204 lines
61 KiB
Plaintext
204 lines
61 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"source": [
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"%matplotlib inline\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"\n",
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"from plotting import plot_trajectory\n",
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"from walker import Walker"
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],
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"outputs": [],
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"execution_count": 4,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2022-08-18T09:50:40.616906Z",
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"start_time": "2022-08-18T11:50:40.181358+02:00"
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},
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"collapsed": false,
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"pycharm": {
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"name": "#%%\n"
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},
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"execution": {
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"iopub.status.busy": "2023-06-28T17:23:15.993Z",
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"iopub.execute_input": "2023-06-28T17:23:16.002Z",
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"shell.execute_reply": "2023-06-28T17:23:16.081Z",
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"iopub.status.idle": "2023-06-28T17:23:16.018Z"
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}
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"For this Exercise let's go back to the version of the walker with only one \"next step proposal\". "
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],
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"metadata": {
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"nteract": {
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}
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"# 1. Complete the run.py script\n",
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"- In the file, at the top we give the desired parameters for the run\n",
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"- create a context map and walker (see previous exercises for reference)\n",
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"- simulate a trajectory (see previous exercises for reference)\n",
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"- save the trajectory using `np.save()` and some metadata"
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],
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"metadata": {
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"nteract": {
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"transient": {
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"deleting": false
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}
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}
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"# 2. Run the run.py script twice and compare that the outcome is identical by plotting the result below"
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],
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"metadata": {
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"nteract": {
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"transient": {
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"deleting": false
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}
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}
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}
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},
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{
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"cell_type": "code",
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"source": [
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"trajectory = np.load(\"sim_20230628-192022.npy\") # change the name of the file here!"
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],
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"outputs": [],
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"execution_count": 5,
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"metadata": {
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"collapsed": true,
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}
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},
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"execution": {
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"iopub.status.busy": "2023-06-28T17:23:19.216Z",
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"iopub.execute_input": "2023-06-28T17:23:19.227Z",
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"iopub.status.idle": "2023-06-28T17:23:19.236Z",
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"shell.execute_reply": "2023-06-28T17:23:19.239Z"
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}
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}
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},
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{
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"cell_type": "code",
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"source": [
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"plt.plot(trajectory[:,0], trajectory[:,1])"
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],
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"outputs": [
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{
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"output_type": "execute_result",
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"execution_count": 6,
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"data": {
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"text/plain": "[<matplotlib.lines.Line2D at 0x12c7436d0>]"
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"metadata": {}
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{
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"output_type": "display_data",
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"data": {
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"text/plain": "<Figure size 432x288 with 1 Axes>",
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"image/png": "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