{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Plotting PXRD patterns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook contains a quick example of PXRD plotting from a cif file, using the matador API directly. The `pxrd_calculator` script bundled with matador may be a more useful entry point." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from matador.scrapers import cif2dict\n", "from matador.crystal import Crystal" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Ag6Bi8I32: test\n", "===============\n", "64 atoms. Fd-3m\n", "(a, b, c) = 12.2227 Å, 12.2227 Å, 12.2227 Å\n", "(α, β, γ) = 90.0000° 90.0000° 90.0000°\n", "\n" ] } ], "source": [ "crystal = Crystal(cif2dict(\"test.cif\")[0])\n", "print(crystal)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "System has partial occupancy, not refining with spglib.\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot with default settings\n", "crystal.pxrd.plot()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot with full function that can control all settings and plot multiple phases\n", "from matador.plotting import plot_pxrd\n", "plot_pxrd(\n", " [crystal.pxrd, crystal.pxrd, crystal.pxrd],\n", " rug=True,\n", " text_offset=0.3,\n", ")" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 2θ \n", "7.227\t 0 1 0\n", "7.227\t 0 0 1\n", "7.227\t 0 0 -1\n", "7.227\t -1 0 0\n", "7.227\t 0 -1 0\n", "7.227\t 1 0 0\n", "10.227\t 1 0 -1\n", "10.227\t -1 0 1\n", "10.227\t -1 1 0\n", "10.227\t 0 -1 -1\n", "10.227\t -1 -1 0\n", "10.227\t 0 -1 1\n", "10.227\t 0 1 -1\n", "10.227\t 1 1 0\n", "10.227\t 0 1 1\n", "10.227\t 1 0 1\n", "10.227\t 1 -1 0\n", "10.227\t -1 0 -1\n", "12.533\t 1 -1 -1\n", "12.533\t -1 -1 1\n", "12.533\t 1 -1 1\n", "12.533\t -1 1 -1\n", "12.533\t -1 1 1\n", "12.533\t 1 1 -1\n", "12.533\t -1 -1 -1\n", "12.533\t 1 1 1\n", "14.482\t 0 0 -2\n", "14.482\t 0 -2 0\n", "14.482\t -2 0 0\n", "14.482\t 0 2 0\n", "14.482\t 2 0 0\n", "14.482\t 0 0 2\n", "16.202\t -2 -1 0\n", "16.202\t -2 0 1\n", "16.202\t -2 0 -1\n", "16.202\t 2 0 -1\n", "16.202\t 1 0 2\n", "16.202\t 1 -2 0\n", "16.202\t 2 0 1\n", "16.202\t 0 2 1\n", "16.202\t -1 2 0\n", "16.202\t 1 0 -2\n", "16.202\t 2 1 0\n", "16.202\t 0 2 -1\n", "16.202\t 0 1 2\n", "16.202\t 0 -2 1\n", "16.202\t 2 -1 0\n", "16.202\t -1 0 2\n", "16.202\t -1 0 -2\n", "16.202\t 1 2 0\n", "16.202\t 0 -2 -1\n", "16.202\t -1 -2 0\n", "16.202\t 0 -1 2\n", "16.202\t 0 1 -2\n", "16.202\t -2 1 0\n", "16.202\t 0 -1 -2\n", "17.761\t -1 1 -2\n", "17.761\t 1 -1 -2\n", "17.761\t 1 1 -2\n", "17.761\t -1 -1 -2\n", "17.761\t 1 1 2\n", "17.761\t 1 -1 2\n", "17.761\t -1 1 2\n", "17.761\t -1 -1 2\n", "17.761\t -2 1 1\n", "17.761\t -1 2 -1\n", "17.761\t -1 -2 1\n", "17.761\t 2 -1 -1\n", "17.761\t -1 -2 -1\n", "17.761\t -1 2 1\n", "17.761\t 2 1 1\n", "17.761\t -2 1 -1\n", "17.761\t -2 -1 1\n", "17.761\t -2 -1 -1\n", "17.761\t 2 1 -1\n", "17.761\t 1 2 -1\n", "17.761\t 1 -2 -1\n", "17.761\t 1 -2 1\n", "17.761\t 1 2 1\n", "17.761\t 2 -1 1\n", "20.536\t 2 -2 0\n", "20.536\t 2 0 -2\n", "20.536\t 2 0 2\n", "20.536\t 2 2 0\n", "20.536\t 0 -2 -2\n", "20.536\t 0 2 -2\n", "20.536\t -2 -2 0\n", "20.536\t 0 2 2\n", "20.536\t -2 0 -2\n", "20.536\t -2 0 2\n", "20.536\t 0 -2 2\n", "20.536\t -2 2 0\n", "21.797\t -1 2 2\n", "21.797\t 0 3 0\n", "21.797\t -2 1 2\n", "21.797\t -2 1 -2\n", "21.797\t 1 -2 -2\n", "21.797\t 2 -1 2\n", "21.797\t -2 -1 -2\n", "21.797\t -2 2 1\n", "21.797\t -1 -2 -2\n", "21.797\t 2 -2 1\n", "21.797\t -2 -1 2\n", "21.797\t 1 -2 2\n", "21.797\t -2 2 -1\n", "21.797\t 2 -1 -2\n", "21.797\t 2 2 1\n", "21.797\t 0 -3 0\n", "21.797\t 0 0 3\n", "21.797\t 2 -2 -1\n", "21.797\t 2 1 2\n", "21.797\t 1 2 2\n", "21.797\t 1 2 -2\n", "21.797\t 3 0 0\n", "21.797\t 0 0 -3\n", "21.797\t -2 -2 -1\n", "21.797\t -1 2 -2\n", "21.797\t -3 0 0\n", "21.797\t 2 1 -2\n", "21.797\t -2 -2 1\n", "21.797\t 2 2 -1\n", "21.797\t -1 -2 2\n", "22.991\t -3 -1 0\n", "22.991\t 3 -1 0\n", "22.991\t -3 0 1\n", "22.991\t 0 1 -3\n", "22.991\t -3 1 0\n", "22.991\t -3 0 -1\n", "22.991\t -1 -3 0\n", "22.991\t 1 -3 0\n", "22.991\t 0 1 3\n", "22.991\t 1 0 3\n", "22.991\t 0 3 1\n", "22.991\t 0 -1 3\n", "22.991\t 0 -3 1\n", "22.991\t 3 0 -1\n", "22.991\t -1 0 -3\n", "22.991\t 0 3 -1\n", "22.991\t 3 1 0\n", "22.991\t 0 -1 -3\n", "22.991\t 3 0 1\n", "22.991\t 1 0 -3\n", "22.991\t 0 -3 -1\n", "22.991\t 1 3 0\n", "22.991\t -1 3 0\n", "22.991\t -1 0 3\n", "24.130\t 3 -1 1\n", "24.130\t -1 3 1\n", "24.130\t 1 -3 1\n", "24.130\t 1 -3 -1\n", "24.130\t -3 -1 1\n", "24.130\t -3 1 -1\n", "24.130\t 3 -1 -1\n", "24.130\t -1 3 -1\n", "24.130\t -3 1 1\n", "24.130\t 1 3 -1\n", "24.130\t -1 -3 -1\n", "24.130\t 3 1 -1\n", "24.130\t 3 1 1\n", "24.130\t 1 3 1\n", "24.130\t -1 -3 1\n", "24.130\t -3 -1 -1\n", "24.130\t 1 1 -3\n", "24.130\t -1 -1 3\n", "24.130\t -1 1 -3\n", "24.130\t 1 -1 3\n", "24.130\t 1 -1 -3\n", 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4\n", "33.573\t -1 2 4\n", "33.573\t -1 2 -4\n", "33.573\t -2 1 4\n", "33.573\t 1 -4 2\n", "33.573\t -2 -4 -1\n", "33.573\t -4 1 -2\n", "33.573\t 1 -2 -4\n", "33.573\t -4 2 1\n", "33.573\t 2 -4 1\n", "33.573\t 1 -4 -2\n", "33.573\t 4 -1 -2\n", "33.573\t 2 -1 4\n", "33.573\t 4 2 1\n", "33.573\t -4 -1 2\n", "33.573\t -1 4 2\n", "33.573\t 2 1 4\n", "33.573\t -2 -1 4\n", "33.573\t -1 4 -2\n", "33.573\t 1 4 -2\n", "33.573\t -2 -1 -4\n", "33.573\t 4 -2 -1\n", "33.573\t 4 -2 1\n", "33.573\t -4 -1 -2\n", "33.573\t 2 1 -4\n", "33.573\t 2 4 -1\n", "33.573\t 4 -1 2\n", "33.573\t 2 4 1\n", "33.573\t 4 1 2\n", "33.573\t -4 2 -1\n", "33.573\t -2 -4 1\n", "33.573\t 4 1 -2\n", "33.573\t -4 -2 -1\n", "33.573\t -4 -2 1\n", "33.573\t 4 2 -1\n", "34.387\t -2 -3 3\n", "34.387\t 3 2 3\n", "34.387\t 3 -2 3\n", "34.387\t -2 3 3\n", "34.387\t 3 -2 -3\n", "34.387\t 3 -3 2\n", "34.387\t 3 3 -2\n", "34.387\t 3 3 2\n", "34.387\t -2 3 -3\n", "34.387\t -2 -3 -3\n", "34.387\t -3 3 2\n", "34.387\t 3 2 -3\n", "34.387\t 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2\n", "39.679\t -2 5 0\n", "39.679\t 4 3 -2\n", "39.679\t -4 -3 -2\n", "39.679\t -4 -3 2\n", "39.679\t -2 4 3\n", "39.679\t 3 -4 -2\n", "39.679\t -2 4 -3\n", "40.386\t 2 5 -1\n", "40.386\t 2 -1 -5\n", "40.386\t 2 -1 5\n", "40.386\t -1 5 -2\n", "40.386\t 2 1 5\n", "40.386\t 2 1 -5\n", "40.386\t -1 2 -5\n", "40.386\t 2 5 1\n", "40.386\t -1 -2 5\n", "40.386\t -2 1 5\n", "40.386\t -2 -1 5\n", "40.386\t -2 1 -5\n", "40.386\t 2 -5 1\n", "40.386\t -1 -5 -2\n", "40.386\t 2 -5 -1\n", "40.386\t 5 -2 -1\n", "40.386\t -5 2 -1\n", "40.386\t 5 1 -2\n", "40.386\t -5 2 1\n", "40.386\t 5 -1 2\n", "40.386\t 1 -2 5\n", "40.386\t -5 -1 2\n", "40.386\t -1 -5 2\n", "40.386\t 5 1 2\n", "40.386\t 1 -2 -5\n", "40.386\t -2 -1 -5\n", "40.386\t -5 -2 1\n", "40.386\t 5 -1 -2\n", "40.386\t 5 2 1\n", "40.386\t -2 -5 -1\n", "40.386\t -5 1 2\n", "40.386\t 5 -2 1\n", "40.386\t 1 -5 -2\n", "40.386\t -2 -5 1\n", "40.386\t 1 -5 2\n", "40.386\t -1 -2 -5\n", "40.386\t -5 -1 -2\n", "40.386\t 1 5 2\n", "40.386\t -5 1 -2\n", "40.386\t 1 2 -5\n", "40.386\t -5 -2 -1\n", "40.386\t 1 2 5\n", "40.386\t -1 5 2\n", "40.386\t -1 2 5\n", "40.386\t -2 5 -1\n", "40.386\t 1 5 -2\n", "40.386\t 5 2 -1\n", "40.386\t -2 5 1\n", "41.772\t 4 -4 0\n", "41.772\t 0 -4 4\n", "41.772\t 0 4 -4\n", "41.772\t 4 0 -4\n", "41.772\t 4 0 4\n", "41.772\t 4 4 0\n", "41.772\t 0 4 4\n", "41.772\t -4 0 -4\n", "41.772\t -4 -4 0\n", "41.772\t 0 -4 -4\n", "41.772\t -4 0 4\n", "41.772\t -4 4 0\n", "42.450\t 2 2 5\n", "42.450\t 2 -2 -5\n", "42.450\t -5 -2 -2\n", "42.450\t -1 4 -4\n", "42.450\t -2 -5 -2\n", "42.450\t 4 -4 1\n", "42.450\t 4 -4 -1\n", "42.450\t 4 1 4\n", "42.450\t 4 1 -4\n", "42.450\t -4 -4 -1\n", "42.450\t 1 -4 4\n", "42.450\t -2 5 -2\n", "42.450\t -1 -4 4\n", "42.450\t -4 -4 1\n", "42.450\t 1 4 4\n", "42.450\t 5 2 -2\n", "42.450\t -5 2 2\n", "42.450\t -2 -5 2\n", "42.450\t -2 -2 -5\n", "42.450\t 5 -2 2\n", "42.450\t -5 -2 2\n", "42.450\t 1 -4 -4\n", "42.450\t 1 4 -4\n", "42.450\t 2 2 -5\n", "42.450\t -2 2 -5\n", "42.450\t -4 1 -4\n", "42.450\t -4 -1 4\n", "42.450\t -5 2 -2\n", "42.450\t -1 4 4\n", "42.450\t 2 -5 2\n", "42.450\t 2 -5 -2\n", "42.450\t -2 5 2\n", "42.450\t -1 -4 -4\n", "42.450\t -4 4 -1\n", "42.450\t -4 4 1\n", "42.450\t -2 -2 5\n", "42.450\t 5 -2 -2\n", "42.450\t 4 4 -1\n", "42.450\t 2 5 2\n", "42.450\t 4 -1 4\n", "42.450\t -2 2 5\n", "42.450\t -4 -1 -4\n", "42.450\t 4 -1 -4\n", "42.450\t -4 1 4\n", "42.450\t 2 5 -2\n", "42.450\t 4 4 1\n", "42.450\t 5 2 2\n", "42.450\t 2 -2 5\n", "43.120\t 3 4 3\n", "43.120\t 4 3 3\n", "43.120\t 5 0 -3\n", "43.120\t 0 5 -3\n", "43.120\t -3 0 5\n", "43.120\t 0 -3 -5\n", "43.120\t -3 5 0\n", "43.120\t 5 3 0\n", "43.120\t 4 -3 -3\n", "43.120\t -5 3 0\n", "43.120\t -5 0 3\n", "43.120\t -5 0 -3\n", "43.120\t 3 0 -5\n", "43.120\t 3 -3 -4\n", "43.120\t 3 -4 -3\n", "43.120\t 4 3 -3\n", "43.120\t 3 -4 3\n", "43.120\t 3 -3 4\n", "43.120\t 3 0 5\n", "43.120\t -4 -3 3\n", "43.120\t -4 -3 -3\n", "43.120\t -3 3 -4\n", "43.120\t 3 -5 0\n", "43.120\t -3 -5 0\n", "43.120\t 5 -3 0\n", "43.120\t 0 5 3\n", "43.120\t -4 3 -3\n", "43.120\t -3 0 -5\n", "43.120\t 5 0 3\n", "43.120\t 0 -5 -3\n", "43.120\t -3 -4 3\n", "43.120\t -3 -3 -4\n", "43.120\t 0 -5 3\n", "43.120\t 3 3 -4\n", "43.120\t 0 -3 5\n", "43.120\t 0 3 5\n", "43.120\t 0 3 -5\n", "43.120\t -4 3 3\n", "43.120\t -3 -3 4\n", "43.120\t -3 3 4\n", "43.120\t 3 5 0\n", "43.120\t -3 4 -3\n", "43.120\t 3 3 4\n", "43.120\t -3 -4 -3\n", "43.120\t -3 4 3\n", "43.120\t 3 4 -3\n", "43.120\t -5 -3 0\n", "43.120\t 4 -3 3\n", "43.782\t -5 1 3\n", "43.782\t -3 1 5\n", "43.782\t 5 -1 -3\n", "43.782\t -1 5 3\n", "43.782\t -3 -1 -5\n", "43.782\t -5 3 1\n", "43.782\t 3 1 5\n", "43.782\t 1 -3 5\n", "43.782\t 5 -3 -1\n", "43.782\t -5 -3 1\n", "43.782\t 3 -1 5\n", "43.782\t -5 -1 -3\n", "43.782\t 1 -3 -5\n", "43.782\t 1 3 -5\n", "43.782\t -1 -3 -5\n", "43.782\t -5 3 -1\n", "43.782\t 3 -5 1\n", "43.782\t 3 1 -5\n", "43.782\t 5 -1 3\n", "43.782\t -1 -5 -3\n", "43.782\t 3 5 -1\n", "43.782\t -5 -3 -1\n", "43.782\t -3 -1 5\n", "43.782\t -3 5 1\n", "43.782\t -5 1 -3\n", "43.782\t 3 -1 -5\n", "43.782\t -3 5 -1\n", "43.782\t -1 3 -5\n", "43.782\t 1 5 -3\n", "43.782\t 1 5 3\n", "43.782\t 5 1 -3\n", "43.782\t 3 5 1\n", "43.782\t -1 5 -3\n", "43.782\t 5 -3 1\n", "43.782\t -5 -1 3\n", "43.782\t -3 -5 -1\n", "43.782\t 3 -5 -1\n", "43.782\t -1 -5 3\n", "43.782\t -3 -5 1\n", "43.782\t -1 3 5\n", "43.782\t 1 3 5\n", "43.782\t 5 1 3\n", "43.782\t 1 -5 -3\n", "43.782\t -3 1 -5\n", "43.782\t 5 3 -1\n", "43.782\t -1 -3 5\n", "43.782\t 5 3 1\n", "43.782\t 1 -5 3\n", "44.436\t 0 0 6\n", "44.436\t 4 -2 -4\n", "44.436\t -2 -4 -4\n", "44.436\t 4 -2 4\n", "44.436\t 4 -4 -2\n", "44.436\t 2 4 -4\n", "44.436\t 0 0 -6\n", "44.436\t -2 -4 4\n", "44.436\t 4 -4 2\n", "44.436\t -4 -4 -2\n", "44.436\t 0 6 0\n", "44.436\t 4 2 -4\n", "44.436\t 2 4 4\n", "44.436\t -4 2 -4\n", "44.436\t -6 0 0\n", "44.436\t -2 4 -4\n", "44.436\t -4 -2 -4\n", "44.436\t -4 2 4\n", "44.436\t -4 4 -2\n", "44.436\t -2 4 4\n", "44.436\t 4 4 2\n", "44.436\t 2 -4 -4\n", "44.436\t 6 0 0\n", "44.436\t 2 -4 4\n", "44.436\t -4 4 2\n", "44.436\t -4 -2 4\n", "44.436\t 4 4 -2\n", "44.436\t -4 -4 2\n", "44.436\t 0 -6 0\n", "44.436\t 4 2 4\n", "45.082\t -6 0 -1\n", "45.082\t 0 -6 1\n", "45.082\t 0 6 -1\n", "45.082\t 0 -6 -1\n", "45.082\t -6 0 1\n", "45.082\t 6 1 0\n", "45.082\t 6 0 -1\n", "45.082\t 1 -6 0\n", "45.082\t 0 1 -6\n", "45.082\t -6 1 0\n", "45.082\t 1 0 6\n", "45.082\t 0 6 1\n", "45.082\t -1 6 0\n", "45.082\t 0 -1 6\n", "45.082\t -6 -1 0\n", "45.082\t 1 0 -6\n", "45.082\t -1 0 -6\n", "45.082\t 0 1 6\n", "45.082\t 0 -1 -6\n", "45.082\t 1 6 0\n", "45.082\t -1 0 6\n", "45.082\t 6 -1 0\n", "45.082\t -1 -6 0\n", "45.082\t 6 0 1\n", "45.722\t -5 3 -2\n", "45.722\t -1 6 1\n", "45.722\t 1 1 -6\n", "45.722\t 3 -5 -2\n", "45.722\t 1 -6 1\n", "45.722\t 5 -3 -2\n", "45.722\t 5 -3 2\n", "45.722\t -6 -1 1\n", "45.722\t -3 5 2\n", "45.722\t -1 -1 -6\n", "45.722\t 3 5 -2\n", "45.722\t -1 -6 -1\n", "45.722\t 6 1 1\n", "45.722\t 6 1 -1\n", "45.722\t -5 -3 2\n", "45.722\t 5 3 2\n", "45.722\t -1 6 -1\n", "45.722\t 5 3 -2\n", "45.722\t -3 -5 -2\n", "45.722\t 6 -1 1\n", "45.722\t -6 -1 -1\n", "45.722\t 3 5 2\n", "45.722\t -1 1 -6\n", "45.722\t 1 -6 -1\n", "45.722\t -6 1 -1\n", "45.722\t -1 -1 6\n", "45.722\t -1 1 6\n", "45.722\t 1 1 6\n", "45.722\t -1 -6 1\n", "45.722\t 1 6 1\n", "45.722\t 1 6 -1\n", "45.722\t 1 -1 -6\n", "45.722\t -6 1 1\n", "45.722\t 1 -1 6\n", "45.722\t 