{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "80222435-9a50-42f2-aa8f-869722821a71",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import json\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sys.path.insert(0, '../codes/')\n",
    "from bulkmotion_utils import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "12691d9a-b509-4cad-a4f6-99d6bf02ce72",
   "metadata": {},
   "outputs": [],
   "source": [
    "font_size = 10\n",
    "w_cm      = 19       # max width of GRL figure [mm]\n",
    "l_cm      = 11.5     # not used\n",
    "cm2in     = 1/2.54   # mm to inches\n",
    "\n",
    "\n",
    "plt.rcParams.update({'font.size': font_size})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "21ecbb67-a67b-4e66-a9d6-8b39a69b2bd3",
   "metadata": {},
   "outputs": [],
   "source": [
    "datahome = '/net/kraken/nobak/ykliu/2022-BulkMotion/data'\n",
    "picdir   = '/net/kraken/nobak/ykliu/2022-BulkMotion/pic'\n",
    "my_json  = '/net/kraken/nobak/ykliu/2022-BulkMotion/inputs/brief.json'\n",
    "\n",
    "ext = 'png'\n",
    "\n",
    "## Read pre-defined paths\n",
    "with open(my_json) as file:\n",
    "    brief = json.load(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "357114a2-4767-4163-b35d-f3010852f1f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def symbol_cbar_velo(cmap, size=[.7, .07], vlim=['-10','10'], orient='horizontal', font_size=10, vpad=[-4,0], hpad=[-13,-2], tpos='bottom', label='[mm/yr]', name='', picdir='.'):\n",
    "    # Fig 3 velocity map colormap (mm/yr)\n",
    "    if orient=='vertical':\n",
    "        fig = plt.figure(figsize=size[::-1])\n",
    "        ax  = fig.add_axes([0.05, 0.05, 0.9, 0.9])\n",
    "    elif orient=='horizontal':\n",
    "        fig = plt.figure(figsize=size)\n",
    "        ax  = fig.add_axes([0.05, 0.05, 0.9, 0.9])        \n",
    "    cbar = mpl.colorbar.ColorbarBase(ax, cmap=plt.get_cmap(cmap), orientation=orient, ticks=[0,1], extend='neither')\n",
    "    cbar.ax.tick_params(which='both', direction='out', labelsize=font_size)    \n",
    "    #ax.text(0.5,1.5, 'LOS velocity', ha='center')\n",
    "    if orient=='vertical':\n",
    "        cbar.ax.set_yticklabels(vlim)   \n",
    "        cbar.ax.yaxis.set_tick_params(pad=vpad[1])\n",
    "        cbar.set_label(label, fontsize=font_size, labelpad=vpad[0], rotation=270)\n",
    "    elif orient=='horizontal':\n",
    "        cbar.ax.xaxis.set_ticks_position(tpos)\n",
    "        cbar.ax.set_xticklabels(vlim)\n",
    "        cbar.ax.xaxis.set_tick_params(pad=hpad[1])\n",
    "        cbar.set_label(label, fontsize=font_size, labelpad=hpad[0])\n",
    "    if picdir:\n",
    "        fn = f\"{picdir}/cbar_velo{name}.pdf\"\n",
    "        plt.savefig(fn, bbox_inches='tight', transparent=True, dpi=800, pad_inches=0.01)\n",
    "        print('save to file: '+fn)\n",
    "    plt.show()\n",
    "\n",
    "    \n",
    "def symbol_cbar_lat(cmap, size=[.7, .07], vlim=['25','32'], orient='horizontal', font_size=10, vpad=[-4,0], hpad=[-13,-2], tpos='bottom', label='Lat [deg]', name='', picdir='.'):\n",
    "    # Fig 3 velocity profile colormap (latitude deg)\n",
    "    if orient=='vertical':\n",
    "        fig = plt.figure(figsize=size[::-1])\n",
    "        ax  = fig.add_axes([0.05, 0.05, 0.9, 0.9])\n",
    "    elif orient=='horizontal':\n",
    "        fig = plt.figure(figsize=size)\n",
    "        ax  = fig.add_axes([0.05, 0.05, 0.9, 0.9])\n",
    "    cbar = mpl.colorbar.ColorbarBase(ax, cmap=plt.get_cmap(cmap), orientation=orient, ticks=[0,1], extend='neither')\n",
    "    cbar.ax.tick_params(which='both', direction='out', labelsize=font_size)\n",
    "    #ax.text(0.5,1.5, 'Lat', ha='center')\n",
    "    if orient=='vertical':\n",
    "        cbar.ax.set_yticklabels(vlim)\n",
    "        cbar.ax.yaxis.set_tick_params(pad=vpad[1])        \n",
    "        cbar.set_label(label, fontsize=font_size, labelpad=vpad[0], rotation=270)\n",
    "    elif orient=='horizontal':\n",
    "        cbar.ax.xaxis.set_ticks_position(tpos)\n",
    "        cbar.ax.set_xticklabels(vlim)\n",
    "        cbar.ax.xaxis.set_tick_params(pad=hpad[1])\n",
    "        cbar.set_label(label, fontsize=font_size, labelpad=hpad[0])\n",
    "    if picdir:    \n",
    "        fn = f\"{picdir}/cbar_lat{name}.pdf\"\n",
    "        plt.savefig(fn, bbox_inches='tight', transparent=True, dpi=800, pad_inches=0.01)\n",
