From 065f4baf142127a30ac3b91f0cfbde5fc6bd00dc Mon Sep 17 00:00:00 2001 From: cetin Date: Sat, 27 Jan 2024 14:02:41 +0100 Subject: [PATCH] VELO --- trackinglosses_endVelo_momEff.ipynb | 28 +- trackinglosses_energy.ipynb | 80 +- ...glosses_rad_length_beginVelo2endVelo.ipynb | 1264 ++++++++++++ trackinglosses_rad_length_endVelo.ipynb | 591 ------ trackinglosses_rad_length_endVelo2endUT.ipynb | 1718 +++++++++++++++++ 5 files changed, 3037 insertions(+), 644 deletions(-) create mode 100644 trackinglosses_rad_length_beginVelo2endVelo.ipynb delete mode 100644 trackinglosses_rad_length_endVelo.ipynb create mode 100644 trackinglosses_rad_length_endVelo2endUT.ipynb diff --git a/trackinglosses_endVelo_momEff.ipynb b/trackinglosses_endVelo_momEff.ipynb index 741abbe..f19eb5d 100644 --- a/trackinglosses_endVelo_momEff.ipynb +++ b/trackinglosses_endVelo_momEff.ipynb @@ -68,12 +68,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAABkMAAAL5CAYAAAADsVMKAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACix0lEQVR4nOz9cXDk130gdn5/M7TpqSOH4MgZlrOXJdmgri7aoyx2j3QX62LdroC1fXvZ7GoAMpXLZXW3GiA8uDa3Khsw964KRJJbCCglcZxgaYDaKm75cjkRGDoXn1deA3SireU6Kw7aWnHXSZ0GTcq3kkKuNAMN6YwpDeZ3f4waGsz07wH4obvR3fP5VHWJ09/fe+/7+3U39Hv9+r2X5XmeBwAAAAAAwIA6cdwJAAAAAAAAdJLBEAAAAAAAYKAZDAEAAAAAAAaawRAAAAAAAGCgGQwBAAAAAAAGmsEQAAAAAABgoBkMAQAAAAAABprBEAAAAAAAYKAZDAEAAAAAAAaawRAAAAC6rl6vx+LiYtRqtRgdHT3udI6s186n0WjEyspKT+QCANALDIYAAAyYtbW1GB8fjyzL9jy2t7cPVc/w8PCe8rVaLWZmZjqTNPeUjY2NmJyc3PMeGx4ejtHR0VhcXIx6vR71ej2Gh4ePO9VDW1tbi4cffjgWFxePO5WeVq/X44tf/GLMzMxEvV4/cLnml/t3/n07yKOTUueztrYWtVrtrnya7/ei+u78Oz4+Ph6NRuNAuYyOjsbw8HBMTk7GxsZGW84RAKDfZXme58edBAAA7bexsbHnF8HT09OxsLBwoLLNAZWmkZGRWF9fb3uO/aw5uDQ0NHSseXTTUc+5+QVvo9GISqUSk5OTMTIyEkNDQ9FoNKJer8f8/Pyedq5evdqe5NsodR1qtVrU6/WoVCqxtbXV3cT60Pj4eKytrR36b8zMzMzuQMLIyEisrq7ueT22t7fjypUr0Wg0dgcoutH1TZ3P6Ojo7sBEtVqNzc3NfetbXFyMmZmZWFhYiOnp6UPlsrKyEpOTkxERXTl3AIBeZ2YIAMCAGhkZ2fPvw/xSfX5+fs8Xi5ZZudtBf6U9SI5yzisrK1Gr1aLRaMTY2FhsbW3F9PR0VKvVqFQqMTIyEtPT03H16tWYmJiIiDj0bKZuSV2HhYWFGBkZOfDA473uzJkzpcrd/jepWq3eNTA1NDS0+7569dVXj5LioaTOZ3V1dfe/Dzob5rvf/W4MDQ0deiAkIqJSqRy6DADAIDMYAgAw4KrV6u5/H2RApLlEUfML6Yh7a/bDQczMzNxzS88c5ZzX1tZ2f6E+MTGx50vhVpaXl2NsbKxUW52233Vozgjo1fzvRUNDQz3xegwNDe35u3qQv8crKyt7ygAAUJ7BEACAAffcc8/t/vf8/Py+x8/Pz8fY2Fh89KMf7WRafWttbe2e2w/iKOe8vb29Z8m1g86YePHFF3fL94p78bUfFPsNwHXL7e///f4eb2xsxPb29p6/4QAAlGcwBABgwFUqld1fRW9vb8fKykrhsdvb27G2tnboL98WFxdjdHQ0arXa7kbYqXaae5I0N2RvbvibZdldm083Go2YnJyMhx9+eHfT4dQX5Nvb23s2567Vai2/wG5ei9tzXVlZ2VOu1UbIFy5c2P33Jz/5yXj44Yfj4Ycf3o3fvlHy7TMIFhcX98Tu3Iy+k9ekyNraWoyOjsb4+Pju63fn67bfOe/n9i98p6enDzzL6M5f0Ufc+nJ4fHx8N8fJycnd87/dQd8DTe28Ds09Kmq1WvL8DvOZKfNePaiDnHu7cpiZmYnh4eGo1WqF7bRbo9FoOZPnuM7n9lkqzb+3RRYWFmJsbOyuvVAO894+iMP+/QYA6Fs5AAADKyLyzc3NfHNzM4+IPCLySqVSePz09HRerVbzPM/z1dXV3TLLy8stj9/c3MwrlUo+Nja2+9zVq1fzsbGxPCLykZGR/OrVq7ux9fX1fGRkZLfeiYmJ3Tanp6fziYmJPW2urq7mlUpl97hKpZJHxG6Od1pfX8+r1Wq+vr6e53meb21t7bZ3e5nmcc22FhYW8rGxsbxareYTExO77UTEnvyb59eMbW5u3pXD1tbWbryZx+2GhobyiMinp6e7ck2KNNu8/fymp6d3r8dhzjnl9mvZ6nocxMLCwp56lpeX85GRkd1rGRH51tZWnucHfw80tes6bG5u7nkdh4aGWp5Lmc9M2ffqfg567kfN4erVq3m1Wr3r3Jrn3Dzvw1hfX98t2/wstbK8vHzX63jc53P734iiv8fNY27/zBz2vX37NWrlsO9FAIB+ZzAEAGCA3f6l7e1f1K6urhYe34wdZDBkaGio8EvfZnutvhRM5dL88n9oaGjPl3R5vvdLxOaX33fG7vyS+vYvsO/80rT5ZfrQ0NCeLx2vXr26GyszMJD68r/5ReuduXTimhRpfkl652vXrOvO58sOhtxe7jD57VdXpVLZvbYLCwv5xMTEnvwP+h7oxHW4/bVqpexnpsx7NeWw536UHKrVavJ6dGIw5OrVq/n6+no+NDRUeF2O83xu/7y3+jvRHOhsKvP3bb/BkLLvRQCAfmWZLACAe8TtyzK1Wqt+ZWVlz5JaB6lve3u7cHPf5tr4Gxsbdy0F01z2ZWRk5K72mvtLbG9v7+4b0VSpVHbL3rmEzczMTAwNDe3ZML7ZVvO5O5d+qVQqEXFrU++RkZE9Zc6dOxcREVtbWy3Pr6yiZaI6cU320zz/pjNnzuy20469Oq5cuZJs7zCGhob2XKPm6zU9PR3Ly8sRUe490Cqvo1yH1PJYR/nMdOq9ephzL5PDyspK1Ov1wqX3bq+nrMXFxd3l55qPhx9+eN/l447zfG7/e9xqH52VlZWYnJzcc3yZ93aq/bLvRQCAfmUwBADgHjEyMrL7pVm9Xr9rHf2FhYW79rFIaX5BVrTRerVa3f2y8Ytf/OKeWPML11YDA81YkWa80Wjclc/29nYMDw/f9WgOEhzmy+1m7ne20ymduCZFRkZGYmtrKzY3N/c8f3v5OwcyyujU5udFAw6HfQ904jqkXqujfGZSyrxX233uRTk0v1S/80v8pv3e2wcxMTERW1tbex6bm5uxurp64D1q7tTp87n97/HGxsaegczm+/j2gYp2/33r1HsRAKCX3XfcCQAA0D3PPffc7iyDhYWF3V8xr62txZUrVwp/JdzKQb54rVQq0Wg0Sm/u3EqrLzeb9Y+MjMT6+nrb2uoXZb7wvX1GwNraWnzxi1880syN/dqIuPVlbdkvp/dT9j3QjevQdFyfmVRbTZ069+Y5d+qaRtx6/7eqv1qttn0ws53nc/vf4/n5+VhdXd3979s3Tu/E37deey8CAHSDmSEAAPeQsbGx3S/xbv818vz8fOmBkNSvx5tttWOWQUqz/m7N4hgUKysrMTw8HFeuXInV1dXCpX/Kun1pq4iIS5cutbX+2x3lPdDp63BnXr3wmWnq5Ln3wufx9r95R9Xu87k9t7W1td2BhzuX4Wr337defS8CAHSamSEAAPeYmZmZ3bXo5+fn47nnnot6vR6vvvrqgeu4/cvF1D4FzS/CO/mr8IjDLxNFxOjoaGxsbMTW1lZHX5+RkZHdJXnW19fbskdEK2XfA926Dr32mYno/LnfvmRTo9HoyjndqVKptK3dTpzP7X+Pm0twVSqVPctwtfvvWy++FwEAusHMEACAe8zExMTul1xra2tx4cKFPc8d1O0zTIo0v7xrbkbcKXcu91Nke3v7UJsMd0Kn9tE4jJmZmdjY2IiJiYmOf9F5+4bvi4uLHTv/Mu+Bbl6H23Pshc9MN8799i/0e2GppTv35jisTpzP7X97V1ZWYmVl5a69mzrx962X3osAAN1iMAQA4B50+xIs9Xq95cbp+y2N0vw1c71eL/zFcvMLw8NszF7G7XsGXLhwofAL9/Hx8bbOTNjvGrXKoxeWnGl+oTo8PHzosofNf2hoaPcX7xG3Xp+DWlxcPPCXzmXeA928DhG99Zk5yrkfRvM1mZ+f72g7B9Hcn+MoOnE+dy5NdueShZ34+9ZL70UAgG4xGAIAMKCaX5i1+qJrenp6978PsqZ+qy/fpqend8vd/mV3U/NLttuPazrKgEAzl+9+97t7nm/msL29HbVabc+X6PV6PWq1WlSr1QP/Cr4ox9tn0Nzexu3XudnG8vLynrK3f6l455f8nbgmRZptffGLX9zz/O1f8N7+mh/knFOmp6djbGwsIm59CT8+Pp6cIdJoNGJ8fDy2trb2/Bp/P4d9D3TiOjTrbPdnJqXMe+ew5142h9tfkzsHI7a3t+Pll1+OiM4vcdds+6Dvp26ez+1/j4v2bmr337dOvRcBAHpaDgDAQFpeXs4jIh8bG2sZn56eziMi39zcbBkfGxvLIyJZx9bWVl6pVPKIyBcWFu56fmJiomW5kZGRPCLykZGRu2Krq6u77a6vr98VHxoaKszp9pzvfLTKJVVXtVrNIyKvVquF+Q8NDeULCwv5yMjInlwXFhZ2261Wq/nY2FheqVTyhYWFu3Lc2trq6DVpZWJiYre+SqWym9/t7TSfvzO/onM+iIWFhd1cm6/J8vJyvr6+nq+vr+fLy8v52NhYPjQ0lK+urt5VPvVaNh3mPdCJ69D8XEVEfvXq1bvyK/uZKfteLVLm3MvmcGdb09PT+fT0dF6pVHbLNa/pQd9Tt1/nkZGRfGtra8/1vnr1ar61tZUvLy/vtnFn3r14PkV/j/P88H/fmv8f0O73IgBAvzIYAgAwYJaXl3e/sL39C/nbv+zK81tfFrb64n16enrPF3qpOpqaXwo3vwws+qJ8c3NzzxeJzS/xml8A3vlleXMAIc/zfH19/a7zmpiY2P2i9s7zHxoayoeGhlrmsrm5WVjX1tbWXV863v6FcJ7f+rLw9i9LW53rwsLC7heNIyMju+c4MTGRj42N7X7Z341r0srExMTuNZqYmNj9srQ5kFOpVPac10HO+aCagx7N63P7F++tBkFuv5a3n2erY5v17/ceaPd1aPU6tuszc5T3aspBz70dOayuru6+JrcPskxPT+djY2MHfj+1+vt20Mfy8nLbrmm7zqfp6tWrBxrMOsh7e2trqyPvRQCAfpfleZ4HAAAAAADAgLJnCAAAAAAAMNAMhgAAAAAAAAPNYAgAAAAAADDQDIYAAAAAAAADzWAIAAAAAAAw0AyGAAAAAAAAA81gCAAAAAAAMNAMhgAAAAAAAAPNYAgAAAAAADDQDIYAAAAAAAADzWAIAAAAAAAw0AyGAAAAAAAAA81gCAAAAAAAMNAMhgAAAAAAAAPNYAgAAAAAADDQDIYAAAAAAAADzWAIAAAAAAAw0AyGAAAAAAAAA81gCAAAAAAAMNAMhgAAAAAAAAPNYAgAAAAAADDQDIYAAAAAAAADzWAIAAAAAAAw0AyGAAAAAAAAA81gCAAAAAAAMNAMhgAAAAAAAAPNYAgAAAAAADDQDIYAAAAAAAADzWAIAAAAAAAw0AyGAAAAAAAAA81gCAAAAAAAMNAMhgAAAAAAAAPNYAgAAAAAADDQDIYAAAAAAAADzWAIAAAAAAAw0AyGAAAAAAAAA81gCAAAAAAAMNAMhgBwz6rX67GysnLcaQAAAADQYQZDAOiIer0eMzMzMT4+HsPDw7G4uHjcKe1qNBoxPj4etVotlpeXk8dubGzE6OhoZFkWWZbFww8/HMPDwzE8PByjo6MxMzMTjUajS5kDAMBgafYbarVa1Gq1Y83FvT/AYMvyPM+POwkABku9Xo9PfvKTcfXq1YiImJmZie3t7X0HHroty7KoVquxubl5oGMjIjY3N6NarUZExNraWly4cCG2t7djfX09RkZGOpovAAAMonq9HrVa7cD35mU0Go04c+ZMDA0N7Xuse3+AwXTfcScAwOCZn5+PM2fO7P57YWHhGLNpr9s7T2NjYxERMT4+HuPj47uDPwAAwME1Bxw6aXx8PFZXVw80GNLk3h9gsFgmC4C2q9frx51C2xV1mpq/CNve3jZlHgAAetD4+Pih+iju/QEGk8EQANpmZWUlxsfHo9Fo7O7LMT4+HhsbG7vHbG9vx+TkZMzMzMTo6GiMjo7uia+trcXDDz8cWZbtdlg2NjZifHw8siyL8fHx3XpWVlaiVqvF2tpabGxsRK1W23PM7ZrtNh/t2sPkypUrbakHAAC42379hzuPmZycjOHh4VhZWYmIW/2LZr9icnLy0AMjt3PvD9DfLJMFQNtMTEzExMREDA8PR0TE6urqnnhzL5FXX311dyr8yspKjI6OxsLCQkxPT8fY2Fisr6/vdl4ibv0Cq1KpxNra2u5zV65cifX19ajX67G8vBzVajVefPHFWF5ejpWVlVhcXIzp6emIuLU+cK1Wi9XV1d1fc7VrMKSZU7VajUql0pY6AQCAg/UfIiIuXLgQlUpld3nelZWV2N7ejohby1u9/vrrsbi4GMvLy0e6Z3fvD9DfzAwBoGsuXLgQ586d27Mm8MTERFSr1ZiZmdmdat5qWvrte5BERFQqlXjmmWciInY7Q9VqdXeT9vX19d1jZ2Zm4ty5c3s2OWx2nA6r2alqNBqxuLgYMzMzUa1W49VXXy1VHwAA0NpB+w93zhSZmJhoS/vu/QEGi8EQALqi0WhEvV5vuTni5ORkRMTuQMZhtRo8aU5hbzQasba2FqOjo6XqvtP4+HgMDw/H+Ph4vP7667G8vBybm5uH2ogRAABIO0z/oVKpxOLi4p7Z32V//HQ79/4Ag8UyWQB0RWpd3nPnzkVEdGQTwmad7ZrGvr6+bko8AAB02GH6D6urq1Gr1WJmZiaWl5djdXW15SDKYbn3BxgsZoYA0FXNqea3a/6y6s6lsNqh2UGy2SEAAPSfg/QfKpVKvPnmmzEyMrK7X+DtexACQITBEAC6pPnLrDvX8434UQenufF6OzV/ybW5udn2ugEAgM44TP+h0WjE0NBQrK+vx+rqakT8aCktAGgyGAJA2125cuWumRiVSiWq1Wo0Go27lsO6dOlSDA0N7W50+IEPfCAi9i6b1fzvVr8MS2lOoV9ZWWlZ9qD1NY87bPsAAMDhHab/sLCwsBsbGxvb3UvkznLu/QHubQZDAOia1dXVGBoa2vMrre3t7VhYWIgXX3xxd7p781dgMzMzsbGxESsrK7sdmo2Njd3N0A+y9NXQ0NDu5om1Wi02Njai0WjEzMxMRNzqIN2+0eJ+LLcFAADdcdD+w8svv7xn4GN7ezsqlcruLPHmDJLl5eVoNBqxtrZ2oPbd+wMMlizP8/y4kwBgMNTr9VheXt5dn3diYiLGx8djZGRk95jt7e24cOHCbgcl4tYU9js3OFxcXIz5+fndehYWFmJ4eDjGxsbimWeeiYiICxcuRL1ej0qlEsvLy3Hu3LmYmZnZbX9hYWF3IGRlZSUWFhai0WhEtVqN1dXVGB0djbGxsZicnCzcGHFjYyMWFhZ2p+dXKpWYnJzcrRcAACjvzj7EwsJCTExM7A50HKT/MDo6Go1GI8bGxiLi1g+ebh8sibj1w6hGoxFPP/307g+t7uTeH2CwGQwBAAAAAAAG2n3HncCd1tbWYn5+fs8vfW//RXHErV8NzM/PR6VSie3t7d1f9h7XMQAAAN2k3wQAQK/b3t7eXfXj9v2dmrp9n9lTgyErKyuxubm5e2FmZmZidHQ0tra2dqdCNhqNqNVqsbm5uTslcnh4OK5cubK7cVY3jwEAAOgm/SYAAHrdxsZGLC8vx9raWst7wuO4z+ypZbIWFxf3rMNYr9ejVqvF6urq7mhPc9Pc9fX13eNWVlZicnIymqfSzWMAAAC6Sb8JAIB+kWVZTExM3LVf03HcZ544dIkOunNDquZGV81Rn+3t7djY2Ni9CE3nzp2LiFsXopvHAAAAdJt+EwAA/ey47jN7ajDkTmtra7GwsLA71fvSpUsREbv/bmre9K+vr3f1GAAAgOOm3wQAQD85rvvMntoz5HYzMzOxsrISL7744u5zjUYjIn70y6c7NRqNrh5T5Dvf+U789m//dvzUT/1U/MRP/EThcfv58R//8fjxH//x0uUBAOAgvv/978f3v//90uX/5E/+JL797W/HX/gLfyF+8id/so2ZsZ9+7TfpMwEAx23Q7oH/6I/+KL7zne8cutxRr0NExE/91E/FBz/4wQMf3+nv54v05GDI4uJiNBqN2N7ejvHx8VheXo6JiYnY2tqKiIgzZ860LLe9vd3VY4r89m//dnz6058ujAMAwCB66aWX4q/8lb9y3GncM/q536TPBAAMil64B/6jP/qjeOLRR+MHx9T+j/3Yj8Xly5fjT//pP32g4zv9/XyRQw2GXLt2LTY2NqLRaES1Wo0/9+f+3KEbPIjmGrgbGxsxPj4eCwsLMTExEcPDwxERceXKlZblKpVKV48p8lM/9VMREfFrv/Zr8dM//dOFx+2n6FdO58+fj4sXL5audz+drL9fc3/vvffiE5/4RHz5y1+OBx54oO31R7jux1F3p19X1737dXtNj6fuTtbv7+/x1e+zejz1H1fuB/012CfeKgj89/84Yv6v7d4H3+v0m/Ye00q7+0zt/Oz0Yl3tqqfdf38H+Vq1sy7X/Xjqct2Pp65eve69eK3aWZfrXq6uw8yI+N1PfOKu5/4oIn4joifugb/zne/EDyLiUxFx2DkqOz98lPXdiPitH/wgvvOd7xx4MKTT388XOfBgyPe+9704d+7cnuknw8PDsb6+Ho8++uihGz6IkZGRmJiYiMXFxYj40QkWjfpUKpWuHlOkOc37p3/6p+Nnf/ZnC48r69SpU7tro3VCJ+vv19yvXbsWEREf+chH4vTp022vP8J1P466O/26uu7dr9trejx1d7J+f3+Pr36f1eOpv+dz36dndZTljgaFftPdx7TS7j5TOz87vVhXu+pp99/fQb5W7azLdT+eulz346mrV697L16rdtblune+rv9fItZL98A/GRH/YpfbLLNgaae/ny9y4MGQmZmZ2NraipGRkRgaGop6vR6XL1+OWq1Wai2yg/roRz+6e2LNneLvXA+s+e9ardbVYwAAAG6n33T3MQAAdMd90f19Mcq0d1z3mScOemBzmvfv/u7vxssvvxyXL1+OS5cuxc2bN+Nv/+2/feiGD6rRaMTIyEhE3NospVqt3rVT/MbGRkREPP300109BgAA4Hb6TXcfAwAAtzuu+8wDD4ZUKpV47LHH9jxXrVbjxRdfjEuXLh264Ts1N/1bW1vbfa7RaMT6+nosLy/vPvfiiy/udjCaFhYWYmFhYXdn+W4eAwAA0KTf1PoYAAA6776I+LEuP1IzQ1KbnB/HfeaBZ7E8/PDDLZ8fGRmJlZWVQzd8p6Ghodje3o4LFy7E8vJyjI6ORqVSuWvkp1qtxubmZszMzESlUolGoxEzMzMxMTFxLMcAAMAgyRp5cfDPvFMQuNqRXPqRfpN+EwDQ3+ay7K7nZvO775H//t//+/F/b7GxOrfU6/XdH+u8/PLLMTo6uruUbMTx3GceeDBkdXU1PvCBD8TIyEiMjIzsbsbz0EMPxXe/+91Sjd/pzhv4ItVqNVZXV3vmGAAAgAj9JgAAiLh1f7i8vLxn9nKrY7p5n3mo/U1uT75SqeyO5gwPD7clGQ5mamqqb+vv59w7zXXvft2d5rp3v+5O85oeX/2d5Lp3v+5Oc92Pr35u0W/qvna+t3uxrl797A76tXLdu19Pu+tqp148x17Mqd0G/Vq57v1fV685Gd3fQP1kl9s7iizPW8zxaeHMmTPx9NNPx9bWVrz66qs/quCH04ZqtVo8/fTTMTIyEh/5yEciIuILX/hCfOYzn2l/1j3u7//9vx+f+MQn4stf/nL87M/+7HGnQxtcu3YtHnroofje9763++s++p/XdfB4TQeP13QweV17W3KZrOGiZbL+24j4S+5/Q7/poPSZjoe/v8fDdT8ervvxcN2Ph+veXodZJqtX7mfq9XrUarX46xHxP+1y2/8sIv7jiNjc3Ixqtdrl1g/nwANFCwsLceHChd1//8Ef/EF88YtfjI2NjajX63Hp0qXY3NyMiFvr2J47dy4uXbp0z93UAwAA9y79JgAAjktzA/Vut9kvDpzr7Tf0ERFPPfVUPPXUUxER8b3vfS82NjZifX19d3f39fX13V8/AQAA3Av0mwAAoDe1ZeDmoYceivPnz8f58+cjIuLNN9+M9fX1+JVf+ZV2VA8AAND39JsAAOgke4akdeTaPP744zExMeEXTgAA0IOyP0wE/0ziHv6+R1o/f/PhiJtHSumepN8EAHB8Wu0NEtF6fxAGw4lOVn7nFHEAAAD20m8CAIDO66f9TQAAAAAAgBZsoJ7W0ZkhAAAAAAAAx62fBm76xo//+I/v+V/63/333x+zs7Nx//33H3cqtJHXdfB4TQeP13QweV0HkftfDkef6Xj4+3s8XPfj4bofD9f9eLjux6MX72dsoJ6W5bkdYdqtXq9HrVaLzc3NqFarx50OAADskd5APREr6lnl9Ygd978cnD4TAHDcjrqBei/dzzRzmY2Ix7rc9lsRMRfRE9dhP0ceKHrrrbdieXk5Go1GnDlzJp544om4cOFCnD59uh35AQAAJTwR/7Q4+GdSIx6vFIduXCsIvHWAjO5t+k0AAMfjqIMeDI4jDYZ8/vOfj5mZmbhzcsnf/Jt/M77whS/EX/7Lf/lIyQEAAPQ7/SYAALrBBupppXN99dVXY3p6OqrVakxOTsa5c+diaGgotre34/XXX49f/uVfjscffzw+8pGPtDHd/nL+/Pk4depUy9jU1FRMTU11OSMAACjrSxHxdwti3+9mIn1FvylNnwkA6GVLS0uxtLTUMnb9+vUuZ8NRlR4MWVhYiOXl5bhw4cJdsaeeeiqefvrpeO655+KFF144UoL97OLFiz2/ThoAABzML0TExwtib8WtlYK5k35Tmj4TANDLUj/OaO7T0Uvui+7P1OinmSEnjlK41Q1909DQ0FGqBgAAGAj6TQAAcPxKD9wcZNSr0WiUrR4AAKDv6TcBANAt9gxJK53r1atX4x//438cP/3TP31X7K233orJyUm/cgIAgA76V2O9MLaVPZYo+aVErGgprIiIesHz7ybK3Nv0mwAAumcuy+56bjbPjyETelHpwZDPfe5zUalU4qMf/ejuGq/b29uxsbERjUYjhoaG4s0332xbogAAAP1GvwkAAHpD6cGQoaGh2NjYiAsXLsTCwsKeWLVajdXV1Th9+vSREwQAAOhX+k0AAHSLZbLSjpRrtVqNzc3NePPNN6Ner+8+9/jjj7clOQAAgH6n3wQAAMevLQM3jz/+eMsb+WvXrvmVEwAAQOg3AQDQWSej+zM1Tna5vaM40cnKV1ZWOlk9AABA39NvAgCAzjvwQNFHP/rRQ1der9fjl37plw5dDgAAuOWJ+KeFsa1sNFHytUTsT5Us93bB899KlLm36DcBAHTeXJa1fH42z7ucyb3htyLi/1MQ+343EzmiAw+G5Hm+u77tQWUFb0oAAIBBpN8EAMBx6dQG6p/64aOVr0fE/7kDbXbCgZfJGhkZic3Nzbh58+aBHxcuXOhk7gAAAD1FvwkAAHrTgWeGPPPMM/HUU08dqvLJyclDJwQAANCv9JsAADguNlBPO/DMkKIb+mvXrsXv/d7v7f771Vdf3f33YTsBAAAA/Uy/CQAAetOBB0NaefbZZ+Phhx+OP//n//zuc5/85Cdja2srnnvuuSMnBwAA0O/0mwAA6IbmniHdfHR7JspRlM71V37lV2J5eTmGhobu2vDvwoUL8ef//J+Pv/23/3b81b/6V4+cJAAADLKfvPnNwth3T/6ZRMlXErHLidjZROyRRIzD0m8CAChv4477p6bZPO9yJgyC0jND1tbWYm1tLa5cuRKf/OQn74qPjo7G5z73uSMlBwAA0M/0mwAAoDeUnhlSqVTiU5/6VETEXb9wioh4/fXXo9FolM8MAACgz+k3AQDQLTZQTys9M2RoaGj3v/M7piX9wR/8QaytrUWlUimdGAAAQL/TbwIAgN5QeqDoueeei5/7uZ+LhYWF3V84vfXWW7G2thYzMzORZVlMTk62LdF+dP78+Th16lTL2NTUVExNTXU5IwAAKOu3IuI3C2I/6GYifUW/KU2fCQDoZUtLS7G0tNQydv369S5ns7/mBurdbrNfHDjXr371q/GRj3xk999PPfVUzM/Px2c+85mo1+uxtrYWET/6tdPMzEz80i/9Unuz7TMXL16MarV63GkAAEAb/GsR8WRB7I8iwr4XEfpNh6XPBAD0stSPM+r1etRqtS5nxFEceDDkwoUL8frrr+95rlqtxqVLl+LNN9+Mzc3NePPNN6NSqcTIyEg89NBDbU8WAAD61V+M1cLYd39yPFHy6yVb/PlE7JuJ2Fsl2yNCvwkAoKy5Fvurzd6xzCgcxYEHQzY3N+MDH/hAPPfcczExMRGnT5/ejT3++OPx+OOPdyRBAACAfqHfBADAcbkvur9sVT8tk3XgDdSr1Wp87nOfi8uXL8djjz0WzzzzTPze7/1eJ3MDAADoK/pNAADQmw48GPLcc8/FhQsX4td//dfjypUr8fTTT8f09HR84AMfiM9//vNx7dq1TuYJAADQ8/SbAAA4Ls0N1Lv5GMiZIefPn7/r35cuXYrXX39991dPP/dzPxe/+Zu/2fYkAQAA+oF+EwAA9KYDD4YUqVQqu796mpiYiL/6V/9qfOADH4i/8Tf+Rrz11lttSBEAAKC/6TcBANBpJ+NH+4Z063GyK2fWHm2bxfKFL3whFhYW4nvf+17keR6f+9zn4urVq/HCCy+0qwkAAIC+pt8EAADH40iDIdeuXYv5+flYWVmJ7e3tyPM8hoaG4rnnnouJiYl46KGH2pUnAAD0vL8Yq4Wx38rGS9a6kYh9PBGrJ2LvJGJPpNNp6Y9LlLl36DcBAPzIXJa1fH42z7ucCfeaAw+GvPLKK/GpT30qIiK++tWvxvz8fKytrUVERJ7nUalUYmZmJi5cuNCZTAEAAHqcfhMAAMeluYF6t9vsFwfOdX5+Pq5cuRKrq6uxsbER+Q9H6kZGRmJmZiY++clPdixJAACAfqDfBAAAvenAgyGbm5sxOTm5ezM/NjYWCwsL8fjjj3csOQAAgH6i3wQAwHExMyTtxGEOzvM8pqen4+rVq/Hyyy+7oQcAALiDfhMAAPSeAw/cVCqVqNfrcfr06U7mAwAA0Lf0mwAAoDcdeDBkeXnZDT0AAPe8yfhPCmO/lf27xQUfTlR69bVE8LFE7HIidj0RezARO1UYyfNfaPl8vV6PWi1R5T1EvwkA4Ja5LGv5/OwPlxOl/U5G95etOtnl9o7iwMtkHXajv89//vPx1ltvHTYfAACAvqXfBAAAvelAA0UvvvhirKysHLjS7e3taDQaceXKlfibf/Nvlk4OAACgX+g3AQBwnO47GfFjrSfkdK7NPCJ2uttmWQcaDDl37lxMTk4euvLV1VU39QAAwD1BvwkAAHrXgZbJeuqpp2JsbCxu3ry5+1hYWIiFhYU9z93+mJ6ejvX19U7nDwAA0BP0mwAAOE4nT0bcd193Hyf7aNOQA+8ZsrCwsOffjUYjfvmXf7nw+MnJyRgfHy+fGQAAQJ/RbwIAgN504M3lH3/88UNV3Gg0ol6vHzqhQXL+/Pk4depUy9jU1FRMTU11OSMAAA7iX43iX+r/gx/7dxMl3y4OXf1SotwjidhbiVjKxxOx1H160Tm8Gln2mYLY9w+W0j1Av+lw9JkAYDDMZXdvVDGb58eQSXstLS3F0tJSy9j169e7nA1HdeDBkDvleR7/9X/9X8ef/bN/9q7YtWvXYnJyMiqVypGS63cXL16MarV63GkAAEAbfPKHj1beioi57qXSR/Sb0vSZAIBelvpxRr1ej1qt1uWM0u47EfFjHVi26td/ELHyg9axP+mjMa/SgyGf+9znolKpxEc/+tEYHR2NSqUSV65cic3NzVhZWYmIiOXl5bYlCgAA0G/0mwAA6Hf/zo/derTyBzsRH/+T7uZTVunBkKGhobh06VLMzMzE9PR0ZD+cCpX/cPrT9PR0fOYzRdPoAQAABp9+EwAA3XLffRH3dXlD8/vuXiGtZ5UeDImIqFQqsbq6Gm+++WZsbW3Fm2++GZVKJc6dOxcPPfRQu3IEAADoW/pNAABw/I40GNL0+OOPt9wo8POf/3z80i/9UjuaAAAA6Gv6TQAAcHyONBjy+c9/PtbX1+PKlSst4/V63U09AAA96S/GamHsH2TjiZIvJWKfSsROJ2LXE7Fy8vzDhbEs+81EybOJOp9t+fytzSNtoF5EvwkAGBRzWes1kWbzPtpFe4DddzLix9oy/eEQbXa3uSMpneszzzwTq6vFHciI2F0PFwAA4F6k3wQAAL3hRNmCq6urMTk5GTdv3ix8XLhwoZ25AgAA9BX9JgAAuuZERJzs8qP0CEP3lU61Wq3G5ORk8piFhYWy1QMAAPQ9/SYAAOgNpQdDFhYW4otf/GLymM3NzbLVAwAA9D39JgAAuuZk3NoYo5uPk105s7YovWfI9vZ21Ov1+PznPx9DQ0Mtj1lYWIivf/3rZZsAAADoa/pNAADQG0oPhszPz0e9Xo/19fXCY2wECADAcfo78Uxh7Lf+xdSv9d9OxE4nYq/tl1KBa4nYu4nY2cJIli0myj2ZiL2RqHOuIPKtRH33Nv0mAKBfzbW4R5nN82PIBNqj9GDIxMREbGxsxDPPtO5gfve7342VlZXSiQEAAPQ7/SYAALqmuXRVN93scntHUPrSPPPMMzE6OhqPP/544TEf/ehHy1YPAADQ9/SbAACgN5QeDHnooYfioYceuuv5t956K86cOROnT5+Op5566kjJAQAA9DP9JgAAuqa5gXo37XS5vSM48KX5vd/7vd3//nN/7s8VHnf16tUYGxuL733vezE6Ohp/62/9raNlCAAA0Cf0mwAAoDedOOiBIyMjMTMzE9vb2xERce3atbseERFPPfVUXLp0KR577LFYXl7uSNIAAAC9SL8JAAB606Emzbz++uu7/72+vh7z8/PxB3/wB1GpVGJycjJ+6Zd+aTe+vLwcH/zgB9uXKQAAtPBvx4uFsd/4mS8WF/z2tUStryRipxKxy4nYg4lYSqrcOyXLpc4hFbueiNGk3wQA9JO5LGv5/GyedzkTjuxE3Foqq9tt9okDD4ZUKpU9/z5//nycP38+Tpw4Eevr6/HYY4/ddXxqk0AAAIBBo98EAAC96cCDIQ8//HDL5yuVyl039PuVuVecP38+Tp1q/cu6qampmJqa6nJGAABQ1j+MiNcKYje6mUhP0286HH0mAKCXLS0txdLSUsvY9es9OGv6ODZQ7/ZMlCM48qXJCqZREXHx4sWoVqvHnQYAALTBz0TEUwWxb0XEShdz6T/6Ta3pMwEAvSz144x6vR61Wq3LGXEUfbSiFwAAAAAAwOEdeGZIo9GIb3zjG5G32Din1fNXr16Ner1+9AwBAAD6hH4TAADH5r7o/jJZ3W7vCA6c6tWrV+/aDLCp6HkAAIB7iX4TAAD0pkON27T6dVOKdXEBAGiHJ+P1wtg/OXOhuODVa4la//NE7MOJ2NcSsZTWm0R3zmOJ2OlE7Gwi9k7B8z+xbzb3Ev0mAKAXzRXcc8we8t6FHnYiur+heR9txHHgVKvVaty8efNQj09+8pOdzB0AAKCn6DcBAEBvOvDMkOeee+7QlU9OTh66DAAAQL/SbwIA4NicjO7v4dHtmShHcOCZIefPnz905WXKAAAA9Cv9JgAA6E19tKIXAAAAAADA4XV70gwAAAAAANBu90X3v/HvoxGGPkoVAIBBNhe/Uhj7J9lfL1nrG4nYI4nY10q292Ai9k4idjYRu56IvZuIfSURO5WIFcvz6ZbP1+v1qNV+rVSdAAC031yW3fXcbJ4fQybQOwyGAAAAAABAvzsRHdnQfOnbtx6tXL/Z/vY6xWAIAAAAAADQ0tRP3Xq0Un8vovaPu5tPWQOzgXqj0TjuFAAAAHqafhMAAPeqnhsMWVtbi1qtFlmWRa1Wi42NjZbHZVm25zE+Pr4nXq/XY3x8PGZmZmJycjLW1tbuqqNdxwAAAHSTfhMAAHc5GT/aRL1bjw4sy9UpPbVM1uLiYqyvr8fk5GRsbW3F4uJijI6Oxvr6eoyMjOwet7KyEhMTEzE8PLz73O3xRqMRtVotNjc3o1qtRkTE8PBwXLlyJSYmJtp6DAAAQDfpNwEAwOFleZ7nx51E0/j4eKyuru7+u16vR61Wi5GRkVhfX999vnmjX2R0dDQiYs8xKysrMTk5Gc3TbdcxrTTzvr0zAABwr/tc/PVk/Ll/8z8uDv4XryVKvl0y9kgyn3J1vpuIPViyvXdKljtbGMnzZ0vVmGVzBZFvRcSK+98uGYR+kz4TALTHXJa1fH62d77yHVi9dD+zm8tHI6qnu9z2tYja69ET12E/PbNM1sbGRiwsLOx5rlqtRrVa3bOu7draWly6dCnGx8djZWXlrnq2t7djY2Nj94a86dy5cxFx66a8XccAAAB0k34TAACU0zODISMjI1GpVFrGbn9+fX09tre3Y21tLSYnJ+Phhx/esz7upUuX7ioTEbujUuvr6207BgAAoJv0mwAAKNTt/UKajz7R86k2Go2YnJzc/ffy8nIsLy9HvV6P5eXlWFlZidHR0dja2opKpbL7a6ihoaHC+tp1zH7ee++9uHbt2r7HFbn//vvj/vvvL10eAAAO4v3334/333//AEf+ScHz329nOpTQr/0mfSYA4Lgc/B64tffee6+N2dANPT0Ysra2FpVKpeWme9VqNZaXl2N0dDTGx8djZmYmVldXY2trKyIizpw507LO7e3tth2zn0984hP7HpMyOzsbzz///JHqAACA/czPz8fcXNF+IPS6fu436TMBAMfFPfC9p6cHQ+bn5/dsDNjK2NhYjI2NRb1ej4iI4eHhiIi4cuVKy+MrlUrbjtnPl7/85fjIRz6y73FF/MIJAIBueO655+Kzn/3svsc99NB8QeR/iIiX2pkSh9DP/SZ9JgDguBz0HrjIV7/61SP/sKPtTkTEyWNos0/07GDIzMxMvPjiiwcadBgdHd1d/7Z5fNEvkCqVStuO2c8DDzwQp0+f3vc4AIBB8Uz8ncLYy9l/vE/ptxOxr5XKJ+JUIvZEIvZaIvZuIvZgyXJnE7Gy3imMZNliotz1ROwnCp7/8YMkRAf0e79JnwkADmYuy1o+P5vnXc5kcBx1uc0HHnigjdnQDT05GNJcz7a56d5BnDt3bs//3rk2bfPftVqtbccAAAAcF/0mAAD2OBnd/8a/2zNRjqDnJrGsra1FRMTIyMie55vTuVtZX1/f3SxwaGgoqtVqrK+v7zmm+Quop59+um3HAAAAHAf9JgAAOJyemhmysbER8/PzMTk5GSsrK7vPb25u7v6i6MKFC/HMM8/E9PR0RNzqBJw5cybGxsZ2j3/xxRejVqtFo9HYnZa9sLAQCwsLMTQ01NZjAAAAukm/CQAADq9nBkPq9XqMjo5GROz+Wul2V69ejYiIM2fOxPz8fKyvr0e1Wo3R0dFYXl7ec2y1Wo3Nzc2YmZmJSqUSjUYjZmZmYmJiou3HAAAAdIt+EwAAhSyTldQzgyHVajXyA2z4c+f061R9q6urXTkGAACgG/SbAACgnJ4ZDAEAoD/82/FiYezln7mQKHltn5qL9zpIeyQRO5WIfbNkuXcSsbMly10vWee7perM8+nCWJYtlqoTAID2mMuyu56bPcCPISBORvdnavTRzJCe20AdAAAAAACgncwMAQAAAACAfmfPkCQzQwAAAAAAgIFmMAQAAAAAABholskCAAAAAIB+Z5msJIMhAADc5a/H5wpjv3HmV4oL/kSq1tf2afV6IvZuInYqEbtcsr2zpdrL808XxrJsLlHnO4lYsTyfLdleyhOJ2NsFz/9JybYAAO5dc1nW8vnZPO9yJnBvMBgCAAAAAAD97mR0f6aGmSEAAAAAAMC9am1tLdbX12NoaCgajUZUKpVYWFjYc0y9Xo/5+fmoVCqxvb0do6OjMTY21pF8DIYAAAAAAABts7a2FvPz87G5ubn73OjoaMzMzOwOiDQajajVarG5uRnVajUiIoaHh+PKlSsxMTHR9pxOtL1GAAAAAACgu5obqHfzUbBM1vLycpw7d27Pc6Ojo7G2trb778nJyRgZGdkdCImImJmZicnJybJXIMlgCAAAAAAA0DZXrlyJjY2NPc9tbW1FpVKJiIjt7e3Y2NiI0dHRPcc0B1BWVlbanpPBEAAAAAAA6Hc9NDNkcnIyGo1GjI+PR8StvUFefvnl3SWyLl26FBGxOzjS1Jwlsr6+Xv46FLBnSAedP38+Tp061TI2NTUVU1NTXc4IAOBH/np8rjD2q9n/MVHyWiL2dul80vU+mIh9IxH7WCL2RiL24URsozCSZXOJcuXk+WyivcVEydb3obfKlcnzKz98tHKjRH2gzwTAvWEuy1o+P5vnXc6Ew1paWoqlpaWWsevXr3c5m854f+fWo6z3ftD6+YmJidjc3IyVlZUYHh6OSqUSb775ZgwNDUXErf1CImL333dqxtvJYEgHXbx4cc96ZwAA0L8+FsWDS9+KiPZPY2fw6TMBAL0s9eOMer0etVqtyxntozkz5BDmNyPmXu9INrG8vByXLl2Ker0ejUYjNjY2YmxsLCJuLZkVEXHmzJmWZbe3t9uej8EQAAAAAAC4Bz13LuKzT5Uv/9XvRHzildax0dHRmJycjEqlEuPj4zE+Ph6rq6sxNjYWw8PDEXFrb5FW7lw+qx0MhgAAAAAAwD3o/pO3HmU9UDDCMDk5GRG3lsuKiHjzzTfj8ccfjwsXLsTY2NiejdRb6cRgiA3UAQAAAACg3508pkcLL7/88p7lUIeGhmJhYSG2t7ejXq/HuXPnIuLuvUGa/+7EEmQGQwAAAAAAgLY5c+bMXbM+RkZGIuLWwMjQ0FBUq9VYX1/fc8zGxkZERDz99NNtz8kyWQAAA+wvxmph7Ld+7FdK1vqlROx6Ivb2PvU+UrLeU4WRPP+FwliWvZWo8+uJ2NlE7LFELNVe8TlkWcECvBGR59OJOtsvyxYLIj/R1TwAAHrVXJbd9dxsnh9DJtyTSmyg3pY2W5icnIz5+flYWFiIoaGhiIhYW1uLarW6uwTWiy++GLVaLRqNxu5zCwsLe8q0k8EQAAAAAACgbaanp2NoaCjGx8d3l8va3t6OV199dfeYarUam5ubMTMzE5VKJRqNRszMzOzuM9JuBkMAAAAAAIC2mpiY2Hdgo1qtxupq8YoG7WQwBAAAAAAA+l0PLZPVi2ygDgAAAAAADDQzQwAAAAAAoN+djO7P1OijmSEGQwAA+t0/ygpDv3UhLy5347WSDb6ViD2SiL2zT72nErEPJ2LF55Flr5TM58lELOXtkuWuJ2LfKIxk2bWSde73WrSW57Mtn6/X61Gr/VqpOgEA+tFc1voefDZP3H8Dx8pgCAAAAAAA9Dt7hiTZMwQAAAAAABhoBkMAAAAAAICBZpksAAAAAADod5bJSjIzBAAAAAAAGGhmhgAA9IG/E88Uxj79v8pL1vpEIvZKIjaSiG0kYk+m00n6emEkz6cLY1n2Qsn2riVi1UTstZLtnSqM5PlsqRqzbC4RPZuIvVOqPQCAQTWXZXc9N5uXvQeHDjIzJMnMEAAAAAAAYKCZGdJB58+fj1OnWv/Kb2pqKqamprqcEQAAlPWV+NCHPtQycv369S7nwqDQZwIAetnS0lIsLS21jLkH7j8GQzro4sWLUa2mllEAAIB+8bH4wz/87ZaRer0etVqty/kwCPSZAIBelvpxRk/eA5+M7i9bZZksAAAAAACA3mBmCAAAAAAA9DsbqCcZDAEA6BX/KCsMffq1vGSlX0vEHitZ528mYg8mYpf3qffnE7HfKYxk2UuJcu/s02aR06VyyfPpUq1l2Vwitpgo+UQidrYwkufPJtp7qUQu30zkAQDQH+ay1vfjs3nZe3GglxgMAQAAAACAfmdmSJI9QwAAAAAAgIFmMAQAAAAAABholskCAAAAAIB+dzK6v2yVZbIAAAAAAAB6g5khAABd9MfvF/9s5oF/Ky8u+N1UrV9LxOqJ2OVE7JGSsWuFkTx/NlEuIsteSkTPJmLfSMROJWLXE7G3E7FiWbaYiKbOoTiWum5Z9kLJcqk8i+X5dMvn6/V61Gq/VqpOAIBum8uyls/P5on7cegHNlBPMjMEAAAAAAAYaGaGAAAAAAAALS39N7cerVz/QTczORqDIQAAAAAA0O86tEzW1MitRyv1b0TU/v32t9kJlskCAAAAAAAGmpkhAAAAAADQ705E9zc076PpFgZDAADa7OfivyqM/e5Hd4oLfjdR6dWXEsHTidgjiVhKNRH7UqlcsixVLiLieiL2biJ2NhF7p1S5PH+2MJZli4k6H0zEUudXLN1euTrzfLpkLnMFkW+Vqg8AoNPmsuyu52bz/BgyAY5bH43bAAAAAAAAHJ6ZIQAAAAAA0O/ui+5/499HIwxmhgAAAAAAAAOtj8ZtAAAAAACAlk5G97/x7/aG7UdgMKSDzp8/H6dOnWoZm5qaiqmpqS5nBAAA5SwtLUXEf1YQvdHNVBgg+kwAQC9bWlr64X3w3a5fv97lbDgqgyEddPHixahWq8edBgAAHNnU1FT84i9+pyD6rYhY6WY6DAh9JgCgl6V+nFGv16NWq3U5o32YGZJkMAQAoIT/Kn6uMPa7Z/5eccGrXy/Z4gcTsbdLxlK/ZEqVS+WykYg9mohFRLybiD1YqlyezxbGsmyuVKy84uudyjMly14oWW4xET18nrc6ggZDAIDjM5dlLZ+fzfMuZwL0KhuoAwAAAAAAA83MEAAAAAAA6HcnovvLVvXRdIs+ShUAAAAAAODwzAwBAAAAAIB+d190/xv/PhphMDMEAAAAAAAYaH00bgMA0F2vx5OFsX/9b7xRXPDq1xO1JsrF24nYSCL2WiJWfA4Rp0vW+Y1E7GzJchERjxZG8vzThbEseyERm9unzSKnErlMl2yvuM6ULHspkcuzJXMBAOhPc1nW8vnZPO9yJkC/MRgCAAAAAAD97mR0/xv/bm/YfgSWyQIAAAAAAAaamSEAAAAAANDvTkT3Z2r00XSLPkoVAAAAAADg8MwMAQAAAACAfmfPkCSDIQDAPe2P3y++c/vY4zvFBb+dqvWNROxaIvbxROw3Uw0mnE7EXkvEHkzEziZi30jETiVi6bJZ9sI+Zcu0eb1UjVk2l4imrs07pdpLX9PuKj73b3U1DwDg3jCXZXc9N5vnx5AJMAgskwUAAAAAAAw0M0MAAAAAAKDf3Rfd/8a/j0YYzAwBAAAAAAAGWh+N2wAAAAAAAC2diO5vaN5H0y36KFUAAAAAAIDDMzOkg86fPx+nTp1qGZuamoqpqakuZwQA96gvZYWhB76UF5f79tdKNvhIIvbxROyVROx6IvZkItb+c8jzTxXGsmwxUWfqHCIiWt833fJuIp/pRD4v7NPm4eX5bKK9uUTJ4vNLlSvf3tlE7J1Dt7e0tBS/+Iv/XkGpHyTagmL6TABERMxlre/XZ/PEvTp0wdLSUiwtLbWMXb++X/+GXmMwpIMuXrwY1Wr1uNMAAIAjm5qail/8xT8uiH4zIn6tm+kwIPSZAIBelvpxRr1ej1qt1uWM9nEyuv+Nf7eX5ToCgyEAAAAAAEBLS2u3Hq1cf7+7uRyFwRAAAAAAAOh390VHvvGf+jduPVqp//cRtX+r/W12gg3UAQAAAACAgWZmCAAAAAAA9Dt7hiQZDAEABsPlrDCU/ft5yUo/XBxK3UXdeCURfDIReyQReywRO52IXU7EUt4ujGTZl0rWebZkuYg8f7YwlmVziXKziXKLpXLJshdKtlecZ7q9cnlGvFMYaX+ef1KiDABwr5nLWt+zz+Zl79cBDs4yWQAAAAAAwEAzMwQAAAAAAPrdiej+slV9NN2ij1IFAAAAAAA4PDNDAAAAAACg39lAPcnMEAAAAAAAYKCZGQIA9I9/lBWGsr+XF5d7PVHnja8lgt9MlLueKPd2IvZKIvbBROzriVgql1TsVCL2bmEkz3+hMJZlb5Sq85Yn9okXOVsYybLFwlieT5cqF/HOQZJqIXW9Ux5MxFKvb1mPJmLf6EB7AMAgmsvuvnefzRP37AAdZjAEAAAAAAD63X3R/W/8+2iEwTJZAAAAAADAQOu5cZu1tbWYn5+Per0e1Wo1FhYWYmRkZM8x9Xo95ufno1KpxPb2doyOjsbY2NixHQMAANBN+k0AANzlRHR/Q/M+mm7RU4Mhi4uLsb6+HpOTk7G1tRWLi4sxOjoa6+vruzf2jUYjarVabG5uRrVajYiI4eHhuHLlSkxMTHT9GAAAgG7SbwIAgMPrqXGb119/PdbX12NiYiIWFhZic3MzIiIWFhZ2j5mcnIyRkZHdm+yIiJmZmZicnDyWYwAAALpJvwkAgJZOxo/2DenWo9szUY6gZwZDNjY29ty8R0RUq9WoVqvRaDQiImJ7ezs2NjZidHR0z3Hnzp2LiIiVlZWuHgMAANBN+k0AAFBOzyyTdef6trerVCoREXHp0qU9/25q/gJpfX19N9aNY0z5BoAOuJwVhrL/PC8u95++XbLBDydi9UTsg4nYtUTsnZKxs4nY5UTsVCKWcr0wkmWLhbE8n06Ue2GfNouvW6rNtAdL1ll8/unXIiVVruz7ovj1Tb0WaWXa+4mSbXFY+k0A9Jq5rPX9+2yeuHcHOAY9MxhSpNFo7E6vbv7SaWhoqPDYbh6zn/feey+uXUt9GZJ2//33x/3331+6PAAAHMT7778f77///g//9SdlamhnOpTQr/0mfSYA4LjsvQc+vPfee6+N2bRJc5msbrfZJ3p6MGRtbS0qlcruL4m2trYiIuLMmTMtj9/e3u7qMfv5xCc+se8xKbOzs/H8888fqQ4AANjP/Px8zM3NHXcalNTP/SZ9JgDguLgHvvf09GDI/Px8rK6u7v57eHg4IiKuXLnS8vhKpdLVY/bz5S9/OT7ykY/se1wRv3ACAKAbnnvuufjsZz8bEREPPfSrJWr4VkQstzMlDqGf+036TADAcbn9HriMr371q0f+YUfbNTc173abfaJnU52ZmYkXX3xxz81z87+Lfl1UqVS6esx+HnjggTh9+vS+xwEAwHHau9RQmf0/fCF9XPq936TPBAAcl6Mut/nAAw+0MRu64cRxJ9DKyspKjI6O7m6613Tu3LmIuHvd2ea/a7VaV48BAAA4LvpNAABwcD03M2RtbS0iIkZGRvY8X6/Xo1qtRrVajfX19Zient6NbWxsRETE008/HUNDQ107BgAo54/fL95h7YGP5cUF/+cdSCapmojVE7FHErHUL6AvlyyXau+NROxsIna9MJLnzxbGsuyVRJ2pPCNS55/n04WxLFtMlCvONSXLyq0dnC53qlSdqXKp65KSZS+UqrP4/Mpsus5R6DcBcBzmsuyu52bzxP070FX5iYi8yxua5z053aK1nhoM2djYiPn5+ZicnIyVlZXd5zc3N6NWq0W1Wo0XX3wxarVaNBqN3SnXCwsLsbCwEENDQxERXT0GAACgm/SbAADg8HpmMKRer8fo6GhERExOTt4Vv3r1akREVKvV2NzcjJmZmahUKtFoNGJmZiYmJiZ2j+3mMQAAAN2i3wQAQJGdkxE7Xf7Gf6fLM1GOomcGQ6rVauQHnFZXrVZjdXW1Z44BAADoBv0mAAAop2cGQwAAAAAAgHJuHsPMkJt9NDOkj7Y3AQAAAAAAODwzQwCAjvjj94t/HvLAV3eKC169Vhz7/dcSLZ5OxM4mYvVE7K1E7FQidj0Ru5yIPZiIJa5Lss6UdwojeT5dGMuyxZLt7Sd1/inF1zuda+p1Sr2+xdctJX1N50rVWVaeP1sYS+WS57Mtn6/X61GrrbSMAQD9Zy7LWj4/e8ClGgF6kcEQAAAAAADoczsns7hxsvVgZufazCOiPwZKDYYAAAAAAAAtLf96Hiu/3nrA40/+pMvJHIHBEAAAAAAA6HM7J0/Gzn3t3yb8M79469HKV+s34xMfu9H2NjvBBuoAAAAAAMBAMxgCAAAAAAAMNMtkAQCl/fH7JwtjD/wvdooLXv56otZHyidU6LWS7Z1KxK4nYqcTsQcTsXdLxs4mYqk8i+vMsrlEudR1KZbn08l4lr2UiC0m6p0tVS7iyUSdn0rUWe7apHMpVvb8Utc7y15ItFju9QUA+s9c1nqj5dm8PzZDBva6efJk7Jzs7vyHmyeziLBMFgAAAAAAwLEzMwQAAAAAAPrcTpyInShewaEzbfYPM0MAAAAAAICBZmZIB50/fz5OnWq95vLU1FRMTU11OSMAACjrH8aHPvShlpHr11N700AxfSYAoJctLS3F0tJSy1gv3gPvxMm4YWZIIYMhHXTx4sWoVqvHnQYAALTBz8Qf/uF/2TJSr9ejVqt1Nx0Ggj4TANDLUj/OcA/cfwyGAABpy1lh6IHn8uJyfylR5+VUg6lf1/xCIva1wkief7owlmVziTo/loi9kYilfDgR20jEnkzE3k7EWv/i+pZ3E7GU1Gt0tjCSZYsl24uIeDBR7wuJcqlci9+I6fdF6pqmpHIprjN13fJ8OlEudQ7lFOfyzba3BQC011x29339bJ64nwcYMAZDAAAAAACgz92Mk7HT5a/8b3a1taOxgToAAAAAADDQzAwBAAAAAIA+txMnYqfrG6j3z9wQM0MAAAAAAICBZjAEAAAAAAAYaJbJAoB73VqWDGd/nBcHr369OPY7H0zU+kgitpGIXUvE3imMZNm7iXIfS8SeKIzk+S8k2vtSos7XErFTidgbJculzv3BRKz43FO55PmzhbEsm0vUGZE+j+LXN+JsyViqzuJc8nw6Ua6c/a/N4eX5bMn2Hi3R2v9YogwA0AlzWev7+9k8cV8PDIRbG6h3d5msm5bJAgAAAAAA6A1mhgAAAAAAQJ+7eQwbqN+Mna62dxRmhgAAAAAAAAPNYAgAAAAAADDQLJMFAAAAAAB97kaciBtdXibrRh/Nt+ifTAEAAAAAAEowMwQA7gUjWWEo+9k8XfZXU8HTxaFvv5Ao91gidjkRezARezIRezsRS3mtMJJlb5Rs72zJXD6YiH0tEXu3MJLnzxbGsmwxUWfxOWTZXKLcfq6XajN1jqk683y2MJY6j1QsVWdKt3Mp215RuXq9HrXaUV57AOCw5rLW9/iz+T7398DAuhn3xU6Xv/K3gToAAAAAAECPMDMEAAAAAAD63M04ETtd3jPk5iHmWzQajVhbW4uIiImJiRgaGoqIWzPN5+fno1KpxPb2doyOjsbY2FjbczUYAgAAAAAAdESj0YiZmZnY3t6O5eXlqFQqe2K1Wi02NzejWq1GRMTw8HBcuXIlJiYm2pqHZbIAAAAAAIC2u7W/YC3OnDkT6+vrewZCIiImJydjZGRkdyAkImJmZiYmJyfbnovBEAAAAAAA6HM7P1wmq7uP4iGG7e3t+OQnPxmVSiWWl5dbxjc2NmJ0dHTP8+fOnYuIiJWVlbZeH8tkddD58+fj1KlTLWNTU1MxNTXV5YwAGGi/lxWGsj+dF5f7nX3qvZoKtv7/uVs+vE/FRZ5IxK4lYm8nYo8kYm+k0ylUTcQuJ2LvFkbyfLowlmUv7ZvRYWXZYslcistFnE3E3tk/qcJ8ni1VLsvmSsXS7+3riTrLXdOUPJ8t1V5K6tyL2ltaWooPfehDLWPXrxdfE0jRZwI4mLns7nv92Txxjw+0xdLSUiwtLbWMuQfeX3NprIWFhZbxS5cuRUTcNVukOUtkfX29rUtlGQzpoIsXL+6Z3gMAAP0q9cV0c+o7HJY+EwDQy/rtHngnTsaNQ26g/v33b8b33y8/uPrue8Wx5syO9fX1mJmZiUajEefOndvdN6TRaERE7G6kfqdmvF0MhgAAAAAAwD3opfl/Hl+Y++dtr7der0fErVkek5OTsbCwEI1GI0ZHR2N4eDiuXr0aW1tbERFx5syZlnVsb2+3NSeDIQAAAAAAcA/69HP/Qvybn/3J0uX/v1+9Hv/OJ9666/nmrI7JycndZbCae4eMjo7G/Px8DA8PR0TElStXWtZ95/JZR2UwBAAAAAAA+tzNOBk7h/zK/+T9EafuL9/mTzyw0/L5oqWvRkZGIiJ2Z4lEFM8AafdgSPFW7wAAAAAAAId07ty5iIjdpbDudObMmd1j7twbpPnvdu/JYmYIAPSTv5AVhrL/ZWLDs+8k6vz9/Rp9OxG7nIhdS8ROl6ozz6cLY1n2Ssn2iqXbWyxVZ8TZRJ1ziXKPJmLvlszliUQuqfO7nog9WBjJ89lkNqnzL3+9T5UslzrHVJ2pcuWk3xfl7PdaAADHYy5rfb8/m5ff3Bi4d+zEydg55Abq7WizlaGhoRgZGYmNjY09zzdngdRqtRgaGopqtRrr6+sxPf2j/nezzNNPP93WXM0MAQAAAAAA2mphYSHq9fqeAZGVlZWoVqsxMTEREREvvvhibGxs7JkdsrCwEAsLC4VLbZVlZggAAAAAAPS5m3Gi6zNDbibmW1Sr1djc3IyZmZlYXV2NoaGh2N7ejs3NzZbHVCqVaDQaMTMzsztY0k4GQwAAAAAAgLZrLoO13zGrq6sdz8UyWQAAAAAAwEAzMwQAAAAAAPrczjEsk7XTR/MtDIYAQK95NisMZf/pzeJyP5eo83KqwRf2Seh/n4g9mYhtJGK/kIh9vTCSZa8kyp1KxL6WiD2YaO+lRLmUJxKx1IvxaCL2TgdyeSMRO1uyvXcLI1m2mCyZ57OJsnOJksW55vmzyTbLyLLiz0yeTyfKpc6h+P2bui4pqfbK11n0Gn6zVH0AcK+ay1rf88/meZczAbh3GAwBAAAAAIA+txMn40bXZ4Z0t72j6J85LAAAAAAAACUYDAEAAAAAAAaaZbIAAAAAAKDP3YyTsdPlr/xvWiYLAAAAAACgN5gZAgDH4V/JCkPZv5wXlzuXqPPqtZLJfHyf+NuJ2AcTsVQ+X0/EHknE3krE3k3EridiKWcTsQcLI3n+qVKtZdliqXJ5Pp2o84VEyUcTsW8kYqcSseJrneeziXIRWTZXss3Ua59qr/3XO12u+PzT595dqVyKzqFer0et9mudSgkA+tpcdve9/2yeuOcHKGknTnR9Q/OdPppv0T+ZAgAAAAAAlGBmSAedP38+Tp1q/SvGqampmJqa6nJGAABQ1lfiQx/6UMvI9etlZ19xr9NnAgB62dLSUiwtLbWM9eI98K09Q7o7M6Sf9gwxGNJBFy9ejGq1etxpAABAG3ws/vAPf7tl5NYyWbUu58Mg0GcCAHpZ6scZ7oH7j2WyAAAAAACAgWZmCAAAAAAA9LmdOBE3bKBeyGAIAHTKfFYYyrK8uNxvlG3wdCL2diL2zX3qfSIReyURS62fWjbXlFSe1xKxVJ7vlsoky+YS0UdL1Vm+vZSzhZE8ny3VXqrc0fJ5NpHPYqnW8nw6UWe5a9q5a3P49tLlyl2z4va+Vao+ABgkc1nr+//ZPHHvD0DXGAwBAAAAAIA+txMnY6fLX/l3e8P2o+ifOSwAAAAAAAAlGAwBAAAAAAAGmmWyAAAAAACgz92Mk11ftuqmZbIAAAAAAAB6g5khAAAAAADQ53biRNdnhuz00XwLgyEAcARfz7LC2P/sX8mLC/7+tUStpxOxVLmNRCzlkX3iv5mIPZmIPXb4VPb1TslYyqlE7Hqpcnk+WxjLsrlEnWcTdT5bqs6yuZTNM8sWE+X2k7re5WTZC4Wx1DVN19n+651ur/iapttLvRYPJmLFr0NRe/V6PWq1lUSdADBY5lr0A2bzxP0/AMfOYAgAAAAAAPS5nTgZN7o+M6R/9gwxGAIAAAAAALS0sfT1+L2lrZax71/f6XI25RkMAQAAAAAAWhqZ+mCMTH2wZeyt+tV4vrbe5YzKMRgCAAAAAAB97macjJ0uf+V/s4+Wyeqfrd4BAAAAAABKMDMEAPYxl2WFsefn8uKCa6la3y4Zu5yInUrEridiDyZi+8X/VCL2O4lYKp9U7MlELHX+qWta9toUt5dlc4lyKe+WLHe2MFI+l5R3CiN5Plu61ixbLBXL8+lEueLzz7IXEnUWn0fZa5qu86VEyW+UyqXsa5G+ZkWxb5VqCwB6XVFfYDZP9AMAjslOnOj6huY7fTTfon8yBQAAAAAAKMFgCAAAAAAAMNAskwUAAAAAAH3u1gbq3V0mq582UDcY0kHnz5+PU6daryc+NTUVU1NTXc4IAADK+soPH63c6GYiDBB9JgCgly0tLcXS0lLL2PXrqf0n6UUGQzro4sWLUa1WjzsNAABog4/98NHKtyJipYu5MCj0mQCAXpb6cUa9Xo9ardbljNJuHsMG6jf7aCcOgyEAEBHXTmWFseeX8uKC/0Gi0m+nWvxgIvb1ROzjidjbidgbqWT28eFE7DcTsb+ciL1WGMnzZwtjWTaXqPPRROwbiVhZqfZSsWJ5/unCWJa9kCj5biLW+hfXtzyYiL1TGMnz2US5YulziMjz6UTZ4tc+yxZL5ZO+NsVS559lryTKfSoR+3SiztT7vvgc0te73OtbfK1/ItEWAPS+uax1f2A2T/QFAOgrBkMAAAAAAKDP3YiTcaPLM0O63d5R9M8cFgAAAAAAgBIMhgAAAAAAAAPNMlkAAAAAANDnbsbJ2OnyV/43LZMFAAAAAADQG8wMAeDe8WxWGHrouby43H+QqPPb1xLBtxOx64lYymuJ2BOJ2KlE7HKyxTz/VGEsyx5MlPydRJ3TiTpfStSZOo+y17Ssd0qWK84zy+ZK1vloqfYi3k3Eiq912TzzfDYZz7IXSpVN5VO2XJYtFsZS13S/cyzXXrH0Z6lcnalyRe3V6/Wo1X6tVHsA0G1z2d39gtk80R8A6BM7cSJ2ujxTY6eP5lv0T6YAAAAAAAAlGAwBAAAAAAAGmmWyAAAAAACgz93aQL27y2TZQB0AAAAAAKBH9P1gSKPROO4UAAAAepp+EwDA4NuJE3EjTnb10U8bqPfUMlnb29sxPz8fERELCwstj8mybM+/q9VqbG5u7v67Xq/H/Px8VCqV2N7ejtHR0RgbG9tTpl3HANB75u74/4nbPf8f5sUFX0pU+u1rxbGHTxfHrm4kKv14IvZKIvZuIpbIJd5KxB5LxCKy7EuJ6NuJ2BMl60wprjMdu1yyvdT5pZxKxL5RGMnz2cJYli2WqrO81DmUk2Uvdajs2dL1lpF+neYSJVPX9Hqpcln2QtvrzPPpRDl6gX4TwMEU9Q1m80S/AICB1TODIRsbG7G8vBxra2sxMTHR8piVlZWYmJiI4eHh3edGRkZ2/7vRaEStVovNzc2oVqsRETE8PBxXrlzZrbNdxwAAAHSbfhMAAEV24mTsdPkr/27vUXIUPTMYMjIyEiMjI3f9gul2q6ursb6+XhifnJyMkZGR3RvxiIiZmZmYnJzcvRlv1zEAAADdpt8EAADl9M2CXmtra3Hp0qUYHx+PlZWVu+Lb29uxsbERo6Oje54/d+5cRNz6dVS7jgEAAOhF+k0AANBa3wyGrK+vx/b2dqytrcXk5GQ8/PDDsbHxo7XYL126FBERlUplT7nmr5TW19fbdgwAAEAv0m8CALh33YyTP1wqq3uPm5bJar/l5eVYXl6Oer0ey8vLsbKyEqOjo7G1tRWVSiUajUZERAwNDbUs32g02nbMQb333ntx7Vpi09193H///XH//feXLg8AAAdz44ePKHX/+t5777U5H8rqt36TPhMAcFzef//9eP/990uXdw/cf/pmMKSpWq3G8vJyjI6Oxvj4eMzMzMTq6mpsbW1FRMSZM2daltve3m7bMQf1iU984sDHtjI7OxvPP//8keoAGERziXXSn9+6WVzwLyUq/U4i9uTp4tgbiXJJbydij5Wss+yXSfudxNlE7J2SsWJ5Pl0Yy7LFRMnUeZzqQC4vJEqmzr34embZXKlyKalzSElf65TUtU6/JzpxvVPl8nw2mU85qfO/3oH22vM5e/7552Nu7tb776GHOnFd6LZ+6TfpMwHtUNQ/mM3zLmcC9JP5+fnde+BBcTNOdH1D85v9s/hU/w2GNI2NjcXY2FjU6/WIiBgeHo6IiCtXrrQ8vlKptO2Yg/ryl78cH/nIRw58/J38wgkAgG547rnn4rOf/WxERDz00K8mjiwa0PkfIuKl9iZFW/R6v0mfCQA4LrffA5fx1a9+9cg/7KC7+nYwJCJidHR0d/3b5s120S+QKpVK2445qAceeCBOn078mhgAAHrA3qWGfiJxZNEvbH+8zRnRTr3cb9JnAgCOy1GX23zggQfamA3d0NeDIRER586d2/O/d65N2/x3rVZr2zEAAAD9RL8JAGDw7XRomaz60leivvSVlrEb12+0vb1O6Z8FvVpYX1+PycnJiLi1cV+1Wo319fU9xzR/AfX000+37RgAAIB+od8EAMBRVKc+Fp/5w19s+fhLF/vnvq+nBkOKpljX6/Wo1WqxuPijjTzX1tbizJkzMTY2tvvciy++GBsbG3t+nbSwsBALCwsxNDTU1mMAAACOg34TAACt7MTJuNHlR7c3bD+Knlkmq16vx/LyckREvPzyyzE6OhojIyMxNDQUlUolzpw5E/Pz87G+vh7VajVGR0d3j2+qVquxubkZMzMzUalUotFoxMzMTExMTLT9GAA67P+aFYae/+2iNesj4j9I1PnGa4ng2eLQtxPF4oOJ2JOJWCqXd0rW+UQi9kYi9mAiFpHOJ3HdIrUG/OXCSJYtFsbSTpUsV7Qh9H5S1yWVS6pcyrslyxXLsrnCWJ7PlipX/nqm5fmzhbH0eZQtV+78O1EupXwuxZ+zPJ8+dB63voRfOXQ5Dk+/CbjXzWV39xNm80T/AAB+qGcGQ6rVaiwvL991ox5xayr3ndOvU/Wsrq525RgAAIBu0m8CAIByemYwBAAAAAAAKOdmnIydLn/lf7OPlsnqqT1DAAAAAAAA2s3MEAAAAAAA6HM7caLrG5rv9NF8i/7JFAAAAAAAoAQzQwAAAAAAoM/d2jOkuzND+mnPEIMhABybxSwrjM2M5MUFv5KodONrieC1krG3Ug0mYh9PxH4hEftSIvanErHLidiTiVjqgkZEnCqM5PmnC2NZ9kLJfK4nYqlzTJUrPodULulzSEnlkjr3txOxd0u2V06WLba9zjyfLd1mnk8nSp4tmVHx+6Lb559lc4mSqfdv2VyKr2c6lyLfKp8MALQwV9BXmM0T/QQASLBMFgAAAAAAMNDMDAEAAAAAgD63Eyfihg3UC/VPpgAAAAAAACWYGQIAAAAAAH1uJ+6LnS5/5d/t9o7CzBAAAAAAAGCg9c+wDQB9aS7LCmPPfzkvLvjJkg0+8eHi2OVELOnridhvlqzzlUTs44nY7yRi1xOxU+l0SsqyxUQ0lU/KO4nYo4nYN0q2dzkRezARK3tNU+0VX7M8ny3VWuo1Kl/nC4k6ny1V5y2p651S/J4p+x4tf23mEtGzpdpL1Vk2z5Qyddbr9ajVVtqeCwCDr6i/MJsn+goAUILBEAAAAAAA6HM340TsdHkD9Zt9tPiUwZAOOn/+fJw61fpXo1NTUzE1NdXljAAAoJylpaVYWlpqGbt+vexMMO51+kwAQC9zDzxYDIZ00MWLF6NarR53GgAAcGSpL6ZvLZNV63JGDAJ9JgCgl/XbPfDOMcwM2emjmSH9kykAAAAAAEAJZoYAAAAAAECfuxknj2HPkO62dxQGQwA4srksK4w9/6/lxQV/PVHpjdcSwQeLQ5cfSZSrJ2Jl/Xwi9s1ELJXnu4nYE4nYtUQstZbp2UQsIuIbJcsmXqekVJ1HOY8i7yRiqXMom0txe3k+WxjLsrlEna3X27+lOM8sW0yUSym3Nu5+7eX5dKl601K5Fl+31PVOvU7p17D4/Mu2V7ZcSifqBICI1v2G2TzRXwCANrJMFgAAAAAAMNDMDAEAAAAAgD63Eyfihg3UC/VPpgAAAAAAACWYGQIAAAAAAH1uJ07GTpe/8u/2hu1HYWYIAAAAAAAw0MwMAeBA5rKsMPb5P/7nxQWfSFT67WuJYKpgqlwqdjoRO5uIfTARW0zEUufwRiJWLM8/VRjLspcSJU8lYu+UymV/5drM8+nCWJYVX+90ublEudlS5VLnl+fPJsoVK5/nK4lyqfdMufOLeLQDdUZk2QuJaOo9k7o2qc/o9WQ+7VfcXuoc0oqvadnPCwAcVVHfYTbPu5wJAPyIwRAAAAAAAOhzN+Nk15etummZLAAAAAAAgN5gZggAAAAAAPS5nTjR9ZkhO30038JgCAAAAAAA0NKbS78Tby39vZaxnevf73I25RkMAQAAAACAPrcTJ+NGB2aG/EtTfyH+pam/0DL2vXoj/mHtl9veZicYDAFg11yWFcbW8q8Uxt77P/1kcaX/PNHgfaeLYzeuJwq+kYg9mYh9PBH7UiKW8vOJ2OWSdb5dGMmyFxLl3k3EnkjEUtc6IuLBwkieP1sYy7K5RLnZRLlXErkU55q6Nun2Utf0VCJWLHXuaY+WLHetMJLOJXV+qfdFcSx1rfdT/j1T7hzL1plli4k6p0u1l1L2upRXfM2Kz/2bHcgDgH7Qqg8xm+fHkAkApPXPgl4AAAAAAAAlmBkCAAAAAAB97macjJ0uf+V/s8sbth+FmSEAAAAAAMBAMzOkg86fPx+nTrVec3lqaiqmpqa6nBEAAJT1DyPi9wtiP+hmIgwQfSYAoJctLS3F0tJSy9j16/vtv9l9O3Eidro8U2Onj+ZbGAzpoIsXL0a1Wj3uNAAAoA1+5oePVr4ZEb/WxVwYFPpMAEAvS/04o16vR61W63JGHIXBEIB7zFyWFcae/w/z4oJnEpWm/r//xguJ4IcTsbOJ2COJ2DuJ2EYi9lgi9v9MxFJ5tv6l6y1PJmLXErGUdxOxN0rmEhFxuTCSZYuJcsXXJsu+VKq9iEcTseLXPp1n6tc85dpLv/ap9lLnMJcoVyzPZxN1Fn8+83y6VHvpa52WzrX4/MueYzrXcq9h+TxTr2/qs1T2ehefQyrPIrc6ggZDAAZZUT9iNk/0IQCghxgMAQAAAACAPndrA/XuLpNlA3UAAAAAAIAeYWYIAAAAAAD0uZ04ETdsoF6ofzIFAAAAAAAowcwQAAAAAADocztxMna6/JV/t/coOQozQwAAAAAAgIFmZgjAAJrLssLY81/Oiwv+G4lK/9eJ2G99LRF8NhH7UiL2YCKWci0R+1Qi9koi9mgi9k46nbYr217qHPaTei3eTcTK5nq2MJLnny6MZVnxa5jnxa99ls2VbO+FRLni9326velS5VLKlkvXuVgYS53D/vWWPcfi1yL1Pszz2bbnkpJ+7dufS6rOlLJ5AjAYivoSs3miHwEAfcBgCAAAAAAA9LmbcbLry1bdtEwWAAAAAABAbzAzBAAAAAAA+tzNOHEMM0P6Z75F/2QKAAAAAABQgsEQAAAAAABgoFkmC6BPzWVZYewL+deLC/6bJRv8rVSwnoi9m4hVE7HXErFTqWQS/k4i9mDJOsuWu56IlT2/syXLvb1P/LFE7E8lYsWvYZ4/WxjLssVE7JVEe5cT5eYSucx2tVxK+faKr1lZ3T6Hg8TLtFm+XOpzWPz5LXsO3XaU1wmAwdGqTzGb58eQCQDtsHMMG6h3u72jMDMEAAAAAAAYaGaGAAAAAABAn9uJE3Gj6zND+me+Rf9kCgAAAAAAUIKZIQAAAAAA0Odu7RnS3a/8D7NnyMbGRoyPj8fVq1f3PF+v12N+fj4qlUpsb2/H6OhojI2NtTtVgyEAAAAAAEBnTU5O3vVco9GIWq0Wm5ubUa1WIyJieHg4rly5EhMTE21t32BIB50/fz5OnTrVMjY1NRVTU1NdzgjoJ3NZlow//9/mxcF/L1Hw9UTsn6da/FIi9ulE7OuJ2OVE7IlE7LVE7LFErKzridi7idjZROyRROztROzJROyNROzBRGw/qfP/zUSs+PyzbK5kLq3/f/WW1DkWx7JssTCW57P7p3RIqTrLX5eyUq9tSup1KK4zda0jIvJ8OlG23LUpf72Lz6Nsnely6WtTLPVaFCvz3l5aWoqlpaWWsevXy76XuNfpM0F3FPUtZvNEnwIA98BtNDMzE5VKJa5cubLn+cnJyRgZGdkdCGkeOzk5aTCkn1y8eHHPiwgAAP0q9cV0vV6PWq3W5YwYBPpMAEAv67d74Jtx8lDLVrWrzf1sbGzEBz7wgahWq3Hp0qXd57e3t2NjYyMWFhb2HH/u3LmIiFhZWWnrgIgN1AEAAAAAgI5YXl6O6em7VwJoDoxUKpU9zzd/LLO+vt7WPMwMAQAAAACAPnczThx6Zkj+/vcjf//7pdu88d6fJOMzMzN3zfxoajQaERExNDSUjLeLwRAAAAAAALgHXZ1/Ma7OvdCRuuv1enzgAx+4a+ZH09bWVkREnDlzpmV8e3u7rfkYDAEAAAAAgHvQw89diKHP/pXS5d//6n8f3/rEp1vG5ufnY3V1tbDs8PBwRMRdm6o3FQ2ilGUwBOAYzWVZYewL+dfThf9iIvbflcsnbryWCH68OJT6f5Mb1xPBt0vGRhKxlNMl27tcsr13SsZS16xsLOXBfeKdOP+zJcu9kYgVn3+ezybKFcuyxUSdd693epD2UnV2Rup98WhhJM8/XRjLsrlSmaSu2f5OJWLl3vvl3xep8y/OM/3apz6H5T73qTzLnjsAva2ofzGb513OBIDjcCNOxMnDbqB+/6lbj5JuPvBAy+dnZmZidHR0z1JXzf9u/m9zsKNoBojBEAAAAAAAoGdtbGzE4mLrH4QNDw9HtVqNV199NSLu3huk+e9ardbWnE60tTYAAAAAAKDrbsZ9sdPlx82C+Rabm5uR5/mex/T0dAwNDUWe57G5uRlDQ0NRrVZjfX19T9mNjY2IiHj66afben0MhgAAAAAAAF334osvxsbGxp7ZIQsLC7GwsBBDQ0NtbcsyWQAAAAAA0OduxonYOeyeIW1o8yiq1Wpsbm7GzMxMVCqVaDQaMTMzExMTE23K8EcMhgAAAAAAAB3VnPFxp2q1Gqurqx1v32AIQIfNZVlhbCP/3cLYP/sbT6QrfisRu/y14tjDH04U/HoilsjnxhuJcg8mYo8kYm8nYq8lYimnS5a7noidKlnu0UTsnXQ6BfJ8tjCWZXOJkqk8IyLOliybOsdy7eX5s4Wx9DkWy7LWG7odRbrOsu+nYnk+Xapc6ppl2QuJ9sq+1/bLp+x1K1dn6rqlziN9/uXa67Z+yROAYq36GbN5fgyZAEB/MBgCAAAAAAB9bidOxIkuL5O100fbkvdPpgAAAAAAACWYGQIAAAAAAH3u5s2TsXOzyxuod7m9ozAzBAAAAAAAGGgGQwAAAAAAgIFmmSyANpjLssLY382/XBj7yl/82eJKL+3T6LevJYIfLg5dTZX7eCL2pUTskUTsa4WRPH+2MJZlryTqPJ2IvZ2IlfVoInY9EXsiEbtcss4HCyNZ9kKiXOoc3knEDhIvUy51jqcKI1k2lyh3NlFuMVEupTjPVJ15Pp0ol3qdyl3r8udXfK0j3i1ZZ7H067ef4tc3/bekuM2j5VOk3HumbJ15PluqxvR7tMx1+VapPADYX1FfYzbPu5wJAL1uZ+dExI0ub6C+0z/zLfonUwAAAAAAgBLMDOmg8+fPx6lTrX9xOTU1FVNTU13OCAAAyvrKDx+t3OhmIgwQfSYAoJctLS3F0tJSy9j166kVD47Hzo2TETe6+5X/TpdnohyFwZAOunjxYlSr1eNOAwAA2uBjP3y08q2IWOliLgwKfSYAoJelfpxRr9ejVqt1OSOOwjJZAAAAAADAQDMzBAAAAAAA+tzNnZNd30D95k7/LJNlZggAAAAAADDQzAwBOKC5LCuMPf/f5sUFP5yo9H+XiO23D9e330oE303EHkzEWm9gess7idgjiVixLHspEU1dgFR7Zc/hbCJ2OhH7RiKWeh1Sis8hz58tjGXZC4k6U9ezU5u+pepNvU7F5fJ8tjCWZXOlyqWk6ixbruw5pOT5dKly6fZSr1Eql/af3y1lP0/dlvr8lnudyir/fkq9hosFkZ8o1RYAP1LU35jNE30NALjNzs6JyLs+M6R/5lv0T6YAAAAAAAAlmBkCAAAAAAB9bufGybj5g+7ODOn2TJSjMDMEAAAAAAAYaAZDAAAAAACAgWaZLAAAAAAA6HP5zZOR73T5K/+b/bNMlsEQgNvMZVlh7Pn/V15c8D9JVPpYIvbridjVlxLBiIhfSMS+WRx6+OOJNr+UqPNscei+RC43XkrUeT0RO5WIjSRiryVij5TM5e1ELJVnyoOJ2LuFkSx7qVRref5sos4XStV5S3Gu6XN8JxErvqZlzz8lyxYLY3k+2/Y609e7+HOWZXOFsbJ5pt+/xZ+J9DWbLpnLflKf0WKpa1P2mnbi/Dvx+pY99zK51Ov1qNV+7eDJAdzjWvU7ZvNEfwMAODKDIQAAAAAA0O9unIjo9obmN/pnJ47+yRQAAAAAAKAEgyEAAAAAAMBA66llsra3t2N+fj4iIhYWFu6K1+v1mJ+fj0qlEtvb2zE6OhpjY2PHdgwAAEC36TcBANDSzsnOLJP1G0sR/4+/1Tr2J+X2dzwOPTMYsrGxEcvLy7G2thYTExN3xRuNRtRqtdjc3IxqtRoREcPDw3HlypXd47t5DAAAQLfpNwEA0HX/h6lbj1b+ST3iXz/X3XxKyvI8z487idtlWRYTExOxvLy85/nR0dGIiFhfX999bmVlJSYnJ6N5Ct08JqVer9/VKQB6x1yWFcY+/8f/vDD23md+srjS/6JsNq8lYk/uU/Z0IvZCInZqn3qLPFKy3J9KxC6XjKX8fCL2OyXrTHkiEXsjEUu9vtcSsdQvLt5JxIrl+WwynmVzpcqmyqWdLVkudf7F7/s8ny6MZVnxZynPnz1IUoeqM+LdROzBkuXK/Uqn7GubLre4T5up16K4bLpc+3NNtZfSiTq7LcteKoi8FRFz7n+7qN/7TfpM3CuK+h6zvfVVDAAl9NL9TDOXeGUz4s90OZd/Wo/4VG9ch/30xZ4h29vbsbGxsXuz3XTu3K0Rp5WVla4eAwAA0Gv0mwAAoFhfDIZcunQpIiIqlcqe55sjTevr6109BgAAoNfoNwEA3ON2IuJGlx87XTmztuiZPUNSGo1GREQMDQ0Vxrt5zEG99957ce1aaqmTtPvvvz/uv//+0uUBAOAg3n///Xj//fcPcGTRsmsHKUun9WO/SZ8JADguB78Hbu29995rYzZ0Q18MhmxtbUVExJkzZ1rGt7e3u3rMQX3iE5848LGtzM7OxvPPP3+kOgAAYD/z8/MxN1d2nx96RT/2m/SZAIDj4h743tMXgyHDw8MREXHlypWW8Uql0tVjDurLX/5yfOQjHznw8XfyCycAALrhueeei89+9rP7HvfQQ/95QeSPIuJzbc2Jw+vHfpM+EwBwXA56D1zkq1/96pF/2NF2zWWyut1mn+iLwZDmjXTRr4sqlUpXjzmoBx54IE6fPn3g44H2mcuywtgf5i8Vxv7Ht08VV/pYosEnErG3ErEbH08E307EIiI2ErEPJ2Jll6KoJmK/nog9mYg9UjKXxOsUv1Mylzc6UC6VZ9lyDxZG8ny2MJZli4lY+pcwZestex4R7yZymS6ZS9HSPt0vl76eqdeiuM70tS6Olb2eqXPolHSuxdet/PU+e5C0upJLJ8rd6falhsrUWa/Xo1YzGHLc+rHfpM/EIGnVB5nN82PIBICDOOpymw888EAbs6Eb+mIw5Ny5cxFx97qzzX/XarWuHgMAANBr9JsAAO5xzU3Nu91mnzhx3AkcxNDQUFSr1VhfX9/z/MbGrV9FP/300109BgAAoNfoNwEAQLGeGgxJbbL34osvxsbGxp5fHi0sLMTCwkIMDQ11/RgAAIDjoN8EAACH1zPLZNXr9VheXo6IiJdffjlGR0djZGRk9ya6Wq3G5uZmzMzMRKVSiUajETMzMzExMbFbRzePAQAA6Db9JgAACt2IiB8cQ5t9omcGQ6rVaiwvL+/e2Bcds7q6um893ToGAACgm/SbAACgnJ4ZDAE4rLksK4w9v3WzuOBocbn4p4kG/0widvntRDDllUTsU/uUfSIRezcRO52InU3ELidip0qWS7lWss4HS7aXup7XE7EnCyN5/guFsSxbLNle8WtUts48n02Ui8iyFxLRctc7z59NtFd8Hlk2l6iz+DzS5/BIos79PoeHb6/8OaTKTZcql4qlP9fFyp7fUcqWv27lypWvs/i9vd+1aXe5snUWn/u32p4HQK8q6ofM5nmXMwGAO9yMiJ1jaLNP9NSeIQAAAAAAAO1mZggAAAAAAPS7nej+Hh7dnolyBGaGAAAAAAAAA81gCAAAAAAAMNAskwUAAAAAAP3uRnR/maxut3cEBkOAnjaXZYWx57duFhf81eJy8a8mGtz4enHs2x9MFLyciD2YiI0kYvv5zUTsVCI2nYi9kIg9loilzvHdROyNROxsIvbxRCzxGsZXSraXUnytsyx1Pa+XbO+RROydUjVm2dw+RzyZiKVew7JtFl/TPJ8tVWe63GIil2Jl2ytbZ1llc0npRJ77t5l6nYo/T2XPv+x7LZVnnqf+/hZLX+/U367ivwmdeF8ADJqivshsnnc5EwCgHQyGAAAAAABAv7OBepI9QwAAAAAAgIFmMAQAAAAAABholskCAAAAAIB+Z5msJDNDAAAAAACAgWZmCAAAAAAA9DszQ5IMhnTQ+fPn49SpUy1jU1NTMTU11eWMoDfNZVlh7Fv5rxYX/LvF5eKFRIP/m1Q2HywO/VSi2LcfTAR/JxF7MhF7OxHbr+y1RCx1cT6eiF1OxN5NxJ5IxPY7x9byvDjPLHstUfJsos5nE3WmrtnpROx6Itb6/x/290YiVnx+Ee+UbC8i/do/moh9ozCS57OFsSyb2z+lloqvaZYtJnKZbnt7KeXPr/j1TZ1fWvF7NPUapWIp+5172XrLSudT9jOa+tyXU/bz0u5yS0tLEfGfFZTqdo+LQaHPRK9o1SeZzfNjyASAXrK0tPTD++C7Xb/e/nt/OstgSAddvHgxqtXqcacBAABHNjU1Fb/4i98piH4rIla6mQ4DQp8JAOhlqR9n1Ov1qNVqXc5oH2aGJNkzBAAAAAAAGGgGQwAAAAAAgIFmmSwAAAAAAOh3NyLiBx2o9+8tRfxu671T4vv9s3eKwRAAAAAAAKC1n5u69WjlzXrEcz22d0oBgyFAV8xlWWFsLf9KYeyf/EcfLa70pUSDiWKxkYilfPvtRPBUIvZkIvZEIvZWMp2I04nYI4nYxxOx1MV5IxFLnf+1ROydROxsYSTLXkiUS3k3UediotyDidjlwkieT5dsL/WritS1Lnc9I76RiEXk+WwyXiTL5krFUu2lyqXPsfjapOssls4z9fqWk+fPJtpLfSaKz73b1/ooyr5nyiv+HJa9bp04h86c++Hbu7V5pA3Ugd5X1C+ZzfMuZwIAHbAT3d/Q3AbqAAAAAAAAvcFgCAAAAAAAMNAskwUAAAAAAP1uJ25tot7tNvuEmSEAAAAAAMBAMzMEAAAAAAD6nZkhSQZDgLaZy7LC2B/mLxXGPhNfKIz9X7700XLJ/P7XEsF3E7G3E7EnE7E3ErFTidg7idhjidh+bX48Efv1ROx6InY2EUud4zcKI3k+WxjLslcS5T6VKPdSIpfTidjlRCx1fsWybDERfbBkrOz7qfh12E+WzRXGUq9h+j3TifbK1Zm6pnk+najzpUSdqc9SOen3U9lrXVxn+vNZttwLB0vskMq+Z8q+n8rqdntlr0v69S3+TAD0kqK+yWyedzkTAKBXGAwBAAAAAIB+Z2ZIkj1DAAAAAACAgWYwBAAAAAAAGGiWyQIAAAAAgH53I7q/TFa32zsCM0MAAAAAAICBZmYIcChzWVYY28h/tzD2D/7GaGHs5f/mrxQ3+PuJZP6VRCw+nIi9XRy67+PFsRtfStR5KhH7hUQsVef1RCwi4sFELHGO8cQ+9baW558qjGVZufNIl7ucKDeXKPdkIvZGYSTPZ0u2V9bZRCz12hfH8ny6MJY+h1QuERHv7BMvyufZRD4vJMqlXouXEi2m8iz+jKauW0qef7pUuSxbLJVL6jUsn0vx65C239+n1lLvif3Lpt4XZc+jWCc+9+k6y71H0++L4msGMEha9VFm8/wYMgGAY2YD9SQzQwAAAAAAgIFmZkgHnT9/Pk6dav0rv6mpqZiamupyRgAAUNY/jA996EMtI9evl5stBPpMAEAvW1paiqWlpZYx98D9x2BIB128eDGq1epxpwEAAG3wM/GHf/hftozU6/Wo1WrdTYeBoM8EAPSy1I8zevIe2DJZSZbJAgAAAAAABpqZIQAAAAAA0O9uRMQPjqHNPmEwBLjLXJYVxv5h/v8ujP2Dxkhxpf8k0eDrqWxeKw79/pPlysWfKg4l/4CfTsQeTMS+Vi6XaL1+9o9cKxlLKV7vMsteKdneu4nYVxKx1Oubau/tROxsYSTLFhPlHi2M5PmnE3W+lKjzG4lYSvH7IsvmStZZXpa9kIg+0oEWy163Yp24bnk+m4imPmfFuaTqTL9/e2cd26Nd6+LPb54/e4R6uyf9vihW9rqVfT8B9Kqifspsnnc5EwCgHxkMAQAAAACAfrcT3d/Dw54hAAAAAAAAvcFgCAAAAAAAMNAskwUAAAAAAP1uJ7q/obllsgAAAAAAAHqDmSFwj5rLssLYn80/Vhj7QnyouNL/W3Gd8aVEMjeuJYIfT8RS5U4nYqdK1vlaIvZEyTqP4huJ2JMl63ynMJLnz5aqMcsWE9FHE7G3S+WSZak32xuJ2PVSsSybK4zl+WyiXOq6pHI5W7Lcu4lY8et+S/FnJv1aFF+bVJ1ly+X5dMk6U+/D1DUtvm5lzyH9XnshUa5Y6n3YCWU/E/vXW/yZSV/vlNT7qf3XrWyeZXMp317xZwmgG4r6KrN53uVMAKDPmBmSZGYIAAAAAAAw0AyGAAAAAAAAA80yWQAAAAAA0O8sk5VkZggAAAAAADDQzAwBAAAAAIB+dyMiftCBev9g6dajZZvXO9BgZxgMgQE2l2WFsev584WxqfjfFsb+2c88Udzg/ySRzL+QiH37rUTwkUTsWiL28UTs7ZKxsnWWlWpvP6lrk7qmxa9vlr2UKPeNffIp493CSJYtJsr9fGEkz3+hZJ3lpOssvlnI89lEnXMlszlbslxEKtdO1Jk6/5TUtenMNS2ru6992XKpXDrxGu2nM++L6ZLlyuWSkn7tX0qU+3TJOrt7fgBFWvVZZvP8GDIBAAo9NXXr0crb9YjfqHU3n5IskwUAAAAAAAw0M0MAAAAAAKDf7UT3NzS3gToAAAAAAEBvMDMEAAAAAAD63U7c2kS92232CYMhHXT+/Pk4depUy9jU1FRMTRVsOgMAAD1maWkplpaWWsauX7/e5WwYFPpMAEAvcw88WAyGdNDFixejWq0edxoAAHBkqS+m6/V61Gq1LmfEINBnAgB6Wd/dA5sZkmQwBPrcXJYVxp7/cl5c8K8lKv1OIvZYIvZWIvbtRCxZ6elE7HIilhqdT7X3zUQs1VG/loil8nwiEXstEYuIeCQRe6tkLOXdROxsItb6154REXn+6cJYli2WbK/4emfZfte0tTx/tlS5LHshES1+j6bP/clE7I1E7J1ELHU9I9K5zu1T9vBtps4/z6dLtZa+pmU9moh9IxEr/kyUv57F8ny2VHvdzuVWm8WvU+rzlPqM7tdmu8t1QupvJUC/KOq3zOaJPgsAQBvZQB0AAAAAABhoZoYAAAAAAEC/uxERPziGNvuEmSEAAAAAAMBAMzMEAAAAAAD63U50f0PzPtpA3cwQAAAAAABgoJkZAn1gLssKY382/1hh7Pm/m6h0LBH79xOxfykRey8RS3otETudiF1LxB5MxF4p2V49EXs7ESvr+j7xVJunErF3SuQSkefThbEsS13TN0q1l/bBRCz1fkpd00dL5pJS7lqn8yz7Xit+T+T5s8mSWfZSIvqNUm2mr02qXEqq3BOJWPF7NM9nS+ZSLMsW295eqs6yOnHuR5F6n6avaepvV7lyZaWuafo1LP6b0P33aPuvCzB4WvVfZvP8GDIBAPgRgyEAAAAAANDvdqL7G5pbJgsAAAAAAKA3mBkCAAAAAAD9zsyQJDNDAAAAAACAgWZmCAAAAAAA9LsbEfGDY2izTxgMgR4xl2WFsW/lv1oY+0TjrxVX+iuJBv+7ROzBRCwlVWfqr82N64lgKjaSiL2WiD2SiKW8lYidSsRS5/BGuVQiIuLJROxyIpZ6gT9cGMmyuUS5s4lY8bXJssVEuZTU61v2DfyNwkiWvZIol7rWqevyzn4JtZTnzxbGUq9Rnk8nyr2wT6vv7pdWgdR7v+xnJiV1vct91tLv0eI883w2Ua7cezSVS+r1TUnlmf7Ml3v90tdlv/dpuXzKvoadeO3Tn9H0temusp9B4F5T1IeZzfMuZwIAsD/LZAEAAAAAAAPNzBAAAAAAAOh3N6P7G5rf7HJ7R2BmCAAAAAAAMNDMDAEAAAAAgH53I7q/oXkfbaBuZggAAAAAANB2a2trUavVIsuyqNVqsbGxcdcx9Xo9xsfHY2ZmJiYnJ2Ntba0juZgZ0kHnz5+PU6dOtYxNTU3F1NRUlzPiuM1lWWFsK18pjP3GP7pQXOlfTzT4QCL2Lydi/ywR2/hacey+DxfHblxLVPqpROyVROyNROyJROx6InY5EXsnEWv9Wb/l0UQs5fQ+8VSuZwsjef7pwliWvZCoM3WOjyRi7yZixa9Fns8WxrJsrgN1LibKFb9Hy+ZSVvo1Kiv1GkV05nVqv9R7OyWVZ55PJ8oVv2fSdRZfs5RULmWVfY3K5rJfe92+NmVf+25LvdfKfj7LXOulpaX40Ic+1DqL6+3/e8e9QZ+pPxT1Y2bzvMuZAEB3LS0txdLSUsuYe+D9LS4uxvr6ekxOTsbW1lYsLi7G6OhorK+vx8jISERENBqNqNVqsbm5GdVqNSIihoeH48qVKzExMdHWfAyGdNDFixd3X0AAAOhnqS+m6/V61Gq1LmfEINBnAgB6Wd/dA+9E95etSmzY/vrrr8f6+vruv5955pmo1WqxsLCwOxgyOTkZIyMje+4JmzNE2j0YYpksAAAAAACgbTY2NmJhYWHPc9VqNarVajQajYiI2N7ejo2NjRgdHd1z3Llz5yIiYmWleCWdMgyGAAAAAABAv7sRET/o8qNgJsrIyEhUKpWWsebzly5d2vPvpuYskdtnlbSDZbIAAAAAAOBedPP9W4+ydt471OGNRiMmJyd3/zsiYmhoqPDYdjIYAgAAAAAA/e5mJPfwaOnN+Yi35jqRzV3W1taiUqns7gWytbUVERFnzpxpefz29nZb2zcYAm02l2WFsaG8eNOf3/hrF4orfSzR4M8nYr+RiF2+lgieTsQSydz4eqLcG4nY24nYqZKxsp4o2d5XErFvJGJPJmKp1ygi4uw+8f9/e3cQI8l1Hgb4b0eQtAJJDVc0BQcOJfTSFwcUnJ6lEMQBCMPTBhIFCGLOrE+GfYhnQKzgBDrMQKfhBAEmvYcglwHds0CyEJIDMUPnFMtAzyFKICQxZjq0idgHeTvmISLICLttkshyaa4rh2W3OLtTb2Zruqu6er8PaJDbf71Xr96rV/vevq6qkzUaNwqli3gyEUu1YSrdndxIo3HttALlyG+nRiP1l3vRdPmybDORZ7Hjy7JXJp5nqh3uyz/XUnWTOv6yFS1no/FaIt16It2NM5VrUoqfT8XaaFrtXrSvFZVu+6LnzOTrJn2u5e+vLv0TmC0nzWc2s6yCkgAApfjadyP+1neKp//wzYj/+dKZNt3e3o69vb3xny9duhQREbdu3Tpx+7zHbBVlMQQAAAAAAB5HP/OF+5+i/sYTZ9psY2Mjrl+/fmyBY/T/eXeAWAwBAAAAAACOuxe5LzSf6j5Psbu7G+12e/xi9JHLly9HxMPvBhn9eXFxcTJl/NTPTDQ3AAAAAACAuP+ekIiIpaWlY9/3+/1YWFiIVqsVvV7vWOzg4CAiIq5cuTLRsrgzBAAAAAAA6u6TKP/OkMT+Dg4OYnt7O9bW1mJ3d3f8/dHRUSwuLkar1Yrr16/H4uJiDAaD8WOxOp1OdDqdWFhYmGhRLYYAAAAAAAAT0+/3o91uR0TE2traQ/Hbt29HRESr1Yqjo6PY2NiIZrMZg8EgNjY2YnV1deJlshgCj2ir0UjG/2b2m7mxTvxufsL/nMj0HyVi28niJDyViL2biPUL7u/5ROyFROytgnn+x0Tsn0xhf88mYhcSsfcTsbcTsYiIryVid05Jm+eDRCx1/Kl6S5UzVW+psqTq9MncSJat58YajdcKprtWKJaS3t9WImWqXlJS7RCRbov89k0df+oYU1LHn2WbhWIpWfbKxMuSkj5nivXrVFnS51Mx6b6UrpdpHH9RxeutaD/MN41zraj8svy41HIA55c3r9nMspJLAgDMo1arFdkZxxWtViv29vamXCKLIQAAAAAAUH+fRMRfVbDPmpibF6g/+MZ5AAAAjjNvAgDgcVXbO0MaD9zSO3q22Ei/34/t7e1oNpsxHA6j3W7H8vLysTST2gYAAGAWmTcBADxG/joi7lWwz5qo5WLI7u5urK6uxqVLl8bfLS0tjf9/MBjE4uJiHB0dRavVioiIS5cuxa1bt8YvXpnUNgAAALPIvAkAAH6qloshe3t70ev1cuNra2uxtLQ0HohHRGxsbMTa2tp4MD6pbQAAAGaReRMAwGPmXpT/Do+y70Q5h9q9M2R/fz8ODw9jZWUldnd3H4oPh8M4ODiIdrt97PvLly9HxP1fR01qGwAAgFlk3gQAAMfV7s6QXq8Xw+Ew9vf3Y39/PzY2NmJvb298u/fh4WFERDSbzWPpRr9S6vV649h5t/Erp/m19cCzlT9rIUu3+/ci/9nIN7/3t4sV6EaxZBE/SsTu5Ic+94382CeJdPF+IvZUIvZBwTwPErHnE7E/T8TeLViWRJ0l83wrEbuQiEVEvHdKPM+TuZEsWy+Y56/nRhqNa4XKko6l5NdLo7GVG8uyzULpIr6WiL2diOVL76+YdJ7PniPn/GNM1+lriTxT14R86XMt/9qVKmdRRc+1VB8sel6k6yUl/xqULmd+2552DNNoi7IVv46mnKePProi52+/34/FRf/oPUvMmxjJm9tsZlnJJQEAqFbtFkO63W50u93o9/vR7XZjd3c32u123Lx5M5rNZgwGg4iIWFhYODH9YDCY2Dan+fDDD+P991P/eJr2hS98Ib7whS8UTg8AAGdx9+7duHv37qd/+ih3u7yx7YcffjiFUnEedZk3mTMBAFU5PgZ+dDM5Bv4kyn9MVtn7O4faLYaMtFqt6Ha70W63Y2VlZfxLp5s3b0ZExMWLF09MNxwOJ7bNaV566aVTt0nZ3NyMV1999Vx5AADAaba3t2Nr6/S7j7785X9VQmmYpFmfN5kzAQBVOesYmPlR28WQkeXl5VheXo5+vx8REZcuXYqIiFu3bp24fbPZnNg2p/nBD34Qv/RLv3Tqdnn8wgkAgDJ897vfje985zsREfHlL2/nbveXf/ndE79/8803z/2P2kzXrM6bzJkAgKp8dgxcxEyOgT+JiL+qYJ81UfvFkIiIdrsdBwf33x0wGmzn/QKp2WxObJvTPPHEE/HUU6n3JAAAQPWOP2roi7nb5Y1tn3jiiSmUikmbxXmTORMAUJXzPm7TGLh+fqbqAkzK5cuXj/33wWfTjv68uLg4sW0AAADqxLwJAIDH1VzcGdLr9WJtbS0i7r+4r9VqRa/Xi/X19fE2o19AXblyZWLbUG9bjUZu7O9lfz839muD30tn/O/z841U0vx3lUbc/pNE8OuJ2J1E7M/zQ598kEiXesHlP0jE+olYSuqXgqnjezcRSx1fKs8LidjbidgLidizidhp3kvEUmX9am6k0bhWsCxPJmKpOi2WZ5a9khtrNFLP+8yv70bjxhnKdJJU28+OLNssnLb4eZGSOn/zpY4j1fZFjz99PqWk+uDk93ee9p20VP+sk6Ln0zTOw6J1WrQss3Q+MVnmTfPvpDnOZpZVUBIAoBJ/HRH3KthnTdTqzpB+vx+Li4tx7dpP/1Fmf38/Ll68GMvLy+Pvrl+/HgcHB8d+ndTpdKLT6cTCwsJEtwEAAJgl5k0AAPCwWt0Z0mw24+LFi7G9vR29Xi9arVa02+3odrvHtmu1WnF0dBQbGxvRbDZjMBjExsZGrK6uTnwbAACAWWLeBADwmLoX5b/QvOw7Uc6hVoshCwsL0ev1zrRtq9WKvb29UrYBAACYFeZNAADwsFothgAAAAAAACdwZ0hSrd4ZAgAAAAAA8KjcGcJc22o0cmP/NPtKbuznv/df8zP98JSd/l4i9s4pafM8/Y382AeJdMmV4BcSsTvp8uT6fiL21UTsrUTs2UTsQiL2XiL2fME8U+VMebfg/n7hlHwPErEncyNZ9uu5sUbjWm6s+HmROsaU/JM7Xc78/WXZK4XyzLLNRLqtgmVZL1SWVNumNBqvJaKp/pKWqpui6VLHnz6OySt6fOk2nLz0+Zt/rqXznPy5fZ59Fm+LYnkW3d80ylJUucfw44nvC8iXN8/ZzLKSSwIAUB8WQwAAAAAAoO7KfkRWVfssyGOyAAAAAACAuebOEAAAAAAAqLt7EZH/1oDp7bMm3BkCAAAAAADMNXeGAAAAAAAAJ/toJ+Luzsmx7E65ZTkHiyHU3lYj/96vX8m+mRv7+X/xP/Iz/b3EDj86pUC3U8F3E7GvFszzTxKx/5OI/UUq04RvJGKp43sqEXuhYJ7vJWL5F+Is+/XcWKPxWiLPJxOxZxOxVDlTsdN8LRF7OzfSaGwl0qWOI/WXW9F0qeO/kBvJsvXcWPr4imk0rhVMWWxAUPz4ip6Hp5Vns2B58tuw7LqZxnmRqpfU8aXOp3Se+Yqeo8XrpVj7nba/oudaKl3ROk2ZxvlUVNF6KZonUK68uc5mlpVcEgCgFqb1yKrPXb3/OXGf/Yj/tzilHU+Wx2QBAAAAAABzzZ0hAAAAAABQd/ciouwbSP+65P2dgztDAAAAAACAuebOkCl6+eWX48KFk5+XfvXq1bh6Nec5awAAMHP+6NPPST4psyDMEXMmAGCW7ezsxM7OyS8Ov3NnBl8c/klE5L9eeTpq9CoziyFT9MYbb0Sr1aq6GAAAMAHf/PRzkh9HxG6JZWFemDMBALMs9eOMfr8fi4v1eHE491kMoRa2GvlLml/PruTGXvovr+dn+oeJHb6TiL2QiEVEfJCI/exXE/v8USLhDxOxpxKx9xOxrydif5GIvVswlipLaiX9GwXTPZ8baTSuJdI9mYil/ELBWH7bZtlvJ/eYPo6Tf2F5P9/1RJ5biXSbhdJNQ3p/+ceerrNiUvVSVNH6zLJXJp7naWmncfwpqTYsWpZpnPdl10uqX6fTzc75e5qyy5ra3zTOi/T1Kf/vu2mUpUhd358IWgyB8zhpzrOZ1einlgAAM85iCAAAAAAA1N298JisBC9QBwAAAAAA5po7QwAAAAAAYB7U6E6NsrkzBAAAAAAAmGsWQwAAAAAAgLnmMVnMjK1G/tt9fiX7Zm7spd99vdgO/2+xZPHWaRt8Pz/0TipdKxH7hUTsTxKxr6d2mPBBwdgvJ2LvJmJ3CqZ7LxFbSsTeT8TeTsQuJGKpdkjVWf6xNxq/n0gXEfFkoX02GluJdKljLCbLNguVJcvWE+leS+wxdV4UPb5UO6XqM1+qXorWWdGynC6/3tJtmH8cxaXa4lqiLPnnU9mmcc6k+kSWvVJof9M4n6ZzTkynTosq2n+nYVr1DZxP3rxnM/NMCwCAaXJnCAAAAAAAMNcshgAAAAAAAHPNYggAAAAAADDXLIYAAAAAAABzzWIIAAAAAAAw1yyGAAAAAAAAc+1zVReAx8tWo5EbW8hWc2Mv/W43P9PDxA7/2w/zY5/75UTC9xOxpxKxs8SLeCERe7dgLFXOJxOxC4lYor7j+YJ5ptri2UTsIBH7IBErJsteyY01GjcS6X47ke7aOUp0JxH7Wm6keHny26LR2Co1XZZtFswzdR6mYsWkypI6hlRZsmw9sb9U+6XOl3S+Kal9Fs0zJX38Res7tb9i6aYhfQ1KnfepPIv1pfPUS9llLVvRuil6DEXbqdj+flwgDcy/k+Y/m1lWQUkAgMfDJxHxVxXssx7cGQIAAAAAAMw1d4YAAAAAAEDtfRLl36nhzhAAAAAAAICZYDEEAAAAAACYax6TBQAAAAAAtecF6ikWQ6bo5ZdfjgsXLpwYu3r1aly9erXkEpVjq9HIjf2d7NdyY//4e938TJ9J7PDDVGmezQ/9bCLZO/8hEfxqaocR8X4i9vYpafO8WzD2QSKWfxxZ9kpurNF4LZFnymn1VsR7BdM9WSiWrpetRJ4nXwdOlypnujzTkGXrubH08Sf6YbIN8+st3RbXEuk2C6WLuFMoz5RUX5rG+ZRqv/NIlbVo3aTlH3+6DVPn4eSl27Ae0vU5HcX7U7H6Lv/8LaZoWSadbmdnJ7797VdzUtVnAsRsmZc5U94caDPLSi4JADBJOzs7sbOzc2Lszp38fytgNlkMmaI33ngjWq1W1cUAAIBzu3r1anz72z/Jif44InbLLA5zwpwJAJhlqR9n9Pv9WFxcLLlEp7kX5f9Q6V7J+yvOO0MAAAAAAIC5ZjEEAAAAAACYax6TBQAAAAAAtecF6ikWQwAAAAAAgBz/NiL+XU7sozILci4WQyhkq9HIjf04+ze5sVf/4J/lZ/rPEzu8/aNE8L1E7JfzQ+/8MJHuG4nYk4lYRMSfJ2IXErF3C+Z5p+D+3sqNJJo30vX9bCKWasOUtxOxFxKxou2Qf3yNxlYiXUp+GxXPMy2db+r4U+dTqn3z88yyVxLp8jUa1wrFsmy90P5S6VL1mYpl2WYill8vRc+LadTL/XxfS+Sbf4zTcJ7jyFO0DYumK6povy67jVJOO7enUdaibcjJ8urz/ssjvUCd+Zc3D9rMspJLAgBwkmndGfKbn35O8lZE/MMp7HPyvDMEAAAAAACYa+4MAQAAAACA2rsX5b/D417J+yvOnSEAAAAAAMBcsxgCAAAAAADMNY/JAgAAAACA2pvWC9RP22c9WAwh11ajkRt79b9n+Qn/dSLTf5mI3X731DI9uh8mYj9KxN5LxJ4/ZZ9vJWLPJmIXciNZtp4bazR+v1BZsmwzkedWIs+UVL0VU7ScqXQpjca1RDS/jSKeTMRS9VKs3U+Trrf8Y5zGeVE0XbosrxXKM6X4eV8sz6Ln6HnOi6Ky7JXc2DSOcRqm0xazc3wRd6ouwJmcp87mvw2BWXPSfGgzS8yDAACYaRZDAAAAAACg9rxAPcU7QwAAAAAAgLlmMQQAAAAAAJhrHpMFAAAAAAC15wXqKe4MAQAAAAAA5po7Qx5zW41GbuzVH2T5Cf9uKtd3E7Hvn1akHHcSsQ8SsScTsQu5kSxbz401GluJPCMink3E3kvs85XEPl8rlGdK+jjyjyFVzuL7y2+LaWg0riWiqXMm1X7558y0nH4unizLNktNl5I6hqLHV3R/qeMru66LKnp851H2MRZVl3KmzMMxnMfjfvxlquJaAlXKmxNtZon5EADATPokyr9Tw50hAAAAAAAAM8GdIVP08ssvx4ULJ//i/erVq3H16tWSSwQAAEX9UfziL/7iiZE7d1J38UI+cyYAYJbt7OzEzs7OibHZHAN7Z0iKxZApeuONN6LValVdDAAAmIBvxp/+6X86MdLv92NxcbHk8jAPzJkAgFmW+nGGMXD9eEwWAAAAAAAw19wZAgAAAAAAtXcvyn9s1b2S91ecxZDHwPPxv3JjN+MP8hO+9Foi1w8SsaLPy/tabiTLXsmNNRr55SyartHYSuS5mRs7j0bjWmKf64l0+WWNOPn5y+fJs2jdpGLpY8g3nTyL1nW+aZ1P0zoXy1T0GIq2RVFl1/U8tC2Pryr+Dk2ZtfLUgXphXm01Gid+v5llJZcEAIAqWAwBAAAAAIDa8wL1FO8MAQAAAAAA5prFEAAAAAAAYK55TBYAAAAAANSeF6inuDMEAAAAAACYa+4MAQAAAACA2vMC9RSLIXOi0biWiN4pmOuFQnlm2WbB/RWTZa+Umm5asmy9YLrJ13f5bViPYyiaZ9n1+TjQFieb9+OjHmbtPJy18gDlaDS2Hvouy7IKSgIAwKywGAIAAAAAALXnnSEp3hkCAAAAAADMNYshAAAAAADAXPOYLAAAAAAAqD0vUE+xGAIAAAAAAOT4fkT8YU7s4zILci4WQ+ZElq1XXQQAAICZkGWbVRcBAKAC07ozZOnTz0n+d0R8dwr7nDzvDAEAAAAAAOaaxRAAAAAAAGCueUwWAAAAAADU3idR/gvNvUCdiHj55ZfjwoULJ8auXr0aV69eLblEAABQzM7OTuzs7JwYu3PnTsmlYV6YMwEAs8wYeL5YDJmiN954I1qtVtXFAACAc0v9w3S/34/FxcWSS8Q8MGcCAGZZ/cbA03qB+mn7rAfvDAEAAAAAAOaaxZAp+Pjjj4/9l/q7e/duvPrqq3H37t2qi8IEadf5o03njzadT9p1/hj/8qicM9Vw/a2Geq+Geq+Geq+Geq/GbI5n7sVP3xtS1udeKUc2CRZDpmA2OwLncffu3dja2vKXypzRrvNHm84fbTqftOv8Mf7lUTlnquH6Ww31Xg31Xg31Xg31Xg3jmfqxGAIAAAAAAMw1L1AHAAAAAIDa8wL1FHeGAAAAAAAAc82dIQAAAAAAUHujF6iXvc96cGcIAAAAAAAw1yyGAAAAAAAAc81jsgAAAAAAoPa8QD3FnSE1tLOzU9v861z2aVPv5ec9beq9/LynTZtWl/80qffy85429V5d/lCVSZ7bs5jXrPbdea8r9V5+PpPOa5Jm8RhnsUyTNu91pd7rnxf1YjGkhuo8Sa5z2adNvZef97Sp9/LznjZtWl3+06Tey8972tR7dflDVWb1H0hm8R+TJmne60q9l5/PpPOapFk8xlks06TNe12p9/rnNXtGL1Av81OfF6h7TNYZ9Pv92N7ejmazGcPhMNrtdiwvL1ddLAAAgJlh3gQAwCyzGHKKwWAQi4uLcXR0FK1WKyIiLl26FLdu3YrV1dWKSwcAAFA98yYAgFngnSEpHpN1irW1tVhaWhoP6CMiNjY2Ym1trcJSAQAAzA7zJgAAZp3FkIThcBgHBwfRbrePfX/58uWIiNjd3a2iWAAAADPDvAkAgDqwGJJweHgYERHNZvPY96NfO/V6vdLLBAAAMEvMmwAAZkXZL08fferBO0MSBoNBREQsLCwk4w/66KOPIiLij//4j8+1/89//vPx+c9//qHv79y5E/1+/1x5p0wz/7qW/cMPP4yIiDfffDOeeOKJiecfod6ryHva7arey89bm1aT9zTzd/2tLn99tZr8qyr7xx9/HB9//HHhfEfj3tE4mMdLkXnTpOdMk+w7s5jXpPKZ9PV3nutqknmp92ryUu/V5DWr9T6LdTXJvNR7sbzmcwz8k8dknwVl5FpfX88iIjs6OnooFhFZs9k8Md2NGzeyiPDx8fHx8fHx8fF5rD43btyY9hCdGVRk3mTO5OPj4+Pj4zMvn1kYA7/99tvZl770pcrq4Etf+lL29ttvV10Np3JnSMKlS5ciIuLWrVsnxh+8DXzkW9/6Vty4cSN+7ud+Lr74xS8W3n/enSEAADBJ5/1V3EcffRTvvPNOfOtb35pgqaiLIvMmcyYAoGrzNAZ+7rnn4s/+7M/iJz+p5i6NZ555Jp577rlK9v0oLIYkjAbtw+EwGX/QM888E7/1W781rWIBAADMjCLzJnMmAIDJeu6552qxIFElL1BPuHz5ckQ8/Izb0Z8XFxdLLxMAAMAsMW8CAKAOLIYkLCwsRKvVil6vd+z7g4ODiIi4cuVKFcUCAACYGeZNAADUgcWQU1y/fj0ODg6O/cqp0+lEp9OJhYWF6grGuT34yzVg9um3UB/6KzxezJuq43rL48q5z+PGOQ/n18iyLKu6ELOu3+/H9vZ2NJvNGAwG0W63Y3V1NbndcDiMdrsdy8vLFZSYkzQajWN/brVacXR0NP7zWdpvUtvwaIbDYWxvb0fE/Un1g8psO+07Oae1a4R+W0f7+/uxvb0d/X4/Wq1WdDqdWFpaOraNPlsvZ2nTCP21bj7brs1mM7rdrr7KuZ1l3qStz8/1drrMPaphblAd4/fyGV9Xw/iXiIjImIibN29mEZEdHR2Nv2s2m1m3262wVIx0u91sdXU163Q6489n2+os7TepbXg0vV4vW15eziIiW11dfSheZttp38k5rV2zTL+to06nky0tLWXdbjdbX1/PIiKLiKzX64230Wfr5SxtmmX6a92M2qvX62W9Xi9rtVpZRGQ3b94cb6OvMg3a+vxcb6fL3KMa5gbVMX4vn/F1NYx/GbEYMiFLS0vZ0tLSse+63W5mvWk2PNg2J8VPa79JbUMxeQPjMttO+05easKj39bP8vLysT8fHR1lEXGsfvXZejlLm2aZ/lo3nU7n2J9H7bq3tzf+Tl9lGrT1+bnelsPcoxrmBuUzfi+f8XU1jH8Z8c6QCRgOh3FwcBDtdvvY95cvX46IiN3d3SqKxaf29/fj8PAwVlZWTmyLs7TfpLZhsspsO+1bLv22fg4ODh56pEGr1YpWqzV+tq0+Wy9nadMI/bWO1tfXj/159D6HVqsVEfoq06Gtz8/1tlqujdVx7k+H8Xv5jK+rY/zLiMWQCTg8PIyIiGazeez7UYfq9Xqll4mf6vV6MRwOY39/P9bW1uLpp5+Og4ODcfws7TepbZisMttO+5ZLv62fpaWlh+pxZPS9PlsvZ2nTCP11Huzv70en09FXmSptfX6ut9VybayOc386jN/LZ3w9O4x/H18WQyZgtHo7WlXMi1ONbrcbWZbF0dFRrK6ujl9KNGqXs7TfpLZhsspsO+1bLv12fgwGg1hZWRn/f4Q+W3efbdMI/bXuNjY2xi9uHNFXmQZtfX6ut9VybayOc79cxu/lM74ul/Hv481iyATcvHkzIiIuXrx4Ynw4HJZYGvK0Wq3odruxt7cXEfcvfhFna79JbcNkldl22rca+m297e/vR7PZjNXV1YjQZ+fBg236Wfpr/Vy7di0Gg0EMh8Njj2HQV5kGbT05rrfVcG2snnN/+ozfy2d8XS7jXyyGTMClS5ciIuLWrVsnxvNugaMay8vLsby8HP1+PyLO1n6T2obJKrPttG+19Nt62t7eHg/cI/TZefBgm55Ef62P9fX12Nvbi16vFwsLC+NnWOurTIO2njzX23K5Ns4O5/70GL+Xz/i6XMa/WAyZgNFJmrdy5ySePe12e3zROUv7TWobJqvMttO+1dNv62VjYyOuX79+rA712Xo7qU3z6K/1srS0FKurq+Nb8vVVpkFbT4frbXlcG2eLc3/yjN/LZ3xdHePfx5fFkAm4fPlyRDz8TLfRnxcXF0svE6cbtdtZ2m9S2zBZZbad9p0N+m097O7uRrvdHr8AbkSfra+8Nk3RX+vlxRdfHE+89FWmQVtPj+ttOVwbZ49zf3KM38tnfF0949/Hk8WQCVhYWIhWqxW9Xu/Y9wcHBxERceXKlSqKRUKv14u1tbWIOFv7TWobJqvMttO+1dNv62F/fz8i7v/S5rP6/b4+W1OpNs2jv9bPYDAYt7G+yjRo6+lwvS2Pa+Nsce5PjvF7+YyvZ4Px72MqYyKOjo6yiMhu3rw5/q7ZbGadTqfCUnF0dJS1Wq1j7bC3t5etrq4+tN1p7TepbXh0t2/fziLioXbLsnLbTvtOVl676rf11ev1slarlXW73WOf1dXVrNvtZlmmz9bNaW2qv9bP7du3s+Xl5Wxvb2/83c2bN7OlpaVj2+mrTIO2Ls71tjzmHtUwN6iG8Xv5jK/LZ/zLZzWyLMsmv8TyeOr3+7G9vR3NZjMGg0G02+1YXV2tuliPteFwGCsrK3F4eBiXL1+OVqsV7Xb7odX3iLO136S24ez6/X50u93Y3d2NhYWFuH79eiwtLcXCwsKxbcpqO+07Gal21W/rqd/vJ2/nvX379rjf6rP1cJY2jQj9tYba7fa4zdrtdjSbzVheXn5oO32VadDWxRgflcPcoxrmBtUwfi+f8XV1jH8ZsRgCAAAAAADMNe8MAQAAAAAA5prFEAAAAAAAYK5ZDAEAAAAAAOaaxRAAAAAAAGCuWQwBAAAAAADmmsUQAAAAAABgrlkMAQAAAAAA5prFEAAAAAAAYK5ZDAEAgBJsbGxEo9GIRqMRTz/9dDz99NO5f240GjEYDKouckRE7O7uHivbyspKtNvtuHTpUqytrcVwOKy6iAAAzCDjX2aNxRAAACjBcDiMpaWluH379viztLQUERHXr1+P27dvR5ZlcXR0NN5+FqyursaVK1fG/7+3txe9Xi96vV7s7u7G4uLizJQVAIDZYfzLrLEYAgAAJel2u7GwsJDcptVqxfr6ejkFOqPRr/Ta7fb4u2azGUtLSzEYDOLg4KCqogEAMMOMf5kln6u6AAAA8Dhot9vRbDbPtO3a2tqUS/NoRpO90S/5RkYT21l5pAEAALPD+JdZ484QAAAowfLy8pm3bTab0Ww2Y39/P9rtdhwcHIyfXby2thb7+/vj5xj3+/2IuD9hW1lZGT/X+LP6/f6xZx1vbGycuSyj/JvN5kO/6hvFWq3WmfMDAODxYPzLrHFnCAAAzKD9/f3Y2NiIwWAwnog1m804PDyMbrc7fmbxyNLS0ngC+Vn9fj82Njai1+uN811ZWYnhcBjdbvfUcrz++uvj/B/Md1S2B2MAAPCojH+ZNneGAADADFpeXh4/LmBhYSE6nU4cHR2NXzB50rOXL168+NB3v/M7vxOdTudYvgsLC7G7u3umFz+OHhEwel7ycDiM/f39+NVf/dVYWFgYTzIBAOA8jH+ZNneGAADAjBpN+F588cVC6QeDQfT7/dje3j4xfnh4mPxV23A4HD8K4PXXX4/t7e24ePFiNJvN6HQ6sbq6WqhcAABwEuNfpsliCAAAzLiTfgV3FqOJ3N7eXqH0o1/FtVqtwnkAAMCjMv5lGjwmCwAA5tRgMDj230c1egTAb/zGb0ysTAAAMC3Gv6RYDAEAgDnVbDYjIh56qeTI6JdveUZxL4gEAKAOjH9JsRgCAAAVu3Xr1iOn+cpXvhIRx3/1Nvr/0YshR5O4jY2N8SMDRnZ3d5P5DwaDGAwGsbCwEK1W65HLBwAAeYx/qYJ3hgAAQEUenLw9aPT9SfHRBG1jYyMWFhZiMBjE0dFRRNz/RVu73Y5erxfr6+tx7dq1WFxcjOXl5XjxxRej1+tFq9VKvgBy9Ku4y5cvFzw6AAA4zviXKrkzBAAASnZwcBBra2vjyeD29nZsbGwc+5Xb/v5+dLvdiLg/4Xvwl2xLS0vR6XTi1q1bsbKyEjdv3oxutxvNZjPW19ej0+lERESn04lOpxPNZnOc58rKyjh+kt3d3djY2IiIiMPDw1N/RQcAACnGv8yCRpZlWdWFAAAAAAAAmBZ3hgAAAAAAAHPNYggAAAAAADDXLIYAAAAAAABzzWIIAAAAAAAw1yyGAAAAAAAAc81iCAAAAAAAMNcshgAAAAAAAHPNYggAAAAAADDXLIYAAAAAAABzzWIIAAAAAAAw1yyGAAAAAAAAc81iCAAAAAAAMNcshgAAAAAAAHPt/wNU0dqVIIkudAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -83,16 +83,16 @@ } ], "source": [ - "endVeloP_found = ak.to_numpy(found[\"ideal_state_770_p\"])\n", + "endVeloP_found = ak.to_numpy(found[\"p_end_velo\"])\n", "trueP_found = ak.to_numpy(found[\"p\"])\n", "\n", - "endVeloP_lost = ak.to_numpy(lost[\"ideal_state_770_p\"])\n", + "endVeloP_lost = ak.to_numpy(lost[\"p_end_velo\"])\n", "trueP_lost = ak.to_numpy(lost[\"p\"])\n", "\n", - "endVeloP_notelectrons = ak.to_numpy(notelectrons[\"ideal_state_770_p\"])\n", + "endVeloP_notelectrons = ak.to_numpy(notelectrons[\"p_end_velo\"])\n", "trueP_notelectrons = ak.to_numpy(notelectrons[\"p\"])\n", "\n", - "stretch_factor = ak.num(trueP_lost, axis=0) / ak.num(trueP_found, axis=0)\n", + "stretch_factor = ak.num(trueP_notelectrons, axis=0) / ak.num(trueP_found, axis=0)\n", "\n", "nbins = 100\n", "vmax = 100\n", @@ -114,10 +114,10 @@ "ax0.set_title(f\"found P\")\n", "\n", "a1 = ax1.hist2d(\n", - " # trueP_notelectrons,\n", - " # endVeloP_notelectrons,\n", - " trueP_lost,\n", - " endVeloP_lost,\n", + " trueP_notelectrons,\n", + " endVeloP_notelectrons,\n", + " # trueP_lost,\n", + " # endVeloP_lost,\n", " density=False,\n", " bins=nbins,\n", " cmap=plt.cm.jet,\n", @@ -136,12 +136,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjgAAAHJCAYAAACIU0PXAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAABhQklEQVR4nO3df5Ac53kf+O8QECHSEDFYMtIxjimgl7w60ieK7FnwYisWTuKMZEWJExO7i5QvkngxMSN5VU7is3aEXOoIJi4PB0XnFMV74szSdbCU5I6YAVWxSqasGcqBYkUxsdOiJJvKFbEDUBWSlkXtDmFIJMjd7ftj2Y15n57pt3u6Z3Z+fD9VU9x3+u2332kMsS/6fd73Sdi2bYOIiIhojFyz0x0gIiIiihsHOERERDR2OMAhIiKiscMBDhEREY0dDnCIiIho7HCAQ0RERGOHAxwiIiIaOxzgEBER0djhAIeIhpZlWSiXyzvdDSIaQRzgEE0oy7KQz+cxNzeH6elpnDx5cqe75Go2m5ibm0MqlUKpVPKtW6/XkclkkEgkkEgksH//fkxPT2N6ehqZTAb5fB7NZnNAPSeiYZFgqgaiyWNZFu69916sr68DAPL5PFqtlnYwMWiJRAKmaaLRaASqCwCNRgOmaQIAqtUqjh07hlarhVqthnQ63df+EtHw2L3THSCiwSsUCpiamnLLxWJxB3sTr2Qy6f48OzsLAJibm8Pc3Jw7oCOi8ccpKqIJZFnWTnchdu0Dm3bOU5tWq8WpKqIJwgEO0QQpl8uYm5tDs9l041zm5uZQr9fdOq1WC7lcDvl8HplMBplMRjlerVaxf/9+JBIJd6BUr9cxNzeHRCKBubk5t51yuYxUKoVqtYp6vY5UKqXUaedc13nFFRO0trYWSztENGJsIpo4hmHYhmF43m80GnYymbQbjYb7XqlUsgHYxWLRfS+bzdoAlHqrq6s2AHt2dtYtz87O2gDsdDptLy4u2o1Gwz23vb3V1VU7mUzatVrNfa9YLNoAbNM0A32mZDJpA7BXV1eV98O2Q0TjgU9wiMh17NgxzMzMuEG6AJDNZmGaprIaqdN0UHtMDwAYhoGjR48CADKZDIrFIkzTdAOZa7WaWzefz2NmZkYJAl5cXOzpM7RaLQDbK7FOnjyJfD4P0zTx1FNP9dQeEY0mDnCICMD2gMCyLGVw48jlcgDQ8yqrTgMiZ+qo2WyiWq0ik8n01LbkLHufm5vDuXPnUCqV0Gg0usboENF44ioqIgLgH3g8MzMDAH0J0nXaNAwjlvZqtVpsbRHR6OITHCJSOFM87ZynH3IaKg7OAIfBwEQUJw5wiAgA3Kmp9hVTDmfQMz09Hft1nactQTbzIyIKigMcogm0trbmeWJiGAZM03SXkLdbWVlBMplENpsFANx4440A1Ckr5+dOT4D8ONNf5XK547lB23Pqhb0+EY0nDnCIyFWpVJBMJt2gYmB7wFAsFrG8vOxOVTlPe/L5POr1OsrlshuA7OSGAoJNOyWTSXfFVCqVQr1eR7PZRD6fB3B1NVRQnOoiIgDcB4dokrTvQwPAzmazyt4ztm3b6+vr9uzsrJ1Op+1sNmtns1llvxtHsVi0k8mknUwm7cXFRdu2t/fXcfa7aTQatmmaNgDbMAy7VqvZ6+vryvXb98IplUq2YRjunjWrq6tue3Jvm3a1Ws1Op9Num4ZhKO0S0WRisk0iIiIaO5yiIiIiorEzdPvgVKtVFAoFWJYFwzBQKpWU3U2B7f06CoUCDMNAq9VCJpNxswbvRB0iIqJJ12q1UCgUAADFYtFzfOC/c3d6jqxdqVRyYwJqtZo7f98+/+7ku2mPCTAMwy6VSjtSh4iIaNLVajU391w2m/Uc34nfuUM1wJGBgY1GwwZgVyoV9710Om2n02mlnpMMcCfqEBER0bZuA5yd+J07VDE4MrmeXJLaarWUJagOuY/GoOoQERGRv536nTtUAxypWq2iWCy6O52urKwA8OascQZAtVptoHWIiIjI3079zh26IGNHPp9HuVzG8vKy+56zU2q3rMDtO7AOok43L7/8Mr785S/j5ptvxlvf+tau9XSuvfZaXHvttT2fT0RE/fX666/j9ddf7/n81157DS+99BI+/OEP46abboqxZ6rvf//7ePnllyP3FwBuvvlm3HbbbYHr9/t3bjdDOcA5efIkms0mWq0W5ubmUCqVkM1msbq6CqB7wr9WqzXQOt18+ctfxv3339/1OBERUbtTp07hYx/7WF/a/v73v49b3/lOvBFTe295y1tw/vx53HLLLYHq9/t3bjehBjiXLl1yt1E3TRPvf//7Q18wCCcWp16vY25uDsViEdls1k30120rdsMwBlqnm5tvvhkA8NnPfhbvfve7u9aTPvKRj+ALX/iCWw7yBOfIkSM4c+ZM4Gv0ek4v512+fBmHDx/G2bNnsXfv3r72j/eh93MGda1B3odez+N9GNw5vd6HQfUv6DnyiYj8e7ybwxff/OG/fhso/Lr7e6MfXn75ZbwBYBbAFIDNKG0B+A9vvIGXX3458ACn379zuwk8wHnllVcwMzOjPCaanp5GrVbDO9/5ztAXDiKdTiObzbp5aJwP2G0kZxjGQOt040xLvfvd78Z73/vervWkn/qpnwpVHwCuu+46d46yn+f0ct6lS5cAAHfddRduuOGGvvaP96H3cwZ1rUHeh17P430Y3Dm93odB9a/XcwL/PS5mo6KEMwT1dgB/PWIbe3o4p9+/c7sJPMDJ5/NYXV1FOp1GMpmEZVk4f/48UqkUXn755dAXDurQoUPuB3OiqeVcnFNOpVIDrUNERBREoimyIv3sX775w/rA+rAbwFtiaCOsnfqdG3gVlTM19dWvfhWnT5/G+fPnsbKygq2tLfze7/1e6AsH1Ww23Z2Mk8kkTNP0RFPX63UAwPz8/EDrEBERjYpd2B6gRHnt6uG6O/U7N/AAxzAMHDhwQHnPNE0sLy+7y7uicAKKq9Wq+16z2UStVkOpVHLfW15edgdbjmKxiGKx6EZfD7IOERHRKHCe4ER5+T3B8QsE3onfuYGfNu3fv7/j++l0OpZN75LJJFqtFo4dO4ZSqYRMJgPDMDyjOdM00Wg0kM/nYRgGms0m8vk8stnsjtQhIiKadJZluQ8jTp8+jUwm44a0ADvzOzfwAKdSqeDGG29EOp1GOp12g8L27duHH/3oRz1dXAq6kY9pmqhUKkNTh4iIqF3iWfHGzybU8u53bP93az+wNZAuuVNUUdvoxDRNlEolZcalU51B/s4N9VnbO28YhjtCc5Z3UTQLCwtDe06U8wZxHd6H3s8Z9LUGdZ1h/x4N6jrjdh96vdYwnzMoOxVkvFMSbybH0pqamsL8/DxWV1fx1FNPXW0gsT0qTaVSmJ+fRzqdxl133QUAeOyxx/DAAw/E3+sh9/Wvf93d3yHssu9xcunSJezbtw+vvPJK6GWg44T3YRvvwzbeh23jfh+8T3BE2RkpbH0d2Orv7wvLspBKpfDPAUTd1OV5AL8FoNFo9LRtwSAFHowVi0UcO3bMLX/rW9/C448/jnq9DsuysLKygkajAWA7nmZmZgYrKysTOcAhIiIaNv2cohpGgT9r++AGAO6++27cfffdALY3AazX66jVam4EdK1Wc5/uEBERjbNb8efqGz8rH9k8oRY3Lr35w//Xry55TNoUVSx93bdvH44cOYIjR44AAC5cuIBarYZPf/rTcTQ/sj760Y/i+uuv73hsYWFhqOdqiYgoLksAHhbvOZHFVwbcl8nRl8HYwYMHkc1mJ/4Jzuc///mJjsEhIiIAWAAgc021P8GRg5/+cDbri9rGqOhrX+W0FhER0Tj4BajbmqwmDogaT4rye0TZevO/P4yvUxqTNkUVeCdjIiIiolExSoMxIiIi6tGkPcEZpb6OjGuvvVb576Tas2cPHnzwQezZs2enu7KjeB+28T5s433Yxvvg2P41PIjfF5O2TDzwRn8UnLOp0ihshERERHpyGfhqQi4D/4Yov02Uz4vyD9787/cBPNzX3xfO76T/C8BtAer/BwB/0OXY6wD+AmO20V83Fy9eRKlUQrPZxNTUFG699VYcO3ZsLHemJCIiGnd/781XJ88B+LUB9iWKSAOcRx55BPl8HvIh0G//9m/jsccewy//8i9H6hwRERHFY9KmqHr+rE899RQWFxdhmiZyuRxmZmaQTCbRarVw7tw5fOpTn8LBgwfdvFRERES0cxhkHFCxWESpVOq4183dd9+N+fl5HD9+HJ/73OcidZCIiGjQbtp6QSn/aJcm9YInxubtovyOGHpFYUQajPlt5JdMJqM0TURERDHiFFVAqVRKW6fZbPba/Fg4cuQIrrvuuo7HmIuKiGhSPAXgrHjvDfHf/uMUVUDr6+v49re/jXe/+92eYxcvXkQul5v4pzhnzpwZ+mV0RETUb/cC+BXx3sU3/7u9TJzi1/MA5+GHH4ZhGDh06JD7S7zVaqFer6PZbCKZTOLChQuxdZSIiKhffgkVpfyjm+ZEjec0LfyiKL8gyhfDdypmTLYZUDKZRL1ex7Fjx1AsFpVjpmmiUqlwLxwiIqIhwSmqEEzTRKPRwIULF2BZlvvewYMHY+kcERERUS9iGYwdPHiw46Dm0qVLfIpDRERDR05JfSkhp6Skuii/R5QtUf5LUb61S7s/1lw3PpO2iuqafjZeLpf72TwREREF5ExRRXmN5RTVoUOHQjduWRZ+8zd/M/R5REREFC/G4HRh27YbZxNUIpEI3SEiIiKiqAIPcNLpNJaXl3H33XcHbvzjH/94T50iIiKKUw7/Wil/KfGP1Qr7xQnr3xBvHBBlmZrhVVF+myirm77a9ocAbM90BNg3NxaTFoMT+LMePXo01OAGAHK5XOgOERERUfx27wLeEnFiZbcNYDOW7vRd4CDjboObS5cu4Wtf+5pbfuqpp9xy2AERERERURwiraL6xCc+gf379+MDH/iA+969996L1dVVHD9+PHLniIiIKB67dgG7d0d77RqhOaqep+M+/elPo1QqIZlMeoKJjx07hg984AP4vd/7Pfzqr/5q5E6OKibbJCLaGb+AmlL+k7eImBv8QC2uPymOv0OUL2qu6LcvzlMAfks5evXX5uuaduOz+xrgLQEGKI++AZS75AB9zY63T/3U8wCnWq2iWq3ivvvuw/z8vOd4JpPBww8/PNEDHCbbJCKi7WSb93Y5dhHAQ4PrSgAff8v2q5NvbQLveW2w/elVzwMcwzBw3333Aei8HPzcuXNoNpu994yIiIhis3v3dqBxpDZGaPeXSMk2HbatPrP61re+hWq1iunp6Z47RkREFJRMvfAnntQLp0T5PlGWaYXksm9/tn2nUk4kvihqvF3U/wQAZ5n4YJ7g7N4FvCXiOvFR2uiv5yDj48eP44Mf/CCeeeYZ9wnOxYsX8cgjj2BmZgaJRILLxImIiGhHBB6MPfPMM7jrrrvc8t13341CoYAHHngAlmWhWq0CuPo0J5/PM00DERHRsLgG0Xfq24qjI4MReIBz7NgxnDt3TnnPNE2srKzgwoULaDQauHDhAgzDQDqdxr59+2LvLBEREfUojq2Mx3GA02g0cOONN+L48ePIZrO44Yar85UHDx7EwYMH+9JBIiIi6fdxVCl/6a8/LmqIZeCeGBuZikG6JMp/JcpqTE0icVIcf5cof1fUd+JuXtT0I0a7MVEDnMAxOKZp4uGHH8b58+dx4MABHD16VNnBmIiIiGhYBB7gHD9+HMeOHcOjjz6KtbU1zM/PY3FxETfeeCMeeeQRXLokR7tEREQ0NJwpqiivEdrJOPAA58iRI57yysoKzp075z7V+eAHP4gvflEujSMiIqId5wQZR3lFSvA0WJGXtBuGgUcffRSPPvoozpw5g1/91V/FAw88gFwuh2w2iwMHDsTQTSIimmQfxbJS/sLPi5ibl+QswhOiLNPmnBflt2l6II//pea4vJ4sh9tnh8KLbc+exx57DMViEa+88gps28bDDz+M9fV1fO5zn4vrEiOHuaiIiAj4EoAz4j0nWndjcN2IYxXVCE1RRfqoly5dQqFQQLlcRqvVgm3bSCaT7kqrSV8qzlxUREQE/F0AB8R7zhOcFwGUB9ONOFZRjdBWxoG7+sQTT7i5p5555hkUCgVlcz/DMJDP53Hs2LH+9JSIiCbGu6Duu/ZnU+J3y7qckvp3onynKH9Hc8XOT9uDOyDKcln620XZmeJ6a8TrUjeBBziFQgFra2uoVCqo1+vujsXpdBr5fB733tstUyoRERHtuDh2Mh7HIONGo4FcLucObGZnZ1EsFrnBHxER0SiYsBicUGMx27axuLiI9fV1nD59eqgGN81mc6e7QEREREMi8FjOMAxYlqWkaOiHarWKQqEAy7JgmiaKxSLS6bSnnpPB3GGaJhqNhlu2LAuFQgGGYaDVaiGTyWB2dlY5J646REQUzUP4tFL+s8Q/1ZzxXVF+hyjrYm50y75lzIxc1i1TNzwtyv4xPba9CGD7d0wq9VnfurFhkHFnpVKp74ObkydPolarIZfLYXV1FSdPnkQmk0GtVlMGOeVyGdlsFtPT0+577cebzSZSqRQajYa7iml6ehpra2vIZrOx1iEiIhoJAWNwll7afnXy6gjlogo8wAkbRPzII49gdnY21EZ/586dQ61Wc8tHjx5FKpXyPMWpVCpKPSmXyyGdTitLtPP5vLv5YJx1iIiIRkLAGJyFn9l+dWL9FZCyYu1V3wQa4CwvL6NcDr5Ov9VqodlsYm1tDb/9278d6Jx6vY5isai8Z5omTNNU4muq1SpWVlYwNzeHTCbjGWi0Wq2Obc3MzADYfvozPz8fSx0OcoiIiIZToAHOzMwMcrlc6MYrlUrgAU6nOBuHYRjuz7VaDa1WC9VqFdVqFfl8HpVKxT1/ZWXFcw4A9ylMrVZzj0WtwwEOEVFvHoYaY3PiV/5PUeMbmvIPRFnG4MiyrC9jaGRMjoy5kTE6khqzY9uf8K2dSDz05k8vatqNEVdRed19992YnZ3F1taW+yoWiygWi8p77a/FxUXfaaSgms0m5ubm3HKpVIJt22g0Gshms27gr/OUx/lvMpns2l5cdXQuX76MS5cu9fy6cuWK9hpERLSTNgC8hu0B0dWX7u/37XNeA/D64LoaNZN4HEHKAxS4q3Kqptls+uaZyuVymJubw7lz57rW0alWqzAMo+OTEtM0USqVkMlkMDc35z7JWV1dBQBMTU11bLPVasVWR+fw4cPaOn4efPBBnDhxIlIbRETUT/8JwFnPu/v2/W+D7wopAg9wwu5502w2YVnRIpEKhQIqlYpvndnZWczOzrrXclZWra2tdaxvGEZsdXTOnj2Lu+66S1uvmz179vR8LhERDcIvAPg5AH9NefeVVx7wPWvfvsKbP/0FgFN96FcH3Mk4GNu28cd//Md43/ve5zl26dIl5HK5QIOAbvL5PJaXlwO1kclkUK/XAVwdeHR7wmIYRmx1dPbu3dv3pfVERKPgKH5fKZ9OyJgbGSMTNnfUraIsY3Z0MTfyuNwHpxtn3kY9f9++R0U9GdPj5KC6NuB1YjBhMTg9f9SHH34YhmHg0KFDyGQyMAwDa2traDQa7oqrUqnUU9vlchmZTCZUJm5ndZPzXxkj45RTqVRsdYiIiGg49fywKZlMYmVlBTfccAMWFxcxNzeHXC7nBgF/6lOfwgMP+D+i68TJUC5XVflNdzmbAzr9Mk3TE+DsPOGZn5+PrQ4REdHIcJ7gRHlNwhMcYHuaplKp4MKFC1hdXcWFCxdgGAZmZmawb9++0O3V63UUCgXkcjll351Go+E+MTl27BiOHj2KxcXtba6r1SqmpqaU9AnLy8tIpVJoNpvuVJKz6stZFRVXHSIi8voolpXy6Z8/JmpcEmVdzKZc9i2nqF7QHNelYpDH5ZSSrC+ntNT6TioGRyJxUtP+AOxC9AHKpAxwHAcPHuwYhPzII4/gN3/zNwO1YVkWMpkMAHTcc2d9fR3A9qqmQqGAWq0G0zSRyWQ8U2FOXqp8Pg/DMNBsNpHP55XVWHHVISIiouETaYDzyCOPoFardV1pZFlW4AGOaZqwbVtbL+jeOqZpaldgxVWHiIho6DHIOJijR49qf/HLjN9ERES0Q/o8wKlWq6jVakgmk25oh9xDz7IsFAoFGIbhbtTbHmISp54/aqVSQS6X893s7+Mf/3ivzRMR0Qj5p3hYKX9h6tNqhbdCkMu4ZUyKjHGRMTXnNefLmBn1fNu+XylfTZ3g8E/NYNsPas6X5DJ2Z1n8a5rzYtTHGJxqtYpCoYBGo+G+l8lkkM/n3UFOs9lEKpVCo9FwV0lPT09jbW2tL6EfPa+iMk1Tm59KjtyIiIho/JRKJXd7FUcmk3FXRgPb8bXpdFrZAiafz/eU6zKIngc4xWIRjz/+uG+d9pEcERER7aA+LhNfW1tzt1FxrK6uKpvm1ut1dzGRwxkUta+cjkvPU1StVguWZeGRRx7pumS6WCziueee6/USREREFJddwJUEcGWz9yYub3V+P5fLuTkoK5UKLMvC6dOn8dRTTwEAVlZWAHizADhPc2q1WuzTVD0PcAqFAizL8l3VNOlBxkeOHMF118l5420LCwtYWFgYcI+IiOIhY24+k/hfRQ25z41MxSDJ+jKVwvOifI8of1eU7xRl9emCPmZG5Y25kfvaXCeOt7f/9JuvTjZC9SOqggU81IfJlWw262YymJ6ehmEYuHDhgvsAxMkC0O2BiMwaEIeeBzjZbBb1eh1Hjx7tePxHP/pRXx45jZIzZ86ESjdBRETj6B54B2SOFwEM6HflLuD4PcBvRMg09MzLwOEnOh8rlUpYWVmBZVloNpuo1+vuCqnV1VUA23vZddIt72MUkZaJZzIZ3yzjhw4d6rV5IiIiitMuYM+1wJ4ITez1OTmTybiJtufm5tzpqtnZWUxPTwNA133zoiTn7qbnAc6+ffs6pmO4ePEipqamcMMNN+Duu++O1DkiIhoOvwR137MvveXTXWo6nhRluYxbTlnJVAyyvlzm/SGlnEhcFPVl/KdcNn5AlOX5cspJfWwhUzGEdXWKy7N+fiQ5K6GcOJoLFy7g4MGDOHbsGGZnZ5Vg4076McAJvIrqa1/7mvvys76+jve///247bbb8Gu/9muRO0hEREQx6OMqqtOnTyshGclkEsVi0V2Q5KyWkrE2TtnJNxmnwAOcdDqNfD7vjr4uXbrkeQHA3XffjZWVFRw4cMCTI4qIiIh2SB8HOFNTU56nM+l0GsD2YCeZTMI0Tc/CJGdp+fz8fNRP5xFqH5xz587hvvvuA7C9pOv9738/9u/fj1Qq5Qko5uCGiIhoMuRyOZw+fVoZ5FSrVZim6U4/LS8vo16vK09xisUiisVi19VVUQSOwZHzY0eOHMGRI0dwzTXXoFar4cCBA576fgHIREQ0xP5U3ebjS8dEMuQNmWpBuijKMsZGpkKQW2rIZd7q9WRMjLe9d/n0DdAvW5cxQOoy9URCLmuX9YOlerAsC6nUZzV9iUkfUzUsLi4imUxibm7OnapqtVruPjjA9p43jUYD+XwehmGg2Wwin8/3JU0DEGKAs3///o7vG4bhGdzoziEiIqIB63OyzWw2qx2smKapTdQdl6gfdeI38yMiIhoJfR7gDJuec1ERERERDavAY7lms4nnn38etm17jnV6f319HZZlRe8hERH13e9D3ZX+/r/p/btedasoy5iYtCjXRVkXI6PuYyP3nUkkPqc5X8bIyF3ldTFEct+dB7vUc/ojUz/IfXf8Y3IGYsKe4AT+qOvr61034unHBj3jgLmoiIgIOAvgKeWdO+54HADw6qsyOLmP+hhkPIxCjeU6Pb3xM+nxOcxFRUREwGEAtyvvPPts+yqq+De5oxADHNM03XTnQX3gAx8I3SEiIhoAsQz8/m/o/gH7HVE+oKn/RVGW2cHPi/IvivJXlFIicUoc10353ODbni7Vgpxy8mYPl1N06pSUbX9CnH+qS3sv+PYjVpyi6uz48eOhG3dyUxAREdEOm7ABTuBVVEeOHAndeC/nEBEREUUVeR8cIiIiGgEMMiYionHz4yvqb6a9/1DE3PxIniFjbuS2HzKGRqZikGV12bYuRsW7zPp5UZYrVOVqJP9UDN6YGnk9XUzN5zTHZfsqJwZo4KkaJmiKigMcIiIici39x+1XJ6++McieRMMBDhER0SQI+ARnIb396sR6Hkj9y1h71Tcc4BAREU2CaxB9immEEjxxgENENIY+iD9Qyl89tKlWkDE366fEG3IfGRlTI8lNTZ/0bS+RkMdlDM1fibIu9YEuZkbGxMh9efx3FPae718/+D47L/rWi9VuRP+tP0KjhhEaixEREREFM0JjsdHDXFRERLS0tISlpSXx7g/f/O/G4DrCVVQUF+aiIiKiTv+gVaeoyoPpCAc4REQ0av4AH1TKX536I7XC+nOaFm4TZbmPjCzr9p2R7dVF+Z2iLGNuZIyMety2H1TK3txRallP/TyyfUnug+M97h+z47S/vQ/OgAY4E4YDHCIioknAVVREREQ0diZsFdUIdZWIiBzn8C6l/Pf+2XfVCp4pKXHcM6Ukd3b7hii/S5TlMnJZX6ZW0KVeUKesbPt+pSynhPRTUOoCD7ls23t+5wUhV+ufEu3JZehhp8So3zjAISIimgQMMiYiIqKxM2ExOCPUVSIiIqJg+ASHiGgE/PiK+k/vew6K1AsvyTNkzM0lUX6PKH9R0wNdzI1c1q2LuZExL+px3TJs7/m6VAsyRkaX+kGS/Y9mR1I1cIqKiIiIxg5XUREREdHYYQwOERER0WjjE5w+YrJNIurZkwmluPdJWz3+0nc0DbxDlGXMzROiLGNY5L434a5n2/cpZV3qAm9MjUzNIPex0cXoqHSpHeT15XH9+X4xPU/j9tsvKEe/970fvfnTG5073A+MwaG4MNkmEREB9+DZZ7+svHN1wPcCgM8OphsBY3CWTgNLlc7HXr0Sa4/6igMcIiIici3Mb786sf4rkPqHg+1PrzjAISIaFuevTksl/qXtUxEA7lSL8m/zDTkFJaec5BTWAVGWy8LPa/qjpn5IJJ7U1JdTOipdKgTvlJGcAoM4rk5p6aec5Pn+7ctl5sHbf03Tbow4RUVERERjh6uoiIiIiEbb0D3BqVarKBQKsCwLpmmiWCwinVaz3FqWhUKhAMMw0Gq1kMlkMDs7u2N1iIiIhh6nqHbOyZMnUavVkMvlsLq6ipMnTyKTyaBWq7mDnGaziVQqhUaj4a5Qmp6extraGrLZ7MDrEBH17E/VpeCJP2qLuzkn6m7IZdoviONy2fUPRFnG5Nwmys+Jsmwv7LLuDynlREKmjvgrUb4V/tSYHRkT411GLmNmdKkYOm/pcZVMReGfGsLrnaIcb+qHQCZsJ+OhmqI6d+4carUastksisUiGo0GAKBYLLp1crkc0um0svw6n88jl8vtSB0iIiIaPkMzwKnX68pABgBM04Rpmmg2mwCAVquFer2OTCaj1JuZmQEAlMvlgdYhIiIaGU6QcZTX0Iwa9IbmYZOMs2lnGAYAYGVlRSk7nCcstVrNPTaIOpymIiKikcEYnOHSbDbdKSHnSU4ymexad5B1dC5fvoxLly5p63WzZ88e7Nmzp+fziWjInBcxN/9O7HXzb2TcTDux7w0sUZYxNfLvHhmDIstyXxq5740uRkWNSdHHyMhUC5fEcd2+M2pMjD4VhP++O/6pFjqVnfuxAWADr7zyT5Sj3r/7vy/KCfHfAeAAZ3hUq1UYhuE+KVldXQUATE1NdazfarUGWkfn8OHD2jp+HnzwQZw4cSJSG0RE1E9/DKCOffse1NakwRrqAU6hUEClcjUhxvT0NABgbW2tY33DMAZaR+fs2bO46667tPW64dMbIqJh9z4Av+B5giPt2/eZLkdeBFCKt0vdTNgqqqHtaj6fx/LysjKQcH7u9vTEMIyB1tHZu3cvbrhBbndORJPix1fU5/l77xFTUv9DlNZlIl85ZSVTMehSL8jj8ny5zFtO6ahTQt5UC3KZumxf7Y9u2bdsX9KnXvDPJu6lHpf987YvU0P8H12ur0vJER/7GsCOOMVkj1CQ8VB2tVwuI5PJeDJxOyuYZPyLU06lUgOtQ0RERMNp6AY41WoVgHdVlWVZSCaTME0TtVpNOVav1wEA8/PzA61DREQ0KjZ3AZu7I74YZNyber2OQqGAXC6n7DPTaDSQSqVgmiaWl5eRSqXQbDbdaaJisYhiseiueBpkHSIiolGw9eYAJ2obo2JoBjiWZbmb6nXaKXh9fR3A9j40jUYD+XwehmGg2Wwin88re9IMsg4RkcMTc/PMplphXSwd/uY3RAvtcTAyxkXG2FwUZRlDIpdJy5gbmXpALmuW9SV12bQ+VYKO7I/kvwxdn0rCP1WDt//+MTw63hikh8Tx7VVXlmUhleLGsf0wNAMc0zRh28GCrUzTVFZX7XQdIiKiYbe5K4GNXfp9d0qP2ig/2vn38Wuvxd2r/hmaAQ4RERH1z+auXdjcrQ+9feCT269OnrG2cPiejZh71h9DF2RMREREFBWf4BAR9cgTc/M/ipib88+JM+TeL35kfI48VxdzI/e1kTEuf6Up++9zI+uH3VfGG/NySpTlvjcP+h4H3iXq3xeqf7qYId319akodPvs9N/Wrl3Y3BXtucbWrgS201MMPw5wiIiIJsAmrsFmxGRSm/oqQ4MDnD46cuQIrruu86h9YWEBCwsLA+4REREN3lls56y66o47TgEAXn1VPhnrn03swgYHOBSHM2fOeHZjJqIRVlJXoOw9Llaa/H1R37PSWv4y+5Aof8f9ybbvV454p1juEWWZSkGS2cjrovwuUZaZzeU/1uSUluSfzTt8tnA55eO/DD58Kgb/Zeb6KSm/ZeW3v/m66nvfc9p/AcBnNX2jXnCAQ0RENAG2sAubEX/tb8XUl0HgAIeIiGgCxBODMzpDHC4TJyIiorHDJzhERN1U1ZibxI9FzM26WAb+ldtEA3Jpt4x7kekRrqYTSCRkjIuMublVKdm2Gs+TSDwp6stl5zImRcbw6GJu5LLzW0VZbU+XukCfWkEuW5dlWV9tT8bM6IRN1eBdRi7Pf2eXM38S6jpRbE9RRXuCszVCT3A4wCEiIpoAWzFMUW2N0DoqTlERERHR2OETHCIiogmwgWsi74OzEeK5SLPZRLVaBQBks1kkk0kA2xnUC4UCDMNAq9VCJpPB7OxspH51wgEOEZEjLWJu3itibj4jTxDpEF6Se7UcEGW5MY6MY2nfi0buQyOpMTWJhIyhkefLmBVJxg99R5TVGBxvTI3c10bue6OLafHfN8cbA6TW18XAyLKsL0VtT3e+c9yyLKRS4eJ9erWF3TEsE9dPUTWbTeTzebRaLZRKJRiGoRxLpVJoNBruPnHT09NYW1tDNpuN1DeJU1REREQUi+0BWwpTU1Oo1WrK4AYAcrkc0um0sgluPp9HLpeLvS8c4BAREU0AJ8g4ymvLZ9jQarVw7733wjAMlEqljsfr9ToymYzy/szMDACgXC7H+nk5wCEiIpoAmzEMcDZ9hg3OtFSxWOx4fGVlBQA8T3Wcpzm1Wi2mT7qNMTh9xGSbREPuayLm5hYRc/MVUX9dNiD//5b5niS5V4zcB6c9bkbuoaPLNSXz3sl4HxlDI3MpndK0r9LnZvKPyfHuW6OSMT7e6/vHxHj/bNSYHV3/vf2RMTX+ubTU/jyN22+/oBy/447Ht3s14GSbP7mSwOtXbH3lLv7qcvdjzhOYWq2GfD6PZrOJmZkZNw6n2WwCgBtsLDnH48IBTh8x2SYREQH34Nlnv9zxiBOzMiinCj/EYw/9MPZ2LcsCsP00JpfLoVgsotlsIpPJYHp6Guvr61hdXQUATE1NdWyj1WrF2icOcIiIiCbAFnbhI8dvxj/4jf+u5zaee+ZVfOKwfDp49elLLpdzp6CcWJxMJoNCoYDp6WkAwNraWse25dRVVBzgENHk+LCYkvqfxKP6l0X9b8oG5NJr+Re9nHISy8hFfe+0zhM+56r0U0KSbtm2TCUgl2VL6nSb9/py6kVdEq9fhq37PJ2n/7tf33/KSidq6oZhsIld2LXnLdi1p/c2rt270fH9btNO6XQaANynOUD3JzVxD3AYZExERESROCuhnGkoaWpqyq0jY22cctxTdRzgEBERTYB+LhNPJpNIp9Oo19WEss7TmlQqhWQyCdM0PaulnHPm5+dj/bwc4BAREU2Afi8TLxaLsCxLGeSUy2WYpunuUry8vIx6va48xSkWiygWi12nuXrFGBwiGl+fEDE3/2ZLPf5BUd8TOylTL/wvovwuUa6L8odE+Tm1P0rMDaDGichUCWoMi35Zt1ySLj+cjLnxX7btbU8uW9elglBjerzLtP1jcmT7umXkUiKh/ll6Y5j8l5nrYmrCpoK4+vlf8K03SkzTRKPRQD6fR6VSQTKZRKvVQqPR6FjHWTqez+djT9MAcIBDREQ0ETaxK3KyzU3N+Z2moDrVqVQqkfoRBAc4REREE2ALu2JIthltgDRIjMEhIiKiscMnOEQ0Pn5OxNzcLva5mRH11+W+NdJ7RFnug3ObKMv2nhNlmX7hoii3x6no9mmRMS9yn5n7fM/W7TPjjVGR8Ugyhud5Ufbfd0YfcyPP99+XJ+zn8R7X9SeabjE62zsZfzbWa3XjBBlHbWNUcIDTR8xFRURES0tLAH5XeW8nclFtvbkSKmobo4IDnD5iLioiIlpYWMAnP6luk/3ss+1PcAaTi2oT18QQZMwnOERE/VcQU1IJMSX1BV0DMh2CnIKSS3jlUmm5zFv+a1zXvtTevpzukm3rpmx0qRj86ado5LJt/ykefeoC/2Xg4afU/Psfvn/+53uPB802/mKo61JwHOAQERFNgM0YVlFFneIaJA5wiIiIJsCkxeCMzmQaERERUUB8gkNEI+O5hBpz89//nIi5+aaMW5ExMPK4TK0gyWXdXxRlmarhgKY9SaZH8EuX4L/sWpdaIGzqA12Mijyua18Xk6JfFq/ypl7wT90Q9vN4z9ellpCf722i3HmZ/HaQcdn32nHhMnEiIiIaO4NI1TBMOMAhIiIiV33pOXxtabXjsddf3Rxwb3rHAQ4REdEECJqL6n0Lt+N9C7d3PPa8tYZ/kfpK3F3rCw5wiGhoPSRibk48JGJuqvIMuc+MLJ8XZV1ci4yjkOWfFmX5F79sT5ZlDE97f2TfdX1TP4t+Hxv/fXS8MTRhUxeo8US6fWZkDIs35sV/nxtvTE64GBtv/VOixvPieLh9dLrHLA1uH5xJi8EZnZ4SERERBcQnOH3EXFRERNQpF9VVGwPrx6Ttg8MBTh8xFxVROJeuE1NSS2JK6rfECS/JFmR2b5nNW5cd/Lt+3QNwpyjLZeO/LMrfUEq6pdhqOgWZnVtHpmLwT81g2/eLvshs4XIKS/5jTU6RhZ2SklNKuiko3TLzzv+Y7NafROIJcfw+Ub7ftz/eKUF5/+T9+KGo73yeFwAMJpv4VgxTVFsjNPHDAQ4REdEE2IhhmXjU8wdpdIZiRERERAHxCQ4REdEECLpMXNfGqOAAh4h2zifUmJt9x3UxNzLVgm4ptfQNUb5VlGUch7qsXMZpJBIyDkVdJu6NKzmluV64dAUqvzQP3rb1y75lDI/sm3+MTvhl2eGWeetTR8iYnc6pErrRxfx4/2z963db9r6dqmEwMThcJj5ims3mTneBiIiIhsxQPcFptVooFAoAgGKx2LFOQmz8ZZomGo2GW7YsC4VCAYZhoNVqIZPJYHZ2VjknrjpERESjgsvEd0i9XkepVEK1WkU2m+1Yp1wuI5vNYnp62n0vnU67PzebTaRSKTQaDXd59vT0NNbW1tw246pDREQ0SjZxTQzJNkdn4mdoBjjpdBrpdNrzhKZdpVJBrVbrejyXyyGdTit7z+TzeeRyOXdgElcdIgrPk3rhd0TMzSlxgoy52X+DWl6vixPkPjdPiLKMGxHt4aIoH1BKicST4riMAVJjerz1JRkD1F6WaSUkeW1Jxveo++p4Y1hkDEnYfXj896GRvPFIuuNv71QtMH3qBl08lG7fG//6MmaH+m9khmLVahUrKyuYm5tDuVz2HG+1WqjX68hkMsr7MzMzALaf/sRVh4iIaNRsvrmKKtprdKaoRmaAU6vV0Gq1UK1WkcvlsH//ftTrV//1trKyAgAwDEM5z3kKU6vVYqtDREQ0apwYnCgvxuD0QalUQqlUgmVZKJVKKJfLyGQyWF1dhWEY7mqqZDLZ8fxmsxlbnaAuX76MS5fkstbg9uzZgz179vR8PhER9dsb2M4n9Zp4X52O7fa74PLly33pFY3QAMdhmiZKpRIymQzm5uaQz+dRqVSwuroKAJiamup4XqvViq1OUIcPHw5ct5MHH3wQJ06ciNQG0U7yxNysbqkV/r444WVRfpeIkdGlivLEpRzQ1Nf9A0ReUMaByL1n/Pei0e+d0n49XW4l2ZZ/LiTZd28Min+Miy6GJHyuKJmrKdzn0e2boxd1DyKnP38M4Ky29r59YfsXP+aiGhGzs7OYnZ2FZVkA4K6sWltb61jfMIzY6gR19uxZ3HXXXYHrS3x6Q0Q07H4BwM953n3lleNKed++z4gazoDqL+CNru+PoBv9WUtPw1p6uuOxjVcHl/08qpEd4ABAJpNx43CcgUe3JyyGYcRWJ6i9e/fihhvkKg0iIhofu9HpV6n37/63irKzgvDaPvSps82AyTbvXPg53LngHbQBwA+sF/FvU/Lp2nAa6QEOcHV1k/NfGSPjlFOpVGx1iKiL/11MSX1Zk3rhuzJ1gpgmeUle4DZRfpcoy/bkNI2sL5dpyykpmYrBf9rHu+xcXeodfhqnnW4KRfbNf0rISy6h9xc2dULYKSDb/oTmerrj0VI96FM56NrrnJpB2k7VwNW5/TA6k2kd1Go15HI5ANtBwaZpelY5OU945ufnY6tDREQ0arZiWCY+SquohmqA021aaHuEm8LJk1dHxNVqFVNTU0r6hOXlZdTrdeXpS7FYRLFYdFdFxVWHiIholDgxONFeQzVs8DU0U1TO8m8AOH36NDKZDNLpNJLJJAzDwNTUFAqFAmq1GkzTRCaTces7nLxU+XzeXTqez+eV3YfjqkNERETDa2gGOM7ybzloAbann4JusGeaJiqVykDqEE26k2IZeD4tYm7kQoz6d8Qbcpm2LF+UDYiyTM3wIVGWqRJ+WpRlOgQZoyM/gNx+/36l7F3aLNuTcSjy+u3HZQyN2pb3WpK8luyLXFIvY3DCxczo44tU4WNWdKkaZCqFqP3RpXLQtSeXvcv2HC+GajcKJtskIiKisTNpyTZHp6dEREREAfEJDhER0QRwVkJFbWNUjE5PiWjHeVIvnBUxN/dqGrj1TrV8/s7O9VzPifIXNfWfEGUZo/MVUZZxJuHiLLxxHmH3qnmnKD/vc66M15F79Oj67hfvE2TfFxkjo6svUyl8oktNh/w8kkzV4H/vw+5jI2N8ou6TI3WrP8h9cJiqgWJz5MgRXHdd5790FhYWsLCwMOAeERHRoC0tLWFpaanjsVdfDZsDi4LiAKePzpw5A9M0d7obRES0g/z+Qevs8zYIQXNR6doYFRzgEFFXnimpvyumpB4VJ2zIVAli2uH8O8RxK2SPflGUXxBl2b5c+ixTM8hl6fJf03JpspxCksd10yyyvu567eT0lryWri2ZvTvssmi1ff0ybP8nE0FTGQRvXy4T959S0i1TH3Rqh0HgMnEiIiIaO1wmTkRERDTi+ASHiIhoAmy+mWwzahujggMcInLJmJtHfvxDtYIMYXlJxrDoYlxk+QZRlnEjt4myjPuQ1/su/Nj2fUo5kTglasi4Exn3ouN/vnf7/u5xKGFjQLxpJPyXZevbf0Icl/dOF7OjLoHX1femntDFDIVdoq8Tbpm5LjVE+Jii/pu0GBxOUREREdHY4RMcIiKiCRB0mfiFpa/g4tIfdW7j1dfj7lbfcIBDREQ0ATaxK9Aqqp9Z+DB+ZuHDHY+9YjXxn1OfirtrfcEBDtEEkzE3VftppXz5H92kniBCcrBbxNBsyDgIGRPzLlGWqRSe7NDLdnIfHJl+QPqBUvLGeej2yZGfR917Rsa5hI1r8e4tc7V/3nNl3/1TM3hjXiSZJkJS46XC7pMTNXVC+Jgj//q6GJn+72PTLWZH7uVEceEAh4iIaAJsxbCKapSCjDnA6SPmoiIiou08VL/T5egbA+sHUzVQbJiLioaNJ/XC74jUC1PiBJkiZ0NOk8hs4HKZt0ydIJdd10X5gCj/e0378h8QcgpMLkuX5BSVbkpNnRLzLlV+uzgup9zklJqcJrp6f/TLoLufu003hSSzc/tPaemmzHTLonWpHcKmQpDX97avSzURdkpM/tmGS1Vh2z/oWGuQuai4TJyIiIhoxPEJDhER0QSYtFxUHOAQERFNAKZqIKKx4Ym5OStibv6BOOFvifKXviPekNv/yxiTt8GfjIm5T5TlMmpdnElYuvN1S6fl55MxPLr21TgO275fKbcvI9elRvCeK2NidEvYZdoI/xgc/bJzWT9c6gL99cOmcgjb37AxOar+LzOnsDjAISIimgCTFmTMAQ4REdEE2IphmfjWCMXgjE5PiYiIiALiExyiMSJjbh6zn1Mr/IqmgS/JNyxRljEncp+nb4iyfzoB4PdFWRfDozsu93rRXV/uqyPJvUsOiPJPi7L6+b1xMCdFWcYcnW87Fi4mJGzMiP583T4v/u2FvV7YGBb9cf99cPodAzOMMTebMUxRhTm/Xq9jbm4O6+vryvuWZaFQKMAwDLRaLWQyGczOzkbqVycc4BAREU2AQS8Tz+VynveazSZSqRQajYa7Ee709DTW1taQzWYj9U3iFBURERHFKp/PwzAMz/u5XA7pdFrZ5T+fz3ccDEXFJzh9xFxU1G+eZeD/RSwD/xfihHOiLLODe5Z93y/KYsrLk3pAZuOWU1YH5AU15JSTnCLTpYaQU0wy9YJMzRB2CuyLvv3RL1WWfz+8rcvPnZZdh5vyiLqM2kveC0mXKsF/GXn41BGyvv+UVPQpOv/pz/b2lpaWcMcdd3Ss9+qruvsYn0Htg1Ov13HjjTfCNE2srKy477daLdTrdRSLRaX+zMwMAKBcLsf6FIcDnD5iLioiIvL7B+045qIqlUqoVCrI5/PK+85gRz7ZcX5P1mo1DnCIiIgonC1cg40rm7CvvN5zGxuXX/M9ns/nPU9oHM1mEwCQTCZ9j8eFAxwiIqIJsV5YxvpDclfoeFiWhRtvvLFj7A0ArK6uAgCmpqY6Hm+1WrH2hwMcohGiXQb+S+KE72ka3JAxMu9Ri/JviA0ZLyBjXGQ5renADZrzZYyPJFMjyLLsr64syZicsP2RMULyuIwButof/bJp/xiWqMu+veS9UtNaeFNH6GJo/FM36GJ4vO2FXWZ+nTgu74/8s/f/7gzjsnBpA9fgbcc/jr2/8Y96buP1Z/4rfnD4Ix2PFQoFVCqVrudOT08DANbW1joe7zYw6hUHOERERBNgC7uxted6YM/1Pbdh7+0ciJ/P55HJZJRpJudn57/OAKbbkxoOcIiIiGio1Ot1nDzZ+Snh9PQ0TNPEU089BcAba+OU4w625j44REREE8DJRRXl1S0XVaPRgG3bymtxcRHJZBK2baPRaCCZTMI0TdRqNeXcer0OAJifn4/18/IJDtEQkzE3dfurSvm//TOx78xF0cD576jl/XeKCnJfG9Hehm6fGN2+MzLGR5IxOJIu9YJ/XIg35kUVdi8Vb0yN7vqSer43lUP3uJXwqRNk/XBpLHQxMrKviYQauBo+dYSuv/71dfvo6GKS9DFB4fS7/V5s4hpcM8CdjDtZXl5GKpVCs9l0p6SKxSKKxWLX1VW94gCHiIiIBsI0TTQaDXen42aziXw+H3uaBoADHCIioomwtbULm1sRN/oLcb7zZEYyTdN3tVVcOMAhIiKaAJub1wAbEaeoNkcndJcDHKIh0x5384f2WeXY07/0XrXyilrES5fEGyLmZl0eF/veeHJRyRgbNabHG0PyhKiv2+dGR8a0yLgMmftK7lMj68v8TnLDM10Mj39Mj34fHrn3ioxLeXvbMV3MTdjcTvKz+n+W8LmYZJ4wf/pcWOHilcLn1vK/f7r6un1ugufWelFzXeoVBzh9xGSbRES0tLQE4He7HN0YWD82N3YBGxGTbUZ8AjRIHOD0EZNtEhHRwsICPvnJl7scfRFAeSD92NrcFXmKamuTAxwiCkguBT/xX+yrBbmq+++IspwBeemieENOG8hl3vIJo5y2kFNUqkTilKZD8nzd9eQybDnF9bwo66ZF1Ot5pznktE3YVA5SuGXtfkupw6ce8D8edtl22GXi+mXn4a4fdsorPPndiLaMW38/uy1Tf2uk64axuXkN7MgDnNGJwRmdnhIREREFxCc4REREE2BzYxe23oj2BCfqE6BB4gCHiIhoAthbu2BvRvy1H3EfnUEaqgFOq9VCoVAAgI6bA1mWhUKhAMMw0Gq1kMlkMDs7u2N1iHrhibn5f221wr9u+/mAOPlRUV4/Jd74kCi/oBb3i2Xh63JZuIiB2S3a25DX08WcpEVZpm6QMTqyPbms3D/OwxtjpMZxeGOGVPoYHUkX4yRjjOQycf/+qHXlMnBdjM5JUZaf5e3iuH/Mjpd/fFH0VAX+8U+6mJ6oqRnC3g9df7q1Z1kWUqnP+rZNvRmaAU69XkepVEK1Wu24ZXOz2UQqlUKj0XBXJk1PT2Ntbc2tP8g6REREI2Uj+kZ/2Bid0N2h6Wk6nfbdujmXyyGdTivLrvP5PHK53I7UISIiGinOMnHd6/9+FLj3zs6vjx/d6U8R2NAMcPy0Wi3U63VkMhnl/ZmZGQBAuVweaB0iIqKx9ZEF4I/+vPNrqbrTvQtsaKao/KysbO9H76RWdzhPWGq1mntsEHU4TUVhyJibR378Q7XCA+KE/8evNRnDcp8oy31jLqpFT8yOJGJiNmSMjty4UqZGkGUZNPSLovwVTX8kmZrhu5rj/nEiMkYm7N4x4fd2kTE63eNMwqZekPFD+lQNMn5IxuTI1AXRYmK8/Peh0aVOiD/mJlyMk44+RurUmz9djHSdUDYTwEZCX0/XxogYiQFOs9kEACSTya7HB1knqMuXL+PSJZn7J7g9e/Zgz549PZ9PRET9deXKFVy5cqWHM50BYy/n9mgT0TNDbMbRkcEYiQHO6uoqAGBqaqrj8VarNdA6QR0+fDhw3U4efPBBnDhxIlIbRETUP4VCAQ89FDbRJw3CSAxwpqenAQBra2sdjxuGMdA6QZ09exZ33XVX4PoSn96MJjkl9ax9Sin/5Adi2uSAaKB9luWiOLYhs3/LZdR1UZa5HnRPFOUUlJxiepco+6dy8E4RySkp2Z6cctIdl+3rjqtTRLppjbDTILrryWkh/2kZXbbrcMf1U0i6Jf/hppSiT/H4Z+PWfx6Z9kMV33TkJoBP45VXjvteb9++glJ26j/zzDOR/zEcGJ/gDB9nUNHt6YlhGAOtE9TevXtxww0yJoKIiMbHbgC7A/xdr+accurv3bu3P93qZAPRBziDS34e2UgMcJwVTDL+xSmnUqmB1iEiIho5GwDeiKGNETESy8STySRM00StVlPer9e3H8fPz88PtA4RERENt6F6guMXwLu8vIxUKoVms+lOExWLRRSLRXfF0yDrEDk8qRdWt9QKGbGs8s9FAz8ryudlXE27J0RZLhOXy6TlUmD5GF3GKchl3jIOQx6XZIyPrC9jUiTZfxkXosbk2LaaSkK/tDncUmhv3IVcau3/ebypH4LH+Hiv9Q5RV/7Zq+T54WNO/GNgvDEv/mk0osa8RF2yH35ZebjUDDrd+/diqHYi2UL0GJotfZVhMTQDHMuyUCqVAACnT59GJpNBOp12BxSmaaLRaCCfz8MwDDSbTeTzeWVPmkHWISIiGikMMt4ZpmmiVCq5g5xudfzSOQy6DhEREQ2noRngEBERUR9xFRUR+dHG3HxGxNz8gmig/pxafuk2UaE9bkXGeKQ1vfuiKMu4CLldvYzzOCDK/vu4ePedkTE9ct8e8dnxtOZ8Sf083jgV/3QC3n17/rJjravtyzgT3b48uvPlXjLd40b0e+74X0ufKiDc5nRhY07Ctu89P1x8lKSPyQmbykG3z476XYq6D1BfTNgU1UisoiIiIiIKg09wiIiIJsGEPcHhAKePjhw5guuu67x0cmFhAQsLCwPuEfVCTkm9aH9GrfCHYkpKzpr8z7JFMSV1szj8Uvu0kC61gVxSLo/LZduyc3IKSS7rllNSchm335J2wLbV9hMJmQ1dfczvXVYt+yuXuevSC0i6KTX/KSvv/XmnKD+vlKJk2A47hRJ2mbaXbgm95D9lFHaKLOqUTthl6/rpTFW0ZepP4/bbL4gWf/jmfwcY1MIBDsXlzJkzME2Z24eIiCbLPXj22S8r76j74JQH3qNJwAEOERHRJOATHCIiIho7QXNR/dES8NWlzsdeDze1t5M4wCESZMxN1VaXMv/ZvzqknnBKNCAOo6654EsyjqU9dkDG1MgYmIuiLGNU5LJoGXMjOydjVGQcg4zpkTErMo5DxtBIaoyPN+5DLlNXY2C86QR0qRrk5/Hvvy6mRgqfHsBv6bHaN10MTdhl5d7zdfFP/sugwy6j1okeo6NLuxHuz0qKGjPknG9ZFlKpAU1RbSLYE5j0wvarkwsW8M9HI+k0l4kTERHR2OETHCIioknAGBwiIiIaOxzgEE0WGXPzrH1KKT+Ax5TyP3lSBtkI3/yOeEPuJaPbu6Y9DkYXM3LA51zAG3PzqCjLGBUZNyGvr9vn5Qlx/D5x/JRoT8YMyX1mdHu76GJ2ZFl3P5+HH32chn+qiTBxHvo0DzL+6JSoHy4Y1HsvdZ9F7tPjHwPkPa6Lz5LX8793ccXE9EofbxV2XyOKigMcIiKiScAnOERERDR2JiybOFdRERER0djhExyaODLmpm5/VSn/yT/LKOXT//FjagPfFA3+nLzCnaIsYm52i7iYjSdF/fZYiw+JY7KujLOQMScy3kfuo6Pyxsz4X897/Lw4LuNI/OKNesndJMm4EXl/5N4oMo4l2l4uur1kvJ/vlE/7/jE33mvf73tcFwPijSHRtaeLofGPAZL3yns83pid8PV1MU/x5tIaCE5RUVyYbJOIiJaWlgD8jvLeHXecAgC8+uoAdwbmAIfiwmSbRES0sLCAT37yx8p7zz67/URoeyfj0dgZeNRwgENjT05J/Wf7PyjlP2mm1RP+TDRwTrb4DbX4TTntIo7jp9Wi519Qcql0+zSTXHIu2tKmUpBlSU45PSGOy/PlkvenRVneC3m+nDKTqR3kUuV3KiU5beKd4vFf5i3vV/gpMJV32kSmxtDR9bf9WuH66p0ykX/W4ZY1h112rqP/POp3QzelFVXYNBy640M5ZRU0F5WujRHBAQ4REdEkCJqLStfGiOAAh4iIaBJMWAwOl4kTERHR2OETHBo7MubmffY9Svkx3KGe8M/V+p6V2BsyjkSmP5DHZUyNLk5Gxuy0L+XWxdBIMqZDxsRI6rJnXZyDLkZGxth4l03LmytTS/gv644eN6JbRi5jjOSycLl0WH4+/6XGYZYie+vKey37rvZVdy3vvfVfht3vVAbe+idFWRezI+9luP7q2o8aozMUqRkm7AkOBzhERESTYMIGOJyiIiIiorHDJzhERESTIOgy8W8tbb86tjHAjQkj4gCHRp6MuXnVPqGUF/C3lfJ/+3mRruCnRIN/TZRfuijekHud6GJ05N4vsqyr70eeK8m+yb6r9yL8vjKSGsPijYn5RaVk22oqCm99f7qYm/CpH2SMjhT2L3f//kjt/YuetiJcX8Lu8yLJ9qLHrIQ7P+5UCrq0GnJPJt39HIp9cYIuE79zYfvVyQ8s4N+PxsaEnKIiIiKiscMnOH3EXFRERAQ8jTvuuKPjEeai6h8OcPqIuaj6Q05JnThrqxV+XZzwsigfEOWLovySvKI8QS4DPy/K8i8sef4Loiy/I+3TSrJtmQ1cLjGXU1AXNWVJLpOWUzZyKe79Stk7ZSTPl9nGZf9V+mXrcmmzXPos++Ofzdy7LNx/WXnYKS9dRm+/unpyGbmcXoyWpkI3BRO9PbksXGZi/4Qo+0/5xD0lpMuu7u8ePPvslzseGWguqgkb4HCKioiIiMYOn+AQERFNAibbJCIiorHDZJtEw0WXeuHEH4oTZkX5X4ryz4jyZV0PZJyIjMGRS7HfJspPaM63RDnMMnEZ7yPPlUHuMsZE5V1qK/suY1Z0bhNleS9l/2UciY7/59HfH0mXiuGUqO8f56JL9eB/fRlvpd778KkIZPxPuFQJOvHHvMh77x+/FCa+qfP1wqX9iH7/dyB1A2NwiIiIiEYbn+AQERFNggl7gsMBDhER0SRgkDHRzpIxNy/an1HKh5tio5tPiwa+J8oyJEaS9eX/FZ7cK7KcFmXd3jTSRVFuj8OQ19LFwMh9XuQ+OvJm3KmUvHuZ+O+Do4/TkPdC94ehxrR4Y4Dk55H908UYybgO3Xb/cp8duU+QJP+8ZMyNblO39s/j/2cdPkbE/96HjRHRp3rw/+ze1A7+qRb03z3dHkjhUlXEn1phdHI4jQvG4BAREU2CLVxdSdXra8v/EtVqFalUColEAqlUCvV63VPHsizMzc0hn88jl8uhWq3G8/kEPsEhIiKaBBuIPsXkc/7JkydRq9WQy+WwurqKkydPIpPJoFarIZ3eftLdbDaRSqXQaDTcnf6np6extraGbDYbsXMqDnD6iLmogpFTUqt2WSl/4U+PqSf8U9HAXlG+XZT/myjXv6OWd6vTNNiQy77vE2Xd0mm5vFc+mpbTLH5LiXXLpnVpI9QpHG9qBTkFI7+vcnpNTtGEzVCtqy+nSe4Tx/3b0/F+Xp2onzccv3QA+uk0meog3JRL2GXL+mzg/u3F3T/d/Ykq7JRXe3lpaQlLS0vK8TvueHy7lUHmouqzc+fOoVarueWjR48ilUqhWCy6A5xcLod0Oq2kMXKe5HCAM0KYi4qIiPz+QTsuuajq9TqKxaLynmmaME0TzWYTANBqtTrWm5mZAQCUy+VYBzkc4BAREU2CDQBXrgBbV3pv40rnnVGdJzSdGIYBAFhZWVHKDudBQK1W4wCHiIiIenChAFyINpUaRrPZRC6Xc38GgGQy2bVunDjAoYGTMTdJWx2xf+HXRczNAdHAL4ryF0T5vIyhkXEqosGN58RxGVOjS3+g235fkjE68vyn236WqQDkMnD5WeWyaZU31YAklxLLzy6P65bmSnKpr24psC7OQ7e9vqzvv/2/l4yPUO9vP5cW69qW8UTemJxTEa+vu5e6VA/h7k30+KVwy76jxgDJ8/u/zDwGWwBuOQ78jd/ovY3LzwDfOhyoarVahWEY7lOZ1dVVAMDU1FTH+q1Wq/d+dcABDhER0STYBLC1B8CeCI3IVR3dFQoFVCoVtzw9PQ0AWFtb61hfTl1FNTb74MT9aIuIiGisbMT0CiCfz2N5eVkZtDg/d3tSE/cAZ2Sf4CTENIdpmmg0Gm7ZsiwUCgUYhoFWq4VMJoPZWTXNdFx1iIiIaFu5XEYmk/GsInZWS8kHEk457tVkIznAcZaSOY+7ADWCO8hGQnHVIT0Zc/PX7Y8o5SJE6oX/KBr4O6Jc0F1RxtzIOBJLc76MkZFxL7p9b74oyr8c8vz2OA8ZnyNjbmSMjtw3R7fHhtznRfZF9lW2L2N+ZHuy/2oMjy41gn6vF12cSLjt/710n0+9H2HTHfjFbehjQnRpJ3QxL/77univF23PH++frS5+Ktr+MOFTSfiLO8bmansvRmonlAHkonJ2JZarqizLcpeN12o1LC5e/X/D2e14fn4+YudUIznAqVQqymZCUpCNhOKqQ0RENBKcVA1R2+iiXq+jUCggl8uhXL66YWuj0UAqlYJpmlheXkYqlUKz2XSnpIrFIorFYtfVVb0auQFOtVrFysoK5ubmkMlkPAONIBsJzc/Px1KHgxwiIqLtJzSZTAYA3GXh7dbX1wFcDSfJ5/MwDAPNZhP5fL4vv09HboBTq9XQarVQrVZRrVaRz+dRqVTcx2FBNhJyjkWtwwFOZ7pl4J+HGsO0+vmf9W/wlO6Kcpm3eLTtScUgH33rlpXLaQlZXyaTk9M8Mn2CnDKT7bX3V9aVU0byMbt/Nm3dFJGXTJUgpxHksnFdtnC1f2GX8nqnyOQUnSr8NIoum7qkXl+3lFuXjVy9v7rs4P5091Y/fefXt07U76Ju+nGnl1WHT+Wg+y746/Z5t3cyLnc6JX593MnYNE3Yth2oCdM0ldVV/TJyA5xSqYRSqQTLslAqldxgptXVVXc0CPhvJBRXHZ3Lly/j0iX5yyu4PXv2YM+eKMv5iIion65cuYIrV4LsDPyaUnJ+N1y+3Hln4L7oc7LNYTNyAxyHaZoolUrIZDJu2vVKpRJoI6G46ugcPhxsM6RuHnzwQZw4cSJSG0RE1D+FQgEPPRR+k8J9+x7uQ2+o3cgOcByzs7OYnZ2FZW2vjAmykVBcdXTOnj2Lu+66S1uvGz69ISIabsePH8dv/IZ+Z+B9+9Tln6+8chwA8Mwzz0T+x3BgA1hFNUxGfoADAJlMxl1mFmQjobjq6Ozduxc33CDjOcaPjLn5eftvKeUPNB9VT/i3an2Iw+JJLrD+HfHGAVGWMTUi5mVDF0PzIVHWLSOXf6by+jJuRl5f1pdxNO1xHXKJui4OQMbgyLbfoZT0cRX+qRl09XVLmb2pD05p2vePuYkq/NJqHf+YKL+Yo+ipDfyXQYdNgxGV/C70W/ypGjr33wkl0Mc8dd7fYu/e4DsDR9bnVVTDZmx2MnZWNwXZSCiuOkRERDScxmKAU6vV3GVpyWTS3UioXftGQnHVISIiGhnOKqoor6hPgAZopAY428vpUjh58upj4mq1iqmpKSV9wvLyMur1uvL0RW4kFFcdIiKikTBhA5yRisExDANTU1MoFAqo1WowTROZTAalUkmpF2QjobjqTCIZc/OAfaNS/huf/0/qCXIVpIy5eUlzwf1iHxsZ0uIJepNxK7q4kSdF+R2iLPeekXEwur1o5L44sr5sv52M55Hn3ibKck8eGROj29dGd69029urfzje9uVeKTJGR6Y6CLfdvi61g26fHu++NeFiaHTHvakm5PWCiz9eyP/8sGkndH82uvPDxiB5Y17i3TdIp/frDThVwzC0MSAjNcBJJpO+KRraBdlIKK46RERENFxGaoBDREREPdoEkNDW0rcxIjjAISIimgRBByevLwFvLHU+ZkfL8j5IHOCQloy5eZ99j1L+G//iT9UTtPvayCvIOBMRA+OpL/fFeUGUL8oTBBHT47m+3OdGxvTI+jJOQ+YQknEvMu5CxoW0x/jItnW5pvxzNelzLcm/vHTH/ffdCZvvSNLHkfj/Zau/vvx8ve9bs03GKPXev7D3yhsDol5bF98k6e69vn/+nz3qPjVRY2yiihozNNSuXdh+dbJpAT8ZjW1SOMAhIiKaBJsAguXD7G6ENvrjAKePjhw5guuu67zqZGFhAQsLXUbIREQ0NpaWlgD8bpejA1yWtIHoMThRB0gDlLCD5jenwJz9ehqNBkzT3OnuhCanpA7Y6qaG93/9cfWET4sGvinKcobne6L810T5pefEG98QZTmFJFMvyGXeFzXHdUux5aN2OcUlp8xk+yJ1hGapsrf9duq90C+LVummbPRTMDq6e6dbZu5Pt9RYCpuOIPq0UDhhlmLHnXpg0PqdGiLuZea6LRTiuv+D+H3hXAO7GkAi4jVsC9gcjd9vfIJDREQ0CeJYRTVCj0Q4wCEiIpoUIzRAiWqkUjUQERERBcEnOKRdBn7410XMjfRDzQU8mQhEagRPqgY5ryvTEciYlwOaDsjcDrL8HlGWMTkyjkS3TDwtyjJG6HlRlnEp7Z9P9lUu/X1CHJfxPTJ1gm5Zsz993IGM8dGlPtBdX37ecHEcuv5GjTGKHvfSfSl32HgjnfDxSJ8Tx9W0GmHb111PJ+4YnujxZtGuT/3HJzhEREQ0djjAISIiorHDAQ4RERGNHcbgTCAZc5O0s0r58K+X1BNWRAPfFPvS7JYxLDLmRO5bI8s6ulQJulQLMi5Fxn3IfXZu1dSXn09u918XZRlH46891iGROCWO3a+Uw6cyUFM56Nt7uzjun+pAdzx8qoNwMUL6mBhdKgnd3if+cTFh9rXppL1+2PieuGNAZMxN1D2FoqYyiDtmRte+pLte73tKvajtW3w2ALwRQxujgQMcIiKiibCB6AOU0RngcIqKiIiIxg6f4PTRsOSiklNSd9sfUMp/7/NiSuom0cBl2aKYkvGkWvh34g2ZukC3bFrSTUnJKSD1et5H7XLpsiT7q6PL8C2nyNSy/1SAborGv62womffllNA8rP5Z7QOuz2+JP9swy6Lj5oKIvw0kVx23v755b0OZ9DZq/XTpf76PUUUVZQpwqWlJdx+u7rdxve+5+yvMcgnIpyiopicOXNm6HN1EBFRf3X6B+3VAdmLAMoD6skmog9QNuPoyEBwioqIiIjGDp/gEBERTQROUdGIkzE3L9qfUcon/vAfqyf8E9HA+nPiDRlnIZaFvySXWd8pyjIG5bwoy7gIGWMj68ulz/J8NTeEuB3wfh4Z6yA/vyRjhuQydt3nU6/vH1sQLlWBpI9BkfdS3gv/mBrv9U76lnUxLroYIF2cRdilzWH7501fEC3OI0zMT9hlyNFTIcg/+3hjWqL2t9/LxvvN6b9lWUilBjVFFXSAcwrA57scey223vQbBzhERETU5v43X518F8DfHlhPouAAh4iIaCJMVpAxBzhEREQTgTE4NGJkzM2J/2KrFf6VOOG3RHldxrzoyJgbXcyOTH3wXVHWxX3IuIwnfNsLPzev28dGFX1LerlfiIyLaY9Z0u0zo4tp8d9nJuy9Cr+dvm7PoXDt6+rr9yoJt8+N93z/GJ8441R2OlWDNz4rXmH3vRn85x9Hk/UEh8vEiYiIaOzwCQ4REdFE4BQVDTnPlNRZMSX1N+UZcgrqSc0V5KNpmQrBPzt31O3+9akV/KeU9BmtdUudw23vr+OdkpL3T37+3qdRwk4hhT2uu17cU0xRP0/U6+v0c1pk0FMuwzbFM2z9iarfqSSCYbJNIiIiopHGJzh9NCzJNomIaOcsLS0B+F3lvTvu2E6++eqr/Q3mVnGKimLCZJtERLSwsIBPfvJl5b1nn23fyTg1oJ5M1ioqDnBGxK34c/fnVfyhevCwjFGRMTO6fyG8UynpYmB0x6NvGe+/fb5+S/mo2/1HiwPR19d9nu7Hhm2pbNilvnG33+/zKT5xx6AMR0xLcMPev3HEAQ4REdFE4BQVERERjZ3JmqLiKioiIiIaO3yCM6S8e6f4xdHIlVpq3ehxDP77xuiOh79euPQD+vYGG8cRZ/1Rn7cftpihYbv+JIn7XvPPrheTNUXFJzh98Prrryv/nVRXrlzBiRMncOXKlZ3uyo7ifdjG+7CN92Eb78O2wf6+cKaoorw4RTXROMDZduXKFTz00EMT/xcY78M23odtvA/beB+2Dfb3hfMEJ8prdJ7gcIqKiIiI2jwJ4Ctdjo3OP9w5wBlSUfIREREReQWNwUm/+erkAoDjsfWonzjAISIimgiTlWyTA5w++uhHP4rrr7++4zHmoiIimgxLS0tv5qPy+slPfjLg3kwODnD66POf/zze+9737nQ3iIhoB/n9g/brX/86Dh8+PKCeTNYycQ5wiIiIJgJ3MiYiIiIaaRzgDJFuc7TDcE6U8wZxHd6H3s8Z9LUGdZ1h/x4N6jrjdh96vdYwnzM4k7UPDgc4Q2TY/wcc5r/IeR96P2fQ1xrUdYb9ezSo64zbfej1WsN8zuBM1k7GjMEJwLIsFAoFGIaBVquFTCaD2dnZne4WERERdcEBjkaz2UQqlUKj0YBpmgCA6elprK2tIZvN7nDviIiIgpqsVVScotLI5XJIp9Pu4AYA8vk8crncDvaKiIgorMmaouIAx0er1UK9Xkcmk1Hen5mZAQCUy+Wd6BYREVEPGGRMb1pZWQEAGIahvO88zanVagPvExEREekxBsdHs9kEACSTSd/j0muvvQYA+Pa3vx3qej/+8Y/x9a9/3S1fe+21uPbaa33PefXVV2FZVqjr9HJOL+ddvnwZAPDMM89g7969fe0f70Pv5wzqWoO8D72ex/swuHN6vQ+D6l/Qc15//XW8/vrVDNvy73Ed5/eE83ujv/4C0Z/AvBxHRwbDpq4WFxdtAHaj0fAcA2AbhtHxvFOnTtkA+OKLL7744ivQ69SpU337Xfb888/b119/fWx9vf766+3nn3++b/2NC5/g+JiengYArK2tdTwup64cH/7wh3Hq1CncfPPNeOtb39rz9YM8wSEiop0jn+CE9dprr+Gll17Chz/84Rh7pbrlllvwve99Dy+/HM/Tl5tuugm33HJLLG31Ewc4PpwBTKvV8j0u3XTTTfjYxz7Wr24RERGFcsstt4zEoCRODDL24ayWkrE2TjmVSg28T0RERKTHAY6PZDIJ0zQ9q6Xq9ToAYH5+fie6RURERBoc4GgsLy+jXq8rT3GKxSKKxWLX1VXjrNvKMSJ+N6gTfi9opyRs27Z3uhPDrj0XVbPZRCaT6ZimYRxzViUSCaVsmiYajYZbDvKZ46ozCK1WC4VCAcD2QFYa5OfdyXuiuw/A5Hw3qtUqCoUCLMuCaZooFotIp9N9+RzDfD+C3Adg/L8X7ffBMAyUSqWJ/D6MhJ1exjUuVldXbUBdUm4Yhl0qlXawV9GUSiU7m83axWLRfbV/viCfOa46g1Cr1ezZ2VkbgJ3NZj3HB/l5d/Ke6O6DbU/Od6NYLNrpdNoulUruthEA7FqtFvvnGOb7EeQ+2Pb4fy+cz1er1exarWabpmkDsFdXV2Pv/zDfh1HBAU5M0um0nU6nlfdKpZI9ymNI+Xk6Hdd95rjqDFK3X+yD/LzDcE/8BjiT8t2YnZ1Vyo1Gwwag9GkSvhdB7oPTPz+jfh+KxaJSdu5DpVIJ1bdRvw+jgnchBuvr6zaArl/+URxNVyoVO5lM2rOzsx37H+Qzx1Vn0Dr9Yh/k5x2We9JtgDMp341arab8y9xhmqa7yeckfC+C3AfbnpzvRTvnCYpzfybh+zBKGGQcg3HMWVWr1dBqtVCtVpHL5bB//3539RgQ7DPHVWcYDPLzDvs9mZTvRjqd7rrXlfP+JHwvgtwH5/qT8L1oV61WUSwWJ+r7MEo4wIlBrzmrhlmpVIJt22g0Gshms27wmvNZgnzmuOoMg0F+3mG/J5P+3Wg2m5ibm1P6MInfi/b7AEze9yKfz7vBvfLak/h9GEYc4MRgdXUVADA1NdXxeLedkEeBaZoolUqoVCoAtv+nBoJ95rjqDINBft5RuSeT+N2oVqswDMNdRTmp3wt5H9pNwvfi5MmTaDabaLVamJubQ7lcBjC534dhxQFODHrNWTVKZmdnMTs762bWDfKZ46ozDAb5eUflnjgm6btRKBTcX9zA5H4v5H3oZJy/F4uLi6hUKqjVakgmk+5WCpP6fRhWHODEoNecVaMmk8m4/zMF+cxx1RkGg/y8o3JP2k3CdyOfz2N5eVm57iR+Lzrdh27G/XuRTqeRzWbd6aBJ/D4MMw5wYjBJOauczxrkM8dVZxgM8vOOyj2Rxvm7US6Xkclk3ABOx6R9L7rdBz/j/L0AgEOHDrmDiUn7Pgy9HV7FNTZM0+y6H8H6+vrOdCpms7Ozyn4PQT5zXHUGCV2WRw/y8w7DPel2HzoZ5+9GpVLpuOTW2VxtUr4XuvvQyTh/LxzFYlH5/2RSvg+jgAOcmDh7D7TvF2EYhmePglHQaDRs0zSVvlcqFc8vuyCfOa46g+LsLdHpF/sgP+9O35Nu92HSvhvObrWlUkl5ZbNZ95f9JHwvdPdhEr4X6+vrngHb6uqqZ4AxCd+HUcFcVDEKmrNq2DkrA1ZWVjAzMwPTNJHJZDrmnQnymeOq02+WZaFUKqFcLiOZTGJ5eRnpdFpZhjnIz7tT98TvPkzSd8OyLN/H/Ovr6+53Y5y/F0HuA4CJ+F5kMhn3M2YyGRiG0THv0zh/H0YJBzhEREQ0dhhkTERERGOHAxwiIiIaOxzgEBER0djhAIeIiIjGDgc4RERENHY4wCEiIqKxwwEOERERjR0OcIiIiGjscIBDRERDLZ/PI5FIIJFIYP/+/di/f3/XciKR8CSg3Cnlclnp29zcHDKZDKanp5HL5bpmAqd4cIBDRERDrdVqIZ1OY3193X05aSCWl5exvr4O27bRaDTc+sMgm81ifn7e/blSqaBWq6FWq6FcLiOVSg1NX8cRBzhERDT0SqWSkheuE9M0sbi4OJgOBeQ8TcpkMu57hmEgnU6j2WyiXq/vVNfG3u6d7gAREZEfJ7FlELlcrs+9CccZwMjEo85gbVim08YRn+AQEdFQ65SxuxvDMGAYBqrVKjKZDOr1uhsLk8vlUK1W3bgYy7IAbA9C5ubm3DiZdpZlKbEz+Xw+cF+c9g3D8Dx9co6Zphm4PQqHT3CIiGisVKtV5PN5NJtNd3BhGAZWVlZQKpXcGBhHOp12B0XtLMtCPp9HrVZz252bm0Or1UKpVNL24/HHH3fbl+06fZPHKD58gkNERGNldnbWnapKJpMoFotoNBpuEHKnWJ6pqSnPe8eOHUOxWFTaTSaTKJfLgYKDnekpJ/6m1WqhWq3i3nvvRTKZdAdO1B98gkNERGPHGcQcOnSop/ObzSYsy0KhUOh4fGVlxffpS6vVcqehHn/8cRQKBUxNTcEwDBSLRWSz2Z76RcFxgENERGNLt/KqG2dwUqlUejrfeXpjmmbPbVA0nKIiIiISnNVNva5ycqafjh49GlufKBwOcIiIiARnWboMPHbo9q/ptjycBocDHCIiGllra2uhz7nxxhsBqE9nnJ+d4GFnYJLP593pKkf7CqxOms0mms0mkskkl4HvIMbgEBHRyJEDEsl5v9NxZ9CRz+eRTCbRbDbdFVb1eh2ZTAa1Wg2Li4s4efIkUqkUZmdncejQIdRqNZim6Rsk7Dy9mZmZ6fHTUSxsIiKiEVGr1exsNmsDsAHYyWTSXlxctFdXV906lUrFNgzDBmAbhmGXSiVPO8Vi0U4mk+75tm3bhmHYi4uLdqPRUOrp2mpXKpXsZDLp9k1Xn/onYdu2vaMjLCIiIqKYMQaHiIiIxg4HOERERDR2OMAhIiKiscMBDhEREY0dDnCIiIho7HCAQ0RERGOHAxwiIiIaOxzgEBER0djhAIeIiIjGDgc4RERENHY4wCEiIqKxwwEOERERjR0OcIiIiGjs/P+vGjOxMliYowAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -161,8 +161,8 @@ " vmax=vmax,\n", " range=[[0, 30000], [0, 30000]],\n", ")\n", - "plt.xlabel(f\"True $P$\")\n", - "plt.ylabel(f\"EndVelo $P$\")\n", + "plt.xlabel(f\"True $P$ [MeV]\")\n", + "plt.ylabel(f\"EndVelo $P$ [MeV]\")\n", "plt.title(f\"found P\")\n", "plt.colorbar(a0[3])\n", "plt.show()" diff --git a/trackinglosses_energy.ipynb b/trackinglosses_energy.ipynb index ea88ca8..78f3468 100644 --- a/trackinglosses_energy.ipynb +++ b/trackinglosses_energy.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 65, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -17,7 +17,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -51,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -116,7 +116,6 @@ " fromPairProd: bool,\n", " fromSignal: bool,\n", " fromStrange: bool,\n", - " ideal_state_770_p: float64,\n", " ideal_state_770_qop: float64,\n", " ideal_state_770_tx: float64,\n", " ideal_state_770_ty: float64,\n", @@ -152,6 +151,8 @@ " originvtx_y: float64,\n", " originvtx_z: float64,\n", " p: float64,\n", + " p_end_ut: float64,\n", + " p_end_velo: float64,\n", " phi: float64,\n", " pid: int32,\n", " pt: float64,\n", @@ -194,7 +195,7 @@ "" ] }, - "execution_count": 67, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -205,7 +206,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -233,7 +234,7 @@ "" ] }, - "execution_count": 68, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -270,7 +271,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -293,7 +294,7 @@ " cut_brem.field(\"brem_photons_pe\")\n", " cut_brem.begin_list()\n", " for jentry in range(brem[itr, \"photon_length\"]):\n", - " if (brem[itr, \"brem_vtx_z\", jentry] > 3000\n", + " if (brem[itr, \"brem_vtx_z\", jentry] > 2700\n", " or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n", " or brem[itr, \"brem_photons_pe\",\n", " jentry] < photon_cut_ratio * tmp_energy):\n", @@ -309,7 +310,7 @@ " cut_brem.field(\"brem_vtx_x\")\n", " cut_brem.begin_list()\n", " for jentry in range(brem[itr, \"photon_length\"]):\n", - " if (brem[itr, \"brem_vtx_z\", jentry] > 3000\n", + " if (brem[itr, \"brem_vtx_z\", jentry] > 2700\n", " or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n", " or brem[itr, \"brem_photons_pe\",\n", " jentry] < photon_cut_ratio * tmp_energy):\n", @@ -324,7 +325,7 @@ " cut_brem.field(\"brem_vtx_z\")\n", " cut_brem.begin_list()\n", " for jentry in range(brem[itr, \"photon_length\"]):\n", - " if (brem[itr, \"brem_vtx_z\", jentry] > 3000\n", + " if (brem[itr, \"brem_vtx_z\", jentry] > 2700\n", " or brem[itr, \"brem_photons_pe\", jentry] < photon_cut\n", " or brem[itr, \"brem_photons_pe\",\n", " jentry] < photon_cut_ratio * tmp_energy):\n", @@ -343,14 +344,14 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "20636\n", + "19715\n", "50501\n" ] }, @@ -381,7 +382,7 @@ "" ] }, - "execution_count": 70, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -401,7 +402,7 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -419,7 +420,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -454,7 +455,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -491,7 +492,7 @@ "" ] }, - "execution_count": 73, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -507,7 +508,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -521,12 +522,12 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -558,6 +559,7 @@ " label=\"found\",\n", " range=[xlim, 1],\n", ")\n", + "plt.yscale(\"log\")\n", "plt.xlabel(r\"$E_\\gamma/E_0$\")\n", "plt.ylabel(\"a.u.