From e6ac8aef8a2f246527212ab73d7dc6b388014077 Mon Sep 17 00:00:00 2001
From: Philipp Griewank <philipp.griewank@uni-koeln.de>
Date: Tue, 7 Mar 2023 10:47:56 +0100
Subject: [PATCH] Added notebook with paper revision plots.

Also some changes to da_functions. Will need to add the data in the next commit.
---
 23-paper-revision-collection.ipynb | 2869 ++++++++++++++++++++++++++++
 da_functions.py                    |  164 ++
 2 files changed, 3033 insertions(+)
 create mode 100644 23-paper-revision-collection.ipynb

diff --git a/23-paper-revision-collection.ipynb b/23-paper-revision-collection.ipynb
new file mode 100644
index 0000000..3bc1265
--- /dev/null
+++ b/23-paper-revision-collection.ipynb
@@ -0,0 +1,2869 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# This is a collection of all the plots used in the revised variance reduction paper\n",
+    "\n",
+    "We intended for this to be online when the second round of reviews occured, but I (Philipp Griewank) forgot to push the updated code after submitting the revisions. \n",
+    "\n",
+    "As some of the experiments take up to 2 hours to run, I stored the data for the larger experiments so that the whole notebook can be run in roughly 10 minutes. The code to generate the data is all there, just commented out. \n",
+    "\n",
+    "This is not intended to be the final version of the code, that will happen once the paper revisions are completed.\n",
+    "\n",
+    "\n",
+    "### To help understand things:\n",
+    "$\\phi$ used to be called $h$, and is still called $h$ throughout most of the code and is only relabeled at the very end\n",
+    "\n",
+    "\n",
+    "For now I will disable all save commands, and reduce the amount of experiments per timestep to speed things up \n",
+    "\n",
+    "\n",
+    "\n",
+    "## ToDo:\n",
+    "\n",
+    "\n",
+    "\n",
+    "## Done\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Important parameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "alpha_default  = 0.1 #Reguralization coeffcient for sensitivity calculation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sens_loc_length = 2000 #Loclization length in meters for the sensitivity localization"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from da_functions import *\n",
+    "from model_functions import *\n",
+    "from plot_functions import *\n",
+    "from misc_functions import *\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "sns.set(color_codes = True)\n",
+    "sns.set_style('whitegrid')\n",
+    "import pickle"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# I need this for some reason so that autocomplete works\n",
+    "%config Completer.use_jedi = False"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Running the default run that is used for the illustration plots and to generate the initial conditions for the variance reduction tests"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "initialize model and data assimilation setup using the default values\n",
+    "\"\"\"\n",
+    "m_const = set_model_constants_22()\n",
+    "da_const = set_da_constants_22()\n",
+    "sat_operator = reflectance_simulator\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 4.86 s, sys: 129 ms, total: 4.99 s\n",
+      "Wall time: 1.27 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# Run the model for the 100 time steps\n",
+    "states   = run_linear_advection_KF_22(m_const,da_const,reflectance_simulator)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plotting the first two and last three timesteps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/pgriewank/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:2: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
+      "  \n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 540x216 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = ensemble_plotter_22(states,m_const,da_const,t_start=1,t_end=3)\n",
+    "ax[1,0].set_xticklabels(['0','5','10','15','20','25'])\n",
+    "ax[0,0].set_title('background ensemble')\n",
+    "ax[1,0].set_xlabel('x [km]')\n",
+    "ax[1,1].set_xlabel('x [km]')\n",
+    "ax[0,0].set_ylabel('assim step 1 \\n' +r'$\\phi$')\n",
+    "ax[1,0].set_ylabel('assim step 2 \\n' +r'$\\phi$')\n",
+    "ax[1,1].legend(bbox_to_anchor=(-0.2,0.45),loc=3,framealpha=1.)\n",
+    "plt.subplots_adjust(wspace=0.05,hspace=0.1)\n",
+    "label_axes_abcd(fig,loc=(0.05,0.75))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 540x324 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = ensemble_plotter_22(states,m_const,da_const,t_start=da_const['ncyc']-3)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# plotting the indirect observations in additions to the direct observations for one timestep\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 7 µs, sys: 0 ns, total: 7 µs\n",
+      "Wall time: 11.2 µs\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "t_step = 40\n",
+    "bg = states[0]['bg'][t_step]\n",
+    "an = states[0]['an'][t_step]\n",
+    "truth = states[0]['truth'][t_step]\n",
+    "obs = states[0]['obs'][t_step] \n",
+    "obs_sat = states[0]['obs_sat'][t_step] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 540x360 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plot_ensemble_sat_analysis_paper(bg,an,obs,obs_sat,truth,reflectance_simulator,m_const,da_const,h_c=0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 396x324 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plot_ensemble_sat_analysis_abstract(bg,an,obs,obs_sat,truth,reflectance_simulator,m_const,da_const,h_c=0.5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Running single OSSE experiments"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "da_const_vr = set_da_constants_22(obs_loc=np.arange(25,299,50)) #changed direct point observations for variance reduction tests"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-119.38467652972545 -123.63563524670326\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 540x288 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "t_step=43\n",
+    "truth_idx=7\n",
+    "vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad, dx = vr_reloaded_22(states[0]['bg'][t_step],states[0]['bg'][t_step][:,truth_idx],m_const,da_const_vr,sat_operator,alpha=alpha_default,obs_seed=22)\n",
+    "fig, ax = quad_plotter_paper(quad,m_const,da_const_vr)\n",
+    "label_axes_abcd(fig,loc=(0.95,0.9))\n",
+    "print(vr_t,vr_r)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_J_quad_paper(J_dict,quad,sens,dx,bw=0.3,dJ=True):\n",
+    "    \"\"\"\n",
+    "    Plots the forecast metric distributions of the free forecast, forecast, and their linear approximations for the given sensitivity\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    fig = plt.figure(figsize=(4,3))\n",
+    "    nens = len(J_dict['bf'])\n",
+    "    dX_bg=(quad['bg'].T-np.mean(quad['bg'],axis=1)).T\n",
+    "    dX_an=(quad['an'].T-np.mean(quad['an'],axis=1)).T\n",
+    "    dX_an=dx\n",
+    "    dJ_ff=np.dot(sens,dX_bg)\n",
+    "    dJ_fc=np.dot(sens,dX_an)\n",
+    "    print('vr_reductions:',np.var(dJ_fc,ddof=1)-np.var(dJ_ff,ddof=1 ),np.var(J_dict['fc'],ddof=1)-np.var(J_dict['bf'],ddof=1))\n",
+    "    print('variance:',np.var(J_dict['bf'],ddof=1),np.var(dJ_ff,ddof=1),np.var(J_dict['fc'],ddof=1),np.var(dJ_fc,ddof=1 ))\n",
+    "            #'response' : np.hstack([J_dict['bf']-np.mean(J_dict['bf']),dJ_ff,J_dict['fc']-np.mean(J_dict['fc']),J_dict['es']-np.mean(J_dict['es'])]),\n",
+    "    if dJ:\n",
+    "        plot_data = {\n",
+    "            'response' : np.hstack([J_dict['bf']-np.mean(J_dict['bf']),dJ_ff,J_dict['fc']-np.mean(J_dict['fc']),dJ_fc]),\n",
+    "            'x_pos'    : np.hstack([np.zeros(nens)+0,np.zeros(nens)+1,np.zeros(nens)+2,np.zeros(nens)+3]),\n",
+    "            'type'     : ['blindforecast']*nens+['estimated']*nens+['forecast']*nens}\n",
+    "    else:\n",
+    "        plot_data = {\n",
+    "            'response' : np.hstack([J_dict['bf'],dJ_ff+np.mean(J_dict['bf']),J_dict['fc'],dJ_fc+np.mean(J_dict['fc'])]),\n",
+    "            'x_pos'    : np.hstack([np.zeros(nens)+0,np.zeros(nens)+1,np.zeros(nens)+2,np.zeros(nens)+3]),\n",
+    "            'type'     : ['blindforecast']*nens+['estimated']*nens+['forecast']*nens}\n",
+    "\n",
+    "    my_pal = [\"blue\",  \"peru\",\"cyan\",\"orange\"  ]\n",
+    "        \n",
+    "    PROPS = {\n",
+    "    'boxprops':{'facecolor':'none', 'edgecolor':'black'},\n",
+    "    }\n",
+    "    #ax = sns.violinplot(data=plot_data, inner='quartile', orient=\"v\",cut=0,bw=bw,y='response',x='x_pos',palette=my_pal)#sns.color_palette('cool',n_colors=3))#,x='type')#,y='response',x='cyc',hue='type',,split=True,palette={dict_label[left_var]:dict_color[left_var],dict_label[right_var]:dict_color[right_var]}\n",
+    "    ax = sns.stripplot(data=plot_data, y='response',x='x_pos',alpha=0.7,jitter=0.15,size=5,palette=my_pal)#color='0.0')#\n",
+    "    #ax = sns.boxplot(data=plot_data, y='response',x='x_pos',showfliers=False,**PROPS)#,patch_artist=False)#color='0.0')#,palette=my_pal\n",
+    "    #plot errorbars\n",
+    "    plt.errorbar(np.arange(4),np.zeros(4),[np.std(J_dict['bf'],ddof=1),np.std(dJ_ff,ddof=1),np.std(J_dict['fc'],ddof=1),np.std(dJ_fc,ddof=1 )],fmt='.',capsize=15,lw=3,color='k') \n",
+    "    \n",
+    "    #if dJ == False: ax.hlines(J_dict['tr_fc'],-0.5,2.5,'k',ls='--',label='truth'); plt.legend()\n",
+    "    #if dJ: ax.hlines(0,-0.5,3.5,'k',ls='--') \n",
+    "    ax.set_xlim(-0.5,3.5)\n",
+    "    if dJ == False: ax.set_ylabel(r'$j$')\n",
+    "    if dJ: ax.set_ylabel(r'$\\delta j$')\n",
+    "    ax.set_xticklabels(['free-\\nforecast','estimated \\n free-forecast','\\n forecast','estimated \\n forecast'])\n",
+    "    return fig, ax"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "vr_reductions: -119.38467652972545 -123.63563524670326\n",
+      "variance: 221.43278926594013 176.91208076683142 97.79715401923687 57.52740423710596\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 288x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plot_J_quad_paper(J_dict,quad,dJdx_inv,dx,bw=0.2)\n",
+    "#ax.set_ylim(-70,55)\n",
+    "import matplotlib as mpl\n",
+    "ax.set_ylabel(r'$\\mathbf{\\delta j}$')\n",
+    "ax.set_ylabel(r'$ \\delta j$')\n",
+    "ax.set_xticklabels([r'$\\mathbf{\\delta j}_\\mathrm{ff}$',r'$\\widetilde{\\mathbf{\\delta j}_\\mathrm{ff}}$',r'$\\mathbf{\\delta j}_\\mathrm{fc}$',r'$\\widetilde{\\mathbf{\\delta j}_\\mathrm{fc}}$'],va='bottom')\n",
+    "ax.tick_params(axis='x', pad=20)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# j evolution plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "t_vec=np.linspace(0,2500,100)\n",
+    "nt = len(t_vec)\n",
+    "J_ff_matrix = np.zeros([nt,da_const['nens']])\n",
+    "J_fc_matrix = np.zeros([nt,da_const['nens']])\n",
+    "\n",
+    "t_step=43\n",
+    "truth_idx=7\n",
+    "for t in range(nt):\n",
+    "    da_const_vr['dt']=t_vec[t]    \n",
+    "    vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad, dx = vr_reloaded_22(states[0]['bg'][t_step],states[0]['bg'][t_step][:,truth_idx],m_const,da_const_vr,sat_operator,alpha=alpha_default,obs_seed=22)\n",
+    "    J_ff_matrix[t,:] = J_dict['bf']\n",
+    "    J_fc_matrix[t,:] = J_dict['fc']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 288x432 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(3,1,figsize=(4,6),sharex='all')\n",
+    "\n",
+    "bla = ax[0].plot(t_vec,J_ff_matrix,'b'   ,alpha=0.5,label='free forecast')\n",
+    "bla = ax[1].plot(t_vec,J_fc_matrix,'cyan',alpha=0.5,label='forecast')\n",
+    "ax[2].plot(t_vec,np.std(J_ff_matrix,axis=1,ddof=1)**2,'b'   ,label='free forecast')\n",
+    "ax[2].plot(t_vec,np.std(J_fc_matrix,axis=1,ddof=1)**2,'cyan',label='forecast')\n",
+    "ax[2].legend(ncol=2,loc='upper left',)\n",
+    "# ax[0].legend()\n",
+    "# ax[1].legend()\n",
+    "ax[0].set_ylabel(r'$j_i$')\n",
+    "ax[1].set_ylabel(r'$j_i$')\n",
+    "ax[2].set_xlabel('lead time [s]')\n",
+    "ax[2].set_ylabel(r'$\\sigma^2$ $j$ ')\n",
+    "ax[2].set_ylim(bottom=0,top=750)\n",
+    "ax[1].set_ylim(-10,80)\n",
+    "ax[0].set_ylim(-10,80)\n",
+    "ax[2].set_xlim(0,t_vec[-1])\n",
+    "ax[0].vlines(550,-100,100,color='k',ls='--',alpha=0.5)\n",
+    "ax[1].vlines(550,-100,100,color='k',ls='--',alpha=0.5)\n",
+    "ax[2].vlines(550,-100,1000,color='k',ls='--',alpha=0.5)\n",
+    "plt.subplots_adjust(hspace=0.1)\n",
+    "label_axes_abcd(fig,loc=(0.95,0.9))\n",
+    "fig.align_ylabels()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Sensitivity plots of the regularized sensitivity and the sensitivity which ignores crosscorrelations\n",
+    "\n",
+    "We have to rerun the default run but with 512 ensemble members, and then make two OSSEs for 300 and 600 seconds.\n",
+    "\n",
+    "\n",
+    "Uncomment plot commands to see the intermediate steps plotted"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "da_const_512 = set_da_constants_22(nens=512,ncyc=t_step+1)\n",
+    "da_const_6   = set_da_constants_22(obs_loc=np.arange(25,299,50),nens=512,dt=300)\n",
+    "da_const_62  = set_da_constants_22(obs_loc=np.arange(25,299,50),nens=512,dt=600)\n",
+    "t_step=23\n",
+    "truth_idx=11"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/pgriewank/pgriewank/code/2021-linear-advection/da_functions.py:328: ComplexWarning: Casting complex values to real discards the imaginary part\n",
+      "  bg[:,i]    = linear_advection_model(analysis[:,i],u_ens,dhdt_ens,m_const[\"dx\"],da_const[\"dt\"],da_const[\"nt\"])\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 10.9 s, sys: 325 ms, total: 11.3 s\n",
+      "Wall time: 2.89 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# Run the model and the single OSSEs, from which we only need the quads\n",
+    "states   = run_linear_advection_KF_22(m_const,da_const_512,reflectance_simulator)\n",
+    "vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad , dx = vr_reloaded_22(states[0]['bg'][t_step],states[0]['bg'][t_step][:,truth_idx],m_const,da_const_6,sat_operator,model_seed=505,obs_seed=55)\n",
+    "vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad2, dx = vr_reloaded_22(states[0]['bg'][t_step],states[0]['bg'][t_step][:,truth_idx],m_const,da_const_62,sat_operator,model_seed=505,obs_seed=55)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n",
+    "def L2_ensemble_limit(quad,nens,alpha=None,dt=0):\n",
+    "    \"\"\"\n",
+    "    Simple function that calculates the sensitivity for a given quad\"\"\"\n",
+    "    X =quad['bg'][:,:nens]\n",
+    "    dX =  X.T - np.mean(X,axis=1)\n",
+    "    dX = dX.T\n",
+    "    J = np.zeros(nens)\n",
+    "    if dt == 0:\n",
+    "        X_J =quad['bg'][:,:nens]\n",
+    "    else:    \n",
+    "        X_J =quad['bf'][:,:nens]\n",
+    "    dX_J =  X_J.T - np.mean(X_J,axis=1)\n",
+    "    dX_J = dX_J.T\n",
+    "    for i in range(nens):\n",
+    "        J[i] = sum_mid_tri(X_J[:,i])\n",
+    "        #J[i] = sum_triangle(X_J[:,i])\n",
+    "    dJ = J-np.mean(J)\n",
+    "    B = np.cov(dX,ddof=1)\n",
+    "    cov_dJdX = np.dot(dJ,dX.T)/(nens-1)\n",
+    "    sens = L2_regularized_inversion(B,cov_dJdX,alpha=alpha)\n",
+    "    return sens\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(2,3,sharex='all',sharey='all',figsize=(8,6))\n",
+    "\n",
+    "alpha_list = [1.,0.1,0.01]\n",
+    "nens_list = [2**5,2**7,2**9]\n",
+    "#Reference lines\n",
+    "ax[0,0].plot([0,99,100,199,200,299],[0,0,1,1,0,0],'k--',label='ref')\n",
+    "ax[1,0].plot([0,99,100,199,200,299],[0,0,1,1,0,0],'k--',label='ref')\n",
+    "\n",
+    "x_advected = np.array([0,99,100,199,200,299])-da_const_6['dt']*m_const['u_ref']/m_const['dx']\n",
+    "x_advected[-1] = 299\n",
+    "ax[0,1].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "ax[1,1].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "x_advected = np.array([0,99,100,199,200,299])-da_const_62['dt']*m_const['u_ref']/m_const['dx']\n",
+    "x_advected[-1] = 299\n",
+    "ax[0,2].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "ax[1,2].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "#ax[2,1].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "\n",
+    "#First all the ensemble ones\n",
+    "n_lines = len(nens_list)\n",
+    "for i in range(n_lines):\n",
+    "    nens = nens_list[i]\n",
+    "    linewidth=2\n",
+    "#     if nens==32: linewidth=4\n",
+    "    ax[1,0].plot(L2_ensemble_limit(quad ,nens,dt=0,alpha=alpha_list[2]),alpha=0.8,          color=plt.cm.cool(i/(n_lines-1)),label=str(nens),linewidth=linewidth)\n",
+    "    ax[1,1].plot(L2_ensemble_limit(quad ,nens,dt=1,alpha=alpha_list[2]),alpha=0.8,          color=plt.cm.cool(i/(n_lines-1)),label=str(nens),linewidth=linewidth)\n",
+    "    ax[1,2].plot(L2_ensemble_limit(quad2,nens,dt=1,alpha=alpha_list[2]),alpha=0.8,          color=plt.cm.cool(i/(n_lines-1)),label=str(nens),linewidth=linewidth)\n",
+    "\n",
+    "\n",
+    "n_lines = len(alpha_list)\n",
+    "for i in range(n_lines):\n",
+    "    linewidth=2\n",
+    "    if alpha_list[i]==0.1: linewidth=4\n",
+    "    ax[0,0].plot(L2_ensemble_limit(quad ,32,dt=0,alpha=alpha_list[i]),alpha=0.8,color=plt.cm.rainbow_r((i)/(n_lines+5)),label=str(alpha_list[i]),linewidth=linewidth)\n",
+    "    ax[0,1].plot(L2_ensemble_limit(quad ,32,dt=1,alpha=alpha_list[i]),alpha=0.8,color=plt.cm.rainbow_r((i)/(n_lines+5)),label=str(alpha_list[i]),linewidth=linewidth)\n",
+    "    ax[0,2].plot(L2_ensemble_limit(quad2,32,dt=1,alpha=alpha_list[i]),alpha=0.8,color=plt.cm.rainbow_r((i)/(n_lines+5)),label=str(alpha_list[i]),linewidth=linewidth)\n",
+    "\n",
+    "ax[0,1].set_ylim(-0.8,1.8)\n",
+    "\n",
+    "ax[0,1].set_xlim(0.,300)\n",
+    "ax[0,1].set_xticks(50*np.arange(0,6));\n",
+    "plt.subplots_adjust(hspace=0.1,wspace=0.1)\n",
+    "\n",
+    "\n",
+    "ax[1,2].legend(title=r'$n_{ens}$',ncol=1,bbox_to_anchor=(1., 0.8),loc='upper left')\n",
+    "ax[0,2].legend(title=r'$\\alpha$' ,ncol=1,bbox_to_anchor=(1., 0.8),loc='upper left')\n",
+    "ax[1,0].set_xlabel(r'$x_i$',size=13)\n",
+    "ax[1,1].set_xlabel(r'$x_i$',size=13)\n",
+    "ax[1,2].set_xlabel(r'$x_i$',size=13)\n",
+    "ax[0,0].set_ylabel(r'$\\frac{\\partial j}{\\partial x_i}$',rotation=0,size=17,labelpad=10)\n",
+    "ax[1,0].set_ylabel(r'$\\frac{\\partial j}{\\partial x_i}$',rotation=0,size=17,labelpad=10)\n",
+    "\n",
+    "ax[0,0].set_title('lead time: 0 s')\n",
+    "ax[0,1].set_title('lead time: '+str(da_const_6['dt']) +' s')\n",
+    "ax[0,2].set_title('lead time: '+str(da_const_62['dt'])+' s')\n",
+    "label_axes_abcd(fig)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def var_ensemble_limit(quad,t,nens,dt=0,response_func = sum_mid_tri):\n",
+    "    \"\"\"\n",
+    "    Looking into the cov(dJ,dX)/var(dX) simplification\n",
+    "    \"\"\"\n",
+    "    X =quad['bg'][:,:nens]\n",
+    "    dX =  X.T - np.mean(X,axis=1)\n",
+    "    dX = dX.T\n",
+    "    J = np.zeros(nens)\n",
+    "    if dt == 0:\n",
+    "        X_J =quad['bg'][:,:nens]\n",
+    "    else:    \n",
+    "        X_J =quad['bf'][:,:nens]\n",
+    "    dX_J =  X_J.T - np.mean(X_J,axis=1)\n",
+    "    dX_J = dX_J.T\n",
+    "    for i in range(nens):\n",
+    "        J[i] = response_func(X_J[:,i])\n",
+    "        #J[i] = sum_triangle(X_J[:,i])\n",
+    "        \n",
+    "    dJ = J-np.mean(J)\n",
+    "    cov_dJdX = np.dot(dJ,dX.T)/(nens-1)\n",
+    "    return cov_dJdX/np.var(dX,axis=1,ddof=1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x216 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Looking into the var simplification that we know doesn't work, but might be worth showing anyway \n",
+    "fig,ax = plt.subplots(1,3,sharex='all',sharey='all',figsize=(8,3))\n",
+    "#nens_list = [2**3,2**5,2**7,2**9]\n",
+    "nens_list = [2**5,2**7,2**9]\n",
+    "n_lines = len(nens_list)\n",
+    "for i in range(n_lines):\n",
+    "    nens = nens_list[i]\n",
+    "    ax[0].plot(var_ensemble_limit(quad,20,nens,dt=0),alpha=0.8,color=plt.cm.cool(i/(n_lines-1)),label=str(nens))\n",
+    "    ax[1].plot(var_ensemble_limit(quad,20,nens,dt=1),alpha=0.8,color=plt.cm.cool(i/(n_lines-1)),label=str(nens))\n",
+    "    ax[2].plot(var_ensemble_limit(quad2,20,nens,dt=1),alpha=0.8,color=plt.cm.cool(i/(n_lines-1)),label=str(nens))\n",
+    "\n",
+    "x_advected = np.array([0,99,100,199,200,299])-da_const_6['dt']*m_const['u_ref']/m_const['dx']\n",
+    "x_advected[-1] = 299\n",
+    "ax[1].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "x_advected = np.array([0,99,100,199,200,299])-da_const_62['dt']*m_const['u_ref']/m_const['dx']\n",
+    "x_advected[-1] = 299\n",
+    "ax[2].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "\n",
+    "plt.subplots_adjust(hspace=0.1,wspace=0.1)\n",
+    "ax[0].set_xlim(0.,300)\n",
+    "ax[0].set_xticks(50*np.arange(0,6));\n",
+    "\n",
+    "ax[0].plot([0,99,100,199,200,299],[0,0,1,1,0,0],'k--',label='ref')\n",
+    "# ax[0].legend(title=r'$n_{ens}$',ncol=3,bbox_to_anchor=(0,1.0),loc='lower left')\n",
+    "ax[2].legend(title=r'$\\alpha$' ,ncol=1,bbox_to_anchor=(1., 0.8),loc='upper left')\n",
+    "ax[0].set_xlabel(r'$x_i$',size=15)\n",
+    "ax[1].set_xlabel(r'$x_i$',size=15)\n",
+    "ax[2].set_xlabel(r'$x_i$',size=15)\n",
+    "ax[0].set_title('lead time: 0 s')\n",
+    "ax[1].set_title('lead time: '+str(da_const_6['dt']) +' s')\n",
+    "ax[2].set_title('lead time: '+str(da_const_62['dt'])+' s')\n",
+    "ax[0].set_ylabel(r'$\\frac{\\partial j}{\\partial x_i}$',rotation=0,size=20,labelpad=20)\n",
+    "ax[0].set_xlim(0.,300)\n",
+    "#plt.xticks(32*np.arange(9));\n",
+    "ax[0].set_ylim(-60,60)\n",
+    "label_axes_abcd(fig)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Now making the localization advection scetch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "Reinitializing to the default values, and calculating the localization matrices\n",
+    "\"\"\"\n",
+    "m_const = set_model_constants_22()\n",
+    "da_const = set_da_constants_22()\n",
+    "L_obs,L_os = localization_matrices_observation_space(m_const,da_const)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 30.0)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# This one has the plus 50 and minus 50 error, and also follows the color scheme of the other plot\n",
+    "o = 2\n",
+    "np.random.seed(2)\n",
+    "u_advect=10\n",
+    "dt = 800\n",
+    "L_adv_mean = semi_lagrangian_advection(L_os[:,o],m_const['dx'],-u_advect,dt)\n",
+    "L_adv_plus = semi_lagrangian_advection(L_os[:,o],m_const['dx'],-u_advect*1.4,dt)\n",
+    "L_adv_minu = semi_lagrangian_advection(L_os[:,o],m_const['dx'],-u_advect*0.6,dt)\n",
+    "L_adv_ens = np.zeros([m_const['nx'],da_const['nens']])\n",
+    "for n in range(da_const['nens']):\n",
+    "    u_ens = np.random.normal(m_const['u_ref'],da_const['u_std_ens'])\n",
+    "    L_adv_ens[:,n] =semi_lagrangian_advection(L_os[:,o],m_const['dx'],-u_ens,dt)  \n",
+    "\n",
+    "    \n",
+    "fig, ax = plt.subplots(1,1,figsize=(8,3))\n",
+    "\n",
+    "\n",
+    "linew = (10-np.abs(60-100)/10)/2\n",
+    "\n",
+    "\n",
+    "\n",
+    "plt.vlines(da_const['obs_loc'][o]/10+0.1,-0.1,1.1,ls='--',color='k',label='obs location')\n",
+    "plt.plot(m_const['x_grid']/1000+0.1,L_os[:,o],lw=3,color='k',label='analysis')\n",
+    "for n in range(da_const['nens']-1):\n",
+    "    plt.plot(m_const['x_grid']/1000+0.1,L_adv_ens[:,n],'grey',alpha=0.2)\n",
+    "plt.plot(m_const['x_grid']/1000+0.1,L_adv_ens[:,n+1],'grey',alpha=0.2,label='ens members')\n",
+    "plt.plot(m_const['x_grid']/1000+0.1,np.mean(L_adv_ens[:,:],axis=1),'grey',lw=3,label='ens mean')\n",
+    "\n",
+    "plt.plot(m_const['x_grid']/1000+0.1,L_adv_minu,lw=linew,color=plt.cm.viridis((2)/(5)))\n",
+    "plt.plot(m_const['x_grid']/1000+0.1,L_adv_mean,lw=5,color=plt.cm.viridis((4)/(5)),label=' $\\overline{u}$ advection')\n",
+    "plt.plot(m_const['x_grid']/1000+0.1,L_adv_plus,lw=linew,color=plt.cm.viridis((2)/(5)),label='$\\overline{u}$ error +- 40%')\n",
+    "   \n",
+    "#plt.plot(m_const['x_grid']/1000,L_adv_mean,lw=3,color='r')\n",
+    "#plt.vlines(da_const['obs_loc'][o]/10+u_advect*dt/1000,-0.1,1.1,ls='--',color='r')\n",
+    "#plt.legend(loc='upper center',ncol=3)\n",
+    "plt.legend(framealpha=1)\n",
+    "ax.set_xlabel('x [km]')\n",
+    "ax.set_ylabel('localization weights')\n",
+    "ax.set_ylim(-0.1,1.1)\n",
+    "ax.set_xlim(0,30)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Localized sensitivity plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def loc_length_sens_comp(loc_lengths,m_const,da_const,quad,nens=32,alpha=0.1):\n",
+    "    \"\"\"\n",
+    "    Calculates the sensitivity with localization.\n",
+    "    Localization is applied both statically and with advected localization.\n",
+    "    I also included sens calculated without regularization, but that is as useless as always\n",
+    "    \"\"\"\n",
+    "    nlen = len(loc_lengths) \n",
+    "    X =quad['bg'][:,:nens]\n",
+    "    dX =  X.T - np.mean(X,axis=1)\n",
+    "    dX = dX.T\n",
+    "    J = np.zeros(nens)\n",
+    "    X_J =quad['bf'][:,:nens]\n",
+    "    dX_J =  X_J.T - np.mean(X_J,axis=1)\n",
+    "    dX_J = dX_J.T\n",
+    "    for i in range(nens):\n",
+    "        J[i] = sum_mid_tri(X_J[:,i])\n",
+    "    dJ = J-np.mean(J)\n",
+    "    cov_dJdX = np.dot(dJ,dX.T)/(nens-1)\n",
+    "    B = np.cov(dX,ddof=1)\n",
+    "    sens_non_loc = L2_regularized_inversion(B,cov_dJdX,alpha=alpha)\n",
+    "    \n",
+    "    dji = dX_J*1\n",
+    "    dji[0:100,:] = 0. \n",
+    "    dji[200:300,:] = 0. \n",
+    "\n",
+    "    da_const_wide = da_const.copy()\n",
+    "    \n",
+    "    sens_loc_mat        =np.zeros([m_const['nx'],nlen]) \n",
+    "    sens_loc_mat_inv    =np.zeros([m_const['nx'],nlen])\n",
+    "    sens_loc_mat_adv    =np.zeros([m_const['nx'],nlen])   \n",
+    "    sens_loc_mat_adv_inv=np.zeros([m_const['nx'],nlen])   \n",
+    "    for n in range(nlen):\n",
+    "        da_const_wide['loc_length'] = loc_lengths[n]\n",
+    "        C = loc_matrix(da_const_wide,m_const)\n",
+    "        sum_loc_cov_djidX=np.sum(C*np.dot(dji,dX.T),axis=0)/(nens-1)\n",
+    "        sens_loc_mat[:,n]     = L2_regularized_inversion(C*B,sum_loc_cov_djidX,alpha=alpha)\n",
+    "        sens_loc_mat_inv[:,n] = np.dot(sum_loc_cov_djidX,np.linalg.inv(C*B))\n",
+    "        \n",
+    "        C_adv = C*1.\n",
+    "        for nn in range(m_const['nx']):\n",
+    "            C_adv[:,nn]     =semi_lagrangian_advection(C[:,nn],m_const['dx'],+m_const['u_ref']     ,da_const['dt'])\n",
+    "        sum_loc_cov_adv_djidX=np.sum(C_adv*np.dot(dji,dX.T),axis=0)/(nens-1)\n",
+    "        sens_loc_mat_adv[:,n]     = L2_regularized_inversion(C*B,sum_loc_cov_adv_djidX,alpha=alpha)\n",
+    "        sens_loc_mat_adv_inv[:,n] = np.dot(sum_loc_cov_djidX,np.linalg.inv(C*B))\n",
+    "\n",
+    "    return sens_loc_mat,sens_loc_mat_inv,sens_loc_mat_adv,sens_loc_mat_adv_inv,sens_non_loc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "loc_lengths= [1000,3333,10000]\n",
+    "t_step=24\n",
+    "truth_idx=20 # Irrelevant for this test\n",
+    "nens = 100\n",
+    "da_const_dt0 = set_da_constants_22(obs_loc=np.arange(25,299,50),nens=512,dt=300)\n",
+    "da_const_dt1 = set_da_constants_22(obs_loc=np.arange(25,299,50),nens=512,dt=600)\n",
+    "da_const_dt2 = set_da_constants_22(obs_loc=np.arange(25,299,50),nens=512,dt=900)\n",
+    "\n",
+    "vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad_dt, dx = vr_reloaded_22(states[0]['bg'][t_step],states[0]['bg'][t_step][:,truth_idx],m_const,da_const_dt0,sat_operator,model_seed=505,obs_seed=55)\n",
+    "_,_,sens_loc_mat_adv0,_,sens_non_loc0 = loc_length_sens_comp(loc_lengths,m_const,da_const_dt0,quad_dt,nens=nens,alpha=0.1)\n",
+    "\n",
+    "vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad_dt, dx = vr_reloaded_22(states[0]['bg'][t_step],states[0]['bg'][t_step][:,truth_idx],m_const,da_const_dt1,sat_operator,model_seed=505,obs_seed=55)\n",
+    "_,_,sens_loc_mat_adv1,_,sens_non_loc1 = loc_length_sens_comp(loc_lengths,m_const,da_const_dt1,quad_dt,nens=nens,alpha=0.1)\n",
+    "\n",
+    "vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad_dt, dx = vr_reloaded_22(states[0]['bg'][t_step],states[0]['bg'][t_step][:,truth_idx],m_const,da_const_dt2,sat_operator,model_seed=505,obs_seed=55)\n",
+    "_,_,sens_loc_mat_adv2,_,sens_non_loc2 = loc_length_sens_comp(loc_lengths,m_const,da_const_dt2,quad_dt,nens=nens,alpha=0.1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n",
+    "def Loc_length_sens(quad,nens,loc_length,dt_adv,alpha=None,dt=0):\n",
+    "    \"\"\"\n",
+    "    Simple function that calculates the sensitivity for a given quad\"\"\"\n",
+    "    X =quad['bg'][:,:nens]\n",
+    "    dX =  X.T - np.mean(X,axis=1)\n",
+    "    dX = dX.T\n",
+    "    J = np.zeros(nens)\n",
+    "    if dt == 0:\n",
+    "        X_J =quad['bg'][:,:nens]\n",
+    "    else:    \n",
+    "        X_J =quad['bf'][:,:nens]\n",
+    "    dX_J =  X_J.T - np.mean(X_J,axis=1)\n",
+    "    dX_J = dX_J.T\n",
+    "    for i in range(nens):\n",
+    "        J[i] = sum_mid_tri(X_J[:,i])\n",
+    "        #J[i] = sum_triangle(X_J[:,i])\n",
+    "    dJ = J-np.mean(J)\n",
+    "    B = np.cov(dX,ddof=1)\n",
+    "    dji = dX_J*1\n",
+    "    dji[0:100,:] = 0. \n",
+    "    dji[200:300,:] = 0. \n",
+    "\n",
+    "    da_const_tmp = set_da_constants_22(loc_length=loc_length,dt=dt_adv)\n",
+    "    m_const_tmp  = set_model_constants_22()\n",
+    "    \n",
+    "    C = loc_matrix(da_const_tmp,m_const)\n",
+    "    C_adv = C*1.\n",
+    "    for nn in range(m_const['nx']):\n",
+    "        C_adv[:,nn]     =semi_lagrangian_advection(C[:,nn],m_const_tmp['dx'],+m_const_tmp['u_ref']     ,da_const_tmp['dt'])\n",
+    "    sum_loc_cov_adv_djidX=np.sum(C_adv*np.dot(dji,dX.T),axis=0)/(nens-1)\n",
+    "    sens_loc     = L2_regularized_inversion(C*B,sum_loc_cov_adv_djidX,alpha=alpha)\n",
+    "    \n",
+    "    return sens_loc\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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LL764XY5r0XFYliuLfZZFixZxxRVXAHDsscdyzjnndPGIujfb3/iatX95DyPQuDaPrKlEfv8/c6O1sGNDF4yue6M1cW0JIbDZutm9a4tuwQQD2k1xJZJSIcm8aYnVUhMIB7O3IZj2glpXsmkwO9SLK2/7iCtd1xvd0Hi9XjZv3twux7boGCxxZbHPsmTJEo455hjOPfdcxo4dyyeffEIoZLm1olG6/Gd+evgdtr2yhK0vL2n0mty8AhpU3pYbv+/k0XV/1q9fz9q1awF49dVXmTBhAklJSV08qia0dymGcMxVUkr8bjB/G8HskbHtBUHt4RpX7ihuwXayXE2cOJGvvvqKoiJVtPWVV17h4YcfbpdjW3QM3ezWysKi/Tj77LO54YYbmDVrFsFgkCOOOIKPPvoIwzCaWRr2d4q+WBv5u3DxTwy+cEr9i/kb1f9DD4JNPyB3burk0XV/Bg8ezBNPPMGOHTvIzs7mwQcf7OohNSdcLby9sgXDwsHlVu49TYeAHxkMRAK7WyRsuYpZXHXjoPawdSqpPuRAOOsD2tuDESNGcNNNN/HrX/8agJycHObMmdMux7boGCxxZbHPMmTIEN56661Gz915551dM5huTvkPWyJ/V67NJ+jxY0syK3cXqNe0Q6ZhbPoBirYjjRBC07tkrN2NiRMn8u6773b1MNqmhZgrYbMrIRCv683nUf87k5TLyuVWcVjeOkhJb33fGGKugL2j1lXYWhe2VkH9+woH7rcDJ598MieffHK7Hc+iY7Fu3y0s9nOklNRuLwHA2SMVDEntNlVpW4aCUFEECOg1GFKzVNp5ZWkrR7TolrToFkywzUy4CKjTdH+6TMuNr23XoDRFh9gX3IINLXhhwrFk4c/IYr/DElcWCROs9bLxmU/Y/b9VXT0Uiz3AqPQS8vixpyWRMW4AALVbzIa8FcVKTKVnI+wOyMpTz5ft7qLRWiRMSwHtCVqHpCkqRNhiExZXsbjCIk2b2xBX4T6I3bgBctj1J1wNMpE7wHJlsXdhuQUtEubHu/8bidWZ4HaSc9jwLh6RRSKEilVgsrtfD1IG5lAI1Gw1e8SVFaj/s1UKuMjqidy2Flm+G8G4No9d/NUGvKt2IA8+2Crf0NVE3IJNln17gnFNYbdgWEiELTextHwJW3Raq3MF9cKvG4urqG7B8PvyW+Jqf8WyXO1FlHyziYKPf1TtFjoRKSVy/XcY/3sJue5bpJRUbyxoFAS97dWlnTomi/YjVKQuhsn9sknqnQWAt7ACAFmqxJUwG/OSabY5KSts87il321m+fX/ovq5b9j+xtftO2iL+Glvt2Ak5kqJirDlRsaSIRer5SosBLtxKYZW3YIByy24v2JZrro5W1cU8/1rCzj59JF8/7t/gpT4y2sYcObhnXJ+KSXyw+eRP36uHi//BHHodArWZQCQN2U0hYt/ouyHLYR8AXRnG1lCFl2GLC8CTzWi95BGz9dbrrJJylOByB5TXGGKq3DvOJGVp4KfY3AL7njzm8jf2177iv6nTbKsV11JS9mCiQaNNwhoB+rdgp4YyjHEbLnq/m7BiBu0oVswHEvm9yGltOb9foglrroxUkr+c7OqOTSwtCBSa2jLf76g/+mTWu7J1Z5j+PZDJaxsDsSBU5A/fIr89kNqVqvYnAFnHU5tfik1mwupWr+LTDNmx6J7ULOtmF0f/MCAI3OwfTgPQkHE9IvQDqwvtRARV32zcfXMBMC7W7UxkeXKQiXCjXnDlqvy1i1X0jAoWbYx8rhuewmeXeW4+2S1y/uyiA9phFTsHEKVTGhIom5Bf9gt2ERcxVLryh+b5UroNiXmg8F269HX7kRxCwrdpoRhKKj+tVWawmKfw3ILdmMKNtdnZAW31FsKvIWVVKzJR3rrMNYsxVi9pN3qqTRElhYgv5gPgDbrcrRjz0FMPBGA/j134eyRSuaBA0kb0QeA6k1WkHN3wgiGWH7dv/j5X4vwvPGvyN2//PJNlQUY3q5UzR13nyxcuaoQoreoEhkyoMqcg+k91P9ppjiqqWi131vtjlKCNV6cOWk4xvcGoOz7n9vx3VnERbDeatXMitJulqs4CokGYiwiqnfvCu3SCJnvRYCziRXObmUM7s9YlqtuTG2l+lHaNYmo9SA1wYDZE9n++tdUfLqUtM+/jvS1ku40tNOvQ/QcuMfnDdb62PzPT+lZ8REpjiDigCMRw1TfNPGLEwh+9SGZPQL0n9ofoWukDlXWjOqNBXt8bov2o/KnfDwF5ThdIVJc1UjNhkhOhepy2LEeBo4BVLYggDMnDd1px5GVgr+sBl9ROfaaShACUjIA8448OU3Nu9pKSM2Meu6qtTsBSB/dl9pMDf+KXVRtsOZHl9FSpiAkFHMlgwEl1jW9/phxZAtKU3C0WYpBN61s3dUt6K2PtxKiia3C4VJCM+ADulGPSYtOwbJcdWOCAdWqJdNc+0rrJMG+edjsBnlVn6oLXM9Bqv5QXRXGq3ORlSVtHtdbXIW/MvoCKEMGy2/8N4GlH5LiqMTn1dhZ0yBGx+aisEDdofbup+5cUwbmAFCXX5boW7XoAMqWK0tRZo4fIcCX1Bsx+jAA5M+qfIYRDGFUe0EInNnqApDUMwMA77YdgISUDCWqwqSYgqq65e+7Zqsq5ZA6JA+9VxoOV4jqTZa46jIiwexR7qcb1pKKNVmmaQFRGgS0x2S5Ml2QsRYR7a7iKhzM7ozS6siyXO3XdCtxVVNTw8yZM8nPz2/22tq1a5k9ezbTp0/njjvuIBjspj+2diQsrtLtasGrCAhKpZ0h43w4nUFCWf3QzrkF7dxbYeBY8NURfHNeq+6a9U8sZNGsB/lsxp/wfNHcTbPtv1/hWb+R4QeopqzrVqTx098+oXKdskSULNtI/np1N+ko/gkpDZJ6qYutp6C8/d68xR5TvVm5aXMGqu+rui4F0X8kALJAffe+0mqQ4MxKQbOp7VymuAruUt85admND5xqugarW/6+a81SDskDchhkrGXKScX0tq/p9ExXC5MWqrMDKnZT0wGJkC2vHY1o6hKE+Prpxdq4WU+w72FnES2YPUwkY9Aqx7A/0m3E1cqVKznnnHPYunVr1Ndvuukm/vjHP/Lhhx8ipeS1117r3AF2AaGgWuhSzPWwOgDP3fAGffoqV+Du0BiE3YERlHz/kQ2fR0Mr2kLd+29EPV7R52vZ8uLnpGf5GXNQKaN2f0LtPx6i6LNP+ew/3/Lc1f9l47x3OejwcnRd8tU6F4t+SkIGQiw8/0n+cNLTfHH/O1SW2fFJF9RUQNGOyMXYU9h6HI5F51KzRQmczF7qZ166w4A8M+HAbGHjK1ZzyZlT33TWlasyBkPFyvokUhsHoQvTFShbE1c7lAU1JcdGbrEq2dG7bzW+zVbcVZfQmluwwfNarBaipsHsUG+FisVSYwa0S93R+na2bp4tGLbSNSzDEMYex+dhsc/RbWKuXnvtNe666y5uvvnmZq/t3LkTr9fL+PHjAZg9ezZ/+9vfOPfcczt5lHvOEUcc0czqdsYZZ3DjjTfi8/mYPHly5Hm/J0CFsxZnaASHMpbSgI/l9rc56nmDkCEIhr7C8excpvf+BUfsTuOLAht/3Pwxks8R9/w5khX0+9//nrPOOovPn/gvc4r/i73CgMg17hPuOGoRR/Tqja+iljsKv0G8DkFDUOW1M9A1jt6BoWTYJcN2bcXtgpAh+GqVxtHj4Ku/vsqIq3+DPcNNoKIOX2kNrgYXaovE+de//sW8efMA8Pv9OBzqQvThhx+SkZHB//3f//Hvf/+72X5ffPEFdpuN/6z8iCVVG0h6xgAp8fqWkPr9Oyy+4HCoLOG+O27lnff/h7+8Br3MjmPiv0lLS+PpX90FwANvvsqyrRvB+Q088E8AevXqxfzbLgfgdw89zjfb6ns1pqam8sorr5CdnR2xYibVbW80tsAPS3ENbVwKwqJ9aHVtqatlynOLlSXo6U8ir1900UVceeWVVAQkJz23GP9Ly3E0CMz+7W9/y8UXX8yuXbs49dRT6w8cDEBtJdefdBRnA5s2beK8c85W1kxNh79/CMAf/vAHZs6cyY8//sivf/3ryByWVWVccEAfDl3+b8Y9+puWs0i7uVswUtPLGUVcWZar/ZpuI64eeOCBFl8rKioiJycn8jgnJ4fCwraLGDZk9erVCY8tFpYvX97ia3PmzCEvL49LL72UoUOHYkSx7ixfvpxgMMjw4fVVziuL6jCKSuhpTwHAE9A5tF8WGckGZSUOvLU6hbsFKb5KDFcab6xIYVz/HNzJIXzCRa0Z3F5dXc27f3mTrEA+Rw3KQAL5xTbw66S7Ddy4yUgxGNrP4LDdWfhtSdRl9eGbH1bgHFLLwEuPpuKRxeS61LgLemQSqrVxNHWkVf/M7495nHNG26ACViz6Gvvg7DY/k/ago4+fCHs6z3744Qeee+45brvtNjweT6P50PAcSUlJzeZLmBUrViDqAuSKZMak9yI3r45QSFCY78I9cCAVznQyKCFd+hiW259gXRl6bgr2Qdm4XC521agMwQFuJ6JvFrXpefjcylqVlpbGxhXbGAoMSHVQYZ6/tLSUlStX8uGHHzK832BCdX6E00bF5pVkAZWBVNLt1Xi2rGFDO39vHTkPuvsci3VtcZTkM6lvFkFHElXZ9eVSgsEgy5cvZwCCSX2zqMgdgtGgyKjX62X58uVUVVU1mmsObzUp5TtJcTlYvnw5xcXFjBg+nMzCjUhNpzxvGADl5eUsX76cXbt2MXbs2Mj+K5Z+wVf5ZYzSq/j63pdIv/ywqO81t7CQ3sDunfkUtPFddMU8yM5fSz+gtMbDjibb9K+uJQvYsn4d5VWtu8O74zyz2DO6jbhqDcMwGqUPJ1KUbezYsTidbfj3E2T58uVMmDChxdfLysrIyspiwoQJPP/8860ea+LEiZG/l7y1ikcufY1D3Sr26oq5sxi9vYSQIXjpzV70coXqz9G3D0OGpONcbeeqGUXYHZKlgcModA1j6QtryEn6gsnHBJkiDuCtdYPwHj0JW0odeYs34F1VxrL8IO7UTO65/RrSjzkCIQRr1qzBZrMxYsQIKkeNZud735M6tCfTf3kI+DyE/nYNw/oE8FV42LXTRm8N+qfn0XvCgW1+JntKRx3f5/PtkUDa03m2a9cutm3bxrBhw5g1axa//e1vgejvt7X3X7V+F6XJQzjzoLGMHLSFiuoUvv04hcPuuJLUypXIos1cM20SJ/Q9iS0vfs6wS45jyCVTAShfuY1lzy3j4rGDyUjJRpt9LWLoePXaiq1suPMJmAxXjR9O0jVzAKioqGDDhg2MGjUKuauapUBynyyyQkqoBXtOgNJFpMmqRuP+cv6PuFKcHHL8iIQ+r46cZ3vDHIt1bZHb3Dx6/AHQfyT62c29A6HvX+fR4w9g7aRzGTv5uKjHOOaYYyJ/G6uXIN9/FjHmUDTzM5p+3LEYj14Bmo5+4zON9p0wYQK9e/dmwoQJVG/Yxc9PXYvdprHjC0FwVQFjBw6PJFQ0xAgVIzcvo2dOD3q38l101TwwAruR66FHn/7kNtnGKFmNLNzIwD69GHxQ5499T+eZxZ6xV4irnj17UlxcHHlcUlJCbm5uF44oPqSUaAkU/Az6lXhKcWkgDUYMlYjtEtvAEZzxxiV8fenfCVbWkXPkSI5/8Dw0m87P325j/dy/MHZCJQcEl/HGM5vplx3gxCkVCAHlfY/itJt/Bagf9dgLj+Xn5xfhL6+h/+xJZIwfGDn/mDFjIn+nj+xD+sg+9YNzuRE5fbAV53PkkWkUr66kd6YV1L6nhAO+E5kvDfEWqSKgadnqeAF7JhCgdkcpaYN6Raqse4vVEuC32Xnxvo9BSqb+chQAdmHG1TQIaN/2xtd4PWpsRmV9tmBGRga/+MUvACjcvQMAd890KF2NRCBGHkzo80XYdS/SW4dwuamt9PDoZf8F4NVdd2F37hXLUbci5rWllYD2hs8LIxT99aZE6lTVuxCFza5cgkYIGQyox1Eo/modY/PSkFLgOWwkxUvWU/TlOvqdfGiL4+quda6itr4JY2UL7tfsFatZnz59cDqdEYX/9ttvN4pN6u4YhpGYuAoYgMRuZvDYSrcAIPqPJKVvD45+8ya8RZUkD8iJWPIGHzqAlSMnUVL4GT3y/DxySVHkeLvLc+l908WNzuHMSmHU9TOjnn/RokUIIZgyZUrU10WfYcjifC789WAe+d1KIET5pvjctRaNaTdxZQaqu1PMwqFpucBO6vJLYYLKGKS8EF+Jio/714OL2Fio0uMXv7aC01IkTqd5QTPFlTQMSr/ZRMirxmbX/QSqPdhTkygsLOTzzz/n6KOPxrO7Qu3WU90U+NyZJA/qQ+17NtIyglC6C/oMpbSgKjLen38sYMSh/fboPe+PxLy2hMVJ076CYczntZjFlVlKwa5iqIxAkNptJbidSapxs9/TopCrWrWFxZ4SpGZn2NEjKF6yntJvNkYXV5Fswe4Zc9V6tqApPK2Yq/2SbpMtGI3LLruMVatUPZ65c+fypz/9iRNOOIG6ujouvPDCLh5d7DR1a8ZKKBjCqYEAbCkuyN8AEEmnt7mdpAzMbXbsficfysqvMykoSAfdhj9gY+2KVOThp8c1jr/+9a888cQTLW/QV8VVJNfm0/sAZdUqXm+Jqz0hWsxMrPg8AR666GUWvboiYrlyOtRFVc9RjZfr8kshI1cVBq0soW63ctuVlPsYN3kwQw/qQ2lBNSTp2GwSaXdG0u3r8ssIVNZhz8ogGNLRdahcoebkhg0buO6669i8eTNeU1ylpqlze1J7kNQznbpadbEN7c7H5wmwa1N9B4Kta6zq/okQ69oiTctVS9akhC1XNgeGP8iy3z7DkvP/hr/GFEEtWGuklNRu2sHfvtnMvOU/02OiWkNKv92sOgI0pbv3Foy0volS5yqe7EmLfY5uZ7n69NNPI38/80y9337kyJG8/vrrXTGkPeaQQw5h8ODBce8X9IdwmQWKk7JcULpVmd17Dmp1v8yDBpHUN4fVX5VQcOhYSr/dhLNHGqOnj4/r/JqmtVqXSPQeggTYvZVhR5yE/7XtFK7fzYrPNoGVMJgQOTk5HHXUUbjdUdwMbbDo1RV8veAnvl7wE3f/7kCg3rVn79cX+I66HaWqIGh6DlQUme1tbAw+bDC3vHohJfmVXD3xrwRRd+SGMw2befEO181KHdKTkL4LGzV4t2yHow6MWE+klHh2K9dwxe5Cerjh60UVbPnmLWbobsCDf8cO7v/Dv1i3rD6T0O/tpm6fbk7Ma0trRUQbPK8ZMYqYSBFQJzvf/57K1coV7KsO4sgAfNEFhb+sBqO2Dk0IEBruvtkk9cnCs7OMynU7yRjTxHrZ3dvfmPW+RDTLld3KFtyf6daWq32Fv/zlL1x77bVx7xcKGhFxlZ5n3p3m9G357tNECBEJTi79djMgGHTeUWiO+LS0EKL1oo/pPVQKcl0VBxylLFduHR684CVCAaveVSIceeSRvPLKK/Tu3Tvufct317vZVP0qiR5UTZldgwcCULfTjJPKygMgLTVIUMI1/zgLm12n56AsppxxIJpTWTCCev1Fo2azskqmDslDulTwcWDnLoCI9cQwDGp3KnFVvl299vPPAT575Qe27VAXyDULvmkkrABrviRIzGtLjHWuYrZchZs82xwUfPwjAO5+2QSD5jrVgrWmdlsxus1AAIY5Z7IPVaU5Sr/b3Gx7Yda5kt3dchU15sqs4WWJq/0SS1x1Y4KBEEmmuErNMM36eQNa2aOeXscfyJBLp5LUK5P+p09iwJmHx33+tsSVEAJy+wOQkaQsHUk2VZ+rNL8m7vNZ7BnhXpQAVdtLcLoMVXE7KQVXrx4Iu46/rIZArZf1m9R8cqcEsWW5ScuqF1EnXT4JR5ISO/5AfeZj2HKVMrQnWrqqSxQsUYkmYcuVr85P2Ua1XVammjsjZo3h0BNGsrtCXSizkptbIYL+bnrx3FcIthFzFS4iGrPlSgkGwxCUr9gKmuCAP5xOyBRXsoUq7TVbi9FtEk0IJKa4OkSJq7Jvm4ur7u8WbLnOlTB7NsruWl3eokOxxFUncOqpp3LvvffGvZ9yC6oLVEqyeeHM6x/TvkIIhl12HFPevInRN/4Socf/VQsh2owBEuZ49MoCNIcNuwY2ISnZXh33+SxgwYIFTJo0iZ07d8a9b3F+ZeTvml0VuJJMK0RaNkLXcPdWtar+ee0bLPpICaDk1CD2vJRGxxlyYG8ycpSqL95Vf9ddbVqukgfmkl+s5mWwrJS6Km/EcvXiPQtxSANDwsCB6uLSe9JgbvvPeQw9XqWbZ6Y1t46EWz1ZxEfMa0sb2YJCD1uuYrQgmm7B6u3lyJBBxtj+ZBzQH0Oo4/iLSqPuVru1CJtNzR0jLK4mKLdm+apthHxNhEhYDHbXgHZfKwHtkZ6N/s4bj0W3odvFXO2L7Ny5k4EDB8a9XyjYIOZKVz3gYrVctQcPPfRQ273gzPHIou04slLw7q4gSYfKwhj6i1k0o7a2lh07diTUgy8ctySQOHVwmuJq2eeFLJz/HKMqPGQC6z5eS0ZvZZFyp4TQo9x19+qvgnELtngYBoS8fjNeS+PVp7/F9lM+g48Flz3A9b94lENPH8vU3IsJbArCQEjqmYru2Q1Cw+9U4m3YjImw8GNSk0NoQmLI+kDsoOUWTIiY15aYSzHEJmKkKa6qtig3c49JwxBCoKelAbXUbdmFK4qxvGZrMXZd8uCxY2DwOAAcmSmkDutF9cYCKlZtj1iygAaWq+5n/ZFSNsgWbM0t2L3GHggEyM/Px+u1Au33BJfLRd++fbHbo/+mLHHVCSSaLRgMGKZbUOKQpiUoO/5YnESJZdEWef1VUHvhNpxZg5S4soHf003vNLs5YUthQvPFrIvmNAW53XTtlVTrrP5yC2k5BpkZ0L9PMrP/Nhs++zPulCCaaH5hyMoSUAPVxQF2rCsiTfpBSrSsND7893KOHKsWFKcrhK2mjvfnfQtoHDQiB4wysgaa1rDUTDBdhsmDe+PzajhdBi+uuZpzR/9f/dgty1VCxLy2tBVzFQlojzXmSlk0a7er+LpwILq9RxbUFuDdET1ruHZrMdluycAMN6JPr8jz2YcMoXpjAaXfbmpBXHXD9cTvBWmA3aGSRJpiugW7m+UqPz+f1NRUBg4cmNA6Y6GEdWlpKfn5+QwaFD3BzHILdgKJFhENW66SkkMIDEjNRERL+e0gPv74YxYsWND6Rlm91CJSVUpSlrKGJOmWuEqUsMUqsdIdSky5IuJKXSjThwzgrFuOYfR0VRR22imj6HfIcEJSx+GUODOaXxjsIRWoK30aH/7r24hLcMsudad+yGzVScCZZHDu1ZOYdtk4hp1h47iLVYuU1BzzIp7eo/6YKS58fvP53Tv53d9PZ9A4dYENC0OL+Ii7iGgbMVexWq4augUB0swCw448VRMtUFLWbBfDG8BbVInNKfjk5yLeW7E+8lqPw9S82f2/VY2ttpEiot1wPYn0FYziEoRuK668Xi/Z2dmWsNoDhBBkZ2e3av2zxFUnkEi7HqiPuUpONReWrJ7tPLLW+fe//x1pHNwSQtMgRy2saVnq4u7WpSWuEqQ9LFcu81edmatE0+SLj+asm6dyyBkHAypjUAiB12eK4ZTGwkaGgghPFVKCHtD55F/fsHOZCjbeXRlk9GEDOOK8IwBwuAx6pNqYdNZQXnz3aTauVxdMd4Y6lmggrgBCurKS+XbsYsoZBzLtgkPU2C3LVULEvLbE6BaMvYioslwFPCGSemfiSFffq7OX6gFrVFdjBBqvAaFCM3M1K4kXftzBvA8WR17LnjAYZ04adfllVKxqkElqNp+nOwaFt5YpCA1irrrf2C1htee09Rla4qoTOOaYYxo1LY2VYMDAoUGyefETWb3a2KP9iaWopehhlmEws8CSbBDwWhfLROjXrx8nnngiLper7Y2bEDQvZmHLVXKK+d2ZFdbdfVSGX7gcQ2212tDtbJIqXlMBSPx+GwKBixBr3l6h9rU7ufbJ09DS1LGcrhB1O0oiC42vzLyANgimb4RbFUAL7FYB9TaHGkPIElcJEfPa0qZbMN4iosoaYwQF6aPq22JpKcodrOsGNVuKGu0SMkuFJGU5EaI+oB1A6Bq9zTp8W1/6sn6n7my58prtoVoSV/buabmy6BwscdUJPPLII1x00UVx7xcKhnBo4A5brrI7V1y1WecqjCn6XHZlJnfp4Pd2w8VwL2DKlCn84x//IDMzM+59w5arC29XDXYduimaTIGT1DsThMC7u4KQ109NqfpukzRP4wNVqUyvgFQu6DFjc8g2KzKc+8hscvtnIhxOpM2JroOvoCgirrylKjbQaTfP3cRyJcwSDkZZCQA2u95o7BbxEfPaEs62a7MUQ3x1rkIhQdqIBj1HHWrO6DZJ1YaCxrvsVnPDkeZA9Z1ofOc/4MzD0Jx2ChetYfUD85VQ784xV75wdfaW3ILd13LV3bnjjjtYunQpAHfeeWekAXXD56NRWFjI2WefDcCOHTu45pprOn6wLWCJq25M0B/CrkGy2R9OdLJbsK0K7WFEDxVk78C8sGoQsNyCnU7EtVbnQ7cZ6CKgLk5uVfBTd9px5aQhQwal32ymzrRcOT2VjY4jq5Rly3ApK9NJxw/EqYM9w80BJ9Y38yYlQ21X2sByZYorm6EuPE3dgrYc1XBd1qhz2uxqCQpYlqsORYbaaH9jiph4LVehkKDa5uTjF75j1ec/I01rjc1mULWucTmRsOWqqrwGTUBdjY/i/IrI667cdMbeMRth08l/9zs+P30uZStMF2F3zBY03YLC1UIcbDjmKmBZruLlgQce4PDDVbrp0qVLI9ehhs9HIy8vj1deeQWAXbt2sWXLlo4fbAtY4qoTOOqoo3jggQfi3i8UDOHQwZVsLngZOe08staJpc4VELGo2f0quNWlS/we62KZCC+//DJjx46lrKx5QHBbBEzrj1HnbVzjqkFsQOpQJdB3ffgDtTWmuKqraHwg03KlZar5tvO979WhhvdudCyRpqxrNs1HoEJdaPzVHjSHDc1TETl/Qxx9lBDX/Gr7sOXKcgsmRsxrS8wxV/EVEQ2FBH/63QLmXfc2d536T564YaF5uMaWq/wNxZT9qNyExTvLVWvLMg/XHvY3Pnv5h8h2vY8/kCNeuJoek4YTqvPz4wNvqRe6o+Uq4hZsO6A9kdIq3ZFgMMhdd93FrFmzmD17Ntdeey21teq3/P3333Puuedy6qmnctppp/HZZ58BMH/+fH77299y1VVXMXPmTE4//XQ2b1YxnB999BGnnnoqs2fP5owzzuDbb78F4IILLmDhwoU89thjFBUVceONN7Jy5crI848++ij33XdfZFyLFy/mjDPOID8/n4MOOohQKMSdd97J9u3bufTSS5k3bx433HBDZPvvvvuOU045pUM/K0tcdQJlZWV4PJ62N2xCKBDCoUmcLlPgpMTvKtoT/vznP/P888+3vWFaD7A50Pw12GwGTsstmDAej4fy8vKE9g1broxaLy5343irMKnDlRDe/b/V1NUoa4XTU9F48a9ULjvVjxAMs7BjxgGNC9gK03LldBn0cWby0UtvMcbVC3evDBW3JYQqxdAAR18lruyaj6DHj81syWQFtCdGzGtLzNmC0b8Hj2llKtlZScGmIjBCGAZUeMGR7ubI2QeQ3TuNresr1GlskuqNBfi9fub/9XNuPPr/cMsQUkLugDT+NHUMv51yDr66AE9c8ybffLA2cq6UQXlMeOwiMg8aiL/CfG/BYPcTKJGmzdFjroSm1Qfkd0dxmAArVqzgm2++4Z133mH+/Pn069eP9evXU1lZyW233cZDDz3Em2++yZNPPsndd9/Nrl2qBda3337LH/7wBxYsWMCBBx7I008/DahainfddRfz58/nd7/7HcuWLWt0vuuvv57c3Fzmzp3LgQceGHn+jDPO4L333sPvV1bBN998kzPPPDPyuq7r3H///fTv359nn32WM888k0WLFlFRUQHAa6+9FnEfdhRWnatOINFsQQIhnC5DlQlKTmuzp2B7k5ubG9N2QtNUJmPRdpJTg7g8Dvx1+8Zi0tm0R7ZgqNZLsttMgjADz8M0FEjBgIZhS0IPepQYMoWQLFPB5q4Rw3HmbDD7FELuUaManzA5A1BB7YHd1WSnJbFDs5PePxmkVKVDmtT/0dKzMFBZhrVbitBNt6AVc5UYMa8tkYD26Eu+0O1ImsdcFW0v5+83vMPKzzZHxE2Sw+Df14MREug9s/m/T64kNcuN3xvgnT+9DbyPZjMIefzccNDD7CzykmGXaAJcPTPoOygIO51ccf+ZZI3dySsPfsoTV7/JY1/0Ibu3ckULIRh4zpH88MNWpAQhpKopJfREP6r2x9dKAdEwNgf4PSpGrZPX745g+PDh6LrOGWecwZFHHsn06dMZN24cixcvpri4mKuuuiqyrRCC9Wb28JgxY+jZU1nNR48ezccffwzAjBkzuPrqq5kyZQpHHHEEl112WUzj6NevHyNGjODTTz/lsMMO4+uvv+aBBx5o8cY0Ozubo48+mrfffptTTjmFL7/8krvuumtPPoo2sSxXnUCi4koEAvXundSs1jfuABYuXMhLL70U07bCLG6anBbEpVnZgokSvoAlVBfNrHIerPbgcofdgo1jnrInDGn0WPQwkyTKGxR9NMWVyO7FiKtPQNh1+sw4mLQRTQrYNrBcFazfytMv/pOCQCWpPU13SNNMQQB3KlKCw2lQuXZHfUC7ZblKiLhLMbRhuaLGQ/VG5c4r2lHBrSc8zYpPNyE0QVavNLJ6ppLXW7nBQiHBhPMmkpqlxIXDZee0W6arw5kazlVXR9/hOVx22xQAUgfnQcDHh5sLeem9DznjxqM5eNpwaio8/N/v3mxkneoxcRi6y05Y7/38/XYeOOcFtq+LXqC00/G20vomTLh69z4Sd5WWlsbbb7/NLbfcgq7rXHfddfznP/8hFAoxZMgQ3n777ci/V199lSOPPBKgUfZzw0Sp66+/npdeeomxY8cyf/58zjvvvJjHcuaZZ/LWW2+xYMECjjvuOJKTW/kegPPOO4833niDBQsWcPzxx7e5/Z5iiatOINEK7SIUwhl273SBuHrzzTcj5ts2MeOuktNUnJgRtC6WibBHlitToASrPA1irhrPG91lZ/QtJ2NLdjLy+ploOUowyRIVfCy9dVBXpe64UzPpPX08x338R8beeVrzMaWkA8pytXP9Fp5a+Ar5gXKSM9WyIqKIK6HbMHQXQkDdui2RUgxW+5vEiHltaSvmyrQwhraUsOSCx/npL+/x8MWvUFFYw+jDB/KPNTfxj9U38Y81N/PIJ79W24ZEpDJ7BIe6iDqcEpCcdenB/HXpNWQ71MU0dVgv8Pt4a30Bz/znVYQQXPmXU0jJTGLFp5v48J/f1g/JaSfjwIEYhnp/bz76Kcs/2sB1RzwR46fTsUQC2ltwCwIN4q66X0B+Inz22WdcfPHFHHTQQVxzzTWccsoprF69mvHjx7Nt27ZIzNTatWuZPn06hYUtC+FgMMjUqVPxeDycc8453HXXXaxfvz7i6guj6zrBKL0lp02bxpo1a3jttdcauQQb7hdo0Hro4IMPRtM0nn322Q53CYLlFuwUTj75ZMaPHx/3flowhCslununM4g5oB2VySiBlAy1iNpC1sUyEYYPH87pp5/eYr+qlpBSRlxrgSoPriHhedNc4PQ/dSL9fnkoQtcwlptxI4VmVlaZGYSclYcQSiTprhaa/aZkIDFdfGuKATCQuDMElNBM2EVwp0ONF8+2HaRYpRj2iJjXlnDMTwviqnpLKcmApkvQBNtfWYJeKMjuncFtL55Lcnp9RlyophaBcgumjWxszRQ2O+g2RCiIpoEsrkQIQdV6FXuTNqI3rPUiEBimkSqrZyq/eeSXzL3kVZ6/ayGjDx9Ar8HZ/Lj4Z5Z9s4sxJwpA8tOXm4G9zS24bzVvnjx5Mp9//jkzZ87E7XaTnp7OfffdR1ZWFn/729946KGH8Pl8SCl56KGH6Nu3L998803UY9lsNm6//XZuvPFGbDYbQgjmzJmDw+FotN20adO46aabuPvuuxs973A4OOmkk1i6dCnjxo1rdvyhQ4fidDo5/fTT+e9//4sQgtmzZ/P+++8zcuTIdvtMWsISV53AQw89lNB+IhjsUrdgzHWuADJVfJbbFIN2aSQea7Yfc8wxx3DMMcfEvZ8RUp+3rgvTLRg9oD2M0E3rUu4AJKrxNtTHW4nMGMp+mG5Bl1sSqKhv1O10mHeLTVySYbSsbKgpJFRSjGbOr2DAitFLhJjXljbcggWL1zE0GWyZLoZeO4NNf1nA4TmSrGsnNxJWALWbd5ICYHOguxzND+ZwgacG3W5QtWEXUkqq1ivLaNqI3rDShxDQcGU5/OSxTD59LZ+//iO3THsKm12nttLLwGRJ+P7Orne3gPYY3IL7mOVK1/UWY5UmTZrEf//732bPz549m9mzZ0d9fNxxx3Hcccc12+eFF16I/H3zzTdz8803A0TcjGFuu+22Ro/79u3LDz+o7NOMjAzeeeedyGvBYJClS5dy4YUXtvoe2wvLLdiN0YKh+tiZLhBXsda5AiBDiSuX0w9IXJpljehMwp+126khhMTlCs+bNjJMc023TslOZCgIJcrCEFPB2nBAe1J9rW1Xr0yEWdohmtUMQDNLODgdQYK7VcmJkOUW7FhacQsa/iCl329VLyfrLF1XzZYacGiQ9MO6ZmtA1U/bANDcLVhszP6nSZkuApV1VK7Jx19ei0iy4+qVDgEfGo3FFcAVc3/J4SePwVcXoLbSS3bvNIp9ykIGYLfV79EtMgfban8D+5zlam9l06ZNHHbYYWRmZnLCCSd0yjnbVVwdd9xx/Pzzz+15yH2CUaNG8eCDD8a9nxYK4UoyY3C6yC0Y6yImnEmQnIamSVxJqhyDJa7i5+9//zuDBg2Ku3RHON4q2aHhdBkIDUhObzPDVDiT8CWlKbdR6S5kgSq6J3oObPOcwuEERxKaMLDZ1TzJOKBfpE5Wi27BZBWr5XAa+PNLGo3fIj5iXltaaX9TvmobQbMunZQG7/9jGUuKNDSXg+Il69n9v1WNtq9Zq8SVLTMt+rnMuKu0wUpcb3ttidq+XwbCFHlC05utLUmpTm549iweWXQlf/74Cp7+8Ub+mX83hnmZSnXUbx9uUt6l+MzfaGsxV3aztcE+YrnaWxk6dCjffvstf/rTnxJKFkqEdnULfvLJJ+15uH0Gr9eb0J2WZnSt5WrOnDlRAwlbJDMPaqtISgni0m0E/EGScHbcAPdBAoEAfr8/7gUgXEA02SkaZApGtxw1pTYtD6enCrn1J9htVjTuOSi2E6dmQKmHIy87jrfrjmfUxcfBMze2fv5IILxB5c8q4NUS4okRy9oipVEfc6U3X/IrftwesQ4Fanz4PQHGnziKkacN5ac/v83aR94l+9ChONLd+Mtr8BaUQD+wZ2dEP6HZAidtUBYs3U3BRz+qp0fnRYqP3n/iIchL7m+2qxCCQQfUW01tdhuawwEEyHTVv8+ANxjJNO0KZDCgrFGaXi+gomFZrvZb4pZw69atY9asWZx00km8+uqrHTGmfY5Yg8KbYpchHE4DKYlckDqTtLQ0srJiF3XCdA26k0O4dAj4rAtmvCSaLRh2qyXZ68VVrNbO6mxV+0ouek1d/Hr0QcQ639JVFfcBRw3gkGtOwa0Z6kLidCtrZjTClitXiLrNKoDesBIgEiKmtSVYL6yizauq9bsicU0EAmia4Jw7jqPfyYeSOX4g/vJa1j/xAQAFH/+IpqmNtZbavpiWq+yD+tY/pwmcB/cFvxJXaakpMa8twmyp0yO1/nLl93VxjF6DYPbWfqvCjLmS3bwUw7Jly5g5c2a7HOvWW2/l2WefbZdjNeWJJ56IGHFiPc/jjz/OpEmT+M1vftPstYULF3LBBRe0uG9BQQEnn3wyY8eOZdWqVS1uF424xVXfvn15/vnnefTRR/nLX/7Cjz+qu5I333yTyy+/PN7D7RdIKRMyRabaVeBngCSE1vl3ae+//z7z5s2LfYdIUHsQp2a5ehIh0TpX4c86ySYatb6JhaoeAxu5i8TwCTGfV5jfecXObTz44IP8uEy5gEhv+dzCFFfOJIl3Zyl2TWIY3SCGZi8kprWlFZcgmOIqHNekS6aedzADRuUhNI0xt56CsOvsfHc529/4mi0vflFv/LJFCWYHhCmukrJcDLl0KrrbyYirTkDPToaAF4APNu6OeW3RXMoyNHXWcLJ6KVdkoKvFVTiYvTWXIFjNm9uZZcuWxedNMTnppJP4+9//Hvd+vXr14u233465oHZD4nYLpqSkAJCVlcWJJ57I559/zrhx49iwYQPDhg2LewD7A4ZhJCSuUpzqbsevJ9PCPWKH8sknn/DFF1/w29/+NrYdMvMAlTGoLFdWBli8JCyu/OqzdunE7RYM2V2IiTOQS95SVdUPPjb2E5uWq5rd+Tz++OP0//1vGAsIcy5Exa0ukK4UlTKW64Sq7hBDsxcS09oSbLkMQ6DKg6egHM0st+GwSU7//ZTI6ykDcxl66bFs/PtH/PSwyrxKHpYKVIE9urgKB7Tj8zDssuMYdpnKBitbvjxiufrfxp18ufi5mNYWLckFfvAXV+BwqUtWl7fXiiWYHRr1F9xbqK6u5p577mHdunUIITjqqKP4/e9/j81mY+XKldx///14PB7sdjs333wzhx12WIvH2rx5Mw888AAVFRWEQiEuuOACTj/9dJYtW8Zjjz1Gv3792LhxI8FgkHvuuYcJEyZQVlbGbbfdxvbt28nIyCAnJ4dhw4aRlZXF6tWreeihh9B1ZWz44YcfOPvssykpKWHYsGE88sgjuFtKtDD561//yrvvvktGRgYDBgwA1O/oV7/6FWPGjOHmm29m6dKl3HrrrcyfP58ePaJnPbdF3Ff8t956i3POOYc//vGPOByOSMGvjRs3Mnz48IQGsa9z8cUXJ1TnKi1J3e0EbSntPKLYiKfOFYDIMMVVcginLgn4LXEVLwceeCAXX3xx3G7BoClOnJokyd1yjauWEIfPQrvobrRL7ke4U2PfL9xMvEpl/cnqCvU4u3f0HSDi4nY41PzIcUnLLZggMa0toZbLMFRtUNmhPlMk2HTI6dfYJTz4oimMuPoEkgf0IOeIkfSZPla90FKskRlzhd/b/DUz5kroesxri+ZWx/OXVmJ3KnHV5WuLb9+1XN1///1kZGTw7rvv8sYbb7B+/Xqee+45AoEAV111FVdddRULFizgvvvuY86cOS1+j8FgkGuvvZYbbriB+fPn8+KLL/Lcc8+xYsUKAH788UcuueQS3nrrLWbPns1jjz0WOf/QoUP54IMP+Otf/8r336vG8eeddx5jx47l5ptvZtq0aQAUFhbyz3/+kw8//JDCwkI++uijVt/bJ598wkcffcRbb73FK6+8Qk1NDaBuZh9++GHefvttPvnkE2699VYeeeSRhIUVxGm52rhxI3PnzuXVV19lx44dXHnllZH6E5a4apn7728euBkLyS4lXEPOFrJyOpi4rW2mi0gFtEuCVsxV3EydOpWpU6fGvV9YnDjNbE2g5Wy9KAghIK9/2xs2xRRXWrUSV0Z1BbhpXVw5kkC3oYWC6LpBrktjXZUlrhIhprWllTIMNVuLANi6sw5/EBw2lKWrgVVKCMGg8ycz6PzJABiL/qvKKLRkuTLdgvijZLyagqtpz8nWsCUrAROsrMHpUDdwgS62XEnTLShaq3EF9Z9RN4+5asjnn3/Oyy+/jBACh8PB2WefzfPPP88RRxyBpmkcffTRAIwdO5Z33323xeNs3bqV7du3c/vtt0ee83q9/PTTTwwZMoTevXszapTqVzp69GjefPNNABYvXhz5Ozc3t9XSCccddxxJSUp8Dxs2jLKyslbf21dffcW0adMiHrjTTjstUlMrNzeX++67jyuvvJJrrrmGQw89tNVjtUVc4mrJkiVMnTqVPn36kJeXh9vtZvLkyVRXV1NSUsKQIUPaPsh+hpSSQCCArusRU2asJJuxM0F3RgeMrG3itlw5k5DOZHRfLRnJhhVzlQDBYBApZdwV2g3TcuXAiNstuEeYbkFqVMNUo6YC8tIRrdTJEkKooPaqUhwug1yfhlFhxVzFS8xrSyviqm6HKptR5jGQwgYElaWrJeEE9S6uFmKucIbFVXPLlTQtV5oWu+VKOBxIQGCQHG7V19UhBzG7Bfe+bMGmLZUMwyAYDKLrejOL+oYNGxg8eDC2KA3BQ6EQqampvP3225HnSkpKSE1NZcWKFS32G7TZbI0yYFu7yW943lhLBzXcpunvZtOmTfTo0SMSS74nxGWaSE5OjgzsySef5JBDDqF3795s2LCB/v37Nytbb6Em2KBBg/jb3/4W977JSWoBkSltFILsQOItISHNi212erDrF8C9kEceeYTBgwfHvV+47k+yPYTNLpG6vfXK0e2EsDsgLRsh1fllXTUIAVltVHhPNuOu0nXcNnBIS4jHS8xrS2tuwZ+V5aoWHUeqKRTacmGZAqlly1UsbkFb7GuLaeXSNEmKWaW9y2OuYnYL7n0xV0ceeSQvvvgiUkr8fj+vvfYahx9+OIMHD0YIwZIlKmllzZo1XHTRRS2K5EGDBuFyuSLiqqCggJkzZ7J69epWzz9lyhRef/11AMrLy/nkk08ioq6lPoOxMnnyZBYuXEhVVRWGYTQSfj/++CP//ve/eeONN6iurub5559P+DwQp7iaNWsWRUVFzJw5k/Xr13PPPfcAWMHsrZBogDKAOyyuWmgj0tHcf//9fP3113Hto5kWi4z0UNenS++FJJpZGjLdgmlJahGXyZmd13oobwC5bgcbnn2Qc8b0hvScNouXhssxpPdX5vkM3RJX8RLz2hJpfdPYurD4tRVsWbIJgIxhPeu/szbFlSkUWoi5CmcLSl8Ut6D53L2XnBH72mKrF1duXc3zjr5xk7INq1osrW+g3nIV2nvWwjvvvJOysjJmzZrFrFmzGDRoEL/5zW9wOBw8/vjjPPHEE5x88sncddddPP744y0aVRwOB08++SSvv/46s2bN4pJLLuF3v/sdEya0no1822238fPPPzNr1iyuvfZaevfuHbFyTZ06lUcffTTiNoyXKVOmcNppp3HaaadxxhlnkJqq4ktramr4/e9/z5133kleXh4PPvggTz75JD/99FNC54E43YIul4unnnqq2fPr16+P+E4tGpNo3SKAJNMtKLJy2nVMsZKIJVJk5yFRQe211fFVGbcg4X6MYbdgqinI4wlm31NEzwGw8XtcP34Gmobo2/aNlnCnqUbfPd1ALRl2afWijJOY15YW3IJ/++3rXDJU/d3/F4PAlq8etCEEwjWbRItuwVYsV+ZzDncqWgO3UKuYFjdNhyTTwtmR4spYuwz53j8Qh0xDO/rM6BvF6hYMC9puLq4mTpzIggULAMjMzOSRRx6Jut0BBxzAyy+/3OqxGnYMGDlyZKM+gdHO1/Tx+++/z69//WsOOugg/H4/5557bsR4c+GFF0Z6A5566qktnrc1Lr/88qhloxoWQe/fvz/Lli2L6Xgtscd14Gtqavjiiy/2OPhrXyVRy1WothaHUzUtFekZHTCytnnvvff405/+FN9OGfW1rgJVlriKl0QtV0ZIIpAkmxmmIrPzBLkYOJa6QJA/LlrL1/ll0D+GjvOm5So5S104sxxWIdF4iXltaaHOVYoNdAE1ARg+aWC9EGjLchVsyy3YcsxV+Ln3l6+KfW0xxyU0icsUVx1lFZdSIr94E4wQ8puFyOry6NuZFjjRlltQ3/uyBbuaoUOHct9993HKKadw6qmnMmXKFKZMmdL2jq3w/vvvRy0i2hbhIqJFRUVx77tH7W++/fZbrr/+ek455ZQ2TX1t8e677zJv3jyCwSAXXXQR5513XqPXn3jiCd544w3S0lSsxplnntlsm+5IwuKqqBAd8NTp6HEGN7cXX3/9NfPnz2/Webw1REYOEkhKDhGoquu4we2jNA0mjZVQSPVzTHKb1oyMzrNc0XMA/vSe/Gvl/xiYnc7hsRQhNWOunG71+8hySoyQjNadxaIFYl1bZLifX4OYK1+dn7SwNkpPZvwxQ+G/YRfWnrkFI+KqFbfg1z9t5s3Pv45tbWkQc+Uwz91hlqvaSqiov5DKn1cBUVx/HpXCT1LrZXKEzY4E1RTdIiYmTpzI/Pnz2+1411xzDddcc01C+4aLiCbCHi1lhx56KF9++eWeHAJQtSoee+wx5s+fH0n9nDhxIkOHDo1ss3r1ah599FEOOuigPT5fZ6LrOldddVXc4w6VFKEDdXUamtY1rpJ4swWBestVcoiQ5RaMm8MOOywhd2woaODUGhYQ7bw4PSE0tBm/hj/9B8YfE4m5aXWf5HQk4LCri06GHULBUKSOkUXbxLy2RHELFu+oIMWmxNnwo4fjcNkJxWplaSugPeIWbP77l+ZzwmaPfW0xx61pYAuosXWYlbNwe+PHu7dCjzHNt4u4BduIuYrVGmixz9EtVrKlS5cyadIkMjIyAJg+fToLFy7k6quvjmyzevVqnnrqKXbu3Mmhhx7KLbfcgtPZ/ZsCOxyORnU+YsUoLwagtlYnvQvFVdwNp5NSCAQ17HYDUV7ZMQPbhzn22GM59tg4KqSbhIKqKn649U2sfQXbCz1bZQfK1BgzW023oPDX4jfAoYO3tAZXcvf/TXcXYl5booir2iofKebqn5SX0fj1WAPabW0UEfVFcQuaz2m2xLIFbX4fICLZse2NLNmp/ujRB0p2Iou2RRdXMVqu6gPaLXG1v9EtxFVRURE5OfUxIrm5uY3qTNTW1jJq1ChuuukmBgwYwK233sqTTz7J9ddfH/M52kr/3FOWL18e9XnDMKipqcHlcsVlkejx8wb6AtW1OjvWrCZ1d4zBn3HS0rgBiouLCQaDrW4Tjf4eO1mpPoKl+XHvGw8deexE2dN55vV6CQaDkSJ3DWnt/W7csAuXrtyxAKu2FxAoqon5vHv6WdbVKRfw9u3box6r6XOOugpGA77yYqqCKfRwSFZ+9jUpY9so4RCFWMeuB3w4PJV4UnNUuYh2PHZnEp5jsa4tOdu30AcoKi1np/l+tq4sJtlc/Qu9FVQtX86gmlrSgU0b1lFV3nLpgNGeWhzAqrXrCLjym29gGIxHWamWf/ddo8+6rrwUN1BeVR3z2tJjZwF9Ac2poRmSJF2wbcs2li9vfPlqj++qz+Z15AC7U3rRs2QnoaJ8GCWbHXtcXTUasGLdBowoJS7CJJfvYhhQU1HBplbG1x3nmcWe0S3EVdM4k6ZZQ8nJyTzzzDORx5dccgm33357XOJq7NixHWbpWr58eYsxZ5WVlYwePZq77rorrsbWtau+gCqoqtUZf9CBZOS0fwuc1sYNKgjQbrfHHU+3/Y2XAR85bmOPY/Faoq2xJ4rP59sjgbSn8+yPf/wjr732GuvWrWv0fFvv15fvZJ3jK5wuAykFBxw2GRFjnF97fJa1tbXouk6/fv2aHSva8aXfi/HVf3AGvdTKNHoQok9SNkPjHEesY5d1VRj/uhtqKhCH/xLtyFPa7djx0l5zLNa1xQjsRm6E3N596Gm+H1mynnLb5wCMOHQcORNGYOQvQ5ZsZciAAWijWn7foS+fA+CACYe0WKE89OWziICfg8eNjbiJly9fjtum1vUeeT1jXlsMWy1yw+c4U5WATLFB7959Gu3b9LuS29YiC35GHHxsTG7qyLi3qhpOvcdPxChYg+7zoAe8jD/syPpjB3wY/wuBbmP8oRNbjZGUBZkY379JSpKzxffaXeeZxZ7RprgaMWLEHp9k/fr1rb7es2dPvvvuu8jj4uLiRl2od+3axdKlSzn99NMBJb6iVYTtjiQa0C7qKgCoqNbR9T1O6kyIP/zhD/zhD3+Ie79aIxkowy1q239Q+wEJ1bkKGuSlm2nqmhtbAsfYE5KTk9m+fXvbG5oIh0vF7AT8BHR1cfLsLO2o4SG/+xhqKtTf33yAPGRa261Lujlx17lq4Bb0ewOkmA9deemNX9/TgHZQrsGAXwWwNxQ3ZrbgH267lT/O+XPr5wljrvX2JDW+FDutugWlYWC8M0+57qrLEdPOj+08AFUl6v+0bNV9oGg7Tk+T8IYG8VZtJp9Y2YIdwhNPPMEHH3wAqNpV4TZ83Yk2FUpbwqg9OPzww3n88ccpKysjKSmJjz76iPvuuy/yusvl4uGHH2bixIn07duX//znP5HGjd2dROtcab5qACpqdEQXxVwlikcoK5tbtwLa4yXhbMGgQU66Cg4P2WNvvNylJKdDRTHCBQTBsyt62nt7IDd+b/4lIBhAblqBGHtEh52vM4h5bQlnqjUQV95af8Qt6ArHXMUgBGQoCEYIhKYKT7WEw6Uy75qWYwg/jsOahKYGakvSAYMUmyTUWmutwm2RmCi5fW3s5wEIl15IzVS9UqOJq1jjrWCvqXO1N7F06VK+/PJL3nzzTYQQ/PrXv+bjjz/udpogJvPPunXruOmmmwiFQlx00UWcddZZ7TqIvLw8rr/+ei688EICgQCnn34648aN47LLLuPaa6/lgAMO4N577+W3v/0tgUCAgw8+mF/96lftOoaOJl5rhB5UP+DSar3LsgXfe+89Fi1axMMPPxzXfh57BgDJzigBrRatkmghzVDQIDtNXXAMV0Y7j6ptAoEAt9xyCyeeeGLsi5w7DSqK0ZOAavAWdIy4kjWVUFoAdifiiJORi16DrWtgLxdXYWKv0N7AclVRh10DQ9exp5hCJ5aA9vBrdkfr8zRarStpmJmGgvc+/h+LFy+OaW0RNhsS0J1hcVXfkSAasqiBBbW0AOmra7seFaZw9NaqGLGk1EhZGUddVeMNPablKhZxFWuSwF7E/We/wPcfb+iQYx88bTh3vnJBq9vk5ORw6623RuIMhwwZwq5duzpkPHtCTOKqb9++PP/88xQVFfGrX/2KUaNGMW7cOObMmUNhYSF//etfAbj77rspLCzk//7v/+IWE+FS+w1pGGc1ffp0pk+fHtcxuwOJWK6kz4MmA4SCUOURaF3kFvzxxx/573//G7e48rpUpprbtff00+ouGIaRYBFRgyxTXJHaiTWuTKSUvPrqqwwcODB2cWVmDDrdEqrBX1LVxg4JsnuL+r/nIMTAMaru0K6fO+ZcnUjslqvmbsFAWTV2IORq4NqLpVVLW2UYwkQpx6CHBYbDxapVq2JfW0zrj82hfhcpdtl6tmBlSePHFcWQN6Dt89QpbwHuVISmIc2yMq25BdtEj+EztYiLhq32tm7dygcffNBm1fiuICZxFc5cysrK4sQTT+Tzzz9n3LhxXHHFFUybNo2NGzfy5ZdfsmrVKl588cWELg77Km63m5tvvpmDDz449p2qywDwenT8hkDT96I6V0AwNQujBlzOENLvjSugdH/n+OOPT6hxsxEyyEg1yzBkdn4vyvAFPp75IpJVCxx3koEhIVhZixEIotnbN55SFm5T5+s5ELJ7qYt1RRHS50GERcBeSMxrSyTmqv5zDZTVYAeku8FvM5b4oFjirSCq5UoLmfs6XQhvHGtLuP2NGQyfYqtv9xSViuLGjytL4hRXqsCtyMhVlitPY9EvTbeg2E8tV21ZljqLjRs3csUVV3DzzTczcODArh5OM2Jaxd566y1effVVhg0bhtvtxu9XP5Ls7GzOO+88brjhBurq6nj55ZdJSlKL1YsvvsjkyZPp379/x41+L8DtdvO73/0uvp2q6sVVwKDLYq40TYu/zhVgT0/BU6STnBpClhch8vbvORAPxxxzDMccc0zc+4WCBqkpSlzpOfGXM9hTwjdUcc2X5AwA0pND1AQ1UuzgLa7C3buda3SVFar/s3shdBtk94ai7VCcDzH0QeyuxLy2RHELGpXK+iJSGojLsPhqLaA9GK5x1brlSjiSlIXQ5yG8eunhfR1J8a0t4TpXZohXig2qWnMLVpmJEbn9oGgHsrKEmFbQsPvPbcYsZqjyQA5vE4tqXJarGD5Ti7hZvnw51157LbfffjszZszo6uFEpU0T08aNG5k7dy5z587lpJNO4rXXXqN3796R10eNGsX69eu55ZZbGtWqOv/88/d7YQUQDAbZsWMHNTWx1xySzSxXXWMJTNRyZU92UlujFhWjqKC9h7VPU1ZWllD8QChkkGLWuNJ79mnvYbVJ2HIVl7hKzQAgIylIjek18Ra2f+FZWa7ElcjKU//n9lPPF+9o93N1JrGuLdK8sIsGbkFZo+qSifQGAiEmy1WsbsEolquwuHImxbe2NCgiKjVBkg1CvlbGWKvmkOg1RD2uii0LVZriSpiWK1IyQAjsvtrG7WviCWi31Qe0J3KjatGcgoICrrrqKubOndtthRXEIK6WLFnC1KlT6dOnD4cccghut5vJkycDsHbtWubMmcMvf/lL3njjjUb7XXBB9zAddjVFRUVMmjQpvv5EpuXKV6fhD9FlAe1JSUmkp6fHvSjYHTrV1eo2M1S4syOGts8yZ86cZrGHMeHz4XQZGAbYeua1/8DaQAhBenp6XDW+RKqyUGW4A9QG1Rxvb3ElpYTy3epBpvm5mOKKor1bXMW8tkSxXIlaFQtly2ggrmJxYbVVnT1MFLegHqqPuYprbWmYcedOMsffSrJM2L2X21f9XxtjLF+4F6JLBb8L3QapWcrqZa7JQANx1bblSjTMqrTirtqFZ599Fp/Px4MPPsjJJ5/MySefvHfGXCUnJ0d+AE8++SSHHHIIvXv3Zvfu3Vx55ZU88MADHHzwwRx77LGsXLmSAw88kLKyMrKyOrf9RncloTpXDSxXAeIv49BeXH311Y1aEMWKzWmjwhRXsrSwvYe1T5NotqDLWwoCPHU20rqg0bcQgp9++im+nVIyAEh3BeotV0XtbLnyVJu1lpLqY2ly+iqXVcneLfxjr3PVvBSD5lEWKHtWg7IdsdS5itVyFWmBU9+8PWK5cri4+uqrYl9bGogrkZoBNXWIuujiSgZ8aoy6DZGZp77nptl+LREWV44GrtK0bGX5qipRpRkAGbaMmQkZbWKzgz+kPldb5/829zXuvPNO7rzzzq4eRpu0ecWfNWsWRUVFzJw5k/Xr13PPPfdQU1PDZZddxq9//WumTJlCamoqF154YSRrcP369QwfPrzDB783kIi4ko3E1d5V4wrA7rBRVmXerVUWt76xRSMSzRZM9qs5U1u3Fy3epuUq3eWnNqh+J97CivY9RzjeKjO3XrSGLVgVRe17rk4m5rUlSrag7lciydGjgbiKuAVbtrBIUyCJtsRVOB7JWy+u9KA6Z9xJBA2yGEWqOq7macFy1SDjL5yNGnYTtkk4s7HB+ES6yryVlQ1ci2Yx2nDMYJtEmjdblqv9iTYtVy6Xi6eeeqrZ8++++26jxw3vQtavX98uld33BRKJWYoEtNdpBGTXiav333+ft956iyeffDKuivg2h05Jpdpe1JW1sbVFQxItIpoSLAcn1Pq6LjPzyiuvZNq0aZx66qmx7eBMArsTJz5MryCe9nYLmgJKZDZwlaZmqgtebdVenTEY89rSxC0oDQN7QD3nyE6LbCZsdmXpadVyFWO2oCmuZDj4G7CFrV5JKfGtLRG3WgCR5lY1r0zLWzMaZvyFY6didgtGKXCaZpY1aVjeISzWUuKwXIEV1L6f0SGR0hs2bLDElUm8lispZaRKsNejE+pCy9WmTZt477334haIdodOcaUNKUH3VzcOBrVoFSllQparFKkuILXBtosldhTvv/9+s56IrSGEiLgGHS4VjN/ubsFwxe20+tpfQmhg1jBqlra/FxF/+xslYnxlNWiAN0R9AVFoYGGJwS3YVrZgOB6pgbjSg6Z4cSXHt7ZExEkI3YwR030tWK4aBpsnpaiCoN7a2NYgX3PLFelmWRMzKF6GgkrACVEv3toiBougxb5Hh4irOXPm0K9fv4449F5HZmYm9957L+PHj49tB28tBP0EAgKfX4MuyhSExGoXAdidNmr9Ap9HQyAbB4NatMppp50WV0PyMCmauqjUhNq/wXesCCHiz4gyXYPOJFNctXe2YEtWBjN+hvK9NyYw5rWliVsw/BnXBNSNUIR4AtpjtFxFqpnTwHLVoCdfTGtLg3IGYXFl80UvUCzNGC/hdKvG5eHK7A1iv1pCmm5B0SDmSqSF3YKm5SpSriEt5sboluVq/2Tv6H68F5OWlsall14a+w6RTEEdn9F1mYKQYO0i1ILtDUFdrQ2X269iWzJz297RgilTpiS0X4pDXRhqtRjvpjuAROqiidQMJJCSbEBAI1BZR8jrR3e1EdMTI+HgY5oEH4cLRMqKor0wqlER89rSxC0YEVdBdSMUIRYREA5KbzPmyhQ1DS1XAWVtEkkp8a0tDWKW9Cx182ALtDDGcIxXWNy5ktUYvHVtW5pisFxRE30+xTZ+S1ztT1il1DsYn8/HunXrqKqK0e8fCWZXZRi6smlzQrWLAJvDhi8EnlozY3Avdr10Njt37uTnn+NrzSI9NThtQYIBgd8Vx6LfAcQdY5imLl656SG0NHVB9ha1YxucljK7wjFYe7HlKua1JdjEcmW6XmuDorHlKq4K7W2JK9OC2khchS1X7vjWFk0HBEgDe4aaI46AP/q+YQuVKylyrqbjaJFIU+kG4sq0rFJdjjRC9cHspjs7JizL1X6JJa46mB07dnDsscfy6aefxrR9w0xBn6Fc+11Fampqo4KxsWJz6HhDgroac+Hey7OyOpP777+fiy66KL6dylQdp7oaHZHcdcHZffr0ITU1te0NG2JWwc7LCKKlKWtDu8ZdtWBpEOZ592bhH/PaEmpciqGh5coWzS0YS2/BNmKucLrU4uX3RuKdbA1iruJZW4QQoKtx2t0OfCHQpCRQGcXVFxZRYXegq3nsV4tEsgXr49CEzY7fmayaTleXx1+GAaz+gvsplrjqYMJ3VzFngJkpv946Hb8Boov6CoIqBPvtt9/idscXJG132vA0slxZ4ipWEglol6a4qq2xoaV0Xbbg559/znXXXRfXPsIMLM/LDKKlKmHYruKqpZgrU1w1a/K7FxHL2iKlbOYW9OxWQf4q5qqBWzAWy1UwtpgrIZrHO+kNYq7iXlvMsemajNRE8+yuaL5dE7egiGQtth1zFbXOFeB3me7EiuIGlqs4xJXNcgu2N0888QQzZsxgxowZPPTQQwAsXbqUWbNmcfzxx/PYY4918QgtcdXhhN0kMV8wTd++p85sfdOFbsFEsTt06syYKwDKLXEVKwnVuSpTLYbqanS01K7LFkyIsOUqPRTpc+ctbh+3oPR7laXFZm92wVTZgwKqyvbabNaY1hYjBEjQ9EgAdliU1AQFtmgxV+3hFoRmQe0NswXjxhQodt2oLzgbRVyFA9rrLVexuQWllNFjrgCfO0NtU7a7Xow3yD5tE8ty1a4sXbqUL7/8kjfffJO33nqLNWvWsGDBAm6//XaefPJJ3n//fVavXs3ixYu7dJxWQHsHE14AY7VchbNSvHV6l8dcLVy4kBdeeIGnn36a5OTYF0SbGdBeG3ELFidceXx/I5HPSZptXGoq7WgpXecWvOyyyzjqqKO48MILY98pJZ2goZGebKAH1UXI116WqwbB7E0/U6HbIC3LrL5dWh+DtRcR09rSJN4K6kVJdbNswbabDEtTXIm23IKg2sNUoEohBAPooaCKn3K44l9bzKBwmyapDghAUrczShayKZAitctidQuGgkqI6rZGPRgBfOFioWUF9X0q45gvQrep5Ing3lgSujnLf/88xUvXd8ixcw4fwYRHWw+LyMnJ4dZbb8XhUHNwyJAhbN26lQEDBkSqFMyaNYuFCxcmnCDUHliWqw4m7grtDSxXPgN0W9d9Rfn5+SxatAi/P3rac0uoOA5BlUfD7xPKlRBrleT9nITcgoVKXJWW2bA5u65C+5IlS9i4cWNc+wihURlQF0Jnsrqzb2i5kgFfJA4xblrIFIwQzgTbS12DMa0tTcRVyOvHX15LSEJdqEm2YHs2bobGVdobuOuEEPGvLWG3oDCoModXlx+lIXNkfM7mY2iNiEuwuVvdm6yC2mVxfn0CRDxiPBaLoEXMDBs2LFJ+ZOvWrXzwwQcIIcjJyYlsk5ubS2Fh1yarWJarDqZXr148+uijjBs3rs1tZTAAtZVIVI0ovwFaF8ZcJVqKQdM0NJsw465sOJwBFdQeT4bNfsrFF19MTU1NzNvL2ipEXSXBgKC4Uqe/U297pw4ioTpXQFUomWxqcTnUhTacLSgrijFe+hPUVCAmHId27LnxHThcmTs5egq+SO+B3LEeWVG8V1oUYlpbwlYo0/ITdgnWhgBE9DpXrbmvYoy5AhXvJFFV2oXXnNOm2Il7bTED2nUhqWrNctVMXMWYLRil9U2YulTzor19Xf028axl+5hbsC3LUmexceNGrrjiCm6++WZ0XWfr1q2R17qDp8SyXHUwmZmZnHXWWfTt27ftjU2rVUC6AIG/iy1XiYorAJtdxV1Z5Rji48gjj+SEE06IfYdi0yVYZaM6KLDZu05caZqWULunipASP8m6al3iMy1XxqcvRwKI5fJPIu7PWJHmvqKlHnCRoPa9c27GtLY0C2avAKDGry48jWKuNB0JYIRU2YFoJGK58tTUi5ukRMWVGr9NM6gy9V1UceVvPD4RpQ1PVHxRyjCYBJ3JqmVSmN5D4rtwWwHt7c7y5cu5+OKLueGGGzj11FPp2bMnxcX1v+Pi4mJyc7u2tqIlrjqY2tpavvvuOyoqKtre2BRX/pDL/L9rLVdhErlg6jZBXVBQZ4orK6g9NjZt2sTatWtj3l4WbgegutJGTUBgc3SdMVoIkdBcKTOU2yVFloEm8JXVENq9HTatUNaU4RMAkD99Fd+B23QLmuIqTuEvQ0FkVWlCNx3tSUxrS9MaV+F4qyBouobeoAOEEAKptdFkOBzQbmvbcoXbLMtRV1XflqZJMHvM88W0vGnCoDoIEvVejGATEdjUshazW9B8PYpbEEAMPaj+7/6jYhtzmIjlyhJX7UFBQQFXXXUVc+fOZcaMGQAceOCBbNmyhW3bthEKhViwYAGTJ0/u0nFa4qqD2bRpEyeffDLffPNNm9uGg9l9fvVj9BsC3d51X1FmZibDhw9H1+O3huh2HU+Q+lpXe3Gxxs7k3nvv5frrr0eWFWL872WMVV+0ehGXBargaGWZvXndok5m6NChCd0tVgglrlJDpTizUkBKQl8tBECMPRLt4GMBkFtWx3fgiLhqwS0YrnUVR8yVLC3AeOY2jL/fhPHaI8iwJacLiGltadL6xlNQAagyDNHmitGgSXJU4rFchUVtbSXSrDcmTHda3GuLKa50YRCSAi8aMmRE3k+L44s1oD1cQLSFJt7i0ONVhmBGLmJ8nEHSVsxVu/Lss8/i8/l48MEHOfnkkzn55JOZP38+Dz74INdccw0nnXQSgwcPjs8D0AFYMVcdTFwB7VXhGlc2wMBngLMLewuGJ24i6HaNOi/UVqspJkt2tufQ9lmklGgCjNfm1rfcCPiBjKjbsnMTAJVlDqoDdKlbcP78+Qnt57WlUecTuJ11pPZKIlRRifbzcgDEhONU4Llug+J8pKcGkRRb/0Rpxly1WPAxzoB2KSXGgqfrv5dtPyG/eBMx9eyY9m9vEglo9zSwXNmjiCsZFlctCYF4Yq6S01XMVW0losZsoG1+F3GvLeFsQaHec42hk6QZ1O0oIblfg7IITXsfxiiuIn0FWxJXGbloVzwEUsbeU7DJ2PeVmKuu5s477+TOO++M+to777zTyaNpGcty1cHEVYrBXOQ9NWpbf0i51/ZGbHaNuqCgpsqGlEDZ7r22nlBnIqVUdYGq6jOh5JK30YJRsqqqSqG2kkBQp65GV3WLutBylSi6Tefn3erin9