    "        print('save to file: '+fn)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def plot_insetprofs(dName, brief, w_cm, picdir='.', **kwargs):\n",
    "    name, track = dName.split()\n",
    "    v, range_g, Lats, Lons, demfile, atr = prepare_data_bm(brief[dName])\n",
    "    \n",
    "    if 'tick_p1' not in kwargs: kwargs['tick_p1']=None\n",
    "    if 'tick_p2' not in kwargs: kwargs['tick_p2']=None\n",
    "    if 'tick_p3' not in kwargs: kwargs['tick_p3']=None\n",
    "    \n",
    "    if kwargs['tick_p1']==None:\n",
    "        if track.startswith('a'):   kwargs['tick_p1']=['in', 'in', -15, -8, True,  False, False, False, 'center', 'left']\n",
    "        elif track.startswith('d'): kwargs['tick_p1']=['in', 'in', -15, -8, False, False, False, False, 'center', 'center']\n",
    "    if kwargs['tick_p2']==None:\n",
    "        if track.startswith('a'):   kwargs['tick_p2']=['in', 'in', -15, -8, False, False, False, False, 'center', 'center']\n",
    "        elif track.startswith('d'): kwargs['tick_p2']=['in', 'in', -15, -8, False,  True, False, False, 'center', 'right']\n",
    "    if kwargs['tick_p3']==None:\n",
    "        kwargs['tick_p3']=['in', 'in', -15, -8, False, False, False, False, 'center', 'center']    \n",
    "    \n",
    "    for key in v:\n",
    "        v[key] = remove_modes(v[key], N=10)\n",
    "    v['Corrected velocity'] = v['Velocity2']-v['Plate motion']\n",
    "    \n",
    "    lat_min = np.nanmin(Lats)\n",
    "    lat_max = np.nanmax(Lats)\n",
    "    print('Latitude: {:.2f} / {:.2f}'.format(lat_min, lat_max))\n",
    "    symbol_cbar_lat(kwargs['cmap'], size=[1.3,0.1], vlim=[str(int(lat_min)), str(int(lat_max))], label=' ', font_size=10, hpad=[-13,4], name='_'+track, picdir=picdir)\n",
    "    kwargs['clim']      = [lat_min, lat_max]\n",
    "    \n",
    "    #-------- before\n",
    "    kwargs['subplot_w']   = w_cm*cm2in\n",
    "    kwargs['subplot_h']   = w_cm*cm2in * .5\n",
    "    kwargs['titstr']      = ''\n",
    "    kwargs['ticks']       = True\n",
    "    kwargs['tick_params'] = kwargs['tick_p1']\n",
    "    fn = f\"{picdir}/{name}_{track}_rb.{ext}\"\n",
    "    plot_rampprof(data1=v['Velocity2'], data2=None, range_dist=range_g, latitude=Lats, super_title=None, outfile=fn, **kwargs)\n",
    "\n",
    "    #-------- after\n",
    "    kwargs['subplot_w']   = w_cm*cm2in\n",
    "    kwargs['subplot_h']   = w_cm*cm2in * .5\n",
    "    kwargs['titstr']      = ''\n",
    "    kwargs['ticks']       = True\n",
    "    kwargs['tick_params'] = kwargs['tick_p2']    \n",
    "    fn = f\"{picdir}/{name}_{track}_ra.{ext}\"\n",
    "    plot_rampprof(data1=v['Corrected velocity'], data2=None, range_dist=range_g, latitude=Lats, super_title=None, outfile=fn, **kwargs)\n",
    "\n",
    "    #-------- PMM\n",
    "    kwargs['subplot_w']   = w_cm*cm2in * 0.4348\n",
    "    kwargs['subplot_h']   = w_cm*cm2in * 0.4348 * .5\n",
    "    kwargs['titstr']      = ''\n",
    "    kwargs['ticks']       = False\n",
    "    kwargs['tick_params'] = kwargs['tick_p3']    \n",
    "    kwargs['slope_leg']   = 'newline'\n",
    "    fn = f\"{picdir}/{name}_{track}_rm.{ext}\"\n",
    "    plot_rampprof(data1=v['Plate motion'], data2=None, range_dist=range_g, latitude=Lats, super_title=None, outfile=fn, **kwargs)        \n",
    "    \n",
    "\n",
    "def make_insetmaps(dName, brief, w_cm, l_cm, picdir='.', **kwargs):\n",
    "    name, track = dName.split()\n",
    "    v, range_g, Lats, Lons, demfile, atr = prepare_data_bm(brief[dName])\n",
    "    \n",
    "    if 'tick_p1' not in kwargs: kwargs['tick_p1']=None\n",
    "    if 'tick_p2' not in kwargs: kwargs['tick_p2']=None\n",
    "    if 'tick_p3' not in kwargs: kwargs['tick_p3']=None    \n",
    "    \n",
    "    if kwargs['tick_p1']==None:\n",
    "        if track.startswith('a') or track.startswith('d046'):    kwargs['tick_p1']=['in', -15, -35, True, False, True, False, 'center', 'center']\n",
    "        elif track.startswith('d') and track.startswith('d119'): kwargs['tick_p1']=['in', -12, -8, False, False, True, False, 'center', 'center']\n",
    "        else:                                                    kwargs['tick_p1']=['in', -15, -35, False, False, True, False, 'center', 'center']\n",
    "    if kwargs['tick_p2']==None:\n",
