTNRB000</td>\n",
              "      <td>CE02SHSM</td>\n",
              "      <td>2016-08-02 00:00:00</td>\n",
              "      <td>2016-09-28 00:00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>The Satlantic ISUS instrument has been discontinued, and all OOI ISUS units have been converted to the Sea-Bird SUNA model. A new data parser is in development, and any resulting data gaps will be filled once the parser has been delivered and the data are processed.</td>\n",
              "      <td>1409.0</td>\n",
              "      <td>RID26</td>\n",
              "      <td>07-NUTNRB000</td>\n",
              "      <td>CE02SHSM</td>\n",
              "      <td>2018-04-04 12:30:23</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    annotation  \\\n",
              "0  CE07SHSM no longer able to recharge batteries (PSC)\\r\\r\\n\\r\\r\\nThe mooring stopped receiving power from photo voltaic panel #1 of 4 on Nov-2. By Nov-20, the mooring stopped receiving power from two more solar panels (PV2 & PV4) and one of two wind turbines (WT2). This indicates the Power System Controller (PSC) they connect to is failing. Mooring components will be shut down as the mooring loses the ability to recharge its batteries.\\r\\r\\n\\r\\r\\n                                                                                                                                                                                                                                                                                                             \n",
              "1  CE07SHSM no longer able to recharge batteries (PSC)\\r\\r\\n\\r\\r\\nThe mooring stopped receiving power from photo voltaic panel #1 of 4 on Nov-2. By Nov-20, the mooring stopped receiving power from two more solar panels (PV2 & PV4) and one of two wind turbines (WT2). This indicates the Power System Controller (PSC) they connect to is failing. Mooring components will be shut down as the mooring loses the ability to recharge its batteries.\\r\\r\\n\\r\\r\\n                                                                                                                                                                                                                                                                                                             \n",
              "2  CE07SHSM no longer able to recharge batteries (PSC)\\r\\r\\n\\r\\r\\nThe mooring stopped receiving power from photo voltaic panel #1 of 4 on Nov-2. By Nov-20, the mooring stopped receiving power from two more solar panels (PV2 & PV4) and one of two wind turbines (WT2). This indicates the Power System Controller (PSC) they connect to is failing. Mooring components will be shut down as the mooring loses the ability to recharge its batteries.\\r\\r\\n\\r\\r\\n                                                                                                                                                                                                                                                                                                             \n",
              "3  The Satlantic ISUS instrument has been discontinued, and all OOI ISUS units have been converted to the Sea-Bird SUNA model. A new data parser is in development, and any resulting data gaps will be filled once the parser has been delivered and the data are processed.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    \n",
              "4  CE07SHSM no longer able to recharge batteries (PSC)\\r\\r\\n\\r\\r\\nThe mooring stopped receiving power from photo voltaic panel #1 of 4 on Nov-2. By Nov-20, the mooring stopped receiving power from two more solar panels (PV2 & PV4) and one of two wind turbines (WT2). This indicates the Power System Controller (PSC) they connect to is failing. Mooring components will be shut down as the mooring loses the ability to recharge its batteries.\\r\\r\\n\\r\\r\\n                                                                                                                                                                                                                                                                                                             \n",
              "5  Communications with instruments on the NSIF for CE02SHSM are offline. Monitoring current draws to the NSIF shows a pattern of increased and expected current draws every 15 minutes, corresponding to the instrument sampling schedules. This suggests that the DCLs and attached instruments are still operating, but communications to the system are offline, reason unknown.\\n\\nAffected systems are:\\nCPM2\\n\\nDCL26\\nADCPT\\nVELPT\\nPHSEN\\nuCSPP (acoustic modem communications)\\nNUTNR\\nSPKIR\\n\\nDCL27\\nOPTAAFLORT\\nDOSTA\\nCTDBP\\n\\nNSIF communicated starting again early on the 14th. Logs from NSIF systems indicate that the systems and instruments are still working, pointing to a communications issue between the NSIF and the surface buoy telemetry system.   \n",