\")\n", "plt.title(r\"$E_{ph}/E_0$\")\n", @@ -567,15 +569,15 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "found: 16049 , lost: 4587\n", - "0.2858122001370802\n" + "found: 15673 , lost: 4042\n", + "0.2578957442735915\n" ] }, { @@ -602,13 +604,13 @@ " -4.27,\n", " -17.8]\n", "---------------------\n", - "type: 16049 * float64" + "type: 15673 * float64" ], "text/plain": [ - "" + "" ] }, - "execution_count": 76, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -633,12 +635,12 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAABkgAAAL5CAYAAAD7Uaj9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACy8UlEQVR4nOz9f5Qj533f+X5qZsRxr/kD0/RK16STkGg6Wfrailhoy3Z8E8YicB3F13uv1N3Dazt2lBMSOErL2RNu1DCXd29zcsNto21zz65vrwLM+NrexJvDAUa65ySOkgCyzWzsa1ODIi35SMmKDdGOSa8YshscMm6NND11/+gpEGjU8zRQAAq/3q9z+nR3PVVPfeupH3ieevBUOb7v+wIAAAAAAAAAAJgjp8YdAAAAAAAAAAAAQNzoIAEAAAAAAAAAAHOHDhIAAAAAAAAAADB36CABAAAAAAAAAABzhw4SAAAAAAAAAAAwd+ggAQAAAAAAAAAAc4cOEgAAAAAAAAAAMHfoIAEAAAAAAAAAAHOHDhIAAAAAAAAAADB36CABAACAUbPZVKVS0drams6dOyfP88YdEmZErVZTLpfTuXPnVKlUxh0OAAAAgDlEBwkAAACMSqWSisWiKpWKms3muMNBDLa3t1sdYufOnVMulxv6vq9UKioWiyqVShxXE6rZbMpxHGUymb6WyefzWlpakuM4HT/B8XR8uuM4KpVKI9ySwVUqFWUyGWUyGaVSKWUyGdVqtaHl73meMplMTx3Qs1rGAAAA40IHCQAAAIw2NjZULBbHHcZUazabU9EJ0Gw2lUql9Oabb6pcLuurX/2qFhcXVSqVhn5zdXV1VeVyeah59mpa9se4Bft8bW2t52USiYQKhYKq1WrHtP39/daP7/vyfV/1el3ZbFaStLy8PNzgh2htbU1ra2ut7arX68rlcspkMsrn8wPl3Wg0tLa2plQq1XOHyyyWMQAAwDjRQQIAAACrxcXFcYcw1dbW1tRoNMYdxony+bw8z1Mul5N0dNN1d3dX1WpVGxsbY45ueKZlf4zbc889J0k6f/5838u2d0CdP39eiUSiax7XdVUsFpVIJOS6btQwRyqXy7VGO7XHuLq6qmw2q+3t7ciPhwtG50U1K2UMAAAwbnSQAAAAACOSz+eH+iieUQpGDBzvEEun0+MIZySmaX+MU6PRkOd5SqfToTfeT9JexieNQOlnZEMwciOOfdhoNFrnRDAK43gskiKPIslmsyoUCioUCpGWH1UZAwAAzBs6SAAAAIARqFQq2t7eHncYPZmHERXTtD/GLRjZEHQC9Kv98U8ndbD186i1YrGoTCbTeixV1NEbvQg6Lkzxu66rRCKhRqMxUIdN1BF6oypjAACAeUMHCQAAAPoSPDc/eCGw7ZFFtVpNa2trrW9i53K50Bc/N5tN5XK51ouHU6mU8WZ2pVLR2tpa65vbwQuOg5cUty/XaDSUy+VaLy7OZDJ9vX/C8zylUqmOlx0fj6tSqbTiDvKvVCp6/PHHW/M88sgjrfJqL8P2fDOZTOub+8E6z507F+kb6tvb260XSi8tLSmTyYS+R6RUKuncuXNKpVKtaffff38r1l47FIKXWAfryOfzHWXe6w3k9uVSqdSJL63udTtP2h9R85WOjt1SqdQxT6lU6jiWTdvRbDZb77hYW1vT0tKSlpaWTuyY8Dyv42XcS0tLrTLe3t7uSmuPvdlsts6XpaWl0PMh6HhYXV21xmESxBJ2477ZbHaUR78jVDY2NrS/v69cLtd6WfkoXkAebIPt0VTJZFKSxvKeplGWMQAAwFzxAQAAAIv9/X1fki/JLxQKviQ/mUz6iUSiNV2SX61WW8sUCgU/mUy20orFop9OpzuW2d3d9X3f96vVqu+6bmv53d1dP51O+5J813VbeVar1dZ0SX42m/U3NjZ813X9jY0NP5vNdqyvXC77yWSyNV8QT3uevW5/EHc6nQ6dJ9heU7nV6/XQ5YrFYmuecrncld/+/n5fsdbrdT+ZTPqrq6sdcayurrbiD8tzd3e3a7/0ur72fRLE7bqu77pux/FRKBS6lm/fX67r+ul0umNfSQqNN8p29rI/+s03OHbbt3F1ddV3XdfPZrMnbkcymewol/39/a71m1Sr1dBjJ9iOsPPyeFmElUOwbC8xnBRXsVjsSs9ms30dYycJzvNEIhF6jEVx/JpnEhwXx8/9qOsyHZfHxV3GAAAAs4wOEgAAAFi138BLJpMdN97ab9QlEgnrcsGN2kKh4GezWd/3370xf/zGYPuyGxsbHWntN+SP3xgOOkkSiUTXDd6onQBBzMGyYVZXV7tuVPZ64zO4wR503AQdMr3eLG2XSCS69kMgKLewTp5Bysb3/Y5joD3u4Ia/Ke/24+P49gadUsf3f9Tt7GV/RC2/INZEItHRIdHeuXb8RnvQOXa8TKrVas+dE0HZhpVRkBZ2gz/o2AmzsbFh7FjpRbD88W3b39/3C4WCsXwHVS6Xfdd1Wx0l/XYutmvvYArrgAi0d8pGFaWDZFxlDAAAMIt4xBYAAAB6VigUWo+VkY4e7xI8XqbZbHY8kimRSLQe7ZJOp1uPgtnY2Ggtk8/nlUgkuh5j0z7t+ONz2vM8/gig4GXFzWZTFy9e7EhLJpOtZU96dNNx7S9pPh5Ps9lUrVYLfZFzL4L3A3iep1KppLW1NWWzWeujfcLk83k1m01jHME7FWq12sje3fDkk092xJ1IJDrelWB6IXWhUOja3uB4Of74tlFt5yD5BudENpvteORRIpFovSB7d3e3Y5ng/+N5pdPpjnPMJngUV9gjpoK0sMc/FYtF42O8SqWSEonEie+1MGnfnuAxY+2Pizt//nykfE+yurqqer2ucrmsarXaWl8/j9QL7O3ttf62vSOk/dFVUdYT1SBlHDzOMHisW/BoPwAAgHlFBwkAAAB6FnbjNpvNtm4Ufv7znw9drv0dF+0qlYqazWbr3QvtP0EnRrPZ7Lj5GNywDHuu/kkvPA7S+70hmEgkWjfOj99wvnz5cuSbydJRmW5sbEg6uqndaDSMHQk2wU3T7/3e7w1Nd123tf+ee+65iNGGC/ZF2D5JJpOtzo+rV6/2nGcQ6/F9NartHFW+pu1YWlqSdNQxc/w9M73u/+CYDDrp2gUdMMF7bQK2Dr1araZmsxm5E6PZbLa2M5vNyj96YoH29/dVrVaVSCRanZijkk6nVa1WVa/X1Wg0dO7cudZ5NQsGLePgWlwul1Uul1udJHF28AAAAEwSOkgAAAAwsOBb8v2MzAjmTafT2t3d7foJbvz5vj+0lwwPkk/wjXvP8zq2s1gs6sknnxworvaROf2OHAn0cgM4WEe/I2gGZRoNEsWotjPu8msfJbS9vd3xovVeJRKJ1iiq9o674MXxQbm3p9k69ILRTCe9JN7k8uXLrb/bb9IHI1KSyeRAnYn9cF1X5XJZu7u72tvb09LSUs+dM+0dre2jSY5r71SI60Xog5RxPp/v6oANOsoef/zxEUUMAAAw2eggAQAAwMB6fSRQu+DG47R8s9t13dYN7eCGc6PRULPZjNyp0S640V2pVPq+Ud5ehrYbusF+ss0zCnffffdQ8hnVdo6r/Or1emu/NxoNZTIZra2t9fVt/qAzIxiNJR09Jmt1dbV1I7z9pnqhUDB26AWP14p6PLc/Ti3sJn1cnSPHnTSy7Lj265ltXwTHQVydI9JgZVwqleS6ble86XS64/gBAACYJ3SQAAAAYGDBDbd+bqxGfdzVOB1/54PtXQ79aDQarZuX7evpVfsN3ePvumgX7KcoHVrDEIw0impU2znO8gsedRTkWalUjI+kC5NOp1txBR0hW1tbrffBJJNJNZtNVSqV1siXsPM0eMRY1HfpSGp17Jlu0kd5dFxUjUZDa2trWlpa0t7ennZ3d1sjZE6SSCRa++PNN980zhd0KMTZ8RO1jD3PU7PZDD0Hg+OtvSMNAABgXtBBAgAAgIEFnRym9zeEab/JbHuZdvC4oEnQ/r6VUqmkUqk00A3lwNramgqFQuvF8o1Go+OF970IytM2+iTYT4N2VPQr6HQYxkibUW1n3OXX/piu1dVV7e7utt5FE3SY9ar9/TiVSkXLy8tdnW3FYtHaoRe8V+XRRx/tf2P07g14ScpkMj0tYzvvo/I8T5lMRktLS1pcXNT+/n5HB1SvgpE9tsepBe/U6XV7BzVIGQex2t7dZOscBAAAmFV0kAAAAGBgnud1vMi8F+3f0n788ceNj3dZW1sb26N5wgQvsM7n8x3f3rexPZIp6AgJ3kkR3CQP3hfQq/Z3pJiWC272Hn8p+KgFnQ7DGG0zjO0M2x9xl1+xWOxaT6FQaN2Y7+dmdXvsjz/+eEd8wTlZq9WsHXqVSkXJZDJyJ1b7i+t7OV+H/bL2Wq2mVCqlRx55RK7ran9/X8ViMfLjr4IyNXWYBY/X6/e6N4hByji4voY97i4oo2kazQcAADAsdJAAAABgILVaTY1GQxcvXuz7ZmTwOJhms6lUKtXxbW3P85RKpVqPCQoM8v6H4Cah7bE5JwluPjebTesN//ayaN+u9puQjUZD+Xy+49E/hUKhtWw/HQobGxutcgp7zE5w4799vsCw3j0Qlk9wfIStN4qo23nS/hik/Gxsx2v7y9MDwciAfkdjBTfMFxcXO26eBy/vlo5GRYSdo8Eog0E6sNo7EmydLM1mU2tra6rVaq3OoEFUKpXWC9gfffRR7e/vd5xDUSWTyVbHR9hIl+AYCTtWGo2GUqlUT+XZz/VskDKO8z0pAAAAU8UHAAAATpBMJn1Jfjqd9nd3d1vTy+Wyn0gk/GKxGLqcJF+Sn81mjXmvrq625jv+E7ZcOp1uxXJcuVxuLVutVrvSE4mEL8lfXV3tZbON0um0n0wme5pPkp9IJPxCoeCn0+mOuFzXDd3G9u0oFAo9x7W7u9vaV+3LBdNN+6F9feVyuef1BYJyldRxLFSrVT+RSISud39/37qN7WU3rO08aX9Ezdd2XLmu60vyXdftmJ7NZkOP03Q63TVvL4J9GLb/grSwcyJYp6SOc7sfu7u7Heft8Xz29/f9er3uFwqFVlltbGxEWlegWCz6yWTSTyaTxuvPMKyurvqJRKJjm6rVqnUbNjY2WmVRr9et+fd67g1axraYgxhs12kAAIBZRQcJAAAAelIoFHzXdf1EIuEnEgk/mUz6q6uroTdVC4VC60Zze2eH6QZgsVj00+l0K+/jN6593/fr9XrrpnJ7nsENyPYbg5L8ZDLZusldrVZbN4Hbl416Q7hcLvd0U3Z3d7fjBnmwTdVqtTU9nU533ETd3d3tinV1ddXf39/vOb7g5n8ymfRd1w0tT98/KtONjY2OckskEv7GxkZfHSXB8sVi0c9ms34ymfQTiYTvum5oOZXL5db2Bz8bGxv+/v6+v7u729VpdryM+t3OgGl/DFJ+puMqbDvaz5dCodC6+Z5Op/1sNuun0+mBOg7COg1PSgs6qqJ0yvi+33X8tB9HYdNNN/h7FZznyWQyUmdeFMH1aXV11U+n08bjMVCv1/1kMmndH+Vy2XjuHT9nhlHGQQdLWCdIsVjs6twEAACYF47v+75xeAkAAAAAnODcuXNqNpsqFouxvY8B8yeXy+nq1asqFAoT9V6iaXHu3Dklk0nV6/WO6blcTqVSSbu7u0N5DB4AAMA0OTPuAAAAAAAAOEnYO1vQu2w2q+3t7a7ptVpN6XSazhEAADCXeEk7AAAAAAAzrlAoKJlMKp/Pt6ZVKhU1Gg06nwAAwNxiBAkAAACAgTSbzXGHAKAHu7u7yuVyyuVykqS9vT0erQUAAOYa7yABAAAAEFmpVGrdbHVdV+VymZutAAAAAKYCHSQAAAAAIllaWlKj0eia7rpu14ugAQAAAGDS0EECAAAAAAAAAADmDi9pBwAAAAAAAAAAc4cOEgAAAAAAAAAAMHfoIAEAAAAAAAAAAHOHDhIAAAAAAAAAADB36CABAAAAAAAAAABzhw4SAAAAAAAAAAAwd+ggAQAAAAAAAAAAc4cOEgAAAAAAAAAAMHfoIAEAAAAAAAAAAHOHDhIAAAAAAAAAADB36CABAAAAAAAAAABzhw4SAAAAAAAAAAAwd+ggAQAAAAAAAAAAc4cOEgAAAAAAAAAAMHfoIAEAAAAAAAAAAHOHDhIAAAAAAAAAADB36CABAAAAAAAAAABzhw4SAAAAAAAAAAAwd+ggAQAAAAAAAAAAc4cOEgAAAAAAAAAAMHfoIAEAAAAAAAAAAHOHDhIAAAAAAAAAADB36CABAAAAAAAAAABzhw4SAAAAAAAAAAAwd+ggAQAAAAAAAAAAc4cOEgAAAAAAAAAAMHfoIAEAAAAAAAAAAHOHDhIAAAAAAAAAADB36CABgAnWbDbHHQIAAACAKUH7AQCA/tBBAgATrFarqVarjTsMAAAAAFOA9gMAAP2hgwQAAAAAAAAAAMwdOkgAAGPleZ5KpdKJ8zUaDZVKJR4bAAAAAMww6v0AgDjRQQIAM8zzPOXzea2trWlpaUnb29vjDqml0WhobW1NqVRKxWLROu/29raWlpaUy+W0t7cXU4SzpdFo6Ny5cz11RgEAAGB+BG2GVCqlVCo11lio9w+Oej8A9OfMuAMAALwrl8t1/N9oNCRJ5XK5Y/pJHQrSUUPnkUce0f7+viQpn89rd3d3SJEOLplMqlwuy3GcE+fd2NjQ5z//eVUqlRgim36NRkOLi4tKJBKtac1mU81mc6KOAQAAAAxmGO0H13UlHXVOBH+PQlgd9Tjq/f2h3g8Ag6ODBAAmyPGGS6VSUSKRUDqd7juvra0tLS4utv4vFAoDxzdO7dsCu7W1NZXL5Y6Gkuu68n1/fEEBAABg6IbVfhhlx0ggrI4ahnp/76j3A8DgeMQWAMwoz/PGHQLGYG1tjX0PAACAiUIddfgoUwAYDjpIAGDGlEolra2tqdFotN7zsba2plqt1pqn2Wwql8spn88rk8kok8l0pFcqFZ07d06O47Qq3bVaTWtra3IcR2tra618SqWSUqmUKpWKarWaUqlUxzztgvUGP1HeiRLkce7cOZ07d67rsQKVSqW1PaVSqWsez/O0tramTCajpaUl5fP5jrxLpZIymYxKpZIajYYymYzOnTunTCbTelFk8Gzkc+fOdSxv4nleqzxTqVTr0QfS0aPPHMfpKAtbjLZtrFQqrf2Vy+U6Gk2VSqV1LJjKNJfLtY6H442tk2JqP6ZyuZyWlpZ47jEAAMAMOKntcHye43VBWx21l/VS76feDwAj5QMAYlcul/1sNutvbGz4ruv6u7u7xvmq1WqkdSSTST+ZTHZNr9frfiKR8Ov1emtasVj0JfmFQqE1LZvN+pI65tvd3fUl+aurq63/V1dXfUl+Op32NzY2/Hq93lq2Pb/d3V0/kUh0bE+hUPAl+a7rnrg9QZ7pdNrPZrN+sVj0XddtTfP9o/JKJpO+pI7yDfKv1+uteYP5g3mDGNvXE2xPtVrtWHe1Wu3Y9vYyMgnWFZRde7m0x3RSjCdt48bGhi+p45ja3d1tlXV73kFaMpnsmD+RSPiJRKLnmHzf91dXV/2NjY3W/8VisWP/AwAAILo42g9h9fJe2w4n1QXD6qgm1Pup9wNAnOggAYCYZbPZjspyIpHwi8ViK639J51Otyrn7T+9MHWQuK7bVVkOprdXsIMKd3sjYH9/v6uyH1Saj1eKj1fKV1dXQ9fbbwdJuVzu2k5JrYZg0CBor7S3b+PxRk0ikfAl+fv7+77vHzUKjjcCgmWPN0CCeXttEASxtisUCh3b1EuMtm20NT7DGkqu63bFH+QfrK+XmBKJRFc8NJQAAAAGF1f7Iaxe3mvb4aS6YJQOEur91PsBIA68pB0AYpTJZHT16lV99atflXQ0/LnZbLZeonj8JYvD1mg05HmeNjY2utKCodbFYjHSC93DXra4t7fXWm+lUhnKi+KPv0AyGN5drVaVTqdbcXzv935vx3zBtm9tbYXme/Xq1Y6XWR7fnmQyKc/zOl4amUwmJUm7u7s9xR7EWqlUtLq6Kkl67rnnVK/X+4rRtI39CtZ38eLFjukbGxutY6TXmJLJpLa3t3X33Xe3lg07zgAAANC7cbYf+mk7jKIuSL2fej8AxIEOEgCISalUUq1WU7lcViKRUKlUUqFQULVabVW4R832rN/l5WVJ6nhO7rAEeY5iO4PGzfG4jzd0gm0vl8tDj6FX2WxW+XxexWJRq6ur8jyvVe5S/zGGdUr1I1ifLZ9eYyqXy0qlUq3tK5fLXY1aAAAA9G7c7Yd+2g5x1AWp90dHvR8AzHhJOwDEJHhhYKPRaL3obnd3t+PbS3EJXjrYLqgst39TaliCRkwwomSYgrhPaiQGMYyiA6hXiURCq6urqtVqajQaeu655zpeJBl3jL2sr9eYksmkvvrVryqdTqvRaCiVSvGyRgAAgAFMSvuhl7ZDHHVB6v3RUe8HADM6SAAgBrVaTdLRN4k2NjZUKBSUzWZjjyP4Zk8QT7ug4bO0tDT09QaNmGBI+TAFcZ807DyIoVKphKaHlckoPPnkk5KOHofgeV7Ht63ijjFYt+lbYo1Go+eYGo2GEomEqtVqK7/2RiAAAAB6Nwnth37aDnHUBan3R0e9HwDM6CABgBiFdT6M6ltDe3t7XSM2ksmkXNdVo9HoWu/Vq1eVSCRaDa+77767K77g77BvkdkEw8lLpVLosv3m165WqymZTLae7WsSfNMun893PS4gzm88ua7bem7v2trayGLspUzb98vxRlg+n9fi4mLPMbW/X2Z1dbX1POxxfnMPAABg2sXZfjiun7ZDr3VB6v3Dj5F6PwAMhg4SAIhBUCENvj0kHT3jdXt7eySPtLIJnmHc/i2fZrOpQqGgixcvtoauB98yyufzqtVqKpVKrcpvrVZTJpOR1NtjsxKJROvFfalUqjXUPHhUQKPR0Pb29ol5BPMGGo1G67m37dvS/tsUw9ramra3t5XJZDoeVWDaniC/9vTg734fHRaU/fnz5yPFaNpG6d1GdLFYVKPRaH0DLCz+RCLRauBkMhmtra0pn88rlUppaWlJiUSi55guX77csW+azaaSyWRs79cBAACYJZPSfui17XBSXdBURw1DvZ96PwDEygcAxKJarfrJZNKX5Luu6xeLxZGsp16v+9ls1pfkS/Kz2axfrVY75tnf3/dXV1f9dDrtZ7NZP5vN+vV6vSuvQqHgJxIJP5FI+BsbG77v+34ymfQ3Njb8er3u1+t133VdX5KfTCb9arXq7+/vd6y/UCi08isWix1lsLu728pvd3fXul37+/v+xsaGn06nO+Le399vzVMul1v5J5PJ0DIuFArGeer1up9Op31JfiKR8MvlcivuYHtWV1f9er3u7+7u+qurq615+9mfQRmZ2GLsZRtd1/UTiURrHfV6vRVrsE+Ol1uwH13X7TpeTorJ930/nU639uXGxoa/urrasQ4AAAD0Z1zth+N1xV7aDr3UBY/XUU2o9/e+jdT7AWBwju/7/qg7YQAAAAAAAAAAACbJmXEHMCzNZlNbW1uSOp+HGPA8T1tbW0omk2o2m8pkMl3PrRzWPAAAAAAwaWgzAQAAAJ1mooOkVqupWCyqUqm0XhDWrtFoKJVKqV6vt56pv7S0pL29vdb8w5oHAAAAACYNbSYAAACg20w9YstxHGWz2dZLhAPBi4Sr1WprWqlUUi6XU7D5w5oHAAAAACYVbSYAAADgXafGHcCoNZtN1Wq1VkU9sLy8LOmosj6seQAAAABg2tBmAgAAwLya+Q6Sq1evSpKSyWTH9GC4d7VaHdo8AAAAADBtaDMBAABgXs3EO0hsGo2GJCmRSBjThzWPzRtvvKFf//Vf17d/+7frW77lW04O3OC2227TbbfdFnl5AAAAoBff+MY39I1vfCPy8l//+tf1J3/yJ/qRH/kRfdu3fdsQI8Ow0WYCAAA4Mmt14D/6oz/SG2+8MZZ1f9u3fZv+7J/9s2NZdz9mvoNkd3dXkrS4uBia3mw2hzaPzb/6V/9KH/vYx3qIGAAAAJgdv/Irv6K/+Tf/5rjDgAVtJgAAgOGahDrwH/3RH+mBP/fn9M0xrf+2227TV77ylYnvJJn5DpKlpSVJ0t7eXmh6Mpkc2jw29913nyTp4sWL+vN//s+fGLdJ2LehVlZWdOXKlch5hnnnnXf08MMP6/nnn9ftt98+1LxHES/5Hpmr/fblL0t/429I/+SfSA8+OLx8TzDUfG9tw59evKi//Pjj87HfZijfuTrfZihf9tt05jt1++2Ez6hBxLnfBv323O///u/r7/7dv6tv//ZvHzQ8jNgstpl+7Md+bOBzZVjXnmGdt8PIZ5JimeryNVznJ6J8h9zGmIhtGnI+c3/8jjgfyne0+cxc+Q6x3jys8v2n//Sfzkwd+I033tA3JX1UUtxjWd6Q9OlvfENvvPEGHSTjFlTCTd9WSiaTQ5vHZmFhQdLR83eDZ/AOy8LCwtDzvHbtmiTpAx/4gO68886h5j2KeMn3yFzutwcflEKWn9h4Q7xz6wbAXO23Gch3Ls+3GciX/Tad+U7jfpNk/IwaxDTtt8Agj0pCPGaxzTSMY3pY155hnV/DyGeSYpmJ8j12nZ+k8h1WG2OStmlY+XD8jjYfyne0+cxi+UoaSr15WOX7/d///QPlEZikOvC3Sbpn3EFMsJ47SIKTZxDDbtD2Ynl5WVL3826D/1Op1NDmAQAAADDfprHdRJsJAABgdp1R/KMkpmlUxqleZ0wkEjp37lzkH9NzaEctkUjIdV1Vq9WO6bVaTZJ0/vz5oc0DAAAAYL5NY7uJNhMAAADmVc+dOYlEQtlsVnfffXffK3njjTd08eLFvpfrh+2FfxcvXlQqlVKj0WgN6y4UCioUCkokEkOdBwAAAMD8muR2E20mAACA+XNG0nvGsM5p0XOs58+f18/+7M9GXpHjOJGXPYnneSoWi5Kky5cvK5PJKJ1OtyrgruuqXq8rn88rmUyq0Wgon88rm8228hjWPAAAAADm16S2m2gzAQAAAN36GkEyqVzXVbFYbFX4TfOUy+UT8xnGPAAAAADm06S2m2gzAQAAAN167iDJ5XIDrWjQ5WG2vr4+7hD6Mqp4yXe0pq0cpi3fUZm2cpi2fEdl2sph2vIdlWkrh2nLd1SId7T5ziPaTZNhko7pYcUyjHwmKZZhmaRtmqRYhmXStmmS9tMwTFK5DCsfyne0+cxi+Q7LrJXvMJ1W/I+8Oh3z+gbh+L7vjyrzS5cu6bHHHhtV9lPF8zylUinV63W5rjvucE507do13XXXXXrrrbd05513jjsc9Giu9pvnSamUVK9LU3BOhbq1De88/7zuePjh+dhvM2SuzrcZwn6bTlO332bhM2oI/s2/+Td6+OGH9fzzz+uv/JW/Mu5wJhrtpiOT1maaumvPlJnq8p3k6zxtjFhM9fE7BSjf0Zqo8p3k62lEk1QHDupWf0/Sd8S87j+W9N9LE1Ovsxmo8+ill15SrVbT7u5uV9re3p5qtRoVfQAAAABzjXYTAAAAxoWXtNtFjvVnfuZn9HM/93OyDUAZ5YvZAQAAAGDS0W4CAAAAJtepqAuWSiWtrKyoXq9rf3+/6+fll1/WysrKMGMFAAAAgKlCuwkAAADjFLyDJM6faXoHSeQRJIuLi9re3tZ9990Xmn7XXXepUChEzR4AAACYGo5zofX3Q3pNniQ3VdSLuke+vzm+wDB2tJsAAACAyRV5BEkul1Oj0bDO89Zbb0XNHgAAAACmHu0mAAAAYHJF7iD55Cc/qXK5rD/8wz/UtWvXun5eeeUVbW1tDTNWAAAAAJgqtJsAAAAwTsFL2uP8mYuXtF+7dk27u7tKJpPDjGfmraysaGFhITRtfX1d6+vrMUcEAAAARLOzs6OdnZ3QtD/90z+NOZrJRLupf7SZAADAJKMOPFsid5Csrq6qVqvJdd3Qyv7+/r5+4zd+Y6DgZtGVK1fkuu64wzjR2bNntbm5qbNnz447FPSB/TadbrvtNvbbFOJ8m07st+nEfptctpvVv/u7v6sf+IEf0G233RZzVJOFdlP/JqXNxLVntCjf0aKNMVocv6NF+Y4W5Tu4aasDBy9pj3ud0yJy2Vy9elW1Wk0f+tCHjPNcvHgxavYYs7Nnz+rpp58edxjoE/ttOt12223stynE+Tad2G/Tif02nYJG4SQ1DseBdtP04tozWpTvaNHGGC2O39GifEeL8h0t6sDTJ3IHyfLyshYXF63zPP7441GzBwAAAKaG72+++4/nSamSvHpOmoBvwWO8aDcBAAAAkyvyS9qLxaKee+456zyf/vSno2YPAAAAAFOPdhMAAADGiZe020WO9XOf+5w8z9PHP/5xJRKJ0HlKpZI++tGPRl0FAAAAAEw12k0AAACYRdVbP2G+EWcgA4rcQXL58mXVajXrPI7jRM0eAAAAAKYe7SYAAACM0xmNZkTHh2/9hPmqpCdHsM5RiFw2a2trSiaTyuVyoelvvvmmtre3IwcGAAAAANOOdhMAAAAwuSJ3kJw/f17pdFr333+/cZ677747avYAAAAAMPVoNwEAAGCcgneQxL3OaRH5Je133XWXtZIvSfV6PWr2AAAAADD1aDcBAAAAk2ugzpyXXnpJtVpNu7u7XWl7e3uq1Wp67LHHBlkFAAAAAEw12k0AAADAZIrcQfIzP/Mz+rmf+zn5vm+ch5cNAgAAAJhntJsAAAAwTjxiyy7yI7ZKpZJWVlZUr9e1v7/f9fPyyy9rZWVlmLECAAAAwFSh3QQAAABMrsidOYuLi9re3tZ9990Xmn7XXXepUChEzR4AAAAAph7tJgAAAIzTacU/ouN0zOsbROQRJLlcTo1GwzrPW2+9FTV7AAAAAJh6tJsAAACAyRW58+iTn/ykPv7xj2tpaUnnzp3rSt/b29PW1paee+65gQKcNSsrK1pYWAhNW19f1/r6eswRAQAAANHs7OxoZ2cnNO3g4CDmaCYT7ab+0WYCAACTjDrwbIncQXLt2jXt7u4qmUwOM56Zd+XKFbmuO+4wAAAAgIHZblZ7nqdUKhVzRJOHdlP/aDMBAIBJNm11YF7Sbhc51tXVVdVqNbmuG1rZ39/f12/8xm8MFBwAAAAATDPaTQAAAMDkitxBcvXqVdVqNX3oQx8yznPx4sWo2QMAAADA1KPdBAAAgHHiJe12kV/Svry8rMXFRes8jz/+eNTsAQAAAGDq0W4CAAAAJlfkDpJisXjiiwQ//elPR80eAAAAAKYe7SYAAACMU/AOkjh/bCNWms2m8vm88vn8ibHXajWdO3eua7rneVpbW1M+n1cul1OlUjkxL5PIo2s+97nPyfM8ffzjH1cikQidp1Qq6aMf/WjUVQAAAADAVKPdBAAAAByp1WoqFouqVCrKZrMnzp/L5bqmNRoNpVIp1et1ua4rSVpaWtLe3l5PeR4XuYPk8uXLqtVq1nkcx4maPQAAAABMPdpNAAAAwJF0Oq10Ot1T/TefzyuZTGpvb69jei6XUzqdbnWOBPPmcrl4O0jW1taUTCZDe3Ek6c0339T29nbU7AEAAABg6tFuAgAAwDhN40vaa7Wa7r77brmuq6tXr7amN5tN1Wo1FQqFjvmXl5clHY3M7reTJHLZnD9/Xul0Wvfff79xnrvvvjtq9gAAAAAw9Wg3AQAAAP0pFosql8td7ykJOkuSyWTH9GA0SbVaHV0HybVr13TnnXe2/r/rrrt01113WZd56KGHjMsDAAAAwKyh3QQAAIBJErykvR/fuPUT1TcHWDafz3eNEAk0Gg1JMr7bL0jvx6leZ9za2uo782EuDwAAAACTjnYTAAAApt0vS3p4gJ/HI67X8zzdfffdXSNEAru7u5KkxcXF0PRms9n3OuN+/BgAAAAAAAAAAJhQf0vSTwyw/P+maJ0kW1tbKpfLxvSlpSVJ6npxe8DUsWLTcwdJpVLRAw88IN/3+15Js9lUqVTi21AAAAAAZhrtJgAAAEySM+p/lMQZSf/ZAOu8I8Iy+XxemUym4zFZwd/B76ADxDRSZKQdJLu7u3r88aiDYyTHcSIvCwAAAADTgHYTAAAA0L9arabt7e3QtKWlJbmuq8997nOSut81EvyfSqX6Xm9fHSQAAAAAADPaTQAAAJgkUV7SPox19qter3dNy+fzKpVK2t/fb01zXVfValUbGxutabVaTZJ0/vz50cV6//339505uq2srGhhYSE0bX19Xevr6zFHBAAAAESzs7OjnZ2d0LSDg4OYo5kMtJsGR5sJAABMMurAg4nyIvV2Fy9eVCqVUqPRaD1Sq1AoqFAoKJFI9J0fL2mP2ZUrV+S67rjDAAAAAAZmu1nteV6kIe4AbSYAADDJpq0OfFrxdwKcNkz3PE/FYlGSdPnyZWUyGaXT6b46NlzXVb1eVz6fVzKZVKPRUD6fVzabjRQrHSQAAAAAAAAAAGCkXNdVsVhsdZKcJBgZEpZPuVweSkx0kAAAAAAAAAAAYuE4FyRJD+k1eZLcVFGe39sNc2DY6CABAAAAAAAAAGAGTctL2sfl1LgDAAAAAAAAAAAAiNtIO0guXbo0yuwBAAAAYOrRbgIAAMCoBCNI4vyZixEkP//zP29Nv3LlinK5XNTsAQAAAGDq0W4CAAAAJlfkDpKtrS39/u//ftf0V155RT/8wz+s8+fPDxQYAAAAAEw72k0AAADA5Io82sV1XX3yk59UKpXS1taWpKNvR+Xzefm+r3Q6rUQiMaw4AQAAAGDq0G4CAADo5PubR394npQqyaszmnaUTiv+R16djnl9g4hcNpVKRXfddZcuXryo7/zO75QkNRoN3X///SoWi3rkkUf01ltvDS1QAAAAAJg2tJsAAACAyRW5g+Rzn/ucXNdVtVrV7u6uJCmRSKhWq+m+++6TJN11111DCRIAAAAAphHtJgAAAIzTmdPSe5yY1+lLOox3nVFFfgfJ6uqqlpaWVKlUlM1mtb+/r1qtptXV1daLCK9duza0QAEAAABg2tBuAgAAACZX5A4SSbr//vtVr9f1j/7RP9Jdd90l13V19epV+b6vBx54gBcOAgAAAJh7tJsAAAAwLqdPS2fOxPtzeopeQhK5gySdTuvll1/WQw891JX2yU9+Uv/6X/9rvfzyywMFBwAAAADTjHYTAAAAMLkiv4OkWCxa05PJ5InzzKOVlRUtLCyEpq2vr2t9fT3miAAAAIBodnZ2tLOzE5p2cHAQczSTiXZT/2gzAQAw2xzngiTpIb0mT5KbKsrzp6c+RB34yMUb0kXDe0a+7scbyyAid5Dcf//9J87zyCOPRM1+Zl25ckWu6447DAAAAGBgtpvVnucplUrFHNHkod3UP9pMAABgkk1bHfjMKek9I3jk1d85Lf0dQ9qLh9IPfn346xyFgd5BAgAAAAAAAAAAMI0ijyABAAAAAAAAAACT68wZ6UzML00/48S7vkEwggQAAAAAAAAAAMwdOkgAAAAAAAAAAMDc4RFbAAAAAAAAAIBY+P7m0R+eJ6VK8uq58QY0486clt4Tcy/ANHU6MIIEAAAAAAAAAADMHTpIetRoNMYdAgAAAABMLNpMAAAAE+iUpNMx/0xRr8MUhTq4TCYjx3FCf2q1Wse8x9PX1tY60j3P09ramvL5vHK5nCqVSpybAgAAAABDR5sJAAAA82SaHgc2kEajoUajoUKhoEQi0Zq+u7ur7e1tpdPp1rRSqaRsNqulpaXWtPb0RqOhVCqler0u13UlSUtLS9rb21M2mx39xgAAAADAkNFmAgAAmEGnFX8vwM2Y1zeAuekgqdVqqtfrHRV9SV0VfUkql8uqVqvGvHK5nNLpdKuiL6n1rSgq+wAAAACmEW0mAAAAzJu56SAxVcKfe+455XK51v+VSkVXr17V2tqaMplM13LNZlO1Wk2FQqFj+vLysqR3v0kFAAAwTo5zIdJyvr855Egmj61s5mH7ARPaTAAAAJg3c/UOkuOazaY8z9P58+db06rVqprNpiqVinK5nM6dO9fxrN2rV69KkpLJZEdewTejbN+iAgAAAIBpQpsJAABgyp0Z08+UmKJQh+/y5ctyXbdjCHmxWFSxWJTneSoWiyqVSspkMtrd3VUymVSj0ZCkrmHngSDd5J133tG1a9cix3z27FmdPXs28vIAAABAL65fv67r169HXv6dd94ZYjQYF9pMAABgnlAHnj9z3UFSLpf16KOPhqa5rqtisahMJqO1tTXl83mVy2Xt7u5KkhYXF0OXazab1nU+/PDDA8W8ubmpp59+eqA8AAAAgJNsbW3pwoVoj2rD7KDNBAAA5slM1oHH8ZL2w5jXN4C57SAJnotbLBat862urmp1dVWe50mSlpaWJEl7e3uh8x8fRn7c888/rw984AP9B3wL34QCAABAHJ588kk98cQTkZd/6aWXBr7RjfGizQQAAOYNdeD5M7cdJLVaTclk8sTKuSRlMpnWM3WD+U3fejopv9tvv1133nlnf8ECAAAAMRv0MUW33377EKPBONBmAgAA84Y68PyZ2w6S5557Tqurqz3Pv7y83PH7+HNzg/9TqdSQIgQAAIjO9zeHnqfj2Ieaj2KdozG3VWCgL7SZAADAKATtiof0mjxJbqooz7ePWMUATunoMVtxr3NKTFGow1WpVIzP0j2uWq0ql8tJOnrRoOu6qlarHfME35Y6f/78cAMFAAAAgDGgzQQAAIBZN5cdJJVKpVVpb+d5nlKplLa3tzvmXVxc7Pjm1MWLF1Wr1Tq+EVUoFFQoFJRIJEYePwAAAACMEm0mAACAGRG8pD3On7hHrAxgLp8v8Nxzz4V+aymZTGpxcVFbW1uqVqtyXVeZTKbrpYSu66peryufzyuZTKrRaCifzyubzca1CQAAAAAwMrSZAAAAYLOzJ+3sh6cd3Iw3lkHMZQdJuVwOnZ5IJLqGgZu4rmvMBwAAAACmGW0mAAAA2KwvHv2E8Q6k1CuxhhPZXHaQAAAAAAAAAAAw84LHXsW9zikxl+8gAQAAAAAAAAAA822K+nIAAADQK8e5EGk539+MlDZNfP+pcYcAAAAAzK1Wu8LzpFRJXj033oBm3SnF/9L0KRqWMUWhAgAAAAAAAAAADAcjSAAAAAAAAAAAmEWnFX8vQNwjVgbACBIAAAAAAAAAADB36CABAAAAAAAAAABzh0dsAQAAAAAAAAAwi84o/l6AKep1mKJQZ8PKyooWFhZC09bX17W+vh5zRAAAYBb5/qYxzXGeiZSn41yIvE7Mpp2dHe3s7ISmHRwcxBwNZgVtJgDAPDPVuSelrh0Wnym2UW3LuMuIOvBsoYMkZleuXJHruuMOAwAAABiY7Wa153lKpVIxR4RZQJsJAABMsqmrA59S/C9Nn6IXe0xRqAAAAAAAAAAAAMNBBwkAAAAAAAAAAJg7PGILAAAAAAAAAIBZdFrx9wLE/UivATCCBAAAAAAAAAAAzB1GkAAAAMwZ338q4nKbQ45kdjjOhdbfD+k1eZLcVFEv6h7KDQAAAD2b9LpjP/GNalsmvYwmDiNIrBhBAgAAAAAAAAAA5g4jSAAAAAAAAAAAmEVnFH8vwBT1OjCCBAAAAAAAAAAAzB06SAAAAAAAAAAAwNyZosEuAAAAAAAAAACgZ6c0kpem77wi7fxReNrB4fDXNyp0kAAAAMwgx7lgTPP9zRgjmR09l6nnSamSvHpOct0YIhs9jicAAIDoHOdS6HTffyzmSIDhWb/v6CeM95aU+u04o4mODhIAAAAAAAAAAGbRacXfCzCCESujwjtIAAAAAAAAAADA3GEEScxWVla0sLAQmra+vq719fWYIwIAAACiekHf9V3fFZpycHAQcyyYFbSZAADAJNvZ2dHOzk5oGnXg6UMHScyuXLkid0aeRQ0AAIB590F96Uu/HprieZ5SqVTM8WAW0GYCAACTzPaFjYmsA/OILSsesQUAAAAAAAAAAOYOI0gAAABmkO9vGtMc50Kk5eZdr2X6kF6TJ8lNFfWi7pmJMp2FbQAAABgX339s3CFMlKDu3F5v9vzieIOaZacV/4gORpAAAAAAAAAAAABMLkaQAAAAAAAAAAAwi3gHiRUjSAAAAAAAAAAAwNyhgwQAAAAAAAAAAMwdHrEFAAAAAAAAAMAs4hFbVnSQAAAAzBnf3xx3CGPlOBeMabay6Xk5z5NSJXn1nOS6kWIEAADA9DHVF+e9/n1cqzza683AmPCILQAAAAAAAAAAZtHpMf0YNJtN5fN55fP50PRKpaJUKiXHcZRKpVSr1brm8TxPa2tryufzyuVyqlQqfRRIJ0aQAAAAAAAAAACAkarVaioWi6pUKspms13p29vbqlaryuVy2t3d1fb2tjKZjKrVqtLptCSp0WgolUqpXq/LvTVif2lpSXt7e6F5noQRJAAAAAAAAAAAYKTS6bTK5bIx/fOf/7yq1aqy2awKhYLq9bokqVAotObJ5XJKp9OtzhFJrZEkUdBBAgAAAAAAAADALApe0h7nT4SXtNdqtY6OEElyXVeu66rRaEg6ejxXrVZTJpPpmG95eVmSVCqV+l4vHSQAAAAAAAAAAGBs0um0kslkaFow/erVqx3/B4LRJNVqte/18g4SAAAAAAAAAABmUTCCpA/XD49+onrnZvRlj2s0Gq3HZwUjSRKJhHHeftFBErOVlRUtLCyEpq2vr2t9fT3miAAAAHrjOBes6b6/GVMkg4paBabqfNzOzo52dnZC0w4ODmKOBrOCNhMAYFqZ6sOmevT01J/Rbh7qwFuedKE+7iikSqWiZDLZevn67u6uJGlxcTF0/maz2fc6aOXF7MqVKx0vkAEAAACmle1mted5SqVSMUeEWUCbCQAATLKpqwNHGEHy5AelJwbYjJfekB7+dPTlA1tbWx0vdV9aWpIk7e3thc5vekSXDR0kAAAAAAAAAABAknT29NFPVLcPodchn8/r4sWLHZ0ewd+mkSJROkh4STsAAAAAAAAAAJgIpVJJmUyma1Tx8vKypO53jQT/Rxm9QwcJAAAAAAAAAACz6PSYfiKqVCqSpHQ63THd8zwlEgm5rqtqtdqRVqvVJEnnz5/ve308YgsAAAAAAAAAAIyc7UXqtVpNW1tbyuVyKpVKren1el2pVEqu6+rixYtKpVJqNBqtR2oVCgUVCgUlEom+46GDBAAAYM44zrPGNN9/wrLkrFQdFyIt5ftPGdMc50Lr74f0mjxJbqqoF3WPfH8z0voAAAAwG2a9PtheF243qu2Oe31TL8JL2oeyzhCe56lYLEqSLl++rEwmo3Q6rUQiIc/zlMlkJEm5XK5r2f39fUmS67qq1+vK5/NKJpNqNBrK5/PKZrORQp2VVi4AAAAAAAAAAJhQruuqWCy2OkmOp/m+33M+5XJ5KDHxDhIAAAAAAAAAADB3GEECAAAAAAAAAMAsmqBHbE0iRpAAAAAAAAAAAIC5wwgSAAAAAAAAAABm0WnFP6JjikaQ0EECAAAwpRznwrhDmFJ3Dj1H39989x/Pk1IlefWc5LpDX5dk3/cdsQAAAGDsTHW3sHpbP/OOg+Nc6poWd2yTUhaYDXSQAAAAAAAAAAAwi3gHiRXvIAEAAAAAAAAAAHOHESQxW1lZ0cLCQmja+vq61tfXY44IAAAAiGZnZ0c7OzuhaQcHBzFHg1lBmwkAAEwy6sCzhQ6SmF25ckXuiJ5FDQAAAMTJdrPa8zylUqmYI8IsoM0EAAAm2dTVgXnElhWP2AIAAAAAAAAAAHOHESQAAEwBx7lgTPP9zRgjmR2zUKZR43ScZyKu8UbE5SaL7z9mTJuW4yLuWKalXAAAmEWmz2E+gyfPPOwrW136uHkoj6nACBIrRpAAAAAAAAAAAIC5QwcJAAAAAAAAAACYOzxiCwAAAAAAAACAWXRaI3nk1c7vSDv/v/C0g28Of32jQgcJAAAAAAAAAADo2fpfOvoJ470qpf7HeOOJikdsSWo0GuMOAQAAAAAmFm0mAACAKRW8pD3Onyl6SftcjiBxHKfjf9d1Va/XW/97nqetrS0lk0k1m01lMhmtrq52LNPLPAAADIvvb447hJkz62XqOBfGHcLEcpxnLKlzWT0+0ayfL+hGmwkAJgefw9PDtK9MdfNp3LeOc6lrmu8/Zpj73tEGAwzB3LUAS6WSstmslpaWWtPS6XTr70ajoVQqpXq9Ltd1JUlLS0va29tTNpvteR4AAAAAmEa0mQAAAGZIMIIk7nVOibnrICmXy6pWq8b0XC6ndDrdqsRLUj6fVy6Xa1Xke5kHAAAAAKYRbSYAAADMi7l6B0mlUtHVq1e1tramUqnUld5sNlWr1ZTJZDqmLy8vSzr6JlUv8wAAAADANKLNBAAAgHkyVx0k1WpVzWZTlUpFuVxO586dU61Wa6VfvXpVkpRMJjuWC771VK1We5oHAAAAAKYRbSYAAIAZc3pMP1Nirh6xVSwWVSwW5XmeisWiSqWSMpmMdnd3lUwm1Wg0JEmJRCJ0+Uaj0dM8Nu+8846uXbsWeRvOnj2rs2fPRl4eAAAA6MX169d1/fr1yMu/8847Q4wGcaHNBAAA5hl14PkzVx0kAdd1VSwWlclktLa2pnw+r3K5rN3dXUnS4uJi6HLNZrOneWwefvjh6IFL2tzc1NNPPz1QHgAATCLHuWBM8/3NGCOZLFHLxZbmOM9GjOaOiMtNmhtDz7F9Pz2k1+RJclNFvah7pvb43dra0oUL5uMPs402EwAAw9NPfXDy646vdk0xtVlM2xLM315v9vzi0CIcxEzWgXlJu9VcdpAEVldXtbq6Ks/zJElLS0uSpL29vdD5k8lkT/PYPP/88/rABz4QMWLxTSgAAADE4sknn9QTTzwRefmXXnpp4BvdGD/aTAAAYJ5QB54/c91BIkmZTKb1TN2gom76RlMymexpHpvbb79dd955Z7RgAQAAgJgM+pii22+/fYjRYJxoMwEAgHlBHXj+zH0HiSQtLy93/D7+TNzg/1Qq1dM8AAAAADBLaDMBAABMKR6xZXVq3AGMW7VaVS6Xk3T0EkHXdVWtVjvmCb4tdf78+Z7mAQAAAIBZQZsJAAAAs2puOkg8z1MqldL29nZrWqVS0eLiolZXV1vTLl68qFqt1vFtp0KhoEKhoEQi0fM8AAAAADBNaDMBAADMoFM6GtER588U9TrMzSO2ksmkFhcXtbW1pWq1Ktd1lclkVCwWO+ZzXVf1el35fF7JZFKNRkP5fF7ZbLaveQAA6JfjXDCm+f5mjJGMxyRt4yTti6jrm6RtGETc2zFNZQMMG20mAJguYfWkUdZlTPUy6k8wHQOOc8k+v+dJqZK8em5UoQEnmpsOkkQi0TXE28R1XZXL5YHnAQAAAIBpQZsJAAAA82ZuOkgAAAAAAAAAAJgrZxR/L8AU9TpM0dPAAAAAAAAAAAAAhmOK+nIAAAAAAAAAAEDPTiv+XoDTMa9vAIwgAQAAAAAAAAAAc4cRJAAAAAAAAAAAzKIRjSDZ+ZdHP2EOvjH89Y0KHSQAAEwI398cdwhTyXEuRFrOVt7Tsi9s227bBsd51rLcE5Y1HvQS1lCNZl/cEWkpx/mUMa0jTs+TUiV59ZzkupHWBQDAvAur50xLHS0ucZfHNJa/qb48ydsy6TH3F8eroVODbXxIr8mT5KaK8vzi4MEhVut/7egnjNeQUvl444mKR2wBAAAAAAAAAIC5wwgSAAAAAAAAAABm0SnF/9L0KRqWQQdJzFZWVrSwsBCatr6+rvX19ZgjAgAAAKLZ2dnRzs5OaNrBQfyPZMNsoM0EAAAmGXXg2UIHScyuXLkil2dRAwAAYAbYblZ7nqdUKhVzRJgFtJkAAMAkm7o68BnF3wswRb0OUzTYBQAAAAAAAAAAYDimqC8HAADEyXEuGNN8fzPGSOwmKZZJMpr9dyPicpPm7YjLvW5McZxnWn8/pNfkSXJTv6QX9Vn5/lMR1wcAwPya5DqeqZ4VFnM/8w5D3OubdKPc7rCy7nd9tjr7pHKcS13TfP+x0HlPLA/Pk1IlefXcMEIDIqGDBAAAAAAAAACAWXRa8fcCxP1S+AHwiC0AAAAAAAAAADB3GEECAAAAAAAAAMAsOqX4R3RM0bCMKQoVAAAAAAAAAABgOBhBAgAAAAAAAADALOIdJFZ0kAAAYuc4F4xpvr8ZYySwmaR9MUnHzChiGUWetuUc51nLck8MPZajdU7OPpTuGEGeC21/n237vRAy7/SZrP0HAMB49fPZF/fnJJ/L8RlGWU/j/vL9x8YdAjBUPGILAAAAAAAAAADMHUaQAAAAAAAAAAAwi84o/l6AKep1YAQJAAAAAAAAAACYO1PUlwMAAAAAAAAAAHp2SvG/NH2KhmVMUagAAAAAAAAAAADDwQiSmK2srGhhYSE0bX19Xevr6zFHBADx8/3NcYcwdRzngjFtHspzkrZxFLFEzdO2nO2YsVUB7cs9cEI8P2FJm5x9aOM4z1hS77Wkfa3t7+ttvw8GjmkSmPbfzs6OHOc/Nyx1Y3QBYabRZgIAjFpYnXeU9VVTHTtsnf3MOw6O89muab7/YcO8l0Kn+/5jQ40pbjs7O9rZ2QlNOziYjfr/PKGDJGZXrlyR67rjDgMAAAAY2Pr6uj7xiTcMqa9JKsUZDmYEbSYAADDJbF/Y8DxPqVQq5ohOcFoj6QXYqRz9hDm4Hj59EtFBAgAAAAAAAAAAera+evQTxvt3UupjsYYTGR0kAAAAAAAAAADMojOKvxdginodeEk7AAAAAAAAAACYO1PUlwMAAAAAAAAAAHo2oneQnLjOKUEHCQAAU8D3N8cdwlA4zgVj2qxs46SwlafjPGtZ7gnLcs8MFNPkWLCkHVjSXu0x/xttv2/YZpwJpmPt6AWVvKQdADAepnondU5IwzkOwo4xU779re/eiBHFw/c/3DXNcS4Z5n0sdHpQdg/pNXmS3FRRnl8cWoxAP3jEFgAAAAAAAAAAmDuMIAEAAAAAAAAAYBadUvyPvJqiYRlTFCoAAAAAAAAAAMBwMIIEAAAAAAAAAIBZxEvarRhBAgAAAAAAAAAA5g4jSADMDce5YEzz/c0YI5kPlPd0iHs/se+Hy3GetaS+bUmLWgVciLjcpLnTkrZnSbOV22Lb319vm/beXoMCAMwgx7nUNc33HxtDJPNnHPXOsLo19d/Z1c++NbW7pvH4CLuuSa/2lUdruz1PSpXk1XODBwZERAcJAAAAAAAAAACz6Izi7wWYol4HHrEFAAAAAAAAAADmzhT15QAAAAAAAAAAgJ6dUvwvTZ+iYRl0kMRsZWVFCwvhz+9eX1/X+vp6zBEBAAAA0ezs7GhnZyc07eDgIOZoMCtoMwEAgElGHXgwzWZTW1tbkqRCodCV7nmetra2lEwm1Ww2lclktLq62vc8vaKDJGZXrlyR67rjDgMAAAAYmO1mted5SqVSMUeEWUCbCQAATLKpqwOfVvy9AIYRK7VaTcViUZVKRdlstiu90WgolUqpXq+36oNLS0va29trzd/LPP2YosEuAAAAAAAAAABgGqXTaZXLZWN6LpdTOp3u+LJMPp9XLpfra55+MIIEwNzw/c1xhzBXopa341wYep4wG0WZ2vahjS0Wx3nGstxTkWKZpOMpepwPWtJesKSFP7rmZO+LuNykedmSdocxxfefMKZ17sO9tt/f0k9gAIAZ4/uPjTuEmWKqM01KvS4sjkmPGdGF7dt52K9c1zAqzWZTtVqt67Fby8vLkqRSqaTz58+fOE+/o0gYQQIAAAAAAAAAwCwKHrEV50+El8JfvXpVkpRMJjumByNFqtVqT/P0ixEkAAAAAAAAAABAknT9unT9G9GXf+dP+1+m0WhIkhKJhDG9l3n6RQcJAAAAAAAAAACzKBjV0YetZ6ULPz+SaIx2d3clSYuLi6HpzWazp3n6RQcJAAAAAAAAAACQJD35X0lPfDz68i/9gfTw/7W/ZZaWliRJe3t7oenJZLKnefpFBwkAAAAAAAAAAJAknT179BPV7d/a/zJB54ZpFEgymexpnn7RQQIAmCi+vznuEEbKcS4Y02Zl26NuR9Syib7cM5blnhr6cqPxgiXNVs17O+L6Xom43KR5wJL2SlxBAADQwVanOW5W6o3zgH01u/rbt/f2Me+r/YYCWPmnJD/CS9MHXWe/lpeXJXW/RyT4P5VK9TRPvyKECgAAAAAAAAAAMByJREKu66parXZMr9VqkqTz58/3NE+/GEECAAAAAAAAAMAMOjwtHcbcC3BoGbFie5H6xYsXlUql1Gg0Wo/LKhQKKhQKSiQSPc/TDzpIAAAAAAAAAADASHmep2KxKEm6fPmyMpmM0ul0q2PDdV3V63Xl83klk0k1Gg3l83lls9lWHr3M0w86SAAAAAAAAAAAmEE3xzCC5KZhBInruioWi61OEtM85XLZmn8v8/SKd5AAAAAAAAAAAIC5wwiSmK2srGhhYSE0bX19Xevr6zFHBEwfx7mgh/SaPEluqqgXdc/Aefr+pnV9UZaDma1MbeIu76j73r59s/HRO4qyibp/ox8XN4wpUY/RqEax7Y7zjGXJ91qWs237vScHNRW+Zkm7z5jiOM9almsv06/f+r0oW1nPgp2dHe3s7ISmHRwcxBwNZgVtJswSx/ls1zTf/3BfedDmeBdlcTJTXY6yi244Zfpqz3lP+r5ynL2uab6/aJjX3q5qv7fj+eYRBZOGOvBsmY27NFPkypUrcl133GEAAAAAA7PdrPY8T6lUKuaIMAtoMwEAgEk2bXXgw9OObpx2Yl6nL8mPdZ1R8YgtAAAAAAAAAAAwdxhBAgAAAAAAAADADDo8fVqHZ+IdJ3F4+qZsj7WeJIwgAQAAAAAAAAAAc4cOEgAAAAAAAAAAMHd4xBaAqeP7m5LnSamSvHpOanuJp+P8mmXJVyKu8Y6Iy8HE9zeNaY5zIcZI7KLGaVsuKsd5xrK+p4a+vpNMVtkM/5ixb595X8TNvu22at5exOUW7AFNDfN2+P5PGNPs+/7ttr/32n5/Sz+BAQCmlOkzuZ+6zyjqSdOsnzoeZfeucZRF2L7qN45h5DEq/cTR77UgbP5hXE9GyfcXu6aZz9d7DdNfHVo8ONnN06d1eDrecRI3TzviEVsAAAAAAAAAAAATig6SHjUajXGHAAAAAAATizYTAADA5DnUKR3qdMw/09PtMD2RDkmlUlEqlZLjOEqlUqrVaqHzOY7T8bO2ttaR7nme1tbWlM/nlcvlVKlU4ggfAAAAAEaKNhMAAADmxVy9g2R7e1vValW5XE67u7va3t5WJpNRtVpVOp1uzVcqlZTNZrW0tNSa1p7eaDSUSqVUr9fl3nr3wdLSkvb29pTNZuPbIAAAAAAYItpMAAAAs+VQp3VDp2Ne5/SYqw6Sz3/+86pWq63/H330UaVSKRUKhY7KfLlc7pjvuFwup3Q63aroS2p9K4rKPgAAAIBpRZsJAAAA82RuOkhqtZoKhULHNNd15bpux7NyK5WKrl69qrW1NWUyma7Ke7PZDM1reXlZ0rvfpAIwHr7/E+MOYeY4zjOW1BvGFN/fjLS+qMvFbRRxOs6FWNc3iLhjtR2HtvVFjXN69sUdI8jzbUvatRGsbxwOIi630ON839r2exT7aDSm57jHqNBmAqKb1+uk6bNjGOUx62U6yrIbVL+xzev+dpxLXdNM29FPmYblO0kc5wtd0/rdf7Z6J6bHL+9c1y/vfCM07esHfszRRDc37yBJp9NKJpOhae3Tq9Wqms2mKpWKcrmczp071/HM3atXr3YtI6n1zSjbt6gAAAAAYFLRZgIAAJg9N3Vahzoz9J+fWv9W/eaXzoX+lK7cOe7N7tncjCAxaTQayuVyrf+LxaKKxaI8z1OxWFSpVFImk9Hu7q6SyWTrm1OJRMKYn80777yja9eif/vy7NmzOnv2bOTlAQAAgN7cUDBSMEr99Z133hlyPBgX2kwAAGBeXL9+XdevX4+8PHXg6TPXHSSVSkXJZDJ0eLfruioWi8pkMlpbW1M+n1e5XNbu7q4kaXFxMTTPZrNpXefDDz88UMybm5t6+umnB8oDAAAAONn/Kul5SdJdd/3seEPB2NBmAgAA82Rra0sXLszWI8AOdUqHsb+k/Was6xvEXHeQbG1tqVwuW+dZXV3V6uqqPM+TJC0tLUmS9vb2Quc3DUkPPP/88/rABz7Qf7C38E0oAAAAxOMvS/oBSdJbbz3Z99IvvfTSwDe6MX60mQAAwDx58skn9cQTT0Renjrw9JnbDpJ8Pq+LFy+eWDmXpEwm03qmbjC/6VtPJ+V3++236847p+cZbAAAAJhXZxQ0F6LUX2+//fYhx4O40WYCAADzZtBHdVIHnj5z2UESPCM3eElgL5aXlzt+H39ubvB/KpUaUpQAJsfBuAMYOceJOnx0Lj9GRsb3N2NfZ/R9H3V9z1hSbxhTopbNKJaLexvsFixpo7h2vWcEeY7DeWOK/ZywXfMebPs7GE5+j6T7eo5q3MZxDcLkos0EjE6/9a9Jvj5PSmxhZTopsZlMcnyTHFu/TOfbcLbx1ZD1XTLMe2/o1LjbY8PxmZBp7w+d01QerfL3PClVklfPhc53lMf0nd+T5ugl7fE+YuvmFD1i69S4A4hbpVKRJKXT6Y7pwXDwMNVqtfVSwkQiIdd1Va1WO+YJvi11/ry5wQ0AAAAAk442EwAAAObFXH31t1araWtrS7lcTqVSqTW9Xq+3vsX0+OOP69FHH9XGxoako8bB4uKiVldXW/NfvHhRqVRKjUajNTy8UCioUCgokUjEt0EAAAAAMES0mQAAAGbLzTG8pP2mDmNd3yDmpoPE8zxlMhlJan2zqd3+/r4kaXFxUVtbW6pWq3JdV5lMRsVisWNe13VVr9eVz+eVTCbVaDSUz+eVzWZHvyEAAAAAMAK0mQAAADBv5qaDxHVd+b5/4nzHh4Hb8iuXy4OGBQAAAAATgTYTAAAA5s3cdJAAAAAAAAAAADBPbuiUbsT8iK0bU/Tq8+mJFAAAAAAAAAAAYEgYQQJgYI5zwZjm+5sxRhKd43zKmOb7T41knW6qKO/W7xd1z7F1Dr/cpmU/Oc4zltQbxpSo2zCKcrHlGZ3tI9tcLlL07bAtF3UbbefTKMrNnqe5TG1xTtY22LzXkvY+S9qXLWmLEWOZNC8YU+zH/bOWPA/a/v562++DkHkBAOg2SXXySWWqF1F202OW9mFYzP3W3YeRR/zuHTiHYBsf0mut+yKeXwydt58ymsbjKA43dUaHMXcDTNNL2hlBAgAAAAAAAAAA5g4jSAAAAAAAAAAAmEE3dUqHMb+D5OYUjcuYnkgBAAAAAAAAAACGhA4SAAAAAAAAAAAwd3jEFgAAAAAAAAAAM+hwDI/YOpyicRl0kMRsZWVFCwsLoWnr6+taX1+POSJgcL6/GWk5x7kwQXm+ZwR5xm+SYrXFIt0RKc9RbIMtT8d5xrLcU0OPxe6GMeWkcrFvR7QynazzfvjbZ1+f7dgefp72Y/SzEdd4r2V9Hx3B+ibN9xhTHOdTluXutKQttv29d+v3Xcem92eyPifD7ezs6BOfeNqQar5uATa0mWASdg2btPp4b8yfw7Az7e9JPjZMn739xDeMPCZF3DHHX0YfNEz/vj7ymL5rhKmd4PuPGeYfrE01jmO/M+YXJL2gBx/8z7vmOzg4iC0mDAcdJDG7cuWKXNcddxgAAADAwNbX1/WJT7xhSH1NUinOcDAjaDMBAIDJ9kFJH9SXvtTdUeN5nlKpVPwhWRzqtG6MYARJeedNVXb2QtOuH9wc+vpGhQ4SAAAAAAAAAADQs7X1u7W2fndo2r/zDvRTqd2YI4pmeh4GBgAAAAAAAAAAMCSMIAEAAAAAAAAAYAbd1GkdxtwNcDPml8IPghEkAAAAAAAAAABg7jCCBJhSjnPBmOb73S+Jmh93RFxu0Zji+49FzNPOq+ekVOno95BeRGrb97ZjJmqeo1jOxnGesazvqYh5RjuXOAejMlc97Mfoey1pNyx5RjtmHOdTlvWZjea4j3buSg9Y0u6MmOesOLCkvc+S9kVL2jfb/n6t7Xf06vYojqdRXNdMaUcvqOQl7QCOhF1j+r3OzU4d695xBzBzZufYCDfr2ycNfo1wnEuGlFdDp46uTE3rM99z6DYP14hgG4O2nK29Nxmm+Tw81GkdxjyiI+71DYIRJAAAAAAAAAAAYO4wggQAAAAAAAAAgBl0U6diH9Fxc4rGZUxPpAAAAAAAAAAAAENCBwkAAAAAAAAAAJg7PGILAAAAAAAAAIAZdDiGR2wdTtG4DDpIgCnl+5vjDmFgtm1wnGcsyz1lyfXtiNHcGXG56NxUUd6t3y/qno40e9lciLS+URwzUWOJLtrH1ijijL6Pon70LlhiecK6pO2ciXquTc9xeMOynHnbbcvZ9mHUPKMfTw9Y0szHjHTNkmbznojL2dm2cTSfd7bPij1jin0/fbrtv/906/fdkt7XT2BjNfzPnteiBwNg5gzjeh52LRplu2hU6/P9D09EHLPO9NlF2Z1sGGUXd/n7/mN9zT+M8yp8G+/tK49wLxim93ftiNf3hU411yE/cuv3Hbd+f3dfa+P8xjDRQQIAAAAAAAAAwAw61GndiH0ESbzrG8T0jHUBAAAAAAAAAAAYEkaQxGxlZUULC+GPvFhfX9f6+nrMEQEAAABRvSDzYyBsj6oDzGgzAQCASbazs6OdnZ3QtIODg5ijwaDoIInZlStX5LruuMMAAAAAhuCDt37CvCapFGMsmBW0mQAAwCSzfWHD8zylUqmYI7K7qdM6jLkb4CaP2AIAAAAAAAAAAJhcjCABppTjfMqY5vsfj5jnBUuem5GWi858eXKcC3pIr8mT5KaKelH39LScnflbio7zTMQ87R6ypNnXeYclLd6hnLbjIqrRHE9mUbch6vkSNU/p7YjL2ePx/adOCmuoou5f+zaM4ji0nYPhj305Yj4Ho15H7cs9a4nF5n0RlxvNN7pHsQ/t/pwlzXyNtR+/3xM5mijri7vMoqzv6NtzjCABMDz9XIvCrqH9XstGda11nC8YUj4zcBxuqtjVTjItb/qcGcZ2D6P8BxV//SJc3HEMoz01ypj7Oe76m/eSYd7H+oiuX2GjaF8NndN03vv++4cYT1zCtvHTEfN4/djv3ozqOjWsvCfNoU7F/tL0wykalzE9kQIAAAAAAAAAAAwJI0gAAAAAAAAAAJhBR+8giXcECe8gAQAAAAAAAAAAmGCMIAEAAAAAAAAAAD379Z0/0r/Y+Q+had84OIw5mujoIAEAAAAAAAAAYAYd6pRujOCRVz+8fr9+eP3+0LSG95Y+mfqdoa9zFOggwdxxnAvWdN/fjH2dJvZY9qIFY2W+JIxiGxznU5YlX7fn6XlSqiSvnpNcty3PaHFKd1jSbljSbJdR23LR+f4TQ8/TXm5Rt/G9ljTz/o26Psd51phmPw6fsSz3lCUWs6h5Rr3+2NZ3cvqCJe3tSPFEP2bM52Hc22A/ZszHmv0YvWRZLuq2f58lbdGS9oBlfbbrwY9a0k5aZ7zs2/G3LWkvR1zj19r+frPt97dGzG80dRIAGBbTdXZSrl39xGH+zLg3JN/HIkbU7jOhU00xh8Vnmter50LbSf2sb1T6PWb62W68axxl1E87fFTx9XtuhsXR/3XthZBpH+ljXkl6fx95TIqw+Pq7rrV4npSSvPoPDh5Wn7ieIEAHCQAAAAAAAAAAM+hQp3UYczdA3C+FHwQvaQcAAAAAAAAAAHOHDhIAAAAAAAAAADB3eMQWAAAAAAAAAAAz6KZOx/7Iq5s8YgsAAAAAAAAAAGByMYIEAAAAAAAAAIAZdKhTsY8gOZyicRl0kMRsZWVFCwsLoWnr6+taX1+POaLp5TjPGNN8/ynLkt8zwDo9yzpdy5IftCz34YjRmJdznAuW5Wyn/XlL2j+zpH2fJc3m4+ak8NNkdB58jznty7Yyu2FJO+kS+61tv+84lva2cSn7/rWxxWNOs59PZrZzNCrf37Ss79mIsZj3YfSytuUZ7do1WHnajtMDS9p7LWmvW9KinsDm495+/NqWs23Dnj0cI1uZ2c6lx4xpUY9RLaTNaQfmzyx9253GJP8/Ws6z6anjnnC9sO37Vyxp/40lrf04/H1JPyvp/yzpL1qWsV9nbNswKXZ2dvSJTzxtSLVdewAz2kyj5zifDZ1uaps4zqWQeeO/RoXFbY6593nN7bUXeoysX+b2YZhJ+DwwfV6ZYusn5n7yjl4/t+dr0u929xPfMPZr+Lnc33HbTznHfSwOY1/1k3e/2xdedt3XS5vwuD/SVx6T4d7Qqc5PGWb/x0f18Yf0ljxJbuotef5oIhuFnZ0d7ezshKYdHNjai5hEdJDE7MqVK3Jd2410AAAAYDqsr6/rE594w5D6mqRSnOFgRtBmAgAAk8z2hQ3P85RKpWKOyO5Qp3Uj9hEkvIMEAAAAAAAAAABgYtFBAgAAAAAAAAAA5g6P2AIAAAAAAAAAYAbd1GkdxtwNcJNHbAEAAAAAAAAAAEwuRpBgojnOMxGX+5Ql9T3RghnI3gjyPLCkmU9t33/KmOY4n7bk+aAl7QctaTZfMCcdfIcxyXF+UQ/pNXmS3FRRL+qettSPRAvlRyxpX16wJNrSTtrv19t+H9+fd1iWs+37G5Y0W6xvG1Mc55Ixzfcfs+S5aEl73ZJm3gb7NcG2fbZYbPvJlqeNuTzt56Dt2hW1PE8StWyiHqO2MrVVS+6zpF2zpNm2wXasXbAsZ4sz6vFrO3cfMCcd2K7b32NOeqNmTHKc3zMv96D5+D1a1lxuvr9pXTZets/JJ4xpjmM71t5s+/uttt9vynae2colannGvR9MeR69oJKXtAODsH8eHXdv6NTw+toLhvW92lfe/XCcz3ZN8/0P95VH2Pz9lVH4+kxxOE54OYXPGx5H6DXynGl9pnp3934xXXvd1GdutZM+oxfl3ZrXVmfvVX/HQPi2mI7R8G3pb9/2nu8w8uhnf/e7HWHzm7el92O0n/WNUl/nijGP7uOr3/3dz3abj4Pu65pkON/OGfIOaa44zijuIQ3Rufd3T9v/TPi8f2zKJEh4/djv+AzjWJwWhzoV+0vTDy3jMiqViqrVqhKJhBqNhpLJpAqFQsc8nudpa2tLyWRSzWZTmUxGq6urI4mVDhIAAAAAAAAAADBSlUpFW1tbqtfrrWmZTEb5fL7VSdJoNJRKpVSv1+W6riRpaWlJe3t7ymazQ4+JR2wBAAAAAAAAAICRKhaLWl5e7piWyWRUqVRa/+dyOaXT6VbniCTl83nlcrmRxEQHCQAAAAAAAAAAM+joJe3x/phe0r63t6darfORz7u7u0omk5KkZrOpWq2mTCbTMU/QqVIqDf8RvnSQAAAAAAAAAACAkcrlcmo0GlpbW5N09K6Ry5cvtx6vdfXqVUlqdZgEgtEk1Wp16DHxDhIAAAAAAAAAAGbQzQgvaf/m9UPduH4YeZ1/+k74stlsVvV6XaVSSUtLS0omk/rqV7+qRCIh6ej9I5Ja/x8XpA8THSToi+NcMKb5/mak5aQ7LGnvs6Q9GC1P5/2W5U5wzj15njA/9BPR12ny4A8ak/wvmdPs+8K8D6XfNif9LXOSdX1/z7K+L5qT/Oqm5HlSqiSvnpPanknoOJ55QYubTzrGtFM//28tS16LtL4j79z6faekxWNpBxHzvNeS9rWIeX7TmOI4z1iWW7CkPWBJs5Xp68YU33/CmOY4n7LkaYvzbUtatI9Qx7kUaTm7k2KxbeNexHXajlHb+mzXddsxasvTttzxc6td1PPM5j5L2iuWNNv2vWxJ+2DEWGy+Yk76FvuStrpAVFHrHlY/cGe05dKW5Wrt+3D/1u97dNJ+cBzL56s+0ltcACaS+foVdm6/apjXdp0/zlYP7G1e338sdPpw6i/9xBcurExNnwWO03sdxzE2Bfq5Dve+r87v/Wro9MuO6Tjop+xeb/sdtb7aTznb2pdx6r2MzMdzd/mbtnsUdZ53dW+LuZzDjrsXes73SO/bbYojbP7+Yg7Xz74yr++nQ6eGx/zZHiOzMcUcfn0NF96G6ed8G+kxuv+Fntdn3odBedy49fs7jasLvUb/Wvi8/o8bs+medwhlFL5PXhs430nwr7d+X5+98OJI8i4Wi7p69ao8z1Oj0VCtVtPq6qqko8dtSdLiYvh50Gw2hx4PHSQAAAAAAAAAAMygGzqtG32OIHnkSVcPP/EXI6/z1Zfe1C8+/M9C0zKZjHK5nJLJpNbW1rS2tqZyuazV1VUtLS1JOnpXSZjjj94aBjpIAAAAAAAAAACAJOnM2dM6c7a/TpV2t93+ntDpuVxO0tGjtiTpq1/9qu6//349/vjjWl1d7XhZexg6SGbAysqKFhbCH6Oxvr6u9fX1mCMCAAAAotnZ2dHOzk5o2sHBKB5jh3lAmwkAAEyyd+vA/zEk9UbINAQuX77c6hyRjt41UigUlMvl5HmelpeXJXW/ayT4P5VKDT0mOkhiduXKFbluxPdYAAAAABPEdrPa87yRNGAw+2gzAQCASRbUgc3vICnFHZLVTZ3WYczdADcNj/RaXFzsGh2STqclHXWWJBIJua6rarWqjY2N1jy1Wk2SdP78+aHHemroOQIAAAAAAAAAALTJ5XK6fPlyRydJpVKR67qtx2ddvHhRtVqtYxRJoVBQoVBQIpEYekyMIEEXx3nGkvqDluVqluX+tjnpc99hTvtdS5Y2H7tuTLr5LY51Ucf5h8a0P+//qGU58/Z/0F+2LPe/WaIJf7SAJK345qUc55olz7Q56Ycsiz1t3vd/+6+EP1pDkn7pl99rTPvAs+Yd/NIXvt+Y5jjP6iH9sTxJbuqf6EX91ruJDzxhXM7ma4t3GdOy/lVj2s/qSWPa6cND6zr/6plP3frrOyX9hWOp5n1v92VL2vssabb1vWxJMx8X0m9b0h60pNmYtyH8mxuBByxp4S/+OvI9xhTf/6gllmcteb5qSTOfL1L8j6rx/aeMafbPCtux9krE9dn27x2WNFu5vW1JszGvz35c2Mos6v61Hb8WD3ynOe3l8BfpSZJetK/PcX7RkmrbT+Z94fublvXZjgsbc55Wn7MlttcDguvm70l6U9KHLctZ9v3nbPUu23XmXstytvra1yxprxhTbOcuMK0c55IhJexz3HBNedAw/f8QMu033x8+708awvhr3ZPO//ivhs7qOJ/pmvbt/k8Z5g3f7tve7P62Zn9lJEkfMUwPi8N0ff/p7nk/ZJj11xZ7z/eHwvfVd/9Gd7vScS7oIb12qy1S1Iu65yjBtL9DvKlvC53+Wf9XQqf/5ev/pnti/XFD7tmuKY7zWcO832eY3r0t5n3S+341HRvm+MJ80DD9hZ5z8P3Hep633+PcVm/pzruf7TZ9tndvtykG07b0E7MpjrDjo798+6vXheVtWt73u68FpvnNZWeIrY/z3iT0ODhnqDvudx//vh8+r/nY7WY6J4Zy3p8znG/7vWcR9ln49E+E39tzXjTcLPv17kmNL90TOmvyN14Lz+OR3o6Zo1HUkzWC5FCndNjnS9qHsc4wGxsbSiQSWltba40Ybjab+tzn3m1sua6rer2ufD6vZDKpRqOhfD7f8WiuYaKDBAAAAAAAAAAAjFw2mz2xs8N1XZXL5Vji4RFbAAAAAAAAAABg7jCCBAAAAAAAAACAGXT0kvZ4H7Flekn7JGIECQAAAAAAAAAAmDuMIAEAAAAAAAAAYAYd6pRuTMhL2icRHSQD8DxPW1tbSiaTajabymQyWl1dHfp6HOcZS+oNS9pHLGnvN6Z8u//jxrT/1kka0163rM3qkagLWjxlTvoHJy37u+aFf9xxjGlPX/GNaX/dstwLz5iX039hTvqnCXOet/2YJc+/YU7a/ut/15i2o79jTLv0//qEMe2XXv26Me1HLXvjxS/8gDHN0b+VlLj133dL+guttP/TV6rm5b4zY0zzf+ktY9qf+Sv/wZi2+C/+1Jj21g+fNaYd+da233ecMG+737ak2c7EtCXta5a0D1rSXrGkPWBJ27OkLVjSvmhJs3kl4nJfNqZEvzbb9rVt/5k/sn3fctGT5DifsqTaytvGtty1SMs5zoWIsRxEWp/0XktatGM0+jZE9WFLmu28/g5L2l+1pC1ao7Ef328bU3x/05hmP9dsVVnLeWi5HDrOs5Y8f9qS1n7Nu37r95+R/VooSd80J1VOWNTItu9t54RtOdt1DTCLq83Ui9Aq+YPh8363/xdDp3+x/njXtK8tPx0676cN1YjXQ6ZvGj6SLvzj8OluyHTvJ8LnfcT/513T/rKhXff03w9vR/w3d3cX3n/3Znj9+Rurd4bn/ZvdeTj/i6Hd8mD454L/sZCd+D3hWVz46yEx/Fr4+vw/NrStQprNjn5fR3XEkqQPKTiIXvhSeCDO/9Jdfz3/42+Ezvs7+kuh03/57Me6pj33xe5pZi/0Ma8kvRoyzXR/ITxv33+sa5rjmOofn+4pKrvuNovjfMEwb9j2Sb4fVq8Kn9ckrC5oqueY6o1h8/dTx+y3Puo4l0Ji6N5/tunDiMNWHxyFoazvyyFthr9vqC//uiGPc7b6/MnC9p9N+Llp2lf3hk/+++Z7il0+YJj+v9/6faCj5vp9ljy6P8asLblQX+6+HiS/9Fr4vIb7lHEfo4gPHSQRNRoNpVIp1et1ua4rSVpaWtLe3p6y2eyYowMAAACA8aLNBAAAMH6HOq3DmLsB4n7nySCmZ6zLhMnlckqn062KviTl83nlcrkxRgUAAAAAk4E2EwAAACYdHSQRNJtN1Wo1ZTKdj+tZXl6WJJVKpXGEBQAAAAATgTYTAAAApgEdJBFcvXpVkpRMdj63NfhmVLVqfgcCAAAAAMw62kwAAACT4aZO33rMVnw/N6foEVu8gySCRqMhSUokEtb0MO+8846uXbO9vDZM+0uuz4jdBgAAgNG7oXdfzv5141ymuu0777wz/JAwNeJvM73r7NmzOnv2bOTlAQDAPLt+66dTr1UT6sDThzvtEezu7kqSFhcXQ9ObzaZx2YcffnigdW9uburpp5/qaV7H2TMn/r1o6//4JXPahcei5Tlpfvr7fi7Sct/+0a9GW+G+Ja1iTnr7P1mWu9eS9u/MSZ/c/EVj2sZP/o/mBc33TOT/h28xpjkV35j2vr/7NXOmP/llSX9465+vSrrZSvq3jb9tXu4+c5Is5fk5pY1pP/3XLcfLoWV9kqT3tv3+jmNpnmW591jSbDvfUqbWNBtbLLbaw53GFN//qDHNcWyxHFjSXrGkLURMs1xjrfvhVUuajTkWx3k28rI29nxt5f22Jc1W9bjDHlCk9UVNe68l7XV7OEa2bX+fJc12LtmuFf+FOek+c5L/FdeY5nzIsjpJ+k1bmZo5zgVzPP6mZblPWZb7uHm5jDFJevAJc9qXP21Z8L62v/9T2++3rdtnPe7/44cty9mOmZctaTbH87wi6TMnLnXXXT8bcX2YZeNvMz0dkvLZrinnvxR+Tb/8XX8zdPpXv/TtXdPuf++fhM778Z8Mj+/CL4RM6/Oj5Ud/uXua97fC5/0L+vdd0zYNH3NPGy477/357ml3L74ZOu+f/L8N9bz/Y/ek8z/+q6Gz/n//2kfC8/ir3ZPu+UJ4Z9tr35Psmrb5l8Mrk87fDG+XfPYLP9Q9cfH90o0bR9WIO75TOvN+SdKb+rbQPML8Lf1K6PRPajt0+vtC6h7/w8eyofN6789JqZK8ek66NWLLcbqPfUnSOcMO3w+r59o+A7uFr/OFvvIIZ6pLh9W/TZ9hHwydav+8Ps5wjIas01T+tjrOIPOatsOURz/b3U/e/cQ8DP2uL2y/+L6t7hUm5DOubpj1y6b24x93T3rw/eGz7n9fyETTfZzwNmn4PjS1Xw3n2893b4vz878XPq/xOvOFW3985ejXK1+RZGiHhNw3M35shsQmKbxMVw15/NSW9D93l9Ndd5lWOvlu6lTsL02/OUUPrqKDJIKlpSVJ0t5e+El3fBh5u+eff14f+MAHuqbfddeWcZm33nqy9TffhAIAAEA8/ktJR43at956tO+lX3rppYFvdGN6jaLN1CvaTAAAILIfe1JaDfnS1H/Zfe+2/Z5tgDrw9KGDJIKgMm/61pOtsn/77bfrzjvDvlFj/pZ9+PwAAADAKL1HwUjBKPXR22+/fcjxYJqMps0EAAAwYredPfrp0n3vNqy+Mk914Ks7n1d952po2o2DG6HTJxEdJBEsLy9L6n5ubvB/KpWKPSYAAAAAmBS0mQAAACbD4YgesfXQ+vfrofXvD037373X9Kup0tDXOQrT8zCwCZJIJOS6rqrVasf0Wq0mSTp//vw4wgIAAACAiUCbCQAAANOAESQRXbx4UalUSo1GozU8vFAoqFAoKJFIjDc4AAAAABgz2kwAAADjd6jTuhHzS9rjfin8IOggich1XdXrdeXzeSWTSTUaDeXzeWWz2Uj5+f7mkCOUfH/RmOY4F4xpf/Lf32FeTnXLGr9mTnrgw+a077Vkea856fmf+z5j2lP6h8a0L37jeywrlN5ydo1pP+pfNqb9ifMZ8zr9f2JeofMpSzQHxpRf8P9bS56ftuS5YExJXP8T82Jnv2Be3atfN6at3FMx5/n9v2ZM+uTHfs6Y5vvnJM+TUv9QXv0jkuu+G8t3mVfnf8mcJsumpxT+PEVJWtUVY9pnTv/fLCuUpN9u+/3asTTzfpLus6RZzkMr87EmvX8E67tmTHEiHr/SFy1p5uuavTy/bEl7nyXNvH3Sey1pr1vSbM9it61PksJfkHvEVqZvW9JsZWrL07aNtvXZqiy2tKjbZysz27bb2M4z2z60HWuW48n5DnPam5bFnGcs69uwpNnZ6jq2ddrqLJGrsq9Y0l62LWi7JjzQ9veZtt9nTth2z5yl5aNeFdux/YAlLeqxBvRv2G2mQfl+d5vEfI0Jn550/kHI1I+GZ/H/MbTHHjSsMsz/I3zy0/8yZOIvGPJwLnVN+p/kh87qf8iQxS+EzB+S75FXQ6c+/WvdeYRHITl3h+ed9v9517TXdH94Hh8Lyf1/DV+f/xuGOH7qN7vn3ZPkSUpJ3m9JutUUcZz/ITzvkDD+n/pL4Ss0qP2H/0v3xOXwed2DnDxJ7l+VXmx9TIbvE+2b2niG+UN9MHzyuZA2xL6pgW9qSxvyDvVCH/Oa7iWEbbepLMKn93NvxzGcQ77/WMi8tvpQ9Bj6nd80b9i2hG3HKPVTnke6jxnHMe3vjximh5xDv2loP/+k4TPhH3e3f2/7t/eFzvqNu3/REEeYfs5j07yGc/bBkG35smHefdOxayrTwdz2Znj74M8vfr5r2hf/Q/g15vN/5rtDp39Q/1X0wDDR6CAZgOu6KpfL4w4DAAAAACYSbSYAAABMMjpIAAAAAAAAAACYQTd1WocxdwPcnKJHbPGSdgAAAAAAAAAAMHcYQQIAAAAAAAAAwAw61KnYX5p+OEXjMqYnUgAAAAAAAAAAgCFhBAkAAAAAAAAAADPo6B0k8Y4gmaZ3kNBBMqd8f3PoeTrOBXPiy1+2pD1oyfU9xpSHf/6zluUWzUmOZTFJ0h8YU/7ZqTVjmu9bVmkdq2UpN4v/7rv+QaRYbJwft6UWzUnfbT6ervzff8KYZi2zv2QJ5XcsaZZDzeqPzEm/cM/95jT9kiXT37Ou8iG9duuv65IOjqVesyxp28gb1nVG8xVL2vG4271tSbvDkvZFS9q9ljTbR5otTtv6bHF+zZK2YEl73ZJm275vRlyfZN8XtmVty9nS7rSHY/ReS5qt3GzM+972Weg4NUuev21Jsx0ztrJ+nyXNdvxa+J457Q3XvJj/lDHNsXy8SpK/F7V+Yb52jaLOopdtiXuWtPssaTdC/r6hk6/Lv2VO+ovRrpUjKTNgRg3jfDG2g/Y/aJj+QsjEj4TPa65Kd/vHnzEkhNUvTG2pD4dP/q+7J/n+Yz0E9S4nrB1maH+Y8nacL4TMbFjhfx22jYbtM7WD/rlheihT+b+/a8rvKLyx8wfOvwid7uhi1zRTGXmeJ6Uk77ck3fq4Dy17Sb7fHdvR/N3b0u+5EnZemPIIW9/R/Ib9FaqfecM5zqshMZhivjTw+qTu9R3l3fs9gn72iznm3rfbrDuPfrbDzNQ+GkbMYXmH75O+pj8Yfl7pj8Mnh53L5nN2Mup4odfic4btDv3Mk969NgZ15e+0rLG7fv70g4aL/93hx90Xw8ruz4Tn8b2GKKLea8Pk4xFbAAAAAAAAAABg7jCCBAAAAAAAAACAGXSoU7rBS9qN6CCJ2crKihYWwh+xsb6+rvX19ZgjAgAAAKLZ2dnRzs5OaNrBQcTHw2Hu0WYCAACTjDrwbKGDJGZXrlyR65qf+w0AAABMC9vNas/zlEqlYo4Is4A2EwAAmGTTVgc+1BkdxtwNEPf6BjE9Y10AAAAAAAAAAACGZHq6cjDxfH8z0nKOcyFSno7zqUjrk3/SULe3Lcv+nmW5pyzLfdacFLncapa03462vn9qztNq/9PmtE/dZ0xyPmUuF2nDkvYeS5pnSTN/E9F5zjem+eYk6/F78iX2Rtvvbx5L2+thuX7XuWhJe92Y4vsfN6Y5zjOWPO+1pF2zpL3XkvY1S1r4oziO2M572/psLNcKa5ptH9nKxZbnHZa0k9Zp2/e2a7Bt3x8/ntvZYjXHMooqi/1zxBaLeRt8/wnL+p615PmKJU/z54vjWK6/tuP+nYjfzB7gsbWDXS+H7SuWtPdZ0l6xpD3c9ndwrVrUSdeYqMdM1PqDTdQ6GTDvTOeH6ZwaxvkUlvcoz1Nbffg487UkrG74WJ+RvBoy7f19zGuqYxvqyfth2xJezv2U/+ecHzDk8SM959EP3++3nGdDv+dgP/twGGUa/2dr2DkxnDhGdV0zxRx2PXGcS6FzmvdVd979bofzoZCJLxlm/rLp/seHQ6aZrqOTUh/7ju5J+7Z7GGG+cOv3V9p+h7dRfL/7Gj3Kz1jMHzpIAAAAAAAAAACYQTd1Socxv6T95hQ9uGp6IgUAAAAAAAAAABgSRpAAAAAAAAAAADCDDscwguRwisZl0EECAAAAAAAAAAB69u93flP/fue3QtMOD2zvJp0sdJAAAAAAAAAAADCDbur0SEaQPLCe1gPr6dC0Pe8P9S9T/2Do6xwFOkgwdr6/GXHJ1yMu9z0npL9iTPH9JyKucxTCL0CS5PvmNLvFiMt91JL2FWOK7z9lTHOcP7ak/ZIe0mvyJLmpol7UPW2ptsuaa076XXOS41yw5HmHJe3AkiZJ19p+7x1Lu2FcKvo5Y2bbRvv2m/n+Y5Y8P2VZ8nhZtDOXi/S2Jc12XNjWZ2Pb9wuWNNu1y7YN91rSrlnSJHu5mcvGcZ6JmKdtG83rsx3bUY9DG9//eMT1mc/t6GVmZo/lI5Hy1L7tuLd8FrwRbXVS/Ncu+/pejpj2Pkta+3G/1/b7dUnfYVnO5qTPkf5FLzMA/TKdU2HnoXnez/aVd3gel0KWN9fTwvPoPWbztnTH0b9X+5j3gyHTftEwr6k8I37OnuQn+2t39VP+kyIsPtNnUH/Hc+959FtGwzhX+lvf4OURnq/pXLO1J8Zv0OOg33Ibxjnk/0bv8zrO9/WRc9j1qz+jOr6OhF3Dwj+vzILr+evHfvdm0q+BmC7T8zAwAAAAAAAAAACAIWEECQAAAAAAAAAAM+hQp3SDl7QbTU+kAAAAAAAAAAAAQ8IIEgAAAAAAAAAAZtChTusw5m6AUbwUflQYQQIAAAAAAAAAAOYOI0hitrKyooWFhdC09fV1ra+vxxzR9PL9zXGH0DPf//AIcr1gSYtWNr7vWlLNaY7zjGW5G5Y0W5y/akk7o3cvX+1/D+Dr5iTbseY4tv1wkhttv4+X0x2WdZrL2/efirScvQwXLWl7EddnOy7M2y6FXz9PisW+Da9b0mzejrhctO3z/cciri+60RwztvVFPZ/MsdjPCdv67rWkfc2SZju2o8Vp4zi/Zkk9sKS9YMnzmmW5j50QUbR9H1X0ukDakud7jGmOY8vzK21/f2vbb9s5H79h1592dna0s7MTmnZwYDsGAbNZbzP1cx4Oox0xjDrEcK4drw4hjt63xfffHzI1bFq/eYRznEuGPEJi/seGeuv/HP45Gnfbd1TrG0a+pjzC6nX9rm9U9W1TnXN05Rx/u2EY+tmHYdP7bUv0k4f5uAs778PbEabreXgeputl758JozxXpC+E5GHaPtN+sbW3Thb3eXUcdeDZQgdJzK5cuSLXtd2EBgAAAKaD7Wa153lKpVIxR4RZQJsJAABMsmmrA9/U6dgfeXWTR2wBAAAAAAAAAABMLkaQAAAAAAAAAAAwgw51KvYRJIdTNC5jeiIFAAAAAAAAAAAYEkaQAAAAAAAAAAAwgw51WjdiH0EyPe8goYMEwBDcsKRFvcyY8/T9TcnzpNT/JK/+t6W2l3g6zoVoq3vxC8Ykx/lMpCx9f9Oa7jpP3PrrWyXdcWzZJ7rmfzce8zba0mzx2Mttz5LnUyOI5VnLch+PtD7bNoziGJUOLGnvs6S9akyJWp6DLbtgSbNto628beVmdtI2DjtPx7lkWTLaNtjKM/o+WrSk2faDjfk4lL58wrI/GHGdk8N+LflRS1r7teR62++Dgc5fAJgVs3+9s31+Hvdpw/THhhHIwMI+t8ax/waNw/T5G/e2xL2+YWz3KMsucpv9RPeGTvX90Z1XYXmb2hGOE37PITyPweKyGc7x+B19zBu+X6QXbv1+7dbvP4geDjAgHrEFAAAAAAAAAADmDiNIAAAAAAAAAACYQTd1WocxdwPcnKJHbDGCBAAAAAAAAAAAzB1GkAAAAAAAAAAAMIMOdSr2l6YfTtG4jOmJFAAAAAAAAAAAYEgYQQJgYL6/OYJc4748vWxJe68l7fUB1vmf2n6/PUA+7xrNvrgRcTnzPnScC8a0qNswmm03s2/DU0PPc7BzItqyvv+EMS3qPhzFvrexl6mN7byPl+M8Y0l1LWnvs6RdixhN1OUmzT8zptiP3z+25Pkv2/7+w1u//0DS2wNc18zXkrjPJQCYBGHXvum85r067gAkmT9LJqVM+4kjbN7o9cDh6jeOQcu/3+XjLqd+4nOcS4aU7nNoGMftcI79ew3Tw897x3mhjzw+HCWgEfjFkGmmsgvf7lZZe56UKsmr5/qKYFKuU5gNdJAAAAAAAAAAADCDjl7SPvxHbL2688/06k74l89uHnxj6OsbFTpIAAAAAAAAAABAz+5d/1Hdu/6joWlvey+rnvrpmCOKhg4SAAAAAAAAAABm0KFO6QYvaTeigyRmKysrWlhYCE1bX1/X+vp6zBEBAAAA0ezs7GhnZyc07eDgIOZoMCtoMwEAgElGHXi20EESsytXrsh1bS9UBQAAAKaD7Wa153lKpVIxR4RZQJsJAABMsmmrAx/qtA5j7gYYxTtPRmV6xroAAAAAAAAAAAAMCSNIgCnl+5vjDmHEbkRcLuplLfwxDkf2IuZp59VzUqp09LuPb0lG3feOcyHScrb12fKM+xgdxfZFZY/FfIyOqsx8/6kR5Gk7Lp6NlGfUfTia6oz5vB/FORg9z0uWVNt17UFL2hctaT94QjyTc02weyDicrayWWz7u3nr913HpvdnNMfMtOwjAPPAdE0yXY8m+TrVT2ymefstj0ENI9+4Y+5nfZNyvPS7v+MWFl+/sYXN32/5DyOPuNnr4r3x/cdC8jWV/4cHXt9wfLD3Wc+Zjv+jsntIfyhPkpv6jDyf0aMYDzpIAAAAAAAAAACYQTd1OvZHXt3kEVsAAAAAAAAAAACTixEkAAAAAAAAAADMoJs6NYYRJNMzLmN6IgUAAAAAAAAAABgSOkgAAAAAAAAAAMDc4RFbAFoc5xljmu8/FTHPC5Y8NyOl2d2IuNyrEZeLzk0V5d36/aLu6Xm5qGUTvUzjzdPGdjzZRI1zFOuznWf2WKKfn1HPw7jzjMq+n+6wpL1tTBnFNc8WS9RjbRTsx28t8rKT5TuMKY5zybLcgiXte9r+/uat339G0gO9h3XMLFy3AcCm32tS2OflNF7XHOcL4w5haOIuf9P6+qlLTcoxM6o4TGXRz/r6jS1s/mHEMel8/7Guaaa6ZNi85nynr4z63W7HGWU0OO5wDC9pj3t9g2AECQAAAAAAAAAAmDuMIAEAAAAAAAAAYAYd6pRuxD6CZHrGZdBBAgAAAAAAAAAAYtdoNFSpVCRJ2WxWiURCkuR5nra2tpRMJtVsNpXJZLS6ujr09dNBAgAAAAAAAADADDp6B0m83QC9vIOk0Wgon8+r2WyqWCwqmUx2pKVSKdXrdbmuK0laWlrS3t6estnsUGOdnrEuAAAAAAAAAABgqnmep1QqpcXFRVWr1Y7OEUnK5XJKp9OtzhFJyufzyuVyQ4+FESQxW1lZ0cLCQmja+vq61tfXY44IeJfvPzWCPDeHnudofM2YMopykSSvnpNSpaPfbRf8kzjOBWPaKMp7WtZnWy4q+/qeiZjrjUh5DnIcRi83czVhks7tWY/FfqyF1ymOvM+Sdi1iNLPis5a0By1pv2VJO2j7+w9v/f4DSW9Len9vYcUg6rXSdGzv7OxoZ2cnNO3g4CB0OnAS2kwwmaTP/MF8JnTq7GxfuH4/g/opj1kvu36YysJU/v2U3TDyMBlGHP3kG5ZHv9vRTx6Ocyl0uu8/1lO+trzjd2/ItBci5hHUF98bPZwxoA48mGazqUceeUTJZFLFYjE0vVarqVAodExfXl6WJJVKpaGOIqGDJGZXrlzp6PkCAAAAppXtZnXwrTCgX7SZAADAJJu2OvBNne7pkVcdy1z/hvzr34i8zhvvXDemBY/VOt4BErh69aokdY0qCeqH1WqVDhIAAAAAAAAAADB8e1u/pL0L/2gkeZdKJUlHHR35fF6NRkPLy8ut95A0Gg1Jar2s/bggfVjoIAEAAAAAAAAAYAbd1Km+R5Aknszqric+Fnmd11/6d3rt4e7lPc+TdDQaJJfLqVAoqNFoKJPJaGlpSfv7+9rd3ZUkLS4uhubdbDYjxxWGDhIAAAAAAAAAACBJcs7eJufsbZGXP3X7fxY6PRj9kcvlWo/QCt5FkslktLW1paWlJUnS3t5eaB7HH701qFNDzQ0AAAAAAAAAAOAY02Oz0um0pKMOlKADxDRSZNgdJIwgATCRHOeCMc33NyOl2fj+U5ZYnrUs90Sk9UmSmyrKu/X7Rd1zLN/hb2PcRrEPo+YZlW19to/QqHHa1zcacZdb1PU5zjOW1BuR8ozKvg+HH6d9fZ+yLHlgSXtfpFikr5yQno6Ua9zntnTNkvZ7xpTePyv+U9tv27riNy2fIQAwCcI+n4ZxHTXlYfo8nJVr96xsx7Qa5bE7qvWNMu9R5WGu135w4PVNjs8MIY8Xbv1+7dbvPxhCnjC5oVM63ecjtoaxzjDLy8uS1HqM1nGLi4uteY6/ayT4P5VKDStMSYwgAQAAAAAAAAAAI5ZIJJROp1Wr1TqmB6NFUqmUEomEXNdVtVrtmCdY5vz580ONiQ6SHhzvrQIAAAAAdKLdBAAAMHlu6owOY/65aXnqRqFQkOd5HZ0kpVJJrusqm81Kki5evKhardZRvywUCioUCsbHdEU1Vx0klUpFqVRKjuMolUp19VQFHMfp+FlbW+tI9zxPa2tryufzyuVyqlQqcYQPAAAAACNHuwkAAACj4rqu6vW6CoWCcrmc8vm8dnd3Va/Xu+bJ5/PK5/OtOuXGxsbQ45mbd5Bsb2+rWq0ql8tpd3dX29vbymQyqlarrZfASEe9VdlsVktLS61p7emNRkOpVEr1el2u60qSlpaWtLe31+rhAgAAAIBpRLsJAABgttzUKR3G/A6SmyeMywh7hFbYPOVyeZhhhZqbDpLPf/7zHYX+6KOPKpVKqVAodFTky+Wydefkcjml0+lWJV9S6xtRVPQBAAAATDPaTQAAAJgnc9FBUqvVVCgUOqa5rivXdTueY1apVHT16lWtra0pk8l0VdybzWZoXsvLy5Le/RYVgMH5/mak5RznGUueT0UNZyS8ek5KlY5+t908GITjXIi0nK28o+6LqMvFneco1mc7Dm37aFTbN451mtiPUXO1ZBTn7yjKxRZn1PPT7j0Rl/tyxOXui7icXdzHofQ+S9pCxDzvbPv7W9t+3xkyLzCZaDcBneL/fOqdqV7h13805kgAtDNdNxzn0sB5TLJ+Y27N73nv3hcBxmQu3kGSTqeVTCZD09qnV6tVNZtNVSoV5XI5nTt3ruN5u1evXu1aRlLrW1EnDQsCAAAAgElFuwkAAGD2HN56xFa8P9PT7TAXI0hMGo2Gcrl3eyiLxaKKxaI8z1OxWFSpVFImk9Hu7q6SyWTrW1OJRMKY30neeecdXbt2LXLMZ8+e1dmzZyMvDwAAAPTi+vXrun79euTl33nnnSFGg3GKu91EmwkAAIwLdeD5M7cdJJVKRclkMnRot+u6KhaLymQyWltbUz6fV7lc1u7uriRpcXExNM9ms3nieh9++OGB4t7c3NTTTz89UB4AAADASba2tnThwigeDYdpMo52E20mAAAwLrNYB75587QOb8b8kvaY1zeIue0g2draUrlcts6zurqq1dVVeZ4nSVpaWpIk7e3thc5vGo7e7vnnn9cHPvCB/oJtwzehAAAAEIcnn3xSTzzxROTlX3rppYFvdGP8xtFuos0EAADGhTrw/JmqDhLP85TP53uaN5lMqlgshqbl83ldvHixpw6NTCbTep5uML/pG0+95Hf77bfrzjt5WScAAAAm26CPKbr99tuHGA36Me3tJtpMAABgXKgDz5+p6iBxXXfgF/oFz8cNXhDYi+Xl5Y7fx5+ZG/yfSqUGig3AZPL96N8ciMpxzMM5fX8zUpp9fc9Y8nwqYp7RtmEW2MrMVi6jKjPbsnHvp1Eco9KNEawv3iHV0cv6VUuarZrXez2ok3dC+ocj5hu391nSvhwxz2+2/X2j7fc3Q+Ydn3m+Ns8T2k1A+PVuGNc5x7mkh/SH8iS5qc/oxRM/G+8NiSP887Kf+IzzeifFc7JRlR0wa/prM3RfC/rNd5LPQ8e5FDrd9x+LOZLeTWM5R3V4eEq6Ee8jrw4Pp+cl7dMT6RBUKhVJUjqd7pjuWSoQ1Wq19ULCRCIR2tgIvil1/vz5YYYLAAAAALGj3QQAAIB5MVUjSAZRq9W0tbWlXC6nUqnUml6v11vfYHr88cf16KOPamNjQ9JRw2BxcVGrq6ut+S9evKhUKqVGo9EaGl4oFFQoFJRIJOLbIAAAAAAYMtpNAAAAs+XwxmnpRrzdAIcxj1gZxFx0kHiep0wmI0mtbzW129/flyQtLi5qa2tL1WpVrusqk8l0PY/XdV3V63Xl83klk0k1Gg3l83lls9nRbwgAAAAAjAjtJgAAAMybueggcV1Xvu+fOF+vz+l1XVflcnnQsAAAAABgYtBuAgAAwLyZiw4SAAAAAAAAAADmzc3D0yN5SfuNi5d04+Kl0DT/618f+vpGhQ4SAAAAAAAAAADQszOPP6Yzjz8Wmnbzpd/X9Yd/KOaIoqGDBMCMWTSmOM6njGm+//FRBBOZ72/GvL6nIi3nOBcseca7DbZYorJtg+M8Y1kuWnmOQ9T9FLW8oy43iuNpFHnGf05Ercq9EnG5hYjLTZrfs6S9bUyxnffSjba/99p+f0vvYcUg7mszAIzLqK53vv+Y5HlS6h/Kq39Ecl1JtjrAqyHTPhw6pymP+NsGg6+vnzrfLH02OU73N6l9P/zmIabfLB27gzId52HnhG3+OM3T/js8PCU/5pem3zw8Fev6BjE9kQIAAAAAAAAAAAwJI0gAAAAAAAAAAJhBhzdO6+Y34x1BEveIlUEwggQAAAAAAAAAAMwdOkgAAAAAAAAAAMDc4RFbAAAAAAAAAADMIP/mafmHMXcD3JyeR2zRQRKzlZUVLSwshKatr69rfX095oiA2eL7Hx96no5zwbK+zUjLSZJf/9HIMcUp6vbHLf5YbkRaKmqcJx1Po1hn1DyjnzPPDBRTv2zr8/2nIuU5iv1rzzPacSi9bokl3v0wHncaU3z/CWOa4zxryfOg7e8zbb+jV7en4fq7s7OjnZ2d0LSDg4PQ6cBJaDNhGpmuy/3U4frJY1I+B0wmPb4wwyhn339sWOHEZhqPr0kxqrKbpfKfxnOiF9SBZwsdJDG7cuWKXNcddxgAAADAwGw3qz3PUyqVijkizALaTAAAYJJNXR34xikp7pem35ieN3tMT6QAAAAAAAAAAABDQgcJAAAAAAAAAACYOzxiCwAAAAAAAACAWXR4Ov5HbB1Oz0vaGUECAAAAAAAAAADmDiNIAOAEvr85muU8L1K+cYu6/bPAcS4Y0+a5XE4S/Zx5yphm2xfRY7kRaX22PKMuN4rjyR7nM5blbPvhUwPFNDmuRVzu/Za034uYpxnXGQCYfsO4lvN5EI9pLOewume/2zGN2x3GVA+Pe/smJY5RmqVtmRuHjnTDiX+dU4IRJAAAAAAAAAAAYO4wggQAAAAAAAAAgFl0KNsDFEa3zinBCBIAAAAAAAAAADB36CABAAAAAAAAAABzh0dsAQAAAAAAAAAwi3jElhUdJACAqeE4F4xpvr859PWNIs+oJikWKf59YWNb3yQdM6OIxb6+T1mWvC/S+qS9iMtNmoOIy/3eUKM4ySSdZwCAaMKu5VzDMSz9HEumesWsHI/j2Y4PhsTx4dA5Z6n8ua5h1tBBAgAAAAAAAADALLqh0Ywgubxz9BPmetQvpcWPDhIAAAAAAAAAANC78+tHP2G+7El/IxVvPBHRQRKzlZUVLSwshKatr69rfd1wUAEAAAATZmdnRzs74d8aOziYnm+NYbLQZgIAAJOMOvBsoYMkZleuXJHruuMOAwAAABiY7Wa153lKpabjW2OYLLSZAADAJJu6OvANSd8cwzqnxKlxBwAAAAAAAAAAABA3RpAAAKaG72+OOwTcEve+iLq+qMs5zoWhr2+SYnGcZyLlOTvCH91zskVL2uttf99o+x39q1Nc8wBg+nEtP5mprjOqsot7fXGb9O3rp247KTGb+P6HR5LvpO/DYQi28SG9Jk+SmyrK84vjDWqW3ZR0OIZ1TglGkAAAAAAAAAAAgLnDCBIAAAAAAAAAAGbRoeJ/J0jcI1YGwAgSAAAAAAAAAAAwd+ggAQAAAAAAAAAAc4dHbAEAAAAAAAAAMItuKP5HbMW9vgHQQQIAkONcMKb5/maMkSAK2/47Cfs3XNRycZxnLHk+ZVku2jloW85+XNxhSZsHB8YUx7lkWe714YcCAMCci7s+Oo31X1O9LmxbJn37Jj2+Uelnuye/jD44cA6tbfQ8KVWSV88NnCcQFR0kAAAAAAAAAADMIl7SbsU7SAAAAAAAAAAAwNyhgwQAAAAAAAAAAMwdHrEFAAAAAAAAAMAs4hFbVowgAQAAAAAAAAAAc4cRJAAAAPj/t3cHIY5kecLY/xrG01NDeyarejDsGvdBefB1OlR7NM0HqW/5WPClMquPe9iZ1CFvAy7RNLi64BvSmQfftHzKmoU57KUnVdi3MUiLmT0t3lJMrzEMLKRgsLf3w+xmyUOz1dVdNeFDdaorKyWVMjMUkkK/HwSVighF/DNehOr/8um9BwAAQBnpQTKVBpKC3blzJ27cuDF2297eXuzt7RUcEUBElt1fdAhro1J5MHHbtHK46vve9F7ylWUfTdx2nTK8WizzeK6LzqrnY3o5/WzK+6Y9oz9/5dXZdfqvIuK/vlxwK6bVakWr1Rq77enTpwVHQ1moMwGcp762XibVG5bnPvinmfc8nyN/I8t+nFcwCyEHLhcNJAV79OhRJEmy6DAAAODapv2xOk3TqNVqBUdEGagzAQDLbOVyYD1IptJAAgAAAAAAzO5XrYj/bXxPmvhydXrSaCABAAAAAABm9x/2Xi7jDNKI/2HJetJMoIEEAAAAAADK6HlEfLWAc66Iby06AAAAAAAAgKLpQQIAhbraf71Zdv/KZ7zOe8nPtHKoVB5c6X1XVan8bMr5Psr9fMvmqr//tPdF3Hrl5+ev/Fv0V7UAgHUxLoeU+583Kc92na4uy358ib3/aW5xcAkvovhJ01doknY9SAAAAAAAgLWjgQQAAAAAAFg7htgCAAAAAIAyehHFT5puiC0AAAAAAIDlpQcJAAAAAACUkR4kU2kgAYACZdlHiw6BJZRl9wt931UVfb75mUft4P995efTV/797hzOBQCwmrlZpfJg7Pp5/S6reI1WMeZJyvS7UF4aSAAAAAAAoIz0IJnKHCQAAAAAAMDa0YOkYHfu3IkbN26M3ba3txd7e3sFRwQAAFfTarWi1WqN3fb06dOCo6Es1JkAgGUmBy4XDSQFe/ToUSRJsugwAADg2qb9sTpN06jVagVHRBmoMwEAy2zlcuDnUfwQW0Wf7xoMsQUAAAAAABSu1+vFzZs3L6xP0zR2dnai2WxGo9GITqczl/PrQQIAjFWpPJi4LcvuFxgJVzGt/OZ1zNW5L66aAk/+GtS53z1NI2pHkfYbEb4FDwAwsjr54tVUKj8fuz7LflxwJMW6at3jvfgs0ohIau1Is3a+QfGNJZ+kvdFoXFg3GAyiVqtFv98f9Sze3NyM09PT2N3dzSvKiNCDBAAAAAAAKFiz2YxqtXphfaPRiK2trXPDrp71JMmbBhIAAAAAAKAwvV4v3nnnnQtzzw2Hw+j1elGv18+tv337dkREHB0d5RqHBhIAAAAAACijsyG2ilxmGGKr3W7HvXv3Lqx//PhxRMSFniVnDSndbnemX3tW5iABAAAAAABeev7s5XJVzz6furnZbMbBwcHYbYPBICIiNjY2pm7Py9o3kAwGg7HjnAEAAPCSehMAwIp6HhFfXfI93f2Iv3kwj2giTdN45513JuaWJycnERFx69atsduHw2Gu8axdA0mlUjn3OkmS6Pf7o9dpmsb+/n5Uq9UYDodRr9dje3v73Htm2QeAcqtUJicKWXa/wEje7KqxLtvvwUVXLdtK5WdXOl957onnuR/x1Wv6XnwWaUQktb+K38SvIss+yv18MG/qTQCskkl5cdH5a5b9+NrHqFR+Prdj52HctZ50nd9YLmkaUTuKtJ//xNt5u8zvXQr/7sOI/+6nV3//Z59GHL0/dtP+/n4cHx9PfOvm5mZERJyeno7dnveXdtaqgeTo6Ch2d3dHFzkiYmtra/TzYDCIWq0W/X5/NKbZ5uZmnJ6exu7u7sz7AAAArCr1JgCAEnkRM80Jck7lrYj/4q2rn/Pbb49d3Ww2o16vnxsm6+zns3/PGkAm9RTRQHINx8fHUydxaTQasbW1NUrgI14WWqPRGCXxs+wDAACwqtSbAACYh16vF4eHh2O3bW5uRpIk8Td/8zcRcXGukbPXtVot15i+levRllin04nHjx/Hzs5OHB0dXdg+HA6j1+tFvV4/t/727dsR8fJbVLPsAwAAsKrUmwAAmJd+vx9Zlp1b7t27FxsbG5FlWfT7/djY2IgkSS58YafX60VExN27d3ONaW0aSLrdbgyHw+h0OtFoNOLmzZujixoR8fjx44i42EXn7BtP3W53pn0AAABWlXoTAEDJvIiX0zAWuVx2SK/XPHz4MHq93rleJAcHB3FwcBAbGxvXO/hr1maIrXa7He12O9I0jXa7HUdHR1Gv1+Pk5CSq1eroYk+6wIPBYKZ93uTzzz+P3//+91f6HSIi3nrrrXjrrWuM/wYAADN49uxZPHv27Mrv//zzz3OMhqIsQ71JnQkAWJTJOfAXF9aMy1fkwPlIkiT6/X40m81RDtpsNucyVOvaNJCcSZIk2u121Ov12NnZiWazGcfHx3FychIREbdu3Rr7vuFwONM+b/L+++9fLfCv3b9/Pz7++ONrHQOA68uy+4sOYWarFCuXM61sK5UHV3ofk8183dI0ovaXkfb/IuKV+RdWzf7+fjx4MPk+otwWWW9SZwKW3aQ8S45VjHHXf1mufR73Rpb9OK9w5uJyv8tylMtlXCYH/sEP/qc5R5OTsx4kRZ9zRmc9Q16XJEkcHx/nGNR4a9dAcmZ7ezu2t7cjTdOIeDkJTETE6enp2P2r1epM+7zJr3/96/jRj350hYhf8k0oAACK8OGHH8ZPf/rTN+73gx/sT9jynyPiF3mGxAIsot6kzgQALMqsOfAkn3766bW/7EGxVqqBJE3TaDabM+1brVaj3W5P3ader4/G0z1L0id9m6larc60z5u8/fbb8f3vf/+N+wEAwCLNPkzRdyes/06e4XAJq15vUmcCABblukN1vv322zlGQxFWqoFk3Oz113X79u1z/74+Hu7Z61qtNtM+AAAAi6TeBADAyJIPsbVo31p0AIvU7Xaj0WhExMsJBMdVJM6+KXX37t2Z9gEAACgT9SYAAMpqLRpI0jSNWq0Wh4eHo3WdTidu3boV29vbo3UPHz6MXq937ptOZ5PEbGxszLwPAADAqlFvAgAooecR8VXBS9E9Vq5hpYbYuqpqtRq3bt2K/f396Ha7kSRJ1Ov1C2PtJkkS/X4/ms1mVKvVGAwG0Ww2Y3d391L7AMAyqVQeTNyWZfcLjIRi5Z/mVSo/m7o9yz7K/ZzLZNqz9Kr34rNIIyKpteM38celf84m/X4v/9h+VHA0XId6E8Bsyv5/+7Jb5us/KbZJeeS4/S+z7yJUKj+/sC7Lfjxh3+X+XSBiTRpINjY2Zh6DN0mSOD4+vvY+AAAAq0S9CQCAdbMWDSQAAAAAALB2XkTxk6abpB0AAAAAAGB56UECAAAAAABl9CKKnzRdDxIAAAAAAIDlpQcJAAAAAACUkR4kU2kgAYCSy7L7uR+zUnlQ6Pm4vCz7aOK2SuV/nvK+n045atFZ9Xxc9R6d9r5pzwQAAOvtMvnn8ten/mnRAUCuNJAAAAAAAACz+79aL5dxnj8tNpZr0EACAAAAAABl9DwivprDcf/bvZfLOP+SRvyvtTmcNH8aSAp2586duHHjxthte3t7sbc34aYCAIAl02q1otUa/62xp09X51tjLBd1JgBgmcmBy0UDScEePXoUSZIsOgwAALi2aX+sTtM0arXV+NYYy0WdCQBYZiuXA7+I4idNX6FJ2r+16AAAAAAAAACKpgcJAHBpWXZ/0SHwBpXKzxYdwtKafm2eT9wy/b7/9pifvx3SbQAAyuQydUH1RlaBGhsAAAAAAJTRi5j2PbD5nXNFGGILAAAAAABYO3qQAAAAAABAGelBMpUeJAAAAAAAwNrRgwQAAAAAAMroeUR8tYBzrggNJAAApTQtI13vFDDLPpq4rVJ5UGAkAACwWsbly1l2fwGRQD4MsQUAAAAAAKyd9f76IAAAAAAAlNUfovhJ0/9Q8PmuQQ8SAAAAAABg7ehBAgAAAAAAZfQ8ip80fYUmadeDBAAAAAAAWDt6kBTszp07cePGjbHb9vb2Ym9vr+CIAIAyyrL7E7dVKg9yP+YqqVR+NmXr1dLjLPvomxdpGlH7y0j7fxGRJFc63qpotVrRarXGbnv69GnB0VAW6kwAlE2l8vOx67PsxwVHcn3j6gSVyq8m7Psf5h3OQsiBy0UDScEePXoUSckrygAArIdpf6xO0zRqtVrBEVEG6kwAwDJbuRz4RRQ/5FXRk8JfgyG2AAAAAACAtaMHCQAAAAAAlNHziPhqDsf9v1sR/8/4ocbixeoMNaaBBAAAAAAAmN1/s/dyGef3acT/sWRDjU2ggQQAAAAAAMroD1H8nCB/KPh816CBBABgRVUqDyZuy7L7BUayWrLso9yPWan8bPTze/FZpBGR1P4qfhO/msv5AABYHVn240WHkJtxdZBJdY9J9RV1FZaJSdoBAAAAAIC1owcJAAAAAACU0Yt4OVF70edcEXqQAAAAAAAAa0cPEgAAAAAAKKPnUXwPkqLPdw16kAAAAAAAAGtHDxIAgJxUKg8mbsuy+7mfb9oxi45llczj2mTZR9+8SNOI2l9G2v+LiCS50vEAAGAZXSZfnrTvWT7+XnwWaUQktXakWTuP8ODSNJAAAAAAAEAZPY+IrxZwzhVhiC0AAAAAAGDt6EECAAAAAABl9IeIeLGAc64IDSQFu3PnTty4cWPstr29vdjb2ys4IgAAuJpWqxWtVmvstqdPnxYcDWWhzgQALDM5cLloICnYo0ePIjFZJwAAJTDtj9VpmkatVis4IspAnQkAWGYrlwO/iOLnBCm6x8o1mIMEAAAAAABYO3qQAACsqErlwcRtWXa/wEhWy1WvzbTr/ar34rNIIyKpteM38cfKAgCAtTQpfx7lx2kaUTuKtN8oMCo4TwMJAAAAAACU0fMofoitos93DYbYAgAAAAAA1o4eJAAAAAAAUEbPI+KrBZxzRehBAgAAAAAArB09SAAAAAAAgNkNWxH/X2v8tuxpsbFcgwYSAICcZNn9Up+vUnkwdXvR8VzVtN9j2u8w8++XphG1o0j7jYgkuWx4AABQCqtSPyi9P0TEizkc97/ce7mM8yyN+Kw2h5PmzxBbAAAAAADA2tGDBAAAAAAAyuhFFD9p+jx6rMyJHiQAAAAAAMDa0YMEAAAAAADKSA+SqfQgAQAAAAAA1o4eJAW7c+dO3LhxY+y2vb292NvbKzgiAGDdVCoPJm7LsvtX2rZKrvp7TLtur6bV78VnkUZEUvur+E38KrLsoyudbxW0Wq1otVpjtz19+rTgaCgLdSYAYJnJgctFA0nBHj16FEmSLDoMAAC4tml/rE7TNGq1WsERUQbqTADAMlu5HLjo4bUWdc4rMsQWAAAAAACwdvQgAQAAAACAMnoREZUFnHNF6EECAAAAAACsHQ0kAAAAAADA2jHEFgAAa6VS+dnEbVn20ZRt96cc88Err56/8u8KzU4IAAA5Op8jf2NaXs0cLGK4K0NsAQAAAAAALC8NJDMYDAaLDgEAAGCpqTcBACyhF/FN5/ailjf0IOl0OlGr1aJSqUStVoter3dhnzRNY2dnJ5rNZjQajeh0Ole/BlOszRBb9Xp97IWOiOh2u7G1tTV6XalUzm1PkiT6/f7odZqmsb+/H9VqNYbDYdTr9dje3p5P4AAAAAVRbwIAYJ4ODw+j2+1Go9GIk5OTODw8jHq9fi7XHAwGUavVot/vR5IkERGxubkZp6ensbu7m2s8a9FAMhgMYjAYxMHBQWxsbIzWnxXAq0n+0dFR7O7uxubm5mjdq9uLLBwAAICiqDcBAJTQ84iovHGvfGWTN/393/99dLvd0esPPvggarVaHBwcjPLJRqMRW1tbozwyIkY9STSQXEGv14t+v38uyY+IC0l+RMTx8fG5AnpdkYUDAABQFPUmAADmqdfrxcHBwbl1SZJEkiSj4VqHw+HY/W7fvh0R33xRJy9r0UAy6YJ98skn0Wg0Rq87nU48fvw4dnZ2ol6vX3hf0YUDADAPWXZ/0SGspErlwcRt565pmkbUjiLtNyJe+eNwWU2+Lp8VGgfXp94EAORJvYPXvf6lm1dVq9WIiHj8+PG512fOvnjT7XZzzSXXdpL24XAYaZrG3bt3R+u63W4Mh8PodDrRaDTi5s2b58bfnaVwAAAAykK9CQBgxb24wvL8WcTz3199efH5pUIcDAaxs7Mz+jkiLvRqfnXfPK1FD5JxfvnLX0aSJOcudLvdjna7HWmaRrvdjqOjo6jX63FychLVajWXwvn888/j97///ZXjfuutt+Ktt9668vsBAGAWz549i2fPns2w5xcT1n+ZZzgsyCLqTepMAMCizJ4Dj/f555drGFhe+xExuQd9njqdTlSr1VGvkJOTk4iIuHXr1tj9h8Nhrudf2waS4+Pj+OCDD8ZuS5Ik2u121Ov12NnZiWazGcfHx7kUzvvvv3/lmCMi7t+/Hx9//PG1jgEAAG+yv78fDx4UUylieS2i3qTOBAAsSmlz4CmTpo/3YUT89Bon/DQiZsvp9vf34/j4ePR6c3MzIiJOT0/H7v96L+XrWssGkrMxcdvt9tT9tre3Y3t7O9I0jYh8CufXv/51/OhHP7pcwK/wTSgAAIrw4Ycfxk9/+uZK0Q9+sD9hy3+OiF/kGRIFW1S9SZ0JAFiUWXPgST799NNrf9ljObz19XJVb8+0V7PZjIcPH57LD89+nvSlmrVuIEnTNJrN5kz7VqvViYl8r9eLarU608Ws1+uj8XTzKJy33347vv/9779xPwAAWKTZhyn67oT138kzHC5h1etN6kwAwKJcd6jOt9+erWGAGA3TejZP3Znbt29HxMVhWc9e12q1XONYqQaSJElymdDvk08+ie3t7Zn3PyuUogsHAID8ZdlHV3zf/YnbKpVvuuG/F59FGhFJrR2/iT+e+r4ymPT7pWkatdpRwdEQod4EAMBy63Q6ERGxtbV1bn2appEkySifvXfv3mjb2Zdx7t69m2ss38r1aCui0+lMHEf3dd1uNxqNRkS8nGRwXGVjXoUDAACwKOpNAADkrdfrxf7+y2F6j46ORkuj0YjHjx9HRMTDhw+j1+ud+8LNwcFBHBwcxMbGRq7xrFQPkjx0Op1Rwv6qNE3jJz/5SXzwwQejlqlOpxO3bt06962phw8fRq1Wi8FgMOoaPq/CAQAAWAT1JgAA8pamadTr9YiI0ZdrXvXkyZOIeNkjut/vR7PZjGq1GoPBIJrNZuzu7uYe09o1kHzyySdjv7FUrVbj1q1bsb+/H91uN5IkiXq9fmE83iILBwAAYBHUmwAAyFuSJJFl2cz7Hh8fzzmiNWwgmXRRNzY2Zh6nt6jCAQAAWAT1JgAA1sFazkECAAAAAACsNw0kAAAAAADA2lm7IbYAACBvWXb/mxdpGlE7irTfiHhtgmsAAFhllcqDmfc9lyOzQM8j4qsFnHM16EECAAAAAACsHT1IAAAAAACglJ5H8T069CABAAAAAABYWhpIAAAAAACAtWOILQAAAAAAKCWTtE+jgaRgd+7ciRs3bozdtre3F3t7ewVHBACwXiqVBxO3Zdn9AiNZfa1WK1qt1thtT58+LTgaykKdCQBWy7rl0HLgctFAUrBHjx5FkiSLDgMAAK5t2h+r0zSNWq1WcESUgToTALDMVi8HfhHF9+h4UfD5rs4cJAAAAAAAwNrRgwQAAAAAALiEn0fEX03Y9kWRgVyLBhIAAAAAACileU3S/udfL+P8nxHx7+dwzvwZYgsAAAAAAFg7epAAALBWsuz+okMAAICVJJdeRfPqQfKmc64GPUgAAAAAAIC1owcJAAAAAACU0osovkfHi4LPd3V6kAAAAAAAAGtHAwkAAAAAALB2DLEFAAAAAAClZJL2aTSQAADA1yqVBxO3Zdn9AiMBAIByOsu534vPIo2IpNaONGsvNijWlgYSAAAAAAAoJZO0T2MOEgAAAAAAYO3oQVKwO3fuxI0bN8Zu29vbi729vYIjAgCAq2m1WtFqtcZue/r0acHRUBbqTADAMpMDl4sGkoI9evQokiRZdBgAAHBt0/5YnaZp1Gq1giOiDNSZAIBltno5sEnapzHEFgAAAAAAsHb0IAEAgK9l2f1FhwAAACulUnkwdv2k3Hq0Pk0jakeR9hvzCo2IeNmbo+geHXqQAAAAAAAALC09SAAAAAAAoJTMQTKNHiQAAAAAAMDa0UACAAAAAACsHUNsAQAAAABAKb2I4oe8elHw+a5OAwkAAAAAAFeSZfcXHQIL8Sgi/pcJ254VGci1aCABAAAAAIBSmtck7f/918s4/xgRjTmcM3/mIAEAAAAAANaOBhIAAAAAAGDtGGILAAAAAABKySTt0+hBAgAAAAAArB09SAAAAAAAoJTmNUn7m865GjSQFOzOnTtx48aNsdv29vZib2+v4IgAAOBqWq1WtFqtsduePn1acDSUhToTALDM5MDlooGkYI8ePYokSRYdBgAAXNu0P1anaRq1Wq3giCgDdSYAYJmtXg5sDpJpzEECAAAAAACsHQ0kAAAAAADA2jHEFgAAAAAAlJJJ2qfRgwQAAAAAAFg7epAAAAAAAEAp6UEyjR4kAAAAAADA2tFAAgAAAAAArB1DbAEAAAAAQCk9j+KHvDLEFgAAAAAAwNLSgwQAAAAAAErJJO3T6EECAAAAAACsHQ0kjPXs2bP4+OOP49mzZ4sOhUtQbqvpyy+/VG4ryPO2mpTbalJuq+nLL7889y+sGp898+X6zpc6xny5f+fL9Z0v13e+ljMHfhHfzENS1PKikN8sDxpIGOvZs2fx4MEDH5YrRrmtpi+//FK5rSDP22pSbqtJua2m5awcwux89syX6ztf6hjz5f6dL9d3vlzf+VqvHPh/j4j/ccLynxYY1+WYg6Rgd+7ciRs3bozdtre3F3t7ewVHBAAAV9NqtaLVao3d9m//9m8FR0NZqDMBAMtMDnzm3329jPO7iPiPBcZydRpICvbo0aNIkmTRYQAAwLVN+2P13/7t38b7779fcESUgToTALDMVi8HNkn7NIbYAgAAAAAA1o4eJAAAAAAAUEpnk7QXfc7VoAcJAAAAAACwdjSQAAAAAAAAa8cQWwAAAAAAUEomaZ9GD5ISaLVaiw7hUuYVr+PO16pdh1U77rys2nVYtePOy6pdh1U77rys2nVYtePOi3jne1xYlGW6p/OKJY/jLFMseVmm32mZYsnLsv1Oy1ROeVim65LXcVzf+R6njNc3L2W7vhRHA0kJrNrDu2oV+1U77rys2nVYtePOy6pdh1U77rys2nVYtePOy6pdh1U77ryId77HhUVZpnu6jH9Yc33nd4w8j5OHZfudlqmc8rBM1yWv47i+8z1OGa9vXsp2ffN1Nkl7kcvqTNJeqiG2hsNh7O/vR0TEwcHBhe1pmsb+/n5Uq9UYDodRr9dje3t7LvsAAAAsI/UmAAB4qTQNJL1eL9rtdnQ6ndjd3b2wfTAYRK1Wi36/H0mSRETE5uZmnJ6ejvbPax8AAIBlpN4EALBuzEEyTWmG2Nra2orj4+OJ2xuNRmxtbY2S84iIZrMZjUYj930AAACWkXoTAAB8ozQNJNMMh8Po9XpRr9fPrb99+3ZERBwdHeW2DwAAwCpSbwIAYN2sRQPJ48ePIyKiWq2eW3/2baZut5vbPgAAAKtIvQkAoIyKnqD9bFkNpZmDZJrBYBARERsbGxO357XPJE+fPo2IlxMVfv755zNEPd53vvOd+M53vnPh2GmaXvmY45zF+Omnn8bbb7+d67HnEa/jvrRW5fbb357/N6/jvkGux/069n/7x3+MiDUptxIdd62etxIdV7mt5nFXrtze8H/UdRRZbl9++WV8+eWXVz7mP/zDP0RExBdffHGt2CjOoutNedaZ8nhW8vrsyeu5zeM4yxTLSl/fCZ/zS3F9c65jLMXvlPNx1v7+nfNxXN/5Hqd01zfHvDmv6/t3f/d3JcyB/2VNznlFWclERLa7u3tu3b1797KIyPr9/tj9q9VqbvtM8td//ddZRFgsFovFYrFYLGu1/OIXv7hCVs+8RSxfvUmdyWKxWCwWS1mWZciBf/e732Xf+973FnYNvve972W/+93vFn0Z3mgtepBsbm5GRMTp6enY7dVqNbd9JvnTP/3T+MUvfhF/9Ed/FN/97ndnjv1143qQAABA3q7bg+SLL76If/7nf44/+7M/yzEq5mnR9SZ1JgBg0cqUA7/77rvx29/+Nv7lXxbTm+OHP/xhvPvuuws592UsTQNJmqbRbDZn2rdarUa73Z752GcJ+HA4nLg9r30m+eEPfxh//ud/PlvAAAAAY5S53qTOBACQr3fffXclGikWaWkaSJIkmdtkfbdv346Ii2Pdnr2u1Wq57QMAADAv6k0AAJCfby06gCJsbGyMrUj0er2IiLh7925u+wAAAKwi9SYAANZNqRpIJnXhjoh4+PBh9Hq9c99iOjg4iIODg9jY2Mh1H5i317+NB8yf5w4Ww7MH+VNvokg+xykD9zFl4D6G8SpZlmWLDiIPaZpGu92Oo6Oj2NjYiIcPH8bW1ta55DtN09jf349qtRqDwSDq9Xrs7u5eOE4e+6yqV3+34XAY9Xo9tre3Fx3W2qtUKudeJ0kS/X5/9HqWclO28zEcDmN/fz8iXlb6X5dX2Si/fL2p3CI8d8us0+nE/v5+pGkaSZLEwcFBbG1tndvHs7d8Zim3CM/esnm13M7ms/C8rTb1pjdzL16Pz/HrU8eYL3WB+ZOvz5e8er7kv2sog6+dnJxkEZH1+/3Rumq1mrXb7QVGRbvdznZ3d7ODg4PR8moZzVJuynY+ut1utr29nUVEtru7e2F7XmWj/PL1pnLLMs/dMjs4OMi2traydrud3bt3L4uILCKybrc72sezt3xmKbcs8+wtm7Py6Ha7WbfbzZIkySIiOzk5Ge3jeaNs3IvX43P8+tQx5ktdYP7k6/Mlr54v+e960kDCyNbWVra1tXVuXbvdzrSjLdbrZTJu+5vKTdnO16TkOq+yUX7zMa1S5LlbXtvb2+de9/v9LCLOXWvP3vKZpdyyzLO3bA4ODs69Piu34+Pj0TrPG2XjXrwen+P5UceYL3WB+ZGvz5e8er7kv+upVHOQcHXD4TB6vV7U6/Vz62/fvh0REUdHR4sIa+11Op14/Phx7OzsjC2DWcpN2S5GXmWj/IrnuVtevV7vwjAISZJEkiSj8XQ9e8tnlnKL8Owto3v37p17fTYEU5IkEeF5o3zci9fjc3z+fO7On/v4euTr8yWvnj/573rSQEJERDx+/DgiIqrV6rn1Zx8A3W638Jh4ed2Hw2F0Op1oNBpx8+bN6PV6o+2zlJuyXYy8ykb5Fc9zt7y2trYuXNMzZ+s9e8tnlnKL8Oytgk6nEwcHB543Ssu9eD0+x+fP5+78uY+vR74+X/Lq4sl/14MGEiIiRi3Nr07OOG47xWq325FlWfT7/djd3R1N2HRWHrOUm7JdjLzKRvkVz3O3egaDQezs7Ix+jvDsrYJXyy3Cs7fsms3maALJM543ysa9eD0+x+fP5+78uY/nQ74+X/Lq+ZD/rg8NJERExMnJSURE3Lp1a+z24XBYYDS8LkmSaLfbcXx8HBEvP6QjZis3ZbsYeZWN8lscz91q6HQ6Ua1WY3d3NyI8e6vi9XJ7lWdv+RweHsZgMIjhcHhuqAbPG2XjXsyHz/H58blbHPdxfuTr8yWvng/573rRQEJERGxubkZExOnp6djtk7rwUazt7e3Y3t6ONE0jYrZyU7aLkVfZKL/F89wtt/39/VHCH+HZWxWvl9s4nr3lce/evTg+Po5utxsbGxujsa89b5SNezFfPsfz53O3eO7j65Ovz5e8ej7kv+tFAwkR8c2DN6mF0oO5POr1+ugDdJZyU7aLkVfZKL/l4LlbTs1mMx4+fHjuenr2lt+4cpvEs7dctra2Ynd3d9Tl3/NG2bgX8+dzPF8+dxfDfXx18vX5klfPn/x3PWggISIibt++HREXx7g7e12r1QqPicnOymuWclO2i5FX2Si/5eG5Wy5HR0dRr9dHk9id8ewtt0nlNo1nb7n8yZ/8yajC5nmjbNyL8+FzPD8+dxfHfXx58vX5klcXR/5bfhpIiIiXkwIlSRLdbvfc+l6vFxERd+/eXURYjNHtdqPRaETEbOWmbBcjr7JRfsvBc7dcOp1ORLz8Ns+r0jT17C2xaeU2iWdv+QwGg1EZet4oG/di/nyO58vn7mK4jy9Pvj5f8upiyX/XQAZf6/f7WURkJycno3XVajU7ODhYYFTrq9/vZ0mSnLv+x8fH2e7u7oX93lRuynZ+njx5kkXEhXLJsvzKRvnlb1K5ee6WX7fbzZIkydrt9rlld3c3a7fbWZZ59pbRm8rNs7d8njx5km1vb2fHx8ejdScnJ9nW1ta5/TxvlI178Wp8judLHWO+1AXmS74+X/Lq+ZH/rq9KlmXZfJtgWCVpmsb+/n5Uq9UYDAZRr9djd3d30WGtpeFwGDs7O/H48eO4fft2JEkS9Xr9wjcEImYrN2WbvzRNo91ux9HRUWxsbMTDhw9ja2srNjY2zu2TR9kov/xMKzfP3XJL03RqV+MnT56Mnj/P3vKYpdwiwrO3hOr1+qhM6vV6VKvV2N7evrCf542ycS9enhwqP+oY86UuMF/y9fmSV8+f/Hc9aSABAAAAAADWjjlIAAAAAACAtaOBBAAAAAAAWDsaSAAAAAAAgLWjgQQAAAAAAFg7GkgAAAAAAIC1o4EEAAAAAABYOxpIAAAAAACAtaOBBAAAAAAAWDsaSAAAAAAAgLXz7UUHAAAAvNlgMIjNzc2oVquxvb0dEREffvhhbGxsLDyudrsdw+EwfvnLX8ZwOIwnT54sPC4AAFab/JciaCABAIAV0mw2Y3d3d9FhjFSr1Tg4OIiIiI2NjTg8PFxwRAAAlIn8l3kyxBYAAJCLd955Z9EhAABAYeS/q08DCQAAAAAAsHY0kAAAQIE2NzejXq/Hzs5ONBqN2NnZiUqlEpVKJdI0vfTxhsNhHB0dRb1ej6OjoxgMBlGv1+PmzZtRr9djOBxGRMTh4WFsbm7GzZs3o9ls5vZ+AACYRv7LMjMHCQAAFGhrayva7fbo9eHhYXQ6ndjd3Y0kSS59vNPT0+j3+9Hr9SIi4uTkJA4ODuL09HRUEa1Wq7GzsxPdbjeazWYcHh7GBx98EEmSXPv9AAAwjfyXZaaBBAAACrSzszP6eTgcRrPZjI2NjdFEj5dVrVaj0WjE0dHRuQkjIyKSJIlerxcnJydRrVYjIuLDDz+MTqcTvV4vkiS59vsBAGAa+S/LzBBbAABQoK2trdHPP/nJTyIi4uDgIDY2Nq597NePcVapu3Xr1oV1Jycnub8fAABeJ/9lmWkgAQCABej1etHpdCJJktjd3V10OAAAMFfyX5aRBhIAAFiARqMRERHHx8cLjgQAAOZP/ssy0kACAAAFazabMRgM4t69e6Mu+wAAUFbyX5aVBhIAACjQYDCIw8PDsRNTHh4eLigqAACYD/kvy0wDCQAAFGjS0AJpmsa//uu/XumYp6enY9cPh8ML289+Hrfuqu8HAIBJ5L8sMw0kAABQkF6vF71eLyJeVhAbjUY0Go2o1+tRq9Vic3Pz0sdM03T0Tbyjo6PodDqjn8/O1Ww2I03TGAwG0Ww2R7EcHR1d+/0AADCJ/JdlV8myLFt0EAAAwHSDwSA2Nzej3W7H7u7uosMZ6/DwMJrNZjx58iQ2NjYWHQ4AACtM/ksR9CABAIAVctbtfxlddYgEAACYRP7LPH170QEAAACz29/fH1XEPvzww4V/U20wGES73Y6IMOQAAAC5k/8yT4bYAgAAAAAA1o4htgAAAAAAgLWjgQQAAAAAAFg7GkgAAAAAAIC1o4EEAAAAAABYOxpIAAAAAACAtaOBBAAAAAAAWDsaSAAAAAAAgLWjgQQAAAAAAFg7GkgAAAAAAIC18/8Dv5PEYcXE/AwAAAAASUVORK5CYII=", + "image/png": "iVBORw0KGgoAAAANSUhEUgAABkgAAAL5CAYAAAD7Uaj9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACvoklEQVR4nOz9f5Qj533f+X5qZshxx/yBafpKx6Rjk2jKu8quvWKh7djW2kwsYH2dHJ97re4ebmTvxns8BI7S174bZtUww7vbnCRMGy2be876dhhgxifxOY68JNDynuOTdRJATmhHjm0NipS9N8pabJBSTPpKV+oGh2O3Rpqeun/0FAg06nkaKACFX+/XOX26u56q5/nWUwXgeerBU+X4vu8LAAAAAAAAAABgjpwZdwAAAAAAAAAAAABxY4AEAAAAAAAAAADMHQZIAAAAAAAAAADA3GGABAAAAAAAAAAAzB0GSAAAAAAAAAAAwNxhgAQAAAAAAAAAAMwdBkgAAAAAAAAAAMDcYYAEAAAAAAAAAADMHQZIAAAAAAAAAADA3GGABAAAAEbNZlOVSkVra2u6cOGCPM8bd0iYEbVaTblcThcuXFClUhl3OAAAAADmEAMkAAAAMCqVSioWi6pUKmo2m+MOBzHY3t5uDYhduHBBuVxu6Me+UqmoWCyqVCpxXk2oZrMpx3GUyWT62iafz2tpaUmO43T8BOfTyeWO46hUKo1wTwZXqVSUyWSUyWSUSqWUyWRUq9WGlr/necpkMj0NQM9qHQMAAIwLAyQAAAAw2tjYULFYHHcYU63ZbE7FIECz2VQqldJXv/pVlctlvf7661pcXFSpVBr6xdXV1VWVy+Wh5tmraTke4xYc87W1tZ63SSQSKhQKqlarHcsODg5aP77vy/d91et1ZbNZSdLy8vJwgx+itbU1ra2ttfarXq8rl8spk8kon88PlHej0dDa2ppSqVTPAy6zWMcAAADjxAAJAAAArBYXF8cdwlRbW1tTo9EYdxinyufz8jxPuVxO0vFF1729PVWrVW1sbIw5uuGZluMxbi+++KIk6eLFi31v2z4AdfHiRSUSia51XNdVsVhUIpGQ67pRwxypXC7Xmu3UHuPq6qqy2ay2t7cj3x4umJ0X1azUMQAAwLgxQAIAAACMSD6fH+qteEYpmDFwckAsnU6PI5yRmKbjMU6NRkOe5ymdTodeeD9Nex2fNgOln5kNwcyNOI5ho9FovSaCWRgnY5EUeRZJNptVoVBQoVCItP2o6hgAAGDeMEACAAAAjEClUtH29va4w+jJPMyomKbjMW7BzIZgEKBf7bd/Om2ArZ9brRWLRWUymdZtqaLO3uhFMHBhit91XSUSCTUajYEGbKLO0BtVHQMAAMwbBkgAAADQl+C++cEDgW23LKrValpbW2t9EzuXy4U++LnZbCqXy7UePJxKpYwXsyuVitbW1lrf3A4ecBw8pLh9u0ajoVwu13pwcSaT6ev5E57nKZVKdTzs+GRclUqlFXeQf6VS0ZNPPtla50Mf+lCrvtrrsD3fTCbT+uZ+UOaFCxcifUN9e3u79UDppaUlZTKZ0OeIlEolXbhwQalUqrXskUceacXa64BC8BDroIx8Pt9R571eQG7fLpVKnfrQ6l7387TjETVf6fjcLZVKHeuUSqWOc9m0H81ms/WMi7W1NS0tLWlpaenUgQnP8zoexr20tNSq4+3t7a609tibzWbr9bK0tBT6eggGHlZXV61xmASxhF24bzabHfXR7wyVjY0NHRwcKJfLtR5WPooHkAf7YLs1VTKZlKSxPKdplHUMAAAwV3wAAADA4uDgwJfkS/ILhYIvyU8mk34ikWgtl+RXq9XWNoVCwU8mk620YrHop9Ppjm329vZ83/f9arXqu67b2n5vb89Pp9O+JN913Vae1Wq1tVySn81m/Y2NDd91XX9jY8PPZrMd5ZXLZT+ZTLbWC+Jpz7PX/Q/iTqfToesE+2uqt3q9HrpdsVhsrVMul7vyOzg46CvWer3uJ5NJf3V1tSOO1dXVVvxhee7t7XUdl17Laz8mQdyu6/qu63acH4VCoWv79uPluq6fTqc7jpWk0Hij7Gcvx6PffINzt30fV1dXfdd1/Ww2e+p+JJPJjno5ODjoKt+kWq2GnjvBfoS9Lk/WRVg9BNv2EsNpcRWLxa70bDbb1zl2muB1nkgkQs+xKE6+55kE58XJ137Uskzn5Ulx1zEAAMAsY4AEAAAAVu0X8JLJZMeFt/YLdYlEwrpdcKG2UCj42WzW9/13L8yfvDDYvu3GxkZHWvsF+ZMXhoNBkkQi0XWBN+ogQBBzsG2Y1dXVrguVvV74DC6wBwM3wYBMrxdL2yUSia7jEAjqLWyQZ5C68X2/4xxojzu44G/Ku/38OLm/waDUyeMfdT97OR5R6y+INZFIdAxItA+unbzQHgyOnayTarXa8+BEULdhdRSkhV3gDwZ2wmxsbBgHVnoRbH9y3w4ODvxCoWCs30GVy2Xfdd3WQEm/g4vt2geYwgYgAu2DslFFGSAZVx0DAADMIm6xBQAAgJ4VCoXWbWWk49u7BLeXaTabHbdkSiQSrVu7pNPp1q1gNjY2Wtvk83klEomu29i0Lzt5+5z2PE/eAih4WHGz2dSVK1c60pLJZGvb027ddFL7Q5pPxtNsNlWr1UIf5NyL4PkAnuepVCppbW1N2WzWemufMPl8Xs1m0xhH8EyFWq02smc3PP300x1xJxKJjmclmB5IXSgUuvY3OF9O3r5tVPs5SL7BayKbzXbc8iiRSLQekL23t9exTfD/ybzS6XTHa8wmuBVX2C2mgrSw2z8Vi0XjbbxKpZISicSpz7Uwad+f4DZj7beLu3jxYqR8T7O6uqp6va5yuaxqtdoqr59b6gX29/dbf9ueEdJ+66oo5UQ1SB0HtzMMbusW3NoPAABgXjFAAgAAgJ6FXbjNZrOtC4Wf+cxnQrdrf8ZFu0qlomaz2Xr2QvtPMIjRbDY7Lj4GFyzD7qt/2gOPg/R+LwgmEonWhfOTF5xfeumlyBeTpeM63djYkHR8UbvRaBgHEmyCi6bf8z3fE5ruum7r+L344osRow0XHIuwY5JMJluDH9euXes5zyDWk8dqVPs5qnxN+7G0tCTpeGDm5HNmej3+wTkZDNK1CwZggufaBGwDerVaTc1mM/IgRrPZbO1nNpuVf3zHAh0cHKharSqRSLQGMUclnU6rWq2qXq+r0WjowoULrdfVLBi0joP34nK5rHK53BokiXOABwAAYJIwQAIAAICBBd+S72dmRrBuOp3W3t5e109w4c/3/aE9ZHiQfIJv3Hue17GfxWJRTz/99EBxtc/M6XfmSKCXC8BBGf3OoBmUaTZIFKPaz7jrr32W0Pb2dseD1nuVSCRas6jaB+6CB8cH9d6eZhvQC2YznfaQeJOXXnqp9Xf7RfpgRkoymRxoMLEfruuqXC5rb29P+/v7Wlpa6nlwpn2gtX02yUntgwpxPQh9kDrO5/NdA7DBQNmTTz45oogBAAAmGwMkAAAAGFivtwRqF1x4nJZvdruu27qgHVxwbjQaajabkQc12gUXuiuVSt8Xytvr0HZBNzhOtnVG4YEHHhhKPqPaz3HVX71ebx33RqOhTCajtbW1vr7NHwxmBLOxpOPbZK2urrYuhLdfVC8UCsYBveD2WlHP5/bbqYVdpI9rcOSk02aWndT+fmY7FsF5ENfgiDRYHZdKJbmu2xVvOp3uOH8AAADmCQMkAAAAGFhwwa2fC6tRb3c1Tief+WB7lkM/Go1G6+Jlezm9ar+ge/JZF+2C4xRlQGsYgplGUY1qP8dZf8GtjoI8K5WK8ZZ0YdLpdCuuYCBka2ur9TyYZDKpZrOpSqXSmvkS9joNbjEW9Vk6kloDe6aL9FFuHRdVo9HQ2tqalpaWtL+/r729vdYMmdMkEonW8fjqV79qXC8YUIhz4CdqHXuep2azGfoaDM639oE0AACAecEACQAAAAYWDHKYnt8Qpv0is+1h2sHtgiZB+/NWSqWSSqXSQBeUA2trayoUCq0HyzcajY4H3vciqE/b7JPgOA06UNGvYNBhGDNtRrWfcddf+226VldXtbe313oWTTBg1qv25+NUKhUtLy93DbYVi0XrgF7wXJUnnnii/53RuxfgJSmTyfS0je11H5XnecpkMlpaWtLi4qIODg46BqB6Fczssd1OLXimTq/7O6hB6jiI1fbsJtvgIAAAwKxigAQAAAAD8zyv40HmvWj/lvaTTz5pvL3L2tra2G7NEyZ4gHU+n+/49r6N7ZZMwUBI8EyK4CJ58LyAXrU/I8W0XXCx9+RDwUctGHQYxmybYexn2PGIu/6KxWJXOYVCoXVhvp+L1e2xP/nkkx3xBa/JWq1mHdCrVCpKJpORB7HaH1zfy+t12A9rr9VqSqVS+tCHPiTXdXVwcKBisRj59ldBnZoGzILb6/X7vjeIQeo4eH8Nu91dUEfTNJsPAABgWBggAQAAwEBqtZoajYauXLnS98XI4HYwzWZTqVSq49vanucplUq1bhMUGOT5D8FFQtttc04TXHxuNpvWC/7tddG+X+0XIRuNhvL5fMetfwqFQmvbfgYUNjY2WvUUdpud4MJ/+3qBYT17ICyf4PwIKzeKqPt52vEYpP5sbOdr+8PTA8HMgH5nYwUXzBcXFzsungcP75aOZ0WEvUaDWQaDDGC1DyTYBlmazabW1tZUq9Vag0GDqFQqrQewP/HEEzo4OOh4DUWVTCZbAx9hM12CcyTsXGk0GkqlUj3VZz/vZ4PUcZzPSQEAAJgqPgAAAHCKZDLpS/LT6bS/t7fXWl4ul/1EIuEXi8XQ7ST5kvxsNmvMe3V1tbXeyZ+w7dLpdCuWk8rlcmvbarXalZ5IJHxJ/urqai+7bZROp/1kMtnTepL8RCLhFwoFP51Od8Tlum7oPrbvR6FQ6Dmuvb291rFq3y5YbjoO7eWVy+WeywsE9Sqp41yoVqt+IpEILffg4MC6j+11N6z9PO14RM3Xdl65rutL8l3X7ViezWZDz9N0Ot21bi+CYxh2/IK0sNdEUKakjtd2P/b29jpetyfzOTg48Ov1ul8oFFp1tbGxEamsQLFY9JPJpJ9MJo3vP8OwurrqJxKJjn2qVqvWfdjY2GjVRb1et+bf62tv0Dq2xRzEYHufBgAAmFUMkAAAAKAnhULBd13XTyQSfiKR8JPJpL+6uhp6UbVQKLQuNLcPdpguABaLRT+dTrfyPnnh2vd9v16vty4qt+cZXIBsvzAoyU8mk62L3NVqtXURuH3bqBeEy+VyTxdl9/b2Oi6QB/tUrVZby9PpdMdF1L29va5YV1dX/YODg57jCy7+J5NJ33Xd0Pr0/eM63djY6Ki3RCLhb2xs9DVQEmxfLBb9bDbrJ5NJP5FI+K7rhtZTuVxu7X/ws7Gx4R8cHPh7e3tdg2Yn66jf/QyYjscg9Wc6r8L2o/31UigUWhff0+m0n81m/XQ6PdDAQdig4WlpwUBVlEEZ3/e7zp/28yhsuekCf6+C13kymYw0mBdF8P60urrqp9Np4/kYqNfrfjKZtB6PcrlsfO2dfM0Mo46DAZawQZBisdg1uAkAADAvHN/3feP0EgAAAAA4xYULF9RsNlUsFmN7HgPmTy6X07Vr11QoFCbquUTT4sKFC0omk6rX6x3Lc7mcSqWS9vb2hnIbPAAAgGlybtwBAAAAAABwmrBntqB32WxW29vbXctrtZrS6TSDIwAAYC7xkHYAAAAAAGZcoVBQMplUPp9vLatUKmo0Ggw+AQCAucUMEgAAAAADaTab4w4BQA/29vaUy+WUy+UkSfv7+9xaCwAAzDWeQQIAAAAgslKp1LrY6rquyuUyF1sBAAAATAUGSAAAAABEsrS0pEaj0bXcdd2uB0EDAAAAwKRhgAQAAAAAAAAAAMwdHtIOAAAAAAAAAADmDgMkAAAAAAAAAABg7jBAAgAAAAAAAAAA5g4DJAAAAAAAAAAAYO4wQAIAAAAAAAAAAOYOAyQAAAAAAAAAAGDuMEACAAAAAAAAAADmDgMkAAAAAAAAAABg7jBAAgAAAAAAAAAA5g4DJAAAAAAAAAAAYO4wQAIAAAAAAAAAAOYOAyQAAAAAAAAAAGDuMEACAAAAAAAAAADmDgMkAAAAAAAAAABg7jBAAgAAAAAAAAAA5g4DJAAAAAAAAAAAYO4wQAIAAAAAAAAAAOYOAyQAAAAAAAAAAGDuMEACAAAAAAAAAADmDgMkAAAAAAAAAABg7jBAAgAAAAAAAAAA5g4DJAAAAAAAAAAAYO4wQAIAAAAAAAAAAOYOAyQAAAAAAAAAAGDuMEACAAAAAAAAAADmDgMkAAAAAAAAAABg7jBAAgAAAAAAAAAA5g4DJAAAAAAAAAAAYO4wQAIAE6zZbI47BAAAAABTgv4DAAD9YYAEACZYrVZTrVYbdxgAAAAApgD9BwAA+sMACQAAAAAAAAAAmDsMkAAAxsrzPJVKpVPXazQaKpVK3DYAAAAAmGG0+wEAcWKABABmmOd5yufzWltb09LSkra3t8cdUkuj0dDa2ppSqZSKxaJ13e3tbS0tLSmXy2l/fz+mCGdLo9HQhQsXehqMAgAAwPwI+gypVEqpVGqssdDuHxztfgDoz7lxBwAAeFcul+v4v9FoSJLK5XLH8tMGFKTjjs6HPvQhHRwcSJLy+bz29vaGFOngksmkyuWyHMc5dd2NjQ195jOfUaVSiSGy6ddoNLS4uKhEItFa1mw21Ww2J+ocAAAAwGCG0X9wXVfS8eBE8PcohLVRT6Ld3x/a/QAwOAZIAGCCnOy4VCoVJRIJpdPpvvPa2trS4uJi6/9CoTBwfOPUvi+wW1tbU7lc7ugoua4r3/fHFxQAAACGblj9h1EOjATC2qhhaPf3jnY/AAyOW2wBwIzyPG/cIWAM1tbWOPYAAACYKLRRh486BYDhYIAEAGZMqVTS2tqaGo1G6zkfa2trqtVqrXWazaZyuZzy+bwymYwymUxHeqVS0YULF+Q4TqvRXavVtLa2JsdxtLa21sqnVCoplUqpUqmoVqsplUp1rNMuKDf4ifJMlCCPCxcu6MKFC123FahUKq39KZVKXet4nqe1tTVlMhktLS0pn8935F0qlZTJZFQqldRoNJTJZHThwgVlMpnWgyKDeyNfuHChY3sTz/Na9ZlKpVq3PpCOb33mOE5HXdhitO1jpVJpHa9cLtfRaapUKq1zwVSnuVyudT6c7GydFlP7OZXL5bS0tMR9jwEAAGbAaX2Hk+ucbAva2qi9lEu7n3Y/AIyUDwCIXblc9rPZrL+xseG7ruvv7e0Z16tWq5HKSCaTfjKZ7Fper9f9RCLh1+v11rJisehL8guFQmtZNpv1JXWst7e350vyV1dXW/+vrq76kvx0Ou1vbGz49Xq9tW17fnt7e34ikejYn0Kh4EvyXdc9dX+CPNPptJ/NZv1isei7rtta5vvH9ZVMJn1JHfUb5F+v11vrBusH6wYxtpcT7E+1Wu0ou1qtdux7ex2ZBGUFdddeL+0xnRbjafu4sbHhS+o4p/b29lp13Z53kJZMJjvWTyQSfiKR6Dkm3/f91dVVf2Njo/V/sVjsOP4AAACILo7+Q1i7vNe+w2ltwbA2qgntftr9ABAnBkgAIGbZbLajsZxIJPxisdhKa/9Jp9Otxnn7Ty9MAySu63Y1loPl7Q3soMHd3gk4ODjoauwHjeaTjeKTjfLV1dXQcvsdICmXy137KanVEQw6BO2N9vZ9PNmpSSQSviT/4ODA9/3jTsHJTkCw7ckOSLBurx2CINZ2hUKhY596idG2j7bOZ1hHyXXdrviD/IPyeokpkUh0xUNHCQAAYHBx9R/C2uW99h1OawtGGSCh3U+7HwDiwEPaASBGmUxG165d0+uvvy7pePpzs9lsPUTx5EMWh63RaMjzPG1sbHSlBVOti8VipAe6hz1scX9/v1VupVIZyoPiTz5AMpjeXa1WlU6nW3F8z/d8T8d6wb5vbW2F5nvt2rWOh1me3J9kMinP8zoeGplMJiVJe3t7PcUexFqpVLS6uipJevHFF1Wv1/uK0bSP/QrKu3LlSsfyjY2N1jnSa0zJZFLb29t64IEHWtuGnWcAAADo3Tj7D/30HUbRFqTdT7sfAOLAAAkAxKRUKqlWq6lcLiuRSKhUKqlQKKharbYa3KNmu9fv8vKyJHXcJ3dYgjxHsZ9B5+Zk3Cc7OsG+l8vlocfQq2w2q3w+r2KxqNXVVXme16p3qf8Ywwal+hGUZ8un15jK5bJSqVRr/8rlclenFgAAAL0bd/+hn75DHG1B2v3R0e4HADMe0g4AMQkeGNhoNFoPutvb2+v49lJcgocOtgsay+3flBqWoBMTzCgZpiDu0zqJQQyjGADqVSKR0Orqqmq1mhqNhl588cWOB0nGHWMv5fUaUzKZ1Ouvv650Oq1Go6FUKsXDGgEAAAYwKf2HXvoOcbQFafdHR7sfAMwYIAGAGNRqNUnH3yTa2NhQoVBQNpuNPY7gmz1BPO2Cjs/S0tLQyw06McGU8mEK4j5t2nkQQ6VSCU0Pq5NRePrppyUd3w7B87yOb1vFHWNQtulbYo1Go+eYGo2GEomEqtVqK7/2TiAAAAB6Nwn9h376DnG0BWn3R0e7HwDMGCABgBiFDT6M6ltD+/v7XTM2ksmkXNdVo9HoKvfatWtKJBKtjtcDDzzQFV/wd9i3yGyC6eSlUil0237za1er1ZRMJlv39jUJvmmXz+e7bhcQ5zeeXNdt3bd3bW1tZDH2Uqftx+VkJyyfz2txcbHnmNqfL7O6utq6H/Y4v7kHAAAw7eLsP5zUT9+h17Yg7f7hx0i7HwAGwwAJAMQgaJAG3x6Sju/xur29PZJbWtkE9zBu/5ZPs9lUoVDQlStXWlPXg28Z5fN51Wo1lUqlVuO3Vqspk8lI6u22WYlEovXgvlQq1ZpqHtwqoNFoaHt7+9Q8gnUDjUajdd/b9n1p/22KYW1tTdvb28pkMh23KjDtT5Bfe3rwd7+3Dgvq/uLFi5FiNO2j9G4nulgsqtFotL4BFhZ/IpFodXAymYzW1taUz+eVSqW0tLSkRCLRc0wvvfRSx7FpNptKJpOxPV8HAABglkxK/6HXvsNpbUFTGzUM7X7a/QAQKx8AEItqteonk0lfku+6rl8sFkdSTr1e97PZrC/Jl+Rns1m/Wq12rHNwcOCvrq766XTaz2azfjab9ev1eldehULBTyQSfiKR8Dc2Nnzf9/1kMulvbGz49Xrdr9frvuu6viQ/mUz61WrVPzg46Ci/UCi08isWix11sLe318pvb2/Pul8HBwf+xsaGn06nO+I+ODhorVMul1v5J5PJ0DouFArGder1up9Op31JfiKR8MvlcivuYH9WV1f9er3u7+3t+aurq611+zmeQR2Z2GLsZR9d1/UTiUSrjHq93oo1OCYn6y04jq7rdp0vp8Xk+76fTqdbx3JjY8NfXV3tKAMAAAD9GVf/4WRbsZe+Qy9twZNtVBPa/b3vI+1+ABic4/u+P+pBGAAAAAAAAAAAgElybtwBDEuz2dTW1pakzvshBjzP09bWlpLJpJrNpjKZTNd9K4e1DgAAAABMGvpMAAAAQKeZGCCp1WoqFouqVCqtB4S1azQaSqVSqtfrrXvqLy0taX9/v7X+sNYBAAAAgElDnwkAAADoNlO32HIcR9lstvUQ4UDwIOFqtdpaViqVlMvlFOz+sNYBAAAAgElFnwkAAAB415lxBzBqzWZTtVqt1VAPLC8vSzpurA9rHQAAAACYNvSZAAAAMK9mfoDk2rVrkqRkMtmxPJjuXa1Wh7YOAAAAAEwb+kwAAACYVzPxDBKbRqMhSUokEsb0Ya1j85WvfEX//J//c33rt36rvumbvun0wA3uvvtu3X333ZG3BwAAAHrx9a9/XV//+tcjb/+1r31Nf/qnf6q//tf/ur7lW75liJFh2OgzAQAAHJu1NvAXv/hFfeUrXxlL2d/yLd+ib//2bx9L2f2Y+QGSvb09SdLi4mJoerPZHNo6Nv/yX/5L/dRP/VQPEQMAAACz45/+03+qv/k3/+a4w4AFfSYAAIDhmoQ28Be/+EU9+h3foW+Mqfy7775bn//85yd+kGTmB0iWlpYkSfv7+6HpyWRyaOvYPPzww5KkK1eu6Du/8ztPjdsk7NtQKysr2t3djZxnmBs3bujxxx/Xyy+/rHvuuWeoeY8iXvI9NlfH7XOfk37yJ6Vf/VXp/e8fXr6nGGq+d/bhz69c0Q8++eR8HLcZyneuXm8zlC/HbTrznbrjdspn1CDiPG6Dfnvus5/9rH72Z39W3/qt3zpoeBixWewz/Y2/8TcGfq0M671nWK/bYeQzSbFMdf0a3ucnon6H3MeYiH0acj5zf/6OOB/qd7T5zFz9DrHdPKz6/bVf+7WZaQN/5Stf0TckfVhS3HNZviLpk1//ur7yla8wQDJuQSPc9G2lZDI5tHVsFhYWJB3ffze4B++wLCwsDD3P69evS5I+8IEP6L777htq3qOIl3yPzeVxe//7pZDtJzbeEDfuXACYq+M2A/nO5ettBvLluE1nvtN43CQZP6MGMU3HLTDIrZIQj1nsMw3jnB7We8+wXl/DyGeSYpmJ+j3xPj9J9TusPsYk7dOw8uH8HW0+1O9o85nF+pU0lHbzsOr3+77v+wbKIzBJbeBvkfTguIOYYD0PkAQvnkEMu0Pbi+XlZUnd97sN/k+lUkNbBwAAAMB8m8Z+E30mAACA2XVO8c+SmKZZGWd6XTGRSOjChQuRf0z3oR21RCIh13VVrVY7ltdqNUnSxYsXh7YOAAAAgPk2jf0m+kwAAACYVz0P5iQSCWWzWT3wwAN9F/KVr3xFV65c6Xu7ftge+HflyhWlUik1Go3WtO5CoaBCoaBEIjHUdQAAAADMr0nuN9FnAgAAmD/nJN01hjKnRc+xXrx4UT//8z8fuSDHcSJvexrP81QsFiVJL730kjKZjNLpdKsB7rqu6vW68vm8ksmkGo2G8vm8stlsK49hrQMAAABgfk1qv4k+EwAAANCtrxkkk8p1XRWLxVaD37ROuVw+NZ9hrAMAAABgPk1qv4k+EwAAANCt5wGSXC43UEGDbg+z9fX1cYfQl1HFS76jNW31MG35jsq01cO05Tsq01YP05bvqExbPUxbvqNCvKPNdx7Rb5oMk3RODyuWYeQzSbEMyyTt0yTFMiyTtk+TdJyGYZLqZVj5UL+jzWcW63dYZq1+h+ms4r/l1dmYyxuE4/u+P6rMr169qkuXLo0q+6nieZ5SqZTq9bpc1x13OKe6fv267r//fr399tu67777xh0OejRXx83zpFRKqtelKXhNhbqzDzdefln3Pv74fBy3GTJXr7cZwnGbTlN33GbhM2oIfvu3f1uPP/64Xn75Zf3QD/3QuMOZaPSbjk1an2nq3numzFTX7yS/z9PHiMVUn79TgPodrYmq30l+P41oktrAQdvqb0v6tpjL/hNJ/7M0Me06m4EGj1599VXVajXt7e11pe3v76tWq9HQBwAAADDX6DcBAABgXHhIu13kWH/u535OH//4x2WbgDLKB7MDAAAAwKSj3wQAAABMrjNRNyyVSlpZWVG9XtfBwUHXz2uvvaaVlZVhxgoAAAAAU4V+EwAAAMYpeAZJnD/T9AySyDNIFhcXtb29rYcffjg0/f7771ehUIiaPQAAADA1HOdy6+/H9JY8SW6qqFf0oHx/c3yBYezoNwEAAACTK/IMklwup0ajYV3n7bffjpo9AAAAAEw9+k0AAADA5Io8QPKxj31M5XJZX/jCF3T9+vWunzfeeENbW1vDjBUAAAAApgr9JgAAAIxT8JD2OH/m4iHt169f197enpLJ5DDjmXkrKytaWFgITVtfX9f6+nrMEQEAAADR7OzsaGdnJzTtz//8z2OOZjLRb+offSYAADDJaAPPlsgDJKurq6rVanJdN7Sxf3BwoN/6rd8aKLhZtLu7K9d1xx3Gqc6fP6/NzU2dP39+3KGgDxy36XT33Xdz3KYQr7fpxHGbThy3yWW7WP17v/d7+v7v/37dfffdMUc1Weg39W9S+ky894wW9Tta9DFGi/N3tKjf0aJ+BzdtbeDgIe1xlzktItfNtWvXVKvV9MM//MPGda5cuRI1e4zZ+fPn9eyzz447DPSJ4zad7r77bo7bFOL1Np04btOJ4zadgk7hJHUOx4F+0/TivWe0qN/Roo8xWpy/o0X9jhb1O1q0gadP5AGS5eVlLS4uWtd58skno2YPAAAATA3f33z3H8+TUiV59Zw0Ad+Cx3jRbwIAAAAmV+SHtBeLRb344ovWdT75yU9GzR4AAAAAph79JgAAAIwTD2m3ixzrpz71KXmep49+9KNKJBKh65RKJX34wx+OWgQAAAAATDX6TQAAAJhF1Ts/Yb4eZyADijxA8tJLL6lWq1nXcRwnavYAAAAAMPXoNwEAAGCczmk0Mzp+9M5PmNclPT2CMkchct2sra0pmUwql8uFpn/1q1/V9vZ25MAAAAAAYNrRbwIAAAAmV+QBkosXLyqdTuuRRx4xrvPAAw9EzR4AAAAAph79JgAAAIxT8AySuMucFpEf0n7//fdbG/mSVK/Xo2YPAAAAAFOPfhMAAAAwuQYazHn11VdVq9W0t7fXlba/v69araZLly4NUgQAAAAATDX6TQAAAMBkijxA8nM/93P6+Mc/Lt/3jevwsEEAAAAA84x+EwAAAMaJW2zZRb7FVqlU0srKiur1ug4ODrp+XnvtNa2srAwzVgAAAACYKvSbAAAAgMkVeTBncXFR29vbevjhh0PT77//fhUKhajZAwAAAMDUo98EAACAcTqr+Gd0nI25vEFEnkGSy+XUaDSs67z99ttRswcAAACAqUe/CQAAAJhckQePPvaxj+mjH/2olpaWdOHCha70/f19bW1t6cUXXxwowFmzsrKihYWF0LT19XWtr6/HHBEAAAAQzc7OjnZ2dkLTDg8PY45mMtFv6h99JgAAMMloA8+WyAMk169f197enpLJ5DDjmXm7u7tyXXfcYQAAAAADs12s9jxPqVQq5ogmD/2m/tFnAgAAk2za2sA8pN0ucqyrq6uq1WpyXTe0sX9wcKDf+q3fGig4AAAAAJhm9JsAAACAyRV5gOTatWuq1Wr64R/+YeM6V65ciZo9AAAAAEw9+k0AAAAYJx7Sbhf5Ie3Ly8taXFy0rvPkk09GzR4AAAAAph79JgAAAGByRR4gKRaLpz5I8JOf/GTU7AEAAABg6tFvAgAAwDgFzyCJ88c2Y6XZbCqfzyufz58ae61W04ULF7qWe56ntbU15fN55XI5VSqVU/MyiTy75lOf+pQ8z9NHP/pRJRKJ0HVKpZI+/OEPRy0CAAAAAKYa/SYAAADgWK1WU7FYVKVSUTabPXX9XC7XtazRaCiVSqler8t1XUnS0tKS9vf3e8rzpMgDJC+99JJqtZp1HcdxomYPAAAAAFOPfhMAAABwLJ1OK51O99T+zefzSiaT2t/f71iey+WUTqdbgyPBurlcLt4BkrW1NSWTydBRHEn66le/qu3t7ajZAwAAAMDUo98EAACAcZrGh7TXajU98MADcl1X165day1vNpuq1WoqFAod6y8vL0s6npnd7yBJ5Lq5ePGi0um0HnnkEeM6DzzwQNTsAQAAAGDq0W8CAAAA+lMsFlUul7ueUxIMliSTyY7lwWySarU6ugGS69ev67777mv9f//99+v++++3bvPYY48ZtwcAAACAWUO/CQAAAJMkeEh7P75+5yeqbwywbT6f75ohEmg0GpJkfLZfkN6PM72uuLW11Xfmw9weAAAAACYd/SYAAABMu38i6fEBfp6MWK7neXrggQe6ZogE9vb2JEmLi4uh6c1ms+8y4779GAAAAAAAAAAAmFD/naSfGGD7P1a0QZKtrS2Vy2Vj+tLSkiR1Pbg9YBpYsel5gKRSqejRRx+V7/t9F9JsNlUqlfg2FAAAAICZRr8JAAAAk+Sc+p8lcU7SXxigzHsjbJPP55XJZDpukxX8HfwOBkBMM0VGOkCyt7enJ5+MOjlGchwn8rYAAAAAMA3oNwEAAAD9q9Vq2t7eDk1bWlqS67r61Kc+Jan7WSPB/6lUqu9y+xogAQAAAACY0W8CAADAJInykPZhlNmver3etSyfz6tUKung4KC1zHVdVatVbWxstJbVajVJ0sWLF0cX6yOPPNJ35ui2srKihYWF0LT19XWtr6/HHBEAAAAQzc7OjnZ2dkLTDg8PY45mMtBvGhx9JgAAMMloAw8myoPU2125ckWpVEqNRqN1S61CoaBCoaBEItF3fjykPWa7u7tyXXfcYQAAAAADs12s9jwv0hR3gD4TAACYZNPWBj6r+AcBzhqWe56nYrEoSXrppZeUyWSUTqf7GthwXVf1el35fF7JZFKNRkP5fF7ZbDZSrAyQAAAAAAAAAACAkXJdV8VisTVIcppgZkhYPuVyeSgxMUACAAAAAAAAAIiF41yWJD2mt+RJclNFeX5vF8yBYWOABAAAAAAAAACAGTQtD2kflzPjDgAAAAAAAAAAACBuIx0guXr16iizBwAAAICpR78JAAAAoxLMIInzZy5mkPzCL/yCNX13d1e5XC5q9gAAAAAw9eg3AQAAAJMr8gDJ1taWPvvZz3Ytf+ONN/QjP/Ijunjx4kCBAQAAAMC0o98EAAAATK7Is11c19XHPvYxpVIpbW1tSTr+dlQ+n5fv+0qn00okEsOKEwAAAACmDv0mAACATr6/efyH50mpkrw6s2lH6aziv+XV2ZjLG0TkuqlUKrr//vt15coVve9975MkNRoNPfLIIyoWi/rQhz6kt99+e2iBAgAAAMC0od8EAAAATK7IAySf+tSn5LquqtWq9vb2JEmJREK1Wk0PP/ywJOn+++8fSpAAAAAAMI3oNwEAAGCczp2V7nJiLtOXdBRvmVFFfgbJ6uqqlpaWVKlUlM1mdXBwoFqtptXV1daDCK9fvz60QAEAAABg2tBvAgAAACZX5AESSXrkkUdUr9f1j//xP9b9998v13V17do1+b6vRx99lAcOAgAAAJh79JsAAAAwLmfPSufOxftzdooeQhJ5gCSdTuu1117TY4891pX2sY99TP/qX/0rvfbaawMFBwAAAADTjH4TAAAAMLkiP4OkWCxa05PJ5KnrzKOVlRUtLCyEpq2vr2t9fT3miAAAAIBodnZ2tLOzE5p2eHgYczSTiX5T/+gzAQAw2xznsiTpMb0lT5KbKsrzp6c9RBv42JVb0hXDc0a+5scbyyAiD5A88sgjp67zoQ99KGr2M2t3d1eu6447DAAAAGBgtovVnucplUrFHNHkod/UP/pMAABgkk1bG/jcGemuEdzy6m+dlf6WIe2VI+mDXxt+maMw0DNIAAAAAAAAAAAAplHkGSQAAAAAAAAAAGBynTsnnYv5oennnHjLGwQzSAAAAAAAAAAAwNxhgAQAAAAAAAAAAMwdbrEFAAAAAAAAAIiF728e/+F5Uqokr54bb0Az7txZ6a6YRwGmadCBGSQAAAAAAAAAAGDuMEDSo0ajMe4QAAAAAGBi0WcCAACYQGcknY35Z4pGHaYo1MFlMhk5jhP6U6vVOtY9mb62ttaR7nme1tbWlM/nlcvlVKlU4twVAAAAABg6+kwAAACYJ9N0O7CBNBoNNRoNFQoFJRKJ1vK9vT1tb28rnU63lpVKJWWzWS0tLbWWtac3Gg2lUinV63W5ritJWlpa0v7+vrLZ7Oh3BgAAAACGjD4TAADADDqr+EcBbsdc3gDmZoCkVqupXq93NPQldTX0JalcLqtarRrzyuVySqfTrYa+pNa3omjsAwAAAJhG9JkAAAAwb+ZmgMTUCH/xxReVy+Va/1cqFV27dk1ra2vKZDJd2zWbTdVqNRUKhY7ly8vLkt79JhUAAMA4Oc7lSNv5/uaQI5k8trqZh/0HTOgzAQAAYN7M1TNITmo2m/I8TxcvXmwtq1arajabqlQqyuVyunDhQse9dq9duyZJSiaTHXkF34yyfYsKAAAAAKYJfSYAAIApd25MP1NiikIdvpdeekmu63ZMIS8WiyoWi/I8T8ViUaVSSZlMRnt7e0omk2o0GpLUNe08EKSb3LhxQ9evX48c8/nz53X+/PnI2wMAAAC9uHnzpm7evBl5+xs3bgwxGowLfSYAADBPaAPPn7keICmXy3riiSdC01zXVbFYVCaT0dramvL5vMrlsvb29iRJi4uLods1m01rmY8//vhAMW9uburZZ58dKA8AAADgNFtbW7p8Odqt2jA76DMBAIB5MpNt4HE8pP0o5vIGMLcDJMF9cYvFonW91dVVra6uyvM8SdLS0pIkaX9/P3T9k9PIT3r55Zf1gQ98oP+A7+CbUAAAAIjD008/raeeeiry9q+++urAF7oxXvSZAADAvKENPH/mdoCkVqspmUye2jiXpEwm07qnbrC+6VtPp+V3zz336L777usvWAAAACBmg96m6J577hliNBgH+kwAAGDe0AaeP3M7QPLiiy9qdXW15/WXl5c7fp+8b27wfyqVGlKEAAAA0fn+5tDzdBz7VPNRlDkac9sEBvpCnwkAAIxC0K94TG/Jk+SmivJ8+4xVDOCMjm+zFXeZU2KKQh2uSqVivJfuSdVqVblcTtLxgwZd11W1Wu1YJ/i21MWLF4cbKAAAAACMAX0mAAAAzLq5HCCpVCqtRns7z/OUSqW0vb3dse7i4mLHN6euXLmiWq3W8Y2oQqGgQqGgRCIx8vgBAAAAYJToMwEAAMyI4CHtcf7EPWNlAHN5f4EXX3wx9FtLyWRSi4uL2traUrValeu6ymQyXQ8ldF1X9Xpd+XxeyWRSjUZD+Xxe2Ww2rl0AAAAAgJGhzwQAAACbnX1p5yA87fB2vLEMYi4HSMrlcujyRCLRNQ3cxHVdYz4AAAAAMM3oMwEAAMBmffH4J4x3KKXeiDWcyOZygAQAAAAAAAAAgJkX3PYq7jKnxFw+gwQAAAAAAAAAAMy3KRrLAQAAQK8c53Kk7Xx/M1LaNPH9Z8YdAgAAADC3Wv0Kz5NSJXn13HgDmnVnFP9D06doWsYUhQoAAAAAAAAAADAczCABAAAAAAAAAGAWnVX8owBxz1gZADNIAAAAAAAAAADA3GGABAAAAAAAAAAAzB1usQUAAAAAAAAAwCw6p/hHAaZo1GGKQp0NKysrWlhYCE1bX1/X+vp6zBEBAIBZ5PubxjTHeS5Sno5zOXKZmE07Ozva2dkJTTs8PIw5GswK+kwAgHlmanNPSls7LD5TbJO+L1HRBp4tDJDEbHd3V67rjjsMAAAAYGC2i9We5ymVSsUcEWYBfSYAADDJpq4NfEbxPzR9ih7sMUWhAgAAAAAAAAAADAcDJAAAAAAAAAAAYO5wiy0AAAAAAAAAAGbRWcU/ChD3Lb0GwAwSAAAAAAAAAAAwd5hBAgAAMGd8/5mI220OOZLZ4TiXW38/prfkSXJTRb2iB6k3AAAA9GzS2479xDfp+zI3mEFixQwSAAAAAAAAAAAwd5hBAgAAAAAAAADALDqn+EcBpmjUgRkkAAAAAAAAAABg7jBAAgAAAAAAAAAA5s4UTXYBAAAAAAAAAAA9O6ORPDR95w1p54vhaYdHwy9vVBggAQAAmEGOc9mY5vubMUYyO3quU8+TUiV59ZzkujFEBgAAgEnmOFdDl/v+pZgjAYZn/eHjnzDe21Lq03FGEx0DJAAAAAAAAAAAzKKzin8UYAQzVkaFZ5AAAAAAAAAAAIC5wwySmK2srGhhYSE0bX19Xevr6zFHBAAAAESzs7OjnZ2d0LTDw8OYo8GsoM8EAAAmGW3g2cIAScx2d3flci9qAAAAzADbxWrP85RKpWKOCLOAPhMAAJhkU9cG5hZbVtxiCwAAAAAAAAAAzB1mkAAAAMwg3980pjnO5Ujbzbte6/QxvSVPkpsq6hU9SJ0CAADMOd+/NO4QMM/OKv4ZHcwgAQAAAAAAAAAAmFzMIAEAAAAAAAAAYBbxDBIrZpAAAAAAAAAAAIC5wwAJAAAAAAAAAACYO9xiCwAAAAAAAACAWcQttqwYIAEAAJgzvr857hDGynEuG9NsddPzdp4npUry6jnJdSPFCAAAgOljai/Oe/sbmGTcYgsAAAAAAAAAgFl0dkw/Bs1mU/l8Xvl8PjS9UqkolUrJcRylUinVarWudTzP09ramvL5vHK5nCqVSh8V0okZJAAAAAAAAAAAYKRqtZqKxaIqlYqy2WxX+vb2tqrVqnK5nPb29rS9va1MJqNqtap0Oi1JajQaSqVSqtfrcu/M2F9aWtL+/n5onqdhBgkAAAAAAAAAABipdDqtcrlsTP/MZz6jarWqbDarQqGger0uSSoUCq11crmc0ul0a3BEUmsmSRQMkAAAAAAAAAAAMIuCh7TH+RPhIe21Wq1jIESSXNeV67pqNBqSjm/PVavVlMlkOtZbXl6WJJVKpb7LZYAEAAAAAAAAAACMTTqdVjKZDE0Lll+7dq3j/0Awm6RarfZdLs8gAQAAAAAAAABgFgUzSPpw8+j4J6obt6Nve1Kj0WjdPiuYSZJIJIzr9osBkpitrKxoYWEhNG19fV3r6+sxRwQAANAbx7lsTff9zZgiGVTUJjBN55N2dna0s7MTmnZ4eBhzNJgV9JkAANPK1B42taOnp/2MdvPQBt7ypMv1cUchVSoVJZPJ1sPX9/b2JEmLi4uh6zebzb7LoJcXs93d3Y4HyAAAAADTynax2vM8pVKpmCPCLKDPBAAAJtnUtYEjzCB5+nulpwbYjVe/Ij3+yejbB7a2tjoe6r60tCRJ2t/fD13fdIsuGwZIAAAAAAAAAACAJOn82eOfqO4ZwqhDPp/XlStXOgY9gr9NM0WiDJDwkHYAAAAAAAAAADARSqWSMplM16zi5eVlSd3PGgn+jzJ7hwESAAAAAAAAAABm0dkx/URUqVQkSel0umO553lKJBJyXVfVarUjrVarSZIuXrzYd3ncYgsAAAAAAAAAAIyc7UHqtVpNW1tbyuVyKpVKreX1el2pVEqu6+rKlStKpVJqNBqtW2oVCgUVCgUlEom+42GABAAAYM44zvPGNN9/yrLlrDQdFyJt5fvPGNMc53Lr78f0ljxJbqqoV/SgfH8zUnkAAACYDbPeHmxvC7eb9f2eGhEe0j6UMkN4nqdisShJeumll5TJZJROp5VIJOR5njKZjCQpl8t1bXtwcCBJcl1X9Xpd+XxeyWRSjUZD+Xxe2Ww2Uqiz0ssFAAAAAAAAAAATynVdFYvF1iDJyTTf93vOp1wuDyUmnkECAAAAAAAAAADmDjNIAAAAAAAAAACYRRN0i61JxAwSAAAAAAAAAAAwd5hBAgAAAAAAAADALDqr+Gd0TNEMEgZIAAAAppTjXB53CFPqvqHn6Pub7/7jeVKqJK+ek1x36GUBAABgupja7R1tyAjrjoPjXO1aNimxAVEwQAIAAAAAAAAAwCziGSRWPIMEAAAAAAAAAADMHWaQxGxlZUULCwuhaevr61pfX485IgAAACCanZ0d7ezshKYdHh7GHA1mBX0mAAAwyWgDzxYGSGK2u7srl3tRAwAAYAbYLlZ7nqdUKhVzRJgF9JkAAMAkm7o2MLfYsuIWWwAAAAAAAAAAYO4wgwQAgCngOJeNab6/GWMks2MW6jRqnI7zXMQSb0XcbrL4/iVj2iycFwAAYLaY2ie0TSbPPBwrW1v6pHmoj6nADBIrZpAAAAAAAAAAAIC5wwAJAAAAAAAAAACYO9xiCwAAAAAAAACAWXRWI7nl1c7vSjv/Ljzt8BvDL29UGCABAAAAAAAAAAA9W/+B458w3ptS6n+JN56ouMWWpEajMe4QAAAAAGBi0WcCAACYUsFD2uP8maKHtM/lDBLHcTr+d11X9Xq99b/nedra2lIymVSz2VQmk9Hq6mrHNr2sAwDAsPj+5rhDmDmzXqeOc3ncIUwsx3nOkjqXzWOgC30mAJgcs95unSWmY2Vqm0/jsXWcq13LfP+SYe2HRhsMMARz1wMslUrKZrNaWlpqLUun062/G42GUqmU6vW6XNeVJC0tLWl/f1/ZbLbndQAAAABgGtFnAgAAmCHBDJK4y5wSczdAUi6XVa1Wjem5XE7pdLrViJekfD6vXC7Xasj3sg4AAAAATCP6TAAAAJgXc/UMkkqlomvXrmltbU2lUqkrvdlsqlarKZPJdCxfXl6WdPxNql7WAQAAAIBpRJ8JAAAA82SuBkiq1aqazaYqlYpyuZwuXLigWq3WSr927ZokKZlMdmwXfOupWq32tA4AAAAATCP6TAAAADPm7Jh+psRc3WKrWCyqWCzK8zwVi0WVSiVlMhnt7e0pmUyq0WhIkhKJROj2jUajp3Vsbty4oevXr0feh/Pnz+v8+fORtwcAAAB6cfPmTd28eTPy9jdu3BhiNIgLfSYAADDPaAPPn7kaIAm4rqtisahMJqO1tTXl83mVy2Xt7e1JkhYXF0O3azabPa1j8/jjj0cPXNLm5qaeffbZgfIAAGASOc5lY5rvb8YYyWSJWi+2NMd5PmI090bcbtLcGnqO7cfpMb0lT5KbKuoVPTi15+/W1pYuXzaff5ht9JkAABieftqDk992fLNrianPYtqXYP32drPnF4cW4SBmsg3MQ9qt5nKAJLC6uqrV1VV5nidJWlpakiTt7++Hrp9MJntax+bll1/WBz7wgYgRi29CAQAAIBZPP/20nnrqqcjbv/rqqwNf6Mb40WcCAADzhDbw/JnrARJJymQyrXvqBg110zeakslkT+vY3HPPPbrvvvuiBQsAAADEZNDbFN1zzz1DjAbjRJ8JAADMC9rA82fuB0gkaXl5ueP3yXviBv+nUqme1gEAAACAWUKfCQAAYEpxiy2rM+MOYNyq1apyuZyk44cIuq6rarXasU7wbamLFy/2tA4AAAAAzAr6TAAAAJhVczNA4nmeUqmUtre3W8sqlYoWFxe1urraWnblyhXVarWObzsVCgUVCgUlEome1wEAAACAaUKfCQAAYAad0fGMjjh/pmjUYW5usZVMJrW4uKitrS1Vq1W5rqtMJqNisdixnuu6qtfryufzSiaTajQayufzymazfa0DAEC/HOeyMc33N2OMZDwmaR8n6VhELW+S9mEQce/HNNUNMGz0mQBguoS1k0bZljG1y2g/wXQOOM5V+/qeJ6VK8uq5UYUGnGpuBkgSiUTXFG8T13VVLpcHXgcAAAAApgV9JgAAAMybuRkgAQAAAAAAAABgrpxT/KMAUzTqMEV3AwMAAAAAAAAAABiOKRrLAQAAAAAAAAAAPTur+EcBzsZc3gCYQQIAAAAAAAAAAOYOM0gAAAAAAAAAAJhFI5pBsvMvjn/CHH59+OWNCgMkAABMCN/fHHcIU8lxLkfazlbf03IsbPtu2wfHed6y3VOWEg97CWuoRnMs7o20leO8YEzriNPzpFRJXj0nuW6ksgAAmHdh7ZxpaaPFJe76mMb6N7WXJ3lfJj3m/uJ4M3RpsI+P6S15ktxUUZ5fHDw4xGr9/3r8E8ZrSKl8vPFExS22AAAAAAAAAADA3GEGCQAAAAAAAAAAs+iM4n9o+hRNy2CAJGYrKytaWFgITVtfX9f6+nrMEQEAAADR7OzsaGdnJzTt8DD+W7JhNtBnAgAAk4w28GxhgCRmu7u7crkXNQAAAGaA7WK153lKpVIxR4RZQJ8JAABMsqlrA59T/KMAUzTqMEWTXQAAAAAAAAAAAIZjisZyAABAnBznsjHN9zdjjMRukmKZJKM5frcibjdp3om43ZeNKY7zXOvvx/SWPElu6pf1in5Tvv9MxPIAAJhfk9zGM7WzwmLuZ91hiLu8STfK/Q6r637Ls7XZJ5XjXO1a5vuXQtc9tT48T0qV5NVzwwgNiIQBEgAAAAAAAAAAZtFZxT8KEPdD4QfALbYAAAAAAAAAAMDcYQYJAAAAAAAAAACz6Izin9ExRdMypihUAAAAAAAAAACA4WAGCQAAAAAAAAAAs4hnkFgxQAIAiJ3jXDam+f5mjJHAZpKOxSSdM6OIZRR52rZznOct2z019FiOy5ycYyjdO4I8F9r+Pt/2eyFkXQAAMM36abvE3c6ZpDb8rBtGXU/j8fL9S+MOARgqbrEFAAAAAAAAAADmDjNIAAAAAAAAAACYRecU/yjAFI06MIMEAAAAAAAAAADMnSkaywEAAAAAAAAAAD07o/gfmj5F0zKmKFQAAAAAAAAAAIDhYAZJzFZWVrSwsBCatr6+rvX19ZgjAoD4+f7muEOYOo5z2Zg2D/U5Sfs4ilii5mnbznbO2JqA9u0ePSWen7CkTc4xtHGc5yypD1nSvtT2982234cDxzTJdnZ2tLOzE5p2eDjb+47Roc8EABi1sDbvKNurpjZ2WJn9rDsOjlPrWub7acO6V0OX+/6locYUN9rAs4UBkpjt7u7Kdd1xhwEAAAAMzHax2vM8pVKpmCPCLKDPBAAAJtnUtYHPaiSjADuV458whzfDl08iBkgAAAAAAAAAAEDP1lePf8J4/0FK/VSs4UTGAAkAAAAAAAAAALPonOIfBZiiUQce0g4AAAAAAAAAAObOFI3lAAAAAAAAAACAno3oGSSnljklGCABAGAK+P7muEMYCse5bEyblX2cFLb6dJznLds9ZdnuuYFimhwLlrRDS9qbPeZ/q+33LduKAABgREztTtqckIZzHoSdY6Z8+yvvoYgRxcP3013LHOeqYd1LocuDuntMb8mT5KaK8vzi0GIE+sEttgAAAAAAAAAAwNxhBgkAAAAAAAAAALPojOK/5dUUTcuYolABAAAAAAAAAACGgxkkAAAAAAAAAADMIh7SbsUMEgAAAAAAAAAAMHeYQQJgbjjOZWOa72/GGMl8oL6nQ9zHiWM/XI7zvCX1HUta1CbgQsTtJs19lrR9S5qt3hbb/v5a27L39BoUAGAGOc7VrmW+f2kMkcyfcbQ7w9rWtH9nVz/H1tTvmsbzI+x9TXqzrzxa++15Uqokr54bPDAgIgZIAAAAAAAAAACYRecU/yjAFI06cIstAAAAAAAAAAAwd6ZoLAcAAAAAAAAAAPTsjOJ/aPoUTctggCRmKysrWlgIv3/3+vq61tfXY44IAAAAiGZnZ0c7OzuhaYeHhzFHg1lBnwkAAEwy2sCDaTab2trakiQVCoWudM/ztLW1pWQyqWazqUwmo9XV1b7X6RUDJDHb3d2V67rjDgMAAAAYmO1ited5SqVSMUeEWUCfCQAATLKpawOfVfyjAIYZK7VaTcViUZVKRdlstiu90WgolUqpXq+32oNLS0va399vrd/LOv2YoskuAAAAAAAAAABgGqXTaZXLZWN6LpdTOp3u+LJMPp9XLpfra51+MIMEwNzw/c1xhzBXota341weep4wG0Wd2o6hjS0Wx3nOst0zkWKZpPMpepzvt6T9gSUt/NY1p3tvxO0mzWuWtHuNKb7/lDGt8xjut/3+pn4CAwDMGN+/NO4QZoqpzTQp7bqwOCY9ZkQXdmzn4bjyvoZRaTabqtVqXbfdWl5eliSVSiVdvHjx1HX6nUXCDBIAAAAAAAAAAGZRcIutOH8iPBT+2rVrkqRkMtmxPJgpUq1We1qnX8wgAQAAAAAAAAAAkqSbN6WbX4++/Y0/73+bRqMhSUokEsb0XtbpFwMkAAAAAAAAAADMomBWRx+2npcu/8JIojHa29uTJC0uLoamN5vNntbpFwMkAAAAAAAAAABAkvT0/1N66qPRt3/1/5Ae/7/1t83S0pIkaX9/PzQ9mUz2tE6/GCABAAAAAAAAAACSpPPnj3+iuueb+98mGNwwzQJJJpM9rdMvBkgAABPF9zfHHcJIOc5lY9qs7HvU/YhaN9G3e86y3TND3240/sCSZmvmvROxvDcibjdpHrWkvREpx45zzfOkVElePSfdeVggAACnsbVpTpqVduM84FjNrv6O7UN9rPtmv6EAVv4ZyY/w0PRBy+zX8vKypO7niAT/p1KpntbpV4RQAQAAAAAAAAAAhiORSMh1XVWr1Y7ltVpNknTx4sWe1ukXM0gAAAAAAAAAAJhBR2elo5hHAY4sM1ZsD1K/cuWKUqmUGo1G63ZZhUJBhUJBiUSi53X6wQAJAAAAAAAAAAAYKc/zVCwWJUkvvfSSMpmM0ul0a2DDdV3V63Xl83klk0k1Gg3l83lls9lWHr2s0w8GSAAAAAAAAAAAmEG3xzCD5LZhBonruioWi61BEtM65XLZmn8v6/SKZ5AAAAAAAAAAAIC5wwySmK2srGhhYSE0bX19Xevr6zFHBEwfx7msx/SWPEluqqhX9ODAefr+prW8KNvBzFanNnHXd9Rjb9+/2fjoHUXdRD2+0c+LW8aUqOdoVKPYd8d5zrLleyzb2fb9odODmgpfsqQ9bExxnOct273bvntMX7zzGVXWK/p9+f5H+w1wauzs7GhnZyc07fDwMOZoMCvoM2GWOE6ta5nvp/vKgz7Hu6iL05nactRddMOp0zd7znvSj5XjfKNrme/fZVjX3q9qv7bj+eYZBZOGNvBsmY2rNFNkd3dXruuOOwwAAABgYLaL1Z7nKZVKxRwRZgF9JgAAMMmmrQ18dNbRrbNOzGX6kvxYy4yKW2wBAAAAAAAAAIC5wwwSAAAAAAAAAABm0NHZszo6F+88iaOzt2W7rfUkYQYJAAAAAAAAAACYOwyQAAAAAAAAAACAucMttgBMHd/flDxPSpXk1XNS20M8HeefWbZ8I2KJ90bcDia+v2lMc5zLMUZiFzVO23ZROc5zlvKeGXp5p5msuhn+OWPfP/OxiJt9323NvP2I2y3YA5oa5v3w/Z8wptmP/Tttf++3/f6mfgIDAEwp02dyP22fUbSTplk/bTzq7l3jqIuwY9VvHMPIY1T6iaPf94Kw9YfxfjJKvn9X1zLz6/Uhw/I3hxYPTnf77FkdnY13nsTts464xRYAAAAAAAAAAMCEYoCkR41GY9whAAAAAMDEos8EAAAweY50Rkc6G/PP9Aw7TE+kQ1KpVJRKpeQ4jlKplGq1Wuh6juN0/KytrXWke56ntbU15fN55XI5VSqVOMIHAAAAgJGizwQAAIB5MVfPINne3la1WlUul9Pe3p62t7eVyWRUrVaVTqdb65VKJWWzWS0tLbWWtac3Gg2lUinV63W5d559sLS0pP39fWWz2fh2CAAAAACGiD4TAADAbDnSWd3S2ZjLnB5zNUDymc98RtVqtfX/E088oVQqpUKh0NGYL5fLHeudlMvllE6nWw19Sa1vRdHYBwAAADCt6DMBAABgnszNAEmtVlOhUOhY5rquXNftuFdupVLRtWvXtLa2pkwm09V4bzaboXktLy9LevebVADGw/d/YtwhzBzHec6SesuY4vubkcqLul3cRhGn41yOtbxBxB2r7Ty0lRc1zuk5FveOIM93LGnXR1DeOBxG3G6hx/W+ue33KI4RMBr0mYDoJqt9EB9Tm2kY9THrdTrKuhtUv7HN6/F2nKtdy0z70U+dhuU7SRzn813L+j1+tv4Wpsc/2bmpf7Lz9dC0rx36MUcT3dw8gySdTiuZTIamtS+vVqtqNpuqVCrK5XK6cOFCxz13r1271rWNpNY3o2zfogIAAACASUWfCQAAYPbc1lkd6dzQf/7b9W/Wv/73F0J/Srv3jXu3ezY3M0hMGo2Gcrlc6/9isahisSjP81QsFlUqlZTJZLS3t6dkMtn65lQikTDmZ3Pjxg1dvx7925fnz5/X+fPnI28PAAAA9OLmzZu6efNm5O1v3LgxxGgwTvSZAADAvKANPH/meoCkUqkomUyGTu92XVfFYlGZTEZra2vK5/Mql8va29uTJC0uLobm2Ww2rWU+/vjjA8W8ubmpZ599dqA8AAAAgNNsbW3p8mVufzDv6DMBAIB5Mott4COd0VHsD2m/HWt5g5jrAZKtrS2Vy2XrOqurq1pdXZXneZKkpaUlSdL+/n7o+qYp6YGXX35ZH/jAB/oP9g6+CQUAAIA4PP3003rqqacib//qq68OfKEb40efCQAAzBPawPNnbgdI8vm8rly5cmrjXJIymUzrnrrB+qZvPZ2W3z333KP77puee7ABAABgPg16m6J77rlniNFgHOgzAQCAeUMbeP7M5QBJcI/c4CGBvVheXu74ffK+ucH/qVRqSFECmByH4w5g5Bwn6vTRufwYGRnf34y9zOjHPmp5z1lSbxlTotbNKLaLex/sFixpo3jvumsEeY7DRWOK/TVhe897f9vfwXTyByU93HNUwCShzwSMTr/tr3G0EXs1KbGF1emkxGYyyfFNcmz9Mr3ehrOPb4aUd9Ww7kOhS+Pujw3HJ0KWhdenqT5a9e95Uqokr54LXQ/DcfyQ9nhvsXV7im6xdWbcAcStUqlIktLpdMfyYDp4mGq12nooYSKRkOu6qlarHesE35a6eNHc4QYAAACASUefCQAAAPNirr76W6vVtLW1pVwup1Kp1Fper9db32J68skn9cQTT2hjY0PScedgcXFRq6urrfWvXLmiVCqlRqPRmh5eKBRUKBSUSCTi2yEAAAAAGCL6TAAAALPl9hge0n5bR7GWN4i5GSDxPE+ZTEaSWt9sandwcCBJWlxc1NbWlqrVqlzXVSaTUbFY7FjXdV3V63Xl83klk0k1Gg3l83lls9nR7wgAAAAAjAB9JgAAAMybuRkgcV1Xvu+fut7JaeC2/Mrl8qBhAQAAAMBEoM8EAACAeTM3AyQAAAAAAAAAAMyTWzqjWzHfYuvWFD36fHoiBQAAAAAAAAAAGBJmkAAYmONcNqb5/maMkUTnOC8Y03z/mZGU6aaK8u78fkUPnihz+PU2LcfJcZ6zpN4ypkTdh1HUiy3P6Gwf2eZ6kaLvh227qPtoez2Not7seZrr1BbnZO2DzXssae+1pH3OkrYYMZZJ8wfGFPt5/7wlz/22v99u+70fsi4AAN0mqU0+qUztIupueszSMQyLud+2+zDyiN9DA+cQ7ONjeqt1XcTzi/aNENltndNRzMMA0/SQdmaQAAAAAAAAAACAucMMEgAAAAAAAAAAZtBtndFRzM8guT1F8zKmJ1IAAAAAAAAAAIAhYYAEAAAAAAAAAADMHW6xBQAAAAAAAADADDoawy22jqZoXgYDJDFbWVnRwsJCaNr6+rrW19djjggYnO9vRtrOcS5PUJ53jSDP+E1SrLZYpHsj5TmKfbDl6TjPWbZ7Zuix2N0yppxWL/b9iFank/W6H/7+2cuzndvDz9N+jv5mxBIfspT34RGUN2m+y5jiOC9YtrvPktZep4d3fr9HtrqeBTs7O9rZ2QlNOzw8DF0OnIY+E0zCPi8nrT3em9n+bBgl0/Ge5HPD1M7rJ75h5DEp4o45/jr6oGH5433kMX3vEY5TC13u+5cM6w+/TxUn2sCzhQGSmO3u7sp13XGHAQAAAAzMdrHa8zylUqmYI8IsoM8EAAAm2bS1gY90VrdGMIOkvPNVVXb2Q9NuHt4eenmjwgAJAAAAAAAAAADo2dr6A1pbfyA07T94h/pvU3sxRxTN9NwMDAAAAAAAAAAAYEiYQQIAAAAAAAAAwAy6rbM6inkY4HbMD4UfBDNIAAAAAAAAAADA3GEGCTClHOeyMc33N2OMZNLcG3G7RWOK71+KmKedV89JqdLx7yE9iNR27G3nTNQ8R7GdjeM8ZynvmYh5Rnst8RqMytz0sJ+j77Gk3bLkGe2ccZwXLOWZjea8j/balR61pN0XMc9ZcWhJe68l7Y8sadfb/v6TO79fl/QNST/aY1wAMLvCPs/6/dycnTbWw+MOYObMzrkRbtb3Txr8PcJxrhpS3gxdOro6fcNQXrqPPB4eRiAT7qE7v4O+nK2/h0Ed6ayOYp7REXd5g2AGCQAAAAAAAAAAmDvMIAEAAAAAAAAAYAbd1pnYZ3TcnqJ5GdMTKQAAAAAAAAAAwJAwQAIAAAAAAAAAAOYOt9gCAAAAAAAAAGAGHY3hFltHUzQvgwESYEr5/ua4QxiYbR8c5znLds9Ycn0nYjT3RdwuOjdVlHfn9yt6sCPNXjeXI5U3inMmaizRRfvYGkWc0Y9R1I/eBUssT1m3tL1mor7Wpuc8vGXZzrzvtu1sxzBqntHPp0ctaeZzRrpuSbO5K+J2drZ9HM3nne2zYt+YYj9On2z77/ad3w9KeriPuABgdg3j/Tzs82KU/aJRlef76YmIY9aZ2hfU3emGUXdx17/vX+pr/WG8rsL38aG+8gj3acPy/t474vV46FJzO/+Dd35/487vBw3rAaPHAAkAAAAAAAAAADPoSGd1K/YZJPGWN4jpmesCAAAAAAAAAAAwJMwgidnKyooWFsJvebG+vq719fWYIwIAAACi2dnZ0c7OTmja4eFhzNFgVtBnAgAAk4w28GxhgCRmu7u7cl133GEAAAAAA7NdrPY8T6lUKuaIMAvoMwEAgEk2bW3g2zqro5iHAW5ziy0AAAAAAAAAAIDJxQwSYEo5zgvGNN//aMQ8L1vy3Iy0XXTmtyfHuazH9JY8SW6qqFf0YE/b2Zm/peg4z0XM0+4xS5q9zHstafFO5bSdF1GN5nwyi7oPUV8vUfOU3om4nT0e33/mtLCGKurxte/DKM5D22sw/LYvx8yvwajvo/btnrfEYvPeiNuN5hvdoziGdt9hSTO/x9rP3++KHA0AoDf9fF6EvWf3+3kzqs8nx/m8IeUTA8fhpopd/STT9qbPtWHs9zDqf1Dxty/CxR3HMPpTo4y5n/Ouv3WvGta91Ed0/fpgyLI3Qtc0ve59/33DCyc2b4Ys+5XYo0DvjnQm9oemH03RvIzpiRQAAAAAAAAAAGBImEECAAAAAAAAAMAMOn4GSbwzSHgGCQAAAAAAAAAAwARjBgkAAAAAAAAAAOjZP9/5ov73nf8Ymvb1w6OYo4mOARIAAAAAAAAAAGbQkc7o1ghuefUj64/oR9YfCU1reG/rY6nfHXqZo8AACeaO41y2pvv+Zuxlmthj2Y8WjJX5LWEU++A4L1i2/LI9T8+TUiV59Zzkum15RotTuteSdsuSZnsbtW0Xne8/NfQ87fUWdR/fY0kzH9+o5TnO88Y0+3n4nGW7ZyyxmEXNM+r7j62809MXLGnvRIon+jljfh3GvQ/2c8Z8rtnP0auW7aLu+1+2pC1a0h61lGd7P/gxS9ppZcbLvh8/bUl7LWKJn2v7+607v1+XdDNifgAw2Uzvs6PoT0XRTxzmz4yHQvK9FDGidp8IXWqKOSw+07pePRfaT+qnvFHp95zpZ7/xrnHUUT/98FHF1+9rMyyO/t/XPh2y7COGdV82LH9fH3lMirD4+ntfa/EWpZTk1W39GmC0GCABAAAAAAAAAGAGHemsjmIeBoj7ofCD4CHtAAAAAAAAAABg7jBAAgAAAAAAAAAA5g632AIAAAAAAAAAYAbd1tnYb3l1m1tsAQAAAAAAAAAATC5mkAAAAAAAAAAAMIOOdCb2GSRHUzQvgwGSmK2srGhhYSE0bX19Xevr6zFHNL0c5zljmu8/Y9nyuwYo07OU6Vq2/F7Ldj8aMRrzdo5z2bKd7WV/0ZL2G5a0v2xJs/moOSn8ZTI677/LnPY5W53dsqSd9hb7zW2/7z2R9o5xK/vxtbHFY06zv57MbK/RqHx/01Le8xFjMR/D6HVtyzPae9dg9Wk7Tw8tae+xpH3Zkhb1BWw+7+3nr2072z7s28MxstWZ7bV0yZgW9RzVQtqcdmj+zNK33GdM8v9/ltfZ9LRxT3m/sB37Nyxpf9eS1n4eflbSP5K0Kum/sGwz/XZ2drSzsxOadnhoe60AZvSZRs9xaqHLfT/8c8Vxroasa36fHZWwuM0x976u9EHD8k/3GFm/TOWFG0ddn2RqF5ti6yfmfvKO3j6352vS7373E98wjmv4a7m/87afeo77XBzGseon7373L7zuut8vbcLj/khfeUyGh0KXOh8zrP4Ln5ckPaYvypPkpr4oz3pdbbLQBp4tDJDEbHd3V647PS94AAAAwMR2sdrzPKVSqZgjwiygzwQAACbZtLWBj3RWt2KfQcIzSAAAAAAAAAAAACYWAyQAAAAAAAAAAGDucIstAAAAAAAAAABm0G2d1VHMwwC3ucUWAAAAAAAAAADA5GIGCSaa4zwXcbsXLKl3RQtmIPsjyPPQkmZ+afv+M8Y0x/mkJc/3W9I+aEmz+UNz0uG3GZMc55f0mN6SJ8lNFfWKHmxL/fFoofx1S9rnFiyJtrTTjvvNtt8nj+e9lu1sx/6WJc0W6zvGFMe5akzz/UuWPBctaV+2pJn3wf6eYNs/Wyy242TL08Zcn/bXoO29K2p9niZq3UQ9R211amuWPGxJu25Js+2D7Vy7bNnOFmfU89f22n3UnHRoe9/+LnPSV2rGJMf5ffN27zefv8fbmuvN9zet28bL9jn5lDHNcWzn2lfb/n677fdXZX+dAYCZ/fPopIdCl4a31z5tKO8NQ94P9xFHOMfp/uzx/XRfeYSt318dhZdnisNxwuspfN3wOEI//x4xlWdqd7/ZW76S3NSv3+kn/bpekXdnXVubvVfh55dJ+L48HLquaV/6O7a95zuMPPo53v3uR9j65n3p/Rztp7xR6uu1Ysyj+/zq93j3s9/m8yCkTX3O8Hr7i4a8G2H5fqPHyMbkkfd1L3v9E+Hrdr99YQyOdCb2h6YfWeZlVCoVVatVJRIJNRoNJZNJFQqFjnU8z9PW1paSyaSazaYymYxWV1dHEisDJAAAAAAAAAAAYKQqlYq2trZUr9dbyzKZjPL5fGuQpNFoKJVKqV6vy3VdSdLS0pL29/eVzWaHHhO32AIAAAAAAAAAACNVLBa1vLzcsSyTyahSqbT+z+VySqfTrcERScrn88rlciOJiQESAAAAAAAAAABm0PFD2uP9MT2kfX9/X7Va5+3p9vb2lEwmJUnNZlO1Wk2ZTKZjnWBQpVQqDb1+GCABAAAAAAAAAAAjlcvl1Gg0tLa2Jun4WSMvvfRS6/Za165dk6TWgEkgmE1SrVaHHhPPIAEAAAAAAAAAYAbdjvCQ9m/cPNKtm0eRy/zzG+HbZrNZ1et1lUolLS0tKZlM6vXXX1cikZB0/PwRSa3/TwrSh4kBEvTFcS4b03x/M9J20r2WtPda0t4fLU/nuy3bneKCe/o6Yf7qT0Qv0+T9HzQm+f/enGY/FuZjKH3anPTfmZOs5f1tS3l/ZE7yq5uS50mpkrx6Tmq7J6HjeOYNLW4/7RjTzvzCv7VseT1Secdu3Pl9n6TFE2mHEfN8yJL2pYh5fsOY4jjPWbZbsKQ9akmz1emXjSm+/5QxzXFesORpi/MdS1q0j1DHuRppO7vTYrHt437EMm3nqK082/u67Ry15Wnb7uRrq13U15nNw5a0Nyxptv17zZL2vRFjsfm8Oemb7Fva2gJRRW17WH3/fdG2S1u265gl/qd3fi/Kfs4DmGXm96+PhCz7gmFdc7u+23f0sW54m9H3L4UuH077pZ/4woXVqemzwHHMbdiude8ypYQdK5Pej9WzjZ8LX+6Y2gO2Nv5JX277HbW92k892/qXceq9jszn85tdS0z7PYo2z7u698Vcz2Hnnanvbqqj3vfbFEfY+v3FHK6fY2Uu7++GLg2PuRayZp9umWIOf38NdS78Tamf19tIz9HXu/sL5nPGUB/n7tSH/450JOnstw8pOAzLv9r6rH7z8isjybtYLOratWvyPE+NRkO1Wk2rq6uSjm+3JUmLi+F9+WazOfR4GCABAAAAAAAAAGAG3dJZ3epzBsmHnnb1+FP/ReQy33z1q/qlx38jNC2TySiXyymZTGptbU1ra2sql8taXV3V0tKSpONnlYQ5eeutYWCABAAAAAAAAAAASJLOnT+rc+f7G1Rpd/c94TOhcrmcpONbbUnS66+/rkceeURPPvmkVldXOx7WHoYBkhmwsrKihYXwabPr6+taX1+POSIAAAAgmp2dHe3s7ISmHR6O4jZ2mAf0mQAAwCSjDRzdSy+91BockY6fNVIoFJTL5eR5npaXlyV1P2sk+D+VSg09JgZIYra7uyvXjfgcCwAAAGCC2C5We543kg4MZh99JgAAMMmmrQ18W2d1FPMwwG3DLb0WFxe7Zoek02lJx4MliURCruuqWq1qY2OjtU6tdvyMoIsXLw491jNDzxEAAAAAAAAAAKBNLpfTSy+91DFIUqlU5Lpu6/ZZV65cUa1W65hFUigUVCgUlEgkhh4TM0jQxXGes6R+0LJdzbLdT5uTPvVt5rTfs2Rp81M3jUm3v8mxbuo4/8CY9p3+j1m2M+//9/rLlu3+2BJN+K0FJGnFN2/lONcteabNSX/Vstmz5mP/0z8UPq1Qkn75n7zHmPaB580H+NU//D5jmuM8r8f0J/Ikualf1Sv6N+8mPvqUcTubLy3eb0zL+teMaT+vp41pZ4+OrGX+lXMv3PnrfZL+kxOp5mNv9zlL2nstabbyXrOkmc8L6dOWtPdb0mzM++A4ly3bPWpJC3/w17HvMqb4/octsTxvyfNNS5r59SLFP03X958xptk/K2zn2hsRy7Md33stabZ6e8eSZmMuz35e2Oos6vG1nb8Wj77PnPZa+IP0JEmv2MtznF+ypNqOk/lY+P6mpTzbeWFjztPqU7bE9ve84H3zs5L+TNKPRisPwNg4zlVDSsjn+DnDe8oPGpaHdX/Khvfl/94Qxo93L3r2B34udFXH6W7n/Zf+DxjWDd/v7/S/t+d1zW2djxiWh8Vhen//u93rmrL9dPe9z435/o3wY7XyiT8IyeMTekxv3emLFPWKHjxOMB3vEF82tPn2/f9X6PILvxnSTvj7Txpyz3YtMfdVHw9fHHJOm49J78dV+kLoUvu1hJNM/Q9b36OT71/qed1+z3Nbu6U77372+yHD8u79NsVg2pd+YjbFEXZ+9Jdvf+26sLxN2/t++HMQ+onZGFsfr3uT0PPgEcN1m9e7z3/fD1/XfO52M70mhvK6f8TwevuPvWeBwR3pjI76fEj7MMoMs7GxoUQiobW1tdaM4WazqU996t3Oluu6qtfryufzSiaTajQayufzHbfmGiYGSAAAAAAAAAAAwMhls9lTBztc11W5XI4lHm6xBQAAAAAAAAAA5g4zSAAAAAAAAAAAmEHHD2mP9xZbpoe0TyJmkAAAAAAAAAAAgLnDDBIAAAAAAAAAAGbQkc7o1oQ8pH0SMUAyAM/ztLW1pWQyqWazqUwmo9XV1aGX4zjPWVJvWdJ+3JL23caUb/U/Ykz7H52kMe3LltKsPhR1Q4tnzEl/77Rtf8+88Uccx5j27K5vTPtrlu3+4DnzdvpPzUm/ljDnefffsOT5k+ak7b/2s8a0Hf0tY9rVv///MKb98ptfM6b9mOVovPKH329Mc/RvJSXu/PefS/pPWmn/5eer5u3elzGm+b/8tjHtL/7QfzSmLf7vf25Me/tHzhvTjn1