From bc53f89cceece55f44025cea3894c4c6b95265c7 Mon Sep 17 00:00:00 2001 From: beckynevin Date: Fri, 29 Sep 2023 23:10:12 -0600 Subject: [PATCH] SBI works for ungrouped model --- notebooks/SBI.ipynb | 364 +++++++++----------------------------------- 1 file changed, 70 insertions(+), 294 deletions(-) diff --git a/notebooks/SBI.ipynb b/notebooks/SBI.ipynb index 19a2f31..3b3cdb9 100644 --- a/notebooks/SBI.ipynb +++ b/notebooks/SBI.ipynb @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 2, "id": "4a76432d", "metadata": {}, "outputs": [ @@ -64,7 +64,7 @@ "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[16], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mdeepbench\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mphysics_object\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Pendulum\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(deepbench\u001b[38;5;241m.\u001b[39m__version__)\n\u001b[0;32m----> 4\u001b[0m \u001b[43mSTOP\u001b[49m\n\u001b[1;32m 6\u001b[0m true_L \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1.0\u001b[39m\n\u001b[1;32m 7\u001b[0m true_theta \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mpi \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m100\u001b[39m\n", + "Cell \u001b[0;32mIn[2], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mdeepbench\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mphysics_object\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Pendulum\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(deepbench\u001b[38;5;241m.\u001b[39m__version__)\n\u001b[0;32m----> 4\u001b[0m \u001b[43mSTOP\u001b[49m\n\u001b[1;32m 6\u001b[0m true_L \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1.0\u001b[39m\n\u001b[1;32m 7\u001b[0m true_theta \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mpi \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m100\u001b[39m\n", "\u001b[0;31mNameError\u001b[0m: name 'STOP' is not defined" ] } @@ -72,54 +72,7 @@ "source": [ "import deepbench\n", "from deepbench.physics_object import Pendulum\n", - "print(deepbench.__version__)\n", - "STOP\n", - "\n", - "true_L = 1.0\n", - "true_theta = np.pi / 100\n", - "true_a = 9.8\n", - "percent_error = 0.1\n", - "dL = percent_error * true_L\n", - "\n", - "pendulum = Pendulum(\n", - " pendulum_arm_length=true_L,\n", - " starting_angle_radians=true_theta,\n", - " acceleration_due_to_gravity=true_a,\n", - " noise_std_percent={\n", - " \"pendulum_arm_length\": percent_error,\n", - " \"starting_angle_radians\": 0.0,\n", - " \"acceleration_due_to_gravity\": 0.0,\n", - " },\n", - " )\n", - "\n", - "time = np.linspace(0,2,100)\n", - "print(time)\n", - "one_time = 0.75\n", - "\n", - "pendulum_noisy = pendulum.create_object(time, noiseless=False)\n", - "pendulum_noiseless = pendulum.create_object(time, noiseless=True)\n", - "\n", - "pendulum_noisy_one = pendulum.create_object(one_time, noiseless=False)\n", - "pendulum_noiseless_one = pendulum.create_object(one_time, noiseless=True)\n", - "\n", - "\n", - "plt.clf()\n", - "plt.plot(time, pendulum_noisy, color = '#832161')\n", - "plt.scatter(time, pendulum_noisy, label = 'Noisy draws', color = '#832161')\n", - "plt.scatter(one_time, pendulum_noisy_one, label = 'Noisy draws one', color = '#ED474A')\n", - "plt.plot(time, pendulum_noiseless, color = '#EDCBB1')\n", - "plt.scatter(time, pendulum_noiseless, label = 'Noise free draws', \n", - " color = '#EDCBB1')\n", - "plt.scatter(one_time, pendulum_noiseless_one, label = 'Noise free draws one', \n", - " color = '#6883BA')\n", - "legend = plt.legend(loc=\"upper right\", edgecolor=\"black\")\n", - "legend.get_frame().set_alpha(1.0)\n", - "plt.xlabel('time [s]')\n", - "plt.ylabel('x position of pendulum')\n", - "plt.show()\n", - "\n", - "print(pendulum_noisy)\n", - "print(pendulum_noiseless)\n" + "print(deepbench.__version__)\n" ] }, { @@ -146,213 +99,6 @@ { "cell_type": "code", "execution_count": 4, - "id": "63760eba", - "metadata": {}, - "outputs": [], - "source": [ - "# okay now make a dataframe with a bunch of different options for the parameters\n", - "# generate the L, theta, a_g values somewhat randomly between ranges\n", - "length_percent_error_all = 0.0\n", - "theta_percent_error_all = 0.1\n", - "a_g_percent_error_all = 0.0\n", - "pos_err = 0.0\n", - "\n", - "time = 0.75\n", - "\n", - "length_df = 1000\n", - "xs = np.zeros((length_df, 3))\n", - "y_noisy = []\n", - "\n", - "for r in range(length_df):\n", - " rs = np.random.RandomState()#2147483648)# \n", - " length = abs(rs.normal(loc=5, scale=1))\n", - " theta = abs(rs.normal(loc=np.pi/100, scale=np.pi/200))\n", - " a_g = abs(rs.normal(loc=10, scale=2))\n", - " xs[r,:] = [length, theta, a_g]\n", - " \n", - " pendulum = Pendulum(\n", - " pendulum_arm_length=length,\n", - " starting_angle_radians=theta,\n", - " acceleration_due_to_gravity=a_g,\n", - " noise_std_percent={\n", - " \"pendulum_arm_length\": length_percent_error_all,\n", - " \"starting_angle_radians\": theta_percent_error_all,\n", - " \"acceleration_due_to_gravity\": a_g_percent_error_all,\n", - " },\n", - " )\n", - " y_noisy.append(pendulum.create_object(time, noiseless=False))\n", - " del pendulum" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "b18cea86", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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w4XrmmWcUHx+vHj16aPv27Zo3b55+/vOfS5JsNpsmT56sp59+Wl27dlVCQoJmzJihuLg4jRw50t3htBrcIAsAAAC4NG5Pfl544QXNmDFDv/rVr3To0CHFxcXpl7/8pWbOnOks8/jjj6uurk4TJkxQdXW1Bg4cqHXr1ik4ONjd4QAAAACAJA8kP2FhYVqwYIEWLFhw3jI2m02zZ8/W7Nmz3f3nAcBytNTCKrz3AODC3D7mBwAAAAC8EckPAAAAAL9A8gMAAADAL7h9zA8AAACAlsFYv+ah5QcAAACAX6DlBwCAVshbrgZ7SxwAINHyAwAAAMBPkPwAAAAA8AskPwAAAAD8AskPAAAAAL9A8gMAAADALzDbmxc4eyacpqwHAAAA0HwkPwAA+CkusgEtizpnPbq9AQAAAPALtPwAQAvhZo8AAFiLlh8AAAAAfoHkBwAAAIBfoNsbAAAA4OXoOu0eJD8AWiW+JOAvmD0KAJqObm8AAAAA/ALJDwAAAAC/QPIDAAAAwC8w5gcAAABwI8bieS+SHwB+iy8nAAD8C93eAC8wd+5c2Ww2TZ482bnu2LFjysjIUFRUlEJDQ5Wenq6qqirrggRgqS7T1ja4AACajuQHsNi2bdv00ksvKSkpyWX9lClT9NZbb2nlypUqKCjQgQMHNGrUKIuiBAAA8H0kP4CFjh49qjFjxmjJkiW6/PLLnetramq0dOlSzZs3T4MGDVJycrJyc3O1ZcsWFRUVWRgxAACA7yL5ASyUkZGhYcOGKS0tzWV9SUmJTpw44bK+e/fuio+PV2FhYYP7cjgcqq2tdVkAAP6FbtTu4S1dS70ljtaE5AewyIoVK/TRRx8pOzv7nG2VlZUKDAxURESEy/ro6GhVVlY2uL/s7GzZ7Xbn0qlTJ0+EDQDwUnSjBhpH8gNYoKKiQo8++qiWL1+u4OBgt+wzKytLNTU1zqWiosIt+wUAeD+6UQNNQ/IDWKCkpESHDh1Snz59FBAQoICAABUUFGjhwoUKCAhQdHS0jh8/rurqapfnVVVVKSYmpsF9BgUFKTw83GUBAPgHd3ajluhKjdaL+/wAFhg8eLB27Njhsm7cuHHq3r27pk6dqk6dOqldu3bKz89Xenq6JKmsrEz79+9XamqqFSEDALzUmW7U27ZtO2fbxXSjlk53pZ41a5a7Q211GIvje2j5ASwQFhamnj17uizt27dXVFSUevbsKbvdrvHjxyszM1Pvv/++SkpKNG7cOKWmpuqmm26yOnygRSxatEhJSUnOlszU1FS98847zu0M4gY8041aois1Wi9afgAvNX/+fLVp00bp6elyOBwaMmSIXnzxRavD8ntc5Ws5HTt21Ny5c9W1a1cZY/Tqq69qxIgR2r59u3r06KEpU6Zo7dq1Wrlypex2uyZOnKhRo0Zp8+bNVocOtJizu1GfcerUKW3atEl//OMftX79emc36rNbfy7UjVo63ZU6KCjIk6EDliD5AbzExo0bXR4HBwcrJydHOTk51gQEWGz48OEuj5955hktWrRIRUVF6tixo5YuXaq8vDwNGjRIkpSbm6vExEQVFRXRQgq/QTdqoHlIfgAAXu/UqVNauXKl6urqlJqa2ugg7vMlPw6HQw6Hw/mYQdzwdWe6UZ/t7G7UkpzdqCMjIxUeHq5JkybRjRp+i+QHAOC1duzYodTUVB07dkyhoaFavXq1rr/+epWWljKI2wed3W1039xhFkbiX+hGDfwfkh8AgNe67rrrVFpaqpqaGv31r3/V2LFjVVBQcNH7y8rKUmZmpvNxbW0tNwRGq0M3auD8SH4AwAJcAW+awMBAXXvttZKk5ORkbdu2TX/4wx907733MogbANBsTHUNAPAZ9fX1cjgcSk5Odg7iPoNB3ACAxtDyAwDwSllZWRo6dKji4+N15MgR5eXlaePGjVq/fr3LvbAYxA0AaCqSHwCAVzp06JAeeOABHTx4UHa7XUlJSVq/fr1+9KMfSWIQNwB8H12qG0fyAwDwSkuXLr3gdgZxAwCai+QHQKtn5ZWws/82YBXehwBwGhMeAAAAAPALJD8AAAAA/ALd3gAAAIBWhskPGuaRlp+vvvpK999/v6KiohQSEqJevXrpww8/dG43xmjmzJmKjY1VSEiI0tLStHv3bk+EAgAAAACSPJD8fPvttxowYIDatWund955Rzt37tTvf/97XX755c4yzz33nBYuXKjFixeruLhY7du315AhQ3Ts2DF3hwMAAAAAkjzQ7e3ZZ59Vp06dlJub61yXkJDg/L8xRgsWLND06dM1YsQISdJrr72m6OhorVmzRqNHj3Z3SAAAeJ3zdUmhqwoAeI7bW37efPNN9e3bV3fffbc6dOig3r17a8mSJc7t5eXlqqysVFpamnOd3W5XSkqKCgsLG9ynw+FQbW2tywIAAAAAzeH25Odf//qXFi1apK5du2r9+vV6+OGH9cgjj+jVV1+VJFVWVkqSoqOjXZ4XHR3t3PZ92dnZstvtzqVTp07uDttndZm21rkAAAAAOD+3Jz/19fXq06eP5syZo969e2vChAl66KGHtHjx4oveZ1ZWlmpqapxLRUWFGyMGAAAA4A/cnvzExsbq+uuvd1mXmJio/fv3S5JiYmIkSVVVVS5lqqqqnNu+LygoSOHh4S4LAAAAADSH25OfAQMGqKyszGXd559/rs6dO0s6PflBTEyM8vPzndtra2tVXFys1NRUd4cDAAAAAJI8MNvblClTdPPNN2vOnDm65557tHXrVr388st6+eWXJUk2m02TJ0/W008/ra5duyohIUEzZsxQXFycRo4c6e5wAAAAAECSB5Kffv36afXq1crKytLs2bOVkJCgBQsWaMyYMc4yjz/+uOrq6jRhwgRVV1dr4MCBWrdunYKDg90dDgAAAABI8kDyI0l33nmn7rzzzvNut9lsmj17tmbPnu2JPw8AAAAA5/BI8gMA7uauGz8yLTwAAP7L7RMeAAAAAIA3ouXHB3HlGgAAAGg+Wn4AAAAA+AWSHwAAAAB+gW5vrYi7BoQDAAAArREtPwAAAAD8AskPAAAAAL9A8gMAAADAL5D8AAAAAPALTHgAAIDFuH9b8zDBD4CLRcsPAAAAAL9A8gMAAADAL5D8AAAAAPALjPkB0GowbgIAAFwILT+ABRYtWqSkpCSFh4crPDxcqampeuedd5zbjx07poyMDEVFRSk0NFTp6emqqqqyMGIAAADfR8tPC+KqNM7o2LGj5s6dq65du8oYo1dffVUjRozQ9u3b1aNHD02ZMkVr167VypUrZbfbNXHiRI0aNUqbN2+2OnQAcIvzzdjGTG4APImWH8ACw4cP149//GN17dpV3bp10zPPPKPQ0FAVFRWppqZGS5cu1bx58zRo0CAlJycrNzdXW7ZsUVFRkdWhAwC8CD0JgOYh+QEsdurUKa1YsUJ1dXVKTU1VSUmJTpw4obS0NGeZ7t27Kz4+XoWFhefdj8PhUG1trcsCAGjdzvQkKCkp0YcffqhBgwZpxIgR+vTTTyVJU6ZM0VtvvaWVK1eqoKBABw4c0KhRoyyOGrAO3d4Ai+zYsUOpqak6duyYQkNDtXr1al1//fUqLS1VYGCgIiIiXMpHR0ersrLyvPvLzs7WrFmzPBw1AMCbDB8+3OXxM888o0WLFqmoqEgdO3bU0qVLlZeXp0GDBkmScnNzlZiYqKKiIt10001WhAxYipYfwCLXXXedSktLVVxcrIcfflhjx47Vzp07L3p/WVlZqqmpcS4VFRVujBYA4O3c1ZNAojcBWi9afgCLBAYG6tprr5UkJScna9u2bfrDH/6ge++9V8ePH1d1dbVL609VVZViYmLOu7+goCAFBQV5OmwAgJdxd08Cid4EaL1o+QG8RH19vRwOh5KTk9WuXTvl5+c7t5WVlWn//v1KTU21MEIAgDdyd08Cid4EaL1o+QEskJWVpaFDhyo+Pl5HjhxRXl6eNm7cqPXr18tut2v8+PHKzMxUZGSkwsPDNWnSJKWmptI/GwBwDnf3JJDoTYDWi+QHsMChQ4f0wAMP6ODBg7Lb7UpKStL69ev1ox/9SJI0f/58tWnTRunp6XI4HBoyZIhefPFFi6P2Ttw/CwBcNdSTID09XRI9CQCSH8ACS5cuveD24OBg5eTkKCcnp4UiAgD4InoSAM1D8gMAAOCj6EkANA/JDwAAgI+iJwHQPCQ/AAB4yNlj0vbNHWZhJAAAieQHACzHD2QAAFoG9/kBAAAA4BdIfgAAAAD4BZIfAAAAAH6B5AcAAACAXyD5AQAAAOAXmO0NAABY6uwZDy+lDAA0huQHAAAA8CFcDLh4dHsDAHil7Oxs9evXT2FhYerQoYNGjhypsrIylzLHjh1TRkaGoqKiFBoaqvT0dFVVVVkUMQDA25H8AAC8UkFBgTIyMlRUVKQNGzboxIkTuv3221VXV+csM2XKFL311ltauXKlCgoKdODAAY0aNcrCqAEA3oxubwAAr7Ru3TqXx8uWLVOHDh1UUlKiW265RTU1NVq6dKny8vI0aNAgSVJubq4SExNVVFSkm266yYqwAQBejJYfAIBPqKmpkSRFRkZKkkpKSnTixAmlpaU5y3Tv3l3x8fEqLCxscB8Oh0O1tbUuCwDAf9DyAwDwevX19Zo8ebIGDBignj17SpIqKysVGBioiIgIl7LR0dGqrKxscD/Z2dmaNWuWp8N1GwY1A551dh3bN3eYhZF4lr8cZ1PQ8gMA8HoZGRn65JNPtGLFikvaT1ZWlmpqapxLRUWFmyIEAPgCWn4AAF5t4sSJevvtt7Vp0yZ17NjRuT4mJkbHjx9XdXW1S+tPVVWVYmJiGtxXUFCQgoKCPB0yAMBL0fIDAD6gy7S1zsVfGGM0ceJErV69Wu+9954SEhJcticnJ6tdu3bKz893risrK9P+/fuVmpra0uECAHwALT8AAK+UkZGhvLw8vfHGGwoLC3OO47Hb7QoJCZHdbtf48eOVmZmpyMhIhYeHa9KkSUpNTWWmNwBAgzze8jN37lzZbDZNnjzZuY6b0gEAGrNo0SLV1NTotttuU2xsrHP5y1/+4iwzf/583XnnnUpPT9ctt9yimJgYrVq1ysKoAQDezKMtP9u2bdNLL72kpKQkl/VTpkzR2rVrtXLlStntdk2cOFGjRo3S5s2bPRkOAMCHGGMaLRMcHKycnBzl5OS0QEQAAF/nsZafo0ePasyYMVqyZIkuv/xy5/ozN6WbN2+eBg0apOTkZOXm5mrLli0qKiryVDgAAAAA/JzHkp+MjAwNGzbM5eZz0sXdlA4AAAAALpVHur2tWLFCH330kbZt23bOtou5KZ3D4ZDD4XA+5o7cAAAAaAmt7Qah3581tDUcU3O4veWnoqJCjz76qJYvX67g4GC37DM7O1t2u925dOrUyS37BQAAAOA/3J78lJSU6NChQ+rTp48CAgIUEBCggoICLVy4UAEBAYqOjnbelO5sF7opHXfkBgAAAHCp3N7tbfDgwdqxY4fLunHjxql79+6aOnWqOnXq5LwpXXp6uqTGb0rHHbkB/3S+G3r6y40+/eU4AQBoKW5PfsLCwtSzZ0+Xde3bt1dUVJRzPTelAwAAANDSPHqfn/OZP3++2rRpo/T0dDkcDg0ZMkQvvviiFaEAAAAA8BMtkvxs3LjR5bG/3JSOLisAAACA9/DYfX4AAAAAwJuQ/AAAAADwCyQ/AAAAAPwCyQ8AAAAAv0DyAwAAAMAvWDLVNTzv7Jnm9s0dZmEkAAAAgHcg+QEAL8IU+QAAeA7d3gALZGdnq1+/fgoLC1OHDh00cuRIlZWVuZQ5duyYMjIyFBUVpdDQUKWnp6uqqsqiiAEAAHwfyQ9ggYKCAmVkZKioqEgbNmzQiRMndPvtt6uurs5ZZsqUKXrrrbe0cuVKFRQU6MCBAxo1apSFUQMAvA0X09yny7S1zqUpZWip9010ewMssG7dOpfHy5YtU4cOHVRSUqJbbrlFNTU1Wrp0qfLy8jRo0CBJUm5urhITE1VUVKSbbrrJirABnIWxlZ7Hj8vGnbmY1q9fP508eVJPPPGEbr/9du3cuVPt27eXdPpi2tq1a7Vy5UrZ7XZNnDhRo0aN0ubNmy2OHmh5JD+AF6ipqZEkRUZGSpJKSkp04sQJpaWlOct0795d8fHxKiwsbDD5cTgccjgczse1tbUejhoAYDUupgHNQ7c3P0DzrHerr6/X5MmTNWDAAPXs2VOSVFlZqcDAQEVERLiUjY6OVmVlZYP7yc7Olt1udy6dOnXydOgAAC/T3ItpgL8h+QEslpGRoU8++UQrVqy4pP1kZWWppqbGuVRUVLgpQgCAL3DXxTTpdG+C2tpalwVoDej2Blho4sSJevvtt7Vp0yZ17NjRuT4mJkbHjx9XdXW1yxdWVVWVYmJiGtxXUFCQgoKCPB0yAMBLnbmY9sEHH1zyvrKzszVr1iw3RAV4F1p+3IwuZmgKY4wmTpyo1atX67333lNCQoLL9uTkZLVr1075+fnOdWVlZdq/f79SU1NbOlwAgJc7czHt/fffP+/FtLNd6GKaRG8CtF60/AAWyMjIUF5ent544w2FhYU5ux7Y7XaFhITIbrdr/PjxyszMVGRkpMLDwzVp0iSlpqYyOBUA4GSM0aRJk7R69Wpt3LjxghfT0tPTJTXtYhq9CdBakfwAFli0aJEk6bbbbnNZn5ubqwcffFCSNH/+fLVp00bp6elyOBwaMmSIXnzxxRaOFADgzbiYBjQPyQ9gAWNMo2WCg4OVk5OjnJycFogIAOCLuJiGS+Vv9ywj+QEAAPBRXEwDmocJDwAAAAD4BZIfAAAAAH6Bbm8AADQRtzEAAN9G8uNn/G1QGwAAAJrGH34n0u0NAAAAgF8g+QEAAADgF0h+AAAAAPgFxvwAgI/xhz7ZAAB4Ai0/AAAAAPwCyQ8AAAAAv0DyAwAAAMAvkPwAAAAA8AskPwAAAAD8AskPAAAAAL9A8gMAAADAL5D8AAAAAPAL3OQUAHwYNzwFAKDpaPkBAAAA4Bdo+QEAAECrQ8v4pWmtrx8tPwAAAAD8AskPAAAAAL9AtzcAAFrA2V1I4BmttZsOAPch+QEAAECrxsUHnEG3NwCA19q0aZOGDx+uuLg42Ww2rVmzxmW7MUYzZ85UbGysQkJClJaWpt27d1sTLADA65H8AAC8Vl1dnW644Qbl5OQ0uP25557TwoULtXjxYhUXF6t9+/YaMmSIjh071sKRAgB8Ad3eAABea+jQoRo6dGiD24wxWrBggaZPn64RI0ZIkl577TVFR0drzZo1Gj16dEuGCgDwASQ/ACzBwGT387fXtLy8XJWVlUpLS3Ous9vtSklJUWFhYYPJj8PhkMPhcD6ura1tkVgBAN6B5AcA4JMqKyslSdHR0S7ro6Ojndu+Lzs7W7NmzfJoXAysBgDv5fYxP9nZ2erXr5/CwsLUoUMHjRw5UmVlZS5ljh07poyMDEVFRSk0NFTp6emqqqpydygAALjIyspSTU2Nc6moqLA6JABAC3J78lNQUKCMjAwVFRVpw4YNOnHihG6//XbV1dU5y0yZMkVvvfWWVq5cqYKCAh04cECjRo1ydygAgFYsJiZGks65eFZVVeXc9n1BQUEKDw93WQAA/sPt3d7WrVvn8njZsmXq0KGDSkpKdMstt6impkZLly5VXl6eBg0aJEnKzc1VYmKiioqKdNNNN7k7JABAK5SQkKCYmBjl5+frxhtvlHR6DE9xcbEefvhha4MDAHglj4/5qampkSRFRkZKkkpKSnTixAmXAardu3dXfHy8CgsLG0x+GKAKAP7p6NGj2rNnj/NxeXm5SktLFRkZqfj4eE2ePFlPP/20unbtqoSEBM2YMUNxcXEaOXKkdUEDALyWR5Of+vp6TZ48WQMGDFDPnj0lnR6gGhgYqIiICJeyVg9Q9Uf+NjMUAN/z4Ycf6oc//KHzcWZmpiRp7NixWrZsmR5//HHV1dVpwoQJqq6u1sCBA7Vu3ToFBwdbFTIAwIt5NPnJyMjQJ598og8++OCS9pOVleX8wpNOt/x06tTpUsMDAHi52267TcaY82632WyaPXu2Zs+e3YJRAQB8lceSn4kTJ+rtt9/Wpk2b1LFjR+f6mJgYHT9+XNXV1S6tP40NUA0KCvJUqAAAnBdTV3u3850fejcAaIjbZ3szxmjixIlavXq13nvvPSUkJLhsT05OVrt27ZSfn+9cV1ZWpv379ys1NdXd4QAAAACAJA+0/GRkZCgvL09vvPGGwsLCnON47Ha7QkJCZLfbNX78eGVmZioyMlLh4eGaNGmSUlNTmekNaMW4eg4AAKzm9pafRYsWqaamRrfddptiY2Ody1/+8hdnmfnz5+vOO+9Uenq6brnlFsXExGjVqlXuDgXwWps2bdLw4cMVFxcnm82mNWvWuGw3xmjmzJmKjY1VSEiI0tLStHv3bmuCBQB4Nb5T4A26TFvrXLyZR7q9NbQ8+OCDzjLBwcHKycnR4cOHVVdXp1WrVp13vA/QGtXV1emGG25QTk5Og9ufe+45LVy4UIsXL1ZxcbHat2+vIUOG6NixYy0cKQDA2/GdAjSdx+/zA+BcQ4cO1dChQxvcZozRggULNH36dI0YMUKS9Nprryk6Olpr1qzR6NGjWzJUAICX4zsFaDq3t/wAuDTl5eWqrKx0uRGw3W5XSkqKCgsLz/s8h8Oh2tpalwUA4N8u9jsFaK1IfgAvc2aSkOjoaJf1F7oRsHT6ZsB2u925cC8sAMDFfqdwQQ2tFd3egFaCmwEDANwlOztbs2bNsjqMZvP2wfawHi0/gJc5M/lHVVWVy/oL3QhYOn0z4PDwcJcFAODfLvY7JSsrSzU1Nc6loqLCo3ECLYWWH1zQ96+gcJdsz0tISFBMTIzy8/N14403SjrdilNcXKyHH37Y2uAAAD7lYr9TgoKCFBQU1EJRAi2H5AewwNGjR7Vnzx7n4/LycpWWlioyMlLx8fGaPHmynn76aXXt2lUJCQmaMWOG4uLiNHLkSOuCBgB4Jb5TgKYj+QEs8OGHH+qHP/yh8/GZsTpjx47VsmXL9Pjjj6uurk4TJkxQdXW1Bg4cqHXr1ik4ONiqkFsM/bXhi3jfwkp8p8DTzv6M8/VeQCQ/kNS63tS+4LbbbpMx5rzbbTabZs+erdmzZ7dgVAAAX8R3CtB0THgAAAAAwC/Q8tMMtI7wGgAAAMB30fIDAAAAwC/Q8gMArRCttAD8BROOtCxf/34h+XGD1lbpWtvxAAAAABLd3gAAAAD4CZIfAAAAAH6Bbm8Xia5hAAAAgG8h+QFgOS4meNb3X19fHKAKAIA70O0NAAAAgF+g5QcXzdenOgQAAIB/oeUHAAAAgF8g+QEAAADgF0h+AAAAAPgFkh8AAAAAfoHkBwAAAIBfYLa3RnD/EQAAAKB1IPkB4DFcPADgDS70WcStGgD/Qrc3AAAAAH6B5AcAAACAXyD5AQAAAOAXSH4AAAAA+AUmPIBbnG8w6fkGkp5dnsGmvo/z6VuaW18BwNswoY538MXzQPIDAAD8VlMu3nCBB2g96PYGAAAAwC+Q/AAAAADwCyQ/AAAAAPwCY34AuJUvDn7EaYxrAOBt+FzyTU2ZWMeqc0vLDwAAAAC/QMsPAABAEzX3ajUtF4B38Yvk51I+qHBpmvJa8sUAAACAlkC3NwAAAAB+wS9afgC4B610aAreJ4D/aYl6T88c39fcc+iJ9xUtPwAAAAD8AskPAAAAAL9AtzcAAAC5b4Kk8z23ueUBuB/Jz/+PfqS+qaW/SBjLAAAA4LtIfgA/dilJPxcMWjduEQDA3ficgDewdMxPTk6OunTpouDgYKWkpGjr1q1WhgN4JeoJ0DjqCdA46glgYcvPX/7yF2VmZmrx4sVKSUnRggULNGTIEJWVlalDhw6XvP/m3lwT3sFd3diaetXa27uxebqeAK0B9QRoHPUEOM2ylp958+bpoYce0rhx43T99ddr8eLFuuyyy/TKK69YFRLgdagnQOOoJ0DjqCfAaZa0/Bw/flwlJSXKyspyrmvTpo3S0tJUWFh4TnmHwyGHw+F8XFNTI0mqra0979+od3zX4Pqzn3O+MvA+5zvXTTmHTX2fXKhcc8uf2WaMaXSf52NlPQHO1ty60dTnUk/gzS7l90Jzn+tt9URqfl1pyvcjdQnncynvq7O3NameGAt89dVXRpLZsmWLy/pf//rXpn///ueUf/LJJ40kFhafWyoqKqgnLCyNLNQTFpbGl5asJ9QVFl9dmlJPfGK2t6ysLGVmZjof19fX6/Dhw4qKipLNZrMwsotXW1urTp06qaKiQuHh4VaHY7nW9noYY3TkyBHFxcW12N90Rz3x5fPgy7FLvh3/xcbuC/XEl8+L5PvxSxyDFfVEsv63V2s4783B8V6a5tQTS5KfK664Qm3btlVVVZXL+qqqKsXExJxTPigoSEFBQS7rIiIiPBliiwkPD/eLN3lTtabXw263X9LzrawnvnwefDl2ybfjv5jYfaWe+PJ5kXw/fsm/j6Gl64nkPb+9WsN5bw6O9+I1tZ5YMuFBYGCgkpOTlZ+f71xXX1+v/Px8paamWhES4HWoJ0DjqCdA46gnwP+xrNtbZmamxo4dq759+6p///5asGCB6urqNG7cOKtCArwO9QRoHPUEaBz1BDjNsuTn3nvv1ddff62ZM2eqsrJSN954o9atW6fo6GirQmpRQUFBevLJJ89pUvZXvB4Na+l64svnwZdjl3w7fqtj92Q9sfrYLpWvxy9xDO7ia7+7vOE1a0kcb8uxGXMJcycCAAAAgI+w7CanAAAAANCSSH4AAAAA+AWSHwAAAAB+geQHAAAAgF8g+fGQnJwcdenSRcHBwUpJSdHWrVsvWH7lypXq3r27goOD1atXL/3tb39roUhbTnNek08//VTp6enq0qWLbDabFixY0HKB+qHs7Gz169dPYWFh6tChg0aOHKmysjKrw7ooc+fOlc1m0+TJk60OpUm++uor3X///YqKilJISIh69eqlDz/80OqwGnXq1CnNmDFDCQkJCgkJ0TXXXKOnnnpK3jaHjrs/i40xmjlzpmJjYxUSEqK0tDTt3r3bpczhw4c1ZswYhYeHKyIiQuPHj9fRo0e94hhOnDihqVOnqlevXmrfvr3i4uL0wAMP6MCBAy77OPPZe/Yyd+5cy+OXpAcffPCc2O644w6XMt58DiSdE/+Z5fnnn3eWcec58CW//e1vzznu7t27Wx2W22zatEnDhw9XXFycbDab1qxZ47K9KZ8xvqSx421KfXY7A7dbsWKFCQwMNK+88or59NNPzUMPPWQiIiJMVVVVg+U3b95s2rZta5577jmzc+dOM336dNOuXTuzY8eOFo7cc5r7mmzdutU89thj5s9//rOJiYkx8+fPb9mA/cyQIUNMbm6u+eSTT0xpaan58Y9/bOLj483Ro0etDq1Ztm7darp06WKSkpLMo48+anU4jTp8+LDp3LmzefDBB01xcbH517/+ZdavX2/27NljdWiNeuaZZ0xUVJR5++23TXl5uVm5cqUJDQ01f/jDH6wOzckTn8Vz5841drvdrFmzxnz88cfmJz/5iUlISDD/+7//6yxzxx13mBtuuMEUFRWZf/zjH+baa6819913n1ccQ3V1tUlLSzN/+ctfzGeffWYKCwtN//79TXJysst+OnfubGbPnm0OHjzoXC7m88AT52Ds2LHmjjvucInt8OHDLvvx5nNgjHGJ/eDBg+aVV14xNpvN7N2711nGXefA1zz55JOmR48eLsf99ddfWx2W2/ztb38zv/nNb8yqVauMJLN69WqX7U35jPEljR1vU+qzu5H8eED//v1NRkaG8/GpU6dMXFycyc7ObrD8PffcY4YNG+ayLiUlxfzyl7/0aJwtqbmvydk6d+5M8tPCDh06ZCSZgoICq0NpsiNHjpiuXbuaDRs2mFtvvdUnkp+pU6eagQMHWh3GRRk2bJj5+c9/7rJu1KhRZsyYMRZFdC53fxbX19ebmJgY8/zzzzu3V1dXm6CgIPPnP//ZGGPMzp07jSSzbds2Z5l33nnH2Gw289VXX1l+DA3ZunWrkWS++OIL5zp3fe56Iv6xY8eaESNGnPdv+uI5GDFihBk0aJDLOn/97nvyySfNDTfcYHUYLeL7yUBTPmN82fmSnwvVZ0+g25ubHT9+XCUlJUpLS3Oua9OmjdLS0lRYWNjgcwoLC13KS9KQIUPOW97XXMxrAmvV1NRIkiIjIy2OpOkyMjI0bNiwc+qSN3vzzTfVt29f3X333erQoYN69+6tJUuWWB1Wk9x8883Kz8/X559/Lkn6+OOP9cEHH2jo0KEWR3aaJz6Ly8vLVVlZ6VLGbrcrJSXFWaawsFARERHq27evs0xaWpratGmj4uJiy4+hITU1NbLZbIqIiHBZP3fuXEVFRal37956/vnndfLkSa+Jf+PGjerQoYOuu+46Pfzww/rmm29c9uFL56Cqqkpr167V+PHjz9l2qefAV+3evVtxcXG6+uqrNWbMGO3fv9/qkFpEUz5jWqML1WdPCPDo3v3Qv//9b506deqcOyZHR0frs88+a/A5lZWVDZavrKz0WJwt6WJeE1invr5ekydP1oABA9SzZ0+rw2mSFStW6KOPPtK2bdusDqVZ/vWvf2nRokXKzMzUE088oW3btumRRx5RYGCgxo4da3V4FzRt2jTV1taqe/fuatu2rU6dOqVnnnlGY8aMsTo0SZ75LD7zb2NlOnTo4LI9ICBAkZGRzf5Mb4nvk2PHjmnq1Km67777FB4e7lz/yCOPqE+fPoqMjNSWLVuUlZWlgwcPat68eZbHf8cdd2jUqFFKSEjQ3r179cQTT2jo0KEqLCxU27Ztfe4cvPrqqwoLC9OoUaNc1rvjHPiilJQULVu2TNddd50OHjyoWbNm6Qc/+IE++eQThYWFWR2eRzXlM6a1aaw+ewLJDwAXGRkZ+uSTT/TBBx9YHUqTVFRU6NFHH9WGDRsUHBxsdTjNUl9fr759+2rOnDmSpN69e+uTTz7R4sWLvT75ef3117V8+XLl5eWpR48eKi0t1eTJkxUXF+f1seO0EydO6J577pExRosWLXLZlpmZ6fx/UlKSAgMD9ctf/lLZ2dkKCgpq6VBdjB492vn/Xr16KSkpSddcc402btyowYMHWxjZxXnllVc0ZsyYcz6/vPkceNLZrcdJSUlKSUlR586d9frrrzfYOgbfZkV9ptubm11xxRVq27atqqqqXNZXVVUpJiamwefExMQ0q7yvuZjXBNaYOHGi3n77bb3//vvq2LGj1eE0SUlJiQ4dOqQ+ffooICBAAQEBKigo0MKFCxUQEKBTp05ZHeJ5xcbG6vrrr3dZl5iY6BNdPH79619r2rRpGj16tHr16qWf/exnmjJlirKzs60OTZJnPovP/NtYmUOHDrlsP3nypA4fPtzszztPfp+cSXy++OILbdiwwaXVpyEpKSk6efKk9u3b5xXxn+3qq6/WFVdcoT179jj34QvnQJL+8Y9/qKysTL/4xS8ajeVizkFrEBERoW7dujnPb2vWlM+Y1u779dkTSH7cLDAwUMnJycrPz3euq6+vV35+vlJTUxt8Tmpqqkt5SdqwYcN5y/uai3lN0LKMMZo4caJWr16t9957TwkJCVaH1GSDBw/Wjh07VFpa6lz69u2rMWPGqLS01GPN5u4wYMCAc6YU//zzz9W5c2eLImq67777Tm3auH6FtG3bVvX19RZF5MoTn8UJCQmKiYlxKVNbW6vi4mJnmdTUVFVXV6ukpMRZ5r333lN9fb1SUlIsPwbp/xKf3bt3691331VUVFSjsZSWlqpNmzbndCezIv7v+/LLL/XNN98oNjbWuQ9vPwdnLF26VMnJybrhhhsajeVizkFrcPToUe3du9d5fluzpnzGtHbfr88e0aLTK/iJFStWmKCgILNs2TKzc+dOM2HCBBMREWEqKyuNMcb87Gc/M9OmTXOW37x5swkICDC/+93vzK5du8yTTz7ZKqe6bs5r4nA4zPbt28327dtNbGyseeyxx8z27dvN7t27rTqEVu3hhx82drvdbNy40WW6ye+++87q0C6Kr8z2tnXrVhMQEGCeeeYZs3v3brN8+XJz2WWXmT/96U9Wh9aosWPHmquuuso51fWqVavMFVdcYR5//HGrQ3PyxGfx3LlzTUREhHnjjTfMP//5TzNixIgGp7ru3bu3KS4uNh988IHp2rXrJU2z7M5jOH78uPnJT35iOnbsaEpLS13qu8PhMMYYs2XLFjN//nxTWlpq9u7da/70pz+ZK6+80jzwwAOWx3/kyBHz2GOPmcLCQlNeXm7effdd06dPH9O1a1dz7Ngx5368+RycUVNTYy677DKzaNGic/6mO8+Br/l//+//mY0bN5ry8nKzefNmk5aWZq644gpz6NAhq0NziyNHjjh/30gy8+bNM9u3b3fOttiUzxhfcqHjbWp9djeSHw954YUXTHx8vAkMDDT9+/c3RUVFzm233nqrGTt2rEv5119/3XTr1s0EBgaaHj16mLVr17ZwxJ7XnNekvLzcSDpnufXWW1s+cD/Q0GstyeTm5lod2kXxleTHGGPeeust07NnTxMUFGS6d+9uXn75ZatDapLa2lrz6KOPmvj4eBMcHGyuvvpq85vf/Mb5A9pbuPuzuL6+3syYMcNER0eboKAgM3jwYFNWVuZS5ptvvjH33XefCQ0NNeHh4WbcuHHmyJEjXnEM5/tslWTef/99Y4wxJSUlJiUlxdjtdhMcHGwSExPNnDlzLvrHiDvj/+6778ztt99urrzyStOuXTvTuXNn89BDDzkTkTO8+Ryc8dJLL5mQkBBTXV19zjZ3nwNfcu+995rY2FgTGBhorrrqKnPvvff6xL3Pmur9999vsP6deQ815TPGl1zoeJtan93NZoyX3Y4bAAAAADyAMT8AAAAA/ALJDwAAAAC/QPIDAAAAwC+Q/AAAAADwCyQ/AAAAAPwCyQ8AAAAAv0DyAwAAAMAvkPwAaLVuu+02TZ482eowtHHjRtlsNlVXV1sdCtBsvH8BtCYkPwDgRt6ScAEXy1PvYZvNpjVr1rh9vwDQHCQ/AAAAAPwCyY+P+/rrrxUTE6M5c+Y4123ZskWBgYHKz89v8Dn79u2TzWbTihUrdPPNNys4OFg9e/ZUQUGBS7mCggL1799fQUFBio2N1bRp03Ty5Enn9r/+9a/q1auXQkJCFBUVpbS0NNXV1XnmQIFL5HA49Nhjj+mqq65S+/btlZKSoo0bNzq3L1u2TBEREVq/fr0SExMVGhqqO+64QwcPHnSWOXnypB555BFFREQoKipKU6dO1dixYzVy5EhJ0oMPPqiCggL94Q9/kM1mk81m0759+5zPLykpUd++fXXZZZfp5ptvVllZWQsdPdA0F3oPN/b+feONN9SnTx8FBwfr6quv1qxZs5zfGV26dJEk3XXXXbLZbM7He/fu1YgRIxQdHa3Q0FD169dP7777bksdLuB269at08CBA53fE3feeaf27t3bpOdu2bJFN954o4KDg9W3b1+tWbNGNptNpaWlng3a3xj4vLVr15p27dqZbdu2mdraWnP11VebKVOmnLd8eXm5kWQ6duxo/vrXv5qdO3eaX/ziFyYsLMz8+9//NsYY8+WXX5rLLrvM/OpXvzK7du0yq1evNldccYV58sknjTHGHDhwwAQEBJh58+aZ8vJy889//tPk5OSYI0eOtMQhA01y6623mkcffdQYY8wvfvELc/PNN5tNmzaZPXv2mOeff94EBQWZzz//3BhjTG5urmnXrp1JS0sz27ZtMyUlJSYxMdH89Kc/de7v6aefNpGRkWbVqlVm165d5j//8z9NeHi4GTFihDHGmOrqapOammoeeughc/DgQXPw4EFz8uRJ8/777xtJJiUlxWzcuNF8+umn5gc/+IG5+eabW/olAS6ooffwu+++2+j7d9OmTSY8PNwsW7bM7N271/z97383Xbp0Mb/97W+NMcYcOnTISDK5ubnm4MGD5tChQ8YYY0pLS83ixYvNjh07zOeff26mT59ugoODzRdffGHJ8QOX6q9//av5n//5H7N7926zfft2M3z4cNOrVy9z6tSpCz6vpqbGREZGmvvvv998+umn5m9/+5vp1q2bkWS2b9/eMsH7CZKfVuJXv/qV6datm/npT39qevXqZY4dO3besmeSn7lz5zrXnThxwnTs2NE8++yzxhhjnnjiCXPdddeZ+vp6Z5mcnBwTGhpqTp06ZUpKSowks2/fPs8dFHCJziQ/X3zxhWnbtq356quvXLYPHjzYZGVlGWNOJz+SzJ49e5zbc3JyTHR0tPNxdHS0ef75552PT548aeLj453Jz9l/82xnkp93333XuW7t2rVGkvnf//1fdxwq4Dbffw835f07ePBgM2fOHJf9/Pd//7eJjY11PpZkVq9e3ejf79Gjh3nhhRcu7SAAL/H1118bSWbHjh0XLLdo0SITFRXl8p2wZMkSkh8PoNtbK/G73/1OJ0+e1MqVK7V8+XIFBQU1+pzU1FTn/wMCAtS3b1/t2rVLkrRr1y6lpqbKZrM5ywwYMEBHjx7Vl19+qRtuuEGDBw9Wr169dPfdd2vJkiX69ttv3X9ggBvs2LFDp06dUrdu3RQaGupcCgoKXLojXHbZZbrmmmucj2NjY3Xo0CFJUk1NjaqqqtS/f3/n9rZt2yo5ObnJcSQlJbnsW5Jz/4C3u9D79+OPP9bs2bNd6tdDDz2kgwcP6rvvvjvvPo8eParHHntMiYmJioiIUGhoqHbt2qX9+/d79mAAD9m9e7fuu+8+XX311QoPD3d28WzsPV1WVqakpCQFBwc71539fQP3CbA6ALjH3r17deDAAdXX12vfvn3q1auXR/9e27ZttWHDBm3ZskV///vf9cILL+g3v/mNiouLlZCQ4NG/DTTX0aNH1bZtW5WUlKht27Yu20JDQ53/b9euncs2m80mY4zb4jh7/2cuLNTX17tt/4AnXej9e/ToUc2aNUujRo0653ln/5j7vscee0wbNmzQ7373O1177bUKCQnRf/zHf+j48eNujh5oGcOHD1fnzp21ZMkSxcXFqb6+Xj179uQ97UVo+WkFjh8/rvvvv1/33nuvnnrqKf3iF79o0tXkoqIi5/9PnjypkpISJSYmSpISExNVWFjo8sNv8+bNCgsLU8eOHSWd/vIbMGCAZs2ape3btyswMFCrV69289EBl6537946deqUDh06pGuvvdZliYmJadI+7Ha7oqOjtW3bNue6U6dO6aOPPnIpFxgYqFOnTrk1fqAlXcx7uE+fPiorKzunfl177bVq0+b0T4127dqds9/NmzfrwQcf1F133aVevXopJibGZZIQwJd88803Kisr0/Tp0zV48GAlJiY2uVfMddddpx07dsjhcDjXnf19A/ch+WkFfvOb36impkYLFy7U1KlT1a1bN/385z9v9Hk5OTlavXq1PvvsM2VkZOjbb791Pu9Xv/qVKioqNGnSJH322Wd644039OSTTyozM1Nt2rRRcXGx5syZow8//FD79+/XqlWr9PXXXzuTJ8CbdOvWTWPGjNEDDzygVatWqby8XFu3blV2drbWrl3b5P1MmjRJ2dnZeuONN1RWVqZHH31U3377rUv30C5duqi4uFj79u3Tv//9b1p24HMu5j08c+ZMvfbaa5o1a5Y+/fRT7dq1SytWrND06dNd9pufn6/KykrnD8KuXbtq1apVKi0t1ccff6yf/vSn1Bn4rMsvv1xRUVF6+eWXtWfPHr333nvKzMxs0nPPvPcnTJigXbt2af369frd734nSS7fMXADqwcd4dK8//77JiAgwPzjH/9wrisvLzfh4eHmxRdfbPA5ZyY8yMvLM/379zeBgYHm+uuvN++9955LuY0bN5p+/fqZwMBAExMTY6ZOnWpOnDhhjDFm586dZsiQIebKK680QUFBplu3bgxQhdc5e+D28ePHzcyZM02XLl1Mu3btTGxsrLnrrrvMP//5T2PM6QkP7Ha7y/NXr15tzv6YPHHihJk4caIJDw83l19+uZk6daq5++67zejRo51lysrKzE033WRCQkKMJFNeXu4cMP7tt986y23fvt25HfAm338Pn5kMpLH377p168zNN99sQkJCTHh4uOnfv795+eWXndvffPNNc+2115qAgADTuXNnY8zp76Mf/vCHJiQkxHTq1Mn88Y9/bHDSEMBXbNiwwSQmJpqgoCCTlJRkNm7c2OTJPjZv3mySkpJMYGCgSU5ONnl5eUaS+eyzzzwfuB+xGePGDu3wCfv27VNCQoK2b9+uG2+80epwAJ9VX1+vxMRE3XPPPXrqqaesDgcA0IosX75c48aNU01NjUJCQqwOp9VgwgMAaKIvvvhCf//733XrrbfK4XDoj3/8o8rLy/XTn/7U6tAAAD7utdde09VXX62rrrpKH3/8saZOnap77rmHxMfNGPMDAE3Upk0bLVu2TP369dOAAQO0Y8cOvfvuu4x1AwBc0Jw5c1ymgj97GTp0qCSpsrJS999/vxITEzVlyhTdfffdevnlly2OvPWh2xsAAADgQYcPH9bhw4cb3BYSEqKrrrqqhSPyXyQ/AAAAAPwC3d4AAAAA+AWSHwAAAAB+geQHAAAAgF8g+QEAAADgF0h+AAAAAPgFkh8AAAAAfoHkBwAAAIBfIPkBAAAA4Bf+PxMqsBIq9nQlAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.clf()\n", - "fig = plt.figure(figsize = (10,4))\n", - "ax = fig.add_subplot(141)\n", - "ax.hist(y_noisy, bins=50)\n", - "ax.set_xlabel('x pos')\n", - "ax1 = fig.add_subplot(142)\n", - "ax1.hist(xs[:,0], bins=50)\n", - "ax1.set_xlabel('length')\n", - "ax2 = fig.add_subplot(143)\n", - "ax2.hist(xs[:,1], bins=50)\n", - "ax2.set_xlabel('theta')\n", - "ax3 = fig.add_subplot(144)\n", - "ax3.hist(xs[:,2], bins=50)\n", - "ax3.set_xlabel('a_g')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "278994cc", - "metadata": {}, - "outputs": [], - "source": [ - "# we need to normalize everything\n", - "xmin = np.min(xs, axis = 0)\n", - "xmax = np.max(xs, axis = 0)\n", - "\n", - "norm_xs = (xs - xmin) / (xmax - xmin)\n", - "norm_ys = (y_noisy - np.min(y_noisy)) / (np.max(y_noisy) - np.min(y_noisy))" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "0e7c1c4a", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(900, 3) (900,)\n", - "(3,)\n" - ] - }, - { - "data": { - "image/png": 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Xoe3T1Qwzl5tu5vLYsxFabgghBAzmVEMtFqTG2mBo4tVqhpnMDKFcbrqZy2PPNihuCCFznmRN4PmIViyI0WsjaoaZClGZy003c3ns2QTdUoSQOQ+DOdVJZSwIM4RIqsi4uHn44YfR2NgIi8WC9vZ2vPXWW5rr33///ViyZAlKSkrQ0NCAG2+8EYFAIE2jJYTkI8mYwNMZr5POY6nFggBIeAwUlSRVZNQt9fTTT2PTpk145JFH0N7ejvvvvx8bNmzAgQMHUFVVFbX+r3/9a9xyyy147LHH0NHRgYMHD+Kqq66CyWTCfffdl4EzIITkA9IErnSP6HUPpDNeJxOxQcpYkD5/D7a5twjHYCR+hhlCJFWYQqFQKFMHb29vxxlnnIGHHnoIABAMBtHQ0IAbbrgBt9xyS9T6119/Pfbt24etW7eGl/3zP/8z3nzzTbz++uvCY0xMTGBiYiL8t8/nQ0NDA4aHh2Gz8QdECDlJPIGt3oAnYqKX6HBtSHrsRDqPFc8Y+vw9hoWXUqzp3Y7MPXw+H+x2u675O2NuqcnJSezYsQPr168/ORizGevXr8f27duF23R0dGDHjh1h11VXVxdeeOEFnHfeearH2bx5M+x2e/hfQ0NDck+EEJI3OCxO1JU3GxIK6XStZIMbR+1YA2PuuOJnaqzRz2TG3ZBEyZi48Xg8mJmZQXV1dcTy6upq9PX1Cbe59NJLceedd+LjH/84CgsLsXDhQpxzzjn41re+pXqcW2+9FcPDw+F/PT09ST0PQsjcJp2ulWxw46gfS+wEiCW80iXYWMNobpHxgGIjvPrqq7j77rvx7//+79i5cyeeeeYZPP/887jrrrtUtykuLobNZov4RwghySIdxdekiVnadyqPFQu1860qrROuH0t4pUOwJVqEkOQeGQsodjqdKCgoQH9/f8Ty/v5+1NTUCLe57bbbcPnll+PLX/4yAGDZsmXw+/346le/im9/+9swm3NKqxFC8oRUFl8TBRB3uDZktNCb2vnGE5SdaDB3LFjDaG6SMXFTVFSENWvWYOvWrbjgggsAzAYUb926Fddff71wm7GxsSgBU1BQAADIYFw0IYSkpPia1sRcV96sa/tUiSDR+cYr8lIpDpNZhJDkDhlNBd+0aROuvPJKrF27FmeeeSbuv/9++P1+XH311QCAK664AnV1ddi8eTMAYOPGjbjvvvuwatUqtLe3o7OzE7fddhs2btwYFjmEEJIvJDIxG00ZT5YQilfkpaoybzbEKZH0k1Fxc/HFF2NwcBC33347+vr6sHLlSrz44ovhIOMjR45EWGq+853vwGQy4Tvf+Q6OHTuGyspKbNy4Ed///vczdQqEEJIy4p2Yjbpi4qmdk0qrUDJJtduLZCcZrXOTCYzkyRNCSKaJR3gcG+nCO4PRJTVWVK6LcmfFUzsnF5uM5ooYI+oYmb/ZOJMQktXM9UkpnngUIxYfo66vXA3QZUPKuQXFDSEka8lFC0EqMDoxG3HFGHV9JTtAN9fEa66Nd65CcUMIyUpy1UKQLei1+BiNSUlmgG6uiddcG+9chuKGEJIUkv1GyxTexNFr8THi+kpWgG6uiddcG+9ch+KGEJIwqXijZQpvalAToUZcX8moS5Nr4jXXxjvXobghhCREqt5o8ymFN51xGlrHSqYITTRAN9fEa66Nd65DcUMISQi9b7TxTPCprFybLtIZp6F1rGxzq+SaeM218c51KG4IyXGCnqOA7zhgWwCzsz7tx9fzRpvIBJ+KFN50XbN0CopYx8qUW0VL1EridWDMDSCk2nwzW8gHsT1XoLghJIeZ3vkyQnu3hf8OtnVg3ur1aR1DrDfabLMYpPOapVNQxDpWut0q3oAHH5zYg8Fxd3iZSNT2+XvC90en972sz0BivZzcgOKGkBwl6DkaMUkDQGjvNgRPaU27BUfrjTabAjFTfc3kFiFfmQX+qRHheqkQFLHESzrdKkpLnYRS1KbbspVui0umrapzGYobQnIV33H15Rl4kKq90WZVIGYKr5nSIjTgsqOzMfp6pEpQ6BEvsdwqyRAAIsEiRy5q0yV8M1GfJhusqnMZihtCchXbAmPLM0RWBWIauGZGJnqRRajJPYyBijL4yi0AAEexE20Va1J63npiQtREaKICQLpe/qlRzfXkojYdwjcTbtFssqrOVShuCMlRzM56BNs6Ih6ipraOrHx4Zksgpt5rZniiV7EIWcenwuLGO+FJYOT6iScmRK8AUBN8am4oJS5rY1RtnVQL34y4RbPMqjoXobghJIeZt3o9gqe0ZtSvr9fCkS2BmLGuWVxv+ioWIX9JYeTfSZpQM1ENWk3wxXJDyXH7u2EZKo0QiqkWvhlxi+aIVTWfobghJMcxO+sz9jaYq712tK5ZPG/6IovQYZcjbLWRCIaCcY74JJmoBq0l+NSuV4vjdACzGVCi7eKtjmyUTLhFc8mqmgqyobkoxQ0hJC6yLcU7WcT7pi+3CA0WBNA580HUOmaTOaEMmkxVg9YSfGrXpWSeFWaTWXW7dN4jmXCLZoNVNRNkywsPxQ0hJC6yKcU7mSTypi9ZhIoDHsAdLW4c+97HzMFd4b+NZtCk8pprCQAtwSe6XgCwx/MmXNZG1e3STSbcopm0qmaCbHrhobghhMRFVqV4J5lE3/RFE/7SUC2KDr4esZ7RDJpUX3M1ARBL8LVWrIK1sBx7PG9GbOf2d8NlbYTb3y3cjuQX2fTCQ3FDCImLrErxTgGJvukrBZLN7caMaEUDGTSZvOaxBJ+aC6qytBaN9iUZj8EgqSebXngobgghcZMtKd7ZilwgBW0B8UoGM2iy9ZrHcl1lyzhJ6simFx6KG0JIQnDi0kcyM2gycc1jBYpm08RGMke2iG+KG0IISRO5mkGjN1A0WyY2klmy4YWH4oaQOUY21KCYK4iudS5m0BgJFM2GiY0QihtC5hDZUoMim0mW+Ev3tU6laE1WoCiFNUkXFDeEzBGyqQZFNuINePDBiT0YHHeHl8UrSFJxrbWEQaqFVDLiaSisSTqhuCFkjpCMGhS59uattxqwWuPHeAVJsut9aAmDdInWROJpKKxJuqG4IWSOkKhrIdfevKd3vhyRmaRWDThW48d4BEky633EEgbpLJwWbzxNNhV3I3MDcdUlQkjeIbkW5Oh1LahNsN6AJ6ljTBZBz9EIYQN8VA3YczRqXbWJVyIeQZLItQ56jiLY9W54rFrCQGt82VQpOhfGSPILWm4ImUPE61rIuTdv33H15Qr3lNYEa0T8Ka9pPNdaZG2ytq0UriuNWxQP47I2hr+zbPh+WAOHpBuKG0LmGPG4FnLuzVut6q9guWjirSxxYdH8Zbquk5a7TtlVW/pbJIbUrE22U1pjCgO5kBoc64Xb3x3u55Qt7kPWwCHphOKGEBKTXHvzNloNON6JN1Y8jFL4uKyNmApOijOyNKxNrc2xxycte8e/XXU8mYY1cEi6oLghhOgiE2/eiWRnGa0GHM/EGyseRil85N2xJSTxYYthbdIzvlS5D3MtS44QihtCiG7S+eadjOysVFcD1nLXxQpUluOf8sHhbI6795QkPoKhoKFx6tmn5OaSyBY3FyFaUNwQQrKOXKmLkix3nSQ+4uk9pRSB9qIKDE8OJTQetbo/QHq/h3gtRrQ0EYobQkjWkUvZWWruOpHwEaEUH0asTSIRODw5hGXOdphN5rgm91h1fwBj34PeQopK4rXc5Vo9JpIaKG4IIVmHmhslGAri2EhX1r2Rq7nr5MLn2Eg3PIHe8GdGMrLUUBOBZpMZdeXNSd2nHL1uLr2FFJXEa7lT285aWB632CO5CcUNISQrqSxxRWQV2YsqsMfzZvjvTL6Ry90eAGJmMfX5eyKEjcvaiJXVZyU8DqMp+nrcNbGEi5FihMJCiqe0xrTgxGu5U9suW+4bkj4obgghWYXSrVBZ4kKNtSFiggIyF4OjFY8imjhF1gS3vxuNgSUJj91IzI9ed41aUcDK0lrdlg9vwIOZgf0QyiRBIUUl8dZV0mNRysbYLZJ8KG4IIVmDSAgMjrthLxanSac7BidWPIpo4kx1/JCeFH2jbp5E0v4lEWWbCqBdtIJayruMeAO19cY5ZWPsFkkuFDeEkKxBPd7DJFya7grJeuJRlBOnlhXCSFaP1rqxUvTjEVjxpP3LRZSv3ILDLjua3MPhz/WmtgPxCyz5dsFQMMriB2RxZW2SNChuCCFZg9qkU1XqQjA0k/EKyXomReU6alaIPn+P7qyeRDOA0tU+QymiOhudGKgow9LCUzG/KnasjZJ46yrJt/NPjWT8viHph+KGEJIUklFbRMsd4bA4M96bKJbbQ23iVFohRia9umOIklHzJ13tM0RiyVduQYFrJcwZEhSpqqwdb4o7SQ8UN4SQhElmbRGtySgbehMtDlWifqoRfkshiqtn0631TJzS2LUCkkVuolgtHiT3S6xU53S0zxCJqKWhWtjcbgRtAaEISEfBvWTfN/GmuJP0QXFDCEmIVFQTzgYRI0Ka1IoBFAPwt7QBK8/RXVMmVkCyyPKh5joaHOuNapIJaAvLdFxXuYhy7HsfRQdfx8xHnylFQC4W3EskxZ2kD3OmB0AIyW1iWRaM4g14cGykC96AJ5FhJR3RpGbt3Iv3Dvx/2D+0S9c+tK6JmptIsobIcVmbhE04gVlhmelr57A4UTtRhKKDkdcltHcbgp6j8AY8OHj8HaEozvTYY6LRvZ1kD7TcEEISIpnBqln9Jq8yeVnHp3RbqtSuyTJnOxpsLcLPvAEPyovsES0V/FM+uP2HVY+T7FTnuFxHKtfL7d6Jd8tGVDfL+jTtGN3bSXZAcUMISYhkBatmfbNMlcnLX1I4+18dk7LatVITNiKxp8cFlswsqLgFp8r16g4NArBErjoSgHV8Cv6SQpQXjyM4+K7hQN10Ncs0O+s1u7ezaWd2QHFDSAbJlwdhMoJVs71ZpmhSO+xywFc+O1HrFRR6r1UssaeWtWVUWGrdg4kITtH18re0wVc+EbFeS7cnohYO8DvVGB010m3xU+ventWWxzkGxQ0hGSLfHoSJBqsmq9hdKpEmNbd7J7pDg2FhY1RQ6LlWscSeslidnsaQyusY6x5MVHAqRQDKLIB7S/hz20hAIWwi0ROoq0eApeL+UXZvz3rL4xyD4oaQDDDXHoR6JpdkFLtLB2ZnPeqd9ShLseDS2xld77GVQsZlbYwKSlbeg8mIp4oQAYpgYev4VOwdxOhFFUuApeslItstj3MNihtCMsBcehAamVyULhsA2CZ70weyRwSmOq1aJPbi6YzuDXgwMHZM2LxThPweTHbxP+V9L8UraRIjUDeWxS9dLxHpqgJN9EFxQ0gGyMYHYSpM9/FMLnLR8NfeV4Tr5LIINHKdY/VJinUttQoGqqG8B5NZ/E+5b1H/KTl6elFpCbBjI13CbWLdP/FUH05XFWiiD4obQjJAtj0IU2W6j8dCJU3+wVAQg+Nu4TrpFIHJFH2i6ywJh3LfOMomZqImVEnsGZ2oYxUMBKJdU1q1dpJxb4ru++CKv0HB8sqTcTkA4DuO0eICjNhKYA14DIlA+fcUz0tEItWH01EFmuiD4oaQDJEtD8JUmu6NTi56LA2VJa60Xatkij6169w1vBct3R5UuYc1s4SMXstYRRSlc2kMLEnrPah638sE3X7TILqG9wCDkWPVQiTAjL5EJKP6cLZW155rUNwQkkGy4UGYyvgfh8UZ0zogt9TocaEsmr8sYju9k3I86ycq+uTHVLvOoowh0YRqdKJWEz0tjmWoKj0pENXuwVRmqGnd98kW2zXWBphNBQBCqCqt096HVvVhtlbIKShuCJnjBENB4fJkuH72D+2KEDYua2PEG7jRmBBpMtdrUZFiJz4MebDP1BteXlniwqL5yzQnuoExsUtsYMyta5IVZSeJUM0YEkyoRmrk+Kd8QmG5eMFyw2NPZ4ZaMsW28jyCoaD2Plh9OG/IeG+phx9+GI2NjbBYLGhvb8dbb72lub7X68V1112H2tpaFBcXY/HixXjhhRfSNFpC8ov9Q7uiglSBkyIikT5Pojdwt787vC89MSHAbGuCFZXr0OHagNaKVapv9soxTu98GTMvPoaZbc+hfvvraOk++fnguBvb3Fti9IQKGVx+si9Wj69TeO4igaOaMaQyoTosTtSVN2sGEW9zb8E7g9vDx5Rfv1jovb6pIlnB9vGch9lZD1NbR8QyPUHNJPvIqOXm6aefxqZNm/DII4+gvb0d999/PzZs2IADBw6gqqoqav3JyUn83d/9HaqqqvDb3/4WdXV1+PDDD+FwONI/eEJyHDVxIfU5SvTtPdYb+MDYsZj7aLa3obzIEbEvPW/2otiJJvcwBirKwoX3AG13R8k8q/A4ast1xQuV1qLRfjLGpc/fgy7sjcoYmlyyCtY4JlTpO5W3M3CjG432JbqtHpkuU5CsYPt4z0Ot+jDJLTIqbu677z585StfwdVXXw0AeOSRR/D888/jsccewy233BK1/mOPPYbjx49j27ZtKCycfdtpbGzUPMbExAQmJk6W+/b54utUTEi+ofbwN5vMSYl70HoD1xIC8gaRff6eiDo3UnZRzONpNLmUixtAfbIzm8SGbdFyvVYoZeE9h8U562aq9KGrdz/Gjh+Bv6QQvnIfmod2GXYF+ad8Ue0MDrvs8FfqFybZUKYgGcH2iZyHsvowyT0y5paanJzEjh07sH79yYwAs9mM9evXY/v27cJtfv/732PdunW47rrrUF1djdNPPx133303ZmZmhOsDwObNm2G328P/GhrED0ZC5hpaD3+tt169OCxO2IsqIpZJf6sJAamJpNQcUiSwpPWU20VMgDGaXMoxOgmKluu5Llpp1tZCGw7NO4HeqvKw+IrHFVTuG48KTm5yD6PcN657H5LlRM/YJRJxX2qNQ8v9pmd7o+dB8oeMWW48Hg9mZmZQXV0dsby6uhr79+8XbtPV1YU//vGPuOyyy/DCCy+gs7MT1157LaampnDHHXcIt7n11luxadOm8N8+n48ChxDEZ/4fHOvV1ZUamJ3whieHIpYNTw6pBuq2OJZFBLtqCaxYb/axmlxKyGOLpIyt8ekxSJk1eq9PolaNZLmCzKNeQ8vVULu+ogyqbO6Rli3lFkj6yalsqWAwiKqqKvzsZz9DQUEB1qxZg2PHjuFHP/qRqrgpLi5GcXFxmkdKSPYin6DUHv6iFG5gNii2wleNBltLzOOoWzNOBuTKY0OqXK6ItWJZTqSxSsdRTlzzVq+Hr7oWh3r+/JGr56SwaXGcHk4LVnORdXrfQ7O9DR2uDXH1xVKi1cxRr5UoVnq231II0dPObylEmerIxCjTtdUKEGZ7j7RsKLdA0k9c4uaDDz7AK6+8goGBAQSDkWmkt99+u659OJ1OFBQUoL+/P2J5f38/ampqhNvU1taisLAQBQUF4WVLly5FX18fJicnUVRUZPBMCJlbqL1lix7+laW1wv5Dezxvwj81EvPtXG3Criqtm+1i/c5rES4U08xuQFa4TiQYXNamsJjR01DTVncaSiyT6FWst3jBCgCxY2WkibquvDnselGzZMiFon9qFJ3ePVH702rmGMtKFMtC4g14MFxejGFFcPJhlwNV1fqsbWqoxWCpxSUNjLlpLSEZxbC4efTRR/G1r30NTqcTNTU1MJlM4c9MJpNucVNUVIQ1a9Zg69atuOCCCwDMWma2bt2K66+/XrjNWWedhV//+tcIBoMwm2d/VAcPHkRtbS2FDSExMBokrOVq0fN2ruX2so0GMKOjcJ1cMAyO9cLtPwy3/7ChMWm5JtRcZHL8Uz6hkJKOKV8mCUVvwCMUN1rNHDtcG1THGeu7ixA+jU4MVJSFLWLO+tUJCwx1K5xJuFR+7tnkpiJzB8Pi5l//9V/x/e9/HzfffHPCB9+0aROuvPJKrF27FmeeeSbuv/9++P3+cPbUFVdcgbq6OmzevBkA8LWvfQ0PPfQQvvGNb+CGG27ABx98gLvvvhtf//rXEx4LIfmO0biOWK4WPfEgqsJCJZvpxMB+FJRZIvYr/f87fnGigd5zUS7XW0BQVDlZtJ1cbGgJO7UeUR+c2IMzaj8pdjfFCPBWjsdXbkFVwxloKk1Oqwp1K5wLwdCMIXdcskhlBWWS+xgWNydOnMDnP//5pBz84osvxuDgIG6//Xb09fVh5cqVePHFF8NBxkeOHAlbaACgoaEBW7ZswY033ojly5ejrq4O3/jGN5IitAjJd+JJjW2tWAVrYbmw0J/eIFphzINKNtO+qQ/hc/dHve3rzdLSMyZvwIOBMbcuYdNsb1N1vYjoGTkEYPacjTZzHBx3w6vSJDKezDZrYVnSJn0tsRZOZ5/ywT81gk7ve1HbJ7tGTjYHMScCBVvyMCxuPv/5z+MPf/gDrrnmmqQM4Prrr1d1Q7366qtRy9atW4e//OUvSTk2IXOJeIujNdha4J8aibuomtQCQV4QLVY2kxTPIQX96hEtyjGJjhvLWlNf1gzLPCvkfYjU0pvlwdDSuHtGOtEz0hnhohLF51SWuIQdz41Y0WJ9B8muS6Pl3pPOc9YdFy1ukjmWVDZ6zST5KtgyhWFx09LSgttuuw1/+ctfsGzZsnAxPQm6iAjJXuJNjZ1tPmgGYIpouiih9sY5vfPlCAHja2kDVp4Dh8UZrgR7YmD/rMVGkabd6X0vnLHUWrFKOLnLzwVAOOC3bO/uiOMG2zow2rYyprXmFNuiqHMTZY6t7QXmHz5ZYfmwy47OxpPbKSdbvX2m1Pp8AerfnWh8esRnPFaCWJlHyaourEWmKyingnwVbJnEsLj52c9+hrKyMvzpT3/Cn/70p4jPTCYTxQ0hSSQVZmqjqbHRzQdni2ZGtBAQvHGKWiBYO/fizZJhOOtXo7ViFczOehSUWeBzR2ZNypEe8lqTu3yMtpEA2vdGtnYI7d2GiQpt64FoEvYGPPjgxJ4IK8vC6fmYf/jtiPVErR2kyVatx5Yo1T5WJppa7JBWc1IRybAS9Pg64Z0YgqO4IqI0QKpry2RDBeVkk4+CLdMYFjeHD4szFQghySUbzNRqb5R6AkjnDX0orLliHZ+KGXyrRHrIiyZ35RjVumxbA1OAoEelvOaNHDUX1tjxI+L9K1o7SJOt2sRVWVqLipLqqHgmI2/sasKpMaDeS0qPlSCWqH7j6IvhAo09I5044uvEWfXnhj9PZW2ZdFiH0k0+CrZMk1ARv1BothiXPB2cEJI42WKmNtJuQc4HJ/ZgItCFdtE+P2qBIH8rld72B8bcqinUeseo1mW7tOJUNJtKoyZFqeaNHK36N2r7ly93WRvD56bmaorV5kLP9xzP9qJtbCMBzHTtRrCqFQdNg5qiusfXKaw83ePr1FXcMRnEsg6J4q2ymXwUbJkmLnHzq1/9Cj/60Y/wwQcfAAAWL16Mf/mXf8Hll1+e1MERMlfJFjN1vG+Og+NuoNwS1e1aHjSs3Lf0tq9MLTYaOOsTHNfU1gGzsx6tqNflMlG7/lIQ8YirHuXuo8LzclmbsLK6A4C69UfvOcWyoMTzxq/87GSjzWOYwTaYXXZAI37IOxEpbCS8E0NoQHrEDaBuHVLGeQXbOjBPVhwyW2GriORiWNzcd999uO2223D99dfjrLPOAgC8/vrruOaaa+DxeHDjjTcmfZCEzDVU04UN9HZKBnpcRkrkmUCdioJykgDQmtyNPuRtowEsHy1Hd2gwvP/gir9BwfJK4du7HpeJyNqi7LaNpmUoqF0I2BagqswCq6APk+i6LXO2hy0cWm/setySatsDiKqmLNrGNhIQNtpUix8CAEdxBXpGOqPOy1FcEbUs3YjivETFIbOVVLrz5hqGxc2DDz6In/70p7jiiivCyz7zmc/gtNNOw3e/+12KG0KSgCgDBoiOpxC92Sc7CFkpNkQBxMqsJXkArq/cAl+5Bcuc7Rif9kPKuIp1/nrGLr2lVwOoBuCXZWMBAOKY0ETWFpEIwOE9wJIzYHbWw4Ho3lZq1h9l3RyRmDPilhR9P9vcW8Kfi0SRtM1M124AkcHXgHr8EDBbGuCIwjVlL6pIm0tKE5XikPAdj+teILmLYXHT29uLjo6OqOUdHR3o7e1NyqAIIeq9nbT6EwHilgByZovYHUNgegyWeaXCYFolcrEhL9qmzFqSH1c5DnmtnE7vnoixxSPI1LKxClo+BlhUNlKgPK6ataXJVAWRCNCaNBMJEo2nmrRRUeSwOBGsasUMIq8hEBk/JLKynVV/rmq2VEZRKQ6pupzkLXHVufnNb36Db33rWxHLn376aSxatChpAyNkrqM1OapNYkpi1VsBEFFLRi+xLCtKawKACGuCfGxqqeQxBU+Cb+kicVheZBeuO89eLd6JxqTpsDhhL6qIsnDEysqSLGEiYgkjo6JIVEzR1NaB05esjCk2G2wtaY2x0YPa+eSCS4okF8Pi5nvf+x4uvvhivPbaa+GYmzfeeANbt27Fb37zm6QPkJC5ilY8hlp/IhFa9VYk5CIoWW4tuQBSG+/eoR3wTkRWAO4a3ovA9FhUUTql+BotLkCJYJ+jxQWIZRtRE4fLnKL8LqC4uhkmlUlT7Xp5Ax5hVpG8xYKWpSWe7Jl4rEVSMUV5fJID0W62XEF0PmTuYVjc/K//9b/w5ptv4ic/+Qmee+45AMDSpUvx1ltvYdUqloomJJkY7U8kIla9FQm17tfJqK2jNl6lsJFQuuNErpURWwn6BNlYKJnGiEowrYRaN/DOE++riwrBpKm0ulSWuLBo/jI4LE5dVhStdeLJnok3pdjsrE8oJkUSeMFQEGaTOePZPomeD8l94koFX7NmDf7zP/8z2WMhhAgQuYC0smTUJrZYgkit+3Uyaus4LE7Vfkp6UbpWrIU2vCPKxpL1NhKJM63+UuMzo7AWlqPDtUEoKuSTpsjqMjjuxuC4W9O1JM/EimVpiSd7Jt0pxVrp7kxtJplCl7jx+Xyw2Wzh/9dCWo8QklrUJjGt5oZqad1a3a+TVVtn0fxlQnGjzApzFDuFFh1RXZxmexu6sDeqL5WEqPJurLR278QQGmwtUS4m5TXVsoSpuZaA6BYLStGXjOJt6UopjuXqzHSFbTJ30SVu5s+fj97eXlRVVcHhcAgrEodCIZhMJszMzCR9kIQQMWpWnVg1ZETZUmrdr5NZAl40kbdWrEJjYEm4h5NI2KhN+K0Vq2AtLId3YgihUBBHR6Nje/S4geQo67Wo1ZvRE9wrjU/UYkEZVyR3aUlke6VdIxWsk2UFTHapg1T0byOZR5e4+eMf/4gFC2azAl555ZWUDogQklrUxI/e7J540IpNkRBZdVocy4RdyNX2K0IuQmIJEus8W0Rac6zUaq0Ch9Kx1CxiyriiwXE3Fs1fFv471ZV2kzGpGxW+iVoBk91vTW1/FDy5jy5xc/bZZ4f/v6mpCQ0NDVHWm1AohJ6enuSOjhCSNvRk98S7X1FsinwiV7MAWAvLVI+tx8WktPjEEiQt80+L+FttXB+c2IMzaj+JGmsDzKYCeMZ7IyxORmKdlMdzWJwpr7SbLJFgtIJ1IlbAZPdbU9ufnkw9kv0YDihuamoKu6jkHD9+HE1NTXRLEZKjpKqflZ79xpPCLN+v1PPJX1KIqoa1sBaWq751t1asggkmHBp+P+ozZdsF1TYY427s7n8jYhJ0WmpRUmiNKmpnRACEj5fCSrvxigQ1a8aswDMDMKFkXmk4W0qUeZfq+ygZ+9OTqSeC1p7swrC4kWJrlIyOjsJi0VkWlBCSdSRSUTfR/YraTehtLqns+TQ5UQXrmRs1xyR6hgH4qD3ESbSyvJSToCfQCwSAnpHOiIBh4GSsU8/IIWFfJkBxvimstBuPSFCz9GhZgNQqWcdLsu/PeCxqaiTbXUYSR7e42bRpE4DZh8Jtt92G0tLS8GczMzN48803sXLlyqQPkBCiD1ErAaM1UlIRc6On9sr+oV0RYsFlbYw5OTgsTiwN1aLefShiedHBXQg2r4rhvhGLG9HyQnOR5jhEiN72pf+XixvJ4lRbuxI1svNNZaXdct84agdGIhqZAhq1iFQsPdbCctXl8sagybJixFvDx8j+XNYmuP2Ho9bVEkLJdpeR5KBb3OzatQvArOVmz549KCo6+YMvKirCihUrcNNNNyV/hIQkkXw1HSvfHJUiRc+bpFrMzcHj70T0n4rnGmrVXhFNDsoGoWqcanJC6AiP4b6pKnWh07tHuFyON+AR9vdyFFXAq7hWSgbGjgnHL1mCIixOnX/A9NBoRMCwkUq7Ur8wqSmp2nWb3vkySvZuw+kf/X3YZUdno1NTJIgsPbaRAIIje2BDICoNf4/nTQyN96OytDbpv7Nk1/AR7c8yVGJIQKXKnUsSQ7e4kbKkrr76ajzwwAOsZ0Nyjnw1HYvEgVKk6HmTVHtId3rfC/efkvYlYeQaqr3FxwralRCKqjjdN+K39sbwWKT9T/R3Ca0c3smhKAEZjSli3INjvWGhJOoyLgoY1lNpV3lfK5uSSoiClJvcw7AtbMdMkV01cFxptTgpyo7BhZMCSY7b3x0+12T/zhwWJ8xD/Zg59g78BcUoOXV5QhYt5X1pVEClyp1LEsNwzM3jjz+einEQklLy2XSs1kpASaw3yVgPYz2NOeNBGcQrMTjuDk+4asI0lvtGy8okZToBIYxNjUZNyC0fDmHB3m2QZJJyEh+eHEJ9WTMACOvrVJW6VFPVreNT4ovhO47gR/9VWmtE56KWMSbqFWYf6kWx4JC9vbvRO1MePm+lEJELQZEoa3IPY6CiTHchxUQZeONJzD980hU5s+/tpKfJG3GnJdtdRpKDLnFz0UUX4YknnoDNZsNFF12kue4zzzyTlIERkky0TMfSf3PXVRXStVYs8WI0rVcilmiK5cZSqwMj7RuIFlbyCVPNfaNlqYtVH8dzdCcW7j0WsUw0iUuiRuQGFI07fF4lhcLlM+5DwLbnwn+PL14F65kbVc9FS9gqe4XZAgGI2oLKx6ImRCRrxkzXbgCR1wWYFWtq4kYaSzJ+W75j70cIGwmR1SuVLmjlvtPd8oLERpe4sdvt4ewCu92e0gERkgpUU3rHevGOf3v470y5qhJ5EFeV1qFT1k9JhDTZHhvp0mxuKD2k93p2wDsprlisREs0KdOlRddXa3troe2jWJJoekZmJzmHxRnlvtGy1En/r4WaZcV5Ykw4iQ9PDmGZsz3iump1bveVW3BY0fTT56qDrTsyDqjo4C4ccBSga96JqHNR1mNRouwVJjrmYZcj6nzUhIjD4kSwqhUz2Bb9WeVi9KJXdSyxAnL13vtTw73CTvAAIuKsUumCVtt3ulpeEH3oEjdyVxTdUiQX0ZsZkQlXVaIPYq105YbyFjSUL0Sfvwfb3FuiPlc7lkjYuKxNsMyLDLZcGqqFze1G0BaAr8wSMUkphQ2gnkUkshg129uiaqXI6RnpRM9IJ1zWRjTal0QcO5alLhZqlpWFR0/AHAxGxZgAsxaouvJm+I69j6Hh3Siwlmkeo1PR9NM6PhUO9JUzdvwIUFUetVxL2ADA+PSY8Jj2hetQOWPBaHEBOid2R60jEiLyNhAmgRuwaeGnMF8QWwRou2iM3vuF9lrVz6Q4q1S6oPPZvZ1vGI65GR8fRygUCqeCf/jhh3j22WfR1taGv//7v0/6AAlJFkrTsX/KJ0z7TMSEbtQCk6yHpVpTyobyheF9ihAdS00AVJbWoK68OXwNHfveR9HB18PZSgOymBRlzRo5ykBhILLnlZTxA0AoyJTIY2WAk92oRegN8hRZOSTUYkyshbZwPIhkXTitoQbvN1jD67isjagsrYV/agSd3vfgK7dounMAdaEVG7G7sri6GWaLE8GAB9ARrqVsAzG5eBVGP3EurIEplFacGnYFSZaLuvJmNAZmxaZkJRQFK8dz79vqTsNA0+4o15Q8ziqV2UvMjModDIubz372s7joootwzTXXwOv14swzz0RRURE8Hg/uu+8+fO1rX0vFOAlJCnpMx/FmOcRjgUnGw1ISVGpF8LTcI6Jj6cn+mHfcg6KDuyI+l0/6WlYFeaCwHOV3E2vcakgTpFZRQFEAqLLIXmejE0GzGQuPRrqEAKAuaIcPExHbm4f6oyZdV08fihv/HjMLqqICgZWuRC23kZZYVKOqtC7KNSW/Bh+ciE6FByLvB1GGVdHBXfiguA6+cguaTaVoRXSmksPiFFYolv8e4r33q866DL7G9zFz7CCKBNlSqcxeYmZU7mBY3OzcuRM/+clPAAC//e1vUVNTg127duF3v/sdbr/9doobkjMkM8shXguMnoelljVIKagky4C0vRRjo4VyDFrXRTpe7cAIRMnWosBSeWsE6TN9QcgjmuPWQuowLqEsCqgWADoy6Y0osueZXyoUN6c2fAzzFW44957/EcaDBH0e1J36sYhlaq44pavKV26J6Jw+MHYsZnwVcPL7UqsS7A14hJY+QHE/qLSBkL5ntXtcz+8hEaFgqzsNqDtN+Fkqs5eYGZU7GBY3Y2NjKC+f9f/+4Q9/wEUXXQSz2YyPfexj+PDDD5M+QEJSSbKyHOJ9C431sNSyBqkWv7MviXprLjJbMBkMRB1f7cEsui7y46m5SuTLXdZGlL7/tsISMeu60prA9HT61sI2EsC8gQOwycSUqCigyIonz9ySRJnbWQaXZ1R2Dg4ETYNotayK2H7KaoUIteWtFatgLSzHHs+bEct95Rac2nQ2qhRB31qxRHKWOdvRYGuJEMV15c0R66i6HksUBQBV6gXJv2fRPa7n95BKoZDK7CVmRuUGhsVNS0sLnnvuOVx44YXYsmULbrzxRgDAwMAAC/uRnCQZWQ6JvIWqPSxjvf3u6PuTcH8DY+6o7UTCRpoE1ZBfF2/AE85OAmJn3jTb27A4VIkZ99aIfTa5hxEqnw8bZoOQzc56eAMeTPR3wRqYQrDMga6J+IWNss+UvDaNHlef1JpggXcsQtC4nVYcd1hPWp8EFgu7axkOu96NuiZVrmVQQ2SdchQ7MT49Jqw0HOt+clkb0WBriekiVduPvFM7IG4DocywEu1L7+8hlUIhldlLzIzKfgyLm9tvvx2XXnopbrzxRnzqU5/CunXrAMxacVatyv1qr4TEQ6JvoaKHpVbl3lAohAmBYJlFX90buZVCrUCcKPtFQuRCkaixNgBusduj+UA3ZjC7P0/TQngnIgVJi6DirRyRm0tarlVgLpYwULYmkOPy+NFTGzmpK8WSw+LEiVOX4ZB5ttu4Z34pnPWrVe+BHl+n0ELlnfDAO+FBp3dPhJtRukfUahG5rE1YWd2hyyVk5H6V1xH6MORBp6k35jai/VeWnGxtobzfKBRIsjEsbj73uc/h4x//OHp7e7FixYrw8r/927/FhRdemNTBEZJLJPstVLU2j0qsBACUFzp01b2R71/0lg/ErgUDQDXbxz/lg01HB+v5hw9hvmKZVsVbLcuMWm0a6/iUpsgAxIGzov1oWSymd76Metk+GkobMWVtwLGRrqj7Qa/rTdTGQH6fiWoW6XWRGrlffWUW+IvLML/QhQ4s17WNtH8p/kn6Jyp4SDcPSTaGxQ0A1NTUoKamBkePHgUA1NfX48wzz0zqwAjJRTL9FtpoXyJ8axZNKMo4Ggk9k27JvDKMT4+qfm4ttMFXOJseLkqnjoVaYLKWZUYtDshkc8auG6QSOCtHvn+5FQJQzyraVTwQ4aprrVil2jIhFnLri9Z9ZsRFqud+TbQOk1KMi/qe5WPPN5JZ1OueqxAMBnHnnXfCbrfj1FNPxamnngqHw4G77roLwaB2VgYh2Y434MGxkS54A/qq86YSvQXnJKzz7CgvcuDYSBdqrA3ocG3Aisp16HBtwFn150b8LU0eRo8hMT49Cpe1ESsq18E6L3LStBdVhINfByrKcKh+/uy/Oofu/c+vXBJ9fhqWGQBw1q/G4KmnRHx22OWA2zKB3f1vqB7LG/BgsEDNxXdyP0WVTSgvdACYnbC3ubdg/9BH6fAaWUUSXcN7w+6YeJFvq3avSuJWTrKzAHt8nSpbqI9XL9J1yiTZ9Bwg8WHYcvPtb38bv/jFL3DPPffgrLPOAgC8/vrr+O53v4tAIIDvf//7SR8kIekg013DlXEIam/gokrBTkstbMXzI4reKccvektPpD6H29+NipJq+KcjJ7DhySF4Ax6Uvr8D7Z0nWycMOsSF8wcdJaj0jof/PuxywFp1KlxjRRGxPqULTgUwELW9q3Y1mqqbZ2v6rLTjTdsrUTE5omwpIPI7b1FYmdzOMhx3lJ7cTyC6vUDX8F5YC8tRpyOrCDjZw0yE01ILj+AYcqS0/lj3aqqzAPd43oR/akRc3Vp2H8d7f2WyKF6ynwOp7HFF1DEsbn75y1/i5z//OT7zmc+Ely1fvhx1dXW49tprKW5ITpLpsupqD9TolhGNWFndAQARkxcQXc1Xz/jVAkul7WPxoe+gcPlEfxcWdO6LWCYXMBHjbFiArgZECBKXIojZaalFWXkjJhdPRxQP9Le0ofgjYQN85A7TiAOSXwvldy4FSK+0tMJvKcT7Mx/EPH/go4ne3oYFTQsjiviJ+jZJE5woKLiooBgdrg3o9L6n2k9rj+dNDI33625rofbd651wtcSJ6Jii+ziWi9TocZON/FoA2k1atbYVfZ7pF6a5jGFxc/z4cbS2tkYtb21txfHjsf3WhGQjmSyrLsqakR6oWm/g8slLrZqvnvGrHcNsKkCnV1zFVsI3GV3gDgDKPGJzvshKIwkA6b+inl+eQO+sVcMJLK34OAr9o+gODcJXPgG4t0Q0L1Sr5qssjChPbQ+fT7kFw5W1sxYSAx6JruG96KoFbGV1wkwuINI1VGNtENYoAoAWx+kI9B9S3Y9apWJlh3v5/8cSIGoTrsPihKPIqdpEVX5/qb0gdLg2CGsmSQHRff6eiLicdBbFU14LZSyVhOh3pFVAUyuejX2o0oNhcbNixQo89NBD+Ld/+7eI5Q899FBE9hQhuUQmyqp7A56oSrpypAeqnqBPtSrE8uVa6d6iQm8l80qNnE6Ytb1A0eG3hZ9NLF2DAvtiwHcc7wYOwm2ZiPh8doKoEfb8kthn6gXKAODkpC+fNFZWnwX0Q7X1QqxMJWuhDRP9XagdGBGKCy2UVqMWxzJYC8siKkZLfc1EuP3dWPThcbQfPGm5ORwjNV5C2eFejlYwc6wJ11laoypu5L8PrReEuvLmKGGuLDRZWeLCovnL0jbxi66FrqrNKtsqM9vKi+zCfbEPVXowLG5++MMf4vzzz8fLL78crnGzfft29PT04IUXXkj6AAlJB3rqfsjfNpXpt0bRkwqstDQMjLkBhFBVWhd1XFEHaAA4ERiE2WSOqlVTWeJCobkoSgBIb/Ba4ysvdGBkyiv87DTUYf7h14SfjbYsRVFVI3yFFqDMBbc72iokxfFIqNW0ETEw5g4LtZXVZ4WbN8YqjCjHaamFdcefYT28J9xeQq+4ECEV4hO95YuwjQRQdDDSoiRKjVdap2L1npIETDwWSrXSAi5rU8Q2Rl4Q1ISFsoigtG4qYla0qjRHtu5oijpurEDpruG9WOZsF36WLX2o8j0WyLC4Ofvss3Hw4EE8/PDD2L9/PwDgoosuwrXXXguXS2zSIyQX0HIBqU328bxt6kkFlqdqK607nd73olwJgWm/cD9HR7twdDTaZSV6Q5UmQOn/ldSXLcQpH1U0VuvWXTElTsceaGrEO1WTwOCsZUHN/A/MFhdstrfB/M5rqjVtRMhdaHI3lZxYk1L1u7sAT+S11Kq7o4X0HYrcjm5/tzCAWCsjTJlSLhdvsx3uuzXHoxXMrDXhioS/PPZLaz01F5OaZUwpslIZs6JVpVku/N3+w7AMleiq8CxHuo+zsQ/VXIgFiqvOjcvlYuAwyUtELiAtMSIVJlM+HLTeimJNsFJbBC3ridyVsH9ol1DAxEPPyCEUF4gn8YqSqvC5iCwF1nk2fDjpwWLBtofLpgAUhP/WKkTonxqFK1CEEpWaNs761QC0A57VXC1ak5JtJACXRywSbRMh+MpVN42gqrQe1aV1Mb/DuvJGFBUUR1zHIkctRBlh/pLCKCFttKaSWjCznglXb/aVnvWmd76MBXu3CS1jSmtlKmNWtILpYwVsa1WKlpBcvdlWoHCuxALFJW5OnDiBX/ziF9i3bzYboq2tDVdffTUWLIhdkZSQTJCICVZPrQ6l2Iinr4+0rtT0MJZ1RxpXIk0mlcg7YisZnfTh2EiXajsG/7QP/iKgUKPnlNzNVFzVLBQ5nd498A+MCNsgWMenwtdZmjT8UyMY6HlbV+dxh8UJ6zxbVPq6tG81fMUm1c+UDIwdxcDYUWFWU8TxCm2oq25Gha8a3cMHMDLlxYdFo1HXz9/ShtOXnGM4602Oy9oY3j7eNHG9YkprPVGxQ7lolW+XjiB/0bXQG5yv1vgUiLzemS7sqSSTyRPpxLC4ee2117Bx40bY7XasXbsWAPBv//ZvuPPOO/Hf//3f+Ju/+ZukD5KQRBBlRBhxJen1kX9wYg8WzV8WV18f5Zj0CCqtwFRl3EAyODT8vq711HpOKVsnTC6uwtTyDRgYcyMw7Y+wPml1HVcGWvvf+m80CQJwrYW2KFHrDXiEwkbrmG6n2CUVK85F6zPJWiKy7EjXb8m8U1BRvRQOZ73qfuQoJ+ru4QMy10o3LEOlYZGdsQlXpdjhSksryhRukXQF+SuvhZHjyvuzyaksrU3O4FJAJpInMoFhcXPdddfh4osvxk9/+lMUFMyamWdmZnDttdfiuuuuw5492qmjJLfJpiA0PWNRC1wUuZLU0GOClvZrL1Yp5qbR10cKUJYT60Ejmc9FXaWlsShxWRsxNjUakfnisjaiwDxP02ITD8qsIVHrhKKDu1DSvAooc0WlZWt1HZdfm6DnaETdG2DWElB46rKobJxmextGJr2aY1Ye0+0sw/uLq6PWrSqtx8rqs2AZKjVsOasva4a1sBwHj7+juq2v3IK/YgDNJidaoU/cACcnam/Ao6sWjhaJ/taF26sUOyytODVqWbwutEQxctxcFAqZuq7pxrC46ezsxG9/+9uwsAGAgoICbNq0Cb/61a+SOjiSXWRTEJresWhZQIw87CUxMjB2LEZTSrH7Qq2vj2gClgJhlQ+g0nllWGCpxim2FvT5e1SDekUsc7bDPzUSlWGzsvqsj2q+JFfcKFFz+bjdO/FumVigqVmAuocPYOVH39nY0IcoFmxbFpjBvjh6Zml1OpdTXVoXc1+AuOqwWpC3iHgFiZro1et6SPS3rra92VmPYFtHhGvK1NYBs4p1KtnNaPWi97i5KhQydV3TiWFxs3r1auzbtw9LlkT2ftm3bx/r3OQx2RSEZmQssd6gjPiZpbfiYCioOlFWlboQDM3oetjFOg9lV+Wx6VGMjY5idHJYWHekxTGbRisqvNczcgjeicht5C0JYrlYEkXN5dMdGoS8Xo0SUbVh+bg/DIkDmL1F8fe5k47ZUN6CsuB01HWxF1XoiouyF1XEbKegB+keNVoNV4Qei0Kiv/VY289bvR7BU1pnXVS2BarCRiJTLjS9x81VoZBtsUDJxrC4+frXv45vfOMb6OzsxMc+9jEAwF/+8hc8/PDDuOeee/Duu++G112+fHnyRkoySjqD0GI9xPWORdqP1sQdj/lYKTokJBHjsDhhLSyHd2IIjuLZiVDE3qEdus5D6WJSL6g2WyxOJG6UwkZ+rD5/T0qFDaDtZlJSVVqPgbGjmvuT7gFRAO5hlwPjtnLAn1jTw4byhXBYnGgMLMERXycmgwFUl9aHv0+1+7ChvAWO4gphoGk8WAttMS0pRsoLxCLR37qe7c3OekBnLFE2o1UEk2QWw+LmkksuAQB885vfFH5mMpkQCoVgMpkwMzOT+AhJVpAu37Iec7iesYiKpk0FJ5NW5t1hceKM2k9+VFzvGAATqkpdUcfuGekMNxiUPwi7hw+oCg49VV/VtnNYnIaCibWsULGQMp8QCgEmE/wlhTi16WyYTWYEQ8Goyd2Iy2dielyz/9DopA/HA4PC/RZXNcNiLogYo9FKw/J7Q+0NV+0+bChfaLgbdotjGapKXUI3JRC735Ha8eQVkrXi0vQ0bNX7W8/FOJR4yCY3PYnGsLg5fFi9LDrJX9LhW45lzpY/hLXGolYavcO1AYvmL0uq+Vg+GXV69witRF3DexGYHtNtHenz94THpndCkJ//ovnLVAOKlRWJ1bI95FgKrKgvb46wCCkznyQmJ/bBeuZGeAMeOIqdUQJOramlnPFpf4SwEQkUZeaWfL8d85dhZNKL4j1/MVQE0GmpRV15o+57I1m/icoSFxYvWB7eZzypyWr3iVQhWQ39DVubwgIq1vnlahyKEbLJTU/EGBY3p54aHdVO5gap9i2rvX32jByKSGsFZh+WHa4NwrFo7aehfGFc5mO1vkxqzQ+VGHH7yB+SsTK1WhynC9sxiGi0L0GjPbIlgTcQ23UTmPFjbGokPA5R5pNE0cFdOFxhne3/FDcng7KVIiqWQJEsHUUnjqNGpQigmrjyBHqxeMFyQ/e12m9C9L2puUeVLQfiSU2OR1Dobdg6W9focLjflx4LRa7GoehlrtSKyWXiKuJH5i6pDEJTe4iLMnmkh7BIqGjtp2ekM2mZH0ZdD0aQPyS1YnwWL1gBb8CDg8ffhdR3ymgDQ0tBKQIz4t5UEpLlq8bagJmu3QCOqa7rHTwIVOks56ug2d4WbtgpElFqAqWhvAUN5QvDWWS1AyMQJR3L2xiIGBhz6wrelaP2mxBN8MrUcTUBEvQcDQfcOpz1wrpIeo6nRDovtUKMQGTDVgBRzTj1Wijk+8imEhLJYK643nIZihuSNeitJyOh9pYUaz/JyvxQe5BFNzVs0uxyLUdywZQXjwMyfSCP8ZFPEkrh1el9T7Upo2i8u/vfiClsJCRx5LNrFyhTy4zSorzQ8ZFVaSQcq6Onz5JEQ/lCACdjU7SKAGoRmPbjr72vRInIeGMplMJHb3sCeap0sK0DravXRwhctVpNWi8ferKpAP2dvvWKlHyMTZkLrrdch+KGZBXSw79n5FDM2itq3Yb9Uz7UWBs095No5ofk4hLFsbRWrEKFrzoiW8oyVBL1IFSWbo9wwXT+DtNtvZi3en3EcZVvw6LJSvRG7rI2RpyLVDzQiLtMut59JdOAIkNJQi0DSk6zvS1cM8gz1gfvpAcjU96oAGS9AkUqdS+PTRFlZ/lb2nBq00qMT/sRmB4T1poRLdMSw/FYJLQEiKg9QWjvttnU6TJLVCyVXqGuJ5sKiJ6gE7VQ5HNsSr673nIdihuSdUgPCS1xI3pLEr0hNpQvFO4n0cwPycUlQi1bSvQglPoPiVww0qTmK7NEdHSWd4LWi9vfnXC698Hj78JkMs1OsLIMJXm2lJqwcVmbUFlaEzUJaBVE1Js+7vZ3Y6p3EjXWhojgY3kWlat2NapPPRN9Oq0XSj44sQdn1H4y/LeoW7uR5qnyz6UK1dZCG2wq7QngOw5/cVnEIulcJwq6gFO1J1Y994rUsFVOohaKfI9NyfdaMbmMYXHzyiuv4JOf/KTws//zf/4P/vEf/zHhQRGiFpBZWVornCy03hDVOv8eG+mKmFjicXEBkdk8XYheTxkgLKeytBZuf7fuCr7yY5XVtKqOKVHqrE04pnClKQvSaWU+1VmbUFJYBikOKCxYfZ3oGTmEInMxJoMTMcehN318cNwN+7530S4IPvaVW9BU3azbeqG2f2/AI3QFShhpnqq2j6WhWnGzBdsCWAtPnnukle9FTA/5oqx8coIh7aKGUsNWEYlYKBibQjKFYXFz7rnn4utf/zruvvtuFBbOmoc9Hg+uvvpqvP766xQ3JGkYeah+cELc08w/5Yvaj1rrArVYAC1Xmd5sHrU31bA1RkcF36hjDY3CddrasEUm3pouInyTJxLa/pj/cNT1fOPoi5q1a1THoiN9XE/wcaIB4ANjboxMejUFklqndmVJA7V97DP1omrxqsh+WU3LAN9x2LAAzfY2eI7uVLXyqVX7VUv5lwKx4w2ajgVjU0imiF3kQsErr7yCZ599FmeccQb27t2L559/Hqeffjp8Ph92794d1yAefvhhNDY2wmKxoL29HW+99Zau7Z566imYTCZccMEFcR2XZD8OizMqw0eJN+BRLVoniQdpP4B6j6Gu4b2qqdEOizMctCqhNqHaRgJR26u9OUsPf8kFI8ff0haemNWOVRsoRIvjdLR0e9C+5xhO7xxA+55jaOlOrDrvyJQ3oe2ByOvZ4+uMS9joRSv4GDjpyrONBFA7MILafl/Ef0XfmRLPeG/MqsNa7kL/lO+jPl6HhJ9LeJeehoJzv4iCjguAxmXA4T2Y2fYcZl58DC0fDmGlRcVip+bSgnbBwVQLjdaKVehwbcCKynXocG3I+WBikhsYttx0dHRg9+7duOaaa7B69WoEg0Hcdddd+OY3vwmTSdw0UIunn34amzZtwiOPPIL29nbcf//92LBhAw4cOICqqirV7bq7u3HTTTfhE5/4hOFjkvxCbTKpLIkuYBbr7f2I74MoS5GUlmuzLYh4C1WbUBtNlXgXkY0L93jeDMfeKAlblip9GDo+gEL/KArttUBFNfCRhUl18g5MYXCsF0sM1nTRoqzQjtEpcR0bo4T7Ik2kTtgAsYOPrYU2lO3djfa96inssWroqFWUlpAsEmqdxw8cf0dXZpq10AZzuRNBANj2XMRnob3bUPKxf4BQKqt03AYyb0FhbApJN3EFFB88eBBvv/026uvr4Xa7ceDAAYyNjcFqtRre13333YevfOUruPrqqwEAjzzyCJ5//nk89thjuOWWW4TbzMzM4LLLLsP3vvc9/PnPf4bX643nNEieoPZWai9eEI6TiLWuhLxjc7O9DS0fDkVkr7S0daCmbbZ4YHnxOND5u6h9uFyrESoKRL3la2WJOCwfdQifOTTrhZroR7O/LTwhqU3ewTIHpnrELjlRyrQe11UsYWPE/RW2nBVXpLTzuFbwscvaBNtoADOKLCQlWoJQVG1ZorLEhUXzl4W/VzUXkB5hE1G/RsUSYzLPg8lAZ22JVGX3yGvyxBoDIenCsLi55557cMcdd+CrX/0qfvSjH6GzsxOXX345li9fjv/8z//EunXrdO9rcnISO3bswK233hpeZjabsX79emzfvl11uzvvvBNVVVX40pe+hD//+c+ax5iYmMDExMnARZ8vdYXX5jKZLNKlFvTb6X0vXPdlZfVZmuuK8BzdiYWKN/3Q3m2wndIKh7MZKAem23qFk4xZR8l8idn+VG5hnEaLYxmWOdthrjRjcuL9iFgMU1sH+kpmdKdMG632K8dR5ESDbSHsO7eh5OjJayLfhygtXjrXBlsLjqTYNSUFHztPzIoIz/zZYoAF5gKMDX2IYh37UCvyNzE9LlxflGFkJFi2qrQO1aX16PP3RNWvWWyrFG9kW4B5zcsNddaWSLYFRVSTRyuwmZB0YVjcPPDAA3juuefw6U9/GgBw+umn46233sK3vvUtnHPOORFCIhYejwczMzOorq6OWF5dXY39+/cLt3n99dfxi1/8Qnd8z+bNm/G9731P95iIcfQU6Uq2+FHuT3orHRhzR3XFdvu7gX6EBY5axV8laq4g+I6HOxrPW70evupaTA33otBeC1vdabPb6swSiVVYTTqXZnsb6s7cCF9dc+Sxjr+jK2XaSLVfEafaF6Hq3XeAo93CfTjrV8/2JDrmODm+itMi1j2r/lz0+DrhnRhCkbkYEzPjwroyiVA1NBo+z4VHT3wkvoDhQADtOrZXE4rjM/6oZWoZRg6LU7MTvZyBsWOYZyoU169xbUCZhoVG2Vk73S8YWjV5aMEhmcawuNmzZw+czsgfTmFhIX70ox/hH/7hH5I2MBEjIyO4/PLL8eijj0aNQY1bb70VmzZtCv/t8/nQ0NCQqiHOGSRT9GhxAbomtIt0JbtCqdr+HBanakyN29+NxsCSiN4/8oq/oi7WqtVsZbEN+4d2zZ6/5Eoamgyb/rUsGYD+wmqArPnmRHfUsTq978VMmTZS7VdEuW8cOKzu/gJm3+JL9m5DyUfLxxr24MTqMyMm2wZbCxowKwi8AQ+GxvsjhEOhqQhTocmY45GoKq3HwNhRALEFnFIAKvE0NuLUpo6YQcOA2GIjZ2X1WUB/ZEHFkgKrUCRptkFYvV6XhSYjVYA1avKA4oZkGMPiRktUnH322Yb3VVBQgP7+/ojl/f39qKmpiVr/0KFD6O7uxsaNG8PLgsHZ0Lp58+bhwIEDWLgwMqOluLgYxcV6DNJEL3JTdAmAFoF7IxxImuQKpbH2p+USELmE5GZ6/9RIxL5FE6KnsREj5iFUBSzhYyvHoqzNU1pYBsCEqtLIfkBGU5NF3cZrrA2wF1VgeHJIM2U63nYEwGwcSNn4DGZUPveXFMIvcOEV9hzE9PgxbFtcE7POi9R+YXzar1nYT0mL4zTMM83TrBUkCbhOQeHByAKEBWieGtFlddHTTX1l9VloDCwJWwhFwkYL6V5WWmiUZKwKsFoAs0ZgMyHpIqMViouKirBmzRps3bo1nM4dDAaxdetWXH/99VHrt7a2Ys+eyLfH73znOxgZGcEDDzxAi0waEJmiRe4NeTVdEXorlCpN7bH2p+USiBULIQ+49E+NqFhECoCPYnlEzQuVyMfR6d0TnuRnz2tEfUOdDIwd0xXHorfar4hF85cBheJUabdz9nuvHRCfi8vjR09tAF3QrvMyMuUNV2vWi2QJq5zywe3v1iXgYtXM6Rreiw7Xhtlz0xiLkbgaLdenRCwrnxyjv4lUYXbWIxhHYDMh6SDj7Rc2bdqEK6+8EmvXrsWZZ56J+++/H36/P5w9dcUVV6Curg6bN2+GxWLB6aefHrG9w+EAgKjlRD+GfPUqpmi5e0P+YFabBPxTI1GZTEpEpvYaq1jAyo8jcgnoTXuVBJI34AlbEJQT4slsoS7AYKp12L1ksBWCy9qE0b59UW4n34T+Ynt6q/3KCV83CzDU3AJH18mMJ7ezDO8vno2X07IASfeGNNlquQ714Ch2oq1iTdQ9ZlTAVZa4hMLDP+ULW11EHbT1iFr5vmIhCV7peFq/Q9FvIjAtzsJKRxXgeTrdZoSkm4yLm4svvhiDg4O4/fbb0dfXh5UrV+LFF18MBxkfOXIEZrPhWoNEhVhdpWP66lVMzgsbPoEqW0nUgzlWJpPa8Yy2U3BYnBFxQJW2WpTMs2IyOBFuXik6fzXUxp1IxpGEaBKXx46IWPThEIoORmcpDYyr122RkMSYdUEj+hZMo1dnDZuq0vqI7+ZE62k4YB0XiiNfuQVuZxlcntGo/UjCRypkmOikK0/Jlr5PyfKhR8BJVXkBsVVFXvhRKv4ody+pdeQWoXauy5ztUW0/YmUyqf0mRLisTWnLWozlNiMkE2Rc3ADA9ddfL3RDAcCrr76que0TTzyR/AHlKUohI3LfxPLVq5mibXWnQW3K0spkUjuelqldVK9DGQfU57LjUOPJBpySC0ivkAt6jqLM3QNbKBCzSnC8xfLkFJmLVD+zjQRQdDCyqq3WcaUYHEApxgYAA2KsurQu/P/egAeB6TFNt86sFScEl+dkbInccuKdGEJ5wKHSN6wJbkUvKy38U77ZukBR8U3l6MQeze9DXpXXSGG7eDpyqxXP0wpGVsNIjFZlaXTMIiFziawQNySSVKR0it76NLM0NI6rZorWGreWO6Jn5BBGJr0Rb7KxUqnlb7l64oBiNTr0HXs/nMJc2j9bu6YaQDVOWkn0ZhzVly1ERUkVjo10RzWbVKv+e3S0C9Z5Nvino6+RkUwnubBJRIyVFFhRXuQAAOzuf0O3y+j9xTUINM/H2PEjUZYTqZO6JCqVAtUyVBLxPcnPRUkwFBTezx2uDQiGZlQtGkrxorewnZbYlv6rtn2yiucZsXixMSWZ61DcZBmpSuk84vtA97p6HoxKU7SecavtV5r0lNvqfqvWEQekhn/Kh8kdWzD/8KFwCnNIsY4kCPRmHFnmlWJwrDdK2ADa1X9Fwka0f63lcjEQT/p36bwyjE2PYnzGj23uLbAUWBHQmeVTVVqPFsdpcFic2N3/BnwqgqhreC/MJjOqSuvC/b4AsQjwBjzY69kB7+RJV1SzvU01W0lk2QNmm15KHcqV6Clsp3bvDo714h3/yYKjar/XZBTPU7MCAdEWSbY6IHMdipssIpUpnZNBce2Q0oIyjM2cjJOI58God9wOi1PzbVy5re43XpU4ID1pzgXHBzD/sHYjQ2BWEPRWlesKWC2ZVxrlfkuEuDOdQkqZFmM5gLHpyJgZvcIGQFjY7B/aFdPSoxZzpRQBDosTHfUboqyCag1OrYW2qHXllietOC8txK60WbeuvB2FPCssFagJQLOpAJJ4o7AhhOImq0hlSmd1aZ0wYHXh/NNQXuRIyGSuZ9xSiwG95fflqd3KwnfKsYrigJSTv72oAhUl1VFvuIX9OsfzkVBSBqwWVTYBMguNllUhEeLJdIJaI1uTSbNXUiIYKUwI6BfvJ2sR+cJ/i4Ty+563I61XAldfvC8MSmHhn/Kh9P23owLM/ZWpTcGW/yaUFtNgKEhxQwgobrIKvSX740HU28dedDKLKN6CelJ1XxHSuGO1GNDaVo6W60seB3QkNIROU2Tw5/DkEE5zroW1sBzeiaFwBpUv8H7MsUi1XCTkQbUryhuxeMFyXVYFJUa7b8eq0aJEzXK1sOETsNWdFnE9bSMB1AXtOGYejjs42mhRQvl2se4/UTC8SCgrl6m6+uJ8YZALC/NQP6oEMU3jvnGg3PCuDZOx4n2E5AAUN1mEmk89WQ8qeW8feXp0PCgnG+VbtDRuo2/y8m3l6HmQm5312G8aRNewuGiavJdUz0gnuocPoNG+BIGmhZquqeOOUtXPRCKsz98TvZ7AgjA6NQyXtRGVpbVRtVTk1Jc1wzKv1FDlXkDszpIy24CTlgjsfhXWzkMAjqEe8aW3A7NWAykIWYnTUguHxSl010mupIGxY5AqOcdqU2G0TpDomIlSNiGu2lw2oVbLOblkqngfIbkAxU2WkazMCjXkvX3iRTTZDE8OCWt3GHmbl+qPiM75gxPiGBZ5m4eBsWOaQkqZyjsy5cUez5uwn1qBhfUL4T38Vyw8Gl0UT7KAKHsDNdvbhOnIool3RdU6jEx6o/oWuf3daLQvQV11M0z9JhxTTYdWcTHFoLPRicJTl+FUk1NYZM081I+SzshrpsyokgSYvOq0SIzt8byJZnub8Bp4Ar1YvGB5VCaT6BrKKzlLx0smLmtjcn5XGW4/kEpLLyG5DsVNFpKMzIpUojbZmE3miOyXoOco7EO9sAUCulwdasLGG/ColrC3Ftp0ub3UqtECs8JsytkClH0ch4OvRVg6JpesQlPzabKsm1nrQsm8UoxPj4k7kAvwT/k0M3z6/D2qwiaRztkuayOaPuqGrmT/0C6M97wJUW3vlZZWDFfWqqb115U3o8JXHSXWuob3osWxTHg8tUymbe4tUevq6RcmElFKC6Lyb5e1CSurO4T7M0qm2w+k2tJLSC5DcUMMo+eNUSqqVwygHbFdHVoPZa039+7hAzFdFAvtp6HaWq/Z48c7MYRlle3wdjTgeH8XrIEplFacCquzHlbEFzckR8tlI6rZohe1TtMSym7oEpL1zaYSlzM4bwJNMqEqbSO3KKoHTouzsUQ1io6NqAs3eVC5aBKXWhbI07wlK54yBipVltBMtx9ItaWXkFyF4oYYJtYbo97mmiI3lggtM7ue2Iuyotn9a3V7dhRXzP7X4gROjYz3OOLrxNHR2Oni4fEK4mskl43ouiWSXbWq+uMYmfSie/gARqa8wnVEMRiSYFRLM+809WK+rPeXkT5fVaV1UYJNKV5jBaMDkd+72iQusnKm2/KZ6fYD2W7pJSQTUNxkiFS+TaYDzTdGnc019QY0q/V50svgWC+shTYUmMW3e0mBNWos3oAnIgDZCGoZOl3De7HM2Y4Wx+mQB87qza4S0efvQWvFKjTYWtDj64xyEwFicShfppZmLo9nMtrny2FxCu8P0XUVpXSLLHl6ygIoSVVRTEJIdkNxkwGy8YGrla2ihuobo8HmmnporVgFa2G5cPLWssgAs9Ydrc9XVX884m+jLih5EbdYsUXy8Y9NjWClhtsFgCJYObr/kjw2pbzIERVbpObuUx5TlGYuDyAWodbnS34M+d9q13V4cgj1Zc0ATLDMK9V1/+n5DTFVmpC5C8VNmsnGB65yolBmqxjFV2YBWtpglWXhiJprGrVeNdha4J8aUY298E/54J8aTag6sNHU9US6hLv93UA/sLL6LFWRoCwaJ2ouKWoiWVniwqL5yzSvq/yYyuwnuSgy0udLjVjXVQqa1hMQq/c3xFRpQuYuFDdpQD6JJ/OBmwzXVo+vM2ZTSSPHCQulKsBWUodGUyVcrtVRgZbxWq9ixV54Ax7D4kZ+7fWmHbc4lsE+EsACt/5u3RJyS48bJwN+440fEQUkD467YZfHEakQ/qwUqCipFsZAxYqx0nN/6L2ueoS+3t+QmijzT43CK4snIoTkHxQ3KUZUWVWE0doUibq29MSUiCwCauZ/KThUvq6v3IJ3MYKyMgscivUTsV5pTfjxxOcMjvWGU9j1fg9VpS7YvG5hETd5bJFUIyYYCmKP502hpUdvuX41kaEWkNzp3aNqhZO+M5HFpk6RJQWoi0q996GR+zuW0Ndb30XtXtC6LoSQ/IDiJoWoVVZVxogYrU2hRxxovU3rjSkRWQSUx9GzL+VklWp3gXIiVgo0JfJ0adGEWGgqwlToZONR6fsK2gLi8ygpRH1ZM06xLYo4n7G+g2gSWHqMlOtXa5yohZHvTEtkigJ69YpU0XVV628VSwgZqe8iXa+BsWNRFZ4z7Q4mhKQOipsUojaJV5bWotG+JG6XUixxoPU2rTemRMsioJVFI0I5WaWjsqp8IpYyd3pGDqFnpFO4vlxYacWiuKyN4Wup1rDTVFGH5VXroo6xaF49ZvB21HKj5fqVIkOPtcrId6ZXZBoVqSJhJrpX9RzbSH0Xh8XJ+BtC5hgUNylEaxJPpDaF1n5jvU3Hin2QWxzULAKxsmjkqKX0qmUHHRvpijuGSMtaJf2tJm5ELg0AeMe/PWK5siieVMRtqH8fvEVBlFQvxFlqKe4JluvXOj8tCwUA+KdGPqrZ80HM4+gVmVr3YdBzVFjYTnnfJ1KEzshviK0KCJlbUNykECPm82TtV63iq/SGqvUwV8YgxBq/2r70FOcTuY7kZfiNxkPoif1Qs3CofSezlW+jGRhzR6xvdtaj0lmPyhhjNFKuXylk9J6fw+IUuhM7ve+h0/seSgvKNMdo5P5Uuz/K9u7GjOwcg20dmLd6veZ+Um09SdVvkRCSnVDcpJhUlUdX269axVdpueghX17oQKN9ibCoXqw6JqIJw0hxPjVXiZF4CFHGl9r2cgtHrJo+gWlxWwNpeTzZanrK9YuC0JV1erSuz8lzdEdljo3NjArHVVVSh5b5p0fF1MQ6P+X9YRsNYGbvf0esE9q7DcFTWtPemkAJWxUQMneguEkDqXozFe1XLU5Gvlx6yEvZUlJ3bP/UiNBaojX+ZEwYicRDaAXHqm2v9/uwzLMKl08GJ7G7/42ooHC9liatcv1qQegitK6PHheknNqyUyL2FctSpBQ+YXHtfld8AN/xjLYokEiHlYgQknkobvIMI7EFyjTweLNHEp0w4o2HiBUcm2g9k6pSl7BmzsDY0ahlsa6dXiuPEUES6/oYiSeRrxvLkqYpfBKMKyKEkGQQf8c+EoU34MGxka6EegUlun/JVSRHFFugZS1JN3rHrCTWWDu9e7DNvQX7h3YlbVzxjGf/0C5sc2/BO4PbY47HaICr1j2hdl1jXWute0NN+EjHNzvrYWrriPhcLa5orpLq5wQhhJabpJHqflFG9q/HVZRI9kgqmn7G497SKwS6hvfCbCpAybxSXV3IRePSSiOXEMU7GY0nEsUxKftFSSiLMIruCT1tHZTj0Lo39LgQ9cQVSeR6A1mjZGNfOULyEYqbJJDqflHx7D+Wqyje7JFUPpz1urfkE6LeasRK95KRccdKI5cQxTvFE0+kFCRAtAtRtEyrgJ6eZXrQK4q14ook5tpEn4195QjJV+iWSgKpdvGkav+tFavQ4dqAFZXr0OHaEHNiieWSSAdKFw8AdLg2oMWxzNB+jI5bj4tKNPHHayFzWJyoK28OixDlsStLXMLtknHPxRJk8bgQlWTDvZRusskVTEi+Q8tNEkh1gbBU7t/IG3ymq7xqvfnGg9a4Re4SvV205SSrvopea04y7olY91umM+RyFRYSJCR9UNwkgVQXCMuWAmSZfjirTYh7h3YIexTFQm3cWu4SSQzWlTejMaCvhUZrxSpYC8vhnRiCo7hCdx0gJUohmqp7Qs/9lqkMuVwmW37HhMwFKG5yhGwoQJaKh7ORgFK1iU9N2EjuE7WYnD5/T9QxjTaD1HPucrHUM9IZUU8okYDaVN4Tqb7f5upEnw2/Y0LmAhQ3SSBdgYLZUIAs3oezaBI3GlAqmhD1jldvV+hku0u07g1lt/J4AmqlMUnjzqX7ba5O9NnwOyYk36G4SQJzLX7A6MNZJGJqrA3CSd9aWK7ptpFPiP6pUWGRPfn+YjUMVX5HyXaXqB13YMydFEGsVyBma8o1J3pCSCpgtlQSyMb4gWwpFKZmuVBrSrnH82bMontSzEtVqThjSI4kLvR+R8nKBlLb/0lCwqVGMmf0ZhwZKSJICCH5AC03SSBb4geCnqOA7zg+DHmwz9QbMZZM1Q9Rn6zFkzug34JhGw1g+Wg5ukOD8JVbhOtI4sLId5RMd4nacatK66LcZPLx6kGPNYq1VQghcxGKmySR6fiB6Z0vI7R3GwCgHsCUy47OxtkxZHIyU5usq0rrEAwFDTe9lJDOtxpANQB/Sxu6m2qjmkzKg4aNfEeJukvkbiBRGrd/yhfV7duoINZjjZprLlNCCAEobpJKpuIHgp6jYWEj0eQexkBFWdiiMTB2LOsyrBwWJ6yF5djjeTNqOy0Lhuh8rZ170dywFEpnl1LYpeM7UouDcViim066rI2oLK2NSxD3+XuilikFUja6TAkhJNVQ3OQDvuPCxdbxqbC46fS+h2AomBH3lMhiIlk2yoscxl16Kuc7NdwLCLxT6bRSxCo0qPzM7e9Go31JUir8AogqaJgtLlNCCEknFDf5gG2BcLG/pDDi70y6p+QWE5Flo8O1Qb9LT+V8C+21wER/1HL/1Gg4yDbVbsN4SuwrY2T0jNGIuynTLlNCCEk3FDd5gNlZj2BbR4Srxtu8CL7y6C7VmY610LJs1JU369qH6HxNbR2w1Z2G5qHJqP13evck1DjTCPG4gaTPjNT9UdufqDM5wJRrQsjcguImh9B6q5+3ej2Cp7TOumxsC1BYZgE+aiwpJ9OxFrEsDnotF8rzNX/UgVqraJ+cVFmxYrmB1D4zmtWkVtBwj+fNiArIhBAyF6G4yRH0vNWbnfXAR5O8A6nrPaQHNZGiZdlQO0cpxV0uYgDAV2aBv7gM1kILHLJ9aRXtk5MqK5aWG0jts3iymmqsDZicmcDR0UMRy5nqTQiZ61Dc5ADx1irJVKyFmkiRBI8oBRqIDrbtGt6LhkNHUXTwZNG5YFsH5q1eH1Ps6bFQpdKKpeUGEn1m1J2lPH8lmXY/EkJIJqG4yQESqVWS7lgLNSEWmB6LEDTKFOhjI11R+7KNBFB0MNIqEdq7Db7qWnRNaIu9WH2osi1jyEhWk1qmlJxMux9zjWxtT0EIiQ+Kmxwgl2qVqAkxZXE9ZQq06Fys41PCfelN+VYrnqc2gWV6gtNraYvlcss24ZbtGG3gSgjJfihucoBcqlVitH2AlqXFUbkY6ByI2k6Z8m0bCcA6PoXy4nGgPHJdpeVK7ZplywSnx9Kmdo1bHMtQVerKyvsiW2F7CkLyE4qbHCFXapWIRIoyxkZCOUmLznF6OKiZ8t3S7UGTe3j2w87fYbqtF/NWrzc05lyb4NTE7uIFy8MNU7P5Hskm2J6CkPyE4iaHyHStEr1uG6VI0dMmQEJ5jlop365AEUrcv4vYPrR3G4KntEZkVcUiFyc4kRDMFutTLpFLLl9CiH4obogujE6ckkjR2yZAC3mKu5yyiRnMiDbwHReur0auTnByIZhr1qdsIZdcvoQQ/VDckJgkMnGm1Cqi0oZBdbkK+TDB5aL1KVvIFZcvIUQ/FDckJolMnKm0iqi1YTDikpLI1glOryswV61P2UKmXb6EkORCcZNmMp1uHA+JTJyptoqoxeTEQ7ZNcEZcgflgfSKEkGRBcZNGjExWai0HMkGiE2c8VhEjIlAtJieXUJ5vPK7AbLU+EUJIuqG4SRNGJqvpnS9HuFqklgOZJNGJ04hVZK5l/YjOt7zILlw3lisw26xPhBCSCcyZHsBcQStuRU7QczRC2AAfpTd7jqZsbHpxWJyoK29O6eSpJgK9AU/KjplJ1M43GAoK1x8c603HsDKGVKcnX79vQkh6oOUmTeiOW/EdF+/AYHpzrjLXsn7UztdsMguLH7r93WgMLMnLazHXLHaEkNRBy02akOJW5AjjVpKU3pyN6Hkrz5Wsn2RZGLTOt7K0VvhZrN5Suchcs9gRQlILLTdpRE/cSjLTm7MJvW/luZD1k0wLQzznm21CLxnMNYsdISS1ZIXl5uGHH0ZjYyMsFgva29vx1ltvqa776KOP4hOf+ATmz5+P+fPnY/369ZrrZxt64lbmrV6PgnO/iIKOC1Bw7hczHkycKEbfylsrVqHDtQErKtehw7Uhq1wTqbAwqJ2vbmtfHpArFjtCSG6QcXHz9NNPY9OmTbjjjjuwc+dOrFixAhs2bMDAQHQ3aAB49dVXcckll+CVV17B9u3b0dDQgL//+7/HsWPH0jzy1GJ21sPcvDznLTaA/mBqOekIXo6HeM5FD2rnm81CL5nMJSFHCEk9plAoFMrkANrb23HGGWfgoYceAgAEg0E0NDTghhtuwC233BJz+5mZGcyfPx8PPfQQrrjiipjr+3w+2O12DA8Pw2bjW2E68AY82ObeErW8w7Uh5yavfDqXbCQXi1wSQtKDkfk7o5abyclJ7NixA+vXn3S7mM1mrF+/Htu3b9e1j7GxMUxNTWHBAnHA7cTEBHw+X8Q/kl7y6a1c7VxsowEEu97NipT9XCZbLXaEkNwiowHFHo8HMzMzqK6ujlheXV2N/fv369rHzTffDJfLFSGQ5GzevBnf+973Eh4rSYx8qp6rPJeyvbsxs/e/w59nQ9FFQgiZy2Q85iYR7rnnHjz11FN49tlnYbFYhOvceuutGB4eDv/r6elJ8yiJRD69lUvnYhsNZG3RRUIImatk1HLjdDpRUFCA/v7+iOX9/f2oqanR3Pbee+/FPffcg5dffhnLly9XXa+4uBjFxcVJGS9RZ87GSszxoouEEJKNZNRyU1RUhDVr1mDr1q3hZcFgEFu3bsW6detUt/vhD3+Iu+66Cy+++CLWrl2bjqESDfYP7cI29xa8M7gd29xbsH9oV6aHlD7yuOgiIYTkKhl3S23atAmPPvoofvnLX2Lfvn342te+Br/fj6uvvhoAcMUVV+DWW28Nr/+DH/wAt912Gx577DE0Njair68PfX19GB0dzdQpzGnmemVZs7MepraOiGX5UHSREEJymYxXKL744osxODiI22+/HX19fVi5ciVefPHFcJDxkSNHYDaf1GA//elPMTk5ic997nMR+7njjjvw3e9+N51DJ2BlWWC26GLwlNZZV5RtAYUNIYRkmIzXuUk3rHOTXHKt7sucjQ0ihJAcx8j8nXHLDcltcqEXlAS7ThNCyNyA4oYkTC7UsFGLDaqxNmTleAkhhMQPxU0GyScXicPizOpzYGwQIYTMHShuMoQRF0k+iaBMwa7ThBAyd6C4yQBGXCSME0kOuRQbRAghJDEobjKAXhcJ40SSSy7EBhFCCEkcipsMoNdFwjiR5JPtsUGEEEISJ+MViucikotEjshFwjgRQgghxDi03GQIPS4SxokQQgghxqG4ySB6XCSMEyGEEEKMQXGTAzBOhBBCCNEPY24IIYQQkldQ3BBCCCEkr6C4IYQQQkheQXFDCCGEkLyCAcUkYdj7ihBCSDZBcUPiQhI0g2O9cPu7w8sT7X1FoUQIISRRKG6IYZTNPOUk0vuKTUIJIYQkA8bcEEOImnkqUeuJZXS/XcN74Q14DO+LEELI3IbihhhCj3CJp/eVVpNQQgghxAgUN8QQsYRLvL2v2CSUEEJIsmDMDTGEqJmny9qEytKahIKA2SSUEEJIsqC4IYZJVTNPNgklhBCSDChuSFykqpknm4QSQghJFMbcEEIIISSvoLghhBBCSF5BcUMIIYSQvILihhBCCCF5BcUNIYQQQvIKihtCCCGE5BVMBScph52+CSGEpBOKG5JS2OmbEEJIuqFbiqQMdvomhBCSCShuSMpIVadvb8CDYyNdFEmEEEKE0C1FUkYqOn3TzUUIISQWtNyQhFGzpEidvuUk0ulbzc3V4+uMa3+EEELyE1puSELEsqQks9O3mjtrj+dN+KdGaMEhhBACgJYbkgB6A4YdFifqypsTTgPXcmcxUJkQQogExQ2Jm1QFDKshcnOl47iEEEJyC4obEjepCBiORWvFKixztqf9uIQQQnIHihsSN8kOGNZLg60lI8clhBCSGzCgmCREMgOGc+G4hBBCsh+KG5IwDoszI+IiU8clhBCS3dAtRQghhJC8guKGEEIIIXkFxQ0hhBBC8gqKG0IIIYTkFRQ3hBBCCMkrKG4IIYQQkldQ3BBCCCEkr6C4IYQQQkheQXFDCCGEkLyC4oYQQggheQXFDSGEEELyCoobQgghhOQVFDeEEEIIySuyQtw8/PDDaGxshMViQXt7O9566y3N9f/rv/4Lra2tsFgsWLZsGV544YU0jZQQQggh2U7Gxc3TTz+NTZs24Y477sDOnTuxYsUKbNiwAQMDA8L1t23bhksuuQRf+tKXsGvXLlxwwQW44IIL8N5776V55IScxBvw4NhIF7wBT6aHQgghcx5TKBQKZXIA7e3tOOOMM/DQQw8BAILBIBoaGnDDDTfglltuiVr/4osvht/vx//8z/+El33sYx/DypUr8cgjj8Q8ns/ng91ux/DwMGw2W/JOhMxZ9g/tQtfw3vDfzfY2tFasyuCICCEk/zAyf2fUcjM5OYkdO3Zg/fr14WVmsxnr16/H9u3bhdts3749Yn0A2LBhg+r6ExMT8Pl8Ef8ISRbegCdC2ABA1/BeWnAIISSDZFTceDwezMzMoLq6OmJ5dXU1+vr6hNv09fUZWn/z5s2w2+3hfw0NDckZPCEA/FNisay2nBBCSOrJeMxNqrn11lsxPDwc/tfT05PpIZE8wlooNo2qLSeEEJJ65mXy4E6nEwUFBejv749Y3t/fj5qaGuE2NTU1htYvLi5GcXFxcgZMiAKHxYlme1tUzI3D4szgqAghZG6TUctNUVER1qxZg61bt4aXBYNBbN26FevWrRNus27duoj1AeCll15SXZ+QVNNasQodrg1YUbkOHa4NDCYmhJAMk1HLDQBs2rQJV155JdauXYszzzwT999/P/x+P66++moAwBVXXIG6ujps3rwZAPCNb3wDZ599Nn784x/j/PPPx1NPPYW3334bP/vZzzJ5GmSO47A4aa0hhJAsIePi5uKLL8bg4CBuv/129PX1YeXKlXjxxRfDQcNHjhyB2XzSwNTR0YFf//rX+M53voNvfetbWLRoEZ577jmcfvrpmToFQgghhGQRGa9zk25Y54YQQgjJPXKmzg0hhBBCSLKhuCGEEEJIXkFxQwghhJC8guKGEEIIIXkFxQ0hhBBC8gqKG0IIIYTkFRQ3hBBCCMkrKG4IIYQQkldQ3BBCCCEkr8h4+4V0IxVk9vl8GR4JIYQQQvQizdt6GivMOXEzMjICAGhoaMjwSAghhBBilJGREdjtds115lxvqWAwCLfbjfLycphMpqTu2+fzoaGhAT09PexblUJ4ndMDr3N64HVOH7zW6SFV1zkUCmFkZAQulyuiobaIOWe5MZvNqK+vT+kxbDYbfzhpgNc5PfA6pwde5/TBa50eUnGdY1lsJBhQTAghhJC8guKGEEIIIXkFxU0SKS4uxh133IHi4uJMDyWv4XVOD7zO6YHXOX3wWqeHbLjOcy6gmBBCCCH5DS03hBBCCMkrKG4IIYQQkldQ3BBCCCEkr6C4IYQQQkheQXFjkIcffhiNjY2wWCxob2/HW2+9pbn+f/3Xf6G1tRUWiwXLli3DCy+8kKaR5jZGrvOjjz6KT3ziE5g/fz7mz5+P9evXx/xeyCxG72eJp556CiaTCRdccEFqB5gnGL3OXq8X1113HWpra1FcXIzFixfz2aEDo9f5/vvvx5IlS1BSUoKGhgbceOONCAQCaRptbvLaa69h48aNcLlcMJlMeO6552Ju8+qrr2L16tUoLi5GS0sLnnjiiZSPEyGim6eeeipUVFQUeuyxx0Lvv/9+6Ctf+UrI4XCE+vv7heu/8cYboYKCgtAPf/jD0N69e0Pf+c53QoWFhaE9e/akeeS5hdHrfOmll4Yefvjh0K5du0L79u0LXXXVVSG73R46evRomkeeWxi9zhKHDx8O1dXVhT7xiU+EPvvZz6ZnsDmM0es8MTERWrt2bei8884Lvf7666HDhw+HXn311dDu3bvTPPLcwuh1fvLJJ0PFxcWhJ598MnT48OHQli1bQrW1taEbb7wxzSPPLV544YXQt7/97dAzzzwTAhB69tlnNdfv6uoKlZaWhjZt2hTau3dv6MEHHwwVFBSEXnzxxZSOk+LGAGeeeWbouuuuC/89MzMTcrlcoc2bNwvX/8IXvhA6//zzI5a1t7eH/vEf/zGl48x1jF5nJdPT06Hy8vLQL3/5y1QNMS+I5zpPT0+HOjo6Qj//+c9DV155JcWNDoxe55/+9Keh5ubm0OTkZLqGmBcYvc7XXXdd6FOf+lTEsk2bNoXOOuuslI4zn9Ajbr75zW+GTjvttIhlF198cWjDhg0pHFkoRLeUTiYnJ7Fjxw6sX78+vMxsNmP9+vXYvn27cJvt27dHrA8AGzZsUF2fxHedlYyNjWFqagoLFixI1TBznniv85133omqqip86UtfSscwc554rvPvf/97rFu3Dtdddx2qq6tx+umn4+6778bMzEy6hp1zxHOdOzo6sGPHjrDrqqurCy+88ALOO++8tIx5rpCpeXDONc6MF4/Hg5mZGVRXV0csr66uxv79+4Xb9PX1Cdfv6+tL2ThznXius5Kbb74ZLpcr6gdFThLPdX799dfxi1/8Art3707DCPODeK5zV1cX/vjHP+Kyyy7DCy+8gM7OTlx77bWYmprCHXfckY5h5xzxXOdLL70UHo8HH//4xxEKhTA9PY1rrrkG3/rWt9Ix5DmD2jzo8/kwPj6OkpKSlByXlhuSV9xzzz146qmn8Oyzz8JisWR6OHnDyMgILr/8cjz66KNwOp2ZHk5eEwwGUVVVhZ/97GdYs2YNLr74Ynz729/GI488kumh5RWvvvoq7r77bvz7v/87du7ciWeeeQbPP/887rrrrkwPjSQBWm504nQ6UVBQgP7+/ojl/f39qKmpEW5TU1NjaH0S33WWuPfee3HPPffg5ZdfxvLly1M5zJzH6HU+dOgQuru7sXHjxvCyYDAIAJg3bx4OHDiAhQsXpnbQOUg893NtbS0KCwtRUFAQXrZ06VL09fVhcnISRUVFKR1zLhLPdb7ttttw+eWX48tf/jIAYNmyZfD7/fjqV7+Kb3/72zCb+e6fDNTmQZvNljKrDUDLjW6KioqwZs0abN26NbwsGAxi69atWLdunXCbdevWRawPAC+99JLq+iS+6wwAP/zhD3HXXXfhxRdfxNq1a9Mx1JzG6HVubW3Fnj17sHv37vC/z3zmM/jkJz+J3bt3o6GhIZ3DzxniuZ/POussdHZ2hsUjABw8eBC1tbUUNirEc53HxsaiBIwkKENsuZg0MjYPpjRcOc946qmnQsXFxaEnnngitHfv3tBXv/rVkMPhCPX19YVCoVDo8ssvD91yyy3h9d94443QvHnzQvfee29o3759oTvuuIOp4Dowep3vueeeUFFRUei3v/1tqLe3N/xvZGQkU6eQExi9zkqYLaUPo9f5yJEjofLy8tD1118fOnDgQOh//ud/QlVVVaF//dd/zdQp5ARGr/Mdd9wRKi8vD/3f//t/Q11dXaE//OEPoYULF4a+8IUvZOoUcoKRkZHQrl27Qrt27QoBCN13332hXbt2hT788MNQKBQK3XLLLaHLL788vL6UCv4v//IvoX379oUefvhhpoJnIw8++GDolFNOCRUVFYXOPPPM0F/+8pfwZ2effXboyiuvjFj/N7/5TWjx4sWhoqKi0GmnnRZ6/vnn0zzi3MTIdT711FNDAKL+3XHHHekfeI5h9H6WQ3GjH6PXedu2baH29vZQcXFxqLm5OfT9738/ND09neZR5x5GrvPU1FTou9/9bmjhwoUhi8USamhoCF177bWhEydOpH/gOcQrr7wifN5K1/bKK68MnX322VHbrFy5MlRUVBRqbm4OPf744ykfpykUov2NEEIIIfkDY24IIYQQkldQ3BBCCCEkr6C4IYQQQkheQXFDCCGEkLyC4oYQQggheQXFDSGEEELyCoobQgghhOQVFDeEEEIIySsobgghGeOcc87BP/3TP2V6GHj11VdhMpng9XozPRRCSBKguCGEzCmyRVARQlIHxQ0hhBBC8gqKG0JIVjAxMYGbbroJdXV1sFqtaG9vx6uvvhr+/IknnoDD4cCWLVuwdOlSlJWV4dxzz0Vvb294nenpaXz961+Hw+FARUUFbr75Zlx55ZW44IILAABXXXUV/vSnP+GBBx6AyWSCyWRCd3d3ePsdO3Zg7dq1KC0tRUdHBw4cOJCmsyeEJBOKG0JIVnD99ddj+/bteOqpp/Duu+/i85//PM4991x88MEH4XXGxsZw77334j/+4z/w2muv4ciRI7jpppvCn//gBz/Ak08+iccffxxvvPEGfD4fnnvuufDnDzzwANatW4evfOUr6O3tRW9vLxoaGsKff/vb38aPf/xjvP3225g3bx6++MUvpuXcCSHJZV6mB0AIIUeOHMHjjz+OI0eOwOVyAQBuuukmvPjii3j88cdx9913AwCmpqbwyCOPYOHChQBmBdGdd94Z3s+DDz6IW2+9FRdeeCEA4KGHHsILL7wQ/txut6OoqAilpaWoqamJGsf3v/99nH322QCAW265Beeffz4CgQAsFktqTpwQkhIobgghGWfPnj2YmZnB4sWLI5ZPTEygoqIi/HdpaWlY2ABAbW0tBgYGAADDw8Po7+/HmWeeGf68oKAAa9asQTAY1DWO5cuXR+wbAAYGBnDKKacYPylCSMaguCGEZJzR0VEUFBRgx44dKCgoiPisrKws/P+FhYURn5lMJoRCoaSNQ75/k8kEALqFESEke2DMDSEk46xatQozMzMYGBhAS0tLxD+R+0iE3W5HdXU1/vrXv4aXzczMYOfOnRHrFRUVYWZmJqnjJ4RkF7TcEEIyzuLFi3HZZZfhiiuuwI9//GOsWrUKg4OD2Lp1K5YvX47zzz9f135uuOEGbN68GS0tLWhtbcWDDz6IEydOhK0wANDY2Ig333wT3d3dKCsrw4IFC1J1WoSQDEHLDSEkK3j88cdxxRVX4J//+Z+xZMkSXHDBBfjrX/9qKN7l5ptvxiWXXIIrrrgC69atQ1lZGTZs2BAREHzTTTehoKAAbW1tqKysxJEjR1JxOoSQDGIKJdNhTQghWUQwGMTSpUvxhS98AXfddVemh0MISRN0SxFC8oYPP/wQf/jDH3D22WdjYmICDz30EA4fPoxLL70000MjhKQRuqUIIXmD2WzGE088gTPOOANnnXUW9uzZg5dffhlLly7N9NAIIWmEbilCCCGE5BW03BB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", 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "'\\nSTOP\\n#\\n\\nscaler = StandardScaler()\\nscaler.fit(data)\\nStandardScaler()\\n>>> print(scaler.mean_)\\n[0.5 0.5]\\n>>> print(scaler.transform(data))\\n\\nx_scaler, x_train, x_val = StandardScaler(x_train, x_val)\\ny_scaler, y_train, y_val = StandardScaler(y_train, y_val)\\n'" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# prepare the training, validation, and test set split:\n", - "\n", - "val_proportion = 0.1\n", - "x_train, x_val, y_train, y_val = train_test_split(norm_xs, norm_ys, test_size=val_proportion, random_state=42)\n", - "\n", - "print(np.shape(x_train), np.shape(y_train))\n", - "print(np.shape(x_train[:][0]))\n", - "\n", - "\n", - "plt.clf()\n", - "plt.scatter(x_train[:,0], y_train, label = 'training', color = '#B5DDA4', s = 10)\n", - "plt.scatter(x_val[:,0], y_val, label = 'val', color = '#FAA381', s = 10)\n", - "plt.legend()\n", - "plt.xlabel('length')\n", - "plt.ylabel('x position')\n", - "plt.show()\n", - "\n", - "plt.clf()\n", - "plt.scatter(x_train[:,1], y_train, label = 'training', color = '#B5DDA4', s = 10)\n", - "plt.scatter(x_val[:,1], y_val, label = 'val', color = '#FAA381', s = 10)\n", - "plt.legend()\n", - "plt.xlabel('theta')\n", - "plt.ylabel('x position')\n", - "plt.show()\n", - "\n", - "plt.clf()\n", - "plt.scatter(x_train[:,2], y_train, label = 'training', color = '#B5DDA4', s = 10)\n", - "plt.scatter(x_val[:,2], y_val, label = 'val', color = '#FAA381', s = 10)\n", - "plt.legend()\n", - "plt.xlabel('a_g')\n", - "plt.ylabel('x position')\n", - "plt.show()\n", - "\n", - "\n", - "\n", - "'''\n", - "STOP\n", - "#\n", - "\n", - "scaler = StandardScaler()\n", - "scaler.fit(data)\n", - "StandardScaler()\n", - ">>> print(scaler.mean_)\n", - "[0.5 0.5]\n", - ">>> print(scaler.transform(data))\n", - "\n", - "x_scaler, x_train, x_val = StandardScaler(x_train, x_val)\n", - "y_scaler, y_train, y_val = StandardScaler(y_train, y_val)\n", - "'''" - ] - }, - { - "cell_type": "code", - "execution_count": 5, "id": "7bfe9a7f", "metadata": {}, "outputs": [], @@ -374,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "26d4dde4", "metadata": {}, "outputs": [ @@ -382,17 +128,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "tensor([4.2693, 0.0320, 7.7920])\n" + "tensor([6.1716, 0.0338, 4.2549])\n" ] } ], "source": [ - "L_low = [0.3]\n", - "L_high = [4.0]\n", - "\n", "num_dim = 3\n", "\n", - "low_bounds = torch.tensor([1, np.pi/200, 5])\n", + "low_bounds = torch.tensor([1, np.pi/500, 1])\n", "high_bounds = torch.tensor([10, 3*np.pi/200, 10])\n", "\n", "prior = utils.BoxUniform(low = low_bounds, high = high_bounds)\n", @@ -401,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "0d90f3ef", "metadata": {}, "outputs": [], @@ -434,39 +177,52 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "c7d0effa", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cc0043d71df740429f053d339a0bf16a", + "model_id": "e86df6e27fb94cea86c5617b8e24f20b", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "Running 1000 simulations.: 0%| | 0/1000 [00:00 1\u001b[0m posterior \u001b[38;5;241m=\u001b[39m \u001b[43minfer\u001b[49m\u001b[43m(\u001b[49m\u001b[43msimulator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprior\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mSNPE\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_simulations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m10000\u001b[39;49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/deepuq-DRzT0TL8-py3.9/lib/python3.9/site-packages/sbi/inference/base.py:72\u001b[0m, in \u001b[0;36minfer\u001b[0;34m(simulator, prior, method, num_simulations, num_workers)\u001b[0m\n\u001b[1;32m 69\u001b[0m simulator, prior \u001b[38;5;241m=\u001b[39m prepare_for_sbi(simulator, prior)\n\u001b[1;32m 71\u001b[0m inference \u001b[38;5;241m=\u001b[39m method_fun(prior\u001b[38;5;241m=\u001b[39mprior)\n\u001b[0;32m---> 72\u001b[0m theta, x \u001b[38;5;241m=\u001b[39m \u001b[43msimulate_for_sbi\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[43m \u001b[49m\u001b[43msimulator\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msimulator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 74\u001b[0m \u001b[43m \u001b[49m\u001b[43mproposal\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprior\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 75\u001b[0m \u001b[43m \u001b[49m\u001b[43mnum_simulations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_simulations\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 76\u001b[0m \u001b[43m \u001b[49m\u001b[43mnum_workers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_workers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 77\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 78\u001b[0m _ \u001b[38;5;241m=\u001b[39m inference\u001b[38;5;241m.