nToGd/LyIUgH4jEdm9VGp83gC1cdH22A/cVquS5HQlOjw1yHC2WGtsWQWF2yA5He2cWwCB/OFTpCf2BIT2JK5SDOG+gpECoqJxpmD4mG1aruKocxX+3Gsq6yvlJ5rUEhZXuhJXVSF16ar5ud4iLsPlFIRWL2jCYqmtxs0tFBBtiBAifmEFluVqP8USVx1MPJYraV5Q68x1yG+A1oUB7R9//DEnn3wyJSXxp6rrdo2aIBghDZ/foRY9s5K4RctIKdHMC4GYeTn0HgKeGrJ3/dR823xV9qCy3AmILrdcXXrppTz++ONx72dz6KzcomJdslIr6DfIfP/jj45sI3r0AeK0gLYRcyWEaGC9ajvuyvj2I7XfIccj+o2AQWMgFESuiTMWrJ3YU8tVNCFeH3PVXAg0Ei9aDPMsXMW8pqK+bYwpruJeW8zx23QlKMtNjVf9c4NYzgZWq4jgdJhteAL+1m/uIm7BDuhwYFmu9ksscdXBxGW5MgNrq0tVkGZXl2IoKSnhu+++w+eLP65Et2tUm+tzdYWZMWi5BtvECIUQAbXQi0Fj0SapgM0e+auQsknw79Y1AJTt1gkBnlDXxlytXLmSLVu2xL2fza7z9fokpIQ08klJDxIgCTH84PqNTHFFya6YjikNA+pU9mEksDoaMQa1y9pK2L5WFZk8UMXcaOb/ctUXMY2pvYllbZENYq4Mf1DVEBNQGwSXu7n1KWK5ihbQHhZcdkds61lyhhJhdVUQ/u2bjZDjXVtEJOZKCcpS09BUs6VBLGeUeDAhRL01KiygohEJaO+AIrxW4+b9EktcdTBDhgzhqaeeYvTo0a1uJ/1edYen2airkGDTCUq6NKB9T0ox6HZNNZ522qkuN99DcX57Dm+f5HfnzOamw4ZCbj8VWzR4HKRl4/RUwdZ665WUBnLLKgBKdjupkTag60sxJFS2w2Fjd4WNDYHBAEgJO+tGRC6oACInTsuVp0Y123UlN6u43ZBYg9rlhu/VwAaOQYRrJw05UMX2FOdHrM6dSUxriymIhG6nbmcpGBJbVhqGFDiTmn8usjW3YNMaUm0gNK2+3EX488lUCQ/xl2IIx1wpQVnsUf/XbilSQrq18cXiGvS1HtC+R0SKs1qWq/0JS1x1MFlZWcycObPtLKoydQcmU1XPM5HkAESjVOnOJnx3mkh6vc2uAQI9M4WaSjOovdiyXLXFL7LsHNEvO5LuLTQtYikxVnxWv+HurVBXTdCWQm21TqWhLopdablKtM6VzXR9L60+kJqDzuWr/2VTsruJeya73nIV0wW5rTIMYcKWq7bE1cbvARAjDok8J3QbDByjXt/8Y9tjamdiWlvCriibndpt6j3actRn4nQ3F1dGK27BuOKtwmTUjy3gcCPMUgdxry0NsgUB6rwGzh6phLwBPLvMYPmWMhkj4qqVuLpWiojuKWFxLy3L1X6FJa46mPLychYvXkx5eXmr28lyFY9kJCmzOS5196V1YUD7noircKyYlp5MTZW5iJdYlqu2WPHtMlburoTegyPPiQOOQgoNNq2MtIKRq5YAUB3MBQQVQfV5d6XlKtE6V2FBGAgY2EaMp7bKjrdpf8HkNJX55auLrZVSeJuU1sWVyFAxV60VuZXBAORvUNsPPqDx/kNUdXT5c+eLq5jWlgYxV7XblbgSWcpN6ojXchVOqoilr6CJyKkvcOpNyap/PkFxhRGKzJeUob0AqPjJXFeaZgqGCTdxbkVcSdNyJTrCLai3Ilgt9lkscdXBrF27lnPPPZeffqp36RjBEHW7yhvfgZuWq4DNrMnjUgtYVwa0Z2dnc9BBB2G3x9+vzh5uw5Lipq5GR6JBZQmyrWJ++zkPvP4h93+5vtFFSaSkU5EzCKSB/GYh0udBrlkKwM58daEsD19Du9ByNXbsWAYMGBD3fuExhwIGzhw1/73FVY1+H0KIeitIDKUTIgHUbVquYgho37lJXRhz+yHcjWtmiYFj1R/5G+rdU51EtLWlGQ2yBWu3qfco01R5gmgxV62WYoinxpWJGFBfcLMqq3/k77jXlgYtZOxmodyUkcqaWfHjttbHF4/lqoUionuEFXPV7jzxxBPMmDGDGTNm8NBDDwGwdOlSZs2axfHHH89jjz0W2Xbt2rXMnj2b6dOnc8cddxDsJPesJa46mKYZPYFqD19d8iSfz36Y7296oX5BNjPp/NJs1+BUC0RXugWnTp3KggUL6NOnT9z7OlPUghJ0OZFS4A3XaTKLXlo0R/o8yGAATYhmjWGLBk4AIZDff4ox/3F1Iek7jJJ1qpZTmRky0pWWq2eeeYYbb7wx7v10mxpz0B/EluTAlupCBkIEKhrXJhKmEDJKdrP99a/Z+soSpLeFhTIBt2BL7ka5XVXMj1aZW6RlqeKSPk+nW2ZjyhaMBLTbIparULKy5ESLuQoHtMtW3YKxxVwB0H8kYsxh0H8U5b1GRJ6Oe20Jt5AJBbC71N/uIablarXZFqmFmKtw7apwLauo+DrOLWhlC7YvS5cu5csvv+TNN9/krbfeYs2aNSxYsIDbb7+dJ598kvfff5/Vq1ezePFiAG666Sb++Mc/8uGHHyKl5LXXXuuUcVpFRNsZWbgN46sFUFmC6DkQQ1MXybAZfNMzn1C9oQCA4i/XUbj4J3oeMxZZqrKgPD5157R6+S5AoNv3zjpXrmS1cPvsTuxAVXUSSakgd25CDBrbtYPrrpTsxJAS3elCNEl196TmIA4+Frn8E9ixDjQd74jjCVS9gbNHKlU71YWvK8VVooQtV8GAypJ15aZTU+3FW1yFI7NBwVBTXBW88Rk/faQuhrYBmRiHTkBr2vanJjZxJZxJkJSiAuBrK6PWYZLbTHE1IHrguOg7HPnTV8j8jYjc/lG36Qjiq3Nlo2aLKlsQSFICwhEl5krq9SKmGWHxEo9bUNMRMy5TQ1m+POb9mtFAoISLnzoH5oImqN5YgMMXRLrMz6Op+HPEY7nqwGzBfcQtGHr9L9BRbvDB49BPv67VTXJycrj11ltxONQ8HDJkCFu3bmXAgAH069cPgFmzZrFw4UKGDh2K1+tl/PjxAMyePZu//e1vnHtunE3gE2C/sVxJKZE//4jxv5cwPngO47uPkHVV7Xf8uiqMD5/HeP5e2LAcCrchVy4m9OHzgLq79FfWsePtbwHoM0v1S9v53veq/ooprmqq1Q+xLmDelXah5eqzzz7juOOOY9u2bXHv6zItV7XmwlKyTd21yV2bW91PGgaytABZsrPR3bMM+JC7NmOsWISx5B2ydq2NtNTYV5DF+UgJWkv9zY45CzH5NMSoiWhn3kjJFiWoZF4Wvjr1+XalW/CSSy7hvvvui3u/sCBc+vYa7j39eexZSlB5i5r8PhtYrnS3A0dmMsFt5ax7/IPmB43VcgWtlmOQPg8UbFElBfoNj75/32Hqf7PuWGcRT50rf02AYI0XZ04aflO4x1uKQZoxVyKegPYWiHtticQtBSPFT1995HNcA3KRIQP/2sI9zBYMW66sOlfdnWHDhkXE0tatW/nggw8QQpCTkxPZJjc3l8LCQoqKiho9n5OTQ2Fh57Ri6zaWq3fffZd58+YRDAa56KKLOO+88xq9vnbtWu644w5qa2s55JBDuOeee7DZYh++8faTGNsa9yaTX8xHTD4dcfCx8XU5D+8vJVSXk/fzt4S+eA7h9yCFhnbwcYih4zGWvI3cpmJjCAbYuWA5hi9I9i+GMvw3x7NzwfeULNuIsWs7hIL4k7JYu3g7LsBr9iPVuzDmqqqqirVr1yZU5ypsuar2Q49UFyXba2EssHMTMhRslGYPKg4t8P2X6N+9U98qQwhwp4GmQXUFql2roj9gbPgcccCRiIknRVxGezVlu5EQyahqitB0hFn3CqBo7nMAfPi/7YTvk7pyvmzevDmh+LyGgnDFZ5s4dEYfBOAtbiyeRXoPJOByhxjyq6lkHzKYry6dx/bXv6bXtHFkjquP96ovWtm2uBLpPZC7tyArSxBhoRRmx3pV0qH30Ja/l77DVJuX/A1IKRNaSxIhLK5kKETNlkJsyS5cuU3er2mB8hSqml8pw3uzo0hVlI9aikG0VoohAbdgC8S9tkQC2uvF1eL/rqQi02BiD/Ct3AXjzO+nifiTuhpv4UfLKV8i6XvyoaQN69X4+JEiou6E3k/rY9+3LFdtWZY6i40bN3LFFVdw8803o+s6W7dujbwW/h0ahtHo99iZv89uIa4KCwt57LHHmD9/Pg6Hg7PPPpuJEycydOjQyDY33XQT999/P+PHj+f222/ntddei8+0V7gNw5WKf8gkpCsFe8FabLvWIf/3EsFNqwgccxE4kwjWevHsLMdbWIG/tBqhazh6pJE+ph96sgOtcAvazvXoxVsRxdvRvDWEf6YlhQ42/JiGY4eXoddmYZ96OaOLinnhFOifv5p1r6s78ZwTD6baa5A0oAeercWse+UjRgLLf6ijcF0BA1LAG1IToCuLiIbviBPJAAvHXJXsrGJobia+zV4CST2we0oIbFyN7D8aKSHk9bP134vRVn3G8JEqE84fsCNcLmxGDcK8SEpNQ2b0Qvboi3RnUL1hNRl1u2DFIoyVn+PvfSDBPqPQklzo/mq06hJETRnS4cboNYzQoPFgpplHYmskqnZR+LmQAaHqPfjEoGp3BXabEzSzVYYmVKyUlMiQJFjjwV9ZR6jaQ8iv7mTtGcnYs1NJK9jJHyePwHPgDHZvLSNQXoNvdwUhj5/S2hJ2pZfULxqVNZR8swnDgO21ao7YHHqnLRzRSLgUQxNX5vdf7WBCNpRtLMK9s5KsXqn4PUGCASdJQFJyCOfRY3FkJOM4eij+Tzeyas58Jjx5BZp5LHt1BQLwkYRnYyFVa/PxlVYjNIE9I5mknpm4emVgT0/GlpyNDgQLdhDsdxAyZBCs8+HJr8Sz5WecgC99AIEdZQib1qgFipQSZDJuZzKipoKajT+b5VQAGX49/EA9DuxhYLOnxkegOkBWicY9x19GwW3vUm5qg/QDBjDihl+S1Edl5ukeHzpQvkXVmVr06Va+2q4sbNGyBQ29fQPaWyLutaVBraiGbXu21ggm9pDUfpfP9nE6/YA6j8S3qwp3mpPq/DLKX/qaoQPBv7uY7T98zfb5y+gzexKDLj5GuZNDAZyhIFLTqdxRQcnS9dTtUPFpzpw0akUtlXmDsKdFF14yZBDyBgh5/ciQeTEXqJtDQKurJgUwfD6qt5ciNAGobYQQeEvqqCqojDwGc9/w4/DxaOICbun58Li0zk2w6EyWL1/Otddey+23386MGTP45ptvKC6utzwXFxeTm5tLz549Gz1fUlKSUHP5ROgW4mrp0qVMmjSJjIwMAKZPn87ChQu5+uqrAdi5c+ce+03Li+3c9cZK1tR9GnnOZjfo18PGC6eC5/FbuGb+RjbWNi4GmGNL5aqcKeT19fJ00RI2VzZ2VQzLTOWOAw9hy0Y39679igqjGrHxA0JvP0plAHo6s/nkisHIn5ehVfegOmDjhvNfRyI4IsdgTAZU/bgaDoAthQ5c5trmMS1XXZktGF4Ar7jiCubNm8fo0aP58MMPefTRR5tt+9RTTzFw4EDeeust5s2bR3lxJeWOOlZ9+jav2iS39jyWZUsM8h35PPGPcymptiGQpDvAaZe8c+FBgJ0/vbeb97btiBw3iMSQcE7STFJtBt8F3mOVbysC0HSJ02ngdsHbZxs4d/7A3K828umWxu6dNKedf54wkTXL0/n7xh9Z52vchidTd3Nd3lTGTazgjcpdTLrqjwl/Zq9dcj9DalPZ7CvmxfKvI89L1Dp4XuZEhjpzWest4LWK7xrtm5wa5NETxlDy73V8+39zaVo/9tNHPmdjtWBXneAXPQz6JcOmGoHPMMVVF8dbaZrGl19+ye23386cOXMAuOCCC9i6dStud/2F6aijjoo0Xj399NMpLihll6P+d1fn7csExvPl81/zt8fuRJoWS6cu6dMjwMxhvVh80KMEpcFPjnfJcIC+GzwHPkdtUJATGsbCqzMIEGD65F/SNGzx2JSRHJkyjLJgLY+XfIpuN0hODhF4/mvqau/jpLSx/MI9iN2BSu72f4quS2prviEUfBCAU9LHc2BSP7b7y/hnmSqJkZQcwm438Pzjl5zq/gWjXL3Y5CviP+XLmn1Olw6dxkF/Pq/Z87Fy9vSTqSgpYYijBxdkHQZAVQCSdKhctY0vLnicd/I1yv2Ca2eWcdQYyP8+H0hiW7Gf8BU5Wp2r1rMFw6UY9txyFe/a0l+38fb6Ap5682/sKpJ4HfXjO6R2KkOS3fzrxXf4qmIjZTXLqKj9M5qQpNvhsYMmM3Qg/GvTJt7auUutsU+8Q/BxqAvCkbaTePIq+NuSTfz3iamNzm0TGnfkzeCrp7/i9fIf+NGrkhbC2sktHNycNx2AV8u/jbq23Nj3aKbMgNveXsqSuUc3ej3PlsZvekxhKR/wbOmX5Acal9XoZ8/kkuwjAXiyZBHFwcY3f0OcOZyfOQmAvxR/QkXIgyHBkDCk1xBufvIPbX8ZexkFBQVcddVVPPbYYxx2mJr/Bx54IFu2bGHbtm307duXBQsWcNppp9GnTx+cTifLly9nwoQJvP3220yePLlTxtktxFVTv2hubi4//vhji68n4jf9/tt07IaLNE0t8kKAMIBKJ9WVNlLTg4wZalD9s5OaWp2gFEgBmWl2Jk0rISUlRK8v7VT7k/B5NQIBjaBfUFaXzj8Kc/jZo1MWTCGAJNsucQhJhi7wBFP5fH0KR4+qYcjoGhZ/koPNKQj4QxR4YEwGDOqlFoothXZGmGtbQ7fg8j0JBG2D1o7tcDg48sgj8fv9bNy4EY/Hw44dOxpdKMOsW7eO0tJSCgoKcLvdiEwbtWanEocEHY2yQjvJQ2wMznZSV+sk2wHJdoOMHn50TfDWN2l8ttmLoZWTrEtcWr0bcFQ66AK21DjICroJSQgaAjwgg/DTmhSyMgPofhfpWjJGSBAKCjRdkuUQJCUbTDiqnP41gsId7gYORkjTXRx4WDk98vy4q/fwrlzaCBigoZOpN/+cpNSpDglqDRtuLVmJRFRbj5w0H3ZNw+bTQQOfIaiRgqAUZOkherigh0sSdo96Q/Bdab1yEJpMeK60xxw7+uij+f777/H5fJHjCSHo0aOxy7auri7yut1uJynJjUPWBxsbhnLvpNslDulGIhGaIMsmyXX7SHfZyMkWlNbYcJKCYUAPh0GmDrW6YIjdTrJLUuGBXJv6rr2GIGjeyFcFnJT4BSE0MnU3Nk2SmeInFBKUeR04sOM3QOrQJ92JlFBU7QTzt6mhvmMpNTLM79htC5GSEqRO6GDoan+pk950Dkgw5J7dMGXZXGi6Gx0Xyyt1tnk1qoIaDiRHZQXpl2RwUh+DBUUOnE41P1I0QbUBRQ06wJRVFzX73nNN6+7unfkUNHktb/tWegEFJSXs3sN5Fu/aYoTKcNt1st1OynQdQ9Y3Mv+p0saQZOiVrNMz6CLgtRPQbOQ6DWwCKnzqi3O77ASNFPxAtl1iExJscNYAtdim2u1k6m48hsBnABJ0TaPIL8i0SdJsDnrYGo8vSXMgJQQlOEX99SVMspZEXUB9B1lJDtI1GbE2qddd+A31lFtzRuZTmBQtCcNcrFI1F0E91Oj1VK3eVZ2mJ6E1OHheO1gYuyPPPvssPp+PBx98MPLc2WefzYMPPsg111yDz+djypQpnHDCCQDMnTuXO++8k5qaGsaMGcOFF17YKeMUMpF+Fe3MvHnz8Pl8XHfddQC89tprrF69mnvvvRdQP8hHHnmEl156CVBBbL/5zW9YuHBhm8f2+XysXr2asWPH4nQ2v+OSUmJ4PciF/0JsNC0JrmSVNVReWB+EmNmT2txDKC5JxV/tx9UjleyJw0gd2pPvv/+eCRMmRI7pr6zjmyv/Qc3m3aQO60XeIb3oX/c+ug6cdRui3xAAitYWsPo3j3P0zCIMBHe8O4bJ/hLsGvxrs4bfEBx72RiuevDsxD7YNgir+Y7g66Xf8NCsdwE4/6bJuN/6DM2pM/ViDVG8gwLfSNZ9WMYhx1SQmuqHQWPRTruukcvFU1hBxarteHaVozntuHLSSO7fA3ffLFasWRXz2KURQi59F/nVu8oN2G8E2gkXIzLzkKUFGO89oyqeJ6cRmH09a3aVtDhfWqK1eSYNAxk0QBNotujWJaOqDPn3G5EON96T/4izRyr21PrMpe++/oa+Hje7Fq6gZksRtswU5MQxPHrzhxE3Z0ZeCs/9dEvMYw7TkfMgluNv/D6fW6Y9FXns1CQXDTHQXHaO/d8fEUKgaRqLT5vLAcM3kJ4ZRDvvdkSfoZFj5y9Yzpo/vYkMGbjcQY46oQSv18bufufQ9+RDcWalRD23EQzhL63C9sLNCCOEvOIv6GmpCCHY/P4rDFz9EQwcg37mDa2+R7l9PcYrf4bc/ugX393qtm2tSW3t10/LIHNIb+xpzTPbQr4A3137HOUrt5E+ph+/mO6Brav5YWkGtVnD2JTXn/eeVhbVRz+/ioFjejbaf/ubz9Jn4xLEhGlox57T6DVj0X+R33yAmHI62sSTYh53mD2ZZ3LdtxjvzIPhE3jgPyms+HRT5DWB5IKDnRw8bDd9BnooSZ3ET++V4iupJnV4Lw69/Wj0dx6DPkPRz7sdgGCdj22vLqXgkx+x+0o45Bc78duz0C68C2d2416Uy5cv5+CDD8ZfVkOg2gNCoNl1bEkO9CQHmtPeen/HgB/jsd+AbkO/4el2/Vwi5zDXgFCdD19pDb6yagybxjZf87Vs7dq1jBrVvKyIRfy09ll2C8tVz549+e67ehdJ2F/a8PWO8psKIdCT3MhTfotcuwz51QKVueetBQQMGI02/mgYfjBpQiOtrQMCjnQ3h/7tVyz7zdNUbyygemMBYmwyA4fXwldvIvrfhBCCnmP6UDzMrlzzPQbwwHu/4dPp9+MPqabN0LVuwT3B7tS5+vFT+e7D9Zxw5VGs2raF8h+2UmKMJIcd5OjrSTtWJzk5CBm5aDMvbySsAJLyMkjKy9jjsQhNRxx5CrL/KIx3/w471mM8czukZUFVGSAhLRvtzBsRyRmwq+0ilfGdX0M4Wv8eRVWJch1m55EyqPncFnadnpPG0vOYxmUsfnHeRM7qfU97DrfTSe+RHPl7zBEDOe6CQwg+8w6BKg+B8lpcPdKo3VGKZ2cZ/kEOIIisLmtoAKDvzAlkjOnHzg9+wOHZDaHFuAb0ZchFx7R6bs2m48rLJJTdC4rz0etKEOnqV55Srto1if4j234TvQaC0KB4B9LvbTH4vT1IH90XewuiTHfaGf+n8/jqkiepXLOD6oFeUp1ghAQjzj+SYQN6R8RVn6HNk0CMduwt2K40yLhrKGRmXD6JqecdTPHuTdgXvg5Awadr8ZUkkTFuAAc/fAF2XykGNCrFYHM7GfKrYxjyq2OQ29dhvPIQjrwe6E2EVRghBM7s1GbCKyZs9WPvqIDq8DFtyS5syS6S+/dQyQKr23cts4idbnHlPvzww/nqq68oKyvD4/Hw0UcfNfKLNvSbAh3iNxVCoI2ehHbJfWi/mYt20V1o1/wV/awbESMOQYj4PipndiqT/vFbBpx9BDmHjyDlzAuVRWz7Oti0IrJd3mD1o6iVOXh3VwBgz04lbDt2uLo2jmZPmHruwdz8/Dm401wMPFvFDax4ZjW7trmw2aQSVuk90M66UTUp7mBE/xFoF9+NOOBIlYFYVQq6jhg3WT2fldf2QTqIcPsVkRHfTUPD4F663AadGD361me4HTB5MFPOOBB3f3XhrzMLX5YuU0HYIt0MFq8qa3aclEG5jLhyOgNnmQI0Ss2qlghXxJe7t0aeSy0z42sGtH2XL+xOyOuvLKMFW2I+b0fgzErh4IcvQE9yEKpRhViT+ueSN2UMvQZncfZtU7nszzMbzx2TVmOuEmh/025EqpwHmf27owA49ISRXPqnGQwa2ws9002PQ1S2aMbBwxh31xlMnHcZjnR326UYOrKAKKhrR0S0WuUY9he6heUqLy+P66+/ngsvvJBAIMDpp5/OuHHjuOyyy7j22ms54IADOs1vKoRQFo20rLY3bgNHuptR19WnzhvZFcj/vYzx2atog8aCNMh0FYEBxQVO0gsrAMge3hO+VZXMhx/eK9qh9zpyJ49i4LlHsvWVJWza2pe0kw8ltX86YvC4Dr3Lb4pITkeceAnyuPOguhxSMtr9/LK6XFk/+wyLvSZQuSrwSEZO69tFITXLTXVZHX2Hx79vd6BhnaakZGUVSe7fg8rVO6jdXkLWwYMpMcWVo28/KN4B1c3FVRhZq5JORHIsdmaTvsPhp6/Vzc9BU5GlBTg9leqGKC+2lj6i9xDk7q3IXZtiEmQdSdqwXkx65jeI1/8EBBhx3S8RZs28M29s2ZrXauNmf/tlC8ZNg/58Y44YxF+WXE1Wz8bfryZUPNKAc6YgzIbaQJu9BcOV2zukr2AY3QZGSIkrW/zlSiz2PrqFuAJVUXXWrFmNnnvmmWcif48cOZLXX3+9s4fVrojxxyB/WARlBcgPn4fkdDTDT0WZncItFdgHqrv0lP7Z3L/gGJxuBxXBgq4ddDshhGDktScx9LLj0B22yELfZeOxOyGrZ9sbxonctRnjrb+pzKrs3io2yBVD7ZxwAcsExNUfX7+I1x9ZxEX3nBD3vt2Fm/55Nov/u5LjzlexJymDlBWxakMBIV+A0m9VjE3S6KGweCkyiuUqQk2F+j8ey1X/Uaoyx/Z1SGkgN6gwBTF0fLNq+S3SZyh8/z/kztYL5XYWqUN7EuqRAmXV2DNjE5phy5WM4haUpluwWQX0zqBJIc7+I6NYmVuqwxW+efJ7kYbRLPygQwuIhrHZlVs1GOgwC5lF96JbuAX3F4RuQ5t1BdgcyDVLkd+oytI/b0indlsJZd8rd0Lq0J6MPmwgQw7s3ZXD7RBsSY4uF1YdifG/V+oX+dJdyCVvxbSfrEzMLQgw5MDe3PLvc+k5aM+trV3FYb8cw60vnEtSqrowpo9WbrrKNTsoW/4zIW+AtOG9cZrtLagqbelQ8VVnD5OZCymZqg1OUT5yneqkIIbHHmgseqtEFXZtRspuUmMoTlee0Zr7qh2LiMZNLFXOW2jPIzStkcBqRvi5DrVc1bs1LfYP9t2rXDdF5PVHO+1ayO6lXFInXIyRoxbl4qXrAUgZ3HWxPxZ7SF0l5A1Au+guAOTKz5Fhd0prVITdgp1T4K67kz6qD8KmU7WxgPx3lBUpd/IoSDUFZHV5i/sm4hYUQiAGHwCA8dYTUJxP0O6Chu6ltkjLVtYyby2UdU6LjTYJu/diFFeyNbdgWLw4urm4iib+Wou76izLFewzVdot2sYSV12AGDAa/dIH0K98FG3cZHKOqM9G0pMcpA3f9yxW+xPa5NMQeQOg9xAI+pE/r2x1e+nzQF21WoBjaNeyP2BzO8maMBgMSeGiNQDkHT1GWaM0HeqqGvWebEQilitAHDwVEFCp3PNF/ccj4oiPEUIo1yAgd3Zun8EWiYir2N5H60VETQtPl1iuYrD8RCxrUYRka3FX4abNHdH6JkxrDbEt9kkscdUN6H3CePQktSDkHTMG3WUFPO61ZPaMWDvEiEMBkOu/a22P+nir9B5xZ6Xuyww4fVLk75wjRpA6tKdy8YRjqVoKak9UXOX2R0w7T30PY4+gqP/4uMcs+pi9Cbevj3vfDiHiFoxtTTFiqdDeFeLKFoM4ac2yFrZc+aOIK1/YLWhZrvYlQqEQl156KdOnT2fZsuadEjqabhPQvj/jyk3nkL/+irLvtzDgjMO6ejgWe4AYMylSc0aMmID87BXYshpphFoOjLZcglHJOXIk4+49i+r1uxh88dH1L6Rlq5irKEHtUsqExRWAdtBUOMhsgZJAFXIxcLQKjN+2BimNLhXL0jBUhhqi3nLS1j4x1bnqgmxBrQ23oJQtxlwB9cIpiuVKms+Jjgw0j8Wt2QIyGEAueg25fR1i4BjE5NPisqjurxQWFrJ+/Xq+/PLLLjm/Ja66CZnjBpA5LraUb4vuixh2cP3fadlKMFUUQdEO6Dkw6j71Na72zlIKHYUQgt7HHwjHH9j4+dQsJWCqy4Am1gZvrRIUzqTYy2C0J9m9VWB8TTkU50Nu/2abyFAoyo4dQAOXYKyFK1stxdCVRURtrYsTYYSUwNJ0RBQhKZyqDZL0eWj2SYStWR0Z0B6p0xW/5Up++jJyxSL1d8lOlQ0764oubdJ++umnN3tu5syZXHzxxXg8Hi644IJmr59xxhmcddZZlJWVcfnllzd7/YILLuDkk0+O6fzLli3j4YcfxjAM+vTpg9vtZuPGjYRCIS677DJmzpzJFVdcQUVFBbNnz2b+/Pnxv8k9xPJBWFi0I01rZol+wwGQO1pxE4UtV5lWIkNMhGvQRSvHEC7DkIDVqj0QQiAGKbew3NQ81k7WVmG8NKdzBhOnSxDACAuTsAvQRBqGKbhE1xQRbcPyoxnm8y0Jv0hAezS3YFhcdaBbMFKnKz7LlawoQq5cDEJDHH8h2J3Idd/A1jUdMMi9i61bt/L8888zYMAAxowZw/z58/nPf/7D3//+d3bs2MG8efPIzc3tEmEFluXKwqJj6TcCVn2pxNWh06NuIs0CopblKkYi4qoUcpokf0RqXGV26pAaIoYfglz1pWqnddjMRhYG+eNilbzQGYTiC2YHMMKB44EmGa4NXIJdYjEJjysYvYWMFn6vbYqrKNmC4VIMHRnQnqDlSq75GqREjJ6INv5oDG8t8vM3MJZ/jD5obNsH6CBaqzmZlJTU6utZWVntUrNy0KBBpKamsnTpUrxeL2+88QagGsNv3LiR4cOH7/E59gRLXFlYdCCi7zDVlWbX5pb7ikVirizLVSw0cgs20aPSLNEgUjM6fVwRBo6GpBRVpb9oh2qLgyrCKZd/0nnjCMRXhgEaW64azdeuDGbHrFUlNJBmHFkT158Wtmi15ApuzXLl7/hSDEK3qzkbDDR3S7ZCONNYjJqo/j9wCnLJ2yqOs7oMkbr31rbbU1wu9X0ZhsHDDz/MmDHKYlxSUkJ6ejqFhV1bDsVyC1pYdCTpOeBOVdaKyuJmL8tgQLm3hIBw3zyL1mnVLWjWv+pKy5Vui1wM5TcLI8/LHz5T88DsY9jhJOAWRGimcJGN4666ssZVmFZcg21brlopxeDrnjFX0lcHu7eq0iP9VLkekZSCGDoepET+1PkZcN2RSZMm8fLLLwNQVFTEL3/5SwoKur6ziSWuLCw6ECEE9BoMgNz1c/MNKksACWnZUQNxLaIQKSQaRVxVV5jbdJ24AhC/OAE0XbkGC7Ygywsj1fq1Ccd3ziAScAsC9QIl2CDuqitrXIVpVVwlZrmSwYA6nqZ3bM+/Bm7NmCnKV0H6OX0RDUXt8EMAkFtWt+MA916uvvpqvF4vM2fO5KKLLuKmm26if//miSSdjbWaW1h0MKL3YOTmlVDwM4ye1PjFSE9BqwxDzLiS1UXe70ULNo4NkmbMlYijr2BHINKyEQcfi/zuI4zXHgFNg4AfMfIXiAEjYXUnXBgTcAsCSqB4a5W1KinFPFbXugUBlTHoI7q4Mlq3XAlHknLLNa1z5a8PZu/QWLJY6nQ1QRbvAEDk9mv0vBgwComAnRuRfl9j4bWfMHHiRCZOVNbhlJQU5s6d22ybvn378umnn3b20CJYlisLiw4m3HNO7mre0FdWqLiARHoK7q8IISLWK4e3pvGLYbdgF1uuAMTk02DwOBVE7amBfiMR0y/qvAEkarkKi7GGQe1dWeMqTCtV2ustV3FmC4YLiHZ0M+VEiogW71T/92jsRhbuVOg5QH0O+d2kWK1FMyzLlYVFR9NzECCgcLsKaG14sQtbrjItcRUXaVlQVoDd2yTzrhvEXIURNjvaab9TcTPSgF6DVFFRXwy9JtuDRGKuoF6gNCzH0JU1rsK0Uj0+HHPVYm2zlrIFI8HsHSyu9PjFlSzJB0Dk9Gn2mhgwCrl7KzJ/I2LwuHYZokX7YlmuLCw6GOFMgh69VZZT0fZGr1llGBJDRLFcyVAQaqtVckAcTZs7EiEEotcgRO8hnV6tXZriSOjxiqvmlqtw83HRpW5B830YzYuwJm656oRgdog7oF1KWW+5ipIAIXqbPSyjWMNjPr7FHtHWZ2iJKwuLTkD0GgREWQxLzAU0q2cnj2gvx8wYtPsauAWrygAJKRkttxran4hk0MUbc9VNLVd6y9XjE84W7IwCohC/W7CuSlnVXMmIaAVxzSQZCraoAq9x4HK5KC0ttQTWHiClpLS0NFIOIhqWW9DCojPoPQRWfQkNMgalr04VwtRtlriKl7QoMVdWj8bGBBPNFowWc+Vv/FpXsCfZgmHx5Pc0qt8lzQKiHdpXEOLPFqwqVf+nRS/PIlLSIb2HyjYu2QlNgt5bo2/fvuTn51Nc3Lw0jEXsuFwu+vZtuayKJa4sLDoB0XuIylYqaFCOoVjFVNCjj2VpiZNwIVFHg5grq0djE8LiKk63oLA7zYKX/vqCl93CctVKQHtb2YK6TQmvgF9VZA+Lqc7oKwjx17kK13BrQVwBiF6DkZUlyIItzTIKW8NutzNo0KCYt7dIDMstaGHRGWT3Vgt/ZQmythIAWRwOWO2kopL7Euk9AHB4quqfs8paNCaYoLUpnC3ob2i5MrPqOtp91hq6eQMSRaC0abmCegHVsByDr5MC2uN0C8rKEgBEWisV2PMGqP+bxHFadA8scWVh0QkITQMz7iriGiwyLVc5sd91Wpik54Buw+GrQZoXSGm5BRuToOUqehHR7uAWDFt/ogW0txFzBdGD2iPiqmNFYzhDWMYac1Udg+XKtFZJS1x1SyxxZWHRSYhIpfZN6v8CFdwuwnegFjEjNA2ye6kHpbvU/xVW5mUj2jPmqrOy6lrDLMQpW7VcxSmu/r+9e42Nqlz3AP5fvU0vDJRCC55Sq2gVpVtkixEvocGEIrQFJEQukUaq0Q+IUYxGRA/xg4oNxMhRvxE/IBoJ5ygbA4hnG42xeCjdCHLCAQQRaKG0tEAv0+lc3vNhzZpLO7e15u2aNdP/LzFth/aZd6ZP0sf38rxmLQtm6jwteEPdc6X4ZmjDKvF1Ib96EULo29ROI4/FFZFJlPJ7AADi9L8gHL3qzFVmVmBGi3RRJqj9f0Rnm3ryyb8syOIKgPFlwTCnBbXO5iO+8TsKJY67BaO2igh3YtCiy4KBDe2RlwWVgrHAmEK1CL7OzelWw+KKyCy3TgPyxwLd7RBN/wAggNI7Izc+pOgm+mauOlvVU1MuJ1AwFop2Zctol+iyYLiZqyQWV4FWDAZOCwL+sYug4koMqE1FFa3wGil6iyttWdAe4zL3oNkrshYWV0QmUTIyoUx7EAAgWv5bfezuB5M5pJSmTNRmrloDm3pLkn9hq2Wk27JgZuT7+WKdFgTU+wUBhHZp1z7PHeHiSseyoHC71OuSMjKBAnvU7/Xvu2r/K+EhklwsrohMpMyaF/jjNXYClMpHkjugVDbpNvXj5XMQreo+Nu5fCxC+ZUFFxvU3g1Y4LRhPnyude658M1ew0sxVv+8EbL49Zld/xfc/E4IzV5bDPldEJlIKS5Dx9FsQZ45CqXw0udeJpDhlbBGcuWNhG7gJ0fyd+tit05I8Kgvxz1zpW3ZWsnPUPlfBxZV/WXCEi5BosqL0uYqnG7029pBWDNrMVYGEAUahp7jq8xVX4TqzD+VfFuSJQavhzBWRyZTiKch4pC56DxuKy43ioMMAOblA6Z3JG4zVGF4W1FoxBC0LDprTsiAqrUgMLvp8/DNXWdFmrnxjd4Yprqx0cbOvD15cxdX4YvX31Xsdou9m7O8n07C4IqKU1Tml0r9Upcyq5kxgMKPF1ZAiRnjcaiwlQ/csmFRRupwH9lzF3tCuFVfC41Zfo5JhqbsFtSbDShyXjytKRuDqmw4uDVoJlwWJKGUN5hcio/7f1R5Xt/8t2cOxFq0Vg96CyH81zEDoR1ue/06+pIgw+yOEiGvPlWLLV5c7tZmrgcBm9hF/XXquv9GzLAhAmTgFovUPiI5WKLdNNzhAko3FFRGlNKVoMi++DsfozFXOkOUzs5bOYok0+6PdgZiVrTaXjWTohnanSZvZgZDN+EJ4o29U15YF82PPXAEAitVTs+i8ZHx8JJ0liqu2tja89tpruHbtGm6//XZs2bIFBQWhGwxbW1tRW1uLW29VN/BNnDgR27dvT8ZwiYisz2hxNfRSY6cFTgoCkYsrrWVErBm6oa0YBvrUjyPdhgFQZ8aystWxu91Rly9Fv86Zq+Ip6oxcB4srK7HEnqt33nkHq1atwoEDB1BZWYlPP/102PecOHECdXV12LNnD/bs2cPCiogoGqPLgv6ZqwG18/2gBRqIAlB8r0O4h2xo9997GGO/3dDTgtoM1kifFNTE2+vKv+cqvuIK2sXvnW0QXl6DYxVJL65cLheam5sxf/58AMDSpUtx4MCBYd/3+++/4/Tp01i8eDHq6+tx6tQps4dKRJQ6DM5cKRmZvpkVoc4KWaGBKBB75ipmcTVkQ7u/O7tJryveTe3+PVfxLQsquQXAmPFqMc1rcCwj6cuC3d3dGDNmDLJ8l3IWFxejvb192PfZbDYsWrQIK1aswM8//4y1a9di3759yMmJ7//KTpw4IXXcQ7W0tDC2ibHNiG/ESOYZf1fpFduoeHNshm8v0r+O/652+45TS0sLpitZyMYgjh85DHv3JZQD6O5z4K8E349E3s8x1y7iTgA93V04GxQn72Y77gbQ73LjdJT4iseNGVCLqpYjRzCh9STKAHT09ONSjHHJyIN7PF7YAJz47SgG80ILp+D4f+vpRiaAY2fOwXO+La7YU212jO3txtn/+Qk3Su5IeKyUOFOLq/379+P9998Peay8vHzYSY1wJzfWrVvn/7yqqgpbt27FuXPnMG1afE0DKysrYbONzDHtlpYWPPDAA4xtUuyRjO90OhMqkEYqz/i7Sp/YZuSY8Ljh/acAFAV/n/Vg3KfhtNfsOfqfQFc/7ru7AuKCB+J/gaLJpZiYwPuR6PspLtnh/e0fsOfnhsQRF/4P3mYgf9z4mPE9P2+H4nHj7zPug3C3Q5wCiqeUY1KUn5OVB56j/wUM9KDynruhTPi3sPGF1wPvPwcBRcGMhx6O2aFd4+05C3HtAqaOtSHDFyvRPKPEmFpcLViwAAsWLAh5zOVy4aGHHoLH40FmZiY6OjpQUlIy7Gd37NiB2tpajB8/HoB6/Fab7SIioiBB3dkNtRnICdrUboUGokDkRpz+PVdxrGLY8oD+HnVpcMCkewU18SwLOrRN9gVxF1YA/PuuuKndOpK+5yo7OxuzZs3Cvn37AADffPMN5syZM+z7mpubsXv3bgDA4cOH4fV6MXXqVFPHSkSUEoyeFNRo+5AG+gOn6pJ59Q0QKJ6M7rkCQk8MOnrUz/PGyBlfLHEVV8bGpEz0bWpncWUZSS+uAGDTpk3YtWsXFi5ciCNHjuDll18GAHz55Zf46KOPAAAbN25EU1MTamtr8cEHH2Dr1q3IiNbThIhotDJ6UtBH8f1xF45eoL9XfTDfLmNkxvlnrkJPCwpfcRVXd/4838nAgT7/dTFKvP2kEhXPFTjazJXegm/CLWqn+etXQ++EpKSxxLpaaWkpduzYMezxlStX+j+fNGkSPvvsMzOHRUSUmvTM5oSTG1SEONTiSjFrhieSRE8LAoHeUX03gH59p/ISpm1jidaKYcBXyObqnLnKygaKJgHXLgPX2oDJtxkbI0nDqR8ionSjZx9SONoMj6PX/OWzSCIWV/G/Vq13lOi7oe69AuLvhJ6oOJYFhW+WUMnX/15rS4Pcd2UNLK6IiNJNvI01I9EKKUev+l/wY8kS6X4+IzNXvdf1XzOTIMW3LCiiLQsanLkCENRMtFX/z5J0LK6IiNKNv+AwOHMVtCwYKK6SvOcqaOZHCBF4XE8hqc1cXbsMeNxATi6UnJFp0TNMPJc3+99r/V3jlQm3AABE1xXdP0vysbgiIko37sRmrhRfISV6rqt/8BXF0B98mRQlI+QCZD8dhaRiV1v54KLvho9xEyWOMAZ/ceiO/D2JFLLa5eUsriyBxRURUZrxn6AzeFoQ9kL145U/1Y9jCtVrcZIt3Ik7PYXkeF8PRa2IGWticRXHacHA4QEDhWxhCQAFuN4B4YlSwJEpWFwREaWbRPdc2Yt8cZyhXydb9vB2DELPEui4YgCBpqrKuAkSBxeDrmVBAxvas3OAcRMA4eUdgxbA4oqIKN3I2HMVPOulLaclW7jZHx19rpSsbLUA0UwslTm66OJqIprg4QEuDVoGiysionSTYCsGRVFCCirFzOWzaMLN/gzq6+mllN8b+LzsLlkji82E4krxFVei67Khnyd5WFwREaWbRJuIAlBKbg18Mbk8wQFJos2muQzuuQKgzJijzszdPQsoukXyAKPIjL4sKIQ3cNVQrsHDA9rr4cxV0lmiQzsREUnkTrCJKABMqQBONQMAlFssco9ruJkrnUugyi1TkfnSf0geWBxizVwN9ANCALY8KJnG/jQrRZMhwHYMVsDiiogo3WgFR1YCM1eVjwJdl4GSciiFxZIGlqCsMPcLJrp53yyxiiuj9woG454ry2BxRUSUbhK9/gaAYsuDMm+1pAFJEq5ASXTzvllitWJIpDu7Zsw49T1y9EIMDhiPQwnjnisiojQjdJygSylRTgsmMktnBsVXGIpIrRj8dx0aL64UJSPQu6un23AcShyLKyKidCNh5sqKtKao2v18wutRr8MBrP9aYywLCt9mdiWRmSsAKNSKq67E4lBCWFwREaUbCacFLUkroLTX5/vozcxW20dYWcw9V8bvFQym+K70ETdZXCUTiysionQj47SgFWnFojYz59tX5DF6zY+ZYnVol3VB9jjf4QPOXCUViysionSTIvuQdMvRiivfZm1fceXV9mJZmTZG12D4f0+0O7uPf+aKxVVSpf1pQSEEAGBwMEJCS+J0OhnbxNgjFV/LEy1v4mVGnvF3lR6xzcgxT0Y2kGtHBhQoOl+Dld9Pb04+RK4disuNDKcTor8f3lw7nHnjkGXhcQOAQAa8uXZAyUTmkHhOpxOeQReQa4diK0BGAs8nxhTBm2vHoMOhfq0zz0gORaT5O9/T04PTp08nexiUYu666y7Y7fFPzzPPSC/mGJlBb56RHGlfXHm9XvT19SE7OwU2PFLSCSHgcrlQUFCAjIz4V82ZZxQv5hiZwWiekRxpX1wRERERmYnlLBEREZFELK6IiIiIJGJxRURERCQRiysiIiIiiVhcEREREUnE4oqIiIhIIhZXRERERBKxuCIiIiKSKO2Lq71792LhwoWorq7Gzp07E463evVq1NTUYPHixVi8eDGOHTuGpqYm1NXVobq6Gh9++KHumL29vaitrcWlS5cAIGK8kydPYunSpZg/fz42btwIt9utO/aGDRtQXV3tH//3339vOPbHH3+Mmpoa1NTUoLGxUerYw8WWOXaZRnuOhYsv63fFHAsY7XmWijkWKb6V84wkEWnsypUrYu7cuaK7u1v09fWJuro6cebMGcPxvF6veOyxx4TL5fI/5nA4RFVVlbhw4YJwuVyioaFB/Pjjj3HH/O2330Rtba2YPn26uHjxYtR4NTU14ujRo0IIITZs2CB27typK7YQQtTW1or29vZh36s39i+//CKWL18unE6nGBwcFPX19WLv3r1Sxh4u9sGDB6WNXabRnmPh4gshJ8+YYwGjPc9SMccixbdynpE8aT1z1dTUhNmzZ6OwsBD5+fmYP38+Dhw4YDjeuXPnAAANDQ1YtGgRPv/8cxw/fhzl5eUoKytDVlYW6urqdD3Hrl27sGnTJpSUlABAxHitra0YGBjA/fffDwBYunRpzOcZGtvhcKCtrQ1vvvkm6urqsG3bNni9XkOxi4uL8cYbbyAnJwfZ2dm44447cP78eSljDxe7ra1N2thlGu05Fi6+rDxjjgWM9jxLxRyLFN/KeUbyZCV7ACPp6tWrKC4u9n9dUlKC48ePG4538+ZNPPzww3j77bfhcrlQX1+P5557bthztLe3xx3z3XffjTnm9vb2YY8XFxfHfJ6hsTs7OzF79mxs2rQJdrsdL7zwAnbv3o2KigrdsSsqKvyfnz9/Hvv378fTTz8tZezhYu/cuROHDx+WMnaZRnuOhYsvK8+YYwGjPc9SMccixbdynpE8aT1z5fV6Q26PF0IkdJv8zJkz0djYCLvdjqKiIixbtgzbtm2T+hyRxizjtZSVleGTTz5BSUkJ8vLysHr1avz0008JxT5z5gwaGhrw+uuvo6ysTOrYg2NPnTpV+thlYI4NJzvPRnuOAcyzoVIpx4bGt3KekTxpXVxNnjwZHR0d/q87Ojr808pGHDlyBIcOHfJ/LYRAaWmp1OeINOahj3d2dup+nlOnTuG7774LGX9WVpbh2C0tLXjmmWfw6quv4sknn5Q69qGxZY9dFubYcDJ/V8wxFfMsVKrkWLj4Vs4zkieti6tHHnkEhw4dQldXFxwOBw4ePIg5c+YYjtfT04PGxkY4nU709vbi66+/xvr16/Hnn3/ir7/+gsfjwbfffpvQc8yYMSNsvNLSUthsNrS0tAAA9uzZo/t5hBB47733cOPGDbhcLnz11VeYN2+eodiXL1/G2rVrsWXLFtTU1Egde7jYMscuE3NsOFm/K+ZYAPMsVCrkWKT4Vs4zkiet91xNmjQJr7zyCurr6+FyubBs2TLcd999huPNnTsXx44dw5IlS+D1erFq1SrMnDkTmzdvxrp16+B0OlFVVYUnnnjC8HPYbLaI8bZs2YK33noLvb29mD59Ourr63XFnjZtGp5//nmsXLkSbrcb1dXVqK2tNRR7+/btcDqd2Lx5s/+xFStWSBl7pNiyxi4Tc2w4WXnGHAtgnoVKhRyLFt+qeUbyKEIIkexBEBEREaWLtF4WJCIiIjIbiysiIiIiiVhcEREREUnE4oqIiIhIIhZXRERERBKxuCIiIiKSiMXVKLJjxw48/vjjGBwcBACcPXsWjz76KPbv35/kkVG6YI6RGZhnZHUsrkaRlStXIicnB1988QUuXryIhoYGrF+/HgsWLEj20ChNMMfIDMwzsjo2ER1lfvjhB2zYsAF2ux319fUhHYAPHjwIm82GqqqqJI6QUh1zjMzAPCMrS+vrb2i4iooKOBwOVFZWDrtaobq6OkmjonTCHCMzMM/IyrgsOIq0t7djzZo1WL58OZqbm3H27NmQf3/qqaf8exiIjGCOkRmYZ2R1LK5Gia6uLqxZswZLlizBxo0bUVdXh8bGRv+/u1wueL1e5OTkJHGUlMqYY2QG5hmlAhZXo0BPTw+effZZVFVV4cUXXwQAvPTSS/j111/R1NQEAPjjjz9QUVGRzGFSCmOOkRmYZ5QquKGdAAC7d+9Gf3//sL0LRLIwx8gMzDOyAs5cEQDg5MmTuPfee5M9DEpjzDEyA/OMrIAzV0REREQSceaKiIiISCIWV0REREQSsbgiIiIikojFFREREZFELK6IiIiIJGJxRURERCQRiysiIiIiiVhcEREREUn0/3PQ7/C1DlxEAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 576x230.4 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "loc_lengths= [250,2000,16000]\n",