6 -1 -1\n", "45.722\t -5 -3 -2\n", "45.722\t -3 5 -2\n", "45.722\t -5 3 2\n", "45.722\t 3 -5 2\n", "45.722\t -3 -5 2\n", "45.722\t 2 3 -5\n", "45.722\t 3 -2 -5\n", "45.722\t -5 2 -3\n", "45.722\t 2 3 5\n", "45.722\t -3 2 5\n", "45.722\t -5 -2 -3\n", "45.722\t 5 -2 -3\n", "45.722\t -2 3 5\n", "45.722\t 2 -3 -5\n", "45.722\t -3 2 -5\n", "45.722\t 2 -3 5\n", "45.722\t -2 -5 3\n", "45.722\t -2 5 3\n", "45.722\t -3 -2 -5\n", "45.722\t -2 5 -3\n", "45.722\t -2 -3 5\n", "45.722\t -5 2 3\n", "45.722\t 5 -2 3\n", "45.722\t -2 -5 -3\n", "45.722\t -2 -3 -5\n", "45.722\t 5 2 -3\n", "45.722\t -5 -2 3\n", "45.722\t 5 2 3\n", "45.722\t 3 2 -5\n", "45.722\t 2 -5 -3\n", "45.722\t -2 3 -5\n", "45.722\t 2 -5 3\n", "45.722\t 3 2 5\n", "45.722\t 3 -2 5\n", "45.722\t 2 5 -3\n", "45.722\t 2 5 3\n", "45.722\t -3 -2 5\n", "46.980\t -2 0 -6\n", "46.980\t -2 -6 0\n", "46.980\t 6 0 -2\n", "46.980\t 0 -6 -2\n", "46.980\t 2 -6 0\n", "46.980\t 0 -2 -6\n", "46.980\t -6 2 0\n", "46.980\t 0 -6 2\n", "46.980\t 6 2 0\n", "46.980\t 2 6 0\n", "46.980\t -2 0 6\n", "46.980\t 0 2 6\n", "46.980\t 0 -2 6\n", "46.980\t 6 0 2\n", "46.980\t -6 0 2\n", "46.980\t 0 2 -6\n", "46.980\t 2 0 -6\n", "46.980\t -2 6 0\n", "46.980\t 2 0 6\n", "46.980\t 0 6 -2\n", "46.980\t 0 6 2\n", "46.980\t -6 -2 0\n", "46.980\t -6 0 -2\n", "46.980\t 6 -2 0\n", "47.599\t -2 -6 1\n", "47.599\t 6 2 -1\n", "47.599\t -2 -6 -1\n", "47.599\t -2 6 -1\n", "47.599\t 6 2 1\n", "47.599\t -6 2 -1\n", "47.599\t -6 -1 -2\n", "47.599\t 1 -6 2\n", "47.599\t -6 -1 2\n", "47.599\t 2 -6 1\n", "47.599\t 1 6 -2\n", "47.599\t 2 -6 -1\n", "47.599\t 2 6 1\n", "47.599\t -6 -2 -1\n", "47.599\t -2 6 1\n", "47.599\t 6 1 -2\n", "47.599\t -6 -2 1\n", "47.599\t 6 1 2\n", "47.599\t -1 -6 -2\n", "47.599\t 1 6 2\n", "47.599\t -1 6 -2\n", "47.599\t 6 -2 1\n", "47.599\t 1 -6 -2\n", "47.599\t 6 -1 -2\n", "47.599\t -6 1 -2\n", "47.599\t -6 2 1\n", "47.599\t -1 6 2\n", "47.599\t 6 -2 -1\n", "47.599\t 6 -1 2\n", "47.599\t 2 6 -1\n", "47.599\t -6 1 2\n", "47.599\t -1 -6 2\n", "47.599\t -4 -5 0\n", "47.599\t -4 -3 -4\n", "47.599\t -4 3 4\n", "47.599\t 4 -4 -3\n", "47.599\t 4 5 0\n", "47.599\t 2 -1 6\n", "47.599\t -1 2 -6\n", "47.599\t 0 -5 -4\n", "47.599\t -4 0 5\n", "47.599\t -3 -4 4\n", "47.599\t 2 1 -6\n", "47.599\t -4 -3 4\n", "47.599\t 4 3 -4\n", "47.599\t -4 4 -3\n", "47.599\t -2 -1 -6\n", "47.599\t 4 4 3\n", "47.599\t 0 -4 -5\n", "47.599\t 5 4 0\n", "47.599\t -4 5 0\n", "47.599\t 2 1 6\n", "47.599\t -1 -2 -6\n", "47.599\t -4 -4 -3\n", "47.599\t 2 -1 -6\n", "47.599\t 1 2 6\n", "47.599\t 1 2 -6\n", "47.599\t 1 -2 6\n", "47.599\t 0 -5 4\n", "47.599\t 5 0 4\n", "47.599\t -2 -1 6\n", "47.599\t 0 5 4\n", "47.599\t -3 4 4\n", "47.599\t 4 0 5\n", "47.599\t 4 -3 4\n", "47.599\t -1 -2 6\n", "47.599\t 5 0 -4\n", "47.599\t 3 -4 -4\n", "47.599\t 1 -2 -6\n", "47.599\t -5 -4 0\n", "47.599\t 4 -4 3\n", "47.599\t 3 4 -4\n", "47.599\t 0 -4 5\n", "47.599\t 0 4 -5\n", "47.599\t -5 0 4\n", "47.599\t -4 3 -4\n", "47.599\t 3 4 4\n", "47.599\t 4 -3 -4\n", "47.599\t 4 4 -3\n", "47.599\t -3 4 -4\n", "47.599\t -5 4 0\n", "47.599\t -4 -4 3\n", "47.599\t -2 1 -6\n", "47.599\t -2 1 6\n", "47.599\t 5 -4 0\n", "47.599\t -1 2 6\n", "47.599\t -4 4 3\n", "47.599\t -3 -4 -4\n", "47.599\t -4 0 -5\n", "47.599\t 4 0 -5\n", "47.599\t 4 3 4\n", "47.599\t 0 4 5\n", "47.599\t -5 0 -4\n", "47.599\t 0 5 -4\n", "47.599\t 4 -5 0\n", "47.599\t 3 -4 4\n", "48.212\t -4 -5 -1\n", "48.212\t 5 -1 -4\n", "48.212\t 4 1 -5\n", "48.212\t -1 -5 4\n", "48.212\t 1 4 -5\n", "48.212\t 4 -5 1\n", "48.212\t 1 -4 5\n", "48.212\t -5 1 -4\n", "48.212\t 4 -5 -1\n", "48.212\t 1 5 -4\n", "48.212\t 1 4 5\n", "48.212\t -5 -1 -4\n", "48.212\t 1 -5 -4\n", "48.212\t 1 5 4\n", "48.212\t 1 -4 -5\n", "48.212\t 1 -5 4\n", "48.212\t -4 5 -1\n", "48.212\t -4 5 1\n", "48.212\t 4 1 5\n", "48.212\t -4 -5 1\n", "48.212\t 5 1 4\n", "48.212\t -5 -1 4\n", "48.212\t 5 -1 4\n", "48.212\t 4 -1 -5\n", "48.212\t -1 -4 -5\n", "48.212\t -1 -5 -4\n", "48.212\t -5 1 4\n", "48.212\t -5 4 1\n", "48.212\t -1 5 4\n", "48.212\t 5 4 1\n", "48.212\t -1 4 -5\n", "48.212\t -1 4 5\n", "48.212\t -1 5 -4\n", "48.212\t 5 4 -1\n", "48.212\t -5 -4 -1\n", "48.212\t -4 -1 -5\n", "48.212\t 4 5 -1\n", "48.212\t 4 -1 5\n", "48.212\t -1 -4 5\n", "48.212\t 5 -4 1\n", "48.212\t 5 1 -4\n", "48.212\t -5 4 -1\n", "48.212\t -5 -4 1\n", "48.212\t 5 -4 -1\n", "48.212\t -4 -1 5\n", "48.212\t -4 1 5\n", "48.212\t -4 1 -5\n", "48.212\t 4 5 1\n", "48.820\t 3 -5 3\n", "48.820\t 3 -3 5\n", "48.820\t 5 -3 -3\n", "48.820\t -5 3 3\n", "48.820\t -3 5 3\n", "48.820\t -3 3 5\n", "48.820\t 3 5 -3\n", "48.820\t 3 -3 -5\n", "48.820\t -3 -3 -5\n", "48.820\t -3 3 -5\n", "48.820\t -5 3 -3\n", "48.820\t -5 -3 3\n", "48.820\t 3 5 3\n", "48.820\t -3 -3 5\n", "48.820\t 5 3 -3\n", "48.820\t 3 3 5\n", "48.820\t -3 5 -3\n", "48.820\t 5 -3 3\n", "48.820\t 3 -5 -3\n", "48.820\t 3 3 -5\n", "48.820\t -5 -3 -3\n", "48.820\t -3 -5 -3\n", "48.820\t -3 -5 3\n", "48.820\t 5 3 3\n", "49.422\t 2 -6 2\n", "49.422\t -2 6 2\n", "49.422\t 2 6 2\n", "49.422\t -2 -6 -2\n", "49.422\t 2 -6 -2\n", "49.422\t -6 -2 2\n", "49.422\t 6 2 -2\n", "49.422\t -2 -6 2\n", "49.422\t 2 6 -2\n", "49.422\t -6 2 -2\n", "49.422\t -6 2 2\n", "49.422\t -6 -2 -2\n", "49.422\t 6 -2 -2\n", "49.422\t 6 -2 2\n", "49.422\t 6 2 2\n", "49.422\t -2 6 -2\n", "49.422\t 2 -2 6\n", "49.422\t -2 -2 6\n", "49.422\t -2 2 -6\n", "49.422\t 2 -2 -6\n", "49.422\t 2 2 6\n", "49.422\t 2 2 -6\n", "49.422\t -2 -2 -6\n", "49.422\t -2 2 6\n", "50.019\t -4 -5 -2\n", "50.019\t -6 0 3\n", "50.019\t -3 -6 0\n", "50.019\t -5 4 -2\n", "50.019\t -5 4 2\n", "50.019\t -4 5 -2\n", "50.019\t 4 -5 2\n", "50.019\t 6 -3 0\n", "50.019\t 3 0 -6\n", "50.019\t 5 -4 -2\n", "50.019\t -4 -5 2\n", "50.019\t -6 0 -3\n", "50.019\t 4 -5 -2\n", "50.019\t 3 -6 0\n", "50.019\t -3 0 6\n", "50.019\t 5 4 -2\n", "50.019\t -6 -3 0\n", "50.019\t 3 6 0\n", "50.019\t -3 0 -6\n", "50.019\t 5 4 2\n", "50.019\t -5 -4 -2\n", "50.019\t 0 6 -3\n", "50.019\t -5 -4 2\n", "50.019\t 5 -4 2\n", "50.019\t 3 0 6\n", "50.019\t 6 0 -3\n", "50.019\t 0 6 3\n", "50.019\t 4 5 -2\n", "50.019\t 6 0 3\n", "50.019\t 0 3 -6\n", "50.019\t 6 3 0\n", "50.019\t 4 5 2\n", "50.019\t -4 5 2\n", "50.019\t -3 6 0\n", "50.019\t -6 3 0\n", "50.019\t 0 -3 -6\n", "50.019\t 0 -6 -3\n", "50.019\t 0 -3 6\n", "50.019\t 0 3 6\n", "50.019\t 0 -6 3\n", "50.019\t 5 -2 4\n", "50.019\t 4 -2 -5\n", "50.019\t 4 -2 5\n", "50.019\t -5 2 4\n", "50.019\t 2 4 -5\n", "50.019\t 2 4 5\n", "50.019\t -5 2 -4\n", "50.019\t 2 -5 -4\n", "50.019\t 2 5 -4\n", "50.019\t 5 -2 -4\n", "50.019\t -4 -2 5\n", "50.019\t 2 5 4\n", "50.019\t -2 5 -4\n", "50.019\t -2 -5 -4\n", "50.019\t 4 2 5\n", "50.019\t 5 2 4\n", "50.019\t -2 -5 4\n", "50.019\t -2 -4 -5\n", "50.019\t 5 2 -4\n", "50.019\t 4 2 -5\n", "50.019\t -2 4 -5\n", "50.019\t -2 5 4\n", "50.019\t -2 4 5\n", "50.019\t 2 -5 4\n", "50.019\t 2 -4 -5\n", "50.019\t -4 2 5\n", "50.019\t -5 -2 -4\n", "50.019\t 2 -4 5\n", "50.019\t -5 -2 4\n", "50.019\t -4 2 -5\n", "50.019\t -4 -2 -5\n", "50.019\t -2 -4 5\n", "50.610\t -1 -6 -3\n", "50.610\t 1 3 6\n", "50.610\t -1 3 -6\n", "50.610\t 3 -1 6\n", "50.610\t 6 1 -3\n", "50.610\t 3 -1 -6\n", "50.610\t -1 -3 6\n", "50.610\t -3 1 6\n", "50.610\t 6 -1 3\n", "50.610\t 6 1 3\n", "50.610\t 3 1 -6\n", "50.610\t 1 6 3\n", "50.610\t 1 -3 6\n", "50.610\t -6 1 3\n", "50.610\t -6 -1 3\n", "50.610\t 1 -3 -6\n", "50.610\t -1 6 -3\n", "50.610\t 3 1 6\n", "50.610\t -1 -6 3\n", "50.610\t -6 1 -3\n", "50.610\t -1 3 6\n", "50.610\t -3 -1 6\n", "50.610\t 6 -1 -3\n", "50.610\t 1 6 -3\n", "50.610\t 1 -6 -3\n", "50.610\t -1 -3 -6\n", "50.610\t -3 1 -6\n", "50.610\t 1 -6 3\n", "50.610\t -3 -1 -6\n", "50.610\t 1 3 -6\n", "50.610\t -1 6 3\n", "50.610\t -6 -1 -3\n", "50.610\t 3 -6 1\n", "50.610\t -6 3 1\n", "50.610\t 3 -6 -1\n", "50.610\t 3 6 -1\n", "50.610\t 6 -3 -1\n", "50.610\t -3 -6 -1\n", "50.610\t 6 -3 1\n", "50.610\t 6 3 -1\n", "50.610\t -3 -6 1\n", "50.610\t -6 3 -1\n", "50.610\t -3 6 1\n", "50.610\t -3 6 -1\n", "50.610\t -6 -3 1\n", "50.610\t 6 3 1\n", "50.610\t -6 -3 -1\n", "50.610\t 3 6 1\n", "51.778\t 4 -4 -4\n", "51.778\t 4 -4 4\n", "51.778\t 4 4 4\n", "51.778\t -4 -4 -4\n", "51.778\t -4 4 -4\n", "51.778\t 4 4 -4\n", "51.778\t -4 -4 4\n", "51.778\t -4 4 4\n", "52.355\t 0 0 -7\n", "52.355\t 6 -3 -2\n", "52.355\t -2 -6 -3\n", "52.355\t -6 2 3\n", "52.355\t -2 -6 3\n", "52.355\t -2 6 3\n", "52.355\t 0 7 0\n", "52.355\t -3 2 -6\n", "52.355\t 2 -3 -6\n", "52.355\t 6 -2 -3\n", "52.355\t 0 0 7\n", "52.355\t -3 -2 -6\n", "52.355\t -2 -3 -6\n", "52.355\t -3 -2 6\n", "52.355\t -3 -6 2\n", "52.355\t 6 -3 2\n", "52.355\t 0 -7 0\n", "52.355\t -6 3 -2\n", "52.355\t -3 -6 -2\n", "52.355\t -6 2 -3\n", "52.355\t -2 -3 6\n", "52.355\t -3 6 2\n", "52.355\t -6 3 2\n", "52.355\t -3 6 -2\n", "52.355\t 6 -2 3\n", "52.355\t -3 2 6\n", "52.355\t -2 3 6\n", "52.355\t 3 6 -2\n", "52.355\t 2 6 3\n", "52.355\t 2 6 -3\n", "52.355\t 2 3 6\n", "52.355\t 6 3 2\n", "52.355\t 2 -6 3\n", "52.355\t 3 6 2\n", "52.355\t 7 0 0\n", "52.355\t 3 -2 6\n", "52.355\t 6 3 -2\n", "52.355\t 3 2 -6\n", "52.355\t 3 2 6\n", "52.355\t -7 0 0\n", "52.355\t 2 -6 -3\n", "52.355\t 6 2 3\n", "52.355\t 3 -2 -6\n", "52.355\t 6 2 -3\n", "52.355\t -6 -3 2\n", "52.355\t -6 -2 -3\n", "52.355\t -6 -3 -2\n", "52.355\t 3 -6 -2\n", "52.355\t -2 3 -6\n", "52.355\t 3 -6 2\n", "52.355\t -2 6 -3\n", "52.355\t -6 -2 3\n", "52.355\t 2 3 -6\n", "52.355\t 2 -3 6\n", "52.928\t -4 5 3\n", "52.928\t -3 -4 5\n", "52.928\t 1 0 7\n", "52.928\t -3 -5 4\n", "52.928\t 4 -5 3\n", "52.928\t 5 4 3\n", "52.928\t 5 -5 0\n", "52.928\t -5 -5 0\n", "52.928\t 7 1 0\n", "52.928\t 0 -1 7\n", "52.928\t 0 7 1\n", "52.928\t -5 4 -3\n", "52.928\t -5 3 4\n", "52.928\t -5 3 -4\n", "52.928\t 7 0 1\n", "52.928\t -3 4 5\n", "52.928\t -5 -4 3\n", "52.928\t -1 7 0\n", "52.928\t -5 4 3\n", "52.928\t 5 -4 3\n", "52.928\t 0 -5 -5\n", "52.928\t 5 3 -4\n", "52.928\t 0 1 -7\n", "52.928\t 5 4 -3\n", "52.928\t 1 7 0\n", "52.928\t -4 3 -5\n", "52.928\t 0 -5 5\n", "52.928\t -3 -4 -5\n", "52.928\t -3 -5 -4\n", "52.928\t -5 -4 -3\n", "52.928\t 5 -3 4\n", "52.928\t -4 3 5\n", "52.928\t 5 -3 -4\n", "52.928\t -4 5 -3\n", "52.928\t 0 -7 1\n", "52.928\t -5 -3 4\n", "52.928\t 4 -5 -3\n", "52.928\t 5 3 4\n", "52.928\t 5 -4 -3\n", "52.928\t 1 0 -7\n", "52.928\t 0 -7 -1\n", "52.928\t 0 5 5\n", "52.928\t 7 -1 0\n", "52.928\t 4 -3 5\n", "52.928\t 1 -7 0\n", "52.928\t -4 -5 3\n", "52.928\t -4 -3 -5\n", "52.928\t 4 -3 -5\n", "52.928\t 5 5 0\n", "52.928\t 4 3 5\n", "52.928\t 3 -4 5\n", "52.928\t -4 -5 -3\n", "52.928\t -1 0 7\n", "52.928\t -5 0 -5\n", "52.928\t 5 0 -5\n", "52.928\t 4 3 -5\n", "52.928\t -7 1 0\n", "52.928\t -1 0 -7\n", "52.928\t 0 -1 -7\n", "52.928\t -5 0 5\n", "52.928\t -5 5 0\n", "52.928\t 3 -5 4\n", "52.928\t -7 0 1\n", "52.928\t -4 -3 5\n", "52.928\t 5 0 5\n", "52.928\t 3 -5 -4\n", "52.928\t -3 5 -4\n", "52.928\t 7 0 -1\n", "52.928\t -1 -7 0\n", "52.928\t 0 5 -5\n", "52.928\t 4 5 -3\n", "52.928\t 0 1 7\n", "52.928\t -3 5 4\n", "52.928\t -7 -1 0\n", "52.928\t -5 -3 -4\n", "52.928\t 4 5 3\n", "52.928\t 3 4 -5\n", "52.928\t 3 5 -4\n", "52.928\t 3 4 5\n", "52.928\t -7 0 -1\n", "52.928\t -3 4 -5\n", "52.928\t 0 7 -1\n", "52.928\t 3 5 4\n", "52.928\t 3 -4 -5\n", "53.496\t -1 -7 -1\n", "53.496\t -1 -7 1\n", "53.496\t 1 1 7\n", "53.496\t -1 -1 -7\n", "53.496\t -7 -1 -1\n", "53.496\t 1 -1 7\n", "53.496\t -7 1 1\n", "53.496\t 1 -1 -7\n", "53.496\t 1 7 1\n", "53.496\t 7 -1 1\n", "53.496\t 1 -7 1\n", "53.496\t -1 1 7\n", "53.496\t -7 -1 1\n", "53.496\t -1 1 -7\n", "53.496\t 7 1 1\n", "53.496\t 1 -7 -1\n", "53.496\t 1 1 -7\n", "53.496\t 7 -1 -1\n", "53.496\t -7 1 -1\n", "53.496\t -1 -1 7\n", "53.496\t 7 1 -1\n", "53.496\t -1 7 -1\n", "53.496\t -1 7 1\n", "53.496\t 1 7 -1\n", "53.496\t 1 -5 5\n", "53.496\t 5 5 -1\n", "53.496\t 5 1 -5\n", "53.496\t -1 5 5\n", "53.496\t -5 -5 -1\n", "53.496\t 5 5 1\n", "53.496\t 5 -1 -5\n", "53.496\t 5 -1 5\n", "53.496\t -5 1 -5\n", "53.496\t -5 -1 -5\n", "53.496\t -5 5 -1\n", "53.496\t 5 1 5\n", "53.496\t -5 5 1\n", "53.496\t 5 -5 1\n", "53.496\t -5 1 5\n", "53.496\t 1 5 5\n", "53.496\t -1 -5 5\n", "53.496\t 1 5 -5\n", "53.496\t -5 -5 1\n", "53.496\t 1 -5 -5\n", "53.496\t -1 5 -5\n", "53.496\t 5 -5 -1\n", "53.496\t -1 -5 -5\n", "53.496\t -5 -1 5\n", "54.060\t 4 0 -6\n", "54.060\t 0 -6 4\n", "54.060\t 6 4 0\n", "54.060\t -6 -4 0\n", "54.060\t 0 6 4\n", "54.060\t 4 0 6\n", "54.060\t 0 6 -4\n", "54.060\t 4 -6 0\n", "54.060\t 6 -4 0\n", "54.060\t -4 6 0\n", "54.060\t -4 0 -6\n", "54.060\t -4 -6 0\n", "54.060\t 6 0 -4\n", "54.060\t -4 0 6\n", "54.060\t -6 4 0\n", "54.060\t 0 -4 -6\n", "54.060\t 0 4 -6\n", "54.060\t -6 0 4\n", "54.060\t 0 4 6\n", "54.060\t 0 -4 6\n", "54.060\t -6 0 -4\n", "54.060\t 4 6 0\n", "54.060\t 0 -6 -4\n", "54.060\t 6 0 4\n", "54.620\t 6 -1 4\n", "54.620\t 0 2 7\n", "54.620\t 2 7 0\n", "54.620\t 1 4 -6\n", "54.620\t 4 1 -6\n", "54.620\t -6 4 1\n", "54.620\t -6 4 -1\n", "54.620\t -1 4 6\n", "54.620\t 0 -7 2\n", "54.620\t 2 0 -7\n", "54.620\t -1 6 -4\n", "54.620\t -6 -4 -1\n", "54.620\t 1 -4 -6\n", "54.620\t 6 -1 -4\n", "54.620\t 0 -7 -2\n", "54.620\t 6 1 4\n", "54.620\t 7 0 2\n", "54.620\t -1 6 4\n", "54.620\t 1 -6 4\n", "54.620\t 7 0 -2\n", "54.620\t 7 2 0\n", "54.620\t 4 -1 -6\n", "54.620\t -1 -4 -6\n", "54.620\t -6 1 4\n", "54.620\t 1 -6 -4\n", "54.620\t 1 4 6\n", "54.620\t 0 2 -7\n", "54.620\t 6 -4 1\n", "54.620\t 6 -4 -1\n", "54.620\t 4 -1 6\n", "54.620\t 2 0 7\n", "54.620\t 4 -6 -1\n", "54.620\t 6 1 -4\n", "54.620\t 4 1 6\n", "54.620\t 1 6 -4\n", "54.620\t -1 -4 6\n", "54.620\t 1 6 4\n", "54.620\t 6 4 1\n", "54.620\t 7 -2 0\n", "54.620\t -2 7 0\n", "54.620\t -4 1 -6\n", "54.620\t -4 -6 -1\n", "54.620\t 4 6 1\n", "54.620\t -4 -6 1\n", "54.620\t -4 -1 6\n", "54.620\t -4 -1 -6\n", "54.620\t -2 0 -7\n", "54.620\t -4 1 6\n", "54.620\t -7 0 -2\n", "54.620\t -4 6 1\n", "54.620\t -4 6 -1\n", "54.620\t 1 -4 6\n", "54.620\t -7 2 0\n", "54.620\t 6 4 -1\n", "54.620\t 4 6 -1\n", "54.620\t -2 -7 0\n", "54.620\t -6 -1 4\n", "54.620\t -7 -2 0\n", "54.620\t 4 -6 1\n", "54.620\t -6 -1 -4\n", "54.620\t -6 1 -4\n", "54.620\t 2 -7 0\n", "54.620\t 0 7 2\n", "54.620\t -1 4 -6\n", "54.620\t 0 -2 -7\n", "54.620\t 0 7 -2\n", "54.620\t 0 -2 7\n", "54.620\t -6 -4 1\n", "54.620\t -7 0 2\n", "54.620\t -1 -6 4\n", "54.620\t -2 0 7\n", "54.620\t -1 -6 -4\n", "55.177\t 3 -3 -6\n", "55.177\t 3 3 6\n", "55.177\t 3 3 -6\n", "55.177\t -3 -3 -6\n", "55.177\t -3 -3 6\n", "55.177\t -3 3 -6\n", "55.177\t 3 -3 6\n", "55.177\t -3 3 6\n", "55.177\t 7 -2 1\n", "55.177\t -2 -7 1\n", "55.177\t 7 -2 -1\n", "55.177\t -7 -2 1\n", "55.177\t -7 -2 -1\n", "55.177\t -5 2 -5\n", "55.177\t 6 -3 -3\n", "55.177\t -2 7 -1\n", "55.177\t -7 2 -1\n", "55.177\t 6 -3 3\n", "55.177\t 1 7 2\n", "55.177\t -7 -1 2\n", "55.177\t -2 -5 -5\n", "55.177\t -7 2 1\n", "55.177\t 1 -2 7\n", "55.177\t 7 -1 -2\n", "55.177\t -2 7 1\n", "55.177\t -5 -2 5\n", "55.177\t -5 -2 -5\n", "55.177\t -5 2 5\n", "55.177\t 7 2 -1\n", "55.177\t -1 2 -7\n", "55.177\t -1 2 7\n", "55.177\t -5 5 2\n", "55.177\t 7 1 -2\n", "55.177\t -2 5 -5\n", "55.177\t 2 5 5\n", "55.177\t 7 -1 2\n", "55.177\t 2 -7 1\n", "55.177\t -5 5 -2\n", "55.177\t 1 -2 -7\n", "55.177\t 1 7 -2\n", "55.177\t 2 -7 -1\n", "55.177\t -2 5 5\n", "55.177\t 6 3 -3\n", "55.177\t -1 -2 7\n", "55.177\t 6 3 3\n", "55.177\t 3 6 3\n", "55.177\t -7 -1 -2\n", "55.177\t -2 -7 -1\n", "55.177\t -6 3 3\n", "55.177\t 3 6 -3\n", "55.177\t 2 7 1\n", "55.177\t -6 3 -3\n", "55.177\t 5 -5 2\n", "55.177\t -7 1 -2\n", "55.177\t 5 -5 -2\n", "55.177\t 5 5 2\n", "55.177\t -1 -7 -2\n", "55.177\t 5 -2 5\n", "55.177\t 1 2 -7\n", "55.177\t -1 7 2\n", "55.177\t -3 6 -3\n", "55.177\t -3 -6 -3\n", "55.177\t -1 -2 -7\n", "55.177\t 2 -5 5\n", "55.177\t 2 -5 -5\n", "55.177\t -1 7 -2\n", "55.177\t -2 1 7\n", "55.177\t 3 -6 3\n", "55.177\t 1 2 7\n", "55.177\t 3 -6 -3\n", "55.177\t -6 -3 -3\n", "55.177\t -2 -5 5\n", "55.177\t -2 1 -7\n", "55.177\t -1 -7 2\n", "55.177\t -3 -6 3\n", "55.177\t 2 1 -7\n", "55.177\t 2 7 -1\n", "55.177\t -2 -1 7\n", "55.177\t 7 1 2\n", "55.177\t 5 2 5\n", "55.177\t -6 -3 3\n", "55.177\t 7 2 1\n", "55.177\t -5 -5 -2\n", "55.177\t -7 1 2\n", "55.177\t 2 5 -5\n", "55.177\t -2 -1 -7\n", "55.177\t 5 5 -2\n", "55.177\t -3 6 3\n", "55.177\t 2 -1 -7\n", "55.177\t 2 -1 7\n", "55.177\t 5 2 -5\n", "55.177\t 1 -7 2\n", "55.177\t -5 -5 2\n", "55.177\t 2 1 7\n", "55.177\t 5 -2 -5\n", "55.177\t 1 -7 -2\n", "56.278\t -2 6 -4\n", "56.278\t -6 -4 -2\n", "56.278\t -6 2 -4\n", "56.278\t 2 -4 -6\n", "56.278\t 4 -2 -6\n", "56.278\t -6 -2 4\n", "56.278\t -4 6 -2\n", "56.278\t 6 -2 4\n", "56.278\t -2 6 4\n", "56.278\t -2 -4 -6\n", "56.278\t 4 -6 -2\n", "56.278\t 4 -6 2\n", "56.278\t 2 6 4\n", "56.278\t 2 -4 6\n", "56.278\t -4 -2 -6\n", "56.278\t 4 6 2\n", "56.278\t -4 6 2\n", "56.278\t 4 2 -6\n", "56.278\t -2 -6 -4\n", "56.278\t -6 2 4\n", "56.278\t 2 -6 -4\n", "56.278\t 2 -6 4\n", "56.278\t -6 -4 2\n", "56.278\t -4 2 6\n", "56.278\t 4 6 -2\n", "56.278\t 2 6 -4\n", "56.278\t -2 -6 4\n", "56.278\t -2 4 -6\n", "56.278\t 2 4 6\n", "56.278\t -6 4 2\n", "56.278\t -4 -2 6\n", "56.278\t -4 -6 2\n", "56.278\t 4 -2 6\n", "56.278\t 6 4 2\n", "56.278\t -2 4 6\n", "56.278\t 4 2 6\n", "56.278\t 6 -2 -4\n", "56.278\t 6 4 -2\n", "56.278\t -6 -2 -4\n", "56.278\t -4 2 -6\n", "56.278\t -4 -6 -2\n", "56.278\t 6 -4 2\n", "56.278\t -2 -4 6\n", "56.278\t 6 2 4\n", "56.278\t -6 4 -2\n", "56.278\t 6 -4 -2\n", "56.278\t 2 4 -6\n", "56.278\t 6 2 -4\n", "56.824\t 4 5 4\n", "56.824\t 7 2 2\n", "56.824\t 2 7 2\n", "56.824\t 7 2 -2\n", "56.824\t -4 -5 4\n", "56.824\t -7 -2 -2\n", "56.824\t -2 7 2\n", "56.824\t -2 7 -2\n", "56.824\t 4 4 -5\n", "56.824\t -4 -5 -4\n", "56.824\t 4 5 -4\n", "56.824\t 4 -4 -5\n", "56.824\t 2 2 -7\n", "56.824\t 5 4 -4\n", "56.824\t -2 -2 -7\n", "56.824\t 5 4 4\n", "56.824\t -5 4 4\n", "56.824\t -2 -2 7\n", "56.824\t 4 -5 -4\n", "56.824\t 2 7 -2\n", "56.824\t 2 2 7\n", "56.824\t 4 -5 4\n", "56.824\t 4 4 5\n", "56.824\t 7 -2 -2\n", "56.824\t 4 -4 5\n", "56.824\t -2 2 7\n", "56.824\t 2 -2 7\n", "56.824\t -4 4 -5\n", "56.824\t 2 -7 2\n", "56.824\t -5 -4 -4\n", "56.824\t 2 -7 -2\n", "56.824\t 2 -2 -7\n", "56.824\t -4 5 4\n", "56.824\t -5 -4 4\n", "56.824\t -2 -7 -2\n", "56.824\t 5 -4 -4\n", "56.824\t -4 5 -4\n", "56.824\t -2 -7 2\n", "56.824\t -4 4 5\n", "56.824\t 7 -2 2\n", "56.824\t -2 2 -7\n", "56.824\t -4 -4 5\n", "56.824\t -7 2 2\n", "56.824\t 5 -4 4\n", "56.824\t -5 4 -4\n", "56.824\t -4 -4 -5\n", "56.824\t -7 2 -2\n", "56.824\t -7 -2 2\n", "57.366\t -7 -3 0\n", "57.366\t 0 -7 -3\n", "57.366\t 3 7 0\n", "57.366\t 0 7 -3\n", "57.366\t 0 -7 3\n", "57.366\t -7 3 0\n", "57.366\t 3 -7 0\n", "57.366\t 0 -3 -7\n", "57.366\t 7 -3 0\n", "57.366\t 0 3 -7\n", "57.366\t 0 3 7\n", "57.366\t 0 -3 7\n", "57.366\t 7 0 -3\n", "57.366\t 7 0 3\n", "57.366\t -3 7 0\n", "57.366\t 0 7 3\n", "57.366\t -7 0 3\n", "57.366\t 3 0 7\n", "57.366\t 7 3 0\n", "57.366\t -3 -7 0\n", "57.366\t -3 0 7\n", "57.366\t -7 0 -3\n", "57.366\t 3 0 -7\n", "57.366\t -3 0 -7\n", "57.905\t -1 7 3\n", "57.905\t -3 -7 -1\n", "57.905\t -3 -7 1\n", "57.905\t 3 5 5\n", "57.905\t 3 1 7\n", "57.905\t 1 7 -3\n", "57.905\t 3 -7 -1\n", "57.905\t -1 3 -7\n", "57.905\t 7 1 -3\n", "57.905\t 3 -1 -7\n", "57.905\t 3 7 -1\n", "57.905\t -1 -7 3\n", "57.905\t 3 7 1\n", "57.905\t -1 3 7\n", "57.905\t -5 5 3\n", "57.905\t 5 5 3\n", "57.905\t 1 7 3\n", "57.905\t 5 3 -5\n", "57.905\t 7 -1 3\n", "57.905\t -7 -3 -1\n", "57.905\t 7 3 1\n", "57.905\t 5 -3 -5\n", "57.905\t 7 -1 -3\n", "57.905\t 1 -7 -3\n", "57.905\t -7 -1 -3\n", "57.905\t 5 -3 5\n", "57.905\t -7 1 3\n", "57.905\t -5 -5 -3\n", "57.905\t 7 1 3\n", "57.905\t -1 -3 7\n", "57.905\t -5 -5 3\n", "57.905\t 5 3 5\n", "57.905\t -7 -1 3\n", "57.905\t -1 -7 -3\n", "57.905\t -1 -3 -7\n", "57.905\t -7 -3 1\n", "57.905\t -3 -5 5\n", "57.905\t -5 3 5\n", "57.905\t -3 -1 -7\n", "57.905\t 1 -3 -7\n", "57.905\t 5 -5 -3\n", "57.905\t -7 1 -3\n", "57.905\t -3 5 -5\n", "57.905\t -3 -1 7\n", "57.905\t 5 -5 3\n", "57.905\t -7 3 -1\n", "57.905\t -3 5 5\n", "57.905\t 1 -7 3\n", "57.905\t -3 -5 -5\n", "57.905\t -5 -3 5\n", "57.905\t -7 3 1\n", "57.905\t 1 3 7\n", "57.905\t -3 1 -7\n", "57.905\t -3 7 -1\n", "57.905\t 1 -3 7\n", "57.905\t -3 7 1\n", "57.905\t 7 3 -1\n", "57.905\t -5 -3 -5\n", "57.905\t -5 5 -3\n", "57.905\t 1 3 -7\n", "57.905\t 3 -1 7\n", "57.905\t 3 -5 5\n", "57.905\t 3 -5 -5\n", "57.905\t 7 -3 -1\n", "57.905\t 7 -3 1\n", "57.905\t -1 7 -3\n", "57.905\t -5 3 -5\n", "57.905\t 3 1 -7\n", "57.905\t 3 -7 1\n", "57.905\t -3 1 7\n", "57.905\t 5 5 -3\n", "57.905\t 3 5 -5\n", "58.973\t -3 -4 6\n", "58.973\t -3 -4 -6\n", "58.973\t -4 -3 6\n", "58.973\t -4 -3 -6\n", "58.973\t 3 -4 -6\n", "58.973\t -4 3 -6\n", "58.973\t 4 3 6\n", "58.973\t -3 4 6\n", "58.973\t 4 -3 6\n", "58.973\t -3 4 -6\n", "58.973\t 3 -4 6\n", "58.973\t -4 3 6\n", "58.973\t 4 3 -6\n", "58.973\t 4 -3 -6\n", "58.973\t 3 4 -6\n", "58.973\t 3 4 6\n", "58.973\t -4 6 -3\n", "58.973\t 6 0 -5\n", "58.973\t 3 6 -4\n", "58.973\t -6 5 0\n", "58.973\t -6 4 3\n", "58.973\t 0 5 6\n", "58.973\t 6 5 0\n", "58.973\t 4 6 -3\n", "58.973\t 5 6 0\n", "58.973\t 6 4 -3\n", "58.973\t 6 3 -4\n", "58.973\t 6 3 4\n", "58.973\t -6 3 -4\n", "58.973\t 0 6 -5\n", "58.973\t 6 -3 4\n", "58.973\t 3 6 4\n", "58.973\t -6 4 -3\n", "58.973\t 5 0 6\n", "58.973\t 6 -4 -3\n", "58.973\t 4 6 3\n", "58.973\t -5 -6 0\n", "58.973\t 0 -5 6\n", "58.973\t 6 -4 3\n", "58.973\t 6 -3 -4\n", "58.973\t -4 6 3\n", "58.973\t 0 6 5\n", "58.973\t 6 0 5\n", "58.973\t -3 6 -4\n", "58.973\t 0 -6 -5\n", "58.973\t 6 4 3\n", "58.973\t -3 -6 -4\n", "58.973\t 4 -6 3\n", "58.973\t -6 0 -5\n", "58.973\t -5 0 -6\n", "58.973\t -6 -3 4\n", "58.973\t 4 -6 -3\n", "58.973\t -6 -3 -4\n", "58.973\t -6 -4 3\n", "58.973\t -3 -6 4\n", "58.973\t 3 -6 -4\n", "58.973\t 3 -6 4\n", "58.973\t -5 0 6\n", "58.973\t 6 -5 0\n", "58.973\t 0 5 -6\n", "58.973\t -4 -6 -3\n", "58.973\t -6 -5 0\n", "58.973\t -6 0 5\n", "58.973\t -5 6 0\n", "58.973\t 5 -6 0\n", "58.973\t -4 -6 3\n", "58.973\t 5 0 -6\n", "58.973\t 0 -6 5\n", "58.973\t -6 3 4\n", "58.973\t 0 -5 -6\n", "58.973\t -3 6 4\n", "58.973\t -6 -4 -3\n", "59.503\t -1 -6 5\n", "59.503\t -1 -6 -5\n", "59.503\t -7 2 -3\n", "59.503\t 3 -7 2\n", "59.503\t 1 -5 -6\n", "59.503\t 1 -5 6\n", "59.503\t -1 6 -5\n", "59.503\t 7 -3 -2\n", "59.503\t 5 1 -6\n", "59.503\t 3 -7 -2\n", "59.503\t -1 5 6\n", "59.503\t -5 -1 -6\n", "59.503\t -5 -1 6\n", "59.503\t 1 -6 5\n", "59.503\t 5 -1 6\n", "59.503\t -1 6 5\n", "59.503\t -7 2 3\n", "59.503\t -1 -5 6\n", "59.503\t 1 6 5\n", "59.503\t -7 -3 2\n", "59.503\t 6 1 -5\n", "59.503\t 2 7 3\n", "59.503\t 7 -3 2\n", "59.503\t 2 7 -3\n", "59.503\t -5 1 6\n", "59.503\t 7 2 3\n", "59.503\t -6 -1 -5\n", "59.503\t -7 3 -2\n", "59.503\t 6 -1 5\n", "59.503\t -1 5 -6\n", "59.503\t -6 1 -5\n", "59.503\t -1 -5 -6\n", "59.503\t -6 1 5\n", "59.503\t 1 -6 -5\n", "59.503\t 5 1 6\n", "59.503\t 3 7 2\n", "59.503\t 1 5 -6\n", "59.503\t -3 7 2\n", "59.503\t -3 7 -2\n", "59.503\t 2 -7 -3\n", "59.503\t -2 7 -3\n", "59.503\t 7 -2 -3\n", "59.503\t 7 3 2\n", "59.503\t -7 3 2\n", "59.503\t 3 7 -2\n", "59.503\t 7 2 -3\n", "59.503\t -7 -3 -2\n", "59.503\t 5 -1 -6\n", "59.503\t 2 -7 3\n", "59.503\t -2 7 3\n", "59.503\t 1 6 -5\n", "59.503\t -3 -7 -2\n", "59.503\t 6 1 5\n", "59.503\t -2 -7 -3\n", "59.503\t -7 -2 3\n", "59.503\t -5 1 -6\n", "59.503\t -3 -7 2\n", "59.503\t -7 -2 -3\n", "59.503\t 1 5 6\n", "59.503\t 6 -1 -5\n", "59.503\t -2 -7 3\n", "59.503\t -6 -1 5\n", "59.503\t 7 -2 3\n", "59.503\t 7 3 -2\n", "59.503\t 6 5 1\n", "59.503\t 6 5 -1\n", "59.503\t 3 2 7\n", "59.503\t -3 -2 7\n", "59.503\t 6 -5 -1\n", "59.503\t -3 -2 -7\n", "59.503\t -5 6 -1\n", "59.503\t 3 -2 7\n", "59.503\t 6 -5 1\n", "59.503\t -2 -3 -7\n", "59.503\t -2 3 7\n", "59.503\t -6 -5 1\n", "59.503\t 3 2 -7\n", "59.503\t 5 -6 1\n", "59.503\t 2 3 7\n", "59.503\t -5 6 1\n", "59.503\t 5 6 -1\n", "59.503\t -6 -5 -1\n", "59.503\t 3 -2 -7\n", "59.503\t 2 -3 7\n", "59.503\t -2 -3 7\n", "59.503\t 2 -3 -7\n", "59.503\t -5 -6 1\n", "59.503\t -5 -6 -1\n", "59.503\t -3 2 7\n", "59.503\t 5 6 1\n", "59.503\t -2 3 -7\n", "59.503\t -3 2 -7\n", "59.503\t -6 5 1\n", "59.503\t 5 -6 -1\n", "59.503\t -6 5 -1\n", "59.503\t 2 3 -7\n", "60.553\t 0 0 8\n", "60.553\t 0 8 0\n", "60.553\t 0 0 -8\n", "60.553\t 8 0 0\n", "60.553\t 0 -8 0\n", "60.553\t -8 0 0\n", "61.075\t -2 -6 -5\n", "61.075\t 2 -5 6\n", "61.075\t -2 5 -6\n", "61.075\t 4 0 -7\n", "61.075\t -2 -5 6\n", "61.075\t 4 -7 0\n", "61.075\t -7 4 0\n", "61.075\t -4 7 0\n", "61.075\t 0 -7 -4\n", "61.075\t 6 5 -2\n", "61.075\t -6 -2 -5\n", "61.075\t 6 -5 2\n", "61.075\t 2 5 6\n", "61.075\t 2 6 -5\n", "61.075\t 0 7 4\n", "61.075\t 6 -5 -2\n", "61.075\t 2 6 5\n", "61.075\t 7 -4 0\n", "61.075\t -5 2 6\n", "61.075\t 6 2 -5\n", "61.075\t 2 -5 -6\n", "61.075\t 5 -6 2\n", "61.075\t -2 6 5\n", "61.075\t 2 -6 -5\n", "61.075\t 5 2 -6\n", "61.075\t -5 6 -2\n", "61.075\t -7 0 4\n", "61.075\t -7 -4 