              "6  Communications with instruments on the NSIF for CE02SHSM are offline. Monitoring current draws to the NSIF shows a pattern of increased and expected current draws every 15 minutes, corresponding to the instrument sampling schedules. This suggests that the DCLs and attached instruments are still operating, but communications to the system are offline, reason unknown.\\n\\nAffected systems are:\\nCPM2\\n\\nDCL26\\nADCPT\\nVELPT\\nPHSEN\\nuCSPP (acoustic modem communications)\\nNUTNR\\nSPKIR\\n\\nDCL27\\nOPTAAFLORT\\nDOSTA\\nCTDBP\\n\\nNSIF communicated starting again early on the 14th. Logs from NSIF systems indicate that the systems and instruments are still working, pointing to a communications issue between the NSIF and the surface buoy telemetry system.   \n",
              "7  NUTNR has been showing light values equivalent to dark values (i.e. all zeros) since 2 August.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                \n",
              "8  The Satlantic ISUS instrument has been discontinued, and all OOI ISUS units have been converted to the Sea-Bird SUNA model. A new data parser is in development, and any resulting data gaps will be filled once the parser has been delivered and the data are processed.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    \n",
              "\n",
              "       id   node        sensor      site               start  \\\n",
              "0  1237.0  None   None          CE07SHSM 2017-12-15 14:05:22   \n",
              "1  1237.0  None   None          CE07SHSM 2017-12-15 14:05:22   \n",
              "2  1237.0  None   None          CE07SHSM 2017-12-15 14:05:22   \n",
              "3  1412.0  RID26  07-NUTNRB000  CE07SHSM 2017-12-22 19:00:30   \n",
              "4  1237.0  None   None          CE07SHSM 2017-12-15 14:05:22   \n",
              "5  865.0   RID26  None          CE02SHSM 2017-05-09 00:00:00   \n",
              "6  877.0   RID26  None          CE02SHSM 2017-05-09 00:00:00   \n",
              "7  880.0   RID26  07-NUTNRB000  CE02SHSM 2016-08-02 00:00:00   \n",
              "8  1409.0  RID26  07-NUTNRB000  CE02SHSM 2018-04-04 12:30:23   \n",
              "\n",
              "                  stop  \n",
              "0  2017-12-15 14:05:22  \n",
              "1  2017-12-15 14:05:22  \n",
              "2  2017-12-15 14:05:22  \n",
              "3  None                 \n",
              "4  2017-12-15 14:05:22  \n",
              "5  2017-05-14 00:00:00  \n",
              "6  2017-05-14 00:00:00  \n",
              "7  2016-09-28 00:00:00  \n",
              "8  None                 "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 155
        }
      ]
    },
    {
      "metadata": {
        "id": "urCmIPH7SfsC",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 5. Full Dataset\n",
        "\n",
        "Now let's take a look at a large range of data. We shall look at all of Deployment 1-5. First we need to add some additional libraries to our Python environment."
      ]
    },
    {
      "metadata": {
        "id": "UN3GufuxakLe",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# Plots\n",
        "# The last column is the depth of the instrument (used in the plots)\n",
        "coastal_CTD_P = [\n",
        "  ['CE07SHSM','RID27','03-CTDBPC000',7],\n",
        "  ['CE02SHSM','RID27','03-CTDBPC000',7]]\n",
        "\n",
        "coastal_CTD_T = [\n",
        "  ['CE07SHSM','RID27','03-CTDBPC000',7],\n",
        "  ['CE02SHSM','RID27','03-CTDBPC000',7]]\n",
        "\n",
        "coastal_DO = [\n",
        "  ['CE07SHSM','RID27','04-DOSTAD000',7],\n",
        "  ['CE02SHSM','RID27','04-DOSTAD000',7]]\n",
        "  \n",
        "coastal_Nitrate = [\n",
        "  ['CE07SHSM','RID26','07-NUTNRB000',7],\n",
        "  ['CE02SHSM','RID26','07-NUTNRB000',7]]\n",
        "\n",
        "coastal_Chlorophyll = [\n",
        "  ['CE07SHSM','RID27','02-FLORTD000',7],\n",
        "  ['CE02SHSM','RID27','02-FLORTD000',7]]\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "R02O5Vv5v5CR",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# API URL template for CTD, DO, nitrate, chlorophyll\n",
        "\n",
        "stream_i = ['ctdbp_cdef_dcl_instrument','ctdbp_cdef_dcl_instrument','dosta_abcdjm_dcl_instrument','nutnr_b_dcl_conc_instrument','flort_sample']\n",
        "parameter = ['6','2','14','315','22']\n",
        "url_template = []\n",
        "for i in range(len(stream_i)):\n",
        "    url_template.append(DATA_API+\\\n",
        "      '%s/'+\\\n",
        "      '%s/'+\\\n",
        "      '%s/'+\\\n",
        "      'telemetered/'+\\\n",
        "      stream_i[i]+'?'+\\\n",
        "      'limit=1000'+\\\n",
        "      '&parameters=7,'+parameter[i])   \n",
        " "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "GSvtCoziakLb",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# Time Processing Routines \n",
        "ntp_epoch = datetime.datetime(1900, 1, 1)\n",
        "unix_epoch = datetime.datetime(1970, 1, 1)\n",
        "ntp_delta = (unix_epoch - ntp_epoch).total_seconds()\n",
        "\n",
        "def ntp_seconds_to_datetime(ntp_seconds):\n",
        "    return datetime.datetime.utcfromtimestamp(ntp_seconds - ntp_delta).replace(microsecond=0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "lbCnDfjRakLd",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# Crude function to retrieve and reformat synchronous data from the OOI API\n",
        "def get_data(instruments,parameter,url):\n",
        "  out = []\n",
        "  for jj in range(len(instruments)):\n",
        "    data_request_url = url % (instruments[jj][0],instruments[jj][1],instruments[jj][2])\n",
        "    print(data_request_url)\n",
        "    r = requests.get(data_request_url, auth=(USERNAME, TOKEN))\n",
        "    data = r.json()\n",
        "    print(instruments[jj]) \n",
        "    print(len(data))\n",
        "    time = []\n",
        "    values = []\n",
        "    for i in range(len(data)):\n",
        "      time.append(ntp_seconds_to_datetime(data[i]['time']))\n",
        "      values.append(data[i][parameter])\n",
        "    out.append({'time':time,'value':values});\n",
        "  return out"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "oQuDxiSHx9ch",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 341
        },
        "outputId": "de7836af-30db-4a68-e69f-0e7cacfa5ead",
        "executionInfo": {
          "elapsed": 58200,
          "status": "ok",
          "timestamp": 1529077814477,
          "user": {
            "displayName": "Sage Lichtenwalner",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "107661401208389246829"
          },
          "user_tz": 240
        }
      },
      "cell_type": "code",
      "source": [
        "# Grab the Coastal Data\n",
        "CTDP_data = get_data(coastal_CTD_P,'pressure',url_template[1])\n",
        "CTDT_data = get_data(coastal_CTD_T,'temp',url_template[0])\n",
        "DO_data = get_data(coastal_DO,'dissolved_oxygen',url_template[2])\n",
        "Nitrate_data = get_data(coastal_Nitrate,'nitrate_concentration',url_template[3])\n",
        "Chlorophyll_data = get_data(coastal_Chlorophyll,'fluorometric_chlorophyll_a',url_template[4])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE07SHSM/RID27/03-CTDBPC000/telemetered/ctdbp_cdef_dcl_instrument?limit=1000&parameters=7,2\n",
            "['CE07SHSM', 'RID27', '03-CTDBPC000', 7]\n",
            "926\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE02SHSM/RID27/03-CTDBPC000/telemetered/ctdbp_cdef_dcl_instrument?limit=1000&parameters=7,2\n",
            "['CE02SHSM', 'RID27', '03-CTDBPC000', 7]\n",
            "999\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE07SHSM/RID27/03-CTDBPC000/telemetered/ctdbp_cdef_dcl_instrument?limit=1000&parameters=7,6\n",
            "['CE07SHSM', 'RID27', '03-CTDBPC000', 7]\n",
            "926\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE02SHSM/RID27/03-CTDBPC000/telemetered/ctdbp_cdef_dcl_instrument?limit=1000&parameters=7,6\n",
            "['CE02SHSM', 'RID27', '03-CTDBPC000', 7]\n",
            "999\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE07SHSM/RID27/04-DOSTAD000/telemetered/dosta_abcdjm_dcl_instrument?limit=1000&parameters=7,14\n",
            "['CE07SHSM', 'RID27', '04-DOSTAD000', 7]\n",
            "781\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE02SHSM/RID27/04-DOSTAD000/telemetered/dosta_abcdjm_dcl_instrument?limit=1000&parameters=7,14\n",
            "['CE02SHSM', 'RID27', '04-DOSTAD000', 7]\n",
            "977\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE07SHSM/RID26/07-NUTNRB000/telemetered/nutnr_b_dcl_conc_instrument?limit=1000&parameters=7,315\n",
            "['CE07SHSM', 'RID26', '07-NUTNRB000', 7]\n",
            "746\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE02SHSM/RID26/07-NUTNRB000/telemetered/nutnr_b_dcl_conc_instrument?limit=1000&parameters=7,315\n",
            "['CE02SHSM', 'RID26', '07-NUTNRB000', 7]\n",
            "909\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE07SHSM/RID27/02-FLORTD000/telemetered/flort_sample?limit=1000&parameters=7,22\n",
            "['CE07SHSM', 'RID27', '02-FLORTD000', 7]\n",
            "878\n",
            "https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv/CE02SHSM/RID27/02-FLORTD000/telemetered/flort_sample?limit=1000&parameters=7,22\n",
            "['CE02SHSM', 'RID27', '02-FLORTD000', 7]\n",
            "921\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "279EVDjBSfsJ",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.patches as mpatches\n",
        "import seaborn as sns # package for nice plotting defaults\n",
        "sns.set()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "DAySNnvAakLj",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 1166
        },
        "outputId": "6aa16e1d-81eb-46c8-8b84-e2395653b20f",
        "executionInfo": {
          "elapsed": 1320,
          "status": "ok",
          "timestamp": 1529077815808,
          "user": {
            "displayName": "Sage Lichtenwalner",
            "photoUrl": "https://lh3.googleusercontent.com/a/default-user=s128",
            "userId": "107661401208389246829"
          },
          "user_tz": 240
        }
      },
      "cell_type": "code",
      "source": [
        "# Plot the Coastal CTD, DO, Nitrate, Chlorophyll\n",
        "plt.close()\n",
        "fig,(ax1,ax2,ax3,ax4,ax5) = plt.subplots(5,1, sharex=True, figsize=(8,12))\n",
        "\n",
        "for jj in range(len(CTDP_data)):\n",
        "    ax1.scatter(CTDP_data[jj]['time'], CTDP_data[jj]['value'], marker='.')\n",
        "    ax1.set(ylabel=coastal_CTD_P[jj][0])  \n",
        "for jj in range(len(CTDT_data)):\n",
        "    ax2.scatter(CTDT_data[jj]['time'], CTDT_data[jj]['value'], marker='.')\n",
        "    ax2.set(ylabel=coastal_CTD_T[jj][0])\n",
        "for jj in range(len(DO_data)):\n",
        "    ax3.scatter(DO_data[jj]['time'], DO_data[jj]['value'], marker='.')\n",
        "    ax3.set(ylabel=coastal_DO[jj][0])\n",
        "for jj in range(len(Nitrate_data)):\n",
        "    ax4.scatter(Nitrate_data[jj]['time'], Nitrate_data[jj]['value'], marker='.')\n",
        "    ax4.set(ylabel=coastal_Nitrate[jj][0])\n",
        "for jj in range(len(Chlorophyll_data)):\n",
        "    ax5.scatter(Chlorophyll_data[jj]['time'], Chlorophyll_data[jj]['value'], marker='.')\n",
        "    ax5.set(ylabel=coastal_Chlorophyll[jj][0])\n",
        "  \n",
        "plt.xlim(datetime.date(2015,4,2),datetime.date(2018,7,18))\n",
        "ax1.set_ylim(0,12)\n",
        "plt.xlabel('time (year-month)')\n",
        "ax1.set_ylabel('Pressure (dbar)')\n",
        "plt.xticks(rotation=30)\n",
        "ax1.title.set_text('OOI Coastal CTD - Pressure')\n",
        "fig.subplots_adjust(top=0.95)\n",
        "\n",
        "ax2.set_ylim(0,25)\n",
        "ax2.set_ylabel('Temp. (C)')\n",
        "ax2.title.set_text('OOI Coastal CTD - Temperature')\n",
        "\n",
        "ax3.set_ylim(0,700)\n",
        "ax3.set_ylabel('DO (µmol/L)')\n",
        "ax3.title.set_text('OOI Coastal CTD - Dissolved Oxygen')\n",
        "\n",
        "ax4.set_ylim(-150,150)\n",
        "ax4.set_ylabel('[Nitrate] (µmol/L)')\n",
        "ax4.title.set_text('OOI Coastal CTD - Nitrate Concentration')\n",
        "\n",
        "ax5.set_ylim(0,50)\n",
        "ax5.set_ylabel('[Chlorophyll] (µg/L)')\n",
        "ax5.title.set_text('OOI Coastal CTD - Chlorophyll Concentration')\n",
        "\n",
        "# data lebel\n",
        "\n",
        "blue_patch = mpatches.Patch(color='blue', label='Washington Shelf')\n",
        "green_patch = mpatches.Patch(color='green', label='Oregon Shelf')\n",
        "plt.legend(handles=[blue_patch,green_patch])\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x864 with 5 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "OPAv2dCOSfsN",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "The above plots are results of CTD (particularly, pressure and temperature), dissolved oxygen, nitrate, and 3-wavelength fluorometer (particularly chlorophyll concentration) as a function of time since they have been measured. \n",
        "\n",
        "According to those plots, there is no obvious pressure variation in both sites. The temperature has a normal fluctuation that it increases during summertime, and decreases during wintertime. \n",
        "\n",
        "For ecological aspects, the fluctuation of dissolved oxygen seems to invesely proportional the nitrate and chlorophyll concentration. These are needed to compare with external dataset of USGS discharge variation."
      ]
    },
    {
      "metadata": {
        "id": "bZc2CQnCSfsN",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 6. Comparison to External Dataset (USGS)"
      ]
    },
    {
      "metadata": {
        "id": "nY3HUV20SfsN",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "![Daily Discharge for Chehalis River, Doty, WA](https://natwebcaww01.wr.usgs.gov/nwisweb/data/img/USGS.12020000.148398.00060.00003.20150402.20180718.log.0..pres.gif)"
      ]
    },
    {
      "metadata": {
        "id": "ZwidmG4ESfsO",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Reference: https://waterdata.usgs.gov/nwis/dv?cb_00060=on&format=gif_default&site_no=12020000&referred_module=sw&period=&begin_date=2015-04-02&end_date=2018-07-18"
      ]
    },
    {
      "metadata": {
        "id": "vjgTQ8HlSfsO",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "![Daily Discharge for Columbia River,Quincy, OR](https://natwebvaww01.er.usgs.gov/nwisweb/data/img/USGS.14246900.114430.00060.00003.20150402.20180718.log.0..pres.gif)\n",
        " "
      ]
    },
    {
      "metadata": {
        "id": "kg6diDjPSfsO",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Reference: https://waterdata.usgs.gov/nwis/dv?cb_00060=on&format=gif_default&site_no=14246900&referred_module=sw&period=&begin_date=2015-04-02&end_date=2018-07-18"
      ]
    },
    {
      "metadata": {
        "id": "JlLFWxmFSfsP",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "![Daily Discharge for Yaquina River,Chitwood, OR](https://natwebvaww01.er.usgs.gov/nwisweb/data/img/USGS.14306030.114492.00060.00003.19880402.19910718.log.0..pres.gif)"
      ]
    },
    {
      "metadata": {
        "id": "Hyy0TVdTSfsP",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Reference: https://waterdata.usgs.gov/nwis/dv?cb_00060=on&format=gif_default&site_no=14306030&referred_module=sw&period=&begin_date=1988-04-02&end_date=1991-07-18"
      ]
    },
    {
      "metadata": {
        "id": "PJKa6AciSfsP",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Note, the discharge fluctuation of Yaquina River near Chitwood, OR does not have a recent record. The way I did is to assume that there is not much variation of fluctuation between 1989-1991 and nowadays. \n",
        "\n",
        "The fluctuation says that discharge increases from October to March/April, but decreases between April and October. This can be described as wet winter-dry summer. The fluctuation of discharge somehow be related to the amount of sediment delivered to the ocean."
      ]
    },
    {
      "metadata": {
        "id": "VEQjsV5QSfsQ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 7. A Closer Look\n",
        "\n",
        "Now, let's look at one year between December 1, 2015 and December 1, 2016. This step is a part of the data that are from the previous step. The data points and time is closer, so the detail of key parameters changed during this time period are considered."
      ]
    },
    {
      "metadata": {
        "id": "oiIjM2FJSfsQ",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        },
        "outputId": "ac21aeb1-1f02-4e2e-a074-28fa2da275a7"
      },
      "cell_type": "code",
      "source": [
        "# Plot the Coastal Temperature, DO, Chlorophyll\n",
        "plt.close()\n",
        "fig,(ax1,ax2,ax3) = plt.subplots(3,1, sharex=True, figsize=(8,12))\n",
        "\n",
        "for jj in range(len(CTDT_data)):\n",
        "    ax1.scatter(CTDT_data[jj]['time'], CTDT_data[jj]['value'], marker='.')\n",
        "    ax1.set(ylabel=coastal_CTD_T[jj][0])\n",
        "for jj in range(len(DO_data)):\n",
        "    ax2.scatter(DO_data[jj]['time'], DO_data[jj]['value'], marker='.')\n",
        "    ax2.set(ylabel=coastal_DO[jj][0])\n",
        "for jj in range(len(Chlorophyll_data)):\n",
        "    ax3.scatter(Chlorophyll_data[jj]['time'], Chlorophyll_data[jj]['value'], marker='.')\n",
        "    ax3.set(ylabel=coastal_Chlorophyll[jj][0])\n",
        "  \n",
        "plt.xlim(datetime.date(2015,12,1),datetime.date(2016,12,1))\n",
        "ax1.set_ylim(0,25)\n",
        "plt.xlabel('time (year-month)')\n",
        "ax1.set_ylabel('Temp. (C)')\n",
        "plt.xticks(rotation=30)\n",
        "ax1.title.set_text('OOI Coastal CTD - Temperature')\n",
        "fig.subplots_adjust(top=0.95)\n",
        "\n",
        "ax2.set_ylim(0,700)\n",
        "ax2.set_ylabel('DO (µmol/L)')\n",
        "ax2.title.set_text('OOI Coastal CTD - Dissolved Oxygen')\n",
        "\n",
        "ax3.set_ylim(-5,50)\n",
        "ax3.set_ylabel('[Chlorophyll] (µg/L)')\n",
        "ax3.title.set_text('OOI Coastal CTD - Chlorophyll Concentration')\n",
        "\n",
        "# data lebel\n",
        "\n",
        "blue_patch = mpatches.Patch(color='blue', label='Washington Shelf')\n",
        "green_patch = mpatches.Patch(color='green', label='Oregon Shelf')\n",
        "plt.legend(handles=[blue_patch,green_patch])\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x864 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "2gZgQTbKSfsS",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "![Daily suspended sediment concentration for Yaquina River,Chitwood, OR](https://natwebvaww01.er.usgs.gov/nwisweb/data/img/USGS.14306030.114493.80154.00003.19721201.19731201..0..pres.gif)"
      ]
    },
    {
      "metadata": {
        "id": "Qgox5XEjSfsS",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Reference: https://waterdata.usgs.gov/nwis/dv?cb_80154=on&format=gif_default&site_no=14306030&referred_module=sw&period=&begin_date=1972-12-01&end_date=1973-12-01"
      ]
    },
    {
      "metadata": {
        "id": "lHKJdsKJSfsS",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "The one year cycle of water temperature, dissolved oxygen, and chlorophyll concentration is well illustrated in terms of explaining how ecosystem seasonally changes. When water temperature increases, light can penetrate and be absorbed by algeas and bacteria in the ocean. This causes an increase in productivity of photosynthesis. Simultaneously, the oxygen available in the water is consumed by this tiny creatures for photosyntheis processes. That's why the dissolved oxygen is reduced, while the concentration of chlorophyll increases."
      ]
    },
    {
      "metadata": {
        "id": "IEbR6DJtSfsT",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "An example of sediment derived from the Yaquina River during 1973 is assumed to behave as similar as today. The concentration of sediment is low during summer, and high during winter due to amount of precipitation. Moreover, it correlates to the productivity of chlorophyll concentration and the reduction of dissolved oxygen."
      ]
    },
    {
      "metadata": {
        "id": "dOrtCJGuSfsT",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## 8. Notable Results and Actions Needed\n",
        "\n",
        "Based on this (somewhat cursory) analysis of the Washington-Oregon shelf geology-ecosystem relationship, we note the following takeaways:\n",
        "\n",
        "- Pressure is constant \n",
        "- Temperature is fluctuation; high during summer, low during winter\n",
        "- The relationship between dissolved oxygen and nitrate-chlorophyll concentrations are invesely proportional due to the oygen consumption of algeas for photosysthesis and nitrogen production of bacterias for respiratory.\n",
        "- In Pacific Northwest, discharge records from Chehalis, Columbia, and Yaquina Rivers fluctuates due to wet winter-dry summer \n",
        "    - the ammount of sediment delivered is expected to behave similarly to the amount of discharge; high  sediment during high discharge, low sediment during low discharge\n",
        "    - low amount of dissolved oxygen, but high concentration of chlorophyll correlate with the presence of low sediment\n",
        " \n",
        "In order to strengthen results and interpretation, historical records and ocean/geology/biology concepts are needed for further actions:\n",
        "\n",
        "- flood dischrge histories \n",
        "- possible paleoearthquake records\n",
        "- deep concepts of ocean mixing, photosynthesis-respiratory concepts"
      ]
    }
  ]
}