+    "loc_lengths= [200,2000,20000]\n",
+    "dt_adv     = [0,300,600]\n",
+    "alpha_val  = [0.01,0.01,0.01]\n",
+    "fig,axes = plt.subplots(1,3,figsize=(8,3.2),sharex='all',sharey='all')\n",
+    "nlen = len(loc_lengths)\n",
+    "for i in range(nlen):\n",
+    "    axes[0].plot(Loc_length_sens(quad ,32,loc_lengths[i],dt_adv[0],dt=0,alpha=alpha_val[0]) ,color=plt.cm.magma((i+1)/(nlen+1)),label=str(int(loc_lengths[i]/100.)),lw=2,alpha=1.0)\n",
+    "    axes[1].plot(Loc_length_sens(quad ,32,loc_lengths[i],dt_adv[1],dt=1,alpha=alpha_val[1]) ,color=plt.cm.magma((i+1)/(nlen+1)),label=str(int(loc_lengths[i]/100.)),lw=2,alpha=1.0)\n",
+    "    axes[2].plot(Loc_length_sens(quad2,32,loc_lengths[i],dt_adv[2],dt=1,alpha=alpha_val[2]) ,color=plt.cm.magma((i+1)/(nlen+1)),label=str(int(loc_lengths[i]/100.)),lw=2,alpha=1.0)\n",
+    "\n",
+    "x_orig =np.array([0,99,100,199,200,299])*100\n",
+    "x_advected = x_orig-da_const_dt0['dt']*m_const['u_ref']\n",
+    "x_advected[-1] = 30000\n",
+    "x_advected = x_advected/100.\n",
+    "axes[0].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "x_advected = x_orig-da_const_dt1['dt']*m_const['u_ref']\n",
+    "x_advected[-1] = 30000\n",
+    "x_advected = x_advected/100.\n",
+    "axes[1].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "x_advected = x_orig-da_const_dt2['dt']*m_const['u_ref']\n",
+    "x_advected[-1] = 30000\n",
+    "x_advected = x_advected/100.\n",
+    "axes[2].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "\n",
+    "\n",
+    "# axes[0].plot(L2_ensemble_limit(quad ,32,dt=0,alpha=alpha_val[0]),'k',label='no loc')\n",
+    "# axes[1].plot(L2_ensemble_limit(quad ,32,dt=1,alpha=alpha_val[1]),'k',label='no loc')\n",
+    "# axes[2].plot(L2_ensemble_limit(quad2,32,dt=1,alpha=alpha_val[2]),'k',label='no loc')\n",
+    "plt.legend(ncol=1,title='loc length [m]',bbox_to_anchor=[1,0.1],loc='lower left')\n",
+    "# plt.legend(title='loc length [m]',loc='lower left',ncol=2)\n",
+    "axes[0].set_title('lead time short')\n",
+    "axes[1].set_title('lead time medium')\n",
+    "axes[2].set_title('lead time long')\n",
+    "axes[2].set_xlabel('x in meter')\n",
+    "fig.subplots_adjust(wspace=0.1)\n",
+    "\n",
+    "axes[0].set_ylim(-0.8,1.4)\n",
+    "axes[1].set_xlim(0.,300)\n",
+    "axes[1].set_xticks(50*np.arange(0,6));\n",
+    "axes[2].legend(title='   sensitivity \\nloc length [dx]' ,ncol=1,bbox_to_anchor=(1., 0.8),loc='upper left')\n",
+    "axes[0].set_xlabel(r'$x_i$',size=13)\n",
+    "axes[1].set_xlabel(r'$x_i$',size=13)\n",
+    "axes[2].set_xlabel(r'$x_i$',size=13)\n",
+    "axes[0].set_ylabel(r'$\\frac{\\partial j}{\\partial x_i}$',rotation=0,size=17,labelpad=10)\n",
+    "axes[0].set_ylabel(r'$\\frac{\\partial j}{\\partial x_i}$',rotation=0,size=17,labelpad=10)\n",
+    "axes[0].set_title('lead time: 0 s')\n",
+    "axes[1].set_title('lead time: '+str(da_const_6['dt']) +' s')\n",
+    "axes[2].set_title('lead time: '+str(da_const_62['dt'])+' s')\n",
+    "label_axes_abcd(fig)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# The incorrectly localized sensitivity plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def Loc_length_sens_wrong(quad,nens,loc_length,dt_adv,alpha=None,dt=0):\n",
+    "    \"\"\"\n",
+    "    Function that calculates the wrong localized sensitivities. This means once only localizing the cost function covariance, once only localizing B, and once not applying localization  \n",
+    "    \"\"\"\n",
+    "    X =quad['bg'][:,:nens]\n",
+    "    dX =  X.T - np.mean(X,axis=1)\n",
+    "    dX = dX.T\n",
+    "    J = np.zeros(nens)\n",
+    "    if dt == 0:\n",
+    "        X_J =quad['bg'][:,:nens]\n",
+    "    else:    \n",
+    "        X_J =quad['bf'][:,:nens]\n",
+    "    dX_J =  X_J.T - np.mean(X_J,axis=1)\n",
+    "    dX_J = dX_J.T\n",
+    "    for i in range(nens):\n",
+    "        J[i] = sum_mid_tri(X_J[:,i])\n",
+    "        #J[i] = sum_triangle(X_J[:,i])\n",
+    "    dJ = J-np.mean(J)\n",
+    "    B = np.cov(dX,ddof=1)\n",
+    "    dji = dX_J*1\n",
+    "    dji[0:100,:] = 0. \n",
+    "    dji[200:300,:] = 0. \n",
+    "\n",
+    "    da_const_tmp = set_da_constants_22(loc_length=loc_length,dt=dt_adv)\n",
+    "    m_const_tmp  = set_model_constants_22()\n",
+    "    \n",
+    "    C = loc_matrix(da_const_tmp,m_const)\n",
+    "    cov_dJdX = np.dot(dJ,dX.T)/(nens-1)\n",
+    "    C_adv = C*1.\n",
+    "    for nn in range(m_const['nx']):\n",
+    "        C_adv[:,nn]      =semi_lagrangian_advection(C[:,nn],m_const_tmp['dx'],+m_const_tmp['u_ref']     ,da_const_tmp['dt'])\n",
+    "    sum_loc_cov_adv_djidX=np.sum(C_adv*np.dot(dji,dX.T),axis=0)/(nens-1)\n",
+    "    sens_locB        = L2_regularized_inversion(C*B,cov_dJdX,alpha=alpha)\n",
+    "    sens_locJX       = L2_regularized_inversion(B,sum_loc_cov_adv_djidX,alpha=alpha)\n",
+    "    sens_loc_nonreg  = np.dot(np.linalg.inv(C*B),sum_loc_cov_adv_djidX)\n",
+    "    \n",
+    "    return sens_locB, sens_locJX,sens_loc_nonreg\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x230.4 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "loc_lengths= [200,2000,20000]\n",
+    "loc_lengths= [20000,2000,200]\n",
+    "dt_adv     = 300\n",
+    "fig,axes = plt.subplots(1,3,figsize=(8,3.2),sharex='all',sharey='all')\n",
+    "nlen = len(loc_lengths)\n",
+    "for i in range(nlen):\n",
+    "    sens_locB, sens_locJX,sens_loc_nonreg = Loc_length_sens_wrong(quad ,32,loc_lengths[i],dt_adv,dt=1,alpha=0.1)\n",
+    "    axes[0].plot(sens_locJX      ,color=plt.cm.magma_r((i+1)/(nlen+1)),label=str(int(loc_lengths[i]/100.)),lw=2,alpha=1)\n",
+    "    axes[1].plot(sens_locB       ,color=plt.cm.magma_r((i+1)/(nlen+1)),label=str(int(loc_lengths[i]/100.)),lw=2,alpha=1)\n",
+    "    axes[2].plot(sens_loc_nonreg ,color=plt.cm.magma_r((i+1)/(nlen+1)),label=str(int(loc_lengths[i]/100.)),lw=2,alpha=1)\n",
+    "\n",
+    "x_orig =np.array([0,99,100,199,200,299])*100\n",
+    "x_advected = x_orig-da_const_dt1['dt']*m_const['u_ref']\n",
+    "x_advected[-1] = 30000\n",
+    "x_advected = x_advected/100.\n",
+    "axes[0].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "axes[1].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "axes[2].plot(x_advected,[0,0,1,1,0,0],'k--',label='ref')\n",
+    "\n",
+    "plt.legend(ncol=1,title='loc length [m]',bbox_to_anchor=[1,0.1],loc='lower left')\n",
+    "# plt.legend(title='loc length [m]',loc='lower left',ncol=2)\n",
+    "# axes[0].set_title('non localized $\\boldscript{B}$')\n",
+    "axes[1].set_title('')\n",
+    "axes[2].set_title('')\n",
+    "fig.subplots_adjust(wspace=0.1)\n",
+    "\n",
+    "axes[0].set_ylim(-2,3)\n",
+    "axes[1].set_xlim(0.,300)\n",
+    "axes[1].set_xticks(50*np.arange(0,6));\n",
+    "axes[2].legend(title='   sensitivity \\nloc length [dx]' ,ncol=1,bbox_to_anchor=(1., 0.8),loc='upper left')\n",
+    "axes[0].set_xlabel(r'$x_i$',size=13)\n",
+    "axes[1].set_xlabel(r'$x_i$',size=13)\n",
+    "axes[2].set_xlabel(r'$x_i$',size=13)\n",
+    "axes[0].set_ylabel(r'$\\frac{\\partial j}{\\partial x_i}$',rotation=0,size=17,labelpad=10)\n",
+    "label_axes_abcd(fig)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Scatterplot for two different lead times\n",
+    "\n",
+    "this is relatively time consuming (roughly 2-3 minutes), but not time consuming enough for me to bother saving the data.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "t_start = 40\n",
+    "t_end = 100\n",
+    "n_rand = 15"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 5.27 s, sys: 104 ms, total: 5.37 s\n",
+      "Wall time: 1.36 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# just resetting a\n",
+    "m_const = set_model_constants_22()\n",
+    "da_const = set_da_constants_22()\n",
+    "sat_operator = reflectance_simulator\n",
+    "da_const_vr = set_da_constants_22(obs_loc=np.arange(25,299,50)) #changed direct point observations for variance reduction tests\n",
+    "# Run the model\n",
+    "states   = run_linear_advection_KF_22(m_const,da_const,reflectance_simulator)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "completed timesteps: 1  seconds spent computing so far: 7.0\n",
+      "completed timesteps: 11  seconds spent computing so far: 92.0\n",
+      "completed timesteps: 21  seconds spent computing so far: 175.0\n",
+      "completed timesteps: 31  seconds spent computing so far: 262.0\n",
+      "completed timesteps: 41  seconds spent computing so far: 354.0\n",
+      "completed timesteps: 51  seconds spent computing so far: 432.0\n",
+      "CPU times: user 8min 14s, sys: 10.1 s, total: 8min 25s\n",
+      "Wall time: 2min 6s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "import time\n",
+    "start_time=time.process_time()\n",
+    "\n",
+    "ndt_steps=3\n",
+    "#t_vec=np.linspace(0,1000,ndt_steps)\n",
+    "t_vec=[300,1000]\n",
+    "n_samples = (t_end-t_start)*n_rand\n",
+    "truth_idx = 0\n",
+    "vr_es        = np.zeros([ndt_steps,n_samples])\n",
+    "vr_es_ca     = np.zeros([ndt_steps,n_samples])\n",
+    "vr_is_ca     = np.zeros([ndt_steps,n_samples])\n",
+    "vr_real      = np.zeros([ndt_steps,n_samples]) \n",
+    "var_total    = np.zeros([ndt_steps,n_samples]) \n",
+    "ref_t = da_const['dt']\n",
+    "counter = 0\n",
+    "\n",
+    "\n",
+    "for t in range(t_start,t_end):\n",
+    "    for n in range(n_rand):\n",
+    "        i = (t-t_start)*n_rand+n\n",
+    "        counter = counter+1\n",
+    "        truth_idx = n\n",
+    "        for dt in range(len(t_vec)): \n",
+    "            da_const_vr['dt'] = t_vec[dt]\n",
+    "            \n",
+    "            vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad, dx = vr_reloaded_22(\n",
+    "                states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_vr,reflectance_simulator,\n",
+    "                obs_seed=i,model_seed=i,alpha=alpha_default)\n",
+    "            var_total[dt,i] = np.var(J_dict['bf'],ddof=1)\n",
+    "            vr_es[dt,i]     = vr_t\n",
+    "            vr_real[dt,i]   = vr_r\n",
+    "\n",
+    "            vr_t, vr_i, vr_r,J_dict,dJdx_inv, bla_quad, dx = vr_reloaded_22_locsens(states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_vr,reflectance_simulator,sens_loc_flag=1,\n",
+    "                                                                 sens_loc_length=sens_loc_length,\n",
+    "                                                                 obs_seed=i,model_seed=i,quad_state=quad)\n",
+    "            vr_es_ca[dt,i]     = vr_t\n",
+    "            \n",
+    "            vr_t, vr_r, quad, J_dict_LA     = vr_individual_loc_22(states[0]['bg'][t],\n",
+    "                            states[0]['bg'][t][:,n],m_const,da_const_vr,sat_operator,\n",
+    "                                                    advect_flag=1,quad_state=quad,obs_seed=i,model_seed=i)\n",
+    "            vr_is_ca[dt,i]  = vr_t\n",
+    "            \n",
+    "            \n",
+    "            \n",
+    "    if np.floor(t/10) == t/10: print('completed timesteps:',t-39,' seconds spent computing so far:',np.floor(time.process_time()-start_time))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculating the mean properties over all experiments\n",
+    "es    =np.sum(vr_es    ,axis=1)/counter\n",
+    "es_ca =np.sum(vr_es_ca ,axis=1)/counter\n",
+    "is_ca =np.sum(vr_is_ca ,axis=1)/counter\n",
+    "real  =np.sum(vr_real  ,axis=1)/counter\n",
+    "total =np.sum(var_total,axis=1)/counter\n",
+    "me_es    =np.mean(vr_es    -vr_real,axis=1)\n",
+    "me_es_ca =np.mean(vr_es_ca -vr_real,axis=1)\n",
+    "me_is_ca =np.mean(vr_is_ca -vr_real,axis=1)\n",
+    "\n",
+    "rmse_es    =np.power(np.sum(np.power((vr_es    -vr_real),2),axis=1)/counter,0.5)\n",
+    "rmse_es_ca =np.power(np.sum(np.power((vr_es_ca -vr_real),2),axis=1)/counter,0.5)\n",
+    "rmse_is_ca =np.power(np.sum(np.power((vr_is_ca -vr_real),2),axis=1)/counter,0.5)\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def vr_scatter_v6_v2(vr_tot1,vr_rea1,vr_tot2,vr_rea2,vr_tot3,vr_tot4,vr_tot5,vr_tot6,alpha=0.3,alpha2=0.5,color1='blueviolet',color2=plt.cm.viridis(0.8),color3='orange',\n",
+    "                  label1='',label2='',label3='',llabel1='explicit global',llabel2='implicit',llabel3='explicit local'):\n",
+    "    \"\"\"\n",
+    "    Slightly tweaked to only have 2 times but three methods \"\"\"\n",
+    "    \n",
+    "    fig, ax = plt.subplots(2,3,figsize=(8,5.5),sharex='all',sharey='all')\n",
+    "    \n",
+    "    color = color1\n",
+    "    vr_rea = vr_rea1\n",
+    "    vr_tot = vr_tot1\n",
+    "    m, b = np.polyfit(vr_rea, vr_tot, 1)\n",
+    "    ax[0,0].plot([-1000,1000],[-1000,1000],'k--',zorder=0)\n",
+    "    ax[0,0].scatter(vr_rea,vr_tot,c=color,alpha=alpha,s=5,zorder=1,label=llabel1)\n",
+    "    ax[0,0].plot(vr_rea, m*np.array(vr_rea) + b,'k',zorder=2) \n",
+    "    ax[0,0].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=100,zorder=2)\n",
+    "    ax[0,0].scatter(np.mean(vr_rea),np.mean(vr_tot),c='k',s=50,zorder=3)\n",
+    "    ax[0,0].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=10,zorder=4)\n",
+    "    ax[0,0].set_aspect('equal', 'box')\n",
+    "#     ax[0,0].legend(loc='lower center')\n",
+    "    \n",
+    "            \n",
+    "    vr_rea = vr_rea2\n",
+    "    vr_tot = vr_tot2\n",
+    "    m, b = np.polyfit(vr_rea, vr_tot, 1)\n",
+    "    ax[1,0].plot([-1000,1000],[-1000,1000],'k--',zorder=0)\n",
+    "    ax[1,0].scatter(vr_rea,vr_tot,c=color,alpha=alpha,s=5,zorder=1)\n",
+    "    ax[1,0].plot(vr_rea, m*np.array(vr_rea) + b,'k',zorder=2) \n",
+    "    ax[1,0].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=100,zorder=2)\n",
+    "    ax[1,0].scatter(np.mean(vr_rea),np.mean(vr_tot),c='k',s=50,zorder=3)\n",
+    "    ax[1,0].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=10,zorder=4)\n",
+    "    ax[1,0].set_aspect('equal', 'box')\n",
+    "    \n",
+    "    \n",
+    "    color = color2\n",
+    "    vr_rea = vr_rea1\n",
+    "    vr_tot = vr_tot3\n",
+    "    m, b = np.polyfit(vr_rea, vr_tot, 1)\n",
+    "    ax[0,1].plot([-1000,1000],[-1000,1000],'k--',zorder=0)\n",
+    "    ax[0,1].scatter(vr_rea,vr_tot,c=color,alpha=alpha2,s=5,zorder=1,label=llabel2)\n",
+    "    ax[0,1].plot(vr_rea, m*np.array(vr_rea) + b,'k',zorder=2) \n",
+    "    ax[0,1].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=100,zorder=2)\n",
+    "    ax[0,1].scatter(np.mean(vr_rea),np.mean(vr_tot),c='k',s=50,zorder=3)\n",
+    "    ax[0,1].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=10,zorder=4)\n",
+    "    ax[0,1].set_aspect('equal', 'box')\n",
+    "#     ax[0,1].legend(loc='lower center')\n",
+    "    \n",
+    "            \n",
+    "    vr_rea = vr_rea2\n",
+    "    vr_tot = vr_tot4\n",
+    "    m, b = np.polyfit(vr_rea, vr_tot, 1)\n",
+    "    ax[1,1].plot([-1000,1000],[-1000,1000],'k--',zorder=0)\n",
+    "    ax[1,1].scatter(vr_rea,vr_tot,c=color,alpha=alpha2,s=5,zorder=1)\n",
+    "    ax[1,1].plot(vr_rea, m*np.array(vr_rea) + b,'k',zorder=2) \n",
+    "    ax[1,1].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=100,zorder=2)\n",
+    "    ax[1,1].scatter(np.mean(vr_rea),np.mean(vr_tot),c='k',s=50,zorder=3)\n",
+    "    ax[1,1].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=10,zorder=4)\n",
+    "    ax[1,1].set_aspect('equal', 'box')\n",
+    "   \n",
+    "\n",
+    "    color = color3\n",
+    "    vr_rea = vr_rea1\n",
+    "    vr_tot = vr_tot5\n",
+    "    m, b = np.polyfit(vr_rea, vr_tot, 1)\n",
+    "    ax[0,2].plot([-1000,1000],[-1000,1000],'k--',zorder=0)\n",
+    "    ax[0,2].scatter(vr_rea,vr_tot,c=color,alpha=alpha2,s=5,zorder=1)\n",
+    "    ax[0,2].plot(vr_rea, m*np.array(vr_rea) + b,'k',zorder=2) \n",
+    "    ax[0,2].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=100,zorder=2)\n",
+    "    ax[0,2].scatter(np.mean(vr_rea),np.mean(vr_tot),c='k',s=50,zorder=3)\n",
+    "    ax[0,2].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=10,zorder=4)\n",
+    "    ax[0,2].set_aspect('equal', 'box')\n",
+    "    \n",
+    "    vr_rea = vr_rea2\n",
+    "    vr_tot = vr_tot6\n",
+    "    m, b = np.polyfit(vr_rea, vr_tot, 1)\n",
+    "    ax[1,2].plot([-1000,1000],[-1000,1000],'k--',zorder=0)\n",
+    "    ax[1,2].scatter(vr_rea,vr_tot,c=color,alpha=alpha2,s=5,zorder=1)\n",
+    "    ax[1,2].plot(vr_rea, m*np.array(vr_rea) + b,'k',zorder=2) \n",
+    "    ax[1,2].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=100,zorder=2)\n",
+    "    ax[1,2].scatter(np.mean(vr_rea),np.mean(vr_tot),c='k',s=50,zorder=3)\n",
+    "    ax[1,2].scatter(np.mean(vr_rea),np.mean(vr_tot),c='w',s=10,zorder=4)\n",
+    "    ax[1,2].set_aspect('equal', 'box')\n",
+    "    \n",
+    "            \n",
+    "    \n",
+    "    plt.subplots_adjust(wspace=0.05,hspace=0.05)\n",
+    "    \n",
+    "    ax[1,0].set_xlabel('variance reduction')\n",
+    "    ax[1,1].set_xlabel('variance reduction')\n",
+    "    ax[1,2].set_xlabel('variance reduction')\n",
+    "    ax[1,0].set_ylabel('estimated var reduction')\n",
+    "    ax[0,0].set_ylabel('estimated var reduction')\n",
+    "    \n",
+    "    ax[0,0].set_title(llabel1)\n",
+    "    ax[0,1].set_title(llabel2)\n",
+    "    ax[0,2].set_title(llabel3)\n",
+    "    \n",
+    "    x_max = np.max(np.hstack([vr_rea1,vr_rea2,vr_tot1,vr_tot2]))\n",
+    "    x_min = np.min(np.hstack([vr_rea1,vr_rea2,vr_tot1,vr_tot2]))\n",
+    "    \n",
+    "   \n",
+    "    ax[0,0].set_xlim(x_min,x_max)\n",
+    "    ax[0,0].set_ylim(x_min,x_max)\n",
+    "    plt.locator_params(axis='y', nbins=4)\n",
+    "    plt.locator_params(axis='x', nbins=4)\n",
+    "    return fig, ax\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
+      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x396 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ind_list = [0,1]\n",
+    "\n",
+    "fig,ax = vr_scatter_v6_v2(vr_es[ind_list[0],:],vr_real[ind_list[0],:],vr_es[ind_list[1],:],vr_real[ind_list[1],:],vr_is_ca[ind_list[0],:],\n",
+    "                       vr_is_ca[ind_list[1],:],vr_es_ca[ind_list[0],:],vr_es_ca[ind_list[1],:],\n",
+    "                       alpha=0.5,\n",
+    "                       label1='',#explicit global',\n",
+    "                       label2='',#implicit       ',\n",
+    "                       label3='')#explicit local ')\n",