0\n", "61.075\t 5 6 2\n", "61.075\t 0 -4 -7\n", "61.075\t -6 -2 5\n", "61.075\t -2 5 6\n", "61.075\t -2 -5 -6\n", "61.075\t 7 0 4\n", "61.075\t 4 0 7\n", "61.075\t -2 -6 5\n", "61.075\t 0 -4 7\n", "61.075\t 2 -6 5\n", "61.075\t -2 6 -5\n", "61.075\t -6 5 -2\n", "61.075\t 6 -2 5\n", "61.075\t -5 -2 -6\n", "61.075\t -6 -5 -2\n", "61.075\t 6 2 5\n", "61.075\t 0 -7 4\n", "61.075\t 4 7 0\n", "61.075\t -4 0 7\n", "61.075\t 5 -2 -6\n", "61.075\t 5 6 -2\n", "61.075\t 6 -2 -5\n", "61.075\t 0 4 7\n", "61.075\t 7 4 0\n", "61.075\t -6 2 5\n", "61.075\t 6 5 2\n", "61.075\t -4 0 -7\n", "61.075\t -4 -7 0\n", "61.075\t 0 4 -7\n", "61.075\t 2 5 -6\n", "61.075\t 5 2 6\n", "61.075\t 0 7 -4\n", "61.075\t -5 -6 2\n", "61.075\t -5 2 -6\n", "61.075\t -6 -5 2\n", "61.075\t 5 -6 -2\n", "61.075\t -6 5 2\n", "61.075\t 5 -2 6\n", "61.075\t -6 2 -5\n", "61.075\t -5 -2 6\n", "61.075\t -7 0 -4\n", "61.075\t -5 -6 -2\n", "61.075\t -5 6 2\n", "61.075\t 7 0 -4\n", "61.075\t 0 1 -8\n", "61.075\t 8 1 0\n", "61.075\t -1 0 -8\n", "61.075\t -8 0 -1\n", "61.075\t -1 0 8\n", "61.075\t 8 0 -1\n", "61.075\t 8 -1 0\n", "61.075\t 1 8 0\n", "61.075\t -1 -8 0\n", "61.075\t -8 1 0\n", "61.075\t -1 8 0\n", "61.075\t 0 1 8\n", "61.075\t 0 -8 -1\n", "61.075\t 0 8 -1\n", "61.075\t 0 8 1\n", "61.075\t 1 0 -8\n", "61.075\t 0 -1 8\n", "61.075\t 0 -1 -8\n", "61.075\t 1 -8 0\n", "61.075\t -8 -1 0\n", "61.075\t 8 0 1\n", "61.075\t 0 -8 1\n", "61.075\t -8 0 1\n", "61.075\t 1 0 8\n", "61.593\t 4 -1 7\n", "61.593\t 1 4 -7\n", "61.593\t -4 7 -1\n", "61.593\t -5 -5 4\n", "61.593\t -4 7 1\n", "61.593\t -7 4 -1\n", "61.593\t -4 5 5\n", "61.593\t 4 -1 -7\n", "61.593\t 1 -1 8\n", "61.593\t -7 4 1\n", "61.593\t 4 -5 -5\n", "61.593\t 1 1 8\n", "61.593\t 1 1 -8\n", "61.593\t 1 7 4\n", "61.593\t 5 -5 -4\n", "61.593\t -5 -4 -5\n", "61.593\t -4 1 7\n", "61.593\t 7 1 4\n", "61.593\t 1 4 7\n", "61.593\t 4 7 -1\n", "61.593\t 1 -1 -8\n", "61.593\t 1 7 -4\n", "61.593\t 4 -7 -1\n", "61.593\t -4 1 -7\n", "61.593\t 4 7 1\n", "61.593\t 5 4 -5\n", "61.593\t 7 4 1\n", "61.593\t 1 -7 4\n", "61.593\t 7 4 -1\n", "61.593\t -4 -1 7\n", "61.593\t -4 5 -5\n", "61.593\t 5 4 5\n", "61.593\t -1 7 4\n", "61.593\t 1 -4 -7\n", "61.593\t -4 -1 -7\n", "61.593\t 1 -4 7\n", "61.593\t -5 -5 -4\n", "61.593\t -7 1 4\n", "61.593\t -5 -4 5\n", "61.593\t 5 -4 5\n", "61.593\t 5 5 -4\n", "61.593\t 4 -7 1\n", "61.593\t 4 -5 5\n", "61.593\t -1 4 -7\n", "61.593\t -4 -7 1\n", "61.593\t -4 -7 -1\n", "61.593\t -1 1 8\n", "61.593\t -1 -4 -7\n", "61.593\t 4 5 5\n", "61.593\t -7 1 -4\n", "61.593\t 7 -1 -4\n", "61.593\t -4 -5 -5\n", "61.593\t -1 -7 4\n", "61.593\t 7 -4 -1\n", "61.593\t -1 1 -8\n", "61.593\t 7 -4 1\n", "61.593\t -7 -4 1\n", "61.593\t -7 -1 -4\n", "61.593\t -7 -4 -1\n", "61.593\t -1 4 7\n", "61.593\t 5 5 4\n", "61.593\t -1 -1 -8\n", "61.593\t 7 -1 4\n", "61.593\t -1 -1 8\n", "61.593\t 5 -5 4\n", "61.593\t 4 1 7\n", "61.593\t 4 1 -7\n", "61.593\t -1 7 -4\n", "61.593\t 1 -7 -4\n", "61.593\t -5 4 -5\n", "61.593\t 4 5 -5\n", "61.593\t -5 5 4\n", "61.593\t -1 -7 -4\n", "61.593\t -5 4 5\n", "61.593\t -5 5 -4\n", "61.593\t -4 -5 5\n", "61.593\t -1 -4 7\n", "61.593\t 7 1 -4\n", "61.593\t -7 -1 4\n", "61.593\t 5 -4 -5\n", "61.593\t 8 -1 1\n", "61.593\t -1 8 -1\n", "61.593\t 1 -8 1\n", "61.593\t -8 -1 -1\n", "61.593\t 1 -8 -1\n", "61.593\t 8 1 1\n", "61.593\t 8 1 -1\n", "61.593\t 1 8 1\n", "61.593\t 1 8 -1\n", "61.593\t -1 -8 -1\n", "61.593\t -1 -8 1\n", "61.593\t -8 1 -1\n", "61.593\t -8 1 1\n", "61.593\t -8 -1 1\n", "61.593\t 8 -1 -1\n", "61.593\t -1 8 1\n", "62.110\t 3 -3 7\n", "62.110\t -7 -3 -3\n", "62.110\t 7 -3 3\n", "62.110\t -3 -3 -7\n", "62.110\t -7 3 -3\n", "62.110\t -3 3 7\n", "62.110\t 3 3 -7\n", "62.110\t 3 3 7\n", "62.110\t -7 3 3\n", "62.110\t -3 -3 7\n", "62.110\t 3 7 3\n", "62.110\t 7 3 3\n", "62.110\t 3 -7 3\n", "62.110\t -3 7 -3\n", "62.110\t -3 -7 3\n", "62.110\t -3 7 3\n", "62.110\t 7 3 -3\n", "62.110\t 3 -7 -3\n", "62.110\t -3 3 -7\n", "62.110\t 3 -3 -7\n", "62.110\t 3 7 -3\n", "62.110\t 7 -3 -3\n", "62.110\t -3 -7 -3\n", "62.110\t -7 -3 3\n", "62.623\t 2 0 -8\n", "62.623\t -4 -6 4\n", "62.623\t -4 -4 -6\n", "62.623\t 4 6 4\n", "62.623\t 2 8 0\n", "62.623\t -6 -4 -4\n", "62.623\t -2 0 8\n", "62.623\t -6 -4 4\n", "62.623\t -8 -2 0\n", "62.623\t -4 -4 6\n", "62.623\t 4 6 -4\n", "62.623\t -6 4 -4\n", "62.623\t -4 6 4\n", "62.623\t -8 0 2\n", "62.623\t -4 6 -4\n", "62.623\t 4 4 -6\n", "62.623\t -4 4 6\n", "62.623\t 2 -8 0\n", "62.623\t 0 -2 -8\n", "62.623\t -4 4 -6\n", "62.623\t 0 -2 8\n", "62.623\t -2 0 -8\n", "62.623\t -2 8 0\n", "62.623\t -2 -8 0\n", "62.623\t 0 -8 2\n", "62.623\t 8 0 -2\n", "62.623\t -6 4 4\n", "62.623\t 0 2 -8\n", "62.623\t 4 -4 -6\n", "62.623\t 6 4 4\n", "62.623\t 8 2 0\n", "62.623\t 8 -2 0\n", "62.623\t 6 -4 -4\n", "62.623\t 0 2 8\n", "62.623\t 0 8 2\n", "62.623\t 6 4 -4\n", "62.623\t 6 -4 4\n", "62.623\t 4 4 6\n", "62.623\t -8 2 0\n", "62.623\t 0 8 -2\n", "62.623\t 4 -6 4\n", "62.623\t -8 0 -2\n", "62.623\t 4 -6 -4\n", "62.623\t 2 0 8\n", "62.623\t 8 0 2\n", "62.623\t -4 -6 -4\n", "62.623\t 0 -8 -2\n", "62.623\t 4 -4 6\n", "63.135\t -4 -7 2\n", "63.135\t -4 -7 -2\n", "63.135\t -7 -4 -2\n", "63.135\t 7 -4 2\n", "63.135\t -7 -4 2\n", "63.135\t 7 -4 -2\n", "63.135\t -2 -7 -4\n", "63.135\t -2 7 -4\n", "63.135\t 4 7 -2\n", "63.135\t 2 7 4\n", "63.135\t 2 7 -4\n", "63.135\t -2 7 4\n", "63.135\t -4 7 -2\n", "63.135\t -4 7 2\n", "63.135\t 4 -7 2\n", "63.135\t -7 -2 -4\n", "63.135\t 4 7 2\n", "63.135\t 2 -7 -4\n", "63.135\t 4 -7 -2\n", "63.135\t -7 2 -4\n", "63.135\t 7 4 2\n", "63.135\t 7 2 -4\n", "63.135\t -7 4 2\n", "63.135\t 7 2 4\n", "63.135\t -7 -2 4\n", "63.135\t 7 -2 4\n", "63.135\t 7 -2 -4\n", "63.135\t -7 4 -2\n", "63.135\t -2 -7 4\n", "63.135\t -7 2 4\n", "63.135\t 7 4 -2\n", "63.135\t 2 -7 4\n", "63.135\t 1 8 -2\n", "63.135\t 8 -2 1\n", "63.135\t 1 2 8\n", "63.135\t 1 2 -8\n", "63.135\t -4 2 7\n", "63.135\t -1 -8 -2\n", "63.135\t 2 4 -7\n", "63.135\t 2 -8 -1\n", "63.135\t 1 8 2\n", "63.135\t 2 8 -1\n", "63.135\t 2 -1 8\n", "63.135\t -4 -2 7\n", "63.135\t -4 -2 -7\n", "63.135\t 2 -1 -8\n", "63.135\t 2 -4 7\n", "63.135\t 2 -4 -7\n", "63.135\t 2 1 8\n", "63.135\t 2 1 -8\n", "63.135\t 2 4 7\n", "63.135\t -2 1 8\n", "63.135\t 2 -8 1\n", "63.135\t -4 2 -7\n", "63.135\t 8 -1 -2\n", "63.135\t 2 8 1\n", "63.135\t -8 -1 -2\n", "63.135\t 4 -2 7\n", "63.135\t 4 2 -7\n", "63.135\t -1 8 2\n", "63.135\t -1 8 -2\n", "63.135\t -8 2 1\n", "63.135\t -8 2 -1\n", "63.135\t 4 2 7\n", "63.135\t -1 2 8\n", "63.135\t -1 2 -8\n", "63.135\t -1 -2 -8\n", "63.135\t 8 2 1\n", "63.135\t -1 -8 2\n", "63.135\t 8 2 -1\n", "63.135\t -2 -8 -1\n", "63.135\t -2 -8 1\n", "63.135\t 8 1 2\n", "63.135\t -8 -1 2\n", "63.135\t 4 -2 -7\n", "63.135\t 1 -8 -2\n", "63.135\t -1 -2 8\n", "63.135\t 8 -2 -1\n", "63.135\t -2 -4 -7\n", "63.135\t 1 -8 2\n", "63.135\t -2 -4 7\n", "63.135\t 8 1 -2\n", "63.135\t -8 -2 1\n", "63.135\t -2 8 1\n", "63.135\t 8 -1 2\n", "63.135\t -2 8 -1\n", "63.135\t -8 -2 -1\n", "63.135\t -2 -1 -8\n", "63.135\t -2 -1 8\n", "63.135\t -2 4 -7\n", "63.135\t -2 1 -8\n", "63.135\t -8 1 -2\n", "63.135\t 1 -2 8\n", "63.135\t -2 4 7\n", "63.135\t 1 -2 -8\n", "63.135\t -8 1 2\n", "63.644\t 3 -6 -5\n", "63.644\t -5 -3 -6\n", "63.644\t 5 -6 3\n", "63.644\t 5 -3 6\n", "63.644\t -3 5 6\n", "63.644\t 5 -3 -6\n", "63.644\t 3 5 -6\n", "63.644\t -3 6 5\n", "63.644\t 5 -6 -3\n", "63.644\t 6 5 -3\n", "63.644\t -5 -6 3\n", "63.644\t -3 -5 6\n", "63.644\t 6 5 3\n", "63.644\t -5 6 -3\n", "63.644\t -5 3 6\n", "63.644\t -3 5 -6\n", "63.644\t -5 -3 6\n", "63.644\t -3 -5 -6\n", "63.644\t -3 -6 -5\n", "63.644\t -3 6 -5\n", "63.644\t -3 -6 5\n", "63.644\t 6 -5 3\n", "63.644\t -5 6 3\n", "63.644\t -5 3 -6\n", "63.644\t 6 3 5\n", "63.644\t 5 3 -6\n", "63.644\t 5 3 6\n", "63.644\t 6 -5 -3\n", "63.644\t 3 6 -5\n", "63.644\t 3 6 5\n", "63.644\t 5 6 3\n", "63.644\t 3 5 6\n", "63.644\t -5 -6 -3\n", "63.644\t -6 -5 3\n", "63.644\t 3 -5 6\n", "63.644\t -6 -5 -3\n", "63.644\t 5 6 -3\n", "63.644\t -6 -3 5\n", "63.644\t 3 -6 5\n", "63.644\t -6 5 3\n", "63.644\t -6 -3 -5\n", "63.644\t 6 3 -5\n", "63.644\t 6 -3 -5\n", "63.644\t 6 -3 5\n", "63.644\t -6 3 -5\n", "63.644\t -6 3 5\n", "63.644\t -6 5 -3\n", "63.644\t 3 -5 -6\n", "64.655\t 0 6 6\n", "64.655\t 0 -6 6\n", "64.655\t 0 -6 -6\n", "64.655\t 6 0 6\n", "64.655\t -6 -6 0\n", "64.655\t 6 -6 0\n", "64.655\t -6 0 6\n", "64.655\t 6 6 0\n", "64.655\t -6 6 0\n", "64.655\t -6 0 -6\n", "64.655\t 0 6 -6\n", "64.655\t 6 0 -6\n", "64.655\t 2 2 -8\n", "64.655\t -8 -2 2\n", "64.655\t -2 8 -2\n", "64.655\t 2 -8 -2\n", "64.655\t -2 -2 -8\n", "64.655\t 2 2 8\n", "64.655\t -2 2 8\n", "64.655\t -2 2 -8\n", "64.655\t 2 -2 -8\n", "64.655\t -2 -2 8\n", "64.655\t -2 -8 -2\n", "64.655\t 8 2 2\n", "64.655\t -2 -8 2\n", "64.655\t 8 2 -2\n", "64.655\t -8 2 -2\n", "64.655\t -8 2 2\n", "64.655\t 2 8 2\n", "64.655\t 2 -2 8\n", "64.655\t 2 8 -2\n", 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2\n", "70.565\t 2 -8 -4\n", "70.565\t 4 8 2\n", "70.565\t -2 4 -8\n", "70.565\t -2 8 4\n", "70.565\t -8 -4 2\n", "70.565\t -8 -2 -4\n", "70.565\t -8 -2 4\n", "70.565\t -2 -4 8\n", "70.565\t -4 -2 8\n", "70.565\t -2 -8 -4\n", "70.565\t -4 -8 -2\n", "70.565\t 8 2 -4\n", "70.565\t 2 -8 4\n", "70.565\t -8 2 4\n", "70.565\t -4 -8 2\n", "70.565\t 4 8 -2\n", "70.565\t -4 2 -8\n", "70.565\t -8 4 -2\n", "70.565\t -2 -4 -8\n", "70.565\t -4 8 -2\n", "70.565\t -4 8 2\n", "70.565\t 2 -4 -8\n", "70.565\t 4 2 -8\n", "70.565\t 4 -8 -2\n", "70.565\t 4 2 8\n", "70.565\t 8 -2 -4\n", "70.565\t -2 4 8\n", "70.565\t 2 -4 8\n", "70.565\t 4 -8 2\n", "70.565\t -4 2 8\n", "70.565\t 8 2 4\n", "70.565\t 4 -2 -8\n", "70.565\t 2 4 8\n", "70.565\t 4 -2 8\n", "70.565\t 2 4 -8\n", "70.565\t 2 8 -4\n", "70.565\t -8 2 -4\n", "70.565\t -8 4 2\n", "70.565\t -2 8 -4\n", "70.565\t 2 8 4\n", "70.565\t -2 -8 4\n", "71.047\t 0 6 7\n", "71.047\t -2 0 9\n", "71.047\t -2 0 -9\n", "71.047\t 9 0 2\n", "71.047\t 0 9 -2\n", "71.047\t 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1\n", "71.527\t -9 2 1\n", "71.527\t 7 1 6\n", "71.527\t -1 -9 -2\n", "71.527\t -1 -7 6\n", "71.527\t 9 2 -1\n", "71.527\t 9 1 -2\n", "71.527\t 1 -7 6\n", "71.527\t 1 6 7\n", "71.527\t 9 -2 -1\n", "71.527\t 1 2 -9\n", "71.527\t 1 7 -6\n", "71.527\t -2 -9 1\n", "71.527\t -1 -6 7\n", "71.527\t -2 -9 -1\n", "71.527\t 7 -1 -6\n", "71.527\t -1 6 7\n", "71.527\t -6 -1 7\n", "71.527\t -2 -1 -9\n", "71.527\t -9 1 -2\n", "71.527\t -9 -1 2\n", "71.527\t -2 1 9\n", "71.527\t 6 -1 7\n", "71.527\t 6 -1 -7\n", "71.527\t 5 -5 -6\n", "71.527\t -1 -6 -7\n", "71.527\t -5 -5 -6\n", "71.527\t 5 -5 6\n", "71.527\t -5 -5 6\n", "71.527\t -9 -1 -2\n", "71.527\t -2 1 -9\n", "71.527\t -1 7 6\n", "71.527\t -1 -7 -6\n", "71.527\t -6 1 7\n", "71.527\t -2 9 -1\n", "71.527\t -2 9 1\n", "71.527\t -6 1 -7\n", "71.527\t 7 -1 6\n", "71.527\t -2 -1 9\n", "71.527\t -6 -1 -7\n", "71.527\t 5 5 6\n", "71.527\t -9 1 2\n", "71.527\t 1 -6 -7\n", "71.527\t 7 1 -6\n", "71.527\t -1 7 -6\n", "71.527\t 1 -2 9\n", "71.527\t 6 1 -7\n", "71.527\t 2 9 1\n", "71.527\t 1 2 9\n", "71.527\t 1 -7 -6\n", "71.527\t -5 5 6\n", "71.527\t 1 -9 2\n", "71.527\t -1 2 9\n", "71.527\t 9 2 1\n", "71.527\t -5 5 -6\n", "71.527\t 1 -9 -2\n", "71.527\t 2 -9 1\n", "71.527\t 6 1 7\n", "71.527\t 1 7 6\n", "71.527\t 2 -9 -1\n", "71.527\t 9 -1 2\n", "71.527\t -1 9 -2\n", "71.527\t -7 -1 -6\n", "71.527\t 1 9 -2\n", "71.527\t 1 -2 -9\n", "71.527\t 2 9 -1\n", "71.527\t -7 -1 6\n", "71.527\t 9 -1 -2\n", "71.527\t 1 -6 7\n", "71.527\t 1 9 2\n", "71.527\t -1 2 -9\n", "71.527\t -7 1 -6\n", "71.527\t -1 -2 -9\n", "71.527\t -7 1 6\n", "71.527\t 2 -1 9\n", "71.527\t 9 1 2\n", "71.527\t 2 1 9\n", "71.527\t -1 -2 9\n", "71.527\t -1 6 -7\n", "71.527\t 9 -2 1\n", "71.527\t 2 -1 -9\n", "71.527\t 1 6 -7\n", "71.527\t -1 9 2\n", "71.527\t 2 1 -9\n", "71.527\t 6 -5 5\n", "71.527\t 5 -6 5\n", "71.527\t -7 6 1\n", "71.527\t -5 6 5\n", "71.527\t -7 -6 -1\n", "71.527\t -6 7 -1\n", "71.527\t 5 -6 -5\n", "71.527\t -6 7 1\n", "71.527\t 5 6 5\n", "71.527\t -6 5 5\n", "71.527\t 6 7 -1\n", "71.527\t 6 5 5\n", "71.527\t 5 6 -5\n", "71.527\t -7 -6 1\n", "71.527\t 6 -7 -1\n", "71.527\t 6 5 -5\n", "71.527\t -6 -7 1\n", "71.527\t -6 -7 -1\n", "71.527\t -5 -6 -5\n", "71.527\t -5 -6 5\n", "71.527\t -7 6 -1\n", "71.527\t 7 6 1\n", "71.527\t 6 7 1\n", "71.527\t -6 -5 -5\n", "71.527\t -6 5 -5\n", "71.527\t -5 6 -5\n", "71.527\t 7 -6 -1\n", "71.527\t 6 -5 -5\n", "71.527\t 6 -7 1\n", "71.527\t 7 -6 