{ "cells": [ { "cell_type": "markdown", "id": "05a81f03-503e-414a-877b-4f8837d37eb5", "metadata": {}, "source": "## Initial imports" }, { "cell_type": "code", "execution_count": 1, "id": "3fe257a7-2374-49d6-94a2-d648a30c3ad4", "metadata": { "execution": { "iopub.status.busy": "2024-05-31T13:46:40.532310Z", "iopub.execute_input": "2024-05-31T13:46:40.532628Z", "iopub.status.idle": "2024-05-31T13:46:42.940764Z", "shell.execute_reply": "2024-05-31T13:46:42.940238Z" } }, "outputs": [], "source": [ "import scm.plams as plams\n", "from scm.params import ResultsImporter, ParAMSJob\n", "from scm.plams import Settings, AMSJob, log, Molecule, packmol_on_slab\n", "from pathlib import Path\n", "import matplotlib.pyplot as plt\n", "\n", "# common_ru_h.py must exist in the current working directory\n", "from common_ru_h import rotation, check_installation" ] }, { "cell_type": "markdown", "id": "2c19c0f9-001b-4ced-96ce-19a0878f9806", "metadata": {}, "source": "## Initialize PLAMS working directory" }, { "cell_type": "code", "execution_count": 2, "id": "81d242b7-b776-491d-a463-cca1b62a70c0", "metadata": { "execution": { "iopub.status.busy": "2024-05-31T13:46:42.945152Z", "iopub.execute_input": "2024-05-31T13:46:42.945302Z", "iopub.status.idle": "2024-05-31T13:46:44.912063Z", "shell.execute_reply": "2024-05-31T13:46:44.910944Z" } }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": "Current AMS version: 2024.102\n05-31 15:46:43 m3gnet is installed: M3GNet ML Backend v[0.2.4] - build:0 [06668e0a45ce742d8f66ff23484b8a1e]\n05-31 15:46:43 qe is installed: Quantum ESPRESSO (AMSPIPE) v[7.1] - build:115 [777d72eb480fe4d632a003cc62e9c1cb]\nPLAMS working folder: /home/hellstrom/SALRuH/fix2024/plams_workdir.004\n" } ], "source": "old_ref_dir = \"reference_data_3\"\ncheck_installation(old_ref_dir)\nnew_ref_dir = \"reference_data_4\"\nplams.init()" }, { "cell_type": "markdown", "id": "90a21277", "metadata": {}, "source": "## Perform training/validation split" }, { "cell_type": "code", "execution_count": 3, "id": "9f8487d6", "metadata": { "execution": { "iopub.status.busy": "2024-05-31T13:46:44.917088Z", "iopub.execute_input": "2024-05-31T13:46:44.917265Z", "shell.execute_reply": "2024-05-31T13:46:45.803774Z", "iopub.status.idle": "2024-05-31T13:46:45.804753Z" } }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": "[31.05|15:46:45] Performing training/validation split\n[31.05|15:46:45] 126 training set entries; 8 validation set entries.\n[31.05|15:46:45] Storing in reference_data_4\n" } ], "source": "## Create a training/validation split\nri = ResultsImporter.from_yaml(old_ref_dir)\nlog(\"Performing training/validation split\")\ntraining_set, validation_set = ri.get_data_set(\"training_set\").split_by_jobids(\n 0.95, 0.05, seed=314\n)\nri.data_sets = {\"training_set\": training_set, \"validation_set\": validation_set}\nlog(\n f\"{len(training_set)} training set entries; {len(validation_set)} validation set entries.\"\n)\nlog(f\"Storing in {new_ref_dir}\")\nri.store(new_ref_dir);" }, { "cell_type": "markdown", "id": "31ab389e-ad8d-4753-b0a2-ea8d434ad794", "metadata": {}, "source": "## Create a ParAMS Job for transfer learning on the M3GNet universal potential" }, { "cell_type": "code", "execution_count": 4, "id": "d8a4a488", "metadata": { "execution": { "iopub.status.busy": "2024-05-31T13:46:45.808853Z", "iopub.execute_input": "2024-05-31T13:46:45.808982Z", "shell.execute_reply": "2024-05-31T13:46:45.840913Z", "iopub.status.idle": "2024-05-31T13:46:45.841782Z" } }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": "Task MachineLearning\n\nDataSet\n BatchSize 10\n Name training_set\n Path /home/hellstrom/SALRuH/fix2024/reference_data_4/training_set.yaml\nend\nDataSet\n BatchSize 10\n Name validation_set\n Path /home/hellstrom/SALRuH/fix2024/reference_data_4/validation_set.yaml\nend\n\nJobCollection /home/hellstrom/SALRuH/fix2024/reference_data_4/job_collection.yaml\n\nEngineCollection /home/hellstrom/SALRuH/fix2024/reference_data_4/job_collection_engines.yaml\n\nMachineLearning\n Backend M3GNet\n CommitteeSize 1\n LossCoeffs\n Energy 10.0\n Forces 1.0\n End\n M3GNet\n LearningRate 0.001\n Model UniversalPotential\n UniversalPotential\n Featurizer No\n Final Yes\n GraphLayer1 No\n GraphLayer2 No\n GraphLayer3 Yes\n ThreeDInteractions1 No\n ThreeDInteractions2 No\n ThreeDInteractions3 Yes\n End\n End\n MaxEpochs 250\n RunAMSAtEnd Yes\n Target\n Forces\n Enabled Yes\n MAE 0.05\n End\n End\nend\n\n\n" } ], "source": "job = ParAMSJob.from_yaml(new_ref_dir)\njob.name = \"initial_training\"\ninp = job.settings.input\ninp.Task = \"MachineLearning\"\ninp.MachineLearning.CommitteeSize = 1 # train only a single model\ninp.MachineLearning.MaxEpochs = 250\ninp.MachineLearning.LossCoeffs.Energy = 10.0\ninp.MachineLearning.LossCoeffs.Forces = 1.0\ninp.MachineLearning.Backend = \"M3GNet\"\ninp.MachineLearning.M3GNet.LearningRate = 1e-3\ninp.MachineLearning.M3GNet.Model = \"UniversalPotential\"\ninp.MachineLearning.M3GNet.UniversalPotential = Settings(\n Featurizer=\"No\", # must use strings here, not Python booleans\n ThreeDInteractions1=\"No\",\n GraphLayer1=\"No\",\n ThreeDInteractions2=\"No\",\n GraphLayer2=\"No\",\n ThreeDInteractions3=\"Yes\",\n GraphLayer3=\"Yes\",\n Final=\"Yes\",\n)\ninp.MachineLearning.Target.Forces.Enabled = \"Yes\"\ninp.MachineLearning.Target.Forces.MAE = 0.05\ninp.MachineLearning.RunAMSAtEnd = \"Yes\"\n# Larger batch sizes require more (GPU) memory but will also typically train faster\n# The amount of memory also depends on the number of atoms in the structures\n# So set the batch size to some appropriate number\ninp.DataSet[0].BatchSize = 10 # training set batch size\ninp.DataSet[1].BatchSize = 10 # validation set batch size\nprint(job.get_input())" }, { "cell_type": "code", "execution_count": 5, "id": "596f444e", "metadata": { "execution": { "iopub.status.busy": "2024-05-31T13:46:45.845710Z", "iopub.execute_input": "2024-05-31T13:46:45.845897Z", "shell.execute_reply": "2024-05-31T13:56:49.517383Z", "iopub.status.idle": "2024-05-31T13:56:49.518490Z" } }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": "[31.05|15:46:45] JOB initial_training STARTED\n[31.05|15:46:45] JOB initial_training RUNNING\n[31.05|15:56:49] JOB initial_training FINISHED\n[31.05|15:56:49] JOB initial_training SUCCESSFUL\n" } ], "source": "job.run();" }, { "cell_type": "markdown", "id": "d38db28f", "metadata": {}, "source": "## Plot some results of the training" }, { "cell_type": "code", "execution_count": 6, "id": "b976c0e1", "metadata": { "execution": { "iopub.status.busy": "2024-05-31T13:56:49.525738Z", "iopub.execute_input": "2024-05-31T13:56:49.525945Z", "shell.execute_reply": "2024-05-31T13:56:50.224688Z", "iopub.status.idle": "2024-05-31T13:56:50.225686Z" } }, "outputs": [ { "output_type": "display_data", "metadata": { "needs_background": "light" }, "data": { "text/plain": "
", "image/png": "iVBORw0KGgoAAAANSUhEUgAAAREAAAE0CAYAAAAL9QcLAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAA/gUlEQVR4nO2dd5xU5fWHn7MFUIo0C9JREKkLu+ICFuzGGBWsSIxEY/eHURM1MSoasSSamESNNWIUBBto7IIF2yosUkRQUUGxICJVabt7fn+87+zeHWZmZ8udmd09z+czu/e+9733PbfMd952zhVVxTAMo6ZkpdsAwzDqNyYihmHUChMRwzBqhYmIYRi1wkTEMIxaYSJiGEatMBExaoyIDBeRT0Rko4gcl257jPQgNk/EqCkiMhN4WlX/kW5bjPRhNRGjNnQFFtVkRxHJqWNbjDRhImLUCBH5FOgB/M83Z5qKyO4i8rSI/CAiS0XkrED+8SLyuIg8LCLrgbEi0lZEHhCRr0VkjYhMD+Q/WkTmichaEXlbRAYEtl0uIl+JyAYR+UhEDknluRuVsV8Do0ao6h4isgz4jarOABCRR3A1k92B3sDLIvKZqs70ux0LnAj8CmgKPA5sBPr6/8P8cQYD/wF+AcwBfgk8LSJ7Ad2AC4F9VPVrEekGZId9vkZ8rCZi1Aki0hnYD7hcVTer6jzgPuC0QLZ3VHW6qpYBrYGfAeeq6hpV3aaqr/t8ZwF3q+q7qlqqqg8CW4BCoBQnQH1EJFdVl6nqpyk5SSMmJiJGXbE78IOqbgikLQc6Bta/DCx39vnXxDhWV+BS35RZKyJrff7dVXUp8FtgPPCdiEwRkd3r7jSM6mIiYtQVXwNtRaRlIK0L8FVgPTgU+KXP3zrGsb4EJqhq68BnR1V9BEBVJ6vqfjixUeDmujwRo3qYiBh1gqp+CbwN3CgizXxH6JnApDj5vwGeB+4UkTYikisiB/jN9wLnisi+4mguIj8XkZYispeIHCwiTYHNwCZcE8dIEyYiRl0yGtfx+TUwDbhGVV9OkP80YBuwBPgO10xBVefg+kVuB9YAS4Gxfp+mwE3A98C3wC7AH+v0LIxqYZPNDMOoFVYTMQyjVpiIGIZRK0xEDMOoFSYihmHUChOReoKIPC8ip9d1XsOoLY1KRERkmYhsFZH2UenzRES9H0YwfbxPHxKVPlZESr3jWfATc+akP8aetbFdVX/mp3/Xad7aIiKHiMgSEflJRF4Vka4J8nbzeX7y+xwa2CYicr13rFsnIq+JSN/A9r+IyJcisl5ElovIlTW090URuS5G+rEi8m3Qu1hEPhaRXjUpp7b4Z+/hdJRdXRqViHg+x81nAEBE+gM7RGcSEcHNY/gBiPWr/o6qtoj6fF0Tg+qrW7wX4yeBq4C2OGe5qQl2eQR4H2gHXAk8LiI7+20nAmcA+/tjvQM8FNj3fqC3qrbCOeqdKiKjamD2ROA0f3+DnAZMUtUSf257AFmq+nENyggdL7qZ8f1V1UbzAZYBfwJmB9JuwT3QCnQLpB+Amw35S2A10CSwbSzwZpJlzvLH/hHnqXoyMAJYAVyOmzD1ENAGeAZYhZtg9QzQKXCc13Aes+Xle9vX4ITxZzXM293buAGYAdwBPJzkuZ0NvB1Yb+6vWe8YeXvhnOhaBtLewDng4a/Fo4FtfYHNccrtCCwELktg29HAPGAtbibtAJ++A7AOOCCQtw1u9uvAQNo44J9++ec48VuPm5I/PpCvm7+/pwNf4CbBXRnYvgPwoL/2i4HLgBWB7ZfjXAM2AB8BhwBHAltxE/E2AvMD93UC8Ja/znviBHW2P6fZwLCo5+B6f/4bgf/hBHySP5fZBJ75Gn+v0v3FTuUHJyKH+pu1N86F/EsqfDCCInI/8CiQixORUYFtY0lSRHx+BfYMrI8ASnA+H039g9YOOB7YEWgJPAZMj3oggsKwDTerMxs4DzdLVGqQ9x2cwDTBeeGuJyAiwALg1Djn9Q/g31FpHwDHx8g7ElgclXY78C+/3BWYixObXOAvwfP3ea7wXwYFPiMgslH5BuNmwO7rz/l0f++b+u33AvcF8p8DzIs6xgvAEYH71R9Xcx8ArASO89u6eXvu9fdxIE4s9/bbbwJexwlVJ389V/hte+Gev90Dx9rDL48nSsz9ff0CJ7A5wK44cTrNr4/26+0C+ZcCewA7AR8CH+O+AznAf4EHavu9yozqUOp5CBfT4jDclOugkxgisiOuej1ZVbfh4l5EN2kKg16m4oL0VIcy3LTwLaq6SVVXq+oTqvqTOk/YCcCBCfZfrqr3qmop7peuA+6hSjqviHQB9gGuVtWtqvom8HRwR1UdoKqT4xy3Be4XMMg6nAhWN+83uJrJR7hf2ROBi6NsucnnH4y7h9HHi5AolAC4a3CiiESasb/yaUD5/d8H9+VHVV9T1YWqWqaqC3DNsuh7c62/j/OB+TgxATgJuEFduIMVwD8D+9QkrMFEVV2krtl1OPCJqj6kqiXqHBSX4OKwRHhAVT9V1XU4X6VPVXWG3/8xYFAV5VVJYxaRU3G/0v+NsX0krqbwnF+fBPws0H4HKNLKXqZ7VNOGVaq6ObIiIjuKyN2+03A9ronRWkTiBdz5NrKgqj/5xRbVzBtx3/8pkDforl8VG4FWUWmtcFXz6ua9BvfF7Qw0A64FXvFf6HLU8T5OaK6NY1fcUAL+GG/imo3HikgPX25QKA/BNdM2A3hHwFdFZJWIrAPOBSp1zhO4xsBPVNyL3al8TcuXtWZhDYLH2h0XbiFIdPiFlYHlTTHW4z0zSdMoRURVl+P6Bo7CdQxGczru4n4hIt/iFDuXQIdsXZgRtX4prnq7r7rOw4hHa3QHYF3yDc4dP/hF7VyN/RdR8YuLiDTHVZ1jxV1dBPSIChUwMJB3IDBVVVf4X9WJuCZAnzhl5/iyYpEwlIDnv7gayGnAS6oa/HIdBTwbWJ+Mq6F1VtWdgLtI/r58g2vGRKh0fTV+WIN4Tm3B9K/9fkGiwy+ETqMUEc+ZwMGq+mMwUUQ64n6Jjgby/Gcg7ubWdO7FSlw80kS0xP0yrBWRtrhf5lDxYjoHGC8iTURkKJWrwlUxDegnIseLSDPgamCBqi6JUdbHuI7Oa3yogJG4/oUnfJbZuCbGriKSJSKn4YR7qV8/R1zIAPFD7hcAM6PL8cQNJRDI819c38BZBJoynp9RUQsFd29+UNXNvuxTk7w+4PrV/uBt74gL7QiAJA5rsBLoVsUIzHNALxE5VURyRORknOg+Uw37ak2jFRHfTpwTY9NpuE62l1T128gH15YdICL9fL6hMeaJ7BOnuPHAg75qfVKcPLfhOua+B4pwHXupYAwwFNd5fD1uiHZLZKOILBKRMbF2VNVVuM7gCbgOvX2BUwL73iUidwV2OQUo8HlvAk7wxwAn0vOpGFG5GNdBu9ZvHwl8imv+PAz8y39i2ZUolEAkzzLcqEVzAv1A/v5uVNUvAtnPB64TkQ04oXw0VrlxuA43Evc5bvTrcSqub6KwBo/5/6tFZG6c81yN+7G7FHf/LgOOVtXvq2FfrbFQAEYlRGQqsERVQ68JZSIichnQXlUvC+n45wGnqGqiTvN6RaOtiRgOEdlHRPbwTYYjcRHZp6fZrHSyDHigrg4mIh3EvSkwS1y0+ktxzcAGQ72cKWnUKbvhOpfb4ard5/nRj0aJqlanqZIMTYC7cZP61gJTgDvruIy0Ys0ZwzBqhTVnDMOoFSYiGYA4r+A3A+sb/SSoKvPWoCwLE2DUKQ1SRCRNLv91hTqP4M9qexyJ4U6uKQoT4Odn3Cwiq/3nLyLbec4G85/qZ+v+KCLT/VyZyLZuIvKcuPf1fisit0tll/1scWEEvhb3ft73Jfb7bBLZ21FESsR570ZvmyYitwTWh4nI29U5fl3in+9Dq86ZGhqkiHgyzuW/kXE2cBxuot4A3HyGc2JlFBc35G7cfdgVN2082Pl4J86hrgNu8t+BuLkbEa7FebMOxU2lPw03eStpVPUr3OS14Gs/8WJ2FJUnpB1F5cloGYWkOrREbT34MvFDelz+7wJuiUp7CrhEKzxQI5OlPgRGxiuHgNcvbtTkaZx37XvAn6Py/gM3zXs9UAzs79MTuZNHPHyz/HVajvuS/hfYSSt7p8Z0cU/ierwNnB1YPxPnbxQr7w04Z8fI+h7e9pZ+fTFwVGD7X3EOduCmxm/Ee78mYVdT/yx8gZsVehewg992Ks5BLZj/fGBuVNpcYHCi6++3jcdNTPuvv++LgILA9sG4EAMbcJPLpgLX+23tcTNP1+J+4N7w9+shnPPmJn/elwXu1Zn+vGYleW9/7W1fg/MH2gfnZbwWuD3pe53uL3wYH9Lg8o8Toy+pGPFq4290xM37RJzDVBYupsiPQIdY5VBZRKZ4+5oD/XB+EcG8v8QJTQ5uDsK3QLPAQxzLnTwiImfgZnP2wPkKPQk8FPWgxXNx3w9Ym+B6rMP5AUXWC4ANcfI+hXsReDBtI5Dvl8/1X4Idcc5lH+BF2F/3tVTEZvkYuCCBXbfhRLktbjr7/4Ab/bZIrJH9AvnfAX4bWO/g70HkPld1/Tfjai7ZwI14IcUN/S4HLsI9e6NwwhkRkRtxApfrP/sHylwGHBqwKXKv/uufkx2SvLd34ZwdD/d2TsfNmu2IE54DTUScEt+I+1V+2d/ochHxD+V6KmJD3A08FSUiJf4hjXw+jVOm4H4FDvDrZwGvJLBxHnBsoJztRMQ/eNsIBPnB/WrHFTbcr8rAwEOcSERmAucHtu3ly8sJPGjBwEjv4WZbJnMPSqPs7umPJzHyzsQHJwqkfQWM8Mt7437lS/wxJlLxhTrVp93vvzwDcB66h8W5Rz8SqLXgmkCfB9bvA+4J2LwV2CWw/Uzg/mpc/xmBbX2ATX75AAJi5NPepEJErsOJ654xylhGbBHpEXVNq7q3HQPbVwMnB9afICCeiT4NuU8EUujyr+7KT6GiH+ZUAu+hFZFf+Y7diGt6P7Z3J49mZ9xND7p/V3L9FpFLRWSxuLika3HBZ6o6boRoV/LlVAS7iRDPxb0qol3/W+F8UjSJvJH8G7wD2ou4X9LmuHNrQ4W36yb//zp18TwW4O7DUTHK2Rn3w1EcuA8v+PQIDwIniXMoPA14QVW/C2yv1B+SxPWPvn7NfJ/F7sBXUdcjeJ//iqtJvCQin4nIFTHOJ5pEYQJi3ds6CRPQoEVEU+/y/whwgrhgxfviPVT9+r04D852qtoaVyWvyp18FU7kgu7jXSILIrI/rhp/EtDGH3dd4LixvrBBol3Ju/jyVsbOXi0qhQmgstt/wrx+eLsprmnSFnf+t6sL4LQaNy09IhIL/P+qzhVcv84moG/gR2EnVS3/sqjqG7hf5WNxTZXyHx8RycV16r7s16u6/on4BugYNWJVfp9VdYOqXqqqPXCe1ZeIyCFVnGswPcx7W4kGLSKelLn8q5suvgpXJX5RKzxQm+Nu8Cpf9q9xNZGqjleKE7/x4oIW9YmyrSXuwVgF5IjI1VT+Ra/KnfwR4GIR6S4iLXBNpanqgxXXkv/iHvyOfkj8UlwzJBaTgF+IyP7iYpJcBzzpv0jf434IzhPn7t4adw3mg/PGxnU6XikiTUVkb1yf03bu8KpahhPzv4vILlA+tHtEDNtvBlrj+kwi7I8LdbDer1d1/RPxDq7Jd6E/r2OB8ikGInK0iOzpRWa9zxsME1BVaIkw720lGryIaGpd/sHdvEMJRMpS1Q+BW3EPzkpcvM63kjyFC3G1pW9xX8IHAttexIW8+xhXXd1M5SptVe7k/8E1+Wbhvqibgf9Lxij/hd+YIMvduC/gQlyt61mfFtl/o/8lR1UX4TpPJ+E69FpSeQh3FK5faxWuil9C5dCJo3G/uqt9OVeparxYI5f7YxSJiyA3A9dfEOS/uF/uqaq6JZAePbRb1fWPi6pu9ed1Jq6v7Zc44YuU19PbthH33Nypqq/5bTcCf/JNst/FKaLG97a6mO+MYSSJiHyIi4HyYUjHfxe4S1UfqDJzBtHgayKGUReISBPgv3UpICJyoIjs5pszp+NGllIVjKrOsFAAhpEEvvlxUx0fdi/cHKAWuImIJ6jqN3VcRuhYc8YwjFphzRnDMGpFg2jOtG/fXrt165ZuMwyj4aAKGzdCWVl5UvHSpd+r6s7RWRuEiHTr1o05c2KN4hqGUW22bIF33oENld9BJsccE/2iLMCaM4ZhBIkjIIkwETEMw+EFpPirDdyxAorXB7blxG+0pFVEROQ/IvKdiHwQSBsvIl95Z7V5IhLLkcowjLokICBjFgm3LhfGLBInJDk5UFgYd9d094lMxL2lLNrD9u+qesv22ZNn27ZtrFixgs2bqxXgykgBzZo1o1OnTuTm5qbbFAMqNWGK1sPWMihD2FamFG3MJv+oQmjTJu7uaRURVZ0lUfFO64oVK1bQsmVLunXrRoLQnkaKUVVWr17NihUr6N69e7rNMaL6QApbQZMs2Fam5GYJhcP7JRQQyNw+kQtFZIFv7sQ8AxE5W0TmiMicVatWbbd98+bNtGvXzgQkwxAR2rVrZzXETCBGJ2p+K5jUV7mkexaTTu1Pfr8uCQ7gyEQR+TcuxmYeLubCrbEyqeo9qlqgqgU777zd0DWACUiGYvclA0gwCpPfNocLThqalIBABoqIqq5U1dJA7IchVe1jGEY1qGoUpjBxH0g0GSciItIhsDoSF4ui3rF69Wry8vLIy8tjt912o2PHjuXrW7duTbjvnDlzGDduXJVlDBs2rK7MrRY33HBDWso16oBkRmGqISCQZgc8EXkEGIGLSbkSuMav5+EigS0DzqnKs7GgoECjZ6wuXryYvffeu65NrhHjx4+nRYsW/O53FfFjSkpKyEkw9p7JtGjRgo0bE8UjqppMuj+NhkAT5o4VcOtyoQwhG9cHcsFJQxMKiIgUq2pBdHpaayKqOlpVO6hqrqp2UtX7VfU0Ve2vqgNU9ZhUukYXL1/DHa8upXj5mlCOP3bsWC655BIOOuggLr/8ct577z2GDRvGoEGDGDZsGB999BEAr732GkcffTTgBOiMM85gxIgR9OjRg3/+85/lx2vRokV5/hEjRnDCCSfQu3dvxowZE4nYzXPPPUfv3r3Zb7/9GDduXPlxgyxatIghQ4aQl5fHgAED+OSTTwB4+OGHy9PPOeccSktLueKKK9i0aRN5eXmMGTMmlOtkhECcUZhskh+FiUf9/CkMgeLlaxhzXxFbS8pokpPFpN8Ukt+1Zhc1ER9//DEzZswgOzub9evXM2vWLHJycpgxYwZ//OMfeeKJJ7bbZ8mSJbz66qts2LCBvfbai/POO2+7ORbvv/8+ixYtYvfdd2f48OG89dZbFBQUcM455zBr1iy6d+/O6NGx40/fddddXHTRRYwZM4atW7dSWlrK4sWLmTp1Km+99Ra5ubmcf/75TJo0iZtuuonbb7+defPm1fm1MUIiwShM0cZsCof3S7oTNRYmIp6iz1aztaSMMoVtJWUUfbY6FBE58cQTyc7OBmDdunWcfvrpfPLJJ4gI27Zti7nPz3/+c5o2bUrTpk3ZZZddWLlyJZ06daqUZ8iQIeVpeXl5LFu2jBYtWtCjR4/y+RijR4/mnnvu2e74Q4cOZcKECaxYsYJRo0bRs2dPZs6cSXFxMfvs48LJbtq0iV122aXOroORIqoYhalqIlkymIh4Cnu0o0lOFttKysjNyaKwR7tQymnevHn58lVXXcVBBx3EtGnTWLZsGSNGjIi5T9OmTcuXs7OzKSnZPmB3rDzJ9nedeuqp7Lvvvjz77LMcccQR3Hfffagqp59+OjfeeGOSZ2ZkHImc6WrYiRqLjBudSRf5Xdsw6TeFXHL4XqE1ZaJZt24dHTt2BGDixIl1fvzevXvz2WefsWzZMgCmTp0aM99nn31Gjx49GDduHMcccwwLFizgkEMO4fHHH+e779x7m3744QeWL3ee4Lm5uXFrTUaGkCIBARORSuR3bcMFB+2ZEgEBuOyyy/jDH/7A8OHDKS0trXqHarLDDjtw5513cuSRR7Lffvux6667stNOO22Xb+rUqfTr14+8vDyWLFnCr371K/r06cP111/P4YcfzoABAzjssMP45hvXx3322WczYMAA61jNVFIoINBAYqxm+hBvOtm4cSMtWrRAVbngggvo2bMnF198cdU7hozdn5AIUUAycojXCJ97772XvLw8+vbty7p16zjnnHPSbZIRFimugZQfus6PaGQUF198cUbUPIyQSZOAgNVEDKP+k0YBARMRw6jfpFlAwETEMOovGSAgYCJiGPWTDBEQMBEJjREjRvDiiy9WSrvttts4//zzE+4TGao+6qijWLt27XZ5xo8fzy23JA4/O336dD78sOK901dffTUzZsyohvV1g4UMCIkMEhAwEQmN0aNHM2XKlEppU6ZMiesEF81zzz1H69ata1R2tIhcd911HHrooTU6Vm0wEQmBDBMQMBGpzJfvwRu3uv+15IQTTuCZZ55hy5YtACxbtoyvv/6a/fbbj/POO4+CggL69u3LNddcE3P/bt268f333wMwYcIE9tprLw499NDycAHg5oDss88+DBw4kOOPP56ffvqJt99+m6effprf//735OXl8emnnzJ27Fgef/xxAGbOnMmgQYPo378/Z5xxRrl93bp145prrmHw4MH079+fJUuWbGeThQxIMxkoIGAiUsGX78GDx8ArE9z/WgpJu3btGDJkCC+88ALgaiEnn3wyIsKECROYM2cOCxYs4PXXX2fBggVxj1NcXMyUKVN4//33efLJJ5k9e3b5tlGjRjF79mzmz5/P3nvvzf3338+wYcM45phj+Otf/8q8efPYY489yvNv3ryZsWPHMnXqVBYuXEhJSQn//ve/y7e3b9+euXPnct5558VsMkVCBsybN485c+bQqVOnSiED5s2bR3Z2dnnIgB122IF58+YxadKkWl1Lg4wVEDARqWDZG1C6FbTU/V/2Rq0PGWzSBJsyjz76KIMHD2bQoEEsWrSoUtMjmjfeeIORI0ey44470qpVK4455pjybR988AH7778//fv3Z9KkSSxatCihPR999BHdu3enV69eAJx++unMmjWrfPuoUaMAyM/PL3faCzJ06FBuuOEGbr75ZpYvX84OO+xQKWRAXl4eM2fO5LPPPkvuAhnJkcECAjZjtYJu+0N2Eycg2U3cei057rjjuOSSS5g7dy6bNm1i8ODBfP7559xyyy3Mnj2bNm3aMHbs2CpfnxAvOvrYsWOZPn06AwcOZOLEibz22msJj1OVn1QknEC8cAMWMiANZLiAgNVEKug8BE5/Gg6+0v3vXPsg8y1atGDEiBGcccYZ5bWQ9evX07x5c3baaSdWrlzJ888/n/AYBxxwANOmTWPTpk1s2LCB//3vf+XbNmzYQIcOHdi2bVulJkPLli3ZEOOh6927N8uWLWPp0qUAPPTQQxx44IFJn4+FDEgx9UBAwGoilek8pE7EI8jo0aMZNWpUebNm4MCBDBo0iL59+9KjRw+GDx+ecP/Bgwdz8sknk5eXR9euXdl//4oa0p///Gf23XdfunbtSv/+/cuF45RTTuGss87in//8Z3mHKrjXVz7wwAOceOKJlJSUsM8++3DuuecmfS5Tp07l4YcfJjc3l912242rr76atm3blocMKCsrIzc3lzvuuIOuXbuWhwwYPHiw9YtUl3oiIGChAIw0YfcnARkqIPFCAVRZExGRXYDhwO7AJtx7YOb4l0sZhlGXZKiAJCKuiIjIQcAVQFvgfeA7oBlwHLCHiDwO3Kqq6+MdwzCMalAPBQQS10SOAs5S1S+iN4hIDnA0cBiw/TsODMOoHvVUQCDB6Iyq/j6WgPhtJao6XVVrJSAi8h8R+U5EPgiktRWRl0XkE/8/M6+cYdQV9VhAIIkhXhFpLSLjRORvIvLPyKeOyp8IHBmVdgUwU1V7AjP9umE0TOq5gEByQ7zPAUXAQqBOO1NVdZaIdItKPhb3Pl6AB4HXgMvrslzDyAgagIBAciLSTFUvCd2SCnaNvH9XVb/xo0PbISJnA2cDdOlS81cAGkZaaCACAsnNWH1IRM4SkQ6+v6KtiLQN3bIqUNV7VLVAVQt23nnndJtjGMnTgAQEkquJbAX+ClwJRGamKdAjJJtWikgHXwvpgBtarjmBaeKh8YtfxEy+6qqraN++PRdddBEAV155Jbvuuivjxo2Le6h169YxZMgQnn76afbaay9Gjx7NwQcfzFlnnRWK6UaKaWACAsmJyCXAnqr6fdjGeJ4GTgdu8v+fSlG5dc6ZZ57JqFGjuOiiiygrK2PKlCm88sor5OXlxcw/efJk+vTpw+23387YsWO56KKLWLNmjQlIQ6EBCggkJyKLgJ/CKFxEHsF1orYXkRXANTjxeFREzgS+AE4Mo+xU0K1bN9q1a8f777/PypUrGTRoEF27dmXevHkJ9zvssMN47LHHuOCCC5g/f35qjDXCpYEKCCQnIqXAPBF5FdgSSVTV+HXyJFHVeLECD6ntsTOF3/zmN0ycOJFvv/2WM844gw0bNlRyogsSqYmUlZWxePFidthhB3744Qc6deqUYquNOqUBCwgkJyLT/ceoASNHjuTqq69m27ZtTJ48mezs7CprIn//+9/Ze++9ueGGGzjjjDN45513yM3NTY3BRt3SwAUEkhARVX1QRJoAvXzSR6paf4JExOn0TBVNmjThoIMOonXr1mRnZ1eZ/+OPP+a+++7jvffeo2XLlhxwwAFcf/31XHvttSmw1qhTGoGAQHJevCNwk76WAQJ0FpHTVXVWgt0MT1lZGUVFRTz22GNJ5e/VqxeLFy8uX//b3/4WlmlGmDQSAYHk5oncChyuqgeq6gHAEcDfwzWrYfDhhx+y5557csghh9CzZ890m2OkikYkIJBcn0iuqpa/p0BVPxYRa6AnQZ8+fSxocWOjkQkIJCcixSJyP/CQXx8DFIdnUt2hqnGDHBvpoyFE04tJIxQQSK45cy5ursg44CLgQ5+W0TRr1ozVq1c33Ae2nqKqrF69mmbNmqXblLqlkQoIVFETEZEsoFhV+wH1qoevU6dOrFixglWrVqXbFCOKZs2aNay5L41YQKAKEVHVMhGZLyJd4gUoylRyc3Pp3r17us0wGjqNXEAguT6RDsAiEXkP+DGSqKrHxN/FMBoBJiBAciJis5wMIxoTkHKSEZGjVLVSZDERuRl4PRyTDCPDMQGpRDKjM4fFSPtZXRtiGPUCE5DtSPTemfOA83HvmFkQ2NQSeCtswwwj4wgISPF6KFoPha0gvxWNVkAgcXNmMvA8cCOVI65vUNUfQrXKMDKNKAEZs0jYWgZNsmDSgCzyj2icAgKJ3zuzTlWXAX8CvlXV5UB34Jci0jo15hlGBhDVhClaD1vLoAxhW5lQ1KpzoxUQSK5P5AmgVET2BO7HCcnkUK0yjEwhRh9IYStXA8kGcnOyKOzbgCbO1YBkRmfKVLVEREYBt6nqv0Tk/bANM4y0E6cTNb+Va8IUtepMYd9O5HdtvLUQSE5EtonIaOBXQCTCj3nxGg2bKkZh8o8oJL8RN2GCJNOc+TUwFJigqp+LSHfg4XDNMow0YsO41SKZ8Igf4jx4I+uf4yKyG0bDwwSk2iQTHnEhFS+tirAOmANcr6qrwzDMMFKOCUiNSKZP5HncayMiIzKn4GKtrgMmUtFPYhj1FxOQGpOMiAxX1eGB9YUi8paqDheRX4ZlmIgsAzbgBKxEVQvCKsto5JiA1IpkRKSFiOyrqu8CiMgQoIXfVhKaZY6DUvj6TqMxYgJSa5IRkd8A/xGRFrhmzHrgNyLSHDcl3jDqJ15Air/aUNkPBkxAqkEyozOzgf4ishMgqro2sPnRsAzDdea+JCIK3K2q9wQ3isjZwNkAXbp0CdEMo0ESEJBKfjB9lfy2JiDVIZnRmabA8UA3ICcSPV1VrwvVMtcX87WI7AK8LCJLgi/M8qJyD0BBQYFFYzaSJ9CEqewHoxRtzCb/KBOQ6pDMZLOngGNx/R8/Bj6hoqpf+//fAdOAIWGXaTQCovpAKvxglNwsoXB4PxOQapJMn0gnVT0ydEsC+P6WLFXd4JcPB8Ku+RgNnRidqPmtXBOmaGM2hcP7kd/PmsbVJRkReVtE+qvqwtCtqWBXYJpvOuUAk1X1hRSWbzQ0EozC5LfNsSZMLUhGRPYDxorI58AW3AiNquqAsIxS1c+AgWEd32hk2ChMqCQjIhZP1ai/2ChM6FTZsaqqy31Us024YdfIxzAym7ijMFC0MdsEpI6oUkRE5BgR+QT4HPeaiGU4fxrDyFxsFCZlJNOc+TNQCMxQ1UEichAwOlyzDKMWeAG5acEGpn8PXZrC5d1sFCYskpknss27+2eJSJaqvgrkhWuWYdSQgIDc9bXw7VbhvQ3CSQsFsrO54KShJiB1TDI1kbXeb2YWMElEviN8xzvDqD5btlD83JsUffsT08vdNt0M61KgqFVnC2kYAsmIyLHAZuBiYAywEzbxy8g0vICMmb2JrWUS2KCAkJ1Fo4/KHhaJ3oD3IvAC8LyqLvHJD6bEKsOoDr4Jc/OHP7G5TPBTmfxGoc8uO/Ln4/MafVT2sEjUJ3I6sAYYLyJzReTfInKsb9oYRmYQ6AN5b0OkBlIhINkCPx/U2QQkROLWRFT1W1z4w4kikgXsi5t4dpmIbAJeUtW/pMRKw4hB8dKVFL0+n8JmW6L6QJRIX0h2llDYo12aLGwcJGrOFKjqHABVLQPe8Z+rRaQ9cERqTDSM7SleupIx/5nDljInGG1zgvMfpfzviQVWCwmbRB2r9/qmyyPAFP/qCAB8yMJJYRtnGNEUL19D0ccr+fqj5Wwui9Q4lNUlUqknJAtokpvFqMHWmRo2iZozg0RkL1x098dFZCsVgrI8VQYaRoTJ737BVdMXUqoAymD5hMKsDykq68Nc7UmbHOHMYV1o024n1vy0lcIe7awWkgISDvGq6kfAtcC1IjIQJyiviMi3URHgDSNUipev4arpH3gBgcHyCZOa3EAuJWwjhzFb/0jObvlccFT/9BraCElmngi+Y3UXXJyP5sCqMI0yjGienL2cUnUKMlg+5qKcJ2jCNrJFQUsozFrMIb8Ym14jGykJRURE9sf5yRwHfABMAS5W1XXhm2YYrgby5PQn2Om79zglqwUjsuZzaPZcoIwsoESFbeSw24BDremSJhKNznwJfIETjmtVdWXKrDIMnIBMuGuia7bkbCU7sE0EShTeKuvHP0qOp3eTvdNmZ2MnUU1kv2AHqog0V9XQAzQbRoRT73mHf2Q/Q1O2kiWg6sQD3LKSzT9Kjmeu9sIkJH3EnbEaERARGSoiHwKL/fpAEbkzRfYZjZDi5Ws46U+38YRcwRHZc3w8zsoCUoZw1baxzNVe5GaLDeWmkWQ6Vm/DTSx7GkBV54vIAWEaZTRebnpuMe+98QKPNxlPZBK7BPzpXA0Ertx2Bk/IoYzZtzOjBney/pA0ktTojKp+KcE76TyrDaNOue2Bh8laOou7cp5DqCweQV4qLWBK2SEc3mcXJoy0Id10k4yIfCkiwwAVkSbAOHzTxjDqguLla5j0+GPcuP4P5OaUEEs7/OgupQj3lB5NTrZwzoF7pNROIzbJiMi5wD+AjsAK4CXggjCNMhoPk9/9giunL+SR7Ptpkl2CRHWgQoWALCrtytWlv6b93vsz9cA9rAmTISTzQu/vccGIDKNOKV6+hiunLeTkrJnsm72kPD2WgPy75Gj+UnoqAL/v3NoEJIOIOzojIn8SkbYJth8sIkeHYxaIyJEi8pGILBWRK8Iqx0gPL73wNK/eezm/z57MhJz7gfh9IGt1x3IByTHX/owjUU1kIfA/EdkMzMVNdW8G9MQFap4B3BCGUSKSDdwBHIZrQs0WkaeDnsRG/eWlF55m/3fO5ODsyhPIgmjAs/+R0oMByBK47th+VgvJMBJ58T4FPCUiPYHhQAdgPfAwcLaqbgrRriHAUv86TURkCi7Wq4lIPWfyu1/wzVvPcnDWNnJi9H8EKVO4u9Q1Y3KyhOuO7cep+1qk9kwjmT6RT4BPUmBLkI7Al4H1FbjIauWIyNnA2QBdutiDVR+Y/O4X/HHaQk7Jak52llaqbcTikbJD+GvpqZy6bxeOt7kgGUtS80TSQMxRvkorqvcA9wAUFBTYaz3rATc+5yqSl2Q9CsSugUSEpYQs3m5xGI+PHmbikeFkqoisADoH1jsBX6fJFqMO+NX977JhSymv5Yxj5+wNMfMEh3Lvb30hd/7u7BRaaNSUTBWR2UBPEekOfIULhnRqek0yakLx8jXc9fqnbFz6Ns/kPEDXbBdROboWEhGQJ0uHc4VeyJQTh6bYUqOmVCkiIvIX4HpgE+49NAOB36rqw2EZpaolInIh8CKQDfxHVReFVZ4RDsXL13DzvQ9yDLM4qclr5HhviVjzQMDNBfmq4AqmWP9HvSKZmsjhqnqZiIzENTNOBF7FjdKEhqo+BzwXZhlGuLz3xgs8mD2Bpmwt94UJikZkeVuZcErJNZxw3PGcb6Mv9Y5kRCTX/z8KeERVf5B4Y3KGASyZPYOimU/RcuNX5GZvK48FAts3Yz4r25VDtv2d4/J2t+HbekoyIvI/EVmCa86cLyI7497NaxjbsWT2DLo+M5o9KaEsW8gm9lCuiwkCvy85DwF67toy1aYadUSi12gCoKpXAEOBAlXdBvyEm/hlGNux5sNXyKWEHCmr1AcSDCgU4eXSAubRi6a5WTaVvR6TTMfqjjiv3S64yV27A3sBz4RrmlEfeXnDHhTgZ6JGbSt351cokRy6HfsHLt3Yzd4PU89JpjnzAFAMDPPrK4DHMBExoiheupL/rNiN85q0oL2sL+9IDdY+Xivtz4dN+nPBr39N785D6J0+c406IhkR2UNVTxaR0QCqukmsZ9WIonjpSm6bNhdQPi3bnfbZ68u3/VDWgi/YhamlB1Hc7hhevnRE2uw06p5kRGSriOyAn3YuInsAW0K1yqhXFC9dycn3z6HEVzn+UnoKU7OvI1vLKCWLs0p+x1ztxQ0j+3OTjcA0OJIRkWtwk8w6i8gknEfv2DCNMuoRW7Zw91PvewFxr9Seq704eevVFGYtpqhsb+ZqL7IE1vy0Nd3WGiGQjBfvyyIyFyjEPSUX+WhnRmNnyxYmT53FzFXbqOhGrRCSuaW9ylOa5NgITEMlmdGZkcArqvqsX28tIsep6vSwjTMyGC8gf/xwC9uPw0ilpdHmyt+gSao5o6rTIiuqulZErgGmh2aVkdls2QLvvMNfPtqMk4nY/exZAtcf199mojZwkhGRWBPSMtX71wgbLyA3LdjA2tKgeET6RKBbux05saCzzf9oJCQjBnNE5G+4mKcK/B9u3ojR2PACUvzVBu7+unIfSERAcrKFW0/KM/FoRCQjIv8HXAVM9esvAX8KzSIjMwkIyG1fRsLMVQjJbi1yOW14D6t9NEISioiPuv6Uqh6aInuMTCQgIKM/ELaWz0B1NZBsgTtO28fEo5GSUERUtVREfhKRnVR1XaqMMjIILyBs2MCT3+EFxDVh9txR2LfXrowaam+ja8wk05zZDCwUkZeBHyOJqjouNKuMzCAgIABaaRBGGNJrVyacUpAW04zMIRkRedZ/jMZElIAAHL8zPL4StinkZgvHD7UXahvJzVh9UESaAL180kc+rojRUAkISPF6KFoPha0gvxU8MjCLoladKexrk8cMRzIzVkcADwLLcI3hziJyuqrOCtUyIz1ECciYRcLWMmiSBZMGZJF/xFDy25h4GBUk05y5FRes+SMAEekFPALkh2mYkQYCozBF6+GrLbC1DMoQtpVBUavOJiDGdiQVqDkiIACq+rGI5CbawaiHBAQkUvvIEfcpVcjNyaKwb6d0W2lkIMnOWL0feMivj8FmrDYsoiaSRWofpaqc0kHYvWcX6wMx4pKMiJyHi7E6DtcnMgu4MyyDRGQ8cBawyif90b+DxgiDqBrIljI3hSwLJTdLGHVIf/L7mQOdEZ+4IiIiM1X1EOA6Vb0c+FvqzOLvqnpLCstrnAQ6UYvWuxqIImShDG8j/PbnJiBG1SSqiXQQkQOBY0RkClH+3qo6N1TLjHCJmgdS2MqNwGwrczUQExAjWRKJyNXAFUAntq+FKHBwWEYBF4rIr4A5wKWquiY6g4icjXuFBV262MNeLWJMJMtvBZP6KkUbsykc3s8ExEga0VivJwtmELlKVf9cp4WKzAB2i7HpSqAI+B4nVH8GOqjqGYmOV1BQoHPmzKlLExsuMQSknJwcKCwEG8Y1YiAixaq6nZ9DMjNW61RA/DGT8goWkXux99vUHSYgRghU+RrNVCMiHQKrI4EP0mVLg8IExAiJTAxz+BcRycM1Z5YB56TVmoaACYgRIomGeNsm2lFVf6h7c0BVTwvjuI0WExAjZBLVRIqpCJ7ZBVjjl1sDXwDdwzbOqCUmIEYKiNsnoqrdVbUH8CLwC1Vtr6rtgKOBJ1NloFFDTECMFJFMx+o+wWnnqvo8cGB4Jhm1xgTESCHJdKx+LyJ/Ah7GNW9+CawO1Sqj5piAGCkmmZrIaGBnYJr/7OzTjEwj4Ex3xwooXh/YZgJihEQyk81+AC4SkRaqujEFNhk1IUY8kCZZbip7flsTECM8qqyJiMgwEfkQ+NCvDxSR0EIBGDUghjdueTSyjdkmIEaoJNOc+TtwBL4fRFXnAweEaZRRDeJ442b7eCCFw/uZgBihktSMVVX9UqRSJIDScMwxqoV54xoZQDIi8qWIDAPUvzpiHLA4XLOMKkkwCpPfNof8o6wJY6SGZJoz5+LCI3YEVgB5wPkh2mRUhQ3jGhlEMjWRvVR1TDBBRIYDb4VjkpEQExAjw0imJvKvJNOMsDEBMTKQRF68Q4FhwM4icklgUysgO2zDjChMQIwMJVFzpgnQwudpGUhfD5wQplFGFCYgRgYTV0RU9XXgdRGZqKrLU2iTEcQExMhwkukTuU9EWkdWRKSNiLwYnklGOSYgRj0gGRFpr6prIyv+9Q27hGaR4TABMeoJyYhImYiUT3sUka64kABGWJiAGPWIZOaJXAm8KSKv+/UD8C+NMkLABMSoZyQTCuAFERkMFOJirF6sqt+HblljxATEqIfEbc6ISG//fzAuUPPXwFdAF59m1CUmIEY9JVFN5FLgLODWGNvCfhdv48IExKjHJJoncpb/f1DqzGmEmIAY9ZxE095HJdpRVWv82ggROREYD+wNDFHVOYFtfwDOxMUsGaeqDXdOigmI0QBI1Jz5hf+/C86H5hW/fhDwGrV798wHwCjg7mCiiPQBTgH6ArsDM0Skl6o2vCBIJiBGAyFRc+bXACLyDNBHVb/x6x2AO2pTqKou9seK3nQsMEVVtwCfi8hSYAjwTm3KyzhMQIwGRDKTzbpFBMSzEugVkj0dgS8D6yt82naIyNkiMkdE5qxatSokc0LABMRoYCQz2ew17yvzCG5U5hTg1ap2EpEZwG4xNl2pqk/F2y1GWszZsap6D3APQEFBQf2YQWsCYjRAkplsdqGIjKQiwvs9qjotif0OrYE9K4DOgfVOuPkp9R8TEKOBklS0d2AusEFVZ4jIjiLSUlVjfBtqzdPAZBH5G65jtSfwXgjlpBYTEKMBk8zLq84CHqdiJKUjML02hYrISBFZAQwFno2EFlDVRcCjuBdlvQBcUO9HZkxAjAZOMjWRC3AjJO8CqOonIlKrUAC+ORSzSaSqE4AJtTl+xmACYjQCkhmd2aKqWyMrIpKDhQKoGhMQo5GQjIi8LiJ/BHYQkcOAx4D/hWtWPccExGhEJCMilwOrgIXAOcBzwJ/CNKpeYwJiNDIS9omISBawQFX7AfemxqR6jAmI0QhJWBNR1TJgfjA8ohEHExCjkZLM6EwHYJGIvAf8GElU1WNCs6q+YQJiNGKSEZFrQ7eiPmMCYjRyEsUTaQacC+yJ61S9X1VLUmVYvcAExDAS9ok8CBTgBORnxA6T2HgxATEMIHFzpo+q9gcQkftpCD4sdYUJiGGUk6gmsi2yYM2YACYghlGJRDWRgSKy3i8Lbsbqer+sqtoqdOsyDRMQw9iOROERs1NpSMZjAmIYMUlm2rthAmIYcTERqQoTEMNIiIlIIkxADKNKTETiYQJiGElhIhILExDDSBoTkWhMQAyjWpiIBDEBMYxqk+wrIxo+W7ZQ/NybFH37E4WtID84lc4ExDDiYiIC5QIyZvYmtpYJTbJgUl91QmICYhgJseaMb8IUffsTW8ugDGFbGRStxwTEMJIgLSIiIieKyCIRKRORgkB6NxHZJCLz/OeuUA0J9IEUtoImWZCNkpsFhW2yTUAMIwnS1Zz5ABhFxVv1gnyqqnmhWxDViZrfyjVhitY7Ack/YqgJiGEkQVpERFUXA4hIOoqPOwqT3wry21oTxjCqQyb2iXQXkfdF5HUR2b/Oj27DuIZRp4RWExGRGcBuMTZdqapPxdntG6CLqq4WkXxguoj0VdX10RlF5GzgbIAuXZJ8o4UJiGHUOaGJiKoeWoN9tgBb/HKxiHwK9ALmxMh7D3APQEFBQdXvBjYBMYxQyKjmjIjsLCLZfrkH0BP4rNYHNgExjNBI1xDvSBFZAQwFnhWRF/2mA4AFIjIfeBw4V1V/qFVhJiCGESrpGp2ZBkyLkf4E8ESdFWQCYhihk1HNmTrFBMQwUkLDFBETEMNIGQ1PRExADCOlNCwRMQExjJTTcEQkICDF6+GOFVAcmaJmAmIYodEw4omoVhKQMYuErWXOK3fSgCzyjzABMYywaBg1kY0by5swResJxAURilp1NgExjBBpGCJSVla+WBEXBHJzsijs2yl9dhlGI6BhNGcC5LdyTZiiVp0p7NuJ/K5WCzGMMGlwIkJODvlHFJJvTRjDSAmiWrUDbKYjIquA5bU4RHvg+zoypz6Wnwk2pLv8TLAh3eVXZUNXVd05OrFBiEhtEZE5qlpQdc6GWX4m2JDu8jPBhnSXX1MbGkbHqmEYacNExDCMWmEi4rinkZcP6bch3eVD+m1Id/lQAxusT8QwjFphNRHDMGqFiYhhGLWi0YpIJrzKM54NftsfRGSpiHwkIkeEZUOgvPEi8lXgvI8Ku8xA2Uf681wqIlekqtxA+ctEZKE/7+3eLBBSmf8Rke9E5INAWlsReVlEPvH/Q50xGceG6j8HqtooP8DewF7Aa0BBIL0b8EGabegDzAeaAt2BT4HskG0ZD/wuDfch259fD6CJP+8+KbZhGdA+xWUeAAwOPmvAX4Ar/PIVwM1psKHaz0GjrYmo6mJV/ShDbTgWmKKqW1T1c2ApMCS11qWMIcBSVf1MVbcCU3Dn36BR1VlA9JsMjgUe9MsPAselwYZq02hFpArCfZVn1XQEvgysr/BpYXOhiCzw1dxUOR+l61yDKPCSiBT7Nyumi11V9RsA/3+XNNlRreegQYuIiMwQkQ9ifBL90kVe5TkIuASYLCKtUmxDrDed13osvgpb/g3sAeThrsGttS0vWbNipKV63sFwVR0M/Ay4QEQOSHH5mUS1n4OG58UbQEN+lWdYNuB+jTsH1jsBX9ek/JrYIiL3As/UtrwkCeVcq4Oqfu3/fyci03BNrFmptMGzUkQ6qOo3ItIB+C7VBqjqyshyss9Bg66J1ITQXuVZPZ4GThGRpiLS3dvwXpgF+oc2wkjgg3h565jZQE8R6S4iTYBTcOefEkSkuYi0jCwDh5O6c4/maeB0v3w6EO/F96FRo+cglT3SmfTxF2gFrtaxEnjRpx8PLMKNEswFfpFqG/y2K3GjFh8BP0vB9XgIWAgswD3MHVJ4L44CPvbne2WKn4Me/l7P9/c9JeUDj+CaC9v8M3Am0A6YCXzi/7dNgw3Vfg5s2rthGLXCmjOGYdQKExHDMGqFiYhhGLXCRMQwjFphImIYRq0wEaklIlLqvR0/EJH/iUjrKvLvLCLv+mn16ZhSXyUi0tuf0/siskca7eggIgknO4nI5yKyV1TabSJyWWC92M9BCRUR+a2I7BjSsY8WkWvDOHZtMRGpPZtUNU9V++GcmS6oIv8hwBJVHaSqbyRTQGTyWwo5DnjK2/hpVZnFEcazdAlwbxV5puAmqEVsyQJOAKb69W7AV+qc+8Lmt0BMEamDe/gscExYIlUrUjmxpyF+gI2B5XOBO/3yHsALQDHwBtAb54/wBbAKmAfsgJsh+Q5uYttjQAu//zLgauBN3JckUb5rffpCoLdPbwE8QMXEoeN9eszjBM7hKOBb4CvgVZ92CW7m4gfAb31aN2AxcCfwPtAVuMyXNx+4Kd518Okn+uPNB2bFubafAU39cjbwV9wM1wXAOT59ALA4sM8I4M3A+nnA+X753zj3hUXAtYE88a7hzsDLPv1u3LuN2gPNcV/q+f4cTgbGAVv9/pHrthG4DngX2C/BdVwC3OfTJwGHAm/hJp0NCdj5d+CkdD/z292ndBtQ3z94EfEP+WPAkX59JtDTL+8LvOKXxwK3++X2OB+N5n79cuBqrXiwL0sy3//55fOB+/zyzcBtATvbJDpO1DmNx8eUAPL9F6M5TpgWAYP8w18GFPp8PwPeBnb0622ruA4LgY5+uXUMG7oDxYH1s4E/+eWmODHo7tcXAQP98l3ABYH9ngJ6RNmUjYvhMqCKa3g78Ae/fCTOMbA9blbzvYEydgocp30gXfFf+iquYwnQH9cyKAb+g3NMPBaYHjjeGOBf6X7moz8N2gEvRewgIvNwD0Mx8LKItACGAY+JlDupNo2xbyEuANFbPl8TXC0hwtQk8z3p/xcDo/zyoQSq+aq6RkSOruI4sdgPmKaqPwKIyJPA/rgp0ctVtShQ3gOq+pMv74cqrsNbwEQReTRgf5AOuBpbhMOBASJygl/fCedT9Dlu+vYpIrII98W72tvaBOikqhHfp5O8q3+OP34fXK0GYl/D/XCuCajqCyKyxqcvBG4RkZuBZzR+s7QUeCJwrHjX8XNVXejTFwEzVVVFZCHuuYrwHbB7nLLSholI7dmkqnkishPO4/ECYCKwVlXzqthXgJdVdXSc7T8mmW+L/19KxT0Vtnepr+o48WyMx4+B5VjlZRHnOqjquSKyL/BzYJ6I5Knq6kCWTUCzqOP/n6q+GMOOR4CXgNeBBaoa8X7dH9ccxDsy/g7YxwvqxKjjx7uG26GqH4tIPq7pd6OIvKSq18XIullVSxMdK6pscLW7LYHl4He0Ge66ZBTWsVpHqOo6XLv4d7gb/bmInAjlHY8DY+xWBAwXkT19vh1FpFct8gV5CbgwsuKDy9TkOLOA43ze5rhf5li/vC8BZ0Q6/kSkraquJ851EJE9VPVdVb0a9+7XzlHH+5jKv8IvAueJSK7fv5e3B3Wdv6uBm3CCEuFI4Hm/3AoneutEZFdc86sq3gRO8uUdjmsSIiK7Az+p6sPALbgQgwAbgJZxjpXsdUxEL9LnYRwXE5E6RFXfx3W2nYJrv54pIhHv0O2CEKnqKlwfySMisgD3Je9d03xRXA+08UPP84GDanIcVZ2Lq1m9h+sgvM+fZ3S+F3BV8zm+efc7vynedfiruODIH+C+YPOjjvcj8GlE8HAdjx8Cc/0+d1P5V/oRfy7TAmkjcLUTVHU+rgN4Ea7P4a1E5+25FjhcRObiROcbnFD0B97z53kl7lqDe/HT8yLyavSBkr2OVXAQrkM3ozAvXiNjEZGRQL6q/qkG+3bCdX4mU+OId4ymQKmqlojIUODfSTRRQ8HXniar6iHpKD8R1idiZCyqOk1E2tVw3xUk12RJRBfgUT/3ZCtwVi2PV1tbLk1j+XGxmohhGLXC+kQMw6gVJiKGYdQKExHDMGqFiYhhGLXCRMQwjFrx/7L2BMou1xj2AAAAAElFTkSuQmCC\n" } } ], "source": "job.results.plot_simple_correlation(\"forces\");" }, { "cell_type": "code", "execution_count": 7, "id": "9e8b8922", "metadata": { "execution": { "iopub.status.busy": "2024-05-31T13:56:50.229773Z", "iopub.execute_input": "2024-05-31T13:56:50.230065Z", "shell.execute_reply": "2024-05-31T13:56:50.398635Z", "iopub.status.idle": "2024-05-31T13:56:50.399633Z" } }, "outputs": [ { "output_type": "display_data", "metadata": { "needs_background": "light" }, "data": { "text/plain": "
", "image/png": "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\n" } } ], "source": "job.results.plot_all_pes()\nplt.subplots_adjust(top=2, hspace=0.5);" }, { "cell_type": "markdown", "id": "f47ffcc4", "metadata": {}, "source": "## Copy the results directory to a known place" }, { "cell_type": "code", "execution_count": 8, "id": "8f74b6b2", "metadata": { "execution": { "iopub.status.busy": "2024-05-31T13:56:50.404061Z", "iopub.execute_input": "2024-05-31T13:56:50.404208Z", "shell.execute_reply": "2024-05-31T13:56:50.807553Z", "iopub.status.idle": "2024-05-31T13:56:50.808865Z" } }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": "[31.05|15:56:50] Copying /home/hellstrom/SALRuH/fix2024/plams_workdir.004/initial_training/results to /home/hellstrom/SALRuH/fix2024/initial_training_results\n[31.05|15:56:50] Use /home/hellstrom/SALRuH/fix2024/initial_training_results as the LoadModel in upcoming active learning.\n" } ], "source": "import shutil\n\norig_training_results_dir = str(job.results.path)\nnew_training_results_dir = Path(\"initial_training_results\").resolve()\nlog(f\"Copying {orig_training_results_dir} to {new_training_results_dir}\")\nshutil.copytree(orig_training_results_dir, new_training_results_dir, dirs_exist_ok=True)\nlog(f\"Use {new_training_results_dir} as the LoadModel in upcoming active learning.\")" } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "name": "python", "version": "3.8.12", "mimetype": "text/x-python", "codemirror_mode": { "name": "ipython", "version": 3 }, "pygments_lexer": "ipython3", "nbconvert_exporter": "python", "file_extension": ".py" } }, "nbformat": 4, "nbformat_minor": 5 }