    "        if track.startswith('a') or track.startswith('d046'):    kwargs['tick_p2']=['in', -15, -35, False, False, True, False, 'center', 'center']\n",
    "        elif track.startswith('d') and track.startswith('d119'): kwargs['tick_p2']=['in', -15, -35, False, True, True, False, 'right', 'center']\n",
    "        else:                                                    kwargs['tick_p2']=['in', -15, -35, False, True, True, False, 'center', 'center']\n",
    "    if kwargs['tick_p3']==None:\n",
    "        kwargs['tick_p3']=['in', -15, -35, False, False, False, False, 'center', 'center']\n",
    "    \n",
    "    vmin, vmax = kwargs['vlims']\n",
    "    symbol_cbar_velo(kwargs['cmap'], size=[1.3,0.1], vlim=[str(int(vmin)), str(int(vmax))], label='LOS velocity\\n[mm/yr]', font_size=10, hpad=[-13,4], name='_'+track, picdir=picdir)\n",
    "        \n",
    "    #-------- before\n",
    "    kwargs['tick_params'] = kwargs['tick_p1']\n",
    "    kwargs['subplot_w'] = w_cm*cm2in\n",
    "    kwargs['subplot_h'] = l_cm*cm2in\n",
    "    show_list = ['Velocity2']\n",
    "    titles    = False\n",
    "    f_suff    = 'vb'\n",
    "    v_show    = {ikey: v[ikey] for ikey in show_list}\n",
    "    fn = f\"{picdir}/{name}_{track}_{f_suff}.{ext}\"\n",
    "    plot_imgs(v_show, atr, demfile, titles=titles, super_title=None, outfile=fn, **kwargs)\n",
    "\n",
    "\n",
    "    #-------- after\n",
    "    kwargs['tick_params'] = kwargs['tick_p2']\n",
    "    kwargs['subplot_w'] = w_cm*cm2in\n",
    "    kwargs['subplot_h'] = l_cm*cm2in    \n",
    "    show_list = ['Corrected velocity']\n",
    "    titles    = False\n",
    "    f_suff    = 'va'\n",
    "    v_show    = {ikey: v[ikey] for ikey in show_list}\n",
    "    fn = f\"{picdir}/{name}_{track}_{f_suff}.{ext}\"\n",
    "    plot_imgs(v_show, atr, demfile, titles=titles, super_title=None, outfile=fn, **kwargs)\n",
    "\n",
    "\n",
    "    #-------- PMM\n",
    "    kwargs['tick_params'] = kwargs['tick_p3']\n",
    "    kwargs['subplot_w'] = w_cm*cm2in * 0.4348\n",
    "    kwargs['subplot_h'] = l_cm*cm2in * 0.4348\n",
    "    show_list = ['Plate motion']\n",
    "    titles    = False\n",
    "    f_suff    = 'vm'\n",
    "    v_show    = {ikey: v[ikey] for ikey in show_list}\n",
    "    fn = f\"{picdir}/{name}_{track}_{f_suff}.{ext}\"\n",
    "    plot_imgs(v_show, atr, demfile, titles=titles, super_title=None, outfile=fn, **kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd94c130-95a3-4f57-a5f9-57d0dc77f294",
   "metadata": {},
   "source": [
    "# Figure 3\n",
    "\n",
    "## Making all the insets for Fig.3 in the maintext. Use *Illustrator* to mosaic all insets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cf926209-b0b0-4489-a24f-0b1a0e6cd039",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prepare range distance in geo-coordinates from file: /net/kraken/nobak/ykliu/2022-BulkMotion/data/Makran_a086_Geo.h5\n",
      "Latitude: 24.89 / 32.00\n",
      "save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/cbar_lat_a086.pdf\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 93.6x7.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 257.52603\n",
      "Valid (non-nan pixels) ground range min/max: 0.7483125 257.50296\n",
      "Ground range distance spans 256.8 km\n",
      "-2.3716600111211266 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Makran_a086_rb.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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bGesXIR8F9DVQezrGQakZRyCbBc4rlHRUxqEmFYVWxGqKCzxyYojDBIMkUFDnBVSKIPLUwxwfaAgDnDJEOsZpi5cCmzkSBF5KbGUJvAU8FsnWtmXzwBIYh3OCjdQx6MBKK0B7RTOKCWtIJxl60ETnnjqv2FeCUZXTlTGlqgiUROaOG/mYbhxihEdaz4s7N/n5lUdYDDp0VMJrB5tsZBM+PrNMv9Fijhab+ZRAQq/RZJjlD0aicQ68REhxa4FrAIkSikYI3/72t3n80cc4c+4ctsr41V/9Vf7whT/gX37pX3G63SKrM2a6C7TiBk+eHfPm1jXyg5yymtDuXOX7r77GwrLg+39qyLYNYuwQOaA83SsWcUbgHnWIosaP98ibLZJrU0QjwjUKjNtBhy0aZgaTV8R9Q5VV1KlACguxpN6dIDsKmWiiBYVFIbSnuiHRfdAOykLiqxoXKNRYUltHVXn6LUmVO5wSZO2cZ+cvcHOyw26dMtcesLG+jg9jRvmEp4LT1KEg8IKDrOby5h6zzZgLvT51bbg2GvLyaJNeFPHH6xeJfcC4zihrz8dnltnMJ2xPUy5PdjnXG6CDBFc7JA+w2IfDqEUBCKCy9rY0kBKK9bWbrK6uoqVEhg1Or57m23/6LZpJA+8M3ahDHTrKqoJI85Gz58krg1U5tn6EOGwwPrvNhacMb1weMn0z58qbJcPdW41OBPJliVhSuGZFkg1hRVAVKeiYYHEG8cMhJiwJ+j38JCRpTgmUotq00HdEkYLME4UpxU6C6ivafYgfh53UYPYKOqGjlDH1gcWVip7wuEqj255OX6G0pxSCmzfXWBgM2JnusDHe4OzSaSpTga3Z3N5nYdBlP7B0dcJmOiK0XSoBo0mKiCXPdpfZL1MQgo18Qq/RZEZr3hzvsZdNaaiQc+059qYTknbIQVUyeyvM+J5IXF9fP94zc+TF/tqv/dptGfW3Bn8dULsaIQ7DXMiQui5REtpxi3YM03JKJ2oRyAF5PsQvf4xG4xKDXsLq6jqjp0Z8Ylhw8eImV14TXLtoYcvh9x0EIbQLZK0JBbBTIUYTnPCEFtxkD6HA7AZoodGxw1djnAxh5LF/ogjOGawDHTkIA9qmRut9mEpGArRU2MxDXdO+oIg1COuoJiXNTLDfqfBbhjK2nFMzUHjOmTYXh5vI+YL9m5Z4qYWpBFXq2K5zmqImNQ5hLb2gQWglRnnOdHrI3CKjgJmgwdBlnO33eO1/fYv//Ud/SGktEjDewQn5xBNJXF5e5miJcWf0/ggrKyvcuHHjFqGOrZtbrNzaNGtcBULhcMf5hSRMMK4GoWg2euRDj+hKUr+Oylu0T5/HLRjOnskYfbLgpT95k1G+zTitGe56Nl8C3/YIb/ErAX5LIHSI1AJhDx0Z6QtklFAfCEQ5JFiKMWODKgJEWaGLkGJP0ZhPsRNP+uoEIRKEGhGvJOQTjQwk+nLO0AUQBbSrlA2pGAQWsSB5fHYJM8kxLmInr2g3Qg6ujpmUFY92L7BXp4Te0W4FOCMIAphOKyauphMH5OZwq0qe5zgpscCZ1gx704KP/I2/zmf+9hfw1KRFiRSWX/7pn7v5nkg8fugeBAJ88pOf5NKlS1y5coWFxVN87WtfO85KaxnihcVzOJd6xGHwmcPkrkfQ6yTkdoVW2Mf4KTbbR8zMUZqa/tyEIGlR5TtcfPk69VnD8NGC4X6FE57Z9iqXL77Kzq7AFCBeEaAlQb+Bi0rCrIZA4m+UiCYQaOqtFF9uwkybPItwlzcJDHg3gYUYNXIknQg33CWvewgHgoxsNsbv7bNnakxzhte+K/jIx5bpNjqIwLK7sUdWlATdmO9/91UeeWyViS25YQwznSahDyGoCYWiMo6WSMhtzs1siPbwidXHOKhLGtGtQLwE4yQ75YRB/ADm9K0obkXe31aB1vzu7/4un/vc57DW8hu/8Rs8/fTTx/eFUIcpmlupGSUU3jsqV5KohNJWxCqmxNMO5hmahDCURKqJCXp0Hj1HWW9y9pEnuLl9g7wyXHt5l2Qmotft0+hLsmLI1saQN9oVfk1DrWCvhoaEbYfogNoCjEEEgvqghMIhrtZIU8OcQkiPqAt8MUEVDn8AIo4ReoJPNX47hcQipCF79QBWKv7vxYz+9gJPL81xLU/ZmY6YM2061vPSq1cJnIAABh89x8hu0ZWzbFTXiKMmc/ESlXOc6ffwuUWrjIY9tFfTaca+FAgcga95Y++1E7m574iN9/74/MW72QrhvblF5uF4cd7edZNxXqeE0iNEQGVTIt2nMhOEDKldSVlsYk2b/fH32Ngz9LuL7O1dIlSLXF9fZ2/3DWQT1l9OufqDlHFqqQoNaQnKQCuE9QJhJWxLXBxhvEMZA84h+mC9hsAi+hZbO9yax2p1aEkCcN0GvhkCHochGAxoz3uKg5LEVmyohFNNBy0PlQMvaCUdVlda2L5l3A5oo2iHGhUJTs90WStyimnNqU5CN+6xO8nJa0+v2aHfTCjtLleGN/nq3/nNB4vYwGH0/rjQPQh03iDFnZuYbv9+RKD1FiUUzhsEEKjwVv7AEwczeG/QKibLxqBjQt0gq8co1+Px1ZjruzdQLqDZHXLmjOL0+Sc52BuyOmjQ6LzOjHiErYPrXHttm95ql+2bU3akPPwhPYeaGOS2RwQBCIGfWoS1OAd2KPGhR5QK3fbUWzVKKMS0xC0oPDmiEVONpwxHHisN417CqXwMcYjdLFHOgLdMsy1evNQimglhscVotoET0B8EJE5gaoMxOXlsSdOa1/enCONZmZtQmoid0R5L8/MncnNfJEoh7kvz7iTwJBztmzkuY3OEigCH9wYhNBJDknRAeLxbQGGJg0dIzT6rsxfY1JfxKSRxSFsPWDjbYLxd0fvZT7Nzs2T/cotP/NQKma05tZpyc3PIjde3KVsGM3GIgUDEHm7EuEmBUArlHKJhQQX4eYG5WtKIYmrtwUvMgad0AQKLGuU45ZGxQJuKyakO7fEEVVkIPCZ3OCRRNoIMSIeUDEDHDG2L7w736HYU8UxIlFfs14ZYQag9G9OMrYOURxdmafqHELFxzpEaQzMM33E/yd1wRMpJ9x0eLSRv288sQMuYvCqI4hWkLRBFhYwUQp6mbB1gAWErjPEE7TYtc8BMb5mf/vQFbmytU48bZH6LJy88TvNzA65eucj3/8/3iBchrWPspyXX/8LhpiB2p8gtiTc5ou0JZxTsW6KZkHokUVKQqIBqbNBAiYCpwG4V2P2CSjsa3Yw0ChmUFh17KAWEwFoNo02INHUjwjwyIA1naQwNV6Tn/KmQ2X7AZKTYzSd0+gFSCvbdQ4idKilpBMF7IhDeblLhdmKF0ATqMKQnRYUQ+vhP33omieOjkoTBHNZNiLQmFMt0OnNkZQWUjIdv0G6sUhlDlc/yxLlTbG9so/UyWTGm1BmnmaPMf4qoHdFZsIyyCS1/nf19OFgckJ2zQIXPKmgIWLbIXBOWIfbW/tajoaaUolAKUXpcerhUyDYd/aSmbkaU25aWEhBZRA/MFUsaG5o9i9rPmL68RbXSgMdnKUWDatBkYaZJNE0Y9FpEVZ8iesCw26GQBSc5QO8FdxLrvUNJiRDx8Tx5J6wrgRilSpAxIafwvkLIkHYjYW/4JnNzz5CnE3qdDr4fUGWe5RVFVloGYZeN9etEc136P9+k21oiFfv0GqdY6L4C3vL6xS3Wdq8TN0PW3rAYUzKeZCAlwknEroR9DzeDQwsQCJLa46IQoySmqpHNBpO6xo89OrxFsrGotRJnBUmlsCOLvwpClyBLxM+V7H50hp21IR/52BNk04LxEHRzCNUDZvaPH3yfN+YKIY+3Jx7Nk3eaYSkUEodSDaQHXAoipChywihh0D9LXeaARAVthPSEHU9daSwFXjqWFi+gdcU4a+BtzOzsKaTwPHHhKSId0Btc5RdaH2XtzU1e4zKyN6GqHOm0QoYx48Ki9JSpU2ztW4KmJLcl1Z+FBG8CQ4XAgwiZcDgVFUIQR55wEFG6mmytxgtB4D2lgQTwf16Sb+0RP93gf6ZvEjYjjFIstmBhYeVE2d03ie/3Duu7mdw7rwmhCY78IJcShAkChdIlde0RUhAnfcKohXcC62sCGaMURHFCEHimVY6QMUuLZ5nmEwLZQCLodQ3GwoWVZ5gWE3rP9jjz2AqXr1xCBxXj3X1EOyO3HTIXMEkPWFqAouPJZZt63rJ/YOnHTW68WSIKgd6B7KLAFpbGTIwJK1Q3IlkoyDcr3MTQGjoyAbZp4WLBwRs5ejAiPN8mOjPPWijYL+4ZrAF+TCT+zu/8Dl/+8pfZ2dlhdnb2vsocaeFx6ustAQMAKSOk0DhvUEKjQoV19eGeHRGitUT68PCMJZ5QKySeVjdBqYAiL+k25wDI65xW3AIkDkuj1mRFm1aQ0X2mx829awxm+mQmZzjapE3ISvdRJvmYWHuiVoe/SNY4P+mi/ZhHV5fZrba5dlkhnxYIY/Ejz5KNmEpBlmjip2KqSzvY3Yok98iGQZzxCKDYsLTsBHfQxTc02W59oqzed3N648YNvvnNb3L69Ol3Ve5IC4824R4ReDSYjgg8Mr1VWROECudASgdIPKCkxvsSrZpYbwnVYdQpikuMnaJkDE6jlEBJiXcxMoFmAkXdZKCgFcQMq3Wmk30ilyPiGbSaIU8L8DG1qXmq8xiNuYT1jXVGdUbHN3n8fMEkDfBENOIAMTHMLi1T5hU3XtnhcphQvXmAC2LE2nWoarSC5AxwYCHbRs33mVtKTpTV+07il770Jb761a/yhS984bbr7/Xk0Vv7IYXGe4P18vAMpAcp5fEAOAosaHUYezS1oaorkmaC8PHhuQ5vSSJNXlkCpUGBsRYlPdofRmea0Qxx3GBLXGGmv4z0AmcNeWeBqtpDioi8GkExwg4MnaJBFM+yMdrHdCyVl2xPDcuLDTbHO5w+1eXMc48yd2kNPhrzymtDRnYJigzqCrdbYnOPHETIbsL2xkNybN6tOTXO8QcvvMDy8jLPPvvs2+6/E4H3295RUOBII62r8ID38rbTVt4bojDCysMXRWh9tFFYYZ1BCkFhMxq6hZbgqEHU1LXCWEW7MUtjtklRF+AktUkZ6BDHEpN8B5WmONmlwSax8iShJApmGGcptioJAoUtMs51a0LtSGTFs6sh61dHPPvsInvzI/Z3FZMdR/yIZX8o8ApMqonPRyfK4L7ziUf44he/eFs+8bOf/Sybm5