1\n", "71.527\t 7 6 -1\n", "71.527\t -6 -5 5\n", "72.484\t 6 4 -6\n", "72.484\t 4 -6 6\n", "72.484\t -6 4 -6\n", "72.484\t 6 -6 -4\n", "72.484\t -6 6 4\n", "72.484\t 6 6 -4\n", "72.484\t -6 6 -4\n", "72.484\t -6 -6 4\n", "72.484\t 6 -6 4\n", "72.484\t -6 -6 -4\n", "72.484\t -4 6 6\n", "72.484\t 6 4 6\n", "72.484\t -6 4 6\n", "72.484\t -6 -4 6\n", "72.484\t 4 -6 -6\n", "72.484\t 6 -4 6\n", "72.484\t -4 6 -6\n", "72.484\t 6 -4 -6\n", "72.484\t -4 -6 -6\n", "72.484\t 4 6 -6\n", "72.484\t 6 6 4\n", "72.484\t -4 -6 6\n", "72.484\t -6 -4 -6\n", "72.484\t 4 6 6\n", 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4\n", "87.319\t 10 2 -4\n", "87.319\t -4 -10 2\n", "87.319\t 10 -2 -4\n", "87.319\t -2 4 10\n", "87.319\t -10 -2 4\n", "87.319\t -2 -4 -10\n", "87.319\t 2 -10 -4\n", "87.319\t -10 -2 -4\n", "87.319\t -4 10 -2\n", "87.319\t -2 10 -4\n", "87.319\t 2 10 4\n", "87.319\t -2 10 4\n", "87.319\t 4 -2 -10\n", "87.319\t 2 4 -10\n", "87.319\t -10 4 2\n", "87.319\t -2 -10 4\n", "87.319\t 10 2 4\n", "87.319\t 4 -10 2\n", "87.319\t 4 2 10\n", "87.319\t 10 -4 -2\n", "87.319\t -4 -2 -10\n", "87.319\t 10 -4 2\n", "87.319\t -10 -4 2\n", "87.319\t -10 -4 -2\n", "87.319\t 2 -4 10\n", "87.319\t -4 2 10\n", "87.319\t -10 2 4\n", "87.319\t -10 4 -2\n", "87.319\t 2 10 -4\n", "87.319\t -2 -10 -4\n", "87.319\t 10 4 -2\n", "87.319\t 4 2 -10\n", "87.319\t 4 -10 -2\n", "87.319\t -10 2 -4\n", "87.319\t -4 2 -10\n", "87.319\t 4 -2 10\n", "87.775\t -6 -9 -2\n", "87.775\t -6 -2 9\n", "87.775\t 2 6 9\n", "87.775\t 9 -2 6\n", "87.775\t -7 -6 6\n", "87.775\t -2 -6 -9\n", "87.775\t 6 9 2\n", "87.775\t 6 -6 -7\n", "87.775\t 2 -9 -6\n", "87.775\t -6 -9 2\n", "87.775\t 6 -6 7\n", "87.775\t -2 -6 9\n", "87.775\t -6 -2 -9\n", "87.775\t -6 -7 -6\n", "87.775\t -11 0 0\n", "87.775\t 6 -9 2\n", "87.775\t -2 6 -9\n", "87.775\t 6 2 9\n", "87.775\t -2 -9 6\n", "87.775\t -2 9 6\n", "87.775\t -6 -7 6\n", "87.775\t 2 9 6\n", "87.775\t 9 2 -6\n", "87.775\t 6 -9 -2\n", "87.775\t 6 -7 6\n", "87.775\t 2 6 -9\n", "87.775\t -6 -6 -7\n", "87.775\t -6 -6 7\n", "87.775\t 0 11 0\n", "87.775\t -2 6 9\n", "87.775\t 7 -6 -6\n", "87.775\t -2 -9 -6\n", "87.775\t -7 -6 -6\n", "87.775\t -9 -6 -2\n", "87.775\t 2 9 -6\n", "87.775\t 7 -6 6\n", "87.775\t -9 -6 2\n", "87.775\t 9 2 6\n", "87.775\t 9 -2 -6\n", "87.775\t -6 2 -9\n", "87.775\t -2 9 -6\n", "87.775\t 0 0 11\n", "87.775\t -9 -2 6\n", "87.775\t 9 6 2\n", "87.775\t 6 -7 -6\n", "87.775\t -7 6 6\n", "87.775\t -6 7 6\n", "87.775\t 7 6 6\n", "87.775\t -6 6 -7\n", "87.775\t 6 -2 -9\n", "87.775\t -7 6 -6\n", "87.775\t -9 2 -6\n", "87.775\t 6 7 -6\n", "87.775\t -6 7 -6\n", "87.775\t 7 6 -6\n", "87.775\t -9 2 6\n", "87.775\t 6 9 -2\n", "87.775\t 6 6 -7\n", "87.775\t 9 -6 -2\n", "87.775\t 2 -6 9\n", "87.775\t 6 2 -9\n", "87.775\t 6 -2 9\n", "87.775\t 0 -11 0\n", "87.775\t -6 9 2\n", "87.775\t -9 6 -2\n", "87.775\t -9 6 2\n", "87.775\t 6 6 7\n", "87.775\t 9 6 -2\n", "87.775\t 6 7 6\n", "87.775\t -6 2 9\n", "87.775\t -6 9 -2\n", "87.775\t 9 -6 2\n", "87.775\t -9 -2 -6\n", "87.775\t 2 -6 -9\n", "87.775\t 0 0 -11\n", "87.775\t -6 6 7\n", "87.775\t 11 0 0\n", "87.775\t 2 -9 6\n", "88.230\t 5 4 -9\n", "88.230\t 7 -3 -8\n", "88.230\t -11 0 1\n", "88.230\t -3 -8 7\n", "88.230\t -1 0 11\n", "88.230\t -1 11 0\n", "88.230\t 9 -5 -4\n", "88.230\t 4 5 9\n", "88.230\t -5 -4 -9\n", "88.230\t -3 7 -8\n", "88.230\t 8 7 3\n", "88.230\t -9 -4 -5\n", "88.230\t 11 0 1\n", "88.230\t 8 -3 7\n", "88.230\t -9 4 -5\n", "88.230\t 0 -11 -1\n", "88.230\t -9 -5 4\n", "88.230\t 1 0 11\n", "88.230\t -11 0 -1\n", "88.230\t -3 -8 -7\n", "88.230\t 9 5 4\n", "88.230\t -9 -5 -4\n", "88.230\t -9 -4 5\n", "88.230\t 11 -1 0\n", "88.230\t -3 -7 -8\n", "88.230\t -8 -7 -3\n", "88.230\t 8 -7 -3\n", "88.230\t 11 0 -1\n", "88.230\t 9 5 -4\n", "88.230\t -11 1 0\n", "88.230\t 0 -1 11\n", "88.230\t 4 -9 5\n", "88.230\t 7 -3 8\n", "88.230\t 8 -3 -7\n", "88.230\t 9 -5 4\n", "88.230\t -1 0 -11\n", "88.230\t -5 -4 9\n", "88.230\t -3 -7 8\n", "88.230\t -4 -5 9\n", "88.230\t -7 -8 -3\n", "88.230\t -3 8 -7\n", "88.230\t -3 7 8\n", "88.230\t -7 -8 3\n", "88.230\t -8 -7 3\n", "88.230\t 8 7 -3\n", "88.230\t 0 -11 1\n", "88.230\t 4 -9 -5\n", "88.230\t 0 1 -11\n", "88.230\t 4 9 -5\n", "88.230\t 9 4 5\n", "88.230\t 4 9 5\n", "88.230\t -7 3 8\n", "88.230\t -5 -9 4\n", "88.230\t -7 3 -8\n", "88.230\t -4 9 5\n", "88.230\t -3 8 7\n", "88.230\t 8 3 7\n", "88.230\t 1 0 -11\n", "88.230\t 4 5 -9\n", "88.230\t 0 1 11\n", "88.230\t 11 1 0\n", "88.230\t -5 -9 -4\n", "88.230\t 7 3 -8\n", "88.230\t -9 5 4\n", "88.230\t -1 -11 0\n", "88.230\t 4 -5 -9\n", "88.230\t -9 4 5\n", "88.230\t -5 4 -9\n", "88.230\t 0 -1 -11\n", "88.230\t 9 -4 -5\n", "88.230\t 3 -7 -8\n", "88.230\t -9 5 -4\n", "88.230\t 9 4 -5\n", "88.230\t -8 3 7\n", "88.230\t 1 11 0\n", "88.230\t -8 -3 -7\n", "88.230\t 3 -8 7\n", "88.230\t 0 11 1\n", "88.230\t -8 7 3\n", "88.230\t 5 -4 9\n", "88.230\t 8 -7 3\n", "88.230\t 3 -7 8\n", "88.230\t 0 11 -1\n", "88.230\t -8 3 -7\n", "88.230\t 5 -4 -9\n", "88.230\t 1 -11 0\n", "88.230\t -4 5 -9\n", "88.230\t -8 7 -3\n", "88.230\t 7 8 -3\n", "88.230\t 5 9 -4\n", "88.230\t 5 9 4\n", "88.230\t 5 4 9\n", "88.230\t -4 9 -5\n", "88.230\t 8 3 -7\n", "88.230\t -4 5 9\n", "88.230\t 3 7 8\n", "88.230\t 7 3 8\n", "88.230\t 3 7 -8\n", "88.230\t 5 -9 -4\n", "88.230\t -5 4 9\n", "88.230\t -7 -3 -8\n", "88.230\t -7 -3 8\n", "88.230\t 7 -8 -3\n", "88.230\t -8 -3 7\n", "88.230\t -5 9 -4\n", "88.230\t -5 9 4\n", "88.230\t -7 8 -3\n", "88.230\t 7 -8 3\n", "88.230\t 7 8 3\n", "88.230\t -11 -1 0\n", "88.230\t -7 8 3\n", "88.230\t -4 -9 5\n", "88.230\t -4 -9 -5\n", "88.230\t 3 8 7\n", "88.230\t 3 8 -7\n", "88.230\t -4 -5 -9\n", "88.230\t 9 -4 5\n", "88.230\t 5 -9 4\n", "88.230\t 4 -5 9\n", "88.230\t 3 -8 -7\n", "88.685\t 5 7 -7\n", "88.685\t 11 -1 1\n", "88.685\t 1 11 1\n", "88.685\t 11 -1 -1\n", "88.685\t 7 5 -7\n", "88.685\t -1 1 11\n", "88.685\t 7 7 5\n", "88.685\t -11 -1 -1\n", "88.685\t -5 -7 -7\n", "88.685\t -5 7 -7\n", "88.685\t -5 -7 7\n", "88.685\t 11 1 -1\n", "88.685\t -7 -5 -7\n", "88.685\t 7 5 7\n", "88.685\t -7 5 -7\n", "88.685\t -1 -1 -11\n", "88.685\t -1 -1 11\n", "88.685\t -7 5 7\n", "88.685\t 5 7 7\n", "88.685\t 7 -7 5\n", "88.685\t -11 -1 1\n", "88.685\t 1 11 -1\n", "88.685\t -1 1 -11\n", "88.685\t 1 -11 -1\n", "88.685\t -7 -7 5\n", "88.685\t -5 7 7\n", "88.685\t 1 -11 1\n", "88.685\t -1 -11 1\n", "88.685\t 5 -7 -7\n", "88.685\t -1 -11 -1\n", "88.685\t -7 7 5\n", "88.685\t 7 -7 -5\n", "88.685\t 7 7 -5\n", "88.685\t -11 1 1\n", "88.685\t 7 -5 7\n", "88.685\t 1 -1 -11\n", "88.685\t 1 -1 11\n", "88.685\t -7 -7 -5\n", "88.685\t -11 1 -1\n", "88.685\t 5 -7 7\n", "88.685\t -1 11 -1\n", "88.685\t 1 1 11\n", "88.685\t -1 11 1\n", "88.685\t -7 7 -5\n", "88.685\t 7 -5 -7\n", "88.685\t -7 -5 7\n", "88.685\t 1 1 -11\n", "88.685\t 11 1 1\n", "89.596\t -11 2 0\n", "89.596\t -11 -2 0\n", "89.596\t 5 -6 8\n", "89.596\t 8 5 -6\n", "89.596\t -6 5 8\n", "89.596\t 10 5 0\n", "89.596\t 0 -11 -2\n", "89.596\t 6 5 -8\n", "89.596\t 4 3 -10\n", "89.596\t 6 -8 -5\n", "89.596\t 4 10 3\n", "89.596\t 10 3 -4\n", "89.596\t 5 -8 -6\n", "89.596\t 2 -11 0\n", "89.596\t 4 3 10\n", "89.596\t 11 -2 0\n", "89.596\t 0 10 -5\n", "89.596\t -3 -10 -4\n", "89.596\t 10 0 5\n", "89.596\t 10 -4 -3\n", "89.596\t 3 -4 -10\n", "89.596\t -3 -10 4\n", "89.596\t -5 8 6\n", "89.596\t 10 -5 0\n", "89.596\t 2 0 11\n", "89.596\t -4 -3 10\n", "89.596\t 3 4 -10\n", "89.596\t 0 11 -2\n", "89.596\t -5 10 0\n", "89.596\t 0 -2 11\n", "89.596\t 0 11 2\n", "89.596\t -3 4 10\n", "89.596\t 0 10 5\n", "89.596\t -6 -5 8\n", "89.596\t -6 -8 5\n", "89.596\t -8 -6 5\n", "89.596\t 5 0 10\n", "89.596\t 8 6 5\n", "89.596\t 11 0 2\n", "89.596\t 11 2 0\n", "89.596\t -8 -6 -5\n", "89.596\t 11 0 -2\n", "89.596\t 10 3 4\n", "89.596\t 10 4 3\n", "89.596\t -2 0 11\n", "89.596\t -11 0 2\n", "89.596\t 4 10 -3\n", "89.596\t 6 5 8\n", "89.596\t 5 -8 6\n", "89.596\t -4 -3 -10\n", "89.596\t -2 11 0\n", "89.596\t 4 -3 10\n", "89.596\t 5 -6 -8\n", "89.596\t 10 4 -3\n", "89.596\t -6 5 -8\n", "89.596\t -6 -8 -5\n", "89.596\t -3 10 -4\n", "89.596\t -8 -5 6\n", "89.596\t 6 -8 5\n", "89.596\t 6 8 -5\n", "89.596\t -3 10 4\n", "89.596\t -6 -5 -8\n", "89.596\t 3 -4 10\n", "89.596\t -2 0 -11\n", "89.596\t -8 -5 -6\n", "89.596\t -11 0 -2\n", "89.596\t 5 0 -10\n", "89.596\t 8 5 6\n", "89.596\t 8 6 -5\n", "89.596\t 5 -10 0\n", "89.596\t -10 -3 4\n", "89.596\t -4 -10 -3\n", "89.596\t -10 4 3\n", "89.596\t 6 -5 8\n", "89.596\t 0 -5 10\n", "89.596\t -5 -6 -8\n", "89.596\t -5 -6 8\n", "89.596\t 0 -10 -5\n", "89.596\t 0 5 -10\n", "89.596\t -8 6 5\n", "89.596\t 0 -11 2\n", "89.596\t -10 -4 -3\n", "89.596\t 4 -10 3\n", "89.596\t 0 -5 -10\n", "89.596\t -10 3 4\n", "89.596\t -5 6 8\n", "89.596\t -10 -3 -4\n", "89.596\t -6 8 -5\n", "89.596\t -8 5 6\n", "89.596\t 5 6 -8\n", "89.596\t 10 -3 4\n", "89.596\t -2 -11 0\n", "89.596\t 10 0 -5\n", "89.596\t 10 -4 3\n", "89.596\t -8 6 -5\n", "89.596\t 0 5 10\n", "89.596\t -4 -10 3\n", "89.596\t -4 10 -3\n", "89.596\t 0 2 11\n", "89.596\t -10 4 -3\n", "89.596\t 0 -10 5\n", "89.596\t -8 5 -6\n", "89.596\t -10 -5 0\n", "89.596\t 8 -5 6\n", "89.596\t -6 8 5\n", "89.596\t -4 3 -10\n", "89.596\t 10 -3 -4\n", "89.596\t 5 10 0\n", "89.596\t -5 6 -8\n", "89.596\t -5 0 10\n", "89.596\t 0 -2 -11\n", "89.596\t 2 11 0\n", "89.596\t -10 0 5\n", "89.596\t 8 -5 -6\n", "89.596\t 3 -10 4\n", "89.596\t -5 0 -10\n", "89.596\t 6 8 5\n", "89.596\t 6 -5 -8\n", "89.596\t 5 8 -6\n", "89.596\t 5 8 6\n", "89.596\t -10 5 0\n", "89.596\t -4 3 10\n", "89.596\t -5 -8 -6\n", "89.596\t 3 -10 -4\n", "89.596\t -3 4 -10\n", "89.596\t 8 -6 5\n", "89.596\t 3 10 -4\n", "89.596\t 2 0 -11\n", "89.596\t -5 8 -6\n", "89.596\t 5 6 8\n", "89.596\t -10 3 -4\n", "89.596\t 4 -10 -3\n", "89.596\t -10 -4 3\n", "89.596\t 0 2 -11\n", "89.596\t -5 -8 6\n", "89.596\t -3 -4 -10\n", "89.596\t -10 0 -5\n", "89.596\t 8 -6 -5\n", "89.596\t -4 10 3\n", "89.596\t 3 4 10\n", "89.596\t 3 10 4\n", "89.596\t -5 -10 0\n", "89.596\t -3 -4 10\n", "89.596\t 4 -3 -10\n" ] } ], "source": [ "# print the peaks and planes that generated the particular peaks, with no grouping\n", "print(\" 2θ \")\n", "for peak, hkl in zip(crystal.pxrd.peak_positions, crystal.pxrd.hkls):\n", " hkl_str = ' '.join([\"{: d}\".format(int(ind)) for ind in hkl])\n", " print(f\"{peak:1.3f}\\t {hkl_str}\")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# match with GSAS for my particular example phase, differences should only arise from broadening\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "from matador.config import set_settings\n", "\n", "mpl.rcParams.update(mpl.rcParamsDefault)\n", "set_settings({\"plotting\": {\"default_style\": \"matador\"}})\n", "gsas_data = \"./cif_test.txt\"\n", "gsas = np.loadtxt(gsas_data, skiprows=1)\n", "fig, ax = plt.subplots() \n", "plt.plot(gsas[:, 0], gsas[:, 1] / np.max(gsas[:, 