z2+97T1m33actabZXYtqS9iVL2vda0t6wpD1qSdu3pC1Y0v7IkmbzRsTtPmdMif7ebDvWtuNn/sj2fcubniTHecGSaqtvG9t21yNt5ziXI8ZyGKk86T2WtGjnaPR9iOpHLWm21/W3WdL+iiVt0RqN/fx+x5ji+5vGNPtrzdaUtbwOLW+HjvO8Jc+fsaQ91PZ38Bp4z4nlwPyJq8/UC+eukIWGJueKH/5eX/n7z3Ytu/w/dS+TJP1OT2FJMr+77v+CIcG0PMTf8n+xa9l7nP8qdN1/+4vh/YiwftAn/M+GrvvHHwnvaz77a915OL9r6Lf8YPjngv+NkD7QA+FZXP5gSAyfDi/P/zvhfavfCFm8qz+W9P+RVNLx5/B/dpzHbngeYfv47A+Et/lqhg+of/+jf6lr2ebVQui64Wz9hxC33ghZaLpO8HLoUt+/1LXMcR425PErPQR1mu4D7jifN6z7hdClvh9W/2/2FUVYW9DUzjG1G8PW76eN2W971HGuhsTQffxsy4cRh609OApDKe93vtG97BfDPmwk/W+GPB6x9dNPF3b8bMJfm6ZjZWjH/uL7ei/w+wzLg+7IDUmvyHaZEhg5BkgiajQaSqVSqtfrcl1XkrS0tKT9/X1ls9kxRwcAAAAA40WfCQAAYPyOdFZHMQ8DxP3Mk0FMz1yXCZPL5ZROp1sNfUnK5/PK5XJjjAoAAAAAJgN9JgAAAEw6BkgiaDabqtVqymQ6b9ezvLwsSSqVSuMICwAAAAAmAn0mAAAATAMGSCK4du2aJCmZ7HweR/DNqGrV/AwEAAAAAJh19JkAAAAmw22dvXObrfh+bk/RLbZ4BkkEjUZDkpRIJKzpYW7cuKHr120Prw3T/pDrc+KwAQAAYNRu3rypmzdvRt7+xo0bQ4wG0yb+PtO7zp8/r/Pnz0feHgAAzC/awPOHK+0R7O3tSZIWFxdD05vNpnHbxx9/fKCyNzc39eyzz/S0ruPsmxP/drTyP3rVnHb5UrQ8J83P/OWPR9ruWz/8erQCDyxpFXPSO39m2e4hS9p/MCd9bPOXjGkb/83/Yt7wa+Yk/z9+kzHNqfjGtPf+7JfMmf43n5P0hTv/vC7pdivp3zZ+2rzdw+YkWerzU0ob037mr1nOlyNLeZKk97T9/rYTaZ5lu7ssabaDb6lTa5qNLRbbhY37jCm+/2FjmuPYYjm0pL1hSVuImGZ5j7UehzctaTbmWBzn+cjb2tjztdX3O5Y0W9PjXntAkcqLmvYeS9qX7eEY2fb9vZY022vJ9l7xn5qTHjYn+Z93jWnOD1uKk6R/batTM8e5bI7H37Rs94Jlu4+at8sYk6T3P2VO+9wnLRu2H8M/a/sdrU4mwdbWli5fNh8bwGb8faZnuxNu1boWPfvb3csk6dkf+vnwzH/pJ7sWLf5P4av+zLeHL7/8xe5ltlZFmM2Q5tJlw1vUX9K/71p2O2Q9SdLqrfDlf6d70XsM7cev/qqhrfNr3Yue/YGfC131E7/9kdDlvxHSFtz+d/8qdN2N//d/1bXM/1x4Y9J5JLxfsv/v/kL3wuT7pJvvSG9JevDbpfPvkyQd/F8M7a3Pdy/6WYX3rZ7UldDl7w2p69/e/d7QdT0vJ6VK8uo56c6MLccJP8/1iKGf8/o3Qhb+Svi6BuFlfrqvPMK9YVj+cMiyTxjW/WDoUlt7pFv4ORpWpqn+bW2cQdY17Ycpj372u5+8+4l5GPotL+y4+L657x/qXEh/+Jph3d8Je11Joef0D74vfNXXwz4fTa+r8D5p+DE09V8N7+d/p3tfnL/zcvi6xveZ4M3xzofiK1+UZO6HxGkW28C3dSb2h6bfnqIbVzFAEsHS0pIkaX8/vBl7chp5u5dfflkf+MAHupbff/+WcZu333669TffhAIAAEAcnn76aT31lGXA6BSvvvrqwBe6Mb1G0WfqFX0mAAAQFW3g+cMASQRBY970rSdbY/+ee+7RffeFfXPa/C378PUBAACA0Rn0NkX33HPPEKPBtBlNnwkAAGC0aAP37trOZ1TfCZ82devQMCt1AjFAEsHy8rKk7vvmBv+nUqnYYwIAAACASUGfCQAAYDIcjegWW4+tf58eW/++0LT/r/eWfiVVGnqZozA9NwObIIlEQq7rqlqtdiyv1Y7vX3jx4sVxhAUAAAAAE4E+EwAAAKYBM0giunLlilKplBqNRmt6eKFQUKFQUCKRGG9wAAAAADBm9JkAAADG70hndSvmh7TH/VD4QTBAEpHruqrX68rn80omk2o0Gsrn88pms5Hy8/3NIUco+f6iMc1xLhvT/vR/vte8neqWEr9kTnr0R81p32PJ8iFz0ssf/8vGtGf0D4xpf/T177IUKL3t7BnTfsx/yZj2p86vm8v0f9VcoPOCJZpDY8ov+v+jJc9PWvJcMKYkbv6pebPzf2gu7s2vGdNWHqyY8/y+f2ZM+thPfdyY5vsXJM+TUv9AXv3HJdd9N5a/ZC7O//fmNFl2PaXw+ylK0qp2jWm/fvb/bilQkj7d9vutE2nm4yQ9bEmzvA6tzOea9N0jKO+6McWJeP5Kf2RJM7+v2evzc5a091rSzPsnvceS9mVLmu1e7LbyJCn8AbnHbHX6jiXNVqe2PG37aCvP1mSxpUXdP1ud2fbdxvY6sx1D27lmOZ+cbzOnfdWymfOcpbwNS5qdra1jK9PWZonclH3DkvaabUPbe8KjbX9/c9vvqOcLMP2G3WcalO+nu5Y5zqdD1pSk8Pce5wNXQpb+zdB1f/bsXeFZ/6ChyDA/H7742bCux/9qyMO52r3sXMgySf63G7L4X/3e8pUk/W7o0mc/3Z1HSK7H6xry/hf+L3Yt+x1lQtcNjfkvhpfn/3T4cudjf969bkOSJykleb8h6U5XxHE+G553SBhldZ+LNju//He6lv3SpfB1//sHj8Nzf0x6pXUL/TfCV37984YSv9BHdIYHET/yvpDyvsOQxycMyz/YRxym13IY08OT3whZ9qZh3fA66ufajmM4z32/++Da20PRY+h3fdO6YfsSth+j1E99Hus+ZxznDcO6HwlffCvkNVQOOfcl6X8wfCb8wstdi77zt8P7DX9sue7UzXTu9rOu4aLcD4bsy+8YXt+vm85dQ50CY8AAyQBc11W5XB53GAAAAAAwkegzAQAAYJIxQAIAAAAAAAAAwAy6rbM6inkY4PYU3WKLh7QDAAAAAAAAAIC5wwwSAAAAAAAAAABm0JHOxP7Q9KMpmpcxPZECAAAAAAAAAAAMCTNIAAAAAAAAAACYQcfPIIl3Bsk0PYOEAZI55fubQ8/TcS6bE1/7nCXt/ZZc7zKmPP4Lv2nZbtGc5Fg2kyT9H8aU3zizZkzzfUuR1rlalnqz+Id/6e9FisXG+YgttWhO+s/N59Puf/0TxjRrnf2AJZTftaRZTjWrL5qTfvHBR8xp+mVLpr9vLfIxvXXnr5uSDk+kXrdsadvJW9Yyo/m8Je1k3O3esaTda0n7I0vaQ5Y020eaLU5bebY4v2RJW7CkfdmSZtu/b0QsT7IfC9u2tu1saffZwzF6jyXNVm825mNv+yx0nJolz09b0mznjK2u32tJs52/Fr5nTvuKa97Mf8aY5lg+XiXJ34/avjC/d42izaLXbIn7lrSHLWm3Qv6+pdG8LwMYlmG8xxj7Qa9/0LA87HPE0BA3ZBHuE4blIe2LW6bPuXT44p/sXuT7l3oJqsUJ69oZmjemvB2nu126Y+pT/Nch+3jOsH+mZtZuyLKPG9Y11n/3OfZv9FfCi3PCP6AcXelaZqqjn/E8KSV5vyHpzse9Y+gD+/77wstzuvel39dK2OvClIc5PsPxCtXPuuEc582QGEwxXx24PKm7vOO8e79G0M9xMcfc+36bdefRz36YmfpHw4g5LO/wYyJ9wbD8je5F3x/+ujJlHfZaDn2/lOT7322II15h78V6xLDfr5uO4cN3fh/c+f3gYEEBA+AWWwAAAAAAAAAAYO4wgwQAAAAAAAAAgBl0pDO6xUPajRggidnKyooWFsJvsbG+vq719fWYIwIAAACi2dnZ0c7OTmja4WHE28Nh7tFnAgAAk4w28GxhgCRmu7u7cl3zfb8BAACAaWG7WO15nlKpVMwRYRbQZwIAAJNs2trARzqno5iHAeIubxDTM9cFAAAAAAAAAABgSKZnKAcTz/c3I23nOJcj5ek4L0QqT/5pU93esWz7+5btnrFs95vmpMj1VrOkfTpaeb9mztPq4JPmtBceNiY5L5jrRdqwpN1lSfMsaeZvIjov+sY035xkPX9Pf4u91fb7GyfS9nvYrt8yFy1pXzam+P5HjWmO85wlz4csadctae+xpH3JkhZ+K45jtte9rTwby3uFNc12jGz1YsvzXkvaaWXajr3tPdh27E+ez+1ssZpjGUWTxf45YovFvA++/5SlvOcteb5hydP8+eI4lvdf23l/I+I3swe4be1g75fD9nlL2nstaW9Y0h5v+zt4r1pU9PcYANPC9Hlpet+L2v4/Le9h5Gvi2z7aTzC/34e1DS/1GckXQpa9z7DuG92Lbpl2xNC/eD1sX8LruZ/6/0fOzxjysPVzovP9fut5NvT7GuznGA6jTkf5mg335sjiGNX7minmsPcTx7kauqb5WHXn3e9+OB8JWfh7hpV/x3C95RPp7mW3TO+jcZ8zJg93L3q9jw8KSe++R7914jcQPwZIAAAAAAAAAACYQbd1RkcxP6T99hTduGp6IgUAAAAAAAAAABgSZpAAAAAAAAAAADCDjsYwg+RoiuZlMEACAAAAAAAAAAB69n/u/Gv9nzv/JjTt6LDf59KMDwMkAAAAAAAAAADMoNs6O5IZJI+up/Xoejo0bd/7gv5F6u8NvcxRYIAEY+f7mxG3/HLE7b7rlPQ3jCm+/1TEMkch/A1IknzfnGa3GHG7D1vSPm9M8f1njGmO8yeWtF/WY3pLniQ3VdQrerAt1fa25pqTfs+c5DiXLXnea0k7tKRJ0vW23/sn0m4Zt4r+mjGz7aN9/818/5IlzxcsW56si3bmepHesaTZzgtbeTa2Y79gSbO9d9n24SFL2nVLmmSvN3PdOM5zEfO07aO5PNu5HfU8tPH9j0Ysz/zajl5nZvZYfjxSnjqwnfeWz4KvRCtOiv+9y17eaxHT3mtJ+0Lb33/a9vs+Sd9m2Q7ArDK9D4W9d5nXrfWVd3geV0O2N7fTwvPoPWbzvnTH0b83+lj38ZBl/9Cwrqk+P9JHeX34H+7qa/V+6n9ShMVn+tzu73zuPY9+62gYr5X+yhu8PsLzNb3WbP2J8Rv0POi33obxGvI/0fu6jhP2nmTywb5j6S5vNOeXJOlcyHvYrfDPK7Og7fynJ34D8Zuem4EBAAAAAAAAAAAMCTNIAAAAAAAAAACYQUc6o1s8pN1oeiIFAAAAAAAAAAAYEmaQAAAAAAAAAAAwg450VkcxDwOM4qHwo8IMEgAAAAAAAAAAMHeYQRKzlZUVLSwshKatr69rfX095oiml+9vjjuEnvn+j44g18uWtGh14/uuJdWc5jjPWba7ZUmzxfkrlrRzevftq/3vAXzNnGQ71xzHdhxOc6vt98l6utdSprm+ff+ZSNvZ63DRkrYfsTzbeWHedyn8/fO0WOz78GVLms07EbeLtn++fyliedGN5pyxlRf19WSOxf6asJX3kCXtS5Y027kdLU4bx/lnltRDS9ofWPK8btnup06JKNqxjyp6WyBtyfMuY5rj2PL8w7a/v7ntt+01P/12dna0s7MTmnZ4aDsHAbNZ7zP1897l++b3q97zGLwNMZy+15tDiKP3ffH994Us7W8/wvMI5zhXDXmExPwL3wjP5OPhn0Fx931HVd4w8jXlEdau67e8UbW3TW3O0dVz/P2GYejnGIYt77cv0U8e5vMu7HX/sCGP8Pfz8DxM75e9fyaM8rWiW58PycO0f6bj8nB/ZU4Y2sCzhQGSmO3u7sp1bRehAQAAgOlgu1jteZ5SqVTMEWEW0GcCAACTbNrawLd1NvZbXt3mFlsAAAAAAAAAAACTixkkAAAAAAAAAADMoCOdiX0GydEUzcuYnkgBAAAAAAAAAACGhBkkAAAAAAAAAADMoCOd1a3YZ5BMzzNIGCABMAS3LGlR32bMefr+puR5Uuofyav/tNT2EE/HuRytuFf+0JjkOL8eKUvf37Smu85Td/76Zkn3ntj2qa71343HvI+2NFs89nrbt+T5zAhied6y3UcjlWfbh1Gco9KhJe29lrQ3jSlR63OwbRcsabZ9tNW3rd7MTtvHYefpOFctW0bbB1t9Rj9Gi5Y023GwMZ+H0udO2faDEcucHPb3kh+zpLW/Jv6s7fc7A8cEALNgFJ/lk8X2+XnSrxiWXxpGIAML+ywcx/EbNA7TZ3rc+xJ3ecPY71HWXeQ++6keCl3q+6N7XYXlbepHOM7ne8/jrsHishnO+fhwH+uGHxfp03d+v3Xn96tRgwEGxi22AAAAAAAAAADA3GEGCQAAAAAAAAAAM+i2zuoo5mGA21N0iy1mkAAAAAAAAAAAgLnDDBIAAAAAAAAAAGbQkc7E/tD0oymalzE9kQIAAAAAAAAAAAwJM0gADMz3N0eQa9xvT69Z0t5jSfvyAGX+WdvvdwbI512jORa3Im5nPoaOc9mYFnUfRrPvZvZ9eGboeQ72moi2re8/ZUyLegxHcext7HVqY3vdx8txnrOkupa091rSrkeMJup2k+Y3jCn28/dPeszzi3d+f17STUkf7CM2AIBJ2Od63G3A4Xhz3AFIMreTJqVO+4kjbN3o7cDh6jeOQeu/3+3jrqd+4nOcq4aU7tfQMM7b4Zz7DxuWfyF0qeO83Ece6f7DGYl/GLLMVHfh73etuvY8KVWSV88NJTIgCgZIAAAAAAAAAACYQccPaR/+Lbbe3PkNvbkT/uWz24dfH3p5o8IACQAAAAAAAAAA6NlD6z+mh9Z/LDTtHe811VM/E3NE0TBAAgAAAAAAAADADDrSGd3iIe1GDJDEbGVlRQsLC6Fp6+vrWl9fjzkiAAAAIJqdnR3t7OyEph0eHsYcDWYFfSYAADDJaAPPFgZIYra7uyvXtT1QFQAAAJgOtovVnucplUrFHBFmAX0mAAAwyaatDXykszqKeRhgFM88GZXpmesCAAAAAAAAAAAwJMwgAaaU72+OO4QRuxVxu6hva+G3cTi2HzFPO6+ek1Kl4999fEsy6rF3nMuRtrOVZ8sz7nN0FPsXlT0W8zk6qjrz/WdGkKftvHg+Up5Rj+FomjPm1/0oXoPR87xqSbW9r73fkvZHlrQPnhLP5Lwn2D0acTtb3dzX9vc3t/2+L2RdAIBk/twwfWZM1mdJp35iM63bb30Mahj5xh1zP+VNyvnS7/GOW1h8/cYWtn6/9T+MPOJmb4v3xvcvheRrqv/0wOUNh71P0OER0/l/XHeP6QvyJLmpX5fnM3sU48EACQAAAAAAAAAAM+i2zsZ+y6vb3GILAAAAAAAAAABgcjGDBAAAAAAAAACAGXRbZ8Ywg2R65mVMT6QAAAAAAAAAAABDwgAJAAAAAAAAAACYO9xiC0CL4zxnTPP9ZyLmedmS52akNLtbEbd7M+J20bmporw7v1/Rgz1vF7VuotdpvHna2M4nm6hxjqI82+vMHkv012fU12HceUZlP073WtLeMaaM4j3PFkvUc20U7OdvLfK2k+XbjCmOc9Wy3YIl7f0hyx4xLAcASP1/boR9Xk7PZ8+7HOfz4w5haOKuf1N5/bSlJuWcGVUcprrop7x+YwtbfxhxTDrfv9S1zNSWDFvXnO/01VG/++04o4wGJx2N4SHtcZc3CGaQAAAAAAAAAACAucMMEgAAAAAAAAAAZtCRzuhW7DNIpmdeBgMkAAAAAAAAAAAgdo1GQ5VKRZKUzWaVSCQkSZ7naWtrS8lkUs1mU5lMRqurq0MvnwESAAAAAAAAAABm0PEzSOIdBujlGSSNRkP5fF7NZlPFYlHJZLIjLZVKqV6vy3VdSdLS0pL29/eVzWaHGuv0zHUBAAAAAAAAAABTzfM8pVIpLS4uqlqtdgyOSFIul1M6nW4NjkhSPp9XLpcbeizMIInZysqKFhYWQtPW19e1vr4ec0TAu3z/mRHkuTn0PEfjS8aUUdSLJHn1nJQqHf9ue8M/jeNcNqaNor6npTzbdlHZy3suYq63IuU5yHkYvd7MzYRJem3Peiz2cy28TXHsvZa06xGjmRW/aUl7vyXt31jSDtv+/sKd3//hzvLe3+Onzc7OjnZ2dkLTDg8PQ5cDp6HPBJNJ+swfzCdCl87O/oXrt73eT33Met31w1QXpvrvp+6GkYfJMOLoJ9+wPPrdj37ycJyroct9/1JP+dryjt93hCz7dJ95PHzn9zfu/H4wcjTjQBt4MM1mUx/60IeUTCZVLBZD02u1mgqFQsfy5eVlSVKpVBrqLBIGSGK2u7vbMfIFAAAATCvbxergW2FAv+gzAQCASTZtbeDbOtvTLa86trn5dfk3vx65zFs3bhrTgttqnRwACVy7dk2SumaVBO3DarXKAAkAAAAAAAAAABi+/a1f1v7lfzySvEulkqTjgY58Pq9Go6Hl5eXWc0gajYYktR7WflKQPiwMkAAAAAAAAAAAMINu60zfM0gST2d1/1M/FbnMm6/+B731ePf2nudJOp4NksvlVCgU1Gg0lMlktLS0pIODA+3t7UmSFhcXQ/NuNpuR4wrDAAkAAAAAAAAAAJAkOefvlnP+7sjbn7nnL4QuD2Z/5HK51i20gmeRZDIZbW1taWlpSZK0v78fmsfJW28N6sxQcwMAAAAAAAAAADjBdNusdDot6XgAJRgAMc0UGfYACTNIAEwkx7lsTPP9zUhpNr7/jCWW5y3bPRWpPElyU0V5d36/ogdP5Dv8fYzbKI5h1DyjspVn+wiNGqe9vNGIu96iluc4z1lSb0XKMyr7MRx+nPbyXrBseWhJe2+kWKTPn5KejpRr3K9t6bol7feNKb1/VvxZ229bWQCASRb2+TSMzyVTHqbPw2lp/59mVvZjWo3y3B1VeaPMe1R5mNu1Hxy4vMnxiSHk8ek7v9+68/vVIeQJk1s6o7N93mJrGGWGWV5elqTWbbROWlxcbK1z8lkjwf+pVGpYYUpiBgkAAAAAAAAAABixRCKhdDqtWq3WsTyYLZJKpZRIJOS6rqrVasc6wTYXL14cakwMkPTg5GgVAAAAAKAT/SYAAIDJc1vndBTzz23LXTcKhYI8z+sYJCmVSnJdV9lsVpJ05coV1Wq1jvZloVBQoVAw3qYrqrkaIKlUKkqlUnIcR6lUqmukKuA4TsfP2tpaR7rneVpbW1M+n1cul1OlUokjfAAAAAAYOfpNAAAAGBXXdVWv11UoFJTL5ZTP57W3t6d6vd61Tj6fVz6fb7UpNzY2hh7P3DyDZHt7W9VqVblcTnt7e9re3lYmk1G1Wm09BEY6Hq3KZrNaWlpqLWtPbzQaSqVSqtfrcl1XkrS0tKT9/f3WCBcAAAAATCP6TQAAALPlts7oKOZnkNw+ZV5G2C20wtYpl8vDDCvU3AyQfOYzn+mo9CeeeEKpVEqFQqGjIV8ul60HJ5fLKZ1Otxr5klrfiKKhDwAAAGCa0W8CAADAPJmLAZJaraZCodCxzHVdua7bcR+zSqWia9euaW1tTZlMpqvh3mw2Q/NaXl6W9O63qAAMzvc3I23nOM9Z8nwmajgj4dVzUqp0/Lvt4sEgHOdypO1s9R31WETdLu48R1Ge7Ty0HaNR7d84yjSxn6PmZskoXr+jqBdbnFFfn3Z3RdzucxG3ezjidnZxn4fSey1pCxHzvK/t729u+31fyLrAZKLfBHSK//Opd6Z2hV//sZgjAdDO9L7hOFcHzmOS9Rtza33Pe/e6CDAmc/EMknQ6rWQyGZrWvrxararZbKpSqSiXy+nChQsd99u9du1a1zaSWt+KOm1aEAAAAABMKvpNAAAAs+fozi224v2ZnmGHuZhBYtJoNJTLvTtCWSwWVSwW5XmeisWiSqWSMpmM9vb2lEwmW9+aSiQSxvxOc+PGDV2/fj1yzOfPn9f58+cjbw8AAAD04ubNm7p582bk7W/cuDHEaDBOcfeb6DMBAIBxoQ08f+Z2gKRSqSiZTIZO7XZdV8ViUZlMRmtra8rn8yqXy9rb25MkLS4uhubZbDZPLffxxx8fKO7NzU09++yzA+UBAAAAnGZra0uXL4/i1nCYJuPoN9FnAgAA4zKLbeDbt8/q6HbMD2mPubxBzO0AydbWlsrlsnWd1dVVra6uyvM8SdLS0pIkaX9/P3R903T0di+//LI+8IEP9BdsG74JBQAAgDg8/fTTeuqppyJv/+qrrw58oRvjN45+E30mAAAwLrSB589UDZB4nqd8Pt/TuslkUsViMTQtn8/rypUrPQ1oZDKZ1v10g/VN33jqJb977rlH993HwzoBAAAw2Qa9TdE999wzxGjQj2nvN9FnAgAA40IbeP5M1QCJ67oDP9AvuD9u8IDAXiwvL3f8PnnP3OD/VCo1UGwAJpPvR//mQFSOY57O6fubkdLs5T1nyfOZiHlG24dZYKszW72Mqs5s28Z9nEZxjkq3RlBevFOqo9f1m5Y0WzOv93ZQJ++U9B+NmG/c3mtJ+1zEPNufl/Bnbb+jP0cBiIp+ExD+WT6Mto3jXNVj+oI8SW7q1/XKqZ+ND4fEkQ5ds5/4jOt6p8VzulHVHTBr+uszPDRwvpP8OnScq6HLff9SzJEgzNHRGelWvLe8Ojqanoe0T0+kQ1CpVCRJ6XRnY8SzNCCq1WrrgYSJRCK0sxF8U+rixYvDDBcAAAAAYke/CQAAAPNiqmaQDKJWq2lra0u5XE6lUqm1vF6vt77B9OSTT+qJJ57QxsaGpOOOweLiolZXV1vrX7lyRalUSo1GozU1vFAoqFAoKJFIxLdDAAAAADBk9JsAAABmy9Gts9KteIcBjmKesTKIuRgg8TxPmUxGklrfamp3cHAgSVpcXNTW1paq1apc11Umk+m6H6/ruqrX68rn80omk2o0Gsrn88pms6PfEQAAAAAYEfpNAAAAmDdzMUDiuq583z91vV7v0+u6rsrl8qBhAQAAAMDEoN8EAACAeTMXAyQAAAAAAAAAAMyb20dnR/KQ9ltXrurWlauhaf7Xvjb08kaFARIAAAAAAAAAANCzc09e0rknL4Wm3X71s7r5+F+NOaJoGCABMGMWjSmO84Ixzfc/OopgIvP9zZjLeybSdo5z2ZJnvPtgiyUq2z44znOW7aLV5zhEPU5R6zvqdqM4n0aRZ/yviahNuTcibrcQcbtJ8/uWtHeMKbbXvXSr7e8/a/ttzg8AMDqjaov6/iXJ86TUP5BX/3HJdSXZ2gBvhixLh65pyiP+vsHg5fXT5ot7/0bJcbq/Se374RcPMf1m6dwdlOk8D3tN2NbHaBwdnZEf80PTbx+dibW8QUxPpAAAAAAAAAAAAEPCDBIAAAAAAAAAAGbQ0a2zuv2NeGeQxD1jZRDMIAEAAAAAAAAAAHOHARIAAAAAAAAAADB3uMUWAAAAAAAAAAAzyL99Vv5RzMMAt6fnFlsMkMRsZWVFCwsLoWnr6+taX1+POSJgtvj+R4eep+NctpS3GWk7SfLrPxY5pjhF3f+4xR/LrUhbRY3ztPNpFGVGzTP6a+a5gWLql608338mUp6jOL72PKOdh9KXLbHEexzG4z5jiu8/ZUxznOcteR62/X2u7fdsN7d3dna0s7MTmnZ4eBi6HDgNfSZMI9PndT9tuH7ymKR2eJhJjy/MMOrZ9y8NK5zYTOP5NSlGVXezVP/T+JroBW3g2TLbPbYJtLu7K9d1xx0GAAAAMDDbxWrP85RKpWKOCLOAPhMAAJhkU9cGvnVGivuh6bem58ke0xMpAAAAAAAAAADAkDBAAgAAAAAAAAAA5g632AIAAAAAAAAAYBYdnY3/FltH0/OQdmaQAAAAAAAAAACAucMMEgA4he9vjmY7z4uUb9yi7v8scJzLxrR5rpfTRH/NPGNMsx2L6LHcilSeLc+o243ifLLH+ZxlO9txeGGgmCbH9Yjbfbcl7fcj5gkAmGXD+Iyn3RmPaaznsLZnv/sxjfsdxtQOj3v/JiWOUZqlfZkbR450y4m/zCnBDBIAAAAAAAAAADB3mEECAAAAAAAAAMAsOpLtBgqjK3NKMIMEAAAAAAAAAADMHQZIAAAAAAAAAADA3OEWWwAAAAAAAAAAzCJusWXFAAkAYGo4zmVjmu9vDr28UeQZ1STFIsV/LGxs5U3SOTOKWOzlvWDZ8uFI5Un7EbebNIcRt/v9oUYBAJh9YZ//k9auw/Tq51wytUVn5Xwcz358MCSOdOias1T/vK9h1jBAAgAAAAAAAADALLql0cwgeWnn+CfMzahfSosfAyQAAAAAAAAAAKB3F9ePf8J8zpN+MhVvPBExQBKzlZUVLSwshKatr69rfd1wUgEAAAATZmdnRzs74d8aOzycnm+NYbLQZwIAAJOMNvBsYYAkZru7u3Jdd9xhAAAAAAOzXaz2PE+p1HR8awyThT4TAACYZFPXBr4l6RtjKHNKnBl3AAAAAAAAAAAAAHFjBgkAYGr4/ua4Q8AdcR+LqOVF3c5xLg+9vEmKxXGei5Tn7Ai/dc/pFi1pX277+1bb7yn66hQAYOhov57O1NYZVd3FXV7cJn3/+mnbTkrMJr6fHkm+k34MhyHYx8f0ljxJbqoozy+ON6hZdlvS0RjKnBLMIAEAAAAAAAAAAHOHGSQAAAAAAAAAAMyiI8U/sT3uGSsDYAYJAAAAAAAAAACYOwyQAAAAAAAAAACAucMttgAAAAAAAAAAmEW3FP8ttuIubwAMkAAA5DiXjWm+vxljJIjCdvxOw/ENF7VeHOc5S57PWLaL9hq0bWc/L+61pM2DQ2OK41y1bPfl4YcCAMCci7s9Oo3tX1O7LmxfJn3/Jj2+Uelnvye/jj44cA6tffQ8KVWSV88NnCcQFQMkAAAAAAAAAADMIh7SbsUzSAAAAAAAAAAAwNxhgAQAAAAAAAAAAMwdbrEFAAAAAAAAAMAs4hZbVswgAQAAAAAAAAAAc4cZJAAAAAAAAAAAzCJmkFgxQBKzlZUVLSwshKatr69rfX095ogAQPL9zXGHMDcc57IxzXYcom532rYYLt9/xpg2yDGMFssoXtdxt6pHw36cnrNsZ3uNvtD239fu/F6U9J7+gpsyOzs72tnZCU07PDyMORrMCvpMANCJ/tp8MfUbJuc8eKPnNR3nauhy3780pFjGgzbwbGGAJGa7u7tyXXfcYQAAAAADs12s9jxPqVQq5ogwC+gzAQCASTZ1bWBmkFgxQAIAAAAAAAAAAHr3mzvSvwifSaOvT89MGgZIAAAAAAAAAABA7350/fgnTMOTPjZhM2kMGCABAAAAAAAAAGAW3ZL0jTGUOSXOjDsAAAAAAAAAAACAuDGDBP//9u4nto38ThT8l0E2PQ56A9mdyzxg+0Ad9poUPceHxgDizmGAvVhyH+cwCXnQLQcTRgPPbWADQTrsTYOlnAFymEtHNHZvcyAHi8xpsGNWehYLBBhABIL3Xg/wMCNzg8Y47tipd3CLbVkkLUtVxT/1+QAFi1XFqq/qV0V/f/rx9/sBUKqr/debZQ+ufMbrvJf8zCuHWu3hld53VbXaT+ec75Pcz7dsrvr7z3tfxK1rRAQA8O6m5ZBy//Nm5dmu09Vl2Y/eYe//WlgcvIOXUf6k6Ss0SbseJAAAAAAAQOVoIAEAAAAAACrHEFsAAAAAALCOXkb5k6YbYgsAAAAAAGB56UECAAAAAADrSA+SuTSQAECJsuyTRYfAEsqyB6W+76rKPl9xiqgd/LfXfj597d8/KuBcAACrmZvVag+nri/qd1nFa7SKMc+yTr8L60sDCQAAAAAArCM9SOYyBwkAAAAAAFA5epCU7M6dO3Hjxo2p23Z3d2N3d7fkiAAA4GoODw/j8PBw6rZnz56VHA3rQp0JAFhmcuD1ooGkZI8fP44kSRYdBgAAXNu8P1anaRqNRqPkiFgH6kwAwDJbuRz4RZQ/xFbZ57sGQ2wBAAAAAAClGwwGcfPmzQvr0zSNnZ2d6HQ60W63o9frFXJ+PUgAgKlqtYczt2XZgxIj4SrmlV9Rx1yd++KqKfDsr0Gd+93TNKJxFOmwHeFb8AAAE6uTL15Nrfazqeuz7EclR1Kuq9Y9fhhfRBoRSaMbadbNNyi+seSTtLfb7QvrRqNRNBqNGA6Hk57Fm5ubcXp6Gq1WK68oI0IPEgAAAAAAoGSdTifq9fqF9e12O7a2ts4Nu3rWkyRvGkgAAAAAAIDSDAaD+OCDDy7MPTcej2MwGESz2Ty3/vbt2xERcXR0lGscGkgAAAAAAGAdnQ2xVeZyiSG2ut1u3Lt378L6J0+eRERc6Fly1pDS7/cv9WtfljlIAAAAAACAV148f7Vc1fMv527udDqxv78/ddtoNIqIiI2Njbnb81L5BpLRaDR1nDMAAABeUW8CAFhRLyLi9+/4nv5exN89LCKaSNM0Pvjgg5m55cnJSURE3Lp1a+r28XicazyVayCp1WrnXidJEsPhcPI6TdPY29uLer0e4/E4ms1mbG9vn3vPZfYBYL3VarMThSx7UGIkb3fVWJft9+Ciq5ZtrfbTK51vfe6JF7kf8fVr+sP4ItKISBp/Hb+Kv40s+yT380HR1JsAWCWz8uKy89cs+9G1j1Gr/aywY+dh2rWedZ3fWi5pGtE4inSY/8TbXNOf3o/4jz+5+vu/+Dzi6KOpm/b29uL4+HjmWzc3NyMi4vT0dOr2vL+0U6kGkqOjo2i1WpOLHBGxtbU1+Xk0GkWj0YjhcDgZ02xzczNOT0+j1Wpdeh8AAIBVpd4EALBGXsal5gQ5p/ZexP/w3tXP+e33p67udDrRbDbPDZN19vPZv2cNILN6imgguYbj4+O5k7i02+3Y2tqaJPARrwqt3W5PkvjL7AMAALCq1JsAACjCYDCIg4ODqds2NzcjSZL4u7/7u4i4ONfI2etGo5FrTN/K9WhLrNfrxZMnT2JnZyeOjo4ubB+PxzEYDKLZbJ5bf/v27Yh49S2qy+wDAACwqtSbAAAoynA4jCzLzi337t2LjY2NyLIshsNhbGxsRJIkF76wMxgMIiLi7t27ucZUmQaSfr8f4/E4er1etNvtuHnz5uSiRkQ8efIkIi520Tn7xlO/37/UPgAAAKtKvQkAYM28jFfTMJa5vOuQXm949OhRDAaDc71I9vf3Y39/PzY2Nq538DdUZoitbrcb3W430jSNbrcbR0dH0Ww24+TkJOr1+uRiz7rAo9HoUvu8zZdffhm//e1vr/Q7RES899578d571xj/DQAALuH58+fx/PnzK7//yy+/zDEayrIM9SZ1JgBgUeTAyyFJkhgOh9HpdCY5aKfTKWSo1so0kJxJkiS63W40m83Y2dmJTqcTx8fHcXJyEhERt27dmvq+8Xh8qX3e5qOPPrpa4F978OBBfPrpp9c6BgDXl2UPFh3Cpa1SrLybeWVbqz280vuY7dLXLU0jGn8V6fAvI16bf2HV7O3txcOHs+8j1tsi603qTMCym5VnybHKMe36L8u1z+PeyLIf5RVOId7td1mOcnkXa5kDn/UgKfucl3TWM+RNSZLE8fFxjkFNV7kGkjPb29uxvb0daZpGxKtJYCIiTk9Pp+5fr9cvtc/b/PKXv4wf/OAHV4j4Fd+EAgCgDPfv34+f/OQnV37/559/fu0/dLN4i6g3qTMBAIsiB66elWogSdM0Op3Opfat1+vR7Xbn7tNsNifj6Z4l6bO+zVSv1y+1z9u8//778b3vfe+t+wEAwCJdd5ii999/P8doeBerXm9SZwIAFkUOXD0r1UAybfb667p9+/a5f98cD/fsdaPRuNQ+AAAAi6TeBADAxJIPsbVo31p0AIvU7/ej3W5HxKsJBKdVJM6+KXX37t1L7QMAALBO1JsAAFhXlWggSdM0Go1GHBwcTNb1er24detWbG9vT9Y9evQoBoPBuW86nU0Ss7Gxcel9AAAAVo16EwDAGnoREb8veSm7x8o1rNQQW1dVr9fj1q1bsbe3F/1+P5IkiWazeWGs3SRJYjgcRqfTiXq9HqPRKDqdTrRarXfaBwCWSa32cOa2LHtQYiSUK/80r1b76dztWfZJ7udcJvOepdf9ML6INCKSRjd+Ff/Bc8bKUG8CuBz/ty/WMl//WbHNyiOn7f8u+y5CrfazC+uy7Ecz9l3u3wUiKtJAsrGxcekxeJMkiePj42vvAwAAsErUmwAAqJpKNJAAAAAAAEDlvIzyJ003STsAAAAAAMDy0oMEAAAAAADW0csof9J0PUgAAAAAAACWlx4kAAAAAACwjvQgmUsDCQCsuSx7kPsxa7WHpZ6Pd5dln8zcVqv973Pe95M5Ry07qy7GVe/Ree+b90wAAFBt75J/Ln996r8uOgDIlQYSAAAAAADg8v6/w1fLNC+elRvLNWggAQAAAACAdfQiIn5fwHH/591XyzT/mkb8X40CTpo/DSQlu3PnTty4cWPqtt3d3djdnXFTAQDAkjk8PIzDw+nfGnv2bHW+NcZyUWcCAJaZHHi9aCAp2ePHjyNJkkWHAQAA1zbvj9VpmkajsRrfGmO5qDMBAMts5XLgl1H+pOkrNEn7txYdAAAAAAAAQNn0IAEA3lmWPVh0CLxFrfbTRYewtOZfmxczt8y/77895edvh3QbAIB18i51QfVGVoEaGwAAAAAArKOXMe97YMWdc0UYYgsAAAAAAKgcPUgAAAAAAGAd6UEylx4kAAAAAABA5ehBAgAAAAAA6+hFRPx+AedcERpIAADW0ryMtNopYJZ9MnNbrfawxEgAAGC1TMuXs+zBAiKBfBhiCwAAAAAAqJxqf30QAAAAAADW1R+i/EnT/1Dy+a5BDxIAAAAAAKBy9CABAAAAAIB19CLKnzR9hSZp14MEAAAAAACoHD1ISnbnzp24cePG1G27u7uxu7tbckQAwDrKsgczt9VqD3M/5iqp1X46Z+vV0uMs++SbF2ka0firSId/GZEkVzreqjg8PIzDw8Op2549e1ZyNKwLdSYA1k2t9rOp67PsRyVHcn3T6gS12mDGvltFh7MQcuD1ooGkZI8fP45kzSvKAABUw7w/VqdpGo1Go+SIWAfqTADAMlu5HPhllD/kVdmTwl+DIbYAAAAAAIDK0YMEAAAAAADW0YuI+H0Bx/3PhxH/ZfpQY/FydYYa00ACAAAAAABc3v+0+2qZ5rdpxP+zZEONzaCBBAAAAAAA1tEfovw5Qf5Q8vmuQQMJAMCKqtUeztyWZQ9KjGS1ZNknuR+zVvvp5OcfxheRRkTS+Ov4VfxtIecDAGB1ZNmPFh1CbqbVQWbVPWbVV9RVWCYmaQcAAAAAACpHDxIAAAAAAFhHL+PVRO1ln3NF6EECAAAAAABUjh4kAAAAAACwjl5E+T1Iyj7fNehBAgAAAAAAVI4eJAAAOanVHs7clmUPcj/fvGOWHcsqKeLaZNkn37xI04jGX0U6/MuIJLnS8QAAYBm9S75c9XoHq0EDCQAAAAAArKMXEfH7BZxzRRhiCwAAAAAAqBw9SAAAAAAAYB39ISJeLuCcK0IDScnu3LkTN27cmLptd3c3dnd3S44IAACu5vDwMA4PD6due/bsWcnRsC7UmQCAZSYHXi8aSEr2+PHjSEzWCQDAGpj3x+o0TaPRaJQcEetAnQkAWGYrlwO/jPLnBCm7x8o1mIMEAAAAAACoHD1IAABWVK32cOa2LHtQYiSr5arXZt71ft0P44tIIyJpdONX8R+UBQAAlTQrf5Yfs0w0kAAAAAAAwDp6EeUPsVX2+a7BEFsAAAAAAEDl6EECAAAAAADr6EVE/H4B51wRepAAAAAAAACVowcJAAAAAABweePDiP//cPq27Fm5sVyDBhIAgJxk2YO1Pl+t9nDu9rLjuap5v8e83+HSv1+aRjSOIh22I5LkXcMDAIC1sCr1g7X3h4h4WcBx/8fdV8s0z9OILxoFnDR/htgCAAAAAAAqRw8SAAAAAABYRy+j/EnTi+ixUhA9SAAAAAAAgMrRgwQAAAAAANaRHiRz6UECAAAAAABUjh4kJbtz507cuHFj6rbd3d3Y3d0tOSIAoGpqtYczt2XZgyttWyVX/T3mXbfX0+ofxheRRkTS+Ov4VfxtZNknVzrfKjg8PIzDw8Op2549e1ZyNKwLdSYAYJnJgdeLBpKSPX78OJIkWXQYAABwbfP+WJ2maTQajZIjYh2oMwEAy2zlcuCyh9da1DmvyBBbAAAAAABA5ehBAgAAAAAA6+hlRNQWcM4VoQcJAAAAAABQORpIAAAAAACAyjHEFgAAlVKr/XTmtiz7ZM62B3OO+fC1Vy9e+3eFZicEAIAcnc+RvzEvr6YAixjuyhBbAAAAAAAAy0sDySWMRqNFhwAAALDU1JsAAJbQy/imc3tZy1t6kPR6vWg0GlGr1aLRaMRgMLiwT5qmsbOzE51OJ9rtdvR6vatfgzkqM8RWs9mceqEjIvr9fmxtbU1e12q1c9uTJInhcDh5naZp7O3tRb1ej/F4HM1mM7a3t4sJHAAAoCTqTQAAFOng4CD6/X602+04OTmJg4ODaDab53LN0WgUjUYjhsNhJEkSERGbm5txenoarVYr13gq0UAyGo1iNBrF/v5+bGxsTNafFcDrSf7R0VG0Wq3Y3NycrHt9e5mFAwAAUBb1JgCANfQiImpv3Stf2exN//iP/xj9fn/y+uOPP45GoxH7+/uTfLLdbsfW1tYkj4yISU8SDSRXMBgMYjgcnkvyI+JCkh8RcXx8fK6A3lRm4QAAAJRFvQkAgCINBoPY398/ty5JkkiSZDJc63g8nrrf7du3I+KbL+rkpRINJLMu2GeffRbtdnvyutfrxZMnT2JnZyeazeaF95VdOAAARciyB4sOYSXVag9nbjt3TdM0onEU6bAd8dofh2HZqTcBAHlS7+BNb37p5nX1ej0iIp48eXLu9ZmzL970+/1cc8nKTtI+Ho8jTdO4e/fuZF2/34/xeBy9Xi/a7XbcvHnz3Pi7lykcAACAdaHeBACw4l5eYXnxPOLFb6++vPzynUIcjUaxs7Mz+TkiLvRqfn3fPFWiB8k0v/jFLyJJknMXutvtRrfbjTRNo9vtxtHRUTSbzTg5OYl6vZ5L4Xz55Zfx29/+9spxv/fee/Hee+9d+f0AAHAZz58/j+fPn1/5/V9++W6VIpbTIupN6kwAwKLIgc/sRcTsHvR56vV6Ua/XJ71CTk5OIiLi1q1bU/cfj8e5nr+yDSTHx8fx8ccfT92WJEl0u91oNpuxs7MTnU4njo+Pcymcjz766MoxR0Q8ePAgPv3002sdAwAA3mZvby8ePiynUsTyWkS9SZ0JAFiUtc2B50yaPt39iPjJNU74eURcLqfb29uL4+PjyevNzc2IiDg9PZ26/5u9lK+rkg0kZ2Pidrvdufttb2/H9vZ2pGkaEfkUzi9/+cv4wQ9+8G4Bv8Y3oQAAKMP9+/fjJz+5eqXo888/v/YfulmsRdWb1JkAgEWRA5957+vlqt6/1F6dTicePXp0Lj88+3nWl2oq3UCSpml0Op1L7Vuv12cm8oPBIOr1+qUuZrPZnIynm0fhvP/++/G9733vrfsBAMAiXXeYovffv1yliPyter1JnQkAWBQ5cHnOhmk9m6fuzO3btyPi4rCsZ68bjUaucaxUA0mSJLlM6PfZZ5/F9vb2pfc/K5SyCwcAgPxl2SdXfN+DnCOBYqg3AQCwzHq9XkREbG1tnVufpmkkSTLJZ+/duzfZdvZlnLt37+Yay7dyPdqK6PV6M8fRfVO/3492ux0RryYZnFbZKKpwAAAAFkW9CQCAvA0Gg9jb24uIV71IzpZ2ux1PnjyJiIhHjx7FYDA494Wb/f392N/fj42NjVzjWakeJHno9XqThP11aZrGj3/84/j4448nLVO9Xi9u3bp17ltTjx49ikajEaPRaNI1vKjCAQAAWAT1JgAA8pamaTSbzYiIyZdrXvf06dOIeNUjejgcRqfTiXq9HqPRKDqdTrRardxjqlwDyWeffTb1G0v1ej1u3boVe3t70e/3I0mSaDabF8bjLbNwAAAAFkG9CQCAvCVJElmWXXrf4+PjgiOqYAPJrIu6sbFx6XF6yyocAACARVBvAgCgCio5BwkAAAAAAFBtGkgAAAAAAIDKqdwQWwAAAAAAvLta7eGl982yBwVGwuW9iIjfL+Ccq0EPEgAAAAAAoHL0IAEAAAAAgLX0Isrv0aEHCQAAAAAAwNLSQAIAAAAAAFSOIbYAAAAAAGAtmaR9Hg0kJbtz507cuHFj6rbd3d3Y3d0tOSIAgGqp1R7O3JZlD0qMZPUdHh7G4eHh1G3Pnj0rORrWhToTAKyWquXQcuD1ooGkZI8fP44kSRYdBgAAXNu8P1anaRqNRqPkiFgH6kwAwDJbvRz4ZZTfo+Nlyee7OnOQAAAAAAAAlaMHCQAAAAAA8A5+FhF/PWPb78oM5Fo0kAAAAAAAwFoqapL2v/h6meb/jYj/pYBz5s8QWwAAAAAAQOXoQQIAQKVk2YNFhwAAACtJLr2KiupB8rZzrgY9SAAAAAAAgMrRgwQAAAAAANbSyyi/R8fLks93dXqQAAAAAAAAlaOBBAAAAAAAqBxDbAEAAAAAwFoySfs8GkgAAOBrtdrDmduy7EGJkQAAwHo6y7l/GF9EGhFJoxtp1l1sUFSWBhIAAAAAAFhLJmmfxxwkAAAAAABA5ehBUrI7d+7EjRs3pm7b3d2N3d3dkiMCAICrOTw8jMPDw6nbnj17VnI0rAt1JgBgmcmB14sGkpI9fvw4kiRZdBgAAHBt8/5YnaZpNBqNkiNiHagzAQDLbPVyYJO0z2OILQAAAAAAoHL0IAEAgK9l2YNFhwAAACulVns4df2s3HqyPk0jGkeRDttFhUZEvOrNUXaPDj1IAAAAAAAAlpYeJAAAAAAAsJbMQTKPHiQAAAAAAEDlaCABAAAAAAAqxxBbAAAAAACwll5G+UNevSz5fFengQQAAAAAgCvJsgeLDoGFeBwR/+eMbc/LDORaNJAAAAAAAMBaKmqS9v/162Waf46IdgHnzJ85SAAAAAAAgMrRQAIAAAAAAFSOIbYAAAAAAGAtmaR9Hj1IAAAAAACAytGDBAAAAAAA1lJRk7S/7ZyrQQNJye7cuRM3btyYum13dzd2d3dLjggAAK7m8PAwDg8Pp2579uxZydGwLtSZAIBlJgdeLxpISvb48eNIkmTRYQAAwLXN+2N1mqbRaDRKjoh1oM4EACyz1cuBzUEyjzlIAAAAAACAytFAAgAAAAAAVI4htgAAAAAAYC2ZpH0ePUgAAAAAAIDK0YMEAAAAAADWkh4k8+hBAgAAAAAAVI4GEgAAAAAAoHIMsQUAAAAAAGvpRZQ/5JUhtgAAAAAAAJaWHiQAAAAAALCWTNI+jx4kAAAAAABA5WggYarnz5/Hp59+Gs+fP190KLwD5baavvrqK+W2gjxvq0m5rSbltpq++uqrc//CqvHZUyzXt1jqGMVy/xbL9S2W61us5cyBX8Y385CUtbws5TfLgwYSpnr+/Hk8fPjQh+WKUW6r6auvvlJuK8jztpqU22pSbqtpOSuHcHk+e4rl+hZLHaNY7t9iub7Fcn2LVa0c+P+OiP80Y/k/FhjXuzEHScnu3LkTN27cmLptd3c3dnd3S44IAACu5vDwMA4PD6du+/d///eSo2FdqDMBAMtMDnzmT79epvlNRPxvJcZydRpISvb48eNIkmTRYQAAwLXN+2P13//938dHH31UckSsA3UmAGCZrV4ObJL2eQyxBQAAAAAAVI4eJAAAAAAAsJbOJmkv+5yrQQ8SAAAAAACgcjSQAAAAAAAAlWOILQAAAAAAWEsmaZ9HD5I1cHh4uOgQ3klR8TpusVbtOqzacYuyatdh1Y5blFW7Dqt23KKs2nVYteMWRbzFHhcWZZnu6bxiyeM4yxRLXpbpd1qmWPKybL/TMpVTHpbpuuR1HNe32OOs4/XNy7pdX8qjgWQNrNrDu2oV+1U7blFW7Tqs2nGLsmrXYdWOW5RVuw6rdtyirNp1WLXjFkW8xR4XFmWZ7ul1/MOa61vcMfI8Th6W7XdapnLKwzJdl7yO4/oWe5x1vL55Wbfrm6+zSdrLXFZnkva1GmJrPB7H3t5eRETs7+9f2J6maezt7UW9Xo/xeBzNZjO2t7cL2QcAAGAZqTcBAMAra9NAMhgMotvtRq/Xi1ardWH7aDSKRqMRw+EwkiSJiIjNzc04PT2d7J/XPgAAAMtIvQkAoGrMQTLP2gyxtbW1FcfHxzO3t9vt2NramiTnERGdTifa7Xbu+wAAACwj9SYAAPjG2jSQzDMej2MwGESz2Ty3/vbt2xERcXR0lNs+AAAAq0i9CQCAqqlEA8mTJ08iIqJer59bf/Ztpn6/n9s+AAAAq0i9CQBgHZU9QfvZshrWZg6SeUajUUREbGxszNye1z6zPHv2LCJeTVT45ZdfXiLq6b7zne/Ed77znQvHTtP0ysec5izGzz//PN5///1cj11EvI77SqXK7de/Pv9vXsd9i1yP+3Xs//7P/xwRFSm3NTpupZ63NTquclvN465cub3l/6jrKLPcvvrqq/jqq6+ufMx/+qd/ioiI3/3ud9eKjfIsut6UZ50pj2clr8+evJ7bPI6zTLGs9PWd8Tm/FNc35zrGUvxOOR+n8vdvwcdxfYs9ztpd3xzz5ryu7z/8wz+sYQ78rxU55xVlayYislardW7dvXv3sojIhsPh1P3r9Xpu+8zyN3/zN1lEWCwWi8VisVgslVp+/vOfXyGrp2gRy1dvUmeyWCwWi8WyLssy5MC/+c1vsu9+97sLuwbf/e53s9/85jeLvgxvVYkeJJubmxERcXp6OnV7vV7PbZ9Z/uzP/ix+/vOfxx//8R/HH/3RH1069jdN60ECAAB5u24Pkt/97nfxL//yL/Hnf/7nOUZFkRZdb1JnAgAWbZ1y4A8//DB+/etfx7/+62J6c3z/+9+PDz/8cCHnfhdL00CSpml0Op1L7Vuv16Pb7V762GcJ+Hg8nrk9r31m+f73vx9/8Rd/cbmAAQAApljnepM6EwBAvj788MOVaKRYpKVpIEmSpLDJ+m7fvh0RF8e6PXvdaDRy2wcAAKAo6k0AAJCfby06gDJsbGxMrUgMBoOIiLh7925u+wAAAKwi9SYAAKpmrRpIZnXhjoh49OhRDAaDc99i2t/fj/39/djY2Mh1Hyjam9/GA4rnuYPF8OxB/tSbKJPPcdaB+5h14D6G6WpZlmWLDiIPaZpGt9uNo6Oj2NjYiEePHsXW1ta55DtN09jb24t6vR6j0SiazWa0Wq0Lx8ljn1X1+u82Ho+j2WzG9vb2osOqvFqtdu51kiQxHA4nry9Tbsq2GOPxOPb29iLiVaX/TXmVjfLL19vKLcJzt8x6vV7s7e1FmqaRJEns7+/H1tbWuX08e8vnMuUW4dlbNq+X29l8Fp631abe9HbuxevxOX596hjFUhconny9WPLqYsl/KyiDr52cnGQRkQ2Hw8m6er2edbvdBUZFt9vNWq1Wtr+/P1leL6PLlJuyLUa/38+2t7eziMhardaF7XmVjfLL19vKLcs8d8tsf38/29rayrrdbnbv3r0sIrKIyPr9/mQfz97yuUy5ZZlnb9mclUe/38/6/X6WJEkWEdnJyclkH88b68a9eD0+x69PHaNY6gLFk68XS15dLPlvNWkgYWJrayvb2to6t67b7Wba0RbrzTKZtv1t5aZsizUruc6rbJRfMeZVijx3y2t7e/vc6+FwmEXEuWvt2Vs+lym3LPPsLZv9/f1zr8/K7fj4eLLO88a6cS9ej8/x/KhjFEtdoDjy9WLJq4sl/62mtZqDhKsbj8cxGAyi2WyeW3/79u2IiDg6OlpEWJXX6/XiyZMnsbOzM7UMLlNuynYx8iob5Vc+z93yGgwGF4ZBSJIkkiSZjKfr2Vs+lym3CM/eMrp3796512dDMCVJEhGeN9aPe/F6fI4Xz+du8dzH1yNfL5a8unjy32rSQEJERDx58iQiIur1+rn1Zx8A/X6/9Jh4dd3H43H0er1ot9tx8+bNGAwGk+2XKTdluxh5lY3yK5/nbnltbW1duKZnztZ79pbPZcotwrO3Cnq9Xuzv73veWFvuxevxOV48n7vFcx9fj3y9WPLq8sl/q0EDCRERk5bm1ydnnLadcnW73ciyLIbDYbRarcmETWflcZlyU7aLkVfZKL/yee5Wz2g0ip2dncnPEZ69VfB6uUV49pZdp9OZTCB5xvPGunEvXo/P8eL53C2e+7gY8vViyauLIf+tDg0kRETEyclJRETcunVr6vbxeFxiNLwpSZLodrtxfHwcEa8+pCMuV27KdjHyKhvltzieu9XQ6/WiXq9Hq9WKCM/eqniz3F7n2Vs+BwcHMRqNYjwenxuqwfPGunEv5sPneHF87pbHfZwf+Xqx5NXFkP9WiwYSIiJic3MzIiJOT0+nbp/VhY9ybW9vx/b2dqRpGhGXKzdluxh5lY3yWzzP3XLb29ubJPwRnr1V8Wa5TePZWx737t2L4+Pj6Pf7sbGxMRn72vPGunEv5svneP587pbPfXx98vViyauLIf+tFg0kRMQ3D96sFkoP5vJoNpuTD9DLlJuyXYy8ykb5LQfP3XLqdDrx6NGjc9fTs7f8ppXbLJ695bK1tRWtVmvS5d/zxrpxL+bP53i+fO4uhvv46uTrxZJXF0/+Ww0aSIiIiNu3b0fExTHuzl43Go3SY2K2s/K6TLkp28XIq2yU3/Lw3C2Xo6OjaDabk0nsznj2ltuscpvHs7dc/uRP/mRSYfO8sW7ci8XwOZ4fn7uL4z5+d/L1YsmryyP/XX8aSIiIV5MCJUkS/X7/3PrBYBAREXfv3l1EWEzR7/ej3W5HxOXKTdkuRl5lo/yWg+duufR6vYh49W2e16Vp6tlbYvPKbRbP3vIZjUaTMvS8sW7ci/nzOZ4vn7uL4T5+d/L1YsmryyX/rYAMvjYcDrOIyE5OTibr6vV6tr+/v8Coqms4HGZJkpy7/sfHx1mr1bqw39vKTdkW5+nTp1lEXCiXLMuvbJRf/maVm+du+fX7/SxJkqzb7Z5bWq1W1u12syzz7C2jt5WbZ2/5PH36NNve3s6Oj48n605OTrKtra1z+3neWDfuxavxOZ4vdYxiqQsUS75eLHl1ceS/1VXLsiwrtgmGVZKmaezt7UW9Xo/RaBTNZjNardaiw6qk8XgcOzs78eTJk7h9+3YkSRLNZvPCNwQiLlduyjZ/aZpGt9uNo6Oj2NjYiEePHsXW1lZsbGyc2yePslF++ZlXbp675Zam6dyuxk+fPp08f5695XGZcosIz94SajabkzJpNptRr9dje3v7wn6eN9aNe/HdyaHyo45RLHWBYsnXiyWvLp78t5o0kAAAAAAAAJVjDhIAAAAAAKByNJAAAAAAAACVo4EEAAAAAACoHA0kAAAAAABA5WggAQAAAAAAKkcDCQAAAAAAUDkaSAAAAAAAgMrRQAIAAAAAAFSOBhIAAAAAAKByvr3oAAAAgLcbjUaxubkZ9Xo9tre3IyLi/v37sbGxsfC4ut1ujMfj+MUvfhHj8TiePn268LgAAFht8l/KoIEEAABWSKfTiVartegwJur1euzv70dExMbGRhwcHCw4IgAA1on8lyIZYgsAAMjFBx98sOgQAACgNPLf1aeBBAAAAAAAqBwNJAAAUKLNzc1oNpuxs7MT7XY7dnZ2olarRa1WizRN3/l44/E4jo6OotlsxtHRUYxGo2g2m3Hz5s1oNpsxHo8jIuLg4CA2Nzfj5s2b0el0cns/AADMI/9lmZmDBAAASrS1tRXdbnfy+uDgIHq9XrRarUiS5J2Pd3p6GsPhMAaDQUREnJycxP7+fpyenk4qovV6PXZ2dqLf70en04mDg4P4+OOPI0mSa78fAADmkf+yzDSQAABAiXZ2diY/j8fj6HQ6sbGxMZno8V3V6/Vot9txdHR0bsLIiIgkSWIwGMTJyUnU6/WIiLh//370er0YDAaRJMm13w8AAPPIf1lmhtgCAIASbW1tTX7+8Y9/HBER+/v7sbGxce1jv3mMs0rdrVu3Lqw7OTnJ/f0AAPAm+S/LTAMJAAAswGAwiF6vF0mSRKvVWnQ4AABQKPkvy0gDCQAALEC73Y6IiOPj4wVHAgAAxZP/sow0kAAAQMk6nU6MRqO4d+/epMs+AACsK/kvy0oDCQAAlGg0GsXBwcHUiSkPDg4WFBUAABRD/ssy00ACAAAlmjW0QJqm8W//9m9XOubp6enU9ePx+ML2s5+nrbvq+wEAYBb5L8tMAwkAAJRkMBjEYDCIiFcVxHa7He12O5rNZjQajdjc3HznY6ZpOvkm3tHRUfR6vcnPZ+fqdDqRpmmMRqPodDqTWI6Ojq79fgAAmEX+y7KrZVmWLToIAABgvtFoFJubm9HtdqPVai06nKkODg6i0+nE06dPY2NjY9HhAACwwuS/lEEPEgAAWCFn3f6X0VWHSAAAgFnkvxTp24sOAAAAuLy9vb1JRez+/fsL/6baaDSKbrcbEWHIAQAAcif/pUiG2AIAAAAAACrHEFsAAAAAAEDlaCABAAAAAAAqRwMJAAAAAABQORpIAAAAAACAytFAAgAAAAAAVI4GEgAAAAAAoHI0kAAAAAAAAJWjgQQAAAAAAKgcDSQAAAAAAEDl/Hf19ag1TNQHmAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -696,7 +698,7 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -761,7 +763,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -795,7 +797,7 @@ "" ] }, - "execution_count": 79, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -806,7 +808,7 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -902,7 +904,7 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -923,7 +925,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -979,12 +981,12 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 19, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkIAAAHJCAYAAABpOFaGAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAxvklEQVR4nO3dT2wj6WH3+V+ne1qepOEpqefgOW26GBhBLjsoqn0IsOlBmhUj8CEwhtTcMgMYTcLQJRgkLHQu030JUUIOuQhwUQjQm9s0abzYQxAkpI3XXiCHtVjpXBaLxbI6wHtIgNdDlY2222r/qT30VA0pkRRF8U9Jz/cDCNNisZ56VMVR/fTU8+dakiSJAAAADPRb664AAADAuhCEAACAsQhCAADAWAQhAABgLIIQAAAwFkEIAAAYiyAEAACMRRACAADGIggBl0gURWo2m4rjeN1VWZs4jtVsNhVF0bqrggULw1DNZnPd1YBhCELAJbG3t6dCoaBarabBYLDu6swkDEN5nqdKpaJCoaC9vb0LlddsNnXnzh3VajWjw+AyRFGkzc3NtQSRKIpUqVRULBYVBMHKjw+zEYSAS6Jer6tcLq+7GjMLw1D379+X7/tqtVoql8vq9/sXKrNaraparS6ohl+Iosj4YBXHseI4HnuNJp2fRZ0327bVarUuXA4wD4IQcIlsbW2tuwozazQaI/X1fX8hf+3fvn37wmWcVKlULk0r27I4jqMkSeT7/qltk84P5w1XAUEIwFKEYbjuKsykUqlcmrquw6Tzw3nDVUEQAiZIO+UWi0W12211u10Vi0Vdu3ZNlUole1+73dbm5qauXbuW3Ri63a4qlcrIe9PyXNfNOvu6rqvNzU25rps9Ykj7Am1ubsrzvIl1q9Vq2tzc1Obmpmq12qn3hGGoSqUi13VVKBROldVut+W6rrrdrprN5sRyJh3b8zy5rpuVkWo2m6pUKoqiKOv7UalURt4z7Vyn9SkWi9rc3FSlUhn7+GUwGGTvO3lNZq1ru93OrlmtVjt1cz9r/1k/IyfLqtVqKhQK5+qPM+16LuKz1W63s2t11vk567yd9dkbPh/p10X7jwFzSwCM1e/3k3K5nEhKSqVSUq/Xk16vl1Sr1URS4vt+9t70tV6vN7K/pKRcLmffp+8bLq/T6WSvVavVpNPpjBx7uMzh/avVahIEQeI4TvZaqtfrjXzfarUSSUm1Ws2+t207e61eryeO4ySO40w9J71eL7Esa6ROQRCcOh9JkiS2bSe2bc90rtOfa/jctFqt7BwMl+P7fvY+3/cnXpNZ61qv1xNJSb/fP/fPep7PSLlcTur1+khZJ8/ZJGddz4t+tvr9/sh5HTbp/Ew7b9Pqmh7Psqyk0+lkr6XHP+szCCwaQQiYIv0lfvKGdfKGkd4Uhm+aR0dHI0EoSV7fJE7eFJIkycLM8E0lfe+4wNVqtUb2T0NNemNxHGekLkmSJJZlJZKSo6OjJEm+uPEM35zP4jjOqRvlpPqfJwgN1ycIgpHXS6XSyM886X0nr8msdZ10Q591/1k/I5ZlnTrXswahWa7nRT9b4+qcJOcPQrPUtVwujz23BCGsA4/GgBlYlnXqtYt0Ej1Znm3bkkY7Q6evjRvF4zjOyPfpI61Op6MoihSGoRqNRvaoY/hxx+Hh4Ugd7t69O1Od03JPHnv4+IvoDJ3+3CfL7nQ6I69vb2+PfG9ZVja30EXrOs/+Z31GbNvW3t7eyCOger0+sQ4n63LW9ZxUj/N+ti5ilrpGUZQ9lgXy4Ma6KwDg4kqlkqQvbkSSZh6OPO4GPs60jrFpKFnGJIdpGDlP2Ret6zJ+1larpWKxKM/zFASBWq3W2KA1qS6XYXj5LHVN+1idDLzAutAiBFwBaZixbXukVWQZxnVcTo+/jOH9aZnz3DgvWtdF/qy2bev58+cqlUqKokjFYnGmztLLvp6LNEtd020Mu0deEISAKyC9Yd+9ezcLDO12e+x7p43emiZtvRi3f3r8QqEwV9nTpDfMYrE48z4XresyftYoimRZljqdTtZiMssovWVdz2WYpa7pe3q93srqBUxDEAIWIJ3kb/gv4fTfq5ixOL3BlMvl7DGZ53mnHvFcZPkE27blOE42LH7Y4eGhLMsamfV5MBgs5K/+drs9UvZnn32Wlb+oukqj12me/c8yPFFhuVzO+hid1dKzrOt5XpM+x8Ovz1LX9NHipDXzTJ/hG6tHEAKmmPVGnrYgeJ6XzYOT3ui63W7WMXRSeekv/+Ht6b+HX0sfy5wMXGmfk/Q9aSfcYrGoSqWivb09ua6rfr+f3azSY57nxtNqtWRZ1khLRhzH8n1fBwcHM/c3mma4E3IcxwqCQAcHB2fuF8fxyLmata5py04QBFlH3vPsP+tn5OnTpyPXLY5j2bZ95iO/Wa/nRT9b494nTT4/416fpa4n39PtdhVFUTbXUBRFzCmE1Vr3sDUgr3q9Xjb02LbtpNPpJEdHRyNz3gwPP/Z9P7Esa2SYtG3b2Zwu6fwqkhLLsrLh4OncNPp8qH2v1xuZ68WyrGyo+NHRUVKv15NSqZTNDVOtVrNhycN838+G1du2PTLcfHgeoZPbznJ0dJQNf06PPzxcengeHX0+nHt4vphJhofzO46TlMvlpFwuj+zbarWyodjpMO2T12R4iPpZdU05jpNYlnVq6PksP+usn5FSqZR9Hur1elIul8det2nnZ9I1u+hnq9frZa+ldR6u26TzM+n1aXVNBUGQvcdxnKTf72fn5+SQfGCZriVJkqwocwHARHt7e/I8T51OJ2vlAIBl49EYAAAwFkEIAAAYiyAEYO3iOM5mjr4MEwcCuDroIwRg7caNEppl+QkAuCiCEAAAMBaPxgAAgLGMXXT1xz/+sf75n/9Zv/u7v6s333xz3dUBAAAzePnypf7jP/5DX//61/X2229fuDxjg9A//uM/6qOPPlp3NQAAwByePHmiDz/88MLlGBuE3nnnHUnSwcFBtjzCMrz//vv67ne/e2nLX8UxXrx4oXv37ukHP/iBbt26tbTjXIVzxbUw5xhci3wdYxXX4yqcp1UcIwxDPXjwILuPX9TSgtC3v/1tbW9v61vf+tayDnEhX/rSlyRJX/3qV5cahN58881LXf4qjvHTn/5UkvTuu+/qy1/+8tKOcxXOFdfCnGNwLfJ1jFVcj6twnlZxjBcvXkj64j5+UUvpLP38+XMFQcDwVwAAkGtLaRG6c+eOgiA4c1VlAACAdVrao7EHDx4sq2gAAICFWNo8Ql//+tf17NmzZRUPAABwYXO3CH3wwQcTt8VxrG63q6dPn+rdd9+d9xAAAABLNXcQmmVhxFarpb/5m7+Z9xBXwu7u7qUuf1XHWIWrcK64FuYdY9muynniWph1jEWae62xnZ0d+b6vra2tU9v6/b6azaa+853vXLiCy/LDH/4wmxPij/7oj9ZdHaP99Kc/1VtvvaWf/OQnSx0mjLNxLfKDa5EvXI/8WPT9e+4+QrVaTXfu3NFbb7116stxHBWLRf31X//1hSsIAACwLHMHofv370/dbtu2giCYt3gAAIClm7uP0LQRYVEUyfO8eYsGAABYibmDkOM4unbt2sTtSZJob29v3uJX5s///M/127/922O37e7uXrpOXwAAXHb7+/va398fu+3nP//5Qo81dxCyLEs7OzuyLOvUttu3b8txnDMfn+XBP/zDP9BZGgCAHJnWEJF2ll6UuYPQwcGB3n///YVVBAAAYNXm7ixNCAIAAJfd0tYa+/a3v63t7W1961vfWtYhLuTmzZsj/720/vXRumtwYRuvfqVPPvlEGxsb666K8TY2NrgWOcG1yBeuR34s+v4994SK0zx//lyFQkGbm5v67LPPFl38QoRhqGKxqF6vJ8dx1l2d+V2BICRJ+sNH664BAOASWPT9eyktQnfu3FEQBLJtexnFAwAALMTSHo3t7OzorbfeWlbxAAAAFzZ3Z+mzfO9739PDhw+XVTwAAMCFXahF6Pvf/746nY7iOB55fTAYKAxDDQYDNRqNixwCAABgaS40j1CtVpv6nmq1Om/xAAAASzf3o7EgCNTpdHR0dKR/+Zd/ke/7+s1vfqPf/OY3GgwGqlar+s53vrPIugIAACzU3EGoVCrp/v37euutt1QqlXR4eJhtsyxLxWKRPkIAACDX5n409pOf/GTk+52dHf3t3/6t/vIv/zJ7rd1u576P0Pvvv68333xz7DYWXQUAYPWmLbr68uXLhR5r7iBk27auX7+uzc1NHR4e6v3339f29rY6nY4sy1K73R67IGvefPe7373cEyoCAHDFTGuISCdUXJS5g9Bf/dVf6cc//rH+7d/+TVtbW5Kkp0+fynVdPX/+XJLk+/5iagkAALAEFxo+fzLo2Latfr+v58+fa2triwkVAQCrc1mWHGJJoVxZ2hIbAAAg38Iw1KeffqputytJ6vV6a67R6i1tZmkAAJBvjuPogw8+UBiG667K2lzpIBRF0bqrAABArpk+YGhpi67OKwxDNRoN2batOI7luq7K5fJM+167dm3ke8dxzmzmCwLpnXfmru7aPfqTddcAAIDLK1dBKIoiFYtF9Xq9LKEWCoVspuppms2mqtWqCoVC9lqpVFpqfQEAWLUwDHX//n3FcSzHcdRqtWTbtiTJ8zzt7e3J933V6/Xs/Y1GQ3EcK4oilcvlmUd1x3Esz/NkWVb2+MzzvCt1f81VEKrVaiqVSiPNdJ7nqVarnRmEWq2WOp3OsqsIAMBaOY6jg4MDVSoV2badhSDp9X00DMOREOR5XnZ/bLfbqlQqiuNYQRBMPU4auL73ve9l9+VmsynXdUeC1mWXmz5CcRyr2+3Kdd2R17e3tyW9PvmTtNttHR4eqlKpTH0fAABXQblclm3barfbI6+32+2RBdEfPHgw0vpTLpdlWZaazabiOJ56jAcPHmh7e3ukcaJarcpxHHmed2X64eYmCKVrlQ0nW+mLTlzTWns6nY7iOM4+AJubm9lQQAAArqI08AyHoU8//TTrVxtFUfZYrFKpZF+p4TVCT0r3HdeROj3uWS1Kl0VuHo2lyXLSshzTkmcQBAqCQGEYKgiCrOmu3++fClYnvXr1QsfHP5273tevb+jGjY259wcAYB7ValWe5ykIApXLZYVhmD1FkZT16Wm1Wucue9pw+vQY87YIHR8f6/j4eK59JenFixdz7ztOboJQv9+XpGy5jpPOasKTXrceBUEg13VVqVTked6ZH4AnT+6du67D7t37RO+99+hCZQAAcF6WZalcLqvdbiuKIn366acjj8XSoBJF0ZmNApOMu/emDRaT7tdnaTQaevz48Vz7LkNuglA62mswGIzdfp6LWC6Xs3R8lo8++oG+8pV3Zy77pOvXaQ0CAKzHw4cP1W63s6ciw/2B0vtmu90e27G52+1OHP2VPhIb180kDUfDo7TPW+ePP/54rn0l6dmzZ7p372KNGMNyE4TSCzap5ee8adZ13Zn6Cd28eUsbG18+V9kAAOSB4ziybVt7e3un+uykIScd7j7c36fZbE69r9q2LcdxFIbhqRalw8NDWZZ15mjuSTY2NrSxMX8jwq1bt+bed5zcdJae9Mwx/b5YLM5dJgAAV1X6OGxnZ2fkdcuyspagYrGoSqWivb29rA/tWXMBtVotWZY18rgtjmP5vq+Dg4OJfXovm9y0CFmWJcdx1Ol0Rprw0ladkxf4LJ1OZ+TiAQCuOENXda9Wq+r3+2ODie/7un37toIgULvdzuYVSltz0kFG6b/39vZUrVZlWZZs29bz58/14MEDua6btQq1Wq0rtSzHtSRJknVXIhWGoYrF4shor0KhoFqtloWjKIrkuq6CIFCpVFIYhnrw4IE++OCD7D3tdludTmfq0L70WNVqT++8c3kv6KM/ebTuKiyGob/AAADnk96/h1ehuIjctAhJX6wN5nmebNtWFEUjyVV63Sw3GAyyvkS2bWtra0uNRkOdTkeO42RBCQAAYJpcBSFJ2bop07YfHR1l31uWxdIaAABgLrnpLA0AALBqBCEAAGAsghAAADAWQQgAABiLIAQAAIyVu1Fjq/b06fu6cePNsdvu3t3V1762u+IaAQBgtv39fe3v74/d9vLly4Uey/ggtLPz3Us9oSIAAFfN7u6udnfHN0SkEyouCo/GAACAsQhCAADAWAQhAABgLIIQAAAwlvGdpQEAV8OjR+uuwWwuSz1NQYsQAACQJMVxrGazqSiK1l2VlSEIAQBwhURRpM3NTTWbzXPt12w2defOHdVqNcVxvJzK5RBBCACAKySOY8VxrH6/f679qtWqqtXqkmqVX/QRAgDgCnEcR0mSzLXv7du3F1yb/KNFCAAAGIsgBADAJdNut+W6rrrdrprNpjY3N1Wr1bJtlUpFlUrl1H5xHKtWq6lWq8l1XbmuqzAMT71vMBio2WyqWCzq2rVrY8u6Kng0BgDAJdJut+V5nqIokm3bsixLtm3r8PBQURQpiiK1222VSqWR/aIokuu66nQ6sm1bkrS5uan79+/r6Oho5L2+78t1XR0cHCgIAjWbTe3t7aler6/s51wV44MQq88DAC6TcrmsKIrkeZ4sy5Lv+yPb6/W6PM87tV+lUlGtVstCkCQ9fPhQnucpjmNZljXy3rTjdBqEOp3OyoIQq8+vEKvPAwAumzS03L17d6b3R1GkMAx1cHAw8nq9Xh8bbra3t08db5VzC7H6PAAAONNwK840aT+gWd9vEoIQAABXXNqaY9KM0bMiCAEAcMU5zusuIK1Wa+x2kwMSQQgAgCsu7fPTbDbV7XZHtnmep62tLUnSZ599Jun18HlTEIQAALhk0rXAxq0Jlr42HGaGR5e5rqtKpSLP81QsFlUoFM7sOxTH8ZUNR8aPGgMAXA2PHq27BqvRbrcVBIGk1605g8EgG+oehqEajUb27729PVWrVVmWpXq9Ltu21Wg01G635TiOfN/P5htqt9vZQq2e5+ng4EC2bWdD8eM4lud5p4brX3bXknkXJLnk0uF31WrvUg+ff/Qnj9ZdhcX4w0frrgEA4BJI79+9Xi/r+3QRPBoDAADGIggBAABjEYQAAICxCEIAAMBYxo8aY9FVAADyZZWLrjJq7JKPGtP/+O/rrsFCPPr799ZdBQDAJcCoMQAAgAUhCAEAAGMRhAAAgLEIQgAAwFgEIQAAYCyCEAAAMBZBCAAAGIsgBAAAjEUQAgAAxiIIAQAAYxGEAACAsVh0lUVXAQDIlVUuump8ENrZ+e7lXnQVAIArZnd3V7u74xsi0kVXF4VHYwAAwFgEIQAAYCyCEAAAMBZBCAAAGIsgBAAAjJW7IBSGoSqVijzPU61WU7vdPncZ3W5Xm5ubS6gdAAC4SnI1fD6KIhWLRfV6PTnO6yHthUJBg8FA1Wp15nJqtdqyqggAAK6QXLUI1Wo1lUqlLARJylqGZuV5nmzbXkb1AADAFZObIBTHsbrdrlzXHXl9e3tbktRsNs8so9vt6vbt2yNBCgAAYJLcBKHDw0NJOtWak4aaTqdzZhlBEKhery++cgAA4ErKTR+hKIokSZZlTd0+ied58n3/3Md99eqFjo9/eu79Utevb+jGjY259wcAwCTHx8c6Pj6ee/8XL14ssDY5CkL9fl+StLW1NXZ7HMcT9w3DULdv356rb9CTJ/fOvc+we/c+0XvvPbpQGQAAmKLRaOjx48frrkYmN0GoUChIkgaDwdjt00JOo9FQq9Wa67gfffQDfeUr7861r/S6RQgAAMzm4cOH+vjjj+fe/9mzZ7p372KNGMNyE4TSoDOp5WdSEPI8T67rjjw6S/+d/ndaiLp585Y2Nr48T5UBAMA5bWxsaGNj/kaEW7duLbA2OQpC6eiwk32B0u+LxeLY/brdrvb29sZuKxQKchxHvV5vgTUFAABXRW5GjVmWJcdxTo0O63a7kqSdnZ2x+/V6PSVJMvJVr9dlWZaSJCEEAQCAiXIThCTp4OBA3W53pFXI9335vp+NJouiSIVCIQtIAAAA88rNozFJ2WOsdHboKIrked7I8hpxHGswGEwdRQYAADCLXAUh6XUYmjYCzHEcHR0dTS0jbUUCAACYJlePxgAAAFaJIAQAAIxFEAIAAMbKXR+hlfuvQ+lX8681BgAALi9ahAAAgLGMbxF6+v1PJq4ef/f3/0xf+4NvrrhGAACYbX9/X/v7+2O3vXz5cqHHMj4I7fzxY73z9lfXXQ0AAPC53d1d7e7ujt0WhuHEZbfmwaMxAABgLIIQAAAwFkEIAAAYiyAEAACMRRACAADGIggBAABjEYQAAICxCEIAAMBYBCEAAGAsghAAADAWQQgAABiLIAQAAIxl/KKrrD4PAEC+sPr8CrH6PAAA+cLq8wAAACtAEAIAAMYiCAEAAGMRhAAAgLEIQgAAwFgEIQAAYCyCEAAAMBZBCAAAGIsgBAAAjEUQAgAAxiIIAQAAYxm/1hiLrgIAkC8surpCLLoKAEC+sOgqAADAChCEAACAsQhCAADAWAQhAABgLIIQAAAwFkEIAAAYiyAEAACMRRACAADGIggBAABjEYQAAICxCEIAAMBYxq81xqKrAADkC4uurhCLrgIAkC8sugoAALACBCEAAGAsghAAADAWQQgAABiLIAQAAIyVuyAUhqEqlYo8z1OtVlO73Z5pv3a7rWKxqGvXrqlQKKjb7S65pgAA4LLL1fD5KIpULBbV6/XkOI4kqVAoaDAYqFqtTtyv2Wyq1+vJ931Jkud5cl1X/X5ftm2vpO4AAODyyVWLUK1WU6lUykKQpKxlaJo4jhUEgUqlkkqlkg4ODiS9bl0CAACYJDdBKI5jdbtdua478vr29rak160+k9Tr9ZHvLcuSpJFABQAAcFJugtDh4aEknXqUlYaZTqczc1ntdlu+7/NYDAAATJWbPkJRFEn6ojVn0vazeJ6nZrOZPR47y6tfvtTxq5/N9N5xrl9/Qzeu35x7fwAATHJ8fKzj4+O593/x4sUCa5OjINTv9yVJW1tbY7fHcXxmGXt7e4qiSHEcq1KpKAiCqZ2sJenJP/3Feas64t67H+o956MLlQEAgCkajYYeP3687mpkchOECoWCJGkwGIzdPstjrrSvULfbVaVSke/7Zwahj/707/SV2793ztp+4fr1N+beFwAA0zx8+FAff/zx3Ps/e/ZM9+7dW1h9chOE0qAzqeXnPP19SqWSqtWq9vb2znzvzTfe1MbN35m5bAAAML+NjQ1tbGzMvf+tW7cWWJscdZZOR4ed7AuUfl8sFs9V3t27d+ksDQAApspNELIsS47jnBodls4QvbOzc67yoihSqVRaWP0AAMDVk5sgJEkHBwfqdrsjrUK+78v3/Ww0WRRFI0topB2jh5fiiKJInU5HQRCstP4AAOByyU0fIen1nEG9Xk+e58m2bUVRJM/zRjo8x3GswWCQ9SWyLEtxHOvBgwcKgkCu68q27XPNOwQAAMyUqyAkvQ5DrVZr6vajo6OR1wg9AABgHrl6NAYAALBKBCEAAGAsghAAADAWQQgAABiLIAQAAIyVu1Fjq/b0+5/oxo3xU33f/f0/09f+4JsrrhEAAGbb39/X/v7+2G0vX75c6LGMD0I7f/xY77z91XVXAwAAfG53d1e7u7tjt4VheO5lt6bh0RgAADAWQQgAABiLIAQAAIxFEAIAAMYiCAEAAGMRhAAAgLEIQgAAwFgEIQAAYCyCEAAAMBZBCAAAGIsgBAAAjEUQAgAAxjJ+0VVWnwcAIF9YfX6FWH0eAIB8YfV5AACAFSAIAQAAYxGEAACAsQhCAADAWAQhAABgLIIQAAAwFkEIAAAYiyAEAACMRRACAADGIggBAABjEYQAAICxjF9rjEVXAQDIFxZdXSEWXQUAIF9YdBUAAGAFCEIAAMBYBCEAAGAsghAAADAWQQgAABiLIAQAAIxFEAIAAMYiCAEAAGMRhAAAgLEIQgAAwFgEIQAAYCzj1xpj0VUAAPKFRVdXiEVXAQDIFxZdBQAAWAGCEAAAMBZBCAAAGIsgBAAAjEUQAgAAxspdEArDUJVKRZ7nqVarqd1uz7Rfu91WsVjUtWvXVCwW1e12l1xTAABw2eVq+HwURSoWi+r1enIcR5JUKBQ0GAxUrVYn7re3t6dOp6NaraZ+v6+9vT25rqtOp6NSqbSq6gMAgEsmVy1CtVpNpVIpC0GSspahaX70ox+p0+moWq3K9331ej1Jku/7S60vAAC43HIThOI4Vrfbleu6I69vb29LkprN5tj9ut3uqcDjOI4cx1EURcupLAAAuBJyE4QODw8lSbZtj7yetg51Op2x+5VKpVP7pCa9DgAAIOWoj1DaemNZ1tTt5ynvrEdqkvTqly91/Opn5yp72PXrb+jG9Ztz7w8AgEmOj491fHw89/4vXrxYYG1yFIT6/b4kaWtra+z2OI5nLqvdbsu27akdrFNP/ukvZi53nHvvfqj3nI8uVAYAAKZoNBp6/PjxuquRyU0QKhQKkqTBYDB2+3keczUaDbVarZne+9Gf/p2+cvv3Zi77pOvX35h7XwAATPPw4UN9/PHHc+//7Nkz3bt3b2H1yU0QSoPOpJafWYOQ53k6ODiY+f0333hTGzd/Z6b3AgCAi9nY2NDGxsbc+9+6dWuBtclRZ+l0dNjJvkDp98Vi8cwyms2mXNcdGX4PAAAwSW6CkGVZchzn1OiwdIbonZ2dqfunM1CfnEAxDMMF1hIAAFwluQlCknRwcKButzvSKuT7vnzfz0aTRVGkQqEwsoRGt9tVo9GQ9LpVKP2q1WrZsHwAAICTctNHSHo9Z1Cv15PnebJtW1EUyfO8kdFfcRxrMBhkfYnCMMwmYRw3XP7o6GgldQcAAJdProKQ9DoMTRvx5TjOSLhxHEdJkqyiagAA4IrJ1aMxAACAVSIIAQAAYxGEAACAsQhCAADAWAQhAABgLIIQAAAwVu6Gz6/a0+9/ohs3xq95cvf3/0xf+4NvrrhGAACYbX9/X/v7+2O3vXz5cqHHMj4I7fzxY73z9lfXXQ0AAPC53d1d7e7ujt0WhuFM64/OikdjAADAWAQhAABgLIIQAAAwFkEIAAAYiyAEAACMRRACAADGIggBAABjEYQAAICxCEIAAMBYBCEAAGAsghAAADCW8WuNsegqAAD5wqKrK8SiqwAA5AuLrgIAAKwAQQgAABiLIAQAAIxFEAIAAMYiCAEAAGMRhAAAgLEIQgAAwFgEIQAAYCyCEAAAMBZBCAAAGIsgBAAAjGX8WmMsugoAQL6w6OoKsegqAAD5wqKrAAAAK0AQAgAAxiIIAQAAYxGEAACAsQhCAADAWAQhAABgLIIQAAAwFkEIAAAYiyAEAACMRRACAADGIggBAABjGb/WGIuuAgCQLyy6ukIsugoAQL6w6CoAAMAKEIQAAICxCEIAAMBYBCEAAGAsghAAADBW7kaNhWGoRqMh27YVx7Fc11W5XJ5p3ziO1Wg0JEm+7y+zmgAA4ArIVRCKokjFYlG9Xk+O40iSCoWCBoOBqtXq1H273a6CIFC73T7zvQAAAFLOHo3VajWVSqUsBEmS53mq1Wpn7lsqldRqtZZZPQAAcMXkJgjFcaxutyvXdUde397eliQ1m811VAsAAFxhuQlCh4eHkiTbtkdeT1uHOp3OyusEAACuttz0EYqiSJJkWdbU7Yv26pcvdfzqZ3Pvf/36G7px/eYCawQAwNV1fHys4+Pjufd/8eLFAmuToyDU7/clSVtbW2O3x3G8lOM++ae/uND+9979UO85Hy2kLgAAXHWNRkOPHz9edzUyuQlChUJBkjQYDMZuP/nIbFE++tO/01du/97c+1+//sYCawMAwNX28OFDffzxx3Pv/+zZM927d29h9clNEEqDzqSWn2UFoZtvvKmNm7+zlLIBAMCojY0NbWxszL3/rVu3FlibHHWWTkeHnewLlH5fLBZXXicAAHC15SYIWZYlx3FOjQ7rdruSpJ2dnXVUCwAAXGG5CUKSdHBwoG63O9Iq5Pu+fN/PRpNFUaRCoZAFpGHL6lANAACuptz0EZJezxnU6/XkeZ5s21YURfI8b2TJjDiONRgMToWeMAwVBIEk6enTp3JdV6VSaeJwfAAAgFwFIel1GJq2VIbjODo6Ohr7ehAEWRgCAAA4S64ejQEAAKwSQQgAABiLIAQAAIxFEAIAAMYiCAEAAGMRhAAAgLFyN3x+1Z5+/xPduDF+zZO7v/9n+toffHPFNQIAwGz7+/va398fu+3ly5cLPZbxQWjnjx/rnbe/uu5qAACAz+3u7mp3d3fstjAMF7r+KI/GAACAsYxvEUJO/OujdddgMf7w0bprAAA4B1qEAACAsQhCAADAWAQhAABgLIIQAAAwFkEIAAAYiyAEAACMRRACAADGIggBAABjEYQAAICxjJ9ZmkVXAQDIFxZdXSEWXQUAIF9YdBUAAGAFCEIAAMBYBCEAAGAsghAAADAWQQgAABiLIAQAAIxl/PB55MOjv39v3VVYiEd/uO4aAADOgxYhAABgLIIQAAAwFkEIAAAYiyAEAACMZXxnaRZdBQAgX1h0dYVYdBUAgHxh0VUAAIAVIAgBAABjEYQAAICxCEIAAMBYBCEAAGAsghAAADAWQQgAABjL2CD06tUrSdKvfvPLNdcEv/r1K/338Il+9etX666K8Y6Pj/Xo0SMdHx+vuyrG41rkC9cjP9L7d/rfizI+CP3m179ac03w61//Uj949r/r178mlK7b8fGxHj9+zC/7HOBa5AvXIz8IQgAAAAtCEAIAAMYyfq2x//Z/NvTGjS+N3caiqwAArN60RVd//vOfL/RYxgehb/5vD/W/vPO/rrsaAADgc9MWXf3hD3+oe/fuLexYPBoDAADGIggBAABjEYQAAICxCEJL9n/93//tUpe/qmOswip+jkmd+y5L+auyip/jqhxj2a7KeeJamHWMRSIILdmP/p//41KXv6pjrMIqfg6C0Gyuyi/jq3A9rsp54lqYdYxFyt2osTAM1Wg0ZNu24jiW67oql8tL2w8AAJgrV0EoiiIVi0X1ej05jiNJKhQKGgwGqlarC98PAACYLVdBqFarqVQqZWFGkjzPU61Wmxpo5t0PWLiX/1P610eXt/yfsY4SALPkpo9QHMfqdrtyXXfk9e3tbUlSs9lc6H4AAAC5aRE6PDyUJNm2PfJ62srT6XTGtu7Mux+wDP8z/h09+vv3llj+k6WWf/zqZ0srGwDyKDdBKIoiSZJlWVO3L2q/X/ziF5Kk/xr0z1HL037r+g3d+K03Jm7/1a+O9Z8//n8vdIxpll3+Ko7x6pcvJUn/9dn/p5tvvLm041yFc7Wqa/Hs2TPdunVracd5+fKlwjBcWvlX4RgvXryQxLXIyzFWcT2uwnma5RivXr3Sq1ev5i7/3//93yV9cR+/sCQn6vV6Iinp9XqntklKbNte6H5PnjxJJPHFF1988cUXX5fw68mTJxcLHp/LTYtQoVCQJA0Gg7HbTz76uuh+3/jGN/TkyRO98847+tKXxq8+P4ubN2/q5s2bc+8PAIBJLtoi9Itf/EL/+Z//qW984xsLqU9uglAaWOI4nrp9Ufu9/fbb+vDDD89XSQAAcKXkZtRYOsrrZJ+e9PtisbjQ/QAAAHIThCzLkuM46nQ6I693u11J0s7OzkL3AwAAyE0QkqSDgwN1u92R1h3f9+X7fjYqLIoiFQqFLOjMuh8AAMBJuekjJL2e+6fX68nzPNm2rSiK5HneyDxAcRxrMBiM9AmaZb8Ua5LlR7vdVqPRUBiGchxHvu+rVCqtu1rQ6xbVSqWio6OjdVfFeFEUqd1uS5Kq1Sp/3K1Qu91Wp9ORZVmKoki2bcv3/XVX68qL41iNRkOSxp7vhd/HFzL27JLo9/uJNDrU3rbtJAiCNdbKTL7vJ6VSKQmCIJsCQVLS6XTWXTUkr/+/sCxr3dUwWr/fT8rlclIqlZJ+v7/u6hin1WoljuOMvFYqlZJ6vb6mGpmh0+kk5XI5kZRUq9VT25dxHzcqCJVKpaRUKo28FgRBYlgezIVyuTzyfa/XSySduj5YvXq9npRKJYLQGvV6vcSyrLE3AqxGqVQ6df593584Nx0Wa1IQWsZ9PFd9hJaJNcnyo9vtnmrudBxHjuNMnAkcq9HtdnX79u2RBYyxWnEc6/79+7JtW0EQrLs6xhoMBiN9USWp3+9PnJIFy7es+7gxQWiWNcmwGqVS6cx5obAeQRCoXq+vuxpG8zxPcRzTF2XNarWaoihSpVKR9LpfytOnT7kua7Ss+7gxQWjeNcmwOsO/dLB6nufxSz4H0r9qO52OisWiNjc35bouv6NWrFqtqlqtqt1uq1AoyPM8PX/+nNbSNVrWfdyYINTvv15cdWtra+z2STNTYzXa7bZs2x470g/LF4ahbt++TYvcmqULVTqOo1qtpl6vp16vl00bwu+p1QqCIHtk3+12Tz0qw2ot6z5uTBCad00yrEaj0VCr1Vp3NYzVaDR4JJYD6V+0tVot+5003FcoHVKM1XBdV7VaLRtCX6lUsqkMsHrLuo/nah6hZZp3TTIsn+d5Ojg44Bqsied5px69pP9O/8u1WY1JTf7p/Fo8HludWq0mSVkr9fPnz3Xnzh09ePCAuefWZFn3cWNahFiTLJ+azaZc1+W5+xp1u13VajUVCoXsq91uK45jFQoF+m2tUPp7Kn0EcNKkRwJYvKdPn478XrIsS77vK47j7BEmVmtZ93FjghBrkuVP2sR8cjZpfsmsVq/XU/J6TrHsq16vy7IsJUmiXq+37ioaw7IslUqlU31R0r+A+YNtdba2tk61PKS/q5jdez2WdR83JghJrEmWJ91uN+vv0Gw2s69arZYNkQRM5Pu+wjAcCUPNZlOO4zCYYIVqtZqePn06Eoba7bYcx+FR8ZJN6/S8jPv4tc9ncDTG8BolURTJdV1+uaxYGIZT/7I9OjoimK6Z53lqNpusNbYmYRhmaydalqU4jplccQ2azaZarVb2iCyd34nfT8sThqGCIFCz2ZRlWTo4OFCpVBo554u+jxsXhAAAAFJGPRoDAAAYRhACAADGIggBAABjEYQAAICxCEIAAMBYBCEAAGAsghAAADAWQQgAcOVEUaRmszl1luKrLo5jNZtNFus9A0EIAHCl7O3tqVAoqFaraTAYrLs6M0lnE69UKioUCtrb27tQec1mU3fu3FGtVjM6DM7ixrorAADAItXrdf3oRz/KFnbOuzAMdf/+/WxJG8/z1O/3L1RmtVpVv9+/cKA6KYoibW1tXallRghCAIArZ2tra91VmFmj0Ripr+/7Cyn39u3bCylnWKVSUavVulJBiEdjAACsURiG667CTCqVyqWp63kQhAAAF5J2yi0Wi2q32+p2uyoWi7p27ZoqlUr2vna7rc3NTV27di27oXa7XVUqlZH3puW5rpt19nVdV5ubm3JdN+vzkvYF2tzclOd5E+tWq9W0ubmpzc1N1Wq1U+8Jw1CVSkWu66pQKJwqq91uy3VddbtdNZvNieVMOrbneXJdNysj1Ww2ValUFEWRoihSpVJRpVIZec+0c53Wp1gsanNzU5VKZWx/oMFgkL3v5DWZta7tdju7ZrVa7VQoOmv/WT8jJ8uq1WoqFApqNptnnu+5JQAAXEC/30/K5XIiKSmVSkm9Xk96vV5SrVYTSYnv+9l709d6vd7I/pKScrmcfZ++b7i8TqeTvVatVpNOpzNy7OEyh/evVqtJEASJ4zjZa6lerzfyfavVSiQl1Wo1+9627ey1er2eOI6TOI4z9Zz0er3EsqyROgVBcOp8JEmS2Lad2LY907lOf67hc9NqtbJzMFyO7/vZ+3zfn3hNZq1rvV5PJCX9fv/cP+t5PiPlcjmp1+sjZZ08Z4tEEAIAXFgaIE7esE4Gj/RmOnzTPDo6GglCSfL65jocSFJpmBm+GafvHRe4Wq3WyP5pqOl0Oll5w3VJkiSxLCuRlBwdHSVJ8kWgGL45n8VxnJGfe1r9zxOEhusTBMHI66VSaeRnnvS+k9dk1rpOCkKz7j/rZ8SyrFPneplBiEdjAICFGdeJ9iJD2E+WZ9u2pNHO0Olr40ZaOY4z8n36SKvT6SiKIoVhqEajkT2WGn5Mc3h4OFKHu3fvzlTntNyTxx4+fhAEM5U1Tfpznyy70+mMvL69vT3yvWVZ2dxCF63rPPuf9RmxbVt7e3sjI97q9frEOlwUo8YAAMYolUqSvriBS1Kr1Zpp31lHSk3rUJyGkmVMcpiGkfOUfdG6LuNnbbVaKhaL8jxPQRCo1WqNDVqLQosQAMAYaZixbXukVWQZxnVcTo+/jOH9aZknW4pmcdG6LvJntW1bz58/V6lUUhRFKhaLS+0sTRACABgjvWHfvXs3CwyTJl6cNnprmrT1Ytz+6fELhcJcZU+TPl4qFosz73PRui7jZ42iSJZlqdPpZK11s4zSmxdBCACwMukkf8OtMOm/V7EURLfblW3bKpfL2WMyz/NOPeK5SAuEbdtyHCcbFj/s8PBQlmWpWq1mrw0Gg4UsBdJut0fK/uyzz7LyF1VXafQ6zbP/WYYnlCyXy1kfo2W13BGEAAAXNuuNPG1B8DwvmwcnvdF1u125rju1vPQmPLw9/ffwa+ljmZOBK+1zkr4n7YRbLBZVqVS0t7cn13XV7/ezoJQe8zxBLZ19ebglI45j+b6vg4ODhczMPNwJOY5jBUGgg4ODM/eL43jkXM1a17RlJwgCRVGUtaTNuv+sn5GnT5+OXLc4jmXb9lyP/GaytPFoAAAj9Hq9bKi0bdtJp9NJjo6ORua8GR7+7Pt+YlnWyDBp27azuWXSuX0kJZZlZcPB07lp9PlQ+16vNzI/jWVZ2VDxo6OjpF6vJ6VSKZtLqFqtZkPih/m+nw2rt217ZLj58DxCJ7ed5ejoKCmXyyPHHx6qPzyPjj6fKiAd1j/N8HB+x3GScrmclMvlkX1brVY2DUA6RcDJazI8RP2suqYcx0ksyzo1rcEsP+usn5FSqZR9Hur1elIul8det0W5liRJspyIBQAAFm1vb0+e56nT6WStVpgfj8YAAICxCEIAAMBYBCEAAC6JOI6zmaNnnQgS09FHCACAS2J42YnUMpefMAFBCAAAGItHYwAAwFgEIQAAYCyCEAAAMBZBCAAAGIsgBAAAjEUQAgAAxiIIAQAAYxGEAACAsf5/ql5nKGAe1xcAAAAASUVORK5CYII=", + "image/png": "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", "text/plain": [ "
" ] @@ -1038,7 +1040,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -1047,7 +1049,7 @@ "' \\nphoton cut = x*E_0\\neffs, all photons included: x=0\\nfound in velo/(found + lost in velo)\\nVELO energy emission, eff: 0.8446167611094543\\nRICH1+UT energy emission, eff: 0.7961586121437423\\neff von e die nicht strahlen: 0.7954674220963173\\n'" ] }, - "execution_count": 44, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } diff --git a/trackinglosses_rad_length_beginVelo2endVelo.ipynb b/trackinglosses_rad_length_beginVelo2endVelo.ipynb new file mode 100644 index 0000000..cfa655a --- /dev/null +++ b/trackinglosses_rad_length_beginVelo2endVelo.ipynb @@ -0,0 +1,1264 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "import uproot\t\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import colormaps\n", + "from mpl_toolkits import mplot3d\n", + "import awkward as ak\n", + "from scipy.optimize import curve_fit\n", + "from scipy import stats\n", + "from methods.fit_linear_regression_model import fit_linear_regression_model\n", + "import sklearn\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def round(n, k):\n", + " # function to round number 'n' up/down to nearest 'k'\n", + " # use positive k to round up\n", + " # use negative k to round down\n", + "\n", + " return n - n % k" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1515 299\n", + "1789\n" + ] + } + ], + "source": [ + "file = uproot.open(\n", + " \"tracking_losses_ntuple_B_rad_length_beginVelo2endVelo.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n", + ")\n", + "\n", + "# selektiere nur elektronen von B->K*ee\n", + "allcolumns = file.arrays()\n", + "found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) &\n", + " (allcolumns.fromB)]\n", + "lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) &\n", + " (allcolumns.fromB)]\n", + "\n", + "electrons = allcolumns[(allcolumns.isElectron)\n", + " & (allcolumns.fromB)\n", + " & (allcolumns.eta <= 5.0)\n", + " & (allcolumns.eta >= 1.5)\n", + " & (np.abs(allcolumns.phi) < 3.142)]\n", + "\n", + "print(ak.num(found, axis=0), ak.num(lost, axis=0))\n", + "print(ak.num(electrons, axis=0))\n", + "# ak.count(found, axis=None)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# variables\n", + "\n", + "eta_a = ak.to_numpy(electrons[\"eta\"])\n", + "phi_a = ak.to_numpy(electrons[\"phi\"])\n", + "rad_length_frac_a = ak.to_numpy(electrons[\"rad_length_frac\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(\n", + " rad_length_frac_a,\n", + " bins=100,\n", + " density=True,\n", + " alpha=0.5,\n", + " color=\"blue\",\n", + " histtype=\"bar\",\n", + " range=[0, 1],\n", + ")\n", + "plt.xlim(0, 1)\n", + "# plt.yscale(\"log\")\n", + "plt.title(\"radiation length fraction beginVelo2endVelo\")\n", + "plt.xlabel(f\"$x/X_0$\")\n", + "plt.ylabel(\"a.u.\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame({\n", + " \"phi\": phi_a * 90.0 / np.pi,\n", + " \"eta\": eta_a,\n", + " \"rad_length_frac\": rad_length_frac_a,\n", + "})\n", + "df = df.round({\"phi\": 0, \"eta\": 1, \"rad_length_frac\": 4})" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "df_pivoted = df.pivot_table(\n", + " index=\"eta\",\n", + " columns=\"phi\",\n", + " values=\"rad_length_frac\",\n", + " margins=False,\n", + " fill_value=0,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