tvK/vbv/3bfOUrX+Eb3/jGySzcq2PvYsBIoTF1idLq0DzCrY3AP8KRdt5t8CipMbUjDn6ULdAywgWHC3olQoTyCKdRok2SBECfvB4T6T7WeeJoFmumuKrgQN7AVymPLf0UV/avUNXQtSXrN28QtAc0As3e3iVm28sMzrRpFdBsBKyempLLGdZfvs73//xbVEWNjhX2OvBezyceBcDfC374wx/ymc98hkajAcDa2hpLS0t85zvfYXFx8T3V+W5gXYkQIYK3H/aEu5xEvhXLPYL3Do/DOXk8L98ZvDfOoISisilKNMjrHUYHb7A/vEHptuklSxSqha322ZmkiLDNdDTB4/BmQkFCXRaHYb3xlGE+gaCiygTt3nlSBElYsTku+He//OUHD4C/WzzzzDNsb28ffz979izf+9737ts7vRMnzaGH+4B4i7ANUoQnvrlKKn97nV7g73jblRQa+ZYmpVB3eMkS52ukDBAYAtWi3VohjOepJy8zzUaI6oCoscAzg4+znY6ZaY7YHm7jREyUZtCdZ3QwxSWK+f48o7xiWh7g2Wa2c4pRUXH6HUT2k3GY/T5wNwKff/75w2yHlLedMTxcnpwcIhRC31bnYbRIvOX+20XjvL1tmaPlYYAikBFKhoQ6opus0ghb/OE3btLtPU4SNBm0H8VQ0pKabrLC3KDPTKtFb7AAQUiz36fXXyLoLTI3v8K5M2eJmwk+36QTNShN/La+vBXvmybeiatXrz70Op9//vnb5mc41MKjefFhobYGgUDf5X128raIksZ7SzOa47/+3u/zS1/4JK3WEhJDLBQ7+SbdUNDTp+j15xkWQ1ZFQuGmpNUQLfvcnKyx1G4iWOba3jrSjHHV9MT+/dhI/HHAew/e4zF43l1q7LD8oTN0pxYG6t71eG+Bt2qxBCxSambaj1HWU5yryCvL6uwFjMloNxYo6jGzyQBHiDYapULGxjNordJSisujiyy0mmxNa6bZ7on9/kCReChIfbgF+K6ZE3/47px7HAG/1ytUTm5T3fFdINAIIA76hKpDWm8ziBo476lNRBx2SaIeRT2htjktndDSfSI9obA53jtajT6mHCNVg+bS3V+ueIS/MnPi/UIIcU8NFLdefPRj6sktDxki3UapCIellcwd9kMoIt0gCVpofXgGMgobOAlKxCgXMvUhYdKld8vDv2dLJy0xhBCvAm8+5F/3MLEEnBwd/svDw+7bI/4e7zs9kcQP8VcDHzhz+v8jPiTxA4APSfwA4EMSPwD4kMQPAP4fLcgL40Ns2B0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 257.52603\n",
      "Valid (non-nan pixels) ground range min/max: 0.7483125 257.50296\n",
      "Ground range distance spans 256.8 km\n",
      "-0.01301148320561213 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Makran_a086_ra.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 257.52603\n",
      "Valid (non-nan pixels) ground range min/max: 0.0 257.52603\n",
      "Ground range distance spans 257.5 km\n",
      "-2.3623179743182026 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:616.25/308.13\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Makran_a086_rm.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 55.4627x27.7313 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prepare range distance in geo-coordinates from file: /net/kraken/nobak/ykliu/2022-BulkMotion/data/Makran_d020_Geo.h5\n",
      "Latitude: 25.10 / 32.00\n",
      "save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/cbar_lat_d020.pdf\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 93.6x7.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 257.334\n",
      "Valid (non-nan pixels) ground range min/max: 0.17575 256.69208\n",
      "Ground range distance spans 256.5 km\n",
      "2.524698752688714 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Makran_d020_rb.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 257.334\n",
      "Valid (non-nan pixels) ground range min/max: 0.17575 256.69208\n",
      "Ground range distance spans 256.5 km\n",
      "0.3070605590585307 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Makran_d020_ra.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 257.334\n",
      "Valid (non-nan pixels) ground range min/max: 0.0 257.334\n",
      "Ground range distance spans 257.3 km\n",
      "2.1911095494620105 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:616.25/308.13\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Makran_d020_rm.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 55.4627x27.7313 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prepare range distance in geo-coordinates from file: /net/kraken/nobak/ykliu/2022-BulkMotion/data/Aqaba_a087_Geo.h5\n",
      "mask velocity using /net/kraken/nobak/ykliu/2022-BulkMotion/data/Aqaba_a087_msk.h5\n",
      "Latitude: 26.17 / 33.33\n",
      "save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/cbar_lat_a087.pdf\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 93.6x7.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 255.40157\n",
      "Valid (non-nan pixels) ground range min/max: 0.929375 252.75\n",
      "Ground range distance spans 251.8 km\n",
      "-2.4303418944047332 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Aqaba_a087_rb.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 255.40157\n",
      "Valid (non-nan pixels) ground range min/max: 0.929375 252.75\n",
      "Ground range distance spans 251.8 km\n",
      "0.11694902995160378 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Aqaba_a087_ra.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 255.40157\n",
