Created
April 5, 2025 19:55
-
-
Save mmore500/92d2aee823b009319c47abab51e565cc to your computer and use it in GitHub Desktop.
Untitled17.ipynb
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"nbformat": 4, | |
"nbformat_minor": 0, | |
"metadata": { | |
"colab": { | |
"provenance": [], | |
"authorship_tag": "ABX9TyNt6hAPl/4l/SLKRX4WkrJf", | |
"include_colab_link": true | |
}, | |
"kernelspec": { | |
"name": "python3", | |
"display_name": "Python 3" | |
}, | |
"language_info": { | |
"name": "python" | |
} | |
}, | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "view-in-github", | |
"colab_type": "text" | |
}, | |
"source": [ | |
"<a href=\"https://colab.research.google.com/gist/mmore500/92d2aee823b009319c47abab51e565cc/untitled17.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 583 | |
}, | |
"id": "Yrax1AR2gvnb", | |
"outputId": "5a020492-1982-4026-bb78-0b444718dcdf" | |
}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stderr", | |
"text": [ | |
"<ipython-input-5-bdb449ccab4f>:39: FutureWarning: \n", | |
"\n", | |
"The `ci` parameter is deprecated. Use `errorbar=('ci', 95)` for the same effect.\n", | |
"\n", | |
" sns.lineplot(x=\"Step\", y=\"Value\", data=df, estimator=np.mean, ci=95, label=\"Mean\")\n" | |
] | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"text/plain": [ | |
"<Figure size 800x500 with 1 Axes>" | |
], | |
"image/png": "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\n" | |
}, | |
"metadata": {} | |
} | |
], | |
"source": [ | |
"import numpy as np\n", | |
"import pandas as pd\n", | |
"import matplotlib.pyplot as plt\n", | |
"import seaborn as sns\n", | |
"\n", | |
"# Set the seaborn theme for a cleaner look\n", | |
"sns.set_theme(style=\"whitegrid\")\n", | |
"\n", | |
"# Parameters\n", | |
"start_value = 100\n", | |
"n_steps = 20\n", | |
"n_replicates = 10000\n", | |
"\n", | |
"# Initialize an array to hold the simulation results.\n", | |
"# Rows represent steps (including the initial step), columns represent replicates.\n", | |
"walks = np.zeros((n_steps + 1, n_replicates))\n", | |
"walks[0, :] = start_value\n", | |
"\n", | |
"# Run the simulation for each replicate.\n", | |
"for rep in range(n_replicates):\n", | |
" current_value = start_value\n", | |
" for step in range(1, n_steps + 1):\n", | |
" # Draw a random increment uniformly from -current_value to current_value.\n", | |
" increment = np.random.uniform(-current_value + 1, current_value - 1)\n", | |
" current_value += increment\n", | |
" walks[step, rep] = current_value\n", | |
"\n", | |
"# Convert the simulation results to a DataFrame in long (tidy) format.\n", | |
"data = []\n", | |
"for step in range(n_steps + 1):\n", | |
" for rep in range(n_replicates):\n", | |
" data.append({\"Step\": step, \"Replicate\": rep, \"Value\": walks[step, rep]})\n", | |
"df = pd.DataFrame(data)\n", | |
"\n", | |
"# Create a plot using Seaborn\n", | |
"plt.figure(figsize=(8, 5))\n", | |
"\n", | |
"# Plot the mean line with a 95% confidence interval.\n", | |
"sns.lineplot(x=\"Step\", y=\"Value\", data=df, estimator=np.mean, ci=95, label=\"Mean\")\n", | |
"\n", | |
"plt.xlabel(\"Step\")\n", | |
"plt.ylabel(\"Value\")\n", | |
"plt.title(\"Random Walk Simulation (10000 Replicates, 20 Steps)\")\n", | |
"plt.legend()\n", | |
"plt.show()\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [], | |
"metadata": { | |
"id": "1IyYUMthgxgy" | |
}, | |
"execution_count": null, | |
"outputs": [] | |
} | |
] | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment