{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare `TECjhr/sub.h5` from JPL high resolution GIM and topside TEC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "from matplotlib import pyplot as plt\n",
    "from mintpy.objects import timeseries\n",
    "from mintpy.utils import ptime, readfile, utils as ut, plot as pp\n",
    "from mintpy.simulation import iono\n",
    "from mintpy import iono_tec\n",
    "plt.rcParams.update({'font.size': 12})\n",
    "figsize = [9, 3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Dataset: Chile Sen asc T149"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "incidence angle on the ground     min/max: 30.0/46.1 deg\n",
      "incidence angle on the ionosphere min/max: 27.9/42.3 deg\n",
      "center lat/lon  on the ground    : -21.0438/-68.4108 deg\n",
      "center lat/lon  on the ionosphere: -21.7329/-71.5353 deg\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "incidence angle on the ground     min/max: 30.0/46.1 deg\n",
      "incidence angle on the ionosphere min/max: 27.9/42.3 deg\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yunjunz/tools/dev/tools/simulation/iono.py:140: RuntimeWarning: invalid value encountered in sin\n",
      "  inc_angle_iono = np.arcsin(EARTH_RADIUS * np.sin(inc_angle) / (EARTH_RADIUS + iono_height))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "center lat/lon  on the ground    : -21.0438/-68.4108 deg\n",
      "center lat/lon  on the ionosphere: -21.7329/-71.5353 deg\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20200228    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhr.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhr.h5 with w mode\n",
      "create dataset /date        of |S8        in size of (104,)               with compression=None\n",
      "create dataset /vtec        of float32    in size of (104,)               with compression=None\n",
      "create dataset /timeseries  of float32    in size of (104, 123, 231)      with compression=None\n",
      "create dataset /tec_ipp     of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_top_tpp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_ipp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_tpp of float32    in size of (104,)               with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhr.h5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yunjunz/tools/dev/tools/simulation/iono.py:81: RuntimeWarning: invalid value encountered in sin\n",
      "  ref_angle = np.arcsin(1 / n_iono_group * np.sin(inc_angle * np.pi / 180)) * 180 / np.pi\n",
      "/Users/yunjunz/tools/dev/tools/simulation/iono.py:59: RuntimeWarning: invalid value encountered in cos\n",
      "  tec = vtec / np.cos(ref_angle * np.pi / 180.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "incidence angle on the ground     min/max: 30.0/46.1 deg\n",
      "incidence angle on the ionosphere min/max: 27.9/42.3 deg\n",
      "center lat/lon  on the ground    : -21.0438/-68.4108 deg\n",
      "center lat/lon  on the ionosphere: -21.7329/-71.5353 deg\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20200228    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECsub.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECsub.h5 with w mode\n",
      "create dataset /date        of |S8        in size of (104,)               with compression=None\n",
      "create dataset /vtec        of float32    in size of (104,)               with compression=None\n",
      "create dataset /timeseries  of float32    in size of (104, 123, 231)      with compression=None\n",
      "create dataset /tec_ipp     of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_top_tpp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_ipp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_tpp of float32    in size of (104,)               with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECsub.h5\n",
      "incidence angle on the ground     min/max: 30.0/46.1 deg\n",
      "incidence angle on the ionosphere min/max: 27.9/42.3 deg\n",
      "center lat/lon  on the ground    : -21.0438/-68.4108 deg\n",
      "center lat/lon  on the ionosphere: -21.7329/-71.5353 deg\n",
      "multiply VTEC by 0.69\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20200228    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhrR69.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhrR69.h5 with w mode\n",
      "create dataset /date        of |S8        in size of (104,)               with compression=None\n",
      "create dataset /vtec        of float32    in size of (104,)               with compression=None\n",
      "create dataset /timeseries  of float32    in size of (104, 123, 231)      with compression=None\n",
      "create dataset /tec_ipp     of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_top_tpp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_ipp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_tpp of float32    in size of (104,)               with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhrR69.h5\n",
      "incidence angle on the ground     min/max: 30.0/46.1 deg\n",
      "incidence angle on the ionosphere min/max: 27.9/42.3 deg\n",
      "center lat/lon  on the ground    : -21.0438/-68.4108 deg\n",
      "center lat/lon  on the ionosphere: -21.7329/-71.5353 deg\n",
      "multiply VTEC adaptively based on the day of the year from: /Users/yunjunz/Papers/2021_Geolocation/figs_src/topTEC/top_tec_perc.txt\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20200228    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhrRA.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhrRA.h5 with w mode\n",
      "create dataset /date        of |S8        in size of (104,)               with compression=None\n",
      "create dataset /vtec        of float32    in size of (104,)               with compression=None\n",
      "create dataset /timeseries  of float32    in size of (104, 123, 231)      with compression=None\n",
      "create dataset /tec_ipp     of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_top_tpp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_ipp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_tpp of float32    in size of (104,)               with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhrRA.h5\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/TECjhrRA.h5'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proj_dir = os.path.expanduser('~/data/geolocation/ChileSenAT149')\n",
    "ts_file   = os.path.join(proj_dir, 'mintpy_offset/timeseriesRg.h5')\n",
    "geom_file = os.path.join(proj_dir, 'mintpy_offset/inputs/geometryRadar.h5')\n",
    "tec_sub_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECsub.h5')\n",
    "tec_gim_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhr.h5')\n",
    "\n",
    "# read GIM/TOP TEC data from Xiaoqing\n",
    "gim_tec_dir = os.path.join(proj_dir, 'GIM_TEC')\n",
    "date_list = timeseries(ts_file).get_date_list()\n",
    "iono_lat, iono_lon = iono.prep_geometry_iono(geom_file, print_msg=True)[1:3]\n",
    "tec_ipp, tec_top_tpp, tec_sub_ipp, tec_sub_tpp, tDicts = iono.get_sub_tec_list(gim_tec_dir, date_list, iono_lat, iono_lon, interp_method='nearest')[1:]\n",
    "\n",
    "# read GMT TEC for the missing dates above\n",
    "gim_tec_file = os.path.join(proj_dir, 'GIM_TEC', 'gimtec.txt')\n",
    "fc = np.loadtxt(gim_tec_file, dtype=bytes).astype(str)\n",
    "for i in range(fc.shape[0]):\n",
    "    ind = date_list.index(fc[i, 0])\n",
    "    if np.isnan(tec_ipp[ind]):\n",
    "        tec_ipp[ind] = float(fc[i, 1])\n",
    "\n",
    "# plot\n",
    "dates = ptime.date_list2vector(date_list)[0]\n",
    "ydays = [x.timetuple().tm_yday for x in dates]\n",
    "titles = ['GIM TEC (IPP)', 'Sub-orbit TEC (IPP)', 'Topside TEC (TPP)']\n",
    "fig, axs = plt.subplots(nrows=3, ncols=1, figsize=[9, 6], sharex=True)\n",
    "for i, vtec in enumerate([tec_ipp, tec_sub_ipp, tec_top_tpp]):\n",
    "    axs[i].plot(dates, vtec, 'o-')\n",
    "    axs[i].annotate(titles[i], xy=(0.25, 0.8), xycoords='axes fraction')\n",
    "ax = axs[1]\n",
    "ax.set_ylabel('zenith TEC [TECU]')\n",
    "pp.auto_adjust_xaxis_date(ax, dates)\n",
    "fig.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# calc iono ramp time-series\n",
    "ds_dict_ext = {}\n",
    "ds_dict_ext['tec_ipp']     = np.array(tec_ipp, dtype=np.float32)\n",
    "ds_dict_ext['tec_top_tpp'] = np.array(tec_top_tpp, dtype=np.float32)\n",
    "ds_dict_ext['tec_sub_ipp'] = np.array(tec_sub_ipp, dtype=np.float32)\n",
    "ds_dict_ext['tec_sub_tpp'] = np.array(tec_sub_tpp, dtype=np.float32)\n",
    "\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, tec_ipp.tolist(),     geom_file=geom_file, iono_file=tec_gim_file, ds_dict_ext=ds_dict_ext)\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, tec_sub_tpp.tolist(), geom_file=geom_file, iono_file=tec_sub_file, ds_dict_ext=ds_dict_ext)\n",
