figures/fig_A2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import glob as glob\n",
    "import matplotlib.gridspec as gridspec\n",
    "from netCDF4 import Dataset\n",
    "\n",
    "import scipy.io as sio\n",
    "\n",
    "import cmocean "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "matplotlib.rcParams.update({'font.size': 12}) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "directory = '/Users/laura/Documents/scripts/IMEDEA/data/new_cutoffs/'\n",
    "\n",
    "mdata  = sio.loadmat(directory + 'wnoises_loop_try2_cut.mat')\n",
    "mdata2 = sio.loadmat(directory + 'wnoises_loop_try2.mat')\n",
    "\n",
    "cut   = mdata['cut1'].squeeze()\n",
    "lamn  =  mdata2['lamn'].squeeze()\n",
    "itern =  mdata2['itern'].squeeze()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "itern_r = reshape(itern, (10, 16))\n",
    "lamn_r  = reshape(lamn, (10, 16))\n",
    "cut_r   = reshape(cut, (10, 16))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rdfHUuZmZmdnm7a8AkdZnbgDmAC8CnwR+KOmFiPivrO5UoCcini1vICI2SFoBbN/Igx1o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\nugAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fb40850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "plt.pcolor(lamn_r, itern_r, cut_r, cmap='viridis')\n",
    "plt.xlim([0, 0.8])\n",
    "plt.colorbar()\n",
    "plt.xlabel('Lambda')\n",
    "plt.ylabel('Number of iterations')\n",
    "\n",
    "savename = '/Users/laura/Documents/scripts/IMEDEA/paperASR/new_version_remote_sensing/figs/' + 'A2' + '.jpeg'\n",
    "plt.savefig(str(savename), bbox_inches='tight', dpi=300)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  16.71864587,   23.95403557,   29.46915114,   33.85355191,\n",
       "          37.58114478,   41.37795918,   45.01642512,   48.19490587,\n",
       "          50.57560976,   53.20377868,   56.12012012,   57.7015873 ,\n",
       "          61.14795009,   63.03030303,   65.03225806,   67.1655914 ],\n",
       "       [  23.95403557,   33.85355191,   41.37795918,   48.19490587,\n",
       "          53.20377868,   57.7015873 ,   63.03030303,   67.1655914 ,\n",
       "          71.8817734 ,   74.4973545 ,   77.31054131,   83.62666667,\n",
       "          87.1884058 ,   91.06719368,   91.06719368,   95.30735931],\n",
       "       [  29.46915114,   41.37795918,   50.57560976,   57.7015873 ,\n",
       "          65.03225806,   71.8817734 ,   77.31054131,   83.62666667,\n",
       "          87.1884058 ,   91.06719368,   95.30735931,   99.96190476,\n",
       "         105.09473684,  110.78362573,  110.78362573,  117.12418301],\n",
       "       [  33.85355191,   48.19490587,   57.7015873 ,   67.1655914 ,\n",
       "          74.4973545 ,   83.62666667,   91.06719368,   95.30735931,\n",
       "          99.96190476,  105.09473684,  110.78362573,  117.12418301,\n",
       "         117.12418301,  124.23529412,  124.23529412,  132.26666667],\n",
       "       [  37.58114478,   53.20377868,   65.03225806,   74.4973545 ,\n",
       "          83.62666667,   91.06719368,   99.96190476,  105.09473684,\n",
       "         110.78362573,  117.12418301,  124.23529412,  124.23529412,\n",
       "         132.26666667,  141.40952381,  141.40952381,  151.91208791],\n",
       "       [  41.37795918,   57.7015873 ,   71.8817734 ,   83.62666667,\n",
       "          91.06719368,   99.96190476,  105.09473684,  117.12418301,\n",
       "         124.23529412,  124.23529412,  132.26666667,  141.40952381,\n",
       "         141.40952381,  151.91208791,  164.1025641 ,  164.1025641 ],\n",
       "       [  45.01642512,   63.03030303,   77.31054131,   91.06719368,\n",
       "          99.96190476,  105.09473684,  117.12418301,  124.23529412,\n",
       "         132.26666667,  141.40952381,  141.40952381,  151.91208791,\n",
       "         164.1025641 ,  164.1025641 ,  164.1025641 ,  178.42424242],\n",
       "       [  48.19490587,   67.1655914 ,   83.62666667,   95.30735931,\n",
       "         105.09473684,  117.12418301,  124.23529412,  132.26666667,\n",
       "         141.40952381,  151.91208791,  151.91208791,  164.1025641 ,\n",
       "         164.1025641 ,  178.42424242,  178.42424242,  178.42424242],\n",
       "       [  50.57560976,   71.8817734 ,   87.1884058 ,   99.96190476,\n",
       "         110.78362573,  124.23529412,  132.26666667,  141.40952381,\n",
       "         151.91208791,  164.1025641 ,  164.1025641 ,  178.42424242,\n",
       "         178.42424242,  178.42424242,  195.49090909,  195.49090909],\n",
       "       [  53.20377868,   74.4973545 ,   91.06719368,  105.09473684,\n",
       "         117.12418301,  124.23529412,  141.40952381,  151.91208791,\n",
       "         164.1025641 ,  164.1025641 ,  178.42424242,  178.42424242,\n",
       "         195.49090909,  195.49090909,  195.49090909,  195.49090909]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cut_r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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