      "Valid (non-nan pixels) ground range min/max: 0.0 255.40157\n",
      "Ground range distance spans 255.4 km\n",
      "-2.496431737834936 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:616.25/308.13\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Aqaba_a087_rm.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 55.4627x27.7313 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prepare range distance in geo-coordinates from file: /net/kraken/nobak/ykliu/2022-BulkMotion/data/Aqaba_d021_Geo.h5\n",
      "mask velocity using /net/kraken/nobak/ykliu/2022-BulkMotion/data/Aqaba_d021_msk.h5\n",
      "Latitude: 26.43 / 34.17\n",
      "save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/cbar_lat_d021.pdf\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 93.6x7.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 2.9802322387695312e-08\n",
      "Ground range min/max: 0.0 257.00183\n",
      "Valid (non-nan pixels) ground range min/max: 1.7585938 254.00235\n",
      "Ground range distance spans 252.2 km\n",
      "2.144168529537837 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Aqaba_d021_rb.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 257.00183\n",
      "Valid (non-nan pixels) ground range min/max: 1.7585938 254.00235\n",
      "Ground range distance spans 252.2 km\n",
      "0.18848668974253338 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Aqaba_d021_ra.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 257.00183\n",
      "Valid (non-nan pixels) ground range min/max: 0.0 257.00183\n",
      "Ground range distance spans 257.0 km\n",
      "1.6988635504271312 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:616.25/308.13\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Aqaba_d021_rm.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 55.4627x27.7313 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prepare range distance in geo-coordinates from file: /net/kraken/nobak/ykliu/2022-BulkMotion/data/Australia_d119_Geo.h5\n",
      "mask velocity using /net/kraken/nobak/ykliu/2022-BulkMotion/data/Australia_d119_msk.h5\n",
      "Latitude: -28.83 / -22.24\n",
      "save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/cbar_lat_d119.pdf\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHMAAAAmCAYAAAD3AKSiAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAADKUlEQVR4nO2ZPYhcVRiGn3dmNiT+FEEtjD9YiyiKIASbgBCtAlpYaCFoJyK2dvYW1pJGQQTRYOUfYgoxGIgomrggQlDQFCERCcjMzjnntbjnTm5Gdndm7sKuZ88DH9/Pufebw/fO3DtzR7aplMFgtzdQ2TmqmAVRxSyIKmZBVDELoopZEKM+Jx8/drMvXw0YkwDbJISBhJrY2ec8+XrcrrU1z2Kun2eatY6nk2NmNdpfWc42V1N3va3dcPx/j5E3P17tzzp319zJ2zj7drOzWrt5Z2eu8dfntp9cRY9eYl65GvnmsyNMHBg7MraZWIw9ZOwRY69lf4BxWmvy7Cepif9JB5ikEZM0YiONmMTGb6QhG3HIRhoyjUOm2Yc0IMTGYhqQYmvCUZAaryjIXgkUhCJNHmlq8UYbzNUHszXP4kE0Ctm39ZDjkFBITR4SihGFBCGhECFGCAFC4x0CTBvvacBhypf+8PZV9aiX2YKoYhZEFbMgqpgFoT4P2iWdB8Y7t50KcND2A6uc2OvbLDC2/WjPHpUOks6tem69zBZEFbMg+or59o7sotJl5Zn2+gJU2VvUy2xBVDELYikxJT0n6cdsZyQ91Fl7TdIFSeclvS/p4M5vtyw2m6ekeySdlrSeZ/rqQg1tL2zAUeBwjp8Czub4LuAicCjnHwAvLNN7P9oW87wTeCTHtwK/APdv12+phwa2z3TSb4G7O/kIOCRpCtwE/LlM7/3IZvO0fQm4lONrktZpPjA/b9Wvzz3zReDT/IJ/AG8Cv+dN/G37ix699yOzeXaRdB/wMHB22w4rXh6OAevAbTk/DHwF3AGsAR8Dz+/2Zez/YvPz7NRvAb4Dnl6kz7afTEkvS/oh2xFJDwIngRO2r+TDngAu2r5sewqcorkfVOZYcJ5IWgM+At6zfWqh5ku+g+4FfgWOztUfAy7Q3CsFvAO8stvv+L1uW8xTwLvAW8v0W+oJkKSTwDPAb7kUnP81kfQG8CwQgO+Bl2xPFm6+D9lsnpIeB74GfgJSXnvd9idb9ltGzMrepj4BKogqZkFUMQuiilkQVcyCqGIWRBWzIKqYBfEvDXYKWDHLUv4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 93.6x7.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 253.31784\n",
      "Valid (non-nan pixels) ground range min/max: 1.0149063 251.99696\n",
      "Ground range distance spans 251.0 km\n",
      "1.608901350750506 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Australia_d119_rb.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 253.31784\n",
      "Valid (non-nan pixels) ground range min/max: 1.0149063 251.99696\n",
      "Ground range distance spans 251.0 km\n",
      "0.02032889932677178 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Australia_d119_ra.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 253.31784\n",
      "Valid (non-nan pixels) ground range min/max: 0.0 253.31784\n",
      "Ground range distance spans 253.3 km\n",