+    "                       \n",
+    "#                        label1='lead time: ' +str(int(t_vec[ind_list[0]]))+' s',\n",
+    "#                        label2='lead time: ' +str(int(t_vec[ind_list[1]]))+' s',\n",
+    "#                        label3='lead time: ' +str(int(t_vec[ind_list[2]]))+' s')\n",
+    "ax[0,0].set_xlim(-190,75)\n",
+    "ax[0,0].set_ylim(-190,75)\n",
+    "\n",
+    "for i in range(2):\n",
+    "    rmse = int(10*rmse_es[ind_list[i]])\n",
+    "    me = int(10*me_es[ind_list[i]])\n",
+    "    ax[i,0].text(-180,30,'RMSE: '+str(rmse/10),ha='left')\n",
+    "    ax[i,0].text(-180,50,'ME: '+str(me/10),ha='left')\n",
+    "for i in range(2):\n",
+    "    rmse = int(10*rmse_is_ca[ind_list[i]])\n",
+    "    me = int(10*me_is_ca[ind_list[i]])\n",
+    "    ax[i,1].text(-180,30,'RMSE: '+str(rmse/10),ha='left')\n",
+    "    ax[i,1].text(-180,50,'ME: '+str(me/10),ha='left')\n",
+    "for i in range(2):\n",
+    "    rmse = int(10*rmse_es_ca[ind_list[i]])\n",
+    "    me = int(10*me_es_ca[ind_list[i]])\n",
+    "    ax[i,2].text(-180,30,'RMSE: '+str(rmse/10),ha='left')\n",
+    "    ax[i,2].text(-180,50,'ME: '+str(me/10),ha='left')\n",
+    "label_axes_abcd(fig,loc=(0.9,0.05))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Comparison between observations\n",
+    "\n",
+    "Should also take a minute or two"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "completed timesteps: 1  seconds spent computing so far: 7.0\n",
+      "completed timesteps: 11  seconds spent computing so far: 79.0\n",
+      "completed timesteps: 21  seconds spent computing so far: 156.0\n",
+      "completed timesteps: 31  seconds spent computing so far: 229.0\n",
+      "completed timesteps: 41  seconds spent computing so far: 303.0\n",
+      "completed timesteps: 51  seconds spent computing so far: 362.0\n",
+      "CPU times: user 6min 48s, sys: 8.35 s, total: 6min 57s\n",
+      "Wall time: 1min 44s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "import time\n",
+    "start_time=time.process_time()\n",
+    "da_const_sur = set_da_constants_22(obs_loc=np.arange(25,299,50),obs_loc_sat=np.array([]))\n",
+    "da_const_sat = set_da_constants_22(obs_loc=np.array([]))\n",
+    "t_start= 40\n",
+    "t_end = 100\n",
+    "n_ens = 15\n",
+    "# n_ens = 2\n",
+    "n_samples = (t_end-t_start)*n_ens\n",
+    "truth_idx = 0\n",
+    "vr_es         = np.zeros(n_samples)\n",
+    "vr_es_ca      = np.zeros(n_samples)\n",
+    "vr_is_ca      = np.zeros(n_samples)\n",
+    "vr_real       = np.zeros(n_samples) \n",
+    "var_total     = np.zeros(n_samples) \n",
+    "sat_vr_es         = np.zeros(n_samples)\n",
+    "sat_vr_is_ca      = np.zeros(n_samples)\n",
+    "sat_vr_es_ca      = np.zeros(n_samples)\n",
+    "sat_vr_real       = np.zeros(n_samples) \n",
+    "sat_var_total     = np.zeros(n_samples) \n",
+    "sur_vr_es         = np.zeros(n_samples)\n",
+    "sur_vr_is_ca      = np.zeros(n_samples)\n",
+    "sur_vr_es_ca      = np.zeros(n_samples)\n",
+    "sur_vr_real       = np.zeros(n_samples) \n",
+    "sur_var_total     = np.zeros(n_samples) \n",
+    "counter = 0\n",
+    "for t in range(t_start,t_end):\n",
+    "    for n in range(n_ens):\n",
+    "        i = (t-t_start)*n_ens+n\n",
+    "        #print(i,n_obs)\n",
+    "        counter = counter+1\n",
+    "        truth_idx = n\n",
+    "\n",
+    "        # point obs\n",
+    "            \n",
+    "        vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad, dx = vr_reloaded_22(\n",
+    "            states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_sur,reflectance_simulator,\n",
+    "            obs_seed=i,model_seed=i,alpha=alpha_default)\n",
+    "        sur_var_total[i] = np.var(J_dict['bf'],ddof=1)\n",
+    "        sur_vr_es[i]     = vr_t\n",
+    "        sur_vr_real[i]   = vr_r\n",
+    "        \n",
+    "        vr_t, vr_r, quad, J_dict= vr_individual_loc_22(states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_sur,reflectance_simulator,\n",
+    "                                              advect_flag=1,obs_seed=i,model_seed=i,quad_state=quad)\n",
+    "        sur_vr_is_ca[i]  = vr_t\n",
+    "        vr_t, vr_i, vr_r,J_dict,dJdx_inv, bla_quad, dx = vr_reloaded_22_locsens(states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_sur,reflectance_simulator,sens_loc_flag=1,\n",
+    "                                                                 sens_loc_length=sens_loc_length,\n",
+    "                                                                 obs_seed=i,model_seed=i,quad_state=quad)\n",
+    "        sur_vr_es_ca[i]     = vr_t\n",
+    "        \n",
+    "        \n",
+    "        # sat obs\n",
+    "        vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad, dx = vr_reloaded_22(\n",
+    "            states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_sat,reflectance_simulator,\n",
+    "            obs_seed=i,model_seed=i,alpha=alpha_default)\n",
+    "        sat_var_total[i] = np.var(J_dict['bf'],ddof=1)\n",
+    "        sat_vr_es[i]     = vr_t\n",
+    "        sat_vr_real[i]   = vr_r\n",
+    "        \n",
+    "        vr_t, vr_r, quad, J_dict= vr_individual_loc_22(states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_sat,reflectance_simulator,\n",
+    "                                              advect_flag=1,obs_seed=i,model_seed=i,quad_state=quad)\n",
+    "        sat_vr_is_ca[i]  = vr_t\n",
+    "        vr_t, vr_i, vr_r,J_dict,dJdx_inv, bla_quad, dx = vr_reloaded_22_locsens(states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_sat,reflectance_simulator,sens_loc_flag=1,\n",
+    "                                                                 sens_loc_length=sens_loc_length,\n",
+    "                                                                 obs_seed=i,model_seed=i,quad_state=quad)\n",
+    "        sat_vr_es_ca[i]     = vr_t\n",
+    "        \n",
+    "        \n",
+    "        \n",
+    "    if np.floor(t/10) == t/10: print('completed timesteps:',t-39,' seconds spent computing so far:',np.floor(time.process_time()-start_time))\n",
+    "       "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sur_es    =np.mean(sur_vr_es    )\n",
+    "sur_is_ca =np.mean(sur_vr_is_ca )\n",
+    "sur_es_ca =np.mean(sur_vr_es_ca )\n",
+    "sur_real  =np.mean(sur_vr_real  )\n",
+    "sat_es    =np.mean(sat_vr_es    )\n",
+    "sat_is_ca =np.mean(sat_vr_is_ca )\n",
+    "sat_es_ca =np.mean(sat_vr_es_ca )\n",
+    "sat_real  =np.mean(sat_vr_real  )\n",
+    "\n",
+    "sur_me_es    =np.mean((sur_vr_es    -sur_vr_real))\n",
+    "sur_me_is_ca =np.mean((sur_vr_is_ca -sur_vr_real))\n",
+    "sur_me_es_ca =np.mean((sur_vr_es_ca -sur_vr_real))\n",
+    "sat_me_es    =np.mean((sat_vr_es    -sat_vr_real))\n",
+    "sat_me_is_ca =np.mean((sat_vr_is_ca -sat_vr_real))\n",
+    "sat_me_es_ca =np.mean((sat_vr_es_ca -sat_vr_real))\n",
+    "\n",
+    "sat_rmse_es    =np.power(np.sum(np.power((sat_vr_es    -sat_vr_real),2))/counter,0.5)\n",
+    "sat_rmse_is_ca =np.power(np.sum(np.power((sat_vr_is_ca -sat_vr_real),2))/counter,0.5)\n",
+    "sat_rmse_es_ca =np.power(np.sum(np.power((sat_vr_es_ca -sat_vr_real),2))/counter,0.5)\n",
+    "sur_rmse_es    =np.power(np.sum(np.power((sur_vr_es    -sur_vr_real),2))/counter,0.5)\n",
+    "sur_rmse_is_ca =np.power(np.sum(np.power((sur_vr_is_ca -sur_vr_real),2))/counter,0.5)\n",
+    "sur_rmse_es_ca =np.power(np.sum(np.power((sur_vr_es_ca -sur_vr_real),2))/counter,0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n",
+      "*c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*.  Please use the *color* keyword-argument or provide a 2-D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x396 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "fig,ax = vr_scatter_v6_v2(sur_vr_es,sur_vr_real ,sat_vr_es,sat_vr_real,sur_vr_is_ca,\n",
+    "                       sat_vr_is_ca,sur_vr_es_ca,sat_vr_es_ca,\n",
+    "                       alpha=0.5,\n",
+    "                       label1='',#explicit global',\n",
+    "                       label2='',#implicit       ',\n",
+    "                       label3='')#explicit local ')\n",
+    "ax[0,0].set_xlim(-135,35)\n",
+    "ax[0,0].set_ylim(-135,35)\n",
+    "\n",
+    "rmse = int(10*sur_rmse_es)\n",
+    "me   = int(10*sur_me_es)\n",
+    "ax[0,0].text(-130, 5,'RMSE: '+str(rmse/10),ha='left')\n",
+    "ax[0,0].text(-130,20,'ME: '+str(me/10),ha='left')\n",
+    "rmse = int(10*sat_rmse_es)\n",
+    "me   = int(10*sat_me_es)\n",
+    "ax[1,0].text(-130, 5,'RMSE: '+str(rmse/10),ha='left')\n",
+    "ax[1,0].text(-130,20,'ME: '+str(me/10),ha='left')\n",
+    "\n",
+    "rmse = int(10*sur_rmse_is_ca)\n",
+    "me   = int(10*sur_me_is_ca)\n",
+    "ax[0,1].text(-130, 5,'RMSE: '+str(rmse/10),ha='left')\n",
+    "ax[0,1].text(-130,20,'ME: '+str(me/10),ha='left')\n",
+    "rmse = int(10*sat_rmse_is_ca)\n",
+    "me   = int(10*sat_me_is_ca)\n",
+    "ax[1,1].text(-130, 5,'RMSE: '+str(rmse/10),ha='left')\n",
+    "ax[1,1].text(-130,20,'ME: '+str(me/10),ha='left')\n",
+    "\n",
+    "rmse = int(10*sur_rmse_es_ca)\n",
+    "me   = int(10*sur_me_es_ca)\n",
+    "ax[0,2].text(-130, 5,'RMSE: '+str(rmse/10),ha='left')\n",
+    "ax[0,2].text(-130,20,'ME: '+str(me/10),ha='left')\n",
+    "rmse = int(10*sat_rmse_es_ca)\n",
+    "me   = int(10*sat_me_es_ca)\n",
+    "ax[1,2].text(-130, 5,'RMSE: '+str(rmse/10),ha='left')\n",
+    "ax[1,2].text(-130,20,'ME: '+str(me/10),ha='left')\n",
+    "\n",
+    "label_axes_abcd(fig,loc=(0.9,0.05))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# The variance reduction as a function of ensemble size, lead time, and analysis localization length\n",
+    "\n",
+    "\n",
+    "This is a bit of a mess because it was originally three separate plots, which where all mashed into one during the review process. On my weak laptop it takes over an hour to run the test, so here they are plotted using the stored data. But the code used to run the scripts is attached at the end of the notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dict_raw_dt     = pickle.load(open('./plot-data/230111-raw-dict-dt.pkl','rb'))\n",
+    "\n",
+    "dict_raw_analoc = pickle.load(open('./plot-data/230111-raw-dict-loclength.pkl','rb'))\n",
+    "\n",
+    "dict_raw_ens    = pickle.load(open('./plot-data/230111_dict_raw_ens.pkl','rb'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### lead time first"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   1.,  100.,  200.,  300.,  400.,  500.,  600.,  700.,  800.,\n",
+       "        900., 1000.])"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "vr_es    =dict_raw_dt['vr_es   ']\n",
+    "vr_is_ca =dict_raw_dt['vr_is_ca']\n",
+    "vr_es_ca =dict_raw_dt['vr_es_ca']\n",
+    "vr_real  =dict_raw_dt['vr_real ']\n",
+    "var_total=dict_raw_dt['var_total']\n",
+    "t_vec    =dict_raw_dt['t_vec']\n",
+    "\n",
+    "# calculating the mean properties over all experiments\n",
+    "es    =np.mean(vr_es    ,axis=1)\n",
+    "es_ca =np.mean(vr_es_ca ,axis=1)\n",
+    "is_ca =np.mean(vr_is_ca ,axis=1)\n",
+    "real  =np.mean(vr_real  ,axis=1)\n",
+    "total =np.mean(var_total,axis=1)\n",
+    "rmse_es    =np.power(np.mean(np.power((vr_es    -vr_real),2),axis=1),0.5)\n",
+    "rmse_es_ca =np.power(np.mean(np.power((vr_es_ca -vr_real),2),axis=1),0.5)\n",
+    "rmse_is_ca =np.power(np.mean(np.power((vr_is_ca -vr_real),2),axis=1),0.5)\n",
+    "std_real    =np.std(vr_real,axis=1)\n",
+    "\n",
+    "#Lets see what changes when we change the localization used to create the background\n",
+    "dt_is_ca =is_ca\n",
+    "dt_es    =es   \n",
+    "dt_es_ca =es_ca\n",
+    "dt_real  =real \n",
+    "dt_total =total\n",
+    "dt_rmse_is_ca= rmse_is_ca\n",
+    "dt_rmse_es_ca= rmse_es_ca\n",
+    "dt_rmse_es   = rmse_es\n",
+    "dt_sample_uncertainty =np.std(vr_real[:,:] ,axis=1)/np.mean(vr_real,axis=1)/np.sqrt(n_samples)\n",
+    "t_vec"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### analysis localization length next"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1.000e+02, 2.000e+02, 4.000e+02, 8.000e+02, 1.600e+03, 3.200e+03,\n",
+       "       6.400e+03, 1.280e+04, 2.560e+04, 5.120e+04, 1.024e+05])"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vr_es    =dict_raw_analoc['vr_es   ']\n",
+    "vr_is_ca =dict_raw_analoc['vr_is_ca']\n",
+    "vr_es_ca =dict_raw_analoc['vr_es_ca']\n",
+    "vr_real  =dict_raw_analoc['vr_real ']\n",
+    "var_total=dict_raw_analoc['var_total']\n",
+    "loc_values=dict_raw_analoc['loc_values']\n",
+    "\n",
+    "es    =np.sum(vr_es    ,axis=1)/counter#/var_total\n",
+    "is_ca =np.sum(vr_is_ca ,axis=1)/counter#/var_total\n",
+    "es_ca =np.sum(vr_es_ca ,axis=1)/counter#/var_total\n",
+    "real  =np.sum(vr_real  ,axis=1)/counter#/var_total\n",
+    "total =np.sum(var_total,axis=1)/counter#/var_total\n",
+    "\n",
+    "sample_uncertainty =np.std(vr_real[:,:] ,axis=1)/np.mean(vr_real,axis=1)/np.sqrt(n_samples)\n",
+    "\n",
+    "rmse_es    =np.power(np.sum(np.power((vr_es    -vr_real),2),axis=1)/counter,0.5)#/np.sum(vr_real,axis=1)*counter\n",
+    "rmse_es_ca =np.power(np.sum(np.power((vr_es_ca -vr_real),2),axis=1)/counter,0.5)#/np.sum(vr_real,axis=1)*counter\n",
+    "rmse_is_ca =np.power(np.sum(np.power((vr_is_ca -vr_real),2),axis=1)/counter,0.5)#/np.sum(vr_real,axis=1)*counter\n",
+    "\n",
+    "std_real    =np.std(vr_real,axis=1)\n",
+    "\n",
+    "#Lets see what changes when we change the localization used to create the background\n",
+    "analoc_is_ca =is_ca\n",
+    "analoc_es    =es   \n",
+    "analoc_es_ca =es_ca\n",
+    "analoc_real  =real \n",
+    "analoc_total =total\n",
+    "analoc_rmse_is_ca= rmse_is_ca\n",
+    "analoc_rmse_es_ca= rmse_es_ca\n",
+    "analoc_rmse_es   = rmse_es\n",
+    "analoc_sample_uncertainty =np.std(vr_real[:,:] ,axis=1)/np.mean(vr_real,axis=1)/np.sqrt(n_samples)\n",
+    "\n",
+    "loc_values\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### and ensemble size last"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([  4,   8,  16,  32,  64, 128, 256, 512])"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vr_es     =dict_raw_ens['vr_es   ']\n",
+    "vr_is_ca  =dict_raw_ens['vr_is_ca']\n",
+    "vr_es_ca  =dict_raw_ens['vr_es_ca']\n",
+    "vr_es_reg =dict_raw_ens['vr_es_reg']\n",
+    "vr_real   =dict_raw_ens['vr_real ']\n",
+    "var_total =dict_raw_ens['var_total']\n",
+    "ens_values=dict_raw_ens['ens_values']\n",
+    "\n",
+    "es    =np.mean(vr_es    ,axis=1)\n",
+    "es_reg=np.mean(vr_es_reg,axis=1)\n",
+    "is_ca =np.mean(vr_is_ca ,axis=1)\n",
+    "es_ca =np.mean(vr_es_ca ,axis=1)\n",
+    "real  =np.mean(vr_real  ,axis=1)\n",
+    "total =np.mean(var_total,axis=1)\n",
+    "\n",
+    "me_es    =np.sum((vr_es    -vr_real),axis=1)/np.sum(vr_real,axis=1)\n",
+    "me_is_ca =np.sum((vr_is_ca -vr_real),axis=1)/np.sum(vr_real,axis=1)\n",
+    "me_es_ca =np.sum((vr_es_ca -vr_real),axis=1)/np.sum(vr_real,axis=1)\n",
+    "\n",
+    "rmse_es    =np.power(np.mean(np.power((vr_es    -vr_real),2),axis=1),0.5)\n",
+    "rmse_es_reg=np.power(np.mean(np.power((vr_es_reg-vr_real),2),axis=1),0.5)\n",
+    "rmse_is_ca =np.power(np.mean(np.power((vr_is_ca -vr_real),2),axis=1),0.5)\n",
+    "rmse_es_ca =np.power(np.mean(np.power((vr_es_ca -vr_real),2),axis=1),0.5)\n",
+    "\n",
+    "#Lets see what changes when we change the localization used to create the background\n",
+    "ens_is_ca =is_ca\n",
+    "ens_es    =es   \n",
+    "ens_es_reg=es_reg   \n",
+    "ens_es_ca =es_ca\n",
+    "ens_real  =real \n",
+    "ens_total =total \n",
+    "ens_rmse_is_ca= rmse_is_ca\n",
+    "ens_rmse_es_ca= rmse_es_ca\n",
+    "ens_rmse_es   = rmse_es\n",
+    "ens_rmse_es_reg   = rmse_es_reg\n",
+    "ens_sample_uncertainty =np.std(vr_real[:,:] ,axis=1)/np.mean(vr_real,axis=1)/np.sqrt(n_samples)\n",
+    "\n",
+    "ens_values\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### and now the plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(2,3,figsize=(10,5),sharex='col',sharey='row')\n",
+    "\n",
+    "lw_eg = 4\n",
+    "#localization length\n",
+    "ax[0,0].plot(np.arange(11,0,-1), analoc_is_ca/analoc_total*100    , lw=4    ,alpha=1.0,label='implicit'        ,color=plt.cm.viridis((4)/(6-1)))\n",
+    "ax[0,0].plot(np.arange(11,0,-1), analoc_es_ca/analoc_total*100    , lw=lw_eg,alpha=1.0,label='explicit local'  ,color='orange',ls=(0, (1, 1)))\n",
+    "ax[0,0].plot(np.arange(11,0,-1), analoc_es   /analoc_total*100    , lw=3    ,alpha=1.0,label='explicit global' ,color='blueviolet',ls='--')      \n",
+    "ax[0,0].plot(np.arange(11,0,-1), analoc_real /analoc_total*100    , lw=2    ,alpha=1,  color='k',ls='-',marker='.',label='truth')\n",
+    "ax[1,0].plot(np.arange(11,0,-1), analoc_rmse_is_ca    , lw=4    ,alpha=1.0,label='implicit'        ,color=plt.cm.viridis((4)/(6-1)))\n",
+    "ax[1,0].plot(np.arange(11,0,-1), analoc_rmse_es_ca    , lw=lw_eg,alpha=1.0,label='explicit local'  ,color='orange',ls=(0, (1, 1)))\n",
+    "ax[1,0].plot(np.arange(11,0,-1), analoc_rmse_es       , lw=3    ,alpha=1.0,label='explicit global' ,color='blueviolet',ls='--')      \n",
+    "ax[1,0].set_xticks(np.arange(1,12,2));\n",
+    "ax[1,0].set_xticklabels(2**np.arange(10,-1,-2));\n",
+    "ax[1,0].set_xlim(left=0.8,right=11.2)\n",
+    "ax[1,0].set_xlabel('analysis localization length [dx]');\n",
+    "ax[0,0].set_ylabel('mean relative \\n variance reduction [%]');\n",
+    "# ax[0,0].set_title('localization length');\n",
+    "ax[1,0].set_ylabel('RMSE variance reduction',labelpad=14);\n",
+    "\n",
+    "# ax[0,0].errorbar(np.arange(11,0,-1),analoc_real /analoc_total*100   ,yerr=analoc_sample_uncertainty*100,color='k',label='truth',capsize=5)\n",
+    "ax[0,0].fill_between(np.arange(11,0,-1),analoc_real /analoc_total*100  -analoc_sample_uncertainty*100 ,analoc_real /analoc_total*100+analoc_sample_uncertainty*100,color='k',alpha=0.15,label='sample size mean std')\n",
+    "\n",
+    "# lead time\n",
+    "ax[0,1].plot(t_vec, dt_is_ca/dt_total*100    , lw=4    ,alpha=1.0,label='implicit'        ,color=plt.cm.viridis((4)/(6-1)))\n",
+    "ax[0,1].plot(t_vec, dt_es_ca/dt_total*100    , lw=lw_eg,alpha=1.0,label='explicit local'  ,color='orange',ls=(0, (1, 1)))\n",
+    "ax[0,1].plot(t_vec, dt_es   /dt_total*100    , lw=3    ,alpha=1.0,label='explicit global' ,color='blueviolet',ls='--')      \n",
+    "ax[0,1].plot(t_vec, dt_real /dt_total*100    , lw=2    ,alpha=1,  color='k',ls='-',marker='.',label='truth')\n",
+    "ax[1,1].plot(t_vec, dt_rmse_is_ca    , lw=4    ,alpha=1.0,label='implicit'        ,color=plt.cm.viridis((4)/(6-1)))\n",
+    "ax[1,1].plot(t_vec, dt_rmse_es_ca    , lw=lw_eg,alpha=1.0,label='explicit local'  ,color='orange',ls=(0, (1, 1)))\n",
+    "ax[1,1].plot(t_vec, dt_rmse_es       , lw=3    ,alpha=1.0,label='explicit global' ,color='blueviolet',ls='--')      \n",
+    "ax[1,1].set_xlabel('forecast lead time [s]');\n",
+    "ax[1,1].set_xlim(left=-10,right=1010)\n",
+    "# ax[0,1].set_title('forecast lead time');\n",
+    "\n",
+    "ax[0,1].fill_between(t_vec,dt_real /dt_total*100  -dt_sample_uncertainty*100 ,dt_real /dt_total*100+dt_sample_uncertainty*100,color='k',alpha=0.15,label='sample size mean std')\n",
+    "\n",
+    "# loc length\n",
+    "ax[0,2].plot(ens_values, ens_is_ca/ens_total*100    , lw=4    ,alpha=1.0,label='implicit'        ,color=plt.cm.viridis((4)/(6-1)))\n",
+    "ax[0,2].plot(ens_values, ens_es_ca/ens_total*100    , lw=lw_eg,alpha=1.0,label='explicit local'  ,color='orange',ls=(0, (1, 1)))\n",
+    "ax[0,2].plot(ens_values, ens_es   /ens_total*100    , lw=3    ,alpha=1.0,label='explicit global' ,color='blueviolet',ls='--')      \n",
+    "ax[0,2].plot(ens_values, ens_es_reg/ens_total*100    , lw=2    ,alpha=1.0,label='explicit global hi reg' ,color='blueviolet',ls='-')      \n",
+    "ax[0,2].plot(ens_values, ens_real /ens_total*100    , lw=2    ,alpha=1,  color='k',ls='-',marker='.',label='truth')\n",