    "# scaled GIM\n",
    "tec_gimRF_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhrR69.h5')\n",
    "tec_gimRA_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhrRA.h5')\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, tec_ipp.tolist(), geom_file=geom_file, iono_file=tec_gimRF_file, ds_dict_ext=ds_dict_ext, sub_tec_ratio='0.69')\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, tec_ipp.tolist(), geom_file=geom_file, iono_file=tec_gimRA_file, ds_dict_ext=ds_dict_ext, sub_tec_ratio='adap')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Dataset: Chile Sen desc T156"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "incidence angle on the ground     min/max: 30.8/46.2 deg\n",
      "incidence angle on the ionosphere min/max: 28.6/42.4 deg\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yunjunz/tools/dev/tools/simulation/iono.py:140: RuntimeWarning: invalid value encountered in sin\n",
      "  inc_angle_iono = np.arcsin(EARTH_RADIUS * np.sin(inc_angle) / (EARTH_RADIUS + iono_height))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "center lat/lon  on the ground    : -21.1462/-68.1329 deg\n",
      "center lat/lon  on the ionosphere: -21.8427/-64.9786 deg\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[======================= 80% ===========>          ] 20190628    0s /     0s"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yunjunz/tools/dev/tools/simulation/iono.py:81: RuntimeWarning: invalid value encountered in sin\n",
      "  ref_angle = np.arcsin(1 / n_iono_group * np.sin(inc_angle * np.pi / 180)) * 180 / np.pi\n",
      "/Users/yunjunz/tools/dev/tools/simulation/iono.py:59: RuntimeWarning: invalid value encountered in cos\n",
      "  tec = vtec / np.cos(ref_angle * np.pi / 180.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[==================================================] 20200229    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhr.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhr.h5 with w mode\n",
      "create dataset /date       of |S8        in size of (201,)               with compression=None\n",
      "create dataset /vtec       of float32    in size of (201,)               with compression=None\n",
      "create dataset /timeseries of float32    in size of (201, 157, 232)      with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhr.h5\n",
      "incidence angle on the ground     min/max: 30.8/46.2 deg\n",
      "incidence angle on the ionosphere min/max: 28.6/42.4 deg\n",
      "center lat/lon  on the ground    : -21.1462/-68.1329 deg\n",
      "center lat/lon  on the ionosphere: -21.8427/-64.9786 deg\n",
      "multiply VTEC by 0.69\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20200229    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhrR69.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhrR69.h5 with w mode\n",
      "create dataset /date        of |S8        in size of (201,)               with compression=None\n",
      "create dataset /vtec        of float32    in size of (201,)               with compression=None\n",
      "create dataset /timeseries  of float32    in size of (201, 157, 232)      with compression=None\n",
      "create dataset /tec_ipp     of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_top_tpp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_ipp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_tpp of float32    in size of (104,)               with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhrR69.h5\n",
      "incidence angle on the ground     min/max: 30.8/46.2 deg\n",
      "incidence angle on the ionosphere min/max: 28.6/42.4 deg\n",
      "center lat/lon  on the ground    : -21.1462/-68.1329 deg\n",
      "center lat/lon  on the ionosphere: -21.8427/-64.9786 deg\n",
      "multiply VTEC adaptively based on the day of the year from: /Users/yunjunz/Papers/2021_Geolocation/figs_src/topTEC/top_tec_perc.txt\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20200229    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhrRA.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhrRA.h5 with w mode\n",
      "create dataset /date        of |S8        in size of (201,)               with compression=None\n",
      "create dataset /vtec        of float32    in size of (201,)               with compression=None\n",