phi-90.0-89.0-88.0-87.0-86.0-85.0-84.0-83.0-82.0-81.0...81.082.083.084.085.086.087.088.089.090.0
eta
1.60.00000.000000.00000.00000.000000.0000000.00000.000000.000000.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
1.70.00000.000000.00000.00000.000000.0000000.26650.000000.000000.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
1.80.00000.000000.00000.00000.000000.0000000.00000.000000.000000.128900...0.000000.00000.00000.0000000.000000.000000.00000.44750.0000000.0000
1.90.00000.000000.00000.00000.000000.0000000.00000.000000.000000.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
2.00.00000.000000.00000.00000.000000.1900000.00000.152250.000000.000000...0.000000.00000.00000.0000000.000000.299050.00000.00000.0000000.0000
2.10.00000.000000.00000.00000.000000.0000000.00000.000000.000000.182700...0.176750.00000.00000.0000000.000000.297050.00000.24220.0000000.0000
2.20.14760.000000.00000.00000.000000.0000000.00000.165350.000000.000000...0.000000.00000.18400.0000000.196500.000000.00000.25670.5531000.0000
2.30.00000.146700.00000.44240.413100.0000000.00000.000000.158900.000000...0.000000.19360.00000.0000000.000000.000000.00000.00000.0000000.0000
2.40.38740.000000.00000.00000.441200.1778330.00000.000000.172950.000000...0.196800.15810.00000.0000000.000000.000000.00000.00000.0000000.0000
2.50.00000.000000.48670.00000.000000.0000000.00000.237900.000000.200300...0.000000.00000.00000.0000000.000000.000000.00000.55980.0000000.0000
2.60.20990.000000.00000.00000.000000.0000000.00000.192800.000000.000000...0.000000.00000.00000.1794000.000000.000000.37560.00000.0000000.0000
2.70.00000.287100.00000.38490.441500.0000000.00000.000000.000000.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
2.80.00000.334400.00000.00000.000000.0000000.00000.223700.000000.000000...0.000000.00000.19980.0000000.000000.000000.38150.00000.5098330.0000
2.90.00000.000000.00000.00000.239500.0000000.00000.000000.000000.252150...0.000000.00000.00000.2298000.000000.000000.21740.00000.1733000.5137
3.00.00000.201900.00000.00000.244750.2843000.29050.215000.000000.206150...0.000000.00000.00000.0000000.000000.219050.00000.00000.0000000.0000
3.10.00000.000000.00000.26860.221800.0000000.00000.000000.000000.284100...0.212900.00000.00000.0000000.251000.209200.00000.25010.0000000.0000
3.20.18400.000000.00000.00000.000000.1865000.00000.286100.000000.000000...0.275500.26440.23160.2448750.000000.000000.23790.18670.0000000.0000
3.30.20640.000000.22580.18070.000000.0000000.21890.000000.000000.000000...0.000000.17910.00000.0000000.257100.000000.00000.00000.0000000.0000
3.40.23300.000000.00000.17830.000000.1852000.00000.214600.233100.194200...0.000000.00000.00000.1979000.000000.000000.00000.24360.0000000.0000
3.50.20060.000000.29010.15540.000000.2073000.00000.000000.000000.198233...0.000000.17810.00000.0000000.000000.000000.27660.00000.0000000.0000
3.60.00000.000000.00000.00000.000000.0000000.00000.000000.000000.211900...0.240200.00000.21310.2597000.000000.000000.00000.00000.2513330.0000
3.70.00000.000000.00000.00000.000000.0000000.00000.000000.000000.000000...0.236750.00000.25130.2581000.000000.000000.00000.00000.0000000.0000
3.80.00000.192650.21500.00000.219800.2296000.00000.245800.198600.000000...0.186550.00000.00000.2002000.000000.263200.17650.00000.1329000.0000
3.90.00000.000000.00000.24000.136200.2329000.00000.205700.254800.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
4.00.00000.000000.00000.00000.000000.0000000.00000.211300.000000.000000...0.000000.27150.00000.0000000.000000.000000.14760.00000.0000000.2502
4.10.00000.000000.00000.00000.054400.0000000.00000.291400.000000.000000...0.000000.00000.00000.0000000.248000.246800.00000.00000.1724000.0000
4.20.00000.000000.00000.00000.000000.0000000.00000.156700.000000.000000...0.000000.00000.20350.0000000.000000.000000.20140.00000.0000000.0000
4.30.00000.000000.00000.13660.000000.0000000.00000.000000.000000.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
4.40.00000.199000.00000.00000.000000.0000000.00000.000000.000000.000000...0.000000.00000.00000.0000000.213450.000000.00000.00000.0000000.0000
4.50.00000.000000.00000.00000.000000.0000000.00000.000000.000000.000000...0.000000.00000.00000.2523000.000000.000000.00000.00000.0000000.0000
4.60.00000.000000.07030.00000.000000.0000000.00000.000000.000000.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
4.70.00000.000000.00000.00000.000000.0000000.00000.000000.000000.129900...0.000000.00000.17990.0000000.252100.000000.00000.00000.1470000.0000
4.80.00000.000000.00000.00000.000000.0000000.00000.000000.000000.131500...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
4.90.00000.000000.00000.00000.000000.0000000.00000.000000.000000.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
5.00.00000.000000.00000.00000.000000.0000000.00000.000000.000000.000000...0.000000.00000.00000.0000000.000000.000000.00000.00000.0000000.0000
\n", + "

35 rows × 181 columns

\n", + "
" + ], + "text/plain": [ + "phi -90.0 -89.0 -88.0 -87.0 -86.0 -85.0 -84.0 -83.0 \\\n", + "eta \n", + "1.6 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "1.7 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.2665 0.00000 \n", + "1.8 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "1.9 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "2.0 0.0000 0.00000 0.0000 0.0000 0.00000 0.190000 0.0000 0.15225 \n", + "2.1 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "2.2 0.1476 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.16535 \n", + "2.3 0.0000 0.14670 0.0000 0.4424 0.41310 0.000000 0.0000 0.00000 \n", + "2.4 0.3874 0.00000 0.0000 0.0000 0.44120 0.177833 0.0000 0.00000 \n", + "2.5 0.0000 0.00000 0.4867 0.0000 0.00000 0.000000 0.0000 0.23790 \n", + "2.6 0.2099 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.19280 \n", + "2.7 0.0000 0.28710 0.0000 0.3849 0.44150 0.000000 0.0000 0.00000 \n", + "2.8 0.0000 0.33440 0.0000 0.0000 0.00000 0.000000 0.0000 0.22370 \n", + "2.9 0.0000 0.00000 0.0000 0.0000 0.23950 0.000000 0.0000 0.00000 \n", + "3.0 0.0000 0.20190 0.0000 0.0000 0.24475 0.284300 0.2905 0.21500 \n", + "3.1 0.0000 0.00000 0.0000 0.2686 0.22180 0.000000 0.0000 0.00000 \n", + "3.2 0.1840 0.00000 0.0000 0.0000 0.00000 0.186500 0.0000 0.28610 \n", + "3.3 0.2064 0.00000 0.2258 0.1807 0.00000 0.000000 0.2189 0.00000 \n", + "3.4 0.2330 0.00000 0.0000 0.1783 0.00000 0.185200 0.0000 0.21460 \n", + "3.5 0.2006 0.00000 0.2901 0.1554 0.00000 0.207300 0.0000 0.00000 \n", + "3.6 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "3.7 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "3.8 0.0000 0.19265 0.2150 0.0000 0.21980 0.229600 0.0000 0.24580 \n", + "3.9 0.0000 0.00000 0.0000 0.2400 0.13620 0.232900 0.0000 0.20570 \n", + "4.0 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.21130 \n", + "4.1 0.0000 0.00000 0.0000 0.0000 0.05440 0.000000 0.0000 0.29140 \n", + "4.2 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.15670 \n", + "4.3 0.0000 0.00000 0.0000 0.1366 0.00000 0.000000 0.0000 0.00000 \n", + "4.4 0.0000 0.19900 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "4.5 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "4.6 0.0000 0.00000 0.0703 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "4.7 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "4.8 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "4.9 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "5.0 0.0000 0.00000 0.0000 0.0000 0.00000 0.000000 0.0000 0.00000 \n", + "\n", + "phi -82.0 -81.0 ... 81.0 82.0 83.0 84.0 85.0 \\\n", + "eta ... \n", + "1.6 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "1.7 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "1.8 0.00000 0.128900 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "1.9 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "2.0 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "2.1 0.00000 0.182700 ... 0.17675 0.0000 0.0000 0.000000 0.00000 \n", + "2.2 0.00000 0.000000 ... 0.00000 0.0000 0.1840 0.000000 0.19650 \n", + "2.3 0.15890 0.000000 ... 0.00000 0.1936 0.0000 0.000000 0.00000 \n", + "2.4 0.17295 0.000000 ... 0.19680 0.1581 0.0000 0.000000 0.00000 \n", + "2.5 0.00000 0.200300 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "2.6 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.179400 0.00000 \n", + "2.7 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "2.8 0.00000 0.000000 ... 0.00000 0.0000 0.1998 0.000000 0.00000 \n", + "2.9 0.00000 0.252150 ... 0.00000 0.0000 0.0000 0.229800 0.00000 \n", + "3.0 0.00000 0.206150 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "3.1 0.00000 0.284100 ... 0.21290 0.0000 0.0000 0.000000 0.25100 \n", + "3.2 0.00000 0.000000 ... 0.27550 0.2644 0.2316 0.244875 0.00000 \n", + "3.3 0.00000 0.000000 ... 0.00000 0.1791 0.0000 0.000000 0.25710 \n", + "3.4 0.23310 0.194200 ... 0.00000 0.0000 0.0000 0.197900 0.00000 \n", + "3.5 0.00000 0.198233 ... 0.00000 0.1781 0.0000 0.000000 0.00000 \n", + "3.6 0.00000 0.211900 ... 0.24020 0.0000 0.2131 0.259700 0.00000 \n", + "3.7 0.00000 0.000000 ... 0.23675 0.0000 0.2513 0.258100 0.00000 \n", + "3.8 0.19860 0.000000 ... 0.18655 0.0000 0.0000 0.200200 0.00000 \n", + "3.9 0.25480 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "4.0 0.00000 0.000000 ... 0.00000 0.2715 0.0000 0.000000 0.00000 \n", + "4.1 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.24800 \n", + "4.2 0.00000 0.000000 ... 0.00000 0.0000 0.2035 0.000000 0.00000 \n", + "4.3 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "4.4 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.21345 \n", + "4.5 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.252300 0.00000 \n", + "4.6 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "4.7 0.00000 0.129900 ... 0.00000 0.0000 0.1799 0.000000 0.25210 \n", + "4.8 0.00000 0.131500 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "4.9 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "5.0 0.00000 0.000000 ... 0.00000 0.0000 0.0000 0.000000 0.00000 \n", + "\n", + "phi 86.0 87.0 88.0 89.0 90.0 \n", + "eta \n", + "1.6 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "1.7 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "1.8 0.00000 0.0000 0.4475 0.000000 0.0000 \n", + "1.9 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "2.0 0.29905 0.0000 0.0000 0.000000 0.0000 \n", + "2.1 0.29705 0.0000 0.2422 0.000000 0.0000 \n", + "2.2 0.00000 0.0000 0.2567 0.553100 0.0000 \n", + "2.3 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "2.4 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "2.5 0.00000 0.0000 0.5598 0.000000 0.0000 \n", + "2.6 0.00000 0.3756 0.0000 0.000000 0.0000 \n", + "2.7 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "2.8 0.00000 0.3815 0.0000 0.509833 0.0000 \n", + "2.9 0.00000 0.2174 0.0000 0.173300 0.5137 \n", + "3.0 0.21905 0.0000 0.0000 0.000000 0.0000 \n", + "3.1 0.20920 0.0000 0.2501 0.000000 0.0000 \n", + "3.2 0.00000 0.2379 0.1867 0.000000 0.0000 \n", + "3.3 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "3.4 0.00000 0.0000 0.2436 0.000000 0.0000 \n", + "3.5 0.00000 0.2766 0.0000 0.000000 0.0000 \n", + "3.6 0.00000 0.0000 0.0000 0.251333 0.0000 \n", + "3.7 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "3.8 0.26320 0.1765 0.0000 0.132900 0.0000 \n", + "3.9 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "4.0 0.00000 0.1476 0.0000 0.000000 0.2502 \n", + "4.1 0.24680 0.0000 0.0000 0.172400 0.0000 \n", + "4.2 0.00000 0.2014 0.0000 0.000000 0.0000 \n", + "4.3 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "4.4 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "4.5 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "4.6 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "4.7 0.00000 0.0000 0.0000 0.147000 0.0000 \n", + "4.8 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "4.9 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "5.0 0.00000 0.0000 0.0000 0.000000 0.0000 \n", + "\n", + "[35 rows x 181 columns]" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_pivoted" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAg8AAAHLCAYAAABPtHudAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAABgw0lEQVR4nO3deXgb1aE28Fd2EgeyyU4I+yY1QEOBIoVAKWWLVMoFCgU7KYUCLY1FYwqU8lmkl4sTPoqRH6DQJoDs0gIfLQ0WBUp7KUjQsrSFJBL7mkpJ2JdEVjaIk9j6/jg5I400I83II1uy3t/z+Ikyc2Z0NOvRmZlXtnQ6nQYRERGRQXUjXQEiIiKqLmw8EBERkSlsPBAREZEpbDwQERGRKWw8EBERkSlsPBAREZEpbDwQERGRKWw8EBERkSlsPBAREZEpbDwQUVVKJBIjXQWimsXGA5FFEokEuru7kUqlRroqNaGlpYXLmmiEsPFAFS0UCsHtdsNms8Fms8HpdKKrq6vgNJFIBC0tLco0jY2N8Pv9yokmlUrB7/ejsbFRKePz+RCLxfLmFYvF4PP54Ha70djYCLfbjZaWFvj9fnR3d6OlpQUA0NXVBafTCZ/Ph2QyaeozRiIROJ1OpS5utxuhUKjgsnC73YjFYnnLR9ZR/mXPNxKJlLxMters9XrhdDqV92lpaVHeo9xisRgcDgfsdjsA0XDz+/2q5ZD9mbKXcWNj47DVk2jUShNVAQBpAOloNGp4GofDkQaQDgaDmuMDgUAaQNrlcuWN6+vrSzc3N6cBpFtbW9PxeFwZF4/H0x6PJw0g7fF4lOGyfHZZo/r6+pTPqFffdDqdDgaDabvdnjdcTqv33i6XKx0OhzWnMbNM0+l0urW1NQ0g3dvbm1e33GVSLq2trXmfJ53OrIPm5mbNcVrrmojMY88DVRX5TdNM2aamJtPj58yZg1AohGAwiGAwCIfDoYxzOBwIh8Nobm5W9TLovY/Rura3twMAent7dctFo1EsXLjQ9PwLTWNmmXq9XnR3dyMajaK5uVk1rrW1FeFwWOmVKKdIJAKPx5M3XH7O3J6FUCiEWCyGaDRa1noR1Qo2Hohy+P1+xGIxuFwutLa26pbr6emx9H2zT3xal1AA4IEHHihYJz3Nzc2aJ1szQqGQctJ2uVyaZeS4SCSieenFCqFQSPezuFwuuFwupFIppQERi8Xg9/sRDofLUh+iWsTGA1EOea282Dd8u92uWSaVSsHn86GxsRGNjY3w+XyG3tdutyvf5js7O/PGy5OmmZ4COZ0VNxb6/X4AUO7z0DNv3jxVeastW7as4DKV44LBIFKpFFpaWtDb26vqPSKioWHjgShL9jd+vW/X2XK77oHMSTMQCMDhcKC7u9twN34gEACgfcLv7Ow03BDJnc4K8tHIYidhOb7Qo5SyNyC3cdXS0oLGxkbdaVOpFBKJRMF1M3fuXABiGc6ZMweBQMDQuiQiE0b6pgsiI1DkhkAtLpcrDSBtt9s1/+Q8s2/w6+3tVYabpXcjobxxU+sGPy3yZsz29nZlWDwe17xRUpJ1djgcqj85vK+vT3caI8s0Go0aLm+mrPys6XTmJshiN4wGAoGi9S104yQRDR17HmjU6+npQV9fX95fMBgsOF2pXf2533LlN2uj19xlz0V3d7cyLBAIGLpRMhwOIx6Pq/6Gu7s++7JKsWUoL4H4fD74/X54PJ6C93QEg0FD93zIz6x374h8z66uLvj9/rLdn0E0WrHxQJQl+0RrVYKhvLnP6Pw8Hg8cDgdSqZTSgCj1RkmHw1HSpY5c2Q2iYp8je3yxhotcNna7vWjZRCKBpqamovd8yBs7HQ4HEomEZgOipaVFecIlEAigs7OT2Q9EJrDxQJQl+yS5cuVKS+YpT3ZmegCy75sIhUKYNWuW6Rslpfb29pKnzWbkXgYg820/O8RpqPMERK9DsYaQvJfiySefVN04mS2RSCAUCqnmNW/ePOV+EyIqjo0HGjVisVjBbmqj5Df8QnkLZsiu+6OOOspUHex2OxKJBObPn29J70EsFjPdm5K9TOXJtdhyWbZsmap8IX6/Hy6Xy9B6C4VCmjeoStlPVtjtdmU9Zl/+AdSNG0k+Xsq4ayJj2HigUcPv91tyfT8QCMButyMSieSdeLLJRzKLkV3ohU58WrLvcTA7rZb58+ebDrLKXqbNzc3KSVbvZC/DmDweT9E6h0IheL1e+Hw+JBIJpWGj1cDRC4XKNmfOHASDQaX3KPvR1+x7GlasWJHXIyKXi9locaJaxcYDVRWtE0sikYDX60UymVSdFGRZvROC/JaZO0+73Y5oNAqPxwOfz4eWlhZVGXkvgvyNi+zpcueXSCQQDAZL6sWQ35zN3Oug9c1ZLp9UKqV5GcHMMo1Go2htbVUSOLOFQiG0tLSgtbVV9/MmEgl0dXUhFAohmUzC4/EojYJgMIiuri7NBk6xSxZerxcOhyOvgSEfkc1+XDWVSuk2ovhLnUQGjfTjHkSF9Pb2Ko/zyT+Xy5V2uVyqRxGR9WhjOBxWHtXDzkc1A4GA8rhiX19fur29XfW4Zmtrq+ZvPMj3l2UdDkfa4/FoPk4o5+vxeNIejyfd2tqabm1t1XxM0qjc39Uws3xyl1Fra2vJyzRXOBxOezyetMPhUKZrbm4u+jhqb29v2m635823ubk5bbfbdX9nw+Fw6NZD1tnhcKgek+3t7VUe18XOxzbD4XA6EAjkPfYqHy8t5XdJiGqRLZ1Op4eroVKqRCLBdDiiGiV/5lz+9sdQyR6S7EOf/D2OKjgcElWEirxsIX9WV/4Vi8MlotHLaLaDUfKeiOxLFPK3TIiqRSwWUy6d+nw+Q1klXq837/wq/8w+qjym1IqXS3d3N1pbW+F0OpVhQ/1BHyKqTkazHcyQN6+GQiGlN2PZsmV8VJOqRiKRgNvtRjQaVRq9TqcTyWRSt6Etb0qWN4RL8XgcXV1dps+zFXfZwuv18tfviAiAeNrjqKOOsuRpk1w+nw9OpxPr16+H0+m0tHeDqJzkjcDZ58ru7m74fD7dS2/d3d2YO3duXkO8q6sL4XDY9Hm3onoeQqEQVq5ciZaWFni9Xu7MRDVOflMqh2Lx5ESVSP7cfO5+MWvWLACZ3vtceufTYr9Sq6ei7nkIh8NIpVJK+ltjYyMjY4lqmFVBXUSjhUy+zX2IQF6+MNODkEqlEIvFlF+iNaOieh6CwSCCwSBisRiCwaDyU8aFftynv78f/f39Q3rfhoYGNDQ0DGkeRERUXtV0vC9XXeWNvnr3AZnJKnnggQfgcrlKuqeoohoPksvlQjAYhNfrVe4m1fsGcsr4TjyNxUN6vxPQgZOwCACwHEsxG21Dmp+WaprvDvTjWXTiG1iIMbB2JzNT3+sfFuFOx/xtIgDAc+c4S+Zrhpzv0+teBwCcMO1QS+b7+2N+hb1n/hgn/nasJfPLXWfLFn8BAJjXsQsAIHbGAADA9Wi96XlX07ZbbfOtlH1N+sb6WwEAz069wtL5GmFkvn/H0I/3HR0dWLRo0ZDmUZTNhk5giDXVrms8HgcA3aAzMxHrvb29mDdvXkl1q8jGg9Tc3Izm5uaCufffwEJ8DVcO6X2yd9pqOvCUa7470I+nsRhfw5UVcUAbjfP94K07sPfMH1s2P66z6pwv15u5+ZZyvO/GUWjFCuX/CxcOTy/zQmCIZyagISuiXpJPIuol5xrNRJL3TpR6709JjYeXXnoJnZ2dSKVScLlccDqdmDVrFr761a+WVIlCvF5vwfsexqDB8p2OiIgqTynH+zrUYzwmK/8flivU9XVoAIZ+ZtKorGwc6PUwGG08yN/cKTWA0XTjYfXq1XC5XLDZbEin0wiHw7DZbMp4u92OWbNmqRoV2ZWbPHmy1mwLkneREhERVbx6W/EyJZLnw9x7G+T/3W63ofksW7ZsSI9Am248yF6Ac845Bz6fD6lUCitWrEAikVB+8lc+M5rdqADEDZE/+tGPTL1fOBy25OeIiYiIhkV9+R5ktNvtcLlcCIfDqsh2eW42+uREKBRCNBotuR6mGw+NjY2w2Wz4zW9+o/QinHPOOaoyq1evRiwWUxoVskVU6OeAY7EY5s+fj3nz5ikLJBQKoampqSwBMURERNWop6cHbrdb9btPgUBAlR4pfxk3GAzmpUeGQiGlEVIq042H5uZmTJkyBatXr8YRRxyhWebAAw/EgQcemNeoKMThcKCpqQmdnZ0Ih8NwuVzKByciIqoaY8p32QIQTyRGo1H4/X44HA4kEgn4/X5VEFQqlUIymdS8N2LZsmUlZTtkK+mGySeffBI33HADli1bNqQ3z2a32xlLTURE1a+Mly0kl8tVMETN5XKhr69Pc5wV4WslfcJoNIpYLIbvfve7+NOf/oSXXnppyBWpFOV4BKka51su1bYcyjXfvQ+x7jHNcqu2ZVtt8y2XalsO1TbfWldSz4PsGonH46oWjHzsw+Vy4aijjsLZZ59tTS2HUbVtwNW2Y1Tbcihb48HCjIdyq7ZlW23zLZdqWw7VNt+Cyvi0RaUoOSTK7/dj1qxZSCQSiMfjWLFiBV588UXE43GEw2E0NjZWZeOBiIhoSIbhssVIK+knua+++mrMnj1bs3GwYcMGrFy5EolEAvPnz7ekkoUsHoEGXveL7wMAWo/cBwDwjx9uBwBDUcNPfvoGAGDO9JnKMDPTD4et2IgbMQXOaz/C96/boyzvcdvdGwEAl19UPPfjT/+9FQAwbqtY2affXDmhYPH+55XXzoZjRqwecp1djQ2qQBwzRmo7vOX3KeX1lefZh/W9c/fl4SbX2yzfZzg9OC1v/MMLxbZ/Vuf44a7aqNVh+oxXgt0nGiq29PPtWPrFdt3xbbf9Gm1tldnjVVLPw4033ogHH3wQN910E6666irVuClTpmDOnDmYM2eOJRUkIiKqKgZ7HtomNaBtUoEvQxXacACGcNnCzGOYRERENaMG7nkY/RdmiIiIyFIV/auaREREVacGbphk44GIiMhKNXDZgo0HyjMGDWg6+eewjamcpxqosDFowAno4M/TV5kxaMDes69BXT3X26gyhj0PVIPGoAHTPP890tUgE8agASdh0UhXg0wagwbse/T/jHQ1iExj44GIiMhKvGxBREREptTADZMlJUxWktNsS7EcS3XHz0abqWzzu2/ZAgC46MoJRcsuW7UaADBvxoEAgAfiCWXcXKfD8HtKwds3AwB8C4ylk40EmfYIAGf/YnhS7+R7Gnm//72iHwDwX7cav4Z8Z/QDAMAl7r1LqF2+e15/FwDw+ef1AIAfH2XNfMtlpFMWh+qOFWL9VeJyfqRdbI9ndllzT8PffrINAPCtX48b0nyKpYkuWf6h8vrS2Xupxr32+UoAwFd2nTWkOpTLchQ+Jyxa0lb+1MbDdjdUbOn6z7E0+YXu+LabbxtdCZOVxGzjgIiIRq9i54RhORcbTZicPhFt0wt8WazQhgMwChoPREREFaUG7nkY/RdmiIiIyFLseSAiIrJSDdwwycYDERGRlXjZgoiIiEiNPQ9ERERW4mULIiIiMqUGLluw8UBERGSlGuh5GP2fkIiIiCxV9fHUiy3uHbrnJhFPfeFVxeOppd+9KuKIf3DYfkXLvrw5CgA4YqK7hNoBT376BgBgzvSZJU2v5c/vrVJef3vfGSXPR8ZI1w2K/5/VWTxO+pbfpwAAV55nV4b94YbPAQDf+/mumtMsWyziXOd17FJiTWk43fjUpwCAq0+eXvI8lm98CQAwe/JXlWFL7toIALj04skAgHvfWAsAuGDm/iW/j9UebxNx0vGv9ivDFsyfVPL8fvNrEWH/o59UboR9OV332DoAwLWnTgMAPP7RWwCAU/Y8RHea23s2Acgs947hOON5nYaKLX1vA5a+v1F3fFvgl4ynJiIiqglG46kPaETbAY0FClRmwwHgZQsiIiIyiT0PREREVqqBGybZeCAiIrJSDTyqOfqbR0RERGQp9jwQERFZiZctiIiIyBRetiAiIiJSY88DERGRlWrgskXVJ0yeZluK5ViqGrZ1Z/ja+M3AbLRhNqwJ2rj/ndUAgHMPOtCS+VnpwUQcAHCOw1iymVEbByMAgMl1Hkvml5sKWO1e2PCy8vroKUeoxj0QTwAA5jodlrxXKcmat967AQBwxQVTLKmDkUQ/K6w8awAAMOvhegDA4kfXAwA6zpiqlHl4oUg0NZJkmuu3t4mkxh9ePrSkxs7wZwCAhd7dNMffFxBpqef7M2mpf7xerMfvXlN6QmroWvHZXzt6szJs0WnTSp6fEY99+DYA4NS9Di7r+wzVcuSfE7ItWtJW/tTG7x1uqNjSd9Zj6ar1uuPbbriZCZPlotU4iJ0kDjyuR+tHokpERDRCin1hHJZzsdGEyS/vhrYvazc8RYHKbDgAvOeBiIiITKr6ngciIqKKUgNPW7DxQEREZKUauGGSjQciIqIqE4vF0NnZCYfDgVQqBa/Xi+bmZlPzSCQSCIVCAIDW1lbY7XbD07LxQEREZKUyX7ZIJBJwu92IRqNwuVwAAKfTiWQyidbWVkPT+/1+pFIpBINBOBzmnwgb/X0rREREw6m+zpo/HT6fDx6PR2k4AIDf74fP5ytatVgsBrfbjaamJoTD4ZIaDgAbD0RERFUjlUohEonA6/Wqhs+aNQsA0N3dXXDaOXPmwOFwIBgMDqkebDwQERFZqYw9DytXrgSAvB4D2QsRDod1qyUvVQQCgSF/RDYeiIiIrFRnQ386jY07Bob019/fnzfrREIk1+rd3CjHa5G9EuFwGG63G42NjfB6vQWn0VP18dSLy/w47S+f+1h5PeMAEa18+j4HlTw/GWecG2VcaSYMPgQA2FL3Hd0yj6xdBQA4c/8ZRednRSRvKW74UxIAcEg0Ew989i/Mxxnr+d8rMjv3f93aYHr697c/BwDYZ+xxquE3PvUpAODqk6cPoXb5/vTfItbYzDJY9Nd1yusvvSaWY3bcspXk/vbT4/YwPe3Nz3wCAJgwYQcA4BL33sq4G0N9AICrmxsNz2/1tn8DAA4c9zXTdbGKXB5b1o0DAFxzVpNu2esfTqrK5Mbp3xn9QCmbvWyKufeNtQCAC2burzm+lNh+uX0DQP8WkQScHT1ezFBi0juG44z3069j0b/fxeIX3h/SbDo6OrBo0SLVML/fj66uLtXNkpLNZoPD4UA8Hs+bl7zXweVyobe3Fw6HA4lEQmk89PX18WkLIiKikbTwqH1wpWuvIc2jYeHCvGFOp/j9omQyqTmN3g2QsnfB5/MpZeS9D16vF52dnaYuZ7DxQEREZKV6Gxrq69GAIf6+UkN+b6Y88adSKc1J9BoPer0KHo/40UOzly7YeCAiIrJSGRMm5VMVuSd7+X+3211wOq1LGgDQ1KR/SUwLb5gkIiKqEna7HS6XK++pikgkAgCYO3eu7nQej0cpJ8keDL1Ghx42HoiIiKxUb7PmT0dPTw8ikYiq9yEQCCAQCCiXJxKJBJxOp6qxEAgEEIvFVMO6u7vhcrkMJVNm42ULIiIiK9WV93u5y+VCNBqF3+9Xnprw+/2qBkAqlUIymVTdG5E9XW9vL+x2O1KpFKLRqOk6sPFARERUZeQjl4XG9/X1aQ4vFCRlFBsPREREVirzD2NVAjYeiIiIrFTGpy0qRdUnTJ5mW4rlWAoASB4gkuWa1mTaRLPRhtloK3n+d738nvL64iP21SzzxkmDAICZf9ffYHLT37TcfcsWAMBFV04wXU+rExzve2sNAOD8Qw5QDV+2arXy+r2VIq3vqnPtqjJ9g38HAHy2LZNCeND4o03X4c47NwEA6o7eAABoPXIf3bKlpNxJA+nHAAD1tlMNT3Pb3SJt9PKLJpt+v0LuuUlsAxdepb8NfPhlscvu9Wbxbze3/usjAMAVx+6pGi6TNwHg52cbf0RryfIPAQCXzt5LVd8p68Xz7Gd1ZpIrI5dsAwB47hxneP567lgh0hF/fJTxZMShuuf1dwEAFx66HwDg5c3iuvARE83dlW4Fub7MrCvpueSrAIDjmg5Thv3tJ2LdfOvX2utGfnYg8/l/96oY9oPD9jNdh3KRx+fsY/NyZM4JWhYtaUNbW+nnBEOu8xgqtvSF97B0hX4KZVtHV/nrWqKq73nIbhzc+gdxoLw050BJRES1odgXxmE5Fxu8bNF27H5oO7ZAY6xCGw7AKGg8EBERVZQyP21RCdh4ICIislIN3DA5+ptHREREZCn2PBAREVmpBp62YOOBiIjISnW8bEFERESkwp4HIiIiK/GyBREREZnCyxZEREREalUfT724QAPvt7dtBgD88PKJlrzXQ2v+AwBY+6GIDs6N/B0qGcG7aYvoEGo/cfe8MjIe+st7rQcAHD5hlmp86NqtAIDm68Yj16K/rhP/njataF26/vEJAODb1+4GAFj9x1UAgLfXZOKYrfz8t/dsUl4vmD9JNe6Xz30MAPjpcXtY9n5GPfbh2wCAU/c6uGhZve3tlVMGAACHP16vDJOfd9rJnwEA5jodAIAH4gnV/wuRscPPRsVyWejdreg0pbjxqU+V11efPH3I89OLzLaaXJYAMHWS2C/mTJ9p6Xus3fYvAMD+4461bJ5HbA4qr1+e6FONu+4xsQ9fe2rxfdiMG0Pi1xevbhaR8xe+/nNl3D2H3qA5zRMfvwkA+OYeXy46/z+/J44f3953xpDqaYWO4Tjj3XGWoWJLn05g6dOrdce3XXMj46mJiIhqgsHLFm0nOdF2klO/gK8yGw4AL1sQERGRSex5ICIishKftiAiIiJTauBpCzYeiIiIrFQDPQ+j/xMSERGRpdjzQEREZCVetiAiIiJTeNmCiIiISI09D0RERFaqgcsWVR9PfZptKZZjqe742WjDbOindN3y+xQA4Mrz7Krh/+57BQDwtcbDlWF3RkV89CXuvVVl//L+OwCAwXRmgzETw3rfW2sAAOcfcoBq+O9efRcA8IPD9lOG3XS/qO9V56rra4ScX+MfRMTwWZ35EdbDRUYrH9d02LC83zPrX1NeHz/1KwCADoj1tRhiF/jPMYMAgOQTryhln1q5FwD9WOYHE3Hl9Zh6Mf2Z+4t1H7lkGwDAc+e4oX+AYSQj0Nf/Q0Qg58aFm6W1HQPAPTdtAQBceNUEZdjyjS8BAGZP/mrJ72dkHjJ+XSsCXpJx8T8+Sr2/P/7RW8rrU/Y8pMRaAu9u/ycAYL+xX9ctsy39NwDAONu3is5vuGK/h2LxoyJWv+OMqcqwR9aK6Gq53xSyZPmHAIBLZ++lOf5Xz3+EraHfYWvobjSt0f5uvGhJW/kjnx8431CxpY+/jaWPv6M7vm3hDYynLpdijQMiIqod45t/gPHNP8Clx2g3oirpXNx2ysFoO6XA7+bMraDK5qj6xgMREVFFqR/9ly3YeCAiIrJS3eh/FmH0f0IiIiKyFHseiIiIrFQDT1uw8UBERGQl3vNAREREpvCeByIiIiI19jwQERFZaNCiex4q+dt91SdMLjawjt75ukj+O+if+avitc9XAgC+sussS+tlhSc+fhMA8M09vjxs7ykTN6Xc5E0zHvvwbeV1625iOb839jzNsn2Df1deN9adVPJ75s5Pzkum2AHFk+zkcgeAbTvqAQCn73OQqoxWUt6vnhcJfwM7xEb50+P2KKnuRnWGPwMALPTuVrTsQ2v+AwD4+slOAMD0hPGDm0xQBTLLoVjSH5BJlpyw6w4AwFynw/B7PvnpGwCAOdNnFi0r65JcL5I8rz1VJGO+sOFlpczRU44w/N43PvUpAKCuThwac1Mos1NFz3E41XW5ayMA4NKLJwPQT9fMNnXgAQDA+vq5hutoxO09mwAMPSG0GK00XunWezcAAK64YErR+egl7RaSvW0C+fspkL+vdgzDGW/HE62Gyt3+59dx56Nv6I5va7+eCZNERESUseDbh2LBtw/VHT/mm5XZcADYeCAiIrKUVZctKhkbD0RERBYaqK/kuxWsMfo/IREREelKJBKmp6noxkMkEkFjY+NIV4OIiMiwwTqbJX+FxGIxtLS0wO/3w+fzIRQKGa6fzWZT/bW0tJj+jBV92cLn8410FYiIiExJlzkkKpFIwO12IxqNwuVyAQCcTieSySRaWws/6dHd3Y3W1lY4nZknhTwej+k6VGzjwe/3w+FwIJlMjnRViIiIKobP54PH41EaDgCUHohijYfe3l6Ew+Eh16EiL1tEIhFMnTpVtWCIiIiqQTkvW6RSKUQiEXi9XtXwWbNEVlF3d7duvUKhEFauXImWlpaC5YyoyMZDMBhEe3v7SFeDiIjItHI2HlauFIF7Doc6dE1+2S7UqxAOh5FKpRAKheDz+dDY2IhIJFLSZ6y4yxZ+vx+BQMBw+R3oxw70FyyzfYdImNyq0VbavnEz6hrGmaskERENu9zj/cCmzarxW7Exb5r055t2jhsLAOjvb0BDQ0MZawkM1tWhf9sO9G8fGNJ8dunvz6urfDLCbrdrTlPoyYlgMIhgMIhYLIZgMIju7m54vV7E4/G8xkgxFdV4iMVimDp1qqkP8Sw68TQWFy70QoFxewATfT/FEThWNfiul98DAFx8xL7KsF8+9zGA0mKHl61aDQCYN+NAw9O8/h/xpMk3TbzPn98TMczf3rdwBDMA3Bn9AABwiXtvZdjcua8BAPYZexwA4Kb7UwCAq861m6iFcOpeByuv34N4rRe5Pd623fT8731jrfL6gpn7q8bJWOqn170OADhzmn6K283PfAIA+Nnxu+fV7brH1gEATs+ZJjuWWrrsmD0BZOJw3/xiBQBg4zbRONWKSJbb2UerJwAAZq7YFQBw9i/G69b3jZNEY9hILLX0nQO+pPr//e+sVl6fe5DYJl/cFAMAHDlJfblw+478RvdujeoGu4x0duyfOZj/oEgctVYcsTJsZyz1I+3ifc7sEgfQ7HU+YbyIvb40JyL6X+eK4ceaiKTOdvXJ01X/f2WL+KZ3+ATRLZwbSQ0Ai/4qtpNFp01TDS8US+3svwcAEK+/sKR6Apn9Hcjf583EUn89+SsAwD+bLjM8zY2hPgDA1TtjqbX2RyOx1JJeLLWMvwaArY1/Uh/vc5L7X9Sawbyd9d3534bODixatMhwvUp16z0r0XVXoZNPcR0du+fVNR4X8ehNTU2a06RSqaLzdblcCAaD8Hq9yhMbvb29pupWUY2Hzs5O0x/gG1iIr+HKkt/z7mc/gG3cOCBY8iyIiGgYFDve/+ZXm5TXP7pM3XgKvy0aWgv3/0p5KpdlsM6Gy35wFC45b2j37e117MK8YfIpCb2HCcx8+W5ubkZzczNisZjpulVM48Hv98Pr9aq6XORr+a/WQhmDBoxB6V1QdRPzu7mIiKjyFDve1+2SuU9gPNSNhzGTJgJA2S9ZAMCArQ5jGsZhzBDfSquu8jyo18Ng9vKD1+st6b6Himk8RCIRdHV1aY5zOp1wuVyIRqPDXCsiIqLKIZ+qyL23Qf7f7XaXPE8zKuZpi2g0inQ6rfprb2+H3W5HOp1mw4GIiKpCOZ+2sNvtcLlceU9VyN6DuXPN/bR7OBwuKZCxYhoPREREo0G546l7enoQiURUvQ+BQACBQEB5CiORSMDpdCqNilgsBrfbrerhD4VCaGpqQnNzs+nPWDGXLYiIiKg4eRlfJjEnEgn4/X5VumQqlUIymVTujXA4HGhqakJnZyfC4TBcLhe8Xi+CwdKeFqjoxoNsSREREVWLcv+2BSAaEIWeTnS5XOjr61P+b7fbLYmlliq68UBERFRtiv0i5mjAex6IiIjIFFs6nU6PdCWGYnGBBt5Da/4DAOh7RCRCTjxdpODNzUq+u2OFSFl07ivyHnKTDwvp+odIJqzf2QSTCYUj4fm5IlVv7F2vAgDck47MK6OVKKknuulF3flIMqVQJhS+coqIYh0IvQxAnVR4670bAABXff8ZAMDjn4mgk+gbIqmx/cTiy27K4IMAgA115+SNeyAubhw6Zr+PAAD7jf160flJHeeKhLzF97+SNy43EVMmKeamEBrx2ucrldd7jxdhNjIJM5dMnmyakklyzE2JNPSeHpFG+eF9bwMwt32bIVM1tZI39Tz2oajT1m31yjC9zyiTQk/QSAqV+/l7H4uUTpn0qeWe198FAFx4qH7yYzk8+ekbyuuX3hLLyMzx4u2tywEAH24SWQWr3p8MAGg9ch+lzKGf/wYA8PquPwKQ2SfmFkj6lMtj3Fix78p9uQOZA+t5XxfjDvqn+rvmgwmRdKiVuHnrv8R+eMWx6nVhpE7l1jEMZ7w1b/zcULl7/xDF/7tf/0nCK65cjLa2NquqZSletiAiIrLQoM3YZYvzz5uF88/Tz1hwfLkyGw4AGw9ERESW4j0PRERERDnY80BERGShwWF4VHOksfFARERkoQGD9zxUs9HfPCIiIiJLseeBiIjIQrxsQURERKakedmCiIiISI09D0RERBaqhZyHqo+nPs22FMuxFACQ3F9ENNfVi49kT4zFbLThzdfPAJAfwQoAf35vFQAg8Z6Ifc2NU5WRzkAm1lnGMn+WHA8ASL8lYnEvv2iyUraUuN5cMnY3O7J3+caXAACzJ3/V8Hx+96qIoN2tcSsA4PR9DlKNl/MsNF8z7/viphgAdTx1Lhlf+43DPgagHYP9wgYRc330lCMAAHtv/wMAYLtNdJgF388ks5mJbr7l9ykAwIbzGgEAi6HeBWRkL1A8xvj6xz9TXl9zym6G62DUslWrldfzZojttlAssNT94vsA1PHFAHD9w0kAwKwnJyrDvvXrcaoyS5Z/CAC4dPZeAICbn/lEGScjlZ9Lihj01x44AABw4h/EPnDIM/qdmfKzyM8hyYh4APjxUcWj04ciN6L9hj+J5fHzs5v0p7lTRIlfcsmkovP/17niGLTPvS8AKByTLuPKH1+5LwDtuOpXtogyh0/QTyGsRPLYNX6cOOZOnfgFAGDTVrGtzZk+U3fav38morxfeHUaAO0o+F89L44fMopcxpf//YXdgb/cBfzlt5j2nog937C7iGif8onYNhctaSt75PNL7/7CULll9zyPZTu3FS0/u6KD8dTlMhttmA2xcG/+f+IgZ5+yDQBw8RFip3wT72pPTEREo8vpFwOnX4xLTxONj7v9WwAAF10pGriVdC6ed+ExmHfhMbrjv7pfBVU2R9U3HoiIiCpJLVy2YOOBiIjIQkZ/GKuasfFARERkoYEayHkY/Z+QiIiILMWeByIiIgvxsgURERGZUguNB162ICIiIlPY80BERGShdA3cMFn1CZOLy9Q79Mz61wAAx0/9SmbYhdvFsHvGludNd8pNwdOilyBYCvlZAfXnNUumLWolLf72ts0AgB9ePlE1/N3t/wSgncQ3Jv0oAGCH7QzV8H/3vQIA+IZ9rTIst8z7258DAOwz9jjD9W+OLwYAhJwdeeO00j6t8MhakXB65v4zVMNlAmdu4ulQFVpHpZDr4vnXRQrgT4/bQxknkyllcuKNT30KIJMY2BkWdVnoLa0u9721BgBw/iEHlDQ9AEQ3vQhAO+HUCJnYec1Z+gmVemQq4gnTDlUN3zD4pPJ6St2ckuo1VB3IHFhzE1jvevk9AJkQvkV/XSf+3RnKlO3eN8Q+esHM/XXfq+sfYjtpP1GdsKmVpPrYh28DAMaNEcmVhZIq9XQMwxnvmXW3GCr30F3P4aHf/kt3/P+57H+YMElEREQZ37n4OHznYv0vOMdPq8yGA8DGAxERkaVq4YZJNh6IiIgsVAuNh9F/VwcRERFZij0PREREFhq0jf7v5Ww8EBERWagWLluw8UBERGShgRr4Se7R37dCRERElmLPAxERkYV4zwMRERGZkq6Bex6qPp76NNtSLMdS3fGz0YbZMJ7SZSb2+Te/FpHLA/Xi/3bvZ5mRfxAxvfM6dik6n9y4118+9zEA4JhDRZzv1xoPLzqP3CjgbLnxr9c9JuJkrz01P042V+7ykHG+gH6kr4ws1qr3pwNPAwCm159Q9L311Kf/AgAYsJ2eN27jYET8OzAeQCae+u2ty5UyB4+fDQDouPZkMeC6vwMAHtvwawDA8imX5s33V8+LuOjLjhFx0VoR4rfdvREAcPlFkwFoR5wX85f33wEAbPlCRKDPm3GgMu7uW7YAAC66coLmtHes+EB5/eOjRL0eiCcAAEfsLda5/Ox/fm+VUrZhZ9TvKXseopqfjMj+YkvmO4aMkpbvJd8nN3raiCc/fQOAsYjhFzfFAABHTnLplpHLrn+b2CGzY42LkfsPkNmH1m4TscFvrJsKAJg5bT0AYP9xxxqer1K3n/Urr0+/ucHwdOsH/gEAmFp/oun3zKvDzuUDAKfvc5Bmmf957EcAgP976m+UYc8lXwUAHNd0mOH3uv+d1QCAcw86UHP8Ex+/qbx+7xMRWS+Pf5JWJLw8Hjn3Fvua1razHOpzwuYZ2wAAE1eNAwAsWtJW9sjnv2y+w1C5v3Y/jb92P6073v+TaxhPXS5mGwdERDR65Z4THnta/B7GqXsdDAAYjnPxIIz1PJzaeiJObT1Rd/y3J15iUY2sV/WNByIiokpSC49qjv67OoiIiMhS7HkgIiKyEJ+2ICIiIlOG47JFLBZDZ2cnHA4HUqkUvF4vmpubTc0jEomgpaUFfX19pt+fjQciIqIqkkgk4Ha7EY1G4XKJJ5CcTieSySRaW1sNz8fn85Vch9Hft0JERDSMBmw2S/70+Hw+eDwepeEAAH6/31RjwO/3w+FwlPwZ2XggIiKy0KDNZsmfllQqhUgkAq/Xqxo+a9YsAEB3d3fR+kUiEUydOlXV+DCLjQciIiILDaIO/f0D2Lyxf0h//f39efNeuXIlAOT1GsiGQDgcLlq/YDCI9vb2IX3Gqk+YnPrCR8prmf732udi4UZCMwAAV1wwBUB+Kp4Wmap3xbF75o1b9FeR0nfBIpE451hh7U0xMgFOL/0NyHyGTz4VKXWLTtNOiZTpbIA6oc0omY74eqIRADC1SWzEc53Gu7lC125VXjdfJxIff/fquwCAEw8Wn2PTdpGkuH2wXin7lYkirbDBdgqATNLfhu0iIe7wCaKFnZ1S9809vgwAOGjrbwEAv9kikhSNpDt27Ax0OebDtwBkwmSATGLl5DoPgPw0UJm+B2QS+O59Yy0A4JSDxL+7jzkeALD40fWZskeLREO9dEX52eTnyia376/sOqvoZ8slk//WpzIph/vtKZIrk717AdBPsAQy+8eG9WJd1A+IZXfNWU2m61KITMD88NNdAaiTPCWZGipTM2WappFtVG5TMi3yntffVcaNGysSN2U64n1vrQEAnH/IAQCA6x9OKmUP/ap4Lfex3HTVp9e9DgA4YdqhReuklVoqxfufBwA4G44BkEkzveLCZ5UyadtpmvN9d/s/AQBfGrNOGbbNdqaqTO6yNCJ4u0jY9S0QCZEyhRXIHItLkZssKRNxgeKpuMs3vqS8nj35q5plOobhjPf7/rvx4P99GA/94pEhzaejowOLFi1SDevu7obP50M4HIbH41GNs9lscLlciEajuvOUlzccDgf8fj+6u7t5wyQREdFIS9tsOMN/Ok694ltDms8Fk36QNywejwMAmpq0G+ypVEp3frFYDFOnTh3SvQ4SGw9EREQWGrTZUD9+HOrHjxvSfBrG5v8OitMpfrMlmUzmjQPyL2dk6+zsRG9v75DqJLHxQEREVCVk40Cvh0Gv8eD3++H1epFIJJRh8rX810yPBBsPREREFjL6w1ilkE9VZDcCsv/vdrs1p4tEIujq6tIc53Q6i94rkYtPWxAREVlo0FZnyZ8Wu90Ol8uV91RFJCJu7p47d67mdNFoFOl0WvXX3t4Ou92OdDptquEAsPFARERUVXp6ehCJRFS9D4FAAIFAAHa7HYDoiXA6nUqjwmq8bEFERGShcl62AKBcYpApkYlEAn6/XxVNnUqlkEwmCz59MRRsPBAREVloOH4Yy+VyFXxywuVyFc1vkL0VpeBlCyIiIjKFPQ9EREQWGijzZYtKUPWNh3F/60byvvsAAEsgoo4hEm2R2ncAtjN+CMAv/p/KD+yQccOTJm4HAKQ/2lX3vfSioDvDnwEAFnp3K1rfrn+IWOJt/ZlOn2tOEdM5p24oOn2haO1spURSZ1v1/hTV+8mI3kJkDO5+Y78OANh+fiauFteJqN8fHLbfzgH7Qc8ja0U0sQzQlRHCudLpzA66etu/xYtxPwQArNkZET3w2RsAgJN2y8RAdwRE6tti/9/EvxB5taeKdGZV5PSrUREP/eOd/5ex1Eodd0ZSZ7tg5v4AgMc+FPHcp8r3PWNqVinxOneZSdt21EPP+s930RwuI4sB4PKLJgPIjzyWkcuF5EZwP5iIK+MavxD7mFZ8O5CJYwaMRTIDwK33ZrZ7GSX/7X1nqMrIyO9338vsn9fkRCmbiU5f9i8RtCPT/S88NLM9ynjklzeLu8/PnygefZMxyeqIZJHyp8RQ74yllgbT+SeRm+5PAQAOO/FjAMApex4CILOOHvvwbaWso0ksm4N3xlJLJ7WIKPvsSGoZn597nNp7jNguciOpsxmJpZbRzzL2OTnji51jRDx1diS1kaj9XI9/JOLhv7NzeUhakdR6PyMwe/JXsRxLsRxL8dSMbaJ2q9TH/WlL29DW1ma4XqUwetni6dsfx7O3P6E/n7b1Za9rqaq+8dD0/e+j6fvfB5B/8Liue2cm+u3DXSsiIhoJs9GG2WjDn58SDfzchuhwnIvTBnsejl/wLRy/QD/Cuq1O+7HLSsB7HoiIiMiUqu95ICIiqiR6AU+jCRsPREREFip3zkMlGP3NIyIiIrIUex6IiIgsVAs9D2w8EBERWagWGg+8bEFERESmsOeBiIjIQgPD8NsWI42NByIiIgvVwmULWzqdTo90JYZij5UfKK9zo5TXrJ0AIBP/LN3z+rvK6+xYWi1PfPym8vqbe3xZNU7Gqb7wkohP1YpRveX3KQDAlefZAeRH/1pFRmQfsP9mAIB94jZl3Ibfis/43Wu0Y421yIjcU/c6GEAmjnn8uAGlzCk5MbK5lq1arbyeN0PEIudG3BayZPmHAIBLZ+9lrNIGnZO4DgDwzu4i2vbVCfMBAB3niDhl960PK2XXfCCid486WCzfr+XED2d7ZctKAMDhE2YVrYOMKW8/cXfVcLl8nnhKrLMTj89s38flRGH/u+8VVZ1ufuYTZdzPjlfPV+p+8X0AQOuR+yjDZPTzbnYRp/3Gf+wAgO07xAHw6pOn583nxqc+BQCMHy+2B724akD/sxYi59+/RcR0T5kqtuf999qilJER7HKZvfmeiIoutk8PhwfiCQDmIrO1yGPZ+YccAAB4e+tyAJk4afk+AODeRywzZ06UtbQt/Tfl9TibdqphxyU7Y6rvXKEMk/Ht0v3viP16ul3EU8+ZLqLf71iR2VYHdsZyn3rEuwXrZISMBQfyj7FPfvqGqg5GdAzDGa8Tjxgq9++l/4vnl/6v7viOtqsZT01ERFQLBg3eTnh02+k4uu103fFtOMOqKlmOjQciIiILGf1ti2rGxgMREZGFauGeBz6qSURERKaw54GIiMhCtdDzwMYDERGRhWqh8cDLFkRERGQKex6IiIgsNFADPQ9sPBAREVmoFh7VrPqEybE/uREDf/4dAGDqu/V542ejDbMhErpkal12Yt7Lm6MAgCMmuou+l0w83K2xHwAwYZftog71gwCKJy5aSSY+HrmX+Ez7jf26avwLG17OvH5TfN7LjlGnAD6z/jUAwPFTv6IMe3rd6wCAXcaJz2YkCbIUMjVOK5VTemjNfwAAH3y6K4DCSZOrt/0bAJDsHw8AcE86UrfspwNPAwB+9vYTAADHzx8CACx++A1DddeTm/hoxKK/iuWw6DSxHGQCadMUsY3JFEUA+NXzHwHIX48yBTU3AbWQv7z/jvL69H0OAgBEN72oKiOXoaxjdj31kv2emr9deX1yz1hDdZFppkAm0VRP9nad3DJeNY38TPZd+/Omy03nLKSU9SgZWRcyDXahdzfdMtKdUZHaeIl7b9VwmSx58O59yjC9Y9hA+jEAQL3t1KLvZ4bcVr/oF8fdbat2VcbN+pZIMs0+tuiRSb25x0+5rrduz3zH/bhPvMcu43cAAL697wzVNA+t+Q/W3Xsf1t17H7ZtF/WaulZ9Xli0pK3sqY0/x+OGykWX/hnRpX/RHb+4rZ0Jk+VSf+bFqD/zYgDApQZ2RiIiGr2mXXA+pl1wPt5OTAYAXJoTrz4c52KjN0we2XYmjmw7U3d8G75pVZUsV/WNByIiokoif9tjyCr46geftiAiIiJT2PNARERkoVrIeWDjgYiIyEK18LQFGw9EREQWMvqT3NVs9H9CIiIishR7HoiIiCw0WANPW7DxQEREZKFaiKfmZQsiIiIypep7HgpFvD6XfBUAkPhYJI1dPXP/vDK5ka4vbooBAI6c5AIAvLJlpTLu0gmzAGTHBB8IAFhy10YAgD0rOvfoKUcUrHf2fA/fOV8zbDubfW+tbwIArN4ZK33CtEPz3n/zpzJ2WcQaywjqEzSiY7fujHSV8ylExgHLeONcv3zuY+X1T4/bA4B+LPWf31ulvJaRsx9/tguAwrHU0oHjvgYA+HL6YQDAVohoZa244On1JwAANq95BkB+LLWM/gWAuU6Halzu9nHvG2uVcRfoxBk/mIgDAMbsjDEHgDP3F59Rxj3//TNRh4t3mwk9jn027XyljqcuFIV8e4+Yps4ltlEZc5zaPE4po2zPOZHe3S+KiOFFR+6TN9/cWGq5nN/7ZGJmYM++uvXKFl2e2YdlgLJcB7nLP3u7fu1zsQ/d99YaAMD5OtshkIk6/ntULLurc1IHs8lYarneznE4dcvKmO66nV80v5mz/mSE87Ztme9pU8eofxFAvs97H4vo5bqsr3SX5cRS37FCxFXve7sYHrsocwjPPeLY0n8FANTbTsur97vb/wkgP9b+kx1in9h9zPF50+TSilDPsAPIfP6BQbGAWjW2Jb1Y/5cTU3WnkWS0+dqPxHZ3SVZdMrHn+uu6XNIGL1u8dvtDeO2Oh3THz2z7P4ynJiIiqgVGcx5mLjgbMxecrTu+rf4bVlXJcrxsQURERKaw54GIiMhClv22RQVj44GIiMhCtRBPXXGXLUKhENxuN2w2G5xOJyKRyEhXiYiIqKLEYjG0tLTA7/fD5/MhFAoZms6qc2xF9Tx0d3cjGo0iEAgAAPx+P7xeL+LxOBwOR5GpiYiIRp7Rpy1KlUgk4Ha7EY1G4XKJJ7+cTieSySRaW1t1p7PyHFtRjYdUKoVgMKj8v6enB263G7FYjI0HIiKqCuW+bOHz+eDxeJSGAwClB6JQ48HKc2xFXbZob29X/d9utwOAagERERFVssG0zZI/LalUCpFIBF6vVzV81iyRF9Td3a1bLyvPsRXV85ArFAohEAgUbBHtQD92oF973MbNAIDBzWIlbMVGzXJj0IAxaBhibYmIqJxyj/c7NsljvAjeyj7Gy3G5x/3+/gY0NJT/eD/Qvw0D/duHNI/+Sf15dV25UoSj5Z4XZQMgHA4X7H3IZuQcq6diGw9+vx/d3d3o6ekpWO5ZdOJpLNYeeYD6vzfqzGPyJVfgyjt/CQB4/q3dAQAyay87/TG66UUA+Ul8l14sEiwf8exasK7ZtFIlZcrix+tEsqJMVsskpQF1tp07yeciITC+dhKATIKjFpkG+NCa/4j5r7aLf1etBgDsMn6HUvaD9ydpzuN3r74r3j+rr6o+K6VQi1adJk0S77X40fUAgI4zRIrcli/yN8UfHyVS9DKJnupkxTHpR5XXO2xnAAC22s5SlZHpizI5DwAm128FADxk+x9Rh2XnizrNuw9AfqphNpksKV2gkVoql7NM3iuUUCiNH7OjaJnALv8LAHgW+kmKuXbdJFbYRTuTCtuf+rEYccgdSpln1r+285V6+RZK9pPbqkwDbRgj0jO/tHd+A71YEuk1ZzUpr+WymzRuQFVGpsUe13RYpg5/E+tpn0M2oRiZTHl0znCZjPnOu1OUYZMmiHVxYc56kymg2esq1TdBTLPrNlXZ6x9OAgDs/SKxtVBKamqT2I+uOHZP3TKS3CcUN++nP9/0eACA/GQD6ceUcfvZTlWVbRzcebNdXTMAoOPRHyjjFp/xO1XZR9aKdf+dnSmpWpYs/xAAMGP6FgD5KZJyfQLAwKDYRmWq7b/7XgEAtGoktuYd7w9Wj1cd43eOi+bMo6GzA4sWLdKtuxUG0ja8ErgXr/3iriHN55CO/LomEiJ9VfYa5JLjizF6jtVTkY2Hrq4uJBIJpFIptLS0IBgM6rakvoGF+BquBAAEnxRxyL456pPWY2+I+Ne9p4iDzNismOCV8emwjRsH3Gn5xyAiIgtlH++z3f+CiME+9+jikegLF5a/1yENG2a2X4RDLv/ekOazcPLX84bF4+J81tTUlDcOEJc1ijFzjtVTkY0HeV0mEomgpaUFgUBA94NlX3KwTRCt3PGYrCpTP0nkno+dLL61Zzce6iZqf9MmIqLKoneJWR7Hc4/9WobhigUAoL5hHOobCvfOFqN1ecXpFD1iyWRScxojlyDMnGP1VNQNk7k8Hg9aW1sNd8MQERGNtHLeMCkbB3o9DGbuXxjKObYiex6yHXXUUXxMk4iIqkY546nlUxW5J3z5f7fbnTdNIaWeYyu65wEQC8Tj8Yx0NYiIiEac3W6Hy+VCOBxWDZdJkXPnzjU1v1LPsRXTeJA3bmRHbCYSCYTDYVWoBRERUSUbTFvzp6enpweRSETV+xAIBBAIBJSnMBKJhCp+2upzbMVctrDb7UilUpg/fz6CwSC8Xi8cDkde64qIiKiSlTue2uVyIRqNwu/3w+FwIJFIwO/3q256TKVSSCaTyr0RVp9jK6bxAIANBSIiIgNcLhd6e3sLju/r61MNs/IcW1GNByIiomqn96TEaMLGAxERkYXK/cNYlcCWTqcL3JZR+RYbWEe5ccGFPP7RWwAycaovboop42Q09IZ+Edyx5hMRTCIjih9MxJWyX2wTsbTnH3KAav53vSyS0LLjmPfY7QsA+rHIMp4ZyEQ0y/lMs4uo5fp6UTe9COCh6vrHJwAy0b2ARlSuCSvPEvHDz171GQDtKOs77xSJoFsPFxn1qb6xAIBFp00DAEwZfFAp++wXYh3I2O8vbb0bAPCf8Rfp1sFIGbmcLz5CJNfJWN31m0T075kFInqfXvc6gEzs7v3vrFbGnXvQgbrTVQpZ/1cTjcqw3Jhl+Znk55HTAJnP/cKGlwFkIqIlGXn+g8PyI5a7X3wfQH5Etoy6BjLbeu585H6oFQt+3WPrAADXnjotb1yuXz4nEmtzt00ZvQwAe04T++7bL4llNHkfsT/mLqfbezIR2gvmTzJdFzPe3/4cAMBlE8vw0zHfzStz5CYRqXvZmv8CkFl25ySuAwA86LhWd/73vbUGQP6xTWvdyGUll0ehqPI7VnwAwNhxZdnOaP15M9T7kdwWgMxnklH4WyZcAwDY5aQ7UG6nbXrJULk13cvwbs8y3fE3/uRnaGtrs6hW1mLPAxER0Qg4oHUeDmidpzu+bdJXh68yJrHxQEREZKFyP21RCdh4ICIistDg4OhvPFRMSBQRERFVB/Y8EBERWaicv21RKdh4ICIislAt5DzwsgURERGZwp4HIiIiC/FpCyIiIjKlFi5bVH3C5Gm2pViOpQCAwS9vAQDUvTlBGT8bbZgN/YSue99YCyCTEpnrgXjmJ09lAqRMLOs4Y+oQap6Rm8Im3fovkSx5xbF75tVH1uWRtasA5Ccd3vN6JmntwkNF0tqdUZHgdom7eILbDX9KAgB+fnaTwU9hjPxM/e+JhMa914i0zs1TBpQyl1wySTWN3vIpZMLgQwCALXXfAQCs3favvDJ7jt0IABhn+5bufOT20TB2EEB+ol2h1EgjiXky/fTjz3YBAExt6gegnzZq1Jj0owCAHbYzDNdJpvaNHydSRLXSM/W2Ny16KYC5spNZc2802/K5+H6jlUIp0z+37xBXXwtt17n7jRly+xu3cxvYtj1ztVduk7lpokNx41OfKq+vPnm64enkujl9P7FN1dtOBZA5FsjjQLblG18CAIy1ic925CRX0ffRS//UIlM6J+xMpi00jZHtRabtyqTdXNN3/BFP3/4Enr7jCex4czIAYOr+og7r14qk0EVL2sqe2njiujcMlfvgrj/gw9/erzu+67IrmTBZLtmNg82vi18Mm1jnHckqERHRCDlhwTdxwoJvKrHcV92zAABw04m3AwCG41w8aPAr+Z4//B72/OH3dMe37TbTohpZr+obD0RERJVkoAZCoth4ICIislAt3DDJRzWJiIjIFPY8EBERWagWnrZg44GIiMhCtXDPAy9bEBERkSnseSAiIrIQL1sQERGRKenBka5B+fGyBREREZlS9fHUi7N6h17eHAUAHDHRDQDYc4eI/ZyZFPGyT07/men5y5hmADjwKxsAZGKIr3tsHQDg2lOn5U1XLFL59p5NyusF8ydpljFDxiTnRiRny62vjIpusm9Tyuw9TUR8v/CciHLNjacuFJ375/dEPO639xXRxVoR2XoeXrhVeX1Wp4iuvu1uER+9yxHi3yMcIhZ8+4Bo8x7XdJju/J74+E0AwF6Txef5yq6zdMt+/43/BgD8v5m/KFhHs2Ts8jkOJwDg8Y/eUsadsuchBafVigA2GvcMAN9YfysA4NmpVxiur5FtSEZCX3zEvqrhhaLP73trDQDg/EMOMFwXScYR79a0tWjdcv3u1cz2pxVvrefWe8V+fsUFUwBktsPLLxJxx3LdAJmoarmfG4nvluvxw09EJPlPj9tDNf76hzPHnGvOEvvfH274HADwvZ/vWrT+8f7nAQDOhmMAaMfpyzjtz7eJzue9p4jjUd3O42n2/vLpwNMAgOn1J6jex0zkt9w+Pn9L/HTAlefZ88rI48fWbfWG51uKjmE443117X8MlVt3731Yd+99uuNvvuKnjKcmIiKqBYMGn7ZoOv/7aDr/+7rj2w50WlUly/GyBREREZnCngciIiIL5f467GjExgMREZGF0jUQEsXGAxERkYWM/iR3NeM9D0RERGQKex6IiIgsVAu/bcHGAxERkYWMPqpZzXjZgoiIiExhzwMREZGF0jXwqGbVx1NPvvoX+PyBewAAjavz20Kz0YbZ0I/3vPmZTwAAPzt+d9VwGd2c7Ypj91T9X8bWbtqzHwAwYcKAMm58g3i9YdNYAEBdnVjM7Seq3ydbbny0jOa97Jg9i04zdoyY/0LvbrplZVxvblSvjNQFgLeeF+99gCsFAPhgeSOATJxsduR0sm8cAGDTJrHcLz/lZQDAr8OHAwCuOSW/LnK55i5LLfKzzf5fEQv8rV+PKzqNnhc3xZTXR05yaZbpuPM7AIDFlzykDMtdZrmx0dlRxQ3jxK/hFIvi1pIb4fyX998BAJy+z0FKGRkNfd9evaJOn50DALhg5v5589uW/hsAYJztW6rhuZHZRsbJ7RAAPv9cRAfnRpNruf7xzwAAA9tEB2d65z6w6DR1nLuMcgfy49zlPLS2pdz6FdpPzDDynrly119upLUWvf0xW9c/xPFJHjduuj8FALjqXHvROmltQ9Lqbf8GABw47mtF5yN1hsVyKXSMKWbZ4i8AAPM6dlGGyWPKR5+IWHoj25beTwNMHXgAz9z+OJ69/XHseFN72S9a0lb2yOcDXnu3eCEAm+6/B5v+eK/u+F9eeQXjqctlwtyLMGHuRQC0c/WJiKh2HL/gFBy/4BSsr5+rOb6SzsWTzr0Qk869UHd821fMfxEZLlXfeCAiIqoktXDDJBsPREREFqqFRzX5tAUREVGVicViaGlpgd/vh8/nQygUMjRdKBSC2+2GzWaD2+1GJBIp6f3Z80BERGShcl+2SCQScLvdiEajcLnEDeBOpxPJZBKtra2603V1dSEcDsPn8yEej6OrqwterxfhcBgej8dUHdjzQEREZKH0oDV/enw+Hzwej9JwAKD0QBSyYsUKhMNhtLa2IhAIIBqNAgACgYDpz8jGAxERkYUG0jZL/rSkUilEIhF4vV7V8FmzZgEAuru7NaeLRCJ5jQSXywWXy4VEImH6M7LxQEREVCVWrlwJAHA4HKrhshciHA5rTufxePKmkfSGF8J7HoiIiCw0OGhDels/sH3bkObT39+PhoYG1TDZS2C32zWnMduLkEgkil7u0FL1CZOLNXp2Ln7ZDwC464ji13EeWvMfAMB3DvgSgPy0uux0vdwEO5m4tn2HqERu2hkA/ObXmwEAP/rJRNXwW+/doLxu+LIo0/+mKHPFBVOK1tsK97+zGgBw7kEHKsN+e5uoyw8vF3UplEh4x4oPAAA/Psp8OFduMmY2mWAny8xwbsqr51DkrvNc1z+cVF5fc1YTgExiYP1MsXzWfSbSLnPTEoHMcl39mliPPz+7Ka/MslWizLwZ6s8kP3N65zbVccZU3c8xd1UHAOCBGYt1y1ghO221Yay4EKu3zm/4U2bZyc9dLLFx0V/XKa+bpm4HkElklYmTekmwRuXu17npjtkpq2fuPwOAOk0VMJYcKqcxUvbGUB8A4OrmxqJlc/3xepHU+N1rdilSMpNMevER+5p+HyMKJXzmJrIaYVV9O24/CwCweMHD6uHDcMZr/PdH+OI3N6H/t7cMaT4dHR1YtGiRapjf70dXV5fqZknJZrPB4XAgHo8bmn8oFEJnZ6dy74MZ7HkgIiKy2PgLfoLx55r/Rp9t4Tfyo+edTvFFLplM5o0DzF2C6OzsRG9vb0l1Y+OBiIjIQulBGzBmvPgbgtxLFkCmcZBKpTSnMdp48Pv96OnpKel+B4CNByIiIkuVM+dBPlWRe2+D/L/b7S46j+7ubni93rzLHmbwaQsiIqIqYbfb4XK58p6qkEmRc+dq/yCYJJMoc0OhYrGYVnFdbDwQERFZaGDQmj89PT09iEQiqt6HQCCAQCCgPIWRSCTgdDpV8dORSASdnZ0ARO+D/PP5fMojoEbxsgUREZGFyh1P7XK5EI1G4ff74XA4kEgk4Pf7VdHUqVQKyWRSuTciFospwVJaj2b29fWZqgMbD0RERFXG5XIVfFLC5XKpGgQulwtWJjOw8UBERGSh9MDo/0luNh6IiIgsVOh+hdGCjQciIiILlfueh0pQ9fHU5/3qIvz9TvHIyvY382OdZ6MNCz/dCgA4IXohAO0Y6cWPrgdQOA441y+f+xgA8NPj9tAtI+OGJyZFO+3K8+y6ZQPLxPUp/zwRV/tAXNxJm87aEHPjjKV7btoCAOg7VsQoX3FsflTsUHT9Q8QDt59oPB74zjs3Ka8vuWQSAOD2HjFswXzxf/mZx39Rr5S9/KLJQ6tslkIR2l/aejcA4D/jL7Ls/YDMOh/c+e1DK8LaSj968f8AAB484mhlWF9dMwBgW/pvAIBxtm+VtQ5aZAT71n36AQBXnzwdQCaOWi4XGT0NZOKnb3zqUwDAYErsN1oR31aSkeKANTHoS5Z/CCATr23EX34mltPpN+cHA8mY+w+/JI5lWsewYm66P6W8vupcu2rcxkFxR/7kOvH43oTBh5RxW+q+oyobvF3UxbdAHblvlfveWgMA+GydCFhKr80ELRU6fkrLsRTLsVR3/KIlbWhraxtSHYup/9u64oUApB+9C+lHf6s7fon/srLXtVRV3/Nw0oJv4qQF3wQAfDD2ezqlbh6+ChER0YiZjTbMhv4JdzjOxYNGL1ucdrH409H2X+X94jEUVd94ICIiqiS2GrhswZAoIiIiMoU9D0RERBaq56OaREREZEZdDTyqycsWREREZAp7HoiIiCxUVwM3TLLxQEREZCHbwEjXoPzYeCAiIrJQfQ30PFR9wuTirHWUm14451MRDrVuV5GE9vLE/J8hlWT6mkxey/1/qWTKokxYlDrDnymvF3p3U08TFamIl7jzUxHvvkUkSV505QTV8Ltefg8A8Nkq8Vmvbm7UrdO9b6wFAFwwc3/dMjLdMrF25/x2pgOW6vqHkwCAa87STgq84U9J5fWhz4vPdmZXftKeVh0BYK7TUbDsg4m48vqA3Taqxh098X0AwCkfvAYAOOnZHyvj5PqX21Zyt+0A9D+HVeQ2sLU/c1vSnruJdMHclNEx6UcBADtsZ+TNRy5XmdD49tblAICDx882XBeZpApk0v6MJP0Vk5s0CeQnvcoE0ilf+hyA9j7xq+c/AgBcdow6VVUuQ63p5P5y8RH75s1P7pt2+zYA2umkxRRKn31qvtiGPttnBwBgXscuqvEyoRQA6urE4dkRFfvE936+q+E6LFslUjMTa8Q+nHucyfbI2lUAgDP3nwEgk0wKFE8nXXKX2J8uvTiTDCsTNpsids16X/945vh3zSn69QK0E0iHomMYzniT/pgyVG7bEz3Y/sRduuN/vfAnTJgkIiKqBUafthjvmY/xnvm649u+Z7emQmXAxgMREZGF6mog54GPahIREZEp7HkgIiKyUC38tgUbD0RERBaqr4FHNXnZgoiIiExhzwMREZGFmDBJREREptTxsgURERGRGnseiIiILFQLT1tUfTz1pPNuxhd/7wEANH6U35EyG22YDf14zxtDIv42N875DzeIOFytOFgZHzt9rYhPzo2e1lIsnrkQGScNFI6UVr2fRvxrbvSvJGOCgUxUsIw1ltfuCsVdS7fdLWJqL79IxNTeF/hcGTd2q5hPbhSvJGO8ASA1bUfB9ywU351Lxu5u2DJOGXbKQWJ5PvSyUzWfrn+IGNz2E/UjcGVU7piE+Bzysw6VXF/FonqBTPTvpbP3suS9c8nte/wuou81e3nkRkr/5tebAQAD9WK8b8FEpayMUh+sF4eYH16eGTccfnvbZuW13nsbiWovFDWdS28bkjHbAOCf16g5Lne4Ea+ckukfP/xxsRLkfne+v3iU9e9efRcA8IPD9jP93rnkMQ4AsHPbMbI9myGjw2XUtta6WY6lWI6l2DKjHwBwwGYxzWcf7QMAWLSkreyRz/su2Vy8EIDNz3Rj87PduuNvvYbx1GWz60mt2PWkVgCZ37QgIqLaJL8wPvHsmwCAfz56DQBg8fwHAQDDcS42Gk89+bhWTD6uVXd8W9vwNrjN4D0PREREZErV9zwQERFVklr4bQs2HoiIiCxkM3jZoprxsgURERGZwp4HIiIiC9XzsgURERGZwYRJIiIiohzseSAiIrJQLfwwVtUnTC62eB3JpL9pq8cDKJweKRP0NjSJPqqtu2T6qnLT4sykIo6kW+/dAAC44oIpmuOzU+SmfTwWANA/XmxCRtIWZZLk4U+LhMZXv7EVgDqZMLes3jqQSYgAcO2pIvHQTFLjslWrAQDzZhxYtGy5FKuvTNQDMql6uT7a8SwAYM8x31CGyYTQn59tPtFUuvGpTwEA01/NJBXKpMab7k8BAK461254fjJ9USqU5JlLJnt+8UWms7Rui0hUlAfq9BSRTKq1nPSSH82kR2rRS201I3St2Ae2jRe36Gul2uqR6wHIXxd66bnDQe6bu6bE99NC20luaqSUm2ZayNtblwMADh4/Wxkm02XP3H+GqmzHMJzxZl73haFyyRfuRN8K/YTJWzouZcIkERERZTQdfQmajr5Ed3xbm3acfyVg44GIiMhCfNqCiIiITKmFpy3YeCAiIrKQ0R/GqmYV96hmKBSC2+2GzWaD2+1GJBIZ6SoRERFVlFgshpaWFvj9fvh8PoRCIcPTplIp+P1++P3+kt+/onoeurq6EA6H4fP5EI/H0dXVBa/Xi3A4DI/HM9LVIyIiKspW5nseEokE3G43otEoXC4XAMDpdCKZTKK1Vf8nvgEgEokgGAwiFAoVLVtIRTUeVqxYgXA4rPx/3rx5cLvdCAQCbDwQEVFVqC/zPQ8+nw8ej0dpOABQeiCKNQg8Hg88Hg9stqE1cCrmskUkEkEgEFANc7lccLlcSCQSI1QrIiKiypFKpRCJROD1elXDZ82aBQDo7tbPjbBSxTQePB4PHA6H5ji94URERJWmbsCaPy0rV64EkH9elL0Q2b335VRRly20JBIJ+Hw+3fE70I8d6B/Se4xBA8agYUjzICKi8tI73m/fuBkAsBUblWEDm/KHAUB/fwMaGsp7vK8bsGFwoB+DA0M7N/X3I6+usifebrdrTjNcPfUVHU8dCoXQ2dmJaDSqW+ZE2yI8jcVDep/xZ16Nqx/pVA275/V3AQAXHrqf7nR/uOFzAJk42T9en4kk/e41pSeDLblLbOyXXizinmVMK2AsqnW0kctj667i+acdY8UmqxW7KyPDL7pyQtH56sXimnF7zybl9YL5+lHmQCb6G9CP/871l/ffUV6fvs9BJmuXEe9/HgDgbDgGAHDCul8q456e9lMApUU1y7jya87Kj8H+za/FwbvpY/EdZVOj+Cp14VXqdSMjnoGhxTzn0pqvjNy++uTputPJaO/tO7czK+okt0tAf9tctlgcP+Z1lD9VUG9d68V4A8UjyWXUOpCJW8+NmM49tpn1dwz9eN/R0YFFixYNaR7FfO2ybXjvhf+LD5ZfP6T5aNXV7/ejq6tLdbOkZLPZ4HA4EI/Hi87bZrOhtbUVwWCwpLpVdM9DZ2cnent7C5b5Bhbia7jS0Pxu+6s4cFx+WubAcecdG4ExDcAjpdeTiIjKT+94H/9UdOU7p88qOo+FC8vfy2wbBPZxtWOvIy4f0nwWLsz/QuJ0OgEAyWQybxwwfJf5K7bx4Pf70dPTU3RBmLnkYJsgWvbjkWn12io3OpyIiLLoHe/HTha9OdnHdj1lvmIBQDxtUY8GoH5ob9bQMC5vmDwnplIpzWmGq/FQMTdMZuvu7obX683rkiEiIqpl8qmK3Hsb5P/dbvew1KPiGg8yJSs31yEWi41EdYiIiEypG7BZ8qfFbrfD5XLlPVUh05jnzp1b9s8HVFjjIRKJoLNT3LjY3d2t/Pl8PuXxFCIiokpWzkc1AaCnpweRSETV+xAIBBAIBJSnMBKJBJxOp+ZPPOhd8jCjYu55iMViSuiF1qOZfX19w10lIiIi08r9q5oulwvRaBR+vx8OhwOJRAJ+v1+VLplKpZBMJvMaCrFYTHnC4oEHHoDX64XH49F99FNPxTQeXC4XKvipUSIioorhcrkKPo3ocrk0v3S7XC4Eg8GSH9GUKqbxQERENBro3a8wmrDxQEREZKFyX7aoBBWdMGnE4jI38AolCFqdyEfWk6mORhMdrSCTFd93bAUAjNku7kvOXue33S2S9i6/SDyX/qvnPwIAXHbMngCAwDLR3eifl5+iKck0wC3JdgDA4rPvseYDVBkjqaI3hsTyHNcvDhhXnmcve70qmV666u9eFcm6PzhMP1m3XIK3i/3Gt2BiWd+nYxjOeKd8b4ehcu++czveW3Wn7vjADW1oa2uzqlqWYs8DERGRhYz2PBzgXIADnAt0x7e1Ve4punJrRkREVIVq4bJFReU8EBERUeVjzwMREZGF+LQFERERmcLLFkREREQ52PNARERkoVroeWDjgYiIyEJsPBAREZEptXDDJO95ICIiIlOqPp76NNtSLMdS3fGz0YbZMB7vec9NIup2/JmfAgDmzThwaBWkUSU3NvqR9n5l3JldDWV9b1v6rwCAtO20sr7PcLsv8Lny+nz/riNYk9oh46kb4+MBAJdcoo7ef+bC7crr4+8ZqxpnJA58JC2HOCdMnLEeALB51VTV+EVLyh/5PO/kQUPlVr1/O+If3K47/oYuxlOXjdnGARERjV7ynPDNZ7oAAE/s2a4aPxznYqP3PBy85wIcvGeheOrKvThQuTUjIiKiilT1PQ9ERESVhE9bEBERkSm10HjgZQsiIiIyhT0PREREFqqFnAc2HoiIiCzEyxZEREREOdjzQEREZKFa6Hlg44GIiMhCtdB4qPp46sUl3JfyzPrXlNfHT/2KhbUhApbctREAcOnFk0e4JuVz670bAABXXDBlhGtCI01G+l94VWXGVefqGIYznm+msTd5PbkUr/fpx1NffwvjqYmIiCjLoU1tOLRJv3HQ1la5T22w8UBERGShWrhswcYDERGRhep2jHQNyo+PalKeHejH37EIO9BfvDBVBK6z6sT1RtWKjQfKswP9eBqLeUCrIlxn1YnrbXSqG7BZ8lfJeNmCiIjIQrVwzwN7HoiIiMgU9jwQERFZqBZ6Hth4ICIishAbD1VgOZZiOZbqjp+NNsyGOoRjOFMl77xzEwDgkksmFS0bunYrAKD5uvFlrROV12hOlpSYLElSpSVLFjsnTFtaOamNL32+FC99oV9XRwXVNVfVNx60GgdERFSbip0ThuNcbLTnwdXQBlfDyNa1VFXfeCAiIqoktXDZgk9b5CjU3VVL8y2XalsO1Tbfcqi2ZVBt8y2XalsO1TbfQuoGrPmrZGw85Ki2DZgHNM633KptGVTbfMul2pZDtc231vGyBRERkYWG47ctYrEYOjs74XA4kEql4PV60dzcXLbpcrHxQEREZKFyX3JIJBJwu92IRqNwuVwAAKfTiWQyidbWVsun08LLFkRERFXE5/PB4/EoDQAA8Pv98Pl8ZZlOCxsPREREFirnDZOpVAqRSARer1c1fNasWQCA7u5uS6fT/YymShMREVFB5Ww8rFy5EgDgcDhUw2VvQjgctnQ6PbzngYiIyGI70D/kn1rv729AQ0ODalgikQAA2O12zWnkeL3hZqfTlSaVJUuW1Px8t27dmu7o6Ehv3brV8nlX03KopvlynVXnfLneqne+xXR0dKQBDOmvo6Mjb77t7e1pAOloNJo3DkDa4XBo1qfU6fTYdk5IREREFunv70d//9B6Hhoa8nseuru74fP5EA6H4fF4VONsNhs8Ho/mJYhSp9PDyxZEREQW0zrxW0Hes5BKpQqOt2o6PbxhkoiIqErIpyNy71GQ/3e73ZZOp4eNByIioipht9vhcrnyLjFEIhEAwNy5cy2dTg/veahRqVQKnZ2dAIBAIJA33kiEqVUxpzQ0XA+Vg/sVDYdYLAa32414PK5cbnA6nfD5fGhvbwcgehS8Xi+CwaByj4OR6QwzdXsljQrhcDjd3NycBpBubW3NGx+Px/PuynU4HOlgMGiqDJUf10Pl4H5Fwykajaabm5vT7e3t6ebm5rxtJBqNpu12e7q3t9fUdEax8VDD9A5yHo8n7fF4VMOCwWA6u61ppAyVH9dD5eF+RbWA9zyQipEIU6tjTqk0XA/Vg/sVjTZsPJCKkQhTq2NOqTRcD9WD+xWNNmw8kIqRCFPLY06pJFwP1YP7FY02bDyQSjweBwA0NTVpjk+lUobKUPlxPVQP7lc02rDxQCpOpxMAkEwmNcc7HA5DZaj8uB6qB/crGm3YeBiFIpEIbDab6k8GgRRjJMLU6phTKg3XQ/XgfkWjDX/bYhTyeDxKF6hk9MBjJMLU6phTKg3XQ/XgfkWjDXseRin5TSb7G40RRiJMrY45pdJwPVQP7lc06ox00ASNjL6+Pt0wm2g0mgaQjsfjyjCHw5EOBAKmylD5cT1UFu5XVCv42xY1KBaLIRgMoru7G3a7HT09PfB4PKpHxLLz9WVGemtra958ipWh8uN6qAzcr6iWsPFAREREpvCeByIiIjKFjQciIiIyhY0HIiIiMoWNByIiIjKFjQciIiIyhY0HIiIiMoWNByIiIjKFjQciIiIyhY0HIiJSicViw/Ie3d3dZX8fKg82HoiISKWlpUX3p8G1JBIJ2Gw2OJ1O+P1++P1+3ekTiQRaWlrgdrsRDAatqXDO/P1+P3w+HxobG2Gz2Ux9FjKGP8lNRER5sn+Twyi/31/0dzgcDgd6e3ths9lKrFlhDocDgUAAgPgMXV1dZXmfWseeByIiUiQSCTgcjpGuhiWmTp060lUYtdh4ICIiAEAoFILP50MikUBXVxe7+0kXGw9ERDUukUjA7XYjmUzC5XLB4/Ggs7MTBx54oCU3T6ZSKfh8PuVP71JCLBZDS0sLvF6vcv+EFjkfp9OJlpaWYbnBk9TYeCAiqmGpVAputxvz5s1Da2srEokEfD4fenp6kEqlMH/+/CHNP5FI4MADD0RLSwuCwaDuTZKxWAx+vx+9vb0Ih8MIBALo6uqCz+dTlXO73bDb7QgGgwiHwwiFQnC73XA6nXllqYzSRERUszweTzr7VOBwONLpdDrd19eXBpAGkO7r6ys4j3g8ngaQDgaDeeOam5vTHo8nbziAtMvlUv7vcrnS0WhUVcZut6vev7e3Nw1AVa61tTUNIB2Px/PeIxAIGKo/mcenLYiIalQikUAkEkFzc3PeuFKettCafygUUp5+KFQuFouhs7NTc/zKlSvh8XiwYsWKvHEtLS3o7u5GLBYbNTd6VgM2HoiIalQoFAIA5aSr96RFqQ2JRCKhmr8eec9Cb29vwXJHHXUUACASicDlcqnG5f6fyov3PBAR1ah4PA4g80hjLBZTTsLyxO/xeEqev5xHMpk0VE7+q6e5uVm5mTMSiSCVSiEQCKC9vZ29DsOMjQciohq3fv16AOLknf3tHsCQbkKUJ/RoNGqonOwJySXrAojeCY/Ho8RbBwKBopdFyHpsPBAR1Siv1wsgc3JesWKFciIPBoNobm7WvB/CqFmzZgEAuru7NTMj5DDZu+H3+/Meu8z9/YuWlhb09vaivb0d7e3tvFwxQth4ICKqUc3NzXC5XMq3eHnZwu/3o6mpqeg9CMXY7Xa0t7cDEI9YRiIR5bcnAChhVLnlWlpa0NXVBa/Xi3g8rjQuuru7EYlElPHd3d0IhULMeRgJI/24BxERjazW1ta0w+FIA0g3NzdrPnJZSKFHNdPpdDoYDCrzd7lc6Xg8nnY4HOn29nbVI5aBQEAp53A48uYnp8POR0iz/xwOR94jmXxUs3xs6XQ6PVINFyIiqgwyHCocDpc0rdPpRDAYLPrDWEMRi8WwbNkyLFy4EMlkEqlUSrkZs7e3F06nU+nBAICuri74/X709fVZ8ugpZfBRTSIiUj1pUapy/haGjNCWDYHcxoDD4VDdWAlkbgQl67HxQEREqictStXZ2amcsBcuXGjpt335GOf8+fOxcOFC1SOlkUgE8XgcgUAAiURCicDOvdmSrMPLFkREBK/Xi0AgUNFPL3R1daGzs1PVw+FyuRAIBIaUR0HmsfFARESWXLYYLvJeBwZDjRw2HoiIiMgU5jwQERGRKWw8EBERkSlsPBAREZEpbDwQERGRKWw8EBERkSlsPBAREZEpbDwQERGRKWw8EBERkSn/H0HU5x5oySPdAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.heatmap(\n", + " df_pivoted,\n", + " robust=True,\n", + " square=False,\n", + " cmap=colormaps[\"rainbow\"],\n", + " xticklabels=False,\n", + " yticklabels=False,\n", + " vmax=0.7,\n", + ")\n", + "ax.set_yticks([5, 15, 25, 35], [2, 3, 4, 5])\n", + "ax.set_xticks([39, 89, 139], [-100, 0, 100])\n", + "# ax.set_xticks([79, 179, 279], [-100, 0, 100])\n", + "ax.set_xlabel(f\"$\\phi$ [deg]\")\n", + "ax.set_ylabel(f\"$\\eta$\")\n", + "\n", + "# ax.set_yticklabels([])\n", + "ax.invert_yaxis()\n", + "ax.set_title(\"LHCb VELO $x/X_0$\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "tuner", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/trackinglosses_rad_length_endVelo.ipynb b/trackinglosses_rad_length_endVelo.ipynb deleted file mode 100644 index 9c8c149..0000000 --- a/trackinglosses_rad_length_endVelo.ipynb +++ /dev/null @@ -1,591 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "import uproot\t\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from mpl_toolkits import mplot3d\n", - "import awkward as ak\n", - "from scipy.optimize import curve_fit\n", - "from methods.fit_linear_regression_model import fit_linear_regression_model\n", - "import sklearn\n", - "import seaborn as sns\n", - "import pandas as pd\n", - "%matplotlib inline" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "41978 8523\n", - "50501\n" - ] - } - ], - "source": [ - "file = uproot.open(\n", - " \"tracking_losses_ntuple_B_EndVeloP.