hima8_pv/ftp_hima8.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [],
   "source": [
    "import netCDF4 as nc"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "outputs": [],
   "source": [
    "data = nc.Dataset('./data/2022-10-09/PAR_Minutes_Download/H08_20221009_0500_RFL020_FLDK.02401_02401.nc')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "outputs": [
    {
     "data": {
      "text/plain": "<class 'netCDF4._netCDF4.Dataset'>\nroot group (NETCDF4 data model, file format HDF5):\n    title: Himawari-08 AHI equal latitude-longitude map data\n    id: H08_20221009_0500_RFL020_FLDK.02401_02401.nc\n    date_created: 2022-10-09T05:26:29Z\n    pixel_number: 2401\n    line_number: 2401\n    upper_left_latitude: 60.0\n    upper_left_longitude: 80.0\n    grid_interval: 0.05\n    band_number: 6\n    algorithm_version: 0201\n    Ancillary meteorological data: JMA forcast\n    Ancillary ozone data: JMA objective analysis\n    BRDF correction: on (Morel and Maritorena 2001)\n    dimensions(sizes): latitude(2401), longitude(2401), band(6), time(1), geometry(17)\n    variables(dimensions): float32 latitude(latitude), float32 longitude(longitude), int32 band_id(band), float64 start_time(time), float64 end_time(time), float64 geometry_parameters(geometry), int16 TAOT_02(latitude, longitude), int16 TAAE(latitude, longitude), int16 PAR(latitude, longitude), int16 SWR(latitude, longitude), int16 UVA(latitude, longitude), int16 UVB(latitude, longitude), uint8 QA_flag(latitude, longitude)\n    groups: "
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "outputs": [
    {
     "data": {
      "text/plain": "dict_keys(['latitude', 'longitude', 'band_id', 'start_time', 'end_time', 'geometry_parameters', 'TAOT_02', 'TAAE', 'PAR', 'SWR', 'UVA', 'UVB', 'QA_flag'])"
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.variables.keys()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "outputs": [
    {
     "data": {
      "text/plain": "<class 'netCDF4._netCDF4.Variable'>\nint16 SWR(latitude, longitude)\n    long_name: Shortwave radiation\n    units: W/m^2\n    scale_factor: 0.05\n    add_offset: 0.0\n    valid_min: 0\n    valid_max: 26000\n    missing_value: -32768\nunlimited dimensions: \ncurrent shape = (2401, 2401)\nfilling on, default _FillValue of -32767 used"
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.variables['SWR']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "outputs": [
    {
     "data": {
      "text/plain": "<class 'netCDF4._netCDF4.Variable'>\nfloat32 latitude(latitude)\n    long_name: latitude\n    units: degrees_north\nunlimited dimensions: \ncurrent shape = (2401,)\nfilling on, default _FillValue of 9.969209968386869e+36 used"
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.variables['latitude']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "import cv2"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[559.4    , 559.45   , 559.5    , ..., 326.30002, 332.75   ,\n        331.55002],\n       [559.55   , 559.65   , 559.9    , ..., 331.7    , 331.7    ,\n        331.55002],\n       [556.8    , 559.15   , 559.4    , ..., 337.95   , 337.75   ,\n        331.95   ],\n       ...,\n       [816.45   , 816.35004, 816.45   , ..., 541.65   , 543.35004,\n        527.65   ],\n       [817.45   , 815.25   , 814.5    , ..., 543.4    , 413.5    ,\n        398.75   ],\n       [817.5    , 813.35004, 817.3    , ..., 544.05   , 239.1    ,\n        339.75   ]], dtype=float32)"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img = cv2.imread('./data/2022-10-09/PAR_Minutes_Analysis/20221009_0500.tif', 2)\n",
    "img"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.image.AxesImage at 0x18f79cd60c8>"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(img, \"Greys_r\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
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}