1]), ls='--', label='GSAS', alpha=0.5)\n", "plot_pxrd(crystal.pxrd, ax=ax, text_offset=0.4, alpha=0.5)\n", "plt.legend();" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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79+8jLCwMnTp1AgCL21gqiC7i7Nmz4tmzZ50dBlGpFvPnP+JHH+4QP/pwh7NDKXV0++3wwWvODoXI5anVavH69euiQqEwmJeUlCTWq1dPnDVrliiKorhq1SoxJCRE7N+/vxgXFyfu379fDAsLEz/77DOj67a1/GeffSY2btxYvHTpkpiXlyd26dJF/O2330RRFMUlS5aI//rXvxyz0UasW7dOHD58uHjixAlx//79YocOHUzGacrZs2fF6OhosW3btuKcOXOMlim4jc5mbb7GHkwiIiKyiSAI6N27NwIDA7F9+3a9nkjdNaUtWrQAoL3eNCsrCwsXLpTG8ZwyZQqmTJmCadOmGVw+YG15URQxd+5cbNy4EcuWLcMLL7yApUuXonbt2ujSpUux7wPdXd579+6VHovp6emJd999F++//77V1882atQIAJCbm4upU6diypQp0v40to2lBRNMorKEd/cQUQkQBAEDBw7Et99+i549e6Jdu3aQy+U4deoUTp8+jbZt20pP+KlWrRrc3Nz0Bol/7rnnkJeXh9TUVINEzJryGo0GM2bMwI4dO7B06VLpuscdO3YgJSVFGtheqVRCrVZLTzxypPPnz8PPz0/vmesNGzaEWq3GnTt3zCaYycnJOH/+PDp06CBNq1u3LpRKJbKyshAQEGByG0sLJphkkzu303Hj+iO0avOss0MhI3TpJe/1IaLi9tFHH6FOnTqIjIzEli1boFKpEBQUhEmTJmH48OHSTUNNmjSBSqWSrt0EtGNA+vj4oFKlSgbrtab8559/jh07dmDFihUICwuTll23bh1UKpX0+vvvv8f58+exaNEih29/tWrVkJGRgfv376NatWpSnIDhk5UKu3LlCsaPH4+DBw+icuXKALRPRwoICJAGqTe1jaUFE0yyyReLDgIAXmoQiEpPeTs5GiIichaZTIZ+/fqhX79+Zss9++yz6NChA6ZNm4b//Oc/yM3NxaJFi9C/f3/pkZJpaWmQy+Xw8/OzWP706dP44YcfMGnSJDRs2BApKSlSXTVq1NCru2LFivDy8nLIYPWFNWnSBPXq1cOUKVMQERGB3NxczJw5E7169bL4JKPmzZujbt26iIiIQEREBJKSkrB48WKMHj0aAMxuY9WqVR2+LcWBCSbZRaFUOzsEMoZnyInIBS1YsABz587FsGHD4Obmht69e2PixInS/PHjx6NGjRr4/PPPLZbXjTG6ePFiLF68WK+eCxculNhz0N3c3LB69WrMmzcPw4YNg7u7Ozp37ozJkydbXNbd3R2rV6/G7Nmz0a9fP/j4+GDYsGEYOnQoANfZxqIQRNH2i7Zef/119OjRAz179kTdunUdEsi5c+cAPLnYlVzTlAk7AQCTI9qjWqCvk6OhwqL/uIQ/fr8EmUzA54u7WV6AJLpju1ffl9Hm1eecHA0RkWuyNl+z60k+MpkM//vf/9C9e3e8+eabWLdunTSwKpUPIrvKXBLv8SEiIldgV4IZHR2Nn376CQMHDsSdO3cwd+5ctGvXDqNHj8bvv/8OhULh6DjJ1TCRMSnu+E3cu5vpnMrz24U3+RARkTPZfRI/JCQEISEhmDFjBg4ePIjt27dj//792L9/P3x9fdG5c2f06tULzZs3d2S85CLYU2ZcWloOIjedAQAsWNrdiZEwwyQiIucp8lWibm5uCAsLQ1hYGBQKBaKjo7Fo0SL8+uuv+PXXX/HMM8+gX79+GDx4MCpWrOiImIlcllLh3JufeOkCERG5AofchpSZmYk9e/bg999/R1xcHBQKBapUqYKOHTsiISEBy5Ytw/r16/HVV1+hcePGjqiSnI6JjFHO7jjkKfKi46FNRFRkdieYeXl52Lt3L3bu3ImDBw9CoVDA09MTHTp0QO/evdG2bVvI5XIAwKFDhzB69Gh8/PHH2L59u8OCJ+fhKXLjBCdnmFKzMMEkG+TmqiCXCXD3kDs7FDIhLS0H0XsuoVPXF+Hn5+nscIgssivBnDJlCmJiYpCdnQ1RFBESEoLevXujS5cu8PPzMyjftm1b1K9fH9euXStywOQamGAa5/SeQ10PpnOjoFJm5rTdcHOTYd7Crs4OhUz49ZezSExIgUqpwcB/BTs7HCKL7Eowt2/fjqCgILzzzjvo3bs3atasaXGZpk2blsjD56lkaDTMMF2RyHPkZCeVSuPsEMiMnGwlACA7R+nkSIisY1eCuX79ejRr1sxiuZycHHh7ax8nOH36dHuqIhdlx/j85YKG+4WIioHuud68RphKC7vGwZw6dSrWrVtntszKlSvx+uuv2xUUuT72YBonOrsTyAGnyFUqDW7dTOePCCIX8iS/LJ3vS1EU8TiLY2SXJ1b1YN66dQtZWVnS69u3b+PKlSu4ePGi0fJKpRJHjx5FTk6OY6Ikl8ME0zhzSZlarcHObX+jeYtaqF6jeIbscsRNPls2n0Pc8Zt4573maNAw0BFhEVGRad/UpfV3X1TkORw/moRJU19D4NOG92pQ2WNVgnnmzBlMmjRJ6qIXBAE///wzfv75Z5PLiKKINm3aOCZKcjlMMI0zt18unLuHwwev4+jhG8X3nHAHfPucib8DALhx41G5TDB5ZBM53vGjSQCAG9cfMcEsJ6xKMLt164a///4bqampEEURW7duxYsvvoiXXnrJaHl3d3dUq1YNgwcPdmiw5Dp4+tQ4c/tFkT8Ie3Em545oFpksv6eknP6IKG+3R/HHYukg3bdXypuL3x3lh9U3+Xz00UfS37Gxsejbty+GDh1aLEGR6+OXknHm9osucStO0p3ARWgeoZzfgV7evgD5Xi4lysjbUuPs69SpxNh1F/nevXsdHQeVMuW1d8sSs1/WJfAFoVZrP72LkiTp8ktXTjw0GrHYEnYX3uxi4crt7Agxf/4DXz9PtGhZy9mhOERp/wFU2uMn61mVYP74449o0qSJ9JjHH3/80eoK2MtZNpX1LyV7qc2MJVgST/nR9WAWpXV0PZiu+kXw84bTiD91G/MWdi2WJFOjtr6LJTHhPir4eKBmrUoOj6OkqAtsryiKZa4He89viQBQ6hPMstIqrvq5Qo5nVYI5b948jBs3Tkow582bB0EQLB4ogiAwwSyjON6jcWYHqy6BbwiHnCKXufbdqidP3AIA5OYqUaGCh8PXn5d/raw11q6OBQAsWNrd4XGUlII/FjUaEXK566QyKfezcCLuFt7oXA9yuV2j6pGLcdXPFXI8qxLM+fPn693QM3/+/GILiEoHniI3ztlPQ9E97cPNrQhfxvnfAK7e06DIU6NCBcevNy9XZVU5V+vF/+fSA/x9/h569H7Zpp7dgj22GrUIuYXHkWek56KCj0fRjjErfbXiCLKyFKhSxQfNW1h+Ylxhaht6o12e4No//Kzl6p8r5DhWJZh9+vQx+5rKn7w863t5yhNzCaZGXfwfrI8fawcyzstTQaXS2JUEqPMTJ3kJJBBFkWtlImirvDzr1qtUOvc9cPdOBn7feREDBjWBj68H1nx1DAAQ3LQGatV+yur1KJVPjlm1RgN3mM4wH6VmY/6cvWjU+GkMGW75aW5FlZU/MHd2tn0DdCts6I1+kPIYTwV4F2tPqVKhhgjAw8NCFm+E7oeAzEIPc9KNR6heoyLc3GyvoySwJ7r8cGhLX758GZGRkTh8+LAjV0suouAXb3oaB9E3JjMzT/q7cLKZW8zPEM7LUyHlvvaBCKKoTUDsocpPnGQufi2etYmgNTLSc6W/7ydnmSn5RMH2dEavzE8/nsLFhPuI/uOS3nRbkirgyY8S4EkPuCkpKY8BAOfO3rOpjqKy94yJosAxYq4382ZSGhbM24dtURfsqsdai/97APP/EwNAOy7un3suWX3s6D5PzL0tL11MwcovDuPXX84VOVZTblx/VKQzNeaW/WXjaSz6fH+xvJ/u3snAjm1/Q6VSIzMjF9evpjp0/cV1RuPK5Qc4GXerWNZd3ATRzpb88ssv8dNPPyE6OhpeXl74/fffMXnyZGjyxyAIDQ3F6tWr4enpadX6zp3TviEaNWpkTzg2SU/LwY/fnQCgf7rB1J4wtov0J4kmphuZVuCFsVWIFtZlVTwFt0n/hZF6zcdTcB2KPLXUaySTCahcpQLkcplVv0jNfShak8eIYuG2Eg3m64I22qa6075PikGEaLCPC673ybIF9mPB/4ysMysrD+r8nko/P09UqOAOQSZAFLXXk+k+hAIDfSF3k9l9Q4UoitBoRKhUGqhVGqhUGuTkKqFSahAY6Ivk5CzIZAL8KnrCw0MOmSBAkAkQBAEymSAtL4raL2+N9FrEo1Ttjwe5XIaq1XxMtq+x0I1N07Wdbt/q2kpqU1GU9qEoTS9QtsB0iCLS0rTJYAUfdzz1lH3nyDUa7T7T/cvNUer15PlV9ISXlxvkcpm0v3T7ShS11yBnZyuQ/VibkFWr5gt3D7lVx3JBtpTXaLRxa9Qi1BoRD/KTPQBSmwOAdwV3PPWUNwRBgCBo96GubXVtXXBa9mOllKz7+Higor+XFFfB41MUtXXqEtgaQf5626Grq3D76bdl/n4s8N7T7dvC7SwCSM9vazc3GaoF+urdgKZ3HGn016vdVu11utn5SXNAQAV4V3A3ehzeu5spbUuNIH+7P6+kNtIUel/l/63bnoLtVblKBXh7uz9po/y20b3WLa877gGgWqCv9L4s2Fa3b6Vb3A5T8esdJ4ViEDXaYz7t0ZPPhmeq+xmss+A6dMepLv5H+cu6u8tQuYpPgc+hJ/tKd0wHBFRABR93aZ36cZr7/jP9/VmwjXUCn/aDm5tMOn6BJ8MoaffDk88p/dcFjllRRE6OEoKg/U7UvQ9MxWFr/Lq4AwMLfsYYNmLffo303pPFydp8za5hijZu3Ijly5ejatWqSE9Ph6enJz7//HPI5XKMHTsWt27dQlRUFNasWYNx48bZU0WxUmtE6c0N6N/da/wNWWCisT/1phkW0FtlgXUZXd7YuoxXLxXWn6a/vN46BGPb9+TpTAZzCq3Ly9MdDV72R/Ugf5yMu4WsrDzth4gN1znZ+nNGhChtg148gmC4fwXDfSYUWFCvnDTf2HoEg7aRyuntQ0FvvwkCULWCL158qRru38/CndsZyM5Waj+MAFSp6gMvLzcolRpkZuZBrdIU6Ze63E0GN7kMcjcZvCu4o9JT3nihXhV0eOMFnIi9ifiTd5CZmYvcXJVeYiRqtHcKCzJIiadMJmj/FgQ8U70ivCu4Iz0tR4rTGkZ/XOW3n/YDXIC0u4Un+1RAgXmFpiM/SRKgjVcQBFR6yhuZGXmQCQIePnhsWKkVZHIBbm7aH0deXm7w8/NE/Reromnzmtj920Xcu5uJvDwV1GrtF6Qufm2Crv3bw8MNijw13N3lePxYAXWGbb06tja9IGjjlstkkMkF+Pt7IT09Fz4+HnicrYSXlxtyc1UQADxKzZG+BAVBe+PWkx8ZeNLeMgG+fh54vl5laNQi7t7NRHpazpOEv0CQgiCgQgV3KBRqyGT6+16X3Blra/121763BJnldhYEAQGVKyD1YTY8vdzwKDWnUFsg/5gRpNcyabr2fy9vd8jkMkAUkZenQo6u17nQcejj64HHWQoIAvQSd5vaEyLkMpnx95VMgLvsyQ+1jIwnZzoeZymQlamQ2kXXVnp/uwmoEeSPGkH+uJn0CJkZedrErVA7VajgjuxspUH7FGwnU7Hr3v+6/S8z8hnx1FPeePQoB2q1RtpPhdcp0223TIBMnh+/XBu/u7sc6ek5yMzIg1qtMdhenZwcJbIe5xn97Ne+NvI5r/faxHxof4Dpeup1Z+KkHzsF90PB4yu/Tt1xW/AYE2QCVGoNVEoN7t/PMhmzsbjNxl6oXHr+WRZTN9gqbTxzURLs6sF86623kJmZiaioKPj4+ODEiRP417/+hb59+2LevHkAgHfeeQfJycn4/fffrVpnSfZgEhEREZHtrM3X7LoG88qVK3j99dfh4+MDADhw4AAEQcDrr78ulWnYsCHu3Lljz+qJiIiIqBSz6xS5u7u73qmTv/76C3K5HC1btpSmpaenw8+PD7R3pLjjNwHAruE6HLUuW5ezpby1ZX/ZeAYA0P/tV6yKwZ66ijLfXHymljO3Pkfsc1PrMBarLTHaUldh1tZdeJo17W9PXNYsU9TXlmK3VL7gfEtlLb02V6+19ZhbzhH1Wfs+s7Yuc8uYqtfc9pqKx5rlbd1mc+1gax2m9pc1+8pSfDrmPmts3dfWtLWxdRaMxdZ6TNGVv5Z/k5Cj9rmpWO35znAVdiWYdevWxf79+/HBBx8gMTERiYmJaNGiBXx9fQEAN2/exO7du3m628Hych13F7K967J1OVvKW1s2N8e+IUtsqaso883FZ2o5c+tzxD43tQ5jsdoSoy112Vt34WnWtL89cVmzTFFfW4rdUvmC8y2VtfTaXL3W1mNuOUfUZ+37zNq6zC1jql5z22sqHmuWt3WbzbWDrXWY2l/W7Ct7PsOsjdGafWhN7Jbey9bUY4qufHHsc0vrsLScq7HrFPngwYNx/fp1tGnTBoMHD4YgCBgyZAgA4Pvvv0fv3r3x+PFjjBw50qHBEhEREZHrs6sHs3v37hAEAWvXrgUADBgwAOHh4QCA3NxcPPPMM5g4cSJatWrluEiJiIiIqFSwK8EEgG7duqFbt24G09977z2MHj26SEERERERUelld4Jpiru7u6NXSfk8vRy3b+1dl63L2VLe2rJe3h42xWBPXUWZby4+U8uZW58j9rmpdRiL1ZYYbanL3roLT7Om/e2Jy5plivraUuyWyhecb6mspdfm6rW2HnPLOaI+a99n1tZlbhlT9ZrbXlPxWLO8rdtsrh1srcPU/rJmX9nzGWZtjNbsQ2tit/RetqYeU3Tli2OfW1qHpeVcjd1P8omMjMSvv/6KW7duQalUGh0wWhAEHD9+3Kr1cRxMIiIiItdWrE/y2bRpE2bPng1RFFGxYkXp7nEiIiIiIrsSzPXr18PPzw//+9//EBwc7OiYiIiIiKgUs2uYohs3bqBnz55MLomIiIjIgF0JZpUqVaBSqRwdCxERERGVAXYlmD169MAff/yBtLQ0B4dDRERERKWdXddg9u7dG4cPH8Zbb72Ft956C7Vr14aHh/Fb8Dt06FCkAImIiIiodLErwezatSsEQYAoili2bJnRMqIoQhAEJCQkFClAIiIiIipd7Eowx44dC0EQHB0LETmARpEDmYe3s8MgIqJyzK4Ec/z48Y6Og4gcIOfKcdyc0xpV+v8XAV0nOzscIiIqp+y6yaegx48fIz4+Hvv37wcApKenF3WVRGSnrFPbAACp2z9zciRERFSe2Z1gPnjwABMmTECLFi0waNAg/Pvf/wYA/PTTT+jYsSNOnDjhsCCJyDq8dIWIiFyBXQlmamoqBgwYgN9//x2NGzdGgwYNpGeRe3t7486dOxg5ciQSExMdGiwRERERuT67Eszly5fj7t27+Oqrr/DTTz8hLCxMmvfOO+/g22+/hUqlwldffeWwQInIeiJEZ4dARETlmF0J5t69e9GxY0e9xLKgFi1a4I033sDp06eLEhsR2YynyImIyPnsSjAfPXqEmjVrmi0TGBiI1NRUu4IiIiIiotLLrgTz6aefxt9//222zNmzZ/H000/bFRQRFZHIU+REROQ8diWYnTp1wtGjR7Fp0yaj87/77jucPHkS4eHhRQqOiGzEu8iJiMgF2DXQ+ujRo3HgwAHMnj0bGzZsgEajAQBERETgwoULuHz5MmrVqoXRo0c7NFgiIiIicn129WD6+vpi48aNGDhwIG7fvo0rV65AFEVs3boVN27cQK9evbBx40ZUrFjR0fESkTV4ipyIiJzIrh5MQJtkzpo1Cx9//DGuXbuGjIwMVKhQAXXq1IGHh4cjYyQiIiKiUsSuHsxp06YhJiYGACCXy/H8888jJCQEL774opRcbt26Fe+9957jIiUiIiKiUsGuBHPLli24ePGi2TKHDx9GXFycXUERERERUell1Sny7777zuCpPKtXr8YPP/xgtLxSqURubi6ef/75okdIRDbgXeREROR8ViWYgwcPxm+//YaHDx8CADIzM+Hh4QFfX1+DsoIgwM3NDYGBgZg8ebJjoyUiIiIil2dVgunh4YHIyEjp9Ysvvohhw4Zh3LhxxRYYERUF7yInIiLnsesu8piYGA5BROSKONA6ERG5ALsSzBo1agAAcnJycO/ePSgUCogmxt178cUX7Y+OiIiIiEoduxLM3NxcfPLJJ/j999+hVqvNlk1ISLArMCIqAg60TkRETmRXgrls2TLs2LEDAQEBCA4Ohp+fHwSemiNyPr4PiYjIBdiVYP7222+oXbs2fv31V6N3khMRERFR+WXXQOuPHj1Cx44dmVwSuSqeIiciIieyK8GsXbs27t696+hYiKjIeIqciIicz64Ec9iwYfjjjz9w9uxZR8dDRERERKWcXddgurm5oV69ehg0aBCaN2+OZ599Fh4eHgblBEFAREREkYMkIlvxFDkRETmPXQlmwaTx6NGjOHr0qNFyTDCJShZHcyAiIldgV4L5448/OjoOIiKnUqXdRfaFP+HXeggTdSKiIrIrwQwNDXV0HETkQKaerEWm3fy8A5T3EiH3qwqfxl2cHQ6VI59++il27txpML179+749NNPSz4gIgewKsHMysqCh4eHdJ1lVlaW1RVwKCOiEsSeN7sp7yUCAFSPbjs5EipvJkyYgNGjRxtM9/b2dkI0RI5hVYLZvHlzjB07FuPGjQMANGvWzKpTSIIg4O+//y5ahEREJYi9v1TS/P394e/v7+wwiBzKqgSzWbNmCAoKkl43b9682AIiIkdgkkRERM5jVYK5bt06s6+JyFXwFDmRI0VFRWHatGkWy61atQrh4eEm5yckJKB3797o06cPPv/8c2n6o0ePsGrVKuzfvx/3799HUFAQ+vTpg+HDh8PNza7bJIpsxIgROHjwINq1a4c1a9Y4JYbitmLFCqxcudJguo+PD2rVqoVu3brhnXfegbu7uzQvIiICW7ZswdatW/HSSy9ZXdetW7fQoUMHhIaGlqv8yTlHLxERUSkSGhpq9gbX5557zuZ1ZmVlYdCgQbh69SrCwsLQsWNHnDp1CosWLcLJkyfx1VdflfiIBikpKThy5Ai8vb1x6NAh3Lt3D08//XSJxlCSOnToICWLarUaWVlZOHHiBBYtWoTTp09j1apVUtnw8HDUqFEDVapUcVa4pQoTTKKyiNcRFgH3HRkKDQ3F+PHjHbrO1atX4+rVq5gxYwaGDh0qTZ80aRJ27tyJAwcOoH379g6t05IdO3ZArVZjxIgRWLFiBTZv3izdf1EWhYeHo2/fvnrTRFHEmDFjEB0djaNHj6JVq1ZSWXO91KTPrkdFEpGL4l3kRKXG7du38cwzz2DQoEF607t27QoAiI+PL/GYtm7dCn9/f4wYMQJ+fn6Iiooqdze+CYIgJZ1xcXFOjqb0YoJJRFRQOfsyJce7ePEixowZg9DQUDRv3hzTpk1DWlqaQbnFixdj//79BtdaXr16FQD0TsVGRESgQYMGePToET7++GO0bNkSwcHBeO+995CUlASFQoGFCxeibdu2CAkJwZAhQ3Dx4kWb405MTESrVq3g5eWF8PBw3L59G4cPHza5TFJSEiZOnIjWrVsjODgYI0eOxJUrV9CxY0cMGTLEpvpdiVwuBwC9x2BHRESgfv36SEhIcFZYpQpPkROVRUySiJwiISEBgwcPhkKhQKdOnVCxYkXExMTg4MGDZpcTRRGpqanYvXs3VqxYgerVq6Nnz54GZYYOHQqNRoM+ffrg0qVLOHToEN5//33Url0bly5dQufOnZGSkoLdu3dj1KhR2LNnj9XjaW7duhXAkx7Url27YsuWLYiMjETbtm0Nyt+4cQMDBw5EWloawsPDERQUhH379mHQoEHQaDSl9tpNURSxZcsWyOVynhIvAiaYRGUKT5EXGZNzMiI2NhYrVqwwOq9Pnz7SUH5z585Fbm4u1q5dK127N378eAwZMgQpKSkm179s2TJ89dVXALQ9l2vXrjUYG1Oj0cDb2xvr16+XetYGDhyI+Ph4KBQKbN++XXq4ybRp0xAVFYXY2Fi89tprFrdPrVZj586d8PHxka77bN26NSpXroyYmBikpqYiICBAb5n58+cjNTUVy5YtQ+fOnQFoB41/5513cPLkSYt1uoLo6Gjcvq19uIIoinj8+DFiY2Pxzz//4JNPPsHzzz/v5AhLryIlmCqVCocPH8bFixeRlpaGqVOnIjExET4+PnrjZhIRlR5MMMlQbGwsYmNjjc4LDQ1FUFAQkpOTERcXh/bt20vJJQAEBARg7NixmDBhgsn116xZEyNHjsT169cRExODwYMH45tvvsHLL7+sV+7tt9/WO20bHByM+Ph4DBgwQO/JeY0bN0ZUVJSUPFly+PBhpKSkoHfv3vD09AQAuLm5oXPnztiwYQO2bduG4cOHS+VTU1Nx4MABNGvWTEouAe0p5cmTJ+Ptt9+2ql5ni4mJQUxMjMF0f39/ZGRkQK1WS6fLyTZ2J5jHjx/H1KlTkZycDFEUIQgCpk6dit9//x1r1qzBxIkT8d577zkyViKyGpMkIkcaN26cxbvIddc8NmzY0GBecHCw2WXffPNN6e99+/ZhzJgxmDp1Knbs2KE3VFGtWrX0lqtQoQIAGHTq6JJEhUJhtl6dbdu2AQC6deumN71Hjx7YsGEDNm/erJdgXrhwARqNBo0bNzZY1yuvvOK0MTxtNX/+fL27yLOzs3H16lUsX74cS5YswfXr1zF//nwnRlh62XUEJCQkYNSoUfDy8sL777+Pq1ev4s8//wQANGnSBFWqVMGiRYvw3HPP4fXXX3dowERkBu8iJ3KajIwMANrBuguz5VGQYWFhaNWqFY4cOYKkpCTUrl1bmqdLKAsr2KtpTEJCAqKjow2mjx8/HllZWdK8kSNHGl3+8uXLOHXqFEJCQgBoB4gHYHRMSLlcbnA6vbSoUKECGjZsiJUrVyI8PBxRUVEYOXIk6tSp4+zQSh27Eszly5fD09MTUVFRqFGjBlauXCklmO3bt0dkZCR69uyJ7777jgkmEZUu7PwlO1WsWBEAkJmZaTAvOztb77VKpUJsbCxEUUSbNm0MylevXh2ANpErmGDaKyEhweiTa8aPH4/du3cjNzcXjRo1QoMGDQzKXLt2DbGxsYiMjJQSTN3p+KysLKP1PX78WO+1UqnEokWLpBuJOnfujBkzZphMjC2VT0pKwrx583Dy5El4e3uja9eumDBhgtRzq/Pxxx/jxo0bNj9Bx8PDA8HBwdi9ezcSExNNJpjp6emYM2cO/vrrL3h6eqJXr16YMGGCVafVr1y5gjlz5uDMmTOoVKkSBg8ejBEjRkjzrd1GV2VXgnny5El07twZNWrUMDq/WrVq6NKlC37//fciBUdEduKNKkQlrkGDBhAEAadOnTKYd/78eYNpo0ePho+PDw4dOmSQkFy8eBGCIDjsfoa+ffsaDCiuozs9HhERgWbNmhnMv3PnDjp06IDdu3djxowZ8PX1xcsvvwxBEHD27FmD8pcvXzZIMBcsWICYmBh8+eWXEAQBkydPxqpVq0xel2quvEKhwOjRo/H8889j06ZNePjwIaZPny5tg87Ro0cRGRlp9glM5uh6pP38/EyWmT17NlJSUrB+/XqkpqZi8uTJqFSpkl6iaIxSqcTIkSPRokULzJ49G1evXsWkSZNQrVo19OzZ0+ptdGV2jYOZl5dnspteRy6XIy8vz66giMg+Jf1YOSJ6omrVqnj11Vdx7Ngx7NmzR5qelZVl0Hvo5uaGjh07IjU1FWvXrtWb99NPP+H8+fNo3759sT+W8Pbt24iLi0ONGjXQtGlTo2WqV6+Oli1bIjs7G7t27QIABAYGok2bNjhy5AgOHDggldWNx1lQRkYGNm7ciDlz5qBp06YICQnBuHHjcOHCBaP1WSp/9uxZJCUlYf78+ahbty5CQ0PxwQcfYMeOHdI6srOz8cknn0g9rrY6c+YMYmNj4e/vbzTp1jlw4ACGDRuGevXqoWXLlujevTuOHTtmcf3Jyclo3LgxZs2ahdq1ayMsLAytW7eWBna3ZhtdnV09mHXr1sXhw4eh0WggkxnmqEqlEocOHbLr2axERESl1cyZMzFw4EB8+OGHCA8PR2BgIPbt22f0u3LKlCk4ceIEFi9ejOPHj6NevXpISEjA0aNHERQUhNmzZxd7vNu2bYMoiujRo4fZH6h9+/bFkSNHEBkZiQEDBgAAZsyYgQEDBmDMmDHSth4+fBipqakAIG2z7hRv69at9dZnqkfVUvk6depg9erVete6CoIg9TgCwNKlSxEaGoqqVasa7VHWKThMEaAdruny5cvYv38/1Go1pk+fDi8vL5PLV6pUCdu3b0ebNm2QkZGBgwcPWjV2ZlBQEL744gsA2uGRTp06hbi4OMyaNcvqbXR1dvVg9uvXD//88w8iIiKkC311Hj58iMmTJ+PGjRsmDx4iIqKyqGbNmvj555/RtWtXxMXF4ddff0WDBg2kMS4LCgwMxObNm9G/f38kJibixx9/xI0bNzBs2DBs3rwZgYGBxR6v7vR44UHdC+vYsSP8/Pxw7tw5JCYmAtAmQRs3bsRrr70mJZ+1atXCDz/8AADSAO9JSUmoXr06du7ciW7duiEsLAz//e9/Td7hbql8QECAXvKp0Wiwfv16aVp8fDx2796NqVOnWtz+mJgYrFy5Uvr3zTff4OzZswgLC8OPP/6I3r17m11+1qxZiI2NRUhICNq1a4cqVarY/Mz6du3aYdCgQQgODkanTp2s2sZSQbTTRx99JNavX1988cUXxVdeeUV88cUXxbCwMPGll14S69evL44dO1bUaDRWr+/s2bPi2bNn7Q2HiERRfLjjczFxmExMHCZzdiiljm6/PYr+0tmhELk8tVotXr9+XVQoFAbzkpKSxHr16omzZs0SRVEUV61aJYaEhIj9+/cX4+LixP3794thYWHiZ599ZnTdtpb/7LPPxMaNG4uXLl0S8/LyxC5duoi//fabKIqiuGTJEvFf//qXYzbaiHXr1onDhw8XT5w4Ie7fv1/s0KGDyThNOXv2rBgdHS22bdtWnDNnjtEyBbfR2azN1+weqGrBggUICwvD5s2b8ffff0OlUiErKwtNmzZFnz592HtJRKUTb5AiskgQBPTu3RuBgYHYvn273t3gumtKW7RoAUB7vWlWVhYWLlwojeM5ZcoUTJkyBdOmTTO4fMDa8qIoYu7cudi4cSOWLVuGF154AUuXLkXt2rXRpUuXYt8Huru89+7dKz0W09PTE++++y7ef/99q6+fbdSoEQAgNzcXU6dOxZQpU6T9aWwbS4sijYTapUuXEmlEIrIWkyMiKn6CIGDgwIH49ttv0bNnT7Rr1w5yuRynTp3C6dOn0bZtW+kJP9WqVYObm5veIPHPPfcc8vLykJqaapCIWVNeo9FgxowZ2LFjB5YuXSpd97hjxw6kpKRIA9srlUqo1WrpiUeOdP78efj5+ek9c71hw4ZQq9W4c+eO2QQzOTkZ58+fR4cOHaRpdevWhVKpRFZWFgICAkxuY2lhV4LZvXt39OzZE927d5fG6qLyQaPIhTozBe6Vazo7FDJCZO8bEZWQjz76CHXq1EFkZCS2bNkClUqFoKAgTJo0CcOHD5duGmrSpAlUKhUSExNRv359ANoxIH18fFCpUiWD9VpT/vPPP8eOHTuwYsUKhIWFScuuW7cOKpVKev3999/j/PnzWLRokcO3v1q1asjIyMD9+/dRrVo1KU7A8MlKhV25cgXjx4/HwYMHUblyZQDapyMFBARIg9Sb2sbSwq4E8969e1iyZAm++OILhISEoGfPnujUqZNNTyqg0inpPy2huHUOdVc9gNznKWeHQ4XpEkwOV0RExUwmk6Ffv37o16+f2XLPPvssOnTogGnTpuE///kPcnNzsWjRIvTv3196pGRaWhrkcjn8/Pwslj99+jR++OEHTJo0CQ0bNkRKSopUV+HxuStWrAgvLy+HDFZfWJMmTVCvXj1MmTIFERERyM3NxcyZM9GrVy+LTzJq3rw56tati4iICERERCApKQmLFy/G6NGjAcDsNlatWtXh21Ic7Eowjxw5gr/++gu7du3C/v37ceLECcyZMwft2rVDjx498Prrr1t8bBWVTopb5wAA6oz7TDBdkq4HkwkmEbmOBQsWYO7cuRg2bBjc3NzQu3dvTJw4UZo/fvx41KhRA59//rnF8roxRhcvXozFixfr1XPhwoUSew66m5sbVq9ejXnz5mHYsGFwd3dH586dMXnyZIvLuru7Y/Xq1Zg9ezb69esHHx8fDBs2DEOHDgXgOttYFIJYxHNqubm52Lt3L3bt2oWDBw9CoVDA19cXHTt2RM+ePdGqVSur1nPunDZx0V3sSq7p0jvap008O+8CPKq/6ORoqLCH2+fiYdRMQCZHvW+NDwFCxumO7Wr/WoFK4f92cjRERK7J2nytyCmwl5cXunbtiq5duyIrKwv79u3D2rVrsXXrVmzbtg1///13UasgImvxGswiE3mjFBFRkTmsj/XMmTP4/fffsW/fPty4cQNyuRwtW7Z01OrJxfBL2DRVejLkPgEQ3NydUDuvwSQiIucrUoJ54cIF/Pbbb/j9999x9+5diKKIBg0aICIiAt26dSs1F6KSHdhTZpQ6Ox1XP6gOz+eao/Ysy8+jdTiR12ASEZHz2ZVgLl26FLt370ZSUhJEUUT16tUxatQo9OzZE3Xr1nV0jOSSmGAao85IBgDkXYtzSv2iqAEACIJdT4ElIiJyCLsSzP/973+oWLEi+vXrh549e6JZs2aOjotcHXswTXCRnkOeIiciIieyK8FcsWIFXnvtNQ5FVJ4xwTTO2Ykd26XouA/JBWmUechJPIAKL4Y56fpuItvYdR6tY8eOTC7LPX4JG+UqCaaz46BS5f5PE/Fw+zxnh0FmPNwyC7cXdcGj3YstFyZyAVb1YIaGhmLUqFEYMWKE9NoagiDg+PHj9kdHLkvUqJ0dgotydmLHm3zIdml/LAMAVO453cmRkCk5F//S/v/PESdHQmQdqxJMX19fvR5LX1/fYguISgkmmMbl32TjvPrZg0lUJsl0Jxx59ohKB6sSzL1795p9TeWPqFY5OwTX5PTEmwkmUdmkfU+Lzv4RS2Qlu67B3Lp1Ky5evGi2zKlTp7Bq1Sq7gqJSQHR2IuWaLH3451w6BE1OZglFY5+sk1txecxTUKZcc3YoRJRP0PVgltKb0B5fiMathZ2gyXvs7FCohNiVYEZERCAmJsZsmT/++AOrV6+2KyhyfbwG0wQz+yXn8lHcnPcabn/Rq9iqF/O/fIQiXIN5d/VQaHIykP7Xt44Kq5QpnV/gVNblv6dLaQ/m7YWdkH0hGpnHf3Z2KFRCrDpFHhUVZXBafNeuXUhISDBaXqlU4vjx46hUqVKRAyQXxQTTODP7RXHvEgAgJ/FASUVjF0GQQUR5/hFRvi4vEEtpjxiVTuX3c6X8sSrBfPXVV/HZZ58hOzsbgPbu8KtXr+Lq1asml/Hw8MD//d//OSZKcjn8kDDO3H4pkafrqBTaOIrSC6eLs5T2lBRdOUu4+F4uHcrKddXl9nOl/LEqwaxatSqio6ORk5MDURQRHh6OYcOGYejQoQZlBUGAm5sbnnrqKbi7czDYMotfSsaZ2y8lkGCK+QkmNEX4EJfJi76O0qycbbeoVjo7hGKVczUWMi8/eFZ/ydmhFJHuFHkp/wHEBLPcsPpJPgEBAdLf8+fPx0svvYQaNWoUS1Dk+tiDaZyoVji3flVe/h/2f4g/uZnANb8IsuJ3IPdqHKq8+Z9iWb8tx7Y6JwOCzA0yzwrFEkuJKOMjQtz8TysAQL3v+ZnlCsRy9gOuPLOrS6VPnz548cUXLZY7duyYPaun0oAJplGiMs/0zBI4xeWIBFPX0+qqPyLuLOuN1B1zi+1ufFFh/V2uV8Y8hWtTXiiWOEpKwR5MV/vy1+RlI/f6SWeH4Rqkzw/2YFLpYNezyAFgw4YN2LlzJ1JTU6FWq6ULxUVRhEqlQmZmJnJzc03eCESlnIsmH84mJXjGlECCqcnNT7rkRbk8pXTcrarJy4LM28/x683Nsqqc7jNPnX7P4THYQ5V2F4q7F1HhpTCblhM1T3owRbUSgszT0aHZ7d6aYcg6EYWgiL2o8OJrNi/vqj+S7KL7/Cjl+WV5uwSlPLOrB3PTpk2YM2cO4uPjkZycjNu3b+PBgwd48OAB7ty5g/v378PDw8PoNZpUNphNpMoxsz2YJfDBqs58mP+Hyu67g3UJh1CkJLX4aXIyime9udb1jIrK3GKp31rqnAykH/xe6nW88Wlz3PpvOBT3r9i0Hr1jVmX+Eg+NIhe3FnZC5sktNsdrj6wTUQCA3Gv29WKKihxHhuNcus+P0n6vj9zufi0qZexKMH/55Rd4e3sjMjISp0+fRpMmTdCzZ0+cOXMG0dHReO211/D48WP06NHD0fGSExXsDVBl3HdiJK5LnZ0m/V04wdPYcOrVXsqHSdq6VXlQpd2xbyW6JMPNw3w5J3NkgqkpkIio0u5at4yVPZ3FJfm7UUhe+x7SYrQPtFDnx616dNum9WiyHz35W2k+Icu59BeyL0Tj7oq3bIy2iOzsTS84qLe50//qrIe48WkoHp/dbVc91nq4fS4eRM0CAChTbyH3RrzVy+o+PwQ3L5NllKm3cHVibWSd2la0QIuTmR++Gcc2IXXXgmKpVpObhZzLR4tl3cVJ/fgRlDa+p12FXT8lrl27hk6dOqFRo0YAgCZNmiA6OhoAEBQUhOXLl6NTp05YvXo1li9f7rhoHUT9OA3pf63VvtA72EXDaUbmixbm6083Xla0MN/S8nbFYmG+aCEWdWaKNCn9wDdQZz6AIHfX9nRZOv1rdr41P8nFQttRaPsLTNPbd2Lh/WR8PQWXEQ32V+FlCq27wN85lw5JEd//cSzkFQO1N82IIrLid0jzHmyZDZm7p/13losiRLUCokoBUZmnTSgf3YLq4Q2pyN0v34Z3nVAInj4QZHJtXYIMgkyufeKQRg2IGu0PB41a+7+okXrwHp/ZBZmHNwS5h/H2M9qmxqbl7x9Ro923uv1e4H8xf37heVL5gvPypf62EF7PNbP90gNRhKhWavedKg+iMg/KB9el2dnn/8D9DR9C5lURgpsHBLmbNjnR7StR+7fywZN9/SBqFmSePnZcBmFDeVGjjVutAtRKZMVGauuOnA51VqpU7NHupcj956g2FkGm18bG2ltxL1FaNmXjJHg88xIgCBAEQRuf8OSSiYLHd+rO/+Zvgq6MAKNtLWpgrp3Fwu2e/7rg51FmXGT+6Xv5k32h0a1XI7XPk7q1r1WPnvzIevDLVMh9q0DvuMqvM+vUVuTdiMftJd1Qpf/ntrVLQRq19gyAbv8W/F9UI23PF9pdJpPj4dbZAICnuk2F3CegQJsYLguNGsp7/wAAcq/G4sGW2RDyfwAK0jEnIP3gt1Cl3sKd5X1Rpd98G96j0O4LjTp/X+rq1v2t/bxQpd3B4zO74NusLzyeedHIOkUpblGtAjSq/P+fdE5kHt0ATXZa/vtK/1hM3TEPgDapkvvm31hs7LNX95eZeYWnpcV8BXVGMnyb9YU68wHybp3DUx3/D4K7V4HjF0+OP7HwMaU7NgvO107TZKdBFEV4PP0CpPdB4TjsjD91x1yIKgUCes3Mv5lQMNqufqH94V65psF0ZxJEO86jNW7cGMOHD8eECRMAaHs0P/30U5w4cQIVKmjvppw9ezYOHTqEP//806p1njt3DgCkpLU4Ke5fxfVSfmG+s8gqVILgUQFqe3vHygu5m1PuznUPfAHPjNmAlJ+nIidhX4nXX5q5Bz4P/9dG4uGWWU4//U1EZIugaftQoX67EqnL2nzNrh7MwMBA3L375DRSrVq1IIoiLl26hCZNmgAAKlSogJSUFBNrcC43/6dRY+KuJxMK/hrQ+2VgOF2wMF9vuhXrFYyWsT6egvMFU8tZis1iPE/KuFerC8HDG8rkf6DOuJ/fo2JhHD1zv2Es/r4R9WMuuI8M2kQw3IeFl9GVt3IZwcx6Cv7qldYpd4fH0/WhycmAIvmS9vq2/F+6cr8q8Hi6HpQPrkOVnqy9jrUIY9oJbh75/zwhuHlA5uUHt8q1IAgCak6NhirtHlTpdyEqsgv1RqilnkzI5NoB4HV/y+SQefnBvWod5N06B01OxpOxNQHo/cIGDOM32B4xv+f0SW/Yk54xmV7vl7QPBZlUFoKgbQPZk2kyT1/IvHyhSP7H7kRQkLtL+01w84Tg4Q33qnUgyGSo9PpoKJIva/ebWgloVFLvr7TfBBkgk8HN/2mIedlQpd8r/uuSBeHJGQOZGwQ3d8i8/aFKvQnI5JB5+kLuWxnK+5ef9O5pNPntKgMEud7fuvaHIIPH0y9AVKuguHsRYt5j6PfyAbp2lHn6wu2p6lCl3oQmLxtPeh11vcv6bSUUansIsgLvP/1joHA7645LecVAKO78nd8W6gLrkUl/a9tFVqCddHVr20ijzIHq4U3tOgx6Z/OPK29/aLIfFTreC7H0fpU92a/a/930XgtunlDnZkCTkwGZd0VAk3/GQNTovyd1baP7W5BD5l0R7lWfgzL5H6jS7+X/gNVvJ0Emh1ul6tr3vbHtMBm/CL3jO/+4KPwZIcjk0ChzoclJN70umRyCzA2C3O3J9svdIPP2h3tAEPJunoUmN+tJj3TBfebmCVGjgiY7/UlbAyY+e3V/mp5XeJrg5gFRka2dLnfTfn4YOc71jqf847Lw8VbwGAMAddYD7fvNyHezse9uq3MJQZDOukg9qEZ41mhodLoz2dWDOWvWLGzfvh1fffUVWrZsifT0dLRp0wb9+/fHzJkzoVQq0a9fP2RmZlp8ZrlOSfZgEhEREZHtirUH8/3338eePXswfPhwzJs3D3369EH37t2xceNGnDt3DhkZGUhKSsKwYcPsWT2ZkH7wOwCA/6vDnbYuW5ezpby1Ze+tfQ8A8PR7a62KwZ66ijLfXHymljO3Pkfsc1PrMBarLTHaUldh1tZdeJo17W9PXNYsU9TXlmK3VL7gfEtlLb02V6+19ZhbzhH1Wfs+s7Yuc8uYqtfc9pqKx5rlbd1mc+1gax2m9pc1+8pSfDrmPmts3dfWtLWxdRaMxdZ6TNGV112P7Kh9bipWe74zXIVdCWb16tXx66+/YvXq1ahduzYAYPr06UhNTcVff/0FmUyGN954A+PHj3dosOWdIweWtnddti5nS3lry6ofp9kUgz11FWW+ufhMLWdufY7Y56bWYSxWW2K0pS576y48zZr2tycua5Yp6mtLsVsqX3C+pbKWXpur19p6zC3niPqsfZ9ZW5e5ZUzVa257TcVjzfK2brO5drC1DlP7y5p9Zc9nmLUxWrMPrYnd0nvZmnpM0ZUvjn1uaR2WlnM1dg9IVaNGDcyePVt6XbFiRaxevRqZmZlwd3eHl5fpoRSIiIiIqOxy+Iinfn6Of7IGEREREZUeViWY48aNs2vlgiBgxYoVdi1LRERERKWTVQmmbhB1W+nfhk9ERERE5YFVCaa1Qw1R8ZJ5O+7yA3vXZetytpS3tqzcp5JNMdhTV1Hmm4vP1HLm1ueIfW5qHcZitSVGW+qyt+7C06xpf3vismaZor62FLul8gXnWypr6bW5eq2tx9xyjqjP2veZtXWZW8ZUvea211Q81ixv6zabawdb6zC1v6zZV/Z8hlkbozX70JrYLb2XranHFF354tjnltZhaTlXY9c4mMWB42ASERERubZiHQdT5/Lly9iyZQsuXryI9PR0bN68Gfv27UN6ejp69uwJmczO5ywTERERUalld4K5evVqLFu2DGq19iH2uustY2Nj8f333+OPP/7AsmXL4O7u7phIiYiIiKhUsKuLcc+ePViyZAkaN26M7777DsOHPxlJfuDAgWjdujX27duHn376yWGBEhEREVHpYFeC+d1336FWrVr44Ycf0KpVK/j4+EjzateujdWrV6NOnTrYsmWLwwIlIiIiotLBrgQzMTERHTp0gIeHh9H5crkc7dq1Q1JSUpGCIyIiIqLSx64EUy6X4/Hjx2bLpKenQy6X2xUUEREREZVediWYjRo1wt69e5GRkWF0/oMHDxATE4OGDRsWKTgiIiIiKn3sSjBHjRqFhw8fYvDgwfjjjz/w4MEDAMDt27exe/duDB48GBkZGXo3/xBR8UvLy8aImHW48PCOs0MhIqJyzO6B1iMjIzFnzhwolUoAgCiK0lBFMpkMH330Ed555x2r18eB1omKblH8n/jidAyqefvh1MAZzg6HiIjKmGIfaL1fv35o164dtm3bhgsXLiAzMxMVKlRA/fr10bNnT9SuXdveVRORnZT549LmqBROjoSIiMqzIj3JJzAwEKNGjTI5PzMzE35+rv+8TKKyxiWe/0pEROWWzddg5uXlISsry2K5Xbt2oUuXLnYFRUT2yb9KhYiIyKms7sE8deoUFi5ciNOnTwMAqlevjnHjxqFPnz565e7cuYNPP/0UBw8edGigRERERFQ6WJVgnjlzBkOHDoVKpYKbmxv8/Pxw+/ZtTJ8+HRkZGRg2bBgA4JdffsH8+fORk5MDX19fTJgwoViDJyLj7Lx3j4iIyCGsOkW+Zs0aqFQqjB07FvHx8Th69Cg2b96MoKAgrFq1CgqFAnPmzMGsWbOQk5ODN954A7t27cLgwYOLO34iKkAAz5ETEZHzWZVgnj17Fk2aNMH48ePh7u4OAGjYsCE+/vhjZGRk4JNPPsGGDRtQuXJlrFy5EsuXL0dgYGCxBk5ERERErsmqBDMtLQ2vvPKKwfSQkBAAwPbt29G8eXNs27YN4eHhjo2QiGzGE+RERORMVl2DqVAojA43pJv29NNPY82aNfDy8nJsdERkE54gJyIiV2DXoyIL69y5M5NLIiIiIgLgoATTx8fHEashIgcReZKciIicyCEJJhG5BoEjrRMRkQuweqD12NhYrFy50qZ5giBg7Nix9kdHRERERKWOTQlmbGysTfOYYBI5B8dZJyIiZ7IqwZw/f35xx0FEREREZYRVCWbh540TEREREZnCm3yIyiDeRU5ERM7EBJOoDOFd5ERE5AqYYBIRERGRQzHBJCIiIiKHYoJJRERERA7FBJOoDOEVmERE5AqYYBIRERGRQzHBJCqDRD7Kh4iInIgJJlEZIvAkORERuQAmmERE0Pb6ZipynR0GEVGZYNWjIomodOEJctt9cnw7vk84iv19JuL5StWcHQ6VI59++il27txpML179+749NNPSz4gIgdggklUhvBBPvb7PuEoACDu/g0mmFSiJkyYgNGjRxtM9/b2dkI0RI7BBJOIqAA+x51Kmr+/P/z9/Z0dBpFD8RpMojKId5Hbj7uOiKjomGASlSG8i5zIsaKiolC/fn2L/6Kjo82uJyEhAfXr10dERITe9EePHuGzzz5DeHg4GjdujK5du2LNmjVQqVTFuVlmjRgxAvXr18fIkSOdFkNxW7FihdF2DAkJQe/evbFmzRoolUq9ZSIiIlC/fn0kJCTYVNetW7dQv359DBkyxJGb4PJ4ipyIqACeIidjQkNDERoaanL+c889Z/M6s7KyMGjQIFy9ehVhYWHo2LEjTp06hUWLFuHkyZP46quvIJTwhdUpKSk4cuQIvL29cejQIdy7dw9PP/10icZQkjp06ICXXnoJAKBWq5GVlYUTJ05g0aJFOH36NFatWiWVDQ8PR40aNVClShVnhVuqMMEkKoOYIhE5VmhoKMaPH+/Qda5evRpXr17FjBkzMHToUGn6pEmTsHPnThw4cADt27d3aJ2W7NixA2q1GiNGjMCKFSuwefNmjBs3rkRjKEnh4eHo27ev3jRRFDFmzBhER0fj6NGjaNWqlVQ2PDzcGWGWSjxFTlSG8AQ5Uelx+/ZtPPPMMxg0aJDe9K5duwIA4uPjSzymrVu3wt/fHyNGjICfnx+ioqLK3TXdgiBISWdcXJyToym9mGASERE50MWLFzFmzBiEhoaiefPmmDZtGtLS0gzKLV68GPv374ebm/7JxKtXrwKA3qnYiIgINGjQAI8ePcLHH3+Mli1bIjg4GO+99x6SkpKgUCiwcOFCtG3bFiEhIRgyZAguXrxoc9yJiYlo1aoVvLy8EB4ejtu3b+Pw4cMml0lKSsLEiRPRunVrBAcHY+TIkbhy5Qo6duxYqq85lMvlAAAPDw9pmr3XYJZXPEVOVAbxOsIi4K6jIkhISMDgwYOhUCjQqVMnVKxYETExMTh48KDZ5URRRGpqKnbv3o0VK1agevXq6Nmzp0GZoUOHQqPRoE+fPrh06RIOHTqE999/H7Vr18alS5fQuXNnpKSkYPfu3Rg1ahT27Nlj9XiaW7duBfCkB7Vr167YsmULIiMj0bZtW4PyN27cwMCBA5GWlobw8HAEBQVh3759GDRoEDQaTam9dlMURWzZsgVyuZynxIuACSZRGVLSNwQQlRexsbFYsWKF0Xl9+vRBUFAQAGDu3LnIzc3F2rVrpWv3xo8fjyFDhiAlJcXk+pctW4avvvoKgLbncu3atQZjY2o0Gnh7e2P9+vVSz9rAgQMRHx8PhUKB7du3w9fXFwAwbdo0REVFITY2Fq+99prF7VOr1di5cyd8fHyk6z5bt26NypUrIyYmBqmpqQgICNBbZv78+UhNTcWyZcvQuXNnANpB49955x2cPHnSYp2uIDo6Grdv3wagTSwfP36M2NhY/PPPP/jkk0/w/PPPOznC0osJJhFRAez9JWNiY2MRGxtrdF5oaCiCgoKQnJyMuLg4tG/fXkouASAgIABjx47FhAkTTK6/Zs2aGDlyJK5fv46YmBgMHjwY33zzDV5++WW9cm+//bbeadvg4GDEx8djwIABUnIJAI0bN0ZUVJSUPFly+PBhpKSkoHfv3vD09AQAuLm5oXPnztiwYQO2bduG4cOHS+VTU1Nx4MABNGvWTEouAe0p5cmTJ+Ptt9+2ql5ni4mJQUxMjMF0f39/ZGRkQK1WS6fLyTZMMInKoHJ2Tb5DcdeRMePGjbN4F7numseGDRsazAsODja77Jtvvin9vW/fPowZMwZTp07Fjh079M5M1KpVS2+5ChUqAIDUg6qjSxIVCoXZenW2bdsGAOjWrZve9B49emDDhg3YvHmzXoJ54cIFaDQaNG7c2GBdr7zyisF1pa5q/vz5eneRZ2dn4+rVq1i+fDmWLFmC69evY/78+U6MsPQqHUcAERGRi8vIyAAA+Pj4GMyz5VGQYWFhaNWqFY4cOYKkpCTUrl1bmqdLKAsr2KtpTEJCgtHB4MePH4+srCxpnqnB1S9fvoxTp04hJCQEgHaAeABGx4SUy+UGp9NLiwoVKqBhw4ZYuXIlwsPDERUVhZEjR6JOnTrODq3UYYJJRFRAeRuShRynYsWKAIDMzEyDednZ2XqvVSoVYmNjIYoi2rRpY1C+evXqALSJXMEE014JCQlYuXKlwfTx48dj9+7dyM3NRaNGjdCgQQODMteuXUNsbCwiIyOlBFN3Oj4rK8tofY8fP9Z7rVQqsWjRIulGos6dO2PGjBkmE2NL5ZOSkjBv3jycPHkS3t7e6Nq1KyZMmCD13Op8/PHHuHHjBtatW2dizxjn4eGB4OBg7N69G4mJiSYTzPT0dMyZMwd//fUXPD090atXL0yYMMGq0+pXrlzBnDlzcObMGVSqVAmDBw/GiBEjpPnWbqOrYoJJRETkAA0aNIAgCDh16pTBvPPnzxtMGz16NHx8fHDo0CGDhOTixYsQBMHg1Le9+vbtazCguI7u9HhERASaNWtmMP/OnTvo0KEDdu/ejRkzZsDX1xcvv/wyBEHA2bNnDcpfvnzZIMFcsGABYmJi8OWXX0IQBEyePBmrVq0yeV2qufIKhQKjR4/G888/j02bNuHhw4eYPn26tA06R48eRWRkpNknMJmj65H28/MzWWb27NlISUnB+vXrkZqaismTJ6NSpUp6iaIxSqUSI0eORIsWLTB79mxcvXoVkyZNQrVq1dCzZ0+rt9GVcRxMojKEzyIncp6qVavi1VdfxbFjx7Bnzx5pelZWlkHvoZubGzp27IjU1FSsXbtWb95PP/2E8+fPo3379sX+WMLbt28jLi4ONWrUQNOmTY2WqV69Olq2bIns7Gzs2rULABAYGIg2bdrgyJEjOHDggFRWNx5nQRkZGdi4cSPmzJmDpk2bIiQkBOPGjcOFCxeM1mep/NmzZ5GUlIT58+ejbt26CA0NxQcffIAdO3ZI68jOzsYnn3wi9bja6syZM4iNjYW/v7/RpFvnwIEDGDZsGOrVq4eWLVuie/fuOHbsmMX1Jycno3Hjxpg1axZq166NsLAwtG7dWhrY3ZptdHXswSQiInKQmTNnYuDAgfjwww8RHh6OwMBA7Nu3DzKZYX/OlClTcOLECSxevBjHjx9HvXr1kJCQgKNHjyIoKAizZ88u9ni3bdsGURTRo0cPs8Oc9e3bF0eOHEFkZCQGDBgAAJgxYwYGDBiAMWPGSNt6+PBhpKamAoC0zbpTvK1bt9Zbn6keVUvl69Spg9WrV+td6yoIgtTjCABLly5FaGgoqlatarRHWafgMEWAdrimy5cvY//+/VCr1Zg+fTq8vLxMLl+pUiVs374dbdq0QUZGBg4ePGjV2JlBQUH44osvAGgvyzl16hTi4uIwa9Ysq7fR1THBJCqDONQOkXPUrFkTP//8M5YuXYrDhw8jLy8Pbdu2xQcffGBwh3ZgYCA2b96M5cuXY9++fTh27BiqVauGYcOGYcyYMXjqqaeKPV7d6fHCg7oX1rFjR/j5+eHcuXNITExE/fr1UadOHWzcuBGLFy/GkSNHoFKp0LJlSyxduhQ9e/aUBnhPSkpC9erVsXPnTnz99dfIzs5G586dMWHCBKPXYFoqHxAQoJd8ajQarF+/XpoWHx+P3bt3Y+fOnfj222/NblfhYYrc3d0REBCAsLAwDBkyxOLp9VmzZmHKlCkICQmBRqNBy5YtbX5mfbt27XD//n2EhYWhU6dOAGBxG0sF0UWcPXtWPHv2rLPDICrVVpzZK9b4dqpY49upzg6l1NHtt+//PuLsUIhcnlqtFq9fvy4qFAqDeUlJSWK9evXEWbNmiaIoiqtWrRJDQkLE/v37i3FxceL+/fvFsLAw8bPPPjO6blvLf/bZZ2Ljxo3FS5cuiXl5eWKXLl3E3377TRRFUVyyZIn4r3/9yzEbbcS6devE4cOHiydOnBD3798vdujQwWScppw9e1aMjo4W27ZtK86ZM8domYLb6GzW5mvswSQiIiKbCIKA3r17IzAwENu3b9fridRdU9qiRQsA2utNs7KysHDhQmkczylTpmDKlCmYNm2aweUD1pYXRRFz587Fxo0bsWzZMrzwwgtYunQpateujS5duhT7PtDd5b13717psZienp5499138f7771t9/WyjRo0AALm5uZg6dSqmTJki7U9j21haMMEkKkM4wk7RcRcSWSYIAgYOHIhvv/0WPXv2RLt27SCXy3Hq1CmcPn0abdu2lZ7wU61aNbi5uekNEv/cc88hLy8PqampBomYNeU1Gg1mzJiBHTt2YOnSpdJ1jzt27EBKSoo0sL1SqYRarZaeeORI58+fh5+fn94z1xs2bAi1Wo07d+6YTTCTk5Nx/vx5dOjQQZpWt25dKJVKZGVlISAgwOQ2lhZMMInKIN5NTkTF7aOPPkKdOnUQGRmJLVu2QKVSISgoCJMmTcLw4cOlm4aaNGkClUolXbsJaMeA9PHxQaVKlQzWa035zz//HDt27MCKFSsQFhYmLbtu3TqoVCrp9ffff4/z589j0aJFDt/+atWqISMjA/fv30e1atWkOAHDJysVduXKFYwfPx4HDx5E5cqVAWifjhQQECANUm9qG0sLJphkkx8SjuLXK/GI6vo+3GR8Pqur4c09RFRSZDIZ+vXrh379+pkt9+yzz6JDhw6YNm0a/vOf/yA3NxeLFi1C//79pUdKpqWlQS6Xw8/Pz2L506dP44cffsCkSZPQsGFDpKSkSHXVqFFDr+6KFSvCy8vLIYPVF9akSRPUq1cPU6ZMQUREBHJzczFz5kz06tXL4pOMmjdvjrp16yIiIgIRERFISkrC4sWLMXr0aAAwu41Vq1Z1+LYUByaYZJMZx7R3HCZlpqKOf+k4yMsTMf8cuZnRRoiIStyCBQswd+5cDBs2DG5ubujduzcmTpwozR8/fjxq1KiBzz//3GJ53RijixcvxuLFi/XquXDhQok9B93NzQ2rV6/GvHnzMGzYMLi7u6Nz586YPHmyxWXd3d2xevVqzJ49G/369YOPjw+GDRuGoUOHAnCdbSwKQRRd46qtc+fOAXhysSu5pqDvtE8QONB3EuoywXQ5X5yOwaL4PyEXZLjxzjxnh1Oq6I7tOS16YniDUjQUCBFRCbI2X+OTfMguLvK7hArRnSJnByYRETkTE0yyC9NL12buiRxERETFjQkm2YU3kxin1mgw9M/vsPnySafUz45lIiJyBUwwyS5MZIy7nvkQe28l4sODkU6pn6fIiYjIFTDBJLuwB9M4Zyd2ulbhKXL78dgmIio6JphkF/ZgmuLcxI43XxGVXRpR4+wQiKzGBJPswl4e41yl45BP8iFb7L99CXHJ150dBpkRfTMBtb6fjsN3rzg7FCKrMMEku7CnzDiZq2SYRDb41x/fos9vXzs7DDLji9N7AQDfXDjk5EiIrMMEk+yi5qkao5ydd/NJPkRlk+7HK88eUWnBBJPsonZ2JuWinH2NlHSTD0+RE5Upune0hp+9VEowwSS7qDXswTTGUuJd3JcWOGKYoqTMVMw/sRu5KqVjgiKiIpN6MEtpfnnncTo2JMby8qpyhAkm2YWnyI0z17uQnJ2Bmt9PK9ZrqHTVF2WYondjfsSqc/vx48VjjgmKiIpM957WlNJT5P1/X42pR6Kw91ais0OhEsIEk+zCBNM4c/vlwO1LAIBPY3cWexxF6SW4lfUIAJCa99hR4ZQqpfPrm8o66SdjKe0BvJ75EACQnJPh5EiopDDBJLvwOiDjzF2DWRJ3mDsi8dfFyTYuH3i5S2lRNq6r5udK+cEEk+zCHkzjzF2DKQjF/3ZTqFUAinYaTfc1Vl5v5Cpv14ipyvh7WaVRO/3mO0cq7UcnE8zygwkm2aW8Jh+WqDRqk/NkJdADocivvyjNo0uERRf9Ur7zOB2nUpKKbf3l7QvQ3DFbFjT66T/otmOVs8MoMt0JkNI+TFF5e3+VZ0wwyS5lqUfAkfLyexCdRanR1l+ULyG5i58iD/1lPnru/LLY7nJXaKxvw0+ObceaCweLJY6Soipwirws9t5mKvNw7uFtZ4dB+fjdUX4wwSS78Lot4xRmeoNKYvDzHAckXaXlGszHqrxiWW+W0vr1fpdwBLNjdxVLHPawJ0FUiU+OWaWL9WZGXYnHi+tn4V62fTeGlKWEuayMbevqnyvkOEwwyS5l/boteynM9GCWxOfqo7xsAIC7TG73OtQabaCu/thLWxLB4livs5MxURSRqciVXn98bBtqfj8N6Xk5Nq1HWeDHosqKH44bEmNxPeOhTXXY6//++hlZyjzsvHbWruVznXxGoTgwP6PSggkmWa1gb0CajV9i5YW5HkSlDade7ZWSkwVAmyQVTD5soYvTXebmsLiKQ5bCcQlmwdN21iZo2UqFw+q3x/rE43hpw6c4fu8aAOD7hKMAgMS0ZJvWk1XgOLGUNMen3MTUI1HosHWpjdEWjb3JfI7qSRuZ681UazRYdXY/7mSl2VWPtU7ev4G45Ot2LZur1n62eLmZfl/mqVX4T+xO3MgsmR8A9pCbudkxKTMVf6feKcFoqDi59jdIMVFq1EjOP+VS8EOn4MdPwWvYdEWMTSu8pCjNt369Bacbm2ZQh4V4RCPxFIzJmniM1Xc/J1OaduTeFYRUrQUPuRxuMpnF0zfm5lozKLgoPolUhKi3D57E/WT7Cm5rwX1beD+L+SWMzRehv79MxYACfx+5e0WK+fCdy6hawQ8yCBABxN2/Ic1LfJQMD7nc7l5CUdQex0qNCnlqNRRqFe5mp+Ny2n2pzNq/D+PV6i+ggpsH5DIBckHbTnKZAI0oSv/UogYaUQO1RoQGIjLze/BuZqXin7T7cJfJjZ7eN9bmxrZG1wYaUbefRKmNdPNEUXvqTJoiPpkuLYsnbQJokx1fD0+bTx2KEKHSaKBQq6HQqKBQq3AlPUWafzz5GmKTr8PX3RMeMjnkMhlEaV/pYtHgavoDaZlLacnwkrsX60lMTX7c2n9qTDu6FQCwOP5PfNaql1Tu79S7qObtB5mg3TMaiNq2FTV6f2vbXcTJAjdM7b99CY0qVwcgQBC0baxre40oIjZZm8zmqVVSL6ZUDqbbWte2+u2qMdvOBT+PrmU8xLWMB1JyopHaQdS2DZ4cz2KBeTcyU6V1nHlwC5U8KxRY95PjcPu1s1hyOhpfnIlBTO8Jdn1eidLxoYG6wPtKpdFI03vt+goAcPDNyZh/YjcupN7BD+HvwFPuZnRZtUb7t1oU8TBHOy7t7aw0JD5Kls5SFGyn7xOOYs2FQ/jh4jHs6zPR6HZYE7/uWFeLmvzp2hgyFbnYfu0M+tRpgpp+AU/WqVsHIB1X2u1WS9uvc/HRPVxJT4FckBls7xvblgMA9vWZCC+5m7TOJ61l+P1n7PNftz0FX/9+4zx+uHgMK18biBsZD3HmwS2837Cd9D4RClwa9OQYfnJMGhxzBco9VuZBJWpQp2IVvToLxmksdv349ZfU/fXt34fxT9p9LGjzJuSCAEEQjH7mVfbygZebu8F0ZxJEF7lI5dy5cwCARo0aFXtdNzIfos3mhcVeD5EzfBTcEavOHUC2yrk9bKWNAAG1/QKkAaGJiEqLzV1GoeXTdUqkLmvztXLZg+nr7okBLzQtMEUw+KvgrzzByPyCZYxNM75W/Rs9dOu1tLzxdRaIy9L8AkWMTbMmFp1XqgSh/lOB2Hb1DB7kZEElaiyevjL3G8byrxtRiqrgr8yCv+EKtoNhmwgG2164XOFlBAjSzik4zWA9guE63WQydK3dCOdT7+Dvh3eg0KjzL2oX8ZSXD16pXAMXHyXjfk4m8tSqIt3t7SGTw10mh4fcDR5yN/i6eaJt9bpoWLkG+tYNxp83E3A/JxM5KmWBnghtb4EMAuQyGWSCUOBvGeSCAF93TzSpUhOH715BljLX6I1LxtrU+JaI+ftOkNpMyO8x0PbeCno9YIIgPOlRyG8HXVldG1Rw84BckOFudrpdd+2LoijtN3eZHJ5yN3i7uePV6i/g5YBnsOv6eVx8dA85KgWUGm0PjEwXl6DtCdbtNz8PL6hFDVJzH9sci60tL0B7ba2bTHvWwE2Q487jNPh7ekMmCPCSu0ttXbB3RZYfs7xA/Nq/tf/LBAHNqtVGjkqJ0yk38Vil0Otd1u0zmSCDr7sHHisVcJfLpe190rOvfa/KCrS1bp/p3iUFe4sKtquxdpZBgCy/9zgtLwcqjRpqUaM9RvKPKV15WYHlZfnbpntd2csHCrUad7PTpWtMC8ag+/9WVhpq+FYyfx21hRaVC/L8fardtwXfV3JBhkxlLh7lZsPH3RMCtENuPePjD42okcrJ8o8vuXSsySCXCfB198LrQfUQffMi7udkQq3R6J0JALQjQDzMfYwALx+jw0+Z+yTW7kfjMRQ8bv68mYCXA6rDTSYzuk65IIObTCb9LxNkcBNk8PPwQoOAZ3Dk7hVkqxRQaTQG+ypXpURydgaqePtp2zp/nQU/93XtB4N5+q/1ywnQiBpcfHQP9SoFIkuZhzuP0/B8pWp6+6/gfpCOpfx1FjzmZPnHrCz/2EvOzkBs8nW0euY5qVbjMdoef3J2JjIUOahdsXJ+rMZbsaq3n9HpzlQuezCJiIiIyHbswSyDfv7nBABgwAvNnLYuW5ezpby1ZScd2gwAWNz2LatisKeuosw3F5+p5cytzxH73NQ6jMVqS4y21FWYtXUXnmZN+9sTlzXLFPW1pdgtlS8431JZS6/N1WttPeaWc0R91r7PrK3L3DKm6jW3vabisWZ5W7fZXDvYWoep/WXNvrIUn465zxpb97U1bW1snQVjsbUeU3TlY/Nv1nLUPjcVqz3fGa6CCWYpYu9dwY5cl63L2VLe2rLp+UPxFIWluooy31x8ppYztz5H7HNT6zAWqy0x2lKXvXUXnmZN+9sTlzXLFPW1pdgtlS8431JZS6/N1WttPeaWc0R91r7PrK3L3DKm6jW3vabisWZ5W7fZXDvYWoep/WXNvrLnM8zaGK3Zh9bEbum9bE09pujKF8c+t7QOS8u5Gg5TREREREQOxQSTiIiIiByKCSYRERERORQTTCIiIiJyKN7kU4r4eXg5fV22LmdLeWvL+ntWsCkGe+oqynxz8Zlaztz6HLHPTa3DWKy2xGhLXfbWXXiaNe1vT1zWLFPU15Zit1S+4HxLZS29NlevtfWYW84R9Vn7PrO2LnPLmKrX3Paaisea5W3dZnPtYGsdpvaXNfvKns8wa2O0Zh9aE7ul97I19ZiiK18c+9zSOiwt52o4DiYRERERWcXafI2nyImIiIjIoZhgEhEREZFDMcEkIiIiIodigklEREREDsUEk4iIiIgcigkmERERETkUE0wiIiIiciiXGWhdqVRCFEVpfCUiIiIici0KhQKCIFgs5zI9mIIgWBWwo6jVamRkZECtVpdYneRcbPPyh21e/rDNyye2e8mxNl9zmSf5lLQLFy6gb9++iIqKwssvv+zscKgEsM3LH7Z5+cM2L5/Y7q7HZXowiYiIiKhsYIJJRERERA5VbhPMqlWrYty4cahataqzQ6ESwjYvf9jm5Q/bvHxiu7uecnsNJhEREREVj3Lbg0lERERExYMJJhERERE5FBNMIiIiInIoJphERERE5FDlMsE8dOgQ3nzzTbzyyit4/fXXsXbtWvBep7JBo9Fg48aN6NGjB4KDg9GhQwfMmzcPWVlZUpkbN25g9OjRaNasGVq0aIFZs2bpzafSbdy4cXj99df1prHNy6bTp09jyJAhaNKkCVq3bo2pU6fi4cOH0ny2e9nzyy+/oFu3bmjSpAm6dOmCDRs26H1/s81dh8s8i7yknD59GqNHj0aXLl3wwQcf4OTJk1i4cCHUajVGjRrl7PCoiL755ht88cUXeO+999CqVStcu3YNy5cvxz///INvv/0WmZmZGDZsGKpUqYLPP/8cqampWLhwIW7duoW1a9c6O3wqom3btuHPP/9EjRo1pGkZGRls8zLo/PnzGDp0KFq3bo2VK1fi/v37WLJkCcaOHYtNmzax3cugyMhIfPLJJxgyZAg6dOiAEydOYM6cOcjLy8O7777LNnc1Yjnz7rvvim+99ZbetAULFojBwcFiTk6Ok6IiR1Cr1WKzZs3ETz/9VG/6rl27xHr16olnz54Vv/76a/GVV14RHz58KM3fv3+/WK9ePfHEiRMlHTI50L1798TmzZuL7dq1E8PCwqTpbPOyaejQoeKAAQNEtVotTduzZ4/Yrl07MSkpie1eBg0YMEB8++239aZNmDBBer+zzV1LuTpFrlAocPz4cXTs2FFveqdOnfD48WOcPHnSSZGRI2RlZaFXr17o3r273vQ6deoAAG7evIlDhw6hadOmCAgIkOa3bdsWPj4++Ouvv0o0XnKsjz/+GG3atEGrVq30prPNy55Hjx4hNjYWb7/9NmSyJ19jb7zxBg4cOICaNWuy3cugvLw8+Pr66k2rVKkS0tLSAPC97mrKVYJ58+ZNKJVKPPvss3rTa9euDQC4du2aE6IiR6lYsSI+/vhjNG3aVG96dHQ0AOD555/HlStX8Nxzz+nNl8vlCAoKYvuXYpGRkbhw4QI++eQTg3ls87InMTERGo0GAQEBmDRpEoKDgxEcHIwpU6YgIyMDANu9LBo6dCgOHTqEbdu2ITMzEwcPHsSWLVvQq1cvAGxzV1OursHMzMwEAINfQD4+PgDAC4HLoDNnzmD16tUICwtDvXr1kJmZKbV3QT4+Pmz/Uur27duYP38+5s+fr9dzocM2L3tSU1MBANOnT0e7du3w5Zdf4vr161iyZAlu3ryJn376ie1eBnXr1g2xsbGYMmWKNK1t27aYPn06AL7XXU25SjA1Go3Z+QVPtVDpd/LkSYwePRpBQUGYP38+AJgdLUAQhJIKjRxEFEVMnz4dr732Gjp16mSyjCls89JJqVQCAF5++WXMnTsXANCqVStUrFgREydOxOHDh9nuZdC///1vnDx5Eh999BEaN26MS5cuYcWKFfjggw+watUqtrmLKVcJpp+fHwDg8ePHetN1v2wK92xS6fXbb78hIiICzz77LL755hs89dRTALRtXLj9Ae0xEBgYWNJhUhFt2LABiYmJ2LFjB1QqFYAnCaVKpYJMJmObl0G6XqqwsDC96a+++ioA4O+//2a7lzGnTp3CwYMH8dlnn6Ffv34AgNDQUNSsWROjRo3C/v372eYuplwlmLVq1YJcLseNGzf0piclJQEA6tat64ywyMHWrl2LhQsXIjQ0FKtWrZJ+WADAc889J7W3jlqtxq1bt/DGG2+UdKhURHv27MGjR4/Qtm1bg3kvv/wyxo0bxzYvg3TX0SsUCr3puh8ZXl5ebPcy5s6dOwCAkJAQvenNmjUDAPzzzz9scxdTrs4Je3p6olmzZvjzzz/1utL37NkDPz8/NG7c2InRkSNs2rQJCxYsQJcuXfDNN9/oJZcA0KZNG8TFxUnXcAHaOw+zs7PRpk2bkg6Ximj27NnYvHmz3r+wsDBUrVoVmzdvRv/+/dnmZVDdunVRo0YN7Nq1S++zPCYmBoA26WC7ly260UBOnDihN/3UqVMAgJo1a7LNXYwgmrtooQw6evQohg8fjjfeeANvvvkm4uPj8fXXX2PSpEkYOXKks8OjIkhJSUF4eDgqV66MBQsWwM1Nv4O+Vq1aAICuXbsiMDAQ48aNQ1paGhYuXIhXXnkFa9ascUbY5GARERGIjY3F3r17AWhvCGGblz27d+/Ghx9+iM6dO6N///64fPkyli5dildffRXLly9nu5dB//d//4eDBw9izJgxeOWVV3D58mWsWLEC1atXxy+//IKMjAy2uQspdwkmAPz5559Yvnw5rl27hsDAQAwePBjvvvuus8OiItq8eTNmzJhhcv78+fPRt29fXLp0CfPmzUN8fDx8fHwQHh6OKVOm8BrcMqJwggmAbV5G7du3D6tWrUJiYiL8/f3Ro0cPTJgwAR4eHgDY7mWNQqHAV199hW3btuH+/fuoXr06wsPDMXbsWOm6XLa56yiXCSYRERERFZ9ydQ0mERERERU/JphERERE5FBMMImIiIjIoZhgEhEREZFDMcEkIiIiIodigklEREREDsUEk4iIiIgcigkmERERETkUE0wiIiIicigmmERERETkUEwwicjpUlJSMHPmTLz22mto2LAh2rRpg8mTJ+PmzZsGZZVKJVatWoXw8HA0atQIr7/+OpYuXQqFQmFTnR9//DFGjx5tsVxCQgLq16+PiIgIm9Zf1nzxxRcYMGAANBqNs0MholKACSYROVVKSgr69euHn3/+GXXr1sWQIUPQqFEj7Ny5E2+99RauX7+uV37KlClYvnw5goKC8M477+DZZ5/F119/jbFjx0IURavqPHbsGLZs2YKPPvqoGLaobBoxYgRu3ryJ9evXOzsUIioF3JwdABGVbytWrMDdu3cRERGB4cOHS9O3bduGKVOm4PPPP8fXX38NADh69Ch+++03vP322/j000+lskuWLMH//vc//Pnnn3jjjTfM1qdSqTBz5kx0794ddevWLZZtKot8fX0xatQoLF26FF26dEHVqlWdHRIRuTD2YBKRU0VHRyMgIADDhg3Tm96rVy/UqlULhw4dkk7LRkVFQRAEjB07Vq/sv//9b3h7e2PLli0W69uzZw9u3LiBIUOGOG4jyom33noLoihi3bp1zg6FiFwcE0wichq1Wo33338f48aNg0xm+HHk4eEBpVIJlUoFADh58iSee+45g94zLy8vvPTSSzh58qTFOr/77jvUqVMHDRs2NJh38eJFjBkzBqGhoWjevDmmTZuGtLQ0o+vJysrCokWLEB4ejoYNG+LVV1/FrFmz8PDhQ4OySUlJmDhxIlq3bo3g4GCMHDkSV65cQceOHfUS3SFDhuD111/HgQMH8Prrr+OVV17BBx98YFed1pZVqVRYuXIlevTogSZNmiA0NBTvvfcejh49arBOX19ftG/fHps2bUJ2drbJfUxExFPkROQ0crncoOdS58qVK7h69Spq1aoFDw8PKBQK3L17F61atTJavlq1ajh16hTS0tJQqVIlo2WSkpJw7tw5DB061GBeQkICBg8eDIVCgU6dOqFixYqIiYnBwYMHDcpmZmZi0KBBuHTpElq1aoU33ngDt27dwi+//IKDBw9i06ZNqFatGgDgxo0bGDhwINLS0hAeHo6goCDs27cPgwYNgkajwdNPP6237kePHuHDDz9Ehw4d4OvrK53Gt6VOW8rOmTMHmzZtQmhoKNq1a4fMzEz89ttveO+99/Ddd9+hRYsWevG1bdsWv//+Ow4dOmTxcgQiKr+YYBKRy9FoNJgzZw40Gg369+8PQJs0aTQa3L59GytWrDBY5tq1awCA9PR0kwnm8ePHAcBo7+XcuXORm5uLtWvXSkns+PHjMWTIEKSkpOiVXbJkCS5duoSZM2di8ODB0vSYmBj8+9//xty5c7Fs2TIAwPz585Gamoply5ahc+fOAIAJEybgnXfeMdrjmp2djeHDhxvctW5LndaWzcrKwi+//ILmzZvrnfbu168f3nrrLWzYsMEgwdTtu9jYWCaYRGQSE0wicimiKGLmzJk4evQoGjZsKPVw6oYhun79OlauXGly+dzcXJPz/v77bwDA888/rzc9OTkZcXFxaN++vV4PaUBAAMaOHYsJEyZI01QqFbZu3YoXXnhBL3kDgA4dOiAkJAR//vknsrKyoFAocODAATRr1kxKLgHtqf/Jkyfj7bffNhpn4cTNljq9vLysLqvRaCCKIu7evYuUlBTp0oNGjRohOjraoHcVAOrUqQOZTIbz588bjZ2ICGCCSUQuRKVS4ZNPPkFUVBRq1qyJL7/8Eh4eHgAg/d++fXv873//M1h20qRJ2LlzJ7y8vEyuX3f94VNPPaU3/eLFiwCM92wGBwfrvb527Rqys7OhVquN9qTm5eVBrVYjMTER2dnZ0Gg0aNy4sUG5V155BW5uxj+Cg4KC7K6zYsWKVpdt2rQpunbtil27diEsLAzBwcFo164dwsLCDJJwHQ8PD/j6+uLRo0dG5xMRAUwwichF5OTk4IMPPsCBAwfw7LPP4rvvvkNgYKA038/PDzKZDFlZWUaXf/z4MQDA39/fZB26ZQsnoRkZGQAAHx8fg2UKr09X9urVq2Z7UtPT06X6qlSpYjBfLpcjICDA6LKm4rOmTh1ry/73v/9Fw4YNERUVhdjYWMTGxmLRokVo2LAhPvvsM7z00ksGy3p7e+vVRURUGBNMInK69PR0jBw5EmfOnEGDBg3wzTffoHLlynplPDw88Mwzzxh9ug+gvYHH39/f5PWXwJNkMSsrSy+5q1ixIgDtdZ6FFb5bWpeE9urVCwsWLDC7XXv37pXqM0aXFFtiS5263lhrygKAu7s73n33Xbz77ru4c+cODh8+jN27d+PQoUN4//33ERMTA3d3d71lMjMzzSbyREQcpoiInCovLw/vv/8+zpw5g9DQUKxbt84gudRp2rQpkpOTcfXqVb3pumlNmzY1W5fuGsPCp3cbNGgAQRBw6tQpg2UKX2v43HPPwcPDAxcuXDD65KDvv/8eX375JR49eoSXX34ZgiDg7NmzBuUuX75sdYJpS522lL158yaWLFmCffv2AQCqV6+Ofv36Ye3atWjZsiWSk5Nx69YtveXz8vKQnZ1t9PpMIiIdJphE5FRLlixBfHw8goODsWbNGvj6+pos27dvXwDA8uXL9ZKnlStXQhRF9OnTx2xdL7zwAgDgn3/+0ZtetWpVvPrqqzh27Bj27NkjTc/KyjI4zezp6YmuXbvi8uXL+O677/TmHT9+HAsWLMCvv/4Kf39/BAYGok2bNjhy5AgOHDgglVMoFFi4cKHZWO2t05ayXl5eWLNmDZYtW6b3LHeFQoGUlBR4eHgYjDl66dIlAMCLL75odfxEVP7wFDkROU1KSgo2bNgAQHt38po1a4yWGzVqFDw9PdGqVSt07doVv/32G+7fv4+QkBCcP38eR48eRbt27dCxY0ez9b322msQBAEnT57EW2+9pTdv5syZGDhwID788EOEh4cjMDAQ+/btMzoA/NSpUxEfH4///ve/iImJQePGjZGcnIw//vgDbm5umDdvnrTcjBkzMGDAAIwZM0Za7+HDh5GamgoARtdvjC11Wlu2atWqGDZsGL777jt0794dr732GmQyGQ4ePIgrV67g3//+t0HCr+vlbdOmjVVxE1H5JIjGzqEQEZWA6Ohog8c+GhMXFyddJ6lUKrF69Wps2bIF9+7dQ7Vq1dCjRw+MHTtWutPcnH79+iElJQV79+41SO5u3bqFpUuX4vDhw8jLy0Pbtm3xwQcfoFu3bujTpw8+//xzqWxaWpr0/PN79+4hICAATZo0wb///W+D3r3Lly9j8eLFiIuLg0qlQsuWLTFhwgT07NkTYWFh0rPWhwwZgtjYWL3tLciWOq0tq1ar8csvvyAyMhJJSUlQq9V4/vnnMWjQIKM9wqNGjUJ8fDwOHToET09Pi/ubiMonJphEVK7s2rULEydOxLffflvsvXAajQY3b95E9erVDW6UuXnzJsLDw/H222/j008/LdY4HCU5ORlhYWEYNWoUPvzwQ2eHQ0QujNdgElG50qVLFzz77LP45Zdfir0uQRDQu3dv9OjRQ+8aRwBYu3YtABg8KceVRUVFwdPT0+TjPYmIdHgNJhGVKzKZDNOnT8fo0aNx8eLFYr1ZRRAEDBw4EN9++y169uyJdu3aQS6X49SpUzh9+jTatm2r94QfV5aRkYHvv/8eY8eONRionoioMJ4iJ6Jyafr06UhJSTF5Y5GjaDQa/Prrr4iMjMS1a9egUqkQFBSEHj16YPjw4Qanzl3V4sWLcezYMWzatAlyudzZ4RCRi2OCSUREREQOxWswiYiIiMihmGASERERkUMxwSQiIiIih2KCSUREREQOxQSTiIiIiByKCSYRERERORQTTCIiIiJyKCaYRERERORQTDCJiIiIyKGYYBIRERGRQ/0/Ht8RO/tTTtwAAAAASUVORK5CYII=\n", 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# can also tweak the plot style by specifying a matplotlib style/ style file\n", "from matador.config import set_settings\n", "import matplotlib.pyplot as plt\n", "\n", "set_settings({\"plotting\": {\"default_style\": \"matador\"}})\n", "plot_pxrd(\n", " [crystal.pxrd, crystal.pxrd, crystal.pxrd],\n", " rug=True,\n", " text_offset=0.3,\n", ")\n", "set_settings({\"plotting\": {\"default_style\": \"seaborn-darkgrid\"}})\n", "plot_pxrd(\n", " [crystal.pxrd, crystal.pxrd, crystal.pxrd],\n", " rug=True,\n", " text_offset=0.3,\n", ")\n", "set_settings({\"plotting\": {\"default_style\": \"ggplot\"}})\n", "plt.xkcd()\n", "plot_pxrd(\n", " [crystal.pxrd, crystal.pxrd, crystal.pxrd],\n", " rug=True,\n", " text_offset=0.3,\n", ")" ] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:matador]", "language": "python", "name": "conda-env-matador-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.7" } }, "nbformat": 4, "nbformat_minor": 4 }