      "create dataset /timeseries  of float32    in size of (201, 157, 232)      with compression=None\n",
      "create dataset /tec_ipp     of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_top_tpp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_ipp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_tpp of float32    in size of (104,)               with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhrRA.h5\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/TECjhrRA.h5'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proj_dir = os.path.expanduser('~/data/geolocation/ChileSenDT156')\n",
    "ts_file   = os.path.join(proj_dir, 'mintpy_offset/timeseriesRg.h5')\n",
    "geom_file = os.path.join(proj_dir, 'mintpy_offset/inputs/geometryRadar.h5')\n",
    "iono_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhr.h5')\n",
    "\n",
    "# read GIM TEC data from Xiaoqing\n",
    "gim_tec_file = os.path.join(proj_dir, 'GIM_TEC', 'gimtec_sent1.txt')\n",
    "fc = np.loadtxt(gim_tec_file, dtype=bytes).astype(str)\n",
    "date_list = fc[:, 0].tolist()\n",
    "vtec = fc[:, 1].astype(np.float32)\n",
    "\n",
    "# plot\n",
    "x = ptime.date_list2vector(date_list)[0]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=[9, 3])\n",
    "ax.plot(x, vtec, 'o-', ms=3)\n",
    "ax.set_ylabel('zenith TEC [TECU]')\n",
    "pp.auto_adjust_xaxis_date(ax, x)\n",
    "fig.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# calc iono ramp time-series\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, vtec.tolist(), geom_file=geom_file, iono_file=iono_file)\n",
    "# scaled GIM\n",
    "tec_gimRF_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhrR69.h5')\n",
    "tec_gimRA_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhrRA.h5')\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, vtec.tolist(), geom_file=geom_file, iono_file=tec_gimRF_file, ds_dict_ext=ds_dict_ext, sub_tec_ratio='0.69')\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, vtec.tolist(), geom_file=geom_file, iono_file=tec_gimRA_file, ds_dict_ext=ds_dict_ext, sub_tec_ratio='adap')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Dataset: Kyushu ALOS-2 desc T23"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "incidence angle on the ground     min/max: 34.2/38.1 deg\n",
      "incidence angle on the ionosphere min/max: 31.6/35.2 deg\n",
      "center lat/lon  on the ground    : 32.0694/130.7785 deg\n",
      "center lat/lon  on the ionosphere: 31.5407/133.9155 deg\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20190819    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhr_v2.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhr_v2.h5 with w mode\n",
      "create dataset /date       of |S8        in size of (49,)                with compression=None\n",
      "create dataset /vtec       of float32    in size of (49,)                with compression=None\n",
      "create dataset /timeseries of float32    in size of (49, 403, 229)       with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhr_v2.h5\n",
      "incidence angle on the ground     min/max: 34.2/38.1 deg\n",
      "incidence angle on the ionosphere min/max: 31.6/35.2 deg\n",
      "center lat/lon  on the ground    : 32.0694/130.7785 deg\n",
      "center lat/lon  on the ionosphere: 31.5407/133.9155 deg\n",
      "multiply VTEC by 0.69\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20190819    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhrR69.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhrR69.h5 with w mode\n",
      "create dataset /date        of |S8        in size of (49,)                with compression=None\n",
      "create dataset /vtec        of float32    in size of (49,)                with compression=None\n",
      "create dataset /timeseries  of float32    in size of (49, 403, 229)       with compression=None\n",
      "create dataset /tec_ipp     of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_top_tpp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_ipp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_tpp of float32    in size of (104,)               with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhrR69.h5\n",
      "incidence angle on the ground     min/max: 34.2/38.1 deg\n",
      "incidence angle on the ionosphere min/max: 31.6/35.2 deg\n",
      "center lat/lon  on the ground    : 32.0694/130.7785 deg\n",
      "center lat/lon  on the ionosphere: 31.5407/133.9155 deg\n",
      "multiply VTEC adaptively based on the day of the year from: /Users/yunjunz/Papers/2021_Geolocation/figs_src/topTEC/top_tec_perc.txt\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20190819    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhrRA.h5\n",
      "create HDF5 file: /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhrRA.h5 with w mode\n",
      "create dataset /date        of |S8        in size of (49,)                with compression=None\n",
      "create dataset /vtec        of float32    in size of (49,)                with compression=None\n",
      "create dataset /timeseries  of float32    in size of (49, 403, 229)       with compression=None\n",
      "create dataset /tec_ipp     of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_top_tpp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_ipp of float32    in size of (104,)               with compression=None\n",
      "create dataset /tec_sub_tpp of float32    in size of (104,)               with compression=None\n",
      "finished writing to /Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhrRA.h5\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/Users/yunjunz/data/geolocation/KyushuAlos2DT23/mintpy_offset/inputs/TECjhrRA.h5'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proj_dir = os.path.expanduser('~/data/geolocation/KyushuAlos2DT23')\n",
    "ts_file   = os.path.join(proj_dir, 'mintpy_offset/timeseriesRg.h5')\n",
    "geom_file = os.path.join(proj_dir, 'mintpy_offset/inputs/geometryRadar.h5')\n",
    "iono_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhr_v2.h5')\n",
    "\n",
    "# read GIM TEC data from Xiaoqing\n",
    "gim_tec_file = os.path.join(proj_dir, 'GIM_TEC', 'gimtec.txt')\n",
    "fc = np.loadtxt(gim_tec_file, dtype=bytes).astype(str)\n",
    "date_list = fc[:, 0].tolist()\n",
    "vtec = fc[:, 1].astype(np.float32)\n",
    "#vtec *= 0.69\n",
    "\n",
    "# plot\n",
    "x = ptime.date_list2vector(date_list)[0]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=[9, 3])\n",
    "ax.plot(x, vtec, 'o-', ms=6)\n",
    "ax.set_ylabel('zenith TEC [TECU]')\n",
    "pp.auto_adjust_xaxis_date(ax, x)\n",
    "fig.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# calc iono ramp time-series\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, vtec.tolist(), geom_file=geom_file, iono_file=iono_file)\n",
    "# scaled GIM\n",
    "tec_gimRF_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhrR69.h5')\n",
    "tec_gimRA_file = os.path.join(proj_dir, 'mintpy_offset/inputs/TECjhrRA.h5')\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, vtec.tolist(), geom_file=geom_file, iono_file=tec_gimRF_file, ds_dict_ext=ds_dict_ext, sub_tec_ratio='0.69')\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, vtec.tolist(), geom_file=geom_file, iono_file=tec_gimRA_file, ds_dict_ext=ds_dict_ext, sub_tec_ratio='adap')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": "true",
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Dataset: Salton Sea Sentinel-1 desc T173"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "incidence angle on the ground     min/max: 30.7/46.1 deg\n",
      "incidence angle on the ionosphere min/max: 28.5/42.3 deg\n",
      "center lat/lon  on the ground    : 33.8499/-115.8618 deg\n",
      "center lat/lon  on the ionosphere: 33.2657/-112.3090 deg\n",
      "calculating ionospheric phase ramp time-series from TEC ...\n",
      "[==================================================] 20151012    0s /     0s \n",
      "delete exsited file: /Users/yunjunz/data/offset4motion/SaltonSeaSenDT173/mintpy_offset_v2/inputs/gimTEC.h5\n",
      "create HDF5 file: /Users/yunjunz/data/offset4motion/SaltonSeaSenDT173/mintpy_offset_v2/inputs/gimTEC.h5 with w mode\n",
      "create dataset /date       of |S8        in size of (6,)                 with compression=None\n",
      "create dataset /vtec       of float32    in size of (6,)                 with compression=None\n",
      "create dataset /timeseries of float32    in size of (6, 792, 677)        with compression=None\n",
      "finished writing to /Users/yunjunz/data/offset4motion/SaltonSeaSenDT173/mintpy_offset_v2/inputs/gimTEC.h5\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/Users/yunjunz/data/offset4motion/SaltonSeaSenDT173/mintpy_offset_v2/inputs/gimTEC.h5'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "proj_dir = os.path.expanduser('~/data/offset4motion/SaltonSeaSenDT173')\n",