      "1.5945083172361656 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:616.25/308.13\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Australia_d119_rm.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 55.4627x27.7313 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prepare range distance in geo-coordinates from file: /net/kraken/nobak/ykliu/2022-BulkMotion/data/Australia_d046_Geo.h5\n",
      "mask velocity using /net/kraken/nobak/ykliu/2022-BulkMotion/data/Australia_d046_msk.h5\n",
      "Latitude: -27.63 / -22.53\n",
      "save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/cbar_lat_d046.pdf\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 93.6x7.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 253.3031\n",
      "Valid (non-nan pixels) ground range min/max: 1.0349687 251.34735\n",
      "Ground range distance spans 250.3 km\n",
      "2.1113368836459903 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Australia_d046_rb.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 253.3031\n",
      "Valid (non-nan pixels) ground range min/max: 1.0349687 251.34735\n",
      "Ground range distance spans 250.3 km\n",
      "0.5497782115000316 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:1417.32/708.66\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Australia_d046_ra.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 127.559x63.7795 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Range ramp scatter plot shifted by median 0.0\n",
      "Ground range min/max: 0.0 253.3031\n",
      "Valid (non-nan pixels) ground range min/max: 0.0 253.3031\n",
      "Ground range distance spans 253.3 km\n",
      "1.5307737620596389 mm/year/100 km\n",
      "Figure ext:png dpi:800 W/H:616.25/308.13\n",
      "Save to file: /net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets/Australia_d046_rm.png\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 55.4627x27.7313 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Start insets\n",
    "picdir    = '/net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets'\n",
    "font_size = 10\n",
    "w_cm      = 4.5      # width of figure [cm]\n",
    "l_cm      = 11.5     # not used\n",
    "cm2in     = 1/2.54   # cm to inches\n",
    "dpi       = 800\n",
    "plt.rcParams.update({'font.size': font_size})\n",
    "\n",
    "\n",
    "## the common kwargs\n",
    "kwargs = dict()\n",
    "kwargs['cmap']        = 'viridis_r' #'GnBu'\n",
    "kwargs['title_pad']   = 4.\n",
    "kwargs['range_type']  = 'Ground'\n",
    "kwargs['xticks']      = [100,200]\n",
    "kwargs['alpha']       = 0.4\n",
    "kwargs['dpi']         = dpi\n",
    "kwargs['font_size']   = font_size\n",
    "kwargs['slope_leg']   = True\n",
    "\n",
    "\n",
    "## Let's plot all datasets\n",
    "dName = 'Makran a086'\n",
    "kwargs['vlim']        = [-6,6]\n",
    "plot_insetprofs(dName, brief, w_cm, picdir, **kwargs)\n",
    "\n",
    "dName = 'Makran d020'\n",
    "kwargs['vlim']        = [-6,6]\n",
    "plot_insetprofs(dName, brief, w_cm, picdir, **kwargs)\n",
    "\n",
    "dName = 'Aqaba a087'\n",
    "kwargs['vlim']        = [-6,6]\n",
    "plot_insetprofs(dName, brief, w_cm, picdir, **kwargs)\n",
    "\n",
    "dName = 'Aqaba d021'\n",
    "kwargs['vlim']        = [-6,6]\n",
    "plot_insetprofs(dName, brief, w_cm, picdir, **kwargs)\n",
    "\n",
    "dName = 'Australia d119'\n",
    "kwargs['vlim']        = [-6,6]\n",
    "kwargs['tick_p1']     = ['in', 'in', -15, -8, True,  False, False, False, 'center', 'left']\n",
    "kwargs['tick_p2']     = ['in', 'in', -15, -8, False, False, False, False, 'center', 'center']\n",
    "plot_insetprofs(dName, brief, w_cm, picdir, **kwargs)\n",
    "\n",
    "dName = 'Australia d046'\n",
    "kwargs['vlim']        = [-6,6]\n",
    "kwargs['tick_p1']     = None\n",
    "kwargs['tick_p2']     = None\n",
    "plot_insetprofs(dName, brief, w_cm, picdir, **kwargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa416262-8f73-417a-bcbe-cd1ca6317b02",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Start insets\n",
    "picdir    = '/net/kraken/nobak/ykliu/2022-BulkMotion/pic/insets'\n",
    "font_size = 10\n",
    "w_cm      = 4.5          # width of inset [cm]\n",
    "l_cm      = w_cm*1.771   # length of inset\n",
    "cm2in     = 1/2.54       # cm to inches\n",
    "dpi       = 800\n",
    "plt.rcParams.update({'font.size': font_size})\n",
    "\n",
    "\n",