+    "ax[1,2].plot(ens_values, ens_rmse_is_ca    , lw=4    ,alpha=1.0,label='implicit'        ,color=plt.cm.viridis((4)/(6-1)))\n",
+    "ax[1,2].plot(ens_values, ens_rmse_es_ca    , lw=lw_eg,alpha=1.0,label='explicit local'  ,color='orange',ls=(0, (1, 1)))\n",
+    "ax[1,2].plot(ens_values, ens_rmse_es       , lw=3    ,alpha=1.0,label='explicit global' ,color='blueviolet',ls='--')      \n",
+    "ax[1,2].plot(ens_values, ens_rmse_es_reg   , lw=2    ,alpha=1.0,label='explicit global hi reg'  ,color='blueviolet')\n",
+    "# ax[0,2].set_title('ensemble size');\n",
+    "\n",
+    "ax[0,2].fill_between(ens_values,ens_real /ens_total*100  -ens_sample_uncertainty*100 ,ens_real /ens_total*100+ens_sample_uncertainty*100,color='k',alpha=0.15,label='sample size mean std')\n",
+    "\n",
+    "#Adding the default setting lines\n",
+    "ax[0,0].vlines(  6,-60,0,'k',ls='--',alpha=0.6)\n",
+    "ax[0,1].vlines(550,-60,0,'k',ls='--',alpha=0.6)\n",
+    "ax[0,2].vlines( 32,-60,0,'k',ls='--',alpha=0.6)\n",
+    "\n",
+    "ax[1,0].vlines(  6,0,50,'k',ls='--',alpha=0.6)\n",
+    "ax[1,1].vlines(550,0,50,'k',ls='--',alpha=0.6)\n",
+    "ax[1,2].vlines( 32,0,50,'k',ls='--',alpha=0.6)\n",
+    "\n",
+    "\n",
+    "\n",
+    "ax[0,2].set_xscale('log');\n",
+    "ax[0,2].set_xticks(ens_values);\n",
+    "ax[0,2].set_xticklabels(ens_values);\n",
+    "ax[1,2].set_xlabel('ensemble size');\n",
+    "\n",
+    "ax[1,2].set_xlim(left=0.9*4,right=512*1.1)\n",
+    "# ax[1,2].set_xlim(left=4,right=128)\n",
+    "ax[1,1].set_ylim(bottom=0,top=40)\n",
+    "ax[0,0].set_ylim(top=0,bottom=-60)\n",
+    "#ax[0,0].legend(bbox_to_anchor=(0.,1.00,0.5,3),loc='lower left',ncol=5,handlelength=2);\n",
+    "ax[0,2].legend(bbox_to_anchor=(-1.,1.00,0.5,3),loc='lower center',ncol=4,handlelength=3);\n",
+    "plt.subplots_adjust(wspace=0.1,hspace=0.1)\n",
+    "label_axes_abcd(fig,loc=(0.1,0.9))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Next up testing for different regularization parameters alpha\n",
+    "\n",
+    "This takes long enough (hour), that I will simply load the data instead of running it by default \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%time\n",
+    "# da_const_vr = set_da_constants_22(obs_loc=np.arange(25,299,50))\n",
+    "\n",
+    "# nalpha_steps=23\n",
+    "# alpha_vec=np.logspace(-9,2,nalpha_steps)\n",
+    "# t_vec=np.array([200,600,1000,1400,1800])\n",
+    "# ndt_steps=len(t_vec)\n",
+    "# t_start= 40\n",
+    "# t_end = 100\n",
+    "# n_rand = 15\n",
+    "# n_samples = (t_end-t_start)*n_rand\n",
+    "# sens_all     = np.zeros([ndt_steps,300])\n",
+    "# vr_es_alpha  = np.zeros([nalpha_steps,ndt_steps,n_samples])\n",
+    "# vr_real      = np.zeros([ndt_steps,n_samples]) \n",
+    "# var_total     = np.zeros([ndt_steps,n_samples]) \n",
+    "# counter = 0\n",
+    "# total_variance = 0.\n",
+    "# for t in range(t_start,t_end):\n",
+    "#     for r in range(n_rand):\n",
+    "#         n = (t-t_start)*n_rand+r\n",
+    "#         np.random.seed(n)\n",
+    "#         #print(i,n_obs)\n",
+    "#         counter = counter+1\n",
+    "#         truth_idx = r\n",
+    "#         for i in range(len(t_vec)): \n",
+    "#             da_const_vr['dt'] = t_vec[i]\n",
+    "            \n",
+    "            \n",
+    "#             for a in range(nalpha_steps):\n",
+    "#                 if a ==0:\n",
+    "#                     vr_t, vr_i, vr_r, J_dict_LA,bla, quad,dx_ni =vr_reloaded_22(states[0]['bg'][t],\n",
+    "#                     states[0]['bg'][t][:,truth_idx],m_const,da_const_vr,reflectance_simulator,iterative_flag = 0,\n",
+    "#                     alpha=alpha_vec[a],obs_seed=counter,model_seed=counter)\n",
+    "#                 else:\n",
+    "#                     vr_t, vr_i, vr_r, J_dict_LA,bla, quad,dx_ni =vr_reloaded_22(states[0]['bg'][t],\n",
+    "#                     states[0]['bg'][t][:,truth_idx],m_const,da_const_vr,reflectance_simulator,iterative_flag = 0,\n",
+    "#                     alpha=alpha_vec[a],obs_seed=counter,model_seed=counter,quad_state=quad)\n",
+    "            \n",
+    "#                 vr_es_alpha[a,i,n]  = vr_t\n",
+    "#             var_total[i,n] = np.var(J_dict_LA['bf'],ddof=1)\n",
+    "#             vr_real[i,n]   = vr_r\n",
+    "            \n",
+    "            \n",
+    "            \n",
+    "#     print('completed t:',t)\n",
+    "       "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### loading raw data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a_file = open(\"plot-data/alpha_OSSEs.pkl\",'rb')\n",
+    "bla=pickle.load(a_file)\n",
+    "dict_raw=bla\n",
+    "a_file.close()\n",
+    "vr_es_alpha=dict_raw['vr_es-alpha']\n",
+    "vr_real    =dict_raw['vr_real ']\n",
+    "var_total  =dict_raw['var_total']\n",
+    "t_vec      =dict_raw['t_vec']\n",
+    "alpha_vec  =dict_raw['alpha_vec']\n",
+    "\n",
+    "counter = vr_real.shape[1]\n",
+    "nalpha_steps = vr_es_alpha.shape[0]\n",
+    "nalpha_steps=23\n",
+    "alpha_vec=np.logspace(-9,2,nalpha_steps)\n",
+    "t_vec=np.array([200,600,1000,1400,1800])\n",
+    "ndt_steps=len(t_vec)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "real  =np.sum(vr_real  ,axis=1)/counter#/var_total\n",
+    "total =np.sum(var_total,axis=1)/counter#/var_total\n",
+    "\n",
+    "rmse_es_alpha =np.zeros([nalpha_steps,ndt_steps])\n",
+    "me_es_alpha =np.zeros([nalpha_steps,ndt_steps])\n",
+    "es_alpha =np.zeros([nalpha_steps,ndt_steps])\n",
+    "\n",
+    "for e in range(nalpha_steps):\n",
+    "    rmse_es_alpha[e,:] =np.power(np.sum(np.power((vr_es_alpha[e,:,:] -vr_real),2),axis=1)/counter,0.5)/np.sum(vr_real,axis=1)*counter\n",
+    "    me_es_alpha[e,:] =np.sum(vr_es_alpha [e,:,:] -vr_real,axis=1)/np.sum(vr_real,axis=1)\n",
+    "    es_alpha[e,:] =np.sum(vr_es_alpha[e,:,:] ,axis=1)/counter#/var_total\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 288x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax=plt.subplots(2,1,figsize=(4,6),sharex='all')\n",
+    "\n",
+    "for t in range(ndt_steps):\n",
+    "    ax[0].plot(alpha_vec,es_alpha[:,t]/total[t]*100,label=str(t_vec[t]),color=plt.cm.copper(t/(ndt_steps-1)),marker='.')\n",
+    "    ax[0].hlines(real[t]/total[t]*100,alpha_vec[0],alpha_vec[-1],linestyle='--',color=plt.cm.copper(t/(ndt_steps-1)))\n",
+    "    \n",
+    "    ax[1].plot(alpha_vec,rmse_es_alpha[:,t]*real[t],label=str(t_vec[t]),color=plt.cm.copper(t/(ndt_steps-1)),marker='.')\n",
+    "    \n",
+    "    \n",
+    "    #plt.hlines(es[t]/total[t]*100,alpha_vec[0],alpha_vec[-1],linestyle=':',color=plt.cm.copper(t/(ndt_steps-1)))\n",
+    "t=2\n",
+    "ax[0].hlines(real[t]/total[t]*100,alpha_vec[0],alpha_vec[-1],linestyle='--',color=plt.cm.copper(t/(ndt_steps-1)),label='truth')\n",
+    "ax[1].hlines(real[t]/total[t]*100,alpha_vec[0],alpha_vec[-1],linestyle='--',color=plt.cm.copper(t/(ndt_steps-1)),label='truth')\n",
+    "\n",
+    "ax[0].vlines(alpha_default,-1000,1000,linestyle=':',color='k',lw=3)\n",
+    "ax[1].vlines(alpha_default,-1000,1000,linestyle=':',color='k',lw=3)\n",
+    "\n",
+    "#plt.legend(title='lead time [s]',bbox_to_anchor=(1,1))\n",
+    "# ax[0].legend(title='lead time [s]',ncol=2,bbox_to_anchor=(2,1),loc='upper right')\n",
+    "ax[1].legend(title='lead time [s]',ncol=2,loc='upper right',handlelength=1)\n",
+    "ax[0].set_xscale('log')\n",
+    "# ax[0].set_xlabel(r'$\\alpha$')\n",
+    "ax[1].set_xlabel(r'$\\alpha$')\n",
+    "ax[1].set_ylabel('RMSE variance reduction',labelpad=0.1)\n",
+    "ax[0].set_ylabel('mean variance reduction [%]')\n",
+    "ax[0].set_ylim(top=1,bottom=-50)\n",
+    "ax[1].set_ylim(top=200,bottom=0)\n",
+    "ax[0].set_xlim(left=1e-8,right=100)\n",
+    "label_axes_abcd(fig,loc=(1.02,0.95))\n",
+    "plt.subplots_adjust(hspace=0.1)\n",
+    "fig.align_labels()\n",
+    "ax[0].yaxis.get_label().set_verticalalignment(\"baseline\")\n",
+    "ax[0].yaxis.get_label().set_verticalalignment(\"baseline\")\n",
+    "# plt.legend(title='lead time [s]',bbox_to_anchor=(-0.05,1.05,1,0.1),ncol=3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2D histograms of ensemble size versus signal propagation error"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "initialize model and data assimilation setup using the default values\n",
+    "\"\"\"\n",
+    "m_const = set_model_constants_22()\n",
+    "da_const = set_da_constants_22()\n",
+    "sat_operator = reflectance_simulator\n",
+    "da_const_vr = set_da_constants_22(obs_loc=np.arange(25,299,50)) #changed direct point observations for variance reduction tests\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "initialize model and data assimilation setup using the default values\n",
+    "\"\"\"\n",
+    "\n",
+    "m_const = set_model_constants_22()\n",
+    "da_const = set_da_constants_22(nens=128,ncyc=100)\n",
+    "sat_operator = reflectance_simulator\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "# slight difference now, instead of running a new state for each ensemble size, i instead first run the max size ensemble, and then randomly select the desired number of ensembles from the large state.\n",
+    "# This is to avoid having differences in the default model run overpower the differences between how many ensembles are used for the vr  test\n",
+    "\n",
+    "n_steps=6\n",
+    "ens_values = 2**np.arange(2,n_steps+2)\n",
+    "ens_values = ens_values.astype(int)\n",
+    "#da_const['nens'] = ens_values[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([  4,   8,  16,  32,  64, 128])"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ens_values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[ 20.  30.  40.  50.  60.  70.  80.  90. 100. 110. 120. 130. 140. 150.\n",
+      " 160. 170. 180.]\n"
+     ]
+    }
+   ],
+   "source": [
+    "error_vec = np.arange(2,18.5)*10\n",
+    "nerrors = len(error_vec)\n",
+    "print(error_vec)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/pgriewank/pgriewank/code/2021-linear-advection/da_functions.py:328: ComplexWarning: Casting complex values to real discards the imaginary part\n",
+      "  bg[:,i]    = linear_advection_model(analysis[:,i],u_ens,dhdt_ens,m_const[\"dx\"],da_const[\"dt\"],da_const[\"nt\"])\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 11.7 s, sys: 240 ms, total: 11.9 s\n",
+      "Wall time: 3.01 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# Run the model\n",
+    "states_big   = run_linear_advection_KF_22(m_const,da_const,reflectance_simulator)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<!-- a_file = open(\"plot-data/state_letkf_512_1220.pkl\", \"rb\") -->\n",
+    "<!-- states_512 = pickle.load(a_file) -->\n",
+    "<!-- a_file.close() -->"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%time\n",
+    "# t_start= 40\n",
+    "# t_end = 100\n",
+    "# n_rand = 15\n",
+    "# # n_rand = 4\n",
+    "# n_samples = (t_end-t_start)*n_rand\n",
+    "# vr_real       = np.zeros([n_steps,n_samples]) \n",
+    "# vr_es         = np.zeros([n_steps,n_samples]) \n",
+    "# vr_is_cw      = np.zeros([nerrors,n_steps,n_samples])\n",
+    "# var_total     = np.zeros([n_steps,n_samples]) \n",
+    "# for i in range(n_steps): \n",
+    "#     n_ens=ens_values[i]\n",
+    "#     for t in range(t_start,t_end):\n",
+    "#         for r in range(n_rand):\n",
+    "#             n = (t-t_start)*n_rand+r\n",
+    "#             np.random.seed(n)\n",
+    "#             # selecting random ensemble members for the ensemble\n",
+    "#             idx_ens = randomized_obs_loc(n_ens,start=0,end=ens_values[-1],seed=n)\n",
+    "#             truth_idx = r\n",
+    "            \n",
+    "#             da_const_vr['nens'] = n_ens\n",
+    "            \n",
+    "#             vr_t, vr_i, vr_r, J_dict_LA,bla, quad,dx_ni =vr_reloaded_22(states_big[0]['bg'][t][:,idx_ens],\n",
+    "#                                 states_big[0]['bg'][t][:,truth_idx],m_const,da_const_vr,sat_operator,\n",
+    "#                                                 obs_seed=n,model_seed=n,alpha=alpha_default)\n",
+    "                                                \n",
+    "#             var_total[i,n] = np.var(J_dict_LA['bf'],ddof=1)\n",
+    "#             vr_es[i,n]     = vr_t\n",
+    "#             vr_real[i,n]   = vr_r\n",
+    "#             for e in range(nerrors):\n",
+    "#                 vr_t, vr_r, quad_bla, J_dict= vr_individual_loc_22(states_big[0]['bg'][t][:,idx_ens],states_big[0]['bg'][t][:,truth_idx],m_const,da_const_vr,reflectance_simulator,\n",
+    "#                                                       advect_flag=1,obs_seed=n,model_seed=n,quad_state=quad,error_u=error_vec[e])\n",
+    "#                 vr_is_cw[e,i,n]  = vr_t\n",
+    "            \n",
+    "            \n",
+    "#     print('completed nens:',ens_values[i])\n",
+    "# counter       =n_samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dict_raw = {\n",
+    "\n",
+    "# 'vr_es   ':vr_es   ,\n",
+    "# 'vr_is_cw':vr_is_cw,\n",
+    "# 'vr_real ':vr_real ,\n",
+    "# 'var_total':var_total,\n",
+    "# 'ens_values':ens_values,\n",
+    "# 'error_vec':error_vec\n",
+    "# }"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# a_file = open(\"plot-data/dict_raw_2dhist.pkl\", \"wb\")\n",
+    "# pickle.dump(dict_raw, a_file)\n",
+    "# a_file.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dict_raw_2dhist    = pickle.load(open('./plot-data/dict_raw_2dhist.pkl','rb'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "vr_es     =dict_raw_2dhist['vr_es   ']\n",
+    "vr_is_cw  =dict_raw_2dhist['vr_is_cw']\n",
+    "vr_real   =dict_raw_2dhist['vr_real ']\n",
+    "var_total =dict_raw_2dhist['var_total']\n",
+    "ens_values=dict_raw_2dhist['ens_values']\n",
+    "error_vec =dict_raw_2dhist['error_vec']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculating the mean properties over all experiments\n",
+    "es    =np.mean(vr_es    ,axis=1)\n",
+    "real  =np.mean(vr_real  ,axis=1)\n",
+    "total =np.mean(var_total,axis=1)\n",
+    "\n",
+    "me_es    =np.sum((vr_es    -vr_real),axis=1)/np.sum(vr_real)\n",
+    "# rmse_es=np.sqrt(np.mean((vr_es    -vr_real)**2))\n",
+    "rmse_es    =np.power(np.mean(np.power((vr_es    -vr_real),2),axis=1),0.5)#/np.sum(vr_real,axis=0)*counter\n",
+    "\n",
+    "rmse_is_cw =np.zeros([nerrors,n_steps])\n",
+    "is_cw      =np.zeros([nerrors,n_steps])\n",
+    "\n",
+    "for l in range(n_steps):\n",
+    "    rmse_es[l]    =np.sqrt(np.mean((vr_es[l,:]-vr_real[l,:])**2))\n",
+    "    for e in range(nerrors):\n",
+    "        rmse_is_cw[e,l] =np.sqrt(np.mean((vr_is_cw[e,l,:]    -vr_real[l,:])**2))\n",
+    "        is_cw[e,l]      =np.mean(vr_is_cw[e,l,:] ,axis=0)#/counter#/var_total\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 288x504 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(2,1,figsize=(4,7),sharex='all')\n",
+    "A =(is_cw-real)/(total)*100 \n",
+    "# p1 = ax[0].pcolormesh(A,vmax=40,vmin=-40,cmap='vlag_r')\n",
+    "p1 = ax[0].pcolormesh(A,vmax=15,vmin=-15,cmap='PRGn_r')\n",
+    "# p1 = ax[0].pcolormesh(A,cmap='plasma_r')#,vmax=np.max(A),vmin=-np.max(A),cmap='vlag_r')\n",
+    "ax[0].set_yticks(np.arange(0,nerrors,2)+0.5)\n",
+    "ax[0].set_xticks(np.arange(0,n_steps,2)+0.5)\n",
+    "ax[0].set_xticklabels((ens_values.astype(int)[::2]),rotation=0)\n",
+    "ax[0].set_yticklabels(np.array(error_vec.astype(int))[::2]-100)\n",
+    "ax[0].set_ylabel('signal propagation error [%]')\n",
+    "# ax[0].set_title('explicit method, local vs global sensitivity')\n",
+    "\n",
+    "A = (rmse_is_cw-rmse_es)/(rmse_es)\n",
+    "# p = ax[1].pcolormesh(A,vmax=np.max(A),vmin=-np.max(A),cmap='vlag_r')\n",
+    "p2 = ax[1].pcolormesh(A,vmax=0.5,vmin=-0.5,cmap='BrBG_r')\n",
+    "ax[1].set_yticks(np.arange(0,nerrors,2)+0.5)\n",
+    "ax[1].set_xticks(np.arange(0,n_steps)+0.5)\n",
+    "ax[1].set_xticklabels((ens_values.astype(int)),rotation=0)\n",
+    "ax[1].set_yticklabels(np.array(error_vec.astype(int))[::2]-100)\n",
+    "ax[1].set_xlabel('ensemble size')\n",
+    "ax[1].set_ylabel('signal propagation error [%]')\n",
+    "# ax[1].set_title('explicit method, local vs global sensitivity')\n",
+    "plt.subplots_adjust(hspace=0.1)\n",
+    "label_axes_abcd(fig,loc=(1.01,1.01))\n",
+    "cbar1 = plt.colorbar(p1,label='mean variance reduction error [%]',ax=ax[0])#,ticks=[-0.4,-0.2,0.0,0.2,0.4])\n",
+    "cbar2 = plt.colorbar(p2,label='relative RMSE difference',ax=ax[1])\n",
+    "cbar1.ax.tick_params(size=0)\n",
+    "cbar2.ax.tick_params(size=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2D histogram of rmse as a function of localization length and advection error. Marks when localizing is worse than not localizing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 13.9 s, sys: 328 ms, total: 14.3 s\n",
+      "Wall time: 3.58 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# just resetting a\n",
+    "m_const = set_model_constants_22()\n",
+    "da_const = set_da_constants_22(nens=8,ncyc=250)\n",
+    "sat_operator = reflectance_simulator\n",
+    "da_const_vr = set_da_constants_22(obs_loc=np.arange(25,299,50),nens=8) #changed direct point observations for variance reduction tests\n",
+    "# Run the model\n",
+    "states   = run_linear_advection_KF_22(m_const,da_const,reflectance_simulator)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%time\n",
+    "# import time\n",
+    "# start_time=time.process_time()\n",
+    "# sens_loc_length=6000\n",
+    "\n",
+    "# t_forecast=500\n",
+    "# t_start= 40\n",
+    "# t_end = 220\n",
+    "# n_ens = 8\n",
+    "# loc_vec=np.sqrt(2)**np.arange(10)*250.\n",
+    "# loc_steps=len(loc_vec)\n",
+    "# error_vec = [20,40,60,80,100,120,140,160,180]\n",
+    "# error_vec = np.arange(2,18.5)*10\n",
+    "# nerrors = len(error_vec)\n",
+    "# n_samples = (t_end-t_start)*n_ens\n",
+    "# truth_idx = 0\n",
+    "# vr_es        = np.zeros([n_samples])\n",
+    "# vr_es_cw     = np.zeros([nerrors,loc_steps,n_samples])\n",
+    "# vr_real      = np.zeros([n_samples]) \n",
+    "# var_total     = np.zeros([n_samples]) \n",
+    "# counter = 0\n",
+    "# for t in range(t_start,t_end):\n",
+    "#     for n in range(n_ens):\n",
+    "#         i = (t-t_start)*n_ens+n\n",
+    "#         counter = counter+1\n",
+    "#         truth_idx = n\n",
+    "#         vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad, dx = vr_reloaded_22(\n",
+    "#                 states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_vr,reflectance_simulator,\n",
+    "#                 obs_seed=i,model_seed=i,alpha=alpha_default)\n",
+    "#         var_total[i] = np.var(J_dict['bf'],ddof=1)\n",
+    "#         vr_es[i]     = vr_t\n",
+    "#         vr_real[i]   = vr_r\n",
+    "#         for dl in range(len(loc_vec)): \n",
+    "#             for e in range(nerrors):\n",
+    "#                 vr_t, vr_i, vr_r,J_dict,dJdx_inv, bla_quad, dx = vr_reloaded_22_locsens(states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_vr,reflectance_simulator,sens_loc_flag=1,\n",
+    "#                                                                  sens_loc_adv_error=error_vec[e],sens_loc_length=loc_vec[dl],\n",
+    "#                                                                  obs_seed=i,model_seed=i,quad_state=quad)\n",
+    "#                 vr_es_cw[e,dl,i]  = vr_t\n",
+    "            \n",
+    "#     if np.floor(t/10) == t/10: print('completed timesteps:',t-39,' seconds spent computing so far:',np.floor(time.process_time()-start_time))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dict_raw = {\n",
+    "\n",
+    "# 'vr_es   ':vr_es   ,\n",
+    "# 'vr_es_cw':vr_es_cw,\n",
+    "# 'vr_real ':vr_real ,\n",
+    "# 'var_total':var_total,\n",
+    "# 'loc_vec':loc_vec,\n",
+    "# 'error_vec':error_vec\n",
+    "# }"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# a_file = open(\"plot-data/dict_raw_2dhist_sensloc.pkl\", \"wb\")\n",
+    "# pickle.dump(dict_raw, a_file)\n",