    "ts_file   = os.path.join(proj_dir, 'mintpy_offset_v2/timeseriesRg.h5')\n",
    "geom_file = os.path.join(proj_dir, 'mintpy_offset_v2/inputs/geometryRadar.h5')\n",
    "iono_file = os.path.join(proj_dir, 'mintpy_offset_v2/inputs/TECjhr.h5')\n",
    "\n",
    "# read GIM TEC data from Xiaoqing\n",
    "gim_tec_file = os.path.join(proj_dir, 'GIM_TEC', 'gimtec.txt')\n",
    "fc = np.loadtxt(gim_tec_file, dtype=bytes).astype(str)\n",
    "date_list = fc[:, 0].tolist()\n",
    "vtec_list = fc[:, 1].astype(np.float32).tolist()\n",
    "\n",
    "# plot\n",
    "x = ptime.date_list2vector(date_list)[0]\n",
    "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=[9, 3])\n",
    "ax.plot(x, vtec_list, 'o-', ms=3)\n",
    "ax.set_ylabel('zenith TEC [TECU]')\n",
    "#pp.auto_adjust_xaxis_date(ax, x)\n",
    "fig.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# calc iono ramp time-series\n",
    "iono_tec.vtec2iono_ramp_timeseries(date_list, vtec_list, geom_file=geom_file, iono_file=iono_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## Backups - SUB TEC for Chile asc track 149"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": "true"
   },
   "source": [
    "### 1. latitude distance between TEC TPP and SAR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min/max distance : 0.0/3.0 deg\n",
      "save figure to file /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/topTEC_latDist.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "flag = np.array([i is not None for i in tDicts], dtype=np.bool_)\n",
    "date_list = np.array(date_list)[flag].tolist()\n",
    "dates = ptime.date_list2vector(date_list)[0]\n",
    "tDicts = [i for i in tDicts if i is not None]\n",
    "\n",
    "# calc nearest TOP TEC in latitude only\n",
    "num_date = len(date_list)\n",
    "lat_dist = np.zeros(num_date, dtype=np.float32)\n",
    "for i in range(num_date):\n",
    "    lats = tDicts[i]['lat']\n",
    "    lat_dist[i] = np.min(np.abs(lats - iono_lat))\n",
    "print('min/max distance : {:.1f}/{:.1f} deg'.format(np.min(lat_dist), np.max(lat_dist)))\n",
    "\n",
    "## plot\n",
    "fig, ax = plt.subplots(figsize=[9, 4])\n",
    "ax.bar(dates, lat_dist, width=8, color='C1', label='dist')\n",
    "ax.set_xlim(dt.datetime(2015, 5, 1), dt.datetime(2020, 5, 1))\n",
    "ax.set_ylim(-0.5, 3.5)\n",
    "ax.set_xlabel('time [years]')\n",
    "ax.set_ylabel('distance [deg]')\n",
    "pp.auto_adjust_xaxis_date(ax, dates, every_year=1, buffer_year=None)\n",
    "ax.grid('on')\n",
    "\n",
    "ax.legend()\n",
    "ax.grid('on')\n",
    "fig.tight_layout()\n",
    "\n",
    "# output\n",
    "out_fig = os.path.join(proj_dir, 'mintpy_offset/inputs/topTEC_latDist.png')\n",
    "print('save figure to file', out_fig)\n",
    "plt.savefig(out_fig, bbox_inches='tight', transparent=True, dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": "true"
   },
   "source": [
    "### 2. location between TEC TPP and SAR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[==================================================] 20200228    0s /     0s \n",
      "save figure to file /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/topTEC_loc.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 96 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(figsize=[15, 10], nrows=8, ncols=12, sharex=True, sharey=True)\n",
    "prog_bar = ptime.progressBar(maxValue=num_date)\n",
    "for i in range(num_date):\n",
    "    ax = axs.flatten()[i]\n",
    "    lats = tDicts[i]['lat']\n",
    "    lons = tDicts[i]['lon']\n",
    "\n",
    "    # plot\n",
    "    ax.plot(iono_lon, iono_lat, 's', color='C1', label='TGT')                   # SAR\n",
    "    ax.plot(lons,     lats,     '.', color='C0', label='TPP', ms=3)             # TPP\n",
    "    ax.set_title(date_list[i])\n",
    "\n",
    "    prog_bar.update(i+1, suffix=date_list[i])\n",
    "prog_bar.close()\n",
    "\n",
    "for i in range(num_date, axs.size):\n",
    "    axs.flatten()[i].set_visible(False)\n",
    "\n",
    "# axis format\n",
    "fig.text(0.5, -0.01, 'lon [deg]', ha='center')\n",
    "fig.text(-0.01, 0.5, 'lat [deg]', va='center', rotation='vertical')\n",
    "fig.tight_layout()\n",
    "\n",
    "# output\n",
    "out_fig = os.path.join(proj_dir, 'mintpy_offset/inputs/topTEC_loc.png')\n",