    "kwargs = dict()\n",
    "kwargs['aspect']    = 'auto'\n",
    "kwargs['font_size'] = font_size\n",
    "kwargs['laloStep']  = 2\n",
    "kwargs['title_pad'] = 4\n",
    "kwargs['suptity']   = 0.1\n",
    "kwargs['alpha']     = 0.85\n",
    "kwargs['refpoint']  = False\n",
    "kwargs['dpi']       = dpi\n",
    "kwargs['cmap']      = 'RdYlBu_r'\n",
    "kwargs['cbox_loc']  = False\n",
    "kwargs['sbox_loc']  = False\n",
    "kwargs['tbox_loc']  = False\n",
    "kwargs['coast_lw']  = 0.3\n",
    "kwargs['constrain'] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53dc9316-ddd2-4098-bae2-2d08faca8ceb",
   "metadata": {},
   "outputs": [],
   "source": [
    "##################  Makran  ####################\n",
    "kwargs['shadeExg']  = 0.02\n",
    "kwargs['shadeMin']  = -6e3\n",
    "kwargs['shadeMax']  =  5e3\n",
    "kwargs['vlims']     = [-5,5]\n",
    "kwargs['yticks']    = [26, 28, 30]\n",
    "\n",
    "dName = 'Makran a086'\n",
    "kwargs['tick_p1']=None\n",
    "kwargs['tick_p2']=None\n",
    "make_insetmaps(dName, brief, w_cm, l_cm, picdir, **kwargs)\n",
    "\n",
    "dName = 'Makran d020'\n",
    "kwargs['tick_p1']=['in', -15, -35, False, False, True, False, 'right', 'center']\n",
    "kwargs['tick_p2']=['in', -15, -35, False,  True, True, False, 'right', 'center']\n",
    "make_insetmaps(dName, brief, w_cm, l_cm, picdir, **kwargs)\n",
    "\n",
    "\n",
    "\n",
    "##################  Aqaba  ####################\n",
    "kwargs['shadeExg']  = 0.04\n",
    "kwargs['shadeMin']  = -6e3\n",
    "kwargs['shadeMax']  =  5e3\n",
    "kwargs['vlims']     = [-5,5]\n",
    "kwargs['yticks']    = [28, 30, 32]\n",
    "\n",
    "dName = 'Aqaba a087'\n",
    "kwargs['tick_p1']=['in', -15, -35, True,  False, True, False, 'left', 'center']\n",
    "kwargs['tick_p2']=['in', -15, -35, False, False, True, False, 'left', 'center']\n",
    "make_insetmaps(dName, brief, w_cm, l_cm, picdir, **kwargs)\n",
    "\n",
    "dName = 'Aqaba d021'\n",
    "kwargs['tick_p1']=['in', -15, -35, False, False, True, False, 'left', 'center']\n",
    "kwargs['tick_p2']=['in', -15, -35, False,  True, True, False, 'left', 'center']\n",
    "make_insetmaps(dName, brief, w_cm, l_cm, picdir, **kwargs)\n",
    "\n",
    "\n",
    "\n",
    "##################  Australia  ####################\n",
    "kwargs['lakes']     = False\n",
    "kwargs['alpha']     = 0.90\n",
    "kwargs['shadeExg']  = 0.10\n",
    "kwargs['shadeMin']  = -7e3\n",
    "kwargs['shadeMax']  =  5e3\n",
    "kwargs['vlims']     = [-5,5]\n",
    "kwargs['yticks']    = [-26, -24]\n",
    "\n",
    "dName = 'Australia d119'\n",
    "kwargs['tick_p1']=['in', -15, -35, True,  False, True, False, 'right', 'center']\n",
    "kwargs['tick_p2']=['in', -15, -35, False, False, True, False, 'right', 'center']\n",
    "make_insetmaps(dName, brief, w_cm, l_cm, picdir, **kwargs)\n",
    "\n",
    "dName = 'Australia d046'\n",
    "kwargs['tick_p1']=['in', -15, -35, False, False, True, False, 'right', 'center']\n",
    "kwargs['tick_p2']=['in', -15, -35, False,  True, True, False, 'right', 'center']\n",
    "make_insetmaps(dName, brief, w_cm, l_cm, picdir, **kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "091d53b4-a0da-4005-9316-19f8e29aa1e2",
   "metadata": {},
   "source": [
    "# Make separate colorbars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fbf69ed1-fe04-4076-870e-9f88665eb3a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 93.6x7.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 93.6x7.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "symbol_cbar_velo(cmap='RdBu',   size=[1.3,0.1], vlim=['-10','10'], orient='horizontal', font_size=10, hpad=[-13,4], label='LOS velocity\\n[mm/yr]', name='', picdir=False)\n",
    "symbol_cbar_lat(cmap='viridis', size=[1.3,0.1], vlim=['25','32'],  orient='horizontal', font_size=10, hpad=[-13,4], label=' ',   name='', picdir=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "727b2b54-474c-45ef-a2ab-66130cd495a6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5b1f2dec-4719-4570-a27b-8a9df57c3993",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "9d0b5a3a6bb0faffb13560f8d5ae92386a5ba894a2bcd68baff1437a82c3b780"
  },
  "kernelspec": {
   "display_name": "Python [conda env:insar]",
   "language": "python",
   "name": "conda-env-insar-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}