diff --git a/DNN.ipynb b/DNN.ipynb index 63baf44..84927a7 100644 --- a/DNN.ipynb +++ b/DNN.ipynb @@ -34,9 +34,7 @@ "metadata": {}, "outputs": [], "source": [ - "l_index=1\n", - "mag_index=1\n", - "Ds_mass= 1968" + "l_index=1" ] }, { @@ -48,12 +46,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "Signal MC amounts to 23821 while bkg data amounts to 86051\n" + "Signal MC amounts to 47950 while bkg data amounts to 188715\n" ] } ], "source": [ - "MC_sig_dict, data_bkg_dict = load_datasets(l_index, mag_index)\n", + "MC_sig_dict, data_bkg_dict = load_datasets(l_index)\n", "m=MC_sig_dict[\"Ds_ConsD_M\"].shape[0]\n", "n=data_bkg_dict[\"Ds_ConsD_M\"].shape[0]\n", "\n", @@ -72,22 +70,24 @@ "MC_sig_dict[\"Ds_OWNPV_CHI2\"]=MC_sig_dict[\"Ds_OWNPV_CHI2\"]/MC_sig_dict[\"Ds_OWNPV_NDOF\"]\n", "MC_sig_dict[\"Ds_IPCHI2_OWNPV\"]=MC_sig_dict[\"Ds_IPCHI2_OWNPV\"]/MC_sig_dict[\"Ds_ENDVERTEX_NDOF\"]\n", "\n", - "del MC_sig_dict[\"Ds_ENDVERTEX_NDOF\"]\n", "del MC_sig_dict[\"Ds_OWNPV_NDOF\"]\n", + "del MC_sig_dict[\"Ds_ENDVERTEX_NDOF\"]\n", + "\n", "\n", "data_bkg_dict[\"Ds_ENDVERTEX_CHI2\"]=data_bkg_dict[\"Ds_ENDVERTEX_CHI2\"]/data_bkg_dict[\"Ds_ENDVERTEX_NDOF\"]\n", "data_bkg_dict[\"Ds_OWNPV_CHI2\"]=data_bkg_dict[\"Ds_OWNPV_CHI2\"]/data_bkg_dict[\"Ds_OWNPV_NDOF\"]\n", "data_bkg_dict[\"Ds_IPCHI2_OWNPV\"]=data_bkg_dict[\"Ds_IPCHI2_OWNPV\"]/data_bkg_dict[\"Ds_ENDVERTEX_NDOF\"]\n", "\n", - "del data_bkg_dict[\"Ds_ENDVERTEX_NDOF\"]\n", "del data_bkg_dict[\"Ds_OWNPV_NDOF\"]\n", + "del data_bkg_dict[\"Ds_ENDVERTEX_NDOF\"]\n", + "\n", "\n", "data_bkg_dict[\"phi_ENDVERTEX_CHI2\"]=data_bkg_dict[\"phi_ENDVERTEX_CHI2\"]/data_bkg_dict[\"phi_ENDVERTEX_NDOF\"]\n", "data_bkg_dict[\"phi_OWNPV_CHI2\"]=data_bkg_dict[\"phi_OWNPV_CHI2\"]/data_bkg_dict[\"phi_OWNPV_NDOF\"]\n", "data_bkg_dict[\"phi_IPCHI2_OWNPV\"]=data_bkg_dict[\"phi_IPCHI2_OWNPV\"]/data_bkg_dict[\"phi_ENDVERTEX_NDOF\"]\n", "\n", - "del data_bkg_dict[\"phi_ENDVERTEX_NDOF\"]\n", - "del data_bkg_dict[\"phi_OWNPV_NDOF\"]" + "del data_bkg_dict[\"phi_OWNPV_NDOF\"]\n", + "del data_bkg_dict[\"phi_ENDVERTEX_NDOF\"]\n" ] }, { @@ -138,8 +138,8 @@ "source": [ "#Convert data dictionaries to arrays for NN\n", "\n", - "MC_sig = extract_array(MC_sig_dict, branches_needed, dim, m)\n", - "data_bkg = extract_array(data_bkg_dict, branches_needed, dim, n)" + "MC_sig = extract_array(MC_sig_dict, branches_needed, dim, m//2)\n", + "data_bkg = extract_array(data_bkg_dict, branches_needed, dim, m)" ] }, { @@ -161,7 +161,6 @@ "outputs": [], "source": [ "#SOME CROSS CHECKS\n", - "#MC_sig.shape==data_bkg.shape\n", "#MC_sig_labelled.shape[1]==dim+1==data_bkg_labelled.shape[1]\n", "#data_bkg_labelled[:,dim].sum()==0\n", "#(MC_sig_labelled[:,dim].sum()/m)==1" @@ -171,54 +170,23 @@ "cell_type": "code", "execution_count": 10, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(101872, 4000, 4000)" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "#Establish train/val/test sizes\n", + "#Merge MC sig and data bkg, shuffle it\n", "\n", - "val_size=4000\n", - "test_size=4000\n", - "\n", - "train_size=MC_sig.shape[0]+data_bkg.shape[0]-val_size-test_size\n", - "(train_size, val_size, test_size)" + "data=np.concatenate((MC_sig_labelled,data_bkg_labelled), axis =0)\n", + "np.random.seed(1)\n", + "np.random.shuffle(data)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "#Merge MC sig and data bkg, shuffle it\n", - "\n", - "data=np.concatenate((MC_sig_labelled,data_bkg_labelled), axis =0)\n", - "np.random.seed(1)\n", - "np.random.shuffle(data)\n", - "\n", - "#Check that nothing is missing\n", - "\n", - "data.shape[0]==train_size+val_size+test_size" + "#Establish train/val/test sizes\n", + "train_size=m+m//2" ] }, { @@ -231,7 +199,7 @@ "\n", "X=data[:,0:dim]\n", "Y_labels=data[:,dim].astype(int)\n", - "Y_labels=Y_labels.reshape(train_size+val_size+test_size,1)\n", + "Y_labels=Y_labels.reshape(train_size,1)\n", "Y_labels_hot = to_one_hot(Y_labels)\n", "Y_labels=Y_labels_hot\n" ] @@ -242,46 +210,26 @@ "metadata": {}, "outputs": [], "source": [ - "#Divide the dataset in train/val/test sets \n", + "#Divide the dataset k \"equi populated\" sets\n", + "k=2\n", + "k_batch_size=train_size//k\n", "\n", - "X_train_0 = X[0:train_size]\n", - "Y_train = Y_labels[0:train_size]\n", + "X_dict={}\n", + "Y_dict={}\n", "\n", - "X_val_0 = X[train_size:train_size+val_size]\n", - "Y_val = Y_labels[train_size:train_size+val_size]\n", - "\n", - "X_test_0 = X[train_size+val_size:train_size+val_size+test_size]\n", - "Y_test = Y_labels[train_size+val_size:train_size+val_size+test_size]" + "for i in range(k):\n", + " X_dict[i]=X[k_batch_size*i:k_batch_size*(i+1)]\n", + " Y_dict[i]=Y_labels[k_batch_size*i:k_batch_size*(i+1)]\n", + "\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['Ds_ENDVERTEX_CHI2',\n", - " 'Ds_OWNPV_CHI2',\n", - " 'Ds_IPCHI2_OWNPV',\n", - " 'Ds_IP_OWNPV',\n", - " 'Ds_DIRA_OWNPV',\n", - " 'phi_ENDVERTEX_CHI2',\n", - " 'phi_OWNPV_CHI2',\n", - " 'phi_IPCHI2_OWNPV',\n", - " 'phi_IP_OWNPV',\n", - " 'phi_DIRA_OWNPV',\n", - " 'Ds_ConsD_M']" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "branches_needed" + "k=range(k)" ] }, { @@ -290,12 +238,37 @@ "metadata": {}, "outputs": [], "source": [ - "#Strip out the reconstructed Ds mass\n", + "#Strip out the reconstructed Ds mass and build train and test sets\n", + "i=0\n", "\n", - "X_train = X_train_0[:,0:dim-1]\n", - "X_val = X_val_0[:,0:dim-1]\n", - "X_test = X_test_0[:,0:dim-1]\n", - "dim=X_train.shape[1]" + "X_test = X_dict[k[i]][:,0:dim-1]\n", + "Y_test = Y_dict[k[i]][:,0:dim-1]\n", + "\n", + "k=np.delete(k, i)\n", + "\n", + "X_train = np.concatenate([X_dict[j][:,0:dim-1] for j in k],axis=0)\n", + "Y_train = np.concatenate([Y_dict[j][:,0:dim-1] for j in k],axis=0)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(35962, 10)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dim=X_train.shape[1]\n", + "X_train.shape" ] }, { @@ -307,19 +280,19 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ - "task='TRAIN'\n", - "#task='TEST'\n", + "#task='TRAIN'\n", + "task='TEST'\n", "\n", - "PATH=l_flv[l_index]+'_Mag'+mag_status[mag_index]+'_test_4'" + "PATH=l_flv[l_index]+'_test_'+str(i)" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -327,9 +300,7 @@ " with open(PATH+'/hyper_parameters.pkl', 'rb') as f: \n", " hyper_dict = pickle.load(f)\n", " \n", - " m=hyper_dict[\"m\"]\n", - " test_size=hyper_dict[\"test_size\"]\n", - " val_size=hyper_dict[\"val_size\"]\n", + " k=hyper_dict[\"k\"]\n", " LEARNING_RATE=hyper_dict[\"LEARNING_RATE\"]\n", " BETA1=hyper_dict[\"BETA1\"]\n", " BATCH_SIZE=hyper_dict[\"BATCH_SIZE\"]\n", @@ -343,11 +314,11 @@ "elif task=='TRAIN' and not os.path.exists(PATH+'/hyper_parameters.pkl'):\n", " \n", " \n", - " LEARNING_RATE = 0.001\n", + " LEARNING_RATE = 0.0001\n", " BETA1 = 0.5\n", " BATCH_SIZE = 64\n", - " EPOCHS = 20000\n", - " VAL_PERIOD = 2000\n", + " EPOCHS = 20\n", + " VAL_PERIOD = 5\n", " SEED=1\n", " LAMBD=1.\n", " \n", @@ -355,10 +326,10 @@ " 'dense_layers': [\n", " #(16, 'bn', 0.8, lrelu, tf.glorot_uniform_initializer()),\n", " #(8, 'bn', 0.5, lrelu, tf.glorot_uniform_initializer()),\n", - " #(16, 'bn',0.8, lrelu, tf.glorot_uniform_initializer()),\n", - " (32, 'bn', 0.8, lrelu, tf.glorot_uniform_initializer()),\n", - " (16, 'bn', 0.8, lrelu, tf.glorot_uniform_initializer()),\n", - " (8, 'bn', 0.8, lrelu, tf.glorot_uniform_initializer()),\n", + " (16, 'bn',0.5, lrelu, tf.glorot_uniform_initializer()),\n", + " (32, 'bn', 0.5, lrelu, tf.glorot_uniform_initializer()),\n", + " (16, 'bn', 0.5, lrelu, tf.glorot_uniform_initializer()),\n", + " (8, 'bn', 0.5, lrelu, tf.glorot_uniform_initializer()),\n", " ],\n", " 'n_classes':2,\n", " }" @@ -366,7 +337,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -376,9 +347,7 @@ " #for key, item in hyper_dict.items():\n", " # print(key+':'+str(item))\n", " \n", - " m=hyper_dict[\"m\"]\n", - " test_size=hyper_dict[\"test_size\"]\n", - " val_size=hyper_dict[\"val_size\"]\n", + " k=hyper_dict[\"k\"]\n", " LEARNING_RATE=hyper_dict[\"LEARNING_RATE\"]\n", " BETA1=hyper_dict[\"BETA1\"]\n", " BATCH_SIZE=hyper_dict[\"BATCH_SIZE\"]\n", @@ -392,12 +361,16 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "def bkg():\n", " \n", + " batch_size_output=128\n", + " test_size=k_batch_size\n", + " n_batches_output = test_size//batch_size_output\n", + " \n", " tf.reset_default_graph()\n", " nn = DNN(dim, sizes,\n", " lr=LEARNING_RATE, beta1=BETA1, lambd=LAMBD,\n", @@ -430,7 +403,7 @@ " print('Model restored.')\n", " \n", " nn.set_session(sess)\n", - " nn.fit(X_train, Y_train, X_val, Y_val)\n", + " nn.fit(X_train, Y_train, X_test, Y_test)\n", " \n", " save_path = saver.save(sess, PATH+'/CNN_model.ckpt')\n", " print(\"Model saved in path: %s\" % save_path)\n", @@ -443,16 +416,22 @@ " nn.set_session(sess)\n", " nn.test(X_test, Y_test)\n", " \n", - " output = nn.predict(X_test)\n", " \n", + " output_dict={}\n", + " \n", + " for i in range(n_batches_output):\n", + " small_dataset = X_test[i*batch_size_output:(i+1)*batch_size_output]\n", + " output_dict[i] = nn.predict(small_dataset)\n", + " \n", + " output=np.concatenate([output_dict[i] for i in range(n_batches_output)])\n", " return output\n" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 29, "metadata": { - "scrolled": true + "scrolled": false }, "outputs": [ { @@ -464,65 +443,10 @@ "Input for propagation (?, 10)\n", "Logits shape (?, 2)\n", "\n", - " Training...\n", - "\n", - " ****** \n", - "\n", - "Training CNN for 20000 epochs with a total of 101872 samples\n", - "distributed in 1591 batches of size 64\n", - "\n", - "The learning rate set is 0.001\n", - "\n", - " ****** \n", - "\n", - "Evaluating performance on validation/train sets\n", - "At iteration 0, train cost: 0.003296, train accuracy 0.9763\n", - "validation accuracy 0.9898\n", - "Evaluating performance on validation/train sets\n", - "At iteration 2000, train cost: 0.002107, train accuracy 0.9792\n", - "validation accuracy 0.9375\n", - "Evaluating performance on validation/train sets\n", - "At iteration 4000, train cost: 0.001401, train accuracy 1\n", - "validation accuracy 1\n", - "Evaluating performance on validation/train sets\n", - "At iteration 6000, train cost: 0.003771, train accuracy 1\n", - "validation accuracy 1\n", - "Evaluating performance on validation/train sets\n", - "At iteration 8000, train cost: 0.001128, train accuracy 1\n", - "validation accuracy 1\n", - "Evaluating performance on validation/train sets\n", - "At iteration 10000, train cost: 0.0007949, train accuracy 1\n", - "validation accuracy 1\n", - "Evaluating performance on validation/train sets\n", - "At iteration 12000, train cost: 0.0005857, train accuracy 1\n", - "validation accuracy 1\n", - "Evaluating performance on validation/train sets\n", - "At iteration 14000, train cost: 0.0006453, train accuracy 1\n", - "validation accuracy 1\n", - "Evaluating performance on validation/train sets\n", - "At iteration 16000, train cost: 0.0004602, train accuracy 1\n", - "validation accuracy 1\n", - "Evaluating performance on validation/train sets\n", - "At iteration 18000, train cost: 0.0005284, train accuracy 1\n", - "validation accuracy 1\n" - ] - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Parameters trained\n", - "Model saved in path: mu_MagDown_test_4/CNN_model.ckpt\n" + " Evaluate model on test set...\n", + "INFO:tensorflow:Restoring parameters from mu_test_0/CNN_model.ckpt\n", + "Model restored.\n", + "Test accuracy: 0.9935\n" ] } ], @@ -562,22 +486,33 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 31, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "if task=='TEST':\n", "\n", " Ds_mass_MC =[MC_sig_dict[\"Ds_ConsD_M\"][i][0] for i in range(m)]\n", - " NN_selected = X_test_0[np.argmax(output, axis=1).astype(np.bool)]\n", + " NN_selected = X_dict[k[i]][0:output.shape[0]][np.argmax(output, axis=1).astype(np.bool)]\n", " Ds_mass_sel_NN = [NN_selected[i][dim] for i in range(NN_selected.shape[0])]\n", - " Ds_mass_train_NN =[X_train_0[i][dim] for i in range(X_train_0.shape[0])]\n", + " Ds_mass_train_NN =X_dict[k[i]][:,dim]\n", "\n", " plt.subplot(1,2,1)\n", " plt.hist(Ds_mass_MC,bins=70);\n", " plt.subplot(1,2,2)\n", " plt.hist(Ds_mass_sel_NN,alpha=0.8,bins=70);\n", - " #plt.hist(Ds_mass_train_NN,alpha=0.2,bins=70);\n", + " plt.hist(Ds_mass_train_NN,alpha=0.2,bins=70);\n", "\n", " fig=plt.gcf();\n", " fig.set_size_inches(20,8)" @@ -585,15 +520,13 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "if task=='TRAIN':\n", " hyper_dict={\n", - " 'm':m,\n", - " 'test_size':test_size,\n", - " 'val_size':val_size,\n", + " 'k':k,\n", " 'LEARNING_RATE':LEARNING_RATE,\n", " 'BETA1':BETA1,\n", " 'BATCH_SIZE':BATCH_SIZE,\n", @@ -614,6 +547,13 @@ "metadata": {}, "outputs": [], "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/DNN_selection.ipynb b/DNN_selection.ipynb index f8d9343..b47498f 100644 --- a/DNN_selection.ipynb +++ b/DNN_selection.ipynb @@ -134,18 +134,18 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 51, "metadata": {}, "outputs": [], "source": [ "task='TEST'\n", "\n", - "PATH=l_flv[l_index]+'_Mag'+mag_status[mag_index]+'_test_4'" + "PATH=l_flv[l_index]+'_Mag'+mag_status[mag_index]+'_test_3'" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 52, "metadata": {}, "outputs": [], "source": [ @@ -157,7 +157,6 @@ " \n", " #m=hyper_dict[\"m\"]\n", " test_size=hyper_dict[\"test_size\"]\n", - " val_size=hyper_dict[\"val_size\"]\n", " LEARNING_RATE=hyper_dict[\"LEARNING_RATE\"]\n", " BETA1=hyper_dict[\"BETA1\"]\n", " BATCH_SIZE=hyper_dict[\"BATCH_SIZE\"]\n", @@ -171,7 +170,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 53, "metadata": {}, "outputs": [], "source": [ @@ -214,21 +213,23 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 54, "metadata": { "scrolled": true }, "outputs": [ { - "ename": "NameError", - "evalue": "name 'sizes' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'No checkpoint'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbkg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m\u001b[0m in \u001b[0;36mbkg\u001b[0;34m(data)\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_default_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m nn = DNN(dim, sizes,\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0mlr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mLEARNING_RATE\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbeta1\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mBETA1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlambd\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mLAMBD\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mBATCH_SIZE\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mEPOCHS\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'sizes' is not defined" + "name": "stdout", + "output_type": "stream", + "text": [ + "Input for propagation (?, 10)\n", + "Logits shape (?, 2)\n", + "Input for propagation (?, 10)\n", + "Logits shape (?, 2)\n", + "\n", + " Selecting signal events with model...\n", + "INFO:tensorflow:Restoring parameters from mu_MagDown_test_3/CNN_model.ckpt\n", + "Model restored.\n" ] } ], @@ -242,25 +243,53 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 55, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0.84979254, 0.15020742],\n", + " [0.8513052 , 0.14869481],\n", + " [0.84863734, 0.15136267],\n", + " ...,\n", + " [0.8504716 , 0.14952841],\n", + " [0.85030866, 0.14969133],\n", + " [0.8818852 , 0.11811486]], dtype=float32)" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "output" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 56, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.argmax(output, axis=1).astype(np.bool).sum()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 57, "metadata": {}, "outputs": [], "source": [ @@ -270,7 +299,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 58, "metadata": {}, "outputs": [], "source": [ @@ -280,7 +309,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 59, "metadata": {}, "outputs": [], "source": [ @@ -289,9 +318,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 60, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plt.hist(full,alpha=0.4,bins=100, range=(0,3000));\n", "plt.hist(NN_selected,alpha=0.4,bins=100, range=(0,3000));\n", @@ -301,9 +341,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "9" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.random.randint(14)" ] diff --git a/dataMC_visualization.ipynb b/dataMC_visualization.ipynb index 10ed703..196209f 100644 --- a/dataMC_visualization.ipynb +++ b/dataMC_visualization.ipynb @@ -32,7 +32,6 @@ "source": [ "l_flv = ['e','mu']\n", "data_type = ['MC','small_data']\n", - "mag_status =['Up','Down'] \n", "tree_name = 'Ds_OfflineTree/DecayTree'" ] }, @@ -43,8 +42,7 @@ "outputs": [], "source": [ "l_index = 1\n", - "#data_index = None \n", - "mag_index = 1" + "data_index = None " ] }, { @@ -53,8 +51,8 @@ "metadata": {}, "outputs": [], "source": [ - "def find_file_path(l_index, type_index, mag_index): \n", - " return \"/disk/lhcb_data/davide/Rphipi/\"+data_type[type_index]+\"/Ds_phipi_\"+l_flv[l_index]+l_flv[l_index]+\"/Ds_phipi_\"+l_flv[l_index]+l_flv[l_index]+\"_Mag\"+mag_status[mag_index]+\".root\"" + "def find_file_path(l_index=l_index, data_index=data_index): \n", + " return \"/disk/lhcb_data/davide/Rphipi/\"+data_type[data_index]+\"/Ds_phipi_\"+l_flv[l_index]+l_flv[l_index]+\"/Ds_phipi_\"+l_flv[l_index]+l_flv[l_index]+\".root\"" ] }, { @@ -63,8 +61,8 @@ "metadata": {}, "outputs": [], "source": [ - "data = r.TFile(find_file_path(l_index, 1, mag_index))\n", - "MC = r.TFile(find_file_path(l_index, 0, mag_index))" + "data = r.TFile(find_file_path(l_index=l_index, data_index=1))\n", + "MC = r.TFile(find_file_path(l_index=l_index, data_index=0))" ] }, { @@ -75,7 +73,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -96,7 +94,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 7, @@ -115,68 +113,10 @@ "metadata": {}, "outputs": [], "source": [ + "#Switch on only the branches that you need\n", "t_data.SetBranchStatus(\"*\",0)\n", - "t_data.SetBranchStatus(\"Ds_ENDVERTEX_CHI2\",1)\n", - "t_data.SetBranchStatus(\"Ds_ENDVERTEX_NDOF\",1)\n", - "t_data.SetBranchStatus(\"Ds_OWNPV_CHI2\",1)\n", - "t_data.SetBranchStatus(\"Ds_OWNPV_NDOF\",1)\n", - "t_data.SetBranchStatus(\"Ds_IP_OWNPV\",1)\n", - "t_data.SetBranchStatus(\"Ds_IPCHI2_OWNPV\",1)\n", - "t_data.SetBranchStatus(\"Ds_DIRA_OWNPV\",1)\n", - "t_data.SetBranchStatus(\"Ds_ConsD_M\",1)\n", + "t_MC.SetBranchStatus(\"*\",0)\n", "\n", - "t_data.SetBranchStatus(l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index], 1)\n", - "t_data.SetBranchStatus(\"Ds_Hlt1TrackMVADecision_TOS\", 1)\n", - "t_data.SetBranchStatus(\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\", 1)\n", - "t_data.SetBranchStatus(\"Ds_Hlt2Phys_TOS\", 1)\n", - "\n", - "\n", - "t_MC.SetBranchStatus(\"Ds_ENDVERTEX_CHI2\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_ENDVERTEX_NDOF\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_OWNPV_CHI2\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_OWNPV_NDOF\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_IP_OWNPV\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_IPCHI2_OWNPV\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_DIRA_OWNPV\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_ConsD_M\", 1)\n", - "\n", - "t_MC.SetBranchStatus(l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index], 1)\n", - "t_MC.SetBranchStatus(\"Ds_Hlt1TrackMVADecision_TOS\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\", 1)\n", - "t_MC.SetBranchStatus(\"Ds_Hlt2Phys_TOS\", 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "t_data.SetBranchStatus(\"phi_ENDVERTEX_CHI2\",1)\n", - "t_data.SetBranchStatus(\"phi_ENDVERTEX_NDOF\",1)\n", - "t_data.SetBranchStatus(\"phi_OWNPV_CHI2\",1)\n", - "t_data.SetBranchStatus(\"phi_OWNPV_NDOF\",1)\n", - "t_data.SetBranchStatus(\"phi_IP_OWNPV\",1)\n", - "t_data.SetBranchStatus(\"phi_IPCHI2_OWNPV\",1)\n", - "t_data.SetBranchStatus(\"phi_DIRA_OWNPV\",1)\n", - "\n", - "\n", - "t_MC.SetBranchStatus(\"phi_ENDVERTEX_CHI2\", 1)\n", - "t_MC.SetBranchStatus(\"phi_ENDVERTEX_NDOF\", 1)\n", - "t_MC.SetBranchStatus(\"phi_OWNPV_CHI2\", 1)\n", - "t_MC.SetBranchStatus(\"phi_OWNPV_NDOF\", 1)\n", - "t_MC.SetBranchStatus(\"phi_IP_OWNPV\", 1)\n", - "t_MC.SetBranchStatus(\"phi_IPCHI2_OWNPV\", 1)\n", - "t_MC.SetBranchStatus(\"phi_DIRA_OWNPV\", 1)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ "branches_needed = [\n", " \"Ds_ENDVERTEX_CHI2\",\n", " \"Ds_ENDVERTEX_NDOF\",\n", @@ -187,6 +127,7 @@ " \"Ds_DIRA_OWNPV\",\n", " \"Ds_ConsD_M\",\n", " l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index],\n", + " l_flv[l_index]+\"_minus_MC15TuneV1_ProbNN\"+l_flv[l_index],\n", " \"Ds_Hlt1TrackMVADecision_TOS\",\n", " \"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\",\n", " \"Ds_Hlt2Phys_TOS\",\n", @@ -198,77 +139,72 @@ " \"phi_IP_OWNPV\",\n", " \"phi_IPCHI2_OWNPV\",\n", " \"phi_DIRA_OWNPV\",\n", + " \"phi_M\",\n", + " ] \n", "\n", - " ] " + "for branch in branches_needed:\n", + " t_data.SetBranchStatus(branch, 1)\n", + " t_MC.SetBranchStatus(branch, 1)" ] }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "MC_count=0\n", - "for event in enumerate(t_MC):\n", - " MC_count+=1\n", - " \n", - "data_count=0\n", - "for event in enumerate(t_data):\n", - " data_count+=1" - ] - }, - { - "cell_type": "code", - "execution_count": 12, + "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "MC event count 24354, real data event count 106404\n" + "MC event count 49002, data event count 233629\n" ] } ], "source": [ - "print(\"MC event count {0}, real data event count {1}\".format(MC_count,data_count))" + "#Count the events in the tuple\n", + "\n", + "MC_count=0\n", + "for event in enumerate(t_MC):\n", + " MC_count+=1\n", + " \n", + "data_count=0\n", + "for event in enumerate(t_data):\n", + " data_count+=1\n", + "print(\"MC event count {0}, data event count {1}\".format(MC_count,data_count))" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 32, "metadata": {}, "outputs": [], "source": [ + "#Create a dictionary\n", + "\n", + "#dict ={'branch_name'=[branch_value[event]]}\n", + "\n", "MC_tuple_dict = {}\n", "\n", - "for i in range(len(branches_needed)):\n", + "for branch in branches_needed:\n", " \n", - " MC_tuple_dict[branches_needed[i]] = rn.root2array(\n", + " MC_tuple_dict[branch] = rn.root2array(\n", " \n", - " filenames=find_file_path(l_index, 0, mag_index),\n", + " filenames=find_file_path(l_index, 0),\n", " treename = tree_name,\n", - " branches = branches_needed[i],\n", + " branches = branch,\n", " start=0,\n", " stop=MC_count,\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ + " )\n", + " \n", "data_tuple_dict = {}\n", "\n", - "for i in range(len(branches_needed)):\n", + "for branch in branches_needed:\n", " \n", - " data_tuple_dict[branches_needed[i]] = rn.root2array(\n", + " data_tuple_dict[branch] = rn.root2array(\n", " \n", - " filenames=find_file_path(l_index, 1, mag_index),\n", + " filenames=find_file_path(l_index, 1),\n", " treename = tree_name,\n", - " branches = branches_needed[i],\n", + " branches = branch,\n", " start=0,\n", " stop=data_count,\n", " )" @@ -276,22 +212,12 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "Ds_constrained_mass_MC = np.array([MC_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(MC_tuple_dict[\"Ds_ConsD_M\"]))])\n", - "Ds_constrained_mass_data = np.array([data_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"]))])" - ] - }, - { - "cell_type": "code", - "execution_count": 16, + "execution_count": 33, "metadata": {}, "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -303,6 +229,10 @@ } ], "source": [ + "#Check the Ds mass plot\n", + "\n", + "Ds_constrained_mass_MC = np.array([MC_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(MC_tuple_dict[\"Ds_ConsD_M\"]))])\n", + "Ds_constrained_mass_data = np.array([data_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"]))])\n", "plt.subplot(1,2,1)\n", "plt.hist(Ds_constrained_mass_MC,bins=70, range=(0,3000));\n", "plt.subplot(1,2,2)\n", @@ -313,368 +243,46 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "data_bkg_indices_over=[]\n", - "data_bkg_indices_under=[]\n", - "\n", - "MC_sig_indices=[]" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"])):\n", - " #retrieving the Ds reconstructed mass\n", - " Ds_m = data_tuple_dict[\"Ds_ConsD_M\"][i][0]\n", - " \n", - " #selecting the out of signal regions\n", - " if 0np.max(data_under_Ds_endvtx_chi2ratio):\n", - " max_endvchi2_under=np.max(MC_Ds_endvtx_chi2ratio)\n", - "else:\n", - " max_endvchi2_under=np.max(data_under_Ds_endvtx_chi2ratio)\n", - " \n", - "if np.max(MC_Ds_endvtx_chi2ratio)>np.max(data_over_Ds_endvtx_chi2ratio):\n", - " max_endvchi2_over=np.max(MC_Ds_endvtx_chi2ratio)\n", - "else:\n", - " max_endvchi2_over=np.max(data_over_Ds_endvtx_chi2ratio)" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [], - "source": [ - "h_mc_under= r.TH1F(\"Ds end vertex MC/data comparison under\", \"Ds end vertex MC/data under Ds mass comparison\",nbins, 0, max_endvchi2_under)\n", - "h_mc_over = r.TH1F(\"Ds end vertex MC/data comparison over\", \"Ds end vertex MC/data over Ds mass comparison\",nbins, 0, max_endvchi2_over)\n", - "\n", - "for i in range(len(MC_Ds_endvtx_chi2ratio)):\n", - " h_mc_under.Fill(MC_Ds_endvtx_chi2ratio[i])\n", - " h_mc_over.Fill(MC_Ds_endvtx_chi2ratio[i])\n", - "\n", - "n1=h_mc_under.Integral(\"width\")\n", - "h_mc_under.Scale(1/n1)\n", - "h_mc_under.Integral(\"width\");\n", - "n2=h_mc_over.Integral(\"width\")\n", - "h_mc_over.Scale(1/n2)\n", - "h_mc_over.Integral(\"width\");" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, max_endvchi2_under)\n", - "h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, max_endvchi2_over)\n", - "for i in range(len(data_under_Ds_endvtx_chi2ratio)):\n", - " h_data_under.Fill(data_under_Ds_endvtx_chi2ratio[i])\n", - "for i in range(len(data_over_Ds_endvtx_chi2ratio)):\n", - " h_data_over.Fill(data_over_Ds_endvtx_chi2ratio[i])\n", - " \n", - " \n", - "n2=h_data_under.Integral(\"width\")\n", - "h_data_under.Scale(1/n2)\n", - "h_data_under.Integral(\"width\");\n", - "n3=h_data_over.Integral(\"width\")\n", - "h_data_over.Scale(1/n3)\n", - "h_data_over.Integral(\"width\");" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAAHnCAYAAABALvsIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3Xm8TfX+x/HXB8c56BxzyBCRShMZM8VVosjQKdStNGm4zaNugyG3uqluSbfxJ5UudbsJDVRkChVREYmSFKnIEZm/vz++ax/77OGcvTnHFu/n43Ee7O/6rrW+e+3vGj5rfdf3a845RERERERERFKhWKoLICIiIiIiIgcvBaUiIiIiIiKSMgpKRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIiIiIimjoFSkkJhZXzNzZtY31WU5GJnZqGD710hinlVmtqwoy5UqZjYk2B6tC2FZbc1shpltCpY5tzDKGLGOQitvUTOzekFZn0t1WVLhz/Rb7S/M7NRgm92V6rLsTw72fSmVzGymme1IdTlEQhSUSqEJTizhfzvMbL2ZfW5mz5tZNzMrXoTrXxGjDJF/fYtq/UmUs2xwcf+HmZUvIG9NM9tpZmvNrGQRlUcXBSlgZicH2/36VJclP2ZWEXgLOBZ4FhgEPJPAfKXM7FYz+8jMNgTHg9/MbL6ZPWdmpxRx0fcbYfuYM7McMysTJ1+xiONYzKDPzCqZ2T1mNtvMfjWz7cG/083sDjM7NJ+yLDGz+YX13fbGntxIEhGRA1OJVBdADkiDgn+LA+XwF7PnAX2Bz83sHOfc0iJc/2PAb3GmLSjC9SbEObfBzP4LXARcAAzLJ/sl+JtHLzjntu2L8h1kTgFcitbdI/h3bIrWn6hTgEOAm5xz/0pkBjPLBGYAJwIrgNHAz0BZoCG+7pcApoXN9igwCviusAq+H9oBZAK9gBExpncEDg/yxTw/m1k34EUgC1gK/I/d27Yp8A/g72ZWxzn3S8S8DYCjgHsK48uIyJ/aeUCpVBdCJERBqRQ659zAyDQzqwI8DpwDvG9mTZxza4uoCI8651YU0bILyzP4C/PLiBOUmlkx4OKw/FLInHPLU7j6HsA859zKFJYhEaGn+T8nMc/N+IB0LHCucy5PE7GghcDR4WlBAJUniDoAfQzUAy4ndlB6OfAHMB04PXKimf0FeA3YDlwIjHLOuYg8x+GPKRkxlv9nuREiIkXsT3DukYOMmu/KPuGc+wnoDUwFagJ/D58eNG972cx+DJqibTKzxUGz34pFUabwd0DNrL2ZTTWzjUHzurfM7Jg489Uzs/8GTZM3mdksMzszmXU752YBi4Djzax5nGyhpyZTnXNfR5Shppn928y+MbOtQdO9cWbWOEZ5c9//MrMLzOxjM/vdzJaZ2RAgtOxLI5o6/zViOZ3N7J1gXVvNbLmZPWhmWRH5bg3mfyVGWTqZ2S4zW2BmsS6ao5hZ6aBJ4qdBubeZ2ddm9lScZopmZleb2UIz22Jma4K8WTEyRr1TambpZnZX2PzbzeyH4LufGmMZ5wdl22K+mfULZlbV8nlfJwgc6hEWHET8Tr3M7BMz2xxs7/+YWbU4y2pqZpOCurvBzN7Lp06F5ukYzLM+KPdXZnZf+DYK6rkDQs26X4pXN2JoGfz7ZGRACuCcW++cmx1RprjvKZrZheab/Ya28YtmViPWNrawd/fM7KTgd9sQ7KtTY22bYFkPmG9q/FvYb/6ymR0dmX8vbAdeAFoEdSC8DFWArsB/idHSw/yrD0/jbyZf45x7KTIgBXDOLQROBdbEWH8PYFmQp0DJ1i0zO9fMXjOz74L99Hczm2tm15i/yRbKVyKoW+cHSd+H1a1lYfmamdkzZrYo2Be2mNlSMxtqZuUS+Q7BcvJ9RaGw6lEwXzXz56215l/RmG9mFxRQvopm9k/zTau3BHXwvTjHm8tC+6CZnWFm04JybU9gO4SaS9cyf5z+Kljf92b2sPkWDrHmS+Z8Uyj7kvmm7E8E5f2vJX6+aGFmr9rua4l1ZjbFzHrHyNvb/LvyOcFv9bmZ3W4xXpWx4FxhZuXMbFjweVtQN88J8qSbP459F6x7uZldFWNZ4XWrlZlNDsqQE9Szk2LMk9R2Da/zZnZUsA1/Nn/+bR3kiVXvzfz+Oi+o6zvM7KdgG/aKsZ6mZjY2WPZW868fDDezqjHyhupfTUvwHC0HFz0plX3GObfLfBDUDuhjZjc655z5i+2P8M3axgNf4evmkUA34GHg1yIsWpfgbzz+CcPR+Iu3pmbWILwJnJkdCcwGKgLv4JsD1wPeCD4n41l8k8XL8N8/0mVh+XKZWRNgEr753lv4ppEVgWxglpl1dc69G2N5twPt8U9a3sVv7ynBcq4F5uO3QcjnYescDNwNrMZfNP8KnADcAnQys5bOud+D7A8F6znXzCY7554JlnEYvtnhJqCXc25LfhsnmKci8AFwPLAY+L9g/nr4JpCjgMgn7g8H638dmAB0AK4A6gKnFbRO4CX8E/1PgSfwT66qAq3xF/vvh5XvVuBBYD0wEtgAdAY+BDbns46ewb+xnlhdB5zB7t+pOdAHONHMGoU34zazNkGeNHwzzuVAI3yz2KmxVmxmf8O3Wvgd/1v+jN9edwBdzay1c24DsA7fFP8kfLA0lt114vPI5UYI/bZHAu8VkDdfZvZ3fJPUdezexh2BmcF3iKcZ/jtNwf+OtfB1ZoqZNYy40dMOX0em4Z9SbgXq43+nrkH9TiiQS8BzwK34/fuGsPS++N/xWeCaGPP9BV/vv8Nvh7icc7uAXeFpZlYLaAwMTaSQe1K38L/T78BEfL3KxO9/jwfrDrX82IWvWz3x+/a/gJxg2rqw5fXD77MzgHH4V0KasPu408I5tymR77MXEq5H5m+SzQJq4+vRLKA6/jedFGvhZlYHf4yrhT+2jAXK4M9B75rZpc6552PM2gu/H7yB376HJ/GdHgfaAK+y+5h1E9DazNo657aGlS/Z80079nJfMrNSwH+A7vjXcW4K6nS+zOxK/G+0HX8u+zoodwvgUmBMWN4H8fvhz/jzyCbgTOABoKOZdXLORQb66fh6kBZsh1L4GyuvmNkm/LG7Pv433IX/jf5tZpuccy/GKHJLfFP6d4Hh+ONlT+AUMzs1uHkd0o4926718S005uOPPVnAxthbEIB/BtvlqyB/DlAZvx90B3JvNptZd3wdcvjz1Ur8KwR/A7qZWas4T2P39hwtByrnnP70Vyh/+AOTKyBPOv6E4YA6Qdq1wecrYuTPADISXP+KYDmPAgPj/GWE5e8b5N8CtIxY1t3BtNsi0t8N0q+JSO8a+v5A3wTLWx4f8GwEDomYdiiwDd+cMT0sPQ34Bn8h0SRinqrBNlgFlAxLHxKUaz1QP0Y56gXTn4tTztOC6e8BZSKm9Q6mDY1IrwT8gA/MjsO3yvggyHtBEnUqdML7F2AR00oBWWGfRwV5vwIqh6UXw19IOOCkiGWswj85Cn2ugL+YmB65vtBvFvb/ukFd/gmoFZZeHH8R74Adcb7XfGBJRFrod1oL1I2Y9kIwrWfE9/o6KG/niPw3hNXH1mHpRwT16tfIugA8GeT/d0T6ZUH6X5P43c5n9741HB9kVy1gniExyntksI1/BKpHfPfRsbYx/saBC7ZL94hpFwfThkWkVyZsPwtLPxYfZE1IZp/JZx+bGnyeGvwG6cFnC37LxcHnMTG2xaAgbWSiv0NEGa4P5m+RQN6k61YwrWaMZRm+qbIDGkdMC+2zNeKUI176RcF8Nye5/eMd42YWUj0Kfc8HItKb4YMIB9wVY93bgTMi0jOBT/DBUvjxLLQ/bgNaJVkHQtt7dfhvRd5j1h1h6XtyvtmrfQkf8M4KtntCv28w3wn4d7HXAMfEmF417P9tgnUuBw4NSy+BD5JinftXBemjgWJh6S2C9I34gLFU2LTa+GPg53HqlgMui5jWI0hfQtg5aC+2qwNuTaLebwi2S8kY+cuF/T8Lf02xlejrp/7Bet+OU/8SPkfr7+D6S3kB9Hfg/IUOgAnkWxPkbRZ8viX43G8v178i7CAc7y/8oNo3/GQYsazqwbTXwtJqBGmL46z/bZIISoN5XopzYro1SH8kIv3sIH1AnOVdE0zvGJYWuti/N848BV2wTcBfINSOM30u8GOM9FPwFwmL8Hdfk7qgBqoF6/0GKJ5A/tAJr3eMaaGL2Csj0iOD0qpBvmkJrG9AkPeWGNNqADuJEZTiL1QccH9Eeuh36h9nW+a52A1LezNGfsOf+B15A5sB+ayjDP6u+O9AWlh60kFpMN9N+Auc8P3vx+B3ah0jf6ygdGCQdkOc+hG1jdl9wTcxxjxp+IuoOUl8jzfwN1eKh6XtbVAaCtrPCz63Dz7fFHyOFZQ+E6QNSeZ3CJt/Kv5GUdTNlnzqW8J1q4DlNQzy/z0iPd+gtIBlrgfeTXL770lQmlA9wt9w/QN/syHWBX3o97srLK1xkPZ8nHJ1IeLcGLY/vrQH2yy0vWPtT6Fj1tdhaUmfbwpYf777ElAnqFtb8a1pkvluoZtqlySQ93ninysOx593lkakrwrSq8WYZ3mwvOYxpk0O5isdo24tiFO+0M3vhG46FLBdV8bb5+PU+z+AZbHqcES+0Dn1qRjTLFiGI+/NxKTP0fo7uP7UfFdSwYJ/Q/XvDfxTgOHm36F5F99E9kvn/NEqSXVcch0dfRIjbXXwb/iQLY2Cf6fHWc5UfDOoZDwD/BXfwUn4+04xm+4CJwf/1jezgTGWVy/49xj8dgw3J8myha/zD6CvmcWangFUM7Oyzjf7BMA5N83M7sUHFg3wd37/lsR6m+HryrvOuZ1JzJfo7xnFObfGzD4A2pvZPHzzog+Bj5xzf0RkD733My0iHefcKjNbjn8yGamgzmYSLX9+63dmNg3fdCtWmSfHmGeTmX2Ev2Cqj7+ZsMecc4+Y2dP4J+0t8YFJc3xAdr6ZDXDODS5gMaF9bkaM5a82//5h3TjzRm1H59x2M/uVGPXAzM7CNyFrjH9aE3l+rEBynT3l53/4JpSX45sp9sM/+YrVxG+vmVklfPPzZxI8pu5J3Qqt51b8k/E6+Bsd4aonWe404Cp8M8gG+Kcz4X1hJLW8PZRoPWqAPxZOcbF7Sp+K/73DhY7nh8Y5nlcK/o3Vv8GeHs8h/2PWkWaW6ZzbyB6eb/ZwX2qAP+9nAKc756Ym84XwTyzB3xwuSH7Hwe/CtsMhbvdrKeBvvq6OnAffWuYIYF6caYbvHTvylY6o3yEwFX/cbIQ//wB7vF0/SvI6ajS+JcDn5kcJmAnMds7lROTLbxu64DxaF3/c/yEiyx6fo+XApqBU9inznRVUCD7+BOCcW2ZmrfDvVpyBf58PfOcXDznn8hsypTBsjUxw/v1X8M2aQsoG/66LzF9AelzOuRlmtgRoZmbHO+e+MLO2+Au+mc65xRGzhDp9Oq+ARR8SI21DjLREVMCfVAcksM7IdfwvmM+AZ11y73+FOjJJtkfWqN+T3e/XJTJObjfgTvx7nEOCtD+CE/Stbnev0YnUh1hBaU/8XfdYJ2ZIvPx7Uh8Lmif07nbCncjkJ/i93wj+QkHGpfh3twea2Vjn3Bf5LCJU3nhDPK3PZ95Y2xH8tsxTD8zsZvy70Ovw7/V9h78R49j93mN6PutKinNui5m9BFxrZi3wNyrGuoghXCKELtr2JBDrhv/Oifa6m3TdMrMK+FYTh+PfkX8xyLcDfwy5luS34f/wr0Ysx5f9J3b/rjftwfL2RKL1aE/2x9Dx/IzgL57CPJ7HK0t4eui9w6TPN3uxLx2Fryfz8K83JCuZ80Uix8F6Qb7woDRePwi7gJ0uRqdu5H/uKeh3CJVzb7ZrsvXkCnzT/YuAu4K0HWb2Fr45dajH+r05l+ztOVoOUApKZV9rja9364BvQ4nOuQVATzMrgR9K4lT8RcxjZrbLOTc8FYWNEDq4V4gzPV56QZ7Fv/h/Ob6jhNDd9FjDwITKcKZzLpE7woUhB9jmnIvV021cQWcVo/Enmxx8EDLeObcs/zlzhQKRSvnmKmTBE4L+QP+gc5i2+DvHF+IvnEJ35MPrQ6yhZaLqQ9ARSkv8e5t70gog3J7Ux0TLvDcXvHE533HIU0EgdhG+2Wp+QWno7ny8IHmvg+cgUB6Av8hr5JxbHzH9JPwFX2F7Br+//xd/MVnQsE8zg3/bm1kxl0DHL2F64AP4DxLMvyd1qx8+II0azzbYhtcmuO7QPC3Y3cFWduT3NbObklhcaN6YTT2IPXxOsvZmf/ybc+7fhVCGRFUg9njAoTKG9rukzjd7uS+NDeYbDEw2s47OuWRu9IafL2L1PB0u/LeK1fqhSI+DMdaT7/r35TEqOEbfD9wfnK/a4G9K9AQamVl95zvCSrS+F/U2lAOIhoSRfcb8kAB3Bh9Hx7qocs7tcM7Nc879E/+kCuCsfVXGAoTu3raNM73dHi73Bfydw78G3aifjb+A/G+MvKEmW232cF2xhJrGxrtgmwNUNrOjklzuY/hOjobgmygfgu+lMKq7/Tg+JnhfyfxwGPucc26lc24UvpfLb4HmtnsYmk+Df0+JnM/MahC7WWk3/HG3MMaJzG/9Fiud3XW4fYx5SuOb127Gv9dVlEIXvfHqXEiovFH1Pei1+8hCKEs1fKcy02Nc7GWwuwljoXLOLcI3V6yBv0FQUMA4Bf+e1uH4GyRxmR9Oo0Tw/0z8Tb434zzJiWVP6laoOe+4GNOi6lsgv2NPaHlvxghIG+N/s0SFftfDIieYWRliN49N1pf4J2kt4hzj2sVIK4rjeSLyO2YtC27MQfLl26t9yTl3L775d2PgAzOrnOB6w8uayCs0+R0Ha+Gfkn4d0XS3KMTaj2B3XQmVM1XHqLXOuf85587Gv7ZUC//QILxssbahhaXvyVNvOUgpKJV9IriQH4M/2K7G3w0NTWtsZmVjzBZKy6+J3j7jnFuF74H2aDPLM2SDmXUl+fdJQ8v9FR+klMf3NlsKGOViD5kyFt+h03Vm1i7W8syskSU4plsgdDc6XrPAR4J/nzOzWO/ilQyGDQhP64V/4jsd38HS28FyTsI3QSpQ8O7Of/Hvpj1kES+0mlkpK+RxzczsUIsYPzKQwe6eo0NNkEfhmybeGlzIhJZRHB+Qxzq+9sBv73jvJSdjBj6YOcPMIuve9cR45w/fsVaozHUipj2Ib7b3ooseCiEpZnaVmTWLM60u/h1BiPGuaISX8YHLrWaWWz+DG1yPUDjnsF/x26R58HQ/tA7D9/pclE/qL8XXieyCnpwH71VfEZT1CTOL2aQyqL9T8J12gT8upZPcjZA9qVuhp1PtIspzLLtvRkYKNfGLdeyJt7yy+E5tEhZcyC8D2oXX++A3fhAonczy4qxjK75lSAXCzm/BeprhWwZEzjMHf2PiXIsxjmYw75HBu7qF6XYzqxm2jvBj1vNh+ZI93+z1vuScewjfgdLxwFSLMd5lHP/GHyvut9jjdoYvZ0Tw770WNg56cCNnGP4myf8luN69caKZXRaeYH6YldPwNwZDQ8Lsk2NUcE6NCnCD+hFqoh26Hnsd/3T6EjNrGjHLzfjAfqJzLvJ9UpG41HxXCp3t7hChGL553bH4Zrslgc+Ac8PeywO4ALjCfOcZi/BPao7ANxfZih/iJRk3mFm8d9Cm7kEHCuH+hr+IeDy4WPsMf/Dtge+ltuseLvcZ/PAqbcI+R3HObTWznvhxAKeY70xgHj5YOgx/x/QofPfxBY4DGixzg5nNBU4zs+fxvd064A3n3ELn3LtmdhdwL/CNmb2Jb0aUgX9SdQq+aWEXADM7Iij/r8D5YZ0U3YF/ynyt+fFLYz1RiXQ1vgOMG4DTzexdfFB4BHA6/in6zPizJ60W8ImZfYa/8/4z/uZIF/z2fST0XqxzbrmZ3YnvWXiBmYWP+VcGWEjYE5gggO6AbyWQ6BOruIL3ni/BdzAywcxew/92jfB3qSfht1H4PMvNv5v0WFiZfwnyN8c/7bljb8uGH+/v32b2Lf7C6vsg/Sj89snAb8tP48wfKu9SMxuEv8j/zPx7vRuC71Uef7yIFSAlLOjg6TngSvw2GY+/KD0dqIKvX633Zh35rHsxfvzdRPNPMbNs/PuaL5vZPfjOUkL1tBl+nMDf2b3/98QfU2OOkxlnPUnXLfxF/LXA02Z2Gj6orYNv+fEWu8fmDTcZuBF43sxex78jty5oyjoFvw9dEARQs/ABXw98gPlTot8nMBR4GphjZmPw55ZT8XXxC/xxZm/1x48ne3twcf8hPuDuhT9mx2r10xu/HUab2Q3477kZPyxYU3xHMU1J/t36/HyM35/Cj1nH499zfziUKdnzTWHtS865J8xsK/73mm5mfwluCuc3zxdmdi1+CKoFZjYOX08OwR/bNhKMgemcm25mj+DfS14U1O/N+ONWA/w+9Uj0WgrdO/jjZDd8HQyNU/oHcGnoRtU+PEaVwY89+zX+xtRq/E3yjvhWT6+7YFxe51yOmV2KH7d0RnBs/h4/jvBp+J7WryqEMsnBxO0HXQDr78D4I3r4lZ34O2mf4+++diNsfK+w+Vrge55diA84duAPaK8ADZNY/4oYZYj8GxiWvy/5DOFC2BAOEen18ANF/xaUdzb+ZJbv8hIo/9Jg/lkJ5K2CD4ZCQfw2fNfvbwCXkLdr+KihNmIsrz7wJv4p3i5iDAGCDyhfC36b7fgL3y/wd6hDw/uUxF/YOOCsGOupE2y3dYSN7VnAdz0EP27sF8F33Yq/i/xv8o51Fnd4CXZ3wR85RmDkkDDl8cH3dPxF4E58U9OZwXaNNXbp+fgmSlvwY4y+iG9ulae7fXxz9JjbpaDfiXyGtMBfsL4b/B45+Kf5zQtYXqcg32/B9vwaP2h82Rh592Sc0gb4jsvew/e8uC1Yz0p85zVnJPn9+wILIrZxDXwz018S+a3j/eZBWhq+B/Dvgrq9OlhHnVj1Kr/fI8468wwJk0D+qCFhIqZXwr9jNht/82c7fp/6EPh7aL/APyHNwV9M7skxKam6hb8gfQ9/XNyE7/ioXwH191Z8z9yhcTzD98cqwe/wSzB9Gf59tzKxfscEvk8//I2XrfgnsU/hA938hoRJuB4F6dXw57uf8cHFfPyN17jLw7dQuCuoz7+H1cGJ+EA/fDiRPRqiKZg3VJdrBds9NPzKKnwQlhlnvmTON4W2L+Ff+9iBvyFSO8Hv2Ar/hHdtMO+v+I6BzomR93z8PrMRf2xZiL8pF2s80Lj1LVb9ibHNw79zbl0IyjslKMPG4DdvHGM5hX6Miiw3/vz9d/w+vCbYfqH9+CbChgoLm6d5UA9+CerFd/hzc6yhc5I+R+vv4PqzoDKIiEghMrOZQAvnXOjdvlfxPWxWcrGbZksSgncBfwbmOef29Tt5fwpmdgb+KeWFzrmXUl0eSS0zG4UPxGq6Ap48StExP/Tde8DdzrkhBeUXOVjonVIRkSJmZun4JnITFZAmx8wqBe+QhqcZ/slNKQqn06gDVQ/80443U10QERGR/OidUhGRIuZ8JyjJ9BYqu/XGv6P3Pr4pcCb+3dxj8e+37cuhNP5UnHOXs3uIKRERkf2WglIREdmffYR/n7gzUJHd75jdCzyoJ88iIiJ/fnqnVERERERERFJG75SKiIiIiIhIyqSs+W6lSpVc7dq1U7V6ERERERERKULz5s37xTlXuaB8KQtKa9euzdy5c1O1ehERERERESlCZvZdIvnUfFdERERERERSJqGg1Mw6mdlCM1tsZv1jTK9qZpPN7EszW2pmVxZ+UUVERERERORAU2BQGgz6/hS+O/4TgGwzOyki2zXAXOdcA6AV8ICZlSrswoqIiIiIiMiBJZEnpc2BRc65751z24FXgDMj8qwCMs3MgEOAX4CthVpSEREREREROeAkEpTWAL4P+7wqSAv3LNAA+BE/yPn1zrldkQsys35mNtfM5v788897WGQRERERERE5UBRWR0d3AJ8DhwENgeFmlhWZyTn3jHOuiXOuSeXKBfYMLCIiIiIiIge4RILSVUDNsM81grRwbYD/Om8Z8C3+yamIiIiIiIhIXIkEpR8Dx5lZDTNLA3oB70TkWQ50ADCzKviAdEUhllNEREREREQOQCUKyuCc22JmVwGT8EHsKOfc3NCwL865p4DBwCgzWwwUB+52zq0pwnKLiIiIFKmtW7eybt06Nm7cyM6dO1NdHBGRlCpevDiZmZlUqFCB9PT0Ql22OecKdYGJatKkiZs7d25K1i0iIiKSn61bt7Jy5UrKly9PVlYWaWlp+EEGREQOPs45tm/fTk5ODuvXr6dWrVoJBaZmNs8516SgfIXV0ZGIiIjIAWPdunWUL1+eSpUqUbJkSQWkInJQMzNKlixJpUqVKF++POvWrSvU5SsoFREREYmwceNGsrKiBhIQETnoZWVlsXHjxkJdpoJSERERkQg7d+4kLS0t1cUQEdnvpKWlFfp79gpKRURERGJQk10RkWhFcWxUUCoiIiIiIiIpo6BUREREREREUkZBqYiIiIgUipEjR2JmjBw5MtVFSYiZ0a5du1QXQ+SgVyLVBRARERH5s7nj9S9SXYR83d/z+EJZzs6dOxkxYgSjRo3iiy++ICcnh9KlS1OzZk0aNWrE2WefTY8ePQplXX8GoXfpzIyvv/6aunXrxszXvn17pk6dCsDzzz9P3759o/Js2rSJZ599lvHjx7Nw4UJ+++03SpcuTf369TnttNO49NJLOeKII4rqq4jsVxSUioiIiEiUnTt30qVLFyZOnEjlypXp1q0b1atXZ/PmzSxatIjXX3+dFStW5AlKe/ToQYsWLahWrVoKS160SpQowY4dO/i///s/7rvvvqjpX3/9NVOnTs3NF8ucOXPIzs7mhx9+oEaNGpxxxhkcdthhbN68mQULFjB06FCGDh3KnDlzOOmkk4r6K4mknIJSAfK/41tYd1tFRETkz2P06NFMnDiRZs2a8f7775OZmZln+ubNm/noo4/ypJUtW5ayZcvuy2Luc1WqVKFatWo8//zzDB48mBIl8l5OP/fccwB07dqVsWPHRs2/ZMkSTj/9dH7//XceeOABbr755qhlrFzPelFqAAAgAElEQVS5kttuu42cnJyi+yIi+xG9UyoiIiIiUWbNmgVA3759owJSgNKlS9O+ffs8afm9Uzpp0iRatWpFmTJlqFChAt27d2fhwoX07dsXM2PFihW5eVesWIGZ0bdvX1asWEHv3r2pVKkSGRkZNGnShDfffDNq+Rs2bGDIkCGccsopVKxYkRIlSlC5cmXOOussZs+evXcbI8Lll1/OmjVrosqxfft2Ro4cScuWLWnQoEHMea+99lpycnK4/fbbuf3226MCUoBatWoxZswYTj755EItt8j+SkGpiIiIiETJyMgAfHPUvTVmzBg6d+7M/PnzOeecc7jiiitYv349rVu3Zvny5XHn++6772jWrBmrV6/m8ssv58ILL2TJkiV069aNDz74IE/exYsXc99991GqVCkuuugi+vfvzxlnnMH06dNp27YtEydO3OvvEdKnTx/KlCmT+1Q0ZPz48axdu5bLL7885nzffvst77//PhkZGdx2220Fric9Pb1Qyiuyv1PzXRERERGJcs455/Doo4/y6KOP8vPPP9OjRw8aN27M4YcfntRyNm7cyFVXXUVGRgazZ8/mxBNPzJ125513xnwvM2Tq1Kk8/PDD3HTTTblpF1xwAW3btmXo0KF5ntQ2aNCANWvWkJWVlWcZa9asoWnTptx444106tQpqbLHk5mZSe/evRk5ciSrVq2iRo0aADz77LNkZWVx7rnnxvxeM2fOBKBx48aUK1euUMoiciDQk1IRERERiXLyySfzn//8hypVqjBq1CjOPvtsateuTcWKFenRowcTJkxIaDnjxo3jt99+45JLLskTkAIMGDCAihUrxp23Xr16eQJSgDZt2lCvXj0+/vjjPOlZWVlRASlA1apV6dWrF0uWLGHlypUJlTkRl19+eW7vxOCf6r733nucf/75lC5dOuY8q1evBsgNYkXEU1AqIiIiIjH17t2blStXMmnSJO6++266dOlC8eLFeeONNzjrrLO46KKLcM7lu4z58+cDPpiMVLJkSZo3bx533iZNmsRMr1atGuvXr49K//DDDzn33HOpWbMm6enpmBlmxsMPPwzADz/8kG9Zk9G8eXOOP/54RowYwa5du3juuefYtWtX3Ka7IhKfmu+KiIiISFxpaWl07NiRjh07ArBr1y7GjRvHxRdfzIsvvkiPHj3o3r173Pk3bNgAELe5avny5ePOG++dymLFirFr1648aWPHjiU7O5uMjAxOO+006tatS5kyZShWrBhTp05l2rRpbN26Nd/vmqzLL7+c6667jnfeeYfnn3+exo0b06hRo7j5Q0PlFGZwLHIgUFAqIiIiIgkrVqwYPXr0YNGiRdx9991MmTIl36A01KT2t99+izk9Xnqy7r77bkqVKsUXX3xBnTp18ky76aabmDZtWqGsJ9wFF1zA7bffzpVXXskPP/zAPffck2/+1q1bAzB37lw2bNhwwA+fI5IoNd8VERERkaSFgs2Cmu+GnhzOmDEjatq2bduYM2dOoZRn6dKlnHDCCVEBKRDVU29hKVeuHNnZ2axatYoyZcrQp0+ffPPXqVOHU089lS1btjB06NACl1/YT3ZF9lcKSkVEREQkyujRo3nvvfeimskC/PLLLzz99NMAtG3bNt/ldOvWjbJlyzJixAg+++yzPNMGDRrEr7/+WijlrVq1Kl9++SVr167Nkz506FAWLFhQKOuIZciQIYwdO5ZJkybFHM810rBhw8jKyuL+++/n4YcfZseOHVF5Vq5cSa9evQp9fFWR/ZWa74qIiIhIlI8++ojHHnuMqlWr0rp1a+rUqUNaWhrffvstb7/9Nhs2bKBbt25kZ2fnu5ysrCyeeOIJLrjgAlq2bMm5555LtWrVmDVrFgsWLKB169bMnDmTYsX27lnJ9ddfzy233EKjRo3Izs6mVKlSzJgxg/nz59O5c2feeeedvVp+PLVq1aJWrVoJ5z/mmGOYNGkS2dnZ3HLLLTz22GN06NCBww47jE2bNvHZZ5/x4YcfYmb079+/SMossr9RUCoiIiIiUW666SZq1qzJ1KlT+eSTTxg/fjzOOSpWrEjLli0577zzOO+88zCzApd1/vnnU6FCBe69915eeeUV0tPTadu2LTNnzmTw4MEAMYdzScbNN99Meno6w4cP58knnyQrK4s2bdowc+ZMxo8fX2RB6Z5o0aIFS5Ys4dlnn2X8+PG89dZbrF+/ntKlS1OvXj1uvvlm+vXrF7MpssiByAp6D6CoNGnSxM2dOzcl65Zod7z+Rdxp9/c8fh+WREREJPUWL17MMccck+piHPCcc9SrV4/NmzfnjuEpIvu/RI+RZjbPORd7bKcweqdURERERIrUhg0bYnba8+ijj/LNN9/Qo0ePFJRKRPYXar4rIiIiIkVq9uzZ/PWvf+W0007jiCOOYOvWrXz44YfMmTOHmjVrMnDgwFQXUURSSEGpiIiIiBSpo446inbt2jFz5kz+97//YWbUqFGD6667jr///e8ceuihqS6iiKSQgtIDlN4RFRERkf1FnTp1eO2111JdDBHZT+mdUhEREREREUkZBaUiIiIiIiKSMgpKRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIiIiIimjoFRERERERERSRuOUStI0BqqIiIiIiBQWPSkVERERERGRlNGT0j8JPZ0UERGR/Unt2rUBWLFiRUrL8WfSt29fXnjhBb799tvc7SeyL02dOpX27dszYMAABg4cmOri5FJQKiIiIpKsuc+nugT5a3JxqkuQMDPjlFNOYerUqakuykGhdu3afPfdd7mfixUrRpkyZahevToNGzakS5cuZGdnk56ensJSysFGQamIiIiIyEHm+uuvp1y5cuzatYucnBy++uorJkyYwJgxY7jzzjsZM2YMLVq0SHUx5SChoFRERERE5CBzww03RDUh3rBhA3fffTePP/44nTp1Ys6cORx99NGpKaAcVNTRkYiIiIjE5Jxj+PDhHHvssWRkZFC9enWuueYaNmzYEDP/hg0bGDJkCKeccgoVK1akRIkSVK5cmbPOOovZs2fnyTty5EjMDIBp06ZhZrl/4e+6PfPMM3Tt2pUaNWqQlpZGVlYWrVq1YtSoUUl9l4EDB2JmMZsJr1ixAjOjb9++edL79u2LmbFixQqefvppjj/+eDIyMqhSpQr9+vWLux3ef/992rRpQ5kyZahQoQLdu3dnyZIl+Zbvo48+Ijs7m6pVq1KyZElq1qzJFVdcwY8//hiVt127dpgZ27ZtY/DgwRx11FGkp6dHlT9ZZcuWZdiwYVx44YVs2LCB/v3755m+Zs0arrrqKg4//HBKlixJRkYG9erVo3fv3ixfvjyhddSuXZvatWuzYcMGbrjhBmrWrEnJkiVp0KABr7zyCgBbt27lnnvuoXbt2qSlpVG3bl2GDx8etaxt27bx8MMP07FjR6pUqUJaWhoVKlTg1FNP5Z133om5/nnz5tG9e3cOPfRQSpQoQWZmJieeeCJXX30127dvz82Xk5PD7bffzpFHHkl6ejrp6ekcfvjhdO/enblz5yb0XUO/09atW7nrrruoU6cO6enp1K1bl0GDBrFt27aY8y1ZsoS+ffvmbpsqVapw3nnn8dVXX0Xl/eqrr7jhhhto1KgRmZmZlCxZksMPP5x+/fqxatWqhMoJsGXLFrKzszEz/va3v7Fr166E5y0MelIqIiIiIjHdcMMNDBs2jGrVqtGvXz/S0tIYN24cH330Edu2baNkyZJ58i9evJj77ruPtm3bctFFF1G6dGm+//57xo0bxzvvvMOECRPo1KkTAA0bNmTAgAEMGjSIww8/PE9A1a5du9z/33jjjZxwwgmcddZZVKxYkfXr1/P2229zwQUX8NVXX3HvvfcW+Xa47bbbmDJlCj179qRr165MmTKFZ599lmXLljFlypQ8eV977TV69epFyZIl6dWrF9WqVWPmzJmcfPLJnHDCCTGXP2LECPr160dmZibdu3fnsMMO45tvvmHkyJFMmDCBOXPmUKtWraj5zj77bObPn0/37t3Jysri0EMPLZTve8899/Diiy/y5ptvkpOTQ1ZWFps3b6Z169Z88803dOrUiT59+lCsWDG+/fZbPvjgAxYvXkzdunUTWv62bds49dRT+eOPP+jduzdbtmzh5Zdfpk+fPpQpU4Ynn3ySRYsW0a1bN0qUKMErr7zCtddeS+nSpbnkkktyl7Nu3TruuOMOWrVqRa9evShbtiw//fQTEyZM4IwzzuDZZ5/lsssuy83/+eef07p1a4oVK0aPHj2oXbs2W7ZsYfHixbz44os8+OCDpKWl4Zyjc+fOzJo1izZt2tCjRw/S0tJYtWoV06ZNY86cOTRp0iTh7XnuuefyySefkJ2dnbsPDRw4kLlz5zJ+/PjcmzMAEydOpGfPngB069aNI444gtWrV/Pf//6Xt956iw8++ICTTjopN//YsWP5z3/+Q7t27ejYsSPFixdn0aJFjBgxggkTJjB37lyqV6+eb/nWr1/PWWedxYcffsj9998fdTNiX1BQKiIiIiJRZs2axbBhw6hfvz6zZ8+mQoUKAPzjH//gtNNOY/Xq1Rx++OF55mnQoAFr1qwhKysrT/qaNWto2rQpN954Y56gtGHDhgwaNIjatWvH7Ql0yZIl1KxZM0/a9u3b6datGw888ABXXnllgRfde2v+/PksWrSIKlWqALBr1y5OP/103n//fT7++GOaNWsGwO+//84VV1xBWloaM2fOpHHjxrnLuOWWW3j44Yejlr106VKuvPJKjjnmGCZPnpwnsJw1axbt27fn+uuvZ+zYsVHzrl69msWLF5OZmVmo37du3brUqFGDVatWMW/ePNq3b8/kyZNZvnw5/fv35/7778+Tf+fOnWzevDnh5a9evZpWrVoxZswYihcvDsCFF15Is2bN6NOnDyeeeCJffvklpUuXBvzNkfr16/PQQw/lCUrLly/PqlWrooLxjRs3csopp3Dbbbdx/vnnU6pUKQBeeOEFtmzZwsSJEzn99NPzzJOTk5O7voULFzJr1ix69+7N6NGj8+RzzpGTk5PwdwX/Gy9atIjy5csDu/ehN998k1GjRnHBBRcAPjjs06cP5cuXZ+rUqRx55JG5y+jfvz8tWrTgsssu49NPP81Nv+iii7jlllsoUSJvWDd9+nTat2/PkCFDePLJJ+OW7bvvvqNz584sW7aMl156ifPPPz+p71ZY1HxXRERERKI8/7zvYXjQoEG5ASlARkZGzOAKICsrKyogBahatSq9evViyZIlrFy5MqlyRAakAGlpaVx99dXs2LGDyZMnJ7W8PTFgwIDcgBR8j7WhJ7sff/xxbvq4ceNYt24dffv2zROQAgwZMiQ3KAn35JNPsn37dh599NGo4Kply5b06NGDCRMmsHHjxqh5//GPfxR6QBoSCvR//vlnwDepBfI81QspXrx40uX417/+lRuQAjRt2pT69evz+++/889//jM3QARfB9q2bcvixYvzbIf09PSYT4czMzO55JJLWL9+PZ988kluen7fISsri2LFihWYz8woW7ZsUt/13nvvzfPbh+9DI0aMyE1/8cUX+e233xg8eHCegBSgfv369OvXj/nz5/Pll1/mplerVi0qIAVo27YtjRo1YtKkSXHLtWDBAk4++WR++OEH3nnnnZQFpKAnpSIiIiISQ+hpzCmnnBI1rWnTppQpUybmfB9++CGPPfYYs2fPZu3atVHvzf3www8xm6LGs3LlSv75z38yefJkVq5cyR9//BG1vKLWtGnTqLRq1aoB/ulWSH7bLCMjgxYtWkS96xh61/b9999nxowZUfP9+OOP7Ny5k6VLl0YFukXZO65zDoAdO3YA0KFDBw499FAeeOABPvvsMzp37szJJ59Mw4YN8wSXiahSpQo1atSImb506dKYTWNDNwV+++23PAHwokWLGDp0KNOnT2f16tVs2bIlz3zh9aNXr148+eST9OzZk+zsbDp06EDLli2jmh03bNiQY445htGjR/PDDz/QtWtXWrZsSZMmTaKarCciv31o/vz5uWmhujB37ly+//77qHlCwejixYtp0KAB4H+nl19+mZEjR/LZZ5+xfv16du7cmTtPvPLOnDmTRx55hMzMTKZPn86JJ56Y9PcqTAkFpWbWCXgIKA684Jx7IGL6rUAotC4BHANUds6tK8SyioiIiMg+EurEJ/wpaYiZUa5cuaj0sWPHkp2dTUZGBqeddhp169alTJkyFCtWjKlTpzJt2rTcp1CJ+Oabb2jWrBnr16+nTZs2dOzYkbJly1K8eHFWrFjBCy+8kNTy9lSsMTtDT9XCA4D8tlm89F9//RWABx54IGpauN9//z0qLdkndskIdbAUCgbLly/P7NmzGThwIG+++SZvv/02AJUqVeLqq6/mrrvuIi0tLaFlZ2RkxEwPbdNEt/ecOXP4y1/+wo4dO+jQoQNnnXVW7hPPBQsWMG7cuDz1o02bNkyePJn777+fMWPG8MILLwBw1FFHMWDAAPr06QNAiRIlmDp1KoMHD+a1115j+vTpgH8Ce9FFF3Hfffcl9WQ4v30ovCOrUF146qmn8l1eeF246aabePTRR6lWrRqnn3461atXz22uPHLkyDxj0oabP38+GzdupGXLlvtFD8sFBqVmlg48BbQB1gCzzexd51xuY2bn3FBgaJC/K3CjAlIRERGRP69QwLNu3brcp4Ihzjl+++03KlWqlCf97rvvplSpUnzxxRfUqVMnz7SbbrqJadOmJVWGRx55hF9//ZVXX32Vc845J8+08ePH5wYViQgFNaEngOEin67tqfBtFkus9NA8GzZsiNn0ORWWLVvGqlWrKFasGA0bNsxNP+KII3jxxRdxzvHll18yZcoUnnjiCQYPHsymTZt46KGH9mk5hwwZwpYtW5gzZ07ue70hw4YNY9y4cVHztGvXjnbt2rF161bmzZvHxIkTefzxxznvvPPIzMykS5cuABx66KEMHz6c4cOHs2zZMqZNm8bTTz/N8OHDWb16Na+99lrC5Vy3bh2VK1fOkxbah8J/81Bd+Oyzz+J2ihVu7dq1DBs2jMaNGzNjxozcYDRk/PjxcYPSa665hrVr1/LUU09x1lln8cYbb0TNvy8l8k5pc2CRc+5759x24BXgzHzy9wFG5zNdRERERPZzoR4+YwWSn3zyCZs2bYpKX7p0KSeccEJUQArwwQcfxFxPsWLFYgaKoeWB74U00eXFE3qnL9YQK+HvHe6N/LZZKHiKFGqCG6vpbqoMHjwYgM6dO1OxYsWo6WbGsccey7XXXst7770H+ABoX1u6dClVq1aNCkih4PqRnp5Oy5YtGTx4MMOGDQPif4d69epx6aWXMm3aNA455BAmTJiQVDnz24caNWqUm5ZsXVi2bBm7du2iY8eOUQHlzz//zMKFC+POa2Y8+eST3HDDDbz77ruceeaZMffpfSWRoLQGEN6oeVWQFsXMSgOdgP/tfdFEREREJFVCHfkMGDAgzxO+LVu2cPPNN8ecp2rVqnz55ZesXbs2T/rQoUNZsGBBzHkqVqwY973QqlWrAkSNLTpjxox8exSNJRS4vPDCC3nGYFy7di2DBg1KalnxdOvWjfLlyzNy5EjmzZuXZ9pdd92V5/3TkGuuuYa0tDRuvPHGmJ1A7dq1i48++qhQyleQnJwcrrvuOl566SUOOeQQhg4dmjtt0aJF/PTTT1HzhJosx+rEqahVrVqVn376icWLF+dJf/XVV2M+JZ01a1bUO8kQ/R2+/fZbvvnmm6h8GzduZOfOnTGbrufn7rvvzvPbh+9DF198cW76xRdfTLly5Rg0aBCff/55zGWFj/cb2j9mzJiRp1nztm3b6NevX55xV+P517/+xR133MEHH3zA6aefnnTPwoWlsDs66gp8GK/prpn1A/oBSb3gLiIiIiL7VqtWrbj22mt5/PHHOe644/KMsVi+fPmoJr0A119/PbfccguNGjUiOzubUqVKMWPGDObPn0/nzp2jOvkB34HOmDFj6NmzJw0bNqRYsWK0bduWtm3bcvXVVzN69Gi6d+9Or169qF69Ol9++SXjx4+nW7duvP766wl/n+bNm9O2bVvee+89WrVqRfv27Vm3bh2vvfYaHTp0YPny5Xu1vQAOOeQQnnnmGXr16kXr1q3zjFO6cOFC2rZtm/t+YsjRRx/NiBEjuOSSSzj66KM588wzOfLII9m5cyfffvst06dPp1y5cixZsmSvyxfu0UcfpVy5crlDnHz11VdMnz6dTZs2Ubt2bUaPHs0xxxyTm/+9997j1ltvpVWrVpx44olkZWXx448/8vrrr1OsWDFuvfXWQi1fIq677jpmzJiRO05p+fLlmTdvHpMnT6Zbt2688cYbefI/+OCDTJkyhfbt23PUUUdRsmTJ3PpUvnx5+vXrB/jmsz179qRZs2Y0btyYChUq8Msvv/DGG2/wxx9/MGTIkKTKWb9+fY499tg8+9Dy5cs588wzc4eDAX+D5rXXXqNHjx40btyY008/neOOOw4z4/vvv2fmzJmsWbMmt7n5EUccQZcuXXjzzTdp2rQpHTt2ZMuWLUyYMAEz44QTTogb3Ia77777yMjIYMCAAZx22mlMnDhxn99kSCQoXQWE98VdI0iLpTf5NN11zj0DPAPQpEmT2O00RERERGS/8Nhjj1G/fn2eeOIJnn76aSpWrEiPHj247777YvbWefPNN5Oens7w4cN58sknycrKok2bNsycOZPx48fHDEofe+wxzIzJkyczbtw4du3axYABA2jbtm1ub7UDBgxgzJgxlChRghNPPJHRo0dTuXLlpIJS8EO23HrrrYwbN45PP/2UI488kvvuu4+OHTvy6quv7vF2Cpednc3EiRMZNGgQr776Kunp6bRt25bZs2fzwAMPRAWlAH/961858cQTefjhh/nggw8YN24cxYsXp1atWnTq1InzzjuvUMoW7rHHHgN8M84yZcpQo0YNunbtSpcuXcjOzo7qbKhjx44sX76cDz/8kOeff57NmzdTvnx5WrVqxc0330z79u0LvYwFyc7OZsyYMTzwwAOMGDGCUqVK0axZMyZNmsT3338fFZReeeWVZGZm8vHHH/Puu++yY8cODjvsMC666CLuvPNOjjjiCACaNGnCLbfcwvTp0/nPf/5DTk4OWVlZnHTSSTzxxBP07NkzqXK++uqr3Hvvvbz88sv8+OOPVK9enYEDB9K/f/+oYWc6dOjA559/zkMPPcSkSZN4//33cc5RvXp1mjdvztlnn50n/5gxY7jzzjt59dVXeeSRR6hSpQpdunRh0KBBnHvuuQmX8Z577qFUqVLcdtttdOjQgXfffTfqnfGiZPHa8OdmMMsAvgJaAT8Bs4ErnXNzI/KVBb4FajrnCmyQ3KRJEzd37tyCskngjte/iDvt/p7H79P8yS5bRETkz2bx4sV5nhKJiCSrXbt2TJs2Le47039miR4jzWyecy56jJ8IBT4pdc5tMbOrgEn4d1BHOefmmtmVwfRQn8U9gHcTCUhFREREREREIMF3Sp1zbwNvR6Q9FfF5JDCysAomIiIiIiIiB75Eet8VERERERERKRKF3fuuiIiIiIjIQS9yKCOJT09KRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIhLDgTi2oIjI3iqKY6OCUhEREZEIxYsXZ/v27akuhojIfmf79u0UL168UJepoFREREQkQmZmJjk5OakuhojIficnJ4fMzMxCXaaCUhEREZEIFSpUYP369fzyyy9s27ZNTXlF5KDmnGPbtm388ssvrF+/ngoVKhTq8jVOqYiIiEiE9PR0atWqxbp161ixYgU7d+5MdZFERFKqePHiZGZmUqtWLdLT0wt12QpKpcjd8foXcafd3/P4fVgSERGRxKWnp1OtWjWqVauW6qKIiBzQ1HxXREREREREUkZBqYiIiIiIiKSMglIRERERERFJGQWlIiIiIiIikjIKSkVERERERCRlFJSKiIiIiIhIyigoFRERERERkZRRUCoiIiIiIiIpo6BUREREREREUkZBqYiIiIiIiKSMglIRERERERFJGQWlIiIiIiIikjIKSkVERERERCRlFJSKiIiIiIhIyigoFRERERERkZRRUCoiIiIiIiIpUyLVBTiY3fH6F3Gn3d/z+H1YEhERERERkdTQk1IRERERERFJGQWlIiIiIiIikjIKSkVERERERCRlFJSKiIiIiIhIyigoFRERERERkZRRUCoiIiIiIiIpo6BUREREREREUkZBqYiIiIiIiKSMglIRERERERFJGQWlIiIiIiIikjIlUl0AkUh3vP5FzPT7ex6/j0siIiIiIiJFTU9KRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIiIiIimjoFRERERERERSRkGpiIiIiIiIpExCQamZdTKzhWa22Mz6x8nTzsw+MbPPzGx64RZTREREREREDkQFjlNqZunAU0AbYA0w28zedc59GpanKvAE0ME5t8bMKhVVgUVEREREROTAkciT0ubAIufc98657cArwJkReXoDrzrn1gA4534p3GKKiIiIiIjIgSiRoLQG8H3Y51VBWrijgWpmNsfMvjCzy2MtyMz6mdlcM5v7888/71mJRURERERE5IBRWB0dFQMaAh2A9sDtZnZcZCbn3DPOuSbOuSaVK1cupFWLiIiIiIjIn1WB75Tin4zWDPtcI0gL9z2w2jm3CdhkZtOAE4CFhVJKEREREREROSAlEpR+DBxnZjWAn4BewJURed4ChppZCaAkcDK+4yORInXH61/EnXZ/z+P3YUlERERERGRPFBiUOue2mNlVwCR8M91Rzrm5ZnZlMP0p59ynZjYR+BxIA/4vvHdeERERERERkVgSeVKKc+5t4O2ItKciPg8FhhZe0UREREkqcKcAABYgSURBVERERORAV1gdHYmIiIiIiIgkTUGpiIiIiIiIpIyCUhEREREREUkZBaUiIiIiIiKSMgpKRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIiIiIimjoFRERERERERSRkGpiIiIiIiIpIyCUhEREREREUkZBaUiIiIiIiKSMgpKRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIiIiIimjoFRERERERERSRkGpiIiIiIiIpIyCUhEREREREUkZBaUiIiIiIiKSMgpKRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIiIiIimjoFRERERERERSRkGpiIiIiIiIpIyCUhEREREREUkZBaUiIiIiIiKSMgpKRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIiIiIimjoFRERERERERSRkGpiIiIiIiIpIyCUhEREREREUkZBaUiIiIiIiKSMgpKRUREREREJGVKpLoAIvvSHa9/EXfa/T2PTzh/rLwiIiIiIpI8PSkVERERERGRlFFQKiIiIiIiIimjoFRERERERERSRkGpiIiIiIiIpIyCUhEREREREUkZBaUiIiIiIiKSMgkFpWbWycwWmtliM+sfY3o7M9tgZguCv3sKv6giIiIiIiJyoClwnFIzSweeAtoAa4DZZvauc+7TiKwznHNdiqCMIiIiIiIicoBK5Elpc2CRc+5759x24BXgzKItloiIiIiIiBwMEglKawDfh31eFaRFOjlo4jvFzBoWSulERERERETkgFZg890EzQNqOuc2m9npwBtmdoRzbld4JjPrB/QDqFWrViGtWkRERERERP6sEnlSugqoGfa5RpCWyzm30Tm3Ofj/JGAbUDVyQc65Z5xzTZxzTSpXrrznpRYREREREZEDQiJB6cfAcWZWw8zSgF7AO+EZzKxy2P8bA4cAawuzoCIiIiIiInLgKbD5rnNui5ldBUzCB7GjnHNzzezKYPpTQJ+gaS74p6TnOed2FFWhRURERERE5MCQ0Dulzrm3gbcj0p4K+/8wYFjhFk1EREREREQOdIk03xUREREREREpEgpKRUREREREJGUUlIqIiIiIiEjKKCgVERERERGRlFFQKiIiIiIiIimjoFRERERERERSRkGpiIiIiIiIpIyCUhEREREREUkZBaUiIiIiIiKSMgpKRUT+v727C7X0OusA/n9MSmqrItiomJOoF6JoWjvlDPErkvoBqfFzUFKtBYeWOEEq4oU2ih8XQipEqDcyROvYmqLBdmy0Tk3EIkWIhm1Skqat9aY4M5BmHPETotY+XpzdsD2dc84+M/vstc8+v99N9vuuNfs8IS9h/udZa70AAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMNePLgDWxX1nn9lx7P4Tr1xiJQAAcHjolAIAADCMUAoAAMAwQikAAADD2FPKvh2//MjOg5NJsnly5vpMjl++uMu32WsJAABHmU4pAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMM4fRcn5AIAAMPolAIAADCMUAoAAMAwlu+uo72W404myebJ5dUDAACwA51SAAAAhhFKAQAAGEYoBQAAYJi59pRW1Z1JHkhyXZJ3dvfbdph3PMnjSV7f3e9ZWJUcHbvth7UXFgAA1s6endKquiHJ6SSvS/KqJD9cVa+5wrzrkvx6kscWXSQAAADraZ5O6W1Jnu3u80lSVQ8nuSvJk9vmvSXJe5McX2iFh8h9Z5/Zcez+E69cYiUAAACHwzyhdCPJ+ZnrC0numJ1QVTcl+aEkr80RDqUs3/HLj+w8aLkvAACsvEUddPT2JD/f3Z/ZbVJV3VNVk6qaXLp0aUE/GgAAgMNqnk7phSQ3z1xvTO/N2kzyh1WVJK9I8j1V9enuft/spO5+MMmDSbK5udlXWzQAAADrYZ5Q+kSSW6tqI8mnktyd5NTshO7+6s9+rqrfS/L+7YGUa2OZKgAAsI72DKXd/UJV3Zvk0Wwt932ouydVdWo6fvqAawQAAGBNzfWe0u4+l+TctntXDKPd/RPXXhYAAABHwaIOOgIAAIB9m6tTCiye99oCAIBOKQAAAAMJpQAAAAxj+S7sZHImxy9f3GHMa3gAAGARhFKOjt1CZpJkdfdx2n8KAMC6snwXAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgmOtHFwDr4vjlR3YenEySzZPLKwYAAA4JnVIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBjvKR1lcibHL1/cZcIrl1YKAxzwf//7zj6z49j9JzxbAACsDp1SAAAAhhFKAQAAGEYoBQAAYBihFAAAgGEcdAQ4GAkAgGF0SgEAABhGKAUAAGAYoRQAAIBh7CmFQ+D45Ud2HpxMks2TyysGAAAWSKcUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGCYuUJpVd1ZVR+pqo9V1VuvMP4DVfVMVT09nfe6xZcKAADAurl+rwlVdUOS00luT/Jckser6rHufnJm2l8m+ZPu7qp6VZL3J7nlIAoGAABgfewZSpPcluTZ7j6fJFX1cJK7krwYSrv7P2bmvzxb4RUYYXImxy9f3GV8kmyenH9+Xrmw0gAAYLt5lu9uJDk/c31heu//qaofqqqPJ/nzJD+9mPIAAABYZws76Ki7/7i7vy7J9yV5V1V9zndX1T1VNamqyaVLlxb1owEAADik5gmlF5LcPHO9Mb13Rd39oWwtC/6yK4w92N2b3b1544037rdWAAAA1sw8ofSJJLdW1UZVvSTJ3Uk+MDuhqr565vNrktyQ5PlFFgoAAMD62fOgo+5+oaruTfJotkLsQ909qapT0/HTSV5fVW+Y/pEXkry+u//3oIoGAABgPcxz+m66+1ySc9vunZ75fH+S+xdbGgAAAOtuYQcdAQAAwH4JpQAAAAwjlAIAADDMXHtKAV40ObP7+ObJ5dQBAMBa0CkFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGG8EgY4OHu9PibxChkAgCNOpxQAAIBhhFIAAACGEUoBAAAYxp5SYF/OPnVxx7ETx25aYiUAAKwDnVIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhnH6LnCg9nVa7+TM7l+2eXIBFQEAsEp0SgEAABhGKAUAAGAYoRQAAIBhhFIAAACGcdDRokzO5PjlnQ90yWTikBYAAIBtdEoBAAAYRigFAABgGKEUAACAYYRSAAAAhnHQEXB4Tc7sPu5wMQCAlSeUAivl7FM7n2J9YvMavliABQBYSZbvAgAAMIxQCgAAwDCW7wJcieW+AABLoVMKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADDM9aMLAFgLkzO7j2+eXM3vBgAYTKcUAACAYeYKpVV1Z1V9pKo+VlVvvcL4G6vqmemcv6uqzcWXCgAAwLrZc/luVd2Q5HSS25M8l+Txqnqsu5+cmfaJJN/W3f9aVa9L8jtJXn0QBQMAALA+5tlTeluSZ7v7fJJU1cNJ7kryYijt7r+dmf/XSW5aZJEAa8UeUQCAF82zfHcjyfmZ6wvTezv5ySR/ci1FAQAAcDQs9PTdqrojyZuSfNsO4/ckuSdJbrnllkX+aAAAAA6heTqlF5LcPHO9Mb33/1TVq5K8I8kPdPflK31Rdz/Y3ZvdvXnjjTdeTb0AAACskXk6pU8kubWqNpJ8KsndSU7NTqiqW5KcTfLG7v7EwqsEuIKzT13ccezEsSO8td2eVQDgENkzlHb3C1V1b5JHs9VZfai7J1V1ajp+OskvJ/mSJL9VVUny6e72WhgAAAB2Ndee0u4+l+TctnunZz6/OcmbF1saAAAA626ePaUAAABwIIRSAAAAhhFKAQAAGEYoBQAAYJi5DjoCYE15fQwAMJhOKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDOH0XgPk5rRcAWDChFDgyzj51ccexE5tLLOSo2CvAJkIsAGD5LgAAAOPolALsYKfO6oljNy25EgCA9aVTCgAAwDA6pQCsBocoAcCRpFMKAADAMDqlAAuw68m+9qACAOxIpxQAAIBhhFIAAACGEUoBAAAYRigFAABgGAcdAXA4eYUMAKwFoRSA9bdXgE2EWAAYRCgFGGDXV8hsLrEQAIDB7CkFAABgGJ1SALhW9rcCwFUTSgFgOyETAJbG8l0AAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGMYrYQBgmfZ63UzilTMAHClCKcAhcPapi1e8f+LYTUuuhKXzzlQA1pxQCgDrRIgF4JCxpxQAAIBhhFIAAACGEUoBAAAYxp5SADiq9rv/1H5VAA6ATikAAADD6JQCAAdDZxWAOeiUAgAAMIxQCgAAwDBzLd+tqjuTPJDkuiTv7O63bRv/uiRnkrwmyS929wOLLhQAWGOW+gIcWXuG0qq6IcnpJLcneS7J41X1WHc/OTPtn5P8dJIfPJAqAQAAWEvzdEpvS/Jsd59Pkqp6OMldSV4Mpd39fJLnq+quA6kSgLmdferijmMnjt20xEoAAPY2z57SjSTnZ64vTO/tW1XdU1WTqppcunTpar4CAACANbLUV8J094NJHkySzc3NXubPBgDWiD2oAGtjnlB6IcnNM9cb03sAHEE7LQ+2NJi1IfACLNU8ofSJJLdW1UaSTyW5O8mpA60KAGBR9gqZyfKC5irVArAi9gyl3f1CVd2b5NFs7UF9qLsnVXVqOn66qr48ySTJFyX5TFX9TJKv7+5/O8DaAViAXQ9G2lxiIXBY6awCXJO59pR297kk57bdOz3z+blc5eFHAAAMoGsLrIh5Tt8FAACAAyGUAgAAMMxSXwkDAMA+2K8KHAFCKQAHZtdDlLxCBtabQA3MSSgFAFgXgiBwCNlTCgAAwDA6pQAA7E0XFjggQikAAGMJvHCkWb4LAADAMEIpAAAAw1i+CwDA4bLf5b6WB8NK0ykFAABgGJ1SAA6ls09d3HHsxLGbllgJsFZ0VWHphFIAAFgWoRc+h1AKwMrYtfu5ucRCAOYlZMI1E0oBAGAVCbwcEUIpAEeCPagAsJqcvgsAAMAwOqUAcAX2twLAcuiUAgAAMIxQCgAAwDCW7wLANXKIEgBcPZ1SAAAAhhFKAQAAGMbyXQBYsoNc7mspMQCHjVAKACtup6ApZAKwDoRSAABYB5Mzu49vnlxOHbBP9pQCAAAwjFAKAADAMJbvAsARtuvBSJvzz7e/FYCrpVMKAADAMDqlAMBK2G/XFoD1oFMKAADAMEIpAAAAw1i+CwCsvV2XBjukCWAooRQAOBAHHQSdBAywHizfBQAAYBihFAAAgGEs3wUAuAb7Xaa80PnbXpVj7yxwGAmlAADbeGcqwPIIpQAAR9Siura6sMC1EEoBADh0BGRYH0IpAAALd5B7Zw/afmsRkOHaCKUAALAkDqOCzzVXKK2qO5M8kOS6JO/s7rdtG68kv5nku5L8V5I3dfeTC64VAACOlFXqIMNB2TOUVtUNSU4nuT3Jc0ker6rHtoXOE0m+Msk3JDmW5EySb1x8uQAAsD+6k1cwObP3nM2TB18HZL5O6W1Jnu3u80lSVQ8nuSvJbCi9K8lD3d1Jnqyq66vq5s/+GQAA4GAdaPjeK8QKsFyDeULpRpLZcHkhyR1zzNl+DwAAWBEHeRjV2d/+td2/ezbEHuau7X7DunB/RbXV3NxlQtWPJfn27j41vf7RJHd090/OzHksyS93999Mrx9N8qvd/fi277onyT3Ty69N8veL+hcZ7BVJ/ml0Eawszwe78XywF88Iu/F8sBfPCLs56OfjK7v7xr0mzdMpvZDk5pnrjem9K835m13mpLsfTPLgHD/zUKmqSXfbas4VeT7YjeeDvXhG2I3ng714RtjNqjwfnzfHnCeS3FpVG1X1kiR3J/nAtjnnkrwhSarqNUk+Yz8pAAAAe9mzU9rdL1TVvUkezVaIfai7J1V1ajp+Osl7k7y2qj6a5L+THM3F0AAAAOzLXO8p7e5z2eqGzt47PfO5k/zUYks7VNZuSTIL5flgN54P9uIZYTeeD/biGWE3K/F87HnQEQAAAByUefaUAgAAwIEQSq9BVd1ZVR+pqo9V1VtH18Nqqarfrarnq+ojo2th9VTVzVX1oen/Qz5RVT8/uiZWR1W9tKomVfXhqvqHqnp7VdXoulg9VXVdVT1VVe8fXQurpao+WVXPTP8/MhldD6unqr64qv6oqp6uqo9X1bcMq8Xy3atTVTdk6z2rtyd5LsnjSe7p7ieHFsbKqKpvT/IfSd7V3beOrofVUlVfnuRLu/vpqvrCJE8m+ZHu/vDg0lgB0wD6su7+z+nJ93+d5L7u/uDg0lgxVfWzSTaTfFF3f+/oelgdVfXJJJvd7R2lXFFV/VGS93X3u6vq+iQv7+5/HVGLTunVuy3Js919vrv/J8nDSe4aXBMrpLs/lOSfR9fBauru57r76ennf0/ydJKbxlbFqugt/zm9fEmS65I8P7AkVlBVbWTr7x6/M7oW4HCpqi9Jcqy7350k3f3pUYE0EUqvxUaS2XexXpjeA9iXqvqqJMez1Q2DJC8uy/xwtsLoX3W3rQBs9/YkP5fkM6MLYSV1kr+YLuF9y+hiWDlfk+TSdPnus1X1+9OVW0MIpQADVdUXJHlPkp8Z+RtKVk93/293vzpbv/C8vapeO7omVkdVfW+S57v770bXwsr65u4+luQ7k5ysqu8eXRAr5fOy9QvxB7r7G7K1uu+XRhbD1bmQ5OaZ643pPYC5TPcKvjfJH3T32dH1sJq6+1+S/FmSbxpdCyvlW5N8/3Tf4B8m+Y6qemhsSayS7n5u+s/ns/XLz+NjK2LFnE9ysbv/dnr9niSvHlWMUHr1nkhya1VtTP9ieXeSDwyuCTgkpgfZvCPJx7r7N0bXw2qpqld8dhlVVX1+ku9OYvkuL+ru+7p7o7u/Ksnrk3ywu398cFmsiKp6eVW97LOfk9yZ5KNjq2KVdPf5JP9UVV87vfWdST4+qp7rR/3gw667X6iqe5M8mq1w/1B3O26bF1XVHyS5I8krqupCkl/p7neMrYoV8q1J3pjkmem+wST5he4+N7AmVsdXJHnX9JcXL81WN/1PB9cEHB5fluR9VdVJXpatAzkfGVsSK+hNSd49/QXGPyZ5w6hCvBIGAACAYSzfBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAY5v8AgOQrT69ZQ/UAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "a=[h_mc_under.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc_under.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Ds End Vertex chisq/ndof Signal MC/ data under peak comparison\", fontsize=20)\n", - "\n", - "plt.bar(b,a,width=0.05,alpha=0.6,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.06, alpha=0.4, label=\"data under Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "a=[h_mc_over.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc_over.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n", - "\n", - "plt.title(\"Ds End Vertex chisq/ndof Signal MC/ data over peak comparison\", fontsize=20)\n", - "plt.bar(b,a,width=0.05,alpha=0.6,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.06, alpha=0.4, label=\"data over Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [], - "source": [ - "nbins=70\n", - "MC_Ds_ownvtx_chi2ratio=MC_tuple_dict[\"Ds_OWNPV_CHI2\"]/MC_tuple_dict[\"Ds_OWNPV_NDOF\"]\n", - "data_under_Ds_ownvtx_chi2ratio=data_tuple_bkg_under[\"Ds_OWNPV_CHI2\"]/data_tuple_bkg_under[\"Ds_OWNPV_NDOF\"]\n", - "data_over_Ds_ownvtx_chi2ratio=data_tuple_bkg_over[\"Ds_OWNPV_CHI2\"]/data_tuple_bkg_over[\"Ds_OWNPV_NDOF\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], - "source": [ - "if np.max(MC_Ds_ownvtx_chi2ratio)>np.max(data_under_Ds_ownvtx_chi2ratio):\n", - " max_ownvchi2_under=np.max(MC_Ds_ownvtx_chi2ratio)\n", - "else:\n", - " max_ownvchi2_under=np.max(data_under_Ds_ownvtx_chi2ratio)\n", - " \n", - "if np.max(MC_Ds_ownvtx_chi2ratio)>np.max(data_over_Ds_ownvtx_chi2ratio):\n", - " max_ownvchi2_over=np.max(MC_Ds_ownvtx_chi2ratio)\n", - "else:\n", - " max_ownvchi2_over=np.max(data_over_Ds_ownvtx_chi2ratio)" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], - "source": [ - "h_mc_under= r.TH1F(\"Ds own PV vertex MC/data comparison under\", \"Ds own PV vertex MC/data under Ds mass comparison\",nbins, 0, max_ownvchi2_under)\n", - "h_mc_over = r.TH1F(\"Ds own PV vertex MC/data comparison over\", \"Ds own PV vertex MC/data over Ds mass comparison\",nbins, 0, max_ownvchi2_over)\n", - "\n", - "for i in range(len(MC_Ds_ownvtx_chi2ratio)):\n", - " h_mc_under.Fill(MC_Ds_ownvtx_chi2ratio[i])\n", - " h_mc_over.Fill(MC_Ds_ownvtx_chi2ratio[i])\n", - "\n", - "n1=h_mc_under.Integral(\"width\")\n", - "h_mc_under.Scale(1/n1)\n", - "h_mc_under.Integral(\"width\");\n", - "n2=h_mc_over.Integral(\"width\")\n", - "h_mc_over.Scale(1/n2)\n", - "h_mc_over.Integral(\"width\");" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [], - "source": [ - "h_data_under= r.TH1F(\"data below signal_1\", \"data below signal_1\",nbins, 0, max_ownvchi2_under)\n", - "h_data_over= r.TH1F(\"data over signal_1\", \"data over signal_1\",nbins, 0, max_ownvchi2_over)\n", - "for i in range(len(data_under_Ds_ownvtx_chi2ratio)):\n", - " h_data_under.Fill(data_under_Ds_ownvtx_chi2ratio[i])\n", - "for i in range(len(data_over_Ds_ownvtx_chi2ratio)):\n", - " h_data_over.Fill(data_over_Ds_ownvtx_chi2ratio[i])\n", - " \n", - " \n", - "n2=h_data_under.Integral(\"width\")\n", - "h_data_under.Scale(1/n2)\n", - "h_data_under.Integral(\"width\");\n", - "n3=h_data_over.Integral(\"width\")\n", - "h_data_over.Scale(1/n3)\n", - "h_data_over.Integral(\"width\");" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "a=[h_mc_under.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc_under.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Ds Own PV Vertex chisq/ndof Signal MC/ data under peak comparison\", fontsize=20)\n", - "\n", - "plt.bar(b,a,width=0.015,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.01, alpha=0.6, label=\"data under Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA58AAAHnCAYAAAA//+n5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3Xl8FEX+//F3BUICmMh9n4IoiCICIldEUQTkipyiruh3Pdav4Aoq6soCrqL7Y3HF4+t6LKCrwAqCoIIIKAgICIoXyioKRkEEIdwLJFC/P6onTCY9mQmkE8HX8/HII0l3dXV1T013f7qqq421VgAAAAAABCmhuAsAAAAAADj1EXwCAAAAAAJH8AkAAAAACBzBJwAAAAAgcASfAAAAAIDAEXwCAAAAAAJH8AkAYYwxPxpjNhQgfUNjjDXGvBBkuYqLMWaZMSa7kPK6xRjzpTHmsLfP/lYY+Uaso9DKGzRjzO+9/XBtcZelOJxMnxWKhjHmIe870b64y/Jbcqqfx/DrQvD5G+UdZMJ/so0xmcaYz4wxk4wxvYwxJYqgHI2MMU8bY9YbY/YZY/YbY/5jjPk/Y8xZQa+/MBhjJvvsz/3GmC+MMY8aY8p76S735n0YR56DvLSz80lTqPmdqN/6hXRxMcbc5+33ZsVdlvwYY66Q9A9JRtLfJI2R9E4cy9U0xkwwxnxljDlgjMkyxvzsBS5/M8acEXDRfzXCvmPWGPNuPukaGmOOho7t+aRrYox5yjtW7fZuCmwxxrxhjLnBGJMUZbkaXv5/L4ztOlEFvWEEACg+JYu7ACh2Y7zfJSSVk3SOpEGSBkv6zBjTz1r7dRArNsYMlfSY3E2QJZLelGQltZB0q6SbjTHDrLVPBLH+AMyW9In3dwVJPSWNkNTXGHOhpIWSNkpqZYw511r7eT553eT9fi6fNIWdH47P95IaS9pVTOtPl/SdtfbTYlp/vK70fg+y1q6NZwEvoH5PUnlJqyU9K2m/pKqSWksaLukLSd+FLTZIUulCKvOvVbakjsaYBtbab33m/14uyM/2fudijDGSRksa6c3/QNK7kvbJ7ds0SRMl3SLpIp/8e3vLzTzRDQHwq1Dc5zH8hhB8/sZZa0dHTjPGVJX0pKR+khYaY1paa7cV5nqNMb+TNEHSTknp1tr3I+Z3kPS6pAnGmExr7b8Kc/0Bed1aOzn0jzHmXknLJDWXNMRaO8br0vKwXDA41C8TY0xDSRdL+kHSvGgrs9bawswPx8damyVpfXGs2xhTS1JLuZs4v3blvd/bC7DMBG+54dbaPNvo1e1cPTSstRnHXcKTx5tyAeDvJd0XPsMYkyh383CFpDMkVfJZfqSkP8tdcPaz1q6OTGCM6SZpWJT1p0vaJmn58RUfwK9JcZ7H8BtkreXnN/gj18Jo85mfINfiYCU9HjGvoaRXJG2RlCXXEvGVpEmSKsax7hS5oNNKuiKfdF28NDskpXjTzvKmvRKRtn5omyR1iJj3V2/6pWHTNnk/ZSWNk5Qh6ZCkDXKtlaYA+3Kyl/9gn3l3ePPe8v6v5u2znZKSo+T3qLfMqDjWfUL5SWoj6TVJP0s6LBeg/kNSdZ+0y+RaUpLkWk2+9vbZC948G+WnVlgeJSXdLmmVpL2SDkj6WNJt4ftcrlUl1BJ+m09ZHvHmPVuAz6m23E2VbyQd9OrtR5LGRKT70asHZSWND6sb30i6K7JuyH0frKQXIqZXl2upy/A+o/96eUyVVD8ibZKkUXIteAe93w9KKuPlvTDKNt3uzW/n8zklSnrA25ZDXjkekZQYJa9rvM/ioFxg8aJXv5ZJyo5yjLhN0hpvX+6X9KFca1n4Z/n7eOpGlDId8tKVKsDnHK28yd4+3Ri2jx+WdJrfPpb0kDe9vaQBci2vB+SOR1Pk/x25UK53wTov7UG578k4SeV80of2zbVxblso/WhvX/8kqWREmqu8NDdI2hq5LyQ18OrjQUmNY6wvyWdaeW/55wvwmcRdt7zvwl2SFsgdl0LHtwWKOF9IuiyfuvVCWLr+kmbIBduH5Vp418h9fxLi3Y4C1vs6ko5KWp1PXgu8sp4dMb1QjssxtqNkqN5LqiV3Tt8ud5xaI2lAPst2lbuRucNb17eS/p+kVJ+0nSX9S+7Yd8j7XnwhdwPEr37lfO8ipteTu844JOnqOD+rkt5n9YGk3V5d+t4rT8OItOXkrhVC54edkt5W2HWDT717QFJbSfO9/PdLmiOpnpeusVyPqN3efn1X0rk++b3s5VdH0t2S/uOV4Qe5c1BKYe5XSdd5dXafpA3e/MI4j8X13fCpf5XlriO2etvyhaTfFeR7yc/J9UPLJ3xZa48aYx6S1FHS1caYO6211hhTXS5wSJE7yP5H7iBypqRecgfKHTGy7yt3AfOhtXZ+PmV42xizWlIrb5lJ1tr/GGM2S7o0InmniL+XRvx/UO4EFC5R7qRRWe5Ef1RSH7lgLVnHuiSfiFCXNxfxW7vVGBNqtegjd8I/ltiYkpKul3RErttbvk4kP2PMTXIXNLvlWpl/krswvVFSd2NMa2vtZp/VzpLUVO6kuk/uJsQHcifrHt78z8LS7/HWV0rSW3In7s8kPS93Musk6Wm5z/kGb7usMWawXDfm8caYZdbaz7x8OsvdIPhcLriPyRjTWu5iqbykxXLdBRMkNZO70B0VsUgpuZNiObmLVsnVwXFyF3kPx1hfWblWoXreekOfS325unuWXBAU6gL5mly31G8kPeWt42avfPm5Su6EvcJn3jS5fTpb7oKhu6R75VrCbgpPaIy5W+7iMVPuZspuuQvM5XIXNZHbZ+QuPvrLXcw9781Kl6tT7ST9zpv2sdx36SpJ50r6u7w6EfY7mkNyn0VDSV/GSBuVMSZBrl52kbs4f8rLd7Bi7+OhkrrJ1YN35Lr7Xi2pmTGmubX2cFjamyVdLnf8mS3XKttSro51McZcZK3df7zbEeF5uUC3u9z3N+Qmuf36qtzNhkg3yh2zp1lrv8pvBdbaQz6Te3jLz4qnkAWtW3LH44e9+dPktqWa3GMM84wxN9pjPUy+k6tbw+QCsPBHND4O+/thuWPV23IBVorccedJucc8bohzW+Ku99baDGPMe5IuNcY0jtzXXq+FSyWtstauD5temMfleFSUO37/IneOKO9t3zRjTA1rba7neo0xD8oFOD9Jmi53vj9Px+p4W2vtvrBF7pELbpd6yyR7++lBSRcbY66w1h7Jr4DGmOaS5sp1p+9irX0v1kZ5zyvPldvH38sdgzPlArzL5M79G7y0FeTq29lywdJrcvWwv1zvr5uttX4D8bSXdL9cvXpK7vjWQ1ITY8xAuXPIh3Lnt3pefou8+uB3nfSkpA5y393Q92SYpPbGmLSI7+Px7tcRki7RseNZiv8ePK7zWLznhHAV5M5fuyS9JHfDdaCkF40xR6y1r/gsg5NdcUe//BTPj2K0fHppkuSCAyvvDpekId7/t/ikT1aU1reIdP/08ng4jrQPK+9d7Je8aeeETZsqd1GxVtLSsOnl5QKvRRH5bvLyeE1hLQdyJ+JtcgdC3xYinzJOlk/Lp9xBdK03b2TY9K7etMU+eaV7894swGdZ4Pzk7sgelvSppMoR8zp4n/v0iOmh1s1Vkk7zWVe+rTg6duf1YeVt5XzGm3elT1my5e54l5W7C/uz3MXV2X7riVKPM7x60NdnfrWI/3/0yvJqRN2oLHeBtlNSibDpee4Yh+33v/isr2T4/pM7IVu5oDgpbHoluYujPK1yYXU1W9I/onxOSyWVDZteWq5bVXb4Z65jLWE/S6oTNr2E3PfDKm/r1HXe9JUR6zhNroXQSuofsUzo7n6+rZ0RyzzvLfOT3AVvB/m0Avhsf2R5b/DyWaCwVlS548N6v30cVl+3SWoQMe9Fb95VEdN9t03uBpCV6z4c93cmn+/YaG9f75XXq8KbX8er5894//u1fC5RlJ4acZZhltyFcczW6OOsW8mKOCZ501PljlfbFdGyI6+3Qj7lqO0zzcgFW1ZSizi3vUD1Piz9oz553efN+0PYtEI/LuezLaGWJyt3Tg0/JjfQsVbNumHTLw/7HpWNyG+gN29crH3vTR/lpe8T5XvX3vu/s1fPf5RPq2E+2/f/vHymR9ZVb9srhv0fuiZ5MiLd2XLXAgfDt0PHWj6PSuoescw/vHl7FdFrR+7mn5U0LGJ66Nj4U8R6wr8n9xXSfs2U1MhnuRM9jxX0uxFe/x6LyPss73vwWbyfNz8n10+xF4CfYvrg4wg+vXRbvbQXev/f5f1/8wmse66Xx61xpL3VSzs3bFroQm5o2LSfJf1brmXqcOjgp2Nd0O6PyHeTN93voiR0wds0zu2Z7KV/Xe6icLSkx+XuCFq5AKJ8WPqEsPWfGZHXW970ngXYnwXOT+4Oq5V0cZQ8Z8hd6ISfREIXOZ2iLBP1QlruJJop1z0rTzc3SafLBUVTfOY94OX7oqRFKuCFs1yXSSvppTjT/yh3UeHXxW2SIrrJyf+kHboQezCO9b3npW3pM2+Qogefg715kV0RQ5/TRT7LhC5MuvhMu8snfS25YCYyQHgvn3WkefPeiZh+PMFnGbkLw2wdu1A5Kncz4jF53dt8tj+yvIu9Zc/3Sd/fbx/r2MXavT7LXKwoQUU+25Lps0+OO/j0/n/e+3xqe/+P8eZf4P3vF3x+7aW5LN6yR3weByRNjTN9getWjPz+6OXXNmJ6vsFnPvmdL5/zQz7pC1Tv5W6YhQKnhIj06+WCmvBzQ6Efl/PZltDFf5b8g/37vfl/Cpv2hvf9y/O98+avkbQlzvWX8/J/LmJ6ePfQwV75vlDBjhuJci3meyWdHiNtklzPkExJpX3m/zmyjuhY8Pm2T/oO3ryvfObV9uZNi5geOjb+MZ/vyTeFtF/zBJLe/MI6j8X73QjVv13yabTw8jvq95nwc/L/0O0WsYS6jYbqyutyFzhPGWMuk+u2sULSl9Y7YhSB0CsGOkl6whjTVFIVucDkB7kAOU2um8ilEcuE22qt/cFn+k/e7/I+8/LTy/uR3Mlsk1ww/Ki1NjOUyLouzf+U6x7ze7luMKFuWF3kuku9Fe9KjzO/Nt7vzsaYS3yyrSb3mTeUuwsfbmW8ZQvTWO6kuEXSn10PnTwOeukijZXr/h3qsvMvGzawUxxCo3XOLcAym621P/lMj7duLJBrJf2TMeYCubq4QtIn1tqjEWkvkGvJ/cgnn8X5rCNdrgUq2is31vhM8yv/Bd7vJZGJrbU/GmO+lRu4JtwFcs/zrPJZx3K5FpPmUcoVN2vtAUn/Y4z5k1xdvtDLt4WkOyXdYozpY619O0ZWzSXttdZ+4jNvqc+0cHkG41GUeuAN9vMHuRseTeRa68JfaVYzxroK6nm57/yN3mMSN0r62Fr7cf6LHbcr5FrQ4+pyq+OrWzLGnCv37Ft7STXkAoRwBdqPxphKXn7d5LoMlj3O/ApU7621+40x0+Va3kPny9BjAGfJtWJmhuVR1MdlyZ27/QYBW+z9Dv8et5E7tw2OcgxPllTdGHO6tXa3JBljTpO7adBbUiO5lrDwhaPt++HeMksk9bbWFmQU1iZy3Unnh8oRI22ypHettf/1mb9I7prH73jmd4z9OY550c4f+X1PzjTGpFhr90ontF8LUk8Keh47nnPC59bagz7Tf5LbnnJydQ6nEIJPRGWMSZbrjy95B01r7QZjTDu5u4Hd5EbElaQfjDF/s/G9FmWr97t2HGlDaXKeX7HW/mCM+UbuuYYSOva85yIv79BzhPO833vkfwHp9zyT5O62SRGjaMbhhgIERRPlWgWuN8Y8YN1IczfKXahOtDGegSmE/Cp6v++Pke9pEf8fscf3zFpofU2U9/nK/NYXCq5n6djn/HgB113O+/1LAZY5obphrd1hjGkjt63ddew1I9uNMU/LdTnP9p6TSZX0Y5SbNzv98veexeksaab3WUc6Yq31e7+jX/lPz29d3vScACFWma21R4wxu3TsMz9h1tqtcj0MJntlqCB3J/8PkiYZY2pH2d5c5Y2SfWaU6SF+dSFaPXhN7pmvb+UCtJ/Dlh+mvEHUCbHWfmiM+UwuuFkr10qS7/PIchd1Z+r4AuGr5LYn3hs5BapbkuSdXxbKHbsWyT3DuFdun18gt3/j3o9eXVkjqa7chfFL3nqz5c5vQ+LJ7wTq/WS5z+d6HXuv7fXe7xcj0hb1cVnK/7ORjn2GkttfRvkfwyVXvt3ec/6L5W4WfS73DO92uXN0grzBcaLkkeb9XljAwFMq2DE/Vh0NPZtZzmeeX9AUOjYU5LgREuuzSJW09wT3a6xgPEdhncdinBMK+zoMJwGCT+SnvVwd2SnvoXJJ8loPrvIGs2kmd0d3iNxrUY5aa5+Kke8yHbsT/KcYaS/zfkcO6f+u3AhqreSCku+t9747Y8yHki4zxtSQe2bjzeMI5gJlrd1sjJkrdyHVwxjzulyweFRu1Leg8wudgMp6rUtBC61vurW2f0EWNMacLTcK4U65O8b/9AZuiXbSihS6cPF75URgrLUbJF3nDXbTRK4V/na5btml5bpzWmPMHknljDHG58RdQf66yt2tL4z3LIY+mwpyQVOkXGWIVWbvhtDpKsBFTkFZa3caY/5Xbj/Uk9u/n0VJa40xe5X7Ijqc30VlgRljLtKxAbf6RrYMGGOivbbkRD0nN9jJ03ItD7EG6Fgmd2HfSXmDn6i8Vt3ukhbY3APK5KdAdcszUm4wqAuttbl6A3j7sEec6w65WS7wHGbzDp5zgdy5K6YTqPdL5QZGSjfGpMpdbA+UuzEROeBeUR+XpejHmND08O3ZI+mwtbZKnHlfJRcgPWGtzTU4nHdTYGQ+yw725v/FGJNgrX0wznVKBTvmh9dRP377ISgV5AbriVaG0ABtJ7JfC6QwzmNFcU7AySUhdhL8FnkHmlBgONWni4WstdnW2o+stX+VG/1RciMSxjJD7uRwoTHm8nzKcLlcN7udOjbiaMgi7/cVchdSiyLmnSfX9U0R835NnvN+/15uIIe6cs9E+J18Cju/UNebDse5Lj+hAN+vP9Y6udaLNt5Ni7h4re//ljvJ9ZMbROJ8uVGV4xXa1q4FWKbQWGuPWmu/8HoFXOFNDv+efCzXUtDCZ/GOUbJNl7vrHqu7aTxCXTQvjpzhdd1u4LPMWrkyt/KZ10YuMA6q66ck74F1V6ck/zoXbq2kFGPM+T7z0nymHY9G3u83fQLPFspnVMkT9Ipct7Rakv4d6paXj4lyrX79vRs7UXkjhoZ0lAvU4+1yKx1f3Wok1+3drxu6X1dUyR17otWB0OcyuwD5RVPgeu/V05d07BjWQ+4m2is+rfVBHJdjaWKMqewzvaP3e23YtJWSKhtjzooz7xPZ95lyN58/kDTGGDM2znVKbmTsvZLaeQF/fkKvb2kTUd9DQo/uBHo88+T3PdkQ9t0uzDodlzjOY8V+TsDJg+ATeRhjqsh14+go10XrwbB5LYwxfi0IoWmxurDJWrtH7nkOSZridbOKLENbuXfpSdKdPhdUoYfbb/PWHR5gvit3IXJv2P+/RvPkugJeIdeNWTo2PHnQ+T0pdwE6wRiTp/uzMSbBey6pIELdk/J05/O6hj4ld4H8mHcnNHKdFXwuav4udyPhEWvtu3KDD62U9L/GmKviLNfrcs8CX2uM6eOz3mpx5hM3Y0xT73sUye97Msn7/bfwix/vObU8d/u9Fqgr5W4sFMZrO16Wqwt3G2PqhK2nhKQJ8j9PhF7bM94YUzpsmdC7USU3UNAJMcaMMcbUjTKvp9yrJXYo9mtYXvJ+j/P2XyiP8vLZx8cp9DhBx/CJ3vHymUJaRx5el8Qr5G5IxOoOKa+HyF/kuuXN9Vr/8jDGXKncz4qnywV5cwpQvOOpW1sl1TDGNAqfaIwZJNfy6meHpCpRbmxF+1zOUeyeN5GOt96HRkf+nY49uz7ZJ10Qx+VYSsptT07wboxpIHeOzlLulvTHvN8veN+dyPKVMsa0DJsUbd/XlBsPIV/etUJnufP9fcaYx2IsElouS+47d5pX1lIR6y9pjKnopT0od61RXhFd1o0xZ8p1lz8sV5eDNiL8c4/4nkwKS3dC+zVeBTyPFck5AacGut3+xhljRnt/Jsjd1T5HrrttKbkBDfpba7eFLXKd3CAfS3TsRepn6NizQHE9j2etnWiMKSfXkrXUGLNYbsAVK9cCdIlcl9E/Wmtf8ln+F+OedQq9oy88wFzhlauK3HMQn8dTpqLmPQcxUS5QbCt3QinIhd1x52etXWeM+b1ccLreGPOW3DsmS8p9nmly+65pAYrwgVxr3D3eCSv0nMoE7+bBKLlAcoikK40x8+UuGk+Xez9aO7lnnf4jScaYvnKjHX8g18VH3vMlV8vdZf2nMeajWC3F1tpDxph+cq2EM4x7996HcnW+qdzd5sgBSE5UF0mPGGOWyX2P9sgF3lfJ1evwC4R/yY24eqWkz40xc+QCg75eOSNbhzrJ7bOCtEBFZa391rgBff4q6RNjTPg75srKjTQZORDUv+TueveRtM64bt5GLkCpKzdq8b8LoXjDJY00xqyVe25vu9wd9JZyn1u23Mjbfs+9hpsk1xPicrl9/IbcMa6vXF06S8eeMTpe78rtq+u8C8gP5LrLpcuNeP1zPsueEGttrEGTIv1F7lmqkZLWGGM+0LEXw1eV27cN5bXEeYFJb0nLrLVxPzt9nHXrCblXZ60wxvxbrpdMS7kWqNk6NqhbuEVyg5nM875zRySttda+JXfBO0TSs15vmm/lBh3qIxdcx3sTSzrOem+t3WSMeV/uuBoqW57zUkDH5Vg+kQtiPjLGvCNXZ/vLHWOGWWs3hZXvHWPMA3L15zvj3jH9vdx38ky5erNMx24STJc7do/0eh18Jve6rL5yz/XWj1U46wZtulLueHend4Pu9ijPyIcbJddzqp9cL6s35epSLbmA9h4dCyhDg1sN9258L9Gx93yeJvc6nIxYZS0EH0r6NOJ7cq7cmBXhvX1OeL/GqaDnsaI4J+BUYH8FQ+7yU/Q/OvbagtDPEbkD82dyF2q95P9KjIvkniH8Qu5CJVtuMKB/y+c1BnGU42y5O5T/kQsYD8i9CuAZxXiPo9zB2Epa5zNvvjfv31GW3SRpU5R5o71lO8a5DZNVwNd/hC1b29v3VtLYQvhcC5SfXPD+otwFxGFv///HqwOXRaTN8woLn/y6yV2w7gurW7XC5ifIDbbxro4N+rFT7kL9QR17ZUR9rz7uVNj7AcPyCb1CZ4Xifx9rXbl3sG3ytnWf3AX3nyPSRX1tgyLeQedN8xui/hy5lt61cifsbLn3Rc6RlOaTb5JX7zbK3cTZ6O2PMop4DYikZ+VaJCpEKWPUz0n5vw7nGq+8B72yviR3QeObn1zwcrvcTaPQd3eN3CBAfseO43nVSie51u8VcjcqsuWOO+vlupnneR1SPuUt7X1+m8L28cNyN6mspBmxPuv8PnNvelVvv/3irWODpEfkAq089Sq/zyPG5zc6zvR5XrUSMb+J3LOi67x6eliut8tcuWfGS3np2njrHRrPeguhbg2SC4oOy7WuzJcLkHz3l1yA8KykzTr2Wp7w72NLuZE793s/a+SeBfX9HGNsS4Hqfdhyg3XsmHhHjHUU6nE5yjpCr7pYKBdQvCIX2B70tm1gPsumyT0Ks0XuWLRP7ibv/8l7LVvEdyX0btj/enVthFzAmuvYlt/3Tu4YOTv0eeW3r8OWSZQ0VC542+/ty43evo18d295uWBqg9x3N1Tv8rySSMdetfJAvMeGyH0eMT10bKwjFwj/xyvDj3KtzXnebVxY+zW/cqvg57G4vxvR9oXPPon7fMHPyfNjvA8ZAPAr43UjzJK0yFp7mXHPYm+Ru+HSKf+lEQ9jzKVyLWcPWWsLbaCOU4kx5v/JXRTXtUXTAoSARR5birs8v2XGmJflbtDUttZGG5UbOGXwzCcAnDzayLWuFUqX298SY0xVn2mpOvacF/s0unRJHxF4AgBOFM98AsBJwlq7XLFHdoW/p7wBRJbLdamrKjfyaFVJT1trGYkxCmvtmcVdBgDAqYHgEwDwWzBbbnTsQXIvRN8v9+z6/dbaifktCAAACgfPfAIAAAAAAscznwAAAACAwAXS7bZSpUq2Xr16QWQNAAAAAChGH3300S/W2soFXS6Q4LNevXpas2ZNEFkDAAAAAIqRMeb741mObrcAAAAAgMARfAIAAAAAAkfwCQAAAAAIHMEnAAAAACBwBJ8AAAAAgMARfAIAAAAAAkfwCQAAAAAIHMEnAAAAACBwJYu7AAAAACeDQ4cOaefOndq7d6+OHDlS3MUBgEJRokQJpaSkqEKFCkpKSgp0XQSfAAAAMRw6dEgZGRkqX7686tWrp8TERBljirtYAHBCrLXKysrSnj17lJGRoTp16gQagNLtFgAAIIadO3eqfPnyqlSpkkqVKkXgCeCUYIxRqVKlVKlSJZUvX147d+4MdH0EnwAAADHs3btXqampxV0MAAhMamqq9u7dG+g6CD4BAABiOHLkiBITE4u7GAAQmMTExMCfZyf4BAAAiANdbQGcyoriGEfwCQAAAAAIHMEnAAAAACBwBJ8AAAAIxOTJk2WM0eTJk4u7KHExxqhjx47FXQzglMV7PgEAAE7QlFUZxV2EfA1qXadQ8jly5IgmTpyol19+WZ9//rn27NmjMmXKqHbt2mrevLn69Omj9PT0QlnXySD0jJwxRt98840aNGjgm+6SSy7R4sWLJUmTJk3S4MGD86TZv3+/nn/+ec2ZM0dffPGFdu3apTJlyqhRo0a6/PLL9T//8z8644wzgtoUoEgQfAIAACCmI0eOqHv37nr77bdVuXJl9erVSzVr1tSBAwe0bt06zZw5U5s2bcoVfKanp+uiiy5S9erVi7HkwSpZsqSys7P1z3/+U2PHjs0z/5tvvtHixYtz0vlZuXKl+vbtq82bN6tWrVrq1q2batSooQMHDuiTTz7RuHHjNG7cOK1cuVIXXHBB0JsEBIbgEwBOVW/cEX1ejwlFVw4Ap4SpU6fq7bff1oUXXqiFCxcqJSUl1/wDBw5o1apVuaadfvrpOv3004uxvsMiAAAgAElEQVSymEWuatWqql69uiZNmqQHH3xQJUvmvrx+4YUXJEk9evTQrFmz8iy/fv16XXHFFdq3b58effRRDR8+PE8eGRkZuueee7Rnz57gNgQoAjzzCQAAgJg++OADSdLgwYPzBJ6SVKZMGV1yySW5puX3zOf8+fPVrl07lS1bVhUqVFDv3r31xRdfaPDgwTLGaNOmTTlpN23aJGOMBg8erE2bNmngwIGqVKmSkpOT1bJlS7355pt58t+9e7ceeughXXzxxapYsaJKliypypUrq2fPnlqxYsWJ7YwIN910k7Zu3ZqnHFlZWZo8ebLatm2rJk2a+C47ZMgQ7dmzRyNGjNCIESPyBJ6SVKdOHU2bNk1t2rQp1HIDRY3gEwAAADElJydLct1IT9S0adPUtWtXrV27Vv369dMtt9yizMxMtW/fXt9++23U5b7//ntdeOGF+umnn3TTTTfpd7/7ndavX69evXrpvffey5X2q6++0tixY1W6dGldf/31uvfee9WtWze9//77SktL09tvv33C2xFy9dVXq2zZsjmtnCFz5szRtm3bdNNNN/kut3HjRi1cuFDJycm65557Yq4nKSmpUMoLFBe63QIAACCmfv366fHHH9fjjz+u7du3Kz09XS1atFDdunULlM/evXv1hz/8QcnJyVqxYoWaNWuWM+9Pf/qT73OTIYsXL9b48eM1bNiwnGnXXXed0tLSNG7cuFwtr02aNNHWrVuVmpqaK4+tW7eqVatWuvPOO9WlS5cClT2alJQUDRw4UJMnT9aPP/6oWrVqSZKef/55paamqn///r7btWzZMklSixYtVK5cuUIpC/BrRssnAAAAYmrTpo2mTJmiqlWr6uWXX1afPn1Ur149VaxYUenp6XrjjTfiymf27NnatWuXbrzxxlyBpySNGjVKFStWjLpsw4YNcwWektShQwc1bNhQH374Ya7pqampeQJPSapWrZoGDBig9evXKyOj8EYpvummm3JGA5ZcK+2CBQt0zTXXqEyZMr7L/PTTT5KUE6wCpzqCTwAAAMRl4MCBysjI0Pz58zVy5Eh1795dJUqU0Ouvv66ePXvq+uuvl7U23zzWrl0ryQWNkUqVKqXWrVtHXbZly5a+06tXr67MzMw805cvX67+/furdu3aSkpKkjFGxhiNHz9ekrR58+Z8y1oQrVu31rnnnquJEyfq6NGjeuGFF3T06NGoXW6B3yK63QIAACBuiYmJ6ty5szp37ixJOnr0qGbPnq0bbrhBL730ktLT09W7d++oy+/evVuSonYzLV++fNRloz3zmJCQoKNHj+aaNmvWLPXt21fJycm6/PLL1aBBA5UtW1YJCQlavHixlixZokOHDuW7rQV10003aejQoZo3b54mTZqkFi1aqHnz5lHTh15BU5hBMPBrRvAJAACA45aQkKD09HStW7dOI0eO1Lvvvptv8BnqCrtr1y7f+dGmF9TIkSNVunRpff7556pfv36uecOGDdOSJUsKZT3hrrvuOo0YMUK33nqrNm/erD//+c/5pm/fvr0kac2aNdq9e/cp/1oagG63AAAAOGGhoDJWt9tQS+DSpUvzzDt8+LBWrlxZKOX5+uuvdd555+UJPCXlGRm3sJQrV059+/bVjz/+qLJly+rqq6/ON339+vV12WWX6eDBgxo3blzM/Au7pRYoagSfAAAAiGnq1KlasGBBnu6tkvTLL7/o2WeflSSlpaXlm0+vXr10+umna+LEifr0009zzRszZox27NhRKOWtVq2avvzyS23bti3X9HHjxumTTz4plHX4eeihhzRr1izNnz/f932okZ544gmlpqbqkUce0fjx45WdnZ0nTUZGhgYMGFDo7ycFihrdbgEAABDTqlWrNGHCBFWrVk3t27dX/fr1lZiYqI0bN2ru3LnavXu3evXqpb59++abT2pqqp5++mldd911atu2rfr376/q1avrgw8+0CeffKL27dtr2bJlSkg4sTaSO+64Q3fddZeaN2+uvn37qnTp0lq6dKnWrl2rrl27at68eSeUfzR16tRRnTp14k7fuHFjzZ8/X3379tVdd92lCRMmqFOnTqpRo4b279+vTz/9VMuXL5cxRvfee28gZQaKCsEnAAAAYho2bJhq166txYsXa/Xq1ZozZ46stapYsaLatm2rQYMGadCgQTLGxMzrmmuuUYUKFfSXv/xF//73v5WUlKS0tDQtW7ZMDz74oCT5vialIIYPH66kpCQ99dRTeuaZZ5SamqoOHTpo2bJlmjNnTmDB5/G46KKLtH79ej3//POaM2eO3nrrLWVmZqpMmTJq2LChhg8frptvvtm3CzFwMjGx+uUfj5YtW9o1a9YUer4AgAJ4447o83pMKLpyAKeAr776So0bNy7uYpzyrLVq2LChDhw4kPMOTABFJ95jnTHmI2ut/7uP8sEznwAAAChSu3fv9h085/HHH9d3332n9PT0YigVgKDR7RYAAABFasWKFbr22mt1+eWX64wzztChQ4e0fPlyrVy5UrVr19bo0aOLu4gAAkDwCQAAgCJ11llnqWPHjlq2bJlee+01GWNUq1YtDR06VPfff7+qVKlS3EUEEACCTwAAABSp+vXra8aMGcVdDABFjGc+AQAAAACBI/gEAAAAAASO4BMAAAAAEDiCTwAAAABA4BhwCADgvHFH9Hk9JhRdOQAAwCmJlk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAACcsHr16qlevXrFXQzgN2ny5Mkyxmjy5MnFXZR8MdotAADAicpvtOhfg5NoxGpjjC6++GItXry4uItyUjHG5Pq/RIkSSklJUe3atdWiRQv17t1b3bt3V4kSJYqphADBJwAAAHDKGDVqlCTpyJEj2rVrl9atW6cpU6Zo8uTJOu+88zR9+nQ1atSomEuJ3yqCTwAAAOAUMXr06DzTfv75Zw0ZMkTTp0/XZZddpjVr1qhKlSpFXzj85vHMJwAAAOJirdVTTz2lc845R8nJyapZs6Zuv/127d692zf97t279dBDD+niiy9WxYoVVbJkSVWuXFk9e/bUihUrcqUNPbMmSUuWLJExJucnPKB67rnn1KNHD9WqVUuJiYlKTU1Vu3bt9PLLLxd4ew4dOqRHH31U5557rsqUKaPU1FR16NBBr776aq50K1eulDFG6enpUfNq3LixkpKStHPnzlzT58+fr27duqlSpUpKSkpSgwYNdPfdd2vXrl158gg9N7tnzx4NGzZM9erVU2Jiom9AWRBVq1bVtGnT1LFjR/3www8aO3ZsrvkbNmzQNddcoxo1aigxMVFly5ZV48aNdcMNN2jHjh1xrcMYo44dO2rLli264YYbVK1aNZUqVUotW7bUokWLJLn6MHToUFWvXl2lSpVSkyZNNH369Dx5FaTehCxcuFCdO3dWhQoVVLJkSZUrV06tWrXSn/70p1zptm7dqj/84Q+qW7euSpUqpeTkZDVs2FADBw7Ut99+G9e2hj6n3bt36/bbb1fNmjWVnJysJk2a6IknnpC11ne5VatWqW/fvjn7pnbt2rrlllu0ZcuWPGlXr16tW265Reecc47KlCmj5ORknXnmmRo+fLgyMzPjKqckZWZmKi0tTQkJCXrkkUfiXi4oJtrOOREtW7a0a9asKfR8AQAFkN8zaH7PfxU0PfAb8tVXX6lx48bRE/xGnvm844479MQTT6h69erq27evEhMTNXv2bJUvX16bN29WqVKltGnTppz0K1eu1KWXXqq0tDQ1adJEZcqU0Q8//KDZs2dr//79euONN9SlSxdJ0ieffKLXX39dY8aMUd26dTV48OCcfDp27KiOHTtKksqWLavzzjtPzZs3V8WKFZWZmam5c+dq48aNeuCBB/SXv/wlrm05fPiwOnfurCVLlujss89W9+7ddeDAAc2YMUPbtm3TfffdlytIO/vss7Vx40Zt2bJFFStWzJXXhx9+qNatW6tPnz6aMWNGzvQxY8Zo9OjRqlatmnr27KlKlSrp888/11tvvaWzzz5bK1asUGpqak76evXq6fDhw6pRo4b27t2rbt26qVSpUjr33HN17bXX5rs9ocA9v2v7RYsW6bLLLlOVKlW0detWGWP0008/qWnTptq7d6969uyps846S9nZ2frmm2+0ePFivf/++2ratGnM/WmM0bnnnqu9e/eqatWq6tixo3bs2KFXXnlFR44c0XvvvachQ4bo4MGD6tq1qw4dOqRXXnlFu3bt0jvvvKPLLrssJ6+C1BtJevvtt3XllVeqXLly6t27t2rUqKF9+/bps88+0/r167V582ZJ0oEDB3Teeefpu+++U5cuXXTeeecpISFBGzdu1HvvvacXXnhB3bt3j7mtoc+pZs2a2rVrl3r27KnDhw/rtdde008//aTbbrtNTz/9dK5lJk6cqJtvvlkpKSk5Zfzuu+80c+ZMVaxYUStXrlSdOnVy0t96662aO3eu0tLSVKdOHR05ckQff/yxFi5cqMaNG2vVqlVKSUnJST958mTdcMMNmjRpUs53JyMjQ126dNGGDRs0ceLEmHVIiuNY5zHGfGStbRkzYeRyBJ8AcIoi+AQKDcGn9MEHH6hdu3Zq1KiRVqxYoQoVKkiSDh48qMsvv1zLli1T3bp1cwWfe/bskaRcAZbkWp9atWql0047TV999VWuebEGHPrhhx9Uu3btXNOysrLUq1cvLViwQJs2bVLNmjVjbs8jjzyi+++/X927d9esWbNUsqR7Gm3btm1q06aNvvvuOy1fvlxt27bNlf7JJ5/U7bffniuv//3f/9X//d//ac6cOerRo4ck6b333tOll16qSy65RHPmzNFpp52Wk3769Onq37+//vjHP+rvf/97zvR69erp+++/15VXXqlZs2YpMTEx5naExBN8Hjp0SKeddpqys7P13XffqX79+nryySc1dOhQ/eMf/9Att9ySK/3BgwclScnJyXGv/84779Rjjz2WM33GjBnq16+fTjvtNHXt2lVTp07NGfRo9erVuvDCC9W1a1fNnTs3Z5mC1ps+ffpo5syZWr9+vc4666xcy+zatUvlypWTJL3xxhvq2bOn7r333jytgEeOHNGBAwdyBXTRhD6ntLQ0vfPOO0pKSpIk7dy5U23atNHXX3+tJUuWKC0tTZL09ddfq2nTpjrrrLO0aNGiXF2eP/jgA11yySXq1q2bZs2alTP9xx9/VM2aNfMMJPXKK6/o2muv1aOPPqoRI0bkTI8MPj/99FN17dpV+/fv12uvvZYruM9P0MEn3W4BAAAQ06RJkyS51rxQ4Cm5wGT8+PG+y6SmpuYJICSpWrVqGjBggNavX6+MjIwClSMy8JSkxMRE3XbbbcrOzs7p4hnLxIkTZYzR008/nRN4SlKVKlVyWk9feOGFnOnXXXedEhIS9OKLL+bK5/Dhw5o2bZqqVKmirl275kx/4oknJLluwuGBpyT169dPrVu31iuvvOJbtvHjxxco8IxXUlJSTqvt9u3bJbmAVMo7Wq7kPtt4As+QlJQUPfzww7mmpaenq3Tp0tq3b58ee+yxXKPttmrVSo0aNdKHH36Ya5mC1pv8tiEUeMZKFxoduCDGjx+fE3hKUoUKFXLqTuj7IknPPPOMsrKy9Pjjj+d51rZt27ZKT0/XG2+8ob179+ZMr1Wrlm85r7nmGlWqVEnz58+PWq4FCxaoQ4cOMsbo/fffjzvwLAoMOAQAAICYPv74Y0nSxRdfnGdeq1atVLZsWd/lli9frgkTJmjFihXatm2bDh8+nGv+5s2bc3U3jCUjI0N//etftWjRImVkZOi///1vnvxi2bt3rzZs2KBGjRr5rrtTp06SpLVr1+ZMq1Wrljp16qQFCxboyy+/VJMmTSS51rSdO3fqzjvvzBXErlixQsnJyVGfRT1w4IC2b9+uHTt25OrGW65cuTytd4Up1DKanZ0tSerdu7dGjRql22+/Pee5yTZt2qhJkya+wU9+mjRpotKlS+eaVqJECVWqVElZWVmqVatWnmWqVq2qDRs25JlekHozaNAgvfXWW2rTpo0GDBigjh07qm3btnnW16lTJ1WpUkWPPvpoTstgmzZtdP755xf4FTSnnXaaWrRokWd6qHt4eN0JPae6cOFCLV26NM8yW7Zs0ZEjR/T111/n5JmVlaVnn31W06ZN05dffqndu3fr6NGjubbfz4wZM/TOO+/ozDPP1Lx58wr03SoKBJ8AAACIKTSoUHirZ4gxJlcLU8isWbPUt29fJScn6/LLL1eDBg1UtmxZJSQkaPHixVqyZElOa1Q8vvvuO1144YXKzMxUhw4d1LlzZ51++ukqUaKENm3apBdffDGu/PLbFkk5wWDkoECDBw/WggUL9OKLL+qvf/2rJOW0hF5//fW50u7YsUPZ2dkaM2ZMvmXZt29fruDz9NNPj1n+43Xw4MGcAZGqVq0qSWrYsKGWL1+uBx98UHPnzs0ZAKh27dq66667NHTo0Ljzj9ZKmpCQkKuFMHJeeFAlFbzeDBo0SElJSfr73/+u559/Xs8884wkqUWLFho7dqw6d+4sSSpfvrxWrFih0aNH680338zp6lupUiXddttteuCBB+JucS5XrpxvcB6qU+GDcIUGbXr00UfzzXPfvn05fw8YMECzZs3SGWecoV69eqlatWo5+/Dxxx+PWs9XrFihrKwstW7d2reXQHEj+AQAAEBMoaBo586dql69eq551lrt2rVLlSpVyjV95MiRKl26tD7//HPVr18/17xhw4ZpyZIlBSrDY489ph07dujVV19Vv379cs2bM2dOni6x8WyLn9D0yEAwPT1dqampevnllzV27Fjt2LFD8+bNU7NmzdSsWbM86zh69GjUdRSHZcuWKTs7WxUqVMj1eZx//vmaOXOmsrOz9emnn2rhwoV68skndccddyghISHPM65BO55606dPH/Xp00f79+/XqlWr9Oabb+qZZ57RlVdeqdWrV+v888+XJJ1xxhl66aWXZK3Vl19+qXfffVdPP/20HnzwQe3fv19/+9vf4irjrl27ZK3NE4D61Z3Q37t37/btThxpzZo1mjVrlnr06KFZs2blaZUNden2M3bsWM2dO1eTJk2StVb//Oc/lZDw63nS8tdTEgAAAPxqXXDBBZLke+G/evVq7d+/P8/0r7/+Wuedd16eAEJyA/L4SUhIiDpoztdffy1J6tWrV9z5+UlJSVGDBg20YcMG/fjjj3nmv/vuu5KObXNI6dKl1b9/f23ZskULFy7UlClTlJ2dnafVU5IuuugiZWZmat26dXGXK0hHjx7NeR7z6quv9g1ISpYsqRYtWmjEiBGaOnWqJBfUF7XjqTchZcuW1aWXXqrHHntM999/v7Kzs3MNZhRijNE555yjIUOGaMGCBZIKtq379u3TRx99lGd6aKCs5s2b50y76KKLJMm3y62fUD3v3r17nsDz008/zfdVK0lJSTmDPE2ePFnXXnttThfrX4O4gk9jzBhjzDfGmP8YY14zxvh36gcAAMApKfT6hlGjRuVqzTt48KCGDx/uu0y1atX05Zdfatu2bbmmjxs3Tp988onvMhUrVoz6PFu1atUkKc9IuEuXLs3pahmvG2+8UUePHtUdd9yhI0eO5Ez/5ZdfNHLkyJw0kUL74aWXXtJLL72kkiVL6pprrsmT7s4775Qk3XTTTb7vyszKylJRvR1i27ZtGjhwoBYvXqzq1avrz3/+c868jz76yPc9raFp5cuXL5IyhitovXn//fd9A6zIbVi3bp1+/vnnmOniddddd+Xq/rpz586cunPDDTfkTL/99tuVmJioO++803eAraNHj2rVqlU5/0er53v27NGtt94as1yJiYmaOnWqrr32Wk2dOlUDBgxQVlZWgbYtKDG73RpjGkr6naQm1tr/GmNelXS1pBfyXxIAAACninbt2mnIkCF68skn1bRp0zzv+Yzsiiu594Leddddat68ufr27avSpUtr6dKlWrt2rbp27ap58+blWaZTp06aNm2arrrqKp1//vlKSEhQWlqa0tLSdNttt2nq1Knq3bu3BgwYoJo1a+rLL7/UnDlz1KtXL82cOTPu7bnrrrs0b948zZw5U82aNVO3bt104MABTZ8+Xdu2bdM999yj9u3b++6Hhg0bavr06crKylKPHj3yjGAa2o5HH31U9913nxo0aKDu3burXr16OnTokL755hstWbJErVu31ttvvx13meMxevRoSS6g2bVrl9atW6dly5bp8OHDatasmV599dVc5f3Xv/6lZ599VhdffLHOOecclSlTJuf9k0lJSfrjH/9YqOWLR0HrzdChQ7V582ZdcsklOuOMM5SQkKCPPvpI77zzjurWrauBAwdKcqPA3n333WrXrp2aNWum1NRUbdmyRTNnzlRCQoLuvvvuuMtYvXp17d+/X02bNlXPnj2VlZWlGTNm5LznM/SaFcm9I3bixIm68cYbdfbZZ+vKK6/UmWeeqSNHjmjjxo16//33Va5cOa1fv16SG9SrWbNmmjp1qjZv3qz27dsrMzNTs2bNUr169VSjRo2Y5StRooRefPFFJScn64UXXtBVV12lGTNmRH32tqjE88znTklZkkobY7IklZFUsDGxAQAAcNKbMGGCGjVqpKefflrPPvusKlasqPT0dI0dOzbPM4+SNHz4cCUlJempp57SM888o9TUVHXo0EHLli3TnDlzfIPPCRMmyBijRYsWafbs2Tp69KhGjRqltLQ0XXTRRZo3b55GjRqladOmqWTJkjkX6ZUrVy5Q8FmqVCktWLBAjz32mKZMmaInn3wyJ7/HH39cV199ddRlr7/++pwWLr8utyEjRoxQu3bt9MQTT+jdd9/V9u3blZSUpHr16mngwIH5Lnu8QgMcJSQkKCUlRXXq1NGgQYPUu3dv9ejRI09324EDB2rfvn1auXKlli5dqkOHDqlKlSrq2bOn7rvvvpxnJYtSQevNiBEjNHPmTK1Zs0azZ8+WtVZ169bV0KFDdf/99+e0aHbu3Fnffvutli9frkmTJunAgQMqX7682rVrp+HDh+uSSy6Ju4ylSpXSwoULdf/992vatGn65ZdfdMYZZ+jee+/VkCFD8qS/9tpr1axZM40fP17vvfeeZs+erRIlSqhOnTrq0qWLBg0alJO2RIkSOYHym2++qZUrV6pWrVr63e9+p5EjR6pp06ZxlTEhIUHPPfeckpOT9dRTT6lnz556/fXX84xIXJRMfi+izUlkzM2SHpP0X0nvWGvz9i0I07JlS1tU3QgAAFHk99J7vxfOFzQ98BsS74vXAZz66tWrJ0natGlTsZYjCPEe64wxH1lrWxY0/5jPfBpjGki6U1J9STUklTXGXOuT7mZjzBpjzJrQS2sBAAAAAJDiG3DoQkkfWGu3W2uzJM2UlKcDvLX2OWttS2tty8qVKxd2OQEAAAAAJ7F4gs9vJV1kjClj3ItsOnnTAAAAAACIS8wBh6y1HxpjZkj6TNJRSZ9IejroggEAAADAr82p+KxnUYlntFtZa0dJGhVwWQAAAAAAp6h4ut0CAAAAAHBCCD4BAAAAAIEj+AQAAIhDPO9GB4CTVVEc4+J65hMA8Cvxxh3R5/WYkPPnlFUZarVtX9Skq1dlSJIGta5TaEUDTmUlSpRQVlaWSpUqVdxFAYBAZGVlqUSJEoGug5ZPAACAGFJSUrRnz57iLgYABGbPnj1KSUkJdB0EnwAAADFUqFBBmZmZ+uWXX3T48GG64AI4JVhrdfjwYf3yyy/KzMxUhQoVAl0f3W4BAABiSEpKUp06dbRz505t2rRJR44cKe4iAUChKFGihFJSUlSnTh0lJSUFui6CTwAAgDgkJSWpevXqql69enEXBQBOSnS7BQAAAAAEjuATAAAAABA4gk8AAAAAQOB45hMATgJTvPdyxnp3J+/tBAAAv1a0fAIAAAAAAkfwCQAAAAAIHMEnAAAAACBwBJ8AAAAAgMARfAIAAAAAAsdotwAATVmVwUi6AAAgULR8AgAAAAACR/AJAAAAAAgcwScAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAgcwScAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAgcwScAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAgcwScAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAgcwScAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAgcwScAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAgcwScAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAgcwScAAAAAIHAEnwAAAACAwJUs7gIAAE5Sb9wRfV6PCUVXDgAAcFKg5RMAAAAAEDiCTwAAAABA4Ag+AQAAAACBI/gEAAAAAASO4BMAAAAAEDiCTwAAAABA4Ag+AQAAAACBI/gEAAAAAASO4BMAAAAAEDiCTwAAAABA4Ag+AQAAAACBI/gEAAAAAASO4BMAAAAAEDiCTwAAAABA4Ag+AQAAAACBI/gEAAAAAASO4BMAAAAAEDiCTwAAAABA4Ag+AQAAAACBI/gEAAAAAASO4BMAAAAAEDiCTwAAAABA4Ag+AQAAAACBI/gEAAAAAASO4BMAAAAAEDiCTwAAAABA4Ag+AQAAAACBI/gEAAAAAASuZHEXAABwcpmyKkOS1GrbvqhpVq/K0KDWdYqqSAAA4CRAyycAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAhcXAMOGWPKSXpe0lmSSkm60Vr7QZAFA4BT3ZRVGWr1xZio81c3HcWgPQAA4JQR72i3z0t63Vr7ijGmpKSyAZYJAAAAAHCKiRl8GmMqSmpure0nSdbabEm7gy4YAAAAAODUEc8zn2dK2m6MmW6MWWeM+Sc+2poAABBHSURBVJcxJiXoggEAAAAATh3xBJ8JklpJ+pu19hxJOyWNjExkjLnZGLPGGLNm+/bthVxMAAAAAMDJLJ7g8wdJm621q7z/Z0g6PzKRtfY5a21La23LypUrF2YZAQAAAAAnuZjBp7X2B0m/GGPO8iZ1krQ+0FIBAAAAAE4p8Y52+z+SXjHGlJGUIema4IoEAAAAADjVxBV8Wms/kdQy4LIAAAAAAE5R8TzzCQAAAADACSH4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABA4gk8AAAAAQOAIPgEAAAAAgSP4BAAAAAAEjuATAAAAABC4ksVdAADAqW3Kqoy40g1qXSfgkgAAgOJEyycAAAAAIHAEnwAAAACAwBF8AgAAAAACR/AJAAAAAAgcwScAAAAAIHCMdgsACFyrL8ZEnbe66agiLAkAACgutHwCAAAAAAJH8AkAAAAACBzBJwAAAAAgcASfAAAAAIDAEXwCAAAAAAJH8AkAAAAACBzBJwAAAAAgcASfAAAAAIDAEXwCAAAAAAJH8AkAAAAACBzBJwAAAAAgcASfAAAAAIDAEXwCAAAAAAJH8AkAAAAACBzBJwAAAAAgcASfAAAAAIDAEXwCAAAAAAJH8AkAAAAACFzJ4i4AAJwqpqzKiCvdoNZ1Ai4JAADArw8tnwAAAACAwBF8AsD/b+9uQzXPyzqAfy93FrH0VQ4ZO04bvShsMIgdhlBjtTdbmz0haFP7IqJVw7BXmVAN0yuDAguqZXPLYBm1VKIHbQ3DTNBxxtXW0a2lSGaXkF0L7AEsZa9enLPLNO7M+d9n57rPfc75fGBg7vP/nZmL4Zr7/n3P9X8AAGCc8AkAAMA413wC3EAnL5295rELJ86ssRIAgM1i8gkAAMA44RMAAIBxwicAAADjFofPqrqpqj5dVX8xWRAAAAAHzyqTzzcneXiqEAAAAA6uReGzqo4luTPJO2bLAQAA4CBaOvl8e5JfTPLkYC0AAAAcUDuGz6r6oSSPd/endlh3d1VdrKqLTzzxxA0rEAAAgP1vyeTzZUl+uKq+kOTdSV5VVfdfvai77+3u27r7tqNHj97gMgEAANjPdgyf3f3W7j7W3bcmeV2Sv+nunxqvDAAAgAPDcz4BAAAYd2SVxd39kSQfGakEAACAA8vkEwAAgHHCJwAAAOOETwAAAMYJnwAAAIwTPgEAABgnfAIAADBO+AQAAGCc8AkAAMA44RMAAIBxwicAAADjhE8AAADGCZ8AAACMEz4BAAAYJ3wCAAAwTvgEAABgnPAJAADAOOETAACAccInAAAA44RPAAAAxgmfAAAAjBM+AQAAGCd8AgAAME74BAAAYJzwCQAAwLgje10AADzl3PnLi9adPnV8uBIA4EYz+QQAAGCc8AkAAMA44RMAAIBxwicAAADjhE8AAADGCZ8AAACMEz4BAAAYJ3wCAAAwTvgEAABgnPAJAADAOOETAACAccInAAAA447sdQEAcLWTl85e89iFE2fWWAkAcKOYfAIAADBO+AQAAGCc8AkAAMA44RMAAIBxwicAAADjhE8AAADGCZ8AAACMEz4BAAAYJ3wCAAAwTvgEAABgnPAJAADAOOETAACAccInAAAA44RPAAAAxgmfAAAAjBM+AQAAGCd8AgAAME74BAAAYJzwCQAAwDjhEwAAgHHCJwAAAOOO7HUBAJvq3PnLi9adPnV8uBIAgP3P5BMAAIBxwicAAADjhE8AAADGCZ8AAACMEz4BAAAYJ3wCAAAwTvgEAABgnPAJAADAOOETAACAccInAAAA44RPAAAAxh3Z6wIANt3JS2eveezCiTNrrAQAYP8y+QQAAGCc8AkAAMA44RMAAIBxwicAAADjhE8AAADGCZ8AAACMEz4BAAAY5zmfAOxb585fXrTu9Knjw5UAADsx+QQAAGCc8AkAAMA44RMAAIBxwicAAADjdgyfVfXiqvpoVV2qqkeq6i3rKAwAAICDY8ndbr+a5E3d/VBVvSDJg1X1QHd/Zrg2AAAADogdJ5/d/cXufmj79/+Z5KEkt0wXBgAAwMGx0jWfVXVrkpNJPjZRDAAAAAfT4vBZVc9P8t4kv9DdX36G43dX1cWquvjEE0/cyBoBAADY5xaFz6q6Ocn7kryru9//TGu6+97uvq27bzt69OiNrBEAAIB9bsndbivJfUke7u7fnC8JAACAg2bJ5PNlSe5K8qqq+sz2rx8crgsAAIADZMdHrXT3x5LUGmoBAADggFrpbrcAAACwG8InAAAA44RPAAAAxgmfAAAAjBM+AQAAGCd8AgAAME74BAAAYJzwCQAAwLgje10AADwbJy+dveaxCyfOrLESAOB6TD4BAAAYJ3wCAAAwTvgEAABgnPAJAADAOOETAACAccInAAAA44RPAAAAxgmfAAAAjBM+AQAAGHdkrwsAWKdz5y8vWnf61PHhSgAADheTTwAAAMYJnwAAAIwTPgEAABgnfAIAADBO+AQAAGCc8AkAAMA4j1oB4NBY8qgdj9kBgBkmnwAAAIwTPgEAABgnfAIAADDONZ/AoXPy0tlrHrtw4swaKwEAODxMPgEAABgnfAIAADBO+AQAAGCc8AkAAMA44RMAAIBx7nYLwKHibscAsDdMPgEAABhn8gkAz+Dc+cuL1p0+dXy4EgA4GEw+AQAAGCd8AgAAME74BAAAYJzwCQAAwDjhEwAAgHHCJwAAAOOETwAAAMYJnwAAAIwTPgEAABgnfAIAADBO+AQAAGCc8AkAAMC4I3tdAMCzce785UXrTp86PlwJAADXY/IJAADAOOETAACAccInAAAA41zzCQDXcfLS2Wseu3DizNO/d/0xAFyfyScAAADjTD6BA2HpdAoAgL1h8gkAAMA44RMAAIBxwicAAADjhE8AAADGCZ8AAACMEz4BAAAYJ3wCAAAwTvgEAABgnPAJAADAuCN7XQAAHBQnL5295rELJ86ssRIA2DwmnwAAAIwTPgEAABgnfAIAADBO+AQAAGCcGw4BwB44d/7yjmtOnzq+hkoAYD2ET2DjnDt/ece7htqUAwDsL8InAOwRj2YB4DARPgFgwy05RTdxmi4Am80NhwAAABgnfAIAADDOabcAsE+4RhSA/Uz4BMa5Xg0AAKfdAgAAME74BAAAYJzTbgHggFnlVHenxQOwLsInABxAbk4EwKYRPoGVPTUp2Wlza1ICAMBTFoXPqrojyW8kuSnJH3X320arAtZu+tQ7Uxg4GM6dv7zo/7MfPgFwtR3DZ1U9N8k9SV6R5ItJPl5VH+ruB6eLAwDWY+oHREt+sPV1QfXP33ztxa/+rV3XAsDeWjL5PJXkc939aJJU1XuS3JlE+IQ1WnUyuZtJpukkMGHpe8vTp/Q//l/XXn/+8rN6n1sp2ArBADfUkvB5LMmjV7x+LMntI9Ww/2zAB/Oq1x9OblZ2U8uqp6+tEhCFSeCgmwy2O61Nsqv383V8Vqz8+TwZyif3CkO1rOXffNIm1QJXqO6+/oKq00m+r7vfsP36J5Lc3t2vv2rd3Unu3n75HUn+8caXuydemORLe10E+4Z+YRX6hVXoF1ahX1iFfmEVL0zyjd19dNVvXDL5fCzJi694fWz7a/9Pd9+b5N5VC9h0VXWxu2/b6zrYH/QLq9AvrEK/sAr9wir0C6vY7pdbd/O9z1mw5pNJTlTVsaq6Oclrk3xwN38ZAAAAh9OOk8/u/kpVvTHJA9kKq/d398XxygAAADgwFj3ns7s/kOQDw7VsqgN3KjGj9Aur0C+sQr+wCv3CKvQLq9h1v+x4wyEAAAB4tpZc8wkAAADPivCZpKruqKpLVfVwVf3SMxyvqvrtqvp8VX26qr5nL+pkcyzombuq6rPbaz5VVe4gd4jt1C9XrDtZVV+rqtessz42y5J+qarbq+pCVf19VX103TWyORZ8Hr2oqj68vYd5pKresBd1sveq6g+q6vGqunSN4/a7PG1Bv+xqr3vow2dVPTfJPUl+IMlLk7zmGf6z/XiSb03yXUl+JskfrrVINsrCnnkkycu7+0SSX07yjvVWyaZY2C+pqpuS/HqSD623QjbJkn6pqhcl+Z0kr+7u787WZxSH0ML3lzcludjdL0nysiRvq6rnrbdSNsQ7k9xxneP2u1zpnbl+v+xqr3vow2eSU0k+192PdvdXk7wnyZ1XrbkzW3f57e5+MMmRqnrx1X8Qh8aOPdPd57v7y9svP5bkljXXyOZY8h6TJD+f5H1JHl9ncWycJf3yuiR/3N1fTJLu9mD4w2tJvzyW5AVVVUmen+RLSf5nvWWyCbr7o0n+/TpL7Hd52k79stu9rvCZHEvy6BWvH9v+2qprODxW7YfXJ/mz0YrYZDv2S1XdkuTHkvzeGutiMy15f/nOJN9SVZ/YPuXpZ9dWHZtmSb/8fpKXJPnXJJ9N8ubufnI95bHP2O+yW4v3uosetQLsTlXdnq1TV16+x6Ww2d6e5C3d/eTWcAKu6znZOsXy+5M8L8knqurj3f2M1+Vw6L01yUNJXpnk25P8dVX9XXf/x96WBRwEq+51TT63fqpz5SkFx7a/tuoaDo9F/VBVL01yX5If6e5/W1NtbJ4l/XJbkndX1ReSvCbJ71bVj66nPDbMkn55NMkD3f3f26fc/m22wiiHz5J+eUWSP9k+lfKfkvxLtiahcDX7XVaym72u8Jl8MsmJqjpWVTcneW2SD1615gNJfjJJti/kf7K7Hw2H1Y49U1XHk7w/yV3d/cge1Mjm2LFfuvvbuvvW7r41yXuT/Fx3/+n6S2UDLPlM+sskL6+qI1X1DUm+N8k/rLlONsOSfvnnbE3JU1XfnK3g+YV1Fsm+Yb/LYrvd6x760267+ytV9cYkD2QrjN/f3RefuhV5d9+TrZuAvLKqPp/kf5P89J4VzJ5b2DO/muSbsjXBSpKvdbfHrRxCC/sFkizrl+5+sKr+KlunUt6c5L7tm4NwyCx8f/m1JPdX1cNJbkryK0/drIrDpareleT2JC+sqseSnMnWe4j9Ll9nQb/saq9b3T1VMwAAACRx2i0AAABrIHwCAAAwTvgEAABgnPAJAADAOOETAACAccInAAAA44RPAAAAxgmfAAAAjPs/l0wiLI2QfYQAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "a=[h_mc_over.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc_over.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n", - "\n", - "plt.title(\"Ds Own PV Vertex chisq/ndof Signal MC/ data over peak comparison\", fontsize=20)\n", - "plt.bar(b,a,width=0.014,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.01, alpha=0.6, label=\"data over Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "nbins=70\n", - "MC_Ds_DIRA_ownpv=MC_tuple_dict[\"Ds_DIRA_OWNPV\"]\n", - "data_under_Ds_DIRA_ownpv=data_tuple_bkg_under[\"Ds_DIRA_OWNPV\"]\n", - "data_over_Ds_DIRA_ownpv=data_tuple_bkg_over[\"Ds_DIRA_OWNPV\"]" - ] - }, - { - "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ - "if np.min(MC_Ds_DIRA_ownpv)0.4)\n", + "#\n", + "#data_PID_indices_plus=np.where(data_tuple_dict_presel_2[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]>0.4)\n", + "#data_PID_indices_minus=np.where(data_tuple_dict_presel_2[l_flv[l_index]+\"_minus_MC15TuneV1_ProbNN\"+l_flv[l_index]]>0.4)\n", + "#\n", + "#data_PID_indices = np.intersect1d(data_PID_indices_plus,data_PID_indices_minus)\n", + "#\n", + "#data_tuple_dict_presel_3={}\n", + "#MC_tuple_dict_presel_3={}\n", + "#\n", + "#for label in branches_needed: \n", + "#\n", + "# data_tuple_dict_presel_3[label] = data_tuple_dict_presel_2[label][data_PID_indices]\n", + "# MC_tuple_dict_presel_3[label] = MC_tuple_dict_presel_2[label]#[MC_PID_indices]\n", + "#\n" ] }, { @@ -683,8 +291,7 @@ "metadata": {}, "outputs": [], "source": [ - "min_DIRA_under=0.99980\n", - "min_DIRA_over=0.99980" + "#np.float(MC_tuple_dict_presel_1[\"Ds_ConsD_M\"].shape[0])/np.float(MC_tuple_dict[\"Ds_ConsD_M\"].shape[0])" ] }, { @@ -693,19 +300,12 @@ "metadata": {}, "outputs": [], "source": [ - "h_mc_under= r.TH1F(\"Ds DIRA own PV MC/data comparison below\", \"Ds DIRAown PV MC/data below Ds mass comparison\",nbins, min_DIRA_under, 1)\n", - "h_mc_over = r.TH1F(\"Ds DIRA own PV MC/data comparison over\", \"Ds DIRA own PV MC/data over Ds mass comparison\",nbins, min_DIRA_over, 1)\n", - "\n", - "for i in range(len(MC_Ds_DIRA_ownpv)):\n", - " h_mc_under.Fill(MC_Ds_DIRA_ownpv[i])\n", - " h_mc_over.Fill(MC_Ds_DIRA_ownpv[i])\n", - "\n", - "n1=h_mc_under.Integral(\"width\")\n", - "h_mc_under.Scale(1/n1)\n", - "h_mc_under.Integral(\"width\");\n", - "n2=h_mc_over.Integral(\"width\")\n", - "h_mc_over.Scale(1/n2)\n", - "h_mc_over.Integral(\"width\");" + "#plt.hist([data_tuple_dict[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"]))],alpha=0.2,bins=70,range=(1000,3000));\n", + "#plt.hist([data_tuple_dict_presel_1[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict_presel_1[\"Ds_ConsD_M\"]))],alpha=0.3,bins=70,range=(1000,3000));\n", + "##plt.hist([data_tuple_dict_presel_2[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict_presel_2[\"Ds_ConsD_M\"]))],alpha=0.4,bins=70,range=(1000,3000));\n", + "##plt.hist([data_tuple_dict_presel_3[\"Ds_ConsD_M\"][i][0] for i in range(len(data_tuple_dict_presel_3[\"Ds_ConsD_M\"]))],alpha=0.6,bins=70,range=(1000,3000));\n", + "#fig=plt.gcf()\n", + "#fig.set_size_inches(16,10)" ] }, { @@ -714,95 +314,78 @@ "metadata": {}, "outputs": [], "source": [ - "h_data_under= r.TH1F(\"data below signal_2\", \"data below signal_2\",nbins, min_DIRA_under, 1)\n", - "h_data_over= r.TH1F(\"data over signal_2\", \"data over signal_2\",nbins, min_DIRA_over, 1)\n", - "for i in range(len(data_under_Ds_DIRA_ownpv)):\n", - " h_data_under.Fill(data_under_Ds_DIRA_ownpv[i])\n", - "for i in range(len(data_over_Ds_DIRA_ownpv)):\n", - " h_data_over.Fill(data_over_Ds_DIRA_ownpv[i])\n", - " \n", - "n2=h_data_under.Integral(\"width\")\n", - "h_data_under.Scale(1/n2)\n", - "h_data_under.Integral(\"width\");\n", - "n3=h_data_over.Integral(\"width\")\n", - "h_data_over.Scale(1/n3)\n", - "h_data_over.Integral(\"width\");" + "#data_tuple_dict=data_tuple_dict_presel_1\n", + "#MC_tuple_dict=MC_tuple_dict_presel_1" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA7UAAAHnCAYAAABngHrgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3XmczvX+//HHC2MGzTAkZC1SaUGkssURUsJoSlQndUqdTvveKVnSdlQH6ed06qCV+iqhQiE7FVERLUpSRBFK9vfvj/fnGtdcc10z14zRuMzzfru5Xeazvj/75/V5b+acQ0RERERERCQRlSjqBIiIiIiIiIgUlIJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqRUQOAjNba2Zf52P6embmzOy5g5muomJmc81sTyEt61oz+9zMdgX77PHCWG7EOgotvQebmV0d7IfLijotRSGRjtWhwswGBedMy6JOy6GkuF9LRcXMSgX7fVpRp0USl4JaOSDBTSj83x4z22xmn5rZKDPramYl/4R01Dezp81spZn9Zma/m9kXZvb/zOz4g73+wmBmo6Psz9/NbJmZPWpm6cF07YNxH8axzF7BtBNymaZQl3eg9FJRNMzs3mC/NyzqtOTGzDoC/wEMeBwYALwbx3zVzWyoma0ws+1mttvMfgoCosfN7NiDnPRDRtg15sxsRi7T1TOzfaF7ey7TNTCz4cG9akvwseFHM5tkZleaWXKM+Y4Olv/vwtiuA5XfD1EiInLoKFXUCZDDxoDgtyRQATgJ6AX0Bj41s4ucc18ejBWb2U3Ak/iPNLOAtwAHNAGuA/qY2W3OuWEHY/0HwQRgafD/ikAX4G4g08yaAdOAb4HTzewU59xnuSzrmuD3v7lMU9jLk4L5DjgR+LWI1p8BfOOc+6SI1h+v84PfXs65JfHMEATq7wPpwEfAM8DvQBXgDOB2YBnwTdhsvYAyhZTmQ9UeoI2Z1XXOrYoy/mr8x4M9wW82ZmZAf6BvMH4+MAP4Db9vWwMjgWuBM6Msv1sw3xsHuiEikricc3vM7ET8fVmkQBTUSqFwzvWPHGZmVYCngIuAaWbW1Dm3oTDXa2Z/BYYCm4AM59zsiPGtgDeBoWa22Tn3YmGu/yB50zk3OvSHmd0DzAUaAzc65wYERVQfwgeZN0VbiJnVA84Gvgcmx1qZc84V5vKkYJxzu4GVRbFuM6sBNMV/HDrUpQe/G/Mxz9Bgvtudczm2MTi3s5Uocc6tKXAKE8db+MDyauDe8BFmloT/KLkAOBY4Msr8fYEH8B9kLnLOfRQ5gZmdB9wWY/0ZwAZgXsGSLyKHC+dckTz/5PCh4sdy0DjnfgIuAWYCNYF/ho8Pira9HBRT2x0UtV0RFFuulNfyzSwVGBL82SsyoA3SMAe4NPhzSDAPZnZ8UKTu5YhlHhNWLK9VxLjHguF/CRu2OvhXzswGm9kaM9tpZl+b2d1BTsYBcc5tB54P/mwW/I7E555cZmYpMWYN5bL8zzm3L4/VHNDyzOwsM3s9KM65y8y+N7P/mFm1yIUExT33mFmymfU3sy+Dffacmc0Fng0mfdGyF8WuEbaMUmZ2g5l9YGbbguKkH5vZ9eH73Ly3gvmvj5KWR4Jxz+Sxf8LnqWlmT5nZV2a2IzhvF5vZgBjTlzOzJ8LOja/M7I7Ic8Ni1Kk1s2pm9kww/24z+yNYxhgzOyZi2mQz62dm3wRp+8bMBppZWcu9vlIox2x82LJCxynJzO4PzumdQToeCYKeaNt7aXAsdpjZBjN73syq5rI/SwTHbVGwL383sw/N15sNP5ZXm5kDQsXSv492bsRwVvA7PNpI59zXzrkvItIVtZ6mmaUE+/TbsH38kJkdEW0fW1jdRTPrYWYfBefrL2b2SoxrpJmZ/dfMlgfT7giuk8FmViGPbc2PT/A5173NLPIj9wX43NZnc8zl01gXH9TuBDpFC2gBnHPvsD93PXz+dKANMDGO+1NonrjPreBauMPM3jN/X9ptZpuCvztGTHtOcG5VB+pa9vvOc2HTXWxm48zsO/P3ud+C8/YGM4v7fcpyqWJhMeoWFuQ8CuY73cymmr9Pbgm2/4w80tfAzF4wXxx7l5mtN/+sPi7KtC8F6aplZjeb2Wfm71F51o0Mlv+1mVUwX1Xox+DYLjezf4Rf/xHz5ed5UyjXkplVMrN55ovL35mP+Xqa2Yzg3NsdbOM4M2saMV2Kmf3TfBH+P8xsq5nNNrPMKMvMelaY2YnBvvgl2Lb3LahCYr7KxYvBuJ3m76tnR1le+Ll1pZktDdLwU7COKlHmydd+DT/nzew8M5sVnI+7g/GxzvvywTJDz5+d5t+5xpvZaVHWc4mZzQn23x/mq8LdbWalo0wbOv/iekbLoU85tXJQOef2mdkg/MtLTzO7NcgZrAZ8AKQCE4Ev8OfjcUBX4AnglzwWn4nPffnQOTc1lzRMMbOPgNODeUY5574wsx+Av0RM3i7i/3Mi/t6BL2IXLgmYClQGXgf2ARcCjwIp7C+afSBCN1cH4Jxbb2ahXJYLgcjgvBRwBbAXH7Dm6kCWZ2bX4Os4bsHniq8D6gJXAZ3N7Azn3A9RVjseOBlf3Po34Ef8vt2Ef6EeD3waNv3WYH2lgbeBc4LxzwK78cfnafxxvjLYLmdmvfHFuZ8ws7nOuU+D5XTAF+v+DLg5r30UzHMGPpc6Hf+x5g38x8GGwB1Av4hZSuOLd1cAxgXDMoHBQDI+dzy39ZXD52LVCdYbOi7H4M/d4/FFx0NFQV/HBxBf4QO4ZKBPkL7cdAfW43PlIo3F79MJwB9AZ+AefM7dNeETBi97/wI2A6Px50SnYBu2R9k+A8YAF+Nz+0IBVAb+nGoB/DUY9jH+WuoOnAL8m+CcCPuNZSf+WNQDPs9j2pjMBy7jgXOBL/H7uDQ+RzOvfXwTcB7+PHgXX+y5J9DQzBo753aFTdsHaI+//0zA5yI3xZ9j55rZmc65wiqm9yy+OkFn/PUbcg1+v74GPBJlvqvw9+yxzrkVua3AObczyuALgvnHRxmXQ37PLfz9+KFg/Fj8tlTFV+eYbGZXhZWI+QZ/bt2G/7gXXlXl47D/P4S/V03BlxRIxd93nsJXd7kynm05QHGfR+Y/zL6Lf0a9DqzCl/iZhb9/5WBm5wfL3oc/974FjsaXuDrfzM6OUUXhafzHo9fxz/TdcW5PMr7I+hHAK8HfF+GvrfpE3JsL8Lw54GvJzOrgj/kxwKXOuTF5bVRwb3sR/1F9I/5ZsR5/DrbD30MWBdMmA+8BLfH3p+FAuWA//J+ZPeiceyDKao7DPzNDVSrq4O+lM8ysHf44/IC/xo8M0jLFzBpFfsQL3InfV6/inzetgb8Bbc2smXMu/J2soPu1B9ABf+yeAmpH34NZ+3Aq/hyfhd+Hu/GZJGfjP/J/HDb9v4Jt2Ai8hC/KfD7+XayDmZ0blIgKd0DPaDnEOOf0T/8K/A8fZLk8pknG34gccEww7Mbg72ujTJ8CpMSx7v8Fy3gojmkfCqZ9LmzYC8Gwk8KGjcHfEJcAc8KGp+MDuukRy10dLON1oFTY8Er4YnW/Aklx7svRwbJ6RwwvG6THAX3DhncKhs2MsqyMYNxb+TiW+V4evg7oLnyOT+WIca2C4/5/EcPnBsv6ADgiyrquDsZfFiOdg0LHHbCw4QaMCMadHyUte4AV+JeFasBP+BfUE+LcP8nAmuA8yIwyvmrE32uDtLwWcW5UBn7GB+8lw4bXi3KOhvb7g1HWVyp8/+GDP4d/WU0OG34k8HUwblqU5VQK9s1/YhynOUC5sOFl8MWk94Qfc/yL5e5gv9YKG14Sf304YE/EOi4Phi+MWMcR+Bc1B1wcMc9LwfAa+Ti3nw3mWYfPXWwFpOYxz9wo6b0yWM57QOmw4enBPsmxj8PO1w1A3YhxzwfjukcMj7pt+A9LDl+MOu5rJpdrrH+wr7cBb4eNrxWc5yOCv9dH2ReziHK/yscxGY8PTErHMW1Bzq0UIu5JwfA0/P1qY/h1EnbNfp1LOmpGGWb4D30OaJLP/Z/jeOGv6wM+j/Af277CB6edIqa/JZjeAS3DhlfCP7O+j7KOE4JxH0UMD12P3wBV8nkOhO6RMyKup/B7VvOw4QV53hzQtQSchr9v/Aq0zce2Xc/++2dalHOmStjffYNp3yT7s6Iq/h1jH3BG2PDQs8IB10cs+55g+DbgXxHjLgnGDYtxbv0ONIwYNyQY90wh7dddQIt4znv8BxgHvBjjuisfcfwd/sPNURHLnRSMuyvG+RfXM1r/Dv1/Kn4sB53zX+lDX/gqB7+h1jBdlOl3OOd2xLHoUFGj7+OYNjTN0WHDpge/4bmzf8E/YKcBZwQ5ZQBt8S8J04nuFudcVlFF579oTgDK43PT8qOb+WK5/c1sCLAcaIS/WYcXn5yKz90623IWC7s6+M1Pg04FWd71+FyAm5xz2eo4Ol/0e0KwPeXI6Z/Oud/ykT7Mt6T9D/wLVF8XPIGC9Tn8A30v+4uch6elP/7F7P/hX8SOAm5w8dfj6Yb/Qvyyc25c5Ejn3Poo8zjg5ohzYyP+IZuO/9Kem9yukz0R+y+US3SHC8sZc879jK/3GMsF+OAgVo7ZnS7si7tz7g/8x5+S+NypkMvwLxCDXVh9VOfcXnxuS7QiplcFv7dErOM3fONNsP/cOxA34wOPysBAYDawxXx1hyeDnJh4XBH83unCcsScc5vJfR8DPOlyNsYUKvXQLHygc25ttAU4557Hv1x3jDa+IIJ9PRafu1IzGPw3/P0uatHjQOj+GzWtuTGzsvhteMdlz6GOJd/nVvAcyVHv2jm3FRiFD5yaRI7PjXMux7MmuO+EcnYL7bjkIt7zqBU++HnHORfZBsJQfEmDSL3xz6z7I9cR3CefA5qaWf0o8z7kfJWjgrgt4noKv2eF537n+3lzINeS+WLqs/DPlFbOuffzsU2hD/e9g3MufN0uYl9dhT+H/xHxrFiP3w+GvyYjrXTO/b+IYaHSPHvxwXK4cfigshnRPety5sLfi//4dJmFVTk5gP36qnMu3jr0uT3/nHNuS9ig0LPkPhfWdkuwP28IlhHtWXKgz2g5hKj4sfxZQsVnQ+fcm/jiXsPN7Bx8EakFwOfhgcpBFurKoh0wzMxOxgc60/FB8B344jeT2V9MOVr3F+ujvezgv+7C/oZt4tU1+Ae+uOdqfFGYR4OXZyCraPf/8C/pV+OL0oYa/TkXX5z37XhXWsDlheoqdjCztlEWWxV/zOvhv66HWxhv2sKciC8m9CPwQIwqLzuC6SI9jC8GHyrO+qILa5ArDqHWW9/Jxzw/OOfWRRke77nxHv6L8X1B/aHJ+OtkqctZD/E0fM7z4ijLmZnLOjLwLy2xunZZFGVYtPSH6jfNipzYObfWzFbhGxwKdxo+d+CDKOuYhy823DhGuuLmfL30v5nZffhzuVmw3CbArcC1Znahc25KHotqDGxzzi2NMm5OlGHhotU5jXoeBC+Pf8cX1WuAz10M/whdPY915dez+Gv+qqC6yFXAx865j3OfrcA64nP84yp6TMHOLczsFHxxxJb4D5qRXQvlaz+a2ZHB8s7DF0WN/FhX2MclmnjPo9z2mTOzWfjiveFC9/NmFlFfP3BC8HsiOYPigtzPAbbEuJ5mBr/h13++nzcHcC31wN8rVuJzuuP+eGNm5fH76osoHyAip03HFxv+3EWvphP6kB7tPhjtXh8Klj9zEcX+nW9h+BdiP3einSt/mO/urz3+A/2yIN0F3a/5OU8W48+zy82sFj7QnA8scjmLEYfO9xwZD86574J7xHFmdkTEx+ADfUbLIURBrRx05hseqhj8+RP4hlnMrAX+K+R5+Loj4Bt/edzF1/1OKGesZq5TZZ/mx9AA59z3ZvYVPmeyJPtzbKcHyw7V05wc/G4l+gtFtPpisD/3IL/99F6Zj2BrJL4e5xVmdn9wo78K/3AZGeRk5Ed+lxdq0Ouf5O6IiL/3uoLVCQytrwE566/mtr5Q0D6e/cd5SOQ0eQg1fvFzPuY5oHPDOfeLmZ2F39bO7G9wZ6OZPY3PHdkT1D1KA9bG+Ci0KdrygxyNDsAbUV4SwB+naP2TRkt/+dzWFQzPCjzySrNzbq+Z/cr+Y37AgpyP0cE/zKwivujd34FRZlYzxvZmS2+MxW+OMTwk2rkQ6zx4HZ+Dvgof+P0UNv9t5AzODohz7kMz+xSfK7YEqEHedcnW4XMxChLIdcdvT7wfiPJ1bgEEz5dp7C9hMwFfJHMf/gX4AvKxH4NzZRG+DuAH+Oorm/DF8Cvic+YK9bjEEO95FM8+ixS61nI0qhchx/0V/2GsIGJdN6H0lQ8bVpDnTUGvpeb4d+QF+Hqp+ZGfZ0VexylUyi1ao1bRSrSFzoXcnj2xnjt5nSvhx6Kg+zXu88Q5t9vMWuOffxfi69ECbDWz0fhc2VCAGs9+rBdMFx7UFvb7mxQhBbXyZ2iJP9c2ETRqAxB8ne0eNELUEN/wz4347nf2OeeitlQaZi7+Jewc4L48pj0n+I0s9jID34fi6fhg57vQl9Xg6+Q5ZnY0/qvrWwUIEg8q59wPZvYO/uFygZm9yf6iTM/lOnPhLC/0gCoX5IYdbKH1/Z9z7uL8zGhmJwCP4c/DdOB/QWMWsR5qkUL9x0br2uSgcc59jf9SXQIfzP8FX5yqPz63654g52UrUMHMLEqQWJHoOuHrHhZGP6GhY1MR/6ITKVsa8kpz8KGpPAV/Wc6Tc26Tmf0Dvx/q4PfvpzGmdWa2jewvduEKpVViMzuT/Q2lZUbmyJtZrO5xDtR/8dUbnsbnnr+c++TMxZdkacf+1tnzFOTwdAbec/FXP8jXuRXoi28EpplzLluOVrAPL4hz3SF98AHtbc65f0cs7zT8syteoWMarahJrNbn8yt8n0UTbXhonpOccwVuUC2fYuWEhdIXfv3n63lzgNfSXfhSLNcAJcysT5TSMbHk51kR73E6aPfBKOvKNQ1/5j0qKKZ9PXB9UC2qDf6d7SZ86+yXhKctSGu07t7+zP0oRUR1auWgCl7EQwHnmGgPBefrBi52zj2Gb8URfAuVeRmHf3g0M7P2uaShPb644Sb2t24XEiqq0hH/gjY9Ytyp+OI1ELs+bVEL1XO9Gl9EqDbwrnPuuz9heaGiRK2ijCuo0IeDaC98y/G5LWdZzi5IYgpKC7yKDwIvwrei2gjfyna8QtvaKR/zFBrn3D7n3LKgFEOovlL4dfIxPociWj3BNjEWm4H/2p9Xsdt4hIqqnh05IijCXjfKPEvwaT49yriz8C/4B6sILJBVJ3Jb8GdeXTgsAVLNrFGUca0LKUmhIqFvRXlZbIJvcfdgeBlf3aEGvt7btjymD3UDdnHwwSimoHXXkDb4DwDxFj2Ggp1b9fFFC6MV0YxWdBX8vSfWORA6LhPysbxYQrmTR0cZF+1aKIjc9plFG87BuZ/npXyM66lN8LskbFh+03cg19JOfImCN/D1WZ8PPrTlKajruRKob77rq9ym3Yxvy+J4i94tU6jq00G9DwainStl8O9P2/G9VEAR3aOcc185554N0vkH2Z9/ofMkx7UYFF2uB3yVjw9pkoAU1MpBY2ZH4RsgaYMvqjYwbFyToN5JpNCwvIryhRr8CDUm80pQ3CwyDc3x3QQA3BrlRe19ghYEg3WHB64z8C8494T9fSiajC8S2ZH9jWvk1sBLYS7vKfyL7dCwRmaymO+DNNc+EaMIFbfKUawxKCI7HP/i/WS0lwwzq2hmkY1z/Rv/geIR59wM4H78C9I/zKx7nOl6E1/X+jIzuzDKemP2xVpQZnZycB1FinadjAp+Hw8PIoJ6gAOJEOSYnY//YFEY3cO8hD8X7gxeIkLrKYlvmCba8ybUwM0TwctTaJ5y7P/g8L8DTZiZDTCz2jHGdcF3LfULeXf380LwO9jCGk0J6sXl2McFFKpW0SZ8YHC/HFFI68jBORdq3CWD3Iv2h6ZfBTyIL2b4jkXpMxKyuogJr4ufgQ8eJ+YjeQU5t9YDR1tEo0Zm1gufUxzNL8BRMT6YxTouJ5F3SaFIi/DPnV4R12oqvvuRwjAHn6t9nplFfoi7mZz1acFfa1uBgebbmMghqA5R2J6wsH5EI+5Zo8Kmy+/z5oCuJecbr+qBbxjvMvx7RrwfU4fh3x9GmVlaxPot4r4+El/MdaiF9XccTDMwbJqD7RoL+rgN8wj+efNyWBWVP+UeZWbHWvRG/FLx13z48y+0fx40s6wqK8HxCh2LA36WyKFNxY+lUJhZ/+C/JfBf4U/CFzsujW+w4eLwFunwXXlca76xiuX4r4DHsr+uVVz1HZ1zI8139P0vYI6ZzcQ3LuDwOVZt8UW9bnHOvRBl/p+DumShG3l44LogSNdR+OIsn8WTpj9bUPdwJD4AbY5/4OTnhbHAy3POLTezq/FB70ozexvfjUQp/PFsjd93UV+QYpiPzz28K3ioh+rIDA0+SvTDB6g34vtNnIp/GS2P77+0Bb7O1RcA5juvvy5Ybv8g3XvMrCf+6+7/zGxxXjnbzrmdZnYRPldznJm9D3yIP+dPxn89jtbK84E4F3jEzObir6Ot+IC+O/68Hhw27Yv4PgrPBz4zs4n4gCMzSGdkjkE7/D7LT45ZTM65VeYbYnoMWGpmr7G/L9Fy+AZGIhvwehH/tf1CYLn54u6GD3xqA684514thOTdDvQ1syX4gGIjPhe4Kf647QH6xKhXHG4U/iW3PX4fT8Lf4zLx59LxRG/lOT9m4PfV5cGL+3x80bkMfDcnBW1hNk/OtyCbHw/iX8b7AovMbD5+//6OLxp4Nj6HZCFk5RB2A+Y638JtvOkqyLk1DB+MLDCzV/Glepric74msL8xvnDT8Q3yTA6uub3AEufc2/gX4huBZ4LSP6vwjUVdiA/a4/04FmrPYSy+ZNKi4L5ZDn+M5xG7ddq4BW0IXIVvhHGSmY3DtxrfGP9cnEpEC7XOuY3BPe514OPg3rosGF0L/0yvRPQ6tQW1Fl8EeVnEPasqvuuZrH7hC/C8OeBrKXhWXIZ/Jl0JJJvZxS7vVrv/g99fvYCvgm37Cf8+0Q5/LxkUTPsY/l5/EXCimU1mfz+1lYGHnXMFbYgrP6YB84Praz1+fzbHnzfh9Zj/rHvUacBrZvYB/r1uM35/dMOfJ4+FJnTOzTazJ/H1eZcH5/t2/POwAb4RrCcLKV1yqHKHQL9C+pe4/9jfV1ro3178y8On+Jt2V6BElPnOxNfRXIZ/AdqDb8TpVaBRAdJxAv4L4Rf4G9l2fKt5I8ijH1J8jpADlkcZNzUY92qMeVcDq2OM6x/M2ybObRjN/i4A8rv9NYN97/APwAM9rvlaHv6jwPP4YlS72F9UaRRwTsS0Ofr/jLK88/Avwr+FnVs1wsaXwHevMoP9jbVswj9cBxL0J4l/6fw1GFcrynq6B8teQPz9CdfGv7CsDrb1N/yL/AMR08Xs85L9/QKG9xEZrZ/ak/A500vwAe0efD+VE4HWUZabHJx33+I/Dn0b7I+y5OwD8Bl8Y2gVY6Qx5nEi9342Lw3SuyNI6wv47l+iLg8fFN2Af2kJXbuL8I03Rbt3FKSf2nb43PoF+A8ge/D3nZX44vYnx7v9+CLsg4LjH9rHD+FfVh0wLq9jndsxD4ZXCfbbz8E6vsbnmJSLdl7ldjzyOH7945w+Rz+1EeMb4OviLg/O01340jnv4Ovklw6mOytY703xHrsDPLd6AUuD9GzG38/bxNpf+GDtGXzDQHsijw0+KH4vOHd+D87TPrGOYx7bkoJ/9qwNjvGX+HqcyURcqwU9j4Jxp+MD29+CY/MecEYeyzsW3/XZ18G+3oEP4scS0Uc3Bbgew+ZdG6yjAv5Z/WOwLz7H3xMsxnz5ed4UyrVE9n7Q3wFS4tg+w7e2Pxv/EWZPsM7/A06Lcl+5H38N7cBXiZhDRD/dcRzvqP0cR+7zWOcW/nr9BF+8dwP+Y06O/ocLa7/mlm78h5TH8e8Cm/HvJJvwwXe3XO4R84L9twP/jnkvEX1Sx9oX8Vxv+nfo/rPg4ImIyGEqKIK1G5junDsnKOL2I/5DTrvc55Z4mNlf8Dl9g5xzkf1DCmBm/8J3iVPbhfU3K8WTma0Fdjjn6hV1Wooz89143Yfvi3duUadHpKBUp1ZEpPg5C/+lvVCKHhcnZlYlyrA09neBo30aWwawWAGtiIgUNtWpFREpZpxz88i7pV+Jbrj5riXm4YvEVcF3b1EFeNo592e0UpqQnHPHFXUaRETk8KSgVkREJH4T8K2l9wLS8HUrlwH/dM79GS2UioiISATVqRUREREREZGEpTq1IiIiIiIikrAStvjxkUce6erUqVPUyRAREREREZGDYPHixT875yrnNV3CBrV16tRh0aJFRZ0MEREREREROQjM7Lt4plPxYxEREREREUlYCmpFREREREQkYSmoFRERERERkYSloFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBJWqaJOwJ9h586dbNq0iW3btrF3796iTo6ISJErWbIkqampVKxYkeTk5KJOjoiIiEiBHfZB7c6dO1mzZg3p6enUqVOHpKQkzKyokyUiUmScc+zevZutW7eyZs0aatWqpcBWREREEtZhX/x406ZNpKenc+SRR1K6dGkFtCJS7JkZpUuX5sgjjyQ9PZ1NmzYVdZJERERECuywD2q3bdtGWlpaUSdDROSQlJaWxrZt24o6GSIiIiIFdtgHtXv37iUpKamokyEickhKSkpSWwMiIiKS0A77oBZQkWMRkRh0fxQREZFEVyyCWhERERERETk8KagVERERERGRhKWgVqIaPXo0Zsbo0aOLOilxMTPatGlT1MkQEREREZE/2WHfT21e7n3js6JOQq4e6X5KoSxn7969jBw5kpdeeonPPvuMrVu3UrZsWWrWrEnjxo258MILycjIKJR1JYJQPUIz46uvvqJu3bpRp2vbti0zZ84EYNSoUfTu3TvHNL///jvPPvssEydOZNmyZfz666+ULVuW+vXr0759e/72t79x7LFhdqKRAAAgAElEQVTHHqxNEREREREp1op9UFsc7N27l86dOzNlyhQqV65M165dqV69Otu3b2f58uW88cYbrF69OltQm5GRwZlnnkm1atWKMOUHV6lSpdizZw//+9//ePjhh3OM/+qrr5g5c2bWdNEsXLiQzMxMfvjhB2rUqMF5553H0Ucfzfbt21m6dCmDBw9m8ODBLFy4kNNOO+1gb5KIiIiISLGjoLYYGDNmDFOmTKFZs2ZMmzaN1NTUbOO3b9/OBx98kG1Y+fLlKV++/J+ZzD9dlSpVqFatGqNGjWLgwIGUKpX9cnjuuecAuOCCCxg/fnyO+VeuXEnHjh357bffePTRR7n99ttzLGPNmjXcddddbN269eBtiIiIiIhILiJLpxZWadBDherUFgPz588HoHfv3jkCWoCyZcvStm3bbMNyq1M7depUWrRoQbly5ahYsSLdunVj2bJl9O7dGzNj9erVWdOuXr0aM6N3796sXr2aSy65hCOPPJKUlBSaNm3KW2+9lWP5W7ZsYdCgQZx99tlUqlSJUqVKUblyZbp06cKCBQsObGdEuOaaa1i/fn2OdOzevZvRo0fTvHlzGjRoEHXeG2+8ka1bt3L33Xdz99135whoAWrVqsXYsWM566yzCjXdIiIiIiLiKagtBlJSUgBfnPZAjR07lk6dOrFkyRIuuugirr32WjZv3kzLli1ZtWpVzPm+++47mjVrxrp167jmmmv461//ysqVK+natSvvv/9+tmlXrFjBww8/TJkyZbjiiiu45557OO+885g9ezatW7dmypQpB7wdIT179qRcuXJZubIhEydOZMOGDVxzzTVR5/v222+ZNm0aKSkp3HXXXXmuJzk5uVDSKyIiIiIi2an4cTFw0UUXMWTIEIYMGcLGjRvJyMigSZMm1K5dO1/L2bZtG3//+99JSUlhwYIFNGzYMGvcfffdF7VeasjMmTN54oknuO2227KGXX755bRu3ZrBgwdnyylu0KAB69evJy0tLdsy1q9fz+mnn86tt97Kueeem6+0x5Kamsoll1zC6NGjWbt2LTVq1ADg2WefJS0tjYsvvjjqds2dOxeAJk2aUKFChUJJi4iIiIiI5J9yaouBs846i1deeYUqVarw0ksvceGFF1KnTh0qVapERkYGkyZNims5EyZM4Ndff+Wqq67KFtAC9OvXj0qVKsWct169etkCWoBWrVpRr149Pvzww2zD09LScgS0AFWrVqVHjx6sXLmSNWvWxJXmeFxzzTVZrUODz1V+7733uPTSSylbtmzUedatWweQFQSLiIiIiEjRUFBbTFxyySWsWbOGqVOn0rdvXzp37kzJkiV588036dKlC1dccQXOuVyXsWTJEsAHo5FKly7NGWecEXPepk2bRh1erVo1Nm/enGP4vHnzuPjii6lZsybJycmYGWbGE088AcAPP/yQa1rz44wzzuCUU05h5MiR7Nu3j+eee459+/bFLHosIiIiIiKHDhU/LkaSkpLo0KEDHTp0AGDfvn1MmDCBK6+8khdeeIGMjAy6desWc/4tW7YAxCxum56eHnPeWHVKS5Qowb59+7INGz9+PJmZmaSkpNC+fXvq1q1LuXLlKFGiBDNnzmTWrFns3Lkz123Nr2uuuYabbrqJyZMnM2rUKJo0aULjxo1jTh/q6qgwg2sREREREck/BbXFWIkSJcjIyGD58uX07duXGTNm5BrUhooE//rrr1HHxxqeX3379qVMmTJ89tlnHHPMMdnG3XbbbcyaNatQ1hPu8ssv5+677+a6667jhx9+4IEHHsh1+pYtWwKwaNEitmzZcth3fyQiIiIicqhS8WPJClbzKn4cyrmcM2dOjnG7du1i4cKFhZKeL7/8klNPPTVHQAvkaCm5sFSoUIHMzEzWrl1LuXLl6NmzZ67TH3PMMZxzzjns2LGDwYMH57n8ws5ZFhERERERT0FtMTBmzBjee++9HMV8AX7++WeeeeYZAFq3bp3rcrp27Ur58uUZOXIkn3zySbZxAwYM4JdffimU9FatWpXPP/+cDRs2ZBs+ePBgli5dWijriGbQoEGMHz+eqVOnRu3PN9KwYcNIS0vjkUce4YknnmDPnj05plmzZg09evQo9P51RURERETEU/HjYuCDDz5g6NChVK1alZYtW3LMMceQlJTEt99+yzvvvMOWLVvo2rUrmZmZuS4nLS2Np59+mssvv5zmzZtz8cUXU61aNebPn8/SpUtp2bIlc+fOpUSJA/tWcvPNN3PHHXfQuHFjMjMzKVOmDHPmzGHJkiV06tSJyZMnH9DyY6lVqxa1atWKe/oTTzyRqVOnkpmZyR133MHQoUNp164dRx99NL///juffPIJ8+bNw8y45557DkqaRURERESKOwW1xcBtt91GzZo1mTlzJh999BETJ07EOUelSpVo3rw5vXr1olevXphZnsu69NJLqVixIg8++CCvvvoqycnJtG7dmrlz5zJw4ECAqN3x5Mftt99OcnIyw4cPZ8SIEaSlpdGqVSvmzp3LxIkTD1pQWxBnnnkmK1eu5Nlnn2XixIm8/fbbbN68mbJly1KvXj1uv/12+vTpE7UotYiIiIiIHDjLqx7loapp06Zu0aJFeU63YsUKTjzxxD8hRcWbc4569eqxffv2rD5cRSQx6D4pIiJyeLv3jc+y/f1I91OKKCX5Y2aLnXPR+wYNozq1ki9btmyJ2ujRkCFD+Oabb8jIyCiCVImIiIiISHGl4seSLwsWLOCyyy6jffv2HHvssezcuZN58+axcOFCatasSf/+/Ys6iSIiIiIiUowoqJV8Of7442nTpg1z587l9ddfx8yoUaMGN910E//85z856qijijqJIiIiIiJSjCiolXw55phjGDduXFEnQ0REREREBFCdWhEREREREUlgCmpFREREREQkYSmoFRERERERkYSloFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqhTp16lCnTp2iTkZC6d27N2bG6tWrizopUkzNnDkTM6N///5FnRQRERGRIlWqqBNQ5BaNKuoU5K7plUWdgriZGWeffTYzZ84s6qQUC3Xq1OG7777L+rtEiRKUK1eO6tWr06hRIzp37kxmZibJyclFmEoRERERkYNLQa1Igrv55pupUKEC+/btY+vWrXzxxRdMmjSJsWPHct999zF27FjOPPPMok6miIiIiMhBoaBWJMHdcsstOYqPb9myhb59+/LUU09x7rnnsnDhQk444YSiSaCIiIiIyEGkOrXFhHOO4cOHc9JJJ5GSkkL16tW54YYb2LJlS9Tpt2zZwqBBgzj77LOpVKkSpUqVonLlynTp0oUFCxZkm3b06NGYGQCzZs3CzLL+hdf3++9//8sFF1xAjRo1SEpKIi0tjRYtWvDSSy/la1v69++PmUUt5rx69WrMjN69e2cbHl4H9plnnuGUU04hJSWFKlWq0KdPn5j7Ydq0abRq1Ypy5cpRsWJFunXrxsqVK3NN3wcffEBmZiZVq1aldOnS1KxZk2uvvZYff/wxx7Rt2rTBzNi1axcDBw7k+OOPJzk5OUf686t8+fIMGzaMv/71r2zZsoV77rkn2/j169fz97//ndq1a1O6dGlSUlKoV68el1xyCatWrYprHaG62Fu2bOGWW26hZs2alC5dmgYNGvDqq68CsHPnTh544AHq1KlDUlISdevWZfjw4TmWtWvXLp544gk6dOhAlSpVSEpKomLFipxzzjlMnjw56voXL15Mt27dOOqooyhVqhSpqak0bNiQ66+/nt27d2dNt3XrVu6++26OO+44kpOTSU5Opnbt2nTr1o1FixbFta2h47Rz507uv/9+jjnmGJKTk6lbty4DBgxg165dUedbuXIlvXv3zto3VapUoVevXnzxxRc5pv3iiy+45ZZbaNy4MampqZQuXZratWvTp08f1q5dG1c6AXbs2EFmZiZmxj/+8Q/27dsX97wiIiIiiUg5tcXELbfcwrBhw6hWrRp9+vQhKSmJCRMm8MEHH7Br1y5Kly6dbfoVK1bw8MMP07p1a6644grKli3L999/z4QJE5g8eTKTJk3i3HPPBaBRo0b069ePAQMGULt27WwBWZs2bbL+f+utt3LqqafSpUsXKlWqxObNm3nnnXe4/PLL+eKLL3jwwQcP+n646667mDFjBt27d+eCCy5gxowZPPvss3z99dfMmDEj27Tjxo2jR48elC5dmh49elCtWjXmzp3LWWedxamnnhp1+SNHjqRPnz6kpqbSrVs3jj76aL755htGjx7NpEmTWLhwIbVq1cox34UXXsiSJUvo1q0baWlpHHXUUYWyvQ888AAvvPACb731Flu3biUtLY3t27fTsmVLvvnmG84991x69uxJiRIl+Pbbb3n//fdZsWIFdevWjWv5u3bt4pxzzuGPP/7gkksuYceOHbz88sv07NmTcuXKMWLECJYvX07Xrl0pVaoUr776KjfeeCNly5blqquuylrOpk2buPfee2nRogU9evSgfPny/PTTT0yaNInzzjuPZ599lquvvjpr+k8//ZSWLVtSokQJMjIyqFOnDjt27GDFihW88MIL/Otf/yIpKQnnHJ06dWL+/Pm0atWKjIwMkpKSWLt2LbNmzWLhwoU0bdo07v158cUX89FHH5GZmZl1DfXv359FixYxceLErI87AFOmTKF79+4AdO3alWOPPZZ169bxf//3f7z99tu8//77nHbaaVnTjx8/nldeeYU2bdrQoUMHSpYsyfLlyxk5ciSTJk1i0aJFVK9ePdf0bd68mS5dujBv3jweeeSRHB8zRERERA5HCmqLgfnz5zNs2DDq16/PggULqFixIgAPPfQQ7du3Z926ddSuXTvbPA0aNGD9+vWkpaVlG75+/XpOP/10br311mxBbaNGjRgwYAB16tSJ2RrrypUrqVmzZrZhu3fvpmvXrjz66KNcd911eb60H6glS5awfPlyqlSpAsC+ffvo2LEj06ZN48MPP6RZs2YA/Pbbb1x77bUkJSUxd+5cmjRpkrWMO+64gyeeeCLHsr/88kuuu+46TjzxRKZPn54tMJ0/fz5t27bl5ptvZvz48TnmXbduHStWrCA1NbVQt7du3brUqFGDtWvXsnjxYtq2bcv06dNZtWoV99xzD4888ki26ffu3cv27dvjXv66deto0aIFY8eOpWTJkgD89a9/pVmzZvTs2ZOGDRvy+eefU7ZsWcB/XKlfvz6PP/54tqA2PT2dtWvX5gjmt23bxtlnn81dd93FpZdeSpkyZQB4/vnn2bFjB1OmTKFjx47Z5tm6dWvW+pYtW8b8+fO55JJLGDNmTLbpnHNs3bo17m0Ff4yXL19Oeno6sP8aeuutt3jppZe4/PLLAR9c9uzZk/T0dGbOnMlxxx2XtYx77rmHM888k6uvvpqPP/44a/gVV1zBHXfcQalS2W/Ls2fPpm3btgwaNIgRI0bETNt3331Hp06d+Prrr3nxxRe59NJL87VtIiIiIolKxY+LgVGjfAvPAwYMyApoAVJSUqIGZwBpaWk5AlqAqlWr0qNHD1auXMmaNWvylY7IgBYgKSmJ66+/nj179jB9+vR8La8g+vXrlxXQgm8xOJSz/OGHH2YNnzBhAps2baJ3797ZAlqAQYMGZQU14UaMGMHu3bsZMmRIjuCsefPmZGRkMGnSJLZt25Zj3oceeqjQA9qQ0IeCjRs3Ar5IMJAtVzGkZMmS+U7Hv//976yAFuD000+nfv36/Pbbbzz22GNZASb4c6B169asWLEi235ITk6OmjudmprKVVddxebNm/noo4+yhue2DWlpaZQoUSLP6cyM8uXL52tbH3zwwWzHPvwaGjlyZNbwF154gV9//ZWBAwdmC2gB6tevT58+fViyZAmff/551vBq1arlCGgBWrduTePGjZk6dWrMdC1dupSzzjqLH374gcmTJyugFRERkWJFObXFQCg36Oyzz84x7vTTT6dcuXJR55s3bx5Dhw5lwYIFbNiwIUe9wR9++CFqUdpY1qxZw2OPPcb06dNZs2YNf/zxR47lHWynn356jmHVqlUDfO5aSG77LCUlhTPPPDNHXc9QXeNp06YxZ86cHPP9+OOP7N27ly+//DJHoHwwWyd2zgGwZ88eANq1a8dRRx3Fo48+yieffEKnTp0466yzaNSoUbbgNB5VqlShRo0aUYd/+eWXUYv2hj4q/Prrr9kC6OXLlzN48GBmz57NunXr2LFjR7b5ws+PHj16MGLECLp3705mZibt2rWjefPmOYpNN2rUiBNPPJExY8bwww8/cMEFF9C8eXOaNm2ao8h9PHK7hpYsWZI1LHQuLFq0iO+//z7HPKFgdsWKFTRo0ADwx+nll19m9OjRfPLJJ2zevJm9e/dmzRMrvXPnzuXJJ58kNTWV2bNn07Bhw3xvl4iIiEgiU1BbDIQaQQrPpQ0xMypUqJBj+Pjx48nMzCQlJYX27dtTt25dypUrR4kSJZg5cyazZs3KygWLxzfffEOzZs3YvHkzrVq1okOHDpQvX56SJUuyevVqnn/++Xwtr6Ci9dkaytULDyBy22exhv/yyy8APProo7mm4bfffssxLL85hvkRaqAqFEymp6ezYMEC+vfvz1tvvcU777wDwJFHHsn111/P/fffT1JSUlzLTklJiTo8tE/j3d8LFy7kL3/5C3v27KFdu3Z06dIlK8d16dKlTJgwIdv50apVK6ZPn84jjzzC2LFjef755wE4/vjj6devHz179gSgVKlSzJw5k4EDBzJu3Dhmz54N+BzgK664gocffjhfOdO5XUPhDYGFzoX//Oc/uS4v/Fy47bbbGDJkCNWqVaNjx45Ur149q7j16NGjs/VJHG7JkiVs27aN5s2bq4VrERERKZYU1BYDoYBp06ZNWbmSIc45fv31V4488shsw/v27UuZMmX47LPPOOaYY7KNu+2225g1a1a+0vDkk0/yyy+/8Nprr3HRRRdlGzdx4sSsoCQeoaAolAMZLjJ3r6DC91k00YaH5tmyZUvUottF4euvv2bt2rWUKFGCRo0aZQ0/9thjeeGFF3DO8fnnnzNjxgyefvppBg4cyO+//87jjz/+p6Zz0KBB7Nixg4ULF2bVaw4ZNmwYEyZMyDFPmzZtaNOmDTt37mTx4sVMmTKFp556il69epGamkrnzp0BOOqooxg+fDjDhw/n66+/ZtasWTzzzDMMHz6cdevWMW7cuLjTuWnTJipXrpxtWOgaCj/moXPhk08+idmoWLgNGzYwbNgwmjRpwpw5c7KC2ZCJEyfGDGpvuOEGNmzYwH/+8x+6dOnCm2++mWN+ERERkcOZ6tQWA6EWVqMFoh999BG///57juFffvklp556ao6AFuD999+Pup4SJUpEDTRDywPfCmy8y4slVKcxWhc54fUuD0Ru+ywUfEUKFSGOVvS4qAwcOBCATp06UalSpRzjzYyTTjqJG2+8kffeew/wAdSf7csvv6Rq1ao5AlrI+/xITk6mefPmDBw4kGHDhgGxt6FevXr87W9/Y9asWRxxxBFMmjQpX+nM7Rpq3Lhx1rD8ngtff/01+/bto0OHDjkC0o0bN7Js2bKY85oZI0aM4JZbbuHdd9/l/PPPj3pNi4iIiByuFNQWA6GGkPr165cth3HHjh3cfvvtUeepWrUqn3/+ORs2bMg2fPDgwSxdujTqPJUqVYpZL7Zq1aoAOfqWnTNnTq4tukYTCnyef/75bH1wbtiwgQEDBuRrWbF07dqV9PR0Ro8ezeLFi7ONu//++7PVvw254YYbSEpK4tZbb43aiNa+ffv44IMPCiV9edm6dSs33XQTL774IkcccQSDBw/OGrd8+XJ++umnHPOEilxHawTrYKtatSo//fQTK1asyDb8tddei5pLO3/+/Bx1siHnNnz77bd88803Oabbtm0be/fujVr0Pjd9+/bNduzDr6Err7wya/iVV15JhQoVGDBgAJ9++mnUZYX39xy6PubMmZOtWPauXbvo06dPtn53Y/n3v//Nvffey/vvv0/Hjh3z3bKziIiISKJS8eNioEWLFtx444089dRTnHzyydn62ExPT89RJBng5ptv5o477qBx48ZkZmZSpkwZ5syZw5IlS+jUqVOORpLAN0A0duxYunfvTqNGjShRogStW7emdevWXH/99YwZM4Zu3brRo0cPqlevzueff87EiRPp2rUrb7zxRtzbc8YZZ9C6dWvee+89WrRoQdu2bdm0aRPjxo2jXbt2rFq16oD2F8ARRxzBf//7X3r06EHLli2z9VO7bNkyWrdunVU/M+SEE05g5MiRXHXVVZxwwgmcf/75HHfccezdu5dvv/2W2bNnU6FCBVauXHnA6Qs3ZMgQKlSokNVFzRdffMHs2bP5/fffqVOnDmPGjOHEE0/Mmv69997jzjvvpEWLFjRs2JC0tDR+/PFH3njjDUqUKMGdd95ZqOmLx0033cScOXOy+qlNT09n8eLFTJ8+na5du/Lmm29mm/5f//oXM2bMoG3bthx//PGULl0663xKT0+nT58+gC/+2717d5o1a0aTJk2oWLEiP//8M2+++SZ//PEHgwYNylc669evz0knnZTtGlq1ahXnn39+Vnc+4D/wjBs3joyMDJo0aULHjh05+eSTMTO+//575s6dy/r167OKyx977LF07tyZt956i9NPP50OHTqwY8cOJk2ahJlx6qmnxgyOwz388MOkpKTQr18/2rdvz5QpU4rkI4WIiIjIn0lBbTExdOhQ6tevz9NPP80zzzxDpUqVyMjI4OGHH47aWurtt99OcnIyw4cPZ8SIEaSlpdGqVSvmzp3LxIkTowa1Q4cOxcyYPn06EyZMYN++ffTr14/WrVtntRbcr18/xo4dS6lSpWjYsCFjxoyhcuXK+QpqwXe5c+eddzJhwgQ+/vhjjjvuOB5++GE6dOjAa6+9VuD9FC4zM5MpU6YwYMAAXnvtNZKTk2ndujULFizg0UcfzRHUAlx22WU0bNiQJ554gvfff58JEyZQsmRJatWqxbnnnkuvXr0KJW3hhg4dCvhiqOXKlaNGjRpccMEFdO7cmczMzByNNXXo0IFVq1Yxb948Ro0axfbt20lPT6dFixbcfvvttG3bttDTmJfMzEzGjh3Lo48+ysiRIylTpgzNmjVj6tSpfP/99zmC2uuuu47U1FQ+/PBD3n33Xfbs2cPRRx/NFVdcwX333cexxx4LQNOmTbnjjjuYPXs2r7zyClu3biUtLY3TTjuNp59+mu7du+crna+99hoPPvggL7/8Mj/++CPVq1enf//+3HPPPTm6DWrXrh2ffvopjz/+OFOnTmXatGk456hevTpnnHEGF154Ybbpx44dy3333cdrr73Gk08+SZUqVejcuTMDBgzg4osvjjuNDzzwAGXKlOGuu+6iXbt2vPvuuznqzIuIiIgcTixWHchDXdOmTd2iRYvynG7FihXZcqlERPKrTZs2zJo1K2ad8USn+6SIiMjh7d43Psv29yPdTymilOSPmS12zuXsIzKC6tSKiIiIiIhIwlJQKyIiIiIiIglLQa2IiIiIiIgkLDUUJSKSh8iuqERERETk0KGcWhEREREREUlYCmpFREREREQkYSmoFRERERERkYRVLILaw7VvSRGRA6X7o4iIiCS6wz6oLVmyJLt37y7qZIiIHJJ2795NyZIlizoZIiIiIgV22Ae1qampbN26taiTISJySNq6dSupqalFnQwRERGRAjvsg9qKFSuyefNmfv75Z3bt2qWidiJS7Dnn2LVrFz///DObN2+mYsWKRZ0kERERkQI77PupTU5OplatWmzatInVq1ezd+/eok6SiEiRK1myJKmpqdSqVYvk5OSiTo6IiIhIgcUd1JpZSWAR8INzrrOZVQReBaoC64AezrnNwbT3An8F9gK3O+emBsObAM8BycA04GbnnDOzZOAF4CRgK9DLObe6cDbRB7bVqlWjWrVqhbVIEREREREROQTkp/jxzcCKsL8HAJOdc6cAk4O/Q4HrhcCpwLnAM0HQCjAKuNo51wCoDWQEw28AfnLOnQwMBoYVbHNERERERESkOIkrqDWzGsD5+FzWkPOBF4P/vxT8HRr+qnNut3NuLbAcaGZmtYCSzrnFMeYJLWsC0DzIGRYRERERERGJKd6c2iHAXcC+sGGVnXMbAYLfo4LhNYDvw6ZbGwyLNTzbPM65fcAvYcsTERERERERiSrPoNbMOgMbwnJYi4yZ9TGzRWa2aOPGjUWdHBERERERESli8eTUtgC6mNlqYCzwFzN7CdhoZpUBgt8NwfRrgZph89cIhsUanm0eMysBVAJyRK3Ouf8655o655pWrlw5rg0UERERERGRw1eeQa1z7l7nXA3nXB3gEmCGc+4y4B3gsmCyy/CNRREM72FmSUFd3JOBD51za4B9ZnZaMN2lEfOEltUVWOic23NgmyYiIiIiIiKHuwPpp7Yf8KqZXQX8BFwM4JxbZGbjgU/xdXCvc87tDOa5EhhpZqWBGcDrwfDhwItmtgz4Deh1AOkSERERERGRYiJfQa1zbiYwM/j/L8A5MaZ7CHgoyvBFQKMow3cAF+UnLSIiIiIiIiL56adWRERERERE5JCioFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqRUREREREJGEpqBUREREREZGEpaBWREREREREEpaCWhEREREREUlYCmpFREREREQkYSmoFRERERERkYSloFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqRUREREREJGEpqBUREREREZGEpaBWRERERAg/aqoAABnoSURBVEREEpaCWhEREREREUlYCmpFREREREQkYSmoFRERERERkYSloFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqRUREREREJGEpqBUREREREZGEpaBWREREREREEpaCWhEREREREUlYCmpFREREREQkYSmoFRERERERkYSloFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqRUREREREJGEpqBUREREREZGEpaBWREREREREEpaCWhEREREREUlYCmpFREREREQkYSmoFRERERERkYSloFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqRUREREREJGEpqBUREREREZGEpaBWREREREREEpaCWhEREREREUlYCmpFREREREQkYSmoFRERERERkYSloFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqRUREREREJGEpqBUREREREZGEpaBWREREREREEpaCWhEREREREUlYCmpFREREREQkYSmoFRERERERkYSloFZEREREREQSloJaERERERERSVgKakVERERERCRhKagVERERERGRhKWgVkRERERERBKWgloRERERERFJWApqRUREREREJGHlGdSaWYqZLTKzpWb2lZkNMa+imb1nZp+Z2btmlh42z71mtsLMlplZx7DhTcxsiZl9bmbDzMyC4clm9mow/Xwzq3MwNlZEREREREQOL/Hk1O4EznbONQIaAGcBbYEBwGTn3CnA5OBvzKwJcCFwKnAu8IyZJQfLGgVc7ZxrANQGMoLhNwA/OedOBgYDwwph20REREREROQwl2dQ67zfgz+TgJLABuB84MVg+EvB3wS/rzrndjvn1gLLgWZmVgso6ZxbHGOe0LImAM3NrGTBN0tERERERESKg7jq1JpZSTNbig9mZzrnlgGVnXMbAYLfo4LJawDfh82+NhgWa3i2eZxz+4BfwpYnIiIiIiIiElVcQa1zbm9Q/LgG0MrM2h7cZEVnZn2C+r2LNm7cWBRJEBERERERkUNIvlo/ds79CrwNnAlsNLPKAMHvhmCytUDNsNlqBMNiDc82j5mVACoBOaJW59x/nXNNnXNNK1eunJ+ki4iIiIiIyGEontaPjzSz1OD/ZYD2wDLgHeCyYLLL8I1FEQzvYWZJZlYDOBn40Dm3BthnZqcF010aMU9oWV2Bhc65PQe0ZSIiIiIiInLYKxXHNEcDLwTd76QAY5xzk8xsPvCqmf3/9u4+xrKzvg/494d3cWL3JdisU9Xrl0RRi5BNsb0QlSrEapEgtRLCUt6MW2WJ5boVUmn5I3EilaLWSqokDXLdCJzGm8okdNWwiESyE1whF6iL3LHX2GsbCKAI76rYG6OioArHaJ/+cZ+1787OeHbWs3PPM/P5SKM55znn3Pvc+c2ZM9/7nHPu+5I8leSdSdJaW6qqTyV5JMnxJDe31p7tj7UvyZ1V9fIkn03yyd5+e5K7qupwku8muX5jXh4AAMA2trQ/r3vm6LK2pWTPvsX05yxYM9S21h5J8toV2p9J8qZVtrk1ya0rtC+t8ljfS/KO0+gvAAAAPG9d19QCAADAlAi1AAAADEuoBQAAYFhCLQAAAMMSagEAABiWUAsAAMCwTudzagEAAJiQWw4+etL8r+y9ckE9WTwjtQAAAAxLqAUAAGBYQi0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMCyhFgAAgGEJtQAAAAxLqAUAAGBYQi0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMCyhFgAAgGEJtQAAAAxLqAUAAGBYQi0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMCyhFgAAgGEJtQAAAAxLqAUAAGBYQi0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMCyhFgAAgGEJtQAAAAxLqAUAAGBYQi0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMCyhFgAAgGEJtQAAAAxLqAUAAGBYQi0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMCyhFgAAgGEJtQAAAAxLqAUAAGBYQi0AAADD2rHoDgAAAHCalvYnSV73zNFl7UvJnn0L6NDiGakFAABgWEItAAAAwxJqAQAAGJZQCwAAwLCEWgAAAIYl1AIAADAsoRYAAIBhCbUAAAAMS6gFAABgWEItAAAAwxJqAQAAGJZQCwAAwLCEWgAAAIYl1AIAADAsoRYAAIBhCbUAAAAMS6gFAABgWEItAAAAwxJqAQAAGNaORXcAAABgu7vl4KMnzf/K3isX1JPxGKkFAABgWGuG2qq6pKo+V1WHq+qrVfULvf2Cqrq3qh6tqs9U1Svmtrmlqp7o27x5rv2aqjpUVY9X1W1VVb393Ko60Ne/v6ou3/iXCgAAwFZzOiO1zyV5f2vtiiTXJLmxql6b5MNJ7mmtXZnknj6fqromyduTvCbJW5J8rKrO7Y+1P8mNrbVXJ7ksydt6+/uTPNWf49eS3LYRLw4AAICtbc1Q21r7VmvtkT79F0keSXJxkuuS3NVX+3ifT/9+oLX2XGvtSJLHkry+qi5Nck5r7cFVtjnxWJ9O8oaqOuclvTIAAAC2vHVdU9tPC35dki8k2dVaO5Yk/ftFfbXdSZ6c2+xIb1ut/aRtWmvHkzwz93gAAACwotMOtVX1V5L8QZIPtNa+c/a69KJ9uKmqlqpq6dixY4voAgAAABNyWqG2qnYm+WSST7TWDvbmY1W1qy/fleTp3n4kySVzm+/ubau1n7RNVb0syYVJTkmtrbU7Wmt7Wmt7du3adTpdBwAAYAtb83Nq+x2KfyfJE62135hbdHeSG5L8Zv9+z1z7R6vqI0l+OMkVSR5orT1bVcer6urW2kNJ3pvZdbXzj/W/k7w1yRdba99/ya8OAABg6pb253XPHF3WtpTs2beY/gxmzVCb5O8l+cdJHq2qh3vbLyX5UJIDVfW+JE8leWeStNaWqupTmd1Q6niSm1trz/bt9iW5s6penuSzmY3+JsntSe6qqsNJvpvk+pf8ygAAANjy1gy1rbUvJKlVFr9plW1uTXLrCu1LSV67Qvv3krxjrb4AAADAvHXd/RgAAACmRKgFAABgWEItAAAAwxJqAQAAGJZQCwAAwLCEWgAAAIYl1AIAADAsoRYAAIBhCbUAAAAMS6gFAABgWEItAAAAwxJqAQAAGJZQCwAAwLCEWgAAAIYl1AIAADAsoRYAAIBhCbUAAAAMS6gFAABgWEItAAAAw9qx6A4AAABsKUv7V27fs29z+7FNGKkFAABgWEItAAAAwxJqAQAAGJZQCwAAwLCEWgAAAIYl1AIAADAsoRYAAIBhCbUAAAAMS6gFAABgWEItAAAAwxJqAQAAGNaORXcAAABgqzl46OhJ83uvunhBPdn6jNQCAAAwLKEWAACAYQm1AAAADEuoBQAAYFhCLQAAAMMSagEAABiWUAsAAMCwhFoAAACGtWPRHQAAAJi0pf2rL9uzb/P6wYqM1AIAADAsoRYAAIBhCbUAAAAMS6gFAABgWEItAAAAwxJqAQAAGJZQCwAAwLCEWgAAAIa1Y9EdAAAA2HRL+1du37Nvc/vBS2akFgAAgGEJtQAAAAxLqAUAAGBYQi0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMCyhFgAAgGEJtQAAAAxLqAUAAGBYQi0AAADDEmoBAAAYllALAADAsHYsugMAAAAv2dL+ldv37NvcfrDpjNQCAAAwLKEWAACAYQm1AAAADMs1tQAAwPSsdo1s4jpZTmKkFgAAgGEZqQUAAFjDwUNHT2nbe9XFC+gJyxmpBQAAYFhCLQAAAMMSagEAABiWa2oBAIDNsdodjd3NmJfASC0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMKw1Q21V3VlVT1fV4bm2C6rq3qp6tKo+U1WvmFt2S1U9UVWHq+rNc+3XVNWhqnq8qm6rqurt51bVgb7+/VV1+ca+RAAAgFMdPHT0pC/GdDojtb+b5C3L2j6c5J7W2pVJ7unzqaprkrw9yWv6Nh+rqnP7NvuT3Nhae3WSy5K8rbe/P8lTrbUrkvxaktvO+NUAAACwrawZaltrn0vy7WXN1yW5q09/vM+faD/QWnuutXYkyWNJXl9VlyY5p7X24CrbnHisTyd5Q1WdcyYvBgAAgO3lTK+p3dVaO5Yk/ftFvX13kifn1jvS21ZrP2mb1trxJM/MPR4AAACsaseiO7AeVXVTkpuS5NJLL11wbwAAYJtb2r9y+559m9sPtrUzHak9VlW7kqR/f7q3H0lyydx6u3vbau0nbVNVL0tyYZJjKz1pa+2O1tqe1tqeXbt2nWHXAQAA2CrONNTeneSGPn1DZjeLOtH+rqraWVW7k1yR5IHW2jeTHK+qq/t67122zYnHemuSL7bWvn+G/QIAAGAbWfP046r6RJJrk7yyqo4k+VD/OlBV70vyVJJ3JklrbamqPpXkkSTHk9zcWnu2P9S+JHdW1cuTfDbJJ3v77Unu6h8Z9N0k12/QawMAAGCLWzPUttbes8qiN62y/q1Jbl2hfSnJa1do/16Sd6zVDwAAAFhuqBtFAQAAZ9FqN35K3PyJyTrTa2oBAABg4YRaAAAAhiXUAgAAMCyhFgAAgGG5URQAAGxlq938yY2f2CKM1AIAADAsoRYAAIBhCbUAAAAMyzW1AAAwEtfIwkmM1AIAADAsI7UAAMCWcPDQ0ZPm91518YJ6wmYyUgsAAMCwjNQCAMAirXaNbOI6WTgNRmoBAAAYllALAADAsJx+DAAAG83H7sCmMVILAADAsIRaAAAAhuX0YwAAWIvTiWGyjNQCAAAwLKEWAACAYQm1AAAADMs1tQAAwCQdPHT0lLa9V128gJ4wZUItAABbw3pu5rTauqutD0yWUAsAwDS54zBwGlxTCwAAwLCEWgAAAIbl9GMAAM6cU4RZp+U3f3LjJ14qI7UAAAAMS6gFAABgWE4/BgBgczhVeUtyOjGLZqQWAACAYQm1AAAADEuoBQAAYFiuqQUA2MpcxwpscUItAAAvEIKBwTj9GAAAgGEJtQAAAAxLqAUAAGBYQi0AAADDcqMoAIDTMaUbKE2pLwALJtQCAGy09YZOIRXgjAm1AADA8w4eOnpK296rLl5AT+D0CLUAwNZgdBRWtTyoCqlsJUItADBdgicAa3D3YwAAAIYl1AIAADAsoRYAAIBhuaYWADhzrnkFYMGEWgBg8wjBAGwwoRYAABZsvZ8N6yN64AWuqQUAAGBYQi0AAADDEmoBAAAYllALAADAsNwoCgA4mTsUAzAQI7UAAAAMS6gFAABgWEItAAAAw3JNLQAAnAUHDx09aX7vVRcvqCewtQm1AABsS+sNnUIqTJPTjwEAABiWkVoA2Op8RA8AW5hQCwDAZDnlF1iLUAsAwJYhBMP2I9QCAHASwRAYiVALAMCmEZiBjSbUAgBscWc7SAqqwCL5SB8AAACGJdQCAAAwLKcfAwAMyCm/ADNCLQDABAipAGdGqAUAti1BEmB8Qu3ZtLR/5fY9+za3HwCwTUwppE6pLwBbmVALAEzalMLhlPoCwIxQCwBsKsEQgI3kI30AAAAYlpFaAOAU6xlNNfIKwCIJtQAwGjciBIDnTSbUVtVbkvx6knOS/JfW2q8uuEsAsGUYTQVgq5rENbVVdW6Sjyb5qSSvSfKPqurqxfYKAACAqZvKSO2PJ3mstfZkklTVgSTXJXloob0CgDO13lOEnVIMAGdkKqF2d5In5+aPJLl2MV3ZWEOe7nW2/7Faz+Ovtu5G9ofNtV3+cV/v7+4I+91GhbGJ9WXFv9Or9OW01+3WewxwcyYAWL9qrS26D6mq65O8sbV2c59/T5JrW2v/dNl6NyW5qc/+7SRf2dSOnh2vTPLni+4Ep1CXaVKXaVKXaVKXaVKXaVKX6VKbadqsulzWWtu11kpTGak9kuSSufndve0krbU7ktyxWZ3aDFW11Frbs+h+cDJ1mSZ1mSZ1mSZ1mSZ1mSZ1mS61maap1WUSN4pK8kCSK6pqd1XtTPKuJPcsuE8AAABM3CRGaltr36uqf5bkTzIL2h9vrS0tuFsAAABM3CRCbZK01u5Ocvei+7EAW+p06i1EXaZJXaZJXaZJXaZJXaZJXaZLbaZpUnWZxI2iAAAA4ExM5ZpaAAAAWDeh9jRU1Vuq6nBVPVFVv7jC8gur6p6qeryqHqiqK+aW/WJV/WlVPVZVH5hr31NVD/X2P6qqv9bbz6+qP6iqL1fV16rqw3PbXFNVh/rz3FZV1dvPraoDvY/3V9XlZ/PnMRVTqEtVnVdVf9Kf46tV9ZtV9bK+7Oeq6lhVPdy/bjz7P5VpmEJt+rL7quorczW4qLfbZxa3z/zVuXo8XFV/XlUf6cu25T6zyXX5gar6vb5ffKmqrp3bxjFmzhTqUo4xp5hCXfoyx5c5U6hLOb6coqrurKqnq+rwKsur/71/vP/9v3pu2Yo1raoLqureqnq0qj5TVa+YW3ZLX/9wVb15rv3sH19aa75e5CvJuUn+LLOPHNqZZCnJ1cvW+Y9JPtSnX5Xkf/Xpa5I8luS8zK5f/u9JXtOXPZrkJ/v0+5L8Rp++Mcl/7dPn9ef+sT7/SJJr+vSnk+zt0x9McluffluSP1z0z2271KVP/0Rvf3mSzyf52T7/c0luX/TParvWps/fl2TPCn20zyywLsue88HMPqd8W+4zC6jLB5Ps79MX9fV29nnHmInVJY4xk6xLn78vji+Tq8uy59zWx5f+ut+Y5Ookh1dZ/vbM/t5XX+9La9W01/Jf9el/Off7fk1fb2dmH8/6Z0nO7cvO+vHFSO3afjzJY621J1trzyU5kOS6Zeu8Kslnk6S19uUkF1XVxb39i621/9da+36S/5Hkp/s2P5bkc3363iQ/06ePJDm/qnYk+cEkf5nk21V1aZJzWmsP9vU+PteP65Lc1ac/neQNVXXOS3/pkzaJuvTH+Hx/jr/M7OOpLt7wVzuWSdRmjT7aZyZQl6r6W5n9Q/L5DXuV49nsusw/1tNJnk7yeseYU0yiLo4xp5hEXdboo/1lAnVxfJlprX0uL/4/0XWZfepMa609lGRHVV2SF6/p/O/48mPFgdbac621I5m9WbFpxxehdm27kzw5N3+kt817NMneJKmq1ye5LMmlvf0n+ykX5yX5h709SZ5I8tY+/Y4T7a21P07ynST/J8k3k/x6a+3ba/Tj+WWtteNJnslsR97KplKX51XVD2X2LtMfzzXv7ada/NF2OQUp06vN7/Ya/Nvqp+3FPpMsvi5J8u7MDoDzdyzcbvvMptalb/MzVbWjqn4ks3fWL12jH/aXxdXleY4xSaZXF8eXmanVJXF8OV2r1e7FarqrtXYsSfr3E7/fZ/JYG7a/CLUb48NJfriqHk/yC5kNvbfW2iNJ/kNmp6jcl9lOeGLn+idJPtDPcX9lkmeTpKpuyOwUjL+Z5EeSfLCqfnTTXsnWsml16aNRv5/ZKRRf781/mOTy1tqrM3v36ffO2isdz2bV5t2ttSsye8dxT5KfP+uvbGyb/bfs3Uk+MTdvn1nZhtUlyUeTHMvsVLCPJbl/bhvWZ9Pq4hizLptVF8eX9dnsv2OOL9vMZD6ndsKOZHY++Qm7e9vzWmvfSXL9ifmq+kaSr/Zlv5Xkt3r7v0nyf3v74STX9vbLM3tnKkl+Ismn+lD/01X1PzM7peL+F+nHiT5+q79TeGFmO/tWNpW6fKMvvyPJ11trH5l7/m/PTf/n6jcr2AYmU5vW2rf6tn9RVXf17X879plkwftMVf2dJDvmTkfarvvMptaln8L6z+ce674kX87s9DTHmBdMpS4nOMbMTKYuji8nmUxd+rzjy+k7Ubsv9vkTtduZ1Wt6rKp2tdaOVdWuzE7/nn+s5du82O/Hhu0vRmrX9kCSK6pqd1XtTPKuJPfMr1BVf72/i3pidOLQiZ2nql7Zv/+Nvu2BZe2V5JeS/E5/uK8n+ft92flJ/m5mB7JvJjleL9yV7L1z/bg7yQ19+q2ZXZvw/Q37CUzTJOrS5/9dkh9K8i+WPf9Fc9M/neRrG/Tap24StemnJV3Q23dmdi3O430b+8wC95nuPTn5XfTtus9sal1qdjfdH+zTb0xyXmvtYceYU0yiLn3eMeYFk6iL48spJlGXuadzfDl9d2f29z797//x1tqTefGazv+O37Cs/V1VtbOqdie5IskDm3Z8aRO4M9fUvzJ7Z+ixzM7t/+XednOSm/v0GzJ7t+mRJAeTvGJu2y/09geT/IO59g9k9q7S4SS/mqR6+/lJ/lt/vK8l+ddz2+xJ8nBmfzhvn9vmB/o2hzN7p+VHF/0z2y51yezdptb78HD/urEv+/eZnUbzeGYj7Vcu+me2zWpzfpKHknwpyZ9mdorSy/sy+8wC/5b15d9I8qplbdtyn9nkulye5Ct9v7g3yWVz2zjGTKwucYyZal0cXyZYl7ntHF9eeN2fyOzeFs9lNir688vqUkn+U/+5PJy5O3qvVNPefmFmd6l+tH+/YG7ZL/f1H0vyU3PtZ/34cuIBAQAAYDhOPwYAAGBYQi0AAADDEmoBAAAYllALAADAsIRaAAAAhiXUAgAAMCyhFgAAgGEJtQAAAAzr/wPuo6Ls2OdrCQAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "a=[h_mc_under.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc_under.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Ds Own PV Vertex chisq/ndof Signal MC/ data under peak comparison\", fontsize=20)\n", + "#Retrieve mc signal and data bkg events\n", + "data_bkg_indices=[]\n", + "MC_sig_indices=[]\n", "\n", - "plt.bar(b,a,width=0.000001,alpha=0.6,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.0000015, alpha=0.4, label=\"data under Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" + "\n", + "for i in range(len(data_tuple_dict[\"Ds_ConsD_M\"])):\n", + " #retrieving the Ds reconstructed mass\n", + " \n", + " #if 850" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "a=[h_mc_over.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc_over.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n", + "#Create the dict tuples with all MC signal and data bkg events\n", "\n", - "plt.title(\"Ds Own PV Vertex chisq/ndof Signal MC/ data over peak comparison\", fontsize=20)\n", - "plt.bar(b,a,width=0.000001,alpha=0.6,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.0000015, alpha=0.4, label=\"data over Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" + "data_tuple_bkg={}\n", + "MC_tuple_sig ={}\n", + "\n", + "for label in branches_needed: \n", + "\n", + " data_tuple_bkg[label] = data_tuple_dict[label][data_bkg_indices]\n", + " MC_tuple_sig[label] = MC_tuple_dict[label][MC_sig_indices]\n", + " " ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(47950,)" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "nbins=70\n", - "MC_probNNmu=MC_tuple_dict[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n", - "data_probNNmu_under=data_tuple_bkg_under[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n", - "data_probNNmu_over=data_tuple_bkg_over[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]" + "MC_tuple_sig[\"Ds_ConsD_M\"].shape" ] }, { @@ -811,35 +394,92 @@ "metadata": {}, "outputs": [], "source": [ - "h_mc= r.TH1F(\"ProbNN e MC/data comparison below\", \"ProbNN e MC/data below Ds mass comparison\",nbins, 0, 1)\n", + "def plot_sb_comparison(nbins=None, particle=None, variable=None, \n", + " MC_sig=None, data_bkg=None, \n", + " width_MC=None, width_data=None,):\n", + " #min_plt_range=None, max_plt_range=None):\n", + " \n", + " #Determine maximum between MC and data\n", + " if \"CHI2\" in variable:\n", + " if np.max(MC_sig)>np.max(data_bkg):\n", + " upper_limit=np.max(MC_sig)\n", + " else:\n", + " upper_limit=np.max(data_bkg)\n", + " \n", + " lower_limit=0\n", + " if \"DIRA\" in variable:\n", + " lower_limit=0.99980\n", + " upper_limit=1.\n", + " \n", + " if \"prob\" in variable:\n", + " lower_limit=0.\n", + " upper_limit=1.\n", + " \n", + " if \"Hlt\" in variable:\n", + " lower_limit=0.\n", + " upper_limit=2.\n", + " \n", + " #Create and fill MC Signal histogram\n", "\n", - "for i in range(len(MC_probNNmu)):\n", - " h_mc.Fill(MC_probNNmu[i]) \n", - "\n", - "n1=h_mc.Integral(\"width\")\n", - "h_mc.Scale(1/n1)\n", - "h_mc.Integral(\"width\");" + " h_mc= r.TH1F(particle+\" \"+variable+\" MC/data comparison\", particle+\" \"+variable+\" MC/data comparison\", nbins, lower_limit, upper_limit)\n", + " \n", + " for i in range(len(MC_sig)):\n", + " h_mc.Fill(MC_sig[i])\n", + " \n", + " n1=h_mc.Integral(\"width\")\n", + " h_mc.Scale(1/n1)\n", + " h_mc.Integral(\"width\");\n", + " \n", + " #Create and fill data bkg histogram\n", + " h_data= r.TH1F(particle+\" \"+variable+\" from data\", particle+\" \"+variable+\" from data\", nbins, lower_limit, upper_limit)\n", + " for i in range(len(data_bkg)):\n", + " h_data.Fill(data_bkg[i])\n", + " \n", + " n2=h_data.Integral(\"width\")\n", + " h_data.Scale(1/n2)\n", + " h_data.Integral(\"width\");\n", + " \n", + " a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", + " b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", + " c=[h_data.GetBinContent(i) for i in range(nbins)]\n", + " d=[h_data.GetBinCenter(i) for i in range(nbins)]\n", + " plt.title(particle+\" \"+variable+\" Signal MC/ data comparison\", fontsize=20)\n", + " \n", + " plt.bar(b,a,width=width_MC,alpha=0.6, label=\"Signal MC\")\n", + " plt.bar(d,c,width=width_data, alpha=0.4, label=\"Background Data\")\n", + " plt.legend(fontsize=20)\n", + " fig = plt.gcf()\n", + " fig.set_size_inches(16,8)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "h_data_under= r.TH1F(\"data below signal_3\", \"data below signal_3\",nbins, 0, 1)\n", - "h_data_over= r.TH1F(\"data over signal_3\", \"data over signal_3\",nbins, 0, 1)\n", - "for i in range(len(data_probNNmu_under)):\n", - " h_data_under.Fill(data_probNNmu_under[i])\n", - "for i in range(len(data_probNNmu_over)):\n", - " h_data_over.Fill(data_probNNmu_under[i])\n", - " \n", - "n2=h_data_under.Integral(\"width\")\n", - "h_data_under.Scale(1/n2)\n", - "h_data_under.Integral(\"width\");\n", - "n3=h_data_over.Integral(\"width\")\n", - "h_data_over.Scale(1/n3)\n", - "h_data_over.Integral(\"width\");" + "\n", + "#Retrieve data from needed branch\n", + "MC_Ds_endvtx_chi2ratio=MC_tuple_dict[\"Ds_ENDVERTEX_CHI2\"]/MC_tuple_dict[\"Ds_ENDVERTEX_NDOF\"]\n", + "data_Ds_endvtx_chi2ratio=data_tuple_bkg[\"Ds_ENDVERTEX_CHI2\"]/data_tuple_bkg[\"Ds_ENDVERTEX_NDOF\"]\n", + "\n", + "#Plot\n", + "plot_sb_comparison(nbins=70,particle=\"Ds\", variable=\"END VTX CHI2\", \n", + " MC_sig=MC_Ds_endvtx_chi2ratio, data_bkg=data_Ds_endvtx_chi2ratio, \n", + " width_MC=0.05, width_data=0.06)" ] }, { @@ -849,7 +489,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -861,17 +501,15 @@ } ], "source": [ - "a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"ProbNN mu Signal MC/ data under peak comparison\", fontsize=20)\n", "\n", - "plt.bar(b,a,width=0.01,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.01, alpha=0.6, label=\"data under Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" + "#Retrieve data from needed branch\n", + "MC_Ds_endvtx_chi2ratio=MC_tuple_dict[\"phi_ENDVERTEX_CHI2\"]/MC_tuple_dict[\"phi_ENDVERTEX_NDOF\"]\n", + "data_Ds_endvtx_chi2ratio=data_tuple_bkg[\"phi_ENDVERTEX_CHI2\"]/data_tuple_bkg[\"phi_ENDVERTEX_NDOF\"]\n", + "\n", + "#Plot\n", + "plot_sb_comparison(nbins=70,particle=\"phi\", variable=\"END VTX CHI2\", \n", + " MC_sig=MC_Ds_endvtx_chi2ratio, data_bkg=data_Ds_endvtx_chi2ratio, \n", + " width_MC=0.07, width_data=0.08)" ] }, { @@ -881,7 +519,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -893,66 +531,99 @@ } ], "source": [ - "a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Prob NN mu Signal MC/ data under peak comparison\", fontsize=20)\n", + "#Retrieve data from needed branch\n", + "MC_Ds_ownpv_chi2ratio=MC_tuple_dict[\"Ds_OWNPV_CHI2\"]/MC_tuple_dict[\"Ds_OWNPV_NDOF\"]\n", + "data_Ds_ownpv_chi2ratio=data_tuple_bkg[\"Ds_OWNPV_CHI2\"]/data_tuple_bkg[\"Ds_OWNPV_NDOF\"]\n", "\n", - "plt.bar(b,a,width=0.01,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.01, alpha=0.6, label=\"data under Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" + "#Plot\n", + "plot_sb_comparison(nbins=70, particle=\"Ds\", variable=\"Own PV CHI2\", \n", + " MC_sig=MC_Ds_ownpv_chi2ratio, data_bkg=data_Ds_ownpv_chi2ratio,\n", + " width_MC=0.01, width_data=0.01)" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "nbins=4\n", - "MC_Hlt1TrackMVA_TOS=MC_tuple_dict[\"Ds_Hlt1TrackMVADecision_TOS\"]\n", - "data_Hlt1TrackMVA_TOS_under=data_tuple_bkg_under[\"Ds_Hlt1TrackMVADecision_TOS\"]\n", - "data_Hlt1TrackMVA_TOS_over=data_tuple_bkg_over[\"Ds_Hlt1TrackMVADecision_TOS\"]" + "#Retrieve data from needed branch\n", + "MC_Ds_ownpv_chi2ratio=MC_tuple_dict[\"phi_OWNPV_CHI2\"]/MC_tuple_dict[\"phi_OWNPV_NDOF\"]\n", + "data_Ds_ownpv_chi2ratio=data_tuple_bkg[\"phi_OWNPV_CHI2\"]/data_tuple_bkg[\"phi_OWNPV_NDOF\"]\n", + "\n", + "#Plot\n", + "plot_sb_comparison(nbins=70, particle=\"phi\", variable=\"Own PV CHI2\", \n", + " MC_sig=MC_Ds_ownpv_chi2ratio, data_bkg=data_Ds_ownpv_chi2ratio,\n", + " width_MC=0.009, width_data=0.008)" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "h_mc= r.TH1F(\"Hlt1 TrackMVA TOS MC/data comparison under\", \"Hlt1 TrackMVA TOS MC/data under Ds mass comparison\",nbins, 0, 2)\n", + "MC_Ds_DIRA_ownpv=MC_tuple_sig[\"Ds_DIRA_OWNPV\"]\n", + "data_Ds_DIRA_ownpv=data_tuple_bkg[\"Ds_DIRA_OWNPV\"]\n", "\n", - "for i in range(len(MC_Hlt1TrackMVA_TOS)):\n", - " h_mc.Fill(MC_Hlt1TrackMVA_TOS[i]) \n", - "\n", - "n1=h_mc.Integral(\"width\")\n", - "h_mc.Scale(1/n1)\n", - "h_mc.Integral(\"width\");" + "#Plot\n", + "plot_sb_comparison(nbins=70, particle=\"Ds\", variable=\"DIRA Own PV\", \n", + " MC_sig=MC_Ds_DIRA_ownpv, data_bkg=data_Ds_DIRA_ownpv,\n", + " width_MC=0.000001, width_data=0.000001)\n" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "h_data_under= r.TH1F(\"data below signal_4\", \"data below signal_4\",nbins, 0, 2)\n", - "h_data_over= r.TH1F(\"data over signal_4\", \"data over signal_4\",nbins, 0, 2)\n", - "for i in range(len(data_Hlt1TrackMVA_TOS_under)):\n", - " h_data_under.Fill(data_Hlt1TrackMVA_TOS_under[i])\n", - "for i in range(len(data_Hlt1TrackMVA_TOS_over)):\n", - " h_data_over.Fill(data_Hlt1TrackMVA_TOS_over[i])\n", - " \n", - "n2=h_data_under.Integral(\"width\")\n", - "h_data_under.Scale(1/n2)\n", - "h_data_under.Integral(\"width\");\n", - "n3=h_data_over.Integral(\"width\")\n", - "h_data_over.Scale(1/n3)\n", - "h_data_over.Integral(\"width\");" + "MC_probNNmu=MC_tuple_sig[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n", + "data_probNNmu=data_tuple_bkg[l_flv[l_index]+\"_plus_MC15TuneV1_ProbNN\"+l_flv[l_index]]\n", + "\n", + "#Plot\n", + "plot_sb_comparison(nbins=70, particle=\"Ds\",variable=\"probNN mu\", \n", + " MC_sig=MC_probNNmu, data_bkg=data_probNNmu,\n", + " width_MC=0.01, width_data=0.01)" ] }, { @@ -962,7 +633,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -974,17 +645,13 @@ } ], "source": [ - "a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data below peak comparison\", fontsize=20)\n", + "MC_Hlt1TrackMVA_TOS=MC_tuple_sig[\"Ds_Hlt1TrackMVADecision_TOS\"]\n", + "data_Hlt1TrackMVA_TOS=data_tuple_bkg[\"Ds_Hlt1TrackMVADecision_TOS\"]\n", "\n", - "plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.5, alpha=0.6, label=\"data below Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" + "#Plot\n", + "plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt1 Track MVA TOS\", \n", + " MC_sig=MC_Hlt1TrackMVA_TOS, data_bkg=data_Hlt1TrackMVA_TOS,\n", + " width_MC=0.5, width_data=0.5)" ] }, { @@ -994,7 +661,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -1006,29 +673,40 @@ } ], "source": [ - "a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data over peak comparison\", fontsize=20)\n", + "MC_Hlt2RareCharm_TOS=MC_tuple_sig[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n", + "data_Hlt2RareCharm_TOS=data_tuple_bkg[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n", "\n", - "plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.5, alpha=0.6, label=\"data over Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" + "#Plot\n", + "plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt2 RareCharm D2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\" TOS\", \n", + " MC_sig=MC_Hlt2RareCharm_TOS, data_bkg=data_Hlt2RareCharm_TOS,\n", + " width_MC=0.5, width_data=0.5)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAAHnCAYAAABALvsIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3XucTfX+x/H3x21cMu5FoSGdrofUUOQyKronoVxKuuj2c0hUTufoco6fTslBddIVXaQ6lUsXqWQqogyRxK9OEV2E3MJxyXx/f3zXHnv27JnZw2aZ8Xo+HvMYe63vWuu719p77Pf+XpY55wQAAAAAQBhKhV0BAAAAAMChi1AKAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAQSgEclMxshZmtCLseiTKz3mbmzKx32HXBHsE1yQy7Hokws/FBfdPCrksYitO1QtGZWVpwjceHXRcABx9CKVCCBR8Aon9+N7MNZvaFmY0zs45mVno/Hn9FYR+yzSwzKJORwP4KDH5mdqqZPWBmc81so5ntMrMfzWyimZ1axLpnxDl/O83sBzP7t5m1KMr+whZ1LRL9uTdm+4pmNsDMPjKzdcG5+NnM3jCzrmZmBRy7vZlNMrOfgmvyXzP7zsymmtmggraNs69mZjbBzL43sx1mtt3MVprZO2b2VzOrtA+nqViJCrHOzP5WQLmro8plFlCufXBul5vZtuA6/cfMnjez8wvYrmuw7877+JT2GcEHAIqnMmFXAMABcV/wu7SkqpJOktRDUm9JX5hZV+fc1yHVLZkek3S6pPmSJkjaKKmxpMsldTGzK5xzrxdxn99LGh/8u5yk5pK6SLrMzLo45yYlo+IHwCj5ax+tt6SjJT0raUXMuszIP8zsJElvSGogfz5ek/SrpPqSLpR0kaT3zOxy59zG6J2Y2V2S/lfSdknTJP2f/Beix0hqI+nioG6/F/YEzOzKoK5O0ruSXpKUHTyHVpLODZb9J2qzEyRtK2zfxdzvkq4xs/ucc7vjrO8TlIn7f76ZVZb0nKRL5a/TB5Jel7RLUpr8eb3SzEY45wbF2UUnSf+Vv75Afn6Ufz9uCrsiAA4+hFLgEOCcuzd2mZkdIekRSV0lvW9m6c65NQe6bkk2QdKVzrnoUCIzu0w+SD1pZm8653YWYZ8rYs+fmf1Z0jBJIyQVi1DqnBsVuyxonT5a0njnXGa87cystqT3JNWRdL+ku51zv0etry7pRfng8oqZneecyw7WHS3pb/IfQpvHfvFhZqUktZcUL0jF1qOipH/Jh9AM59zsOGVaSloX87yXFbbvEuBN+UB5nqS3oleY2QmSzpR/nXaK3TC4Bv+Wv34z5d8/P8WUKSfpBknHx9m+nPwXE+8650p6+Mc+cM7tknQovB8B7AW67wKHKOfcL5K6ybeI1ZN0V/R6M2sUdOWLdLncamZLg26/NQ50fYNuh+OCh+NiupqmSZJz7pHYQBosf13SYkk1JP0xCdV5LPjdwMxqxalrO/Pdkn8zs81m9lYQDqLLTAzq3jbeAcysc7D+0ahlYVyTofKB9CXn3F3RgVSSnHPrJXWW9J18wOwetfp0+db56fFa4p1z2c656c45l0A9TpaUKmlBvEAa7O+TOC21cbusmlmd4LytCbqpLjSz62xPt+17Y8pHupmXMbO7zOyboPvwKvNdxsvFOUYX8129V5jv7rzVzOabWb8gDCbLBPmWyj5x1kWWPZ3Ptt3lA+l/JF0cG0glyTm30zn3qKSBcbY/S/66JPTljJmVM7MhZvZtcP6Wm9lQM0vJp/yRZjbMcnfJ/8nMXjSzE2PK3itpefAwustyTpf/4PgDzexdM/sl2N96M3u/oC7KBTyf0mZ2k5nNNrNNwf6+N7MXzOwPMWWrmNn9ZvZ/5rudbzCz6WZ2Tpz95rwOzewM893TNwavoTfMrEFQ7jjzXeM3Ba/jTDNrEmd/ka7eDc3sNjNbFtThBzMbaWapcbY5x8yeC17r24P9f2lm95hZ+Tjl7w2OkWFmPczsUzPbYsHcAJZP12ozq21mY4LztjM41n/M7CUzOyambKngfM8L9r01+PfN8d5TwfEyzaymmT1pfsjBDjNbYmbX5HddARx4tJQChzDnXLaZDZWUIam7mQ1wzjkzqyPpU0mVJU2V73JZRtKxkjrKtxD+eoCrO16+O25HSVMkLYxatzHeBjEiY2cL7SaagOgxkLGB6qLgZ6qkh+VblzpJamZmJzrnIi15Y+S/FLhB0odxjnFj8PtxyYcoHeBrYmYVJF0ZPMx3zKJzbquZjZBvybxBPiRJviuoJB1jZqUiLah7KbKvemZW3jm3vcDSBTCzwyXNkW8l/kjSJ5Jqy1+vmYVs/qKkFvKvwa3y1/oOSYdLiv2Q+3dJO+S7Gq+RdJiksyWNltRM0lV7+xxibJRv7exhZrWdc6slKQh6veRfX/l1z78h+P2Qc25rQQdxzu2Is/gy+ffUG4VV0sxM0ivyr9dvJT0q3yX+WuX/ZVEbSbfIP4eP5c/nsfItw5eY2ZnOuUVB2Uz5Lur9JS2SNDlqP5G/F9XlW/xnS3pZvhX/CPlu5G+bWR/nXH4BPvb5lJNvpW4vaZX8a2O9/Jd850h6X8F5N7OqwTFPlDRPvst6TfmhBe+a2c3OuSfiHKaF/Otruvz76yT583ey+TG870taEKyrL/83ZYaZneCcWxtnfyPlz+kr8q/hcyXdKqm1mbWKeV8Nku+y/7GknyWlyLe63yspw8zOyae7+ED5Lytele9lETtsIIf5HhCzJDWU9I6kifK9IRpIaiff3ffbqE2elx96skr+ixYn//f1Mfku/D3jHCZy7rcE21eQP09jzSzbOfdsfvUDcAA55/jhh58S+iP/H7YrpEyK/NgxJ6lBsOxPweMb45QvL6l8gsdfEexnlPwHmXg/kTIZcbZdEbOsd1C2dxHPQ/Ngux8llU5wm4xgm8w46+4K1n0bp27bJbWMKT8kWHdHzPLFQfkaMcsbyn8wmx21LCnXJGa7zHjnPmp968h5S2BfxwZld0TOsXyAXhMs/0g+fJyU6DWI2X8pSUuCfS2U9D+Smkoql8B7IDNm2TPB8v+NWd5Efvypk3RvPufqE0mHxZz7JfJdkGvHbFMvTn1M0pPBvk6PWTc+WJ6W4DmJlD9H/gO5k/TnqPXdgmU9JTWKPRfyX2rsCJY32str8ouk9xMs3yM41sfRr1f5oPh/+VyrWvFe2/Jf9vwmaVrM8rRgP+PzqUOKpMPjLK8sH+7WS6qQ4PMZFhzrdUkpMevKSKoZ9fiJoOwYSRbzvlkfXIe0qOUZQflsSZfG7PvRYN1vkvrFrBuk+H9rIq+VXyQdHXMNXwnWDSns9Rss/0tQ/oqY5fcGyzdKOj7OdnmujfyXAU7S/XHKl5ZUOepx96DsPOV+D1aS/8LOSeoRsw8X/IyOWd4oOOdfFfV1zw8//OyfH7rvAoc451s/Ii1ska6oka50ebpVOue2u6K3UvWXdE8+P0cXtc5FEbRQPB88HOjif7NfkLSgW9q9Zva/Zvae/MQ92fIfAGO94Jz7JGbZ2OB385jlY+TPde+Y5X3kw0t0y0myr0ki6gS/VyVQNlKmnHw3aTnnfpPUQT5EtpYPg19K+s3MPjSzWyyfbpuxnG9lvVA+HDaR/2C+QNKWoJvgnfG6IMYKWre6S9qgPROARY6xSPl3c424wzm3JWqb7fItZKUkpcfsL895c845+RZZybdSJYVzbpb8eL3rgxZJyb+ONsiPp46nuvz1kqQf9uKwLeVbiBMdVx1pSb49+vXqfBfwIfE2cM6tjffadn6s8HRJ7cysbKIVds7tcHHGzgev1bGSqsm3YhfI/Kzlt8h/iXGdi2lFds797oJeEcFr7kpJmyUNCl4DkXLfSHpI/jr0inOoD5xzk2OWRXoi/OycezifdbF/ayKGO+e+jzp+tvzf593yXxpFP4f83vejg9/5vX7HuMTHchf0d213cF0iIvUbEPMe3CppQPDw+jjH+E3S4Jh9/0f+i7ITzOywBOsKYD8ilAKQ9nRHjXTpnyz/YetRM3vFzK43s5OiPuwWVQPnnMX7Ufyuq0lh/vYgb0j6g/yHsZf2YjdHa0+AvkO+pe91Sa1d/Jl358VZ9nPwu1rM8uflu5RFulAq+IDdWz5MvBJVNtnX5IBwzi10zjWV/6B/h/zsuD/JdyH8l6RPzSz2vOS3rxXOuXbyXSD7y5+/r+U/gP9D0uLIWLsCHCfffe9TF3/Cq48L2T7h62tmNczsH+ZvwbQlGN/m5FvIJemoQo5VVE/Jt7KfZWaN5Ls/Pr+fvrCQfLdJp9zdZAtyqvzY18/irMvMbyMzuzAYR/mz+TGbkfPYWT7U1CxKpYP3zXjztyX6b9T+HgmKJHJdjpdURdIc59yGQsoeJ6mipLkufhfpGcHvpnHWZcVZ9kvwe34B6/J7T+X5e+uc+1n+fZQWfIknyf/9ND9+ep75MavZwXmKBMX8ztPcfJbHM0O+N8Vg82Pv+5rZaRb/VmWnyvcsif3SL3LMbYp/Dpc45/4bZ3l+f5cBhIAxpcAhLpiwonrw8BfJf4tsZmdKulvSBfIz9ErSKjN7KM638wedIJC+Jd+t8Z/OuTv2clcfOucyilA+z7g758fuSnvGtUaW/2ZmL0i6yczaOedmSrpEfnzjqJjWpDCuyergd70EykbK7FScsa3OuSxFfcA2s6bytyFpIh/4b020Us65pZKWRu2rkXwLZ1v5MXOXFrB5leB3fuOQCwwYsS1igchY2ZzrG3y4nyc/Nu4z+ee6Xn78ZWTcY0KtxEXwnHyX0uvlb91j8kE1P+vlr1c5+YDxbQFl4+kkaZ5z7scEy1eRtNbFH1u8Pt4GZtZfvvv/BvnxiSu1p4v1pfKvn4TPo5mdIX/LmzLygWiqfAtmtqRT5MdrJrK/SHhbV2ApL/Kai/sctef9Em/sZbwvFCLnL+G/NVHyq0NkeRVJG4Mvxz6Q/8LnS/nxt2vlh3pI/j2b33lK+JYvzrkN5u/5fK/8+OwLglXrzOwxSUOdn7U3Ure4r5/geW+QdGScw8R7z0px3rcAwkMoBdBK/m/Beu2ZuVLOuYXy9+IsI//B7xz5cY2jg8khHo23s4OB+fsuviXfZfRB59ydIVepII9Jukl+YqOZ2jPB0ZOxBUO4JvPkP9AdGUycsrSAspEZROcm0kXaOfe5md0s3zJ51r5UMgjsV8p3IS5sX5uD3/lNvpLvpCxFdL18IL3DOTc8eoWZNZYPpUnlnFtnZpFbv2yWb8X7soDyv5vZXPlW67NVhFBqZqfIP794k/PkZ5OkKvlMelU9tnDwOr9Xvmtxk6Cbb/T6xvLvg6L4q/w44DOcc7labM2sn3woTUTkS41EWmkjIS3Pc4xZfiDu31ld8a9zbB06ygfSx5xz/xNdMOgmf0+yKuSc+05Sr6DXx4ny7+H/kf8CrpL2DJPI9/UTbFtVe97fAIoZuu8ChzDzU+j/JXg4MZ9voH93zs13zj2gPbf7uORA1TFGJOzk22XVzKrIz3baWn4im4M5kMo5t1h+9slOZna6fLj7qKAAeKCuSdDl7cXg4V/zKxfM0ntb8DBPmC5A5ANkMrogJ7qvZfJdSJtbnNu4yAe0ZIjcDmRKnHXtknSMeJ6Sb8GqpYJbSSMi12tQMBNqvmLG/0bueVqU+/QukO86HW+8Y0acZYfLB42P4wTScvIzwcYq7G/EHyStjg2kgaJcl2XywbRFdJfXfPyffOvu6cF7JVbki5QFRTj+3mobu8D8zN5/kJ9YLhK2D/jr13lLnHOPyM9oLOX+u/a5/OvnjDibny4fYA/EOQSwHxBKgUOU+dtivCT/YfBnRd3yIxjTUyXOZpFlhY2h2l8i3dzijmUKxia+L/+h5R7nXL5B6iDzmHwXytfkP0w/HlsgxGvyV/lu3T3M7O9B61V0varJ3/qhkfy5nxi1rrmZ9Y73QTzYT+QLg48Kq4SZNTB/f8885yBoJYncZ7fAfQXjSF+WbxnK1doTtLzFmyhlb0S6PmfEHOME5TOpT5LMlG/l6iT//i7MRPkJg46VNCUIKLmYv7fnn+RvOxTRSX7m0vxuNRPPuOD3cIu6z6WZVZe/fU6sSPfi5tGBObje/5QPrbE2yHftzW+842pJR1je+wZfrsRbSRX0BnhMfqzoMzGBPXL/0siEXzvlJyCqIn87muhyx0i6Xb5b7PPa/243s5zJ5YIvJkfJd2EdF1Uuv9dvHfmJmZIiGN97RJxV8f6uRSaMeyjm9VBR/vUg+cnUABRDdN8FDgHmbyov+S+iqspP1tNKPggtknR5zIyUV0m60cw+lL/dxTb5CVQuk+/OOerA1DyPOUFdBgYf+CIh9RHn3Cb5Vpt0+e5ppaKed7TJQTfYg8lr8pN9HCU/Ru31OGVCuSbOuZ/MrIP82Lu/SrrSzN6RDwz15WfEjXwZ0DWmtf1I+Q+6j5rZLElfyd/b83D5mTuPlvQfFXAP1ChV5Gf9HG5ms+XHuW0Kjh2Z/GiN/D0SCzNYvnXqrmCc7ifyMw1fLj+O7kLtGW+2t8bJj5N9zMzOkn+eafKT87wtf92SLpjZdWoRymebWVf5QNRR0ndmNkN+zO5u+TqfJd/y+pCUM4b3j/KzUBfFRElXyLd+fWlmUySVldRFvqv4H6ILO+e2m9mTkvpKWmhmU+UD57ny1+sjxbRsO+e2mNmn8pM9jZf/W+AkTXXOfSE/83FrSbPN7GX50HOafPflKSp4PHKs++Rb6C6T9LWZvRns7yj5Waf/In8rFsm/5lpL6h+Ma52pPfcprSypr3Nuufa/ufLnMnKP1nPlu0DPl/RgVLnX5N+Xfw6+rFkoP9a9i/xY3EZJqk977XlPL5Lv8XCk/DnNlpTT9d0596KZdZQ/Z0vMbLL2jC1uIOll59wEASiWCKXAoSHSIpQtP3PiSvlumZMlvRGn2+5Lkg6Tb3FsLd8dcI38h937wwp1waQYneWfTx/57lqS9IL8B6y04PExyn/M0wr5D1gHDefcTjObIH9bg/H5TKYT2jVxzn1hZifJj3e9TD5YHCYfTD+Rn2Dn39G3ugjMkL8NSHv5mTMj9d4s3/3xcUmPRt/eoQBL5e+72UF+Jt/e8q1UW+UD3//K34twbQLP5xczayk/KdAF8sHi/+THef4kH0r3aWyac265mWXIzwp8kXwL+DL5azxd+ymU7o3gthuXBl8+9JbUQj6kmfz5eF/Sc865d4JNIl134315UtBxXBCABwfH6SvfS2OcfACKN6nPAPkvaq6Rvz6/yk941Em+xTled+ur5Ce8ulj+SwuTH5f6hXPuVTPrFtThWu2ZDfhc+cm6Eg6lwfv2PPkx4b0kXS3/Rd9P8q/92VFl1wcT+vxZ/trfFnXs4c65dxM97j4aIH/u+sj/vfxV/sueu2MmVttkZm3kv4g4S35YwbeSHgiWxZu5em+8K//3+kz5a1xRPtjPljQimPwtWnf5GYSv1Z7x90vlW/HHJKlOAEJgeT9DAAAOtKAFtLWk45y/dyFCYGZ3y7eAneecmx52fQ5GZvaJpCOdc2lh1wWJCVqNr5a/PdeKcGsDAHkxphQAQmZm6fItPtMJpAdGvHFsZvYH+dmM12s/3j+3OAvGFJ6hxO9NCgBAoei+CwAhCW6JcpR8V8ZsJfE2CyjUfDP7Wn5Gz+3yY+Qulu9efFV0V0bs4Zz7WXyhDQBIMkIpAITnTvnJgr6X1Duf21Rg/3hWfsKdG+VvM7FBfpKjh5xzmSHWCwCAQw5jSgEAAAAAoaELDgAAAAAgNKF1361Zs6ZLS0sL6/AAAAAAgP1o/vz565xztQorF1ooTUtLU1ZWVliHBwAAAADsR2b2fSLl6L4LAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAQSgEAAAAAoSGUAgAAAABCQygFAAAAAISmTNgVSMSOHTu0fv16/fbbb9q9e3fY1QGwl0qXLq3KlSurevXqSklJCbs6AAAAOAgc9KF0x44dWrlypapVq6a0tDSVLVtWZhZ2tQAUkXNOu3bt0ubNm7Vy5UrVr1+fYAoAAICDv/vu+vXrVa1aNdWsWVPlypUjkALFlJmpXLlyqlmzpqpVq6b169eHXSUAAAAcBA76UPrbb78pNTU17GoASKLU1FT99ttvYVcDAAAAB4GDPpTu3r1bZcuWDbsaAJKobNmyjA8HAACApGIQSiXRZRcoYXhPAwAAIKJYhFIAAAAAQMlEKAUAAAAAhIZQWkKNHz9eZqbx48eHXZWEmJkyMjLCrgYAAACAA+ygv09pYf78+uKwq1Cg+y/7Y1L2s3v3bo0dO1YvvPCCFi9erM2bN6tixYqqV6+emjZtqs6dO6tTp05JOVZxEBmTaGb65ptvdMwxx8Qt165dO2VmZkqSxo0bp969e+cps3XrVj311FOaOnWqvvzyS23cuFEVK1bUH/7wB7Vv317XXXedGjZsuL+eCgAAAHBIK/ah9FCwe/duXXTRRXrnnXdUq1YtdezYUUcddZS2bdumJUuW6PXXX9eKFStyhdJOnTrpjDPOUJ06dUKs+f5VpkwZ/f7773rmmWc0bNiwPOu/+eYbZWZm5pSLZ+7cuerSpYt+/PFH1a1bVxdccIGOPPJIbdu2TQsXLtTw4cM1fPhwzZ07V6eeeur+fkoAAADAIYdQWgxMnDhR77zzjpo3b673339flStXzrV+27Zt+vTTT3Mtq1KliqpUqXIgq3nAHXHEEapTp47GjRunv/3tbypTJvfL+emnn5YkXXzxxZo0aVKe7ZctW6Zzzz1XW7Zs0T/+8Q8NHDgwzz5WrlypO+64Q5s3b95/TwQAAOSWNS7sGgAHv/Rrwq5B0jCmtBj45JNPJEm9e/fOE0glqWLFimrXrl2uZQWNKZ0+fbrOPPNMVapUSdWrV9ell16qL7/8Ur1795aZacWKFTllV6xYITNT7969tWLFCnXr1k01a9ZU+fLllZ6erjfffDPP/jdt2qShQ4eqbdu2qlGjhsqUKaNatWrpkksu0Zw5c/btZMTo06ePVq9enaceu3bt0vjx49WyZUudeOKJcbf905/+pM2bN+vOO+/UnXfemSeQSlL9+vX10ksvqUWLFkmtNwAAAACPUFoMlC9fXpLvjrqvXnrpJZ1//vn6/PPP1bVrV914443asGGDWrVqpW+//Tbf7b7//ns1b95cP//8s/r06aNevXpp2bJl6tixo2bOnJmr7NKlSzVs2DBVqFBBV199tQYPHqwLLrhAH330kdq0aaN33nlnn59HRPfu3VWpUqWcVtGIqVOnas2aNerTp0/c7ZYvX673339f5cuX1x133FHocVJSUpJSXwAAAAC50X23GOjatatGjRqlUaNGae3aterUqZNOO+00HX300UXaz2+//aabb75Z5cuX15w5c9SkSZOcdX/5y1/ijsuMyMzM1IgRI3TbbbflLLvqqqvUpk0bDR8+PFdL7YknnqjVq1crNTU11z5Wr16tZs2aacCAATrvvPOKVPf8VK5cWd26ddP48eP1ww8/qG7dupKkp556Sqmpqbr88svjPq9Zs2ZJkk477TRVrVo1KXUBAAAAUHS0lBYDLVq00IsvvqgjjjhCL7zwgjp37qy0tDTVqFFDnTp10htvvJHQfqZMmaKNGzfq2muvzRVIJemee+5RjRo18t22UaNGuQKpJLVu3VqNGjXSZ599lmt5ampqnkAqSbVr19YVV1yhZcuWaeXKlQnVORF9+vTJmZ1Y8q267733nnr27KmKFSvG3ebnn3+WpJwQCwAAACAchNJiolu3blq5cqWmT5+uIUOG6KKLLlLp0qU1efJkXXLJJbr66qvlnCtwH59//rkkHyZjlStXTqeffnq+26anp8ddXqdOHW3YsCHP8tmzZ+vyyy9XvXr1lJKSIjOTmWnEiBGSpB9//LHAuhbF6aefrj/+8Y8aO3assrOz9fTTTys7OzvfrrsAAAAADh503y1GypYtqw4dOqhDhw6SpOzsbE2ZMkXXXHONnnvuOXXq1EmXXnppvttv2rRJkvLtrlqtWrV8t81vTGWpUqWUnZ2da9mkSZPUpUsXlS9fXu3bt9cxxxyjSpUqqVSpUsrMzNSHH36oHTt2FPhci6pPnz7q16+fpk2bpnHjxum0005T06ZN8y0fuVVOMsMxAAAAgKIjlBZjpUqVUqdOnbRkyRINGTJEH3zwQYGhNNKlduPGjXHX57e8qIYMGaIKFSpo8eLFatCgQa51t912mz788MOkHCfaVVddpTvvvFM33XSTfvzxR919990Flm/VqpUkKSsrS5s2bSrxt88BAAAADlZ03y0BImGzsO67kZbDjz/+OM+6nTt3au7cuUmpz9dff63GjRvnCaSS8szUmyxVq1ZVly5d9MMPP6hSpUrq3r17geUbNGigc845R9u3b9fw4cML3X+yW3YBAAAAeITSYmDixIl677338nSTlaR169bpiSeekCS1adOmwP107NhRVapU0dixY7Vo0aJc6+677z79+uuvSalv7dq19dVXX2nNmjW5lg8fPlwLFy5MyjHiGTp0qCZNmqTp06fHvZ9rrIcfflipqam6//77NWLECP3+++95yqxcuVJXXHFF0u+vCgAAAMCj+24x8Omnn2r06NGqXbu2WrVqpQYNGqhs2bJavny53n77bW3atEkdO3ZUly5dCtxPamqq/vWvf+mqq65Sy5Ytdfnll6tOnTr65JNPtHDhQrVq1UqzZs1SqVL79l1F//79NWjQIDVt2lRdunRRhQoV9PHHH+vzzz/X+eefr2nTpu3T/vNTv3591a9fP+HyJ5xwgqZPn64uXbpo0KBBGj16tM4++2wdeeSR2rp1qxYtWqTZs2fLzDR48OD9UmcAAADgUEcoLQZuu+021atXT5mZmZo3b56mTp0q55xq1Kihli1bqkePHurRo4fMrNB99ezZU9WrV9ff//53vfzyy0pJSVGbNm00a9Ys/e1vf5OkuLdzKYqBAwcqJSVFjz76qMaMGaPU1FS1bt1as2bN0tSpU/dbKN0bZ5xxhpYtW6annnpKU6dO1VtvvaUNGzaoYsVDBW/jAAAgAElEQVSKatSokQYOHKgbbrghbldkAAAAAPvOChuHuL+kp6e7rKysQsstXbpUJ5xwwgGo0aHNOadGjRpp27ZtOffwBPYn3tsAgHxljQu7BsDBL/2asGtQKDOb75yLf2/JKIwpPcRs2rQp7qQ9o0aN0nfffadOnTqFUCsAAAAAhyq67x5i5syZoyuvvFLt27dXw4YNtWPHDs2ePVtz585VvXr1dO+994ZdRQAAAACHkEJDqZmNlXSRpDXOuZPzKZMhabikcpI2OecKngYWoTnuuOOUkZGhWbNm6bXXXpOZqW7duurXr5/uuusuHX744WFXEQAAAMAhJJGW0vGSHpX0XLyVZlZb0r8kne2cW21mNZNXPSRbgwYN9Oqrr4ZdDQAAAACQlMCYUufcR5LWF1Ckm6RXnHOrg/LrklQ3AAAAAEAJl4yJjo6XVMfM5prZYjPrk4R9AgAAAAAOAcmY6KiUpMaSzpZUQdJcM5vjnPsytqCZ3SDpBkmqX79+Eg4NAAAAACjOktFSukrSdOfc1qDr7ofyITUP59yTzrl051x6rVq1knBoAAAAAEBxloxQ+pakVmZWxswqSmohaVkS9gsAAAAAKOESuSXMREkZkmqa2Q+S7pFUVpKcc4875xaY2TuSvgiWP+OcW7D/qgwAAAAAKCkKDaXOue4JlBkuf59SAAAAAAASlozuuwAAAAAA7BVCKQAAAAAgNIRS7DUzU0ZGRtjVKFYyMzNlZrr33nvDrgoAAABwUEjGfUrDlTUu7BoULP2apOzGzPIsK1eunOrUqaO2bdtq8ODBOuGEE5JyLBw8MjMz1a5du1zLypYtq6pVq+qYY45RixYt1K1bNzVv3jwpx+vdu7eeffZZLV++XGlpaUnZJwAAAFCQ4h9KDzH33HNPzr+3bdumzz77TM8995xee+01zZo1S6ecckqItcP+cvTRR6t3796SpJ07d2rt2rVasGCBRo4cqZEjR6pz584aP368DjvssHArCgAAABQRobSYidft8/bbb9dDDz2kUaNGafz48Qe8Ttj/0tLS4l77hQsXqlevXnrttde0detWTZs27cBXDgAAANgHjCktAdq3by9J+umnn3It37Rpk4YOHaq2bduqRo0aKlOmjGrVqqVLLrlEc+bMyXd/y5Yt07XXXqu0tDSlpKQoNTVVLVq00OjRoxOqz/Dhw1WqVCmdeeaZWr9+fa763Hrrrapbt67Kly+v448/Xg8++KC+++47mVlOS2BE7969ZWb67rvv9Mgjj6hx48aqUKFCrnGs2dnZevzxx9WsWTMddthhqlSpkpo1a6YxY8YoOzs71/5WrFgR9zgRGRkZebpJR48BXbhwoS688EJVrVpVFStWVNu2bfXJJ5/E3dcvv/yi6667TkcccYQqVKigU045Rc8++2xC568oTjnlFL3//vuqVauW3nnnHU2ePDnX+ldffVVdu3ZVWlqaypUrp0qVKum0007Tww8/nOf8mFlOHRs0aCAzk5nl6sY7b9483XjjjTrppJNUsWJFlS9fXscee6wGDhyoDRs2JP35AQAAoOSjpbQEmDFjhiTptNNOy7V86dKlGjZsmNq0aaOrr75aFStW1KpVqzRlyhRNmzZNb7zxhs4777xc27z11lvq2rWrduzYofPOO0/du3fXjh07NH/+fD3yyCPq379/vvXIzs7WrbfeqkceeUSXXXaZJkyYoPLly0uStm/frrPOOksLFixQ06ZN1bNnT23atEkPPPCAPvroowKfX//+/fXJJ5+oc+fOuvjii1W6dOmcdVdddZVefPFF1atXT9dff73MTJMmTdItt9yiWbNmacKECUU6l/nJysrSQw89pIyMDN1yyy1atWqVXn75ZZ199tlauHChjjvuuJyy69atU8uWLfXdd9+pVatWatWqlX7++WfddNNN6tChQ1LqE+3www/XjTfeqKFDh2rChAm69NJLc9YNGTJEKSkp6tChgw4//HBt2bJFM2bMUP/+/TVv3jw9//zzOWXvueceTZ48WYsWLVL//v1VtWpVScr5LUnPPPOMpk2bpjZt2qhjx47avXu3FixYoH/+85+aNm2aPv30U1WuXDnpzxEAAAAlF6G0mInuwrl9+3bNmzdPH3zwgdq3b6/BgwfnKnviiSdq9erVSk1NzbV89erVatasmQYMGJArlK5bt049evSQc04zZ85UmzZt8myXn+3bt6tnz556/fXX1bdvX40ePVqlSu1piB8+fLgWLFignj176vnnn89pkfzLX/6iZs2aFficFy9erCVLlqh27dq5lk+cOFEvvvii0tPTNXPmzJzxlEOHDtVZZ52lF198URdeeKF69OhR4P4T8fbbb+vf//63OnfunLOsQ4cO6tWrl0aPHq3HHnssZ/ldd92l7777ToMGDdLw4cNzlvft21etWrXa57rEk5GRoaFDh+qzzz7Ltfzdd99VvXr1ci1zzunGG2/UU089pb59++r000+X5F9bK1as0KJFi3TrrbfGnejor3/9q8aMGZOnRXnChAm68sor9dhjj+nOO+9M7pMDAABAiUb33WLmvvvuy/l54IEH9MEHH6hBgwbq3r27qlSpkqtsampqnkAqSbVr19YVV1yhZcuWaeXKlTnLn332WW3evFkDBgzIE0gj28Wzfv16nXPOOZo0aZIeeOABPfLII7kCaWTfpUuX1ogRI3IFmnr16umOO+4o8Dn/+c9/jnvssWPHSpJGjhyZa4KfSpUqaeTIkZKkp59+usB9J+qss87KFUglqXv37ipfvnyuILhr1y5NmDBBVatW1d///vdc5dPT03XttdcmpT6xjjrqKEnS2rVrcy2PDaSS76bbr18/SdL06dOLdJy6devGnQm6Z8+eqlmzZpH3BwAAABBKixnnXM7Pzp07c7qOXnvttRowYECe8rNnz9bll1+uevXqKSUlJWec4IgRIyRJP/74Y07ZuXPnSpIuuOCChOvzyy+/6Mwzz9S8efP0wgsvxA2Ymzdv1rfffqtjjz1WRxxxRJ71rVu3LvAYZ5xxRtzlCxYsUPny5dWyZcu421SsWFGff/55gs+kYPFacyNjdKPHUi5btkzbtm1T8+bNc7ouR9tf93V1zkmSfv/991zLf/31Vw0ePFiNGzfWYYcdlnP9//jHP0rKff0TsWvXLj366KNq1aqVqlevrtKlS+fsc926dUXeHwAAAED33WKsbNmyatKkiV599VUdddRRGj16tPr166cGDRpIkiZNmqQuXbqofPnyat++vY455hhVqlRJpUqVUmZmpj788EPt2LEjZ38bN26UJNWsWTPhOqxevVqbN29W3bp18+2aunnzZkm5xyZGq1atWoHHiG0Bjti0aZNq1aqVp1VWkkqVKqVq1arlmfxpb6WkpMRdXqpUKe3evTtXnSSpevXqccvnt3xfRZ5ndOjfuHGjmjVrpuXLl6t58+bq1auXqlevrjJlymjjxo0aPXp0ruufiCuuuEKTJk1Sw4YN1bFjR9WuXTvn3IwaNarI+wMAAAAIpSVApUqVdOKJJ2rOnDn67LPPckLpkCFDVKFCBS1evDhnWcRtt92mDz/8MNeySGhct25dwsdu0qSJrr/+evXu3Vtt2rTRBx98oIYNG+YqE+lCHAm9sfJbXpgqVapo06ZNys7OzhNMnXPauHFjru7LkTKRVsVY27dv36t6xNZJUq5Zh6Plt3xfzZw5U1Luya6efvppLV++XA8++KBuv/32XOW/+OKLhGdTjsjKytKkSZN08cUXa9KkSbkmnJKkhx9+eC9rDwAAgEMZ3XdLiEiwK1euXM6yr7/+Wo0bN84TSKU9ISZapJtsUe91eeWVV+qll17STz/9pDZt2ujrr7/OtT41NVUNGzbUN998o19++SXP9oXNvpufpk2b6r///W9Ot+Non376qbZu3apTTz01Z1mkRTZe6+m2bdu0ZMmSvapHtOOPP14VK1bUZ599FjfkZmZm7vMxYq1Zs0ZPPPGEJH8tIiLXoWPHjnm2iXf9JeUEzXjBPbK/iy66KE8gXbRoEbeEAQAAwF4hlJYA06dP19KlS1W2bNlc4ytr166tr776SmvWrMlVfvjw4Vq4cGGe/Vx99dVKTU3VyJEj4wbFgmbf7dKli1599VWtW7dObdu2zRPwevXqpd27d2vQoEG5As+qVav04IMPJvxco0UmDRo0aJC2bduWs3zbtm267bbbJEnXXXddzvLKlSvr+OOP18cff6z//Oc/ufY1ePBgbdmyZa/qEa1s2bLq2bOnNm7cqCFDhuRal5WVlTM5U7IsWrRI7du317p163TOOefkmowpMjlUbBBeunRpnkmYImrUqCEp/ljT/Pa3efNm3XTTTXv7FAAAAHCIo/tuMRN9S5hdu3bpq6++0ptvvilJGjZsWK4xhf3799egQYPUtGlTdenSRRUqVNDHH3+szz//XOeff36eFtGaNWvqxRdfVJcuXdSuXTudf/75aty4sXbu3KkFCxZo5cqVecJctEsuuURTpkxRp06dlJGRoffff19NmjSRJN1xxx2aPHmyXnjhBS1ZskQdOnTQpk2b9Morr6hFixZ666234o4NLUiPHj00ZcoUvfLKKzrppJN06aWXysw0efJkLV++XFdccYV69uyZa5vbb79d1113nVq2bKlu3bqpQoUKmjFjhrZs2aImTZpo0aJFRapDPMOGDdOMGTP00EMPae7cuTn3KX355Zd17rnnaurUqUXe54oVK3Ku/a5du7Ru3TrNnz9f8+fPlyR17dpVY8eOzTUz7jXXXKNRo0bplltu0QcffKBGjRppxYoVeu2113TBBRfo9ddfz3Ocs88+W8OHD9f111+vzp07q0KFCqpatar69u2rtm3bqkmTJpo4caJ+/PFHtWrVShs2bNCkSZOUlpamI488cu9OGAAAAA5phNJi5r777sv5d+nSpVWrVi1dcMEF6tu3r9q3b5+r7MCBA5WSkqJHH31UY8aMUWpqqlq3bq1Zs2Zp6tSpcbvpXnjhhcrKytIDDzygGTNmaPr06apYsaJOPvlk3XrrrYXW79xzz9Xbb7+tiy++WO3atdP06dPVrFkzVahQQTNnztTdd9+tV199VSNHjlSDBg1055136vzzz9dbb70V9/Y1hZk4caLatm2rsWPH5nRhPeGEEzRw4EDdfPPNecpfe+21cs7pn//8p5544glVq1ZNHTt21LBhw/Lc8mVv1axZU7Nnz9Zdd92lN954Q1lZWTruuOM0ZswYpaWl7VUo/f7773OufZkyZVStWjU1bNhQAwYMUPfu3ePODtygQQNlZmZq8ODBevPNN+Wc0/HHH6+RI0fq3HPPjRtKzz33XI0YMUJPPfWUHnroIe3cuVNHH320+vbtq9KlS+u9997T7bffrjfffFNz585V3bp11atXLw0ZMkQnn3xy0U8WAAAADnmW36Qv+1t6errLysoqtNzSpUt1wgknHIAaISzPPfecrr76aj3++OO68cYbw64ODhDe2wCAfGWNC7sGwMEv/Zqwa1AoM5vvnEsvrBxjSnHAxJvk6JdfftHQoUNVpkwZXXzxxSHUCgAAAECY6L6LA6ZTp07Kzs7W6aefrsqVK2vVqlWaMmWKNm3apPvvv58xiQAAAMAhiFCKA6Zbt2567rnnNH78eG3ZskWpqak69dRT1bdvX1122WVhVw8AAABACAilOGD69eunfv36hV0NAAAAAAcRxpQCAAAAAEJDKAUAAAAAhIZQCgAAAAAITbEIpWHdSxXA/sF7GgAAABEHfSgtXbq0du3aFXY1ACTRrl27VLp06bCrAQAAgIPAQR9KK1eurM2bN4ddDQBJtHnzZlWuXDnsagAAAOAgcNCH0urVq2vDhg1at26ddu7cSbc/oJhyzmnnzp1at26dNmzYoOrVq4ddJQAAABwEDvr7lKakpKh+/fpav369VqxYod27d4ddJQB7qXTp0qpcubLq16+vlJSUsKsDAACAg8BBH0olH0zr1KmjOnXqhF0VAAAAAEASHfTddwEAAAAAJRehFAAAAAAQGkIpAAAAACA0hFIAAAAAQGgIpQAAAACA0BBKAQAAAAChIZQCAAAAAEJDKAUAAAAAhIZQCgAAAAAITaGh1MzGmtkaM/uykHLNzOx3M+uSvOoBAAAAAEqyRFpKx0s6r6ACZlZa0gOS3k1CnQAAAAAAh4hCQ6lz7iNJ6wsp9idJr0lak4xKAQAAAAAODfs8ptTMjpLUSdKYfa8OAAAAAOBQkoyJjkZJutM5l11YQTO7wcyyzCxr7dq1STg0AAAAAKA4K5OEfaRLesnMJKmmpAvM7Hfn3OTYgs65JyU9KUnp6ekuCccGAAAAABRj+xxKnXMNIv82s/GS3owXSAEAAAAAiFVoKDWziZIyJNU0sx8k3SOprCQ55x7fr7UDAAAAAJRohYZS51z3RHfmnOu9T7UBAAAAABxSkjHREQAAAAAAe4VQCgAAAAAIDaEUAAAAABAaQikAAAAAIDSEUgAAAABAaAilAAAAAIDQEEoBAAAAAKEhlAIAAAAAQkMoBQAAAACEhlAKAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAQSgEAAAAAoSGUAgAAAABCQygFAAAAAISGUAoAAAAACA2hFAAAAAAQGkIpAAAAACA0hFIAAAAAQGgIpQAAAACA0BBKAQAAAAChIZQCAAAAAEJDKAUAAAAAhIZQCgAAAAAIDaEUAAAAABAaQikAAAAAIDSEUgAAAABAaAilAAAAAIDQEEoBAAAAAKEhlAIAAAAAQkMoBQAAAACEhlAKAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAQSgEAAAAAoSGUAgAAAABCQygFAAAAAISm0FBqZmPNbI2ZfZnP+qvMbLGZfWlm880sPfnVBAAAAACURIm0lI6XdF4B67+W1Mo5d7Kkv0p6Ogn1AgAAAAAcAsoUVsA595GZpRWw/tOoh7MkHbXv1QIAAAAAHAqSPab0RklTk7xPAAAAAEAJVWhLaaLMLEPSdZJaFVDmBkk3SFL9+vWTdWgAAAAAQDGVlJZSM2ss6RlJHZ1zv+ZXzjn3pHMu3TmXXqtWrWQcGgAAAABQjO1zKDWz+pJel3SVc+7rfa8SAAAAAOBQUWj3XTObKClDUk0z+0HSPZLKSpJz7nFJd0uqIekxM5Ok351z3BYGAAAAAFCoRGbf7V7I+uslXZ+0GgEAAAAADhnJnn0XAAAAAICEJW32XQAAACAZXv/8x7CrABz0LitBAyZpKQUAAAAAhIZQCgAAAAAIDaEUAAAAABAaQikAAAAAIDSEUgAAAABAaAilAAAAAIDQEEoBAAAAAKEhlAIAAAAAQkMoBQAAAACEhlAKAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAQSgEAAAAAoSGUAgAAAABCQygFAAAAAISGUAoAAAAACA2hFAAAAAAQGkIpAAAAACA0hFIAAAAAQGgIpQAAAACA0BBKAQAAAAChIZQCAAAAAEJDKAUAAAAAhIZQCgAAAAAIDaEUAAAAABAaQikAAAAAIDSEUgAAAABAaAilAAAAAIDQEEoBAAAAAKEhlAIAAAAAQkMoBQAAAACEhlAKAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAUGkrNbKyZrTGzL/NZb2b2sJl9ZWafm9mpya8mAAAAAKAkSqSldLyk8wpYf5mkoyWdJOk6SeP2vVoAAAAAgENBoaHUOfeRpPUFFLlQ0gvOWyCpjJnVS1YFAQAAAAAlVzLGlNaVtCrq8Q/BMgAAAAAACnRAJzoysxvMLMvMstauXXsgDw0AAAAAOAglI5T+ICm6u27dYFkezrknnXPpzrn0WrVqJeHQAAAAAIDiLBmh9G1JPSUpmHk32zm3quBNAAAAAACQyhRWwMwmSsqQVNPMfpB0j6SykuSce1zSa5LamdlXknZKuma/1RYAAAAAUKIUGkqdc90LWe8k/U/SagQAAAAAOGQc0ImOAAAAAACIRigFAAAAAISGUAoAAAAACA2hFAAAAAAQGkIpAAAAACA0hFIAAAAAQGgIpQAAAACA0BBKAQAAAAChIZQCAAAAAEJDKAUAAAAAhIZQCgAAAAAIDaEUAAAAABAaQikAAAAAIDSEUgAAAABAaAilAAAAAIDQEEoBAAAAAKEhlAIAAAAAQkMoBQAAAACEhlAKAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAQSgEAAAAAoSGUAgAAAABCQygFAAAAAISGUAoAAAAACA2hFAAAAAAQGkIpAAAAACA0hFIAAAAAQGgIpQAAAACA0BBKAQAAAAChIZQCAAAAAEJDKAUAAAAAhIZQCgAAAAAIDaEUAAAAABAaQikAAAAAIDRlwq4AgOLvz68vDrsKQLFw/2V/DLsKAAAcdGgpBQAAAACEhlAKAAAAAAgNoRQAAAAAEJqEQqmZnWdmX5rZUjMbHGd9bTObYWZfmdnXZnZT8qsKAAAAAChpCg2lZpYi6XFJ50tqLKmLmZ0aU6yvpCzn3ImSzpT0DzOrkOzKAgAAAABKlkRaSk+XtMQ5t8o5t0vSy5IujCnzg6TKZmaSDpO0TtKOpNYUAAAAAFDiJBJK60paFfX4h2BZtKcknSjpJ0mLJfV3zmXH7sjMbjCzLDPLWrt27V5WGQAAAABQUiRroqM/S/pC0pGSTpH0qJmlxhZyzj3pnEt3zqXXqlUrSYcGAAAAABRXiYTSHyTVi3pcN1gWrbWkfzvvP5KWy7ecAgAAAACQr0RC6WeSTjazumZWVtIVkqbFlPlW0tmSZGZHyAfSFUmsJwAAAACgBCpTWAHn3HYzu1nSdPkQ+4JzLity2xfn3OOS/ibpBTNbKqm0pCHOudX7sd4AAAAAgBKg0FAqSc65tyW9HbPs8ah/r5Z0TnKrBgAAAAAo6ZI10REAAAAAAEVGKAUAAAAAhIZQCgAAAAAIDaEUAAAAABAaQikAAAAAIDSEUgAAAABAaAilAAAAAIDQEEoBAAAAAKEhlAIAAAAAQkMoBQAAAACEhlAKAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAQSgEAAAAAoSGUAgAAAABCQygFAAAAAISGUAoAAAAACA2hFAAAAAAQGkIpAAAAACA0hFIAAAAAQGgIpQAAAACA0BBKAQAAAAChIZQCAAAAAEJDKAUAAAAAhIZQCgAAAAAIDaEUAAAAABAaQikAAAAAIDSEUgAAAABAaAilAAAAAIDQEEoBAAAAAKEhlAIAAAAAQkMoBQAAAACEhlAKAAAAAAgNoRQAAAAAEBpCKQAAAAAgNIRSAAAAAEBoCKUAAAAAgNAQSgEAAAAAoUkolJrZeWb2pZktNbPB+ZTJMLN5ZrbIzD5KbjUBAAAAACVRmcIKmFmKpMcltZa0WtIcM3vXObcgqkxtSf+SdLZzbrWZ1dxfFQYAAAAAlByJtJSeLmmJc26Vc26XpJclXRhTppukV5xzqyXJObcuudUEAAAAAJREiYTSupJWRT3+IVgW7XhJdcxsrpktNrM+yaogAAAAAKDkKrT7boJKSWos6WxJFSTNNbM5zrkvowuZ2Q2SbpCk+vXrJ+nQAAAAAIDiKpGW0h8k1Yt6XDdYFm2VpOnOua1B190P5UNqLs65J51z6c659Fq1au1tnQEAAAAAJUQiofQzSSebWV0zKyvpCknTYsq8JamVmZUxs4qSWkhaltyqAgAAAABKmkK77zrntpvZzZKmy4fYF5xzWWZ2U7D+cefcAjN7R9IXkspKeiZ6dl4AAAAAAOJJaEypc+5tSW/HLHs85vFwScOTVzUAAAAAQEmXSPddAAAAAAD2C0IpAAAAACA0hFIAAAAAQGgIpQAAAACA0BBKAQAAAAChIZQCAAAAAEJDKAUAAAAAhIZQCgAAAAAIDaEUAAAAABAaQimA/2/vfkMsO+86gH9/mBhoK8UmW8XMtupbYwhxQyhWTUEwyeKL2mCsbcCakiaUgoraoBgDvvKFIhHrEloVXImBNjSlbExSipSKbdiksdkkNb4p7gpp1gjBP4Rkzc8X9669mczunJnc2efu3c8HLnP+PGfmmfObcx6+95x7BgAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGCYSaG0qq6vqmNV9WxV3XmWdtdU1amquml5XQQAAGBdbRtKq+qSJIeS3JDkyiQ3VdXVW7T7niR/mOSRZXcSAACA9TTlSum1SZ7u7uPd/WqS+5Mc3KLdJ5J8LskLS+wfAAAAa2xKKN1Icnxh/sR82f+rqsuTvD/Jny+vawAAAKy7ZT3o6E+SfLK7Xztbo6q6raqOVtXRkydPLulHAwAAcL66aEKbE0n2L8xvzJctOpDkb6sqSS5LcmNVneruzy826u57k9ybJAcOHOjddhoAAID1MCWUPpbkiqraSPKdJDcnuX2xQXf/yOnpqvqrJF/cHEgBAABgs21DaXe/XFV3JHk4s9t9D3f30aq6fb7+0B73EQAAgDU15UppuvtIkiOblm0ZRrv7V958twAAALgQLOtBRwAAALBjQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlMID7bIAAAmVSURBVAIAADCMUAoAAMAwQikAAADDXDS6A8D575oXHxzdBThP/PjoDgDAynGlFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIaZFEqr6vqqOlZVz1bVnVusv6Wqnpq3ebyqDiy/qwAAAKybi7ZrUFWXJDmU5KeSPJ/kH6vqke5+YqHZc0ne290vVdUNST6d5Kq96DAAAADrY8qV0muTPN3dx7v71ST3Jzm42KC7v97dL81nv5rk8uV2EwAAgHU0JZRuJDm+MH9ivuxMPpbkC1utqKrbqupoVR09efLk9F4CAACwlpb6oKOqui7JrUl+e6v13X1vdx/o7gP79u1b5o8GAADgPLTtZ0ozuzK6f2F+Y77sdarqyiSfSXJDd7+4nO4BAACwzqZcKX0syRVVtVFVFye5OclDiw2q6l1JHkhyS3c/t/xuAgAAsI62vVLa3S9X1R1JHs4sxB7u7qNVdft8/aEkdyW5NMmnqipJTnW3fwsDAADAWU25fTfdfSTJkU3LDi1MfzTJR5fbNQAAANbdUh90BAAAADshlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDTAqlVXV9VR2rqmer6s4t1ldV3VNVz1TVN6rq6uV3FQAAgHWzbSitqkuSHEpyQ5Irk9y0Rej8hSTvTvJjSW5N8pdL7icAAABraMqV0muTPN3dx7v71ST3Jzm4qc3BJId75okkF1XV/iX3FQAAgDUzJZRuJDm+MH9ivmynbQAAAOB1LjqXP6yqbkty23z2v6rqn8/lz9+Fy5L8++hO8DpqsprUZfWoySq67ffUZfWoyWpSl9WjJqvm/BhT3j2l0ZRQeiLJ4q24G/NlW7X52lnapLvvTXLvlI6tgqo62t0HRveD71KT1aQuq0dNVpO6rB41WU3qsnrUZPWsU02m3L77WJIrqmqjqi5OcnOShza1OZLkQ0kyfwjSa919PAAAAHAW214p7e6Xq+qOJA9nFmIPd/fRqrp9vv5Qks8leV9VPZPklSQf2cM+AwAAsCYmfaa0u49kdjV0cdmhhelO8vHldm0lnDe3Gl9A1GQ1qcvqUZPVpC6rR01Wk7qsHjVZPWtTk5rlSQAAADj3pnymFAAAAPbEBR9Kq+odVfVoVT1VVY9U1fefod23522erKqjO92e6abs06raX1VfqapjVfVcVX1yYd3dVfVv81o9WVU3ntvfYH1U1fXzffxsVd25xfqqqnuq6pmq+sb8QWeTtmX3JtTllvnxc6yqHq+qAwvrtjyX8eZMqMl1VfXSwnnprqnbsjsTavJbC/U4VlX/W1XvmK9znOyBqvqLqnqhqo6dYb0xZYAJdTGmnGMTarJ+Y0p3X9CvJH+a5Dfm07+e5J4ztPt2kst2u73XcmuS5AeTXDmf/r4k/5Lkqvn83Ul+c/Tvcb6/klwy/7vfn+TiJEeTXL2pzQeSPJikklyd5J+mbuu1p3W5Nsnb59M3JHlyYd2W5zKvPa/JdUm+uJttvfamJpva/3ySLy/MO072pi4/PR8rjp1hvTFlNetiTFm9mqzdmHLBXylNcjDJX8+nD8/nz+X2vNG2+7S7n+/ub86n/zPJN5Ncfs56eGG4NsnT3X28u19Ncn/eWIuDmT2Ru7v7iSQXVdX+iduyO9vu2+7+ene/NJ/9ahwbe+3N/L07VvbGTvfrB5Pcd056dgHr7q8k+Y+zNDGmDLBdXYwp596EY+VMzttjRShN9nX3ySSZf33nGdp1ktO3lH5iF9sz3Y72aVX9cJJrMjtRnvbxqvpWVf1NVV26Vx1dcxtJFv/f8In5siltpmzL7ux0334syRcW5s90LmP3ptbkPfNbqr5cVVftcFt2ZvJ+raq3JLk+s39vd5rjZAxjyuozpqyOtRpTJv1LmPNdVX0ps9s9N/vdHXyb93T381X1ziR/V1Xf6u5Hl9PDC8+SapKqeluSzyb5tYV38f4syR9kdqK8O8k9ST60687Ceaqqrktya5L3Lix2Lhvj8ST7u/t/qurnkny+qn50dKdIMrt19x+6e/GqhOMENjGmrJS1G1MuiFDa3T97pnVVdbKq9nX3yaral+SFM3yP5+dfX6iqz2Z2Ze7RJJO25/WWUZOqujizd7bv6+4HFr73yYU2h5L8/dI6fmE5kdlnEk7bmC/bqs3XNrW5eMK27M6UuqSqrkzymSQ3dPeLp5ef5VzG7m1bk/nHDE5PP1xVr2T2xtykerJjO9mvv5RNt+46ToYxpqwoY8pqWccxxe27yZEkH55PfzjJQ5sbVNVb57f3pKremtltPs9M3Z4dm1KTyuzk+Gx3/9GmdYu3+34g360VO/NYkiuqamP+BsDNeWMtjmR+FXr+lMTXuvv4xG3ZnW33bVW9K8kDSW7p7ucWlp/tXMbuTanJvoXpn0jytszecHOs7I1J+7Wq3p7kZzJ7uM7pZY6TcYwpK8iYsnrWcUy5IK6UbuP3k9xfVb+a5DtJfjFJquqHkny6u29M8gOZXRbvJG/J7EPDD55te96UKTX5ySS3JHmqqp6cb/c73X0kyR/P39H73iT/mtmtJuxQd79cVXckeTizN7AOd/fRqrp9vv5QZleq31dVzyR5JclHzrbtiN9j3Uysy11JLk3yqdn7NznV3Qdy9nMZuzSxJh+sqtvmm7yS5Je7+1SSU46V5ZtYkyR5f5JHuvu/FzZ3nOyRqrovs6eGXlZVJzIb7y9OjCkjTaiLMeUcm1CTtRtTqmePDwYAAIBzzu27AAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADD/B9s1rgFwzptKAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "nbins=4\n", - "MC_Hlt2RareCharm_TOS=MC_tuple_dict[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n", - "data_Hlt2RareCharm_TOS_under=data_tuple_bkg_under[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]\n", - "data_Hlt2RareCharm_TOS_over=data_tuple_bkg_over[\"Ds_Hlt2RareCharmD2Pi\"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+\"OSDecision_TOS\"]" + "MC_Hlt2Phys_TOS=MC_tuple_sig[\"Ds_Hlt2Phys_TOS\"]\n", + "data_Hlt2Phys_TOS=data_tuple_bkg[\"Ds_Hlt2Phys_TOS\"]\n", + "\n", + "plot_sb_comparison(nbins=4, particle=\"Ds\",variable=\"Hlt2 Phys TOS\", \n", + " MC_sig=MC_Hlt2Phys_TOS, data_bkg=data_Hlt2Phys_TOS,\n", + " width_MC=0.5, width_data=0.5)" ] }, { @@ -1037,229 +715,6 @@ "metadata": {}, "outputs": [], "source": [ - "h_mc= r.TH1F(\"Hlt2 RareCharm TOS MC/data comparison under\", \"Hlt2 RareCharm TOS MC/data under Ds mass comparison\",nbins, 0, 2)\n", - "\n", - "for i in range(len(MC_Hlt2RareCharm_TOS)):\n", - " h_mc.Fill(MC_Hlt2RareCharm_TOS[i]) \n", - "\n", - "n1=h_mc.Integral(\"width\")\n", - "h_mc.Scale(1/n1)\n", - "h_mc.Integral(\"width\");" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [], - "source": [ - "h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, 2)\n", - "h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, 2)\n", - "for i in range(len(data_Hlt2RareCharm_TOS_under)):\n", - " h_data_under.Fill(data_Hlt2RareCharm_TOS_under[i])\n", - "for i in range(len(data_Hlt2RareCharm_TOS_over)):\n", - " h_data_over.Fill(data_Hlt2RareCharm_TOS_over[i])\n", - " \n", - "n2=h_data_under.Integral(\"width\")\n", - "h_data_under.Scale(1/n2)\n", - "h_data_under.Integral(\"width\");\n", - "n3=h_data_over.Integral(\"width\")\n", - "h_data_over.Scale(1/n3)\n", - "h_data_over.Integral(\"width\");" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6UAAAHnCAYAAABALvsIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3XeUFFXax/HfMzAMQYYsIFFRzARBUDKLgiiSHAVUFAPoumYM7BoIuoZFXUR8DSigq4IsKwIGWAHJQUFQyYuKgIKoREXyff+41WNPT/dMDwwW4vdzzpyBqlu3boXuqaduMuecAAAAAAAIQ0rYBQAAAAAA/HERlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQij80M3NmNi3scvxemNnNwTnLCLssOLzMbLGZbQ27HMkws9uD+7Jj2GUJw+/pWkmSmXUMrtfth3EfdYJ9DDpc+zgacd7C83v7HAP5jaAUv3vBH9AcJ9w1szVBuupJ5NcvSNsiwfrKZnafmf3bzFab2YEg/Yl5KHOPSLmT/Uk27yOJmY2JOoZ7ckj3l6h07wTLCpnZ92a238yq5bKfkma208x+NrMScdafnkw5EuT9dh6v1dsx26eY2RVm9p6ZbTSzPWb2g5lNC447LYd91zKzEWb2lZntMrPdZrbezD4ws/5mVioPx1HdzJ41s5Vm9ouZ7Q3KM93MHjezqnk5L79nUUGsM7PxOaSrFZUu4cOimdU2s+fNbLmZbY+6Tm+b2ZVmlppgu5OCvB/Kj+M6VGa21cwWh10OAMAfT8GwCwD8DtWX9LAkJ+krSdsklcxjHosl9Y9ZVl3S1ZK+ljTikEp45Nkn6TpJ/0iwvmeQJvM7yTm3x8xekdQ72PbBHPK/QlIRSSOcc9virO8V9e/rzWygcy7ZQH+U/PWKdoGkhpImSZoXs25F5B9mVk7SWEmNJf0o6T1J6yWVC/IYIulmM2vnnPsiOhMz6yDp3/LnZIqkMZL2SqoS5HeepAmSFuR2AGbWUNIHkopLmiPpXUk7JVWUdI6keyR9LGlt1GYdJcUNpo4i+yRdaGbHOee+jbO+l/znPO69YmYpkh6XdFeQZpb8PRE5ty0kdZDUQ/56xeoU/H7roI8AwNHij/CdCyREUArk3QJJzSR96pzbbr75b/O8ZOCcW6yYQCeomb1a0hrnXL98KemR4x1JHc2suXNuevQKMztbUm354K1TzHYvygel15hZf+fc/gT5Xx+VPgszKyypu6Tv5AOzKyW1lDQ1mYI750bFybOkfFA60TkXt5mbmRWSDxobSvqPpGudc9uj1qdJekLSzZImmVl959zWYF0BSS/If0e3dc5NipN/fUnrkjkGSc/KB6Q3OOfinaNT5APeTM65NUnm/Xv2jvyD4DWS/h69wsyKyL/smCypUYLtH5MPSP8nKcM591lMHhbkf32cbSV/v3/tnFt0sAcA4OjwB/nOBRKi+S4QxczWSOob/PfDeM1nnXPrnXMzowOM37B8ZwTlGRI0SX0raOJ6IAhSZGaNzOzloCnhL0Gzz5Vm9piZFU+Qr5nZVUGT0i1B085vzGy0mdVJolzHmtlH5pva3honyQj5oKdnnHU9Je2XNCx2hXNulaTpkirL1yzG23d9SXUkLXHOzY2TJENSKUmvSXopap+HWy/5gPQzSd1i7xfn3G7n3C2SJkqqIem+qNU1JJWX9L94AWmw/QLn3He5FSIIfutJ2iVpaIK8VsSpqY3bv8nMigb30tdBM9XVZtbXzMolaL48KFheJ7jHFgX35fdm9kpQmxy7jyZmNszMVkTdwyvM7FEzOya3Y86D2ZKWS7ouCCCjXSrfAiLuOTOzM+QD0p8lXRAbkEqS88ZK6hxn++Pk74+xyRbWzK41s0+D87HRzF4ys7IJ0hYzsz5mNjU41/vM7Ecze9/MWsak7Rh8x5WQVNuyNkcfFJWuu5mNNbO15puh7zCz+WbWM875S/aY/mS+CfkOM9tmZhOCcxsvbSEzu8PMFpjZT+ab639sZtflcZ/VzGyoma0LjuM7M3szdr9m1iU4B3fHLO8ULN9n/gVV9LpJwfdx3OsSkzbSNaCsmd1vZv8Lru3Xwb1eNMF2JwTlXxN8Br8331WiVpy0x5vZwOA8bQ+Od13w2auR3BmTzKygmQ0PyvuqJWiSHme7Zub/Tm00/3flR/PdD7L1/zazq81sTnAv7DT/HXSHmWWrQLGgqXlw7p43s2+DY/vUzC4O0hQ1s39EXedVZnZNnLwy+zgnez/m9bxaVF9dMzsz+Bz9ECyrE6TJ9p1rZgXM7M5g3c7gHG4ws8kJzmHjoMw/BPfGl2b2z3j3Y9T9Vzo4z8uDbb41s8GJ7j/gcKGmFMhqkHzNRnNJr0haE2ppEjtdvtnofPmH5pLyD8eSdJN8886Z8g+8BSU1kHSvpNZm1sg5tyuSkfkmiG/KB2/fyTcZ/V6++WEr+WaHCfuZme9LO1FSJUmXOufiNUX8Tr7W8BIzu8U5tyXY9hhJ3YLt1yfYxVD563G9fLPTWNdHpYsn0nR3uKRlkr6U1MnMyjrnfkh0XPkgEvg+5pzbm0O6h+QD7uvM7F7n3AH5AFKSyptZ+iG+ANkv/0IgTVI1HcI9HTwcvi/fUmCppNGSisrfc2fnsvnfJLWRb4b8vvw9epWk082sQXDcETfL37Mz5Zu2FpQP4PpIOs/Mmjjndh/sccQYKukp+Xt9ctTynvKfg3EJtuspyST9yzn3ZU47SFDWjsH2SQWlZtZfvgn7D/IvcH6WdJGkGYrf5K+KpH7y5/B1STskHSffnHiymXV1zv07SLtCvjtBH0lbJT0flU908/THJX0r3wz9B0npklrLt1CoJemWZI4lynmSBsrXWD8j6TRJ7SU1N7MWzrlPoo6/qKT/yt83C+VbEuyXv6deMrO6zrmbc9uhmZ0m/6KrrPx9+JqkEyRdIqmdmV3knJsWJJ8q3yy7VVDOiFbB7wLyTbTfDvIuJKmJfCuavHy3vCzpXPnPRuS69pF0rpmd55zbF1X+JvLfg4Xlv1NXSjpW/iXKhWbWxjk3MyrvNpKulTRN0ofy3wWnSOoq6eLgs7c6p8IF39Njgrwedc79LZmDMrPe8udtl/zn6Ev5v1WN5FsFvR2V9v8k/VnSRvm/vbslXSz/2fyTmXWI+Y6QpGLy9/9uSf+Svx+vlDTWzFrL3/8V5P+mpcj/rRlmZtsS/J1K+n7UwZ/XMyXNDX5elH9hujPuCfSeCc7LUvl7/if5632O/H0SfQ67Bedhr/x387fy5/p2Se3NrLFzbmOcfTwv/50+Vv46tZH/LFdR9tZLwOHjnOOHn9/1j37t89Uvh5+tQZrqcbadFrOsX7C8RZL7nxakP/EQj6NFvPLEpDkj6nhvSZCmSoLlNwTb/SVm+Z3B8imSjolZlyLp2Kj/3xykzQj+31DSJvn+ko3j7HNMkP4c+cArS7nlA0on/6BcJ/j3OzF5pAX575VUIWZdMfk+vb9IKhVn/6cEeX4UtezBYFnvQ7hWg4I8bk+wvoSkA0GacrnklSIfMDhJZ0QtnxssWy7/UFFfUuGDLO/IIK91kv4q/6ByTC7bLJa0NWbZLUE+4yUViFp+rHz/aifp7QTnan3svSnfrNlJap3kPfyXIP0NMctvD5Z3TPJ8RNLfJamM/EPzm3Hum4HB/3+Kcy4WRn8WDuKafCD/siYlibRnyAdg6yRVjFqeKh9YuTjlKyapdJy8SssHMuuir2GwbqukxTmUI9t1kQ/MRgX3+ylJHntH/fo91jVm3ZXB8oUJ7qO/xfn8vBqsax61PPJ9Migm/fxg+Y0xy1tHneNCUcs/kw8Uo5ctlw/2d0p6Jmp58yDvJ5M8D28H6ddIKp/gukZ/XxaVDzR+lHRmTF5Vg3WrlfWzWV5Sapx9R1pPjIxZnuW8yQd1C+X7X9+YzHEF250T3BNrJdWIs75C1L/bBvtcFn3Pyn/3TwnW3RTnXnXyAb1FLT8vWL4jOIfR1+2U4Djm5MP9eLDn1Un6c4JzluU7V/5l3G5JSxTzWQ3Wl4z6d1n576mdks6KSRcZA2N0gvvvU0X9/Qz2Oy9YVzPZa84PP4f6E3oB+OHnUH+ivuiT+akeZ9tpMcv66cgPSv93EPmnyD9cjY9Z/lXwhzpuIBCTNjMolX+L/bP8A1Xch1FlDUpT5Adx+ixq/Xz5B6mCShCUBun+GazrE7P8mmD5qwn2/2TsQ4B8beEBSSsO4VrlFpTWDNbvSjK/FYoJzuRrqt+LuX/3yj8gPqg4AUcO+afL1wjtj8rrgPzb939Iqhxnm3hB6YJE97p8rYFT4qD05jjbXBSsuz/J4ygg/8D3Vszygw5Kg/+PlH/4Kxtz35wc/D9eUPpt5N4+iPunVHAthyaZfqDiBFIx99rWPOz//mCbWjHLcwxKc8ivSZDfrUmmjwQBsxKsnxOsrx38v7D8w/ZnCdJXCNK/GLUsW1Aq38LESVqQIJ/Rwfr2Ucsi3z3Ngv8fF/z/r/IvFpZFpR0QrLswyfMQCQquz+G6LopadrVyeKEmX7vqJDVKcv+TJW2OWZZ53iSdLP/3YaekDnm8J/4V5HNZEmn/HaRtF2fdacG6T+Lcq3sU/2Xkd8E2p8dZNz/YLiVqWZ7ux0M8r8tz2C42KE2T/87+THGC0phtIy/snoizrqCkb4K8ooPPyP0X77xH8rsyL9edH34O5Yc+pThqOOcs0Y98MHQ0iR3xNZOZpQX9Q+aa7x+633x/sf3yb9orRaUtLz/q7xLnXLKD5ki+2eVYSaskneucW5FLejnf9OplSWeaWUPz/Z8aSBruopqnJRBpmhvb969nzPpM5vtSXqXgrXVUOb6Wb251spk1y63cYXHObXDOXSjpJPmXAcPlg8i68k0tlwZNEZPJa7tz7kr52pTr5ZuBLZB/8L1b0jJLMAVSRHDea0va6OI3S5sZZ1m0j+Ms2xD8zjK1TXAP9zazeUHfsQPBPbxP/kGtUmxGh2iopEKSro66b2Y451bm834i2sk/KCbbn/Ss4Pf02BXO97veELtcksysnpm9br7v4S77tX98ZAqaPJ1HM6tgZk+Z2VLz/Tkj+UWufV6vS7bjCUwLftcNfteRH117v/kpu7L8SLpRPsg/NZf9Rc7jlATrI8vrRi2LDIgWabL7p6i0UyWdamYVo9btk29Smhc5XdczzQ98JvkmvpJ0RoLzEDm+LOfBzDLMbKL5vrN7o65bK0mlzA/qFauufDB2jKQ/OecSNWNP5Jzg93tJpI2UO9vgc865ZfJNemsFXU2ifemCriAxvpN/Ibg0wbpU+ZYEsZK9HyUd9HlN+Lc7lvPN/v8j3+T30+A6n2/x+9UnvLeDv68z5F8MZ+t3rDx8NwOHE31Kgd+neNOeRAKH8fJN0VbJ98f7Tv7NsOSn/oieFzMySEde+1Y2lq+1muWci/tAnMAw+Vq+6+Vrppx+HXwoIefcMjObHey3hfwgVKfJP6Qtd1n7UEV0lm/S9KYLRrWNMlz+AbKX8v4AmYzIm/o0MyvnnPs+UcLgQeu44L/ZpiUJAsDVUemrSnpO0oWS/k/+fCTFOfeN/IuBl4O8ysnXlPaQNNzMTnDOuQSbF5P/m5Fovs54D4fR4vWrjPQRizx0R+7h9+Svz0r52vZN+vUe7qOs93B++FD+HF8nX6NQVon7KEdskK/NPpgAubN888JEwVGsyNy7mxOs3yz/wimTmZ0nfx73y9fcvCVf43tAPmBoozycRzOrIOkT+VrJOfLnbKt8EFZBvntAXq9LTscj/XrcZYLfdYKfRHIbBCu38/hj8Dt68KLp8uewlfwgeK3kv38XRqVpZX6ArwbyXQV+yqUcsXI6DxXlj2ubfj0PPXLJL/M8mFlf+dY/38vfb+vkuzs4+f6PJ8tft19i8jhDvqn3bEmfJ3UUWZWUtDvJc1FCPohM1LfyR/l7rLiy/u3bFT+5Dij+901knRT1nRMl2fvxUM5r3L/dObhK/mVkd/06COMeMxsnX2MeeZl8MPd2RFLfzcDhRlAKHF2aywekoyRdHh1gBMFPn5j0kQAj15EiY9wh39fm5iDfm3MIZjI559ab2fvyf7T3SZrsnPsqyX2+KB+U9pR/IE5YSxqIDHDUxcy6JEhziZnd6pxL9If8oDjntpnZEvk33OcpqqY2jobyD1tb5PtU5Zb3WjO7Qv5FQlMzS3U5D6SUU17fm9n18gFudUnHyw9GEs9O+YfzRHPy5nWu3kRayQekr0vqHnMPF1DWUYrzhXPOmdlL8lO8DJS/FmNy2WyWfO1EK/najKQEA/a0kTTOJT9YU+RBtrT8C49YpeMs6xf8rhfUNkWX4cGgDHlxs3yA1Ms5l+UzF7Q4uCGP+Unxyx29fFvM7+HOuWsPYj8R0ecxmf3K+Wm/FkhqaH708j/Jd7HYb2YLg7TnyQcDqUpyqqk4+/0xwfL98i8TosvV3DmX68s0Mysm38x4paSznXM7YtY3kw+e4vmXfNB3r/yUVRe6vA24tlVSWTM7JonAdJukMmZWNEFgGnseDpek7otDPK954vyghP0l9Q9q5JvKB6iXyo+UfZrzU6Xl+d4GjjQ03wWyi8yFeVBTHISsZvB7Qpwg8VzF1GQ4P6XIGvnmYFXysJ+d8n1K35EfeXVonKZViQyVf5OfcLqNBP4t/6DTOfjj3F3+De+rsQnN7CT5GsQf9GvNYOzPAvm+at3zUIa8iNQA32s5T59wf/D7ZZd9dMlEfpK/Tw/5Hg0eaCIjNyfMLyjbp5IqmB9xOVZ+NYWO3MPj49zDTXT4XqaOkG8CWll+RN1EtTARQ+VrRa4ys+o5JQyaBEe0kW+KmvRUMPI1lFKc+ZDNrKZ8sBirpqTVsQFpoGWcZVLO91TkusRrxpkov9xkO55Ai+D3oqjfuyU1jmm+n1eR/BKVN9I095OY5VPk77vr5JvAT5EyPzvT9euLlEjavMrpun7ufp2fOdL0s2mS+VaT/86fGidwOkZ+8LSEnHN95AOixpI+MLO8NOWMlLVtEmkj16VF7ArzcyhXlO9PnGie6vyS7P14SOf1YAVdOkY75y6Wr6mvqV+D34T3dvAyr5l87eenh6NsQH4gKAWyi7yxzu9+a7+FyHDvLaIXmllpSUMSbDNYvonOiOANcPR2ZnHmkZQy+7t0lm8WeJ2kV6L6PuXkXfmBJTop8XQb8fb3i/xgPWnyU9iUkR/wJl4NQ2YtqnPu+ng/8v3QotPmtxfk++rUlvS6xcwRa37OxUHytZRfSvp71LryZnaPmZVRfHfL94Gcm0wtqZn93czi3s/mpxE4Xn503NxqrSMvAJ6MvtbBPfJAbuVIUqJ7uIz8vXpYBC9o2sjfl48mkX6JpCfkmzVPtPhzGZqZdZL/jER0kg+w3s9D8V6Vf6C8L2hGG8k/VdLTCbbZKOl4M6sWU6aeStzk+0dJFRMEfomuy1nyoxgfjMZm1jUmvyvlX6Atcs59KknOuZ/lW0rUlPRIvPKZnyc33suSTME1+1jS2RYzX6WZtZKvffpGfoqqaJHaz78Gv6fErKss/3LrF/lRs/PqfvP9+yNlib6uw6PSjZS/DveY2TmKw8waRH02I90IGpmfriaSpoB80/+481ZHc871k29h00DSlBy+k2INCfb9pJmdEKecFaL+G5mj+lEzi24iW0i/fuZfTnK/hyKp+1H5cF6TYWbpFsw/HrM8uk9spLXTm/Ivi/9sZmfGbPKA/PPMWwn64AJHBJrvAtl9KP8A+Hjw5b5DkpxzD0cSmNmIqPSnBL8fN7PIW9OXnHOzfoOyxpok36SoZ/AgMF8+eOssP6x8vD9IT8u/Cb9E0mozGy/fT6aCfA3As/IP39k45/YGTWNfkW/OW8jMrshp4KLgbXdeB82IeFG+GWHTqP9nEfzBjoxSmfBBxjm30MwWS6pjfv622QdZpkT57zY/ifvb8g+7Lc3sPfngr6x8DUIV+evVLqbfaxH5OSH/bmbz5N9ub5HvN9RMPtDdquTnhfybpL8GzRA/ka9BLir/oNlYPkjqlURN7f8Fx9JefuCN94J8LpV/2K+uX/siHaz35Pt3/jkIMj6WP1+d5Uen3JHDtofEOfdhHjfpI/9yt7f8+ZgpX2OxU752p4V8wD9Zyrw328k3W0/6OJxzn5vZ3+UfLj83s9HBPi4KkqyWFPvy6Gn52vqPg/Q75PuSNpaf3/LiOLuaIv+y5l0zmy9fczrfOfeB/Getp6R/Bff11/KDcHWUbzHROdnjifJukF8X+WlWTpWfHuon/Tr/cMS98qPn9pFvLTFZvslsSfnPw7nyn4cc59yUHyV6uvx8lZfIj2wamad0j6SrnHN7YraZLd+U9VhJG2JqnyMB6rHy1/Vg5s/9VP66/lu/XtdT5fu7/18kkXPu5+Alx7uSZgfnYLH8daokf21rKBgUyjn3o5m9Lv/d/EnweS0g/yKsuPzfh4a5Fc4597iZ/SJ/T00zP3dqvGbk0dvMN7N75JvDLzHf5/ZL+ZHAG8n3wewUpH3PzIbK31/LzOw/8tfiYvkXEe8r69y5h0tS92N+ndcklJb//C6X78e9UT4YvUD+ueNV59y3QZm+N7Mb5P8Wzw8+85F5SpvLf15vzYcyAYePOwKGAOaHn0P5UTDFRS5p1ijJKWGC5VfK/7H/JV7+kWU5/PQ4iONokag8UWkiU8IMySHNcfL98X6UDzZWyY+2WUQ+GFkSZxuTf1ibLWm7fDPGdfJ9U2tFpcsyT2nU8hT5t91OPggrFCzPnBImieNPOCVMTLrI/J0rE6y/NFg/NYl93hSkfSWP1yrHKWFi0haQr0WZKD9gz97g2kwPzmdanG0Kyj/kvyAf5GyTf/DcHvz/H5KOy0N5L5B/oJwf7HuffJPdZfIvHU6Os022KWGC5cWC/a8L7q/V8gNwVAvOyYgE56pODtc8di7JSvK1Qpvlg4GV8s0ICyvOtCU6xClhkkifbUqYmPW15R+al8sHf3vka9wmBNe+YJDu/GC/1+blfovaz3Xyg87slq+teVk+YE90ra6Rfxm1J7ju78o/pMY9X/IB3jD5QZwi0wdFT6nSSP6l3c7gnMyXfwEU9zrmcByRKThul2/2Oj3Ib3twzs5MsF0B+eBgun4dZOlH+f69DyrrHK4JyyT/8uRl+RdEe+U/l6MVM0VOzDaR+TJfj7NuY7Dur3m8npEpOcrKN+NfHVzbtfL9m4sm2K6SpKfkp5L6Jbi+a+T7NndX1nk704K81gXHGhnsrHLU/qPnu8zpvPVSMJ2Wkvz+kW9OOkH+b8++4PckxZliRv5v0LzgXvhFPljvrfjzgSacvkgJPg8x5zz6mPN8P+bneU1UbvkXfg/K18Z/F5y/yOfuZsWfu7Sp/EuizcF98ZX8d3+2+bLjlTPeOcnLPc0PP4fyY87FdtkBACBvzKy9fA14H+fc42GX50hkZv8n/2BfwTmX1xGvcZQJag87yM8dmWhUaxxmZtZRvo/3Hc65QWGXB/ijok8pACBp0X3fopaVkq/JjNSUI0bQD7KD/DRKBKQAAEShTykAIC9GBAMbzZVvQldJvo9pGUmPO+dWhlm4I5XzzZJ+j4OnAQBw2BGUAgDy4j/yA5J0lx/U4yf5vl8vOOdeD7NgAADg9ynXPqVmNkx+tMBNzrlsQ94HaVrIj7BWSNI251x+zVcHAAAAADiKJROUNpN/E/5qvKA0mGtqiqRWzrmNZlaW/jIAAAAAgGTk2nzXOTfDzKrnkKSrpNHOuY1B+qQC0rJly7rq1XPKFgAAAADwe7Vw4cIfnHOxc2lnkx99Sk+RpGCC92KSBjvnhsZLaGa95IfDV9WqVbVgwYJ82D0AAAAA4EhjZl8nky4/poRJkZ8UuJX8JMn3mlncvqfOuRedc/Wdc/XLlcs1YAYAAAAAHOXyo6Z0naQNzrmfJf1sZtMl1ZK0JB/yBgAAAAAcxfKjpvRdSU3MrKCZFZV0rqQV+ZAvAAAAAOAol2tNqZmNlNRCUlkzWy+pr6RUSXLOPe+c+8TMJkr6LFj+snPuk8NXZAAAAADA0SKZ0Xe7JZFmoPw8pQAAAAAAJC0/mu8CAAAAAHBQCEoBAAAAAKEhKAUAAAAAhCY/poQBAAA46uzevVubN2/Wjh07tH///rCLAwChKlCggIoXL67SpUsrLS0tX/MmKAUAAIixe/durV27VqVKlVL16tWVmpoqMwu7WAAQCuec9u7dq+3bt2vt2rWqWrVqvgamNN8FAACIsXnzZpUqVUply5ZVoUKFCEgB/KGZmQoVKqSyZcuqVKlS2rx5c77mT1AKAAAQY8eOHUpPTw+7GABwxElPT9eOHTvyNU+CUgAAgBj79+9Xampq2MUAgCNOampqvvezJygFAACIgya7AJDd4fhuJCgFAAAAAISGoBQAAAAAEBqCUgAAAOSLESNGyMw0YsSIsIuSFDNTixYtwi4G8IfHPKUAAAB59Mb8tWEXIUeXN6yaL/ns379fw4YN02uvvabPP/9c27dvV9GiRVWlShXVrVtXl1xyiTp16pQv+/o9iPSlMzP973//U40aNeKma9mypaZNmyZJGj58uHr06JEtzc8//6yhQ4dq/PjxWrJkibZu3aqiRYuqZs2aOv/883XdddfphBNOOFyHAhxRCEoBAACQzf79+9WuXTtNnDhR5cqVU4cOHVSpUiXt3LlTS5cu1VtvvaU1a9ZkCUo7deqkc845RxUrVgyx5IdXwYIFtW/fPr388st65JFHsq3/3//+p2nTpmWmi2fevHnKyMjQN998o8qVK+vCCy/Ucccdp507d2rx4sUaOHCgBg4cqHnz5umss8463IcEhI6gFMAhO9JrDIAjRX7VXgG/hZEjR2rixIlq0KCBJk+erOLFi2dZv3PnTs2fPz/LshIlSqhEiRK/ZTF/c+XLl1fFihU1fPhwDRgwQAULZn2cfumllyRJF198scaOHZtt+xUrVqhNmzb66aef9Nhjj6l3797Z8li7dq3uuecebd++/fAdCHAEoU8pAAAAspkzZ44kqUePHtkCUkkqWrSoWrZsmWVZTn1KJ02apMaNG6tYsWIqXbq0OnbsqCVLlqhHjx4yM61ZsyYz7Zo1a2SdK1InAAAgAElEQVRm6tGjh9asWaOuXbuqbNmyKly4sOrXr6933nknW/7btm3Tww8/rObNm6tMmTIqWLCgypUrp/bt22vu3LmHdjJi9OzZUxs3bsxWjr1792rEiBFq1KiRTjvttLjb3nLLLdq+fbvuvfde3XvvvdkCUkmqWrWqRo0apXPPPTdfyw0cqQhKAQAAkE3hwoUl+eaoh2rUqFFq27atFi1apEsvvVQ33HCDtmzZoiZNmuiLL75IuN3XX3+tBg0aaMOGDerZs6euuuoqrVixQh06dNCHH36YJe3y5cv1yCOPqEiRIrr66qvVp08fXXjhhZoxY4aaNWumiRMnHvJxRHTr1k3FihXLrBWNGD9+vDZt2qSePXvG3e6rr77S5MmTVbhwYd1zzz257ictLS1fygsc6Wi+CwAAgGwuvfRSDRo0SIMGDdL333+vTp06qV69eqpWrVqe8tmxY4f+/Oc/q3Dhwpo7d65q166due6+++6L2y8zYtq0aXryySd15513Zi7r3r27mjVrpoEDB2apqT3ttNO0ceNGpaenZ8lj48aNOvvss3XHHXfoggsuyFPZEylevLi6du2qESNGaP369apcubIkaejQoUpPT9dll10W97hmzZolSapXr55KliyZL2UBjgbUlAIAACCbc889V2+88YbKly+v1157TZdccomqV6+uMmXKqFOnTpowYUJS+YwbN05bt27VtddemyUglaS+ffuqTJkyCbc98cQTswSkktS0aVOdeOKJ+uijj7IsT09PzxaQSlKFChXUpUsXrVixQmvX5t8YCD179swcnVjytboffPCBrrjiChUtWjTuNhs2bJCkzCAWgEdQCgAAgLi6du2qtWvXatKkSXrggQfUrl07FShQQG+//bbat2+vq6++Ws65HPNYtGiRJB9MxipUqJAaNmyYcNv69evHXV6xYkVt2bIl2/LZs2frsssuU5UqVZSWliYzk5npySeflCR98803OZY1Lxo2bKgzzzxTw4YN04EDB/TSSy/pwIEDCZvuAkiM5rsAAABIKDU1Va1bt1br1q0lSQcOHNC4ceN0zTXX6NVXX1WnTp3UsWPHhNtv27ZNkhI2Vy1VqlTCbRP1qUxJSdGBAweyLBs7dqwyMjJUuHBhnX/++apRo4aKFSumlJQUTZs2TdOnT9fu3btzPNa86tmzp2699Va9//77Gj58uOrVq6e6desmTB+ZKic/g2PgaEBQCgAAgKSlpKSoU6dOWrp0qR544AFNnTo1x6A00qR269atcdcnWp5XDzzwgIoUKaLPP/9cxx9/fJZ1d955p6ZPn54v+4nWvXt33Xvvvbrxxhv1zTff6MEHH8wxfZMmTSRJCxYs0LZt24766XOAZNF8FwAAAHkWCTZza74bqTmcOXNmtnV79uzRvHnz8qU8q1atUq1atbIFpJKyjdSbX0qWLKmMjAytX79exYoVU7du3XJMf/zxx+u8887Trl27NHDgwFzzz++aXeBIRVAKAACAbEaOHKkPPvggWzNZSfrhhx/0wgsvSJKaNWuWYz4dOnRQiRIlNGzYMH366adZ1vXv318//vhjvpS3QoUKWrZsmTZt2pRl+cCBA7V48eJ82Uc8Dz/8sMaOHatJkybFnc811uDBg5Wenq5HH31UTz75pPbt25ctzdq1a9WlS5d8n18VOFLRfBcAAADZzJ8/X08//bQqVKigJk2a6Pjjj1dqaqq++uorvffee9q2bZs6dOigjIyMHPNJT0/Xs88+q+7du6tRo0a67LLLVLFiRc2ZM0eLFy9WkyZNNGvWLKWkHFpdyW233aa77rpLdevWVUZGhooUKaKZM2dq0aJFatu2rd5///1Dyj+RqlWrqmrVqkmnP/XUUzVp0iRlZGTorrvu0tNPP61WrVrpuOOO088//6xPP/1Us2fPlpmpT58+h6XMwJGGoBQAAADZ3HnnnapSpYqmTZumjz/+WOPHj5dzTmXKlFGjRo10+eWX6/LLL5eZ5ZrXFVdcodKlS+uhhx7Sm2++qbS0NDVr1kyzZs3SgAEDJCnudC550bt3b6WlpWnIkCF67rnnlJ6erqZNm2rWrFkaP378YQtKD8Y555yjFStWaOjQoRo/frzeffddbdmyRUWLFtWJJ56o3r17q1evXnGbIgNHI8utH8DhUr9+fbdgwYJQ9g0gf70xP//mfQOOZpc3TL42BeFavny5Tj311LCLcdRzzunEE0/Uzp07M+fwBHDkS/Y70swWOufiz+0UhT6lAAAAOKy2bdsWd9CeQYMG6csvv1SnTp1CKBWAIwXNdwEAAHBYzZ07V1deeaXOP/98nXDCCdq9e7dmz56tefPmqUqVKurXr1/YRQQQIoJSAAAAHFYnn3yyWrRooVmzZuk///mPzEyVK1fWrbfeqr/97W869thjwy4igBARlAIAAOCwOv744zVmzJiwiwHgCEWfUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAAAChISgFAAAAAISGoBQAAAAAEBqCUgAAAABAaAhKAQAAkGfVq1dX9erVwy7G70qPHj1kZlqzZk3YRcEf1LRp02Rm6tevX9hFyaJg2AUAAAD43ZlwW9glyNnFT4ddgqSZmZo3b65p06aFXZQ/hOrVq+vrr7/O/H9KSoqKFSumSpUqqU6dOmrXrp0yMjKUlpYWYinxR0NQCgAAAPzB3HbbbSpZsqQOHDig7du3a+XKlZowYYJGjRql++67T6NGjdI555wTdjHxB0FQCgAAAPzB3H777dmaX2/btk0PPPCAnnnmGV1wwQWaN2+eTjnllHAKiD8U+pQCAAAgLuechgwZotNPP12FCxdWpUqVdPPNN2vbtm1x02/btk0PP/ywmjdvrjJlyqhgwYIqV66c2rdvr7lz52ZJO2LECJmZJGn69Okys8yf6P5uL774oi6++GJVrlxZqampSk9PV+PGjfXaa6/l6Vj69esnM4vbTHjNmjUyM/Xo0SPL8ug+oC+88ILOPPNMFS5cWOXLl1evXr0SnofJkyeradOmKlasmEqXLq2OHTtqxYoVOZZv/vz5ysjIUIUKFVSoUCFVqVJFN9xwg7799ttsaVu0aCEz0549ezRgwACdfPLJSktLy1b+vCpRooQGDx6sq666Stu2bVOfPn2yrN+4caP+/Oc/q1q1aipUqJAKFy6sE088UV27dtUXX3yR1D4ifZG3bdum22+/XVWqVFGhQoV02mmn6c0335Qk7d69Ww8++KCqV6+u1NRU1ahRQ0OGDMmW1549e/Tkk0+qdevWKl++vFJTU1W6dGmdd955ev/99+Puf+HCherYsaOOPfZYFSxYUMWLF1ft2rV10003ae/evZnptm/frnvvvVcnnXSS0tLSlJaWpmrVqqljx45asGBBUscauU67d+/W/fffr+OPP15paWmqUaOG+vfvrz179sTdbsWKFerRo0fmuSlfvrwuv/xyrVy5MlvalStX6vbbb1fdunVVvHhxFSpUSNWqVVOvXr20fv36pMopSbt27VJGRobMTH/5y1904MCBpLfND7nWlJrZMEntJG1yzp2RQ7qzJc2V1NU5Nyb/iggAAIAw3H777Ro8eLAqVqyoXr16KTU1VePGjdP8+fO1Z88eFSpUKEv65cuX65FHHlGzZs109dVXq2jRolq3bp3GjRun999/XxMmTNAFF1wgSapTp4769u2r/v37q1q1alkCqhYtWmT++4477lCtWrXUvn17lSlTRlu2bNF7772n7t27a+XKlXrooYcO+3m45557NHXqVHXu3FkXX3yxpk6dqqFDh2r16tWaOnVqlrRjxoxRly5dVKhQIXXp0kUVK1bUrFmzdO6556pWrVpx8x82bJh69eql4sWLq2PHjjruuOP05ZdfasSIEZowYYLmzZunqlWrZtvukksu0aJFi9SxY0elp6fr2GOPzZfjffDBB/Xqq6/qnXfe0fbt25Wenq6dO3eqSZMm+vLLL3XBBReoW7duSklJ0VdffaUPP/xQy5cvV40aNZLKf8+ePTrvvPP0yy+/qGvXrtq1a5def/11devWTcWKFdNzzz2npUuXqkOHDipYsKDefPNN3XLLLSpatKiuvfbazHw2b96sv/71r2rcuLG6dOmiEiVK6LvvvtOECRN04YUXaujQobr++usz03/22Wdq0qSJUlJS1KlTJ1WvXl27du3S8uXL9eqrr+of//iHUlNT5ZxT27ZtNWfOHDVt2lSdOnVSamqq1q9fr+nTp2vevHmqX79+0ufzsssu08cff6yMjIzMz1C/fv20YMECjR8/PvPljCRNnDhRnTt3liR16NBBJ5xwgjZs2KB///vfevfdd/Xhhx/qrLPOykw/duxYvfHGG2rRooVat26tAgUKaOnSpRo2bJgmTJigBQsWqFKlSjmWb8uWLWrfvr1mz56tRx99NNvLiN9CMs13R0gaIunVRAnMrICkxyX9N3+KBQAAgDDNmTNHgwcPVs2aNTV37lyVLl1akvT3v/9d559/vjZs2KBq1apl2ea0007Txo0blZ6enmX5xo0bdfbZZ+uOO+7IEpTWqVNH/fv3V/Xq1ROOBrpixQpVqVIly7K9e/eqQ4cOeuyxx3TjjTfm+tB9qBYtWqSlS5eqfPnykqQDBw6oTZs2mjx5sj766CM1aNBAkvTTTz/phhtuUGpqqmbNmqV69epl5nHXXXfpySefzJb3qlWrdOONN+rUU0/VlClTsgSWc+bMUcuWLXXbbbdp7Nix2bbdsGGDli9fruLFi+fr8daoUUOVK1fW+vXrtXDhQrVs2VJTpkzRF198oT59+ujRRx/Nkn7//v3auXNn0vlv2LBBjRs31qhRo1SgQAFJ0lVXXaUGDRqoW7duql27tpYtW6aiRYtK8i9HatasqSeeeCJLUFqqVCmtX78+WzC+Y8cONW/eXPfcc4+uuOIKFSlSRJL0yiuvaNeuXZo4caLatGmTZZvt27dn7m/JkiWaM2eOunbtqpEjR2ZJ55zT9u3bkz5WyV/jpUuXqlSpUpJ+/Qy98847eu2119S9e3dJPjjs1q2bSpUqpWnTpumkk07KzKNPnz4655xzdP311+uTTz7JXH711VfrrrvuUsGCWcO6GTNmqGXLlnr44Yf13HPPJSzb119/rbZt22r16tX617/+pSuuuCJPx5Zfcm2+65ybIWlzLslukfQfSZvyo1AAAAAI1/DhwyVJ/fv3zwxIJalw4cJxgytJSk9PzxaQSlKFChXUpUsXrVixQmvXrs1TOWIDUklKTU3VTTfdpH379mnKlCl5yu9g9O3bNzMglfyItZGa3Y8++ihz+bhx47R582b16NEjS0AqSQ8//HBmUBLtueee0969ezVo0KBswVWjRo3UqVMnTZgwQTt27Mi27d///vd8D0gjIoH+999/L8k3qZWUpVYvokCBAnkuxz//+c/MgFSSzj77bNWsWVM//fSTHn/88cwAUfL3QLNmzbR8+fIs5yEtLS1u7XDx4sV17bXXasuWLfr4448zl+d0DOnp6UpJSck1nZmpRIkSeTrWhx56KMu1j/4MDRs2LHP5q6++qq1bt2rAgAFZAlJJqlmzpnr16qVFixZp2bJlmcsrVqyYLSCVpGbNmqlu3bqaNGlSwnItXrxY5557rr755hu9//77oQWkUj4MdGRmlSR1ktRS0tmHXCIAAACELlIb07x582zrzj77bBUrVizudrNnz9bTTz+tuXPnatOmTdn6zX3zzTdxm6ImsnbtWj3++OOaMmWK1q5dq19++SVbfofb2Wdnf8StWLGiJF+7FZHTOStcuLDOOeecbH0dI31tJ0+erJkzZ2bb7ttvv9X+/fu1atWqbIHu4Rwd1zknSdq3b58kqVWrVjr22GP12GOP6dNPP1Xbtm117rnnqk6dOlmCy2SUL19elStXjrt81apVcZvGRl4KbN26NUsAvHTpUg0cOFAzZszQhg0btGvXrizbRd8fXbp00XPPPafOnTsrIyNDrVq1UqNGjbI1O65Tp45OPfVUjRw5Ut98840uvvhiNWrUSPXr18/WZD0ZOX2GFi1alLksci8sWLBA69aty7ZNJBhdvny5TjvtNEn+Or3++usaMWKEPv30U23ZskX79+/P3CZReWfNmqWnnnpKxYsX14wZM1S7du08H1d+yo/RdwdJutc5dyDe24RoZtZLUi9JefoyAgAAwG8rMohPdC1phJmpZMmS2ZaPHTtWGRkZKly4sM4//3zVqFFDxYoVU0pKiqZNm6bp06dn1kIl48svv1SDBg20ZcsWNW3aVK1bt1aJEiVUoEABrVmzRq+88kqe8jtY8ebsjNSqRQcAOZ2zRMt//PFHSdJjjz2WYxl++umnbMvyWmOXF5EBliLBYKlSpTR37lz169dP77zzjt577z1JUtmyZXXTTTfp/vvvV2pqalJ5Fy5cOO7yyDlN9nzPmzdPf/rTn7Rv3z61atVK7du3z6zxXLx4scaNG5fl/mjatKmmTJmiRx99VKNGjdIrr7wiSTr55JPVt29fdevWTZJUsGBBTZs2TQMGDNCYMWM0Y8YMSb4G9uqrr9YjjzySp5rhnD5D0QNZRe6F559/Psf8ou+FO++8U4MGDVLFihXVpk0bVapUKbO58ogRI7LMSRtt0aJF2rFjhxo1anREjLCcH0FpfUmjgoC0rKQLzWyfc+7t2ITOuRclvShJ9evXd/mwbwAAABwGkYBn8+bNmbWCEc45bd26VWXLls2y/IEHHlCRIkX0+eef6/jjj8+y7s4779T06dPzVIannnpKP/74o0aPHq1LL700y7rx48dnBhXJiAQ1kRrAaLG1awcr+pzFE295ZJtt27bFbfochtWrV2v9+vVKSUlRnTp1MpefcMIJevXVV+Wc07JlyzR16lQ9++yzGjBggH7++Wc98cQTv2k5H374Ye3atUvz5s3L7NcbMXjwYI0bNy7bNi1atFCLFi20e/duLVy4UBMnTtQzzzyjyy+/XMWLF1e7du0kSccee6yGDBmiIUOGaPXq1Zo+fbpeeOEFDRkyRBs2bNCYMcmP67p582aVK1cuy7LIZyj6mkfuhU8//TThoFjRNm3apMGDB6tevXqaOXNmZjAaMX78+IRB6c0336xNmzbp+eefV/v27fX2229n2/63dMhTwjjnjnfOVXfOVZc0RtJN8QJSAAAA/H5ERviMF0h+/PHH+vnnn7MtX7VqlWrVqpUtIJWkDz/8MO5+UlJS4gaKkfwkPwppsvklEunTF2+Kleh+h4cip3MWCZ5iRZrgxmu6G5YBAwZIktq2basyZcpkW29mOv3003XLLbfogw8+kOQDoN/aqlWrVKFChWwBqZT7/ZGWlqZGjRppwIABGjx4sKTEx3DiiSfquuuu0/Tp03XMMcdowoQJeSpnTp+hunXrZi7L672wevVqHThwQK1bt84WUH7//fdasmRJwm3NTM8995xuv/12/fe//9VFF10U9zP9W8k1KDWzkfJTvZxsZuvN7Dozu9HMbjz8xQMAAEAYIgP59O3bN0sN365du9S7d++421SoUEHLli3Tpk1Zx74cOHCgFi9eHHebMmXKJOwXWqFCBUnKNrfozJkzcxxRNJ5I4PLKK69kmYNx06ZN6t+/f57ySqRDhw4qVaqURowYoYULF2ZZd//992fpfxpx8803KzU1VXfccUfcQaAOHDig+fPn50v5crN9+3bdeuut+te//qVjjjlGAwcOzFy3dOlSfffdd9m2iTRZjjeI0+FWoUIFfffdd1q+fHmW5aNHj45bSzpnzpxsfZKl7Mfw1Vdf6csvv8yWbseOHdq/f3/cpus5eeCBB7Jc++jP0DXXXJO5/JprrlHJkiXVv39/ffbZZ3Hzip7vN/L5mDlzZpZmzXv27FGvXr2yzLuayD//+U/99a9/1Ycffqg2bdrkeWTh/JJr813nXLdkM3PO9Tik0gAAAOCI0LhxY91yyy165plndMYZZ2SZY7FUqVLZmvRK0m233aa77rpLdevWVUZGhooUKaKZM2dq0aJFatu2bbZBfiQ/gM6oUaPUuXNn1alTRykpKWrWrJmaNWumm266SSNHjlTHjh3VpUsXVapUScuWLdP48ePVoUMHvfXWW0kfT8OGDdWsWTN98MEHaty4sVq2bKnNmzdrzJgxatWqlb744otDOl+SdMwxx+jFF19Uly5d1KRJkyzzlC5ZskTNmjXL7J8Yccopp2jYsGG69tprdcopp+iiiy7SSSedpP379+urr77SjBkzVLJkSa1YseKQyxdt0KBBKlmyZOYUJytXrtSMGTP0888/q3r16ho5cqROPfXUzPQffPCB7r77bjVu3Fi1a9dWenq6vv32W7311ltKSUnR3Xffna/lS8att96qmTNnZs5TWqpUKS1cuFBTpkxRhw4d9PbbWRtv/uMf/9DUqVPVsmVLnXzyySpUqFDm/VSqVCn16tVLkm8+27lzZzVo0ED16tVT6dKl9cMPP+jtt9/WL7/8oocffjhP5axZs6ZOP/30LJ+hL774QhdddFHmdDCSf0EzZswYderUSfXq1VObNm10xhlnyMy0bt06zZo1Sxs3bsxsbn7CCSeoXbt2euedd3T22WerdevW2rVrlyZMmCAzU61atRIGt9EeeeQRFS5cWH379tX555+viRMn/uYvGfKjTykAAACOQk8//bRq1qypZ599Vi+88ILKlCmjTp066ZFHHok7Wmfv3r2VlpamIUOG6LnnnlN6erqaNm2qWbNmafz48XGD0qefflpmpilTpmjcuHE6cOCA+vbtq2bNmmWOVtu3b1+NGjVKBQsWVO3atTVy5EiVK1cuT0Gp5KdsufvuuzVu3Dh98sknOumkk/TII4+odevWGj169EGfp2gZGRmaOHGi+vfvr9GjRystLU3NmjXT3Llz9dhjj2ULSiXpyiuvVO3atfXkk0/qww8/1Lhx41SgQAFVrVpVF1xwgS6//PJ8KVu0p59+WpJvxlmsWDFVrlxZF198sdq1a6eMjIxsgw21bt1aX3zxhWbPnq3hw4dr586dKlWqlBo3bqzevXurZcuW+V7G3GRkZGjUqFF67LHHNGzYMBUpUkQNGjTQpEmTtG7dumxB6Y033qjixYvro48+0n//+1/t27dPxx13nK6++mrdd999OuGEEyRJ9evX11133aUZM2bojTfe0Pbt25Wenq6zzjpLzz77rDp37pynco4ePVoPPfSQXn/9dX377beqVKmS+vXrpz59+mSbdqZVq1b67LPP9MQTT2jSpEmaPHmynHOqVKmSGjZsqEsuuSRL+lGjRum+++7T6NGj9dRTT6l8+fJq166d+vfvr8suuyzpMj744IMqUqSI7rnnHrVq1Ur//e9/s/UZP5wsURv+w61+/fpuwYIFoewbQP56Y37e5pwD/qgub8jI878Xy5cvz1JLBAB51aJFC02fPj1hn+nfs2S/I81soXMu+xw/MQ55oCMAAAAAAA4WQSkAAAAAIDQEpQAAAACA0DDQEQAAAADks9ipjJAYNaUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAABAHEfj3IIAcKgOx3cjQSkAAECMAgUKaO/evWEXAwCOOHv37lWBAgXyNU+CUgAAgBjFixfX9u3bwy4GABxxtm/fruLFi+drngSlAAAAMUqXLq0tW7bohx9+0J49e2jKC+APzTmnPXv26IcfftCWLVtUunTpfM2feUoBAABipKWlqWrVqtq8ebPWrFmj/fv3h10kAAhVgQIFVLx4cVWtWlVpaWn5mjdBKQAAQBxpaWmqWLGiKlasGHZRAOCoRvNdAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAAAAAKEhKAUAAAAAhIagFAAAAAAQGoJSAAAAAEBoCEoBAAAAAKHJNSg1s2FmtsnMliRY393MPjezJWa20Mzq538xAQAAAABHo2RqSkdIuiCH9askNXHOnSHpfkkv5UO5AAAAAAB/AAVzS+Ccm2Fm1XNYPz/qv7MkVTr0YgEAAAAA/gjyu0/pDZLG53OeAAAAAICjVK41pckysxaSrpPUJIc0vST1kqSqVavm164BAAAAAL9T+VJTama1JL0sqYNz7sdE6ZxzLzrn6jvn6pcrVy4/dg0AAAAA+B075KDUzKpKektSd+fcqkMvEgAAAADgjyLX5rtmNlJSC0llzWy9pL6SUiXJOfe8pAcllZH0f2YmSfucc0wLAwAAAADIVTKj73bLZf31kq7PtxIBAAAAAP4w8nv0XQAAAAAAkkZQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAIhixG8AABOMSURBVAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQpNrUGpmw8xsk5ktSbDezGywmS0zs0Vmdlb+FxMAAAAAcDRKpqZ0hKQLcljfWVI1SadLuk7S8EMvFgAAAADgjyDXoNQ5N0PS5hySXCTpNed9IqmgmVXJrwICAAAAAI5eBfMhj8qS1kX9f32cZQAAAEByJtwWdgmAI9/FT4ddgnzzmw50ZGa9zGyBmS34/vvvf8tdAwAAAACOQPlRU7peUhVJ84L/Vw6WZeOce1HSi5JUv359lw/7BnAEOHtJ/7CLAPw+NHw57BIAAHDEyY+a0vckXSFJwci7B5xzNN0FAAAAAOQq15pSMxspqYWksma2XlJfSamS5Jx7XtJ/JLU0s2WS9ki65rCVFgAAAABwVMk1KHXOdctlvZP0l3wrEQAAAADgD+M3HegIAAAAAIBoBKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAAAAQkNQCgAAAAAIDUEpAAAAACA0BKUAAAAAgNAQlAIAAOD/27v/GMvOsg7g30d3beSHRugCymxRExODTdPUJQ2xaAkktjTGqMSq0EQElzZI/BENVSMS/UdDNKaKbqqgiWuw/iBqdGuLEiUYsC61ttsuFo3EXXXpgglRTKWVxz/uXb0ddnfOTO/se/fu55NM9p5z3jPzzH323Dffe849AzCMUAoAAMAwQikAAADDTAqlVXVDVR2rquNVdftZtr+gqv68qh6pqker6tbllwoAAMC62TKUVtVlSQ4luTHJVUleXVXXbBr2fUmOdveLk3xdkp+pqi9cdrEAAACslylnSq9N8nB3n+juJ5LcleSmTWNOJnl2VVWSZyX5RJL/XmqlAAAArJ0poXQjyYmF5ZPzdYt+NcmLk/xrkoeSfH93f3YpFQIAALC2lnWjox9N8mCSL0tydZJfqqov2jyoqg5W1dGqOnr69Okl/WgAAAAuVlNC6ckk+xeWN+brFr0sye/2zD8k+afMzpw+RXff2d0HuvvAvn37dlozAAAAa2JKKL0vyZVVtVFVe5PcnOTuTWP+MckrkqSqnp9ZIP3YEusEAABgDe3ZakB3P15VtyW5J7MQe7i7j575sy/dfSjJTyU5XFXHk3x+kp/o7lO7WDcAAABrYMtQmiTdfSTJkU3rDi08PpXklcstDQAAgHW3rBsdAQAAwLYJpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADDMplFbVDVV1rKqOV9Xt5xhzfVX9TVX9XVW9f7llAgAAsI72bDWgqi5LcijJy5KcSvLBqrq3u+9fGPOCJO9I8oruPlVVl+9WwQAAAKyPKWdKr03ycHef6O4nktyV5KZNY74jye9096kk6e5PLLdMAAAA1tGUULqR5MTC8sn5ukVfneRLq+pDVfVQVX3v2b5RVR2sqqNVdfT06dM7qxgAAIC1sawbHX1ekquTvCLJy5O8paqu3Dyou+/s7gPdfWDfvn1L+tEAAABcrLb8TGlmZ0b3LyxvzNctOpHk37r700k+XVV/meSqJMeWUiUAAABracqZ0vuSXFlVG1W1N8nNSe7eNOZPklxXVXuq6hlJXprkI8stFQAAgHWz5ZnS7n68qm5Lck9mIfZwdx+tqlvn2w919/1V9adJHkyyN8k7F+/OCwAAAGcz5fLddPeRJEc2rTu0afntSd6+vNIAAABYd8u60REAAABsm1AKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMMye0QUAAMCijz72n6NLgJX3VaMLWCJnSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAYRigFAABgGKEUAACAYYRSAAAAhhFKAQAAGEYoBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhJoXSqrqhqo5V1fGquv08415SVU9W1auXVyIAAADrastQWlWXJTmU5MYkVyV5dVVdc5Zxn5/kZ5Pcu+wiAQAAWE9TzpRem+Th7j7R3U8kuSvJTWcZ9+Ykv5/ksSXWBwAAwBqbEko3kpxYWD45X/d/quqFSb4lya+c7xtV1cGqOlpVR0+fPr3dWgEAAFgzy7rR0S8keUt3f/Z8g7r7zu4+0N0H9u3bt6QfDQAAwMVqz4QxJ5PsX1jemK9bdCDJb1dVklye5FVV9WR3/8FSqgQAAGAtTQml9yW5sqo2knw8yc1Jbl0c0N1fceZxVf1Gkj8WSAEAANjKlqG0ux+vqtuS3JPZ5b6Hu/toVd06335ol2sEAABgTU05U5ruPpLkyKZ1Zw2j3f3dT78sAAAALgXLutERAAAAbJtQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwzKRQWlU3VNWxqjpeVbefZfstVfXQfMyHq+rA8ksFAABg3ezZakBVXZbkUJKXJTmV5INVdW93378w7NEk13X3p6rqxiS/luTq3SgYAACA9THlTOm1SR7u7hPd/USSu5LctDigu/+6uz81X/xAkhcut0wAAADW0ZRQupHkxMLyyfm6c3ljkj96OkUBAABwadjy8t3tqKrrk7w+yXXn2H4wycEkueKKK5b5owEAALgITTlTejLJ/oXljfm6p6iqq5K8M8k3d/cnz/aNuvvO7j7Q3Qf27du3k3oBAABYI1NC6X1Jrqyqjaram+TmJHcvDqiqK5K8J8kt3f3o8ssEAABgHW15+W53P15VtyW5J7MQe7i7j1bVrfPth5K8Nclzk/xyVSXJk93tz8IAAABwXpM+U9rdR5Ic2bTu0MLjNyR5w3JLAwAAYN1NuXwXAAAAdoVQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwjFAKAADAMEIpAAAAwwilAAAADCOUAgAAMIxQCgAAwDBCKQAAAMMIpQAAAAwjlAIAADCMUAoAAMAwQikAAADDCKUAAAAMI5QCAAAwzKRQWlU3VNWxqjpeVbefZXtV1R1V9UhV/W1VXbP8UgEAAFg3W4bSqrosyaEkNya5KsmrzxI6vzXJi5J8TZLXJ/n1JdcJAADAGppypvTaJA9394nufiLJXUlu2jTmpiSHe+b+JHuqav+SawUAAGDNTAmlG0lOLCyfnK/b7hgAAAB4ij0X8odV1cEkB+eL/1lVf38hf/4OXJ7kE6OL4Cn0ZDXpy+rRk1X0hnfpy+rRk9WkL6tHT1bNxTGnvGjKoCmh9GSSxUtxN+brzjbmQ+cZk+6+M8mdUwpbBVV1tLsPjK6D/6cnq0lfVo+erCZ9WT16spr0ZfXoyepZp55MuXz3viRXVtVGVe1NcnOSuzeNOZLkNUkyvwnSZ7v7RAAAAOA8tjxT2t2PV9VtSe7JLMQe7u6jVXXrfPuhJL+f5OVV9UiSzyR53S7WDAAAwJqY9JnS7j6S2dnQxXWHFh53kjctt7SVcNFcanwJ0ZPVpC+rR09Wk76sHj1ZTfqyevRk9axNT2qWJwEAAODCm/KZUgAAANgVl3worarnVNV7q+qhqrq3qr7kHOM+Nh/zQFUd3e7+TDflOa2q/VX1/qo6VlWPVtVbFra9rar+Zd6rB6rqVRf2N1gfVXXD/Dk+XlW3n2V7VdUdVfVIVf3t/EZnk/Zl5yb05Zb58XOsqj5cVQcWtp31tYynZ0JPrq+qTy28Lr116r7szISe/MhCP45V1f9U1XPm2xwnu6Cq3lVVj1XVsXNsN6cMMKEv5pQLbEJP1m9O6e5L+ivJLyb5ofnjH0xyxznGfSzJ5Tvd39dye5LkBUmumj9+dpKPJrl6vvy2JD88+ve42L+SXDb/f78/yd4kR5Ncs2nMtyX5wySV5Jokfzd1X1+72pdrk3zx/PGNSR5Y2HbW1zJfu96T65P88U729bU7Pdk0/puSvG9h2XGyO335+vlccewc280pq9kXc8rq9WTt5pRL/kxpkpuS/Ob88eH58oXcn8+15XPa3ae6+8H54/9I8mCSF16wCi8N1yZ5uLtPdPcTSe7K5/bipszuyN3dfX+SPVW1f+K+7MyWz213/3V3f2q++IE4Nnbb0/n/7ljZHdt9Xr8zybsvSGWXsO5+f5J/P88Qc8oAW/XFnHLhTThWzuWiPVaE0mRfd59Okvm/zzvHuE5y5pLSN+9gf6bb1nNaVV+e5CWZvVCe8aaq+khV/VZVPXe3Cl1zG0kW/97wyfm6KWOm7MvObPe5fWOSP1pYPtdrGTs3tScvnV9S9b6qunqb+7I9k5/XqnpGkhsy+/N2ZzhOxjCnrD5zyupYqzll0p+EudhV1Z9ldrnnZj++jW/z0u4+VVXPS/KnVfWR7n7vciq89CypJ6mqZyX5vSQ/sPAu3juS/HRmL5RvS3JHktfsuFi4SFXV9Ulen+S6hdVey8b4cJL93f1fVfWNSf6gqr5ydFEkmV26+1fdvXhWwnECm5hTVsrazSmXRCjt7leea1tVna6qfd19uqr2JXnsHN/j1Pzfx6rq9zI7M/feJJP256mW0ZOq2pvZO9vv7u73LHzv0wtjDiX5i6UVfmk5mdlnEs7YmK8725gPbRqzd8K+7MyUvqSqrkryziQ3dvcnz6w/z2sZO7dlT+YfMzjz+J6q+kxmb8xN6ifbtp3n9Tuy6dJdx8kw5pQVZU5ZLes4p7h8NzmS5LXzx69NcvfmAVX1zPnlPamqZ2Z2mc8jU/dn26b0pDJ7cTze3T+3advi5b7flv/vFdtzX5Irq2pj/gbAzfncXhzJ/Cz0/C6Jn+3uExP3ZWe2fG6r6ook70lyS3c/urD+fK9l7NyUnuxbePy1SZ6V2RtujpXdMel5raovTvINmd1c58w6x8k45pQVZE5ZPes4p1wSZ0q38JNJ7qqq70ny8STfniRV9WVJfq27X5Xk+ZmdFu8kz8jsQ8N/eL79eVqm9OTrktyS5KGqemC+349195EkPz9/R+8LkvxzZpeasE3d/XhV3ZbknszewDrc3Uer6tb59kOZnal+eVU9kuQzSV53vn1H/B7rZmJf3prkuUl+efb+TZ7s7gM5/2sZOzSxJ99ZVQfnu3wmyXd195NJnnSsLN/EniTJtyS5t7s/vbC742SXVNW7M7tr6OVVdTKz+X5vYk4ZaUJfzCkX2ISerN2cUj27fTAAAABccC7fBQAAYBihFAAAgGGEUgAAAIYRSgEAABhGKAUAAGAYoRQAAIBhhFIAAACGEUoBAAAY5n8Bb7QAAKqGlyEAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data below peak comparison\", fontsize=20)\n", - "\n", - "plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.5, alpha=0.6, label=\"data under Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data under peak comparison\", fontsize=20)\n", - "\n", - "plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.5, alpha=0.6, label=\"data under Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "metadata": {}, - "outputs": [], - "source": [ - "nbins=4\n", - "MC_Hlt2Phys_TOS=MC_tuple_dict[\"Ds_Hlt2Phys_TOS\"]\n", - "data_Hlt2Phys_TOS_under=data_tuple_bkg_under[\"Ds_Hlt2Phys_TOS\"]\n", - "data_Hlt2Phys_TOS_over=data_tuple_bkg_over[\"Ds_Hlt2Phys_TOS\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "metadata": {}, - "outputs": [], - "source": [ - "h_mc= r.TH1F(\"Hlt2 Phys TOS MC/data comparison under\", \"Hlt2 Phys TOS MC/data under Ds mass comparison\",nbins, 0, 2)\n", - "\n", - "for i in range(len(MC_Hlt2Phys_TOS)):\n", - " h_mc.Fill(MC_Hlt2Phys_TOS[i]) \n", - "\n", - "n1=h_mc.Integral(\"width\")\n", - "h_mc.Scale(1/n1)\n", - "h_mc.Integral(\"width\");" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "TFile::Append:0: RuntimeWarning: Replacing existing TH1: data below signal (Potential memory leak).\n", - "TFile::Append:0: RuntimeWarning: Replacing existing TH1: data over signal (Potential memory leak).\n" - ] - } - ], - "source": [ - "h_data_under= r.TH1F(\"data below signal\", \"data below signal\",nbins, 0, 2)\n", - "h_data_over= r.TH1F(\"data over signal\", \"data over signal\",nbins, 0, 2)\n", - "for i in range(len(data_Hlt2Phys_TOS_under)):\n", - " h_data_under.Fill(data_Hlt2Phys_TOS_under[i])\n", - "for i in range(len(data_Hlt2Phys_TOS_under)):\n", - " h_data_over.Fill(data_Hlt2Phys_TOS_under[i])\n", - " \n", - "n2=h_data_under.Integral(\"width\")\n", - "h_data_under.Scale(1/n2)\n", - "h_data_under.Integral(\"width\");\n", - "n3=h_data_over.Integral(\"width\")\n", - "h_data_over.Scale(1/n3)\n", - "h_data_over.Integral(\"width\");" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_under.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_under.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Hlt2 Phys TOS Signal MC/ data below peak comparison\", fontsize=20)\n", - "\n", - "plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.5, alpha=0.6, label=\"data below Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "a=[h_mc.GetBinContent(i) for i in range(nbins)]\n", - "b=[h_mc.GetBinCenter(i) for i in range(nbins)]\n", - "c=[h_data_over.GetBinContent(i) for i in range(nbins)]\n", - "d=[h_data_over.GetBinCenter(i) for i in range(nbins)]\n", - "plt.title(\"Hlt1 TrackMVA TOS Signal MC/ data over peak comparison\", fontsize=20)\n", - "\n", - "plt.bar(b,a,width=0.5,alpha=0.4,label=\"Signal MC\")\n", - "plt.bar(d,c,width=0.5, alpha=0.6, label=\"data over Ds mass peak\")\n", - "plt.legend(fontsize=20)\n", - "fig = plt.gcf()\n", - "fig.set_size_inches(16,8)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [], - "source": [ "#h_data_under.SetLineColor(38)\n", "#h_mc_under.SetLineColor(46)\n", "#\n", @@ -1279,15 +734,15 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 52, "metadata": {}, "outputs": [], "source": [ - "with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/MC_for_NN_'+l_flv[l_index]+l_flv[l_index]+'_Mag'+mag_status[mag_index]+'.pickle', 'wb') as handle:\n", + "with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/MC_for_NN_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'wb') as handle:\n", " pickle.dump(MC_tuple_sig, handle, protocol=pickle.HIGHEST_PROTOCOL)\n", - "with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/data_for_NN_'+l_flv[l_index]+l_flv[l_index]+'_Mag'+mag_status[mag_index]+'.pickle', 'wb') as handle:\n", + "with open('/disk/lhcb_data/davide/Rphipi/NN/'+l_flv[l_index]+l_flv[l_index]+'/data_for_NN_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'wb') as handle:\n", " pickle.dump(data_tuple_bkg, handle, protocol=pickle.HIGHEST_PROTOCOL)\n", - "with open('/disk/lhcb_data/davide/Rphipi/NN_for_selection/'+l_flv[l_index]+l_flv[l_index]+'/data_for_NN_'+l_flv[l_index]+l_flv[l_index]+'_Mag'+mag_status[mag_index]+'.pickle', 'wb') as handle:\n", + "with open('/disk/lhcb_data/davide/Rphipi/NN_for_selection/'+l_flv[l_index]+l_flv[l_index]+'/data_for_NN_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'wb') as handle:\n", " pickle.dump(data_tuple_dict, handle, protocol=pickle.HIGHEST_PROTOCOL)" ] }, @@ -1297,6 +752,13 @@ "metadata": {}, "outputs": [], "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": {