Skip to content

Instantly share code, notes, and snippets.

@tomkreker
Last active March 17, 2020 14:03
Show Gist options
  • Select an option

  • Save tomkreker/aaf5125eb4afe477a8f17c340174a9c3 to your computer and use it in GitHub Desktop.

Select an option

Save tomkreker/aaf5125eb4afe477a8f17c340174a9c3 to your computer and use it in GitHub Desktop.
--- Note: I completed only the first exercise because I spent the rest of yesterday on calls with airlines to make travel plans. I have done most of the readings but could not finish all of the PCW. ---
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEWCAYAAABrDZDcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/w9hSwjaqpToEQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1d56e381898>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#Exercise 8\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"num_sims = 200\n",
"ph = 0.6\n",
"num_steps = 30\n",
"final_position = []\n",
"\n",
"for i in range(num_sims):\n",
" position = [0]\n",
" for j in range(num_steps):\n",
" if np.random.random() < ph:\n",
" position.append(position[-1]+1)\n",
" else:\n",
" position.append(position[-1]-1)\n",
" final_position.append(position[-1])\n",
"\n",
"plt.plot(range(num_steps+1),position)\n",
"plt.ylabel('Position')\n",
"plt.xlabel('Step')\n",
"plt.title('Sample Path for one Simulation')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1d56e3eb0f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#Exercise 8 - histogram\n",
"plt.hist(final_position)\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment