{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2dea1b7d-b275-4ff8-8290-115d1e4e58d1",
   "metadata": {
    "id": "2dea1b7d-b275-4ff8-8290-115d1e4e58d1"
   },
   "source": [
    "# SoundCoop Paper - Figure for Case Study 3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49c2ab53-1fb8-42d4-a6fa-e7bb16c07891",
   "metadata": {},
   "source": [
    "This Jupyter Notebook applies the analysis and creates the subsequent plot for the Case Study 3 figure in the Wall et al A Collaborative Framework to Address Big Data Challenges in Marine Passive Acoustic Monitoring paper detailing the SoundCoop project. This case study discovers dominant sound sources using blue and fin whale call indices.\n",
    "\n",
    "The code pulls one-minute hybrid millidecade (HMD) spectra calculated for the Acoustic and Environmental Observation Network dataset (AEON5), NOAA-National Park Service Ocean Noise Reference Station Network dataset (NRS11), and Monterey Bay Aquarium Research Institute Monterey Accelerated Research System dataset (MARS). All data were recorded throughout 2021. \n",
    "\n",
    "AEON5 and NRS11 are hosted on the NOAA Open Data Dissemination Program Google Cloud Platform (GCP) bucket associated with the NOAA National Centers for Environmental Information Passive Acoustic Data Archive while MARS is hosted on the Amazon Web Services (AWS) Open Data Registry bucket associated with MBARI Pacific Ocean Sound Recordings. The weekly  call index (CI) was calculated for blue whale B calls and fin whale 20 Hz calls. For blue whales, the CI ratio was calculated as [42, 43 Hz] / [37, 50 Hz] where the 3rd and strongest harmonic of B calls occurs between 42 and 44 Hz, and 37 and 50 Hz represent frequency bands that would not include energy from a B call. CI was calculated for fin whale calls using [20, 21 Hz] / [12, 34 Hz]. The results are then binned to one-day resolution using the median and then aggregated further to one week resolution and plotted over time. \n",
    "\n",
    "NOAA OAR Pacific Marine Environmental Laboratory, Cooperative Institute for Marine Ecosystem and Resources Studies, National Marine Fisheries Service, NOS Office of National Marine Sanctuaries, and DOI NPS Natural Resource Stewardship and Science Directorate (2023). Hybrid Millidecade Spectra at 1 Minute Resolution Recorded at the Ocean Noise Reference Station Network (NRS). NOAA National Centers for Environmental Information. (https://doi.org/10.25921/tr4q-xa94).\n",
    "\n",
    "University of New Hampshire and Office of Naval Research (2023). Hybrid Millidecade Spectra at 1 Minute Resolution Recorded at the Acoustic and Environmental Observation Network (AEON) for the Office of Naval Research. NOAA National Centers for Environmental Information. (https://doi.org/10.25921/d21t-be25).\n",
    "\n",
    "Monterey Bay Aquarium Research Institute (2023). Hybrid Millidecade Spectra at 1 Minute Resolution Recorded at the Monterey Accelerated Research System (MARS) Cabled Observatory. NOAA National Centers for Environmental Information. (https://doi.org/10.25921/6gvv-dk87).\n",
    "\n",
    "contact: carrie.wall@noaa.gov"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b4a79f3-a9ee-4830-9377-00051a94415d",
   "metadata": {
    "id": "1b4a79f3-a9ee-4830-9377-00051a94415d",
    "tags": []
   },
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b96b0570-8b05-43a6-8ce4-cb4fea2e1095",
   "metadata": {},
   "source": [
    "To start, we need to install the required dependencies. This notebook has been tested in Python 3.11. You only need to run this once per environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "733ea265-8309-4506-bc95-2c4ded1c132d",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "733ea265-8309-4506-bc95-2c4ded1c132d",
    "outputId": "99da8caa-1335-49e0-b22b-dce79fb7756a",
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Requirement already satisfied: cffi>=1.0.1 in c:\\users\\cwall\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from argon2-cffi-bindings->argon2-cffi->minio) (1.16.0)\n",
      "Requirement already satisfied: pycparser in c:\\users\\cwall\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->minio) (2.22)\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path = ['.'] + sys.path\n",
    "!pip install pvlib\n",
    "!pip install lifewatch-pypam==0.3.2\n",
    "!pip install minio"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "325d18bc-8a4a-46f4-aa19-65eb34b38a7e",
   "metadata": {
    "id": "325d18bc-8a4a-46f4-aa19-65eb34b38a7e",
    "tags": []
   },
   "source": [
    "## Import packages"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c041d6b-6685-468e-b473-62a26c2a0874",
   "metadata": {},
   "source": [
    "We'll start importing all the packages we will need"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cb70157f-c555-4334-83ac-862c306d2ace",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pathlib\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from datetime import datetime\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "32a9fb8a-6034-41e1-988a-78944da2ccbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pypam.acoustic_survey import ASA\n",
    "import pypam.utils\n",
    "import pypam.plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0aa5ec52-cf35-4ca6-bc25-9cfe4a4a2c97",
   "metadata": {
    "id": "325d18bc-8a4a-46f4-aa19-65eb34b38a7e",
    "tags": []
   },
   "source": [
    "## Download the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cab776ec-2e9f-4876-bf59-69d4f0af6e6b",
   "metadata": {
    "id": "cab776ec-2e9f-4876-bf59-69d4f0af6e6b",
    "tags": []
   },
   "outputs": [],
   "source": [
    "from minio import Minio\n",
    "from minio.error import S3Error\n",
    "\n",
    "from pathlib import Path\n",
    "import os.path"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c3f7fa8-e3f8-496f-bc09-b4403f6a28e5",
   "metadata": {},
   "source": [
    "Let's define which stations will we download and the overall start and end date for downloading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2aeceffc-07c0-4637-a758-f6453ba49440",
   "metadata": {},
   "outputs": [],
   "source": [
    "stations_to_download_gp = ['AEON5', 'NRS11']\n",
    "stations_to_download_aws = ['MARS']\n",
    "first_date = '2021-01-01'\n",
    "last_date = '2022-12-31'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "636a5127-e3c3-4ce0-8213-e2a685f9dfd4",
   "metadata": {
    "id": "636a5127-e3c3-4ce0-8213-e2a685f9dfd4"
   },
   "source": [
    "Here we define the local paths where we will download the data and the output from this notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2a4ad259-bea3-47fe-a038-5505f7fa898f",
   "metadata": {
    "id": "2a4ad259-bea3-47fe-a038-5505f7fa898f",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Make the main storage folder\n",
    "local_path = '../../shared/data' # Change to your local path\n",
    "output_path = local_path + '/figures'\n",
    "if not os.path.isdir(local_path):\n",
    "    Path(local_path).mkdir()\n",
    "\n",
    "if not os.path.isdir(output_path):\n",
    "    Path(output_path).mkdir()\n",
    "\n",
    "for station in stations_to_download_gp + stations_to_download_aws:\n",
    "    station_path = Path(local_path).joinpath(station)\n",
    "    if not os.path.isdir(station_path):\n",
    "        Path(station_path).mkdir()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fc88ba01-17b9-401c-aca3-c69e71c86bdf",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "fc88ba01-17b9-401c-aca3-c69e71c86bdf",
    "outputId": "6df6d4c9-a333-4557-c501-45a5ca12a9ae",
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "def download_data_station(station_name, \n",
    "                          client_obj, \n",
    "                          bucket_str, \n",
    "                          prefix_str, \n",
    "                          data_path,\n",
    "                          name_format,\n",
    "                          start_datetime, \n",
    "                          end_datetime):\n",
    "    start_datetime_obj = datetime.fromisoformat(start_datetime) \n",
    "    end_datetime_obj = datetime.fromisoformat(end_datetime)\n",
    "    station_folder = pathlib.Path(data_path).joinpath(station_name)\n",
    "    if not station_folder.exists():\n",
    "        os.mkdir(station_folder)\n",
    "    objects = list(client_obj.list_objects(bucket_str, prefix=prefix_str))\n",
    "    ct = 0\n",
    "    for i, obj in enumerate(objects):\n",
    "        object_name = obj.object_name\n",
    "        path_name = pathlib.Path(object_name).name\n",
    "        if (not path_name.startswith('.')) & path_name.endswith('.nc'):\n",
    "            match = re.findall(r\"_(\\d+)\", path_name)[-1]\n",
    "            file_date = datetime.strptime(match, name_format)\n",
    "            # Here we filter by start and end time as all the data we will download is in the same period of time \n",
    "            if (file_date >= start_datetime_obj) & (file_date <= end_datetime_obj):\n",
    "                download_path = data_path + '/' + station_name + '/' + pathlib.Path(object_name).name\n",
    "                if os.path.isfile(download_path):\n",
    "                    print('Already downloaded: ' + download_path)\n",
    "                else:\n",
    "                    print('Download ' + str(ct) + ' of ' + str(len(objects)) + ': ' + download_path)\n",
    "                    object_data = client_obj.get_object(bucket_str, object_name)\n",
    "                    if not os.path.isdir(download_path):\n",
    "                        with open(str(download_path), 'wb') as file_data:\n",
    "                            for data in object_data:\n",
    "                                file_data.write(data)\n",
    "                    file_data.close()\n",
    "            else: \n",
    "                print('Ignored, out of selected period or not a netCDF file ' + path_name)\n",
    "        ct += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6edc01a2-b1ab-4d58-b72e-452d315f606a",
   "metadata": {},
   "source": [
    "We first define where the data are stored to be able to access it, and then we download the data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17c44c0b-c9cc-472c-a6a8-20f955c73916",
   "metadata": {},
   "source": [
    "Let's start with the GCP hosted datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b3801bfb-b51b-4476-b737-a1d7e757a3c5",
   "metadata": {
    "id": "b3801bfb-b51b-4476-b737-a1d7e757a3c5",
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210702_DAILY_MILLIDEC_MinRes_v2.nc\n",
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      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210705_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210706_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210707_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210708_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210709_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210710_DAILY_MILLIDEC_MinRes_v2.nc\n",
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      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210716_DAILY_MILLIDEC_MinRes_v2.nc\n",
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      "Already downloaded: ../../shared/data/AEON5/AEON5_AMAR501.2.16000_20210720_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191023_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191024_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191025_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191026_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191027_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191028_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191029_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191030_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191031_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191101_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191102_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191103_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191104_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191105_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191106_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191107_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191108_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191109_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191110_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191111_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191112_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191113_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191114_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191115_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191116_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191117_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191118_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191119_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191120_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191121_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191122_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191123_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191124_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191125_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191126_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191127_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191128_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191129_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191130_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191201_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191202_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191203_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191204_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191205_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191206_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191207_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191208_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191209_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191210_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191211_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191212_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191213_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191214_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191215_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191216_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191217_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191218_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191219_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191220_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191221_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191222_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191223_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191224_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191225_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191226_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191227_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191228_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191229_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191230_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20191231_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200101_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200102_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200103_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200104_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200105_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200106_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200107_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200108_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200109_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200110_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200111_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200112_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200113_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200114_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200115_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200116_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200117_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200118_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200119_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200120_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200121_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200122_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200123_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200124_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200125_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200126_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200127_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200128_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200129_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200130_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200131_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200201_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200202_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200203_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200204_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200205_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200206_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200207_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200208_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200209_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200210_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200211_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200212_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200213_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200214_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200215_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200216_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200217_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200218_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200219_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200220_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200221_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200222_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200223_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200224_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200225_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200226_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200227_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200228_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200229_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200301_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200302_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200303_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200304_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200305_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200306_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200307_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200308_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200309_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200310_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200311_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200312_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200313_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200314_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200315_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200316_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200317_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200318_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200319_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200320_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200321_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200322_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200323_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200324_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200325_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200326_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200327_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200328_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200329_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200330_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200331_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200401_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200402_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200403_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200404_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200405_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200406_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200407_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200408_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200409_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200410_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200411_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200412_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200413_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200414_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200415_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200416_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200417_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200418_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200419_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200420_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200421_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200422_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200423_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200424_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200425_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200426_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200427_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200428_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200429_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200430_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200501_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200502_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200503_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200504_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200505_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200506_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200507_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200508_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200509_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200510_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200511_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200512_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200513_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200514_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200515_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200516_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200517_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200518_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200519_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200520_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200521_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200522_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200523_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200524_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200525_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200526_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200527_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200528_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200529_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200530_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200531_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200601_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200602_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200603_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200604_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200605_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200606_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200607_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200608_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200609_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200610_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200611_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200612_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200613_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200614_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200615_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200616_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200617_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200618_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200619_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200620_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200621_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200622_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200623_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200624_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200625_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200626_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200627_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200628_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200629_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200630_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200701_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200702_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200703_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200704_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200705_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200706_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200707_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200708_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200709_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200710_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200711_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200712_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200713_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200714_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200715_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200716_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200717_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200718_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200719_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200720_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200721_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200722_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200723_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200724_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200725_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200726_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200727_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200728_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200729_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200730_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200731_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200801_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200802_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200803_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200804_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200805_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200806_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200807_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200808_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200809_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200810_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200811_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200812_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200813_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200814_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200815_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200816_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200817_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200818_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200819_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200820_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200821_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200822_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200823_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200824_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200825_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200826_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200827_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200828_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200829_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200830_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200831_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200901_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200902_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200903_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200904_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200905_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200906_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200907_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200908_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200909_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200910_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200911_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200912_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200913_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200914_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200915_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200916_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200917_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200918_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200919_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200920_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200921_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200922_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200923_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200924_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200925_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200926_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200927_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200928_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200929_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20200930_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201001_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201002_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201003_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201004_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201005_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201006_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201007_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201008_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201009_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201010_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201011_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201012_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201013_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201014_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201015_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201016_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201017_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201018_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201019_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201020_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201021_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201022_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201023_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201024_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201025_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201026_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201027_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201028_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201029_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201030_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201031_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201101_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201102_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201103_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201104_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201105_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201106_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201107_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201108_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201109_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201110_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201111_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201112_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201113_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201114_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201115_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201116_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201117_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201118_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201119_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201120_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201121_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201122_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201123_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201124_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201125_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201126_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201127_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201128_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201129_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201130_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201201_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201202_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201203_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201204_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201205_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201206_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201207_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201208_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201209_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201210_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201211_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201212_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201213_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201214_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201215_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201216_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201217_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201218_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201219_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201220_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201221_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201222_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201223_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201224_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201225_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201226_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201227_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201228_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201229_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201230_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Ignored, out of selected period or not a netCDF file NRS11_H5R6.1.5000_20201231_DAILY_MILLIDEC_MinRes_v2.nc\n",
      "Already downloaded: ../../shared/data/NRS11/NRS11_H5R6.1.5000_20210101_DAILY_MILLIDEC_MinRes_v2.nc\n",
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     ]
    }
   ],
   "source": [
    "CLIENT = Minio('storage.googleapis.com')\n",
    "BUCKET = 'noaa-passive-bioacoustic'\n",
    "PREFIX = 'soundcoop'\n",
    "CLIENT = Minio('storage.googleapis.com')\n",
    "name_format = '%Y%m%d'\n",
    "for station in stations_to_download_gp: \n",
    "    download_data_station(station, CLIENT, BUCKET, f'{PREFIX}/{station}/', local_path, name_format=name_format, start_datetime=first_date, end_datetime=last_date)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ced9a14-0b8f-408a-ac62-fe1ddfcbfc87",
   "metadata": {
    "id": "4ced9a14-0b8f-408a-ac62-fe1ddfcbfc87"
   },
   "source": [
    "We will do the same for MARS data on AWS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "1cc7bff3-9018-4f12-ae68-17bf44c26ab7",
   "metadata": {
    "id": "1cc7bff3-9018-4f12-ae68-17bf44c26ab7",
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "CLIENT = Minio( \"s3.us-west-2.amazonaws.com\", secure=False)\n",
    "BUCKET = 'pacific-sound-spectra'\n",
    "PREFIX = '2021/'\n",
    "name_format = '%Y%m%d'\n",
    "for station in stations_to_download_aws: \n",
    "    download_data_station(station, CLIENT, BUCKET, f'{PREFIX}', local_path, name_format=name_format, start_datetime=first_date, end_datetime=last_date)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18969e6d-f6e3-4550-b54b-d068342bc2dc",
   "metadata": {},
   "source": [
    "## Get data by station & resample the temporal resolution"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffaf9c2d-0e30-4409-9ad0-5caa421e7eba",
   "metadata": {
    "id": "ffaf9c2d-0e30-4409-9ad0-5caa421e7eba"
   },
   "source": [
    "We will load only a part of the data in frequency range to save some memory. \n",
    "The MARS station does not have a quality_flag variable so we need to take that into account when loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b184717e-cc3f-4bf3-8043-5f99c615b0c2",
   "metadata": {
    "id": "b184717e-cc3f-4bf3-8043-5f99c615b0c2",
    "tags": []
   },
   "outputs": [],
   "source": [
    "min_freq = 0\n",
    "max_freq = 435"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8fafb1dc-bd6a-433c-96b5-9aeaeeb47152",
   "metadata": {
    "id": "abb80112-e139-4a3b-a8c0-37ffa3170486",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Only get data from 2021  and remove data with bad quality flag\n",
    "def load_data_from_station_year(station, year, data_vars, freq_bounds=None):\n",
    "    deployment_path = pathlib.Path(local_path).joinpath(station)\n",
    "    print('loading station %s...' % station)\n",
    "\n",
    "    aggregated_ds = pypam.utils.join_all_ds_output_deployment(deployment_path, data_vars=data_vars, datetime_coord='time',\n",
    "                                                              join_only_if_contains='_%s' % year, load=True,\n",
    "                                                              parallel=False, freq_band=freq_bounds,\n",
    "                                                              freq_coord='frequency',\n",
    "                                                              )\n",
    "    if 'quality_flag' in aggregated_ds.data_vars:\n",
    "        aggregated_ds['psd'] = aggregated_ds.psd.where(aggregated_ds.quality_flag.isin([1]))\n",
    "        aggregated_ds = aggregated_ds.drop_vars('quality_flag')\n",
    "\n",
    "    return aggregated_ds # this assigns an xarray dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02d9defe-65d0-44fd-b374-68fb6803e2f1",
   "metadata": {
    "id": "02d9defe-65d0-44fd-b374-68fb6803e2f1"
   },
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "⚠️ Be patient, loading full years of data can take a while...\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5150060c-bcef-42d4-9e9f-00e65368b835",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "5150060c-bcef-42d4-9e9f-00e65368b835",
    "outputId": "e239941d-5aa2-41fd-f694-0fd37b5b1534",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading station AEON5...\n",
      "[########################################] | 100% Completed | 15.10 ss\n",
      "loading station MARS...\n",
      "[########################################] | 100% Completed | 29.39 s\n",
      "loading station NRS11...\n",
      "[########################################] | 100% Completed | 17.54 s\n"
     ]
    }
   ],
   "source": [
    "# Load all the data in one dictionary\n",
    "stations_to_load = ['AEON5', 'MARS', 'NRS11'] # Make a list of stations to compare\n",
    "ds_collection = {}\n",
    "for station in stations_to_load:\n",
    "    if 'MARS' in stations_to_load:\n",
    "        ds_collection[station] = load_data_from_station_year(station, 2021, data_vars=['psd'], freq_bounds=[min_freq, max_freq])\n",
    "    else: \n",
    "        ds_collection[station] = load_data_from_station_year(station, 2021, data_vars=['psd', 'quality_flag'], freq_bounds=[min_freq, max_freq])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8dd56ed3-416a-4e9a-ae18-890a10199eb4",
   "metadata": {
    "id": "8dd56ed3-416a-4e9a-ae18-890a10199eb4",
    "tags": []
   },
   "source": [
    "## Whale presence indices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30b0da84-6083-4ba0-bc4c-b8af842d6b81",
   "metadata": {
    "id": "30b0da84-6083-4ba0-bc4c-b8af842d6b81"
   },
   "source": [
    "Indices are the ratio of mean power spectral density (PSD) within the frequency band of peak call energy to mean PSD at background frequencies.\n",
    "These peak and background frequencies will be illustrated in the summary plot and call index calculations below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "24e51b70-4a64-4b3d-8ad9-77e5de1226b3",
   "metadata": {
    "id": "24e51b70-4a64-4b3d-8ad9-77e5de1226b3",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Define the frequencies that are used to compute call indices\n",
    "bluepeak = np.array([42, 43])\n",
    "finpeak = np.array([20, 21])\n",
    "bluebackground = np.array([37, 50])\n",
    "finbackground = np.array([12, 34])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2d623f4e-a635-41a5-a4f0-16de921fdcba",
   "metadata": {},
   "outputs": [],
   "source": [
    "whale_station1 = 'AEON5' \n",
    "whale_station2 = 'NRS11' \n",
    "whale_station3 = 'MARS'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5ffe4f4e-d464-48e3-a5d1-f46d62ec56e4",
   "metadata": {
    "id": "5ffe4f4e-d464-48e3-a5d1-f46d62ec56e4"
   },
   "outputs": [],
   "source": [
    "def compute_whale_index(peak, background, daily_ds):\n",
    "    pk = daily_ds.sel(frequency=peak).psd.mean(dim='frequency')\n",
    "    bg = daily_ds.sel(frequency=background).psd.mean(dim='frequency')\n",
    "    CI = pk / bg\n",
    "    CI = CI.resample(time='1D').median()  # Resample to daily spectra\n",
    "    return CI"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f372197-dbd2-4822-b7c9-0a88d91374a7",
   "metadata": {},
   "source": [
    "Let's compute the call indices per station and whale species"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "09f65f52-adea-4b38-834d-e7c297225395",