+    "# a_file.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dict_raw_2dhist2    = pickle.load(open('./plot-data/dict_raw_2dhist_sensloc.pkl','rb'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "vr_es     =dict_raw_2dhist2['vr_es   ']\n",
+    "vr_es_cw  =dict_raw_2dhist2['vr_es_cw']\n",
+    "vr_real   =dict_raw_2dhist2['vr_real ']\n",
+    "var_total =dict_raw_2dhist2['var_total']\n",
+    "loc_vec   =dict_raw_2dhist2['loc_vec']\n",
+    "error_vec =dict_raw_2dhist2['error_vec']\n",
+    "nerrors = len(error_vec)\n",
+    "loc_steps = len(loc_vec)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# calculating the mean properties over all experiments\n",
+    "es    =np.mean(vr_es    ,axis=0)\n",
+    "real  =np.mean(vr_real  ,axis=0)\n",
+    "total =np.mean(var_total,axis=0)\n",
+    "\n",
+    "me_es    =np.sum((vr_es    -vr_real))/np.sum(vr_real)\n",
+    "rmse_es=np.sqrt(np.mean((vr_es    -vr_real)**2))\n",
+    "\n",
+    "rmse_es_cw =np.zeros([nerrors,loc_steps])\n",
+    "es_cw      =np.zeros([nerrors,loc_steps])\n",
+    "\n",
+    "for e in range(nerrors):\n",
+    "    for l in range(loc_steps):\n",
+    "        rmse_es_cw[e,l] =np.sqrt(np.mean((vr_es_cw[e,l,:]    -vr_real)**2))\n",
+    "        es_cw[e,l] =np.mean(vr_es_cw[e,l,:] ,axis=0)#/var_total\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'explicit method, local vs global sensitivity')"
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 288x252 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(1,1,figsize=(4.,3.5))\n",
+    "A = (rmse_es_cw-rmse_es)/np.abs(rmse_es)\n",
+    "\n",
+    "# plt.pcolormesh(A,vmax=np.max(A),vmin=-np.max(A),cmap='PiYG_r')\n",
+    "plt.pcolormesh(A,vmax=0.4,vmin=-0.4,cmap='PuOr_r')\n",
+    "plt.colorbar(label='relative RMSE difference',ticks=[-0.4,-0.2,0.0,0.2,0.4])\n",
+    "ax.set_yticks(np.arange(0,nerrors,2)+0.5)\n",
+    "ax.set_xticks(np.arange(0,loc_steps,2)+0.5)\n",
+    "ax.set_xticklabels((loc_vec.astype(int)[::2]),rotation=0)\n",
+    "ax.set_yticklabels(np.array(error_vec)[::2]-100)\n",
+    "ax.set_xlabel('sensitivity localization length [m]')\n",
+    "ax.set_ylabel('signal propagation error in %')\n",
+    "ax.set_title('explicit method, local vs global sensitivity')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Code to reproduce the localization length, lead time, and ensemble plots "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### ens size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# \"\"\"\n",
+    "# initialize model and data assimilation setup using the default values\n",
+    "# \"\"\"\n",
+    "\n",
+    "# m_const = set_model_constants_22()\n",
+    "# da_const = set_da_constants_22(nens=512,ncyc=100)\n",
+    "# sat_operator = reflectance_simulator\n",
+    "# n_rand = 60"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # slight difference now, instead of running a new state for each ensemble size, i instead first run the max size ensemble, and then randomly select the desired number of ensembles from the large state.\n",
+    "# # This is to avoid having differences in the default model run overpower the differences between how many ensembles are used for the vr  test\n",
+    "# n_steps=8\n",
+    "# ens_values = 2**np.arange(2,n_steps+2)\n",
+    "# ens_values = ens_values.astype(int)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%time\n",
+    "# # Run the model\n",
+    "# states_big   = run_linear_advection_KF_22(m_const,da_const,reflectance_simulator)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%time\n",
+    "# da_const_vr = set_da_constants_22(obs_loc=np.arange(25,299,50)) #changed direct point observations for variance reduction tests\n",
+    "\n",
+    "\n",
+    "\n",
+    "# n_samples = (t_end-t_start)*n_rand\n",
+    "# counter =n_samples\n",
+    "# vr_real       = np.zeros([n_steps,n_samples]) \n",
+    "# vr_es         = np.zeros([n_steps,n_samples]) \n",
+    "# vr_es_reg     = np.zeros([n_steps,n_samples]) \n",
+    "# vr_is_ca      = np.zeros([n_steps,n_samples]) \n",
+    "# vr_es_ca      = np.zeros([n_steps,n_samples]) \n",
+    "# var_total     = np.zeros([n_steps,n_samples]) \n",
+    "# for i in range(n_steps): \n",
+    "#     nn_ens=ens_values[i]\n",
+    "#     for t in range(t_start,t_end):\n",
+    "#         for r in range(n_rand):\n",
+    "\n",
+    "#             n = (t-t_start)*n_rand+r\n",
+    "#             np.random.seed(n)\n",
+    "#             # selecting random ensemble members for the ensemble\n",
+    "#             idx_ens = randomized_obs_loc(nn_ens,start=0,end=ens_values[-1],seed=n)\n",
+    "#             truth_idx = idx_ens[np.random.randint(0,nn_ens)]\n",
+    "\n",
+    "#             da_const_vr['nens'] = nn_ens\n",
+    "         \n",
+    "            \n",
+    "            \n",
+    "#             vr_t, vr_i, vr_r, J_dict_LA,bla, quad,dx_ni =vr_reloaded_22(states_big[0]['bg'][t][:,idx_ens],\n",
+    "#                                 states_big[0]['bg'][t][:,truth_idx],m_const,da_const_vr,sat_operator,\n",
+    "#                                                 obs_seed=n,model_seed=n,alpha=alpha_default)\n",
+    "                                                \n",
+    "#             var_total[i,n] = np.var(J_dict_LA['bf'],ddof=1)\n",
+    "#             vr_real[i,n]   = vr_r\n",
+    "#             vr_es[i,n]     = vr_t\n",
+    "            \n",
+    "#             vr_t, vr_i, vr_r, J_dict_LA,bla, quad,dx_ni =vr_reloaded_22(states_big[0]['bg'][t][:,idx_ens],\n",
+    "#                                 states_big[0]['bg'][t][:,truth_idx],m_const,da_const_vr,sat_operator,\n",
+    "#                                                 obs_seed=n,model_seed=n,alpha=1,quad_state=quad)\n",
+    "                                                \n",
+    "#             vr_es_reg[i,n]     = vr_t\n",
+    "#             vr_t, vr_r, quad, J_dict_LA     = vr_individual_loc_22(states_big[0]['bg'][t][:,:],\n",
+    "#                             states_big[0]['bg'][t][:,truth_idx],m_const,da_const_vr,sat_operator,\n",
+    "#                                                                    advect_flag=1,quad_state=quad,\n",
+    "#                                                                    obs_seed=n,model_seed=n)\n",
+    "#             vr_is_ca[i,n]  = vr_t\n",
+    "#             vr_t, vr_i, vr_r,J_dict,dJdx_inv, bla_quad, dx = vr_reloaded_22_locsens(states_big[0]['bg'][t][:,idx_ens],states_big[0]['bg'][t][:,truth_idx],m_const,da_const_vr,reflectance_simulator,sens_loc_flag=1,\n",
+    "#                                         sens_loc_length=sens_loc_length,\n",
+    "#                                         obs_seed=n,model_seed=n,quad_state=quad)\n",
+    "#             vr_es_ca[i,n]  = vr_t\n",
+    "            \n",
+    "#     print('completed nens:',ens_values[i])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### lead time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%time\n",
+    "# # just resetting a\n",
+    "# m_const = set_model_constants_22()\n",
+    "# da_const = set_da_constants_22()\n",
+    "# sat_operator = reflectance_simulator\n",
+    "# da_const_vr = set_da_constants_22(obs_loc=np.arange(25,299,50)) #changed direct point observations for variance reduction tests\n",
+    "# # Run the model\n",
+    "# states   = run_linear_advection_KF_22(m_const,da_const,reflectance_simulator)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%time\n",
+    "# import time\n",
+    "# start_time=time.process_time()\n",
+    "\n",
+    "# ndt_steps=6\n",
+    "# ndt_steps=11\n",
+    "# t_vec=np.linspace(0,1000,ndt_steps)\n",
+    "# n_samples = (t_end-t_start)*n_rand\n",
+    "# truth_idx = 0\n",
+    "# vr_es        = np.zeros([ndt_steps,n_samples])\n",
+    "# vr_es_ca     = np.zeros([ndt_steps,n_samples])\n",
+    "# vr_is_ca     = np.zeros([ndt_steps,n_samples])\n",
+    "# vr_real      = np.zeros([ndt_steps,n_samples]) \n",
+    "# var_total    = np.zeros([ndt_steps,n_samples]) \n",
+    "# ref_t = da_const['dt']\n",
+    "# t_vec[0] = 1\n",
+    "# counter = 0\n",
+    "\n",
+    "\n",
+    "# for t in range(t_start,t_end):\n",
+    "#     for n in range(n_rand):\n",
+    "#         i = (t-t_start)*n_rand+n\n",
+    "#         counter = counter+1\n",
+    "#         truth_idx = n\n",
+    "#         for dt in range(len(t_vec)): \n",
+    "#             da_const_vr['dt'] = t_vec[dt]\n",
+    "            \n",
+    "#             vr_t, vr_i, vr_r,J_dict,dJdx_inv, quad, dx = vr_reloaded_22(\n",
+    "#                 states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_vr,reflectance_simulator,\n",
+    "#                 obs_seed=i,model_seed=i,alpha=alpha_default)\n",
+    "#             var_total[dt,i] = np.var(J_dict['bf'],ddof=1)\n",
+    "#             vr_es[dt,i]     = vr_t\n",
+    "#             vr_real[dt,i]   = vr_r\n",
+    "\n",
+    "#             vr_t, vr_i, vr_r,J_dict,dJdx_inv, bla_quad, dx = vr_reloaded_22_locsens(states[0]['bg'][t],states[0]['bg'][t][:,n],m_const,da_const_vr,reflectance_simulator,sens_loc_flag=1,\n",
+    "#                                                                  sens_loc_length=sens_loc_length,\n",
+    "#                                                                  obs_seed=i,model_seed=i,quad_state=quad)\n",
+    "#             vr_es_ca[dt,i]     = vr_t\n",
+    "            \n",
+    "#             vr_t, vr_r, quad, J_dict_LA     = vr_individual_loc_22(states[0]['bg'][t],\n",
+    "#                             states[0]['bg'][t][:,n],m_const,da_const_vr,sat_operator,\n",
+    "#                                                     advect_flag=1,quad_state=quad,obs_seed=i,model_seed=i)\n",
+    "#             vr_is_ca[dt,i]  = vr_t\n",
+    "            \n",
+    "            \n",
+    "            \n",
+    "#     if np.floor(t/10) == t/10: print('completed timesteps:',t-39,' seconds spent computing so far:',np.floor(time.process_time()-start_time))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### localization length"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %%time\n",
+    "# import time\n",
+    "# start_time=time.process_time()\n",
+    "\n",
+    "\n",
+    "# n_samples = (t_end-t_start)*n_rand\n",
+    "# truth_idx = 0\n",
+    "\n",
+    "# loc_values = 2.**np.arange(11)*m_const['dx']\n",
+    "# vr_es        = np.zeros([11,n_samples])\n",
+    "# vr_es_ca     = np.zeros([11,n_samples])\n",
+    "# vr_is_ca     = np.zeros([11,n_samples])\n",
+    "# vr_real      = np.zeros([11,n_samples]) \n",
+    "# var_total     = np.zeros([11,n_samples]) \n",
+    "# counter = 0\n",
+    "# for t in range(t_start,t_end):\n",
+    "#     for r in range(n_rand):\n",
+    "#         n = (t-t_start)*n_rand+r\n",
+    "#         np.random.seed(n)\n",
+    "#         counter = counter+1\n",
+    "#         truth_idx = r\n",
+    "#         for i in range(len(loc_values)): \n",
+    "                \n",
+    "#             da_const_vr = set_da_constants_22(loc_length=loc_values[i],obs_loc=np.arange(25,299,50))\n",
+    "            \n",
+    "#             vr_t, vr_i, vr_r, J_dict_LA,bla, quad,dx_ni =vr_reloaded_22(states[0]['bg'][t],states[0]['bg'][t][:,truth_idx],m_const,da_const_vr,reflectance_simulator,iterative_flag = 0,\n",
+    "#                                                                         obs_seed=counter,model_seed=counter,alpha=alpha_default)\n",
+    "#             var_total[i,n] = np.var(J_dict_LA['bf'],ddof=1)\n",
+    "#             vr_es[i,n]     = vr_t\n",
+    "#             vr_real[i,n]   = vr_r\n",
+    "            \n",
+    "#             vr_t, vr_i, vr_r,J_dict,dJdx_inv, bla_quad, dx = vr_reloaded_22_locsens(states[0]['bg'][t],states[0]['bg'][t][:,truth_idx],m_const,da_const_vr,reflectance_simulator,sens_loc_flag=1,\n",
+    "#                                                                  sens_loc_length=sens_loc_length,\n",
+    "#                                                                  obs_seed=i,model_seed=i,quad_state=quad)\n",
+    "#             vr_es_ca[i,n]     = vr_t\n",
+    "            \n",
+    "#             vr_t, vr_r, quad, J_dict_LA     = vr_individual_loc_22(states[0]['bg'][t],states[0]['bg'][t][:,truth_idx],m_const,da_const_vr,reflectance_simulator,advect_flag=1,quad_state=quad,obs_seed=counter,model_seed=counter)\n",
+    "#             vr_is_ca[i,n]  = vr_t\n",
+    "#     if np.floor(t/10) == t/10: print('completed timesteps:',t-39,' seconds spent computing so far:',np.floor(time.process_time()-start_time))\n",
+    "       "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.6.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/da_functions.py b/da_functions.py
index fefebff..8dc15c0 100644
--- a/da_functions.py
+++ b/da_functions.py
@@ -2821,3 +2821,167 @@ def vr_individual_loc_22(background,truth,m_const,da_const,sat_operator,response
 
    #     
    # 
+
+########################################################################################################################
+# 2023 
+########################################################################################################################
+def vr_reloaded_22_locsens(background,truth,m_const,da_const,sat_operator,
+                func_J=sum_mid_tri,
+                sens_loc_flag=0,sens_loc_length = 2000,sens_loc_adv_error=100,
+                reduc = 1,reg_flag=1,
+                quad_state = None,dJdx_inv=None,alpha=0.01,mismatch_threshold=0.1,
+                iterative_flag=0,explicit_sens_flag = 1,exp_num=0,obs_seed=0,model_seed=0):
+
+    """
+    Version of vr_reloaded_22 that includes the possibility to apply localization to the the sensitivity.
+    Takes only the background and truth, then caculates the quad, finaly calculates the response function and the variance reduction. 
+    
+    The quad can be supplied to save time, which makes sense when you comparing different methods for the same experiment calculating. 
+    
+    Should also return the dJ values of all 4 ensembles (analysis, background, forecast, blind forecast)
+    
+    
+    -reg_flag added to use L2 regularization
+    
+    not implemented:
+    - state model reduction
+    
+    
+    Speed up options: 
+    - If the same forecast can be recycled, the quad can be calculated once and than passed on. 
+    - If the sensitivity can be recycled, that can be calculated once and then reused. 
+    - Don't use LETKF
+
+    First getting the explicit all at once verion working, will then add the various approaches
+    
+    to be implemented:
+    -iteratively and all at once
+    -explicit vs implicit 
+    -reduced model spacing by subsampling the grid. Reduc is the spacing, eg reduc 3 means every third grid point is used. 
+     should find the nearest reduced model grid point for each observation.
+
+    
+
+    """
+    if iterative_flag ==0: from scipy.linalg import sqrtm
+    ###########################################################################
+    #First, need we calculate the quad (analysis, forecast, blind forecast)
+    #A precomputed quad_state can be supplied to quickly use different response functions
+    ###########################################################################
+    if type(quad_state)== type(None):
+        quad_state = single_step_analysis_forecast_22(background,truth,da_const,m_const,sat_operator,obs_seed=obs_seed,model_seed=model_seed)
+    
+    ###########################################################################
+    # Next we need the response functions. 
+    # We only really need the forecast and blind forecast, but for fun I'll calculate all for now
+    ###########################################################################
+    
+    #For now I am not worried about being efficient
+    nobs = len(da_const["obs_loc"])
+    obs = np.arange(nobs)
+    nens = da_const["nens"]
+    nstate = len(truth)
+
+    bf_response = np.zeros(nens)
+    fc_response = np.zeros(nens)
+    an_response = np.zeros(nens)
+    bg_response = np.zeros(nens)
+    for n in range(da_const["nens"]):
+        bf_response[n] = func_J(quad_state["bf"][:,n])
+        fc_response[n] = func_J(quad_state["fc"][:,n])
+        an_response[n] = func_J(quad_state["an"][:,n])
+        bg_response[n] = func_J(quad_state["bg"][:,n])
+        
+    J_dict = {}
+    J_dict['bf']  = bf_response
+    J_dict['bg']  = bg_response
+    J_dict['an']  = an_response
+    J_dict['fc']  = fc_response
+    J_dict['tr_bg']  = func_J(quad_state['tr_bg'])
+    
+
+
+    x = quad_state['bg'][:,:]
+        
+    dx = x.T-np.mean(x,axis=1)
+    dx = dx.T
+    dx_orig = dx+0
+    
+    A = np.dot(dx,dx.T)/(dx.shape[1]-1)
+
+    J  = bf_response
+    dJ      = J-np.mean(J)
+    dJ_orig = J-np.mean(J)
+    
+    if sens_loc_flag==1:
+        X_J =quad_state['bf'][:,:]
+        dX_J =  X_J.T - np.mean(X_J,axis=1)
+        dX_J = dX_J.T
+
+        dji = dX_J*1
+        dji[0:100,:] = 0. 
+        dji[200:300,:] = 0. 
+    
+    
+    ###############################################################################################
+    # Sensitivity
+    ###############################################################################################
+    #Covarianz between reponse function dJ and state ensemble dx
+    cov_dJdx_vec = np.dot(dJ,dx.T)/(dx.shape[1]-1)
+
+    if explicit_sens_flag==1:
+        #If a sensitivity is provided it is used instead of calculating it 
+        if type(dJdx_inv) == np.ndarray:
+            #testing supplied sensitivity
+            rel_error_sens = np.sum(np.abs(A.dot(dJdx_inv)-cov_dJdx_vec))/np.sum(np.abs(cov_dJdx_vec))
+            if rel_error_sens>0.05:
+                print('using supplied sensitivity has a relative error of:',rel_error_sens)
+        #Computing the sensitivity, highly recommend using the regularized version before doing so. 
+        else:
+            if reg_flag == 1:
+                dJdx_inv = L2_regularized_inversion(A,cov_dJdx_vec,alpha=alpha,mismatch_threshold=mismatch_threshold)
+            else:
+                A_inv = np.linalg.pinv(A)
+                dJdx_inv = np.dot(A_inv,cov_dJdx_vec)
+            if sens_loc_flag==1: 
+                da_const_wide = da_const.copy()
+                da_const_wide['loc_length'] = sens_loc_length
+                C_sens = loc_matrix(da_const_wide,m_const)
+                C_adv = C_sens*1.
+                for nn in range(m_const['nx']):
+                    C_adv[:,nn]     =semi_lagrangian_advection(C_sens[:,nn],m_const['dx'],+m_const['u_ref']*sens_loc_adv_error/100.   ,da_const['dt'])
+
+                sum_loc_cov_adv_djidX=np.sum(C_adv*np.dot(dji,dx.T),axis=0)/(da_const['nens']-1)
+                dJdx_inv = L2_regularized_inversion(C_sens*A,sum_loc_cov_adv_djidX,alpha=alpha)
+
+    estimated_J = bf_response + 0.
+    
+    
+    #if iterative_flag ==0:
+        
+    vr_individual = 0.
+    
+    
+    if explicit_sens_flag ==1:
+        #Tanjas approach of calculating the square root K following Kalman gain, formula (10) Whitaker and Hamil 2002
+        sqK = square_root_Kalman_gain_observation_deviations(x,m_const,da_const,sat_operator)
+        bg_obs_deviations,bg_obs_ol = state_to_observation_space(x,m_const,da_const,sat_operator)
+        dx_prime = dx - np.dot(sqK,bg_obs_deviations)
+        
+        #estimated J calculated by updating the original dJ
+        estimated_J = estimated_J -np.dot(dJdx_inv,np.dot(sqK,bg_obs_deviations))
+        
+        #Using the cheaper variance calculation instead of going to A-B
+        new_J = np.dot(dJdx_inv.T,dx_prime)
+        vr_total = np.var(new_J,ddof=1)-np.var(np.dot(dJdx_inv.T,dx),ddof=1)
+        #print('all at once:',vr_individual)
+        dx = dx_prime
+    
+  
+    J_dict['es'] =  estimated_J
+    
+    J_fc= fc_response
+    dJ_fc = J_fc-np.mean(J_fc)
+    real_reduction=np.var(dJ_fc,ddof=1) - np.var(dJ_orig,ddof=1)
+        
+    return vr_total,vr_individual,real_reduction,J_dict,dJdx_inv,quad_state,dx
\ No newline at end of file
-- 
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