    "print('save figure to file', out_fig)\n",
    "plt.savefig(out_fig, bbox_inches='tight', transparent=True, dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": "true"
   },
   "source": [
    "### 3. Impact of interpolation method for TOPTEC\n",
    "\n",
    "TOP TEC from **nearest lat/lon** gives the smallest final residual (SAR - subTEC - ERA5 - SET)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final RMSE w TEC = TECsubMean.h5       : 5.47 cm\n",
      "Final RMSE w TEC = TECsubMed.h5        : 5.50 cm\n",
      "Final RMSE w TEC = TECsubNearLat.h5    : 5.50 cm\n",
      "Final RMSE w TEC = TECsubNearLatLon.h5 : 5.10 cm\n"
     ]
    }
   ],
   "source": [
    "proj_dir = os.path.expanduser('~/data/geolocation/ChileSenAT149')\n",
    "ts_file = os.path.join(proj_dir, 'mintpy_offset/timeseriesRg_S1Bias.h5')\n",
    "tec_files = [\n",
    "    os.path.join(proj_dir, 'mintpy_offset/inputs/TECsubMean.h5'),\n",
    "    os.path.join(proj_dir, 'mintpy_offset/inputs/TECsubMed.h5'),\n",
    "    os.path.join(proj_dir, 'mintpy_offset/inputs/TECsubNearLat.h5'),\n",
    "    os.path.join(proj_dir, 'mintpy_offset/inputs/TECsubNearLatLon.h5'),\n",
    "]\n",
    "set_file  = os.path.join(proj_dir, 'mintpy_offset/inputs/SET.h5')\n",
    "era5_file = os.path.join(proj_dir, 'mintpy_offset/inputs/ERA5.h5')\n",
    "\n",
    "geom_file = os.path.join(proj_dir, 'mintpy_offset', 'inputs/geometryRadar.h5')\n",
    "mask_file = os.path.join(proj_dir, 'mintpy_offset', 'maskResInv.h5')\n",
    "\n",
    "# date info\n",
    "date_list = timeseries(ts_file).get_date_list()\n",
    "num_date = len(date_list)\n",
    "\n",
    "# Point of interest\n",
    "lalo = [-21.30, -67.39]\n",
    "atr = readfile.read_attribute(ts_file)\n",
    "coord = ut.coordinate(atr, lookup_file=geom_file)\n",
    "y, x = coord.geo2radar(lalo[0], lalo[1])[:2]\n",
    "win = 10\n",
    "box = (x-win, y-win, x+win+1, y+win+1)\n",
    "\n",
    "# read data\n",
    "mask = readfile.read(mask_file, box=box)[0].flatten()\n",
    "for tec_file in tec_files:\n",
    "    ts_data  = readfile.read(ts_file,   box=box)[0].reshape(num_date, -1)[:, mask]\n",
    "    ts_data += readfile.read(tec_file,  box=box)[0].reshape(num_date, -1)[:, mask]\n",
    "    ts_data -= readfile.read(set_file,  box=box)[0].reshape(num_date, -1)[:, mask]\n",
    "    ts_data -= readfile.read(era5_file, box=box)[0].reshape(num_date, -1)[:, mask]\n",
    "    ts_med = np.nanmedian(ts_data, axis=-1)\n",
    "    ts_med -= np.nanmedian(ts_med)\n",
    "\n",
    "    # print out stats\n",
    "    rmse = ut.root_mean_sq_error(ts_med) * 100\n",
    "    print('Final RMSE w TEC = {:<20}: {:.2f} cm'.format(os.path.basename(tec_file), rmse))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": "true"
   },
   "source": [
    "### 4. GIM TEC vs. GIM TEC\n",
    "\n",
    "IGS TEC can be pretty bad sometimes!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tsview.py /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/igsTEC.h5 /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/gimTEC.h5 --lalo -21.0 -68.4 --lookup /Users/yunjunz/data/geolocation/ChileSenAT149/mintpy_offset/inputs/geometryRadar.h5 --noverbose --figsize 9 4\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x398.712 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tsview.py /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/igsTEC.h5 /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/gimTEC.h5 --lalo -21.0 -68.4 --lookup /Users/yunjunz/data/geolocation/ChileSenDT156/mintpy_offset/inputs/geometryRadar.h5 --noverbose --figsize 9 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 613.817x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mintpy import tsview\n",
    "proj_dirs = [os.path.expanduser('~/data/geolocation/ChileSenAT149'),\n",
    "             os.path.expanduser('~/data/geolocation/ChileSenDT156')]\n",
    "for proj_dir in proj_dirs:\n",
    "    gim_tec_file = os.path.join(proj_dir, 'mintpy_offset/inputs/gimTEC.h5')\n",
    "    igs_tec_file = os.path.join(proj_dir, 'mintpy_offset/inputs/igsTEC.h5')\n",
    "    geom_file    = os.path.join(proj_dir, 'mintpy_offset/inputs/geometryRadar.h5')\n",
    "    iargs = [igs_tec_file, gim_tec_file, '--lalo', '-21.0', '-68.4', '--lookup', geom_file, '--noverbose', '--figsize', '9', '4']\n",
    "    tsview.main(iargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}