   "metadata": {
    "id": "09f65f52-adea-4b38-834d-e7c297225395",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Compute the whale indices\n",
    "finCI1 = compute_whale_index(finpeak, finbackground, ds_collection[whale_station1])\n",
    "blueCI1 = compute_whale_index(bluepeak, bluebackground, ds_collection[whale_station1])\n",
    "finCI2 = compute_whale_index(finpeak, finbackground, ds_collection[whale_station2])\n",
    "blueCI2 = compute_whale_index(bluepeak, bluebackground, ds_collection[whale_station2])\n",
    "finCI3 = compute_whale_index(finpeak, finbackground, ds_collection[whale_station3])\n",
    "blueCI3 = compute_whale_index(bluepeak, bluebackground, ds_collection[whale_station3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4e92dd2-591f-4294-98b0-112f8acf3bc1",
   "metadata": {},
   "source": [
    "Here we resample the data by week and calculate the 25th, 50th (median), and 75th percentiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e540a8d3-e14b-4757-aa14-0a7c87a6f1e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "date_range1 = blueCI1.time.values\n",
    "time_series1 = pd.Series(blueCI1, index=date_range1)\n",
    "\n",
    "date_range2 = blueCI2.time.values\n",
    "time_series2 = pd.Series(blueCI2, index=date_range2)\n",
    "\n",
    "date_range3 = blueCI3.time.values\n",
    "time_series3 = pd.Series(blueCI3, index=date_range3)\n",
    "\n",
    "# Resample the data by week and calculate percentiles\n",
    "weekly1 = time_series1.resample('W').agg(['median', lambda x: np.percentile(x, 25), lambda x: np.percentile(x, 75)])\n",
    "weekly1.columns = ['median', '25th_percentile', '75th_percentile']\n",
    "\n",
    "weekly2 = time_series2.resample('W').agg(['median', lambda x: np.percentile(x, 25), lambda x: np.percentile(x, 75)])\n",
    "weekly2.columns = ['median', '25th_percentile', '75th_percentile']\n",
    "\n",
    "weekly3 = time_series3.resample('W').agg(['median', lambda x: np.percentile(x, 25), lambda x: np.percentile(x, 75)])\n",
    "weekly3.columns = ['median', '25th_percentile', '75th_percentile']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "da1678ee-a2ee-4935-b528-9a7f028e7b12",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_theme(style='ticks')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35d51051-0fbb-479c-948c-3f6282acce3e",
   "metadata": {},
   "source": [
    "Here we plot and save the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "470f377a-e962-4922-9498-e4149b0db67c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams.update({\n",
    "    \"text.usetex\": False,\n",
    "    \"font.family\": \"sans-serif\"\n",
    "})\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "ax.plot(weekly2.index, weekly2['median'], label='NRS11') #, color='blue'\n",
    "ax.fill_between(weekly2.index, \n",
    "                weekly2['25th_percentile'], \n",
    "                weekly2['75th_percentile'], \n",
    "                alpha=0.2)\n",
    "\n",
    "ax.plot(weekly3.index, weekly3['median'], label='MARS') \n",
    "ax.fill_between(weekly3.index, \n",
    "                weekly3['25th_percentile'], \n",
    "                weekly3['75th_percentile'], \n",
    "                alpha=0.2) \n",
    "ax.plot(weekly1.index, weekly1['median'], label='AEON5') #, color='blue'\n",
    "ax.fill_between(weekly1.index, \n",
    "                weekly1['25th_percentile'], \n",
    "                weekly1['75th_percentile'], \n",
    "                alpha=0.2) # color='blue', alpha=0.2, label='25th-75th Percentile Range')\n",
    "\n",
    "# Set face color to white\n",
    "ax.set_ylim(0.95, 1.23) #ax.set_ylim(1, 1.2)\n",
    "\n",
    "plt.yticks([0.95, 1, 1.05, 1.1, 1.15, 1.2], ['0.95', '1.0', '1.05', '1.1', '1.15','1.2']) \n",
    "\n",
    "ax.axhline(1,color='black',linestyle='--',linewidth=0.5)\n",
    "\n",
    "# Add titles and labels\n",
    "# #plt.title('Weekly Blue Whale Call Index')\n",
    "# #plt.xlabel('2021')\n",
    "plt.ylabel('Blue Whale Call Index', fontsize=18)\n",
    "\n",
    "# Set the font size of x-tick labels\n",
    "ax.tick_params(axis='x', labelsize=16)\n",
    "\n",
    "# Set the font size of y-tick labels (optional)\n",
    "ax.tick_params(axis='y', labelsize=16)\n",
    "\n",
    "plt.legend(fontsize=12,loc = \"upper right\")\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n",
    "\n",
    "# Save the plot\n",
    "fig.savefig(output_path+ '/SoundCoopPaper-CaseStudy3-weeklyBlueWhale.png') # save as png"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e4e06f74-ae90-4662-b3e6-a97ff21cb2c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Weekly fin whale calculations\n",
    "\n",
    "date_range1 = finCI1.time.values\n",
    "time_series1 = pd.Series(finCI1, index=date_range1)\n",
    "\n",
    "date_range2 = finCI2.time.values\n",
    "time_series2 = pd.Series(finCI2, index=date_range2)\n",
    "\n",
    "date_range3 = finCI3.time.values\n",
    "time_series3 = pd.Series(finCI3, index=date_range3)\n",
    "\n",
    "# Resample the data by month and calculate percentiles\n",
    "weekly1Fin = time_series1.resample('W').agg(['median', lambda x: np.percentile(x, 25), lambda x: np.percentile(x, 75)])\n",
    "weekly1Fin.columns = ['median', '25th_percentile', '75th_percentile']\n",
    "\n",
    "weekly2Fin = time_series2.resample('W').agg(['median', lambda x: np.percentile(x, 25), lambda x: np.percentile(x, 75)])\n",
    "weekly2Fin.columns = ['median', '25th_percentile', '75th_percentile']\n",
    "\n",
    "weekly3Fin = time_series3.resample('W').agg(['median', lambda x: np.percentile(x, 25), lambda x: np.percentile(x, 75)])\n",
    "weekly3Fin.columns = ['median', '25th_percentile', '75th_percentile']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8c89b4b3-c09b-44c7-b214-cccc2d1d2330",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the results\n",
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "ax.plot(weekly2Fin.index, weekly2Fin['median'], label='NRS11') \n",
    "ax.fill_between(weekly2Fin.index, \n",
    "                weekly2Fin['25th_percentile'], \n",
    "                weekly2Fin['75th_percentile'], \n",
    "                alpha=0.2)\n",
    "\n",
    "ax.plot(weekly3Fin.index, weekly3Fin['median'], label='MARS') \n",
    "ax.fill_between(weekly3Fin.index, \n",
    "                weekly3Fin['25th_percentile'], \n",
    "                weekly3Fin['75th_percentile'], \n",
    "                alpha=0.2) \n",
    "ax.plot(weekly1Fin.index, weekly1Fin['median'], label='AEON5') \n",
    "ax.fill_between(weekly1Fin.index, \n",
    "                weekly1Fin['25th_percentile'], \n",
    "                weekly1Fin['75th_percentile'], \n",
    "                alpha=0.2) \n",
    "\n",
    "# Set face color to white\n",
    "ax.set_facecolor('white')\n",
    "ax.set_ylim(0.90, 1.53) #ax.set_ylim(1, 1.5)\n",
    "\n",
    "ax.axhline(1,color='black',linestyle='--',linewidth=0.5)\n",
    "\n",
    "# Add titles and labels\n",
    "plt.ylabel('Fin Whale Call Index', fontsize=18)\n",
    "\n",
    "# Set the font size of x-tick labels\n",
    "ax.tick_params(axis='x', labelsize=16)\n",
    "\n",
    "# Set the font size of y-tick labels (optional)\n",
    "ax.tick_params(axis='y', labelsize=16)\n",
    "\n",
    "plt.legend(fontsize=12)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n",
    "\n",
    "# Save the plot\n",
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