From 77a4959fe2c16b32f558de2be985aaa3297be1be Mon Sep 17 00:00:00 2001 From: Remy Moll Date: Fri, 3 Jan 2025 14:20:22 +0100 Subject: [PATCH] better structure. most of task 1 done --- nbody/checklist.md | 12 +- nbody/{ => data}/N_Body_project_2021-2.pdf | Bin nbody/notebook.ipynb | 422 ----------------- nbody/{ => reference}/1990ApJ___356__359H.pdf | Bin nbody/{ => reference}/N_Body_project_2022.pdf | Bin nbody/{ => reference}/notes.md | 0 nbody/task1.ipynb | 366 +++++++++++++++ nbody/task2-particle-mesh.ipynb | 443 ++++++++++++++++++ nbody/utils/__init__.py | 13 +- nbody/utils/{forces.py => forces_basic.py} | 6 +- nbody/utils/forces_mesh.py | 185 ++++++++ nbody/utils/forces_tree.py | 0 nbody/utils/logging_config.py | 15 + 13 files changed, 1032 insertions(+), 430 deletions(-) rename nbody/{ => data}/N_Body_project_2021-2.pdf (100%) delete mode 100644 nbody/notebook.ipynb rename nbody/{ => reference}/1990ApJ___356__359H.pdf (100%) rename nbody/{ => reference}/N_Body_project_2022.pdf (100%) rename nbody/{ => reference}/notes.md (100%) create mode 100644 nbody/task1.ipynb create mode 100644 nbody/task2-particle-mesh.ipynb rename nbody/utils/{forces.py => forces_basic.py} (96%) create mode 100644 nbody/utils/forces_mesh.py create mode 100644 nbody/utils/forces_tree.py create mode 100644 nbody/utils/logging_config.py diff --git a/nbody/checklist.md b/nbody/checklist.md index d8d6632..a8c0e2f 100644 --- a/nbody/checklist.md +++ b/nbody/checklist.md @@ -4,8 +4,16 @@ - [ ] Compute characteristic quantities/scales - [x] Compare analytical model and particle density distribution - [ ] Compute forces through nbody simulation -- [ ] vary softening length and compare results -- [ ] compare with the analytical expectation from Newtons 2nd law +- [x] vary softening length and compare results +- [x] compare with the analytical expectation from Newtons 2nd law - [ ] compute the relaxation time ### Task 2 + + + + + + +### Questions +- Procedure for each time step of a mesh simulation? Potential on mesh -> forces on particles -> update particle positions -> new mesh potential? or skip the creation of particles in each time step? \ No newline at end of file diff --git a/nbody/N_Body_project_2021-2.pdf b/nbody/data/N_Body_project_2021-2.pdf similarity index 100% rename from nbody/N_Body_project_2021-2.pdf rename to nbody/data/N_Body_project_2021-2.pdf diff --git a/nbody/notebook.ipynb b/nbody/notebook.ipynb deleted file mode 100644 index d8bbb4e..0000000 --- a/nbody/notebook.ipynb +++ /dev/null @@ -1,422 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2\n", - "from pathlib import Path\n", - "import numpy as np\n", - "import utils\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import logging\n", - "# logging.basicConfig(level=logging.INFO)\n", - "logging.basicConfig(level=logging.DEBUG)\n", - "logger = logging.getLogger(__name__)\n", - "\n", - "# silence some debug messages\n", - "logging.getLogger('matplotlib.font_manager').setLevel(logging.WARNING)\n", - "logging.getLogger('matplotlib.ticker').setLevel(logging.WARNING)\n", - "logging.getLogger('matplotlib.pyplot').setLevel(logging.WARNING)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "DATA_ROOT = Path('data')\n", - "# DATA_NAME = 'data.txt'\n", - "DATA_NAME = 'data0.txt'\n", - "# DATA_NAME = 'data1.txt'\n", - "NBINS = 50" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:utils.load:Loaded 1008 rows and 9 columns from data/data0.txt\n", - "DEBUG:__main__:Fetched 1008 points, columns: ['ID', 'M', 'x', 'y', 'z', 'vx', 'vy', 'vz', 'eps']\n" - ] - } - ], - "source": [ - "points, columns = utils.load_data(DATA_ROOT / DATA_NAME)\n", - "logger.debug(f\"Fetched {points.shape[0]} points, columns: {columns}\")\n", - "# reorder the columns to match the expected order (x, y, z, mass)\n", - "particles = points[:, [2, 3, 4, 1]]\n", - "\n", - "particles = particles[::10, ...]\n", - "# particles = particles[:5000, ...]\n", - "# TODO: remove this\n", - "\n", - "particles = utils.remove_outliers(particles)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# plot the distribution of the particles\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "ax.scatter(particles[:,0], particles[:,1], particles[:,2], cmap='viridis', c=particles[:,3])\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": [ - "all_r = utils.r_distribution(particles)\n", - "rbins = np.logspace(np.min(all_r), np.max(all_r), NBINS)\n", - "rho, err = utils.density_distribution(rbins, particles, ret_error=True)\n", - "rho_t = utils.model_density_distribution(rbins)\n", - "\n", - "\n", - "plt.figure()\n", - "plt.title('Density distribution')\n", - "# set the scale to log-log\n", - "plt.xscale('log')\n", - "plt.yscale('log')\n", - "plt.xlabel('r')\n", - "plt.ylabel('rho')\n", - "plt.errorbar(rbins, rho, yerr=err, fmt='o', label=\"Particle data\")\n", - "plt.plot(rbins, rho_t, 'r-', label=\"Analytic model\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Choice of units" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# Set G = 1\n", - "G = 1\n", - "\n", - "# Since we have an elliptical galaxy, we can use typical values\n", - "M_TOT = 1e12 # Msol\n", - "R_TOT = 100 # kpc\n", - "\n", - "# For this system the virial theorem gives the typical velocity\n", - "V_MEAN = np.sqrt(G * M_TOT / R_TOT)\n", - "# For units of time we use the dynamical time or crossing time\n", - "T_MEAN = R_TOT / V_MEAN\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEBUG:utils.particles:Half mass radius: 0.0 for 0th particle of 101\n", - "DEBUG:utils.particles:Number of particles within half mass radius: 0 of 101\n", - "/home/remy/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/particles.py:73: RuntimeWarning: invalid value encountered in scalar divide\n", - " rho = n_half_mass / (4/3 * np.pi * r_half_mass**3)\n", - "INFO:__main__:Mean interparticle distance: nan\n", - "DEBUG:utils.forces:Computing forces for 101 particles using n^2 algorithm\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Computing forces for 101 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Computing forces for 101 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Computing forces for 101 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Computing forces for 101 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Computing forces for 101 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Computing forces for 101 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Computing forces for 101 particles using spherical approximation\n", - "/home/remy/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/forces.py:71: RuntimeWarning: invalid value encountered in scalar divide\n", - " f = - m_current * m_enclosed / r_current**2\n", - "DEBUG:utils.forces:Particle 0 done\n" - ] - } - ], - "source": [ - "### Direct N body force computation\n", - "epsilon = utils.mean_interparticle_distance(particles)\n", - "logger.info(f\"Mean interparticle distance: {epsilon}\")\n", - "\n", - "f_nsquare = utils.n_body_forces(particles, G, 0)\n", - "f_nsquare_1e = utils.n_body_forces(particles, G, epsilon)\n", - "f_nsquare_2e = utils.n_body_forces(particles, G, 2*epsilon)\n", - "f_nsquare_5e = utils.n_body_forces(particles, G, 5*epsilon)\n", - "f_nsquare_05e = utils.n_body_forces(particles, G, 0.5*epsilon)\n", - "f_nsquare_01e = utils.n_body_forces(particles, G, 0.1*epsilon)\n", - "f_nsquare_001e = utils.n_body_forces(particles, G, 0.01*epsilon)\n", - "\n", - "f_analytical = utils.analytical_forces(particles)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/remy/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/matplotlib/axes/_axes.py:6973: RuntimeWarning: All-NaN slice encountered\n", - " xmin = min(xmin, np.nanmin(xi))\n", - "/home/remy/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/matplotlib/axes/_axes.py:6974: RuntimeWarning: All-NaN slice encountered\n", - " xmax = max(xmax, np.nanmax(xi))\n" - ] - }, - { - "ename": "ValueError", - "evalue": "autodetected range of [nan, nan] is not finite", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[9], line 13\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;66;03m# plot the distribution of the error\u001b[39;00m\n\u001b[1;32m 11\u001b[0m \u001b[38;5;66;03m# create 4 stacked histograms, sharing the same x axis\u001b[39;00m\n\u001b[1;32m 12\u001b[0m fig, ax \u001b[38;5;241m=\u001b[39m plt\u001b[38;5;241m.\u001b[39msubplots(\u001b[38;5;241m4\u001b[39m, sharex\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m---> 13\u001b[0m \u001b[43max\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhist\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdiff_mag\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbins\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mNBINS\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 14\u001b[0m ax[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mset_title(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMagnitude of the force difference\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 15\u001b[0m ax[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mset_yscale(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlog\u001b[39m\u001b[38;5;124m'\u001b[39m)\n", - "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/matplotlib/__init__.py:1476\u001b[0m, in \u001b[0;36m_preprocess_data..inner\u001b[0;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1473\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m 1474\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minner\u001b[39m(ax, \u001b[38;5;241m*\u001b[39margs, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 1475\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m data \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1476\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1477\u001b[0m \u001b[43m \u001b[49m\u001b[43max\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1478\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mmap\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43msanitize_sequence\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1479\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m{\u001b[49m\u001b[43mk\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43msanitize_sequence\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1481\u001b[0m bound \u001b[38;5;241m=\u001b[39m new_sig\u001b[38;5;241m.\u001b[39mbind(ax, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 1482\u001b[0m auto_label \u001b[38;5;241m=\u001b[39m (bound\u001b[38;5;241m.\u001b[39marguments\u001b[38;5;241m.\u001b[39mget(label_namer)\n\u001b[1;32m 1483\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m bound\u001b[38;5;241m.\u001b[39mkwargs\u001b[38;5;241m.\u001b[39mget(label_namer))\n", - "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/matplotlib/axes/_axes.py:7001\u001b[0m, in \u001b[0;36mAxes.hist\u001b[0;34m(self, x, bins, range, density, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)\u001b[0m\n\u001b[1;32m 6997\u001b[0m \u001b[38;5;66;03m# Loop through datasets\u001b[39;00m\n\u001b[1;32m 6998\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(nx):\n\u001b[1;32m 6999\u001b[0m \u001b[38;5;66;03m# this will automatically overwrite bins,\u001b[39;00m\n\u001b[1;32m 7000\u001b[0m \u001b[38;5;66;03m# so that each histogram uses the same bins\u001b[39;00m\n\u001b[0;32m-> 7001\u001b[0m m, bins \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhistogram\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbins\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mw\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\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[43mhist_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 7002\u001b[0m tops\u001b[38;5;241m.\u001b[39mappend(m)\n\u001b[1;32m 7003\u001b[0m tops \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(tops, \u001b[38;5;28mfloat\u001b[39m) \u001b[38;5;66;03m# causes problems later if it's an int\u001b[39;00m\n", - "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/numpy/lib/_histograms_impl.py:797\u001b[0m, in \u001b[0;36mhistogram\u001b[0;34m(a, bins, range, density, weights)\u001b[0m\n\u001b[1;32m 688\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 689\u001b[0m \u001b[38;5;124;03mCompute the histogram of a dataset.\u001b[39;00m\n\u001b[1;32m 690\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 793\u001b[0m \n\u001b[1;32m 794\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 795\u001b[0m a, weights \u001b[38;5;241m=\u001b[39m _ravel_and_check_weights(a, weights)\n\u001b[0;32m--> 797\u001b[0m bin_edges, uniform_bins \u001b[38;5;241m=\u001b[39m \u001b[43m_get_bin_edges\u001b[49m\u001b[43m(\u001b[49m\u001b[43ma\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbins\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 799\u001b[0m \u001b[38;5;66;03m# Histogram is an integer or a float array depending on the weights.\u001b[39;00m\n\u001b[1;32m 800\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m weights \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/numpy/lib/_histograms_impl.py:430\u001b[0m, in \u001b[0;36m_get_bin_edges\u001b[0;34m(a, bins, range, weights)\u001b[0m\n\u001b[1;32m 427\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n_equal_bins \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m 428\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m`bins` must be positive, when an integer\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 430\u001b[0m first_edge, last_edge \u001b[38;5;241m=\u001b[39m \u001b[43m_get_outer_edges\u001b[49m\u001b[43m(\u001b[49m\u001b[43ma\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 432\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m np\u001b[38;5;241m.\u001b[39mndim(bins) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m 433\u001b[0m bin_edges \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39masarray(bins)\n", - "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/numpy/lib/_histograms_impl.py:323\u001b[0m, in \u001b[0;36m_get_outer_edges\u001b[0;34m(a, range)\u001b[0m\n\u001b[1;32m 321\u001b[0m first_edge, last_edge \u001b[38;5;241m=\u001b[39m a\u001b[38;5;241m.\u001b[39mmin(), a\u001b[38;5;241m.\u001b[39mmax()\n\u001b[1;32m 322\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (np\u001b[38;5;241m.\u001b[39misfinite(first_edge) \u001b[38;5;129;01mand\u001b[39;00m np\u001b[38;5;241m.\u001b[39misfinite(last_edge)):\n\u001b[0;32m--> 323\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 324\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mautodetected range of [\u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m] is not finite\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(first_edge, last_edge))\n\u001b[1;32m 326\u001b[0m \u001b[38;5;66;03m# expand empty range to avoid divide by zero\u001b[39;00m\n\u001b[1;32m 327\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m first_edge \u001b[38;5;241m==\u001b[39m last_edge:\n", - "\u001b[0;31mValueError\u001b[0m: autodetected range of [nan, nan] is not finite" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "## compare the two force calculations\n", - "# since the forces were computed for each particle, rather than comparing them directly we compare the relative error in the magnitude and direction of the forces\n", - "\n", - "\n", - "# f_diff = f_nsquare_1e - f_analytical\n", - "f_diff = f_nsquare_2e - f_analytical\n", - "diff_mag = np.linalg.norm(f_diff, axis=1)\n", - "\n", - "\n", - "# plot the distribution of the error\n", - "# create 4 stacked histograms, sharing the same x axis\n", - "fig, ax = plt.subplots(4, sharex=True)\n", - "ax[0].hist(diff_mag, bins=NBINS)\n", - "ax[0].set_title('Magnitude of the force difference')\n", - "ax[0].set_yscale('log')\n", - "\n", - "ax[1].hist(f_diff[:,0], bins=NBINS)\n", - "ax[1].set_title('X component of the force difference')\n", - "ax[1].set_yscale('log')\n", - "\n", - "ax[2].hist(f_diff[:,1], bins=NBINS)\n", - "ax[2].set_title('Y component of the force difference')\n", - "ax[2].set_yscale('log')\n", - "\n", - "ax[3].hist(f_diff[:,2], bins=NBINS)\n", - "ax[3].set_title('Z component of the force difference')\n", - "ax[3].set_yscale('log')\n", - "\n", - "plt.title('Error in forces')\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "## Plot the radial force behaviour\n", - "r = np.linalg.norm(particles[:,:3], axis=1)\n", - "r_sort = np.argsort(r)\n", - "# r = r[r_sort]\n", - "# f_nsquare_1e = f_nsquare_1e[r_sort]\n", - "# f_nsquare_2e = f_nsquare_2e[r_sort]\n", - "# f_analytical = f_analytical[r_sort]\n", - "\n", - "plt.figure()\n", - "plt.title('Radial force behaviour')\n", - "plt.xscale('log')\n", - "plt.yscale('log')\n", - "plt.xlabel('r')\n", - "plt.ylabel('f')\n", - "\n", - "plt.plot(r, np.linalg.norm(f_analytical, axis=1), 'o', label=\"Analytical\")\n", - "\n", - "plt.plot(r, np.linalg.norm(f_nsquare, axis=1), 'o', label=\"N^2\")\n", - "plt.plot(r, np.linalg.norm(f_nsquare_1e, axis=1), 'o', label=\"N^2 - 1epsilon\")\n", - "plt.plot(r, np.linalg.norm(f_nsquare_2e, axis=1), 'o', label=\"N^2 - 2epsilon\")\n", - "plt.plot(r, np.linalg.norm(f_nsquare_5e, axis=1), 'o', label=\"N^2 - 5epsilon\")\n", - "# plt.plot(r, np.linalg.norm(f_nsquare_05e, axis=1), 'o', label=\"N^2 - 0.5epsilon\")\n", - "# plt.plot(r, np.linalg.norm(f_nsquare_01e, axis=1), 'o', label=\"N^2 - 0.1epsilon\")\n", - "# plt.plot(r, np.linalg.norm(f_nsquare_001e, axis=1), 'o', label=\"N^2 - 0.01epsilon\")\n", - "\n", - "plt.legend()\n", - "plt.show()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Task 2 - Particle mesh" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEBUG:utils.integrate:Reshaped (1008, 7) to y0 with (6048,) and masses with (1008,)\n", - "DEBUG:utils.integrate:y with shape (6048,)\n", - "DEBUG:utils.integrate:Unstacked y into x with shape (1008, 3) and v with shape (1008, 3)\n", - "DEBUG:utils.forces:Computing forces for 1008 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEBUG:utils.forces:Particle 1000 done\n", - "DEBUG:utils.integrate:y with shape (6048,)\n", - "DEBUG:utils.integrate:Unstacked y into x with shape (1008, 3) and v with shape (1008, 3)\n", - "DEBUG:utils.forces:Computing forces for 1008 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Particle 1000 done\n", - "DEBUG:utils.integrate:y with shape (6048,)\n", - "DEBUG:utils.integrate:Unstacked y into x with shape (1008, 3) and v with shape (1008, 3)\n", - "DEBUG:utils.forces:Computing forces for 1008 particles using n^2 algorithm\n", - "DEBUG:utils.forces:Particle 0 done\n", - "DEBUG:utils.forces:Particle 1000 done\n", - "/tmp/ipykernel_36731/3498856150.py:13: ODEintWarning: Excess accuracy requested (tolerances too small). Run with full_output = 1 to get quantitative information.\n", - " sol = spi.odeint(y_prime, y0, np.arange(0, n_steps*dt, dt), atol=1e3,rtol=1e2)\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " lsoda-- at t (=r1), too much accuracy requested \u0000\u0000\n", - " for precision of machine.. see tolsf (=r2) \u0000\u0000\n", - " in above, r1 = 0.1000000000000D+00 r2 = NaN\n" - ] - } - ], - "source": [ - "# load the particles in the format [x, y, z, vx, vy, vz, mass]\n", - "particles = points[:, [2, 3, 4, 5, 6, 7, 1]]\n", - "\n", - "# we can now integrate this system for a few steps\n", - "dt = 0.1\n", - "n_steps = 10\n", - "force_function = lambda x: utils.n_body_forces(x, G, epsilon)\n", - "y0, y_prime = utils.ode_setup(particles, force_function)\n", - "\n", - "import scipy.integrate as spi\n", - "\n", - "# integrate the system\n", - "sol = spi.odeint(y_prime, y0, np.arange(0, n_steps*dt, dt), atol=1e3,rtol=1e2)\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "projects-X-9bmgL6", - "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": "3.12.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/nbody/1990ApJ___356__359H.pdf b/nbody/reference/1990ApJ___356__359H.pdf similarity index 100% rename from nbody/1990ApJ___356__359H.pdf rename to nbody/reference/1990ApJ___356__359H.pdf diff --git a/nbody/N_Body_project_2022.pdf b/nbody/reference/N_Body_project_2022.pdf similarity index 100% rename from nbody/N_Body_project_2022.pdf rename to nbody/reference/N_Body_project_2022.pdf diff --git a/nbody/notes.md b/nbody/reference/notes.md similarity index 100% rename from nbody/notes.md rename to nbody/reference/notes.md diff --git a/nbody/task1.ipynb b/nbody/task1.ipynb new file mode 100644 index 0000000..7c8feac --- /dev/null +++ b/nbody/task1.ipynb @@ -0,0 +1,366 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The autoreload extension is already loaded. To reload it, use:\n", + " %reload_ext autoreload\n" + ] + } + ], + "source": [ + "# automatically reflect changes in imported modules\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "from pathlib import Path\n", + "import numpy as np\n", + "import utils\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import utils.logging_config\n", + "import logging\n", + "logger = logging.getLogger(\"task1\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "DATA_ROOT = Path('data')\n", + "DATA_NAME = 'data.txt'\n", + "# DATA_NAME = 'data0.txt'\n", + "# DATA_NAME = 'data1.txt'\n", + "NBINS = 100" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "13:55:14 - utils.load - Loaded 50010 rows and 10 columns from data/data.txt\n", + "13:55:14 - task1 - Fetched 50010 points, columns: ['ID', 'MASS', 'X', 'Y', 'Z', 'VX', 'VY', 'VZ', 'SOFTENING', '?']\n" + ] + } + ], + "source": [ + "points, columns = utils.load_data(DATA_ROOT / DATA_NAME)\n", + "logger.debug(f\"Fetched {points.shape[0]} points, columns: {columns}\")\n", + "# reorder the columns to match the expected order (x, y, z, mass)\n", + "particles = points[:, [2, 3, 4, 1]]\n", + "\n", + "particles = particles[::10, ...]\n", + "# particles = particles[:5000, ...]\n", + "# TODO: remove this\n", + "\n", + "# particles = utils.remove_outliers(particles)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# plot the distribution of the particles\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "ax.scatter(particles[:,0], particles[:,1], particles[:,2], cmap='viridis', c=particles[:,3])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/remy/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/numpy/_core/function_base.py:314: RuntimeWarning: overflow encountered in power\n", + " return _nx.power(base, y)\n", + "/home/remy/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/particles.py:19: RuntimeWarning: overflow encountered in power\n", + " volume = 4/3 * np.pi * (r_bins[1:]**3 - r_bins[:-1]**3)\n", + "/home/remy/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/particles.py:19: RuntimeWarning: invalid value encountered in subtract\n", + " volume = 4/3 * np.pi * (r_bins[1:]**3 - r_bins[:-1]**3)\n", + "/home/remy/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/model.py:11: RuntimeWarning: overflow encountered in power\n", + " rho = M / (2 * np.pi) * a / (r_bins * (r_bins + a)**3)\n", + "/home/remy/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/model.py:11: RuntimeWarning: overflow encountered in multiply\n", + " rho = M / (2 * np.pi) * a / (r_bins * (r_bins + a)**3)\n", + "/home/remy/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/matplotlib/scale.py:255: RuntimeWarning: overflow encountered in power\n", + " return np.power(self.base, values)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "all_r = utils.r_distribution(particles)\n", + "rbins = np.logspace(np.min(all_r), np.max(all_r), NBINS)\n", + "rho, err = utils.density_distribution(rbins, particles, ret_error=True)\n", + "rho_t = utils.model_density_distribution(rbins)\n", + "\n", + "\n", + "plt.figure()\n", + "plt.title('Density distribution')\n", + "# set the scale to log-log\n", + "plt.xscale('log')\n", + "plt.yscale('log')\n", + "plt.xlabel('r')\n", + "plt.ylabel('rho')\n", + "plt.errorbar(rbins, rho, yerr=err, fmt='o', label=\"Particle data\")\n", + "plt.plot(rbins, rho_t, 'r-', label=\"Analytic model\")\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Choice of units" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# Set G = 1\n", + "G = 1\n", + "\n", + "# Since we have an elliptical galaxy, we can use typical values\n", + "M_TOT = 1e12 # Msol\n", + "R_TOT = 100 # kpc\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "13:56:50 - utils.particles - Half mass radius: 0.18508311314012416 for 2499th particle of 5001\n", + "13:56:50 - utils.particles - Number of particles within half mass radius: 2499 of 5001\n", + "13:56:50 - task1 - Mean interparticle distance: 0.021985731180436525\n", + "13:56:50 - utils.forces_basic - Computing forces for 5001 particles using n^2 algorithm (using softening=np.float64(2.1985731180436524e-05))\n", + "13:56:50 - utils.forces_basic - Particle 0 done\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1.e-03 1.e-02 1.e-01 1.e+00 1.e+01 1.e+02 1.e+03]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "13:56:51 - utils.forces_basic - Particle 5000 done\n", + "13:56:51 - utils.forces_basic - Computing forces for 5001 particles using n^2 algorithm (using softening=np.float64(0.00021985731180436527))\n", + "13:56:51 - utils.forces_basic - Particle 0 done\n", + "13:56:53 - utils.forces_basic - Particle 5000 done\n", + "13:56:53 - utils.forces_basic - Computing forces for 5001 particles using n^2 algorithm (using softening=np.float64(0.0021985731180436527))\n", + "13:56:53 - utils.forces_basic - Particle 0 done\n", + "13:56:54 - utils.forces_basic - Particle 5000 done\n", + "13:56:54 - utils.forces_basic - Computing forces for 5001 particles using n^2 algorithm (using softening=np.float64(0.021985731180436525))\n", + "13:56:54 - utils.forces_basic - Particle 0 done\n", + "13:56:55 - utils.forces_basic - Particle 5000 done\n", + "13:56:55 - utils.forces_basic - Computing forces for 5001 particles using n^2 algorithm (using softening=np.float64(0.21985731180436524))\n", + "13:56:55 - utils.forces_basic - Particle 0 done\n", + "13:56:56 - utils.forces_basic - Particle 5000 done\n", + "13:56:56 - utils.forces_basic - Computing forces for 5001 particles using n^2 algorithm (using softening=np.float64(2.1985731180436523))\n", + "13:56:56 - utils.forces_basic - Particle 0 done\n", + "13:56:58 - utils.forces_basic - Particle 5000 done\n", + "13:56:58 - utils.forces_basic - Computing forces for 5001 particles using n^2 algorithm (using softening=np.float64(21.985731180436524))\n", + "13:56:58 - utils.forces_basic - Particle 0 done\n", + "13:56:59 - utils.forces_basic - Particle 5000 done\n", + "13:56:59 - utils.forces_basic - Computing forces for 5001 particles using spherical approximation\n", + "13:56:59 - utils.forces_basic - Particle 0 done\n", + "13:56:59 - utils.forces_basic - Particle 5000 done\n" + ] + } + ], + "source": [ + "### Direct N body force computation and comparison with analytical model\n", + "epsilon = utils.mean_interparticle_distance(particles)\n", + "logger.info(f\"Mean interparticle distance: {epsilon}\")\n", + "\n", + "\n", + "# TODO: compute this in a threaded way\n", + "epsilon_range = np.logspace(-3, 3, 7)\n", + "n_squared_forces = []\n", + "for e in epsilon_range:\n", + " f = utils.n_body_forces(particles, G, e * epsilon)\n", + " n_squared_forces.append(f)\n", + "\n", + "\n", + "analytical_force = utils.analytical_forces(particles)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\"## compare the two force calculations\n", + "# since the forces were computed for each particle, rather than comparing them directly we compare the relative error in the magnitude and direction of the forces\n", + "\n", + "\n", + "# f_diff = f_nsquare_1e - f_analytical\n", + "f_diff = f_nsquare_2e - f_analytical\n", + "diff_mag = np.linalg.norm(f_diff, axis=1)\n", + "\n", + "\n", + "# plot the distribution of the error\n", + "# create 4 stacked histograms, sharing the same x axis\n", + "fig, ax = plt.subplots(4, sharex=True)\n", + "ax[0].hist(diff_mag, bins=NBINS)\n", + "ax[0].set_title('Magnitude of the force difference')\n", + "ax[0].set_yscale('log')\n", + "\n", + "ax[1].hist(f_diff[:,0], bins=NBINS)\n", + "ax[1].set_title('X component of the force difference')\n", + "ax[1].set_yscale('log')\n", + "\n", + "ax[2].hist(f_diff[:,1], bins=NBINS)\n", + "ax[2].set_title('Y component of the force difference')\n", + "ax[2].set_yscale('log')\n", + "\n", + "ax[3].hist(f_diff[:,2], bins=NBINS)\n", + "ax[3].set_title('Z component of the force difference')\n", + "ax[3].set_yscale('log')\n", + "\n", + "plt.title('Error in forces')\n", + "plt.show()\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Plot the radial force behaviour\n", + "r = np.linalg.norm(particles[:,:3], axis=1)\n", + "\n", + "plt.figure()\n", + "plt.title('Radial force behaviour')\n", + "plt.xscale('log')\n", + "plt.yscale('log')\n", + "plt.xlabel('$r$')\n", + "plt.ylabel('$F_r(r)$')\n", + "\n", + "plt.plot(r, np.linalg.norm(analytical_force, axis=1), 'o', label=\"Analytical\", zorder=10)\n", + "\n", + "for e, f in zip(epsilon_range, n_squared_forces):\n", + " plt.plot(r, np.linalg.norm(f, axis=1), '.', label=f\"N^2 - {e:.1g} * epsilon\")\n", + "\n", + "\n", + "plt.legend()\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Takeaways:**\n", + "- basic $N^2$ matches analytical solution without dropoff. but: noisy data from \"bad\" samples\n", + "- $N^2$ with softening matches analytical solution but has a dropoff. No noisy data.\n", + " - softening $\\approx 1 \\varepsilon$ is a sweet spot since the dropoff is \"late\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Relation time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "projects-X-9bmgL6", + "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": "3.12.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/nbody/task2-particle-mesh.ipynb b/nbody/task2-particle-mesh.ipynb new file mode 100644 index 0000000..2bc3111 --- /dev/null +++ b/nbody/task2-particle-mesh.ipynb @@ -0,0 +1,443 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# automatically reflect changes in imported modules\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "from pathlib import Path\n", + "import numpy as np\n", + "import utils\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import utils.logging_config\n", + "import logging\n", + "logger = logging.getLogger(\"task2\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "DATA_ROOT = Path('data')\n", + "# DATA_NAME = 'data0.txt'\n", + "DATA_NAME = 'data1.txt'\n", + "NBINS = 100" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "G = 1\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "14:02:37 - utils.load - Loaded 9913 rows and 9 columns from data/data1.txt\n", + "14:02:37 - task2 - Fetched 9913 points, columns: ['ID', 'M', 'x', 'y', 'z', 'vx', 'vy', 'vz', 'eps']\n" + ] + } + ], + "source": [ + "points, columns = utils.load_data(DATA_ROOT / DATA_NAME)\n", + "logger.debug(f\"Fetched {points.shape[0]} points, columns: {columns}\")\n", + "# reorder the columns to match the expected order (x, y, z, mass)\n", + "particles = points[:, [2, 3, 4, 1]]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# plot the distribution of the particles\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "ax.scatter(particles[:,0], particles[:,1], particles[:,2], cmap='viridis', c=particles[:,3])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "14:02:37 - utils.particles - Half mass radius: 0.26777121151983396 for 4460th particle of 9913\n", + "14:02:37 - utils.particles - Number of particles within half mass radius: 4371 of 9913\n", + "14:02:37 - task2 - Mean interparticle distance: 0.026399750218803673\n", + "14:02:37 - utils.forces_basic - Computing forces for 9913 particles using n^2 algorithm (using softening=np.float64(0.026399750218803673))\n", + "14:02:37 - utils.forces_basic - Particle 0 done\n", + "14:02:39 - utils.forces_basic - Particle 5000 done\n", + "14:02:41 - utils.forces_basic - Computing forces for 9913 particles using spherical approximation\n", + "/home/remy/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/forces_basic.py:71: RuntimeWarning: invalid value encountered in scalar divide\n", + " f = - m_current * m_enclosed / r_current**2\n", + "14:02:41 - utils.forces_basic - Particle 0 done\n", + "14:02:41 - utils.forces_basic - Particle 5000 done\n", + "14:02:42 - utils.forces_mesh - Computing forces for 9913 particles using mesh (using mapping=particle_to_cells_nn)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mesh information for Mesh\n", + "Total mapped mass: 11\n", + "Max cell value: 1.0\n", + "Min cell value: 0.0\n", + "Mean cell value: 1.1e-05\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "14:02:42 - utils.forces_mesh - Using mesh spacing: 0.018181818181818188\n", + "14:02:42 - utils.forces_mesh - Got k_square with: (100, 100, 100), 0.75 0.0\n", + "14:02:42 - utils.forces_mesh - Count of zeros: 1\n", + "14:02:42 - utils.forces_mesh - Got phi with: (100, 100, 100), -109999.75416785493\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mesh information for Mesh potential\n", + "Total mapped mass: -110000000000\n", + "Max cell value: -109999.75416785493\n", + "Min cell value: -110009.05961379336\n", + "Mean cell value: -110000.00000000001\n" + ] + }, + { + "data": { + "image/png": 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", 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AIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUIj4EAoFAIBCMFCI+BAKBQCAQjBQiPgQCgUAgEIwUT3vxsXz5crztbW+b69OYM3z961+HUgpf//rXe253zTXXQCmFn/zkJyM5L0F/CHeFu/MZwt+nN3+3WvFBD6z0ef/73z/r4z/88MM455xz8N3vfrexbvXq1bj44otn/R2CpyeEu4L5DOGvYBB05voEtjTOO+88rFixIln2ghe8YNbHffjhh3Huuedi+fLleMlLXpKsW716Nb73ve/htNNOm/X3jAve+ta34uijj8bU1NRcn8rTBsLdzQPh7txA+Lt5sLXyd6sXH4ceeihe9rKXzfVpzHtUVYWqqub6NJ5WEO5uHgh35wbC382DrZW/W23YZaZ47LHH8Od//ud44QtfiAULFmDRokU49NBDcdddd4Vtvv71r2O//fYDABx//PHBUrzmmmvwyle+El/60pfwwAMPhOXLly8P+27cuBFnn302nvOc52BqagpLly7F+973PmzcuDE5D6UUTj31VNxwww14wQtegKmpKey777646aabGuf80EMP4YQTTsCSJUvCdv/4j//Y2O5nP/sZ3vCGN2C77bbDLrvsgtNPP73xvW0oxR2XL1+O1772tbj11lvx8pe/HNtssw2e/exn4xOf+ETf45199tnQWuPmm29Olp944omYnJxM7rdgMAh3y9ic3LXWYvny5Xj961/fWPfUU09h8eLFOOmkkwY6L0EK4W8Zm7vufeUrX9kaFrvmmmsGOqfNga3e+Vi/fj0effTRZNlOO+3Uuv2Pf/xj3HDDDXjTm96EFStWYN26dfjoRz+Kgw8+GPfccw9233137L333jjvvPPwgQ98ACeeeCJ+93d/FwBw4IEH4lnPehbWr1+Pn/3sZ7jooosAAAsWLAAAGGPwute9DrfeeitOPPFE7L333rj77rtx0UUX4Yc//CFuuOGG5FxuvfVWfO5zn8PJJ5+MhQsX4pJLLsERRxyBBx98EDvuuCMAYN26dXjFK14RCszOO++ML3/5y3j729+ODRs2BPvxN7/5DV796lfjwQcfxLvf/W7svvvu+OQnP4l/+7d/m9X9/dGPfoQjjzwSb3/723HcccfhH//xH/G2t70NK1euxL777tu631/91V/hxhtvxNvf/nbcfffdWLhwIb7yla/gYx/7GM4//3y8+MUvntV5bQ0Q7p4GYLy4q5TCscceiw9+8IN47LHHsMMOO4R1N954IzZs2IBjjz12Vue1tUD4exqA8eIvAPzlX/4l3vGOdyTLPvWpT+ErX/kKdtlll1md01CwWymuvvpqC6D44Vi2bJk97rjjwvxTTz1l67pOtrn//vvt1NSUPe+888Ky22+/3QKwV199deO7DzvsMLts2bLG8k9+8pNWa23/4z/+I1l+5ZVXWgD2G9/4RlgGwE5OTtof/ehHYdldd91lAdiPfOQjYdnb3/52u9tuu9lHH300OebRRx9tFy9ebH/9619ba629+OKLLQB7/fXXh22efPJJ+5znPMcCsF/72tca58tB9/P+++8Py5YtW2YB2H//938Pyx555BE7NTVl/+zP/qzn8ay19u6777aTk5P2He94h/3lL39pn/WsZ9mXvexldnp6uu++WzOEu+PN3XvvvdcCsFdccUWy/HWve51dvny5Ncb03H9rh/B3vPmb4xvf+IadmJiwJ5xwwlD7zRZbfdjlsssuw7/+678mn16YmpqC1u621HWNX/ziF1iwYAGe//zn484775zVuaxZswZ777039tprLzz66KPh8/u///sAgK997WvJ9qtWrcKee+4Z5l/0ohdh0aJF+PGPfwzAWcD//M//jMMPPxzW2uSYhxxyCNavXx/O+V/+5V+w22674cgjjwzHe8YznoETTzxxVte0zz77hNYHAOy88854/vOfH86xF17wghfg3HPPxf/5P/8HhxxyCB599FFce+216HS2ekNuIAh3x5O7z3ve87D//vvjuuuuC8see+wxfPnLX8YxxxwDpdSszmtrgfB3PPnLsXbtWhx55JF4yUtegssvv3xW5zMstvpa/uUvf/lQSU/GGHz4wx/G5Zdfjvvvvx91XYd1ZLfNFPfddx++//3vY+eddy6uf+SRR5L5PfbYo7HNM5/5TPzyl78EAPz85z/H448/jquuugpXXXVVz2M+8MADeM5zntOoGJ///OcPfR3DnGM/vPe978WnP/1pfPvb38YFF1yAffbZZ1bnszVBuDu+3P3jP/5jnHrqqXjggQewbNkyrFmzBtPT03jrW986q3PamiD8HV/+AkC328VRRx2Fuq7xuc99buS9abZ68TEsLrjgApx11lk44YQTcP7552OHHXaA1hqnnXYajDGzOrYxBi984QvxoQ99qLh+6dKlyXxbhrO1NhwPAI499lgcd9xxxW1f9KIXzfR0B0K/c+yHH//4x7jvvvsAAHffffdmO6+nI4S7w2E23D366KNx+umn47rrrsNf/MVf4FOf+hRe9rKXzfoH5ekM4e9wmG3d+973vhe33XYbvvrVr+K3fuu3NuepDQQRHxk++9nP4lWvehU+/vGPJ8sff/zxJFmql7Xatm7PPffEXXfdhVe/+tWbxZrdeeedsXDhQtR1jVWrVvXcdtmyZfje974Ha23y3ffee++sz2OmMMbgbW97GxYtWoTTTjsNF1xwAY488ki88Y1vnLNzms8Q7o4OO+ywAw477DBcd911OOaYY/CNb3xDBreaJYS/o8OnP/1pXHzxxbj44otx8MEHz8k5bPU5H8OiqqqGclyzZg0eeuihZNl2220HwBWMHNtttx3Wr1/fWH7UUUfhoYcewsc+9rHGut/85jd48sknhz7XI444Av/8z/+M733ve431P//5z8P0H/zBH+Dhhx/GZz/72bDs17/+datlOAp86EMfwje/+U1cddVVOP/883HggQfiXe96VyNDXjAYhLujxVvf+lbcc889eO9734uqqnD00UfP6fnMdwh/R4Pvfe97eMc73oFjjz0W73nPe+bkHABxPhp47Wtfi/POOw/HH388DjzwQNx999247rrr8OxnPzvZbs8998T222+PK6+8EgsXLsR2222H/fffHytWrMDKlSvxmc98BmeccQb2228/LFiwAIcffjje+ta34vrrr8ef/Mmf4Gtf+xoOOugg1HWNH/zgB7j++uvxla98ZehBef72b/8WX/va17D//vvjne98J/bZZx889thjuPPOO/HVr34Vjz32GADgne98Jy699FL88R//Me644w7stttu+OQnP4lnPOMZm+3eDYPvf//7OOuss/C2t70Nhx9+OADXn/0lL3kJTj75ZFx//fVzcl7zGcLd0eKwww7DjjvuiDVr1uDQQw8dbTfFrRDC39Hg+OOPBwD83u/9Hj71qU8l6w488MDG/d5iGGnfmhGCuifdfvvtPbcrdff6sz/7M7vbbrvZbbfd1h500EH2tttuswcffLA9+OCDk32/8IUv2H322cd2Op2k69evfvUr+5a3vMVuv/32FkDS9WvTpk327/7u7+y+++5rp6am7DOf+Uy7cuVKe+6559r169eH7QDYU045pe/5WmvtunXr7CmnnGKXLl1qJyYm7K677mpf/epX26uuuirZ7oEHHrCve93r7DOe8Qy700472fe85z32pptumlV3r8MOO6yxbelecXS7XbvffvvZ3/qt37KPP/54su7DH/6wBWA/85nP9DyfrRnC3fHlbo6TTz7ZArCrV68eeJ+tHcLf8eYvddMtfUrdl7cUlLUDZqcIBAKBIMHpp5+Oj3/841i7du2cOzECwXyC5HwIBALBDPDUU0/hU5/6FI444ggRHgLBkJCcD4FAIBgCjzzyCL761a/is5/9LH7xi1/MadKeQDBfIeJDIBAIhsA999yDY445BrvssgsuueSSxmvdBQJBf2yxsMtll12G5cuXY5tttsH++++Pb3/721vqqwSCzQrhrqAXXvnKV8Jai3Xr1uHUU0+d69NJINwVzBdsEfFBXZ3OPvts3HnnnXjxi1+MQw45pDGErUAwbhDuCuYrhLuC+YQt0ttl//33x3777YdLL70UgBvJcunSpfjTP/1TvP/97++5rzEGDz/8MBYuXCgvaBLMGNZaPPHEE9h9993Dy6oGgXBXMNcQ7grmK4bh7mbP+di0aRPuuOMOnHnmmWGZ1hqrVq3Cbbfd1th+48aN2LhxY5h/6KGH5OVigs2Gn/70pwO/t0C4KxgnCHcF8xWDcHezi49HH30UdV1jyZIlyfIlS5bgBz/4QWP7Cy+8EOeee25j+QN3LseiBU3lVNv0BUMGlk0bv026rPbbkMlTw4KOUluLGmDzbrSVGsrPKxgo1FAwVoXlBgrGatRQqKHDutpqWB/NonkDjdpva/w6A+WP7be1GjWtsypMWxuP1YYKFkoZP+3+amXDdKUMNAwq5a7fnaFB5e/LhOqG7SpYKJgwrf0+FWjeQMMm6ybC91i/vz8vFeN6FYBKKTbvtlJKhWnt11YqnXfT6fVXqreq3vArg2Uv/QkWLlzYczsO4a5wV7jbn7u9eBvmGW9p2rDt6jDvjkO8rW3kaC/eumOk3HXH0ck85ygAdqzI5XiN6XMy6P2cNJovu+M8zberYFF5rmvGb1rHuQvEchDnI3/jeuuWqbhcwfHXfU/kb5yP/IWfz/nrttX+7+D8HYa7c97b5cwzz8QZZ5wR5jds2IClS5di0QKNRQtLhSCdTwsCbcMLgo7kH7ACN+hfgdeNClwnFTZt06jAQyHQoQKv2TJjY8Fy55wVGj+vVSQ+J6ebN2nF6ytwgCpZA61U2M9VrAaVX6ah4nQ4Jvy8L0RJ5a6SAhAq6QEqcN2jAufLhq3ACVvSQhbuCnefjtztzVs/z3ibi4+a7UvHJd62iQ/OIc5bAK3cdceJHKV1JpkncTKc8CDkAoTEB8DFNP3IWwCVFxxV4C2tczypmHg2gbvuOJG/bj4VH/E4g4kPXRAfSLadOX8H4e5mFx877bQTqqrCunXrkuXr1q3Drrvu2th+amoKU1NTm/s0WlGzglPPMN0lJ3DbNkCZxFR558vy6bbKm6apcq3hKlu+zFgVKtjaakA1CwrtVzx/qwFlAHbMHPw7kuVoz2Tuvc4khSBdZxuFYHNDuBu3AYS7w63bermbO3YEg/LysN42RUr5OPl8FBvp8XRjea/5nL/NbWcnPPi2xM/aqiAEamhUMIHbxNna6uB48OnGsT33wdwPuo4qEYAKsKnwyVFbG0RFDRsESDzG4PytrRlYQPfCZu/tMjk5iZUrV+Lmm28Oy4wxuPnmm3HAAQds1u8q2X+bE9RybF3fp0IJrcKWyj4nuWGFoK3yzlsBpR+Sus9j5a2G0vnONQb5YW2rEGcD4S7fX7g7E2xt3O0VKozblEMuvZDfAe56hG1smaM5R/JnX+JCk4tN4eE8tuax2j7p9TABzo6Zi/HWfVhYk59vsv0A4iueQ3HxUOD1Uum5zxZbJOxyxhln4LjjjsPLXvYyvPzlL8fFF1+MJ598MrxNb1wxkwfGbeve25VbnI2CU6h888qcpktqOG9BQulg/7nvU70VMhSc4dZLjcc4ZXotClDN5f1QUuJzBeFuaTvhbvt3br3c3RwiqZdbNwhnuWDlyHlr0Jx336EHFh7pufUXs7QNORfcBWnjaj/3w0B7F6O301f7cGHp+GDhQ7fMhV7c8aPjYKyFVmpGHN4c7scWER9vfvOb8fOf/xwf+MAHsHbtWrzkJS/BTTfd1EiGGhYzKQx5zLy5PgWPmcdtVPK3/fx0oxA0vy/Gy/mytpZjL/uaKlKylzlByfKjaVg07OtQGbdY2+l2QNW4W/3Ry6qeLTaX/cch3BXuhn3x9OVuia/9EqSBMmdNsj6dbwu55K5HKdfDfX/qVtS2PN0mPNr2jefb/owCRwsihAQIAICes0WD67St+66mwEDgr0mWO7HuQockRHLBU4dyQ/ODhV74djwcUwq/uOueGY/H7q22GzZswOLFi/HLHz47SXwatjDkFmCvhD23PQZK2KN107byx2sm7JWS9dw+HXZcWpcm6nFFn0+7fVOi66wlp5XJpk3MmmaZ1jF5z4QsbI0s2xomS37i0zHxaSIcN826psQnSnpy5z1Y4h5tmy8bNPlpwxMGz3zej7F+/XosWrSouM3mhnBXuAu2bb5sPnD30XuXFxNO28KEvTg7SC8XnmhKYcKcs80eLu0J0u6YPBFa9RUegzh4/cDFAXcteLI0bcd5n/I6Lm/wOeMwAEyCylFMPKXv4omnkbP9E0/dOiqnTQ67+fYGyoYnDHZ6/k8G4u54BEpngJnEzNssQF4Y4vr2G5yT2W3f+1bGCph+HHoTPk/Qy/cJBa3F1k6PpXyrtYctXvjB6YdBW9VuG/adxfUzTKDcAvHzLQ3hrnAXmD/cnYnwiNtHDOrU8Z5Z6bpymLARfpmh8KiRdhkf5FPal+eEmOx73bGbgik/l3CclpBTft3uuwr3zGbPgD2bvs5q9nzj92wev2LOu9oOgtkW0kFt68Z+LfHG9NishYeyIm8eNxYIPi4CHatoXVvdJBcjK9l53MYuWnZ+GawJMfVePQfCNfi4ZDyuad2nmY1dVrmDZl33sv7cNW1+C3tzQbgr3J2v3M1/ZHoJj7ANc+nybd32ZbFc4it3PUpJpjxMyAUo39dN61bRwY9bSnDtF3bh+7gQiA7rgphQMQ+kFILhocPQUyuEbnQSXoR3P4zVqFTt90cjXynP/aCnVMr9iPs4TvfjsZuffQ+usRYf7V28hlPi6b7tiJZ2qfWlGoTu22XR8oo5HRuhFCvPLUaTKGiVTGvYJG4eQETl03mFTZU8FQabb4tQAHjyE4/FN66ViJh1+apt7HPu5mM8cXNi3Cpx4a5wd1CME3cNbLFlW+IqRw3bEB6lXI+2cT3C97Tw1a0rhwjd8ZrCg7sdbaIjdy8a192rnORU4GVeZSJEZdsQd4FMXCDhMM8HyQVISF5lAoT2r3wuCGD9PF0jgELuR5582pb/AcQwTJkng7siYys+XOVdIMNm7vKTV0eD2bCpTdwWLweQFIK2cRN6Vd4hDpq1Hg2REUgrbT+ftN4KlThPdJopeKWdj5lQyrpuwyDET7ZvUd3jYmMLd4W785W7JbQJj0GEMs9NytfF+cJopllooZTnEfefnfBI3Y/BRSDf1rkYUXAEUcOcDjefuiA0DgiVA94DpiSi4/mSYGmOAULf1y/5FD6HKRcg4fpauNxrTJBhMLbiYxD0U+NAfxvQzQ9WIIZFUtGzeDm3rHO72p1zrLyLrUcaIIm3HvOWpErJaTyxTdJiRKjU+7Ugc+uv1wBOpW5mbbbfoN28hrX9xrkyB4S7wt3x5m4pF6mX8Bg03BJECWKSaZ5/w//2yvNoC7XkYZZ+oiPpPdPjuZgevEkFNF9uknBM6lCYVJxkvbdyAcIHznNOXh2Fiz+GTgSH8t81WNdbd43Wh3Ci20ECBECrCzITzCvxMUjLsaTGe9mASJbRjS3F/noPSV3qJdDLsi61GttajLzijiQ2MLaKFXmpJemnDei9AHHfSpG6jt0QKY7o7kG7TR3udfIDoUKhyvufc/s6t/3isfqr7i0RdxwVhLvC3fnAXVOQHSXRAZSFR8nxyPM8SsIjCoJ2rgLAtP/ZbOOrW9f/vUOlpM3c9SgmvdoqTDdyg4JrUcV1ynOI7kwSbkEzDNMjBJOsB1AXBTwSLnMBkggfIHDZhB2j6KjZPOdumwiJ92Fw4TxvxMcgyU9hvlcCWp+exTUrBPzvMMhbjaUkvVLlnZ5HufJu2nmemDkRWSUe+pQz5Z6MpcAswCRBr0V5UwsyjsvQTPprU90cpeBEqTXZK9Y+rpU4h3BXuFs+xnhzN+dbP+FRgsmmB8nz4MLDnUca+uvVu2k27xzKj9U3BJO7IIn7kbt5tE3udmTJqIyrlTJBSLtzi+tdrkdTZOf5H1xMG/+dJTHN3TznoEQRUkpC3Rz5T/NCfAwaK2/LvM7BY5D5+Ajp/v3V+CDxcvc9aZIer7RLyXnhb6LWY/euaF/rWIkDiWVdsrHzJL6ShV2pGrXtYTG2wHjLOiQV5uvRrLDdvSjHHIvfkRUCt2x8K3HhrnA3HmP8uVtbWxS5gwiP3PWI8/1Dg6W8IXdsFj5pcejcdk2Xzh2n2SOrdHy+zJ1z/3BCbdP3snD3I+FvMo+C29FbgNTJscpiul/+h3MJ/fNi+R8lAeLuhds2z2cCYqgl58mwYmRsxccgWddAvAH9unwZpDcrtwLdsdKBmdz+vNLNKuQWJd5mWfezq0sVN6+w+bxW1tl51sAo/2ZOos8sKvFKxWuuONH7kN5tHzOw4z1TIMuvUqwSKhA+7tNU270sbLcsfudcV+bCXeHufOUuR4OvmehIliFydNg3LecCGSCHxE33C7W0uR1toqMhQJjQyMOWbSIkjGbKwjAuzEGOBS3zo5HCCxN/DW7awKAKDkbllxGv6b5V8CJnCD4noR2aV2xFDwHCQzA8oTosY7zI3ZBhXng5tuJjELR1+cphkvXt65rHKhM27zHQ3K8cK8+PPUjlnY4gyS1urp7z6eEqcbLhXOuCbDfWRcwTXQPBzi63Av0wv0xxz/RNi736nLtzbc+4bvvxHycIdyHcLWCuuVvM+eDWfYvwiMvY9IDCI+4bxUI8n+FEsts/C9skDolqiA6ep5Tei3YhaGzVdMiYIEnWtSVX56GY3MkDEjeP83lQQZ1cS+aA+D0CE2vbDMHkrl7O9adFzgfQHisfZKCb9DgpeAKU279/66OfDRiPXY6VD1p588q/S8NiWzeksyO4CRW3sV7K+oS+CV0PVInr0LpLrT9K4OPXTF0cTYHw/H0D+f3lLcie97WHfb2lunyNAsJd4e58427OwRI381ALLWuOrNl05twx0/DHbJOh3bGaPbHaREeb6zFQ2MX/rUqig4mMEJ5RBiEZNeE1ygIEABTrVm41E9ZDOCCZ4Ghz9Cr0FiAAGi7IbDAvxEebXZ2vG6a/eSkO6Y4RLet+mdf8Ly8U9O6MTbaTVN7TtmptNU4bt8+0rbJKPPYgoG2MVTCK3lOhoK119rVyF8WndSmOnVXiBgXiE+kHUNy8y1feeyBvQVK8EYhkb+tv3s/C5s9/XCty4a5wdz5xt4ZtcLGX27E5Qi1u/8i92uok1DJtO2G7adtB3o22VzK0O/9mXlI+7bYrhyn7IR/llI4N0DuDfO8uG0MyGgoG1ouJKohj48trEoZBx4UllQFsZ2YhGEUCzL8DhkIweXgGaIQVk5BLQYRwDPOqgbEWH/36mifLs3hkr/7m6X7t/c3D+iwOyYf1JVsw71+exh91WuAKlXepxWjCdtTijC1cWKe0jbKhlWgsQusRQMPKLg7upHzlWIqhJxY4QtZ1Xix5rDyPm7t7oQLZdbJf7+F+OXpV4rQeGJ+KXLgr3I3PbX5xF0gFBzCY2+GWzS7U0kh+RuZgsB5YJJDpOCRe+nX/pmm3bdyfz8f7UG7dc4fMoArz1K2WupI7UUYhvTgNoOyEtLkgMxzPpjQGCA/BEK9LSajuHElEpSEXzo9+idZtGFvxYfoW6fb4UikWmazPCkhyzKyXQFyeWdKZFRjPKVXjDfuvYFcPWnlP21hQtXJv94R1rUqa75oK0O4aJ1AnlbjmJAdY69E2YujuHkRSV/7cqfsXJ3u0HdlYC5up90DbQE7tI0ia5O9cQLgr3J2v3LU2DpMOlEUHUBbFg4ZagCgQ+HRJHLtwHhPDXJhkSaV5iIXz1B0vhgfpeHQc/pevawMlfFNXVx6yIzESx/fQTqwy0cydkGF7dM1GgKAlBFMSIG1hGHfdPHQWj2e3xoTTYfqcl/bL3y0Q1/fPvi4VjjwGuYlZhlQJk11I+0+bTigAuUVN83nF3WWKv0vWNRR0Yl/bZB7GJd1No0p6FIR9MxtbU6uSyAw0CF+HSp72QYg9uhZbfN8AUO49AP8MePy8ra95WwIfkHb12hLv2tjcEO4Kd+cLd4thF76ecZKvG8TxgF8fwivoH2rpld8xTA8sAAlnaZ7Og8/nYr0XuqhY99roLlTewUv46wUKuS8Tqg4ixHguU9drHoahc3QhRmwWAVJDMZeRVsT1hBBeBIILEjdsYqsJuwBlq3qYPuduWb5/tKz7Ic+8TuLmrHDE9bFg5IWCF4helfe0qYJNzVuPXVaItHKxO6q4J3QNYxU6AKaBEE/nVrYjctPGngYAVQfCUhIfr8TzGHqlLHol8AFIiVxQ3bwFWbSjW7Kse424N04Q7gp33b2ef9xthPgSNyRuk78ozm3bHmpJXAybhVcyR65NeJBgcdwbTnTkPbD4OaUJp4M9k0pZUHdbDQtjnXhO3A8/xLoLBqaJzW2OXi4utHcKAQoPakB1ZxWC4WFQ4jcX2JwD3AWh502YabBwbMXHMIPdNLeJx+DL8pajW95U5736nOcxSbdMJctK3bzqrHDwwtCr8u6aKlT4vPAEeOKRfa2pkvYq2SXQOfu6brGxtYovN9Lg+8RBc7gtTddFRM97FvRCr0xrek68BTnI4E3uGYxPRS7cFe7OV+4atIdXSm4HGtv3D7Vwx8LtHx25dNuy8AhioY/wKDkdueiIOSAq+e443f5MtHJiw02bcD3Um4uECJRmIRg085lshQkvoGurAd0tCBB3HHqxYimvaaYhmLwbbi5A8jAMkHKVP/9hAoZjKz5KaKu8eyXq5e/B4C3Htvdg5PN5LJKWUwEpFQ6yF0NPgcyu7ppYiXdtlVjVeYsxr+ST1qMy6GjDWpIaE7oOrUpohB4FMCjb2AYwymAC1JIEI7tubUES0Wv0JzlNt72yvG2kPXq+eQy9LUkvPPchYo+jgHBXuDsfuFsSzlye5W6HW98/1NIWCqRQi+vFUnY88p5XbeHAQbp889Agzbu/aZkayPngnLA6cpNcDdajyy33A+qxcGIQNzr2jJk2nSQMMwEn0CbQxabQ8wXYZN1geqFumaEA4deTC5Bw3Ma1t4RdhuDuUI7JhRdeiP322w8LFy7ELrvsgje84Q249957k22eeuopnHLKKdhxxx2xYMECHHHEEVi3bt0wX9OAQTr0Ta/Ku0159eqe2DNezipv3nLkBaSUpJdX3rld7SrxKlTeblpj2lRhumtdRU/bbTKVn/cfq9G1VTJvrGuBTvv9aZrOhbdCw3lRRcDPmc4zXLNKKo303qaJie65lFsPtb/XbWo5jvpZdgea8ejBtLZwV7gr3B0MdfYx7FMSHo5H5VAL8YnzchMJWpCwbQqPaVth2naKXb7DJxMeji/u0zWaTTsOdq3jE/F0k+mgazU2mrh82lTYWHfcPuyzyXTc9tnyjXUn7DdtdeCu479bv9F0/HK3T36ONXRy7vz6+P2b9vcilktfhsEbCexelkJYST3BylMoS6w+Yc+c6iBT4MhMMZT4uOWWW3DKKafgW9/6Fv71X/8V09PTeM1rXoMnn3wybHP66afjxhtvxJo1a3DLLbfg4Ycfxhvf+MYZn2DbEL9ArLxztLUc3bIBbNDMFoznEh9mYgmySplXZG12dahIM3u6psrVk8JVylWoyI1VqI0/BxOXEal5JW5CK1T5QptW4ryCTs+R2/f0I6XZdTaJnd873uJJWj+N+5mGE0pE7jWkczxOaVzGFMJd4a5wtz9yl4OHWNqEh1uWhlpaczyC+5PmeuSOR1tiaR5miT/U/bt8c3HMlxkvFIJbBxUFhOW8LCzn2/rjTxsnyqeZcDde3LjtmyIkFcxcUGWJ37bT5HZ+z/k9HUCAgD1P7grF40UO5LwgzsxEjCg7TN+YDD//+c+xyy674JZbbsHv/d7vYf369dh5552xevVqHHnkkQCAH/zgB9h7771x22234RWveEXfY27YsAGLFy/GT3+wOxYtzFopLZV324uNaFmeFDVMLwHKus4zsDf5gWGo1ZUrc144aJvcrqYYOVWu3KqmSp0qacvWAS7eSPZ1pU2Y76jaWdl+XUfXqJRFRxlnaXu7e0LV0MpiQtVheRWWu78VLCZUF1q5d29MqC6qMF2jUgYaBpPKGfgV9V5QJm7jn82Eii89ct9l3baI9rVGjJ9TTJEYQJZ1HkNvG2VvwxMGS/d6GOvXr8eiRYsa64W7wl3hLvtOz93/755dsJBxlwustjALLeOhltijZfhQC/3AkojIE0s5RynM0jbAXT7ODJ931xQFU/43XLdtttHzFxcSh2kagOerDdtWIdxoQ/fynNPEV60Ypz2/ObfjtAlcLvE78LrA8Tjt+Uw9dWBDCIm4Hq7T/20b7feJJwxetM8jrdzlmFXOx/r16wEAO+ywAwDgjjvuwPT0NFatWhW22WuvvbDHHnu0FoKNGzdi48aNYX7Dhg2NbYYdcW+YyhvoHZPM4+alWDmvvOP2qqHIya7myXnTNi7jLcag4I0OFXltsh4DylXexihPThcnN7UO8XQYhPg5TIxDAm4shWlUfnksMEDsRcAHcWqLodeIMUaewEeJgHzkyGGH+eXPuZTE1zaWQj8Id4W7wt0md7nDEe5Fcs0xH4K4CKBVCAMIYgFACLWUWuS0XT/BEaaZ2GjrdeW+XwcBwXtd0cfN68Td4gIkFyOu54nO5iP/NPEZJEpcPkhb9/IgTkv5ID4XxECFvCb+JmTj7/Ok6mbdy32PGHQHzgFxrz6wxTwQgOWC0PJZYqa9ZGCMwWmnnYaDDjoIL3jBCwAAa9euxeTkJLbffvtk2yVLlmDt2rXF41x44YVYvHhx+CxdujRZP0jlHeZbTJxepmbJyuaVdjx2tA+jLZXGyt35MRuYWYfhE9Q3azX6CppX3lRhk21tqUJnn1DBk01JdjaaSX/TZDdaHgNPCzCPoRv2CT0n2D3hrQFuYef2Xn6Pc2svHoPf/97PrjT64jD9y4W7wl1+b4S7Te7yPA93noMLj/R6Wf7MEKGWQYUH5U0ER87qpNdV2ZlL85EoPJiuix+T8bW0Tcxjirkdyba0juWH8BAjD8Xw0BF3eHJBlpSDIOii6Gvc6z4hGHrO3MEKeSDsGXN+5Cj1ymvDjJ2PU045Bd/73vdw6623zvQQAIAzzzwTZ5xxRpjfsGEDli5dWiyUvUbeaw7klIK3HN2xeOFJW47JfoVKKybupbHyoNwtj/VRZZ0m6FGh4Il53KoOxw/zcRoArHJK2vUzV8G+pgun6Y6u0YVGB/7FW9DowLUou6ZyKttap5i9QKZuX6H7o9Xg79BwFp6vkPx2dF+4uq58N8jQDc2mwxLTcwHSoavjvW8fwKnUjTHpMdKjQhfuCneFu2XuWjQFh7ue+GPE15WER8mFI/dt0FBL4qBkopg7HfSDzEMqpV5XdK58sLvU+XDhQX6NtDwBezR8SHVyNmg5uSNaWWhrgxvCx7iBRl8XBNqdA72GgA/N3nOAPXQwk14wYbA973hQV1wN65wRlQ7Gl9dVwxgiMxIfp556Kr74xS/i3//93/Fbv/VbYfmuu+6KTZs24fHHH09U+Lp167DrrrsWjzU1NYWpqame3zfIewbiujRBhizrdBvVmG4rLKVEvdyy5pU3xc2pYCSqPLOreYycpqnFSNO8lVgbV0CsVdDaQCugJvva+tHztELHk8Vo94PVUTWMommDmmLS1EXRVoHo1C3Mjb6n2SBOHUygGyzsTRaYBDxhdUJu6s9ek19u+3dfNGxd3q+8VyXurmNw61q4K9wV7rZzl7duk7EvWkQHLSuFWtwx9IxCLWGaWvys9T9IV++0m3cMx/BllhwzJkAARBGSC48CSICoTHiQSFA0r3TSxZy/NFH7gfZ6dTGvjXbC2j8LbbUTJhSC8QKjFIJxJ4KBBIgBy2ex/rsUG/GXV2eF21NyY1vv3cBbArDW4tRTT8XnP/95/Nu//RtWrFiRrF+5ciUmJiZw8803h2X33nsvHnzwQRxwwAHDfFXAoC84cuvYdpkEG+TNivG4LG7OC4tVrCWZZgzzrn+JHcysNW5X55U3t6prP12HittV3oYtN36Z+9APi8rsaxUKaJzm3089CdLzDddtuX0dt+E2fsw813F54Z62gey89P7n27RzwD0L2+BJDuGucFe42x88NBbOcUjhYdi95KGWdPveoZb4bHz4xDR7huTCI+nq3QitxGXU64pzlz7Tte8Cy3nZ45Mck8qB0a5rOXGRh3DC9VGOVNqtnKZpu7yLedr9fbAQTNIooX1aQjCBB0yEkgijsGPgQ3YvhsVQzscpp5yC1atX4wtf+AIWLlwY4omLFy/Gtttui8WLF+Ptb387zjjjDOywww5YtGgR/vRP/xQHHHDAQBnXHPkLjoD+rUZaXkrU6wfecozfodk6/vDSeFlbrDwm86V/S70CqEcAEdUCSeVt/QOm1qMNipqMUg2rLKAN4JP7qPFGyXzOyjbBoiQbu2srdOAS+JxdaEJrM1jTVsP4rOsa5QS+OMqfT+ALyUvtLUidP9NCAh9fT0+nlKzX6wVHwl3hrnB3cJjsh8idYypCSgK45MARt+J63TPUkgxsB9Wa+My7evM8D96NO3c6eK8rngRt2fVZy6+nvfxx16P27l1tlWORsiG8SI6Hqxfcdh2tknAMNP0Ye6YY5u4hJljTX3o+E0AjBJO/YmAmI6GmI7bG8y4JcyoHw4qQocTHFVdcAQB45StfmSy/+uqr8ba3vQ0AcNFFF0FrjSOOOAIbN27EIYccgssvv3yYr2mg7UVHvWLleQXfr3tiTKRpthxzlR7ijDbdNtjUXp1TfDxW1LHC3mQ6cVuuwC2LlRuFbu1y7I3RMMG6BrT2xNYuZmitgfIxdOOtbGuVs7Kp4vSVuKHx+VnF7shfo2t0smxC1Zg2HUB3PcGdhV1DN8hNFjb1GqhZgajQ7AEeiMzii+65pqNH5hY2XUrpDYttEO4Kd4W7/RESdxNBURYdNJ2H/YDYqwUA8pfEDRpqSfM6VMJL7nb0Eh3U4yqZZ2KDkqEB+GmEaQKfBmKIhU9rFee1skkYpmLLSHTnIgRw3NZKO85rJKP+GqvR0Y6HvCcMgGYIBlRnuBDMTEZCrW3lBbgTIYOEXOh7B8VQ4mOQIUG22WYbXHbZZbjsssuGOXQrer1hMW7Dpi1froJlXT42KfpoE9LfYqIedFIQQ+uR7CiyxchGZOunWeXNM6FLlTe1GENBsQrGqKQCd7Fzp6ZRuRYjb0mWWpE03UGNro2JfDq0JquQIAWlnTL3BDS+9UhvAiV1zfu711kLsmJPK1bmsQXZL4EvxsrLXRjjfv0rcuGucFe42x8lu52W09+S8AAiB5N3tDBHY9BQCxceaVfa1IHjA9uVEp+509EmOkhwkCvHr7v1rvv1/IlFwaG8yHBChBw9EhvkhkDH50oJ1twFic6HT7ZW7rzI/SCOAzHHCczlI3GdCG2ViupeAqSCCdtyFwRInRDOjXy6H8b23S4zfbVzPh2P12w5uuVppd2WqBePE2PJVFjKXRPdfryQhG5biJV3W3IeFRbj4+XWAqZ2FrcFQG9M1BoANKy2sKHSjpW4tsot04CyNrQOKaGpaypUlfX3wyQEN1CupWldhe16EMBX5iYk8NXB5ksT+DQrEJUqPRX+PFXruzPS7crv0HDPxhanRw3hrnB3vnKXOBDPJc/3aBEeBfetNJx/26i6vXKPeI8WLjzaEp9D3oNVSSgwFx0UEqTrtoguR+p8NO8T15FKWffEbBpyUQqwSoUfasVcECCKjpBkCoUO3BueXS8vP2YN24ZCjMRxzqR+IRjO9cFCMP7L/TNOesMARXXWK0yVY2zFB0dbElfbWxbduthyLKmx3C6Mx84ScXyB2WQ7DYuQq/TEGuTdEtmwvUmCHms1Tvu/1ip0a/+d3qqua1d5Wz8PUunaQmkLawBbGRdPNAq2MsHKpgLEW2lkY2u48+poA22qYPNVygaC082d0HUo+PkATm4qZlbXXnXHty8itDj7xc9J4fdqQdLzz23scYVwV7g7n7hbZ5xrEx20LA+1APDcSkMtnIvEteLLCxGTS0l49OrmTWEW4mMQLln+US44uNjgjlwUH/Ge5GEXIIZbSIQoFmpRKs4rAJU2wQ2xfpoEq9HeEbGuy7lRCsYadLTr5dVRLrxSua4nQXwTccLAZvTXh2Dgu5zHly3SiWNwAULbE1s5/3vwZ1CMvfhoq7xz5Il6jeMUWo5x39hyTJYjzYQHWJJVptJDQTF5QVGhoJAyt1YV7GpXadeWKm3/1/iCYtwHxhUU0EdTq9JAa0B5slIrUimXzBeuzNejXWXdmAnWun7wvqKe9pV5xyvrmlnY8Y2iNlh7GjYk8JGtV/l72hwx0u3N776hQoj4xtLw3G35tc6NZ8subZwg3BXuzkfu5gmkfFmb8Ai9WbgLR/uS42Gj40HuW9J7A2lyacwBiTlHPOk5Fx6co9OJ4NAw1uceMeeDCw6aBrzwSJyPdvGBIDhUIj60NmGZNTqIEGM1Km2TBGvLQi35iL40DV2DElEndO3GK9FspN9wYiYR2qVxbkIX3H4CBCiGYQAUQzHDYmzFh0HvyrufZR1HcmyLmactxzxD2ySVdoxPJvuULGuKXyZ/aV+Vdkn089bGytu1Gn2CHrOtrVGwtXKFwrtnsArWWugKgKGEImKuW6Y8mWuroK2Csspb1pqR3FWgPIauoVH7GDpZ2LwHgYbyNrarTLSKLcnaE7bf0NUAgo2XD11dSuCj504xdABJHL23Jh8dhLvCXXeP5yN3U6cDaBcecZ9mqCXuG5fx8WVITJPwaOttxZOdp5n7xoVH5C4L+TF+UijQApGTNuYjAVFwUGjQLWyGXuiRBUFCggNekFC4xerggGhtgwipfG6TpQP5fBA37R2MkETtBDaFGKFraH8fXBJqzAnLw4xumY3OXeE1A1yAaEXc57w3kQtMgLicjyhCOEe2WMLpXKHZV96hl2Xt1sd4Xt5LgLZ127HCEirpmBzF45N0DG5XN1S61UlBIcs6r7yn6yrY1V1faRujUdcKlir22rcYjQJq35SyCtAWVltAO5tOaUDZyhELgDFAVblpbmOT6kcFFl6PlTnF0KcBaOu6Nk6jKibwFVuQiLFyjdiCTBKd2B2vfauRxxHjKHrOwq69xR33adrYOcalMhfuCnfnE3dzkQqkosPNl0MtPN/IjWTKc5CyMAsTuKUXGPIQS9uIuptqNtS6oZCgdz4ox8jG7uCW3I/gwDGxYaMrZ71IDuAihCZUqkac8FBu1rt1SrnwojFMgGgLRY6ZdZzWPmfEWBd6iS4Iiao6vOsIWQgGiCEXEuMc8X0wGhPoYhM6Ppm6mwmQjhMbfRwQ9/wRE7IzJ9akX98TYy8+Bq288wLLK+90/yyGyf5y+5onR5US9XhSFE+IIus62IK8IqdKnPUKMKZZeRujg1VtfQUOqsDJskacttCA9b0HPCOVtt72cz8GZGOT1acSe69ilXkVVHfXxrETpm3lyckT+FSw9SiruoZ7g2J6v9tbkHnmNN37SjVZzBP18kocQLEin0sId4W78ZnOD+7ynI+S6AAi38I+mfDg+UalLrW5CCYBURIefGA5LoYpqTSMM2OiI8LDgLG3lU98Nl4cA05wGCY2SmGX1h9TFZMyvfCAsrAKPtHUh2KsFx3sr/ZhF8pvqrT/Em1gas8MjdjLKYRe6K8LwWhrAFRJmLFtnJt+Dkil6uD6NQQIkOSBkFMYQjEZfwbF2IqP2trWyrt1n5YbMUwvgcZ6mx4jsQkR15P127CswbOrozoPljUrHKFg8MqbV+AGUIZV3BqeKBYWLtPadeVSrp72FbjWLunKxSQ1dFWH79bhPLWz+GxqYRurAEVdGx2JuTUbW4exe2KsnKN61vQ8goXXPnZCHj+nFiSPoRMfeBx9XCpy4a5w193X+cddIHII6C088lALTzDl4CK61NOK3Le8m3fo1WLz0GDalZt4mQuPKDii20GuHIUDSXQEwUECua/4gI+1OGvLOqsjChFtvRhRztmrFZSOwlZ5XZv08ILLC6HBzzrauFCj53jXALqyIQRDvbwozBhEeOb08S64FEqJQsMJEA3TyNsg8a1Z+aGQCwkQAu+aPijGVnzkKL0tspSo16uXgDtOWpjcPmlh69VypMo7FAYbW4zhL1fpLBmKV9618d0X/YfsauMr7mBV+wpcGQXUsQK32ovWygJd7azsCiB5bHS8PhpPwQSis1EFNKAMb0m6WLmzrm0YQbJrtLME4VqPfPCmXr0H+Iu7hhk7gXoP0MuLeHXWqxJ3+zZ//OcSwl3hLn/+48xd3n3WzUfRAcT8DlpWHKbbc7DUs4WL4LxLLeVx8G7exENax0Mt03V06rp11b+bNzkdRnnXIxMbufAA+osPYqOylPjhE0jdX6Wt47wClHf5KAxjrQvDWDieUxjGaAo5qlAWjFJuQDJjQxfdSsUX1KXOCPyzcvumXXA7nuf+2rwAoZBjbStM0jq/XzhgHobx4EKkXyOLY+zFR34xvSzrfGjXtni5aSlIoQsja0nmyVGh9Yio2NMRIKuesfK88q7rzK6uFWxXR6uaWoy1gqrds1dGwVYWVvsCU3muWOKMTmxssu+UskFp11qBBnKiStsoqgD820MtDeTklPW09f3LVWyd9Oo9QPc4tfWcCi+NnVDqPdCWwJdX4kC5N8FcQrgr3J1v3OVuGaHkdgDoKTxKPVtqKEybDniehwuz6GaXWtbNO+nVwkIt+cB2tJy6eRsvMhw/fXjFMNHhHbnE5bCA4kKEwKdV869zPtiHohaGdy1XQOUcEWe1mODC0GB7iQvCxgMJA5KhCm971j7xlMa7oR4wlGhNYpv42NYDBsqJbSeiY9J1uG5yPMgNBKIIARIh0u89RRxjKz5qtFfevdCr5Zgcn98wpLHNsNzmFb5KWo8hc5tarMwWzP+GAhMUuUqtQLKrmU0N6+w6GF9518pV4Bbg0tV1R1Su9VgzQZvZ2MZowFt5tZ/Wwa70Vp9i502VtB8O2JHUdV+c8BVyv94DIbbttwn3n2S6t7+pos57D8RnlFrYfFk85nhU4sJdCHeT5zqfuMtyPpjIoHUELjzCvkx4cEuei2jesyX0SuFcLIT9kl4tLNRCzz70ZmGOB8/tSNwOyj0irgKOq4kLgiBIgqEVfnTjvbIqbkDdxG3I//D7kGlglUs+hfvNdzrDjfRrjPZhmChAtFKoAWh/rSEE4xsJHd/bhVw2Pgpqr/wPEzibCm23fww1cpGdhFxYGCas5xwYoP4ijK34yJG2EtNlvJdA2J4peB4vL3VRpGl37BgTz3sJ5IWGxydDX3QqQJbFyVnLkY+HYIyKlmBuV/vKW/lWI4xyeUbGi84Kjv1E7splUVv/REknQ5lAdNetTKMG/KA3PkZuNLTfv2td7wBS1lrb0IJMcwQ0iynWntTcpq79vbbegs4HbmLPs1BpuwITew8k3Rn7VOL87zhAuCvc5c9/nLlLPCHkwiPvTpvwkwmP3PVIOOhFRdLrCjHPIx/Onw8gxnOP8lBL4CWJZArz+TFnYJCKDp6HZJTTEcH9QBQcWfmMggOxy6zykThyPrTfzRkcPoE0Hh+WnDUfmiGnz49hUyviOTl+bpOuse4Fi94Vgk9ApTyQfq8ZcMKi8qEYn6PEwi+lMUB4zkc4EbD7AxTdwH4Ye/GRX1Kp8o7bpiQpKTKeJOX2oUpZxwIEzSrici8BrtYpIzsUGJv2EOCWNR8B0tQ+bl4r2NoTqat9i9FX4F3Wauy6wqIMYI2Lk9sqVnaBEx0kNjYqV3nWdbSxtXKxcYBClTaQm6w9V0G486qqaF3XSkc17ROQGu/NQPouAQ0ir4ufU99xqt54d0VX4ZNdHXsP5JU150hp+VxDuCvcnY/cTXqyFFwQ7njEBGfVEB5teR58ILE8zyOEWwrhv7icBDJz5WqdDmxXMzeOEp9JZNB0HQWH8sKECxCAGR1J2EWFRSQ2rBcLUApWMyGiHc+DCKl8+MeHXYx2PWKs9TlJ2qBWCqjdNFABVR3DjHQiPELjOU4ChA9ARt3NCfkQ7MkIqD0ECF1wlQwuxpjrT2uYfKWxFx8cdct1pe+vUKGVA6R2dG5Nl1qO8TjpOv7jUGo5xhZlzMIOtmKwrXWsvKmQ8NhjKCAIrcZQedeAppZkYl0TNxSsk9NQtbexDdx4Ckb5AuJsbmvdtZKFXWmTnG9qezrrurYKHWZdO9u6DqEC7e+v8RW3+yFMuy7y+553XdSZcs57D1ALsmRhu+czfpU4h3BXuDsfuGsz7gBN4UGIXb4VTHYFOXd7DSRG4Za6+Azj3/Q9QnmoRTVG1I1hwCg+FOOrIieOLVfuJkT3g+Y5FPur+Lzy1PbqWTteK6gwro2jlPVj13jloP0AegYA0hCMC5X4d8b4e0EvYgy9vFQMv/BQI4VftBchNHovD7+456OS/A/qzcV7ylSKuX+IIoSENj1/Wwg7tmFsxYdBs+XI1wH9W45pd0XdWJ/OU0GKFm2S0JcVnLTibsYpDVRIigpdwCwNdMO6JdbpeAjcrg5/DaC71JJ0hcJQXNK6Ss7dE6qoPeEBp8T9KqP9dyjtLGmjoVQdWhSAe3+G8ZWJ8QM1hVis9YVF+R8x5QhNyXtQBhP+Xpa6LpZ7DDS7Lho72NgJpUq8ND1qCHeFu2HbecbdUs4HkAqPtgRTLip4onQebimF/poOXDPPg/5S7pEJwkNHQUzCg9w4locUkp9ZTlKY5oKDcpN8WcofH+l85cf1gPIhGA0vPkiIO8Fhq3h8CwSnzx0nJlj7NFCXPwLtcpw85/kYNx1t0PXhxuAesRFQS6P8UvIpD7+kL6CLPKb8D+I88Z0ECM/54HXRsEOsj6344OCtxqaVnbYc+d/GcYL9V7CtmXovdVHkBcdZ3GnFncQnybpmmdi1LyB1rb1lTZW3DrFyZRRUqKhd5a1puuunmVp3iVTux0tb1yqkHzJbWVcQ6mgRWkXX6Adt8l0Ya2NDAl/X6tB9UQeCu8p82mo3Yp6NcUXKpqa3hrpkPZ/QB57Q1LSvk+dGKhspiUu9B3hLse0NouMC4a5wl7abD9xtzfkYQnjw3i2cg6XtKMzCu3lzcVL7sAu9wHC6jrlHvFeLMTqGWoiXBoB1ghi+qzflIIXkZ8N5qTLxgabrAW90KDhxTM9PO6cumAgaYYwP16XWhWOURRzjBjEPxPiDqBC2cEyhHCcSIzrL/wjmSTK6r4VRsfcLkL4DJh9+vdT7JQm/ADEEE25Aem9IiGxVCaetdnXLRTZafohET4/btBfdfG5nc8WvWaFgf/OWo43D9tK7L2g6vDnRIkmCorEQSKErzwvegnT2tdtGAzD+6SlS3MptE0qHLwROTvtYo5PW4Txc0p4KCXwVa2VQxU2VBxB/IML1Kpp3LUj3MchfWc6t6kFgvI2Yx8/nSyUOCHeFu/OXu/kIpkAqPErI39vCk0ybvVsKITJqxfskVHqWuQMSc490cOJo3I7YjRbOWjAIwiPwtfaU45xlwjjkgHi0OR8AwmimXiH797pQ2CVsFUIxjho+zMjLr3f9oH34KAzbrsIYN9r35tI2ltXc6YOfpjAMfzbkbvDeL6XRT3MBwh2QCja4HuSCJBzZWnI+8sq7reXY1kUxr7TdtjqpnAFfaJitaAqVe6nfelpodEuB8ZVdKCg02E20q0OsnKxrX1lHC9u1HDVZ1ybGiW0FZyU7trh4oVGAss4S155JbLmxvqVKQ1j7c1Z0/lChWxdZ1GRfV97qhooxdLKwa6hgXXMbj997qsxL4ybEbmCqtQWZ84FX4sD4VOTCXeEuPd/5xF2D6K4BTeERlzddj3CM8EMUXQ93DO5q6FAGSnlHfIyZXPzGt9AC4f0sBpGX9BJDEsDc8SAxbCNPSWwUQzAF9yMMQuu/Rin3Ow0S0pUvFyRCgKhQanfuCl5sGHcgq+jAblRU/qZd4ncY6df/DUJbxb/wDiKFGUncuWdL2/icJ8vzPnQQHHycmwrULRfhTba5AAEQRMgwGFvx0avy7tdybD9m007MK3k6RpttnSRAFZZRdzALxCQ9q9JEPQNmDfpKuxsra7Ku9bSvtH3lrTcBurahoBjjuida5StzT3DjmB2yr2kgJ6udMgbcWxVpCOtaxeGru8qG3gPGmqxSMJj2XRh5bNvZ0jaQU/v7yEeN1Og/bkKvsRLc96QtyPI26d+5gHBXuNt8fvODu+77mchA5JSb7x1u4dv3GtODfiDTd7g0nbgY/tNsgDseAtQNThIvQ6iFwn9BcPAQDBMjPlkrTAfh4P4oy1wP79ZZ+ktOnRcibt4nT1sfHrFelFTxQJb+U9Yn+xrfE1iHHjB8gL3Kj5xaG8d3qly0Z2hH0+B6rrx03dDBoaeX64JrWtwPeuYktA3jbVmAAEhEiBki76Psnw2Iv/3bv4VSCqeddlpY9tRTT+GUU07BjjvuiAULFuCII47AunXrZvM1xcqbtxyRrd8c4yOE42Ux0OS8WNy89OFJUk6dxwGZQOQ2ACVBBfuvTitzHVqP1hUk3pLk8XRWqFxBU9FutACN7pe/lyNpWSCqbd4SyRU0b8XQMrrnpVY73cs8Z6Ef+sUQZ5qcJ9wV7gp3mxhUeBT3DWEZ1bg/FKoJIjd7RvQ9nIMkhMmFi71bmsOlpz1bkOR4NIQHd+XICelGvnKe8k++TBWWx+8ofB8JHcpHoWnPbwpnWuMTrW1M8g4hJxrzpNBwSHiPyG+6/+G+2tQp5c85SRq25Kpy56rsrPLPoJix+Lj99tvx0Y9+FC960YuS5aeffjpuvPFGrFmzBrfccgsefvhhvPGNb5zp1wyEXkl6HCU7sdcx04KYjo/QeNi8wgZVgvDLfUsPiPFy6z7KUpKTiio8VMa+MNSAqm3DwtZdm5LcNP9SnDPYh4HoKpDbhnMHkko5bxXblNChJQO+LFZUdM/J9h722SXflf1wp71FhoNwV7gr3O2NkvBI1hdcD0Ij7MIEBd8mCQew55UKSJXlHvEP5SAxkWpJCKvAHxIeMQyTca1mXE1EhIXqWmj61NbzNi5P9s35bPh8zCuJHyo3XDhFEUIi2yb3BFk5zfOcorPpnkG2PHCbykUqQtrFd6mcDJdgmmNG4uNXv/oVjjnmGHzsYx/DM5/5zLB8/fr1+PjHP44PfehD+P3f/32sXLkSV199Nb75zW/iW9/61tDfQ/UPoVkhp5XJ0MenAoRYkHhPAfqOpm2dVeKZbU2q3SRKHawLmHItRrIGWQGgbonUYlRdQE9b6Gmg2gRUmyw6Gy2qjdbN+3V6Oir2YIMnhU2F73XqGqwF6cjKSZ68uZTnBhQq8rQ7J+8mmrd+VNi+9Bx4y6m0X46ZVOLCXeGucLcd/B7kwoOHW+L2ac+WsC/7cSuP6xF7uLjwShV4mud61OGHOE0ytV5cJN29Az8zF47xM3T7JsfCc7DaZD1frZve5Hirs09Fy7N96DiJY1LzecbtMO3KEbmI8OUsjlWik7Anlcue7kcW0grlnrlPufuRcqDpfpAQ5w2ZXIQMK0ZmJD5OOeUUHHbYYVi1alWy/I477sD09HSyfK+99sIee+yB2267rXisjRs3YsOGDckHaOT4JMiHow7Ls0JD04ldzezTfuCFh383VWbu+E21nrTEPHGCbZ204sgajF28kClmp7odeatp6ytsWuat7JopcJNV3JRIldnlvAXLE7lIVbdZenzchEaiWakV2ajAWALb7KJ+hefVvyIX7gp3hbvt3AWA9IclCg+O/P65ZSRu+Q9byY2KP4i0nP7mrkfiypELR2GXpHeLYk6Cn0/cjcgpHfjJQyepOzfoJw3R2MD5IHBqODcmD8FYNk3nTkTgYRigwXEqn3XxfunGPU9di3TcoFhPNMUzHSMRm7SM5Z21uSX9MHTC6ac//WnceeeduP322xvr1q5di8nJSWy//fbJ8iVLlmDt2rXF41144YU499xz+37voPZ0v/ESeh0v76rIwSttvixMQzUKUSQOSyyy0VqLXcKiDZfYcnVekdtQaVsNhKF865jsRPtBuWMr32pVxgarms7DWtusvP3fStmExKXrNlYByt8b32vALY89C2jEyHwwpnDPre7ZldHYmBxIPQfaBm6Kz6IsAIS76bIwLdwV7obvT10NgOco6Yag7ZUrkzskdKxEjNCHiUUg/dE1lotMWoeYwEk/3OxHWxlHI2UZN1k4LxW7Nnn3UPj4L0ve8wIAXvu6XE2fd0JDqPvColTknlaAqeLx3YkhjvfBc6i0Avy4NzB+nBCjwui+vFzSPVTsPvGeL64Hi/HPLt5fTeWD8T7hgNWAcu80SgbdQ+xaW9wHwBZLOP3pT3+K97znPbjuuuuwzTbbDLNrK84880ysX78+fH760582tkmTW6KtR2izrQcZGZIS9oLKY/ZqI0s7Ue1NpZlW2rGwhFYaj0OGT6myJjVtE1tQT1vojRbVJoNqY2b3MeUex1XwLYEkhu4+wUq3KrX1fCy1tmmFzlst/P7n976UkJSvK7UaTVap5RbeoD/gbRDuCneFuxH9uFsSHhy8BZ0kLBLHWPiK880dK7bGOQ952Cxw16ggNkJ+h2WuR5JkypKebcpL7oIkCc/T0amopqNDV4VwoQvBpMstKsbrED5MXJHo+uXcTse/YefMXBzKbbIGjOc85IJwn2zgd/yEe8tDrZnT5J4vD8ukjZT4fHWr+9E25ssgGGrPO+64A4888ghe+tKXotPpoNPp4JZbbsEll1yCTqeDJUuWYNOmTXj88ceT/datW4ddd921eMypqSksWrQo+cwEvQpyI/O6j000iI1UzjJObbGkIjeILUd3gGhdF1qOPImJEp30Jqq867Q1yRL7groO1jhYUqBTybwFmydvWUZeW6gg6JrD+xiol4XVzfvMyFlKtovbpRV1v1Y6P17bMXMId9k2wl3hbgt3qTcQP08+ymkebinZ9Vz8JvciCbXoJg+RPr/8E5IviSPkFsBz0EYOBo6SiA2iNnXkuGjmgkF3vahIwimWieqUw0nIJQgcmwifxG2hMuOdGR7KTHq+WEr2ZgnWYMmmiA5Scq9t5Fr6vPJ8jthgyZ8pPw5tYzJu0DFDLsgQOR9DhV1e/epX4+67706WHX/88dhrr73wv/7X/8LSpUsxMTGBm2++GUcccQQA4N5778WDDz6IAw44YJivCii1HEvr+u3Pu8m1oZGs12Jh5+fBK7q02x8SqyzJ2rcqHcTGFAqOcZV3JC/LtJ42sJWGrRR0bWGMe225ya1DgzCsr/Ln404avhXhLG3yFfNKnAZtGhS11WG46nxZvh3U5o6ct0O4K9zte7+FuwENvhaTEpvCOOddcN4KLefSD2aaw+CWh14t4HxUjAdofEJvEssELecqG3PGiQLLcjFsCLtQzgaHUjYOlW5dCDBet4WqVRh8DMq681CMqgau2U9/bQzhBJIHfrvpPNzCy2345nDfNOiFc/HeapiWcJ/juBt0rI3XpfBLvxBiPwwlPhYuXIgXvOAFybLtttsOO+64Y1j+9re/HWeccQZ22GEHLFq0CH/6p3+KAw44AK94xStmfJI52tRVMh5C4RYmAzUxG7WXfZQPSx33jy0qoKUSD4WEFxAVVDpytW5jYdC1TRS6s6gN9KbaVd4dBdNV0NpCTSjorhPMQWlrrrCtzwxnH2pBaBZLtUiuh67bxb5jLDEk7jHi0brk/rbEw3mFbpC+K2MYcPL3GrwJEO4Kd4W7w5wbYTYSq9k9Nw0JuL9pgiQQf+t5oimF2oiPISSI6BYEzjBeBneBemR5ly1JOjXezSDRQfy13o3LHk0UFk4cU76HrUgcWLjXADi6Kn8blAKCjq0BpRVgrDsOCRAuUBRA+U20TRDYYKKM5XDQ6L50j4nr4X0uVgF+sDEDVRxVN+SK+NwPWJO8LBFIBQiAGYmQzT7C6UUXXQStNY444ghs3LgRhxxyCC6//PKhjzPTPsSl/uat39HSKuplbXPrkC8DYqFpWoeIFTltyFqKefw8thxjZa67FmraQHUN1HQNNa2hKw1buf7ntkZoSVp/vETpIyp195dUNZiqJhsPjsRZZV68H6ySb1sfXtDVI2GpDbxi7ldJ91vfD8Jd4W6+/mnH3YLwyN8PlCecJgPjsXCKWx9DKu6YqaUf+Jc4HrkLx5wPzkfudHhBjOByNMfVAHM8kAnlOIaHEyMkOtx0+lyUVnE4dGsDX60FTAU/9L/f1n8nlM/z8K8UoONbLzKUUbDahvMmEWKtjW/Y5fdFWRgLhDzXjOPGxsRSmq+tQifjOrl4NOIp0P4uIz7yaWOd/562eqmEWYuPr3/968n8Nttsg8suuwyXXXbZbA89ENoqlpmgLW6Z92um780LGQBWSKJFBv6XFxYgsa/DOwWI/MZGO5CmjQWMYfNpyzNajtyujhZesK/DOcVCbZNr4Eo5XrP7q4GWHgC0vlL07gDeSkzfJ9ALvbajngMlDFOJC3eFuzmEu4OhNKZJKeTSun9L0nV8Tm4+FR6qyEfOQRKqjbBgiWPEQVpWZ/y1Xjjkj4RezqIBwIdYavfFSqlwbKiY10HvbCNDIS83NpuO16hiGWBfz++XYuVYU7lWkf+1Zb2uQogllo1BYGz6SoL8xXIzwajClrPGMIqq77F6JfgN8ETakntCJY5IkKjcUSwsYR6ILT3+8Tah6lrXcuwabwtSDN1EG9FEFZ5U6OF7Ugs9qcRLP0DhtEqVQzN/IN823tN+rfjy6HozHT1vtiPvbW4Id4W7g2JcuJuHW2bTqyHvjptzzn1fJjKy9Y1upp4HKnNAQsiC8YfGoWnwk+d/1DYID56fREJZ1wa69sK5tnEbJqyDgxLySSxyoRO4DeJ44fxLH3btSWg03OO8XPfKD/MuRWGsFo6B6pNR9XYZB8QuXIMX0La3gfL5QQdKySutZgwzrrOsYuRDUue2Yd7aSwuH9Ta2gaoN0DVAtwZ8ZR6T+spET74j/8EIZKbzZeed38MWkhrWwh5mXP9e78cY5tluzh/2LQ3hrnA32XZMuds2lH/PHyqb7sO7abplqS2fh2UI4fHmLlzgIhLBGUUIIl8YFzlH0eAn414IGVrAkICICdLKf/Sm2gvpuF5xsVHo2QLG34bTR8sBJKKaz/u/JL44uAjJHU0g1jmlkGvr88t6JaXdyHVj+5kKkHknPkrY3K2FtqTA3B7MC2Ou3OOKAb84L0DcCgxK2zjruq6h6rKFXWyhgs0n39lsNZauaVhs7tbb5gxRjBOEu8LdccKwPyS56zNMV8vGd+fPL9+gdB9t+jfmR/B5EiSWccsyYWv9JxMttXU8rb1YnmbuHXE35GRYlm/i5pvuHVIeZ/P58l7InY8S0lCjX1Zy91gvuVFiXoiP2bQQBmnRzLZySO3BvEKkFfEvj0mmhQMZWcnO85agbzmq6a4rBFSxc7s6++SF002rlOCFViNvBeck3pKV6Wzs3XGEcFe4O1+RO2003daCbr73puy0lVDK+2gF/zEH+/HOt+F//XTCVeMFCHM9VO0FBQmProHaWDvHY1PXuR/TTjyD8kFIqHhRQ/kiicihdYUyw8+zn8DOp4nrjXvdR0i09pAbIFxTXDcD7m/23i7zCT3HTcgztvs8zJJQtaWFjY1yy9CGv7yQqK6B2jQN9ZuNsE9tBDoV1IT/BBVeiB9iOEVN16tRJtuwiUqul0CdLSsP6zvY8WbXK2BrgXC35dqFu/MGvLt3Di6Ak1Z+2w8gC8OUEqJzByKK3CgOYJiYIF5OG+inNgHTXahuDTs1CTvVAWzlusrW7svCGB1WNRyPRqI08mnaN84rC1i/gPJbwysGNhN69fSa0fEw+LungHnifMwlipXY5rCnbEHlZusbrctuDbtpE+yvfw013XUtR85GqvRHgFFbdILhIdwtQ7g7t5jp/S/+8LY5ZH0P1r5KxYFj3PR0F+rJ38Cuf8KJ6K6JIZawT/m4JU73LTtPE4j4mE8wBti4EeY3TwG1iZW36c/YUVXsw2KYkT4F8xjC3a0OM32baY6Z5uYMiiS8MfR+1gnnpzaiXr8BmO4G/gaRMghmIpCGxKD3cSbPbUuEFJ/WYZdBoJVtEKatn/5Q8AnbPenCVloF2IkO1IIFqDodYHLCjainlHsTIgAo1deVHDcMYkOLVT0zCHe3LJ7u3NXKoLbDB6E0bOJ+qAJPS1BqZr/dVgFqCA5ZpWhwUUBr2KlJqO0XobPdM2C3nYKd6ET+5gfO87VVtnwLclkNqNLz1wUMgpmO5NsLT2vxoWFaFZ2GDZV3qRLPMWNOKetIzA+i4rTVLp5oKw10KmCiA2WnYDsVbFW5IabZ9sn++UmVlhWQD6Vb3GYrrlTnA4S7ZQh35xf4KJwcTpAM8MADX6wTAkwY56LDcm757axS7l0tCi6Hw7IcjkpDGetyPCrtRPNEB3aiArR2wlnHY9GXWb4MzctocD65jj6XuxnFyyBlZehjDiFSntbiYxgMWmFx9UnCON+zWKYCURUAV6nbMGQfXEU9UQF1x2060QEqV3lbrfz2KJK38X103Oy7cxA5OUmHJWxJMc+mNbg1tyS3FIS7aEwPAuHucKiUgWFOiFaW8jGL0GG4z3Y4HlonEKzysZABRQmfLgoAz1ftue63U7ROA7bjXt5iqwrKWthKAVrDdHQQL+TgJeIm/14meJJzAJpxRWVd+fHTqm27WWAmTka/8jPsaKfzQnxUyvbtsljBFuOrrkD0JvggrcN8O61so4JT7G9igeUkRFTllpEyTGvWatQKpqOgO64CV7XLgbYTFcxE5QqH5vuwT6b0c/KHFgM7ZxWuqXT9JrneLYG2QrElv3NLQrgr3J1P3OU/IJUybiht5rJVMICKeQOV6xoyULfwXlwticTWUlPgRRDKXqyAO3J8G88ven8KvZ0WXHBYuF9GA1ilvSMCJz6Y0LAd7XnO+e/FNG2j4nrrnZnolKTToRyVLjlpGDS5nnMsuJ9Iwyylhgi9RkDDFt/bMghmMsz6vE045a2Ifi0KDdPYhiqKcOP7PKDWY/eoWFTozE0LvKINH6SFSEfLLsxXsSKH1q7C7lRegSsXe6QCwEju4pVZJR7OI56PO8/CeReme92DvOIdKB7eQvStvoUo3BXujjHafkh68YX/gCXLA1dt8rd0LK1sfLyZC5fwDihwE8mPeVkYq7iM805zHqqQz2G1cgKjctw1HffXdlQiPBD258dMy4Tbjk3n5YeuKVlu419aVOC3YveUi47m/W0XCIOKjrzuAWYmPNx+8wyzjdfOVNnF/dsebKpEeaXYrMjdH1LqvICkrUdfYHih0BpWa1eZ07IqFqxGS5G1VkuVObf08nPm9foghB7m3s7mhUQcM3mV81xBuCvc5ZgP3J0J5yplEkGX/+jlLkf+fPoKyAIfk2nGm4a70HDWVBDKnM+JKKn8p6OZYE6FR+S/yo6fngMXReEcG9eXXVd2ncMIbKpz2uqeUtmoYJlTaGYUohkE8yLsAgxmXw98LNji7XTLLabZMq0sKmtgWO1GBSY82NzC9tuRy5bY1BrOztPZspbK21QWqqOgOi5xT3UsYIxX4Qqmch9bIfzNFbfVTEGXVHWLpReulV2n+xh3X0qtl5Kt54efcccoxNGVSQhP282kFUn7jFMLVLgr3B0E48RdDZMMGMVDL0DM1+j1s5Qnk+Y5HkkoEO7ZaV9WtHLrLei5qtjyDzlCPlGUJZrC8xUagAUs8dWHU8J0BRijAOuOHcamqRFFiR/p1GqV6B3H+5izBAXYyoUYbYUgqh2/ARMcwFT4EL/JFUkcEbBpf02Kiew09JIKOM5zoClyaft+ooLzkB8/ulyzEyVj63wMWgAbsS7VrriH+n5lGqq/dLxS7FyrGIMOlWFiGaafqLS54gYjMilvxaw/DTOh47oecfNgaRPZM3vPl7WkxcgJrVS7lVcCV83JPZ0BWUshijYVPw6VNiDcFe7SPvOPuxy6ZLFnP1pcaJVyBgLH2DZamRAeoL+5aARiqz7hY0OIgv1w2/RHvcHNTARUiII38DSKhxh2ccKCPrajvVh2HzMRhYfxfKa/YN8JJjIaYcrAdxbe1Na7ehRyskGAeP1TLLvF++8Fd7EegA3PrmdopkcZqPzxh3HzxlZ8AO0FchD7upipnlcopAzzmG+PB6BhGxUUnQ9v2zZjlgitNKpAow1nMwIWPpWCqajCZvZflRcqlcQWS/FFZOdD51tK2Gso6tCSZBVIoYIfSYLfFjz2bCHcFe72wrhyt9cPSK8fnzzvaCa9jHLRCKS8DOG1TIDEXCSwZejhymVixPPQJA4cCwsmoRYmKpJtm8IjcLggquka4jLb5DhY+aNppII6Ed2ZoGu77/w5luoLLijb6pc0MXlmXJ43YRegv31NvQbaeg9waJ+hTeMlVN5mdNZg7C5WwdnWThladMP+UVFS5UcPXCn3ropUsRIRLWAVrLZQGoBRKUkTJW5hKgXVAZQBzISC8lanmdRRjZO1x2xrW/njeVuvUZFrr6C1hdImdK3Mr4eukf9otuYODJgtvTmSlRrHHMOWI4dwV7jbeswx5C7xlcIv1PMlrPe9XvggY3lXW8dLN+9+0BSMsi5EGH4kDTRU4J/xP6aaPUd6vpR4Sl1howumgsAI71fRgLXWdemmodCt55lVAGx4Ea2q3bxS/r0sCo7fFvGNywwhLKiYyODCg/jMQi8Jv0vOh+d77ujQ9ZYcybawCy2j+567TW375BhEhM9GRI+9+OhVGQ9SUVNXMFigRuUqjKzQEPiIfWRFNbdxhSeoSxsfps0qP6UArS1gLWqlwAfCCYWFKu0aQOVGoVaVK0Omgqu8LaCMgpnQgFLQ2lt9k9wKRPhrKwTLMfQa0NZX5ryVwAt2+YcoaS2qqKzJwqvgPzx5L1PNLgxg03UtcfHSsmJSFFs2jpU3INwV7s4/7uZCjQsQgERHfCFc5KiTYtrPu5cbVgh5R6iSY1P+B/Ewz89xzxKBl1obWKtDHhK0dTaXFwsh9EIiozQN0CtbXJ4HrEsN8QJGKbhBxbSCrt3G4YWHHL7Y8uRS7nzYCjAd5qoUPzYVIcHx8xynkEvgfCyTCoDWjNOc84q5m1leV7z37Dl40U0hlzY+8nISw3E2WZ/zpx/GOuxC6Nsd0Veqmwtp7D0m5/TKGE4VpVueJgh55R7IhdCKi6Rzy5IWpGaJSxPe3pvQodUYFTYa8USurnMbkhNbqYKqRtr6GAS9KvH8vib7If4YtG3XL2Y+rhDuCnfnG3dTW56LkeGcnlLohVrgABJxyLdLQgpJSz/yMjpzQNINXNN8dBOaYUCazlwJnizqcz94bkfI8aiarl0SamGhmMTxaAsL+fyUlOPk9DBzh5XTcH/ovmVhxFD2STirlKe56ObgnG7k+PQQHsNiaPHx0EMP4dhjj8WOO+6IbbfdFi984Qvxne98J6y31uIDH/gAdtttN2y77bZYtWoV7rvvvhmdXAmhn/gMYuel8RJcjJNlBvPWTUs8LH3QpkGGvEJUiZqFb9HZWDBoGVfDRNyOKwim41qM9aR2LceJmOgUC0pWkFjSVUJsTefEiU2VNpq2NWs1hlZkS8xc90lacs9uAHsbg/0oD/PDLdwV7gp3B0POvyTGz36UqLVM964ijjEBx4VH+mOYPiueNBmfj3+2OvKREk+V9rwkjjCxkSxrCAz+iWLDcL52FOoJBTMB1BNxHZ/mSaim4/huO83QS/7dprLM4aPzJWcPTORTeNFkrqS7L9zxoHvYEHYszys8y0xQ6iA2ygmpcbtUeJBz2MaTfhhKfPzyl7/EQQcdhImJCXz5y1/GPffcg3/4h3/AM5/5zLDNBz/4QVxyySW48sor8Z//+Z/YbrvtcMghh+Cpp54a5qsahnS7HZRamBW7kUBU1RX7Wxq4ye1vwnHCMqYAqfDwijsqzGxeO9WZkyYpMIGUtkHWQPAJb0v7QlBPKXS3UagnXeGoJ5GQ3zQKF/0wWNgqfrfylTgRm2w8pWy4xk6hsu4VM89t1XBfCiR19n+7+o7HSS1C90zaK23+W8Uh3BXuCnf7QyMKsBiWsmFd3vOFg/94RSufuW/8eSDjIdK/lbKo/POtwnNORXHko/uxdhzJwhpVxlGNyLcJ+pAYjsvq8JeEs/uEaeLvBN+HhLVf1iEHpSA8krLjzz2EkxjH/XWHD/Fcm+DwdbRBpU2hbMdu5Uk5YM+CnpV7ngYl1yNxBZnwoH34ZxgMlfPxd3/3d1i6dCmuvvrqsGzFihVh2lqLiy++GH/1V3+F17/+9QCAT3ziE1iyZAluuOEGHH300UOdnAbKYxqo4cZNaIuv88Q9So6ipD2tDLTV2fYWvN4vZXWHijp8yD5zSXrWBRyDNai8/Ze0IGsXZwyWtFWAtS4xSrnEqNhqbFHY9COhWMsACDYlbzlSHDHPoub3if7GSoMRtGBZtz2H/hX24ATOv6uXkhbuCneFu4NDq3Rof87bKuQhaVDiKeV80HpjXY5HHY4X3/Pi7pMGLA8XGGilWSKqGyMkcBIIP8TW88l698Na5W6gddxR1vGSkk/dOgtAwVpA1Y6bmh4BFS/lklOJ+xaObpa2s3xbRGdOAa1deLNQT+rSxP0Dt1muRx5mio2ByPeE61mOR5WVA+5CBXEYHKreLpxmInSQEOMgGMr5+L//9//iZS97Gd70pjdhl112wW//9m/jYx/7WFh///33Y+3atVi1alVYtnjxYuy///647bbbisfcuHEjNmzYkHzaTrBZYNPKsx/y9xa4YzaVfKnbWFhHyrCxzBWaRtKbNv7DSJVZhaHiVmixBmMLkSzsoN5Zol60rm2jMreslZASO2vd5uevUkK7exeXp4l5aes7H1o5v/fxvlPyX7kgDJLc14/Iwl3hrrt3wl2gnbs8ZMSFmrt229NWT0IwPATI8gzaQi95iCwPMVQs9OCcDxPDb8z9yH/Y+zognnuGnLcO3Jg0LCwYnbxmeMYWwi7FMA93OjQT2EFoI5x7uK4gQmwILZLr0QwpMteDPYM81MoFCD0fzbhfcj3ykBs967jMDhxqTPgyzMY//vGPccUVV+C5z30uvvKVr+Bd73oX3v3ud+Paa68FAKxduxYAsGTJkmS/JUuWhHU5LrzwQixevDh8li5d2vMkY1zbNpbx6Txzl1cOpTET8gqdtgsfmKTw0IPtKIOOrtEha1BFy5rHK4NlRoTzNjJZbi5Gbn2lbIMNzW09MwnU7JNbfHQMl2nN7Dyf0IfKQlWM0Oy8tDbBbidyd7RBR7lri70E3LUnsVxwGzWtsPjokJzIZOH2CkkMalsPQmLhrnBXuBvRxl0uwlI+xhBMvP5y7gcdJ+YTNMXFhK6bP46wCRcb4RfVDEHoEI5LeYnKOk42hLCNQqFiosJz1EwgC6f4nlmTKpmuJ1XYPvkwcRJyQDo2lo9EBFnGc/dR2vFc+7BivF4XWql0DC9W2pVh+ku8D6GW8JeHX218LqxeyZN+8zJQ8WUFjvD6ZlAMJT6MMXjpS1+KCy64AL/927+NE088Ee985ztx5ZVXDnOYBGeeeSbWr18fPj/96U+HOtFSCzKtuNtjUflNz+PmpSxsrjQb51IoNIliZxUnt9gSpa5IjdtUoScJTl6dE9Fz6zqz+ULLkVnoCbH9j01+jY1rK5A0t675ulILfVikOQzN51viRaXch0O4K9wV7kb04m4pFNVIWiwIkMY+XARnQsUdk4lCarkzscLdj8r/APMciNAFlTtynifkLCTuR+KA2CLvDBMllDDNE6j5Nny7xL0r5XgETttwTsE9VNHVC0mmKv7V2rBGQXrPePfaXq5H+uzS7rX0zLjw5jxoEx60zczfhDsEdtttN+yzzz7Jsr333hsPPvggAGDXXXcFAKxbty7ZZt26dWFdjqmpKSxatCj5AM0CyDHTrom9BgiKrZy0sJXGTIiZ3QXrK7MMKV6ZJEsFqxBpBZuRsmHfBTUdK+/U3nNEJzuPkvV4L4HYRbHQs6FI6pTcFZ9myUjUEqyQVUTFH9XcmuaJToPbdzl5SxU3QbiLsE64K9xt4y4fUj0PRQUHpCBe43rLONZsTaecK4UGjEugpL9JiAHhRziIECY+8t4vNrghTHAoLg4suKggEVISIGVHo110uEH2bHJcmwkPl2TKwy8FZ4/lNFU6OnuKl9vs0+Z6pGN12ObzKoRbmnkjqdsR1sGEz6AYSnwcdNBBuPfee5NlP/zhD7Fs2TIALglq1113xc033xzWb9iwAf/5n/+JAw44YJivAtAskM0CyxR2IdYabxZT2zw+y9bTPJDeZG4n8QJE9vWErqN9TRYYs744YarKQFcujk4WcrAKM2vO2YE2tfMmmG09GZfbibgttxa5Ze1sa+MtPYOqch/NzjG0eH3BJ9u6E36sCjYqs63p3rn7z2xqfu+zCr+tZe/uNW9BpT8ESTijR8VNEO4Kd4W7g4H/iETnoilAeoVfeO7HhKoDB5Pt/PyEiuG/XAznTlwYXIt+nDknPUeIM0F0MH7aCZuFW6zjHIVdJhF7wvBcjyy0UrP5tOeM9cd03I7hRP/9HRdKtB0WKmIhxXhNNuRcUbiF85yEGXGdC7qOFxNtIS/+TPMQLz3z8Px5yDZzO3LBMawLMlRvl9NPPx0HHnggLrjgAhx11FH49re/jauuugpXXXUVAEAphdNOOw1//dd/jec+97lYsWIFzjrrLOy+++54wxveMMxXJagUYqY0XC8C6gWQZGHDt5Qsij0E3D50zJjN7W6sBqy70QYKBnG4aqqkaLjq2iI8WMrIji0s7bbVJqyrtM/Q9r0HlLZQ1rXsFBxBadhqV+ECLoXaq2Mo93gt/LDWqdoudd8CtRwrpqh11kuAF2oV44VNm57HzWP8F+xe0n10f9PQAd/GPcMsb6FHy3JzDcwk3BXuCnf7w/2AqNCTCgAM3PDqsDpwk0Y6dd1DAFjAuIfvrl25EXd5zxcoxysa8t+NbGoAaPdDmLgfvgwYwGgFGA14XlprAKOdk2DdyKRaWbcd3PFCDxUDOBYq+HfkupO1QOg2pQEY6y7FAuEtthbxOCX4Xio0XkcY+Tf5G/kd8lFYqCXkeTDXIwqPZiOg5FZqFbuWB563uB58XA/+rIrhM2ogZcIDSB2ymWIo8bHffvvh85//PM4880ycd955WLFiBS6++GIcc8wxYZv3ve99ePLJJ3HiiSfi8ccfx+/8zu/gpptuwjbbbDPjkwTSSnx2xzG+gh9suGr3V0flDovKGnRBXRpVrLgVs31JtVNFrt221iIME6y0Kw7QyhERyqliCwAWyrrBaqj4WAugRtk6ZHHLMGAN+0Q7z8TKm1mYoStbRupo5TeX5dZs3hLvNSx13quAEzyPUYZn19JyLCF3GoS7wl3h7uCge0MihAsQqLQbbuAiohipbeUFtXHdvlV874tWjodGKVRwgkGTEKbn5IdcN/6ZWSaWK20BGFgQ39xPobIW0Mq90yU8hiiElWIChBSxoT61CLoE1r33JTzKUtd4ZeOIpWBigwRJnt/BerPwXjlceIQQEgkQznHG+TS0yEWJCYK3bVwPcj7cc0h5m4dbSo5HvNup8Gjr7dULytqe2m7k2LBhAxYvXozv3bMLFi5sRpCoEqflpMRrq2D89LQvGDUUaigYr9inbccts84s2mSdwVpbjWlboYb7u8l2YKzbftpWbp3V2Gg7mDZVWLbJdFBbhU2mg411B12r0TUam0wHXaPdtnWFaaNRG43pboWu0TBGodutYGoNaxVMV8F2tSsItXJjItSAqhVUV0HVgDKA7gLKuILT6DrGM6g7nuwdA+XtPV1Z6KpGVTkLvdIGnapGpS0mK2d5TlQ1JnSNSV1DK4PJqsak7gZbdEp3MeHt7AlVx49fXsFiSk+jgsGE6mJS1YG8E6obKvAJ1WWWXzNmTrY17yVQStTrFdZ44gmDF+zzCNavXx/i2Vsawl3h7nzn7prv7oVnLHQigTtwxDuajtzUwb1zHNWBf7QNcdBAOf4Zx9euceu6flnX6vC3azS6tKx2f2ujAx9ro9Gt3Xcbo1HXGnXtfv2N0TC1AoyC9ZyDUf7jeWgdR70+8n+9ELFxOA+aT6Di37BKk/CII6yG9xKR+FAIbh40673FnA6tLQspGnQqx20FYMJznUKLk7obQosdXQeu098KJvC9UpH3kdd14HEIjfUQHrnoaDp9Bk8+UePIl/xwIO4O5XzMBciqbltOFrZbZmGggqXc2CdT7nywHGol5oM2aShokA3J4mbWq0zlvreja2cRqmhld5RBrbRrRWmDWitoP+iNGyzH2YfKx7YtcwSDTUiqvHb2tTIWKlTg1JLMRsoLFjirvAO5m3HEkNiV2J48Xp5mWHMLr0oq3rIi5mTNY+mlypsjT24bpPIeFwh3IdzNnrtb3lw2LnBBOzrBKISJb36jwEX3jJ0IqNi8RuRrOB7jIaxphF/IieuAuOj2rbShaIorG9qHgyxCOIbO1xhqmWv/vhcFC43wHhj4EKHx12F8mMUgDFAGCxfOCc5H4ya5xV5s+EuLYZiQKM2mVeR16NXCHI+8C3GnqhHGNwFYLpZhgiO6HhN52CULt/D8pmKSaUF4EHoJj9m82XnsxQeQVuLDWNi8cucxc3dMg9rHKCtvU1dsmVZxRL4KFkZRPF3BWIUuKK6ufWFCtL8QLUOyxywQyASjw1saDQyUrVxcHZ7E1lXO0bqGX6giwYNdHSvvYOt5y4/HESmZiQarqXSskJtWXmrjhbh5qHyjhefm0+Qkd09tg8D8udD2bc+thPlQeecQ7gLC3fnDXXetnkcUboENAqT2zhwPwZDgSPM/VBApxtsLFAL0A4MHIUzhFxNcohgK7KCGUSqMfFppA1NXISTok0JglROneQgG/njWsBtv4MIzyoViYEk8R+cD1gdoSgIkER9xWfKCRTYdQ4hIhIfO+M3H86DyRvlMfCyPJNwCNq24CLdJmS4lmZbyPBIuwDaER0l0VC1lpR/GVnxU/hOG50WzEuctSBdnVKFSgXIqmeKOxqZDAddhP1rnpitf5KgAGUT1rply73g1Pg1XgU0ohWkAHaVgfEsSGqitP2uj0an8u8cRC46iQktKna7AALbjEuysBlBTqVYhjhjsvQ6z9hq9A2KsnNt54UPkVmkvAUrS6+g6/HUKu05ajqmSTsnqnhXrOQAeZ29W6Bx5L4FSRd3oQdIyPWoId4W785e7Nv0B4XEFIIoNoOiAhJwPxGlNSRC6i2nTQZ58OkElJRQUjY4ywekw1sR1/jRqo2G0CTt1ANRK+cRopwisUbBKwTARYGvtdrGejyQefPjF8jCLN+/acj7CPSDBQe4KOR1BeLh5GkAsjN9RsRymhN/kfFhMMOHBe7cQzynM4sox/Y18j+EU7nYwzgdnpBluicub7h8w+5yPsRUfhEErcbcsfW+G9vNUOfPkvGgjatQwrrAAvgWpQgHSoJZlswVJtuGEMjBKYwLur/YVnjHeivQFxlgF6wuMtQZdf/Z0WkZ5JQ8NWyPGFIPCdslUwbr2xHZxcn8zOqbYbSuPI5a7J5qE1KGXAFPJvOXIiVwllbQN8XC610ncO7Ot43QaL6flCR9U5ALnyDhCuAvhLufDPOEunXcItwCpCFExzNcmQHhvGBLBsDrwkFy3JEHSuu7fiJoCXegQFswFSDgjpZy+rSkE4zY0Srn3vsD3jDHKnYdR9KoXJw6scoKZCRH+VxV+T20uPmhD7nZ4ERLHqEHB7TCNUEunqmPIsEV48DyPGHZJhQeJbJ7nkeYrDSY8crejLefDPYutSHwA7ZV4uk36Aq5gFWb2NXyByStz12JMI1i86yLVmrHyivFzik8CGtR7wJ2rt60tizn7+GRtXHwdGrDWb2Nct7JgYwOhBrewvuGpoq1HlbiyoH7tSbctFiuPXRO9TQ0k4zrkmdN8OOpcJdM9A2JlnNt3WkViu3thGhU5f1aDYL5U3hzCXeGu+05/7GTf8QPdy+CoAUnIhfIpSIAAMQST8I+JkTz/I/R+8UIYSgcuOlHCemKF7uAxF8Ra53hZ67urA2Ek0JgD4s7N9dAyUFbB0M1XNnLRuLBLIG34qBhe6fWMuQjRfpqcDr8seR+RNqG7OBceeaglLmPdbJF2Ka8S7rPlQVREcTdonkfJ8XCXVBYePDw5LMZWfFQqtbpKlXhbC5Js53R/m1XO5LNlXRehQOMmQAHTlt4WqsONbmtBTgOYUApGmaDYw3mYtL96h2oj31+dlDpdYWJjB1svWoPJmz99r4DyewHc3w5L0ksHk2paefTehQnfc4DUNBWAXEnnXRTzcRQaLUCksUeAfgBYYVGxl4BGGivnnGgs8/cw588oIdwV7s5b7sKAhmoJoG61BQHi+OpyOWqyu/rlf/jwy4SqAQ1oGwvCNIAJILhx3O0w1gZOOjHhpkmgAI7vyigvSJjzQWEW/5TCW5q1CmLD0ltwLRAG+Gh7AzUXHfSXBIeKTkcyGi/L8wj5HX4dOXo81MI5Hhw95ZLBaYDA+I4c2+B62fmIYnyYUEsv0ZGGIQcXI2MrPoBYCGtL6q29Enfr094DAEIBqKFCRZy3IHlCn6vonWXouGlDQaqsq/R5/HwCdajIKWmKW4fG1qG500GstI1vRcZXIms27W1sZQBF3cVUGCfB7egLrK+0eRITHyGvqnxsvDJJHHGiqpuVt4qWNf0lQpd6CXDFHcjMiJzHB7lVzcmbW3XJkL4ZJ0LiXoEn4wThrnB3PnKXRFni0SkkuUUAQtgPviVdW40KGpWq/b3rRAFC2ysnLGAr9Mr/mAYwoWsXhmThFqNU4CT1CNPKomu0E8aV47NSjo/GaD9vYYyC1grGuIHJKB/E9cryjp2FEyvkfPgTLw1GoTiX/T1SKgoOeIcujk2DRHSQe0cviqPutDy5NB/BlMItufBw4Ze6EXIh0cG7jKflYbBQSzIfRAgXHLY43Q9jLT4IbsS9ZiXOUUrgS46RWdsI2/bvuui6ksEv96P2hRZkFS3erMtYsAy9TWh8V0WAdxlzMXQntlVmYyPEHYONTfYgy55WlXEjQKpmq7FS0bomq67tvQDN7onRli71EiAlzS1tuq9JRY+00ubJSW2JSjxRL7esx7nyziHcFe7SMyYOcG6MK5KQC7iI0FnXWzbqKQ/FeO7BGs9LG/I/SEjz/I8JXaP2cREnirUTPeQi6RpdU4VkaQOdhGAAIMRVWN6HsuTYMTPDupwNY5TrlQV4bqp0Izhetz2lILiZ4AC8IFWp4KD3InG3g9w8GigvFx6acT139nhvLp7TFJKpmTuX5iexPI9ZCo9hhEYJ80J8AOVKvJeFDaQtSN57gFqQBhTfjjaiQey6CNXsPUDdxqgFSYWmYhnZ3DIkm7BrXEXP45VkY1vfe6DObWxDMXtE+9ogVOAhPl7ZQPiKjYvQ0Sa+bpwl6fV7L8AEazl2dKygS70E3LOJFl5bDDBW1O22HO8lEJ87rStzonmM9u3nCsJdCHcLnGgeo337UcG1lN00z/sI7PThEzcdBUhMOEUjAZV4CKUxgS5cVyiX/zFBX2w1JpQL9U2jcmE/ErzGfwdz5boGYQh2xYSxtso5IdpAK+UFjRPTzgVRXigDSmkvmH0Cqhf9lgQJAOWdkQb8sw4GSCY4eLgliA8giI3kvUkqTifvWPKuRp5IzXtxtY3nMaHjYHhteR5toZa8a22b6CiVl2FyQMZWfGjEQhhj4tHKbqvEgXILknoPuOk4/HQ+XLBThLHw5L0HyDZMVLuPXZI1OKFrTBvXy4C6jBG63iY0oYQ7u5CsQsDFKt1HQynjuotpZmFbxPddJC1G9wlEpp4BvvKe8NZ1blmnmdNpfLGCq9D56Hj5yHh5L4GorGO8MGZY54q83EugWGHzaVZ5j5PQAIS7wt0m5g93o6MTQixAFByZC1ISII6bnVSQwP14bUKHCZA65HjQPZxGFbreTqNCB5GfGlGM6MpCGwvXCV2ha9xzMHBhFs1CLpV2IsRYhFCMBfxgefTaAMoPQZgPl5418LlujLzn047LQHTewhDpLMG0Yuuoy3gMr7BwIhPVU1U3iG0eViSe58LDjd7rjjOpuu18Vynn3fOKzgrNu2tqdz50YVkbxlZ8cOStQmpJ5pV4vi0l8AFkH9psOsbP8xYkZW9XysJYV3D4S7tKWdt8xD6KndfKjQxJ1rWGCoSKv1A+SU8jjhxZ2XBFBoC2FgYafkwcV4EDjcqbBqnhL97iyppX3sGy1rFr14RKlXIjps1agfk63kugZOOVjpMsUzZZ3tZyHOfKO4dwV7ibbjfe3CVhlXMu7QFjQoivJEBqm74HhoSw8VLBIIpncuOA6LRNw/XMcvkfVeAkiWIKwdDzD+EYADA6TGvv0FG3WGXpOpy4qNk6Eh9ReMTlbeBiw/2NbocCEtERRisNYUHWi4Vx25WvsvDosJALFx48rMjdir4JpgXhwXkwqPDYqnM+gGYlXkJbAl9jOzR7D7gfAhN6D+Txc96CpEJjfAHiCXwAki5jE0p5mzDGK5NmsZ+28Pahh7UKqNxZKqVgjLO34QtJqa94UNA0cE1uV4fKmytst014DXNG7JC4lFh4sRIv9RKge5rOp4UCQLHlSM86n6aWY7/Ku6L4c2ukdvQQ7gp33TOeP9zNxW6bAAnbFhwQHoLhvbDcVtYNcucduOQFdIhdcCe889E1VUyGRgzBhJ5ZPvQSElA1gvNRGw2lXW5SbbTL87CAUnUQHQZIhEj82/5jypOsueAA4EdbRSI6Yj5S5LtGnCYec55TcqlWMVSSC49kMDHGc55QXUow5WKjFGrhwqOU88QRrlttBeKjggqFsKYC79e5Vl25BVl5vhhECzvcJz9d6j1QQfmMbVeZx77rJiROUeIVFZqJcD70YjAfS1c1amWTTG3+V1sLuvWKeXr01kbAJzoZl+zk3iyqUNcxRhnHQEBIYuIxciI6t6snq6ig2zKnk9HxMiuPXsA1obrpi4gyQvPxFDhx+/USyBP1Bq28x6Gy5hDuCnfnK3dzx0jDhpwjl2ha+y61GhVq1MqLkJYQTBQgXVTQ2BSWIQgRAwsKqYS35WpyzKKFFASGNeiayuUImcq9MsDqkIiqK4uucedtrUJXxWk+mF/tQzCA46zxl52Kj95IQi0KbJoN/c/uK08k5c4HdzuSvA7V7NXCQy3Ee967pVeoJX2BXMp77m5wwQ00RUe7q7gViA+OUkXeqxJHNt08XnvvAVhfUfjCwfuuu4Q+sg51SJqiBD7eZYxenBS6MMKNINmBH0dBkaKPQwlTZrYJiXwxWaoOBQKh9chbjDyJKbf12vqK84xpPiBT3kOAiMnJ6O5xM3EpITRT0G29BHol6qXL5kflnUO4K9ydT9zl1xi6fqtMgAS+kPNhmommgzgg1oda/HoKwUwkZ+RFMdi4M6hC6CXvkmusDSLF+CRT+HwmY13vlpB86t2QIEz8NGCD62F6/JZysUH3KZlGmvNB3A3TOnI3Fx5h5FIWaklCKH7bXHgMEmrhzzo4HgMKDy46hhEaJcwL8dELvCdBXJa+wIvHz/v1HgCQFC6azruQlYau7jVk8LQvKNOmQgd+ZMmkmxjCcMCVsnH4XmgYa5PeBdai2Fecv++CJzEl4yCwynuQoXm5lZdnTYf7AQQ17c84IXlyXwvTpfm85Zgvd+vKlbf2SY/jDuGucDfHXHOXRJtp5HyQLYBEgDQSUfsIEO7GUTiw8Q4Y5UIwEyp2TJ9GFc6v44OI8OEY9ytfJyKDXBAa/E75nKWiCHEbgIcPyfXoNwotFxvwl8ndI+IynXvudsRpWh65zROoc+Ex01CLOw+TcD70cmkRHrnbwfneDDtuBc6HUgraE8eEboqxFZkm5ynA2mILEsEutKziBqvQXQGqqSCxglOzAmVo2h0yKHbT8iC4XZjEK7XryUCvT6f4ZJiuHGGpfzlNG22hDSVFqdBapIqbrGreTatXl60JZViyXrPypkqIZ/eXFHVuWSfEbCFziA/6lmMsFGnLMbes2ypvPWZCQ7gr3J2v3K38s+C/ISRGAKT8A0KyKA8D9hQggHfogE0WmFRdL0AQOJmHYIibdA4GKoQGq8qFUSgMQ9O6sjCWEqVdjxhyQsjpCLkliO4HTRP4dI4kPJW5HlzI02sJEteuj+iYYNsNEmqhkGLYTnUbwsNt321wvpTfUXI7IteZEG84f1uB+OAoVeR5Je6Wx0GcSgl8SSHKwK3DeAzWjVE1E/j4oDmaFYz8ldFUiWtl/A13drVLljI+cSpN6guk9xnZylvZ1rr7EN5z4SsL3mLklXc+Oh4RO8YUmyPjcXJHNV1W1HSfwrPKKvLcsh4mUc8de35V3jmEu8Ld+cTdcM3sR4TeuBzcECYiApgTN4gAyV8FEI7XIwTjxo8BaqUD17jzwaeN1Y7Pofyp4ISQAFFWoVI+34NtF8MvqfNBwpkjFyDEDQqtJGFAJjrisv7CI4gPFROoewmPkuNR6kJeCq1wwU7XNJDoyMrMIJgX4qOEvBLnMXSEZQgJfOm+rgAN+tbQkmXY1mWsLYYOjZD1T69/7sCreX8RxluJMAjqH0C0Br11rXxyX+Xt61LlnZKbtQT9fJWvZ9txG47HEenetCXqhdh5pqZ5rD15Dg3V3G5Z8+dO6FV5j2M8nSDcFe6OM3f5Dwg5byRA+HLtHRIKw5iwb28BUkP77QcPwZC4cd9pok0YxG4VRIeGwjT8d1qEruKUD8JFCIAgRNweftmAwpDfExIcABrcpWUxz4NxGqzLOFI3TwfOR0evX6il1+ilSQ+XIDx42KW38OC8n23Oh+6/SURd1zjrrLOwYsUKbLvttthzzz1x/vnnuxfyeFhr8YEPfAC77bYbtt12W6xatQr33Xff0CdGPQbyAlsqtKHQtyR2afjWC1OmQDOO2+uBJYMNMRXaGD/fZ9a7LPs6GWnRtdScdTalXUZ+x2fsd7QJ05NVjUr7gWMq9vEtwonKHZPeczFR1ZjU3obz05O6i8mqi442mPTfM6F4LwFaFj8UJ3e9BWIPASI3z5xuS9RLn2FqffOWI5G48j/Cg1jWvSpvzpdS5S3cFe4Kd/tD+XOmTwhbqfjRtIzdlwr5S/vKre5g/avYK8Md02DS90RqfHS2nHGTlk3qbuBnx3N0SncxVXUdn7TnVlVjMixj6yr3iXwd8OO3n+p03TE047DuhpAhrQuD4vlzpG0cv+ncu8m19bwX1HuLlfdJ/hz4/YYrJ5NUZmAwibrIdc53zZ8/f/YZVzQwlGweyvn4u7/7O1xxxRW49tprse++++I73/kOjj/+eCxevBjvfve7AQAf/OAHcckll+Daa6/FihUrcNZZZ+GQQw7BPffcg2222WaYrwto9BhQTsXmy+P2sQcBVJrABzC1WoiftyXwwQKl0SNhya6O6tx4RTnt353Blfo0ABpHgWxsniwFxC5llDhFiVIA3MA5SG29itl5RO40ppja1WFsB6au8zERIhEp9p1mTvNKxV1FOYbY+7nawg+tXzdg5T1oK1G4K9wV7vZHpaKYomH/HRzZyAlJaJuHYRgf+4VgXEjRIHkRHctLcvvW3slwMIgujMv/0OHNuC7HQ8N4t4acED7fCMd4EefGFkF4rwwdvw28McDdjcT9AJ83SF27zPlALAs8jBjCiWzk0jyPqS3Hoy3U0pZYmrsdXGj7p9fgS6/5XhhKfHzzm9/E61//ehx22GEAgOXLl+Of/umf8O1vfxuAU98XX3wx/uqv/gqvf/3rAQCf+MQnsGTJEtxwww04+uijh/m6nqBKPMwjtbAb27szDJZ172PHBL7Q7xzOtg1vE1WxG5b2yj3YhIUYOnVfpLc2uoonVuLGF+iONq4LI+pgZQdbUMfuY/kANZqRuFR5c7u61zsB8lh53kMg3B+GKiuEJRuvLV7u7mXLcyg+m+Erb0C4K9xl94dBuNuONhFSCsWEl8sFcTyYAKmg2cvryiEYEiAhQZoNRoawnQ7dcWtlY/4HxWas4/o0AO0FBo1NQyEYraz/6wfcs6r4HAl5vkfyd0DRwUMmbcKDO0qD9mrpF2pJnjPjediOcb0kPHLe6+zvIBgq7HLggQfi5ptvxg9/+EMAwF133YVbb70Vhx56KADg/vvvx9q1a7Fq1aqwz+LFi7H//vvjtttuKx5z48aN2LBhQ/JxJ+b+cbTZkrQsTexi0w11Fq1DbhuWLENuF+b9/6OazGJsiHE7njDEycVt7GAnJza2acxXfjuyqWNiXrTs4jyN9x9tPtqmggl2eq/s6bb+4m3Wfh4KaEM+KFPj2RVsaaB35a0L/ziEu8Jd4W5EO3ebH+6G5KEYt6xp17dxshSC4WGAUgiG/+D2CsPwUEzHhzSmdNeFOKpuCMdMKBNCMrQdhUQobBJCJT0+xG2+r/vbZaGVLqaycAsPseTnXfo0rt/fG3ePYtilJDx6hVooNNmoS5CGWXIeUH4T/8wEQzkf73//+7FhwwbstddeqKoKdV3jb/7mb3DMMccAANauXQsAWLJkSbLfkiVLwrocF154Ic4999zW76SCaJh6Cwl7rCcBT+JDjwQ+Uu7xWMMk8NG8U948W7tvslQ4FxWytcnGpq6MZA/CoGkNQvvuY2nrMc+g5kPxptOxV0CurofuL55V2m12Xlu8PKnoFben2y3rtso7r6jbINwV7gp3I9q4WyEVvyEECBR6udiWni9sfkAHhI7jhElzJFTfNyvwjnrCUC8cDevfCcMHI0vDJjwcAyCEZAA47iJ1FrlzWAJ3EXgiZsn1iMubTgd36LjbAaDgepRFdSPHgxofLfwGmKOROXu9upC3NZJ6LWu9f0Nsi+uvvx7XXXcdVq9ejTvvvBPXXnst/v7v/x7XXnvtMIdJcOaZZ2L9+vXh89Of/rTlRJstyV7o9R4FUu2DJPClx4wVl9suKvXECuYVGCNUlRGPFDol+JWmeUtSw4bWJCcybzGGGHmPypvb1fG8yrHyJDbOWohtiXr5feZWHkfzmTTX9XIK3HaD01e4K9wV7ka0cbdSKuEfFyPh2jIXxC1jP155S3oAB6TxQ6n4j2eZn1FMxh9s4il37OI0CVZ/fBVzjDpsHa3vl2xK7sCE35d47I5pwjZuXXQ6+gmPtMdLWXj0CrW4Z2PYsyj1cBlOeHCHIxeoxJmcO/0wlPPx3ve+F+9///tDDPGFL3whHnjgAVx44YU47rjjsOuuuwIA1q1bh9122y3st27dOrzkJS8pHnNqagpTU1ON5aWLcCMVNCsMnsSXd2GkAZzcMdHovsgTl6owTQ8nDkWdK3WewEfDV9N0KYZOL/FyLUkdfzzYWAouhBnf2AiNJEGKYpIUnyy1GJt9x9MfjUD8jOhtsfJeiXrhWbW0HJP1iDZtfMa9LWv+fN1xelfeSaWZHUu4K9wV7ka0cbd0DtyJC0gcDxuX+UneFdetG8IB8V3DK8USsj0/J9D1ZcmCutRqxYd6R8MFoYTUMDgZYmIqMDPXg1ByP6h88CRULjjceZZFBxfT9HdCdcNx8ne19Aq10DmUuF1y9cLycD3+GmmeXfcwIqMNQ4mPX//619A6a8VVFYxxF7pixQrsuuuuuPnmmwPpN2zYgP/8z//Eu971rqFPLi8AQGplJ6NGZpV4DqrUaTpP4KPK0U2nAzSVCopBujzvQVBMlEI5Uxs+JyoUCF9xu3dqlLO0I8H5+P/NZKa8BdAvkamnrZe3UKh16QlO9yu3rJNn6sld6p4Yn03Tsu5VeQ9SEIS7fm/hrnC3B/IYfhDCiCKkEYophGFCQvUsQjDx3UQsHON7xbgQYsdxlIVh6jxU6F8FQHztwI/5AQWoOryZ11iFjmKiQ1FCa697lfKDiw0AjFepywFgINFRcjs4r6lMABgo1ELcpnMqhRNzt8Ndh//bw5Htt7yEocTH4Ycfjr/5m7/BHnvsgX333Rf/9V//hQ996EM44YQTAABKKZx22mn467/+azz3uc8NXb523313vOENbxjmqxpo6wnQBl5ht40eGbe1rUo97IfYCnX7GKbSveotxNApBh8UciFTOwzmpNxZTwCh4i5lbbvj5ZV178o7t6tTi5S3HuO2bn0sFOk9iyQPz6jww0n3N4+X0zMK+xbi4uVxMYavvAHhrnA3vX7hbhmUGN32NmYAgOfyICPyUl7STB0Q7tDFtzN7ce1FdKVqwFbOrfPim74/HAPaOSFWOYePBLv13KZjqjoK+ezeGN/NvISS4KC/fFnC31kIjySUQgIDzVBLHnaJ59R09Pj1tgmPkrjg4nqYXlxDiY+PfOQjOOuss3DyySfjkUcewe67746TTjoJH/jAB8I273vf+/Dkk0/ixBNPxOOPP47f+Z3fwU033TTjcRI4eCXObWyexDdIAl84HmtBUqFpfKcvJMZq5Al8BN1WQCy3vpkiz2xs14XR2YTuBUq0PcBH7ePJUjzGSmMgAAgx8lJcMVfapZhiTvRA4qzlyLsvtqlrHksM9wqpZV1K1Gs+A1o/s8obEO4Kd4W7w4D/iAQ+Iu0SnoRiSg7IZgrBJAIEXcc2zzEDgxraJ5+q4IK409BOTIC/niCKkEr5odoBN04IEJbHa4/PjbrguvvT/EHPp3PR4a6u6Xa4bYcTHjwck+dzcTcvnm/q6JVCLSXHY0u+kVlZO0STbATYsGEDFi9ejEfuXYZFC8txct6KpPXcrjbWhnnD9qmTeTdNlfa0t9tquLh0DeWntZ/WcdpqTKNCbTWMLwhxW41pW/ll2h/L7Tttq7idt6Jrvzxup7Jp2k6FvulAbD0CCPFxN10H8vN3AgxSeZdiijHrutuwrHtZeyVbj8cSNVJV3c+y5pV3W05FwqMnDHZ5/gNYv349Fi1a1Nh+S0C4K9x11zd/ufuTH+yGRQvj+fDxaBKe0jKWl9TGT3oZ4aD8NMimM47WvgdViacAkmMTX935qWTanVsMu8TrTJ9H/nK5UiIy/7HnoRUgCg4+zR25YUVHWwhxtqGWfm5Ho4t4gcsbnjBYvtd/D8TdsX+3S7G7YqEVmcfLB4mfu+36v7irhIpaf16h19a9K4O/wAsWMKx9kMTggaKNTfYft7JDSxIGNEBOblNzm69XFnWpW2KvWLm731Gd8+vvVXm7e10opAPc4lKsvOf2re3OuYVwV7jbd/sx5S4h7xIOpG9mHuStzITNHYIJx1LaO28eYVsXkgl5UMwJqZDnh7DnYHkp6//cuRjhIiOfT52JZmhkGOER9kN6jHCfC+fYFmoZVniURAet32Jhl7lE3lugFEcvVeKALRaSWMHy7xg8SSpkV/tp+iHgtnUeQ+eFomRjV8p9TV6JUxzS3QPlChRTzW1Wda+kpjbCp/czVdnuHjW3KyHY1y3x8l4txxy9Wo7jXnkDwl3hbty+bd24IB8ML38tAG3TS4BA8VFRLeNrJkSAzSJAKpgYhvFDpJeEMhch9N0kQkiUAFFskCvSeq8yLiXd33uIDj4dBcNwjoc7NgsrsuPw4w8aanHL6NzLwqP0TqLZYN6ID6BZibctbxu+GnA3OE2+A6iA5ENX81g6T9pz0wbw9qAuFZxCDL21Eke0BCd0nWRna/8mRheftIkFWOrCxTOgXb91d9ZkV7v9TLHyHrSHwCCWtfvOpsJO7m/Jgh7Qsh7HirsXhLvC3Xi88eUujbDKc5KA2CsLSF2QXCAHtAgQWkeL3fxgAsS5bx0vYA1cppHPJcpcEBqUjHJANCj3qQ4/1BSSCcOpc9HFlvcCFyBF8ZG5Ef1EhzvOcKEWOk7+HW0hRH9XG47HsIPkxevWbHpwjK340FDQUOBd/dxyVjB6WNh5JZ5v7+Z7v7jLsJEjXQvRFBP4mn3U+XeWrMJyKzJdFq3sJDPbtyzbunHl2dT0V7PC4IiZd/tqEr4XeIyzaPOFQtFsOZaP11tFD5Kgp6GK06OGcFe4m6yfR9yN5xCvtq1reNy2JRGVcTQPuVASKh+dt58AqT13a+/WtYZhkC4j4ZHwFUjdEL4cSJyQ9nuUl1HeiGgPh6Tdu1MB7Y7TX3jkx+PfWxIe6XnPXnhsDgE9tuKDMEwlXkJuEbplDnk7lF6W1PecVDqMdWl9sVDMtBIHUjsbMc7Yq/Lu1Y0r3p/MOuTWYI+Wo9u3WbDKlXnT3huk61YbwfPl41BZlyDcFe42jzfe3O03QF6v3llcgLj9kIQISwIkhvxs3GaQEAxirlKDn0C6LJxHFB1um2w+vxfoHXpphF0SbqYuBF+fiOfMuYvr+4da4vHbc5fiuaaJ0/waw/mHZanwGER0EG+22Ainc4X4pk2utpuV+CAtyBz93ptRsgZrZMq70ILslRw1SCVOI/UZ5TO0rQHvGubOMVbc8NvzihtAYlcPktgU70taMfeaDs+EJev1GxsheQYtMcV4Lu3kH7fKO4dwV7gbjzE/uJv/gBA/gdQFaYRP0D9HqclNN+2cEC4K+ggQAJOKJY16flaokzCMGyWVOOj4z0MwLvQY58M1h+daFibJ/eJlu0WAuPmm6HBXlXK4X6iFjj1I+DDvsZUOje/Pc4AeW26fchhxppgX4mO24Ml8uTJPbGZWMHpZbpWPKLrjpQl8riDFCp6Us/YVPwBvN1Irs6USB5LlFRU0londq8Xo1qdknklXLjr3Uh/yXko7nGPj3pXX9YqXx+3nR+W9OSHcFe7ONQYdo8atbyahumMgCBA3bxsCBIgipLYVKFRYFCBAWTAD7S4IkDohQLv70SfZlKMkOPjyPMTirr8cZqFj5MKDo5fwSM5rACHda4C8QbuK822GCcbMK/FRsrGb25S7L7p17cl7vRAenq9Qg0q3LGkPOib4sYqbkvZqq7IKPlboyfd4AtasJ4GLxfv9EyL0rrxzuzqPlcfvbbYa4z3rr/z5+Q/7HoyZxsvnU+UNCHeFu/y8xpe7lHAK9O8inqNfmHBQp46HY5LjMwGS7M+EbsxvcgLEgOc4AVDa50N5FyQXzchcmAHRT3Tw+WGERzhmFjrkwoNjpnkeMxEes837GFvxUanyhfFKfJD4eem9Gb3ikvF7qNJuDjKTnCfSngShACQtQwxmYSObZvN5v/S84g7TTCm3Vt5UKFicsS1eTsdtU9tu3+Z9HzS+6PbvT+pBiU68GWRMhi0F4S6SeeHu/OEuRy5C+Dte2sKEw47QS06dy/mIL0gsJqCG5e7sUrcDGRfRDMP45RSKCcOt0/7hutk7Xga5Ty1ieBDRQftXSZnIwisF4cG/t5Rg2q9LbSlvadS9tcZWfACuMNbZgC9AeyXe2L/Qguz7nb5QtHVd1Fmh4L0HyM7WzNouX1epUm/a1QH5OjoGyFprkriUoOeuo92ypnMvWdY97xf727zWnrtnx8pbOoO3HNt+8OcKwl0P4W6CceduqadWSYQMIkD4tu44aM3/MIhvPu7F13hO3klT+eB4zMXz7kZ4d5H//tpG9y6Iz7ysDvXsm+4DX95MFk1dkpLwKCZOM+HBuZvnecTzas/zoHm3nZqV8JhpT63xYX0LhimYUc2175NYqD3WJctV70qq/D3NWLMb1bFkk5lCRRu/K6+s+Xw8jilOu2O1D8aUbJcoeJtMc+K3X3PTtm5+x+C29aAYp8qbQ7gr3O2HceVu6Uek9INEy0qJt8Pwlb/p2G2f/5CmeT1xeTbPfqiTH2uVcrIKTlgMjSQjlcI0Pr2W0/6DCA/aryQ80nvSL+ej4JZiZnkebeiXMD2bEOJYOx+EtlYkoVcLEoj2dXrM3uMm8ISo0ku74rEzi5qpcSC2OtPjRgs7fXFR1nLMWpEhlh6O1d5qjNMGubXclqjHj9mGXglOfJv0+9pt67jPYMl64xwvL0G4689DuDvvuNuvp1avZb3CL2B85W5ddDwif3muUikB1SDtvRVzPHh+ExoOCG1HLgiA1Anx4GHLUkglveZUBLl7k4qfXqEWmqZQS3KPWdgw/c7+43nEbdNwS788jzbhsbl4PC/EB9CsxAdJ4Gsco5AQ5Y7VHDeh/RgWPB6ZJ95xUC8BXjiaiXomWNghASpLDATQzMZGGvOj+bbKuzGQTeGKk/cEtKju5jmUK/Kc+O37lzcatCvXuLYcOYS7wt3yduPPXaCdrw0RPGD4xc2jtfdLMxk18qq5PIYM8xBiGr7xO/oE6vDjzh8Vu0Teu6sXci7mSaLh2ti2ufDg+3LhwV0cjmHH82i6TKXrmJ3wmEm+0vxg/xAYxL5Ots/mnSIsVEgtFVX63amC5X/T7dI+2/FcytZxPId0tEe+XT/rOv/+5Bh9WoxtqjvZZoAf05nY1r2IP18q70Eh3BXuzjUqpYvnlsb12x2eQe5NM5l3MBcq7J//GGfPN0/YzPepVAyxcYch70U1yIfvO6jwyL+vWJ4K5aAkROga+3G4bVjBNgEd1vcRHm18GQTjWQJaMJOL7DcI0GDHaH+wpVZYafuYINQkWd7K45VzjF02Y+R5weLkzC3rUkwxOcaA7ef8u9NrGXxwpqcbhLsOwt35gdKPSkmAtCbWMis/JDYqlfwI5t2Y3XHLLfrY2k/dg14/2iUBkgqGsgDpJ2jz78tFRz/hkQulcKws3NKWr9TL9Ujn0/vb70WI/Z5pjtkK6HldvjZ3DLX58qjBrPG25J94nKbqBZqVJidTL6uNx6xLhE5boc2WYylJkM6zFG9sbDdkyKAfZpK8N64tx0Eh3BXuzgf0EiBxm7x31czcj5yz5NiVkk/T7zeJ+1F08TKO5YmoXDTQfoN84vXk+/cWHqU8j+S7i7kd5eWN7YBsWRmlUUyT9VvYuZs/paAPttSbIkt2VmwJDm5lp/ubpkptqTR72sU9rMX8PGaCNpsvfn+LLTqjb+utvOdbst4wEO4Kd+cjmr0ftqz93k8oA+2uAj9GYx/Ve59h0RRR/d2Z0nf34m+yXUG4bcmxYjaXeN5qxMeg4CpvNuPT9yPGbFpYbWq5FDdv3ze3kEs/Gv1bvJsbTzvCbUYIdwc7R+Hu5sWMY/oDdrtt7FdwO8rH7y9GgLL74ebLPBlGgLQ5HqXjD3Ou/Bj93I5B0C9nqXcX/y2jZOZdeRqmIMymRTnTCniQBLhkPks2yvuJl84nSVrq0XLsN7YBne9s1f5Mk536H3fe0bMnhLvCXcHMMGjohc8DM3M/aL9+3MrX9xIevc5rJuKibVCx9Pz6o21wvPa3124+XksJEcwKmzuGLhCMCsLdzYfN8ZZTd5zZP5PN+VzbBMiworec5Nwecnk6YOzG+bC+L/iGX7U/DD5mAu9/TgPd8P7kBib0Nadj17DhUdf+zYtxPnb3rqFQWwUDhRoqDDhTwy0z1m8DhIGg3D4WFjpMG1j/PXHQHgMThsE20KitDn3L4/do2OyFRzmI1Ir1FABIGZtEacfkKhsStEqJTwp8SN/Ymg09GFi2Ne/mRT0G6Cwp27rt1c1Kuc7+sY953I7Pu+lcoTduRQLijy28M2VLQbgr3N1auduPt24bG3nMeEvTBpHfJd4SR3LeRu5F3oZjMG467qZcpvOtGcf5NaTnX34w+esG2oRCmjuS9qThiaa0nIeDVMbjnLsAivyl7+K9tRQif90xUl4SZ5VSQ/N3c3J37MTHE088AQBY9tKfzO2JCLYKPPHEE1i8ePHIvgsQ7go2D4S7gvmKQbir7Cjl9QAwxuDee+/FPvvsg5/+9KdYtGjRXJ/SWGLDhg1YunSp3KMWWGvxxBNPYPfdd4fWo4kuCncHg3C3N4S74wvhbm8Mw92xcz601njWs54FAFi0aJE84D6Qe9SOUbUaCcLd4SD3qB3C3fGG3KN2DMpdSTgVCAQCgUAwUoj4EAgEAoFAMFKMpfiYmprC2Wefjampqbk+lbGF3KPxhDyX/pB7NJ6Q59Ifco82H8Yu4VQgEAgEAsHWjbF0PgQCgUAgEGy9EPEhEAgEAoFgpBDxIRAIBAKBYKQQ8SEQCAQCgWCkGEvxcdlll2H58uXYZpttsP/+++Pb3/72XJ/SnOCcc86BUir57LXXXmH9U089hVNOOQU77rgjFixYgCOOOALr1q2bwzMWCHcdhLvzD8JdB+HuaDB24uMzn/kMzjjjDJx99tm488478eIXvxiHHHIIHnnkkbk+tTnBvvvui//+7/8On1tvvTWsO/3003HjjTdizZo1uOWWW/Dwww/jjW984xye7dMbwt0Uwt35A+FuCuHuCGDHDC9/+cvtKaecEubrura77767vfDCC+fwrOYGZ599tn3xi19cXPf444/biYkJu2bNmrDs+9//vgVgb7vtthGdoYBDuBsh3J1fEO5GCHdHg7FyPjZt2oQ77rgDq1atCsu01li1ahVuu+22OTyzucN9992H3XffHc9+9rNxzDHH4MEHHwQA3HHHHZienk7u1V577YU99tjjaXuv5hLC3SaEu/MDwt0mhLtbHmMlPh599FHUdY0lS5Yky5csWYK1a9fO0VnNHfbff39cc801uOmmm3DFFVfg/vvvx+/+7u/iiSeewNq1azE5OYntt98+2efpeq/mGsLdFMLd+QPhbgrh7mgwdm+1FUQceuihYfpFL3oR9t9/fyxbtgzXX389tt122zk8M4GgN4S7gvkK4e5oMFbOx0477YSqqhqZw+vWrcOuu+46R2c1Pth+++3xvOc9Dz/60Y+w6667YtOmTXj88ceTbeRezQ2Eu70h3B1fCHd7Q7i7ZTBW4mNychIrV67EzTffHJYZY3DzzTfjgAMOmMMzGw/86le/wv/7f/8Pu+22G1auXImJiYnkXt1777148MEH5V7NAYS7vSHcHV8Id3tDuLuFMNcZrzk+/elP26mpKXvNNdfYe+65x5544ol2++23t2vXrp3rUxs5/uzP/sx+/etft/fff7/9xje+YVetWmV32mkn+8gjj1hrrf2TP/kTu8cee9h/+7d/s9/5znfsAQccYA844IA5PuunL4S7EcLd+QXhboRwdzQYO/FhrbUf+chH7B577GEnJyfty1/+cvutb31rrk9pTvDmN7/Z7rbbbnZyctI+61nPsm9+85vtj370o7D+N7/5jT355JPtM5/5TPuMZzzD/uEf/qH97//+7zk8Y4Fw10G4O/8g3HUQ7o4Gylpr59p9EQgEAoFA8PTBWOV8CAQCgUAg2Poh4kMgEAgEAsFIIeJDIBAIBALBSCHiQyAQCAQCwUgh4kMgEAgEAsFIIeJDIBAIBALBSCHiQyAQCAQCwUgh4kMgEAgEAsFIIeJDIBAIBALBSCHiQyAQCAQCwUgh4kMgEAgEAsFIIeJDIBAIBALBSPH/A+H3N4SgxBr8AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mesh information for Mesh potential grad x\n", + "Total mapped mass: 7\n", + "Max cell value: 169.19632685316168\n", + "Min cell value: -169.18919774521777\n", + "Mean cell value: 7.173556951775168e-06\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "14:03:19 - utils.forces_mesh - Got phi_grad with: (3, 100, 100, 100), 171.6251363560513\n" + ] + } + ], + "source": [ + "### Direct N body force computation\n", + "epsilon = utils.mean_interparticle_distance(particles)\n", + "logger.info(f\"Mean interparticle distance: {epsilon}\")\n", + "f_nsquare = utils.n_body_forces(particles, G, epsilon)\n", + "f_analytical = utils.analytical_forces(particles)\n", + "\n", + "mapping = utils.particle_to_cells_nn\n", + "mesh_size = 100\n", + "f_mesh = utils.mesh_forces_v2(particles, G, mesh_size, mapping)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## Compare the mesh computation with the \"straightforward\" computations\n", + "r = np.linalg.norm(particles[:,:3], axis=1)\n", + "\n", + "plt.figure()\n", + "plt.title('Radial force behaviour')\n", + "plt.xscale('log')\n", + "plt.yscale('log')\n", + "plt.xlabel('$r$')\n", + "plt.ylabel('$F_r(r)$')\n", + "\n", + "plt.plot(r, np.linalg.norm(f_analytical, axis=1), 'o', label=\"Analytical\")\n", + "plt.plot(r, np.linalg.norm(f_nsquare, axis=1), 'o', label=\"N^2\")\n", + "plt.plot(r, np.linalg.norm(f_mesh, axis=1), 'o', label=f\"Mesh ({mesh_size})\")\n", + "\n", + "plt.legend()\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "13:11:29 - __main__ - Considering 50010 particles\n", + "13:11:29 - __main__ - Total mass: 4622219.258999999\n" + ] + } + ], + "source": [ + "# load the particles in the format [x, y, z, vx, vy, vz, mass]\n", + "particles = points[:, [2, 3, 4, 5, 6, 7, 1]]\n", + "\n", + "logger.info(f\"Considering {particles.shape[0]} particles\")\n", + "logger.info(f\"Total mass: {np.sum(particles[:,6])}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "13:11:29 - utils.integrate - Reshaped (50010, 7) to y0 with (300060,) and masses with (50010,)\n", + "13:11:29 - utils.integrate - y with shape (300060,)\n", + "13:11:29 - utils.integrate - Unstacked y into x with shape (50010, 3) and v with shape (50010, 3)\n", + "13:11:29 - utils.forces_basic - Computing forces for 50010 particles using n^2 algorithm (using softening=np.float64(0.021985731180436525))\n", + "13:11:29 - utils.forces_basic - Particle 0 done\n", + "13:11:50 - utils.forces_basic - Particle 5000 done\n", + "13:12:11 - utils.forces_basic - Particle 10000 done\n", + "13:12:34 - utils.forces_basic - Particle 15000 done\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)\n", + "Cell \u001b[0;32mIn[12], line 10\u001b[0m\n", + "\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mintegrate\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mspi\u001b[39;00m\n", + "\u001b[1;32m 9\u001b[0m \u001b[38;5;66;03m# integrate the system\u001b[39;00m\n", + "\u001b[0;32m---> 10\u001b[0m sol \u001b[38;5;241m=\u001b[39m \u001b[43mspi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43modeint\u001b[49m\u001b[43m(\u001b[49m\u001b[43my_prime\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marange\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_steps\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdt\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43matol\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1e2\u001b[39;49m\u001b[43m)\u001b[49m\n", + "\n", + "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/scipy/integrate/_odepack_py.py:247\u001b[0m, in \u001b[0;36modeint\u001b[0;34m(func, y0, t, args, Dfun, col_deriv, full_output, ml, mu, rtol, atol, tcrit, h0, hmax, hmin, ixpr, mxstep, mxhnil, mxordn, mxords, printmessg, tfirst)\u001b[0m\n", + "\u001b[1;32m 245\u001b[0m t \u001b[38;5;241m=\u001b[39m copy(t)\n", + "\u001b[1;32m 246\u001b[0m y0 \u001b[38;5;241m=\u001b[39m copy(y0)\n", + "\u001b[0;32m--> 247\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43m_odepack\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43modeint\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mDfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcol_deriv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mml\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmu\u001b[49m\u001b[43m,\u001b[49m\n", + "\u001b[1;32m 248\u001b[0m \u001b[43m 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\u001b[49m\u001b[38;5;28;43mint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mbool\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtfirst\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[1;32m 251\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m output[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n", + "\u001b[1;32m 252\u001b[0m warning_msg \u001b[38;5;241m=\u001b[39m (\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m_msgs[output[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m Run with full_output = 1 to \u001b[39m\u001b[38;5;124m\"\u001b[39m\n", + "\u001b[1;32m 253\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mget quantitative information.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\n", + "File \u001b[0;32m~/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/integrate.py:47\u001b[0m, in \u001b[0;36mode_setup..f\u001b[0;34m(y, t)\u001b[0m\n", + "\u001b[1;32m 45\u001b[0m x_with_m[:, :\u001b[38;5;241m3\u001b[39m] \u001b[38;5;241m=\u001b[39m x\n", + "\u001b[1;32m 46\u001b[0m x_with_m[:, \u001b[38;5;241m3\u001b[39m] \u001b[38;5;241m=\u001b[39m masses\n", + "\u001b[0;32m---> 47\u001b[0m forces \u001b[38;5;241m=\u001b[39m \u001b[43mforce_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx_with_m\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[1;32m 49\u001b[0m \u001b[38;5;66;03m# compute the accelerations\u001b[39;00m\n", + "\u001b[1;32m 50\u001b[0m a \u001b[38;5;241m=\u001b[39m forces \u001b[38;5;241m/\u001b[39m masses[:, \u001b[38;5;28;01mNone\u001b[39;00m]\n", + "\n", + "Cell \u001b[0;32mIn[12], line 4\u001b[0m, in \u001b[0;36m\u001b[0;34m(x)\u001b[0m\n", + "\u001b[1;32m 2\u001b[0m dt \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.1\u001b[39m\n", + "\u001b[1;32m 3\u001b[0m n_steps \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m10\u001b[39m\n", + "\u001b[0;32m----> 4\u001b[0m force_function \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m x: \u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mn_body_forces\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepsilon\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[1;32m 5\u001b[0m y0, y_prime \u001b[38;5;241m=\u001b[39m utils\u001b[38;5;241m.\u001b[39mode_setup(particles, force_function)\n", + "\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mintegrate\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mspi\u001b[39;00m\n", + "\n", + "File \u001b[0;32m~/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/forces_basic.py:41\u001b[0m, in \u001b[0;36mn_body_forces\u001b[0;34m(particles, G, softening)\u001b[0m\n", + "\u001b[1;32m 38\u001b[0m r_adjusted[i] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n", + "\u001b[1;32m 39\u001b[0m num[i] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n", + "\u001b[0;32m---> 41\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msum\u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnum\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mT\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mr_adjusted\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m1.5\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mT\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;241m*\u001b[39m m_current\n", + "\u001b[1;32m 42\u001b[0m forces[i] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m-\u001b[39mf\n", + "\u001b[1;32m 44\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m i \u001b[38;5;241m%\u001b[39m \u001b[38;5;241m5000\u001b[39m \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n", + "\n", + "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.12/site-packages/numpy/_core/fromnumeric.py:2344\u001b[0m, in \u001b[0;36m_sum_dispatcher\u001b[0;34m(a, axis, dtype, out, keepdims, initial, where)\u001b[0m\n", + "\u001b[1;32m 2338\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPassing `min` or `max` keyword argument when \u001b[39m\u001b[38;5;124m\"\u001b[39m\n", + "\u001b[1;32m 2339\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`a_min` and `a_max` are provided is forbidden.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[1;32m 2341\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _wrapfunc(a, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mclip\u001b[39m\u001b[38;5;124m'\u001b[39m, a_min, a_max, out\u001b[38;5;241m=\u001b[39mout, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n", + "\u001b[0;32m-> 2344\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_sum_dispatcher\u001b[39m(a, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, out\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, keepdims\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n", + "\u001b[1;32m 2345\u001b[0m initial\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, where\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n", + "\u001b[1;32m 2346\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (a, out)\n", + "\u001b[1;32m 2349\u001b[0m \u001b[38;5;129m@array_function_dispatch\u001b[39m(_sum_dispatcher)\n", + "\u001b[1;32m 2350\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msum\u001b[39m(a, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, out\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, keepdims\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39m_NoValue,\n", + "\u001b[1;32m 2351\u001b[0m initial\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39m_NoValue, where\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39m_NoValue):\n", + "\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], + "source": [ + "# we can now integrate this system for a few steps\n", + "dt = 0.1\n", + "n_steps = 10\n", + "force_function = lambda x: utils.n_body_forces(x, G, epsilon)\n", + "y0, y_prime = utils.ode_setup(particles, force_function)\n", + "\n", + "import scipy.integrate as spi\n", + "\n", + "# integrate the system\n", + "sol = spi.odeint(y_prime, y0, np.arange(0, n_steps*dt, dt), atol=1e2)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sol[4]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# map the particles to a mesh\n", + "mapping_function = utils.particle_to_cells_nn\n", + "GRID_SIZE = 50\n", + "mesh, grid = utils.to_mesh(particles, GRID_SIZE, mapping_function)\n", + "\n", + "utils.show_mesh_information(mesh, f\"Initial mesh {GRID_SIZE=}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "projects-X-9bmgL6", + "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": "3.12.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/nbody/utils/__init__.py b/nbody/utils/__init__.py index bb2d1cf..62ec024 100644 --- a/nbody/utils/__init__.py +++ b/nbody/utils/__init__.py @@ -1,7 +1,14 @@ -# Import all functions in all the files in the current directory +## Import all functions in all the files in the current directory +# Basic helpers for interacting with the data from .load import * from .mesh import * from .model import * from .particles import * -from .forces import * -from .integrate import * \ No newline at end of file + +# Helpers for computing the forces +from .forces_basic import * +from .forces_tree import * +from .forces_mesh import * + +# Helpers for solving the IVP and having time evolution +from .integrate import * diff --git a/nbody/utils/forces.py b/nbody/utils/forces_basic.py similarity index 96% rename from nbody/utils/forces.py rename to nbody/utils/forces_basic.py index 60678df..06a9f71 100644 --- a/nbody/utils/forces.py +++ b/nbody/utils/forces_basic.py @@ -16,7 +16,7 @@ def n_body_forces(particles: np.ndarray, G: float, softening: float = 0): n = particles.shape[0] forces = np.zeros((n, 3)) - logger.debug(f"Computing forces for {n} particles using n^2 algorithm") + logger.debug(f"Computing forces for {n} particles using n^2 algorithm (using {softening=})") for i in range(n): # the current particle is at x_current @@ -41,7 +41,7 @@ def n_body_forces(particles: np.ndarray, G: float, softening: float = 0): f = np.sum((num.T / r_adjusted**1.5).T, axis=0) * m_current forces[i] = -f - if i % 1000 == 0: + if i % 5000 == 0: logger.debug(f"Particle {i} done") return forces @@ -71,7 +71,7 @@ def analytical_forces(particles: np.ndarray): f = - m_current * m_enclosed / r_current**2 forces[i] = f - if i % 1000 == 0: + if i % 5000 == 0: logger.debug(f"Particle {i} done") return forces diff --git a/nbody/utils/forces_mesh.py b/nbody/utils/forces_mesh.py new file mode 100644 index 0000000..785e4e6 --- /dev/null +++ b/nbody/utils/forces_mesh.py @@ -0,0 +1,185 @@ +## Implementation of a mesh based force solver +import numpy as np +import matplotlib.pyplot as plt +from scipy import fft + +import logging +logger = logging.getLogger(__name__) + +#### Version 1 - keeping the derivative of phi + +def mesh_forces(particles: np.ndarray, G: float, n_grid: int, mapping: callable) -> np.ndarray: + """ + Computes the gravitational forces between a set of particles using a mesh. + Assumes that the particles array has the following columns: x, y, z, m. + """ + if particles.shape[1] != 4: + raise ValueError("Particles array must have 4 columns: x, y, z, m") + + mesh, axis = to_mesh(particles, n_grid, mapping) + # show_mesh_information(mesh, "Initial mesh") + + grad_phi = mesh_poisson(mesh, G) + # show_mesh_information(mesh, "Mesh potential") + + # compute the particle forces from the mesh potential + forces = np.zeros_like(particles[:, :3]) + for i, p in enumerate(particles): + ijk = np.digitize(p, axis) - 1 + forces[i] = -grad_phi[ijk[0], ijk[1], ijk[2]] * p[3] + + return forces + + +def mesh_poisson(mesh: np.ndarray, G: float) -> np.ndarray: + """ + 'Solves' the poisson equation for the mesh using the FFT. + Returns the gradient of the potential since this is required for the force computation. + """ + rho_hat = fft.fftn(mesh) + # the laplacian in fourier space takes the form of a multiplication + k = np.fft.fftfreq(mesh.shape[0]) + # TODO: probably need to take the actual mesh bounds into account + kx, ky, kz = np.meshgrid(k, k, k) + k_vec = np.array([kx, ky, kz]) + logger.debug(f"Got k_square with: {k_vec.shape}, {np.max(k_vec)} {np.min(k_vec)}") + + grad_phi_hat = 4 * np.pi * G * rho_hat / (1j * k_vec * 2 * np.pi) + + # the inverse fourier transform gives the potential (or its gradient) + grad_phi = np.real(fft.ifftn(grad_phi_hat)) + return grad_phi + + +#### Version 2 - only storing the scalar potential +def mesh_forces_v2(particles: np.ndarray, G: float, n_grid: int, mapping: callable) -> np.ndarray: + if particles.shape[1] != 4: + raise ValueError("Particles array must have 4 columns: x, y, z, m") + + logger.debug(f"Computing forces for {particles.shape[0]} particles using mesh (using mapping={mapping.__name__})") + + mesh, axis = to_mesh(particles, n_grid, mapping) + show_mesh_information(mesh, "Mesh") + + spacing = axis[1] - axis[0] + logger.debug(f"Using mesh spacing: {spacing}") + phi = mesh_poisson_v2(mesh, G) + logger.debug(f"Got phi with: {phi.shape}, {np.max(phi)}") + phi_grad = np.stack(np.gradient(phi, spacing), axis=0) + show_mesh_information(phi, "Mesh potential") + show_mesh_information(phi_grad[0], "Mesh potential grad x") + logger.debug(f"Got phi_grad with: {phi_grad.shape}, {np.max(phi_grad)}") + forces = np.zeros_like(particles[:, :3]) + for i, p in enumerate(particles): + ijk = np.digitize(p, axis) - 1 + # this gives 4 entries since p[3] the mass is digitized as well -> this is meaningless and we discard it + # logger.debug(f"Particle {p} maps to cell {ijk}") + forces[i] = - p[3] * phi_grad[..., ijk[0], ijk[1], ijk[2]] + + return forces + + +def mesh_poisson_v2(mesh: np.ndarray, G: float) -> np.ndarray: + rho_hat = fft.fftn(mesh) + k = np.fft.fftfreq(mesh.shape[0]) + kx, ky, kz = np.meshgrid(k, k, k) + k_sr = kx**2 + ky**2 + kz**2 + logger.debug(f"Got k_square with: {k_sr.shape}, {np.max(k_sr)} {np.min(k_sr)}") + logger.debug(f"Count of zeros: {np.sum(k_sr == 0)}") + k_sr[k_sr == 0] = 1e-10 # Add a small epsilon to avoid division by zero + phi_hat = - G * rho_hat / k_sr + # 4pi cancels, - comes from i squared + phi = np.real(fft.ifftn(phi_hat)) + return phi + + +## Helper functions for star mapping +def to_mesh(particles: np.ndarray, n_grid: int, mapping: callable) -> tuple[np.ndarray, np.ndarray]: + """ + Maps a list of particles to a of mesh of size n_grid x n_grid x n_grid. + Assumes that the particles array has the following columns: x, y, z, ..., m. + Uses the mass of the particles and a smoothing function to detemine the contribution to each cell. + """ + # axis provide an easy way to map the particles to the mesh + max_pos = np.max(particles[:, :3]) + axis = np.linspace(-max_pos, max_pos, n_grid) + mesh_grid = np.meshgrid(axis, axis, axis) + mesh = np.zeros_like(mesh_grid[0]) + + for p in particles: + m = p[-1] + if logger.level <= logging.DEBUG and m <= 0: + logger.warning(f"Particle with negative mass: {p}") + # spread the star onto cells through the shape function, taking into account the mass + ijks, weights = mapping(p, axis) + for ijk, weight in zip(ijks, weights): + mesh[ijk[0], ijk[1], ijk[2]] += weight * m + + return mesh, axis + + +def particle_to_cells_nn(particle, axis): + # find the single cell that contains the particle + ijk = np.digitize(particle, axis) - 1 + # the weight is obviously 1 + return [ijk], [1] + + +def particle_to_cells_cic(particle, axis, width): + # create a virtual cell around the particle + cell_bounds = [ + particle + np.array([1, 0, 0]) * width, + particle + np.array([-1, 0, 0]) * width, + particle + np.array([1, 1, 0]) * width, + particle + np.array([-1, -1, 0]) * width, + particle + np.array([1, 1, 1]) * width, + particle + np.array([-1, -1, 1]) * width, + particle + np.array([1, 1, -1]) * width, + particle + np.array([-1, -1, -1]) * width, + ] + # find all the cells that intersect with the virtual cell + ijks = [] + weights = [] + for b in cell_bounds: + w = np.linalg.norm(particle - b) + ijk = np.digitize(b, axis) - 1 + # print(f"b: {b}, ijk: {ijk}") + ijks.append(ijk) + weights.append(w) + # ensure that the weights sum to 1 + weights = np.array(weights) + weights /= np.sum(weights) + return ijks, weights + + + +## Helper functions for mesh plotting +def show_mesh_information(mesh: np.ndarray, name: str): + print(f"Mesh information for {name}") + print(f"Total mapped mass: {np.sum(mesh):.0f}") + print(f"Max cell value: {np.max(mesh)}") + print(f"Min cell value: {np.min(mesh)}") + print(f"Mean cell value: {np.mean(mesh)}") + plot_3d(mesh, name) + plot_2d(mesh, name) + + +def plot_3d(mesh: np.ndarray, name: str): + fig = plt.figure() + fig.suptitle(name) + ax = fig.add_subplot(111, projection='3d') + ax.scatter(*np.where(mesh), c=mesh[np.where(mesh)], cmap='viridis') + plt.show() + + +def plot_2d(mesh: np.ndarray, name: str): + fig = plt.figure() + fig.suptitle(name) + axs = fig.subplots(1, 3) + axs[0].imshow(np.sum(mesh, axis=0)) + axs[0].set_title("Flattened in x") + axs[1].imshow(np.sum(mesh, axis=1)) + axs[1].set_title("Flattened in y") + axs[2].imshow(np.sum(mesh, axis=2)) + axs[2].set_title("Flattened in z") + plt.show() \ No newline at end of file diff --git a/nbody/utils/forces_tree.py b/nbody/utils/forces_tree.py new file mode 100644 index 0000000..e69de29 diff --git a/nbody/utils/logging_config.py b/nbody/utils/logging_config.py new file mode 100644 index 0000000..d3c2fc0 --- /dev/null +++ b/nbody/utils/logging_config.py @@ -0,0 +1,15 @@ +import logging + +logging.basicConfig( + ## set logging level + # level=logging.INFO, + level=logging.DEBUG, + format='%(asctime)s - %(name)s - %(message)s', + datefmt='%H:%M:%S' +) + + +# silence some debug messages +logging.getLogger('matplotlib.font_manager').setLevel(logging.WARNING) +logging.getLogger('matplotlib.ticker').setLevel(logging.WARNING) +logging.getLogger('matplotlib.pyplot').setLevel(logging.WARNING)