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n", - ")\n", - "\n", - "# selektiere nur elektronen von B->K*ee\n", - "allcolumns = file.arrays()\n", - "found = allcolumns[\n", - " (allcolumns.isElectron) & (~allcolumns.lost) & (allcolumns.fromB)\n", - "] # B: 9056\n", - "lost = allcolumns[\n", - " (allcolumns.isElectron) & (allcolumns.lost) & (allcolumns.fromB)\n", - "] # B: 1466\n", - "\n", - "electrons = allcolumns[(allcolumns.isElectron) & (allcolumns.fromB)]\n", - "\n", - "print(ak.num(found, axis=0), ak.num(lost, axis=0))\n", - "print(ak.num(electrons, axis=0))\n", - "# ak.count(found, axis=None)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "stretch factor: 0.20303492305493354\n" - ] - } - ], - "source": [ - "rad_length_found = ak.to_numpy(found[\"rad_length_frac\"])\n", - "eta_found = ak.to_numpy(found[\"eta\"])\n", - "phi_found = ak.to_numpy(found[\"phi\"])\n", - "rad_length_lost = ak.to_numpy(lost[\"rad_length_frac\"])\n", - "eta_lost = ak.to_numpy(lost[\"eta\"])\n", - "phi_lost = ak.to_numpy(lost[\"phi\"])\n", - "\n", - "stretch_factor = ak.num(eta_lost, axis=0) / ak.num(eta_found, axis=0)\n", - "print(\"stretch factor: \", stretch_factor)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.hist(\n", - " rad_length_lost,\n", - " bins=100,\n", - " density=True,\n", - " alpha=0.5,\n", - " color=\"darkorange\",\n", - " histtype=\"bar\",\n", - " label=\"lost\",\n", - " range=[0, 1],\n", - ")\n", - "plt.hist(\n", - " rad_length_found,\n", - " bins=100,\n", - " density=True,\n", - " alpha=0.5,\n", - " color=\"blue\",\n", - " histtype=\"bar\",\n", - " label=\"found\",\n", - " range=[0, 1],\n", - ")\n", - "plt.xlim(0, 1)\n", - "# plt.yscale(\"log\")\n", - "plt.title(\"radiation length fraction endVelo\")\n", - "plt.xlabel(f\"$x/X_0$\")\n", - "plt.ylabel(\"a.u.\")\n", - "\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "nbins = 100\n", - "vmax = 80\n", - "\n", - "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20, 8))\n", - "\n", - "a0 = ax0.hist2d(\n", - " rad_length_found,\n", - " eta_found,\n", - " density=False,\n", - " bins=nbins,\n", - " cmap=plt.cm.jet,\n", - " cmin=1,\n", - " vmax=vmax,\n", - " range=[[0, 0.6], [2, 5]],\n", - ")\n", - "ax0.set_xlabel(f\"$x/X_0$\")\n", - "ax0.set_ylabel(f\"$\\eta$\")\n", - "ax0.set_title(f\"found $\\eta$ rad_length_frac\")\n", - "\n", - "a1 = ax1.hist2d(\n", - " rad_length_lost,\n", - " eta_lost,\n", - " density=False,\n", - " bins=nbins,\n", - " cmap=plt.cm.jet,\n", - " cmin=1,\n", - " vmax=vmax * stretch_factor,\n", - " range=[[0, 0.6], [2, 5]],\n", - ")\n", - "ax1.set_xlabel(f\"$x/X_0$\")\n", - "ax1.set_ylabel(f\"$\\eta$\")\n", - "ax1.set_title(f\"lost $\\eta$ rad_length_frac\")\n", - "# ax1.set(xlim=(0,4000), ylim=(-1000,1000))\n", - "\n", - "plt.suptitle(\"radiation length fraction and eta endVelo\")\n", - "plt.colorbar(a0[3], ax=ax1)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Parameterisation for rad_length_frac:\n", - "intercept= 0.0\n", - "coef= {'1': 0.19830920321074946, 'x': -4.49175976974402e-05, 'y': 0.00039490060416272056, 'tx': 0.00015102371088508598, 'ty': -0.3004315695136339, 'qop': -15.314945266490128, 'x^2': -1.8619394568578818e-05, 'x y': -4.953907513838906e-06, 'x tx': 0.021617503882699386, 'x ty': 0.03829244150062255, 'x qop': -0.41798007270055415, 'y^2': -2.4410328131494868e-05, 'y tx': -0.03443063985633742, 'y ty': 0.024201355785359608, 'y qop': 0.069823295273139, 'tx^2': -9.507076220830514, 'tx ty': -0.3980701633198789, 'tx qop': -0.04742639222342226, 'ty^2': -5.342167619183405, 'ty qop': 0.04842038611881145, 'qop^2': 0.2070268831284635, 'x^3': 1.5823479402461545e-07, 'x^2 y': -5.806838940825474e-07, 'x^2 tx': -0.00023418353598118923, 'x^2 ty': 0.0037081774556846224, 'x^2 qop': 0.01641641113222204, 'x y^2': 6.398758958085149e-08, 'x y tx': -0.002932641224303519, 'x y ty': -0.001396824762733282, 'x y qop': -0.020888196868450136, 'x tx^2': 0.09096908124129072, 'x tx ty': -2.939755357349759, 'x tx qop': -8.73057282483271, 'x ty^2': -0.15340975596199197, 'x ty qop': 9.249941815315987, 'x qop^2': 0.030205199863621846, 'y^3': 1.6478595155078324e-07, 'y^2 tx': 0.0013152209574444013, 'y^2 ty': -0.000257931039205234, 'y^2 qop': -0.0057816482028933735, 'y tx^2': 2.685350530706497, 'y tx ty': 0.17814134491255038, 'y tx qop': 9.050929476915277, 'y ty^2': 0.10064678584510746, 'y ty qop': 4.6142369495362185, 'y qop^2': -0.00046589334175238057, 'tx^3': -0.6242025517665986, 'tx^2 ty': -0.017658603327465147, 'tx^2 qop': -0.022216794668845363, 'tx ty^2': -0.01024816705930792, 'tx ty qop': 0.024042119917448937, 'tx qop^2': 6.093129132646114e-05, 'ty^3': 0.09834545208780196, 'ty^2 qop': 0.011664187426493774, 'ty qop^2': -2.1825340747940462e-05, 'qop^3': -1.559907925017188e-06, 'x^4': -2.9483981922595603e-09, 'x^3 y': -6.13444928188045e-09, 'x^3 tx': 7.101384723817716e-06, 'x^3 ty': 7.16725431293419e-06, 'x^3 qop': 4.00953960828232e-05, 'x^2 y^2': 1.0679747086683733e-08, 'x^2 y tx': 7.616826922074438e-06, 'x^2 y ty': -3.91052449297824e-05, 'x^2 y qop': 9.93899828579223e-05, 'x^2 tx^2': -0.005400741368580057, 'x^2 tx ty': -0.009338160688408294, 'x^2 tx qop': -0.0017215190824096578, 'x^2 ty^2': 0.0007665795500993852, 'x^2 ty qop': 0.08528819041114723, 'x^2 qop^2': 8.037042310903203, 'x y^3': 8.933181749881669e-09, 'x y^2 tx': 1.766907321343325e-05, 'x y^2 ty': -2.1412010806409754e-05, 'x y^2 qop': -7.010215747540322e-05, 'x y tx^2': -0.0021778144582400415, 'x y tx ty': 0.0326584774738, 'x y tx qop': -0.1598215452174385, 'x y ty^2': 0.012945427966444779, 'x y ty qop': -0.23950569088511311, 'x y qop^2': -0.8775916738593352, 'x tx^3': 1.366672968587086, 'x tx^2 ty': 1.7459886700480327, 'x tx^2 qop': 0.4423601484422016, 'x tx ty^2': -1.0803356692637864, 'x tx ty qop': -0.0706577637682464, 'x tx qop^2': 0.006422119173581787, 'x ty^3': -2.2905272843167253, 'x ty^2 qop': -0.0063092971067729734, 'x ty qop^2': -0.001963650254414034, 'x qop^3': -1.0318719588655238e-06, 'y^4': -2.213189409516758e-09, 'y^3 tx': 7.716181404937572e-08, 'y^3 ty': 3.7462658548648164e-06, 'y^3 qop': -2.6897178570957402e-05, 'y^2 tx^2': -0.019391135282039867, 'y^2 tx ty': 0.003922857934752042, 'y^2 tx qop': 0.30048105074735626, 'y^2 ty^2': -0.0014404468920953982, 'y^2 ty qop': 0.017062949506976018, 'y^2 qop^2': -0.5172314152946776, 'y tx^3': 1.1761566789450086, 'y tx^2 ty': -1.8639649790914088, 'y tx^2 qop': -0.07088661078488609, 'y tx ty^2': -2.1282820437243197, 'y tx ty qop': -0.001276549939024397, 'y tx qop^2': -0.0019180156335069092, 'y ty^3': -0.06849699842395515, 'y ty^2 qop': -0.0351395250211265, 'y ty qop^2': -0.0005408300561230844, 'y qop^3': 4.1258598459708434e-06, 'tx^4': -0.02399482130004447, 'tx^3 ty': 0.010297903626621132, 'tx^3 qop': 0.0018304232474417028, 'tx^2 ty^2': -0.01163526658236639, 'tx^2 ty qop': -0.00029701477688915344, 'tx^2 qop^2': 2.0001744822333693e-06, 'tx ty^3': -0.014645131120788562, 'tx ty^2 qop': -2.1232731978440055e-05, 'tx ty qop^2': -3.4544969537609295e-06, 'tx qop^3': 8.78704309226661e-09, 'ty^4': -0.001422061237110601, 'ty^3 qop': -0.0001708364957408537, 'ty^2 qop^2': -7.126783100939319e-07, 'ty qop^3': 6.1964331341077185e-09, 'qop^4': -5.174168949842998e-10, 'x^5': -1.5976409084572651e-10, 'x^4 y': -1.2852829911480512e-10, 'x^4 tx': 4.777915697529167e-07, 'x^4 ty': -9.081653267184464e-07, 'x^4 qop': -7.95855762181219e-07, 'x^3 y^2': -1.3157031020227805e-10, 'x^3 y tx': 1.2230534549573235e-06, 'x^3 y ty': -1.0267895049764775e-06, 'x^3 y qop': 6.863633592146812e-06, 'x^3 tx^2': -0.0005342802093432353, 'x^3 tx ty': 0.0011253536068463917, 'x^3 tx qop': 0.0006881448740720732, 'x^3 ty^2': 0.0033717855327176985, 'x^3 ty qop': -0.006259805047891221, 'x^3 qop^2': -0.0297856432575138, 'x^2 y^3': 1.382156611384744e-10, 'x^2 y^2 tx': 1.322090420252664e-06, 'x^2 y^2 ty': 5.288591697905076e-08, 'x^2 y^2 qop': 2.9553628222434014e-06, 'x^2 y tx^2': -0.0013788732936473938, 'x^2 y tx ty': -0.005451132472848938, 'x^2 y tx qop': -0.0016912696788365421, 'x^2 y ty^2': 0.00031313327173996576, 'x^2 y ty qop': -0.00464221485985505, 'x^2 y qop^2': -0.021052188879644034, 'x^2 tx^3': 0.2645245528224416, 'x^2 tx^2 ty': -0.33220588343665813, 'x^2 tx^2 qop': -0.1711975210821735, 'x^2 tx ty^2': -2.5912873965567513, 'x^2 tx ty qop': 0.6199222216667238, 'x^2 tx qop^2': 0.26554090739446995, 'x^2 ty^3': 0.21995419222883894, 'x^2 ty^2 qop': 0.5566329227084174, 'x^2 ty qop^2': 0.007138707803204316, 'x^2 qop^3': -0.0036233474117857143, 'x y^4': 3.4643399260403385e-11, 'x y^3 tx': -3.715471736942533e-07, 'x y^3 ty': 5.088992998114605e-07, 'x y^3 qop': -2.9562267287452926e-06, 'x y^2 tx^2': 0.001848217429633696, 'x y^2 tx ty': -0.0006914744675563748, 'x y^2 tx qop': -0.0005866344884493824, 'x y^2 ty^2': -0.0007084811094364334, 'x y^2 ty qop': 0.0021049811349424605, 'x y^2 qop^2': 0.010952363514219516, 'x y tx^3': 0.4012187913820339, 'x y tx^2 ty': 4.799588041207373, 'x y tx^2 qop': 1.3345269234332224, 'x y tx ty^2': -0.3492025592669184, 'x y tx ty qop': 0.7401379477245426, 'x y tx qop^2': 0.00853019020452141, 'x y ty^3': 0.2663977835465425, 'x y ty^2 qop': -0.609737555278061, 'x y ty qop^2': 0.04129006001688038, 'x y qop^3': 0.0008163990713127198, 'x tx^4': -48.942089737430436, 'x tx^3 ty': -0.7028902863652343, 'x tx^3 qop': 0.06643076319999941, 'x tx^2 ty^2': -3.4139167347725943, 'x tx^2 ty qop': 0.004841829970654066, 'x tx^2 qop^2': 0.0007186793516648628, 'x tx ty^3': -0.2579234851632811, 'x tx ty^2 qop': 0.005881970664042852, 'x tx ty qop^2': 3.936368237569365e-06, 'x tx qop^3': -6.671449197806545e-06, 'x ty^4': -0.7419058590355208, 'x ty^3 qop': 0.0013112782683548875, 'x ty^2 qop^2': 0.00010835312377364621, 'x ty qop^3': 2.0484219462302866e-06, 'x qop^4': 2.580463321616666e-08, 'y^5': -3.2720492981752614e-12, 'y^4 tx': -5.762284480681501e-07, 'y^4 ty': 2.5788644553159656e-09, 'y^4 qop': -2.837759991436428e-07, 'y^3 tx^2': 0.0006211299557630969, 'y^3 tx ty': 0.000747045380526546, 'y^3 tx qop': 0.0020744456340701305, 'y^3 ty^2': 4.4960392427497754e-06, 'y^3 ty qop': 0.001141710321238258, 'y^3 qop^2': 0.002696814911126153, 'y^2 tx^3': -2.1363036642104674, 'y^2 tx^2 ty': 0.0687773207312733, 'y^2 tx^2 qop': 0.9871972836921945, 'y^2 tx ty^2': -0.2701567032221813, 'y^2 tx ty qop': -0.848252914690415, 'y^2 tx qop^2': 0.03660886322324573, 'y^2 ty^3': -0.005452852127128314, 'y^2 ty^2 qop': -0.7021206166732931, 'y^2 ty qop^2': -0.08018559047526934, 'y^2 qop^3': -0.00011753193330693663, 'y tx^4': -0.6680420541418445, 'y tx^3 ty': -3.384167006412971, 'y tx^3 qop': 0.006637451265825805, 'y tx^2 ty^2': -0.2331985780185122, 'y tx^2 ty qop': 0.006353552479363033, 'y tx^2 qop^2': 5.615722587673721e-06, 'y tx ty^3': -0.7572903037298312, 'y tx ty^2 qop': 0.0005634713263895614, 'y tx ty qop^2': 0.00010068765868206922, 'y tx qop^3': 2.012241389483668e-06, 'y ty^4': 1.5039421870145853, 'y ty^3 qop': -0.004362654564735129, 'y ty^2 qop^2': -0.00021869646501481262, 'y ty qop^3': 2.17774577667171e-07, 'y qop^4': -5.1794510300353154e-09, 'tx^5': -0.3290348306030112, 'tx^4 ty': -0.004713501192249353, 'tx^4 qop': 0.00039080511691431735, 'tx^3 ty^2': -0.02293656439194589, 'tx^3 ty qop': 1.795982117437259e-05, 'tx^3 qop^2': 1.3703545654537173e-06, 'tx^2 ty^3': -0.0016697750693905097, 'tx^2 ty^2 qop': 2.67609154249412e-05, 'tx^2 ty qop^2': -3.12791956432394e-08, 'tx^2 qop^3': -1.1594178303086993e-08, 'tx ty^4': -0.005076176679563355, 'tx ty^3 qop': 1.1834454126493736e-05, 'tx ty^2 qop^2': 1.9879319916637808e-07, 'tx ty qop^3': 4.055187311820455e-09, 'tx qop^4': 4.214995181248244e-11, 'ty^5': 0.010165548951092954, 'ty^4 qop': -1.6822916965291464e-05, 'ty^3 qop^2': -4.4801213131046415e-07, 'ty^2 qop^3': 7.260260169082666e-10, 'ty qop^4': -1.2734042962503632e-11, 'qop^5': -3.472724885502462e-13}\n", - "r2 score= -0.008270330873300091\n", - "RMSE = 0.10823208615961777\n", - "\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rad_length_frac = found[\"rad_length_frac\"]\n", - "# @ z = 9400.mm or 770.mm\n", - "state = 1\n", - "\n", - "if state == 1:\n", - " slopex = found[\"ideal_state_770_tx\"]\n", - " slopey = found[\"ideal_state_770_ty\"]\n", - " x = found[\"ideal_state_770_x\"]\n", - " y = found[\"ideal_state_770_y\"]\n", - " qop = found[\"ideal_state_770_qop\"]\n", - "elif state == 2:\n", - " slopex = found[\"ideal_state_9410_tx\"]\n", - " slopey = found[\"ideal_state_9410_ty\"]\n", - " x = found[\"ideal_state_9410_x\"]\n", - " y = found[\"ideal_state_9410_y\"]\n", - " qop = found[\"ideal_state_9410_qop\"]\n", - "\n", - "data = ak.zip({\n", - " \"rad_length_frac\": rad_length_frac,\n", - " \"x\": x,\n", - " \"y\": y,\n", - " \"tx\": slopex,\n", - " \"ty\": slopey,\n", - " \"qop\": qop,\n", - "})\n", - "lin_reg, features, xx0_test, xx0_predicted = fit_linear_regression_model(\n", - " data,\n", - " \"rad_length_frac\",\n", - " [\"x\", \"y\", \"tx\", \"ty\", \"qop\"],\n", - " 5,\n", - " include_bias=True,\n", - ")\n", - "\n", - "nbins = 100\n", - "vmax = 100\n", - "\n", - "a0 = plt.hist2d(\n", - " xx0_test,\n", - " xx0_predicted,\n", - " density=False,\n", - " bins=nbins,\n", - " cmap=plt.cm.jet,\n", - " cmin=1,\n", - " vmax=vmax,\n", - " range=[[0, 0.5], [0, 0.5]],\n", - ")\n", - "plt.plot([0, 0.5], [0, 0.5], marker=\"\", alpha=0.8)\n", - "plt.xlabel(f\"True $x/X_0$\")\n", - "plt.ylabel(f\"Predicted $x/X_0$\")\n", - "plt.title(f\"found rad_length_frac\")\n", - "\n", - "plt.colorbar(a0[3])\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "nbins = 100\n", - "vmax = 80\n", - "\n", - "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(15, 6))\n", - "\n", - "# ax0.set_aspect(\"equal\")\n", - "\n", - "a0 = ax0.hist2d(\n", - " xx0_test,\n", - " xx0_predicted,\n", - " density=False,\n", - " bins=nbins,\n", - " cmap=plt.cm.jet,\n", - " cmin=1,\n", - " vmax=vmax,\n", - " range=[[0, 0.5], [0, 0.5]],\n", - ")\n", - "ax0.plot([0, 0.5], [0, 0.5], marker=\"\", alpha=0.8)\n", - "ax0.set_box_aspect(1)\n", - "ax0.set_xlabel(f\"True $x/X_0$\")\n", - "ax0.set_ylabel(f\"Predicted $x/X_0$\")\n", - "ax0.set_title(f\"found rad_length_frac\")\n", - "plt.colorbar(a0[3], ax=ax0)\n", - "\n", - "ax1.hist(\n", - " xx0_test,\n", - " bins=100,\n", - " density=True,\n", - " alpha=0.5,\n", - " color=\"darkorange\",\n", - " histtype=\"bar\",\n", - " label=\"test\",\n", - " range=[0, 0.5],\n", - ")\n", - "ax1.hist(\n", - " xx0_predicted,\n", - " bins=100,\n", - " density=True,\n", - " alpha=0.5,\n", - " color=\"blue\",\n", - " histtype=\"bar\",\n", - " label=\"predicted\",\n", - " range=[0, 0.5],\n", - ")\n", - "ax1.set_xlim(0, 0.5)\n", - "ax1.set_title(\"radiation length fraction endVelo\")\n", - "ax1.set_xlabel(f\"$x/X_0$\")\n", - "ax1.set_ylabel(\"a.u.\")\n", - "ax1.set_box_aspect(1)\n", - "\n", - "ax1.legend()\n", - "\n", - "# plt.gca().set_aspect(\"equal\")\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.hist(\n", - " xx0_test,\n", - " bins=100,\n", - " density=True,\n", - " alpha=0.5,\n", - " color=\"darkorange\",\n", - " histtype=\"bar\",\n", - " label=\"test\",\n", - " range=[0, 0.5],\n", - ")\n", - "plt.hist(\n", - " xx0_predicted,\n", - " bins=100,\n", - " density=True,\n", - " alpha=0.5,\n", - " color=\"blue\",\n", - " histtype=\"bar\",\n", - " label=\"predicted\",\n", - " range=[0, 0.5],\n", - ")\n", - "plt.xlim(0, 0.5)\n", - "# plt.yscale(\"log\")\n", - "plt.title(\"radiation length fraction endVelo\")\n", - "plt.xlabel(f\"$x/X_0$\")\n", - "plt.ylabel(\"a.u.\")\n", - "\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Parameterisation for rad_length_frac:\n", - "intercept= 0.0\n", - "coef= {'1': 0.2484410418213911, 'x': -0.0007601095488043627, 'y': 0.0010569724392146917, 'tx': 0.6185505303064777, 'ty': -0.9394058560136732, 'qop': -9.741031889614183, 'x^2': -0.00016580416280366622, 'x y': 5.149038989659081e-05, 'x tx': 0.22996768886351043, 'x ty': -0.043161009059129354, 'x qop': -0.21658279194428842, 'y^2': 3.9826067539320166e-05, 'y tx': -0.033498957247677735, 'y ty': -0.08085122767618998, 'y qop': 0.06428923004582791, 'tx^2': -83.06687438225835, 'tx ty': 28.76266798578089, 'tx qop': -0.32072666519746007, 'ty^2': 32.80290436519906, 'ty qop': 0.29785759094660047, 'qop^2': 0.7177557091128425, 'x^3': -1.037888276319177e-06, 'x^2 y': 5.744977724613286e-07, 'x^2 tx': 0.0016261562680787358, 'x^2 ty': 0.00819223051446815, 'x^2 qop': 0.014940216048602184, 'x y^2': 1.55836456652794e-06, 'x y tx': -0.009042353485603404, 'x y ty': 0.002769481233443616, 'x y qop': 0.007035099510620806, 'x tx^2': -0.623629094925692, 'x tx ty': -0.5792857627094614, 'x tx qop': 3.819052794399519, 'x ty^2': -1.214138821848195, 'x ty qop': -4.179406422119741, 'x qop^2': -0.11723833703778899, 'y^3': -2.1060731703048674e-07, 'y^2 tx': -0.005136952674035623, 'y^2 ty': 0.0002523550890177065, 'y^2 qop': 0.020199755591199943, 'y tx^2': 0.8881296792413045, 'y tx ty': 2.1057062787476855, 'y tx qop': -4.322557205912296, 'y ty^2': -0.062185778412248593, 'y ty qop': -12.744670929978815, 'y qop^2': 0.10865361350283592, 'tx^3': -0.2772083890350773, 'tx^2 ty': -0.002155259913110253, 'tx^2 qop': 0.01973183125611695, 'tx ty^2': 0.2547275714314975, 'tx ty qop': -0.01267461996128659, 'tx qop^2': -0.0002315355231400779, 'ty^3': 0.12852489701010045, 'ty^2 qop': -0.03229168715651398, 'ty qop^2': 0.0001733290594162183, 'qop^3': -1.1131786479856305e-06, 'x^4': 1.4072631948636172e-09, 'x^3 y': -4.525309382774623e-08, 'x^3 tx': -5.048150129027817e-07, 'x^3 ty': 2.845994251238215e-07, 'x^3 qop': 6.161442924141475e-05, 'x^2 y^2': -1.8614020325102842e-08, 'x^2 y tx': 9.737839179148333e-05, 'x^2 y ty': -1.3038804363763035e-05, 'x^2 y qop': -8.415032085912991e-05, 'x^2 tx^2': -0.0010152847281566686, 'x^2 tx ty': -0.0032259545758118137, 'x^2 tx qop': -0.041785493301881166, 'x^2 ty^2': 0.013227443641328787, 'x^2 ty qop': 0.0035654519670473366, 'x^2 qop^2': 1.2621531315710728, 'x y^3': 3.906278722709544e-08, 'x y^2 tx': 6.858475435222999e-05, 'x y^2 ty': -5.862278080592809e-05, 'x y^2 qop': -0.00016236412225426912, 'x y tx^2': -0.06608751351613794, 'x y tx ty': -0.04864228625905696, 'x y tx qop': 0.06901548261804959, 'x y ty^2': 0.04159526642181612, 'x y ty qop': 0.28489071089527757, 'x y qop^2': 0.2535927965752249, 'x tx^3': 0.5018159233398294, 'x tx^2 ty': 0.9699678165589771, 'x tx^2 qop': 0.4741265130417677, 'x tx ty^2': 10.315681588678894, 'x tx ty qop': -0.22617149043686857, 'x tx qop^2': 0.00898570789717606, 'x ty^3': -12.737405175272935, 'x ty^2 qop': -0.014062351992903526, 'x ty qop^2': 0.005154120346378951, 'x qop^3': -4.609067543005094e-05, 'y^4': 9.455609628616912e-09, 'y^3 tx': -2.99210479094425e-05, 'y^3 ty': -2.583154312318925e-05, 'y^3 qop': 5.980622324156491e-05, 'y^2 tx^2': -0.016833583405836638, 'y^2 tx ty': 0.02458057322196644, 'y^2 tx qop': -0.169419352054439, 'y^2 ty^2': 0.02331391517451325, 'y^2 ty qop': -0.04589466917231106, 'y^2 qop^2': -1.206224538163147, 'y tx^3': 15.19059646701743, 'y tx^2 ty': 5.490478536183617, 'y tx^2 qop': -0.25278933198832354, 'y tx ty^2': -3.577260288354769, 'y tx ty qop': 0.03161480393545275, 'y tx qop^2': 0.005952281392129449, 'y ty^3': -6.821531531863169, 'y ty^2 qop': 0.09776598757839021, 'y ty qop^2': 0.0023614626852912395, 'y qop^3': -1.973415862163393e-05, 'tx^4': -0.05310859403428924, 'tx^3 ty': 0.023505514315239354, 'tx^3 qop': 0.0021762610547612377, 'tx^2 ty^2': 0.04763359558524625, 'tx^2 ty qop': -0.0009428124122745564, 'tx^2 qop^2': 1.2893218326397415e-05, 'tx ty^3': -0.018754843662608302, 'tx ty^2 qop': 4.8170564904883127e-05, 'tx ty qop^2': 1.6878183944633644e-05, 'tx qop^3': -4.12730477319448e-08, 'ty^4': 0.013919613173737298, 'ty^3 qop': 0.00022052138073417403, 'ty^2 qop^2': 9.713683885787424e-06, 'ty qop^3': -5.4325325107576684e-08, 'qop^4': 1.3416430509507416e-09, 'x^5': 2.37521113888306e-11, 'x^4 y': 6.566414079145488e-11, 'x^4 tx': -3.448894636548516e-08, 'x^4 ty': 4.817853991312404e-07, 'x^4 qop': -2.777657812425005e-06, 'x^3 y^2': 6.322311563167204e-10, 'x^3 y tx': -6.301214341419836e-07, 'x^3 y ty': 5.610926190335874e-06, 'x^3 y qop': 1.114123449319493e-05, 'x^3 tx^2': 1.3140964452713899e-05, 'x^3 tx ty': -0.0006698763738434144, 'x^3 tx qop': 0.004955643949611535, 'x^3 ty^2': -0.00020626810552818679, 'x^3 ty qop': -0.008992879337357176, 'x^3 qop^2': -0.01489312550273759, 'x^2 y^3': -1.0491474355944774e-10, 'x^2 y^2 tx': -7.058621529054676e-06, 'x^2 y^2 ty': 1.8916574067162628e-06, 'x^2 y^2 qop': 1.7843819655416482e-05, 'x^2 y tx^2': 0.0007719987709393639, 'x^2 y tx ty': -0.008372751086851777, 'x^2 y tx qop': -0.0094662761279594, 'x^2 y ty^2': -0.003982741017285164, 'x^2 y ty qop': -0.014247815997652827, 'x^2 y qop^2': -0.0933449616547058, 'x^2 tx^3': -0.00211924986590092, 'x^2 tx^2 ty': 0.1354990398386329, 'x^2 tx^2 qop': -2.4034242614405197, 'x^2 tx ty^2': 1.709794803412642, 'x^2 tx ty qop': 2.929391659772189, 'x^2 tx qop^2': -0.12899963468243164, 'x^2 ty^3': 0.41237245103458525, 'x^2 ty^2 qop': 0.9459129147227289, 'x^2 ty qop^2': 0.6716348674023994, 'x^2 qop^3': 0.0065213742878363744, 'x y^4': -3.1660363219998544e-10, 'x y^3 tx': -1.6554844943783564e-06, 'x y^3 ty': -1.8566065946856725e-06, 'x y^3 qop': -9.75035823502779e-06, 'x y^2 tx^2': 0.009680843788897421, 'x y^2 tx ty': 0.004952813049497684, 'x y^2 tx qop': -0.016925260798516226, 'x y^2 ty^2': 0.003475670476866588, 'x y^2 ty qop': 0.01417176786308785, 'x y^2 qop^2': -0.01761212366224941, 'x y tx^3': -0.15192958327351774, 'x y tx^2 ty': -0.060788822811239596, 'x y tx^2 qop': 4.3726462974483224, 'x y tx ty^2': 0.253839828387595, 'x y tx ty qop': 2.515358567018165, 'x y tx qop^2': 0.7384529496261274, 'x y ty^3': -1.4590050438376516, 'x y ty^2 qop': -4.598361895076147, 'x y ty qop^2': 0.31170679839759735, 'x y qop^3': -0.01024453299524337, 'x tx^4': 1.0757508065772434, 'x tx^3 ty': -1.6800363456087655, 'x tx^3 qop': 0.025130628317134973, 'x tx^2 ty^2': 1.1790180726236092, 'x tx^2 ty qop': 0.013852458993079927, 'x tx^2 qop^2': -0.0004548226751025624, 'x tx ty^3': -0.0007529047666109905, 'x tx ty^2 qop': 0.007719696430873407, 'x tx ty qop^2': 0.0018986412331720088, 'x tx qop^3': 7.660654451074145e-06, 'x ty^4': 1.3495131383656807, 'x ty^3 qop': -0.027518299643244655, 'x ty^2 qop^2': 0.0007835380395695195, 'x ty qop^3': -1.7215942880021808e-05, 'x qop^4': -4.814887567180262e-08, 'y^5': 1.1069811733932511e-11, 'y^4 tx': 2.5401641039479728e-06, 'y^4 ty': -3.659565095404105e-08, 'y^4 qop': -8.233519552314217e-06, 'y^3 tx^2': -0.0011440038498780267, 'y^3 tx ty': -0.003958853981003943, 'y^3 tx qop': 0.0019569523522222627, 'y^3 ty^2': 4.620362246071652e-05, 'y^3 ty qop': 0.013501593121770603, 'y^3 qop^2': 0.00013943149170339843, 'y^2 tx^3': -1.930662753166049, 'y^2 tx^2 ty': -0.6244835760091016, 'y^2 tx^2 qop': 9.706592754727314, 'y^2 tx ty^2': 1.567415053011399, 'y^2 tx ty qop': -1.8692848199146312, 'y^2 tx qop^2': 0.2576730572143735, 'y^2 ty^3': -0.02555256934016916, 'y^2 ty^2 qop': -5.570585900979827, 'y^2 ty qop^2': 0.4524728269219666, 'y^2 qop^3': -0.0012165533583740602, 'y tx^4': -1.705633938705921, 'y tx^3 ty': 0.9697939146444974, 'y tx^3 qop': 0.01417529417479696, 'y tx^2 ty^2': 0.24892206316288593, 'y tx^2 ty qop': 0.02112066742630421, 'y tx^2 qop^2': 0.001983588330826661, 'y tx ty^3': 1.0027301725129028, 'y tx ty^2 qop': -0.019989975028401157, 'y tx ty qop^2': 0.000703255023993435, 'y tx qop^3': -1.7780249221490402e-05, 'y ty^4': 5.039018301955912, 'y ty^3 qop': -0.03181545636834986, 'y ty^2 qop^2': 0.0013016040850667482, 'y ty qop^3': -4.788925524502292e-06, 'y qop^4': 8.952440180633341e-08, 'tx^5': 0.009735740982675399, 'tx^4 ty': -0.013441638488465971, 'tx^4 qop': 0.00015663907591491764, 'tx^3 ty^2': 0.008836930257445317, 'tx^3 ty qop': 4.602358365785842e-05, 'tx^3 qop^2': -1.2528198912759552e-06, 'tx^2 ty^3': 8.384431822878086e-05, 'tx^2 ty^2 qop': 3.2449454369351206e-05, 'tx^2 ty qop^2': 3.870208943851117e-06, 'tx^2 qop^3': 1.1062889336368561e-08, 'tx ty^4': 0.008284216728547011, 'tx ty^3 qop': -8.101830871580909e-05, 'tx ty^2 qop^2': 1.3999083905485367e-06, 'tx ty qop^3': -2.8838718241492492e-08, 'tx qop^4': -7.302022445954643e-11, 'ty^5': 0.033986172363938666, 'ty^4 qop': -0.00011487779463878022, 'ty^3 qop^2': 2.8267877400850516e-06, 'ty^2 qop^3': -1.0303917259481338e-08, 'ty qop^4': 1.343104287668482e-10, 'qop^5': -5.690015320531571e-16}\n", - "r2 score= 0.01281806793978646\n", - "RMSE = 0.2644569540509028\n", - "\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rad_length_frac = lost[\"rad_length_frac\"]\n", - "# @ z = 9400.mm or 770.mm\n", - "state = 1\n", - "\n", - "if state == 1:\n", - " slopex = lost[\"ideal_state_770_tx\"]\n", - " slopey = lost[\"ideal_state_770_ty\"]\n", - " x = lost[\"ideal_state_770_x\"]\n", - " y = lost[\"ideal_state_770_y\"]\n", - " qop = lost[\"ideal_state_770_qop\"]\n", - "elif state == 2:\n", - " slopex = lost[\"ideal_state_9410_tx\"]\n", - " slopey = lost[\"ideal_state_9410_ty\"]\n", - " x = lost[\"ideal_state_9410_x\"]\n", - " y = lost[\"ideal_state_9410_y\"]\n", - " qop = lost[\"ideal_state_9410_qop\"]\n", - "\n", - "data = ak.zip(\n", - " {\n", - " \"rad_length_frac\": rad_length_frac,\n", - " \"x\": x,\n", - " \"y\": y,\n", - " \"tx\": slopex,\n", - " \"ty\": slopey,\n", - " \"qop\": qop,\n", - " }\n", - ")\n", - "lin_reg, features, xx0_test, xx0_predicted = fit_linear_regression_model(\n", - " data,\n", - " \"rad_length_frac\",\n", - " [\"x\", \"y\", \"tx\", \"ty\", \"qop\"],\n", - " 5,\n", - " include_bias=True,\n", - ")\n", - "\n", - "nbins = 100\n", - "vmax = 50\n", - "\n", - "a0 = plt.hist2d(\n", - " xx0_test,\n", - " xx0_predicted,\n", - " density=False,\n", - " bins=nbins,\n", - " cmap=plt.cm.jet,\n", - " cmin=1,\n", - " vmax=vmax * stretch_factor,\n", - " range=[[-0.1, 1.0], [-0.1, 1.0]],\n", - ")\n", - "plt.plot([-0.1, 1.0], [-0.1, 1.0], marker=\"\", alpha=0.8)\n", - "plt.xlabel(f\"True $x/X_0$\")\n", - "plt.ylabel(f\"Predicted $x/X_0$\")\n", - "plt.title(f\"lost rad_length_frac\")\n", - "# ax1.set(xlim=(0,4000), ylim=(-1000,1000))\n", - "\n", - "plt.colorbar(a0[3])\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], - "source": [ - "df = pd.DataFrame({\n", - " \"phi\": phi_found,\n", - " \"eta\": eta_found,\n", - " \"rad_length_frac\": rad_length_found\n", - "})" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "ename": "RuntimeError", - "evalue": "latex was not able to process the following string:\nb'sale price $'\n\nHere is the full command invocation and its output:\n\nlatex -interaction=nonstopmode --halt-on-error --output-directory=tmpg0jlxahb 82002a6a534310632a0ec6d082310260.tex\n\nThis is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020) (preloaded format=latex)\n restricted \\write18 enabled.\nentering extended mode\n(./82002a6a534310632a0ec6d082310260.tex\nLaTeX2e <2020-02-02> patch level 5\nL3 programming layer <2020-09-24>\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/article\n.cls\nDocument Class: article 2019/12/20 v1.4l Standard LaTeX document class\n\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/size10.\nclo))\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/mathp\ntmx.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/type1cm/type\n1cm.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/cm-super/typ\ne1ec.sty\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/t1cmr.f\nd))\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/inputen\nc.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/geometry/geo\nmetry.sty\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/graphics/key\nval.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/generic/iftex/ifvt\nex.sty\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/generic/iftex/ifte\nx.sty)))\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/underscore/u\nnderscore.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/textcom\np.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/l3backend/l3\nbackend-dvips.def)\nNo file 82002a6a534310632a0ec6d082310260.aux.\n\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/ot1pt\nm.fd)\n*geometry* driver: auto-detecting\n*geometry* detected driver: dvips\n\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/ot1zt\nmcm.fd)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/omlzt\nmcm.fd)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/omszt\nmcm.fd)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/omxzt\nmcm.fd)\n! Extra }, or forgotten $.\n }\n \nl.30 {\\rmfamily sale price $}\n %\nNo pages of output.\nTranscript written on tmpg0jlxahb/82002a6a534310632a0ec6d082310260.log.\n\n\n", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/IPython/core/formatters.py:340\u001b[0m, in \u001b[0;36mBaseFormatter.__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m 338\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[1;32m 339\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 340\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mprinter\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobj\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 341\u001b[0m \u001b[38;5;66;03m# Finally look for special method names\u001b[39;00m\n\u001b[1;32m 342\u001b[0m method \u001b[38;5;241m=\u001b[39m get_real_method(obj, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprint_method)\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/IPython/core/pylabtools.py:152\u001b[0m, in \u001b[0;36mprint_figure\u001b[0;34m(fig, fmt, bbox_inches, base64, **kwargs)\u001b[0m\n\u001b[1;32m 149\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbackend_bases\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m FigureCanvasBase\n\u001b[1;32m 150\u001b[0m FigureCanvasBase(fig)\n\u001b[0;32m--> 152\u001b[0m \u001b[43mfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcanvas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprint_figure\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbytes_io\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkw\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 153\u001b[0m data \u001b[38;5;241m=\u001b[39m bytes_io\u001b[38;5;241m.\u001b[39mgetvalue()\n\u001b[1;32m 154\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m fmt \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msvg\u001b[39m\u001b[38;5;124m'\u001b[39m:\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/backend_bases.py:2158\u001b[0m, in \u001b[0;36mFigureCanvasBase.print_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)\u001b[0m\n\u001b[1;32m 2155\u001b[0m \u001b[38;5;66;03m# we do this instead of `self.figure.draw_without_rendering`\u001b[39;00m\n\u001b[1;32m 2156\u001b[0m \u001b[38;5;66;03m# so that we can inject the orientation\u001b[39;00m\n\u001b[1;32m 2157\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(renderer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m_draw_disabled\u001b[39m\u001b[38;5;124m\"\u001b[39m, nullcontext)():\n\u001b[0;32m-> 2158\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2159\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m bbox_inches:\n\u001b[1;32m 2160\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m bbox_inches \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtight\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/artist.py:95\u001b[0m, in \u001b[0;36m_finalize_rasterization..draw_wrapper\u001b[0;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(draw)\n\u001b[1;32m 94\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdraw_wrapper\u001b[39m(artist, renderer, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m---> 95\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m renderer\u001b[38;5;241m.\u001b[39m_rasterizing:\n\u001b[1;32m 97\u001b[0m renderer\u001b[38;5;241m.\u001b[39mstop_rasterizing()\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/artist.py:72\u001b[0m, in \u001b[0;36mallow_rasterization..draw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m 69\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 70\u001b[0m renderer\u001b[38;5;241m.\u001b[39mstart_filter()\n\u001b[0;32m---> 72\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/figure.py:3154\u001b[0m, in \u001b[0;36mFigure.draw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m 3151\u001b[0m \u001b[38;5;66;03m# ValueError can occur when resizing a window.\u001b[39;00m\n\u001b[1;32m 3153\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpatch\u001b[38;5;241m.\u001b[39mdraw(renderer)\n\u001b[0;32m-> 3154\u001b[0m \u001b[43mmimage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_draw_list_compositing_images\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 3155\u001b[0m \u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43martists\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msuppressComposite\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3157\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m sfig \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msubfigs:\n\u001b[1;32m 3158\u001b[0m sfig\u001b[38;5;241m.\u001b[39mdraw(renderer)\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/image.py:132\u001b[0m, in \u001b[0;36m_draw_list_compositing_images\u001b[0;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[1;32m 130\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m not_composite \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m has_images:\n\u001b[1;32m 131\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m artists:\n\u001b[0;32m--> 132\u001b[0m \u001b[43ma\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 133\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 134\u001b[0m \u001b[38;5;66;03m# Composite any adjacent images together\u001b[39;00m\n\u001b[1;32m 135\u001b[0m image_group \u001b[38;5;241m=\u001b[39m []\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/artist.py:72\u001b[0m, in \u001b[0;36mallow_rasterization..draw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m 69\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 70\u001b[0m renderer\u001b[38;5;241m.\u001b[39mstart_filter()\n\u001b[0;32m---> 72\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/axes/_base.py:3034\u001b[0m, in \u001b[0;36m_AxesBase.draw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m 3031\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m spine \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mspines\u001b[38;5;241m.\u001b[39mvalues():\n\u001b[1;32m 3032\u001b[0m artists\u001b[38;5;241m.\u001b[39mremove(spine)\n\u001b[0;32m-> 3034\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_update_title_position\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3036\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxison:\n\u001b[1;32m 3037\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _axis \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_axis_map\u001b[38;5;241m.\u001b[39mvalues():\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/axes/_base.py:2978\u001b[0m, in \u001b[0;36m_AxesBase._update_title_position\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m 2976\u001b[0m top \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmax\u001b[39m(top, bb\u001b[38;5;241m.\u001b[39mymax)\n\u001b[1;32m 2977\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m title\u001b[38;5;241m.\u001b[39mget_text():\n\u001b[0;32m-> 2978\u001b[0m \u001b[43max\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43myaxis\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_tightbbox\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# update offsetText\u001b[39;00m\n\u001b[1;32m 2979\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ax\u001b[38;5;241m.\u001b[39myaxis\u001b[38;5;241m.\u001b[39moffsetText\u001b[38;5;241m.\u001b[39mget_text():\n\u001b[1;32m 2980\u001b[0m bb \u001b[38;5;241m=\u001b[39m ax\u001b[38;5;241m.\u001b[39myaxis\u001b[38;5;241m.\u001b[39moffsetText\u001b[38;5;241m.\u001b[39mget_tightbbox(renderer)\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/axis.py:1352\u001b[0m, in \u001b[0;36mAxis.get_tightbbox\u001b[0;34m(self, renderer, for_layout_only)\u001b[0m\n\u001b[1;32m 1350\u001b[0m \u001b[38;5;66;03m# take care of label\u001b[39;00m\n\u001b[1;32m 1351\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlabel\u001b[38;5;241m.\u001b[39mget_visible():\n\u001b[0;32m-> 1352\u001b[0m bb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlabel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_window_extent\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1353\u001b[0m \u001b[38;5;66;03m# for constrained/tight_layout, we want to ignore the label's\u001b[39;00m\n\u001b[1;32m 1354\u001b[0m \u001b[38;5;66;03m# width/height because the adjustments they make can't be improved.\u001b[39;00m\n\u001b[1;32m 1355\u001b[0m \u001b[38;5;66;03m# this code collapses the relevant direction\u001b[39;00m\n\u001b[1;32m 1356\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m for_layout_only:\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/text.py:956\u001b[0m, in \u001b[0;36mText.get_window_extent\u001b[0;34m(self, renderer, dpi)\u001b[0m\n\u001b[1;32m 951\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 952\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot get window extent of text w/o renderer. You likely \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 953\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwant to call \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfigure.draw_without_rendering()\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m first.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 955\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m cbook\u001b[38;5;241m.\u001b[39m_setattr_cm(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfigure, dpi\u001b[38;5;241m=\u001b[39mdpi):\n\u001b[0;32m--> 956\u001b[0m bbox, info, descent \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_layout\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_renderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 957\u001b[0m x, y \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_unitless_position()\n\u001b[1;32m 958\u001b[0m x, y \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_transform()\u001b[38;5;241m.\u001b[39mtransform((x, y))\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/text.py:381\u001b[0m, in \u001b[0;36mText._get_layout\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m 379\u001b[0m clean_line, ismath \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_preprocess_math(line)\n\u001b[1;32m 380\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m clean_line:\n\u001b[0;32m--> 381\u001b[0m w, h, d \u001b[38;5;241m=\u001b[39m \u001b[43m_get_text_metrics_with_cache\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 382\u001b[0m \u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclean_line\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_fontproperties\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 383\u001b[0m \u001b[43m \u001b[49m\u001b[43mismath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mismath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdpi\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdpi\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 384\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 385\u001b[0m w \u001b[38;5;241m=\u001b[39m h \u001b[38;5;241m=\u001b[39m d \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/text.py:69\u001b[0m, in \u001b[0;36m_get_text_metrics_with_cache\u001b[0;34m(renderer, text, fontprop, ismath, dpi)\u001b[0m\n\u001b[1;32m 66\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Call ``renderer.get_text_width_height_descent``, caching the results.\"\"\"\u001b[39;00m\n\u001b[1;32m 67\u001b[0m \u001b[38;5;66;03m# Cached based on a copy of fontprop so that later in-place mutations of\u001b[39;00m\n\u001b[1;32m 68\u001b[0m \u001b[38;5;66;03m# the passed-in argument do not mess up the cache.\u001b[39;00m\n\u001b[0;32m---> 69\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_get_text_metrics_with_cache_impl\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 70\u001b[0m \u001b[43m \u001b[49m\u001b[43mweakref\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtext\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfontprop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mismath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdpi\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/text.py:77\u001b[0m, in \u001b[0;36m_get_text_metrics_with_cache_impl\u001b[0;34m(renderer_ref, text, fontprop, ismath, dpi)\u001b[0m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mlru_cache(\u001b[38;5;241m4096\u001b[39m)\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_get_text_metrics_with_cache_impl\u001b[39m(\n\u001b[1;32m 75\u001b[0m renderer_ref, text, fontprop, ismath, dpi):\n\u001b[1;32m 76\u001b[0m \u001b[38;5;66;03m# dpi is unused, but participates in cache invalidation (via the renderer).\u001b[39;00m\n\u001b[0;32m---> 77\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrenderer_ref\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_text_width_height_descent\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtext\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfontprop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mismath\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:213\u001b[0m, in \u001b[0;36mRendererAgg.get_text_width_height_descent\u001b[0;34m(self, s, prop, ismath)\u001b[0m\n\u001b[1;32m 211\u001b[0m _api\u001b[38;5;241m.\u001b[39mcheck_in_list([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTeX\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mTrue\u001b[39;00m, \u001b[38;5;28;01mFalse\u001b[39;00m], ismath\u001b[38;5;241m=\u001b[39mismath)\n\u001b[1;32m 212\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ismath \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTeX\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m--> 213\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_text_width_height_descent\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mismath\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 215\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ismath:\n\u001b[1;32m 216\u001b[0m ox, oy, width, height, descent, font_image \u001b[38;5;241m=\u001b[39m \\\n\u001b[1;32m 217\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmathtext_parser\u001b[38;5;241m.\u001b[39mparse(s, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdpi, prop)\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/backend_bases.py:652\u001b[0m, in \u001b[0;36mRendererBase.get_text_width_height_descent\u001b[0;34m(self, s, prop, ismath)\u001b[0m\n\u001b[1;32m 648\u001b[0m fontsize \u001b[38;5;241m=\u001b[39m prop\u001b[38;5;241m.\u001b[39mget_size_in_points()\n\u001b[1;32m 650\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ismath \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mTeX\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 651\u001b[0m \u001b[38;5;66;03m# todo: handle properties\u001b[39;00m\n\u001b[0;32m--> 652\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_texmanager\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_text_width_height_descent\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 653\u001b[0m \u001b[43m \u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfontsize\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 655\u001b[0m dpi \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpoints_to_pixels(\u001b[38;5;241m72\u001b[39m)\n\u001b[1;32m 656\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ismath:\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/texmanager.py:363\u001b[0m, in \u001b[0;36mTexManager.get_text_width_height_descent\u001b[0;34m(cls, tex, fontsize, renderer)\u001b[0m\n\u001b[1;32m 361\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m tex\u001b[38;5;241m.\u001b[39mstrip() \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 362\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m--> 363\u001b[0m dvifile \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmake_dvi\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtex\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfontsize\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 364\u001b[0m dpi_fraction \u001b[38;5;241m=\u001b[39m renderer\u001b[38;5;241m.\u001b[39mpoints_to_pixels(\u001b[38;5;241m1.\u001b[39m) \u001b[38;5;28;01mif\u001b[39;00m renderer \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 365\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m dviread\u001b[38;5;241m.\u001b[39mDvi(dvifile, \u001b[38;5;241m72\u001b[39m \u001b[38;5;241m*\u001b[39m dpi_fraction) \u001b[38;5;28;01mas\u001b[39;00m dvi:\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/texmanager.py:295\u001b[0m, in \u001b[0;36mTexManager.make_dvi\u001b[0;34m(cls, tex, fontsize)\u001b[0m\n\u001b[1;32m 293\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m TemporaryDirectory(\u001b[38;5;28mdir\u001b[39m\u001b[38;5;241m=\u001b[39mcwd) \u001b[38;5;28;01mas\u001b[39;00m tmpdir:\n\u001b[1;32m 294\u001b[0m tmppath \u001b[38;5;241m=\u001b[39m Path(tmpdir)\n\u001b[0;32m--> 295\u001b[0m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_run_checked_subprocess\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 296\u001b[0m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlatex\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m-interaction=nonstopmode\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--halt-on-error\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 297\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m--output-directory=\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mtmppath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 298\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mtexfile\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtex\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcwd\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcwd\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 299\u001b[0m (tmppath \u001b[38;5;241m/\u001b[39m Path(dvifile)\u001b[38;5;241m.\u001b[39mname)\u001b[38;5;241m.\u001b[39mreplace(dvifile)\n\u001b[1;32m 300\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m dvifile\n", - "File \u001b[0;32m/work/cetin/LHCb/reco_tuner/env/tuner_env/envs/tuner/lib/python3.10/site-packages/matplotlib/texmanager.py:258\u001b[0m, in \u001b[0;36mTexManager._run_checked_subprocess\u001b[0;34m(cls, command, tex, cwd)\u001b[0m\n\u001b[1;32m 254\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 255\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mFailed to process string with tex because \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcommand[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 256\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcould not be found\u001b[39m\u001b[38;5;124m'\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mexc\u001b[39;00m\n\u001b[1;32m 257\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m subprocess\u001b[38;5;241m.\u001b[39mCalledProcessError \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[0;32m--> 258\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 259\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{prog}\u001b[39;00m\u001b[38;5;124m was not able to process the following string:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 260\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{tex!r}\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 261\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mHere is the full command invocation and its output:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 262\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{format_command}\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 263\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{exc}\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m 264\u001b[0m prog\u001b[38;5;241m=\u001b[39mcommand[\u001b[38;5;241m0\u001b[39m],\n\u001b[1;32m 265\u001b[0m format_command\u001b[38;5;241m=\u001b[39mcbook\u001b[38;5;241m.\u001b[39m_pformat_subprocess(command),\n\u001b[1;32m 266\u001b[0m tex\u001b[38;5;241m=\u001b[39mtex\u001b[38;5;241m.\u001b[39mencode(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124municode_escape\u001b[39m\u001b[38;5;124m'\u001b[39m),\n\u001b[1;32m 267\u001b[0m exc\u001b[38;5;241m=\u001b[39mexc\u001b[38;5;241m.\u001b[39moutput\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mutf-8\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbackslashreplace\u001b[39m\u001b[38;5;124m'\u001b[39m))\n\u001b[1;32m 268\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 269\u001b[0m _log\u001b[38;5;241m.\u001b[39mdebug(report)\n\u001b[1;32m 270\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m report\n", - "\u001b[0;31mRuntimeError\u001b[0m: latex was not able to process the following string:\nb'sale price $'\n\nHere is the full command invocation and its output:\n\nlatex -interaction=nonstopmode --halt-on-error --output-directory=tmpg0jlxahb 82002a6a534310632a0ec6d082310260.tex\n\nThis is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020) (preloaded format=latex)\n restricted \\write18 enabled.\nentering extended mode\n(./82002a6a534310632a0ec6d082310260.tex\nLaTeX2e <2020-02-02> patch level 5\nL3 programming layer <2020-09-24>\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/article\n.cls\nDocument Class: article 2019/12/20 v1.4l Standard LaTeX document class\n\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/size10.\nclo))\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/mathp\ntmx.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/type1cm/type\n1cm.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/cm-super/typ\ne1ec.sty\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/t1cmr.f\nd))\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/inputen\nc.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/geometry/geo\nmetry.sty\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/graphics/key\nval.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/generic/iftex/ifvt\nex.sty\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/generic/iftex/ifte\nx.sty)))\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/underscore/u\nnderscore.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/base/textcom\np.sty)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/l3backend/l3\nbackend-dvips.def)\nNo file 82002a6a534310632a0ec6d082310260.aux.\n\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/ot1pt\nm.fd)\n*geometry* driver: auto-detecting\n*geometry* detected driver: dvips\n\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/ot1zt\nmcm.fd)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/omlzt\nmcm.fd)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/omszt\nmcm.fd)\n(/cvmfs/sft.cern.ch/lcg/external/texlive/2020/texmf-dist/tex/latex/psnfss/omxzt\nmcm.fd)\n! Extra }, or forgotten $.\n }\n \nl.30 {\\rmfamily sale price $}\n %\nNo pages of output.\nTranscript written on tmpg0jlxahb/82002a6a534310632a0ec6d082310260.log.\n\n\n" - ] - }, - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(9, 6))\n", - "\n", - "contour = sns.kdeplot(\n", - " data=df,\n", - " x=\"phi\",\n", - " y=\"eta\",\n", - " cmap=\"Greens\",\n", - " fill=True,\n", - " cbar=True,\n", - " # cbar_kws={\"label\": \"density of two variables (KDE weights)\", \"format\": \"{x:.1e}\"},\n", - ")\n", - "\n", - "ax.set_title(f\"Radiation Length Fraction $x/X_0$\", size=14)\n", - "ax.set_xlabel(f\"$\\phi$ [°]\", size=10)\n", - "ax.set_ylabel(f\"$\\eta$\", size=10)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "tuner", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/trackinglosses_rad_length_endVelo2endUT.ipynb b/trackinglosses_rad_length_endVelo2endUT.ipynb new file mode 100644 index 0000000..71e53bc --- /dev/null +++ b/trackinglosses_rad_length_endVelo2endUT.ipynb @@ -0,0 +1,1718 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import uproot\t\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import colormaps\n", + "from mpl_toolkits import mplot3d\n", + "import awkward as ak\n", + "from scipy.optimize import curve_fit\n", + "from scipy import stats\n", + "from methods.fit_linear_regression_model import fit_linear_regression_model\n", + "import sklearn\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "def round(n, k):\n", + " # function to round number 'n' up/down to nearest 'k'\n", + " # use positive k to round up\n", + " # use negative k to round down\n", + "\n", + " return n - n % k" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "41978 8523\n", + "49865\n" + ] + } + ], + "source": [ + "file = uproot.open(\n", + " \"tracking_losses_ntuple_B_EndVeloP.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n", + ")\n", + "\n", + "# selektiere nur elektronen von B->K*ee\n", + "allcolumns = file.arrays()\n", + "found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) &\n", + " (allcolumns.fromB)] # B: 9056\n", + "lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) &\n", + " (allcolumns.fromB)] # B: 1466\n", + "\n", + "electrons = allcolumns[(allcolumns.isElectron)\n", + " & (allcolumns.fromB)\n", + " & (allcolumns.eta <= 5.0)\n", + " & (allcolumns.eta >= 1.5)\n", + " & (np.abs(allcolumns.phi) < 3.142)]\n", + "\n", + "print(ak.num(found, axis=0), ak.num(lost, axis=0))\n", + "print(ak.num(electrons, axis=0))\n", + "# ak.count(found, axis=None)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "stretch factor: 0.1943140448361755\n" + ] + } + ], + "source": [ + "rad_length_found = ak.to_numpy(\n", + " found[(found.eta <= 5.0) & (found.eta >= 1.5) & (np.abs(found.phi) < 3.142)][\n", + " \"rad_length_frac\"\n", + " ]\n", + ")\n", + "eta_found = ak.to_numpy(\n", + " found[(found.eta <= 5.0) & (found.eta >= 1.5) & (np.abs(found.phi) < 3.142)][\"eta\"]\n", + ")\n", + "phi_found = ak.to_numpy(\n", + " found[(found.eta <= 5.0) & (found.eta >= 1.5) & (np.abs(found.phi) < 3.142)][\"phi\"]\n", + ")\n", + "rad_length_lost = ak.to_numpy(\n", + " lost[(lost.eta <= 5.0) & (lost.eta >= 1.5) & (np.abs(lost.phi) < 3.142)][\n", + " \"rad_length_frac\"\n", + " ]\n", + ")\n", + "eta_lost = ak.to_numpy(\n", + " lost[(lost.eta <= 5.0) & (lost.eta >= 1.5) & (np.abs(lost.phi) < 3.142)][\"eta\"]\n", + ")\n", + "phi_lost = ak.to_numpy(\n", + " lost[(lost.eta <= 5.0) & (lost.eta >= 1.5) & (np.abs(lost.phi) < 3.142)][\"phi\"]\n", + ")\n", + "\n", + "eta_a = ak.to_numpy(electrons[\"eta\"])\n", + "phi_a = ak.to_numpy(electrons[\"phi\"])\n", + "rad_length_frac_a = ak.to_numpy(electrons[\"rad_length_frac\"])\n", + "\n", + "stretch_factor = ak.num(eta_lost, axis=0) / ak.num(eta_found, axis=0)\n", + "print(\"stretch factor: \", stretch_factor)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(\n", + " rad_length_lost,\n", + " bins=100,\n", + " density=True,\n", + " alpha=0.5,\n", + " color=\"darkorange\",\n", + " histtype=\"bar\",\n", + " label=\"lost\",\n", + " range=[0, 1],\n", + ")\n", + "plt.hist(\n", + " rad_length_found,\n", + " bins=100,\n", + " density=True,\n", + " alpha=0.5,\n", + " color=\"blue\",\n", + " histtype=\"bar\",\n", + " label=\"found\",\n", + " range=[0, 1],\n", + ")\n", + "plt.xlim(0, 1)\n", + "# plt.yscale(\"log\")\n", + "plt.title(\"radiation length fraction endVelo2endUT\")\n", + "plt.xlabel(f\"$x/X_0$\")\n", + "plt.ylabel(\"a.u.\")\n", + "\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nbins = 100\n", + "vmax = 80\n", + "\n", + "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20, 8))\n", + "\n", + "a0 = ax0.hist2d(\n", + " rad_length_found,\n", + " eta_found,\n", + " density=False,\n", + " bins=nbins,\n", + " cmap=plt.cm.jet,\n", + " cmin=1,\n", + " vmax=vmax,\n", + " range=[[0, 0.6], [2, 5]],\n", + ")\n", + "ax0.set_xlabel(f\"$x/X_0$\")\n", + "ax0.set_ylabel(f\"$\\eta$\")\n", + "ax0.set_title(f\"found $\\eta$ rad_length_frac\")\n", + "\n", + "a1 = ax1.hist2d(\n", + " rad_length_lost,\n", + " eta_lost,\n", + " density=False,\n", + " bins=nbins,\n", + " cmap=plt.cm.jet,\n", + " cmin=1,\n", + " vmax=vmax * stretch_factor,\n", + " range=[[0, 0.6], [2, 5]],\n", + ")\n", + "ax1.set_xlabel(f\"$x/X_0$\")\n", + "ax1.set_ylabel(f\"$\\eta$\")\n", + "ax1.set_title(f\"lost $\\eta$ rad_length_frac\")\n", + "# ax1.set(xlim=(0,4000), ylim=(-1000,1000))\n", + "\n", + "plt.suptitle(\"radiation length fraction and eta endVelo\")\n", + "plt.colorbar(a0[3], ax=ax1)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Parameterisation for rad_length_frac:\n", + "intercept= 0.0\n", + "coef= {'1': 0.19830920321074946, 'x': -4.49175976974402e-05, 'y': 0.00039490060416272056, 'tx': 0.00015102371088508598, 'ty': -0.3004315695136339, 'qop': -15.314945266490128, 'x^2': -1.8619394568578818e-05, 'x y': -4.953907513838906e-06, 'x tx': 0.021617503882699386, 'x ty': 0.03829244150062255, 'x qop': -0.41798007270055415, 'y^2': -2.4410328131494868e-05, 'y tx': -0.03443063985633742, 'y ty': 0.024201355785359608, 'y qop': 0.069823295273139, 'tx^2': -9.507076220830514, 'tx ty': -0.3980701633198789, 'tx qop': -0.04742639222342226, 'ty^2': -5.342167619183405, 'ty qop': 0.04842038611881145, 'qop^2': 0.2070268831284635, 'x^3': 1.5823479402461545e-07, 'x^2 y': -5.806838940825474e-07, 'x^2 tx': -0.00023418353598118923, 'x^2 ty': 0.0037081774556846224, 'x^2 qop': 0.01641641113222204, 'x y^2': 6.398758958085149e-08, 'x y tx': -0.002932641224303519, 'x y ty': -0.001396824762733282, 'x y qop': -0.020888196868450136, 'x tx^2': 0.09096908124129072, 'x tx ty': -2.939755357349759, 'x tx qop': -8.73057282483271, 'x ty^2': -0.15340975596199197, 'x ty qop': 9.249941815315987, 'x qop^2': 0.030205199863621846, 'y^3': 1.6478595155078324e-07, 'y^2 tx': 0.0013152209574444013, 'y^2 ty': -0.000257931039205234, 'y^2 qop': -0.0057816482028933735, 'y tx^2': 2.685350530706497, 'y tx ty': 0.17814134491255038, 'y tx qop': 9.050929476915277, 'y ty^2': 0.10064678584510746, 'y ty qop': 4.6142369495362185, 'y qop^2': -0.00046589334175238057, 'tx^3': -0.6242025517665986, 'tx^2 ty': -0.017658603327465147, 'tx^2 qop': -0.022216794668845363, 'tx ty^2': -0.01024816705930792, 'tx ty qop': 0.024042119917448937, 'tx qop^2': 6.093129132646114e-05, 'ty^3': 0.09834545208780196, 'ty^2 qop': 0.011664187426493774, 'ty qop^2': -2.1825340747940462e-05, 'qop^3': -1.559907925017188e-06, 'x^4': -2.9483981922595603e-09, 'x^3 y': -6.13444928188045e-09, 'x^3 tx': 7.101384723817716e-06, 'x^3 ty': 7.16725431293419e-06, 'x^3 qop': 4.00953960828232e-05, 'x^2 y^2': 1.0679747086683733e-08, 'x^2 y tx': 7.616826922074438e-06, 'x^2 y ty': -3.91052449297824e-05, 'x^2 y qop': 9.93899828579223e-05, 'x^2 tx^2': -0.005400741368580057, 'x^2 tx ty': -0.009338160688408294, 'x^2 tx qop': -0.0017215190824096578, 'x^2 ty^2': 0.0007665795500993852, 'x^2 ty qop': 0.08528819041114723, 'x^2 qop^2': 8.037042310903203, 'x y^3': 8.933181749881669e-09, 'x y^2 tx': 1.766907321343325e-05, 'x y^2 ty': -2.1412010806409754e-05, 'x y^2 qop': -7.010215747540322e-05, 'x y tx^2': -0.0021778144582400415, 'x y tx ty': 0.0326584774738, 'x y tx qop': -0.1598215452174385, 'x y ty^2': 0.012945427966444779, 'x y ty qop': -0.23950569088511311, 'x y qop^2': -0.8775916738593352, 'x tx^3': 1.366672968587086, 'x tx^2 ty': 1.7459886700480327, 'x tx^2 qop': 0.4423601484422016, 'x tx ty^2': -1.0803356692637864, 'x tx ty qop': -0.0706577637682464, 'x tx qop^2': 0.006422119173581787, 'x ty^3': -2.2905272843167253, 'x ty^2 qop': -0.0063092971067729734, 'x ty qop^2': -0.001963650254414034, 'x qop^3': -1.0318719588655238e-06, 'y^4': -2.213189409516758e-09, 'y^3 tx': 7.716181404937572e-08, 'y^3 ty': 3.7462658548648164e-06, 'y^3 qop': -2.6897178570957402e-05, 'y^2 tx^2': -0.019391135282039867, 'y^2 tx ty': 0.003922857934752042, 'y^2 tx qop': 0.30048105074735626, 'y^2 ty^2': -0.0014404468920953982, 'y^2 ty qop': 0.017062949506976018, 'y^2 qop^2': -0.5172314152946776, 'y tx^3': 1.1761566789450086, 'y tx^2 ty': -1.8639649790914088, 'y tx^2 qop': -0.07088661078488609, 'y tx ty^2': -2.1282820437243197, 'y tx ty qop': -0.001276549939024397, 'y tx qop^2': -0.0019180156335069092, 'y ty^3': -0.06849699842395515, 'y ty^2 qop': -0.0351395250211265, 'y ty qop^2': -0.0005408300561230844, 'y qop^3': 4.1258598459708434e-06, 'tx^4': -0.02399482130004447, 'tx^3 ty': 0.010297903626621132, 'tx^3 qop': 0.0018304232474417028, 'tx^2 ty^2': -0.01163526658236639, 'tx^2 ty qop': -0.00029701477688915344, 'tx^2 qop^2': 2.0001744822333693e-06, 'tx ty^3': -0.014645131120788562, 'tx ty^2 qop': -2.1232731978440055e-05, 'tx ty qop^2': -3.4544969537609295e-06, 'tx qop^3': 8.78704309226661e-09, 'ty^4': -0.001422061237110601, 'ty^3 qop': -0.0001708364957408537, 'ty^2 qop^2': -7.126783100939319e-07, 'ty qop^3': 6.1964331341077185e-09, 'qop^4': -5.174168949842998e-10, 'x^5': -1.5976409084572651e-10, 'x^4 y': -1.2852829911480512e-10, 'x^4 tx': 4.777915697529167e-07, 'x^4 ty': -9.081653267184464e-07, 'x^4 qop': -7.95855762181219e-07, 'x^3 y^2': -1.3157031020227805e-10, 'x^3 y tx': 1.2230534549573235e-06, 'x^3 y ty': -1.0267895049764775e-06, 'x^3 y qop': 6.863633592146812e-06, 'x^3 tx^2': -0.0005342802093432353, 'x^3 tx ty': 0.0011253536068463917, 'x^3 tx qop': 0.0006881448740720732, 'x^3 ty^2': 0.0033717855327176985, 'x^3 ty qop': -0.006259805047891221, 'x^3 qop^2': -0.0297856432575138, 'x^2 y^3': 1.382156611384744e-10, 'x^2 y^2 tx': 1.322090420252664e-06, 'x^2 y^2 ty': 5.288591697905076e-08, 'x^2 y^2 qop': 2.9553628222434014e-06, 'x^2 y tx^2': -0.0013788732936473938, 'x^2 y tx ty': -0.005451132472848938, 'x^2 y tx qop': -0.0016912696788365421, 'x^2 y ty^2': 0.00031313327173996576, 'x^2 y ty qop': -0.00464221485985505, 'x^2 y qop^2': -0.021052188879644034, 'x^2 tx^3': 0.2645245528224416, 'x^2 tx^2 ty': -0.33220588343665813, 'x^2 tx^2 qop': -0.1711975210821735, 'x^2 tx ty^2': -2.5912873965567513, 'x^2 tx ty qop': 0.6199222216667238, 'x^2 tx qop^2': 0.26554090739446995, 'x^2 ty^3': 0.21995419222883894, 'x^2 ty^2 qop': 0.5566329227084174, 'x^2 ty qop^2': 0.007138707803204316, 'x^2 qop^3': -0.0036233474117857143, 'x y^4': 3.4643399260403385e-11, 'x y^3 tx': -3.715471736942533e-07, 'x y^3 ty': 5.088992998114605e-07, 'x y^3 qop': -2.9562267287452926e-06, 'x y^2 tx^2': 0.001848217429633696, 'x y^2 tx ty': -0.0006914744675563748, 'x y^2 tx qop': -0.0005866344884493824, 'x y^2 ty^2': -0.0007084811094364334, 'x y^2 ty qop': 0.0021049811349424605, 'x y^2 qop^2': 0.010952363514219516, 'x y tx^3': 0.4012187913820339, 'x y tx^2 ty': 4.799588041207373, 'x y tx^2 qop': 1.3345269234332224, 'x y tx ty^2': -0.3492025592669184, 'x y tx ty qop': 0.7401379477245426, 'x y tx qop^2': 0.00853019020452141, 'x y ty^3': 0.2663977835465425, 'x y ty^2 qop': -0.609737555278061, 'x y ty qop^2': 0.04129006001688038, 'x y qop^3': 0.0008163990713127198, 'x tx^4': -48.942089737430436, 'x tx^3 ty': -0.7028902863652343, 'x tx^3 qop': 0.06643076319999941, 'x tx^2 ty^2': -3.4139167347725943, 'x tx^2 ty qop': 0.004841829970654066, 'x tx^2 qop^2': 0.0007186793516648628, 'x tx ty^3': -0.2579234851632811, 'x tx ty^2 qop': 0.005881970664042852, 'x tx ty qop^2': 3.936368237569365e-06, 'x tx qop^3': -6.671449197806545e-06, 'x ty^4': -0.7419058590355208, 'x ty^3 qop': 0.0013112782683548875, 'x ty^2 qop^2': 0.00010835312377364621, 'x ty qop^3': 2.0484219462302866e-06, 'x qop^4': 2.580463321616666e-08, 'y^5': -3.2720492981752614e-12, 'y^4 tx': -5.762284480681501e-07, 'y^4 ty': 2.5788644553159656e-09, 'y^4 qop': -2.837759991436428e-07, 'y^3 tx^2': 0.0006211299557630969, 'y^3 tx ty': 0.000747045380526546, 'y^3 tx qop': 0.0020744456340701305, 'y^3 ty^2': 4.4960392427497754e-06, 'y^3 ty qop': 0.001141710321238258, 'y^3 qop^2': 0.002696814911126153, 'y^2 tx^3': -2.1363036642104674, 'y^2 tx^2 ty': 0.0687773207312733, 'y^2 tx^2 qop': 0.9871972836921945, 'y^2 tx ty^2': -0.2701567032221813, 'y^2 tx ty qop': -0.848252914690415, 'y^2 tx qop^2': 0.03660886322324573, 'y^2 ty^3': -0.005452852127128314, 'y^2 ty^2 qop': -0.7021206166732931, 'y^2 ty qop^2': -0.08018559047526934, 'y^2 qop^3': -0.00011753193330693663, 'y tx^4': -0.6680420541418445, 'y tx^3 ty': -3.384167006412971, 'y tx^3 qop': 0.006637451265825805, 'y tx^2 ty^2': -0.2331985780185122, 'y tx^2 ty qop': 0.006353552479363033, 'y tx^2 qop^2': 5.615722587673721e-06, 'y tx ty^3': -0.7572903037298312, 'y tx ty^2 qop': 0.0005634713263895614, 'y tx ty qop^2': 0.00010068765868206922, 'y tx qop^3': 2.012241389483668e-06, 'y ty^4': 1.5039421870145853, 'y ty^3 qop': -0.004362654564735129, 'y ty^2 qop^2': -0.00021869646501481262, 'y ty qop^3': 2.17774577667171e-07, 'y qop^4': -5.1794510300353154e-09, 'tx^5': -0.3290348306030112, 'tx^4 ty': -0.004713501192249353, 'tx^4 qop': 0.00039080511691431735, 'tx^3 ty^2': -0.02293656439194589, 'tx^3 ty qop': 1.795982117437259e-05, 'tx^3 qop^2': 1.3703545654537173e-06, 'tx^2 ty^3': -0.0016697750693905097, 'tx^2 ty^2 qop': 2.67609154249412e-05, 'tx^2 ty qop^2': -3.12791956432394e-08, 'tx^2 qop^3': -1.1594178303086993e-08, 'tx ty^4': -0.005076176679563355, 'tx ty^3 qop': 1.1834454126493736e-05, 'tx ty^2 qop^2': 1.9879319916637808e-07, 'tx ty qop^3': 4.055187311820455e-09, 'tx qop^4': 4.214995181248244e-11, 'ty^5': 0.010165548951092954, 'ty^4 qop': -1.6822916965291464e-05, 'ty^3 qop^2': -4.4801213131046415e-07, 'ty^2 qop^3': 7.260260169082666e-10, 'ty qop^4': -1.2734042962503632e-11, 'qop^5': -3.472724885502462e-13}\n", + "r2 score= -0.008270330873300091\n", + "RMSE = 0.10823208615961777\n", + "\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rad_length_frac = found[\"rad_length_frac\"]\n", + "# @ z = 9400.mm or 770.mm\n", + "state = 1\n", + "\n", + "if state == 1:\n", + " slopex = found[\"ideal_state_770_tx\"]\n", + " slopey = found[\"ideal_state_770_ty\"]\n", + " x = found[\"ideal_state_770_x\"]\n", + " y = found[\"ideal_state_770_y\"]\n", + " qop = found[\"ideal_state_770_qop\"]\n", + "elif state == 2:\n", + " slopex = found[\"ideal_state_9410_tx\"]\n", + " slopey = found[\"ideal_state_9410_ty\"]\n", + " x = found[\"ideal_state_9410_x\"]\n", + " y = found[\"ideal_state_9410_y\"]\n", + " qop = found[\"ideal_state_9410_qop\"]\n", + "\n", + "data = ak.zip(\n", + " {\n", + " \"rad_length_frac\": rad_length_frac,\n", + " \"x\": x,\n", + " \"y\": y,\n", + " \"tx\": slopex,\n", + " \"ty\": slopey,\n", + " \"qop\": qop,\n", + " }\n", + ")\n", + "lin_reg, features, xx0_test, xx0_predicted = fit_linear_regression_model(\n", + " data,\n", + " \"rad_length_frac\",\n", + " [\"x\", \"y\", \"tx\", \"ty\", \"qop\"],\n", + " 5,\n", + " include_bias=True,\n", + ")\n", + "\n", + "nbins = 100\n", + "vmax = 100\n", + "\n", + "a0 = plt.hist2d(\n", + " xx0_test,\n", + " xx0_predicted,\n", + " density=False,\n", + " bins=nbins,\n", + " cmap=plt.cm.jet,\n", + " cmin=1,\n", + " vmax=vmax,\n", + " range=[[0, 0.5], [0, 0.5]],\n", + ")\n", + "plt.plot([0, 0.5], [0, 0.5], marker=\"\", alpha=0.8)\n", + "plt.xlabel(f\"True $x/X_0$\")\n", + "plt.ylabel(f\"Predicted $x/X_0$\")\n", + "plt.title(f\"found rad_length_frac\")\n", + "\n", + "plt.colorbar(a0[3])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nbins = 100\n", + "vmax = 80\n", + "\n", + "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(15, 6))\n", + "\n", + "# ax0.set_aspect(\"equal\")\n", + "\n", + "a0 = ax0.hist2d(\n", + " xx0_test,\n", + " xx0_predicted,\n", + " density=False,\n", + " bins=nbins,\n", + " cmap=plt.cm.jet,\n", + " cmin=1,\n", + " vmax=vmax,\n", + " range=[[0, 0.5], [0, 0.5]],\n", + ")\n", + "ax0.plot([0, 0.5], [0, 0.5], marker=\"\", alpha=0.8)\n", + "ax0.set_box_aspect(1)\n", + "ax0.set_xlabel(f\"True $x/X_0$\")\n", + "ax0.set_ylabel(f\"Predicted $x/X_0$\")\n", + "ax0.set_title(f\"found rad_length_frac\")\n", + "plt.colorbar(a0[3], ax=ax0)\n", + "\n", + "ax1.hist(\n", + " xx0_test,\n", + " bins=100,\n", + " density=True,\n", + " alpha=0.5,\n", + " color=\"darkorange\",\n", + " histtype=\"bar\",\n", + " label=\"test\",\n", + " range=[0, 0.5],\n", + ")\n", + "ax1.hist(\n", + " xx0_predicted,\n", + " bins=100,\n", + " density=True,\n", + " alpha=0.5,\n", + " color=\"blue\",\n", + " histtype=\"bar\",\n", + " label=\"predicted\",\n", + " range=[0, 0.5],\n", + ")\n", + "ax1.set_xlim(0, 0.5)\n", + "ax1.set_title(\"radiation length fraction endVelo\")\n", + "ax1.set_xlabel(f\"$x/X_0$\")\n", + "ax1.set_ylabel(\"a.u.\")\n", + "ax1.set_box_aspect(1)\n", + "\n", + "ax1.legend()\n", + "\n", + "# plt.gca().set_aspect(\"equal\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(\n", + " xx0_test,\n", + " bins=100,\n", + " density=True,\n", + " alpha=0.5,\n", + " color=\"darkorange\",\n", + " histtype=\"bar\",\n", + " label=\"test\",\n", + " range=[0, 0.5],\n", + ")\n", + "plt.hist(\n", + " xx0_predicted,\n", + " bins=100,\n", + " density=True,\n", + " alpha=0.5,\n", + " color=\"blue\",\n", + " histtype=\"bar\",\n", + " label=\"predicted\",\n", + " range=[0, 0.5],\n", + ")\n", + "plt.xlim(0, 0.5)\n", + "# plt.yscale(\"log\")\n", + "plt.title(\"radiation length fraction endVelo\")\n", + "plt.xlabel(f\"$x/X_0$\")\n", + "plt.ylabel(\"a.u.\")\n", + "\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Parameterisation for rad_length_frac:\n", + "intercept= 0.0\n", + "coef= {'1': 0.2484410418213911, 'x': -0.0007601095488043627, 'y': 0.0010569724392146917, 'tx': 0.6185505303064777, 'ty': -0.9394058560136732, 'qop': -9.741031889614183, 'x^2': -0.00016580416280366622, 'x y': 5.149038989659081e-05, 'x tx': 0.22996768886351043, 'x ty': -0.043161009059129354, 'x qop': -0.21658279194428842, 'y^2': 3.9826067539320166e-05, 'y tx': -0.033498957247677735, 'y ty': -0.08085122767618998, 'y qop': 0.06428923004582791, 'tx^2': -83.06687438225835, 'tx ty': 28.76266798578089, 'tx qop': -0.32072666519746007, 'ty^2': 32.80290436519906, 'ty qop': 0.29785759094660047, 'qop^2': 0.7177557091128425, 'x^3': -1.037888276319177e-06, 'x^2 y': 5.744977724613286e-07, 'x^2 tx': 0.0016261562680787358, 'x^2 ty': 0.00819223051446815, 'x^2 qop': 0.014940216048602184, 'x y^2': 1.55836456652794e-06, 'x y tx': -0.009042353485603404, 'x y ty': 0.002769481233443616, 'x y qop': 0.007035099510620806, 'x tx^2': -0.623629094925692, 'x tx ty': -0.5792857627094614, 'x tx qop': 3.819052794399519, 'x ty^2': -1.214138821848195, 'x ty qop': -4.179406422119741, 'x qop^2': -0.11723833703778899, 'y^3': -2.1060731703048674e-07, 'y^2 tx': -0.005136952674035623, 'y^2 ty': 0.0002523550890177065, 'y^2 qop': 0.020199755591199943, 'y tx^2': 0.8881296792413045, 'y tx ty': 2.1057062787476855, 'y tx qop': -4.322557205912296, 'y ty^2': -0.062185778412248593, 'y ty qop': -12.744670929978815, 'y qop^2': 0.10865361350283592, 'tx^3': -0.2772083890350773, 'tx^2 ty': -0.002155259913110253, 'tx^2 qop': 0.01973183125611695, 'tx ty^2': 0.2547275714314975, 'tx ty qop': -0.01267461996128659, 'tx qop^2': -0.0002315355231400779, 'ty^3': 0.12852489701010045, 'ty^2 qop': -0.03229168715651398, 'ty qop^2': 0.0001733290594162183, 'qop^3': -1.1131786479856305e-06, 'x^4': 1.4072631948636172e-09, 'x^3 y': -4.525309382774623e-08, 'x^3 tx': -5.048150129027817e-07, 'x^3 ty': 2.845994251238215e-07, 'x^3 qop': 6.161442924141475e-05, 'x^2 y^2': -1.8614020325102842e-08, 'x^2 y tx': 9.737839179148333e-05, 'x^2 y ty': -1.3038804363763035e-05, 'x^2 y qop': -8.415032085912991e-05, 'x^2 tx^2': -0.0010152847281566686, 'x^2 tx ty': -0.0032259545758118137, 'x^2 tx qop': -0.041785493301881166, 'x^2 ty^2': 0.013227443641328787, 'x^2 ty qop': 0.0035654519670473366, 'x^2 qop^2': 1.2621531315710728, 'x y^3': 3.906278722709544e-08, 'x y^2 tx': 6.858475435222999e-05, 'x y^2 ty': -5.862278080592809e-05, 'x y^2 qop': -0.00016236412225426912, 'x y tx^2': -0.06608751351613794, 'x y tx ty': -0.04864228625905696, 'x y tx qop': 0.06901548261804959, 'x y ty^2': 0.04159526642181612, 'x y ty qop': 0.28489071089527757, 'x y qop^2': 0.2535927965752249, 'x tx^3': 0.5018159233398294, 'x tx^2 ty': 0.9699678165589771, 'x tx^2 qop': 0.4741265130417677, 'x tx ty^2': 10.315681588678894, 'x tx ty qop': -0.22617149043686857, 'x tx qop^2': 0.00898570789717606, 'x ty^3': -12.737405175272935, 'x ty^2 qop': -0.014062351992903526, 'x ty qop^2': 0.005154120346378951, 'x qop^3': -4.609067543005094e-05, 'y^4': 9.455609628616912e-09, 'y^3 tx': -2.99210479094425e-05, 'y^3 ty': -2.583154312318925e-05, 'y^3 qop': 5.980622324156491e-05, 'y^2 tx^2': -0.016833583405836638, 'y^2 tx ty': 0.02458057322196644, 'y^2 tx qop': -0.169419352054439, 'y^2 ty^2': 0.02331391517451325, 'y^2 ty qop': -0.04589466917231106, 'y^2 qop^2': -1.206224538163147, 'y tx^3': 15.19059646701743, 'y tx^2 ty': 5.490478536183617, 'y tx^2 qop': -0.25278933198832354, 'y tx ty^2': -3.577260288354769, 'y tx ty qop': 0.03161480393545275, 'y tx qop^2': 0.005952281392129449, 'y ty^3': -6.821531531863169, 'y ty^2 qop': 0.09776598757839021, 'y ty qop^2': 0.0023614626852912395, 'y qop^3': -1.973415862163393e-05, 'tx^4': -0.05310859403428924, 'tx^3 ty': 0.023505514315239354, 'tx^3 qop': 0.0021762610547612377, 'tx^2 ty^2': 0.04763359558524625, 'tx^2 ty qop': -0.0009428124122745564, 'tx^2 qop^2': 1.2893218326397415e-05, 'tx ty^3': -0.018754843662608302, 'tx ty^2 qop': 4.8170564904883127e-05, 'tx ty qop^2': 1.6878183944633644e-05, 'tx qop^3': -4.12730477319448e-08, 'ty^4': 0.013919613173737298, 'ty^3 qop': 0.00022052138073417403, 'ty^2 qop^2': 9.713683885787424e-06, 'ty qop^3': -5.4325325107576684e-08, 'qop^4': 1.3416430509507416e-09, 'x^5': 2.37521113888306e-11, 'x^4 y': 6.566414079145488e-11, 'x^4 tx': -3.448894636548516e-08, 'x^4 ty': 4.817853991312404e-07, 'x^4 qop': -2.777657812425005e-06, 'x^3 y^2': 6.322311563167204e-10, 'x^3 y tx': -6.301214341419836e-07, 'x^3 y ty': 5.610926190335874e-06, 'x^3 y qop': 1.114123449319493e-05, 'x^3 tx^2': 1.3140964452713899e-05, 'x^3 tx ty': -0.0006698763738434144, 'x^3 tx qop': 0.004955643949611535, 'x^3 ty^2': -0.00020626810552818679, 'x^3 ty qop': -0.008992879337357176, 'x^3 qop^2': -0.01489312550273759, 'x^2 y^3': -1.0491474355944774e-10, 'x^2 y^2 tx': -7.058621529054676e-06, 'x^2 y^2 ty': 1.8916574067162628e-06, 'x^2 y^2 qop': 1.7843819655416482e-05, 'x^2 y tx^2': 0.0007719987709393639, 'x^2 y tx ty': -0.008372751086851777, 'x^2 y tx qop': -0.0094662761279594, 'x^2 y ty^2': -0.003982741017285164, 'x^2 y ty qop': -0.014247815997652827, 'x^2 y qop^2': -0.0933449616547058, 'x^2 tx^3': -0.00211924986590092, 'x^2 tx^2 ty': 0.1354990398386329, 'x^2 tx^2 qop': -2.4034242614405197, 'x^2 tx ty^2': 1.709794803412642, 'x^2 tx ty qop': 2.929391659772189, 'x^2 tx qop^2': -0.12899963468243164, 'x^2 ty^3': 0.41237245103458525, 'x^2 ty^2 qop': 0.9459129147227289, 'x^2 ty qop^2': 0.6716348674023994, 'x^2 qop^3': 0.0065213742878363744, 'x y^4': -3.1660363219998544e-10, 'x y^3 tx': -1.6554844943783564e-06, 'x y^3 ty': -1.8566065946856725e-06, 'x y^3 qop': -9.75035823502779e-06, 'x y^2 tx^2': 0.009680843788897421, 'x y^2 tx ty': 0.004952813049497684, 'x y^2 tx qop': -0.016925260798516226, 'x y^2 ty^2': 0.003475670476866588, 'x y^2 ty qop': 0.01417176786308785, 'x y^2 qop^2': -0.01761212366224941, 'x y tx^3': -0.15192958327351774, 'x y tx^2 ty': -0.060788822811239596, 'x y tx^2 qop': 4.3726462974483224, 'x y tx ty^2': 0.253839828387595, 'x y tx ty qop': 2.515358567018165, 'x y tx qop^2': 0.7384529496261274, 'x y ty^3': -1.4590050438376516, 'x y ty^2 qop': -4.598361895076147, 'x y ty qop^2': 0.31170679839759735, 'x y qop^3': -0.01024453299524337, 'x tx^4': 1.0757508065772434, 'x tx^3 ty': -1.6800363456087655, 'x tx^3 qop': 0.025130628317134973, 'x tx^2 ty^2': 1.1790180726236092, 'x tx^2 ty qop': 0.013852458993079927, 'x tx^2 qop^2': -0.0004548226751025624, 'x tx ty^3': -0.0007529047666109905, 'x tx ty^2 qop': 0.007719696430873407, 'x tx ty qop^2': 0.0018986412331720088, 'x tx qop^3': 7.660654451074145e-06, 'x ty^4': 1.3495131383656807, 'x ty^3 qop': -0.027518299643244655, 'x ty^2 qop^2': 0.0007835380395695195, 'x ty qop^3': -1.7215942880021808e-05, 'x qop^4': -4.814887567180262e-08, 'y^5': 1.1069811733932511e-11, 'y^4 tx': 2.5401641039479728e-06, 'y^4 ty': -3.659565095404105e-08, 'y^4 qop': -8.233519552314217e-06, 'y^3 tx^2': -0.0011440038498780267, 'y^3 tx ty': -0.003958853981003943, 'y^3 tx qop': 0.0019569523522222627, 'y^3 ty^2': 4.620362246071652e-05, 'y^3 ty qop': 0.013501593121770603, 'y^3 qop^2': 0.00013943149170339843, 'y^2 tx^3': -1.930662753166049, 'y^2 tx^2 ty': -0.6244835760091016, 'y^2 tx^2 qop': 9.706592754727314, 'y^2 tx ty^2': 1.567415053011399, 'y^2 tx ty qop': -1.8692848199146312, 'y^2 tx qop^2': 0.2576730572143735, 'y^2 ty^3': -0.02555256934016916, 'y^2 ty^2 qop': -5.570585900979827, 'y^2 ty qop^2': 0.4524728269219666, 'y^2 qop^3': -0.0012165533583740602, 'y tx^4': -1.705633938705921, 'y tx^3 ty': 0.9697939146444974, 'y tx^3 qop': 0.01417529417479696, 'y tx^2 ty^2': 0.24892206316288593, 'y tx^2 ty qop': 0.02112066742630421, 'y tx^2 qop^2': 0.001983588330826661, 'y tx ty^3': 1.0027301725129028, 'y tx ty^2 qop': -0.019989975028401157, 'y tx ty qop^2': 0.000703255023993435, 'y tx qop^3': -1.7780249221490402e-05, 'y ty^4': 5.039018301955912, 'y ty^3 qop': -0.03181545636834986, 'y ty^2 qop^2': 0.0013016040850667482, 'y ty qop^3': -4.788925524502292e-06, 'y qop^4': 8.952440180633341e-08, 'tx^5': 0.009735740982675399, 'tx^4 ty': -0.013441638488465971, 'tx^4 qop': 0.00015663907591491764, 'tx^3 ty^2': 0.008836930257445317, 'tx^3 ty qop': 4.602358365785842e-05, 'tx^3 qop^2': -1.2528198912759552e-06, 'tx^2 ty^3': 8.384431822878086e-05, 'tx^2 ty^2 qop': 3.2449454369351206e-05, 'tx^2 ty qop^2': 3.870208943851117e-06, 'tx^2 qop^3': 1.1062889336368561e-08, 'tx ty^4': 0.008284216728547011, 'tx ty^3 qop': -8.101830871580909e-05, 'tx ty^2 qop^2': 1.3999083905485367e-06, 'tx ty qop^3': -2.8838718241492492e-08, 'tx qop^4': -7.302022445954643e-11, 'ty^5': 0.033986172363938666, 'ty^4 qop': -0.00011487779463878022, 'ty^3 qop^2': 2.8267877400850516e-06, 'ty^2 qop^3': -1.0303917259481338e-08, 'ty qop^4': 1.343104287668482e-10, 'qop^5': -5.690015320531571e-16}\n", + "r2 score= 0.01281806793978646\n", + "RMSE = 0.2644569540509028\n", + "\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rad_length_frac = lost[\"rad_length_frac\"]\n", + "# @ z = 9400.mm or 770.mm\n", + "state = 1\n", + "\n", + "if state == 1:\n", + " slopex = lost[\"ideal_state_770_tx\"]\n", + " slopey = lost[\"ideal_state_770_ty\"]\n", + " x = lost[\"ideal_state_770_x\"]\n", + " y = lost[\"ideal_state_770_y\"]\n", + " qop = lost[\"ideal_state_770_qop\"]\n", + "elif state == 2:\n", + " slopex = lost[\"ideal_state_9410_tx\"]\n", + " slopey = lost[\"ideal_state_9410_ty\"]\n", + " x = lost[\"ideal_state_9410_x\"]\n", + " y = lost[\"ideal_state_9410_y\"]\n", + " qop = lost[\"ideal_state_9410_qop\"]\n", + "\n", + "data = ak.zip({\n", + " \"rad_length_frac\": rad_length_frac,\n", + " \"x\": x,\n", + " \"y\": y,\n", + " \"tx\": slopex,\n", + " \"ty\": slopey,\n", + " \"qop\": qop,\n", + "})\n", + "lin_reg, features, xx0_test, xx0_predicted = fit_linear_regression_model(\n", + " data,\n", + " \"rad_length_frac\",\n", + " [\"x\", \"y\", \"tx\", \"ty\", \"qop\"],\n", + " 5,\n", + " include_bias=True,\n", + ")\n", + "\n", + "nbins = 100\n", + "vmax = 50\n", + "\n", + "a0 = plt.hist2d(\n", + " xx0_test,\n", + " xx0_predicted,\n", + " density=False,\n", + " bins=nbins,\n", + " cmap=plt.cm.jet,\n", + " cmin=1,\n", + " vmax=vmax * stretch_factor,\n", + " range=[[-0.1, 1.0], [-0.1, 1.0]],\n", + ")\n", + "plt.plot([-0.1, 1.0], [-0.1, 1.0], marker=\"\", alpha=0.8)\n", + "plt.xlabel(f\"True $x/X_0$\")\n", + "plt.ylabel(f\"Predicted $x/X_0$\")\n", + "plt.title(f\"lost rad_length_frac\")\n", + "# ax1.set(xlim=(0,4000), ylim=(-1000,1000))\n", + "\n", + "plt.colorbar(a0[3])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame(\n", + " {\n", + " \"phi\": phi_a * 90.0 / np.pi,\n", + " \"eta\": eta_a,\n", + " \"rad_length_frac\": rad_length_frac_a,\n", + " }\n", + ")\n", + "df = df.round({\"phi\": 0, \"eta\": 1, \"rad_length_frac\": 4})" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "df_pivoted = df.pivot_table(\n", + " index=\"eta\",\n", + " columns=\"phi\",\n", + " values=\"rad_length_frac\",\n", + " margins=False,\n", + " fill_value=0,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
phi-90.0-89.0-88.0-87.0-86.0-85.0-84.0-83.0-82.0-81.0...81.082.083.084.085.086.087.088.089.090.0
eta
1.50.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000...0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
1.60.0000000.7459000.0000000.7468000.0000000.0000000.0000000.0000000.0000000.000000...0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
1.70.0000001.1784000.2952000.7435000.3790000.6148001.6933000.0000000.9300750.111500...0.3813000.0000000.0000000.3802501.1143000.7302000.4206000.0000000.3779500.000000
1.80.3811000.3860500.2434500.1689000.0000000.2298330.2299000.3906670.1659000.327267...0.2235000.2362430.8839800.2703501.3667000.1608500.0000000.2721000.2345000.124500
1.90.1530000.0000000.1422000.2394670.2955000.1509000.2735000.1610000.8676000.000000...0.2202000.1712670.1639000.1513250.1546170.2512000.1391000.1918000.2248670.144000
2.00.1510000.1377900.1395000.1416870.1625500.1600670.1614500.1490600.1694000.176289...0.1724400.1764750.1534500.1528570.1789710.1546860.1415000.1400430.1417400.134250
2.10.1322000.1376300.1473000.1367000.1398630.1655000.1507800.1492900.1522290.168450...0.1656140.1559000.1500200.1484830.1600910.1415500.1434330.1370180.1379370.137000
2.20.1382670.1361600.1373420.1367500.1383950.1613750.1558640.1503500.1488880.153114...0.1557500.1491200.1488750.1585000.1591170.1397370.1364670.1369000.1362380.146150
2.30.1401200.1351500.1363920.1360000.1352830.1387330.1623300.1561820.1479250.145092...0.1593670.1489000.1554670.1603000.1456290.1452000.1398940.1412710.1380730.141620
2.40.1463430.1371500.1408200.1371430.1344250.1386000.1538400.1626500.1544000.144275...0.1437630.1514440.1571560.1538780.1385330.1382000.1385250.1366670.1358710.139700
2.50.1385500.1377250.1354900.1349000.1364000.1372180.1392500.1566250.1594140.147300...0.1492290.1580000.1514140.1435500.1353580.1363430.1349270.1343370.1367560.136367
2.60.1377250.1346240.1351830.1341500.1356170.1342460.1353110.1443500.1581500.156129...0.1578640.1578360.1458800.1357800.1343190.1347550.1345330.1356330.1359000.134450
2.70.1358400.1351290.1329570.1329000.1331530.1328600.1351220.1369070.1488170.159080...0.1615430.1513890.1396000.1340670.1329200.1331560.1332440.1338370.1329170.134400
2.80.1461000.1393090.1387500.1386780.1366570.1357800.1359000.1332180.1400780.150836...0.1536250.1440110.1364180.1377290.1375000.1381120.1416140.1372900.1402920.144650
2.90.1386500.1370570.1401110.1364220.1358690.1367150.1384000.1339000.1408560.138470...0.1426670.1347300.1365690.1370100.1361920.1375890.1396430.1381330.1356710.143737
3.00.1405800.1322200.1326730.1323400.1323700.1323300.1323500.1323640.1323640.132875...0.1325600.1323670.1323670.1323300.1323210.1323230.1323360.1325000.1322500.131733
3.10.1408500.1335500.1322430.1331600.1322000.1350890.1336300.1353550.1360690.135850...0.1347550.1342140.1359830.1349420.1325530.1328400.1336670.1322170.1321880.140175
3.20.1418830.1388430.1374000.1384560.1358290.1347380.1331430.1329360.1338220.134731...0.1364500.1394730.1349750.1358120.1363600.1355140.1363620.1376780.1420220.136033
3.30.1394000.1363780.1371670.1349400.1324600.1363620.1332740.1328630.1365330.130312...0.1314000.1318790.1306910.1317400.1329380.1343180.1367600.1385130.1404000.146788
3.40.1410000.1307900.1292200.1293290.1309160.1292670.1286550.1324000.1286810.128758...0.1312800.1284780.1286670.1288310.1337270.1339140.1305000.1287000.1284570.136000
3.50.1339330.1402820.1357450.1476910.1270750.1345000.1303120.1462780.1283200.142617...0.1353670.1474640.1353470.1354800.1316140.1286620.1404110.1345220.1373870.137213
3.60.1571600.1501250.1905220.1634140.1533400.1824890.1466330.1742830.1646000.156060...0.1678180.1757600.1723000.1700700.1727090.1607820.1653380.1502070.1690280.172525
3.70.2126000.2035500.1826130.2170330.1965300.1927330.1968000.1966780.1944000.193862...0.2070250.2137780.1994580.1957670.2025820.1930500.2037170.1888900.1871860.219900
3.80.2580140.2268000.2145070.2208120.2128430.2131900.2148630.2147230.2254330.221414...0.2587500.2190290.2162130.2185650.2145890.2153420.2120150.2086690.2187620.209350
3.90.3124600.2596400.2296500.2630780.2520180.2372250.2377450.2972000.2988830.219567...0.2817250.2635570.2888110.2964270.2691450.2879750.3270730.3297880.2747910.319000
4.00.2617000.2656180.1584000.2760250.3536500.2745870.2894180.2506570.2472400.233933...0.2305250.3122000.2616830.3217330.2955500.3196080.2704500.3038560.3554000.277650
4.10.1419750.1467890.1882870.1799200.1780420.1987500.1698620.1836320.1332430.188200...0.2599200.1893210.2526000.1175500.1304330.2039730.1676620.1892600.1947000.145700
4.20.2086500.1728330.2401230.2705670.1747830.1877540.2578600.1798330.1615250.129600...0.2333500.3576000.2301430.1988750.1537500.2073880.2516900.1983250.1783000.300800
4.30.4887330.8945500.4389140.6665000.4364170.2239570.3154330.2876440.3465130.350088...0.3474130.6027670.6221000.7841330.2149430.3086670.2468500.6866200.1890400.310000
4.40.1043500.5076141.5305500.9096330.0000000.7792330.0986671.6915000.0995000.609345...0.2672000.2471600.7568250.6857630.5197250.5193601.2213500.1276370.1699670.296950
4.50.0000000.1046900.1185330.1215830.0928000.0927170.1000130.1002170.1033750.108060...0.0989500.0973140.0991400.1040000.1142500.0985330.0891000.1762130.1167000.106100
4.60.1044500.1035000.0952000.0966000.1003170.0979090.0995670.0955500.1014670.096550...0.0000000.1011500.1037000.1029170.0890000.1021500.1094000.1007880.1025000.000000
4.70.0943000.1014000.0994750.0987000.0950500.0950200.0959250.0998500.0000000.098260...0.0000000.0965000.0961000.0903500.0969000.0877000.0979500.0894500.0972330.094300
4.80.0000000.0943330.0977500.0995250.0949290.0890000.0926000.0952500.0951000.094150...0.0912000.0900000.1005000.0951000.0988000.0971000.0960000.0941330.0940670.000000
4.90.0922000.0923000.0917000.0884200.0926000.0890000.0851000.0906670.0906500.000000...0.0000000.0828500.0000000.0896670.0931000.0000000.0920000.0878500.0916500.000000
5.00.0000000.1411000.0762000.1191000.0000000.1785000.0900000.0984000.0000000.000000...0.3018000.1042500.1035670.0855000.0000000.0000000.0000000.0816000.0815000.000000
\n", + "

36 rows × 181 columns

\n", + "
" + ], + "text/plain": [ + "phi -90.0 -89.0 -88.0 -87.0 -86.0 -85.0 -84.0 \\\n", + "eta \n", + "1.5 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "1.6 0.000000 0.745900 0.000000 0.746800 0.000000 0.000000 0.000000 \n", + "1.7 0.000000 1.178400 0.295200 0.743500 0.379000 0.614800 1.693300 \n", + "1.8 0.381100 0.386050 0.243450 0.168900 0.000000 0.229833 0.229900 \n", + "1.9 0.153000 0.000000 0.142200 0.239467 0.295500 0.150900 0.273500 \n", + "2.0 0.151000 0.137790 0.139500 0.141687 0.162550 0.160067 0.161450 \n", + "2.1 0.132200 0.137630 0.147300 0.136700 0.139863 0.165500 0.150780 \n", + "2.2 0.138267 0.136160 0.137342 0.136750 0.138395 0.161375 0.155864 \n", + "2.3 0.140120 0.135150 0.136392 0.136000 0.135283 0.138733 0.162330 \n", + "2.4 0.146343 0.137150 0.140820 0.137143 0.134425 0.138600 0.153840 \n", + "2.5 0.138550 0.137725 0.135490 0.134900 0.136400 0.137218 0.139250 \n", + "2.6 0.137725 0.134624 0.135183 0.134150 0.135617 0.134246 0.135311 \n", + "2.7 0.135840 0.135129 0.132957 0.132900 0.133153 0.132860 0.135122 \n", + "2.8 0.146100 0.139309 0.138750 0.138678 0.136657 0.135780 0.135900 \n", + "2.9 0.138650 0.137057 0.140111 0.136422 0.135869 0.136715 0.138400 \n", + "3.0 0.140580 0.132220 0.132673 0.132340 0.132370 0.132330 0.132350 \n", + "3.1 0.140850 0.133550 0.132243 0.133160 0.132200 0.135089 0.133630 \n", + "3.2 0.141883 0.138843 0.137400 0.138456 0.135829 0.134738 0.133143 \n", + "3.3 0.139400 0.136378 0.137167 0.134940 0.132460 0.136362 0.133274 \n", + "3.4 0.141000 0.130790 0.129220 0.129329 0.130916 0.129267 0.128655 \n", + "3.5 0.133933 0.140282 0.135745 0.147691 0.127075 0.134500 0.130312 \n", + "3.6 0.157160 0.150125 0.190522 0.163414 0.153340 0.182489 0.146633 \n", + "3.7 0.212600 0.203550 0.182613 0.217033 0.196530 0.192733 0.196800 \n", + "3.8 0.258014 0.226800 0.214507 0.220812 0.212843 0.213190 0.214863 \n", + "3.9 0.312460 0.259640 0.229650 0.263078 0.252018 0.237225 0.237745 \n", + "4.0 0.261700 0.265618 0.158400 0.276025 0.353650 0.274587 0.289418 \n", + "4.1 0.141975 0.146789 0.188287 0.179920 0.178042 0.198750 0.169862 \n", + "4.2 0.208650 0.172833 0.240123 0.270567 0.174783 0.187754 0.257860 \n", + "4.3 0.488733 0.894550 0.438914 0.666500 0.436417 0.223957 0.315433 \n", + "4.4 0.104350 0.507614 1.530550 0.909633 0.000000 0.779233 0.098667 \n", + "4.5 0.000000 0.104690 0.118533 0.121583 0.092800 0.092717 0.100013 \n", + "4.6 0.104450 0.103500 0.095200 0.096600 0.100317 0.097909 0.099567 \n", + "4.7 0.094300 0.101400 0.099475 0.098700 0.095050 0.095020 0.095925 \n", + "4.8 0.000000 0.094333 0.097750 0.099525 0.094929 0.089000 0.092600 \n", + "4.9 0.092200 0.092300 0.091700 0.088420 0.092600 0.089000 0.085100 \n", + "5.0 0.000000 0.141100 0.076200 0.119100 0.000000 0.178500 0.090000 \n", + "\n", + "phi -83.0 -82.0 -81.0 ... 81.0 82.0 83.0 \\\n", + "eta ... \n", + "1.5 0.000000 0.000000 0.000000 ... 0.000000 0.000000 0.000000 \n", + "1.6 0.000000 0.000000 0.000000 ... 0.000000 0.000000 0.000000 \n", + "1.7 0.000000 0.930075 0.111500 ... 0.381300 0.000000 0.000000 \n", + "1.8 0.390667 0.165900 0.327267 ... 0.223500 0.236243 0.883980 \n", + "1.9 0.161000 0.867600 0.000000 ... 0.220200 0.171267 0.163900 \n", + "2.0 0.149060 0.169400 0.176289 ... 0.172440 0.176475 0.153450 \n", + "2.1 0.149290 0.152229 0.168450 ... 0.165614 0.155900 0.150020 \n", + "2.2 0.150350 0.148888 0.153114 ... 0.155750 0.149120 0.148875 \n", + "2.3 0.156182 0.147925 0.145092 ... 0.159367 0.148900 0.155467 \n", + "2.4 0.162650 0.154400 0.144275 ... 0.143763 0.151444 0.157156 \n", + "2.5 0.156625 0.159414 0.147300 ... 0.149229 0.158000 0.151414 \n", + "2.6 0.144350 0.158150 0.156129 ... 0.157864 0.157836 0.145880 \n", + "2.7 0.136907 0.148817 0.159080 ... 0.161543 0.151389 0.139600 \n", + "2.8 0.133218 0.140078 0.150836 ... 0.153625 0.144011 0.136418 \n", + "2.9 0.133900 0.140856 0.138470 ... 0.142667 0.134730 0.136569 \n", + "3.0 0.132364 0.132364 0.132875 ... 0.132560 0.132367 0.132367 \n", + "3.1 0.135355 0.136069 0.135850 ... 0.134755 0.134214 0.135983 \n", + "3.2 0.132936 0.133822 0.134731 ... 0.136450 0.139473 0.134975 \n", + "3.3 0.132863 0.136533 0.130312 ... 0.131400 0.131879 0.130691 \n", + "3.4 0.132400 0.128681 0.128758 ... 0.131280 0.128478 0.128667 \n", + "3.5 0.146278 0.128320 0.142617 ... 0.135367 0.147464 0.135347 \n", + "3.6 0.174283 0.164600 0.156060 ... 0.167818 0.175760 0.172300 \n", + "3.7 0.196678 0.194400 0.193862 ... 0.207025 0.213778 0.199458 \n", + "3.8 0.214723 0.225433 0.221414 ... 0.258750 0.219029 0.216213 \n", + "3.9 0.297200 0.298883 0.219567 ... 0.281725 0.263557 0.288811 \n", + "4.0 0.250657 0.247240 0.233933 ... 0.230525 0.312200 0.261683 \n", + "4.1 0.183632 0.133243 0.188200 ... 0.259920 0.189321 0.252600 \n", + "4.2 0.179833 0.161525 0.129600 ... 0.233350 0.357600 0.230143 \n", + "4.3 0.287644 0.346513 0.350088 ... 0.347413 0.602767 0.622100 \n", + "4.4 1.691500 0.099500 0.609345 ... 0.267200 0.247160 0.756825 \n", + "4.5 0.100217 0.103375 0.108060 ... 0.098950 0.097314 0.099140 \n", + "4.6 0.095550 0.101467 0.096550 ... 0.000000 0.101150 0.103700 \n", + "4.7 0.099850 0.000000 0.098260 ... 0.000000 0.096500 0.096100 \n", + "4.8 0.095250 0.095100 0.094150 ... 0.091200 0.090000 0.100500 \n", + "4.9 0.090667 0.090650 0.000000 ... 0.000000 0.082850 0.000000 \n", + "5.0 0.098400 0.000000 0.000000 ... 0.301800 0.104250 0.103567 \n", + "\n", + "phi 84.0 85.0 86.0 87.0 88.0 89.0 90.0 \n", + "eta \n", + "1.5 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "1.6 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "1.7 0.380250 1.114300 0.730200 0.420600 0.000000 0.377950 0.000000 \n", + "1.8 0.270350 1.366700 0.160850 0.000000 0.272100 0.234500 0.124500 \n", + "1.9 0.151325 0.154617 0.251200 0.139100 0.191800 0.224867 0.144000 \n", + "2.0 0.152857 0.178971 0.154686 0.141500 0.140043 0.141740 0.134250 \n", + "2.1 0.148483 0.160091 0.141550 0.143433 0.137018 0.137937 0.137000 \n", + "2.2 0.158500 0.159117 0.139737 0.136467 0.136900 0.136238 0.146150 \n", + "2.3 0.160300 0.145629 0.145200 0.139894 0.141271 0.138073 0.141620 \n", + "2.4 0.153878 0.138533 0.138200 0.138525 0.136667 0.135871 0.139700 \n", + "2.5 0.143550 0.135358 0.136343 0.134927 0.134337 0.136756 0.136367 \n", + "2.6 0.135780 0.134319 0.134755 0.134533 0.135633 0.135900 0.134450 \n", + "2.7 0.134067 0.132920 0.133156 0.133244 0.133837 0.132917 0.134400 \n", + "2.8 0.137729 0.137500 0.138112 0.141614 0.137290 0.140292 0.144650 \n", + "2.9 0.137010 0.136192 0.137589 0.139643 0.138133 0.135671 0.143737 \n", + "3.0 0.132330 0.132321 0.132323 0.132336 0.132500 0.132250 0.131733 \n", + "3.1 0.134942 0.132553 0.132840 0.133667 0.132217 0.132188 0.140175 \n", + "3.2 0.135812 0.136360 0.135514 0.136362 0.137678 0.142022 0.136033 \n", + "3.3 0.131740 0.132938 0.134318 0.136760 0.138513 0.140400 0.146788 \n", + "3.4 0.128831 0.133727 0.133914 0.130500 0.128700 0.128457 0.136000 \n", + "3.5 0.135480 0.131614 0.128662 0.140411 0.134522 0.137387 0.137213 \n", + "3.6 0.170070 0.172709 0.160782 0.165338 0.150207 0.169028 0.172525 \n", + "3.7 0.195767 0.202582 0.193050 0.203717 0.188890 0.187186 0.219900 \n", + "3.8 0.218565 0.214589 0.215342 0.212015 0.208669 0.218762 0.209350 \n", + "3.9 0.296427 0.269145 0.287975 0.327073 0.329788 0.274791 0.319000 \n", + "4.0 0.321733 0.295550 0.319608 0.270450 0.303856 0.355400 0.277650 \n", + "4.1 0.117550 0.130433 0.203973 0.167662 0.189260 0.194700 0.145700 \n", + "4.2 0.198875 0.153750 0.207388 0.251690 0.198325 0.178300 0.300800 \n", + "4.3 0.784133 0.214943 0.308667 0.246850 0.686620 0.189040 0.310000 \n", + "4.4 0.685763 0.519725 0.519360 1.221350 0.127637 0.169967 0.296950 \n", + "4.5 0.104000 0.114250 0.098533 0.089100 0.176213 0.116700 0.106100 \n", + "4.6 0.102917 0.089000 0.102150 0.109400 0.100788 0.102500 0.000000 \n", + "4.7 0.090350 0.096900 0.087700 0.097950 0.089450 0.097233 0.094300 \n", + "4.8 0.095100 0.098800 0.097100 0.096000 0.094133 0.094067 0.000000 \n", + "4.9 0.089667 0.093100 0.000000 0.092000 0.087850 0.091650 0.000000 \n", + "5.0 0.085500 0.000000 0.000000 0.000000 0.081600 0.081500 0.000000 \n", + "\n", + "[36 rows x 181 columns]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_pivoted" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.heatmap(\n", + " df_pivoted,\n", + " robust=True,\n", + " square=False,\n", + " cmap=colormaps[\"rainbow\"],\n", + " xticklabels=False,\n", + " yticklabels=False,\n", + " vmax=0.7,\n", + ")\n", + "ax.set_yticks([5, 15, 25, 35], [2, 3, 4, 5])\n", + "ax.set_xticks([39, 89, 139],\n", + " [-100, 0, 100]) # ([79, 179, 279], [-100, 0, 100])\n", + "ax.set_xlabel(f\"$\\phi$ [deg]\")\n", + "ax.set_ylabel(f\"$\\eta$\")\n", + "\n", + "# ax.set_yticklabels([])\n", + "ax.invert_yaxis()\n", + "ax.set_title(\"LHCb EndVelo to EndUT $x/X_0$\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# make these smaller to increase the resolution\n", + "dy, dx = 0.1, 1.0\n", + "\n", + "# generate 2 2d grids for the x & y bounds\n", + "y, x = np.mgrid[slice(1.5, 5 + dy, dy), slice(-180, 180 + dx, dx)]\n", + "\n", + "plt.pcolormesh(x, y, df_pivoted, cmap=colormaps[\"jet\"], vmax=0.7)\n", + "\n", + "plt.colorbar()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "tuner", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}