\u001b[39mappend_simulations(theta, x)\u001b[38;5;241m.\u001b[39mtrain()\n\u001b[1;32m 79\u001b[0m posterior \u001b[38;5;241m=\u001b[39m inference\u001b[38;5;241m.\u001b[39mbuild_posterior()\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/deepuq-DRzT0TL8-py3.9/lib/python3.9/site-packages/sbi/inference/base.py:495\u001b[0m, in \u001b[0;36msimulate_for_sbi\u001b[0;34m(simulator, proposal, num_simulations, num_workers, simulation_batch_size, show_progress_bar)\u001b[0m\n\u001b[1;32m 466\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Returns ($\\theta, x$) pairs obtained from sampling the proposal and simulating.\u001b[39;00m\n\u001b[1;32m 467\u001b[0m \n\u001b[1;32m 468\u001b[0m \u001b[38;5;124;03mThis function performs two steps:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 490\u001b[0m \u001b[38;5;124;03mReturns: Sampled parameters $\\theta$ and simulation-outputs $x$.\u001b[39;00m\n\u001b[1;32m 491\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 493\u001b[0m theta \u001b[38;5;241m=\u001b[39m proposal\u001b[38;5;241m.\u001b[39msample((num_simulations,))\n\u001b[0;32m--> 495\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[43msimulate_in_batches\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 496\u001b[0m \u001b[43m \u001b[49m\u001b[43msimulator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtheta\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msimulation_batch_size\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_workers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshow_progress_bar\u001b[49m\n\u001b[1;32m 497\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 499\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m theta, x\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/deepuq-DRzT0TL8-py3.9/lib/python3.9/site-packages/sbi/simulators/simutils.py:88\u001b[0m, in \u001b[0;36msimulate_in_batches\u001b[0;34m(simulator, theta, sim_batch_size, num_workers, seed, show_progress_bars)\u001b[0m\n\u001b[1;32m 86\u001b[0m simulation_outputs \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 87\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m batch \u001b[38;5;129;01min\u001b[39;00m batches:\n\u001b[0;32m---> 88\u001b[0m simulation_outputs\u001b[38;5;241m.\u001b[39mappend(\u001b[43msimulator\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 89\u001b[0m pbar\u001b[38;5;241m.\u001b[39mupdate(sim_batch_size)\n\u001b[1;32m 91\u001b[0m x \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mcat(simulation_outputs, dim\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/deepuq-DRzT0TL8-py3.9/lib/python3.9/site-packages/sbi/utils/user_input_checks.py:551\u001b[0m, in \u001b[0;36mbatch_loop_simulator\u001b[0;34m(theta)\u001b[0m\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/deepuq-DRzT0TL8-py3.9/lib/python3.9/site-packages/sbi/utils/user_input_checks.py:515\u001b[0m, in \u001b[0;36mpytorch_simulator\u001b[0;34m(theta)\u001b[0m\n", + "Cell \u001b[0;32mIn[6], line 7\u001b[0m, in \u001b[0;36msimulator\u001b[0;34m(thetas)\u001b[0m\n\u001b[1;32m 3\u001b[0m length, theta, a_g \u001b[38;5;241m=\u001b[39m thetas\n\u001b[1;32m 4\u001b[0m \u001b[38;5;66;03m#print('heres what were inputting', thetas, a_g)\u001b[39;00m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m#length_percent_error_all, theta_percent_error_all, a_g_percent_error_all = \\\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;66;03m# percent_errors\u001b[39;00m\n\u001b[0;32m----> 7\u001b[0m pendulum \u001b[38;5;241m=\u001b[39m \u001b[43mPendulum\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43mpendulum_arm_length\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mlength\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[43mstarting_angle_radians\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtheta\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43macceleration_due_to_gravity\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ma_g\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43mnoise_std_percent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\n\u001b[1;32m 12\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpendulum_arm_length\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.0\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 13\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstarting_angle_radians\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 14\u001b[0m \u001b[43m 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\u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/deepuq-DRzT0TL8-py3.9/lib/python3.9/site-packages/deepbench/physics_object/pendulum.py:135\u001b[0m, in \u001b[0;36m__init__\u001b[0;34m(self, pendulum_arm_length, starting_angle_radians, noise_std_percent, acceleration_due_to_gravity, big_G_newton, phi_planet, mass_pendulum_bob, coefficient_friction)\u001b[0m\n", + "File \u001b[0;32m/opt/homebrew/Caskroom/miniconda/base/lib/python3.9/logging/__init__.py:1135\u001b[0m, in \u001b[0;36m__init__\u001b[0;34m(self, filename, mode, encoding, delay, errors)\u001b[0m\n", + "File \u001b[0;32m/opt/homebrew/Caskroom/miniconda/base/lib/python3.9/posixpath.py:380\u001b[0m, in \u001b[0;36mabspath\u001b[0;34m(path)\u001b[0m\n", + "\u001b[0;31mOSError\u001b[0m: [Errno 24] Too many open files" ] } ], "source": [ - "posterior = infer(simulator, prior, \"SNPE\", num_simulations=1000)" + "posterior = infer(simulator, prior, \"SNPE\", num_simulations=10000)" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "id": "4102596e", "metadata": {}, "outputs": [ @@ -474,29 +230,29 @@ "name": "stdout", "output_type": "stream", "text": [ - "[0. 0.00197814 0.00355215 0.00518085 0.00828634 0.00966774\n", - " 0.00919774 0.01167764 0.0122135 0.01491799 0.01526217 0.01883471\n", - " 0.02081954 0.02058699 0.02494227 0.02217283 0.024586 0.02578148\n", - " 0.02496162 0.03236943 0.03217136 0.03195316 0.04126398 0.04011\n", - " 0.04309779 0.0413649 0.03431496 0.05272706 0.04339631 0.05056688\n", - " 0.05622976 0.06275812 0.04611334 0.05582771 0.06824473 0.05559005\n", - " 0.05904306 0.05903583 0.07764199 0.07493586 0.06455917 0.06258196\n", - " 0.06761967 0.07656815 0.0932496 0.07637863 0.06456149 0.06926533\n", - " 0.08423988 0.08916312 0.09140379 0.09752479 0.07640514 0.09955078\n", - " 0.07920522 0.0966264 0.10068067 0.10153785 0.09035003 0.08220051\n", - " 0.10226456 0.10669141 0.10436796 0.09725107 0.12668815 0.1140712\n", - " 0.12901969 0.13200387 0.10876126 0.11896254 0.11521305 0.10945707\n", - " 0.11242771 0.14384585 0.12532788 0.12397351 0.14857099 0.10404748\n", - " 0.11984162 0.14550079 0.12608133 0.16050655 0.14860422 0.12747917\n", - " 0.12439881 0.14937617 0.14112443 0.12644754 0.14633483 0.13729243\n", - " 0.13925727 0.15544037 0.15743326 0.17506317 0.15130409 0.13960172\n", - " 0.15229963 0.178797 0.17178572 0.19207072]\n" + "[ 0.07625158 0.08049497 0.09278156 0.06236312 0.08333401 0.08372527\n", + " 0.07612885 0.08864967 0.06947212 0.08427258 0.07112986 0.07345919\n", + " 0.08093297 0.08278143 0.07708453 0.0896376 0.07609298 0.0623881\n", + " 0.08728749 0.06844008 0.06962766 0.08282833 0.06933933 0.07545184\n", + " 0.06952057 0.06881789 0.0761766 0.06252401 0.06426313 0.0582699\n", + " 0.04921441 0.05879513 0.05600547 0.0541257 0.06640297 0.05142542\n", + " 0.04955162 0.05071783 0.05250058 0.05361158 0.05015727 0.04254812\n", + " 0.03757062 0.04678548 0.03337447 0.0382374 0.03071208 0.04042319\n", + " 0.03530869 0.02688927 0.02644155 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", + "image/png": 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", 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" ] @@ -519,7 +275,8 @@ } ], "source": [ - "x_o_1 = simulator([5, np.pi/100, 5])\n", + "#x_o_1 = simulator([5, np.pi/100, 5])\n", + "x_o_1 = simulator([5, np.pi/200, 7])\n", "print(x_o_1)\n", "posterior_samples_1 = posterior.sample((10000,), x=x_o_1)\n", "\n", @@ -528,15 +285,34 @@ " posterior_samples_1, \n", " labels = ['L',r'$\\theta_0$','$a_g$'],\n", " limits = [[0,10],[np.pi/200,3*np.pi/200],[0,10]],\n", + " truths = [5, np.pi/100, 5],\n", " figsize=(5, 5)\n", ")\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "053817fb", "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.031415926535897934\n" + ] + } + ], + "source": [ + "print(np.pi/100)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23d40aa4-5e55-496e-a32b-dec65d90fb58", + "metadata": {}, "outputs": [], "source": [] }